Dataset Information

Aberrant functional connectivity of default-mode network in type 2 diabetes patients.

ABSTRACT:

Objectives

Type 2 diabetes mellitus is associated with increased risk for dementia. Patients with impaired cognition often show default-mode network disruption. We aimed to investigate the integrity of a default-mode network in diabetic patients by using independent component analysis, and to explore the relationship between network abnormalities, neurocognitive performance and diabetic variables.

Methods

Forty-two patients with type 2 diabetes and 42 well-matched healthy controls were included and underwent resting-state functional MRI in a 3 Tesla unit. Independent component analysis was adopted to extract the default-mode network, including its anterior and posterior components. Z-maps of both sub-networks were compared between the two groups and correlated with each clinical variable.

Results

Patients showed increased connectivity around the medial prefrontal cortex in the anterior sub-network, but decreased connectivity around the posterior cingulate cortex in the posterior sub-network. The decreased connectivity in the posterior part was significantly correlated with the score on Complex Figure Test-delay recall test (r?=?0.359, p?=?0.020), the time spent on Trail-Making Test-part B (r?=?-0.346, p?=?0.025) and the insulin resistance level (r?=?-0.404, p?=?0.024).

Conclusion

Dissociation pattern in the default-mode network was found in diabetic patients, which might provide powerful new insights into the neural mechanisms that underlie the diabetes-related cognitive decline.

Key points

• Type 2 diabetes mellitus is associated with impaired cognition • Default- mode network plays a central role in maintaining normal cognition • Network connectivity within the default mode was disrupted in type 2 diabetes patients • Decreased network connectivity was correlated with cognitive performance and insulin resistance level • Disrupted default-mode network might explain the impaired cognition in diabetic population.

SUBMITTER: Cui Y

PROVIDER: S-EPMC4595523 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Publications

Aberrant functional connectivity of default-mode network in type 2 diabetes patients.

Cui Ying Y Jiao Yun Y Chen Hua-Jun HJ Ding Jie J Luo Bing B Peng Cheng-Yu CY Ju Sheng-Hong SH Teng Gao-Jun GJ

European radiology 20150423 11

<h4>Objectives</h4>Type 2 diabetes mellitus is associated with increased risk for dementia. Patients with impaired cognition often show default-mode network disruption. We aimed to investigate the integrity of a default-mode network in diabetic patients by using independent component analysis, and to explore the relationship between network abnormalities, neurocognitive performance and diabetic variables.<h4>Methods</h4>Forty-two patients with type 2 diabetes and 42 well-matched healthy controls ...[more]

PMID: 25903712

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Project description:Background: Schizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network (DMN) of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well-characterized. Method: Resting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects. Results: We found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity. Conclusions: To our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

Project description:Functional magnetic resonance imaging research suggests that major depressive disorder (MDD) in both adults and adolescents is marked by aberrant connectivity of the default mode network (DMN) during resting state. However, emotional dysregulation is also a key feature of MDD. No studies to date have examined emotion-related DMN pathology in adolescent depression. Comprehensively understanding the dynamics of DMN connectivity across brain states in individuals with depression with short disease histories could provide insight into the etiology of MDD.We collected functional magnetic resonance imaging data during an emotion identification task and during resting state from 26 medication-free adolescents (13-17 years old) with MDD and 37 well-matched healthy control subjects. We examined between-group differences in blood oxygenation level-dependent task responses and emotion-dependent and resting-state functional connectivity of the two primary nodes of the DMN: medial prefrontal cortex and posterior cingulate cortex (PCC). Additionally, we examined between-group differences in DMN functional connectivity and its relationship to depression severity and onset.Relative to healthy control subjects, unmedicated adolescents with MDD demonstrated reduced medial prefrontal cortex and PCC emotion-related deactivation and greater medial prefrontal cortex and PCC emotion-dependent functional connectivity with precuneus, cingulate gyrus, and striatum/subcallosal cingulate gyrus. The PCC-subcallosal cingulate connectivity remained inflexibly elevated in the subjects with MDD versus healthy control subjects during resting state. Stronger PCC emotion-dependent functional connectivity was associated with greater depression severity and an earlier age of depression onset.Adolescent depression is associated with inflexibly elevated DMN connections. Given more recent evidence of DMN maturation throughout adolescence, our findings suggest that early-onset depression adversely affects normal development of functional brain networks.

Dataset Information

Aberrant functional connectivity of default-mode network in type 2 diabetes patients.

Objectives

Methods

Results

Conclusion

Key points

Publications

Aberrant functional connectivity of default-mode network in type 2 diabetes patients.

Similar Datasets

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