Multi-stage metabolomics and genetic analyses identified metabolite biomarkers of metabolic syndrome and their genetic determinants

• DOI: 10.1016/j.ebiom.2021.103707
• Publication Date: 2021-11-18T10:06:37Z
• Authors: Qiong Wu; Jiankang Li; Xiaohui Sun; Di He; Zongxue Cheng; Jun Li; Xuhui Zhang; Yongming Xie; Yimin Zhu; Maode Lai
• Keywords: Mendelian Randomization; Metabolome; Genome-wide Association Study

Metabolic syndrome (MetS) is a cluster of multiple cardiometabolic risk factors that increase the type 2 diabetes and cardiovascular diseases. Identifying novel biomarkers MetS their genetic associations could provide insights into mechanisms diseases.Potential MetS-associated metabolites were screened internally validated by untargeted metabolomics analyses among 693 patients with 705 controls. External validation was conducted using two well-established targeted metabolomic methods 149 253 The determined linear regression our previous genome-wide SNP data. Causal relationships assessed one-sample Mendelian Randomization (MR) approach.Nine ultimately found to be associated or its components. Five metabolites, including LysoPC(14:0), LysoPC(15:0), propionyl carnitine, phenylalanine, docosapentaenoic acid (DPA) selected construct metabolite score (MRS), which have dose-response relationship metabolic abnormalities. Moreover, MRS displayed good ability differentiate Three SNPs (rs11635491, rs7067822, rs1952458) LysoPC(15:0). Two SNPs, rs1952458 rs11635491 marginally correlated several MR showed higher LysoPC(15:0) level causally overweight/obesity, dyslipidaemia, high uric acid, insulin HOMA-IR.We identified five three revealed abnormal LysoPC metabolism may linked risk.This work supported grants from National Key Research Development Program China (2017YFC0907004).