Literature DB >> 30755725

Baseline and follow-up activity and functional connectivity in reward neural circuitries in offspring at risk for bipolar disorder.

Heather E Acuff1,2, Amelia Versace3, Michele A Bertocci3, Cecile D Ladouceur3, Lindsay C Hanford3, Anna Manelis3, Kelly Monk3, Lisa Bonar3, Alicia McCaffrey3, Benjamin I Goldstein4, Tina R Goldstein3, Dara Sakolsky3, David Axelson5, Boris Birmaher3, Mary L Phillips3.   

Abstract

Bipolar disorder (BD) is a serious psychiatric illness with demonstrated abnormalities in reward processing circuitry. Examining this circuitry in youth at familial risk for BD may provide further insight into the underlying mechanisms of BD development. In this study, we compared offspring of bipolar parents (OBP, n = 32), offspring of comparison parents with non-BD psychopathology (OCP, n = 36), and offspring of healthy parents (OHP, n = 39) during a functional magnetic resonance imaging reward processing task. Elastic net regression analyses identified 26 activity, functional connectivity (FC), and demographic variables that explained 34.24% of the variance in group (λ = 0.224). ANOVA and post-hoc analyses revealed that OBP had significantly lower right ventral striatum-left caudal anterior cingulate FC to loss (OBP versus OCP: p = 0.028, OBP versus OHP: p = 0.015) and greater right pars orbitalis-left (OBP versus OCP: p = 0.003, OBP versus OHP: p = 0.036) and -right (OBP versus OCP: p = 0.001, OBP versus OHP: p = 0.038) orbitofrontal cortex FC to reward versus OCP and OHP, respectively. These findings were not affected by non-BD psychopathology, psychotropic medication use, or symptomatology. There were no changes in, or relationships between, neuroimaging or symptom measures at follow-up (mean(SD) = 2.70(1.22) year inter-scan interval) in a subset of youth with follow-up data (OBP, n = 14; OCP, n = 8; OHP, n = 19). These findings suggest that lower right ventral striatum-left caudal anterior cingulate FC to loss and greater right pars orbitalis-orbitofrontal cortex FC to reward may be trait-level neural markers that may reflect risk for BD in at-risk youth. These findings comprise important steps toward identifying neural markers of BD risk, which may enhance early identification and guide interventions for youth at familial risk for BD.

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Year:  2019        PMID: 30755725      PMCID: PMC6785101          DOI: 10.1038/s41386-019-0339-2

Source DB:  PubMed          Journal:  Neuropsychopharmacology        ISSN: 0893-133X            Impact factor:   7.853


  45 in total

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3.  How green is the grass on the other side? Frontopolar cortex and the evidence in favor of alternative courses of action.

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4.  The epidemiology of DSM-III-R bipolar I disorder in a general population survey.

Authors:  R C Kessler; D R Rubinow; C Holmes; J M Abelson; S Zhao
Journal:  Psychol Med       Date:  1997-09       Impact factor: 7.723

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Authors:  W Schultz; L Tremblay; J R Hollerman
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Review 7.  Dysregulation of the behavioral approach system (BAS) in bipolar spectrum disorders: review of theory and evidence.

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8.  Dissociable patterns of abnormal frontal cortical activation during anticipation of an uncertain reward or loss in bipolar versus major depression.

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9.  Reward processing in healthy offspring of parents with bipolar disorder.

Authors:  Manpreet K Singh; Ryan G Kelley; Meghan E Howe; Allan L Reiss; Ian H Gotlib; Kiki D Chang
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10.  Ventral striatum activity in response to reward: differences between bipolar I and II disorders.

Authors:  Xavier Caseras; Natalia S Lawrence; Kevin Murphy; Richard G Wise; Mary L Phillips
Journal:  Am J Psychiatry       Date:  2013-05       Impact factor: 18.112

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2.  Intrinsic Connectivity and Family Dynamics: Striatolimbic Markers of Risk and Resilience in Youth at Familial Risk for Mood Disorders.

Authors:  Adina S Fischer; Bailey Holt-Gosselin; Kelsey E Hagan; Scott L Fleming; Akua F Nimarko; Ian H Gotlib; Manpreet K Singh
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2022-03-08

3.  Protocol for a machine learning algorithm predicting depressive disorders using the T1w/T2w ratio.

Authors:  David A A Baranger; Yaroslav O Halchenko; Skye Satz; Rachel Ragozzino; Satish Iyengar; Holly A Swartz; Anna Manelis
Journal:  MethodsX       Date:  2021-12-02

4.  Neural correlates of reward processing distinguish healthy youth at familial risk for bipolar disorder from youth at familial risk for major depressive disorder.

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Journal:  Transl Psychiatry       Date:  2022-01-24       Impact factor: 6.222

5.  Changes in Intrinsic Brain Connectivity in Family-Focused Therapy Versus Standard Psychoeducation Among Youths at High Risk for Bipolar Disorder.

Authors:  Manpreet K Singh; Akua F Nimarko; Amy S Garrett; Aaron J Gorelik; Donna J Roybal; Patricia D Walshaw; Kiki D Chang; David J Miklowitz
Journal:  J Am Acad Child Adolesc Psychiatry       Date:  2020-08-01       Impact factor: 8.829

Review 6.  Neurobiology of bipolar disorders: a review of genetic components, signaling pathways, biochemical changes, and neuroimaging findings.

Authors:  Giselli Scaini; Samira S Valvassori; Alexandre P Diaz; Camila N Lima; Deborah Benevenuto; Gabriel R Fries; Joao Quevedo
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  6 in total

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