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 stu...

Full description

Saved in:
Bibliographic Details
Main Authors: Haiping Tang, Yan Xia, Chenjie Gao, Yufan Cai, Yongqi Shao, Wenji Chen, Yonggui Yuan, Chunyu Liu, Zhijun Zhang, Zhi Xu
Format: Article
Language:English
Published: BMC 2025-05-01
Series:BMC Psychiatry
Subjects:
Online Access:https://doi.org/10.1186/s12888-025-06895-0
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849325930771644416
author Haiping Tang
Yan Xia
Chenjie Gao
Yufan Cai
Yongqi Shao
Wenji Chen
Yonggui Yuan
Chunyu Liu
Zhijun Zhang
Zhi Xu
author_facet Haiping Tang
Yan Xia
Chenjie Gao
Yufan Cai
Yongqi Shao
Wenji Chen
Yonggui Yuan
Chunyu Liu
Zhijun Zhang
Zhi Xu
author_sort Haiping Tang
collection DOAJ
description 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.
format Article
id doaj-art-9c4e0a7da3324a3fbb9eed72bde1c1e0
institution Kabale University
issn 1471-244X
language English
publishDate 2025-05-01
publisher BMC
record_format Article
series BMC Psychiatry
spelling doaj-art-9c4e0a7da3324a3fbb9eed72bde1c1e02025-08-20T03:48:18ZengBMCBMC Psychiatry1471-244X2025-05-0125111410.1186/s12888-025-06895-0Association of psychosocial factors and biological pathways identified from rare-variant analysis with longitudinal trajectories of treatment response in major depressive disorderHaiping Tang0Yan Xia1Chenjie Gao2Yufan Cai3Yongqi Shao4Wenji Chen5Yonggui Yuan6Chunyu Liu7Zhijun Zhang8Zhi Xu9Department of Psychosomatics and Psychiatry, School of Medicine, Zhongda Hospital, Southeast UniversityDepartment of Molecular Biophysics and Biochemistry, Yale UniversityDepartment of Psychosomatics and Psychiatry, School of Medicine, Zhongda Hospital, Southeast UniversityDepartment of Psychosomatics and Psychiatry, School of Medicine, Zhongda Hospital, Southeast UniversityDepartment of Psychosomatics and Psychiatry, School of Medicine, Zhongda Hospital, Southeast UniversityDepartment of General Practice, School of Medicine, Zhongda Hospital, Southeast UniversityDepartment of Psychosomatics and Psychiatry, School of Medicine, Zhongda Hospital, Southeast UniversityCenter for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South UniversityDepartment of Neurology, Affiliated Zhongda Hospital, Southeast UniversityDepartment of Psychosomatics and Psychiatry, School of Medicine, Zhongda Hospital, Southeast UniversityAbstract 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.https://doi.org/10.1186/s12888-025-06895-0Antidepressant efficacyTarget exome sequencingRare variantsResponse trajectoriesGenetic factorsPsychosocial factors
spellingShingle Haiping Tang
Yan Xia
Chenjie Gao
Yufan Cai
Yongqi Shao
Wenji Chen
Yonggui Yuan
Chunyu Liu
Zhijun Zhang
Zhi Xu
Association of psychosocial factors and biological pathways identified from rare-variant analysis with longitudinal trajectories of treatment response in major depressive disorder
BMC Psychiatry
Antidepressant efficacy
Target exome sequencing
Rare variants
Response trajectories
Genetic factors
Psychosocial factors
title Association of psychosocial factors and biological pathways identified from rare-variant analysis with longitudinal trajectories of treatment response in major depressive disorder
title_full Association of psychosocial factors and biological pathways identified from rare-variant analysis with longitudinal trajectories of treatment response in major depressive disorder
title_fullStr Association of psychosocial factors and biological pathways identified from rare-variant analysis with longitudinal trajectories of treatment response in major depressive disorder
title_full_unstemmed Association of psychosocial factors and biological pathways identified from rare-variant analysis with longitudinal trajectories of treatment response in major depressive disorder
title_short Association of psychosocial factors and biological pathways identified from rare-variant analysis with longitudinal trajectories of treatment response in major depressive disorder
title_sort association of psychosocial factors and biological pathways identified from rare variant analysis with longitudinal trajectories of treatment response in major depressive disorder
topic Antidepressant efficacy
Target exome sequencing
Rare variants
Response trajectories
Genetic factors
Psychosocial factors
url https://doi.org/10.1186/s12888-025-06895-0
work_keys_str_mv AT haipingtang associationofpsychosocialfactorsandbiologicalpathwaysidentifiedfromrarevariantanalysiswithlongitudinaltrajectoriesoftreatmentresponseinmajordepressivedisorder
AT yanxia associationofpsychosocialfactorsandbiologicalpathwaysidentifiedfromrarevariantanalysiswithlongitudinaltrajectoriesoftreatmentresponseinmajordepressivedisorder
AT chenjiegao associationofpsychosocialfactorsandbiologicalpathwaysidentifiedfromrarevariantanalysiswithlongitudinaltrajectoriesoftreatmentresponseinmajordepressivedisorder
AT yufancai associationofpsychosocialfactorsandbiologicalpathwaysidentifiedfromrarevariantanalysiswithlongitudinaltrajectoriesoftreatmentresponseinmajordepressivedisorder
AT yongqishao associationofpsychosocialfactorsandbiologicalpathwaysidentifiedfromrarevariantanalysiswithlongitudinaltrajectoriesoftreatmentresponseinmajordepressivedisorder
AT wenjichen associationofpsychosocialfactorsandbiologicalpathwaysidentifiedfromrarevariantanalysiswithlongitudinaltrajectoriesoftreatmentresponseinmajordepressivedisorder
AT yongguiyuan associationofpsychosocialfactorsandbiologicalpathwaysidentifiedfromrarevariantanalysiswithlongitudinaltrajectoriesoftreatmentresponseinmajordepressivedisorder
AT chunyuliu associationofpsychosocialfactorsandbiologicalpathwaysidentifiedfromrarevariantanalysiswithlongitudinaltrajectoriesoftreatmentresponseinmajordepressivedisorder
AT zhijunzhang associationofpsychosocialfactorsandbiologicalpathwaysidentifiedfromrarevariantanalysiswithlongitudinaltrajectoriesoftreatmentresponseinmajordepressivedisorder
AT zhixu associationofpsychosocialfactorsandbiologicalpathwaysidentifiedfromrarevariantanalysiswithlongitudinaltrajectoriesoftreatmentresponseinmajordepressivedisorder