Targeting immunoglobulin for treating aging and metabolic diseases

Abstract

The methods provide reducing IgG levels in blood and tissues to extend healthspan and lifespan. Embodiments disclosed herein relate to reducing aging, obesity, and / or metabolic decline in a subject by reducing IgG levels. Embodiments disclosed herein relate to reducing IgG recycling by inhibiting FcRn. Embodiments disclosed herein relate to determining the biological age or health of a subject by detecting IgG levels.

Description

Attorney Docket No. 44010.206WO-PCT / / CU24263 TARGETING IMMUNOGLOBULIN FOR TREATING AGING AND METABOLIC DISEASES RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. provisional patent application 63 / 555,358, filed February 19, 2024, to The Trustees of Columbia University, titled “TARGETING IMMUNOGLOBULIN FOR TREATING AGING AND METABOLIC DISEASES- IgG IS AN AGING FACTOR THAT DRIVES ADIPOSE TISSUE FIBROSIS AND METABOLIC DECLINE,” the entirety of the disclosure of which is hereby incorporated by this reference. INCORPORATION-BY-REFERENCE OF MATERIAL ELECTRONICALLY FILED

[0002] The present application contains a sequence listing which has been submitted electronically as an XML document in the ST.26 format and is hereby incorporated by reference in its entirety. Said XML copy, created on February 14, 2025, is named 44010206WO-PCT.xml and is 5,000 bytes in size. STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

[0003] This invention was made with government support under DK134471, DK063608, and DK112943 awarded by the National Institutes of Health. The government has certain rights in the invention. TECHNICAL FIELD

[0004] The subject matter disclosed herein is generally directed to methods of improving tissue integrity, metabolic health, inflammation, fibrosis, or any condition associated with aging and obesity by reducing IgG levels in a subject. BACKGROUND

[0005] Advances in science and technology have significantly extended human lifespan but simultaneously aggravated age-associated complications. Age is a prominent risk factor for obesity, insulin resistance, type 2 diabetes, dyslipidemia, liver steatosis, etc.1,2These metabolic conditions, in turn, dramatically impair human health and, eventually, lifespan.3Multiple signalingAttorney Docket No. 44010.206WO-PCT / / CU24263 pathways have been linked with the molecular signature of aging under the rubric of insulin / insulin-like growth factor-1 (IGF-1) / forkhead- box O transcription factor (FoxO; DAF-16 in Caenorhabditis elegans),4–6mammalian target of rapamycin (mTOR),7,8Sirtuins,9,10and adenosine 5’monophosphate-activated protein kinase (AMPK).11,12These classic longevity pathways are all crucial for metabolic regulation, implying a metabolic basis of aging. However, the mechanistic details connecting metabolic dysregulation and aging remain poorly understood.

[0006] Adipose tissue is the primary site of energy storage, and maintaining its integrity is vital to energy homeostasis and metabolic health, processes often perturbed in aging. Indeed, adipose tissue is one of the few organs where organ-restricted intervention is sufficient to impact both lifespan and healthspan.13Most longevity interventions in rodents are associated with alterations of adipose tissue function; examples include caloric restriction (CR),14rapamycin treatment,15,16surgical removal of visceral fat,17and elimination of senescent cells.18Age- associated transcriptomic changes occur earlier and with a greater magnitude in adipose tissue compared with other major metabolic organs,19implying that adipose tissue could be driving at least a subset of the metabolic derangements in aging. Concurrent with aging, adipose tissue develops phenotypic hallmarks, including adipocyte hypertrophy, chronic inflammation, fibrosis, insulin resistance, and compromised adipogenesis, all of which are closely correlated with metabolic dysfunction.20–22Nevertheless, the pathological remodeling of adipose tissue in aging remains an enigma, and a driving factor that could underlie multiple hallmarks is desired.

[0007] Antibodies, in the form of immunoglobulins (Igs), are the preeminent effectors for adaptive immune defense against pathogens. Among the five primary classes of antibodies, immunoglobulin G (IgG) accounts for 80% of total serum antibodies. IgG consists of an antigen- binding fragment (Fab) and an Fc fragment. In the canonical adaptive immune response, B cells are activated in the presence of an antigen and produce specific antibodies to neutralize it through Fab, while simultaneously interacting with Fc gamma receptors (FcgRs) on innate immune cells to trigger antibody-dependent cytotoxicity and destroy antigen-containing pathogens through endosomal internalization.23,24Unlike IgA or IgM, IgG has an exceptionally long half-life because it has a unique recycling mechanism. IgG is internalized into endosomes upon binding to its receptors (FcgRs). As the endosomes acidify during maturation, IgG is transferred from FcgRs to the neonatal Fc receptor (FcRn), the sole IgG recycling receptor. FcRn then recycles and releasesAttorney Docket No. 44010.206WO-PCT / / CU24263 IgG out of the plasma membrane at a neutral pH, while the unbound IgG is sorted for lysosomal degradation.25Beyond the classic immune function, the role of IgG in metabolism is not appreciated. Of note, IgG is primarily considered a plasma protein, and its tissue presence, regulation, and function in the context of aging, if any, are unknown.

[0008] Citation or identification of any document in this application is not an admission that such a document is available as prior art to the present invention. SUMMARY

[0009] In one aspect, the present invention provides for a method of treating tissue integrity, metabolic health, inflammation, and / or fibrosis in a subject comprising administering to the subject one or more agents that reduce IgG levels, wherein the subject is protected from tissue degeneration, reduced metabolic health, inflammation, and / or fibrosis; or wherein tissue integrity and / or metabolic health is restored in the subject; and / or wherein inflammation and / or fibrosis is reduced in the subject.

[0010] In certain embodiments, the one or more agents reduce IgG recycling. In certain embodiments, the one or more agents comprise a neonatal fragment crystallizable (Fc) receptor (FcRn) inhibitor. In certain embodiments, the FcRn inhibitor is an antibody. In certain embodiments, the FcRn inhibitor is a peptide comprising the consensus peptide sequence GHFGGXY (SEQ ID NO: 1). In certain embodiments, the FcRn inhibitor is selected from the group consisting of efgartigimod, rozanolixizumab, nipocalimab, orilanolimab, batoclimab, CSL730 / M230, ABY-039, SYN1436, and SYN1327. In certain embodiments, the FcRn inhibitor is an antisense oligonucleotide (ASO), RNAi, or a CRISPR system capable of targeting mRNA encoding for FcRn. In certain embodiments, the one or more agents that reduce IgG levels comprise an antibody, peptide, small molecule, antisense oligonucleotide (ASO), RNAi, or CRISPR system capable of targeting mRNA. In certain embodiments, the one or more agents are targeted to macrophages.

[0011] In certain embodiments, the subject is over 30, 60, or 70 years old. In certain embodiments, the subject is being treated for age-associated tissue degeneration and / or reduced metabolic health. In certain embodiments, the subject is obese, whereby obesity is treated. InAttorney Docket No. 44010.206WO-PCT / / CU24263 certain embodiments, the subject has dyslipidemia, whereby dyslipidemia is treated. In certain embodiments, the subject has type 2 diabetes, whereby insulin resistance is treated.

[0012] In certain embodiments, the IgG levels are reduced to a calorie restriction (CR) reference level, whereby IgG levels are not eliminated. In certain embodiments, the IgG levels are reduced by at least 30%, 40%, 50%, 60%, 70%, 80%, or 90%. In certain embodiments, the one or more agents reduce IgG levels in white adipose tissue (WAT), brown adipose tissue (BAT), liver, kidney, and / or muscle. In certain embodiments, adipose tissue integrity is restored.

[0013] In another aspect, the present invention provides for a method of determining the biological age of a subject comprising determining the plasma or tissue IgG level in the subject and comparing to one or more control reference levels. In certain embodiments, the one or more control reference levels are the average plasma or tissue IgG levels for control subjects at different ages. In certain embodiments, the tissue is white adipose tissue (WAT). In certain embodiments, the IgG level is determined by ELISA, western blot, mass spectrometry, or isotope labelling.

[0014] In another aspect, the present invention provides for a method of determining a reduction in the biological age of a subject comprising determining the plasma or tissue IgG level in a first sample obtained from the subject at a first time point and comparing to the plasma or tissue IgG level in a second sample obtained from the subject at a second time point, whereby a reduction in the plasma or tissue IgG level indicates a reduction in the biological age of the subject. In certain embodiments, the subject consumed a healthier diet between the first and second time point. In certain embodiments, the subject was treated with an age reducing therapy between the first and second time point. In certain embodiments, the IgG level is determined by ELISA, western blot, mass spectrometry, or isotope labelling.

[0015] These and other aspects, objects, features, and advantages of the example embodiments will become apparent to those having ordinary skill in the art upon consideration of the following detailed description of example embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0017] An understanding of the features and advantages of the present invention will hereinafter be described in conjunction with the appended and / or included DRAWINGS, where like designations denote like elements, and:

[0018] FIG. 1A-FIG. 1H – IgG is preferentially accumulated in adipose tissue during aging. (FIG.1A) Coomassie blue staining of SDS-PAGE of total protein extracted from young (3 months) and aged (33 months) male mouse eWAT. Red bracket indicates the ~1 cm slice (showing the most significant changes at this region) for mass spectrometry analysis. (FIG.1B) Flow graph summary of mass spectrometric identification of immunoglobulin (Ig) proteins enriched in aged eWAT. The full list of significant differentially expressed peptides is provided in Table 1. (FIG. 1C) Immunohistochemical (IHC) staining and quantification of IgG in eWAT from young and aged male mice. Scale bars, 100 µm (n = 5, 5).*** p < 0.001 by Student’s t test, data are presented as mean ± SEM. (FIG. 1D) Western blot (WB) analysis of IgG heavy (H) and light (L) chains in eWAT protein extracts and plasma samples from C57BL / 6J mice during aging. Ponceau red staining band was used as the loading control for the plasma samples. Mice were perfused to clear blood in the circulation before harvesting tissues. (FIG. 1E) WB of IgG across different tissues from 33-month-old male mice. Heat shock protein 90 (HSP90) was used as a loading control. Mice were perfused to clear blood in the circulation before harvesting tissues. (FIG. 1F) WB analysis of IgG in human epicardial fat at the indicated ages. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as a loading control. (FIG.1G) The correlations of human IgG (heavy chain) levels to age (quantifications of WB in F). (FIG. 1H) Transcriptomic analyses reveal the top progressively increased (top) and decreased (bottom) biological processes (BPs) in eWAT during aging of C57BL / 6J male mice. The complete BPs list is provided in FIG. 9. See also FIGS. 8 and 9 and Table 1.

[0019] FIG. 2A-FIG. 2H – The metabolic improvements by calorie restriction in aging are mediated through reducing IgG. (FIG. 2A–E) 12-month-old male C57BL / 6J mice were subjected to 30% caloric restriction (CR) for 4 weeks. (FIG. 2A and B) WB of plasma IgG, IgA, and IgM levels in ad libitum and CR mice (FIG.2A) and quantifications (FIG.2B). ***p < 0.001 for CR vs. ad libitum control by two-tailed Student’s t test (n = 6 and 6). (FIG. 2C and D) WB analysis (FIG.2C) and quantification (FIG.2D) of IgG and SirT1 in protein lysates of eWAT and iWAT from ad libitum and CR mice. HSP90 was used as the loading control (n = 6, 6). (FIG.2E)Attorney Docket No. 44010.206WO-PCT / / CU24263 qPCR analysis of gene expression (arbitrary units [a.u.]) in eWAT of a different cohort of 4-week CR and ad libitum mice (n = 8 and 8). (FIG. 2F–H) 5-month-old male C57BL / 6J mice were intraperitoneally (i.p.) administered 3mg mouse total IgG or vehicle (Veh) per week for 4 weeks since the beginning of CR. The regularly fed mice were included as the ad libitum control group. (FIG.2F) WB analysis of IgG in eWAT from mice treated with ad libitum, CR-Veh, and CR-IgG. (G) qPCR analysis of eWAT gene expression from all three groups of mice (n = 5, 8, and 7). (FIG. 2H) Insulin tolerance test (ITT) and the area under curve (AUC) after 3-week treatment (n = 5, 8, and 7). Data are presented as mean ± SEM; *p < 0.05, **p < 0.01 vs. CR-Veh group by two-tailed Student’s t test or one-way ANOVA. See also FIG. 10.

[0020] FIG. 3A-FIG.3N – IgG activates macrophages to promote adipose tissue fibrosis. (FIG. 3A) Picrosirius red staining of eWAT fibrosis in young (3 months) and aged (33 months) mice imaged by bright-field and polarized-light microscopy and fibrosis area quantification (n = 10 and 10). Scale bars, 50 µm. (FIG. 3B) Immunostaining of IgG, SMA, CD68, and DAPI of eWAT sections from young and aged mice. Scale bars, 50 µm. (FIG. 3C) Schematic diagram of the TGF-b / SMAD signaling pathway to activate fibrotic response. (FIG. 3D) WB analysis of phospho-SMAD2 and phospho-SMAD3 in the eWAT of young and aged mice. HSP90 was used as the loading control. (FIG. 3E–G) Young C57BL / 6J mice were i.p. injected with mouse total IgG (3 mg weekly) for 4 weeks. (FIG.3E) WB analysis of SMADs phosphorylation in the eWAT. (FIG.3F) qPCR analysis of fibrotic gene expression in the eWAT from Veh- or IgG-treated mice (n = 5 and 5). (FIG. 3G) Enrichment of biological processes by IgG treatment in eWAT. The biological processes influenced by IgG treatment in eWAT were analyzed by differentially expressed genes (DEGs). The significant changed signal pathways were plotted for IgG treat vs. vehicle. The top 15 significant biological processes (BPs) were ranked according to their false discovery rate (FDR), and redundant terms were removed by reduce visualize gene ontology (REVIGO). (FIG. 3H and I) Mouse BMDMs were treated with 200 µg / mL IgG for 24 h, and RNA was extracted for RNA-seq and qPCR analysis. (FIG. 3H) Enriched BPs by IgG treatment inBMDMs. The BPs affected by IgG treatment in BMDM were analyzed by DEG. The significant changed signal pathways were plotted for IgG treat vs. vehicle. The top 15 significant biological processes were ranked according to their FDR, and redundant terms were removed by REVIGO. (FIG.3I) qPCR analysis of the expression of inflammatory markers and Tgfb isoforms in BMDMsAttorney Docket No. 44010.206WO-PCT / / CU24263 (n = 3, 3). (FIG. 3J) qPCR analysis of fibrotic genes’ expression in 3T3-L1 preadipocytes treated with conditioned media (CM) collected from vehicle- (Veh-CM) or IgG-treated (IgG-CM) BMDMs. 5 µM TGF-bR inhibitor LY2109761 or 10 ng / mL TGF-b was added as control treatments (n = 3 / group). *p < 0.05, **p < 0.01, ***p < 0.001 vs. Veh-CM;$p < 0.05,$$p < 0.01,$$$p < 0.001 for IgG-CM + LY2109761 vs. IgG-CM. (FIG. 3K) WB analysis of TGF-b signaling in the CM-treated 3T3-L1 preadipocytes. (FIG. 3L) WB analysis of ERK and MEK phosphorylation in BMDMs treated with 200 µg / mL IgG, 50 ng / mL LPS (pro-inflammatory activation), or 50 ng / mL IL-4 (alternative activation) for 24 h. (FIG. 3M) Ras activity was measured in the BMDMs treated with 200 µg / mL IgG or 50 ng / mL LPS for 24 h. 50 ng / mL epidermal growth factor (EGF) was used as the positive control for Ras activation (n = 3 / group). (FIG. 3N) ELISA determination of TGF-b production in the CM of vehicle (Veh), IgG-, boiled IgG-, and IgG-ERK inhibitor- (1 µM) treated BMDMs (n = 6 / group). Data are presented as mean ± SEM, *p < 0.05, **p < 0.01, ***p < 0.001 for the treatment group vs. vehicle group by two- tailed Student’s t test or one-way ANOVA analysis. See also FIG. 11.

[0021] FIG. 4A-FIG. 4I – Bnullmice are protected from aging-associated adipose tissue fibrosis. (FIG. 4A–F) 24-month-old male control (Ctrl) and Bnullmice on the C57BL / 6J background were used in the following studies (n = 6 and 6). (FIG.4A) Picrosirius red staining of eWAT sections imaged by bright-field and polarized-light microscopy. Scale bars, 100 µm. (FIG. 4B) Quantification of eWAT fibrosis area of Ctrl and Bnullmice in (FIG. 4A) (n = 6 and 6). (FIG. 4C) Insulin tolerance test (ITT) in aged Ctrl and Bnullmice. (FIG. 4D) qPCR analysis of eWAT fibrotic gene expression. (FIG.4E) WB analysis of IgG and SMADs signaling in the eWAT tissue extracts. HSP90 was used as the loading control. (FIG. 4F) qPCR analysis of pro- and anti- inflammatory genes in eWAT. (G–I) 22- to 24-month-old Bnullmice were i.p. administered 3 mg mouse total IgG or vehicle (Veh) per week for 4 weeks (n = 6). (FIG. 4G) Insulin tolerance test (ITT) were compared before and after IgG treatment (n = 6 and 6). (FIG. 4H) qPCR analysis of eWAT fibrotic and inflammatory gene expression after 4 weeks’ treatment. Aged Bnullmice were used as the control group (n = 6 and 6). (FIG. 4I) WB analysis of eWAT proteins, with aged Bnullmice as the control group. HSP90 was used as the loading control. Data are presented as mean ± SEM, *p < 0.05, **p < 0.01, and ***p < 0.001 by two-tailed Student’s t test.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0022] FIG. 5A-FIG. 5K – Abolishing IgG recycling in macrophages prevents IgG accumulation and adipose tissue fibrosis in aged mice. (FIG. 5A) Schematic diagram of FcRn- dependent IgG recycling. (FIG. 5B) Fcgrt mRNA expression in peritoneal macrophages (MØ) isolated from 6-week-old Fcgrtflox / flox;LysM-cre (mKO) and Fcgrtflox / floxcontrol (Ctrl) mice (n = 3 and 3). (FIG. 5C) The half-life of circulating biotin-labeled mouse IgG in 15-month-old Ctrl and mKO mice (n = 5 and 6). (FIG. 5D) WB analysis of FcRn and IgG in eWAT from 15-month-old Ctrl and mKO mice. (FIG.5E) Picrosirius red staining of eWAT fibrosis in 15-month-old Ctrl and mKO mice imaged by bright-field and polarized-light microscopy. Scale bars, 200 µm. (FIG.5F) Quantification of fibrosis area shown in (FIG. 5E) (n = 10 and 10). (FIG. 5G) WB analysis of SMADs phosphorylation in the eWAT of 15-month-old Ctrl and mKO mice. (FIG. 5H) qPCR analysis of eWAT fibrotic gene expression in 15-month-old Ctrl and mKO mice (n = 9 and 10). (FIG. 5I) qPCR analysis of eWAT inflammatory gene expression in 15-month-old Ctrl and mKO mice (n = 9 and 10). (FIG. 5J) H&E staining of eWAT and iWAT from 15-month-old Ctrl and mKO mice. Scale bars, 200 µm. (K) eWAT adipocyte size frequency distribution (n = 10 and 10). Data are presented as mean ± SEM, *p < 0.05, **p < 0.01, and ***p < 0.001 for mKO vs. Ctrl by two-tailed Student’s t test. See also FIG. 12.

[0023] FIG. 6A-FIG. 6H – Prevention of IgG accumulation extends the healthspan and lifespan of mKO mice. (FIG.6A) Body weight of Ctrl and mKO mice at indicated ages; 3 month (n = 7 and 5), 6 month (n = 10 and 9), and 12 and 15 months (n = 10 and 10). (FIG. 6B and C) Glucose tolerance test (GTT) and its area under curve (AUC) (FIG. 6B), ITT and its AUC (FIG. 6C) in 5-month-old male Ctrl and mKO mice (n = 6 and 8). (FIG. 6D and E) GTT (n = 10 and 10) (FIG. 6D) and ITT (n = 10 and 9) (FIG. 6E) with their AUC in 15-month-old Ctrl and mKO mice. (FIG. 6F) Oxygen consumption over a 24-h dark / light cycle from indirect calorimetry in 15-month-old Ctrl and mKO mice (n = 10 and 10). (FIG. 6G) qPCR analysis of eWAT gene expression involved in lipid metabolism in 15-month-old Ctrl and mKO mice (n = 9 and 10). (FIG. 6H) Survival curve of Ctrl and mKO mice with Gehan-Breslow-Wilcoxon test: p = 0.0121, and log rank (Mantel-Cox) test: p = 0.0043. Data are presented as mean ± SEM, *p < 0.05, **p < 0.01, and ***p < 0.001 for mKO vs. Ctrl by two-tailed Student’s t test except (FIG. 6H). See also FIG. 14.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0024] FIG. 7A-FIG. 7M – Targeting IgG recycling improves metabolism and adipose remodeling in aged mice. (FIG. 7A) Experimental design for treating 70-week-old male mice with control (Ctrl) or FcRn antisense oligonucleotides (ASOs) for 8 weeks. The following parameters were measured. (FIG. 7B) WB analysis of FcRn in eWAT. GAPDH was used as the loading control. (FIG. 7C) Plasma IgG levels determined by ELISA after 8 weeks of ASO treatment (n = 7 and 7). (FIG. 7D) WB analysis of IgGs in eWAT with GAPDH as the loading control. (FIG. 7E) Body weight curve during the treatment (n = 8 and 8). (FIG. 7F) O2consumption by indirect calorimetry. (FIG. 7G) ITT after 5 weeks of ASO treatment (n = 8 and 8).

[0025] FIG.8A-FIG.8I – IgG accumulates in aging, related to FIG.1. (FIG.8A) Western blots (WB) quantification of FIG.1D (n=4 / group), *p<0.05, **p<0.01, ***p<0.001, for 6, 18 mon vs 2 mon. (FIG. 8B) Plasma IgG levels in young and aged C57BL / 6J male mice were measured by ELISA (n=5, 5). (FIG. 8C) WB analysis of IgG heavy chain (IgG H) and light chain (IgG L) in the eWAT and plasma of 2-, 6-, and 18-mon old C57BL / 6J female mice. HSP90 was used as the loading control for the perigonadal pgWAT samples. Coomassie blue staining band was used as the plasma sample loading control (L. C.). (FIG. 8D) WB of tissue IgG heavy chain (H) in young (3 mon) and aged (33 mon) mice. GAPDH was used as the loading control. The blots are at different exposure times. (FIG. 8E) WB quantification in FIG. 1E (n=3). (FIG. 8F) WB of IgG across different tissues from 24-month-old female mice. HSP90 was used as a loading control. Mice were perfused to clear blood in the circulation before harvesting tissues. (FIG. 8G) WB of Igs in eWAT of young and aged mice. (FIG. 8H) WB of IgG H accumulation in tissues during early aging. (FIG. 8I) Correlations between human adipose tissue IgG levels and metabolic genes expression. Data are presented as mean ± s.e.m.

[0026] FIG.9A-FIG.9B – Gene Set Enrichment Analysis of biological processes (BPs) in eWAT during aging, related to FIG. 1. Gene set enrichment analysis of biological processes in eWAT during aging. RNA-seq was performed on eWAT samples from 8-, 26-, 60-, 78-, and 104- wk-old C57BL / 6J mice to identify differential gene expression in older mice versus young (8-wk- old) mice. NES: normalized enrichment score. (FIG. 9A) BPs in eWAT that progressively increased in male C57BL / 6J mice at ages 26, 60, 78, and 104 weeks compared with 8-wk-old mice. The upregulated BPs are enriched in B cell activation and adaptive immune response (marked asAttorney Docket No. 44010.206WO-PCT / / CU24263 red). (FIG. 9B) BPs in eWAT that progressively declined during aging. The top downregulated BPs (marked as red) are related to adipogenesis and metabolism.

[0027] FIG. 10A-FIG. 10F – Manipulations of IgG levels, related to FIG. 2. (FIG. 10A- C) 12-month-old male C57BL / 6 mice were subjected to ad lib or 30% calorie restriction (CR) for 4 weeks. *p<0.05, **p<0.01, ***p<0.001, for CR vs ad lib. (FIG. 10A) ITT after 4-wk CR treatment. ***p<0.001 for CR vs ad lib control by 2-tailed t-test (n=8, 8). (FIG.10B) WB analyses of liver IgG heavy (H) chain and SirT1. HSP90 was used as a loading control. (FIG. 10C) Immunostaining of IgG, F4 / 80, DAPI of eWAT sections from aging ad lib and CR mice. Scale bar, 100 μm. (FIG.10D) WB quantification of FIG.2F, **p<0.01, ***p<0.001 (n=4, 5, 5). (FIG. 10E) 5 months-old male C57BL / 6J mice were subjected to CR for 4 weeks. Mice were IP administered 3 mg mouse total IgG or vehicle (Veh) per week since the beginning of CR. WB analyses of IgG in the plasma and tissues after IgG treatment in CR. (FIG. 10F) Body weight curve for the ad lib, CR-Vehicle and CR-IgG treated mice (n=5, 8, 7). Data are presented as mean ± s.e.m.

[0028] FIG. 11A-FIG. 11G – Adipose tissue IgG levels correlate with TGF-b signaling, related to FIG.3. (FIG. 11A) qPCR analysis of fibrotic gene expression in the eWAT after 4-wk calorie restriction (n=8, 8). (FIG. 11B) WB analysis of SMAD2 / 3 phosphorylation in the eWAT after CR. (FIG. 11C) IgG treatment did not activate TGF-β signaling pathway in 3T3-L1 preadipocytes (n=3, 3). (FIG. 11D) qPCR analysis of fibrotic gene expression in Veh- or IgG- treated 3T3-L1 preadipocytes (n=3, 3). (FIG. 11E) Percentage of inflammatory genes among the detectable genes and differentially expressed genes in IgG treated eWAT. “Background” indicates the detectable genes, while “DEG” represents the differentially expressed genes (log2FoldChange > 0.75 & FDR < 0.1). (FIG. 11F) Bone marrow-derived macrophages (BMDMs) were treated with indicated IgG doses, and qPCR analysis of pro-inflammatory genes (n=4, 3) and anti- inflammatory genes (n=3, 3). (FIG. 11G) Schematic diagram of IgG-induced Ras / MEK / ERK signaling pathway. Data are presented as mean ± s.e.m, *p<0.05, **p<0.01, and ***p<0.001 for analysis used by 2-tailed t -test or one-way ANOVA.

[0029] FIG. 12A-FIG. 12G – Generation of FcRn macrophage conditional knockout mice, related to FIG. 5. (FIG. 12A) Staining for IgG-Cy5.5 uptake by BMDMs. Scale bar, 50 μm. (FIG. 12B) Targeting scheme. Fcgrt exons 2 and 3 were floxed to target the start codonAttorney Docket No. 44010.206WO-PCT / / CU24263 together with the first 325 nt of the coding sequence. (FIG. 12C) PCR genotyping of WT (+ / +), heterozygous (fl / +), and homozygous (fl / fl) Fcgrt alleles. (FIG. 12D) Immunostaining of FcRn, F4 / 80, DAPI of eWAT sections from aging Ctrl and mKO mice. Scale bar, 100 μm. (FIG. 12E) Representative detections of biotin-labelled mouse IgG in the same mouse’s circulation post injection time course in aged control or mKO mice (n=5, 7). (FIG. 12F) WB analysis of plasma proteins in control or mKO mice. (FIG. 12G) WB of IgG in tissues of 15-mon-old Ctrl and mKO mice. HSP90 was used as a loading control.

[0030] FIG.13A-FIG.13H – Metabolic improvements in aged mKO mice, related to FIG. 6. (A-H) In 15-mon-old male control and mKO mice. (FIG.13A) Plasma non-esterified fatty acid (NEFA) levels (n=9, 10). (FIG.13B) Plasma triglyceride (TG) levels (n=9, 10). (FIG.13C-F) 24- hr area under curve (AUC) of total energy expenditure as a function of lean mass (FIG.13C), 24- hour food intake (FIG. 13D), average Respiration Exchange Ratio (RER) (FIG. 13E), and total locomotor activity during one dark-light cycle (FIG. 13F) (n=10, 10). (FIG. 13G) H&E staining of BAT, scale bar, 200μm. (FIG.13H) qPCR analysis of BAT gene expression involved in whiting and browning metabolism in 15-mon-old Ctrl and mKO mice (n=10, 10). Data are mean ± s.e.m.; *p<0.05, **p<0.01 for mKO vs Ctrl by 2-tailed t-test.

[0031] FIG. 14A-FIG. 14L – Characterization of FcRn ASO treatment in aged mice, related to FIG.7. The mice were the same as in FIG.7. (FIG.14A) qPCR analyses of knockdown efficiency by FcRn ASO in metabolic tissues, normalized to Ctrl ASO in each tissue (n=6-8). (FIG. 14B) WB of IgG (heavy chain) in the plasma, BAT, and liver. L.C., loading control for plasma proteins. GAPDH was used as a loading control for tissues. (FIG. 14C) WB analysis of immunoglobulins in iWAT. GAPDH was used as a loading control. (FIG. 14D-G) Indirect calorimetric analyses of energy expenditure (EE) plotted as a function of lean mass (FIG. 14D), food intake (FIG. 14E), respiration exchange ratio (RER) (FIG. 14F), and total activity (FIG. 14G) after FcRn KD (n=8, 8). (FIG. 14H) H&E staining of iWAT and BAT. (I-L) 7-wk-old male C57BL / 6J mice were treated with FcRn ASO or Ctrl ASO for 6 weeks (n=6, 7). (FIG. 14I) WB of IgG in the plasma and eWAT. L.C., loading control for plasma proteins. GAPDH was used as a loading control for eWAT. (FIG.14J) Body weight curve during the treatment. (FIG.14K) GTT (after 4 weeks’ ASO treatment. (FIG.14L) ITT after 5 weeks’ ASO treatment. Data are presented as mean ± SEM; *p<0.05, ***p<0.001, for FcRn ASO vs. Ctrl ASO.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0032] FIG. 15 – Summary schematic demonstrating that IgG accumulates during aging, inducing adipose tissue fibrosis and metabolic dysfunction. Preventing IgG buildup by targeting the recycling receptor FcRn increases lifespan and improves the metabolic health of aged mice.

[0033] FIG. 16A-FIG. 16E – Anti-FcRn antibody treatment improves metabolic functions in aged mice. Control IgG1 and anti-FcRn antibody (50 μg / mouse) were intraperitoneally administrated to aged C57BL / 6 male mice weekly for up to 8 weeks (n=8, 8). (FIG.16A) WB analysis of plasma samples showing decreased IgG levels by anti-FcRn treatment. Coomassie blue staining was used as the loading control. (FIG.16B-C) Plasma triglycerides (FIG. 16B) and free fatty acids (FIG. 16C) levels were decreased by anti-FcRn. (FIG. 16D) Insulin Tolerance Test (ITT) after 7-week antibody treatment. (FIG. 16E) Glucose tolerance test (GTT) after 8-week antibody treatment. Data are presented as mean ± SEM. *p<0.05, **p<0.01, ***p<0.001 by 2-tailed student’s t-test.

[0034] FIG. 17A-FIG. 17K – IgG predominantly accumulates in WAT of DIO mice in a B cell-independent manner. (FIG.17A–E) 8-week-old male C57BL / 6J mice were fed with HFD for 12 weeks to induce obesity. Age-matched chow diet (CD)-fed mice were used as controls. Tissues were collected after PBS perfusion. (FIG. 17A) Immunohistochemical (IHC) staining of IgG in eWAT. Bnullmouse eWAT section was used as a negative control of IgG staining. Scale bars, 100 μm. (FIG. 17B) Western blot (WB) analysis of IgG (heavy chain, H; light chain, L), IgA, and IgM protein levels in eWAT. HSP90 was used as the loading control. (FIG. 17C) WB analysis of plasma antibodies. Coomassie blue staining was used as the loading control (L.C.) for plasma proteins. (FIG. 17D) Quantification of eWAT (FIG. 17B) and plasma (FIG. 17C) IgG WB (n = 5, 5). au, arbitrary units; eWAT, IgG-H / HSP90; plasma, IgG-H / L.C. (FIG. 17E) WB analysis of IgG tissue distribution. Heat shock protein 90 (HSP90) was used as the loading control. (FIG. 17F) WB analysis of exogenous IgG tissue distribution in DIO Bnullmice. 3mg mouse total IgG was administered to these mice by intraperitoneal (i.p.) injection, and tissues were collected after 1 day. (FIG. 17G) IHC staining of IgG in the subcutaneous adipose tissue from lean and obese human subjects. The mock staining was incubated without anti-IgG primary antibody but with the same secondary antibody. Scale bars, 100 μm. (FIG. 17H) IgG-related biological processes (BPs) are upregulated in the omental visceral adipose tissue of obese humans compared with lean controls by reanalyzing a published RNA-seq dataset. Boxplot indicates the log2(foldAttorney Docket No. 44010.206WO-PCT / / CU24263 change [FC] of expression) between obese and lean groups for the genes in the corresponding BP. The straight line within the box represents the median value of log2FC. The color within the box represents the normalized enrichment score (NES), while the outer color indicates the false discovery rate (FDR). NES and FDR are both calculated by gene set enrichment analysis (GSEA). (FIG.17I–K) 8-week-old C57BL / 6J male mice fed with CD were i.p. injected with vehicle (Veh) or 1.5 mg IgG twice weekly for 4 weeks. Mice were perfused with PBS before collecting tissues at sacrifice. (FIG. 17I) Insulin tolerance test (ITT) after 4 weeks of IgG treatment. 0.75 U / kg * BW insulin was administrated (n = 5, 5). (FIG.17J) WB analysis of IgG and F4 / 80 in eWAT from Veh- or IgG-treated mice. (FIG.17K) qPCR analysis of inflammation genes’ expression in eWAT (n = 5, 5). All data are presented as mean ± SEM; *p < 0.05, **p < 0.01, ***p < 0.001 by two- tailed Student’s t test.

[0035] FIG.18A-FIG.18N. – IgG is recycled by adipocyte progenitor cells to accumulate in WAT during early DIO. (FIG. 18A) Fcgrt expression in different subtype cell populations of mouse adipose tissue-derived stromal vascular fraction (SVF) cells by reanalyzing a published scRNAseq dataset. Normalized Fcgrt expression values were plotted as violin plots in different cell clusters (Macro, macrophage; APC, adipocyte progenitor cell; Endo, endothelial; Mast, mastocyte; Eryth, erythropoiesis; Div, dividing cell; Dend, dendritic cell; Neu, neutrophils). (FIG. 18B) IgG-Cy5.5 uptake in APCs. Scale bars, 50 μm. (FIG. 18C) Experiment schematic of Ctrl (Fcgrtflox / flox)and APC Fcgrt conditional knockout (Fcgrtflox / flox; Pdgfra-cre, pKO) male mice under short (4 weeks) and prolonged (12 weeks) HFD feeding. (FIG. 18D) Fcgrt mRNA expression in APCs isolated from inguinal fat of 8-week-old Ctrl and pKO mice (n = 3). (FIG. 18E) IgG recycling in APCs isolated from Ctrl and pKO mice. APCs were pretreated with 200 μg / mL IgG overnight. Cell lysates and media were collected at 0 and 4 h for WB assessment. HSP90 was used as the loading control. (FIG. 18F) Body weight growth curve of Ctrl and pKO mice during 12 weeks of HFD feeding (n = 5, 5). (FIG.18G) WB analysis of IgG and FcRn in eWAT and plasma from Ctrl and pKO mice after 4 weeks’ HFD feeding. (FIG. 18H) Quantification of (FIG. 18G). (FIG. 18I) ITT of mice in (FIG. 18G). 0.75 U / kg,BW insulin was administered (n = 7, 6). (FIG. 18J) GTT of mice in (FIG. 18G). 2 g / kg,BW glucose was administered (n = 7, 6). (FIG. 18K) WB analysis of eWAT and plasma proteins from Ctrl and pKO mice after 12 weeks’ HFD feeding. (FIG. 18L) Quantification of (FIG. 18K). (FIG. 18M) ITT of mice at 11-week HFD feeding. 1Attorney Docket No. 44010.206WO-PCT / / CU24263 U / kg,BW insulin was administered (n = 6, 5). (FIG.18N) GTT of mice at 10-week HFD feeding. 1.5 g / kg,BW glucose was administered (n = 6, 5). All data are presented as mean ± SEM. *p < 0.05, **p < 0.01 by two-tailed Student’s t test. See also FIG. 25.

[0036] FIG. 19A-FIG. 19O – Abolishing IgG recycling in macrophages prevents IgG accumulation and metabolic derangements in DIO. (FIG. 19A) WB analysis of IgG and F4 / 80 protein levels in eWAT from wild-type (WT) mice during an HFD time course. HSP90 was used as the loading control. (FIG.19B) Quantification of WB in (FIG.19A). (FIG.19C) Fcgrt mRNA expression in bone marrow-derived macrophages (BMDMs) isolated from 8-week-old Fcgrtflox / flox;LysM-cre (mKO) and Fcgrtflox / flox(Ctrl) mice (n = 3, 3). (FIG. 19D–O) 8-week-old Ctrl and mKO mice were fed with HFD for 12 weeks (n = 7, 8). (FIG. 19D and E) WB analysis of plasma (FIG.19D) and eWAT proteins (FIG.19E) from DIO mice after 12-week HFD feeding. Quantifications are in FIGS. 26J and 26K, respectively. (FIG. 19F) Body weight growing curve during 12-week HFD feeding (n = 6, 6). (FIG.19G) ITT at 12-week HFD feeding.0.75 U / kg,BW insulin was administered (n = 6, 6). (FIG.19H) GTT at 10-week HFD feeding.2 g / kg,BW glucose was administered. (FIG. 19I) Plasma insulin levels of Ctrl and mKO DIO mice (n = 7, 8). (FIG. 19J) Body composition of DIO mice was determined by EchoMRI (n = 7, 8). (FIG. 19K) H&E staining of adipose tissues as indicated. Scale bar, 100 μm. (FIG. 19L) Functional enrichment analysis of the differentially upregulated and downregulated genes in eWAT between mKO and control DIO mice. The top 20 enriched biological processes (BPs) are shown for the downregulated genes. The color indicates statistical significance. (FIG.19M) WB of IgG in brown adipose tissue (BAT). (FIG. 19N) qPCR analysis of gene expression in BAT (n = 7, 7). (FIG. 19O) Oxygen consumption was determined using metabolic cage in Ctrl and mKO DIO mice (n = 6, 6). All data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001 by two-tailed Student’s t test. See also FIGS. 26 and 27.

[0037] FIG. 20A-FIG. 20P – IgG interacts with the IR to inhibit insulin signaling. (FIG. 20A) 8-week-old C57BL / 6J male mice fed with chow diet were i.p. injected with vehicle or a large dose of IgG (12 mg / mouse) for overnight and then performed ITT. 0.5 U / kg * BW insulin was administrated (n = 5, 5). (FIG. 20B and C) 8-week-old chow-fed C57BL / 6J male mice were i.p. injected with vehicle or 1.5 mg IgG twice weekly for 4 weeks and then examined insulin response by WB. Mice were perfused with PBS before collecting tissues at sacrifice. (FIG. 20B) WBAttorney Docket No. 44010.206WO-PCT / / CU24263 analysis of insulin signaling proteins (insulin receptor beta [IRb]) in eWAT. Mice were fasted for 4 h before insulin (3 U / kg * BW) administration through the inferior vena cava. eWAT were collected from the same mice before and after 4-min insulin treatment. (FIG. 20C) Quantification of (FIG. 20B). (FIG. 20D) WB analysis of insulin signaling proteins in eWAT from 12-week HFD-fed Ctrl and mKO mice as performed in (FIG. 20B). (FIG. 20E) Quantification of (FIG. 20D). (FIG.20F) WB analysis of insulin signaling in day 7 differentiated 3T3-L1 cells. Cells were serum starved overnight and then pretreated with vehicle or 200 μg / mL IgG for 4 h. Cells were further treated with or without 1 μg / mL insulin for another 20 min. In the co-treatment group, 200 μg / mL IgG was added simultaneously with insulin to the vehicle-treated cells for 20 min. (FIG. 20G) C3H10T1 / 2 mature adipocytes were pretreated with vehicle or IgG (400 μg / mL) for 4 h to detect lipolysis stimulated by 30 μM isoproterenol (ISO) for 1 h in the presence of vehicle, 1 μM insulin, and 1 μM insulin plus IgG. Glycerol released into the medium was measured as an indicator of lipolysis (n = 3 / group). (FIG. 20H) WB analysis of membrane-bound IgG and IR. 3T3-L1 cells were pretreated with vehicle or 400 μg / mL IgG for 12 h, followed by 1 μg / mL insulin treatment for 20 min. Total membrane proteins were isolated and subjected to WB analysis. (FIG. 20I) Schematic of the TurboID-IR system depicting a method to detect biotin labeling of proteins in IR proximity. (FIG. 20J) WB analysis of streptavidin pull-down samples from IgG-treated TurboID-IR transfected 293T cells. (FIG. 20K) WB analysis of insulin signaling proteins in 3T3- L1 adipocytes pretreated with 200 μg / mL IgG-Fc fragment for 4 h followed by 1 μg / mL insulin exposure for 20 min. (FIG. 20L) The predicted local distance difference test (pLDDT) score for multimer structures of the Ig-like domain 1 (IgLD1) of IR (right) and IgG2b-CH3 domain of IgG- Fc (left) predicted with AlphaFold Multimer V2. pLDDT score (1–100) is a per-residue confidence score. (FIG.20M) Predicted alignment error (PAE) score to indicate the expected positional error at residue x if the predicted and actual structures are aligned on residue y (using the Ca, N, and C atoms), which defines the accuracy of the algorithm in predicting the relative spatial distance of amino acids. The pLDDT score defines how precise the local structure prediction is, and sequence alignment blots (coverage) indicate the number of sequences between proteins with alignment, showing the predicted interaction of IgLD1 of IR and IgG2b CH3 domain. (FIG. 20N) Plasmid map of the TurboID-IR-D1 plasmid showing removal of the IgLD1 coding sequence from TurboID-IR. (FIG. 20O) WB of IRb phosphorylation in 293T cells transfected with TurboID-IRAttorney Docket No. 44010.206WO-PCT / / CU24263 or its IgLD1 truncated mutant, with or without 1 μg / mL insulin treatment for 20 min. (FIG. 20P) WB analysis of streptavidin pull-down samples to evaluate the interaction between IgG and IR or IR-D1 in 293T cells overexpressing TurboID-IR or TurboIDIR- D1. All data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by two-tailed Student’s t test or two- way ANOVA analysis followed Tukey’s test. See also FIG. 28.

[0038] FIG. 21A-FIG. 21J – IgG competes with insulin for binding to the IR through its CH3 domain. (FIG.21A) Computed model of inactive IR ectodomain-IgG2b CH3 domain dimer compared with insulin binding. (FIG.21B) Computed model of active IR ectodomain-IgG2b CH3 domain dimer complex in comparison to insulin binding. (FIG. 21C) Changes in thermophoresis in a titration of insulin at concentrations from 60.1 pM to 2 μM against 50 nM IR are shown (n = 3). (FIG. 21D) After preincubation of 50 nM IR with 0.52 μM of IgG at RT for 10 min, changes in thermophoresis in a titration of insulin at concentrations from 60.1 pM to 2 μM against the IR- IgG mixture (n = 3). (FIG. 21E) After preincubation of 50 nM IR with 250 μM of IgG at room temperature (RT) for 10 min, changes in thermophoresis in a titration of insulin at concentrations from 60.1 pM to 2 μM against the IR-IgG mixture. No binding KD of insulin to IR was detected (n = 3). (FIG. 21F) Changes in thermophoresis in a titration of native IgG at concentrations from 24.4 nM to 800 μM against 20 nM IR are shown (n = 3). (FIG. 21G) Changes in thermophoresis in a titration of native IgG at concentrations from 24.4 nM to 800 μM against the IR-insulin mixture after preincubation of 20 nM IR with 20 nM insulin at RT for 10 min (n = 3). (FIG. 21H) SPR assay for kinetic binding of insulin with IR. The titration of insulin at concentrations from 6.25 to 200 nM. (FIG. 21I and J) SPR assay for kinetic binding of insulin and IR in the presence of 50 μM IgG (FIG. 21I) or albumin (FIG. 21J). The titration of insulin at concentrations from 6.25 to 200 nM. All data are presented as mean ± SEM. See also FIG. 29.

[0039] FIG. 22A-FIG. 22L – IgG obstructs adipogenesis. (FIG. 22A) Adipogenic gene expression in eWAT during an HFD time course. 8-week-old C56BL / 6J male mice were fed with HFD for 0, 1, 2, 4, 8, and 12 weeks (n = 5 for each time point). (FIG. 22B) Adipogenic gene expression in eWAT from Ctrl and pKO mice after 4-week HFD feeding (n = 6, 6). (FIG. 22C) Adipogenic gene expression in eWAT from Ctrl and mKO mice after 12-week HFD feeding (n = 7, 8). (FIG. 22D) Adipogenic gene expression in eWAT from Veh- or IgG-treated mice in FIGS. 1I–1K (n = 5, 5). (FIG.22E) qPCR analysis of adipogenic gene expression in 10-day differentiatedAttorney Docket No. 44010.206WO-PCT / / CU24263 APCs. APCs were treated with indicated doses of IgG during the 10-day adipocyte differentiation before being harvested for RNA extraction (n = 3). (FIG. 22F) Oil red O staining for lipid accumulation in primary adipocytes differentiated in the presence or absence of 100 μg / mL native mouse IgG for 10 days (n = 3). Scale bars, 100 μm. (FIG. 22G) Repressed adipogenic genes in fully differentiated APCs as described in (FIG. 22F). (FIG. 22H) Oil red O staining for neutral lipid contents in 3T3-L1 adipocytes treated with native IgG or boiled IgG during differentiation. Scale bar, 200 μm. (FIG. 22I) WB analysis of adipogenic markers during 3T3-L1 cell adipogenesis treated with vehicle or 200 μg / mL IgG. HSP90 was used as the loading control. CCAAT enhancer binding protein alpha (C / EBPα) and beta (C / EBPβ) and peroxisome proliferator-activated receptor gamma (PPARγ) were probed. (FIG. 22J) WB analysis of adipocyte markers in 200 μg / mL IgG-Fc fragment-treated 3T3-L1 cells after 3 days of differentiation. (FIG. 22K) Time course expression of adipogenic genes in differentiated 3T3-L1 cells treated with Veh or 100 μg / mL IgG (n = 3). (FIG. 22L) Ectopic PPARγ2 reconstitution in Pparg- / -(PgKO) mouse embryonic fibroblasts circumvented the inhibitory effect of IgG on adipogenesis. Cells were induced to differentiate for 7 days with vehicle or 100 μg / mL IgG before oil red O staining. Scale bars, 50 μm. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001 by two-tailed Student’s t test. See also FIG. 30.

[0040] FIG. 23A-FIG. 23K – Targeting Fcgrt with ASO improves metabolic health and promotes adipose remodeling in DIO mice. Ctrl and Fcgrt ASO were administrated to 16-week- old WT male mice (HFD since 8 weeks old) twice weekly for up to 7 weeks. Blood was collected and analyzed after 6-week ASO treatment (n = 7, 7). (FIG. 23A) WB analysis of plasma samples from Ctrl and Fcgrt ASO-treated DIO mice. (FIG.23B) Body weight curve during ASO treatment. (FIG.23C) Magnetic resonance imaging (MRI) to assess body composition after 6 weeks of ASO treatment. (FIG. 23D) GTT after 4-week ASO treatment. (FIG. 23E) ITT after 5-week ASO treatment. (FIG. 23F) Plasma insulin levels before and after ASO treatment. (FIG. 23G) Plasma triglyceride (TG) levels after ASO treatment. (FIG. 23H) WB of FcRn and IgG in eWAT from ASO-treated mice. HSP90 was used as the loading control. (FIG. 23I) H&E staining of eWAT. Scale bar, 200 μm. (FIG.23J) Fat mass of eWAT and iWAT in ASO-treated DIO mice (n = 6, 7). (FIG. 23K) qPCR analysis of genes associated with browning and adipose remodeling in eWATAttorney Docket No. 44010.206WO-PCT / / CU24263 (n = 6, 6). Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001 by two-tailed Student’s t test. See also FIG. 30.

[0041] FIG. 24A-FIG. 24M – IgG preferentially accumulates in WAT in obesity. (FIG. 24A) Immunostaining of IgG, F4 / 80 (macrophage marker), Perilipin 1 (adipocyte marker) and DAPI in eWAT. Scale bars, 50 μm. (FIG.24B) Western blot (WB) analysis of IgG1, IgG2a, IgG3 in eWAT in mice fed with chow diet (CD) or 12-week high fat diet (HFD). HSP90 was used as the loading control. (FIG. 24C) Quantification of FIGS. 1B and S1B (n=5, 5). (FIG. 24D) WB analysis of IgG1, IgG2a, IgG3 in eWAT in mice fed with CD or HFD (n=5, 5). HSP90 was used as the loading control. (FIG. 24E) Quantification of FIGS. 1C and S1D. (FIG. 24F) WB analysis of IgG in iWAT, BAT, and Heart in mice fed with CD or HFD. HSP90 was used as the loading control. (FIG.24G) Quantification of FIGS.17E and 24F. (FIG.24H) Additional IHC staninning of IgG in the human subcutaneous adipose tissue from lean and obese subjects. Scale bars, 100 μm. (FIG.24I) 8-week-old C57BL / 6J mice on chow feeding were i.p. injected with vehicle or 1.5 mg IgG twice weekly for 4 weeks. Mice were perfused with PBS before collecting tissues at sacrifice. WB analysis of IgG tissue distribution. HSP90 was used as the loading control. (FIG. 24J) Body weight curve for the IgG-treated mice. The treatment details are in FIG.1I. (FIG.24K) Quantification of FIG. 17J. (FIG. 24L) Glucose tolerance test (GTT) for IgG treatment in lean mice as in FIG. 17I (n=5, 5).2 g / kg·BW glucose was used. (FIG. 24M) The biological processes influenced by IgG treatment in eWAT were analyzed by GSEA (Gene Set Enrichment Analysis). The top positively enriched and bottom negatively enriched biological processes were plotted for eWAT IgG treat vs. eWAT Vehicle. The biological processes were ranked according to their NES (Normalized Enrichment Score) and redundant terms were removed by REVIGO. In the plots, Red indicates positive enrichment, while blue represents negative enrichment. *p<0.05, by 2-tailed student’s t-test. Data are presented as mean ± SEM. Related to FIG. 17.

[0042] FIG. 25A-FIG. 25V – FcRn in APCs regulates IgG accumulation in early obesity. (FIG. 25A) FcRn tissue expression in adult chow-fed C57BL / 6J mice (n=2). HSP90 was used as the loading control. (FIG.25B) Upregulation of FcRn in eWAT after 12-week HFD feeding. (FIG. 25C) Representative WB showing shortened half-life of biotin-labeled IgG in the circulation of Fcgrtflox / flox(Ctrl) and Fcgrtflox / flox; Pdgfra-cre (pKO) mice. (FIG. 25D) Quantification of the half- life of biotin-labelled IgG in the circulation of 6-9 week old Ctrl and pKO mice (n=6, 4). (FIG.Attorney Docket No. 44010.206WO-PCT / / CU24263 25E) qPCR validation of Fcgrt knockout efficiency in eWAT of 6-week-old Ctrl and pKO mice (n=6, 6). (FIG. 25F) ITT in 9-week-old male Ctrl and pKO mice (n=7, 7), 0.5 U / kg·BW insulin was administered. (FIG. 25G) GTT in 8-week-old male Ctrl and pKO mice (n=7, 7), 2 g / kg·BW glucose was administered. (FIG.25H) Tissue weight after 4 weeks HFD feeding in Ctrl and pKO mice (n=7, 6). (FIG. 25I) H&E staining of eWAT. Scale bar, 100 μm. (FIG. 25J) Plasma TG levels in Ctrl and pKO mice after 4-week HFD feeding (n=7, 6). (FIG.25K) Plasma NEFA levels in Ctrl and pKO mice after 4-week HFD feeding (n=7, 6). (FIG. 25L) Tissue weight of Ctrl and pKO mice after 12 weeks of HFD feeding (n=5, 5). (FIG. 25M) H&E staining of eWAT. Scale bar, 100 μm. (FIG. 25N) Plasma TG levels in Ctrl and pKO mice after 12-week HFD feeding (n=7, 5). (FIG.25O) Plasma NEFA level in Ctrl and pKO mice after 12-week HFD feeding (n=7, 5). (FIG. 25P) Generation and validation of FcRn adipocyte conditional knockout (Fcgtflox / flox; Adipoq-cre, aKO). The knockout efficiency was detected in the eWAT of chow diet-fed mice (n=7, 7). (FIG.25Q) WB analysis of FcRn expression in primary adipocyte differentiation derived from control and aKO mice. (FIG. 25R) Representative blot showing no changes in half-life of biotin-labeled IgG in the circulation of 8-10 weeks old chow diet-fed Ctrl and aKO mice (n=9, 6). (FIG. 25S) Quantification of (FIG. 25R). (FIG. 25T) WB analysis of IgG and FcRn in eWAT and plasma from Ctrl and aKO mice after 12-week HFD feeding (n=6, 7). (FIG. 25U) ITT of Ctrl and aKO mice after 12-week HFD feeding (n=9, 9), 1 U / kg·BW insulin was used. (FIG. 25V) GTT of Ctrl and aKO mice after 12-week HFD feeding (n=9, 9), 1.5 g / kg·BW glucose was injected. Data are presented as mean ± SEM. *p<0.05, **p<0.01, ***p<0.001 by 2-tailed student’s t-test. Related to FIG. 18.

[0043] FIG. 26A-FIG. 26K – Characterizations of mKO mice. (FIG. 26A) Representative blots showing the half-life of biotin-labelled IgG in the circulation of Fcgrtflox / flox(Ctrl) and Fcgrtflox / flox-; LysM-cre (mKO) mice. Biotin-IgG input was loaded as the positive control (Input). WT plasma was loaded as the negative control (NC). (FIG. 26B) Quantification of the half-life of biotin-labelled IgG in the circulation of Ctrl and mKO mice at 6-9 weeks of HFD feeding (n=7, 8). (FIG. 26C-I) In 8-12 weeks old chow-fed male Ctrl and mKO mice, (FIG. 26C-D) WB of plasma proteins and quantification (n=4, 7); (FIG. 26E-F) WB of eWAT proteins and quantification (5, 5); (FIG. 26G) Body composition (n=7, 9); (FIG. 26H-I) ITT and GTT (n=11, 9); (FIG. 26J-K) Quantification of FIG. 19D-E. Related to FIG. 19.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0044] FIG. 27A-FIG. 27O – Characterizations of mKO mice in DIO. (FIG. 27A-L) 8- week-old Fcgrtflox / flox(Ctrl) and Fcgrtflox / flox; LysM-cre (mKO) mice were fed on HFD for 12 weeks. (FIG. 27A) WB of IgG in iWAT from DIO Ctrl and mKO mice. HSP90 was used as the loading control. (FIG. 27B) IHC staining of IgG in eWAT and BAT from DIO Ctrl and mKO mice. Scale bar, 100 μm. (FIG. 27C) Tissue weight after 12-week HFD feeding (n=7, 8). (D) Adipocyte size distribution in eWAT (n=7, 8). (FIG.27E) Sirius red staining of eWAT fibrosis in Ctrl and mKO mice. Scale bar, 100 μm. (FIG. 27F) qPCR analysis of eWAT fibrotic genes expression (n=7, 8). (FIG. 27G) qPCR analysis of eWAT gene expression (n=7, 8). (FIG. 27H) qPCR analysis of iWAT genes expression (n=7, 8). (FIG. 27I-L) Indirect calorimetric analysis of DIO Ctrl and mKO mice after 12 weeks HFD feeding: (FIG. 27I) total energy expenditure as a function of lean mass analysis; (FIG. 27J) food intake; (FIG. 27K) Respiratory exchange ratio (RER); (L) total locomotion activity. (n=6, 6). (FIG. 27M-O) Mice on chow diet were intravenously injected with vehicle or mouse albumin (5 mg / injection, twice a week) for 3 weeks (n=5, 5). (FIG. 27M) WB analysis of albumin accumulation in eWAT. HSP90 was used as the loading control. (FIG. 27N) Body weight curve during albumin treatment. (FIG. 27O) ITT. 0.75 U / kg·BW insulin was administered. *p<0.05, **p<0.01, ***p<0.001 by 2-tailed student’s t-test. Data are presented as mean ± SEM. Related to FIG. 19.

[0045] FIG. 28A-FIG. 28I – Predicted interactions between the IgGs’ CH3 domain and the insulin receptor (IR) immunoglobulin- like domain 1 (IgLD1). (FIG. 28A) 10-week-old C57BL / 6J male mice fed with chow diet were i.p. injected with vehicle or albumin (12 mg / mouse) for overnight and then performed ITT. 0.5 U / kg·BW insulin was administrated (n=8, 7). (FIG. 28B-C) 3T3-L1 adipocytes and C2C12 myotubes were pre-treated with 200 μg / ml IgG or albumin (Alb) for 4 hrs. Cells were further treated with or without 1 μg / ml insulin for another 30 minutes. WB analysis of insulin signaling, with HSP90 as the loading control. (FIG. 28D) Differentiated C2C12 myotubes were pretreated with vehicle or IgG (400 μg / ml) or albumin (Alb, 400 μg / ml) for 4 hours to detect the effects on insulin-stimulated glucose uptake (n=3 / group). (FIG. 28E) In vitro pull-down of IgG and IR. TurboID-IR protein was purified from 293T cells using Streptavidin magnetic beads and incubated with 200 μg / ml IgG for 4 hours, and then examined the pulled down proteins. (FIG. 28F-H) Multimer predictions with Alphafold Multimer V2 using pLDDT, PAE, coverage and pLDDT plots for IgLD1 of IR and subclasses of IgG CH3 domains:Attorney Docket No. 44010.206WO-PCT / / CU24263 (FIG. 28F) IgG1; (FIG. 28G) IgG2a; (FIG.28H) IgG3; (FIG. 28I) Alphafold prediction of PAE of all subclass of IgG-CH3 interacted with the IgLD1 of IR. Related to FIG. 20.

[0046] FIG. 29A-FIG. 29E – Computational models for the competitive binding of IgG with IR through the CH3 domain of IgG. (FIG.29A) Experimental structure of the ectodomain of mouse insulin receptor (mIR) (PDB code: 7SL1). Complete structure of mIR ectodomain after the missing residues in the experimental structure are added and superimposition of the experimental and complete structures of mIR ectodomain. (FIG. 29B) Modelled structures of IR ectodomain in the active sate: T-shape conformation of the ectodomain of the full-length human IR (active state); modelled T-shape conformation of the ectodomain of the full-length mouse IR using SWISS-MODEL; superimposition of the experimental and complete structures of mIR ectodomain in the active sate. (FIG. 29C) Modelled structures of IgG2b CH3 monomer, dimer, and RMSD between template and modelled structures. (FIG. 29D) Two models of the mouse IR ectodomain‒Insulin complex based on the ‘consensus rank’, and the superimposition of the structures of IR ectodomain in the two models and the experimental structures of IR ectodomain‒ insulin complex. (FIG. 29E) PAE and pLDDT of AlphaFold 3 Prediction of albumin binding to IR. Related to FIG. 21.

[0047] FIG. 30A-FIG. 30J – IgG obstructs adipogenesis. (FIG. 30A) Mice were the same as in FIG.S2L. qPCR analysis of gene expression in eWAT of Ctrl and pKO mice after 12-week HFD feeding (n=5, 5). (FIG. 30B) Mice were the same as in FIG.S2P. qPCR analysis of gene expression in eWAT of Ctrl and aKO mice after 12-week HFD feeding (n=7, 6). (FIG. 30C) Oil red O staining for neutral lipid content with IgG treatment in C3H10T1 / 2 cells. Scale bars, 100 μm. (FIG. 30D) Adipogenic gene expression in 3T3-L1 adipocytes with vehicle, boiled IgG, or IgG treatment (n=3 / group). (FIG. 30E) Time course expression of adipogenic genes in differentiated 3T3-L1 cells treated with vehicle or 100 μg / mL IgG (n=3 / time point). (FIG. 30F) Ectopic PPARγ reconstitution in Pparg- / - mouse embryonic fibroblasts circumvented the inhibitory effect of IgG on adipogenesis. Cells were induced to differentiate for 7 days with Veh or 100 μg / ml IgG and were further analyzed qPCR analysis of adipocyte gene expression (n=3, 3). further analyzed qPCR analysis of adipocyte gene expression (n=3, 3). (FIG.30G) Plasma NEFA of DIO mice after ASO treatment (n=7, 7). (FIG. 30H) WB analysis of IgG in iWAT from ASO- treated DIO mice. (FIG.30I) Expression of Fcgrt level in livers from ASO-treated DIO mice (n=6,Attorney Docket No. 44010.206WO-PCT / / CU24263 6). (FIG. 30J) H&E staining of liver sections from ASO-treated DIO mice. *p<0.05, **p<0.01, ***p<0.001 by 2-tailed student’s t-test. Data are presented as mean ± SEM. Related to FIG.22 & 23.

[0048] FIG. 31 – Table showing basic predicted binding affinities in the reference models of mouse IR-insulin and IR-IgG complexes using Area-affinity. Related to FIG. 29.

[0049] FIG. 32 – Table showing basic information of the templates of IgG CH3 domains. Related to FIGS. 28-29.

[0050] FIG. 33 – Summary schematic demonstrating that IgG accumulates preferentially in adipose tissue via FcRn-dependent recycling by adipose progenitor cells and macrophages. This buildup promotes macrophage infiltration and adipose inflammation and impairs insulin binding to its receptor, ultimately leading to insulin resistance and metabolic dysfunction.

[0051] The figures herein are for illustrative purposes only and are not necessarily drawn to scale. DETAILED DESCRIPTION OF THE EXAMPLE EMBODIMENTS General Definitions

[0052] Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. Definitions of common terms and techniques in molecular biology may be found in Molecular Cloning: A Laboratory Manual, 2ndedition (1989) (Sambrook, Fritsch, and Maniatis); Molecular Cloning: A Laboratory Manual, 4thedition (2012) (Green and Sambrook); Current Protocols in Molecular Biology (1987) (F.M. Ausubel et al. eds.); the series Methods in Enzymology (Academic Press, Inc.): PCR 2: A Practical Approach (1995) (M.J. MacPherson, B.D. Hames, and G.R. Taylor eds.): Antibodies, A Laboratory Manual (1988) (Harlow and Lane, eds.): Antibodies A Laboratory Manual, 2ndedition 2013 (E.A. Greenfield ed.); Animal Cell Culture (1987) (R.I. Freshney, ed.); Benjamin Lewin, Genes IX, published by Jones and Bartlet, 2008 (ISBN 0763752223); Kendrew et al. (eds.), The Encyclopedia of Molecular Biology, published by Blackwell Science Ltd., 1994 (ISBN 0632021829); Robert A. Meyers (ed.), Molecular Biology and Biotechnology: a Comprehensive Desk Reference, published by VCH Publishers, Inc., 1995 (ISBN 9780471185710); Singleton et al., Dictionary of Microbiology and Molecular Biology 2ndAttorney Docket No. 44010.206WO-PCT / / CU24263 ed., J. Wiley & Sons (New York, N.Y. 1994), March, Advanced Organic Chemistry Reactions, Mechanisms and Structure 4th ed., John Wiley & Sons (New York, N.Y. 1992); and Marten H. Hofker and Jan van Deursen, Transgenic Mouse Methods and Protocols, 2ndedition (2011).

[0053] As used herein, the singular forms “a”, “an”, and “the” include both singular and plural referents unless the context clearly dictates otherwise.

[0054] The term “optional” or “optionally” means that the subsequent described event, circumstance or substituent may or may not occur, and that the description includes instances where the event or circumstance occurs and instances where it does not.

[0055] The recitation of numerical ranges by endpoints includes all numbers and fractions subsumed within the respective ranges, as well as the recited endpoints.

[0056] The terms “about” or “approximately” as used herein when referring to a measurable value such as a parameter, an amount, a temporal duration, and the like, are meant to encompass variations of and from the specified value, such as variations of + / -10% or less, + / -5% or less, + / - 1% or less, and + / -0.1% or less of and from the specified value, insofar such variations are appropriate to perform in the disclosed invention. It is to be understood that the value to which the modifier “about” or “approximately” refers is itself also specifically, and preferably, disclosed.

[0057] As used herein, a “biological sample” may contain whole cells and / or live cells and / or cell debris. The biological sample may contain (or be derived from) a “bodily fluid”. The present invention encompasses embodiments wherein the bodily fluid is selected from amniotic fluid, aqueous humour, vitreous humour, bile, blood serum, breast milk, cerebrospinal fluid, cerumen (earwax), chyle, chyme, endolymph, perilymph, exudates, feces, female ejaculate, gastric acid, gastric juice, lymph, mucus (including nasal drainage and phlegm), pericardial fluid, peritoneal fluid, pleural fluid, pus, rheum, saliva, sebum (skin oil), semen, sputum, synovial fluid, sweat, tears, urine, vaginal secretion, vomit and mixtures of one or more thereof. Biological samples include cell cultures, bodily fluids, cell cultures from bodily fluids. Bodily fluids may be obtained from a mammal organism, for example by puncture, or other collecting or sampling procedures.

[0058] Various embodiments are described hereinafter. It should be noted that the specific embodiments are not intended as an exhaustive description or as a limitation to the broader aspects discussed herein. One aspect described in conjunction with a particular embodiment is not necessarily limited to that embodiment and can be practiced with any other embodiment(s).Attorney Docket No. 44010.206WO-PCT / / CU24263 Reference throughout this specification to “one embodiment”, “an embodiment,” “an example embodiment,” means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases “in one embodiment,” “in an embodiment,” or “an example embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment, but may. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner, as would be apparent to a person skilled in the art from this disclosure, in one or more embodiments. Furthermore, while some embodiments described herein include some but not other features included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention. For example, in the appended claims, any of the claimed embodiments can be used in any combination.

[0059] Reference is made to Yu L, Wan Q, Liu Q, Fan Y, Zhou Q, Skowronski AA, Wang S, Shao Z, Liao CY, Ding L, Kennedy BK, Zha S, Que J, LeDuc CA, Sun L, Wang L, Qiang L. IgG is an aging factor that drives adipose tissue fibrosis and metabolic decline. Cell Metab. 2024 Apr 2;36(4):793-807.e5. doi: 10.1016 / j.cmet.2024.01.015. Epub 2024 Feb 19. PMID: 38378001; PMCID: PMC11070064; and Yu L, Yang YX, Gong Z, et al. FcRn-dependent IgG accumulation in adipose tissue unmasks obesity pathophysiology. Cell Metab. Published online December 11, 2024. doi:10.1016 / j.cmet.2024.11.001.

[0060] All publications, published patent documents, and patent applications cited herein are hereby incorporated by reference to the same extent as though each individual publication, published patent document, or patent application was specifically and individually indicated as being incorporated by reference. OVERVIEW

[0061] Embodiments disclosed herein relate to reducing aging in a subject by reducing IgG levels. Embodiments disclosed herein relate to reducing obesity in a subject by reducing IgG levels. Embodiments disclosed herein relate to treating diabetes in a subject by reducing IgG levels. In example embodiments, IgG directly causes insulin resistance. Embodiments disclosed herein relate to reducing IgG recycling. Embodiments disclosed herein relate to reducing aging- associated adipose tissue fibrosis. Embodiments disclosed herein relate to determining theAttorney Docket No. 44010.206WO-PCT / / CU24263 biological age of a subject. Embodiments disclosed herein relate to reducing the biological age of a subject. Embodiments disclosed herein relate to the pathogenic remodeling of adipose tissue in aging as a mechanism for metabolic decline with age. Applicants unexpectedly discovered a remarkable age-associated accumulation of IgG in white adipose tissue (WAT). Applicants unexpectedly discovered an accumulation of IgG in every tissue examined. Not being bound by a theory, any tissue that accumulates IgG is projected to degeneration. Using in vitro and complementary in vivo models, Applicants demonstrate that IgG is a driving factor of adipose tissue degeneration and metabolic decline in aging and, therefore, an emerging therapeutic target to extend healthspan.

[0062] Aging is underpinned by pronounced metabolic decline; however, the drivers remain obscure. Here, Applicants report that IgG accumulates during aging, particularly in white adipose tissue (WAT), to impair adipose tissue function and metabolic health. Caloric restriction (CR) decreases IgG accumulation in WAT, whereas replenishing IgG counteracts CR’s metabolic benefits. IgG activates macrophages via Ras signaling and consequently induces fibrosis in WAT through the TGF-β / SMAD pathway. Consistently, B cell null mice are protected from aging- associated WAT fibrosis, inflammation, and insulin resistance, unless exposed to IgG. Conditional ablation of the IgG recycling receptor, neonatal Fc receptor (FcRn), in macrophages prevents IgG accumulation in aging, resulting in prolonged healthspan and lifespan. Further, targeting FcRn by antisense oligonucleotide restores WAT integrity and metabolic health in aged mice. These findings pinpoint IgG as a hidden culprit in aging and enlighten a novel strategy to rejuvenate metabolic health.

[0063] In summary, IgG accumulates in adipose tissue during aging and is reduced by caloric restriction, IgG activates macrophages to induce adipose tissue fibrosis, preventing IgG accumulation in aging prolongs healthspan and lifespan, and targeting IgG recycling receptor FcRn rejuvenates metabolic health in aged mice. Terminology and Definitions

[0064] The terms “subject,” “individual,” and “patient” are used interchangeably herein to refer to a vertebrate, preferably a mammal, more preferably a human. Mammals include, but are not limited to, murines, simians, humans, farm animals, sport animals, and pets. Tissues, cells and their progeny of a biological entity obtained in vivo or cultured in vitro are also encompassed.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0065] The terms “condition,” “disease,” and “disorder” are used interchangeably. Non- limiting examples of conditions, diseases, and disorders include acute injuries, neurodegenerative diseases, chronic diseases, proliferative diseases, cardiovascular diseases, genetic diseases, inflammatory diseases, autoimmune diseases, neurological diseases, hematological diseases, painful conditions, psychiatric disorders, metabolic disorders, chronic diseases, cancers, aging, age-related diseases, and diseases affecting any tissue in a subject. For example, age-related conditions include, loss of physiological integrity of tissue, heart failure, stroke, heart disease, atherosclerosis, neurodegenerative diseases (e.g., Parkinson's disease and Alzheimer's disease), cognitive decline, memory loss, diabetes, osteoporosis, arthritis, muscle loss, hearing loss (partial or total), eye-related conditions (e.g., poor eye sight or retinal disease), glaucoma, a progeroid syndrome (e.g., Hutchinson-Gilford progeria syndrome), and cancer.

[0066] As used herein the term “aging” refers to the natural deterioration over time of an organism, and specifically the cells of an organism. In some embodiments, aging comprises a diminished capacity of stem cells to produce differentiated cells. In some embodiments, aging comprises a diminished capacity of stem cells to self-renew. In some embodiments, aging comprises cells entering senescence. In some embodiments, aging comprises increased cell death. In some embodiments, aging comprises decreased cellular respiration. In some embodiments, aging comprises increased cellular reactive oxidation species (ROS). In some embodiments, aging comprises increased inflammation. In some embodiments, aging comprises increased fibrosis. In some embodiments, aging comprises increased scar tissue. In some embodiments, aging comprises cardiac heterotrophy. In some embodiments, aging comprises impaired glucose homeostasis. In some embodiments, aging comprises reduced cognitive function. In some embodiments, aging comprises reduced or impaired memory. In some embodiments, aging comprises reduced chondrocyte survival.

[0067] As used herein, the term “disease associated with aging” is a disease in which aging is a major risk factor.

[0068] As used herein “biological age” refers to a subject’s physiological state and overall health, as opposed to their chronological age (time since birth). For example, biological age reflects the accumulation of cellular damage and functional decline over time. In example embodiments, biological age can be reversed.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0069] As used herein “fibrosis” (also known as fibrotic scarring) is the development of fibrous connective tissue in response to an injury. Fibrosis can be a normal connective tissue deposition or excessive tissue deposition caused by a disease. Repeated injuries, chronic inflammation and repair are susceptible to fibrosis, where an accidental excessive accumulation of extracellular matrix components, such as the collagen, is produced by fibroblasts, leading to the formation of a permanent fibrotic scar. Physiologically, fibrosis acts to deposit connective tissue, which can interfere with or totally inhibit the normal architecture and function of the underlying organ or tissue. Fibrosis can be used to describe the pathological state of excess deposition of fibrous tissue, as well as the process of connective tissue deposition in healing. Defined by the pathological accumulation of extracellular matrix (ECM) proteins, fibrosis results in scarring and thickening of the affected tissue. Fibrosis can occur in many tissues within the body, typically as a result of inflammation or damage. Common sites of fibrosis include the lungs, liver, kidneys, brain, and heart. Adipose tissue fibrosis is a condition characterized by the excessive accumulation of extracellular matrix (ECM) proteins in adipose tissue.

[0070] As used herein “adipose fibrosis” refers to the excessive buildup of fibrous connective tissue within adipose (fat) tissue, and it is a significant hallmark of aging, where this tissue progressively accumulates fibrosis as people get older, often leading to impaired As used herein function and contributing to age-related diseases like diabetes and cardiovascular issues; essentially, as people age, their fat tissue becomes increasingly fibrotic, impacting its ability to store and release energy effectively. The accumulation of immune cells, particularly macrophages, within aging adipose tissue contributes to the inflammatory environment that promotes fibrosis.

[0071] As used herein “tissue integrity” refers to the structural and functional soundness of tissues in the body. It encompasses the ability of tissues to withstand external stresses, heal from injuries, and maintain their normal functions. Tissue integrity declines with age due to decreased cell turnover and extracellular matrix production.

[0072] As used herein, “metabolic health” refers to the body's ability to process and use energy efficiently. As used herein, a “metabolic” disease, disorder, or condition is a condition that occurs when the body's chemical reactions that convert food into energy are disrupted. Metabolic health, disease, disorder, or condition encompasses various factors that influence how the body handles glucose, insulin, cholesterol, and blood pressure. Maintaining good metabolic health is crucial forAttorney Docket No. 44010.206WO-PCT / / CU24263 overall health and well-being. By addressing the factors that influence metabolic health, individuals can reduce their risk of chronic diseases and improve their quality of life. Poor metabolic health is linked to an increased risk of chronic diseases such as, type 2 diabetes, heart disease, stroke, kidney disease, and non-alcoholic fatty liver disease (NAFLD). The term “metabolic disorder” is used broadly herein to refer to the conditions, diseases, and disorders associated with insulin and / or glucose dysregulation.

[0073] As used herein “inflammation” refers to the activation of the immune system in response to harmful stimuli, such as, e.g., a pathogen, infection, irritant, or damage to cells. Inflammation can be classified as either acute or chronic. Severe or prolonged stimulation results in a chronic inflammatory response that leads to a progressive shift in the type of cells present at the site of tissue injury. Chronic inflammation may be characterized as the simultaneous destruction and healing of tissue from the inflammatory process, with the net result of provoking injury rather than mediating repair. Inflammation is initiated by tissue resident cells that undergo activation and release of inflammatory molecules, such as, pro-inflammatory cytokines.

[0074] As used herein “Type 2 diabetes” (T2D) (also referred to as, type-2 diabetes mellitus (T2DM), and adult-onset diabetes), refers to a form of diabetes mellitus that is characterized by high blood sugar, insulin resistance or insulin insensitivity, and relative lack of insulin or inappropriate insulin secretion, and additional metabolic disturbances such as dyslipidemia and impaired liver functions. Type 2 diabetes primarily occurs as a result of obesity and lack of exercise. Some people are genetically more at risk than others. Diagnosis of diabetes is by blood tests such as fasting plasma glucose, oral glucose tolerance test, or glycated hemoglobin (A1c).

[0075] As used herein “insulin sensitivity” refers to reduced ability to effectively use insulin to lower blood sugar levels.

[0076] As used herein “obesity” refers to having too much body fat. A BMI of 30 (kg / m2) or higher is the usual benchmark for obesity in adults. Body mass index (BMI) is a calculated measure of weight relative to height. Obesity can be further subdivided into three classes based on BMI (Class 1 Obesity - 30 to less than 35; Class 2 Obesity - 35 to less than 40; Class 3 Obesity (Severe Obesity) - 40 or greater).

[0077] As used herein “dyslipidemia” refers to a condition characterized by abnormal levels of lipids (fats) in the bloodstream. It is a major risk factor for cardiovascular diseases, such as heartAttorney Docket No. 44010.206WO-PCT / / CU24263 attack and stroke. Dyslipidemia includes hypercholesterolemia (high levels of total cholesterol and / or LDL (low-density lipoprotein) cholesterol), hypertriglyceridemia (high levels of triglycerides), low HDL (high-density lipoprotein) cholesterol (low levels of HDL cholesterol), mixed dyslipidemia (a combination of abnormal lipid levels).

[0078] As used herein “calorie restriction” refers to the reduction of energy intake without malnutrition (see, e.g., Anderson RM, Weindruch R. The caloric restriction paradigm: implications for healthy human aging. Am J Hum Biol. 2012;24(2):101-106).

[0079] Immunoglobulin G (IgG) is the most common antibody in the body. IgG has four subclasses: IgG1, IgG2, IgG3, and IgG4. IgG binds to Fcγ receptors on the surface of cells like macrophages and neutrophils, which activates the complement system.

[0080] The terms “therapeutic agent”, “therapeutic capable agent” or “treatment agent” are used interchangeably and refer to a molecule or compound that confers some beneficial effect upon administration to a subject. The beneficial effect includes enablement of diagnostic determinations; amelioration of a disease, symptom, disorder, or pathological condition; reducing or preventing the onset of a disease, symptom, disorder or condition; and generally counteracting a disease, symptom, disorder or pathological condition.

[0081] As used herein, “treatment” or “treating,” or “palliating” or “ameliorating” are used interchangeably. These terms refer to an approach for obtaining beneficial or desired results including but not limited to a therapeutic benefit and / or a prophylactic benefit. By therapeutic benefit is meant any therapeutically relevant improvement in or effect on one or more diseases, conditions, or symptoms under treatment. For prophylactic benefit, the compositions may be administered to a subject at risk of developing a particular disease, condition, or symptom, or to a subject reporting one or more of the physiological symptoms of a disease, even though the disease, condition, or symptom may not have yet been manifested. As used herein “treating” includes ameliorating, curing, preventing it from becoming worse, slowing the rate of progression, or preventing the disorder from re-occurring (i.e., to prevent a relapse).

[0082] The term “effective amount” or “therapeutically effective amount” refers to the amount of an agent that is sufficient to effect beneficial or desired results. The therapeutically effective amount may vary depending upon one or more of: the subject and disease condition being treated, the weight and age of the subject, the severity of the disease condition, the manner ofAttorney Docket No. 44010.206WO-PCT / / CU24263 administration and the like, which can readily be determined by one of ordinary skill in the art. The term also applies to a dose that will provide an image for detection by any one of the imaging methods described herein. The specific dose may vary depending on one or more of: the particular agent chosen, the dosing regimen to be followed, whether it is administered in combination with other compounds, timing of administration, the tissue to be imaged, and the physical delivery system in which it is carried.

[0083] A “pharmaceutical composition” refers to a composition that usually contains an excipient, such as a pharmaceutically acceptable carrier that is conventional in the art and that is suitable for administration to cells or to a subject.

[0084] A “control” condition or sample refers to a sample that serves as a reference, usually a known reference, for comparison to a test condition or sample. For example, a test sample can represent a patient sample, while a control can represent a sample from an individual known to have a disorder, or from an individual that is known to not have the disorder. In another example, a test sample can be taken from a test condition, e.g., in the presence of a test compound, and compared to samples from known conditions, e.g., in the absence of the test compound (negative control), or in the presence of a known compound (positive control). A control can also represent an average value gathered from a number of tests or results. One of skill in the art will recognize that controls can be designed for assessment of any number of parameters. For example, a control can be devised to compare therapeutic benefit based on pharmacological data (e.g., half-life) or therapeutic measures (e.g., comparison of benefit and / or side effects). One of skill in the art will understand which controls are valuable in a given situation and be able to analyze data based on comparisons to control values. Controls are also valuable for determining the significance of data. For example, if values for a given parameter are widely variant in controls, variation in test samples will not be considered as significant.

[0085] As used herein “neonatal fragment crystallizable (Fc) receptor” (FcRn) refers to the receptor encoded for by the FCGRT gene (also known as, FCRN; FcgammaRn; alpha-chain; Brambell receptor). This gene encodes a receptor that binds the Fc region of monomeric immunoglobulin G. The encoded protein transfers immunoglobulin G antibodies from mother to fetus across the placenta. This protein also binds immunoglobulin G to protect the antibody from degradation. This receptor exists as a non-covalently bound heterodimer consisting of an alpha (α)Attorney Docket No. 44010.206WO-PCT / / CU24263 heavy chain of approximately 50 kDa and a β2-microglobulin (β2m) light chain of 12 kDa. Alternative splicing results in multiple transcript variants. Exemplary reference sequences include NM_001136019.3, NP_001129491.1, NM_001411064.1, NP_001397993.1, NM_004107.5, and NP_004098.1.

[0086] All gene name symbols refer to the gene as commonly known in the art. The examples described herein that refer to the mouse gene names are to be understood to also encompasses human genes, as well as genes in any other organism (e.g., homologous, orthologous genes). Any reference to the gene symbol is a reference made to the entire gene or variants of the gene. Any reference to the gene symbol is also a reference made to the gene product (e.g., protein). The term, homolog, may apply to the relationship between genes separated by the event of speciation (e.g., ortholog). Orthologs are genes in different species that evolved from a common ancestral gene by speciation. Normally, orthologs retain the same function in the course of evolution. Gene symbols may be those referred to by the HUGO Gene Nomenclature Committee (HGNC) or National Center for Biotechnology Information (NCBI). METHOD OF REDUCING METABOLIC DECLINE AND PATHOGENIC REMODELING OF TISSUE IN AGING BY REDUCING IGG

[0087] In example embodiments, IgG levels are reduced to treat tissue integrity, metabolic health, inflammation, and / or fibrosis in a subject. In example embodiments, IgG levels are reduced by one or more therapeutic agents. In preferred embodiments, IgG is reduced and not eliminated. For example, reducing or completely eliminating IgG can make a subject more likely to get infections. In example embodiments, IgG is reduced by 5, 10, 20, 30, 40, 50, 60, 70, 80, or 90% (e.g., 5, 10, 20, 30, 40, 50, 60, 70, 80, or 90% of the untreated level). In example embodiments, calorie restriction (CR) reduces IgG levels and the IgG is reduced to this level (i.e., a CR reference level). CR IgG levels can be determined by detecting IgG levels in control subjects undergoing CR. In example embodiments, IgG is reduced to a control reference level. In example embodiments, the control reference value is determined by detecting the average IgG levels in control subjects at different ages. For example, the average IgG levels for subjects above 30 years old or subjects above 60 years old or subjects above 70 years old.

[0088] In example embodiments, IgG recycling is reduced. In example embodiments, inhibiting IgG recycling reduces IgG levels without compromising its production. In exampleAttorney Docket No. 44010.206WO-PCT / / CU24263 embodiments, inhibiting IgG recycling has a greater impact on IgG levels than production by B cells. In example embodiments, IgG recycling is inhibited by inhibiting a neonatal fragment crystallizable (Fc) receptor (FcRn). In example embodiments, FcRn is inhibited on myeloid cells. In example embodiments, the myeloid cells are macrophages. Diseases, Conditions, or Disorders

[0089] In example embodiments, the subject has or is at risk for a disease, condition, or disorder associated with metabolic health (e.g., obesity, type 2 diabetes).

[0090] In example embodiments, the subject has or is at risk for a disease, condition, or disorder associated with aging. Exemplary conditions associated with aging include, but are not limited to reduced tissue integrity, reduced metabolic health, inflammation, and / or fibrosis.

[0091] In example embodiments, age is used for a subject herein based on the age equivalent in development as compared to humans (e.g., age at mature adult, middle age, and old). In example embodiments, the human subject treated is over 30, 60, or 70 years old. For example, mice age can be compared to human age, however, the average lifespan of a laboratory mouse is about two years, while the average human lives about 80 years. In example embodiments, on average throughout a lifespan, one mouse day is equivalent to about 40 human days, while one human year equates to about 9 mouse days. In example embodiments, mice are mature adults at 3-6 months (20-30 years in humans), middle aged at 10-14 months (38-47 years in humans), and old at 18-24 months (56-69 years in humans).

[0092] In example embodiments, the one or more agents can be used to slow the onset of the consequences of aging. In example embodiments, the methods of the invention are for treating an aging associated disease or condition that is not cancer and decreasing the risk of developing cancer. In example embodiments, a subject is treated for an age associated disease. Based on the type of disease, age-related diseases include the following three main types: (1) abnormally proliferative diseases such as cancer; (2) degenerative diseases, neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, stroke), myocardial infarction, heart failure, atherosclerosis, hypertension, osteoarthritis, osteoporosis, sarcopenia, bone marrow reduction, rheumatoid arthritis, immune function, diabetes, idiopathic pulmonary fibrosis, age-related macular degeneration, and (3) hypofunctional diseases such as testosterone, estrogen, growth hormone, IGF-I decrease, energy production decreased, etc. There are two main types of cell-Attorney Docket No. 44010.206WO-PCT / / CU24263 related diseases associated with aging, (1) neuronal degeneration (Alzheimer's disease, Parkinson's disease, stroke), sarcopenia (muscle loss), cardiovascular disease (heart failure, myocardial infarction); and (2) cancer, bone marrow reduction, immune function decline, diabetes, idiopathic pulmonary fibrosis, age-related macular degeneration, rheumatoid arthritis, osteoarthritis in mitotic cells, osteoporosis, atherosclerosis, and hypertension. Specifically, age-related diseases include mitochondrial dysfunction and / or telomere dysfunction, cancer, osteoarthritis, age-related macular degeneration, idiopathic pulmonary fibrosis, Parkinson's disease, Alzheimer's disease, Huntington Diseases, skin aging, cataracts, multiple sclerosis, Sjogren's syndrome, rheumatoid arthritis, atherosclerosis, myocardial infarction, heart failure, hypertension, stroke, diabetes, osteoporosis, obesity, gray hair, hearing loss, etc. In example embodiments, an aging-associated disease refers to a condition or disease whose prevalence increases with age (e.g., adipose tissue fibrosis). In example embodiments, an aging-associate disease or condition is a disease or condition that occurs with increasing frequency when there is increasing or increased IgG. Age related diseases or conditions are not limited. All the above diseases or conditions are encompassed by the present invention.

[0093] In example embodiments, the one or more agents can be used to slow the onset of a metabolic disease or condition. In example embodiments, the one or more agents can be used to reverse a metabolic disease or condition. In example embodiments, the methods of the invention are for treating a metabolic disease or condition that is not cancer and decreasing the risk of developing cancer. In example embodiments, a subject is treated for a metabolic disease or condition. Non-limiting metabolic diseases or conditions include obesity, type 2 diabetes, insulin insensitivity, glucose intolerance, elevated blood glucose levels, high percent body fat, fatty liver, dyslipidemia, and metabolic syndrome. Metabolic syndrome is diagnosed when a person has three or more of the following conditions: abdominal obesity (waist circumference greater than 40 inches in men or 35 inches in women), high blood pressure (systolic blood pressure greater than or equal to 130 mmHg or diastolic blood pressure greater than or equal to 80 mmHg), high blood sugar (fasting blood glucose level greater than or equal to 100 mg / dL), high triglycerides (triglyceride level greater than or equal to 150 mg / dL), and low HDL cholesterol (HDL cholesterol level less than 40 mg / dL in men or less than 50 mg / dL in women). One of skill will understand that metabolic disorders are associated with and can result in a wide range of other disorders, e.g.,Attorney Docket No. 44010.206WO-PCT / / CU24263 high blood pressure, heart disease, poor circulation, etc., which can be ameliorated by addressing the metabolic disorder according to the methods of the invention. In example embodiments, the methods described herein can be used to treat any obese subject in any class. For example, class I, II, or III obesity. In example embodiments, the subject is generally healthy and is treated to improve tissue integrity, metabolic health, inflammation, and / or fibrosis associated with normal aging. Therapeutic agents

[0094] In example embodiments, the present invention provides for one or more therapeutic agents capable of reducing IgG levels in a subject. Reducing IgG levels may provide for enhanced healthspan and / or lifespan. In example embodiments, the one or more agents comprises a small molecule inhibitor, small molecule degrader (e.g., ATTEC, AUTAC, LYTAC, or PROTAC), genetic modifying agent, antibody, antibody fragment, antibody-like protein scaffold, aptamer, protein, or any combination thereof. In example embodiments, any therapeutic agent or therapeutic method disclosed herein may be used in a combination therapy. In example embodiments, administering a combination of therapeutic agents would reduce the dosage of individual therapeutic agents while having the same or improved therapeutic effect. In example embodiments, administering a combination therapy reduces adverse effects associated with a therapeutic agent (e.g., because the dosage is reduced). FcRn inhibitors

[0095] In example embodiments, a subject is treated with one or more agents that reduce IgG recycling. In example embodiments, the one or more agents is a neonatal fragment crystallizable (Fc) receptor (FcRn) inhibitor. In example embodiments, any FcRn inhibitor known in the art or under development can be used to treat a subject according to the present invention. FcRn inhibitors are used in basic research and clinical trials for treating subjects having autoimmune diseases (see, e.g., Zhu LN, Hou HM, Wang S, et al. FcRn inhibitors: a novel option for the treatment of myasthenia gravis. Neural Regen Res. 2023;18(8):1637-1644. doi:10.4103 / 1673- 5374.363824; and Peter HH, Ochs HD, Cunningham-Rundles C, et al. Targeting FcRn for immunomodulation: Benefits, risks, and practical considerations. J Allergy Clin Immunol. 2020;146(3):479-491.e5).Attorney Docket No. 44010.206WO-PCT / / CU24263

[0096] In example embodiments, the FcRn inhibitor is an antibody. As used herein, antibody includes Fc fragments. In example embodiments, the antibodies are humanized anti-FcRn monoclonal antibodies (or Fc fragments) that have a higher affinity for FcRn than wild-type IgG in both acidic and neutral environments.

[0097] In example embodiments, the antibody is an Abdeg (antibodies that enhance IgG degradation) (see, e.g., Vaccaro C, Zhou J, Ober RJ, Ward ES. Engineering the Fc region of immunoglobulin G to modulate in vivo antibody levels. Nat Biotechnol.2005;23(10):1283-1288). Abdegs are engineered variants of human IgG1 that contain amino acid modifications (M252Y / S254T / T256E / H433K / N434F). Compared with wild-type IgG, Abdegs display higher affinity for human FcRn (hFcRn) both at pH 6 and pH 7.2. Abdegs cannot target specific tissues and produce predominant local effects; they can only systematically induce the degradation of all IgGs, leading to a reduction in total IgG levels in vivo. Not being bound by a theory, the instant disclosure provides for the first time that systemic reduction in total IgG levels can improve or reverse the adverse effects of aging.

[0098] Example antibodies include, but are not limited to efgartigimod, rozanolixizumab, nipocalimab, orilanolimab, batoclimab, and ABY039. Efgartigimod is a modified human IgG1- derived Fc fragment harboring amino acid modifications, introduced using Abdeg technology, that enhance its binding affinity for FcRn in both acidic and neutral environments (equilibrium dissociation constant [KD]=14.2 nM at pH 6.0 and 320 nM at pH 7.4) while retaining the pH- dependent interaction with FcRn (Zhu, et al. 2023). Rozanolixizumab is a subcutaneously (SC) administered, humanized, anti-FcRn monoclonal antibody (IgG4P) with high affinity for FcRn at both pH 6.0 and pH 7.4 (Smith et al., 2018). Rozanolixizumab selectively inhibits the binding of FcRn and IgG, leading to IgG degradation and clearance via the lysosomal pathway and, consequently, a decrease in serum IgG levels. Id. Batoclimab (HBM9161) is a fully human, IgG1 monoclonal anti-FcRn antibody, the Fc portion of which was modified to reduce antibody- dependent cell-mediated cytotoxicity. HBM9161 specifically targets the IgG binding site on FcRn, thereby blocking FcRn from binding to IgG and accelerating IgG clearance. Id. Nipocalimab is an aglycosylated, fully human, IgG1 monoclonal anti-FcRn antibody that shows high affinity for FcRn at both pH 6.0 and pH 7.6. Id. Orilanolimab (SYNT001) is a humanized, de-immunized IgG4 monoclonal antibody harboring a S241P mutation. SYNT001 binds to hFcRn at both neutralAttorney Docket No. 44010.206WO-PCT / / CU24263 and acidic pHs, thereby disrupting IgG homeostasis and achieving a reduction in serum IgG levels. Id. ABY-039 is a bivalent antibody mimetic and CSL730 / M230 is a Fc fragment (see, e.g., Patel DD, Bussel JB. Neonatal Fc receptor in human immunity: Function and role in therapeutic intervention. J Allergy Clin Immunol. 2020;146(3):467-478).

[0099] In example embodiments, the FcRn inhibitor is a peptide. In example embodiments, the peptide has a high affinity for FcRn at pH 6.0 and 7.4 and outcompetes IgG for hFcRn binding both intracellularly and on the cell surface. In example embodiments, the peptide comprises the consensus peptide sequence GHFGGXY. In example embodiments, X is preferably a hydrophobic amino acid. Mezo et al. (Mezo AR, McDonnell KA, Castro A, Fraley C. Structure-activity relationships of a peptide inhibitor of the human FcRn:human IgG interaction. Bioorg Med Chem. 2008;16(12):6394-6405; and Mezo AR, McDonnell KA, Hehir CA, et al. Reduction of IgG in nonhuman primates by a peptide antagonist of the neonatal Fc receptor FcRn. Proc Natl Acad Sci U S A.2008;105(7):2337-2342) identified a family of five peptides (SYN722–SYN726) that bind hFcRn and block IgG binding. SYN1436 is a 26-amino acid peptide dimer (molecular mass: 3.1 kDa) containing the SYN722 core sequence and has a high affinity for FcRn at pH 6.0 and 7.4. SYN1436 outcompetes IgG for hFcRn binding both intracellularly and on the cell surface, thereby inhibiting the interaction of hFcRn with IgG which, in turn, reduces circulating IgG levels. SYN1436 reduced IgG levels by up to 80% in cynomolgus monkeys without affecting serum albumin levels (Mezo et al., 2008). Similar effects were observed for SYN1327, a monomeric peptide based on SYN1436 (Mezo et al., 2008). Additional agents and methods for reducing IgG

[0100] In example embodiments, immunoglobulin G (IgG) production can be reduced by administering immunosuppressive and anti-B-cell drugs, such as, but not limited to rituximab, eculizumab, methotrexate, zilucoplan, ravulizumab, acetylcholinesterases, and corticosteroids (see, e.g., Narayanaswami P, Sanders DB, Wolfe G, et al. International Consensus Guidance for Management of Myasthenia Gravis: 2020 Update. Neurology.2021;96(3):114-122; and Menon D, Bril V. Pharmacotherapy of Generalized Myasthenia Gravis with Special Emphasis on Newer Biologicals. Drugs. 2022;82(8):865-887). In example embodiments, immunoglobulin G (IgG) production can be reduced by increasing IgG clearance via intravenous immunoglobulin (IVIG) infusion, plasma exchange (PE), and immunoadsorption (IA) (see, e.g., Karelis G, Balasa R, DeAttorney Docket No. 44010.206WO-PCT / / CU24263 Bleecker JL, et al. A Phase 3 Multicenter, Prospective, Open-Label Efficacy and Safety Study of Immune Globulin (Human) 10% Caprylate / Chromatography Purified in Patients with Myasthenia Gravis Exacerbations. Eur Neurol. 2019;81(5-6):223-230; and Liu C, Liu P, Ma M, Yang H, Qi G. Efficacy and safety of double-filtration plasmapheresis treatment of myasthenia gravis: A systematic review and meta-analysis. Medicine (Baltimore). 2021;100(17):e25622). In example embodiments, serum IgG levels are reduced by approximately 50% and clinical effects can be seen within days to weeks. Antibodies

[0101] The term “antibody” is used interchangeably with the term “immunoglobulin” herein, and includes intact antibodies, fragments of antibodies, e.g., Fab, F(ab')2 fragments, and intact antibodies and fragments that have been mutated either in their constant and / or variable region (e.g., mutations to produce chimeric, partially humanized, or fully humanized antibodies, as well as to produce antibodies with a desired trait, e.g., enhanced binding and / or reduced FcR binding). The term “fragment” refers to a part or portion of an antibody or antibody chain comprising fewer amino acid residues than an intact or complete antibody or antibody chain. Fragments can be obtained via chemical or enzymatic treatment of an intact or complete antibody or antibody chain. Fragments can also be obtained by recombinant means. Exemplary fragments include Fab, Fab', F(ab')2, Fabc, Fd, dAb, VHHand scFv and / or Fv fragments.

[0102] As used herein, a preparation of antibody protein having less than about 50% of non- antibody protein (also referred to herein as a “contaminating protein”), or of chemical precursors, is considered to be “substantially free.” 40%, 30%, 20%, 10% and more preferably 5% (by dry weight), of non-antibody protein, or of chemical precursors is considered to be substantially free. When the antibody protein or biologically active portion thereof is recombinantly produced, it is also preferably substantially free of culture medium, i.e., culture medium represents less than about 30%, preferably less than about 20%, more preferably less than about 10%, and most preferably less than about 5% of the volume or mass of the protein preparation.

[0103] The term “antigen-binding fragment” refers to a polypeptide fragment of an immunoglobulin or antibody that binds antigen or competes with intact antibody (i.e., with the intact antibody from which they were derived) for antigen binding (i.e., specific binding). As suchAttorney Docket No. 44010.206WO-PCT / / CU24263 these antibodies or fragments thereof are included in the scope of the invention, provided that the antibody or fragment binds specifically to a target molecule.

[0104] It is intended that the term “antibody” encompass any Ig class or any Ig subclass (e.g. the IgG1, IgG2, IgG3, and IgG4 subclasses of IgG) obtained from any source (e.g., humans and non-human primates, and in rodents, lagomorphs, caprines, bovines, equines, ovines, etc.).

[0105] The term “Ig class” or “immunoglobulin class”, as used herein, refers to the five classes of immunoglobulin that have been identified in humans and higher mammals, IgG, IgM, IgA, IgD, and IgE. The term “Ig subclass” refers to the two subclasses of IgM (H and L), three subclasses of IgA (IgA1, IgA2, and secretory IgA), and four subclasses of IgG (IgG1, IgG2, IgG3, and IgG4) that have been identified in humans and higher mammals. The antibodies can exist in monomeric or polymeric form; for example, lgM antibodies exist in pentameric form, and IgA antibodies exist in monomeric, dimeric or multimeric form.

[0106] The term “IgG subclass” refers to the four subclasses of immunoglobulin class IgG - IgG1, IgG2, IgG3, and IgG4 that have been identified in humans and higher mammals by the heavy chains of the immunoglobulins, V1 - γ4, respectively. The term “single-chain immunoglobulin” or “single-chain antibody” (used interchangeably herein) refers to a protein having a two- polypeptide chain structure consisting of a heavy and a light chain, said chains being stabilized, for example, by interchain peptide linkers, which has the ability to specifically bind antigen. The term “domain” refers to a globular region of a heavy or light chain polypeptide comprising peptide loops (e.g., comprising 3 to 4 peptide loops) stabilized, for example, by β pleated sheet and / or intrachain disulfide bond. Domains are further referred to herein as “constant” or “variable”, based on the relative lack of sequence variation within the domains of various class members in the case of a “constant” domain, or the significant variation within the domains of various class members in the case of a “variable” domain. Antibody or polypeptide “domains” are often referred to interchangeably in the art as antibody or polypeptide “regions”. The “constant” domains of an antibody light chain are referred to interchangeably as “light chain constant regions”, “light chain constant domains”, “CL” regions or “CL” domains. The “constant” domains of an antibody heavy chain are referred to interchangeably as “heavy chain constant regions”, “heavy chain constant domains”, “CH” regions or “CH” domains. The “variable” domains of an antibody light chain are referred to interchangeably as “light chain variable regions”, “light chain variable domains”, “VL”Attorney Docket No. 44010.206WO-PCT / / CU24263 regions or “VL” domains. The “variable” domains of an antibody heavy chain are referred to interchangeably as “heavy chain constant regions”, “heavy chain constant domains”, “VH” regions or “VH” domains.

[0107] The term “region” can also refer to a part or portion of an antibody chain or antibody chain domain (e.g., a part or portion of a heavy or light chain or a part or portion of a constant or variable domain, as defined herein), as well as more discrete parts or portions of said chains or domains. For example, light and heavy chains or light and heavy chain variable domains include “complementarity determining regions” or “CDRs” interspersed among “framework regions” or “FRs”, as defined herein.

[0108] The term “conformation” refers to the tertiary structure of a protein or polypeptide (e.g., an antibody, antibody chain, domain or region thereof). For example, the phrase “light (or heavy) chain conformation” refers to the tertiary structure of a light (or heavy) chain variable region, and the phrase “antibody conformation” or “antibody fragment conformation” refers to the tertiary structure of an antibody or fragment thereof.

[0109] The term “antibody-like protein scaffolds” or “engineered protein scaffolds” broadly encompasses proteinaceous non-immunoglobulin specific-binding agents, typically obtained by combinatorial engineering (such as site-directed random mutagenesis in combination with phage display or other molecular selection techniques). Usually, such scaffolds are derived from robust and small soluble monomeric proteins (such as Kunitz inhibitors or lipocalins) or from a stably folded extra-membrane domain of a cell surface receptor (such as protein A, fibronectin or the ankyrin repeat).

[0110] Such scaffolds have been extensively reviewed in Binz et al. (Engineering novel binding proteins from nonimmunoglobulin domains. Nat Biotechnol 2005, 23:1257-1268), Gebauer and Skerra (Engineered protein scaffolds as next-generation antibody therapeutics. Curr Opin Chem Biol. 2009, 13:245-55), Gill and Damle (Biopharmaceutical drug discovery using novel protein scaffolds. Curr Opin Biotechnol 2006, 17:653-658), Skerra (Engineered protein scaffolds for molecular recognition. J Mol Recognit 2000, 13:167-187), and Skerra (Alternative non-antibody scaffolds for molecular recognition. Curr Opin Biotechnol 2007, 18:295-304), and include without limitation affibodies, based on the Z-domain of staphylococcal protein A, a three- helix bundle of 58 residues providing an interface on two of its alpha-helices (Nygren, AlternativeAttorney Docket No. 44010.206WO-PCT / / CU24263 binding proteins: Affibody binding proteins developed from a small three-helix bundle scaffold. FEBS J 2008, 275:2668-2676); engineered Kunitz domains based on a small (ca.58 residues) and robust, disulphide-crosslinked serine protease inhibitor, typically of human origin (e.g. LACI-D1), which can be engineered for different protease specificities (Nixon and Wood, Engineered protein inhibitors of proteases. Curr Opin Drug Discov Dev 2006, 9:261-268); monobodies or adnectins based on the 10th extracellular domain of human fibronectin III (10Fn3), which adopts an Ig-like beta-sandwich fold (94 residues) with 2–3 exposed loops, but lacks the central disulphide bridge (Koide and Koide, Monobodies: antibody mimics based on the scaffold of the fibronectin type III domain. Methods Mol Biol 2007, 352:95-109); anticalins derived from the lipocalins, a diverse family of eight-stranded beta-barrel proteins (ca. 180 residues) that naturally form binding sites for small ligands by means of four structurally variable loops at the open end, which are abundant in humans, insects, and many other organisms (Skerra, Alternative binding proteins: Anticalins— harnessing the structural plasticity of the lipocalin ligand pocket to engineer novel binding activities. FEBS J 2008, 275:2677-2683); DARPins, designed ankyrin repeat domains (166 residues), which provide a rigid interface arising from typically three repeated beta-turns (Stumpp et al., DARPins: a new generation of protein therapeutics. Drug Discov Today 2008, 13:695-701); avimers (multimerized LDLR-A module) (Silverman et al., Multivalent avimer proteins evolved by exon shuffling of a family of human receptor domains. Nat Biotechnol 2005, 23:1556-1561); and cysteine-rich knottin peptides (Kolmar, Alternative binding proteins: biological activity and therapeutic potential of cystine-knot miniproteins. FEBS J 2008, 275:2684-2690).

[0111] As used herein, the term “monoclonal antibody” refers to an antibody derived from a clonal population of antibody-producing cells (e.g., B lymphocytes or B cells) which is homogeneous in structure and antigen specificity. The term “polyclonal antibody” refers to a plurality of antibodies originating from different clonal populations of antibody-producing cells which are heterogeneous in their structure and epitope specificity but which recognize a common antigen. Monoclonal and polyclonal antibodies may exist within bodily fluids, as crude preparations, or may be purified, as described herein.

[0112] The term “binding portion” of an antibody (or “antibody portion”) includes one or more complete domains, e.g., a pair of complete domains, as well as fragments of an antibody that retain the ability to specifically bind to a target molecule. It has been shown that the binding function ofAttorney Docket No. 44010.206WO-PCT / / CU24263 an antibody can be performed by fragments of a full-length antibody. Binding fragments are produced by recombinant DNA techniques, or by enzymatic or chemical cleavage of intact immunoglobulins. Binding fragments include Fab, Fab', F(ab')2, Fabc, Fd, dAb, Fv, single chains, single-chain antibodies, e.g., scFv, and single domain antibodies.

[0113] “Humanized” forms of non-human (e.g., murine) antibodies are chimeric antibodies that contain minimal sequence derived from non-human immunoglobulin. For the most part, humanized antibodies are human immunoglobulins (recipient antibody) in which residues from a hypervariable region of the recipient are replaced by residues from a hypervariable region of a non-human species (donor antibody) such as mouse, rat, rabbit or nonhuman primate having the desired specificity, affinity, and capacity. In some instances, FR residues of the human immunoglobulin are replaced by corresponding non-human residues. Furthermore, humanized antibodies may comprise residues that are not found in the recipient antibody or in the donor antibody. These modifications are made to further refine antibody performance. In general, the humanized antibody will comprise substantially all of at least one, and typically two, variable domains, in which all or substantially all of the hypervariable regions correspond to those of a non- human immunoglobulin and all or substantially all of the FR regions are those of a human immunoglobulin sequence. The humanized antibody optionally also will comprise at least a portion of an immunoglobulin constant region (Fc), typically that of a human immunoglobulin.

[0114] Examples of portions of antibodies or epitope-binding proteins encompassed by the present definition include: (i) the Fab fragment, having VL, CL, VHand CH1 domains; (ii) the Fab' fragment, which is a Fab fragment having one or more cysteine residues at the C-terminus of the CH1 domain; (iii) the Fd fragment having VH and CH1 domains; (iv) the Fd' fragment having VH and CH1 domains and one or more cysteine residues at the C-terminus of the CHI domain; (v) the Fv fragment having the VLand VHdomains of a single arm of an antibody; (vi) the dAb fragment (Ward et al., 341 Nature 544 (1989)) which consists of a VH domain or a VL domain that binds antigen; (vii) isolated CDR regions or isolated CDR regions presented in a functional framework; (viii) F(ab')2fragments which are bivalent fragments including two Fab' fragments linked by a disulphide bridge at the hinge region; (ix) single chain antibody molecules (e.g., single chain Fv; scFv) (Bird et al., 242 Science 423 (1988); and Huston et al., 85 PNAS 5879 (1988)); (x) “diabodies” with two antigen binding sites, comprising a heavy chain variable domain (VH)Attorney Docket No. 44010.206WO-PCT / / CU24263 connected to a light chain variable domain (VL) in the same polypeptide chain (see, e.g., EP 404,097; WO 93 / 11161; Hollinger et al., 90 PNAS 6444 (1993)); (xi) “linear antibodies” comprising a pair of tandem Fd segments (VH-Ch1-VH-Ch1) which, together with complementary light chain polypeptides, form a pair of antigen binding regions (Zapata et al., Protein Eng. 8(10):1057-62 (1995); and U.S. Patent No. 5,641,870).

[0115] The antibodies as defined for the present invention include derivatives that are modified, i.e., by the covalent attachment of any type of molecule to the antibody such that covalent attachment does not prevent the antibody from generating an anti-idiotypic response. For example, but not by way of limitation, the antibody derivatives include antibodies that have been modified, e.g., by glycosylation, acetylation, pegylation, phosphylation, amidation, derivatization by known protecting / blocking groups, proteolytic cleavage, linkage to a cellular ligand or other protein, etc. Any of numerous chemical modifications may be carried out by known techniques, including, but not limited to specific chemical cleavage, acetylation, formylation, metabolic synthesis of tunicamycin, etc. Additionally, the derivative may contain one or more non-classical amino acids. Bi-specific abs

[0116] In example embodiments, the one or more therapeutic agents can be bi-specific antigen- binding constructs, e.g., bi-specific antibodies (bsAb) or BiTEs, that bind two antigens (see, e.g., Suurs et al., A review of bispecific antibodies and antibody constructs in oncology and clinical challenges. Pharmacol Ther.2019 Sep;201:103-119; and Huehls, et al., Bispecific T cell engagers for cancer immunotherapy. Immunol Cell Biol. 2015 Mar; 93(3): 290–296). In example embodiments, bi-specific antibodies specific for targeting an FcRn inhibitor to macrophages are used. Antibody Drug Conjugates

[0117] In example embodiments, the one or more therapeutic agents can be an antibody-drug- conjugate that targets an FcRn inhibitor to macrophages. The term “antibody-drug-conjugate” or “ADC” refers to a binding protein, such as an antibody or antigen binding fragment thereof, chemically linked to one or more agents that inhibit FcRn. In a preferred embodiment, an ADC includes an antibody and a linker that enables attachment or conjugation of the agent to the antibody.Attorney Docket No. 44010.206WO-PCT / / CU24263 Aptamers

[0118] Nucleic acid aptamers are nucleic acid species that have been engineered through repeated rounds of in vitro selection or equivalently, SELEX (systematic evolution of ligands by exponential enrichment) to bind to various molecular targets such as small molecules, proteins, nucleic acids, cells, tissues and organisms. Nucleic acid aptamers have specific binding affinity to molecules through interactions other than classic Watson-Crick base pairing. Aptamers are useful in biotechnological and therapeutic applications as they offer molecular recognition properties similar to antibodies. In addition to their discriminate recognition, aptamers offer advantages over antibodies as they can be engineered completely in a test tube, are readily produced by chemical synthesis, possess desirable storage properties, and elicit little or no immunogenicity in therapeutic applications. In certain embodiments, RNA aptamers may be expressed from a DNA construct. In other embodiments, a nucleic acid aptamer may be linked to another polynucleotide sequence. The polynucleotide sequence may be a double stranded DNA polynucleotide sequence. The aptamer may be covalently linked to one strand of the polynucleotide sequence. The aptamer may be ligated to the polynucleotide sequence. The polynucleotide sequence may be configured, such that the polynucleotide sequence may be linked to a solid support or ligated to another polynucleotide sequence.

[0119] Aptamers, like peptides generated by phage display or monoclonal antibodies (“mAbs”), are capable of specifically binding to selected targets and modulating the target's activity, e.g., through binding, aptamers may block their target's ability to function. A typical aptamer is 10-15 kDa in size (30-45 nucleotides), binds its target with sub-nanomolar affinity, and discriminates against closely related targets (e.g., aptamers will typically not bind other proteins from the same gene family). Structural studies have shown that aptamers are capable of using the same types of binding interactions (e.g., hydrogen bonding, electrostatic complementarity, hydrophobic contacts, steric exclusion) that drives affinity and specificity in antibody-antigen complexes.

[0120] Aptamers have a number of desirable characteristics for use in research and as therapeutics and diagnostics including high specificity and affinity, biological efficacy, and excellent pharmacokinetic properties. In addition, they offer specific competitive advantages over antibodies and other protein biologics. Aptamers are chemically synthesized and are readily scaledAttorney Docket No. 44010.206WO-PCT / / CU24263 as needed to meet production demand for research, diagnostic or therapeutic applications. Aptamers are chemically robust. They are intrinsically adapted to regain activity following exposure to factors such as heat and denaturants and can be stored for extended periods (>1 yr) at room temperature as lyophilized powders. Not being bound by a theory, aptamers bound to a solid support or beads may be stored for extended periods.

[0121] Oligonucleotides in their phosphodiester form may be quickly degraded by intracellular and extracellular enzymes such as endonucleases and exonucleases. Aptamers can include modified nucleotides conferring improved characteristics on the ligand, such as improved in vivo stability or improved delivery characteristics. Examples of such modifications include chemical substitutions at the ribose and / or phosphate and / or base positions. SELEX identified nucleic acid ligands containing modified nucleotides are described, e.g., in U.S. Pat. No. 5,660,985, which describes oligonucleotides containing nucleotide derivatives chemically modified at the 2' position of ribose, 5 position of pyrimidines, and 8 position of purines, U.S. Pat. No. 5,756,703 which describes oligonucleotides containing various 2' -modified pyrimidines, and U.S. Pat. No. 5,580,737 which describes highly specific nucleic acid ligands containing one or more nucleotides modified with 2'-amino (2'-NH2), 2'-fluoro (2'-F), and / or 2'-0-methyl (2'-OMe) substituents. Modifications of aptamers may also include modifications at exocyclic amines, substitution of 4- thiouridine, substitution of 5-bromo or 5-iodo-uracil; backbone modifications, phosphorothioate or allyl phosphate modifications, methylations, and unusual base-pairing combinations such as the isobases isocytidine and isoguanosine. Modifications can also include 3' and 5' modifications such as capping. As used herein, the term phosphorothioate encompasses one or more non-bridging oxygen atoms in a phosphodiester bond replaced by one or more sulfur atoms. In further embodiments, the oligonucleotides comprise modified sugar groups, for example, one or more of the hydroxyl groups is replaced with halogen, aliphatic groups, or functionalized as ethers or amines. In one embodiment, the 2'-position of the furanose residue is substituted by any of an O- methyl, O-alkyl, O-allyl, S-alkyl, S-allyl, or halo group. Methods of synthesis of 2'-modified sugars are described, e.g., in Sproat, et al., Nucl. Acid Res.19:733-738 (1991); Cotten, et al, Nucl. Acid Res. 19:2629-2635 (1991); and Hobbs, et al, Biochemistry 12:5138-5145 (1973). Other modifications are known to one of ordinary skill in the art. In certain embodiments, aptamers include aptamers with improved off-rates as described in International Patent Publication No. WOAttorney Docket No. 44010.206WO-PCT / / CU24263 2009012418, “Method for generating aptamers with improved off-rates,” incorporated herein by reference in its entirety. In certain embodiments aptamers are chosen from a library of aptamers. Such libraries include, but are not limited to those described in Rohloff et al., “Nucleic Acid Ligands With Protein-like Side Chains: Modified Aptamers and Their Use as Diagnostic and Therapeutic Agents,” Molecular Therapy Nucleic Acids (2014) 3, e201. Aptamers are also commercially available (see, e.g., SomaLogic, Inc., Boulder, Colorado). In certain embodiments,the present invention may utilize any aptamer containing any modification as described herein.RNAi and antisense oligonucleotides (ASO)

[0122] In example embodiments, FcRn is targeted with RNAi or antisense oligonucleotides (ASO). As used herein, “gene silencing” or “gene silenced” in reference to an activity of an RNAi molecule, for example a siRNA or miRNA refers to a decrease in the mRNA level in a cell for a target gene by at least about 5%, about 10%, about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, about 80%, about 90%, about 95%, about 99%, about 100% of the mRNA level found in the cell without the presence of the miRNA or RNA interference molecule. In one preferred embodiment, the mRNA levels are decreased by at least about 70%, about 80%, about 90%, about 95%, about 99%, about 100%. Additionally, inhibitory nucleic acid molecules such as RNAi and ASOs can be used in vivo (see, e.g., Yan Y, Liu XY, Lu A, Wang XY, Jiang LX, Wang JC. Non-viral vectors for RNA delivery. J Control Release. 2022;342:241-279).

[0123] As used herein, the term “RNAi” refers to any type of interfering RNA, including but not limited to, siRNAi, shRNAi, endogenous microRNA and artificial microRNA. For instance, it includes sequences previously identified as siRNA, regardless of the mechanism of down-stream processing of the RNA (i.e. although siRNAs are believed to have a specific method of in vivo processing resulting in the cleavage of mRNA, such sequences can be incorporated into the vectors in the context of the flanking sequences described herein). The term “RNAi” can include both gene silencing RNAi molecules, and also RNAi effector molecules which activate the expression of a gene.

[0124] As used herein, a “siRNA” refers to a nucleic acid that forms a double stranded RNA, which double stranded RNA has the ability to reduce or inhibit expression of a gene or target gene when the siRNA is present or expressed in the same cell as the target gene. The double stranded RNA siRNA can be formed by the complementary strands. In one embodiment, a siRNA refers toAttorney Docket No. 44010.206WO-PCT / / CU24263 a nucleic acid that can form a double stranded siRNA. The sequence of the siRNA can correspond to the full-length target gene, or a subsequence thereof. Typically, the siRNA is at least about 15- 50 nucleotides in length (e.g., each complementary sequence of the double stranded siRNA is about 15-50 nucleotides in length, and the double stranded siRNA is about 15-50 base pairs in length, preferably about 19-30 base nucleotides, preferably about 20-25 nucleotides in length, e.g., 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, or 30 nucleotides in length).

[0125] As used herein “shRNA” or “small hairpin RNA” (also called stem loop) is a type of siRNA. In one embodiment, these shRNAs are composed of a short, e.g., about 19 to about 25 nucleotide, antisense strand, followed by a nucleotide loop of about 5 to about 9 nucleotides, and the analogous sense strand. Alternatively, the sense strand can precede the nucleotide loop structure and the antisense strand can follow.

[0126] The terms “microRNA” or “miRNA” are used interchangeably herein are endogenous RNAs, some of which are known to regulate the expression of protein-coding genes at the posttranscriptional level. Endogenous microRNAs are small RNAs naturally present in the genome that are capable of modulating the productive utilization of mRNA. The term artificial microRNA includes any type of RNA sequence, other than endogenous microRNA, which is capable of modulating the productive utilization of mRNA. MicroRNA sequences have been described in publications such as Lim, et al., Genes & Development, 17, p.991 - 1008 (2003), Lim et al Science 299, 1540 (2003), Lee and Ambros Science, 294, 862 (2001), Lau et al., Science 294, 858-861 (2001), Lagos-Quintana et al, Current Biology, 12, 735-739 (2002), Lagos-Quintana et al, Science 294, 853- 857 (2001), and Lagos-Quintana et al, RNA, 9, 175- 179 (2003), which are incorporated herein by reference. Multiple microRNAs can also be incorporated into a precursor molecule. Furthermore, miRNA-like stem-loops can be expressed in cells as a vehicle to deliver artificial miRNAs and short interfering RNAs (siRNAs) for the purpose of modulating the expression of endogenous genes through the miRNA and or RNAi pathways.

[0127] As used herein, “double stranded RNA” or “dsRNA” refers to RNA molecules that are comprised of two strands. Double-stranded molecules include those comprised of a single RNA molecule that doubles back on itself to form a two-stranded structure. For example, the stem loop structure of the progenitor molecules from which the single-stranded miRNA is derived, called the pre-miRNA (Bartel et al. 2004. Cell 116:281 -297), comprises a dsRNA molecule.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0128] Antisense therapy is a form of treatment that uses antisense oligonucleotides (ASOs) to target messenger RNA (mRNA). ASOs are capable of altering mRNA expression through a variety of mechanisms, including ribonuclease H mediated decay of the pre-mRNA, direct steric blockage, and exon content modulation through splicing site binding on pre-mRNA (see, e.g., Crooke ST, Liang XH, Baker BF, Crooke RM. Antisense technology: A review. J Biol Chem. 2021;296:100416. doi:10.1016 / j.jbc.2021.100416). Antisense oligonucleotides (ASO) generally inhibit their target by binding target mRNA and sterically blocking expression by obstructing the ribosome. ASOs can also inhibit their target by binding target mRNA thus forming a DNA-RNA hybrid that can be a substance for RNase H. Commonly used antisense mechanisms to degrade target RNAs include RNase H1-dependent and RISC-dependent mechanisms. Preferred ASOs include Locked Nucleic Acid (LNA), Peptide Nucleic Acid (PNA), and morpholinos. Small Molecules

[0129] In example embodiments, the one or more agents is a small molecule. The term “small molecule” refers to compounds, preferably organic compounds, with a size comparable to those organic molecules generally used in pharmaceuticals. The term excludes biological macromolecules (e.g., proteins, peptides, nucleic acids, etc.). Preferred small organic molecules range in size up to about 5000 Da, e.g., up to about 4000, preferably up to 3000 Da, more preferably up to 2000 Da, even more preferably up to about 1000 Da, e.g., up to about 900, 800, 700, 600 or up to about 500 Da. In example embodiments, the small molecule may act as an antagonist (e.g., blocking a receptor by binding to a ligand binding site).

[0130] One type of small molecule applicable to the present invention is a degrader molecule (see, e.g., Ding, et al., Emerging New Concepts of Degrader Technologies, Trends Pharmacol Sci. 2020 Jul;41(7):464-474). The terms “degrader” and “degrader molecule” refer to all compounds capable of specifically targeting a protein for degradation (e.g., ATTEC, AUTAC, LYTAC, or PROTAC, reviewed in Ding, et al. 2020). Proteolysis Targeting Chimera (PROTAC) technology is a rapidly emerging alternative therapeutic strategy with the potential to address many of the challenges currently faced in modern drug development programs. PROTAC technology employs small molecules that recruit target proteins for ubiquitination and removal by the proteasome (see, e.g., Zhou et al., Discovery of a Small-Molecule Degrader of Bromodomain and Extra- Terminal (BET) Proteins with Picomolar Cellular Potencies and Capable of Achieving Tumor Regression.Attorney Docket No. 44010.206WO-PCT / / CU24263 J. Med. Chem. 2018, 61, 462−481; Bondeson and Crews, Targeted Protein Degradation by Small Molecules, Annu Rev Pharmacol Toxicol. 2017 Jan 6; 57: 107–123; and Lai et al., Modular PROTAC Design for the Degradation of Oncogenic BCR-ABL Angew Chem Int Ed Engl. 2016 Jan 11; 55(2): 807–810). In example embodiments, LYTACs are particularly advantageous for cell surface proteins as described herein (e.g., FcRn). CRISPR-Cas

[0131] In example embodiments, FcRn is inhibited using a CRISPR-Cas system. CRISPR-Cas systems comprise a Cas polypeptide and a guide sequence, wherein the guide sequence is capable of forming a CRISPR-Cas complex with the Cas polypeptide and directing site-specific binding of the CRISPR-Cas sequence to a target sequence in one or more of the target genes. Additionally, CRISPR systems can be used in vivo (see, e.g., Chen H, Shi M, Gilam A, et al. Hemophilia A ameliorated in mice by CRISPR-based in vivo genome editing of human Factor VIII. Sci Rep. 2019;9(1):16838; Hana S, Peterson M, McLaughlin H, et al. Highly efficient neuronal gene knockout in vivo by CRISPR-Cas9 via neonatal intracerebroventricular injection of AAV in mice. Gene Ther.2021;28(10-11):646-658; and Rosenblum D, Gutkin A, Kedmi R, et al. CRISPR-Cas9 genome editing using targeted lipid nanoparticles for cancer therapy. Sci Adv. 2020;6(47):eabc9450).

[0132] In general, a CRISPR-Cas or CRISPR system as used in herein and in documents, such as International Patent Publication No. WO 2014 / 093622 (PCT / US2013 / 074667), refers collectively to transcripts and other elements involved in the expression of or directing the activity of CRISPR-associated (“Cas”) genes, including sequences encoding a Cas gene, a tracr (trans- activating CRISPR) sequence (e.g. tracrRNA or an active partial tracrRNA), a tracr-mate sequence (encompassing a “direct repeat” and a tracrRNA-processed partial direct repeat in the context of an endogenous CRISPR system), a guide sequence (also referred to as a “spacer” in the context of an endogenous CRISPR system), or “RNA(s)” as that term is herein used (e.g., RNA(s) to guide Cas, such as Cas9, e.g. CRISPR RNA and transactivating (tracr) RNA or a single guide RNA (sgRNA) (chimeric RNA)) or other sequences and transcripts from a CRISPR locus. In general, a CRISPR system is characterized by elements that promote the formation of a CRISPR complex at the site of a target sequence (also referred to as a protospacer in the context of an endogenous CRISPR system). See, e.g., Shmakov et al. (2015) “Discovery and Functional Characterization ofAttorney Docket No. 44010.206WO-PCT / / CU24263 Diverse Class 2 CRISPR-Cas Systems”, Molecular Cell, DOI: dx.doi.org / 10.1016 / j.molcel.2015.10.008.

[0133] In example embodiments, a gRNA is made up of two parts: crispr RNA (crRNA), a 17- 20 nucleotide sequence complementary to the target DNA (also referred to as a “spacer” in the context of an endogenous CRISPR system), and a tracr RNA, which serves as a binding scaffold for the Cas nuclease. In example embodiments, a sgRNA is composed of four different components named as target sequence (crRNA sequence or spacer), crRNA repeat sequence, tetra loop sequence and tracrRNA sequence and has six secondary structural modules (spacer, lower stem, bulge, upper stem, nexus, and hairpins). The loop sequence joins the crRNA and tracRNA.

[0134] CRISPR-Cas systems can generally fall into two classes based on their architectures of their effector molecules, which are each further subdivided by type and subtype. The two class are Class 1 and Class 2. Class 1 CRISPR-Cas systems have effector modules composed of multiple Cas proteins, some of which form crRNA-binding complexes, while Class 2 CRISPR-Cas systems include a single, multi-domain crRNA-binding protein.

[0135] In some embodiments, the CRISPR-Cas system that can be used to modify a polynucleotide of the present invention described herein can be a Class 1 CRISPR-Cas system. In some embodiments, the CRISPR-Cas system that can be used to modify a polynucleotide of the present invention described herein can be a Class 2 CRISPR-Cas system. Class 2 CRISPR-Cas Systems

[0136] The compositions, systems, and methods described in greater detail elsewhere herein can be designed and adapted for use with Class 2 CRISPR-Cas systems. Thus, in some embodiments, the CRISPR-Cas system is a Class 2 CRISPR-Cas system. Class 2 systems are distinguished from Class 1 systems in that they have a single, large, multi-domain effector protein. In certain example embodiments, the Class 2 system can be a Type II, Type V, or Type VI system, which are described in Makarova et al. “Evolutionary classification of CRISPR-Cas systems: a burst of class 2 and derived variants” Nature Reviews Microbiology, 18:67-81 (Feb 2020), incorporated herein by reference. Each type of Class 2 system is further divided into subtypes. See Makarova et al. 2020, particularly at FIG. 2. Class 2, Type II systems can be divided into 4 subtypes: II-A, II-B, II-C1, and II-C2. Class 2, Type V systems can be divided into 17 subtypes: V-A, V-B1, V-B2, V-C, V-D, V-E, V-F1, V-F1(V-U3), V-F2, V-F3, V-G, V-H, V-I, V-K (V-U5),Attorney Docket No. 44010.206WO-PCT / / CU24263 V-U1, V-U2, and V-U4. Class 2, Type IV systems can be divided into 5 subtypes: VI-A, VI-B1, VI-B2, VI-C, and VI-D.

[0137] The distinguishing feature of these types is that their effector complexes consist of a single, large, multi-domain protein. Type VI (Cas13) are unrelated to the effectors of Type II and V systems and contain two HEPN domains and target RNA. Cas13 proteins also display collateral activity that is triggered by target recognition.

[0138] In some embodiments the Class 2 system is a Type VI system. In some embodiments, the Type VI CRISPR-Cas system is a VI-A CRISPR-Cas system. In some embodiments, the Type VI CRISPR-Cas system is a VI-B1 CRISPR-Cas system. In some embodiments, the Type VI CRISPR-Cas system is a VI-B2 CRISPR-Cas system. In some embodiments, the Type VI CRISPR-Cas system is a VI-C CRISPR-Cas system. In some embodiments, the Type VI CRISPR- Cas system is a VI-D CRISPR-Cas system. In some embodiments, the Type VI CRISPR-Cas system includes a Cas13a (C2c2), Cas13b (Group 29 / 30), Cas13c, and / or Cas13d. RNA Base Editing

[0139] In one example embodiment, FcRn mRNA is edited by administering an RNA base editing system to decrease expression of FcRn. In one example embodiment, a catalytically inactive Cas protein is connected or fused to a nucleotide deaminase. As used herein, “base editing” refers generally to the process of polynucleotide modification via a CRISPR-Cas-based or Cas-based system that does not include excising nucleotides to make the modification. Base editing can convert base pairs at precise locations without generating excess undesired editing byproducts that can be made using traditional CRISPR-Cas systems. Accordingly, in one example embodiment, the base editing system edits the target gene to reduce or eliminate its expression.

[0140] In one example embodiment, the base editing system may be an RNA base editing system. A nucleotide deaminase capable of converting nucleotide bases may be fused to a Cas protein. However, in these embodiments, the Cas protein will need to be capable of binding RNA. Example RNA binding Cas proteins include, but are not limited to, RNA-binding Cas9s such as Francisella novicida Cas9 (“FnCas9”), and Class 2 Type VI Cas systems. The nucleotide deaminase may be a cytidine deaminase or an adenosine deaminase, or an adenosine deaminase engineered to have cytidine deaminase activity. In certain example embodiments, the RNA base editor may be used to delete or introduce a post-translation modification site in the expressedAttorney Docket No. 44010.206WO-PCT / / CU24263 mRNA. In contrast to DNA base editors, whose edits are permanent in the modified cell, RNA base editors can provide edits where finer, temporal control may be needed, for example in modulating a particular immune response. Example Type VI RNA-base editing systems are described in Cox et al. 2017. Science 358: 1019-1027, International Patent Publication Nos. WO 2019 / 005884, WO 2019 / 005886, and WO 2019 / 071048, and International Patent Application Nos. PCT / US20018 / 05179 and PCT / US2018 / 067207, which are incorporated herein by reference. An example FnCas9 system that may be adapted for RNA base editing purposes is described in International Patent Publication No. WO 2016 / 106236, which is incorporated herein by reference. Example RNA Base Editing Modifications to Decrease Expression of FcRn

[0141] RNA base editors enable targeted RNA editing without modifying the underlying DNA sequence and may be useful where more temporal control of gene expression is desired. In one embodiment, an RNA base editing system is used to introduce one or more base edits to one or more RNA molecules transcribed from one or more genes. such that expression or activity of the gene product is reduced. In one embodiment, the one or more base edits introduce a frame-shift mutation leading to introduction of a premature stop code resulting in production of a truncated protein or triggering NMD, both which lead to decreased gene expression. In another embodiment, the one or more base edits introduce splice sites or splice regulatory elements that lead to aberrant splicing and production of non-functional proteins or mRNA that is degraded through NMD, thereby decreasing gene expression. In one embodiment, the one or more base edits target specific functional domains of the gene product encoded within the mRNA that impair the function of the gene product. While this approach may not directly decrease translation of the mRNA, it leads to the production of non-functional gene product or gene products with decreased function, effectively achieving a loss-of-function effect. In one embodiment, the one or more base edits modify regulatory elements within the mRNA. Some mRNAs have regulatory elements that can affect gene expression, such as upstream reading frames (uORFs) or IRESs and disrupting these elements may reduce gene expression. In one embodiment, the one or more base edits target translation initiation or elongation by introducing mutations in the mRNA’s 5’ untranslated (5’UTR), 3’ untranslated region (3’UTR), or within the coding sequence, affecting translation initiation or elongation and resulting in decreased production of a gene product.Attorney Docket No. 44010.206WO-PCT / / CU24263 METHODS OF DETERMINING BIOLOGICAL AGE

[0142] In example embodiments, IgG level is a measure of biological age. In example embodiments, any method capable of detecting or measuring IgG can be used. In example embodiments, the plasma IgG level correlates to the IgG level in any tissue. (e.g., white adipose tissue levels). In example embodiments, IgG accumulates in every tissue during aging.

[0143] In example embodiments, IgG levels can be used to determine an increase or decrease in health in a subject by comparing IgG levels at one or more time points. For example, IgG levels can be detected at an initial time point before initiating a treatment program (e.g., diet, exercise, sleep, medication) and IgG levels can be detected at one or more time points after the treatment program. In example embodiments, IgG levels over time can be detected in a subject not being treated. For example, to detect an IgG level trend over time in a subject. For example, a graph plotting IgG levels over time can be generated. Methods of detection Immunoassays

[0144] In example embodiments, IgG levels are detected by an immunoassay. Immunoassay methods are based on the reaction of an antibody to its corresponding target or analyte and can detect the analyte in a sample depending on the specific assay format. To improve specificity and sensitivity of an assay method based on immunoreactivity, monoclonal antibodies are often used because of their specific epitope recognition. Polyclonal antibodies have also been successfully used in various immunoassays because of their increased affinity for the target as compared to monoclonal antibodies. Immunoassays have been designed for use with a wide range of biological sample matrices. Immunoassay formats have been designed to provide qualitative, semi- quantitative, and quantitative results.

[0145] Quantitative results may be generated through the use of a standard curve created with known concentrations of the specific analyte to be detected. The response or signal from an unknown sample is plotted onto the standard curve, and a quantity or value corresponding to the target in the unknown sample is established.

[0146] Numerous immunoassay formats have been designed. enzyme-linked immunosorbent assay (ELISA) or EIA can be quantitative for the detection of an analyte / biomarker. This method relies on attachment of a label to either the analyte or the antibody and the label componentAttorney Docket No. 44010.206WO-PCT / / CU24263 includes, either directly or indirectly, an enzyme. ELISA tests may be formatted for direct, indirect, competitive, or sandwich detection of the analyte. Other methods rely on labels such as, for example, radioisotopes (I125) or fluorescence. Additional techniques include, for example, agglutination, nephelometry, turbidimetry, Western blot, immunoprecipitation, immunocytochemistry, immunohistochemistry, flow cytometry, Luminex assay, and others (see ImmunoAssay: A Practical Guide, edited by Brian Law, published by Taylor & Francis, Ltd., 2005 edition).

[0147] Exemplary assay formats include enzyme-linked immunosorbent assay (ELISA), radioimmunoassay, fluorescent, chemiluminescence, and fluorescence resonance energy transfer (FRET) or time resolved-FRET (TR-FRET) immunoassays. Examples of procedures for detecting IgG include immunoprecipitation followed by quantitative methods that allow size and peptide level discrimination, such as gel electrophoresis, capillary electrophoresis, planar electrochromatography, and the like.

[0148] Methods of detecting and / or quantifying a detectable label or signal generating material depend on the nature of the label. The products of reactions catalyzed by appropriate enzymes (where the detectable label is an enzyme; see above) can be, without limitation, fluorescent, luminescent, or radioactive or they may absorb visible or ultraviolet light. Examples of detectors suitable for detecting such detectable labels include, without limitation, x-ray film, radioactivity counters, scintillation counters, spectrophotometers, colorimeters, fluorometers, luminometers, and densitometers.

[0149] Any of the methods for detection can be performed in any format that allows for any suitable preparation, processing, and analysis of the reactions. This can be, for example, in multi- well assay plates (e.g., 96 wells or 384 wells) or using any suitable array or microarray. Stock solutions for various agents can be made manually or robotically, and all subsequent pipetting, diluting, mixing, distribution, washing, incubating, sample readout, data collection and analysis can be done robotically using commercially available analysis software, robotics, and detection instrumentation capable of detecting a detectable label. MS methods

[0150] IgG detection may also be evaluated using mass spectrometry methods. A variety of configurations of mass spectrometers can be used to detect IgG values. Several types of massAttorney Docket No. 44010.206WO-PCT / / CU24263 spectrometers are available or can be produced with various configurations. In general, a mass spectrometer has the following major components: a sample inlet, an ion source, a mass analyzer, a detector, a vacuum system, and instrument-control system, and a data system. Difference in the sample inlet, ion source, and mass analyzer generally define the type of instrument and its capabilities. For example, an inlet can be a capillary-column liquid chromatography source or can be a direct probe or stage such as used in matrix-assisted laser desorption. Common ion sources are, for example, electrospray, including nanospray and microspray or matrix-assisted laser desorption. Common mass analyzers include a quadrupole mass filter, ion trap mass analyzer and time-of-flight mass analyzer. Additional mass spectrometry methods are well known in the art (see Burlingame et al., Anal. Chem. 70:647 R-716R (1998); Kinter and Sherman, New York (2000)).

[0151] Protein biomarkers and biomarker values can be detected and measured by any of the following: electrospray ionization mass spectrometry (ESI-MS), ESI-MS / MS, ESI-MS / (MS)n, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), surface-enhanced laser desorption / ionization time-of-flight mass spectrometry (SELDI-TOF-MS), desorption / ionization on silicon (DIOS), secondary ion mass spectrometry (SIMS), quadrupole time-of-flight (Q-TOF), tandem time-of-flight (TOF / TOF) technology, called ultraflex III TOF / TOF, atmospheric pressure chemical ionization mass spectrometry (APCI-MS), APCI- MS / MS, APCI-(MS).sup.N, atmospheric pressure photoionization mass spectrometry (APPI-MS), APPI-MS / MS, and APPI-(MS).sup.N, quadrupole mass spectrometry, Fourier transform mass spectrometry (FTMS), quantitative mass spectrometry, and ion trap mass spectrometry.

[0152] Sample preparation strategies are used to label and enrich samples before mass spectroscopic characterization of protein biomarkers and determination biomarker values. Labeling methods include but are not limited to isobaric tag for relative and absolute quantitation (iTRAQ) and stable isotope labeling with amino acids in cell culture (SILAC). Capture reagents used to selectively enrich samples for candidate biomarker proteins prior to mass spectroscopic analysis include but are not limited to aptamers, antibodies, nucleic acid probes, chimeras, small molecules, an F(ab')2fragment, a single chain antibody fragment, an Fv fragment, a single chain Fv fragment, a nucleic acid, a lectin, a ligand-binding receptor, affybodies, nanobodies, ankyrins, domain antibodies, alternative antibody scaffolds (e.g. diabodies etc.) imprinted polymers,Attorney Docket No. 44010.206WO-PCT / / CU24263 avimers, peptidomimetics, peptoids, peptide nucleic acids, threose nucleic acid, a hormone receptor, a cytokine receptor, and synthetic receptors, and modifications and fragments of these.

[0153] Further embodiments are illustrated in the following Examples which are given for illustrative purposes only and are not intended to limit the scope of the invention. EXAMPLES Example 1 – IgG is an aging factor that drives adipose tissue fibrosis and metabolic decline IgG is an age-associated factor

[0154] The most significant age-related transcriptomic changes in mice occur in the epididymal WAT (eWAT).19However, there are possible discrepancies in gene expression caused by loss of proteostasis in aging.26To better understand the age-associated pathologic remodeling of adipose tissue, Applicants performed a quantitative proteomic comparison of eWAT from young (3 months old) and aged (33 months old) mice. Of the 1,110 proteins identified in the 50 kDa gel slice region that displayed the most noticeable difference according to Coomassie blue staining, there were 93 proteins within the size range between 35 and 60 kDa showing over 2-fold enrichments in aging, and 45 of them were Ig proteins (FIGS. 1A and 1B; Table 1). Applicants first confirmed this accumulation by immunohistochemistry staining of the dominant Ig component IgG in the aged eWAT (FIG. 1C). The accumulation of IgG in eWAT is age- associated, becoming noticeable at 6 months old and increasing further at 18 months old (FIGS. 1D and 8A). Plasma IgG increased in parallel during aging in both male and female mice (FIGS. 1D and 8A–8C). Indeed, IgG accumulated across all examined tissues in aging, including subcutaneous inguinal WAT (iWAT), interscapular brown adipose tissue (BAT), liver, and kidney (FIG. 8D), but the highest accumulation was in WAT (FIGS. 1E, 8E, and 8F). The accumulated IgG proteins in aged eWAT consisted of all major subtypes, including IgG1, IgG2a, and IgG3, together with Ig isotypes IgM and IgA, suggesting polyclonal responses (FIG.8G). Although IgM and IgA increased in aging, unlike IgG, IgM is too large to diffuse into intercellular tissue fluid efficiently, and IgA is predominantly found in external secretions such as breast milk. Therefore, Applicants focused on IgG in the context of adipose tissue. To learn the timing of IgG accumulation, Applicants examined tissues at earlier ages and found that IgG started to accumulate in WAT at 4 months old, whereas only minimal levels were detected in the liver and muscle atAttorney Docket No. 44010.206WO-PCT / / CU24263 even 9 months old (FIG. 8H). Furthermore, this aging-associated accumulation of IgG was recapitulated in humans by western blotting (WB) analysis of human epicardial fat biopsies (FIG. 1F). The IgG levels correlate with age but inversely correlate with the expression of adipocyte functional markers Pparg1, Pparg2, and Leptin (FIGS. 1G and 8I), implicating a detrimental effect.

[0155] Transcriptomic analyses of eWAT during aging indicate that the primary biological processes (BPs) that increase with age are immune pathways, particularly those involved in B cell development and activation, Ig production, and inflammatory responses (FIGS. 1H and 9A). On the other hand, BPs that progressively decrease with age are tightly associated with energy metabolism and adipocyte differentiation (FIGS. 1H and 9B). These results collectively indicate an inverse association of IgG levels with adipose tissue function in aging. Table 1. Mass Spectrometry identified 93 Enriched proteins around 50 kD in aged eWAT, related to FIG. 1. MS / MS MS / MS Mol. count count w i ht S n LFQ int n it LFQ int n it Y n A d ioAttorney Docket No. 44010.206WO-PCT / / CU24263 Nuclear factor 1;Nuclear factor 1 X-type Nfix 43.594 391 0 35532000 0 3 n / a Pre-mRNA-splicing 06 93 24 26 19 08 85 73 41 35 72 82 67 61 46 32 95 84 76 74 68 65 64 56 44Attorney Docket No. 44010.206WO-PCT / / CU24263 Lactadherin Mfge8 47.169 426 226700000 1004100000 4 14 4.43 Igh 53.018 487 26119000 115080000 0 1 4.41 Igh;Ighg1;HC 51.975 469 2608800000 10482000000 15 15 4.02 97 79 72 67 63 43 42 36 27 11 99 86 83 83 77 72 67 60 47 38 35 29 28 27 21 21 20 20 19 15 13Attorney Docket No. 44010.206WO-PCT / / CU24263 Nucleus accumbens- associated protein 1 Nacc1 56.536 514 76044000 161330000 1 0 2.12 Fibrinogen beta 11 08 07 05 02 02

[0156] CR is a common and effective anti-aging intervention.27In 12-month-old C57BL / 6J male mice, 4 weeks of CR improved insulin sensitivity (FIG. 10A) and selectively decreased circulating IgG levels (by 60%) without affecting IgA or IgM levels (FIGS. 2A and 2B). CR specifically decreased IgG accumulation in eWAT, iWAT, and liver (FIGS. 2C, 2D, and 10B). This reduction in IgG in eWAT was associated with the upregulation of SirT1 and adipogenic genes (Pparg, Cebpa, and Srebf1), as well as repression of inflammation (Mcp1, Tnfa, and Il-6), and senescence markers (p16, p21, and p53) (FIGS. 2E and 10C). These results reinforce IgG’s inverse correlation with adipose tissue function and further suggest that IgG accumulation can be interdicted.

[0157] To assess any role of IgG in CR’s metabolic effects, Applicants administered mouse total IgG via intraperitoneal (i.p.) injection to CR mice (5 months old) to replenish IgG. Interestingly, the exogenous IgG predominantly accumulated in adipose tissues (eWAT and iWAT), compared with plasma and liver (FIGS. 2F, 10D, and 10E). This elevated IgG restored the CR-suppressed inflammatory markers F4 / 80, Mcp1, and Tnfa and senescence genes p19, p21, and p53 in eWAT (FIG. 2G). Moreover, IgG treatment attenuated the CR-induced expression of adipogenic genes Pparg and Srebf1, accompanied by repression of Adipoq (FIG. 2G). Importantly, the insulin tolerance test (ITT) revealed that IgG treatment counteracted the potent insulin sensitizing function of CR without affecting body weight (FIGS.2H and 10F). These data provide direct evidence of a pathogenic role of IgG in adipose tissue function and metabolic health.Attorney Docket No. 44010.206WO-PCT / / CU24263 IgG promotes adipose tissue fibrosis in aging

[0158] Applicants further asked how IgG triggers adipose tissue degeneration in aging. Fibrosis is increasingly appreciated as a driving force for compromised adipocyte regeneration, insulin resistance, inflammation, and metabolic dysfunction in obesity.28In aged mice, adipose tissue develops significant fibrosis (FIG. 3A) that coincides with the accumulation of IgG and infiltration of macrophages (FIG.3B). The most prominent signaling pathway that triggers fibrosis is transforming growth factor b (TGF-β)-mediated phosphorylation of suppressor of mothers against decapentaplegic 2 / 3 (SMAD2 / 3) (FIG. 3C).29Supportively, SMAD2 / 3 phosphorylation was markedly induced in the eWAT of aged mice (FIG. 3D). Conversely, CR prevalently suppressed fibrogenic genes and Tgfb in eWAT (FIG.11A), accompanied by inhibited SMAD2 / 3 phosphorylation (FIG. 11B). The correlations of adipose IgG and fibrosis in both aging and CR prompted Applicants to test a fibrotic role of IgG in adipose tissue. To this end, Applicants administered 3 mg mouse total IgG to young mice weekly to mimic its accumulation in aging. 4 weeks of IgG treatment was sufficient to increase phosphorylation of SMAD2 and SMAD3 (FIG. 3E) and stimulate fibrotic gene expression in eWAT, including Timp1, Mmp9, Col1a1, and Lgals3 together with Tgfb genes (FIG.3F). As such, IgG is uncovered as a causal factor of adipose tissue fibrosis in aging. IgG activates macrophages to stimulate the fibrotic response

[0159] To understand this surprising fibrotic function of IgG, Applicants first tested its direct effect on adipocyte progenitor cells but failed to activate the SMAD2 / 3 pathway (FIG. 11C) or induce fibrotic genes in 3T3-L1 preadipocytes (FIG.11D), implying an indirect mechanism. RNA sequencing (RNA-seq) analysis of eWAT from vehicle- or IgG-treated young mice revealed the top-upregulated BPs in IgG-treated eWAT was the immune response (FIG. 3G), as demonstrated by a 4.5-fold enrichment of differentially expressed genes (DEGs) within inflammatory pathways compared with the background (FIG. 11E). IgG is known to neutralize pathogens and induce inflammatory responses through targeting immune cells. Given the correlations of IgG and macrophages in WAT, Applicants reasoned that macrophages might be the mediator of IgG. Indeed, IgG treatment directly activated bone marrow-derived monocytes (BMDMs) as demonstrated by the enriched BPs in inflammatory and metabolic responses from transcriptomic analyses (FIG. 3H). IgG treatment potently activated inflammatory markers and simultaneouslyAttorney Docket No. 44010.206WO-PCT / / CU24263 induced Tgfb genes (FIGS.3I and 11F). Macrophages are appreciated as a major source of TGF- β.30For functional test, Applicants treated 3T3- L1 preadipocytes with conditioned media (CM) from vehicle- or IgG-treated BMDMs. The representative fibrotic genes Sma, Timp1, Mmp9, Col3a1, and Lgals3 in 3T3-L1 cells were substantially induced by CM from IgG-treated BMDMs, largely mimicking TGF-β treatment; such effects are TGF-β-dependent as they were abrogated by TGF-β receptor (TGF-βR) inhibitor LY2109761 (FIG.3J). Supportively, CM collected from IgG treated BMDMs increased SMAD2 and SMAD3 phosphorylation in 3T3-L1 cells, which was blunted by the addition of LY2109761 (FIG. 3K).

[0160] Next, Applicants sought to understand the activation of macrophages by IgG. The mitogen-activated protein kinase / extracellular signal-regulated kinases (MEK / ERK) pathway is crucial for the pro-inflammatory activation of macrophages.31The Toll-like receptor 4 (TLR4) ligand lipopolysaccharide (LPS) activated phosphorylation of MEK / ERK, while the anti- inflammatory activation by interleukin-4 (IL-4) blunted this effect (FIG. 3L). Here, Applicants found that IgG treatment functioned similarly as LPS to induce MEK / ERK phosphorylation (FIG. 3L). Consistently, ERK1 / ERK2 pathway was among the top-induced BPs by IgG treatment in eWAT and BMDMs (FIGS. 3G and 3H). The classic MEK / ERK activation is mediated through the upstream Ras signaling and eventually converges with the TLR4 pathway (FIG. 11G).32Interestingly, IgG induced 4-fold Ras activation in BMDMs, in contrast to the more immediate effect of LPS (FIG. 3M). Ras activation by IgG is likely mediated by its receptors FcgRs. Upon binding with IgG, FcgR clustering induces the activation of Src / Syk kinases, which triggers Ras activity (FIG.11G).33,34Lastly, IgG treatment directly increased the amount of secreted TGF-β in the CM from BMDMs, while boiled IgG lost this effect (FIG. 3N), indicating that native IgG is required to activate TGF-β production. Moreover, inhibition of ERK also abolished IgG’s effect (FIG. 3N). Collectively, these data suggest that IgG activates macrophages through the Ras / MEK / ERK signaling pathway, stimulating TGF-β production to induce fibrogenesis in the adipose tissue microenvironment. B cell null mice are protected from aging-associated adipose tissue fibrosis

[0161] To determine whether IgG is required for the aging-associated development of adipose tissue fibrosis, Applicants employed B cell null (Bnull) mice, which are deprived of IgG together with IgA and IgM.3524-month-old Bnullmice developed much less fibrosis in eWAT than theAttorney Docket No. 44010.206WO-PCT / / CU24263 control mice (FIGS.4A and 4B) and showed improved insulin sensitivity (FIG.4C). The reduced fibrosis was further confirmed by their decreased expression of fibrogenic genes, including Timp1, Col1a1, Mmp9, and Tgfb3 (FIG.4D). As expected, with the depletion of IgG, phosphorylation of SMAD2 / 3 was diminished in the BnulleWAT (FIG. 4E). In line with the stimulation of adipose tissue inflammation by IgG administration, Bnullmice showed alleviated immune cell infiltration (F4 / 80 and Cd11c) and inflammation (Tnfa, Il6, Mcp1, and Il1b) in eWAT (FIG.4F). On the other hand, macrophage anti-inflammatory genes Arg1 and Fizz1 were upregulated (FIG. 4F). To directly assess any causal role of IgG in metabolic dysregulation in aged conditions, Applicants administered mouse total IgG for 4 weeks to aged Bnullmice to replenish the circulating IgG. The 4-week IgG treatment offset the insulin-sensitizing effect in aged Bnullmice (FIG. 4G). Consistently, the fibrotic genes (Timp1, Lgals3, Mmp9, Col1a1, and Tgfb1) and inflammatory markers (Ccl2, F4 / 80, Il1b, and iNos) were upregulated in the eWAT (FIG. 4H). With the elevation of IgG in the eWAT of aged Bnullmice, phosphorylation of SMAD2 and SMAD3 was also elevated, accompanied by increased macrophage infiltration as indicated by the strong induction of F4 / 80 (FIG. 4I). Hence, B cells are involved in the development of adipose tissue fibrosis along with inflammation in aging, likely mediated through its main product—IgG. Abolishing IgG recycling in macrophages prevents adipose tissue fibrosis in aging

[0162] The lack of mature B cells in Bnullmice leads to immunodeficiency in producing Ig isotypes (IgG, IgA, and IgM) and B cell-derived cytokines. To isolate the role of IgG, Applicants devised a strategy to specifically manipulate IgG levels without compromising its production. Previous studies show that IgG recycling has a greater impact on determining IgG levels than production by B cells.36As the sole recycling receptor of IgG (FIG. 5A), FcRn is abundantly expressed in myeloid cells and is reported to be critical for maintaining circulating IgG levels.37,38Applicants observed efficient internalization of IgG in macrophages (FIG. 12A). Together with the stimulation of macrophage activation and infiltration into WAT by IgG, Applicants hypothesized that FcRn-mediated IgG recycling in macrophages is involved in IgG accumulation during aging. To test this, Applicants generated Fcgrt floxed mice (FIGS. 12B and 12C) and crossed them with a LyzM-Cre line to specifically knockout Fcgrt (encoding FcRn) in myeloid cells (FcRn mKO) (FIG. 5B). Though FcRn is still expressed in other cell types in adipose tissue (FIG. 12D), the half-life of circulating IgG was reduced by 80% in FcRn mKO mice (FIGS. 5CAttorney Docket No. 44010.206WO-PCT / / CU24263 and 12E). As they aged, FcRn mKO mice modestly decreased IgG levels in the circulation, while the levels of IgA and IgM were unaffected (FIG.12F). FcRn also recycles albumin, but Applicants observed a marginal decrease in the plasma albumin levels in the knockout animals (FIG. 12F). Importantly, age-associated tissue IgG accumulation was prevented in mKO mice, especially adipose tissue (FIGS. 5D and 12G). Therefore, Applicants conclude that IgG recycling by FcRn in macrophages is required for its age-associated accumulation.

[0163] Given the specific inhibition of IgG accumulation, this model allows Applicants to dissect the effects of IgG on adipose tissue function. FcRn mKO mice were strongly protected from adipose tissue fibrosis at 15 months of age (FIGS. 5E and 5F), and the phosphorylation of SMAD2 and SMAD3 in their eWAT was potently reduced (FIG.5G). Consistently, the expression of fibrotic genes showed a broad decrease in the eWAT of aged mKO mice, in line with reduced expression of Tgfb2 and Tgfb3 (FIG. 5H). Another hallmark of adipose tissue in aging is chronic inflammation. Preventing IgG accumulation resulted in the overall downregulation of inflammation and immune cell markers in aged mKO eWAT (FIG. 5I). Adipocyte hypertrophy signifies adipose tissue inflammation and insulin resistance and is closely related to metabolic dysfunction.22In line with their reduced fibrosis and inflammation, mKO mice showed alleviated adipocyte hypertrophy (FIGS. 5J and 5K). Therefore, preventing IgG accumulation retains adipose tissue health in aging. mKO mice extend the healthspan and lifespan

[0164] Adipose tissue IgG accumulation is not significant until approximately 6 months of age. Applicants hereby detected negligible effects on body weight, glucose tolerance, and insulin sensitivity in 5-month-old mKO mice (FIGS.6A–6C). However, at 12 months of age, mKO mice started to weigh less than controls (FIG.6A). The age-associated declines in glucose homeostasis and insulin sensitivity were prevented in mKO mice (FIGS. 6D and 6E), accompanied by alleviated dyslipidemia (FIGS. 13A and 13B). Aging mKO mice better preserved their energy expenditure (EE), as indicated by their increased oxygen consumption (FIG. 6F) and higher EE despite higher food intake compared with their age-matched controls (FIGS.13C and 13D). Their respiration exchange ratio (RER) was also higher, reinforcing higher carbohydrate consumption (FIG.13E). This increased EE was not explained by locomotor activity (FIG.13F). Instead, their eWAT showed a phenotype of brown remodeling with the increased expression of lipolytic genesAttorney Docket No. 44010.206WO-PCT / / CU24263 (Lpl and Hsl) and lipid utilization genes (Ucp1, Cox7a1, Cox8b, and Acadm) (FIG. 6G). Moreover, aging is associated with the decline in BAT function, characterized by lipid filling,39,40whereas this whitening phenotypic conversion was inhibited in mKO mice (FIG. 13G), as indicated by their upregulation of catabolic genes and glucose uptake gene Glut4 but downregulation of Fabp4, which encodes lipid droplet-binding protein aP2 (FIG. 13H). As such, at the age of 15 months old, when metabolic decline is normally well underway, mKO mice are resistant to these changes, pointing to prolonged healthspan.

[0165] Metabolic dysfunction will contribute to the development of complications in aging and ultimately shorten lifespan. Applicants, therefore, investigated whether the delayed metabolic decline in mKO mice will benefit lifespan. After tracing these mice for over 3 years, Applicants observed a 12% increase in median survival time in the mKO mice compared with the control group (FIG. 6H). Therefore, inhibiting IgG accumulation in aging prolongs both healthspan and lifespan in mice. Targeting IgG recycling rejuvenates metabolic health in aging

[0166] From a therapeutic perspective, Applicants designed an antisense oligonucleotide (ASO) against Fcgrt to rectify IgG accumulation in aging. Applicants treated 70-week-old C57BL / 6J male mice with control or FcRn ASO by i.p. injection twice weekly for up to 8 weeks (FIG. 7A). FcRn ASO treatment efficiently knocked down FcRn in eWAT and other peripheral tissues (FIGS. 7B and 14A), resulting in decreased IgG levels in the plasma, WATs, BAT, and liver, and all major subtypes of IgG contributed to the decrease (FIGS. 7C, 7D, 14B, and 14C). The FcRn knockdown (KD) mice did not gain weight like their controls over the treated period, owing to their higher oxygen consumption and EE revealed by indirect calorimetry (FIGS. 7E, 7F, and 14D). Similar to the mKO mice, FcRn KD increased food intake and RER without affecting locomotor activity (FIGS. 14E–14G). Consistently, FcRn KD mice improved glucose tolerance and insulin sensitivity (FIGS. 7G and 7H). By contrast, KD FcRn in young (7 weeks old) mice, which have basal levels of IgG, had minimal effects on reducing IgG and, consequently, body weight, glucose tolerance, and insulin sensitivity (FIGS. 14I–14L), supporting an IgG- dependent improvement. Therefore, targeting IgG recycling receptor FcRn rejuvenates metabolic functions in aging.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0167] FcRn KD reduced the weight of eWAT (64% reduction) and iWAT (33%) depots in aged mice (FIG.7I) and mitigated their adipocyte hypertrophy (FIGS.7J and 14H), accompanied by the restored adipogenic gene expression (Pparg2, Fasn, Scd1, Adipoq, and Adipsin) (FIG.7K). In line with their increased EE, the KD mice showed increased expression of brown remodeling markers, e.g., Ucp1, Cidea, Cox8b, and SirT1,41and downregulation of the white adipocyte- enriched gene Lep in eWAT (FIG. 7K). Moreover, BAT whitening was alleviated (FIG. 14H). Importantly, FcRn KD repressed the expression of fibrogenic and Tgfb genes (FIG.7L), supported by inhibited phosphorylation of SMAD2 and SMAD3 in the eWAT (FIG. 7M). Collectively, targeting IgG recycling to inhibit IgG accumulation improves adipose tissue remodeling and rejuvenates metabolism in aging. Discussion

[0168] This study unveils for the first time that IgG is an aging factor, and its abnormal accumulation impairs metabolic health. Unlike its canonical immune-defensive function, IgG activates macrophage inflammatory response and prompts the TGF-β / SMAD pathway to induce adipose tissue fibrosis. This hitherto unrecognized pathogenic function of IgG connects multiple hallmarks of adipose tissue dysfunction, including chronic inflammation, fibrosis, impaired adipogenesis, adipocyte hypertrophy, and decreased catabolic activity, eventually leading to the loss of physiological integrity of adipose tissue in aging. The data further reveal that FcRn- mediated IgG recycling in macrophages is required for IgG accretion in aging; thereby, intervening in this recycling process conveys therapeutic potential in rejuvenating metabolic health.

[0169] IgG is primarily considered a circulating factor, while its intratissue homeostasis is rarely appreciated. Though Applicants observed correlations of IgG levels between tissues and circulation, adipose tissue IgG is more responsive to aging than plasma IgG. At the same level of circulating IgG, IgG accumulates faster and to a greater degree in adipose tissue compared with other tissues in aging, highlighting a specific regulation of IgG in adipose tissue. This could be related to efficient macrophage recycling and infiltration into adipose tissue under metabolic stress. Recent studies have also demonstrated age-related B cell infiltration into adipose tissue.42These resident B cells likely contribute to the robust accumulation of IgG in adipose tissue during aging; the accumulated IgG will then worsen inflammation, fibrosis, and macrophage infiltration to self- accelerate this process. Moreover, FcRn also recycles albumin; however, Applicants did notAttorney Docket No. 44010.206WO-PCT / / CU24263 observe significant changes in albumin levels in either the mKO or FcRn ASO mouse model. Even if there is any possible detriment of marginal albumin decrease, it unlikely offsets the dominant metabolic improvements from abrogating IgG accumulation.

[0170] The function of IgG in adipose tissue pathological remodeling is actually supported by clues from previous studies. Bnullmice are protected from insulin resistance in diet-induced obesity.35,43,44IgG2c, a pro-inflammatory isotype, was taken as a marker of adipose inflammation in diet-induced obesity.35The infiltrated B cells in obese adipose tissue are believed to interact with macrophages and T cells to induce adipose inflammation and cause insulin resistance and glucose intolerance through IgG-independent mechanisms.35,43,44Interestingly, antibody production, the housekeeping function of B cells, was not counted, probably due to the traditional view of Igs as primarily plasma-relevant. In fact, the increased IgG in the circulation was noticed in older humans45as well as in aging mice46for decades, but the tissue accumulation remained not examined. The finding of IgG as a pathogenic factor in adipose remodeling reveals a highly abundant, direct mediator of adipose-infiltrated B cells to impair metabolic function in aging. Although future investigations are warranted to determine whether the accumulated IgG is accounted for by autoantibodies or not, IgG stands out as a unique factor to connect macrophages, adipocyte progenitor cells, adipocytes, and B cells—the major cell types that determine adipose health. The classic view of IgG as a circulating immune-defensive factor might be oversimplified in the context of adipose degeneration and the consequent metabolic dysfunction.

[0171] Here, Applicants primarily focused on fibrosis to delineate the pathogenic role of IgG in adipose tissue aging. Interestingly, the metabolic improvements in aged mKO mice are quite similar to those of Smad3- / -mice undergoing a high-fat diet, including antiobesity, improved insulin sensitivity and glucose tolerance, increased EE, and browning remodeling of WAT.47Given the pronounced fibrogenic function of IgG and the driving role of fibrosis in adipose tissue degeneration, it is conceivable that this fibrotic pathway is among the major contributors to IgG’s detriments in adipose tissue. In addition, IgG is able to directly activate the inflammatory response of macrophages. These two parallel pathways will mutually aggravate each other to worsen adipose tissue derangement. However, it is not exclusive of other possible pathways that work in synchronization to execute IgG’s pathogenic function in aging, such as dampening BAT’s function.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0172] By identifying IgG as a causal factor of metabolic dysfunction in aging, this work highlights the potential of inhibiting IgG accumulation as a novel therapeutic strategy to tackle age-associated metabolic decline. Various FcRn inhibitors have been developed for IgG engineering or for treating autoimmune diseases in the forms of antibodies,48,49IgG mutants,38and small peptides.50These FcRn inhibitors could be repurposed to improve metabolic conditions and aging; however, the treatment should be carefully optimized as it may increase the risk of infection with uncontrolled IgG depletion. Limitations of the study

[0173] Applicants are cognizant of several limitations of this study. First, Applicants demonstrate preferential accumulation of IgG in adipose tissue during aging; however, Applicants do not yet fully understand this preference. It may involve multiple processes in IgG homeostasis besides macrophage recycling, such as antigen presence, B cell infiltration and activation in adipose tissue, decreased clearance of IgG immune complexes, etc. Second, adipose tissue is unlikely the only effector tissue of IgG. Given the prevalent accumulation of IgG across tissues during aging, though at lower levels, IgG may target multiple cell types in different tissues to execute its pro-aging effects. Third, despite the prolonged lifespan of FcRn mKO mice, here, Applicants mainly investigate the physiological development of metabolic dysfunction during aging, which starts in middle age. It is envisioned that the further accretion of IgG in the advanced aging stage will contribute to aging-associated complications, such as cancer, dementia, and fragility. A systemic characterization of FcRn mKO mice in old age (e.g., >2 years old) will help to establish the full spectrum pro-aging effects of IgG. Last but not least, the discovery of IgG as an aging factor will invite caution of antibody immunotherapy. However, current studies on potential long-term effects of IgG on metabolism, particularly in human tissues and cells, are very limited.

[0174] MethodsAttorney Docket No. 44010.206WO-PCT / / CU24263

[0176] Key Resources TableAttorney Docket No. 44010.206WO-PCT / / CU24263Attorney Docket No. 44010.206WO-PCT / / CU24263

[0177] Data and code availability. The RNA-seq data have been deposited to the NGDC (ngdc.cncb.ac.cn / ) (PRJCA002140 & PRJCA020637) and are publicly available at the date of publication. Experimental Model and Study Participant Details

[0178] Mice. All mice were on C57BL / 6J background and maintained under standard laboratory conditions with ad libitum access to water and standard chow diet (except CR mice, PicoLab rodent diet 20, 5053). Mice were housed on a 12-hr light / 12-hr dark cycle with lights on at 07:00 and off at 19:00. All animal experiments were performed in accordance with NIH guidelines for Animal Care and Use, approved and overseen by Columbia University Institutional Animal Care and Use Committee (IACUC).

[0179] Body composition was determined by EchoMRI. For glucose tolerance tests (GTT), mice were fasted overnight for 16 h (17:00– 09:00) and intraperitoneally injected with glucose at a dose of 2 g / kg,BW. Blood glucose levels were measured at basal state (0 min) and subsequently at 15, 30, 60, 90, and 120 min after injection. Insulin tolerance tests (ITT) were performed after a 4-hr (09:00–13:00) fast with intraperitoneal injection of human insulin (0.75 U / kg,BW). Blood glucose levels were measured via tail vein bleeding using a OneTouch glucometer. Plasma insulin concentrations were determined with Mouse Insulin ELISA Kit (Mercodia, USA). Infinity Triglyceride Reagent (Thermo Scientific) and NEFA-HR (Fujifilm Wako) were used to measure plasma triglyceride and NEFA levels, respectively.

[0180] Indirect calorimetry analyses were performed using the Comprehensive Laboratory Animal Monitoring System (CLAMS) equipped with an Oxymax Open Circuit Calorimeter System (Columbus Instruments). The following parameters of individual mice were monitored: food intake, O2 consumption (VO2), CO2 production (VCO2), heat, and locomotion. Mouse energy metabolism was analyzed according to the ANCOVA flowchart.51

[0181] For aging studies with ASO treatment, 70-wk-old mice were used. Fcgrt (5’- GATGATACATCAGTGG-3’) (SEQ ID NO: 2) and control (5’-GGCCAAT ACGCCGTCA-3’) (SEQ ID NO: 3) ASOs were injected intraperitoneally twice a week at a dose of 50 mg / kg,body weight (BW) into aged (70-weekold) and young (6-week-old) mice. Prior to sacrifice, mice were fasted overnight for 16 h and then refed for 4 h.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0182] Mice were perfused with phosphate-buffered saline (PBS) for 5 min to clear the blood trace in tissues at sacrifice. Tissues were fixed in 10% formalin (in PBS) at 4 C overnight for histological analyses or frozen for molecular analyses.

[0183] Calorie restriction treatment. Wildtype C57BL / 6J male mice at indicated ages were randomly assigned into ad libitum fed and CR groups. All mice were single housed, and CR mice were fed 70% of the ad libitum food intake, consisting of one 2.6–2.8 g meal / day. Mice were monitored, including but not limited to body weight, GTT, ITT, etc.

[0184] IgG treatment of mice. Commercially purified mouse total IgG (>95%, ProteinMods and Cusabio) was dissolved in PBS. Male mice were administered with 3 mg IgG or vehicle (Veh) intraperitoneally per week. The selection of a 3 mg IgG dosage was based on its ability to elicit notable IgG accumulation in adipose tissue, akin to the levels observed in aging mice. This dosage resembles the cumulative endogenous IgG quantity present in the plasma of young adult mice (approximately 1.7 mg / mL in a plasma volume of around 2 mL), enabling Applicants to mimic the amount of IgG in the plasma under physiological conditions.

[0185] Human tissues. Frozen heart tissues were obtained from the National Disease Research Interchange (NDRI). 5 cm x 5 cm left ventricle tissues were collected from normal human donors within 12 h post-death and kept frozen at -80 C. The detailed age (sex) information is as follows: 24 (m), 37 (m), 41 (m), 47 (m), 71 (f), 80 (m), 82 (f), 100 (f). Method Details

[0186] Generation of Fcgrt conditional knockout mice. Fcgrt floxed mice were generated at the Columbia University Transgenic Mouse Shared Resource Core by flanking exons 2 and 3 of the Fcgrt gene (which contain the ATG start codon and first 325 nt of coding sequence). The strategy allows the deletion of the entire FcRn protein. A Loxp-Neo-Loxp (LNL) cassette was inserted in the intron upstream of exon 2 of the Fcgrt gene in a Bacterial Artificial Chromosome (BAC clone ID: RP23-476N22). The Neo cassette was removed by Cre recombinase, leaving behind one loxp site (L83). An Frt-Neo-Frt-Loxp (FNFL) cassette was inserted in the intron downstream of the Fcgrt exon 3. A gene targeting vector was constructed by retrieving the 2 kb short-homology arm (5’ to L83), the L83-FNFL cassette, and the 5 kb long-homology arm (end of FNFL cassette to 3’) into the pMCS-DTA vector carrying a DTA (Diphtheria Toxin Alpha chain) negative selection marker. The FNFL cassette confers G418 resistance during gene targeting inAttorney Docket No. 44010.206WO-PCT / / CU24263 KV1 (129B6 hybrid) ES cells, and the DTA cassette provides an autonomous negative selection to reduce random integration events during gene targeting. Several positive targeted ES cell clones were identified and karyotyped. One of the targeted ES cell clones (2F2) was injected into C57BL / 6J blastocysts to generate chimeric mice. Male chimeras were bred to homozygous ACTB (Flpe / Flpe) females on C57BL / 6J background (Jackson Laboratory 005703) to transmit the floxed Fcgrt allele. The Fcgrtflox / +mice were backcrossed to C57BL / 6J mice for 6 generations and then bred with LyzM-Cre mice (Jackson Laboratory 004781 on C57BL / 6J background) to conditionally knock out Fcgrt in macrophages. Applicants genotyped the Fcgrt floxed allele using the following primer pair: forward: 5’-GGTGTCTTGGTATTGGGAGAAG-3’ (SEQ ID NO: 4) and reverse: 5’- AGTC CAATTGCCGATTCTTG-3’ (SEQ ID NO: 5). The amplicon from the floxed allele band is 598 bp, and the wildtype allele is 452 bp.

[0187] IgG half-life determination. 200 µg of biotin-labeled mouse IgG (ProteinMods) was injected intraperitoneally into 15-mon-old FcRn mKO and age-matched control mice. Plasma was collected via tail vein bleeding at 3 h (as baseline) and at 1, 3, 7, 14, and 21 days after injection. Diluted plasma was resolved by SDS-PAGE and transferred to a PVDF membrane. The biotin signal was determined with goat anti-biotin HRP (Vector Laboratories Cat. No. SP-3010-1). Blots were quantified and normalized to the 3 h signal.

[0188] RNA extraction and qPCR analysis. RNA was extracted from tissues or cells using the IBI Tri-isolate total RNA kit (IBI Scientific). 1 µg total RNA was used to synthesize cDNA using the High-capacity cDNA Reverse Transcription kit (Applied Biosystems). A Bio-Rad CFX96 Real-Time PCR system with GoTaq qPCR Master Mix (Promega and Azura) was used to perform quantitative real-time PCR (qPCR). Applicants calculated relative gene expression levels using the DDCt method, and Rpl23 or cyclophilin A was used as the reference gene. QPCR primer sequences are available upon request.

[0189] RNA sequencing. RNA libraries for sequencing were prepared and sequenced by the professional services offered at Novogene, incorporating thorough examination of RNA quality and libraries through the Agilent 2100 platform. Subsequently, RNA libraries were multiplexed and sequenced utilizing the Illumina NovaSeq 6000 platform. Quality assurance was ensured by utilizing FastQC (v0.11.9) for the RNA-seq data.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0190] Gene set enrichment analysis. To assess functional changes of eWAT during aging, Applicants analyzed the RNA-seq dataset (NGDC: PRJCA002140; ngdc.cncb. ac.cn / bioproject / browse / PRJCA002140) of wildtype C57BL / 6J mouse eWAT at the ages of 8, 26, 60, 78, and 104 weeks to identify gene expression changes.19Applicants performed GSEA of BPs based on the gene rank of expression change for each pairwise comparison. Applicants retained only BP with FDR < 0.05 in at least one comparison for downstream analysis. To identify upregulated or downregulated BPs during aging, Applicants calculated the correlation between normalized enrichment score (NES) and age for each BP. Applicants defined the BP with aging correlation > 0.95 in addition to NES of 104 weeks vs 8 weeks > 0 and NES of 78 weeks vs. 8 weeks > 0 as upregulated BP during aging. The downregulated BPs during aging were defined as BP with aging correlation < -0.7 in addition to NES of 104 weeks vs. 8 weeks < 0 and NES of 78 weeks vs. 8 weeks < 0.

[0191] RNA sequencing analyses were performed in the eWAT and BMDMs with and without IgG treatment. The RNA-seq data were deposited at the Genome Sequence Archive (GSA, ngdc.cncb.ac.cn / gsa / ) database with the accession number PRJCA020637. The RNA-seq data was processed and analyzed as previously described.52Briefly, the sequencing data was mapped to the mouse genome (GRCm39) using STAR (v2.7.7a) and calculated the read counts for each gene across the samples using featureCounts (v2.0.1). Gene expression was analyzed using edgeR. Normalization: Read counts were normalized across the samples using the Trimmed Mean of M- values (TMM) method. The normalized values were then converted to gene expression levels, represented as FPKM (fragments per kilobase per million). To prevent infinite values during log2FoldChange calculation, Applicants added 0.5 to each FPKM value. Differentially Expressed Genes (DEG) were identified based on the criteria of log2FoldChange > 0.75 and an adjusted p- value of < 0.1. Applicants showed the top 15 biological processes (BPs) in the results.

[0192] Cell culture. 3T3-L1 cells were grown in high glucose DMEM (Corning Cat. No: 10- 017) supplemented with 10% calf serum (CS, heat-inactivated, Gemini Bio-Products, Cat. No: 100506) and 1x Pen / Strep (Thermo Fisher). In the CM-treated assay, 3T3-L1 cells at >90% confluence were treated with the CM from BMDMs for 24 h and then harvested for RNA and protein analyses.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0193] Bone marrow-derived macrophages (BMDMs). Bone marrow cells were collected from the femur and tibia of 8-12 weeks old mice, and erythrocytes were removed by resuspending in 1 x red blood cell lysis buffer on ice. The remaining monocytes were cultured for 5-6 days in a petri dish in low glucose DMEM within 10% FBS and 1% penicillin-streptomycin supplemented with 10 ng / mL M-CSF. The cells were then seeded for macrophage activation in 12-well or 6-well plates for 24hr in the serum-free medium before stimulation by vehicle, indicated doses of IgG, 50 ng / mL LPS, or 50 ng / mL IL-4. IgG treatment was for 2 days. Conditioned media (CM) was collected from the 2ndday’s media to treat 3T3-L1 preadipocytes for 24 h. Cells were then harvested for RNA and WB analyses. For assessing IgG uptake, BMDMs were treated with 50 µg / mL IgG-Cy5.5 overnight in the serum-free medium.

[0194] Western blotting. Tissues or cultured cells were homogenized in protein lysis buffer (50 mM Tris-HCl pH 7.4, 180 mM NaCl, 1% Triton X-100, 10% glycerol, and 1 mM EDTA) supplemented with 0.5 mM PMSF, and protease and phosphatase inhibitor cocktails (Sigma- Aldrich) or using the IntactProtein Lysis kit (GenulN Biotech, USA). Protein concentration was determined using the Pierce BCA Protein Assay kit (Thermo Fisher Scientific). Protein extracts (25–50 µg) were resolved by SDS-PAGE, transferred onto PVDF membranes, blocked for 1 h with 5% skim milk in PBST, and incubated with primary antibodies overnight. For serum proteins, 1 µL plasma was diluted to 100 µL in protein lysis buffer, and 7–10 µL diluted plasma was subjected to SDS-PAGE. The antibodies used were anti-Hsp90 (Proteintech 13171-1-AP), anti- Sirt1 (Proteintech 13161-1-AP), anti-FcRn (Abcam 193148, Thermo Fisher Scientific PA5-79246, R&D AF6775), anti-IgG (Abcam 46540), anti-IgG1 (Bethyl A90-205P), anti-IgG2a (Bethyl A90- 107P), anti-IgG3 (Bethyl A90-211P), anti-IgA (Bethyl A90-103P), anti-IgM (Jackson ImmunoResearch Laboratories 115-035-075), anti-F4 / 80 (Cell Signaling 70076), p-Smad2 (Cell Signaling 18338), p-Smad3 (Cell Signaling 9520), and p-Smad3 (Abcam ab52903), Smad2 (Cell Signaling 5339), and Smad2 / 3 (Cell Signaling 8685). Membranes were incubated with HRP- conjugated secondary antibodies and visualized by enhanced chemiluminescence (Thermo Fisher Scientific). Equal loading was confirmed using anti-GAPDH or anti-HSP90 (Proteintech) and / or membrane staining. Mouse plasma and tissue total IgG were also detected directly using secondary mouse antibodies conjugated with HRP (Sigma-Aldrich A9044, GE NA931), both of which gave results consistent with rabbit anti-IgG (Abcam 46540) followed by anti-rabbit secondary antibody.Attorney Docket No. 44010.206WO-PCT / / CU24263 Human IgG was detected using goat-anti-human IgG HRP (Thermo Fisher Scientific 62-8420). Densitometric analyses of WB were performed using ImageJ and normalized to loading control.

[0195] Antibody and TGF-β ELISA. Plasma IgG levels were measured using the total IgG ELISA kit (Bethyl Laboratories E99-131). TGF-β in BMDM conditioned media was measured using the TGF-β1 ELISA kits (Proteintech KE10005).

[0196] Ras activation assay. BMDMs were treated with 100 ng / mL LPS or 200 µg / mL IgG for 1 h, and EGF was used as the positive control for activating Ras. Ras activity was determined using the Ras G-LISA Activation Assay Kit (Cytoskeleton, BK131).

[0197] Proteomic analysis of adipose tissue proteins. Adipose tissue was lysed in protein lysis buffer, and 30 µg of total protein was separated on 8% SDS-PAGE and stained with SimplyBlue (Thermo Fisher Scientific). Protein gel slices were excised, and in-gel digestion was performed. Mass spectrometry using a Thermo ScientificTM Orbitrap FusionTM TribridTM mass spectrometer was performed at Columbia Herbert Irving Comprehensive Cancer Center core facility.

[0198] Histology and immunostaining. Tissues were stained with hematoxylin and eosin (H&E). For the immunohistochemical staining of IgG, sections were incubated with anti-IgG (Abcam 46540) at a 1:500 dilution overnight. For the immunofluorescent staining of F4 / 80, FcRn, and SMA, sections were incubated with anti-IgG (Invitrogen A31570), anti-F4 / 80 (Invitrogen MA5-16624), anti-FcRn (abcam ab193148), and anti-SMA (Cell signaling D4K9N) at 1:100-200 dilution. Quantification of fluorescence signal co-localization based on Colorc 2 plugin in Fiji software.

[0199] Statistical analysis. Statistical analyses were performed using Prism 8.0 software (Graphpad). Applicants used the two-tailed Student’s t test for comparison between two groups and one-way ANOVA for comparisons among three or more groups. p < 0.05 was adopted to declare statistical significance. All data were presented as means ± SEM (standard error). Sample sizes are included in the figure legends. Example 1 References 1. Barzilai, N., Huffman, D.M., Muzumdar, R.H., and Bartke, A. (2012). The critical role of metabolic pathways in aging. Diabetes 61, 1315–1322.Attorney Docket No. 44010.206WO-PCT / / CU24263 2. Hildrum, B., Mykletun, A., Hole, T., Midthjell, K., and Dahl, A.A. (2007). Age-specific prevalence of the metabolic syndrome defined by the International Diabetes Federation and the National Cholesterol Education Program: the Norwegian HUNT 2 study. BMC Public Health 7, 220. 3. Grover, S.A., Kaouache, M., Rempel, P., Joseph, L., Dawes, M., Lau, D.C., and Lowensteyn, I. (2015). Years of life lost and healthy life-years lost from diabetes and cardiovascular disease in overweight and obese people: a modelling study. Lancet Diabetes Endocrinol. 3, 114–122. 4. Kenyon, C.J. (2010). The genetics of ageing. Nature 464, 504–512. 5. Junnila, R.K., List, E.O., Berryman, D.E., Murrey, J.W., and Kopchick, J.J. (2013). The GH / IGF-1 axis in ageing and longevity. Nat. Rev. Endocrinol. 9, 366–376. 6. van Heemst, D. (2010). Insulin, IGF-1 and longevity. Aging Dis. 1, 147–157. 7. Johnson, S.C., Rabinovitch, P.S., and Kaeberlein, M. (2013). mTOR is a key modulator of ageing and age-related disease. Nature 493, 338–345. 8. Lamming, D.W., Ye, L., Sabatini, D.M., and Baur, J.A. (2013). Rapalogs and mTOR inhibitors as anti-aging therapeutics. J. Clin. Invest. 123, 980–989. 9. Hall, J.A., Dominy, J.E., Lee, Y., and Puigserver, P. (2013). The sirtuin family’s role in aging and age-associated pathologies. J. Clin. Invest. 123, 973–979. 10. Merksamer, P.I., Liu, Y., He, W., Hirschey, M.D., Chen, D., and Verdin, E. (2013). The sirtuins, oxidative stress and aging: an emerging link. Aging (Albany, NY) 5, 144–150. 11. Burkewitz, K., Zhang, Y., and Mair, W.B. (2014). AMPK at the nexus of energetics and aging. Cell Metab. 20, 10–25. 12. Salminen, A., and Kaarniranta, K. (2012). AMP-activated protein kinase (AMPK) controls the aging process via an integrated signaling network. Ageing Res. Rev. 11, 230–241. 13. Palmer, A.K., and Kirkland, J.L. (2016). Aging and adipose tissue: potential interventions for diabetes and regenerative medicine. Exp. Gerontol. 86, 97–105. 14. Barzilai, N., and Gupta, G. (1999). Revisiting the role of fat mass in the life extension induced by caloric restriction. J. Gerontol. A Biol. Sci. Med. Sci. 54, B89–B96.Attorney Docket No. 44010.206WO-PCT / / CU24263 15. Harrison, D.E., Strong, R., Sharp, Z.D., Nelson, J.F., Astle, C.M., Flurkey, K., Nadon, N.L., Wilkinson, J.E., Frenkel, K., Carter, C.S., et al. (2009). Rapamycin fed late in life extends lifespan in genetically heterogeneous mice. Nature 460, 392–395. 16. Chang, G.R., Chiu, Y.S., Wu, Y.Y., Chen, W.Y., Liao, J.W., Chao, T.H., and Mao, F.C. (2009). Rapamycin protects against high fat diet-induced obesity in C57BL / 6J mice. J. Pharmacol. Sci. 109, 496–503. 17. Muzumdar, R., Allison, D.B., Huffman, D.M., Ma, X., Atzmon, G., Einstein, F.H., Fishman, S., Poduval, A.D., McVei, T., Keith, S.W., and Barzilai, N. (2008). Visceral adipose tissue modulates mammalian longevity. Aging Cell 7, 438–440. 18. Kirkland, J.L., and Tchkonia, T. (2017). Cellular Senescence: A Translational Perspective. EBioMedicine 21, 21–28. 19. Zhou, Q., Wan, Q., Jiang, Y., Liu, J., Qiang, L., and Sun, L. (2020). A Landscape of Murine Long Non-Coding RNAs Reveals the Leading Transcriptome Alterations in Adipose Tissue during Aging. Cell Rep. 31, 107694. 20. Tchkonia, T., Morbeck, D.E., Von Zglinicki, T., Van Deursen, J., Lustgarten, J., Scrable, H., Khosla, S., Jensen, M.D., and Kirkland, J.L. (2010). Fat tissue, aging, and cellular senescence. Aging Cell 9, 667–684. 21. Karagiannides, I., Tchkonia, T., Dobson, D.E., Steppan, C.M., Cummins, P., Chan, G., Salvatori, K., Hadzopoulou-Cladaras, M., and Kirkland, J.L. (2001). Altered expression of C / EBP family members results in decreased adipogenesis with aging. Am. J. Physiol. Regul. Integr. Comp. Physiol. 280, R1772–R1780. 22. Gustafson, B., Hammarstedt, A., Hedjazifar, S., and Smith, U. (2013). Restricted adipogenesis in hypertrophic obesity: the role of WISP2, WNT, and BMP4. Diabetes 62, 2997– 3004. 23. McHeyzer-Williams, L.J., Cool, M., and McHeyzer-Williams, M.G. (2000). Antigen- specific B cell memory: expression and replenishment of a novel b220(-) memory b cell compartment. J. Exp. Med. 191, 1149–1166. 24. Nimmerjahn, F., Gordan, S., and Lux, A. (2015). FcgammaR dependent mechanisms of cytotoxic, agonistic, and neutralizing antibody activities. Trends Immunol. 36, 325–336.Attorney Docket No. 44010.206WO-PCT / / CU24263 25. Roopenian, D.C., and Akilesh, S. (2007). FcRn: the neonatal Fc receptor comes of age. Nat. Rev. Immunol. 7, 715–725. 26. Hipp, M.S., Kasturi, P., and Hartl, F.U. (2019). The proteostasis network and its decline in ageing. Nat. Rev. Mol. Cell Biol. 20, 421–435. 27. Anderson, R.M., Shanmuganayagam, D., and Weindruch, R. (2009). Caloric restriction and aging: studies in mice and monkeys. Toxicol. Pathol. 37, 47–51. 28. Sun, K., Tordjman, J., Cle´ ment, K., and Scherer, P.E. (2013). Fibrosis and adipose tissue dysfunction. Cell Metab. 18, 470–477. 29. Derynck, R., and Zhang, Y.E. (2003). Smad-dependent and Smad-independent pathways in TGF-beta family signalling. Nature 425, 577–584. 30. Meng, X.-M., Nikolic-Paterson, D.J., and Lan, H.Y. (2016). TGF-β: the master regulator of fibrosis. Nat. Rev. Nephrol. 12, 325–338. 31. Rao, K.M. (2001). MAP kinase activation in macrophages. J. Leukoc. Biol. 69, 3–10. 32. McKay, M.M., and Morrison, D.K. (2007). Integrating signals from RTKs to ERK / MAPK. Oncogene 26, 3113–3121. 33. Zhang, J., Guo, J., Dzhagalov, I., and He, Y.-W. (2005). An essential function for the calcium-promoted Ras inactivator in Fcg receptor–mediated phagocytosis. Nat. Immunol.6, 911– 919. 34. Botelho, R.J., Harrison, R.E., Stone, J.C., Hancock, J.F., Philips, M.R., Jongstra-Bilen, J., Mason, D., Plumb, J., Gold, M.R., and Grinstein, S. (2009). Localized diacylglycerol-dependent stimulation of Ras and Rap1 during phagocytosis. J. Biol. Chem. 284, 28522–28532. 35. Winer, D.A., Winer, S., Shen, L., Wadia, P.P., Yantha, J., Paltser, G., Tsui, H., Wu, P., Davidson, M.G., Alonso, M.N., et al. (2011). B cells promote insulin resistance through modulation of T cells and production of pathogenic IgG antibodies. Nat. Med. 17, 610–617. 36. Kim, J., Hayton, W.L., Robinson, J.M., and Anderson, C.L. (2007). Kinetics of FcRn- mediated recycling of IgG and albumin in human: pathophysiology and therapeutic implications using a simplified mechanism-based model. Clin. Immunol. 122, 146–155. 37. Akilesh, S., Christianson, G.J., Roopenian, D.C., and Shaw, A.S. (2007). Neonatal FcR expression in bone marrow-derived cells functions to protect serum IgG from catabolism. J. Immunol. 179, 4580–4588.Attorney Docket No. 44010.206WO-PCT / / CU24263 38. Challa, D.K., Wang, X., Montoyo, H.P., Velmurugan, R., Ober, R.J., and Ward, E.S. (2019). Neonatal Fc receptor expression in macrophages is indispensable for IgG homeostasis. mAbs 11, 848–860. 39. Mancuso, P., and Bouchard, B. (2019). The Impact of Aging on Adipose Function and Adipokine Synthesis. Front. Endocrinol. 10, 137. 40. Cypess, A.M., Lehman, S., Williams, G., Tal, I., Rodman, D., Goldfine, A.B., Kuo, F.C., Palmer, E.L., Tseng, Y.H., Doria, A., et al. (2009). Identification and importance of brown adipose tissue in adult humans. N. Engl. J. Med. 360, 1509–1517. 41. Qiang, L., Wang, L., Kon, N., Zhao, W., Lee, S., Zhang, Y., Rosenbaum, M., Zhao, Y., Gu, W., Farmer, S.R., and Accili, D. (2012). Brown remodeling of white adipose tissue by SirT1- dependent deacetylation of Ppargamma. Cell 150, 620–632. 42. Camell, C.D., Günther, P., Lee, A., Goldberg, E.L., Spadaro, O., Youm, Y.H., Bartke, A., Hubbard, G.B., Ikeno, Y., Ruddle, N.H., et al. (2019). Aging Induces an Nlrp3 Inflammasome- Dependent Expansion of Adipose B Cells That Impairs Metabolic Homeostasis. Cell Metab. 30, 1024–1039.e6. 43. Ying, W., Wollam, J., Ofrecio, J.M., Bandyopadhyay, G., El Ouarrat, D., Lee, Y.S., Oh, D.Y., Li, P., Osborn, O., and Olefsky, J.M. (2017). Adipose tissue B2 cells promote insulin resistance through leukotriene LTB4 / LTB4R1 signaling. J. Clin. Invest. 127, 1019–1030. 44. DeFuria, J., Belkina, A.C., Jagannathan-Bogdan, M., Snyder-Cappione, J., Carr, J.D., Nersesova, Y.R., Markham, D., Strissel, K.J., Watkins, A.A., Zhu, M., et al. (2013). B cells promote inflammation in obesity and type 2 diabetes through regulation of T-cell function and an inflammatory cytokine profile. Proc. Natl. Acad. Sci. USA 110, 5133–5138. 45. Radl, J., Sepers, J.M., Skvaril, F., Morell, A., and Hijmans, W. (1975). Immunoglobulin patterns in humans over 95 years of age. Clin. Exp. Immunol. 22, 84–90. 46. Natsuume-Sakai, S., Motonishi, K., and Migita, S. (1977). Quantitative estimations of five classes of immunoglobulin in inbred mouse strains. Immunology 32, 861–866. 47. Yadav, H., Quijano, C., Kamaraju, A.K., Gavrilova, O., Malek, R., Chen, W., Zerfas, P., Zhigang, D., Wright, E.C., Stuelten, C., et al. (2011). Protection from obesity and diabetes by blockade of TGF-βeta / Smad3 signaling. Cell Metab. 14, 67–79.Attorney Docket No. 44010.206WO-PCT / / CU24263 48. Kuo, T.T., Baker, K., Yoshida, M., Qiao, S.W., Aveson, V.G., Lencer, W.I., and Blumberg, R.S. (2010). Neonatal Fc receptor: from immunity to therapeutics. J. Clin. Immunol.30, 777–789. 49. Zuercher, A.W., Spirig, R., Baz Morelli, A., Rowe, T., and Käsermann, F. (2019). Next- generation Fc receptor-targeting biologics for autoimmune diseases. Autoimmun. Rev. 18, 102366. 50. Mezo, A.R., McDonnell, K.A., Hehir,C.A., Low, S.C., Palombella, V.J., Stattel, J.M., Kamphaus, G.D., Fraley, C., Zhang, Y., Dumont, J.A., and Bitonti, A.J. (2008). Reduction of IgG in nonhuman primates by a peptide antagonist of the neonatal Fc receptor FcRn. Proc. Natl. Acad. Sci. USA 105, 2337–2342. 51. Tschöp, M.H., Speakman, J.R., Arch, J.R., Auwerx, J., Brüning, J.C., Chan, L., Eckel, R.H., Farese, R.V., Jr., Galgani, J.E., Hambly, C., et al. (2011). A guide to analysis of mouse energy metabolism. Nat. Methods 9, 57–63. 52. Zhou, Q., Yu, L., Cook, J.R., Qiang, L., and Sun, L. (2023). Deciphering the decline of metabolic elasticity in aging and obesity. Cell Metab. 35, 1661– 1671.e6. Example 2 – Reducing IgG improves metabolic functions in aged mice.

[0200] Control IgG1 and anti-FcRn antibody (50 μg / mouse) were intraperitoneally administrated to aged C57BL / 6 male mice weekly for up to 8 weeks (n=8, 8). Applicants showed that IgG levels were decreased by anti-FcRn treatment (FIG.16A). Applicants showed that plasma triglycerides (FIG. 16B) and free fatty acids (FIG. 16C) levels were decreased by anti-FcRn treatment. Applicants showed that insulin tolerance was improved by anti-FcRn treatment (FIG. 16D). Applicants showed that glucose tolerance was improved by anti-FcRn treatment (FIG.16E). Example 3 – FcRn-dependent IgG accumulation in adipose tissue unmasks obesity pathophysiology. In brief

[0201] Applicants found that in obesity, IgG accumulates preferentially in adipose tissue via FcRn-dependent recycling by adipose progenitor cells and macrophages. This buildup promotes macrophage infiltration and adipose inflammation and impairs insulin binding to its receptor, ultimately leading to insulin resistance and metabolic dysfunction.Attorney Docket No. 44010.206WO-PCT / / CU24263 Highlights IgG accumulates in adipose tissue in obesity, causing metabolic dysfunctions. This occurs via FcRn-dependent recycling in adipose progenitor cells and macrophages. IgG accumulation triggers macrophage infiltration and expedites adipose inflammation. IgG impedes insulin’s binding to the insulin receptor to promote insulin resistance. Summary

[0202] Immunoglobulin G (IgG) is traditionally recognized as a plasma protein that neutralizes antigens for immune defense. However, this research demonstrates that IgG predominantly accumulates in adipose tissue during obesity development, triggering insulin resistance and macrophage infiltration. This accumulation is governed by neonatal Fc receptor (FcRn)-dependent recycling, orchestrated in adipose progenitor cells and macrophages during the early and late stages of diet-induced obesity (DIO), respectively. Targeting FcRn abolished IgG accumulation and rectified insulin resistance and metabolic degeneration in DIO. By integrating artificial intelligence (AI) modeling with in vivo and in vitro experimental models, Applicants unexpectedly uncovered an interaction between IgG’s Fc-CH3 domain and the insulin receptor’s ectodomain. This interaction hinders insulin binding, consequently obstructing insulin signaling and adipocyte functions. These findings unveil adipose IgG accumulation as a driving force in obesity pathophysiology, providing a novel therapeutic strategy to tackle metabolic dysfunctions. Introduction

[0203] The rising prevalence of obesity and overweight casts unprecedented medical burdens worldwide owing to a variety of comorbidities. A primary comorbidity associated with obesity is insulin resistance, a driving force of type 2 diabetes (T2D) and other metabolic conditions.1,2Profound progress has been made in investigating the insulin signaling pathway and its impairment in obesity through cell-intrinsic, endocrine, neural, and inflammatory mechanisms.3–5However, understanding the pathophysiology of obesity remains a priority for treating and preventing metabolic diseases.

[0204] Adipose tissue plays a key role in the development of obesity and comorbidities. Its function is compromised during the hypertrophic expansion in obesity, manifested in insulin resistance, altered adipokine production, and impaired glucose uptake and lipid metabolism, inflammation, and fibrosis.6,7These pathological changes are indeed intrinsically connected. GivenAttorney Docket No. 44010.206WO-PCT / / CU24263 that insulin signaling is required for adipocyte development, insulin resistance impairs adipogenesis and adipocyte function.8Impaired adipogenesis restrains adipose tissue remodeling and catabolic activation (e.g., browning),9–11leading to adipocyte hypertrophy.12,13On the other hand, hypertrophic obesity promotes chronic inflammation14by recruiting immune cells into adipose tissue, such as macrophages.15Reciprocally, adipose tissue inflammation worsens insulin resistance and metabolic function.16Moreover, obese adipose tissue enriches a large number of fibrotic cells, escalating these pathogenic manifestations.17Nevertheless, a trigger that unifies these pathological hallmarks is enigmatic.

[0205] Immunoglobulin G (IgG) is the predominant circulating antibody for adaptive immune response with a recently identified pro-aging function.18IgG is produced by mature B plasma cells, endocytosed to clear bound antigens, and then recycled into circulation by the neonatal Fc receptor (FcRn). Among all the immunoglobulins, only IgG has a professional recycling receptor, FcRn, and thus a long half-life.19This FcRn-dependent recycling outperforms B cell production in determining the systemic homeostasis of IgG. Compared with IgG, the other two less abundant classes of antibodies, IgA and IgM, do not bind FcRn and undergo much faster degradation. Studies have established that B cells infiltrate adipose tissue in diet-induced obesity (DIO)20,21and aging22to contribute to metabolic dysregulation mostly by interacting with other immune cells through non-IgG cytokines. As such, B cell-null mice (Bnull) are protected from insulin resistance in DIO.20,21,23However, the contribution from the main secreted product of B cells, IgG, remains unclear.

[0206] Here, Applicants demonstrated that IgG accumulates predominantly in white adipose tissue (WAT) during DIO through FcRn-dependent recycling, where it triggers insulin resistance and macrophage infiltration. Surprisingly, IgG obstructs insulin signaling by interacting with the insulin receptor (IR) to hinder insulin binding, thereby compromising adipose functions. Collectively, these findings provide a unified mechanism through IgG accumulation that connects key components in obesity pathophysiology. RESULTS IgG predominantly accumulates in WAT in obesity

[0207] In endeavors to understand metabolic dysregulation in obesity, Applicants noted a striking accumulation of IgG, in contrast to IgA and IgM, in the epididymal WAT (eWAT) ofAttorney Docket No. 44010.206WO-PCT / / CU24263 C57BL / 6J mice fed with high-fat diet (HFD) (FIGS. 17A and 17B). IgG was dispersed among adipose tissue cells, not limited to co-localization with macrophages (FIG. 24A). While this adipose IgG accumulation could result from the circulation, the only 2-fold increase in plasma IgG is unlikely to account for the 16-fold accumulation in the eWAT (FIGS. 17C and 17D). The accumulated IgG proteins consisted of all major subtypes, including IgG1, IgG2a, and IgG3 (FIGS. 24B–24E), suggesting polyclonal responses. Strong IgG accumulation was also detected in inguinal WAT (iWAT) but not in brown adipose tissue (BAT) or heart (FIGS. 24F and 24G). Indeed, IgG predominantly accumulates in WATs in DIO mice compared with other tissues (FIG. 17E). A likely cause of IgG accumulation in adipose tissue is the influx of B cells in DIO. However, when Applicants administered exogenous IgG into DIO B cell-null (Bnull) mice, which are deprived of endogenous IgG, the highest IgG accumulation was still detected in eWAT and iWAT (FIG. 17F). These data indicate that adipose IgG is a pathological marker in obesity, and WAT harbors a unique mechanism independent of B cells to enrich IgG.

[0208] The accumulation of IgG was similarly detected in obese human adipose tissue compared with lean control biopsies (FIGS. 17G and 24H). Transcriptomic analysis of the omental adipose tissue from obese human subjects revealed a prevailing enrichment of pathways related to adaptive immune response and immunoglobulin together with macrophage activation (FIG. 17H), implying the involvement of IgG in the pathological remodeling of adipose tissue in obesity.

[0209] To examine any possible metabolic consequence of adipose IgG accumulation, Applicants injected total IgG isolated from chow-fed mice into lean mice twice weekly for 4 weeks. The treated mice showed a similar pattern of tissue IgG accumulation as in DIO mice, with the highest accumulation in WATs (FIG. 24I). Notably, this 4-week IgG treatment was sufficient to impair insulin sensitivity but without affecting body weight and glucose tolerance test (GTT) (FIGS. 17I, 24J, and 24K). Upon IgG accumulation, macrophage marker F4 / 80 was induced in eWAT (FIGS. 17J and 24L), along with the upregulation of inflammatory genes Cd68, Tnfa, Mcp1, and Il1b (FIG. 17K). RNA sequencing (RNAseq) analysis further revealed activated immune response and impaired lipid metabolism in the eWAT of IgG-treated mice (FIG. 24M). These results suggest that IgG plays a causal role in adipose tissue pathological remodeling and insulin resistance.Attorney Docket No. 44010.206WO-PCT / / CU24263 IgG is recycled by adipocyte progenitor cells to accumulate in WAT during early DIO

[0210] Next, Applicants sought to understand how IgG is accumulated in obese adipose tissue. Previous studies have demonstrated that IgG recycling plays a more pivotal role than B cell production in regulating tissue accumulation of IgG levels.18,24Given the B cell-independent accumulation of IgG in WAT, Applicants asked whether FcRn-dependent recycling mediates WAT IgG accumulation in obesity. Though FcRn was discovered as a neonatal receptor in the placenta, it is expressed abundantly in adult mouse tissues, particularly in eWAT and iWAT (FIG. 25A). Interestingly, its levels were increased in obese eWAT (FIG. 25B). Adipose tissue is a highly heterogeneous organ,25and Fcgrt (encoding FcRn) was expressed mainly in adipose progenitor cells (APCs) and macrophages among the stromal vascular fraction (SVF) cells from a published WAT single-cell RNA-seq dataset26(FIG. 18A). After confirming that APCs were capable of absorbing Cy5.5-labeled IgG (FIG. 18B), Applicants hypothesized that APCs recycle IgG, contributing to its accumulation in adipose tissue during obesity. To test this, Applicants bred Fcgrt floxed mice with Pdgfra-Cre to knockout FcRn in APCs (pKO) (FIGS. 18C and 18D). In vitro IgG uptake by APCs from pKO mice showed no difference from the control cells, while after a 4-h chase period, the pKO APCs failed to release IgG into the media (FIG.18E), indicating that APCs convey a function of recycling IgG.

[0211] The half-life of IgG was modestly reduced in the pKO mice (FIGS. 25C and 25D), leading to attenuated IgG accumulation in eWAT and a lesser extent in the plasma at 4 weeks of HFD feeding regardless of their comparable weight gain on HFD feeding (FIGS. 18F–18H and 25E). Interestingly, pKO mice were protected from the development of insulin resistance and glucose intolerance in early DIO (FIGS. 18I and 18J). These metabolic phenotypes were not observed in chow diet-fed at basal IgG levels (FIGS. 25F and 25G). Notably, the inhibition of IgG accumulation in WAT vanished after prolonged HFD feeding (12 weeks) (FIGS. 18K and 18L), and so did the improvements in insulin sensitivity and glucose tolerance (FIGS. 18M and 18N). Meanwhile, no significant changes in tissue composition, adipocyte size, plasma triglycerides (TGs), and non-esterified fatty acids (NEFA) were observed in pKO mice regardless of 4- or 12-week HFD feeding (FIGS. 25H–25O). Because FcRn was induced during adipocyte differentiation, Applicants further ablated FcRn in adipocytes (Fcgrtflox / flox: Adipoq-Cre, aKO) (FIGS. 25P and 25Q) but found no impact on IgG half-life and accumulation, insulin sensitivity,Attorney Docket No. 44010.206WO-PCT / / CU24263 and glucose tolerance in DIO (FIGS. 25R– 25V). Together, these findings demonstrate that IgG is recycled by APCs to account for its deposition into adipose tissue and trigger metabolic dysregulation in early obesity. Abolishing IgG recycling in macrophages prevents advanced IgG accumulation and metabolic derangements in DIO

[0212] Applicants then investigated the mechanism underlying IgG accumulation in late obesity. Besides APCs, FcRn is abundantly expressed in macrophages (FIG. 18A). Although macrophage infiltration is a hallmark of obese adipose tissue, a significant increase of the macrophage marker F4 / 80 was not detected until 8 weeks of DIO27,28(FIGS. 19A and 19B). In contrast, IgG accumulation in eWAT was induced as early as 2 weeks upon HFD feeding, and there was interestingly a further increase in IgG accumulation after macrophage infiltration. Given this temporal pattern, Applicants employed a myeloid cell FcRn conditional knockout mouse model (Fcgrtflox / flox: LysM-Cre mice, mKO) to test whether adipose IgG accumulation depends on its recycling by macrophages.

[0213] Following the efficient deletion of Fcgrt in macrophages (FIG. 19C), the half-life of IgG was significantly shortened in the mKO mice (FIGS.26A and 26B). Regardless of a decrease of basal IgG levels but not IgA, IgM, or albumin, chow-fed mKO mice showed minimal metabolic phenotype in terms of body weight, body composition, insulin sensitivity, and glucose tolerance (FIGS. 26C–26I). However, when challenged with HFD feeding, the accumulation of IgG in the circulation and WATs was abolished in mKO mice, unlike their largely normal IgA, IgM, and albumin levels (FIGS.19D, 19E, 26J, 26K, 27A, and 27B). Strikingly, mKO mice were prevented from HFD-induced weight gain, insulin resistance, and glucose intolerance (FIGS. 19F–19H), in line with their significant decrease in plasma insulin levels (FIG. 19I). This lean phenotype is exclusively owing to their lower fat mass (FIG.19J), supported by >60% reduction in eWAT and iWAT depot sizes (FIG. 27C).

[0214] Underlying DIO mKO’s lower fat mass is their mitigated adipocyte hypertrophy (FIGS. 19K and 27D). Accordingly, RNA-seq analysis revealed profound repression of inflammation-related pathways in the mKO eWAT in orchestration with activated catabolic responses (FIG. 19L). In line with IgG’s pro-fibrotic function in aging,18eWAT fibrosis was inhibited in DIO mKO mice (FIGS. 27E and 27F). With the prevention of IgG accumulation,Attorney Docket No. 44010.206WO-PCT / / CU24263 brown remodeling genes (Ppara, Ppargc1a, Ucp1, Cidea, Hsl, Atgl, and Cox7a1) were upregulated, whereas macrophage infiltration indicators F4 / 80 and Mcp1 were suppressed in eWAT (FIG. 27G). Similarly, adipogenesis genes in iWAT were upregulated, and the expression of inflammatory genes was alleviated (FIG. 27H). IgG accumulation was also inhibited in the BAT of mKO mice (FIGS. 19M and 27B), resulting in abrogated BAT whitening (FIG. 19K) and upregulation of lipolytic genes (Lpl and Hsl) and catabolic genes (Ppargc1a, Ucp1, Cox7a1, and Cox8b) (FIG. 19N). Moreover, indirect calorimetric analyses revealed higher oxygen consumption in DIO mKO mice without reducing food intake, accompanied by an increased respiratory exchange ratio (RER) in the dark phase and unaffected locomotion (FIGS. 19O and 27I–27L). Collectively, these data highlight the essential role of macrophage-mediated IgG accumulation in the full development of metabolic derangement in DIO.

[0215] Besides IgG, FcRn also recycles albumin but mainly in hepatocytes.29Applicants detected marginal changes in albumin levels when intervening FcRn in APCs and macrophages. Nevertheless, Applicants treated lean mice with albumin for 3 weeks and observed no effect on body weight or insulin sensitivity despite significant accumulation in eWAT (FIGS. 27M–27O). These data reinforce the special metabolic consequences of FcRn-dependent recycling of IgG. IgG interacts with the IR to impede insulin signaling

[0216] IgG treatment induced insulin resistance in lean mice (FIG.17I), while pKO and mKO mice showed improved insulin sensitivity along with their inhibited IgG accumulation. This inverse correlation between IgG and insulin sensitivity raised the possibility that IgG might interfere with insulin signaling. Strikingly, acute treatment of IgG but not albumin was able to impair insulin sensitivity in lean mice overnight (FIGS. 20A and 28A), implying a direct effect of IgG on insulin signaling. Indeed, insulin signaling in adipose tissue was impeded by IgG treatment (FIGS.20B and 20C). Consistently, insulin-induced AKT phosphorylation increased in the eWAT of DIO mKO mice (FIGS. 20D and 20E). The impact of IgG on insulin signaling was attributed to the IR, as shown by decreased IR phosphorylation in IgG-treated mouse eWAT and the converse increase in mKO mice. The repression of insulin signaling by IgG was recapitulated in vitro in 3T3-L1 adipocytes (FIGS. 20F and 28B) and also verified in myotubes (FIG. 28C). Intriguingly, this repression requires IgG pre-treatment prior to insulin stimulation, while simultaneous treatment showed minimal effect, implying a preoccupation with IR by IgGAttorney Docket No. 44010.206WO-PCT / / CU24263 treatment. To functionally test the inhibitory effect of IgG on IR activation, Applicants treated mature C3H10T1 / 2 adipocytes with IgG and insulin undergoing isoproterenol-stimulated lipolysis. As expected, IgG antagonized insulin’s inhibition of lipolysis, as reflected by glycerol release in adipocytes (FIG. 20G). Similarly, IgG inhibited insulin-stimulated glucose uptake in differentiated C2C12 myotube (FIG. 28D).

[0217] To elucidate the inhibitory mechanism of IR by IgG, Applicants purified membrane- bound proteins from 3T3-L1 adipocytes with or without IgG pre-treatment. IgG was present in the membrane bound proteins, and insulin treatment inhibited this binding (FIG. 20H). Notably, IgG prevented IR phosphorylation on the membrane, suggesting a competition between IgG and insulin to bind to IR. To determine whether IgG can bind to IR, Applicants employed a proximity labeling technique by adding a TurboID tag to IR (FIG. 20I). TurboID is an engineered biotin ligase that can rapidly add biotin to its near-neighbor protein.30Significant biotin labeled IgG was detected in the streptavidin pull-down samples from TurboID-IR-transfected 293T cell lysates, evidencing an interaction between IgG and IR (FIG. 20J), which was confirmed by ex vitro pull-down (FIG. 28E). IgG consists of a variable antigen-binding fragment (Fab) and a constant Fc fragment. Treatment of Fc fragments was sufficient to inhibit insulin-stimulated phosphorylation of IR and AKT in 3T3-L1 adipocytes (FIG.20K), excluding the involvement of antigen recognition in IgG- mediated impairment of insulin signaling.

[0218] Applicants subsequently applied AlphaFold2 to screen for the potential interacting domains between IR and IgG. The immunoglobulin-like domain 1 (IgLD1, 501–619 aa, according to the homologous superfamily analysis of the InterPro: P15208-IR) of IR was predicted to interact with the CH3 domain in the Fc fragment in all the IgG subclasses with high probability, as shown by the confidence of the predicted local distance difference test (pLDDT) with a very low inter- complex predicted alignment error (PAE) at high sequence coverage (FIGS.20L, 20M, and 28F– 28I). IgLD1 is next to the L2 domain of IRa, nearly identical to the FnIII-1 domain (mouse IRB499–620 aa)31(FIG. 20N),which mediates the conformational switch of IR upon insulin binding.32,33A TurboID-IR mutant that deleted IgLD1 domain (IR-D1) abolished IRb phosphorylation upon insulin stimulation in 293T cells and diminished the biotin labeling of IgG as well (FIGS. 20O and 20P). Therefore, IgG interacts with IR at the IgLD1 domain to inhibit insulin signaling.Attorney Docket No. 44010.206WO-PCT / / CU24263 Computational modeling and interaction assays reveal a competing binding between IgG and insulin to the IR

[0219] To understand the inhibitory mechanism, Applicants performed computational modeling of the interaction between IgG and IR. Applicants adopted the recently resolved cryoelectron microscopy (cryo-EM) structures of mouse IR ectodomain in different states upon insulin binding (PDB: 7SL1, resolution = 3.40 Å)34and the ectodomain of the full-length human IR in the active state (Tshape)32as the initial structure to generate structural models of IR ectodomain-IgG complexes using two complementary protein-protein docking methods, Zdock3.0.235and InterEv-Dock3.36The IgG CH3 domain is known for interacting with other proteins, and it shows the highest possibility of binding to the IgLD1 region of IR in the AlphaFold2 prediction. IgG CH3 domain structures were then constructed using SWISS-MODEL and used for docking with the IR ectodomain model. The root mean-square deviation (RMSD) value indicates the variance between the experimental structure and the predicted model, and the RMSD values between the modeled structures of the CH3 monomers and dimers of IgG1, IgG2a, IgG2b, and IgG3 are smaller than 1.50 Å (FIGS. 29A–29C), comparable to the RMSD values at 1.86 and 1.47 Å in the two top-ranked IR ectodomain-insulin interaction models (FIG. 29D), suggesting near-native structures of IR ectodomain and IgGCH3 in the complexes. Among the computed interaction models, the top-ranked structures showed that the CH3 domain could occupy the type-2 insulin-binding site at the FnIII-1 domain of inactive IR, which aligns with the AlphaFold2 prediction.37,38This interaction model is prominent as the CH3 domains of IgG1, IgG2a, IgG2b, and IgG3 are all predicted to interact with IR at the same binding site as insulin in both monomer and dimer forms (Fc fragment is in the dimer form) (FIG. 21A). When the active IR ectodomain was employed for modeling, the top-ranked model similarly showed that the CH3 domain of IgG2b can bind to the active type-2 insulin-binding site (FIG. 21B), similarly to IgG1, IgG2a, and IgG3, though at slightly lower affinity scores (FIG. 31). Moreover, when Applicants applied the newly released AlphaFold3,39Applicants obtained the same binding model of the IgG domain (Fc CH3 dimer) to IR as the computation modeling. Furthermore, albumin was used as a control for testing nonspecific binding, and it showed weak PAE of the predicted interaction model with IR (FIG. 29E).Attorney Docket No. 44010.206WO-PCT / / CU24263

[0220] Applicants then calculated the binding strengths in the predicted IR ectodomain-IgG CH3 complexes using AREA-AFFINITY.40The IgG CH3 domains bind to the IR ectodomain with a relatively strong binding affinity (e.g., IR ectodomain-IgG2b CH3 models) (log(K) = ‒6.58 ± 1.74, K is disassociation constant), albeit lower than insulin (log(K) = ‒7.60 ± 1.64) (FIG. 31). This binding pattern supports a hypothesis that IgG might compete with insulin to bind to IR. To test it, Applicants employed microscale thermophoresis (MST) to experimentally measure their binding affinity. Insulin bound to IR at a dissociation constant (KD) of 14.76 nM under this experimental condition (FIG. 21C), which is less sensitive than the isotype labeling method. The titrated insulin KD value was increased to 30.76 nM if IR was preincubated with IgG at a concentration of 0.52 μM (much lower than the physiological concentration 20–67 μM ≈ 3–10 mg / mL) for 10 min (FIG. 21D). The binding of insulin to IR was completely abolished by a high concentration of IgG (FIG.21E). Consistently, native mouse IgG was found to bind to IR at a KD of 152.7 μM (FIG.21F), which was increased to 376.2 μM in the presence of 20 nM insulin (FIG. 21G). In parallel, surface plasmon resonance (SPR) assays demonstrated that the interaction between insulin and IR had a KD of 23.6 nM, and it was reduced to 85.3 nM in the presence of 50 μM IgG (FIGS. 21H and 21I). By contrast, in the presence of 50 μM albumin, the interaction of insulin and IR was not impeded (FIG. 21J). These binding affinity data pinpoint that IgG hinders insulin binding to IR to impair insulin signaling. IgG obstructs adipogenesis

[0221] Insulin signaling is essential for the development of adipocytes.41,42During DIO, adipogenic genes, including Pparg1, Pparg2, Cebpb, Fabp4, Fasn, and Adipoq, were initially stimulated; however, this upregulation declined after approximately 4 weeks of HFD feeding (FIG. 22A), congruent with the accumulation of IgG (FIG. 19A). Adipogenic genes were increased in pKO mice at 4 weeks but not with prolonged HFD feeding (FIGS. 22B and 30A) or in obese aKO mice (FIG.30B). Consistently, with the prevention of IgG accumulation, DIO mKO mice increased the expression of adipogenic genes in eWAT (FIG. 22C), while IgG treatment in lean mice suppressed adipogenic genes in eWAT (FIG. 22D).

[0222] Considering the persistent inverse correlation of IgG levels with adipogenic gene expression across different in vivo models, Applicants hypothesized IgG inhibits adipogenesis. IgG treatments in differentiated APCs showed dose-dependent inhibitory effects, abrogatingAttorney Docket No. 44010.206WO-PCT / / CU24263 adipogenesis at 1 mg / mL (FIG. 22E). Oil red O staining reflected that IgG inhibited lipid accumulation in primary adipocyte differentiation, accompanied by inhibited induction of adipogenic markers such as Pparg1, Pparg2, Cfd, and Fabp4 (FIGS.22F and 22G). This inhibition of adipogenesis was recapitulated in 3T3-L1 and C3H10T1 / 2 cells but was abolished by boiling IgG, indicating the requirement of native IgG (FIGS. 22H, 30C, and 30D).

[0223] Notably, the inhibited adipogenesis was underlain by impaired insulin signaling (FIG. 22I), and it is the Fc fragment that accounted for this inhibitory effect (FIG. 22J), in line with the CH3 domain-binding model with IR. To identify the effector of IgG in adipogenesis, Applicants performed time course treatment of IgG in 3T3-L1 cells and noticed that the inhibition began mostly after day 2 of differentiation (FIGS. 22K and 30E). IgG did not suppress the early adipogenic transcription factor CCAAT enhancer binding protein beta (C / EBPβ) in the adipogenic cascade but inhibited the adipogenic program since peroxisome proliferator-activated receptor gamma (PPARγ), the master regulator of adipogenesis,43,44and consequently its downstream targets (e.g., fatty acid synthase [FASN], CCAAT enhancer binding protein alpha [C / EBPα], adiponectin [APN], and fatty acid binding protein 4 (FABP4)) (FIGS. 22I–22K, 30D, and 30E). This divergent regulation of C / EBPβ and PPARγ was also seen in vivo, regardless of IgG loss or gain of functions (FIGS. 22B–22E, 22G, and 29D). As the premier therapeutic target of insulin sensitivity, the induction of PPARγ actually requires insulin signaling. Supportively, overexpressing PPARγ mostly blunted the inhibitory effect of IgG on adipogenesis (FIGS. 22L and 30F). These data collectively support an inhibitory function of IgG in adipogenesis through impairing insulin signaling-mediated activation of PPARγ. Targeting IgG recycling rectifies metabolic dysfunction in DIO mice

[0224] Given the improved metabolic function and adipose integrity by FcRn loss of function in DIO mKO and pKO mice, together with the inhibition of insulin signaling by IgG, Applicants asked whether FcRn is a suitable therapeutic target in obesity. Applicants treated DIO mice with an antisense oligonucleotide (ASO) against Fcgrt to inhibit FcRn-mediated IgG recycling.18Fcgrt ASO treatment efficiently decreased plasma IgG levels, accompanied by an increase in adiponectin, a downstream target of PPARγ45,46(FIG. 23A). Despite no significant decreases in body weight and fat composition (FIGS. 23B and 23C), glucose tolerance and insulin sensitivity were improved (FIGS.23D and 23E), in line with the over 50% decrease in plasma insulin levelsAttorney Docket No. 44010.206WO-PCT / / CU24263 after 7 weeks’ Fcgrt ASO treatment (FIG. 23F). Moreover, obesity-associated dyslipidemia was alleviated, indicated by the reduced plasma TG and NEFA levels (FIGS. 23G and 30G). Following efficient knockdown (KD) of FcRn, IgG accumulation in adipose tissue was mitigated (FIGS. 23H and 30H), resulting in reduced eWAT depot size and alleviated adipocyte hypertrophy (FIGS. 23I and 23J). Consistently, KD of FcRn increased adipogenic genes and brown adipocyte markers Ucp1, Cidea, Cox8b, and Ppargc1a in eWAT (FIG. 23K), suggesting improved adipose tissue remodeling. Unlike lipodystrophy, the decrease of adiposity by FcRn KD did not cause hepatic steatosis (FIG.30I), accompanied by efficient KD of Fcgrt in the liver (FIG. 30J). Hence, targeting FcRn to inhibit IgG accumulation rectifies metabolic dysfunction in DIO mice. Discussion

[0225] Diverging from the dogmatic notion of IgG to neutralize antigens for adaptive immune responses, Applicants demonstrate that IgG predominantly accumulates in WAT during the development of obesity to cause metabolic dysfunction. This adipose IgG accumulation requires FcRn-dependent recycling initially by APCs and subsequently by macrophages, forming a descending loop to impair metabolic health. IgG can bind to the FnIII-1 domain of IR in a Fab- independent manner to impede insulin binding. Considering the prevalent presence of IgG in the obese WAT microenvironment, its impact on insulin sensitivity can be substantial. These findings thereof unveil a hitherto unrecognized role of IgG as a driving force of metabolic dysregulation.

[0226] Increased IgG has been previously noticed in obese WAT but was considered to manifest as a readout of B cell infiltration.20Moreover, autoantibodies of the IgG2c subclass can be induced in obesity and contribute to metabolic dysfunction.20However, IgG2c only accounts for a marginal proportion of IgG antibodies, so it is impossible to explain the marked accumulation of all IgG subclasses in obesity. This observation raised a possibility that IgG could function through a mechanism independent of antibody recognition. Conclusive evidence came from the inhibition of insulin signaling by isolated Fc fragments. In the classic model, upon antigen binding at the Fab, IgG interacts with FcgRs to initiate antigen clearance and adaptive immune responses. The finding of competitive binding of the Fc fragment with IR departs from this dogma, illustrating an unconventional mechanism linking IgG with insulin signaling. Consistently, ablating FcgRs showed minimal effects on glucose tolerance and insulin sensitivity in DIO mice.47With theAttorney Docket No. 44010.206WO-PCT / / CU24263 identification of IgG as a native inhibitor of IR, IgG antibodies show broader implications beyond their presumed antigen-neutralizing function.

[0227] IR contains three IgLDs (IgLD1-3) that typically interact with proteins carrying a similar domain. Among them, IgLD1 almost completely overlaps with the FnIII-1 domain,31which is the insulin- binding site and the hinge region that mediates the conformational switch between the T (active) and U (inactive) shapes of IR. The U-shaped model was first selected for computational modeling because of the availability of its high-resolution structure and definite inactive state. The similar computational results from our docking modeling and AlphaFold3 prediction suggest that IgG can bind to the side of the FnIII-1 domain in the inactive IR (rather than occupying the complete binding site 1), and this binding would hinder the conformational change of IR to an active state. It is thus plausible that IgG binds to the FnIII-1 domain, albeit at a much lower affinity than insulin, to chronically impede insulin signaling, especially under the robust induction in obesity. In supporting this model, treatment of IgG to mimic the obese condition impaired systemic insulin sensitivity in lean mice.

[0228] This weak interaction between IgG and IR is meaningful for insulin signaling at the physiological condition. It is equally important for efficiently shutting off insulin signaling as activating it upon nutritional status change, such as fasting. However, the absolute absence of insulin under physiological conditions does not exist. IgG levels are rather constant compared with insulin in vivo. It is conceivable that at the fasting state, when insulin levels drop below a threshold, IR is occupied by IgG. This occupation thus provides a buffering solution to efficiently shut off insulin signaling. It may also act as a protective mechanism against unwanted activation of IR by other growth factors, such as insulin-like growth factor 1 (IGF1). This desensitization might outpace the benefit under the hyperinsulinemia condition in obesity. Endocytosis of the IR upon insulin binding is a key mechanism regulating the intensity and duration of insulin signaling.48Interestingly, IR protein abundance was increased in the DIO mKO eWAT, likely owing to their alleviated insulin resistance and hyperinsulinemia. It is also worthy of further investigation of the possibility that IgG’s binding to IR induces the latter’s endocytosis.

[0229] B cells are the major component of lymphocytes and play pivotal roles in both innate and adaptive immunity by producing antibodies and various cytokines. Antibody production is abrogated in Bnullmice or by anti-CD20-mediated B cell depletion. Despite their immuneAttorney Docket No. 44010.206WO-PCT / / CU24263 abnormalities, these mice are protected from insulin resistance in DIO. This metabolic detriment of B cells in obesity was attributed to mechanisms including producing leukotriene B4 (LTB4) to stimulate macrophages,21generating IgG2c autoantibodies,20and modulating IgG glycosylation to activate FcgRIIB in obesity.49Departing from these ‘‘qualitative’’ mechanisms, obesity induces substantial IgG accumulation. Notably, even IgG from lean, chow-fed mice can quantitatively induce insulin resistance by inhibiting IRs. This discovery provides a direct link between the adaptive immune system and insulin sensitivity. Infiltrated B cells in obese WAT arguably contribute to IgG accumulation. Surprisingly, they are not a determinant for adipose IgG accumulation. The enrichment of exogenous IgG in WAT indicates a B cell-independent mechanism. Here, Applicants established a crucial role of macrophages in recycling IgG and enriching it in adipose tissue in advanced obesity. Applicants also identify APCs as an important recycling site, especially in early obesity. Considering antigen clearance upon IgG endocytosis, APCs possibly convey a new function of antigen clearance. Moreover, adipocytes also express FcRn. However, knockout of FcRn in adipocytes (aKO) showed no effect on IgG half-life or accumulation in WAT or circulation in DIO mice. These results suggest that adipocytes are dispensable for recycling IgG in obesity, raising an interesting question of whether FcRn has an IgG-independent function in adipocytes.

[0230] WAT macrophage infiltration is a hallmark of chronic inflammation in obesity and correlates with adipocyte hypertrophy. However, it is not significant until the later stage of DIO. What induces macrophage infiltration and initiates adipose tissue inflammation remained elusive. IgG starts to accumulate in WAT as early as 2 weeks on HFD feeding, and IgG administration in lean mice induced macrophage infiltration into WAT. Given that IgG can mediate the inflammatory activation of macrophages,18IgG ideally serves as the trigger of macrophage infiltration into adipose tissue. In summary, these findings establish IgG as a knot connecting the major players in adipose tissue, including macrophages, B cells, APCs, and adipocytes, and thereby provide a unified mechanism of obesity, insulin resistance, and inflammation, enlightening a novel strategy of targeting IgG clearance to intervene metabolic diseases. Limitations of the study

[0231] In this study, Applicants have addressed how IgG is enriched in WAT in obesity, which requires FcRn to coordinate its recycling in APCs and macrophages. Applicants have alsoAttorney Docket No. 44010.206WO-PCT / / CU24263 elucidated what IgG does in WAT, which is to induce insulin resistance, impair adipogenesis, and promote chronic inflammation. However, it remains unclear why IgG preferentially accumulates in WAT. WAT may have a unique microenvironment harboring rich extracellular matrix (ECM), adipokines, lipids, or antigens that attract IgG. Another possibility is that WAT can function as a reservoir to store antibodies. Currently, Applicants are limited in an efficient approach to ablate IgG recycling specifically in WAT to test this possibility. Both mKO mice and FcRn ASO treatment abolish whole-body IgG recycling, while our pKO model only addresses the accumulation in early obesity. Mouse models of lipodystrophy may be considered to test whether IgG is spilled into other tissues due to adipose tissue insufficiency, therefore contributing to the development of inflammation and insulin resistance in non-adipose tissues. Further, despite the complementary experimental and computational evidence supporting a competitive binding model of IgG to IR with insulin, resolving the structure of the IgG-IR complex is expected in future studies. Data and code availability

[0232] The RNA-seq data have been deposited to the NGDC (ngdc.cncb.ac.cn / ) (PRJCA020695 and PRJCA020637) and are publicly available at the date of publication. Experimental Model and Study Participant Details Animal studies

[0233] C57BL / 6J, LysM-Cre (#0004781), Adipoq-Cre (#028020), and Pdgfra-Cre (#013148) mouse lines were purchased from Jackson laboratory.

[0234] Fcgrt loxp mouse line was generated at the Columbia University transgenic mouse core. Mice were housed in a 12-hours light / dark cycle (7 am / 7 pm) barrier facility with free access to water and food. Standard chow diet (PicoLab rodent diet 20, 5053) and high-fat diet (HFD, 60% fat) from Research Diets, Inc. (D12492i) were used in this study. Body compositions were determined by EchoMRI. Purified mouse IgG, biotin-labeled IgG, and IgG-Cy5 were obtained from Cosmo Bio USA, Inc., ProteinModes, and Sigma-Aldrich (I5381). Mice on the chow diet were intraperitoneally (i.p.) injected with IgG (1.5 mg, twice / week) for the indicated time. Bnullmice on HFD feeding were i.p. injected with IgG (3 mg, twice) for IgG tissue distribution detection. Mice on the chow diet were i.p. injected with albumin (5 mg, twice / week) for the indicated time. Fcgrt-targeted and control ASOs were administrated twice weekly through i.p.Attorney Docket No. 44010.206WO-PCT / / CU24263 injection at a dose of 50 mg / kg,body weight (BW) into DIO mice (HFD since 7 weeks old) for 8 weeks. All animal experiments were performed in accordance with NIH guidelines for Animal Care and Use, approved and overseen by Columbia University’s Institutional Animal Care and Use Committee (IACUC). In vitro adipocyte studies

[0235] 3T3-L1 and C3H10T1 / 2 cell lines were purchased from ATCC. 3T3-L1 cells were maintained in high glucose DMEM supplemented with 10% calf serum and penicillin- streptomycin (Pen-strep). C3H10T1 / 2 cells were grown in high glucose DMEM supplemented with 10% fetal bovine serum (FBS, heat-inactivated) and 1x Pen Strep. Cells were cultured in DMEM with 10% FBS since the induction of adipogenesis. The adipogenic cocktail contained 1 μM dexamethasone, 0.5 mM 3-isobutyl-1-methylxanthine, and 10 μg / mL insulin. Two days after induction, cells were maintained in a medium containing 2.5 μg / mL insulin until fully differentiated. Lipid content was assessed by Oil Red O staining.

[0236] To study insulin signaling in cultured adipocytes, 3T3-L1 cells (undifferentiated or differentiated) in 6-well culture plates were serum-starved overnight prior to treatment. Cells were pretreated with vehicle or IgG at indicated doses for 4 hours and then added 1 μg / mL insulin for 20 minutes. Cells were harvested for further Western blotting analysis of insulin signaling proteins.

[0237] For membrane isolation, 3T3-L1 cells were treated with 400 μg / mL IgG for 12 hours and pelleted by centrifugation at 300x g for 5 minutes, followed by membrane isolation using a Mem-PER kit. E-Cadherin was used as a loading control of membrane proteins. Primary adipocyte differentiation

[0238] Inguinal fat pads with the lymph node removed were dissected from 6 to 8-week-old C57BL / 6J mice and digested in LiberaseTMTM at 37° C for 20 minutes with gentle agitation. SVF cells were pelleted by centrifuging at 500x g for 5 minutes at 4° C after passing through a 70 mm cell strainer. The pellet was further suspended and plated in a basic medium (DMEM supplemented with 10% FBS, 1% Pen-Strep, 1% gentamycin). Upon reaching 70-80% confluence, the obtained APCs were passaged twice for expansion and seeded onto 12-well or 6-well plates. After confluence, APCs were differentiated in the adipogenic cocktail containing 1 μM dexamethasone, 0.5 mM 3-isobutyl-1-methylxanthine, 10 μg / mL insulin, and 5 μM Rosiglitazone for 2-3 days and then switched to maintaining medium until fully differentiated.Attorney Docket No. 44010.206WO-PCT / / CU24263 Bone marrow-derived macrophages (BMDMs)

[0239] Bone marrow cells were isolated from the femur and tibia of 6-8-week-old mice. Erythrocytes were removed by incubating with red blood cell lysis buffer on ice for 10 minutes. The remaining cells were collected and cultured for 5-6 days in low glucose DMEM with 10% FBS and 1% Pen-Strep with 10 ng / mL M-CSF to develop into macrophages.50BMDMs were then harvested for Fcgrt gene expression analysis. Method Details Metabolic studies

[0240] Indirect calorimetric analyses were performed using the Comprehensive Laboratory Animal Monitoring System (CLAMS) equipped with an Oxymax Open Circuit Calorimeter System (Columbus Instruments). The following parameters were monitored continuously for 6 days: food intake, O2 consumption (VO2), CO2 production (VCO2), heat, and locomotion over a 24-hour period (12 h light / 12 h dark) for each individual mouse. For the glucose tolerance test (GTT), mice were fasted overnight for 16 hours (5 pm to 9 am). Body weight and basal blood glucose level were recorded. Mice were i.p. injected with glucose at a dose of 2 g / kg,BWfor regular tolerance test or 1.5 g / kg,BW for 12-week DIO pKO cohorts to avoid exceeding the reading limit of glucometer. Blood glucose levels were measured by the OneTouch glucometer at 0, 15, 30, 60, 90, and 120 minutes after glucose injection. The insulin tolerance test (ITT) was performed after a 4-hour (9 am to 1 pm) fasting. Mice were i.p. injected with 0.75 U / kg,BW of human insulin for regular tolerance test or 1 U / kg,BW for 12-week DIO pKO mice, and glucose levels were measured at 0, 15, 30, 45, and 60 minutes. Plasma TG and NEFA concentrations were determined by Infinity Triglyceride Reagent and NEFA-HR, respectively.

[0241] To investigate tissue insulin signaling in vivo, Applicants fasted mice for 4 hours (9 am to 1 pm) before anesthesia with isoflurane. Untreated muscle, eWAT, and liver tissue were collected as controls. Applicants then injected insulin (3 U / kg,BW) into the same mice through the inferior vena cava and collected tissues at 4 minutes post-injection, as described previously.51Total proteins were isolated from these tissues and further analyzed by Western blotting. Adipocyte progenitor cells IgG recycling detection

[0242] APCs were isolated and cultured as the primary adipocyte description. After confluence, cells were treated with 200 μg / mL IgG for overnight and then washed with DMEMAttorney Docket No. 44010.206WO-PCT / / CU24263 three times to remove IgG before changing into fresh DMEM. An aliquot was taken as the 0-hour time point. After another 4-hour incubation, the medium was collected for detecting IgG release by Western blotting. In vitro IgG tracking using IgG-Cy5.5

[0243] IgG-Cy5.5 was dissolved into PBS to make a final concentration of 1 mg / mL and sterilized by filtration. To access uptake in vitro, IgGCy5.5 was added to the culture medium at a concentration of 10 μg / mL overnight. Cells were washed twice with PBS for about 5 minutes per wash and fixed using 4% paraformaldehyde in PBS (pH 7.4) for 10 minutes at room temperature. Cells were then incubated with 0.1-1 μg / mL DAPI (DNA stain) for 1 minute, rinsed with PBS, and imaged using confocal microscopy. TurboID labeling of IR-interacting proteins

[0244] The mouse IR cDNA ORF clone was purchased from Sinobiological (mg51062-cf) and then subcloned into a TurboID pcDNA3.1 backbone to generate a TurboID-IR plasmid. Applicants further generated an IR-D1 mutant plasmid by deleting the sequence encoding amino acids 501- 619 of TurboID-IR. HEK293 cells were transfected with 1 μg TurboID-IR or IR-D1 mutant plasmid DNA using TransIT-LT1 reagent (Mirus), according to the manufacturer’s instruction.24 hours later, cells were treated with 0 or 1 μg / mL insulin with or without 6-hour 200 μg / mL IgG pretreatment. Cells were treated with 500 μM biotin before harvest and subjected to Streptavidin Magnetic Beads (NEB S1420S) pull-down to purify biotin-labeled proteins. Ex vitro IR and IgG interaction

[0245] TurboID-IR plasmid DNA was transfected into 293T cells, and 48 hours later, the cells were harvested for Streptavidin magnetic beads pull-down to purify IR. The IR-conjugated beads were incubated with or without 200 μg / mL IgG for 4 hours. After extensive washing, pulled down proteins were eluted and subjected to WB to detect the interaction. RNA isolation and qPCR analysis

[0246] Tissues or cells were lysed in 1 mL TriZol reagent (ThermoFisher). After phase separation by adding 500 μL chloroform, RNA was isolated using the NucleoSpin RNA kit with DNase I digestion (Macherey-Nagel). cDNA was synthesized from 1 μg total RNA using the High- capacity cDNA Reverse Transcription kit (Applied Biosystems). Quantitative real-time PCR (qPCR) was performed on a Bio- Rad CFX96 Real-Time PCR system using the GoTaq qPCR Master Mix (Promega). Relative gene expression levels were calculated using the 2-ΔΔCtmethodAttorney Docket No. 44010.206WO-PCT / / CU24263 and presented as relative expression levels in arbitrary units (AU). Rpl23 or Cyclophilin A was used as reference genes. RNA sequencing analyses

[0247] Total RNA isolated from the eWAT of DIO control and mKO mice was sequenced and analyzed as previously described.52The RNAseq data were deposited at the Genome Sequence Archive (GSA, ngdc.cncb.ac.cn / gsa / ) database with the accession number PRJCA020695. The differentially expressed genes (DEGs) between the mKO and control groups were identified using the criteria of |log2FoldChange| > 0.75 & adjusted p-value < 0.1. DEGs were categorized into upregulated or downregulated groups based on their expression changes for mKO versus control. Functional enrichment analysis was conducted separately for upregulated and downregulated genes using DAVID (v6.8) within the biological processes category, and the False Discovery Rate less than 0.1 was considered significant enrichment. Additionally, REVIGO was employed to eliminate redundant terms and simplify the visualization of biological processes.

[0248] The sequencing data of visceral adipose tissue from lean and obese human subjects with metabolic dysfunction was from a previous study.53The Gene Set Enrichment Analysis (GSEA) based on the pre-ranked gene list of log2(fold change) was employed to investigate alterations in IgG-related biological processes (BP) between the two groups. Examination of Fcgrt expression in SVF scRNA-seq

[0249] The Seurat R package version 3.0.0.9000 (github.com / satijalab / seurat) was used to project all sequenced adipose SVF cells in a published scRNA-seq dataset according to the described cell clustering.26Fcgrt gene expression was indicated using violin plot with cell clusters (Macro: macrophage; APC: adipocyte progenitor cells; Endo: endothelial; Mast: mastocyte; Eryth: erythropoiesis; Div: dividing cell; Dend: dendritic cell; Neu: neutrophils cell) in rows and expression level in columns. Western blotting (WB)

[0250] Tissues or cultured cells were homogenized in protein lysis buffer (50 mM Tris-HCl pH 7.4, 180 mM NaCl, 1% Triton X-100, 10% glycerol, and 1 mM EDTA) supplemented with 1 mM DTT, 0.5 mM PMSF, and a phosphatase inhibitor cocktail (Sigma-Aldrich). Protein concentration was determined by a PierceTMBCA Protein Assay kit (ThermoFisher Scientific). Protein extracts (25–50 μg) were resolved by SDS-PAGE, transferred onto the PVDF membrane,Attorney Docket No. 44010.206WO-PCT / / CU24263 blocked with5%skim milk, and incubated with antibodies. For serum proteins, 1 μL plasma was diluted in 100 μL water, and 7–10 μL diluted plasma was subjected to SDS-PAGE. The antibodies used were in the key resources table. Membranes were incubated with HRP-conjugated secondary antibodies and visualized by enhanced chemiluminescence (ECL). Equal loading was confirmed using loading controls. Mouse plasma and total tissue IgG were also detected directly using secondary mouse antibodies conjugated with HRP (Sigma-Aldrich A9044 or GE NA931), both of which gave consistent results as rabbit anti-IgG (Abcam 46540) followed by an anti-Rabbit secondary antibody. WB’s densitometry analyses were performed using Photoshop and normalized to the loading control. IgG half-life determination

[0251] To determine IgG half-life, Applicants intravenously injected biotin-labeled mouse IgG at 200 μg / mouse (ProteinMods) into mice. Applicants collected blood through tail vein bleeding at 3 hours, 1, 3, 7, 14, and 21 days after IgG injection. The diluted plasma was analyzed by WB. Applicants applied goat anti-Biotin HRP (Vector Laboratories SP-3010-1) to probe biotin-labeled exogenous IgG. The blots were quantified and normalized to the 3-hour signal. In Vitro lipolysis assay

[0252] C3H10T1 / 2 cells were differentiated into mature adipocytes, and 30 μM isoproterenol was added to stimulate lipolysis. After IgG (400 μg / mL) pretreatment for 4 hours, cells were treated with vehicle, 1 μM Insulin, or IgG for 0.5 hour at 37° C and then stimulated with isoproterenol for 1 hr.54The medium was then collected for glycerol measurement using the Glycerol Assay Kit (Sigma). In Vitro glucose uptake assay

[0253] Muscle myotubes were differentiated from C2C12 cells by serum starvation. On day 8-9 after differentiation, the differentiated muscle myotubes were pretreated with vehicle or IgG (400 μg / mL) or albumin (400 μg / mL) for 4 hours to detect insulin (100 nM)-stimulated glucose- uptake (n=3 / group) using the Glucose Uptake-GloTMAssay (Promega J1341). Histology, immunohistochemistry, immunofluorescence, and lipid staining

[0254] Dissected adipose and liver tissues were fixed in 10% buffered formalin (Sigma- Aldrich, HT501128-4L) and embedded in paraffin. 5 mm tissue sections were stained with Hematoxylin and eosin (H&E) according to the manufacturer’s instructions. The images wereAttorney Docket No. 44010.206WO-PCT / / CU24263 acquired by optical microscope. Adipocyte sizes were quantified using the ImageJ plugin, Adiposoft.

[0255] For immunohistochemical (IHC) staining of IgG, sections were incubated with anti- mouse IgG (Abcam 46540) or anti-human IgG (Abcam 6858) at a 1:300 dilution overnight and detected according to the general manufacturer’s instructions.

[0256] IgG (Abcam 46540), F4 / 80, and Perilipin 1 were co-immunostained at a 1:300 dilution overnight to detect the colocalization in eWAT.

[0257] Cultured cells were fixed with 10% buffered formalin for 10 minutes at room temperature. After fixation, cells were washed twice with PBS for 5 minutes and further rinsed with 60% isopropanol before incubating with a filtered Oil Red O working solution (Electron Microscopy Sciences, 26079-05) for 15 minutes at room temperature. IR and IgG interaction prediction by AlphaFold 2 and AlphaFold 3

[0258] Multimer structure prediction was performed using AlphaFold 2 and Alphafold multimer V2 (colab.research.google.com / github / sokrypton / ColabFold / blob / main / AlphaFold2 .ipynb, and cosmic-cryoem.org / tools / alphafoldmultimer / ). The Immunoglobulin-like fold domain (IgLD1) (aa501-aa619, according to the homologous superfamily analysis from the InterPro: P15208-IR; www.ebi.ac.uk / interpro / protein / UniProt / P15208 / ) region of the IR and CH3 domain of Ighg were predicted alone and in combination. The same was performed for the sequences for the extracellular domains of IR and the other domains of Ighg. To define the Immunoglobulin-like fold domains for IR and the CH3 domain of Ighg, Applicants used the sequence files of IR and Ighg from the Alphafold and Uniprot databases and mapped the amino acids for alignment. Structures were assembled using ChimeraX Viewer.

[0259] The complex structure of IgG2b-CH3 dimer or albumin binding to IR were validated using AlphaFold 3 by taking the primary amino acid sequences of IR and IgG2b-CH3 or albumin as inputs.39The input mouse IR sequence was the ectodomain of mouse InsR (UniProt P15208), and the copies were 2. The input mouse IgG2b-CH3 sequence was derived from mouse IgG2b (UniProt P01867-2), and the copies were 4. The input mouse albumin sequence was derived from mouse IgG2b (UniProt P07724), and the copies were 2. Structural modeling of the mouse IR ectodomain and IgG CH3 domainAttorney Docket No. 44010.206WO-PCT / / CU24263

[0260] Recent cryo-EM structures of the mouse IR ectodomain at different states have been determined by Li et al.34The inverted U-shape conformation with two insulins bound to the FnIII- 1 domains (PDB code: 7SL1, resolution = 3.40 Å)34and the constructed full-length human IR in active state32were used as the initial structure of the mouse IR ectodomain. The missing residues in the experimental structure were added using SWISS-MODEL, a widely-used web server for protein structure prediction based on homology modeling.55The structures of IgG CH3 monomers and dimers were also modeled using SWISS-MODEL.

[0261] The structures of IR ectodomain—insulin are shown in 2B>Waterhouse< / Au used protein-protein docking methods, Zdock3.0.235and InterEvDock3.36Zdock3.0.2, a rigid-body docking method, was developed by Weng et al., which can generate the docking results for two given protein binding partners.35The scoring function adopted by Zdock3.0.2 employs several terms, such as statistical pair potential, shape complementarity, and electrostatic energy, which have been proven effective in selecting models for near-native docking.56InterEvDock3 is a web server for protein-protein docking based on a more sophisticated method, further combining template- based and free docking and the evolutionary constraints.36The available experimental structure of the mouse IR ectodomain insulin complex was used to validate the effectiveness of Zdock3.0.2 and InterEvDock3 in predicting the structures of the IR ectodomain-IgG CH3 complexes. While the near-native structures of the IR ectodomain-Insulin complex were found among the docking models, these near-native docking models were not in the top 10 models generated by Zdock3.0.2 and the 10 consensus models generated by InterEvDock3. Therefore, Applicants constructed new effective scoring functions for better prediction and selection of the near-native structure of an IR ectodomain‒protein complex.

[0262] Different interfaces and surface areas were employed to construct the new scoring functions.40To divide the interface and surface areas into groups with different biophysical properties, the 20 amino acid (AA) types were categorized into four groups: basic AAs (basic amino acids: H, R, and K), nonpolar AAs (nonpolar or hydrophobic amino acids: I, F, L, W, A, M, P, and V), polar AAs (polar but uncharged amino acids: C, N, G, S, Q, Y, and T), and acidic AAs (acidic amino acids: D and E). In the structures of the protein- protein complex, the receptor (or ligand) surface area was divided into 4 parts corresponding to the four groups of amino acids, and the total surface area of the complex was divided into 8 components: RSA (Receptor SurfaceAttorney Docket No. 44010.206WO-PCT / / CU24263 Area) of basic AAs (A1), RSA of nonpolar AAs (A2), RSA of polar AAs (A3), RSA of acidic AAs (A4); LSA (Ligand Surface Area) of basic AAs (A5), LSA of nonpolar AAs (A6), LSA of polar AAs (A7), and LSA of acidic AAs (A8). The interface area in the complex was divided into 10 parts: basic AAs basic AAs (A9), nonpolar AAs nonpolar AAs (A10), polar AAs polar AAs (A11), acidic AAs acidic AAs (A12), basic AAs nonpolar AAs (A13), basic AAs polar AAs (A14), basic AAs acidic AAs (A15), nonpolar AAs polar AAs (A16), nonpolar AAs acidic AAs (A17), and polar AAs acidic AAs (A18). The total receptor surface area (A19), total ligand surface area (A20), and total interface area (A21) were also employed to construct the models. The interface and surface areas were calculated using Qcontact and dr_sasa,57,58respectively.

[0263] The models with explicit formations were constructed based on no more than 3 variables from the 21 areas. The possible power exponent was selected among 8 values:  1, 0.75,  0.5, 0.25, 0.25, 0.5, 0.75, 1. In total, there are 694568 (nchoosek(21,1)*8 + nchoosek(21,2)*82+ nchoosek(21,3)*83) models (here, nchoosek(n, k) represents the combination number of k variables taken from n items). The effective models would rank the near-native models of the IR ectodomain-insulin complex in the top 10. The effective scoring functions and the corresponding sort orders were recorded to select the near-native structures of the IR ectodomain protein complex in a comprehensive way. If a model is ranked in the top 10 by most of the selected effective functions, it would be the possible near-native structure of the protein-protein complex. The number of ranks % 10 based on the effective functions were counted and recorded for every model. The models were ranked again based on this number, and the new rank was named the ‘‘consensus rank.’’ The near-native structures were selected based on the consensus rank.

[0264] Among the 694568 constructed scoring functions, there were 64 functions for which at least 3 near-native structures were ranked in the top 10 among the 450 docking models (top 300 models generated by Zdock3.0.2 and 150 models provided by InterEvDock3) for the IR ectodomain‒insulin complex. After accounting for redundancy (for example, A10.5and A1 had the same performances, so A10.5was removed), 57 functions were retained. All these models use 3 variables, and the most frequently used areas in these models are A10(interface area of nonpolar Aas ~ nonpolar AAs) and A13 (interface area of basic AAs nonpolar AAs), which indicates that these types of interface areas play a key role in the structure formation of the IR ectodomain‒ insulin complex.Attorney Docket No. 44010.206WO-PCT / / CU24263

[0265] Area affinity was employed to predict the binding affinity in the near-native IR ectodomain-insulin complex and the possible near native structures of IR ectodomain-IgG CH3 complexes.40Area-affinity incorporates 60 area-based models for protein-protein binding affinity prediction. Microscale thermophoresis (MST)

[0266] MST experiments were performed on a Monolith NT.115 (NanoTemper Technologies GmbH) using a red filter set. Proteins were diluted in PBST, and after mixing the different components, samples were loaded into standard capillaries (Nanotemper Technologies). For protein labeling, Applicants used a His-labeling dye with an affinity of 100 nM in combination with 200 nM IR following a standard protocol. For the insulin-IR titration assay, an equal volume of labeled IR was mixed with insulin to obtain a final concentration ranging from 0.0305 nM to 4 μM. Capillaries were then loaded, and the LED was set to 20%–60% excitation using medium MST power. For the IgG-IR titration assay, the IgG sample at various concentrations ranging from 800 μM to 24.41 nM was mixed with a fixed concentration of fluorescent IR. For the IgG competitive binding assay, IgG at a physiologically relevant concentration of 0.52 μM or a high- concentration of 250 μM was preincubated with the labeled IR, then employed in the Insulin-IR titration assay. For insulin effects on the IgG-IR binding assay, 20 nM insulin was preincubated with the labeled IR, followed by the IgG-IR titration assay. In all MST protocols, MST-on time was measured at 1.5 s after infrared laser heating. The binding affinity Kd value was calculated using GraphPad. The fitted curve uses log (agonist) vs. response (three parameters), and the KD calculation formula uses KD =LogEC50, Y=Bottom + (Top-Bottom) / (1+10^((LogEC50-X))). All results are presented as mean ± SEM. Surface plasmon resonance (SPR)

[0267] SPR experiments were performed on Biacore instrument (Cytiva Biacore 8K+). CM5 sensor chip was installed on the Biacore instrument according to the standard procedure. Mouse recombinant IR Protein (7544-MR, R&D) was diluted with activation buffer (10 μM sodium acetate, pH=4.5) and immobilized with amine coupling (Cytiva) on the chip. Insulin was used at concentrations ranging from 6.25 nM to 200 nM and injected separately on the surface of the ligand (PBS buffer, pH=7.5) chip in the absence or presence of 50 μM IgG or albumin. The parameters of SPR were set as follows: 25° C; flow rate: 30 mL / min; contact time: 120 s;Attorney Docket No. 44010.206WO-PCT / / CU24263 disassociation time: 360 s. The kinetic parameters of the binding reactions were calculated and analyzed using Biacore Insight Control Software. Quantification And Statistical Analysis

[0268] Statistical analyses were performed using Prism 9 software (GraphPad). Applicants used a two-tailed Student’s t-test for comparisons between the two groups, one-way ANOVA for comparisons among three or more groups, and two-way ANOVA to examine effects of two variables. p<0.05 is used to declare statistical significance. All results are presented as mean ± SEM (standard error). Statistical details pertaining to each experiment, including n-values, can be found in the figure legends. Example 3 References 1. Kahn, B.B., and Flier, J.S. (2000). Obesity and insulin resistance. J. Clin. Invest. 106, 473– 481. doi.org / 10.1172 / JCI10842. 2. Jin, X., Qiu, T., Li, L., Yu, R., Chen, X., Li, C., Proud, C.G., and Jiang, T. (2023). Pathophysiology of obesity and its associated diseases. Acta Pharm. Sin. B 13, 2403–2424. doi.org / 10.1016 / j.apsb.2023. 01.012. 3. Haeusler, R.A., McGraw, T.E., and Accili, D. (2018). Biochemical and cellular properties of insulin receptor signalling. Nat. 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[0269] Various modifications and variations of the described methods, pharmaceutical compositions, and kits of the invention will be apparent to those skilled in the art without departing from the scope and spirit of the invention. Although the invention has been described in connection with specific embodiments, it will be understood that it is capable of further modifications and that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the invention that are obvious to those skilled in the art are intended to be within the scope of the invention. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure come within known customary practice within the art to which the invention pertains and may be applied to the essential features herein before set forth.

Claims

Attorney Docket No. 44010.206WO-PCT / / CU24263 CLAIMS What is claimed:

1. A method of treating tissue integrity, metabolic health, inflammation, and / or fibrosis in a subject comprising administering to the subject one or more agents that reduce IgG levels, wherein the subject is protected from tissue degeneration, reduced metabolic health, inflammation, and / or fibrosis; or wherein tissue integrity and / or metabolic health is restored in the subject; and / or wherein inflammation and / or fibrosis is reduced in the subject.

2. The method of claim 1, wherein the one or more agents reduce IgG recycling.

3. The method of claim 2, wherein the one or more agents comprise a neonatal fragment crystallizable (Fc) receptor (FcRn) inhibitor.

4. The method of claim 3, wherein the FcRn inhibitor is an antibody.

5. The method of claim 3, wherein the FcRn inhibitor is a peptide comprising the consensus peptide sequence GHFGGXY.

6. The method of any one of claims 3 to 5, wherein the FcRn inhibitor is selected from the group consisting of efgartigimod, rozanolixizumab, nipocalimab, orilanolimab, batoclimab, CSL730 / M230, ABY-039, SYN1436, and SYN1327.

7. The method of claim 3, wherein the FcRn inhibitor is an antisense oligonucleotide (ASO), RNAi, or a CRISPR system capable of targeting mRNA encoding for FcRn.

8. The method of any one of claims 1 to 3, wherein the one or more agents that reduce IgG levels comprise an antibody, peptide, small molecule, antisense oligonucleotide (ASO), RNAi, or CRISPR system capable of targeting mRNA.

9. The method of any one of claims 1 to 8, wherein the subject is over 30, 60, or 70 years old.Attorney Docket No. 44010.206WO-PCT / / CU24263 10. The method of any one of claims 1 to 9, wherein the subject is being treated for age- associated tissue degeneration and / or reduced metabolic health.

11. The method of any one of claims 1 to 10, wherein the subject is obese, whereby obesity is treated.

12. The method of any one of claims 1 to 11, wherein the subject has dyslipidemia, whereby dyslipidemia is treated.

13. The method of any one of claims 1 to 12, wherein the subject has type 2 diabetes, whereby insulin resistance is treated.

14. The method of any one of claims 1 to 13, wherein the one or more agents are targeted to macrophages.

15. The method of any one of claims 1 to 14, wherein the IgG levels are reduced to a calorie restriction (CR) reference level, whereby IgG levels are not eliminated.

16. The method of any one of claims 1 to 15, wherein the IgG levels are reduced by at least 30%, 40%, 50%, 60%, 70%, 80%, or 90%.

17. The method of any one of claims 1 to 16, wherein the one or more agents reduce IgG levels in white adipose tissue (WAT), brown adipose tissue (BAT), liver, kidney, and / or muscle.

18. The method of any one of claims 1 to 17, wherein adipose tissue integrity is restored.

19. A method of determining the biological age of a subject comprising determining the plasma or tissue IgG level in the subject and comparing to one or more control reference levels.

20. The method of claim 19, wherein the one or more control reference levels are the average plasma or tissue IgG levels for control subjects at different ages.

21. The method of claim 19 or 20, wherein the tissue is white adipose tissue (WAT).Attorney Docket No. 44010.206WO-PCT / / CU24263 22. A method of determining a reduction in the biological age of a subject comprising determining the plasma or tissue IgG level in a first sample obtained from the subject at a first time point and comparing to the plasma or tissue IgG level in a second sample obtained from the subject at a second time point, whereby a reduction in the plasma or tissue IgG level indicates a reduction in the biological age of the subject.

23. The method of claim 22, wherein the subject consumed a healthier diet between the first and second time point.

24. The method of claim 22, wherein the subject was treated with an age reducing therapy between the first and second time point.

25. The method of any one of claims 19 to 24, wherein the IgG level is determined by ELISA, western blot, mass spectrometry, or isotope labelling.

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