Abstract
Aims/hypothesis
Characterisation of genetic variation that influences the response to glucose-lowering medications is instrumental to precision medicine for treatment of type 2 diabetes. The Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans (SUGAR-MGH) examined the acute response to metformin and glipizide in order to identify new pharmacogenetic associations for the response to common glucose-lowering medications in individuals at risk of type 2 diabetes.
Methods
One thousand participants at risk for type 2 diabetes from diverse ancestries underwent sequential glipizide and metformin challenges. A genome-wide association study was performed using the Illumina Multi-Ethnic Genotyping Array. Imputation was performed with the TOPMed reference panel. Multiple linear regression using an additive model tested for association between genetic variants and primary endpoints of drug response. In a more focused analysis, we evaluated the influence of 804 unique type 2 diabetes- and glycaemic trait-associated variants on SUGAR-MGH outcomes and performed colocalisation analyses to identify shared genetic signals.
Results
Five genome-wide significant variants were associated with metformin or glipizide response. The strongest association was between an African ancestry-specific variant (minor allele frequency [MAFAfr]=0.0283) at rs149403252 and lower fasting glucose at Visit 2 following metformin (p=1.9×10−9); carriers were found to have a 0.94 mmol/l larger decrease in fasting glucose. rs111770298, another African ancestry-specific variant (MAFAfr=0.0536), was associated with a reduced response to metformin (p=2.4×10−8), where carriers had a 0.29 mmol/l increase in fasting glucose compared with non-carriers, who experienced a 0.15 mmol/l decrease. This finding was validated in the Diabetes Prevention Program, where rs111770298 was associated with a worse glycaemic response to metformin: heterozygous carriers had an increase in HbA1c of 0.08% and non-carriers had an HbA1c increase of 0.01% after 1 year of treatment (p=3.3×10−3). We also identified associations between type 2 diabetes-associated variants and glycaemic response, including the type 2 diabetes-protective C allele of rs703972 near ZMIZ1 and increased levels of active glucagon-like peptide 1 (GLP-1) (p=1.6×10−5), supporting the role of alterations in incretin levels in type 2 diabetes pathophysiology.
Conclusions/interpretation
We present a well-phenotyped, densely genotyped, multi-ancestry resource to study gene–drug interactions, uncover novel variation associated with response to common glucose-lowering medications and provide insight into mechanisms of action of type 2 diabetes-related variation.
Data availability
The complete summary statistics from this study are available at the Common Metabolic Diseases Knowledge Portal (https://hugeamp.org) and the GWAS Catalog (www.ebi.ac.uk/gwas/, accession IDs: GCST90269867 to GCST90269899).
Graphical Abstract

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Abbreviations
- AOC:
-
Area over the curve
- DPP:
-
Diabetes Prevention Program
- EAF:
-
Effect allele frequency
- gePS:
-
Global extended polygenic score
- GLP-1:
-
Glucagon-like peptide 1
- GWAS:
-
Genome-wide association study
- LD:
-
Linkage disequilibrium
- MAF:
-
Minor allele frequency
- PC:
-
Principal component
- PP:
-
Posterior probability
- pPS:
-
Process-specific polygenic score
- SUGAR-MGH:
-
Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans
- V1:
-
Visit 1
- V2:
-
Visit 2
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Acknowledgements
We would like to thank J. Del Rio (freelance graphic designer, Cambridge, MA, USA) for his support with Fig. 1 generation. Portions of this study were previously presented as an oral presentation at the 81st Virtual Scientific Sessions of the American Diabetes Association, 25–29 June 2021.
Data availability
The complete summary statistics from this study will be deposited and made available at the Common Metabolic Diseases Knowledge Portal (https://hugeamp.org) and the GWAS Catalog (www.ebi.ac.uk/gwas/, accession IDs: GCST90269867 to GCST90269899) following article publication. Related study documents, including the original study protocol and informed consent forms, are available [14]. Additional data requests should be sent by email to the corresponding author.
Funding
This work was conducted with support from National Institutes of Health/NIDDK awards R01 GM117163, R01 DK088214, R03 DK077675 and P30 DK036836; from the Joslin Clinical Research Center from its philanthropic donors; and from the Harvard Catalyst: the Harvard Clinical and Translational Science Center (National Center for Research Resources and the National Center for Advancing Translational Sciences, NIH Awards M01-RR-01066, 1 UL1 RR025758-04 and 8UL1TR000170-05, and financial contributions from Harvard University and its affiliated academic healthcare centres). JHL received individual support from NIH T32DK007028 and NIDDK K23DK131345. LNB is supported by NIDDK K23DK125839. MSU is supported by NIDDK K23DK114551. AL is supported by grant 2020096 from the Doris Duke Charitable Foundation and the American Diabetes Association grant 7-22-ICTSPM-23. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1-19-ICTS-068, American Diabetes Association grant #11-22-ICTSPM-16, and by NHGRI U01HG011723. JCF is supported by NHLBI K24HL157960.
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The authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work.
Contribution statement
All authors took part in designing the experiments presented in this manuscript. VK, LNB, MSU, AL and JCF recruited participants in SUGAR-MGH. VK supervised participant recruitment, data collection, and IRB review and approval, and performed DNA extractions and managed GWAS genotyping. Quality control, imputation of the genetic data and GWAS analyses were performed by JMM. JHL, LNB, VK, KF, PS, AH-C and JMM performed follow-up of GWAS data analysis. JHL, LNB, VK, JMM and JCF contributed to the interpretation of the results. JHL, LNB, VK and JMM wrote and prepared the manuscript. All authors revised and approved the final manuscript. JMM and JCF jointly supervised this study. JCF is the guarantor of this work.
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Li, J.H., Brenner, L.N., Kaur, V. et al. Genome-wide association analysis identifies ancestry-specific genetic variation associated with acute response to metformin and glipizide in SUGAR-MGH. Diabetologia 66, 1260–1272 (2023). https://doi.org/10.1007/s00125-023-05922-7
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DOI: https://doi.org/10.1007/s00125-023-05922-7