Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas

Author:

Dawed Adem Y.1ORCID,Yee Sook Wah2,Zhou Kaixin1,van Leeuwen Nienke3,Zhang Yanfei4,Siddiqui Moneeza K.1ORCID,Etheridge Amy5,Innocenti Federico5,Xu Fei6,Li Josephine H.78,Beulens Joline W.9,van der Heijden Amber A.1011,Slieker Roderick C.310,Chang Yu-Chuan2,Mercader Josep M.78,Kaur Varinderpal78,Witte John S.12,Lee Ming Ta Michael4,Kamatani Yoichiro13,Momozawa Yukihide13,Kubo Michiaki13,Palmer Colin N.A.1,Florez Jose C.7814,Hedderson Monique M.12,‘t Hart Leen M.31516,Giacomini Kathleen M.217,Pearson Ewan R.1ORCID,Pearson EwanORCID,Dawed AdemORCID,Zhou Kaixin,Holman Rury,Coleman Ruth,‘t Hart Leen,Slieker Roderick,Beulens Joline,van der Heijden Amber,Nijpels Giel,Elders Petra,Rutters Femke,Stricker Bruno,Ahmadizar Fariba,de Keyser Catherine,Koov Adriaan,Out Mattijs,Kloviņš Jānis,Zaharenko Linda,Javorsky Martin,Tkac Ivan,Florez Jose,Giacomini Kathy,Wah Yee Sook,Hedderson Monique,Kubo Michiaki,Motsinger-Reif Alison,Wagner Michael,Semiz Sabina,Dujic Tanja,Christensen Mette,Brøsen Kim,Waterworth Dawn,Ehm Meg,Ma Ronald,Psaty Bruce,Floyd James, ,

Affiliation:

1. Population Health and Genomics, School of Medicine, University of Dundee, Dundee, U.K.

2. Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA

3. Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands

4. Genomic Medicine Institute, Geisinger, Danville, PA

5. Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC

6. Division of Research, Kaiser Permanente Northern California, Oakland, CA

7. Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA

8. Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA

9. Amsterdam UMC, location VUmc, Department of General Practice, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands

10. Amsterdam UMC, location VUmc, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands

11. Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands

12. Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA

13. RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

14. Department of Medicine, Harvard Medical School, Boston, MA

15. Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands

16. Department of General Practice Medicine, Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands

17. Institute for Human Genetics, University of California, San Francisco, San Francisco, CA

Abstract

OBJECTIVE Sulfonylureas, the first available drugs for the management of type 2 diabetes, remain widely prescribed today. However, there exists significant variability in glycemic response to treatment. We aimed to establish heritability of sulfonylurea response and identify genetic variants and interacting treatments associated with HbA1c reduction. RESEARCH DESIGN AND METHODS As an initiative of the Metformin Genetics Plus Consortium (MetGen Plus) and the DIabetes REsearCh on patient straTification (DIRECT) consortium, 5,485 White Europeans with type 2 diabetes treated with sulfonylureas were recruited from six referral centers in Europe and North America. We first estimated heritability using the generalized restricted maximum likelihood approach and then undertook genome-wide association studies of glycemic response to sulfonylureas measured as HbA1c reduction after 12 months of therapy followed by meta-analysis. These results were supported by acute glipizide challenge in humans who were naïve to type 2 diabetes medications, cis expression quantitative trait loci (eQTL), and functional validation in cellular models. Finally, we examined for possible drug-drug-gene interactions. RESULTS After establishing that sulfonylurea response is heritable (mean ± SEM 37 ± 11%), we identified two independent loci near the GXYLT1 and SLCO1B1 genes associated with HbA1c reduction at a genome-wide scale (P < 5 × 10−8). The C allele at rs1234032, near GXYLT1, was associated with 0.14% (1.5 mmol/mol), P = 2.39 × 10−8), lower reduction in HbA1c. Similarly, the C allele was associated with higher glucose trough levels (β = 1.61, P = 0.005) in healthy volunteers in the SUGAR-MGH given glipizide (N = 857). In 3,029 human whole blood samples, the C allele is a cis eQTL for increased expression of GXYLT1 (β = 0.21, P = 2.04 × 10−58). The C allele of rs10770791, in an intronic region of SLCO1B1, was associated with 0.11% (1.2 mmol/mol) greater reduction in HbA1c (P = 4.80 × 10−8). In 1,183 human liver samples, the C allele at rs10770791 is a cis eQTL for reduced SLCO1B1 expression (P = 1.61 × 10−7), which, together with functional studies in cells expressing SLCO1B1, supports a key role for hepatic SLCO1B1 (encoding OATP1B1) in regulation of sulfonylurea transport. Further, a significant interaction between statin use and SLCO1B1 genotype was observed (P = 0.001). In statin nonusers, C allele homozygotes at rs10770791 had a large absolute reduction in HbA1c (0.48 ± 0.12% [5.2 ± 1.26 mmol/mol]), equivalent to that associated with initiation of a dipeptidyl peptidase 4 inhibitor. CONCLUSIONS We have identified clinically important genetic effects at genome-wide levels of significance, and important drug-drug-gene interactions, which include commonly prescribed statins. With increasing availability of genetic data embedded in clinical records these findings will be important in prescribing glucose-lowering drugs.

Publisher

American Diabetes Association

Subject

Advanced and Specialized Nursing,Endocrinology, Diabetes and Metabolism,Internal Medicine

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