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We investigate the extent to which human genetic data are incorporated into studies that hypothesize novel links between genes and metabolic disease. To lower the barriers to using genetic data, we present an approach to enable researchers to evaluate human genetic support for experimentally determined hypotheses.

Background: There is limited information on how polygenic scores (PSs) — based on variants from genome-wide association studies (GWAS) of T2D — add to clinical variables in predicting T2D incidence. Methods: For participants in a longitudinal study in an Indigenous population from the Southwest United States (US) with high T2D prevalence, we analyzed 10 constructions of PS using publicly available GWAS summary statistics. T2D incidence was examined in three cohorts of individuals without T2D at baseline. The adult cohort, comprised of 2333 participants followed from age≥20y, had 640 T2D cases. The youth cohort was comprised of 2229 participants followed from age 5-19y (228 cases). The birth cohort was comprised of 2894 participants followed from birth (438 cases). We assessed contributions of the PS and clinical variables in predicting T2D incidence. Results: Of the 10 PS constructions, a PS using 293 genome-wide significant variants from a large T2D GWAS meta-analysis in European-ancestry populations performed best. In the adult cohort, area under the receiver operating characteristic curve (AUC) for clinical variables for prediction of T2D incidence was 0·728; with the PS, 0·735. The PS’s hazard ratio (HR) was 1.27 per SD (p=1·6×10-8; 95% CI 1·17-1·38). In the youth cohort, the analogous model’s AUC was 0·805; with the PS, 0·812. The PS’s HR was 1·49 (p=4·3×10-8; 95% CI 1·29-1·72). In the birth cohort, AUC for the clinical variables was 0·614; with the PS, 0·685. The PS’s HR was 1·48 (p=2·8×10-16; 95% CI 1·35-1·63). To further assess the potential impact of including PS for assessing individual T2D risk, the net reclassification improvement (NRI) was calculated: NRI for the PS was 0·264, 0·249, and 0·309 for adult, youth, and birth cohorts, respectively. For comparison, NRI for HbA1c was 0·292 and 0·150 for adult and youth cohorts, respectively. Across all cohorts, as estimated using decision curve analyses, the net benefit of including the PS in addition to clinical variables was most pronounced at moderately stringent threshold probability (pt) values for instituting a preventive intervention. Discussion: This study demonstrates that the PS contributes significantly to prediction of T2D incidence in addition to the information provided by clinical factors; however, overall improvement of the prediction model was modest. Discriminatory power of the PS for predicting incident T2D was similar to that of other commonly measured clinical factors (e.g. HbA1c). Including T2D PS in addition to clinical factors may be clinically beneficial for identifying individuals at higher risk for T2D, especially at younger ages. Funding Statement: This study used computational resources of the Biowulf system at the National Institutes of Health (NIH), Bethesda, MD. The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Intramural Research Program provided support for NIDDK-based coauthors. The NIH Oxford-Cambridge Scholars Program provided funding support for L.E.W.’s doctoral programme. M.I.M. was a Wellcome Senior Investigator and an NIHR Senior Investigator. This work was funded in Oxford by the Wellcome Trust (098381, 106130, 203141), NIH (U01- DK105535; U01-DK085545) and National Institute for Health Research (NIHR) (NF-SI-0617- 10090) and Oxford Biomedical Research Centre (BRC). Declaration of Interests: The views expressed in this article are those of the author(s) and not necessarily those of NIH, NHS, NIHR, or UK Department of Health. M.I.M. has served on advisory panels for Pfizer, Novo Nordisk, and Zoe Global; has received honoraria from Merck, Pfizer, Novo Nordisk, and Eli Lilly; and research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier, and Takeda. As of June 2019, M.I.M. and A.M. are employees of Genentech and holders of Roche stock. Ethics Approval Statement: Protocols were approved by the institutional review board of the National Institute of Diabetes and Digestive and Kidney Diseases.

Summary The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments., Graphical abstract, Highlights • Soft clustering based on 32 phenotypes identified 4 quantitative archetypes • These reflect different patterns of dysfunction across T2D etiological processes • The four archetypes are different in disease progression, GRSs, and omics signals • Some patients are dominated by one archetype, but many have etiological combinations, Wesolowska-Andersen et al. represent the clinical heterogeneity of newly diagnosed T2D as four quantitative archetype profiles reflecting patterns of dysfunction in disease etiological processes, rather than clustering individuals into categorical subgroups as attempted by others. The archetype profiles differ in genetic risk scores, disease progression, and circulating omics biomarkers.

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.

Objective Relationship of high sensitivity C-reactive protein (hsCRP) with Metabolic Syndrome (MetS) is well documented in many populations, but comprehensive data is lacking in Indian population. Thus, we set out to investigate the association of hsCRP levels with MetS and its features and the effect of obesity and insulin resistance on this association in urban Indians. Methods This is a cross-sectional study that included 9517 subjects comprising 4066 subjects with MetS. MetS was defined according to the modified National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP III) criteria for Asians. Results Median levels of hsCRP were considerably higher in individuals with MetS with higher levels in women compared to men. Among the features of MetS, waist circumference was most strongly correlated with hsCRP levels ( r =0.28) and contributed maximally ( β =0.025mg/l lnhsCRP, P =7.4×10 −147 ). Subjects with high risk hsCRP levels (>3mg/l) were at high risk of MetS (OR (95% CI)=1.65(1.41–1.92), P =1.7×10 −10 ). Risk of MetS increased in a dose dependent manner from low risk to high risk hsCRP category with increase in BMI and HOMA-IR. Conclusions Our findings suggest that hsCRP predicts the risk of MetS, independent of obesity and insulin resistance, and therefore, can be a valuable tool to aid the identification of individuals at risk of MetS. The study provides a lead for future investigation for effects of hsCRP, obesity, and insulin resistance on MetS in this population.

Molecular epidemiology studies have used the counts of different mutational types like transitions, transversions, etc. to identify putative mutagens, with little reference to gene organization and structure-function of the translated product. Moreover, geographical variation in the mutational spectrum is not limited to the mutational types at the nucleotide level but also have a bearing at the functional level. Here, we developed a novel measure to estimate the rate of spontaneous detrimental mutations called "mutation index" for comparing the mutational spectra consisting of all single base, missense, and non-missense changes. We have analyzed 1609 mutations occurring in 38 exons in 24 populations in three diseases viz. hemophilia B (F9 gene - 420 mutations in 9 populations across 8 exons), hemophilia A (F8 gene - 650, 8 and 26, respectively) and ovarian carcinoma (TP53 gene - 539, 7 and 4, respectively). We considered exons as units of evolution instead of the entire gene and observed feeble differences among populations implying lack of a mutagen-specific effect and the possibility of mutation causing endogenous factors. In all the three genes we observed elevated rates of detrimental mutations in exons encoding regions of significance for the molecular function of the protein. We propose that this can be extended to the entire exome with implications in exon-shuffling and complex human diseases.

Background A genetic overlap between type 2 diabetes and depression has been reported in twin studies, but the finding has not been replicated with data from genome-wide association studies. Visceral adiposity has been postulated as being on the causal pathway of the association between type 2 diabetes and depression. Since waist-to-hip ratio can be a proxy measure of intra-abdominal fat deposition, we examined its effect on the association using the polygenic scores approach in the UK Biobank. Methods Type 2 diabetes polygenic scores were constructed from the association summary statistics of the Diabetes Genetic Replication And Meta-analysis Consortium, and depression polygenic scores from the Psychiatric Genetics Consortium Major Depressive Disorders Workgroup (29 studies at seven association p-value thresholds [p=0·001 to p=0·5). Logistic regression examined the association between type 2 diabetes polygenic scores and depression case-control status and the effect of body-mass index (BMI)-adjusted waist-to-hip ratio on the association, adjusting for ancestry, centres, and genotyping batches. Findings The UK Biobank sample with genotyping data consisted of 152 551 participants. There were 10 005 cases and 19 314 controls for depression among individuals of European ancestry, with a mean age of 57·1 years (SD 7·8), BMI of 27·5 kg/m 2 (4·7), and waist-to-hip ratio of 0·88 (0·09). Type 2 diabetes polygenic scores were not predictive of depression case-status at all p-value thresholds examined. The interaction between waist-to-hip ratio and type 2 diabetes polygenic scores had an effect on depression case-status (at p-value threshholds Interpretation Our exploratory study tentatively suggests that waist-to-hip ratio might have a role in the effect of type 2 diabetes polygenic scores on depression case-status. Higher adiposity is associated with greater level of inflammation, which is in turn associated with increased risk of type 2 diabetes and depression. Further research is needed to determine the direction of causation and to replicate our finding, given the cross-sectional design and the proxy use of waist-to-hip ratio for visceral adiposity. Funding Novo Nordisk UK Research Foundation.