Introduction: Genetic variants could aid in predicting antidiabetic drug response by associating them with markers of glucose control, such as glycated hemoglobin (HbA1c). However, pharmacogenetic implementation for antidiabetics is still under development, as the list of actionable markers is being populated and validated. This study explores potential associations between genetic variants and plasma levels of HbA1c in 100 patients under treatment with metformin. Methods: HbA1c was measured in a clinical chemistry analyzer (Roche), genotyping was performed in an Illumina-GSA array and data were analyzed using PLINK. Association and prediction models were developed using R and a 10-fold cross-validation approach. Results: We identified genetic variants on SLC47A1, SLC28A1, ABCG2, TBC1D4, and ARID5B that can explain up to 55% of the interindividual variability of HbA1c plasma levels in diabetic patients under treatment. Variants on SLC47A1, SLC28A1, and ABCG2 likely impact the pharmacokinetics (PK) of metformin, while the role of the two latter can be related to insulin resistance and regulation of adipogenesis. Conclusions: Our results confirm previous genetic associations and point to previously unassociated gene variants for metformin PK and glucose control.

1.
Chien
KL
,
Lin
HJ
,
Lee
BC
,
Hsu
HC
,
Chen
MF
.
Prediction model for high glycated hemoglobin concentration among ethnic Chinese in Taiwan
.
Cardiovasc Diabetol
.
2010
;
9
:
59
. .
2.
Goswami
S
,
Yee
SW
,
Xu
F
,
Sridhar
SB
,
Mosley
JD
,
Takahashi
A
,
A longitudinal HbA1c model elucidates genes linked to disease progression on metformin
.
Clin Pharmacol Ther
.
2016
;
100
(
5
):
537
47
. .
3.
Kleinberger
JW
,
Pollin
TI
.
Personalized medicine in diabetes mellitus: current opportunities and future prospects
.
Ann N Y Acad Sci
.
2015 Jun
;
1346
(
1
):
45
56
. .
4.
Mannino
GC
,
Andreozzi
F
,
Sesti
G
.
Pharmacogenetics of type 2 diabetes mellitus, the route toward tailored medicine
.
Diabetes Metab Res Rev
.
2019 Mar
;
35
(
3
):
e3109
. .
5.
Williams
LK
,
Padhukasahasram
B
,
Ahmedani
BK
,
Peterson
EL
,
Wells
KE
,
Burchard
EG
,
Differing effects of metformin on glycemic control by race-ethnicity
.
J Clin Endocrinol Metab
.
2014
;
99
(
9
):
3160
8
.
6.
Rena
G
,
Hardie
DG
,
Pearson
ER
.
The mechanisms of action of metformin
.
Diabetologia
.
2017 Sep 3
;
60
(
9
):
1577
85
. .
7.
Pawlyk
AC
,
Giacomini
KM
,
McKeon
C
,
Shuldiner
AR
,
Florez
JC
.
Metformin pharmacogenomics: current status and future directions
.
Diabetes
.
2014
;
63
(
8
):
2590
9
. .
8.
Florez
JC
.
The pharmacogenetics of metformin
.
Diabetologia
.
2017
;
60
(
9
):
1648
55
.
9.
Zolk
O
.
Current understanding of the pharmacogenomics of metformin
.
Clin Pharmacol Ther
.
2009
;
86
(
6
):
595
8
.
10.
Pearson
ER
.
Pharmacogenetics and target identification in diabetes
.
Current Opin Genet Dev
.
2018
;
50
:
68
73
.
11.
Zhou
K
,
Pedersen
HK
,
Dawed
AY
,
Pearson
ER
.
Pharmacogenomics in diabetes mellitus: insights into drug action and drug discovery
.
Nat Rev Endocrinol
.
2016 Jun 11
;
12
(
6
):
337
46
. .
12.
Gong
L
,
Goswami
S
,
Giacomini
KM
,
Altman
RB
,
Klein
TE
.
Metformin pathways: pharmacokinetics and pharmacodynamics
.
Pharmacogenet Genomics
.
2012 Nov
;
22
(
11
):
820
7
. .
13.
Rotroff
DM
,
Yee
SW
,
Zhou
K
,
Marvel
SW
,
Shah
HS
,
Jack
JR
,
Genetic variants in CPA6 and PRPF31 are associated with variation in response to metformin in individuals with type 2 diabetes
.
Diabetes
.
2018 Jul
;
67
(
7
):
1428
40
. .
14.
Williams
LK
,
Padhukasahasram
B
,
Ahmedani
BK
,
Peterson
EL
,
Wells
KE
,
González Burchard
E
,
Differing effects of metformin on glycemic control by race-ethnicity
.
J Clin Endocrinol Metab
.
2014 Sep
;
99
(
9
):
3160
8
. .
15.
Chan
P
,
Shao
L
,
Tomlinson
B
,
Zhang
Y
,
Liu
Z-M
.
Metformin transporter pharmacogenomics: insights into drug disposition: where are we now?
Expert Opin Drug Metab Toxicol
.
2018 Oct 30
:
1
11
.
16.
Sanchez-Ibarra
HE
,
Reyes-Cortes
LM
,
Jiang
XL
,
Luna-Aguirre
CM
,
Aguirre-Trevino
D
,
Morales-Alvarado
IA
,
Genotypic and phenotypic factors influencing drug response in Mexican patients with type 2 diabetes mellitus
.
Front Pharmacol
.
2018
;
9
:
320
. .
17.
Flannick
J
,
Mercader
JM
,
Fuchsberger
C
,
Udler
MS
,
Mahajan
A
,
Wessel
J
,
Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls
.
Nature
.
2019 Jun 22
;
570
(
7759
):
71
6
. .
18.
Ordelheide
AM
,
Hrabě de Angelis
M
,
Häring
HU
,
Staiger
H
.
Pharmacogenetics of oral antidiabetic therapy
.
Pharmacogenomics
.
2018 Apr
;
19
(
6
):
577
87
. .
19.
Alexander
DH
,
Lange
K
.
Enhancements to the ADMIXTURE algorithm for individual ancestry estimation
.
BMC Bioinformatics
.
2011 Dec 18
;
12
(
1
):
246
. .
20.
Purcell
S
,
Neale
B
,
Todd-Brown
K
,
Thomas
L
,
Ferreira
MA
,
Bender
D
,
PLINK: a tool set for whole-genome association and population-based linkage analyses
.
Am J Hum Genet
.
2007
;
81
(
3
):
559
75
. .
21.
R Core Team
.
R: a language and environment for statistical computing [Internet]
.
Vienna, Austria
:
R Foundation for Statistical Computing
;
2015
.
22.
Pruim
RJ
,
Welch
RP
,
Sanna
S
,
Teslovich
TM
,
Chines
PS
,
Gliedt
TP
,
LocusZoom: regional visualization of genome-wide association scan results
.
Bioinformatics
.
2010 Sep 15
;
26
(
18
):
2336
7
. .
23.
Tibshirani
R
.
Regression shrinkage and selection via the lasso: a retrospective
.
J R Stat Soc Ser B
.
2011 Jun 1
;
73
(
3
):
273
82
. .
24.
Anderson
CA
,
Pettersson
FH
,
Clarke
GM
,
Cardon
LR
,
Morris
AP
,
Zondervan
KT
.
Data quality control in genetic case-control association studies
.
Nat Protoc
.
2010 Sep 26
;
5
(
9
):
1564
73
. .
25.
Hanefeld
M
,
Engelmann
K
,
Appelt
D
,
Sandner
D
,
Weigmann
I
,
Ganz
X
,
Intra-individual variability and circadian rhythm of vascular endothelial growth factors in subjects with normal glucose tolerance and type 2 diabetes
.
PLoS One
.
2017 Oct 1
;
12
(
10
):
e0184234
. .
26.
Zhang
Y
,
Tian
C
,
Liu
X
,
Zhang
H
.
Identification of genetic biomarkers for diagnosis of myocardial infarction compared with angina patients
.
Cardiovasc Ther
.
2020
;
2020
. .
27.
Mosedale
M
,
Egodage
S
,
Calma
RC
,
Chi
NW
,
Chessler
SD
.
Neurexin-1α contributes to insulin-containing secretory granule docking
.
J Biol Chem
.
2012 Feb 24
;
287
(
9
):
6350
61
. .
28.
Kneeshaw
S
,
Keyani
R
,
Delorme-Hinoux
V
,
Imrie
L
,
Loake
GJ
,
Le Bihan
T
,
Nucleoredoxin guards against oxidative stress by protecting antioxidant enzymes
.
Proc Natl Acad Sci U S A
.
2017 Aug 1
;
114
(
31
):
8414
9
. .
29.
Stocker
SL
,
Morrissey
KM
,
Yee
SW
,
Castro
RA
,
Xu
L
,
Dahlin
A
,
The effect of novel promoter variants in MATE1 and MATE2 on the pharmacokinetics and pharmacodynamics of metformin
.
Clin Pharmacol Ther
.
2013 Feb
;
93
(
2
):
186
94
. .
30.
Christensen
MM
,
Pedersen
RS
,
Stage
TB
,
Brasch-Andersen
C
,
Nielsen
F
,
Damkier
P
,
A gene-gene interaction between polymorphisms in the OCT2 and MATE1 genes influences the renal clearance of metformin
.
Pharmacogenet Genomics
.
2013 Oct
;
23
(
10
):
526
34
. .
31.
Hung
SW
,
Marrache
S
,
Cummins
S
,
Bhutia
YD
,
Mody
H
,
Hooks
SB
,
Defective hCNT1 transport contributes to gemcitabine chemoresistance in ovarian cancer subtypes: Overcoming transport defects using a nanoparticle approach
.
Cancer Lett
.
2015 Apr 10
;
359
(
2
):
233
40
. .
32.
Yee
SW
,
Chen
L
,
Giacomini
KM
.
Pharmacogenomics of membrane transporters: past, present and future
.
Pharmacogenomics
.
2010 May 20
;
11
(
4
):
475
9
. .
33.
Kroetz
DL
,
Yee
SW
,
Giacomini
KM
.
The pharmacogenomics of membrane transporters project: research at the interface of genomics and transporter pharmacology
.
Clin Pharmacol Ther
.
2010 Jan
;
87
(
1
):
109
16
. .
34.
Lin
L
,
Yee
SW
,
Kim
RB
,
Giacomini
KM
.
SLC transporters as therapeutic targets: emerging opportunities
.
Nat Rev Drug Discov
.
2015 Aug 26
;
14
(
8
):
543
60
. .
35.
Moltke
I
,
Grarup
N
,
Jørgensen
ME
,
Bjerregaard
P
,
Treebak
JT
,
Fumagalli
M
,
A common Greenlandic TBC1D4 variant confers muscle insulin resistance and type 2 diabetes
.
Nature
.
2014 Aug 18
;
512
(
7513
):
190
3
. .
36.
Kjøbsted
R
,
Chadt
A
,
Jørgensen
NO
,
Kido
K
,
Larsen
JK
,
de Wendt
C
,
TBC1D4 Is Necessary for Enhancing Muscle Insulin Sensitivity in Response to AICAR and Contraction
.
Diabetes
.
2019 Sep
;
68
(
9
):
1756
66
.
37.
Archer
NP
,
Perez-Andreu
V
,
Stoltze
U
,
Scheurer
ME
,
Wilkinson
AV
,
Lin
T-N
,
Family-based exome-wide association study of childhood acute lymphoblastic leukemia among Hispanics confirms role of ARID5B in susceptibility. Chang JS
.
PLoS One
.
2017 Aug 17
;
12
(
8
):
e0180488
.
38.
Sun
LL
,
Zhang
SJ
,
Chen
MJ
,
Elena
K
,
Qiao
H
.
Relationship between Modulator Recognition Factor 2/AT-rich Interaction Domain 5B Gene Variations and Type 2 Diabetes Mellitus or Lipid Metabolism in a Northern Chinese Population
.
Chin Med J
.
2017 May 5
;
130
(
9
):
1055
61
. .
39.
Wang
G
,
Watanabe
M
,
Imai
Y
,
Hara
K
,
Manabe
I
,
Maemura
K
,
Associations of variations in the MRF2/ARID5B gene with susceptibility to type 2 diabetes in the Japanese population
.
J Hum Genet
.
2012 Nov 13
;
57
(
11
):
727
33
. .
40.
Claussnitzer
M
,
Hui
CC
,
Kellis
M
.
FTO Obesity Variant and Adipocyte Browning in Humans
.
N Engl J Med
.
2016 Jan 14
;
374
(
2
):
192
3
. .
41.
Moreno-Estrada
A
,
Gignoux
CR
,
Fernendez-Lopez
JC
,
Zakharia
F
,
Sikora
M
,
Contreras
AV
,
The genetics of Mexico recapitulates Native American substructure and affects biomedical traits
.
Science
.
2014
;
344
(
6189
):
1280
5
.
Copyright / Drug Dosage / Disclaimer
Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.
You do not currently have access to this content.