The Influence of CYP2D6 and CYP2C19 Genetic Variation on Diabetes Mellitus Risk in People Taking Antidepressants and Antipsychotics

Abstract

CYP2D6 and CYP2C19 enzymes are essential in the metabolism of antidepressants and antipsychotics. Genetic variation in these genes may increase risk of adverse drug reactions. Antidepressants and antipsychotics have previously been associated with risk of diabetes. We examined whether individual genetic differences in CYP2D6 and CYP2C19 contribute to these effects. We identified 31,579 individuals taking antidepressants and 2699 taking antipsychotics within UK Biobank. Participants were classified as poor, intermediate, or normal metabolizers of CYP2D6, and as poor, intermediate, normal, rapid, or ultra-rapid metabolizers of CYP2C19. Risk of diabetes mellitus represented by HbA1c level was examined in relation to the metabolic phenotypes. CYP2D6 poor metabolizers taking paroxetine had higher Hb1Ac than normal metabolizers (mean difference: 2.29 mmol/mol; p < 0.001). Among participants with diabetes who were taking venlafaxine, CYP2D6 poor metabolizers had higher HbA1c levels compared to normal metabolizers (mean differences: 10.15 mmol/mol; p < 0.001. Among participants with diabetes who were taking fluoxetine, CYP2D6 intermediate metabolizers and decreased HbA1c, compared to normal metabolizers (mean difference −7.74 mmol/mol; p = 0.017). We did not observe any relationship between CYP2D6 or CYP2C19 metabolic status and HbA1c levels in participants taking antipsychotic medication. Our results indicate that the impact of genetic variation in CYP2D6 differs depending on diabetes status. Although our findings support existing clinical guidelines, further research is essential to inform pharmacogenetic testing for people taking antidepressants and antipsychotics.

Associations of antidepressants and antipsychotics with lipid parameters: Do CYP2D6/CYP2C19 genes play a role? A UK population-based study

“…We investigated aims in individual medications only if reported as being taken by ≥1,800 participants (consistent with a previous study). 18 Medications not reaching this threshold were considered for inclusion in a higher-level combined group (e.g. all antipsychotics together).…”

“…Using the fully-imputed dataset, we performed local quality control and assigned CYP450 metabolic phenotypes, as described previously. 18 In brief, to include and account for participants of non-European ancestry (European ancestry was determined centrally), two rounds of principal component analysis was conducted (using PC-AiR 26 and PC-Relate 27 ), identifying four ancestry groups (East Asian, South Asian, African, admixed with predominantly European origin); participants not clustering with any main group were excluded. Subsequent processing excluded: variants with minor allele frequency <1% and/or Fisher information score of <0.3 in each ancestry group; one of each pair of participants with a kinship score >0·083 (approximately third-degree relatives); and participants with >10% missingness, excessive genetic relatedness (>10 third-degree relatives); or a mismatch between self-reported and genetically-inferred sex.…”

“…Using the fully-imputed dataset, we performed local quality control and assigned CYP450 metabolic phenotypes, as described previously. 18 In brief, to include and account for participants of non-European ancestry (European ancestry was determined centrally), two rounds of principal component analysis was conducted (using PC-AiR To assign CYP metabolic phenotypes, we extracted CYP2D6 and CYP2C19 regions of interest (defined as one mega-base upstream of the 5′ end and one mega-base downstream of the 3′ end of the gene). Using an input map and reference panel from the 1000 genomes project, 28 haplotypes were constructed based on genetic data, imputed using Beagle (version 5•0), allele nomenclature system.…”

“…one wild-type and one reduced capacity allele); and ‘rapid’ and ‘ultra-rapid metabolisers’ have greater than normal enzymatic capacity, due to either at least one increased function allele or duplications of functional allele(s). 14,15 Phenotypes, of which distributions vary across ancestries, impact medication plasma concentrations and risk of adverse reactions, 17,18 with poor metabolisers predicted as most at risk due to greater concentrations.…”

The Promise of Nanotechnology in Personalized Medicine

“…This system is particularly important to detect variants of CYP2D6 and CYP2C19 that can determine drug response variability in variants associated with ultrarapid metabolism compared to other variants associated with poor drug metabolism [ 218 ].…”