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Doctoral Thesis
DOI
https://doi.org/10.11606/T.9.2021.tde-05082021-120102
Document
Author
Full name
Patrícia Conceição Gonzalez Dias Carvalho
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2021
Supervisor
Committee
Nakaya, Helder Takashi Imoto (President)
Ferreira, Daniela Mulari
Hashimoto, Ronaldo Fumio
Soares, Irene da Silva
Title in Portuguese
Vacinologia de Sistemas Aplicada à Vacina rVSV-ZEBOV contra Ebola
Keywords in Portuguese
Aprendizado de máquina
Ebola
Eventos adversos
Vacina
Vacina rVSV-ZEBOV
Abstract in Portuguese
A febre hemorrágica causada pelo vírus Ebola é uma doença grave com alta mortalidade, sendo a vacinação uma importante estratégia de intervenção. A rVSV-ZEBOV, uma vacina recombinante do vírus da estomatite vesicular (VSV) em que a glicoproteína de envelope é a do vírus Ebola da cepa Zaire, foi a primeira aprovada para uso clínico. Apesar de imunogênica e segura, a vacina é reatogênica podendo causar febre, calafrios, mialgia e artrite. Usando dados de transcriptoma do sangue nós realizamos análises de transcriptoma para compreender a resposta à vacina em diferentes tempos para 4 diferentes coortes. A partir dos mesmos dados obtidos antes da vacinação, nós identificamos conjuntos de genes preditores de eventos adversos relacionados à vacina rVSV-ZEBOV. Os dados foram obtidos por RNA-seq para 64 voluntários e por dual-color Reverse Transcriptase Multiplex Ligation-dependent Probe Amplification (dcRT-MLPA) para 375 voluntários entre vacinados e placebos. A identificação de genes preditores das reações adversas foi realizada utilizando o algoritmo Random Forest. Com o algoritmo "AdaBoost" obtivemos modelo capaz de predizer indivíduos com artrite, com valor preditivo positivo de 1 e valor preditivo negativo de 0.818, utilizando dados de expressão de apenas cinco genes. Este trabalho foi importante para compreender melhor a resposta induzida pela vacina rVSV-ZEBOV e identificar genes possivelmente relacionados à predisposição das pessoas a desenvolver reatogenicidade pós vacinal.
Title in English
Systems Vaccinology of rVSV-ZEBOV Ebola Vaccine
Keywords in English
Adverse events
Ebola
Machine Learning
rVSV-ZEBOV vaccine
Vaccine
Abstract in English
Hemorrhagic fever caused by the Ebola virus is a high mortality disease, and vaccination is an important intervention strategy. The rVSV-ZEBOV, a recombinant vesicular stomatitis virus (VSV) vaccine in which the envelope glycoprotein is that of the Ebola virus of the Zaire strain, was the first one to be approved for medical use. Although immunogenic and safe, the vaccine is very reactogenic and can cause fever, chills, myalgia and arthritis. From blood transcriptome data we performed transcriptome analysis to understand the response to the vaccine at different time points for 4 different cohorts. With the same data obtained before vaccination, we identified sets of genes that predict adverse events related to the rVSV-ZEBOV vaccine. Data were obtained by RNA-seq for 64 volunteers and by dual-color Reverse Transcriptase Multiplex Ligation-dependent Probe Amplification (dcRT-MLPA) for 375 volunteers. The identification of predictor genes was performed with Random Forest Algorithm. Using the "AdaBoost'' algorithm, we selected a model capable of predicting individuals with arthritis, with positive predictive value of 1, and negative predictive value of 0.818 based on expression data from only five genes. This work was important to better understand the response induced by the rVSV-ZEBOV vaccine and to identify genes possibly related to people's predisposition to develop post-vaccine reactogenicity.
 
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Publishing Date
2021-08-11
 
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