Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways.

BACKGROUND: Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation. METHODS: We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particular where some of the effect of an exposure on the outcome may operate through an intermediate variable (a mediator). If instrumental variables for the exposure and mediator are available, direct and indirect effects of the exposure on the outcome can be estimated, for example using either a regression-based method or structural equation models. The direction of effect between the exposure and a possible mediator can also be assessed. Methods are illustrated in an applied example considering causal relationships between body mass index, C-reactive protein and uric acid. RESULTS: These estimators are consistent in the presence of unmeasured confounding if, in addition to the instrumental variable assumptions, the effects of both the exposure on the mediator and the mediator on the outcome are homogeneous across individuals and linear without interactions. Nevertheless, a simulation study demonstrates that even considerable heterogeneity in these effects does not lead to bias in the estimates. CONCLUSIONS: These methods can be used to estimate direct and indirect causal effects in a mediation setting, and have potential for the investigation of more complex networks between multiple interrelated exposures and disease outcomes

Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways

Background: Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation. Methods: We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particular where some of the effect of an exposure on the outcome may operate through an intermediate variable (a mediator). If instrumental variables for the exposure and mediator are available, direct and indirect effects of the exposure on the outcome can be estimated, for example using either a regression-based method or structural equation models. The direction of effect between the exposure and a possible mediator can also be assessed. Methods are illustrated in an applied example considering causal relationships between body mass index, C-reactive protein and uric acid. Results: These estimators are consistent in the presence of unmeasured confounding if, in addition to the instrumental variable assumptions, the effects of both the exposure on the mediator and the mediator on the outcome are homogeneous across individuals and linear without interactions. Nevertheless, a simulation study demonstrates that even considerable heterogeneity in these effects does not lead to bias in the estimates. Conclusions: These methods can be used to estimate direct and indirect causal effects in a mediation setting, and have potential for the investigation of more complex networks between multiple interrelated exposures and disease outcomes

Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors.

OBJECTIVE: Mendelian randomization is a popular technique for assessing and estimating the causal effects of risk factors. If genetic variants which are instrumental variables for a risk factor are shown to be additionally associated with a disease outcome, then the risk factor is a cause of the disease. However, in many cases, the instrumental variable assumptions are not plausible, or are in doubt. In this paper, we provide a theoretical classification of scenarios in which a causal conclusion is justified or not justified, and discuss the interpretation of causal effect estimates. RESULTS: A list of guidelines based on the 'Bradford Hill criteria' for judging the plausibility of a causal finding from an applied Mendelian randomization study is provided. We also give a framework for performing and interpreting investigations performed in the style of Mendelian randomization, but where the choice of genetic variants is statistically, rather than biologically motivated. Such analyses should not be assigned the same evidential weight as a Mendelian randomization investigation. CONCLUSION: We discuss the role of such investigations (in the style of Mendelian randomization), and what they add to our understanding of potential causal mechanisms. If the genetic variants are selected solely according to statistical criteria, and the biological roles of genetic variants are not investigated, this may be little more than what can be learned from a well-designed classical observational study.Stephen Burgess is supported by the Wellcome Trust (grant number 100114).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.jclinepi.2015.08.00

Leucocyte telomere length and risk of cardiovascular disease: systematic review and meta-analysis.

OBJECTIVE: To assess the association between leucocyte telomere length and risk of cardiovascular disease. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Studies published up to March 2014 identified through searches of Medline, Web of Science, and Embase. ELIGIBILITY CRITERIA: Prospective and retrospective studies that reported on associations between leucocyte telomere length and coronary heart disease (defined as non-fatal myocardial infarction, coronary heart disease death, or coronary revascularisation) or cerebrovascular disease (defined as non-fatal stroke or death from cerebrovascular disease) and were broadly representative of general populations--that is, they did not select cohort or control participants on the basis of pre-existing cardiovascular disease or diabetes. RESULTS: Twenty four studies involving 43,725 participants and 8400 patients with cardiovascular disease (5566 with coronary heart disease and 2834 with cerebrovascular disease) were found to be eligible. In a comparison of the shortest versus longest third of leucocyte telomere length, the pooled relative risk for coronary heart disease was 1.54 (95% confidence interval 1.30 to 1.83) in all studies, 1.40 (1.15 to 1.70) in prospective studies, and 1.80 (1.32 to 2.44) in retrospective studies. Heterogeneity between studies was moderate (I(2) = 64%, 41% to 77%, Phet<0.001) and was not significantly explained by mean age of participants (P = 0.23), the proportion of male participants (P = 0.45), or distinction between retrospective versus prospective studies (P = 0.32). Findings for coronary heart disease were similar in meta-analyses restricted to studies that adjusted for conventional vascular risk factors (relative risk 1.42, 95% confidence interval 1.17 to 1.73); studies with ≥ 200 cases (1.44, 1.20 to 1.74); studies with a high quality score (1.53, 1.22 to 1.92); and in analyses that corrected for publication bias (1.34, 1.12 to 1.60). The pooled relative risk for cerebrovascular disease was 1.42 (1.11 to 1.81), with no significant heterogeneity between studies (I(2) = 41%, 0% to 72%, Phet = 0.08). Shorter telomeres were not significantly associated with cerebrovascular disease risk in prospective studies (1.14, 0.85 to 1.54) or in studies with a high quality score (1.21, 0.83 to 1.76). CONCLUSION: Available observational data show an inverse association between leucocyte telomere length and risk of coronary heart disease independent of conventional vascular risk factors. The association with cerebrovascular disease is less certain

Lipoprotein(a) in Alzheimer, Atherosclerotic, Cerebrovascular, Thrombotic, and Valvular Disease: Mendelian Randomization Investigation.

Lipoprotein(a) (Lp[a]) is a circulating lipoprotein with proatherogenic, proinflammatory, and possibly prothrombotic properties. Circulating Lp(a) levels are largely genetically determined, in particular, by the LPA gene. As such, genetic variants at the LPA locus can serve as instrumental variables for investigating the clinical effects of circulating Lp(a) levels. Mendelian randomization (MR) studies have shown that elevated Lp(a) levels are associated with a higher risk of coronary artery disease1–3 and aortic valve stenosis.2–4 Evidence on the causal role of elevated Lp(a) levels for other atherosclerotic and specific valvular diseases is limited, although there are MR data supporting a positive association between genetically predicted Lp(a) levels and peripheral artery disease.2,3 Whether Lp(a) is causally related to thrombotic disease and cerebrovascular disease remains unclear.2,3,5 In this study, we used the UK Biobank cohort to perform an MR investigation into the causal effects of circulating Lp(a) levels on atherosclerotic, cerebrovascular, thrombotic, and valvular diseases. Because a recent MR study provided evidence of an inverse association of Lp(a) levels with Alzheimer disease,5 we additionally explored whether genetically predicted Lp(a) levels are associated with Alzheimer disease and dementia.Dr Larsson receives support from the Swedish Heart-Lung Foundation (Hjärt-Lungfonden, grant number 20190247), the Swedish Research Council (Vetenskapsrådet, grant number 2019-00977), and the Swedish Research Council for Health, Working Life and Welfare (Forte, grant number 2018-00123). Dr Gill is funded by the Wellcome 4i Clinical PhD Program at Imperial College London. Dr Burgess is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (award number 204623/Z/16/Z). Drs Burgess and Butterworth report funding from Novartis relating to the investigation of lipoprotein(a). The funder had no influence on the content of the investigation or the decision to publish. This work was supported by core funding from the UK Medical Research Council (MR/L003120/1), the British Heart Foundation (RG/13/13/30194; RG/18/13/33946), the National Institute for Health Research [Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust] and Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome

PhenoScanner V2: an expanded tool for searching human genotype-phenotype associations.

SUMMARY: PhenoScanner is a curated database of publicly available results from large-scale genetic association studies in humans. This online tool facilitates 'phenome scans', where genetic variants are cross-referenced for association with many phenotypes of different types. Here we present a major update of PhenoScanner ('PhenoScanner V2'), including over 150 million genetic variants and more than 65 billion associations (compared to 350 million associations in PhenoScanner V1) with diseases and traits, gene expression, metabolite and protein levels, and epigenetic markers. The query options have been extended to include searches by genes, genomic regions and phenotypes, as well as for genetic variants. All variants are positionally annotated using the Variant Effect Predictor and the phenotypes are mapped to Experimental Factor Ontology terms. Linkage disequilibrium statistics from the 1000 Genomes project can be used to search for phenotype associations with proxy variants. AVAILABILITY AND IMPLEMENTATION: PhenoScanner V2 is available at www.phenoscanner.medschl.cam.ac.uk.This work was supported by the UK Medical Research Council [G0800270; MR/L003120/1], the British Heart Foundation [SP/09/002; RG/13/13/30194; RG/18/13/33946], Pfizer [G73632], the European Research Council [268834], the European Commission Framework Programme 7 [HEALTH-F2-2012-279233], the National Institute for Health Research and Health Data Research UK (*). *The views expressed are those of the authors and not necessarily those of the NHS or the NIHR

Inflammatory cytokines and risk of coronary heart disease: new prospective study and updated meta-analysis.

AIMS: Because low-grade inflammation may play a role in the pathogenesis of coronary heart disease (CHD), and pro-inflammatory cytokines govern inflammatory cascades, this study aimed to assess the associations of several pro-inflammatory cytokines and CHD risk in a new prospective study, including meta-analysis of prospective studies. METHODS AND RESULTS: Interleukin-6 (IL-6), IL-18, matrix metalloproteinase-9 (MMP-9), soluble CD40 ligand (sCD40L), and tumour necrosis factor-α (TNF-α) were measured at baseline in a case-cohort study of 1514 participants and 833 incident CHD events within population-based prospective cohorts at the Danish Research Centre for Prevention and Health. Age- and sex-adjusted hazard ratios (HRs) for CHD per 1-SD higher log-transformed baseline levels were: 1.37 (95% CI: 1.21-1.54) for IL-6, 1.26 (1.11-1.44) for IL-18, 1.30 (1.16-1.46) for MMP-9, 1.01 (0.89-1.15) for sCD40L, and 1.13 (1.01-1.27) for TNF-α. Multivariable adjustment for conventional vascular risk factors attenuated the HRs to: 1.26 (1.08-1.46) for IL-6, 1.12 (0.95-1.31) for IL-18, 1.21 (1.05-1.39) for MMP-9, 0.93 (0.78-1.11) for sCD40L, and 1.14 (1.00-1.31) for TNF-α. In meta-analysis of up to 29 population-based prospective studies, adjusted relative risks for non-fatal MI or CHD death per 1-SD higher levels were: 1.25 (1.19-1.32) for IL-6; 1.13 (1.05-1.20) for IL-18; 1.07 (0.97-1.19) for MMP-9; 1.07 (0.95-1.21) for sCD40L; and 1.17 (1.09-1.25) for TNF-α. CONCLUSIONS: Several different pro-inflammatory cytokines are each associated with CHD risk independent of conventional risk factors and in an approximately log-linear manner. The findings lend support to the inflammation hypothesis in vascular disease, but further studies are needed to assess causality.This work was supported by a grant from the British Heart Foundation (RG/08/014), the U.K. Medical Research Council, and the U.K. National Institute of Health Research Cambridge Biomedical Research Centre.This is the accepted manuscript. The final version is available from OUP at http://eurheartj.oxfordjournals.org/content/35/9/578

The influence of rare variants in circulating metabolic biomarkers.

Circulating metabolite levels are biomarkers for cardiovascular disease (CVD). Here we studied, association of rare variants and 226 serum lipoproteins, lipids and amino acids in 7,142 (discovery plus follow-up) healthy participants. We leveraged the information from multiple metabolite measurements on the same participants to improve discovery in rare variant association analyses for gene-based and gene-set tests by incorporating correlated metabolites as covariates in the validation stage. Gene-based analysis corrected for the effective number of tests performed, confirmed established associations at APOB, APOC3, PAH, HAL and PCSK (p<1.32x10-7) and identified novel gene-trait associations at a lower stringency threshold with ACSL1, MYCN, FBXO36 and B4GALNT3 (p<2.5x10-6). Regulation of the pyruvate dehydrogenase (PDH) complex was associated for the first time, in gene-set analyses also corrected for effective number of tests, with IDL and LDL parameters, as well as circulating cholesterol (pMETASKAT<2.41x10-6). In conclusion, using an approach that leverages metabolite measurements obtained in the same participants, we identified novel loci and pathways involved in the regulation of these important metabolic biomarkers. As large-scale biobanks continue to amass sequencing and phenotypic information, analytical approaches such as ours will be useful to fully exploit the copious amounts of biological data generated in these efforts

Information and Risk Modification Trial (INFORM): design of a randomised controlled trial of communicating different types of information about coronary heart disease risk, alongside lifestyle advice, to achieve change in health-related behaviour

Abstract Background Cardiovascular disease (CVD) remains the leading cause of death globally. Primary prevention of CVD requires cost-effective strategies to identify individuals at high risk in order to help target preventive interventions. An integral part of this approach is the use of CVD risk scores. Limitations in previous studies have prevented reliable inference about the potential advantages and the potential harms of using CVD risk scores as part of preventive strategies. We aim to evaluate short-term effects of providing different types of information about coronary heart disease (CHD) risk, alongside lifestyle advice, on health-related behaviours. Methods/Design In a parallel-group, open randomised trial, we are allocating 932 male and female blood donors with no previous history of CVD aged 40–84 years in England to either no intervention (control group) or to one of three active intervention groups: i) lifestyle advice only; ii) lifestyle advice plus information on estimated 10-year CHD risk based on phenotypic characteristics; and iii) lifestyle advice plus information on estimated 10-year CHD risk based on phenotypic and genetic characteristics. The primary outcome is change in objectively measured physical activity. Secondary outcomes include: objectively measured dietary behaviours; cardiovascular risk factors; current medication and healthcare usage; perceived risk; cognitive evaluation of provision of CHD risk scores; and psychological outcomes. The follow-up assessment takes place 12 weeks after randomisation. The experiences, attitudes and concerns of a subset of participants will be also studied using individual interviews and focus groups. Discussion The INFORM study has been designed to provide robust findings about the short-term effects of providing different types of information on estimated 10-year CHD risk and lifestyle advice on health-related behaviours. Trial registration Current Controlled Trials ISRCTN17721237 . Registered 12 January 2015