Individuals at increased risk for development of bipolar disorder display structural alterations similar to people with manifest disease

Abstract

In psychiatry, there has been a growing focus on identifying at-risk populations. For schizophrenia, these efforts have led to the development of early recognition and intervention measures. Despite a similar disease burden, the populations at risk of bipolar disorder have not been sufficiently characterized. Within the BipoLife consortium, we used magnetic resonance imaging (MRI) data from a multicenter study to assess structural gray matter alterations in N = 263 help-seeking individuals from seven study sites. We defined the risk using the EPIbipolar assessment tool as no-risk, low-risk, and high-risk and used a region-of-interest approach (ROI) based on the results of two large-scale multicenter studies of bipolar disorder by the ENIGMA working group. We detected significant differences in the thickness of the left pars opercularis (Cohen’s d = 0.47, p = 0.024) between groups. The cortex was significantly thinner in high-risk individuals compared to those in the no-risk group (p = 0.011). We detected no differences in the hippocampal volume. Exploratory analyses revealed no significant differences in other cortical or subcortical regions. The thinner cortex in help-seeking individuals at risk of bipolar disorder is in line with previous findings in patients with the established disorder and corresponds to the region of the highest effect size in the ENIGMA study of cortical alterations. Structural alterations in prefrontal cortex might be a trait marker of bipolar risk. This is the largest structural MRI study of help-seeking individuals at increased risk of bipolar disorder.

Prediction of estimated risk for bipolar disorder using machine learning and structural MRI features

“…20.3% of the participants screened positive on one of these syndromes. Surprisingly, SVM could not detect participants at risk estimated using EPIbipolar, although we detected signi cant differences in cortical thickness between the high-risk and no-risk individuals in our previous study [43]. Given similar sample size (previous study N = 263), we pooled the individuals in the high-risk and low-risk groups in order to allow for a binary classi cation.…”

“…However, after removing the low risk group, we obtained a balanced accuracy of 60.9 / 55.5% (10-fold / leave-one-site-out). This suggests, that whereas in a hypothesis driven region-of-interest analysis EPIbipolar selected participants displaying signi cantly thinner cortex in the left pars opercularis [43], BPSS-P selected participants displaying widespread structural alterations enabling for more accurate, single subject classi cation using machine learning. Interestingly, in our above mentioned previous study [43], the pars opercularis was not signi cantly thinner in participants scoring positive in BPSS-P, however, the low p-value might have suggested a non-signi cant trend.…”

“…This suggests, that whereas in a hypothesis driven region-of-interest analysis EPIbipolar selected participants displaying signi cantly thinner cortex in the left pars opercularis [43], BPSS-P selected participants displaying widespread structural alterations enabling for more accurate, single subject classi cation using machine learning. Interestingly, in our above mentioned previous study [43], the pars opercularis was not signi cantly thinner in participants scoring positive in BPSS-P, however, the low p-value might have suggested a non-signi cant trend. Additionally, among the participants scoring positive on any risk criterion in both EPIbipolar and BARS, those with depression were more represented comparing to BPSS-P. As a result, more participants with unipolar depression might have been selected by EPIbipolar and BARS, which might have impeded the classi cation.…”

Machine Learning Prediction of Estimated Risk for Bipolar Disorders Using Hippocampal Subfield and Amygdala Nuclei Volumes

“…Finally, subjects are categorized into four different risk groups: No risk at present, risk status (at least one secondary symptom accompanied by specific changes in sleep and circadian rhythm), high risk status (one primary and at least one secondary symptom, and ultra-high risk (more than one primary symptom). In later analyses, the high risk and ultra-high-risk groups were fused, since the high-risk group contained a disproportionally low number of subjects (3.2%) [36]. Therefore, we used the EPIbipolar version with three risk categories: no risk, low-risk and high-risk across this manuscript.…”

The inferior frontal gyrus and familial risk for bipolar disorder

“…For the left IFG, although volume increase is not consistently observed, reduced cortical thickness has been widely reported. A multicenter study found thinner pars opercularis of the left IFG in high-risk participants compared to low-risk participants (Mikolas et al ., 2021 ). Roberts et al .…”