Major depressive disorder is associated with changes in a cluster of serum and urine biomarkers

Buel, E. M. van; Meddens, Marcus; Arnoldussen, Eduard A; Heuvel, Edwin R. van den; Bohlmeijer, Willem C; Boer, Johan A. den; Kobold, Anneke Muller; Winter, Leandra J M Boonman-de; Rumpt, Dirk van; Timmers, Lambertus F J; Veerman, Mattheus F A; Kamphuis, Johannes S.; Gladkevich, Anatoliy V.; Schoevers, Robert A.; Luiten, P.G.M.; Eisel, Ulrich; Bosker, Fokko J.; Klein, Hans

doi:10.1016/j.jpsychores.2019.109796

Cited by 15 publications

(24 citation statements)

References 27 publications

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“…An advantage of the new advanced statistical method we used is that we were able to utilize the full informative potential of our biomarkers with respect to underlying biomarker dynamics and the contribution to disease status, thereby limiting the effects of the high variability in biological pathways involved in MDD. The application of advanced statistical methods is not new: others have shown that by utilizing potential information buried within biomarker data, one can develop biomarker panels with high discriminative power [5,15]. This concept of identifying contributing biomarkers is in line with our QBP method, which showed not only that with gender stratification, different patterns of contributing biomarkers can be identified, but that this method also eliminated non-relevant biomarkers which were previously identified as biomarkers associated with MDD and vice versa.…”

Section: Discussionsupporting

confidence: 66%

“…Another factor which could have had substantial effect on the performance of our biomarker panel is the Caucasian descent of our study population, which may limit extrapolation to other ethnic groups. In a recent study, van Buel et al (2019) showed that the AUC varies using the same set of biomarkers when stratified for Caucasians and other ethnicities [15].…”

Section: Discussionmentioning

confidence: 99%

“…For the binary classification of MDD presence, a newly developed method called quantile-based prediction (QBP) was used [15]. In short, QBP assigns scores to certain percentiles in the left and right tails of empirical biomarker distributions.…”

Section: Discussionmentioning

confidence: 99%

“…The selection of biomarkers was based on a previous study by our group [15] which identified seven biomarkers in serum and eleven in urine. These biomarkers were supplemented with an additional seven biomarkers in serum and three in urine, based on a literature search using various combinations of the terms MDD, depression, biomarkers, urine, serum and pathophysiology.…”

Section: Biomarker Selection and Measurementsmentioning

confidence: 99%

“…By using multiple markers, the discriminative power of a test is likely to be increased by covering a broader range of the biological processes accompanying MDD [5,14,15]. Nevertheless, discriminative power may still vary depending on individual patient characteristics [5,[15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

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Gender Differences in Developing Biomarker-Based Major Depressive Disorder Diagnostics

jentsch

Burger

Meddens³

et al. 2020

IJMS

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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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Section: Discussionsupporting

confidence: 66%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Biomarker Selection and Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Gender Differences in Developing Biomarker-Based Major Depressive Disorder Diagnostics

jentsch

Burger

Meddens³

et al. 2020

IJMS

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Serum indoleamine 2, 3-dioxygenase and tryptophan-2, 3-dioxygenase: potential biomarkers for the diagnosis of major depressive disorder

Liang,

Cheng,

Shan

et al. 2024

Psychopharmacology

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New challenges in the COVID-19 pandemic

Fiedorowicz

2020

Journal of Psychosomatic Research

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Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre-including this research content-immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

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Major depressive disorder is associated with changes in a cluster of serum and urine biomarkers

Cited by 15 publications

References 27 publications

Gender Differences in Developing Biomarker-Based Major Depressive Disorder Diagnostics

Gender Differences in Developing Biomarker-Based Major Depressive Disorder Diagnostics

Serum indoleamine 2, 3-dioxygenase and tryptophan-2, 3-dioxygenase: potential biomarkers for the diagnosis of major depressive disorder

New challenges in the COVID-19 pandemic

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