Objective To describe the usage patterns of antidepressants with published CYP2D6- and CYP2C19-based prescribing guidelines among depressed primary care patients and estimate the proportion of patients taking antidepressants not recommended for them based on their CYP2C19 and CYP2D6 genotype-predicted metabolizer status. Methods Medication use and pharmacogenetic testing results were collected on 128 primary care patients enrolled in a 10-year depression cohort study. At each 12-month interval, we calculated the proportion of patients that: (1) reported use of one or more of the 13 antidepressant medications (i.e. amitriptyline, citalopram, escitalopram, clomipramine, desipramine, doxepin, fluvoxamine, imipramine, nortriptyline, paroxetine, sertraline, trimipramine, venlafaxine) with published CYP2D6- and CYP2C19-based prescribing guidelines, (2) were taking an antidepressant that was not recommended for them based on their CYP2C19 and CYP2D6 genotype-predicted metabolizer phenotype, and (3) switched medications from the previous 12-month interval. Results The annual proportion of individuals taking an antidepressant with a CYP2D6- and CYP2C19-based prescribing guidelines ranged from 45 to 84%. The proportion of participants that used an antidepressant that was not recommended for them, based on available CYP2D6 and CYP2C19 metabolizer phenotype, ranged from 18 to 29% and these individuals tended to switch medications more frequently (10%) compared to their counterparts taking medication aligned with their metabolizer phenotype (6%). Conclusion One-quarter of primary care patients used an antidepressant that was not recommended for them based on CYP2D6- and CYP2C19-based prescribing guidelines and switching medications tended to be more common in this group. Studies to determine the impact of CYP2D6 and CYP2C19 genotyping on reducing gene-antidepressant mismatches are warranted.

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Caffeine is the most consumed drug in the world, and it is commonly used by children. Despite being considered relatively safe, caffeine can have marked effects on sleep. Studies in adults suggest that genetic variants in the adenosine A2A receptor (ADORA2A, rs5751876) and cytochrome P450 1A (CYP1A, rs2472297, rs762551) loci are correlated with caffeine-associated sleep disturbances and caffeine intake (dose), but these associations have not been assessed in children. We examined the independent and interaction effects of daily caffeine dose and candidate variants in ADORA2A and CYP1A on the sleep quality and duration in 6112 children aged 9–10 years who used caffeine and were enrolled in the Adolescent Brain Cognitive Development (ABCD) study. We found that children with higher daily caffeine doses had lower odds of reporting > 9 h of sleep per night (OR = 0.81, 95% CI = 0.74–0.88, and p = 1.2 × 10−6). For every mg/kg/day of caffeine consumed, there was a 19% (95% CI = 12–26%) decrease in the odds of children reporting > 9 h of sleep. However, neither ADORA2A nor CYP1A genetic variants were associated with sleep quality, duration, or caffeine dose. Likewise, genotype by caffeine dose interactions were not detected. Our findings suggest that a daily caffeine dose has a clear negative correlation with sleep duration in children, but this association is not moderated by the ADORA2A or CYP1A genetic variation.