Dataset Information

A review of potassium channels in bipolar disorder.

ABSTRACT: Although bipolar disorder (BP) is one of the most heritable psychiatric conditions, susceptibility genes for the disorder have yet to be conclusively identified. It is likely that variants in multiple genes across multiple pathways contribute to the genotype-phenotype relationship in the affected population. Recent evidence from genome-wide association studies implicates an entire class of genes related to the structure and regulation of ion channels, suggesting that the etiology of BP may arise from channelopathies. In this review, we examine the evidence for this hypothesis, with a focus on the potential role of voltage-gated potassium channels. We consider evidence from genetic and expression studies, and discuss the potential underlying biology. We consider animal models and treatment implications of the involvement of potassium ion channelopathy in BP. Finally, we explore intriguing parallels between BP and epilepsy, the signature channelopathy of the central nervous system.

SUBMITTER: Judy JT

PROVIDER: S-EPMC3678088 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A review of potassium channels in bipolar disorder.

Judy Jennifer T JT Zandi Peter P PP

Frontiers in genetics 20130611

Although bipolar disorder (BP) is one of the most heritable psychiatric conditions, susceptibility genes for the disorder have yet to be conclusively identified. It is likely that variants in multiple genes across multiple pathways contribute to the genotype-phenotype relationship in the affected population. Recent evidence from genome-wide association studies implicates an entire class of genes related to the structure and regulation of ion channels, suggesting that the etiology of BP may arise ...[more]

PMID: 23781230

Similar Datasets

Project description:Autism spectrum disorders (ASDs) are characterized by impaired ability to properly implement environmental stimuli that are essential to achieve a state of social and cultural exchange. Indeed, the main features of ASD are impairments of interpersonal relationships, verbal and non-verbal communication and restricted and repetitive behaviors. These aspects are often accompanied by several comorbidities such as motor delay, praxis impairment, gait abnormalities, insomnia, and above all epilepsy. Genetic analyses of autistic individuals uncovered deleterious mutations in several K(+) channel types strengthening the notion that their intrinsic dysfunction may play a central etiologic role in ASD. However, indirect implication of K(+) channels in ASD has been also reported. For instance, loss of fragile X mental retardation protein (FMRP) results in K(+) channels deregulation, network dysfunction and ASD-like cognitive and behavioral symptoms. This review provides an update on direct and indirect implications of K(+) channels in ASDs. Owing to a mounting body of evidence associating a channelopathy pathogenesis to autism and showing that nearly 500 ion channel proteins are encoded by the human genome, we propose to classify ASDs - whose susceptibility is significantly enhanced by ion channels defects, either in a monogenic or multigenic condition - in a new category named " c hannel A utism S pectrum D isorder" (channelASD; cASD) and introduce a new taxonomy (e.g., Kv x.y-channelASD and likewise Nav x.y-channelASD, Cav x.y-channelASD; etc.). This review also highlights some degree of clinical and genetic overlap between K(+) channelASDs and K(+) channelepsies, whereby such correlation suggests that a subcategory characterized by a channelASD-channelepsy phenotype may be distinguished. Ultimately, this overview aims to further understand the different clinical subgroups and help parse out the distinct biological basis of autism that are essential to establish patient-tailored treatments.

Project description:BackgroundHealth researchers are increasingly using natural language processing (NLP) to study various mental health conditions using both social media and electronic health records (EHRs). There is currently no published synthesis that relates specifically to the use of NLP methods for bipolar disorder, and this scoping review was conducted to synthesize valuable insights that have been presented in the literature.ObjectiveThis scoping review explored how NLP methods have been used in research to better understand bipolar disorder and identify opportunities for further use of these methods.MethodsA systematic, computerized search of index and free-text terms related to bipolar disorder and NLP was conducted using 5 databases and 1 anthology: MEDLINE, PsycINFO, Academic Search Ultimate, Scopus, Web of Science Core Collection, and the ACL Anthology.ResultsOf 507 identified studies, a total of 35 (6.9%) studies met the inclusion criteria. A narrative synthesis was used to describe the data, and the studies were grouped into four objectives: prediction and classification (n=25), characterization of the language of bipolar disorder (n=13), use of EHRs to measure health outcomes (n=3), and use of EHRs for phenotyping (n=2). Ethical considerations were reported in 60% (21/35) of the studies.ConclusionsThe current literature demonstrates how language analysis can be used to assist in and improve the provision of care for people living with bipolar disorder. Individuals with bipolar disorder and the medical community could benefit from research that uses NLP to investigate risk-taking, web-based services, social and occupational functioning, and the representation of gender in bipolar disorder populations on the web. Future research that implements NLP methods to study bipolar disorder should be governed by ethical principles, and any decisions regarding the collection and sharing of data sets should ultimately be made on a case-by-case basis, considering the risk to the data participants and whether their privacy can be ensured.

Dataset Information

A review of potassium channels in bipolar disorder.

Publications

A review of potassium channels in bipolar disorder.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets