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Over the past few decades, neuroimaging research in bipolar disorder has identified neural differences underlying cognitive and emotional processing. However, substantial clinical and methodological heterogeneity across neuroimaging experiments (resulting from differences in healthcare systems, diagnostic subtypes, mood state, treatment response, comorbidity, chronicity, and severity)—as well as additional factors including methodological differences—can hinder the identification of consistent neural biomarkers of bipolar disorder. 

In spite of the challenges of the heterogeneity of neuroimaging studies, meta-analyses are needed to reconcile the literature’s pitfalls and provide a framework to test whether the findings of small, heterogeneous studies can be reproducible across different studies. Meta-analyses can be used to synthesize results of individual studies, highlight irregularities and issues in the field, and comprehensively, quantitatively summarize and integrate disparate findings.

A team of scientists including Maya Schumer (neuroscience PhD candidate, University of Pittsburgh); Henry Chase, PhD (Research Assistant Professor of Psychiatry); Renata Rozovsky, PhD (postdoctoral associate); and Mary Phillips, MD, MD (Cantab) (Distinguished Professor of Psychiatry, Clinical and Translational Science, and Bioengineering, and Pittsburgh Foundation-Emmerling Endowed Chair in Psychotic Disorders), published a meta-analysis in Molecular Psychiatry that comprehensively reassesses brain activation and connectivity in bipolar disorder to identify replicable differences that converge across and within resting-state, cognitive, and emotional neuroimaging experiments.

“The neuroimaging literature on bipolar disorder is fast-growing, so meta-analysis is an increasingly useful and valuable tool to further validate and evolve our working neural models of bipolar disorder. Our study evaluated nearly thirty years of functional neuroimaging work in bipolar disorder, so that gave us a substantial and well-powered dataset to test our questions,” said Maya Schumer, the paper’s corresponding author.

The team analyzed 205 published studies, yielding 506 individual neuroimaging experiments. Four parallel, independent meta-analyses were calculated using the revised activation likelihood estimation algorithm: all experiment types, all resting-state experiments, all cognitive experiments, and all emotional experiments. The team employed two different meta-analytic significance tests to confirm reliability of identified clusters.

Analyses of the data showed that individuals with bipolar disorder showed functional differences in the right posterior cingulate cortex during resting-state experiments, the left amygdala during emotional experiments—including those using a mixed (positive/negative) valence manipulation—and the left superior and right inferior parietal lobules during cognitive experiments, while hyperactivating the left medial orbitofrontal cortex during cognitive experiments. Across all experiments, there was convergence in the right caudate extending to the ventral striatum, surviving only one significance test.

“Bipolar Disorder is one of the mental health disorders with the highest suicide rate.  In our meta-analysis,  we identified robust Bipolar Disorder brain markers to enable the development of novel, targeted treatments to help those suffering from this extremely debilitating illness,” said Dr. Phillips, senior author.

Prefrontal, parietal, and limbic condition-dependent differences in bipolar disorder: A large-scale meta-analysis of functional neuroimaging studies
Schumer MC, Chase HW, Rozovsky R, Eickhoff SB, Phillips ML.
Molecular Psychiatry (2023). https://doi.org/10.1038/s41380-023-01974-8