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Sex-specific genetic effects across biomarkers

European Journal of Human Genetics, 2020-09-01

Video Abstract (AI generated) Paper Preprint European Journal of Human Genetics

Sex differences have been shown in laboratory biomarkers; however, the extent to which this is due to genetics is unknown. In this study, we infer sex-specific genetic parameters (heritability and genetic correlation) across 33 quantitative biomarker traits in 181,064 females and 156,135 males from the UK Biobank study. We apply a Bayesian mixture model, Sex Effects Mixture Model, to Genome-wide Association Study summary statistics in order to (1) estimate the contributions of sex to the genetic variance of these biomarkers and (2) identify variants whose statistical association with these traits is sex-specific. We find that the genetics of most biomarker traits are shared between males and females, with the notable exception of testosterone, where we identify 119 female and 444 male-specific variants. These include protein-altering variants in steroid hormone production genes (POR, CYP3A43, UGT2B7). Using the sex-specific variants as genetic instruments for Mendelian Randomization, we find evidence for causal links between testosterone levels and height, body mass index, waist circumference, and type 2 diabetes. We also show that sex-specific polygenic risk score models for testosterone outperform a combined model. Overall, these results demonstrate that while sex has a limited role in the genetics of most biomarker traits, sex plays an important role in testosterone genetics.

LPA and APOE are associated with statin selection in the UK Biobank

Video Abstract (AI generated) Paper Preprint Supplemental File 1 Supplemental Figures

Genetics plays a key role in drug response, affecting efficacy and toxicity. Pharmacogenomics aims to understand how genetic variation influences drug response and develop clinical guidelines to aid clinicians in personalized treatment decisions informed by genetics. Although pharmacogenomics has not been broadly adopted into clinical practice, genetics influences treatment decisions regardless. Physicians adjust patient care based on observed response to medication, which may occur as a result of genetic variants harbored by the patient. Here we seek to understand the genetics of drug selection in statin therapy, a class of drugs widely used for high cholesterol treatment. Genetics are known to play an important role in statin efficacy and toxicity, leading to significant changes in patient outcome. We performed genome-wide association studies (GWAS) on statin selection among 59,198 participants in the UK Biobank and found that variants known to influence statin efficacy are significantly associated with statin selection. Specifically, we find that carriers of variants in APOE and LPA that are known to decrease efficacy of treatment are more likely to be on atorvastatin, a stronger statin. Additionally, carriers of the APOE and LPA variants are more likely to be on a higher intensity dose (a dose that reduces low‑density lipoprotein cholesterol by greater than 40%) of atorvastatin than non-carriers (APOE: p(high intensity) = 0.16, OR = 1.7, P = 1.64 x 10-4, LPA: p(high intensity) = 0.17, OR = 1.4, P = 1.14 x 10-2). These findings represent the largest genetic association study of statin selection and statin dose association to date and provide evidence for the role of LPA and APOE in statin response, furthering the possibility of personalized statin therapy. ### Competing Interest Statement R.B.A. is a stockholder in Personalis.com, 23andme.com. M.A.R. is on the SAB of 54Gene and Computational Advisory Board for Goldfinch Bio and has advised BioMarin, Third Rock Ventures, MazeTx and Related Sciences.