Nasopharyngeal angiotensin converting enzyme 2 (ACE2) expression as a risk-factor for SARS-CoV-2 transmission in concurrent hospital associated outbreaks

被引:0
作者
Nikiforuk, Aidan M. [1 ,4 ]
Kuchinski, Kevin S. [1 ,2 ]
Short, Katy [3 ]
Roman, Susan [3 ]
Irvine, Mike A. [1 ,5 ]
Prystajecky, Natalie [1 ,2 ]
Jassem, Agatha N. [1 ,2 ]
Patrick, David M. [1 ,4 ]
Sekirov, Inna [1 ,2 ]
机构
[1] British Columbia Ctr Dis Control, Vancouver, BC V5Z 4R4, Canada
[2] Univ British Columbia, Dept Pathol & Lab Med, Vancouver, BC V6T 1Z4, Canada
[3] Fraser Hlth Author, New Westminster, BC V3L 3C2, Canada
[4] Univ British Columbia, Sch Populat & Publ Hlth, Vancouver, BC V6T 1Z4, Canada
[5] Simon Fraser Univ, Fac Hlth Sci, Burnaby, BC V5A 1S6, Canada
基金
加拿大健康研究院;
关键词
ACE2; SARS-CoV-2; Infection tracing; Transmission network; Outbreak investigation; Multivariable analysis; Poisson regression model; Negative binomial regression;
D O I
10.1186/s12879-024-09067-9
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
BackgroundWidespread human-to-human transmission of the severe acute respiratory syndrome coronavirus two (SARS-CoV-2) stems from a strong affinity for the cellular receptor angiotensin converting enzyme two (ACE2). We investigate the relationship between a patient's nasopharyngeal ACE2 transcription and secondary transmission within a series of concurrent hospital associated SARS-CoV-2 outbreaks in British Columbia, Canada.MethodsEpidemiological case data from the outbreak investigations was merged with public health laboratory records and viral lineage calls, from whole genome sequencing, to reconstruct the concurrent outbreaks using infection tracing transmission network analysis. ACE2 transcription and RNA viral load were measured by quantitative real-time polymerase chain reaction. The transmission network was resolved to calculate the number of potential secondary cases. Bivariate and multivariable analyses using Poisson and Negative Binomial regression models was performed to estimate the association between ACE2 transcription the number of SARS-CoV-2 secondary cases.ResultsThe infection tracing transmission network provided n = 76 potential transmission events across n = 103 cases. Bivariate comparisons found that on average ACE2 transcription did not differ between patients and healthcare workers (P = 0.86). High ACE2 transcription was observed in 98.6% of transmission events, either the primary or secondary case had above average ACE2. Multivariable analysis found that the association between ACE2 transcription (log2 fold-change) and the number of secondary transmission events differs between patients and healthcare workers. In health care workers Negative Binomial regression estimated that a one-unit change in ACE2 transcription decreases the number of secondary cases (beta = -0.132 (95%CI: -0.255 to -0.0181) adjusting for RNA viral load. Conversely, in patients a one-unit change in ACE2 transcription increases the number of secondary cases (beta = 0.187 (95% CI: 0.0101 to 0.370) adjusting for RNA viral load. Sensitivity analysis found no significant relationship between ACE2 and secondary transmission in health care workers and confirmed the positive association among patients.ConclusionOur study suggests that ACE2 transcription has a positive association with SARS-CoV-2 secondary transmission in admitted inpatients, but not health care workers in concurrent hospital associated outbreaks, and it should be further investigated as a risk-factor for viral transmission.
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页数:13
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