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Lifecourse Mendelian randomization is a causal inference technique which harnesses genetic variants with time-varying effects to develop insight into the influence of age-dependent lifestyle factors on disease risk. Here, we apply this approach to evaluate whether childhood body size has a direct consequence on 8 major disease endpoints by analysing parental history data from the UK Biobank study.Our findings suggest that, whilst childhood body size increases later risk of outcomes such as heart disease (odds ratio (OR) = 1.15, 95% CI = 1.07 to 1.23, P = 7.8 × 10− 5) and diabetes (OR = 1.43, 95% CI = 1.31 to 1.56, P = 9.4 × 10− 15) based on parental history data, these findings are likely attributed to a sustained influence of being overweight for many years over the lifecourse. Likewise, we found evidence that remaining overweight throughout the lifecourse increases risk of lung cancer, which was partially mediated by lifetime smoking index. In contrast, using parental history data provided evidence that being overweight in childhood may have a protective effect on risk of breast cancer (OR = 0.87, 95% CI = 0.78 to 0.97, P = 0.01), corroborating findings from observational studies and large-scale genetic consortia.Large-scale family disease history data can provide a complementary source of evidence for epidemiological studies to exploit, particularly given that they are likely more robust to sources of selection bias (e.g. survival bias) compared to conventional case control studies. Leveraging these data using approaches such as lifecourse Mendelian randomization can help elucidate additional layers of evidence to dissect age-dependent effects on disease risk.

Background The prevalence of atrial fibrillation (AF) is increasing with an aging worldwide population, yet a comprehensive understanding of its causes and consequences remains limited. We aim to assess the causes and consequences of AF via a bidirectional Mendelian randomization (MR) analysis. Methods We used publicly available genome-wide association study (GWAS) summary data, centralized and harmonized by an open GWAS database. We assessed the genetically predicted effects of 5048 exposures on risk of AF, and the genetically predicted effects of genetic liability to AF, on 10 308 outcomes via two-sample MR analysis. Multivariable MR analysis was further conducted to explore the comparative roles of identified risk factors. Results MR analysis suggested that 55 out of 5048 exposure traits, including four proteins, play a causal role in AF (P Conclusions Our results suggest body mass index, height, systolic blood pressure and genetic liability to coronary artery disease are independent causal risk factors for AF. Several proteins, including DUSP13, IL-6R and TNFSF12, may have therapeutic potential for AF.

Sclerostin inhibition is a new therapeutic approach for increasing bone mineral density (BMD) but its cardiovascular safety is unclear. We conducted a genome-wide association study (GWAS) meta-analysis of circulating sclerostin in 33,961 Europeans followed by Mendelian randomization (MR) to estimate the causal effects of sclerostin on 15 atherosclerosis-related diseases and risk factors. GWAS meta-analysis identified 18 variants independently associated with sclerostin, which including a novel cis signal in the SOST region and three trans signals in B4GALNT3, RIN3 and SERPINA1 regions that were associated with opposite effects on circulating sclerostin and eBMD. MR combining these four SNPs suggested lower sclerostin increased hypertension risk (odds ratio [OR]=1.09, 95%CI=1.04 to 1.15), whereas bi-directional analyses revealed little evidence for an effect of genetic liability to hypertension on sclerostin levels. MR restricted to cis (SOST) SNPs additionally suggested sclerostin inhibition increased risk of type 2 diabetes (T2DM) (OR=1.26; 95%CI=1.08 to 1.48) and myocardial infarction (MI) (OR=1.31, 95% CI=1.183 to 1.45). Furthermore, these analyses suggested sclerostin inhibition increased coronary artery calcification (CAC) (β=0.74, 95%CI=0.33 to 1.15), levels of apoB (β=0.07; 95%CI=0.04 to 0.10; this result was driven by rs4793023) and triglycerides (β=0.18; 95%CI=0.13 to 0.24), and reduced HDL-C (β=-0.14; 95%CI=-0.17 to -0.10). This study provides genetic evidence to support a causal effect of sclerostin inhibition on increased hypertension risk. Cis-only analyses suggested that sclerostin inhibition additionally increases the risk of T2DM, MI, CAC, and an atherogenic lipid profile. Together, our findings reinforce the requirement for strategies to mitigate against adverse effects of sclerostin inhibitors like romosozumab on atherosclerosis and its related risk factors.

Background and aims Observational studies have linked elevated blood pressure (BP) to impaired cognitive function. However, the functional and structural changes in the brain that mediate the relationship between BP elevation and cognitive impairment remain unknown. Using observational and genetic data from large consortia, this study aimed to identify brain structures potentially associated with BP values and cognitive function. Methods and results Data on BP were integrated with 3935 brain magnetic resonance imaging-derived phenotypes (IDPs) and cognitive function defined by fluid intelligence score. Observational analyses were performed in the UK Biobank and a prospective validation cohort. Mendelian randomisation (MR) analyses used genetic data derived from the UK Biobank, International Consortium for Blood Pressure, and COGENT consortium. Mendelian randomisation analysis identified a potentially adverse causal effect of higher systolic BP on cognitive function [−0.044 standard deviation (SD); 95% confidence interval (CI) −0.066, −0.021] with the MR estimate strengthening (−0.087 SD; 95% CI −0.132, −0.042), when further adjusted for diastolic BP. Mendelian randomisation analysis found 242, 168, and 68 IDPs showing significant (false discovery rate P < 0.05) association with systolic BP, diastolic BP, and pulse pressure, respectively. Most of these IDPs were inversely associated with cognitive function in observational analysis in the UK Biobank and showed concordant effects in the validation cohort. Mendelian randomisation analysis identified relationships between cognitive function and the nine of the systolic BP-associated IDPs, including the anterior thalamic radiation, anterior corona radiata, or external capsule. Conclusion Complementary MR and observational analyses identify brain structures associated with BP, which may be responsible for the adverse effects of hypertension on cognitive performance.

Background: Observational findings for high-density lipoprotein (HDL)-mediated cholesterol efflux capacity (HDL-CEC) and coronary heart disease (CHD) appear inconsistent, and knowledge of the genetic architecture of HDL-CEC is limited. Objectives: A large-scale observational study on the associations of HDL-CEC and other HDL-related measures with CHD and the largest genome-wide association study (GWAS) of HDL-CEC. Participants/methods: Six independent cohorts were included with follow-up data for 14,438 participants to investigate the associations of HDL-related measures with incident CHD (1,570 events). The GWAS of HDL-CEC was carried out in 20,372 participants. Results: HDL-CEC did not associate with CHD when adjusted for traditional risk factors and HDL cholesterol (HDL-C). In contradiction, almost all HDL-related concentration measures associated consistently with CHD after corresponding adjustments. There were no genetic loci associated with HDL-CEC independent of HDL-C and triglycerides. Conclusion: HDL-CEC is not unequivocally associated with CHD in contrast to HDL-C, apolipoprotein A-I, and most of the HDL subclass particle concentrations. publishedVersion

Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry metaanalysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk., United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Heart Lung & Blood Institute (NHLBI) R01HL127564 R01HL142711, Wellcome Trust 201543/B/16/Z 202802/Z/16/Z, European Commission HEALTH-F2-2013-601456 608765 786833, TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation NNF15CC0018486, American Diabetes Association 1-19-ICTS-068, Academy of Finland 312062 Finnish Foundation for Cardiovascular Research, Sigrid Juselius Foundation, Finnish innovation fund Sitra (EW) Finska Lakaresallskapet, American Heart Association 15POST24470131 17POST33650016, University of Bristol NIHR Biomedical Research Centre BRC-1215-2001, MRC & WT 217065/Z/19/Z, UK Research & Innovation (UKRI), Medical Research Council UK (MRC) MC_UU_00011, CRUK Integrative Cancer Epidemiology Programme C18281/A19169, Medical Research Council UK (MRC) MC_UU_00011/1, UK National Institute for Health Research Academic Clinical Fellowship, American Heart Association 18CDA34110116, Miguel Servet contract from the ISCIII Spanish Health Institute CP17/00142, European Social Fund (ESF), Westlake Education Foundation, British Heart Foundation FS/14/66/3129 Z01HG200362 R01HL142302 R01HL105756

INTRODUCTIONStudies have suggested sleep duration may be associated with Alzheimer’s disease risk, but findings based on self-reported sleep duration are likely to be influenced by reverse causation and residual confounding bias.METHODSA polygenic score (PGS) for device-measured sleep duration was constructed using LDpred2-auto in 77,770 white British UK Biobank participants. We applied the PGS to 264,746 white British participants independent of the sample from which the PGS was developed. We assessed the association of fifths of genetically predicted sleep duration with Alzheimer’s disease risk (1,451 cases/264,746 individuals over median 12.5y of follow-up).RESULTSThe PGS explained ∼2% of variation in device-measured sleep duration. Compared to individuals in the middle fifth of PGS, those in the highest fifth (indicating ∼15 mins/day longer sleep) had a lower risk of Alzheimer’s disease (HR=0.79[95%CI,0.67-0.94]).DISCUSSIONOur results indicate that genetic predisposition to relatively long sleep duration is associated with a lower Alzheimer’s disease risk.

Despite early interest, the evidence linking fatty acids to cardiovascular diseases remains controversial. We used Mendelian randomization to explore the involvement of polyunsaturated (PUFA) and monounsaturated (MUFA) fatty acids biosynthesis in the aetiology of several cardiovascular disease endpoints in up to 1,153,768 European and 212,453 East Asian ancestry individuals. As instruments, we selected single nucleotide polymorphisms (SNP) 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 cardiovascular diseases, 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 genetically-determined PUFA and MUFA biosynthesis are involved in the aetiology of cardiovascular diseases and suggest LDL-cholesterol as a potential mediating trait between PUFA biosynthesis and cardiovascular diseases risk.

Objective: Depression and chronic widespread pain (CWP) frequently coexist, but whether depression is an independent causal risk factor for CWP, and/or vice versa, remains unclear. We investigated the bidirectional causal relationship between depression and CWP.Methods: We performed a two‐sample Mendelian randomization (MR) study to estimate the causal relationship between genetically predicted depression (170,756 cases, 329,443 controls) and risk of CWP (6,914 cases, 242,929 controls), and the effect of CWP on depression susceptibility, using large population level genetic data. We used a new MR method, Causal Analysis Using Summary Effect estimates (CAUSE), which allows for sample overlap, in addition to traditional MR and sensitivity analyses.Results: For each doubling in odds of genetic liability to depression, the risk of chronic widespread pain was increased (OR 1.004, 95% credible interval 1.003-1.005; p=7.3x10-5 that the causal model is a better fit than non-causal model). There was bidirectional evidence of causality, with genetic liability to chronic widespread pain increasing depression susceptibility (OR 2.31; 95%CrI 1.57, 3.40; p=0.0026 that the causal model is a better fit). Other MR methods produced concordant results.Conclusions: This study provides evidence in support of a bidirectional causal relationship between depression and increased risk of chronic widespread pain, whilst overcoming the major limitations of previous epidemiological studies. Interventions for depression may be an effective strategy to prevent or reduce the burden of chronic widespread pain and vice versa.

Background Visceral fat (VF) increases risk for cardiometabolic disease (CMD), the leading cause of morbidity and mortality. Variations in the circulating metabolome predict the risk for CMD but whether or not this is related to VF is unknown. Further, CMD is now also present in adolescents, and the relationships between VF, circulating metabolome, and CMD may vary between adolescents and adults. Methods With an aim to add understanding to the metabolic variations in visceral obesity, we tested associations between VF, measured directly with magnetic resonance imaging, and 228 fasting serum metabolomic measures, quantified with nuclear magnetic resonance spectroscopy, in 507 adults (36–65 years) and 938 adolescents (12–18 years). We further utilized data from published studies to estimate similarities between VF and CMD-associated metabolic profiles. Results Here we show that VF, independently of body mass index (BMI) or subcutaneous fat, is associated with triglyceride-rich lipoproteins, fatty acids, and inflammation in both adults and adolescents, whereas the associations with amino acids, glucose, and intermediary metabolites are significant in adults only. BMI-adjusted metabolomic profile of VF resembles those predicting type 2 diabetes in adults (R2 = 0.88) and adolescents (R2 = 0.70), and myocardial infarction in adults (R2 = 0.59) and adolescents (R2 = 0.40); this is not the case for ischemic stroke (adults: R2 = 0.05, adolescents: R2 = 0.08). Conclusions Visceral adiposity is associated with metabolomic profiles predictive of type 2 diabetes and myocardial infarction even in normal-weight individuals and already in adolescence. Targeting factors contributing to the emergence and maintenance of these profiles might ameliorate their cumulative effects on cardiometabolic health.

BackgroundKidney stone disease (KSD) is linked to obesity, metabolic syndrome and biochemical alterations including higher serum calcium concentration. The mechanisms by which these phenotypes associate with KSD are uncertain. We aimed to establish the effects of adiposity on KSD using conventional and genetic epidemiological techniques.MethodsWe assessed observational associations between measures of adiposity and incident KSD in 479,405 people from the UK Biobank. To facilitate Mendelian randomization (MR) analyses, we undertook genome-wide association studies (GWAS) of KSD in the UK Biobank in combined and sex-specific subsets. Univariable, multivariable and mediation MR analyses were used to calculate odds ratio (OR) or beta coefficient (ß) for risk of KSD per genetically instrumented higher marker of adiposity, metabolic syndrome parameter, biochemical phenotype, and inflammation and identify violations of MR assumptions.FindingsObservational analyses demonstrated that measures of central adiposity (waist-to-hip ratio (WHR) and waist circumference (WC)) are more strongly associated with incident KSD than measures of general adiposity (body mass index (BMI)). Three novel KSD-GWAS loci were identified (SLC2A12, TRPV5, and SLC28A1); no sex-specific loci were detected. MR analyses established that higher central adiposity is causally linked to both KSD and higher adjusted serum calcium concentrations independent of BMI (one standard deviation higher WHR: OR for KSD=1·43, p=4·1×10−6; ß for serum calcium concentration=0·11mmol/L, p=2·7×10−7). Mediation analyses indicated that 12% of the effect of WHR on KSD is due its role in elevating serum calcium concentration. Our MR studies indicated that other components of the metabolic syndrome, serum uric acid levels, and biomarkers of inflammation are unlikely to be implicated in the causation of KSD.InterpretationOur study indicates that visceral adipose depots elevate serum calcium concentration and cause an increased risk of KSD. Therapies targeting central adipose deposition may affect calcium homeostasis and have utility for the prevention of KSD.

Background Despite early interest in the health effects of polyunsaturated fatty acids (PUFA), there is still substantial controversy and uncertainty on the evidence linking PUFA to cardiovascular diseases (CVDs). We investigated the effect of plasma concentration of omega-3 PUFA (i.e. docosahexaenoic acid (DHA) and total omega-3 PUFA) and omega-6 PUFA (i.e. linoleic acid and total omega-6 PUFA) on the risk of CVDs using Mendelian randomization. Methods We conducted the largest genome-wide association study (GWAS) of circulating PUFA to date including a sample of 114,999 individuals and incorporated these data in a two-sample Mendelian randomization framework to investigate the involvement of circulating PUFA on a wide range of CVDs in up to 1,153,768 individuals of European ancestry (i.e. coronary artery disease, ischemic stroke, haemorrhagic stroke, heart failure, atrial fibrillation, peripheral arterial disease, aortic aneurysm, venous thromboembolism and aortic valve stenosis). Results GWAS identified between 46 and 64 SNPs for the four PUFA traits, explaining 4.8–7.9% of circulating PUFA variance and with mean F statistics >100. Higher genetically predicted DHA (and total omega-3 fatty acids) concentration was related to higher risk of some cardiovascular endpoints; however, these findings did not pass our criteria for multiple testing correction and were attenuated when accounting for LDL-cholesterol through multivariable Mendelian randomization or excluding SNPs in the vicinity of the FADS locus. Estimates for the relation between higher genetically predicted linoleic acid (and total omega-6) concentration were inconsistent across different cardiovascular endpoints and Mendelian randomization methods. There was weak evidence of higher genetically predicted linoleic acid being related to lower risk of ischemic stroke and peripheral artery disease when accounting by LDL-cholesterol. Conclusions We have conducted the largest GWAS of circulating PUFA to date and the most comprehensive Mendelian randomization analyses. Overall, our Mendelian randomization findings do not support a protective role of circulating PUFA concentration on the risk of CVDs. However, horizontal pleiotropy via lipoprotein-related traits could be a key source of bias in our analyses.

Polycystic ovary syndrome (PCOS) is a common complex disease in women with a strong genetic component and downstream consequences for reproductive, metabolic and psychological health. There are currently 19 known PCOS risk loci, primarily identified in women of Han Chinese or European ancestry, and 14 of these risk loci were identified or replicated in a genome-wide association study of PCOS performed in up to 10,074 cases and 103,164 controls of European descent. However, for most of these loci the gene responsible for the association is unknown. We therefore use a Bayesian colocalization approach (Coloc) to highlight genes in PCOS-associated regions that may have a role in mediating the disease risk. We evaluated the posterior probabilities of evidence consistent with shared causal variants between 14 PCOS genetic risk loci and intermediate cellular phenotypes in one protein (N = 3301) and two expression quantitative trait locus datasets (N = 31,684 and N = 80–491). Through these analyses, we identified seven proteins or genes with evidence of a possibly shared causal variant for almost 30% of known PCOS signals, including follicle stimulating hormone and ERBB3, IKZF4, RPS26, SUOX, ZFP36L2, and C8orf49. Several of these potential effector proteins and genes have been implicated in the hypothalamic–pituitary–gonadal signalling pathway and provide an avenue for functional follow-up in order to demonstrate a causal role in PCOS pathophysiology.

ObjectiveTo use the example of the effect of body mass index (BMI) on COVID-19 susceptibility and severity to illustrate methods to explore potential selection and misclassification bias in Mendelian randomisation (MR) of COVID-19 determinants.DesignTwo-sample MR analysis.SettingSummary statistics from the Genetic Investigation of ANthropometric Traits (GIANT) and COVID-19 Host Genetics Initiative (HGI) consortia.Participants681,275 participants in GIANT and more than 2.5 million people from the COVID-19 HGI consortia.ExposureGenetically instrumented BMI.Main outcome measuresSeven case/control definitions for SARS-CoV-2 infection and COVID-19 severity: very severe respiratory confirmed COVID-19 vs not hospitalised COVID-19 (A1) and vs population (those who were never tested, tested negative or had unknown testing status (A2)); hospitalised COVID-19 vs not hospitalised COVID-19 (B1) and vs population (B2); COVID-19 vs lab/self-reported negative (C1) and vs population (C2); and predicted COVID-19 from self-reported symptoms vs predicted or self-reported non-COVID-19 (D1).ResultsWith the exception of A1 comparison, genetically higher BMI was associated with higher odds of COVID-19 in all comparison groups, with odds ratios (OR) ranging from 1.11 (95%CI: 0.94, 1.32) for D1 to 1.57 (95%CI: 1.57 (1.39, 1.78) for A2. As a method to assess selection bias, we found no strong evidence of an effect of COVID-19 on BMI in a ‘no-relevance’ analysis, in which COVID-19 was considered the exposure, although measured after BMI. We found evidence of genetic correlation between COVID-19 outcomes and potential predictors of selection determined a priori (smoking, education, and income), which could either indicate selection bias or a causal pathway to infection. Results from multivariable MR adjusting for these predictors of selection yielded similar results to the main analysis, suggesting the latter.ConclusionsWe have proposed a set of analyses for exploring potential selection and misclassification bias in MR studies of risk factors for SARS-CoV-2 infection and COVID-19 and demonstrated this with an illustrative example. Although selection by socioeconomic position and arelated traits is present, MR results are not substantially affected by selection/misclassification bias in our example. We recommend the methods we demonstrate, and provide detailed analytic code for their use, are used in MR studies assessing risk factors for COVID-19, and other MR studies where such biases are likely in the available data.SummaryWhat is already known on this topic-Mendelian randomisation (MR) studies have been conducted to investigate the potential causal relationship between body mass index (BMI) and COVID-19 susceptibility and severity.-There are several sources of selection (e.g. when only subgroups with specific characteristics are tested or respond to study questionnaires) and misclassification (e.g. those not tested are assumed not to have COVID-19) that could bias MR studies of risk factors for COVID-19.-Previous MR studies have not explored how selection and misclassification bias in the underlying genome-wide association studies could bias MR results.What this study adds-Using the most recent release of the COVID-19 Host Genetics Initiative data (with data up to June 2021), we demonstrate a potential causal effect of BMI on susceptibility to detected SARS-CoV-2 infection and on severe COVID-19 disease, and that these results are unlikely to be substantially biased due to selection and misclassification.-This conclusion is based on no evidence of an effect of COVID-19 on BMI (a ‘no-relevance control’ study, as BMI was measured before the COVID-19 pandemic) and finding genetic correlation between predictors of selection (e.g. socioeconomic position) and COVID-19 for which multivariable MR supported a role in causing susceptibility to infection.-We recommend studies use the set of analyses demonstrated here in future MR studies of COVID-19 risk factors, or other examples where selection bias is likely.

Hypersensitivity reactions to drugs are often unpredictable and can be life threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. We extracted data from the electronic health records of more than 600,000 participants from the UK, Estonian, and Vanderbilt University Medical Center's BioVU biobanks to study the role of genetic variation in the occurrence of self-reported penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from these cohorts to further fine map the human leukocyte antigen (HLA) association and replicated our results in 23andMe's research cohort involving a total of 1.12 million individuals. Genome-wide meta-analysis of penicillin allergy revealed two loci, including one located in the HLA region on chromosome 6. This signal was further fine-mapped to the HLA-B∗55:01 allele (OR 1.41 95% CI 1.33-1.49, p value 2.04 × 10-31) and confirmed by independent replication in 23andMe's research cohort (OR 1.30 95% CI 1.25-1.34, p value 1.00 × 10-47). The lead SNP was also associated with lower lymphocyte counts and in silico follow-up suggests a potential effect on T-lymphocytes at HLA-B∗55:01. We also observed a significant hit in PTPN22 and the GWAS results correlated with the genetics of rheumatoid arthritis and psoriasis. We present robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.

We performed Mendelian randomization analyses of body mass index and waist–hip ratio adjusted for body mass index in Dupuytren’s disease using summary statistics from genome-wide association study meta-analyses. We found that adiposity is causally protective against Dupuytren’s disease, with the inverse-variance weighted Mendelian randomization analysis estimating that a 1 standard deviation increase in body mass index (equivalent to 4.8 kg/m2) leads to 28% (95% confidence interval: 18–37%) lower relative odds of developing Dupuytren’s disease, and a 1 standard deviation increase in waist–hip ratio adjusted for body mass index (equivalent to a waist–hip ratio of 0.09) leads to 26% (95% confidence interval: 6–42%) lower relative odds of developing Dupuytren’s disease. We conclude from this study that regardless of the well-established negative health effects of obesity, the raised body mass index is associated with a lower risk of Dupuytren’s disease and may be causally protective for the development of the disease.

The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here, we estimated the effects of 1002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium (LD) is widespread in naive phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes (www.epigraphdb.org/pqtl/). Evaluation of data from historic drug development programmes showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of our approach in identifying and prioritising potential therapeutic targets.

ObjectiveThere is limited prospective evidence on the association of physical activity with hepatobiliary cancer subtypes and other major hepatobiliary diseases, especially in China. We aimed to quantify the associations with risk of these diseases.MethodsThe study population involved 460 937 participants of the prospective China Kadoorie Biobank aged 30–79 years from 10 diverse areas in China without history of cancer or hepatobiliary disease at baseline. Cox regression was used to estimate adjusted hazard ratios (HRs) for each disease associated with self-reported total and domain-specific physical activity (occupational and non-occupational, ie, leisure time, household and commuting).ResultsDuring ~10 years of follow-up, 22 012 incident cases of hepatobiliary diseases were recorded. The overall mean (SD) total physical activity was 21.2 (13.9) metabolic equivalent of task (MET)-hours/day, with 62% from occupational activity. Total physical activity was inversely associated with hospitalised non-alcoholic fatty liver disease (HR comparing top vs bottom quintile: 0.62, 95% confidence interval (CI) 0.53 to 0.72), viral hepatitis (0.73, 95% CI 0.62 to 0.87), cirrhosis (0.76, 95% CI 0.66 to 0.88) and liver cancer (0.81, 95% CI 0.71 to 0.93), as well as gallstone disease (0.86, 95% CI 0.81 to 0.90), gallbladder cancer (0.51, 95% CI 0.32 to 0.80) and biliary tract cancer (0.55, 95% CI 0.38 to 0.78). The associations for occupational physical activity were similar to those for total physical activity, but for non-occupational physical activity they differed by disease subtype. For leisure-time physical activity, there was an inverse association with liver cancer and an inverse trend for gallstone disease (HR comparing ≥7.5 MET-hours/day with none: 0.83, 95% CI 0.75 to 0.91 and 0.82, 95% CI 0.66 to 1.01).ConclusionAmong Chinese adults, high total physical activity, particularly occupational physical activity, was inversely associated with risk of major hepatobiliary cancers and diseases, including non-alcoholic fatty liver disease, cirrhosis and certain types of cancer.

Background . Ultrasound assessment of myocardial strain allows non-invasive identification of early stages of heart failure with preserved ventricular ejection fraction. A decline of the left ventricle (LV) global longitudinal strain in hypertension (HT) accompanied by LV hypertrophy (LVH) was reported in clinical samples with manifest HT. Data on the relationship between longitudinal strain and blood pressure (BP) and HT in general population is lacking. Objective . We studied the relationship between LV peak systolic global longitudinal strain ( GLS ) and strain rate ( GSR ) in subjects with high and controlled BP from a general population sample aged over 55 years. Design and methods . The cross-sectional study was based on a population cohort (HAPIEE, Novosibirsk). In a random sample (n = 416, aged 55–84 years old) we performed echocardiography and evaluated GLS and GSR of LV by speckle tracking technique. ANOVA multivariable models were applied. Results. In the studied sample, the prevalence of HT comprised 78,9 %. The mean GLS value was –18,7 ± 3,79 %, and it was lower in men than in women (–18,2 ± 3,85 % vs –19,2 ± 3,66 %, p = 0,005). The mean GSR value was –0,84 ± 0,17s –1 , and did not differ by sex. The absolute value of GLS in HT was lower than in normotensives: –18,5 ± 3,73 % vs –19,9 ± 3,42 %, p = 0,003; this difference was independent of age, sex and LV myocardial mass index (IMM), p = 0,011; but it was attenuated in a multivariable-adjusted model including body mass index (BMI). In HT groups, the GLS was the lowest among those “treated ineffectively” and significantly lower than in normotensives independently of age, sex and myocardium mass index (p = 0,008). The absolute value of GSR in HT was lower than in normotensives: –0,90 ± 0,17 s –1 vs –0,83 ± 0,17s –1 , p < 0,001; and persisted in multivariable models. GSR was the lowest among those “treated ineffectively” and significantly lower than in normotensives in multivariable models independently of age, sex, BMI and myocardial mass index (p = 0,017; 0,002). The average values of LV ejection fraction (Simpson) in all groups were above 50 % without significant inter-group differences (p = 0,904). conclusions. In the studied population sample, GLS and GSR of LV were associated with HT; however, the association between GLS and HT was largely explained by BMI. In hypertensives, the lowest GLS and GSR , as well as higher extent of LVH, were found among those treated ineffectively, which might point at the initial reduction of systolic ventricular function in HT with inadequate BP control.

We respond to criticisms of Mendelian randomization (MR) by Mukamal, Stampfer and Rimm (MSR). MSR consider that MR is receiving too much attention and should be renamed. We explain how MR links to Mendel’s laws, the origin of the name and our lack of concern regarding nomenclature. We address MSR’s substantive points regarding MR of alcohol and cardiovascular disease, an issue on which they dispute the MR findings. We demonstrate that their strictures with respect to population stratification, confounding, weak instrument bias, pleiotropy and confounding have been addressed, and summarise how the field has advanced in relation to the issues they raise. We agree with MSR that “the hard problem of conducting high-quality, reproducible epidemiology” should be addressed by epidemiologists. However we see more evidence of confrontation of this issue within MR, as opposed to conventional observational epidemiology, within which the same methods that have demonstrably failed in the past are simply rolled out into new areas, leaving their previous failures unexamined.

The mitochondrial DNA (mtDNA) copy number was analyzed via quantitative real-time PCR. A random subset of 996 people was studied (437 men with an average age of 67.3 ± 7.2 years and 559 women with an average age of 67.6 ± 7.1 years). They were selected from a population cohort of 9360 people who were initially examined in the international HAPIEE project (2003–2005, initial age of 45–69 years) in Novosibirsk. The participants were reexamined after 12 years in 2015–2017. The average relative mtDNA copy number in women was significantly higher than in men, regardless of age and smoking status, p = 0.001. The relative mtDNA copy number of blood leukocytes negatively correlated with age in men (p = 0.005) and women (p < 0.001). In the age-standardized analysis, the mtDNA copy number was negatively associated with waist and hip size and heart rate in people of both genders. Associations with some other indicators depend on gender. In women, the mtDNA copy number was negatively associated with the atherogenicity level, body mass indices, and blood glucose level and positively associated with HDL cholesterol. In men, the mtDNA copy number is positively related to the level of physical activity. Regardless of age, the average relative mtDNA copy number in peripheral blood leukocytes was higher in nonsmoking men than in smokers (p = 0.003). The mtDNA copy number was lower in women with diabetes mellitus than in women without it (p = 0.005). In both genders, people with an initial history of arterial hypertension had a lower mtDNA copy number in peripheral blood leukocytes after 12 years of observation than normotonics (p = 0.05). These results broadly support the hypothesis that the mtDNA copy number may act as a biomarker of age.

Large-scale molecular profiling and genotyping provide a unique opportunity to systematically compare the genetically predicted effects of therapeutic targets on the human metabolome. We firstly constructed genetic risk scores for 8 drug targets on the basis that they primarily modify low-density lipoprotein (LDL) cholesterol (HMGCR, PCKS9, and NPC1L1), high-density lipoprotein (HDL) cholesterol (CETP), or triglycerides (APOC3, ANGPTL3, ANGPTL4, and LPL). Conducting mendelian randomisation (MR) provided strong evidence of an effect of drug-based genetic scores on coronary artery disease (CAD) risk with the exception of ANGPTL3. We then systematically estimated the effects of each score on 249 metabolic traits derived using blood samples from an unprecedented sample size of up to 115,082 UK Biobank participants. Genetically predicted effects were generally consistent among drug targets, which were intended to modify the same lipoprotein lipid trait. For example, the linear fit for the MR estimates on all 249 metabolic traits for genetically predicted inhibition of LDL cholesterol lowering targets HMGCR and PCSK9 was r2 = 0.91. In contrast, comparisons between drug classes that were designed to modify discrete lipoprotein traits typically had very different effects on metabolic signatures (for instance, HMGCR versus each of the 4 triglyceride targets all had r2 < 0.02). Furthermore, we highlight this discrepancy for specific metabolic traits, for example, finding that LDL cholesterol lowering therapies typically had a weak effect on glycoprotein acetyls, a marker of inflammation, whereas triglyceride modifying therapies assessed provided evidence of a strong effect on lowering levels of this inflammatory biomarker. Our findings indicate that genetically predicted perturbations of these drug targets on the blood metabolome can drastically differ, despite largely consistent effects on risk of CAD, with potential implications for biomarkers in clinical development and measuring treatment response.

Publisher Copyright: © 2022 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. Previous studies had limited power to assess the associations of testosterone with aggressive disease as a primary endpoint. Further, the association of genetically predicted testosterone with aggressive disease is not known. We investigated the associations of calculated free and measured total testosterone and sex hormone-binding globulin (SHBG) with aggressive, overall and early-onset prostate cancer. In blood-based analyses, odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression from prospective analysis of biomarker concentrations in the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group (up to 25 studies, 14 944 cases and 36 752 controls, including 1870 aggressive prostate cancers). In Mendelian randomisation (MR) analyses, using instruments identified using UK Biobank (up to 194 453 men) and outcome data from PRACTICAL (up to 79 148 cases and 61 106 controls, including 15 167 aggressive cancers), ORs were estimated using the inverse-variance weighted method. Free testosterone was associated with aggressive disease in MR analyses (OR per 1 SD = 1.23, 95% CI = 1.08-1.40). In blood-based analyses there was no association with aggressive disease overall, but there was heterogeneity by age at blood collection (OR for men aged

Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel's laws of inheritance and instrumental variable estimation methods, which enable the inference of causal effects in the presence of unobserved confounding. In this Primer, we outline the principles of MR, the instrumental variable conditions underlying MR estimation and some of the methods used for estimation. We go on to discuss how the assumptions underlying an MR study can be assessed and give methods of estimation that are robust to certain violations of these assumptions. We give examples of a range of studies in which MR has been applied, the limitations of current methods of analysis and the outlook for MR in the future. The difference between the assumptions required for MR analysis and other forms of non-interventional epidemiological studies means that MR can be used as part of a triangulation across multiple sources of evidence for causal inference.

Aims/hypothesisMetformin use has been associated with reduced incident dementia in diabetic patients in observational studies. However, the causality between the two in the general population is unclear. This study uses Mendelian randomization (MR) to investigate the causal effect of metformin targets on Alzheimer’s disease (AD) and potential causal mechanisms in the brain linking the two.MethodsGenetic proxies for the effects of metformin drug targets were identified as variants in the gene for the corresponding target that associated with HbA1c level (N=344,182) and expression level of the corresponding gene (N≤31,684). The cognitive outcomes were derived from genome-wide association studies comprising of 527,138 middle-aged Europeans, including 71,880 AD or AD-by-proxy patients. MR estimates representing lifelong metformin use on AD and cognitive function in the general population were generated. Effect of expression level of 22 metformin-related genes in brain cortex (N=6,601 donors) on AD was further estimated.ResultsGenetically proxied metformin use equivalent to a 6.75 mmol/mol (1.09%) reduction of HbA1c was associated with 4% lower odds of AD (odds ratio [OR]=0.964, 95%CI=0.982∼0.946, P=1.06×10−4) in non-diabetic individuals. One metformin target, mitochondrial complex 1 (MCI), showed a robust effect on AD (OR=0.88, P=4.73×10−4) that was independent of AMPK. MR of expression in brain cortex tissue showed that decreased MCI-related gene, NDUFA2, expression was associated with reduced AD risk (OR=0.95, P=4.64×10−4) and less cognitive decline.Conclusion/interpretationMetformin use is likely to cause reduced AD risk in the general population. Mitochondrial function and the NDUFA2 gene are likely mechanisms of action in dementia protection.Research in contextWhat is already known about this subjectMetformin is an anti-diabetic drug with repurposing potential for dementia prevention.In a search of PubMed, Embase and clinicaltrials.gov, a few observational studies suggested the association of metformin use with reduced dementia incidence in diabetic patientsWhat is the key question?What is the effect of genetically proxied metformin use on Alzheimer’s disease (AD) and cognitive function in the general population, especially for those without diabetes? Is the causal role between the two at least partly influenced by mechanisms in the brain?What are the new findings?In a Mendelian randomization analysis of over 527,138 individuals (71,880 AD or AD-by-proxy cases), genetically proxied metformin use equivalent to a 6.75 mmol/mol (1.09%) reduction of HbA1c was associated with 14% lower odds of AD (odds ratio=0.86), where mitochondrial complex I is a key effect modifier.Expression level of a mitochondrial complex I related gene, NDUFA2, showed an effect on reducing AD risk and less cognitive decline in brain.How might this impact on clinical practice in the foreseeable future?Our study predicts the efficacy of metformin on reducing AD risk and reducing cognitive decline in the general population, especially for those without diabetes.Mitochondrial function and a mitochondrial related gene, NDUFA2, could be considered as a novel drug target for dementia prevention.Graphical abstractTweet Effect of metformin targets reduced 4% of Alzheimer’s disease risk in non-diabetic individuals. @oldz84 @tomgaunt @mendel_random @mrc_ieu

Aims Obesity and kidney diseases are common complex disorders with an increasing clinical and economic impact on healthcare around the globe. Our objective was to examine if modifiable anthropometric obesity indices show putatively causal association with kidney health and disease and highlight biological mechanisms of potential relevance to the association between obesity and the kidney. Methods and results We performed observational, one-sample, two-sample Mendelian randomization (MR) and multivariable MR studies in ∼300 000 participants of white-British ancestry from UK Biobank and participants of predominantly European ancestry from genome-wide association studies. The MR analyses revealed that increasing values of genetically predicted body mass index and waist circumference were causally associated with biochemical indices of renal function, kidney health index (a composite renal outcome derived from blood biochemistry, urine analysis, and International Classification of Disease-based kidney disease diagnoses), and both acute and chronic kidney diseases of different aetiologies including hypertensive renal disease and diabetic nephropathy. Approximately 13–16% and 21–26% of the potentially causal effect of obesity indices on kidney health were mediated by blood pressure and type 2 diabetes, respectively. A total of 61 pathways mapping primarily onto transcriptional/translational regulation, innate and adaptive immunity, and extracellular matrix and metabolism were associated with obesity measures in gene set enrichment analysis in up to 467 kidney transcriptomes. Conclusions Our data show that a putatively causal association of obesity with renal health is largely independent of blood pressure and type 2 diabetes and uncover the signatures of obesity on the transcriptome of human kidney.

Background Peripheral artery disease (PAD) and coronary artery disease (CAD) represent atherosclerosis in different vascular beds. We used detailed metabolic biomarker profiling to identify common and discordant biomarkers and clarify pathophysiological differences for these vascular diseases. Methods and Results We used 5 prospective cohorts from Finnish population (FINRISK 1997, 2002, 2007, and 2012, and Health 2000; n=31 657; median follow‐up time of 14 years) to estimate associations between >200 metabolic biomarkers and incident PAD and CAD. Metabolic biomarkers were measured with nuclear magnetic resonance, and disease events were obtained from nationwide hospital records. During the follow‐up, 498 incident PAD and 2073 incident CAD events occurred. In age‐ and sex‐adjusted Cox models, apolipoproteins and cholesterol measures were robustly associated with incident CAD (eg, hazard ratio [HR] per SD for higher apolipoprotein B/A‐1 ratio, 1.30; 95% CI, 1.25–1.36), but not with incident PAD (HR per SD for higher apolipoprotein B/A‐1 ratio, 1.04; 95% CI, 0.95–1.14; P heterogeneity P heterogeneity >0.05). Lower proportion of polyunsaturated fatty acids relative to total fatty acids, and higher concentrations of monounsaturated fatty acids, glycolysis‐related metabolites, and inflammatory protein markers were strongly associated with incident PAD, and many of these associations were stronger for PAD than for CAD ( P heterogeneity Conclusions The metabolic biomarker profile for future PAD risk is distinct from that of CAD. This may represent pathophysiological differences.

Triangulation of evidence from clinical trials and human genetics suggests a potential excess risk of cardiovascular disease events arising from therapeutic inhibition of sclerostin.

Polygenic risk scores (PRS) are becoming an increasingly popular approach to predict complex disease risk, although they also hold the potential to develop insight into the molecular profiles of patients with an elevated genetic predisposition to disease. In this study, we have constructed an atlas of associations between 129 different PRS and 249 circulating metabolites in up to 83,004 participants from the UK Biobank study. As an exemplar to demonstrate the value of this atlas we conducted a hypothesis-free evaluation of all associations with glycoprotein acetyls (GlycA), an inflammatory biomarker. Using bi-directional Mendelian randomization, we find that the associations highlighted likely reflect the effect of risk factors, such as body mass index (Beta=0.16 per standard deviation change in GlycA, 95% CI=0.11 to 0.21, P=9.9×10−10) or liability towards smoking cigarettes (Beta=0.28, 95% CI=0.20 to 0.35, P=2.4×10−14), on systemic inflammation as opposed to the converse direction of effect. Furthermore, we repeated all analyses in our atlas within age strata to investigate potential sources of collider bias, such as medication usage. This was exemplified by comparing associations between lipoprotein lipid profiles and the coronary artery disease PRS in the youngest and oldest age strata, which had differing proportions of individuals undergoing statin therapy. All results can be visualised athttp://mrcieu.mrsoftware.org/metabolites_PRS_atlas.

Aims The HERMES (HEart failure Molecular Epidemiology for Therapeutic targets) consortium aims to identify the genomic and molecular basis of heart failure.Methods and results The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34-90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of >1.10 for common variants (allele frequency > 0.05) and >1.20 for low-frequency variants (allele frequency 0.01-0.05) at P < 5 x 10(-8) under an additive genetic model.Conclusions HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.

Background: The direct effects of general adiposity (body mass index (BMI)) and central adiposity (waist-to-hip-ratio (WHR)) on circulating lipoproteins, lipids, and metabolites are unknown.Methods: We used new metabolic data from UK Biobank (N=109,532, a five-fold higher N over previous studies). EDTA-plasma was used to quantify 249 traits with nuclear-magnetic-resonance spectroscopy including subclass-specific lipoprotein concentrations and lipid content, plus preglycemic and inflammatory metabolites. We used univariable and multivariable two-stage leastsquares regression models with genetic risk scores for BMI and WHR as instruments to estimate total (unadjusted) and direct (mutually-adjusted) effects of BMI and WHR on metabolic traits; plus effects on statin use and interaction by sex, statin use, and age (proxy for medication use).Findings: Higher BMI decreased apolipoprotein B and low-density lipoprotein cholesterol (LDL-C) before and after WHR-adjustment, whilst BMI increased triglycerides only before WHR-adjustment. These effects of WHR were larger and BMI-independent. Direct effects differed markedly by sex, e.g., triglycerides increased only with BMI among men, and only with WHR among women.Adiposity measures increased statin use and showed metabolic effects which differed by statin use and age. Among the youngest (38-53y, statins-5%), BMI and WHR (per-SD) increased LDL-C (total effects: 0.04-SD, 95%CI=-0.01,0.08 and 0.10-SD, 95%CI=0.02,0.17 respectively), but only WHR directly. Among the oldest (63-73y, statins-29%), BMI and WHR directly lowered LDL-C (-0.19-SD, 95%CI=-0.27,-0.11 and -0.05-SD, 95%CI=-0.16,0.06 respectively).Interpretation: Excess adiposity likely raises atherogenic lipid and metabolite levels exclusively via adiposity stored centrally, particularly among women. Apparent effects of adiposity on lowering LDL-C are likely explained by an effect of adiposity on statin use.

The virus SARS-CoV-2 can exploit biological vulnerabilities (e.g. host proteins) in susceptible hosts that predispose to the development of severe COVID-19.To identify host proteins that may contribute to the risk of severe COVID-19, we undertook proteome-wide genetic colocalisation tests, and polygenic (pan) and cis-Mendelian randomisation analyses leveraging publicly available protein and COVID-19 datasets.Our analytic approach identified several known targets (e.g. ABO, OAS1), but also nominated new proteins such as soluble Fas (colocalisation probability0.9, p=1 × 10Our work provides a prioritised list of host targets potentially exploited by SARS-CoV-2 and is a precursor for further research on CD209 and FAS as therapeutically tractable targets for COVID-19.MAK, JSc, JH, AB, DO, MC, EMM, MG, ID were funded by Open Targets. J.Z. and T.R.G were funded by the UK Medical Research Council Integrative Epidemiology Unit (MC_UU_00011/4). JSh and GJW were funded by the Wellcome Trust Grant 206194. This research was funded in part by the Wellcome Trust [Grant 206194]. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.Individuals who become infected with the virus that causes COVID-19 can experience a wide variety of symptoms. These can range from no symptoms or minor symptoms to severe illness and death. Key demographic factors, such as age, gender and race, are known to affect how susceptible an individual is to infection. However, molecular factors, such as unique gene mutations and gene expression levels can also have a major impact on patient responses by affecting the levels of proteins in the body. Proteins that are too abundant or too scarce may mean the difference between dying from or surviving COVID-19. Identifying the molecular factors in a host that affect how viruses can infect individuals, evade immune defences or trigger severe illness, could provide new ways to treat patients with COVID-19. Such factors are likely to remain constant, even when the virus mutates into new strains. Hence, insights would likely apply across all virus strains, including current strains, such as alpha and delta, and any new strains that may emerge in the future. Using such a ‘natural experiment’ approach, Karim et al. compared the genetic profiles of over 30,000 COVID-19 patients and a million healthy individuals. Nine proteins were found to have an impact on COVID-19 infection and disease severity. Four proteins were ranked as top priorities for potential treatment targets. One protein, called CD209 (also known as DC-SIGN), is involved in how the virus enters the host cells, and had one of the strongest associations with COVID-19. Two proteins, called IL-6R and FAS, were involved in the immune response and could be responsible for the immune over-activation often seen in severe COVID-19. Finally, one protein, called OAS1, formed part of the body’s innate antiviral defence system and appeared to reduce susceptibility to COVID-19. Knowing more about the proteins that influence the severity of COVID-19 opens up new ways to predict, protect and treat patients who may have severe or fatal reactions to infection. Indeed, one of the identified proteins (IL-6R) had already been targeted in recent clinical trials with some encouraging results. Considering CD209 as a potential receptor for the virus could provide another avenue for therapeutics, similar to previously successful approaches to block the virus’ known interaction with a receptor protein. Ultimately, this research could supply an entirely new set of treatment options to help combat the COVID-19 pandemic.

BackgroundLarge-scale molecular profiling and genotyping provide a unique opportunity to systematically compare the genetically predicted effects of therapeutic targets on the human metabolome.MethodsWe firstly constructed genetic risk scores for 8 drug targets on the basis that they primarily modify low-density lipoprotein (LDL) cholesterol (HMGCR, PCKS9 & NPC1L1), high-density lipoprotein (HDL) cholesterol (CETP), or triglycerides (APOC3, ANGPTL3, ANGPTL4 & LPL). We then used Mendelian randomization to evaluate the effect of each score on coronary artery disease (CAD) risk, and to systematically estimate their effects on 249 metabolic traits derived using blood samples from an unprecedented sample size of up to 115,082 UK Biobank participants.ResultsThere was strong evidence of an effect of drug-based genetic scores on CAD risk with the exception of ANGPTL3. Genetically predicted effects on the blood metabolome were generally consistent amongst drug targets which were intended to modify the same lipoprotein lipid trait. For example, the linear fit for the MR estimates on all 249 metabolic traits for genetically-predicted inhibition of LDL cholesterol lowering targets HMGCR and PCSK9 was r2=0.91. In contrast, comparisons between drug classes that were designed to modify discrete lipoprotein traits typically had very different effects on metabolic signatures (e.g. HMGCR vs all 4 triglyceride targets had r2−50).ConclusionsMultiple lipid-modifying drug targets have therapeutically beneficial effects on CAD risk. Our findings indicate that genetically predicted perturbations of these drug targets on the blood metabolome can drastically differ, with potential implications for biomarkers in clinical development and measuring treatment response.

Background: Gallstone disease (GSD) is associated with a higher risk of gastrointestinal (GI) cancer. However, it is unclear whether the associations are causal. Methods: The prospective China Kadoorie Biobank (CKB) recorded 17,598 cases of GI cancer among 510,137 participants without cancer at baseline during 10 years of follow-up. Cox regression was used to estimate hazard ratios (HRs) for specific cancer by GSD status and duration. Mendelian randomisation was conducted to assess the genetic associations of GSD with specific cancer. Results: Overall 6% of participants had symptomatic GSD at baseline. Compared with those without GSD, individuals with symptomatic GSD had adjusted HRs of 1.13 (1.01–1.29) for colorectal, 2.01 (1.78–2.26) for liver, 3.70 (2.88–4.87) for gallbladder, 2.31 (1.78–3.07) for biliary tract, and 1.38 (1.18–1.74) for pancreatic cancer. Compared with participants without GSD, the risks of colorectal, liver, gallbladder, biliary tract, and pancreatic cancer were highest during 0 to Conclusions: GSD was associated with higher risks of several GI cancers, warranting future studies on the underlying mechanisms.

Observational studies demonstrate an inverse association between type II diabetes and abdominal aortic aneurysm (AAA) for reasons that are unclear. The aim of this study was to clarify the causal association between type II diabetes predisposition and AAA using Mendelian randomisation.Effect estimates for single nucleotide polymorphisms (SNPs) associated with diabetes were obtained from the DIAbetes Meta-ANalysis of Trans-Ethnic association studies (DIAMANTE) consortium to construct a genetic instrumental variable. Corresponding effect estimates for associations of these SNPs with AAA were obtained from the International Aneurysm Consortium comprising six separate AAA genomewide association studies (4 972 cases and 99 858 controls). Mendelian randomisation estimates were calculated using inverse variance, weighted median, and MR-Egger methods, and compared against recently published observational estimates.A genetic risk score was constructed from 206 SNPs associated with diabetes. All three Mendelian randomisation models showed no effect of genetic liability to diabetes and risk of AAA (inverse variance: odds ratio 1.04 per unit higher log odds, 95% 0.98 - 1.11, p = .19; MR-Egger slope p = .33; weighted median p = .50). Results were similar after excluding the TCF7L2 locus (inverse variance p = .075). Findings from the Mendelian randomisation analysis differed from previous observational reports of an inverse association (pLifelong genetic predisposition to diabetes does not appear to protect against AAA. These findings differ from traditional epidemiological studies showing an inverse association between diabetes and AAA, for reasons that remain unclear.

OBJECTIVE The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF). RESEARCH DESIGN AND METHODS Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators. RESULTS Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11–1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00–1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01–2.19; P = 0.042), although again with evidence of pleiotropy. CONCLUSIONS These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered.

BackgroundThe causal impact of excess adiposity on systemic metabolism is unclear. We used multivariable Mendelian randomization to compare the direct effects of total adiposity (using body mass index (BMI)) and abdominal adiposity (using waist-to-hip-ratio (WHR)) on circulating lipoproteins, lipids, and metabolites with a five-fold increase in sample size over previous studies.MethodsWe used new metabolic data on 109,532 UK Biobank participants. BMI and WHR were measured in 2006-2010, during which EDTA plasma was collected. Plasma samples were used in 2019-2020 to quantify 249 metabolic traits with high-throughput nuclear magnetic resonance spectroscopy including subclass-specific lipoprotein concentrations, apolipoprotein B, cholesterol and triglycerides, plus pre-glycemic and inflammatory metabolites. We used two-stage least squares regression models with genetic risk scores for BMI and WHR as instruments to estimate the total (unadjusted) and direct (mutually adjusted) effects of BMI and WHR on metabolic traits. We also estimated the effects of BMI and WHR on statin use, and examined interaction of main effects by sex, statin use, and age as a proxy for medication use.ResultsHigher BMI (per standard deviation (SD) or 4.8 kg/m2) was estimated to moderately decrease apolipoprotein B and low-density lipoprotein (LDL) cholesterol before and after adjustment for WHR, whilst higher BMI increased triglycerides before but not after WHR adjustment. Estimated effects of higher WHR (per SD, or 0.090 ratio-unit) on lipoproteins, lipids, and metabolites were often larger than those of BMI, but null for LDL cholesterol, and attenuations were minimal upon adjustment for BMI. Patterns of effect estimates differed by sex, e.g., only BMI independently increased triglycerides among men, whereas only WHR independently increased triglycerides among women. Higher BMI and WHR (per SD) were each estimated to directly increase the relative odds of using statins (by 3.49 (95% CI = 3.42, 3.57) times higher for WHR). These patterns were most pronounced among women, and there was strong evidence that the effects of BMI and WHR on metabolic traits differed by statin use and age. Among the youngest adults (38-53 years, statin use 5%), higher BMI and WHR (per SD) each modestly increased LDL cholesterol (0.04 SD, 95% CI = -0.01, 0.08 for total effect of BMI and 0.10 SD, 95% CI = 0.02, 0.17 for total effect of WHR). This estimate for BMI fully attenuated, and the estimate for WHR remained unchanged, upon mutual adjustment. These direct effects on LDL cholesterol were more inverse for BMI and less positive for WHR at intermediate ages (54-62 years, statins 17%) and older ages (63-73 years, statins 29%) where the mutually adjusted effects of BMI and WHR on LDL cholesterol had reversed to -0.19 SD (95% CI = -0.27, -0.11) and -0.05 SD (95% CI = -0.16, 0.06), respectively.ConclusionsOur results suggest that abdominal adiposity has a dominant role in driving the metabolic harms of excess adiposity, particularly among women. Our findings also suggest that apparent effects of adiposity on lowering LDL cholesterol are explained by an effect of adiposity on statin use.

Background Apolipoprotein B (apoB) is emerging as the lipoprotein entity that is critical for the role that lipoprotein lipids play in the aetiology of coronary heart disease (CHD). In this study, we explored effects of genetically-predicted apoB on endpoints in first-degree relatives. Methods Univariable Mendelian randomization (MR) used a weighted genetic instrument (229 SNPs) for apoB. For endpoints that apoB associated with at FDR Findings Parents were less likely to be alive with 10.7 months of life lost in fathers (95%CI: 7.6, 13.9; FDR-adjusted P=4.0×10−10) and 5.8 months of life lost in mothers (95%CI: 3.0, 8.52; FDR-adjusted P=1.7×10−4) per 1-SD higher apoB in offspring. Effects strengthened to ∼2 yrs of life lost in multivariable MR and replicated in conventional two-sample MR (OR surviving to 90th centile: 0.38; 95%CI: 0.22, 0.65). Genetically-elevated apoB caused higher risks of heart disease in all first-degree relatives and higher risk of stroke in mothers. Findings in first-degree relatives were replicated in two-sample multivariable MR which identified apoB to increase (OR 2.32; 95%CI: 1.49, 3.61) and LDL-C lower (OR 0.34; 95%CI: 0.21, 0.54) risk of T2D. Interpretation Higher apoB shortens the lifespan, and increases risks of heart disease and stroke. T2D effects may represent injurious effects of dyslipidaemia to pancreatic islets. Research in Context Evidence before this study Prior observational and Mendelian randomization studies have indicated that circulating concentrations of apoB are of critical importance to lipid-mediated atherogenesis, manifest as coronary heart disease. Added value of this study In this study, we explored the effects of genetically-predicted elevations in apoB on multiple endpoints occuring in first degree relatives including longevity and sought replication of findings using more conventional methods to exploit the statistical power from data available in large-scale GWAS consortia. We identified that apoB had a deleterious effect on longevity, shortening the lifespan by months to years. Furthermore, apoB caused higher risks of CHD and stroke in first degree relatives. Finally, apoB was identified to increase risk of T2D, in contradistinction to LDL-C which lowered risk of T2D, when employing multivairable MR methods. Implications of all the available evidence Our findings support apoB as being the major lipoprotein entity critical for CHD and stroke and extends this to identify higher apoB as negatively impacting longevity and increasing risk of T2D. These findings highlight the critical role of apoB in causing cardiometabolic disease, which collectively shortens the lifespan.

Background Quantitative molecular data from urine are rare in epidemiology and genetics. NMR spectroscopy could provide these data in high throughput, and it has already been applied in epidemiological settings to analyse urine samples. However, quantitative protocols for large-scale applications are not available. Methods We describe in detail how to prepare urine samples and perform NMR experiments to obtain quantitative metabolic information. Semi-automated quantitative line shape fitting analyses were set up for 43 metabolites and applied to data from various analytical test samples and from 1004 individuals from a population-based epidemiological cohort. Novel analyses on how urine metabolites associate with quantitative serum NMR metabolomics data (61 metabolic measures; n = 995) were performed. In addition, confirmatory genome-wide analyses of urine metabolites were conducted (n = 578). The fully automated quantitative regression-based spectral analysis is demonstrated for creatinine and glucose (n = 4548). Results Intra-assay metabolite variations were mostly Conclusion Quantitative urine metabolomics data suggest broad novelty for systems epidemiology. A roadmap for an open access methodology is provided.

Age-related cognitive changes in the Russian population have not been sufficiently studied.Objective: to assess the time course of changes in cognitive functions (CF) in two serial measurements 9 years apart in the urban population of middle, elder, and senile age and their relationship to education level.Patients and methods. A random male and female sample of45-69-year-old Novosibirsk residents (n=9360; HAPIEE project) was surveyed. CF was tested by standard methods. Resurvey was conducted in a random subsample (n=1663) included in this analysis. The mean follow-up period was 8.8 years (SD 1.1).Results and discussion. The test for semantic verbal fluency revealed its dynamic decline in all age groups, which was steeper in women than in men (pConclusion.It is established that a dynamic decrease in CF begins at the age of55—59years; it is steeper among those aged 70 years and older. An age-related decline in memory function is accelerated in persons with lower educational levels.

Background and Aims Obesity and kidney diseases are common complex disorders with an increasing clinical and economic impact on healthcare around the globe. We aim to examine if modifiable anthropometric indices of obesity exert putatively causal effects on different measures of kidney health and disease. Method We performed conventional observational and Mendelian randomisation (MR) study to examine if modifiable anthropometric indices of obesity exert putatively causal effects on different kidney health and disease-related phenotypes. These analyses were conducted using approximately 300,000 participants of white-British ancestry from UK Biobank and up to 480,000 participants of predominantly European ancestry from genome-wide association studies. Results The Mendelian randomisation analysis indicated that increasing values of genetically predicted BMI and waist circumference were causally linked to changes in renal function indices including reduced estimated glomerular filtration (PeGFRcystatineC=5.96 × 10-59 for BMI and PeGFRcystatineC=1.72 × 10-69 for waist circumference) and increased blood urea nitrogen (PBUN=2.01 × 10-10 for BMI and PBUN=4.54 × 10-12 for waist circumference) in UK Biobank individuals. These associations were replicated using data from CKDGen Consortium individuals (PeGFRcystatineC=1.47 × 10-5 for BMI and PeGFRcystatineC=7.63 × 10-5 for waist circumference; PBUN=1.96 × 10-4 for BMI and PBUN=3.10 × 10-3 for waist circumference). One standard deviation increase in genetically-predicted BMI and waist circumference decreased the relative odds of kidney health index by 14% and 18% (OR=0.86; 95%CI: 0.82-0.92; P=9.18 × 10-6 for BMI and OR=0.82; 95%CI: 0.75-0.90; P=2.12 × 10-5 for waist circumference). Approximately 13-16% of the causal effect of obesity indices on kidney health was mediated by blood pressure. Obesity increased the risk of both acute and chronic kidney disease of several aetiologies including hypertensive renal disease (OR=1.79; 95%CI: 1.14-2.82; P=1.15 × 10-2 for BMI and OR=2.41; 95%CI: 1.30-4.45; P=5.03 × 10-3 for waist circumference), renal failure (OR=1.51; 95%CI: 1.25-1.83; P=2.60 × 10-5 for BMI and OR=1.86; 95%CI: 1.43-2.42; P=4.16 × 10-6 for waist circumference) and CKD (OR=1.50; 95%CI: 1.16-1.96; P=2.44 × 10-3 for BMI and OR=1.83; 95%CI: 1.28-2.63; P=9.49 × 10-4 for waist circumference) and diabetic nephropathy (OR=1.92; 95%CI: 1.44-2.54; P=6.86 × 10-6 for BMI). Conclusion These findings indicate that obesity is causally linked to indices of renal health and the risk of different kidney diseases. This evidence substantiates the value of weight loss as a strategy of preventing and/or counteracting a decline in kidney health as well as decreasing the risk of renal disease.

Insulin‐like growth factor‐I (IGF‐I) and testosterone have been implicated in prostate cancer aetiology. Using data from a large prospective full‐cohort with standardised assays and repeat blood measurements, and genetic data from an international consortium, we investigated the associations of circulating IGF‐I, sex hormone‐binding globulin (SHBG), and total and calculated free testosterone concentrations with prostate cancer incidence and mortality. For prospective analyses, risk was estimated using multivariable‐adjusted Cox regression in 199 698 male UK Biobank participants. Hazard ratios (HRs) were corrected for regression dilution bias using repeat hormone measurements from a subsample. Two‐sample Mendelian randomisation (MR) analysis of IGF‐I and risk used genetic instruments identified from UK Biobank men and genetic outcome data from the PRACTICAL consortium (79 148 cases and 61 106 controls). We used cis‐ and all (cis and trans) SNP MR approaches. A total of 5402 men were diagnosed with and 295 died from prostate cancer (mean follow‐up 6.9 years). Higher circulating IGF‐I was associated with elevated prostate cancer diagnosis (HR per 5 nmol/L increment = 1.09, 95% CI 1.05‐1.12) and mortality (HR per 5 nmol/L increment = 1.15, 1.02‐1.29). MR analyses also supported the role of IGF‐I in prostate cancer diagnosis (cis‐MR odds ratio per 5 nmol/L increment = 1.34, 1.07‐1.68). In observational analyses, higher free testosterone was associated with a higher risk of prostate cancer (HR per 50 pmol/L increment = 1.10, 1.05‐1.15). Higher SHBG was associated with a lower risk (HR per 10 nmol/L increment = 0.95, 0.94‐0.97), neither was associated with prostate cancer mortality. Total testosterone was not associated with prostate cancer. These findings implicate IGF‐I and free testosterone in prostate cancer development and/or progression., What's new? Testosterone, insulin‐like growth factor‐I (IGF‐I), and sex hormone‐binding globulin (SHBG) all have been associated with prostate‐cancer risk. In this large, prospective study, the authors analyzed how these circulating hormones might impact mortality as well as risk. They found that men with higher IGF‐I had a higher risk of both prostate‐cancer diagnosis and mortality. Men with higher free testosterone had an increased risk of prostate cancer, while men with higher SHBG had a decreased risk. These results support the roles of IGF‐I and testosterone in prostate cancer development.

Aims Angiopoietin-like protein 3 (ANGPTL3) and 4 (ANGPTL4) inhibit lipoprotein lipase (LPL) and represent emerging drug targets to lower circulating triglycerides and reduce cardiovascular risk. To investigate the molecular effects of genetic mimicry of ANGPTL3 and ANGPTL4 inhibition and compare them to the effects of genetic mimicry of LPL enhancement. Methods and results Associations of genetic variants in ANGPTL3 (rs11207977-T), ANGPTL4 (rs116843064-A), and LPL (rs115849089-A) with an extensive serum lipid and metabolite profile (208 measures) were characterized in six cohorts of up to 61 240 participants. Genetic associations with anthropometric measures, glucose-insulin metabolism, blood pressure, markers of kidney function, and cardiometabolic endpoints via genome-wide summary data were also explored. ANGPTL4 rs116843064-A and LPL rs115849089-A displayed a strikingly similar pattern of associations across the lipoprotein and lipid measures. However, the corresponding associations with ANGPTL3 rs11207977-T differed, including those for low-density lipoprotein and high-density lipoprotein particle concentrations and compositions. All three genotypes associated with lower concentrations of an inflammatory biomarker glycoprotein acetyls and genetic mimicry of ANGPTL3 inhibition and LPL enhancement were also associated with lower C-reactive protein. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower waist-to-hip ratio, improved insulin-glucose metabolism, and lower risk of coronary heart disease and type 2 diabetes, whilst genetic mimicry of ANGPTL3 was associated with improved kidney function. Conclusions Genetic mimicry of ANGPTL4 inhibition and LPL enhancement have very similar systemic metabolic effects, whereas genetic mimicry of ANGPTL3 inhibition showed differing metabolic effects, suggesting potential involvement of pathways independent of LPL. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower risk of coronary heart disease and type 2 diabetes. These findings reinforce evidence that enhancing LPL activity (either directly or via upstream effects) through pharmacological approaches is likely to yield benefits to human health., Graphical Abstract

Drug development in cardiovascular disease is stagnating, with lack of validated targets a major roadblock to innovation. Human genetics can provide compelling evidence of causation through approaches such as Mendelian randomization (MR). Such genetic support can increase the probability of a clinical trial succeeding. MR is being widely applied to quantitative traits (e.g. adiposity and blood lipids) with the aim of identifying risk factors for disease that are both causal and amenable to therapeutic modification. However, there are important differences between genetic investigations of a biomarker (such as HDL-cholesterol) and a drug target that seeks to modify the same biomarker of interest (such as CETP), with implications on the methodology, interpretation and applications of MR to drug development. Differences include the comparative nature of the genetic architecture, i.e. that of a biomarker typically being polygenic, whereas that for a protein drug target being monogenic. and the potential for drug targets to show pleiotropic disease associations which may differ to those of the biomarker it is designed to modify. In this review, we compare and contrast the role of MR as applied to quantitative traits versus drug targets, describing differences between approaches and the function each plays. Our review will put into context findings emerging from this burgeoning field of scientific investigation, with the aim of clarifying the aetiological roles of biomarkers in disease, prioritizing candidate drug targets based on genetic-guided credibility of causation and in so doing, improve the odds of success in the drug development pipeline.