Transcriptome profiling in blood before and after hepatitis B vaccination shows significant differences in gene expression between responders and non-responders

Bartholomeus, Esther; Neuter, Nicolas De; Meysman, Pieter; Suls, Arvid; Keersmaekers, Nina; Elias, George; Jansens, Hilde; Hens, Niel; Smits, Evelien; Tendeloo, Viggo Van; Beutels, Philippe; Damme, Pierre Van; Ogunjimi, Benson; Laukens, Kris; Mortier, Geert

doi:10.1016/j.vaccine.2018.09.001

Cited by 45 publications

(46 citation statements)

References 28 publications

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“…Overall these results suggest that this in vitro stimulation approach in combination with others in vitro tests recently described ( 34 ) may provide important information in term of prediction of vaccine responsiveness and early pre-clinical selection of effective vaccine candidates for VPs. Our data may thus confirm that gene expression after a relatively short (16 h) in vitro stimulation may emulate early transcriptional changes that were analyzed in vivo both in mice ( 35 ) and in humans ( 36 , 37 ). Early transcriptional changes, derived from whole transcriptome sequencing from blood samples collected at day 0, 1, 3, and 7 after immunization were shown to be informative in predicting long-term humoral and cell mediated responses to Hepatitis B, Ebola ( 38 ) and yellow fever ( 36 ) vaccinations.…”

Section: Discussionsupporting

confidence: 81%

Artificial Intelligence Applied to in vitro Gene Expression Testing (IVIGET) to Predict Trivalent Inactivated Influenza Vaccine Immunogenicity in HIV Infected Children

et al. 2020

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The number of patients affected by chronic diseases with special vaccination needs is burgeoning. In this scenario, predictive markers of immunogenicity, as well as signatures of immune responses are typically missing even though it would especially improve the identification of personalized immunization practices in these populations. We aimed to develop a predictive score of immunogenicity to Influenza Trivalent Inactivated Vaccination (TIV) by applying deep machine learning algorithms using transcriptional data from sort-purified lymphocyte subsets after in vitro stimulation. Peripheral blood mononuclear cells (PBMCs) collected before TIV from 23 vertically HIV infected children under ART and virally controlled were stimulated in vitro with p09/H1N1 peptides (stim) or left unstimulated (med). A multiplexed-qPCR for 96 genes was made on fixed numbers of 3 B cell subsets, 3 T cell subsets and total PBMCs. The ability to respond to TIV was assessed through hemagglutination Inhibition Assay (HIV) and ELIspot and patients were classified as Responders (R) and Non Responders (NR). A predictive modeling framework was applied to the data set in order to define genes and conditions with the higher predicted probability able to inform the final score. Twelve NR and 11 R were analyzed for gene expression differences in all subsets and 3 conditions [med, stim or Δ (stim-med)]. Differentially expressed genes between R and NR were selected and tested with the Adaptive Boosting Model to build a prediction score. The score obtained from subsets revealed the best prediction score from 46 genes from 5 different subsets and conditions. Calculating a combined score based on these 5 categories, we achieved a model accuracy of 95.6% and only one misclassified patient. These data show how a predictive bioinformatic model applied to transcriptional analysis deriving from in-vitro stimulated lymphocytes subsets may predict poor or protective vaccination immune response in vulnerable populations, such as HIV-infected individuals. Future studies on larger cohorts are needed to validate such strategy in the context of vaccination trials.

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Section: Discussionsupporting

confidence: 81%

Artificial Intelligence Applied to in vitro Gene Expression Testing (IVIGET) to Predict Trivalent Inactivated Influenza Vaccine Immunogenicity in HIV Infected Children

et al. 2020

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“…There is accumulating evidence that increased chronic background levels of inflammation might be detrimental for vaccine responses (76)(77)(78)(79)(80)(81). Nakaya et al investigated gene signatures predictive of influenza vaccine responses in young and old adults and found that pre-vaccination signatures associated with T and B-cell function were positively correlated with antibody responses at day 28 after vaccination, while monocyte-and inflammation-related genes were negatively correlated with antibody responses (76).…”

Section: Inflammagingmentioning

confidence: 99%

“…Nakaya et al investigated gene signatures predictive of influenza vaccine responses in young and old adults and found that pre-vaccination signatures associated with T and B-cell function were positively correlated with antibody responses at day 28 after vaccination, while monocyte-and inflammation-related genes were negatively correlated with antibody responses (76). Similarly, studies on HBV vaccination in the elderly revealed that a more pronounced inflammatory gene expression profile at baseline predicted a poorer response to vaccination (77,78). Our group has shown that older individuals exhibit reduced cutaneous immunity to varicella zoster virus recall antigen challenge associated with increased baseline local inflammation (79).…”

Section: Inflammagingmentioning

confidence: 99%

“…Furthermore there is a growing appreciation that pre-existing inflammation may be a determinant of vaccine responsiveness and thus modulating baseline inflammation prior to vaccination has become an attractive area of research to boost vaccine responses ( 16 , 83 , 171 ). Using high-throughput technology researchers have identified baseline transcriptional signatures that predict protective immune responses to vaccines ( 76 , 78 – 81 ). Most of the signatures identified so far are indicative of broad immune activation and excessive inflammation.…”

Section: Novel Strategies For Enhancing Vaccine Responsesmentioning

confidence: 99%

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Targeting Inflammation and Immunosenescence to Improve Vaccine Responses in the Elderly

2020

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One of the most appreciated consequences of immunosenescence is an impaired response to vaccines with advanced age. While most studies report impaired antibody responses in older adults as a correlate of vaccine efficacy, it is now widely appreciated that this may fail to identify important changes occurring in the immune system with age that may affect vaccine efficacy. The impact of immunosenescence on vaccination goes beyond the defects on antibody responses as T cell-mediated responses are reshaped during aging and certainly affect vaccination. Likewise, age-related changes in the innate immune system may have important consequences on antigen presentation and priming of adaptive immune responses. Importantly, a low-level chronic inflammatory status known as inflammaging has been shown to inhibit immune responses to vaccination and pharmacological strategies aiming at blocking baseline inflammation can be potentially used to boost vaccine responses. Yet current strategies aiming at improving immunogenicity in the elderly have mainly focused on the use of adjuvants to promote local inflammation. More research is needed to understand the role of inflammation in vaccine responses and to reconcile these seemingly paradoxical observations. Alternative approaches to improve vaccine responses in the elderly include the use of higher vaccine doses or alternative routes of vaccination showing only limited benefits. This review will explore novel targets and potential new strategies for enhancing vaccine responses in older adults, including the use of anti-inflammatory drugs and immunomodulators.

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“…Within human and livestock populations, biomarkers capable of predicting vaccine immunogenicity and efficacy could be used to reduce the costs associated with vaccine production and testing 4 . This need has spawned 'systems vaccinology' approaches that define the host factors contributing to immune responses to a variety of vaccines [5][6][7][8][9] . As vaccine-induced immune responses have shown significant heritability in animals 10 , identifying traits indicative of immune responsiveness could likely be applied for marker-assisted selection of animals 11 .…”

mentioning

confidence: 99%

Kinome profiling of peripheral blood mononuclear cells collected prior to vaccination reveals biomarkers and potential mechanisms of vaccine unresponsiveness in pigs

Lipsit

Wilkinson

Scruten

et al. 2020

Sci Rep

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Inter-individual variance in host immune responses following vaccination can result in failure to develop protective immunity leaving individuals at risk for infection in addition to compromising herd immunity. While developing more efficacious vaccines is one strategy to mitigate this problem, predicting vaccine responsiveness prior to vaccination could inform which individuals require adjunct disease management strategies. To identify biomarkers of vaccine responsiveness, a cohort of pigs (n = 120) were vaccinated and pigs representing the high (n = 6; 90th percentile) and low (n = 6; 10th percentile) responders based on vaccine-specific antibody responses following vaccination were further analyzed. Kinase-mediated phosphorylation events within peripheral blood mononuclear cells collected prior to vaccination identified 53 differentially phosphorylated peptides when comparing low responders with high responders. Functional enrichment analysis revealed pro-inflammatory cytokine signaling pathways as dysregulated, and this was further substantiated by detection of higher (p < 0.01) concentrations of interferon-gamma in plasma of low responders compared to high responders prior to vaccination. In addition, low responder pigs with high plasma interferon-gamma showed lower (p < 0.01) birth weights than high responder pigs. These associations between vaccine responsiveness, cytokine signaling within peripheral immune cells, and body weight in pigs provide both evidence and insight into potential biomarkers for identifying low responders to vaccination.

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Transcriptome profiling in blood before and after hepatitis B vaccination shows significant differences in gene expression between responders and non-responders

Cited by 45 publications

References 28 publications

Artificial Intelligence Applied to in vitro Gene Expression Testing (IVIGET) to Predict Trivalent Inactivated Influenza Vaccine Immunogenicity in HIV Infected Children

Artificial Intelligence Applied to in vitro Gene Expression Testing (IVIGET) to Predict Trivalent Inactivated Influenza Vaccine Immunogenicity in HIV Infected Children

Targeting Inflammation and Immunosenescence to Improve Vaccine Responses in the Elderly

Kinome profiling of peripheral blood mononuclear cells collected prior to vaccination reveals biomarkers and potential mechanisms of vaccine unresponsiveness in pigs

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