Composition for improving function of pancreatic β cells aged by pregnancy and childbirth, and biomarkers for predicting pancreatic β cell function

Abstract

Disclosed in the present specification are a composition for improving, enhancing, or restoring the function of pancreatic β cells aged by pregnancy and childbirth, and biomarkers for predicting or diagnosing the function of pancreatic β cells aged by pregnancy and childbirth. In one aspect, the composition of the present invention can effectively enhance the proliferation of pancreatic β cells aged by pregnancy, childbirth, and multiple births by containing dasatinib and quercetin, and the biomarkers of the present invention are used such that conditions caused by pregnancy, childbirth and multiple births, such as an increased cellular stress of pancreatic β cells, impaired cellular respiration and secretory function, or decreased cell proliferation capacity can be predicted or diagnosed.

Description

Composition for improving pancreatic β cell function aged by pregnancy and childbirth and biomarker for predicting pancreatic β cell function

[0001] Disclosed herein are compositions for improving, enhancing or restoring pancreatic β cell function aged by pregnancy and childbirth and biomarkers for predicting or diagnosing pancreatic β cell function aged by pregnancy and childbirth.

[0002]

[0003] Cross-reference to related applications

[0004] This application claims priority to Republic of Korea Patent Application No. 10-2023-0147133, filed October 30, 2023, and Republic of Korea Patent Application No. 10-2024-0050100, filed April 15, 2024, the entire contents of which are incorporated herein by reference.

[0005]

[0006] Meanwhile, this application was supported by the following national development project.

[0007] [National Research and Development Project Supporting This Invention]

[0008] [Project ID] 1711195966

[0009] [Assignment Number] 00222910

[0010] [Ministry Name] Ministry of Science and ICT

[0011] [Name of Project Management (Specialist) Institution] National Research Foundation of Korea

[0012] [Research Project Name] Development of Future Medical Innovation Response Technology

[0013] [Research Project Name] Development of Medical Field Application Technologies for Five Major Diseases and Training of Physician Scientists through a Customized Future Medical Research Center in the Era of 6P Medicine

[0014] [Name of the project performing organization] Bundang Seoul National University Hospital

[0015] Research Period: April 1, 2023 - December 31, 2023

[0016] [National Research and Development Project Supporting This Invention]

[0017] [Project ID] 1711181087

[0018] [Assignment Number] 2021R1C1C1009875

[0019] [Ministry Name] Ministry of Science and ICT

[0020] [Name of Project Management (Specialist) Institution] National Research Foundation of Korea

[0021] [Research Project Name] Outstanding New Researcher

[0022] [Research Project Name] Identification of the Mechanisms of Pregnancy-Induced Diabetes and Fatty Liver Disease and Development of Treatment Factors

[0023] [Name of the project performing organization] Bundang Seoul National University Hospital

[0024] [Research Period] March 1, 2021 - February 29, 2024

[0025] [National Research and Development Project Supporting This Invention]

[0026] [Project ID] 1465039479

[0027] [Assignment Number] HI22C0444000023

[0028] [Ministry Name] Ministry of Health and Welfare

[0029] [Name of Project Management (Specialist) Agency] Korea Health Industry Development Institute

[0030] [Research Project Name] K-Medi Convergence Talent Development Support Project

[0031] [Research Project Title] Multi-omic Analysis to Unravel the Mechanism of Improved Adipose Tissue Insulin Sensitivity Due to Breastfeeding and Discovery of Diabetes Treatment Targets

[0032] [Name of the project performing organization] Bundang Seoul National University Hospital

[0033] Research Period: April 1, 2022 - December 31, 2023

[0034] [National Research and Development Project Supporting This Invention]

[0035] [Project Number] RS-2024-00403679

[0036] [Ministry Name] Ministry of Health and Welfare

[0037] [Name of Project Management (Specialist) Agency] Korea Health Industry Development Institute

[0038] [Research Project Name] Global Physician Scientist Training Program

[0039] [Research Project Name] Identifying Treatment Targets for Maternal-Fetal Metabolic Disorders through Multi-Omegame Analysis of Pregnancy Adipose Tissue

[0040] [Name of the project performing organization] Bundang Seoul National University Hospital

[0041] Research Period: April 1, 2024 - December 31, 2024

[0042] [National Research and Development Project Supporting This Invention]

[0043] [Project ID] 1345366101

[0044] [Project Number] 2022R1I1A1A01068401

[0045] [Ministry Name] Ministry of Education

[0046] [Name of Project Management (Specialist) Institution] National Research Foundation of Korea

[0047] [Research Project Name] Establishment of a Research Base for Science and Engineering

[0048] [Research Project Name] Identification of Key Regulators of Beta Cell Dedifferentiation Using a Beta Cell Gene Screening Platform

[0049] [Name of the project performing organization] Catholic University of Korea (Seongui Campus)

[0050] [Research Period] March 1, 2023 - February 29, 2024.

[0051] [National Research and Development Project Supporting This Invention]

[0052] [Project Number] RS-2024-00408915

[0053] [Ministry Name] Korea Health Industry Development Institute (Ministry of Health and Welfare)

[0054] [Name of Project Management (Specialist) Agency] Korea Health Industry Development Institute

[0055] [Research Project Name] Global Physician Scientist Training Program

[0056] [Research Project Name] Discovery of New Drug Candidates for Fatty Liver Disease Associated with Metabolic Disorders through Intermediary Research

[0057] [Name of the project implementing organization] Catholic University of Korea Industry-Academic Cooperation Foundation

[0058] Research Period: April 1, 2024 - December 31, 2026

[0059]

[0060] South Korea has the lowest birth rate among OECD countries. While increasing the birth rate is crucial for national competitiveness, there is a severe lack of understanding of the medical and metabolic impact of pregnancy and childbirth on the mother, and a lack of consideration for the socioeconomic impact.

[0061] The incidence of gestational diabetes and postpartum diabetes in pregnant women increases with advancing maternal age. More than 10% of all pregnant women develop gestational diabetes, and more than half of these develop diabetes after childbirth. Women who have experienced pregnancy and childbirth are at a higher risk of developing diabetes than those who have not. Diabetes can cause various complications, including cardiovascular, cerebrovascular, neurological, and retinal diseases, significantly reducing women's health and quality of life. Multiple pregnancies and childbirths, i.e., multiple births, are expected to be a significant metabolic and medical burden on pregnant women, but current research is limited.

[0062] Meanwhile, pancreatic β cells are a key organ in the pathophysiology of diabetes, and cellular senescence is closely related to chronic diseases such as diabetes. Therefore, the development of a pancreatic β-cell aging model is crucial for understanding the pathophysiology of diabetes. Accordingly, the present inventors established a multiparous mouse model that underwent three consecutive pregnancies using the C57BL6 / J mouse model and a pancreatic β-cell aging model, and confirmed that the multiparous mouse model exhibited characteristics such as pancreatic β-cell aging, decreased pancreatic β-cell proliferation and increased cellular stress, decreased telomere length, and decreased insulin secretion and cellular respiratory function. In other words, multiple pregnancies and pregnancies can cause an increased metabolic risk of diabetes and a decline in pancreatic β-cell function in the mother.

[0063] Accordingly, the inventors of the present invention have made efforts to develop a technology for managing maternal health after childbirth, and as a result, have confirmed that dasatinib and quercetin can effectively restore pancreatic β cell function aged due to pregnancy and childbirth, and have completed the present invention by identifying a gene capable of predicting or diagnosing pancreatic β cell function aged due to pregnancy and childbirth through single cell RNA sequencing.

[0064] One object of the present invention is to provide a composition for improving, promoting or restoring the function of pancreatic β cells aged by pregnancy and childbirth.

[0065] Another object of the present invention is to provide a biomarker for predicting or diagnosing pancreatic β cell function aged by pregnancy and childbirth.

[0066] In order to achieve the above purpose, the present invention provides, in one aspect, a composition for promoting the proliferation of pancreatic β cells aged due to pregnancy and childbirth, comprising dasatinib and quercetin as active ingredients.

[0067] In another aspect, the present invention provides a biomarker for predicting or diagnosing pancreatic β cell function aged by pregnancy and childbirth, comprising one or more genes selected from the group consisting of Ddit3, Fkbp11, Sdf2l1, Nupr1, Atf5, Atf3, Hspa1a, Hspa1b and Dnajb1 genes.

[0068] In one aspect, the composition of the present invention can effectively promote the proliferation of pancreatic β cells aged by pregnancy, childbirth, and fertility by including dasatinib and quercetin.

[0069] In another aspect, the biomarker of the present invention can be used to predict or diagnose conditions such as increased cell stress, impaired cell respiration and secretory function, or decreased cell proliferation capacity of pancreatic β cells due to pregnancy, childbirth, and fertility.

[0070] Figure 1a is a schematic diagram of a multi-fertility mouse model.

[0071] Figure 1b shows whole images of virgin and multiparous mice and inguinal white adipose tissue (iWAT), visceral WAT (vWAT), and brown adipose tissue (BAT) dissected 3 weeks after the last delivery.

[0072] Figure 1c shows the body weights of virgin and multiparous mice after overnight fasting.

[0073] Figure 1d shows data from intraperitoneal glucose tolerance test (2 g / kg) in virgin and multiparous mice; virgin n=7, multiparous n=10.

[0074] Figure 1e shows the intraperitoneal insulin tolerance test (0.75 U / kg, n = 3 per group) after 6 h fasting in virgin and multiparous mice.

[0075] Figures 1f and 1g show glucose infusion rate, whole-body glucose turnover, and glucose production during the clamp. In Figure 1g, glucose uptake from the soleus muscle and retroperitoneal adipose tissue was measured using the hyperinsulinemic-euglycemic clamp method in virgin and multiparous mice (virgin n=4, multiparous n=5).

[0076] Figure 1h shows the indirect calorimetry analysis of virgin and multiparous mice. Oxygen consumption (VO2), carbon dioxide consumption (VCO2), total work (XTOT) on the x-axis, heat production, and respiratory exchange ratio (RER) are shown (n=4 per group).

[0077] Figure 1i shows that islets were incubated with 2.8 or 16.8 mM glucose for 15 minutes and secreted insulin concentrations were measured by ELISA (n=3 per group).

[0078] Figure 1j shows plasma insulin concentrations measured after intraperitoneal glucose injection (2 g / kg; n=3 per group).

[0079] Figure 1k shows representative images of pancreatic islets from virgin and multiparous mice. Insulin was immunohistochemically stained (brown) with hematoxylin and eosin counterstain. Scale bar: 50 μm, n = 3 per group.

[0080] Figure 1l shows β-cell area. β-cell area was quantified as the percentage of insulin-positive area relative to the total pancreatic area (n = 3 per group).

[0081] In Figure 1, data are expressed as mean ± SEM: *P<0.05, **P<0.01 and ***P<0.001, determined by Student's t test for Figures 1c to 1g, 1l or one-way ANOVA with Tukey's post hoc test for Figures 1i and 1j.

[0082] Figure 2 shows a bulk RNA-seq analysis of islets from virgin and multiparous mice.

[0083] Figures 2a and 2b show bulk RNA-seq analyses of islets from virgin and multiparous mice (non-S-961 injected, n=2 per group).

[0084] Figures 2c and 2d show bulk RNA-seq analysis of islets from virgin and multiparous mice (S-961 injected, n≥3 per group).

[0085] Figures 2a and 2c are PCA plots in which virgin (black) and multiparous (gray) mouse samples are represented as dots.

[0086] Figures 2b and 2d show differentially expressed genes (DEGs) as volcano plots: dark gray: downregulated, light gray: upregulated, black: not significant, cutoff: log2 fold change >1 or <-1, adjusted p-value <0.05.

[0087] Figure 3a shows a multiparous mouse model evaluated 16 weeks after the last delivery (34 weeks of age).

[0088] Figure 3b shows the change in body weight of virgin and multiparous mice (n = 4 per group).

[0089] Figure 3c shows the intraperitoneal glucose tolerance test (2 g / kg) after overnight fasting (n = 4 per group).

[0090] Figure 3d shows the intraperitoneal insulin tolerance test (0.75 U / kg) after 6 hours of fasting (n = 4 per group).

[0091] Figures 3e and 3f show the percentage of fat or lean mass in virgin and multiparous mice (virgin n = 4, multiparous n = 3).

[0092] Figure 3g shows the weight of the indicated tissues (n=3 per group).

[0093] Figure 3h is a representative image of liver, vWAT, iWAT, and BAT (n=3 per group, scale bar: 50 μm).

[0094] Figures 3i and 3j relate to plasma insulin concentration and insulin production index (2 g / kg, n = 4 per group).

[0095] Figure 3k shows that islets were incubated with 2.8 mM or 16.8 mM glucose for 15 min and secreted insulin concentrations were measured by ELISA (n=6 per group).

[0096] Figure 3L shows representative images of pancreatic islets from virgin and multiparous mice. Insulin was detected immunohistochemically using hematoxylin and eosin counterstaining (dark areas). Scale bar: 50 μm, n=4 per group.

[0097] Figure 3m shows β-cell area. β-cell area was quantified as the percentage of insulin-positive area relative to the total pancreatic area (n=4 per group).

[0098] Data in Figure 3 are expressed as mean ± SEM: NS not significant. *P<0.05. Figures 3b to 3g, 3j, and 3m were determined by Student's t test, or Figures 3i and 3k by one-way ANOVA with Tukey's post hoc test.

[0099] Figure 4a is about the test of β-cell replication capacity in virgin and multiparous mice through administration of S-961 (insulin receptor antagonist).

[0100] Figure 4b shows glucose concentrations after S-961 administration in virgin and multiparous mice (n = 3 per group).

[0101] Figure 4c is a representative image of Ki67 (red) and insulin (green) immunofluorescence in pancreatic sections after S-961 administration (scale bar: 50 μm, n = 3 per group).

[0102] Figure 4d shows the β-cell proliferation rate. The β-cell proliferation rate was calculated as the percentage of insulin and Ki-67 co-positive cells relative to all insulin-positive cells (n = 3 per group).

[0103] Figure 4e illustrates administration of S-961 to mice transplanted with islets from virgin and multiparous mice into the left and right renal capsules, respectively. In Figures 4e and 4g, islets of matched size from virgin and multiparous mice were transplanted into the left and right renal capsules of C57BL / 6 J mice, respectively, followed by intraperitoneal injection of S-961.

[0104] Figure 4f is a representative image of Ki67 (brightest area) and insulin (second brightest area) immunofluorescence in kidney sections after S-961 administration (scale bar: 100 μm, n = 3 per group).

[0105] Figure 4g shows β-cell proliferation rate expressed as the percentage of insulin and Ki-67 co-positive cells relative to all insulin-positive cells (n = 3 per group).

[0106] Figures 4h to 4j show RNA sequencing of islets obtained from virgin (n=3) and multiparous (n=4) mice that received intraperitoneal injections of S-961. Figure 4h shows gene set enrichment analysis of islets from virgin and multiparous mice, with Figure 4i showing genes downregulated in multiparous mouse islets compared to virgin mouse islets, and Figure 4j showing genes upregulated. Figures 4i and 4j show Z-scores of DESeq2 normalized counts, annotated with a color scale.

[0107] In Figure 4, data are presented as mean ± SEM: *P<0.05, **P<0.01, and ***P<0.001, determined by Student's t test.

[0108] Figures 5a to 5f relate to single cell RNA sequencing of islets from virgin and multiparous mice (n≥2 per group).

[0109] In Figures 5a and 5b, the multiparous mouse-specific β-cell transcriptome clusters were annotated as Cluster 1 and Cluster 2 (Figure 6).

[0110] Pathways of enriched genes in Figures 5c (cluster 1) and 5d (cluster 2) were analyzed using gene set enrichment analysis.

[0111] Figures 5e and 5f visualize stress-related genes using UMAP and violin plot, respectively.

[0112] In Fig. 5g, telomere length was measured in islets from virgin (n=4) and multiparous (n=5) mice.

[0113] In Fig. 5h, mRNA expression levels in islets of virgin and multiparous mice were assessed by qRT / u201bPCR (n=3 per group).

[0114] In Figure 5, data are presented as mean ± SEM: *P<0.05, **P<0.01, and ***P<0.001, determined by Student's t test.

[0115] Figure 6 shows single-cell RNA-seq analysis of islets from virgin and multiparous mice.

[0116] Figures 6a to 6g relate to single cell RNA sequencing of islets from virgin and multiparous mice (n≥2 per group).

[0117] Figure 6a screened representative marker genes for each cell type in the islet: Ins1 (Insulin 1) for β cells, Gcg (glucagon) for α cells, Sst (Somatostatin) for δ cells, Ppy (pancreatic polypeptide) for PP cells, Des (Desmin) for mesenchymal cells, Cd86 (Cluster of Differentiation 86) and Trbc2 (T cell receptor beta constant 2) for immune cells, Hmbs (Hydroxymethylbilane synthase) for erythrocytes, and Pecam1 (platelet and endothelial cell adhesion molecule 1) for endothelial cells.

[0118] Figure 6b shows a comparison between groups for the proportion of each cell type.

[0119] Figure 6c shows the expression patterns of islet cells from virgin and multiparous mice as indicated by UMAP.

[0120] Figure 6d Unsupervised clustering of β cells from virgin and multiparous mice was performed based on expression patterns.

[0121] Figure 6e shows a comparison between groups regarding the proportion of each β cell cluster.

[0122] Figures 6f and 6g show the pathways of genes enriched in cluster 5 and cluster 7, respectively, analyzed using gene set enrichment analysis.

[0123] Figure 7a shows the results of a 75g glucose tolerance test two months after birth.

[0124] Figure 7b shows the hyperbola of the insulin production index and the Matsuda index (insulin sensitivity) at 2 months after birth.

[0125] In Figure 7c, the hyperbola of women with high parity (n=77) followed for a median of 4.0 years after delivery was categorized into tertiles based on the change in body mass index from the initial follow-up (2 months postpartum) to the last follow-up.

[0126] In Figure 7, data are expressed as mean ± SEM: *P<0.05, determined by Student's t test.

[0127] Figure 8 shows a multi-fertility mouse model treated with senolytics.

[0128] Figures 9 and 10 relate to pancreatic β cell proliferation in a multiparous mouse model administered with senolytics (dasatinib and quercetin).

[0129] Hereinafter, the present invention will be described in detail.

[0130]

[0131] The present invention relates to a composition for promoting the proliferation of aged pancreatic β cells, comprising dasatinib and quercetin as active ingredients.

[0132] In an exemplary embodiment, the dasatinib and quercetin may be included in a weight ratio of 1:1 to 1:20, and more specifically, the dasatinib and quercetin may be included in a weight ratio of 1:1 or more, 1:2 or more, 1:3 or more, 1:4 or more, 1:5 or more, 1:6 or more, 1:7 or more, 1:8 or more, or 1:9 or more, and may be included in a weight ratio of 1:20 or less, 1:19 or less, 1:18 or less, 1:17 or less, 1:16 or less, 1:15 or less, 1:14 or less, 1:13 or less, 1:12 or less, or 1:11 or less. When dasatinib and quercetin are included in the above weight ratio, the proliferation of aged pancreatic β cells can be effectively promoted. For example, dasatinib and quercetin can be included in a weight ratio of 1:10, but is not limited thereto.

[0133] In an exemplary embodiment, the aged pancreatic β cells may be pancreatic β cells aged by pregnancy and childbirth.

[0134] In an exemplary embodiment, the birth may be characterized as two or more births. For example, the birth may be three or more births.

[0135] The term “application” in this specification means providing the composition to a subject by any suitable method, and includes administration, coating, absorption, and ingestion. In this case, the subject means any animal to which the composition can be applied, such as a human, monkey, dog, goat, pig, or rat.

[0136] In an exemplary embodiment, the composition may be applied to a subject in need of enhancing the insulin secretory capacity of aged pancreatic β cells.

[0137] In an exemplary embodiment, the composition may be applied to a subject in need of enhancing cellular respiratory function of aged pancreatic β cells.

[0138] As used herein, the term "prevention" refers to any action that suppresses or delays diabetes by applying a pharmaceutical composition. The term "treatment" refers to any action that improves or beneficially alters the symptoms of a subject suspected of or diagnosed with diabetes by applying a pharmaceutical composition.

[0139] In an exemplary embodiment, the composition may be a pharmaceutical composition for preventing or treating diabetes.

[0140] In an exemplary embodiment, the composition may be a health functional food composition for preventing or improving diabetes.

[0141] In an exemplary embodiment, the daily dosage of the active ingredient of the composition may be from 1 mg / kg to 150 mg / kg. More specifically, it may be from 1 mg / kg to 5 mg / kg, from 10 mg / kg to 15 mg / kg, from 20 mg / kg to 25 mg / kg, from 30 mg / kg to 35 mg / kg, from 40 mg / kg to 45 mg / kg, or from 50 mg / kg to 50 mg / kg, and from 150 mg / kg to 140 mg / kg, from 130 mg / kg to 140 mg / kg, from 130 mg / kg to 120 mg / kg, from 110 mg / kg to 100 mg / kg, from 90 mg / kg to 80 mg / kg, from 70 mg / kg to 60 mg / kg. The above application amount has excellent effects of inhibiting fat production, inhibiting fat accumulation, or promoting fat decomposition. If the application amount is less than the above, the effect of promoting the proliferation of aged pancreatic β cells is minimal, and if the application amount is more than the above, problems such as toxicity may occur. The above application may be applied once a day or divided into several times. For example, it may be applied 2 to 24 times a day, 1 to 2 times every 3 days, 1 to 6 times a week, 1 to 10 times every 2 weeks, 1 to 15 times every 3 weeks, 1 to 3 times every 4 weeks, or 1 to 12 times a year, but is not limited thereto.

[0142] In an exemplary embodiment, the daily dose of dasatinib of the composition may be from 0.5 mg / kg to 50 mg / kg. More specifically, it may be 0.5 mg / kg or more, 0.7 mg / kg or more, 0.8 mg / kg or more, 0.9 mg / kg or more, 1.0 mg / kg or more, 1.5 mg / kg or more, 2.0 mg / kg or more, 2.5 mg / kg or more, 3.0 mg / kg or more, 3.5 mg / kg or more, 4.0 mg / kg or more, or 4.5 mg / kg or more, and may be 50 mg / kg or less, 40 mg / kg or less, 30 mg / kg or less, 20 mg / kg or less, 10 mg / kg or less, 9 mg / kg or less, 8 mg / kg or less, 7 mg / kg or less, 6 mg / kg or less, or 5.5 mg / kg or less. The above application amount has excellent effects of inhibiting fat production, inhibiting fat accumulation, or promoting fat decomposition. If the application amount is less than the above, the effect of promoting the proliferation of aged pancreatic β cells is minimal, and if the application amount is more than the above, problems such as toxicity may occur. The above application may be applied once a day or divided into several times. For example, it may be applied 2 to 24 times a day, 1 to 2 times every 3 days, 1 to 6 times a week, 1 to 10 times every 2 weeks, 1 to 15 times every 3 weeks, 1 to 3 times every 4 weeks, or 1 to 12 times a year, but is not limited thereto.

[0143] In an exemplary embodiment, the daily dosage of quercetin of the composition may be from 1 mg / kg to 100 mg / kg. More specifically, it may be from 1 mg / kg to 5 mg / kg, from 10 mg / kg to 15 mg / kg, from 20 mg / kg to 25 mg / kg, from 30 mg / kg to 35 mg / kg, from 40 mg / kg to 45 mg / kg, and from 100 mg / kg to 140 mg / kg, from 130 mg / kg to 120 mg / kg, from 85 mg / kg to 75 mg / kg, from 70 mg / kg to 65 mg / kg, from 60 mg / kg to 55 mg / kg. The above application amount has excellent effects of inhibiting fat production, inhibiting fat accumulation, or promoting fat decomposition. If the application amount is less than the above, the effect of promoting the proliferation of aged pancreatic β cells is minimal, and if the application amount is more than the above, problems such as toxicity may occur. The above application may be applied once a day or divided into several times. For example, it may be applied 2 to 24 times a day, 1 to 2 times every 3 days, 1 to 6 times a week, 1 to 10 times every 2 weeks, 1 to 15 times every 3 weeks, 1 to 3 times every 4 weeks, or 1 to 12 times a year, but is not limited thereto.

[0144] From another perspective, the present invention relates to a method for promoting proliferation of aged pancreatic β cells by applying dasatinib and quercetin to a subject.

[0145] In another aspect, the present invention relates to a method for preventing, improving or treating diabetes by applying dasatinib and quercetin to a subject.

[0146] The present invention relates to the use of dasatinib and quercetin for the preparation of a composition for promoting the proliferation of aged pancreatic β cells from another aspect.

[0147] In another aspect, the present invention relates to the use of dasatinib and quercetin for the preparation of a composition for preventing, improving or treating diabetes.

[0148] In another aspect, the present invention relates to the use of dasatinib and quercetin for promoting proliferation of aged pancreatic β cells.

[0149] In another aspect, the present invention relates to the use of dasatinib and quercetin for preventing, improving or treating diabetes.

[0150] The present invention relates in another aspect to non-therapeutic or therapeutic uses of dasatinib and quercetin.

[0151] In another aspect, the present invention relates to a biomarker for predicting or diagnosing pancreatic β-cell function aged by pregnancy and childbirth, comprising one or more genes selected from the group consisting of Ddit3 (DNA damage inducible transcript 3), Fkbp11 (FKBP Prolyl Isomerase 11), Sdf2l1 (Stromal cell-derived factor 2-like protein 1), Nupr1 (Nuclear Protein 1, Transcriptional Regulator), Atf5 (Activating transcription factor 5), Atf3 (Activating transcription factor 3), Hspa1a (heat shock protein family A (Hsp70) member 1A), Hspa1b (heat shock protein family A (Hsp70) member 1B), and Dnajb1 (DnaJ Heat Shock Protein Family (Hsp40) Member B1) genes.

[0152] In an exemplary embodiment, the Ddit3 (DNA damage inducible transcript 3) gene may include, but is not limited to, a base sequence represented by SEQ ID NO: 1.

[0153] In an exemplary embodiment, the Fkbp11 (FKBP Prolyl Isomerase 11) gene may include, but is not limited to, the base sequence represented by SEQ ID NO: 2.

[0154] In an exemplary embodiment, the Sdf2l1 (Stromal cell-derived factor 2-like protein 1) gene may include, but is not limited to, the base sequence represented by SEQ ID NO: 3.

[0155] In an exemplary embodiment, the Nupr1 (Nuclear Protein 1, Transcriptional Regulator) gene may include, but is not limited to, the base sequence represented by SEQ ID NO: 4.

[0156] In an exemplary embodiment, the Atf5 (Activating transcription factor 5) gene may include, but is not limited to, a base sequence represented by SEQ ID NO: 5.

[0157] In an exemplary embodiment, the Atf3 (Activating transcription factor 3) gene may include, but is not limited to, the base sequence represented by SEQ ID NO: 6.

[0158] In an exemplary embodiment, the Hspa1a (heat shock protein family A (Hsp70) member 1A) gene may include, but is not limited to, the base sequence represented by SEQ ID NO: 7.

[0159] In an exemplary embodiment, the Hspa1b (heat shock protein family A (Hsp70) member 1B) gene may include, but is not limited to, the base sequence represented by SEQ ID NO: 8.

[0160] In an exemplary embodiment, the Dnajb1 (DnaJ Heat Shock Protein Family (Hsp40) Member B1) gene may include, but is not limited to, a base sequence represented by SEQ ID NO: 9.

[0161] In an exemplary embodiment, the birth may be characterized as two or more births. For example, the birth may be three or more births.

[0162] In an exemplary embodiment, if the expression of the biomarker is increased, it can be predicted or diagnosed that pancreatic β cells are in a state of increased cellular stress, impaired cellular respiration and secretion function, or reduced cellular proliferation capacity due to pregnancy and childbirth.

[0163] The present invention relates to a composition for predicting or diagnosing pancreatic β-cell function aged by pregnancy and childbirth, comprising a preparation for measuring the mRNA or protein expression level of the biomarker from another perspective.

[0164] In an exemplary embodiment, the agent for measuring the expression level of the mRNA may comprise a primer pair, probe or antisense nucleotide that specifically binds to the biomarker, and the agent for measuring the expression level of the protein may comprise an antibody specific for the protein of the biomarker gene.

[0165] In another aspect, the present invention relates to a kit for predicting or diagnosing pancreatic β cell function aged by pregnancy and childbirth, comprising the composition.

[0166] The present invention relates to a method for providing information for predicting or diagnosing pancreatic β cell function aged by pregnancy and childbirth, comprising the steps of measuring the mRNA or protein expression level of the biomarker in a sample isolated from a subject from another perspective, and comparing the measured mRNA or protein expression level of the biomarker with a normal control sample.

[0167] In one exemplary embodiment, the method can measure gene expression at the single cell level.

[0168] In an exemplary embodiment, the method may further include a step of predicting or diagnosing that pancreatic β cells are in a state of increased cellular stress; impaired cellular respiration and secretion function; or decreased cellular proliferation capacity due to pregnancy and childbirth when the mRNA or protein expression level of the measured biomarker is increased compared to the expression level of a normal control sample.

[0169] In another aspect, the present invention relates to a composition for improving cell stress, promoting cell respiration and secretion, or promoting cell proliferation in pancreatic β cells aged due to pregnancy and childbirth, comprising a substance that suppresses the expression or activity of a protein encoded by the biomarker.

[0170] In an exemplary embodiment, the composition may be a pharmaceutical composition for preventing or treating diabetes.

[0171] In an exemplary embodiment, the composition may be a health functional food composition for preventing or improving diabetes.

[0172] In an exemplary embodiment, the pharmaceutical composition may be provided in any dosage form suitable for topical application. For example, it may be administered orally, transdermally, intravenously, intramuscularly, or subcutaneously. For example, the pharmaceutical composition may be, but is not limited to, an injection, a topical solution for skin application, a suspension, an emulsion, a gel, a patch, or a spray. The dosage form may be readily prepared according to a method conventional in the art, and may appropriately use surfactants, excipients, wetting agents, emulsifying promoters, suspending agents, salts or buffers for osmotic pressure adjustment, coloring agents, flavoring agents, stabilizers, preservatives, preservatives, or other commonly used auxiliary agents.

[0173] In one exemplary embodiment, the active ingredient of the pharmaceutical composition will vary depending on the subject's age, sex, weight, pathological condition and its severity, the route of administration, and the prescriber's judgment. Determining the appropriate dosage based on these factors is within the skill of those skilled in the art.

[0174] In an exemplary embodiment, there is no particular limitation on the type of the health functional food, and examples of foods to which the composition can be added include dairy products including meat, confectionery, noodles, gum, ice cream, various soups, beverages, tea, drinks, alcoholic beverages, and vitamin complexes, and all foods in the conventional sense can be included.

[0175] In an exemplary embodiment, when manufacturing the health functional food or beverage, the composition may be added in an amount of 15 parts by weight or less, preferably 10 parts by weight or less, per 100 parts by weight of the raw material. However, in the case of long-term consumption for health and hygiene purposes or for health control purposes, the amount may be below the above range.

[0176] In an exemplary embodiment, the beverage among the health functional foods may contain various flavoring agents or natural carbohydrates as additional ingredients, just like a regular beverage. The natural carbohydrates described above may be monosaccharides such as glucose and fructose, disaccharides such as maltose and sucrose, polysaccharides such as dextrin and cyclodextrin, and sugar alcohols such as xylitol, sorbitol, and erythritol. As a sweetener, a natural sweetener such as thaumatin and stevia extract, or a synthetic sweetener such as saccharin and aspartame may be used. The proportion of the natural carbohydrate may be about 0.01 to 0.04 g, preferably about 0.02 to 0.03 g, per 100 mL of the beverage according to the present invention, but is not limited thereto.

[0177] In an exemplary embodiment, in addition to the above, the health functional food according to the present invention may contain various nutrients, vitamins, electrolytes, flavoring agents, coloring agents, pectic acid and its salts, alginic acid and its salts, organic acids, protective colloid thickeners, pH adjusters, stabilizers, preservatives, glycerin, alcohol, and carbonating agents used in carbonated beverages. In addition, the health functional food according to the present invention may contain fruit pulp for the production of natural fruit juice, fruit juice drinks, and vegetable drinks. These ingredients may be used independently or in mixtures. The ratio of these additives is not limited, but is generally selected in the range of 0.01 to 0.1 parts by weight per 100 parts by weight of the health functional food according to the present invention.

[0178] From another perspective, the present invention relates to a method for improving cell stress, promoting cell respiration and secretion, or promoting cell proliferation in pancreatic β cells aged due to pregnancy and childbirth by applying to a subject a substance that suppresses the expression or activity of a protein encoded by the biomarker.

[0179] From another perspective, the present invention relates to a method for preventing, improving or treating diabetes by applying to a subject a substance that suppresses the expression or activity of a protein encoded by the biomarker.

[0180] In another aspect, the present invention relates to the use of a substance that inhibits the expression or activity of a protein encoded by the biomarker for the preparation of a composition for improving cell stress in pancreatic β cells aged due to pregnancy and childbirth, for promoting cell respiration and secretion, or for promoting cell proliferation.

[0181] In another aspect, the present invention relates to the use of a substance that inhibits the expression or activity of a protein encoded by the biomarker for the preparation of a composition for preventing, improving or treating diabetes.

[0182] In another aspect, the present invention relates to the use of a substance that suppresses the expression or activity of a protein encoded by the biomarker for improving cell stress, promoting cell respiration and secretion, or promoting cell proliferation in pancreatic β cells aged due to pregnancy and childbirth.

[0183] From another perspective, the present invention relates to the use of a substance that inhibits the expression or activity of a protein encoded by the biomarker for preventing, improving or treating diabetes.

[0184] In another aspect, the present invention relates to non-therapeutic or therapeutic uses of substances that inhibit the expression or activity of a protein encoded by the biomarker.

[0185]

[0186] Hereinafter, the composition and effects of the present invention will be described in more detail with examples. However, the examples below are provided for illustrative purposes only to aid understanding of the present invention and are not intended to limit the scope and scope of the present invention.

[0187]

[0188] [Example]

[0189] Example 1

[0190] Experimental Materials and Methods

[0191] (1-1) Animal testing

[0192] For the multiparity model experiment, 9-week-old littermate female mice (C57BL / 6 J, The Jackson Laboratory) were randomly assigned to either a virgin group or a multiparous group without previous pregnancy. Mice in the multiparous group then gave birth to three consecutive litters, and mice in the virgin group served as controls. Metabolic phenotypes were assessed at least 3 weeks after the last parturition (3-week washout for the Figure 1 cohort and 16-week washout for the Figure 3 cohort). In the S-961 study, mice were administered S-961 (insulin receptor antagonist, Novo Nordisk) intraperitoneally at 100 nmol / kg twice daily for 3–7 days. All mouse studies were approved by the Institutional Animal Care and Use Committee (IACUC) of the Korea Advanced Institute of Science and Technology (KAIST), and all experiments were performed in accordance with relevant guidelines and regulations.

[0193] (1-2) Glucose dynamics analysis

[0194] For the intraperitoneal glucose tolerance test (GTT), mice were fasted overnight and intraperitoneally administered D-glucose (2 g / kg). Blood glucose levels were measured continuously from the tail vein at 0, 15, 30, 60, 90, and 120 minutes. For the in vivo glucose-stimulated insulin secretion (GSIS) experiment, mice were fasted overnight and intraperitoneally injected with D-glucose (2 g / kg). Blood was collected from the tail vein into heparinized tubes at 0 and 15 minutes. The blood was centrifuged at 1,500 g at 4°C for 10 minutes, and the supernatant was collected. For the insulin tolerance test (ITT), mice were fasted for 6 hours and then injected with Humulin R (Lilly) 0.75 U / kg. Blood glucose was measured continuously from the tail vein at 0, 15, 30, 45, 60, 75, and 90 minutes. The insulinogenic index was calculated using the in vivo GSIS test as follows: (Insulin [15 minutes] - Insulin [0 minutes]) / (Glucose [15 minutes] - Glucose [0 minutes]). Blood glucose was measured using a glucometer (Allmedicus, AGM-3000), and plasma insulin was measured using an enzyme-linked immunosorbent assay (ELISA; ALPCO, 80-INSMSU-E01).

[0195] (1-3) Hyperinsulinemic-euglycemic clamp study

[0196] During the hyperinsulinemic-euglycemic clamp study, mice were pre-catheterized and not anesthetized. Somatostatin was infused at 6 μg / kg / min to suppress endogenous insulin secretion. Humulin R (Lilly) was infused at 15 pmol / kg / min, and 20% glucose was infused to maintain plasma glucose concentration at 6 mM. Radiolabeled [3-3H] glucose (0.1 μCi / min, PerkinElmer) was infused to measure whole-body glucose turnover. 2-deoxy-D-[1-14C] glucose (10 μCi, PerkinElmer) was infused to measure tissue glucose uptake. Hepatic glucose production (HGP) was calculated by subtracting the glucose infusion rate (GIR) from the whole-body glucose uptake rate. Plasma glucose levels were measured using a blood glucose meter (Analox, GM9), and plasma insulin concentrations were measured using ELISA (Merck, EZRMI-13K).

[0197] (1-4) Islet Research

[0198] Pancreatic islets were isolated from C57BL / 6 J virgin and multiparous mice. For ex vivo GSIS, isolated islets were cultured in RPMI-1640 medium (Thermo Fisher Scientific, 11875101) supplemented with 10% fetal bovine serum (Thermo Fisher Scientific, 16000044) and 100 U / ml penicillin-streptomycin (Thermo Fisher Scientific, 15070063) in a humidified incubator at 37°C, CO2 for 4 h. After incubation, islets were incubated in 2.8 mM glucose Krebs-Ringer HEPES (KRH) buffer for 30 min and transferred to uncoated plates (12-well, 10 islets per mouse). Islets were incubated in KRH buffer containing 2.8 mM (basal, low) or 16.8 mM (stimulated, high) glucose for 15 min, and secreted insulin levels were measured. Islets were then sonicated and incubated in acid-ethanol (1.5% HCl in 100 ml of 70% ethanol) at 4°C for 18 h to extract intracellular insulin. An equal volume of 1 M tris-Cl buffer (pH 8.0) was added for neutralization. All supernatants were immediately flash frozen in liquid nitrogen and stored at -80°C until ELISA experiments. Insulin secretion was normalized to the content of insulin extracted from the islets.

[0199] (1-5) Quantitative reverse transcription PCR (qRT-PCR) and RNA sequencing

[0200] RNA was extracted from pancreatic islets using TRIzol (Invitrogen, 15596026). Actb was used as an internal control. Telomere length was measured using qRT-PCR, and the primers used to assess the expression of each gene are listed in Table 1.

[0201] [Table 1] Primer sequences used in qRT-PCR

[0202]

[0203]

[0204] For RNA sequencing, samples with RNA integrity number (RIN) >8.0 were selected, and 1 μg of total RNA was used to construct a cDNA library using the Illumina TruSeq Stranded mRNA kit (RS-122-9004DOC).

[0205] Specifically, 1 μg of total RNA was applied to construct a cDNA library using the HighCapacity cDNA Reverse Transcription Kit (Applied Biosystems) according to the provided instructions. The generated cDNA was mixed with Fast SYBR Green Master Mix (Applied Biosystems) and qRT-PCR was performed using the Viia 7 Real-time PCR System (Applied Biosystems). The cDNA library size was measured using a DNA 1000 chip (Agilent Technologies 2100 Bioanalyzer). The prepared library was sequenced using NovaSeq 6000 (Illumina) to generate 100-bp paired-ends. The total read coverage per base was 7,100,000,000–7,900,000,000 bp, and the Q30 of all samples was greater than 94%.

[0206] (1-6) Single-cell RNA sequencing

[0207] Pancreatic islets isolated from C57BL / 6J mice were dissociated into single cells by gentle pipetting in the presence of 0.25% trypsin for 5 minutes. The dissociated cells were applied to the 10X Genomics Chromium system, and cDNA libraries were constructed using Chromium SingleCell 3' Reagent Kits (v3.1 Chemistry). Specifically, islets were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum and 100 U / ml penicillin streptomycin in a humidified incubator at 37°C CO2 for 30 minutes, and then dissociated to the single cell level by gentle pipetting. Cell viability and concentration of dissociated cells in the presence of 0.25% trypsin (Hyclone, SH30042.01) for 5 minutes were assessed using a Countess II Automated Cell Counter (AMQAX1000, Invitrogen). Samples with a viability greater than 80% were concentrated to 800-1000 cells / μL. Dissociated cells were administered to the 10X Genomics Chromium System to generate nanoliter-scale droplets containing uniquely barcoded beads, called Gel Bead-In EMulsions (GEMs), and cDNA libraries were constructed using Chromium Single Cell 3' Reagent Kits (v3.1 Chemistry) according to the manufacturer's instructions. Libraries were sized using a DNA 1000 chip, and each library was sequenced using a HiSeq X Ten (Illumina). The Q30 was greater than 90% and the total number of reads ranged from 384 million to 406 million. The sequenced data were aligned with Cell Ranger (3.1.0) and analyzed with Seurat v3.0 after Gm42418 was removed from the gene-cell matrix (to identify correlating genes before removal). Ambient RNA was removed using SoupX (v1.4.5) 4.Cells satisfying the criteria of nGene_RNA>200, nFeature_RNA<6000, nCount_RNA<60,000, and Percent.mt<10 were used for analysis. Gene set enrichment analysis (GSEA) was performed using fgsea (v.1.12.0)16. GSEA was based on the molecular signature database (msigdb c5.all.v7.1.symbols, https: / / data.broadinstitute.org / gsea-msigdb / msigdb / release / 7.1 / ). The number of permutations adopted was 1000, and p<0.05 was considered statistically significant. Differential gene expression was evaluated using MAST (v.1.12.0)5, and gene set enrichment analysis (GSEA) was performed using fgsea (v.1.12.0)6.

[0208] (1-7) Immunostaining

[0209] Immunofluorescence and immunohistochemical staining were performed using formalin-fixed, paraffin-embedded mouse tissues according to standard protocols. Mice were sacrificed, and pancreatic tissues were collected, fixed in 10% formalin for 4 h at room temperature, and then washed in deionized water for 1 h at room temperature. The fixed pancreas was processed using an automated tissue processor (Leica, TP1020), embedded in paraffin, and whole sections were cut into 4-μm-thick sections and mounted on glass slides. For liver and fat, tissues were fixed in formalin overnight and then washed in deionized water for 1 h.

[0210] For immunofluorescence staining, slide-mounted samples were rehydrated and subjected to antigen retrieval in sodium citrate buffer. Non-target epitopes were blocked with 2% donkey serum (The Jackson Laboratory) in phosphate-buffered saline (PBS) for 1 h at room temperature. Anti-insulin (guinea pig, Dako, 1:500) or anti-Ki-67 (rabbit, Abcam, 1:1000) was applied as the primary antibody overnight at 4°C. The slides were washed with PBS and incubated with secondary antibodies [Alexa 488-conjugated donkey anti-mouse IgG (Jackson ImmunoResearch, 1:500), Alexa 594-conjugated donkey anti-rabbit IgG (Jackson ImmunoResearch, 1:500)] for 2 h at room temperature under a light shield. The slides were washed with PBS, stained with DAPI (Invitrogen, 1:1000) for 5 minutes, and then fluorescent mounting medium (Dako) was applied to the cover glass.

[0211] For immunohistochemical staining, pancreatic sections were subjected to antigen retrieval and washed with PBS as described for immunofluorescence staining. Endogenous peroxidases were blocked with BLOXALL (Vector, SP-6000-100) for 10 minutes at room temperature. Slides were blocked with 2% goat serum and incubated overnight at 4°C with anti-insulin (guinea pig, Dako, 1:1000), followed by washing with PBS. Immunohistochemistry was performed using the VECTASTAIN ABC kit (Vector Laboratories, PK-6100) and DAB (Vector Laboratories, SK-4100) according to the manufacturer's protocol, and slides were counterstained with hematoxylin and eosin.

[0212] (1-8) Measurement of β-cell mass and proliferation

[0213] To measure β-cell mass, pancreatic sections were collected every 80 μm and immunohistochemically stained for insulin. Images were acquired using a JuLI Stage recorder (NanoEnTek). The insulin-immunoreactive area and total pancreatic area were measured, and the β-cell mass was assessed by calculating the former divided by the latter. To assess β-cell proliferation, Ki-67 and insulin were immunostained in pancreatic sections collected every 80 μm. The percentage of Ki-67 and insulin co-positive cells was calculated as the β-cell proliferation rate as a ratio of the percentage of insulin-positive cells.

[0214] (1-9) Human studies

[0215] For the human study, we conducted a multicenter, prospective cohort study of subjects diagnosed with gestational diabetes mellitus (GDM) or gestational impaired glucose tolerance (GIGT) for the first time. Subjects were recruited from four centers in Korea between August 1995 and May 1997.

[0216] Women with GDM or GIGT who visited the initial postpartum assessment were enrolled in this study. The first postpartum follow-up visit occurred 2 months postpartum, and follow-up visits were conducted annually thereafter. Women who had 1 to 3 previous pregnancies were classified as “parity-low,” and those who had 4 or more previous pregnancies were classified as “parity-high.” A total of 455 women were included in the analysis (parity-low, n = 376; parity-high, n = 79). The median follow-up period was 4.0 years (interquartile range, 2.2–5.0) after delivery. At each visit, a standard 75-g OGTT and anthropometric measurements were measured. Insulin sensitivity was assessed by the Matsuda index as follows: 10,000 / √fasting glucose × (fasting insulin) × (mean glucose) × (mean insulin)]. The insulin production index was used to assess insulin secretion as follows: (insulin [30 min] - insulin [0 min]) / (glucose [30 min] - glucose [0 min]). The propensity index was used to assess the complexity of insulin secretion considering the degree of insulin sensitivity: (Matsuda index) × (insulin production index).

[0217] All subjects participated voluntarily, and prior consent was obtained from each subject. This study was approved by the Institutional Review Board of Seoul National University Bundang Hospital (IRB number: B-1903526-107) and was conducted in accordance with the requirements of the Declaration of Helsinki.

[0218] (1-10) Statistical Analysis

[0219] All data are presented as mean ± standard error of measurement (SEM) for continuous variables and as numbers (percentages) for nominal variables. Statistical significance was assessed by Student's t test (two-tailed) or ANOVA (with Tukey's post hoc test) for continuous variables and the ÷ test for categorical variables. Statistical analyses were performed using SPSS version 22 (IBM). Statistical significance levels are indicated as *P<0.05, **P<0.01, and ***P<0.001.

[0220]

[0221] Example 2

[0222] Increased β-cell mass and improved glucose tolerance following fertility

[0223] To investigate whether multiparity increases the risk of postpartum diabetes, a multiparous mouse model was established (Fig. 1a). Nine-week-old female C57BL / 6J mice were bred to produce three consecutive pregnancies (multiparous), and metabolic characteristics were analyzed three weeks after the last delivery. Virgin mice served as a control.

[0224] Compared to virgin mice, multiparous mice exhibited increased fat in inguinal white adipose tissue (iWAT) and visceral white adipose tissue (vWAT) (Fig. 1b). The body weight of multiparous mice was higher than that of virgin mice (Fig. 1c). However, multiparous mice exhibited improved glucose tolerance, and insulin tolerance was similar to that of virgin mice (Figs. 1d and 1e). Insulin sensitivity was further assessed using a hyperinsulinemic clamp study. Peripheral glucose infusion rate, glucose turnover rate, hepatic glucose production, and glucose uptake were similar in multiparous and virgin mice (Figs. 1f and 1g). Furthermore, energy expenditure and thermogenesis were unchanged in multiparous mice (Fig. 1h). These data indicate that multiparous mice, despite increased adiposity, did not induce insulin resistance but rather improved glucose tolerance.

[0225] To investigate whether β-cell changes in multiparous mice could explain the improved glucose tolerance without altering insulin sensitivity, we assessed β-cell function in multiparous mice. Ex vivo glucose-stimulated insulin secretion (GSIS) assays using isolated islets confirmed that insulin secretion was similar between virgin and multiparous mice (Fig. 1i). However, while basal insulin levels were similar, in vivo GSIS was enhanced in multiparous mice (Fig. 1j). Histological analysis revealed a 2.2-fold increase in β-cell mass in multiparous mice (0.6% in virgin mice and 1.3% in multiparous mice) (Figs. 1k and 1l). These results indicate that multiparous mice did not develop insulin resistance despite being more obese than virgin mice. Furthermore, glucose tolerance was improved in multiparous mice, and the increased β-cell mass remained intact 3 weeks after the last delivery.

[0226]

[0227] Example 3

[0228] Increased insulin resistance without β-cell compensation due to fertility

[0229] The observation that multiparous mice exhibited improved glucose tolerance as early as 3 weeks after their last birth contrasts with observations reported in humans. However, because the human analysis was performed much later after their last birth, it is possible that the phenotype observed in these multiparous mice reflects the acute effects of multiparity. To avoid the acute effects of pregnancy and explore the long-term metabolic effects of multiparity, the phenotypes of multiparous mice were assessed long-term after their last birth and compared with age-matched virgin mice (Fig. 3a). Multiparous mice continued to gain weight for 16 weeks after their last birth, reaching ~40 g at 34 weeks of age and becoming glucose intolerant and insulin resistant (Figs. 3b and 3d). Fat mass increased in multiparous mice, reflecting increases in iWAT and vWAT mass, and lean mass decreased (Figs. 3e to 3g). Hepatic steatosis worsened, white adipocyte size increased, and brown adipocytes became whiter in multiparous mice compared to virgin mice (Fig. 3h). These data indicate that multiparous mice tend to gain weight and become more insulin resistant over time than virgin mice.

[0230] Glucose intolerance develops when β cells fail to compensate for increased insulin resistance. Despite having a larger β-cell mass than virgin mice at 3 weeks after the last delivery, multiparous mice developed insulin resistance and worsened their glycemic profiles over time. Therefore, to test whether multiparous β-cells adequately compensated for insulin resistance, we analyzed β-cell function in multiparous mice at 34 weeks of age. Fasting plasma insulin concentrations were increased, and GSIS was blunted in multiparous mice, reflecting a substantial decrease in the insulin production index (Figures 3i and 3j). Furthermore, ex vivo GSIS analysis revealed increased basal insulin secretion under hypoglycemic conditions and impaired GSIS in islets of multiparous mice (Figure 3k). Given that insulin secretion was intact in multiparous β-cells up to 3 weeks after the last delivery, these data suggest that the insulin secretory function of multiparous β-cells deteriorated over time after the last delivery, consistent with the progression of insulin resistance.

[0231] To investigate whether multiparous mice could further increase mass in response to the development of insulin resistance, β-cell mass was measured in multiparous mice at 33 weeks of age. In multiparous mice, β-cell mass increased 2.2-fold 3 weeks after the last birth (0.6% of virgin control mice at 21 weeks of age and 1.3% in multiparous mice), before the development of insulin resistance (Fig. 1l). However, at 34 weeks of age, there was no significant difference in β-cell mass between multiparous and virgin mice (0.7% and 1.0%, respectively) (Figs. 3l and 3m). Interestingly, insulin resistance and weight gain did not further increase β-cell mass in multiparous mice (1.3% at 21 weeks of age and 1.0% at 34 weeks of age) (Figs. 1l and 3m).

[0232] That is, although obesity and subsequent insulin resistance developed in multiparous mice over time, β cells were unable to compensate for insulin resistance by increasing β cell mass due to impaired proliferative capacity. Furthermore, β cell function declined over time in multiparous mice. Therefore, this suggests that glucose intolerance in multiparous mice may be due to insufficient β cell compensation for insulin resistance.

[0233]

[0234] Example 4

[0235] Impaired β-cell proliferation following fertility

[0236] The failure of multiparous mice to increase β-cell mass to compensate for insulin resistance suggests that multiparous mice themselves may alter β-cell properties (increased cellular stress and induction of senescence) before the development of insulin resistance. Therefore, multiparous mice were treated with S-961, an insulin receptor antagonist that induces insulin resistance and β-cell proliferation, 3 weeks after the last delivery, and β-cell proliferation was assessed in these mice (Fig. 4a). Administration of S-961 for 3 days similarly induced glucose intolerance in both virgin and multiparous mice (Fig. 4b). However, while S-961 induced robust β-cell proliferation in virgin mice, this was not observed in multiparous mice (6.1% and 0.3%, respectively) (Figs. 4c and 4d). These results suggest that multiparous mouse β-cells may be defective in their ability to proliferate in response to insulin resistance.

[0237] To rule out the possibility that systemic changes in multiparous mice might inhibit β-cell proliferation, islets isolated from virgin and multiparous mice were transplanted into the left and right kidneys of virgin mice, respectively, and treated with S-961 for 7 days (Fig. 4e). As a result, S-961 treatment induced strong proliferation in β-cells in the left kidney of virgin mice, but not in the right kidney of multiparous mice (7.3% and 3.7%, respectively) (Figs. 4f and 4g). These results indicate that β-cells in multiparous mice have limited proliferative capacity even before the development of insulin resistance.

[0238] To gain insight into the molecular features associated with impaired β-cell proliferation in multiparous mice, we performed bulk RNA sequencing (RNA-seq) using islets isolated from virgin and multiparous mice treated or not with S-961 for 3 days (Figs. 1a and 4a). Analysis of bulk RNA-seq data from islets from virgin and multiparous mice without S-961 treatment identified numerous differentially expressed genes (DEGs). However, principal component analysis (PCA) did not reveal any significant changes in gene expression expected to impair proliferative capacity (Figs. 2a and 2b). Most of the genes upregulated in multiparous mouse islets have previously been reported to be upregulated during pregnancy (e.g., Lrrc55, Matn2, and Lars2). In contrast, bulk RNA-seq analysis of islets isolated from S-961-treated multiparous and virgin mice revealed distinct expression patterns in PCA (Fig. 2c and 2d). Gene set enrichment analysis (GSEA) revealed that the expression levels of genes involved in pathways related to cell cycle regulation were downregulated in islets from S-961-treated multiparous mice, whereas the expression levels of genes involved in pathways related to voltage-gated cation channels, potassium channel activity, and membrane protein complexes were upregulated (Fig. 4h). Analysis of cell cycle-related genes revealed that genes involved in centromere proteins (Cenpi and CeNPf), cell cycle progression (Cdk1, Cdk2, and Cdkn2d), and other cell cycle regulation (Hmmr, Stmn1, and Cdc20) were downregulated in islets from S-961-treated multiparous mice (Fig. 4i). In contrast, relatively few genes were upregulated in islets from S-961-treated multiparous mice, including genes reported to be upregulated during pregnancy (e.g., Matn2 and Lrrc55) (Fig. 4j).These transcriptomic changes indicate that β cells from multiparous mice are unable to activate their proliferative machinery in response to increased metabolic demands.

[0239]

[0240] Example 5

[0241] Increased cellular stress with aging in β cells following fertility

[0242] Although β-cell proliferative capacity was reduced in multiparous mice, bulk RNA-seq of islets did not reveal any relevant genetic signatures. Pancreatic islets are composed of various cell types, and β-cells themselves represent a heterogeneous population, with only a small fraction proliferating at any given time. Therefore, some transcriptomic information regarding β-cell proliferative capacity may be obscured in bulk RNA-seq analyses performed on islets. To overcome this limitation, single-cell RNA sequencing (scRNA-seq) was performed using islet cells isolated from multiparous and age-matched virgin mice 3 weeks after their last delivery. Islet cells from multiparous and virgin mice exhibited similar cell proportions and expression patterns, with the exception of β-cells (Figs. 6a and 6b, 2c). Uniform Manifold Approximation and Projection (UMAP) was used to divide β-cells into seven subpopulations (Figs. 5a and 6d). Among them, two different β-cell subpopulations, clusters 1 and 2, were mainly present in β-cells from multiparous mice, while clusters 5 and 7 were mainly present in β-cells from virgin mice (Fig. 5b and Fig. 6e). Compared with other β-cells, cluster 1 β-cells were enriched in genes related to the 'Response to Topologically Misplaced Proteins' and 'Response to Endoplasmic Reticulum (ER) Stress' pathways, and showed downregulation of genes related to the 'Electron Transport Chain', 'Cellular Respiration', 'ATP Metabolism', and 'Oxidative Phosphorylation' pathways (Fig. 5c). Cluster 2 β-cells were enriched in genes related to the 'Negative Regulation of Cell Population Proliferation' pathway, and showed downregulation of genes related to the 'Transport Vesicle' and 'Secretory Vesicle' pathways (Fig. 5d).More specifically, ER stress genes (Ddit3, Fkbp11, and Sdf2l1) and other stress-related genes (Nupr1, Atf5, Atf3, Hspa1a, Hspa1b, and Dnajb1) were upregulated in β-cells from multiparous mice, indicating increased cellular stress in multiparous mice (Figures 5e and 5f). Cluster 5, enriched in virgin β-cells, was upregulated in pathways related to oxidative phosphorylation and ATP metabolism, whereas ER-related pathways were downregulated (Figures 6f and 6g). Thus, scRNA-seq analysis indicates that β-cells from multiparous mice have the following characteristics: (1) increased cellular stress, including ER stress; (2) impaired cellular respiration and secretion functions; and (3) reduced proliferative capacity.

[0243] The expression levels of ER stress genes (Ddit3, Fkbp11, and Sdf2l1) and other stress-related genes (Nupr1, Atf5, Atf3, Hspa1a, Hspa1b, and Dnajb1) upregulated in β-cells of multiparous mice are shown in Table 2 below. On the other hand, among the genes related to cell stress, the genes whose expression was not confirmed to be increased in aged pancreatic β-cells according to multiparity are shown in Table 3 below. In Tables 2 and 3, avg_log2FC: average Fold change (Log2), p_val: p value, p_val_adj: adjusted p value, pct1: proportion of the gene expressed in clusters 2 and 5, pct 2: proportion of the gene expressed in clusters 1, 3, 4, 6, and 7.

[0244] [Table 2] DEG expression levels: fertile vs. virgin

[0245]

[0246]

[0247] [Table 3] Non-DEG expression levels: multiparous vs. virgin

[0248]

[0249] Cellular senescence is a state of cell cycle arrest that can be induced by repeated cell divisions and increased cellular stress. scRNA-seq analysis revealed that repeated β-cell divisions and increased cellular stress associated with multiparity likely impair the proliferative capacity of β-cells in multiparous mice. Indeed, telomere length was shortened (Fig. 5g), and the expression level of the senescence marker Cdkn2a (p16) was increased in islets from multiparous mice (Fig. 5h). These results suggest that multiparity increases cellular stress in β-cells, which induces β-cell senescence and aging.

[0250]

[0251] Example 6

[0252] Risk of diabetes due to fertility

[0253] To investigate the metabolic impact of multiparity on maternal metabolic physiology in humans, women with a history of gestational diabetes or impaired glucose tolerance underwent a 75-g hormone tolerance test 2 months postpartum. Women with one to three previous pregnancies were classified as low-parity, and those with four or more previous pregnancies as high-parity. A total of 455 women were analyzed (low-parity, n=376; high-parity, n=79). Baseline characteristics, including glucose levels during pregnancy, exercise, lactation, and follow-up duration, were similar between the two groups, but age and body mass index were higher in the high-parity group due to previous birth (Table 4). At 2 months postpartum, women with high parity had worse glycemic profiles compared to women with low parity (Figure 7a). The Matsuda index (insulin sensitivity) was ~10% lower in the high-parity group compared to the low-parity group, and the insulin production index and susceptibility index (β-cell function) tended to be lower in women with high parity, but these changes were not statistically significant (Figure 7b and Table 4). In a normal situation where β-cells are physiologically capable of compensating for insulin resistance, a decrease in the Matsuda index would result in an increase in the insulin production index, leaving the susceptibility index unchanged. Similarly, because the Matsuda index was lower compared to the results obtained in women with low parity, one might expect a higher insulin production index in women with high parity. However, despite the decrease in the Matsuda index, the insulin production index was not higher in women with high parity. Therefore, the susceptibility index was lower in women with high parity than in women with low parity. These results indicate that β-cells in women with high parity are unable to adequately compensate for insulin resistance.

[0254] [Table 4] Clinical characteristics of the human cohort

[0255]

[0256]

[0257] In Table 4, women who had one to three pregnancies were classified as low-parity (n=376), and women who had four or more pregnancies were classified as high-parity (n=79). Baseline characteristics, including anthropometric information and blood glucose profile data obtained from a 50-g glucose challenge and a 100-g oral glucose tolerance test during pregnancy, were compared. Clinical characteristics, including insulin production index, propensity index (β-cell function), and Matsuda index (insulin sensitivity) at 2 months postpartum, were compared. Data are expressed as mean ± SEM. *P < 0.05.

[0258] To further investigate whether β-cells in multiparous women can adequately compensate for insulin resistance, we examined how changes in postpartum BMI affect β-cell compensation for insulin resistance and metabolic profiles in multiparous women. Women with high parity were followed for a median of 4.0 years after their last delivery and stratified into tertiles based on the change in body mass index (BMI) from the initial follow-up (2 months postpartum) to the last follow-up. Interestingly, the Matsuda index was strongly correlated with BMI change. The Matsuda index increased in the first tertile with a decrease in BMI, decreased in the third tertile with a BMI increase, and remained unchanged in the second tertile (Figure 7c, Table 4). However, despite the decrease in Matsuda index, the insulin production index did not increase in the third tertile. Accordingly, the disposition index, which comprehensively measures β-cell insulin secretion function by considering the degree of insulin sensitivity, was lower in the third tertile compared to the first and second tertiles. The above findings that β cells fail to compensate for insulin resistance in multiparous women further support animal studies. Furthermore, they suggest that multiparity may increase the risk of postpartum diabetes in women by reducing the ability of β cells to compensate for insulin resistance.

[0259]

[0260] Example 7

[0261] Improvement of β-cell proliferation capacity following fertility

[0262] Nine-week-old female C57BL6 / J mice underwent three consecutive pregnancies and deliveries. At 20 weeks of age, dasatinib (5 mg / kg) and quercetin (50 mg / kg) were administered to 20-week-old mice over six days, while vehicle (PEG400) was administered to control mice over the same number of days. Subsequently, the insulin receptor antagonist S-961 was administered intraperitoneally at a dose of 100 nmol / kg mouse twice daily for three days, for a total of six times. After euthanasia, the mice were euthanized, and pancreatic tissues were obtained and formalin-fixed, paraffin-embedded samples were prepared, and immunofluorescence staining for Ki-67 was performed to evaluate the proliferation of pancreatic β cells.

[0263] As a result, it was confirmed that the pancreatic β-cell proliferation rate (1.52%) of mice administered dasatinib and quercetin was significantly higher than that of control mice (0.29%) (Figs. 9 and 10) (P value = 0.01). In other words, dasatinib and quercetin treatment can improve or restore the pancreatic β-cell proliferation ability impaired by fertility.

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Claims

1. A composition for promoting the proliferation of aged pancreatic β cells, comprising dasatinib and quercetin as active ingredients.

2. In paragraph 1, The composition wherein the aged pancreatic β cells are pancreatic β cells aged by pregnancy and childbirth.

3. In paragraph 2, A composition characterized in that the above-mentioned birth is two or more births.

4. In paragraph 1, The above composition is applied to a subject in need of enhancing the insulin secretion capacity of aged pancreatic β cells.

5. In paragraph 1, The above composition is a composition applied to a subject in need of enhancing the cellular respiratory function of aged pancreatic β cells.

6. In any one of paragraphs 1 to 5, The composition above is a pharmaceutical composition for preventing or treating diabetes.

7. In any one of paragraphs 1 to 5, The composition above is a health functional food composition for preventing or improving diabetes.

8. A biomarker for predicting or diagnosing pancreatic β-cell function aged by pregnancy and childbirth, comprising one or more genes selected from the group consisting of Ddit3, Fkbp11, Sdf2l1, Nupr1, Atf5, Atf3, Hspa1a, Hspa1b and Dnajb1 genes.

9. In paragraph 8, The above birth is a biomarker of two or more births.

10. In paragraph 8, A biomarker that predicts or diagnoses a condition in which pancreatic β cells are subjected to increased cellular stress; impaired cellular respiration and secretory function; or reduced cellular proliferation capacity due to pregnancy and childbirth when the expression of the above biomarker is increased.

11. A composition for predicting or diagnosing pancreatic β-cell function aged by pregnancy and childbirth, comprising a preparation for measuring the mRNA or protein expression level of a biomarker of any one of claims 8 to 10.

12. In paragraph 11, A composition wherein the agent for measuring the expression level of the mRNA comprises a primer pair, probe or antisense nucleotide that specifically binds to the biomarker, and the agent for measuring the expression level of the protein comprises an antibody specific to the protein of the biomarker gene.

13. A kit for predicting or diagnosing pancreatic β cell function aged by pregnancy and childbirth, comprising the composition of claim 11.

14. A step of measuring the mRNA or protein expression level of any one of the biomarkers of clauses 8 to 10 in a sample isolated from a subject; and A method for providing information for predicting or diagnosing pancreatic β cell function aged by pregnancy and childbirth, comprising a step of comparing the mRNA or protein expression level of the measured biomarker with that of a normal control sample.

15. In paragraph 14, The above method is a method for measuring gene expression at a single cell level.

16. In paragraph 14, The method further comprises a step of predicting or diagnosing that pancreatic β cells are in a state of increased cell stress; impaired cell respiration and secretion function; or decreased cell proliferation capacity due to pregnancy and childbirth when the mRNA or protein expression level of the measured biomarker is increased compared to a normal control sample.

17. A composition for improving cell stress in pancreatic β cells aged due to pregnancy and childbirth; for promoting cell respiration and secretion; or for promoting cell proliferation, comprising a substance that suppresses the expression or activity of a protein encoded by a biomarker of any one of claims 8 to 10.

18. In paragraph 17, The composition above is a pharmaceutical composition for preventing or treating diabetes.

19. In paragraph 17, The composition above is a health functional food composition for preventing or improving diabetes.

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