Abstract
Many rare kidney disorders exhibit a monogenic, Mendelian pattern of inheritance. Population-based genetic studies have identified many genetic variants associated with an increased risk of developing common kidney diseases. Strongly associated variants have potential clinical uses as predictive markers and may advance our understanding of disease pathogenesis. These principles are elegantly illustrated by a region within chromosome 22q12 that has a strong association with common forms of kidney disease. Researchers had identified DNA sequence variants in this locus that were highly associated with an increased prevalence of common chronic kidney diseases in people of African ancestry. Initial research concentrated on MYH9 as the most likely candidate gene; however, population-based whole-genome analysis enabled two independent research teams to discover more strongly associated mutations in the neighboring APOL1 gene. The powerful evolutionary selection pressure of an infectious pathogen in West Africa favored the spread of APOL1 variants that protect against a lethal form of African sleeping sickness but are highly associated with an increased risk of kidney disease. We describe the data sources, process of discovery, and reasons for initial misidentification of the candidate gene, as well as the lessons that can be learned for future population genetics research.
Original language | English |
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Pages (from-to) | 313-326 |
Number of pages | 14 |
Journal | Nature Reviews Nephrology |
Volume | 7 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2011 |
Externally published | Yes |
Bibliographical note
Funding Information:K. Skorecki acknowledges the support of the Canadian and American Technion Societies (Eshagian Estate Fund, Dr Sidney Kremer Kidney Disease Research Fund), the Israel Science Foundation (grant number 890015), and the Legacy Heritage Fund. S. Rosset acknowledges the support of European Research Commission grant MIRG-CT-2007-208019, Israel Science Foundation (grant number 1227/09) and an IBM Open Collaborative Research grant. D. M. Behar thanks the European Commission, Directorate-General for Research for FP7 Ecogene grant 205419.