A System for Phenotype Harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program

Adrienne M Stilp, Leslie S Emery, Jai G Broome, Erin J Buth, Alyna T Khan, Cecelia A Laurie, Fei Fei Wang, Quenna Wong, Dongquan Chen, Catherine M D'Augustine, Nancy L Heard-Costa, Chancellor R Hohensee, William Craig Johnson, Lucia D Juarez, Jingmin Liu, Karen M Mutalik, Laura M Raffield, Kerri L Wiggins, Paul S de Vries, Tanika N KellyCharles 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

Research output: Contribution to journalArticlepeer-review

Abstract

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase 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 program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 studies per phenotype (participants recruited 1948-2012). 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 code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.

Original languageEnglish (US)
JournalAmerican journal of epidemiology
DOIs
StatePublished - 2021

Bibliographical note

© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

PubMed: MeSH publication types

  • Journal Article

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