A comparison study of metabolic profiles, immunity, and brain gray matter volumes between patients with bipolar disorder and depressive disorder

Bai, Ya Mei; Chen, Mu Hong; Hsu, Ju Wei; Huang, Kou‐Yuan; Tu, Pei Chi; Chang, Wan Chen; Su, Tung Ping; Li, Cheng Ta; Lin, Wei Chen; Tsai, Shih‐Jen

doi:10.1186/s12974-020-1724-9

Cited by 60 publications

(41 citation statements)

References 69 publications

(79 reference statements)

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“…The fusiform gyrus and the lingual gyrus, as the same as the inferior temporal lobe, are also involved in visual processing. Gray matter volume reductions in these two regions have been reported in both this present research and previous studies [13,[82][83][84][85]. And the precuneus is a part of the parietal lobe, which involves a variety of complex functions, including recollection and memory, integration of information relating to the perception of the environment, episodic memory retrieval, and affective responses pain.…”

Section: Discussionsupporting

confidence: 83%

Identification of bipolar disorder using a combination of multimodality magnetic resonance imaging and machine learning techniques

Cui

Cao

et al. 2020

BMC Psychiatry

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Background Bipolar disorder (BPD) is a common mood disorder that is often goes misdiagnosed or undiagnosed. Recently, machine learning techniques have been combined with neuroimaging methods to aid in the diagnosis of BPD. However, most studies have focused on the construction of classifiers based on single-modality MRI. Hence, in this study, we aimed to construct a support vector machine (SVM) model using a combination of structural and functional MRI, which could be used to accurately identify patients with BPD. Methods In total, 44 patients with BPD and 36 healthy controls were enrolled in the study. Clinical evaluation and MRI scans were performed for each subject. Next, image pre-processing, VBM and ReHo analyses were performed. The ReHo values of each subject in the clusters showing significant differences were extracted. Further, LASSO approach was recruited to screen features. Based on selected features, the SVM model was established, and discriminant analysis was performed. Results After using the two-sample t-test with multiple comparisons, a total of 8 clusters were extracted from the data (VBM = 6; ReHo = 2). Next, we used both VBM and ReHo data to construct the new SVM classifier, which could effectively identify patients with BPD at an accuracy of 87.5% (95%CI: 72.5–95.3%), sensitivity of 86.4% (95%CI: 64.0–96.4%), and specificity of 88.9% (95%CI: 63.9–98.0%) in the test data (p = 0.0022). Conclusions A combination of structural and functional MRI can be of added value in the construction of SVM classifiers to aid in the accurate identification of BPD in the clinic.

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Section: Discussionsupporting

confidence: 83%

Identification of bipolar disorder using a combination of multimodality magnetic resonance imaging and machine learning techniques

Cui

Cao

et al. 2020

BMC Psychiatry

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“…Recent structural MRI studies showed that IL-8 was associated with reduced gray matter volumes (GMV) in the left OFC in schizophrenia [91] and bilateral hippocampus in old rhesus macaques [89], which implicated in ammation might contribute to structural abnormalities. Another structural MRI study showed that GMV in the precentral gyrus negatively correlated with pro-in ammatory cytokine levels in BD patients [92], further supporting the idea that in ammation might contribute to structural abnormalities in the right precentral gyrus. A diffusion tensor imaging study found that higher levels of IL-8 were associated with lower fractional anisotropy values across the brain including the corticospinal tract [93], which suggested in ammation might contribute to white matter abnormalities and possibly impair the neural function of the precentral gyrus, for the reason that outputs of voluntary movements are controlled by the precentral gyrus through the corticospinal tract [94].…”

Section: Correlation Between Fc In the Right Precentral Gyrus And Il-mentioning

confidence: 80%

“…Recently, studies found that in ammation could affect cortical reward and motor circuits and was related to such symptoms (anhedonia and motor slowing) in psychiatric diseases such as BD [19,44,45]. Also, a recent neuroimaging study found abnormalities of brain regions in SMN correlated with in ammation in BD patients [46].…”

Section: Introductionmentioning

confidence: 99%

Inflammation is Correlated with Abnormal Functional Connectivity in Unmedicated Bipolar Depression: A Resting State FMRI Study

Tang¹,

Chen²,

Chen³

et al. 2020

Preprint

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Objectives Inflammation might play a role in bipolar disorder (BD), but it remains unclear the relationship between inflammation and brain structural and functional abnormalities in patients with BD. In this study, we focused on the alterations of functional connectivity (FC), peripheral pro-inflammatory cytokines and their correlations to investigate the role of inflammation in FC in BD depression.Methods In this study, 42 unmedicated patients with BD II depression and 62 healthy controls (HCs) were enrolled. Resting-state-functional magnetic resonance imaging (rs-fMRI) was performed in all participants and independent component analysis (ICA) was used. Serum levels of Interleukin-6 (IL-6) and Interleukin-8 (IL-8) were measured in all participants. Correlation between FC values and IL-6 and IL-8 levels in BD was calculated.Results Compared with the HCs, BD II patients showed decreased FC in the left orbitofrontal cortex (OFC) implicating the limbic network and the right precentral gyrus implicating the somatomotor network (SMN). BD II showed increased IL-6 (P = 0.039), IL-8 (P = 0.002) levels. Moreover, abnormal FC in the right precentral gyrus were inversely correlated with the IL-8 (r=-0.458, P = 0.004) levels in BD II. No significant correlation was found between FC in the left OFC and cytokines levels.Conclusions Our findings that serum IL-8 levels is associated with impaired FC in the right precentral gyrus in BD II patients suggest that inflammation might play a crucial role in brain functional abnormalities in BD.

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“…Patients with BD show high levels of soluble IL-6 receptors and TNF receptors in serum samples [ 207 ], and the levels of proinflammatory cytokines have been correlated to the reduction of gray matter volume [ 207 ]. Maternal inflammation during the third trimester of pregnancy increased the plasma concentration of IL-6, TNF-α, and CCL2, and the rate of the attention-deficit hyperactivity disorder of the birthed children [ 208 ]. Thus, many current studies suggest the risk of aberrant immunity on the emergence of psychosis symptoms.…”

Section: Main Textmentioning

confidence: 99%

A Destruction Model of the Vascular and Lymphatic Systems in the Emergence of Psychiatric Symptoms

Segawa

Blumenthal

Yamawaki

et al. 2021

Biology

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The lymphatic system is important for antigen presentation and immune surveillance. The lymphatic system in the brain was originally introduced by Giovanni Mascagni in 1787, while the rediscovery of it by Jonathan Kipnis and Kari Kustaa Alitalo now opens the door for a new interpretation of neurological diseases and therapeutic applications. The glymphatic system for the exchanges of cerebrospinal fluid (CSF) and interstitial fluid (ISF) is associated with the blood-brain barrier (BBB), which is involved in the maintenance of immune privilege and homeostasis in the brain. Recent notions from studies of postmortem brains and clinical studies of neurodegenerative diseases, infection, and cerebral hemorrhage, implied that the breakdown of those barrier systems and infiltration of activated immune cells disrupt the function of both neurons and glia in the parenchyma (e.g., modulation of neurophysiological properties and maturation of myelination), which causes the abnormality in the functional connectivity of the entire brain network. Due to the vulnerability, such dysfunction may occur in developing brains as well as in senile or neurodegenerative diseases and may raise the risk of emergence of psychosis symptoms. Here, we introduce this hypothesis with a series of studies and cellular mechanisms.

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A comparison study of metabolic profiles, immunity, and brain gray matter volumes between patients with bipolar disorder and depressive disorder

Cited by 60 publications

References 69 publications

Identification of bipolar disorder using a combination of multimodality magnetic resonance imaging and machine learning techniques

Identification of bipolar disorder using a combination of multimodality magnetic resonance imaging and machine learning techniques

Inflammation is Correlated with Abnormal Functional Connectivity in Unmedicated Bipolar Depression: A Resting State FMRI Study

A Destruction Model of the Vascular and Lymphatic Systems in the Emergence of Psychiatric Symptoms

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