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 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

8 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1977-1992
Number of pages16
JournalAmerican journal of epidemiology
Volume190
Issue number10
DOIs
StatePublished - 2021
Externally publishedYes

Keywords

  • Cardiovascular disease
  • Common data elements
  • Hematologic disease
  • Information dissemination
  • Lung diseases
  • Phenotypes
  • Sleep-wake disorders

ASJC Scopus subject areas

  • Epidemiology

Fingerprint

Dive into the research topics of 'A system for phenotype harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) program'. Together they form a unique fingerprint.

Cite this