DOI: 10.1007/s13311-017-0538-7 Pages: 698-715
Article Type: Review

HCN Channel Targets for Novel Antidepressant Treatment

1. Icahn School of Medicine at Mount Sinai, Department of Pharmacological Sciences and Institute for Systems Biomedicine

2. Icahn School of Medicine at Mount Sinai, Fishberg Department of Neuroscience and Friedman Brain Institute

Correspondence to:
Ming-Hu Han



Major depressive disorder (MDD) is a chronic and potentially life threatening illness that carries a staggering global burden. Characterized by depressed mood, MDD is often difficult to diagnose and treat owing to heterogeneity of syndrome and complex etiology. Contemporary antidepressant treatments are based on improved monoamine-based formulations from serendipitous discoveries made > 60 years ago. Novel antidepressant treatments are necessary, as roughly half of patients using available antidepressants do not see long-term remission of depressive symptoms. Current development of treatment options focuses on generating efficacious antidepressants, identifying depression-related neural substrates, and better understanding the pathophysiological mechanisms of depression. Recent insight into the brain’s mesocorticolimbic circuitry from animal models of depression underscores the importance of ionic mechanisms in neuronal homeostasis and dysregulation, and substantial evidence highlights a potential role for ion channels in mediating depression-related excitability changes. In particular, hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are essential regulators of neuronal excitability. In this review, we describe seminal research on HCN channels in the prefrontal cortex and hippocampus in stress and depression-related behaviors, and highlight substantial evidence within the ventral tegmental area supporting the development of novel therapeutics targeting HCN channels in MDD. We argue that methods targeting the activity of reward-related brain areas have significant potential as superior treatments for depression.

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  • Online: May 30, 2017

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