Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes

Role of pancreatic ductal adenocarcinoma risk factors in intraductal papillary mucinous neoplasm progression

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) is lethal due to its late diagnosis and lack of successful treatments. A possible strategy to reduce its death burden is prevention. Intraductal papillary mucinous neoplasms (IPMNs) are precursors of PDAC. It is difficult to estimate the incidence of IPMNs because they are asymptomatic. Two recent studies reported pancreatic cysts in 3% and 13% of scanned subjects. The possibility of identifying a subgroup of IPMN patients with a higher probability of progression into cancer could be instrumental in increasing the survival rate. In this study, genetic and non-genetic PDAC risk factors were tested in a group of IPMN patients under surveillance.

METHODS

A retrospective study was conducted on 354 IPMN patients enrolled in two Italian centres with an average follow-up of 64 months. With the use of DNA extracted from blood, collected at IPMN diagnosis, all patients were genotyped for 30 known PDAC risk loci. The polymorphisms were analysed individually and grouped in an unweighted polygenic score (PGS) in relation to IPMN progression. The ABO blood group and non-genetic PDAC risk factors were also analysed. IPMN progression was defined based on the development of worrisome features and/or high-risk stigmata during follow-up.

RESULTS

Two genetic variants (rs1517037 and rs10094872) showed suggestive associations with an increment of IPMN progression. After correction for multiple testing, using the Bonferroni correction, none of the variants showed a statistically significant association. However, associations were observed for the non-genetic variables, such as smoking status, comparing heavy smokers with light smokers (HR = 3.81, 95% 1.43-10.09, p = 0.007), and obesity (HR = 2.46, 95% CI 1.22-4.95, p = 0.012).

CONCLUSION

In conclusion, this study is the first attempt to investigate the presence of shared genetic background between PDAC risk and IPMN progression; however, the results suggest that the 30 established PDAC susceptibility polymorphisms are not associated with clinical IPMN progression in a sample of 354 patients. However, we observed indications of cigarette smoking and body mass index (BMI) involvement in IPMN progression. The biological mechanism that could link these two risk factors to progression could be chronic inflammation, of which both smoking and obesity are strong promoters.

CaMK1D signalling in AgRP neurons promotes ghrelin-mediated food intake

Hypothalamic AgRP/NPY neurons are key players in the control of feeding behaviour. Ghrelin, a major orexigenic hormone, activates AgRP/NPY neurons to stimulate food intake and adiposity. However, cell-autonomous ghrelin-dependent signalling mechanisms in AgRP/NPY neurons remain poorly defined. Here we show that calcium/calmodulin-dependent protein kinase ID (CaMK1D), a genetic hot spot in type 2 diabetes, is activated upon ghrelin stimulation and acts in AgRP/NPY neurons to mediate ghrelin-dependent food intake. Global Camk1d-knockout male mice are resistant to ghrelin, gain less body weight and are protected against high-fat-diet-induced obesity. Deletion of Camk1d in AgRP/NPY, but not in POMC, neurons is sufficient to recapitulate above phenotypes. In response to ghrelin, lack of CaMK1D attenuates phosphorylation of CREB and CREB-dependent expression of the orexigenic neuropeptides AgRP/NPY in fibre projections to the paraventricular nucleus (PVN). Hence, CaMK1D links ghrelin action to transcriptional control of orexigenic neuropeptide availability in AgRP neurons.

Prioritization of potential causative genes for schizophrenia in placenta

Our earlier work has shown that genomic risk for schizophrenia converges with early life complications in affecting risk for the disorder and sex-biased neurodevelopmental trajectories. Here, we identify specific genes and potential mechanisms that, in placenta, may mediate such outcomes. We performed TWAS in healthy term placentae (N = 147) to derive candidate placental causal genes that we confirmed with SMR; to search for placenta and schizophrenia-specific associations, we performed an analogous analysis in fetal brain (N = 166) and additional placenta TWAS for other disorders/traits. The analyses in the whole sample and stratifying by sex ultimately highlight 139 placenta and schizophrenia-specific risk genes, many being sex-biased; the candidate molecular mechanisms converge on the nutrient-sensing capabilities of placenta and trophoblast invasiveness. These genes also implicate the Coronavirus-pathogenesis pathway and showed increased expression in placentae from a small sample of SARS-CoV-2-positive pregnancies. Investigating placental risk genes for schizophrenia and candidate mechanisms may lead to opportunities for prevention that would not be suggested by study of the brain alone.

Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes

DNA methylation variations are prevalent in human obesity but evidence of a causative role in disease pathogenesis is limited. Here, we combine epigenome-wide association and integrative genomics to investigate the impact of adipocyte DNA methylation variations in human obesity. We discover extensive DNA methylation changes that are robustly associated with obesity (N = 190 samples, 691 loci in subcutaneous and 173 loci in visceral adipocytes, P < 1 × 10-7). We connect obesity-associated methylation variations to transcriptomic changes at >500 target genes, and identify putative methylation-transcription factor interactions. Through Mendelian Randomisation, we infer causal effects of methylation on obesity and obesity-induced metabolic disturbances at 59 independent loci. Targeted methylation sequencing, CRISPR-activation and gene silencing in adipocytes, further identifies regional methylation variations, underlying regulatory elements and novel cellular metabolic effects. Our results indicate DNA methylation is an important determinant of human obesity and its metabolic complications, and reveal mechanisms through which altered methylation may impact adipocyte functions.

Dissecting the causal relationship between household income status and genetic susceptibility to cardiovascular-related diseases: Insights from bidirectional mendelian randomization study

OBJECTIVES

Observational studies have revealed that socioeconomic status is associated with cardiovascular health. However, the potential causal effect remains unclear. Hence, we aimed to investigate the causal relationship between household income status and genetic susceptibility to cardiovascular-related diseases using a bidirectional Mendelian randomization (MR) study.

METHODS

An MR study based on a large-sample cohort of the European population from a publicly available genome-wide association study datasets was conducted using a random-effects inverse-variance weighting model as the main standard. Simultaneously, MR-Egger regression, weighted median, and maximum likelihood estimation were used as supplements. Sensitivity analysis, consisting of a heterogeneity test and horizontal pleiotropy test, was performed using Cochran's Q, MR-Egger intercept, and MR-PRESSO tests to ensure the reliability of the conclusion.

RESULTS

The results suggested that higher household income tended to lower the risk of genetic susceptibility to myocardial infarction (OR: 0.503, 95% CI = 0.405-0.625, P < 0.001), hypertension (OR: 0.667, 95% CI = 0.522-0.851, P = 0.001), coronary artery disease (OR: 0.674, 95% CI = 0.509-0.893, P = 0.005), type 2 diabetes (OR: 0.642, 95% CI = 0.464-0.889, P = 0.007), heart failure (OR: 0.825, 95% CI = 0.709-0.960, P = 0.013), and ischemic stroke (OR: 0.801, 95% CI = 0.662-0.968, P = 0.022). In contrast, no association was evident with atrial fibrillation (OR: 0.970, 95% CI = 0.767-1.226, P = 0.798). The reverse MR study suggested a potentially negative trend between heart failure and household income status. A sensitivity analysis verified the reliability of the results.

CONCLUSIONS

The results revealed that the population with higher household income tended to have a lower risk of genetic susceptibility to myocardial infarction and hypertension.

Sleep traits and risk of end-stage renal disease: a mendelian randomization study

BACKGROUND

Epidemiological evidence relating sleep disorders to end-stage renal disease (ESRD) has been obscure. The present study is sought to examine the association between sleep traits and ESRD.

METHODS

For this analysis, we selected genetic instruments for sleep traits from published genome-wide association studies (GWAS). As instrumental variables, independent genetic variations linked with seven sleep-related features (sleep duration, getting up in the morning, daytime napping, chronotype of morning/evening person, sleeplessness/insomnia, non-snoring, and daytime dozing) were chosen. A two-sample Mendelian randomization (TSMR) study was conducted to assess the causal relationship between sleep traits and ESRD (N = 33,061). The reverse MR analysis subsequently determined the causal relationship between ESRD and sleep traits. The causal effects were estimated using inverse variance weighted, MR-Egger, weighted median. To conduct sensitivity studies, Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis, and funnel plot were used. To study the potential mediators, multivariable mendelian randomization analyses were undertaken further.

RESULTS

Genetically predicted sleeplessness/ insomnia (OR = 6.11, 95%CI 1.00-37.3, P = 0.049, FDR = 0.105), getting up in the morning easily(OR = 0.23, 95%CI 0.063-0.85; P = 0.0278, FDR = 0.105), non-snoring (OR = 4.76E-02, 95%CI 2.29E-03-0.985, P = 0.0488, FDR = 0.105) was suggestively associated with the risk of ESRD. However, we found no evidence favoring a causal association between other sleep traits and ESRD through the IVW method.

CONCLUSION

The present TSMR found no strong evidence of a bidirectional causal association between genetically predicted sleep traits and ESRD.

Association Between Obesity and Chronic Kidney Disease: Multivariable Mendelian Randomization Analysis and Observational Data From a Bariatric Surgery Cohort

Obesity is postulated to independently increase chronic kidney disease (CKD), even after adjusting for type 2 diabetes (T2D) and hypertension. Dysglycemia below T2D thresholds, frequently seen with obesity, also increases CKD risk. Whether obesity increases CKD independent of dysglycemia and hypertension is unknown and likely influences the optimal weight loss (WL) needed to reduce CKD. T2D remission rates plateau with 20-25% WL after bariatric surgery (BS), but further WL increases normoglycemia and normotension. We undertook bidirectional inverse variance weighted Mendelian randomization (IVWMR) to investigate potential independent causal associations between increased BMI and estimated glomerular filtration rate (eGFR) in CKD (CKDeGFR) (<60 mL/min/1.73 m2) and microalbuminuria (MA). In 5,337 BS patients, we assessed whether WL influences >50% decline in eGFR (primary outcome) or CKD hospitalization (secondary outcome), using <20% WL as a comparator. IVWMR results suggest that increased BMI increases CKDeGFR (b = 0.13, P = 1.64 × 10-4; odds ratio [OR] 1.14 [95% CI 1.07, 1.23]) and MA (b = 0.25; P = 2.14 × 10-4; OR 1.29 [1.13, 1.48]). After adjusting for hypertension and fasting glucose, increased BMI did not significantly increase CKDeGFR (b = -0.02; P = 0.72; OR 0.98 [0.87, 1.1]) or MA (b = 0.19; P = 0.08; OR 1.21 [0.98, 1.51]). Post-BS WL significantly reduced the primary outcome with 30 to <40% WL (hazard ratio [HR] 0.53 [95% CI 0.32, 0.87]) but not 20 to <30% WL (HR 0.72 [0.44, 1.2]) and ≥40% WL (HR 0.73 [0.41, 1.30]). For CKD hospitalization, progressive reduction was seen with increased WL, which was significant for 30 to <40% WL (HR 0.37 [0.17, 0.82]) and ≥40% WL (HR 0.24 [0.07, 0.89]) but not 20 to <30% WL (HR 0.60 [0.29, 1.23]). The data suggest that obesity is likely not an independent cause of CKD. WL thresholds previously associated with normotension and normoglycemia, likely causal mediators, may reduce CKD after BS.

Genetic association of lipids and lipid-lowering drug target genes with non-alcoholic fatty liver disease

BACKGROUND

Some observational studies found that dyslipidaemia is a risk factor for non-alcoholic fatty liver disease (NAFLD), and lipid-lowering drugs may lower NAFLD risk. However, it remains unclear whether dyslipidaemia is causative for NAFLD. This Mendelian randomisation (MR) study aimed to explore the causal role of lipid traits in NAFLD and evaluate the potential effect of lipid-lowering drug targets on NAFLD.

METHODS

Genetic variants associated with lipid traits and variants of genes encoding lipid-lowering drug targets were extracted from the Global Lipids Genetics Consortium genome-wide association study (GWAS). Summary statistics for NAFLD were obtained from two independent GWAS datasets. Lipid-lowering drug targets that reached significance were further tested using expression quantitative trait loci data in relevant tissues. Colocalisation and mediation analyses were performed to validate the robustness of the results and explore potential mediators.

FINDINGS

No significant effect of lipid traits and eight lipid-lowering drug targets on NAFLD risk was found. Genetic mimicry of lipoprotein lipase (LPL) enhancement was associated with lower NAFLD risks in two independent datasets (OR₁ = 0.60 [95% CI 0.50-0.72], p₁ = 2.07 × 10^-8; OR₂ = 0.57 [95% CI 0.39-0.82], p₂ = 3.00 × 10^-3). A significant MR association (OR = 0.71 [95% CI, 0.58-0.87], p = 1.20 × 10^-3) and strong colocalisation association (PP.H₄ = 0.85) with NAFLD were observed for LPL expression in subcutaneous adipose tissue. Fasting insulin and type 2 diabetes mediated 7.40% and 9.15%, respectively, of the total effect of LPL on NAFLD risk.

INTERPRETATION

Our findings do not support dyslipidaemia as a causal factor for NAFLD. Among nine lipid-lowering drug targets, LPL is a promising candidate drug target in NAFLD. The mechanism of action of LPL in NAFLD may be independent of its lipid-lowering effects.

FUNDING

Capital's Funds for Health Improvement and Research (2022-4-4037). CAMS Innovation Fund for Medical Sciences (CIFMS, grant number: 2021-I2M-C&T-A-010).

The Association Between Insulin Use and Asthma: An Epidemiological Observational Analysis and Mendelian Randomization Study

BACKGROUND

Asthma is a common respiratory disease caused by genetic and environmental factors, but the contribution of insulin use to the risk of asthma remains unclear. This study aimed to investigate the association between insulin use and asthma in a large population-based cohort, and further explore their causal relationship by Mendelian randomization (MR) analysis.

METHODS

An epidemiological study including 85,887 participants from the National Health and Nutrition Examination Survey (NHANES) 2001-2018 was performed to evaluate the association between insulin use and asthma. Based on the inverse-variance weighted approach, MR analysis were conducted to estimate the causal effect of insulin use on asthma from the UKB and FinnGen datasets, respectively.

RESULTS

In the NHANES cohort, we found that insulin use was associated with an increased risk of asthma [odd ratio (OR) 1.38; 95% CI 1.16-1.64; p < 0.001]. For the MR analysis, we found a causal relationship between insulin use and a higher risk of asthma in both Finn (OR 1.10; p < 0.001) and UK Biobank cohorts (OR 1.18; p < 0.001). Meanwhile, there was no causal association between diabetes and asthma. After multivariable adjustment for diabetes in UKB cohort, the insulin use remained significantly associated with an increased risk of asthma (OR 1.17, p < 0.001).

CONCLUSIONS

An association between insulin use and an increased risk of asthma was found via the real-world data from the NHANES. In addition, the current study identified a causal effect and provided a genetic evidence of insulin use and asthma. More studies are needed to elucidate the mechanisms underlying the association between insulin use and asthma.

Causal associations between modifiable risk factors and pancreatitis: A comprehensive Mendelian randomization study

Background

The pathogenesis of pancreatitis involves diverse environmental risk factors, some of which have not yet been clearly elucidated. This study systematically investigated the causal effects of genetically predicted modifiable risk factors on pancreatitis using the Mendelian randomization (MR) approach.

Methods

Genetic variants associated with 30 exposure factors were obtained from genome-wide association studies. Summary-level statistical data for acute pancreatitis (AP), chronic pancreatitis (CP), alcohol-induced AP (AAP) and alcohol-induced CP (ACP) were obtained from FinnGen consortia. Univariable and multivariable MR analyses were performed to identify causal risk factors for pancreatitis.

Results

Genetic predisposition to smoking (OR = 1.314, P = 0.021), cholelithiasis (OR = 1.365, P = 1.307E-19) and inflammatory bowel disease (IBD) (OR = 1.063, P = 0.008) as well as higher triglycerides (OR = 1.189, P = 0.016), body mass index (BMI) (OR = 1.335, P = 3.077E-04), whole body fat mass (OR = 1.291, P = 0.004) and waist circumference (OR = 1.466, P = 0.011) were associated with increased risk of AP. The effect of obesity traits on AP was attenuated after correcting for cholelithiasis. Genetically-driven smoking (OR = 1.595, P = 0.005), alcohol consumption (OR = 3.142, P = 0.020), cholelithiasis (OR = 1.180, P = 0.001), autoimmune diseases (OR = 1.123, P = 0.008), IBD (OR = 1.066, P = 0.042), type 2 diabetes (OR = 1.121, P = 0.029), and higher serum calcium (OR = 1.933, P = 0.018), triglycerides (OR = 1.222, P = 0.021) and waist-to-hip ratio (OR = 1.632, P = 0.023) increased the risk of CP. Cholelithiasis, triglycerides and the waist-to-hip ratio remained significant predictors in the multivariable MR. Genetically predicted alcohol drinking was associated with increased risk of AAP (OR = 15.045, P = 0.001) and ACP (OR = 6.042, P = 0.014). After adjustment of alcohol drinking, genetic liability to IBD had a similar significant causal effect on AAP (OR = 1.137, P = 0.049), while testosterone (OR = 0.270, P = 0.002) a triglyceride (OR = 1.610, P = 0.001) and hip circumference (OR = 0.648, P = 0.040) were significantly associated with ACP. Genetically predicted higher education and household income levels could lower the risk of pancreatitis.

Conclusions

This MR study provides evidence of complex causal associations between modifiable risk factors and pancreatitis. These findings provide new insights into potential therapeutic and prevention strategies.

Association between serum calcium level and type 2 diabetes: An NHANES analysis and Mendelian randomization study

AIMS

This study investigated the association between serum calcium levels and the prevalence of T2D using a cross-sectional study and Mendelian randomization analysis.

METHODS

Cross-sectional data were obtained from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. Serum calcium levels were divided into three groups (low, medium and high groups) according to the tertiles. Logistic regression was used to estimate the association between serum calcium levels and T2D prevalence. Instrumental variables for serum calcium levels were obtained from the UK Biobank and a two-sample MR analysis was performed to examine the causal relationship between genetically predicted serum calcium levels and the risk of T2D.

RESULTS

A total of 39,645 participants were available for cross-sectional analysis. After adjusting for covariates, participants in the high serum calcium group had significantly higher odds of T2D (OR = 1.18, 95% CI = 1.07, 1.30, p = 0.001) than those in the moderate group. Restricted cubic spline plots showed a J-shaped curve relationship between serum calcium level and prevalence of T2D. Consistently, Mendelian randomization analysis showed that higher genetically predicted serum calcium levels were causally associated with a higher risk of T2D (OR = 1.16, 95% CI: 1.01, 1.33, p = 0.031).

CONCLUSIONS

The results of this study suggest that higher serum calcium levels are causally associated with a higher risk of T2D. Further studies are needed to clarify whether intervening in high serum calcium could reduce the risk of T2D.

Sex-Specific Reproductive Factors Augment Cardiovascular Disease Risk in Women: A Mendelian Randomization Study

Background Observational studies suggest that reproductive factors are associated with cardiovascular disease, but these are liable to influence by residual confounding. This study explores the causal relevance of reproductive factors on cardiovascular disease in women using Mendelian randomization. Methods and Results Uncorrelated (r2<0.001), genome-wide significant (P<5×10-8) single-nucleotide polymorphisms were extracted from sex-specific genome-wide association studies of age at first birth, number of live births, age at menarche, and age at menopause. Inverse-variance weighted Mendelian randomization was used for primary analyses on outcomes of atrial fibrillation, coronary artery disease, heart failure, ischemic stroke, and stroke. Earlier genetically predicted age at first birth increased risk of coronary artery disease (odds ratio [OR] per year, 1.49 [95% CI, 1.28-1.74], P=3.72×10-7) heart failure (OR, 1.27 [95% CI, 1.06-1.53], P=0.009), and stroke (OR, 1.25 [95% CI, 1.00-1.56], P=0.048), with partial mediation through body mass index, type 2 diabetes, blood pressure, and cholesterol traits. Higher genetically predicted number of live births increased risk of atrial fibrillation (OR for <2, versus 2, versus >2 live births, 2.91 [95% CI, 1.16-7.29], P=0.023), heart failure (OR, 1.90 [95% CI, 1.28-2.82], P=0.001), ischemic stroke (OR, 1.86 [95% CI, 1.03-3.37], P=0.039), and stroke (OR, 2.07 [95% CI, 1.22-3.52], P=0.007). Earlier genetically predicted age at menarche increased risk of coronary artery disease (OR per year, 1.10 [95% CI, 1.06-1.14], P=1.68×10-6) and heart failure (OR, 1.12 [95% CI, 1.07-1.17], P=5.06×10-7); both associations were at least partly mediated by body mass index. Conclusions These results support a causal role of a number of reproductive factors on cardiovascular disease in women and identify multiple modifiable mediators amenable to clinical intervention.

Effect of tissue-grouped regulatory variants associated to type 2 diabetes in related secondary outcomes

Genome-wide association studies have identified over five hundred loci that contribute to variation in type 2 diabetes (T2D), an established risk factor for many diseases. However, the mechanisms and extent through which these loci contribute to subsequent outcomes remain elusive. We hypothesized that combinations of T2D-associated variants acting on tissue-specific regulatory elements might account for greater risk for tissue-specific outcomes, leading to diversity in T2D disease progression. We searched for T2D-associated variants acting on regulatory elements and expression quantitative trait loci (eQTLs) in nine tissues. We used T2D tissue-grouped variant sets as genetic instruments to conduct 2-Sample Mendelian Randomization (MR) in ten related outcomes whose risk is increased by T2D using the FinnGen cohort. We performed PheWAS analysis to investigate whether the T2D tissue-grouped variant sets had specific predicted disease signatures. We identified an average of 176 variants acting in nine tissues implicated in T2D, and an average of 30 variants acting on regulatory elements that are unique to the nine tissues of interest. In 2-Sample MR analyses, all subsets of regulatory variants acting in different tissues were associated with increased risk of the ten secondary outcomes studied on similar levels. No tissue-grouped variant set was associated with an outcome significantly more than other tissue-grouped variant sets. We did not identify different disease progression profiles based on tissue-specific regulatory and transcriptome information. Bigger sample sizes and other layers of regulatory information in critical tissues may help identify subsets of T2D variants that are implicated in certain secondary outcomes, uncovering system-specific disease progression.

Shared genetics of psychiatric disorders and type 2 diabetes:a large-scale genome-wide cross-trait analysis

BACKGROUND

Individuals with psychiatric disorders have elevated rates of type 2 diabetes comorbidity. Although little is known about the shared genetics and causality of this association. Thus, we aimed to investigate shared genetics and causal link between different type 2 diabetes and psychiatric disorders.

METHODS

We conducted a large-scale genome-wide cross-trait association study(GWAS) to investigate genetic overlap between type 2 diabetes and anorexia nervosa, attention deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, obsessive-compulsive disorder, schizophrenia, anxiety disorders and Tourette syndrome. By post-GWAS functional analysis, we identify variants genes expression in various tissues. Enrichment pathways, potential protein interaction and mendelian randomization also provided to research the relationship between type 2 diabetes and psychiatric disorders.

RESULTS

We discovered that type 2 diabetes and psychiatric disorders had a significant correlation. We identified 138 related loci, 32 were novel loci. Post-GWAS analysis revealed that 86 differentially expressed genes were located in different brain regions and peripheral blood in type 2 diabetes and related psychiatric disorders. MAPK signaling pathway plays an important role in neural development and insulin signaling. In addition, there is a causal relationship between T2D and mental disorders. In PPI analysis, the central genes of the DEG PPI network were FTO and TCF7L2.

CONCLUSION

This large-scale genome-wide cross-trait analysis identified shared genetics andpotential causal links between type 2 diabetes and related psychiatric disorders, suggesting potential new biological functions in common among them.

Association between psoriatic disease and lifestyle factors and comorbidities: cross-sectional analysis and Mendelian randomization

OBJECTIVES

To examine associations between PsA and psoriasis vs lifestyle factors and comorbidities by triangulating observational and genetic evidence.

METHODS

We analysed cross-sectional data from the UK Biobank (1836 PsA, 8995 psoriasis, 36 000 controls) to describe the association between psoriatic disease and lifestyle factors (including BMI and smoking) and 15 comorbidities [including diabetes and coronary artery disease (CAD)] using logistic models adjusted for age, sex and lifestyle factors. We applied bidirectional Mendelian randomization (MR) to genome-wide association data (3609 PsA and 7804 psoriasis cases, up to 1.2 million individuals for lifestyle factors and 757 601 for comorbidities) to examine causal direction, using the inverse-variance weighted method.

RESULTS

BMI was cross-sectionally associated with risk of PsA (OR 1.31 per 5 kg/m2 increase; 95% CI 1.26, 1.37) and psoriasis (OR 1.23; 1.20, 1.26), with consistent MR estimates (PsA OR 1.38; 1.14, 1.67; psoriasis OR 1.36; 1.18, 1.58). In both designs, smoking was more strongly associated with psoriasis than PsA. PsA and psoriasis were cross-sectionally associated with diabetes (OR 1.35 and 1.39, respectively) and CAD (OR 1.56 and 1.38, respective). Genetically predicted glycated haemoglobin (surrogate for diabetes) increased PsA risk (OR 1.18 per 6.7 mmol/mol increase; 1.02, 1.36) but not psoriasis. Genetic liability to PsA (OR 1.05; 1.003, 1.09) and psoriasis (OR 1.03; 1.001, 1.06) were associated with increased risk of CAD.

CONCLUSION

Observational and genetic evidence converge to suggest that BMI and glycaemic control are associated with increased psoriatic disease risk, while psoriatic disease is associated with increased CAD risk. Further research is needed to understand the mechanism of these associations.

A Mendelian Randomization Analysis Investigates Causal Associations between Inflammatory Bowel Diseases and Variable Risk Factors

The question of whether variable risk factors and various nutrients are causally related to inflammatory bowel diseases (IBDs) has remained unanswered so far. Thus, this study investigated whether genetically predicted risk factors and nutrients play a function in the occurrence of inflammatory bowel diseases, including ulcerative colitis (UC), non-infective colitis (NIC), and Crohn's disease (CD), using Mendelian randomization (MR) analysis. Utilizing the data of genome-wide association studies (GWASs) with 37 exposure factors, we ran Mendelian randomization analyses based on up to 458,109 participants. Univariable and multivariable MR analyses were conducted to determine causal risk factors for IBD diseases. Genetic predisposition to smoking and appendectomy as well as vegetable and fruit intake, breastfeeding, n-3 PUFAs, n-6 PUFAs, vitamin D, total cholesterol, whole-body fat mass, and physical activity were related to the risk of UC (p < 0.05). The effect of lifestyle behaviors on UC was attenuated after correcting for appendectomy. Genetically driven smoking, alcohol consumption, appendectomy, tonsillectomy, blood calcium, tea intake, autoimmune diseases, type 2 diabetes, cesarean delivery, vitamin D deficiency, and antibiotic exposure increased the risk of CD (p < 0.05), while vegetable and fruit intake, breastfeeding, physical activity, blood zinc, and n-3 PUFAs decreased the risk of CD (p < 0.05). Appendectomy, antibiotics, physical activity, blood zinc, n-3 PUFAs, and vegetable fruit intake remained significant predictors in multivariable MR (p < 0.05). Besides smoking, breastfeeding, alcoholic drinks, vegetable and fruit intake, vitamin D, appendectomy, and n-3 PUFAs were associated with NIC (p < 0.05). Smoking, alcoholic drinks, vegetable and fruit intake, vitamin D, appendectomy, and n-3 PUFAs remained significant predictors in multivariable MR (p < 0.05). Our results provide new and comprehensive evidence demonstrating that there are approving causal effects of various risk factors on IBDs. These findings also supply some suggestions for the treatment and prevention of these diseases.

FHL2 Genetic Polymorphisms and Pro-Diabetogenic Lipid Profile in the Multiethnic HELIUS Cohort

Type 2 diabetes mellitus (T2D) is a prevalent disease often accompanied by the occurrence of dyslipidemia. Four and a half LIM domains 2 (FHL2) is a scaffolding protein, whose involvement in metabolic disease has recently been demonstrated. The association of human FHL2 with T2D and dyslipidemia in a multiethnic setting is unknown. Therefore, we used the large multiethnic Amsterdam-based Healthy Life in an Urban Setting (HELIUS) cohort to investigate FHL2 genetic loci and their potential role in T2D and dyslipidemia. Baseline data of 10,056 participants from the HELIUS study were available for analysis. The HELIUS study contained individuals of European Dutch, South Asian Surinamese, African Surinamese, Ghanaian, Turkish, and Moroccan descent living in Amsterdam and were randomly sampled from the municipality register. Nineteen FHL2 polymorphisms were genotyped, and associations with lipid panels and T2D status were investigated. We observed that seven FHL2 polymorphisms associated nominally with a pro-diabetogenic lipid profile including triglyceride (TG), high-density and low-density lipoprotein-cholesterol (HDL-C and LDL-C), and total cholesterol (TC) concentrations, but not with blood glucose concentrations or T2D status in the complete HELIUS cohort upon correcting for age, gender, BMI, and ancestry. Upon stratifying for ethnicity, we observed that only two of the nominally significant associations passed multiple testing adjustments, namely, the association of rs4640402 with increased TG and rs880427 with decreased HDL-C concentrations in the Ghanaian population. Our results highlight the effect of ethnicity on pro-diabetogenic selected lipid biomarkers within the HELIUS cohort, as well as the need for more large multiethnic cohort studies.

Genome-wide genotype-serum proteome mapping provides insights into the cross-ancestry differences in cardiometabolic disease susceptibility

Identification of protein quantitative trait loci (pQTL) helps understand the underlying mechanisms of diseases and discover promising targets for pharmacological intervention. For most important class of drug targets, genetic evidence needs to be generalizable to diverse populations. Given that the majority of the previous studies were conducted in European ancestry populations, little is known about the protein-associated genetic variants in East Asians. Based on data-independent acquisition mass spectrometry technique, we conduct genome-wide association analyses for 304 unique proteins in 2,958 Han Chinese participants. We identify 195 genetic variant-protein associations. Colocalization and Mendelian randomization analyses highlight 60 gene-protein-phenotype associations, 45 of which (75%) have not been prioritized in Europeans previously. Further cross-ancestry analyses uncover key proteins that contributed to the differences in the obesity-induced diabetes and coronary artery disease susceptibility. These findings provide novel druggable proteins as well as a unique resource for the trans-ancestry evaluation of protein-targeted drug discovery.

Causal effects of serum testosterone levels on brain volume: a sex-stratified Mendelian randomization study

PURPOSE

To assess the causal effects of serum testosterone and sex hormone-binding globulin levels on brain volumetric measurements in women and men.

METHODS

We performed a sex-stratified two-sample Mendelian randomization study using the random-effects inverse variance-weighted method as the primary analysis method. Sex-specific genetic instruments were obtained from a study with up to 194,453 men and 230,454 women. For testosterone, variants with dominant effects on both total and bioavailable testosterone but no aggregate effect on sex hormone-binding globulin were used as the main genetic instruments. Sex-specific summary-level data for magnetic resonance imaging brain volumetric measurements were obtained from a study with 11,624 women and 10,514 men.

RESULTS

Analyses showed per standard deviation (approximately 3.7 nmol/L) higher testosterone levels in men were suggestively associated with larger gray matter volume (beta = 0.208, 95% confidence interval = 0.067 to 0.349, p = 0.004). The association remained in sensitivity analyses and multivariable analyses. Further analyses showed the effect was mainly act on peripheral cortical gray matter, but not on subcortical gray matter. Testosterone in men was not associated with hippocampal volume. Testosterone in women and sex hormone binding globulin in both sexes had no effect on all outcomes.

CONCLUSION

Our findings overall support previous evidence that testosterone might have neuroprotective properties in elderly men. Future larger trials with long duration of intervention are warranted to assess the efficacy of testosterone for elderly men with cognitive impairment, especially in those with hypoandrogenism.

Genetic Predisposition to a Higher Whole Body Water Mass May Increase the Risk of Atrial Fibrillation: A Mendelian Randomization Study

BACKGROUND

Observational studies have found an association between increased whole body water mass (BWM) and atrial fibrillation (AF). However, the causality has yet to be confirmed. To provide feasible protective measures on disease development, we performed Mendelian randomization (MR) design to estimate the potential causal relationship between increased BWM and AF.

METHODS

We implemented a two-sample MR study to assess whether increased BWM causally influences AF incidence. For exposure, 61 well-powered genetic instruments extracted from UK Biobank (N = 331,315) were used as the proxies of BWM. Summary genetic data of AF were obtained from FinnGen (Ncase = 22,068; Ncontrol = 116,926). Inverse-variance weighted (IVW), MR-Egger and weighted median methods were selected to infer causality, complemented with a series of sensitivity analyses. MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) and Radial MR were employed to identify outliers. Furthermore, risk factor analyses were performed to investigate the potential mechanisms between increased BWM and AF.

RESULTS

Genetic predisposition to increased BWM was demonstrated to be significantly associated with AF in the IVW model (OR = 2.23; 95% CI = 1.47-3.09; p = 1.60 × 10^-7), and the result was consistent in other MR approaches. There was no heterogeneity or pleiotropy detected in sensitivity analysis. MR-PRESSO identified no outliers with potential pleiotropy after excluding outliers by Radial MR. Furthermore, our risk factor analyses supported a positive causal effect of genetic predicted increased BWM on edematous diseases.

CONCLUSIONS

MR estimates showed that a higher BWM could increase the risk of AF. Pathological edema is an important intermediate link mediating this causal relationship.

Metabolic Signatures Elucidate the Effect of Body Mass Index on Type 2 Diabetes

Obesity plays an important role in the development of insulin resistance and diabetes, but the molecular mechanism that links obesity and diabetes is still not completely understood. Here, we used 146 targeted metabolomic profiles from the German KORA FF4 cohort consisting of 1715 participants and associated them with obesity and type 2 diabetes. In the basic model, 83 and 51 metabolites were significantly associated with body mass index (BMI) and T2D, respectively. Those metabolites are branched-chain amino acids, acylcarnitines, lysophospholipids, or phosphatidylcholines. In the full model, 42 and 3 metabolites were significantly associated with BMI and T2D, respectively, and replicate findings in the previous studies. Sobel mediation testing suggests that the effect of BMI on T2D might be mediated via lipids such as sphingomyelin (SM) C16:1, SM C18:1 and diacylphosphatidylcholine (PC aa) C38:3. Moreover, mendelian randomization suggests a causal relationship that BMI causes the change of SM C16:1 and PC aa C38:3, and the change of SM C16:1, SM C18:1, and PC aa C38:3 contribute to T2D incident. Biological pathway analysis in combination with genetics and mice experiments indicate that downregulation of sphingolipid or upregulation of phosphatidylcholine metabolism is a causal factor in early-stage T2D pathophysiology. Our findings indicate that metabolites like SM C16:1, SM C18:1, and PC aa C38:3 mediate the effect of BMI on T2D and elucidate their role in obesity related T2D pathologies.

Inflammatory and immune etiology of type 2 diabetes

Type 2 diabetes (T2D) represents a global threat affecting millions of patients worldwide. However, its causes remain incompletely dissected and we lack the tools to predict which individuals will develop T2D. Although there is a clear proven clinical association of T2D with metabolic disorders such as obesity and nonalcoholic fatty liver disease (NAFLD), the existence of a significant number of nondiabetic obese subjects suggests yet-uncovered features of such relationships. Here, we propose that a significant proportion of individuals may harbor an immune profile that renders them susceptible to developing T2D. We note the heterogeneity of circulating monocytes and tissue macrophages in organs that are key to metabolic disorders such as liver, white adipose tissue (WAT), and endocrine pancreas, as well as their contribution to T2D genesis.

A Guide for Selection of Genetic Instruments in Mendelian Randomization Studies of Type 2 Diabetes and HbA1c: Toward an Integrated Approach

In this study we examine the instrument selection strategies currently used throughout the type 2 diabetes and HbA1c Mendelian randomization (MR) literature. We then argue for a more integrated and thorough approach, providing a framework to do this in the context of HbA1c and diabetes. We conducted a literature search for MR studies that have instrumented diabetes and/or HbA1c. We also used data from the UK Biobank (UKB) (N = 349,326) to calculate instrument strength metrics that are key in MR studies (the F statistic for average strength and R2 for total strength) with two different methods ("individual-level data regression" and Cragg-Donald formula). We used a 157-single nucleotide polymorphism (SNP) instrument for diabetes and a 51-SNP instrument (with partition into glycemic and erythrocytic as well) for HbA1c. Our literature search yielded 48 studies for diabetes and 22 for HbA1c. Our UKB empirical examples showed that irrespective of the method used to calculate metrics of strength and whether the instrument was the main one or included partition by function, the HbA1c genetic instrument is strong in terms of both average and total strength. For diabetes, a 157-SNP instrument was shown to have good average strength and total strength, but these were both substantially lesser than those of the HbA1c instrument. We provide a careful set of five recommendations to researchers who wish to genetically instrument type 2 diabetes and/or HbA1c. In MR studies of glycemia, investigators should take a more integrated approach when selecting genetic instruments, and we give specific guidance on how to do this.

The Variants in ADIPOQ are Associated with Maternal Circulating Adipokine Profile in Gestational Diabetes Mellitus

Background

Gestational diabetes mellitus (GDM) is the most common association with hyperglycemia and glucose intolerance during pregnancy. The adipokines play an important to control insulin secretion and glucose. This study aimed to investigate the association between maternal circulating adipokine levels and ADIPOQ gene polymorphism among pregnant women subjects with GDM and normal glucose tolerance (NGT).

Methods

Participants including 229 normal pregnant women and 197 GDM pregnant women were enrolled from 2015 to 2018 at Siriraj hospital. Serum adipokine levels including adiponectin, adipsin/factor D, NGAL/Lipocalin-2, total PAI-1, and resistin were measured by immunoassay. ADIPOQ variations were investigated including -11377C/G (rs266729), +45T/G (rs2241766), and +276G/T (rs1501299).

Results

Serum adiponectin concentration was also significantly decreased among the GDM who had aged less than 35 years old whereas adipsin levels were significantly lower among the GDM who had aged more than 35 years old. Also, adiponectin and total PAI-1 levels were significantly lower among the GDM who had a BMI of less than 30 kg/m². The G allele frequency of ADIPOQ +45T/G was significantly different between GDM and controls (p = 0.03). ADIPOQ +45T/G was associated with an increased risk of GDM (odds ratio [OR]: 1.554; 95% confidence interval [CI]: 1.010-2.390; p=0.045). The -11377C/G was affected by the level of adiponectin (p = 0.04). The C allele of -11377C/G SNP declined serum adiponectin levels and may be a risk factor for GDM.

Conclusion

This study revealed that genetics play important roles in circulating adipokines among pregnant women. ADIPOQ polymorphisms had significant associations with adiponectin levels in GDM patients.

Blood transcriptomic biomarkers of alcohol consumption and cardiovascular disease risk factors: the Framingham Heart Study

BACKGROUND

The relations of alcohol consumption and gene expression remain to be elucidated.

MATERIALS AND METHODS

We examined cross-sectional associations between alcohol consumption and whole blood derived gene expression levels and between alcohol-associated genes and obesity, hypertension, and diabetes in 5531 Framingham Heart Study (FHS) participants.

RESULTS

We identified 25 alcohol-associated genes. We further showed cross-sectional associations of 16 alcohol-associated genes with obesity, nine genes with hypertension, and eight genes with diabetes at P < 0.002. For example, we observed decreased expression of PROK2 (β = -0.0018; 95%CI: -0.0021, -0.0007; P = 6.5e - 5) and PAX5 (β = -0.0014; 95%CI: -0.0021, -0.0007; P = 6.5e - 5) per 1 g/day increase in alcohol consumption. Consistent with our previous observation on the inverse association of alcohol consumption with obesity and positive association of alcohol consumption with hypertension, we found that PROK2 was positively associated with obesity (OR = 1.42; 95%CI: 1.17, 1.72; P = 4.5e - 4) and PAX5 was negatively associated with hypertension (OR = 0.73; 95%CI: 0.59, 0.89; P = 1.6e - 3). We also observed that alcohol consumption was positively associated with expression of ABCA13 (β = 0.0012; 95%CI: 0.0007, 0.0017; P = 1.3e - 6) and ABCA13 was positively associated with diabetes (OR = 2.57; 95%CI: 1.73, 3.84; P = 3.5e - 06); this finding, however, was inconsistent with our observation of an inverse association between alcohol consumption and diabetes.

CONCLUSIONS

We showed strong cross-sectional associations between alcohol consumption and expression levels of 25 genes in FHS participants. Nonetheless, complex relationships exist between alcohol-associated genes and CVD risk factors.

Integration of transcriptome sequencing and whole genome resequencing reveal candidate genes in egg production of upright and pendulous-comb chickens

Egg production performance plays an important role in the poultry industry across the world. Previous studies have shown a great difference in egg production performance between pendulous-comb (PC) and upright-comb (UC) chickens. However, there are no reports to identify potential candidate genes for egg production in PC and UC chickens. In the present study, 1,606 laying chickens were raised, and the egg laid by individual chicken was collected for 100 d. Moreover, the expression level of estrogen and progesterone hormones was measured at the start-laying and peak-laying periods of hens. Besides, 4 PC and 4 UC chickens were selected at 217 d of age to perform transcriptome sequencing (RNA-seq) and whole genome resequencing (WGS) to screen the potential candidate genes of egg production. The results showed that PC chicken demonstrated better egg production performance (P < 0.05) and higher estrogen and progesterone hormone expression levels than UC chicken (P < 0.05). RNA-seq analysis showed that 341 upregulated and 1,036 downregulated differentially expressed genes (DEGs) were identified in the ovary tissues of PC and UC chickens. These DEGs were mainly enriched in protein-related, lipid-related, and nucleic acids-related biological processes including ribosome, peptide biosynthetic process, lipid transport terms, and catalytic activity acting on RNA which can significantly affect egg production in chicken. The enrichment results of WGS analysis were consistent with RNA-seq. Further, joint analysis of WGS and RNA-seq data was utilized to screen 30 genes and CAMK1D, CLSTN2, MAST2, PIK3C2G, TBC1D1, STK3, ADGRB3, and PPARGC1A were identified as potential candidate genes for egg production in PC and UC chickens. In summary, our study provides a wealth of information for a better understanding of the genetic and molecular mechanism for the future breeding of PC and UC chickens for egg production.

Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.

Appraising the Effects of Metabolic Traits on the Risk of Glaucoma: A Mendelian Randomization Study

Metabolic traits are associated with the risk of developing glaucoma in observational studies. To assess whether theses associations reflect causality, we conducted a Mendelian randomization (MR) study. Our study included up to 20,906 glaucoma cases and 438,188 controls. Genetic instruments associated with the concerned 11 exposures at the genome-wide significance level were selected from corresponding genome-wide association studies. Summary-level data for glaucoma were obtained from the UK Biobank, the GERA study, and the FinnGen consortium. Univariable and multivariable MR analyses were conducted separately in two populations. Our results showed that higher genetic liability to type 2 diabetes (T2D) was causally and independently associated with an increased risk of glaucoma (odds ratio [OR], 1.11; 95% confidence interval [CI], 1.06-1.16; p = 4.4 × 10-6). The association for T2D persisted after multivariable adjustment. In addition, higher genetically predicted systolic blood pressure (SBP), fasting glucose (FG), and HbA1c, were also suggestively associated with glaucoma risk. The OR was 1.08 (95% CI, 1.01-1.16; p = 0.035) for SBP, 1.24 (95% CI, 1.05-1.47; p = 0.011) for FG, and 1.28 (95% CI, 1.01-1.61; p = 0.039) for HbA1c. No evidence was observed to support the causal effects of body mass index and blood lipids for glaucoma. This study suggests a causal role for diabetes, as well as possible roles for higher SBP, FG, and HbA1c in the development of glaucoma. Further validation is needed to assess the potential of these risk factors as pharmacological targets for glaucoma prevention.

Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes

We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, P_FDR = 3.40 × 10^-5), CCR5 rs333 (OR = 1.99, P_FDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, P_FDR = 2.64 × 10^-4), TCF7L2 rs114758349 (OR = 1.77, P_FDR = 9.37 × 10^-5), and CCL2 rs1024611 (OR = 1.38, P_FDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7-87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 × 10^-6). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = -17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.

E96V Mutation in the Kdelr3 Gene Is Associated with Type 2 Diabetes Susceptibility in Obese NZO Mice

Type 2 diabetes (T2D) represents a multifactorial metabolic disease with a strong genetic predisposition. Despite elaborate efforts in identifying the genetic variants determining individual susceptibility towards T2D, the majority of genetic factors driving disease development remain poorly understood. With the aim to identify novel T2D risk genes we previously generated an N2 outcross population using the two inbred mouse strains New Zealand obese (NZO) and C3HeB/FeJ (C3H). A linkage study performed in this population led to the identification of the novel T2D-associated quantitative trait locus (QTL) Nbg15 (NZO blood glucose on chromosome 15, Logarithm of odds (LOD) 6.6). In this study we used a combined approach of positional cloning, gene expression analyses and in silico predictions of DNA polymorphism on gene/protein function to dissect the genetic variants linking Nbg15 to the development of T2D. Moreover, we have generated congenic strains that associated the distal sublocus of Nbg15 to mechanisms altering pancreatic beta cell function. In this sublocus, Cbx6, Fam135b and Kdelr3 were nominated as potential causative genes associated with the Nbg15 driven effects. Moreover, a putative mutation in the Kdelr3 gene from NZO was identified, negatively influencing adaptive responses associated with pancreatic beta cell death and induction of endoplasmic reticulum stress. Importantly, knockdown of Kdelr3 in cultured Min6 beta cells altered insulin granules maturation and pro-insulin levels, pointing towards a crucial role of this gene in islets function and T2D susceptibility.

Proteomic analysis of diabetes genetic risk scores identifies complement C2 and neuropilin-2 as predictors of type 2 diabetes: the Atherosclerosis Risk in Communities (ARIC) Study

AIMS/HYPOTHESIS

Genetic predisposition to type 2 diabetes is well-established, and genetic risk scores (GRS) have been developed that capture heritable liabilities for type 2 diabetes phenotypes. However, the proteins through which these genetic variants influence risk have not been thoroughly investigated. This study aimed to identify proteins and pathways through which type 2 diabetes risk variants may influence pathophysiology.

METHODS

Using a proteomics data-driven approach in a discovery sample of 7241 White participants in the Atherosclerosis Risk in Communities Study (ARIC) cohort and a replication sample of 1674 Black ARIC participants, we interrogated plasma levels of 4870 proteins and four GRS of specific type 2 diabetes phenotypes related to beta cell function, insulin resistance, lipodystrophy, BMI/blood lipid abnormalities and a composite score of all variants combined.

RESULTS

Twenty-two plasma proteins were identified in White participants after Bonferroni correction. Of the 22 protein-GRS associations that were statistically significant, 10 were replicated in Black participants and all but one were directionally consistent. In a secondary analysis, 18 of the 22 proteins were found to be associated with prevalent type 2 diabetes and ten proteins were associated with incident type 2 diabetes. Two-sample Mendelian randomisation indicated that complement C2 may be causally related to greater type 2 diabetes risk (inverse variance weighted estimate: OR 1.65 per SD; p=7.0 × 10-3), while neuropilin-2 was inversely associated (OR 0.44 per SD; p=8.0 × 10-3).

CONCLUSIONS/INTERPRETATION

Identified proteins may represent viable intervention or pharmacological targets to prevent, reverse or slow type 2 diabetes progression, and further research is needed to pursue these targets.

Diabetes and intervertebral disc degeneration: A Mendelian randomization study

INTRODUCTION

Intervertebral disc degeneration (IVDD) is an important contributor of low back pain, which represents one of the most disabling symptoms within the adult population. Recently, increasing evidence suggests the potential association between Type 2 diabetes mellitus (T2DM) and IVDD. However, the causal relationship between these two common diseases remains unclear.

METHODS

We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal association between T2DM and IVDD. Sensitivity analysis was performed to test for heterogeneity and horizontal pleiotropy. Multivariable MR was also conducted to adjust for the effect of BMI on IVDD.

RESULTS

A total of 128 independent single-nucleotide polymorphisms (SNPs) that were significantly associated with T2DM were selected as instrumental variables in univariable MR analysis. Our results showed that patients with T2DM had a higher risk of developing IVDD (OR, 1.069; 95% CI, 1.026-1.115; p = 0.002). The relationship remained stable in sensitive analysis including multivariable MR, which implicated the direct causal effect of T2DM on IVDD (OR, 1.080; 95% CI, 1.041-1.121; p < 0.001) after adjusting for BMI.

CONCLUSIONS

MR analysis indicated a causal effect of T2DM on IVDD, and the effect persisted even when we accounted for the impact of BMI.

Investigating the association between fasting insulin, erythrocytosis and HbA1c through Mendelian randomization and observational analyses

BACKGROUND

Insulin resistance (IR) with associated compensatory hyperinsulinemia (HI) are early abnormalities in the etiology of prediabetes (preT2D) and type 2 diabetes (T2D). IR and HI also associate with increased erythrocytosis. Hemoglobin A1c (HbA1c) is commonly used to diagnose and monitor preT2D and T2D, but can be influenced by erythrocytosis independent of glycemia.

METHODS

We undertook bidirectional Mendelian randomization (MR) in individuals of European ancestry to investigate potential causal associations between increased fasting insulin adjusted for BMI (FI), erythrocytosis and its non-glycemic impact on HbA1c. We investigated the association between the triglyceride-glucose index (TGI), a surrogate measure of IR and HI, and glycation gap (difference between measured HbA1c and predicted HbA1c derived from linear regression of fasting glucose) in people with normoglycemia and preT2D.

RESULTS

Inverse variance weighted MR (IVWMR) suggested that increased FI increases hemoglobin (Hb, b=0.54 ± 0.09, p=2.7 x 10^-10), red cell count (RCC, b=0.54 ± 0.12, p=5.38x10^-6) and reticulocyte (RETIC, b=0.70 ± 0.15, p=2.18x10^-6). Multivariable MR indicated that increased FI did not impact HbA1c (b=0.23 ± 0.16, p=0.162) but reduced HbA1c after adjustment for T2D (b=0.31 ± 0.13, p=0.016). Increased Hb (b=0.03 ± 0.01, p=0.02), RCC (b=0.02 ± 0.01, p=0.04) and RETIC (b=0.03 ± 0.01, p=0.002) might modestly increase FI. In the observational cohort, increased TGI associated with decreased glycation gap, (i.e., measured HbA1c was lower than expected based on fasting glucose, (b=-0.09 ± 0.009, p<0.0001)) in people with preT2D but not in those with normoglycemia (b=0.02 ± 0.007, p<0.0001).

CONCLUSIONS

MR suggests increased FI increases erythrocytosis and might potentially decrease HbA1c by non-glycemic effects. Increased TGI, a surrogate measure of increased FI, associates with lower-than-expected HbA1c in people with preT2D. These findings merit confirmatory studies to evaluate their clinical significance.

Sleep traits, fat accumulation, and glycemic traits in relation to gastroesophageal reflux disease: A Mendelian randomization study

Background

Sleep traits, fat accumulation, and glycemic traits are associated with gastroesophageal reflux disease (GERD) in observational studies. However, whether their associations are causal remains unknown. We performed a Mendelian randomization (MR) study to determine these causal relationships.

Methods

Independent genetic variants associated with insomnia, sleep duration, short sleep duration, body fat percentage, visceral adipose tissue (VAT) mass, type 2 diabetes, fasting glucose, and fasting insulin at the genome-wide significance level were selected as instrumental variables. Summary-level data for GERD were derived from a genome-wide association meta-analysis including 78,707 cases and 288,734 controls of European descent. Inverse variance weighted (IVW) was used for the main analysis, with weighted median and MR-Egger as complements to IVW. Sensitivity analyses were performed using Cochran's Q test, MR-Egger intercept test, and leave-one-out analysis to estimate the stability of the results.

Results

The MR study showed the causal relationships of genetically predicted insomnia (odds ratio [OR] = 1.306, 95% confidence interval [CI] 1.261 to 1.352; p = 2.24 × 10^-51), short sleep duration (OR = 1.304, 95% CI: 1.147 to 1.483, p = 4.83 × 10^-5), body fat percentage (OR = 1.793, 95% CI 1.496 to 2.149; p = 2.68 × 10^-10), and visceral adipose tissue (OR = 2.090, 95% CI 1.963 to 2.225; p = 4.42 × 10^-117) with the risk of GERD. There was little evidence for causal associations between genetically predicted glycemic traits and GERD. In multivariable analyses, genetically predicted VAT accumulation, insomnia, and decreased sleep duration were associated with an increased risk of GERD.

Conclusion

This study suggests the possible roles of insomnia, short sleep, body fat percentage, and visceral adiposity in the development of GERD.

Association of the gut microbiota with coronary artery disease and myocardial infarction: A Mendelian randomization study

Background: Previous studies have indicated that the gut microbiota (GM) is associated with coronary artery disease (CAD), but the causality of these associations remains unestablished due to confounding factors and reverse causality. We conducted Mendelian randomization study (MR) to determine the causal effect of the specific bacterial taxa on CAD/myocardial infarction (MI) and identify the mediating factors involved. Methods: Two-sample MR, multivariable MR (MVMR) and mediation analysis were performed. Inverse-variance weighting (IVW) was the main method used to analyze causality, and sensitivity analysis was used to verify the reliability of the study. Causal estimates from CARDIoGRAMplusC4D and FinnGen databases were combined using the meta-analysis method, and repeated validation was conducted based on the UK Biobank (UKB) database. Confounders that may affect the causal estimates were corrected by MVMP and the potential mediation effects were investigated by using mediation analysis. Results: The study suggested that increased abundance of the RuminococcusUCG010 genus leads to a lower risk of CAD (OR, 0.88; 95% CI, 0.78, 1.00; p = 2.88 × 10^-2) and MI (OR, 0.88; 95% CI, 0.79, 0.97; p = 1.08 × 10^-2), with consistent results in both meta-analysis (CAD: OR, 0.86; 95% CI, 0.78, 0.96; p = 4.71 × 10^-3; MI: OR, 0.82; 95% CI, 0.73, 0.92; p = 8.25 × 10^-4) and repeated analysis of the UKB dataset (CAD: OR, 0.99; 95% CI, 0.99, 1.00, p = 2.53 × 10^-4; MI: OR, 0.99; 95% CI, 0.99, 1.00, p = 1.85 × 10-11). Based on multiple databases, T2DM was proved as a mediating factor in the causal effect of RuminococcusUCG010 and CAD/MI, with an average mediation effect proportion of 20% on CAD and 17% on MI, respectively. Conclusion: This MR study provided suggestive genetic evidence that the higher the RuminococcusUCG010 abundance is, the lower the risk of CAD and MI, with T2DM playing a mediating effect. This genus may become a novel target in strategies for treating and preventing CAD and MI.

Genetically predicted body selenium concentration and eGFR: A Mendelian randomization study

Introduction

Selenium is a trace mineral that is commonly included in micronutrient supplements. The effect of selenium on kidney function remains unclear. A genetically predicted micronutrient and its association with estimated glomerular filtration rate (eGFR) can be used to assess the causal estimates by Mendelian randomization (MR).

Methods

In this MR study, we instrumented 11 genetic variants associated with blood or total selenium levels from a previous genome-wide association study (GWAS). The association between genetically predicted selenium concentration and eGFR was first assessed by summary-level MR in the chronic kidney disease(CKDGen) GWAS meta-analysis summary statistics, including 567,460 European samples. Inverse-variance weighted and pleiotropy-robust MR analyses were performed, in addition to multivariable MR adjusted for the effects of type 2 diabetes mellitus. Replication analysis was performed with individual-level UK Biobank data, including 337,318 White individuals of British ancestry.

Results

Summary-level MR analysis indicated that a genetically predicted 1 SD increase in selenium concentration was significantly associated with lower eGFR (-1.05 [-1.28, -0.82] %). The results were similarly reproduced by pleiotropy-robust MR analysis, including MR-Egger and weighted-median methods, and consistent even in the multivariable MR adjusted for diabetes. In the UK Biobank data, genetically predicted higher selenium concentration was also significantly associated with lower eGFR (- 0.36 [-0.52, -0.20] %), and the results were similar when body mass index, waist circumference, hypertension, and diabetes mellitus covariates were adjusted (-0.33 [-0.50, -0.17] %).

Conclusion

This MR study supports the hypothesis that higher genetically predicted body selenium is causally associated with lower eGFR.

Mendelian randomization reveals no associations of genetically-predicted obstructive sleep apnea with the risk of type 2 diabetes, nonalcoholic fatty liver disease, and coronary heart disease

BACKGROUND

Obstructive sleep apnea (OSA) has been reported to affect cardiometabolic diseases. However, whether such association is causal is still unknown. Here, we attempt to explore the effect of OSA on type 2 diabetes (T2D), nonalcoholic fatty liver disease (NAFLD) and coronary heart disease (CHD).

METHODS

Genetic variants associated with OSA were requested from a published genome-wide association study (GWAS) and those qualified ones were selected as instrumental variables (IV). Then, the IV-outcome associations were acquired from T2D, NAFLD and CHD GWAS consortia separately. The Mendelian randomization (MR) was designed to estimate the associations of genetically-predicted OSA on T2D, NAFLD and CHD respectively, using the inverse-variance weighted (IVW) method. We applied the Bonferroni method to adjust the p-value. Besides, MR-Egger regression and weighted median methods were adopted as a supplement to IVW. The Cochran's Q value was used to evaluate heterogeneity and the MR-Egger intercept was utilized to assess horizontal pleiotropy, together with MR-PRESSO. The leave-one-out sensitivity analysis was carried out as well.

RESULTS

No MR estimate reached the Bonferroni threshold (p < 0.017). Although the odds ratio of T2D was 3.58 (95% confidence interval (CI) [1.06, 12.11], IVW-p-value = 0.040) using 4 SNPs, such causal association turned insignificant after the removal of SNP rs9937053 located in FTO [OR = 1.30 [0.68, 2.50], IVW p = 0.432]. Besides, we did not find that the predisposition to OSA was associated with CHD [OR = 1.16 [0.70, 1.91], IVW p = 0.560] using 4 SNPs.

CONCLUSION

This MR study reveals that genetic liability to OSA might not be associated with the risk of T2D after the removal of obesity-related instruments. Besides, no causal association was observed between NAFLD and CHD. Further studies should be carried out to verify our findings.

Evolution of the diagnostic value of "the sugar of the blood": hitting the sweet spot to identify alterations in glucose dynamics

In this paper, we provide an overview of the evolution of the definition of hyperglycemia during the past century and the alterations in glucose dynamics that cause fasting and postprandial hyperglycemia. We discuss how extensive mechanistic, physiological research into the factors and pathways that regulate the appearance of glucose in the circulation and its uptake and metabolism by tissues and organs has contributed knowledge that has advanced our understanding of different types of hyperglycemia, namely prediabetes and diabetes and their subtypes (impaired fasting plasma glucose, impaired glucose tolerance, combined impaired fasting plasma glucose, impaired glucose tolerance, type 1 diabetes, type 2 diabetes, gestational diabetes mellitus), their relationships with medical complications, and how to prevent and treat hyperglycemia.

DNA methylation trajectories and accelerated epigenetic aging in incident type 2 diabetes

DNA methylation (DNAm) patterns across the genome changes during aging and development of complex diseases including type 2 diabetes (T2D). Our study aimed to estimate DNAm trajectories of CpG sites associated with T2D, epigenetic age (DNAmAge), and age acceleration based on four epigenetic clocks (GrimAge, Hannum, Horvath, phenoAge) in the period 10 years prior to and up to T2D onset. In this nested case-control study within Doetinchem Cohort Study, we included 132 incident T2D cases and 132 age- and sex-matched controls. DNAm was measured in blood using the Illumina Infinium Methylation EPIC array. From 107 CpG sites associated with T2D, 10 CpG sites (9%) showed different slopes of DNAm trajectories over time (p < 0.05) and an additional 8 CpG sites (8%) showed significant differences in DNAm levels (at least 1%, p-value per time point < 0.05) at all three time points with nearly parallel trajectories between incident T2D cases and controls. In controls, age acceleration levels were negative (slower epigenetic aging), while in incident T2D cases, levels were positive, suggesting accelerated aging in the case group. We showed that DNAm levels at specific CpG sites, up to 10 years before T2D onset, are different between incident T2D cases and healthy controls and distinct patterns of clinical traits over time may have an impact on those DNAm profiles. Up to 10 years before T2D diagnosis, cases manifested accelerated epigenetic aging. Markers of biological aging including age acceleration estimates based on Horvath need further investigation to assess their utility for predicting age-related diseases including T2D.

The impact of fatty acids biosynthesis on the risk of cardiovascular diseases in Europeans and East Asians: a Mendelian randomization study

Despite early interest, the evidence linking fatty acids to cardiovascular diseases (CVDs) remains controversial. We used Mendelian randomization to explore the involvement of polyunsaturated (PUFA) and monounsaturated (MUFA) fatty acids biosynthesis in the etiology of several CVD endpoints in up to 1 153 768 European (maximum 123 668 cases) and 212 453 East Asian (maximum 29 319 cases) ancestry individuals. As instruments, we selected single nucleotide polymorphisms mapping to genes with well-known roles in PUFA (i.e. FADS1/2 and ELOVL2) and MUFA (i.e. SCD) biosynthesis. Our findings suggest that higher PUFA biosynthesis rate (proxied by rs174576 near FADS1/2) is related to higher odds of multiple CVDs, particularly ischemic stroke, peripheral artery disease and venous thromboembolism, whereas higher MUFA biosynthesis rate (proxied by rs603424 near SCD) is related to lower odds of coronary artery disease among Europeans. Results were unclear for East Asians as most effect estimates were imprecise. By triangulating multiple approaches (i.e. uni-/multi-variable Mendelian randomization, a phenome-wide scan, genetic colocalization and within-sibling analyses), our results are compatible with higher low-density lipoprotein (LDL) cholesterol (and possibly glucose) being a downstream effect of higher PUFA biosynthesis rate. Our findings indicate that PUFA and MUFA biosynthesis are involved in the etiology of CVDs and suggest LDL cholesterol as a potential mediating trait between PUFA biosynthesis and CVDs risk.

Deconstructing a Syndrome: Genomic Insights Into PCOS Causal Mechanisms and Classification

Polycystic ovary syndrome (PCOS) is among the most common disorders in women of reproductive age, affecting up to 15% worldwide, depending on the diagnostic criteria. PCOS is characterized by a constellation of interrelated reproductive abnormalities, including disordered gonadotropin secretion, increased androgen production, chronic anovulation, and polycystic ovarian morphology. It is frequently associated with insulin resistance and obesity. These reproductive and metabolic derangements cause major morbidities across the lifespan, including anovulatory infertility and type 2 diabetes (T2D). Despite decades of investigative effort, the etiology of PCOS remains unknown. Familial clustering of PCOS cases has indicated a genetic contribution to PCOS. There are rare Mendelian forms of PCOS associated with extreme phenotypes, but PCOS typically follows a non-Mendelian pattern of inheritance consistent with a complex genetic architecture, analogous to T2D and obesity, that reflects the interaction of susceptibility genes and environmental factors. Genomic studies of PCOS have provided important insights into disease pathways and have indicated that current diagnostic criteria do not capture underlying differences in biology associated with different forms of PCOS. We provide a state-of-the-science review of genetic analyses of PCOS, including an overview of genomic methodologies aimed at a general audience of non-geneticists and clinicians. Applications in PCOS will be discussed, including strengths and limitations of each study. The contributions of environmental factors, including developmental origins, will be reviewed. Insights into the pathogenesis and genetic architecture of PCOS will be summarized. Future directions for PCOS genetic studies will be outlined.

Insight into genetic, biological, and environmental determinants of sexual-dimorphism in type 2 diabetes and glucose-related traits

There is growing evidence that sex and gender differences play an important role in risk and pathophysiology of type 2 diabetes (T2D). Men develop T2D earlier than women, even though there is more obesity in young women than men. This difference in T2D prevalence is attenuated after the menopause. However, not all women are equally protected against T2D before the menopause, and gestational diabetes represents an important risk factor for future T2D. Biological mechanisms underlying sex and gender differences on T2D physiopathology are not yet fully understood. Sex hormones affect behavior and biological changes, and can have implications on lifestyle; thus, both sex-specific environmental and biological risk factors interact within a complex network to explain the differences in T2D risk and physiopathology in men and women. In addition, lifetime hormone fluctuations and body changes due to reproductive factors are generally more dramatic in women than men (ovarian cycle, pregnancy, and menopause). Progress in genetic studies and rodent models have significantly advanced our understanding of the biological pathways involved in the physiopathology of T2D. However, evidence of the sex-specific effects on genetic factors involved in T2D is still limited, and this gap of knowledge is even more important when investigating sex-specific differences during the life course. In this narrative review, we will focus on the current state of knowledge on the sex-specific effects of genetic factors associated with T2D over a lifetime, as well as the biological effects of these different hormonal stages on T2D risk. We will also discuss how biological insights from rodent models complement the genetic insights into the sex-dimorphism effects on T2D. Finally, we will suggest future directions to cover the knowledge gaps.

Inflammatory Cytokines Rewire the Proinsulin Interaction Network in Human Islets

CONTEXT

Aberrant biosynthesis and secretion of the insulin precursor proinsulin occurs in both type I and type II diabetes. Inflammatory cytokines are implicated in pancreatic islet stress and dysfunction in both forms of diabetes, but the mechanisms remain unclear.

OBJECTIVE

We sought to determine the effect of the diabetes-associated cytokines on proinsulin folding, trafficking, secretion, and β-cell function.

METHODS

Human islets were treated with interleukin-1β and interferon-γ for 48 hours, followed by analysis of interleukin-6, nitrite, proinsulin and insulin release, RNA sequencing, and unbiased profiling of the proinsulin interactome by affinity purification-mass spectrometry.

RESULTS

Cytokine treatment induced secretion of interleukin-6, nitrites, and insulin, as well as aberrant release of proinsulin. RNA sequencing showed that cytokines upregulated genes involved in endoplasmic reticulum stress, and, consistent with this, affinity purification-mass spectrometry revealed cytokine induced proinsulin binding to multiple endoplasmic reticulum chaperones and oxidoreductases. Moreover, increased binding to the chaperone immunoglobulin binding protein was required to maintain proper proinsulin folding in the inflammatory environment. Cytokines also regulated novel interactions between proinsulin and type 1 and type 2 diabetes genome-wide association studies candidate proteins not previously known to interact with proinsulin (eg, Ataxin-2). Finally, cytokines induced proinsulin interactions with a cluster of microtubule motor proteins and chemical destabilization of microtubules with Nocodazole exacerbated cytokine induced proinsulin secretion.

CONCLUSION

Together, the data shed new light on mechanisms by which diabetes-associated cytokines dysregulate β-cell function. For the first time, we show that even short-term exposure to an inflammatory environment reshapes proinsulin interactions with critical chaperones and regulators of the secretory pathway.

Shared genetic mechanism between type 2 diabetes and COVID-19 using pathway-based association analysis

Recent studies have shown that, compared with healthy individuals, patients with type 2 diabetes (T2D) suffer a higher severity and mortality of COVID-19. When infected with this retrovirus, patients with T2D are more likely to face severe complications from cytokine storms and be admitted to high-dependency or intensive care units. Some COVID-19 patients are known to suffer from various forms of acute respiratory distress syndrome and have a higher mortality risk due to extreme activation of inflammatory cascades. Using a conditional false discovery rate statistical framework, an independent genome-wide association study data on individuals presenting with T2D (N = 62,892) and COVID-19 (N = 38,984) were analysed. Genome-wide association study data from 2,343,084 participants were analysed and a significant positive genetic correlation between T2D and COVID-19 was observed (T2D: r for genetic = 0.1511, p-value = 0.01). Overall, 2 SNPs (rs505922 and rs3924604) shared in common between T2D and COVID-19 were identified. Functional analyses indicated that the overlapping loci annotated into the ABO and NUS1 genes might be implicated in several key metabolic pathways. A pathway association analysis identified two common pathways within T2D and COVID-19 pathogenesis, including chemokines and their respective receptors. The gene identified from the pathway analysis (CCR2) was also found to be highly expressed in blood tissue via the GTEx database. To conclude, this study reveals that certain chemokines and their receptors, which are directly involved in the genesis of cytokine storms, may lead to exacerbated hyperinflammation in T2D patients infected by COVID-19.

Precision mitochondrial medicine

Mitochondria play a key role in cell homeostasis as a major source of intracellular energy (adenosine triphosphate), and as metabolic hubs regulating many canonical cell processes. Mitochondrial dysfunction has been widely documented in many common diseases, and genetic studies point towards a causal role in the pathogenesis of specific late-onset disorder. Together this makes targeting mitochondrial genes an attractive strategy for precision medicine. However, the genetics of mitochondrial biogenesis is complex, with over 1,100 candidate genes found in two different genomes: the nuclear DNA and mitochondrial DNA (mtDNA). Here, we review the current evidence associating mitochondrial genetic variants with distinct clinical phenotypes, with some having clear therapeutic implications. The strongest evidence has emerged through the investigation of rare inherited mitochondrial disorders, but genome-wide association studies also implicate mtDNA variants in the risk of developing common diseases, opening to door for the incorporation of mitochondrial genetic variant analysis in population disease risk stratification.

Elucidating the genetic architecture of DNA methylation to identify promising molecular mechanisms of disease

DNA methylation commonly occurs at cytosine-phosphate-guanine sites (CpGs) that can serve as biomarkers for many diseases. We analyzed whole genome sequencing data to identify DNA methylation quantitative trait loci (mQTLs) in 4126 Framingham Heart Study participants. Our mQTL mapping identified 94,362,817 cis-mQTLvariant-CpG pairs (for 210,156 unique autosomal CpGs) at P < 1e-7 and 33,572,145 trans-mQTL variant-CpG pairs (for 213,606 unique autosomal CpGs) at P < 1e-14. Using cis-mQTL variants for 1258 CpGs associated with seven cardiovascular disease (CVD) risk factors, we found 104 unique CpGs that colocalized with at least one CVD trait. For example, cg11554650 (PPP1R18) colocalized with type 2 diabetes, and was driven by a single nucleotide polymorphism (rs2516396). We performed Mendelian randomization (MR) analysis and demonstrated 58 putatively causal relations of CVD risk factor-associated CpGs to one or more risk factors (e.g., cg05337441 [APOB] with LDL; MR P = 1.2e-99, and 17 causal associations with coronary artery disease (e.g. cg08129017 [SREBF1] with coronary artery disease; MR P = 5e-13). We also showed that three CpGs, e.g., cg14893161 (PM20D1), are putatively causally associated with COVID-19 severity. To assist in future analyses of the role of DNA methylation in disease pathogenesis, we have posted a comprehensive summary data set in the National Heart, Lung, and Blood Institute's BioData Catalyst.

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.