Genetic epidemiologic design focusing on African Americans or Hispanics is particularly challenging because both groups have experienced recent admixture. Indeed, in the presence of cryptic population structure, case-control association designs can produce false-positive association findings. However, case-control designs have unique advantages that family-based designs cannot replace. Therefore, it is crucial to develop approaches that analyze case-control studies and are immune to the perils of population stratification. At the same time, recent admixture creates strong linkage disequilibrium, providing exciting opportunities for novel disease-mapping approaches. The long-term goal of this research is to develop novel quantitative methods which enable researchers to identify the factors that influence disease risk in admixed or stratified populations. This project aims to develop new methods that improve the robustness and efficiency of casecontrol association studies, with applications to African Americans and Mexican Americans. Bootstrap- and resampling-based procedures will be developed to infer important aspects of an individual's ancestry, using genotype data at linked and unlinked genetic markers (Aim 1).
Aim 2 strives to shed light on a long-standing controversy regarding the scope of confounding that is likely to occur in practice.
Aim 3 develops an adjustment-based approach which incorporates the estimated individual admixture in a regression model and thereby explicitly controls for confounding due to population stratification. Finally, Aim 4 proposes a linkage-disequilibrium mapping approach. The strengths and limitations of the adjustment approach (Aim 3) and the linkage disequilibrium mapping approach (Aim 4) will be assessed analytically and through simulations. Results from this research will enable investigators to better identify and control for bias due to admixture in population-based case-control studies, and to design new valid and more powerful studies. Genotypic data from various multiethnic studies will be used together with extensive simulation experiments to test and refine the methodology for real-world applications.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
Project #
Application #
Study Section
Genome Study Section (GNM)
Program Officer
Anderson, Richard A
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Stanford University
Schools of Medicine
United States
Zip Code
Choi, Yoonha; Coram, Marc; Peng, Jie et al. (2017) A Poisson Log-Normal Model for Constructing Gene Covariation Network Using RNA-seq Data. J Comput Biol 24:721-731
Szulc, Piotr; Bogdan, Malgorzata; Frommlet, Florian et al. (2017) Joint genotype- and ancestry-based genome-wide association studies in admixed populations. Genet Epidemiol 41:555-566
Liang, Jingjing; Le, Thu H; Edwards, Digna R Velez et al. (2017) Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations. PLoS Genet 13:e1006728
Coram, Marc A; Fang, Huaying; Candille, Sophie I et al. (2017) Leveraging Multi-ethnic Evidence for Risk Assessment of Quantitative Traits in Minority Populations. Am J Hum Genet 101:218-226
Coram, Marc A; Fang, Huaying; Candille, Sophie I et al. (2017) Leveraging Multi-ethnic Evidence for Risk Assessment of Quantitative Traits in Minority Populations. Am J Hum Genet 101:638
Lloyd-Jones, Luke R; Robinson, Matthew R; Moser, Gerhard et al. (2017) Inference on the Genetic Basis of Eye and Skin Color in an Admixed Population via Bayesian Linear Mixed Models. Genetics 206:1113-1126
Wang, Heming; Choi, Yoonha; Tayo, Bamidele et al. (2017) Genome-wide survey in African Americans demonstrates potential epistasis of fitness in the human genome. Genet Epidemiol 41:122-135
Below, Jennifer E; Parra, Esteban J; Gamazon, Eric R et al. (2016) Meta-analysis of lipid-traits in Hispanics identifies novel loci, population-specific effects, and tissue-specific enrichment of eQTLs. Sci Rep 6:19429
Shetty, Priya B; Tang, Hua; Feng, Tao et al. (2015) Variants for HDL-C, LDL-C, and triglycerides identified from admixture mapping and fine-mapping analysis in African American families. Circ Cardiovasc Genet 8:106-13
Banda, Yambazi; Kvale, Mark N; Hoffmann, Thomas J et al. (2015) Characterizing Race/Ethnicity and Genetic Ancestry for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort. Genetics 200:1285-95

Showing the most recent 10 out of 33 publications