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GWAS Study

Exome Chip Analysis Identifies Low-Frequency and Rare Variants in MRPL38 for White Matter Hyperintensities on Brain Magnetic Resonance Imaging.

Jian X, Satizabal CL, Smith AV et al.

30002152 PubMed ID
GWAS Study Type
11911 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

JX
Jian X
SC
Satizabal CL
SA
Smith AV
WK
Wittfeld K
BJ
Bis JC
SJ
Smith JA
HF
Hsu FC
NK
Nho K
HE
Hofer E
HS
Hagenaars SP
NP
Nyquist PA
MA
Mishra A
AH
Adams HHH
LS
Li S
TA
Teumer A
ZW
Zhao W
FB
Freedman BI
SY
Saba Y
YL
Yanek LR
CG
Chauhan G
VB
van Buchem MA
CM
Cushman M
RN
Royle NA
BR
Bryan RN
NW
Niessen WJ
WB
Windham BG
DA
DeStefano AL
HM
Habes M
HS
Heckbert SR
PN
Palmer ND
LC
Lewis CE
EG
Eiriksdottir G
MP
Maillard P
MR
Mathias RA
HG
Homuth G
VM
Valdés-Hernández MDC
DJ
Divers J
BA
Beiser AS
LS
Langner S
RK
Rice KM
BM
Bastin ME
YQ
Yang Q
MJ
Maldjian JA
SJ
Starr JM
SS
Sidney S
RS
Risacher SL
UA
Uitterlinden AG
GV
Gudnason VG
NM
Nauck M
RJ
Rotter JI
SP
Schreiner PJ
BE
Boerwinkle E
VD
van Duijn CM
MB
Mazoyer B
VS
von Sarnowski B
GR
Gottesman RF
LD
Levy D
SS
Sigurdsson S
VM
Vernooij MW
TS
Turner ST
SR
Schmidt R
WJ
Wardlaw JM
PB
Psaty BM
MT
Mosley TH
DC
DeCarli CS
SA
Saykin AJ
BD
Bowden DW
BD
Becker DM
DI
Deary IJ
SH
Schmidt H
KS
Kardia SLR
IM
Ikram MA
DS
Debette S
GH
Grabe HJ
LW
Longstreth WT
SS
Seshadri S
LL
Launer LJ
FM
Fornage M
Chapter II

Abstract

Summary of the research findings

Background and Purpose- White matter hyperintensities (WMH) on brain magnetic resonance imaging are typical signs of cerebral small vessel disease and may indicate various preclinical, age-related neurological disorders, such as stroke. Though WMH are highly heritable, known common variants explain a small proportion of the WMH variance. The contribution of low-frequency/rare coding variants to WMH burden has not been explored. Methods- In the discovery sample we recruited 20 719 stroke/dementia-free adults from 13 population-based cohort studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, among which 17 790 were of European ancestry and 2929 of African ancestry. We genotyped these participants at ≈250 000 mostly exonic variants with Illumina HumanExome BeadChip arrays. We performed ethnicity-specific linear regression on rank-normalized WMH in each study separately, which were then combined in meta-analyses to test for association with single variants and genes aggregating the effects of putatively functional low-frequency/rare variants. We then sought replication of the top findings in 1192 adults (European ancestry) with whole exome/genome sequencing data from 2 independent studies. Results- At 17q25, we confirmed the association of multiple common variants in TRIM65, FBF1, and ACOX1 ( P<6×10-7). We also identified a novel association with 2 low-frequency nonsynonymous variants in MRPL38 (lead, rs34136221; PEA=4.5×10-8) partially independent of known common signal ( PEA(conditional)=1.4×10-3). We further identified a locus at 2q33 containing common variants in NBEAL1, CARF, and WDR12 (lead, rs2351524; Pall=1.9×10-10). Although our novel findings were not replicated because of limited power and possible differences in study design, meta-analysis of the discovery and replication samples yielded stronger association for the 2 low-frequency MRPL38 variants ( Prs34136221=2.8×10-8). Conclusions- Both common and low-frequency/rare functional variants influence WMH. Larger replication and experimental follow-up are essential to confirm our findings and uncover the biological causal mechanisms of age-related WMH.

7, 790 European ancestry individuals, 2,929 African American individuals

Chapter III

Study Statistics

Key metrics and study information

11911
Total Participants
GWAS
Study Type
Yes
Replicated
1,192 European ancestry individuals
Replication Participants
European, African American or Afro-Caribbean
Ancestry
Finland, Germany, Italy, U.S.
Recruitment Country
Chapter IV

Analysis

Comprehensive review of health and genetic findings

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