1. A system for phenotype harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) program
- Author
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Tanika N. Kelly, May E Montasser, Alyna T. Khan, Laura M. Raffield, Carla Wilson, Elizabeth C. Oelsner, Kerri L. Wiggins, Ming-Huei Chen, Gina M. Peloso, Adolfo Correa, Andrew D. Johnson, Donna K. Arnett, Xiuqing Guo, Jai G. Broome, Daniel E. Weeks, Rebecca D. Jackson, Lucia Juarez, Stephen T. McGarvey, Pradeep Natarajan, Braxton D. Mitchell, Kent D. Taylor, Bruce M. Psaty, Santhi K Ganesh, Cathy C. Laurie, Nicola L. Hawley, Leslie S. Emery, Adrienne M. Stilp, Alanna C. Morrison, Jennifer A Smith, Charles Kooperberg, Catherine M. D’Augustine, Jan Graffelman, Paul S. de Vries, Chancellor Hohensee, Sharon L R Kardia, Patricia A Peyser, Wan-Ling Hsu, Erin J Buth, Kathleen C. Barnes, Susan R. Heckbert, Ramachandran S. Vasan, Nathan Pankratz, Karen M. Mutalik, Quenna Wong, Brian E. Cade, Jingmin Liu, Joshua C. Bis, Cecelia A. Laurie, Kari E. North, Fei Fei Wang, Mariza de Andrade, Nancy L. Heard-Costa, William Craig Johnson, L. Adrienne Cupples, Scott T. Weiss, Seyed Mehdi Nouraie, Patrick T. Ellinor, Jerome I. Rotter, Weiniu Gan, Shannon Kelly, Stephen S. Rich, Cashell E. Jaquish, Dongquan Chen, Nora Franceschini, Lisa R. Yanek, Jiwon Lee, Alexander P. Reiner, Megan L. Grove, Stella Aslibekyan, Myriam Fornage, Lawrence F Bielak, Rasika A. Mathias, Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa, and Universitat Politècnica de Catalunya. COSDA-UPC - COmpositional and Spatial Data Analysis
- Subjects
0301 basic medicine ,Program evaluation ,Computer science ,Epidemiology ,common data elements ,hematologic disease ,Matemàtiques i estadística::Matemàtica aplicada a les ciències [Àrees temàtiques de la UPC] ,Medical and Health Sciences ,Mathematical Sciences ,0302 clinical medicine ,Documentation ,cardiovascular disease ,and Blood Institute (U.S.) ,030212 general & internal medicine ,Phenomics ,Precision Medicine ,Lung ,lung diseases ,Sleep-wake disorders ,phenotypes ,92 Biology and other natural sciences::92B Mathematical biology in general [Classificació AMS] ,Common data elements ,Cardiovascular disease ,Phenotype ,Phenotypes ,Biomatemàtica ,Information Dissemination ,Harmonization ,62 Statistics::62D05 Sampling theory, sample surveys [Classificació AMS] ,Hematologic disease ,03 medical and health sciences ,Data Aggregation ,Clinical Research ,Controlled vocabulary ,Genetics ,Humans ,AcademicSubjects/MED00860 ,sleep-wake disorders ,Sampling (Statistics) ,Genetic Association Studies ,Lung diseases ,Biomathematics ,Data collection ,Study Design ,Matemàtiques i estadística::Estadística aplicada::Estadística biosanitària [Àrees temàtiques de la UPC] ,Information dissemination ,Human Genome ,National Heart ,Precision medicine ,Data science ,United States ,030104 developmental biology ,Good Health and Well Being ,National Heart, Lung, and Blood Institute (U.S.) ,Mostreig (Estadística) ,Program Evaluation - 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.
- Published
- 2021