Publications by authors named "Isobel D Stewart"

19 Publications

  • Page 1 of 1

The trans-ancestral genomic architecture of glycemic traits.

Nat Genet 2021 06 31;53(6):840-860. Epub 2021 May 31.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
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http://dx.doi.org/10.1038/s41588-021-00852-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610958PMC
June 2021

Plasma metabolites to profile pathways in noncommunicable disease multimorbidity.

Nat Med 2021 03 11;27(3):471-479. Epub 2021 Mar 11.

MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.

Multimorbidity, the simultaneous presence of multiple chronic conditions, is an increasing global health problem and research into its determinants is of high priority. We used baseline untargeted plasma metabolomics profiling covering >1,000 metabolites as a comprehensive readout of human physiology to characterize pathways associated with and across 27 incident noncommunicable diseases (NCDs) assessed using electronic health record hospitalization and cancer registry data from over 11,000 participants (219,415 person years). We identified 420 metabolites shared between at least 2 NCDs, representing 65.5% of all 640 significant metabolite-disease associations. We integrated baseline data on over 50 diverse clinical risk factors and characteristics to identify actionable shared pathways represented by those metabolites. Our study highlights liver and kidney function, lipid and glucose metabolism, low-grade inflammation, surrogates of gut microbial diversity and specific health-related behaviors as antecedents of common NCD multimorbidity with potential for early prevention. We integrated results into an open-access webserver ( https://omicscience.org/apps/mwasdisease/ ) to facilitate future research and meta-analyses.
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http://dx.doi.org/10.1038/s41591-021-01266-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8127079PMC
March 2021

A cross-platform approach identifies genetic regulators of human metabolism and health.

Nat Genet 2021 01 7;53(1):54-64. Epub 2021 Jan 7.

Metabolic Research Laboratories, University of Cambridge, Cambridge, UK.

In cross-platform analyses of 174 metabolites, we identify 499 associations (P < 4.9 × 10) characterized by pleiotropy, allelic heterogeneity, large and nonlinear effects and enrichment for nonsynonymous variation. We identify a signal at GLP2R (p.Asp470Asn) shared among higher citrulline levels, body mass index, fasting glucose-dependent insulinotropic peptide and type 2 diabetes, with β-arrestin signaling as the underlying mechanism. Genetically higher serine levels are shown to reduce the likelihood (by 95%) and predict development of macular telangiectasia type 2, a rare degenerative retinal disease. Integration of genomic and small molecule data across platforms enables the discovery of regulators of human metabolism and translation into clinical insights.
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http://dx.doi.org/10.1038/s41588-020-00751-5DOI Listing
January 2021

Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals.

Nat Genet 2020 12 23;52(12):1314-1332. Epub 2020 Nov 23.

Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.

Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to ~1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency ≤ 0.01) variant BP associations (P < 5 × 10), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were ~8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
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http://dx.doi.org/10.1038/s41588-020-00713-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610439PMC
December 2020

Plasma Vitamin C and Type 2 Diabetes: Genome-Wide Association Study and Mendelian Randomization Analysis in European Populations.

Diabetes Care 2021 Jan 17;44(1):98-106. Epub 2020 Nov 17.

Unit of Nutrition and Cancer, Cancer Epidemiology Research Program and Translational Research Laboratory; Catalan Institute of Oncology - ICO, Group of Research on Nutrition and Cancer, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet of Llobregat, Barcelona, Spain.

Objective: Higher plasma vitamin C levels are associated with lower type 2 diabetes risk, but whether this association is causal is uncertain. To investigate this, we studied the association of genetically predicted plasma vitamin C with type 2 diabetes.

Research Design And Methods: We conducted genome-wide association studies of plasma vitamin C among 52,018 individuals of European ancestry to discover novel genetic variants. We performed Mendelian randomization analyses to estimate the association of genetically predicted differences in plasma vitamin C with type 2 diabetes in up to 80,983 case participants and 842,909 noncase participants. We compared this estimate with the observational association between plasma vitamin C and incident type 2 diabetes, including 8,133 case participants and 11,073 noncase participants.

Results: We identified 11 genomic regions associated with plasma vitamin C ( < 5 × 10), with the strongest signal at , and 10 novel genetic loci including , , , , , , , , , and . Plasma vitamin C was inversely associated with type 2 diabetes (hazard ratio per SD 0.88; 95% CI 0.82, 0.94), but there was no association between genetically predicted plasma vitamin C (excluding variant due to its apparent pleiotropic effect) and type 2 diabetes (1.03; 95% CI 0.96, 1.10).

Conclusions: These findings indicate discordance between biochemically measured and genetically predicted plasma vitamin C levels in the association with type 2 diabetes among European populations. The null Mendelian randomization findings provide no strong evidence to suggest the use of vitamin C supplementation for type 2 diabetes prevention.
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http://dx.doi.org/10.2337/dc20-1328DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7783939PMC
January 2021

Meta-analysis investigating the role of interleukin-6 mediated inflammation in type 2 diabetes.

EBioMedicine 2020 Nov 21;61:103062. Epub 2020 Oct 21.

MRC Epidemiology Unit, University of Cambridge, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrookes Hospital, Cambridge CB2 0QQ, United Kingdom; Regeneron Genetics Center, 777 Old Saw Mill River Rd, Tarrytown, NY 10591, United States.

Background: Evidence from animal models and observational epidemiology points to a role for chronic inflammation, in which interleukin 6 (IL-6) is a key player, in the pathophysiology of type 2 diabetes (T2D). However, it is unknown whether IL-6 mediated inflammation is implicated in the pathophysiology of T2D.

Methods: We performed a meta-analysis of 15 prospective studies to investigate associations between IL-6 levels and incident T2D including 5,421 cases and 31,562 non-cases. We also estimated the association of a loss-of-function missense variant (Asp358Ala) in the IL-6 receptor gene (IL6R), previously shown to mimic the effects of IL-6R inhibition, in a large trans-ethnic meta-analysis of six T2D case-control studies including 260,614 cases and 1,350,640 controls.

Findings: In a meta-analysis of 15 prospective studies, higher levels of IL-6 (per log pg/mL) were significantly associated with a higher risk of incident T2D (1·24 95% CI, 1·17, 1·32; P = 1 × 10). In a trans-ethnic meta-analysis of 260,614 cases and 1,350,640 controls, the IL6R Asp358Ala missense variant was associated with lower odds of T2D (OR, 0·98; 95% CI, 0·97, 0·99; P = 2 × 10). This association was not due to diagnostic misclassification and was consistent across ethnic groups. IL-6 levels mediated up to 5% of the association between higher body mass index and T2D.

Interpretation: Large-scale human prospective and genetic data provide evidence that IL-6 mediated inflammation is implicated in the etiology of T2D but suggest that the impact of this pathway on disease risk in the general population is likely to be small.

Funding: The EPICNorfolk study has received funding from the Medical Research Council (MRC) (MR/N003284/1, MC-UU_12015/1 and MC_PC_13048) and Cancer Research UK (C864/A14136). The Fenland Study is funded by the MRC (MC_UU_12015/1 and MC_PC_13046).
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http://dx.doi.org/10.1016/j.ebiom.2020.103062DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581887PMC
November 2020

The association between circulating 25-hydroxyvitamin D metabolites and type 2 diabetes in European populations: A meta-analysis and Mendelian randomisation analysis.

PLoS Med 2020 10 16;17(10):e1003394. Epub 2020 Oct 16.

Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Background: Prior research suggested a differential association of 25-hydroxyvitamin D (25(OH)D) metabolites with type 2 diabetes (T2D), with total 25(OH)D and 25(OH)D3 inversely associated with T2D, but the epimeric form (C3-epi-25(OH)D3) positively associated with T2D. Whether or not these observational associations are causal remains uncertain. We aimed to examine the potential causality of these associations using Mendelian randomisation (MR) analysis.

Methods And Findings: We performed a meta-analysis of genome-wide association studies for total 25(OH)D (N = 120,618), 25(OH)D3 (N = 40,562), and C3-epi-25(OH)D3 (N = 40,562) in participants of European descent (European Prospective Investigation into Cancer and Nutrition [EPIC]-InterAct study, EPIC-Norfolk study, EPIC-CVD study, Ely study, and the SUNLIGHT consortium). We identified genetic variants for MR analysis to investigate the causal association of the 25(OH)D metabolites with T2D (including 80,983 T2D cases and 842,909 non-cases). We also estimated the observational association of 25(OH)D metabolites with T2D by performing random effects meta-analysis of results from previous studies and results from the EPIC-InterAct study. We identified 10 genetic loci associated with total 25(OH)D, 7 loci associated with 25(OH)D3 and 3 loci associated with C3-epi-25(OH)D3. Based on the meta-analysis of observational studies, each 1-standard deviation (SD) higher level of 25(OH)D was associated with a 20% lower risk of T2D (relative risk [RR]: 0.80; 95% CI 0.77, 0.84; p < 0.001), but a genetically predicted 1-SD increase in 25(OH)D was not significantly associated with T2D (odds ratio [OR]: 0.96; 95% CI 0.89, 1.03; p = 0.23); this result was consistent across sensitivity analyses. In EPIC-InterAct, 25(OH)D3 (per 1-SD) was associated with a lower risk of T2D (RR: 0.81; 95% CI 0.77, 0.86; p < 0.001), while C3-epi-25(OH)D3 (above versus below lower limit of quantification) was positively associated with T2D (RR: 1.12; 95% CI 1.03, 1.22; p = 0.006), but neither 25(OH)D3 (OR: 0.97; 95% CI 0.93, 1.01; p = 0.14) nor C3-epi-25(OH)D3 (OR: 0.98; 95% CI 0.93, 1.04; p = 0.53) was causally associated with T2D risk in the MR analysis. Main limitations include the lack of a non-linear MR analysis and of the generalisability of the current findings from European populations to other populations of different ethnicities.

Conclusions: Our study found discordant associations of biochemically measured and genetically predicted differences in blood 25(OH)D with T2D risk. The findings based on MR analysis in a large sample of European ancestry do not support a causal association of total 25(OH)D or 25(OH)D metabolites with T2D and argue against the use of vitamin D supplementation for the prevention of T2D.
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http://dx.doi.org/10.1371/journal.pmed.1003394DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7567390PMC
October 2020

Integrated Analyses of Microbiome and Longitudinal Metabolome Data Reveal Microbial-Host Interactions on Sulfur Metabolism in Parkinson's Disease.

Cell Rep 2019 11;29(7):1767-1777.e8

School of Medicine, National University of Galway, Galway, Ireland; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Campus Belval, Esch-sur-Alzette, Luxembourg; Division of Microbiology, National University of Galway, Galway, Ireland; APC Microbiome Ireland, Ireland. Electronic address:

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.
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http://dx.doi.org/10.1016/j.celrep.2019.10.035DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856723PMC
November 2019

Epigenome-Wide Association Study of Incident Type 2 Diabetes in a British Population: EPIC-Norfolk Study.

Diabetes 2019 12 10;68(12):2315-2326. Epub 2019 Sep 10.

MRC Epidemiology Unit, Institute of Metabolic Science, School of Clinical Medicine, University of Cambridge, Cambridge, U.K.

Epigenetic changes may contribute substantially to risks of diseases of aging. Previous studies reported seven methylation variable positions (MVPs) robustly associated with incident type 2 diabetes mellitus (T2DM). However, their causal roles in T2DM are unclear. In an incident T2DM case-cohort study nested within the population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk cohort, we used whole blood DNA collected at baseline, up to 11 years before T2DM onset, to investigate the role of methylation in the etiology of T2DM. We identified 15 novel MVPs with robust associations with incident T2DM and robustly confirmed three MVPs identified previously (near to , , and ). All 18 MVPs showed directionally consistent associations with incident and prevalent T2DM in independent studies. Further conditional analyses suggested that the identified epigenetic signals appear related to T2DM via glucose and obesity-related pathways acting before the collection of baseline samples. We integrated genome-wide genetic data to identify methylation-associated quantitative trait loci robustly associated with 16 of the 18 MVPs and found one MVP, cg00574958 at , with a possible direct causal role in T2DM. None of the implicated genes were previously highlighted by genetic association studies, suggesting that DNA methylation studies may reveal novel biological mechanisms involved in tissue responses to glycemia.
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http://dx.doi.org/10.2337/db18-0290DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868468PMC
December 2019

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

Cell 2019 04;177(3):597-607.e9

University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK. Electronic address:

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-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.
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http://dx.doi.org/10.1016/j.cell.2019.03.044DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6476272PMC
April 2019

Assessing the causal association of glycine with risk of cardio-metabolic diseases.

Nat Commun 2019 03 5;10(1):1060. Epub 2019 Mar 5.

MRC Epidemiology Unit, University of Cambridge, Cambridge, CB2 0QQ, UK.

Circulating levels of glycine have previously been associated with lower incidence of coronary heart disease (CHD) and type 2 diabetes (T2D) but it remains uncertain if glycine plays an aetiological role. We present a meta-analysis of genome-wide association studies for glycine in 80,003 participants and investigate the causality and potential mechanisms of the association between glycine and cardio-metabolic diseases using genetic approaches. We identify 27 genetic loci, of which 22 have not previously been reported for glycine. We show that glycine is genetically associated with lower CHD risk and find that this may be partly driven by blood pressure. Evidence for a genetic association of glycine with T2D is weaker, but we find a strong inverse genetic effect of hyperinsulinaemia on glycine. Our findings strengthen evidence for a protective effect of glycine on CHD and show that the glycine-T2D association may be driven by a glycine-lowering effect of insulin resistance.
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http://dx.doi.org/10.1038/s41467-019-08936-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6400990PMC
March 2019

Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies.

Metabolomics 2018 09 20;14(10):128. Epub 2018 Sep 20.

Institute of Computational Biology, Helmholtz-Zentrum München, Neuherberg, Germany.

Background: Untargeted mass spectrometry (MS)-based metabolomics data often contain missing values that reduce statistical power and can introduce bias in biomedical studies. However, a systematic assessment of the various sources of missing values and strategies to handle these data has received little attention. Missing data can occur systematically, e.g. from run day-dependent effects due to limits of detection (LOD); or it can be random as, for instance, a consequence of sample preparation.

Methods: We investigated patterns of missing data in an MS-based metabolomics experiment of serum samples from the German KORA F4 cohort (n = 1750). We then evaluated 31 imputation methods in a simulation framework and biologically validated the results by applying all imputation approaches to real metabolomics data. We examined the ability of each method to reconstruct biochemical pathways from data-driven correlation networks, and the ability of the method to increase statistical power while preserving the strength of established metabolic quantitative trait loci.

Results: Run day-dependent LOD-based missing data accounts for most missing values in the metabolomics dataset. Although multiple imputation by chained equations performed well in many scenarios, it is computationally and statistically challenging. K-nearest neighbors (KNN) imputation on observations with variable pre-selection showed robust performance across all evaluation schemes and is computationally more tractable.

Conclusion: Missing data in untargeted MS-based metabolomics data occur for various reasons. Based on our results, we recommend that KNN-based imputation is performed on observations with variable pre-selection since it showed robust results in all evaluation schemes.
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http://dx.doi.org/10.1007/s11306-018-1420-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6153696PMC
September 2018

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

JAMA 2018 12;320(24):2553-2563

MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.

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.
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http://dx.doi.org/10.1001/jama.2018.19329DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6583513PMC
December 2018

Association of Genetically Enhanced Lipoprotein Lipase-Mediated Lipolysis and Low-Density Lipoprotein Cholesterol-Lowering Alleles With Risk of Coronary Disease and Type 2 Diabetes.

JAMA Cardiol 2018 10;3(10):957-966

MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom.

Importance: Pharmacological enhancers of lipoprotein lipase (LPL) are in preclinical or early clinical development for cardiovascular prevention. Studying whether these agents will reduce cardiovascular events or diabetes risk when added to existing lipid-lowering drugs would require large outcome trials. Human genetics studies can help prioritize or deprioritize these resource-demanding endeavors.

Objective: To investigate the independent and combined associations of genetically determined differences in LPL-mediated lipolysis and low-density lipoprotein cholesterol (LDL-C) metabolism with risk of coronary disease and diabetes.

Design, Setting, And Participants: In this genetic association study, individual-level genetic data from 392 220 participants from 2 population-based cohort studies and 1 case-cohort study conducted in Europe were included. Data were collected from January 1991 to July 2018, and data were analyzed from July 2014 to July 2018.

Exposures: Six conditionally independent triglyceride-lowering alleles in LPL, the p.Glu40Lys variant in ANGPTL4, rare loss-of-function variants in ANGPTL3, and LDL-C-lowering polymorphisms at 58 independent genomic regions, including HMGCR, NPC1L1, and PCSK9.

Main Outcomes And Measures: Odds ratio for coronary artery disease and type 2 diabetes.

Results: Of the 392 220 participants included, 211 915 (54.0%) were female, and the mean (SD) age was 57 (8) years. Triglyceride-lowering alleles in LPL were associated with protection from coronary disease (approximately 40% lower odds per SD of genetically lower triglycerides) and type 2 diabetes (approximately 30% lower odds) in people above or below the median of the population distribution of LDL-C-lowering alleles at 58 independent genomic regions, HMGCR, NPC1L1, or PCSK9. Associations with lower risk were consistent in quintiles of the distribution of LDL-C-lowering alleles and 2 × 2 factorial genetic analyses. The 40Lys variant in ANGPTL4 was associated with protection from coronary disease and type 2 diabetes in groups with genetically higher or lower LDL-C. For a genetic difference of 0.23 SDs in LDL-C, ANGPTL3 loss-of-function variants, which also have beneficial associations with LPL lipolysis, were associated with greater protection against coronary disease than other LDL-C-lowering genetic mechanisms (ANGPTL3 loss-of-function variants: odds ratio, 0.66; 95% CI, 0.52-0.83; 58 LDL-C-lowering variants: odds ratio, 0.90; 95% CI, 0.89-0.91; P for heterogeneity = .009).

Conclusions And Relevance: Triglyceride-lowering alleles in the LPL pathway are associated with lower risk of coronary disease and type 2 diabetes independently of LDL-C-lowering genetic mechanisms. These findings provide human genetics evidence to support the development of agents that enhance LPL-mediated lipolysis for further clinical benefit in addition to LDL-C-lowering therapy.
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http://dx.doi.org/10.1001/jamacardio.2018.2866DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6217943PMC
October 2018

Genetic Predisposition to an Impaired Metabolism of the Branched-Chain Amino Acids and Risk of Type 2 Diabetes: A Mendelian Randomisation Analysis.

PLoS Med 2016 Nov 29;13(11):e1002179. Epub 2016 Nov 29.

MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.

Background: Higher circulating levels of the branched-chain amino acids (BCAAs; i.e., isoleucine, leucine, and valine) are strongly associated with higher type 2 diabetes risk, but it is not known whether this association is causal. We undertook large-scale human genetic analyses to address this question.

Methods And Findings: Genome-wide studies of BCAA levels in 16,596 individuals revealed five genomic regions associated at genome-wide levels of significance (p < 5 × 10-8). The strongest signal was 21 kb upstream of the PPM1K gene (beta in standard deviations [SDs] of leucine per allele = 0.08, p = 3.9 × 10-25), encoding an activator of the mitochondrial branched-chain alpha-ketoacid dehydrogenase (BCKD) responsible for the rate-limiting step in BCAA catabolism. In another analysis, in up to 47,877 cases of type 2 diabetes and 267,694 controls, a genetically predicted difference of 1 SD in amino acid level was associated with an odds ratio for type 2 diabetes of 1.44 (95% CI 1.26-1.65, p = 9.5 × 10-8) for isoleucine, 1.85 (95% CI 1.41-2.42, p = 7.3 × 10-6) for leucine, and 1.54 (95% CI 1.28-1.84, p = 4.2 × 10-6) for valine. Estimates were highly consistent with those from prospective observational studies of the association between BCAA levels and incident type 2 diabetes in a meta-analysis of 1,992 cases and 4,319 non-cases. Metabolome-wide association analyses of BCAA-raising alleles revealed high specificity to the BCAA pathway and an accumulation of metabolites upstream of branched-chain alpha-ketoacid oxidation, consistent with reduced BCKD activity. Limitations of this study are that, while the association of genetic variants appeared highly specific, the possibility of pleiotropic associations cannot be entirely excluded. Similar to other complex phenotypes, genetic scores used in the study captured a limited proportion of the heritability in BCAA levels. Therefore, it is possible that only some of the mechanisms that increase BCAA levels or affect BCAA metabolism are implicated in type 2 diabetes.

Conclusions: Evidence from this large-scale human genetic and metabolomic study is consistent with a causal role of BCAA metabolism in the aetiology of type 2 diabetes.
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http://dx.doi.org/10.1371/journal.pmed.1002179DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5127513PMC
November 2016

Integrative genomic analysis implicates limited peripheral adipose storage capacity in the pathogenesis of human insulin resistance.

Nat Genet 2017 01 14;49(1):17-26. Epub 2016 Nov 14.

MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.

Insulin resistance is a key mediator of obesity-related cardiometabolic disease, yet the mechanisms underlying this link remain obscure. Using an integrative genomic approach, we identify 53 genomic regions associated with insulin resistance phenotypes (higher fasting insulin levels adjusted for BMI, lower HDL cholesterol levels and higher triglyceride levels) and provide evidence that their link with higher cardiometabolic risk is underpinned by an association with lower adipose mass in peripheral compartments. Using these 53 loci, we show a polygenic contribution to familial partial lipodystrophy type 1, a severe form of insulin resistance, and highlight shared molecular mechanisms in common/mild and rare/severe insulin resistance. Population-level genetic analyses combined with experiments in cellular models implicate CCDC92, DNAH10 and L3MBTL3 as previously unrecognized molecules influencing adipocyte differentiation. Our findings support the notion that limited storage capacity of peripheral adipose tissue is an important etiological component in insulin-resistant cardiometabolic disease and highlight genes and mechanisms underpinning this link.
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http://dx.doi.org/10.1038/ng.3714DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5774584PMC
January 2017

Association Between Low-Density Lipoprotein Cholesterol-Lowering Genetic Variants and Risk of Type 2 Diabetes: A Meta-analysis.

JAMA 2016 Oct;316(13):1383-1391

Danish Cancer Society Research Center, Copenhagen, Denmark.

Importance: Low-density lipoprotein cholesterol (LDL-C)-lowering alleles in or near NPC1L1 or HMGCR, encoding the respective molecular targets of ezetimibe and statins, have previously been used as proxies to study the efficacy of these lipid-lowering drugs. Alleles near HMGCR are associated with a higher risk of type 2 diabetes, similar to the increased incidence of new-onset diabetes associated with statin treatment in randomized clinical trials. It is unknown whether alleles near NPC1L1 are associated with the risk of type 2 diabetes.

Objective: To investigate whether LDL-C-lowering alleles in or near NPC1L1 and other genes encoding current or prospective molecular targets of lipid-lowering therapy (ie, HMGCR, PCSK9, ABCG5/G8, LDLR) are associated with the risk of type 2 diabetes.

Design, Setting, And Participants: The associations with type 2 diabetes and coronary artery disease of LDL-C-lowering genetic variants were investigated in meta-analyses of genetic association studies. Meta-analyses included 50 775 individuals with type 2 diabetes and 270 269 controls and 60 801 individuals with coronary artery disease and 123 504 controls. Data collection took place in Europe and the United States between 1991 and 2016.

Exposures: Low-density lipoprotein cholesterol-lowering alleles in or near NPC1L1, HMGCR, PCSK9, ABCG5/G8, and LDLR.

Main Outcomes And Measures: Odds ratios (ORs) for type 2 diabetes and coronary artery disease.

Results: Low-density lipoprotein cholesterol-lowering genetic variants at NPC1L1 were inversely associated with coronary artery disease (OR for a genetically predicted 1-mmol/L [38.7-mg/dL] reduction in LDL-C of 0.61 [95% CI, 0.42-0.88]; P = .008) and directly associated with type 2 diabetes (OR for a genetically predicted 1-mmol/L reduction in LDL-C of 2.42 [95% CI, 1.70-3.43]; P < .001). For PCSK9 genetic variants, the OR for type 2 diabetes per 1-mmol/L genetically predicted reduction in LDL-C was 1.19 (95% CI, 1.02-1.38; P = .03). For a given reduction in LDL-C, genetic variants were associated with a similar reduction in coronary artery disease risk (I2 = 0% for heterogeneity in genetic associations; P = .93). However, associations with type 2 diabetes were heterogeneous (I2 = 77.2%; P = .002), indicating gene-specific associations with metabolic risk of LDL-C-lowering alleles.

Conclusions And Relevance: In this meta-analysis, exposure to LDL-C-lowering genetic variants in or near NPC1L1 and other genes was associated with a higher risk of type 2 diabetes. These data provide insights into potential adverse effects of LDL-C-lowering therapy.
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http://dx.doi.org/10.1001/jama.2016.14568DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5386134PMC
October 2016