title: Early signs of anomalous neural functional connectivity in healthy offspring of parents with bipolar disorder.
abstract: OBJECTIVE
  Bipolar disorder (BD) has been associated with dysfunctional brain connectivity and with family chaos. It is not known whether aberrant connectivity occurs before illness onset, representing vulnerability for developing BD amidst family chaos. We used resting-state functional magnetic resonance imaging (fMRI) to examine neural network dysfunction in healthy offspring living with parents with BD and healthy comparison youth.
  
  
  METHODS
  Using two complementary methodologies [data-driven independent component analysis (ICA) and hypothesis-driven region-of-interest (ROI)-based intrinsic connectivity], we examined resting-state fMRI data in 8-17-year-old healthy offspring of a parent with BD (n = 24; high risk) and age-matched healthy youth without any personal or family psychopathology (n = 25; low risk).
  
  
  RESULTS
  ICA revealed that, relative to low-risk youth, high-risk youth showed increased connectivity in the ventrolateral prefrontal cortex (VLPFC) subregion of the left executive control network (ECN), which includes frontoparietal regions important for emotion regulation. ROI-based analyses revealed that high-risk versus low-risk youth had decreased connectivities between the left amygdala and pregenual cingulate, between the subgenual cingulate and supplementary motor cortex, and between the left VLPFC and left caudate. High-risk youth showed stronger connections in the VLPFC with age and higher functioning, which may be neuroprotective, and weaker connections between the left VLPFC and caudate with more family chaos, suggesting an environmental influence on frontostriatal connectivity.
  
  
  CONCLUSIONS
  Healthy offspring of parents with BD show atypical patterns of prefrontal and subcortical intrinsic connectivity that may be early markers of resilience to or vulnerability for developing BD. Longitudinal studies are needed to determine whether these patterns predict outcomes.
authors.affiliation: Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.
authors.forename: Manpreet K
authors.initials: MK
authors.lastname: Singh
authors.forename: Kiki D
authors.initials: KD
authors.lastname: Chang
authors.forename: Ryan G
authors.initials: RG
authors.lastname: Kelley
authors.forename: Manish
authors.initials: M
authors.lastname: Saggar
authors.forename: Allan L
authors.initials: AL
authors.lastname: Reiss
authors.forename: Ian H
authors.initials: IH
authors.lastname: Gotlib
mesh_terms: D000293:Adolescent; D001714:Bipolar Disorder / Q000175:diagnosis* / Q000235:genetics* / Q000523:psychology; D001921:Brain / Q000098:blood supply / Q000503:physiopathology*; D002648:Child; D016241:Child of Impaired Parents / Q000523:psychology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D009434:Neural Pathways / Q000098:blood supply / Q000502:physiology; D010100:Oxygen; D010290:Parents; D025341:Principal Component Analysis; D011569:Psychiatric Status Rating Scales; D013223:Statistics as Topic
chemical_list: D010100:Oxygen
keywords: amygdala; bipolar; functional connectivity; resting state; risk; ventrolateral prefrontal cortex