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GWAS Study

Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction.

Schormair B, Zhao C, Bell S et al.

38839884 PubMed ID
GWAS Study Type
27050 Participants
135 Views
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

SB
Schormair B
ZC
Zhao C
BS
Bell S
DM
Didriksen M
NM
Nawaz MS
SN
Schandra N
SA
Stefani A
HB
Högl B
DY
Dauvilliers Y
BC
Bachmann CG
KD
Kemlink D
SK
Sonka K
PW
Paulus W
TC
Trenkwalder C
OW
Oertel WH
HM
Hornyak M
TM
Teder-Laving M
MA
Metspalu A
HG
Hadjigeorgiou GM
PO
Polo O
FI
Fietze I
RO
Ross OA
WZ
Wszolek ZK
IA
Ibrahim A
BM
Bergmann M
KV
Kittke V
HP
Harrer P
DJ
Dowsett J
CS
Chenini S
OS
Ostrowski SR
SE
Sørensen E
EC
Erikstrup C
PO
Pedersen OB
TB
Topholm Bruun M
NK
Nielsen KR
BA
Butterworth AS
SN
Soranzo N
OW
Ouwehand WH
RD
Roberts DJ
DJ
Danesh J
BB
Burchell B
FN
Furlotte NA
NP
Nandakumar P
EC
Earley CJ
OW
Ondo WG
XL
Xiong L
DA
Desautels A
PM
Perola M
VP
Vodicka P
DC
Dina C
SM
Stoll M
FA
Franke A
LW
Lieb W
SA
Stewart AFR
SS
Shah SH
GC
Gieger C
PA
Peters A
RD
Rye DB
RG
Rouleau GA
BK
Berger K
SH
Stefansson H
UH
Ullum H
SK
Stefansson K
HD
Hinds DA
DA
Di Angelantonio E
OK
Oexle K
WJ
Winkelmann J
Chapter II

Abstract

Summary of the research findings

Restless legs syndrome (RLS) affects up to 10% of older adults. Their healthcare is impeded by delayed diagnosis and insufficient treatment. To advance disease prediction and find new entry points for therapy, we performed meta-analyses of genome-wide association studies in 116,647 individuals with RLS (cases) and 1,546,466 controls of European ancestry. The pooled analysis increased the number of risk loci eightfold to 164, including three on chromosome X. Sex-specific meta-analyses revealed largely overlapping genetic predispositions of the sexes (rg = 0.96). Locus annotation prioritized druggable genes such as glutamate receptors 1 and 4, and Mendelian randomization indicated RLS as a causal risk factor for diabetes. Machine learning approaches combining genetic and nongenetic information performed best in risk prediction (area under the curve (AUC) = 0.82-0.91). In summary, we identified targets for drug development and repurposing, prioritized potential causal relationships between RLS and relevant comorbidities and risk factors for follow-up and provided evidence that nonlinear interactions are likely relevant to RLS risk prediction.

7,248 European ancestry cases, 19,802 European ancestry controls

Chapter III

Study Statistics

Key metrics and study information

27050
Total Participants
GWAS
Study Type
Yes
Replicated
29,028 cases, 398,815 controls
Replication Participants
European
Ancestry
Greece, Canada, Austria, Czech Republic, U.S., Finland, France, Germany, Estonia, U.K.
Recruitment Country
Chapter IV

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