Disease-specific crosstalk of Alistipes with lipoprotein profiles in overweight individuals at high cardiometabolic risk

Abstract

Abstract Metabolic syndrome (MS) and systemic lupus erythematosus (SLE) represent two pathophysiologically distinct chronic conditions associated with elevated cardiovascular risk. Emerging evidence links gut microbiota to host lipid metabolism and lipoprotein function. This investigation aimed to analyze disease-specific relations between gut microbiota and an advanced lipoprotein profiling in an overweight population affected by MS and SLE. A total of 85 individuals with MS and 66 with SLE, all overweight, were included. Anthropometric, body composition, and biochemical parameters were assessed. Lipoprotein profiles were quantified by 1 H-NMR spectroscopy, and gut microbiota composition via 16S rRNA sequencing. Machine learning Boruta feature selection identified microbial taxa linked to lipid traits. Regression models evaluated microbiota–LDL particle associations by disease type. Participants in the MS group showed more unfavorable values in anthropometric, body composition and clinical biochemistry. Advanced lipoprotein analysis revealed that MS individuals had higher levels of IDL-C, VLDL-TG, small LDL-P, and total LDL-P, with decreased HDL-C, reflecting a more atherogenic profile. Gut microbiota analysis identified Alistipes as a key discriminant taxon. A significant association was observed between Alistipes abundance and small LDL particle concentrations, being modulated by disease type, suggesting that the association between gut microbiota and lipid metabolism may differ by disease type. Participants with metabolic syndrome showed unfavorable anthropometric, clinical, and lipoprotein profiles, along with distinct gut microbiota, compared to individuals with the autoimmune-driven SLE. The results highlight condition-specific host–microbiota–lipid relationship and supports the use of novel approaches to guide precision strategies for cardiovascular risk reduction in high-risk populations.