A System for Phenotype Harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Program
Adrienne M. Stilp, Leslie S. Emery, Jai Broome, Erin Buth, Alyna Khan, Cecelia Laurie, Fei Fei Wang, Quenna Wong, Dongquan Chen, Catherine M. D’Augustine, Nancy L. Heard‐Costa, Chancellor Hohensee, W. Craig Johnson, Lucia Juarez, Jingmin Liu, Karen Mutalik, Laura M. Raffield, Kerri L. Wiggins, Paul S. de Vries, Tanika N. Kelly, Charles Kooperberg, Pradeep Natarajan, Gina M. Peloso, Patricia A. Peyser, Alex P. Reiner, Donna K. Arnett, Stella Aslibekyan, Kathleen C. Barnes, Lawrence F. Bielak, Joshua C Bis, Brian E. Cade, Ming‐Huei Chen, Adolfo Correa, L. Adrienne Cupples, Mariza de Andrade, Patrick T. Ellinor, Myriam Fornage, Nora Franceschini, Weiniu Gan, Santhi K. Ganesh, Jan Graffelman, Megan L. Grove, Xiuqing Guo, Nicola L. Hawley, Wan‐Ling Hsu, Rebecca D. Jackson, Cashell E. Jaquish, Andrew D. Johnson, Sharon L. R. Kardia, Shannon Kelly, Jiwon Lee, Rasika A. Mathias, Stephen T. McGarvey, Braxton D. Mitchell, May E. Montasser, Alanna C. Morrison, Kari E. North, Seyed Mehdi Nouraie, Elizabeth C. Oelsner, Nathan Pankratz, Stephen S. Rich, Jerome I. Rotter, Jennifer A. Smith, Kent D. Taylor, Ramachandran S. Vasan, Daniel E. Weeks, Scott T. Weiss, Carla G. Wilson, Lisa R. Yanek, Bruce M. Psaty, Susan R. Heckbert, Cathy C. Laurie
Abstract
Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948-2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms.