Purpose of review Neuropsychiatric lupus (NPSLE) comprises a disparate collection of syndromes affecting the central and peripheral nervous systems. Progress in the attribution of neuropsychiatric syndromes to SLE-related mechanisms and development of targeted treatment strategies has been impeded by a lack of objective imaging biomarkers that reflect specific neuropsychiatric syndromes and/or pathologic mechanisms. The present review addresses recent publications of neuroimaging techniques in NPSLE. Recent findings Imaging studies grouping all NPSLE syndromes together are unable to differentiate between NPSLE and non-NPSLE. In contrast, diffusion tensor imaging, FDG-PET, resting, and functional MRI techniques in patients with stable non-NPSLE demonstrate abnormal network structural and functional connectivity and regional brain activity in multiple cortical areas involving the limbic system, hippocampus, frontal, parietal, and temporal lobes. Some of these changes associate with impaired cognitive performance or mood disturbance, autoantibodies or inflammatory proteins. Longitudinal data suggest progression over time. DCE-MRI demonstrates increased Blood-brain barrier permeability. Summary Study design issues related to patient selection (non-NPSLE vs. NPSLE syndromes, SLE disease activity, medications) are critical for biomarker development. Regional and network structural and functional changes identified with advanced brain imaging techniques in patients with non-NPSLE may be further developed as biomarkers for cognitive and mood disorders attributable to SLE-related mechanisms.

Advanced neuroimaging in neuropsychiatric systemic lupus erythematosus.

Neuropsychiatric systemic lupus erythematosus (NPSLE) is an autoimmune entity comprised of heterogenous syndromes affecting both the peripheral and central nervous system. Research on the pathophysiological substrate of NPSLE manifestations, including functional neuroimaging studies, is extremely limited. The present study examined person-specific patterns of whole-brain functional connectivity in NPSLE patients (n = 44) and age-matched healthy control participants (n = 39). Static functional connectivity graphs were calculated comprised of connection strengths between 90 brain regions. These connections were subsequently filtered through rigorous surrogate analysis, a technique borrowed from physics, novel to neuroimaging. Next, global as well as nodal network metrics were estimated for each individual functional brain network and were input to a robust machine learning algorithm consisting of a random forest feature selection and nested cross-validation strategy. The proposed pipeline is data-driven in its entirety, and several tests were performed in order to ensure model robustness. The best-fitting model utilizing nodal graph metrics for 11 brain regions was associated with 73.5% accuracy (74.5% sensitivity and 73% specificity) in discriminating NPSLE from healthy individuals with adequate statistical power. Closer inspection of graph metric values suggested an increased role within the functional brain network in NSPLE (indicated by higher nodal degree, local efficiency, betweenness centrality, or eigenvalue efficiency) as compared to healthy controls for seven brain regions and a reduced role for four areas. These findings corroborate earlier work regarding hemodynamic disturbances in these brain regions in NPSLE. The validity of the results is further supported by significant associations of certain selected graph metrics with accumulated organ damage incurred by lupus, with visuomotor performance and mental flexibility scores obtained independently from NPSLE patients.

/pdf/quantitative-identification-of-functional-connectivity-2cnwpqyulf.pdf

Quantitative Identification of Functional Connectivity Disturbances in Neuropsychiatric Lupus Based on Resting-State fMRI: A Robust Machine Learning Approach.

Converging evidence of impaired brain function in systemic lupus erythematosus: changes in perfusion dynamics and intrinsic functional connectivity

The aim of the study is to explore interhemispheric homotopic functional connectivity alterations in systemic lupus erythematosus (SLE) patients with and without neuropsychiatric lupus (NPSLE and non-NPSLE, respectively) and their potential correlations with clinical characteristics and neuropsychological performance. Based on resting-state functional MRI (rs-fMRI) data collected from SLE patients and matched healthy controls (HCs), the voxel-mirrored homotopic connectivity (VMHC) analysis was conducted to measure functional homotopy. Subsequently, correlations between altered functional homotopy and clinical/neuropsychological data were analyzed. Compared with the HC group, both NPSLE and non-NPSLE groups showed attenuated homotopic connectivity in middle temporal gyrus (MTG), cuneus (CUN), middle occipital gyrus (MOG), angular gyrus (ANG), and postcentral gyrus (PoCG). NPSLE patients also exhibited decreased homotopic connectivity in inferior parietal gyrus (IPG) and middle frontal gyrus (MFG). Compared with non-NPSLE patients, NPSLE patients showed weaker interhemispheric homotopic functional connectivity in MOG. Decreased homotopic functional connectivity in PoCG, IPG, and MOG were associated with the anxiety state of SLE patients. Our findings revealed attenuated functional homotopy in both NPSLE and non-NPSLE groups compared to the HC group, which appeared to be more severe in patients with comorbid neuropsychiatric lupus. Interhemispheric homotopy dysconnectivity may participate in the neuropathology of anxiety symptoms in SLE.

Disrupted resting-state interhemispheric functional connectivity in systemic lupus erythematosus patients with and without neuropsychiatric lupus.

The advent of fast informatics platforms, together with their wide availability led the computer science to play a primary role in many scientific fields such as chemistry, biology, physics and engineering. Although such a phenomenon allows performing analyses that were previously only imaginable, today an always-wider portion of the scientific community must deal with complex ad hoc installations procedures, command line scripts, external libraries dependences and other informatics issues. This editorial intends to highlight the need of more easy to handle software in order to allow a more widespread usage of the available bioinformatics tools while leaving the end user to focus only on the analysis itself.

The unbearable lightness of the GUI

Using resting-state functional magnetic resonance imaging and graph theory approaches to investigate the topological characteristics of functional networks and their potential correlations with clinical information in patients with systemic lupus erythematosus (SLE). A total of 41 patients and 35 volunteers were consecutively recruited. Detailed clinical data of all participants were recorded. All participants underwent a resting-state functional magnetic resonance imaging examination. Functional networks were constructed by a Pearson correlation matrix of 116 brain regions. The topological properties were analyzed by graph theory. Parametric tests were used to compare the topological properties between the groups. Partial correlation analysis was used to identify relationships between the abnormal topological properties and the clinical data. The nodal network metrics were abnormal in the SLE patients compared to the controls. Decreased nodal efficiency was identified in the right insula, bilateral putamen, and bilateral Heschl's gyrus in the SLE patients. Decreased degree centrality was also found in the right amygdala and bilateral Heschl's gyrus. In addition, the SLE patients showed decreased network functional connectivity (FC) between several regions, particularly between the basal ganglia and the cerebellum. Moreover, FC values between the right putamen and vermis 6 were positively correlated with Mini-Mental State Examination scores. The nodal efficiency and the degree centrality values in the left Heschl's gyrus were both positively correlated with the course of the disease. The topological structure of the functional network was apparently abnormal in SLE patients. FC values between the right putamen and vermis 6 may serve as a neuroimaging marker for evaluating the progressive cognitive decline in SLE patients. Decreased synergy between the basal ganglia region and the cerebellum in the extrapyramidal system may be one cause of cognitive dysfunction in SLE patients.

Abnormal topological organization in systemic lupus erythematosus: a resting-state functional magnetic resonance imaging analysis

The aim of this study was to investigate the abnormities in functional connectivity (FC) within each modular network and between modular networks in patients with systemic lupus erythematosus (SLE). Twelve meaningful modular networks were identified via independent component analysis from 41 patients and 40 volunteers. Parametric tests were used to compare the intra- and intermodular FC between the groups. Partial correlation analysis was used to seek the relationships between abnormal FCs and the clinical data. Compared to the controls, SLE patients showed decreased intramodular FC in the anterior default mode network (aDMN), posterior default mode network (pDMN), ventral attention network (VAN), and sensorimotor network (SMN) and increased intramodular FC in the medial visual network (mVN) and left frontoparietal network. In addition, SLE patients showed decreased intermodular FC between the SMN and the lateral visual network (lVN), between the SMN and the VAN, and between the pDMN and the lVN and exhibited increased intermodular FC between the SMN and the salience network (SAN), between the pDMN and the SAN, and between the aDMN and the VAN. Moreover, we found several correlations among the abnormal FCs and the Mini-Mental State Examination in SLE patients. Mild cognitive impairment is compensated by the hyperconnectivity between the aDMN and the VAN, while severe cognitive impairment tends to be compensated by the hyperconnectivity between the SMN and the SAN. The FC value between the SMN and the SAN and between the aDMN and the VAN may serve as neuroimaging markers for monitoring cognitive progression in SLE patients.

Jing-Tao Wu

Papers

Abnormal topological organization in systemic lupus erythematosus: a resting-state functional magnetic resonance imaging analysis

The altered functional modular organization in systemic lupus erythematosus: an independent component analysis study.