Search PubMedSearch

Biomedical subjects

Zekai Chen

Publications and source records attributed to Zekai Chen.

2 recordsLinked to original sources

Drug targets for lipid modification and risk of type 2 diabetes: a cis-Mendelian randomization study.

BACKGROUND AND AIMS: Reducing plasma levels of low-density lipoprotein cholesterol (LDL-C) is the cornerstone in the prevention of coronary artery disease (CAD) but may also increase risk of type 2 diabetes (T2D). A comprehensive examination of the genetic evidence of T2D related side-effects of all current lipid-modifying drugs, including those in development, has not yet been performed. METHODS: This cis-Mendelian randomization study used individual level data from the UK Biobank, Lifelines, and publicly available genome-wide association data. We identified loci that are either targeted directly with drugs, or alternatively, targeting their gene products (mRNA and/or protein). Included are, in alphabetical order, the loci ACLY, ANGPTL3, ANGPTL4, APOB, APOC3, CETP, HMGCR, LDLR, LIPG, LPA, MTTP, NPC1L1, and PCSK9. We used cis-genetic instruments weighted for LDL-C, HDL-C, triglycerides, and apolipoproteins as downstream proxies for the drug targets. Main outcomes were prevalent and incident T2D, with CAD as a contrast outcome. RESULTS: Lipid modification through HMGCR is predicted to reduce CAD risk and increase T2D risk. Modification through targeting APOC3, LDLR, LPA, MTTP, NPC1L1, and PCSK9 is predicted to reduce CAD risk without a change in T2D risk. Modification through ANGPTL4 and CETP is predicted to reduce risk of both CAD and T2D. For ACLY, ANGPTL3, APOB, and LIPG, we found evidence for neither CAD nor T2D. CONCLUSIONS: This study provides genetic evidence for variation in diabetes-related side-effects of different lipid-modifying drugs, with potential relevance for future clinical trials and individual treatment decisions.

Humans

Genome-wide gene-sleep interaction study identifies novel lipid loci in 732,564 participants.

BACKGROUND AND AIMS: Deviations from the population mean in sleep duration have been associated with increased risk for developing dyslipidemia and atherosclerotic cardiovascular disease, but the mechanism of effect is poorly characterized. We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. METHODS: We collected data from 55 cohorts with a combined sample size of 732,564 participants (87&#xa0;% European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20&#xa0;% of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for one-degree of freedom tests of interaction and two-degree of freedom joint tests of the SNP-main and -interaction effect on lipid levels. RESULTS: The one-degree of freedom variant-sleep interaction test identified 10 novel loci (Pint<5.0e-9), and we additionally identify 7 loci within the two-degree of freedom analyses (Pjoint<5.0e-9 in combination with Pint<6.6e-6). Multiple loci, including those mapped to APSH (target for aspartic and succinic acid) and SLC8A1 showed biological plausibility and druggability potential based on literature. CONCLUSIONS: Collectively, the 17 (9 with short and 8 with long sleep) loci provided evidence into the biomolecular mechanisms underlying sleep-associated lipid changes, including potential involvement of the vitamin D receptor pathway. Collectively, these findings may contribute developing novel interventions for treating dyslipidemia in people with sleep disturbances.

Humans