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Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS‐CoV‐2 variants

INTRODUCTION: The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) pandemic revealed a worldwide lack of effective molecular surveillance networks at local, state, and national levels, which are essential to identify, monitor, and limit viral community spread. SARS‐CoV‐2 variants of conc...

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Autores principales: Guerrero‐Preston, Rafael, Rivera‐Amill, Vanessa, Caraballo, Karem, Rodríguez‐Torres, Sebastian, Purcell‐Wiltz, Ana, García, Andrea A., Torres, Raphael S., Zamuner, Fernando T., Zanettini, Claudio, MacKay, Matthew J., Baits, Rachel, Salgado, Daisy, Khullar, Gaurav, Metti, Jessica, Baker, Timothy, Dudley, Joel, Vale, Keilyn, Pérez, Gabriela, De Jesús, Lorena, Miranda, Yaima, Ortiz, Denise, García‐Negrón, Amanda, Viera, Liliana, Ortiz, Alberto, Canabal, Jorge A., Romaguera, Josefina, Jiménez‐Velázquez, Ivonne, Marchionni, Luigi, Rodríguez‐Orengo, José F., Baez, Adriana, Mason, Christopher E., Sidransky, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092005/
https://www.ncbi.nlm.nih.gov/pubmed/35634961
http://dx.doi.org/10.1002/iid3.634
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author Guerrero‐Preston, Rafael
Rivera‐Amill, Vanessa
Caraballo, Karem
Rodríguez‐Torres, Sebastian
Purcell‐Wiltz, Ana
García, Andrea A.
Torres, Raphael S.
Zamuner, Fernando T.
Zanettini, Claudio
MacKay, Matthew J.
Baits, Rachel
Salgado, Daisy
Khullar, Gaurav
Metti, Jessica
Baker, Timothy
Dudley, Joel
Vale, Keilyn
Pérez, Gabriela
De Jesús, Lorena
Miranda, Yaima
Ortiz, Denise
García‐Negrón, Amanda
Viera, Liliana
Ortiz, Alberto
Canabal, Jorge A.
Romaguera, Josefina
Jiménez‐Velázquez, Ivonne
Marchionni, Luigi
Rodríguez‐Orengo, José F.
Baez, Adriana
Mason, Christopher E.
Sidransky, David
author_facet Guerrero‐Preston, Rafael
Rivera‐Amill, Vanessa
Caraballo, Karem
Rodríguez‐Torres, Sebastian
Purcell‐Wiltz, Ana
García, Andrea A.
Torres, Raphael S.
Zamuner, Fernando T.
Zanettini, Claudio
MacKay, Matthew J.
Baits, Rachel
Salgado, Daisy
Khullar, Gaurav
Metti, Jessica
Baker, Timothy
Dudley, Joel
Vale, Keilyn
Pérez, Gabriela
De Jesús, Lorena
Miranda, Yaima
Ortiz, Denise
García‐Negrón, Amanda
Viera, Liliana
Ortiz, Alberto
Canabal, Jorge A.
Romaguera, Josefina
Jiménez‐Velázquez, Ivonne
Marchionni, Luigi
Rodríguez‐Orengo, José F.
Baez, Adriana
Mason, Christopher E.
Sidransky, David
author_sort Guerrero‐Preston, Rafael
collection PubMed
description INTRODUCTION: The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) pandemic revealed a worldwide lack of effective molecular surveillance networks at local, state, and national levels, which are essential to identify, monitor, and limit viral community spread. SARS‐CoV‐2 variants of concern (VOCs) such as Alpha and Omicron, which show increased transmissibility and immune evasion, rapidly became dominant VOCs worldwide. Our objective was to develop an evidenced‐based genomic surveillance algorithm, combining reverse transcription polymerase chain reaction (RT‐PCR) and sequencing technologies to quickly identify highly contagious VOCs, before cases accumulate exponentially. METHODS: Deidentified data were obtained from 508,969 patients tested for coronavirus disease 2019 (COVID‐19) with the TaqPath COVID‐19 RT‐PCR Combo Kit (ThermoFisher) in four CLIA‐certified clinical laboratories in Puerto Rico (n = 86,639) and in three CLIA‐certified clinical laboratories in the United States (n = 422,330). RESULTS: TaqPath data revealed a frequency of S Gene Target Failure (SGTF) > 47% for the last week of March 2021 in both, Puerto Rico and US laboratories. The monthly frequency of SGTF in Puerto Rico steadily increased exponentially from 4% in November 2020 to 47% in March 2021. The weekly SGTF rate in US samples was high (>8%) from late December to early January and then also increased exponentially through April (48%). The exponential increase in SGFT prevalence in Puerto Rico was concurrent with a sharp increase in VOCs among all SARS‐CoV‐2 sequences from Puerto Rico uploaded to Global Influenza Surveillance and Response System (GISAID) (n = 461). Alpha variant frequency increased from <1% in the last week of January 2021 to 51.5% of viral sequences from Puerto Rico collected in the last week of March 2021. CONCLUSIONS: According to the proposed evidence‐based algorithm, approximately 50% of all SGTF patients should be managed with VOCs self‐quarantine and contact tracing protocols, while WGS confirms their lineage in genomic surveillance laboratories. Our results suggest this workflow is useful for tracking VOCs with SGTF.
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spelling pubmed-90920052022-05-16 Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS‐CoV‐2 variants Guerrero‐Preston, Rafael Rivera‐Amill, Vanessa Caraballo, Karem Rodríguez‐Torres, Sebastian Purcell‐Wiltz, Ana García, Andrea A. Torres, Raphael S. Zamuner, Fernando T. Zanettini, Claudio MacKay, Matthew J. Baits, Rachel Salgado, Daisy Khullar, Gaurav Metti, Jessica Baker, Timothy Dudley, Joel Vale, Keilyn Pérez, Gabriela De Jesús, Lorena Miranda, Yaima Ortiz, Denise García‐Negrón, Amanda Viera, Liliana Ortiz, Alberto Canabal, Jorge A. Romaguera, Josefina Jiménez‐Velázquez, Ivonne Marchionni, Luigi Rodríguez‐Orengo, José F. Baez, Adriana Mason, Christopher E. Sidransky, David Immun Inflamm Dis Original Articles INTRODUCTION: The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) pandemic revealed a worldwide lack of effective molecular surveillance networks at local, state, and national levels, which are essential to identify, monitor, and limit viral community spread. SARS‐CoV‐2 variants of concern (VOCs) such as Alpha and Omicron, which show increased transmissibility and immune evasion, rapidly became dominant VOCs worldwide. Our objective was to develop an evidenced‐based genomic surveillance algorithm, combining reverse transcription polymerase chain reaction (RT‐PCR) and sequencing technologies to quickly identify highly contagious VOCs, before cases accumulate exponentially. METHODS: Deidentified data were obtained from 508,969 patients tested for coronavirus disease 2019 (COVID‐19) with the TaqPath COVID‐19 RT‐PCR Combo Kit (ThermoFisher) in four CLIA‐certified clinical laboratories in Puerto Rico (n = 86,639) and in three CLIA‐certified clinical laboratories in the United States (n = 422,330). RESULTS: TaqPath data revealed a frequency of S Gene Target Failure (SGTF) > 47% for the last week of March 2021 in both, Puerto Rico and US laboratories. The monthly frequency of SGTF in Puerto Rico steadily increased exponentially from 4% in November 2020 to 47% in March 2021. The weekly SGTF rate in US samples was high (>8%) from late December to early January and then also increased exponentially through April (48%). The exponential increase in SGFT prevalence in Puerto Rico was concurrent with a sharp increase in VOCs among all SARS‐CoV‐2 sequences from Puerto Rico uploaded to Global Influenza Surveillance and Response System (GISAID) (n = 461). Alpha variant frequency increased from <1% in the last week of January 2021 to 51.5% of viral sequences from Puerto Rico collected in the last week of March 2021. CONCLUSIONS: According to the proposed evidence‐based algorithm, approximately 50% of all SGTF patients should be managed with VOCs self‐quarantine and contact tracing protocols, while WGS confirms their lineage in genomic surveillance laboratories. Our results suggest this workflow is useful for tracking VOCs with SGTF. John Wiley and Sons Inc. 2022-05-11 /pmc/articles/PMC9092005/ /pubmed/35634961 http://dx.doi.org/10.1002/iid3.634 Text en © 2022 The Authors. Immunity, Inflammation and Disease published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Guerrero‐Preston, Rafael
Rivera‐Amill, Vanessa
Caraballo, Karem
Rodríguez‐Torres, Sebastian
Purcell‐Wiltz, Ana
García, Andrea A.
Torres, Raphael S.
Zamuner, Fernando T.
Zanettini, Claudio
MacKay, Matthew J.
Baits, Rachel
Salgado, Daisy
Khullar, Gaurav
Metti, Jessica
Baker, Timothy
Dudley, Joel
Vale, Keilyn
Pérez, Gabriela
De Jesús, Lorena
Miranda, Yaima
Ortiz, Denise
García‐Negrón, Amanda
Viera, Liliana
Ortiz, Alberto
Canabal, Jorge A.
Romaguera, Josefina
Jiménez‐Velázquez, Ivonne
Marchionni, Luigi
Rodríguez‐Orengo, José F.
Baez, Adriana
Mason, Christopher E.
Sidransky, David
Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS‐CoV‐2 variants
title Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS‐CoV‐2 variants
title_full Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS‐CoV‐2 variants
title_fullStr Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS‐CoV‐2 variants
title_full_unstemmed Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS‐CoV‐2 variants
title_short Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS‐CoV‐2 variants
title_sort precision health diagnostic and surveillance network uses s gene target failure (sgtf) combined with sequencing technologies to track emerging sars‐cov‐2 variants
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092005/
https://www.ncbi.nlm.nih.gov/pubmed/35634961
http://dx.doi.org/10.1002/iid3.634
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