Carriers of PAM (peptidylglycine alpha-amidating monooxygenase) coding variant alleles have reduced insulinogenic index, higher risk of developing type 2 diabetes (T2D), and islets from heterozygous carriers of the PAM p.Asp563Gly variant display reduced insulin secretion. Exactly how global PAM deficiency contributes to hyperglycemia remains unclear. PAM is the only enzyme capable of converting glycine-extended peptide hormones into amidated products. Like neuropeptide Y (NPY), α-melanocyte stimulating hormone (αMSH), and glucagon-like peptide 1 (GLP-1), islet amyloid polypeptide (IAPP), a beta cell peptide that forms islet amyloid in type 2 diabetes, is a PAM substrate. We hypothesized that Pam deficiency limited to beta cells would lead to reduced insulin secretion, prevent the production of amidated IAPP, and reveal the extent to which loss of Pam in β-cells could accelerate the onset of hyperglycemia in mice.

PAM activity was assessed in human islets from donors based on their PAM genotype. We generated beta cell-specific Pam knockout (Ins1Cre/+, Pamfl/fl; βPamKO) mice and performed islet culture, histological, and metabolic assays to evaluate the physiological roles of Pam in beta cells. We analyzed human IAPP (hIAPP) amyloid fibril forming kinetics using synthetic amidated and non-amidated hIAPP peptides, and generated hIAPP knock-in beta cell-specific Pam knockout (hIAPPw/w βPamKO) mice to determine the impact of hIAPP amidation on islet amyloid burden, islet graft survival, and glucose tolerance.

PAM enzyme activity was significantly reduced in islets from donors with the PAM p. Asp563Gly T2D-risk allele. Islets from βPamKO mice had impaired second-phase glucose- and KCl-induced insulin secretion. Beta cells from βPamKO mice had larger dense-core granules and fewer and shorter cilia. Interestingly, non-amidated hIAPP was less fibrillogenic in vitro, and high glucose-treated hIAPPw/w βPamKO islets had reduced amyloid burden. Despite these changes in beta cell function, βPamKO mice were not more susceptible to diet-induced hyperglycemia. In vitro beta cell death and in vivo islet graft survival remained comparable between hIAPPw/w βPamKO and hIAPPw/w islets. Surprisingly, aged hIAPPw/w βPamKO mice had improved insulin secretion and glucose tolerance.

Eliminating Pam expression only in beta cells leads to morphological changes in insulin granules, reduced insulin secretion, reduced hIAPP amyloid burden and altered ciliogenesis. However, in mice beta-cell Pam deficiency has no impact on the development of diet- or hIAPP-induced hyperglycemia. Our data are consistent with current studies revealing ancient, highly conserved roles for peptidergic signaling in the coordination of the diverse signals needed to regulate fundamental processes such as glucose homeostasis.

The human solute carrier (SLC) superfamily of ~460 membrane transporters remains the largest understudied protein family despite its therapeutic potential. To advance SLC research, we developed a comprehensive knowledgebase that integrates systematic multi-omics data sets with selected curated information from public sources. We annotated SLC substrates through literature curation, compiled SLC disease associations using data mining techniques, and determined the subcellular localization of SLCs by combining annotations from public databases with an immunofluorescence imaging approach. This SLC-centric knowledge is made accessible to the scientific community via a web portal featuring interactive dashboards and visualization tools. Utilizing this systematically collected and curated resource, we computationally derived an integrated functional landscape for the entire human SLC superfamily. We identified clusters with distinct properties and established functional distances between transporters. Based on all available data sets and their integration, we assigned biochemical/biological functions to each SLC, making this study one of the largest systematic annotations of human gene function and a potential blueprint for future research endeavors.

Multiple studies have shown that genetic polymorphism in the MTHFR gene is associated with susceptibility to type 2 diabetes mellitus (T2DM), but the results remain controversial. This study was divided into two parts. The first part was to explore the relationship between the SNPs of MTHFR gene (C677T and A1298C) and genetic susceptibility to T2DM. Second, a meta-analysis was performed to evaluate the association between C677T gene and T2DM.

A case-control study was conducted to assess the association of MTHFR polymorphisms with T2DM risk. A meta-analysis including 7 studies was conducted by using Stata 17.0 software.

In case-control study at the C677T (rs1801133), we found that compared with the AA genotype, GG + GA genotype was associated with an increased risk of T2DM (OR = 1.605; 95% CI: 1.229-2.095; p = 0.001); compared with the GG/GA genotype, AA genotype was associated with a decreased risk of T2DM (OR = 0.620; 95% CI: 0.450-0.855; p = 0.004; OR = 0.625; 95% CI: 0.470-0.830; p = 0.001). After adjusting for age, gender, and BMI statistical differences persisted. In case-control study at the A1298C (rs1801131), there was no significant association in all genetic models after adjusting for age, gender, and BMI. In the overall meta-analysis of the C677T gene, significant heterogeneity was detected in the recessive model (I2 = 89.84%, p < 0.01) and allele model (I2 = 88.38%, p < 0.01). Subgroup analysis showed that there was a significant association in the recessive model (I2 = 76.52%, p < 0.01; OR = 2.27, 95% CI: 1.16-4.44) under random-effects models in Asians.

The results suggest that the C677T polymorphism might have ethnicity-dependent effects in T2DM and may be associated with susceptibility to T2DM in Asians.

We present OmniPRS, a scalable biobank-scale framework that improves genetic risk prediction for complex traits by integrating genome-wide association study (GWAS) summary statistics and functional annotations. It employs a mixed model incorporating tissue-specific genetic variance components from annotations to re-estimate single-nucleotide polymorphism (SNP) effects and constructs tissue-specific polygenic risk scores (PRSs) and aggregates them into the final OmniPRS. Our experiments, encompassing 135 simulation scenarios and 11 representative traits, demonstrate that OmniPRS is flexible and robust, delivering efficient and accurate predictions comparable to ten leading PRS methods. For quantitative (binary) traits, OmniPRS achieved an average improvement of 52.31% (19.83%) versus the clumping and thresholding (C+T) method, 3.92% (1.31%) versus the annotation-integrated PRSs (LDpred-funct), and 8.44% (2.27%) versus the Bayesian-based PRSs (PRScs). Notably, it achieved 35× faster computation than the PRScs. This rapid, precise framework enables efficient polygenic risk scoring with multi-annotation integration for large-scale genomic studies.

Insulin resistance (IR) is a metabolic disorder characterized by an impaired response to insulin. This condition is associated with excess adiposity and metabolic inflammation, contributing to an increased risk for related chronic diseases. Single-nucleotide polymorphisms (SNPs) can affect genes related to metabolic pathways which are related to IR and the individual response to nutrients and dietary patterns, affecting metabolic inflammation and insulin sensitivity. This narrative review explores the current evidence on interactions between genetic variants and dietary factors, specifically their effects in modulating IR and metabolic inflammation. A comprehensive search of the literature was conducted in PubMed, Google Scholar, and Web of Science, and a total of 95 articles were reviewed. The key findings reveal that SNPs in the TCF7L2, ADIPOQ, and TNF genes significantly influence metabolic responses and modulate the effects of the Mediterranean diet on biomarkers of inflammation and IR. Genotype-dependent variations in IR and inflammation biomarkers were observed in the response to different diets for SNPs in the TCF7L2, ADIPOQ, and TNF genes. Additionally, polygenic risk scores (PRSs) can also predict the response to the intake of nutrients and specific diets, and offer a promising tool for assessing genetic predisposition to IR. This review underscores the pivotal role of an individual's genetic background in the effects of their nutrient intake and in the responses to dietetic interventions, thereby laying the foundation for personalized and effective nutritional strategies tailored to each individual's necessity in mitigating IR and its associated risk factors for chronic diseases.

To examine the association between frailty and incident type 2 diabetes mellitus (T2DM), considering the joint effect of multimorbidity and genetic risk.

The study included 429,022 individuals in the UK Biobank. We used Cox regression with hazard ratio (HR) and 95 % confidence interval (CI) to 1) evaluate the associations of frailty with incident T2DM, 2) explore whether frailty and multimorbidity would have a joint effect, and 3) assess whether the associations were modified by genetic risk.

Compared with non-frail individuals, prefrail and frail individuals were at higher risk of T2DM: HR[95 %CI] = 1.42 [1.38;1.47] for prefrailty and 1.81[1.70;1.92] for frailty. Five frailty components were associated with increased risk of T2DM: HR[95 %CI] = 1.21[1.17;1.26] for weight loss, 1.35[1.30;1.40] for exhaustion, 1.31[1.26;1.37] for low physical activity, 1.27[1.20;1.33] for low grip strength, and 1.47[1.41;1.52] for slow gait speed. The increased risks were more pronounced among frail individuals with more than three morbidities: HR[95 %CI] = 4.10[3.76;4.46]. Frail individuals at high genetic risk had a four and a half-fold greater risk of T2DM compared with non-frail individuals at low genetic risk: HR[95 %CI] = 4.54[4.14;4.97].

Frailty was associated with increased risk of T2DM, especially in individuals with higher number of morbidities and high genetic risk. Frailty may be an independent risk factor for T2DM and targeted strategies to prevent and manage frailty would contribute to reducing the risk of T2DM.

Background To explore whether there is a bidirectional relationship between Parkinson's disease (PD) and type 2 diabetes mellitus (T2DM), study the common pathogenic mechanisms, screen relevant genes involved in the pathological process, and predict the potential targets of metformin (Met), so as to develop new therapeutic strategies. Method A two-sample Mendelian randomization (MR) analysis was conducted to analyze the correlation between PD and T2DM. Common confounding genes identified in both PD and T2DM datasets were subjected to GO and KEGG analysis, PPI network analysis, and Hub gene identification. qPCR was used to verify the expression of hub genes in an animal model of T2DM complicated with PD. Subsequently, the analysis focused on whether metformin alleviates the behavioral and pathological manifestations of PD aggravated by T2DM. The intersection of metformin with T2DM and PD targets was identified, and the core targets and signaling pathways were analyzed. Finally, molecular docking analysis was performed between metformin and core proteins to identify the docking sites. Result Through MR analysis, a positive correlation between PD and T2DM was identified, indicating a mutual causal relationship. The hub genes RAC1, TPM2, MGA, and DENND3 are up-regulated in animal models of T2DM with PD. Met targets intersecting with T2DM and PD were analyzed, revealing 17 and 21 intersecting genes respectively, involved in various pathways related to oxidative stress, immune, and inflammation. PPI analysis identified hub genes for T2DM (MMP9, NCF1, CYCS, EIF4E, SOD2) and PD (GFAP, VIM, MOCOS, EIF1, TH, ACTA2, CDC42). Animal models validated the expression of these genes and pathways. Molecular docking analysis explored Met's binding sites on proteins, with lower binding energies indicating greater stability. Conclusion This study contributes to a deeper understanding of the co pathogenesis of PD and T2DM, and provides new insights into the role of metformin in this disease.

Peptidylglycine-α-amidating monooxygenase (PAM) is a critical enzyme in the endocrine system responsible for activation, by amidation, of bioactive peptides.

To define the clinical phenotype of carriers of genetic mutations associated with impaired PAM-amidating activity (PAM-AMA).

We used genetic and phenotypic data from cohort studies: the Malmö Diet and Cancer (MDC; 1991-1996; reexamination in 2002-2012), the Malmö Preventive Project (MPP; 2002-2006), and the UK Biobank (UKB; 2012).

Exome-wide association analysis was used to identify loss-of-function (LoF) variants associated with reduced PAM-AMA and subsequently used for association with the outcomes.

This study included n∼4500 participants from a subcohort of the MDC (MDC-Cardiovascular cohort), n∼4500 from MPP, and n∼300,000 from UKB.

Endocrine-metabolic traits suggested by prior literature, muscle mass, muscle function, and sarcopenia.

Two LoF variants in the PAM gene, Ser539Trp (minor allele frequency: 0.7%) and Asp563Gly (5%), independently contributed to a decrease of 2.33 [95% confidence interval (CI): 2.52/2.15; P = 2.5E-140] and 0.98 (1.04/0.92; P = 1.12E-225) SD units of PAM-AMA, respectively. The cumulative effect of the LoF was associated with diabetes, reduced insulin secretion, and higher levels of GH and IGF-1. Moreover, carriers had reduced muscle mass and function, followed by a higher risk of sarcopenia. Indeed, the Ser539Trp mutation increased the risk of sarcopenia by 30% (odds ratio 1.31; 95% CI: 1.16/1.47; P = 9.8E-06), independently of age and diabetes.

PAM-AMA genetic deficiency results in a prediabetic sarcopenic phenotype. Early identification of PAM LoF carriers would allow targeted exercise interventions and calls for novel therapies that restore enzymatic activity.

According to the IDF Diabetes Atlas regularly published by International Diabetes Federation, the prevalence of diabetes and impaired glucose tolerance (IGT), diabetes-related mortality and health expenditure are becoming serious eventually at the global, regional and national level. While the data alarm people, the exact cause remains unknown. It is widely accepted that glucose metabolism can be impaired by circadian rhythms disruption and sleep disturbances, both closely linked to exposure to light at night. However, there is little direct experiment on primates to study the precise extent of how serious bright sleeping environment at night impairs glucose metabolism, what the relationship is between nocturnal brightness and the development of diabetes and IGT, any difference between male and female, and whether aging and weight are involved. This study aims to address these questions in monkeys.

In a reduced daytime bright condition resembling human living rooms, 197 Cynomolgus (130 male, 67 female) were exposed to three distinct light intensities (13, 35, 75Lux) at night for consecutive ten months. Animals were retrospectively divided into four groups according to glucose metabolic status by the end of the experimental session, spontaneous diabetes mellitus (SDM, N=11), light-induced diabetes (LID, N=83), impaired fasting glucose tolerance (IFG, N=36), and normal glucose tolerance (NGT, N=67). Data pertaining to the glucose metabolism such as concentrations of fasting glucose, glycosylated hemoglobin, plasma insulin and C-peptide were collected monthly and analyzed.

1) Bright night exasperated glucose metabolism in individuals with pre-existing diabetes, led to premature death; 2) Stronger white light intensity-dependently induced diabetes and IFG in previous healthy monkeys: the brighter the light, the quicker the metabolism disturbance and IFG developed, and also the higher morbidity of LID and IFG; 3) Exposure to nocturnal light had a synergistic impairing effect on glucose metabolism with aging and weight. 4) Female were more susceptible to night brightness.

Light in sleeping environment exacerbates glucose metabolism in individuals with pre-existing diabetes, leads to IFG and diabetes in healthy primates. Moreover, the harmful effects of bright night on glucose metabolism are synergistic with aging and weight.

Recent advances in lineage-tracing technologies have significantly improved our understanding of pancreatic cell biology, particularly in elucidating the ontogeny and regenerative capacity of pancreatic cells. A deeper appreciation of the mechanisms underlying pancreatic cell identity and plasticity holds the potential to inform the development of new therapeutic modalities for conditions such as diabetes and pancreatitis. With this goal in mind, here we summarize advances, challenges, and future directions in tracing pancreatic cell origins and fates using lineage-tracing technologies. Given their essential role for blood glucose regulation, we pay particular attention on the insights gained from endocrine cells, especially β-cells.

Southern Schisandra is the dried and matured fruit of Schisandra sphenanthera Rehd. et Wils. in the family of Magnoliaceae; Traditional medicine reports that Schisandra sphenanthera has astringent and astringent properties, benefiting qi and promoting the production of body fluid, tranquilising the heart and calming the mind; it is clinically utilized for prolonged cough, thirst due to injury of the body fluid, internal heat and thirst, palpitation and insomnia, etc., and thirst belongs to the category of diabetes mellitus; the literature reports and the preliminary study of our team showed that Schisandra sphenanthera can be used to prevent and control diabetes mellitus.

In the research, we investigated the mechanism of action of SDP against T2DM by integrating pharmacodynamics, endogenous metabolite assays and signalling pathways.

UPLC-MS/MS was used to identify the chemical constituents. HPLC was utilized to determine the content of eight lignan-like components in SDP. A T2DM rat model was established by the combined induction of high-fat and high-sugar feed and STZ, and the mechanism of action of SDP on T2DM was investigated by using biochemical indices, Western blot analysis of protein expression, mRNA expression, immunohistochemistry and endogenous metabolites.

The chemical components in SDP were determined by UPLC-MS/MS and HPLC, and biochemical indicators determined that SDP has the effects of lowering blood glucose, anti-glycolipid metabolism, and anti-oxidative stress, and is able to restore pathological damage in the liver and pancreas, activate the PI3K/AKT, AMPK/mTOR, and sweetness receptor signalling pathways, restore the sweetness receptor mRNAs, and modulate the urinary compounds such as malic acid, γ-aminobutyric acid, leucine, N-acetylaspartic acid and other compounds thereby achieving the therapeutic effect of T2DM.

SDP can ameliorate diabetes-induced symptoms related to elevated blood glucose, dyslipidaemia, elevated fasting insulin levels and impaired glucose tolerance in rats; the anti-T2DM of SDP may be through the regulation of the sweet taste receptor pathway, the PI3K/AKT/mTOR and the AMPK/mTOR signalling pathway, which leads to the development of a normal level and exerts an antidiabetic effect.

Phenotyping and genotyping initiatives within the Integrated Islet Distribution Program (IIDP), the largest source of human islets for research in the U.S., provide standardized assessment of islet preparations distributed to researchers, enabling the integration of multiple data types. Data from islets of the first 299 organ donors without diabetes, analyzed using this pipeline, highlights substantial heterogeneity in islet cell composition associated with hormone secretory traits, sex, reported race and ethnicity, genetically predicted ancestry, and genetic risk for type 2 diabetes (T2D). While α and β cell composition influenced insulin and glucagon secretory traits, the abundance of δ cells showed the strongest association with insulin secretion and was also associated with the genetic risk score (GRS) for T2D. These findings have important implications for understanding mechanisms underlying diabetes heterogeneity and islet dysfunction and may provide insight into strategies for personalized medicine and β cell replacement therapy.

The present study aimed to investigate the potential effects of white hyacinth bean polysaccharide (WHBP) against type 2 diabetic mellitus (T2DM) which was established by high-glucose/high-fat for 8 weeks, combined with a low-dose streptozotocin (STZ) injection. Our results showed that WHBP behaved the hypoglycemic effect by attenuating fasting blood glucose in vivo. WHBP-mediated anti-diabetic effects associated with the attenuation of insulin resistance and pancreatic impairment, as evidenced by the mitigation of pathological changes, inflammatory response and oxidative stress in the pancreas of T2DM rats. Meanwhile, gut protection was also shown during WHBP-mediated anti-diabetic effects, and glucagon-like peptide-1 (GLP-1), a mediator of the entero-insular axis, was observed to be elevated in both gut and pancreas of WHBP groups when compared to DM group, suggesting that hypoglycemic effects of WHBP were implicated in gut-pancreas interaction. Subsequently, untargeted metabolomics analysis performed by UPLC-QTOF/MS and showed that WHBP administration significantly adjusted the levels of 40 metabolites when compared to DM group. Further data concerning pathway analysis showed that WHBP administration significantly regulated the phenylalanine metabolism, tryptophan metabolism, arginine and proline, isoleucine metabolism, and glycerophospholipid metabolism in T2DM rats. Together, our results suggested that WHBP performed hypoglycemic effects and pancreatic protection linked to entero-insular axis involvement with GLP-1 and reversed metabolic disturbances in T2DM rats.

Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycaemia, beta cell glucotoxicity and subsequently type 2 diabetes. In this study, we explored the effects of in vitro hyperglycaemic conditions on human pancreatic islet gene expression across 24 h in six pancreatic cell types: alpha; beta; gamma; delta; ductal; and acinar. We hypothesised that genes associated with hyperglycaemic conditions may be relevant to the onset and progression of diabetes.

We exposed human pancreatic islets from two donors to low (2.8 mmol/l) and high (15.0 mmol/l) glucose concentrations over 24 h in vitro. To assess the transcriptome, we performed single-cell RNA-seq (scRNA-seq) at seven time points. We modelled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Additionally, we integrated genomic features and genetic summary statistics to nominate candidate effector genes. For three of these genes, we functionally characterised the effect on insulin production and secretion using CRISPR interference to knock down gene expression in EndoC-βH1 cells, followed by a glucose-stimulated insulin secretion assay.

In the discrete time models, we identified 1344 genes associated with time and 668 genes associated with glucose exposure across all cell types and time points. In the continuous time models, we identified 1311 genes associated with time, 345 genes associated with glucose exposure and 418 genes associated with interaction effects between time and glucose across all cell types. By integrating these expression profiles with summary statistics from genetic association studies, we identified 2449 candidate effector genes for type 2 diabetes, HbA1c, random blood glucose and fasting blood glucose. Of these candidate effector genes, we showed that three (ERO1B, HNRNPA2B1 and RHOBTB3) exhibited an effect on glucose-stimulated insulin production and secretion in EndoC-βH1 cells.

The findings of our study provide an in-depth characterisation of the 24 h transcriptomic response of human pancreatic islets to glucose exposure at a single-cell resolution. By integrating differentially expressed genes with genetic signals for type 2 diabetes and glucose-related traits, we provide insights into the molecular mechanisms underlying glucose homeostasis. Finally, we provide functional evidence to support the role of three candidate effector genes in insulin secretion and production.

The scRNA-seq data from the 24 h glucose exposure experiment performed in this study are available in the database of Genotypes and Phenotypes (dbGap; https://www.ncbi.nlm.nih.gov/gap/ ) with accession no. phs001188.v3.p1. Study metadata and summary statistics for the differential expression, gene set enrichment and candidate effector gene prediction analyses are available in the Zenodo data repository ( https://zenodo.org/ ) under accession number 11123248. The code used in this study is publicly available at https://github.com/CollinsLabBioComp/publication-islet_glucose_timecourse .

Numerous research studies have indicated a possible association between type 2 diabetes (T2DM) and gut microbiota. To explore specific metabolic pathways connecting gut microbiota and T2DM, we employed Mendelian randomization (MR) and linkage disequilibrium score regression (LDSC) techniques.

This research utilized data from genome-wide association studies (GWAS) that are publicly accessible. We evaluated the genetic correlation between gut microbiota and T2DM using LDSC. Causality was primarily determined through the inverse variance weighted (IVW) method. To verify the robustness of our results, we conducted sensitivity analyses using several approaches, including the weighted median, MR-Egger, and MR-PRESSO. We integrated summary effect estimates from LDSC, along with forward and reverse MR, into a meta-analysis for T2DM using various data sources. Additionally, mediation analysis was performed to explore the impact of plasma metabolites on the relationship between gut microbiota and T2DM.

Our study indicated a significant genetic correlation between genus RuminococcaceaeUCG005 (Rg = -0.26, Rg_P = 2.07×10-4) and T2DM. Moreover, the forward MR analysis identified genus RuminococcaceaeUCG010 (OR = 0.857, 95% CI 0.795, 0.924; P = 6.33×10-5) and order Clostridiales (OR = 0.936, 95% CI 0.878, 0.997; P = 0.039) as being significantly associated with a decreased risk of T2DM. The analysis also highlighted several plasma metabolites as significant mediators in these relationships, with metabolites like octadecadienedioate (C18:2-DC) and branched chain 14:0 dicarboxylic acid being notably involved.

The findings demonstrate a significant impact of gut microbiota on T2DM via plasma metabolites, suggesting potential metabolic pathways for therapeutic targeting. This study enhances our understanding of the microbiota's role in T2DM pathogenesis and supports the development of microbiota-based interventions.

Obesity causes significant morbidity and mortality globally. Research in the last three decades has delivered a step-change in our understanding of the fundamental mechanisms that regulate energy homeostasis, building on foundational discoveries in mouse models of metabolic disease. However, not all findings made in rodents have translated to humans, hampering drug discovery in this field. Here, we review how studies in mice and humans have informed our current framework for understanding energy homeostasis, discuss their challenges and limitations, and offer a perspective on how human studies may play an increasingly important role in the discovery of disease mechanisms and identification of therapeutic targets in the future.

While most genetic variants of type 2 diabetes (T2D) are suggested to be associated with β-cell dysfunction cross sectionally, their association with the longitudinal change of β-cell function remains largely unknown.

We analyzed data from 6,311 participants without T2D at baseline (mean [SD] age 51.6 [8.7] years) from a community-based prospective cohort in Korea. Participants underwent biennial 2-h 75-g oral glucose tolerance tests (OGTTs) during 14 years of follow-up, and the OGTT-derived disposition index (DI) was used as a marker for β-cell function. Genetic risk was quantified using the genome-wide polygenic risk score (PRS) and was stratified into low (1st quintile), intermediate (2nd-4th quintiles), and high (5th quintile) genetic risk. Lifestyle was assessed according to Life's Essential 8.

During a mean follow-up of 10.9 years, 374 (29.6%), 851 (22.5%), and 188 (14.9%) participants developed T2D in the high, intermediate, and low genetic risk groups, respectively. Compared with the low genetic risk group, participants in the high genetic risk group had a 25% lower DI at baseline. Furthermore, in longitudinal analysis, we observed a 1.83-fold faster decline in log2-transformed DI per year (-0.034 vs. -0.019, P = 2.1 × 10-3; per 1-SD increase in T2D PRS, P = 1.2 × 10-4). Healthy lifestyle attenuated the rate of decline in DI across all genetic risk groups.

Individuals with a higher genetic risk for T2D exhibited not only a lower OGTT-derived β-cell function at baseline but also a notably more rapid decline during follow-up. This information could be used to enable a focused precision prevention with lifestyle intervention.

Inducible pluripotent stem cell-derived human β-like cells (BLCs) hold promise for both therapy and disease modeling, but their generation remains challenging and their functional analyses beyond transcriptomic and morphological assessments remain limited. Here, we validate an approach using multicellular and single-cell electrophysiological tools to evaluate function of BLCs from pioneer protocols that can be easily adapted to more differentiated BLCs. The multi-electrode arrays (MEAs) measuring the extracellular electrical activity revealed that BLCs, like primary β-cells, are electrically coupled and produce slow potential (SP) signals that are closely linked to insulin secretion. We also used high-resolution single-cell patch clamp measurements to capture the exocytotic properties, and characterize voltage-gated sodium and calcium currents, and found that they were comparable with those in primary β- and EndoC-βH1 cells. The KATP channel conductance is greater than in human primary β-cells, which may account for the limited glucose responsiveness observed with MEA. We used MEAs to study the impact of the type 2 diabetes-protective SLC30A8 allele (p.Lys34Serfs50*) and found that BLCs with this allele have stronger electrical coupling activity. Our data suggest that BLCs can be used to evaluate the functional impact of genetic variants on β-cell function and coupling.

Epinephrine influences the function of pancreatic β-cells, primarily through the α2A-adrenergic receptor (α2A-AR) on their plasma membrane. Previous studies indicate that epinephrine transiently suppresses insulin secretion, whereas prolonged exposure induces its compensatory secretion. Nonetheless, the impact of epinephrine-induced α2A-AR signaling on the survival and function of pancreatic β-cells, particularly the impact of reprogramming after their removal from sustained epinephrine stimulation, remains elusive. In the present study, we applied MIN6, a murine insulinoma cell line, with 3 days of high concentration epinephrine incubation and 2 days of standard incubation, explored cell function and activity, and analyzed relevant regulatory pathways. The results showed that chronic epinephrine incubation led to the desensitization of α2A-AR and enhanced insulin secretion. An increased number of docked insulin granules and impaired Syntaxin-2 was found after chronic epinephrine exposure. Growth curve and cell cycle analyses showed the inhibition of cell proliferation. Transcriptome analysis showed the occurrence of endoplasmic reticulum stress (ER stress) and oxidative stress, such as the presence of BiP, CHOP, IRE1, ATF4, and XBP, affecting cellular endoplasmic reticulum function and survival, along with UCP2, OPA1, PINK, and PRKN, associated with mitochondrial dysfunction. Consequently, we conclude that chronic exposure to epinephrine induces α2A-AR desensitization and leads to ER and oxidative stress, impairing protein processing and mitochondrial function, leading to modified pancreatic β-cell secretory function and cell fate.

Bayesian network (BN) models were developed to explore the specific relationships between influencing factors and type 2 diabetes mellitus (T2DM), coronary heart disease (CAD), and their comorbidities. The aim was to predict disease occurrence and diagnose etiology using these models, thereby informing the development of effective prevention and control strategies for T2DM, CAD, and their comorbidities.

Employing a case-control design, the study compared individuals with T2DM, CAD, and their comorbidities (case group) with healthy counterparts (control group). Univariate and multivariate Logistic regression analyses were conducted to identify disease-influencing factors. The BN structure was learned using the Tabu search algorithm, with parameter estimation achieved through maximum likelihood estimation. The predictive performance of the BN model was assessed using the confusion matrix, and Netica software was utilized for visual prediction and diagnosis.

The study involved 3,824 participants, including 1,175 controls, 1,163 T2DM cases, 982 CAD cases, and 504 comorbidity cases. The BN model unveiled factors directly and indirectly impacting T2DM, such as age, region, education level, and family history (FH). Variables like exercise, LDL-C, TC, fruit, and sweet food intake exhibited direct effects, while smoking, alcohol consumption, occupation, heart rate, HDL-C, meat, and staple food intake had indirect effects. Similarly, for CAD, factors with direct and indirect effects included age, smoking, SBP, exercise, meat, and fruit intake, while sleeping time and heart rate showed direct effects. Regarding T2DM and CAD comorbidities, age, FBG, SBP, fruit, and sweet intake demonstrated both direct and indirect effects, whereas exercise and HDL-C exhibited direct effects, and region, education level, DBP, and TC showed indirect effects.

The BN model constructed using the Tabu search algorithm showcased robust predictive performance, reliability, and applicability in forecasting disease probabilities for T2DM, CAD, and their comorbidities. These findings offer valuable insights for enhancing prevention and control strategies and exploring the application of BN in predicting and diagnosing chronic diseases.

Diet is a key lifestyle component that influences metabolic health through several factors, including total energy intake and macronutrient composition. While the impact of caloric intake on gene expression and physiological phenomena in various tissues is well described, the influence of dietary macronutrient composition on these parameters is less well studied. Here, we use the Nutritional Geometry framework to investigate the role of macronutrient composition on metabolic function and gene regulation in adipose tissue. Using ten isocaloric diets that vary systematically in their proportion of energy from fat, protein, and carbohydrates, we find that gene expression and splicing are highly responsive to macronutrient composition, with distinct sets of genes regulated by different macronutrient interactions. Specifically, the expression of many genes associated with Bardet-Biedl syndrome is responsive to dietary fat content. Splicing and expression changes occur in largely separate gene sets, highlighting distinct mechanisms by which dietary composition influences the transcriptome and emphasizing the importance of considering splicing changes to more fully capture the gene regulation response to environmental changes such as diet. Our study provides insight into the gene regulation plasticity of adipose tissue in response to macronutrient composition, beyond the already well-characterized response to caloric intake.

Progression of β-cell loss in diabetes mellitus is significantly influenced by persistent hyperglycemia. At the cellular level, a number of signaling cascades affect the expression of apoptotic genes, ultimately resulting in β-cell failure; these cascades have not been elucidated. Mitochondrial aldehyde dehydrogenase-2 (ALDH2) plays a central role in the detoxification of reactive aldehydes generated from endogenous and exogenous sources and protects against mitochondrial deterioration in cells. Here we report that under diabetogenic conditions, ALDH2 is strongly inactivated in β-cells through CDK5-dependent glutathione antioxidant imbalance by glucose-6-phosphate dehydrogenase (G6PD) degradation. Intriguingly, CDK5 inhibition strengthens mitochondrial antioxidant defense through ALDH2 activation. Mitochondrial ALDH2 activation selectively preserves β-cells against high-glucose-induced dysfunction by activating AMPK and Hydrogen Sulfide (H2S) signaling. This is associated with the stabilization and enhancement of the activity of G6PD by SIRT2, a cytoplasmic NAD+-dependent deacetylase, and is thereby linked to an elevation in the GSH/GSSG ratio, which leads to the inhibition of mitochondrial dysfunction under high-glucose conditions. Furthermore, treatment with NaHS, an H2S donor, selectively preserves β-cell function by promoting ALDH2 activity, leading to the inhibition of lipid peroxidation by high-glucose concentrations. Collectively, our results provide the first direct evidence that ALDH2 activation enhances H2S-AMPK-G6PD signaling, leading to improved β-cell function and survival under high-glucose conditions via the glutathione redox balance.

This study aims to investigate the correlations between islet function/ insulin resistance and serum lipid levels, as well as to assess whether the strength of such correlations is affected by the GCKR rs1260326 variant in healthy and T2D individuals. We performed an oral glucose tolerance test (OGTT) on 4889 middle-aged adults, including 3135 healthy and 1754 T2D individuals from the REACTION population study in the Nanjing region. We also measured their serum lipid levels and genotyped for rs1260326. We found that serum high-density lipoprotein (HDL) cholesterol and triglyceride (TG) levels were independently correlated with indexes of islet function (HOMA-β and IGI [insulinogenic index]) and insulin resistance (HOMO-IR and ISIMatsuda) in both healthy and T2D individuals. The correlations were significantly decreased in T2D individuals, with significant heterogeneities compared to healthy controls (I2 > 75%, Phet < 0.05). Although no correlation was observed between serum total cholesterol (TC) level and islet function/ insulin resistance in healthy controls, significant correlations were found in T2D individuals, with significant heterogeneity to healthy controls in the correlation with ISIMatsuda(I2 = 85.3%, Phet = 0.009). Furthermore, we found significant interactions of the GCKR rs1260326 variant for the correlations between serum HDL cholesterol and HOMA-β/ISIMatsuda in T2D subjects (P = 0.015 and 0.038, respectively). These findings illustrate that distinct correlations between serum lipid levels and islet function/ insulin resistance occurred in T2D subjects compared to healthy individuals. Common gene variants, such as rs1260326, might interact substantially when studied in specific populations, especially T2D disease status.

Genetic studies have identified numerous loci associated with type 2 diabetes (T2D), but the functional roles of many loci remain unexplored. Here, we engineered isogenic knockout human embryonic stem cell lines for 20 genes associated with T2D risk. We examined the impacts of each knockout on β cell differentiation, functions, and survival. We generated gene expression and chromatin accessibility profiles on β cells derived from each knockout line. Analyses of T2D-association signals overlapping HNF4A-dependent ATAC peaks identified a likely causal variant at the FAIM2 T2D-association signal. Additionally, the integrative association analyses identified four genes (CP, RNASE1, PCSK1N, and GSTA2) associated with insulin production, and two genes (TAGLN3 and DHRS2) associated with β cell sensitivity to lipotoxicity. Finally, we leveraged deep ATAC-seq read coverage to assess allele-specific imbalance at variants heterozygous in the parental line and identified a single likely functional variant at each of 23 T2D-association signals.

Extracellular vesicles (EVs) have emerged as a unique mediator of interorgan communications, playing important roles in the pathophysiologic process of various diseases, including diabetes and other metabolic diseases. Here, we reported that the EVs released by steatotic hepatocytes exerted a detrimental effect on pancreatic β cells, leading to β-cell apoptosis and dysfunction. The effect was profoundly attributable to an up-regulation of miR-126a-3p in the steatotic hepatocyte-derived EVs. Accordingly, overexpression of miR-126a-3p promoted, whereas inhibition of miR-126a-3p prevented β-cell apoptosis, through a mechanism related to its target gene, insulin receptor substrate-2. Moreover, inhibition of miR-126a-3p by its specific antagomir was able to partially reverse the loss of β-cell mass and ameliorate hyperglycaemia in diabetic mice. Thus, the findings reveal a novel pathogenic role of steatotic hepatocyte-derived EVs, which mechanistically links nonalcoholic fatty liver disease to the development of diabetes.

While type 2 diabetes mellitus (T2DM) is commonly considered a putative causal risk factor for stroke, the effect of stroke on T2DM remains unclear. The intrinsic link underlying T2DM and stroke has not been thoroughly examined. We aimed to evaluate the phenotypic and genetic relationships underlying T2DM and stroke. We evaluated phenotypic associations using data from the UK Biobank (N = 472,050). We then investigated genetic relationships by leveraging genomic data in European ancestry for T2DM, with and without adjusting (adj) for BMI (T2DM: n = 74,124 case subjects/824,006 control subjects; T2DMadjBMI: n = 50,409 case subjects/523,897 control subjects), and for stroke (n = 73,652 case subjects/1,234,808 control subjects). We performed additional analyses using genomic data in East Asian ancestry for T2DM (n = 77,418 case subjects/356,122 control subjects) and for stroke (n = 27,413 case subjects/237,242 control subjects). Observational analyses suggested a significantly increased hazard of stroke among individuals with T2DM (hazard ratio 2.28 [95% CI 1.97-2.64]), but a slightly increased hazard of T2DM among individuals with stroke (1.22 [1.03-1.45]) which attenuated to 1.14 (0.96-1.36) in sensitivity analysis. A positive global T2DM-stroke genetic correlation was observed (rg = 0.35; P = 1.46 × 10-27), largely independent of BMI (T2DMadjBMI-stroke: rg = 0.27; P = 3.59 × 10-13). This was further corroborated by 38 shared independent loci and 161 shared expression-trait associations. Mendelian randomization analyses suggested a putative causal effect of T2DM on stroke in Europeans (odds ratio 1.07 [95% CI 1.06-1.09]), which remained significant in East Asians (1.03 [1.01-1.06]). Conversely, despite a putative causal effect of stroke on T2DM also observed in Europeans (1.21 [1.07-1.37]), it attenuated to 1.04 (0.91-1.19) in East Asians. Our study provides additional evidence to underscore the significant relationship between T2DM and stroke.

Adipose tissue dysfunction underlies many of the metabolic complications associated with obesity. A better understanding of the gene regulation differences present in metabolically unhealthy adipose tissue can provide insights into the mechanisms underlying adipose tissue dysfunction. Here, we used RNA-seq data collected from a differentiation time course of lean, obese, and obese with type 2 diabetes (T2D) individuals to characterize the role of alterative splicing in adipocyte differentiation and function. We found that splicing was highly dynamic across adipocyte differentiation in all three cohorts, and that the dynamics of splicing were significantly impacted by metabolic phenotype. We also found that there was very little overlap between genes that were differentially spliced in adipocyte differentiation and those that were differentially expressed, positioning alternative splicing as a largely independent gene regulatory mechanism whose impact would be missed when looking at gene expression changes alone. To assess the impact of alternative splicing across adipocyte differentiation on genetic risk for metabolic diseases, we integrated the differential splicing results generated here with genome-wide association study results for body mass index and T2D, and found that variants associated with T2D were enriched in regions that were differentially spliced in early differentiation. These findings provide insight into the role of alternative splicing in adipocyte differentiation and can serve as a resource to guide future variant-to-function studies.

iPSC-derived human β-like cells (BLC) hold promise for both therapy and disease modelling, but their generation remains challenging and their functional analyses beyond transcriptomic and morphological assessments remain limited. Here, we validate an approach using multicellular and single cell electrophysiological tools to evaluate BLCs functions. The Multi-Electrode Arrays (MEAs) measuring the extracellular electrical activity revealed that BLCs are electrically coupled, produce slow potential (SP) signals like primary β-cells that are closely linked to insulin secretion. We also used high-resolution single-cell patch-clamp measurements to capture the exocytotic properties, and characterize voltage-gated sodium and calcium currents. These were comparable to those in primary β and EndoC-βH1 cells. The KATP channel conductance is greater than in human primary β cells which may account for the limited glucose responsiveness observed with MEA. We used MEAs to study the impact of the type 2 diabetes protective SLC30A8 allele (p.Lys34Serfs*50) and found that BLCs with this allele have stronger electrical coupling. Our data suggest that with an adapted approach BLCs from pioneer protocol can be used to evaluate the functional impact of genetic variants on β-cell function and coupling.

Hepatocyte nuclear factor 1α (HNF-1A) is a transcription factor with important gene regulatory roles in pancreatic β-cells. HNF1A gene variants are associated with a monogenic form of diabetes (HNF1A-MODY) or an increased risk for type 2 diabetes. While several pancreatic target genes of HNF-1A have been described, a lack of knowledge regarding the structure-function relationships in HNF-1A prohibits a detailed understanding of HNF-1A-mediated gene transcription, which is important for precision medicine and improved patient care. Therefore, we aimed to characterize the understudied transactivation domain (TAD) of HNF-1A in vitro. We present a bioinformatic approach to dissect the TAD sequence, analyzing protein structure, sequence composition, sequence conservation, and the existence of protein interaction motifs. Moreover, we developed the first protocol for the recombinant expression and purification of the HNF-1A TAD. Small-angle X-ray scattering and synchrotron radiation circular dichroism suggested a disordered conformation for the TAD. Furthermore, we present functional data on HNF-1A undergoing liquid-liquid phase separation, which is in line with in silico predictions and may be of biological relevance for gene transcriptional processes in pancreatic β-cells.

Restoring functional β cell mass is a potential therapy for those with diabetes. However, the pathways regulating β cell mass are not fully understood. Previously, we demonstrated that Sox4 is required for β cell proliferation during prediabetes. Here, we report that Sox4 regulates β cell mass through modulating expression of the type 2 diabetes (T2D) susceptibility gene GRK5. β cell-specific Grk5 knockout mice showed impaired glucose tolerance with reduced β cell mass, which was accompanied by upregulation of cell cycle inhibitor gene Cdkn1a. Furthermore, we found that Grk5 may drive β cell proliferation through a pathway that includes phosphorylation of HDAC5 and subsequent transcription of immediate-early genes (IEGs) such as Nr4a1, Fosb, Junb, Arc, Egr1, and Srf. Together, these studies suggest GRK5 is linked to T2D through regulation of β cell growth and that it may be a target to preserve β cells during the development of T2D.

Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycemia, beta cell glucotoxicity, and ultimately type 2 diabetes (T2D). In this study, we sought to explore the effects of hyperglycemia on human pancreatic islet (HPI) gene expression by exposing HPIs from two donors to low (2.8mM) and high (15.0mM) glucose concentrations over 24 hours, assaying the transcriptome at seven time points using single-cell RNA sequencing (scRNA-seq). We modeled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Across all cell types, we identified 1,528 genes associated with time, 1,185 genes associated with glucose exposure, and 845 genes associated with interaction effects between time and glucose. We clustered differentially expressed genes across cell types and found 347 modules of genes with similar expression patterns across time and glucose conditions, including two beta cell modules enriched in genes associated with T2D. Finally, by integrating genomic features from this study and genetic summary statistics for T2D and related traits, we nominate 363 candidate effector genes that may underlie genetic associations for T2D and related traits.

Genetic studies have identified numerous loci associated with type 2 diabetes (T2D), but the functional role of many loci has remained unexplored. In this study, we engineered isogenic knockout human embryonic stem cell (hESC) lines for 20 genes associated with T2D risk. We systematically examined β-cell differentiation, insulin production and secretion, and survival. We performed RNA-seq and ATAC-seq on hESC-β cells from each knockout line. Analyses of T2D GWAS signals overlapping with HNF4A-dependent ATAC peaks identified a specific SNP as a likely causal variant. In addition, we performed integrative association analyses and identified four genes ( CP, RNASE1, PCSK1N and GSTA2 ) associated with insulin production, and two genes ( TAGLN3 and DHRS2 ) associated with sensitivity to lipotoxicity. Finally, we leveraged deep ATAC-seq read coverage to assess allele-specific imbalance at variants heterozygous in the parental hESC line, to identify a single likely functional variant at each of 23 T2D GWAS signals.

Cellular exposure to free fatty acids (FFAs) is implicated in the pathogenesis of obesity-associated diseases. However, there are no scalable approaches to comprehensively assess the diverse FFAs circulating in human plasma. Furthermore, assessing how FFA-mediated processes interact with genetic risk for disease remains elusive. Here, we report the design and implementation of fatty acid library for comprehensive ontologies (FALCON), an unbiased, scalable, and multimodal interrogation of 61 structurally diverse FFAs. We identified a subset of lipotoxic monounsaturated fatty acids associated with decreased membrane fluidity. Furthermore, we prioritized genes that reflect the combined effects of harmful FFA exposure and genetic risk for type 2 diabetes (T2D). We found that c-MAF-inducing protein (CMIP) protects cells from FFA exposure by modulating Akt signaling. In sum, FALCON empowers the study of fundamental FFA biology and offers an integrative approach to identify much needed targets for diverse diseases associated with disordered FFA metabolism.