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Review
. 2018 Jan;41(1):18-30.
doi: 10.1016/j.tins.2017.10.006. Epub 2017 Nov 20.

The Emerging Neurobiology of Bipolar Disorder

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Review

The Emerging Neurobiology of Bipolar Disorder

Paul J Harrison et al. Trends Neurosci. 2018 Jan.

Abstract

Bipolar disorder (BD) is a leading cause of global disability. Its biological basis is unknown, and its treatment unsatisfactory. Here, we review two recent areas of progress. First, the discovery of risk genes and their implications, with a focus on voltage-gated calcium channels as part of the disease process and as a drug target. Second, facilitated by new technologies, it is increasingly apparent that the bipolar phenotype is more complex and nuanced than simply one of recurring manic and depressive episodes. One such feature is persistent mood instability, and efforts are underway to understand its mechanisms and its therapeutic potential. BD illustrates how psychiatry is being transformed by contemporary neuroscience, genomics, and digital approaches.

Keywords: L-type calcium channels; digital phenotyping; genomics; mood disorder; mood instability; therapeutics.

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Figures

Figure I
Figure I
The Voltage-Gated Calcium Channel (VGCC) Family of Proteins. (A) Structure of VGCCs, showing the transmembrane topology of the α1 subunit, its long intracellular C terminus and interactions with accessory (β and α2δ) subunits. (B) Dendrogram and nomenclature of the VGCC family.
Figure 1
Figure 1
Key Figure: Genomics, Neuroscience, and Treatment Innovation in Bipolar Disorder (BD) The study of voltage-gated calcium channels (VGCCs) in BD exemplifies the potential and the challenges of translating genomic discoveries into pathophysiology and therapeutics. Although sometimes portrayed as a one-way, bottom-up, process from genes to treatments, the wheel-like figure emphasises that it is iterative. Underpinning this approach is the increasing wealth of ‘big data’, since it is the scale of both the genomics and the contemporary digital approaches to phenotyping that have driven the developments discussed in this review. Looking ahead, an integrative, collaborative approach will be essential to link the power of big data with the more-focussed, hypothesis-driven studies that are required for most of the intervening segments.

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