Rochester, Minnesota




The complex genetic basis of common human diseases and traits necessitates the development of new statistical methods to address new questions and new types of data. Hence, the main focus of the Statistical Genetics and Genetic Epidemiology Laboratory directed by Daniel J. Schaid, Ph.D., is the development and evaluation of statistical methods for the analysis of genetic data.

Much of Dr. Schaid's work is motivated by ongoing collaborations on projects that focus on the genetics of complex and common diseases, such as breast and prostate cancers and cardiovascular disease, along with the genetics of immune response. General issues addressed by Dr. Schaid's research are study design, data analysis and computational methods, and the use of genetic information to predict disease or response to treatments. As a result of Dr. Schaid's work, new software is developed and distributed to the research community.

Focus areas

  • Quantitative methods for genetic epidemiology. The overall objectives of this research are to facilitate analyses of complex genetic data by developing innovative statistical methods and software for biomedical researchers. A primary focus is the development of methods to integrate different types of complex data, a type of mediation analysis such as linking genomics with intermediate traits, and linking these intermediate traits with disease outcomes. Another research focus is the development of methods to use single-nucleotide polymorphisms from genome-wide association studies to predict disease (polygenic risk scores).
  • Collaborative genetic analyses. Collaborations are key to research progress, and Dr. Schaid's collaborations cover many different diseases and types of genetic data. In general, Dr. Schaid seeks to understand the genetic causes of disease and how genes control the different ways people react to drugs used to treat their disease. New statistical methods and software developed by Dr. Schaid and his team are used to screen the genome for single genetic variants, variants grouped into genes, or even genes grouped into larger biological networks. Dr. Schaid expects that different views of the genome will provide insights into causes of disease and ways to best treat disease.
  • Prostate cancer. The major aims of this research program are to localize genetic susceptibility loci that increase the risk of prostate cancer and to analyze and characterize genes in the candidate regions to identify prostate cancer susceptibility genes. This program is conducted by international collaborations that compile large numbers of study participants to seek the many different genetic variants that influence the risk of prostate cancer.
  • Breast cancer. This research aims to evaluate how genes influence response to breast cancer treatment and how multiple genetic markers influence the likelihood of developing breast cancer.
  • Cardiovascular disease. As a co-investigator on the national Electronic Medical Records and Genomics (eMERGE) study, Dr. Schaid and his colleagues study the use of genetic risk scores for heart disease in diverse populations.
  • Vaccine research. Through studies of the immunogenetics of vaccine response in adults and children, the Vaccine Research Group aims to improve health around the world by pursuing challenges posed by infectious diseases and bioterrorism through clinical laboratory and epidemiologic vaccine research.

Significance to patient care

Finding genes that increase the risk of disease or impact how patients respond to therapies would have a dramatic impact on clinical practice. The immediate impact of using genetic information to predict common diseases will guide physicians and their patients on how best to screen for disease for early diagnosis or prevention.

Professional highlights

  • Chair, Department of Quantitative Health Sciences, Mayo Clinic, 2021-present
  • Fellow, American Association for Advancement of Science, 2021
  • Recipient, Curtis L. Carlson Family Professor of Genomics Research, Mayo Clinic, 2009-present
  • Chair, Genomics, Computational Biology and Technology Study Section, National Institutes of Health, 2007-2011
  • Member, Board of Scientific Counselors, National Cancer Institute, 2006-2011
  • Fellow, American Statistical Association, 2009
  • Recipient, Leadership Award, International Genetic Epidemiology Society, 2008
  • President, International Genetic Epidemiology Society, 2006
  • Editor-in-chief, Genetic Epidemiology, 2000-2005


Primary Appointment

  1. Consultant, Division of Computational Biology, Department of Quantitative Health Sciences
  2. Enterprise Chair, Department of Quantitative Health Sciences

Academic Rank

  1. Professor of Biostatistics


  1. Mayo Clinic Scholar - Statistical Genetics Department of Biometry and Genetics, Louisiana State University Medical Center
  2. PhD - Biostatistics University of Pittsburgh, Pittsburgh
  3. MS - Human Genetics University of Pittsburgh, Pittsburgh
  4. BS - Biology St Vincent College

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