{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Dima D"],"funding":["NIMH NIH HHS"],"pagination":["e706"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC5068872"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["6"],"pubmed_abstract":["Bipolar disorder (BD) is characterized by emotional dysregulation and cognitive deficits associated with abnormal connectivity between subcortical-primarily emotional processing regions-and prefrontal regulatory areas. Given the significant contribution of genetic factors to BD, studies in unaffected first-degree relatives can identify neural mechanisms of genetic risk but also resilience, thus paving the way for preventive interventions. Dynamic causal modeling (DCM) and random-effects Bayesian model selection were used to define and assess connectomic phenotypes linked to facial affect processing and working memory in a demographically matched sample of first-degree relatives carefully selected for resilience (n=25), euthymic patients with BD (n=41) and unrelated healthy controls (n=46)."],"journal":["Translational psychiatry"],"pubmed_title":["Connectomic markers of disease expression, genetic risk and resilience in bipolar disorder."],"pmcid":["PMC5068872"],"funding_grant_id":["R01 MH104284","R01 MH104284-01A1"],"pubmed_authors":["Roberts RE","Dima D","Frangou S"],"additional_accession":[]},"is_claimable":false,"name":"Connectomic markers of disease expression, genetic risk and resilience in bipolar disorder.","description":"Bipolar disorder (BD) is characterized by emotional dysregulation and cognitive deficits associated with abnormal connectivity between subcortical-primarily emotional processing regions-and prefrontal regulatory areas. Given the significant contribution of genetic factors to BD, studies in unaffected first-degree relatives can identify neural mechanisms of genetic risk but also resilience, thus paving the way for preventive interventions. Dynamic causal modeling (DCM) and random-effects Bayesian model selection were used to define and assess connectomic phenotypes linked to facial affect processing and working memory in a demographically matched sample of first-degree relatives carefully selected for resilience (n=25), euthymic patients with BD (n=41) and unrelated healthy controls (n=46).","dates":{"release":"2016-01-01T00:00:00Z","publication":"2016 Jan","modification":"2025-04-05T15:57:52.667Z","creation":"2019-03-27T02:27:00Z"},"accession":"S-EPMC5068872","cross_references":{"pubmed":["26731443"],"doi":["10.1038/tp.2015.193"]}}