Genomic insights into the causes of type 2 diabetes.

Genome-wide association studies have implicated around 250 genomic regions in predisposition to type 2 diabetes, with evidence for causal variants and genes emerging for several of these regions. Understanding of the underlying mechanisms, including the interplay between β-cell failure, insulin sensitivity, appetite regulation, and adipose storage has been facilitated by the integration of multidimensional data for diabetes-related intermediate phenotypes, detailed genomic annotations, functional experiments, and now multiomic molecular features. Studies in diverse ethnic groups and examples from population isolates have shown the value and need for a broad genomic approach to this global disease. Transethnic discovery efforts and large-scale biobanks in diverse populations and ancestries could help to address some of the Eurocentric bias. Despite rapid progress in the discovery of the highly polygenic architecture of type 2 diabetes, dominated by common alleles with small, cumulative effects on disease risk, these insights have been of little clinical use in terms of disease prediction or prevention, and have made only small contributions to subtype classification or stratified approaches to treatment. Successful development of academia-industry partnerships for exome or genome sequencing in large biobanks could help to deliver economies of scale, with implications for the future of genomics-focused research

Prioritising Risk Factors for Type 2 Diabetes: Causal Inference through Genetic Approaches.

PURPOSE OF THE REVIEW: Causality has been demonstrated for few of the many putative risk factors for type 2 diabetes (T2D) emerging from observational epidemiology. Genetic approaches are increasingly being used to infer causality, and in this review, we discuss how genetic discoveries have shaped our understanding of the causal role of factors associated with T2D. RECENT FINDINGS: Genetic discoveries have led to the identification of novel potential aetiological factors of T2D, including the protective role of peripheral fat storage capacity and specific metabolic pathways, such as the branched-chain amino acid breakdown. Consideration of specific genetic mechanisms contributing to overall lipid levels has suggested that distinct physiological processes influencing lipid levels may influence diabetes risk differentially. Genetic approaches have also been used to investigate the role of T2D and related metabolic traits as causal risk factors for other disease outcomes, such as cancer, but comprehensive studies are lacking. Genome-wide association studies of T2D and metabolic traits coupled with high-throughput molecular phenotyping and in-depth characterisation and follow-up of individual loci have provided better understanding of aetiological factors contributing to T2D

Genome-wide association study of adipocyte lipolysis in the GENetics of Adipocyte Lipolysis (GENiAL) cohort

Objectives: Lipolysis, hydrolysis of triglycerides to fatty acids in adipocytes, is tightly regulated, poorly understood, and, if perturbed, can lead to metabolic diseases including obesity and type 2 diabetes. The goal of this study was to identify the genetic regulators of lipolysis and elucidate their molecular mechanisms. Methods: Adipocytes from abdominal subcutaneous adipose tissue biopsies were isolated and were incubated without (spontaneous lipolysis) or with a catecholamine (stimulated lipolysis) to analyze lipolysis. DNA was extracted and genome-wide genotyping and imputation conducted. After quality control, 939 samples with genetic and lipolysis data were available. Genome-wide association studies of spontaneous and stimulated lipolysis were conducted. Subsequent in vitro gene expression analyses were used to identify candidate genes and explore their regulation of adipose tissue biology. Results: One locus on chromosome 19 demonstrated genome-wide significance with spontaneous lipolysis. 60 loci showed suggestive associations with spontaneous or stimulated lipolysis, of which many influenced both traits. In the chromosome 19 locus, only HIF3A was expressed in the adipocytes and displayed genotype-dependent gene expression. HIF3A knockdown in vitro increased lipolysis and the expression of key lipolysis-regulating genes. Conclusions: In conclusion, we identified a genetic regulator of spontaneous lipolysis and provided evidence of HIF3A as a novel key regulator of lipolysis in subcutaneous adipocytes as the mechanism through which the locus influences adipose tissue biology

Definitions of Metabolic Health and Risk of Future Type 2 Diabetes in BMI Categories: A Systematic Review and Network Meta-analysis.

OBJECTIVE: Various definitions of metabolic health have been proposed to explain differences in the risk of type 2 diabetes within BMI categories. The goal of this study was to assess their predictive relevance. RESEARCH DESIGN AND METHODS: We performed systematic searches of MEDLINE records for prospective cohort studies of type 2 diabetes risk in categories of BMI and metabolic health. In a two-stage meta-analysis, relative risks (RRs) specific to each BMI category were derived by network meta-analysis and the resulting RRs of each study were pooled using random-effects models. Hierarchical summary receiver operating characteristic curves were used to assess predictive performance. RESULTS: In a meta-analysis of 140,845 participants and 5,963 incident cases of type 2 diabetes from 14 cohort studies, classification as metabolically unhealthy was associated with higher RR of diabetes in all BMI categories (lean RR compared with healthy individuals 4.0 [95% CI 3.0-5.1], overweight 3.4 [2.8-4.3], and obese 2.5 [2.1-3.0]). Metabolically healthy obese individuals had a high absolute risk of type 2 diabetes (10-year cumulative incidence 3.1% [95% CI 2.6-3.5]). Current binary definitions of metabolic health had high specificity (pooled estimate 0.88 [95% CI 0.84-0.91]) but low sensitivity (0.40 [0.31-0.49]) in lean individuals and satisfactory sensitivity (0.81 [0.76-0.86]) but low specificity (0.42 [0.35-0.49]) in obese individuals. However, positive (0.4) likelihood ratios were consistent with insignificant to small improvements in prediction. CONCLUSIONS: Although individuals classified as metabolically unhealthy have a higher RR of type 2 diabetes compared with individuals classified as healthy in all BMI categories, current binary definitions of metabolic health have limited relevance to the prediction of future type 2 diabetes.The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement n° 115372, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution. This work was supported by the Netherlands Organization for Scientific Research (NWO), and the Medical Research Council UK (grant no. MC_U106179471). A.A. is supported by a Rubicon grant from the NWO (Project no. 825.13.004).This is an author-created, uncopyedited electronic version of an article accepted for publication in Diabetes Care. The American Diabetes Care Association (ADA), publisher of Diabetes Care, is not responsible for any errors or omissions in this version of the manuscript or any version derived from it by third parties. The definitive publisher-authenticated version will be available in a future issue of Diabetes Care in print and online at http://care.diabetesjournals.org

Genome-wide association study of adipocyte lipolysis in the GENetics of adipocyte lipolysis (GENiAL) cohort.

OBJECTIVES:Lipolysis, hydrolysis of triglycerides to fatty acids in adipocytes, is tightly regulated, poorly understood, and, if perturbed, can lead to metabolic diseases including obesity and type 2 diabetes. The goal of this study was to identify the genetic regulators of lipolysis and elucidate their molecular mechanisms. METHODS:Adipocytes from abdominal subcutaneous adipose tissue biopsies were isolated and were incubated without (spontaneous lipolysis) or with a catecholamine (stimulated lipolysis) to analyze lipolysis. DNA was extracted and genome-wide genotyping and imputation conducted. After quality control, 939 samples with genetic and lipolysis data were available. Genome-wide association studies of spontaneous and stimulated lipolysis were conducted. Subsequent in vitro gene expression analyses were used to identify candidate genes and explore their regulation of adipose tissue biology. RESULTS:One locus on chromosome 19 demonstrated genome-wide significance with spontaneous lipolysis. 60 loci showed suggestive associations with spontaneous or stimulated lipolysis, of which many influenced both traits. In the chromosome 19 locus, only HIF3A was expressed in the adipocytes and displayed genotype-dependent gene expression. HIF3A knockdown in vitro increased lipolysis and the expression of key lipolysis-regulating genes. CONCLUSIONS:In conclusion, we identified a genetic regulator of spontaneous lipolysis and provided evidence of HIF3A as a novel key regulator of lipolysis in subcutaneous adipocytes as the mechanism through which the locus influences adipose tissue biology

Elevated Plasma Levels of 3-Hydroxyisobutyric Acid Are Associated With Incident Type 2 Diabetes.

Branched-chain amino acids (BCAAs) metabolite, 3-Hydroxyisobutyric acid (3-HIB) has been identified as a secreted mediator of endothelial cell fatty acid transport and insulin resistance (IR) using animal models. To identify if 3-HIB is a marker of human IR and future risk of developing Type 2 diabetes (T2D), we measured plasma levels of 3-HIB and associated metabolites in around 10,000 extensively phenotyped individuals. The levels of 3-HIB were increased in obesity but not robustly associated with degree of IR after adjusting for BMI. Nevertheless, also after adjusting for obesity and plasma BCAA, 3-HIB levels were associated with future risk of incident T2D. We also examined the effect of 3-HIB on fatty acid uptake in human cells and found that both HUVEC and human cardiac endothelial cells respond to 3-HIB whereas human adipose tissue-derived endothelial cells do not respond to 3-HIB. In conclusion, we found that increased plasma level of 3-HIB is a marker of future risk of T2D and 3-HIB may be important for the regulation of metabolic flexibility in heart and muscles

Functional Screening of Candidate Causal Genes for Insulin Resistance in Human Preadipocytes and Adipocytes.

Rationale: Genome-wide association studies have identified genetic loci associated with insulin resistance (IR) but pinpointing the causal genes of a risk locus has been challenging. Objective: To identify candidate causal genes for IR, we screened regional and biologically plausible genes (16 in total) near the top 10 IR-loci in risk-relevant cell types, namely preadipocytes and adipocytes. Methods and Results: We generated 16 human Simpson-Golabi-Behmel syndrome preadipocyte knockout lines each with a single IR-gene knocked out by lentivirus-mediated CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 system. We evaluated each gene knockout by screening IR-relevant phenotypes in the 3 insulin-sensitizing mechanisms, including adipogenesis, lipid metabolism, and insulin signaling. We performed genetic analyses using data on the genotype-tissue expression portal expression quantitative trait loci database and accelerating medicines partnership type 2 diabetes mellitus Knowledge Portal to evaluate whether candidate genes prioritized by our in vitro studies were expression quantitative trait loci genes in human subcutaneous adipose tissue, and whether expression of these genes is associated with risk of IR, type 2 diabetes mellitus, and cardiovascular diseases. We further validated the functions of 3 new adipose IR genes by overexpression-based phenotypic rescue in the Simpson-Golabi-Behmel syndrome preadipocyte knockout lines. Twelve genes, PPARG, IRS-1, FST, PEPD, PDGFC, MAP3K1, GRB14, ARL15, ANKRD55, RSPO3, COBLL1, and LYPLAL1, showed diverse phenotypes in the 3 insulin-sensitizing mechanisms, and the first 7 of these genes could affect all the 3 mechanisms. Five out of 6 expression quantitative trait loci genes are among the top candidate causal genes and the abnormal expression levels of these genes (IRS-1, GRB14, FST, PEPD, and PDGFC) in human subcutaneous adipose tissue could be associated with increased risk of IR, type 2 diabetes mellitus, and cardiovascular disease. Phenotypic rescue by overexpression of the candidate causal genes (FST, PEPD, and PDGFC) in the Simpson-Golabi-Behmel syndrome preadipocyte knockout lines confirmed their function in adipose IR. Conclusions: Twelve genes showed diverse phenotypes indicating differential roles in insulin sensitization, suggesting mechanisms bridging the association of their genomic loci with IR. We prioritized PPARG, IRS-1, GRB14, MAP3K1, FST, PEPD, and PDGFC as top candidate genes. Our work points to novel roles for FST, PEPD, and PDGFC in adipose tissue, with consequences for cardiometabolic diseases

Association of Genetic Variants Related to Gluteofemoral vs Abdominal Fat Distribution With Type 2 Diabetes, Coronary Disease, and Cardiovascular Risk Factors.

IMPORTANCE: Body fat distribution, usually measured using waist-to-hip ratio (WHR), is an important contributor to cardiometabolic disease independent of body mass index (BMI). Whether mechanisms that increase WHR via lower gluteofemoral (hip) or via higher abdominal (waist) fat distribution affect cardiometabolic risk is unknown. OBJECTIVE: To identify genetic variants associated with higher WHR specifically via lower gluteofemoral or higher abdominal fat distribution and estimate their association with cardiometabolic risk. DESIGN, SETTING, AND PARTICIPANTS: Genome-wide association studies (GWAS) for WHR combined data from the UK Biobank cohort and summary statistics from previous GWAS (data collection: 2006-2018). Specific polygenic scores for higher WHR via lower gluteofemoral or via higher abdominal fat distribution were derived using WHR-associated genetic variants showing specific association with hip or waist circumference. Associations of polygenic scores with outcomes were estimated in 3 population-based cohorts, a case-cohort study, and summary statistics from 6 GWAS (data collection: 1991-2018). EXPOSURES: More than 2.4 million common genetic variants (GWAS); polygenic scores for higher WHR (follow-up analyses). MAIN OUTCOMES AND MEASURES: BMI-adjusted WHR and unadjusted WHR (GWAS); compartmental fat mass measured by dual-energy x-ray absorptiometry, systolic and diastolic blood pressure, low-density lipoprotein cholesterol, triglycerides, fasting glucose, fasting insulin, type 2 diabetes, and coronary disease risk (follow-up analyses). RESULTS: Among 452 302 UK Biobank participants of European ancestry, the mean (SD) age was 57 (8) years and the mean (SD) WHR was 0.87 (0.09). In genome-wide analyses, 202 independent genetic variants were associated with higher BMI-adjusted WHR (n = 660 648) and unadjusted WHR (n = 663 598). In dual-energy x-ray absorptiometry analyses (n = 18 330), the hip- and waist-specific polygenic scores for higher WHR were specifically associated with lower gluteofemoral and higher abdominal fat, respectively. In follow-up analyses (n = 636 607), both polygenic scores were associated with higher blood pressure and triglyceride levels and higher risk of diabetes (waist-specific score: odds ratio [OR], 1.57 [95% CI, 1.34-1.83], absolute risk increase per 1000 participant-years [ARI], 4.4 [95% CI, 2.7-6.5], P < .001; hip-specific score: OR, 2.54 [95% CI, 2.17-2.96], ARI, 12.0 [95% CI, 9.1-15.3], P < .001) and coronary disease (waist-specific score: OR, 1.60 [95% CI, 1.39-1.84], ARI, 2.3 [95% CI, 1.5-3.3], P < .001; hip-specific score: OR, 1.76 [95% CI, 1.53-2.02], ARI, 3.0 [95% CI, 2.1-4.0], P < .001), per 1-SD increase in BMI-adjusted WHR. CONCLUSIONS AND RELEVANCE: Distinct genetic mechanisms may be linked to gluteofemoral and abdominal fat distribution that are the basis for the calculation of the WHR. These findings may improve risk assessment and treatment of diabetes and coronary disease.This study was funded by the United Kingdom’s Medical Research Council through grants MC_UU_12015/1, MC_PC_13046, MC_PC_13048 and MR/L00002/1. This work was supported by the MRC Metabolic Diseases Unit (MC_UU_12012/5) and the Cambridge NIHR Biomedical Research Centre and EU/EFPIA Innovative Medicines Initiative Joint Undertaking (EMIF grant: 115372). EPIC-InterAct Study funding: funding for the InterAct project was provided by the EU FP6 program (grant number LSHM_CT_2006_037197). D.B.S. and S.O’R. are supported by the Wellcome Trust (WT107064 and WT095515 respectively) the MRC Metabolic Disease Unit, the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre and the NIHR Rare Disease Translational Research Collaboration

Human Gain-of-Function MC4R Variants Show Signaling Bias and Protect against Obesity.

The melanocortin 4 receptor (MC4R) is a G protein-coupled receptor whose disruption causes obesity. We functionally characterized 61 MC4R variants identified in 0.5 million people from UK Biobank and examined their associations with body mass index (BMI) and obesity-related cardiometabolic diseases. We found that the maximal efficacy of β-arrestin recruitment to MC4R, rather than canonical Gαs-mediated cyclic adenosine-monophosphate production, explained 88% of the variance in the association of MC4R variants with BMI. While most MC4R variants caused loss of function, a subset caused gain of function; these variants were associated with significantly lower BMI and lower odds of obesity, type 2 diabetes, and coronary artery disease. Protective associations were driven by MC4R variants exhibiting signaling bias toward β-arrestin recruitment and increased mitogen-activated protein kinase pathway activation. Harnessing β-arrestin-biased MC4R signaling may represent an effective strategy for weight loss and the treatment of obesity-related cardiometabolic diseases

Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study.

BACKGROUND: Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR). METHODS AND FINDINGS: We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, NSNPs = 49), fasting glucose (NSNPs = 36), insulin resistance (NSNPs = 10), body mass index (BMI, NSNPs = 32), total cholesterol (NSNPs = 73), HDL-cholesterol (NSNPs = 71), LDL-cholesterol (NSNPs = 57), triglycerides (NSNPs = 39), systolic blood pressure (SBP, NSNPs = 24), smoking initiation (NSNPs = 1), smoking quantity (NSNPs = 3), university completion (NSNPs = 2), and years of education (NSNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP-AD associations from the International Genomics of Alzheimer's Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62-0.91]; p = 3.4 × 10(-3)). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10(-8)). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51-0.89]; p = 6.5 × 10(-3)), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses. CONCLUSIONS: Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure--or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications--may reduce AD risk.We thank the International Genomics of Alzheimer's Project (IGAP) for providing summary results data for these analyses. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients, and their families. The i–Select chips were funded by the French National Foundation on Alzheimer's disease and related disorders. EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical Research Council (Grant n° 503480), Alzheimer's Research UK (Grant n° 503176), the Wellcome Trust (Grant n° 082604/2/07/Z) and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant n° 01GI0102, 01GI0711, 01GI0420. CHARGE was partly supported by the NIH/NIA grant R01 AG033193 and the NIA AG081220 and AGES contract N01–AG–12100, the NHLBI grant R01 HL105756, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer's Association grant ADGC–10–196728.This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pmed.100184