The Multiethnic Cohort: A Resource for the Study of Genetic and Nongenetic Cancer Risk across Populations

Read full text
Authors: David Daniel Bogumil, Xin Sheng, Peggy C. Wan, Lucy Y. Xia, Loreall Pooler, Iona C. Cheng, Samantha A. Streicher, Brian Z. Huang, Fei Chen, Daniel O. Stram, Sylvia S. Shen, Gillian A King
+12 more Charleston W. K. Chiang, Chrissie M. Ongaco, Marcia Adams, Ivy McMullen, Peng Zhang, Hua Ling, Michelle Mawhinney, Kimberly Floy Doheny, Loı̈c Le Marchand, Lynne Ross Wilkens, Christopher A. Haiman, David V. Conti
Cited by: 1
References: 58

Abstract

BACKGROUND: The Multiethnic Cohort Study (MEC) is a US prospective cohort of more than 215,000 participants, designed to investigate variation in risk factors and disease across diverse racial and ethnic groups. More than 74,000 participants contributed biospecimens for genetic studies. We describe this subcohort and demonstrate the types of analyses it enables. METHODS: The MEC recruited adults aged 45 to 75 in California and Hawaii between 1993 and 1996. Cancer diagnoses were identified via state tumor registries. The MEC Genetics Database includes 73,139 participants with germline genotype data. We evaluated genetic similarity, its relationship with self-reported race/ethnicity, and baseline characteristics, including neighborhood socioeconomic status (nSES). Using breast, colorectal, and prostate cancer as examples, we conducted genome-wide association studies (GWAS), assessed nongenetic risk factors, and performed time-to-event analyses. RESULTS: Participants included 10,962 African Americans, 24,234 Japanese Americans, 17,242 Latinos, 5,488 Native Hawaiians, 14,649 Whites, and 564 others. Principal component analysis showed substantial diversity. Multiethnic GWAS replicated known variants with effective control of population stratification. Polygenic risk score (PRS) effects varied across groups. Time-to-event models revealed associations between cancer incidence and nSES, population descriptors, and genetic similarity. CONCLUSIONS: The MEC Genetics Database enables multiancestry analyses of genetic and nongenetic cancer risk, supporting research on disparities, polygenic traits, and integrated risk prediction. IMPACT: Example analyses using these resources show the relationship between population descriptors, PRSs, and common cancer risk factors that require special consideration in genetic analyses.

Fields of Study & Subjects

Genetic Associations and Epidemiology BRCA gene mutations in cancer Forensic and Genetic Research

Publication details

Journal / source
Cancer Epidemiology Biomarkers & Prevention
Publisher
American Association for Cancer Research (AACR)
Volume
35
Issue
7
Pages
1088–1099
Publication date
1 May 2026
Language
EN