Comprehensive Characterization of Antidepressant Pharmacogenetics: A Systematic Review of Studies in Major Depressive Disorder.

Journal: Clinical and translational science
Published Date:

Abstract

Pharmacogenetics is a promising strategy to facilitate individualized care for patients with Major Depressive Disorder (MDD). Research is ongoing to identify the optimal genetic markers for predicting outcomes to antidepressant therapies. The primary aim of this systematic review was to summarize antidepressant pharmacogenetic studies to enhance understanding of the genes, variants, datatypes/methodologies, and outcomes investigated in the context of MDD. The secondary aim was to identify clinical genetic panels indicated for antidepressant prescribing and summarize their genes and variants. Screening of N = 5793 articles yielded N = 390 for inclusion, largely comprising adult (≥ 18 years) populations. Top-studied variants identified in the search were discussed and compared with those represented on the N = 34 clinical genetic panels that were identified. Summarization of articles revealed sources of heterogeneity across studies and low rates of replicability of pharmacogenetic associations. Heterogeneity was present in outcome definitions, treatment regimens, and differential inclusion of mediating variables in analyses. Efficacy outcomes (i.e., response, remission) were studied at greater frequency than adverse-event outcomes. Studies that used advanced analytical approaches, such as machine learning, to integrate variants with complimentary biological datatypes were fewer in number but achieved higher rates of significant associations with treatment outcomes than candidate variant approaches. As large biological datasets become more prevalent, machine learning will be an increasingly valuable tool for parsing the complexity of antidepressant response. This review provides valuable context and considerations surrounding pharmacogenetic associations in MDD which will help inform future research and translation efforts for guiding antidepressant care.

Authors

  • Caroline W Grant
    Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota, USA.
  • Karina Delaney
    Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota, USA.
  • Linsey E Jackson
    Department of Clinical and Translational Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • Justin Bobo
    Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota, USA.
  • Leslie C Hassett
    Mayo Medical Libraries, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Liewei Wang
    All authors: Mayo Clinic, Rochester, MN.
  • Richard M Weinshilboum
    All authors: Mayo Clinic, Rochester, MN.
  • Paul E Croarkin
    Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA.
  • Melanie T Gentry
    Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA.
  • Ann M Moyer
    Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.
  • Arjun P Athreya
    Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, USA.