Exploring <i>LEPR</i> -Linked Metabolic Diversity through Gut Microbiome-Metabolome Network Analysis in Non-Obese Adults

Genetic variation in the leptin receptor (<i>LEPR</i>) 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 <i>LEPR</i> 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 <i>LEPR</i> 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. <i>LEPR</i> 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. <i>LEPR</i> 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.