Systemic cytokines and GlycA discriminate disease status and predict corticosteroid response in HTLV-1-associated neuroinflammation.

BACKGROUND: HTLV-1-Associated Myelopathy/Tropical Spastic Paraparesis (HAM/TSP) is an incapacitating neuroinflammatory disorder for which no disease-modifying therapy is available, but corticosteroids provide some clinical benefit. Although HAM/TSP pathogenesis is not fully elucidated, older age, female sex and higher proviral load are established risk factors. We investigated systemic cytokines and a novel chronic inflammatory marker, GlycA, as possible biomarkers of immunopathogenesis and therapeutic response in HAM/TSP, and examined their interaction with established risk factors. PATIENTS AND METHODS: We recruited 110 People living with HTLV-1 (PLHTLV-1, 67 asymptomatic individuals and 43 HAM/TSP patients) with a total of 946 person-years of clinical follow-up. Plasma cytokine levels (IL-2, IL-4, IL-6, IL-10, IL-17A, IFN-γ, TNF) and GlycA were quantified by Cytometric Bead Array and 1NMR, respectively. Cytokine signaling and prednisolone response were validated in an independent cohort by nCounter digital transcriptomics. We used multivariable regression, machine learning algorithms and Bayesian network learning for biomarker identification. RESULTS: We found that systemic IL-6 was positively correlated with both age (r = 0.50, p < 0.001) and GlycA (r = 0.45, p = 0.00049) in asymptomatics, revealing an 'inflammaging" signature which was absent in HAM/TSP. GlycA levels were higher in women (p = 0.0069), but cytokine levels did not differ between the sexes. IFN-γ (p = 0.007) and IL-17A (p = 0.0001) levels were increased in untreated HAM/TSP Multivariable logistic regression identified IL-17A and proviral load as independent determinants of clinical status, resulting in modest accuracy of predicting HAM/TSP status (64.1%), while a machine learning-derived decision tree classified HAM/TSP patients with 90.7% accuracy. Pre-treatment GlycA and TNF levels significantly predicted clinical worsening (measured by Osame Motor Disability Scale), independent of proviral load. In addition, a poor prednisolone response was significantly correlated with higher post-treatment IFN-γ levels. Likewise, a transcriptomic IFN signaling score, significantly correlated with previously proposed HAM/TSP biomarkers (CASP5/CXCL10/FCGR1A/STAT1), was efficiently blunted by in vitro prednisolone treatment of PBMC from PLHTLV-1 and incident HAM/TSP. CONCLUSIONS: An age-related increase in systemic IL-6/GlycA levels reveals inflammaging in PLHTLV-1, in the absence of neurological disease. IFN-γ and IL-17A are biomarkers of untreated HAM/TSP, while pre-treatment GlycA and TNF predict therapeutic response to prednisolone pulse therapy, paving the way for a precision medicine approach in HAM/TSP.

Evaluation of the New Multi-HTLV Serological Assay: Improvement for HTLV-2 Detection.

Despite the accuracy of confirmatory tests for the diagnosis of human T cell lymphotropic virus (HTLV), inconclusive or false-negative results still occur when diagnosing human T cell lymphotropic virus type 2 (HTLV-2)-positive patients. The goal of this study was to evaluate the sensitivity and accuracy of a confirmatory immunoassay, the Multi-HTLV assay. A total of 246 plasma samples were tested by real-time polymerase chain reaction (qPCR) and used to calculate the sensitivity and typing accuracy of the Multi-HTLV assay. Of the 246 plasma samples, 127 were positive for human T cell lymphotropic virus type 1 (HTLV-1), 112 were positive for HTLV-2, and 7 were positive for both HTLV-1 and HTLV-2. Thereafter, the nonparametric Mann-Whitney U test was used to calculate the concordance between the qPCR test and Multi-HTLV assay in 12 samples with discrepant and inconclusive qPCR results. The Multi-HTLV assay showed high performance in identifying HTLV-1 and HTLV-2 with sensitivities of 97% [95% confidence interval (CI): 0.92-0.98] and 94% (0.87-0.96), respectively. However, due to typing performance (98% for HTLV-1 and 94% for HTLV-2), it had 95% agreement with positive HTLV-1 qPCR results (95% CI: 90.07-97.81) and 86% (78.04-91.01) of HTLV-2 qPCR results were positive. Moreover, this test was able to recognize 80% of indeterminate samples and all HTLV-2 positive samples that showed false-negative qPCR results. Our findings, derived from a substantial number of HTLV-positive samples, underscore the inherent reliability and feasibility of the Multi-HTLV assay, regardless of the molecular testing facilities. Furthermore, the distinctive multiparametric nature of this assay, combined with its straightforward procedural execution, introduces novel perspectives for analyzing specific serological profiles in each patient, as well as the potential for immunological monitoring of disease progression.

IL-10 predicts incident neuroinflammatory disease and proviral load dynamics in a large Brazilian cohort of people living with human T-lymphotropic virus type 1.

Human T-Lymphotropic Virus type-1 (HTLV-1) is a unique retrovirus associated with both leukemogenesis and a specific neuroinflammatory condition known as HTLV-1-Associated Myelopathy (HAM). Currently, most proposed HAM biomarkers require invasive CSF sampling, which is not suitable for large cohorts or repeated prospective screening. To identify non-invasive biomarkers for incident HAM in a large Brazilian cohort of PLwHTLV-1 (n=615 with 6,673 person-years of clinical follow-up), we selected all plasma samples available at the time of entry in the cohort (between 1997-2019), in which up to 43 cytokines/chemokines and immune mediators were measured. Thus, we selected 110 People Living with HTLV-1 (PLwHTLV-1), of which 68 were neurologically asymptomatic (AS) at baseline and 42 HAM patients. Nine incident HAM cases were identified among 68 AS during follow-up. Using multivariate logistic regression, we found that lower IL-10, IL-4 and female sex were independent predictors of clinical progression to definite HAM (AUROC 0.91), and outperformed previously suggested biomarkers age, sex and proviral load (AUROC 0.77). Moreover, baseline IL-10 significantly predicted proviral load dynamics at follow-up in all PLwHTLV-1. In an exploratory analysis, we identified additional plasma biomarkers which were able to discriminate iHAM from either AS (IL6Rα, IL-27) or HAM (IL-29/IFN-λ1, Osteopontin, and TNFR2). In conclusion, female sex and low anti-inflammatory IL-10 and IL-4 are independent risk factors for incident HAM in PLwHTLV-1,while proviral load is not, in agreement with IL-10 being upstream of proviral load dynamics. Additional candidate biomarkers IL-29/IL-6R/TNFR2 represent plausible therapeutic targets for future clinical trials in HAM patients.