ReviewJournal of neural transmission (Vienna, Austria : 1996)2019
Blood-based biomarkers predicting response to antidepressants.
Review in Journal of neural transmission (Vienna, Austria : 1996), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The association of FKBP5 gene polymorphism with genetic susceptibility to depression and response to antidepressant treatment- a systematic review.BMC psychiatry · 2024Pooled it
- Brain-Derived Neurotrophic Factor (BDNF) as a Predictor of Treatment Response in Major Depressive Disorder (MDD): A Systematic Review.International journal of molecular sciences · 2023Pooled it
- The Role of Mitochondrial Dysfunction-Mediated Changes in Immune Cytokine Expression in the Pathophysiology and Treatment of Major Depressive Disorder.Molecular neurobiology · 2025Review
- The Neurometabolic Function of the Dopamine-Aminotransferase System.Metabolites · 2025Review
- Article
- Are There Biological Correlates of Response to Yoga-Based Interventions in Depression? A Critical Scoping Review.Brain sciences · 2024Article
- Genetic variation of the 5-HT1A rs6295, 5-HT2A rs6311, and CNR1 rs1049353 and an altered endocannabinoid system in depressed patients.Brain and behavior · 2023Article
- Kaixin Jieyu Granule attenuates neuroinflammation-induced depressive-like behavior through TLR4/PI3K/AKT/FOXO1 pathway: a study of network pharmacology and experimental validation.BMC complementary medicine and therapies · 2023Article
- Prognostic Significance of Blood-Based Baseline Biomarkers in Treatment-Resistant Depression: A Literature Review of Available Studies on Treatment Response.Brain sciences · 2022Review
- A novel joint index based on peripheral blood CD4+/CD8+ T cell ratio, albumin level, and monocyte count to determine the severity of major depressive disorder.BMC psychiatry · 2022Article
- Computational approaches and machine learning for individual-level treatment predictions.Psychopharmacology · 2021Review
- Article
- Ex vivo glucocorticoid receptor-mediated IL-10 response predicts the course of depression severity.Journal of neural transmission (Vienna, Austria : 1996) · 2021Article
- Mechanism of Chaihu Shugan Powder () for Treating Depression Based on Network Pharmacology.Chinese journal of integrative medicine · 2020Article
- Identification of Key Genes and the Pathophysiology Associated With Major Depressive Disorder Patients Based on Integrated Bioinformatics Analysis.Frontiers in psychiatry · 2020Article
- Weighted Gene Coexpression Network Analysis Identifies Specific Modules and Hub Genes Related to Major Depression.Neuropsychiatric disease and treatment · 2020Article
- Moving pharmacoepigenetics tools for depression toward clinical use.Journal of affective disorders · 2019Review
- Patterns of Membrane Protein Clustering in Peripheral Lymphocytes as Predictors of Therapeutic Outcomes in Major Depressive Disorder.Frontiers in pharmacology · 2019Review
- Genistein Improves the Major Depression through Suppressing the Expression of miR-221/222 by Targeting Connexin 43.Psychiatry investigation · 2018Article
- Precision pharmacotherapy: psychiatry's future direction in preventing, diagnosing, and treating mental disorders.Pharmacogenomics and personalized medicine · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Major depressive disorder is a common, serious and in some cases, life-threatening condition and affects approximately 350 million people globally. Although there is effective treatment available for it, more than 50% of the patients fail to respond to the first antidepressant they receive. The selection of a distinct treatment is still exclusively based on clinical judgment without incorporating lab-derived objective measures. However, there is growing evidence of biomarkers that it helps to improve diagnostic processes and treatment algorithms. Here genetic markers and blood-based biomarkers of the monoamine pathways, inflammatory pathways and the hypothalamic-pituitary-adrenal (HPA) axis are reviewed. Promising findings arise from studies investigating inflammatory pathways and immune markers that may identify patients suitable for anti-inflammatory based treatment regimes. Next, an early normalization of a disturbed HPA axis or depleted neurotrophic factors may predict stable treatment response. Genetic markers within the serotonergic system may identify patients who are vulnerable because of stressful life events, but evidence for guiding treatment regimes still is inconsistent. Therefore, there is still a great need for studies investigating and validating biomarkers for the prediction of treatment response to facilitate the treatment selection and shorten the time to remission and thus provide personalized medicine in psychiatry.
Indexed as
Identifiers
29374800What OpenQuestion holds
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 OpenQuestion graph.