Changes in default mode network connectivity in different glucose metabolism status and diabetes duration

Diabetes-related clinical and microstructural white matter changes in patients with Alzheimer's disease

AIM

Although there exists substantial epidemiological evidence indicating an elevated risk of dementia in individuals with diabetes, our understanding of the neuropathological underpinnings of the association between Type-2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) remains unclear. This study aims to unveil the microstructural brain changes associated with T2DM in AD and identify the clinical variables contributing to these changes.

METHODS

In this retrospective study involving 64 patients with AD, 31 individuals had concurrent T2DM. The study involved a comparative analysis of diffusion tensor imaging (DTI) images and clinical features between patients with and without T2DM. The FSL FMRIB software library was used for comprehensive preprocessing and tractography analysis of DTI data. After eddy current correction, the "bedpost" model was utilized to model diffusion parameters. Linear regression analysis with a stepwise method was used to predict the clinical variables that could lead to microstructural white matter changes.

RESULTS

We observed a significant impairment in the left superior longitudinal fasciculus (SLF) among patients with AD who also had T2DM. This impairment in patients with AD and T2DM was associated with an elevation in creatine levels.

CONCLUSION

The white matter microstructure in the left SLF appears to be sensitive to the impairment of kidney function associated with T2DM in patients with AD. The emergence of AD in association with T2DM may be driven by mechanisms distinct from the typical AD pathology. Compromised renal function in AD could potentially contribute to impaired white matter integrity.

Aberrant Brain Triple-Network Effective Connectivity Patterns in Type 2 Diabetes Mellitus

INTRODUCTION

Aberrant brain functional connectivity network is thought to be related to cognitive impairment in patients with type 2 diabetes mellitus (T2DM). This study aims to investigate the triple-network effective connectivity patterns in patients with T2DM within and between the default mode network (DMN), salience network (SN), and executive control network (ECN) and their associations with cognitive declines.

METHODS

In total, 92 patients with T2DM and 98 matched healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Spectral dynamic causal modeling (spDCM) was used for effective connectivity analysis within the triple network. The posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), lateral prefrontal cortex (LPFC), supramarginal gyrus (SMG), and anterior insula (AINS) were selected as the regions of interest. Group comparisons were performed for effective connectivity calculated using the fully connected model, and the relationships between effective connectivity alterations and cognitive impairment as well as clinical parameters were detected.

RESULTS

Compared to HCs, patients with T2DM exhibited increased or decreased effective connectivity patterns within the triple network. Furthermore, diabetes duration was significantly negatively correlated with increased effective connectivity from the r-LPFC to the mPFC, while body mass index (BMI) was significantly positively correlated with increased effective connectivity from the l-LPFC to the l-AINS (r = - 0.353, p = 0.001; r = 0.377, p = 0.004).

CONCLUSION

These results indicate abnormal effective connectivity patterns within the triple network model in patients with T2DM and provide new insight into the neurological mechanisms of T2DM and related cognitive dysfunction.

Altered dynamic effective connectivity of the default mode network in type 2 diabetes

Introduction

Altered functional connectivity of resting-state functional magnetic resonance imaging (rs-fMRI) within default mode network (DMN) regions has been verified to be closely associated with cognitive decline in patients with Type 2 diabetes mellitus (T2DM), but most studies neglected the fluctuations of brain activities-the dynamic effective connectivity (DEC) within DMN of T2DM is still unknown.

Methods

For the current investigation, 40 healthy controls (HC) and 36 T2DM patients have been recruited as participants. To examine the variation of DEC between T2DM and HC, we utilized the methodologies of independent components analysis (ICA) and multivariate granger causality analysis (mGCA).

Results

We found altered DEC within DMN only show decrease in state 1. In addition, the causal information flow of diabetic patients major affected areas which are closely associated with food craving and metabolic regulation, and T2DM patients stayed longer in low activity level and exhibited decreased transition rate between states. Moreover, these changes related negatively with the MoCA scores and positively with HbA1C level.

Conclusion

Our study may offer a fresh perspective on brain dynamic activities to understand the mechanisms underlying T2DM-related cognitive deficits.

Alterations of spontaneous brain activity in type 2 diabetes mellitus without mild cognitive impairment: a resting-state functional magnetic resonance study

Background

Type 2 diabetes mellitus (T2DM) has been demonstrated an increased risk factor of cognitive impairment or even dementia. Kinds of resting-state functional magnetic resonance imaging indices have been proposed and used to investigate the brain mechanism underlying diabetic cognitive impairment. This study aimed to explore the early changes in spontaneous neural activity among T2DM patients without cognitive impairment by means of multiple rs-fMRI indices.

Methods

T2DM patients without cognitive impairment and age-, sex-, and education matched control subjects were included in this study. Three rs-fMRI indices, namely amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and voxel-mirrored homotopic connectivity (VMHC) were computed after image pre-processing. The Montreal Cognitive Assessment (MoCA) was performed to distinguish normal cognition. Brain volume was also evaluated. Correlation analyses were conducted to explore any relationship among rs-fMRI indices and clinical characteristics.

Results

The T2DM patients were detected significantly decreased neural activity in right angular and left prefrontal gyrus including middle and superior frontal gyrus. Increased activities were also observed in left caudate and the supplementary motor area. No correlation between rs-fMRI indices and clinical characteristics was survived after multiple comparison correction. But we observed a significant, but decreased correlation between ALFF and ReHo values in the reported brain areas.

Conclusion

The combination of ALFF, ReHo and VMHC analyses demonstrated abnormal spontaneous neural activity in brain regions which were reported in T2DM patients without cognitive impairment. These results may enhance our understanding of the diabetic brain changes at the early stage.

The hemodynamic response function as a type 2 diabetes biomarker: a data-driven approach

Introduction

There is a need to better understand the neurophysiological changes associated with early brain dysfunction in Type 2 diabetes mellitus (T2DM) before vascular or structural lesions. Our aim was to use a novel unbiased data-driven approach to detect and characterize hemodynamic response function (HRF) alterations in T2DM patients, focusing on their potential as biomarkers.

Methods

We meshed task-based event-related (visual speed discrimination) functional magnetic resonance imaging with DL to show, from an unbiased perspective, that T2DM patients' blood-oxygen-level dependent response is altered. Relevance analysis determined which brain regions were more important for discrimination. We combined explainability with deconvolution generalized linear model to provide a more accurate picture of the nature of the neural changes.

Results

The proposed approach to discriminate T2DM patients achieved up to 95% accuracy. Higher performance was achieved at higher stimulus (speed) contrast, showing a direct relationship with stimulus properties, and in the hemispherically dominant left visual hemifield, demonstrating biological interpretability. Differences are explained by physiological asymmetries in cortical spatial processing (right hemisphere dominance) and larger neural signal-to-noise ratios related to stimulus contrast. Relevance analysis revealed the most important regions for discrimination, such as extrastriate visual cortex, parietal cortex, and insula. These are disease/task related, providing additional evidence for pathophysiological significance. Our data-driven design allowed us to compute the unbiased HRF without assumptions.

Conclusion

We can accurately differentiate T2DM patients using a data-driven classification of the HRF. HRF differences hold promise as biomarkers and could contribute to a deeper understanding of neurophysiological changes associated with T2DM.

Reduced gray matter volume in the default-mode network associated with insulin resistance

Insulin resistance may lead to structural and functional abnormalities of the human brain. However, the mechanism by which insulin resistance impairs the brain remains elusive. In this study, we used two large neuroimaging databases to investigate the brain regions where insulin resistance was associated with the gray matter volume and to examine the resting-state functional connectivity between these brain regions and each hypothalamic nucleus. Insulin resistance was associated with reduced gray matter volume in the regions of the default-mode and limbic networks in the cerebral cortex in older adults. Resting-state functional connectivity was prominent between these networks and the paraventricular nucleus of the hypothalamus, a hypothalamic interface connecting functionally with the cerebral cortex. Furthermore, we found a significant correlation in these networks between insulin resistance-related gray matter volume reduction and network paraventricular nucleus of the hypothalamus resting-state functional connectivity. These results suggest that insulin resistance-related gray matter volume reduction in the default-mode and limbic networks emerged through metabolic homeostasis mechanisms in the hypothalamus.

The Interaction of Glycemia with Anxiety and Depression Is Related to Altered Cerebellar and Cerebral Functional Correlations

Depression, type 2 diabetes (T2D), and obesity are comorbid, and prevention and treatment of all three diseases are needed. We hypothesized an inverse relationship between the connectivity of the cingulo-opercular task control network with the somatosensory mouth network and the interaction between HbA1c and depression. Three-hundred and twenty-five participants (BMI: 26.11 ± 0.29; Achenbach adult self-report (ASR) DSM depressive problems T-score (depression): 54.60 ± 6.77; Age: 28.26 ± 3.90 y; adult self-report anxiety and depression scale (anxiety and depression): 54.69 ± 7.27; HbA1c: 5.26 ± 0.29; 68% white) were sampled from the Human Connectome Project 1200 subjects PTN release. Inclusion criteria were: four (15 min) resting state fMRI scans; BMI; hemoglobin A1c (HbA1c); and complete adult self-report data. The following models were run to assess the connectivity between 15 independent fMRI components: the interaction of depression with HbA1c; anxiety and depression with HbA1c; depression with BMI; and anxiety and depression with BMI. All models were corrected for a reported number of depressive symptoms, head motion in the scanner, age, and race. Functional connectivity was modeled in FSLNets. Corrected significance was set at pFWE < 0.05. The interaction HbA1c and anxiety and depression was positively related to the connectivity of the cerebellum with the visual network (t = 3.76, pFWE = 0.008), frontoparietal network (t = 3.45, pFWE = 0.02), and somatosensory mouth network (t = 4.29, pFWE = 0.0004). Although our hypotheses were not supported, similar increases in cerebellar connectivity are seen in patients with T2D and overall suggest that the increased cerebellar connectivity may be compensatory for an increasingly poor glycemic control.

Early life factors and hippocampal functional connectivity in children with overweight/obesity

OBJECTIVE

We investigated the association of anthropometric neonatal data (birth length and birth weight) and breastfeeding practices (exclusive and any breastfeeding) with hippocampal functional connectivity and its academic implication in children with overweight/obesity.

METHODS

Ninety six children with overweight/obesity aged 8-11 years (10.01 ± 1.14), from the ActiveBrains project were included in this cross-sectional study. Anthropometric neonatal data were collected from birth records, whereas breastfeeding practices were reported by parents. A 3.0 Tesla Siemens Magnetom Tim Trio system was used to acquire T1-weighted and resting-state functional magnetic resonance images. Academic performance was assessed by the Woodcock-Muñoz standardized test. Hippocampal seed-based methods with post-hoc regression analyses were performed. Analyses were considered significant when surpassing Family-Wise Error corrections.

RESULTS

Birth weight showed a positive association with the connectivity between the hippocampus and the pre- and postcentral gyri, and the cerebellum. In addition, breastfeeding was negatively associated with the connectivity between the hippocampus and the primary motor cortex and the angular gyrus. Any breastfeeding, in turn, showed a positive association with the connectivity between the hippocampus and the middle temporal gyrus. None of the connectivity outcomes related to early life factors was coupled with better academic abilities (all p > 0.05).

CONCLUSIONS

Our findings suggest that birth weight at birth and breastfeeding are associated with hippocampal connectivity in children with overweight/obesity. Despite this, how the results relate to academic performance remains a matter of speculation. Our findings suggest that clinicians should recognize the importance early life factors for potentially avoiding consequences on offspring's brain development.

Changes in hemodynamic response function components reveal specific changes in neurovascular coupling in type 2 diabetes

Type 2 Diabetes Mellitus (T2DM) is a metabolic disease that leads to multiple vascular complications with concomitant changes in human neurophysiology, which may lead to long-term cognitive impairment, and dementia. Early impairments of neurovascular coupling can be studied using event-related functional magnetic resonance imaging (fMRI) designs. Here, we aimed to characterize the changes in the hemodynamic response function (HRF) in T2DM to probe components from the initial dip to late undershoot. We investigated whether the HRF morphology is altered throughout the brain in T2DM, by extracting several parameters of the fMRI response profiles in 141 participants (64 patients with T2DM and 77 healthy controls) performing a visual motion discrimination task. Overall, the patients revealed significantly different HRFs, which extended to all brain regions, suggesting that this is a general phenomenon. The HRF in T2DM was found to be more sluggish, with a higher peak latency and lower peak amplitude, relative slope to peak, and area under the curve. It also showed a pronounced initial dip, suggesting that the initial avidity for oxygen is not compensated for, and an absent or less prominent but longer undershoot. Most HRF parameters showed a higher dispersion and variability in T2DM. In sum, we provide a definite demonstration of an impaired hemodynamic response function in the early stages of T2DM, following a previous suggestion of impaired neurovascular coupling. The quantitative demonstration of a significantly altered HRF morphology in separate response phases suggests an alteration of distinct physiological mechanisms related to neurovascular coupling, which should be considered in the future to potentially halt the deterioration of the brain function in T2DM.

Evaluation of altered brain activity in type 2 diabetes using various indices of brain function: A resting-state functional magnetic resonance imaging study

Background

Type 2 diabetes mellitus (T2DM) has been identified as a risk factor that increases the rate of cognitive decline. Previous studies showed that patients with T2DM had brain function alterations based on a single index of resting-state functional magnetic resonance imaging (rs-fMRI). The present study aimed to explore spontaneous brain activity in patients with T2DM by comparing various rs-fMRI indices, and to determine the relationship between these changes and cognitive dysfunction.

Methods

A total of 52 patients with T2DM and age- and sex-matched control participants were included in this study. The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel-mirrored homotopic connectivity (VMHC) values were calculated to represent the status of spontaneous neural activity. The Montreal Cognitive Assessment (MoCA) was used for the rapid evaluation of cognition in all subjects. Pearson correlation and mediation analyses were conducted to investigate the relationship between rs-fMRI indices and clinical parameters such as fasting glucose, disease duration, and MoCA.

Results

Patients with T2DM had alterations of concordant spontaneous brain activity in brain areas including the bilateral cerebellum posterior lobe, the left inferior temporal gyrus (ITG.L), the parahippocampal gyrus, and the left supplementary motor area (SMA.L). The indices were significantly correlated to each other in most of the detected brain areas. Positive correlations were observed between fasting glucose and neural activity in the surrounding areas of the left insula and the inferior frontal gyrus. MoCA scores were negatively correlated with the ReHo values extracted from the left anterior occipital lobe and the superior cerebellar cortex and were positively correlated with VMHC values extracted from the left caudate and the precentral gyrus (PreCG). No significant mediation effect of abnormal brain activity was found in the relationship between clinical parameters and MoCA scores.

Conclusion

The current study demonstrated the functional concordance of abnormal brain activities in patients with T2DM by comparing ALFF, ReHo, and VMHC measurements. Widespread abnormalities mainly involved in motor and sensory processing functions may provide insight into examining T2DM-related neurological pathophysiology.

Alteration in topological organization characteristics of gray matter covariance networks in patients with prediabetes

OBJECTIVES

Prediabetes is associated with an increased risk of cognitive impairment and neurodegenerative diseases. However, the exact mechanism of prediabetes-related brain diseases has not been fully elucidated. The brain structure of patients with prediabetes has been damaged to varying degrees, and these changes may affect the topological characteristics of large-scale brain networks. The structural covariance of connected gray matter has been demonstrated valuable in inferring large-scale structural brain networks. The alterations of gray matter structural covariance networks in prediabetes remain unclear. This study aims to examine the topological features and robustness of gray matter structural covariance networks in prediabetes.

METHODS

A total of 48 subjects were enrolled in this study, including 23 patients with prediabetes (the PD group) and 25 age-and sex-matched healthy controls (the Ctr group). All subjects' high-resolution 3D T1 images of the brain were collected by a 3.0 Tesla MR machine. Mini-mental state examination was used to evaluate the cognitive status of each subject. We calculated the gray matter volume of 116 brain regions with automated anatomical labeling (AAL) template, and constructed gray matter structural covariance networks by thresholding interregional structural correlation matrices as well as graph theoretical analysis. The area under the curve (AUC) in conjunction with permutation testing was employed for testing the differences in network measures, which included small world parameter (Sigma), normalized clustering coefficient (Gamma), normalized path length (Lambda), global efficiency, characteristic path length, local efficiency, mean clustering coefficient, and network robustness parameters.

RESULTS

The network in both groups followed small-world characteristics, showing that Sigma was greater than 1, the Lambda was much higher than 1, and Gamma was close to 1. Compared with the Ctr group, the network of the PD group showed increased Sigma, Lambda, and Gamma across a range of network sparsity. The Gamma of the PD group was significantly higher than that in the Ctr group in the network sparsity range of 0.12-0.16, but there was no difference between the 2 groups (all P>0.05). The grey matter network showed an increased characteristic path length and a decreased global efficiency in the PD group, but AUC analysis showed that there was no significant difference between groups (all P>0.05). For the network separation measures, the local efficiency and mean clustering coefficient of the gray matter network in the PD group were significantly increased and AUC analysis also confirmed it (P=0.001 and P=0.004, respectively). In addition, network robustness analysis showed that the grey matter network of the PD group was more vulnerable to random damage (P=0.001).

CONCLUSIONS

The prediabetic gray matter network shows an increased average clustering coefficient and local efficiency, and is more vulnerable to random damage than the healthy control, suggesting that the topological characteristics of the prediabetes grey matter covariant network have changed (network separation enhanced and network robustness reduced), which may provide new insights into the brain damage relevant to the disease.

Aberrant brain functional networks in type 2 diabetes mellitus: A graph theoretical and support-vector machine approach

Objective

Type 2 diabetes mellitus (T2DM) is a high risk of cognitive decline and dementia, but the underlying mechanisms are not yet clearly understood. This study aimed to explore the functional connectivity (FC) and topological properties among whole brain networks and correlations with impaired cognition and distinguish T2DM from healthy controls (HC) to identify potential biomarkers for cognition abnormalities.

Methods

A total of 80 T2DM and 55 well-matched HC were recruited in this study. Subjects’ clinical data, neuropsychological tests and resting-state functional magnetic resonance imaging data were acquired. Whole-brain network FC were mapped, the topological characteristics were analyzed using a graph-theoretic approach, the FC and topological characteristics of the network were compared between T2DM and HC using a general linear model, and correlations between networks and clinical and cognitive characteristics were identified. The support vector machine (SVM) model was used to identify differences between T2DM and HC.

Results

In patients with T2DM, FC was higher in two core regions [precuneus/posterior cingulated cortex (PCC)_1 and later prefrontal cortex_1] in the default mode network and lower in bilateral superior parietal lobes (within dorsal attention network), and decreased between the right medial frontal cortex and left auditory cortex. The FC of the right frontal medial-left auditory cortex was positively correlated with the Montreal Cognitive Assessment scales and negatively correlated with the blood glucose levels. Long-range connectivity between bilateral auditory cortex was missing in the T2DM. The nodal degree centrality and efficiency of PCC were higher in T2DM than in HC (P < 0.005). The nodal degree centrality in the PCC in the SVM model was 97.56% accurate in distinguishing T2DM patients from HC, demonstrating the reliability of the prediction model.

Conclusion

Functional abnormalities in the auditory cortex in T2DM may be related to cognitive impairment, such as memory and attention, and nodal degree centrality in the PCC might serve as a potential neuroimaging biomarker to predict and identify T2DM.

Changes of brain function in patients with type 2 diabetes mellitus measured by different analysis methods: A new coordinate-based meta-analysis of neuroimaging

Objective

Neuroimaging meta-analysis identified abnormal neural activity alterations in patients with type 2 diabetes mellitus (T2DM), but there was no consistency or heterogeneity analysis between different brain imaging processing strategies. The aim of this meta-analysis was to determine consistent changes of regional brain functions in T2DM via the indicators obtained by using different post-processing methods.

Methods

Since the indicators obtained using varied post-processing methods reflect different neurophysiological and pathological characteristics, we further conducted a coordinate-based meta-analysis (CBMA) of the two categories of neuroimaging literature, which were grouped according to similar data processing methods: one group included regional homogeneity (ReHo), independent component analysis (ICA), and degree centrality (DC) studies, while the other group summarized the literature on amplitude of low-frequency fluctuation (ALFF) and cerebral blood flow (CBF).

Results

The final meta-analysis included 23 eligible trials with 27 data sets. Compared with the healthy control group, when neuroimaging studies were combined with ReHo, ICA, and DC measurements, the brain activity of the right Rolandic operculum, right supramarginal gyrus, and right superior temporal gyrus in T2DM patients decreased significantly. When neuroimaging studies were combined with ALFF and CBF measurements, there was no clear evidence of differences in the brain function between T2DM and HCs.

Conclusion

T2DM patients have a series of spontaneous abnormal brain activities, mainly involving brain regions related to learning, memory, and emotion, which provide early biomarkers for clarifying the mechanism of cognitive impairment and neuropsychiatric disorders in diabetes.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=247071, PROSPERO [CRD42021247071].

Impairments in intrinsic functional networks in type 2 diabetes: A meta-analysis of resting-state functional connectivity

Type 2 diabetes mellitus (T2DM) is associated with abnormal communication among large-scale brain networks, revealed by resting-state functional connectivity (rsFC), with inconsistent results between studies. We performed a meta-analysis of seed-based rsFC studies to identify consistent network connectivity alterations. Thirty-three datasets from 30 studies (1014 T2DM patients and 902 healthy controls [HC]) were included. Seed coordinates and between-group effects were extracted, and the seeds were divided into networks based on their location. Compared to HC, T2DM patients showed hyperconnectivity and hypoconnectivity within the DMN, DMN hypoconnectivity with the affective network (AN), ventral attention network (VAN) and frontal parietal network, and DMN hyperconnectivity with the VAN and visual network. T2DM patients also showed AN hypoconnectivity with the somatomotor network and hyperconnectivity with the VAN. T2DM illness durations negatively correlated with within-DMN rsFC. These DMN-centered impairments in large-scale brain networks in T2DM patients may help to explain the cognitive deficits associated with T2DM.

Altered Functional Network Connectivity of Precuneus and Executive Control Networks in Type 2 Diabetes Mellitus Without Cognitive Impairment

In epidemiological studies, type 2 diabetes mellitus (T2DM) has been associated with cognitive impairment and dementia, but studies about functional network connectivity in T2DM without cognitive impairment are limited. This study aimed to explore network connectivity alterations that may help enhance our understanding of damage-associated processes in T2DM. MRI data were analyzed from 82 patients with T2DM and 66 normal controls. Clinical, biochemical, and neuropsychological assessments were conducted in parallel with resting-state functional magnetic resonance imaging, and the cognitive status of the patients was assessed using the Montreal Cognitive Assessment-B (MoCA-B) score. Independent component analysis revealed a positive correlation between the salience network and the visual network and a negative connection between the left executive control network and the default mode network in patients with T2DM. The differences in dynamic brain network connectivity were observed in the precuneus, visual, and executive control networks. Internal network connectivity was primarily affected in the thalamus, inferior parietal lobe, and left precuneus. Hemoglobin A1c level, body mass index, MoCA-B score, and grooved pegboard (R) assessments indicated significant differences between the two groups (p < 0.05). Our findings show that key changes in functional connectivity in diabetes occur in the precuneus and executive control networks that evolve before patients develop cognitive deficits. In addition, the current study provides useful information about the role of the thalamus, inferior parietal lobe, and precuneus, which might be potential biomarkers for predicting the clinical progression, assessing the cognitive function, and further understanding the neuropathology of T2DM.

Large-scale functional connectivity predicts cognitive impairment related to type 2 diabetes mellitus

BACKGROUND

Large-scale functional connectivity (LSFC) patterns in the brain have unique intrinsic characteristics. Abnormal LSFC patterns have been found in patients with dementia, as well as in those with mild cognitive impairment (MCI), and these patterns predicted their cognitive performance. It has been reported that patients with type 2 diabetes mellitus (T2DM) may develop MCI that could progress to dementia. We investigated whether we could adopt LSFC patterns as discriminative features to predict the cognitive function of patients with T2DM, using connectome-based predictive modeling (CPM) and a support vector machine.

AIM

To investigate the utility of LSFC for predicting cognitive impairment related to T2DM more accurately and reliably.

METHODS

Resting-state functional magnetic resonance images were derived from 42 patients with T2DM and 24 healthy controls. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Patients with T2DM were divided into two groups, according to the presence (T2DM-C; n = 16) or absence (T2DM-NC; n = 26) of MCI. Brain regions were marked using Harvard Oxford (HOA-112), automated anatomical labeling (AAL-116), and 264-region functional (Power-264) atlases. LSFC biomarkers for predicting MoCA scores were identified using a new CPM technique. Subsequently, we used a support vector machine based on LSFC patterns for among-group differentiation. The area under the receiver operating characteristic curve determined the appearance of the classification.

RESULTS

CPM could predict the MoCA scores in patients with T2DM (Pearson’s correlation coefficient between predicted and actual MoCA scores, r = 0.32, P=0.0066 [HOA-112 atlas]; r = 0.32, P=0.0078 [AAL-116 atlas]; r = 0.42, P=0.0038 [Power-264 atlas]), indicating that LSFC patterns represent cognition-level measures in these patients. Positive (anti-correlated) LSFC networks based on the Power-264 atlas showed the best predictive performance; moreover, we observed new brain regions of interest associated with T2DM-related cognition. The area under the receiver operating characteristic curve values (T2DM-NC group vs. T2DM-C group) were 0.65-0.70, with LSFC matrices based on HOA-112 and Power-264 atlases having the highest value (0.70). Most discriminative and attractive LSFCs were related to the default mode network, limbic system, and basal ganglia.

CONCLUSION

LSFC provides neuroimaging-based information that may be useful in detecting MCI early and accurately in patients with T2DM.

Type 1 diabetes affects the brain functional connectivity underlying working memory processing

Visuospatial working memory (VSWM) deficits have been demonstrated to occur during the development of type-1-diabetes (T1D). Despite confirming the early appearance of distinct task-related brain activation patterns in T1D patients compared to healthy controls, the effect of VSWM load on functional brain connectivity during task performance is still unknown. Using electroencephalographic methods, the present study evaluated this topic in clinically well-controlled T1D young patients and healthy individuals, while they performed a VSWM task with different memory load levels during two main VSWM processing phases: encoding and maintenance. The results showed a significantly lower number of correct responses and longer reaction times in T1D while performing the task. Besides, higher and progressively increasing functional connectivity indices were found for T1D patients in response to cumulative degrees of VSWM load, from the beginning of the VSWM encoding phase, without notably affecting the VSWM maintenance phase. In contrast, healthy controls managed to solve the task, showing lower functional brain connectivity during the initial VSWM processing steps with more gradual task-related adjustments. Present results suggest that T1D patients anticipate high VSWM load demands by early recruiting supplementary processing resources as the probable expression of a more inefficient, though paradoxically better adjusted to task demands cognitive strategy.

Brain energy failure in dementia syndromes: Opportunities and challenges for glucagon-like peptide-1 receptor agonists

Medications for type 2 diabetes (T2DM) offer a promising path for discovery and development of effective interventions for dementia syndromes. A common feature of dementia syndromes is an energy failure due to reduced energy supply to neurons and is associated with synaptic loss and results in cognitive decline and behavioral changes. Among diabetes medications, glucagon‐like peptide‐1 (GLP‐1) receptor agonists (RAs) promote protective effects on vascular, microglial, and neuronal functions. In this review, we present evidence from animal models, imaging studies, and clinical trials that support developing GLP‐1 RAs for dementia syndromes. The review examines how changes in brain energy metabolism differ in conditions of insulin resistance and T2DM from dementia and underscores the challenges that arise from the heterogeneity of dementia syndromes. The development of GLP‐1 RAs as dementia therapies requires a deeper understanding of the regional changes in brain energy homeostasis guided by novel imaging biomarkers.

Concomitant functional impairment and reorganization in the linkage between the cerebellum and default mode network in patients with type 2 diabetes mellitus

BACKGROUND

Increasing evidence shows that the default mode network (DMN) and cerebellum are prone to structural and functional abnormalities in patients with type 2 diabetes mellitus (T2DM). However, the type of change in the functional connection between the DMN and cerebellum is still unknown.

METHODS

In this study, seed-based functional connectivity (FC) analysis was used to examine the intrinsic FC of the cerebellum-DMN between healthy controls (HCs) and T2DM patients. Pearson correlation analysis was used to explore the relationship between clinical variables and changes in FC.

RESULTS

Compared with HCs, T2DM patients showed significantly increased FC of the left crus I-left medial superior frontal gyrus, left crus I-right medial superior frontal gyrus, and right crus I-left medial orbitofrontal cortex. Compared with HCs, T2DM patients showed decreased FC of the lobule IX-the right angular gyrus. Moreover, diabetes duration was positively correlated with increased FC of the left crus I-right medial superior frontal gyrus (r=0.438, P=0.007).

CONCLUSIONS

Concomitant functional impairment and reorganization in the linkage between the cerebellum and DMN in patients with T2DM may be a biomarker of early brain damage that can help us better understand the pathogenesis of cognitive impairment in T2DM.

Abnormalities of Brain White Matter in Type 2 Diabetes Mellitus: A Meta-Analysis of Diffusion Tensor Imaging

Aims: The study aimed to conduct a meta-analysis to determine the abnormalities of white matter in patients with type 2 diabetes mellitus (T2DM) by identifying the consistency of diffusion tensor imaging (DTI). Method: The literature for DTI comparing patients with T2DM with controls published before October 30, 2020, were reviewed in PubMed, Web of Science, Embase, CNKI, and Wan Fang databases. The meta-analysis was performed using the activation likelihood estimation (ALE) method, including 12 reports and 381 patients with T2DM. Results: The meta-analysis identified 10 white matter regions that showed a consistent reduction of fractional anisotropy (FA) in patients with T2DM, including genu of the corpus callosum, the body of corpus callosum, bilateral anterior corona radiata, bilateral superior corona radiata, bilateral cingulum, and bilateral superior fronto-occipital fasciculus. Conclusion: This study revealed the abnormal characteristics of white matter in T2DM, which would be helpful to understand the underlying neuropathological and physiological mechanisms of T2DM and provide evidence for clinical diagnosis and treatment.

A multimodal meta-analysis of regional structural and functional brain alterations in type 2 diabetes

Neuroimaging studies have identified brain structural and functional alterations of type 2 diabetes mellitus (T2DM) patients; however, there is no systematic information on the relations between abnormalities in these two domains. We conducted a multimodal meta-analysis of voxel-based morphometry and regional resting-state functional MRI studies in T2DM, including fifteen structural datasets (693 patients and 684 controls) and sixteen functional datasets (378 patients and 358 controls). We found, in patients with T2DM compared to controls, conjoint decreased regional gray matter volume (GMV) and altered intrinsic activity mainly in the default mode network including bilateral superior temporal gyrus/Rolandic operculum, left middle and inferior temporal gyrus, and left supramarginal gyrus; decreased GMV alone in the limbic system; and functional abnormalities alone in the cerebellum, insula, and visual cortex. This meta-analysis identified complicated patterns of conjoint and dissociated brain alterations in T2DM patients, which may help provide new insight into the neuropathology of T2DM.

Regional Spontaneous Neural Activity Alterations in Type 2 Diabetes Mellitus: A Meta-Analysis of Resting-State Functional MRI Studies

Objective: Resting-state functional magnetic resonance imaging (rs-fMRI) studies have revealed inconsistent regional spontaneous neural activity alterations in patients with type 2 diabetes mellitus (T2DM). The aim of our meta-analysis was to identify concordant regional spontaneous neural activity abnormalities in patients with T2DM. Methods: A systematic search was conducted to identify voxel-based rs-fMRI studies comparing T2DM patients with healthy controls. The permutation of subject images seed-based d mapping (SDM) was used to quantitatively estimate the regional spontaneous neural activity abnormalities in patients with T2DM. Metaregression was conducted to examine the associations between clinical characteristics and functional alterations. Results: A total of 16 studies with 19 datasets including 434 patients with T2DM and 391 healthy controls were included. Patients with T2DM showed hypoactivity in the right medial superior frontal gyrus, right superior temporal gyrus, and left lingual gyrus, whereas hyperactivity in the right cerebellum. Metaregression analysis identified negative correlation between regional activity in the medial superior frontal and anterior cingulate gyri and illness duration of patients with T2DM. Conclusion: The patterns of regional spontaneous neural activity alterations, characterized by hypoactivity in the medial pre-frontal cortex, visual cortex, and superior temporal gyrus, whereas hyperactivity in the cerebellum, might represent the underlying neuropathological mechanisms of T2DM.

Right Frontoinsular Cortex: A Potential Imaging Biomarker to Evaluate T2DM-Induced Cognitive Impairment

Cognitive impairment in type 2 diabetes mellitus (T2DM) is associated with functional and structural abnormalities in the intrinsic brain network. The salience network (SN) is a neurocognitive network that maintains normal cognitive function, but it has received little attention in T2DM. We explored SN changes in patients with T2DM with normal cognitive function (DMCN) and in patients with T2DM with mild cognitive impairment (DMCI). Sixty-five T2DM patients and 31 healthy controls (HCs) underwent a neuropsychological assessment, independent component analysis (ICA), and voxel-based morphometry (VBM) analysis. The ICA extracted the SN for VBM to compare SN functional connectivity (FC) and gray matter (GM) volume (GMV) between groups. A correlation analysis examined the relationship between abnormal FC and GMV and clinical/cognitive variables. Compared with HCs, DMCN patients demonstrated increased FC in the left frontoinsular cortex (FIC), right anterior insula, and putamen, while DMCI patients demonstrated decreased right middle/inferior frontal gyrus FC. Compared with DMCN patients, DMCI patients showed decreased right FIC FC. There was no significant difference in SN GMV in DMCN and DMCI patients compared with HCs. FIC GMV was decreased in the DMCI patients compared with DMCN patients. In addition, right FIC FC and SN GMV positively correlated with Montreal Cognitive Assessment and Mini-Mental State Examination (MMSE) scores. These findings indicate that changes in SN FC, and GMV are complex non-linear processes accompanied by increased cognitive dysfunction in patients with T2DM. The right FIC may be a useful imaging biomarker for supplementary assessment of early cognitive dysfunction in patients with T2DM.

Brain deficits in prediabetic adults: A systematic review

Previous findings on the relationship between prediabetes (the precursor stage of type 2 diabetes) and brain health in humans are inconsistent. Thus, this systematic review of cross-sectional and longitudinal studies aimed to summarize what is currently known about brain deficits in prediabetic adults. Following the PRISMA reporting standards for systematic reviews, we conducted a comprehensive review of peer-reviewed journal articles published from 2009 to present, focusing on studies that assessed brain volume, structural connectivity, and cerebrovascular health in prediabetic adults and older adults (i.e., 18 years or older). We systematically searched PsychINFO, Scopus, Web of Science, Ovid MEDLINE, CINAHL, and EMbase databases. Quality assessment was based on the NIH Quality Assessment Tool for Observational and Cross-sectional Studies. In total, 19 studies were included in our review. Results from these studies show that prediabetes may be associated with deficits in brain structure and pathology, however, several studies also refute these findings. Moreover, we identified clear inconsistencies in study methodologies, including diabetes measures and classification, across studies that may account for these conflicting findings.

Aberrant Brain Functional Connectivity Strength and Effective Connectivity in Patients with Type 2 Diabetes Mellitus

Alterations of brain functional connectivity in patients with type 2 diabetes mellitus (T2DM) have been reported by resting-state functional magnetic resonance imaging studies, but the underlying precise neuropathological mechanism remains unclear. This study is aimed at investigating the implicit alterations of functional connections in T2DM by integrating functional connectivity strength (FCS) and Granger causality analysis (GCA) and further exploring their associations with clinical characteristics. Sixty T2DM patients and thirty-three sex-, age-, and education-matched healthy controls (HC) were recruited. Global FCS analysis of resting-state functional magnetic resonance imaging was performed to explore seed regions with significant differences between the two groups; then, GCA was applied to detect directional effective connectivity (EC) between the seeds and other brain regions. Correlations of EC with clinical variables were further explored in T2DM patients. Compared with HC, T2DM patients showed lower FCS in the bilateral fusiform gyrus, right superior frontal gyrus (SFG), and right postcentral gyrus, but higher FCS in the right supplementary motor area (SMA). Moreover, altered directional EC was found between the left fusiform gyrus and bilateral lingual gyrus and right medial frontal gyrus (MFG), as well as between the right SFG and bilateral frontal regions. In addition, triglyceride, insulin, and plasma glucose levels were correlated with the abnormal EC of the left fusiform, while disease duration and cognitive function were associated with the abnormal EC of the right SFG in T2DM patients. These results suggest that T2DM patients show aberrant brain function connectivity strength and effective connectivity which is associated with the diabetes-related metabolic characteristics, disease duration, and cognitive function, providing further insights into the complex neural basis of diabetes.

Dynamic brain-body coupling of breath-by-breath O2-CO2 exchange ratio with resting state cerebral hemodynamic fluctuations

BACKGROUND

The origin of low frequency cerebral hemodynamic fluctuations (CHF) in the resting state remains unknown. Breath-by breath O2-CO2 exchange ratio (bER) has been reported to correlate with the cerebrovascular response to brief breath hold challenge at the frequency range of 0.008-0.03Hz in healthy adults. bER is defined as the ratio of the change in the partial pressure of oxygen (ΔPO2) to that of carbon dioxide (ΔPCO2) between end inspiration and end expiration. In this study, we aimed to investigate the contribution of respiratory gas exchange (RGE) metrics (bER, ΔPO2 and ΔPCO2) to low frequency CHF during spontaneous breathing.

METHODS

Twenty-two healthy adults were included. We used transcranial Doppler sonography to evaluate CHF by measuring the changes in cerebral blood flow velocity (ΔCBFv) in bilateral middle cerebral arteries. The regional CHF were mapped with blood oxygenation level dependent (ΔBOLD) signal changes using functional magnetic resonance imaging. Temporal features and frequency characteristics of RGE metrics during spontaneous breathing were examined, and the simultaneous measurements of RGE metrics and CHF (ΔCBFv and ΔBOLD) were studied for their correlation.

RESULTS

We found that the time courses of ΔPO2 and ΔPCO2 were interdependent but not redundant. The oscillations of RGE metrics were coherent with resting state CHF at the frequency range of 0.008-0.03Hz. Both bER and ΔPO2 were superior to ΔPCO2 in association with CHF while CHF could correlate more strongly with bER than with ΔPO2 in some brain regions. Brain regions with the strongest coupling between bER and ΔBOLD overlapped with many areas of default mode network including precuneus and posterior cingulate.

CONCLUSION

Although the physiological mechanisms underlying the strong correlation between bER and CHF are unclear, our findings suggest the contribution of bER to low frequency resting state CHF, providing a novel insight of brain-body interaction via CHF and oscillations of RGE metrics.

Aberrant Brain Spontaneous Activity and Synchronization in Type 2 Diabetes Mellitus Patients: A Resting-State Functional MRI Study

The study aimed to investigate the aberration of brain spontaneous activity and synchronization in type 2 diabetes mellitus (T2DM) patients homozygous for the apolipoprotein E (APOE)-ε3 allele. In the APOE-ε3 homozygotes, 37 T2DM patients and 37 well-matched healthy controls (HC) were included to acquire blood sample measurements, neuropsychological tests, and brain functional MRI data. The amplitude of low-frequency fluctuations (ALFF) analysis was conducted to identify the brain areas with abnormal spontaneous activity. Then, the identified brain areas were taken as seeds to compute their functional connectivity (FC) with other brain regions. The two-sample t-test or the Mann-Whitney U test were applied to reveal significant differences in acquired measurements between the two groups. The potential correlations among the three types of measurements were explored using partial correlation analysis in the T2DM group. The T2DM group had elevated glycemic levels and scored lower on the cognitive assessment but higher on the anxiety and depression tests (p < 0.05). The T2DM group exhibited higher ALFF in the left middle occipital gyrus, and the left middle occipital gyrus had lower FC with the left caudate nucleus and the left inferior parietal gyrus (p < 0.05). No significant correlations were observed. T2DM patients homozygous for the APOE-ε3 allele exhibited aberrant brain spontaneous activity and synchronization in brain regions associated with vision-related information processing, executive function, and negative emotions. The findings may update our understanding of the mechanisms of brain dysfunction in T2DM patients in a neuroimaging perspective.

Large-Scale Neuronal Network Dysfunction in Diabetic Retinopathy

Diabetic retinopathy (DR) patients are at an increased risk of cognitive decline and dementia. There is accumulating evidence that specific functional and structural architecture changes in the brain are related to cognitive impairment in DR patients. However, little is known regarding whether the functional architecture of resting-state networks (RSNs) changes in DR patients. The purpose of this study was to investigate the intranetwork functional connectivity (FC) and functional network connectivity (FNC) of RSN changes in DR patients using independent component analysis (ICA). Thirty-four DR patients (18 men and 16 women; mean age, 53.53 ± 8.67 years) and 38 nondiabetic healthy controls (HCs) (15 men and 23 women; mean age, 48.63 ± 11.83 years), closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. ICA was applied to extract the nine RSNs. Then, two-sample t-tests were conducted to investigate different intranetwork FCs within nine RSNs between the two groups. The FNC toolbox was used to assess interactions among RSNs. Pearson correlation analysis was conducted to explore the relationship between intranetwork FCs and clinical variables in the DR group. A receiver operating characteristic (ROC) curve was conducted to assess the ability of the intranetwork FCs of RSNs in discriminating between the two groups. Compared to the HC group, DR patients showed significant decreased intranetwork FCs within the basal ganglia network (BGN), visual network (VN), ventral default mode network (vDMN), right executive control network (rECN), salience network (SN), left executive control network (lECN), auditory network (AN), and dorsal default mode network (dDMN). In addition, FNC analysis showed increased VN-BGN, VN-vDMN, VN-dDMN, vDMN-lECN, SN-BGN, lECN-dDMN, and AN-BGN FNCs in the DR group, relative to the HC group. Furthermore, altered intranetwork FCs of RSNs were significantly correlated with the glycosylated hemoglobin (HbA1c) level in DR patients. A ROC curve showed that these specific intranetwork FCs of RSNs discriminated between the two groups with a high degree of sensitivity and specificity. Our study highlighted that DR patients had widespread deficits in both low-level perceptual and higher-order cognitive networks. Our results offer important insights into the neural mechanisms of visual loss and cognitive decline in DR patients.

Abnormal Cingulum Bundle Induced by Type 2 Diabetes Mellitus: A Diffusion Tensor Tractography Study

Purpose: In Type 2 diabetes (T2DM), white matter (WM) pathology has been suggested to play an important role in the etiology of T2DM-related cognitive impairment. This study aims to investigate the integrity of the cingulum bundle (CB), a major WM tract, in T2DM patients using diffusion tensor tractography. Methods: Thirty-seven T2DM patients and 34 age-, sex- and education matched healthy controls were included and underwent diffusion tensor imaging. Tractography of bilateral CB tracts was performed and diffusion measurements were compared between the two groups. Next, brain regions with significant group differences on fractional anisotropy (FA) values were set as the region of interest (ROI), and the CB fibers that passed through were identified. Diffusion measures were extracted from these fibers to investigate their correlations with the cognitive performances and endocrine parameters. Results: T2DM patients exhibited decreased FA in bilateral CB, increased mean diffusion (MD) in the right CB, and decreased length in the left CB. Through voxel-wise comparison, the most prominent FA difference was identified in the posterior segment of the CB and the reconstructed tract was part of the retrosplenial component. Importantly, the diffusion measurements of the tract were significantly correlated with the impaired performance in executive functioning and elevated insulin resistance (IR) in the T2DM group, instead of the control group. Conclusions: The diffusion measurements in bilateral CB were altered in T2DM patients, which might reflect important neuropathologic changes in the fibers. Our study adds to knowledge about how the cingulum changes structurally along its entire length in T2DM and highlights the relationship between WM and cognitive performance. Besides, IR might be an important risk factor that warrants further exploration.

Neurovascular decoupling in type 2 diabetes mellitus without mild cognitive impairment: Potential biomarker for early cognitive impairment

Type 2 diabetes mellitus (T2DM) is a significant risk factor for mild cognitive impairment (MCI) and the acceleration of MCI to dementia. The high glucose level induce disturbance of neurovascular (NV) coupling is suggested to be one potential mechanism, however, the neuroimaging evidence is still lacking. To assess the NV decoupling pattern in early diabetic status, 33 T2DM without MCI patients and 33 healthy control subjects were prospectively enrolled. Then, they underwent resting state functional MRI and arterial spin labeling imaging to explore the hub-based networks and to estimate the coupling of voxel-wise cerebral blood flow (CBF)-degree centrality (DC), CBF-mean amplitude of low-frequency fluctuation (mALFF) and CBF- mean regional homogeneity (mReHo). We further evaluated the relationship between NV coupling pattern and cognitive performance (false discovery rate corrected). T2DM without MCI patients displayed significant decrease in the absolute CBF-mALFF, CBF-mReHo coupling of CBFnetwork and in the CBF-DC coupling of DCnetwork. Besides, networks which involved CBF and DC hubs mainly located in the default mode network (DMN). Furthermore, less severe disease and better cognitive performance in T2DM patients were significantly correlated with higher coupling of CBF-DC, CBF-mALFF or CBF-mReHo, especially for the cognitive dimensions of general function and executive function. Thus, coupling of CBF-DC, CBF-mALFF and CBF-mReHo may serve as promising indicators to reflect NV coupling state and to explain the T2DM related early cognitive impairment.