ArticleInternational journal of molecular sciences2020
Gender Differences in Developing Biomarker-Based Major Depressive Disorder Diagnostics.
Article in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Trial
- Feasibility of diagnosing major depressive disorder with a panel of serum and urine biomarkers.BJPsych open · 2026Article
- Identification of AICD-associated transcriptomic markers in major depressive disorder.Frontiers in psychiatry · 2026Article
- Review
- The Relationship between Insomnia and the Pathophysiology of Major Depressive Disorder: An Evaluation of a Broad Selection of Serum and Urine Biomarkers.International journal of molecular sciences · 2023Article
- Critical Considerations for Investigating MicroRNAs during Tumorigenesis: A Case Study in Conceptual and Contextual Nuances of miR-211-5p in Melanoma.Epigenomes · 2023Review
- Depression and HIV: a scoping review in search of neuroimmune biomarkers.Brain communications · 2023Article
- Changes in major psychiatric disorders in children and adolescents from 2001 to 2020: A retrospective single-center study.Frontiers in psychiatry · 2022Article
- Combined serum IL-6, C-reactive protein, and cortisol may distinguish patients with anhedonia in major depressive disorder.Frontiers in molecular neuroscience · 2022Article
- Article
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Authors and funding
7 authors.
Funding
Abstract
The identification of biomarkers associated with major depressive disorder (MDD) holds great promise to develop an objective laboratory test. However, current biomarkers lack discriminative power due to the complex biological background, and not much is known about the influence of potential modifiers such as gender. We first performed a cross-sectional study on the discriminative power of biomarkers for MDD by investigating gender differences in biomarker levels. Out of 28 biomarkers, 21 biomarkers were significantly different between genders. Second, a novel statistical approach was applied to investigate the effect of gender on MDD disease classification using a panel of biomarkers. Eleven biomarkers were identified in men and eight in women, three of which were active in both genders. Gender stratification caused a (non-significant) increase of Area Under Curve (AUC) for men (AUC = 0.806) and women (AUC = 0.807) compared to non-stratification (AUC = 0.739). In conclusion, we have shown that there are differences in biomarker levels between men and women which may impact accurate disease classification of MDD when gender is not taken into account.
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