Honors & Awards

  • Fellowship for research internship abroad, São Paulo State Research Support Foundation (FAPESP) (2022)
  • Doctoral Researcher Fellowship, São Paulo State Research Support Foundation (FAPESP) (2020)
  • Santander Universities Ibero-American Scholarship, Santander (2017)
  • PIBIC scholarship grant, CAPES (2015)
  • Scientific Initiation scholarship awarded by the Young Talents for Science Program,, CAPES (2013)

Professional Education

  • Ph.D, University of Sao Paulo, Brazil, Pharmacy and Pathophysiology (2024)
  • B.S., Institute of Science and Technology, Federal University of Sao Paulo, Brazil, Biotechnology (2017)
  • Studentship, Superior Health School of Porto, Portugal, Medicinal Biotechnology (2017)
  • Research Internship, Paulista School of Medicine, Federal University of Sao Paulo, Brazil, Medicine (2016)
  • B.S., Institute of Science and Technology, Federal University of Sao Paulo, Brazil, Science and Technology (2015)

Contact

  • Academic
    dplaca@stanford.edu
    University - Scholar Department: School of Medicine Position: Postdoctoral Scholar

Additional Info

  • Mail Code: 4020

Current Research and Scholarly Interests

I am dedicated to understanding the interplay between Flaviviridae viruses, particularly dengue (DENV) and Zika (ZIKV), and the human host in the context of viral infections and disease pathogenesis. My research focuses on T cell and myeloid dysregulation in severe dengue to inform safer and more effective vaccine design, as well as the identification of biomarkers and therapeutic targets.
I've employed a systems immunology approach to identify immune determinants shared between DENV vaccines and natural infection. My work provided a phenotypic characterization of T cell subtypes in the DENV-specific immune response, shedding light on T cell differentiation mechanisms.
Since beginning my postdoctoral training in November 2024, I have generated and analyzed high-quality CITE-seq data from dengue patients and have been characterizing the regulatory immune response to DENV through integrative systems analysis. My ultimate goal is to contribute to the development of improved diagnostic tools and vaccines for pediatric infectious diseases, particularly in endemic regions like Brazil.

All Publications

  • Immunological signatures unveiled by integrative systems vaccinology characterization of dengue vaccination trials and natural infection. Frontiers in immunology Plaça, D. R., Fonseca, D. L., Marques, A. H., Zaki Pour, S., Usuda, J. N., Baiocchi, G. C., Prado, C. a., Salgado, R. C., Filgueiras, I. S., Freire, P. P., Rocha, V., Camara, N. O., Catar, R., Moll, G., Jurisica, I., Calich, V. L., Giil, L. M., Rivino, L., Ochs, H. D., Cabral-Miranda, G., Schimke, L. F., Cabral-Marques, O. 2024; 15: 1282754

    Abstract

    Dengue virus infection is a global health problem lacking specific therapy, requiring an improved understanding of DENV immunity and vaccine responses. Considering the recent emerging of new dengue vaccines, here we performed an integrative systems vaccinology characterization of molecular signatures triggered by the natural DENV infection (NDI) and attenuated dengue virus infection models (DVTs).We analyzed 955 samples of transcriptomic datasets of patients with NDI and attenuated dengue virus infection trials (DVT1, DVT2, and DVT3) using a systems vaccinology approach. Differential expression analysis identified 237 common differentially expressed genes (DEGs) between DVTs and NDI. Among them, 28 and 60 DEGs were up or downregulated by dengue vaccination during DVT2 and DVT3, respectively, with 20 DEGs intersecting across all three DVTs. Enriched biological processes of these genes included type I/II interferon signaling, cytokine regulation, apoptosis, and T-cell differentiation. Principal component analysis based on 20 common DEGs (overlapping between DVTs and our NDI validation dataset) distinguished dengue patients by disease severity, particularly in the late acute phase. Machine learning analysis ranked the ten most critical predictors of disease severity in NDI, crucial for the anti-viral immune response.This work provides insights into the NDI and vaccine-induced overlapping immune response and suggests molecular markers (e.g., IFIT5, ISG15, and HERC5) for anti-dengue-specific therapies and effective vaccination development.

    View details for DOI 10.3389/fimmu.2024.1282754

    View details for PubMedID 38444851

    View details for PubMedCentralID PMC10912564

  • Interferome signature dynamics during the anti-dengue immune response: a systems biology characterization. Frontiers in immunology Usuda, J. N., Plaça, D. R., Fonseca, D. L., Marques, A. H., Filgueiras, I. S., Chaves, V. G., Adri, A. S., Torrentes-Carvalho, A., Hirata, M. H., Freire, P. P., Catar, R., Cabral-Miranda, G., Schimke, L. F., Moll, G., Cabral-Marques, O. 2023; 14: 1243516

    Abstract

    Dengue virus (DENV) infection manifests as a febrile illness with three distinct phases: early acute, late acute, and convalescent. Dengue can result in clinical manifestations with different degrees of severity, dengue fever, dengue hemorrhagic fever, and dengue shock syndrome. Interferons (IFNs) are antiviral cytokines central to the anti-DENV immune response. Notably, the distinct global signature of type I, II, and III interferon-regulated genes (the interferome) remains uncharacterized in dengue patients to date. Therefore, we performed an in-depth cross-study for the integrative analysis of transcriptome data related to DENV infection. Our systems biology analysis shows that the anti-dengue immune response is characterized by the modulation of numerous interferon-regulated genes (IRGs) enriching, for instance, cytokine-mediated signaling (e.g., type I and II IFNs) and chemotaxis, which is then followed by a transcriptional wave of genes associated with cell cycle, also regulated by the IFN cascade. The adjunct analysis of disease stratification potential, followed by a transcriptional meta-analysis of the interferome, indicated genes such as IFI27, ISG15, and CYBRD1 as potential suitable biomarkers of disease severity. Thus, this study characterizes the landscape of the interferome signature in DENV infection, indicating that interferome dynamics are a crucial and central part of the anti-dengue immune response.

    View details for DOI 10.3389/fimmu.2023.1243516

    View details for PubMedID 37638052

    View details for PubMedCentralID PMC10449254

  • Integrative systems immunology uncovers molecular networks of the cell cycle that stratify COVID-19 severity. Journal of medical virology Prado, C. a., Fonseca, D. L., Singh, Y., Filgueiras, I. S., Baiocchi, G. C., Plaça, D. R., Marques, A. H., Dantas-Komatsu, R. C., Usuda, J. N., Freire, P. P., Salgado, R. C., Napoleao, S. a., Ramos, R. N., Rocha, V., Zhou, G., Catar, R., Moll, G., Camara, N. O., de Miranda, G. C., Calich, V. L., Giil, L. M., Mishra, N., Tran, F., Luchessi, A. D., Nakaya, H. I., Ochs, H. D., Jurisica, I., Schimke, L. F., Cabral-Marques, O. 2023; 95 (2): e28450

    Abstract

    Several perturbations in the number of peripheral blood leukocytes, such as neutrophilia and lymphopenia associated with Coronavirus disease 2019 (COVID-19) severity, point to systemic molecular cell cycle alterations during severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. However, the landscape of cell cycle alterations in COVID-19 remains primarily unexplored. Here, we performed an integrative systems immunology analysis of publicly available proteome and transcriptome data to characterize global changes in the cell cycle signature of COVID-19 patients. We found significantly enriched cell cycle-associated gene co-expression modules and an interconnected network of cell cycle-associated differentially expressed proteins (DEPs) and genes (DEGs) by integrating the molecular data of 1469 individuals (981 SARS-CoV-2 infected patients and 488 controls [either healthy controls or individuals with other respiratory illnesses]). Among these DEPs and DEGs are several cyclins, cell division cycles, cyclin-dependent kinases, and mini-chromosome maintenance proteins. COVID-19 patients partially shared the expression pattern of some cell cycle-associated genes with other respiratory illnesses but exhibited some specific differential features. Notably, the cell cycle signature predominated in the patients' blood leukocytes (B, T, and natural killer cells) and was associated with COVID-19 severity and disease trajectories. These results provide a unique global understanding of distinct alterations in cell cycle-associated molecules in COVID-19 patients, suggesting new putative pathways for therapeutic intervention.

    View details for DOI 10.1002/jmv.28450

    View details for PubMedID 36597912

    View details for PubMedCentralID PMC10107240

  • Autoantibodies targeting GPCRs and RAS-related molecules associate with COVID-19 severity. Nature communications Cabral-Marques, O., Halpert, G., Schimke, L. F., Ostrinski, Y., Vojdani, A., Baiocchi, G. C., Freire, P. P., Filgueiras, I. S., Zyskind, I., Lattin, M. T., Tran, F., Schreiber, S., Marques, A. H., Plaça, D. R., Fonseca, D. L., Humrich, J. Y., Müller, A., Giil, L. M., Graßhoff, H., Schumann, A., Hackel, A., Junker, J., Meyer, C., Ochs, H. D., Lavi, Y. B., Scheibenbogen, C., Dechend, R., Jurisica, I., Schulze-Forster, K., Silverberg, J. I., Amital, H., Zimmerman, J., Heidecke, H., Rosenberg, A. Z., Riemekasten, G., Shoenfeld, Y. 2022; 13 (1): 1220

    Abstract

    COVID-19 shares the feature of autoantibody production with systemic autoimmune diseases. In order to understand the role of these immune globulins in the pathogenesis of the disease, it is important to explore the autoantibody spectra. Here we show, by a cross-sectional study of 246 individuals, that autoantibodies targeting G protein-coupled receptors (GPCR) and RAS-related molecules associate with the clinical severity of COVID-19. Patients with moderate and severe disease are characterized by higher autoantibody levels than healthy controls and those with mild COVID-19 disease. Among the anti-GPCR autoantibodies, machine learning classification identifies the chemokine receptor CXCR3 and the RAS-related molecule AGTR1 as targets for antibodies with the strongest association to disease severity. Besides antibody levels, autoantibody network signatures are also changing in patients with intermediate or high disease severity. Although our current and previous studies identify anti-GPCR antibodies as natural components of human biology, their production is deregulated in COVID-19 and their level and pattern alterations might predict COVID-19 disease severity.

    View details for DOI 10.1038/s41467-022-28905-5

    View details for PubMedID 35264564

    View details for PubMedCentralID PMC8907309