Mononuclear cell transcriptome changes associated with dimethyl fumarate in MS

Response to Fingolimod in Multiple Sclerosis Patients Is Associated with a Differential Transcriptomic Regulation

Fingolimod is an immunomodulatory sphingosine-1-phosphate (S1P) analogue approved for the treatment of relapsing-remitting multiple sclerosis (RRMS). The identification of biomarkers of clinical responses to fingolimod is a major necessity in MS to identify optimal responders and avoid the risk of disease progression in non-responders. With this aim, we used RNA sequencing to study the transcriptomic changes induced by fingolimod in peripheral blood mononuclear cells of MS-treated patients and their association with clinical response. Samples were obtained from 10 RRMS patients (five responders and five non-responders) at baseline and at 12 months of fingolimod therapy. Fingolimod exerted a vast impact at the transcriptional level, identifying 7155 differentially expressed genes (DEGs) compared to baseline that affected the regulation of numerous signaling pathways. These DEGs were predominantly immune related, including genes associated with S1P metabolism, cytokines, lymphocyte trafficking, master transcription factors of lymphocyte functions and the NF-kB pathway. Responder and non-responder patients exhibited a differential transcriptomic regulation during treatment, with responders presenting a higher number of DEGs (6405) compared to non-responders (2653). The S1P, NF-kB and TCR signaling pathways were differentially modulated in responder and non-responder patients. These transcriptomic differences offer the potential of being exploited as biomarkers of a clinical response to fingolimod.

Dimethyl fumarate-related immune and transcriptional signature is associated with clinical response in multiple sclerosis-treated patients

Background and objective

Dimethyl fumarate (DMF) is an immunomodulatory drug approved for the therapy of multiple sclerosis (MS). The identification of response biomarkers to DMF is a necessity in the clinical practice. With this aim, we studied the immunophenotypic and transcriptomic changes produced by DMF in peripheral blood mononuclear cells (PBMCs) and its association with clinical response.

Material and methods

PBMCs were obtained from 22 RRMS patients at baseline and 12 months of DMF treatment. Lymphocyte and monocyte subsets, and gene expression were assessed by flow cytometry and next-generation RNA sequencing, respectively. Clinical response was evaluated using the composite measure "no evidence of disease activity" NEDA-3 or "evidence of disease activity" EDA-3 at 2 years, classifying patients into responders (n=15) or non-responders (n=7), respectively.

Results

In the whole cohort, DMF produced a decrease in effector (TEM) and central (TCM) memory T cells in both the CD4+ and CD8+ compartments, followed by an increase in CD4+ naïve T cells. Responder patients presented a greater decrease in TEM lymphocytes. In addition, responder patients showed an increase in NK cells and were resistant to the decrease in the intermediate monocytes shown by non-responders. Responder patients also presented differences in 3 subpopulations (NK bright, NK dim and CD8 TCM) at baseline and 4 subpopulations (intermediate monocytes, regulatory T cells, CD4 TCM and CD4 TEMRA) at 12 months. DMF induced a mild transcriptional effect, with only 328 differentially expressed genes (DEGs) after 12 months of treatment. The overall effect was a downregulation of pro-inflammatory genes, chemokines, and activators of the NF-kB pathway. At baseline, no DEGs were found between responders and non-responders. During DMF treatment a differential transcriptomic response was observed, with responders presenting a higher number of DEGs (902 genes) compared to non-responders (189 genes).

Conclusions

Responder patients to DMF exhibit differences in monocyte and lymphocyte subpopulations and a distinguishable transcriptomic response compared to non-responders that should be further studied for the validation of biomarkers of treatment response to DMF.

Gut Microbiota Changes during Dimethyl Fumarate Treatment in Patients with Multiple Sclerosis

The gut microbiota is involved in the development of the immune system and can modulate the risk for immune-mediated disorders such as multiple sclerosis (MS). Dysbiosis has been demonstrated in MS patients and its restoration by disease-modifying treatments (DMTs) is hypothesized. We aimed to study the changes in gut microbiota composition during the first 6 months of treatment with dimethyl fumarate (DMF), an oral DMT, and to identify the microorganisms associated with DMF side effects. We collected and analyzed the gut microbiota of 19 MS patients at baseline and after 1, 3, and 6 months of DMF treatment. We then cross-sectionally compared gut microbiota composition according to the presence of gastrointestinal (GI) symptoms and flushing. Overall, the gut microbiota biodiversity showed no changes over the 6-month follow-up. At the genus level, DMF was associated with decreased Clostridium abundance after 6 months. In subjects reporting side effects, a higher abundance of Streptococcus, Haemophilus, Clostridium, Lachnospira, Blautia, Subdoligranulum, and Tenericutes and lower of Bacteroidetes, Barnesiella, Odoribacter, Akkermansia, and some Proteobacteria families were detected. Our results suggest that gut microbiota may be involved in therapeutic action and side effects of DMF, representing a potential target for improving disease course and DMT tolerability.

Omics approaches to understanding the efficacy and safety of disease-modifying treatments in multiple sclerosis

From the perspective of precision medicine, the challenge for the future is to improve the accuracy of diagnosis, prognosis, and prediction of therapeutic responses through the identification of biomarkers. In this framework, the omics sciences (genomics, transcriptomics, proteomics, and metabolomics) and their combined use represent innovative approaches for the exploration of the complexity and heterogeneity of multiple sclerosis (MS). This review examines the evidence currently available on the application of omics sciences to MS, analyses the methods, their limitations, the samples used, and their characteristics, with a particular focus on biomarkers associated with the disease state, exposure to disease-modifying treatments (DMTs), and drug efficacies and safety profiles.

Central stress processing, T cell responsivity to stress hormones, and disease severity in multiple sclerosis

Epidemiological, clinical and neuroscientific studies support a link between psychobiological stress and multiple sclerosis. Neuroimaging suggests that blunted central stress processing goes along with higher multiple sclerosis severity, neuroendocrine studies suggest that blunted immune system sensitivity to stress hormones is linked to stronger neuroinflammation. Until now, however, no effort has been made to elucidate whether central stress processing and immune system sensitivity to stress hormones are related in a disease-specific fashion, and if so, whether this relation is clinically meaningful. Consequently, we conducted two functional MRI analyses based on a total of 39 persons with multiple sclerosis and 25 healthy persons. Motivated by findings of an altered interplay between neuroendocrine stress processing and T-cell glucocorticoid sensitivity in multiple sclerosis, we searched for neural networks whose stress task-evoked activity is differentially linked to peripheral T-cell glucocorticoid signalling in patients versus healthy persons as a potential indicator of disease-specific CNS–immune crosstalk. Subsequently, we tested whether this activity is simultaneously related to disease severity. We found that activity of a network comprising right anterior insula, right fusiform gyrus, left midcingulate and lingual gyrus was differentially coupled to T-cell glucocorticoid signalling across groups. This network’s activity was simultaneously linked to patients’ lesion volume, clinical disability and information-processing speed. Complementary analyses revealed that T-cell glucocorticoid signalling was not directly linked to disease severity. Our findings show that alterations in the coupling between central stress processing and T-cell stress hormone sensitivity are related to key severity measures of multiple sclerosis.

Breaking the cycle: Reversal of flux in the tricarboxylic acid cycle by dimethyl fumarate

Objective

To infer molecular effectors of therapeutic effects and adverse events for dimethyl fumarate (DMF) in patients with relapsing-remitting MS (RRMS) using untargeted plasma metabolomics.

Methods

Plasma from 27 patients with RRMS was collected at baseline and 6 weeks after initiating DMF. Patients were separated into discovery (n = 15) and validation cohorts (n = 12). Ten healthy controls were also recruited. Metabolomic profiling using ultra-high-performance liquid chromatography mass spectrometry (UPLC-MS) was performed on the discovery cohort and healthy controls at Metabolon Inc (Durham, NC). UPLC-MS was performed on the validation cohort at the National Phenome Centre (London, UK). Plasma neurofilament concentration (pNfL) was assayed using the Simoa platform (Quanterix, Lexington, MA). Time course and cross-sectional analyses were performed to identify pharmacodynamic changes in the metabolome secondary to DMF and relate these to adverse events.

Results

In the discovery cohort, tricarboxylic acid (TCA) cycle intermediates fumarate and succinate, and TCA cycle metabolites succinyl-carnitine and methyl succinyl-carnitine increased 6 weeks following treatment (q < 0.05). Methyl succinyl-carnitine increased in the validation cohort (q < 0.05). These changes were not observed in the control population. Increased succinyl-carnitine and methyl succinyl-carnitine were associated with adverse events from DMF (flushing and abdominal symptoms). pNfL concentration was higher in patients with RRMS than in controls and reduced over 15 months of treatment.

Conclusion

TCA cycle intermediates and metabolites are increased in patients with RRMS treated with DMF. The results suggest reversal of flux through the succinate dehydrogenase complex. The contribution of succinyl-carnitine ester agonism at hydroxycarboxylic acid receptor 2 to both therapeutic effects and adverse events requires investigation.