Multiomics Analysis Identifies Candidate Molecular, Microbiota, and Metabolite Features Associated with Acute
Huijing Li1, Huiqiong Li1, Rongjing Wu1
1Nephrology Department, Hunan Aerospace Hospital, The Affiliated Aerospace Hospital of Hunan Normal University, Changsha, Hunan, China.
None:
Chronic renal failure (CRF) is a major risk factor for acute myocardial infarction (AMI) progression and poor outcomes, but the molecular, microbial, and metabolic features of AMI combined with CRF remain unclear. In this study, four Gene Expression Omnibus datasets were analyzed separately. GSE194388 and GSE180393 were used as discovery cohorts for AMI and CRF, and GSE109048 and GSE142153 were used as validation cohorts. Fecal samples from CRF patients without AMI (negative control [NC], n = 10) and patients with AMI and advanced CKD (SY, n = 10) were analyzed by 16S rRNA sequencing. Matched serum samples were analyzed by untargeted metabolomics. Four shared candidate hub genes, PTPRC, ITGAL, CD44, and SELL, were identified and showed preliminary discriminatory performance in validation datasets, although potential overfitting should be considered. These genes were positively correlated with increased immune cell subsets. Compared with NC, SY showed exploratory taxa-level microbiota differences, including increased Enterobacterales and decreased Bifidobacterium, without significant global diversity differences. Differential serum metabolites, including increased l-kynurenine and decreased glucose, were also identified and correlated with altered taxa. This integrated multiomics analysis identified candidate immune-related genes, microbiota features, and serum metabolites associated with AMI combined with CRF, providing preliminary evidence for future validation.
