HTLV-1-Induced Neuroimmunome Correlates with Disease Progression and Severity

HTLV-1-Induced Neuroimmunome Correlates with Disease Progression and Severity | 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 HTLV-1-Induced Neuroimmunome Correlates with Disease Progression and Severity Fernando Nery do Vale, Carlota Miranda-Solé, Adriel Nóbile, Júlia Usuda, and 20 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7357522/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract HTLV-1 infects 10–20 million people globally. While most remain asymptomatic, some develop severe neuroinflammatory or malignant diseases, such as adult T-cell leukemia/lymphoma (ATL) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Using a systems biology approach, we integrated bulk transcriptomics from PBMCs (n = 200) with single-cell RNA sequencing from 233,093 PBMCs. We identified a consistent neuroimmune signature (“neuroimmunome”) composed of differentially expressed genes mediating nervous–immune crosstalk. This signature was enriched in synapse-related pathways, including glutamatergic, noradrenergic, and neuregulin signaling, and linked to neuroinflammatory processes such as glial activation, motor neuron apoptosis, L-glutamate transport, and synaptic dysfunction. Through PCA, gradient boosting, and MANOVA with bootstrapping, we found potential biomarkers predictive of HTLV-1 leukemogenesis, validated via flow cytometry in ATL, HAM/TSP, and asymptomatic cohorts. Proteins such as ATF4 and SKIL correlated with proviral load, suggesting sustained neuroimmune dysregulation drives disease progression. These findings reveal a deeper pathophysiological complexity, framing HTLV-1 disease as rooted in neuroimmune network disruption. Biological sciences/Cancer/Tumour immunology Biological sciences/Biological techniques/Bioinformatics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryDataHTLV1.pdf Supplementary data SupplementarytablepaperHTLV.xlsx Supplementary table 7695RS.pdf Reporting Summary Cite Share Download PDF Status: Under Review Version 1 posted 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. 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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-7357522","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":509619895,"identity":"051acea7-5732-4bfd-8862-2e3cce4a6496","order_by":0,"name":"Fernando Nery do 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S. Dalmolin Dalmolin","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Rodrigo","middleName":"J. S. Dalmolin","lastName":"Dalmolin","suffix":""},{"id":509619912,"identity":"9a6f5580-8494-4233-b6fb-56b03ccc95f3","order_by":17,"name":"Haroldo Dias","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Haroldo","middleName":"","lastName":"Dias","suffix":""},{"id":509619913,"identity":"5d550b0c-ceea-4eef-b40f-dd5353412744","order_by":18,"name":"Yuki Saito","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yuki","middleName":"","lastName":"Saito","suffix":""},{"id":509619914,"identity":"ac7de328-2114-4510-9dee-439b9ae03032","order_by":19,"name":"Yasunori Kogure","email":"","orcid":"https://orcid.org/0000-0003-1158-5131","institution":"National Cancer Center Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Yasunori","middleName":"","lastName":"Kogure","suffix":""},{"id":509619915,"identity":"0116e3d9-1971-492d-a3d9-060326770c14","order_by":20,"name":"Junji Koya","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Junji","middleName":"","lastName":"Koya","suffix":""},{"id":509619916,"identity":"82178e8a-da6b-411e-b53d-4a7e93aa0c83","order_by":21,"name":"Keisuke Kataoka","email":"","orcid":"https://orcid.org/0000-0002-8263-9902","institution":"National Cancer Center Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Keisuke","middleName":"","lastName":"Kataoka","suffix":""},{"id":509619917,"identity":"250b1649-3f50-45e4-ad72-930f3d9be3f8","order_by":22,"name":"Igor Filgueiras","email":"","orcid":"https://orcid.org/0000-0002-3493-4464","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Igor","middleName":"","lastName":"Filgueiras","suffix":""},{"id":509619918,"identity":"62ea95ad-2df8-46c9-a1b9-7accd57b6644","order_by":23,"name":"Margarita Dominguez-Villar","email":"","orcid":"https://orcid.org/0000-0002-9719-0028","institution":"Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Margarita","middleName":"","lastName":"Dominguez-Villar","suffix":""}],"badges":[],"createdAt":"2025-08-12 15:51:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7357522/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7357522/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90852229,"identity":"df256238-4582-42ec-8e03-7410518cca3b","added_by":"auto","created_at":"2025-09-09 03:35:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":458460,"visible":true,"origin":"","legend":"\u003cp\u003eSingle-cell analysis of PBMCs from HTLV-1 patients across disease stages. a. UMAP \u0026nbsp;visualization (reproduced from [Koya et al., 2021\u003csup\u003e41\u003c/sup\u003e]) shows increasing cellular heterogeneity with disease \u0026nbsp;progression, from healthy controls to chronic and acute HTLV-1 stages. b. The emergence of novel immune \u0026nbsp;cell clusters in the acute phase suggests dynamic remodeling of the peripheral immune landscape. c. CD4\u003csup\u003e+\u003c/sup\u003e T helper cells are the predominant cell type across all conditions, with notable enrichment in the acute \u0026nbsp;subtype. d. Malignant-like cell populations (blue) are primarily observed in chronic and acute stages, \u0026nbsp;consistent with disease-associated clonal expansion.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7357522/v1/3feaf6592a89485bb65b627a.png"},{"id":90852938,"identity":"a16217ea-d95b-428d-a695-c377b4dbf0b3","added_by":"auto","created_at":"2025-09-09 03:43:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":937965,"visible":true,"origin":"","legend":"\u003cp\u003eNeuro-immune genes and biological processes signature across HTLV-1 disease stages \u0026nbsp;at the single-cell level. a. Bars represent DEGs classified as upregulated (blue) and downregulated (teal) \u0026nbsp;in each subset. A marked increase in DEGs is observed in the acute ATL phase, particularly among T cell \u0026nbsp;populations b. DEGs functionally annotated as immune related or nervous system related, revealing stage-dependent enrichment of neuroimmune genes, which peak during the acute ATL phase, notably within T \u0026nbsp;CD4\u003csup\u003e+\u003c/sup\u003e/CD8\u003csup\u003e+\u003c/sup\u003e cells. c. Gene ontology enrichment analysis of PBMBs highlights neuroimmune-associated \u0026nbsp;biological processes, with significance and gene ratios across HTLV-1 clinical subtypes, especially \u0026nbsp;associated to T cell of acute subtype. d. functional gene network constructed from DEGs identified in \u0026nbsp;peripheral CD4⁺ T cells of individuals with the acute subtype of ATL. Nodes represent individual genes, and \u0026nbsp;edges indicate known or predicted functional associations based on pathway enrichment and co-expression.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7357522/v1/47800c56c69396d341054c96.png"},{"id":90852935,"identity":"8920142b-8ca4-438a-ae64-6a7ad5cdae38","added_by":"auto","created_at":"2025-09-09 03:43:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1293168,"visible":true,"origin":"","legend":"\u003cp\u003eEnrichment analysis of synaptic and neuroimmune pathways in HTLV-1–associated \u0026nbsp;malignant cells. a. Heatmap depicting synaptic pathway enrichment scores across immune cell types and \u0026nbsp;HTLV-1 clinical subtypes, highlighting significant activation of serotonergic, glutamatergic, and GABAergic \u0026nbsp;synapses. b. DEGs associated with major neurotransmitter pathways (glutamatergic, GABAergic, \u0026nbsp;cholinergic, dopaminergic, serotonergic) across immune cell types and clinical stages. Neurotransmission-related transcriptional activity increases progressively, peaking in acute-phase T cells. c. Network \u0026nbsp;representation of DEGs from neurotransmitter pathways mapped to PBMC subtypes. Node colors reflect \u0026nbsp;clinical stage, while edge colors indicate neurotransmitter pathways. Acute CD4⁺ and CD4⁺/CD8⁺ T cells \u0026nbsp;display dense interconnectivity, particularly with glutamatergic and GABAergic signaling genes, suggesting \u0026nbsp;neuroimmune transcriptional remodeling in late-stage infection. d. Spatial enrichment analysis using \u0026nbsp;ArchipelaGO reveals a strong association between synaptic biological processes and malignant T cells, \u0026nbsp;supporting the hypothesis of synapse-related gene expression programs in HTLV-1–driven malignancy.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7357522/v1/2155820036e8a4d724d4652b.png"},{"id":90852230,"identity":"646ae802-49b0-476c-8cdc-62e33d38cb7b","added_by":"auto","created_at":"2025-09-09 03:35:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":331474,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA workflow for dataset selection and meta-analysis of RNA-seq and single-cell \u0026nbsp;studies. Flow diagram summarizing the selection process of transcriptomic datasets involving HTLV-1 \u0026nbsp;infection. Out of 536 datasets identified through database searches, 64 datasets were screened after \u0026nbsp;excluding non-human or array/bulk RNA-seq datasets. Following eligibility assessment, 60 datasets were \u0026nbsp;excluded due to criteria such as use of therapeutic samples, insufficient infected sample count, lack of \u0026nbsp;replicates, or time-point designs. Ultimately, 6 datasets were included, comprising both single-cell and bulk \u0026nbsp;RNA-seq data from public databases and published studies. The bottom section provides a breakdown of \u0026nbsp;sample distribution across conditions (Controls, ACs, ATL, and HAM/TSP) and the associated \u0026nbsp;transcriptomic datasets used.\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7357522/v1/8f22992965383aed437c30d2.png"},{"id":90852233,"identity":"3602b772-897d-4a0b-acaa-389f64f81a33","added_by":"auto","created_at":"2025-09-09 03:35:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1287491,"visible":true,"origin":"","legend":"\u003cp\u003eMeta-analysis of transcriptomic datasets reveals neuroimmune terms enrichment in ATL. \u0026nbsp;Meta-analysis of publicly available microarray and bulk RNA-seq data highlights the involvement of \u0026nbsp;neuroimmune pathways in HTLV-1–associated conditions. a. Bar plot showing the number of differentially \u0026nbsp;expressed genes (DEGs) categorized as immune-, nervous-, or neuroimmune-related across \u0026nbsp;asymptomatic, ATL, and HAM/TSP cohorts. b. UMAP projections of sample clusters reveal distinct patterns \u0026nbsp;across disease states, with neuroimmune gene expression predominantly enriched in ATL and HAM \u0026nbsp;clusters. c. Functional annotation of DEGs demonstrates a significant increase in nervous system–related \u0026nbsp;biological processes in ATL. d. Gene ontology enrichment of biological processes (BP) reveals specific \u0026nbsp;neuroimmune terms such as glial cell activation, neuron apoptotic process, and synapse organization \u0026nbsp;enriched across disease states. e. Cumulative counts of significantly enriched BP terms categorized by \u0026nbsp;functional class show a pronounced nervous system signature in ATL. f. The network reveals a \u0026nbsp;transcriptional reprogramming of PBMCs toward neuronal and neuroimmune phenotypes, characterized by \u0026nbsp;the activation of CNS biological process related terms.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7357522/v1/bf44a74b183291d447d780c6.png"},{"id":90852236,"identity":"9ae73d37-07a4-48c2-af29-af7134cce769","added_by":"auto","created_at":"2025-09-09 03:35:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":499818,"visible":true,"origin":"","legend":"\u003cp\u003eIntegrated machine learning, statistical modeling, and flow cytometry reveal \u0026nbsp;neuroimmune-related intracellular signatures associated with HTLV-1 infection. a. Neuro-immun-related genes with the highest contributions to the first two principal components (Dim1 and Dim2) were \u0026nbsp;identified, highlighting their role in distinguishing ATL patients from healthy controls. b. The top 20 neuro\u0002immune genes with the highest eigenvalues were selected based on their contribution to group segregation. \u0026nbsp;c. Arrows indicate the direction and magnitude of each gene's contribution to the PCA dimensions. Genes \u0026nbsp;such as TIAM2, SKIL, CXCR4, and XRCC5 show strong directional influence on the principal components, \u0026nbsp;suggesting they are key drivers of the observed transcriptional variation. The color gradient represents the \u0026nbsp;contribution magnitude (\"Contrib\") of each gene to the PCA dimensions, with warmer tones (green to yellow) \u0026nbsp;indicating higher contribution. d. A relative effect analysis was conducted to quantify the association of \u0026nbsp;neuro-immune genes (identified through PCA) with ATL and control groups. Circle size represents the \u0026nbsp;magnitude of the relative effect. e. Gradient Boosting Machine (GBM) analysis was used to determine the \u0026nbsp;relative influence of neuro-immune genes in group discrimination, revealing key contributors, including two \u0026nbsp;novel candidate genes. f. Boxplots represent expression levels of selected genes involved in neuroimmune \u0026nbsp;interactions across samples from acute ATL patients (red), chronic (blue) and healthy controls (green). \u0026nbsp;Each gene is displayed in a separate facet. Statistical comparisons were performed using the Wilcoxon \u0026nbsp;rank-sum test. Significance levels are indicated by asterisks: p \u0026lt; 0.05 (), p \u0026lt; 0.01 (), p \u0026lt; 0.001 (), and \u0026nbsp;p \u0026lt; 0.0001 (****); non-significant results are marked as \"ns\".\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7357522/v1/81febb27c70ae41a04f808f3.png"},{"id":90853882,"identity":"8639486c-c624-4244-ba54-b29d4921a7e3","added_by":"auto","created_at":"2025-09-09 03:59:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":204152,"visible":true,"origin":"","legend":"\u003cp\u003eAltered Expression of Neuroimmune and Stress-Response Markers in PBMCs from HTLV-1–Infected Individuals Correlates with Proviral Load and Disease Progression. Multiparameter flow \u0026nbsp;cytometry was used to assess neuroimmune and stress-response markers in PBMCs from HD, AC, HAM, \u0026nbsp;and ATL individuals. Scatter plots show linear regressions between HTLV-1 proviral load and marker\u0002positive cell frequencies, revealing associations with disease progression and immune dysregulation. (a) Frequency of PBMCs with intracellular V-ATPase D1 (ATP6V0D1), ATF4, SKIL, Senataxin (SETX), \u0026nbsp;PTBP1 and CXCR4. (b) Geometric mean fluorescence intensity of intracellular VAMP2 and Ku80 (XRCC5). \u0026nbsp;Data points represent individual donors, with bars showing mean ± SD. Significant decreases in V-ATPase \u0026nbsp;D1, SKIL, CXCR4, and PTBP1 were observed across HTLV-1 infection groups compared to healthy \u0026nbsp;controls, suggesting downregulation of stress response and RNA processing pathways. ATF4 expression \u0026nbsp;showed an increase in asymptomatic carriers, while Senataxin levels were elevated in a subset of ATL \u0026nbsp;patients relative to ACs and HAM. VAMP2 and Ku80 also showed significant alterations, indicating broader immunoneural dysregulation. Statistical significance was determined using unpaired t-tests with Welch’s \u0026nbsp;correction. p \u0026lt; 0.05 (*), p \u0026lt; 0.01 (**), p \u0026lt; 0.001 (***), p \u0026lt; 0.0001 (****). (c) all individuals regardless of HTLV-1 infection, (d) individuals with HTLV-1 infection or (e) individuals with symptomatic HTLV-1 infection \u0026nbsp;(HAM/ATL). Each point represents one subject; regression lines with 95% confidence intervals are shown. \u0026nbsp;Markers analyzed include CXCR4, SKIL, V-ATPase D1, ATF4 and Senataxin. Significant inverse \u0026nbsp;correlations were observed for CXCR4 (R² = 0.3340, p = 0.0061), SKIL (R² = 0.2362, p = 0.0255) and V-ATPase D1 (R² = 0.3771, p = 0.0031) when looking at all individuals (a), and ATF4 (R² = 0.3504, p = 0.0201) when excluding HD (b); indicating downregulation of key homeostatic and stress-response pathways with \u0026nbsp;increasing PVL. In contrast, Senataxin expression was positively correlated with PVL (individuals with \u0026nbsp;HTLV-1 infection: R² = 0.5666, p = 0.0012; symptomatic HTLV-1 infection: R² = 0.7153, p = 0.0020), \u0026nbsp;suggesting disease-related transcriptional reprogramming. These results reveal that HTLV-1 burden is \u0026nbsp;associated with distinct shifts in the expression of intracellular proteins involved in chemokine signaling, \u0026nbsp;lysosomal function, and genomic maintenance.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7357522/v1/2a767468049e6ddeecb0d50a.png"},{"id":104406282,"identity":"43d9860e-e2f6-4662-ad85-897a37252e52","added_by":"auto","created_at":"2026-03-11 12:25:13","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2027957,"visible":true,"origin":"","legend":"Article File","description":"","filename":"HTLV1manuscriptfinal.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7357522/v1_covered_0ea83744-e923-4398-af3b-c5bbd555e9bc.pdf"},{"id":90853079,"identity":"62fd8cdd-8514-4587-aea3-08706e2bf20f","added_by":"auto","created_at":"2025-09-09 03:51:15","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1387670,"visible":true,"origin":"","legend":"Supplementary data","description":"","filename":"SupplementaryDataHTLV1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7357522/v1/3afe674c1894236ba29d2455.pdf"},{"id":90852244,"identity":"4e3bf688-76e8-4fff-8f97-dff26eb3e5b5","added_by":"auto","created_at":"2025-09-09 03:35:15","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3297888,"visible":true,"origin":"","legend":"Supplementary table","description":"","filename":"SupplementarytablepaperHTLV.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7357522/v1/807046ae3e43699dc9038537.xlsx"},{"id":90852248,"identity":"d18a8d75-c95a-4d4f-b98b-f8db0167426f","added_by":"auto","created_at":"2025-09-09 03:35:15","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":6507724,"visible":true,"origin":"","legend":"Reporting Summary","description":"","filename":"7695RS.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7357522/v1/62e21125d3eecfa9c904496c.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"HTLV-1-Induced Neuroimmunome Correlates with Disease Progression and Severity","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7357522/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7357522/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"HTLV-1 infects 10–20 million people globally. While most remain asymptomatic, some develop severe neuroinflammatory or malignant diseases, such as adult T-cell leukemia/lymphoma (ATL) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Using a systems biology approach, we integrated bulk transcriptomics from PBMCs (n = 200) with single-cell RNA sequencing from 233,093 PBMCs. We identified a consistent neuroimmune signature (“neuroimmunome”) composed of differentially expressed genes mediating nervous–immune crosstalk. This signature was enriched in synapse-related pathways, including glutamatergic, noradrenergic, and neuregulin signaling, and linked to neuroinflammatory processes such as glial activation, motor neuron apoptosis, L-glutamate transport, and synaptic dysfunction. Through PCA, gradient boosting, and MANOVA with bootstrapping, we found potential biomarkers predictive of HTLV-1 leukemogenesis, validated via flow cytometry in ATL, HAM/TSP, and asymptomatic cohorts. Proteins such as ATF4 and SKIL correlated with proviral load, suggesting sustained neuroimmune dysregulation drives disease progression. These findings reveal a deeper pathophysiological complexity, framing HTLV-1 disease as rooted in neuroimmune network disruption.","manuscriptTitle":"HTLV-1-Induced Neuroimmunome Correlates with Disease Progression and Severity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-09 03:35:10","doi":"10.21203/rs.3.rs-7357522/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-biology","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsbio","sideBox":"Learn more about [Communications Biology](http://www.nature.com/commsbio/)","snPcode":"","submissionUrl":"","title":"Communications Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"97ebca28-aeff-4aee-a80f-3845d08cf270","owner":[],"postedDate":"September 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":54127179,"name":"Biological sciences/Cancer/Tumour immunology"},{"id":54127180,"name":"Biological sciences/Biological techniques/Bioinformatics"}],"tags":[],"updatedAt":"2026-03-25T15:11:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-09 03:35:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7357522","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7357522","identity":"rs-7357522","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}