Transcriptional reprogramming in immune cells of HTLV-1 asymptomatic carriers and HAM/TSP patients following antiretroviral therapy

Transcriptional reprogramming in immune cells of HTLV-1 asymptomatic carriers and HAM/TSP patients following antiretroviral therapy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Transcriptional reprogramming in immune cells of HTLV-1 asymptomatic carriers and HAM/TSP patients following antiretroviral therapy Pooja Jain, Sai Chaitanya Rajendra Gaekwar, Salwa Ahmed, Felice Deminco, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7724833/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Human T-cell lymphotropic virus type 1 (HTLV-1) causes HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP), a chronic, immune-mediated spinal cord disease in which peripheral immune activation is thought to fuel central neuroinflammation. To delineate cell type-specific programs linked to disease, we performed single-cell RNA sequencing on the peripheral blood mononuclear cells (PBMCs) of the HTLV-1 infected asymptomatic carrier (AC) and HAM/TSP patient. Differential expression and pathway analysis localized the most pronounced transcriptional divergence to the monocyte compartment, revealing coordinated remodeling of macrophage classical (M1-like) activation, IL-10-regulatory signaling, leukocyte adhesion/diapedesis, and trans-endothelial migration pathway, and cytokine storm-related modules. Ingenuity Pathway Analysis highlighted overlap with multiple sclerosis-associated signaling, consistent with myeloid-driven neuroinflammation and potential blood-spinal cord barrier involvement. In an independent validation phase, we assayed the selected subsets of up- and down-regulated monocyte genes in AC and HAM/TSP participants enrolled in a randomized, open-label pilot trial in Brazil. Expression of several inflammatory markers was higher at baseline in HAM/TSP and decreased during dolutegravir (DTG) therapy, paralleling reductions in HTLV-1 proviral load (PVL) in the DTG arm. Collectively, these data suggest that antiviral strategies may modulate immune cell transcriptional programs that help reduce HTLV-1 PVL. Biological sciences/Immunology/Infectious diseases/Viral infection Biological sciences/Immunology/Infection HTLV-1 HAM/TP Monocytes Single cell sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Human T-cell lymphotropic virus type 1 (HTLV-1) is an oncogenic delta retrovirus that causes ໿adult T-cell leukemia/lymphoma (ATL) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP), a chronic, progressive inflammatory myelopathy of the spinal cord. Although an estimated 5–20 million people are infected worldwide, ~ 90% remain asymptomatic carriers (ACs); in symptomatic individuals, HAM/TSP manifests with gait disturbance, lower-extremity weakness, spasticity, low-back pain, urinary dysfunction, and sexual dysfunction, often with stepwise or insidious progression [ 1 ]. HAM/TSP pathogenesis is characterized by high peripheral proviral load (PVL) and persistent immune activation. HTLV-1-infected CD4 + T cells are expanded in the blood and traffic to the central nervous system (CNS), where they are thought to amplify neuroinflammation [ 2 , 3 ]. Patients exhibit elevated pro-inflammatory cytokines (e.g., IFN-γ, IL-6, and TNF-α) and robust Tax-specific Th1/CTL responses that correlate with disease severity, suggesting that peripheral immune dysregulation fuels spinal cord pathology [ 4 , 5 ]. Identifying the immune elements that contribute to HAM/TSP remains a major gap in our understanding of HTLV-1 pathogenesis. To address this, we applied Ingenuity Pathway Analysis (IPA) to single-cell transcriptomic data, revealing immune signaling networks including IL-10 signaling, classical macrophage activation, cytokine storm, and multiple sclerosis-related pathways that may shape the pathogenesis of HAM/TSP. Despite this T-cell centric framework, myeloid cells particularly monocytes, remain underexplored in HTLV-1 disease. Monocytes orchestrate antigen presentation, cytokine/chemokine production, and leukocyte trafficking across the blood–spinal cord barrier (BSCB). Prior reports in HTLV-1 infection describe increased PBMC expression of CXCL9/CXCL10/TNF, shifts in monocyte subsets (reduced classical CD14⁺⁺CD16⁻ with relative expansion of intermediate/nonclassical CD16⁺ populations), and monocyte-dependent modulation of T-cell activation and apoptosis, implicating peripheral myeloid programs in HAM/TSP pathogenesis [ 6 – 9 ]. Defining monocyte-intrinsic transcriptional states in HAM/TSP could therefore yield accessible biomarkers and therapeutic entry points. Therapeutic options for HAM/TSP remain limited. Corticosteroids and interferon-α can transiently attenuate inflammation in some patients, but durable disease-modifying effects are uncommon. Antiretrovirals have shown mixed results; zidovudine (AZT) and other reverse-transcriptase inhibitors have been evaluated primarily in ATL, with uncertain benefit in HAM/TSP [ 10 – 13 ]. Given that integration is essential for delta retroviral persistence, integrase inhibitors such as dolutegravir (DTG) merit investigation; however, clinical data in HTLV-1 are sparse and mechanistic effects on peripheral immune programs are poorly defined [ 14 ]. Dolutegravir works by inhibiting the integration stage in the viral life cycle, which could, in theory, help reduce the persistence of HTLV-1 infections and their related health issues. Studies indicate that anti-inflammatory medications, for example, resveratrol, might help downregulate pro-inflammatory cytokines and could be a way to improve immune response in infected patients [ 15 , 16 ]. Although antiretroviral therapy has significantly improved conditions of HIV-1 infected patients, such successes have not yet been translated into effective solution for HTLV-1 [ 10 ]. The efficacy of these therapeutic approaches has been limited, mainly because we don’t have full grasp on how pathogenesis of HTLV-1 works, especially with the role of different immune cells. To better understand this complex immunopathology, we utilized single-cell RNA sequencing (scRNA-seq). This allowed us to closely examine the specific signaling pathways that are more pronounced in patients with HTLV-1 infection [ 17 ]. Monocytes, which exhibit both pro- and anti-inflammatory responses, play a crucial role in immune regulation and the pathogenesis of HTLV-1-associated inflammatory diseases [ 6 ]. It is speculated that HTLV-1 transmission between monocytes and T cells may occur during antigen presentation and T-cell activation, and infected monocytes play a major role in inducing T-cell apoptosis. Increased expression of proinflammatory mediators such as CXCL9, CXCL10, and TNF was observed in PBMCs isolated from HAM/TSP patients. This hints that monocytes may play a significant role in HTLV-1 pathogenesis [ 8 ]. HTLV-1 infection has been indicated to dramatically change monocyte subsets, resulting in a drop in classical monocytes and a spike in intermediate and non-classical monocytes. These findings lend support to the role of monocytes in HTLV-1 pathogenesis and their survival in humans [ 9 ]. Here, we used single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) from a pair of one AC and one HAM/TSP subject to map cell type–specific transcriptional differences. Differential expression and pathway analysis localized the most pronounced divergence to the monocyte compartment, highlighting macrophage classical activation, IL-10 counter-regulation, leukocyte adhesion/diapedesis and trans-endothelial migration, and neuroinflammation-linked modules (including multiple-sclerosis–associated signaling). We then validated a prespecified subset of up- and down-regulated monocyte genes in an independent Brazilian cohort of AC and HAM/TSP participants enrolled in a longitudinal trial of DTG, testing whether these signatures are (i) enriched at baseline in HAM/TSP and (ii) modulated during integrase inhibitor therapy. This discovery-to-validation framework nominates peripheral monocyte programs as candidate biomarkers of disease activity and as potential targets to complement existing markers. MATERIALS AND METHODS Participants and samples A discovery pair was drawn from the University of California San Francisco HTLV Outcomes Study (HOST) cohort of HTLV-seropositive blood donors enrolled in 1992–1994, as previously described [ 18 , 19 ]. One asymptomatic carrier (AC) and one patient with HTLV-1–associated myelopathy/tropical spastic paraparesis (HAM/TSP) with detectable HTLV-1 at the time of blood donation were selected (Table 3). Cryopreserved peripheral blood mononuclear cells (PBMCs) were used for single-cell RNA-seq (scRNA-seq). For independent validation, we leveraged an open-label, randomized, controlled, phase 2 trial (PI: C. Brites) in Salvador, Brazil, evaluating dolutegravir (DTG, 50 mg/day) versus vitamin C (500 mg/day) in HTLV-1–infected adults. The target sample size was 100 participants (n = 50 HAM/TSP; n = 50 AC). Participants in the vitamin C arm who remained symptomatic after 12 months could cross over to DTG. Interim analyses included 83 participants (DTG n = 43, vitamin C n = 40) with study visits at baseline, week 24, week 48, and week 96. Clinical assessments included Functional Independence Measure, ASIA Impairment Scale, OSA-ME Motor Disability Scale, Modified Ashworth Scale, and DN4 Pain Questionnaire. Whole blood was collected at each time point for HTLV-1 proviral load (PVL) quantification by real-time PCR and for gene-expression validation in a prespecified subset of DTG-treated participants. All participants provided written informed consent in accordance with the Declaration of Helsinki and Brazilian National Health Council Resolution 466/12. The clinical validation cohort protocol was approved by the Institutional Review Boards of the Federal University of Bahia and CONEP and registered in ReBEC. Honeycomb Single-cell Sequencing and cell handling PBMCs were thawed, washed, and resuspended in PBS + 1% BSA. Cells were counted on a Countess 3 (Thermo Fisher). Two 96-well round-bottom plates were prepared with 1.25 × 10 5 cells/well. One plate was incubated with exosomes (30 µg/well) and the other left untreated for 18hr at 37°C. After incubation, ~ 20,000 cells from each condition were loaded into HIVE CLX collectors per manufacturer’s instructions (Honeycomb Bio) and stored at -80°C until processing. scRNA-seq was performed via the HIVE CLX system from Honeycomb Bio. Briefly, PBMCs were resuspended in phosphate-buffered saline (PBS) with 1% Bovine Serum Albumin, followed by cell counting using Countess 3 automated cell counter (Invitrogen). Two batches of 125,000 cells each were seeded into a round bottom 96 well plate. The first batch was treated with 30 µg of exosomes, while no treatment was administered to the second batch. This was followed by 18 hours of incubation at 37 ºC. After the incubation step, 20,000 cells from both batches were loaded into HIVE collectors following the manufacturer’s instructions (Honeycomb Bio). The HIVE collectors, containing the loaded cells, were stored at -80 ºC until scRNAseq analysis. Sequencing Data analysis and Ingenuity Pathway (IPA) network design We processed the raw single-cell RNA sequencing data obtained from Honeycomb hives and analyzed it using the Seurat v4.0 R package. To make sure the data was clean, we removed cells that had fewer than 100 genes detected, less than 10% mitochondrial content, less than 45% ribosomal gene content, or less then 20% hemoglobin gene content. Post quality control, we normalized the gene expression matrices and used principal component analysis (PCA) for dimensionality reduction. Finally, we applied Uniform Manifold Approximation and Projection (UMAP) to visualize how the cells clustered. We annotated different cell types using canonical marker genes and monocyte clusters were selected for a further comparative analysis between HAM/TSP patients and asymptomatic carriers. For differential gene expression analysis, we used the Wilcoxon rank-sum test, which helped us identify genes that were significantly upregulated and downregulated, setting our limits at a false discovery rate (FDR) of less than 0.05 and an absolute log2 fold change greater than 1. To understand the biological importance of differentially expressed genes, we used Ingenuity Pathway Analysis (IPA, Qiagen). We put the DEGs into the IPA system to identify important signaling pathways, key regulators, and functional networks. The analysis especially focused on immune-modulatory pathways relevant to monocyte activation and neuroinflammation. Quantitative Real-time PCR Total RNA was extracted from PBMCs with the RNeasy Mini Kit (Qiagen). The isolated RNA was then kept at -20°C to further quantify and analyze it using RT-PCR. RNA was converted into cDNA following the protocol from the QuantiTect Reverse Transcription Kit (Qiagen). qPCR primers were found in existing literature or were made using the NCBI Blast database and the online Primer3Plus software. The primer sequences are listed in Table 4, and they were synthesized by Integrated DNA Technologies. For RT-PCR, the QuantStudio 6 Flex Real-Time PCR System (Applied Biosystems) was used with Maxima SYBR Green qPCR Master Mix (ThermoFisher Scientific). The thermal cycling protocol included an initial activation step at 95°C for 10 minutes, then 40 cycles for denaturation at 95°C for 15 seconds and annealing/extension at 60°C for 1 minute. The PCR setup included a melt curve analysis right after the thermal cycling steps to ensure there were no unwanted primer-dimers or non-specific amplifications. To measure the fold changes in gene expression in PBMCs, the 2 − ΔΔCT method was used and compared the results to the housekeeping gene GAPDH. RESULTS Quality Control of Single-Cell RNA Sequencing Data. To ensure high-quality single-cell transcriptomic analysis, standard quality control filtering was applied to the dataset. All selected cells had 100 genes. In addition, cells with greater than 10% mitochondrial gene content were removed to exclude dying or stressed cells. Further, we filtered out cells with greater than 45% ribosomal gene content and more than 20% hemoglobin gene expression to eliminate potential background noise. These thresholds ensured that downstream analysis was based on viable, high-integrity single cells (Supplemental Fig. 1). The entire data set has been deposited in the NCBI library with the accession number GSE308157. Clustering Reveals Major Immune Cell Populations in HTLV-1-Infected PBMCs. After quality control study, we carried out dimensionality reduction and clustering to visualize and categorize transcriptionally distinct immune cells in the PBMC samples. Using Uniform Manifold Approximation and Projection (UMAP), we observed clear clustering of the major immune cell types across different conditions (Supplemental Fig. 1). Important subsets like monocytes, T cells, B cells, and NK cells were clearly distinguished. These clusters were annotated based on canonical marker gene expression, which helped us with further comparison between individuals infected with HTLV-1, HTLV-2, and those who were asymptomatic. Differential Gene Expression in Monocytes Highlights Inflammatory Shifts in HAM/TSP. To investigate transcriptional changes associated with disease manifestation, we performed differential gene expression analysis between HAM/TSP patients and ACs (Fig. 1 ). The volcano plot shows a clear picture of some genes that are either significantly upregulated or downregulated in HAM/TSP, pointing to notable changes connected to inflammation and immune responses (Fig. 1 ). These differentially expressed genes became the starting point for further exploration of pathways and functions to realize the biological effects in monocytes due to HTLV-1. Key Upregulated and Downregulated Genes in Monocytes from HAM/TSP Patients . Tables 1 and 2 present the top differentially expressed genes in monocytes from HAM/TSP patients compared to ACs, ranked by statistical significance and log₂ fold change. Notably, TGFBI (log₂FC = 3.0), CCL2 (log₂FC = 2.8), and HLA-DRA (log₂FC = 2.5) emerged as some of the most highly upregulated genes in HAM/TSP monocytes (Table 1). These genes are involved in tissue remodeling, chemotaxis, and antigen presentation respectively, and their upregulation reflects an inflammatory microenvironment and active immune cell recruitment in HAM/TSP. In contrast, the most significantly downregulated genes included THBS1 (log₂FC = − 4.6), SERPINB2 (log₂FC = − 4.3), and IL1B (log₂FC = − 4.3) (Table 2). THBS1, a multifunctional glycoprotein involved in immune regulation and matrix interactions, and SERPINB2, an inhibitor of fibrinolysis, both showed sharp downregulation, pointing toward impaired resolution of inflammation. Interestingly, the downregulation of IL1B, a typically pro-inflammatory cytokine, may indicate compensatory or subset-specific expression differences in monocyte populations. Overall, these patterns suggest substantial transcriptional reprogramming in monocytes of HAM/TSP patients, skewed toward a chronic inflammatory and dysregulated immune response. IPA Network Analysis Identifies Key Inflammatory Genes Driving HAM/TSP Pathogenesis. IPA analysis of differentially expressed genes in HAM/TSP monocytes highlighted a range of inflammation-related signaling pathways, including Macrophage Classical Activation, IL-10 Signaling, Pathogen-Induced Cytokine Storm Signaling, Granulocyte Adhesion and Diapedesis, and the Multiple Sclerosis Pathway (Fig. 2 ). Among the genes driving these networks, several were both significantly differentially expressed (Tables 1 & 2) and prominently highlighted in the IPA visualization. Upregulated genes such as STAT1 and CCL2 (marked in red) mapped across multiple inflammatory networks. STAT1, a key transcription factor in interferon signaling, may contribute to the heightened immune activation seen in HAM/TSP. CCL2, a potent chemokine involved in monocyte recruitment, was linked to the Cytokine Storm and Granulocyte Adhesion pathways, supporting its central role in leukocyte trafficking and sustained inflammation. Conversely, IL1B, CXCL1, CXCL8, and IL-1 (marked in green) were among the most downregulated genes and were connected to pathways like IL-10 Signaling and Pathogen-Induced Cytokine Storm. These cytokines typically mediate acute inflammatory responses, and their suppression may suggest a dysfunctional or desensitized inflammatory axis in chronic disease settings like HAM/TSP. Monocyte DEGs and Associated Enriched GO Terms. Figure 3 A illustrates the top DEGs in monocytes from HAM/TSP patients compared to ACs, based on log₂ fold change values. Genes such as HLA-DRA, S100A8, and IFI30 were among the most upregulated in HAM/TSP monocytes, indicating enhanced antigen presentation and interferon-stimulated responses. In contrast, several pro-inflammatory and chemotactic genes, including THBS1 (log₂FC ~ 3.3), CXCL1, IL1B, and EREG, were significantly downregulated, suggesting complex regulation of cytokine signaling and tissue remodeling in HAM/TSP pathogenesis. Figure 3 B highlights enriched Gene Ontology (GO) biological processes associated with these DEGs. Notably, upregulated genes were enriched for MHC class II receptor activity, myeloid dendritic cell antigen presentation, and cytokine activity, pointing toward heightened immune surveillance and T-cell activation potential in monocytes. Downregulated genes were enriched in processes like response to external stimulus, extracellular vesicle activity, and cell surface signaling, reflecting possible dysregulation of monocyte-environment interactions in disease progression. Validation of Differential Gene Expression in Monocytes from HAM/TSP Patients. To validate transcriptomic changes identified via scRNAseq, qPCR was performed for selected upregulated and downregulated genes in monocytes from HTLV-1-infected individuals at baseline and after 96 weeks post-treatment (wpt) with DTG. As shown in Fig. 4 A, HTLV-1 proviral load (PVL) decreased in both AC and HAM/TSP patients at 96 wpt, with a more substantial reduction observed in the AC group. Figure 4 B presents qPCR-based expression profiles for genes found to be differentially expressed in the scRNA-seq analysis. At baseline, genes such as PTMA, S100A8, IFI30, FUCA1, and HLA-DRA were significantly upregulated in HAM/TSP compared to ACs, while IL1B, THBS1, CXCL1, CCL3 and others were markedly downregulated. At 96 wpt, these expression differences were either reduced or not statistically significant in most genes, suggesting a dampening of dysregulation following treatment. In Fig. 4 C, heatmaps visualize these fold-change trends in gene expression. Upregulated genes (green scale) such as PTMA, S100A8, IFI30, and HLA-DRA remained more highly expressed at baseline in HAM/TSP compared to ACs, but their levels tended to decline at 96 wpt. Similarly, several downregulated genes (blue scale), particularly IL1B, CXCL1, and CCL3, displayed notably lower expression in HAM/TSP patients at baseline, reinforcing the inflammatory and immunomodulatory differences observed between the groups. The expression shifts observed in qPCR broadly support the directionality of the single-cell RNAseq findings, strengthening the significance of monocyte-associated transcriptional alterations in HAM/TSP. Discussion We identify a monocyte-centric transcriptional program associated with HAM/TSP, complementing the prevailing T-cell focused paradigm of HTLV-1 immunopathogenesis [ 8 ]. Using a single-cell discovery set (one AC vs one HAM/TSP subject) and cohort-level validation, we show that peripheral monocytes from HAM/TSP exhibit coordinated remodeling of interferon-responsive, antigen-presentation, and trafficking modules, nominating myeloid pathways as contributors, not merely bystanders, to the chronic neuroinflammatory cascade. Our study offers comprehensive single-cell transcriptional profiling of monocytes in HAM/TSP patients, highlighting a previously underexplored role for these myeloid cells in HTLV-1 immunopathogenesis. Traditionally, HAM/TSP research has focused on CD4⁺ and CD8⁺ T cells as primary mediators of neuroinflammation and tissue damage [ 20 ]. However, proteomic and functional studies have documented altered adhesion, migration, and cytoskeletal profiles in monocytes from HAM/TSP patients, suggesting enhanced endothelial transmigration and inflammatory potential [ 21 ]. Our single-cell data confirms and extend this evidence, revealing significant dysregulation of genes associated with monocyte activation, cytokine signaling, and immune regulation. These findings suggest that monocytes may play a direct and active role in disease progression-beyond passive involvement in the chronic neuroinflammatory cascade of HAM/TSP. Our data revealed significant transcriptional shifts in HAM/TSP monocytes, notably the upregulation of STAT1 and CCL2, and downregulation of IL-1b, CXCL1, and CXCL8. STAT1 upregulation aligns with its recognized role in promoting M1-like macrophage polarization and IFN-γ signaling phenomena previously observed in neuroinflammatory disorders (e.g., multiple sclerosis) [ 22 ]. The elevated expression of CCL2, a potent monocyte chemoattractant implicated in monocyte trafficking across the blood-brain barrier and in CNS inflammation, suggests enhanced monocyte homing in HAM/TSP. Conversely, the reduced levels of IL-1b, CXCL1, and CXCL8, the key mediators of acute inflammatory responses-may indicate a skewing towards a chronic or dysfunctional immune phenotype (as seen in other chronic viral infections) [ 8 ]. In parallel with upregulated proinflammatory signatures, we observed a marked downregulation of several key genes involved in immune homeostasis and resolution of inflammation, including IL1B, THBS1, CXCL1, and CXCL8. While IL-1β is classically known as a pro-inflammatory cytokine, its chronic suppression particularly in the context of an activated monocyte population-can indicate a disrupted temporal orchestration of inflammation, where resolution-phase mediators are aberrantly silenced, thereby contributing to immune dysregulation [ 23 ]. THBS1 is a matricellular protein with potent anti-angiogenic and immunomodulatory roles. It has been shown to negatively regulate T cell activation and promote TGF-β signaling. The loss of THBS1 expression in HAM monocytes could relieve this immunosuppressive brake, potentially enhancing inflammatory responses in peripheral and CNS compartments. Likewise, the reduced expression of chemokines such as CXCL1 and CXCL8 (IL-8) both involved in neutrophil recruitment and tissue remodeling might impair the recruitment of regulatory granulocytes and limit the resolution of inflammation, fostering a state of chronic immune activation [ 24 ]. Collectively, these transcriptional changes suggest that HAM/TSP monocytes are not only hyperactivated but are also impaired in mounting a regulatory or wound-healing response, creating a skewed inflammatory environment. Such dysfunction could synergize with T cell-mediated neurotoxicity, perpetuating CNS damage in HAM/TSP patients [ 25 ] . Ingenuity Pathway Analysis (IPA) of the differentially expressed genes revealed strong enrichment for canonical pathways related to innate immune dysregulation, including Macrophage Classical Activation, IL-10 Signaling, Pathogen-Induced Cytokine Storm, Multiple Sclerosis Pathway, and Granulocyte Adhesion and Diapedesis. The activation of classical macrophage polarization pathways supports the notion that monocytes in HAM/TSP patients are skewed towards an M1-like phenotype characterized by heightened antigen presentation and proinflammatory cytokine production [ 26 ]. Strikingly, IL-10 signaling, a pathway known to temper inflammation and promote regulatory macrophage functions, was concurrently highlighted, likely reflecting a compensatory anti-inflammatory response. However, in chronic neuroinflammatory diseases, IL-10 responses often become dysregulated or insufficient to fully counterbalance persistent immune activation. This paradox underscores the complexity of monocyte responses in HAM/TSP, where both inflammatory and counter-regulatory signals coexist [ 26 , 27 ]. Further, the presence of Pathogen-Induced Cytokine Storm and Granulocyte Adhesion and Diapedesis pathways suggest potential parallels between HAM/TSP and hyperinflammatory responses seen in acute viral infections and autoimmune conditions. Enhanced expression of adhesion molecules and chemokines, such as CCL2 and CXCL8, may drive excessive leukocyte infiltration into CNS tissue, exacerbating tissue damage a mechanism similarly implicated in Multiple Sclerosis, another demyelinating neuroinflammatory disorder [ 28 , 29 ]. Declarations Conflict of Interest: Authors declare no conflict of interest related to this manuscript Author contributions SG wrote manuscript and SA performed IPA analysis and generated signaling pathway networks under the supervision of PJ. FD extracted RNA from patient PBMCs and performed PCRs. CB made contributions by overseeing the clinical study and patient outcomes. AL performed primary data analysis on the data and deposited meta files into the repository. RT has performed secondary data analysis and produced tables of significant gene changes. PT and RA have assisted in the single cell sequencing experimentation and gene expression analysis on the validation data. BBH contributed to the execution of experiments, facilitated validation studies, data analysis, and editing of the manuscript draft. PJ conceptualized the study, designed experiments, ensured proper execution, provided intellectual insights to the data analysis, and finalized data flow/presentation for submission. References Yoshida, M., et al., Monoclonal integration of human T-cell leukemia provirus in all primary tumors of adult T-cell leukemia suggests causative role of human T-cell leukemia virus in the disease . Proc Natl Acad Sci U S A, 1984. 81(8): p. 2534–7. Nakamura, T., HAM/TSP Pathogenesis: The Transmigration Activity of HTLV-1-Infected T Cells into Tissues . Pathogens, 2023. 12(3). Youssefi, M., et al., What is the role of the thioredoxin antioxidant complex in relation to HAM/TSP? Access Microbiol, 2020. 2(3): p. acmi000090. Gois, L.L., et al., Imbalanced IL10/TGF-beta production by regulatory T-lymphocytes in patients with HTLV-1-associated myelopathy/ tropical spastic paraparesis . BMC Infect Dis, 2024. 24(1): p. 652. Mozhgani, S.H., et al., Interferon Lambda Family along with HTLV-1 Proviral Load, Tax, and HBZ Implicated in the Pathogenesis of Myelopathy/Tropical Spastic Paraparesis . Neurodegener Dis, 2018. 18(2–3): p. 150–155. Jones, K.S., et al., Cell-free HTLV-1 infects dendritic cells leading to transmission and transformation of CD4(+) T cells . Nat Med, 2008. 14(4): p. 429–36. Wakamatsu, S., et al., Monocyte-driven activation-induced apoptotic cell death of human T-lymphotropic virus type I-infected T cells . J Immunol, 1999. 163(7): p. 3914–9. Amorim, C.F., et al., Functional activity of monocytes and macrophages in HTLV-1 infected subjects . PLoS Negl Trop Dis, 2014. 8(12): p. e3399. de Castro-Amarante, M.F., et al., Human T Cell Leukemia Virus Type 1 Infection of the Three Monocyte Subsets Contributes to Viral Burden in Humans . J Virol, 2015. 90(5): p. 2195–207. Futsch, N., R. Mahieux, and H. Dutartre, HTLV-1, the Other Pathogenic Yet Neglected Human Retrovirus: From Transmission to Therapeutic Treatment . Viruses, 2017. 10(1). Tardiota, N., et al., HTLV-1 reverse transcriptase homology model provides structural basis for sensitivity to existing nucleoside/nucleotide reverse transcriptase inhibitors . Virol J, 2024. 21(1): p. 14. Bohiltea, R.E., et al., Implications of human T-lymphotropic virus in pregnancy: A case report and a review of the diagnostic criteria and management proposal . Exp Ther Med, 2021. 21(1): p. 82. Avallone, G., et al., Case Report: Atypical Cutaneous Presentation of Human T-cell Lymphotropic Virus Type 1-Related Adult T-cell Lymphoma . Am J Trop Med Hyg, 2021. 105(6): p. 1590–1593. Ye, L., G.P. Taylor, and C. Rosadas, Human T-Cell Lymphotropic Virus Type 1 and Strongyloides stercoralis Co-infection: A Systematic Review and Meta-Analysis . Front Med (Lausanne), 2022. 9: p. 832430. Fuggetta, M.P., et al., Downregulation of proinflammatory cytokines in HTLV-1-infected T cells by Resveratrol . J Exp Clin Cancer Res, 2016. 35(1): p. 118. Satou, Y. and M. Matsuoka, HTLV-1 and the host immune system: how the virus disrupts immune regulation, leading to HTLV-1 associated diseases . J Clin Exp Hematop, 2010. 50(1): p. 1–8. Hoffman, P.M., et al., Human T-cell leukemia virus type I infection of monocytes and microglial cells in primary human cultures . Proc Natl Acad Sci U S A, 1992. 89(24): p. 11784–8. Murphy, E.L., et al., HTLV-associated myelopathy in a cohort of HTLV-I and HTLV-II-infected blood donors. The REDS investigators . Neurology, 1997. 48(2): p. 315–20. Bartman, M.T., et al., Long-term increases in lymphocytes and platelets in human T-lymphotropic virus type II infection . Blood, 2008. 112(10): p. 3995–4002. Nozuma, S., R. Kubota, and S. Jacobson, Human T-lymphotropic virus type 1 (HTLV-1) and cellular immune response in HTLV-1-associated myelopathy/tropical spastic paraparesis . J Neurovirol, 2020. 26(5): p. 652–663. Echevarria-Lima, J., et al., Protein Profile of Blood Monocytes is Altered in HTLV-1 Infected Patients: Implications for HAM/TSP Disease . Sci Rep, 2018. 8(1): p. 14354. Christophi, G.P., et al., Macrophages of multiple sclerosis patients display deficient SHP-1 expression and enhanced inflammatory phenotype . Lab Invest, 2009. 89(7): p. 742–59. Italiani, P., et al., Profiling the Course of Resolving vs. Persistent Inflammation in Human Monocytes: The Role of IL-1 Family Molecules . Front Immunol, 2020. 11: p. 1426. Lopez-Dee, Z., K. Pidcock, and L.S. Gutierrez, Thrombospondin-1: multiple paths to inflammation . Mediators Inflamm, 2011. 2011: p. 296069. Filep, J.G., Targeting Neutrophils for Promoting the Resolution of Inflammation . Front Immunol, 2022. 13: p. 866747. Murray, P.J. and T.A. Wynn, Protective and pathogenic functions of macrophage subsets . Nat Rev Immunol, 2011. 11(11): p. 723–37. Ivashkiv, L.B., IFNgamma: signalling, epigenetics and roles in immunity, metabolism, disease and cancer immunotherapy . Nat Rev Immunol, 2018. 18(9): p. 545–558. Merad, M. and J.C. Martin, Pathological inflammation in patients with COVID-19: a key role for monocytes and macrophages . Nat Rev Immunol, 2020. 20(6): p. 355–362. Chousterman, B.G., F.K. Swirski, and G.F. Weber, Cytokine storm and sepsis disease pathogenesis . Semin Immunopathol, 2017. 39(5): p. 517–528. Tables Tables 1 to 4 are available in the Supplementary Files section. Additional Declarations There is NO conflict of interest to disclose. There is no Conflict of Interest Supplementary Files Table1.tif Table 1 Table1contd.tif Table 1 contd. Table2.tif Table 2 Table2contd.tif Table 2 contd. Table3.tif Table 3 Table4.tif Table 4 SupplementFigure1.tif Supplement Figure 1. Quality control and cell type annotation of single-cell transcriptomic data.(Top panels) Violin plots showing quality control (QC) metrics before (left) and after (right) filtering of single cells from HAM/TSP and AC samples. Cells were retained if they expressed 100 genes (to eliminate empty droplets), <10% mitochondrial gene content (to exclude dying cells), and <45% ribosomal or <20% hemoglobin content (to minimize noise). (Bottom left) UMAP projection showing clustering of major immune cell types identified using canonical marker expression and SingleR-based annotation aligned with the Human Cell Atlas. (Bottom middle) Violin plots showing canonical marker gene expression used to assign immune cell identities to the clusters. (Bottom right) Stacked bar plot indicating the proportion of each immune cell type across HAM/TSP and AC samples, revealing compositional differences in PBMC subsets. Cite Share Download PDF Status: Under Review Version 1 posted Review # 4 received at journal 10 Apr, 2026 Reviewer # 4 agreed at journal 30 Mar, 2026 Reviewer # 3 agreed at journal 05 Jan, 2026 Reviewer # 2 agreed at journal 24 Oct, 2025 Review # 1 received at journal 18 Oct, 2025 Reviewer # 1 agreed at journal 17 Oct, 2025 Reviewers invited by journal 17 Oct, 2025 Submission checks completed at journal 07 Oct, 2025 First submitted to journal 07 Oct, 2025 Unknown event 29 Sep, 2025 Editor assigned by journal 26 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7724833","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":531319303,"identity":"8cd9b5ab-357c-42ea-8358-edab8f7b8e34","order_by":0,"name":"Pooja 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06:51:24","extension":"html","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":94381,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/0053e4666dcf9e0714503c35.html"},{"id":94806623,"identity":"f3faca5c-5b86-4242-aa7c-f8a8b53652ad","added_by":"auto","created_at":"2025-10-31 01:39:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":201786,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential gene expression across immune cell types in HAM/TSP vs asymptomatic carriers (ACs).\u003c/strong\u003e Volcano plots displaying differentially expressed genes (DEGs) in monocytes, CD8 T cells, B cells, naïve CD4 T cells, and memory CD4 T cells between HAM/TSP patients and ACs. The x-axis represents log₂ fold change, and the y-axis represents –log₁₀ adjusted p-value. Red dots indicate genes significantly differentially expressed by both statistical significance and fold change (padj \u0026lt; 0.05 and |log₂FC| \u0026gt; 1). Blue dots represent genes significant by adjusted p-value only, and green dots indicate genes with significant fold change only. Monocytes showed the highest number of significantly altered genes, whereas minimal transcriptional changes were observed in other immune subsets. A total of 17,883 genes were analyzed per cell type.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/d0a9b8d422e0e924f5dee903.png"},{"id":94806611,"identity":"ad734b07-6383-4de0-859f-84c3536ed41b","added_by":"auto","created_at":"2025-10-31 01:39:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":453256,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIngenuity Pathway Analysis (IPA) of differentially expressed genes (DEGs) in monocytes from HAM/TSP vs asymptomatic carriers (AC).\u003c/strong\u003e Canonical pathway enrichment identified multiple immune-related pathways activated or suppressed in HAM/TSP monocytes compared to ACs. (A) The Macrophage Classical Activation Signaling Pathway showed increased activation of pro-inflammatory nodes, including STAT1 and TNF-related signaling molecules, and upregulation of CCL2 and CD40, suggesting skewing toward an M1-like phenotype. (B) The IL-10 Signaling Pathway was predominantly inhibited, as reflected by suppressed STAT3 activity and downregulation of IL1β and CXCL8, indicating impaired anti-inflammatory signaling.\u003c/p\u003e\n\u003cp\u003e(C \u0026amp; D) The Multiple Sclerosis Signaling Pathway and Granulocyte Adhesion and Diapedesis Pathway highlighted involvement of shared inflammatory and neuroimmune mechanisms, with downregulation of adhesion molecules and chemokines like CXCL8 and IL1β. (E) The Pathogen-Induced Cytokine Storm Signaling Pathway showed mixed regulation, including upregulation of STAT1 and CCL2, and suppression of IL-1, CXCL1, and CXCL8, pointing to dysregulated inflammatory responses potentially contributing to HTLV-1-associated neuroinflammation. Color intensity and arrows represent predicted activation or inhibition based on directionality of gene expression. Nodes highlighted in bright red or green reflect significant up- or downregulation in the dataset.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/4ffb7c565d015ed6c9dd4a0a.png"},{"id":94806603,"identity":"3951b156-c932-47a6-8cbc-980d288f7ce5","added_by":"auto","created_at":"2025-10-31 01:39:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":209965,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential gene expression and GO enrichment analysis of monocytes in HAM/TSP.\u003c/strong\u003e (A) Top: Volcano plot showing differentially expressed genes (DEGs) in monocytes from HAM/TSP patients compared to asymptomatic carriers (ACs). Genes meeting significance thresholds for both adjusted p-value and log₂ fold change are highlighted in red. Notable upregulated genes include IFI30, PTMA, and HLA-DRA, while strongly downregulated genes include THBS1, CXCL1, and IL1B. Bottom: Bar plot showing top 10 significantly upregulated (green) and downregulated (blue) DEGs ranked by log₂ fold change. (B) Gene Ontology (GO) enrichment analysis of DEGs revealed overrepresentation of immune-related processes, including MHC class II receptor activity, cytokine activity, and signaling receptor binding, along with processes involving cell surface and vesicle localization. Gene ratio represents the proportion of DEGs mapped to each GO term.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/9932761f4803f845fe3410ab.png"},{"id":94806677,"identity":"91b86f5b-6818-4dd3-95cc-f1e1b93a4be4","added_by":"auto","created_at":"2025-10-31 01:39:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":165889,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eValidation of monocyte gene signatures in longitudinal samples using qPCR.\u003c/strong\u003e (A) Proviral load (PVL) measurements (HTLV-1 DNA copies/mm³) in asymptomatic carriers (AC) and HAM/TSP patients at baseline and after 96 weeks post-treatment (wpt). Both groups show a decline in PVL, with individual trajectories plotted. (B) qPCR validation of selected monocyte DEGs at baseline and 96 wpt. Genes upregulated in HAM/TSP patients (top panels) include PTMA, S100A8, IFI30, FUCA1, and HLA-DRA; genes downregulated (bottom panels) include IL1B, THBS1, CXCL1, EREG, CXCL5, AKR1C1, TGB8, SLC25A37, and CXCL8. Asterisks indicate statistically significant differences (p\u0026lt;0.05). (C) Heatmaps showing expression intensities of validated upregulated (top) and downregulated (bottom) genes across groups and timepoints. HAM/TSP samples show consistent upregulation of genes like S100A8 and IFI30 at baseline, which decline at 96 wpt, whereas downregulated genes show opposite trends.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/c4abf0b5a67745568e847be5.png"},{"id":94827309,"identity":"ae1f449c-2675-4173-adfb-2936716191c1","added_by":"auto","created_at":"2025-10-31 06:57:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1665051,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/8d4ba345-11c4-4867-bf55-f9caeee29b9f.pdf"},{"id":94806630,"identity":"0d437481-e6d3-4a4f-b900-fe1af52caab5","added_by":"auto","created_at":"2025-10-31 01:39:41","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2249934,"visible":true,"origin":"","legend":"Table 1","description":"","filename":"Table1.tif","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/e50e3fb035193811604eac44.tif"},{"id":94806613,"identity":"6473959e-c656-481a-89e4-8b4f30683381","added_by":"auto","created_at":"2025-10-31 01:39:40","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2249934,"visible":true,"origin":"","legend":"\u003cp\u003eTable 1 contd.\u003c/p\u003e","description":"","filename":"Table1contd.tif","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/134be9f4f32929e15ecf6e99.tif"},{"id":94806584,"identity":"15dc7fc9-0a55-4fd5-823b-6646f10bcdd1","added_by":"auto","created_at":"2025-10-31 01:39:33","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":2249934,"visible":true,"origin":"","legend":"Table 2","description":"","filename":"Table2.tif","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/8790ad9badc86fe140840a09.tif"},{"id":94806646,"identity":"e2cffe7f-ec8b-4a0f-aea9-45c0ed90e6c7","added_by":"auto","created_at":"2025-10-31 01:39:42","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2249934,"visible":true,"origin":"","legend":"Table 2 contd.","description":"","filename":"Table2contd.tif","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/e1a98d33762bc795955feb66.tif"},{"id":94806605,"identity":"a5ee8e96-a118-462a-afef-9b4c41321e4d","added_by":"auto","created_at":"2025-10-31 01:39:38","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":2249934,"visible":true,"origin":"","legend":"\u003cp\u003eTable 3\u003c/p\u003e","description":"","filename":"Table3.tif","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/140e25e80948c202af5c6c03.tif"},{"id":94806631,"identity":"9d572ead-7b26-4f9e-aefc-9c2dd086f8be","added_by":"auto","created_at":"2025-10-31 01:39:41","extension":"tif","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":2249934,"visible":true,"origin":"","legend":"Table 4","description":"","filename":"Table4.tif","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/7cee99a36e4bac24495f1d2d.tif"},{"id":94806687,"identity":"a32c58b9-f16b-47be-aed1-fb7240aae346","added_by":"auto","created_at":"2025-10-31 01:39:45","extension":"tif","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":2249934,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplement Figure 1. Quality control and cell type annotation of single-cell transcriptomic data.\u003c/strong\u003e(Top panels) Violin plots showing quality control (QC) metrics before (left) and after (right) filtering of single cells from HAM/TSP and AC samples. Cells were retained if they expressed \u0026lt;4500 genes (to remove multiples), \u0026gt;100 genes (to eliminate empty droplets), \u0026lt;10% mitochondrial gene content (to exclude dying cells), and \u0026lt;45% ribosomal or \u0026lt;20% hemoglobin content (to minimize noise). (Bottom left) UMAP projection showing clustering of major immune cell types identified using canonical marker expression and SingleR-based annotation aligned with the Human Cell Atlas. (Bottom middle) Violin plots showing canonical marker gene expression used to assign immune cell identities to the clusters. (Bottom right) Stacked bar plot indicating the proportion of each immune cell type across HAM/TSP and AC samples, revealing compositional differences in PBMC subsets.\u003c/p\u003e","description":"","filename":"SupplementFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-7724833/v1/03c8946d97d2499054587c1b.tif"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.\nThere is no Conflict of Interest","formattedTitle":"Transcriptional reprogramming in immune cells of HTLV-1 asymptomatic carriers and HAM/TSP patients following antiretroviral therapy","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eHuman T-cell lymphotropic virus type 1 (HTLV-1) is an oncogenic delta retrovirus that causes ໿adult T-cell leukemia/lymphoma (ATL) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP), a chronic, progressive inflammatory myelopathy of the spinal cord. Although an estimated 5\u0026ndash;20\u0026nbsp;million people are infected worldwide, ~\u0026thinsp;90% remain asymptomatic carriers (ACs); in symptomatic individuals, HAM/TSP manifests with gait disturbance, lower-extremity weakness, spasticity, low-back pain, urinary dysfunction, and sexual dysfunction, often with stepwise or insidious progression [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHAM/TSP pathogenesis is characterized by high peripheral proviral load (PVL) and persistent immune activation. HTLV-1-infected CD4\u0026thinsp;+\u0026thinsp;T cells are expanded in the blood and traffic to the central nervous system (CNS), where they are thought to amplify neuroinflammation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Patients exhibit elevated pro-inflammatory cytokines (e.g., IFN-γ, IL-6, and TNF-α) and robust Tax-specific Th1/CTL responses that correlate with disease severity, suggesting that peripheral immune dysregulation fuels spinal cord pathology [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Identifying the immune elements that contribute to HAM/TSP remains a major gap in our understanding of HTLV-1 pathogenesis. To address this, we applied Ingenuity Pathway Analysis (IPA) to single-cell transcriptomic data, revealing immune signaling networks including IL-10 signaling, classical macrophage activation, cytokine storm, and multiple sclerosis-related pathways that may shape the pathogenesis of HAM/TSP.\u003c/p\u003e\u003cp\u003eDespite this T-cell centric framework, myeloid cells particularly monocytes, remain underexplored in HTLV-1 disease. Monocytes orchestrate antigen presentation, cytokine/chemokine production, and leukocyte trafficking across the blood\u0026ndash;spinal cord barrier (BSCB). Prior reports in HTLV-1 infection describe increased PBMC expression of CXCL9/CXCL10/TNF, shifts in monocyte subsets (reduced classical CD14⁺⁺CD16⁻ with relative expansion of intermediate/nonclassical CD16⁺ populations), and monocyte-dependent modulation of T-cell activation and apoptosis, implicating peripheral myeloid programs in HAM/TSP pathogenesis [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Defining monocyte-intrinsic transcriptional states in HAM/TSP could therefore yield accessible biomarkers and therapeutic entry points.\u003c/p\u003e\u003cp\u003eTherapeutic options for HAM/TSP remain limited. Corticosteroids and interferon-α can transiently attenuate inflammation in some patients, but durable disease-modifying effects are uncommon. Antiretrovirals have shown mixed results; zidovudine (AZT) and other reverse-transcriptase inhibitors have been evaluated primarily in ATL, with uncertain benefit in HAM/TSP [\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Given that integration is essential for delta retroviral persistence, integrase inhibitors such as dolutegravir (DTG) merit investigation; however, clinical data in HTLV-1 are sparse and mechanistic effects on peripheral immune programs are poorly defined [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Dolutegravir works by inhibiting the integration stage in the viral life cycle, which could, in theory, help reduce the persistence of HTLV-1 infections and their related health issues.\u003c/p\u003e\u003cp\u003eStudies indicate that anti-inflammatory medications, for example, resveratrol, might help downregulate pro-inflammatory cytokines and could be a way to improve immune response in infected patients [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Although antiretroviral therapy has significantly improved conditions of HIV-1 infected patients, such successes have not yet been translated into effective solution for HTLV-1 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The efficacy of these therapeutic approaches has been limited, mainly because we don\u0026rsquo;t have full grasp on how pathogenesis of HTLV-1 works, especially with the role of different immune cells. To better understand this complex immunopathology, we utilized single-cell RNA sequencing (scRNA-seq). This allowed us to closely examine the specific signaling pathways that are more pronounced in patients with HTLV-1 infection [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMonocytes, which exhibit both pro- and anti-inflammatory responses, play a crucial role in immune regulation and the pathogenesis of HTLV-1-associated inflammatory diseases [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. It is speculated that HTLV-1 transmission between monocytes and T cells may occur during antigen presentation and T-cell activation, and infected monocytes play a major role in inducing T-cell apoptosis. Increased expression of proinflammatory mediators such as CXCL9, CXCL10, and TNF was observed in PBMCs isolated from HAM/TSP patients. This hints that monocytes may play a significant role in HTLV-1 pathogenesis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. HTLV-1 infection has been indicated to dramatically change monocyte subsets, resulting in a drop in classical monocytes and a spike in intermediate and non-classical monocytes. These findings lend support to the role of monocytes in HTLV-1 pathogenesis and their survival in humans [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHere, we used single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) from a pair of one AC and one HAM/TSP subject to map cell type\u0026ndash;specific transcriptional differences. Differential expression and pathway analysis localized the most pronounced divergence to the monocyte compartment, highlighting macrophage classical activation, IL-10 counter-regulation, leukocyte adhesion/diapedesis and trans-endothelial migration, and neuroinflammation-linked modules (including multiple-sclerosis\u0026ndash;associated signaling). We then validated a prespecified subset of up- and down-regulated monocyte genes in an independent Brazilian cohort of AC and HAM/TSP participants enrolled in a longitudinal trial of DTG, testing whether these signatures are (i) enriched at baseline in HAM/TSP and (ii) modulated during integrase inhibitor therapy. This discovery-to-validation framework nominates peripheral monocyte programs as candidate biomarkers of disease activity and as potential targets to complement existing markers.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eParticipants and samples\u003c/h2\u003e\u003cp\u003eA discovery pair was drawn from the University of California San Francisco HTLV Outcomes Study (HOST) cohort of HTLV-seropositive blood donors enrolled in 1992\u0026ndash;1994, as previously described [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. One asymptomatic carrier (AC) and one patient with HTLV-1\u0026ndash;associated myelopathy/tropical spastic paraparesis (HAM/TSP) with detectable HTLV-1 at the time of blood donation were selected (Table\u0026nbsp;3). Cryopreserved peripheral blood mononuclear cells (PBMCs) were used for single-cell RNA-seq (scRNA-seq).\u003c/p\u003e\u003cp\u003eFor independent validation, we leveraged an open-label, randomized, controlled, phase 2 trial (PI: C. Brites) in Salvador, Brazil, evaluating dolutegravir (DTG, 50 mg/day) versus vitamin C (500 mg/day) in HTLV-1\u0026ndash;infected adults. The target sample size was 100 participants (n\u0026thinsp;=\u0026thinsp;50 HAM/TSP; n\u0026thinsp;=\u0026thinsp;50 AC). Participants in the vitamin C arm who remained symptomatic after 12 months could cross over to DTG. Interim analyses included 83 participants (DTG n\u0026thinsp;=\u0026thinsp;43, vitamin C n\u0026thinsp;=\u0026thinsp;40) with study visits at baseline, week 24, week 48, and week 96. Clinical assessments included Functional Independence Measure, ASIA Impairment Scale, OSA-ME Motor Disability Scale, Modified Ashworth Scale, and DN4 Pain Questionnaire. Whole blood was collected at each time point for HTLV-1 proviral load (PVL) quantification by real-time PCR and for gene-expression validation in a prespecified subset of DTG-treated participants.\u003c/p\u003e\u003cp\u003e All participants provided written informed consent in accordance with the Declaration of Helsinki and Brazilian National Health Council Resolution 466/12. The clinical validation cohort protocol was approved by the Institutional Review Boards of the Federal University of Bahia and CONEP and registered in ReBEC.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eHoneycomb Single-cell Sequencing and cell handling\u003c/h3\u003e\n\u003cp\u003ePBMCs were thawed, washed, and resuspended in PBS\u0026thinsp;+\u0026thinsp;1% BSA. Cells were counted on a Countess 3 (Thermo Fisher). Two 96-well round-bottom plates were prepared with 1.25 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/well. One plate was incubated with exosomes (30 \u0026micro;g/well) and the other left untreated for 18hr at 37\u0026deg;C. After incubation, ~\u0026thinsp;20,000 cells from each condition were loaded into HIVE CLX collectors per manufacturer\u0026rsquo;s instructions (Honeycomb Bio) and stored at -80\u0026deg;C until processing.\u003c/p\u003e\u003cp\u003escRNA-seq was performed via the HIVE CLX system from Honeycomb Bio. Briefly, PBMCs were resuspended in phosphate-buffered saline (PBS) with 1% Bovine Serum Albumin, followed by cell counting using Countess 3 automated cell counter (Invitrogen). Two batches of 125,000 cells each were seeded into a round bottom 96 well plate. The first batch was treated with 30 \u0026micro;g of exosomes, while no treatment was administered to the second batch. This was followed by 18 hours of incubation at 37 \u0026ordm;C. After the incubation step, 20,000 cells from both batches were loaded into HIVE collectors following the manufacturer\u0026rsquo;s instructions (Honeycomb Bio). The HIVE collectors, containing the loaded cells, were stored at -80 \u0026ordm;C until scRNAseq analysis.\u003c/p\u003e\n\u003ch3\u003eSequencing Data analysis and Ingenuity Pathway (IPA) network design\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWe processed the raw single-cell RNA sequencing data obtained from Honeycomb hives and analyzed it using the Seurat v4.0 R package. To make sure the data was clean, we removed cells that had fewer than 100 genes detected, less than 10% mitochondrial content, less than 45% ribosomal gene content, or less then 20% hemoglobin gene content. Post quality control, we normalized the gene expression matrices and used principal component analysis (PCA) for dimensionality reduction. Finally, we applied Uniform Manifold Approximation and Projection (UMAP) to visualize how the cells clustered. We annotated different cell types using canonical marker genes and monocyte clusters were selected for a further comparative analysis between HAM/TSP patients and asymptomatic carriers. For differential gene expression analysis, we used the Wilcoxon rank-sum test, which helped us identify genes that were significantly upregulated and downregulated, setting our limits at a false discovery rate (FDR) of less than 0.05 and an absolute log2 fold change greater than 1. To understand the biological importance of differentially expressed genes, we used Ingenuity Pathway Analysis (IPA, Qiagen). We put the DEGs into the IPA system to identify important signaling pathways, key regulators, and functional networks. The analysis especially focused on immune-modulatory pathways relevant to monocyte activation and neuroinflammation.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eQuantitative Real-time PCR\u003c/h3\u003e\n\u003cp\u003eTotal RNA was extracted from PBMCs with the RNeasy Mini Kit (Qiagen). The isolated RNA was then kept at -20\u0026deg;C to further quantify and analyze it using RT-PCR. RNA was converted into cDNA following the protocol from the QuantiTect Reverse Transcription Kit (Qiagen). qPCR primers were found in existing literature or were made using the NCBI Blast database and the online Primer3Plus software. The primer sequences are listed in Table\u0026nbsp;4, and they were synthesized by Integrated DNA Technologies. For RT-PCR, the QuantStudio 6 Flex Real-Time PCR System (Applied Biosystems) was used with Maxima SYBR Green qPCR Master Mix (ThermoFisher Scientific). The thermal cycling protocol included an initial activation step at 95\u0026deg;C for 10 minutes, then 40 cycles for denaturation at 95\u0026deg;C for 15 seconds and annealing/extension at 60\u0026deg;C for 1 minute. The PCR setup included a melt curve analysis right after the thermal cycling steps to ensure there were no unwanted primer-dimers or non-specific amplifications. To measure the fold changes in gene expression in PBMCs, the 2\u0026thinsp;\u0026minus;\u0026thinsp;ΔΔCT method was used and compared the results to the housekeeping gene GAPDH.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cb\u003eQuality Control of Single-Cell RNA Sequencing Data.\u003c/b\u003e To ensure high-quality single-cell transcriptomic analysis, standard quality control filtering was applied to the dataset. All selected cells had\u0026thinsp;\u0026lt;\u0026thinsp;4500 genes multiplets (noise) and \u0026gt;\u0026thinsp;100 genes. In addition, cells with greater than 10% mitochondrial gene content were removed to exclude dying or stressed cells. Further, we filtered out cells with greater than 45% ribosomal gene content and more than 20% hemoglobin gene expression to eliminate potential background noise. These thresholds ensured that downstream analysis was based on viable, high-integrity single cells (Supplemental Fig.\u0026nbsp;1). The entire data set has been deposited in the NCBI library with the accession number GSE308157.\u003c/p\u003e\u003cp\u003e\u003cb\u003eClustering Reveals Major Immune Cell Populations in HTLV-1-Infected PBMCs.\u003c/b\u003e After quality control study, we carried out dimensionality reduction and clustering to visualize and categorize transcriptionally distinct immune cells in the PBMC samples. Using Uniform Manifold Approximation and Projection (UMAP), we observed clear clustering of the major immune cell types across different conditions (Supplemental Fig.\u0026nbsp;1). Important subsets like monocytes, T cells, B cells, and NK cells were clearly distinguished. These clusters were annotated based on canonical marker gene expression, which helped us with further comparison between individuals infected with HTLV-1, HTLV-2, and those who were asymptomatic.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDifferential Gene Expression in Monocytes Highlights Inflammatory Shifts in HAM/TSP.\u003c/b\u003e To investigate transcriptional changes associated with disease manifestation, we performed differential gene expression analysis between HAM/TSP patients and ACs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The volcano plot shows a clear picture of some genes that are either significantly upregulated or downregulated in HAM/TSP, pointing to notable changes connected to inflammation and immune responses (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These differentially expressed genes became the starting point for further exploration of pathways and functions to realize the biological effects in monocytes due to HTLV-1.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eKey Upregulated and Downregulated Genes in Monocytes from HAM/TSP Patients\u003c/b\u003e. Tables\u0026nbsp;1 and 2 present the top differentially expressed genes in monocytes from HAM/TSP patients compared to ACs, ranked by statistical significance and log₂ fold change. Notably, TGFBI (log₂FC\u0026thinsp;=\u0026thinsp;3.0), CCL2 (log₂FC\u0026thinsp;=\u0026thinsp;2.8), and HLA-DRA (log₂FC\u0026thinsp;=\u0026thinsp;2.5) emerged as some of the most highly upregulated genes in HAM/TSP monocytes (Table\u0026nbsp;1). These genes are involved in tissue remodeling, chemotaxis, and antigen presentation respectively, and their upregulation reflects an inflammatory microenvironment and active immune cell recruitment in HAM/TSP. In contrast, the most significantly downregulated genes included THBS1 (log₂FC = \u0026minus;\u0026thinsp;4.6), SERPINB2 (log₂FC = \u0026minus;\u0026thinsp;4.3), and IL1B (log₂FC = \u0026minus;\u0026thinsp;4.3) (Table\u0026nbsp;2). THBS1, a multifunctional glycoprotein involved in immune regulation and matrix interactions, and SERPINB2, an inhibitor of fibrinolysis, both showed sharp downregulation, pointing toward impaired resolution of inflammation. Interestingly, the downregulation of IL1B, a typically pro-inflammatory cytokine, may indicate compensatory or subset-specific expression differences in monocyte populations. Overall, these patterns suggest substantial transcriptional reprogramming in monocytes of HAM/TSP patients, skewed toward a chronic inflammatory and dysregulated immune response.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIPA Network Analysis Identifies Key Inflammatory Genes Driving HAM/TSP Pathogenesis.\u003c/b\u003e IPA analysis of differentially expressed genes in HAM/TSP monocytes highlighted a range of inflammation-related signaling pathways, including Macrophage Classical Activation, IL-10 Signaling, Pathogen-Induced Cytokine Storm Signaling, Granulocyte Adhesion and Diapedesis, and the Multiple Sclerosis Pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among the genes driving these networks, several were both significantly differentially expressed (Tables\u0026nbsp;1 \u0026amp; 2) and prominently highlighted in the IPA visualization. Upregulated genes such as STAT1 and CCL2 (marked in red) mapped across multiple inflammatory networks. STAT1, a key transcription factor in interferon signaling, may contribute to the heightened immune activation seen in HAM/TSP. CCL2, a potent chemokine involved in monocyte recruitment, was linked to the Cytokine Storm and Granulocyte Adhesion pathways, supporting its central role in leukocyte trafficking and sustained inflammation. Conversely, IL1B, CXCL1, CXCL8, and IL-1 (marked in green) were among the most downregulated genes and were connected to pathways like IL-10 Signaling and Pathogen-Induced Cytokine Storm. These cytokines typically mediate acute inflammatory responses, and their suppression may suggest a dysfunctional or desensitized inflammatory axis in chronic disease settings like HAM/TSP.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eMonocyte DEGs and Associated Enriched GO Terms.\u003c/b\u003e Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA illustrates the top DEGs in monocytes from HAM/TSP patients compared to ACs, based on log₂ fold change values. Genes such as HLA-DRA, S100A8, and IFI30 were among the most upregulated in HAM/TSP monocytes, indicating enhanced antigen presentation and interferon-stimulated responses. In contrast, several pro-inflammatory and chemotactic genes, including THBS1 (log₂FC\u0026thinsp;~\u0026thinsp;3.3), CXCL1, IL1B, and EREG, were significantly downregulated, suggesting complex regulation of cytokine signaling and tissue remodeling in HAM/TSP pathogenesis. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB highlights enriched Gene Ontology (GO) biological processes associated with these DEGs. Notably, upregulated genes were enriched for MHC class II receptor activity, myeloid dendritic cell antigen presentation, and cytokine activity, pointing toward heightened immune surveillance and T-cell activation potential in monocytes. Downregulated genes were enriched in processes like response to external stimulus, extracellular vesicle activity, and cell surface signaling, reflecting possible dysregulation of monocyte-environment interactions in disease progression.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eValidation of Differential Gene Expression in Monocytes from HAM/TSP Patients.\u003c/b\u003e To validate transcriptomic changes identified via scRNAseq, qPCR was performed for selected upregulated and downregulated genes in monocytes from HTLV-1-infected individuals at baseline and after 96 weeks post-treatment (wpt) with DTG. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, HTLV-1 proviral load (PVL) decreased in both AC and HAM/TSP patients at 96 wpt, with a more substantial reduction observed in the AC group. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB presents qPCR-based expression profiles for genes found to be differentially expressed in the scRNA-seq analysis. At baseline, genes such as PTMA, S100A8, IFI30, FUCA1, and HLA-DRA were significantly upregulated in HAM/TSP compared to ACs, while IL1B, THBS1, CXCL1, CCL3 and others were markedly downregulated. At 96 wpt, these expression differences were either reduced or not statistically significant in most genes, suggesting a dampening of dysregulation following treatment. In Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, heatmaps visualize these fold-change trends in gene expression. Upregulated genes (green scale) such as PTMA, S100A8, IFI30, and HLA-DRA remained more highly expressed at baseline in HAM/TSP compared to ACs, but their levels tended to decline at 96 wpt. Similarly, several downregulated genes (blue scale), particularly IL1B, CXCL1, and CCL3, displayed notably lower expression in HAM/TSP patients at baseline, reinforcing the inflammatory and immunomodulatory differences observed between the groups. The expression shifts observed in qPCR broadly support the directionality of the single-cell RNAseq findings, strengthening the significance of monocyte-associated transcriptional alterations in HAM/TSP.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe identify a monocyte-centric transcriptional program associated with HAM/TSP, complementing the prevailing T-cell focused paradigm of HTLV-1 immunopathogenesis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Using a single-cell discovery set (one AC vs one HAM/TSP subject) and cohort-level validation, we show that peripheral monocytes from HAM/TSP exhibit coordinated remodeling of interferon-responsive, antigen-presentation, and trafficking modules, nominating myeloid pathways as contributors, not merely bystanders, to the chronic neuroinflammatory cascade.\u003c/p\u003e\u003cp\u003eOur study offers comprehensive single-cell transcriptional profiling of monocytes in HAM/TSP patients, highlighting a previously underexplored role for these myeloid cells in HTLV-1 immunopathogenesis. Traditionally, HAM/TSP research has focused on CD4⁺ and CD8⁺ T cells as primary mediators of neuroinflammation and tissue damage [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, proteomic and functional studies have documented altered adhesion, migration, and cytoskeletal profiles in monocytes from HAM/TSP patients, suggesting enhanced endothelial transmigration and inflammatory potential [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Our single-cell data confirms and extend this evidence, revealing significant dysregulation of genes associated with monocyte activation, cytokine signaling, and immune regulation. These findings suggest that monocytes may play a direct and active role in disease progression-beyond passive involvement in the chronic neuroinflammatory cascade of HAM/TSP. Our data revealed significant transcriptional shifts in HAM/TSP monocytes, notably the upregulation of STAT1 and CCL2, and downregulation of IL-1b, CXCL1, and CXCL8. STAT1 upregulation aligns with its recognized role in promoting M1-like macrophage polarization and IFN-γ signaling phenomena previously observed in neuroinflammatory disorders (e.g., multiple sclerosis) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The elevated expression of CCL2, a potent monocyte chemoattractant implicated in monocyte trafficking across the blood-brain barrier and in CNS inflammation, suggests enhanced monocyte homing in HAM/TSP. Conversely, the reduced levels of IL-1b, CXCL1, and CXCL8, the key mediators of acute inflammatory responses-may indicate a skewing towards a chronic or dysfunctional immune phenotype (as seen in other chronic viral infections) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In parallel with upregulated proinflammatory signatures, we observed a marked downregulation of several key genes involved in immune homeostasis and resolution of inflammation, including IL1B, THBS1, CXCL1, and CXCL8. While IL-1β is classically known as a pro-inflammatory cytokine, its chronic suppression particularly in the context of an activated monocyte population-can indicate a disrupted temporal orchestration of inflammation, where resolution-phase mediators are aberrantly silenced, thereby contributing to immune dysregulation [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. THBS1 is a matricellular protein with potent anti-angiogenic and immunomodulatory roles. It has been shown to negatively regulate T cell activation and promote TGF-β signaling. The loss of THBS1 expression in HAM monocytes could relieve this immunosuppressive brake, potentially enhancing inflammatory responses in peripheral and CNS compartments. Likewise, the reduced expression of chemokines such as CXCL1 and CXCL8 (IL-8) both involved in neutrophil recruitment and tissue remodeling might impair the recruitment of regulatory granulocytes and limit the resolution of inflammation, fostering a state of chronic immune activation [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Collectively, these transcriptional changes suggest that HAM/TSP monocytes are not only hyperactivated but are also impaired in mounting a regulatory or wound-healing response, creating a skewed inflammatory environment. Such dysfunction could synergize with T cell-mediated neurotoxicity, perpetuating CNS damage in HAM/TSP patients [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] .\u003c/p\u003e\u003cp\u003eIngenuity Pathway Analysis (IPA) of the differentially expressed genes revealed strong enrichment for canonical pathways related to innate immune dysregulation, including Macrophage Classical Activation, IL-10 Signaling, Pathogen-Induced Cytokine Storm, Multiple Sclerosis Pathway, and Granulocyte Adhesion and Diapedesis. The activation of classical macrophage polarization pathways supports the notion that monocytes in HAM/TSP patients are skewed towards an M1-like phenotype characterized by heightened antigen presentation and proinflammatory cytokine production [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Strikingly, IL-10 signaling, a pathway known to temper inflammation and promote regulatory macrophage functions, was concurrently highlighted, likely reflecting a compensatory anti-inflammatory response. However, in chronic neuroinflammatory diseases, IL-10 responses often become dysregulated or insufficient to fully counterbalance persistent immune activation. This paradox underscores the complexity of monocyte responses in HAM/TSP, where both inflammatory and counter-regulatory signals coexist [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Further, the presence of Pathogen-Induced Cytokine Storm and Granulocyte Adhesion and Diapedesis pathways suggest potential parallels between HAM/TSP and hyperinflammatory responses seen in acute viral infections and autoimmune conditions. Enhanced expression of adhesion molecules and chemokines, such as CCL2 and CXCL8, may drive excessive leukocyte infiltration into CNS tissue, exacerbating tissue damage a mechanism similarly implicated in Multiple Sclerosis, another demyelinating neuroinflammatory disorder [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of Interest:\u003c/h2\u003e\n\u003cp\u003eAuthors declare no conflict of interest related to this manuscript\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003eSG wrote manuscript and SA performed IPA analysis and generated signaling pathway networks under the supervision of PJ. FD extracted RNA from patient PBMCs and performed PCRs. CB made contributions by overseeing the clinical study and patient outcomes. AL performed primary data analysis on the data and deposited meta files into the repository. RT has performed secondary data analysis and produced tables of significant gene changes. PT and RA have assisted in the single cell sequencing experimentation and gene expression analysis on the validation data. BBH contributed to the execution of experiments, facilitated validation studies, data analysis, and editing of the manuscript draft. PJ conceptualized the study, designed experiments, ensured proper execution, provided intellectual insights to the data analysis, and finalized data flow/presentation for submission.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYoshida, M., et al., \u003cem\u003eMonoclonal integration of human T-cell leukemia provirus in all primary tumors of adult T-cell leukemia suggests causative role of human T-cell leukemia virus in the disease\u003c/em\u003e. Proc Natl Acad Sci U S A, 1984. 81(8): p. 2534\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNakamura, T., \u003cem\u003eHAM/TSP Pathogenesis: The Transmigration Activity of HTLV-1-Infected T Cells into Tissues\u003c/em\u003e. Pathogens, 2023. 12(3).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYoussefi, M., et al., \u003cem\u003eWhat is the role of the thioredoxin antioxidant complex in relation to HAM/TSP?\u003c/em\u003e Access Microbiol, 2020. 2(3): p. acmi000090.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGois, L.L., et al., \u003cem\u003eImbalanced IL10/TGF-beta production by regulatory T-lymphocytes in patients with HTLV-1-associated myelopathy/ tropical spastic paraparesis\u003c/em\u003e. BMC Infect Dis, 2024. 24(1): p. 652.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMozhgani, S.H., et al., \u003cem\u003eInterferon Lambda Family along with HTLV-1 Proviral Load, Tax, and HBZ Implicated in the Pathogenesis of Myelopathy/Tropical Spastic Paraparesis\u003c/em\u003e. Neurodegener Dis, 2018. 18(2\u0026ndash;3): p. 150\u0026ndash;155.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJones, K.S., et al., \u003cem\u003eCell-free HTLV-1 infects dendritic cells leading to transmission and transformation of CD4(+) T cells\u003c/em\u003e. Nat Med, 2008. 14(4): p. 429\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWakamatsu, S., et al., \u003cem\u003eMonocyte-driven activation-induced apoptotic cell death of human T-lymphotropic virus type I-infected T cells\u003c/em\u003e. J Immunol, 1999. 163(7): p. 3914\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmorim, C.F., et al., \u003cem\u003eFunctional activity of monocytes and macrophages in HTLV-1 infected subjects\u003c/em\u003e. PLoS Negl Trop Dis, 2014. 8(12): p. e3399.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Castro-Amarante, M.F., et al., \u003cem\u003eHuman T Cell Leukemia Virus Type 1 Infection of the Three Monocyte Subsets Contributes to Viral Burden in Humans\u003c/em\u003e. J Virol, 2015. 90(5): p. 2195\u0026ndash;207.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFutsch, N., R. Mahieux, and H. Dutartre, \u003cem\u003eHTLV-1, the Other Pathogenic Yet Neglected Human Retrovirus: From Transmission to Therapeutic Treatment\u003c/em\u003e. Viruses, 2017. 10(1).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTardiota, N., et al., \u003cem\u003eHTLV-1 reverse transcriptase homology model provides structural basis for sensitivity to existing nucleoside/nucleotide reverse transcriptase inhibitors\u003c/em\u003e. Virol J, 2024. 21(1): p. 14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBohiltea, R.E., et al., \u003cem\u003eImplications of human T-lymphotropic virus in pregnancy: A case report and a review of the diagnostic criteria and management proposal\u003c/em\u003e. Exp Ther Med, 2021. 21(1): p. 82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAvallone, G., et al., \u003cem\u003eCase Report: Atypical Cutaneous Presentation of Human T-cell Lymphotropic Virus Type 1-Related Adult T-cell Lymphoma\u003c/em\u003e. Am J Trop Med Hyg, 2021. 105(6): p. 1590\u0026ndash;1593.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYe, L., G.P. Taylor, and C. Rosadas, \u003cem\u003eHuman T-Cell Lymphotropic Virus Type 1 and Strongyloides stercoralis Co-infection: A Systematic Review and Meta-Analysis\u003c/em\u003e. Front Med (Lausanne), 2022. 9: p. 832430.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFuggetta, M.P., et al., \u003cem\u003eDownregulation of proinflammatory cytokines in HTLV-1-infected T cells by Resveratrol\u003c/em\u003e. J Exp Clin Cancer Res, 2016. 35(1): p. 118.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSatou, Y. and M. Matsuoka, \u003cem\u003eHTLV-1 and the host immune system: how the virus disrupts immune regulation, leading to HTLV-1 associated diseases\u003c/em\u003e. J Clin Exp Hematop, 2010. 50(1): p. 1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHoffman, P.M., et al., \u003cem\u003eHuman T-cell leukemia virus type I infection of monocytes and microglial cells in primary human cultures\u003c/em\u003e. Proc Natl Acad Sci U S A, 1992. 89(24): p. 11784\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMurphy, E.L., et al., \u003cem\u003eHTLV-associated myelopathy in a cohort of HTLV-I and HTLV-II-infected blood donors. The REDS investigators\u003c/em\u003e. Neurology, 1997. 48(2): p. 315\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBartman, M.T., et al., \u003cem\u003eLong-term increases in lymphocytes and platelets in human T-lymphotropic virus type II infection\u003c/em\u003e. Blood, 2008. 112(10): p. 3995\u0026ndash;4002.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNozuma, S., R. Kubota, and S. Jacobson, \u003cem\u003eHuman T-lymphotropic virus type 1 (HTLV-1) and cellular immune response in HTLV-1-associated myelopathy/tropical spastic paraparesis\u003c/em\u003e. J Neurovirol, 2020. 26(5): p. 652\u0026ndash;663.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEchevarria-Lima, J., et al., \u003cem\u003eProtein Profile of Blood Monocytes is Altered in HTLV-1 Infected Patients: Implications for HAM/TSP Disease\u003c/em\u003e. Sci Rep, 2018. 8(1): p. 14354.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChristophi, G.P., et al., \u003cem\u003eMacrophages of multiple sclerosis patients display deficient SHP-1 expression and enhanced inflammatory phenotype\u003c/em\u003e. Lab Invest, 2009. 89(7): p. 742\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eItaliani, P., et al., \u003cem\u003eProfiling the Course of Resolving vs. Persistent Inflammation in Human Monocytes: The Role of IL-1 Family Molecules\u003c/em\u003e. Front Immunol, 2020. 11: p. 1426.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLopez-Dee, Z., K. Pidcock, and L.S. Gutierrez, \u003cem\u003eThrombospondin-1: multiple paths to inflammation\u003c/em\u003e. Mediators Inflamm, 2011. 2011: p. 296069.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFilep, J.G., \u003cem\u003eTargeting Neutrophils for Promoting the Resolution of Inflammation\u003c/em\u003e. Front Immunol, 2022. 13: p. 866747.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMurray, P.J. and T.A. Wynn, \u003cem\u003eProtective and pathogenic functions of macrophage subsets\u003c/em\u003e. Nat Rev Immunol, 2011. 11(11): p. 723\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIvashkiv, L.B., \u003cem\u003eIFNgamma: signalling, epigenetics and roles in immunity, metabolism, disease and cancer immunotherapy\u003c/em\u003e. Nat Rev Immunol, 2018. 18(9): p. 545\u0026ndash;558.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMerad, M. and J.C. Martin, \u003cem\u003ePathological inflammation in patients with COVID-19: a key role for monocytes and macrophages\u003c/em\u003e. Nat Rev Immunol, 2020. 20(6): p. 355\u0026ndash;362.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChousterman, B.G., F.K. Swirski, and G.F. Weber, \u003cem\u003eCytokine storm and sepsis disease pathogenesis\u003c/em\u003e. Semin Immunopathol, 2017. 39(5): p. 517\u0026ndash;528.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"genes-and-immunity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"genes","sideBox":"Learn more about [Genes \u0026 Immunity](http://www.nature.com/gene/)","snPcode":"41435","submissionUrl":"https://mts-gene.nature.com/cgi-bin/main.plex","title":"Genes \u0026 Immunity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"HTLV-1, HAM/TP, Monocytes, Single cell sequencing","lastPublishedDoi":"10.21203/rs.3.rs-7724833/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7724833/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHuman T-cell lymphotropic virus type 1 (HTLV-1) causes HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP), a chronic, immune-mediated spinal cord disease in which peripheral immune activation is thought to fuel central neuroinflammation. To delineate cell type-specific programs linked to disease, we performed single-cell RNA sequencing on the peripheral blood mononuclear cells (PBMCs) of the HTLV-1 infected asymptomatic carrier (AC) and HAM/TSP patient. Differential expression and pathway analysis localized the most pronounced transcriptional divergence to the monocyte compartment, revealing coordinated remodeling of macrophage classical (M1-like) activation, IL-10-regulatory signaling, leukocyte adhesion/diapedesis, and trans-endothelial migration pathway, and cytokine storm-related modules. Ingenuity Pathway Analysis highlighted overlap with multiple sclerosis-associated signaling, consistent with myeloid-driven neuroinflammation and potential blood-spinal cord barrier involvement. In an independent validation phase, we assayed the selected subsets of up- and down-regulated monocyte genes in AC and HAM/TSP participants enrolled in a randomized, open-label pilot trial in Brazil. Expression of several inflammatory markers was higher at baseline in HAM/TSP and decreased during dolutegravir (DTG) therapy, paralleling reductions in HTLV-1 proviral load (PVL) in the DTG arm. Collectively, these data suggest that antiviral strategies may modulate immune cell transcriptional programs that help reduce HTLV-1 PVL.\u003c/p\u003e","manuscriptTitle":"Transcriptional reprogramming in immune cells of HTLV-1 asymptomatic carriers and HAM/TSP patients following antiretroviral therapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-31 01:39:12","doi":"10.21203/rs.3.rs-7724833/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-04-10T17:52:25+00:00","index":4,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-03-30T13:16:36+00:00","index":4,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-01-05T16:33:54+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-24T16:58:47+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-10-18T11:11:11+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-17T16:46:31+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-10-17T15:42:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-07T14:40:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Genes \u0026 Immunity","date":"2025-10-07T14:31:42+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2025-09-29T12:29:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-26T21:38:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"genes-and-immunity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"genes","sideBox":"Learn more about [Genes \u0026 Immunity](http://www.nature.com/gene/)","snPcode":"41435","submissionUrl":"https://mts-gene.nature.com/cgi-bin/main.plex","title":"Genes \u0026 Immunity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"12a4bf98-c80e-4b26-8709-c64de663902a","owner":[],"postedDate":"October 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":56487141,"name":"Biological sciences/Immunology/Infectious diseases/Viral infection"},{"id":56487142,"name":"Biological sciences/Immunology/Infection"}],"tags":[],"updatedAt":"2025-10-31T01:39:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-31 01:39:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7724833","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7724833","identity":"rs-7724833","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}