ArticleJournal of inflammation research2021
Potential Biomarkers for Diagnosing Major Depressive Disorder Patients with Suicidal Ideation.
Article in Journal of inflammation research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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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
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 27 citations in OpenAlex.
- Role of machine learning algorithms in suicide risk prediction: a systematic review-meta analysis of clinical studies.BMC medical informatics and decision making · 2024Pooled it
- Potential Inflammatory Biomarkers for Major Depressive Disorder Related to Suicidal Behaviors: A Systematic Review.International journal of molecular sciences · 2023Pooled it
- Unraveling the role of IL-17 signaling pathway in breast cancer-related depression: insights from in vivo/in vitro models and transcriptomic analysis.Functional & integrative genomics · 2026Article
- Towards Objective Major Depressive Disorder Detection: a Systematic Review and Meta-Analysis of Diagnostic Biomarkers.The Psychiatric quarterly · 2025Review
- Leaky Gut Biomarkers as Predictors of Depression and Suicidal Risk: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2025Review
- Differential relationships among homocysteine levels, cognitive deficits, and low-frequency fluctuation in brain activity in bipolar disorder with suicidal ideation.BMC psychiatry · 2025Article
- A Clinical-Metabolic Prediction Model for Suicidal Behaviors Risk Stratification in First-Admission Major Depressive Disorder: A Cross-Sectional Analysis.Neuropsychiatric disease and treatment · 2025Article
- Investigating the modulatory effects of lactoferrin on depressed rats through 16S rDNA gene sequencing and LC-MS metabolomics analysis.Scientific reports · 2024Article
- Suicide, neuroinflammation and other physiological alterations.European archives of psychiatry and clinical neuroscience · 2024Review
- Oral D-ribose causes depressive-like behavior by altering glycerophospholipid metabolism via the gut-brain axis.Communications biology · 2024Article
- Development and validation of a nomogram for suicide attempts in patients with first-episode drug-naïve major depressive disorder.Frontiers in psychiatry · 2024Article
- Peripheral Markers of Suicidal Behavior: Current Findings and Clinical Implications.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2023Review
- Multi-omics data reveals the important role of glycerophospholipid metabolism in the crosstalk between gut and brain in depression.Journal of translational medicine · 2023Article
- Multi-omics data reveals the disturbance of glycerophospholipid metabolism caused by disordered gut microbiota in depressed mice.Journal of advanced research · 2022Article
- Suicide Biomarkers to Predict Risk, Classify Diagnostic Subtypes, and Identify Novel Therapeutic Targets: 5 Years of Promising Research.The international journal of neuropsychopharmacology · 2022Review
- Bioimpedance Body Measures and Serum Lipid Levels in Masculine Depression.Frontiers in psychiatry · 2022Article
- Peripheral blood cytokines as potential diagnostic biomarkers of suicidal ideation in patients with first-episode drug-naïve major depressive disorder.Frontiers in public health · 2022Article
- Gut Microbiota-Related Inflammation Factors as a Potential Biomarker for Diagnosing Major Depressive Disorder.Frontiers in cellular and infection microbiology · 2022Article
- Gut Microbiota-Derived Inflammation-Related Serum Metabolites as Potential Biomarkers for Major Depressive Disorder.Journal of inflammation research · 2021Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMajor depressive disorder (MDD) and suicide are two major health problems, but there are still no objective methods to diagnose MDD or suicidal ideation (SI). This study was conducted to identify potential biomarkers for diagnosing MDD patients with SI.
methodsFirst-episode drug-naïve MDD patients with SI and demographics-matched healthy controls (HCs) were recruited. First-episode drug-naïve MDD patients without SI were also included. The serum lipids, C-reactive protein (CRP), transferring (TRSF), homocysteine (HCY) and alpha 1-antitrypsin (AAT) in serum were detected. The univariate and multivariate statistical analyses were used to identify and validate the potential biomarkers.
resultsThe 86 HCs, 53 MDD patients with SI and 20 MDD patients without SI were included in this study. Four potential biomarkers were identified: AAT, TRSF, high-density lipoprotein cholesterol (HDLC), and apolipoprotein A1 (APOA1). After one month treatment, the levels of AAT and APOA1 were significantly improved. The panel consisting of these potential biomarkers had an excellent diagnostic performance, yielding an area under the ROC curve (AUC) of 0.994 and 0.990 in the training and testing set, respectively. Moreover, this panel could effectively distinguish MDD patients with SI from MDD patients without SI (AUC=0.928).
conclusionThese results showed that these potential biomarkers could facilitate the development of an objective method for diagnosing MDD patients with SI, and the decreased AAT levels in MDD patients might lead to the appearance of SI by resulting in the elevated inflammation.
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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.