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A system for phenotype harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) program

Authors :
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
Universitat Politècnica de Catalunya. COSDA-UPC - COmpositional and Spatial Data Analysis
Source :
UPCommons. Portal del coneixement obert de la UPC, Universitat Politècnica de Catalunya (UPC), American Journal of Epidemiology, American journal of epidemiology, vol 190, iss 10
Publication Year :
2021

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.

Details

Language :
English
Database :
OpenAIRE
Journal :
UPCommons. Portal del coneixement obert de la UPC, Universitat Politècnica de Catalunya (UPC), American Journal of Epidemiology, American journal of epidemiology, vol 190, iss 10
Accession number :
edsair.doi.dedup.....0380088474cfe1cc5218a3fad8da984a