Search

The current understanding of the genetic determinants of thoracic aortic aneurysms and dissections (TAAD) has largely been informed through studies of rare, Mendelian forms of disease. Here, we conducted a genome-wide association study (GWAS) of TAAD, testing ~25 million DNA sequence variants in 8,626 participants with and 453,043 participants without TAAD in the Million Veteran Program, with replication in an independent sample of 4,459 individuals with and 512,463 without TAAD from six cohorts. We identified 21 TAAD risk loci, 17 of which have not been previously reported. We leverage multiple downstream analytic methods to identify causal TAAD risk genes and cell types and provide human genetic evidence that TAAD is a non-atherosclerotic aortic disorder distinct from other forms of vascular disease. Our results demonstrate that the genetic architecture of TAAD mirrors that of other complex traits and that it is not solely inherited through protein-altering variants of large effect size.

Introduction: Non-linear Mendelian randomization is an extension of conventional Mendelian randomization that performs separate instrumental variable analyses in strata of the study population with different average levels of the exposure. The approach estimates a localized average causal effect function, representing the average causal effect of the exposure on the outcome at different levels of the exposure. The commonly-used residual method for dividing the population into strata works under the assumption that the effect of the genetic instrument on the exposure is linear and constant in the study population. However, this assumption may not hold in practice. Methods: We use the recently developed doubly-ranked method to re-analyse various datasets previously analysed using the residual method. In particular, we consider a genetic score for 25-hydroxyvitamin D [25(OH)D] used in a recent non-linear Mendelian randomization analysis to assess the potential effect of vitamin D supplementation on all-cause mortality. Results: The effect of the genetic score on 25(OH)D concentrations varies strongly, with a five-fold difference in the estimated genetic association with the exposure in the lowest and highest decile groups. Evidence for a protective causal effect of vitamin D supplementation on all-cause mortality in low vitamin D individuals is evident for the residual method, but not for the doubly-ranked method. We show that the constant genetic effect assumption is more reasonable for some exposures, and less reasonable for others. If the doubly-ranked method indicates that this assumption is violated, then estimates from both the residual and doublyranked methods can be biased, although bias was smaller on average in the doubly-ranked method. Conclusion: Analysts wanting to perform non-linear Mendelian randomization should compare results from both the residual and doubly-ranked methods, as well as considering transforming the exposure for the residual method to reduce heterogeneity in the genetic effect on the exposure.

BACKGROUND: The causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain. METHODS: Using a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures. FINDINGS: Genetically elevated PUFA desaturase activity was associated (P

Iron deficiency is the most common nutritional deficiency worldwide, and is estimated to affect a quarter of the pregnant population.1 Low systemic iron levels have been associated with several maternal pregnancy complications, including infection and preeclampsia.2 However, these results from traditional observational studies may be affected by confounding. A systematic review of trials found that daily iron supplementation in pregnancy reduced iron deficiency anemia, but there was no clear effect on other maternal complications, which in large part may be due to low statistical power.3 To robustly evaluate whether systemic iron status affects risk of maternal pregnancy complications, we conducted a Mendelian randomization (MR) study. By leveraging genetic instruments for systemic iron status, the approach greatly reduced the risk of confounding and allowed for a large study sample.

Carotid intima-media thickness (cIMT) is a measure of atherosclerosis used to predict cardiovascular disease.1 Lipid traits and type 2 diabetes (T2D) have been implicated in the pathogenesis of cIMT. Statins, which reduce low-density lipoprotein cholesterol (LDL-C), have been shown in a meta-analysis of randomized trials to slow cIMT growth or even reduce cIMT. However, most research into cIMT has been conducted in European ancestry individuals, and little is known about whether the same causal risk factors apply for African ancestry populations.

Peer reviewed: True, Acknowledgements: We want to thank the Lee Lab, the FinnGen study, the International Inflammatory Bowel Disease Genetics Consortium (IIBDGC), and the Genetic Epidemiology Research on Aging (GERA) for sharing data. XL: the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001). XYW: National Natural Science Foundation of China (81970494) and Key Project of Research and Development Plan of Hunan Province(2019SK2041); SCL: the Swedish Heart Lung Foundation (Hjärt-Lungfonden, 20210351), the Swedish Research Council (Vetenskapsrådet, 2019–00977), and the Swedish Cancer Society (Cancerfonden). Funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication., Funder: Cancerfonden; FundRef: http://dx.doi.org/10.13039/501100002794, BACKGROUND: Whether the positive associations of smoking and alcohol consumption with gastrointestinal diseases are causal is uncertain. We conducted this Mendelian randomization (MR) to comprehensively examine associations of smoking and alcohol consumption with common gastrointestinal diseases. METHODS: Genetic variants associated with smoking initiation and alcohol consumption at the genome-wide significance level were selected as instrumental variables. Genetic associations with 24 gastrointestinal diseases were obtained from the UK Biobank, FinnGen study, and other large consortia. Univariable and multivariable MR analyses were conducted to estimate the overall and independent MR associations after mutual adjustment for genetic liability to smoking and alcohol consumption. RESULTS: Genetic predisposition to smoking initiation was associated with increased risk of 20 of 24 gastrointestinal diseases, including 7 upper gastrointestinal diseases (gastroesophageal reflux, esophageal cancer, gastric ulcer, duodenal ulcer, acute gastritis, chronic gastritis, and gastric cancer), 4 lower gastrointestinal diseases (irritable bowel syndrome, diverticular disease, Crohn's disease, and ulcerative colitis), 8 hepatobiliary and pancreatic diseases (non-alcoholic fatty liver disease, alcoholic liver disease, cirrhosis, liver cancer, cholecystitis, cholelithiasis, and acute and chronic pancreatitis), and acute appendicitis. Fifteen out of 20 associations persisted after adjusting for genetically predicted alcohol consumption. Genetically predicted higher alcohol consumption was associated with increased risk of duodenal ulcer, alcoholic liver disease, cirrhosis, and chronic pancreatitis; however, the association for duodenal ulcer did not remain statistically significant after adjustment for genetic predisposition to smoking initiation. CONCLUSIONS: This study provides MR evidence supporting causal associations of smoking with a broad range of gastrointestinal diseases, whereas alcohol consumption was associated with only a few gastrointestinal diseases. FUNDING: The Natural Science Fund for Distinguished Young Scholars of Zhejiang Province; National Natural Science Foundation of China; Key Project of Research and Development Plan of Hunan Province; the Swedish Heart Lung Foundation; the Swedish Research Council; the Swedish Cancer Society.

Background: Observational studies identified elevated blood pressure (BP) as a strong risk factor for thoracic aortic dilation, and BP reduction is the primary medical intervention recommended to prevent progression of aortic aneurysms. However, although BP may impact aortic dilation, aortic size may also impact BP. The causal relationship between BP and thoracic aortic size has not been reliably established. Methods: Genome-wide association studies summary statistics were obtained for BP and ascending thoracic aortic diameter (AscAoD). Causal effects of BP on AscAoD were estimated using 2-sample Mendelian randomization using a range of pleiotropy-robust methods. Results: Genetically predicted increased systolic BP, diastolic BP, and mean arterial pressure all significantly associate with higher AscAoD (systolic BP: β estimate, 0.0041 mm/mm Hg [95% CI, 0.0008–0.0074]; P =0.02, diastolic BP: β estimate, 0.0272 mm/mm Hg [95% CI, 0.0224–0.0320]; P P P P P =0.02), while directly associated with diastolic BP (0.8203 mm Hg/mm [95% CI, 0.2735–1.3672]; P =0.004). Conclusions: BP likely contributes causally to ascending thoracic aortic dilation. Increased AscAoD likely contributes to lower systolic BP and pulse pressure, but not diastolic BP, consistent with the hemodynamic consequences of a reduced aortic diameter.

Funder: Karolinska Institute, Background The associations of rheumatoid arthritis (RA) with risk of site-specific cancers beyond lymphohematopoietic cancer have been scarcely explored. We conducted a Mendelian randomization investigation of the associations of RA with site-specific cancers in European and East Asian populations. Methods Independent genetic variants strongly associated with RA in European and East Asian populations were selected as instrumental variables from genome-wide association studies of 58,284 European individuals (14,361 cases and 43,923 controls) and 22,515 East Asian individuals (4873 cases and 17,642 controls), respectively. The associations of genetic variants with overall and 22 site-specific cancers were extracted from the UK Biobank study (n = 367,561), the FinnGen study (n = 260,405), Biobank Japan (n = 212,453), and international consortia. The associations for one outcome from different data sources were combined by meta-analysis. Results In the European population, the combined odds ratios per 1-unit increase in log odds of genetic liability to RA were 1.06 (95% confidence interval [CI] 1.03–1.10) for head and neck cancer, 1.06 (95% CI 1.02–1.10) for cervical cancer, 0.92 (95% CI 0.87–0.96) for testicular cancer, and 0.94 (95% CI 0.90–0.98) for multiple myeloma. In the East Asian population, the corresponding odds ratios were 1.17 (95% CI 1.06–1.29) for pancreatic cancer, 0.91 (95% CI 0.88–0.94) for breast cancer, and 0.90 (95% CI 0.84–0.96) for ovarian cancer. There were suggestive associations for breast and ovarian cancer and overall cancer in the European population. No other associations were observed. Conclusion This study suggests that RA may play a role in the development of several site-specific cancers.

Introduction Genetic associations for variants identified through genome-wide association studies (GWASs) tend to be overestimated in the original discovery data set as, if the association was underestimated, the variant may not have been detected. This bias, known as winner’s curse, can affect Mendelian randomization estimates, but its severity and potential impact are unclear. Methods We performed an empirical investigation to assess the potential bias from winner’s curse in practice. We considered Mendelian randomization estimates for the effect of body mass index (BMI) on coronary artery disease risk. We randomly divided a UK Biobank data set 100 times into three equally sized subsets. The first subset was treated as the ‘discovery GWAS’. We compared genetic associations estimated in the discovery GWAS to those estimated in the other subsets for each of the 100 iterations. Results For variants associated with BMI at P Conclusions Winner’s curse can bias Mendelian randomization estimates, although its practical impact may not be substantial. If avoiding sample overlap is infeasible, analysts should consider performing a sensitivity analysis based on variants strongly associated with the exposure.

Many individual genetic risk loci have been associated with multiple common human diseases. However, the molecular basis of this pleiotropy often remains unclear. We present an integrative approach to reveal the molecular mechanism underlying the PROCR locus, associated with lower coronary artery disease (CAD) risk but higher venous thromboembolism (VTE) risk. We identify PROCR-p.Ser219Gly as the likely causal variant at the locus and protein C as a causal factor. Using genetic analyses, human recall-by-genotype and in vitro experimentation, we demonstrate that PROCR-219Gly increases plasma levels of (activated) protein C through endothelial protein C receptor (EPCR) ectodomain shedding in endothelial cells, attenuating leukocyte–endothelial cell adhesion and vascular inflammation. We also associate PROCR-219Gly with an increased pro-thrombotic state via coagulation factor VII, a ligand of EPCR. Our study, which links PROCR-219Gly to CAD through anti-inflammatory mechanisms and to VTE through pro-thrombotic mechanisms, provides a framework to reveal the mechanisms underlying similar cross-phenotype associations.

Funder: Karolinska Institute, BACKGROUND: Obesity is a worldwide epidemic that has been associated with a plurality of diseases in observational studies. The aim of this study was to summarize the evidence from Mendelian randomization (MR) studies of the association between body mass index (BMI) and chronic diseases. METHODS: PubMed and Embase were searched for MR studies on adult BMI in relation to major chronic diseases, including diabetes mellitus; diseases of the circulatory, respiratory, digestive, musculoskeletal, and nervous systems; and neoplasms. A meta-analysis was performed for each disease by using results from published MR studies and corresponding de novo analyses based on summary-level genetic data from the FinnGen consortium (n = 218,792 individuals). RESULTS: In a meta-analysis of results from published MR studies and de novo analyses of the FinnGen consortium, genetically predicted higher BMI was associated with increased risk of type 2 diabetes mellitus, 14 circulatory disease outcomes, asthma, chronic obstructive pulmonary disease, five digestive system diseases, three musculoskeletal system diseases, and multiple sclerosis as well as cancers of the digestive system (six cancer sites), uterus, kidney, and bladder. In contrast, genetically predicted higher adult BMI was associated with a decreased risk of Dupuytren's disease, osteoporosis, and breast, prostate, and non-melanoma cancer, and not associated with Alzheimer's disease, amyotrophic lateral sclerosis, or Parkinson's disease. CONCLUSIONS: The totality of the evidence from MR studies supports a causal role of excess adiposity in a plurality of chronic diseases. Hence, continued efforts to reduce the prevalence of overweight and obesity are a major public health goal., This work was supported by research grants from the Swedish Research Council (Vetenskapsr��det; 2016-01042 and 2019-00977), the Swedish Research Council for Health, Working Life and Welfare (Forte; 2018-00123), and the Swedish Heart-Lung Foundation (Hj��rt-Lungfonden; 20190247). Stephen Burgess is supported by Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (204623/Z/16/Z). Open Access funding provided by Karolinska Institute.

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

ObjectivTo assess the associations between gout, brain structure, and neurodegenerative disease incidence.MethodsUsing observational and Mendelian randomization analyses we investigated causal relationships between gout and brain health. Exposures included gout diagnosis (from self-report, linked health records and death records) and genetically proxied gout and serum urate. Outcomes were neuroimaging markers of brain structure and neurodegenerative disease incidence (ascertained through self-report, health records and death reports). Cox proportional hazards models were used to examine time to neurodegenerative disease diagnosis.Results11,735 UK Biobank participants (mean age 55.5±8.0 years and 50.5% female) had a diagnosis of gout (n=1165 in MRI subset). Dementia was ascertained in 3126 individuals over a mean follow-up time of 12.4±1.9 years. Gout patients had smaller global and regional brain volumes and higher brain iron markers. Genetic associations mirrored observational associations. Genetically proxied gout associated with lower global grey matter volume (beta= -0.05[-0.08 to -0.01]). Participants with gout had higher incidence of all-cause dementia (hazard ratio (HR)=1.60, 95% confidence interval (CI) [1.38-1.85]), Parkinson’s disease (HR=1.43[1.15 to 1.79]), and probable essential tremor (HR=6.75[5.69 to 8.00]). Risks were strongly time dependent, whereby associations with incident dementia were highest in the first 3 years after gout diagnosis (HR=7.40[4.95 to 11.07]).ConclusionsThese findings suggest gout is causally related to several measures of brain structure. Lower brain reserve amongst gout patients may explain their higher vulnerability to multiple neurodegenerative diseases.Key pointsWhat is already known on this topic?Studies of neurodegenerative disease risk in gout are contradictory.Relationships with neuroimaging markers of brain structure, which may offer insights, are uncertain.What this study adds?In this prospective cohort study gout was associated with smaller brain volumes and higher incidence of multiple neurodegenerative diseases.Mendelian randomization analyses suggested gout is causally related to brain structure.How might this study affect research, practice or policy?Our findings emphasise the importance for clinicians of assessing for motor and cognitive impairments amongst gout patients, particularly in early years after diagnosis.

Background and ObjectivesAngiotensin-converting enzyme (ACE) inhibitors are a commonly prescribed class of medication used to treat heart failure, hypertension, and chronic kidney disease. However, previous observational studies have shown conflicting directions of associations between ACE inhibitors and risk of Alzheimer disease. Genetic evidence has supported a protective effect of cerebral ACE against Alzheimer disease (AD). However, it is unclear whether this effect is mediated through blood pressure and extends to other neurodegenerative diseases.MethodsWe performed genetic colocalization investigating an effect of cortical ACE expression on AD risk in people of European ancestry. We further investigated whether any effect of ACE expression on AD risk is mediated through changes in blood pressure and whether effects extend to Parkinson disease, small-vessel disease, or cognitive function in a Mendelian randomization paradigm.ResultsThere was genetic evidence supporting a protective effect of cortical ACE expression on AD risk in people of European ancestry. Although higher cortical ACE expression was associated with higher blood pressure, there was no strong evidence to support that its association with AD was mediated through blood pressure nor that ACE expression affected risk of other neurodegenerative traits.DiscussionGenetic evidence supports protective effects of cerebral ACE expression on AD, but not other neurodegenerative outcomes in people of European ancestry. Further work is required to investigate whether therapeutic inhibition of ACE increases risk of Alzheimer disease.

Background: Microvascular damage from large artery stiffness (LAS) in pancreatic, hepatic, and skeletal muscles may affect glucose homeostasis. Our goal was to evaluate the association between LAS and the risk of type 2 diabetes using prospectively collected, carefully phenotyped measurements of LAS as well as Mendelian randomization analyses. Methods: Carotid-femoral pulse wave velocity (CF-PWV) and brachial and central pulse pressure were measured in 5676 participants of the FHS (Framingham Heart Study) without diabetes. We used Cox proportional hazards regression to evaluate the association of CF-PWV and pulse pressure with incident diabetes. We subsequently performed 2-sample Mendelian randomization analyses evaluating the associations of genetically predicted brachial pulse pressure with type 2 diabetes in the UKBB (United Kingdom Biobank). Results: In FHS, individuals with higher CF-PWV were older, more often male, and had higher body mass index and mean arterial pressure compared to those with lower CF-PWV. After a median follow-up of 7 years, CF-PWV and central pulse pressure were associated with an increased risk of new-onset diabetes (per SD increase, multivariable-adjusted CF-PWV hazard ratio, 1.36 [95% CI, 1.03–1.76]; P =0.030; central pulse pressure multivariable-adjusted CF-PWV hazard ratio, 1.26 [95% CI, 1.08–1.48]; P =0.004). In United Kingdom Biobank, genetically predicted brachial pulse pressure was associated with type 2 diabetes, independent of mean arterial pressure (adjusted odds ratio, 1.16 [95% CI, 1.00–1.35]; P =0.049). Conclusions: Using prospective cohort data coupled with Mendelian randomization analyses, we found evidence supporting that greater LAS is associated with increased risk of developing diabetes. LAS may play an important role in glucose homeostasis and may serve as a useful marker of future diabetes risk.

Background & aims: Vitamin C is an antioxidant with a potential role in the prevention of digestive system cancers, but there is yet no consensus whether vitamin C has a causal role in these cancers. The aim of this study was to utilize Mendelian randomization to decipher the potential causal associations of vitamin C with risk of digestive system cancers.Methods: Ten genetic variants previously found to be significantly associated with circulating vitamin C were used as instrumental variables. Effect size estimates for the genetic associations of the vitamin Cassociated genetic variants with six major malignancies of digestive system were obtained from the FinnGen (N = 309 154) and UK Biobank (N = 367 542) studies. Results from the two studies were combined using meta-analysis.Results: Genetically predicted higher circulating vitamin C showed a suggestive association with lower risk of small intestine and colorectal cancer after accounting for multiple testing. The odds ratio per 1 standard deviation increment in circulating vitamin C was 0.55 (95% confidence interval 0.32-0.94; P = 0.029) for small intestine cancer and 0.84 (95% confidence interval 0.73-0.96; P = 0.013) for colorectal cancer. There was a suggestive association between genetically predicted higher circulating vitamin C with lower risk of liver cancer in FinnGen but no association in the meta-analysis (odds ratio 0.69; 95% CI 0.36-1.32; P = 0.265). Genetically predicted circulating vitamin C was not associated with cancers of the esophagus, stomach, or pancreas.Conclusion: This Mendelian randomization study indicates that vitamin C might play a role in the prevention of small intestine and colorectal cancer. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

BACKGROUND: Cortisol's immunosuppressive, obesogenic, and hyperglycaemic effects suggest that it may play a role in cancer development. However, whether cortisol increases cancer risk is not known. We investigated the potential causal association between plasma cortisol and risk of overall and common site-specific cancers using Mendelian randomisation. METHODS: Three genetic variants associated with morning plasma cortisol levels at the genome-wide significance level (P < 5 × 10-8) in the Cortisol Network consortium were used as genetic instruments. Summary-level genome-wide association study data for the cancer outcomes were obtained from large-scale cancer consortia, the UK Biobank, and the FinnGen consortium. Two-sample Mendelian randomisation analyses were performed using the fixed-effects inverse-variance weighted method. Estimates across data sources were combined using meta-analysis. RESULTS: A standard deviation increase in genetically predicted plasma cortisol was associated with increased risk of endometrial cancer (odds ratio 1.50, 95% confidence interval 1.13-1.99; P = 0.005). There was no significant association between genetically predicted plasma cortisol and risk of other common site-specific cancers, including breast, ovarian, prostate, colorectal, lung, or malignant skin cancer, or overall cancer. CONCLUSIONS: These results indicate that elevated plasma cortisol levels may increase the risk of endometrial cancer but not other cancers. The mechanism by which this occurs remains to be investigated.

Introduction In observational studies, venous thromboembolism (VTE) has been associated with Cushing’s syndrome and with persistent mental stress, two conditions associated with higher cortisol levels. However, it remains unknown whether high cortisol levels within the usual range are causally associated with VTE risk. We aimed to assess the association between plasma cortisol levels and VTE risk using Mendelian randomization. Methods Three genetic variants in the SERPINA1/SERPINA6 locus (rs12589136, rs11621961 and rs2749527) were used to proxy plasma cortisol. The associations of the cortisol-associated genetic variants with VTE were acquired from the INVENT (28 907 cases and 157 243 non-cases) and FinnGen (6913 cases and 169 986 non-cases) consortia. Corresponding data for VTE subtypes were available from the FinnGen consortium and UK Biobank. Two-sample Mendelian randomization analyses (inverse-variance weighted method) were performed. Results Genetic predisposition to higher plasma cortisol levels was associated with a reduced risk of VTE (odds ratio [OR] per one standard deviation increment 0.73, 95% confidence interval [CI] 0.62–0.87, p Conclusions This study provides evidence that genetically predicted plasma cortisol levels in the high end of the normal range are associated with a decreased risk of VTE and that this association may be mediated by blood pressure. This study has implications for the planning of observational studies of cortisol and VTE, suggesting that blood pressure traits should be measured and accounted for.

Funder: National Institute for Health Research (NIHR), Funder: Wellcome Trust, Funder: Medical Research Council, BACKGROUND: Interleukin 6 (IL-6) signaling is being investigated as a therapeutic target for atherosclerotic cardiovascular disease (CVD). While changes in circulating high-sensitivity C-reactive protein (hsCRP) are used as a marker of IL-6 signaling, it is not known whether there is effect heterogeneity in relation to baseline hsCRP levels or other cardiovascular risk factors. The aim of this study was to explore the association of genetically predicted IL-6 signaling with CVD risk across populations stratified by baseline hsCRP levels and cardiovascular risk factors. METHODS: Among 397,060 White British UK Biobank participants without known CVD at baseline, we calculated a genetic risk score for IL-6 receptor (IL-6R)-mediated signaling, composed of 26 variants at the IL6R gene locus. We then applied linear and non-linear Mendelian randomization analyses exploring associations with a combined endpoint of incident coronary artery disease, ischemic stroke, peripheral artery disease, aortic aneurysm, and cardiovascular death stratifying by baseline hsCRP levels and cardiovascular risk factors. RESULTS: The study participants (median age 59 years, 53.9% females) were followed-up for a median of 8.8 years, over which time a total of 46,033 incident cardiovascular events occurred. Genetically predicted IL-6R-mediated signaling activity was associated with higher CVD risk (hazard ratio per 1-mg/dL increment in absolute hsCRP levels: 1.11, 95% CI: 1.06-1.17). The increase in CVD risk was linearly related to baseline absolute hsCRP levels. There was no evidence of heterogeneity in the association of genetically predicted IL-6R-mediated signaling with CVD risk when stratifying the population by sex, age, body mass index, estimated glomerular filtration rate, or systolic blood pressure, but there was evidence of greater associations in individuals with low-density lipoprotein cholesterol ≥ 160 mg/dL. CONCLUSIONS: Any benefit of inhibiting IL-6 signaling for CVD risk reduction is likely to be proportional to absolute reductions in hsCRP levels. Therapeutic inhibition of IL-6 signaling for CVD risk reduction should therefore prioritize those individuals with the highest baseline levels of hsCRP.

Funder: British Heart Foundation, Clonal hematopoiesis (CH), the clonal expansion of a blood stem cell and its progeny driven by somatic driver mutations, affects over a third of people, yet remains poorly understood. Here we analyze genetic data from 200,453 UK Biobank participants to map the landscape of inherited predisposition to CH, increasing the number of germline associations with CH in European-ancestry populations from 4 to 14. Genes at new loci implicate DNA damage repair (PARP1, ATM, CHEK2), hematopoietic stem cell migration/homing (CD164) and myeloid oncogenesis (SETBP1). Several associations were CH-subtype-specific including variants at TCL1A and CD164 that had opposite associations with DNMT3A- versus TET2-mutant CH, the two most common CH subtypes, proposing key roles for these two loci in CH development. Mendelian randomization analyses showed that smoking and longer leukocyte telomere length are causal risk factors for CH and that genetic predisposition to CH increases risks of myeloproliferative neoplasia, nonhematological malignancies, atrial fibrillation and blood epigenetic ageing.

Mendelian randomization is the use of genetic variants analogously to randomized treatment allocation in a trial to make causal inferences from observational data. In their recent paper, Hegazy and colleagues assessed associations between genetic variants in the CRP gene region, which they treated analogously to random allocation to increased levels of C-reactive protein (CRP), and risk of dementia (1). However, rather than assessing associations in the population as a whole, they assessed associations in strata of the population defined according to body mass index (BMI): those with BMI ≤25 kg/m2, and those with BMI >25 kg/m2. They observed positive associations between variants and dementia risk in the low BMI stratum, and inverse associations (although mostly not statistically significant) in the high BMI stratum. The authors interpreted the positive associations as evidence that CRP has a deleterious effect on dementia risk in low BMI individuals. However, there are reasons to be sceptical of this interpretation.

The causal effects of alcohol-in-moderation on cardiometabolic health are continuously debated. Mendelian randomization (MR) is an established method to address causal questions in observational studies. We performed a systematic review of the current evidence from MR studies on the association between alcohol consumption and cardiometabolic diseases, all-cause mortality and cardiovascular risk factors. We performed a systematic search of the literature, including search terms on type of design and exposure. We assessed methodological quality based on key elements of the MR design: use of a full instrumental variable analysis and validation of the three key MR assumptions. We additionally looked at exploration of non-linearity. We reported the direction of the studied associations. Our search yielded 24 studies that were eligible for inclusion. A full instrumental variable analysis was performed in 17 studies (71%) and 13 out of 24 studies (54%) validated all three key assumptions. Five studies (21%) assessed potential non-linearity. In general, null associations were reported for genetically predicted alcohol consumption with the primary outcomes cardiovascular disease (67%) and diabetes (75%), while the only study on all-cause mortality reported a detrimental association. Considering the heterogeneity in methodological quality of the included MR studies, it is not yet possible to draw conclusions on the causal role of moderate alcohol consumption on cardiometabolic health. As MR is a rapidly evolving field, we expect that future MR studies, especially with recent developments regarding instrument selection and non-linearity methodology, will further substantiate this discussion.

Funder: EU/EFPIA Innovative Medicines Initiative Joint Undertaking BigData@Heart grant 116074 The Royal Society (204623/Z/16/Z) United Kingdom Research and Innovation Medical Research Council (MC_UU_00002/7) NIHR Cambridge Biomedical Research Centre (BRC-1215-20014), Iron is essential for many biological processes, but iron levels must be tightly regulated to avoid harmful effects of both iron deficiency and overload. Here, we perform genome-wide association studies on four iron-related biomarkers (serum iron, serum ferritin, transferrin saturation, total iron-binding capacity) in the Trøndelag Health Study (HUNT), the Michigan Genomics Initiative (MGI), and the SardiNIA study, followed by their meta-analysis with publicly available summary statistics, analyzing up to 257,953 individuals. We identify 123 genetic loci associated with iron traits. Among 19 novel protein-altering variants, we observe a rare missense variant (rs367731784) in HUNT, which suggests a role for DNAJC13 in transferrin recycling. We further validate recently published results using genetic risk scores for each biomarker in HUNT (6% variance in serum iron explained) and present linear and non-linear Mendelian randomization analyses of the traits on all-cause mortality. We find evidence of a harmful effect of increased serum iron and transferrin saturation in linear analyses that estimate population-averaged effects. However, there was weak evidence of a protective effect of increasing serum iron at the very low end of its distribution. Our findings contribute to our understanding of the genes affecting iron status and its consequences on human health.

The EPIC-CVD project was supported by the European Union Framework 7 (HEALTH-F2-2012-279233), the European Research Council (268834), the UK Medical Research Council (G0800270, MR/L003120/1), the British Heart Foundation (SP/09/002, RG/08/014, RG13/13/30194), and the UK National Institute of Health Research (to EPIC-CVD). The establishment of the subcohort was supported by the EU Sixth Framework Programme (FP6) (grant LSHM_CT_2006_037197 to the InterAct project) and the Medical Research Council Epidemiology Unit (grants MC_ UU_12015/1 and MC_UU_12015/5). The national EPIC cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Generale de l'Education Nationale, Institut National de la Sante et de la Recherche Medicale (INSERM) (France); Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); Ministry of Health and Social Solidarity, Stavros Niarchos Foundation and Hellenic Health Foundation (Greece); Italian Association for Research on Cancer (AIRC) and National Research Council (Italy) and MIUR "Dipartimenti di Eccellenza"(Project D15D18000410001) to the Department of Medical Sciences; Dutch Ministry of Public Health, Welfare and Sports (VWS), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF); ERC-2009-AdG 232997 and Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), Regional Governments of Andalucia, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Scientific Council and Regional Government of Skane and Vasterbotten (Sweden); and Cancer Research UK, Medical Research Council (United Kingdom). LIFE-Heart is funded by the Leipzig Research Center for Civilization Diseases (LIFE). LIFE is an organizational unit affiliated to the Medical Faculty of the University of Leipzig. LIFE is funded by means of the European Union, by the European Regional Development Fund (ERDF), and by funds of the Free State of Saxony within the framework of the excellence initiative. This work is supported by the Dutch Heart Foundation (2013T083 to V.D.), by a UK Medical Research Council Skills Development Fellowship (MR/P014550/1 to S.A.E.P.), and by a Sir Henry Dale Fellowship jointly funded by the Welcome Trust and the Royal Society (204623/Z/16/Z to S.B.). None of the funding sources had a role in the collection, analysis, and interpretation of the data, nor in the decision to submit the article for publication., Background: Accelerated reproductive aging, in women indicated by early natural menopause, is associated with increased coronary heart disease (CHD) risk in observational studies. Conversely, an adverse CHD risk profile has been suggested to accelerate menopause. Objectives: To study the direction and evidence for causality of the relationship between reproductive aging and (non-)fatal CHD and CHD risk factors in a bidirectional Mendelian randomization (MR) approach, using age at natural menopause (ANM) genetic variants as a measure for genetically determined reproductive aging in women. We also studied the association of these variants with CHD risk (factors) in men. Design: Two-sample MR, using both cohort data as well as summary statistics, with 4 methods: simple and weighted median-based, standard inverse-variance weighted (IVW) regression, and MR-Egger regression. Participants: Data from EPIC-CVD and summary statistics from UK Biobank and publicly available genome-wide association studies were pooled for the different analyses. Main Outcome Measures: CHD, CHD risk factors, and ANM. Results: Across different methods of MR, no association was found between genetically determined reproductive aging and CHD risk in women (relative risk estimateIVW = 0.99; 95% confidence interval (CI), 0.97-1.01), or any of the CHD risk factors. Similarly, no associations were found in men. Neither did the reversed analyses show evidence for an association between CHD (risk factors) and reproductive aging. Conclusion: Genetically determined reproductive aging is not causally associated with CHD risk (factors) in women, nor were the genetic variants associated in men. We found no evidence for a reverse association in a combined sample of women and men., European Commission HEALTH-F2-2012-279233 European Research Council (ERC) European Commission 268834, UK Research & Innovation (UKRI) Medical Research Council UK (MRC) G0800270 MR/L003120/1 British Heart Foundation SP/09/002 RG/08/014 RG13/13/30194, National Institute for Health Research (NIHR), EU Sixth Framework Programme (FP6) LSHM_CT_2006_037197, UK Research & Innovation (UKRI), Medical Research Council UK (MRC) MC_ UU_12015/1 MC_UU_12015/5, Danish Cancer Society, Ligue Contre le Cancer (France), Institut Gustave Roussy (France), Mutuelle Generale de l'Education Nationale (France), Institut National de la Sante et de la Recherche Medicale (Inserm), Deutsche Krebshilfe Federal Ministry of Education & Research (BMBF) Deutsches Krebsforschungszentrum (Germany), Ministry of Health and Social Solidarity (Greece) Stavros Niarchos Foundation (Greece) Hellenic Health Foundation (Greece), Fondazione AIRC per la ricerca sul cancro Consiglio Nazionale delle Ricerche (CNR) MIUR "Dipartimenti di Eccellenza" D15D18000410001, Dutch Ministry of Public Health, Welfare and Sports, LK Research Funds, Dutch Prevention Funds Netherlands Organization for Scientific Research (NWO), World Cancer Research Fund International (WCRF) ERC-2009-AdG 232997, Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway), Instituto de Salud Carlos III, Junta de Andalucia, Principality of Asturias, Regional Government of Basque Country (Spain) Regional Government of Murcia (Spain) Regional Government of Navarra (Spain), Instituto de Salud Carlos III RD06/0020, Swedish Cancer Society Swedish Scientific Council (Sweden) Regional Government of Skane and Vasterbotten (Sweden), Cancer Research UK UK Research & Innovation (UKRI) Medical Research Council UK (MRC), Leipzig Research Center for Civilization Diseases (LIFE), European Commission, Free State of Saxony, Netherlands Heart Foundation 2013T083, Medical Research Council UK (MRC) MR/P014550/1, Sir Henry Dale Fellowship - Welcome Trust 204623/Z/16/Z, Sir Henry Dale Fellowship - Royal Society 204623/Z/16/Z

Mendelian randomization is an epidemiological technique that compares disease risk in groups of individuals defined based on their genetic variants to make causal inferences (1). Rather than comparing individuals with high levels of an exposure versus those with low levels of an exposure as in a conventional epidemiological analysis, the approach compares those with genetic variants predisposing them to increased versus decreased levels of the exposure. This is analogous to the analysis of a randomized controlled trial for a treatment that increases levels of the exposure, which does not compare those with high versus low levels of the exposure after treatment, but rather compares those who were randomly assigned to receive the treatment versus those who were randomly assigned to the control group. The logic is that randomization should be independent of all competing risk factors, meaning that the randomly-assigned groups only differ systematically with respect to their average levels of the treatment and any downstream consequences of the treatment. Hence, an association between randomization and the trial outcome is indicative of a causal effect of the treatment. In the same way, if genetic variants act analogously to randomization by dividing the population into groups that differ systematically only with respect to the exposure and its consequences, then an association between the genetic variants and the outcome is indicative of a causal effect of the exposure (2).

Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10−6; IFNAR2, P = 9.8 × 10−11 and IL-10RB, P = 2.3 × 10−14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.

Supplemental Digital Content is Available in the Text. Mendelian randomization study supports that depression is a causal risk factor for headache and pain at neck/shoulder, back, and abdominal/stomach., To understand a putative causal link for depression and pain, we retrieved summary statistics from genome-wide association studies conducted for pain at 7 different body sites (N = 151,922-226,683) and major depression disorder (MDD, Ncase/control = 246,363/561,190). We conducted a bidirectional Mendelian randomization analysis using distinct genome-wide association studies-identified single nucleotide polymorphisms for each trait as instrumental variables and performed several sensitivity analyses to verify Mendelian randomization assumptions. We also conducted functional annotation analysis using 396 tissue-specific annotations from the roadmap project. Across 7 different body sites, genetic predisposition to depression was associated with pain at the neck/shoulder (odds ratio [OR] = 1.08 per one log-unit increase in depression risk, 95% confidence interval [CI]: 1.06-1.10), back (OR = 1.05, 95% CI: 1.04-1.07), abdominal/stomach (OR = 1.03, 95% CI: 1.02-1.04), as well as headache (OR = 1.10, 95% CI: 1.07-1.12), but not with pain on the face, hip, and knee. In the reverse direction, genetically instrumented multisite chronic pain (OR = 1.78 per one increment in the number of pain site, 95% CI: 1.51-2.11) and headache (OR = 1.55 per one log-unit increase in headache risk, 95% CI = 1.13-2.10) were associated with MDD. Functional annotation analysis showed differential clustering patterns where depression clustered closely with headache and neck/shoulder pain, exhibiting substantial brain tissue enrichment. Our study indicates that depression is a causal risk factor for headache and pain localized at neck/shoulder, back, and abdominal/stomach, rather than pain at face, hip, and knee, and suggests common neurological pathologies underlying the development of depression, headache, and neck/shoulder pain.

Reverse causation occurs when the outcome variable at an earlier timepoint, or a proximal precursor of the outcome (such as pre-clinical disease), has a causal effect on the risk factor. This confounding by pre-clinical or prior outcome can lead to bias when trying to estimate an average causal effect of the risk factor on the outcome. By proposing genetic variants as instrumental variables, Mendelian randomization can make inferences about the effect of shifting the trajectory of a risk factor on a later-measured outcome. As genetic variants are fixed at conception, it has been stated that Mendelian randomization investigations are not affected by reverse causation. While Mendelian randomization analyses have some protection against bias due to reverse causation, the claim of complete immunity is a misconception. We provide three plausible scenarios and accompanying examples of how reverse causation can influence Mendelian randomization estimates: 1) the effect of the genetic variant on the risk factor is mediated (at least in part) by the outcome, 2) the genetic association with the outcome is distorted by a feedback mechanism whereby the risk factor and outcome variable both influence each other over time, and 3) the genetic association with the outcome is distorted by an effect of the outcome in the parental generation on the outcome in the offspring generation. In these scenarios, we show that all causal effects typically estimated in Mendelian randomization analyses will be biased, though hypothesis testing can still be valid in Scenario 2 and 3 for a sharp causal null hypothesis. This underscores the general recommendation to view Mendelian randomization as primarily testing a causal null hypothesis rather than estimating a causal effect.

Funder: NIHR Cambridge Biomedical Research Centre; Id: http://dx.doi.org/10.13039/501100018956, OBJECTIVE: To assess the causality of the associations of rheumatoid arthritis (RA) with coronary artery disease (CAD) and stroke using the Mendelian randomization approach. METHODS: Independent single-nucleotide polymorphisms strongly associated with RA (n = 70) were selected as instrumental variables from a genome-wide association meta-analysis including 14,361 RA patients and 43,923 controls of European ancestry. Summary-level data for CAD, all stroke, any ischemic stroke and its subtypes, intracerebral hemorrhage (ICH), and subarachnoid hemorrhage were obtained from meta-analyses of genetic studies, international genetic consortia, the UK Biobank, and the FinnGen consortium. We obtained summary-level data for common cardiovascular risk factors and related inflammatory biomarkers to assess possible mechanisms. RESULTS: Genetic liability to RA was associated with an increased risk of CAD and ICH. For a 1-unit increase in log odds of RA, the combined odds ratios were 1.02 (95% confidence interval [1.01, 1.03]; P = 0.003) for CAD and 1.05 (95% confidence interval [1.02, 1.08]; P = 0.001) for ICH. Genetic liability to RA was associated with increased levels of tumor necrosis factor and C-reactive protein (CRP). The association with CAD was attenuated after adjustment for genetically predicted CRP levels. There were no associations of genetic liability to RA with the other studied outcomes. CONCLUSION: This study found that genetic liability to RA was associated with an increased risk of CAD and ICH and that the association with CAD might be mediated by CRP. The heightened cardiovascular risk should be actively monitored and managed in RA patients, and this may include dampening systemic inflammation.

ObjectiveTo investigate the association between smoking and infertility.DesignProspective study.SettingNationwide cohort.Patients28,606 women and 27,096 men with questionnaire and genotype information from the Norwegian Mother, Father, and Child Cohort Study.InterventionSelf-reported information on smoking (having ever smoked [both sexes], age at initiation [women only], cessation [women only], and cigarettes/week in current smokers [both sexes]) was gathered. Genetically predetermined levels or likelihood of presenting these traits were estimated for Mendelian randomization.Main outcome measureInfertility (time-to-pregnancy ≥12 months).ResultsHaving ever smoked was unrelated to infertility in women or men. Higher smoking intensity in women was associated with greater infertility odds (+1 standard deviation [SD, 48 cigarettes/week]: odds ratio [OR]crude, 1.19; 95% confidence interval [CI] 1.11–1.28; ORadjusted 1.12; 95% CI, 1.03–1.21), also after adjusting for the partner’s tobacco use. Later smoking initiation (+1 SD [3.2 years]: ORcrude, 0.94; 95% CI, 0.88–0.99; ORadjusted 0.89; 95% CI, 0.84–0.95) and smoking cessation (vs. not quitting: ORcrude, 0.83; 95% CI, 0.75–0.91; ORadjusted, 0.83; 95% CI, 0.75–0.93) were linked to decreased infertility in women. Nevertheless, Mendelian randomization results were not directionally consistent for smoking intensity and cessation and were estimated imprecisely in the 2-sample approach. In men, greater smoking intensity was not robustly associated with infertility in multivariable regression and Mendelian randomization.ConclusionsWe did not find robust evidence of an effect of smoking on infertility. This may be due to a true lack of effect, weak genetic instruments, or other kinds of confounding.

Mendelian randomization and colocalization are two statistical approaches that can be applied to summarized data from genome-wide association studies (GWASs) to understand relationships between traits and diseases. However, despite similarities in scope, they are different in their objectives, implementation, and interpretation, in part because they were developed to serve different scientific communities. Mendelian randomization assesses whether genetic predictors of an exposure are associated with the outcome and interprets an association as evidence that the exposure has a causal effect on the outcome, whereas colocalization assesses whether two traits are affected by the same or distinct causal variants. When considering genetic variants in a single genetic region, both approaches can be performed. While a positive colocalization finding typically implies a non-zero Mendelian randomization estimate, the reverse is not generally true: there are several scenarios which would lead to a non-zero Mendelian randomization estimate but lack evidence for colocalization. These include the existence of distinct but correlated causal variants for the exposure and outcome, which would violate the Mendelian randomization assumptions, and a lack of strong associations with the outcome. As colocalization was developed in the GWAS tradition, typically evidence for colocalization is concluded only when there is strong evidence for associations with both traits. In contrast, a non-zero estimate from Mendelian randomization can be obtained despite only nominally significant genetic associations with the outcome at the locus. In this review, we discuss how the two approaches can provide complementary information on potential therapeutic targets.

Dietary factors are assumed to play an important role in cancer risk, apparent in consensus recommendations for cancer prevention that promote nutritional changes. However, the evidence in this field has been generated predominantly through observational studies, which may result in biased effect estimates because of confounding, exposure misclassification, and reverse causality. With major geographical differences and rapid changes in cancer incidence over time, it is crucial to establish which of the observational associations reflect causality and to identify novel risk factors as these may be modified to prevent the onset of cancer and reduce its progression. Mendelian randomization (MR) uses the special properties of germline genetic variation to strengthen causal inference regarding potentially modifiable exposures and disease risk. MR can be implemented through instrumental variable (IV) analysis and, when robustly performed, is generally less prone to confounding, reverse causation and measurement error than conventional observational methods and has different sources of bias (discussed in detail below). It is increasingly used to facilitate causal inference in epidemiology and provides an opportunity to explore the effects of nutritional exposures on cancer incidence and progression in a cost-effective and timely manner. Here, we introduce the concept of MR and discuss its current application in understanding the impact of nutritional factors (e.g., any measure of diet and nutritional intake, circulating biomarkers, patterns, preference or behaviour) on cancer aetiology and, thus, opportunities for MR to contribute to the development of nutritional recommendations and policies for cancer prevention. We provide applied examples of MR studies examining the role of nutritional factors in cancer to illustrate how this method can be used to help prioritise or deprioritise the evaluation of specific nutritional factors as intervention targets in randomised controlled trials. We describe possible biases when using MR, and methodological developments aimed at investigating and potentially overcoming these biases when present. Lastly, we consider the use of MR in identifying causally relevant nutritional risk factors for various cancers in different regions across the world, given notable geographical differences in some cancers. We also discuss how MR results could be translated into further research and policy. We conclude that findings from MR studies, which corroborate those from other well-conducted studies with different and orthogonal biases, are poised to substantially improve our understanding of nutritional influences on cancer. For such corroboration, there is a requirement for an interdisciplinary and collaborative approach to investigate risk factors for cancer incidence and progression.

IMPORTANCE: Previous in vitro and postmortem research suggests that inflammation may lead to structural brain changes via activation of microglia and/or astrocytic dysfunction in a range of neuropsychiatric disorders. OBJECTIVE: To investigate the relationship between inflammation and changes in brain structures in vivo and to explore a transcriptome-driven functional basis with relevance to mental illness. DESIGN, SETTING, AND PARTICIPANTS: This study used multistage linked analyses, including mendelian randomization (MR), gene expression correlation, and connectivity analyses. A total of 20 688 participants in the UK Biobank, which includes clinical, genomic, and neuroimaging data, and 6 postmortem brains from neurotypical individuals in the Allen Human Brain Atlas (AHBA), including RNA microarray data. Data were extracted in February 2021 and analyzed between March and October 2021. EXPOSURES: Genetic variants regulating levels and activity of circulating interleukin 1 (IL-1), IL-2, IL-6, C-reactive protein (CRP), and brain-derived neurotrophic factor (BDNF) were used as exposures in MR analyses. MAIN OUTCOMES AND MEASURES: Brain imaging measures, including gray matter volume (GMV) and cortical thickness (CT), were used as outcomes. Associations were considered significant at a multiple testing-corrected threshold of P < 1.1 × 10-4. Differential gene expression in AHBA data was modeled in brain regions mapped to areas significant in MR analyses; genes were tested for biological and disease overrepresentation in annotation databases and for connectivity in protein-protein interaction networks. RESULTS: Of 20 688 participants in the UK Biobank sample, 10 828 (52.3%) were female, and the mean (SD) age was 55.5 (7.5) years. In the UK Biobank sample, genetically predicted levels of IL-6 were associated with GMV in the middle temporal cortex (z score, 5.76; P = 8.39 × 10-9), inferior temporal (z score, 3.38; P = 7.20 × 10-5), fusiform (z score, 4.70; P = 2.60 × 10-7), and frontal (z score, -3.59; P = 3.30 × 10-5) cortex together with CT in the superior frontal region (z score, -5.11; P = 3.22 × 10-7). No significant associations were found for IL-1, IL-2, CRP, or BDNF after correction for multiple comparison. In the AHBA sample, 5 of 6 participants (83%) were male, and the mean (SD) age was 42.5 (13.4) years. Brain-wide coexpression analysis showed a highly interconnected network of genes preferentially expressed in the middle temporal gyrus (MTG), which further formed a highly connected protein-protein interaction network with IL-6 (enrichment test of expected vs observed network given the prevalence and degree of interactions in the STRING database: 43 nodes/30 edges observed vs 8 edges expected; mean node degree, 1.4; genome-wide significance, P = 4.54 × 10-9). MTG differentially expressed genes that were functionally enriched for biological processes in schizophrenia, autism spectrum disorder, and epilepsy. CONCLUSIONS AND RELEVANCE: In this study, genetically determined IL-6 was associated with brain structure and potentially affects areas implicated in developmental neuropsychiatric disorders, including schizophrenia and autism.

BACKGROUND AND PURPOSE: The roles of blood low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides in the development of post-stroke dementia remain uncertain. This study was to investigate their potential associations. METHODS: A retrospective cohort study was conducted using the Clinical Practice Research Datalink. Patients with first-ever stroke but no prior dementia were followed up for 10 years. Cox regression was used to examine the association of baseline LDL-C, HDL-C and triglycerides with post-stroke dementia. RESULTS: Amongst 63,959 stroke patients, 15,879 had complete baseline data and were included in our main analysis. 10.8% developed dementia during a median of 4.6 years of follow-up. The adjusted hazard ratio of dementia for LDL-C (per log mmol/l increase) was 1.29 (95% confidence interval [CI] 1.14-1.47), with a linear increasing trend (p trend

Funder: MQ: Transforming Mental Health; Grant(s): MQDS17/40, Background Schizophrenia commonly co-occurs with cardiometabolic and inflammation-related traits. It is unclear to what extent the comorbidity could be explained by shared genetic aetiology. Methods We used GWAS data to estimate shared genetic aetiology between schizophrenia, cardiometabolic and inflammation-related traits: fasting insulin (FI), fasting glucose, glycated haemoglobin, glucose tolerance, type 2 diabetes (T2D), lipids, body mass index (BMI), coronary artery disease (CAD), and C-reactive protein (CRP). We examined genome-wide correlation using linkage disequilibrium score regression (LDSC); stratified by minor-allele frequency using genetic covariance analyzer (GNOVA); then refined to locus-level using heritability estimation from summary statistics (ρ-HESS). Regions with local correlation were used in hypothesis prioritization multi-trait colocalization to examine for colocalisation, implying common genetic aetiology. Results We found evidence for weak genome-wide negative correlation of schizophrenia with T2D (rg=-0.07; 95% C.I., -0.03,0.12; p=0.002) and BMI (rg=-0.09; 95% C.I., -0.06,-0.12; p=1.83x10-5). We found a trend of evidence for positive genetic correlation between schizophrenia and cardiometabolic traits confined to lower-frequency variants. This was underpinned by 85 regions of locus-level correlation with evidence of opposing mechanisms. Ten loci showed strong evidence of colocalization. Four of those (rs6265 (BDNF); rs8192675 (SLC2A2); rs3800229 (FOXO3); rs17514846 (FURIN)) are implicated in brain-derived neurotrophic factor (BDNF)-related pathways. Conclusions LDSC may lead to downwardly-biased genetic correlation estimates between schizophrenia, cardiometabolic and inflammation-related traits. Common genetic aetiology for these traits could be confined to lower-frequency common variants and involve opposing mechanisms. Genes related to BDNF and glucose transport amongst others may partly explain the comorbidity between schizophrenia and cardiometabolic disorders.

Introduction For many exposures present across the life course, the effect of the exposure may vary over time. Multivariable Mendelian randomization (MVMR) is an approach that can assess the effects of related risk factors using genetic variants as instrumental variables. Recently, MVMR has been used to estimate the effects of an exposure during distinct time periods. Methods We investigated the behaviour of estimates from MVMR in a simulation study for different time-varying causal scenarios. We also performed an applied analysis to consider how MVMR estimates of body mass index on systolic blood pressure vary depending on the time periods considered. Results Estimates from MVMR in the simulation study were close to the true values when the outcome model was correctly specified: i.e. when the outcome was a discrete function of the exposure at the precise time points at which the exposure was measured. However, in more realistic cases, MVMR estimates were misleading. For example, in one scenario, MVMR estimates for early life were clearly negative despite the true causal effect being constant and positive. In the applied example, estimates were highly variable depending on the time period in which genetic associations with the exposure were estimated. Conclusions The poor performance of MVMR to study time-varying causal effects can be attributed to model misspecification and violation of the exclusion restriction assumption. We would urge caution about quantitative conclusions from such analyses and even qualitative interpretations about the direction, or presence or absence, of a causal effect during a given time period.

Funder: Wellcome Trust, Many individual genetic risk loci have been associated with multiple common human diseases. However, the molecular basis of this pleiotropy often remains unclear. We present an integrative approach to reveal the molecular mechanism underlying the PROCR locus, associated with lower coronary artery disease (CAD) risk but higher venous thromboembolism (VTE) risk. We identify PROCR-p.Ser219Gly as the likely causal variant at the locus and protein C as a causal factor. Using genetic analyses, human recall-by-genotype and in vitro experimentation, we demonstrate that PROCR-219Gly increases plasma levels of (activated) protein C through endothelial protein C receptor (EPCR) ectodomain shedding in endothelial cells, attenuating leukocyte-endothelial cell adhesion and vascular inflammation. We also associate PROCR-219Gly with an increased pro-thrombotic state via coagulation factor VII, a ligand of EPCR. Our study, which links PROCR-219Gly to CAD through anti-inflammatory mechanisms and to VTE through pro-thrombotic mechanisms, provides a framework to reveal the mechanisms underlying similar cross-phenotype associations.

Background Obesity and type 2 diabetes (T2D) are correlated risk factors for chronic kidney disease (CKD). Methods Using summary data from GIANT (Genetic Investigation of Anthropometric Traits), DIAGRAM (DIAbetes Genetics Replication And Meta-analysis), and CKDGen (CKD Genetics), we examined causality and directionality of the association between obesity and kidney function. Bidirectional 2-sample Mendelian randomization (MR) estimated the total causal effects of body mass index (BMI) and waist-to-hip ratio (WHR) on kidney function, and vice versa. Effects of adverse obesity and T2D were examined by stratifying BMI variants by their association with WHR and T2D. Multivariable MR estimated the direct causal effects of BMI and WHR on kidney function. The inverse variance weighted random-effects MR for Europeans was the main analysis, accompanied by several sensitivity MR analyses. Results One standard deviation (SD ≈ 4.8 kg/m2) genetically higher BMI was associated with decreased estimated glomerular filtration rate (eGFR) [β=−0.032 (95% confidence intervals: −0.036, −0.027) log[eGFR], P = 1 × 10−43], increased blood urea nitrogen (BUN) [β = 0.010 (0.005, 0.015) log[BUN], P = 3 × 10−6], increased urinary albumin-to-creatinine ratio [β = 0.199 (0.067, 0.332) log[urinary albumin-to-creatinine ratio (UACR)], P = 0.003] in individuals with diabetes, and increased risk of microalbuminuria [odds ratios (OR) = 1.15 [1.04–1.28], P = 0.009] and CKD [1.13 (1.07–1.19), P = 3 × 10−6]. Corresponding estimates for WHR and for trans-ethnic populations were overall similar. The associations were driven by adverse obesity, and for microalbuminuria additionally by T2D. While genetically high BMI, unlike WHR, was directly associated with eGFR, BUN, and CKD, the pathway to albuminuria was likely through T2D. Genetically predicted kidney function was not associated with BMI or WHR. Conclusions Genetically high BMI is associated with impaired kidney function, driven by adverse obesity, and for albuminuria additionally by T2D.

Pulse pressure (PP), the difference between systolic blood pressure (SBP) and diastolic blood pressure (DBP), arises due to pulsatile ejection of blood from the left ventricle. Previous observational studies have identified an inverse association of PP with aortic diameter1, and positive associations of PP with aortic wall stiffness and thickness2. However, it is not known whether these associations reflect a causal effect of PP on the risk of AAA, an effect of the aorta on PP, a shared etiology, or confounding from environmental factors.

Funder: BHF Centre of Research Excellence, Oxford, Funder: China Scholarship Council, Funder: Li Ka Shing Foundation, BACKGROUND: Brain iron deposition has been linked to several neurodegenerative conditions and reported in alcohol dependence. Whether iron accumulation occurs in moderate drinkers is unknown. Our objectives were to investigate evidence in support of causal relationships between alcohol consumption and brain iron levels and to examine whether higher brain iron represents a potential pathway to alcohol-related cognitive deficits. METHODS AND FINDINGS: Observational associations between brain iron markers and alcohol consumption (n = 20,729 UK Biobank participants) were compared with associations with genetically predicted alcohol intake and alcohol use disorder from 2-sample mendelian randomization (MR). Alcohol intake was self-reported via a touchscreen questionnaire at baseline (2006 to 2010). Participants with complete data were included. Multiorgan susceptibility-weighted magnetic resonance imaging (9.60 ± 1.10 years after baseline) was used to ascertain iron content of each brain region (quantitative susceptibility mapping (QSM) and T2*) and liver tissues (T2*), a marker of systemic iron. Main outcomes were susceptibility (χ) and T2*, measures used as indices of iron deposition. Brain regions of interest included putamen, caudate, hippocampi, thalami, and substantia nigra. Potential pathways to alcohol-related iron brain accumulation through elevated systemic iron stores (liver) were explored in causal mediation analysis. Cognition was assessed at the scan and in online follow-up (5.82 ± 0.86 years after baseline). Executive function was assessed with the trail-making test, fluid intelligence with puzzle tasks, and reaction time by a task based on the "Snap" card game. Mean age was 54.8 ± 7.4 years and 48.6% were female. Weekly alcohol consumption was 17.7 ± 15.9 units and never drinkers comprised 2.7% of the sample. Alcohol consumption was associated with markers of higher iron (χ) in putamen (β = 0.08 standard deviation (SD) [95% confidence interval (CI) 0.06 to 0.09], p < 0.001), caudate (β = 0.05 [0.04 to 0.07], p < 0.001), and substantia nigra (β = 0.03 [0.02 to 0.05], p < 0.001) and lower iron in the thalami (β = -0.06 [-0.07 to -0.04], p < 0.001). Quintile-based analyses found these associations in those consuming >7 units (56 g) alcohol weekly. MR analyses provided weak evidence these relationships are causal. Genetically predicted alcoholic drinks weekly positively associated with putamen and hippocampus susceptibility; however, these associations did not survive multiple testing corrections. Weak evidence for a causal relationship between genetically predicted alcohol use disorder and higher putamen susceptibility was observed; however, this was not robust to multiple comparisons correction. Genetically predicted alcohol use disorder was associated with serum iron and transferrin saturation. Elevated liver iron was observed at just >11 units (88 g) alcohol weekly c.f.

Background We aimed to map and describe the current state of Mendelian randomization (MR) literature on cancer risk and to identify associations supported by robust evidence. Methods We searched PubMed and Scopus up to 06/10/2020 for MR studies investigating the association of any genetically predicted risk factor with cancer risk. We categorized the reported associations based on a priori designed levels of evidence supporting a causal association into four categories, namely robust, probable, suggestive, and insufficient, based on the significance and concordance of the main MR analysis results and at least one of the MR-Egger, weighed median, MRPRESSO, and multivariable MR analyses. Associations not presenting any of the aforementioned sensitivity analyses were not graded. Results We included 190 publications reporting on 4667 MR analyses. Most analyses (3200; 68.6%) were not accompanied by any of the assessed sensitivity analyses. Of the 1467 evaluable analyses, 87 (5.9%) were supported by robust, 275 (18.7%) by probable, and 89 (6.1%) by suggestive evidence. The most prominent robust associations were observed for anthropometric indices with risk of breast, kidney, and endometrial cancers; circulating telomere length with risk of kidney, lung, osteosarcoma, skin, thyroid, and hematological cancers; sex steroid hormones and risk of breast and endometrial cancer; and lipids with risk of breast, endometrial, and ovarian cancer. Conclusions Despite the large amount of research on genetically predicted risk factors for cancer risk, limited associations are supported by robust evidence for causality. Most associations did not present a MR sensitivity analysis and were thus non-evaluable. Future research should focus on more thorough assessment of sensitivity MR analyses and on more transparent reporting.

Inflammation contributes to atherosclerosis and coronary artery disease (CAD). In order to help identify therapeutic targets, it is important to ascertain whether biomarkers associated with CAD risk are causal. In a recent meta-analysis of clinical trials, neutrophil-to lymphocyte ratio (NLR) was associated with increased cardiovascular risk 1 . We investigate a potential causal nature of this relationship by performing Mendelian randomization (MR) analyses

Clustering genetic variants based on their associations with different traits can provide insight into their underlying biological mechanisms. Existing clustering approaches typically group variants based on the similarity of their association estimates for various traits. We present a new procedure for clustering variants based on their proportional associations with different traits, which is more reflective of the underlying mechanisms to which they relate. The method is based on a mixture model approach for directional clustering and includes a noise cluster that provides robustness to outliers. The procedure performs well across a range of simulation scenarios. In an applied setting, clustering genetic variants associated with body mass index generates groups reflective of distinct biological pathways. Mendelian randomization analyses support that the clusters vary in their effect on coronary heart disease, including one cluster that represents elevated body mass index with a favourable metabolic profile and reduced coronary heart disease risk. Analysis of the biological pathways underlying this cluster identifies inflammation as potentially explaining differences in the effects of increased body mass index on coronary heart disease.

ContextThe causal role of endogenous estradiol in cancers other than breast and endometrial cancer remains unclear.ObjectiveThis Mendelian randomization study assessed the causal associations of endogenous 17β-estradiol (E2), the most potent estrogen, with cancer risk in women.MethodsAs primary genetic instrument, we used a genetic variant in the CYP19A1 gene that is strongly associated with serum E2 levels. Summary statistics genetic data for the association of the E2 variant with breast, endometrial, and ovarian cancer were obtained from large-scale consortia. We additionally estimated the associations of the E2 variant with any and 20 site-specific cancers in 198 825 women of European descent in UK Biobank. Odds ratios (OR) of cancer per 0.01 unit increase in log-transformed serum E2 levels in pmol/L were estimated using the Wald ratio.ResultsGenetic predisposition to higher serum E2 levels was associated with increased risk of estrogen receptor (ER)-positive breast cancer (OR 1.02; 95% CI, 1.01-1.03; P = 2.5 × 10−3), endometrial cancer overall (OR 1.09; 95% CI, 1.06-1.11; P = 7.3 × 10−13), and endometrial cancer of the endometrioid histology subtype (OR 1.10; 95% CI, 1.07-1.13; P = 2.1 × 10−11). There were suggestive associations with breast cancer overall (OR 1.01; 95% CI, 1.00-1.02; P = 0.02), ovarian cancer of the endometrioid subtype (OR 1.05; 95% CI, 1.01-1.10; P = 0.02), and stomach cancer (OR 1.12; 95% CI, 1.00-1.26; P = 0.05), but no significant association with other cancers.ConclusionThis study supports a role of E2 in the development of ER-positive breast cancer and endometrioid endometrial cancer but found no strong association with other cancers in women.

Aim We conducted a two-sample Mendelian randomization (MR) study to assess the associations of genetically predicted circulating vitamin C levels with cardiovascular diseases (CVDs). Methods and results Ten lead single-nucleotide polymorphisms associated with plasma vitamin C levels at the genome-wide significance level were used as instrumental variables. Summary-level data for 15 CVDs were obtained from corresponding genetic consortia, the UK Biobank study, and the FinnGen consortium. The inverse-variance-weighted method was the primary analysis method, supplemented by the weighted median and MR-Egger methods. Estimates for each CVD from different sources were combined. Genetically predicted vitamin C levels were not associated with any CVD after accounting for multiple testing. However, there were suggestive associations of higher genetically predicted vitamin C levels (per 1 standard deviation increase) with lower risk of cardioembolic stroke [odds ratio, 0.79; 95% confidence interval (CI), 0.64, 0.99; P = 0.038] and higher risk of atrial fibrillation (odds ratio, 1.09; 95% CI, 1.00, 1.18; P = 0.049) in the inverse-variance-weighted method and with lower risk of peripheral artery disease (odds ratio, 0.76, 95% CI, 0.62, 0.93; P = 0.009) in the weighted median method. Conclusion We found limited evidence with MR techniques for an overall protective role of vitamin C in the primary prevention of CVD. The associations of vitamin C levels with cardioembolic stroke, atrial fibrillation, and peripheral artery disease need further study.

Funder: Swedish Cancer Society (Cancerfonden); Id: http://dx.doi.org/10.13039/501100002794, Funder: EC‐Innovative Medicines Initiative (BigData@Heart), Evidence on the association between selenium and cancer risk is inconclusive. We conducted a Mendelian randomization study to examine the associations of selenium levels with 22 site-specific cancers and any cancer. Single nucleotide polymorphisms (SNPs) strongly associated with toenail and blood (TAB) and blood selenium levels in mild linkage disequilibrium (r2 < .3) were used as instrumental variables. Genetic associations of selenium-associated SNPs with cancer were obtained from the UK Biobank including a total of 59 647 cancer cases and 307 914 controls. Associations with P < .1 in UK Biobank were tested for replication in the FinnGen consortium comprising more than 180 000 individuals. The inverse-variance weighted method accounting for linkage disequilibrium was used to estimate the associations. Genetically predicted TAB selenium levels were not associated with the risk of the 22 site-specific cancers or any cancer (all 22 site-specific cancers). Similarly, we observed no strong association for genetically predicted blood selenium levels. However, genetically predicted blood selenium levels showed suggestive associations with risk of kidney cancer (odds ratio [OR] per one-unit increase in log-transformed levels: 0.83; 95% confidence interval [CI]: 0.67-1.03) and multiple myeloma (OR: 1.40; 95% CI: 1.02-1.93). The same direction of association for kidney cancer but not for multiple myeloma was observed in FinnGen. In the metaanalysis of UK Biobank and FinnGen, the OR of kidney cancer was 0.83 (95% CI: 0.69-1.00). Our study suggests that high selenium status may not prevent cancer development. The associations for kidney cancer and multiple myeloma need to be verified in well-powered studies.

Background Schizophrenia commonly co-occurs with cardiometabolic and inflammation-related traits. It is unclear to what extent the comorbidity could be explained by shared genetic aetiology. Methods We used GWAS data to estimate shared genetic aetiology between schizophrenia, cardiometabolic, and inflammation-related traits: fasting insulin (FI), fasting glucose, glycated haemoglobin, glucose tolerance, type 2 diabetes (T2D), lipids, body mass index (BMI), coronary artery disease (CAD), and C-reactive protein (CRP). We examined genome-wide correlation using linkage disequilibrium score regression (LDSC); stratified by minor-allele frequency using genetic covariance analyzer (GNOVA); then refined to locus-level using heritability estimation from summary statistics (ρ-HESS). Regions with local correlation were used in hypothesis prioritization multi-trait colocalization to examine for colocalisation, implying common genetic aetiology. Results We found evidence for weak genome-wide negative correlation of schizophrenia with T2D (rg = −0.07; 95% C.I., −0.03,0.12; P = .002) and BMI (rg = −0.09; 95% C.I., −0.06, −0.12; P = 1.83 × 10−5). We found a trend of evidence for positive genetic correlation between schizophrenia and cardiometabolic traits confined to lower-frequency variants. This was underpinned by 85 regions of locus-level correlation with evidence of opposing mechanisms. Ten loci showed strong evidence of colocalization. Four of those (rs6265 (BDNF); rs8192675 (SLC2A2); rs3800229 (FOXO3); rs17514846 (FURIN)) are implicated in brain-derived neurotrophic factor (BDNF)-related pathways. Conclusions LDSC may lead to downwardly-biased genetic correlation estimates between schizophrenia, cardiometabolic, and inflammation-related traits. Common genetic aetiology for these traits could be confined to lower-frequency common variants and involve opposing mechanisms. Genes related to BDNF and glucose transport amongst others may partly explain the comorbidity between schizophrenia and cardiometabolic disorders.

Funder: NIHR Cambridge Biomedical Research Centre, Clustering genetic variants based on their associations with different traits can provide insight into their underlying biological mechanisms. Existing clustering approaches typically group variants based on the similarity of their association estimates for various traits. We present a new procedure for clustering variants based on their proportional associations with different traits, which is more reflective of the underlying mechanisms to which they relate. The method is based on a mixture model approach for directional clustering and includes a noise cluster that provides robustness to outliers. The procedure performs well across a range of simulation scenarios. In an applied setting, clustering genetic variants associated with body mass index generates groups reflective of distinct biological pathways. Mendelian randomization analyses support that the clusters vary in their effect on coronary heart disease, including one cluster that represents elevated body mass index with a favourable metabolic profile and reduced coronary heart disease risk. Analysis of the biological pathways underlying this cluster identifies inflammation as potentially explaining differences in the effects of increased body mass index on coronary heart disease.

Funder: Chief Scientist Office, Funder: Medical Research Council, INTRODUCTION: In observational studies, venous thromboembolism (VTE) has been associated with Cushing's syndrome and with persistent mental stress, two conditions associated with higher cortisol levels. However, it remains unknown whether high cortisol levels within the usual range are causally associated with VTE risk. We aimed to assess the association between plasma cortisol levels and VTE risk using Mendelian randomization. METHODS: Three genetic variants in the SERPINA1/SERPINA6 locus (rs12589136, rs11621961 and rs2749527) were used to proxy plasma cortisol. The associations of the cortisol-associated genetic variants with VTE were acquired from the INVENT (28 907 cases and 157 243 non-cases) and FinnGen (6913 cases and 169 986 non-cases) consortia. Corresponding data for VTE subtypes were available from the FinnGen consortium and UK Biobank. Two-sample Mendelian randomization analyses (inverse-variance weighted method) were performed. RESULTS: Genetic predisposition to higher plasma cortisol levels was associated with a reduced risk of VTE (odds ratio [OR] per one standard deviation increment 0.73, 95% confidence interval [CI] 0.62-0.87, p

Bias from weak instruments may undermine the ability to estimate causal effects in instrumental variable regression (IVR). We present here a new approach to handling weak instrument bias through the application of a new type of instrumental variable coined ‘Cross-Fitted Instrument’ (CFI). CFI splits the data at random and estimates the impact of the instrument on the exposure in each partition. These estimates are then used to perform an IVR on each partition. We adapt CFI to the Mendelian randomization (MR) setting and term this adaptation ‘Cross-Fitting for Mendelian Randomization’ (CFMR). We show that, even when using weak instruments, CFMR is, at worst, biased towards the null, which makes it a conservative one-sample MR approach. In particular, CFMR remains conservative even when the two samples used to perform the MR analysis completely overlap, whereas current state-of-the-art approaches (e.g., MR RAPS) display substantial bias in this setting. Another major advantage of CFMR lies in its use of all of the available data to select genetic instruments, which maximizes statistical power, as opposed to traditional two-sample MR where only part of the data is used to select the instrument. Consequently, CFMR is able to enhance statistical power in consortia-led meta-analyses by enabling a conservative one-sample MR to be performed in each cohort prior to a meta-analysis of the results across all the cohorts. In addition, CFMR enables a cross-ethnic MR analysis by accounting for ethnic heterogeneity, which is particularly important in meta-analyses where the participating cohorts may have different ethnicities. To our knowledge, none of the current MR approaches can account for such heterogeneity. Finally, CFMR enables the application of MR to exposures that are either rare or difficult to measure, which would normally preclude their analysis in the regular two-sample MR setting.