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Clin Pharmacol Ther. 2016 Nov;100(5):537-547. doi: 10.1002/cpt.428. Epub 2016 Sep 23.

A Longitudinal HbA1c Model Elucidates Genes Linked to Disease Progression on Metformin.

Author information

1
University of California, San Francisco, San Francisco, California, USA.
2
Kaiser Permanente Northern California, Oakland, California, USA.
3
Vanderbilt University, Nashville, Tennessee, USA.
4
RIKEN Institute, Center for Genomic Medicine, Saitama, Japan.
5
Kaiser Permanente Georgia, Atlanta, Georgia, USA.
6
Center for Biomedical Informatics, University of Tennessee Health Sciences Center, Memphis, Tennessee, USA.
7
University of California, San Francisco, San Francisco, California, USA. Kathy.giacomini@ucsf.edu.
8
University of California, San Francisco, San Francisco, California, USA. rada.savic@ucsf.edu.

Abstract

One-third of type-2 diabetic patients respond poorly to metformin. Despite extensive research, the impact of genetic and nongenetic factors on long-term outcome is unknown. In this study we combine nonlinear mixed effect modeling with computational genetic methodologies to identify predictors of long-term response. In all, 1,056 patients contributed their genetic, demographic, and long-term HbA1c data. The top nine variants (of 12,000 variants in 267 candidate genes) accounted for approximately one-third of the variability in the disease progression parameter. Average serum creatinine level, age, and weight were determinants of symptomatic response; however, explaining negligible variability. Two single nucleotide polymorphisms (SNPs) in CSMD1 gene (rs2617102, rs2954625) and one SNP in a pharmacologically relevant SLC22A2 gene (rs316009) influenced disease progression, with minor alleles leading to less and more favorable outcomes, respectively. Overall, our study highlights the influence of genetic factors on long-term HbA1c response and provides a computational model, which when validated, may be used to individualize treatment.

PMID:
27415606
PMCID:
PMC5534241
DOI:
10.1002/cpt.428
[Indexed for MEDLINE]
Free PMC Article

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