Exploring LEPR-Linked Metabolic Diversity through Gut Microbiome-Metabolome Network Analysis in Non-Obese Adults
10.4062/biomolther.2025.161
- Author:
Kyeong-Seog KIM
;
Joo-Youn CHO
;
Ye Chan PARK
;
Jang Hee HONG
;
Jin-Gyu JUNG
;
Jung SUNWOO
- Publication Type:Original Article
- From:Biomolecules & Therapeutics
2026;34(2):448-460
- CountryRepublic of Korea
- Language:English
-
Abstract:
Genetic variation in the leptin receptor (LEPR) gene has been implicated in metabolic regulation, while the gut microbiome and circulating metabolites are increasingly recognized as mediators of host metabolic phenotype. However, the systems-level interactions among LEPR genotypes, gut microbial composition, and serum metabolomic profiles remain poorly understood, particularly in healthy individuals. We conducted a cross-sectional study involving 37 healthy Korean adults. Three LEPR single nucleotide polymorphisms (rs1137101, rs1173100, rs790419) were genotyped. Untargeted metabolomics of fasting serum was performed using gas chromatography–time-of-flight mass spectrometry, and gut microbiome composition was profiled by 16S rRNA gene sequencing. Statistical analysis included principal component analysis, Mann–Whitney U tests, and Spearman correlations. Network analysis integrating microbiome, metabolomic, and clinical phenotype data was conducted using Cytoscape. A total of 54 serum metabolites were identified. LEPR genotypes, particularly rs1137101 and rs1173100, were associated with differences in metabolites such as pimelic acid, malonic acid, and 2,4-dihydroxybutyric acid. Firmicutes negatively correlated with saturated fatty acids and organic acids, whereas Actinobacteria positively correlated with cholesterol and amino acids. Network analysis revealed indole-3-acetate and cholesterol as central nodes linking microbial taxa with body mass index and leptin levels. However, no direct molecular pathways connecting leptin or its receptor were identified. LEPR genetic variation is associated with distinct serum metabolomic patterns and microbiome–host networks in healthy adults. Although no direct leptin signaling links were found, network-level associations suggest indirect genetic influences on metabolic states through microbiome–metabolome interactions.These findings advance understanding of personalized metabolic regulation and gene–microbiome interplay.
