Gender Differences in Developing Biomarker-Based Major Depressive Disorder Diagnostics

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.

Increased serum resistin but not G-CSF levels are associated in the pathophysiology of major depressive disorder: Findings from a case-control study

“…Jentsch et al reported higher serum and urine resistin levels in MDD patients. Also, they identified these elevations were more in females than males in a recent gender-specific investigation [53]. Also, another study discovered a positive association between resistin levels and atypical depressive symptoms.…”

Assessing Biomarker Stability and Assay Performance Parameters for the Use of Biomarkers in Mental Disorders; A Study of Early Stage Biomarker Assay Method Development

“…Within the psychiatric biomarker eld, several studies have identi ed potential biomarkers which could be utilized within a diagnostic setting but results varied and the road to actual clinical application is still long [6, 9,12,13,[34][35][36]. The complex underlying biological background of psychiatric disorders may however not be the only explanation for the huge variations in biomarkers studies.…”

“…serum/urine was obtained from an existing cohort of 40 patients with MDD, included based on a MINI diagnostic interview, for which biomarker data and HAM-D score were available [12]. Biomarker selection was performed on the basis of our previous work [12,13] and supplemented with Acetyl L-Carnitine as recent literature suggested that this biomarker may be implicated in the pathophysiology of MDD [22].…”

“…Therefore, recent focus shifted to nding disease, or subtype-associated biomarker patterns. Such approach has shown to be fruitful as evidenced by recent studies showing promising biomarker panels for major depressive disorder (MDD) [9][10][11][12][13]. However, as multiple biomarkers are needed to identify a disorder, the margin of error in terms of reliability is considered low demanding a high application stringency which currently hampers the advancement of these panels to a clinical stage [14,15].…”

Assessing biomarker stability and assay performance parameters for the use of biomarkers in mental disorders; A study of early stage biomarker assay method development

“…Therefore, recent focus shifted to nding disease, associated multiple biomarker patterns. Such an approach has shown to be fruitful by recent studies showing promising biomarker panels for major depressive disorder (MDD) (Bilello et al, 2015;Chen et al, 2018;Jentsch et al, 2020;Liu et al, 2015;van Buel et al, 2019). However, as multiple biomarkers are needed to identify a disorder, the margin of error in terms of reliability is considered small, demanding a high application stringency which currently hampers the advancement of these panels from a research setting to a clinical stage (Drucker and Krapfenbauer, 2013;Mcdermott et al, 2013).…”