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Insomnia exhibits a clinically relevant relationship with major depressive disorder (MDD). Increasing evidence suggests that insomnia is associated with neurobiological alterations that resemble the pathophysiology of MDD. However, research in a clinical population is limited. The present study, therefore, aimed to investigate the relationship between insomnia and the main pathophysiological mechanisms of MDD in a clinical sample of individuals with MDD. Data were extracted from three cohorts (N = 227) and included an evaluation of depression severity (Quick Inventory of Depressive Symptomatology, QIDS-SR16) and insomnia severity (QIDS-SR16 insomnia items) as well as serum and urine assessments of 24 immunologic (e.g., tumour necrosis factor α receptor 2 and calprotectin), neurotrophic (e.g., brain-derived neurotrophic factor and epidermal growth factor), neuroendocrine (e.g., cortisol and aldosterone), neuropeptide (i.e., substance P), and metabolic (e.g., leptin and acetyl-L-carnitine) biomarkers. Linear regression analyses evaluating the association between insomnia severity and biomarker levels were conducted with and without controlling for depression severity (M = 17.32), antidepressant use (18.9%), gender (59.0% female; 40.5% male), age (M = 42.04), and the cohort of origin. The results demonstrated no significant associations between insomnia severity and biomarker levels. In conclusion, for the included biomarkers, current findings reveal no contribution of insomnia to the clinical pathophysiology of MDD.

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.

Major Depressive Disorder (MDD) is a heterogeneous disorder with a considerable symptomatic overlap with other psychiatric and somatic disorders. This study aims at providing evidence for association of a set of serum and urine biomarkers with MDD. We analyzed urine and serum samples of 40 MDD patients and 47 age- and sex-matched controls using 40 potential MDD biomarkers (21 serum biomarkers and 19 urine biomarkers). All participants were of Caucasian origin. We developed an algorithm to combine the heterogeneity at biomarker level. This method enabled the identification of correlating biomarkers based on differences in variation and distribution between groups, combined the outcome of the selected biomarkers, and calculated depression probability scores (the "bio depression score"). Phenotype permutation analysis showed a significant discrimination between MDD and euthymic (control) subjects for biomarkers in urine (P