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- Nunes, A, et al.
(författare)
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Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group
- 2020
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Ingår i: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 25:9, s. 2130-2143
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Tidskriftsartikel (refereegranskat)abstract
- Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.
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- Aas, M, et al.
(författare)
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Telomere length is associated with childhood trauma in patients with severe mental disorders
- 2019
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Ingår i: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 9:1, s. 97-
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Tidskriftsartikel (refereegranskat)abstract
- Reduced telomere length (TL) and structural brain abnormalities have been reported in patients with schizophrenia (SZ) and bipolar disorder (BD). Childhood traumatic events are more frequent in SZ and BD than in healthy individuals (HC), and based on recent findings in healthy individuals could represent one important factor for TL and brain aberrations in patients. The study comprised 1024 individuals (SZ [n = 373]; BD [n = 249] and HC [n = 402]). TL was measured by quantitative polymerase chain reaction (qPCR), and childhood trauma was assessed using the Childhood Trauma Questionnaire (CTQ). Diagnosis was obtained by the Structured Clinical Interview (SCID) for the diagnostic and statistical manual of mental disorders-IV (DSM-IV). FreeSurfer was used to obtain regional and global brain volumes from T1-weighted magnetic resonance imaging (MRI) brain scans. All analyses were adjusted for current age and sex. Patients had on average shorter TL (F = 7.87, p = 0.005, Cohen’s d = 0.17) and reported more childhood trauma experiences than HC (χ2 = 148.9, p < 0.001). Patients with a history of childhood sexual, physical or emotional abuse had shorter TL relative to HC and to patients without a history of childhood abuse (F = 6.93, p = 0.006, Cohen’s d = 0.16). After adjusting for childhood abuse, no difference in TL was observed between patients and HC (p = 0.12). There was no statistically significant difference in reported childhood abuse exposure or TL between SZ and BD. Our analyses revealed no significant associations between TL and clinical characteristics or brain morphometry. We demonstrate shorter TL in SZ and BD compared with HC and showed that TL is sensitive to childhood trauma experiences. Further studies are needed to identify the biological mechanisms of this relationship.
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