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GWAS Study

Polygenic risk score, genome-wide association, and gene set analyses of cognitive domain deficits in schizophrenia.

Nakahara S, Medland S, Turner JA et al.

29907492 PubMed ID
GWAS Study Type
263 Participants
108 Views
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

NS
Nakahara S
MS
Medland S
TJ
Turner JA
CV
Calhoun VD
LK
Lim KO
MB
Mueller BA
BJ
Bustillo JR
OD
O'Leary DS
VJ
Vaidya JG
MS
McEwen S
VJ
Voyvodic J
BA
Belger A
MD
Mathalon DH
FJ
Ford JM
GG
Guffanti G
MF
Macciardi F
PS
Potkin SG
VE
van Erp TGM
Chapter II

Abstract

Summary of the research findings

This study assessed genetic contributions to six cognitive domains, identified by the MATRICS Cognitive Consensus Battery as relevant for schizophrenia, cognition-enhancing, clinical trials. Psychiatric Genomics Consortium Schizophrenia polygenic risk scores showed significant negative correlations with each cognitive domain. Genome-wide association analyses identified loci associated with attention/vigilance (rs830786 within HNF4G), verbal memory (rs67017972 near NDUFS4), and reasoning/problem solving (rs76872642 within HDAC9). Gene set analysis identified unique and shared genes across cognitive domains. These findings suggest involvement of common and unique mechanisms across cognitive domains and may contribute to the discovery of new therapeutic targets to treat cognitive deficits in schizophrenia.

2 Alaskan native ancestry schizophrenia cases, 18 Asian ancestry schizophrenia cases, 20 African American schizophrenia cases, 1 Native Hawaiian ancestry schizophrenia cases, 86 European ancestry schizophrenia cases, 2 Alaskan native ancestry controls, 10 Asian ancestry controls, 17 African American controls, 1 Native Hawaiian ancestry controls, 106 European ancestry controls

Chapter III

Study Statistics

Key metrics and study information

263
Total Participants
GWAS
Study Type
No
Replicated
Native American, Oceanian, Asian unspecified, African American or Afro-Caribbean, European
Ancestry
Chapter IV

AI-Generated Summary

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