Peter Kraft
Primary Faculty

Peter Kraft

Professor of Epidemiology


Other Positions

Faculty Affiliate in the Department of Biostatistics


Harvard T.H. Chan School of Public Health

Co-Director, Computational Biology & Quantitative Genetics Master's Program


Harvard T.H. Chan School of Public Health


My research concentrates on the design and analysis of genetic association studies, with particular emphasis on studies linking variation in germline DNA to cancer risk. I have played a key role in multiple international consortia studying genetics and other exposures in relation to cancer risk over the last ten years: I have been a member of the statistical working group of the Breast and Prostate Cancer Cohort Consortium since its inception, and currently chair the BPC3 steering committee; I played a leading role in the design and analysis of GWAS of breast, prostate and pancreatic cancers as part of the NCI's Cancer Genetic Markers of Susceptibility and PanScan projects; and I chair the Analytic Working Group for the NCI's "post-GWAS" GAME-ON consortium, which aims to better understand the biological mechanisms underlying GWAS-identified cancer risk markers at five cancer sites (including breast and lung) and their public health implications.

I am also the contact PI for the epidemiology project of the breast cancer arm of GAME-ON, which focuses on gene-environment interactions and risk prediction. I have been the primary statistical geneticist for the Nurses' Health Study (NHS) and Health Professionals Follow-up Study (HPFS) for over ten years, and oversee the genotype databases for both studies, including genome-wide association data on over 20,000 subjects. I have collaborated on numerous analyses in the NHS and HPFS examining associations between genetic markers, behaviors (including diet and smoking), and risk of complex diseases. I have also collaborated with NHS investigators on the analyses of metabolite profiles in a case-control study of pancreatic cancer.

My current methodological research focuses on 1) efficient and interpretable "gene x environment interaction" analyses, 2) genetic risk prediction using common and rare genetic variation, biomarkers (including metabolites), and clinical and environmental risk factors, and 3) methods linking low-frequency variation, emerging functional annotation, and risk of complex disease.


Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women.

Wang X, Kapoor PM, Auer PL, Dennis J, Dunning AM, Wang Q, Lush M, Michailidou K, Bolla MK, Aronson KJ, Murphy RA, Brooks-Wilson A, Lee DG, Cordina-Duverger E, Guénel P, Truong T, Mulot C, Teras LR, Patel AV, Dossus L, Kaaks R, Hoppe R, Lo WY, Brüning T, Hamann U, Czene K, Gabrielson M, Hall P, Eriksson M, Jung A, Becher H, Couch FJ, Larson NL, Olson JE, Ruddy KJ, Giles GG, MacInnis RJ, Southey MC, Le Marchand L, Wilkens LR, Haiman CA, Olsson H, Augustinsson A, Krüger U, Wagner P, Scott C, Winham SJ, Vachon CM, Perou CM, Olshan AF, Troester MA, Hunter DJ, Eliassen HA, Tamimi RM, Brantley K, Andrulis IL, Figueroa J, Chanock SJ, Ahearn TU, García-Closas M, Evans GD, Newman WG, van Veen EM, Howell A, Wolk A, Håkansson N, Anton-Culver H, Ziogas A, Jones ME, Orr N, Schoemaker MJ, Swerdlow AJ, Kitahara CM, Linet M, Prentice RL, Easton DF, Milne RL, Kraft P, Chang-Claude J, Lindström S.

Sci Rep. 2022 04 13. 12(1):6199. PMID: 35418701

Rare germline copy number variants (CNVs) and breast cancer risk.

Dennis J, Tyrer JP, Walker LC, Michailidou K, Dorling L, Bolla MK, Wang Q, Ahearn TU, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Freeman LEB, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bogdanova NV, Bojesen SE, Brenner H, Castelao JE, Chang-Claude J, Chenevix-Trench G, Clarke CL, Collée JM, Couch FJ, Cox A, Cross SS, Czene K, Devilee P, Dörk T, Dossus L, Eliassen AH, Eriksson M, Evans DG, Fasching PA, Figueroa J, Fletcher O, Flyger H, Fritschi L, Gabrielson M, Gago-Dominguez M, García-Closas M, Giles GG, González-Neira A, Guénel P, Hahnen E, Haiman CA, Hall P, Hollestelle A, Hoppe R, Hopper JL, Howell A, Jager A, Jakubowska A, John EM, Johnson N, Jones ME, Jung A, Kaaks R, Keeman R, Khusnutdinova E, Kitahara CM, Ko YD, Kosma VM, Koutros S, Kraft P, Kristensen VN, Kubelka-Sabit K, Kurian AW, Lacey JV, Lambrechts D, Larson NL, Linet M, Ogrodniczak A, Mannermaa A, Manoukian S, Margolin S, Mavroudis D, Milne RL, Muranen TA, Murphy RA, Nevanlinna H, Olson JE, Olsson H, Park-Simon TW, Perou CM, Peterlongo P, Plaseska-Karanfilska D, Pylkäs K, Rennert G, Saloustros E, Sandler DP, Sawyer EJ, Schmidt MK, Schmutzler RK, Shibli R, Smeets A, Soucy P, Southey MC, Swerdlow AJ, Tamimi RM, Taylor JA, Teras LR, Terry MB, Tomlinson I, Troester MA, Truong T, Vachon CM, Wendt C, Winqvist R, Wolk A, Yang XR, Zheng W, Ziogas A, Simard J, Dunning AM, Pharoah PDP, Easton DF.

Commun Biol. 2022 01 18. 5(1):65. PMID: 35042965


Dozens of new genetic regions linked to breast cancer

Two studies represent the largest-ever examination of the inherited genetic contribution to the risk of getting breast cancer For immediate release: October 23, 2017 Boston, MA – Two large genome-wide association studies of thousands of women have identified…