Biology subjects

Mason, A. M.

Publications and source records attributed to Mason, A. M..

3 recordsLinked to original sources

bioRxiv2022

Relaxing parametric assumptions for non-linear Mendelian randomization using a doubly-ranked stratification method

Non-linear Mendelian randomization is an extension to standard Mendelian randomization to explore the shape of the causal relationship between an exposure and outcome using an instrumental variable. The approach divides the population into strata and calculates separate instrumental variable estimates in each stratum. However, the standard implementation of stratification in non-linear Mendelian randomization, referred to as the residual method, relies on strong parametric assumptions of linearity and homogeneity between the instrument and the exposure to form the strata. If these stratification assumptions are violated, the instrumental variable assumptions may be violated in the strata even if they are satisfied in the population, resulting in misleading estimates. We propose a new stratification method, referred to as the doubly-ranked method, that does not require strict parametric assumptions to create strata with different average levels of the exposure such that the instrumental variable assumptions are satisfied within the strata. Our simulation study indicates that the doubly-ranked method can obtain unbiased stratum-specific estimates and appropriate coverage rates even when the effect of the instrument on the exposure is non-linear or heterogeneous. Moreover, it can also provide unbiased estimates when the exposure is coarsened (that is, rounded, binned into categories, or truncated), a scenario that is common in applied practice and leads to substantial bias in the residual method. We applied the proposed doubly-ranked method to investigate the effect of alcohol intake on systolic blood pressure, and found evidence of a positive effect of alcohol intake, particularly at higher levels of alcohol consumption.

genetics↗

bioRxiv2019

Genetic determinants of lipids and cardiovascular disease outcomes: a wide-angled Mendelian randomization investigation

AimsTo systematically investigate causal relationships between circulating lipids and cardiovascular outcomes, using a Mendelian randomization approach.\n\nMethods and ResultsIn the primary analysis, we performed two-sample multivariable Mendelian randomization using data from participants of European ancestry. We also conducted univariable analyses using inverse-variance weighted and robust methods, and gene-specific analyses using variants that can be considered as proxies for specific lipid-lowering medications. We obtained associations with lipid fractions from the Global Lipids Genetics Consortium, a meta-analysis of 188,577 participants, and genetic associations with cardiovascular outcomes from 367,703 participants in UK Biobank.\n\nFor LDL-cholesterol, in addition to the expected positive associations with coronary artery disease (CAD) risk (odds ratio per 1 standard deviation increase [OR], 1.45; 95% confidence interval [95%CI] 1.35-1.57) and other atheromatous outcomes (ischemic cerebrovascular disease and peripheral vascular disease), we found independent associations of genetically-predicted LDL-cholesterol with abdominal aortic aneurysm (OR 1.75; 95%CI 1.40-2.17), and aortic valve stenosis (OR 1.46; 95%CI 1.25-1.70). Genetically-predicted triglyceride levels were positively associated with CAD (OR 1.25; 95%CI 1.12-1.40), aortic valve stenosis (OR 1.29; 95%CI 1.04-1.61), and hypertension (OR 1.17; 95%CI 1.07-1.27), but inversely associated with venous thromboembolism (OR 0.79; 95%CI 0.67-0.93). The positive associations of genetically-predicted LDL-cholesterol and triglycerides with heart failure and aortic stenosis appeared to be mediated by CAD.\n\nConclusionLowering LDL-cholesterol is likely to prevent abdominal aortic aneurysm and aortic stenosis, in addition to CAD and other atheromatous cardiovascular outcomes. Lowering triglycerides is likely to prevent CAD and aortic valve stenosis, but may increase risk of thromboembolism.

epidemiology↗

bioRxiv2019

Shared mechanisms between coronary heart disease and depression: findings from a large UK general population-based cohort

While comorbidity between coronary heart disease (CHD) and depression is evident, it is unclear whether the two diseases have shared underlying mechanisms. We performed a range of analyses in 367,703 unrelated middle-aged participants of European ancestry from UK Biobank, a population based cohort study, to assess whether comorbidity is primarily due to genetic or environmental factors, and to test whether cardiovascular risk factors and CHD are likely to be causally related to depression using Mendelian randomization. We showed family history of heart disease was associated with a 20% increase in depression risk (95% confidence interval [CI] 16% to 24%, p<0.0001), but a genetic risk score that is strongly associated with CHD risk was not associated with depression. An increase of one standard deviation in the CH D genetic risk score was associated with 71% higher CHD risk, but 1% higher depression risk (95% CI 0% to 3%; p=0.11). Mendelian randomization analyses suggested that triglycerides, interleukin-6 (IL-6), and C-reactive protein (CRP) are likely causal risk factors for depression. The odds ratio for depression per standard deviation increase in genetically-predicted triglycerides was 1.18 (95% CI 1.09 to 1.27; p=2x10-5); per unit increase in genetically-predicted log-transformed I L-6 was 0.74 (95% CI 0.62 to 0.89; p=0.0012); and per unit increase in genetically-predicted log-transformed CRP was 1.18 (95% CI 1.07 to 1.29; p=0.0009). Our analyses suggest that comorbidity between depression and CHD arises largely from shared environmental factors. I L-6, CRP and triglycerides, are likely to be causally linked with depression, so could be targets for treatment and prevention of depression.

genetics↗