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GWAS Study

Associations between common genetic variants and income provide insights about the socio-economic health gradient.

Kweon H, Burik CAP, Ning Y et al.

39875632 PubMed ID
GWAS Study Type
72601 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

KH
Kweon H
BC
Burik CAP
NY
Ning Y
AR
Ahlskog R
XC
Xia C
AE
Abner E
BY
Bao Y
BL
Bhatta L
FT
Faquih TO
DF
de Feijter M
FP
Fisher P
GA
Gelemanović A
GA
Giannelis A
HJ
Hottenga JJ
KB
Khalili B
LY
Lee Y
LR
Li-Gao R
MJ
Masso J
MR
Myhre R
PT
Palviainen T
RC
Rietveld CA
TA
Teumer A
VR
Verweij RM
WE
Willoughby EA
AE
Agerbo E
BS
Bergmann S
BD
Boomsma DI
BA
Børglum AD
BB
Brumpton BM
DN
Davies NM
ET
Esko T
GS
Gordon SD
HG
Homuth G
IM
Ikram MA
JM
Johannesson M
KJ
Kaprio J
KM
Kidd MP
KZ
Kutalik Z
KA
Kwong ASF
LJ
Lee JJ
LA
Luik AI
MP
Magnus P
MP
Marques-Vidal P
MN
Martin NG
MD
Mook-Kanamori DO
MP
Mortensen PB
OS
Oskarsson S
PE
Pedersen EM
PO
Polašek O
RF
Rosendaal FR
SM
Smart MC
SH
Snieder H
VD
van der Most PJ
VP
Vollenweider P
VH
Völzke H
WG
Willemsen G
BJ
Beauchamp JP
DT
DiPrete TA
LR
Linnér RK
LQ
Lu Q
MT
Morris TT
OA
Okbay A
HK
Harden KP
AA
Abdellaoui A
HW
Hill WD
DV
de Vlaming R
BD
Benjamin DJ
KP
Koellinger PD
Chapter II

Abstract

Summary of the research findings

We conducted a genome-wide association study on income among individuals of European descent (N = 668,288) to investigate the relationship between socio-economic status and health disparities. We identified 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes (the Income Factor). Our polygenic index captures 1-5% of income variance, with only one fourth due to direct genetic effects. A phenome-wide association study using this index showed reduced risks for diseases including hypertension, obesity, type 2 diabetes, depression, asthma and back pain. The Income Factor had a substantial genetic correlation (0.92, s.e. = 0.006) with educational attainment. Accounting for the genetic overlap of educational attainment with income revealed that the remaining genetic signal was linked to better mental health but reduced physical health and increased risky behaviours such as drinking and smoking. These findings highlight the complex genetic influences on income and health.

72,601 European ancestry individuals

Chapter III

Study Statistics

Key metrics and study information

72601
Total Participants
GWAS
Study Type
No
Replicated
European
Ancestry
Netherlands, U.S., Norway, Finland, U.K., Australia, Switzerland, Germany, Croatia, Estonia, Denmark
Recruitment Country
Chapter IV

Analysis

Comprehensive review of health and genetic findings

Important Disclaimer: This review has been performed semi-automatically and is provided for informational purposes only. While we strive for accuracy, this analysis may contain errors, omissions, or misinterpretations of the original research. DNA Genics disclaims all liability for any inaccuracies, errors, or consequences arising from the use of this information. Users should independently verify all information and consult original research publications before making any decisions based on this content. This analysis is not intended as a substitute for professional scientific review or medical advice.

Analysis In Progress

Our analysis of this publication is currently being prepared. Please check back soon for comprehensive insights into the health and genetic findings discussed in this research.