Quantitative analysis of porcine reproductive and respiratory syndrome (PRRS) viremia profiles from experimental infection: a statistical modelling approach.

Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically significant viral diseases facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of infection within the host and provide crucial information for subse...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Zeenath U Islam, Stephen C Bishop, Nicholas J Savill, Raymond R R Rowland, Joan K Lunney, Benjamin Trible, Andrea B Doeschl-Wilson
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d51c5a6cd7e54c6abd168553eaadc3d9
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:d51c5a6cd7e54c6abd168553eaadc3d9
record_format	dspace
spelling	oai:doaj.org-article:d51c5a6cd7e54c6abd168553eaadc3d92021-11-18T08:41:34ZQuantitative analysis of porcine reproductive and respiratory syndrome (PRRS) viremia profiles from experimental infection: a statistical modelling approach.1932-620310.1371/journal.pone.0083567https://doaj.org/article/d51c5a6cd7e54c6abd168553eaadc3d92013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24358295/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically significant viral diseases facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of infection within the host and provide crucial information for subsequent control measures. In this study we analyse the largest longitudinal PRRS viremia dataset from an in-vivo experiment. The primary objective was to provide a suitable mathematical description of all viremia profiles with biologically meaningful parameters for quantitative analysis of profile characteristics. The Wood's function, a gamma-type function, and a biphasic extended Wood's function were fit to the individual profiles using Bayesian inference with a likelihood framework. Using maximum likelihood inference and numerous fit criteria, we established that the broad spectrum of viremia trends could be adequately represented by either uni- or biphasic Wood's functions. Three viremic categories emerged: cleared (uni-modal and below detection within 42 days post infection(dpi)), persistent (transient experimental persistence over 42 dpi) and rebound (biphasic within 42 dpi). The convenient biological interpretation of the model parameters estimates, allowed us not only to quantify inter-host variation, but also to establish common viremia curve characteristics and their predictability. Statistical analysis of the profile characteristics revealed that persistent profiles were distinguishable already within the first 21 dpi, whereas it is not possible to predict the onset of viremia rebound. Analysis of the neutralizing antibody(nAb) data indicated that there was a ubiquitous strong response to the homologous PRRSV challenge, but high variability in the range of cross-protection of the nAbs. Persistent pigs were found to have a significantly higher nAb cross-protectivity than pigs that either cleared viremia or experienced rebound within 42 dpi. Our study provides novel insights into the nature and degree of variation of hosts' responses to infection as well as new informative traits for subsequent genomic and modelling studies.Zeenath U IslamStephen C BishopNicholas J SavillRaymond R R RowlandJoan K LunneyBenjamin TribleAndrea B Doeschl-WilsonPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 12, p e83567 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Zeenath U Islam Stephen C Bishop Nicholas J Savill Raymond R R Rowland Joan K Lunney Benjamin Trible Andrea B Doeschl-Wilson Quantitative analysis of porcine reproductive and respiratory syndrome (PRRS) viremia profiles from experimental infection: a statistical modelling approach.
description	Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically significant viral diseases facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of infection within the host and provide crucial information for subsequent control measures. In this study we analyse the largest longitudinal PRRS viremia dataset from an in-vivo experiment. The primary objective was to provide a suitable mathematical description of all viremia profiles with biologically meaningful parameters for quantitative analysis of profile characteristics. The Wood's function, a gamma-type function, and a biphasic extended Wood's function were fit to the individual profiles using Bayesian inference with a likelihood framework. Using maximum likelihood inference and numerous fit criteria, we established that the broad spectrum of viremia trends could be adequately represented by either uni- or biphasic Wood's functions. Three viremic categories emerged: cleared (uni-modal and below detection within 42 days post infection(dpi)), persistent (transient experimental persistence over 42 dpi) and rebound (biphasic within 42 dpi). The convenient biological interpretation of the model parameters estimates, allowed us not only to quantify inter-host variation, but also to establish common viremia curve characteristics and their predictability. Statistical analysis of the profile characteristics revealed that persistent profiles were distinguishable already within the first 21 dpi, whereas it is not possible to predict the onset of viremia rebound. Analysis of the neutralizing antibody(nAb) data indicated that there was a ubiquitous strong response to the homologous PRRSV challenge, but high variability in the range of cross-protection of the nAbs. Persistent pigs were found to have a significantly higher nAb cross-protectivity than pigs that either cleared viremia or experienced rebound within 42 dpi. Our study provides novel insights into the nature and degree of variation of hosts' responses to infection as well as new informative traits for subsequent genomic and modelling studies.
format	article
author	Zeenath U Islam Stephen C Bishop Nicholas J Savill Raymond R R Rowland Joan K Lunney Benjamin Trible Andrea B Doeschl-Wilson
author_facet	Zeenath U Islam Stephen C Bishop Nicholas J Savill Raymond R R Rowland Joan K Lunney Benjamin Trible Andrea B Doeschl-Wilson
author_sort	Zeenath U Islam
title	Quantitative analysis of porcine reproductive and respiratory syndrome (PRRS) viremia profiles from experimental infection: a statistical modelling approach.
title_short	Quantitative analysis of porcine reproductive and respiratory syndrome (PRRS) viremia profiles from experimental infection: a statistical modelling approach.
title_full	Quantitative analysis of porcine reproductive and respiratory syndrome (PRRS) viremia profiles from experimental infection: a statistical modelling approach.
title_fullStr	Quantitative analysis of porcine reproductive and respiratory syndrome (PRRS) viremia profiles from experimental infection: a statistical modelling approach.
title_full_unstemmed	Quantitative analysis of porcine reproductive and respiratory syndrome (PRRS) viremia profiles from experimental infection: a statistical modelling approach.
title_sort	quantitative analysis of porcine reproductive and respiratory syndrome (prrs) viremia profiles from experimental infection: a statistical modelling approach.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/d51c5a6cd7e54c6abd168553eaadc3d9
work_keys_str_mv	AT zeenathuislam quantitativeanalysisofporcinereproductiveandrespiratorysyndromeprrsviremiaprofilesfromexperimentalinfectionastatisticalmodellingapproach AT stephencbishop quantitativeanalysisofporcinereproductiveandrespiratorysyndromeprrsviremiaprofilesfromexperimentalinfectionastatisticalmodellingapproach AT nicholasjsavill quantitativeanalysisofporcinereproductiveandrespiratorysyndromeprrsviremiaprofilesfromexperimentalinfectionastatisticalmodellingapproach AT raymondrrrowland quantitativeanalysisofporcinereproductiveandrespiratorysyndromeprrsviremiaprofilesfromexperimentalinfectionastatisticalmodellingapproach AT joanklunney quantitativeanalysisofporcinereproductiveandrespiratorysyndromeprrsviremiaprofilesfromexperimentalinfectionastatisticalmodellingapproach AT benjamintrible quantitativeanalysisofporcinereproductiveandrespiratorysyndromeprrsviremiaprofilesfromexperimentalinfectionastatisticalmodellingapproach AT andreabdoeschlwilson quantitativeanalysisofporcinereproductiveandrespiratorysyndromeprrsviremiaprofilesfromexperimentalinfectionastatisticalmodellingapproach
_version_	1718421471601098752

Quantitative analysis of porcine reproductive and respiratory syndrome (PRRS) viremia profiles from experimental infection: a statistical modelling approach.

Ejemplares similares