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GWAS Study

Genome-wide characterization of circulating metabolic biomarkers.

Karjalainen MK, Karthikeyan S, Oliver-Williams C et al.

38448586 PubMed ID
GWAS Study Type
136016 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

KM
Karjalainen MK
KS
Karthikeyan S
OC
Oliver-Williams C
SE
Sliz E
AE
Allara E
FW
Fung WT
SP
Surendran P
ZW
Zhang W
JP
Jousilahti P
KK
Kristiansson K
SV
Salomaa V
GM
Goodwin M
HD
Hughes DA
BM
Boehnke M
FS
Fernandes Silva L
YX
Yin X
MA
Mahajan A
NM
Neville MJ
VZ
van Zuydam NR
DM
de Mutsert R
LR
Li-Gao R
MD
Mook-Kanamori DO
DA
Demirkan A
LJ
Liu J
NR
Noordam R
TS
Trompet S
CZ
Chen Z
KC
Kartsonaki C
LL
Li L
LK
Lin K
HF
Hagenbeek FA
HJ
Hottenga JJ
PR
Pool R
IM
Ikram MA
VM
van Meurs J
HT
Haller T
MY
Milaneschi Y
KM
Kähönen M
MP
Mishra PP
JP
Joshi PK
ME
Macdonald-Dunlop E
MM
Mangino M
ZJ
Zierer J
AI
Acar IE
HC
Hoyng CB
LY
Lechanteur YTE
FL
Franke L
KA
Kurilshikov A
ZA
Zhernakova A
BM
Beekman M
VD
van den Akker EB
KI
Kolcic I
PO
Polasek O
RI
Rudan I
GC
Gieger C
WM
Waldenberger M
AF
Asselbergs FW
HC
Hayward C
FJ
Fu J
DH
den Hollander AI
MC
Menni C
ST
Spector TD
WJ
Wilson JF
LT
Lehtimäki T
RO
Raitakari OT
PB
Penninx BWJH
ET
Esko T
WR
Walters RG
JJ
Jukema JW
SN
Sattar N
GM
Ghanbari M
WV
Willems van Dijk K
KF
Karpe F
MM
McCarthy MI
LM
Laakso M
JM
Järvelin MR
TN
Timpson NJ
PM
Perola M
KJ
Kooner JS
CJ
Chambers JC
VD
van Duijn C
SP
Slagboom PE
BD
Boomsma DI
DJ
Danesh J
AM
Ala-Korpela M
BA
Butterworth AS
KJ
Kettunen J
Chapter II

Abstract

Summary of the research findings

Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism1-7. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases8-11. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases.

4,435 East Asian ancestry individuals, 11,340 South Asian ancestry individuals, 120,241 European ancestry individuals

Chapter III

Study Statistics

Key metrics and study information

136016
Total Participants
GWAS
Study Type
No
Replicated
East Asian, South Asian, European
Ancestry
China, U.K., Netherlands, Republic of Ireland, Finland, Germany, Croatia, Estonia
Recruitment Country
Chapter IV

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