Publications

Human T-lymphotropic virus type 1 (HTLV-1) infection presents a wide clinical spectrum ranging from lifelong asymptomatic carriage to severe inflammatory neurodegeneration (HAM/TSP) or adult T-cell leukemia/lymphoma (ATLL). Although IgG responses contribute to viral control and immunopathology, the extent to which HTLV-1 clinical outcomes shape pathogen-derived IgG repertoires remains unclear. In this study, we applied a high-density infectious-disease epitope microarray containing 4,345 linear epitopes from viral, bacterial, parasitic, and fungal pathogens to profile IgG responses in healthy controls (HCs), asymptomatic carriers (ACs), HAM/TSP patients, and ATLL patients. Signal intensities were quantified in arbitrary units, and recognized epitopes were evaluated using similarity clustering (80% identity threshold) to assess repertoire structure. HTLV-1–infected individuals exhibited extensive remodeling of humoral immunity, with marked differences in the breadth and intensity of IgG recognition across clinical groups. HAM/TSP patients displayed broad and high-magnitude responses consistent with chronic inflammation and heightened Th1 activation, whereas ATLL patients recognized the largest number of epitopes but with distinct patterns indicative of altered B-cell regulation. Enhanced IgG responses to Mycobacterium tuberculosis, Strongyloides stercoralis, Toxoplasma gondii, and Plasmodium species were consistent with known co-infection susceptibilities in HTLV-1. Epitope similarity analysis revealed hundreds of low-redundancy clusters across all groups, arguing against simple linear cross-reactivity and suggesting phenotype-specific reshaping of B-cell selection and idiotypic networks. These findings demonstrate that HTLV-1 infection produces distinct, clinically dependent IgG epitope signatures across multiple pathogen classes, with potential relevance for understanding HTLV-1 pathogenesis and informing future studies integrating epitope mapping with B-cell repertoire analysis.

Background The contribution of antibody-mediated responses to COVID – 19 outcomes remains unclear, particularly regarding cross-reactivity with unrelated pathogens. While co-infections are known to influence disease progression, the broader landscape of IgG reactivity during SARS-CoV-2 infection has not been systematically explored. Methods We employed a high-density peptide microarray containing 4,344 linear epitopes from 37 viruses, 27 bacteria, 17 parasites, and 8 fungi to characterize serum IgG repertoires from individuals with moderate (n = 39) or severe (n = 40) COVID – 19. Controls included pre-pandemic healthy donors and a pooled intravenous immunoglobulin (IVIg) formulation. Data analysis included intensity ranking, epitope mapping, and comparative analysis of mean signal intensities for each epitope between the COVID-Mod and COVID-Sev groups. Results COVID – 19 patients showed widespread IgG reactivity against diverse pathogens, with patterns differing by disease severity. Severe cases displayed broader and more intense reactivity, notably against hepatitis C virus (HCV), SARS-CoV-1, influenza A, Mycobacterium tuberculosis, and Plasmodium falciparum. Moderate cases showed preferential recognition of epitopes from HTLV-I, Neisseria meningitidis, and Trypanosoma cruzi. These findings suggest that SARS-CoV-2 infection modulates pre-existing humoral memory, possibly through epitope spreading or immune reprogramming. Conclusions SARS-CoV-2 infection reshapes the IgG epitope repertoire in a severity-dependent manner, extending to antigens from unrelated pathogens. This phenomenon may reflect underlying immune dysregulation or idiotype-driven interactions. Comprehensive profiling of pathogen-related IgG responses may reveal potential biomarkers of disease severity. This phenomenon may inform future investigations aimed at improving personalized management strategies for co-infected or immunocompromised patients.

This study aimed to elucidate the complexity of the humoral immune response in COVID-19 patients with varying disease trajectories using a SARS-CoV-2 whole proteome peptide microarray chip. The microarray, containing 5347 peptides spanning the entire SARS-CoV-2 proteome and key variants of concern, was used to analyze IgG responses in 10 severe-to-recovered, 9 nonsevere-to-severe cases, and 10 control case (5 pre-pandemic and 5 SARS-CoV-2-negative) plasma samples. We identified 1151 IgG-reactive peptides corresponding to 647 epitopes, with 207 peptides being cross-reactive across 124 epitopes. Nonstructural protein 3 (nsp3) exhibited the highest number of total and unique epitopes, followed by the spike protein. nsp12 had the most number of cross-reactive epitopes. Peptides from the spike protein and nsps 2, 3, 5, and 13 were notably associated with recovery. Additionally, specific mutations in SARS-CoV-2 variants were found to alter peptide immunoreactivity, with some mutations (e.g., G142D, L452R, and N501Y) enhancing and others (e.g., R190S and E484 K) reducing immune recognition. These findings have critical implications for the development of diagnostics, vaccines, and therapeutics. Understanding the distribution of epitopes and the impact of viral mutations on antigenicity provides insights into immune evasion mechanisms, informing strategies for controlling COVID-19 and future coronavirus outbreaks.