TY - JOUR
T1 - Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS-CoV-2 variants
AU - Guerrero-Preston, Rafael
AU - Rivera-Amill, Vanessa
AU - Caraballo, Karem
AU - Rodríguez-Torres, Sebastian
AU - Purcell-Wiltz, Ana
AU - García, Andrea A.
AU - Torres, Raphael S.
AU - Zamuner, Fernando T.
AU - Zanettini, Claudio
AU - MacKay, Matthew J.
AU - Baits, Rachel
AU - Salgado, Daisy
AU - Khullar, Gaurav
AU - Metti, Jessica
AU - Baker, Timothy
AU - Dudley, Joel
AU - Vale, Keilyn
AU - Pérez, Gabriela
AU - De Jesús, Lorena
AU - Miranda, Yaima
AU - Ortiz, Denise
AU - García-Negrón, Amanda
AU - Viera, Liliana
AU - Ortiz, Alberto
AU - Canabal, Jorge A.
AU - Romaguera, Josefina
AU - Jiménez-Velázquez, Ivonne
AU - Marchionni, Luigi
AU - Rodríguez-Orengo, José F.
AU - Baez, Adriana
AU - Mason, Christopher E.
AU - Sidransky, David
N1 - Funding Information:
Thanks to Inno Diagnostics scientists: Omayra De Jesús, MT and Gerardo Hernández Buitrago, PhD; University of Puerto Rico Medical Sciences Campus Clinical Laboratory scientists: Carmen Irizarry MT and Carmen Cadilla Vázquez, PhD; Laboratorio Clínico Villa Ana scientists and staff: José Carlos Flores MBA, BS, Myrna Beltrán MPH, MT, BS; and Carla Franco MT, BS; LifeGene-Biomarks, Inc staff: Margie Cathirys Robinson, Malia Calderón and Teresa Moraima Torres; EDP University President Ing. Gladys Nieves Vázquez; Center for Puerto Rican Studies at Hunter College Director Edwin Meléndez, PhD; Puerto Rico Public Health Trust scientist: Marcos López-Casillas, PhD; Puerto Rico Department of Health scientist: Fabiola Cruz, MS; and Center for Disease Control-Puerto Rico scientists and staff: Eddie Oneill PhD, MS, MPH and Gilberto Santiago, PhD. This study was supported by: National Institute on Minority Health and Health Disparities R44MD014911 Small Business Innovation Research Fast Track Phase 1/Phase 2 award, National Cancer Institute R44CA254690 Small Business Innovation Research Fast Track Phase 1/Phase 2 award and Puerto Rico Science and Technology Research Trust Small Business Innovation Research Phase 1 and Phase 2 Cash Match Awards (R. Guerrero-Preston); NIMHD U54 MD007579: Research Centers in Minority Institutions Center for Research Resources, and Puerto Rico Science and Technology Research Trust (V. Rivera-Amill) under agreement 2020-00259; and National Cancer Institute U01CA84986 (D. Sidransky).
Funding Information:
Thanks to Inno Diagnostics scientists: Omayra De Jesús, MT and Gerardo Hernández Buitrago, PhD; University of Puerto Rico Medical Sciences Campus Clinical Laboratory scientists: Carmen Irizarry MT and Carmen Cadilla Vázquez, PhD; Laboratorio Clínico Villa Ana scientists and staff: José Carlos Flores MBA, BS, Myrna Beltrán MPH, MT, BS; and Carla Franco MT, BS; LifeGene‐Biomarks, Inc staff: Margie Cathirys Robinson, Malia Calderón and Teresa Moraima Torres; EDP University President Ing. Gladys Nieves Vázquez; Center for Puerto Rican Studies at Hunter College Director Edwin Meléndez, PhD; Puerto Rico Public Health Trust scientist: Marcos López‐Casillas, PhD; Puerto Rico Department of Health scientist: Fabiola Cruz, MS; and Center for Disease Control‐Puerto Rico scientists and staff: Eddie Oneill PhD, MS, MPH and Gilberto Santiago, PhD. This study was supported by: National Institute on Minority Health and Health Disparities R44MD014911 Small Business Innovation Research Fast Track Phase 1/Phase 2 award, National Cancer Institute R44CA254690 Small Business Innovation Research Fast Track Phase 1/Phase 2 award and Puerto Rico Science and Technology Research Trust Small Business Innovation Research Phase 1 and Phase 2 Cash Match Awards (R. Guerrero‐Preston); NIMHD U54 MD007579: Research Centers in Minority Institutions Center for Research Resources, and Puerto Rico Science and Technology Research Trust (V. Rivera‐Amill) under agreement 2020‐00259; and National Cancer Institute U01CA84986 (D. Sidransky).
Publisher Copyright:
© 2022 The Authors. Immunity, Inflammation and Disease published by John Wiley & Sons Ltd.
PY - 2022/6
Y1 - 2022/6
N2 - 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.
AB - 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.
KW - SARS-CoV-2
KW - algorithms
KW - genomics
KW - population surveillance
KW - precision medicine
KW - public health
UR - http://www.scopus.com/inward/record.url?scp=85130903939&partnerID=8YFLogxK
U2 - 10.1002/iid3.634
DO - 10.1002/iid3.634
M3 - Article
C2 - 35634961
AN - SCOPUS:85130903939
SN - 2050-4527
VL - 10
JO - Immunity, inflammation and disease
JF - Immunity, inflammation and disease
IS - 6
M1 - e634
ER -