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Neurotransmitter Receptor Influence on Behavior / Treatment of Major Depression · Journal article
The British Journal of Psychiatry · July 17, 2026
Early or partial results. Treat as a signal, not a conclusion.
This is a retrospective observational study of 82,633 UK Biobank individuals prescribed antidepressants, describing patterns of medication switching and discontinuation across depression and non-depression indications. Clinical and genetic factors associated with treatment changes are identified, but the study does not measure efficacy or symptom outcomes and is primarily hypothesis-generating.
Retrospective cohort study with genetic association analyses. UK Biobank participants with primary care antidepressant prescriptions; divided into depression group (those with ≥1 primary care depression diagnosis; n=28,332) and non-depression group (those without evidence of depression; n=24,543). Setting: primary care records.. Intervention: Antidepressant prescription (observational; not assigned). n = 82,633. UK Biobank (UK-wide).
28,332 individuals with depression diagnosis; 24,543 without depression in antidepressant cohort Recurrent depression associated with early discontinuation (OR = 1.96) and late discontinuation (OR = 2.63) in depression group Anxiety associated with early discontinuation (OR = 1.37) and late discontinuation (OR = 1.99) in depression group
Primary outcomes are prescribing patterns (changes, discontinuation) rather than clinical efficacy, symptom remission, or quality of life Recurrent depression associated with early discontinuation (OR = 1.96) and late discontinuation (OR = 2.63) in depression group
This descriptive study characterizes real-world antidepressant prescribing patterns and identifies clinical/genetic factors associated with medication changes and discontinuation, but does not measure treatment efficacy or clinical outcomes. Clinicians should view findings as exploratory; genetic discoveries require validation and do not yet inform clinical practice.
Large observational study from medical records with genetic association analyses, but lacks prospective design, randomization, and hard clinical outcomes; findings are descriptive and hypothesis-generating rather than confirmatory of treatment efficacy.
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Quoted from the source exactly as published.
This descriptive study characterizes real-world antidepressant prescribing patterns and identifies clinical/genetic factors associated with medication changes and discontinuation, but does not measure treatment efficacy or clinical outcomes. Clinicians should view findings as exploratory; genetic discoveries require validation and do not yet inform clinical practice.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
Background Antidepressants are the most frequently prescribed medications in psychiatry. Medical records of thousands of individuals provide a valuable opportunity to explore prescribing patterns and identify factors that influence treatment outcomes. Aims To investigate antidepressant change patterns in depression and non-depression indications and assess clinical and genetic factors associated with outcomes of antidepressant treatment. Methods Using primary care records from the UK Biobank, we examined outcomes including number of antidepressant changes and discontinuation due to either side-effects or inadequate response. Genetic analyses including heritability estimation, genetic correlation and polygenic score association were performed. Results A total of 82 633 individuals were prescribed at least 1 antidepressant. Of these, 28 332 individuals with at least 1 primary care depression diagnosis were classified as the depression group, and 24 543 individuals without evidence of depression were classified as the non-depression group. Citalopram and fluoxetine were the most prescribed antidepressants for depression, whereas amitriptyline dominated prescriptions for non-depression indications. Individuals with depression were more likely to stay on antidepressants longer than those without depression and to follow preferred antidepressants that changed over time. Antidepressant changes and discontinuation were associated with a range of psychiatric and somatic conditions, including recurrent depression (early discontinuation: odds ratio = 1.96; late discontinuation: odds ratio = 2.63) and anxiety (early discontinuation: odds ratio = 1.37; late discontinuation: odds ratio = 1.99) in the depression group, and pain-related conditions in the non-depression group. Genetic analyses identified two novel variants associated with early discontinuation of selective serotonin reuptake inhibitors. Notable genetic overlap was shown between these outcomes and multiple psychiatric and physical traits, including the number of antidepressant changes with anxiety and depression ( r g = 0.81–0.83), and polygenic scores for depression and attention-deficit hyperactivity disorder showed significant predictive value with respect to treatment outcomes. Conclusions These findings characterise antidepressant change patterns in primary care records and highlight the potential value of integrating clinical and genetic data to better understand factors associated with treatment outcomes.
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