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Insulin secretion is critical for glucose homeostasis, and increased levels of the precursor proinsulin relative to insulin indicate pancreatic islet beta-cell stress and insufficient insulin secretory capacity in the setting of insulin resistance. We conducted meta-analyses of genome-wide association results for fasting proinsulin from 16 European-ancestry studies in 45,861 individuals. We found 36 independent signals at 30 loci (p-value < 5x10-8), which validated 12 previously reported loci for proinsulin and 10 additional loci previously identified for another glycemic trait. Half of the alleles associated with higher proinsulin showed higher vs. lower effects on glucose levels, corresponding to different mechanisms. Proinsulin loci included genes that affect prohormone convertases, beta-cell dysfunction, vesicle trafficking, beta-cell transcriptional regulation, and lysosomes/autophagy processes. We colocalized 11 proinsulin signals with islet expression quantitative trait loci (eQTL) data, suggesting candidate genes including ARSG, WIPI1, SLC7A14, and SIX3. The NKX6-3/ANK1 proinsulin signal colocalized with a T2D signal and an adipose ANK1 eQTL signal, but not the islet NKX6-3 eQTL. Signals were enriched for islet enhancers, and we showed a plausible islet regulatory mechanism for the lead signal in the MADD locus. These results show how detailed genetic studies of an intermediate phenotype can elucidate mechanisms predisposing to disease.

BACKGROUND: Self-reported meat consumption is associated with disease risk but objective assessment of different dimensions of this heterogeneous dietary exposure in observational and interventional studies remains challenging. OBJECTIVES: We aimed to derive and validate scores based on plasma metabolites for types of meat consumption. For the most predictive score, we aimed to test whether the included metabolites varied with change in meat consumption, and whether the score was associated with incidence of type 2 diabetes (T2D) and other noncommunicable diseases. METHODS: We derived scores based on 781 plasma metabolites for red meat, processed meat, and poultry consumption assessed with 7-d food records among 11,432 participants in the EPIC-Norfolk (European Prospective Investigation into Cancer and Nutrition-Norfolk) cohort. The scores were then tested for internal validity in an independent subset (n = 853) of the same cohort. In focused analysis on the red meat metabolite score, we examined whether the metabolites constituting the score were also associated with meat intake in a randomized crossover dietary intervention trial of meat (n = 12, Lyon, France). In the EPIC-Norfolk study, we assessed the association of the red meat metabolite score with T2D incidence (n = 1478) and other health endpoints. RESULTS: The best-performing score was for red meat, comprising 139 metabolites which accounted for 17% of the explained variance of red meat consumption in the validation set. In the intervention, 11 top-ranked metabolites in the red meat metabolite score increased significantly after red meat consumption. In the EPIC-Norfolk study, the red meat metabolite score was associated with T2D incidence (adjusted HR per SD: 1.17; 95% CI: 1.10, 1.24). CONCLUSIONS: The red meat metabolite score derived and validated in this study contains metabolites directly derived from meat consumption and is associated with T2D risk. These findings suggest the potential for objective assessment of dietary components and their application for understanding diet-disease associations.The trial in Lyon, France, was registered at clinicaltrials.gov as NCT03354130.

Metabolite levels measured in the human population are endophenotypes for biological processes. We combined sequencing data for 3,924 (whole-exome sequencing, WES, discovery) and 2,805 (whole-genome sequencing, WGS, replication) donors from a prospective cohort of blood donors in England. We used multiple approaches to select and aggregate rare genetic variants (minor allele frequency [MAF] 0.1%) in protein-coding regions and tested their associations with 995 metabolites measured in plasma by using ultra-high-performance liquid chromatography-tandem mass spectrometry. We identified 40 novel associations implicating rare coding variants (27 genes and 38 metabolites), of which 28 (15 genes and 28 metabolites) were replicated. We developed algorithms to prioritize putative driver variants at each locus and used mediation and Mendelian randomization analyses to test directionality at associations of metabolite and protein levels at the ACY1 locus. Overall, 66% of reported associations implicate gene targets of approved drugs or bioactive drug-like compounds, contributing to drug targets' validating efforts.

Type 2 diabetes (T2D) is a heritable metabolic disorder. While population studies have identified hundreds of common genetic variants associated with T2D, the role of rare (frequency < 0.1%) protein-coding variation is less clear. We performed exome sequence analysis in 418,436 (n = 32,374 T2D cases) individuals in the UK Biobank. We identified previously reported genes (GCK, GIGYF1, HNF1A) in addition to missense variants in ZEB2 (n = 31 carriers; odds ratio [OR] = 5.5 [95% confidence interval = 2.5-12.0]; p = 6.4 × 10-7), MLXIPL (n = 245; OR = 2.3 [1.6-3.2]; p = 3.2 × 10-7), and IGF1R (n = 394; OR = 2.4 [1.8-3.2]; p = 1.3 × 10-10). Carriers of damaging missense variants within IGF1R were also shorter (-2.2 cm [-1.8 to -2.7]; p = 1.2 × 10-19) and had higher circulating insulin-like growth factor-1 (IGF-1) protein levels (2.3 nmol/L [1.7-2.9]; p = 2.8 × 10-14), indicating relative IGF-1 resistance. A likely causal role of IGF-1 resistance was supported by Mendelian randomization analyses using common variants. These results increase understanding of the genetic architecture of T2D and highlight the growth hormone/IGF-1 axis as a potential therapeutic target.

Purpose: The study aimed to systematically ascertain male sex chromosome abnormalities, 47,XXY (Klinefelter syndrome [KS]) and 47,XYY, and characterize their risks of adverse health outcomes. Methods: We analyzed genotyping array or exome sequence data in 207,067 men of European ancestry aged 40 to 70 years from the UK Biobank and related these to extensive routine health record data. Results: Only 49 of 213 (23%) of men whom we identified with KS and only 1 of 143 (0.7%) with 47,XYY had a diagnosis of abnormal karyotype on their medical records or self-report. We observed expected associations for KS with reproductive dysfunction (late puberty: risk ratio [RR] = 2.7; childlessness: RR = 4.2; testosterone concentration: RR = -3.8 nmol/L, all P < 2 x 10(-8)), whereas XYY men appeared to have normal reproductive function. Despite this difference, we identified several higher disease risks shared across both KS and 47,XYY, including type 2 diabetes (RR = 3.0 and 2.6, respectively), venous thrombosis (RR = 6.4 and 7.4, respectively), pulmonary embolism (RR = 3.3 and 3.7, respectively), and chronic obstructive pulmonary disease (RR = 4.4 and 4.6, respectively) (all P Conclusion: KS and 47,XYY were mostly unrecognized but conferred substantially higher risks for metabolic, vascular, and respiratory diseases, which were only partially explained by higher levels of body mass index, deprivation, and smoking. (C) 2022 The Authors. Published by Elsevier Inc. on behalf of American College of Medical Genetics and Genomics.

Funder: Department of Health, Funder: Medical Research Council, BackgroundTargeted obesity prevention policies would benefit from the identification of population groups with the highest risk of weight gain. The relative importance of adult age, sex, ethnicity, geographical region, and degree of social deprivation on weight gain is not known. We aimed to identify high-risk groups for changes in weight and BMI using electronic health records (EHR).MethodsIn this longitudinal, population-based cohort study we used linked EHR data from 400 primary care practices (via the Clinical Practice Research Datalink) in England, accessed via the CALIBER programme. Eligible participants were aged 18-74 years, were registered at a general practice clinic, and had BMI and weight measurements recorded between Jan 1, 1998, and June 30, 2016, during the period when they had eligible linked data with at least 1 year of follow-up time. We calculated longitudinal changes in BMI over 1, 5, and 10 years, and investigated the absolute risk and odds ratios (ORs) of transitioning between BMI categories (underweight, normal weight, overweight, obesity class 1 and 2, and severe obesity [class 3]), as defined by WHO. The associations of demographic factors with BMI transitions were estimated by use of logistic regression analysis, adjusting for baseline BMI, family history of cardiovascular disease, use of diuretics, and prevalent chronic conditions.FindingsWe included 2 092 260 eligible individuals with more than 9 million BMI measurements in our study. Young adult age was the strongest risk factor for weight gain at 1, 5, and 10 years of follow-up. Compared with the oldest age group (65-74 years), adults in the youngest age group (18-24 years) had the highest OR (4·22 [95% CI 3·86-4·62]) and greatest absolute risk (37% vs 24%) of transitioning from normal weight to overweight or obesity at 10 years. Likewise, adults in the youngest age group with overweight or obesity at baseline were also at highest risk to transition to a higher BMI category; OR 4·60 (4·06-5·22) and absolute risk (42% vs 18%) of transitioning from overweight to class 1 and 2 obesity, and OR 5·87 (5·23-6·59) and absolute risk (22% vs 5%) of transitioning from class 1 and 2 obesity to class 3 obesity. Other demographic factors were consistently less strongly associated with these transitions; for example, the OR of transitioning from normal weight to overweight or obesity in people living in the most socially deprived versus least deprived areas was 1·23 (1·18-1·27), for men versus women was 1·12 (1·08-1·16), and for Black individuals versus White individuals was 1·13 (1·04-1·24). We provide an open access online risk calculator, and present high-resolution obesity risk charts over a 1-year, 5-year, and 10-year follow-up period.InterpretationA radical shift in policy is required to focus on individuals at the highest risk of weight gain (ie, young adults aged 18-24 years) for individual-level and population-level prevention of obesity and its long-term consequences for health and health care.FundingThe British Hearth Foundation, Health Data Research UK, the UK Medical Research Council, and the National Institute for Health Research.

Summary 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.

SummaryMetabolic dysregulation in multiple tissues alters glucose homeostasis and influences risk for type 2 diabetes (T2D). To identify pathways and tissues influencing T2D-relevant glycemic traits (fasting glucose [FG], fasting insulin [FI], two-hour glucose [2hGlu] and glycated hemoglobin [HbA1c]), we investigated associations of exome-array variants in up to 144,060 individuals without diabetes of multiple ancestries. Single-variant analyses identified novel associations at 21 coding variants in 18 novel loci, whilst gene-based tests revealed signals at two genes, TF (HbA1c) and G6PC (FG, FI). Pathway and tissue enrichment analyses of trait-associated transcripts confirmed the importance of liver and kidney for FI and pancreatic islets for FG regulation, implicated adipose tissue in FI and the gut in 2hGlu, and suggested a role for the non-endocrine pancreas in glucose homeostasis. Functional studies demonstrated that a novel FG/FI association at the liver-enriched G6PC transcript was driven by multiple rare loss-of-function variants. The FG/HbA1c-associated, islet-specific G6PC2 transcript also contained multiple rare functional variants, including two alleles within the same codon with divergent effects on glucose levels. Our findings highlight the value of integrating genomic and functional data to maximize biological inference.Highlights23 novel coding variant associations (single-point and gene-based) for glycemic traits51 effector transcripts highlighted different pathway/tissue signatures for each traitThe exocrine pancreas and gut influence fasting and 2h glucose, respectivelyMultiple variants in liver-enriched G6PC and islet-specific G6PC2 influence glycemia

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin concentrations in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We confirmed five previously established and identified five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The novel missense Val94Met (rs17151919) variant in LEP was common in individuals with African ancestry ( minor allele frequency ( MAF) AFR=8%; MAFEUR=0.02%) and was associated with 0.34 standard deviations lower leptin concentrations per Met94 allele in adults (P=2x10-16, n=3,901). Using in vitro analyses, we showed that the Met94 allele decreases leptin secretion (P=0.025). The Met94 allele was associated with higher BMI in young African-ancestry children (P=0.002, n=2,030) but not in adults, suggesting leptin regulates early adiposity.

Obesity is genetically heterogeneous with monogenic and complex polygenic forms. Using exome sequencing followed by targeted sequencing in 2,737 severely obese cases and 6,704 controls, we identified three genes (PHIP, DGKI, ZMYM4) with an excess burden in cases of variants (MAF

Risk calculation supplemented with physiologic and imaging information is an optimal approach for preventive health management in cost-tolerant demographic groups. However, its application is limited by availability of necessary equipment, patient inconvenience, and cost. We tested whether

Summary Parkinson’s disease (PD) exhibits systemic effects on the human metabolism, with emerging roles for the gut microbiome. Here, we integrate longitudinal metabolome data from 30 drug-naive, de novo PD patients and 30 matched controls with constraint-based modeling of gut microbial communities derived from an independent, drug-naive PD cohort, and prospective data from the general population. Our key results are (1) longitudinal trajectory of metabolites associated with the interconversion of methionine and cysteine via cystathionine differed between PD patients and controls; (2) dopaminergic medication showed strong lipidomic signatures; (3) taurine-conjugated bile acids correlated with the severity of motor symptoms, while low levels of sulfated taurolithocholate were associated with PD incidence in the general population; and (4) computational modeling predicted changes in sulfur metabolism, driven by A. muciniphila and B. wadsworthia, which is consistent with the changed metabolome. The multi-omics integration reveals PD-specific patterns in microbial-host sulfur co-metabolism that may contribute to PD severity., Graphical Abstract, Highlights • Longitudinal metabolomics reveal disturbed transsulfuration in Parkinson’s disease • Metabolic modeling of gut microbiomes show altered microbial sulfur metabolism • Changed microbial sulfur metabolism is linked to B. wadsworthia and A. muciniphila • Taurine-conjugated bile acids are associated with incident Parkinson’s disease, Hertel et al. demonstrate complex alterations in human and microbial sulfur metabolism in Parkinson’s disease by integrating longitudinal metabolomics and computational modeling of gut microbiomes. Then, potential clinical importance is revealed as secondary taurine-conjugated bile acids are shown to be associated with disease severity and Parkinson’s disease incidence.

Summary Background Low circulating concentrations of 25-hydroxyvitamin D (25[OH]D), a marker of vitamin D status, are associated with an increased risk of type 2 diabetes, but whether this association is causal remains unclear. We aimed to estimate the unconfounded, causal association between 25(OH)D concentration and risk of type 2 diabetes using a mendelian randomisation approach. Methods Using several data sources from populations of European descent, including type 2 diabetes cases and non-cases, we did a mendelian randomisation analysis using single nucleotide polymorphisms (SNPs) within or near four genes related to 25(OH)D synthesis and metabolism: DHCR7 (related to vitamin D synthesis), CYP2R1 (hepatic 25-hydroxylation), DBP (also known as GC ; transport), and CYP24A1 (catabolism). We assessed each SNP for an association with circulating 25(OH)D concentration (5449 non-cases; two studies), risk of type 2 diabetes (28 144 cases, 76 344 non-cases; five studies), and glycaemic traits (concentrations of fasting glucose, 2-h glucose, fasting insulin, and HbA 1c ; 46 368 non-cases; study consortium). We combined these associations in a likelihood-based mendelian randomisation analysis to estimate the causal association of 25(OH)D concentration with type 2 diabetes and the glycaemic traits, and compared them with that from a meta-analysis of data from observational studies (8492 cases, 89 698 non-cases; 22 studies) that assessed the association between 25(OH)D concentration and type 2 diabetes. Findings All four SNPs were associated with 25(OH)D concentrations (p −6 ). The mendelian randomisation-derived unconfounded odds ratio for type 2 diabetes was 1·01 (95% CI 0·75–1·36; p=0·94) per 25·0 nmol/L (1 SD) lower 25(OH)D concentration. The corresponding (potentially confounded) relative risk from the meta-analysis of data from observational studies was 1·21 (1·16–1·27; p=7·3 × 10 −19 ). The mendelian randomisation-derived estimates for glycaemic traits were not significant (p>0·25). Interpretation The association between 25(OH)D concentration and type 2 diabetes is unlikely to be causal. Efforts to increase 25(OH)D concentrations might not reduce the risk of type 2 diabetes as would be expected on the basis of observational evidence. These findings warrant further investigations to identify causal factors that might increase 25(OH)D concentration and also reduce the risk of type 2 diabetes. Funding UK Medical Research Council Epidemiology Unit and European Union Sixth Framework Programme.

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 Gα(s)-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.

Objective A large body of epidemiologic data strongly suggests an association between excess adiposity and coronary artery disease (CAD). Low adiponectin levels, a hormone secreted only from adipocytes, have been associated with an increased risk of CAD in observational studies. However, these associations cannot clarify whether this relationship is causal or due to a shared set of causal factors or even confounding. Genome-wide association studies have identified common variants that influence adiponectin levels, providing valuable tools to examine the genetic relationship between adiponectin and CAD. Methods Using 145 genome wide significant SNPs for adiponectin from the ADIPOGen consortium ( n = 49,891), we tested whether adiponectin-decreasing alleles influenced risk of CAD in the CARDIoGRAM consortium ( n = 85,274). Results In single-SNP analysis, 5 variants among 145 SNPs were associated with increased risk of CAD after correcting for multiple testing ( P −4 ). Using a multi-SNP genotypic risk score to test whether adiponectin levels and CAD have a shared genetic etiology, we found that adiponectin-decreasing alleles increased risk of CAD ( P = 5.4 × 10 −7 ). Conclusion These findings demonstrate that adiponectin levels and CAD have a shared allelic architecture and provide rationale to undertake a Mendelian randomization studies to understand if this relationship is causal.

Background Research on complement factor H (fH) in human disease is hampered by lack of an assay suitable for use in large-scale epidemiological studies. We describe the development and validation of a high throughput nephelometric assay for fH. Methods Reagents from a commercial radial immunodiffusion (RID) assay (The Binding Site) were adapted for use on the Siemens BNII high throughput nephelometric instrument. The assay was calibrated with a highly purified human fH preparation with rigorously determined concentration, and assay performance was comprehensively evaluated using samples from healthy human volunteers, with the commercial RID assay as a comparator. The distribution and determinants of circulating fH concentration in humans were then investigated in a large representative population sample. Results The nephelometric assay had recovery close to 100%, was reproducible with intra- and inter-assay CV's of 11% and 5–15% respectively, and had a wider operating range than the RID assay. fH values were unaffected after multiple freeze-thaw cycles demonstrating that it is evidently a stable analyte for immunoassay. fH concentration was unaltered by an acute inflammatory stimulus. The population study showed that plasma fH concentration is associated with circulating lipids and indices of body fat. Conclusion We present the first high throughput assay for circulating fH; the assay is accurate and reliable with reproducible measures from stored samples. It has established the distribution of fH values at a population level and demonstrated important associations with circulating lipids and indices of body fat, thus providing an important reference for future clinical and epidemiological investigations.

Type 2 diabetes is a complex metabolic disorder characterised by varying degrees of impairment in insulin secretion and resistance to the action of insulin. Considerable progress has been made recently in understanding the genetic determinants of diabetes. A logical next step is to describe how these variants relate to the underlying pathophysiological processes that lead to diabetes as this may provide insights into pathways to disease. These quantitative traits are, of course, of direct interest in themselves and a growing literature is now emerging on the genetic determinants of insulin secretion and insulin resistance. This review article focuses on describing the complex associations between type 2 diabetes risk variants and quantitative glycaemic traits and the relationship between variants initially discovered in association studies of these traits and risk of type 2 diabetes.

To examine the sex-specific contributions of the metabolic syndrome and microalbuminuria to cardiovascular disease (CVD) and coronary heart disease (CHD) mortality in community-dwelling older adults, 869 women and 575 men aged 40 to 96 years (mean age 71) completed questionnaires, physical examinations, and fasting laboratory tests between 1992 and 1995. Participants were followed over an average of 8 years. CVD and CHD mortality were analyzed using Cox proportional hazards models. At baseline, 267 participants had the Adult Treatment Panel III metabolic syndrome, 151 had microalbuminuria, and 34 had both. During follow-up, there were 180 CVD deaths, including 83 CHD deaths. In women, microalbuminuria was associated with a twofold increased risk of CVD and CHD mortality (p ≤0.01). Women with both microalbuminuria and the metabolic syndrome (n = 18) had a threefold increased risk of CVD mortality and a fivefold increased risk of CHD mortality compared with women without either (n = 657). A significant interaction existed between microalbuminuria and the metabolic syndrome in the prediction of both CVD and CHD (p = 0.02). In men, neither the combination of the metabolic syndrome and microalbuminuria (n = 16), nor either alone, significantly increased the risk of CVD or CHD mortality. In conclusion, in this cohort, microalbuminuria and the metabolic syndrome together were a more powerful predictor of CVD mortality than either alone in women but not in men. Screening for microalbuminuria in older women may identify women at high risk for CVD mortality beyond that conferred by risk factors included in the metabolic syndrome.

Summary Background The negative effect of birthweight on systolic blood pressure has been suggested to be initiated in utero and amplified with age. We aimed to investigate this hypothesis. Methods A sample of 3634 people from a birth cohort study of men and women born in Britain in 1946 were included in analyses. Cohort members have been contacted regularly since birth, and systolic and diastolic blood pressures were measured at ages 36, 43, and 53 years. Multilevel models, with blood pressure as a repeated outcome, were used to test the amplification hypothesis and to compare results for birthweight with those for childhood social class. Findings Considering both men and women together, a consistent negative association between birthweight and systolic blood pressure was noted from age 36 to 53 years, but no evidence was recorded of substantial amplification with age. A 1 kg higher birthweight was associated with a slower mean increase in systolic blood pressure by −0·4 mm Hg (95% CI −1·3 to 0·4; p=0·3) per 10-year increase in age. Birthweight was not associated with diastolic blood pressure at any age. People from a manual social class in childhood had higher systolic and diastolic blood pressure than did those from a non-manual class. The effect on systolic blood pressure rose with age, by 1·0 mm Hg (95% CI 0·1 to 2·0; p=0·03) per 10 years, but was largely accounted for by current body-mass index, which was an increasingly strong determinant of blood pressure. Interpretation These findings suggest that weight control throughout life is key to prevention of raised blood pressure during middle age. Understanding the link between the early childhood socioeconomic environment and adult obesity could make this strategy more effective.

Introduction L’obesite est un facteur de risque majeur du diabete de type 2 (DT2) mais l’indice de masse corporelle (IMC) varie sensiblement entre les patients DT2. C’est pourquoi, nous avons emis l’hypothese qu’en reduisant cette heterogeneite clinique, nous pourrions identifier de nouveaux variants genetiques associes a la maladie. Materiels et methodes Nous avons realise une etude pangenomique chez des europeens en comparant 2112 DT2 non obeses (IMC 2 ) et 4 123 DT2 obeses (IMC 30 kg/m 2 ) avec 54 412 controles non diabetiques qui n’etaient pas apparies pour l’IMC. Une replication des variants genetiques les plus associes au DT2 a ensuite ete effectuee chez 2 881 DT2 non obeses, 8 702 DT2 obeses et 18 957 controles non diabetiques. Resultats Un nouveau polymorphisme dans le gene LAMA1 etait plus frequent chez les DT2 non obeses que chez les non diabetiques (OR = 1,13 [1,09–1,18], P = 8,4×10-9) alors qu’il etait tres modestement associe au DT2 en comparant les patients obeses et les controles (OR = 1,03 [1,002 – 1,06], P = 0,04). Inversement, un polymorphisme dans le gene HMG20A etait plus frequent chez les DT2 obeses que chez les non diabetiques (OR = 1,11 [1,07–1,15], P = 1,3×10-8) alors que l’association etait tres modeste quand les DT2 non obeses etaient compares aux controles (OR = 1,09 [1,02–1,17], P = 0,015). De plus, nous avons montre que les variants genetiques de 29 des 36 loci valides par des etudes pangenomiques etaient plus associes au DT2 chez les non obeses que chez les obeses (P = 0,0002). Conclusion La prise en compte de l’IMC chez des patients DT2 a permis l’identification de nouveaux loci. L’impact des marqueurs genetiques du DT2 est plus important chez les non obeses que chez les obeses.

Introduction Les etudes GWA ( Genome-wide association studies ) ont identifie et confirme plus de 20 genes de susceptibilite au DT2 et ont contribue a mieux comprendre sa physiopathologie. L'hyperglycemie a jeun (GJ), et 2 heures apres une HGPO (G2h) sont les deux mesures cliniques du diagnostic du DT2. Nous avons identifie recemment la G6P du pancreas ( G6PC2 ) comme determinant de la variabilite physiologique de la GJ puis le recepteur a la melatonine ( MTNR1B ) qui de plus lie la regulation du rythme circadien au DT2. Dans ce travail nous avons etudie la genetique de la G2h a l'aide de l'approche GWA. Resultats Nous avons realisee une meta-analyse GWA dans le cadre de MAGIC ( Meta-Analysis of Glucose and Insulin related traits Consortium ) qui a inclus 9 etudes GWA (N = 15 234). La replication de 29 loci (N = 6 958-30 121, p -5 ) a confirme 5 nouveaux loci ; 2 etant connus comme associes avec le DT2 ( TCF7L2 , p=1,6 ×10 -10 ) et la GJ ( GCKR , p=5,6 ×10 -10 ) ; alors que GIPR (p = 5,2 × 10 -12 ), VSP13C (p = 3,9 × 10 -8 ) et ADCY5 (p = 1,11 × 10 -15 ) sont inedits. GIPR code le recepteur au GIP ( gastric inhibitory polypeptide ) qui est secrete par les cellules intestinales pour stimuler la secretion de l'insuline en reponse au glucose (l'effet incretine). Les porteurs du variant GIPR qui augmente la G2h ont egalement un indice insulinogenique plus bas, (p = 1,0 × 10 -17 ) mais ils ne presentent aucune modification de leur glycemie suite a une hyperglycemie provoquee par voie veineuse (p = 0,21). Ces resultats soutiennent un effet incretine du locus GIPR qui expliquerait ∼9,6 % de la variance total de ce trait. La biologie de ADCY5 et VPS13C et son lien avec l'homeostasie du glucose restent a elucider. GIPR n'est pas associe avec le risque de DT2 indiquant qu'il influence la variabilite physiologique de la G2h alors que le locus ADCY5 est associe avec le DT2 (OR = 1,11, p=1,5 × 10 -15 ). Conclusion Notre etude demontre que l'etude de la G2h est une approche efficace d'une part pour la comprehension de la base genetique de la physiologie de ce trait clinique important et d'autre part pour identifier de nouveaux genes de susceptibilite au DT2.