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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Exploring the causal correlations between 486 serum metabolites and systemic lupus erythematosus: a bidirectional
1Department of Dermatology and Venereology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Abstract:
Objective: The observational association between circulating metabolites and systemic lupus erythematosus (SLE) has been well documented. However, whether the association is causal remains unclear. In this study, bidirectional Mendelian randomization (MR) was introduced to analyse the causal relationships and possible mechanisms. Methods: We conducted a two-sample bidirectional MR study. A genome-wide association study (GWAS) with 7,824 participants provided data on 486 human blood metabolites. Outcome information was obtained from a large-scale GWAS summary, which contained 5,201 single nucleotide polymorphisms (SNPs) cases and 9,066 control cases of Europeans and yielded a total of 7,071,163 SNPs. The inverse variance weighted (IVW) model was recruited as the primary two-sample MR analysis approach, followed by sensitivity analyses such as the heterogeneity test, horizontal pleiotropy test, leave-one-out analysis, and linkage disequilibrium score (LDSC) regression. Results: In this study, we discovered that 24 metabolites belonging to the lipid, carbohydrate, xenobiotic and amino acid superpathways may increase the risk of SLE occurrence (p < 0.05). In addition, the metabolic disorders of 51 metabolites belonging to the amino acid, energy, xenobiotics, peptide and lipid superpathways were affected by SLE (p < 0.05). Palmitoleate belonging to the lipid superpathway and isobutyrylcarnitine and phenol sulfate belonging to the amino acid superpathway were factors with two-way causation. The metabolic enrichment pathway of bile acid biosynthesis was significant in the forward MR analysis (p = 0.0435). Linolenic acid and linoleic acid metabolism (p = 0.0260), betaine metabolism (p = 0.0314), and glycerolipid metabolism (p = 0.0435) were the significant metabolically enriched pathways in the reverse MR analysis. Conclusion: The levels of some specific metabolites may either contribute to the immune response inducing SLE, or they may be intermediates in the development and progression of SLE. These metabolites can be used as auxiliary diagnostic tools for SLE and for the evaluation of disease progression and therapeutic effects.
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