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Exploring the molecular causes of hepatitis B virus vaccination response: an approach with epigenomic and transcriptomic data

BACKGROUND: Variable responses to the Hepatitis B Virus (HBV) vaccine have recently been reported as strongly dependent on genetic causes. Yet, the details on such mechanisms of action are still unknown. In parallel, altered DNA methylation states have been uncovered as important contributors to a v...

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Autores principales: Lu, Youtao, Cheng, Yi, Yan, Weili, Nardini, Christine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4008305/
https://www.ncbi.nlm.nih.gov/pubmed/24612962
http://dx.doi.org/10.1186/1755-8794-7-12
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author Lu, Youtao
Cheng, Yi
Yan, Weili
Nardini, Christine
author_facet Lu, Youtao
Cheng, Yi
Yan, Weili
Nardini, Christine
author_sort Lu, Youtao
collection PubMed
description BACKGROUND: Variable responses to the Hepatitis B Virus (HBV) vaccine have recently been reported as strongly dependent on genetic causes. Yet, the details on such mechanisms of action are still unknown. In parallel, altered DNA methylation states have been uncovered as important contributors to a variety of health conditions. However, methodologies for the analysis of such high-throughput data (epigenomic), especially from the computational point of view, still lack of a gold standard, mostly due to the intrinsic statistical distribution of methylomic data i.e. binomial rather than (pseudo-) normal, which characterizes the better known transcriptomic data. We present in this article our contribution to the challenge of epigenomic data analysis with application to the variable response to the Hepatitis B virus (HBV) vaccine and its most lethal degeneration: hepatocellular carcinoma (HCC). METHODS: Twenty-five infants were recruited and classified as good and non-/low- responders according to serological test results. Whole genome DNA methylation states were profiled by Illumina HumanMethylation 450 K beadchips. Data were processed through quality and dispersion filtering and with differential methylation analysis based on a combination of average methylation differences and non-parametric statistical tests. Results were finally associated to already published transcriptomics and post-transcriptomics to gain further insight. RESULTS: We highlight 2 relevant variations in poor-responders to HBV vaccination: the hypomethylation of RNF39 (Ring Finger Protein 39) and the complex biochemical alteration on SULF2 via hypermethylation, down-regulation and post-transcriptional control. CONCLUSIONS: Our approach appears to cope with the new challenges implied by methylomic data distribution to warrant a robust ranking of candidates. In particular, being RNF39 within the Major Histocompatibility Complex (MHC) class I region, its altered methylation state fits with an altered immune reaction compatible with poor responsiveness to vaccination. Additionally, despite SULF2 having been indicated as a potential target for HCC therapy, we can recommend that non-responders to HBV vaccine who develop HCC are quickly directed to other therapies, as SULF2 appears to be already under multiple molecular controls in such patients. Future research in this direction is warranted.
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spelling pubmed-40083052014-05-19 Exploring the molecular causes of hepatitis B virus vaccination response: an approach with epigenomic and transcriptomic data Lu, Youtao Cheng, Yi Yan, Weili Nardini, Christine BMC Med Genomics Research Article BACKGROUND: Variable responses to the Hepatitis B Virus (HBV) vaccine have recently been reported as strongly dependent on genetic causes. Yet, the details on such mechanisms of action are still unknown. In parallel, altered DNA methylation states have been uncovered as important contributors to a variety of health conditions. However, methodologies for the analysis of such high-throughput data (epigenomic), especially from the computational point of view, still lack of a gold standard, mostly due to the intrinsic statistical distribution of methylomic data i.e. binomial rather than (pseudo-) normal, which characterizes the better known transcriptomic data. We present in this article our contribution to the challenge of epigenomic data analysis with application to the variable response to the Hepatitis B virus (HBV) vaccine and its most lethal degeneration: hepatocellular carcinoma (HCC). METHODS: Twenty-five infants were recruited and classified as good and non-/low- responders according to serological test results. Whole genome DNA methylation states were profiled by Illumina HumanMethylation 450 K beadchips. Data were processed through quality and dispersion filtering and with differential methylation analysis based on a combination of average methylation differences and non-parametric statistical tests. Results were finally associated to already published transcriptomics and post-transcriptomics to gain further insight. RESULTS: We highlight 2 relevant variations in poor-responders to HBV vaccination: the hypomethylation of RNF39 (Ring Finger Protein 39) and the complex biochemical alteration on SULF2 via hypermethylation, down-regulation and post-transcriptional control. CONCLUSIONS: Our approach appears to cope with the new challenges implied by methylomic data distribution to warrant a robust ranking of candidates. In particular, being RNF39 within the Major Histocompatibility Complex (MHC) class I region, its altered methylation state fits with an altered immune reaction compatible with poor responsiveness to vaccination. Additionally, despite SULF2 having been indicated as a potential target for HCC therapy, we can recommend that non-responders to HBV vaccine who develop HCC are quickly directed to other therapies, as SULF2 appears to be already under multiple molecular controls in such patients. Future research in this direction is warranted. BioMed Central 2014-03-11 /pmc/articles/PMC4008305/ /pubmed/24612962 http://dx.doi.org/10.1186/1755-8794-7-12 Text en Copyright © 2014 Lu et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Lu, Youtao
Cheng, Yi
Yan, Weili
Nardini, Christine
Exploring the molecular causes of hepatitis B virus vaccination response: an approach with epigenomic and transcriptomic data
title Exploring the molecular causes of hepatitis B virus vaccination response: an approach with epigenomic and transcriptomic data
title_full Exploring the molecular causes of hepatitis B virus vaccination response: an approach with epigenomic and transcriptomic data
title_fullStr Exploring the molecular causes of hepatitis B virus vaccination response: an approach with epigenomic and transcriptomic data
title_full_unstemmed Exploring the molecular causes of hepatitis B virus vaccination response: an approach with epigenomic and transcriptomic data
title_short Exploring the molecular causes of hepatitis B virus vaccination response: an approach with epigenomic and transcriptomic data
title_sort exploring the molecular causes of hepatitis b virus vaccination response: an approach with epigenomic and transcriptomic data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4008305/
https://www.ncbi.nlm.nih.gov/pubmed/24612962
http://dx.doi.org/10.1186/1755-8794-7-12
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