Combining Evidence of Natural Selection with Association Analysis Increases Power to Detect Malaria-Resistance Variants

• Published in: American journal of human genetics Vol. 81; no. 2; pp. 234 - 242
• Main Authors: Ayodo, George, Price, Alkes L., Keinan, Alon, Ajwang, Arthur, Otieno, Michael F., Orago, Alloys S.S., Patterson, Nick, Reich, David
• Format: Journal Article
• Language: English
• Published: Chicago, IL Elsevier Inc 01-08-2007; University of Chicago Press; Cell Press; American Society of Human Genetics
• Subjects: Adolescent; Adult; Biological and medical sciences; Biostatistics; Case-Control Studies; Child; Child, Preschool; Evolution; Female; Fundamental and applied biological sciences. Psychology; Gene Frequency; General aspects. Genetic counseling; Genetic Variation; Genetics of eukaryotes. Biological and molecular evolution; Human protozoal diseases; Humans; Immunity, Innate - genetics; Infant; Infectious diseases; Kenya; Linkage Disequilibrium; Malaria; Malaria - genetics; Male; Medical genetics; Medical sciences; Molecular and cellular biology; Parasitic diseases; Parasitic protozoa; Protozoal diseases; Risk factors; Selection, Genetic; Statistics as Topic; Kenya; Infection; Human; Resistance; Variant; Protozoal disease; Association; Malaria; Genetics; Increase; Parasitosis; Power; Natural selection
• ISSN: 0002-9297; 1537-6605
• DOI: 10.1086/519221

Statistical power to detect disease variants can be increased by weighting candidates by their evidence of natural selection. To demonstrate that this theoretical idea works in practice, we performed an association study of 10 putative resistance variants in 471 severe malaria cases and 474 controls from the Luo in Kenya. We replicated associations at
HBB (
P=.0008) and
CD36 (
P=.03) but also showed that the same variants are unusually differentiated in frequency between the Luo and Yoruba (who historically have been exposed to malaria) and the Masai and Kikuyu (who have not been exposed). This empirically demonstrates that combining association analysis with evidence of natural selection can increase power to detect risk variants by orders of magnitude—up to
P=.000018 for
HBB and
P=.00043 for
CD36.