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The Pathophysiology of Depression in Huntington's Disease
Tamrin Barta1, Yifat Glikmann-Johnston1, Peter McColgan2
1Turner Institute of Brain and Mental Health at the School of Psychological Sciences, and, Faculty of Medicine, Nursing and Health Sciences, Monash University.
Abstract:
Depression affects Huntington's disease (HD) gene-expansion carriers at up to four times the general population rate, yet its neurobiological underpinnings remain inadequately understood, potentially contributing persistent symptoms and suboptimal therapeutic outcomes despite commonly used interventions. Understanding the pathophysiological mechanisms remains constrained by fragmented, single-level approaches that do not capture interactions between biological systems. Here, we present an illustrative multilevel, reciprocal pathophysiological framework that integrates evidence across brain network (macro), neurotransmitter (meso), and molecular and systemic (micro) scales that contribute to depression vulnerability in HD. We highlight available evidence suggesting HD-related neurobiological changes contribute to depression. Preferential vulnerability of GABAergic medium spiny neurons in HD may contribute to dysfunction across cortico-basal-ganglia-thalamic circuits, interacting with cellular, molecular, and systemic processes. At the macro level, altered neurocircuitry is represented by structural changes and functional dysconnectivity across brain networks. The meso level represents cellular and neurotransmitter alterations, including glutamatergic, serotonergic, and dopaminergic dysregulation. At the micro level, molecular and systemic alterations include neuroendocrine, immune, neurotrophic, and gut microbiota-brain axis processes. We discuss how this reciprocal framework provides a foundation for generating testable hypotheses regarding the mechanisms underlying depression in HD and highlight future research priorities, including improved psychiatric phenotyping, longitudinal multimodal study designs, cross-species behavioral harmonization, and integration of behavioral, circuit-level, molecular, and systemic measures.
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