Abstract
Diabetic kidney disease (DKD) is a major complication of diabetes mellitus and the leading cause of end-stage renal disease (ESRD) worldwide. Despite considerable research efforts, the pathogenesis of DKD remains incompletely understood, largely due to its multifactorial etiology and pronounced phenotypic heterogeneity. Genome-wide association studies (GWAS) have identified over 40 loci associated with DKD; however, these common variants collectively explain only a small fraction of the disease’s heritability. Rare and low-frequency variants, often undetected by GWAS, are increasingly recognized as important contributors, and next-generation sequencing (NGS) technologies offer valuable tools for their identification. Kazakhstan, characterized by a unique genetic landscape and substantial ethnic admixture, remains underrepresented in DKD genomics research. Expanding integrative, high-resolution genomic studies in such settings is essential for identifying population-specific risk variants, improving diagnostic accuracy, and advancing precision medicine approaches to DKD prevention and management.