Systematic replication of smoking disease associations using survey responses and EHR data in the All of Us Research Program

Author:

Schlueter David J12,Sulieman Lina3,Mo Huan14ORCID,Keaton Jacob M1,Ferrara Tracey M1,Williams Ariel1,Qian Jun3,Stubblefield Onajia1,Zeng Chenjie1,Tran Tam C14,Bastarache Lisa3,Dai Jian1,Babbar Anav1,Ramirez Andrea15,Goleva Slavina B1,Denny Joshua C1

Affiliation:

1. Precision Health Informatics Section, National Human Genome Research Institute, National Institutes of Health , Bethesda, MD, United States

2. Department of Health and Society, University of Toronto , Scarborough, Toronto, ON, Canada

3. Department of Biomedical Informatics, Vanderbilt University Medical Center , Nashville, TN, United States

4. The Cohort Analytics Core (CAC), Center for Precision Health Research, National Human Genome Research Institute , Bethesda, MD, USA

5. Department of Medicine, Vanderbilt University Medical Center , Nashville, TN, United States

Abstract

Abstract Objective The All of Us Research Program (All of Us) aims to recruit over a million participants to further precision medicine. Essential to the verification of biobanks is a replication of known associations to establish validity. Here, we evaluated how well All of Us data replicated known cigarette smoking associations. Materials and Methods We defined smoking exposure as follows: (1) an EHR Smoking exposure that used International Classification of Disease codes; (2) participant provided information (PPI) Ever Smoking; and, (3) PPI Current Smoking, both from the lifestyle survey. We performed a phenome-wide association study (PheWAS) for each smoking exposure measurement type. For each, we compared the effect sizes derived from the PheWAS to published meta-analyses that studied cigarette smoking from PubMed. We defined two levels of replication of meta-analyses: (1) nominally replicated: which required agreement of direction of effect size, and (2) fully replicated: which required overlap of confidence intervals. Results PheWASes with EHR Smoking, PPI Ever Smoking, and PPI Current Smoking revealed 736, 492, and 639 phenome-wide significant associations, respectively. We identified 165 meta-analyses representing 99 distinct phenotypes that could be matched to EHR phenotypes. At P < .05, 74 were nominally replicated and 55 were fully replicated. At P < 2.68 × 10−5 (Bonferroni threshold), 58 were nominally replicated and 40 were fully replicated. Discussion Most phenotypes found in published meta-analyses associated with smoking were nominally replicated in All of Us. Both survey and EHR definitions for smoking produced similar results. Conclusion This study demonstrated the feasibility of studying common exposures using All of Us data.

Funder

National Human Genome Research Institute

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

Reference182 articles.

1. Mendelian randomization case-control PheWAS in UK Biobank shows evidence of causality for smoking intensity in 28 distinct clinical conditions;King,2020

2. Mortality in relation to smoking: 50 years’ observations on male British doctors;Doll;BMJ,2004

3. The “All of Us” Research Program;Denny;N Engl J Med,2019

4. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age;Sudlow;PLoS Med,2015

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3