Advances and Challenges in Depression Marker Research
Weifeng Jin, Shuzi Chen, Dan Li, Qing Chen, Mengyuan Zhu, Mengxia Wang, Xiaomei Fu, Ping Lin Department of Medical Laboratory, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of ChinaCorrespondence: Ping Lin, Email Linpingsun20000@aliyun.c...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Dove Medical Press
2025-07-01
|
| Series: | Neuropsychiatric Disease and Treatment |
| Subjects: | |
| Online Access: | https://www.dovepress.com/advances-and-challenges-in-depression-marker-research-peer-reviewed-fulltext-article-NDT |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849246119295451136 |
|---|---|
| author | Jin W Chen S Li D Chen Q Zhu M Wang M Fu X Lin P |
| author_facet | Jin W Chen S Li D Chen Q Zhu M Wang M Fu X Lin P |
| author_sort | Jin W |
| collection | DOAJ |
| description | Weifeng Jin, Shuzi Chen, Dan Li, Qing Chen, Mengyuan Zhu, Mengxia Wang, Xiaomei Fu, Ping Lin Department of Medical Laboratory, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of ChinaCorrespondence: Ping Lin, Email Linpingsun20000@aliyun.comAbstract: Depressive disorders diagnosis relies on subjective clinical assessment due to the lack of validated biomarkers. This review synthesizes recent advances in depression biomarkers across genetic, epigenetic, neuroendocrine, neuroimaging, immune/inflammatory, and gut microbiota domains. Literature was systematically searched via PubMed/Web of Science.We analyze mechanisms, highlight challenges (eg, clinical heterogeneity, inadequate animal models), and propose future directions: multidimensional bioinformatics, AI-driven models, RDoC framework implementation, and interdisciplinary collaboration. Critically, our analysis reveals that multimodal integration of biomarkers—rather than single-domain approaches—holds the greatest promise for overcoming diagnostic heterogeneity and guiding personalized interventions. These strategies may revolutionize MDD management through early detection and tailored therapeutics.Keywords: depressive disorders, biomarkers |
| format | Article |
| id | doaj-art-7d2707dc26444b339b09095ff7d6743e |
| institution | Kabale University |
| issn | 1178-2021 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Dove Medical Press |
| record_format | Article |
| series | Neuropsychiatric Disease and Treatment |
| spelling | doaj-art-7d2707dc26444b339b09095ff7d6743e2025-08-20T03:58:36ZengDove Medical PressNeuropsychiatric Disease and Treatment1178-20212025-07-01Volume 21Issue 115491567105345Advances and Challenges in Depression Marker ResearchJin W0Chen SLi D1Chen QZhu M2Wang MFu XLin P3Department of Medical Laboratorylablatoryshanghai mental healthy centerMedical LaboratoryWeifeng Jin, Shuzi Chen, Dan Li, Qing Chen, Mengyuan Zhu, Mengxia Wang, Xiaomei Fu, Ping Lin Department of Medical Laboratory, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of ChinaCorrespondence: Ping Lin, Email Linpingsun20000@aliyun.comAbstract: Depressive disorders diagnosis relies on subjective clinical assessment due to the lack of validated biomarkers. This review synthesizes recent advances in depression biomarkers across genetic, epigenetic, neuroendocrine, neuroimaging, immune/inflammatory, and gut microbiota domains. Literature was systematically searched via PubMed/Web of Science.We analyze mechanisms, highlight challenges (eg, clinical heterogeneity, inadequate animal models), and propose future directions: multidimensional bioinformatics, AI-driven models, RDoC framework implementation, and interdisciplinary collaboration. Critically, our analysis reveals that multimodal integration of biomarkers—rather than single-domain approaches—holds the greatest promise for overcoming diagnostic heterogeneity and guiding personalized interventions. These strategies may revolutionize MDD management through early detection and tailored therapeutics.Keywords: depressive disorders, biomarkershttps://www.dovepress.com/advances-and-challenges-in-depression-marker-research-peer-reviewed-fulltext-article-NDTdepressive disordersbiomarks |
| spellingShingle | Jin W Chen S Li D Chen Q Zhu M Wang M Fu X Lin P Advances and Challenges in Depression Marker Research Neuropsychiatric Disease and Treatment depressive disorders biomarks |
| title | Advances and Challenges in Depression Marker Research |
| title_full | Advances and Challenges in Depression Marker Research |
| title_fullStr | Advances and Challenges in Depression Marker Research |
| title_full_unstemmed | Advances and Challenges in Depression Marker Research |
| title_short | Advances and Challenges in Depression Marker Research |
| title_sort | advances and challenges in depression marker research |
| topic | depressive disorders biomarks |
| url | https://www.dovepress.com/advances-and-challenges-in-depression-marker-research-peer-reviewed-fulltext-article-NDT |
| work_keys_str_mv | AT jinw advancesandchallengesindepressionmarkerresearch AT chens advancesandchallengesindepressionmarkerresearch AT lid advancesandchallengesindepressionmarkerresearch AT chenq advancesandchallengesindepressionmarkerresearch AT zhum advancesandchallengesindepressionmarkerresearch AT wangm advancesandchallengesindepressionmarkerresearch AT fux advancesandchallengesindepressionmarkerresearch AT linp advancesandchallengesindepressionmarkerresearch |