Altered Integration of Structural Covariance Networks in Young Children With Type 1 Diabetes

Non-alcoholic fatty liver disease is associated with structural covariance network reconfiguration in cognitively unimpaired adults with type 2 diabetes

Type 2 diabetes (T2D) is often accompanied by non-alcoholic fatty liver disease (NAFLD), both of which are related to brain damage and cognitive impairment. However, cortical structural alteration and its relationship with metabolism and cognition in T2D with NAFLD (T2NAFLD) and without NAFLD (T2noNAFLD) remain unclear. The brain MRI scans, clinical measures and neuropsychological test were evaluated in 50 normal controls (NC), 73 T2noNAFLD, and 58 T2NAFLD. The cortical thickness and graph theory properties of structural covariance network was calculated. Statistical analyses included one-way analysis of covariance with post hoc, partial correlation and mediation analysis. The nonparametric permutation test was performed to evaluate differences in topological properties of structural covariance network. We found T2NAFLD group had worse glucose and lipid profiles, more obesity and more severe insulin resistance, and poorer working memory compared to T2noNAFLD and NC. T2D patients demonstrated increase in cortical thickness compared to NC, but no difference between the two T2D groups. The structural covariance network integration decreased in T2D patients, with T2NAFLD exhibiting more obvious network reconfiguration at node level. Cortical thickness mediated the relationship between post-prandial glucose, waist-hip ratio, and working memory. The findings suggest that cortical thickening may be a compensatory response to reduced network integration, with NAFLD exacerbating regional structural network changes in T2D. This research advances our understanding of how these metabolic comorbidities contribute to cognitive decline, potentially guiding future therapeutic strategies for T2D patients with and without NAFLD.

Voxel-based texture similarity networks reveal individual variability and correlate with biological ontologies

The human brain is organized as a complex, hierarchical network. However, the structural covariance patterns among brain regions and the underlying biological substrates of such covariance networks remain to be clarified. The present study proposed a novel individualized structural covariance network termed voxel-based texture similarity networks (vTSNs) based on 76 refined voxel-based textural features derived from structural magnetic resonance images. Validated in three independent longitudinal healthy cohorts (40, 23, and 60 healthy participants, respectively) with two common brain atlases, we found that the vTSN could robustly resolve inter-subject variability with high test-retest reliability. In contrast to the regional-based texture similarity networks (rTSNs) that calculate radiomic features based on region-of-interest information, vTSNs had higher inter- and intra-subject variability ratios and test-retest reliability in connectivity strength and network topological properties. Moreover, the Spearman correlation indicated a stronger association of the gene expression similarity network (GESN) with vTSNs than with rTSNs (vTSN: r = 0.600, rTSN: r = 0.433, z = 39.784, P < 0.001). Hierarchical clustering identified 3 vTSN subnets with differential association patterns with 13 coexpression modules, 16 neurotransmitters, 7 electrophysiology, 4 metabolism, and 2 large-scale structural and 4 functional organization maps. Moreover, these subnets had unique biological hierarchical organization from the subcortex-limbic system to the ventral neocortex and then to the dorsal neocortex. Based on 424 unrelated, qualified healthy subjects from the Human Connectome Project, we found that vTSNs could sensitively represent sex differences, especially for connections in the subcortex-limbic system and between the subcortex-limbic system and the ventral neocortex. Moreover, a multivariate variance component model revealed that vTSNs could explain a significant proportion of inter-subject behavioral variance in cognition (80.0 %) and motor functions (63.4 %). Finally, using 494 healthy adults (aged 19-80 years old) from the Southwest University Adult Lifespan Dataset, the Spearman correlation identified a significant association between aging and vTSN strength, especially within the subcortex-limbic system and between the subcortex-limbic system and the dorsal neocortex. In summary, our proposed vTSN is robust in uncovering individual variability and neurobiological brain processes, which can serve as biologically plausible measures for linking biological processes and human behavior.

A longitudinal study of the brain structure network changes in HIV patients with ANI: combined VBM with SCN

Background

Despite the widespread adoption of combination antiretroviral therapy (cART) in managing HIV, the virus's impact on the brain structure of patients remains significant. This study aims to longitudinally explore the persistent effects of HIV on brain structure, focusing on changes in gray matter volume (GMV) and structural covariance network (SCN) among patients at the Asymptomatic Neurocognitive Impairment (ANI) stage.

Methods

This research involved 45 HIV patients diagnosed with ANI and 45 demographically matched healthy controls (HCs). The participants were observed over a 1.5-year period. Differences in GMV between groups were analyzed using voxel-based morphometry (VBM), while the graph theory model facilitated the establishment of topological metrics for assessing network indices. These differences were evaluated using two-sample t-tests and paired-sample t-tests, applying the network-based statistics method. Additionally, the study examined correlations between GMV and cognitive performance, as well as clinical variables.

Results

Compared with HCs, HIV patients demonstrated reduced GMV in the right middle temporal gyrus and left middle frontal gyrus (FWE, p < 0.05), along with decreased betweenness centrality (BC) in the left anterior cingulate and paracingulate cortex. Conversely, an increase in the clustering coefficient (Cp) was observed (FDR, p < 0.05). During the follow-up period, a decline in GMV in the right fusiform gyrus (FWE, p < 0.05) and a reduction in node efficiency (Ne) in the triangular part of the inferior frontal gyrus were noted compared with baseline measurements (FDR, p < 0.05). The SCN of HIV patients exhibited small-world properties across most sparsity levels (Sigma >1), and area under the curve (AUC) analysis revealed no significant statistical differences between groups.

Conclusion

The findings suggest that despite the administration of combination antiretroviral therapy (cART), HIV continues to exert slow and sustained damage on brain structures. However, when compared to HCs, the small-world properties of the patients' SCNs did not significantly differ, and the clustering coefficient, indicative of the overall information-processing capacity of the brain network, was slightly elevated in HIV patients. This elevation may relate to compensatory effects of brain area functions, the impact of cART, functional reorganization, or inflammatory responses.

Abnormal Topological Organization of Structural Covariance Networks in Patients with Temporal Lobe Epilepsy Comorbid Sleep Disorder

OBJECTIVE

The structural covariance network (SCN) alterations in patients with temporal lobe epilepsy and comorbid sleep disorder (PWSD) remain poorly understood. This study aimed to investigate changes in SCNs using structural magnetic resonance imaging.

METHODS

Thirty-four PWSD patients, thirty-three patients with temporal lobe epilepsy without sleep disorder (PWoSD), and seventeen healthy controls underwent high-resolution structural MRI imaging. Subsequently, SCNs were constructed based on gray matter volume and analyzed via graph-theoretical approaches.

RESULTS

PWSD exhibited significantly increased clustering coefficients, shortest path lengths, transitivity, and local efficiency. In addition, various distributions and numbers of SCN hubs were identified in PWSD. Furthermore, PWSD networks were less robust to random and target attacks than those of healthy controls and PWoSD patients.

CONCLUSION

This study identifies aberrant SCN changes in PWSD that may be related to the susceptibility of patients with epilepsy to sleep disorders.

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.

Altered gray matter structural covariance networks in drug-naïve and treated early HIV-infected individuals

Background

While regional brain structure and function alterations in HIV-infected individuals have been reported, knowledge about the topological organization in gray matter networks is limited. This research aims to investigate the effects of early HIV infection and combination antiretroviral therapy (cART) on gray matter structural covariance networks (SCNs) by employing graph theoretical analysis.

Methods

Sixty-five adult HIV+ individuals (25–50 years old), including 34 with cART (HIV+/cART+) and 31 medication-naïve (HIV+/cART–), and 35 demographically matched healthy controls (HCs) underwent high-resolution T1-weighted images. A sliding-window method was employed to create “age bins,” and SCNs (based on cortical thickness) were constructed for each bin by calculating Pearson's correlation coefficients. The group differences of network indices, including the mean nodal path length (Nlp), betweenness centrality (Bc), number of modules, modularity, global efficiency, local efficiency, and small-worldness, were evaluated by ANOVA and post-hoc tests employing the network-based statistics method.

Results

Relative to HCs, less efficiency in terms of information transfer in the parietal and occipital lobe (decreased Bc) and a compensated increase in the frontal lobe (decreased Nlp) were exhibited in both HIV+/cART+ and HIV+/cART– individuals (P &lt; 0.05, FDR-corrected). Compared with HIV+/cART– and HCs, less specialized function segregation (decreased modularity and small-worldness property) and stronger integration in the network (increased Eglob and little changed path length) were found in HIV+/cART+ group (P &lt; 0.05, FDR-corrected).

Conclusion

Early HIV+ individuals exhibited a decrease in the efficiency of information transmission in sensory regions and a compensatory increase in the frontal lobe. HIV+/cART+ showed a less specialized regional segregation function, but a stronger global integration function in the network.

A Pilot randomized trial to examine effects of a hybrid closed-loop insulin delivery system on neurodevelopmental and cognitive outcomes in adolescents with type 1 diabetes

Type 1 diabetes (T1D) is associated with lower scores on tests of cognitive and neuropsychological function and alterations in brain structure and function in children. This proof-of-concept pilot study (ClinicalTrials.gov Identifier NCT03428932) examined whether MRI-derived indices of brain development and function and standardized IQ scores in adolescents with T1D could be improved with better diabetes control using a hybrid closed-loop insulin delivery system. Eligibility criteria for participation in the study included age between 14 and 17 years and a diagnosis of T1D before 8 years of age. Randomization to either a hybrid closed-loop or standard diabetes care group was performed after pre-qualification, consent, enrollment, and collection of medical background information. Of 46 participants assessed for eligibility, 44 met criteria and were randomized. Two randomized participants failed to complete baseline assessments and were excluded from final analyses. Participant data were collected across five academic medical centers in the United States. Research staff scoring the cognitive assessments as well as those processing imaging data were blinded to group status though participants and their families were not. Forty-two adolescents, 21 per group, underwent cognitive assessment and multi-modal brain imaging before and after the six month study duration. HbA1c and sensor glucose downloads were obtained quarterly. Primary outcomes included metrics of gray matter (total and regional volumes, cortical surface area and thickness), white matter volume, and fractional anisotropy. Estimated power to detect the predicted treatment effect was 0.83 with two-tailed, α = 0.05. Adolescents in the hybrid closed-loop group showed significantly greater improvement in several primary outcomes indicative of neurotypical development during adolescence compared to the standard care group including cortical surface area, regional gray volumes, and fractional anisotropy. The two groups were not significantly different on total gray and white matter volumes or cortical thickness. The hybrid closed loop group also showed higher Perceptual Reasoning Index IQ scores and functional brain activity more indicative of neurotypical development relative to the standard care group (both secondary outcomes). No adverse effects associated with study participation were observed. These results suggest that alterations to the developing brain in T1D might be preventable or reversible with rigorous glucose control. Long term research in this area is needed.

Young Children with Type 1 Diabetes: Recent Advances in Behavioral Research

PURPOSE OF REVIEW

This review provides a recent update of behavioral research pertinent to young children with T1D and addresses current priorities and future directions.

RECENT FINDINGS

Rates of type 1 diabetes (T1D) in young children (ages 1-7) are continuing to rise. Since 2014, changes to diabetes care and management have impacted young children and reinforced the need for increased attention and interventions to support diabetes management, especially in caregivers who are primarily responsible for their young child's diabetes management. T1D is associated with unique physiologic challenges in young children, with constant management demands elevating parental diabetes-related stress and fear of hypoglycemia. Diabetes technology use has significantly increased in young children, contributing to improvements in glycemic levels and parent and child psychosocial functioning. Yet despite the positive outcomes demonstrated in select clinical behavioral interventions, research with this young child age group remains limited in scope and quantity.

Abnormalities of Cortical Morphology and Structural Covariance Network in Patients with Subacute Basal Ganglia Stroke

RATIONALE AND OBJECTIVES

The direct damage caused by ischemic stroke is relatively localized, but structural reorganization of cortical regions could occur across the brain. Changes of large-scale, cortical structural brain networks after basal ganglia stroke are less well reported. We, therefore, aim to explore the abnormalities of cortical morphology and structural network topology in patients with unilateral basal ganglia stroke during the subacute period.

MATERIALS AND METHODS

Thirty patients with first-ever basal ganglia stroke and thirty age- and sex-matched healthy controls were recruited for our analysis. Patients underwent structural magnetic resonance imaging examinations and clinical assessment from seven days to three months post-stroke. Alterations in cortical morphology and topological properties of the cortical structural network were measured respectively using the surface-based morphology and graph-theoretical methods.

RESULTS

We observed focal cortical atrophy, specifically in areas of frontal and temporal cortices. Moreover, the cortical thickness in the contralesional transverse temporal gyrus and superior temporal gyrus was positively correlated with cognitive function scores. Network analysis revealed that patients with basal ganglia stroke showed increased clustering coefficient, increased mean local efficiency as well as a reorganization of degree-based hubs. In addition, these patients also showed reduced robustness under a random attack compared to healthy controls.

CONCLUSION

These findings indicated a unique pattern of cortical reorganization and the abnormal topological organization of cortical thickness-based structural covariance networks in patients with basal ganglia stroke, which is beneficial to understand the pathophysiological mechanisms of functional disorders at the cortical structural network level and find potential targets for induced neuromodulation.

Altered structural brain networks in linguistic variants of frontotemporal dementia

Semantic (svPPA) and nonfluent (nfvPPA) variants of primary progressive aphasia (PPA) have recently been associated with distinct patterns of white matter and functional network alterations in left frontoinsular and anterior temporal regions, respectively. Little information exists, however, about the topological characteristics of gray matter covariance networks in these two PPA variants. In the present study, we used a graph theory approach to describe the structural covariance network organization in 34 patients with svPPA, 34 patients with nfvPPA and 110 healthy controls. All participants underwent a 3 T structural MRI. Next, we used cortical thickness values and subcortical volumes to define subject-specific connectivity networks. Patients with svPPA and nfvPPA were characterized by higher values of normalized characteristic path length compared with controls. Moreover, svPPA patients had lower values of normalized clustering coefficient relative to healthy controls. At a regional level, patients with svPPA showed a reduced connectivity and impaired information processing in temporal and limbic brain areas relative to controls and nfvPPA patients. By contrast, local network changes in patients with nfvPPA were focused on frontal brain regions such as the pars opercularis and the middle frontal cortex. Of note, a predominance of local metric changes was observed in the left hemisphere in both nfvPPA and svPPA brain networks. Taken together, these findings provide new evidences of a suboptimal topological organization of the structural covariance networks in svPPA and nfvPPA patients. Moreover, we further confirm that distinct patterns of structural network alterations are related to neurodegenerative mechanisms underlying each PPA variant.

Gout Is Not Just Arthritis: Abnormal Cortical Thickness and Structural Covariance Networks in Gout

Background: Hyperuricemia is the cause of gout. The antioxidant and neuroprotective effects of uric acid seem to benefit some patients with central nervous system injury. However, changes in the brain structure have not been discovered in patients with gout.

Object: Clarify the changes in cortical thickness in patients with gout and the alteration of the structural covariance networks (SCNs) based on cortical thickness.

Methods: We collected structural MRIs of 23 male gout patients and 23 age-matched healthy controls. After calculating and comparing the difference in cortical thickness between the two groups, we constructed and analyzed the cortical thickness covariance networks of the two groups, and we investigated for any changes in SCNs of gout patients.

Results: Gout patients have thicker cortices in the left postcentral, left supramarginal, right medial temporal, and right medial orbitofrontal regions; and thinner cortices were found in the left insula, left superior frontal, right pericalcarine, and right precentral regions. In SCN analysis, between-group differences in global network measures showed that gout patients have a higher global efficiency. In regional network measures, more nodes in gout patients have increased centrality. In network hub analysis, we found that the transfer of the core hub area, rather than the change in number, may be the characteristic of the gout's cortical thickness covariance network.

Conclusion: This is the first study on changes in brain cortical thickness and SCN based on graph theory in patients with gout. The present study found that, compared with healthy controls, gout patients show regional cortical thinning or thickening, and variation in the properties of the cortical thickness covariance network also changed. These alterations may be the combined effect of disease damage and physiological compensation. More research is needed to fully understand the complex underlying mechanisms of gout brain variation.

Cognitive impairment and associations with structural brain networks, endocrine status, and risk genotypes in newly orchiectomized testicular cancer patients

A higher incidence of cognitive impairment (CI) has previously been reported among orchiectomized testicular cancer patients (TCPs), but little is known about the underlying pathophysiology. The present study assessed CI in newly orchiectomized TCPs and explored the structural brain networks, endocrine status, and selected genotypes. Forty TCPs and 22 healthy controls (HCs) underwent neuropsychological testing and magnetic resonance imaging, and provided a blood sample. CI was defined as a z-score ≤ -2 on one neuropsychological test or ≤ -1.5 on two neuropsychological tests, and structural brain networks were investigated using graph theory. Associations of cognitive performance with brain networks, endocrine status (including testosterone levels and androgen receptor CAG repeat length), and genotypes (APOE, BDNF, COMT) were explored. Compared with HCs, TCPs performed poorer on 6 out of 15 neuropsychological tests, of which three tests remained statistically significant when adjusted for relevant between-group differences (p < 0.05). TCPs also demonstrated more CI than HCs (65% vs. 36%; p = 0.04). While global brain network analysis revealed no between-group differences, regional analysis indicated differences in node degree and betweenness centrality in several regions (p < 0.05), which was inconsistently associated with cognitive performance. In TCPs, CAG repeat length was positively correlated with delayed memory performance (r = 0.36; p = 0.02). A COMT group × genotype interaction effect was found for overall cognitive performance in TCPs, with risk carriers performing worse (p = 0.01). No effects were found for APOE, BDNF, or testosterone levels. In conclusion, our results support previous findings of a high incidence of CI in newly orchiectomized TCPs and provide novel insights into possible mechanisms.

Irregular structural networks of gray matter in patients with type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) induces dementia and cognitive decrements indicating the impairment of the central nervous system. While there is evidence showing abnormalities in white-matter structural networks in T2DM, the topological features of gray matter are still unknown. The study enrolled 30 right-handed T2DM patients and 20 healthy control subjects with matched age, gender, handedness, and education. Graph theoretical analysis of magnetic resonance imaging on gray matter volume was conducted to explore large-scale structural networks of brain. Although retaining small-worldness characteristics, the structural networks of grey matter in the T2DM group exhibited an increased clustering coefficient, prolonged characteristic path, decreased global efficiency, and more vulnerability to random failures or targeted attacks compared with controls. Additionally, the degree of structural networks in both T2DM and control groups was distributed exponentially in truncated power law. Our findings suggest that T2DM disturbed the overall topological features of gray matter networks, which provides a novel insight into the neurobiological mechanisms accounting for the cognitive impairment of T2DM patients.

Impact of Type 1 Diabetes in the Developing Brain in Children: A Longitudinal Study

OBJECTIVE

To assess whether previously observed brain and cognitive differences between children with type 1 diabetes and control subjects without diabetes persist, worsen, or improve as children grow into puberty and whether differences are associated with hyperglycemia.

RESEARCH DESIGN AND METHODS

One hundred forty-four children with type 1 diabetes and 72 age-matched control subjects without diabetes (mean ± SD age at baseline 7.0 ± 1.7 years, 46% female) had unsedated MRI and cognitive testing up to four times over 6.4 ± 0.4 (range 5.3-7.8) years; HbA1c and continuous glucose monitoring were done quarterly. FreeSurfer-derived brain volumes and cognitive metrics assessed longitudinally were compared between groups using mixed-effects models at 6, 8, 10, and 12 years. Correlations with glycemia were performed.

RESULTS

Total brain, gray, and white matter volumes and full-scale and verbal intelligence quotients (IQs) were lower in the diabetes group at 6, 8, 10, and 12 years, with estimated group differences in full-scale IQ of -4.15, -3.81, -3.46, and -3.11, respectively (P < 0.05), and total brain volume differences of -15,410, -21,159, -25,548, and -28,577 mm3 at 6, 8, 10, and 12 years, respectively (P < 0.05). Differences at baseline persisted or increased over time, and brain volumes and cognitive scores negatively correlated with a life-long HbA1c index and higher sensor glucose in diabetes.

CONCLUSIONS

Detectable changes in brain volumes and cognitive scores persist over time in children with early-onset type 1 diabetes followed longitudinally; these differences are associated with metrics of hyperglycemia. Whether these changes can be reversed with scrupulous diabetes control requires further study. These longitudinal data support the hypothesis that the brain is a target of diabetes complications in young children.

Brain Structural Covariance Networks in Behavioral Variant of Frontotemporal Dementia

Recent research on behavioral variant frontotemporal dementia (bvFTD) has shown that personality changes and executive dysfunctions are accompanied by a disease-specific anatomical pattern of cortical and subcortical atrophy. We investigated the structural topological network changes in patients with bvFTD in comparison to healthy controls. In particular, 25 bvFTD patients and 20 healthy controls underwent structural 3T MRI. Next, bilaterally averaged values of 34 cortical surface areas, 34 cortical thickness values, and six subcortical volumes were used to capture single-subject anatomical connectivity and investigate network organization using a graph theory approach. Relative to controls, bvFTD patients showed altered small-world properties and decreased global efficiency, suggesting a reduced ability to combine specialized information from distributed brain regions. At a local level, patients with bvFTD displayed lower values of local efficiency in the cortical thickness of the caudal and rostral middle frontal gyrus, rostral anterior cingulate, and precuneus, cuneus, and transverse temporal gyrus. A significant correlation was also found between the efficiency of caudal anterior cingulate thickness and Mini-Mental State Examination (MMSE) scores in bvFTD patients. Taken together, these findings confirm the selective disruption in structural brain networks of bvFTD patients, providing new insights on the association between cognitive decline and graph properties.

Abnormal Topological Organization of Sulcal Depth-Based Structural Covariance Networks in Parkinson's Disease

Recent research on Parkinson's disease (PD) has demonstrated the topological abnormalities of structural covariance networks (SCNs) using various morphometric features from structural magnetic resonance images (sMRI). However, the sulcal depth (SD)-based SCNs have not been investigated. In this study, we used SD to investigate the topological alterations of SCNs in 60 PD patients and 56 age- and gender-matched healthy controls (HC). SCNs were constructed by thresholding SD correlation matrices of 68 regions and analyzed using graph theoretical approaches. Compared with HC, PD patients showed increased normalized clustering coefficient and normalized path length, as well as a reorganization of degree-based and betweenness-based hubs (i.e., less frontal hubs). Moreover, the degree distribution analysis showed more high-degree nodes in PD patients. In addition, we also found the increased assortativity and reduced robustness under a random attack in PD patients compared to HC. Taken together, these findings indicated an abnormal topological organization of SD-based SCNs in PD patients, which may contribute in understanding the pathophysiology of PD at the network level.

Cognitive impairment and associations with structural brain networks, endocrine status, and risk genotypes in patients with newly diagnosed prostate cancer referred to androgen-deprivation therapy

BACKGROUND

Evidence suggests that patients with prostate cancer (PCPs) receiving androgen-deprivation therapy (ADT) are at risk for cognitive impairment. Research with other populations with cancer indicates that cognitive impairment may also occur before systemic treatment. The authors assessed cognitive impairment in untreated PCPs referred to ADT and explored associations with structural brain networks, endocrine status, and selected genotypes.

METHODS

Forty untreated PCPs and 27 healthy controls (HCs) who completed a questionnaire package underwent neuropsychological testing, magnetic resonance imaging, and blood sampling. Cognitive impairment was defined as a z score ≤-2 on 1 neuropsychological test or ≤-1.5 on 2 neuropsychological tests. Structural brain networks were investigated using diffusion-weighted imaging and graph theory. Associations of cognitive performance with patient-reported outcome measures (PROMs), brain networks, testosterone levels, and genotypes (apolipoprotein ε [APOE], catechol-O-methyltransferase [COMT], and brain-derived neurotrophic factor [BDNF]) were explored.

RESULTS

PCPs performed poorer than HCs on 7 of 15 neuropsychological tests and exhibited a higher frequency of cognitive impairment (57.5% vs 22.2%; P ≤ .01 to .03). All neuropsychological outcomes were associated with ≥1 PROM (P ≤ .01 to .04). Compared with the HC group, the PCP group exhibited altered global network organization as well as disrupted regional network characteristics in frontal and temporal regions (P < .01). PCPs had lower testosterone levels (P < .01) than HCs, which correlated with better visuospatial performance (r = -0.33; P = .04). No effects were found of APOE, COMT, or BDNF.

CONCLUSIONS

The current results suggest that untreated PCPs may demonstrate cognitive impairment and that psychological and behavioral symptoms (PROMs), as well as impairment in structural brain networks, might be the underlying mechanisms.

Aberrant Brain Network Integration and Segregation in Diabetic Peripheral Neuropathy Revealed by Structural Connectomics

Diabetic peripheral neuropathy (DPN) is one of the most common forms of peripheral neuropathy, and its incidence has been increasing. Mounting evidence has shown that patients with DPN have been associated with widespread alterations in the structure, function and connectivity of the brain, suggesting possible alterations in large-scale brain networks. Using structural covariance networks as well as advanced graph-theory-based computational approaches, we investigated the topological abnormalities of large-scale brain networks for a relatively large sample of patients with DPN (N = 67) compared to matched healthy controls (HCs; N = 88). Compared with HCs, the structural covariance networks of patients with DPN showed an increased characteristic path length, clustering coefficient, sigma, transitivity, and modularity, suggestive of inefficient global integration and increased local segregation. These findings may improve our understanding of the pathophysiological mechanisms underlying alterations in the central nervous system of patients with DPN from the perspective of large-scale structural brain networks.

Brain Function Differences in Children With Type 1 Diabetes: A Functional MRI Study of Working Memory

Glucose is a primary fuel source to the brain, yet the influence of dysglycemia on neurodevelopment in children with type 1 diabetes remains unclear. We examined brain activation using functional MRI in 80 children with type 1 diabetes (mean ± SD age 11.5 ± 1.8 years; 46% female) and 47 children without diabetes (control group) (age 11.8 ± 1.5 years; 51% female) as they performed a visuospatial working memory (N-back) task. Results indicated that in both groups, activation scaled positively with increasing working memory load across many areas, including the frontoparietal cortex, caudate, and cerebellum. Between groups, children with diabetes exhibited reduced performance on the N-back task relative to children in the control group, as well as greater modulation of activation (i.e., showed greater increase in activation with higher working memory load). Post hoc analyses indicated that greater modulation was associated in the diabetes group with better working memory function and with an earlier age of diagnosis. These findings suggest that increased modulation may occur as a compensatory mechanism, helping in part to preserve working memory ability, and further, that children with an earlier onset require additional compensation. Future studies that test whether these patterns change as a function of improved glycemic control are warranted.

Topological Regularization of Networks in Adult Patients with Moderate-to-Severe Obstructive Sleep Apnea-Hypopnea Syndrome: A Structural MRI Study

OBJECTIVE

Patients with obstructive sleep apnea-hypopnea syndrome (OSAHS) exhibit neurocognitive impairments; however, the neuroimaging mechanism of neurocognitive impairments remains unclear. The aim of this study was to understand the neuroimaging mechanism in adult patients with moderate-to-severe OSAHS, from the perspective of the connectome.

PATIENTS AND METHODS

Thirty-one untreated patients with moderate-to-severe OSAHS (mean age: 41.23±8.22) were compared with 26 good sleepers (GS) (mean age: 39.50±7.92) matched according to age, gender, handedness, and education level. All subjects underwent thin-slice T1WI scanning of the skull using a 3.0T MRI. Then, a large-scale structural covariance network was constructed based on the gray matter volume extracted from the structural MRI. Graph theory was then used to determine the topological changes in the structural covariance network of OSAHS patients.

RESULTS

Although small-world networks were retained,the structural covariance network exhibited topological irregularities in regular architecture as evidenced by an increase in the clustering coefficient (p=0.009), transfer coefficient (p=0.029) and local efficiency (p=0.031), and a local increase in the shortest path length (p<0.05) compared with the GS group. Locally, OSAHS patients showed a decrease in nodal betweenness and degree in the left inferior parietal gyrus, left angular gyrus and right anterior cingulate cortex compared with the GS group (p<0.05, uncorrected). In addition, the resistance of structural covariance networks in OSAHS patients to random fault is significantly lower than that of the GS group (p=0.044).

CONCLUSION

Structural covariance networks are abnormal in terms of multiple network parameters, which provide network-level insight into the neuroimaging mechanism of cognitive impairments in adult OSAHS patients.

Executive task-based brain function in children with type 1 diabetes: An observational study

BACKGROUND

Optimal glycemic control is particularly difficult to achieve in children and adolescents with type 1 diabetes (T1D), yet the influence of dysglycemia on the developing brain remains poorly understood.

METHODS AND FINDINGS

Using a large multi-site study framework, we investigated activation patterns using functional magnetic resonance imaging (fMRI) in 93 children with T1D (mean age 11.5 ± 1.8 years; 45.2% female) and 57 non-diabetic (control) children (mean age 11.8 ± 1.5 years; 50.9% female) as they performed an executive function paradigm, the go/no-go task. Children underwent scanning and cognitive and clinical assessment at 1 of 5 different sites. Group differences in activation occurring during the contrast of "no-go > go" were examined while controlling for age, sex, and scan site. Results indicated that, despite equivalent task performance between the 2 groups, children with T1D exhibited increased activation in executive control regions (e.g., dorsolateral prefrontal and supramarginal gyri; p = 0.010) and reduced suppression of activation in the posterior node of the default mode network (DMN; p = 0.006). Secondary analyses indicated associations between activation patterns and behavior and clinical disease course. Greater hyperactivation in executive control regions in the T1D group was correlated with improved task performance (as indexed by shorter response times to correct "go" trials; r = -0.36, 95% CI -0.53 to -0.16, p < 0.001) and with better parent-reported measures of executive functioning (r values < -0.29, 95% CIs -0.47 to -0.08, p-values < 0.007). Increased deficits in deactivation of the posterior DMN in the T1D group were correlated with an earlier age of T1D onset (r = -0.22, 95% CI -0.41 to -0.02, p = 0.033). Finally, exploratory analyses indicated that among children with T1D (but not control children), more severe impairments in deactivation of the DMN were associated with greater increases in hyperactivation of executive control regions (T1D: r = 0.284, 95% CI 0.08 to 0.46, p = 0.006; control: r = 0.108, 95% CI -0.16 to 0.36, p = 0.423). A limitation to this study involves glycemic effects on brain function; because blood glucose was not clamped prior to or during scanning, future studies are needed to assess the influence of acute versus chronic dysglycemia on our reported findings. In addition, the mechanisms underlying T1D-associated alterations in activation are unknown.

CONCLUSIONS

These data indicate that increased recruitment of executive control areas in pediatric T1D may act to offset diabetes-related impairments in the DMN, ultimately facilitating cognitive and behavioral performance levels that are equivalent to that of non-diabetic controls. Future studies that examine whether these patterns change as a function of improved glycemic control are warranted.

Abnormal Gray Matter Structural Covariance Networks in Children With Bilateral Cerebral Palsy

Bilateral cerebral palsy (BCP) is a common movement disorder in children, which often results in lifelong motor disability. One main symptom of BCP is the limitation of hand function in everyday activities. However, the neuroanatomical basis of this prominent hand impairment is yet to discover. Recent advances mainly focus on the lesions of BCP, but the views on the atypical development of cortical parcellations are extremely lacking. Here, in our study, neuroimaging with network analysis was employed to evaluate the changes of structural covariance networks (SCNs) in BCP children. We aimed to elucidate the alteration of SCNs based on cortical thickness (CT), and to reveal the relationship of CT and hand function in the participants with BCP. SCNs were constructed using covariance between regional CT, which was acquired from T1-weighted images of 19 children with BCP and 19 demographically matched healthy controls (HCs). Compared with HCs, BCP children showed increased CT in several regions involving the bilateral areas (lateral occipital, lingual, and fusiform) and right areas (cuneus, pericalcarine, inferior temporal, middle temporal, superior temporal, and insula). Decreased CT was found in the left superior temporal and right superior parietal cortices. Global network analyses revealed significantly decreased normalized clustering and small-worldness in the BCP network. The area under the curve (AUC) of global network measures varied slightly between the BCP and HC networks. The resistance of the both SCNs to the target and random attack showed no significant difference. Also, the BCP foci (right superior temporal and subtemporal cortex) showed a significantly negative correlation between the CT and manual ability. In this work, we identified the CT-based SCNs changes in children with BCP. The abnormal topological organization of SCNs was revealed, indicating abnormal CT, incongruous development of structural wiring, destructive nodal profiles of betweenness, and moved hub distribution in BCP children. This may provide a neuroanatomical hallmark of BCP in the developing brain. Therefore, our results may not only reflect neurodevelopmental aberrations but also compensatory mechanisms.

Aberrant brain structural large-scale connectome in Crohn's disease

BACKGROUND

Disturbed brain-gut interactions and a bidirectional relationship between inflammation and psychiatric symptoms such as anxiety and depression are being discussed in patients with inflammatory bowel diseases (IBD). Alterations of brain structure and function in IBD have been reported with heterogeneous results. Whether these changes reflect independent localized deficits or rather a systematic disruption in the anatomical organization of large-scale brain networks remains unclear. The present study investigated the gray matter structural connectome in patients with Crohn's disease (CD).

METHODS

Sixty participants (30 with quiescent CD and 30 matched healthy controls [HC]) underwent high-resolution brain MRI at 3 Tesla. Well-established graph theoretical metrics were analyzed at the global and regional network level and compared between groups.

KEY RESULTS

The networks in both groups followed a small-world organization, that is, an architecture that is simultaneously highly segregated and integrated. However, transitivity, a measure of global network segregation, was significantly reduced in patients (P = 0.003). Regionally, patients showed a reduction of nodal betweenness centrality in the right insula and cuneus and the left superior frontal cortex and reduced nodal degree within the left-hemispheric cingulate and the left lateral and right medial orbitofrontal cortex.

CONCLUSION AND INFERENCES

These findings lend support to the hypothesis that CD is accompanied by alterations in both global network organization and regional connectivity. A deeper understanding of neural central networks in IBD may facilitate the development of complementary strategies in the treatment of "extraintestinal" comorbid conditions such as depression or anxiety.

A promising structural magnetic resonance imaging assessment in patients with preclinical cognitive decline and diabetes mellitus

Subjective cognitive decline (SCD) is frequently reported in diabetic patients. Diabetes mellitus (DM) is associated with changes in the microstructure of the brain arise in diabetic patients, including changes in gray matter volume (GMV). However, the underlying mechanisms of changes in GMV in DM patients with cognitive impairment remain uncertain. Here, we present an overview of amyloid-β-dependent cognitive impairment in DM patients with SCD. Moreover, we review the evolving insights from studies on the GMV changes in GMV and cognitive dysfunction to which provide the mechanisms of cognitive impairment in T2DM. Ultimately, the novel structural magnetic resonance imaging (MRI) protocol was used for detecting neuroimaging biomarkers that can predict the clinical outcomes in diabetic patients with SCD. A reliable MRI protocol would be helpful to detect neurobiomarkers, and to understand the pathological mechanisms of preclinical cognitive impairment in diabetic patients.

Abnormal topological organization of structural covariance networks in amyotrophic lateral sclerosis

Neuroimaging studies of patients with amyotrophic lateral sclerosis (ALS) have shown widespread alterations in structure, function, and connectivity in both motor and non-motor brain regions, suggesting multi-systemic neurobiological abnormalities that might impact large-scale brain networks. Here, we examined the alterations in the topological organization of structural covariance networks of ALS patients (N = 60) compared with normal controls (N = 60). We found that structural covariance networks of ALS patients showed a consistent rearrangement towards a regularized architecture evidenced by increased path length, clustering coefficient, small-world index, and modularity, as well as decreased global efficiency, suggesting inefficient global integration and increased local segregation. Locally, ALS patients showed decreased nodal degree and betweenness in the gyrus rectus and/or Heschl's gyrus, and increased betweenness in the supplementary motor area, triangular part of the inferior frontal gyrus, supramarginal gyrus and posterior cingulate cortex. In addition, we identified a different number and distribution of hubs in ALS patients, showing more frontal and subcortical hubs than in normal controls. In conclusion, we reveal abnormal topological organization of structural covariance networks in ALS patients, and provide network-level evidence for the concept that ALS is a multisystem disorder with a cerebral involvement extending beyond the motor areas.