From GWAS Signals to Causal Genes in Chronic Kidney Disease

Area of Science:

• Genetics
• Nephrology
• Genomic Medicine

Background:

• Genome-wide association studies (GWAS) have identified numerous genetic loci linked to chronic kidney disease (CKD) and its risk factors across diverse populations.
• A significant hurdle is translating these statistical associations into causal genes and understanding their mechanisms, as variants often reside in non-coding regulatory regions with cell-type-specific effects.

Purpose of the Study:

• This review synthesizes current strategies for identifying causal genes for CKD from GWAS signals.
• It aims to provide a framework for linking genetic discoveries to mechanistic insights and clinical applications in precision nephrology.

Main Methods:

• The review discusses advances in statistical and functional fine-mapping, molecular quantitative trait locus (QTL) mapping, colocalization, and transcriptome-wide association studies.
• It highlights the utility of kidney-specific single-cell, single-nucleus, and spatial transcriptomic atlases.
• Integration with chromatin interaction data, multi-omics, and CRISPR-based studies is also examined.

Main Results:

• Emerging transcriptomic atlases enable mapping genetic risk to specific renal cell types and microanatomical locations.
• Combining multiple functional genomics approaches refines the identification of causal relationships and mechanistic understanding.
• A unifying framework is proposed to integrate GWAS with functional genomics for distinguishing CKD susceptibility from progression modifiers.

Conclusions:

• Genetically informed gene prioritization is crucial for experimentation and therapeutic target discovery.
• These advancements pave the way for a precision nephrology framework by linking human genetics with functional genomics and experimental biology.
• The ultimate goal is to translate genetic association signals into clinically relevant interpretations for CKD.