Identification of Biomarkers As Predictors of Patient-Reported Outcomes in Persons with Multiple Sclerosis Given Autologous Hematopoietic Stem Cell Transplantation

Introduction: Around 80% of persons with multiple sclerosis (MS) have a positive patient-reported outcome (PRO) to autologous hematopoietic stem cell transplantation (aHSCT); this figure is better than that obtained with the novel immunossuppresive drugs.

Objective: To identify markers for the appropriate selection of patients with multiple sclerosis who would benefit from aHSCT.

Methods: We evaluated the levels of six biomarkes in the peripheral blood of patients with MS prior to aHSCT. Each biomarker was selected according to its possible role in MS: microRNAs (miR-146a, miR-155 and miR-326) as immune system alteration markers; interleukin 4 induced 1 (IL4I1) as remyelination marker; neurofilament light chain protein (NFL) as neuroaxonal damage marker; and the human leukocyte antigen (HLA) allele HLA-DRB1*15 as a MS risk marker. The design of this study is cross-sectional; sample was divided into two transplant response groups (responders and non-responders). The response to transplantation was assessed using the PRO (expanded disability status scale -EDSS) score, evaluated before aHSCT and one year later. Pre-transplant samples were used to identify the different markers. The techniques used for markers analysis were qPCR for microRNA measurement (miR-146a, miR155, miR326), SSP-PCR for HLA-DRB1*15, and immunoassay for IL4I1 and NFL

Results: 34 patients were prospectively enrolled. 14 (41.2%) non-responders to transplantation (ΔEDSS < 0) and 20 (58.8%) with a positive response to transplantation (ΔEDSS > 0). The comparison made between the aHSCT PRO response groups, using the Mann-Whitney U statistical test, showed a statistically significant increase in the non-responder group in the following variables: hemoglobin (median = 14.9 vs median = 13.5) U = 81.5, p = .039; serum iron levels (median = 122.5 vs median = 91) U = 39, p =.04 and transferrin saturation (median = 33.94 vs median = 20.4) U = 30, p = .001. In addition, an increase in platelet count was observed in the good response group (median = 278.5 vs median = 229) U = 197.5, p = .043. Within the biomarkers evaluated, significant difference was only found in miR-146a levels, which showed an increase for the non-responder group (median = 6. 43 vs median = 3) U = 78, p = .03. We then performed a logistic regression analysis using the variables hemoglobin, serum iron levels, platelet count, miR146a, miR155, miR326, IL4I1 and NFL, to evaluate their predictive capacity in the response to transplantation. The logistic region model was configured to perform forward variable selection obtaining the following results: in the first step, 74.2% correct overall classification with the variable Iron; in the second step 82.8%, with the variables iron and hemoglobin; in the third step 89.7%, with the variables hemoglobin, serum iron levels and IL4I1; and in the third step 100%, with the variables hemoglobin, iron levels, IL4I1 and miR146a.

Conclusions: Serum iron levels, hemoglobin levels, transferrin saturation and platelet count before aHSCT prior to transplantation show differences between PRO responders and non-responders to aHSCT; these variables coupled with the biomarkers IL4I1 and miR146a can be employed in predictive models of the PRO positive response to aHSCT in persons with MS.

No relevant conflicts of interest to declare.