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ObjectivesThe identification of novel uses for existing drug therapies has the potential to provide a rapid, low-cost approach to drug (re)discovery. In the current study we developed and tested a genetically-informed drug-repurposing pipeline for diabetes management.DesignWe developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug-gene pairs. These drug-gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR).SettingThe SCCS experiments were completed using two EHRs: the Million Veterans Program (USA) as the discovery and the Vanderbilt University Medical Center (Tennessee, USA) as the replication.ResultsAfter filtering on sample size, 20 candidate drug-gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: -0.11%, p=0.01 and -0.85 mg/dL, p=0.02, respectively; MR: OR=0.84, 95% CI=0.81, 0.87, p=5.0×10-25).ConclusionsOur results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions.Summary BoxesSection 1: What is already known on this topicMedications with genetic support are significantly more likely to make it through clinical trials.Section 2: What this study addsOur results identified two anti-hypertensive medication classes, calcium channel blockers and angiotensin-converting enzyme inhibitors, as genetically supported drug-repurposing targets that demonstrated glycemic measurement reduction in real-world clinical populations. These results suggest patients with diabetes or pre-diabetes could benefit from preferential use of these medication classes when they present with comorbid hypertension or other cardiovascular conditions. Finally, this study demonstrates a successful implementation of a novel genetically-supported drug-repurposing pipeline for diabetes treatment that can be readily adapted and applied to other diseases and as such it has the potential to identify/prioritize drug repurposing targets for these other conditions.

Structured AbstractINTRODUCTIONDiabetes and dementia are diseases of high healthcare burden worldwide. Individuals with diabetes have 1.4 to 2.2 times higher risk of dementia. Our objective was to evaluate evidence of causality between these two common diseases.METHODSWe conducted a one-sample Mendelian randomization (MR) analysis in the U.S. Department of Veterans Affairs Million Veteran program. The study included 334,672 participants ≥65 years of age with type 2 diabetes and dementia case-control status and genotype data.RESULTSFor each standard deviation increase in genetically-predicted diabetes, we found increased odds of three dementia diagnoses in non-Hispanic White participants (all-cause: OR=1.07[1.05-1.08],P=3.40E-18; vascular: OR=1.11[1.07-1.15],P=3.63E-09, Alzheimer’s: OR=1.06[1.02-1.09],P=6.84E-04) and non-Hispanic Black participants (all-cause: OR=1.06[1.02-1.10],P=3.66E-03, vascular: OR=1.11[1.04-1.19],P=2.20E-03, Alzheimer’s: OR=1.12 [1.02-1.23],P=1.60E-02) but not in Hispanic participants (allP>.05).DISCUSSIONWe found evidence of causality between diabetes and dementia using a one-sample MR study, with access to individual level data, overcoming limitations of prior studies utilizing two-sample MR techniques.

Introduction: Relative to the general population, patients with schizophrenia or schizoaffective disorder have higher rates of suicide attempts and mortality from COVID-19 infection. Therefore, determining whether a history of suicide attempt is associated with COVID-19 in patients with schizophrenia or schizoaffective disorder has implications for COVID-19 vulnerability stratification in this patient population. Methods: We carried out cross-sectional analyses of electronic health records of veterans with a diagnosis of schizophrenia or schizoaffective disorder that received treatment at any United States Veterans Affairs Medical Center between January 1, 2020, and January 31, 2021. We used logistic regression to estimate unadjusted and adjusted (including age, sex, race, marital status, body mass index (BMI), and a medical comorbidity score) odds ratios (ORs) for COVID-19 positivity in suicide attempters relative to nonattempters. Results: A total of 101,032 veterans (mean age 56.67 ± 13.13 years; males 91,715 [90.8%]) were included in the analyses. There were 2,703 (2.7%) suicide attempters and 719 (0.7%) patients were positive for COVID-19. The association between history of suicide attempt and COVID-19 positivity was modified by age and BMI, such that the relationship was only significant in patients younger than 59 years, and in obese (BMI ≥30) patients (adjusted OR 3.42, 95% CI 2.02–5.79 and OR 2.85, 95% CI 1.65–4.94, respectively). Conclusions: Higher rates of COVID-19 in young or obese suicide attempters with a diagnosis of schizophrenia or schizoaffective disorder might be due to the elevated risk for the infection in this subgroup of patients.

Aims/hypothesis The aim of this study was to leverage human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide (GIP) signalling. Methods Data were obtained from summary statistics of large-scale genome-wide association studies. We examined whether genetic associations for type 2 diabetes liability in the GIP and GIPR genes co-localised with genetic associations for 11 cardiometabolic outcomes. For those outcomes that showed evidence of co-localisation (posterior probability >0.8), we performed Mendelian randomisation analyses to estimate the association of genetically proxied GIP signalling with risk of cardiometabolic outcomes, and to test whether this exceeded the estimate observed when considering type 2 diabetes liability variants from other regions of the genome. Results Evidence of co-localisation with genetic associations of type 2 diabetes liability at both the GIP and GIPR genes was observed for five outcomes. Mendelian randomisation analyses provided evidence for associations of lower genetically proxied type 2 diabetes liability at the GIP and GIPR genes with lower BMI (estimate in SD units −0.16, 95% CI −0.30, −0.02), C-reactive protein (−0.13, 95% CI −0.19, −0.08) and triacylglycerol levels (−0.17, 95% CI −0.22, −0.12), and higher HDL-cholesterol levels (0.19, 95% CI 0.14, 0.25). For all of these outcomes, the estimates were greater in magnitude than those observed when considering type 2 diabetes liability variants from other regions of the genome. Conclusions/interpretation This study provides genetic evidence to support a beneficial role of sustained GIP signalling on cardiometabolic health greater than that expected from improved glycaemic control alone. Further clinical investigation is warranted. Data availability All data used in this study are publicly available. The scripts for the analysis are available at: https://github.com/vkarhune/GeneticallyProxiedGIP. Graphical abstract

ObjectiveTo investigate the effects of metabolic traits, lifestyle factors, and drug interventions on liver fat using the mendelian randomisation paradigm.DesignMendelian randomisation study.SettingPublicly available summary level data from genome-wide association studies.ParticipantsGenome-wide association studies of 32 974 to 1 407 282 individuals who were predominantly of European descent.ExposuresGenetic variants predicting nine metabolic traits, six lifestyle factors, four lipid lowering drug targets, three antihypertensive drug targets, and genetic association estimates formagnetic resonance imaging measured liver fat.Main outcome measuresMendelian randomisation analysis was used to investigate the effects of these exposures on liver fat, incorporating sensitivity analyses that relaxed the requisite modelling assumptions.ResultsGenetically predicted liability to obesity, type 2 diabetes, elevated blood pressure, elevated triglyceride levels, cigarette smoking, and sedentary time watching television were associated with higher levels of liver fat. Genetically predicted lipid lowering drug effects were not associated with liver fat; however, β blocker and calcium channel blocker antihypertensive drug effects were associated with lower levels of liver fat.ConclusionThese analyses provide evidence of a causal effect of various metabolic traits, lifestyle factors, and drug targets on liver fat. The findings complement existing epidemiological associations, further provide mechanistic insight, and potentially supports a role for drug interventions in reducing the burden of hepatic steatosis and related disease. Further clinical study is now warranted to investigate the relevance of these genetic analyses for patient care.

This PSB 2023 session discusses challenges in clinical implication and application of risk prediction models, which includes but is not limited to: implementation of risk models, responsible use of polygenic risk scores (PGS), and other risk prediction strategies. We focus on the development and use of new, scalable methods for harmonizing and refining risk prediction models by incorporating genetic and non-genetic risk factors, applying new phenotyping strategies, and integrating clinical factors and biomarkers. Lastly, we will discuss innovation in expanding the utility of these prediction models to underrepresented populations. This session focuses on the overarching theme of enabling early diagnosis, and treatment and preventive measures related to complex diseases and comorbidities.

Objective: Diabetes and dementia are diseases of high healthcare burden worldwide, and studies have shown that diabetes is associated with increased relative risk of dementia. We set out to examine whether type 2 diabetes-associated genetic variants were associated with dementia and if they differed by race/ethnicity or clinical dementia diagnosis. Research Design and Methods: We evaluated associations of two type 2 diabetes genetic risk scores (GRS and GRS-NonAPOE: a score without rs429358, a variant associated with Alzheimer’s disease [AD]) with three classifications of clinical dementia diagnoses in the Million Veteran Program (MVP): all-cause-dementia, vascular dementia (VaD), and AD. We conducted our analysis stratified by European (EUR), African (AFR), and Hispanic (HIS) race/ethnicities. Results: In EUR, we found associations of the GRS with all-cause-dementia (OR = 1.06, P = 1.60e-07), and clinically diagnosed VaD (OR = 1.12, P = 5.2e-05) but not clinically diagnosed AD (OR = 1.02, P = .43). The GRS was not associated with any dementia outcome in AFR or HIS. When testing with GRS-NonAPOE, we found that effect size estimates in EUR increased and P values decreased (for all-cause-dementia OR = 1.08, P = 2.6e-12; for VaD OR = 1.14, P = 7.2e-07and for AD OR = 1.06, P = .018). For AFR, the association of GRS-NonAPOE and clinically diagnosed VaD (OR = 1.15, P = .016) was statistically significant. There were no significant findings for HIS. Conclusions: We found evidence suggesting shared genetic pathogenesis of diabetes with all-cause-dementia and clinically diagnosed VaD.

Plasma levels of liver enzymes provide insights into hepatic function and related diseases. Here, the authors perform a genome-wide association study on three liver enzymes, identifying genetic variants associated with their plasma concentration as well as links to metabolic and cardiovascular diseases.Serum concentration of hepatic enzymes are linked to liver dysfunction, metabolic and cardiovascular diseases. We perform genetic analysis on serum levels of alanine transaminase (ALT), alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) using data on 437,438 UK Biobank participants. Replication in 315,572 individuals from European descent from the Million Veteran Program, Rotterdam Study and Lifeline study confirms 517 liver enzyme SNPs. Genetic risk score analysis using the identified SNPs is strongly associated with serum activity of liver enzymes in two independent European descent studies (The Airwave Health Monitoring study and the Northern Finland Birth Cohort 1966). Gene-set enrichment analysis using the identified SNPs highlights involvement in liver development and function, lipid metabolism, insulin resistance, and vascular formation. Mendelian randomization analysis shows association of liver enzyme variants with coronary heart disease and ischemic stroke. Genetic risk score for elevated serum activity of liver enzymes is associated with higher fat percentage of body, trunk, and liver and body mass index. Our study highlights the role of molecular pathways regulated by the liver in metabolic disorders and cardiovascular disease.

While newborns and children with hearing loss are routinely offered genetic testing, adults are rarely clinically tested for a genetic etiology. One clinically actionable result from genetic testing in children is the discovery of variants in syndromic hearing loss genes. EYA4 is a known hearing loss gene which is also involved in important pathways in cardiac tissue. The pleiotropic effects of rare EYA4 variants are poorly understood and their prevalence in a large cohort has not been previously reported. We investigated cardio-auditory phenotypes in 11,451 individuals in a large biobank using a rare variant, genome-first approach to EYA4. We filtered 256 EYA4 variants carried by 6737 participants to 26 rare and predicted deleterious variants carried by 42 heterozygotes. We aggregated predicted deleterious EYA4 gene variants into a combined variable (i.e. “gene burden”) and performed association studies across phenotypes compared to wildtype controls. We validated findings with replication in three independent cohorts and human tissue expression data. EYA4 gene burden was significantly associated with audiometric-proven HL (p = $${5.43\times 10}^{-5})$$ , Mobitz Type II AV block (p = $${2.16\times 10}^{-5}$$ ) and the syndromic presentation of HL and primary cardiomyopathy (p = 0.0194). Analyses on audiogram, echocardiogram, and electrocardiogram data validated these associations. Prior reports have focused on identifying variants in families with severe or syndromic phenotypes. In contrast, we found, using a genotype-first approach, that gene burden in EYA4 is associated with more subtle cardio-auditory phenotypes in an adult medical biobank population, including cardiac conduction disorders which have not been previously reported. We show the value of using a focused approach to uncover human disease related to pleiotropic gene variants and suggest a role for genetic testing in adults presenting with hearing loss.

Clinical observations have linked tobacco smoking with increased type 2 diabetes risk. Mendelian randomization analysis has recently suggested smoking may be a causal risk factor for type 2 diabetes. However, this association could be mediated by additional risk factors correlated with smoking behavior, which have not been investigated. We hypothesized that body mass index (BMI) could help to explain the association between smoking and diabetes risk. First, we confirmed that genetic determinants of smoking initiation increased risk for type 2 diabetes (OR 1.21, 95% CI: 1.15–1.27, P = 1 × 10−12) and coronary artery disease (CAD; OR 1.21, 95% CI: 1.16–1.26, P = 2 × 10−20). Additionally, 2-fold increased smoking risk was positively associated with increased BMI (~0.8 kg/m2, 95% CI: 0.54–0.98 kg/m2, P = 1.8 × 10−11). Multivariable Mendelian randomization analyses showed that BMI accounted for nearly all the risk smoking exerted on type 2 diabetes (OR 1.06, 95% CI: 1.01–1.11, P = 0.03). In contrast, the independent effect of smoking on increased CAD risk persisted (OR 1.12, 95% CI: 1.08–1.17, P = 3 × 10−8). Causal mediation analyses agreed with these estimates. Furthermore, analysis using individual-level data from the Million Veteran Program independently replicated the association of smoking behavior with CAD (OR 1.24, 95% CI: 1.12–1.37, P = 2 × 10−5), but not type 2 diabetes (OR 0.98, 95% CI: 0.89–1.08, P = 0.69), after controlling for BMI. Our findings support a model whereby genetic determinants of smoking increase type 2 diabetes risk indirectly through their relationship with obesity. Smokers should be advised to stop smoking to limit type 2 diabetes and CAD risk. Therapeutic efforts should consider pathophysiology relating smoking and obesity.

Aims/hypothesis Type 2 diabetes and atherosclerotic CVD share many risk factors. This study aimed to systematically assess a broad range of continuous traits to separate their direct effects on coronary and peripheral artery disease from those mediated by type 2 diabetes. Methods Our main analysis was a two-step Mendelian randomisation for mediation to quantify the extent to which the associations observed between continuous traits and liability to atherosclerotic CVD were mediated by liability to type 2 diabetes. To support this analysis, we performed several univariate Mendelian randomisation analyses to examine the associations between our continuous traits, liability to type 2 diabetes and liability to atherosclerotic CVD. Results Eight traits were eligible for the two-step Mendelian randomisation with liability to coronary artery disease as the outcome and we found similar direct and total effects in most cases. Exceptions included fasting insulin and hip circumference where the proportion mediated by liability to type 2 diabetes was estimated as 56% and 52%, respectively. Six traits were eligible for the analysis with liability to peripheral artery disease as the outcome. Again, we found limited evidence to support mediation by liability to type 2 diabetes for all traits apart from fasting insulin (proportion mediated: 70%). Conclusions/interpretation Most traits were found to affect liability to atherosclerotic CVD independently of their relationship with liability to type 2 diabetes. These traits are therefore important for understanding atherosclerotic CVD risk regardless of an individual’s liability to type 2 diabetes. Graphical abstract

OBJECTIVE Diabetes and dementia are diseases of high health care burden worldwide, and studies have shown that diabetes is associated with an increased relative risk of dementia. We set out to examine whether type 2 diabetes–associated genetic variants were associated with dementia and whether they differed by race/ethnicity or clinical dementia diagnosis. RESEARCH DESIGN AND METHODS We evaluated associations of two type 2 diabetes genetic risk scores (GRS and GRS-nonAPOE: a score without rs429358, a variant associated with Alzheimer disease [AD]) with three classifications of clinical dementia diagnoses in the Million Veteran Program (MVP): all-cause dementia, vascular dementia (VaD), and AD. We conducted our analysis stratified by European (EUR), African (AFR), and Hispanic (HIS) races/ethnicities. RESULTS In EUR, we found associations of the GRS with all-cause dementia (odds ratio [OR] 1.06, P = 1.60e−07) and clinically diagnosed VaD (OR 1.12, P = 5.2e−05) but not with clinically diagnosed AD (OR 1.02, P = 0.43). The GRS was not associated with any dementia outcome in AFR or HIS. When testing with GRS-nonAPOE, we found that effect size estimates in EUR increased and P values decreased for all-cause dementia (OR 1.08, P = 2.6e−12), for VaD (OR 1.14, P = 7.2e−07), and for AD (OR 1.06, P = 0.018). For AFR, the association of GRS-nonAPOE and clinically diagnosed VaD (OR 1.15, P = 0.016) was statistically significant. There were no significant findings for HIS. CONCLUSIONS We found evidence suggesting shared genetic pathogenesis of diabetes with all-cause dementia and clinically diagnosed VaD.

INTRODUCTION: Vitamin E supplementation is recommended for the treatment of non-alcoholic fatty liver disease (NAFLD) for nondiabetic patients, but its preventative effects are unclear. METHODS: We assessed dietary Vitamin E intake with disease phenotypes and evaluated Vitamin E levels with the development of NAFLD. RESULTS: Data from >210,000 participants demonstrate that increased dietary Vitamin E associates with reduced rates of several gastrointestinal diseases and reduced overall mortality. Diabetic and overweight subjects with increased Vitamin E intake have fewer NAFLD diagnoses. CONCLUSION: Our findings reveal the relevance of Vitamin E consumption for several gastrointestinal diseases and warrant further mechanistic and therapeutic investigations.

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n=35) or hospitalization (n=42) due to severe COVID-19 using genome-wide association summary from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (nrs495828= 53 and nrs505922=59); strongest association with venous embolism, odds ratio (ORrs495828 1.33 (p=1.32 × 10−199), and thrombosis ORrs505922 1.33, p=2.2 ×10−265. Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p=4.12 × 10−191; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p=2.26× 10−12. The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p=6.48 ×10−23, lupus OR 0.84, p=3.97 × 10−06. PheWAS stratified by genetic ancestry demonstrated differences in genotype-phenotype associations across ancestry. LMNA (rs581342) associated with neutropenia OR 1.29 p=4.1 × 10−13 among Veterans of African ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.

Although affecting different arterial territories, the related atherosclerotic vascular diseases coronary artery disease (CAD) and peripheral artery disease (PAD) share similar risk factors and have shared pathobiology. To identify novel pleiotropic loci associated with atherosclerosis, we performed a joint analysis of their shared genetic architecture, along with that of common risk factors. Using summary statistics from genome-wide association studies of nine known atherosclerotic (CAD, PAD) and atherosclerosis risk factors (body mass index, smoking initiation, type 2 diabetes, low density lipoprotein, high density lipoprotein, total cholesterol, and triglycerides), we perform 15 separate multi-trait genetic association scans which resulted in 25 novel pleiotropic loci not yet reported as genome-wide significant for their respective traits. Colocalization with single-tissue eQTLs identified candidate causal genes at 14 of the detected signals. Notably, the signal between PAD and LDL-C at the PCSK6 locus affects PCSK6 splicing in human liver tissue and induced pluripotent derived hepatocyte-like cells. These results show that joint analysis of related atherosclerotic disease traits and their risk factors allowed identification of unified biology that may offer the opportunity for therapeutic manipulation. The signal at PCSK6 represent possible shared causal biology where existing inhibitors may be able to be leveraged for novel therapies.

ImportanceAs patients with schizophrenia or schizoaffective disorder have a high risk of suicide, and a history of suicide attempt is a strong predictor of suicide, determining whether history of suicide attempt is associated with COVID-19 in patients with schizophrenia or schizoaffective disorder has implications for suicide prevention in this patient population.ObjectiveTo determine whether a history of suicide attempt is associated with COVID-19 in Veterans with schizophrenia or schizoaffective disorder.DesignCross-sectional analyses of nation-wide electronic health records (EHR).SettingUnited States Veterans Health Administration.ParticipantsVeterans with a diagnosis of schizophrenia or schizoaffective disorder that received treatment at any United States Veterans Affairs Medical Center from January 1, 2020 to January 31, 2021.ExposureHistory of suicide attempt.Main OutcomeAdjusted and unadjusted odds ratios (ORs) for COVID-19 positivity in suicide attempters relative to non-attempters. Adjusted analyses included age, sex, race, marital status, BMI, and a medical comorbidity score.ResultsA total of 101,032 Veterans [mean age 56.67 ± 13.13 years; males 91,715 (90.8%)] were included in the analyses. There were 2,703 (2.7%) suicide attempters and 719 (0.7%) patients were positive for COVID-19. There was effect modification by age and BMI in the association of history of suicide attempt with COVID-19 positivity such that the association was only significant in obese (BMI ≥ 30) patients and patients younger than 59 years respectively. In the entire sample, the unadjusted OR for COVID-19 positivity in attempters was 1.42 (95% CI 0.97 to 2.10) and the adjusted odds ratio was 1.90 (95% CI 1.28 to 2.80). In patients younger than 59 years, and in the obese patients respectively, history of suicide attempt was associated with COVID-positive status in unadjusted analyses [OR 3.53 (95% CI 2.10 to 5.94); OR 2.22 (95% CI 1.29 to 3.81)] and adjusted analyses [OR 3.42 (95% CI 2.02 to 5.79); OR 2.85 (95% CI 1.65 to 4.94)].Conclusions and RelevanceYoung or obese suicide attempters with a diagnosis of schizophrenia or schizoaffective disorders have higher rates of COVID-19 diagnosis; due to possible long-term neuropsychiatric sequelae of infection with SARS-CoV-2, such patients should be monitored closely.

Polygenic risk scores (PRS) can enhance risk stratification and are useful for precision medicine interventions. Here we show that African American Genome-wide Association Study (GWAS) derived PRS enhance prediction of lipid traits in Sub-Saharan Africans. Our PRS prediction varied greatly between South African Zulus (LDL-C, R2 = 8.49%) and Ugandans (LDL-C, R2= 0.043%), potentially attributable to environmental factors. Moreover, the PRS shown here had a higher discriminatory ability (AUC = 74.6%) than conventional risk factors (AUC= 67.8%) to identify extreme phenotypes. This work highlights the utility of PRS derived from relevant ethnic groups for identifying high-risk cases missed by conventional clinical factors.

BackgroundType 2 diabetes and atherosclerotic cardiovascular disease share several risk factors. However, it is unclear whether the effect of these risk factors on liability to atherosclerotic cardiovascular disease is independent of their effect on liability to type 2 diabetes.MethodsWe performed univariate Mendelian randomization to quantify the effects of continuous risk factors from the IEU OpenGWAS database on liability to three outcomes: type 2 diabetes, coronary artery disease, and peripheral artery disease, as well as the effects of liability to type 2 diabetes on the risk factors. We also performed two-step Mendelian randomization for mediation to estimate the mediating pathways between the risk factors, liability to type 2 diabetes, and liability to the atherosclerotic cardiovascular disease outcomes where possible.ResultsWe found evidence for 53 risk factors as causes of liability to coronary artery disease, including eight which were causes of liability to type 2 diabetes only and four which were consequences only. Except for fasting insulin and hip circumference, the direct and total effects from the two-step Mendelian randomization were similar. This suggests that the combination of these risk factors with liability to type 2 diabetes was unlikely to alter liability to coronary artery disease beyond their individual effects. We also found 13 risk factors that were causes of liability peripheral artery disease, including six which were causes of liability to type 2 diabetes only and four which were consequences only. Again, the direct and total effects were similar for these ten risk factors apart from fasting insulin.ConclusionsMost risk factors were likely to affect liability to atherosclerotic cardiovascular disease independently of their relationship with liability to type 2 diabetes. Control of modifiable risk factors therefore remains important for reducing atherosclerotic cardiovascular disease risk regardless of patient liability to type 2 diabetes.RESEARCH IN CONTEXTWhat is already known about this subject?Type 2 diabetes, coronary artery disease and peripheral artery disease, share several risk factorsType 2 diabetes is also one of the strongest independent risk factors for both coronary and peripheral artery diseaseWhat is the key question?Which risk factors for atherosclerotic cardiovascular disease are mediated by liability to type 2 diabetes and which are independent?What are the new findings?Among 108 risk factors in this study, there was evidence to support: 10 risk factors as causes, 23 risk factors as consequences, and 34 risk factors as both causes and consequences of liability to type 2 diabetesIn addition, we found evidence for 53 risk factors as causes of liability to coronary artery disease and 42 risk factors as causes of liability to peripheral artery diseaseUsing two-step Mendelian randomization for mediation, we found most risk factors for atherosclerotic cardiovascular disease were likely to act independently of liability to type 2 diabetesHow might this impact on clinical practice in the foreseeable future?Our findings support continued control of modifiable risk factors as this is likely to reduce atherosclerotic cardiovascular disease, regardless of patient liability to type 2 diabetes

Background This study was designed to investigate the genetic evidence for repurposing of GLP1R (glucagon‐like peptide‐1 receptor) agonists to prevent heart failure (HF) and whether the potential benefit exceeds the benefit conferred by more general glycemic control. Methods and Results We applied 2‐sample Mendelian randomization of genetically proxied GLP1R agonism on HF as the main outcome and left ventricular ejection fraction as the secondary outcome. The associations were compared with those of general glycemic control on the same outcomes. Genetic associations were obtained from genome‐wide association study summary statistics of type 2 diabetes mellitus (228 499 cases and 1 178 783 controls), glycated hemoglobin (n=344 182), HF (47,309 cases and 930 014 controls), and left ventricular ejection fraction (n=16 923). Genetic proxies for GLP1R agonism associated with reduced risk of HF (odds ratio per 1 mmol/mol decrease in glycated hemoglobin 0.75; 95% CI, 0.64–0.87; P =1.69×10 −4 ), and higher left ventricular ejection fraction (SD change in left ventricular ejection fraction per 1 mmol/mol decrease in glycated hemoglobin 0.22%; 95% CI, 0.03–0.42; P =0.03). The magnitude of these benefits exceeded those expected from improved glycemic control more generally. The results were similar in sensitivity analyses, and we did not find evidence to suggest that these associations were mediated by reduced coronary artery disease risk. Conclusions This genetic evidence supports the repurposing of GLP1R agonists for preventing HF.

Adult onset T1D is often misdiagnosed as T2D, leading to poor metabolic control and increased risk of microvascular complications and cardiovascular morbidity and mortality. We examined characteristics associated with a T1D genetic risk score in Veterans, a population where new diagnoses are generally presumed to be T2D, since persons with typical juvenile-onset T1D are excluded from military service. A 30 SNP T1D genetic risk score (GRS), previously validated with the Wellcome Trust Case Control Consortium (WTCCC), was applied to 111,663 Veterans with diabetes in the MVP. Patients were stratified by T1D GRS centile groups (≤5th, >5th-≤36th, >36th-≤50th, and >50th) which corresponded to T1D specificity in the WTCCC of 29%, 53%, 90%, and 95%, respectively. Typical T1D clinical characteristics were significantly more common (p Conclusions: The 10% of US Veterans with diabetes in MVP in the two highest T1D GRS centile groups have characteristics suggestive of T1D, although only 5% were tested for GAD antibodies, and most had no use of T1D diagnosis codes. Since adult-onset T1D may be misdiagnosed as T2D in settings where T2D is more common, genetic analyses and/or clinical characteristics may warrant definitive testing and appropriate management. Disclosure P. K. Yang: None. M. K. Rhee: None. C. Mercado: None. R. A. Oram: Consultant; Self; Janssen Research & Development, LLC. M. Vujkovic: None. P. Reaven: Research Support; Self; AstraZeneca, Dexcom, Inc. K. Cho: None. L. S. Phillips: Other Relationship; Self; Diasyst Inc., Research Support; Self; AbbVie Inc., Eli Lilly and Company, GlaxoSmithKline plc., Janssen Pharmaceuticals, Inc., Kowa Pharmaceuticals America, Inc., Novartis Pharmaceuticals Corporation, Novo Nordisk Pharma Ltd., Pfizer Inc., Sanofi-Aventis. A. Leong: None. S. Jackson: None. B. R. Charest: None. M. N. Weedon: None. Y. J. Cheng: None. Y. V. Sun: None. S. Raghavan: None. E. M. Litkowski: None. B. T. Legvold: None. Funding U.S. Department of Veterans Affairs (CSP2008, I01CX001899, I01CX001737); National Institutes of Health (R18DK066204, R21AI156161, U01DK091958, U01DK098246, UL1TR002378)

Venous thromboembolism (VTE) is a significant cause of mortality1, yet its genetic determinants remain incompletely defined. We performed a discovery genome-wide association study in the Million Veteran Program and UK Biobank testing ~13 million DNA sequence variants for association with VTE (26,066 cases; 624,053 controls) and meta-analyzed both studies, followed by independent replication with up to 17,672 VTE cases and 167,295 controls. We identified 22 novel loci, bringing the total number of VTE-associated loci to 33 and subsequently fine-mapped these associations. We developed a genome-wide polygenic risk score for VTE that identifies 5% of the population at equivalent incident VTE risk to carriers of the established F5 Leiden (p.R506Q) and prothrombin G20210A mutations. Our data provide new mechanistic insights into the genetic epidemiology of VTE and suggest a greater overlap among venous and arterial cardiovascular disease than previously suggested., Editorial summary Genome-wide analysis of venous thromboembolism identifies 22 new risk loci and facilitates construction of a polygenic risk score. Comparison to arterial vascular disease highlights shared pathophysiology and potential therapeutic strategies.

Large-scale multi-ethnic cohorts offer unprecedented opportunities to elucidate the genetic factors influencing complex traits related to health and disease among minority populations. At the same time, the genetic diversity in these cohorts presents new challenges for analysis and interpretation. We consider the utility of race and/or ethnicity categories in genome-wide association studies (GWASs) of multi-ethnic cohorts. We demonstrate that race/ethnicity information enhances the ability to understand population-specific genetic architecture. To address the practical issue that self-identified racial/ethnic information may be incomplete, we propose a machine learning algorithm that produces a surrogate variable, termed HARE. We use height as a model trait to demonstrate the utility of HARE and ethnicity-specific GWASs.

Peripheral artery disease (PAD) is a leading cause of cardiovascular morbidity and mortality; however, the extent to which genetic factors increase risk for PAD is largely unknown. Using electronic health record data, we performed a genome-wide association study in the Million Veteran Program testing ~32 million DNA sequence variants with PAD (31,307 cases and 211,753 controls) across veterans of European, African and Hispanic ancestry. The results were replicated in an independent sample of 5,117 PAD cases and 389,291 controls from the UK Biobank. We identified 19 PAD loci, 18 of which have not been previously reported. Eleven of the 19 loci were associated with disease in three vascular beds (coronary, cerebral, peripheral), including LDLR, LPL and LPA, suggesting that therapeutic modulation of low-density lipoprotein cholesterol, the lipoprotein lipase pathway or circulating lipoprotein(a) may be efficacious for multiple atherosclerotic disease phenotypes. Conversely, four of the variants appeared to be specific for PAD, including F5 p.R506Q, highlighting the pathogenic role of thrombosis in the peripheral vascular bed and providing genetic support for Factor Xa inhibition as a therapeutic strategy for PAD. Our results highlight mechanistic similarities and differences among coronary, cerebral and peripheral atherosclerosis and provide therapeutic insights.