Portrait of Patrick Turley on the USC campus

Patrick Turley, PhD

Associate Professor (Research) of Economics

I study social science genomics, statistical genetics, and econometrics — developing methods that integrate genetic data into social science research and examining how education shapes health and economic outcomes.

Curriculum Vitae Google Scholar GitHub X Bsky Email

Research Fields

  • Social science genomics
  • Statistical genetics
  • Econometrics

Education

  • PhD, Economics Harvard University, 2016 NSF Graduate Research Fellow
  • BS, Mathematics & Economics Brigham Young University, 2010 Valedictorian, University Honors

Research Interests

Statistical Genetics & Genomic Methods

I develop methods for genetic discovery, polygenic prediction, and the analysis of large-scale genomic data — combining information across traits and populations, improving the interpretation of genome-wide association studies, and assessing the strengths and limits of polygenic scores. A recurring goal is building tools for concrete empirical problems: confounding, sample overlap, population structure, measurement error, and limited portability across ancestries.

Social, Behavioral & Health Genomics

I pair genetic data with econometric and quasi-experimental designs to study education, health, and aging. Much of this work examines how genetic associations vary across social and policy environments — including educational attainment, obesity, dementia, and later-life outcomes — using genetically informed designs to understand how environments shape the relationship between genetic risk and social or health outcomes.

Responsible Use of Polygenic Prediction

I study the scientific, clinical, and social implications of using polygenic scores in research and decision-making. I encourage careful and conservative interpretation of research results, emphasizing the challenges of communicating what genetic prediction can and cannot tell us. Relatedly, I have studied the benefits and risks of polygenic embryo screening and public attitudes toward genetic technologies.

Selected Publications

Full list on Google Scholar →

  1. Public views on polygenic screening of embryos

    Meyer, Tan, Benjamin, Laibson, Turley · Science, 2023

  2. Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

    Okbay, Wu, … Turley · Nature Genetics, 2022

  3. Problems with using polygenic scores to select embryos

    Turley, Meyer, Cesarini, … · New England Journal of Medicine, 2021

  4. Resource profile and user guide of the Polygenic Index Repository

    Becker, Burik, … Turley · Nature Human Behaviour, 2021

  5. Gene discovery and polygenic prediction from a 1.1-million-person GWAS of educational attainment

    Lee, Wedow, … Turley · Nature Genetics, 2018

  6. Multi-trait analysis of genome-wide association summary statistics using MTAG

    Turley, Walters, Maghzian, … · Nature Genetics, 2018

  7. Education can reduce health differences related to genetic risk of obesity

    Barcellos, Carvalho, Turley · PNAS, 2018

  8. Was that SMART? Institutional financial incentives and field of study

    Denning, Turley · Journal of Human Resources, 2017

  9. Distributional effects of education on health

    Barcellos, Carvalho, Turley · Journal of Human Resources, forthcoming

Selected Working Papers

  1. The effect of education on the relationship between genetics, early-life disadvantages, and later-life SES

    Barcellos, Carvalho, Turley · NBER Working Paper 28750

  2. Multi-ancestry meta-analysis yields novel genetic discoveries and ancestry-specific associations

    Turley, Martin, Goldman, … · bioRxiv

Teaching

  • Genoeconomics Visiting Faculty · University of Aarhus · 2019
  • Summer Institute in Social Science Genomics Faculty · Russell Sage Foundation · 2016, 2017, 2019
  • Microeconomic Theory Teaching Fellow (with Edward Glaeser) · Harvard University · 2012

Software & Resources

MTAG

Multi-Trait Analysis of GWAS — a Python tool that jointly analyzes summary statistics from genetically correlated traits to boost statistical power for gene discovery.

View on GitHub →

Polygenic Index Repository

A standardized resource of polygenic indices for social-science and health phenotypes, described in the Nature Human Behaviour resource profile.

SSGAC resources →

Contact

The best way to reach me is by email.

pturley@usc.edu

Center for Economic and Social Research
University of Southern California
635 Downey Way
Los Angeles, CA 90089-3332