Methods for modeling and reducing cerebrovascular pathologies

Abstract

Methods for making a reconstructed human brain tissue are provided. Also provided are methods for evaluating whether a drug candidate inhibits amyloid deposition.

Description

[0001] Docket No. 084284.00346

[0002] METHODS FOR MODELING AND REDUCING CEREBROVASCULAR PATHOLOGIES

[0003] CROSS-REFERENCE TO RELATED APPLICATIONS

[0004] This application claims the benefit under 35 U. S. C. §119(e) of the earlier filing date of U. S. Provisional Patent No. 63 / 727,224, filed on December 3, 2024, which is hereby incorporated by reference in its entirety.

[0005] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0006] This invention was made with government support under Grant No. 1R01 AG089533-01 awarded by the National Institute on Aging, Grant No. NS115064 awarded by the National Institute of Neurological Disorders and Stroke, and Grant No. 80ARC022CA004 awarded by the National Aeronautics and Space Administration. The government has certain rights in the invention.

[0007] FIELD

[0008] This disclosure relates generally to methods for modeling and reducing cerebrovascular pathologies.

[0009] BACKGROUND

[0010] Cerebrovascular disease is a major, but poorly understood feature of Alzheimer’s disease (AD). In AD, the nearly 400 miles of blood vessels that feed the human brain accumulate amyloid and degenerate. The causes of these vascular phenotypes, however, remain unclear. The vast majority of AD cases are classified as late-onset AD, where aging and genetic factors play a major role in disease risk. The presence of the APOE4 allele is the strongest genetic risk factor for AD and is associated with cerebrovascular degeneration, including vascular amyloid deposition and fibrosis. Homozygosity for the APOE4 allele has been identified as a unique and highly penetrant form of the disease, highlighting the need to develop preventative therapies for this patient population. The APOE4 allele differs from the more common APOE3 allele by encoding a single amino acid substitution (Cysl 12 -> Argl 12). Yet individuals carrying two copies of the APOE4 allele face up to 16-fold increased risk of developing AD. Furthermore, 40-65 % of all individuals with AD carry at least one APOE4 Docket No. 084284.00346

[0011] copy, underscoring the allele’s relevance to disease pathogenesis. Of note, because carriers of the APOE4 allele exhibit a very fragile cerebrovasculature, the only disease-modifying AD therapeutic, an anti-amyloid monoclonal antibody for treating early stage AD, is contraindicated in APOE4 carriers due to a high risk of hemorrhage and edema.

[0012] There are currently no FDA-approved treatments to treat middle or late-stage AD. Consequently, there remains a need to develop accurate modeling systems of AD to identify effective treatments.

[0013] SUMMARY

[0014] This disclosure relates to methods for modeling and reducing cerebrovascular pathologies in a neurodegenerative disease. In one embodiment, the neurodegenerative disease Alzheimer's disease (AD).

[0015] In one aspect, provided is a method for making a reconstructed human brain tissue, the method comprising:

[0016] a) differentiating human induced pluripotent stem cells (iPSCs) into iPSC-derived mural cells (iMCs), wherein the iPSCs express an allelic variant oiAPOE. and

[0017] b) co-culturing the iMCs with human neurons, astrocytes, microglia, oligodendroglia, endothelial cells, and pericytes.

[0018] In one embodiment, the iPSCs have an APOE3 / 3, APOE3 '4, or APOE4 / 4 genotype. In one embodiment, the co-culturing occurs within a three-dimensional matrix. In some embodiments, the method further comprises a step c) of inhibiting transforming growth factor beta (TGF-P) signaling by contacting the reconstructed human brain tissue with a TGF-P inhibitor. In some embodiments, the TGF-P inhibitor is a small molecule, a small hairpin RNA (shRNA), an aptamer, or an antibody or antigen-binding fragment thereof. In some embodiments, the small molecule is SB431542, A83-01, or Galunisertib (LY2157299).

[0019] In some embodiments, the method further comprises a step of c) stimulating TGF-P signaling by contacting the reconstructed human brain tissue with a TGF-P agonist. In some embodiments, the TGF-P agonist is TGFpi, TGFP2, or TGFP3.

[0020] In one embodiment, the iMCs overexpress fibronectin (FNP). In one embodiment, the iMCs express an FN1 variant. In one embodiment, the iMCs have reduced FNJ levels. Docket No. 084284.00346

[0021] In some embodiments, the iPSCs have been isolated from a subject that has AD. In one aspect, provided is a method for evaluating whether a drug candidate inhibits amyloid deposition in vitro, comprising:

[0022] a) contacting the reconstructed human brain tissue described herein with the drug candidate; and

[0023] b) quantifying amyloid deposition in the reconstructed human brain tissue as compared to amyloid deposition levels in the reconstructed human brain tissue in the absence of the drug candidate.

[0024] In one embodiment, provided is a method for evaluating whether a drug candidate inhibits amyloid deposition in a reconstructed human brain tissue, the method comprising: contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying a level of amyloid deposition in the reconstructed human brain tissue as compared to a control level of amyloid deposition levels in the reconstructed human brain tissue in the absence of the drug candidate.

[0025] In one embodiment, provided is a method for evaluating whether a drug candidate inhibits fibronectin deposition in a reconstructed human brain tissue, the method comprising contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying the level of fibronectin deposition in the reconstructed human brain tissue as compared to a control level of fibronectin deposition in the reconstructed human brain tissue in the absence of the drug candidate.

[0026] In one embodiment, provided is a method for evaluating whether a drug candidate is able to cross an in vitro brain-blood barrier (iBBB), the method comprising: providing a reconstructed human brain tissue described herein, wherein the reconstructed human brain tissue further comprises an iBBB comprising a proximal side and a distal side, contacting the proximal side of the iBBB with the drug candidate, and quantifying the amount of drug candidate that crosses the iBBB to reach the distal side of the iBBB.

[0027] In one embodiment, provided is a method for evaluating whether a drug candidate induces neurotoxicity in a reconstructed human brain tissue, the method comprising contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying Docket No. 084284.00346

[0028] the level of neurotoxicity in the reconstructed human brain tissue as compared to a control level of neurotoxicity in the reconstructed human brain tissue in the absence of the drug candidate.

[0029] In one embodiment, provided is a method for evaluating whether a drug candidate induces reduces tau pathology in a reconstructed human brain tissue, the method comprising contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying the level of tau pathology in the reconstructed human brain tissue as compared to a control level of tau pathology in the reconstructed human brain tissue in the absence of the drug candidate.

[0030] In one embodiment, provided is a method for evaluating whether a drug candidate induces reduces cerebral amyloid angiopathy (CAA) pathology in a reconstructed human brain tissue, the method comprising contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying the level of CAA pathology in the reconstructed human brain tissue as compared to a control level of CAA pathology in the reconstructed human brain tissue in the absence of the drug candidate.

[0031] In one embodiment, provided is a method for evaluating whether a drug candidate induces reduces Lewy Body pathology in a reconstructed human brain tissue, the method comprising contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying the level of Lewy Body pathology in the reconstructed human brain tissue as compared to a control level of Lewy Body pathology in the reconstructed human brain tissue in the absence of the drug candidate.

[0032] In some embodiments, the drug candidate is selected from the group consisting of a small molecule, a nucleic acid, a peptide, a polypeptide, an antibody, and an antibody fragment.

[0033] In one aspect, provided is a method of reducing or preventing APOE4 vascular dysfunction in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor. In one aspect, provided is a method of reducing or preventing my ofibroblast accumulation in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor. In one aspect, provided is a method of reducing or preventing cerebrovascular fibrosis in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor. In one aspect, provided is a method of reducing or preventing amyloid deposition in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor. In one aspect, provided is a method of reducing or preventing AD progression in a subject in need thereof, the method comprising administering to the subject a Docket No. 084284.00346

[0034] TGF-P inhibitor. In one aspect, provided is a method of reducing fibronectin expression levels in a subject in need thereof, the method comprising administering to the subject a TGF-β inhibitor, wherein the TGF-β inhibitor reduces fibronectin expression levels by at least about 20%.

[0035] In some embodiments, the TGF-P inhibitor is a small molecule, an shRNA, an aptamer, or an antibody or antigen-binding fragment thereof. In some embodiments, the small molecule is SB431542, A83-01, or Galunisertib (LY2157299). In one embodiment, the subject is a human. In one embodiment, the subject has a neurodegenerative disease. In one embodiment, the neurodegenerative disease is AD. In one embodiment, the subject is homozygous for APOE4. In one embodiment, the subject is heterozygous for APOE4.

[0036] BRIEF DESCRIPTION OF THE DRAWINGS FIGS. 1A-1C demonstrate that single-nuclei analysis of post-mortem human brain reveals a shift in APOE4 mural cells from pericytes to extracellular matrix-producing, myofibroblast-like cells. FIG. 1A shows graphs of UMAP (Uniform Manifold Approximation and Projection) visualization of mural cell subclusters in APOE3 / 3 individuals and APOE4 carriers (n = 4 individuals per genoty pe). The circled aSMC subcluster was analyzed in FIG.

[0037] 1C. FIG. IB depicts differential abundance analysis of cell neighborhoods in APOE4 carriers compared to APOE3 / 3 individuals for each mural cell subcluster along with a model highlighting the hypothesized transition (AAPOE4 mural cells to a fibrotic-like state. Gray dots represent non-differentially abundant neighborhoods between genoty pes whereas other dots represent significantly (FDR < 10%) down regulated and upregulated neighborhoods in APOE4 carriers compared to APOE3 3, respectively. All analysis was performed with MiloR. FIG. 1C shows graphs of ECM and myofibroblast scores of aSMCs with APOE3 and APOE4 genotypes. Scores were assigned based on expression of ECM and myofibroblast genes from publicly available gene sets. Statistical analysis was performed via Wilcoxon rank-sum test.

[0038] FIGS. 2A and 2B illustrate that iPSC-derived APOE4 / 4 mural cells (iMCs) adopt a fibrotic-like state. FIG. 2A shows graphs of FPKM (Fragments Per Kilobase of transcript per Million mapped reads) values of ACTA2 (actin alpha 2) and FN1 (fibronectin) from bulk RNA-sequencing of iMCs (n = 3 per genotype). FIG. 2B shows a dot blot of fibronectin in conditioned media from iMCs. Quantification was performed for signal intensity (n = 4 per genotype). Statistical analysis was performed via unpaired t-tests. Docket No. 084284.00346

[0039] FIGS. 3A-3C demonstrate that inhibition of TGF-P signaling attenuates the fibrotic phenotype of APOE4 / 4 iMCs. FIG. 3A shows three of the top fifteen most significant upregulated GO: MP terms mAPOE4 / 4 compared to APOE3 3 iMCs. FIG. 3B shows graphs of FPKM values of TGFBR1, TGFBR2, and TGFBR3 from bulk RNA-sequencing of iMCs (n = 3 per genotype; statistical analysis via unpaired t-test. FIG. 3C shows quantification of a-SMA and fibronectin volumes within NG2 (Neural / glial antigen 2)-positive regions of APOE3 / 3 and APOE4'4 iMCs treated with 10 pM SB431542 (TGF-P inhibitor) or nothing (control) for 96 hours (6 images taken per biological replicate, n = 4 per genotype and condition; statistical analysis via two-way ANOVA. Cells were stained for Hoechst, NG2, a-SMA, and fibronectin.

[0040] FIGS. 4A and 4B demonstrate that iPSC-derived multi-cellular integrated brains (miBrains) recapitulate the perivascular fibrosis and amyloidosis phenotypes observed in APOE4 carriers. FIG. 4A shows quantification of a-SMA volume normalized by nuclei volume and the percentage of CD144 volume that is covered by NG2 (pericyte coverage) in APOE3 / 3 and APOE4 / 4 miBrains. APOE3 / 3 and APOE4 / 4 miBrains immunostained for Hoechst, CD 144, a-SMA, and NG2. FIG.4B shows quantification of fibronectin and collagen I volumes normalized by nuclei volume, normalized amyloid volumes using three different antibodies (D54D2, 12F4, 6E10), and the association between normalized fibronectin and amyloid volumes via Pearson correlation analysis of miBrains (6 images per biological replicate, n = 6 per genotype; statistical analysis via unpaired t-test). On the x axis bars on the left for each indicated antibody represent APOE3 / 3, while bars on the right for each indicated antibody represent APOE4 / 4. miBrains were immunostained for Hoechst, PECAM (platelet and endothelial cell adhesion molecule 1). collagen I, amyloid (D54D2 antibody), and fibronectin.

[0041] FIGS. 5A-5E illustrate that a myofibroblast-like mural cell population is enriched in the APOE4 brain. FIG. 5A is a graph that quantifies normalized NG2 per VE-CAD from images of post-mortem human hippocampus stained for markers of pericytes (NG2) and blood vessels (VE-CAD) in APOE3 / 3 and APOE4 carriers. Pericyte coverage for each genotype was calculated by quantifying the overlapping area of pericyte and blood vessel staining, expressed relative to APOE3 / 3. Data points represent individuals (n = 13 APOE3 / 3 and n = 7 APOE4 carriers). Bars are group means ± SEM. P-values were calculated using an unpaired two-tailed Student’s t-test. FIG. 5B is a graph that quantifies normalized a-SMA per nuclei from images Docket No. 084284.00346

[0042] of APOE4 carrier and non-carrier post-mortem human hippocampus stained for the smooth muscle cell marker a-SMA. The area positive for a-SMA was quantified, normalized to nuclei, and expressed relative to APOE3 / 3. Data points represent individuals (n = 11 APOE3 / 3 and n = 9 APOE4 carriers). Bars are group means ± SEM. P values were calculated using an unpaired two-tailed Student’s t-test. FIG. 5C depicts subject-level predicted proportion of myofibroblasts in non-AD individuals, as estimated by the binomial generalized linear model. Data points represent individuals (n = 13 per genotype). Bars are group means ± SEM. P-values are derived from the binomial GLM. FIG.5D shows graphs of normalized vascular NG2 or a-SMA from images of images of small vessels (<6 pm) in the corpus callosum of age- (9 to 10 months of age) and sex-matched APOE3 / 3 and APOE4 / 4-TR mice stained for markers of blood vessels (lectin), myofibroblasts (a-SMA), and pericytes (NG2). Scale bar, 10 pm. The area positive for a-SMA was quantified, normalized to nuclei, and expressed relative to APOE3 / 3. Pericyte coverage was measured by quantifying the overlapping NG2 and lectin area, normalized to APOE3 / 3. Data points represent mean values from individual mice (n = 6 images per mouse, n = 3 mice per genotype). Bars are mean group values ± SEM. P-values were calculated using unpaired two-sample Student’s t-tests. FIG. 5E shows graphs of normalized 3D pericyte overage and normalized a-SMA from images of isogenic APOE3 / 3 and APOE4 / 4 miBrains stained for markers of blood vessels (CD 144), myofibroblasts (a-SMA), and pericytes (NG2). Three-dimensional pericyte coverage was measured by the overlapping NG2 and CD 144 volume, normalized to the total CD 144 volume, and expressed relative to APOE3 / 3. The area positive for a-SMA was quantified, normalized to nuclei, and expressed relative to APOE3 / 3. Data points represent mean values from individual miBrains (n = 6 images per miBrain, n = 6 miBrains per genotype). Bars are mean group values ± SEM. P-values were calculated using unpaired two-sample Student’s t-tests.

[0043] FIGS. 6A and 6B demonstrate that APOE4 promotes a pericyte-to-myofibroblast transition. FIG. 6A shows graphs that quantify normalized 3D pericyte coverage and normalized a-SMA from images of isogenic APOE3 / 3, APOE4 / 4, and APOE4 / 4 miBrains integrated with APOE3 / 3 iMCs stained for PECAM, a-SMA, and NG2. Three-dimensional pericyte coverage was measured by the overlapping NG2 and CD 144 volume, normalized to the total CD144 volume, and expressed relative to APOE3 / 3. The area positive for a-SMA was quantified, normalized to nuclei, and expressed relative to APOE3 / 3. Data points represent mean values from individual miBrains (n = 6 images per miBrain, n = 6 miBrains per Docket No. 084284.00346

[0044] genotype). Bars are mean group values ± SEM. P-values were calculated using a one-way ANOVA with Dunnett’s multiple comparisons test. FIG. 6B is a graph of Subject-level predicted proportion of intermediate cells (ACTA2+ / CSPG4+). Data points represent individuals (n = 25 APOE3 / 3, n = 24 APOE4 carriers). Bars are group means ± SEM. P-values are derived from the binomial GLM.

[0045] FIGS. 7A-7G show that myofibroblast-derived fibronectin drives amyloid accumulation in APOE4 models. FIG. 7A shows quantification of normalized fibronectin and a-SMA per nuclei area from images of small vessels in the corpus callosum of APOE3 / 3-TR and APOE4 / 4-TR mice stained for lectin, a-SMA, and fibronectin. FIG. 7B shows quantification of normalized fibronectin per nuclei area from images of APOE3 / 3 and APOE4 / 4 miBrains stained for PECAM and fibronectin. FIG. 7C shows quantification of FN1 expression across cell types in the cerebrovascular atlas. FN1 expression was aggregated per cell type for each individual. Individuals missing more than one cell type were excluded from the analysis. Data points represent individuals (n = 57). Bars are group means ± SEM. P-values were calculated using a repeated measures mixed-effects analysis with the Geisser-Greenhouse correction and Dunnett’s multiple comparisons test. FIG. 7D shows quantification of normalized amyloid per nuclei area from images of isogenic pairs of APOE3 / 3 and APOE4 / 4 miBrains stained for three amyloid antibodies targeting different epitopes of the amyloid-P peptide. On the x axis, dots on the left for each indicated antibody represent APOE3 / 3, while dots on the right for each indicated antibody represent APOE4 / 4. FIG.7E shows quantification of normalized amyloid-P (D54D2) and normalized fibronectin per nuclei area from images of isogenic APOE3 / 3, APOE4 / 4, and APOE4 / 4 miBrains integrated with APOE3 / 3 iMCs stained for PECAM, fibronectin, and amyloid (D54D2). Data represent two independent experiments. In the first experiment, APOE3 / 3 and APOE4 / 4 w ere compared using an unpaired tw o-sample Student’s t-test. In the second experiment, APOE4 / 4 w as compared to APOE4 / 4 with APOE3 / 3 iMCs using an unpaired two-sample Student’s t-test. P-values shown reflect these independent comparisons. FIG. 7F shows quantification of normalized amyloid-P (12F4) and normalized fibronectin per nuclei area from images of APOE4 / 4 miBrains integrated with either iMCs transduced with scramble shRNA (control) or shRNA targeting FN1 stained for fibronectin and amyloid (12F4). FIG. 7G shows quantification of normalized amyloid-P (D542D) per nuclei area from images of treated encapsulated E3 / 3 iPSC-derived endothelial cells (iECs) with fibronectin and amyloid mixtures. For the control group, iECs were left untreated. For the Docket No. 084284.00346

[0046] experimental groups, iECs were treated with either 20 nM amyloid-β 1-40 and 1-42 or 20 nM amyloid-β 1-40 and 1-42 mixed with 50 ng / mL fibronectin for 96 hrs. iECs were then fixed and stained for amyloid (D54D2). The area positive for a-SMA, fibronectin, or amyloid immunoreactivity was quantified, normalized to nuclei, and expressed relative to APOE3 / 3 or APOE4 / 4. Data points represent mean values from individual miBrains (n = 6 images per miBrain, n = 6 miBrains per condition) or mice (n = 6 images per mouse, n = 4 mice per genotype). Bars are mean group values ± SEM. Unless stated otherwise, p-values were calculated using a one-way ANOVA with Dunnett’s multiple comparisons test.

[0047] FIGS. 8A-8C illustrate that increased TGF-P signaling in the APOE4 brain drives the pericyte-to-myofibroblast transition. FIG. 8A shows TGF-P expression scores of pericytes from APOE4 carriers and APOE3 / 3 individuals. A TGF-P module scores were calculated using Seurat’s AddModuleScore() function based on the specified genes. The scores from Pericyte 1 and Pericyte 2 cells were then averaged per individual. Data points represent individuals (n = 106 APOE3 / 3, n = 103 APOE4 carriers). Bars are group medians. P-values were calculated using the Wilcoxon rank-sum test. FIG. 8B shows quantification of normalized pSMAD2+ vascular nuclei from images of APOE3 / 3 and APOE4 / 4 miBrains and TR-mice stained for a vascular marker (PECAM / lectin) and pSMAD2. Nuclei along the vasculature were classified as pSMAD2+ using an intensity -based threshold in CellProfiler, normalized to the total number of vascular nuclei, and expressed relative to APOE3 / 3. Data points represent mean values from individual miBrains or mice (n = 6 images per miBrain / mouse, n = 6 miBrains and n = 4 mice per genotype). On the x axis, dots on the left for each indicated antibody represent APOE3 / 3, while dots on the right for each indicated antibody represent APOE4 / 4. Bars are mean group values ± SEM. P-values were calculated using unpaired two-sample Student’s t-tests. FIG.8C shows quantification of TGF R expression in isogenic pairs of iMCs from two donor lines. MSSM3 line: FPKM values from iMC bulk RNA-seq dataset normalized to APOE3 / 3. Data points represent individual bulk RNA-sequencing replicates (n = 3 per genotype). Bars are mean group values ± SEM. Adjusted p-values were calculated using the R package limma to account for multiple comparisons. sAD line: TGFfiR expression in iMCs via qRT-PCR relative to APOE3 / 3. Data points represent mean values from individual wells of iMCs (3 qRT-PCR replicates per well, 4 wells per genotype). Bars are mean group values ± SEM. P-values were calculated using unpaired two-sample Student’s t-tests.

[0048] FIGS. 9A and 9B demonstrate that TGF-P inhibition reverses APOE4-driven myofibroblast accumulation, cerebrovascular fibrosis, and amyloid deposition. FIG.9A shows Docket No. 084284.00346

[0049] quantification of normalized 3D pericyte coverage from images of myofibroblast phenotypes after TGF-p> inhibition in miBrains. For the control group, APOE3 / 3 and APOE4 / 4 miBrains were treated with a DMSO vehicle for two weeks. For the experimental group, APOE4 / 4 miBrains were treated with 10 pM SB431542 for two weeks. miBrains w ere then fixed and stained for PECAM, a-SMA, and NG2. Three-dimensional pericyte coverage w as measured by the overlapping NG2 and PECAM volume, normalized to the total PECAM volume and expressed relative to APOE4 / 4. The area positive for a-SMA was quantified, normalized to nuclei, and expressed relative to APOE4 / 4. Data points represent mean values from individual miBrains (n = 6 images per miBrain, n = 6 miBrains per condition). Bars are mean group values ± SEM. P-values were calculated using a one-way ANOVA with Dunnett's multiple comparisons test. FIG. 9B shows quantification of normalized fibronectin and normalized amyloid-P (D54D2) per nuclei area from images of cerebrovascular fibrosis and amyloid deposition in miBrains after TGF-P inhibition. For the control group, APOE3 / 3 and APOE4 / 4 miBrains were treated with a DMSO vehicle for 4 weeks. For the experimental group, APOE4 / 4 miBrains were treated with either 50 pM SB431542 or 50 pM galunisertib for 4 weeks. miBrains were then fixed and stained for PECAM, fibronectin, and amyloid (D54D2). The data represent two independent experiments. In the first experiment, APOE3 / 3 DMSO, APOE4 / 4 DMSO, and APOE4 / 4 treated with galunisertib were compared using a one-way ANOVA with Dunnett's multiple comparisons test. In the second experiment, APOE4 / 4 DMSO was compared to APOE4 / 4 treated with SB431542 using an unpaired two-sample Student’s t-t-test. P-values shown reflect these independent comparisons. Data points represent mean values from individual miBrains (n = 6 images per miBrain, n = 6 miBrains per condition). Bars are mean group values ± SEM.

[0050] DETAILED DESCRIPTION

[0051] This disclosure relates to compositions and methods for modeling a cerebrovascular pathology in a neurodegenerative disease in human brain tissue. In some embodiments, the neurodegenerative disease is Alzheimer’s disease (AD). Also provided is a fully iPSC-derived, multi-cellular integrated model of the human brain (miBrain) that comprises iPSC-derived mural cells (iMCs). In some embodiments, the iMCs express an allelic variant of APOE (Apolipoprotein E). In some embodiments, the two allelic variants of APOE that an individual carries areAPOES and APOE3 (also referred to herein as aAPOE3 / 3 genotype) or APOE4 and APOE4 (also referred to herein as aAPOE4 / 4 genotype). Docket No. 084284.00346

[0052] APOE is a protein that associates with lipid particles. APOE has various functions including lipid metabolism. In particular, APOE plays a key role in regulating the clearance of lipoproteins. APOE is largely produced by astrocytes, and transports cholesterol to neurons via APOE receptors. There are three major isoforms of APOE arising from different alleles: APOE2, APOE3, and APOE4. These isoforms differ from one another by encoding for Cysteine / Arginine substitutions at 2 positions, rs429358 (T / C polymorphism at position 19:44908684 on chromosome 19 in the Genome Reference Consortium Human Build 38 patch release 2 / GRCh38.p2) and rs7412 (C / T polymorphism at position 19:44908822 on chromosome 19 in GRCh38.p2), affecting residues 130 and 176 in the synthesized proteins containing the signal-peptide and residues 112 and 158 in the mature protein. APOE4 harbors a C at position 19:44908684 and position 19:44908822. APOE2 harbors a T at both positions 19:44908684 and 19:44908822. Lastly, APOE3 harbors a T at position 19:44908684 and a C at position 19:44908822. See U. S. Patent Publication No. 20190338363, which is herein incorporated by reference in its entirety7.

[0053] An '‘allele” is a variant or alternative form of a gene that exists in a population. An individual normally inherits two such alleles for each gene at conception. For example, an individual may have an APOE3 / 4 genotype, meaning the individual carries one APOE3 and one APOE4 allele.

[0054] The miBrain described herein is composed of six major brain cell types (neurons, astrocytes, microglia, oligodendroglia, endothelial cells, and pericytes) cultured together within a 3D matrix. miBrains can develop AD-relevant pathologies while allowing for the manipulation of individual cell types to tease apart cell type-specific mechanisms.

[0055] As used herein, a “reconstructed human brain tissue” refers to an engineered brain tissue that mimics tissue found in a human brain. In some embodiments, the reconstructed human brain tissue comprises (i) human iPSC-derived mural cells expressing an allelic variant of APOE, and (ii) human neurons, astrocytes, microglia, oligodendroglia, endothelial cells, and pericytes.

[0056] As used herein, “mural cells” refers to a heterogenous population of cells comprising smooth muscle cells and pericytes of the vasculature. Docket No. 084284.00346

[0057] As used herein, “modeling a cerebrovascular pathology” refers to mimicking the conditions that are present in a cerebrovascular pathology such as perivascular fibrosis and amyloid accumulation. Modeling a cerebrovascular pathology enables one to replay events or neurological diseases in a controlled laboratory setting.

[0058] I. Methods for making a reconstructed human brain tissue

[0059] In one aspect, provided is a method for making a reconstructed human brain tissue, the method comprising:

[0060] a) differentiating human induced pluripotent stem cells (iPSCs) into IPSC-derived mural cells (iMCs), wherein the iPSCs express an allelic variant of APOE, and

[0061] b) co-culturing the iMCs with human neurons, astrocytes, microglia, oligodendroglia, endothelial cells, and pericytes.

[0062] In one embodiment, the co-culturing occurs within a three-dimensional matrix as known in the art.

[0063] In one embodiment, the iPSCs have been isolated from a subject that has been diagnosed with Alzheimer’s disease.

[0064] In one embodiment, the human neurons, astrocytes, microglia, oligodendroglia, endothelial cells, and pericytes are derived from a subject who has Alzheimer’s disease. In one embodiment, the human neurons, astrocytes, microglia, oligodendroglia, endothelial cells, and pericytes are derived from a subject who does not have Alzheimer’s disease. In one embodiment, the human neurons, astrocytes, microglia, oligodendroglia, endothelial cells, and pericytes are engineered to express an APOE allelic variant (such as APOE3 / 3 or APOE4 / 4), for example by editing the cells’ genotype with CRISPR. For example, the neurons, astrocytes, microglia, oligodendroglia, endothelial cells, and pericytes can be derived from a subject who has an APOE3 / 3 genotype and does not have Alzheimer's disease. In this case, CRISPR can be used to engineer these cells to carry an APOE4 / 4 pair of alleles. In another example, the human neurons, astrocytes, microglia, oligodendroglia, endothelial cells, and pericytes are derived from a subject who has an APOE4 / 4 genotype and Alzheimer's disease. In this case. CRISPR can be used to engineer these cells to carry an APOE3 / 3 pair of alleles.

[0065] The profibrotic cytokine TGF-P has been linked to vascular degeneration, which implicates dysregulation of the extracellular matrix in APOE4-associated cerebrovascular pathology. Thus, inhibiting TGF-P in a subject with is homozygous for the APOE4 allele may be beneficial in treating AD. Docket No. 084284.00346

[0066] In some embodiments, the method for making a reconstructed human brain tissue further comprises a step c) of inhibiting transforming growth factor beta (TGF-P) signaling by contacting the reconstructed human brain tissue with a TGF-P inhibitor, e.g., by contacting the reconstructed human brain tissue with a TGF-P inhibitor.

[0067] As used herein, “transforming growth factor beta (TGF-P) signaling” is a signaling pathway involved in the regulation of cell growth, differentiation, and development in various biological systems. As used herein, a “TGF-P inhibitor” is a composition that reduces or eliminates TGF-P signaling as compared to a control.

[0068] As used herein, the terms “decrease,” “reduce,” “downregulate,” and “inhibit” all generally refer to a decrease by a statistically significant amount relative to a control. However, for avoidance of doubt, the term “reduced,” “decrease.” “reduce.” or “inhibit” means a decrease by at least 5% (e.g., 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%) as compared to a reference level, for example, a decrease by at least about 10%, a decrease by at least about 20%, or at least about 30%, or at least about 40%, or at least about 50%, or at least about 60%, or at least about 70%, or at least about 80%. or at least about 90% or up to and including a 100% decrease (e.g., absent level as compared to a reference sample), or any decrease of 10-100% as compared to a reference level. In some embodiments, these terms refer to a decrease of 10-20%, 10-30%, 10-40%, 10-50%, 10-60%, 10-70%, 10-80%, 10-90%, 10-100%, 10-110%, 10-120%, 10-130%, 10-140%, 10-150%, 10-160%. 10-170%, 10-180%, 10-190%, 10-200%, 10-210%. 10-220%, 10-230%, 10-240%, 10-250%, 10-260%, 10-270%, 10-280%, 10-290%, or 10-300%, as compared to a reference level. In some embodiments, these terms refer to a decrease of 10-300%, 20-300%, 30-300%, 40-300%, 50-300%, 60-300%, 70-300%, 80-300%, 90-300%, 100-300%, 110-300%, 120-300%, 130-300%, 140-300%, 150-300%, 160-300%, 170-300%. 180-300%. 190-300%, 200-300%, 210-300%, 220-300%, 230-300%, 240-300%, 250-300%, 260-300%, 270-300%, 280-300%, or 290-300%, as compared to a reference level. In some embodiments, these terms refer to a decrease of 10-20%, 20-30%, 30-40%, 40-50%, 50-60%, 60-70%, 70-80%, 80-90%, 90-100%, 100-110%, 110-120%, 120-130%, 130-140%, 140-150%, 150-160%, 160-170%, 170-180%, 180-190%, 190-200%. 200-210%. 210-220%. 220-230%. 230-240%. 240-250%, 250-260%, 260-270%, 270-280%, 280-290%, or 290-300%, as compared to a reference level. Docket No. 084284.00346

[0069] In some embodiments, the TGF-β inhibitor is a small molecule, a small hairpin RNA (shRNA), an aptamer, or an antibody or antigen-binding fragment thereof. In some embodiments, the small molecule is SB431542 (CAS Number: 301836-41-9), A83-01 (CAS Number: 909910-43-6), or Galunisertib (LY2157299) (CAS Number: 700874-72-2).

[0070] As used herein, “shRNA” or “small hairpin RNA” (also called stem loop) is a type of small interfering RNA (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. shRNAs function as RNAi and / or siRNA species but differ in that shRNA species are double stranded hairpin-like structure for increased stability.

[0071] As used herein an “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.

[0072] As used herein, an “aptamer” is a single-stranded DNA or RNA molecule that binds to protein targets by folding into a three-dimensional conformation.

[0073] The term "antibody" as referred to herein includes whole antibodies and any antigenbinding fragment or single chains thereof. Whole antibodies are glycoproteins comprising at least two heavy (H) chains and two light (L) chains inter-connected by disulfide bonds. Each heavy chain is comprised of a heavy chain variable region (abbreviated herein as VH) and a heavy chain constant region. The heavy chain constant region is comprised of three domains, CH1, CH2 and CH3. Each light chain is comprised of a light chain variable region (abbreviated herein as VL) and a light chain constant region. The light chain constant region is comprised of one domain, CL. The VH and VL regions can be further subdivided into regions of hypervariability, termed complementarity determining regions (CDR), interspersed with regions that are more conserved, termed framework regions (FR). Each VH and VL is composed of three CDRs and four FRs, arranged from amino-terminus to carboxy-terminus in the following order: FR1, CDR1, FR2, CDR2, FR3, CDR3, FR4. The heavy chain variable region CDRs and FRs are HFR1, HCDR1, HFR2, HCDR2, HFR3, HCDR3, HFR4. The light chain variable region CDRs and FRs are LFR1, LCDR1, LFR2, LCDR2, LFR3, LCDR3, LFR4. The variable regions of the heavy and light chains contain a binding domain that interacts with an antigen. The constant regions of the antibodies can mediate the binding of the immunoglobulin Docket No. 084284.00346

[0074] to host tissues or factors, including various cells of the immune system (e.g., effector cells) and the first component (Clq) of the classical complement system.

[0075] The term '‘antibody” as used herein is used in the broadest sense and specifically may include any immunoglobulin, whether natural or partly or wholly synthetically produced, including but not limited to monoclonal antibodies, polyclonal antibodies, multispecific antibodies (for example, bispecific antibodies and polyreactive antibodies), and antibody fragments.

[0076] The term "antigen-binding fragment or portion" of an antibody (or simply "antibody fragment or portion"), as used herein, refers to one or more fragments of an antibody that retain the abi lity to specifically bind to an antigen (e.g., TGF-P). It has been shown that the antigenbinding function of an antibody can be performed by fragments of a full-length antibody. Examples of binding fragments encompassed within the term "antigen-binding fragment or portion" of an antibody include (i) a Fab fragment, a monovalent fragment consisting of the VL, VH, CL and CHI domains; (ii) a F(ab')2 fragment, a bivalent fragment comprising two Fab fragments linked by a disulfide bridge at the hinge region; (iii) a Fab' fragment, which is essentially an Fab with part of the hinge region (see, FUNDAMENTAL IMMUNOLOGY (Paul ed., 3rded. 1993)); (iv) a Fd fragment consisting of the VH and CHI domains; (v) a Fv fragment consisting of the VL and VH domains of a single arm of an antibody, (vi) a dAb fragment (Ward el al., (1989) Nature 341:544-546), which consists of a VH domain; (vii) an isolated CDR; and (viii) a nanobody, a heavy chain variable region containing a single variable domain and two constant domains. Furthermore, although the two domains of the Fv fragment, VL and VH, are coded for by separate genes, they can be joined, using recombinant methods, by a synthetic linker that enables them to be made as a single protein chain in which the VL and VH regions pair to form monovalent molecules (known as single chain Fv or scFv); see e.g., Bird et al. (1988) Science 242:423-426; and Huston et al. (1988) Proc. Natl. Acad. Sci. USA 85:5879-5883). Such single chain antibodies are also intended to be encompassed within the term "antigen-binding fragment or portion" of an antibody. These antibody fragments are obtained using conventional techniques known to those with skill in the art, and the fragments are screened for utility in the same manner as are intact antibodies.

[0077] In some embodiments, the method for making a reconstructed human brain tissue further comprises a step c) stimulating TGF-P signaling by contacting the reconstructed human brain tissue with a TGF-P agonist. As used herein, a ‘'TGF-P agonist” is a composition that Docket No. 084284.00346

[0078] increases TGF-β signaling as compared to a control. In some embodiments, the TGF-β agonist is TGFβ1, TGFβ2, or TGFβ3.

[0079] The terms '‘improve,” "increased", "increase", "enhance", or "activate" are all used herein to mean an increase by a statically significant amount. In some embodiments, the terms “improve,” "increased," "increase", "enhance", or "activate" can mean an increase of at least 10% as compared to a reference level, for example an increase of at least about 20%, or at least about 30%, or at least about 40%, or at least about 50%, or at least about 60%, or at least about 70%, or at least about 80%, or at least about 90% or up to and including a 100% increase or any increase between 10-100% as compared to a reference level, or at least about a 2-fold, or at least about a 3-fold, or at least about a 4-fold, or at least about a 5-fold or at least about a 10-fold increase, or any increase between 2-fold and 10-fold or greater as compared to a reference level. In the context of a marker or symptom, an "increase" is a statistically significant increase in such level.

[0080] Fibrosis is defined as the pathologic accumulation of the extracellular matrix (ECM) that can occur along the vascular basement membrane (perivascular fibrosis). Brains of APOE4 homozygotes have increased perivascular fibronectin (FN 1 ) deposition compared to APOE3 homozygotes. Thus, inhibiting expression of FN1 may help treat AD in a subject who V& APOE4 homozygous.

[0081] Fibronectin is a basement membrane protein that accumulates in several pathological states. For example, myofibroblasts deposit fibronectin during fibrosis and this protein is upregulated along the vasculature in APOE4 carriers and AD (Lepelletier F-X et al. Early changes in extracellular matrix in Alzheimer’s disease. Neuropathology and Applied Neurobiology 2017;43:167-82; Bhattarai P et al. Rare genetic variation in fibronectin 1 (FN1) protects against APOEε4 in Alzheimer's disease. Acta Neuropathol 2024:147:70; To WS et al. Plasma and cellular fibronectin: distinct and independent functions during tissue repair. Fibrogenesis & Tissue Repair. 2011;4:21; Torr EE et al. Myofibroblasts Exhibit Enhanced Fibronectin Assembly That Is Intrinsic to Their Contractile Phenotype. J Biol Chem 2015;290:6951-61). Along with several other cerebrovascular ECM components, there is a positive correlation between fibronectin deposition and amyloid accumulation (Lepelletier F-X et al. Early changes in extracellular matrix in Alzheimer’s disease. Neuropathology and Applied Neurobiology7. 2017;43:167-82). Studies geared towards understanding the interaction between these two proteins have shown that fibronectin directly binds to amyloid and that fibronectin injection into mice leads to increased perivascular amyloid deposition (Howe MD Docket No. 084284.00346

[0082] et al. Fibronectin induces the perivascular deposition of cerebrospinal fluid-derived amyloid-P in aging and after stroke. Neurobiol Aging 2018;72:1-13). Additionally, a loss-of-function FN1 variant was recently discovered to be protective of AD in APOEε4 carriers (Bhattarai P et al. Rare genetic variation in fibronectin 1 (FN1) protects against APOEs4 in Alzheimer’s disease. Acta Neuropathol 2024;147:70).

[0083] In one embodiment, the iMCs overexpress fibronectin (FN1) relative to iMCs that have not been engineered for such expression using methods such as transfection. In one embodiment, the iMCs express an FN1 variant. In one embodiment, iMCs express reduced FN1 levels compared to iMCs that have not been engineered to reduce FN1 expression using methods including, but not limited to siRNA, shRNA. or CRISPR.

[0084] In one embodiment, the reconstructed human brain tissue is cryopreserved.

[0085] II. Methods of using reconstructed human brain tissue

[0086] Provided herein are various methods of use of the reconstructed human brain tissue described herein.

[0087] In one aspect, provided is a method for evaluating whether a drug candidate inhibits amyloid deposition, comprising:

[0088] a) contacting the reconstructed human brain tissue described herein with the drug candidate; and

[0089] b) quantifying amyloid deposition in the reconstructed human brain tissue as compared to amyloid deposition levels in the reconstructed human brain tissue in the absence of the drug candidate.

[0090] In one embodiment, provided is a method for evaluating whether a drug candidate inhibits amyloid deposition in a reconstructed human brain tissue, the method comprising: contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying a level of amyloid deposition in the reconstructed human brain tissue as compared to a control level of amyloid deposition levels in the reconstructed human brain tissue in the absence of the drug candidate.

[0091] In one embodiment, the reconstructed human brain tissue is evaluated using immunocytochemistry using anti-amyloid antibodies and imaged using confocal microscopy. In this case, the amount of amyloid staining along the vasculature in the drug-treated reconstructed human brain tissue is compared to such tissue in the absence of drug treatment.

[0092] In one embodiment, provided is a method for evaluating whether a drug candidate inhibits fibronectin deposition in a reconstructed human brain tissue, the method comprising Docket No. 084284.00346

[0093] contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying the level of fibronectin deposition in the reconstructed human brain tissue as compared to a control level of fibronectin deposition in the reconstructed human brain tissue in the absence of the drug candidate.

[0094] In one embodiment, provided is a method for evaluating whether a drug candidate is able to cross an in vitro brain-blood barrier (iBBB), the method comprising: providing a reconstructed human brain tissue of described herein, wherein the reconstructed human brain tissue further comprises an iBBB comprising a proximal and a distal side, contacting the proximal side of the iBBB with the drug candidate, and quantifying the amount of drug candidate that crosses the iBBB to reach the distal side of the iBBB.

[0095] In one aspect, the reconstructed human brain tissue described herein is used in a neurotoxicity assay to determine whether a drug candidate is toxic to human brain tissue. The term ‘‘neurotoxicity” as used herein refers to the level of neuron degeneration or necrosis, e.g., as measured by neuronal vacuolation after exposure to the drug candidate. In one embodiment, provided is a method for evaluating whether a drug candidate induces neurotoxicity in a reconstructed human brain tissue, the method comprising contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying the level of neurotoxicity in the reconstructed human brain tissue as compared to a control level of neurotoxicity in the reconstructed human brain tissue in the absence of the drug candidate.

[0096] In one aspect, the reconstructed human brain tissue described herein is used in a neurodegeneration tau pathology test to determine whether a drug candidate reduces tau pathology in human brain tissue. In one embodiment, provided is a method for evaluating whether a drug candidate induces reduces tau pathology in a reconstructed human brain tissue, the method comprising contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying the level of tau pathology in the reconstructed human brain tissue as compared to a control level of tau pathology in the reconstructed human brain tissue in the absence of the drug candidate. A neurodegeneration tau pathology can be a blood test that detects abnormal tau accumulation via biomarkers. Tau proteins are microtubule-associated proteins involved in stabilizing neurons. Tau proteins are hyperphosphorylated in Alzheimer’s disease. Increased phosphorylation of tau causes it to self-assemble into paired helical filaments that form neurofibrillary tangle that destabilize neurons.

[0097] In one aspect, the reconstructed human brain tissue described herein is used in a neurodegeneration Cerebral amyloid angiopathy (CAA) pathology test to determine whether a Docket No. 084284.00346

[0098] drug candidate reduces CAA pathology. In one embodiment, provided is a method for evaluating whether a drug candidate induces reduces cerebral amyloid angiopathy (CAA) pathology in a reconstructed human brain tissue, the method comprising contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying the level of CAA pathology in the reconstructed human brain tissue as compared to a control level of CAA pathology in the reconstructed human brain tissue in the absence of the drug candidate. CAA causes bleeding inside the brain, which damages brain tissue. CAA pathology can be evaluated for example, using biomarkers known in the art (such as Ap and tau). A CAA pathology test can comprise imaging (such as MRI).

[0099] In one aspect, the reconstructed human brain tissue described herein is used in a neurodegeneration amyloid pathology test to determine whether a drug candidate reduces amyloid pathology in human brain tissue. In one embodiment, provided is a method for evaluating whether a drug candidate induces reduces cerebral amyloid pathology in a reconstructed human brain tissue, the method comprising contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying the level of amyloid pathology in the reconstructed human brain tissue as compared to a control level of amyloid pathology in the reconstructed human brain tissue in the absence of the drug candidate. Amyloid is abnormal fibrous, extracellular, proteinaceous deposits found in organs and tissues. Amyloid pathology occurs in various diseases including Alzheimer's disease. The neurodegeneration amyloid pathology test can comprise a blood test that measures biomarkers (such as pTau217 and beta-amyloid 1-42).

[0100] In one aspect, the reconstructed human brain tissue described herein is used in a neurodegeneration Lewy Body pathology test to determine whether a drug candidate reduces Lewy Body pathology in human brain tissue. In one embodiment, provided is a method for evaluating whether a drug candidate induces reduces Lewy Body pathology in a reconstructed human brain tissue, the method comprising contacting a reconstructed human brain tissue described herein with the drug candidate; and quantifying the level of Lewy Body pathology¬ in the reconstructed human brain tissue as compared to a control level of Lewy Body pathology in the reconstructed human brain tissue in the absence of the drug candidate. Lewy bodies are abnormal deposits of alpha-synuclein in the brain. The neurodegeneration Lewy Body pathology test can comprise a blood test that measures biomarkers (such as Aβ40, Aβ42, and total tau). Docket No. 084284.00346

[0101] In some embodiments, the drug candidate is selected from the group consisting of a small molecule, a nucleic acid, a peptide, a polypeptide, an antibody, and an antibody fragment. In one embodiment, the drug candidate is a TGF-P inhibitor as described herein.

[0102] III. Methods of treatment

[0103] In one aspect, provided is a method of reducing or preventing APOE4 vascular dysfunction in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor.

[0104] In one aspect, provided is a method of reducing non-vascular a-SMA immunoreactivity in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor.

[0105] In one aspect, provided is a method of reducing a pericyte-to-myofibroblast-like transition in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor.

[0106] In one aspect, provided is a method of reducing or preventing myofibroblast accumulation in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor.

[0107] In one aspect, provided is a method of reducing or preventing cerebrovascular fibrosis in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor.

[0108] In one aspect, provided is a method of reducing or preventing amyloid deposition in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor.

[0109] In one aspect, provided is a method of reducing or preventing AD progression in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor.

[0110] In one aspect, provided is a method of reducing fibronectin expression levels in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor, wherein the TGF-P inhibitor reduces fibronectin expression levels by at least about 20% such as about 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or any percent therebetween.

[0111] In one embodiment, the subject is a human. In one embodiment, the subject has a neurodegenerative disease. In one embodiment, the neurodegenerative disease is Alzheimer’s disease. In some embodiments, the subject is homozygous or heterozygous for APOE4.

[0112] As used herein, the term " APOE4 vascular dysfunction” refers to a vascular pathology such as pericyte loss, myeloid deposition, and / or fibrosis that occurs in subject who is homozygous or heterozygous for APOE4. Docket No. 084284.00346

[0113] As used herein, the terms "treat." “treated,” “treating,” or “treatment” refer to therapeutic treatment, wherein the object is to slow down (lessen) an undesired physiological condition, disorder or disease, or to obtain beneficial or desired clinical results. For the purposes of this disclosure, beneficial or desired clinical results include, but are not limited to alleviation of symptoms; diminishment of the extent of the condition, disorder or disease; stabilization (i.e., not worsening) of the state of the condition, disorder or disease; delay in onset or slowing of the progression of the condition, disorder or disease; amelioration of the condition, disorder or disease state; and remission (whether partial or total), or enhancement or improvement of the condition, disorder or disease. Treatment includes eliciting a clinically significant response without excessive levels of side effects. As used herein, the terms “including.” “comprising.” “containing,” or “having” and variations thereof are meant to encompass the items listed thereafter and equivalents thereof as well as additional subject matter unless otherwise noted.

[0114] As used herein, a "subject" or "individual" means a human or animal. Usually, the animal is a vertebrate such as a primate, rodent, domestic animal or game animal. Primates include chimpanzees, cynomolgus monkeys, spider monkeys, and macaques, e.g., Rhesus. Rodents include mice, rats, woodchucks, ferrets, rabbits and hamsters. Domestic and game animals include cows, horses, pigs, sheep, goats, deer, bison, buffalo, feline species, e.g., domestic cat, canine species, e.g., dog, fox, wolf, avian species, e.g., chicken, emu, ostrich, and fish, e.g., trout, catfish and salmon. In some embodiments, the subject is a mammal, e.g, a human or a non-human mammal. The mammal can be a human, non-human primate, mouse, rat, dog, cat, horse, or cow, but is not limited to these examples. Mammals other than humans can be advantageously used as subjects that represent animal models of disorders. The terms, "individual," "patient" and "subject" are used interchangeably herein. A subject can be male or female.

[0115] As used herein, the phrases “in one embodiment,” “in various embodiments,” “in some embodiments,” and the like are used repeatedly. Such phrases do not necessarily refer to the same embodiment, but they may unless the context dictates otherwise.

[0116] As used herein, the terms “and / or” or

[0117]

[0118] means any one of the items, any combination of the items, or all of the items with which this term is associated. Docket No. 084284.00346

[0119] As used herein and in the appended claims, the singular forms “a,” “and"’ and “the” include plural references unless the context clearly dictates otherwise.

[0120] As used herein, the term “approximately” or “about,” as applied to one or more values of interest, refers to a value that is similar to a stated reference value. In some embodiments, the term “approximately” or “about” refers to a range of values that fall within 25%, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, or less in either direction (greater than or less than) of the stated reference value unless otherwise stated or otherwise evident from the context (except where such number would exceed 100% of a possible value). Unless indicated otherwise herein, the term “about” is intended to include values, e.g., weight percents, proximate to the recited range that are equivalent in terms of the functionality of the individual ingredient, the composition, or the embodiment.

[0121] As used herein, the term “each.” when used in reference to a collection of items, is intended to identify an individual item in the collection but does not necessarily refer to every item in the collection. Exceptions can occur if explicit disclosure or context clearly dictates otherwise.

[0122] As disclosed herein, a number of ranges of values are provided. It is understood that each intervening value, to the tenth of the unit of the lower limit, unless the context clearly dictates otherwise, between the upper and lower limits of that range is also specifically disclosed. Each smaller range between any stated value or intervening value in a stated range and any other stated or intervening value in that stated range is encompassed within the present disclosure. The upper and lower limits of these smaller ranges may independently be included or excluded in the range, and each range where either, neither, or both limits are included in the smaller ranges is also encompassed within the present disclosure, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the present disclosure.

[0123] The following examples serve to further illustrate the methods of the present disclosure. Docket No. 084284.00346

[0124] EXAMPLES

[0125] Example 1. Single-nucleus transcriptomic analysis of mural cells reveals a profibrotic state in APOE4 carriers.

[0126] To gain insight into APOE-mediated phenotypes in mural cells, a previously published single nuclei RNA-sequencing (snRNA-seq) dataset of vascular brain cells isolated from APOE3 / 3 individuals and APOE4 carriers (Yang, AC et al. A human brain vascular atlas reveals diverse mediators of Alzheimer’s risk. Nature 2022;603:885-92) was analyzed. Aligning with the published results, four subclusters of mural cells in this population were identified: matrix pericytes (m.pericyte), transport pericytes (t.pericyte), arterial smooth muscle cells (aSMC), and arteriolar smooth muscle cells (aaSMC) (FIG. 1A). To investigate changes in cell type populations between genotypes, differential abundance analysis was performed (Dann E et al. Differential abundance testing on single-cell data using k-nearest neighbor graphs. Nat Biotechnol 2022;40:245-53). This analysis revealed that APOE4 carriers exhibit a significant reduction in t.pericytes compared to APOE3 / 3 individuals, a finding that is consistent with the loss of pericyte vascular coverage that has been reported in APOE4 (Montagne A et al. APOE4 accelerates advanced-stage vascular and neurodegenerative disorder in old Alzheimer’s mice via cyclophilin A independently of amyloid-β. Nat Aging 2021;1:506-20) (FIG. IB). Coinciding with this reduction in pericytes, a gain of aSMCs in APOE4 carriers was detected (FIG. IB).

[0127] Smooth muscle cells and myofibroblasts share similar gene expression profiles, making their distinction difficult with single-cell clustering (Liu X et al. Categorization of lung mesenchymal cells in development and fibrosis. iScience2021;24: 102551). Hypothesizing that the shift from pericytes to aSMCs in APOE carriers could represent aspects of the PMT, scores were assigned reflecting the expression of ECM and myofibroblast genes to cells within the aSMC cluster. Indeed, APOE4 cells had a significant upregulation of ECM and myofibroblast genes compared to APOE3 / 3 (FIG. 1C), suggesting a shift in APOE4 mural cells from pericytes to ECM-producing, myofibroblast-like cells.

[0128] Example 2. Fibrotic phenotypes are confirmed in APOE4 iMCs.

[0129] To validate the findings of the snRNA-seq analysis (FIGS. 1A-1C), isogenic APOE3 / 3 W APOE4 4 iPSCs were differentiated into mural cells and the expression of two commonly used markers for fibrosis and myofibroblasts, alpha-smooth muscle actin (a-SMA) and fibronectin, were investigated (Sava P et al. Human pericytes adopt myofibroblast properties in the microenvironment of the IPF lung. JCI Insight n.d.;2:e96352; Zhao Z et al. TGF-P Docket No. 084284.00346

[0130] promotes pericyte-myofibroblast transition in subretinal fibrosis through the Smad2 / 3 and Akt / mTOR pathways. Exp Mol Med 2022;54:673-84: Younesi FS et al. Myofibroblast Markers and Microscopy Detection Methods in Cell Culture Cell cultures and Histology. In: Hinz B, Lagares D, editors. Myofibroblasts: Methods and Protocols. New York, NY: Springer US; 2021. p. 17-47; and Torr EE et al. Myofibroblasts Exhibit Enhanced Fibronectin Assembly That Is Intrinsic to Their Contractile Phenotype. J Biol Chem 2015;290:6951-61). Immunocytochemistry revealed that APOE4 / 4 iMCs had increased a-SMA and fibronectin expression, consistent with a fibrotic-like phenotype. Dot blot analysis found significantly elevated levels of secreted fibronectin in APOE4 / 4 mural cell conditioned media compared to isogenicN / V / A’j 3 control conditioned media (FIG.2B). To corroborate these results with gene expression, bulk RNA-seq data was analyzed from the iMCs, which indicated an upregulation of ACTA2 and FN1 in APOE4 / 4 (FIG. 2A). These results are consistent with the snRNA-seq analysis, demonstrating that APOE4 iMCs adopt a fibrotic-like state not seen in APOE3 mural cells.

[0131] Example 3. TGF-p signaling is upregulated in APOE4 mural cells.

[0132] The data disclosed herein indicated that APOE4 mural cells associate with a profibrotic state. However, the molecular mechanisms underlying APOE4-mediated fibrosis are largely unclear. To gain insight into relevant pathways, bulk RNA-seq data from iMCs were further analyzed, specifically by annotating upregulated molecular function pathways in APOE4 / 4 compared to APOE3 / 3. Consistent with the previous data. APOE4 / 4 iMCs were enriched in genes associated with extracellular matrix structural constituents (FIG. 3A). Interestingly, growth factor binding and TGF-β receptor activity were two other upregulated pathways in APOE4 / 4, and all three TGF-β receptors had increased expression in this genotype (FIGS.3A and 3B). TGF-P signaling is a well-characterized driver of fibrosis and myofibroblast differentiation (Brenmoehl J et al. Transforming growth factor-pi induces intestinal myofibroblast differentiation and modulates their migration. World J Gastroenterol 2009;15:1431-42; Lodyga M et al. TGF-pi - A truly transforming growth factor in fibrosis and immunity. Seminars in Cell & Developmental Biology 2020;101:123-39; and Zhao Z et al. TGF-P promotes pericyte-myofibroblast transition in subretinal fibrosis through the Smad2 / 3 and Akt / mTOR pathways. Exp Mol Med 2022;54:673-84), suggesting that the overactivity of this pathway in APOE4 / 4 mural cells could facilitate their fibrotic-like state. To test this hypothesis, APOE3 / 3 and APOE4 / 4 iMCs were treated with a TGF-β inhibitor (SB431542) and immunocytochemistry was performed for a-SMA and fibronectin. Control APOE4 / 4 iMCs Docket No. 084284.00346

[0133] had increased expression of these markers compared to control APOE3 / 3 cells (FIG. 3C).

[0134] TGF-β inhibitor treatment selectively reverted this phenotype in APOE4 / 4, suggesting a causal role for this pathway in APOE4- mediated fibrosis (FIG. 3C). Notably, the reduction in fibronectin expression with SB431542 treatment indicates that TGF-P inhibition can attenuate perivascular amyloid deposition observed in APOE4.

[0135] Example 4. Perivascular fibronectin is associated with amyloid accumulation in miBrains.

[0136] A significant limitation of monocultures is the inability to recapitulate complex pathologies in the human brain, such as perivascular fibrosis and amyloidosis. Utilizing a vascularized miBrain system, it was hypothesized that this model could recapitulate the perivascular ECM and amyloid accumulation that has been observed in the postmortem brains of APOE4 carriers. The miBrain is composed of the six major brain cell types (neurons, astrocytes, microglia, oligodendroglia, endothelial cells, and pericytes) cultured together within a 3D matrix and can uniquely develop AD-relevant pathologies while allowing for the manipulation of individual cell types to tease apart cell type-specific mechanisms. Indeed, culturing APOE3 / 3 and APOE4 / 4 miBrains revealed a pericyte-to-myofibroblast-like transition in APOE4 / 4 miBrains characterized by an increase in a-SMA immunoreactivity and a loss of pericyte vascular coverage (FIG. 4A). This transformation was associated with an increase in fibronectin and collagen deposition along the vasculature, a hallmark of perivascular fibrosis (FIG.4B). It was hypothesized that the upregulation of perivascular fibronectin in the APOE4 miBrains would be associated with amyloid accumulation along the vasculature. Consistent with this hypothesis, immunostaining miBrains with several amyloid antibodies demonstrated an increase in perivascular amyloid accumulation along the APOE4 vasculature that is positively correlated with fibronectin (FIG.4B). These results validate the miBrain system in studying these pathologies and indicate that FN1 is a causal driver of perivascular amyloid pathology.

[0137] Example 5. The role of TGF-p signaling on APOE4-mediated mural cell fibrosis and perivascular amyloidosis.

[0138] The presence of one or two copies of the APOE4 allele is the strongest genetic risk factor for AD (DiBattista AM et al. Alzheimer’s Disease Genetic Risk Factor APOE-E4 Also Affects Normal Brain Function. Curr Alzheimer Res 2016;13:1200-7). While molecular pathways that are early drivers of AD pathogenesis in APOE4 carriers are poorly defined. Docket No. 084284.00346

[0139] recent evidence suggests that ECM dysregulation may contribute to AD progression in this population (Amontree M et al. Matrix disequilibrium in Alzheimer’s disease and conditions that increase Alzheimer’s disease risk. Front Neurosci 2023;17: doi.org / 10.3389 / fnins.2023.1188065). Indeed, the data disclosed herein reveal a phenotypic shift in APOE4 mural cells to a profibrotic state associated with increased amyloid accumulation. However, the mechanisms driving APOE4 mural cells to adopt myofibroblastlike features are unknown. TGF-P signaling is an important facilitator of fibrosis and the pericyte-to-myofibroblast transition (Brenmoehl J et al. Transforming growth factor-|31 induces intestinal myofibroblast differentiation and modulates their migration. World J Gastroenterol 2009;15:1431-42; LodygaM et al. TGF-P 1 - A truly transforming growth factor in fibrosis and immunity. Seminars in Cell & Developmental Biology 2020:101:123-39; and Zhao Z et al. TGF-P promotes pericyte-myofibroblast transition in subretinal fibrosis through the Smad2 / 3 and Akt / mTOR pathways. Exp Mol Med 2022;54:673-84), and this pathway is significantly upregulated in APOE4 mural cells (FIGS. 3A and 3B). Furthermore, inhibiting this pathway attenuates the fibrotic characteristics of these cells (FIG. 3C). It is possible that increased TGF-P signaling drives the fibrotic-like state of APOE4 mural cells and exacerbates perivascular amyloid deposition. Thus, this study determined the role of TGF-P signaling on APOE4-mediated mural cell fibrosis and perivascular amyloidosis.

[0140] Patient-derived isogenic iPSC lines with APOE3 / 3 and APOE4 / 4 allelic variants were differentiated into mural cell monocultures and miBrain multi-cultures. To modulate TGF-P signaling, iMCs and miBrains of both genotypes were treated with well -characterized chemical inhibitors (SB431542 and Galunisertib) and a stimulator (i.e., TGFpi) of this pathway, along with a DMSO vehicle as a control.

[0141] To investigate the effects of TGF-P signaling on the fibrotic-like state of APOE4 mural cells, immunocytochemistry was performed on fixed APOE3 / 3 and APOE4 / 4 iMC monocultures after treatment wdth chemical modulators of this pathway, or DMSO vehicle, using antibodies for the myofibroblast markers a-SMA and fibronectin. The intracellular expression of these proteins was quantified via the imaging analysis software NIS-Elements and compared between genotypes and conditions.

[0142] In the study of AD, a significant limitation of 2D monocultures is the inability to recapitulate relevant pathologies. miBrains successfully model amyloid accumulation along the vasculature (FIG. 4B). Harnessing this system to examine the effects of TGF-P signaling on.-l / ’O / '.-mediated perivascular amyloid pathology, immunocytochemistry was performed on Docket No. 084284.00346

[0143] fixed APOE3 / 3 and APOE4 / 4 miBrains after treatment with TGF-P chemical modulators or DMSO vehicle using antibodies for amyloid (6E10, D54D2) and the vasculature (PECAM1, VE-Cadherin). The amount of amyloid present along the vasculature was then quantified via NIS-Elements. While this pharmacologic approach uncovered the effect of TGF-P signaling in all brain cells on amyloid, a unique advantage of the miBrain is the ability to exchange individual cell types and dissect cell type-specific mechanisms.

[0144] Aligning with the data that show SB431542 reduces fibronectin and a-SMA expression only in APOE4 / 4 iMCs, it is hypothesized that TGF-P inhibition selectively attenuates the fibrotic phenotype of APOE4 mural cells. Given that TGF-P can drive normal cells to adopt characteristics of myofibroblasts, it is also hypothesized that TGF-P stimulation reprograms APOE3 mural cells to a fibrotic-like state, mirroring APOE4 at baseline. There is a well-characterized association between perivascular ECM deposition and amyloid (Lepelletier F-X et al. Early changes in extracellular matrix in Alzheimer’s disease. Neuropathology and Applied Neurobiology 2017;43:167-82; Wyss-Coray T et al. Chronic Overproduction of Transforming Growth Factor-pi by Astrocytes Promotes Alzheimer’s Disease-Like Microvascular Degeneration in Transgenic Mice. Am J Pathol 2000;156: 139-50; Wyss-Coray T et al. Alzheimer’s Disease-like Cerebrovascular Pathology in Transforming Growth Factor-pi Transgenic Mice and Functional Metabolic Correlates. Annals of the New York Academy of Sciences 2000;903:317-23; and Howe MD et al. Fibronectin induces the perivascular deposition of cerebrospinal fluid-derived amyloid-P in aging and after stroke. Neurobiol Aging 2018;72: 1-13), suggesting that fibrosis in APOE4 mural cells can contribute to amyloid deposition along the vasculature. To this end, it is hypothesized that global and mural cellspecific TGF-P inhibition selectively reduce perivascular amyloid accumulation in APOE4 miBrains, whereas stimulation of this pathway in APOE3 miBrains can exacerbate pathology’.

[0145] Due to signaling from other cell types, it is possible that TGF-P modulation affects fibrotic phenoty pes of mural cells in monoculture, but not in the miBrain. Besides TGF-P, there are other pathways that drive myofibroblast differentiation, such as IRAK4 and ROCK1. Intriguingly, snRNA-seq analysis revealed that both these pathways may be involved in the APOE4-mediated PMT.

[0146] Example 6. The molecular contribution of fibronectin to perivascular amyloid deposition.

[0147] No causal role for fibronectin has been established in the formation of AD-associated amyloid pathology in human brain tissue. As discussed herein, there is a positive correlation Docket No. 084284.00346

[0148] between fibronectin and amyloid in miBrains, with both proteins accumulating more in APOE4 (FIGS. 4A and 4B). Therefore, a study was performed to determine if the direct binding of fibronectin drives perivascular amyloid accumulation in a dose-dependent manner, thus leading to increased amyloid deposition in APOE4.

[0149] To investigate the role of fibronectin expression in the formation of perivascular amyloid deposits, immunocytochemistry was performed on fixed APOE3 / 3 and APOE4 / 4 miBrains cultured with fibronectin overexpressing or knockdown iMCs of the same genotype. To validate FN1 genetic manipulation and assess perivascular amyloid accumulation, antibodies were used for fibronectin, amyloid (6E10, D54D2), and the vasculature (PECAM1, VE-cadherin). The amount of each protein present along the vasculature was then quantified with NIS-Elements.

[0150] Since perivascular fibronectin levels are positively correlated with amyloid regardless oiAPOE genotype (Lepelletier F-X et al. Early changes in extracellular matrix in Alzheimer’s disease. Neuropathology and Applied Neurobiology 2017;43:167-82), it is hypothesized that fibronectin knockdown attenuates amyloid accumulation along the vasculature in both APOE3 / 3 and APOE4 / 4. Furthermore, it is hypothesized that fibronectin overexpression exacerbates perivascular amyloid deposition in both genotypes with a more severe phenotype in APOE4 / 4 given the baseline upregulation of fibronectin compared to APOE3 / 3. Based on the protein structural changes associated with the protective FN1 variant, perivascular amyloid accumulation may decrease in the presence of variant iMCs for both APOE3 / 3 and APOE4 / 4 compared to wild type.

[0151] In combining gene-editing technologies and chemical manipulations, the studies described herein harness innovative iPSC-derived models of the human brain to uncover molecular pathways driving AD pathogenesis in APOE4 carriers. To summarize the data presented herein, it was found that APOE4 mural cells transition into a profibrotic, myofibroblast-like state (FIGS. 1A-1C), which was confirmed in vitro (FIGS. 2A and 2B) and reversed with TGF-β inhibition (FIGS. 3A-3B). Investigating the pathologic consequence of this fibrotic phenotype, a positive correlation was identified between perivascular fibronectin and amyloid accumulation in a vascularized. iPSC-derived model of the human brain that is consistent with postmortem studies (FIGS.4A and 4B).

[0152] Example 7. Materials and Methods.

[0153] This Example contains the Materials and Methods used in Examples 8-15. Docket No. 084284.00346

[0154] Table 1. Resources used.

[0155] REAGENT OR SOURCE IDENTIFIER RESOURCE

[0156] Chemicals, peptides, and recombinant proteins

[0157] Accutase™ Stemcell Cat# 07920 Activin A Peprotech Cat# 120-14P Astrocyte Growth ScienCell Cat# 1852 Supplement

[0158] Astrocyte Medium (AM) ScienCell Cat# 1801

[0159] B27 Gibco Cat# 17504044 B27 without Vitamin A Gibco Cat# 12587010 BDNF Peprotech Cat# 450-02 Biotin Sigma Cat#B4639 Blasticidin Gibco Cat # Al 113903 BMP4 Peprotech Cat# 120-05ET CD Lipids Gibco Cat# 11905031 CHIR99021 Tocris Cat# 4423

[0160] CNTF Peprotech Cat# 450-13 DAPT Cayman Cat# 13197

[0161] Di butyryl cAMP Biogems Cat# 1698950 DMEM Gibco Cat# 11965092 DMEM / F12 with Gibco Cat# 10565018 GlutaMAX™

[0162] Doxycyline Millipore Cat# D3072

[0163] FGF-basic Peprotech Cat# 100-18B Fibronectin R& D Systems Cat# 4305-FNB-200 Forkskolin R& D Systems Cat# 1099 / 10 Galunisertib Tocris Cat# 6956

[0164] GDNF Peprotech Cat# 450-10 Gelxtrex Gibco Cat# A1413201 GlutaMAX™ Gibco Cat# 35050061 HGF Peprotech Cat# 100-39H Hoechst33342 Thermo Scientific Cat# 62249 Human Endothelial SFM Gibco Cat# 11111044 IGF-1 Peprotech Cat# 100-11

[0165] IL-34 Peprotech Cat# 200-34 Insulin Sigma Cat# 19278 Laminin Gibco Cat# 23017015 L- Ascorbic Acid Fisher Scientific Cat# BP351 LDN193189 Tocris Cat# 6053 Lipofectamine™ Stem Invitrogen Cat# STEM00001 Transfection Reagent

[0166] Lycopersicon Thermo Scientific Cat# L32470 Esculentum (Tomato)

[0167] Lectin (LEL, TL),

[0168] DyLight 488

[0169]

[0170] MCSF Peprotech Cat# 300-25 Docket No. 084284.00346

[0171] MEM-Non-Essential Gibco Cat# 11400050 Amino Acids

[0172] N2 Gibco Cat# 17502048 Neurobasal Gibco Cat# 21103049 NT3 Peprotech Cat# 450-03 PDGF-AA Peprotech Cat# 100-13 A PDGF-BB Peprotech Cat# AF- 100-14B Penicillin-Streptomycin Gibco Cat# 15140122 Puromycin Gibco Cat# Al 113803 Retinoic Acid Millipore Cat# R2625

[0173] SAG Cayman Cat# 11914 SB431542 Stemgent Cat# 04-0010 StemFlex Gibco Cat# A3349401 TGFB1 Peprotech Cat# 100-21 TrypLE™ Select Gibco Cat# 12563011 VEGF-A Peprotech Cat# 100-20

[0174] ¥-27632 Tocris Cat# 1254 Antibodies

[0175] a-smooth muscle actin R& D Systems Cat# MAB1420 Amyloid-β (12F4) BioLegend Cat# 805501 Amyloid-β (6E10) BioLegend Cat# 803001 Amyloid-β (D54D2) Cell Signaling Technology Cat# 8243S CD31 / PECAM-1 R& D Systems Cat# AF806 CD31 / PECAM-1 R& D Systems Cat# BBA7 CD31 / PECAM-1 Thermo Scientific Cat# MA5-29475 Fibronectin R& D Systems Cat# AF1918 NG2 Abeam Cat# Ab255811 PDGFRB Abeam Cat# Ab69506 pSmad2 Millipore-Sigma Cat# AB3849-I Smad2 Cell Signaling Technology Cat# 5339S VECAD / CD144 R& D Systems Cat# AF938 Animals

[0176] B6.Cg-Apoeem2(APOE*) Jackson Labs RRID:

[0177] Adiuj / J (APOE*3 KI) IMSR JAX:029018 B6(SJL)- Jackson Labs RRID: IMSR_JAX:027 Apoetml.l(APOE*4)Adi 894

[0178] uj / J (APOE*4 KI)

[0179] Cell lines

[0180] AG09173 (MSSM3) Massachusetts Institute of RRID: CVCL 4L66 iPSCs Technology

[0181] ADRC5 iPSCs UCI

[0182] sAD iPSCs Massachusetts Institute of

[0183] Technology

[0184] Plasmids

[0185] FN1 shRNA plasmid for Thermo Scientific TRCN0000293840

[0186]

[0187] lentiviral production Docket No. 084284.00346

[0188] piggyBac-rtTA Addgene Cat# 209077 (4th_Gen)-NGN2-2A- PURO-IRES-SNAP

[0189] PB iETV2 P2A GFP P Addgene Cat# 168805

[0190] uro

[0191] Scramble shRNA Millipore-Sigma Cat# SHC016 plasmid for lentiviral

[0192] production

[0193] Software and algorithms

[0194] CellProfiler (v4.2.8) Stirling et al. (2021). CellProfiler cellprofiler.org /

[0195] 4' improvements in speed, utility

[0196] and usability. BMC Bioinformatics

[0197] 22. 433

[0198] CIBERSORTx Newman et al. (2019). Determining cibersortx.stanford.edu / cell type abundance and expression

[0199] from bulk tissues with digital

[0200] cytometry. Nat Biotechnol 37,

[0201] 773-782

[0202] ClusterProfiler (v4.10.1) Yu el al. (2012). clusterProfiler: an guangchuangyu.github.

[0203] R Package for Comparing io / software / clusterProfi Biological Themes Among Gene ler /

[0204] Clusters

[0205] Condiments (vl.10.0) Roux de Bezieux et al. (2024). github.com / HectorRD Trajectory inference across B / condiments multiple conditions with

[0206] condiments. Nat Commun 15, 833

[0207] DAseq (v 1.0.0) Zhao et al. (2021). Detection of github. com / KlugerLab / differentially abundant cell DAseq subpopulations in scRNA-seq data.

[0208] Proceedings of the National

[0209] Academy of Sciences 118,

[0210] e2100293118

[0211] DoubletFinder (v2.0.4) McGinnis et al.( 2019). github.com / chris-mcginnis-ucsf / DoubletFinder Data Using Artificial Nearest

[0212] Neighbors. Cell Systems 8, 329- 337

[0213] enrichR (v3.4) Chen et al. (2013). Enrichr: github. com / guokai 8 / En interactive and collaborative richR

[0214] HTML5 gene list enrichment

[0215] analysis tool. BMC Bioinformatics

[0216] 14, 128

[0217] Fgsea (v 1.28.0) Korotkevich et al. (2021). Fast github. com / alsergl ab / fg gene set enrichment analysis. sea

[0218] Preprint at bioRxiv

[0219] Fiji (v2.3.0) Schindehn et al. (2012). Fiji: an imagej.net / software / fiji

[0220]

[0221] open-source platform for / Docket No. 084284.00346

[0222] biological-image analysis. Nat

[0223] Methods 9, 676-682

[0224] GraphPad Prism GraphPad Software graphpad.com (vlO.4.1)

[0225] GSVA (vl.50.5) Hanzelmann et al. (2013). GSVA: github.com / rcastelo / GS gene set variation analysis for VA

[0226] microarray and RNA-Seq data.

[0227] BMC Bioinformatics 14, 7

[0228] Harmony (vl.2.3) Korsunsky et al. (2019). Fast, gitliub. com / immunoge sensitive and accurate integration n omi cs / harmony of single-cell data with Harmony.

[0229] Nat Methods 16, 1289-1296

[0230] Limma (v3.58.1) Ritchie et al. (2015). limma powers bi oconductor. org / packa differential expression analyses for ges / release / bioc / html / li RNA-sequencing and microarray mma.html studies. Nucleic Acids Res 43, e47

[0231] MAST (vl.28.0) Finak et al. (2015). MAST: a github. com / RGLab / M flexible statistical framework for AST

[0232] assessing transcriptional changes

[0233] and characterizing heterogeneity in

[0234] single-cell RNA sequencing data.

[0235] Genome Biology 16, 278

[0236] Mgcv (vl.9.3) Wood. (2011). Fast Stable https: / / cran.r- Restricted Maximum Likelihood proj ect. org / web / packag and Marginal Likelihood es / mgcv / index.html Estimation of Semiparametric

[0237] Generalized Linear Models. J. R.

[0238] Stat. Soc. Ser B. Stat. Methodol.

[0239] 73, 3-36

[0240] miloR (vl.10.0) Dann et al. (2022). Differential https: / / github. com / Mari abundance testing on single-cell oniLab / miloR data using k-nearest neighbor

[0241] graphs. Nat Biotechnol 40, 245- 253

[0242] Msigdbr (vl0.0.2) Dolgalev (2025). msigdbr: https: / / igordot.github.io MSigDB Gene Sets for Multiple / msigdbr / Organisms in a Tidy Data Format.

[0243] Version 25.1.1.

[0244] NicheNet (v2.1.5) Broweays et al. (2020). NicheNet: https: / / github. com / saey modeling intercellular slab / nichenetr communication by linking ligands

[0245] to target genes. Nat Methods 17,

[0246] 159-162'’

[0247] Nikon NIS Elements Nikon microscope.healthcare. software nikon.com

[0248] R (v4.3.2) R Project / www.r-project.org / R Studio (v2024.04.2) Posit https: / / posit.co / downlo

[0249]

[0250] ad / rstudio-desktop / Docket No. 084284.00346

[0251] Seurat (v5.2.1) Hao et al. (2024). Dictionary satij alab. org / seurat / learning for integrative,

[0252] multimodal and scalable single-cell

[0253] analysis. Nat Biotechnol 42, 293- 304*

[0254] Slingshot (v2.10.0) Street et al. (2018). Slingshot: cell github.com / kstreetl3 / sl lineage and pseudotime inference ingshot

[0255] for single-cell transcriptomics.

[0256] BMC Genomics 19, 477

[0257] Other

[0258] 96-well plate with cover Greiner Bio-One 655096

[0259] glass thickness

[0260] polystyrene bottom

[0261] Ti2E Ax R Confocal Nikon microscope.healthcare.

[0262]

[0263] Microscope nikon.com

[0264] Processing and subject selection of individual snRNA-seq studies

[0265] Datasets from the following studies were downloaded and processed following the original methods as a guide. All analysis was performed in R with the Seurat package (Hao et al. (2024). Dictionary learning for integrative, multimodal and scalable single-cell analysis. Nat Biotechnol 42, 293-304) unless otherwise specified.

[0266] 1. Y ang. A. C. et al. (2022). A human brain vascular atlas reveals diverse mediators of Alzheimer’s risk. Nature 603, 885-892

[0267] Raw data from hippocampal samples were downloaded from GSE163577. To pass quality control, nuclei had to meet the following criteria: (1) more than 200 features, (2) less than 5000 features, (3) less than 5% mitochondrial RNAs, and (4) less than 5% ribosomal RNAs. Doublets were filtered out using DoubletFinder (McGinnis et al. (2019). DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors. Cell Systems 8, 329-337. e4). The standard Seurat pipeline of NormalizeData(), FindVariableFeatures() (nfeatures = 2000), and ScaleData() was performed. The top 30 principal components (PCs) were used for UMAP generation at a resolution of 0.2. Harmony was used for batch correction (Korsunsky et al. (2019). Fast, sensitive and accurate integration of single-cell data with Harmony. Nat Methods 16, 1289-1296). Clusters were annotated using the marker genes defined in the source publication. Clusters annotated as astrocytes, endothelial cells, and mural cells were then extracted for generation of the harmonized cerebrovascular atlas. Docket No. 084284.00346

[0268] 2. Sun, N et al. (2023). Single-nucleus multiregion transcriptomic analysis of brain vasculature in Alzheimer's disease. NatNeurosci 26, 970-982

[0269] Processed and clustered data was downloaded from the source publication. Only individuals with APOE3 / 3, APOE3 / 4, and APOE4 / 4 genotypes were included. Nuclei labeled as endothelial cells, smooth muscle cells, and pericytes were extracted for construction of the cerebrovascular atlas.

[0270] 3. Haney, M. S. et al. (2024). APOE4 / 4 is linked to damaging lipid droplets in Alzheimer's disease microglia. Nature 628, 154-161

[0271] Raw data of AD samples was downloaded from GSE254205. Nuclei that passed the following quality control parameters were included for further analysis: (1) more than 500 features, (2) more than 1000 reads, (3) less than 10% mitochondrial reads, and (4) less than 10% ribosomal reads. Doublets were removed using DoubletFinder. The standard Seurat pipeline of NormalizeData(), FindVariableFeatures() (nfeatures = 2500), and ScaleData() was performed. The top 20 principal components (PCs) were used for UMAP generation at a resolution of 0.2. Harmony was used for batch correction. Clusters were annotated using the marker genes defined in the source publication. Clusters annotated as astrocytes and vascular cells were extracted.

[0272] After extracting the cerebrovascular cell types from each dataset, propensity matching for APOE4 carriers and non-carriers was performed within each dataset to minimize confounding variables and equalize the number of individuals with each genotype. Specifically, the R package Matchit (Ho et al. (2011). Matchit: Nonparametric Preprocessing for Parametric Causal Inference. Journal of Statistical Software 42. 1-28) was employed to match individuals using the following parameters:

[0273] APOE ~ age + sex + AD status + total cell count, method = ‘nearest ratio = 1 Cerebrovascular atlas integration and clustering

[0274] After propensity matching, data from the selected individuals were merged. The standard Seurat pipeline of NormalizeData(), FindVariableFeatures() (nfeatures = 2000), and ScaleData() was performed. Harmony was used for integration of the datasets with the following parameters: Docket No. 084284.00346

[0275] RunHarmony(c("subject", "dataset"), theta = c(2, 4)) The top 15 principal components (PCs) were used for UMAP generation at a resolution of 0.5. Clusters with high expression of markers of two or more cell types were excluded from further analysis. After excluding a cluster, the Seurat pipeline and harmony integration was repeated. Ultimately, three rounds of clustering were performed and the final integrated UMAP was generated at a resolution of 0.2. Clusters were manually annotated using canonical marker genes for astrocytes, endothelial cells, pericytes, and smooth muscle cells (SMCs).

[0276] For mural cell subclustering, pericytes and smooth muscle cell clusters were extracted. FindNeighbors(), FindClusters(), and RunUMAP() were re-run with the top 15 PCs at a resolution of 0.2. Subclusters were annotated using previously described marker genes (Yang et al. (2022). A human brain vascular atlas reveals diverse mediators of Alzheimer’s risk. Nature 603, 885-892; Sun et al. (2023). Single-nucleus multiregion transcriptomic analysis of brain vasculature in Alzheimer’s disease. NatNeurosci 26, 970-982).

[0277] Differential abundance analysis

[0278] 1. miloR

[0279] The miloR package was implemented in R (Dann et al. (2022). Differential abundance testing on single-cell data using k-nearest neighbor graphs. Nat Biotechnol 40, 245-253). For the entire cerebrovascular atlas, a k-nearest-neighbor (KNN) graph was generated using the buildGraph() function with parameters k = 50 and d = 30. Neighborhoods were generated with the makeNhoods() function with parameters prop = 0.1, k = 50, and d = 30 followed by calcNhoodDistance() with d = 30. Differential abundance between APOE4 carriers and non-carriers was assessed using the testNhoods() function with default parameters and the following design:

[0280] Design = -age + sex + AD status + dataset + apoe

[0281] For miloR differential abundance analysis of the mural cell subclusters, the same pipeline was used as disclosed herein, apart from the following differences in the parameters: buildGraph() (k = 30, d = 30). makeNhoods() (k = 30, d = 30), and calcNhoodDistance() (d = 30) For all functions, Harmony embeddings were used as the dimensionality reduction input. Docket No. 084284.00346

[0282] 2. DASeq

[0283] The DAseq package was implemented in R (Keable et al. (2020). ApoE4 Astrocytes Secrete Basement Membranes Rich in Fibronectin and Poor in Laminin Compared to ApoE3 Astrocytes. Int J Mol Sci 21, 4371). To compute APOE4 carrier vs. non-carrier differential abundance in mural cell subclusters. Harmony embeddings were used as input to DAseq along with APOE genotype labels for each subject. A range of neighborhood sizes (k.vector = seq(50, 500, 50)) was used to compute differential abundance (DA). Cells with DA scores above 0.7 or below -0.7 were classified as differentially abundant and visualized on UMAP coordinates. DA regions were identified using the getDAregion() function at a resolution of 0.05.

[0284] 3. Binomial generalized linear models to estimate subject-level cell proportions For myofibroblast proportions, the number of cells in the SMC_2 DAseq region defined as myofibroblasts were counted for each non- AD individual. Myofibroblast proportion per individual was defined as the number of myofibroblast cells divided by the total number of SMC_2 cells. A binomial generalized linear model (GLM) was then fit with a logit link using the glm() function in R. The following design was used:

[0285] glm(cbind(myofibroblast count, total SMC 2 count – myofibroblast count) ~ apoe + ns(age, df = 3) + sex + dataset, family = binomial())

[0286] Age was modeled with a natural cubic spline with 3 degrees of freedom to account for potential non-linear effects. Model diagnostics were assessed with the DHARMA package (Hartig, F. (2025). florianhartig / DHARMa). Model coefficients for each for the variables were extracted and expressed as odds ratios with 95% confidence intervals. For intermediate (ACTA2+ / CSPG4+) cell proportions, the same analysis was performed as disclosed herein except as a proportion of total mural cell count per individual.

[0287] Differential gene expression (DGE) analysis

[0288] 1. Single-cell DGE analysis of mural cell subclusters

[0289] Single-cell differential gene expression was performed with MAST (Finak et al. (2015). MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data. Genome Biology 16, 278) by using the Seurat FindMarkers() function. Pairwise comparisons between APOE4 carriers and non-carriers were performed for each mural cell subcluster. Age. sex, AD Docket No. 084284.00346

[0290] status, and dataset were included as covariates. A differentially expressed gene was defined as |logFC| > 0.25 and an adjusted p-value < 0.05.

[0291] 2. Pseudobulk DGE analysis of SMC_2 cluster

[0292] For the mural cell subclusters, gene expression counts were aggregated across cells for each subject using the AggregateExpression() function in Seurat, grouping by subject, APOE genotype, and mural cell t pe. The data was filtered to only include SMC 2 cells from individuals contributing at least 5 cells. A voom-limma (Ritchie et al. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43, e47) pipeline was then employed to model differential gene expression between APOE4 carriers and non-carriers. The following linear model was fit for each gene:

[0293] Yij = β₀ + β₁APOE4j + β₂agej + β₃sexj + β₄datasetj + β₅ADstatusj + εij In this model, Yy represents the voom-transformed expression value of gene i in subject / ; APOE4j is an indicator variable for APOE4 genot pe (with APOE3 as the reference); age,, sexj. dataset,, and ADstatusj represent the subj ect-level covariates for age, sex, dataset, and AD status, respectively; fio is the model intercept; Pi-fis are the estimated coefficients for each predictor; and Sy is the residual error term. For each gene, statistics were calculated using the eBayes () function.

[0294] 3. Myofibroblast marker genes

[0295] DGE was performed with MAST by using the Seurat FindMarkers() function. Within the SMC_2 subcluster, a pairwise comparison was performed between the cells in the APOE4-enriched DAseq region and the remaining SMC_2 cells. Age, sex, AD status, and dataset were included as covariates. A myofibroblast marker gene was defined as logFC > 0.25 and an adjusted p-value < 0.05.

[0296] Pathway analysis

[0297] Gene set enrichment analysis (GSEA) was performed using the fgsea R package (Korotkevich et al. (2021). Fast gene set enrichment analysis. Preprint at bioRxiv). The REACTOME database was input via the msigdbr R package (Dolgalev, I. (2025). msigdbr: MSigDB Gene Sets for Multiple Organisms in a Tidy Data Format. Version 25.1.1). Following APOE4 carrier vs. non-carrier differential gene expression analysis via MAST or voom-limma Docket No. 084284.00346

[0298] (see differential gene expression analysis methods section), genes were ranked according to the following formula:

[0299] ranking score = sign(avg_log2FC) × -log₁₀(p-value) Genes were then sorted in decreasing order and input into the fgsea package. The enrichment score, normalized enrichment score, p-values, and FDR-adjusted p-values were computed for each pathway. Significant pathways were defined as an adjusted p-value < 0.05. Redundant pathways were merged to enhance readability.

[0300] For Gene Ontology (GO) enrichment analysis, differentially expressed genes were input into the ClusterProfiler R package (Yu. et al. (2012). clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters) using the enrichGO() function with ont = “ALL Redundant pathways were merged with the simplify() function. Significant pathways were defined as an adjusted p-value < 0.05.

[0301] Unbiased cell type annotation

[0302] Cell type annotation was performed with the CellMarker_Augmented_2021 database via the enrichR package (Chen et al. (2013). Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14, 128; Zhang et al. (2019). CellMarker: a manually curated resource of cell markers in human and mouse. Nucleic Acids Res 47, D721-D728). APOE4-enriched genes from the pseudobulk SMC_2 DGE analysis (logFC > 0.25, p < 0.05, see DGE analysis methods) or the myofibroblast marker genes (see DGE analysis methods) were input into enrichR with default parameters. Only cell types with at least 10 marker genes and 3 hits were included. Redundant cell types were merged to enhance readability.

[0303] Seurat module scores

[0304] 1. Cellular contraction, extracellular matrix (ECM), and co-expression scores in mural cells

[0305] Module scores were calculated for each cell using the AddModuleScore() function in Seurat. The following genes were used for each module:

[0306] Contraction: ACTA2, TAGLN, ITGA1, ITGA2, ITGA8, CDH11, PALLD, SORBS1, LMOD2, TPM2

[0307] ECM: COL4A1, COL6A2, COL1A1, COL3A1, COL1A2, COL5A2, COL14A1, FN1, FBN1, DCN

[0308] Co-expression: Minimum of the two scores for each cell Docket No. 084284.00346

[0309] For comparison of module scores in APOE4 carriers vs. non-carriers, the data was filtered to only include SMC_2 cells from individuals contributing at least 5 cells. The module scores were then averaged across all cells per individual for subject-level comparisons between

[0310]

[0311] genotypes.

[0312] 2. TGF-P signaling in pericytes

[0313] The Pericyte_l and Pericyte_2 mural cell subclusters were extracted and a module score was calculated for each cell using the AddModuleScore() function in Seurat. The following genes were used for the module:

[0314] TGF-β signaling: TGFBR1, TGFBR2, TGFB1, TGFB2

[0315] For comparison of TGF-P gene expression in APOE4 carriers vs. non-carriers, the module score was then averaged across all cells per individual for subject-level comparisons between APOE genotypes.

[0316] Myofibroblast gene activity scores

[0317] Gene set variation analysis was performed using the GSVA R package (Hanzelmann et al. (2013). GSVA: gene set variation analysis for microarray and RNA-Seq data. BMC Bioinformatics 14, 7).

[0318] 1. Human cerebrovascular atlas

[0319] The data was filtered to only include SMC_2 cells from individuals contributing at least 5 cells. Gene expression counts were aggregated across cells for each subject using the AggregateExpression() function in Seurat, grouping by subject and APOE genotype. Myofibroblast marker genes were downloaded from a previous publication (cluster 11) (Gao et al. (2024). Cross-tissue human fibroblast atlas reveals myofibroblast subty pes with distinct roles in immune modulation. Cancer Cell 42, 1764-1783) and GSVA scores were assigned to each subject using the top 10 highly expressed myofibroblast marker genes in the dataset.

[0320] 2. APOE-TR mice

[0321] The processed and normalized 4-month-old mouse bulk RNA-seq data was downloaded from Synapse (syn26561824) (Foley et al. (2022). The APOEe3 / s4 Genotype Drives Distinct Gene Signatures in the Cortex ofYoung Mice. Front AgingNeurosci 14, 838436). GSVA scores were calculated for each sample using the myofibroblast marker genes from the cerebrovascular atlas (see myofibroblast marker genes in the DGE analysis methods section). The human genes were converted to their mouse orthologs prior to GSVA input. Docket No. 084284.00346

[0322] Pseudotime analysis

[0323] 1. Lineage assignment

[0324] Lineages were generated using the slingshot R package (Street et al. (2018). Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genomics 19, 477). The UMAP of mural cell subclusters was input into slingshot with the Pericyte_2 cluster assigned as the start cluster.

[0325] 2. Lineage bias

[0326] For the lineages predicted by slingshot, curve weights were assigned to each cell. The R package condiments (Roux de Bezieux et al. (2024). Trajectory inference across multiple conditions with condiments. Nat Commun 15, 833) was then used to test for differential lineage assignment between APOE genotypes. Specifically, the differentiationTest() function was performed for this analysis.

[0327] 3. Generalized additive models (GAMs)

[0328] Three sets of module scores were assigned to mural cells using the AddModuleScore() function in Seurat with the following genes:

[0329] Pericyte signature score: PDGFRB, ANPEP, CSPG4, KCNJ8, SLC20A2, SLC6A1

[0330] Myofibroblast signature score: the co-expression score defined in the Seurat module scores methods section

[0331] TGF-β signaling signature score: the hallmark TGF-β signaling gene set After assigning scores, separate GAMs with slingshot-derived lineage weights were fit for each module score with a smoothing parameter of k = 7 using the mgcv R package (Wood et al. (2011). Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models. J. R. Stat. Soc. Ser. B. Stat. Methodol. 73, 3-36). To compare scores between lineages, the differences in areas under the curve (A-AUC: pericyte-to-myofibroblast - pericyte-to-pericyte lineage) was calculated for each GAM. Permutation testing (n = 1000) was then used to generate a null distribution of A-AUC values. A two-sided p-value was calculated as the proportion of permuted A-AUC values exceeding the observed A-AUC in magnitude. Docket No. 084284.00346

[0332] NicheNet

[0333] The NicheNet R package was utilized for this analysis (Browaeys et al. (2020). NicheNet: modeling intercellular communication by linking ligands to target genes. Nat Methods 17, 159–162). A sender-focused approach was performed. The DAseq APOE4-enriched myofibroblast region was assigned as the receiver cell type. The astrocyte, endothelial, pericyte_l, pericyte_2, SMC_1, SMC_2, and myofibroblast clusters were assigned as the sender cell types. Genes expressed in at least 5% of receivers or senders were used in the analysis, and the differential genes input into NicheNet for ligand prediction were the myofibroblast marker genes defined in the DGE analysis methods section.

[0334] Association of mural cell FN1 expression with AD phenotypes

[0335] Mural cells from the Haney (2024) dataset (Haney et al. (2024). APOE4 / 4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628, 154-161) were extracted from the cerebrovascular atlas and FN1 expression was averaged per individual. Mural cell FN1 expression was then correlated with age of AD diagnosis. A global cerebral pathology score was assigned to each individual by averaging the following metadata columns reported in the original dataset: sum_lb_density, PlaqueTotal, TangleTotal, infarct_cerebral_total_volume. Scores were then dichotomized into high (top 25%) and low (bottom 75%) pathology groups to compare mural cell FN1 expression between them.

[0336] Bulk RNA-seq analysis of iPSC-derived mural cells (iMCs)

[0337] FPKM values were analyzed from a previous study (Blanchard, J. W., Bula, M., Davila-Velderrain, J., Akay, L A., Zhu, L., Frank, A., Victor, M B., Bonner, J. M., Mathys, H., Lin, Y.-T., et al. (2020). Reconstruction of the human blood-brain barrier in vitro reveals a pathogenic mechanism of APOE4 in pericytes. Nat Med 26, 952-963). After log-transforming the FPKM values, differential expression analysis between APOE3 / 3 and APOE4 / 4 iMCs was performed using the standard limma pipeline. Array weights were estimated using the arrayWeights () function and statistics were calculated for each gene using the eBayes() function with trend = TRUE and robust = TRUE. A differentially expressed gene was defined as |logFC| > 0.25 and an adjusted p-value < 0.05. Differentially expressed genes were input into ClusterProfiler for GO pathway analysis. Significant pathways were defined as an adjusted p-value < 0.05.

[0338] For CIBERSORTx (Newman et al. (2019). Determining cell ty pe abundance and expression from bulk tissues with digital cytometry. Nat Biotechnol 37, 773-782) deconvolution, the web-based application was used. Mural cell subclusters from the Docket No. 084284.00346

[0339] cerebrovascular atlas were used as the reference. Specifically, 10,000 mural cells were randomly downsampled from the atlas, and their gene counts were extracted. A signature matrix was generated using standard parameters, with a sampling ratio of 0.5 and inclusion of genes expressed in at least 25% of cells. Cell type proportions were then estimated from the bulk RNA-seq gene expression data using default CIBERSORTx settings. For downstream analysis, cell type proportions in APOE4 / 4 samples were expressed as log fold changes relative to the mean proportions in APOE3 / 3 samples.

[0340] Human iPSC cultures

[0341] Pre-coated Geltrex™ Matrix plates were seeded with iPSCs. iPSC colonies were then grown in StemFlex™ medium until 60-70% confluency. Subsequently, maintenance iPSCs were passaged using 0.5 mM EDTA to gently lift colonies. iPSCs for differentiation were harvested with Accutase™ cell detachment solution for 5-10 minutes at 37°C and differentiated as single cells according to the specified differentiated protocol.

[0342] Differentiation of human iPSCs into neurons

[0343] Protocol for neuron differentiation was adapted from Zhang et al. (2013). Rapid Single-Step Induction of Functional Neurons from Human Pluripotent Stem Cells. Neuron 78, 785–79 and Lam et al. (2024). Rapid iPSC inclusionopathy models shed light on formation, consequence, and molecular subtype of α-synuclein inclusions. Neuron 112, 2886-2909. In brief, Lipofectamine™ Stem Transfection Reagent was used to transfect iPSCs with PiggyBac plasmids to confer doxycycline-inducible expression of the Neurogenin-2 gene (NGN2, Addgene Plasmid #209077). In short, dissociated iPSCs were seeded on day zero at -104,000 cells / cm2onto plates coated with Geltrex™. The seeded cells then received StemFlex™ media containing 10μM Y27632 and 5μg / mL doxycycline supplements. On day 1, culture medium was replaced with Neurobasal N2B27 medium (Neurobasal, 1x B-27, 1x N-2, 1x MEM-NEAA, lx GlutaMAX™, 1% penicillin-streptomycin) containing 10μM SB431542, 100nM LDN, 5μg / mL doxycycline, and 5μg / mL puromycin supplements. On days 3-6, daily medium changes were performed with Neurobasal N2B27 media containing 1μg / mL puromycin and 5μg / mL doxycycline supplements. On day 6, cells were treated with 0.5 pM Ara-C. On day 7, cells were lifted with Accutase™ for integration into miBrains.

[0344] Differentiation of human iPSCs into astrocytes

[0345] Previously published iPSC-derived NPC (Chambers et al. (2009). Highly efficient neural conversion of human ES and iPS cells by dual inhibition of SMAD signaling. Nat Biotechnol 27, 275-280) and astrocyte (TCW et al. (2022). Cholesterol and matrisome Docket No. 084284.00346

[0346] pathways dysregulated in astrocytes and microglia. Cell 185, 2213-2233) differentiation protocols were followed to generate astrocytes. In summary, dissociated iPSCs were seeded onto Geltrex™ - coated plates at a cell density of 100,000 cells / cm2in pre-warmed StemFlex™ media containing 10μM Y27632 supplement. Cells received StemFlex™ every other day until cells reached 95% confluence. Once confluent, cells received NPC medium (1:1 DMEM / F12: Neurobasal Medium, lx N-2 Supplement, lx B-27 Serum-Free supplement, lx GlutaMAX™ Supplement, lx MEM-NEAA, 1% penicillin-streptomycin) containing 10μM SB43152 and 100nM LDN193189 supplements (day 0). From days 1 to 9, cells received daily media changes with the same media as day 0. On day 10, cells were split with Accutase™ and seeded onto plates coated with Geltrex™ and were grown in NPC media supplemented with 10 pM Y27632 and 20ng / mL bFGF. From days 11 through 13, cells received NPC media supplemented 20 ng / mL bFGF. On day 14, cells were split with Accutase™ and replated onto Geltrex™-coated plates and received NPC media supplemented with 10μM Y27632 and 20ng / mL bFGF. From day 15 onward, cells received fresh Astrocyte Medium (AM, ScienCell) every 2-3 days and were passaged using Accutase™ upon reaching 90% confluence. From this point on, NPCs were differentiated into astrocytes over a 30-day time course. NPCs and differentiated astrocytes were then cryopreserved in freezing medium, which consisted of 90% knockout serum replacement (KSR) and 10% dimethyl sulfoxide (DMSO).

[0347] Differentiation of human iPSC into brain microvascular endothelial cells

[0348] Brain endothelial cells were differentiated according to adapted protocols outlined in Blanchard et al. (2020). Reconstruction of the human blood-brain barrier in vitro reveals a pathogenic mechanism of APOE4 in pericytes. Nat Med 26, 952-963, Qian et al. (2017). Directed differentiation of human pluripotent stem cells to blood-brain barrier endothelial cells. Sci Adv 3, el701679, and Wang et al. (2020). Robust differentiation of human pluripotent stem cells into endothelial cells via temporal modulation of ETV2 with modified mRNA. Sci Adv 6, eaba7606. In summary, doxycycline-inducible expression of the ETS variant transcription factor 2 (ETV2, Addgene Plasmid #168805) was conferred in iPSCs by transfecting iPSCs with a PiggyBac plasmid. Inducible ETV2-iPSCs were cultured until 60-70% confluence before they were dissociated with Accutase™ and seeded at 20,800 cells / cm2onto plates coated in Geltrex™ that contained StemFlex™ supplemented with 10μM Y27632 on day 0. On day 1, culture medium was replaced with DeSR1 medium (DMEM / F12 with GlutaMAX™, lx MEM-NEAA, lx penicillin-streptomycin) containing 10 ng / mL BMP4, 6pM CHIR99021, and 5pg / mL doxycycline supplements. On days 5 and 7, cell media was changed and replaced with Docket No. 084284.00346

[0349] hECSR medium (Human Endothelial Serum-free Medium, Gibco; lx MEM-NEAA; 1 x B-27, 1% penicillin-streptomycin) that was supplemented with 50 ng / mL VEGF-A, 2pM Forskolin, and 5pg / mL doxycycline. On day 8, cells were lifted with Accutase™ and re-plated onto fresh plates coated with Geltrex™. Cells received hECSR media that was supplemented with 50 ng / mL VEGF-A and 5 pg / mL doxycycline. In the week following day 8, the supplemented day 8 medium was given to cells every’ 2-3 days to maintain cells until they were ready for tissue assembly in miBrains.

[0350] Differentiation of human iPSCs into mural cells

[0351] Mural cell differentiation protocol was based on published protocol from Patsch et al. (2015). Generation of vascular endothelial and smooth muscle cells from human pluripotent stem cells. Nat Cell Biol 17, 994-1003. Dissociated iPSCs were seeded at 37,000 to 40,000 cells / cm2onto plates coated with Geltrex™ and grown in StemFlex™ containing 10μM Y27632 supplement on day 0. On day 1, StemFlex™ medium was replaced with N2B27 medium (1:1 DMEM / F12, Neurobasal media, lx B-27, lx N-2, lx MEM-NEAA, lx GlutaMAX™, and 1% penicillin-streptomycin) containing 25 ng / mL BMP4 and 8pM CHIR99021 supplements. On days 3 and 4, cultures received a media change with N2B27 media supplemented with 10 ng / mL Activin A and 10 ng / mL PDGF-BB. On day 5, pericytes were lifted with Accutase™, plated at 35,000 cells / cm2onto plates coated in 0.1% gelatin, and grown in N2B27 containing 10 ng / mL PDGF-BB supplement. Cells received media changes with day 5 media every 2-3 days until confluent, at which point they were either frozen in freezing medium (90% KSR / 10%DMSO) in liquid nitrogen tanks or split onto 0.1% coated gelatin plates in N2B27 media and maintained until ready for miBrain tissue assembly. For monoculture experiments, cells were plated onto 96-well pClear plastic-bottom plates (Greiner) coated with 0.1% gelatin at a density of 2500-5000 cells per well, and fixed 96 h post-plating unless specified otherwise.

[0352] Differentiation of human iPSCs into oligodendrocyte progenitor cells

[0353] At nearly 100% confluence, iPSCs in mTeSRl with 10 pM Y27632 were plated on Matrigel (day -1). Every day until day 7, 2 mL of neural induction media (DMEM / F12 with lx NEAA, GlutaMAX™, 2-mercaptoethanol, and penicillin-streptomycin), with 10 pM SB431542, 250 nM LDN193189, and 100 nM RA (freshly added per use) was added. From day 8 through day 11, media was replaced daily with N2 medium (DMEM / F12 w ith lx NEAA, GlutaMAX™, 2-mercaptoethanol, and penicillin-streptomycin), along with lxN2 and 100 nM RA and luM SAG (added fresh daily). On day 12, a cell scraper lifted the cells, which were Docket No. 084284.00346

[0354] gently transferred to a 6-well ultra-low attachment plate with 3 mL of OPC-N2B27 medium (DMEM / F12 with lx NEAA, GlutaMAX™, 2-mercaptoethanol, penicillin-streptomycin. lx N2, lx B27 without Vit A, 25 μg / mL insulin, and freshly added 100 nM RA and 1 pM SAG). About two-thirds of the OPC-N2B27 media was changed every two days until day 20, without disturbance of the cell aggregates. From day 21 until day 30, PDGF medium (DMEM / F12 with lx NEAA, GlutaMAX™, 2-mercaptoethanol and penicillin-streptomycin, 1x N2, 1X B27 without Vit A, 25 ug / ml insulin, 100 ng / ml biotin, 1 pM cAMP, 5 ng / ml HGF, 10 ng / ml IGF-1, lOng / ml NT3, and 10 ng / ml PDGFaa) was added every other day. On day 30, aggregates measuring 300-800 pm in size were picked with a p200 pipette and plated on PLO / laminin-coated 6-well adherent plates. Cells were plated at a density of 20 cells per well in PDGF medium. Until day 75, two-thirds of the PDGF media was changed every other day. PDGF media was then changed every 2-3 days, and the differentiated OPCs were enriched through FACS with a lineage-specific marker. OPC differentiation followed the protocol from Douvaras et al. (2015). Generation and isolation of oligodendrocyte progenitor cells from human pluripotent stem cells. Nat Protoc 10, 1143-1154.

[0355] Differentiation of human iPSCs into microglia

[0356] To generate microglia, iPSCs were first differentiated into hematopoietic progenitor cells (HPCs) using STEMdiff™ Hematopoietic Kit (Catalog #05310). On days 12, 14, and 16 of the differentiation, floating HPCs were collected from media before freezing in CellBanker (AMSBIO). Following week 2 of miBrain assembly, HPCs were seeded into the existing tissue (25000 / 10 pL miBrain). miBrains were then maintained in miBrain media supplemented with lOOng / mL IL34 and 25ng / mL M-CSF. Microglia differentiation protocol was adapted from previous studies (McQuade et al. (2022). Human Induced Pluripotent Stem Cell-Derived Microglia (hiPSC-Microglia). In Induced Pluripotent Stem (iPS) Cells: Methods and Protocols, A. Nagy and K. Turksen, eds. (Springer US), pp. 473-482; McQuade et al. (2018). Development and validation of a simplified method to generate human microglia from pluripotent stem cells. Mol Neurodegeneration 13, 67).

[0357] 3D Tissue Assembly for miBrains

[0358] Neurons, endothelial cells, mural cells, and OPCs were lifted with Accutase™, and astrocytes in TrypLE™ Select. Cells were then resuspended in their respective media, counted, and resuspended at 1 x 106cells / mL. To assemble miBrains, a 15 mL Falcon tube for each miBrain condition was prepared to receive approximately 5 x 106neurons, 5 x 106endothelial cells. 1 x 106astrocytes. 1 x 106OPCs, and 1 x 106pericytes per 1 mL. Each tube of pooled Docket No. 084284.00346

[0359] cells was spun down for five minutes at RT at 200 x g. After carefully aspirating as not to disturb the cell pellet, each resulting pellet was placed on ice before resuspension in 1 mL Geltrex™, 10 μM Y27632 and 5 pg / mL doxycycline. Resuspension technique took care to avoid air bubbles, and cell pellets were kept on ice to prevent premature Geltrex™ polymerization and ensure successful seeding. 10 pL of encapsulated cell suspensions were then plated per well of a 96-well pClear plastic-bottom plate (Greiner). To allow the Geltrex™ to polymerize, seeded plates were transferred into a 37°C 95% / 5% Air / CO2 incubator for 30 minutes. After polymerization, miBrain cultures were completely submerged in miBrain week-1 medium (Human Endothelial Serum-free Medium, lx Pen / Strep, IX MEM-NEAA, IX CD Lipids, lx Astrocyte Growth Supplement (ScienCell), lx B27 Supplement, lOug / mL Insulin, IpM cAMP-dibutyl, 50pg / mL Ascorbic acid, 10ng / mLNT3, lOng / mL IGF, lOOng / mL Biotin, 60 ng / mL T3, 50 ng / mL VEGF, IpM SAG, 5 pg / mL doxycycline). Each well received 200 pL of media. Every 2-3 days, a half-media change was performed until day 8, before changing the media to miBrain week-2 medium (Human Endothelial Serum-free Medium, lx Pen / Strep, IX MEM-NEAA, IX CD Lipids, lx Astrocyte Growth Supplement (ScienCell), lx B27 Supplement, lOug / mL Insulin, IpM cAMP-dibutyl, 50pg / mL Ascorbic acid, lOng / mL NT3, lOng / mL IGF, lOOng / mL Biotin, 60 ng / mL T3, 5 pg / mL doxycycline). After 4 weeks, miBrain cultures were considered ready for downstream assays.

[0360] 3D tissue assembly for iPSC-derived endothelial cell monocultures

[0361] This protocol is the same as the miBrain protocol with the following differences. Each 10 pL Geltrex™ droplet contained 120,000 of only endothelial cells. Cultures were maintained in hECSR media supplemented with 50 ng / mL VEGF and 5 pg / mL doxycycline for two weeks until fixation (see immunofluorescence methods section).

[0362] Transduction of iPSC-derived mural cells with lentiviral shRNAs

[0363] FN1 and scramble MISSION lentiviral shRNAs were purchased from Sigma Aldrich. Lentivirus was generated in HEK293T cells following standard protocols. iPSC-derived mural cells were then transduced at a 1:40 dilution in mural cell culture media. Media was replaced 24 hours after transduction, and puromycin selection was initiated 72 hours post-transduction. Puromycin selection was maintained until cells were integrated into miBrains or collected for qRT-PCR validation of FN1 knockdown.

[0364] Amyloid and fibronectin treatments

[0365] 3D iPSC-derived endothelial cell monocultures were generated as previously described. For the amyloid treatment group, 20 nM of both amyloid-β 1-40 and 1-42 were incubated in Docket No. 084284.00346

[0366] cell culture media for 1 hour at RT. For the amyloid and fibronectin treatment group, 20 nM of both amyloid-β 1-40 and 1-42 were incubated with 50 ng / mL fibronectin for 1 h in cell culture media at RT. Cells were treated with these mixtures for 96 h before fixing (see immunofluorescence methods section).

[0367] TGF-β ligand treatments

[0368] iPSC-derived mural cells were seeded onto 96-well plates as previously described. 24 h post-plating, cells were treated with 50 ng / mL TGFβ1 for 96 hours followed by fixation (see immunofluorescence methods section).

[0369] TGF-β inhibitor treatments

[0370] For 2D treatments, iPSC-derived mural cells were seeded onto 96-well plates as previously described. 24 hours post-plating, cells were treated with 10 pM SB431542 for 96 hours followed by fixation. For miBrains, treatments were either initiated at 3-4 days postplating and maintained for 4 weeks until fixation or initiated at 2 weeks post-plating and maintained for the remaining 2 weeks until fixation. The concentrations used for miBrains were 10 pM SB431542 and 10 pM Galunisertib.

[0371] Immunofluorescence of cell cultures

[0372] 2D cultures were fixed in 4% paraformaldehyde for 15 minutes at room temperature, rinsed with PBS and permeabilized in 0.1% Triton-X100 in PBS for 10 minutes. Cultures were then blocked in 5% normal donkey serum in PBS for 2 h. Primary antibodies diluted 1:500 in blocking solution were added to cultures and incubated overnight at 4°C, before 3 consecutive rinses with PBS for 10, 20, and 30 minutes. Cultures were then incubated for 2h at room temperature with secondary antibodies diluted 1: 1000 in blocking solution. After rinsing once with PBS for 10 min, cultures were incubated for 20 min in Hoechst 33258 (Sigma- Aldrich, Cat. no. 94403) diluted at 1:1000 PBS. Cultures were then rinsed once more with PBS for 30 min. The PBS was then replaced prior to imaging. See corresponding image acquisition and quantification section.

[0373] 3D cultures and miBrains were incubated overnight at 4°C in blocking solution (0.3% Triton-X100, 5% normal donkey serum, in PBS). Primary antibodies, diluted 1:500 in blocking solution, were added the following day and left for 2-3 nights at 4°C. Cultures received 5 x 30 min rinses with 0.3% Triton-X100 PBS before adding secondary antibodies and Hoechst. Both were diluted at 1:1000 in blocking solution and cultures were left to incubate at 4°C for 1-3 nights. Cultures were rinsed for 5 x 30 min with 0.3% Triton-X100 PBS, before rinsing once Docket No. 084284.00346

[0374] more and leaving cells in regular PBS for image acquisition. See corresponding image acquisition and quantification section.

[0375] Mouse models

[0376] All experiments were performed in accordance with the Guide for the Care and Use of Laboratory Animals and were approved by the Institutional Animal Care and Use Committee at the Icahn School of Medicine at Mount Sinai (ISMMS). For all mouse experiments, C57BL / 6J background mice with their endogenous murine Apoe replaced with human APOE3 / 3 or APOE4 / 4 were used. Aged, retired breeder APOE-TR mice were purchased from Jackson Laboratories (APOE3 / 3-TR strain number: 029018; APOE4 / 4-TR strain number: 027894). Ages ranged from 8-10 months and were females. Mice were housed in the ISMMS vivarium under standard conditions until experimentation.

[0377] Immunofluorescence of mouse brain tissue

[0378] Mice were first anaesthetized via gaseous isoflurane exposure, followed by cardiac perfusion with ice-cold PBS and subsequently 4% paraformaldehyde (PFA). The brains were dissected out and post-fixed in 4% PFA at 4°C overnight. Fixed brains were placed in 30% sucrose in PBS until the tissue had sunk and were then embedded in OCT. Slices were cut at a thickness of 40 pm using a Leica cryostat and stored at -20°C in cryoprotectant solution until staining.

[0379] For free-floating immunofluorescence, sections were carefully transferred into a 24-well plate with fresh PBS and rinsed two more times. Slices were then blocked in a buffer containing 0.3% Triton X-100 and 5% normal donkey serum in PBS overnight at 4°C. Primary antibodies diluted in blocking buffer were added the following day for 2-3 nights at 4°C. Sections were washed 5 x 30 min in PBS, and secondary antibodies diluted in blocking buffer were added for 2 hours at RT. Slices were then washed 5 x 30 min in PBS and mounted on glass slides for imaging. For slices stained with lectin, lectin was diluted 1:200 in PBS as part of the first wash and left for 1 h. Hoechst was added 1:1000 in PBS as part of the second wash and left for 30 min. All images were acquired in the corpus callosum and in approximately the same locations of each slice to minimize biasing the results due to differences in anatomical regions (see image acquisition and quantification methods section).

[0380] Image acquisition and quantification

[0381] Images were acquired using a Nikon AX R confocal microscope. The same parameters were used for each image within an experiment, and the experimenter was blinded to the channels of interest or experimental condition during imaging. Images were analyzed using Docket No. 084284.00346

[0382] scripts from the Nikon AXR built-in quantification software, CellProfiler (Stirling et al. (2021). CellProfiler 4: improvements in speed, utility and usability. BMC Bioinformatics 22, 433), or FIJI / ImageJ (Schindelin et al. (2012). Fiji: an open-source platform for biological-image analysis. Nat Methods 9, 676-682). Statistical analysis was performed with GraphPad Prism or R.

[0383] Example 8. Harmonized single-nucleus atlas of the human APOE4 cerebrovasculature.

[0384] To generate a single-nuclei transcriptomics atlas of human cerebrovasculature from APOE3 / 3 and APOE4 carriers, three previously published snRNA-seq datasets of the postmortem human brain were integrated (Haney et al. (2024). APOE4 / 4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628, 154-161; Yang et al. (2022). A human brain vascular atlas reveals diverse mediators of Alzheimer’s risk. Nature 603, 885-892; and Sun et al. (2023). Single-nucleus multiregion transcriptomic analysis of brain vasculature in Alzheimer’s disease. Nat Neurosci 26, 970-982). These studies were selected for their inclusion of APOE genotype information and complementary strategies to enrich vascular cell populations that are typically underrepresented in single-cell transcriptomic datasets. To minimize confounding variables, unbiased propensity score matching was performed independently within each dataset to select a final cohort of APOE4 carriers and non-carriers matched for age, sex, AD status, and the number of vascular cell nuclei contributed per individual. Vascular cells from these matched individuals were harmonized to generate an integrated cerebrovascular atlas, capturing diverse vascular subtypes across individuals and providing a comprehensive foundation for downstream analyses. After processing and quality control, the atlas consisted of -64,000 nuclei from 220 individuals (32,396 APOE3 / 3 (n = 110; F=57, M=53) and 31,673 APOE4 (n = 110; F=53, M=57). Clustering based on canonical cell-type-specific marker gene expression identified distinct populations of the major cerebrovascular cell types: astrocytes (AQP4), endothelial cells (PECAM1), pericytes (PDGFRB), and smooth muscle cells (SMCs) (MYH11).

[0385] Example 9. APOE4 alters vascular cell composition in the human brain.

[0386] Previous transcriptomic studies of the APOE4 vasculature primarily focused on differential gene expression, with limited statistical power to detect changes in cell type abundance. By harmonizing multiple datasets into a single, integrated atlas, this study was able to overcome these limitations and robustly assess whether APOE4 alters the cerebrovascular cell-type composition. Differential abundance analysis was performed across all vascular cell types using MiloR, a k-nearest neighbor graph-based approach designed to detect changes in Docket No. 084284.00346

[0387] non-discrete cell populations that occur along differentiation or developmental trajectories (Dann et al. (2022). Differential abundance testing on single-cell data using k-nearest neighbor graphs. Nat Biotechnol 40, 245-253). Given the plasticity of vascular cell states and the absence of consistent markers to clearly delineate vascular subtypes, this approach is well-suited for capturing abundance differences across transitional populations. Using MiloR, 148 cell neighborhoods were identified with significant differential abundance between APOE4 carriers and APOE3 / 3 individuals (spatial FDR < 0.05).

[0388] Example 10. Pericyte loss in APOE4 carriers coincides with the emergence of atypical non-vascular SMCs.

[0389] To examine the directionality of APOE4-associated changes in vascular cell composition, the fold changes of significantly altered neighborhoods for each cell type were plotted. APOE4 carriers showed a significant reduction of pericytes (0.36-log-fold decrease, p = 0.006) and a significant increase of SMCs (0.75-log-fold increase, p = 0.0001) compared to APOE3 / 3 individuals. In contrast, astrocytes and endothelial cells exhibited no significant net changes in abundance (1.1-log-fold decrease in astrocytes, p = 0.50; 0.11-log-fold increase in endothelial cells, p = 0.42), leading the analysis to focus on mural cells.

[0390] Age-related cognitive decline is associated with hippocampal cerebrovascular degeneration and elevated cerebrospinal fluid (CSF) levels of the pericyte injury marker soluble PDGFRp (sPDGFR ). APOE4 further accelerates cognitive decline and increases CSF sPDGFRβ) in humans, suggesting that the reduced pericyte abundance observed in APOE4 carriers may reflect pericyte injury or a cell-state transition. To directly assess APOE4-associated pericyte loss, NG2 immunostaining was performed on postmortem human hippocampal sections. APOE4 carriers exhibited a significant reduction in NG2-positive pericyte coverage along hippocampal vasculature compared to age-matched APOE3 / 3 individuals (0.21 ± 0.042-fold change, corresponding to a 79% decrease relative to APOE3 / 3, p = 0.0008, FIG.5A). It was next asked whether pericyte loss corresponded with the increase in SMCs revealed by the differential abundance analysis. Human postmortem staining revealed significantly increased a-SMA immunoreactivity in the APOE4 hippocampus compared to APOE3 / 3 controls (1.97 ± 0.35-fold increase, p = 0.0141, FIG. 5B). However, while a-SMA positivity was primarily confined to large vessels in APOE3 / 3 hippocampi, APOE4 carriers displayed abundant a-SMA immunoreactivity throughout the parenchyma (FIG. 5B).

[0391] Together, these findings indicated that APOE4 carriers exhibit both pericyte loss and the emergence of atypical non-vascular a-SMC cells, consistent with a mural cell phenotypic shift. Docket No. 084284.00346

[0392] This prompted further investigation of whether APOE4 alters mural cell identity at the transcriptional level.

[0393] Example 11. A myofibroblast-like mural cell population is enriched in the APOE4 brain.

[0394] To investigate APOE4-associated transcriptional changes in mural cells, the original pericyte and SMC populations were subclustered. Consistent with previous studies, two pericyte subtypes (Pericyte_1 and Pericyte_1) and two SMC subtypes (SMC_1 and SMC_2) were identified. Differential gene expression analysis was performed between APOE4 carriers and APOE3 / 3 homozygotes within each mural cell subtype and gene set enrichment analysis was employed to identify dysregulated pathways. Among all mural cell subtypes, SMC_2 showed the greatest impact of APOE4, with 40 dysregulated pathways, followed by Pericyte_1 (11 pathways), SMC_1 (7 pathways), and Pericyte_2 (5 pathways) (FDR < 0.05).

[0395] Because SMC_2 exhibited the most extensive transcriptional changes, it was hypothesized that transcriptional changes in this cluster may underlie the non-vascular a-SMA staining pattern observed in the APOE4 postmortem human brain. Pathway enrichment analysis revealed that the most upregulated pathways in APOE4 SMC_2 cells were related to cellular contraction (e.g., muscle contraction, RHO GTPase signaling) and extracellular matrix (ECM) production (e.g., elastic fiber formation, ECM proteoglycans). To account for intraindividual cellular correlations, upregulation of contraction- and ECM-related pathways in APOE4 SMC_2 cells was confirmed using a pseudobulk approach (FDR < 0.05). SMCs are classically described as adopting either a contractile state (high expression of ACTA2 and TAGLN and low ECM gene expression), or a synthetic state (low contractile gene expression and high levels of ECM components, including FN1 and various collagens). To determine whether the APOE4 SMC_2 population reflects an expansion of these canonical states or a distinct phenotype with simultaneous activation of both programs, the contraction and ECM gene signature scores were calculated for mural cells in the cerebrovascular atlas using established marker genes. Consistent with the pathway analysis, both contraction and ECM signatures were significantly upregulated in SMC_2 cells from APOE4 carriers (contraction score: 1.37 ± 0.10-fold increase, p = 0.0343; ECM score: 1.51 ± 0.10-fold increase, p = 0.0113). Importantly, the proportion of SMC_2 cells co-expressing both ECM and contractile signatures was significantly higher in APOE4 carriers (1.33 ± 0.07-fold increase, p = 0.0321).

[0396] The concurrent expression of both contraction and ECM signatures is a hallmark of myofibroblasts, the principal effector cells of tissue fibrosis. Although myofibroblasts have been extensively studied in peripheral organs, they have also been reported in the brain Docket No. 084284.00346

[0397] following traumatic injury or ischemic events, where some are thought to arise from pericytes that detach from the vasculature. To determine whether the APOE4-enriched SMC 2 population resembles myofibroblasts, unbiased cell-type annotation was performed using EnrichR with the CellMarker database (Chen et al. (2013). Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14, 128; Kuleshov et al. (2016). Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res 44, W90-97; Xie et al. (2021). Gene Set Knowledge Discovery with Enrichr. Current Protocols 1, e90). Myofibroblasts were identified as the top-matching cell type for the APOE4 SMC_2 gene signature. Consistent with this annotation, myofibroblast gene activity scores were significantly higher in SMC_2 cells from APOE4 carriers compared with APOE3 / 3 individuals (1.39 ± 0.41-fold increase, p = 0.0436).

[0398] To determine whether myofibroblasts are selectively enriched in APOE4 carriers, differential abundance analysis of mural cell clusters was performed using DAseq. This analysis revealed a distinct subregion within the SMC_2 cluster that was significantly enriched in APOE4 individuals and spatially colocalized with the peak of ECM and contractile gene coexpression, a finding independently validated with miloR analysis. Differential gene expression and pathway enrichment analyses further showed that this APOE4-enriched subregion upregulated genes involved in cell-substrate junctions, ECM organization, and contractile fibers (e.g., FN1, COL3A1, ACTA2, COL8A1, TGFbIII), hallmark features of a myofibroblast state. In contrast, the remaining SMC 2 cells expressed genes linked to vascular stability (e.g., FLT1, EPAS1, TIMP3, ADAMTS9) and downregulated cell migration pathways, consistent with a more quiescent, vessel-associated phenotype. Unbiased annotation of this enriched subregion again identified myofibroblast as the top-matching cell type. Together, the transcriptional profile of APOE4 SMC_2 cells, the results of unbiased cell-type annotation and differential abundance analyses, and the presence of non-vascular parenchymal a-SMA staining in postmortem brain tissue strongly support that the APOE4-enriched SMC_2 subpopulation represents myofibroblasts.

[0399] Previous studies have shown that cerebrovascular degeneration in APOE4 carriers occurs independently of amyloid and tau pathology, but the mechanisms by which APOE4 drives cerebrovascular degeneration remain unclear. Therefore, it was asked whether the myofibroblast population that were identified arise independently of AD pathology and could represent an upstream driver of APOE4-mediated vascular degeneration. A sub-cohort of non-AD individuals with and without APOE4 was first analyzed. For each individual, the Docket No. 084284.00346

[0400] proportion of myofibroblasts were quantified and these values were modeled using a binomial generalized linear model, adjusting for APOE4 genotype, age, sex. and dataset origin. Model diagnostics confirmed a good fit with no significant violations of assumptions. APOE4 emerged as the strongest predictor of myofibroblast abundance (odds ratio = 5.51 ± 0.28, p < 0.0001), and even in the absence of AD, carriers exhibited significantly higher myofibroblast proportions than APOE3 / 3 individuals (19.80 ± 2.13% increase, p < 0.0001; FIG. 5C), suggesting that APOE4 itself promotes myofibroblast accumulation.

[0401] To further test whether APOE4 promotes myofibroblast formation in the absence of AD or other cerebrovascular pathology, aged APOE targeted replacement (TR) mice were analyzed in which the murine Apoe gene is replaced with human APOE3 / 3 or APOE4 / 4 alleles. Bulk RNA-seq data (Foley et al. (2022). The APOEε3 / ε4 Genotype Drives Distinct Gene Signatures in the Cortex of Young Mice. Front Aging Neurosci 14, 838436) from cerebral cortices of APOE3 / 3, APOE3 / 4, and APOE4 / 4 TR mice were scored for myofibroblast gene activity using GSVA with marker genes from the human cerebrovascular atlas. APOE4 gene dosage was positively correlated with myofibroblast gene activity (pcc = 0.25, p = 0.038). Immunofluorescence of hippocampal and cortical vessels further validated these findings. While both genoty pes exhibited strong a-SMA expression in large cerebral vessels, APOE4 / 4 mice displayed a significant reduction in pericyte coverage of small vessels (< 6 pm) compared with APOE3 / 3 controls (0.80 ± 0.044-fold change; 20% decrease; p = 0.0189; FIG. 5D). This pericyte loss coincided with increased a-SMA immunoreactivity in cells proximal to small vessels and within the parenchyma, consistent with a myofibroblast identity (1.74 ± 0.21-fold increase; p = 0.0264; FIG. 5D). These results indicate that APOE4 promotes the induction of non-vascular myofibroblasts in aged mice in the absence of other AD genetic factors.

[0402] Finally, it was assessed whether APOE4 is sufficient to induce myofibroblasts in a human context using miBrains, a 3D human brain tissue derived from isogenic APOE3 / 3 or APOE4 / 4 iPSCs differentiated into the six major brain cell types (Stanton et al. (2023). Engineered 3D Immuno-Glial-Neurovascular Human Brain Model. Preprint at bioRxiv; Mesentier-Louro et al. (2025). Cholesterol-mediated Lysosomal Dysfunction in APOE4 Astrocytes Promotes a-Synuclein Pathology in Human Brain Tissue. Preprint at bioRxiv). Consistent with the human and mouse findings, compared to isogenic APOE3 / 3 miBrains, APOE4 / 4 miBrains exhibited a marked reduction in pericyte coverage (0.43 ± 0.056-fold change; 57% decrease; p < 0.0001). accompanied by increased non-vascular a- Docket No. 084284.00346

[0403] SMA immunoreactivity' (3.80 ± 0.43-fold increase; p < 0.0001; FIG. 5E). Together, these results demonstrate that APOE4 is sufficient to promote pericyte loss and the emergence of non-vascular myofibroblasts, recapitulating the transcriptional and morphological features observed in human and mouse APOE4 brains.

[0404] Example 12. APOE4 promotes a pericyte-to-myofibroblast transition.

[0405] Having identified a robust APOE4-associated myofibroblast phenotype across three model systems, the next goal was to determine whether this phenotype arises within mural cells or requires interaction with other APOE4-expressing cell types. To test this, a hybrid genetic mixing experiment was performed in which isogenic APOE3 / 3 mural cells (iMCs) were selectively integrated into APOE4 / 4 miBrains. As expected, APOE4 / 4 miBrains exhibited significantly reduced pericyte coverage and increased a-SMA immunoreactivity compared to isogenic APOE3 / 3 controls (pericyte coverage: 0.39 ± 0.10-fold change, corresponding to 61% decrease relative to APOE3 / 3, p = 0.0018; a-SMA: 2.99 ± 0.65-fold increase, p = 0.0214; FIG.

[0406] 6A). Strikingly, replacing APOE4 / 4 iMCs with isogenic APOE3 / 3 iMCs reversed these phenotypes, leading to a significant reduction in a-SMA-positive cells and restoration of NG2-positive cell coverage along the vasculature (pericyte coverage: 1.60 ± 0.016-fold increase relative to APOE4 / 4, p < 0.0001; a-SMA: 0.34 ± 0.14-fold change, corresponding to a 66% decrease relative to APOE4 / 4, p = 0.0229; FIG. 6A). These findings indicated that APOE4 expression in mural cells is necessary for pericyte loss and myofibroblast accumulation. This experiment was repeated with iMCs derived from two additional isogenic iPSC lines from an AD and non- AD individual with reciprocal gene editing strategies (Non- AD E3- E4 [ADRC line] and AD E4- E3 [sAD line]) and similar results were obtained. To assess whether APOE4 mural cells are sufficient to induce myofibroblasts, iMC monocultures were examined. Immunostaining showed significantly higher a-SMA and fibronectin levels in APOE4 / 4 iMCs compared to isogenic APOE3 / 3 controls across all donor lines. Taken together, these findings from both APOE-TR mice and the iPSC models point to a causal role for APOE4 mural cells in the expansion of a myofibroblast population.

[0407] It was next investigated how APOE4 mural cells generate the myofibroblast population. In multiple organ systems, including the brain, pericytes differentiate into myofibroblasts following injury. A pericyte-to-myofibroblast transition (PMT) would explain the observed correlation between myofibroblast expansion and pericyte loss (FIGS. 5A-5B, 5D and 5E).

[0408] To explore this possibility, pseudotime analysis w as performed of the human cerebrovascular atlas. This revealed two distinct pericyte-derived trajectories: one first terminating in the Docket No. 084284.00346

[0409] APOE4-enriched myofibroblast population (pericyte-to-myofibroblast lineage) and another terminating in pericytes (pericyte-to-pericyte lineage). Gene signature scoring confirmed that the first trajectory was characterized by strong myofibroblast gene activity (AUC = 2.45, p < 0.0001) and the loss of pericyte identity (AUC = -4.18, p < 0.0001). To determine whether APOE genotype influences lineage conversion, curve weights were calculated for both trajectories. APOE4 mural cells were significantly enriched along the pericyte-to-myofibroblast trajectory, whereas APOE3 / 3 cells preferentially aligned with the pericyte-to-pericyte trajectory.

[0410] In vivo, the PMT transition is reported to occur as a gradual continuum, rather than a binary' switch, with cells progressively shifting from a pericy te to a myofibroblast identity. This process includes an intermediate state in which cells co-express CSPG4 (pericvte marker) and ACTA2 (SMC / myofibroblast marker). It was reasoned that if APOE4 promotes a PMT, APOE4 carriers should show not only pericyte loss and a gain of myofibroblasts, but also an enrichment of these intermediate CSPG4 i / ACTA2 i mural cells. To test this, double-positive cells were identified in the cerebrovascular atlas using defined gene expression cutoffs. The analysis was restricted to non-AD individuals to isolate the effect of APOE genotype. APOE4 carriers exhibited a higher abundance of double-positive CSPG4+ / ACTA2+ cells compared to APOE3 / 3 individuals (4.60-fold increase, p < 0.0001). To confirm this enrichment, this proportion of intermediate cells per individual was modeled using a binomial generalized linear model, adjusted for APOE genotype, age, sex. and dataset origin. Model diagnostics indicated a good fit, with no significant violations of model assumptions. APOE4 genotype emerged as the strongest predictor of CSPG4+ ACTA2+ mural cell abundance (odds ratio = 5.51 ± 0.10,p < 0.0001). Even in the absence of AD, APOE4 carriers had a significantly higher proportion of intermediate cells than age- and sex-matched APOE3 / 3 individuals (5.98 ± 0.76% increase, p < 0.0001; FIG. 6B), supporting an APOE4-driven pericyte-to-myofibroblast transition.

[0411] To determine whether this intermediate state is also present in the experimental models, mural cells in miBrains and APOE-TRmice were quantified as pericytes (vascular NG2+ / a-SMA), intermediate cells (NG2+ / a-SMA+), or myofibroblasts (non-vascularNG2- / a-SMA+). To avoid misclassification, analyses were restricted to small vessels (< 6 mm) lacking SMCs, focusing on non-vascular a-SMA+ cells. Consistent with the atlas findings, APOE4 / 4 miBrains and APOE4 / 4-TR mice exhibited a significant reduction in pericyte abundance (miBrains: 80.55 ± 4.90% APOE4 / 4 vs. 97.68 ± 1.08% APOE3 / 3, p = 0.0116; APOE-TR mice: 37.56 ± 4.09% APOE4 / 4-TR vs. 91.93 ± 4.46% APOE3 / 3-TR. p = 0.0009). This decrease coincided Docket No. 084284.00346

[0412] with a significant increase in APOE4 / 4 myofibroblast abundance that was absent in isogenic APOE3 / 3 control (miBrains: 11.44 ± 3.14% APOE4 / 4 vs. 0.33 ± 0.22% APOE3 / 3, p = 0.0164; APOE-TR mice: 37.68 ± 3.72% APOE4 / 4 vs. 1.96 ± 1.96% APOE3 / 3, p = 0.0033). Notably, in APOE4 mice and miBrains cells along small cerebral vessels strongly co-expressing a-SMA and NG2 were also observed, reflective of an intermediate transition state associated with the PMT (miBrains: 8.02 ± 2.25% APOE4 / 4 vs. 1.99 ± 0.88% APOE3 / 3, p = 0.0439; APOE-TR mice: 24.76 ± 3.28% APOE4 / 4 vs. 6.11 ± 4.72% APOE3 / 3, p = 0.0371). To further validate the occurrence of a pericyte-to-myofibroblast transition in the experimental models, the average distance of each cell type from the vasculature in both APOE4 / 4 miBrains and APOE4 / 4-TR mice was quantified. In both model systems, vascular distance increased in a stepwise manner from pericytes to intermediate cells to myofibroblasts, supporting a model in which pericytes detach from vessels and migrate into the parenchyma while acquiring myofibroblast characteristics (APOE4 / 4 miBrains: R2= 0.53, p = 0.0009; APOE4 / 4-TR mice: R2= 0.81, p = 0.0028). Taken together, these results support that APOE4 promotes a stepwise pericyte-to-myofibroblast transition in both human and in vivo models.

[0413] Finally, the APOE4-induced PMT was examined in iMC monocultures. Using CIBERSORTx (Newman et al. (2019). Determining cell type abundance and expression from bulk tissues with digital cytometry. Nat Biotechnol 37, 773-782) deconvolution of a bulk RNA-seq dataset (Blanchard, et al. (2020). Reconstruction of the human blood-brain barrier in vitro reveals a pathogenic mechanism of APOE4 in pericytes. Nat Med 26. 952-963), iMCs were mapped onto mural cell subclusters from the cerebrovascular atlas. Without stratifying by APOE genoty pe, it was found that iMCs transcriptionally align most with the Pericyte_l cluster compared to other mural cell subtypes. However, investigating cell type identify scores between genotypes revealed two significant shifts: a loss of Pericyte_1 identity and a gain of myofibroblast identity in APOE4 / 4 iMCs relative to APOE3 / 3 (Pericyte l: -0.36 ± 0.078 logFC, adjusted p = 0.0473; myofibroblast: 0.53 ± 0.063 logFC, adjusted p = 0.0116). Differential expression analysis further confirmed upregulation of canonical myofibroblast genes in APOE4 / 4 iMCs. Collectively, these results across human tissue, iPSC-derived models, and APOE-TR mice demonstrate that APOE4 in mural cells is sufficient to drive a pericyte-to-myofibroblast transition. Docket No. 084284.00346

[0414] Example 13. Myofibroblast-derived fibronectin increases amyloid accumulation in APOE4 models.

[0415] Myofibroblasts are key mediators of fibrosis, functioning as major sources of extracellular matrix (ECM) proteins, particularly collagens and fibronectin (FN1). Excessive ECM deposition by myofibroblasts leads to pathological tissue remodeling and organ dysfunction. Recent studies have identified genetic variants in FN1 associated with cognitive resilience in APOE4 carriers, suggesting that altered fibronectin biology may influence disease outcomes in APOE4 carriers. Therefore, it was examined whether APOE4-associated myofibroblasts promote fibronectin deposition in the brain vasculature. In APOE4 / 4-TRmice, fibronectin immunoreacti vity was significantly increased along small vessels compared to age-and sex-matched APOE3 / 3-TR controls (2.02 ± 0.19-fold increase, p = 0.0028), coinciding with elevated a-SMA staining (2.39 ± 0.52-fold increase, p = 0.0447; FIG. 7A). Notably, most of the fibronectin deposition in APOE4 / 4-TR mice occurred near a-SMA+ regions (72.66 ± 1.90%, p = 0.0013), implicating myofibroblasts as a causal source of vascular fibrosis. Consistent with these findings, APOE4 / 4 miBrains also exhibited increased fibronectin accumulation along the vasculature relative to isogenic APOE3 / 3 miBrains (1.56 ± 0.16-fold increase, p = 0.0058; FIG. 7B).

[0416] Myofibroblasts were the largest contributor of FN1 expression among individuals from the cerebrovascular atlas (FIG. 7C). In the central nervous system, perivascular fibroblasts are also a major source of fibronectin and contribute to fibrotic scar formation in response to brain injury. To further confirm that APOE4-myofibroblasts are primarily responsible for FN1 upregulation, perivascular fibroblasts were analyzed from the original snRNA-seq datasets corresponding to the same subjects included in the cerebrovascular atlas. It was found that the myofibroblasts identified in this study exhibited significantly (p < 0.0001) higher FN1 expression compared to fibroblasts, and that APOE genotype had no significant (FDR > 0.05) effect on ECM-related pathways in fibroblasts, further highlighting myofibroblasts as the causal cell type in the study.

[0417] To assess how mural cell FN1 expression relates to clinical characteristics of AD, the cerebrovascular atlas was analyzed using the Haney (2024) dataset (Haney et al. (2024). APOE4 / 4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628, 154-161), which includes extensive clinical annotations. This study focused on individuals with an AD diagnosis and pseudobulked mural cell FN1 expression for each individual to specifically examine FN1 within the context of the pericyte-to-myofibroblast transition. Docket No. 084284.00346

[0418] Consistent with earlier findings, APOE4 carriers had significantly higher mural cell FN1 expression compared to APOE3 / 3 individuals (1.30 ± 0.11-fold increase, p = 0.0294). Supporting a role for fibronectin in AD progression, mural cell FN1 expression negatively correlated with age of AD diagnosis (r = -0.53, p = 0.036). A global pathology score for each individual was also derived by averaging their total amyloid plaque, neurofibrillary tangle, Lewy body, and cerebral infarct scores reported in the original dataset. Individuals in the highest quartile of global pathology had significantly elevated mural cell FN1 expression compared to the remaining individuals (1.33 ± 0.11 -fold increase relative to the low pathology group, p = 0.0114), suggesting a link between APOE4-driven fibronectin deposition and AD pathology.

[0419] To investigate the causal role of fibronectin in AD pathology, the miBrain system was leveraged. Because APOE4 carriers are highly susceptible to vascular amyloid deposition and fibronectin can directly bind amyloid, this study focused on perivascular amyloid-P accumulation. To first validate the miBrain as a model for this pathology', isogenic APOE3 / 3 and APOE4 / 4 miBrains were immunostained using three separate antibodies each targeting distinct amyloid-P epitopes. Consistent with observations in APOE4 carriers, APOE4 / 4 miBrains showed significantly increased amyloid-P immunoreactivity along the vasculature with all three antibodies compared to isogenic APOE3 / 3 controls (12F4: 1.61 ± 0.16-fold increase, p = 0.0085; 6E10: 1.26 ± 0.056-fold increase, p = 0.0149; D54D2: 3.38 ± 0.074-fold increase, p < 0.0001; FIG. 7D).

[0420] Previous results indicate that APOE4 mural cell-derived myofibroblasts are the primary source of increased fibronectin deposition in APOE4 / 4-TR mice. To directly test this, APOE4 / 4 mural cells were swapped to APOE3 / 3 in an APOE4 / 4 miBrain, an approach that previously reversed APOE4-associated myofibroblast phenotypes (FIG.6A). Remarkably, this single swap led to a significant reduction in fibronectin protein accumulation to similar levels as the APOE3 / 3 baseline (0.60 ± 0.058-fold change, corresponding to a 40% decrease relative to APOE4 / 4, p = 0.0344; FIG. 7E), demonstrating that APOE4 vascular fibrosis is driven by myofibroblasts. These results were reproduced with isogenic mural cells derived from two different donors (with and without AD). If fibronectin causally contributes to amyloid-P pathology, then reducing myofibroblast-derived fibronectin should also lower amyloid accumulation. Consistent with this, APOE4 / 4 miBrains containing APOE3 / 3 iMCs displayed significantly reduced vascular amyloid deposition compared to all APOE4 / 4 controls (0.69 ± Docket No. 084284.00346

[0421] 0.073-fold change, corresponding to a 31% decrease relative to APOE4 / 4, p = 0.0336; FIG.

[0422] 7E).

[0423] To determine whether the reduction in amyloid pathology observed when APOE3 / 3 iMCs replaced APOE4 / 4 iMCs in the miBrain was mediated by decreased fibronectin, APOE4 / 4 iMCs were transduced with a shRNA targeting FN1 or a scramble control. qRT-PCR of iMC monocultures confirmed robust FN1 knockdown (0.037 ± 0.0018-fold change, corresponding to a 96.3% decrease relative to scramble, p = 0.0009). FN1 knockdown and control APOE4 / 4 iMCs were then incorporated into APOE4 / 4 miBrains to directly assess the impact of fibronectin depletion on amyloid accumulation. FN1 knockdown led to markedly reduced fibronectin staining and a concomitant decrease in vascular amyloid deposition compared to scramble controls (fibronectin: 0.44 ± 0.036-fold change, corresponding to a 56% decrease relative to scramble, p = 0.0037; amyloid: 0.88 ± 0.027-fold change, corresponding to a 12% decrease relative to scramble, p = 0.0353; FIG. 7F). To further validate the causal link between fibronectin and amyloid accumulation, APOE3 / 3 iPSC-derived endothelial cells were treated with amyloid alone or an amyloid-fibronectin mixture. Cells exposed to the amyloid-fibronectin mixture exhibited significantly greater amyloid accumulation than those treated with amyloid alone (2.08 ± 0.15-fold increase, p < 0.0001, FIG. 7G). Together, these findings demonstrate that fibronectin secreted by APOE4-derived myofibroblasts promotes vascular amyloid accumulation, establishing a direct mechanistic link between myofibroblasts and AD progression in APOE4 carriers.

[0424] Example 14. Increased TGF-P signaling in the APOE4 brain promotes the pericyte-to-myofibroblast transition

[0425] Having identified a key role for APOE4-derived myofibroblasts in AD pathology, it was next investigated the molecular mechanisms through which APOE4 promotes the PMT. NicheNet (Browaeys et al. (2020). NicheNet: modeling intercellular communication by linking ligands to target genes. Nat Methods 17, 159–162) was applied, which is a computational tool that predicts upstream ligands regulating target gene expression, using APOE4 myofibroblast marker genes identified in the human cerebrovascular atlas as input. NicheNet identified TGF-P as the top predicted driver of the PMT. In agreement with its established role in fibrosis, TGF- ligands were predicted to regulate multiple myofibroblast-associated genes, including FN1, ACTA2, and COL1A2. Fibrosis in the CNS can also arise dow nstream of an interferon-gamma-mediated cascade, particularly in neuroinflammatory diseases such as multiple sclerosis. However, APOE4 myofibroblasts show no change in interferon-gamma signaling at Docket No. 084284.00346

[0426] either the gene or pathway level. These findings suggest that APOE4 cerebrovascular fibronectin and amyloid deposition occur through a TGF-p-dependent, IFN-y-independent mechanism.

[0427] Within the postmortem human cerebrovascular atlas, TGFβ1 was predominantly expressed by myofibroblasts and TGFβ2 by astrocytes, with only modest differences in ligand expression between APOE4 and APOE3 / 3 individuals. However, TGF-P signature scoring along pseudotime lineages revealed significantly increased TGF-P hallmark gene activity along the pericyte-to-myofibroblast trajectory compared to the pericyte-to-pericyte trajectory (0.479 AUC, p < 0.0001). Furthermore, pericytes from APOE4 carriers displayed significant upregulation of key TGF-β genes (TGFβ1, TGFβ2, TGFβR1, TGFβR2) relative to APOE3 / 3 controls (1.13-fold increase. IQR: 0.90-1.34, p = 0.0297; FIG. 8A). To functionally validate the increase in TGF-P signaling along the APOE4 vasculature, miBrains and APOE-TR mice were immunostained for pSmad2, a canonical marker of TGF-P pathway activation. Consistent with the computational predictions, APOE4 / 4 miBrains exhibited significantly more pSMAD2+ vascular nuclei compared to APOE3 / 3 (1.43 ± 0.17-fold increase, p = 0.0383; FIG.

[0428] 8B). Similarly, APOE4 / 4-TR mice showed significantly more pSmad2 immunoreactive nuclei around cortical micro vasculature compared to age-matched APOE3 / 3-TR mice (1.79 ± 0.17-fold increase, p = 0.0386; FIG. 8B).

[0429] The next goal was to identify the cellular source of increased TGF-P in APOE4 brains. Given the prior finding that APOE4 mural cells are both necessary and sufficient to generate myofibroblasts, it was hypothesized that TGF-P pathway activation is intrinsic to APOE4 mural cells. Supporting this, APOE4 / 4 iMCs in monoculture exhibited significantly higher nuclear SMAD2 intensities compared to isogenic APOE3 / 3 controls (1.21 ± 0.060-fold increase, p = 0.0104). Moreover, treating APOE3 / 3 iMCs with recombinant TGFpi (50 ng / mL) increased nuclear SMAD2 levels comparable to APOE4 / 4 cells (1.17 ± 0.016-fold increase, p = 0.0393), indicating that elevated baseline TGF-P signaling in APOE4 / 4 mural cells accounts for their increased SMAD2 activation.

[0430] To explore the mechanism underlying this elevated signaling, iMC bulk RNA-seq data was analyzed. Consistent with the immunofluorescence findings, APOE4 / 4 iMCs exhibited significant upregulation of TGF-P pathway genes. It was reasoned that enhanced signaling could result from either increased TGF-P ligand production or upregulation of TGF-P receptors. Analysis of TGF-P ligand expression revealed no significant differences between genotypes for TGFβ1 (1.09 ± 0.062-fold increase in APOE4 / 4, adjusted p = 0.63) and TGFβ3 Docket No. 084284.00346

[0431] (1.04 ± 0.022-fold increase in APOE4 / 4, adjusted p = 0.50, and even a significant decrease in TGFP2 expression for APOE4 / 4 iMCs compared to isogenic control APOE3 / 3 (0.47 ± 0.013-fold change, corresponding to a 53% decrease in APOE4 / 4 relative to APOE3 / 3, adjusted p = 0.001). By contrast, both TGFβR1 and TGFβR2 were significantly upregulated in APOE4 / 4 mural cells compared to isogenic APOE3 / 3 controls (TGFβR1: 1.61 ± 0.057-fold increase, adjusted p = 0.0012; TGFβR2: 1.22 ± 0.042-fold increase, adjusted p = 0.0102; FIG. 8C).

[0432] These findings were validated in another iMC isogenic pair via qRT-PCR (TGFβR1 2.35 ± 0.20-fold increase, adjusted p = 0.0020; TGFβR2 1.95 ± 0.15-fold increase, adjusted p = 0.0020; FIG. 8C). Finally, to test whether receptor upregulation is functionally linked to myofibroblast induction, TGF-P signaling was inhibited using the SB431542 compound. This treatment significantly reduced a-SMA and fibronectin expression (a-SMA: 0.39 ± 0.033-fold change, corresponding to a 61% decrease relative to APOE4 / 4, p < 0.0001; fibronectin: 0.76 ± 0.085-fold change, corresponding to a 24% decrease relative to APOE4 / 4, p = 0.0308). Together, these results indicate that increased expression of TGF-P receptors in APOE4 mural cells drives enhanced TGF-P signaling and promotes the pericyte-to-myofibroblast transition.

[0433] Example 15. TGF-P inhibition reverses APOE4-d riven myofibroblast accumulation, cerebrovascular fibrosis, and amyloid deposition.

[0434] AD patients exhibit significantly elevated TGFβ1 mRNA levels that strongly correlate with CAA severity, and chronic TGF-P overexpression in mice induces cerebrovascular fibrosis and perivascular amyloid accumulation. The findings described herein support a model in which heightened TGF-β signaling in APOE4 brains causes a PMT leading to vascular fibronectin and amyloid deposition. To directly test this mechanism, TGF-β signaling was inhibited in APOE4 / 4 miBrains using two chemically distinct ALK5 (TGFβR1) inhibitors (SB431452 and Galunisertib).

[0435] Treatment of APOE4 / 4 miBrains with the TGF-P inhibitor significantly reduced non-vascular a-SMA immunoreactivity and led to a significant increase of pericyte vascular coverage to levels comparable to APOE3 / 3 controls (a-SMA: 0.38 ± 0.091-fold change, corresponding to a 62% decrease relative to APOE4 / 4, p < 0.0001; pericyte coverage: 1.37 ± 0.072-fold increase relative to APOE4 / 4, p = 0.0249; FIG. 9A), indicating a reversal of the PMT. Given the causal link that was established between fibronectin secretion from myofibroblasts and perivascular amyloid accumulation, it was next tested whether TGF-P inhibition could reduce both vascular fibrosis and amyloid burden. Consistent with this prediction, treatment of APOE4 / 4 miBrains with either SB431542 or Galunisertib significantly Docket No. 084284.00346

[0436] decreased fibronectin levels (SB431542: 0.59 ± 0.095-fold change, corresponding to a 41% decrease relative to APOE4 / 4, p = 0.0306; Galunisertib: 0.67 ± 0.030-fold change, corresponding to a 33% decrease relative to APOE4 / 4, p = 0.0005; FIG. 9B). Notably, these reductions in fibronectin were accompanied by significant reductions in amyloid deposition, restoring levels to those seen in APOE3 / 3 control miBrains (SB431542: 0.48 ± 0.041-fold change, corresponding to a 52% decrease relative to APOE4 / 4, p = 0.0009; Galunisertib: 0.49 ± 0.034-fold change, corresponding to a 51% decrease relative to APOE4 / 4, p = 0.0060; FIG.

[0437] 9B). Together, these findings demonstrate that APOE4 promotes a pericyte-to-myofibroblast transition through upregulation of TGF- receptor signaling, driving vascular fibrosis and fibronectin-dependent amyloid accumulation, and that pharmacological inhibition of this pathway reverses these pathological phenotypes in human brain tissue.

[0438] Overall, the results described herein reveal that elevated TGF-P signaling drives a pericyte-to-myofibroblast transition in the APOE4 brain. This leads to a loss of pericyte coverage and fibrosis of the APOE4 vasculature, with fibronectin accumulation directly- promoting perivascular amyloid deposition. Pharmacologically inhibiting TGF-P signaling in APOE4 human brain tissue reverses the pericyte-to-myofibroblast transition and attenuates cerebrovascular pathology. These results establish a causal link between TGF-P and cerebrovascular dysfunction in APOE4 carriers, which may influence AD progression in this large patient population. This study thus discovers a novel pathological mechanism in AD and reveals therapeutic opportunities for APOE4-driven cerebrovascular pathology. Importantly, targeting this mechanism may reduce the severe vascular side effects APOE4 carriers experience with anti-amyloid monoclonal antibody therapies.

[0439] AD has long been characterized by the presence of amyloid plaques and neurofibrillary tangles in the brain parenchyma. However, cerebrovascular pathology is often one of the earliest manifestations of AD, sometimes occurring even before symptoms arise. As part of disease progression, pericytes are lost along the vasculature leading to microvessel degeneration and the leakage of intravascular components into the brain parenchyma. In addition to forming plaques, amyloid often accumulates along the vasculature in AD patients, leading to cerebral amyloid angiopathy. Perivascular ECM accumulation is another feature of aging and AD, and several cerebrovascular ECM proteins, particularly fibronectin, are positively correlated with amyloid pathology7. Strikingly, TGF-P overexpression in mice leads to thickening of the cerebrovascular basement membrane that precedes amyloid accumulation Docket No. 084284.00346

[0440] and vascular dysfunction. These findings suggest a link between TGF-P, perivascular fibrosis, and AD pathogenesis.

[0441] This study is the first to demonstrate that APOE4 directly increases TGF-P signaling along the cerebrovasculature, leading to vascular fibrosis and amyloid deposition via pericyte differentiation into myofibroblasts. Cerebrovascular degeneration is a well -characterized phenotype in APOE4 carriers that is linked to accelerated cognitive decline. Independent of AD pathology, pericyte coverage is significantly reduced in APOE4 individuals and carriers of this allele are more susceptible to cerebral hemorrhages. Additionally, perivascular amyloid accumulation is far more common in APOE4 carriers. More recently, ECM dysregulation has also been implicated in APOE4-associated AD. APOE4 astrocytes and microglia upregulate matrisome pathways and solutes from the brain parenchyma, including amyloid, drain along the vasculature. This suggests that perivascular accumulation of pro-aggregatory ECM proteins may drive impaired amyloid clearance. Indeed, perivascular amyloid drainage is decreased in human APOE4-targeted replacement mice. Strong evidence for a fibrotic phenotype in APOE4-mediated AD pathogenesis is a recent study that identified genetic factors protecting carriers of this allele from developing the disease. They found that many protective variants are in ECM genes and that a particular loss-of-function FN1 variant reduces the risk of developing AD by approximately 71%. Coinciding with these results, the brains of APOE4 carriers have increased perivascular fibronectin deposition compared to non-carriers. To date, these APOE4-associated vascular pathologies - pericyte loss, amyloid deposition, and fibrosis - have all been investigated separately. However, this study uniquely identifies a TGF-P-dependent mechanism that links these phenotypes together into a single, targetable pathway. This study shows that inhibiting TGF-P can reverse cerebrovascular pathology in APOE4 which is, at least in part, due to reduced fibronectin accumulation. Therefore, the work described herein simultaneously explains a mechanism of AD risk and resilience and offers a novel therapeutic opportunity for APOE4 individuals.

[0442] This study utilized an orthogonal approach integrating single-nuclei transcriptomic and immunocytochemical analysis of the postmortem human brain with isogenic iPSC brain models and humanized APOE knock-in mice. From this rigorous approach, it was discovered for the first time a causal link between APOE4, TGF-P signaling, cerebrovascular fibrosis, and AD pathology, which can be used for new therapeutic opportunities in the treatment and prevention of AD in high-risk individuals. Docket No. 084284.00346

[0443] The present disclosure is not to be limited in scope by the specific embodiments described herein. Indeed, various modifications of the invention, in addition to those described herein, will become apparent to those skilled in the art from the foregoing description and the accompanying figures. Such modifications are intended to fall within the scope of the appended claims.

[0444] All references cited herein are incorporated herein by reference in their entireties.

Claims

Docket No. 084284.14006CLAIMSWhat is claimed is:

1. A method for making a reconstructed human brain tissue, the method comprising:a) differentiating human induced pluripotent stem cells (iPSCs) into iPSC- derived mural cells (iMCs), wherein the iPSCs express an allelic variant of APOE,' andb) co-culturing the iMCs with human neurons, astrocytes, microglia, oligodendroglia, endothelial cells, and pericytes.

2. The method of claim 1, wherein the iPSCs have an APOE3 / 3, APOE3 / 4, or APOE4 / 4 genotype.

3. The method of claims 1 or 2, wherein the co-culturing occurs within a three- dimensional matrix.

4. The method of any one of claims 1-3, further comprising a step c) of inhibiting transforming growth factor beta (TGF-P) signaling by contacting the reconstructed human brain tissue with a TGF-P inhibitor.

5. The method of claim 4, wherein the TGF-P inhibitor is a small molecule, a small hairpin RNA (shRNA), an aptamer, or an antibody or antigen-binding fragment thereof.

6. The method of claim 5. wherein the small molecule is SB431542, A83-01, or Galunisertib (LY2157299).

7. The method of any one of claims 1-3, further comprising a step of c) stimulating TGF-P signaling by contacting the reconstructed human brain tissue with a TGF-P agonist.

8. The method of claim 7, wherein the TGF-P agonist is TGFpi. TGFP2, or TGFP3.

9. The method of any one of claims 1-8, wherein the iMCs overexpress fibronectin (FN1) relative to iMCs that are not engineered to express FN1.

10. The method of any one of claims 1-8, wherein the iMCs express an FN1 variant.

11. The method of any one of claims 1-8, wherein the iMCs have reduced FN1 levels as compared to iMCs that are not engineered to express FN1.

12. The method of any one of claims 1-11, wherein the iPSCs have been isolated from a subject that has Alzheimer's disease (AD).

13. A method for evaluating whether a drug candidate inhibits amyloid deposition in a reconstructed human brain tissue, the method comprising: contacting theDocket No. 084284.14006reconstructed human brain tissue of any one of claims 1-12 with the drug candidate; and quantifying a level of amyloid deposition in the reconstructed human brain tissue as compared to a control level of amyloid deposition in the reconstructed human brain tissue in the absence of the drug candidate.

14. A method for evaluating whether a drug candidate inhibits fibronectin deposition in a reconstructed human brain tissue, the method comprising contacting the reconstructed human brain tissue of any one of claims 1-12 with the drug candidate; and quantifying the level of fibronectin deposition in the reconstructed human brain tissue as compared to a control level of fibronectin deposition in the reconstructed human brain tissue in the absence of the drug candidate.

15. A method for evaluating whether a drug candidate is able to cross an in vitro brainblood barrier (iBBB), the method comprising: providing a reconstructed human brain tissue of any one of claims 1-12, wherein the reconstructed human brain tissue further comprises an iBBB comprising a proximal side and a distal side, contacting the proximal side of the iBBB with the drug candidate, and quantifying the amount of drug candidate that crosses the iBBB to reach the distal side of the iBBB.

16. A method for evaluating whether a drug candidate induces neurotoxicity in a reconstructed human brain tissue, the method comprising contacting the reconstructed human brain tissue of any one of claims 1-12 with the drug candidate; and quantifying the level of neurotoxicity in the reconstructed human brain tissue as compared to a control level of neurotoxicity in the reconstructed human brain tissue in the absence of the drug candidate.

17. A method for evaluating whether a drug candidate induces reduces tau pathology in a reconstructed human brain tissue, the method comprising contacting the reconstructed human brain tissue of any one of claims 1-12 with the drug candidate; and quantifying the level of tau pathology in the reconstructed human brain tissue as compared to a control level of tau pathology in the reconstructed human brain tissue in the absence of the drug candidate.

18. A method for evaluating whether a drug candidate induces reduces cerebral amyloid angiopathy (CAA) pathology in a reconstructed human brain tissue, the method comprising contacting the reconstructed human brain tissue of any one of claims 1- 12 with the drug candidate; and quantifying the level of CAA pathology in theDocket No. 084284.14006reconstructed human brain tissue as compared to a control level of CAA pathology in the reconstructed human brain tissue in the absence of the drug candidate.

19. A method for evaluating whether a drug candidate induces reduces Lewy Body pathology in a reconstructed human brain tissue, the method comprising contacting the reconstructed human brain tissue of any one of claims 1-12 with the drug candidate; and quantifying the level of Lewy Body pathology in the reconstructed human brain tissue as compared to a control level of Lewy Body pathology in the reconstructed human brain tissue in the absence of the drug candidate.

20. The method of any one of claims 13-19, wherein the drug candidate is selected from the group consisting of a small molecule, a nucleic acid, a peptide, a polypeptide, an antibody, and an antibody fragment.

21. A method of reducing or preventing APOE4 vascular dysfunction in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor.

22. A method of reducing or preventing myofibroblast accumulation in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor.

23. A method of reducing or preventing cerebrovascular fibrosis in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor.

24. A method of reducing or preventing amyloid deposition in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor.

25. A method of reducing or preventing Alzheimer’s disease (AD) progression in a subject in need thereof, the method comprising administering to the subject a TGF- P inhibitor.

26. A method of reducing fibronectin expression levels in a subject in need thereof, the method comprising administering to the subject a TGF-P inhibitor, wherein the TGF-P inhibitor reduces fibronectin expression levels by at least about 20%.

27. The method of any one of claims 21-26, herein the TGF-P inhibitor is a small molecule, an shRNA, an aptamer, or an antibody or antigen-binding fragment thereof.

28. The method of claim 27, wherein the small molecule is SB431542, A83-01, or Galunisertib (LY2157299).

29. The method of any one of claims 21-28, wherein the subject is a human.

30. The method of any one of claims 21-24 or 26-29, wherein the subject has a neurodegenerative disease.Docket No. 084284.1400631. The method of claim 30, wherein the neurodegenerative disease is AD.

32. The method of any one of claims 21-31, wherein the subject is homozygous for APOE4.

33. The method of any one of claims 21-31, wherein the subject is heterozygous for APOE4.

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