Common and Specific Characteristics of Adolescent Bipolar Disorder Types I and II: A Combined Cortical Thickness and Structural Covariance Analysis

Kuang, Liangfeng; Gao, Weijia; Long, Zhiliang; Cao, Weifang; Cui, Dong; Guo, Yongxin; Jiao, Qing; Qiu, Jianfeng; Su, Linyan; Lu, Guangming

doi:10.3389/fpsyt.2021.750798

Cited by 3 publications

(2 citation statements)

References 78 publications

(81 reference statements)

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“…Both BD I and BD II had reduced SC connections between superior frontal gyrus (SFG), postcentral gyrus (PCG), superior temporal gyrus (STG), and pars opercularis, while only type I patients had decreased SC connections between STG, inferior parietal gyrus (IPG), pars opercularis ( 20 ). In contrast to SCH, BD patients showed increased clustering coefficients in the left suborbital sulcus and the right superior frontal sulcus ( 21 ).…”

Section: Introductionmentioning

confidence: 99%

Degeneracy and disordered brain networks in psychiatric patients using multivariate structural covariance analyzes

Paunova,

Ramponi,

Kandilarova

et al. 2023

Front. Psychiatry

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IntroductionIn this study, we applied multivariate methods to identify brain regions that have a critical role in shaping the connectivity patterns of networks associated with major psychiatric diagnoses, including schizophrenia (SCH), major depressive disorder (MDD) and bipolar disorder (BD) and healthy controls (HC). We used T1w images from 164 subjects: Schizophrenia (n = 17), bipolar disorder (n = 25), major depressive disorder (n = 68) and a healthy control group (n = 54).MethodsWe extracted regions of interest (ROIs) using a method based on the SHOOT algorithm of the SPM12 toolbox. We then performed multivariate structural covariance between the groups. For the regions identified as significant in t term of their covariance value, we calculated their eigencentrality as a measure of the influence of brain regions within the network. We applied a significance threshold of p = 0.001. Finally, we performed a cluster analysis to determine groups of regions that had similar eigencentrality profiles in different pairwise comparison networks in the observed groups.ResultsAs a result, we obtained 4 clusters with different brain regions that were diagnosis-specific. Cluster 1 showed the strongest discriminative values between SCH and HC and SCH and BD. Cluster 2 had the strongest discriminative value for the MDD patients, cluster 3 – for the BD patients. Cluster 4 seemed to contribute almost equally to the discrimination between the four groups.DiscussionOur results suggest that we can use the multivariate structural covariance method to identify specific regions that have higher predictive value for specific psychiatric diagnoses. In our research, we have identified brain signatures that suggest that degeneracy shapes brain networks in different ways both within and across major psychiatric disorders.

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Section: Introductionmentioning

confidence: 99%

Degeneracy and disordered brain networks in psychiatric patients using multivariate structural covariance analyzes

Paunova,

Ramponi,

Kandilarova

et al. 2023

Front. Psychiatry

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“…Cortical thickness (CT) and surface area (SA) are important components that measure cortical morphometry. CT and SA abnormalities are commonly observed in neurodevelopmental disorders, including bipolar disorder ( 9 ), schizophrenia ( 10 ), autism ( 11 ), and attention-deficit/hyperactivity disorder ( 12 ). Shaw et al used 3D-T1WI's longitudinal study of the correlation between intelligence and cortical thickness in normal children and adolescents and found that in early childhood, there was a significant negative correlation between intelligence and cortical thickness, while with age, they gradually showed a positive correlation ( 13 ).…”

Section: Introductionmentioning

confidence: 99%

A structural MRI study of global developmental delay in infants (<2 years old)

Sun¹,

Xiao

et al. 2022

Front. Neurol.

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ObjectiveTo use structural magnetic resonance imaging (3D-MRI) to evaluate the abnormal development of the cerebral cortex in infants with global developmental delay (GDD).MethodsThe GDD group includes 67 infants aged between 112 and 699 days with global developmental delay and who underwent T1-weighted MRI scans in Shanxi Children's Hospital from December 2019 to March 2022. The healthy control (HC) group includes 135 normal developing infants aged between 88 and 725 days in Shanxi Children's Hospital from September 2020 to August 2021. Whole-brain T1-weighted MRI scans were carried out with a 3.0-T magnetic resonance scanner, which was later processed using InfantSurfer to perform MR image processing and cortical surface reconstruction. Two morphological features of the cortical surface of the 68 brain regions were computed, i.e., the cortical thickness (CT) and cortical surface area (SA), and compared between the GDD and HC groups.ResultsWith regard to the CT, the HC group showed a rapid decrease at first and then a slow increase after birth, and the CT of the GDD group decreased slowly and then became relatively stable. The GDD group showed bilaterally higher hemispherical average CT than those in the HC group. In detail, for the left hemisphere, except in the entorhinal and temporal poles in which the average CT values of the two brain regions were lower than those of the HC group, the CT of the 26 brain regions in the GDD group was higher than those of the HC group (p < 0.05). For the right hemisphere, the CT of the entorhinal in the GDD group was lower than that in the HC group. Otherwise, the CT of the remaining 28 brain regions was higher than those in the HC group (p < 0.05). With regard to the SA, both groups showed a rapid increase after birth till 23 months and remained quite stable afterward. The GDD group shows lower SA bilaterally than that in the HC group. In detail, SA in the GDD group was lower in most cortical regions of both hemispheres than in the HC group (p < 0.05), except for the right temporal pole and entorhinal. When testing for brain asymmetry, we found that the HC group showed obvious asymmetry of CT and SA, while only a few cortical regions in the GDD group showed asymmetry.

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Correlations between multimodal neuroimaging and peripheral inflammation in different subtypes and mood states of bipolar disorder: a systematic review

Long,

Li,

Ding

et al. 2024

Int J Bipolar Disord

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Background Systemic inflammation-immune dysregulation and brain abnormalities are believed to contribute to the pathogenesis of bipolar disorder (BD). However, the connections between peripheral inflammation and the brain, especially the interactions between different BD subtypes and episodes, remain to be elucidated. Therefore, we conducted the present study to provide a comprehensive understanding of the complex association between peripheral inflammation and neuroimaging findings in patients with bipolar spectrum disorders. Methods This systematic review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (CRD42023447044) and conducted according to the Population, Intervention, Comparison, Outcomes, and Study Design (PICOS) framework. Online literature databases (PubMed, Web of Science, Scopus, EMBASE, MEDLINE, PsycINFO, and the Cochrane Library) were searched for studies that simultaneously investigated both peripheral inflammation-related factors and magnetic resonance neurography of BD patients up to July 01, 2023. Then, we analysed the correlations between peripheral inflammation and neuroimaging, as well as the variation trends and the shared and specific patterns of these correlations according to different clinical dimensions. Results In total, 34 publications ultimately met the inclusion criteria for this systematic review, with 2993 subjects included. Among all patterns of interaction between peripheral inflammation and neuroimaging, the most common pattern was a positive relationship between elevated inflammation levels and decreased neuroimaging measurements. The brain regions most susceptible to inflammatory activation were the anterior cingulate cortex, amygdala, prefrontal cortex, striatum, hippocampus, orbitofrontal cortex, parahippocampal gyrus, postcentral gyrus, and posterior cingulate cortex. Limitations The small sample size, insufficiently explicit categorization of BD subtypes and episodes, and heterogeneity of the research methods limited further implementation of quantitative data synthesis. Conclusions Disturbed interactions between peripheral inflammation and the brain play a critical role in BD, and these interactions exhibit certain commonalities and differences across various clinical dimensions of BD. Our study further confirmed that the fronto-limbic-striatal system may be the central neural substrate in BD patients.

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Common and Specific Characteristics of Adolescent Bipolar Disorder Types I and II: A Combined Cortical Thickness and Structural Covariance Analysis

Cited by 3 publications

References 78 publications

Degeneracy and disordered brain networks in psychiatric patients using multivariate structural covariance analyzes

Degeneracy and disordered brain networks in psychiatric patients using multivariate structural covariance analyzes

A structural MRI study of global developmental delay in infants (<2 years old)

Correlations between multimodal neuroimaging and peripheral inflammation in different subtypes and mood states of bipolar disorder: a systematic review

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