Estimating Clinically Relevant Cut-Off Values for a High-Throughput Quantitative Real-Time PCR Detecting Bacterial Respiratory Pathogens in Cattle
Bovine respiratory disease (BRD) results from interactions between pathogens, environmental stressors, and host factors. Obtaining a diagnosis of the causal pathogens is challenging but the use of high-throughput real-time PCR (rtPCR) may help target preventive and therapeutic interventions. The aim...
Main Authors: | , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2021-05-01
|
Series: | Frontiers in Veterinary Science |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fvets.2021.674771/full |
id |
doaj-2acc7db2fa0649b6828285f8d93905ef |
---|---|
record_format |
Article |
spelling |
doaj-2acc7db2fa0649b6828285f8d93905ef2021-05-25T05:13:05ZengFrontiers Media S.A.Frontiers in Veterinary Science2297-17692021-05-01810.3389/fvets.2021.674771674771Estimating Clinically Relevant Cut-Off Values for a High-Throughput Quantitative Real-Time PCR Detecting Bacterial Respiratory Pathogens in CattleAlicia F. Klompmaker0Maria Brydensholt1Anne Marie Michelsen2Matthew J. Denwood3Carsten T. Kirkeby4Lars Erik Larsen5Nicole B. Goecke6Nicole B. Goecke7Nina D. Otten8Liza R. Nielsen9Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkCentre for Diagnostics, Technical University of Denmark, Kongens Lyngby, DenmarkDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkBovine respiratory disease (BRD) results from interactions between pathogens, environmental stressors, and host factors. Obtaining a diagnosis of the causal pathogens is challenging but the use of high-throughput real-time PCR (rtPCR) may help target preventive and therapeutic interventions. The aim of this study was to improve the interpretation of rtPCR results by analysing their associations with clinical observations. The objective was to develop and illustrate a field-data driven statistical method to guide the selection of relevant quantification cycle cut-off values for pathogens associated with BRD for the high-throughput rtPCR system “Fluidigm BioMark HD” based on nasal swabs from calves. We used data from 36 herds enrolled in a Danish field study where 340 calves within pre-determined age-groups were subject to clinical examination and nasal swabs up to four times. The samples were analysed with the rtPCR system. Each of the 1,025 observation units were classified as sick with BRD or healthy, based on clinical scores. The optimal rtPCR results to predict BRD were investigated for Pasteurella multocida, Mycoplasma bovis, Histophilus somni, Mannheimia haemolytica, and Trueperella pyogenes by interpreting scatterplots and results of mixed effects logistic regression models. The clinically relevant rtPCR cut-off suggested for P. multocida and M. bovis was ≤ 21.3. For H. somni it was ≤ 17.4, while no cut-off could be determined for M. haemolytica and T. pyogenes. The demonstrated approach can provide objective support in the choice of clinically relevant cut-offs. However, for robust performance of the regression model sufficient amounts of suitable data are required.https://www.frontiersin.org/articles/10.3389/fvets.2021.674771/fullbovine respiratory diseasecalfdiagnosticsnasal swabrtPCRclinically relevant cut-off |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alicia F. Klompmaker Maria Brydensholt Anne Marie Michelsen Matthew J. Denwood Carsten T. Kirkeby Lars Erik Larsen Nicole B. Goecke Nicole B. Goecke Nina D. Otten Liza R. Nielsen |
spellingShingle |
Alicia F. Klompmaker Maria Brydensholt Anne Marie Michelsen Matthew J. Denwood Carsten T. Kirkeby Lars Erik Larsen Nicole B. Goecke Nicole B. Goecke Nina D. Otten Liza R. Nielsen Estimating Clinically Relevant Cut-Off Values for a High-Throughput Quantitative Real-Time PCR Detecting Bacterial Respiratory Pathogens in Cattle Frontiers in Veterinary Science bovine respiratory disease calf diagnostics nasal swab rtPCR clinically relevant cut-off |
author_facet |
Alicia F. Klompmaker Maria Brydensholt Anne Marie Michelsen Matthew J. Denwood Carsten T. Kirkeby Lars Erik Larsen Nicole B. Goecke Nicole B. Goecke Nina D. Otten Liza R. Nielsen |
author_sort |
Alicia F. Klompmaker |
title |
Estimating Clinically Relevant Cut-Off Values for a High-Throughput Quantitative Real-Time PCR Detecting Bacterial Respiratory Pathogens in Cattle |
title_short |
Estimating Clinically Relevant Cut-Off Values for a High-Throughput Quantitative Real-Time PCR Detecting Bacterial Respiratory Pathogens in Cattle |
title_full |
Estimating Clinically Relevant Cut-Off Values for a High-Throughput Quantitative Real-Time PCR Detecting Bacterial Respiratory Pathogens in Cattle |
title_fullStr |
Estimating Clinically Relevant Cut-Off Values for a High-Throughput Quantitative Real-Time PCR Detecting Bacterial Respiratory Pathogens in Cattle |
title_full_unstemmed |
Estimating Clinically Relevant Cut-Off Values for a High-Throughput Quantitative Real-Time PCR Detecting Bacterial Respiratory Pathogens in Cattle |
title_sort |
estimating clinically relevant cut-off values for a high-throughput quantitative real-time pcr detecting bacterial respiratory pathogens in cattle |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Veterinary Science |
issn |
2297-1769 |
publishDate |
2021-05-01 |
description |
Bovine respiratory disease (BRD) results from interactions between pathogens, environmental stressors, and host factors. Obtaining a diagnosis of the causal pathogens is challenging but the use of high-throughput real-time PCR (rtPCR) may help target preventive and therapeutic interventions. The aim of this study was to improve the interpretation of rtPCR results by analysing their associations with clinical observations. The objective was to develop and illustrate a field-data driven statistical method to guide the selection of relevant quantification cycle cut-off values for pathogens associated with BRD for the high-throughput rtPCR system “Fluidigm BioMark HD” based on nasal swabs from calves. We used data from 36 herds enrolled in a Danish field study where 340 calves within pre-determined age-groups were subject to clinical examination and nasal swabs up to four times. The samples were analysed with the rtPCR system. Each of the 1,025 observation units were classified as sick with BRD or healthy, based on clinical scores. The optimal rtPCR results to predict BRD were investigated for Pasteurella multocida, Mycoplasma bovis, Histophilus somni, Mannheimia haemolytica, and Trueperella pyogenes by interpreting scatterplots and results of mixed effects logistic regression models. The clinically relevant rtPCR cut-off suggested for P. multocida and M. bovis was ≤ 21.3. For H. somni it was ≤ 17.4, while no cut-off could be determined for M. haemolytica and T. pyogenes. The demonstrated approach can provide objective support in the choice of clinically relevant cut-offs. However, for robust performance of the regression model sufficient amounts of suitable data are required. |
topic |
bovine respiratory disease calf diagnostics nasal swab rtPCR clinically relevant cut-off |
url |
https://www.frontiersin.org/articles/10.3389/fvets.2021.674771/full |
work_keys_str_mv |
AT aliciafklompmaker estimatingclinicallyrelevantcutoffvaluesforahighthroughputquantitativerealtimepcrdetectingbacterialrespiratorypathogensincattle AT mariabrydensholt estimatingclinicallyrelevantcutoffvaluesforahighthroughputquantitativerealtimepcrdetectingbacterialrespiratorypathogensincattle AT annemariemichelsen estimatingclinicallyrelevantcutoffvaluesforahighthroughputquantitativerealtimepcrdetectingbacterialrespiratorypathogensincattle AT matthewjdenwood estimatingclinicallyrelevantcutoffvaluesforahighthroughputquantitativerealtimepcrdetectingbacterialrespiratorypathogensincattle AT carstentkirkeby estimatingclinicallyrelevantcutoffvaluesforahighthroughputquantitativerealtimepcrdetectingbacterialrespiratorypathogensincattle AT larseriklarsen estimatingclinicallyrelevantcutoffvaluesforahighthroughputquantitativerealtimepcrdetectingbacterialrespiratorypathogensincattle AT nicolebgoecke estimatingclinicallyrelevantcutoffvaluesforahighthroughputquantitativerealtimepcrdetectingbacterialrespiratorypathogensincattle AT nicolebgoecke estimatingclinicallyrelevantcutoffvaluesforahighthroughputquantitativerealtimepcrdetectingbacterialrespiratorypathogensincattle AT ninadotten estimatingclinicallyrelevantcutoffvaluesforahighthroughputquantitativerealtimepcrdetectingbacterialrespiratorypathogensincattle AT lizarnielsen estimatingclinicallyrelevantcutoffvaluesforahighthroughputquantitativerealtimepcrdetectingbacterialrespiratorypathogensincattle |
_version_ |
1721427847472480256 |