
Abstract Chronic kidney disease (CKD) remains a major global health burden, with sub-Saharan Africa, particularly Nigeria, experiencing disproportionately high prevalence and mortality rates. Conventional diagnostic markers such as serum creatinine, estimated glomerular filtration rate (eGFR), and urine albumin primarily detect functional decline and do not capture early molecular alterations. This limitation highlights the urgent need to integrate genomics and bioinformatics approaches to improve early detection and precision management of CKD in Nigeria. This review examines the genetic and molecular mechanisms underlying CKD, focusing on key susceptibility genes such as APOL1, MYH9, UMOD, and COL4A5, which influence disease onset and progression in African populations. Evidence from genome-wide association studies (GWAS) and next-generation sequencing (NGS) demonstrates the importance of identifying population-specific genetic variants to enhance predictive accuracy. Bioinformatics tools and public repositories, including the Gene Expression Omnibus (GEO), were also explored for their role in biomarker discovery, such as CCR7, and in the development of predictive and personalized therapeutic models. The findings indicate that Nigeria’s genomic research landscape is expanding through initiatives led by NIMR, LASU, Covenant University, and ACEGID, supported by continental collaborations like H3Africa. However, progress remains limited by inadequate funding, poor infrastructure, insufficient training, and weak translational frameworks. Emerging opportunities such as affordable sequencing technologies, regional genomic databases, and structured capacity-building initiatives offer promising pathways for advancement. In conclusion, integrating genomics and bioinformatics into Nigeria’s CKD management framework requires stronger policy support, improved research infrastructure, and targeted human-capacity development. Strengthening these areas will promote the adoption of precision medicine, enable earlier disease detection, and enhance health equity across Nigerian populations.
Chronic kidney disease; Genomic profiling; Bioinformatics integration; Genetic susceptibility; Precision medicine; Nigeria.
Chronic kidney disease; Genomic profiling; Bioinformatics integration; Genetic susceptibility; Precision medicine; Nigeria.
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