| 1. |
- Gonzalez Dias Carvalho, Patrícia Conceição, et al.
(författare)
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Baseline gene signatures of reactogenicity to Ebola vaccination: a machine learning approach across multiple cohorts
- 2023
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Ingår i: Frontiers in Immunology. - 1664-3224. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: The rVSVDG-ZEBOV-GP (Ervebo®) vaccine is both immunogenic and protective against Ebola. However, the vaccine can cause a broad range of transient adverse reactions, from headache to arthritis. Identifying baseline reactogenicity signatures can advance personalized vaccinology and increase our understanding of the molecular factors associated with such adverse events. Methods: In this study, we developed a machine learning approach to integrate prevaccination gene expression data with adverse events that occurred within 14 days post-vaccination. Results and Discussion: We analyzed the expression of 144 genes across 343 blood samples collected from participants of 4 phase I clinical trial cohorts: Switzerland, USA, Gabon, and Kenya. Our machine learning approach revealed 22 key genes associated with adverse events such as local reactions, fatigue, headache, myalgia, fever, chills, arthralgia, nausea, and arthritis, providing insights into potential biological mechanisms linked to vaccine reactogenicity.
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| 2. |
- Martinez-Murillo, Paola Andrea, et al.
(författare)
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Refined innate plasma signature after rVSVΔG-ZEBOV-GP immunization is shared among adult cohorts in Europe and North America
- 2024
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Ingår i: FRONTIERS IN IMMUNOLOGY. - 1664-3224. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- Background: During the last decade Ebola virus has caused several outbreaks in Africa. The recombinant vesicular stomatitis virus-vectored Zaire Ebola (rVSV Delta G-ZEBOV-GP) vaccine has proved safe and immunogenic but is reactogenic. We previously identified the first innate plasma signature response after vaccination in Geneva as composed of five monocyte-related biomarkers peaking at day 1 post-immunization that correlates with adverse events, biological outcomes (haematological changes and viremia) and antibody titers. In this follow-up study, we sought to identify additional biomarkers in the same Geneva cohort and validate those identified markers in a US cohort.Methods: Additional biomarkers were identified using multiplexed protein biomarker platform O-link and confirmed by Luminex. Principal component analysis (PCA) evaluated if these markers could explain a higher variability of the vaccine response (and thereby refined the initial signature). Multivariable and linear regression models evaluated the correlations of the main components with adverse events, biological outcomes, and antibody titers. External validation of the refined signature was conducted in a second cohort of US vaccinees (n=142).Results: Eleven additional biomarkers peaked at day 1 post-immunization: MCP2, MCP3, MCP4, CXCL10, OSM, CX3CL1, MCSF, CXCL11, TRAIL, RANKL and IL15. PCA analysis retained three principal components (PC) that accounted for 79% of the vaccine response variability. PC1 and PC2 were very robust and had different biomarkers that contributed to their variability. PC1 better discriminated different doses, better defined the risk of fever and myalgia, while PC2 better defined the risk of headache. We also found new biomarkers that correlated with reactogenicity, including transient arthritis (MCP-2, CXCL10, CXCL11, CX3CL1, MCSF, IL-15, OSM). Several innate biomarkers are associated with antibody levels one and six months after vaccination. Refined PC1 correlated strongly in both data sets (Geneva: r = 0.97, P < 0.001; US: r = 0.99, P< 0.001).Conclusion: Eleven additional biomarkers refined the previously found 5-biomarker Geneva signature. The refined signature better discriminated between different doses, was strongly associated with the risk of adverse events and with antibody responses and was validated in a separate cohort.
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| 3. |
- Schuck, Sebastian D, et al.
(författare)
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Identification of T-cell antigens specific for latent mycobacterium tuberculosis infection
- 2009
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Ingår i: PLOS ONE. - San Fransisco, USA : Public Library Science. - 1932-6203. ; 4:5
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Tidskriftsartikel (refereegranskat)abstract
- Background: T-cell responses against dormancy-, resuscitation-, and reactivation-associated antigens of Mycobacterium tuberculosis are candidate biomarkers of latent infection in humans.Methodology/Principal findings: We established an assay based on two rounds of in vitro restimulation and intracellular cytokine analysis that detects T-cell responses to antigens expressed during latent M. tuberculosis infection. Comparison between active pulmonary tuberculosis (TB) patients and healthy latently M. tuberculosis-infected donors (LTBI) revealed significantly higher T-cell responses against 7 of 35 tested M. tuberculosis latency-associated antigens in LTBI. Notably, T cells specific for Rv3407 were exclusively detected in LTBI but not in TB patients. The T-cell IFNgamma response against Rv3407 in individual donors was the most influential factor in discrimination analysis that classified TB patients and LTBI with 83% accuracy using cross-validation. Rv3407 peptide pool stimulations revealed distinct candidate epitopes in four LTBI.Conclusions: Our findings further support the hypothesis that the latency-associated antigens can be exploited as biomarkers for LTBI.
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| 4. |
- Persson, Josefine, 1980, et al.
(författare)
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Stratification of COVID-19 patients based on quantitative immune-related gene expression in whole blood.
- 2022
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Ingår i: Molecular immunology. - : Elsevier BV. - 1872-9142 .- 0161-5890. ; 145, s. 17-26
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Tidskriftsartikel (refereegranskat)abstract
- The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes mild symptoms in the majority of infected individuals, yet in some cases it leads to a life-threatening condition. Determination of early predictive biomarkers enabling risk stratification for coronavirus disease 2019 (COVID-19) patients can inform treatment and intervention strategies. Herein, we analyzed whole blood samples obtained from individuals infected with SARS-CoV-2, varying from mild to critical symptoms, approximately one week after symptom onset. In order to identify blood-specific markers of disease severity status, a targeted expression analysis of 143 immune-related genes was carried out by dual-color reverse transcriptase multiplex ligation-dependent probe amplification (dcRT-MLPA). The clinically well-defined subgroups of COVID-19 patients were compared with healthy controls. The transcriptional profile of the critically ill patients clearly separated from that of healthy individuals. Moreover, the number of differentially expressed genes increased by severity of COVID-19. It was also found that critically ill patients can be distinguished by reduced peripheral blood expression of several genes, which most likely reflects the lower lymphocyte counts. There was a notable predominance of IFN-associated gene expression in all subgroups of COVID-19, which was most profound in critically ill patients. Interestingly, the gene encoding one of the main TNF-receptors, TNFRS1A, had selectively lower expression in mild COVID-19 cases. This report provides added value in understanding COVID-19 disease, and shows potential of determining early immune transcript signatures in the blood of patients with different disease severity. These results can guide further explorations to uncover mechanisms underlying immunity and immunopathology in COVID-19.
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| 5. |
- Vianello, Eleonora, et al.
(författare)
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Global blood miRNA profiling unravels early signatures of immunogenicity of Ebola vaccine rVSVΔG-ZEBOV-GP
- 2023
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Ingår i: iScience. - 2589-0042. ; 26:12
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Tidskriftsartikel (refereegranskat)abstract
- The vectored Ebola vaccine rVSVΔG-ZEBOV-GP elicits protection against Ebola Virus Disease (EVD). In a study of forty-eight healthy adult volunteers who received either the rVSVΔG-ZEBOV-GP vaccine or placebo, we profiled intracellular microRNAs (miRNAs) from whole blood cells (WB) and circulating miRNAs from serum-derived extracellular vesicles (EV) at baseline and longitudinally following vaccination. Further, we identified early miRNA signatures associated with ZEBOV-specific IgG antibody responses at baseline and up to one year post-vaccination, and pinpointed target mRNA transcripts and pathways correlated to miRNAs whose expression was altered after vaccination by using systems biology approaches. Several miRNAs were differentially expressed (DE) and miRNA signatures predicted high or low IgG ZEBOV-specific antibody levels with high classification performance. The top miRNA discriminators were WB-miR-6810, EV-miR-7151-3p, and EV-miR-4426. An eight-miRNA antibody predictive signature was associated with immune-related target mRNAs and pathways. These findings provide valuable insights into early blood biomarkers associated with rVSVΔG-ZEBOV-GP vaccine-induced IgG antibody responses.
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