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

statistics for genome-wide association studies (GWAS) are increasingly available for downstream analyses. Meanwhile, the popularity of casual inference methods has grown as we look to gather robust evidence for novel medical and public health interventions. This has led to the development of methods that use GWAS summary statistics for causal inference. Here, we describe these methods in order of their escalating complexity, from genetic associations to extensions of Mendelian randomization that consider thousands of phenotypes simultaneously. We also cover the assumptions and limitations of these approaches before considering the challenges faced by researchers performing causal inference using GWAS data. GWAS summary statistics constitute an important data source for causal inference research that offers a counterpoint to nongenetic methods when triangulating evidence. Continued efforts to address the challenges in using GWAS data for causal inference will allow the full impact of these approaches to be realized. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Objective: We aimed to estimate the effect of blood pressure (BP) traits and BP-lowering medications (via genetic proxies) on peripheral artery disease. Approach and Results: Genome-wide association studies summary statistics were obtained for BP, peripheral artery disease (PAD), and coronary artery disease. Causal effects of BP on PAD were estimated by 2-sample Mendelian randomization using a range of pleiotropy-robust methods. Increased systolic BP (SBP), diastolic BP, mean arterial pressure (MAP), and pulse pressure each significantly increased risk of PAD (SBP odds ratio [OR], 1.20 [1.16–1.25] per 10 mm Hg increase, P =1×10 −24 ; diastolic BP OR, 1.27 [1.18–1.35], P =4×10 −11 ; MAP OR, 1.26 [1.19–1.33], P =6×10 −16 ; pulse pressure OR, 1.31 [1.24–1.39], P =9×10 −23 ). The effects of SBP, diastolic BP, and MAP were greater for coronary artery disease than PAD (SBP ratio of OR [ROR], 1.06 [1.0–1.12], P = 0.04; MAP ratio of OR, 1.15 [1.06–1.26], P =8.6×10 −4 ; diastolic BP ratio of OR, 1.21 [1.08–1.35], P =6.9×10 −4 ). Considered jointly, both pulse pressure and MAP directly increased risk of PAD (pulse pressure OR, 1.26 [1.17–1.35], P =3×10 −10 ; MAP OR, 1.14 [1.06–1.23], P =2×10 −4 ). The effects of antihypertensive medications were estimated using genetic instruments. SBP-lowering via β-blocker (OR, 0.74 per 10 mm Hg decrease in SBP [95% CI, 0.65–0.84]; P =5×10 −6 ), loop diuretic (OR, 0.66 [0.48–0.91], P =0.01), and thiazide diuretic (OR, 0.57 [0.41–0.79], P =6×10 −4 ) associated variants were protective of PAD. Conclusions: Higher BP is likely to cause PAD. BP-lowering through β blockers, loop diuretics, and thiazide diuretics (as proxied by genetic variants) was associated with decreased risk of PAD. Future study is needed to clarify the specific mechanisms by which BP influences PAD.

Background Traditionally, heritability has been estimated using family-based methods such as twin studies. Advancements in molecular genomics have facilitated the development of methods that use large samples of (unrelated or related) genotyped individuals. Methods Here, we provide an overview of common methods applied in genetic epidemiology to estimate heritability, i.e. the proportion of phenotypic variation explained by genetic variation. We provide a guide to key genetic concepts required to understand heritability estimation methods from family-based designs (twin and family studies), genomic designs based on unrelated individuals [linkage disequilibrium score regression, genomic relatedness restricted maximum-likelihood (GREML) estimation] and family-based genomic designs (sibling regression, GREML-kinship, trio-genome-wide complex trait analysis, maternal-genome-wide complex trait analysis, relatedness disequilibrium regression). Results We describe how heritability is estimated for each method and the assumptions underlying its estimation, and discuss the implications when these assumptions are not met. We further discuss the benefits and limitations of estimating heritability within samples of unrelated individuals compared with samples of related individuals. Conclusions Overall, this article is intended to help the reader determine the circumstances when each method would be appropriate and why.

Genetic studies of disease progression can be used to identify factors that may influence survival or prognosis, which may differ from factors which influence on disease susceptibility. Studies of disease progression feed directly into therapeutics for disease, whereas studies of incidence inform prevention strategies. However, studies of disease progression are known to be affected by collider (also known as “index event”) bias since the disease progression phenotype can only be observed for individuals who have the disease. This applies equally to observational and genetic studies, including genome-wide association studies and Mendelian randomization analyses. In this paper, our aim is to review several statistical methods that can be used to detect and adjust for index event bias in studies of disease progression, and how they apply to genetic and Mendelian Randomization studies using both individual and summary-level data. Methods to detect the presence of index event bias include the use of negative controls, a comparison of associations between risk factors for incidence in individuals with and without the disease, and an inspection of Miami plots. Methods to adjust for the bias include inverse probability weighting (with individual-level data), or Slope-hunter and Dudbridge’s index event bias adjustment (when only summary-level data are available). We also outline two approaches for sensitivity analysis. We then illustrate how three methods to minimise bias can be used in practice with two applied examples. Our first example investigates the effects of blood lipid traits on mortality from coronary heart disease, whilst our second example investigates genetic associations with breast cancer mortality.

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

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.

Supplemental Digital Content is available in the text., Background: Hypertension in midlife is associated with increased risk of Alzheimer disease and vascular dementia late in life. In addition, some antihypertensive drugs have been proposed to have cognitive benefits, independent of their effect on hypertension. Consequently, there is potential to repurpose antihypertensive drugs for the prevention of dementia. This study systematically compared seven antihypertensive drug classes for this purpose, using the Clinical Practice Research Datalink. Methods: We assessed treatments for hypertension in an instrumental variable analysis to address potential confounding and reverse causation. We used physicians’ prescribing preference as an ordinal instrument, defined by the physicians’ last seven prescriptions. Participants considered were new antihypertensive users between 1996 and 2016, aged 40 and over. Results: We analyzed 849,378 patients, with total follow up of 5,497,266 patient-years. We estimated that β-adrenoceptor blockers and vasodilator antihypertensives conferred small protective effects—for example, β-adrenoceptor blockers were associated with 13 (95% confidence interval = 6, 20) fewer cases of any dementia per 1000 treated compared with other antihypertensives. Conclusions: We estimated small differences in the effects of antihypertensive drug classes on dementia outcomes. We also show that the magnitude of the differences between drug classes is smaller than that previously reported. Future research should look to implement other causal analysis methods to address biases in conventional observational research, with the ultimate aim of triangulating the evidence concerning this hypothesis.

Therapeutic targets for halting the progression of Alzheimer’s disease pathology are lacking. Recent evidence suggests that APOE4, but not APOE3, activates the Cyclophilin-A matrix metalloproteinase-9 (CypA-MMP9) pathway, leading to an accelerated breakdown of the blood–brain barrier (BBB) and thereby causing neuronal and synaptic dysfunction. Furthermore, blockade of the CypA-MMP9 pathway in APOE4 knock-in mice restores BBB integrity and subsequently normalizes neuronal and synaptic function. Thus, CypA has been suggested as a potential target for treating APOE4 mediated neurovascular injury and the resulting neuronal dysfunction and degeneration. The odds of drug targets passing through clinical trials are greatly increased if they are supported by genomic evidence. We found little evidence to suggest that CypA or MMP9 affects the risk of Alzheimer’s disease or cognitive impairment using two-sample Mendelian randomization and polygenic risk score analysis in humans. This casts doubt on whether they are likely to represent effective drug targets for cognitive impairment in human APOE4 carriers.

Funder: Government Department of Business, Funder: Energy and Industrial Strategy (BEIS), Funder: Vice-Chancellor Fellowship from the University of Bristol, Funder: Shanghai Thousand Talents Program, Funder: Academy of Medical Sciences (AMS) Springboard Award, Funder: BBSRC Innovation fellowship, Funder: NIHR Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol, BACKGROUND: This study was to systematically test whether previously reported risk factors for chronic kidney disease (CKD) are causally related to CKD in European and East Asian ancestries using Mendelian randomization. METHODS: A total of 45 risk factors with genetic data in European ancestry and 17 risk factors in East Asian participants were identified as exposures from PubMed. We defined the CKD by clinical diagnosis or by estimated glomerular filtration rate of 25 kg/m2. CONCLUSIONS: Eight cardiometabolic risk factors showed causal effects on CKD in Europeans and three of them showed causality in East Asians, providing insights into the design of future interventions to reduce the burden of CKD.

ImportanceThe long-term effects of COVID-19 on the incidence of vascular diseases are unclear.ObjectiveTo quantify the association between time since diagnosis of COVID-19 and vascular disease, overall and by age, sex, ethnicity, and pre-existing disease.DesignCohort study based on population-wide linked electronic health records, with follow up from January 1st to December 7th 2020.Setting and participantsAdults registered with an NHS general practice in England or Wales and alive on January 1st 2020.ExposuresTime since diagnosis of COVID-19 (categorised as 0-6 days, 1-2 weeks, 3-4, 5-8, 9-12, 13-26 and 27-49 weeks since diagnosis), with and without hospitalisation within 28 days of diagnosis.Main outcomes and measuresPrimary outcomes were arterial thromboses (mainly acute myocardial infarction and ischaemic stroke) and venous thromboembolic events (VTE, mainly pulmonary embolism and lower limb deep vein thrombosis). We also studied other vascular events (transient ischaemic attack, haemorrhagic stroke, heart failure and angina). Hazard ratios were adjusted for demographic characteristics, previous disease diagnoses, comorbidities and medications.ResultsAmong 48 million adults, 130,930 were and 1,315,471 were not hospitalised within 28 days of COVID-19. In England, there were 259,742 first arterial thromboses and 60,066 first VTE during 41.6 million person-years follow-up. Adjusted hazard ratios (aHRs) for first arterial thrombosis compared with no COVID-19 declined rapidly from 21.7 (95% CI 21.0-22.4) to 3.87 (3.58-4.19) in weeks 1 and 2 after COVID-19, 2.80 (2.61-3.01) during weeks 3-4 then to 1.34 (1.21-1.48) during weeks 27-49. aHRs for first VTE declined from 33.2 (31.3-35.2) and 8.52 (7.59-9.58) in weeks 1 and 2 to 7.95 (7.28-8.68) and 4.26 (3.86-4.69) during weeks 3-4 and 5-8, then 2.20 (1.99-2.44) and 1.80 (1.50-2.17) during weeks 13-26 and 27-49 respectively. aHRs were higher, for longer after diagnosis, after hospitalised than non-hospitalised COVID-19. aHRs were also higher among people of Black and Asian than White ethnicity and among people without than with a previous event. Across the whole population estimated increases in risk of arterial thromboses and VTEs were 2.5% and 0.6% respectively 49 weeks after COVID-19, corresponding to 7,197 and 3,517 additional events respectively after 1.4 million COVID-19 diagnoses.Conclusions and RelevanceHigh rates of vascular disease early after COVID-19 diagnosis decline more rapidly for arterial thromboses than VTEs but rates remain elevated up to 49 weeks after COVID_19. These results support continued policies to avoid COVID-19 infection with effective COVID-19 vaccines and use of secondary preventive agents in high-risk patients.Key pointsQuestionIs COVID-19 associated with higher long-term incidence of vascular diseases?FindingsIn this cohort study of 48 million adults in England and Wales, COVID-19 was associated with higher incidence, that declined with time since diagnosis, of both arterial thromboses [week 1: adjusted HR [aHR] 21.7 (95% CI 21.0-22.4) weeks 27-49: aHR 1.34 (1.21-1.48)] and venous thromboembolism [week 1: aHR 33.2 (31.3-35.2), weeks 27–49 1.80 (1.50-2.17)]. aHRs were higher, for longer, after hospitalised than non-hospitalised COVID-19. The estimated excess number of arterial thromboses and venous thromboembolisms was 10,500.MeaningAvoidance of COVID-19 infection through vaccination, and use of secondary preventive agents after infection in high-risk patients, may reduce post-COVID-19 acute vascular diseases.

2AbstractBackgroundThere is some evidence that circulating blood lipids play a role in the development of Alzheimer’s disease (AD) and dementia. These modifiable risk factors could be targeted by existing lipid-regulating agents, including statins, for dementia prevention. Here, we test the association between lipid-regulating agents and incidence of dementia and related conditions in the Clinical Practice Research Datalink (CPRD), an United Kingdom-based electronic health record database.MethodsA retrospective cohort study was performed using routinely collected CPRD data (January 1995 and March 2016). Multivariable Cox proportional hazard models, allowing for a time-varying treatment indicator, were used to estimate the association between seven lipid-regulating drug classes (vs. no drug) and five dementia outcomes (all-cause, vascular and other dementias, and probable and possible Alzheimer’s disease).ResultsWe analyzed 1,684,564 participants with a total follow-up of 10,835,685 patient-years (median: 5.9 years (IQR:2.7-9.7)). We found little evidence that lipid-regulating agents were associated with incidence of Alzheimer’s disease (probable HR:0.98, 95%CI:0.94-1.01; possible HR:0.97, 95%CI:0.93-1.01), but there was evidence of an increased risk of all-cause (HR:1.17, 95%CI:1.14-1.19), vascular (HR:1.81, 95%CI:1.73-1.89) and other dementias (HR:1.19, 95%CI:1.15-1.24). Evidence from a number of control outcomes indicated the presence of substantial residual confounding by indication (ischaemic heart disease HR: 1.62, 95%CI: 1.59-1.64; backpain HR: 1.04, 95%CI: 1.03-1.05; and Type 2 diabetes HR: 1.50, 95%CI: 1.48-1.51).ConclusionLipid-regulating agents were not associated with reduced Alzheimer’s disease risk. There was some evidence of an increased the risk of all-cause, vascular and other dementias, likely due to residual confounding by indication.3Key messagesA large cohort of patients from the Clinical Practice Research Datalink (CPRD) electronic health record database was assembled to examine the association of lipid-regulating agents, such as statins, with dementia outcomes.There was little evidence that lipid-regulating agents were associated with Alzheimer’s disease, but there was some evidence for a harmful association with all-cause, vascular and other dementias. In all cases, the estimated associations were driven by the any statin subgroup, which comprised most participants in our cohort.Evidence from the control outcome analyses indicated strong residual confounding by indication, mostly likely related to vascular factors.

SummaryMendelian randomization (MR) studies carried out among patients with a particular health condition should establish the genetic instrument influences the exposure in that subgroup, however this is normally investigated in the general population. Here, we investigated whether the genetic associations of four cis-acting C-reactive protein (CRP) variants differed between participants with and without three cardiometabolic conditions: obesity, type 2 diabetes, and cardiovascular disease. Associations of cis-genetic variants with CRP differed between obese and non-obese individuals. A multivariable analysis suggested strong independent associations of the gene-by-body mass index (BMI) interaction on CRP (P−8 for the CRP variants). Applying MR, we observed strong causal effect of BMI on CRP (P=2.14×10−65). In summary, our study indicates that genetic associations with CRP differ across disease sub-groups, with evidence to suggest that BMI is an effect modifier. MR studies of disease progression should report on the genetic instrument-exposure association in the disease subgroup under investigation.

ObjectiveEvaluate antithrombotic (AT) use in individuals with atrial fibrillation (AF) and high stroke risk (CHA2DS2-VASc score>=2) and investigate whether pre-existing AT use may improve COVID-19 outcomes.MethodsIndividuals with AF and a CHA2DS2-VASc score>=2 on January 1st 2020 were identified using pseudonymised, linked electronic health records for 56 million people in England and followed-up until May 1st 2021. Factors associated with pre-existing AT use were analysed using logistic regression. Differences in COVID-19 related hospitalisation and death were analysed using logistic and Cox regression for individuals exposed to pre-existing AT use vs no AT use, anticoagulants (AC) vs antiplatelets (AP) and direct oral anticoagulants (DOACs) vs warfarin.ResultsFrom 972,971 individuals with AF and a CHA2DS2-VASc score>=2, 88.0% (n=856,336) had pre-existing AT use, 3.8% (n=37,418) had a COVID-19 related hospitalisation and 2.2% (n=21,116) died. Factors associated with no AT use included comorbidities that may contraindicate AT use (liver disease and history of falls) and demographics (socioeconomic status and ethnicity). Pre-existing AT use was associated with lower odds of death (OR=0.92 [0.87-0.96 at 95% CI]), but higher odds of hospitalisation OR=1.20 [1.15-1.26 at 95% CI]). The same pattern was observed for AC vs AP (death (OR=0.93 [0.87-0.98]), hospitalisation (OR=1.17 [1.11-1.24])) but not for DOACs vs warfarin (death (OR=1.00 [0.95-1.05]), hospitalisation (OR=0.86 [0.82-0.89]).ConclusionsPre-existing AT use may offer marginal protection against COVID-19 death, with AC offering more protection than AP. Although this association may not be causal, it provides further incentive to improve AT coverage for eligible individuals with AF.KEY QUESTIONSWhat is already known about this subject?Anticoagulants (AC), a sub-class of antithrombotics (AT), reduce the risk of stroke and are recommended for individuals with atrial fibrillation (AF) and at high risk of stroke (CHA2DS2-VASc score>=2, National Institute for Health and Care Excellence threshold). However, previous evaluations suggest that up to one third of these individuals may not be taking AC. Over estimation of bleeding and fall risk in elderly patients have been identified as potential factors in this under medicating.In response to the COVID-19 pandemic, several observational studies have observed correlations between pre-existing AT use, particularly anticoagulants (AC), and lower risk of severe COVID-19 outcomes such as hospitalisation and death. However, these correlations are inconsistent across studies and have not compared all major sub-types of AT in one study.What does this study add?This study uses datasets covering primary care, secondary care, pharmacy dispensing, death registrations, multiple COVID-19 diagnoses routes and vaccination records for 56 million people in England and is the largest scale evaluation of AT use to date. This provides the statistical power to robustly analyse targeted sub-types of AT and control for a wide range of potential confounders. All code developed for the study is opensource and an updated nationwide evaluation can be rapidly created for future time points.In 972,971 individuals with AF and a CHA2DS2-VASc score>=2, we observed 88.0% (n=856,336) with pre-existing AT use which was associated with marginal protection against COVID-19 death (OR=0.92 [0.87-0.96 at 95% CI]).How might this impact on clinical practice?These findings can help shape global AT medication policy and provide population-scale, observational analysis results alongside gold-standard randomised control trials to help assess whether a potential beneficial effect of pre-existing AT use on COVID-19 death alters risk to benefit assessments in AT prescribing decisions.

BackgroundThromboses in unusual locations after the COVID-19 vaccine ChAdOx1-S have been reported. Better understanding of population-level thrombotic risks after COVID-19 vaccination is needed.MethodsWe analysed linked electronic health records from adults living in England, from 8th December 2020 to 18th March 2021. We estimated incidence rates and hazard ratios (HRs) for major arterial, venous and thrombocytopenic outcomes 1-28 and >28 days after first vaccination dose for ChAdOx1-S and BNT162b2 vaccines. Analyses were performed separately for ages ResultsOf 46,162,942 adults, 21,193,814 (46%) had their first vaccination during follow-up. Adjusted HRs 1-28 days after ChAdOx1-S, compared with unvaccinated rates, at ages Rates of intracranial venous thrombosis (ICVT) and thrombocytopenia in adults aged ConclusionsIncreases in ICVT and thrombocytopenia after ChAdOx1-S vaccination in adults aged

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

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Supplemental Digital Content is available in the text., Background: Lipoprotein-related traits have been consistently identified as risk factors for atherosclerotic cardiovascular disease, largely on the basis of studies of coronary artery disease (CAD). The relative contributions of specific lipoproteins to the risk of peripheral artery disease (PAD) have not been well defined. We leveraged large-scale genetic association data to investigate the effects of circulating lipoprotein-related traits on PAD risk. Methods: Genome-wide association study summary statistics for circulating lipoprotein-related traits were used in the mendelian randomization bayesian model averaging framework to prioritize the most likely causal major lipoprotein and subfraction risk factors for PAD and CAD. Mendelian randomization was used to estimate the effect of apolipoprotein B (ApoB) lowering on PAD risk using gene regions proxying lipid-lowering drug targets. Genes relevant to prioritized lipoprotein subfractions were identified with transcriptome-wide association studies. Results: ApoB was identified as the most likely causal lipoprotein-related risk factor for both PAD (marginal inclusion probability, 0.86; P=0.003) and CAD (marginal inclusion probability, 0.92; P=0.005). Genetic proxies for ApoB-lowering medications were associated with reduced risk of both PAD (odds ratio,0.87 per 1-SD decrease in ApoB [95% CI, 0.84–0.91]; P=9×10−10) and CAD (odds ratio,0.66 [95% CI, 0.63–0.69]; P=4×10−73), with a stronger predicted effect of ApoB lowering on CAD (ratio of effects, 3.09 [95% CI, 2.29–4.60]; P

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BackgroundEpidemiological studies have reported conflicting findings on the potential adverse effects of long-term antihypertensive medication use on cancer risk. Naturally occurring variation in genes encoding antihypertensive drug targets can be used as proxies for these targets to examine the effect of their long-term therapeutic inhibition on disease outcomes.MethodsSingle-nucleotide polymorphisms (SNPs) in ACE, ADRB1, and SLC12A3 associated (P < 5.0 x 10-8) with systolic blood pressure in genome-wide association studies (GWAS) were used to proxy inhibition of angiotensin-converting enzyme (ACE), β-1 adrenergic receptor (ADRB1), and sodium-chloride symporter (NCC), respectively. Summary genetic association estimates for these SNPs were obtained from GWAS consortia for the following cancers: breast (122,977 cases, 105,974 controls), colorectal (58,221 cases, 67,694 controls), lung (29,266 cases, 56,450 controls), and prostate (79,148 cases, 61,106 controls). Replication analyses were performed in the FinnGen consortium (1,573 colorectal cancer cases, 120,006 controls). Inverse-variance weighted random- effects models were used to examine associations between genetically-proxied inhibition of these drug targets and risk of cancer. Multivariable Mendelian randomization and colocalisation analyses were employed to examine robustness of findings to violations of Mendelian randomization assumptions.ResultsGenetically-proxied ACE inhibition equivalent to a 1 mmHg reduction in systolic blood pressure was associated with increased odds of colorectal cancer (OR 1.13, 95% CI 1.06-1.22; P = 3.6 x 10-4). This finding was replicated in the FinnGen consortium (OR 1.40, 95% CI 1.02-1.92; P = 0.035). There was little evidence of association of genetically-proxied ACE inhibition with risk of breast cancer (OR 0.98, 95% CI 0.94-1.02, P = 0.35), lung cancer (OR 1.01, 95% CI 0.92-1.10; P = 0.93), or prostate cancer (OR 1.06, 95% CI 0.99-1.13; P = 0.08). Genetically-proxied inhibition of ADRB1 and NCC were not associated with risk of these cancers.ConclusionGenetically-proxied long-term ACE inhibition was associated with an increased risk of colorectal cancer, warranting comprehensive evaluation of the safety profiles of ACE inhibitors in clinical trials with adequate follow-up. There was little evidence to support associations across other drug target-cancer risk analyses, consistent with findings from short-term randomised controlled trials for these medications.

ObjectivesDescribe a new England-wide electronic health record (EHR) resource enabling whole population research on Covid-19 and cardiovascular disease whilst ensuring data security and privacy and maintaining public trust.DesignCohort comprising linked person-level records from national healthcare settings for the English population accessible within NHS Digital’s new Trusted Research Environment.SettingEHRs from primary care, hospital episodes, death registry, Covid-19 laboratory test results and community dispensing data, with further enrichment planned from specialist intensive care, cardiovascular and Covid-19 vaccination data.Participants54.4 million people alive on 1st January 2020 and registered with an NHS general practitioner in England.Main measures of interestConfirmed and suspected Covid-19 diagnoses, exemplar cardiovascular conditions (incident stroke or transient ischaemic attack (TIA) and incident myocardial infarction (MI)) and all-cause mortality between 1st January and 31st October 2020.ResultsThe linked cohort includes over 96% of the English population. By combining person-level data across national healthcare settings, data on age, sex and ethnicity are complete for over 95% of the population. Among 53.2M people with no prior diagnosis of stroke/TIA, 98,721 had an incident stroke/TIA, of which 30% were recorded only in primary care and 4% only in death registry records. Among 53.1M people with no prior history of MI, 62,966 had an incident MI, of which 8% were recorded only in primary care and 12% only in death records. A total of 959,067 people had a confirmed or suspected Covid-19 diagnosis (714,162 in primary care data, 126,349 in hospital admission records, 776,503 in Covid-19 laboratory test data and 48,433 participants in death registry records). While 58% of these were recorded in both primary care and Covid-19 laboratory test data, 15% and 18% respectively were recorded in only one.ConclusionsThis population-wide resource demonstrates the importance of linking person-level data across health settings to maximize completeness of key characteristics and to ascertain cardiovascular events and Covid-19 diagnoses. Although established initially to support research on Covid-19 and cardiovascular disease to benefit clinical care and public health and to inform health care policy, it can broaden further to enable a very wide range of research.

Drugs whose targets have genetic evidence to support efficacy and safety are more likely to be approved after clinical development. In this paper, we provide an overview of how natural sequence variation in the genes that encode drug targets can be used in Mendelian randomization analyses to offer insight into mechanism-based efficacy and adverse effects. Large databases of summary level genetic association data are increasingly available and can be leveraged to identify and validate variants that serve as proxies for drug target perturbation. As with all empirical research, Mendelian randomization has limitations including genetic confounding, its consideration of lifelong effects, and issues related to heterogeneity across different tissues and populations. When appropriately applied, Mendelian randomization provides a useful empirical framework for using population level data to improve the success rates of the drug development pipeline.

BackgroundCirculating lipid and lipoprotein levels have consistently been identified as risk factors for atherosclerotic cardiovascular disease (ASCVD), largely on the basis of studies focused on coronary artery disease (CAD). The relative contributions of specific lipoproteins to risk of peripheral artery disease (PAD) have not been well-defined. Here, we leveraged large scale genetic association data to identify genetic proxies for circulating lipoprotein-related traits, and employed Mendelian randomization analyses to investigate their effects on PAD risk.MethodsGenome-wide association study summary statistics for PAD (Veterans Affairs Million Veteran Program, 31,307 cases) and CAD (CARDIoGRAMplusC4D, 60,801 cases) were used in the Mendelian Randomization Bayesian model averaging (MR-BMA) framework to prioritize the most likely causal major lipoprotein and subfraction risk factors for PAD and CAD. Mendelian randomization was used to estimate the effect of apolipoprotein B lowering on PAD risk using gene regions that proxy potential lipid-lowering drug targets. Transcriptome-wide association studies were performed to identify genes relevant to circulating levels of prioritized lipoprotein subfractions.ResultsApoB was identified as the most likely causal lipoprotein-related risk factor for both PAD (marginal inclusion probability 0.86, p = 0.003) and CAD (marginal inclusion probability 0.92, p = 0.005). Genetic proxies for ApoB-lowering medications were associated with reduced risk of both PAD (OR 0.87 per 1 standard deviation decrease in ApoB, 95% CI 0.84 to 0.91, p = 9 × 10−10) and CAD (OR 0.66, 95% CI 0.63 to 0.69, p = 4 × 10−73), with a stronger predicted effect of ApoB-lowering on CAD (ratio of ORs 1.33, 95% CI 1.25 to 1.42, p = 9 × 10−19). Among ApoB-containing subfractions, extra-small VLDL particle concentration (XS.VLDL.P) was identified as the most likely subfraction associated with PAD risk (marginal inclusion probability 0.91, p = 2.3 × 10−4), while large LDL particle concentration (L.LDL.P) was the most likely subfraction associated with CAD risk (marginal inclusion probability 0.95, p = 0.011). Genes associated with XS.VLDL.P and L.LDL.P included canonical ApoB-pathway components, although gene-specific effects varied across the lipoprotein subfractions.ConclusionApoB was prioritized as the major lipoprotein fraction causally responsible for both PAD and CAD risk. However, diverse effects of ApoB-lowering drug targets and ApoB-containing lipoprotein subfractions on ASCVD, and distinct subfraction-associated genes suggest possible biologic differences in the role of lipoproteins in the pathogenesis of PAD and CAD.

Drugs whose targets have genetic evidence to support efficacy and safety are more likely to be approved after clinical development. In this paper, we provide an overview of how natural sequence variation in the genes that encode drug targets can be used in Mendelian randomization analyses to offer insight into mechanism-based efficacy and adverse effects. Large databases of summary level genetic association data are increasingly available and can be leveraged to identify and validate variants that serve as proxies for drug target perturbation. As with all empirical research, Mendelian randomization has limitations including genetic confounding, its consideration of lifelong effects, and issues related to heterogeneity across different tissues and populations. When appropriately applied, Mendelian randomization provides a useful empirical framework for using population level data to improve the success rates of the drug development pipeline.

Supplemental Digital Content is available in the text., Observational studies have shown an association between hypertension and atrial fibrillation (AF). Aggressive blood pressure management in patients with known AF reduces overall arrhythmia burden, but it remains unclear whether hypertension is causative for AF. To address this question, this study explored the relationship between genetic predictors of blood pressure and risk of AF. We secondarily explored the relationship between genetically proxied use of antihypertensive drugs and risk of AF. Two-sample Mendelian randomization was performed using an inverse-variance weighted meta-analysis with weighted median Mendelian randomization and Egger intercept tests performed as sensitivity analyses. Summary statistics for systolic blood pressure, diastolic blood pressure, and pulse pressure were obtained from the International Consortium of Blood Pressure and the UK Biobank discovery analysis and AF from the 2018 Atrial Fibrillation Genetics Consortium multiethnic genome-wide association studies. Increases in genetically proxied systolic blood pressure, diastolic blood pressure, or pulse pressure by 10 mm Hg were associated with increased odds of AF (systolic blood pressure: odds ratio [OR], 1.17 [95% CI, 1.11–1.22]; P=1×10−11; diastolic blood pressure: OR, 1.25 [95% CI, 1.16–1.35]; P=3×10−8; pulse pressure: OR, 1.1 [95% CI, 1.0–1.2]; P=0.05). Decreases in systolic blood pressure by 10 mm Hg estimated by genetic proxies of antihypertensive medications showed calcium channel blockers (OR, 0.66 [95% CI, 0.57–0.76]; P=8×10−9) and β-blockers (OR, 0.61 [95% CI, 0.46–0.81]; P=6×10−4) decreased the risk of AF. Blood pressure–increasing genetic variants were associated with increased risk of AF, consistent with a causal relationship between blood pressure and AF. These data support the concept that blood pressure reduction with calcium channel blockade or β-blockade could reduce the risk of AF.

BACKGROUNDThe chronic kidney disease (CKD) public health burden is substantial and has not declined as expected with current interventions on disease treatments. A large number of clinical, biological, and behavioural risk factors have been associated with CKD. However, it is unclear which of them are causal.OBJECTIVETo systematically test whether previously reported risk factors for CKD are causally related to the disease in European and East Asian ancestries.DESIGNTwo-sample Mendelian randomization (MR) and non-linear MR analyses.PARTICIPANTS53,703 CKD cases and 960,624 controls of European ancestry from CKDGen, UK Biobank and HUNT, and 13,480 CKD cases and 238,118 controls of East Asian ancestry from Biobank Japan, China Kadoorie Biobank and Japan-Kidney-Biobank/ToMMo.MEASURESSystematic literature mining of PubMed studies identified 45 clinical risk factors and biomarkers with robustly associated genetic variants, including phenotypes related to blood pressure, diabetes, glucose, insulin, lipids, obesity, smoking, sleep disorders, nephrolithiasis, uric acid, coronary artery disease, bone mineral density, homocysteine, C-reactive protein, micro-nutrients and thyroid function, which were selected as exposures. The outcome was CKD (defined by clinical diagnosis or by estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73m2).RESULTSEight risk factors showed evidence of causal effects on CKD in European ancestry, including body mass index (BMI), hypertension, systolic blood pressure, high density lipoprotein cholesterol, apolipoprotein A-I, lipoprotein A, type 2 diabetes (T2D) and nephrolithiasis. In East Asian ancestry, BMI, T2D and nephrolithiasis showed evidence of causal effects on CKD. Hypertension showed reliable evidence of a strong causal effect on CKD in Europeans but in contrast appeared to show a null effect in East Asians, suggesting the possibility of different causal risk factors in Europeans and East Asians. Although liability to T2D showed consistent effects on CKD, the effect of glycemic traits on CKD was weak, suggesting T2D may have glucose-independent mechanisms to influence CKD. Nonlinear MR indicated a threshold relationship between genetically predicted BMI and CKD, with increased risk at BMI above 25 kg/m2.LIMITATIONDue to the unbalanced distribution of data between ancestries, we could only test 17 of the 45 risk factors in East Asian participants.CONCLUSIONSEight CKD-associated risk factors showed evidence of causal effects on the disease in over 1.2 million European and East Asian ancestries. These risk factors were predominantly related to cardio-metabolic health, which supports the shared causal link between cardio-metabolic health and kidney function. This study provides evidence of potential intervention targets for primary prevention of CKD, which could help reduce the global burden of CKD and its cardio-metabolic co-morbidities.Research in contextEvidence before this studyChronic kidney disease (CKD) has a major effect on global health, both as a direct cause of morbidity and mortality, and as an important complication for cardio-metabolic diseases. However, even with the existing interventions, the burden of CKD has not declined as expected over the last 30 years. Existing epidemiological studies of CKD have mainly focused on disease treatment in patients from specific populations and estimated association rather than causality. A systematic assessment of the causal determinants of CKD in different populations is urgently needed, to help promote a shift from treatment of CKD patients to prevention of the disease in high-risk groups. The use of genetic data and the latest Mendelian randomization (MR) methodologies offers a cost-effective way to evaluate the potential intervention targets for prevention of CKD in high-risk groups.Added value of this studyIn this study, we systematically constructed a causal atlas of 45 risk factors on CKD in European and East Asian ancestries using MR. To maximise power of these analyses and accuracy of the findings, we collected and harmonised CKD genetic association data from six large-scale biobanks (in over 1.1 million Europeans and 250,000 East Asians). By applying a comprehensive MR framework, including linear two-sample MR, bidirectional MR, multivariable MR and non-linear MR approaches, we identified eight risk factors with reliable evidence of causal effects on CKD in European ancestry studies, including body mass index (BMI), hypertension, systolic blood pressure, high density lipoprotein cholesterol, apolipoprotein A-I, lipoprotein A, type 2 diabetes (T2D) and nephrolithiasis. In East Asian studies, BMI, T2D and nephrolithiasis also showed causal effects on CKD. Among other factors, hypertension showed reliable evidence of a strong causal effect on CKD in Europeans but in contrast appeared to show a null effect in East Asians. This MR finding together with previous literature evidence opens up the possibility that hypertension could play different causal roles on CKD across ancestries. For diabetes and glycemic phenotypes, our MR and sensitivity analyses suggested the causal role of liability of T2D on CKD but suggested weak effects of glycemic phenotypes on CKD. This aligns with the recent trial of SGLT2 inhibitors on kidney disease, which implies T2D may have glucose-independent mechanisms to influence CKD. For lipids phenotypes, we found good evidence to support the role of high-density lipoprotein cholesterol on CKD and further suggested the effects of two lipids targets: circulating CETP level and lipoprotein A concentration. For body weight, our study quantified a threshold relationship between BMI and CKD, with increased risk at BMI above 25 kg/m2. The causal relationship between nephrolithiasis and CKD were reported in previous studies, but our study confirmed the causal links between the two for the first time.Implication of all the available evidenceThis study makes a significant advance in comprehensively prioritising intervention targets for CKD in over 1.2 million participants. Our study presents causal evidence from both European and East Asian population samples, widening the generalisability of the causal atlas. Importantly, the prioritised risk factors are predominantly related to cardio-metabolic health, which supports the shared causal link between cardio-metabolic health and kidney function. Clinically, the high-quality evidence from this study highlights the value of exploring these causal factors in the general population and prioritizes drug targets and life-style interventions for CKD primary prevention, which could help reduce the global burden of CKD and its cardio-metabolic co-morbidities.

ImportanceObservational studies have shown an association between hypertension and atrial fibrillation (AF). Aggressive blood pressure management in patients with known AF reduces overall arrhythmia burden, but it remains unclear whether hypertension is causative for AF.ObjectiveThe primary objective of this study was to investigate the relationship between blood pressure and risk of AF using genetic proxies for blood pressure within a Mendelian randomization (MR) framework. We secondarily explored the relationship between genetically proxied use of anti-hypertensive drugs and risk of AF.DesignTwo-sample MR was performed using an inverse-variance weighted meta-analysis with weighted median MR and Egger intercept tests performed as sensitivity analyses. Genetic proxies for the anti-hypertensive drug classes were used to investigate the impact of these therapies on the risk of AF.SettingInternational Consortium of Blood Pressure, UK Biobank and Atrial Fibrillation Genetics Consortium.ParticipantsSummary statistics for systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP) were obtained from the International Consortium of Blood Pressure and the UK Biobank discovery analysis (>750,000 individuals of European ancestry).Summary statistics for AF were obtained from the 2018 Atrial Fibrillation Genetics Consortium multi-ethnic GWAS (>65,000 AF cases and >522,000 referents).ExposureGenetically predicted SBP, DBP and PP as quantified by risk scores.Main OutcomeOdds ratio for AF per 10 mmHg increase in genetically proxied blood pressure.ResultsTen mmHg increases in genetically proxied SBP, DBP or PP were associated with increased odds of AF (SBP: OR 1.17, 95% CI 1.11-1.22, p=1⨯ 10−11; DBP: OR 1.25, 95% CI 1.16-1.35, p=3⨯ 10−8; PP: OR 1.1, 95% CI 1.0-1.2, p=0.05). Ten mmHg decreases in SBP estimated by genetic proxies of anti-hypertensive medications showed calcium channel blockers (OR 0.66, 95% CI 0.57-0.76, p=8⨯ 10−9) and beta-blockers (OR 0.61, 95% CI 0.46-0.81, p=6⨯ 10−4) decreased the risk of AF.Conclusions and RelevanceBlood pressure-increasing genetic variants were associated with increased risk of AF, consistent with a causal relationship between blood pressure and AF. These data support the concept that blood pressure reduction through pharmacologic intervention, and specifically calcium channel blockade or beta blockade could reduce the risk of AF.

IntroductionGenome-wide association studies (GWASs) often adjust for covariates, correct for medication use, or select on medication users. If these summary statistics are used in two-sample Mendelian randomization analyses, estimates may be biased. We used simulations to investigate how GWAS adjustment, correction and selection affects these estimates and performed an analysis in UK Biobank to provide an empirical example.MethodsWe simulated six GWASs: no adjustment for a covariate, correction for medication use, or selection on medication users; adjustment only; selection only; correction only; both adjustment and selection; and both adjustment and correction. We then ran two-sample Mendelian randomization analyses using these GWASs to evaluate bias. We also performed equivalent GWASs using empirical data from 306,560 participants in UK Biobank with systolic blood pressure as the exposure and body mass index as the covariate and ran two-sample Mendelian randomization with coronary heart disease as the outcome.ResultsThe simulation showed that estimates from GWASs with selection can produce biased two-sample Mendelian randomization estimates. Yet, we observed relatively little difference between empirical estimates of the effect of systolic blood pressure on coronary artery disease across the six scenarios.ConclusionsGiven the potential for bias from using GWASs with selection on Mendelian randomization estimates demonstrated in our simulation, careful consideration before using this approach is warranted. However, based on our empirical results, using adjusted, corrected or selected GWASs is unlikely to make a large difference to two-sample Mendelian randomization estimates in practice.

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Background: Drugs for dementia have been available in England from 1997. Since their launch, there have been several changes to national guidelines and initiatives that may have influenced prescribing. These include changes in National Institute for health and Care Excellence (NICE) guidance; several government dementia strategies; the addition of dementia to the Quality and Outcomes Framework (QOF); and the expiry of drug patents. Despite this, there has been little research into the effect of these events on prescribing. This paper examines prescribing trends in England using data from the UK Clinical Practice Research Datalink since the launch of drugs for dementia up to 1st January 2016. Methods: We considered the monthly proportion of patients eligible for treatment, with a diagnosis of probable Alzheimer’s disease, receiving their first prescription for each drug class – namely acetylcholinesterase (AChE) inhibitors (donepezil, rivastigmine, galantamine) and N-Methyl-D-aspartate (NMDA) receptor antagonists (memantine). Trend analysis using joinpoint models was then applied to identify up to two trend changes per treatment of interest. Results: The overall trend was for increasing prescriptions in each drug class over the period they were studied. This was indicated by the average monthly percentage change, which was 6.0% (95% CI: -6.4 to 19.9; June 1997 to December 2015) for AChE inhibitors and 15.4% (95% CI: -77.1 to 480.9; January 2003 to December 2015) for NMDA receptor antagonists. Prescriptions of AChE inhibitors increased at the end of 2012, probably in response to the patent expiry of these drugs earlier that year. The Prime Minister’s Dementia Challenge launched in May 2012 may also have contributed to the observed increase. However, neither this strategy nor patent expiry appeared to influence prescriptions of NMDA receptor antagonists. Instead trend changes in this drug class were driven by NICE guidance released in 2011 that allowed access to these drugs outside of clinical trials. Conclusions: Dementia drug prescribing does not always respond to factors such as regulatory guidance, recommendations or patent expiry and, when it does, not necessarily in a predictable way. This suggests that improved communication with clinicians may be needed to improve the cost-effective use of drugs for dementia.

Identification of unintended drug effects, specifically drug repurposing opportunities and adverse drug events, maximizes the benefit of a drug and protects the health of patients. However, current observational research methods are subject to several biases. These include confounding by indication, reverse causality, and missing data. We propose that Mendelian randomization (MR) offers a novel approach for the prediction of unintended drug effects. In particular, we advocate the synthesis of evidence from this method and other approaches, in the spirit of triangulation, to improve causal inferences concerning drug effects. MR overcomes some of the limitations associated with the existing methods in this field. Furthermore, it can be applied either pre- or post-approval of the drug and could therefore prevent the potentially harmful exposure of patients in clinical trials and beyond. The potential of MR as a pharmacovigilance and drug repurposing tool is yet to be realized and could both help prevent adverse drug events and identify novel indications for existing drugs in the future.

Mendelian randomization (MR) estimates the causal effect of exposures on outcomes by exploiting genetic variation to address confounding and reverse causation. This method has a broad range of applications, including investigating risk factors and appraising potential targets for intervention. MR-Base has become established as a freely accessible, online platform, which combines a database of complete genome-wide association study results with an interface for performing Mendelian randomization and sensitivity analyses. This allows the user to explore millions of potentially causal associations. MR-Base is available as a web application or as an R package. The technical aspects of the tool have previously been documented in the literature. The present article is complementary to this as it focuses on the applied aspects. Specifically, we describe how MR-Base can be used in several ways, including to perform novel causal analyses, replicate results and enable transparency, amongst others. We also present three use cases, which demonstrate important applications of Mendelian randomization and highlight the benefits of using MR-Base for these types of analyses.

BackgroundInstrumental variable analysis, for example with physicians’ prescribing preferences as an instrument for medications issued in primary care, is an increasingly popular method in the field of pharmacoepidemiology. Existing power calculators for studies using instrumental variable analysis, such as Mendelian randomisation power calculators, do not allow for the structure of research questions in this field. This is because the analysis in pharmacoepidemiology will typically have stronger instruments and detect larger causal effects than in other fields. Consequently, there is a need for dedicated power calculators for pharmacoepidemiological research.Methods and resultsThe formula for calculating the power of a study using instrumental variable analysis in the context of pharmacoepidemiology is derived before being validated by a simulation study. The formula is applicable for studies using a single binary instrument to analyse the causal effect of a binary exposure on a continuous outcome. A web application is provided for the implementation of the formula by others.ConclusionsThe statistical power of instrumental variable analysis in pharmacoepidemiological studies to detect a clinically meaningful treatment effect is an important consideration. Research questions in this field have distinct structures that must be accounted for when calculating power.FUNDING STATEMENTThis work was supported by the Perros Trust and the Integrative Epidemiology Unit. The Integrative Epidemiology Unit is supported by the Medical Research Council and the University of Bristol [grant number MC_UU_12013/9]. Stephen Burgess is supported by a post-doctoral fellowship from the Wellcome Trust [100114].Key MessagesResearch questions using instrumental variable analysis in pharmacoepidemiology have distinct structures that have previously not been catered for by instrumental variable analysis power calculators.Power can be calculated for studies using a single binary instrument to analyse the causal effect of a binary exposure on a continuous outcome in the context of pharmacoepidemiology using the presented formula and online power calculator.The use of this power calculator will allow investigators to determine whether a pharmacoepidemiology study is likely to detect clinically meaningful treatment effects prior to the study’s commencement.

Introduction There is evidence that hypertension in midlife can increase the risk of Alzheimer's disease and vascular dementia in late life. In addition, some treatments for hypertension have been proposed to have cognitive benefits, independent of their effect on hypertension. Consequently, there is potential to repurpose treatments for hypertension for dementia. This study systematically assessed ten antihypertensive drug classes for this purpose, using data on over 940,000 patients from the UK Clinical Practice Research Datalink. Methods Treatments for hypertension were assessed in an instrumental variable (IV) analysis to address potential confounding by indication. Physicians’ prescribing preference was used as a categorical instrument, defined by the physicians’ last seven prescriptions, and the analysis was adjusted for prescription year. A multivariable logistic regression analysis was also conducted to compare biases. Beta-adrenoceptor blockers were used as the control drug throughout. Results Treatments for hypertension had little effect reducing the risk of Alzheimer's disease, vascular dementia, and other dementias. These results differ from existing studies considering specific antihypertensive drug classes. For example, we estimated angiotensin converting enzyme inhibitors to result in 2.2 per 1000 (95% CI 8.1–3.6) fewer cases of Alzheimer's disease among those treated–a much smaller reduction than previously reported. Comparison of our IV and logistic regression analyses suggests that this is likely due to confounding in non-IV studies. Conclusions This study is the first to systematically assess all the major antihypertensive drug classes. The contradiction with previous studies suggests that continued research into the repurposing of these treatments for dementia is required. It also highlights the need for further research into the biological mechanisms that link hypertension and dementia so that we can better understand the confounding in such analyses.

Introduction Current treatments for Alzheimer's and other neurodegenerative diseases have only limited effectiveness meaning that there is an urgent need for new medications that could influence disease incidence and progression. We will investigate the potential of a selection of commonly prescribed drugs, as a more efficient and cost-effective method of identifying new drugs for the prevention or treatment of Alzheimer's disease, non-Alzheimer's disease dementias, Parkinson's disease and amyotrophic lateral sclerosis. Our research will focus on drugs used for the treatment of hypertension, hypercholesterolaemia and type 2 diabetes, all of which have previously been identified as potentially cerebroprotective and have variable levels of preclinical evidence that suggest they may have beneficial effects for various aspects of dementia pathology.Methods and analysis We will conduct a hypothesis testing observational cohort study using data from the Clinical Practice Research Datalink (CPRD). Our analysis will consider four statistical methods, which have different approaches for modelling confounding. These are multivariable adjusted Cox regression; propensity matched regression; instrumental variable analysis and marginal structural models. We will also use an intention-to-treat analysis, whereby we will define all exposures based on the first prescription observed in the database so that the target parameter is comparable to that estimated by a randomised controlled trial.Ethics and dissemination This protocol has been approved by the CPRD's Independent Scientific Advisory Committee (ISAC). We will publish the results of the study as open-access peer-reviewed publications and disseminate findings through national and international conferences as are appropriate.