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Leveraging an Electronic Health Record-Linked Biorepository to Generate a Metformin Pharmacogenomics Hypothesis.

Breitenstein MK, Wang L, Simon G, Ryu E, Armasu SM, Ray B, Weinshilboum RM, Pathak J - AMIA Jt Summits Transl Sci Proc (2015)

Bottom Line: Using a cohort of 258 T2DM patients who had new metformin exposure, existing genetic data, and longitudinal electronic health records, we compared genetic variation within FMO5 to change in glycemic response.Gene-level and SNP-level analysis identified marginally significant associations for FMO5 variation, representing an EHR-driven pharmacogenetics hypothesis for a potential novel mechanism for metformin biotransformation.However, functional validation of this EHR-based hypothesis is necessary to ascertain its clinical and biological significance.

View Article: PubMed Central - PubMed

Affiliation: Mayo Clinic, Rochester, MN ; University of Minnesota, Minneapolis, MN.

ABSTRACT
Metformin is a first-line antihyperglycemic agent commonly prescribed in type 2 diabetes mellitus (T2DM), but whose pharmacogenomics are not clearly understood. Further, due to accumulating evidence highlighting the potential for metformin in cancer prevention and treatment efforts it is imperative to understand molecular mechanisms of metformin. In this electronic health record(EHR)-based study we explore the potential association of the flavin-containing monooxygenase(FMO)-5 gene, a biologically plausible biotransformer of metformin, and modifying glycemic response to metformin treatment. Using a cohort of 258 T2DM patients who had new metformin exposure, existing genetic data, and longitudinal electronic health records, we compared genetic variation within FMO5 to change in glycemic response. Gene-level and SNP-level analysis identified marginally significant associations for FMO5 variation, representing an EHR-driven pharmacogenetics hypothesis for a potential novel mechanism for metformin biotransformation. However, functional validation of this EHR-based hypothesis is necessary to ascertain its clinical and biological significance.

No MeSH data available.


Related in: MedlinePlus

Study Cohort Development Process
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f1-2091597: Study Cohort Development Process

Mentions: The MayoGC stores existing GWAS data generated from multiple studies. These data were harmonized to the forward strand mapped to become on the same strand as the 1000 genome cosmopolitan reference population. Genotypes for unmappable or ambiguous SNPs were excluded. We selected SNPs 20 kb upstream and downstream of each gene using 1000 genomes project variants and NCBI build 37 as the reference genome. By this mapping rule, a total of 1,381 SNPs were mapped to the 5 genes, but only 205 SNPs were available in the genotype data. Further, due to their proximity the FMO1, FMO2, FMO3, and FMO4 genes some SNPs belong to multiple genes. For the remaining SNPs, two main quality control filters were applied:(i) SNPs with unacceptable high rates of missing genotype calls (>10%); and (ii) monomorphic SNPs were excluded. The quality control of the genotype data was performed by PLINK v1.0715. A detailed diagram of cohort development is found in Figure 1.


Leveraging an Electronic Health Record-Linked Biorepository to Generate a Metformin Pharmacogenomics Hypothesis.

Breitenstein MK, Wang L, Simon G, Ryu E, Armasu SM, Ray B, Weinshilboum RM, Pathak J - AMIA Jt Summits Transl Sci Proc (2015)

Study Cohort Development Process
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4525256&req=5

f1-2091597: Study Cohort Development Process
Mentions: The MayoGC stores existing GWAS data generated from multiple studies. These data were harmonized to the forward strand mapped to become on the same strand as the 1000 genome cosmopolitan reference population. Genotypes for unmappable or ambiguous SNPs were excluded. We selected SNPs 20 kb upstream and downstream of each gene using 1000 genomes project variants and NCBI build 37 as the reference genome. By this mapping rule, a total of 1,381 SNPs were mapped to the 5 genes, but only 205 SNPs were available in the genotype data. Further, due to their proximity the FMO1, FMO2, FMO3, and FMO4 genes some SNPs belong to multiple genes. For the remaining SNPs, two main quality control filters were applied:(i) SNPs with unacceptable high rates of missing genotype calls (>10%); and (ii) monomorphic SNPs were excluded. The quality control of the genotype data was performed by PLINK v1.0715. A detailed diagram of cohort development is found in Figure 1.

Bottom Line: Using a cohort of 258 T2DM patients who had new metformin exposure, existing genetic data, and longitudinal electronic health records, we compared genetic variation within FMO5 to change in glycemic response.Gene-level and SNP-level analysis identified marginally significant associations for FMO5 variation, representing an EHR-driven pharmacogenetics hypothesis for a potential novel mechanism for metformin biotransformation.However, functional validation of this EHR-based hypothesis is necessary to ascertain its clinical and biological significance.

View Article: PubMed Central - PubMed

Affiliation: Mayo Clinic, Rochester, MN ; University of Minnesota, Minneapolis, MN.

ABSTRACT
Metformin is a first-line antihyperglycemic agent commonly prescribed in type 2 diabetes mellitus (T2DM), but whose pharmacogenomics are not clearly understood. Further, due to accumulating evidence highlighting the potential for metformin in cancer prevention and treatment efforts it is imperative to understand molecular mechanisms of metformin. In this electronic health record(EHR)-based study we explore the potential association of the flavin-containing monooxygenase(FMO)-5 gene, a biologically plausible biotransformer of metformin, and modifying glycemic response to metformin treatment. Using a cohort of 258 T2DM patients who had new metformin exposure, existing genetic data, and longitudinal electronic health records, we compared genetic variation within FMO5 to change in glycemic response. Gene-level and SNP-level analysis identified marginally significant associations for FMO5 variation, representing an EHR-driven pharmacogenetics hypothesis for a potential novel mechanism for metformin biotransformation. However, functional validation of this EHR-based hypothesis is necessary to ascertain its clinical and biological significance.

No MeSH data available.


Related in: MedlinePlus