Kidney stone disease (KSD) is a multifactorial disorder influenced by environmental exposures, metabolic dysregulation, and genetic predisposition. However, exactly which genes and how they interact with the various environmental/metabolic/lifestyle factors are largely unknown. Enhanced insights into these interactions are critical for identifying high-risk populations, informing preventive strategies, and reducing the clinical and economic burden of KSD.
This research aims to systematically identify and characterize the interactions between genetic, metabolic and environmental risk factors contributing to KSD. Integrating multi-omics data on different etiologies and outcomes of KSD may improve the pathophysiological and phenotypic understanding of KSD and identify preventive, diagnostic and therapeutic targets of KSD.
Emerging evidence highlights the interplay of genetic, metabolic and environmental factors in KSD. Genome-wide association studies have identified loci associated with calcium homeostasis and phosphate transport, while metabolomic profiling reveals dysregulation in citrate, oxalate, and uric acid pathways. Environmental factors such as low fluid intake, high sodium diet, and obesity further exacerbate stone risk. However, most studies focus on isolated factors, neglecting synergistic interactions and imply limited causal inference. By leveraging the UK Biobank’s multi-omics and epidemiological data, this study adopts a systems biology framework to address these gaps. The integration of genomics, metabolomics, proteomics, and lifestyle data will enable the identification of novel risk clusters and mechanistic pathways. In this proposed study, we could investigate whether there are statistically significant interactions between genetic risk and each of the environmental factors and metabolic traits and whether this interaction increases an individual’s risk for developing KSD.
