Our research is centered around using human population genetics to understand the role of genetics in human health outcomes. We are strongly interested in leveraging population differences in the genetic architecture of rare and common disorders to serve community health. 

This type of research involves understanding both the environmental and clinical contexts in which genetics contributes to phenotype in different populations. We employ three main strategies to carry out this research. The first is evolutionary genetic approaches to understanding why humans vary, where in the genome this may occur, and how this may affect disease risk. The second is using population genetic approaches to address epidemiological questions, such as predicting who might be at highest risk for a particular disease and understanding the genetic architecture underlying this. Lastly, we use anthropological genetics approaches to understand the genetic variation and environmental contexts which may predispose an individual to disease. This involves extensive fieldwork to understand the contribution of human genetic and local environmental variation to phenotypic variation among specific populations.

This multi-pronged approach enables us to apply population genetic principles and approaches broadly to understand the genetic contribution to community health outcomes, which can be multifaceted and vary among populations and disease contexts.

Myer PA, Lee JK, Madison R, Pradhan K, Newberg J, Isasi CR, Klempner SJ, Frampton G, Ross JS, Venstrom J, Schrock AB, Das S, Augenlicht L, Verma A, Greally JM, Raj SM, Goel S, Ali SM (2022) The Genomics of Colorectal Cancer in Populations with African and European Ancestry. Cancer Discovery 12 (5): 1282-1293.

Raj SM, R Ekanayake, M Bhat, J Kadandale, P Pingali. Multiple risk factors contributing to stunting in Karnataka state, India. Current Science 121(3):360-64.

Raj SM, R Ekanayake, K Crowley, M Bhat, J Kadandale, P Pingali. Risk factors  in childhood stunting in Karnataka state vary by geography. Current Science 121(4):502-10.

Yu F*, Lu J*, Liu X*, Gazave E, Chang D, Raj S, Hunter-Zinck H, Blekhman R, Arbiza L, Van Hout C, Morrison A, Johnson AD, Bis J, Cupples LA, Psaty BM, Muzny D, Yu J, Gibbs RA, Keinan A, Clark AG, Boerwinkle E. 2015. A population genetic analysis of 962 whole genome sequences reveals natural selection in non-coding regions of the human genome. PLoS One 10, e0121644.

Cardona, A., Pagani L, Antao T, Lawson DJ, Eichstadt CA, Yngvadottir B, Shwe MTT, Wee J, Tyler-Smith C, Gallego Romero I, Raj S, Metspalu M, Villems R, Nielsen R, Willerslev E, Malyarchuk BA, Derenko MV, Kivisild T. (2014) Genome-wide analysis of cold adaption in indigenous Siberian populations PLoS One 9:e98076.

Raj SM, Pagani L, Romero IG, Kivisild T, Amos W (2013). A general linear model based approach for inferring selection to climate. BMC Genetics 14: 87.

Ye K, Lu J, Raj SM, Gu Z (2013). Human expression QTLs are enriched in signals of environmental adaptation. Genome Biol Evol 5:1689-701.

Raj SM, Halebeedu P, Iliescu FM, Romero IG, Kadandale, J, Thangaraj, K, Chandra HS, Muniyappa, K, Kivisild, T. Patterns of variation at diabetes and obesity-associated loci mirror neutral patterns of human population diversity and diabetes prevalence in India. Annals of Human Genetics 77(5): 392-408.