Antidepressant Use Patterns May Help Personalize MDD Treatment
Key Clinical Summary
- A cohort study of 12,074 adults with major depressive disorder (MDD) found that sustained use of a single antidepressant (≥360 days) was associated with distinct phenotypic profiles among patients.
- Polygenic risk scores for psychiatric disorders were linked to more complex antidepressant treatment patterns, suggesting a genetic contribution to difficult-to-treat depression.
- Researchers identified a genome-wide significant immune-related genetic variant (SLAMF3/LY9) associated with sustained selective serotonin reuptake inhibitor (SSRI) use.
Antidepressant therapy for major depressive disorder (MDD) often relies on trial and error, with many patients failing to respond to first-line treatments. A new cohort study published in JAMA Psychiatry examined whether real-world antidepressant prescription patterns could help identify biologically meaningful subtypes of depression. Authors found that phenotypic factors were associated with ongoing single antidepressant use and treatment complexity.
Study Findings
To determine whether medication use patterns correlate with phenotypic and genomic differences among individuals with MDD, investigators analyzed data from 12,074 participants enrolled in the Australian Genetics of Depression Study, all of whom had a lifetime diagnosis of major depressive disorder and had filled at least 1 prescription for 1 of the 10 most commonly used antidepressants. Prescription records spanning 4.5 years (2013–2017) were used to categorize treatment patterns.
Researchers defined “sustained-use 360” groups as individuals who received at least 360 cumulative days of a single antidepressant during the study period. These groups were compared with patients who had more complex treatment patterns involving multiple antidepressant classes. Investigators evaluated 44 self-reported phenotypic characteristics and polygenic scores for 15 traits to explore clinical and genetic differences between subgroups.
The analysis showed that patients who remained on a single antidepressant for extended periods exhibited distinct phenotypic profiles, suggesting that medication response patterns may reflect underlying biological heterogeneity in MDD.
Genetic analysis further revealed differences between treatment groups. Polygenic risk scores for psychiatric disorders were associated with individuals who had greater diversity of antidepressant classes, indicating that genetic susceptibility may contribute to treatment complexity or resistance.
In addition, investigators identified one genome-wide significant immune-related genetic variant within the SLAMF3/LY9 region associated with sustained use of selective serotonin reuptake inhibitors. This finding highlights a potential immunologic component in antidepressant response for certain patient subgroups.
Clinical Implications
Major depressive disorder is widely recognized as a heterogeneous condition, yet clinical decision-making often relies on sequential medication trials rather than biologically informed strategies. The findings from this study suggest that longitudinal antidepressant prescription patterns may offer clinically useful signals for identifying subtypes of depression.
If validated in additional populations, treatment pattern–based classification could support precision psychiatry approaches, enabling clinicians to better match patients with medications that are more likely to be effective. For example, sustained response to a specific antidepressant class may reflect underlying biological characteristics that distinguish one subgroup of patients from another.
The genetic findings also underscore the potential role of polygenic risk scores in identifying individuals at risk for difficult-to-treat depression, which could influence earlier use of alternative strategies such as combination pharmacotherapy, psychotherapy, or neuromodulation.
However, translating these insights into clinical practice will require further validation, including prospective studies examining whether prescription patterns reliably predict treatment outcomes or biological subtypes.
Expert Commentary
“If these subtypes and difficult-to-treat depression represent biologically meaningful differences, genetic markers from blood or saliva samples at first diagnosis could help predict treatment outcomes,” concluded Alicia Walker, BSc, Department of Psychiatry, Warneford Hospital, University of Oxford, London, and co-authors. “Retrospective associations such as ours would not only guide the design of prospective studies and inform algorithmic decision-support tools, but also inform clinical decision-making, for example, identifying patients likely to follow a more complex course who may benefit from earlier senior clinical (psychiatrist) input.”
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