Predicting brain-age from multimodal imaging data captures cognitive impairment.
LIFE Adult

Abstract (Expand)

The disparity between the chronological age of an individual and their brain-age measured based on biological information has the potential to offer clinically relevant biomarkers of neurological … syndromes that emerge late in the lifespan. While prior brain-age prediction studies have relied exclusively on either structural or functional brain data, here we investigate how multimodal brain-imaging data improves age prediction. Using cortical anatomy and whole-brain functional connectivity on a large adult lifespan sample (N=2354, age 19-82), we found that multimodal data improves brain-based age prediction, resulting in a mean absolute prediction error of 4.29 years. Furthermore, we found that the discrepancy between predicted age and chronological age captures cognitive impairment. Importantly, the brain-age measure was robust to confounding effects: head motion did not drive brain-based age prediction and our models generalized reasonably to an independent dataset acquired at a different site (N=475). Generalization performance was increased by training models on a larger and more heterogeneous dataset. The robustness of multimodal brain-age prediction to confounds, generalizability across sites, and sensitivity to clinically-relevant impairments, suggests promising future application to the early prediction of neurocognitive disorders.

Authors: F. Liem, G. Varoquaux, J. Kynast, F. Beyer, S. Kharabian Masouleh, J. M. Huntenburg, L. Lampe, M. Rahim, A. Abraham, R. C. Craddock, S. Riedel-Heller, T. Luck, M. Loeffler, M. L. Schroeter, A. V. Witte, A. Villringer, D. S. Margulies

Date Published: 1st Mar 2017

Publication Type: Journal article

First evidence for glial pathology in late life minor depression: S100B is increased in males with minor depression.
LIFE Adult

Abstract (Expand)

Minor depression is diagnosed when a patient suffers from 2 to 4 depressive symptoms for at least 2 weeks. Though minor depression is a widespread phenomenon, its pathophysiology has hardly been studied. … To get a first insight into the pathophysiological mechanisms underlying this disorder we assessed serum levels of biomarkers for plasticity, glial and neuronal function: brain-derived neurotrophic factor (BDNF), S100B and neuron specific enolase (NSE). 27 subjects with minor depressive episode and 82 healthy subjects over 60 years of age were selected from the database of the Leipzig population-based study of civilization diseases (LIFE). Serum levels of BDNF, S100B and NSE were compared between groups, and correlated with age, body-mass index (BMI), and degree of white matter hyperintensities (score on Fazekas scale). S100B was significantly increased in males with minor depression in comparison to healthy males, whereas other biomarkers did not differ between groups (p = 0.10-0.66). NSE correlated with Fazekas score in patients with minor depression (rs = 0.436, p = 0.048) and in the whole sample (rs = 0.252, p = 0.019). S100B correlated with BMI (rs = 0.246, p = 0.031) and with age in healthy subjects (rs = 0.345, p = 0.002). Increased S100B in males with minor depression, without alterations in BDNF and NSE, supports the glial hypothesis of depression. Correlation between white matter hyperintensities and NSE underscores the vascular hypothesis of late life depression.

Authors: M. Polyakova, C. Sander, K. Arelin, L. Lampe, T. Luck, M. Luppa, J. Kratzsch, K. T. Hoffmann, S. Riedel-Heller, A. Villringer, P. Schoenknecht, M. L. Schroeter

Date Published: 27th Oct 2015

Publication Type: Not specified

Human Diseases: mental depression

BDNF as a biomarker for successful treatment of mood disorders: a systematic & quantitative meta-analysis.
LIFE Adult

Abstract (Expand)

BACKGROUND: Peripheral brain-derived neurotrophic factor (BDNF) is decreased in acute major depressive disorder (MDD) and bipolar disorder (BD) and recovered after treatment. Here we validated on a … meta-analytical level whether BDNF restores differentially according to treatment response and whose measurements could be used as a biomarker, plasma or serum. METHODS: Using strict inclusion criteria, we compared BDNF in healthy controls and patients with MDD (38 studies, n=6619), and BD (17 studies, n=1447). Pre- and post-treatment BDNF levels were meta-analyzed according to treatment response in patients from 21 MDD studies (n=735) and 7 BD studies (n=88). Serum and plasma subgroups were analyzed, publication bias was assessed and heterogeneity was investigated. RESULTS: Serum and plasma BDNF were decreased in acute MDD and BD, and did not differ in euthymia in comparison with control subjects. Antidepressive treatment increased serum BDNF levels in MDD in responders (Cohens d (d)=1.27, p=4.4E-07) and remitters (d=0.89, p=0.01), significantly more than in non-responders (d=0.11, p=0.69). For plasma BDNF in MDD and for BD, the evidence was insufficient for a meta-analysis. Although no significant difference was found between serum and plasma ES, variance of plasma ES was higher. LIMITATIONS: Between-study heterogeneity was explained only partially; signs of publication bias in serum studies. CONCLUSION: Serum BDNF might be regarded as a biomarker for the successful treatment of MDD. Serum measurements seem more reliable than plasma ones. Further research should focus on defining optimal time points for BDNF measurements and increase evidence for the usage of BDNF as a predictive biomarker in BD.

Authors: M. Polyakova, K. Stuke, K. Schuemberg, K. Mueller, P. Schoenknecht, M. L. Schroeter

Date Published: 15th Mar 2015

Publication Type: Not specified

Human Diseases: mental depression, bipolar disorder

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