title: Neuroprogression and illness trajectories in bipolar disorder.
abstract: The longitudinal course of bipolar disorder is highly variable, and a subset of patients seems to present a progressive course associated with brain changes and functional impairment. Areas covered: We discuss the theory of neuroprogression in bipolar disorder. This concept considers the systemic stress response that occurs within mood episodes and late-stage deficits in functioning and cognition as well as neuroanatomic changes. We also discuss treatment refractoriness that may take place in some cases of bipolar disorder. We searched PubMed for articles published in any language up to June 4th, 2016. We found 315 abstracts and included 87 studies in our review. Expert commentary: We are of the opinion that the use of specific pharmacological strategies and functional remediation may be potentially useful in bipolar patients at late-stages. New analytic approaches using multimodal data hold the potential to help in identifying signatures of subgroups of patients who will develop a neuroprogressive course.
authors.affiliation: a Bipolar Disorder Program , Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre (HCPA) , Porto Alegre , Brazil.|b Graduation Program in Psychiatry and Department of Psychiatry , Universidade Federal do Rio Grande do Sul (UFRGS) , Porto Alegre , Brazil.
authors.forename: Natália S
authors.initials: NS
authors.lastname: Kapczinski
authors.affiliation: c Department of Psychiatry and Behavioral Sciences , University of Texas Health Science Center at Houston , Houston , TX , USA.
authors.forename: Benson
authors.initials: B
authors.lastname: Mwangi
authors.affiliation: c Department of Psychiatry and Behavioral Sciences , University of Texas Health Science Center at Houston , Houston , TX , USA.
authors.forename: Ryan M
authors.initials: RM
authors.lastname: Cassidy
authors.affiliation: d Graduation Program in Psychiatry , Universidade Federal das Ciências da Saúde , Porto Alegre , Brazil.
authors.forename: Diego
authors.initials: D
authors.lastname: Librenza-Garcia
authors.affiliation: d Graduation Program in Psychiatry , Universidade Federal das Ciências da Saúde , Porto Alegre , Brazil.
authors.forename: Mariane Bagatin
authors.initials: MB
authors.lastname: Bermudez
authors.affiliation: a Bipolar Disorder Program , Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre (HCPA) , Porto Alegre , Brazil.|b Graduation Program in Psychiatry and Department of Psychiatry , Universidade Federal do Rio Grande do Sul (UFRGS) , Porto Alegre , Brazil.
authors.forename: Márcia
authors.initials: M
authors.lastname: Kauer-Sant'anna
authors.affiliation: a Bipolar Disorder Program , Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre (HCPA) , Porto Alegre , Brazil.|b Graduation Program in Psychiatry and Department of Psychiatry , Universidade Federal do Rio Grande do Sul (UFRGS) , Porto Alegre , Brazil.
authors.forename: Flávio
authors.initials: F
authors.lastname: Kapczinski
authors.affiliation: a Bipolar Disorder Program , Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre (HCPA) , Porto Alegre , Brazil.|b Graduation Program in Psychiatry and Department of Psychiatry , Universidade Federal do Rio Grande do Sul (UFRGS) , Porto Alegre , Brazil.
authors.forename: Ives Cavalcante
authors.initials: IC
authors.lastname: Passos
mesh_terms: D001714:Bipolar Disorder / Q000503:physiopathology*; D001921:Brain / Q000503:physiopathology; D003071:Cognition; D018450:Disease Progression; D006801:Humans
keywords: Bipolar disorder; allostatic load; big data; machine learning; neuroprogression