Igor Salerno Filgueiras

Human T-cell lymphotropic virus type 1 (HTLV-1) is a retrovirus that infects approximately 5–10 million people worldwide. While most individuals remain asymptomatic, a significant subset develops debilitating neuroinflammatory or malignant disorders, including adult T-cell leukemia/lymphoma (ATL) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). To unravel the systemic molecular mechanisms underlying HTLV-1 pathogenesis, we employed a multi-dimensional systems biology approach, integrating bulk transcriptomic data from total PBMCs (n = 200) with single-cell RNA sequencing (scRNA-seq) from 233,093 peripheral blood mononuclear cells (PBMCs). Our analysis revealed a consistent and clinically relevant neuroimmune signature within leukocytes, termed the neuroimmunome, comprising a set of differentially expressed genes shared across the nervous and immune systems. Through dimensionality reduction and machine learning techniques, such as PCA, gradient boosting, and MANOVA with bootstrapping, we identified potential biomarkers predictive of HTLV-1-driven leukemogenesis, which were subsequently validated across ATL, HAM/TSP, and asymptomatic cohorts via flow cytometry. Notably, expression levels of proteins such as ATF4 and SKIL were strongly correlated with proviral load, suggesting that sustained neuroimmune dysregulation may contribute to disease progression. These findings highlight a previously underappreciated neuroimmunological layer, redefining HTLV-1-associated disease as a condition deeply rooted in neuroimmune network disruption within leukocytes and offering potential novel targets.

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.

The COVID-19 vaccinations have played a significant role in controlling the pandemic. To elucidate their impact on the immune system, a COVID-19 vaccination atlas was developed using an integrative systems vaccinology approach. The atlas includes 562 samples from 245 participants, including both healthy individuals and those infected with or without prior vaccination, and covers the administration of five vaccines in different regimens. Key findings include the identification of distinct immune markers that differentiate between vaccine types and infection statuses. We observed that mRNA vaccines induced transient but strong immune responses after booster doses, whereas viral vector vaccines showed sustained immune activation with infection, partially resembling the immune profile exhibited during infection. Heterologous vaccination regimens demonstrated enhanced immune diversification compared to homologous regimens. Finally, we described the immunological landscape of COVID-19 vaccines and vaccines against other pathogens, at the gene-level and in cell population dynamics.

Este artigo tem como objetivo demonstrar a importância do letramento de dados por meio do desenvolvimento de competências em visualização para identificar correlações entre fatores ambientais e a incidência de casos de dengue no Brasil. Utilizando o Design Thinking e a ferramenta Tableau, foi criado o DengueMap, um dashboard interativo que permite a análise detalhada de dados epidemiológicos, meteorológicos e demográficos. A visualização de dados ajudou a evidenciar correlações significativas entre variáveis como temperatura e umidade e a ocorrência da doença. O dashboard facilita a comunicação de informações complexas para tomadores de decisão e o público em geral, mostrando-se crucial em situações de emergência de saúde pública. Neste relato de experiência, destaca-se o potencial das visualizações interativas na gestão de políticas públicas de saúde e reforça-se a importância do letramento de dados.

Major depressive disorder (MDD) involves complex neuroimmune interactions linked to gene modulation. Our study investigates synaptic-related gene dysregulation in peripheral blood mononuclear cells (PBMCs) from MDD patients, showing how these immune cells mirror neural processes. Using RNA-seq data, we identified 1,383 differentially expressed genes (DEGs) related to neuroimmune crosstalk, with 49 DEGs effectively distinguishing MDD patients from controls based on synaptic functions. Synaptic genes, enriched for roles like vesicle transport, suggest mechanistic links between immune cells and neural signaling. Eleven synaptic-related DEGs were shared between PBMCs and brain regions involved in mood regulation, highlighting a common molecular signature. Among them, ADORA3 and RPS28 emerged as potential biomarkers. These findings highlight the potential of PBMCs in the diagnosis and treatment of MDD, reinforcing the development of future neuroimmune-targeted therapies for depression.

Major depressive disorder (MDD) is a complex psychiatric condition with a significant global impact. This study applied a genomic-driven integrative systems neuroimmunology approach to analyze transcriptomic data from 3,114 individuals (1,877 MDD patients and 1,237 controls). The analysis revealed neuroimmunological transcriptomic alterations, indicating cross-talk between the immune and nervous systems in peripheral blood mononuclear cells (PBMCs) and specific brain regions. Among 31 shared genes, NEGR1, PPP6C, SORCS3, and PAX6 emerged as significant predictors of MDD in patients’ PBMCs. Notably, PAX6 was also identified as a differentially expressed gene (DEG) in the amygdala, while NEGR1, PPP6C, and SORCS3 showed no significant differential expression in other central nervous system (CNS) regions. Validation by immunophenotyping in a mouse model of chronic stress demonstrated increased PAX6 expression in PBMCs, a gene previously associated with MDD in GWAS studies. Collectively, our findings suggest the existence of shared transcriptomic modules across the brain and immune system, highlighting PAX6 as a potential therapeutic target in MDD.

The COVID-19 vaccinations have played a significant role in controlling the pandemic. To elucidate their impact on the immune system, a COVID-19 vaccination atlas was developed through an integrative systems vaccinology approach. The atlas includes both healthy individuals and those infected with or without prior vaccination, and covers the administration of five vaccines in different regimens: Covilo®, Zifivax®, Vaxzebria® or Covishield®, Spikevax®, and Comirnaty®. Critical markers were identified to discriminate the different types of vaccines and infection, in which infection was associated with GATA3, ZNF3, KMT2A, ASXL1, SP100, and GZMM, and vaccine types were marked by ITGAM, ACTG1, LGALS3, and STAT5B. Additionally, the immunological signatures of heterologous vaccination and infection were described, and it was also shown how a full vaccination regimen markedly limited the shift of immune responses during natural infection, thereby constraining disease progression. Finally, the common transcripts shared across COVID-19 vaccines and vaccines against other pathogens were described.

Tumor-associated myeloid-derived cells (MDCs) significantly impact cancer prognosis and treatment responses due to their remarkable plasticity and tumorigenic behaviors. Here, we integrate single-cell RNA-sequencing data from different cancer types, identifying 29 MDC subpopulations within the tumor microenvironment. Our analysis reveals abnormally expanded MDC subpopulations across various tumors and distinguishes cell states that have often been grouped together, such as TREM2+ and FOLR2+ subpopulations. Using deconvolution approaches, we identify five subpopulations as independent prognostic markers, including states co-expressing TREM2 and PD-1, and FOLR2 and PDL-2. Additionally, TREM2 alone does not reliably predict cancer prognosis, as other TREM2+ macrophages show varied associations with prognosis depending on local cues. Validation in independent cohorts confirms that FOLR2-expressing macrophages correlate with poor clinical outcomes in ovarian and triple-negative breast cancers. This comprehensive MDC atlas offers valuable insights and a foundation for futher analyses, advancing strategies for treating solid cancers.

Acute leukemias (ALs) are complex hematological disorders, and accurate diagnosis is crucial for guiding treatment decisions and predicting patient outcomes. While changes in cell marker levels are well documented, the impact of these changes on marker relationships through an integrative systems approach remains uncharacterized. To address this gap, we conducted a 12-year study investigating 41 markers, including ontogenic markers and those used to diagnose both common and rare leukemia types, using immunophenotyping flow cytometry (IFC) data from 1,069 leukocyte samples obtained from peripheral blood (PB) or bone marrow (BM) aspirates of patients with suspected ALs. Machine learning techniques, such as principal component analysis (PCA) and random forest (RF) classification, demonstrated the stratification power of the cellular markers. Hierarchical clustering analysis of leukocyte ontogenetic markers revealed disease-specific clusters, irrespective of sex or sample type (PB or BM). Additionally, we found that patients with acute myeloid leukemia (AML) showed mild disruption in cell marker correlations, whereas the most significant dysregulation was observed in patients with T-cell acute lymphoblastic leukemia (T-ALL). Importantly, we identified ontogenic correlation changes indicating clusters of immature versus mature leukocyte markers, as well as cell lineage-specific markers influencing cellular relationships. These findings underscore the value of integrating systems strategies into conventional IFC analyses to enhance synthetic diagnosis and deepen our understanding of ALs pathophysiology.

The COVID-19 vaccinations have played a significant role in controlling the pandemic. To elucidate their impact on the immune system, a COVID-19 vaccination atlas was developed through an integrative systems vaccinology approach. The atlas includes both healthy individuals and those infected with or without prior vaccination, and covers the administration of five vaccines in different regimens: Covilo®, Zifivax®, Vaxzebria® or Covishield®, Spikevax®, and Comirnaty®. Critical markers were identified to discriminate the different types of vaccines and infection, in which infection was associated with GATA3, ZNF3, KMT2A, ASXL1, SP100, and GZMM, and vaccine types were marked by ITGAM, ACTG1, LGALS3, and STAT5B. Additionally, the immunological signatures of heterologous vaccination and infection were described, and it was also shown how a full vaccination regimen markedly limited the shift of immune responses during natural infection, thereby constraining disease progression. Finally, the common transcripts shared across COVID-19 vaccines and vaccines against other pathogens were described.