Structural Brain Network Reorganization in Patients with Neuropsychiatric Systemic Lupus Erythematosus

Disrupted resting-state brain functional network properties in non-neuropsychiatric systemic lupus erythematosus patients

INTRODUCTION

Previous fMRI studies revealed that the abnormal functional connectivity (FC) was related to cognitive impairment in patients with SLE. However, it remains unclear how the disease severity affects the functional topological organization of the whole-brain network in SLE patients without neuropsychiatric symptoms (non-NPSLE).

OBJECTIVE

We aim to examine the impairment of the whole-brain functional network in SLE patients without neuropsychiatric symptoms (non-NPSLE), which may improve the understanding of neural mechanism in SLE.

METHODS

We acquired resting-state fMRI data from 32 non-NPSLE patients and 32 healthy controls (HC), constructed their whole-brain functional network, and then estimated the topological properties including global and nodal parameters by using graph theory. Meanwhile, we also investigated the differences in intra- and inter-network FC between the non-NPSLE patients and the HC.

RESULTS

The non-NPSLE patients showed significantly lower clustering coefficient, global and local efficiency, but higher characteristic path length than the HC. The non-NPSLE patients had significantly lower nodal strength in two regions, ventromedial prefrontal cortex (vmPFC) and anterior PFC (aPFC) than the HC. We found the non-NPSLE patients had significantly lower intra-network FC within frontal-parietal network (FPN) and within default mode network (DMN), and significantly lower inter-network FC between DMN and FPN than the HC. The intra-network FC within DMN was negatively correlated with systemic lupus erythematosus disease activity index (SLEDAI).

CONCLUSION

Abnormal whole-brain functional network properties and abnormal intra- and inter-network FC may be related to cognitive impairment and disease degree in the non-NPSLE patients. Our findings provide a network perspective to understand the neural mechanisms of SLE.

Cerebral Metabolic Network in Patients With Anti-N-Methyl-D-Aspartate Receptor Encephalitis on 18F-FDG PET Imaging

Background

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is the most common autoimmune encephalitis (AE), and the prognosis may significantly be improved if identified earlier and immune-related treated more effectively. This study evaluated the brain metabolic network using fluorodeoxyglucose positron emission tomography (FDG PET).

Material and methods

FDG PET imaging of patients with NMDAR encephalitis was used to investigate the metabolic connectivity network, which was analyzed using the graph theory. The results in patients were compared to those in age- and sex-matched healthy controls.

Results

The hub nodes were mainly in the right frontal lobe in patients with NMDAR encephalitis. The global and local efficiencies in most brain regions were significantly reduced, and the shortest characteristic path length was significantly longer, especially in the temporal and occipital lobes. Significant network functions of topology properties were enhanced in the right frontal, caudate nucleus, and cingulate gyrus. In addition, the internal connection integration in the left cerebral hemisphere was poor, and the transmission efficiency of Internet information was low.

Conclusion

The present findings indicate that those characteristic and connections of metabolic network were changed in the brain by graph theory analysis quantitatively, which is helpful to better understand neuropathological and physiological mechanisms in patients with anti-NMDAR encephalitis.

Small-World Networks and Their Relationship With Hippocampal Glutamine/Glutamate Concentration in Healthy Adults With Varying Genetic Risk for Alzheimer's Disease

Background

Apolipoprotein E ɛ4 allele (ApoE4) is the most common gene polymorphism related to Alzheimer's disease (AD). Impaired synaptic dysfunction occurs in ApoE4 carriers before any clinical symptoms. It remains unknown whether ApoE4 status affects the hippocampal neuromodulation, which further influences brain network topology.

Purpose

To study the relationship of regional and global network properties by using graph theory analysis and glutamatergic (Glx) neuromodulation in the ApoE isoforms.

Study Type

Prospective.

Subjects

Eighty‐four cognitively normal adults (26 ApoE4 and 58 non‐ApoE4 carriers).

Field Strength/Sequence

Gradient‐echo echo‐planar and point resolved spectroscopy sequence at 3 T.

Assessment

Glx concentration in bilateral hippocampi were processed with jMRUI (4.0), and graph theory metrics (global: γ, λ, small‐worldness in whole brain; regional: nodal clustering coefficient (C_i) and nodal characteristic path length (L_i)) in top 20% highly connected hubs of subgroups (low‐risk: non‐ApoE4; high‐risk: APOE4) were calculated and compared.

Statistical Tests

Two‐sample t test was used to compare metrics between subgroups. Correlations between regional properties and Glx by Pearson's partial correlation with false discovery rate correction.

Results

Significant differences (P < 0.05) in C_i between subgroups were found in hubs of left inferior frontal, bilateral inferior temporal, and bilateral precentral gyri, right parahippocampus, and bilateral precuneus. In addition, there was a significant correlation between Glx in the left hippocampus and C_i in inferior frontal gyrus (r = −0.537, P = 0.024), right inferior temporal (r = −0.478, P = 0.043), right parahippocampus (r = −0.629, P = 0.016), left precentral (r = −0.581, P = 0.022), right precentral (r = −0.651, P = 0.003), left precuneus (r = −0.545, P = 0.024), and right precuneus (r = −0.567, P = 0.022); and L_i in left precuneus (r = 0.575, P = 0.032) and right precuneus (r = 0.586, P = 0.032) in the high‐risk group, but not in the low‐risk group.

Data Conclusion

Our results suggested that healthy ApoE4 carriers exhibit poorer local interconnectivity. Moreover, the close relationship between glutamate and small‐world network properties in ApoE4 carriers might reflect a compensatory response to the impaired network efficiency.

Evidence Level

2

Technical Efficacy

Stage 3

Altered properties of brain white matter structural networks in patients with nasopharyngeal carcinoma after radiotherapy

Previous neuroimaging studies revealed radiation-induced brain injury in patients with nasopharyngeal carcinoma (NPC) in the years after radiotherapy (RT). These injuries may be associated with structural and functional alterations. However, differences in the brain structural connectivity of NPC patients at different times after RT, especially in the early-delayed period, remain unclear. We acquired diffusion tensor imaging (DTI) data from three groups of NPC patients, 25 in the pre-RT (before RT) group, 22 in the early-delayed (1-6 months) period (post-RT-ED) group, and 33 in the late-delayed (>6 months) period (post-RT-LD) group. Then, we constructed brain white matter (WM) structural networks and used graph theory to compare their between-group differences. The NPC patients in the post-RT-ED group showed decreased global properties when compared with the pre-RT group. We also detected the nodes with between-group differences in nodal parameters. The nodes that differed between the post-RT-ED and pre-RT groups were mainly located in the default mode (DMN) and central executive networks (CEN); those that differed between the post-RT-LD and pre-RT groups were located in the limbic system; and those that differed between the post-RT-LD and post-RT-ED groups were mainly in the DMN. These findings may indicate that radiation-induced brain injury begins in the early-delayed period and that a reorganization strategy begins in the late-delayed period. Our findings may provide new insight into the pathogenesis of radiation-induced brain injury in normal-appearing brain tissue from the network perspective.

Brain connectomic associations with traditional Chinese medicine diagnostic classification of major depressive disorder: a diffusion tensor imaging study

Background

Major depressive disorder (MDD) is highly heterogeneous in pathogenesis and manifestations. Further classification may help characterize its heterogeneity. We previously have shown differential metabolomic profiles of traditional Chinese medicine (TCM) diagnostic subtypes of MDD. We further determined brain connectomic associations with TCM subtypes of MDD.

Methods

In this naturalistic study, 44 medication-free patients with a recurrent depressive episode were classified into liver qi stagnation (LQS, n = 26) and Heart and Spleen Deficiency (HSD, n = 18) subtypes according to TCM diagnosis. Healthy subjects (n = 28) were included as controls. Whole-brain white matter connectivity was analyzed on diffusion tensor imaging.

Results

The LQS subtype showed significant differences in multiple network metrics of the angular gyrus, middle occipital gyrus, calcarine sulcus, and Heschl's gyrus compared to the other two groups. The HSD subtype had markedly greater regional connectivity of the insula, parahippocampal gyrus, and posterior cingulate gyrus than the other two groups, and microstructural abnormalities of the frontal medial orbital gyrus and middle temporal pole. The insular betweenness centrality was strongly inversely correlated with the severity of depression and dichotomized the two subtypes at the optimal cutoff value with acceptable sensitivity and specificity.

Conclusions

The LQS subtype is mainly characterized by aberrant connectivity of the audiovisual perception-related temporal-occipital network, whereas the HSD subtype is more closely associated with hyperconnectivity and microstructural abnormalities of the limbic-paralimbic network. Insular connectivity may serve a biomarker for TCM-based classification of depression.Trial registration Registered at http://www.clinicaltrials.gov (NCT02346682) on January 27, 2015.

Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus

Objective To investigate brain structural connectivity in relation to cognitive abilities and systemic damage in systemic lupus erythematosus (SLE). Methods Structural and diffusion MRI data were acquired from 47 patients with SLE. Brains were segmented into 85 cortical and subcortical regions and combined with whole brain tractography to generate structural connectomes using graph theory. Global cognitive abilities were assessed using a composite variable g, derived from the first principal component of three common clinical screening tests of neurological function. SLE damage ( LD) was measured using a composite of a validated SLE damage score and disease duration. Relationships between network connectivity metrics, cognitive ability and systemic damage were investigated. Hub nodes were identified. Multiple linear regression, adjusting for covariates, was employed to model the outcomes g and LD as a function of network metrics. Results The network measures of density (standardised ß = 0.266, p = 0.025) and strength (standardised ß = 0.317, p = 0.022) were independently related to cognitive abilities. Strength (standardised ß = -0.330, p = 0.048), mean shortest path length (standardised ß = 0.401, p = 0.020), global efficiency (standardised ß = -0.355, p = 0.041) and clustering coefficient (standardised ß = -0.378, p = 0.030) were independently related to systemic damage. Network metrics were not related to current disease activity. Conclusion Better cognitive abilities and more SLE damage are related to brain topological network properties in this sample of SLE patients, even those without neuropsychiatric involvement and after correcting for important covariates. These data show that connectomics might be useful for understanding and monitoring cognitive function and white matter damage in SLE.