Cross-Sectional and Longitudinal Relationships between Depressive Symptoms and Brain Atrophy in MS Patients

Front Hum Neurosci. 2016 Dec 16:10:622. doi: 10.3389/fnhum.2016.00622. eCollection 2016.

Abstract

Introduction: Depressive symptoms are a frequent and distressing phenomenon in Multiple Sclerosis (MS) patients. Cross-sectional research links these symptoms to reduced brain gray matter volumes in parts of the prefrontal and temporal lobe as well as subcortical structures like the hippocampus, nucleus caudatus and globus pallidus. Nevertheless, prospective relationships between regional gray matter volume and the course of depressive symptoms are poorly understood. Methods: Forty-four patients with relapsing-remitting or secondary progressive MS participated in a prospective study with two assessments of depressive symptoms and high-resolution MRI with an inter-test-interval of 17 months. Relationships between baseline gray matter volume and baseline depressive symptoms, as well as prospective associations between the development of atrophy and depression were assessed using voxel-based morphometry (VBM). Results: Cross-sectional analyses revealed an association between depressive symptoms and gray matter loss in the left temporal lobe. Prospective analysis showed that gray matter losses in the right middle cingulate and middle frontal gyrus at baseline predicted increasing depressive symptoms during follow-up. Increase in depressive symptoms was related to a concomitant increase in atrophy in the left thalamus and right globus pallidus. Discussion: Our results fit well into the concept of a disturbed cortico-striatal-pallido-thalamic loop in depression. In this framework, progressive gray matter loss in limbic basal ganglia structures including globus pallidus and thalamus may lead to depression-typical deficits in hedonic motivation, whereas atrophy of the prefrontal cortex may contribute to maladaptive coping strategies, promoting an unfavorable development of depressive symptoms.

Keywords: depression; multiple sclerosis; prediction; prospective study; structural MRI.