Type 2 Diabetes Cases Research Articles

Abstract MP29: Ready-to-Eat Food Environment and Risk of Incident Type 2 Diabetes: A Prospective Cohort Study

Introduction: Access to environments providing ready-to-eat food has been linked with a higher prevalence of type 2 diabetes (T2D), however, no study has prospectively assessed the food environment with T2D incidence. Hypothesis: We hypothesized that being exposed to ready-to-eat food environments was prospectively associated with a higher risk of developing T2D. Method: The current study included 480,909 participants free of T2D at baseline from the UK Biobank. Individual food environment variables, including pubs or bars, restaurants or cafeterias, and fast-food outlets, were objectively measured within 1 km catchment areas of the residential street of the participants. A composite food environment variable was created as the sum of the density of all three individual food environment variables. Cox proportional hazard model was used to assess the prospective relationship between the ready-to-eat food environments and incident T2D. Results: During a median of 12 years of follow-up, a total of 28,762 T2D cases were documented. Being exposed to a higher density of ready-to-eat food environments was associated with a higher risk of developing T2D ( Table ): HR = 1.22 (95% CI: 1.16-1.27) for comparing the extreme categories of pubs and bars density; HR=1.05 (95% CI: 1.00-1.10) for restaurants and cafeterias, and HR=1.14 (95% CI: 1.09-1.18) for fast-food outlets. Being exposed to the highest density of a composite food environment was associated with a 26% higher risk of developing T2D (HR=1.26, 95% CI: .1.19-1.33). In addition, we found that the higher T2D risk associated with exposure to ready-to-eat food environments was more pronounced among women than men (p-interaction=0.025). Conclusions: Our results indicate that exposure to ready-to-eat food environments is associated with an increased risk of developing T2D.

Abstract P138: Smoking Timing, Genetic Susceptibility, and Risk of Incident Type 2 Diabetes: A Cohort Study in UK Biobank

Objective: Smoking is an establish risk factor for type 2 diabetes (T2D); however, little is known about how the timing patterns of smoking is related to T2D risk. We prospectively assessed the association of smoking timing with risk of T2D and examined whether smoking amount or genetic susceptibility might modify the relationship. Methods: This study analyzed 294815 participants from the UK Biobank who were free of diabetes at baseline and with complete data on the time from waking to the first cigarette. Cox proportional hazards models were used to evaluate the association between smoking timing and risk of incident T2D. Results: During a median follow-up time of 12 years, a total of 9937 incident cases of T2D were documented among the 294815 participants. Compared to non-smokers, shorter time from waking to the first cigarette was significantly associated with a higher risk of incident T2D ( P for trend <0.0001). The adjusted hazard ratio (aHR) associated with smoking timing was 1.46 (95% confidence interval [CI] 1.17-1.81) for >2 hours, 1.51 (1.21-1.87) for 1-2 hours, 1.58 (1.34-1.85) for 30-60 minutes, 1.86 (1.57-2.21) for 5-15 minutes, and 2.01 (1.60-2.54) for <5 minutes, respectively. We found that even among light smokers, those with the shortest time from waking to the first cigarette had a 105% higher risk of T2D (HR 2.05, 95% CI 1.52-2.76), which was comparable to heavy smokers. The genetic risk score for T2D did not modify this association ( P -interaction =0.51). Conclusions: Our findings indicate that shorter time from waking to the first cigarette is significantly associated with a higher risk of incident T2D, independent of the amount of cigarettes smoked.

Abstract P143: Lignan Intake and Mortality Among Adults With Incident Type 2 Diabetes

Introduction: Lignans are polyphenolic compounds abundant in plant-based foods such as seeds, whole grains, and certain fruits and vegetables and may lead to better metabolic health. It remains elucidated regarding the role of lignan consumption in the etiology of premature deaths among diabetes patients. Hypothesis: We hypothesize that a higher intake of post-diagnosis lignans is associated with lower risk of mortality among individuals with incident type 2 diabetes (T2D). Design: Data from two prospective U.S. cohorts were analyzed, including the Nurses' Health Study (1984-2020) and Health Professionals Follow-up Study (1986-2022). Average daily consumption of total and individual lignans were calculated, and post-diagnosis lignan intakes were cumulatively averaged. Multivariable-adjusted Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between post-diagnosis lignan intake and mortality. Results: Among 8,691 incident T2D cases contributing 119,065 person-years of follow-up, 4,502 deaths were documented, among which 1,379 cases were attributed to cardiovascular disease (CVD) and 777 to cancer. The pooled multivariable-adjusted HRs (95% CIs) of all-cause mortality comparing extreme quintiles of post-diagnosis lignan intake were 0.83 (0.74, 0.94) for total lignans, 0.87 (0.78, 0.96) for matairesinol (MAT), 0.77 (0.69, 0.86) for secoisolariciresinol (SECO), 0.92 (0.82, 1.03) for pinoresinol (PINO), and 0.92 (0.82, 1.03) for lariciresinol (LARIC). Higher post-diagnosis intakes of SECO were also significantly associated with lower CVD and cancer mortality. The HRs (95% CIs) of total mortality comparing extreme quintiles of changes in lignan intake from pre- to post-diagnosis were 0.84 (0.75, 0.93) for total lignans, 0.85 (0.76, 0.94) for MAT, and 0.79 (0.71, 0.89) for SECO. No significant associations were observed for PINO and LARIC. Stratified analyses showed that the associations of lignans were significantly stronger among non-white individuals. Conclusions: In conclusion, among individuals diagnosed with T2D, a higher intake of lignans, particularly SECO, was significantly associated with reduced overall, cardiovascular, and cancer mortality. Minority groups may particularly benefit from lignan intake, although further studies are warranted to substantiate this observation.

Association between Protein Intake and Diabetes Complications Risk Following Incident Type 2 Diabetes: The EPIC-Potsdam Study.

Our knowledge about the connection between protein intake and diabetes-related complications comes largely from studies among those already diagnosed with type 2 diabetes (T2D). However, there is a lack of information on whether changing protein intake after diabetes diagnosis affects complications risk. We aimed to explore the association between protein intake (total, animal, and plant) and vascular complications in incident T2D patients considering pre-diagnosis intake and changes in intake after diagnosis. This prospective cohort study included 1064 participants from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort who developed T2D during follow-up (physician-verified). Dietary protein intake was measured with a food frequency questionnaire at baseline and follow-up. We included physician-reported incident diabetes complications (myocardial infarction, stroke, nephropathy, and neuropathy). A total of 388 participants developed complications, 82 macrovascular complications, and 343 microvascular complications. Substituting carbohydrates with protein showed a trend towards lower complications risk, although this association was not statistically significant (hazard ratio (HR) for 5% energy (E) substitution: 0.83; 95% confidence intervals (CI): 0.60-1.14). Increasing protein intake at the expense of carbohydrates after diabetes diagnosis was not associated with total and microvascular complications (HR for 5% E change substitution: 0.98; 95% CI: 0.89-1.08 and HR for 5% E change substitution: 1.02; 95% CI: 0.92-1.14, respectively). Replacing carbohydrates with protein did not elevate the risk of diabetes complications in incident T2D cases.

Type 2 Diabetes, the Epidemic: Trends in Prevalence and Incidence, 2004-2020.

Only a few studies reported the incidence of type 2 diabetes (T2D). Understanding recent trends in diabetes is vital for planning future diabetes care. This study updated national trends in the prevalence and incidence of type 2 diabetes (T2D) in the Netherlands from 2004-2020. The DIAbetes, MANagement and Treatment (DIAMANT) cohort was used. A cross-sectional design with yearly measurements for the study period was used. The prevalence was calculated by dividing the total number of people with T2D by the total number of all residents. The incidence was calculated by dividing new cases of T2D by the resident population at risk during the calendar year of interest. Among men, the prevalence of T2D in the Netherlands increased from 2.3% in 2004 to 6.3% in 2020. Women's prevalence increased from 2.3% in 2004 to 5.3% in 2020. During 2005-2009, the incidence rate for both men and women was relatively stable Between 2010 and 2020, the incidence rate fell about 1.5 per 1000 in both men and women. From 2004-2020, the prevalence of T2D in the Netherlands more than doubled, with a decreasing incidence from 2010 onwards.

Hidden hunger in patients with type 2 diabetes (T2D) and its effect on glycaemic control: a protocol for systematic review and meta-analysis

IntroductionHidden hunger or micronutrient deficiencies are quite common in many parts of the world, particularly in the countries of sub-Saharan Africa and South Asia. Micronutrient deficiencies may impact insulin signalling...

Community credit scores and community socioeconomic deprivation in association with type 2 diabetes across an urban to rural spectrum in Pennsylvania: a case–control study

BackgroundArea-level credit scores (the mean of credit scores for persons in a community) may be a unique indicator of community-level socioeconomic conditions associated with health outcomes. We analysed community credit...

Linkage and association of rs3110045 and rs28499085 variants in the thyrotropin-releasing hormone receptor (TRHR) gene with the risk of familial type 2 diabetes

Type 2 diabetes (T2D) is a chronic and prevalent multisystemic disease that significantly increases morbidity and mortality. Dysfunction of the thyroid hormone system is common in patients with T2D, increasing their risk of both hyperthyroidism and hypothyroidism. Several components of the thyroid system are candidate risk genes for T2D. The thyrotropin-releasing hormone receptor (TRHR) gene encoding for TRHR is of particular interest since it is expressed by the dorsomedial hypothalamus neurons, which are known to regulate food intake. In humans, a variant in the TRHR gene has been previously reported in T2D patients in a population-based case-control study but not in familial T2D. We recruited 212 multigenerational families with T2D originated from the Italian peninsula with multiple cases of T2D and tested, via Pseudomarker 9 single nucleotide polymorphisms (SNPs) in the TRHR gene for linkage and linkage disequilibrium (i.e., linkage plus association) to/with T2D. We identified 2 novel risk variants (rs3110045 and rs28499085) significantly linked to and associated with the risk of T2D in the Italian families across several inheritance models. Our study is the first to confirm the previously reported association of TRHR gene with T2D and extends the risk to familial inheritance. However, functional and replication studies are still needed to confirm these results.

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10−8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

Maternal smoking, nutritional factors at different life stage, and the risk of incident type 2 diabetes: a prospective study of the UK Biobank

BackgroundThis study aims to investigate potential interactions between maternal smoking around birth (MSAB) and type 2 diabetes (T2D) pathway-specific genetic risks in relation to the development of T2D in offspring. Additionally, it seeks to determine whether and how nutritional factors during different life stages may modify the association between MSAB and risk of T2D.MethodsThis study included 460,234 participants aged 40 to 69 years, who were initially free of T2D from the UK Biobank. MSAB and breastfeeding were collected by questionnaire. The Alternative health eating index(AHEI) and dietary inflammation index(DII) were calculated. The polygenic risk scores(PRS) of T2D and pathway-specific were established, including β-cell function, proinsulin, obesity, lipodystrophy, liver function and glycated haemoglobin(HbA1c). Cox proportion hazards models were performed to evaluate the gene/diet-MSAB interaction on T2D. The relative excess risk due to additive interaction (RERI) were calculated.ResultsDuring a median follow-up period of 12.7 years, we identified 27,342 cases of incident T2D. After adjustment for potential confounders, participants exposed to MSAB had an increased risk of T2D (HR=1.11, 95%CI:1.08-1.14), and this association remained significant among the participants with breastfeeding (HR= HR=1.10, 95%CI: 1.06-1.14). Moreover, among the participants in the highest quartile of AHEI or in the lowest quartile of DII, the association between MSAB and the increased risk of T2D become non-significant (HR=0.94, 95%CI: 0.79-1.13 for AHEI; HR=1.09, 95%CI:0.99-1.20 for DII). Additionally, the association between MSAB and risk of T2D became non-significant among the participants with lower genetic risk of lipodystrophy (HR=1.06, 95%CI:0.99-1.14), and exposed to MSAB with a higher genetic risk for β-cell dysfunction or lipodystrophy additively elevated the risk of T2D(RERI=0.18, 95%CI:0.06-0.30 for β-cell function; RERI=0.16, 95%CI:0.04-0.28 for lipodystrophy).ConclusionsThis study indicates that maintaining a high dietary quality or lower dietary inflammation in diet may reduce the risk of T2D associated with MSAB, and the combination of higher genetic risk of β-cell dysfunction or lipodystrophy and MSAB significantly elevate the risk of T2D in offspring.

Measurement of cumulative high-sensitivity C-reactive protein and monocyte to high-density lipoprotein ratio in the risk prediction of type 2 diabetes: a prospective cohort study

BackgroundConverging data have suggested that monocytic inflammation and C-reactive protein (CRP) are biologically intertwined processes and are involved in diabetogenesis. This study aimed to investigate the association between systemic inflammation assessed by joint cumulative high-sensitivity C-reactive protein (CumCRP) and monocyte to high-density lipoprotein ratio (CumMHR) and incident type 2 diabetes (T2D) and their predictive value for T2D in a general population.MethodsA total of 40,813 nondiabetic participants from a prospective real-life cohort (Kailuan Study, China) were followed biennially from 2010/2011 until December 31, 2020. Multivariable Cox regression analyses were conducted to evaluate the adjusted hazard ratios (aHRs) of incident diabetes.ResultsDuring a median follow-up of 7.98 (IQR: 5.74–8.87) years, 4848 T2D cases developed. CumMHR and CumCRP were alone or jointly associated with incident T2D after adjusting for potential confounders. Elevated CumMHR levels significantly increased the risk of incident diabetes in each CumCRP strata (P-interaction: 0.0278). Participants with concomitant elevations in CumMHR and CumCRP levels had the highest risk (aHR: 1.71, 95% CI 1.52–1.91) compared to both in the low strata. Notably, the coexposure-associated T2D risk was modified by age, sex, hypertension, dyslipidemia, and prediabetes status. C-statistics increased from 0.7377 to 0.7417 when CumMHR and CumCRP were added into the multivariable-adjusted model, with a net reclassification improvement (%) of 12.39 (9.39–15.37) (P < 0.0001).ConclusionsCumulative hsCRP and MHR were both independently and jointly associated with an increased risk of T2D and their addition to established risk factors should improve risk prediction and reclassification of diabetes.

Genetic architecture and biology of youth-onset type 2 diabetes

The prevalence of youth-onset type 2 diabetes (T2D) and childhood obesity has been rising steadily1, producing a growing public health concern1 that disproportionately affects minority groups2. The genetic basis of youth-onset T2D and its relationship to other forms of diabetes are unclear3. Here we report a detailed genetic characterization of youth-onset T2D by analysing exome sequences and common variant associations for 3,005 individuals with youth-onset T2D and 9,777 adult control participants matched for ancestry, including both males and females. We identify monogenic diabetes variants in 2.4% of individuals and three exome-wide significant (P < 2.6 × 10−6) gene-level associations (HNF1A, MC4R, ATXN2L). Furthermore, we report rare variant association enrichments within 25 gene sets related to obesity, monogenic diabetes and β-cell function. Many youth-onset T2D associations are shared with adult-onset T2D, but genetic risk factors of all frequencies—and rare variants in particular—are enriched within youth-onset T2D cases (5.0-fold increase in the rare variant and 3.4-fold increase in common variant genetic liability relative to adult-onset cases). The clinical presentation of participants with youth-onset T2D is influenced in part by the frequency of genetic risk factors within each individual. These findings portray youth-onset T2D as a heterogeneous disease situated on a spectrum between monogenic diabetes and adult-onset T2D.

Adipose tissue-derived metabolite risk scores and risk for type 2 diabetes in South Asians

BackgroundSouth Asians are at higher risk for type 2 diabetes (T2D) than many other race/ethnic groups. Ectopic adiposity, specifically hepatic steatosis and visceral fat may partially explain this. Our objective was to derive metabolite risk scores for ectopic adiposity and assess associations with incident T2D in South Asians.MethodsWe examined 550 participants in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) cohort study aged 40–84 years without known cardiovascular disease or T2D and with metabolomic data. Computed tomography scans at baseline assessed hepatic attenuation and visceral fat area, and fasting serum specimens at baseline and after 5 years assessed T2D. LC-MS-based untargeted metabolomic analysis was performed followed by targeted integration and reporting of known signals. Elastic net regularized linear regression analyses was used to derive risk scores for hepatic steatosis and visceral fat using weighted coefficients. Logistic regression models associated metabolite risk score and incident T2D, adjusting for age, gender, study site, BMI, physical activity, diet quality, energy intake and use of cholesterol-lowering medication.ResultsAverage age of participants was 55 years, 36% women with an average body mass index (BMI) of 25 kg/m2 and 6% prevalence of hepatic steatosis, with 47 cases of incident T2D at 5 years. There were 445 metabolites of known identity. Of these, 313 metabolites were included in the MET-Visc score and 267 in the MET-Liver score. In most fully adjusted models, MET-Liver (OR 2.04 [95% CI 1.38, 3.03]) and MET-Visc (OR 2.80 [1.75, 4.46]) were associated with higher odds of T2D. These associations remained significant after adjustment for measured adiposity.ConclusionsMetabolite risk scores for intrahepatic fat and visceral fat were strongly related to incident T2D independent of measured adiposity. Use of these biomarkers to target risk stratification may help capture pre-clinical metabolic abnormalities.

Nutrient patterns and risk of diabetes mellitus type 2: a case-control study

BackgroundsAlthough the significance of diet in preventing or managing diabetes complications is highlighted in current literature, there is insufficient evidence regarding the correlation between nutrient patterns and these complications. The objective of this case-control study is to investigate this relationship by analyzing the dietary intake of nutrients in participants with and without type 2 diabetes (T2D).MethodsA case-control study was conducted at the Tabriz Center of Metabolism and Endocrinology to investigate the relationship between nutrient patterns and type 2 diabetes (T2D). The study enrolled 225 newly diagnosed cases of T2D and 225 controls. The dietary intake of nutrients was assessed using a validated semi-quantitative food frequency questionnaire (FFQ). Principal component analysis using Varimax rotation was used to obtain nutrient patterns. Logistic regression analysis was performed to estimate the risk of T2D.ResultsThe participants’ mean (SD) age and BMI were 39.8 (8.8) years and 27.8 (3.6) kg/m2, respectively. The results identified three major nutrient patterns. The first nutrient pattern was characterized by high consumption of sucrose, animal protein, vitamin E, vitamin B1, vitamin B12, calcium, phosphorus, zinc, and potassium. The second nutrient pattern included fiber, plant protein, vitamin D, Riboflavin, Vitamin B5, copper, and Magnesium. The third nutrient pattern was characterized by fiber, plant protein, vitamin A, riboflavin, vitamin C, calcium, and potassium. Individuals in the highest tertile of nutrient pattern 3 (NP3) had a lower risk of T2D compared to those in the lowest tertile after adjusting for confounders. The odds ratio was 0.52 with a 95% confidence interval of 0.30–0.89 and a P_trend of 0.039.ConclusionThis study found that conforming to a nutrient pattern consisting of plant protein, vitamin C, vitamin A, vitamin B2, potassium, and calcium is linked to a lower likelihood of developing T2D.The initial results suggest that following a nutrient pattern that includes these nutrients may reduce the risk of T2D. However, further research is required to confirm the relationship between nutrient patterns and T2D.

Assessing the importance of primary care diagnoses in the UK Biobank

The UK Biobank has made general practitioner (GP) data (censoring date 2016–2017) available for approximately 45% of the cohort, whilst hospital inpatient and death registry (referred to as “HES/Death”) data are available cohort-wide through 2018–2022 depending on whether the data comes from England, Wales or Scotland. We assessed the importance of case ascertainment via different data sources in UKB for three diseases that are usually first diagnosed in primary care: Parkinson’s disease (PD), type 2 diabetes (T2D), and all-cause dementia. Including GP data at least doubled the number of incident cases in the subset of the cohort with primary care data (e.g. from 619 to 1390 for dementia). Among the 786 dementia cases that were only captured in the GP data before the GP censoring date, only 421 (54%) were subsequently recorded in HES. Therefore, estimates of the absolute incidence or risk-stratified incidence are misleadingly low when based only on the HES/Death data. For incident cases present in both HES/Death and GP data during the full follow-up period (i.e. until the HES censoring date), the median time difference between an incident diagnosis of dementia being recorded in GP and HES/Death was 2.25 years (i.e. recorded 2.25 years earlier in the GP records). Similar lag periods were also observed for PD (median 2.31 years earlier) and T2D (median 2.82 years earlier). For participants with an incident GP diagnosis, only 65.6% of dementia cases, 69.0% of PD cases, and 58.5% of T2D cases had their diagnosis recorded in HES/Death within 7 years since GP diagnosis. The effect estimates (hazard ratios, HR) of established risk factors for the three health outcomes mostly remain in the same direction and with a similar strength of association when cases are ascertained either using HES only or further adding GP data. The confidence intervals of the HR became narrower when adding GP data, due to the increased statistical power from the additional cases. In conclusion, it is desirable to extend both the coverage and follow-up period of GP data to allow researchers to maximise case ascertainment of chronic health conditions in the UK.

Identifying the key components of social support for patients living with type 2 diabetes: A protocol for a systematic review and meta-analysis of type 2 diabetes social support interventions.

Type 2 diabetes (T2D) is a disease that impacts a huge portion of the world's population. The number of T2D cases is expected to keep rising during the next decade. Committing to the treatment to manage this condition makes participants feel a burden of emotions making them require emotional support from caregivers or close ones. Support from family or caregivers can help improve glycaemia control, medication adherence, and T2D self-management. However, little is known about what aspects of social support effectively improve patients' T2D self-management outcomes. The aim of this systematic review and meta-analysis is to identify the effective components of social support that can help participants improve their T2D self-management. Methods: The protocol of this review was developed based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The PRISMA recommendations were applied to develop a search strategy in collaboration with a team of academics to identify relevant T2D social support interventions via healthcare and psychology databases, Medline, Web of Science, ProQuest, CINHAL. Discussion: This review will provide an overview of what intervention social support components have a significant impact on T2D glycaemia control. These findings will inform future T2D interventions on what social support components could be used to encourage better diabetes self-management and glycemic control.

Type 2 diabetes metabolomics score and risk of progression to type 2 diabetes among women with a history of gestational diabetes mellitus.

Several metabolites are individually related to incident type 2 diabetes (T2D) risk. We prospectively evaluated a novel T2D-metabolite pattern with a risk of progression to T2D among high-risk women with a history of gestational diabetes mellitus (GDM). The longitudinal Nurses' Health Study II cohort enroled 116,429 women in 1989 and collected blood samples from 1996 to 1999. We profiled plasma metabolites in 175 incident T2D cases and 175 age-matched controls, all with a history of GDM before the blood draw. We derived a metabolomics score from 21 metabolites previously associated with incident T2D in the published literature by scoring according to the participants' quintile (1-5 points) of each metabolite. We modelled the T2D metabolomics score categorically in quartiles and continuously per 1 standard deviation (SD) with the risk of incident T2D using conditional logistic regression models adjusting for body mass index at the blood draw, and other established T2D risk factors. The percentage of women progressing to T2D ranged from 10% in the bottom T2D metabolomics score quartile to 78% in the highest score quartile. Adjusting for established T2D risk factors, women in the highest quartile had more than a 20-fold greater diabetes risk than women in the lowest quartile (odds ratios [OR]=23.1 [95% CI=8.6, 62.1]; p for trend<0.001). The continuous T2D metabolomics score was strongly and positively associated with incident T2D (adjusted OR=2.7 per SD [95% CI=1.9, 3.7], p<0.0001). A pattern of plasma metabolites among high-risk women is associated with a markedly elevated risk of progression to T2D later in life.

Predicting cell-type specific disease genes of diabetes with the biological network

Type 2 diabetes (T2D) is a chronic condition that can lead to significant harm, such as heart disease, kidney disease, nerve damage, and blindness. Although T2D-related genes have been identified through Genome-wide association studies (GWAS) and various computational methods, the biological mechanism of T2D at the cell type level remains unclear. Exploring cell type-specific genes related to T2D is essential to understand the cellular mechanisms underlying the disease. To address this issue, we introduce DiGCellNet (predicting Disease Genes with Cell type specificity based on biological Networks), a model that integrates graph convolutional network (GCN) and multi-task learning (MTL) to predict T2D-associated cell type-specific genes based on the biological network. Our work represents the first attempt to predict cell type-specific disease genes using GCN and MTL. We evaluate our approach by predicting genes specific to four cell types and demonstrate that the proposed DiGCellNet outperforms other models that combine node embeddings with traditional machine learning algorithms. Moreover, DiGCellNet successfully identifies CALM1 as a gene specific to beta cell type in T2D cases, and this association is confirmed using an independent dataset. The code is available at https://github.com/23AIBox/23AIBox-DiGCellNet.

Genes with epigenetic alterations in human pancreatic islets impact mitochondrial function, insulin secretion, and type 2 diabetes

Epigenetic dysregulation may influence disease progression. Here we explore whether epigenetic alterations in human pancreatic islets impact insulin secretion and type 2 diabetes (T2D). In islets, 5,584 DNA methylation sites exhibit alterations in T2D cases versus controls and are associated with HbA1c in individuals not diagnosed with T2D. T2D-associated methylation changes are found in enhancers and regions bound by β-cell-specific transcription factors and associated with reduced expression of e.g. CABLES1, FOXP1, GABRA2, GLR1A, RHOT1, and TBC1D4. We find RHOT1 (MIRO1) to be a key regulator of insulin secretion in human islets. Rhot1-deficiency in β-cells leads to reduced insulin secretion, ATP/ADP ratio, mitochondrial mass, Ca2+, and respiration. Regulators of mitochondrial dynamics and metabolites, including L-proline, glycine, GABA, and carnitines, are altered in Rhot1-deficient β-cells. Islets from diabetic GK rats present Rhot1-deficiency. Finally, RHOT1methylation in blood is associated with future T2D. Together, individuals with T2D exhibit epigenetic alterations linked to mitochondrial dysfunction in pancreatic islets.

Sick individuals, sick populations revisited: a test of the Rose hypothesis for type 2 diabetes disparities

IntroductionThe Rose hypothesis predicts that since genetic variation is greater within than between populations, genetic risk factors will be associated with individuals’ risk of disease but not population disparities, and...