The nuclear factor (erythroid 2)-like 2 (NRF2 or NFE2L2) transcription factor regulates the expression of many genes that are critical in maintaining cellular homeostasis. Its deregulation has been implicated in many diseases, including cancer and metabolic and neurodegenerative diseases. While several mechanisms by which NRF2 can be activated have gradually been identified over time, a more complete regulatory network of NRF2 is still lacking. Here we show through a genome-wide clustered regularly interspaced short palindromic repeat (CRISPR) screen that a total of 273 genes, when knocked out, will lead to sustained NRF2 activation. Pathway analysis revealed a significant overrepresentation of genes (18 of the 273 genes) involved in autophagy. Molecular validation of a subset of the enriched genes identified 8 high-confidence genes that negatively regulate NRF2 activity irrespective of cell type: ATG12, ATG7, GOSR1, IFT172, NRXN2, RAB6A, VPS37A, and the well-known negative regulator of NRF2, KEAP1. Of these, ATG12, ATG7, KEAP1, and VPS37A are known to be involved in autophagic processes. Our results present a comprehensive list of NRF2 negative regulators and reveal an intimate link between autophagy and NRF2 regulation.

Background Multiple sclerosis (MS) is a complex, heterogenous disease characterized by inflammation, demyelination, and blood–brain barrier (BBB) permeability. Currently, active disease is determined by physician confirmed relapse or detection of contrast enhancing lesions via MRI indicative of BBB permeability. However, clinical confirmation of active disease can be cumbersome. As such, disease monitoring in MS could benefit from identification of an easily accessible biomarker of active disease. We believe extracellular vesicles (EV) isolated from plasma are excellent candidates to fulfill this need. Because of the critical role BBB permeability plays in MS pathogenesis and identification of active disease, we sought to identify EV originating from central nervous system (CNS) endothelial as biomarkers of active MS. Because endothelial cells secrete more EV when stimulated or injured, we hypothesized that circulating concentrations of CNS endothelial derived EV will be increased in MS patients with active disease. Methods To test this, we developed a novel method to identify EV originating from CNS endothelial cells isolated from patient plasma using flow cytometry. Endothelial derived EV were identified by the absence of lymphocyte or platelet markers CD3 and CD41, respectively, and positive expression of pan-endothelial markers CD31, CD105, or CD144. To determine if endothelial derived EV originated from CNS endothelial cells, EV expressing CD31, CD105, or CD144 were evaluated for expression of the myelin and lymphocyte protein MAL, a protein specifically expressed by CNS endothelial cells compared to endothelial cells of peripheral organs. Results Quality control experiments indicate that EV detected using our flow cytometry method are 0.2 to 1 micron in size. Flow cytometry analysis of EV isolated from 20 healthy controls, 16 relapsing–remitting MS (RRMS) patients with active disease not receiving disease modifying therapy, 14 RRMS patients with stable disease not receiving disease modifying therapy, 17 relapsing-RRMS patients with stable disease receiving natalizumab, and 14 RRMS patients with stable disease receiving ocrelizumab revealed a significant increase in the plasma concentration of CNS endothelial derived EV in patients with active disease compared to all other groups (p = 0.001). Conclusions: For the first time, we have identified a method to identify CNS endothelial derived EV in circulation from human blood samples. Results from our pilot study indicate that increased levels of CNS endothelial derived EV may be a biomarker of BBB permeability and active disease in MS.

Background and Purpose: Identification of new MS lesions on longitudinal MRI by human readers is time-consuming and prone to error. Our objective was to evaluate the improvement in a subject-level detection performance by readers when assisted by the automated statistical detection of change (SDC) algorithm. Materials and Methods: A total of 200 MS patients with mean inter-scan interval of 13.2 ± 2.4 months were included. SDC was applied to the baseline and follow-up FLAIR images to detect potential new lesions for confirmation by readers (Reader+SDC method). This method was compared with readers operating in the clinical workflow (Reader method) for a subject-level detection of new lesions. Results: Reader+SDC found 30 subjects (15.0%) with at least one new lesion, while Reader detected 16 subjects (8.0%). As a subject-level triage tool, SDC achieved a perfect sensitivity of 1.00 (95% CI: [0.88, 1.00]) and a moderate specificity of 0.67 (95% CI: [0.59, 0.74]). The agreement on a subject-level was 0.91 (95% CI: [0.87, 0.95]) between Reader+SDC and Reader, and 0.72 (95% CI: [0.66, 0.78]) between Reader+SDC and SDC. Conclusion: SDC improves the detection accuracy of human readers and can serve as a time-saving patient triage tool for detecting new MS lesion activity on longitudinal FLAIR images.

Background: Multiple sclerosis (MS) is a complex, heterogenous disease characterized by inflammation, demyelination, and blood-brain barrier (BBB) permeability. Currently, active disease is determined by physician confirmed relapse or detection of contrast enhancing lesions via MRI indicative of BBB permeability. However, clinical confirmation of active disease can be cumbersome. As such, active disease monitoring in MS could benefit from identification of an easily accessible biomarker of active disease. We believe extracellular vesicles (EV) isolated from plasma are excellent candidates to fulfill this need. Because of the critical role BBB permeability plays in MS pathogenesis and identification of active disease, we sought to identify EV originating from CNS endothelial as biomarkers of active MS. Because endothelial cells secrete more EV when stimulated or injured, we hypothesized that circulating concentrations of CNS endothelial derived EV will be increased in MS patients with active disease. Methods: To test this, we developed a novel method to identify EV originating from CNS endothelial cells isolated from patient plasma using flow cytometry. Endothelial derived EV were identified by the absence of lymphocyte or platelet markers CD3 and CD41, respectively, and positive expression of pan-endothelial markers CD31, CD105, and CD144. To determine if endothelial derived EV originated from CNS endothelial cells, EV expressing CD31, CD105, or CD144 were evaluated for MAL expression, a protein specifically expressed by CNS endothelial cells. Results: Analysis of EV isolated from 20 healthy controls, 16 relapsing-remitting MS (RRMS) patients with active disease not receiving disease modifying therapy, 14 RRMS patients with stable disease not receiving disease modifying therapy, 17 relapsing-RRMS patients with stable disease receiving natalizumab, and 14 RRMS patients with stable disease receiving ocrelizumab revealed a significant increase in the plasma concentration of CNS endothelial derived EV in patients with active disease compared to all other groups ( p = 0.001). Conclusions: For the first time, we have identified a method to identify CSN endothelial derived EV in circulation from human blood samples. Results from our pilot study indicate that increased levels of CNS endothelial derived EV may be a biomarker of BBB permeability and active disease in MS.