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Multi-stage metabolomics and genetic analyses identified metabolite biomarkers of metabolic syndrome and their genetic determinants
- Source :
- EBioMedicine, Vol 74, Iss , Pp 103707- (2021)
- Publication Year :
- 2021
- Publisher :
- Elsevier, 2021.
-
Abstract
- Background: Metabolic syndrome (MetS) is a cluster of multiple cardiometabolic risk factors that increase the risk of type 2 diabetes and cardiovascular diseases. Identifying novel biomarkers of MetS and their genetic associations could provide insights into the mechanisms of cardiometabolic diseases. Methods: Potential MetS-associated metabolites were screened and internally validated by untargeted metabolomics analyses among 693 patients with MetS and 705 controls. External validation was conducted using two well-established targeted metabolomic methods among 149 patients with MetS and 253 controls. The genetic associations of metabolites were determined by linear regression using our previous genome-wide SNP data. Causal relationships were assessed using a one-sample Mendelian Randomization (MR) approach. Findings: Nine metabolites were ultimately found to be associated with MetS or its components. Five metabolites, including LysoPC(14:0), LysoPC(15:0), propionyl carnitine, phenylalanine, and docosapentaenoic acid (DPA) were selected to construct a metabolite risk score (MRS), which was found to have a dose-response relationship with MetS and metabolic abnormalities. Moreover, MRS displayed a good ability to differentiate MetS and metabolic abnormalities. Three SNPs (rs11635491, rs7067822, and rs1952458) were associated with LysoPC(15:0). Two SNPs, rs1952458 and rs11635491 were found to be marginally correlated with several MetS components. MR analyses showed that a higher LysoPC(15:0) level was causally associated with the risk of overweight/obesity, dyslipidaemia, high uric acid, high insulin and high HOMA-IR. Interpretation: We identified five metabolite biomarkers of MetS and three SNPs associated with LysoPC(15:0). MR analyses revealed that abnormal LysoPC metabolism may be causally linked the metabolic risk. Funding: This work was supported by grants from the National Key Research and Development Program of China (2017YFC0907004).
Details
- Language :
- English
- ISSN :
- 23523964
- Volume :
- 74
- Issue :
- 103707-
- Database :
- Directory of Open Access Journals
- Journal :
- EBioMedicine
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.21253ba40e1f4d57aa9656e1865a5273
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.ebiom.2021.103707