Association of psychosocial factors and biological pathways identified from rare-variant analysis with longitudinal trajectories of treatment response in major depressive disorder

Abstract

Background: Antidepressant 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.

Methods: The 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.

Results: Three 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).

Conclusions: Our 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.

Keywords: Antidepressant efficacy; Genetic factors; Psychosocial factors; Rare variants; Response trajectories; Target exome sequencing.

Fig. 1

Study design flow chart. HAMD-17, 17-item Hamilton depression rating scale; CTQ-SF, childhood trauma questionnaire-short form; FES-CV, family environment scale-Chinese version; SSRS, social support rating scale; BSI-CV, Beck scale for suicide ideation-Chinese version; SHAPS: Snaith-Hamilton pleasure scale; TAS-20: 20-item Toronto alexithymia scale; ANOVA, Analysis of Variance; Tukey HSD, Tukey honestly significant difference

Fig. 2

A: Assignment of patients based on classifications for both response and remission derived from decision-tree analysis. B: Representative individual examples illustrating distinct antidepressant response trajectories identified within patient clusters. Each solid line represents one patient's change in HAMD-17 scores over the treatment period. The three dashed horizontal lines indicate clinically relevant cutoff points on the HAMD-17 scale. Red line: HAMD-17 score of 24, differentiating severe depressive states; Brown line: HAMD-17 score of 17, distinguishing moderate depressive severity; Green line: HAMD-17 score of 7, indicating clinical remission

Fig. 3

HAMD-17 score change rate trajectories and resulting cluster shape characteristics for all patients. X-axis: observation time in weeks; Y-axis: normalized HAMD-17 score change ratio; membership: each sample has a membership value ranging from 0 to 1, which indicates its degree of belonging to the cluster

Fig. 4

Violin plots of clinical psychological scale scores for the three clusters of patients. ANOVA analysis and Tukey HSD test of clinical psychological scale scores among three clusters were conducted. Figures above each two violin plots are p-values by Tukey’s HSD test. The numbers 1, 2, and 3 on the X-axis represent the C1, C2, and C3 cluster, respectively. a. Family control: Distribution of the control subscale score from the Family Environment Scale among clusters; b. Support utility: Distribution of support utility scores among clusters; c. BSI at baseline: Distribution of baseline BSI scores across clusters; d. BSI at week 8: Distribution of Beck Scale for Suicide Ideation scores at week 8 among clusters. e. SHAPS at week 8: Distribution of Snaith-Hamilton Pleasure Scale scores at week 8; f. Change in SHAPS (week 8 - baseline): Change scores for SHAPS from baseline to week 8; g. TAS-20 total at week 8: Distribution of Toronto Alexithymia Scale total scores at week 8; h. Change in TAS-20 (week 8 - baseline): Change scores for TAS-20 total scores from baseline to week 8

Fig. 5

The top ten enriched KEGG pathways for the treatment response-related rare variant genes. A: The top ten enriched KEGG pathways of response efficiency-related genes. B: The top ten enriched KEGG pathways of response volatility-related genes