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GWAS Study

Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis.

Wheeler E, Leong A, Liu CT et al.

28898252 PubMed ID
GWAS Study Type
158869 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

WE
Wheeler E
LA
Leong A
LC
Liu CT
HM
Hivert MF
SR
Strawbridge RJ
PC
Podmore C
LM
Li M
YJ
Yao J
SX
Sim X
HJ
Hong J
CA
Chu AY
ZW
Zhang W
WX
Wang X
CP
Chen P
MN
Maruthur NM
PB
Porneala BC
SS
Sharp SJ
JY
Jia Y
KE
Kabagambe EK
CL
Chang LC
CW
Chen WM
EC
Elks CE
ED
Evans DS
FQ
Fan Q
GF
Giulianini F
GM
Go MJ
HJ
Hottenga JJ
HY
Hu Y
JA
Jackson AU
KS
Kanoni S
KY
Kim YJ
KM
Kleber ME
LC
Ladenvall C
LC
Lecoeur C
LS
Lim SH
LY
Lu Y
MA
Mahajan A
MC
Marzi C
NM
Nalls MA
NP
Navarro P
NI
Nolte IM
RL
Rose LM
RD
Rybin DV
SS
Sanna S
SY
Shi Y
SD
Stram DO
TF
Takeuchi F
TS
Tan SP
VD
van der Most PJ
VV
Van Vliet-Ostaptchouk JV
WA
Wong A
YL
Yengo L
ZW
Zhao W
GA
Goel A
ML
Martinez Larrad MT
RD
Radke D
SP
Salo P
TT
Tanaka T
VI
van Iperen EPA
AG
Abecasis G
AS
Afaq S
AB
Alizadeh BZ
BA
Bertoni AG
BA
Bonnefond A
BY
Böttcher Y
BE
Bottinger EP
CH
Campbell H
CO
Carlson OD
CC
Chen CH
CY
Cho YS
GW
Garvey WT
GC
Gieger C
GM
Goodarzi MO
GH
Grallert H
HA
Hamsten A
HC
Hartman CA
HC
Herder C
HC
Hsiung CA
HJ
Huang J
IM
Igase M
IM
Isono M
KT
Katsuya T
KC
Khor CC
KW
Kiess W
KK
Kohara K
KP
Kovacs P
LJ
Lee J
LW
Lee WJ
LB
Lehne B
LH
Li H
LJ
Liu J
LS
Lobbens S
LJ
Luan J
LV
Lyssenko V
MT
Meitinger T
MT
Miki T
MI
Miljkovic I
MS
Moon S
MA
Mulas A
MG
Müller G
MM
Müller-Nurasyid M
NR
Nagaraja R
NM
Nauck M
PJ
Pankow JS
PO
Polasek O
PI
Prokopenko I
RP
Ramos PS
RL
Rasmussen-Torvik L
RW
Rathmann W
RS
Rich SS
RN
Robertson NR
RM
Roden M
RR
Roussel R
RI
Rudan I
SR
Scott RA
SW
Scott WR
SB
Sennblad B
SD
Siscovick DS
SK
Strauch K
SL
Sun L
SM
Swertz M
TS
Tajuddin SM
TK
Taylor KD
TY
Teo YY
TY
Tham YC
TA
Tönjes A
WN
Wareham NJ
WG
Willemsen G
WT
Wilsgaard T
HA
Hingorani AD
EJ
Egan J
FL
Ferrucci L
HG
Hovingh GK
JA
Jula A
KM
Kivimaki M
KM
Kumari M
NI
Njølstad I
PC
Palmer CNA
SR
Serrano Ríos M
SM
Stumvoll M
WH
Watkins H
AT
Aung T
BM
Blüher M
BM
Boehnke M
BD
Boomsma DI
BS
Bornstein SR
CJ
Chambers JC
CD
Chasman DI
CY
Chen YI
CY
Chen YT
CC
Cheng CY
CF
Cucca F
DG
de Geus EJC
DP
Deloukas P
EM
Evans MK
FM
Fornage M
FY
Friedlander Y
FP
Froguel P
GL
Groop L
GM
Gross MD
HT
Harris TB
HC
Hayward C
HC
Heng CK
IE
Ingelsson E
KN
Kato N
KB
Kim BJ
KW
Koh WP
KJ
Kooner JS
KA
Körner A
KD
Kuh D
KJ
Kuusisto J
LM
Laakso M
LX
Lin X
LY
Liu Y
LR
Loos RJF
MP
Magnusson PKE
MW
März W
MM
McCarthy MI
OA
Oldehinkel AJ
OK
Ong KK
PN
Pedersen NL
PM
Pereira MA
PA
Peters A
RP
Ridker PM
SC
Sabanayagam C
SM
Sale M
SD
Saleheen D
SJ
Saltevo J
SP
Schwarz PE
SW
Sheu WHH
SH
Snieder H
ST
Spector TD
TY
Tabara Y
TJ
Tuomilehto J
VD
van Dam RM
WJ
Wilson JG
WJ
Wilson JF
WB
Wolffenbuttel BHR
WT
Wong TY
WJ
Wu JY
YJ
Yuan JM
ZA
Zonderman AB
SN
Soranzo N
GX
Guo X
RD
Roberts DJ
FJ
Florez JC
SR
Sladek R
DJ
Dupuis J
MA
Morris AP
TE
Tai ES
SE
Selvin E
RJ
Rotter JI
LC
Langenberg C
BI
Barroso I
MJ
Meigs JB
Chapter II

Abstract

Summary of the research findings

Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.

88,355 European ancestry individuals,18,472 East Asian ancestry individuals, 7,572 South Asian ancestry individuals, 7,564 African American individuals

Chapter III

Study Statistics

Key metrics and study information

158869
Total Participants
GWAS
Study Type
Yes
Replicated
33,238 European ancestry individuals, 2,366 East Asian ancestry individuals, 1,302 South Asian ancestry individuals
Replication Participants
European, African American or Afro-Caribbean, South Asian, East Asian
Ancestry
U.S., France, Germany, Netherlands, Finland, Iceland, Sweden, U.K., Croatia, Italy, Spain, Norway, Singapore, China, Japan, Republic of Korea, Taiwan, Pakistan
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.