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Background: A genetic variant in the manganese transporter SLC30A10 (rs188273166, p.Thr95Ile) was associated with increased plasma alanine transaminase (ALT) in a recent genome-wide association study in the UK Biobank (UKB). The aims of the present study were to test the association of rs188273166 with ALT in an independent cohort, and to begin to assess the clinical, hepatic, and biochemical phenotypes associated with the variant. Methods: We included n = 334,886 white participants from UKB, including 14,462 with hepatic magnetic resonance imaging (MRI), and n = 113,612 individuals from the Copenhagen City Heart Study and the Copenhagen General Population Study combined. Results: Genotyping SLC30A10 p.Thr95Ile identified 816 heterozygotes in the UKB and 111 heterozygotes in the Copenhagen cohort. Compared to noncarriers, heterozygotes had 4 and 5 U/L higher levels of ALT in the UKB and Copenhagen cohort, respectively, and 3 U/L higher plasma aspartate transaminase and gamma-glutamyl transferase in the UKB. Heterozygotes also had higher corrected T1 on liver MRI, a marker of hepatic inflammation (p = 4 × 10–7), but no change in MRI-quantified steatosis (p = 0.57). Plasma manganese was within the normal range in nine heterozygotes that provided new blood samples. SLC30A10 p.Thr95Ile heterozygotes had an eightfold increased risk of biliary tract cancer in UKB (p = 4 × 10–7), but this association was not replicated in the Copenhagen cohort. Conclusions: SLC30A10 p.Thr95Ile was associated with elevated liver enzymes in two large general population cohorts, and with MRI-quantified hepatic inflammation. Graphical abstract: A rare genetic variant (p.Thr95Ile) in the manganese transporter SLC30A10 is associated with elevated plasma alanine transaminase (ALT) and higher corrected T1 on liver MRI, markers of liver inflammation. These data support that the variant may increase the risk of liver disease. [Figure not available: see fulltext.]

Background Higher birthweight is associated with higher adult body mass index (BMI). Alleles that predispose to greater adult adiposity might act in fetal life to increase fetal growth and birthweight. Whether there are fetal effects of recently identified adult metabolically favorable adiposity alleles on birthweight is unknown. Aim We aimed to test the effect on birthweight of fetal genetic predisposition to higher metabolically favorable adult adiposity and compare that with the effect of fetal genetic predisposition to higher adult BMI. Methods We used published genome wide association study data (n = upto 406 063) to estimate fetal effects on birthweight (adjusting for maternal genotype) of alleles known to raise metabolically favorable adult adiposity or BMI. We combined summary data across single nucleotide polymorphisms (SNPs) with random effects meta-analyses. We performed weighted linear regression of SNP-birthweight effects against SNP-adult adiposity effects to test for a dose-dependent association. Results Fetal genetic predisposition to higher metabolically favorable adult adiposity and higher adult BMI were both associated with higher birthweight (3 g per effect allele (95% CI: 1–5) averaged over 14 SNPs; P = 0.002; 0.5 g per effect allele (95% CI: 0–1) averaged over 76 SNPs; P = 0.042, respectively). SNPs with greater effects on metabolically favorable adiposity tended to have greater effects on birthweight (R2 = 0.2912, P = 0.027). There was no dose-dependent association for BMI (R2 = −0.0019, P = 0.602). Conclusions Fetal genetic predisposition to both higher adult metabolically favorable adiposity and BMI is associated with birthweight. Fetal effects of metabolically favorable adiposity-raising alleles on birthweight are modestly proportional to their effects on future adiposity, but those of BMI-raising alleles are not.

Data Availability Statement: I confirm that my Data Availability Statement (pasted below) complies with the Expects Data Policy. The data that support the findings of this study are available in the supplementary material of this article. Copyright © 2022 The Authors. The role of diabetes in developing microvascular and macrovascular complications has been subject to extensive research. Despite multiple observational and genetic studies, the causal inference of diabetes (and associated risk factors) on those complications remains incomplete. In this review, we focused on type 2 diabetes, as the major form of diabetes, and investigated the evidence of causality provided by observational and genetic studies. We found that genetic studies based on Mendelian randomization provided consistent evidence of causal inference of type 2 diabetes on macrovascular complications; however, the evidence for causal inference on microvascular complications has been somewhat limited. We also noted high BMI could be causal for several diabetes complications, notable given high BMI is commonly upstream of type 2 diabetes and the recent calls to target weight loss more aggressively. We emphasize the need for further studies to identify type 2 diabetes components that mostly drive the risk of those complications. Even so, the genetic evidence summarized broadly concurs with the need for a multifactorial risk reduction approach in type 2 diabetes, including addressing excess adiposity.

This research has been conducted using the UK Biobank resource under application number 9072. Copyright © The Author(s) 2021. Higher adiposity is an established risk factor for psychiatric diseases including depression and anxiety. The associations between adiposity and depression may be explained by the metabolic consequences and/or by the psychosocial impact of higher adiposity. We performed one-and two-sample Mendelian randomization (MR) in up to 145 668 European participants from the UK Biobank to test for a causal effect of higher adiposity on 10 well-validated mental health and well-being outcomes derived using the Mental Health Questionnaire (MHQ). We used three sets of adiposity genetic instruments: (a) a set of 72 BMI genetic variants, (b) a set of 36 favourable adiposity variants and (c) a set of 38 unfavourable adiposity variants. We additionally tested causal relationships (1) in men and women separately, (2) in a subset of individuals not taking antidepressants and (3) in non-linear MR models. Two-sample MR provided evidence that a genetically determined one standard deviation (1-SD) higher BMI (4.6 kg/m2) was associated with higher odds of current depression [OR: 1.50, 95%CI: 1.15, 1.95] and lower well-being [ß:-0.15, 95%CI:-0.26,-0.04]. Findings were similar when using the metabolically favourable and unfavourable adiposity variants, with higher adiposity associated with higher odds of depression and lower well-being scores. Our study provides further evidence that higher BMI causes higher odds of depression and lowers well-being. Using genetics to separate out metabolic and psychosocial effects, our study suggests that in the absence of adverse metabolic effects higher adiposity remains causal to depression and lowers well-being. Academy of Medical Sciences (AMS) Springboard award, which is supported by the AMS, the Wellcome Trust, GCRF, the Government Department of Business, Energy and Industrial strategy, the British Heart Foundation and Diabetes UK (SBF004\1079 to J.O., F.C. and J.T.); Wellcome Senior Research Fellowship (WT220390 to R.M.F.). Diabetes UK RD Lawrence fellowship (17/0005594 to H.Y.).

OBJECTIVE Fat content and volume of liver and pancreas are associated with risk of diabetes in observational studies; whether these associations are causal is unknown. We conducted a Mendelian randomization (MR) study to examine causality of such associations. RESEARCH DESIGN AND METHODS We used genetic variants associated (P < 5 × 10−8) with the exposures (liver and pancreas volume and fat content) using MRI scans of UK Biobank participants (n = 32,859). We obtained summary-level data for risk of type 1 (9,358 cases) and type 2 (55,005 cases) diabetes from the largest available genome-wide association studies. We performed inverse-variance weighted MR as main analysis and several sensitivity analyses to assess pleiotropy and to exclude variants with potential pleiotropic effects. RESULTS Observationally, liver fat and volume were associated with type 2 diabetes (odds ratio per 1 SD higher exposure 2.16 [2.02, 2.31] and 2.11 [1.96, 2.27], respectively). Pancreatic fat was associated with type 2 diabetes (1.42 [1.34, 1.51]) but not type 1 diabetes, and pancreas volume was negatively associated with type 1 diabetes (0.42 [0.36, 0.48]) and type 2 diabetes (0.73 [0.68, 0.78]). MR analysis provided evidence only for a causal role of liver fat and pancreas volume in risk of type 2 diabetes (1.27 [1.08, 1.49] or 27% increased risk and 0.76 [0.62, 0.94] or 24% decreased risk per 1SD, respectively) and no causal associations with type 1 diabetes. CONCLUSIONS Our findings assist in understanding the causal role of ectopic fat in the liver and pancreas and of organ volume in the pathophysiology of type 1 and type 2 diabetes.

Background & Aims MRI-based corrected T1 (cT1) is a non-invasive method to grade the severity of steatohepatitis and liver fibrosis. We aimed to identify genetic variants influencing liver cT1 and use genetics to understand mechanisms underlying liver fibroinflammatory disease and its link with other metabolic traits and diseases. Methods First, we performed a genome-wide association study (GWAS) in 14,440 Europeans, with liver cT1 measures, from the UK Biobank. Second, we explored the effects of the cT1 variants on liver blood tests, and a range of metabolic traits and diseases. Third, we used Mendelian randomisation to test the causal effects of 24 predominantly metabolic traits on liver cT1 measures. Results We identified 6 independent genetic variants associated with liver cT1 that reached the GWAS significance threshold (p, Graphical abstract, Highlights • Variants in metal ion transporter and NAFLD genes are associated with liver MRI-derived cT1, a steatohepatitis and fibrosis proxy. • cT1 is highly heritable, and is correlated with BMI, NAFLD and VLDL, and inversely correlated with HDL. • Insulin resistance, NAFLD and higher BMI are genetically linked to higher liver cT1, whilst favourable adiposity is linked to lower cT1.

Background Gastro-oesophageal reflux disease (GORD) is associated with multiple risk factors but determining causality is difficult. We used a genetic approach [Mendelian randomization (MR)] to identify potential causal modifiable risk factors for GORD. Methods We used data from 451 097 European participants in the UK Biobank and defined GORD using hospital-defined ICD10 and OPCS4 codes and self-report data (N = 41 024 GORD cases). We tested observational and MR-based associations between GORD and four adiposity measures [body mass index (BMI), waist–hip ratio (WHR), a metabolically favourable higher body-fat percentage and waist circumference], smoking status, smoking frequency and caffeine consumption. Results Observationally, all adiposity measures were associated with higher odds of GORD. Ever and current smoking were associated with higher odds of GORD. Coffee consumption was associated with lower odds of GORD but, among coffee drinkers, more caffeinated-coffee consumption was associated with higher odds of GORD. Using MR, we provide strong evidence that higher WHR and higher WHR adjusted for BMI lead to GORD. There was weak evidence that higher BMI, body-fat percentage, coffee drinking or smoking caused GORD, but only the observational effects for BMI and body-fat percentage could be excluded. This MR estimated effect for WHR equates to a 1.23-fold higher odds of GORD per 5-cm increase in waist circumference. Conclusions These results provide strong evidence that a higher waist–hip ratio leads to GORD. Our study suggests that central fat distribution is crucial in causing GORD rather than overall weight.

Urinary albumin-to-creatinine ratio (ACR) is a marker of diabetic nephropathy and microvascular damage. Metabolic-related traits are observationally associated with ACR, but their causal role is uncertain. Here, we confirmed ACR as a marker of microvascular damage and tested whether metabolic-related traits have causal relationships with ACR. The association between ACR and microvascular function (responses to acetylcholine [ACH] and sodium nitroprusside) was tested in the SUMMIT study. Two-sample Mendelian randomization (MR) was used to infer the causal effects of 11 metabolic risk factors, including glycemic, lipid, and adiposity traits, on ACR. MR was performed in up to 440,000 UK Biobank and 54,451 CKDGen participants. ACR was robustly associated with microvascular function measures in SUMMIT. Using MR, we inferred that higher triglyceride (TG) and LDL cholesterol (LDL-C) levels caused elevated ACR. A 1 SD higher TG and LDL-C level caused a 0.062 (95% CI 0.040, 0.083) and a 0.026 (95% CI 0.008, 0.044) SD higher ACR, respectively. There was evidence that higher body fat and visceral body fat distribution caused elevated ACR, while a metabolically “favorable adiposity” phenotype lowered ACR. ACR is a valid marker for microvascular function. MR suggested that seven traits have causal effects on ACR, highlighting the role of adiposity-related traits in causing lower microvascular function.

Data availability: Our study uses two-sample MR. We used both published summary results (i.e. taking results from published research papers and websites) and individual participant cohort data: journal-published and website summary data were used for sample one of the two-sample MR (published GWAS of BMI and body fat percentage). The references to the published data sources are provided in the main paper. The data for the GWAS of BMI are available at https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files. The data for the GWAS of body fat percentage are available at https://walker05.u.hpc.mssm.edu. We used individual participant data for the second MR sample and for undertaking sensitivity analyses from the UKB, ALSPAC, BiB, EFSOCH and HAPO cohorts. The data in UKB, ALSPAC and BiB are fully available, via managed systems, to any researchers. The managed system for both studies is a requirement of the study funders but access is not restricted on the basis of overlap with other applications to use the data or on the basis of peer review of the proposed science. Researchers have to pay for a dataset to be prepared for them. Full information on how to access UKB data can be found at www.ukbiobank.ac.uk/using-the-resource/. The ALSPAC data management plan (www.bristol.ac.uk/alspac/researchers/data-access/documents/alspac-data-management-plan.pdf) describes, in detail, the policy regarding data sharing, which is through a system of managed open access. The following steps highlight how to apply for access to the data included in this paper and all other ALSPAC data: (1) please read the ALSPAC access policy (PDF, 627 kB), which describes the process of accessing the data and samples in detail, and outlines the costs associated with doing so; (2) you may also find it useful to browse the fully searchable ALSPAC research proposals database, which lists all research projects that have been approved since April 2011; (3) please submit your research proposal for consideration by the ALSPAC Executive Committee and you will receive a response within 10 working days to advise you whether your proposal has been approved. If you have any questions about accessing data, please e-mail alspac-data@bristol.ac.uk. Full information on how to access BiB data can be found at https://borninbradford.nhs.uk/research/how-to-access-data/. Requests for access to the original EFSOCH dataset should be made in writing in the first instance to the EFSOCH data team via the Exeter Clinical Research Facility (crf@exeter.ac.uk). Copyright © The Author(s) 2022. Aims/hypothesis: Higher maternal BMI during pregnancy is associated with higher offspring birthweight, but it is not known whether this is solely the result of adverse metabolic consequences of higher maternal adiposity, such as maternal insulin resistance and fetal exposure to higher glucose levels, or whether there is any effect of raised adiposity through non-metabolic (e.g. mechanical) factors. We aimed to use genetic variants known to predispose to higher adiposity, coupled with a favourable metabolic profile, in a Mendelian randomisation (MR) study comparing the effect of maternal ‘metabolically favourable adiposity’ on offspring birthweight with the effect of maternal general adiposity (as indexed by BMI). Methods: To test the causal effects of maternal metabolically favourable adiposity or general adiposity on offspring birthweight, we performed two-sample MR. We used variants identified in large, published genetic-association studies as being associated with either higher adiposity and a favourable metabolic profile, or higher BMI (n = 442,278 and n = 322,154 for metabolically favourable adiposity and BMI, respectively). We then extracted data on the metabolically favourable adiposity and BMI variants from a large, published genetic-association study of maternal genotype and offspring birthweight controlling for fetal genetic effects (n = 406,063 with maternal and/or fetal genotype effect estimates). We used several sensitivity analyses to test the reliability of the results. As secondary analyses, we used data from four cohorts (total n = 9323 mother–child pairs) to test the effects of maternal metabolically favourable adiposity or BMI on maternal gestational glucose, anthropometric components of birthweight and cord-blood biomarkers. Results: Higher maternal adiposity with a favourable metabolic profile was associated with lower offspring birthweight (−94 [95% CI −150, −38] g per 1 SD [6.5%] higher maternal metabolically favourable adiposity, p = 0.001). By contrast, higher maternal BMI was associated with higher offspring birthweight (35 [95% CI 16, 53] g per 1 SD [4 kg/m2] higher maternal BMI, p = 0.0002). Sensitivity analyses were broadly consistent with the main results. There was evidence of outlier SNPs for both exposures; their removal slightly strengthened the metabolically favourable adiposity estimate and made no difference to the BMI estimate. Our secondary analyses found evidence to suggest that a higher maternal metabolically favourable adiposity decreases pregnancy fasting glucose levels while a higher maternal BMI increases them. The effects on neonatal anthropometric traits were consistent with the overall effect on birthweight but the smaller sample sizes for these analyses meant that the effects were imprecisely estimated. We also found evidence to suggest that higher maternal metabolically favourable adiposity decreases cord-blood leptin while higher maternal BMI increases it. Conclusions/interpretation: Our results show that higher adiposity in mothers does not necessarily lead to higher offspring birthweight. Higher maternal adiposity can lead to lower offspring birthweight if accompanied by a favourable metabolic profile. US National Institute of Health (R01 DK10324); European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement no 669545; British Heart Foundation (CS/16/4/32482 and AA/18/7/34219); NIHR Biomedical Centre at the University Hospitals Bristol NHS Foundation Trust; University of Bristol.

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.Analyses of expression profiles from whole blood of 31,684 individuals identify cis-expression quantitative trait loci (eQTL) effects for 88% of genes and trans-eQTL effects for 37% of trait-associated variants.

Type 2 diabetes is linked to higher risk of many non-metabolic conditions (e.g. cancers, neuropsychiatric and musculoskeletal disease) which all share a common risk factor: obesity. The causal pathways from excess weight to disease are unknown. We aimed to use specific genetic variants to separately test the causal roles of higher adiposity with and without its adverse metabolic effects. Using metabolic biomarkers from 442,278 UK Biobank individuals, we identified two clusters of body fat % increasing alleles: a) 36 “favourable adiposity” (FA) alleles associated with a favourable metabolic profile (higher HDL and SHBG and lower triglyceride and liver enzymes); b) 38 “unfavourable adiposity” (UFA) alleles associated with an unfavourable profile (lower HDL and SHBG and higher triglyceride and liver enzymes). We used two-sample Mendelian randomization with 43 diseases from non-UK Biobank GWASs. We identified two sets of diseases. 1) Those where the metabolic effect of higher adiposity is the likely primary cause of the disease. Here the FA and UFA clusters had an opposing effect on the risk of disease: type 2 diabetes (FA: 0.11 OR per 1 standard deviation higher body fat % [95%CI: 0.08, 0.16] vs. UFA: 5.50 [4.29, 7.05]), stroke (0.65 [0.52, 0.83] vs. 1.43 [1.23, 1.67]), gout (0.44 [0.29, 0.68] vs. 2.49 [1.88, 3.29]), breast cancer (1.12 [0.64, 1.94] vs. 0.52 [0.39, 0.68]) and colorectal cancer (0.67 [0.52, 0.85] vs. 1.20 [1, 1.50]). 2) Those where the mechanical excess weight (or other non-metabolic effects) is likely a cause of the disease. Here the FA cluster, despite having lower metabolic risk, and the UFA cluster were both associated with higher disease risk: venous thromboembolism (2.52 [1.82, 3.47] vs. 1.63 [1.25, 2.13]), osteoarthritis (1.45 [1.19, 1.76] vs. 2.20 [1.64, 2.95]), depression (2.85 [1.38, 5.89] vs. 2.59 [1.60, 4.21]). Our results assist in understanding the consequences of higher adiposity uncoupled from its adverse metabolic effects in non-metabolic diseases pathophysiological mechanisms. Disclosure S. Martin: None. J. D. Bell: None. T. M. Frayling: None. H. Yaghootkar: None. J. Tyrrell: None. E. L. Thomas: None. M. Bown: None. J. T. Elder: None. C. Kabrhel: Research Support; Self; Diagnostica Stago, Grifols. N. Papadimitriou: None. M. Gunter: None. E. E. Vincent: None. Funding Diabetes UK (17/0005594)

To understand the consequences of higher adiposity uncoupled from its adverse metabolic effects, we selected 37 diseases associated with obesity and genetic variants associated with different aspects of excess weight including metabolically “favourable adiposity” (FA) and “unfavourable adiposity” (UFA). Mendelian randomisation (MR) identified two sets of diseases. First, 12 conditions where the metabolic effect of higher adiposity is the likely primary cause of the disease. Here MR with the FA and UFA genetics showed opposing effects on the risk of disease, including colorectal and ovarian cancer, and gout. Second, 7 conditions where the non-metabolic effects of excess weight (e.g. mechanical effect) is likely a cause. Here MR with the FA genetics, despite leading to lower metabolic risk, and MR with the UFA genetics, were both associated with higher disease risk, including osteoarthritis and venous thromboembolism. Individuals with high BMI are at higher risk of some diseases despite being relatively metabolically healthy.

To understand the causal role of adiposity and ectopic fat in type 2 diabetes and cardiometabolic diseases, we aimed to identify two clusters of adiposity genetic variants: one with “adverse” metabolic effects (UFA) and the other with, paradoxically, “favorable” metabolic effects (FA). We performed a multivariate genome-wide association study using body fat percentage and metabolic biomarkers from UK Biobank and identified 38 UFA and 36 FA variants. Adiposity-increasing alleles were associated with an adverse metabolic profile, higher risk of disease, higher CRP, and higher fat in subcutaneous and visceral adipose tissue, liver, and pancreas for UFA and a favorable metabolic profile, lower risk of disease, higher CRP and higher subcutaneous adipose tissue but lower liver fat for FA. We detected no sexual dimorphism. The Mendelian randomization studies provided evidence for a risk-increasing effect of UFA and protective effect of FA for type 2 diabetes, heart disease, hypertension, stroke, nonalcoholic fatty liver disease, and polycystic ovary syndrome. FA is distinct from UFA by its association with lower liver fat and protection from cardiometabolic diseases; it was not associated with visceral or pancreatic fat. Understanding the difference in FA and UFA may lead to new insights in preventing, predicting, and treating cardiometabolic diseases.

The CREBRF missense variant (p.Arg457Gln) is paradoxically associated with lower risk of type 2 diabetes, yet higher body mass index (BMI). Here we sought to determine whether this CREBRF variant might be associated with adult height. Linear regression was used to analyse the association of the CREBRF minor (A) allele with height in 2286 Māori and Pacific adults living in Aotearoa/New Zealand. A potential type 2 diabetes index event was corrected to account for a bias that may be the cause of paradoxical association between the CREBRF diabetes-protective allele and higher BMI and height. The CREBRF protective allele was associated with increased adult height (s = 1.25 cm, P = 3.9 × 10−6), with the effect being more pronounced in males. The lower odds of diabetes remained similar when analyses were adjusted for height (OR = 0.67–0.65). We found no evidence of a diabetes index event bias to explain the paradoxical effect of CREBRF with either BMI or height and diabetes. The orthologous CREBRF p.Arg457Gln variant was created in knock-in mice to independently assess the effect of the variant, and length was found to be greater in male mice at 8 weeks of age. These data taken together indicate that CREBRF p.Arg457Gln is associated with taller stature in Māori and Pacific adults.

Aim To examine the extent to which discriminatory testing using antibodies and Type 1 diabetes genetic risk score, validated in European populations, is applicable in a non‐European population. Methods We recruited 127 unrelated children with diabetes diagnosed between 9 months and 5 years from two centres in Iran. All children underwent targeted next‐generation sequencing of 35 monogenic diabetes genes. We measured three islet autoantibodies (islet antigen 2, glutamic acid decarboxylase and zinc transporter 8) and generated a Type 1 diabetes genetic risk score in all children. Results We identified six children with monogenic diabetes, including four novel mutations: homozygous mutations in WFS1 (n=3), SLC19A2 and SLC29A3, and a heterozygous mutation in GCK. All clinical features were similar in children with monogenic diabetes (n=6) and in the rest of the cohort (n=121). The Type 1 diabetes genetic risk score discriminated children with monogenic from Type 1 diabetes [area under the receiver‐operating characteristic curve 0.90 (95% CI 0.83–0.97)]. All children with monogenic diabetes were autoantibody‐negative. In children with no mutation, 59 were positive to glutamic acid decarboxylase, 39 to islet antigen 2 and 31 to zinc transporter 8. Measuring zinc transporter 8 increased the number of autoantibody‐positive individuals by eight. Conclusions The present study provides the first evidence that Type 1 diabetes genetic risk score can be used to distinguish monogenic from Type 1 diabetes in an Iranian population with a large number of consanguineous unions. This test can be used to identify children with a higher probability of having monogenic diabetes who could then undergo genetic testing. Identification of these individuals would reduce the cost of treatment and improve the management of their clinical course., What's new? Studies in white European populations have recently shown that a genetic risk score for Type 1 diabetes has a high ability to discriminate between Type 1 diabetes and monogenic diabetes.The diagnostic utility of this genetic risk score in non‐European populations is unknown.This study provides the first evidence that the Type 1 diabetes genetic risk score discriminates children with monogenic diabetes from those with Type 1 diabetes in the Iranian population with a large number of consanguineous unions.The Type 1 diabetes genetic risk score can be used to improve the selection of non‐European children for monogenic diabetes testing, resulting in the correct diagnosis, improving their clinical management and providing families with recurrence risk information.

Background Wolcott-Rallison syndrome is a rare autosomal recessive disorder characterized by neonatal/early-onset non-autoimmune insulin-dependent diabetes, multiple epiphyseal dysphasia and growth retardation. It is caused by mutations in the gene encoding eukaryotic translation initiation factor 2α kinase 3 (EIF2AK3). We aimed to study the clinical characteristics and frequency of the disease in the Iranian population. Methods We recruited 42 patients who referred to the endocrine and metabolism clinic at Mashhad Imam Reza Hospital with neonatal diabetes. Molecular screening of KCNJ11, INS, ABCC8 and EIF2AK3 was performed at the Exeter Molecular Genetics Laboratory, UK. We calculated the frequency of the disease in 124 patients referred from Iran to the Exeter Molecular Genetics Laboratory for genetic screening and compared it to other countries worldwide. Results We identified seven patients as having Wolcott-Rallison syndrome. Genetic testing confirmed the clinical diagnosis and indicated five novel mutations. Only two patients developed clinical features of the syndrome by 6 months of age. Of all 124 cases of Iranian neonatal diabetes referred to the Exeter Molecular Genetics Laboratory for genetic screening, 28 patients (22.58%) had a recessive mutation in EIF2AK3. Conclusions The results of this study raises awareness of the condition and provides further accurate data on the genetic and clinical presentation of Wolcott-Rallison syndrome in the Iranian population. Our study highlights the importance of genetic testing in patients from consanguineous families with diabetes diagnosed within the first 6 months of life.

Data availability statement: We used patient-level data which was fully anonymised prior to analysis. Any requests for access to the Salford data should be made to Dr Adrian Heald. Copyright © 2021 The Authors. Aims Change in weight, HbA1c, lipids, blood pressure and cardiometabolic events over time is variable in individuals with type 2 diabetes. We hypothesised that people with a genetic predisposition to a more favourable adiposity distribution could have a less severe clinical course/progression. Methods We involved people with type 2 diabetes from two UK-based cohorts: 11,914 individuals with GP follow-up data from the UK Biobank and 723 from Salford. We generated a ‘favourable adiposity’ genetic score and conducted cross-sectional and longitudinal studies to test its association with weight, BMI, lipids, blood pressure, medication use and risk of myocardial infarction and stroke using 15 follow-up time points with 1-year intervals. Results The ‘favourable adiposity’ genetic score was cross-sectionally associated with higher weight (effect size per 1 standard deviation higher genetic score: 0.91 kg [0.59,1.23]) and BMI (0.30 kg/m2 [0.19,0.40]), but higher high-density lipoprotein (0.02 mmol/L [0.01,0.02]) and lower triglycerides (−0.04 mmol/L [−0.07, −0.02]) in the UK Biobank at baseline, and this pattern of association was consistent across follow-up. There was a trend for participants with higher ‘favourable adiposity’ genetic score to have lower risk of myocardial infarction and/or stroke (odds ratio 0.79 [0.62, 1.00]) compared to those with lower score. A one standard deviation higher score was associated with lower odds of using lipid-lowering (0.91 [0.86, 0.97]) and anti-hypertensive medication (0.95 [0.91, 0.99]). Conclusions In individuals with type 2 diabetes, having more ‘favourable adiposity’ alleles is associated with a marginally better lipid profile long-term and having lower odds of requiring lipid-lowering or anti-hypertensive medication in spite of relatively higher adiposity. Diabetes UK. Grant Number: 17/0005594; European Research Council. Grant Number: 323195.

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 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 identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only and its association with lower leptin concentrations was specific to this ancestry (P=2x10-16, n=3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting leptin regulates early adiposity.

BACKGROUND: Recent genome-wide association studies (GWASs) identified the first genetic loci associated with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). The next step is to use these results to increase our understanding of the biological mechanisms involved. Most of the identified variants likely influence gene regulation. The aim of the current study is to shed light on the mechanisms underlying the genetic signals and prioritize genes by integrating GWAS results with gene expression and DNA methylation (DNAm) levels.METHODS: We applied summary-data-based Mendelian randomization to integrate ADHD and ASD GWAS data with fetal brain expression and methylation quantitative trait loci, given the early onset of these disorders. We also analyzed expression and methylation quantitative trait loci datasets of adult brain and blood, as these provide increased statistical power. We subsequently used summary-data-based Mendelian randomization to investigate if the same variant influences both DNAm and gene expression levels.RESULTS: We identified multiple gene expression and DNAm levels in fetal brain at chromosomes 1 and 17 that were associated with ADHD and ASD, respectively, through pleiotropy at shared genetic variants. The analyses in brain and blood showed additional associated gene expression and DNAm levels at the same and additional loci, likely because of increased statistical power. Several of the associated genes have not been identified in ADHD and ASD GWASs before.CONCLUSIONS: Our findings identified the genetic variants associated with ADHD and ASD that likely act through gene regulation. This facilitates prioritization of candidate genes for functional follow-up studies.

Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated diseases. Using a large study (n = 1,288) from 4 independent cohorts, we aimed to investigate the relationship between mean adipocyte area and obesity-related traits, and identify genetic factors associated with adipocyte cell size. To perform the first large-scale study of automatic adipocyte phenotyping using both histological and genetic data, we developed a deep learning-based method, the Adipocyte U-Net, to rapidly derive mean adipocyte area estimates from histology images. We validate our method using three state-of-the-art approaches; CellProfiler, Adiposoft and floating adipocytes fractions, all run blindly on two external cohorts. We observe high concordance between our method and the state-of-the-art approaches (Adipocyte U-net vs. CellProfiler: R2visceral = 0.94, P < 2.2 × 10−16, R2subcutaneous = 0.91, P < 2.2 × 10−16), and faster run times (10,000 images: 6mins vs 3.5hrs). We applied the Adipocyte U-Net to 4 cohorts with histology, genetic, and phenotypic data (total N = 820). After meta-analysis, we found that mean adipocyte area positively correlated with body mass index (BMI) (Psubq = 8.13 × 10−69, βsubq = 0.45; Pvisc = 2.5 × 10−55, βvisc = 0.49; average R2 across cohorts = 0.49) and that adipocytes in subcutaneous depots are larger than their visceral counterparts (Pmeta = 9.8 × 10−7). Lastly, we performed the largest GWAS and subsequent meta-analysis of mean adipocyte area and intra-individual adipocyte variation (N = 820). Despite having twice the number of samples than any similar study, we found no genome-wide significant associations, suggesting that larger sample sizes and a homogenous collection of adipose tissue are likely needed to identify robust genetic associations., Author summary Fundamental aspects of biology such as how the size or number of adipocytes relates to obesity and cardiometabolic health are still unanswered. To answer such questions, fast, accurate and automated measurements need to be acquired, free from human biases. Glastonbury et al., 2020 describe a novel machine learning method to perform rapid acquisition of adipocyte area estimates from histological imaging data. Using these imaging derived phenotypes, Glastonbury et al., 2020 assess the relationship between adipocyte size and a range of cardio-metabolic comorbidities, demonstrating that adipocyte size can vary depending on where adipose is stored throughout the body. By tying genetics with imaging data, Glastonbury et al., 2020 were able to demonstrate that previous findings associating adipocyte size with Type 2 Diabetes variants, are likely to be false positives. This study provides a means of being able to scale up GWAS type analyses to imaging derived phenotypes.

Objective Differences in the content and distribution of body fat and ectopic lipids may be responsible for ethnic variations in metabolic disease susceptibility. The aim of this study was to examine the ethnic distribution of body fat in two separate UK-based populations. Methods Anthropometry and body composition were assessed in two separate UK cohorts: the Hammersmith cohort and the UK Biobank, both comprising individuals of South Asian descent (SA), individuals of Afro-Caribbean descent (AC), and individuals of European descent (EUR). Regional adipose tissue stores and liver fat were measured by magnetic resonance techniques. Results The Hammersmith cohort (n = 747) had a mean (SD) age of 41.1 (14.5) years (EUR: 374 men, 240 women; SA: 68 men, 22 women; AC: 14 men, 29 women), and the UK Biobank (n = 9,533) had a mean (SD) age of 55.5 (7.5) years (EUR: 4,483 men, 4,873 women; SA: 80 men, 43 women, AC: 31 men, 25 women). Following adjustment for age and BMI, no significant differences in visceral adipose tissue or liver fat were observed between SA and EUR individuals in the either cohort. Conclusions Our data, consistent across two independent UK-based cohorts, present a limited number of ethnic differences in the distribution of body fat depots associated with metabolic disease. These results suggest that the ethnic variation in susceptibility to features of the metabolic syndrome may not arise from differences in body fat.

Aims/HypothesisHigher maternal BMI during pregnancy results in higher offspring birth weight, but it is not known whether this is solely the result of adverse metabolic consequences of higher maternal adiposity, such as maternal insulin resistance and fetal exposure to higher glucose levels, or whether there is any effect of raised adiposity through non-metabolic (e.g. mechanical) factors. We aimed to use genetic variants known to predispose to higher adiposity coupled with a favourable metabolic profile, in a Mendelian Randomisation (MR) study comparing the effect of maternal “metabolically favourable adiposity” on offspring birth weight with the effect of maternal general adiposity (as indexed by BMI).MethodsTo test the causal effects of maternal metabolically favourable adiposity or general adiposity on offspring birth weight, we performed two sample MR. We used variants identified in large genetic association studies as associated with either higher adiposity and a favourable metabolic profile, or higher BMI (N = 442,278 and N = 322,154 for metabolically favourable adiposity and BMI, respectively). We then used data from the same variants in a large genetic study of maternal genotype and offspring birth weight independent of fetal genetic effects (N = 406,063 with maternal and/or fetal genotype effect estimates). We used several sensitivity analyses to test the reliability of the results. As secondary analyses, we used data from four cohorts (total N = 9,323 mother-child pairs) to test the effects of maternal metabolically favourable adiposity or BMI on maternal gestational glucose, anthropometric components of birth weight and cord-blood biomarkers.ResultsHigher maternal adiposity with a favourable metabolic profile was associated with lower offspring birth weight (−94 (95% CI: −150 to −38) grams per 1 SD (6.5%) higher maternal metabolically favourable adiposity). By contrast, higher maternal BMI was associated with higher offspring birth weight (35 (95% CI: 16 to 53) grams per 1 SD (4 kg/m2) higher maternal BMI). Sensitivity analyses were broadly consistent with the main results. There was evidence of outlier SNPs for both exposures and their removal slightly strengthened the metabolically favourable adiposity estimate and made no difference to the BMI estimate. Our secondary analyses found evidence to suggest that maternal metabolically favourable adiposity decreases pregnancy fasting glucose levels whilst maternal BMI increases them.The effects on neonatal anthropometric traits were consistent with the overall effect on birth weight, but the smaller sample sizes for these analyses meant the effects were imprecisely estimated. We also found evidence to suggest that maternal metabolically favourable adiposity decreases cord-blood leptin whilst maternal BMI increases it.Conclusions/InterpretationOur results show that higher adiposity in mothers does not necessarily lead to higher offspring birth weight. Higher maternal adiposity can lead to lower offspring birth weight if accompanied by a favourable metabolic profile.Research in ContextWhat is already known about this subject?Studies in non-pregnant people with obesity suggest many people can have a “metabolically healthy” form of obesity, but effects in pregnancy and on offspring are not known.Multiple lines of evidence show that higher maternal BMI is causally associated with higher offspring birth weight, and that this may be mediated by the fetal insulin response to higher maternal gestational glucose.Recently, genetic variants have been identified, where one allele is associated with higher adiposity but lower risk of type II diabetes and favourable metabolic profile, including lower insulin and glucose levels, so called “metabolically favourable adiposity”; the mechanism is thought to be due to greater subcutaneous adipose storage capacity that leads to higher insulin sensitivity.What is the key question?What is the effect of maternal metabolically favourable adiposity on birth weight, and how does it compare with the effect of maternal BMI on birth weight?What are the new findings?Higher maternal adiposity can lead to lower, not higher birth weight, if it is also associated with a metabolically favourable profile; this contrasts with the effect of higher maternal general adiposity (BMI), on higher birth weight.Higher maternal metabolically favourable adiposity causes lower maternal fasting plasma glucose levels, most likely due to higher insulin sensitivity; in contrast higher maternal general adiposity leads to higher maternal fasting plasma glucose levels, most likely due to lower insulin sensitivity.How might this impact on clinical practice in the foreseeable future?Identifying ways of stratifying overweight and obese pregnant women into those with and without metabolically favourable adiposity could allow for targeted management to obtain healthy fetal growth and birth weight.

Recent developments in the field of genetics have accelerated our understanding of the aetiology of complex diseases. Type 2 diabetes mellitus and cancer are no exception, with large-scale genome-wide association studies (GWAS) facilitating exploration of the underlying pathology. Here, we discuss how genetics studies can be used to investigate the relationship between these complex diseases. Observational epidemiological studies consistently report that people with type 2 diabetes have a higher risk of several types of cancer. Indeed, type 2 diabetes and cancer share many common risk factors, such as obesity, ageing, poor diet and low levels of physical activity. However, questions remain regarding the biological mechanisms that link these two diseases. Large-scale GWAS of type 2 diabetes and cancer allow us to consider the evidence for shared genetic architecture. Several shared susceptibility genes have been identified, yet tissue specificity and direction of effect must be taken into account when considering common genetic aetiology. We also consider how GWAS, and associated techniques such as Mendelian randomisation, allow us to dissect the link between the two diseases and address questions such as ‘Does type 2 diabetes cause cancer or is the increased risk observed driven by higher adiposity or another associated metabolic feature?’ Graphical abstract Electronic supplementary material The online version of this article (10.1007/s00125-020-05228-y) contains a slideset of the figures for download, which is available to authorised users.

Purpose Many women with X chromosome aneuploidy undergo lifetime clinical monitoring for possible complications. However, ascertainment of cases in the clinic may mean that the penetrance has been overestimated. Methods We characterized the prevalence and phenotypic consequences of X chromosome aneuploidy in a population of 244,848 women over 40 years of age from UK Biobank, using single-nucleotide polymorphism (SNP) array data. Results We detected 30 women with 45,X; 186 with mosaic 45,X/46,XX; and 110 with 47,XXX. The prevalence of nonmosaic 45,X (12/100,000) and 47,XXX (45/100,000) was lower than expected, but was higher for mosaic 45,X/46,XX (76/100,000). The characteristics of women with 45,X were consistent with the characteristics of a clinically recognized Turner syndrome phenotype, including short stature and primary amenorrhea. In contrast, women with mosaic 45,X/46,XX were less short, had a normal reproductive lifespan and birth rate, and no reported cardiovascular complications. The phenotype of women with 47,XXX included taller stature (5.3 cm; SD = 5.52 cm; P = 5.8 × 10−20) and earlier menopause age (5.12 years; SD = 5.1 years; P = 1.2 × 10−14). Conclusion Our results suggest that the clinical management of women with 45,X/46,XX mosaicism should be minimal, particularly those identified incidentally.

More than one in three adults worldwide is either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, are more informative for predicting risk of obesity sequelae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio (WHR) adjusted for body mass index (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.

Background & AimsA common genetic variant near MBOAT7 (rs641738C>T) has been previously associated with hepatic fat and advanced histology in non-alcoholic fatty liver disease (NAFLD), however, these findings have not been consistently replicated in the literature. We aimed to establish whether rs641738C>T is a risk factor across the spectrum of NAFLD and characterize its role in the regulation of related metabolic phenotypes through meta-analysis.MethodsWe performed meta-analysis of studies with data on the association between rs641738C>T genotype and: liver fat, NAFLD histology, and serum ALT, lipids, or insulin. These included directly genotyped studies and population-level data from genome-wide association studies (GWAS). We performed random effects meta-analysis using recessive, additive, and dominant genetic models.ResultsData from 1,047,265 participants (8,303 with liver biopsies) across 42 studies was included in the meta-analysis. rs641738C>T was associated with higher liver fat on CT/MRI (+0.03 standard deviations [95% CI: 0.02 - 0.05]) and diagnosis of NAFLD (OR 1.22 [95% CI 1.08 - 1.39]) in Caucasian adults. The variant was also positively associated with presence of severe steatosis, NASH, and advanced fibrosis (OR: 1.32 [95% CI: 1.06 - 1.63]) in Caucasian adults using a recessive model of inheritance (CC+CT vs. TT). Meta-analysis of data from previous GWAS found the variant to be associated with higher ALT (Pz=0.002) and lower serum triglycerides (Pz=1.5×10−4). rs641738C>T was not associated with fasting insulin and no effect was observed in children with NAFLD.ConclusionOur study validates rs641738C>T near MBOAT7 as a risk factor for the presence and severity of NAFLD in individuals of European descent.

Depression is a common and disabling disorder, representing a major social and economic health issue. Moreover, depression is associated with the progression of diseases with an inflammatory etiology including many inflammatory-related disorders. At the molecular level, the mechanisms by which depression might promote the onset of these diseases and associated immune-dysfunction are not well understood. In this study we assessed genome-wide patterns of DNA methylation in whole blood-derived DNA obtained from individuals with a self-reported history of depression (n = 100) and individuals without a history of depression (n = 100) using the Illumina 450K microarray. Our analysis identified six significant (Šidák corrected P

MRI-based corrected T1 (cT1) is a non-invasive method to grade the severity of steatohepatitis and liver fibrosis. We aimed to identify genetic variants influencing liver cT1 and use genetics to understand mechanisms underlying liver fibroinflammatory disease and its link with other metabolic traits and diseases.First, we performed a genome-wide association study (GWAS) in 14,440 Europeans, with liver cT1 measures, from the UK Biobank. Second, we explored the effects of the cT1 variants on liver blood tests, and a range of metabolic traits and diseases. Third, we used Mendelian randomisation to test the causal effects of 24 predominantly metabolic traits on liver cT1 measures.We identified 6 independent genetic variants associated with liver cT1 that reached the GWAS significance threshold (p 5×10The association between 2 metal ion transporters and cT1 indicates an important new mechanism in steatohepatitis. Future studies are needed to determine whether interventions targeting the identified transporters might prevent liver disease in at-risk individuals.We estimated levels of liver inflammation and scarring based on magnetic resonance imaging of 14,440 UK Biobank participants. We performed a genetic study and identified variations in 6 genes associated with levels of liver inflammation and scarring. Participants with variations in 4 of these genes also had higher levels of markers of liver cell injury in blood samples, further validating their role in liver health. Two identified genes are involved in the transport of metal ions in our body. Further investigation of these variations may lead to better detection, assessment, and/or treatment of liver inflammation and scarring.

Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated diseases. Using a large study (n = 1,288) from 4 independent cohorts, we aimed to investigate the relationship between adipocyte area and obesity-related traits, and identify genetic factors associated with adipocyte cell size. To perform the first large-scale study of automatic adipocyte phenotyping using both histological and genetic data, we developed a deep learning-based method, the Adipocyte U-Net, to rapidly derive area estimates from histology images. We validate our method using three state-of-the-art approaches; CellProfiler, Adiposoft and floating adipocytes fractions, all run blindly on two external cohorts. We observe high concordance between our method and the state-of-the-art approaches (Adipocyte U-net vs. CellProfiler: R2visceral= 0.94, P < 2.2 × 10−16, R2subcutaneous= 0.91, P < 2.2 × 10−16), and faster run times (10,000 images: 6mins vs 3.5hrs). We applied the Adipocyte U-Net to 4 cohorts with histology, genetic, and phenotypic data (total N = 820). After meta-analysis, we found that adipocyte area positively correlated with body mass index (BMI) (Psubq = 8.13 × 10−69, βsubq = 0.45; Pvisc= 2.5 × 10−55, βvisc= 0.49; average R2 across cohorts = 0.49) and that adipocytes in subcutaneous depots are larger than their visceral counterparts (Pmeta= 9.8 × 10−7). Lastly, we performed the largest GWAS and subsequent meta-analysis of adipocyte area and intra-individual adipocyte variation (N = 820). Despite having twice the number of samples than any similar study, we found no genome-wide significant associations, suggesting that larger sample sizes and a homogenous collection of adipose tissue are likely needed to identify robust genetic associations.

Background and aims Excess liver fat affects up to 1 in 4 adults globally1 and has been implicated in the pathogenesis of liver disease including cirrhosis and hepatocellular carcinoma, as well as extrahepatic diseases such as type 2 diabetes and cardiovascular diseases2. We aimed to find genetic variants influencing liver fat content. Methods Data was acquired from UK Biobank (application 9914). Liver phenotypes were calculated from MRI data by trained analysts using LiverMultiScanTM. We used GEMMA to perform a genome-wide association study (GWAS) of MRI scan measures of liver fat using 8,289 individuals of European ancestry from UK Biobank. We adjusted our analysis for age, sex, BMI, genotyping array, and population structure. Results We identified two loci in/near PNPLA3 (rs738409, p = 2.1 x 10−41) and TM6SF2 (rs58542926, p = 4.3 x 10−40) that reached genome-wide significance. We further identified four suggestive loci previously associated with circulating lipid levels, type 2 diabetes and obesity (APOE, GPAM, TRIB1, GCKR). Phenome-wide association analysis (PheWAS) of rs58542926 in TM6SF2 demonstrated positive associations with diabetes, rosacea and liver cirrhosis, and inverse associations with cholesterol, peripheral vascular disease, gout, pulmonary embolism and gallstones. Phenome-wide association analysis of rs738409 in PNPLA3 demonstrated positive associations with liver disease, type 2 diabetes and hypertension, and inverse associations with height, hip circumference, leg and arm fat free mass, cholesterol, and ischaemic heart diseases. Conclusion This is the first GWAS using MRI determined liver fat content to date. Mechanisms underlying elevated liver fat content contribute to hypertension and type 2 diabetes risk, but may also confer health benefits. The identification of loci previously associated with non-alcoholic fatty liver disease provide genetic validation of the utility of MRI for a fast and non-invasive assessment of liver fat content. References Younossi, Z et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat. Rev. Gastroenterol. Hepatol.15, 11–20 (2018). Adams, L A, Anstee, Q M, Tilg, H. & Targher, G. Non-alcoholic fatty liver disease and its relationship with cardiovascular disease and other extrahepatic diseases. Gut (2017). doi:10.1136/gutjnl-2017–313884

Introduction Gastro-oesophageal Reflux Disease (GORD) is a common condition in which acid from the stomach leaks to the oesophagus causing heartburn and unpleasant taste in mouth, potentially leading to Barrett’s Oesophagus and Oesophageal Adenocarcinoma. Observationally, it has been reported that low body mass index (BMI), high BMI, past smoking, alcohol and caffeine consumption increase risk of GORD. Recently, it was reported that waist hip ratio (WHR) was a better measure of obesity than BMI for predicting GORD. However, observational relationships may be affected by bias and confounding. Methods We used data from 379,713 unrelated European participants in the UK Biobank, including 23,123 GORD cases to firstly explore the observational associations between GORD and adiposity measures, smoking status and smoking frequency, alcohol and caffeine consumption. We then used one- and two-sample Mendelian Randomisation (MR) techniques to test the causal relationship between the predictors and GORD. MR is a genetic technique which uses genetic variation to examine the causal effect of a risk factor on an outcome through the use of a genetic instrument for the risk factor. Results Observationally male gender, age, past smoking, current smoking, higher BMI, higher WHR, higher body fat percentage and waist circumference associated with higher odds of GORD, whilst higher caffeinated coffee consumption was associated with lower risk of GORD. There was some tentative evidence of a J-shaped relationship between BMI and GORD. Alcohol consumption was not associated with GORD. MR provided strong evidence of a causal role for WHR, with a one-SD higher WHR causing a 1.34 higher odds of GORD (95%CI: 1.16–1.55, p=5e-5). Similarly, a one-SD higher WHR adjusted for BMI was associated with 1.21 higher odds of GORD (95%CI: 1.14–1.29, p=2e-9). However, there was no evidence of a causal relationship for BMI (OR: 1.00 (95%CI: 0.09–1.12), p=0.97). There was no evidence of a causal role for body fat percentage, smoking and caffeine. All results were robust to 2 sample MR approaches. Conclusions The results show robust causal evidence for the link between obesity and reflux being primarily down to WHR, not BMI. These results emphasise the importance of measuring WHR when studying gastrointestinal disorders, and the importance of weight loss in reducing the risk of reflux.

BackgroundSmoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk.MethodsWe analyzed ∼250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci.ResultsMeta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals.ConclusionsRare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.

Background and aims Excess liver iron content is common, affecting approximately 10% of the population, and observationally associates with hepatic and extrahepatic diseases such as liver fibrosis, hepatocellular carcinoma and metabolic syndrome1. Genome wide association studies (GWAS) on MRI determined liver iron content, compared to circulating iron traits, permit detection of liver-specific susceptibility loci. Here we aim to find genetic variants influencing liver iron content, using data from UK Biobank. Methods Data was acquired from UK Biobank (application 9914). Liver phenotypes were calculated from MRI data by trained analysts using LiverMultiScanTM. We used GEMMA to perform a GWAS of MRI scan measures of liver iron in 8,289 individuals of European ancestry. We adjusted for age, sex, BMI, genotyping array, and population structure. Results We identified three independent genetic variants (rs1800562 & rs1799945 in HFE, rs855791 in TMPRSS6) associated with liver iron content at genome-wide significance (p Conclusion Our study provides genetic evidence that mechanisms underlying liver iron content are mostly systemic and not organ specific. The identification of loci which affect circulating iron traits provide genetic validation of the utility of MRI for a fast and non-invasive assessment of liver iron content. Reference Deugnier, Y., Bardou-Jacquet, E. & Laine, F. Dysmetabolic iron overload syndrome (DIOS). Presse Med.46, e306–e311 (2017).

Birth weight (BW) variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. These associations have been proposed to reflect the lifelong consequences of an adverse intrauterine environment. In earlier work, we demonstrated that much of the negative correlation between BW and adult cardio-metabolic traits could instead be attributable to shared genetic effects. However, that work and other previous studies did not systematically distinguish the direct effects of an individual’s own genotype on BW and subsequent disease risk from indirect effects of their mother’s correlated genotype, mediated by the intrauterine environment. Here, we describe expanded genome-wide association analyses of own BW (n=321,223) and offspring BW (n=230,069 mothers), which identified 278 independent association signals influencing BW (214 novel). We used structural equation modelling to decompose the contributions of direct fetal and indirect maternal genetic influences on BW, implicating fetal- and maternal-specific mechanisms. We used Mendelian randomization to explore the causal relationships between factors influencing BW through fetal or maternal routes, for example, glycemic traits and blood pressure. Direct fetal genotype effects dominate the shared genetic contribution to the association between lower BW and higher type 2 diabetes risk, whereas the relationship between lower BW and higher later blood pressure (BP) is driven by a combination of indirect maternal and direct fetal genetic effects: indirect effects of maternal BP-raising genotypes act to reduce offspring BW, but only direct fetal genotype effects (once inherited) increase the offspring’s later BP. Instrumental variable analysis using maternal BW-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring BP. In successfully separating fetal from maternal genetic effects, this work represents an important advance in genetic studies of perinatal outcomes, and shows that the association between lower BW and higher adult BP is attributable to genetic effects, and not to intrauterine programming.

The CREBRF missense variant (p.Arg457Gln) is paradoxically associated with lower risk of type 2 diabetes, yet higher body mass index (BMI). Here we sought to determine whether this CREBRF variant might be associated with adult height.Linear regression was used to analyse the association of the CREBRF minor (A) allele with height in 2286 Māori and Pacific adults living in Aotearoa/New Zealand. A potential type 2 diabetes index event was corrected to account for a bias that may be the cause of paradoxical association between the CREBRF diabetes-protective allele and higher BMI and height.The CREBRF protective allele was associated with increased adult height (ß = 1.25 cm, P = 3.9 × 10These data taken together indicate that CREBRF p.Arg457Gln is associated with taller stature in Māori and Pacific adults.