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Illness, at-risk and resilience neural markers of early-stage bipolar disorder

J Affect Disord. 2018 Oct 1:238:16-23. doi: 10.1016/j.jad.2018.05.017. Epub 2018 May 21.

Abstract

Background: Current knowledge on objective and specific neural markers for bipolar risk and resilience-related processes is lacking, partly due to not subdividing high-risk individuals manifesting different levels of subclinical symptoms who possibly possess different levels of resilience.

Methods: We delineated grey matter markers for bipolar illness, genetic high risk (endophenotype) and resilience, through comparing across 42 young non-comorbid bipolar patients, 42 healthy controls, and 72 diagnosis-free, medication-naive high-genetic-risk individuals subdivided into a combined-high-risk group who additionally manifested bipolar risk-relevant subsyndromes (N = 38), and an asymptomatic high-risk group (N = 34). Complementary analyses assessed the additional predictive and classification values of grey matter markers beyond those of clinical scores, through using logistic regression and support vector machine analyses.

Results: Illness-related effects manifested as reduced grey matter volumes of bilateral temporal limbic-striatal and cerebellar regions, which significantly differentiated bipolar patients from healthy controls and improved clinical classification specificity by 20%. Reduced bilateral cerebellar grey matter volume emerged as a potential endophenotype and (along with parieto-occipital grey matter changes) separated combined-high-risk individuals from healthy and high-risk individuals, and increased clinical classification specificity by approximately 10% and 27%, respectively, while the relatively normalized cerebellar grey matter volumes in the high-risk sample may confer resilience.

Limitations: The cross-validation procedure was not performed on an independent sample using independently-derived features. The BD group had different age and sex distributions than some other groups which may not be fully addressable statistically.

Conclusions: Our framework can be applied in other measurement domains to derive complete profiles for bipolar patients and at-risk individuals, towards forming strategies for promoting resilience and preclinical intervention.

Keywords: Bipolar disorder; Cerebellum; Endophenotype; Grey matter volume; Resilience; Support vector machine.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Biomarkers / analysis
  • Bipolar Disorder / genetics
  • Bipolar Disorder / pathology*
  • Bipolar Disorder / psychology
  • Cerebellum / pathology
  • Endophenotypes
  • Female
  • Gray Matter / pathology*
  • Humans
  • Logistic Models
  • Male
  • Organ Size
  • Resilience, Psychological*
  • Risk Factors
  • Support Vector Machine

Substances

  • Biomarkers