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GWAS Study

Multi-ancestry genome- and phenome-wide association studies of diverticular disease in electronic health records with natural language processing enriched phenotyping algorithm.

Joo YY, Pacheco JA, Thompson WK et al.

37196047 PubMed ID
GWAS Study Type
21777 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

JY
Joo YY
PJ
Pacheco JA
TW
Thompson WK
RL
Rasmussen-Torvik LJ
RL
Rasmussen LV
LF
Lin FTJ
AM
Andrade M
BK
Borthwick KM
BE
Bottinger E
CA
Cagan A
CD
Carrell DS
DJ
Denny JC
ES
Ellis SB
GO
Gottesman O
LJ
Linneman JG
PJ
Pathak J
PP
Peissig PL
SN
Shang N
TG
Tromp G
VA
Veerappan A
SM
Smith ME
CR
Chisholm RL
GA
Gawron AJ
HM
Hayes MG
KA
Kho AN
Chapter II

Abstract

Summary of the research findings

Objective: Diverticular disease (DD) is one of the most prevalent conditions encountered by gastroenterologists, affecting ~50% of Americans before the age of 60. Our aim was to identify genetic risk variants and clinical phenotypes associated with DD, leveraging multiple electronic health record (EHR) data sources of 91,166 multi-ancestry participants with a Natural Language Processing (NLP) technique.

12,577 European ancestry, African ancestry, NR cases, 9,200 European ancestry, African ancestry, NR controls

Chapter III

Study Statistics

Key metrics and study information

21777
Total Participants
GWAS
Study Type
No
Replicated
European, African unspecified, NR
Ancestry
Chapter IV

AI-Generated Summary

AI-generated by DNAGENICS

Independent AI summary of health and genetic findings from the published study

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