ArticleBMC psychiatry2025
Association of psychosocial factors and biological pathways identified from rare-variant analysis with longitudinal trajectories of treatment response in major depressive disorder.
Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Obesity-related differences in amygdala and hippocampal volume and metabolism before and after a placebo-controlled antidepressant trial in major depressive disorder.Scientific reports · 2026Trial
- Symptom-specific genetics reveal heterogeneity within major depressive disorder.medRxiv : the preprint server for health sciences · 2026Article
- Longitudinal trajectories of major depressive disorder provide further clinical perspectives for precision psychiatry.PCN reports : psychiatry and clinical neurosciences · 2025Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundAntidepressant efficacy is influenced by a multitude of factors, yet predicting treatment outcomes remains challenging. This difficulty is partly due to the commonly employed dichotomous classifications of treatment response that rely on a single primary endpoint.
methodsThe study enrolled 972 patients diagnosed with depression, including both first-episode and recurrent cases. All patients received treatment with a single class of antidepressant medication over an eight-week period. Treatment response trajectories were identified through cluster analysis using normalized score change ratios from the 17-item Hamilton Rating Scale for Depression (HAMD-17) at baseline and weeks 2, 4, 6, and 8. The impact of psychosocial factors-including childhood trauma experience, social support, and family environment-on these response patterns was evaluated using ANOVA and Tukey's HSD tests. Additionally, targeted exome sequencing was conducted to perform rare-variant burden and enrichment analyses to investigate genetic influences on antidepressant response.
resultsThree patterns of antidepressant treatment response were identified: gradual response (C1 cluster), early response (C2 cluster), and fluctuating response (C3 cluster). Notably, patients in the C3 cluster exhibited higher levels of suicidal ideation, alexithymia, and anhedonia after the treatment period, along with the highest baseline levels of family control (a subscale of the family environment). Our rare-variant analysis revealed genes associated with response efficiency between C1 and C2 clusters to be significantly enriched in the neurotrophin signaling pathway (odds ratio = 23.94; p-adjusted = 6.96e-05). In addition, genes linked to response volatility between C1 and C3 clusters were enriched in the regulation of inflammatory mediators of transient receptor potential (TRP) channels (odds ratio = 31.5; p-adjusted = 1.83e-07).
conclusionsOur findings suggest that patients exhibiting a fluctuating response to antidepressant treatment may endure more severe clinical symptoms throughout the treatment course. The involvement of the neurotrophin signaling pathway and TRP channels in these response patterns highlights their potential as novel targets for therapeutic intervention in depression. This underscores the importance of personalized treatment strategies that consider the underlying genetic and psychological factors influencing antidepressant efficacy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.