title: Differences in resting-state functional magnetic resonance imaging functional network connectivity between schizophrenia and psychotic bipolar probands and their unaffected first-degree relatives.
abstract: BACKGROUND
  Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both disorders.
  
  
  METHODS
  We compared 70 schizophrenia and 64 psychotic bipolar probands, their respective unaffected first-degree relatives (n = 70, and n = 52), and 118 healthy subjects, all group age-, gender-, and ethnicity-matched. We used functional network connectivity analysis to measure differential connectivity among 16 functional magnetic resonance imaging resting state networks. First, we examined connectivity differences between probands and control subjects. Next, we probed these dysfunctional connections in relatives for potential endophenotypes. Network connectivity was then correlated with Positive and Negative Syndrome Scale (PANSS) scores to reveal clinical relationships.
  
  
  RESULTS
  Three different network pairs were differentially connected in probands (false-discovery rate corrected q < .05) involving five individual resting-state networks: (A) fronto/occipital, (B) anterior default mode/prefrontal, (C) meso/paralimbic, (D) fronto-temporal/paralimbic, and (E) sensory-motor. One abnormal pair was unique to schizophrenia, (C-E), one unique to bipolar, (C-D), and one (A-B) was shared. Two of these three combinations (A-B, C-E) were also abnormal in bipolar relatives but none was normal in schizophrenia relatives (nonsignificant trend for C-E). The paralimbic circuit (C-D), which uniquely distinguished bipolar probands, contained multiple mood-relevant regions. Network relationship C-D correlated significantly with PANSS negative scores in bipolar probands, and A-B with PANSS positive and general scores in schizophrenia.
  
  
  CONCLUSIONS
  Schizophrenia and psychotic bipolar probands share several abnormal resting state network connections, but there are also unique neural network underpinnings between disorders. We identified specific connections that might also be candidate psychosis endophenotypes.
authors.affiliation: Olin Neuropsychiatry Research Center, Hartford Hospital/Institute of Living, Hartford, Connecticut 06106, USA.
authors.forename: Shashwath A
authors.initials: SA
authors.lastname: Meda
authors.forename: Adrienne
authors.initials: A
authors.lastname: Gill
authors.forename: Michael C
authors.initials: MC
authors.lastname: Stevens
authors.forename: Raymond P
authors.initials: RP
authors.lastname: Lorenzoni
authors.forename: David C
authors.initials: DC
authors.lastname: Glahn
authors.forename: Vince D
authors.initials: VD
authors.lastname: Calhoun
authors.forename: John A
authors.initials: JA
authors.lastname: Sweeney
authors.forename: Carol A
authors.initials: CA
authors.lastname: Tamminga
authors.forename: Matcheri S
authors.initials: MS
authors.lastname: Keshavan
authors.forename: Gunvant
authors.initials: G
authors.lastname: Thaker
authors.forename: Godfrey D
authors.initials: GD
authors.lastname: Pearlson
mesh_terms: D000328:Adult; D001714:Bipolar Disorder / Q000235:genetics / Q000503:physiopathology*; D001921:Brain / Q000503:physiopathology*; D016022:Case-Control Studies; D005260:Female; D059907:Functional Neuroimaging; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D011618:Psychotic Disorders / Q000503:physiopathology*; D012559:Schizophrenia / Q000235:genetics / Q000503:physiopathology*