Key points are not available for this paper at this time.
BACKGROUND: Quantitative nuclear magnetic resonance (NMR) metabolomics techniques provide detailed measurements of lipoprotein particle concentration. Metabolic dysfunction often represents a cluster of conditions, including dyslipidaemia, hypertension, and diabetes, that increase the risk of cardiovascular diseases (CVDs). However, the causal relationship between lipid profiles and blood pressure (BP) remains unclear. We performed a Mendelian Randomisation (MR) study to disentangle and prioritize the potential causal effects of major lipids, lipoprotein particles, and circulating metabolites on BP and pulse pressure (PP). METHODS: We employed single-nucleotide polymorphisms (SNPs) associated with major lipids, lipoprotein particles, and other metabolites from the UK Biobank as instrumental variables. Summary-level data for BP and PP were obtained from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. Two-sample MR and MR Bayesian model averaging approaches (MR-BMA) were conducted to analyse and rank causal associations. FINDINGS: Genetically predicted TG was the most likely causal exposure among the major lipids to increase systolic blood pressure (SBP) and diastolic blood pressure (DBP), with marginal inclusion probabilities (MIPs) of 0. 993 and 0. 847, respectively. Among the majority of lipoproteins and their containing lipids, including major lipids, genetically elevated TG in small high-density lipoproteins (SHDLTG) had the strongest association with the increase of SBP and DBP, with MIPs of 0. 416 and 0. 397, respectively. HDL cholesterol (HDLC) and low-density lipoprotein cholesterol (LDLC) were potential causal factors for PP elevation among the major lipids (MIP = 0. 927 for HDLC and MIP = 0. 718 for LDLC). Within the sub-lipoproteins, genetically predicted atherogenic lipoprotein particles (i. e. , sub-very low-density lipoprotein (VLDL), intermediate-density lipoprotein (IDL), and LDL particles) had the most likely causal impact on increasing PP. INTERPRETATION: This study provides genetic evidence for the causality of lipids on BP indicators. However, the effect size on SBP, DBP, and PP varies depending on the lipids' components and sizes. Understanding this potential relationship may inform the potential benefits of comprehensive management of lipid profiles for BP control. FUNDING: Key Research and Development Program of Hubei Province, Science and Technology Innovation Project of Huanggang Central Hospital of Yangtze University, the Hubei Industrial Technology Research Institute of Heart-Brain Diseases, and the Hubei Provincial Engineering Research Centre of Comprehensive Care for Heart-Brain Diseases.
Liu et al. (Thu,) studied this question.