TY - JOUR
T1 - Gender differences in developing biomarker-based major depressive disorder diagnostics
AU - Jentsch, Mike C.
AU - Burger, Huibert
AU - Meddens, Marjolein B.M.
AU - Beijers, Lian
AU - van den Heuvel, Edwin R.
AU - Meddens, Marcus J.M.
AU - Schoevers, Robert A.
PY - 2020/5/1
Y1 - 2020/5/1
N2 - 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.
AB - 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.
KW - Bio depression score
KW - Biomarker panel
KW - Diagnostic methods
KW - ELISA
KW - Gender
KW - Major depressive disorder
KW - Quantile-based prediction
UR - http://www.scopus.com/inward/record.url?scp=85084050304&partnerID=8YFLogxK
U2 - 10.3390/ijms21093039
DO - 10.3390/ijms21093039
M3 - Article
C2 - 32344909
AN - SCOPUS:85084050304
VL - 21
JO - International Journal of Molecular Sciences
JF - International Journal of Molecular Sciences
SN - 1422-0067
IS - 9
M1 - 3039
ER -