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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Nikiforuk, Aidan M. Kuchinski, Kevin S. Short, Katy Roman, Susan Irvine, Mike A. Prystajecky, Natalie Jassem, Agatha N. Patrick, David M. Sekirov, Inna |
| Abstract | Background Widespread 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. Methods Epidemiological 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. Results The 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 (β = -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 (β = 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. Conclusion Our 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. |
| Related Links | https://bmcinfectdis.biomedcentral.com/counter/pdf/10.1186/s12879-024-09067-9.pdf |
| Ending Page | 13 |
| Page Count | 13 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| ISSN | 14712334 |
| DOI | 10.1186/s12879-024-09067-9 |
| Journal | BMC Infectious Diseases |
| Issue Number | 1 |
| Volume Number | 24 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2024-02-26 |
| Access Restriction | Open |
| Subject Keyword | Infectious Diseases Parasitology Medical Microbiology Tropical Medicine Internal Medicine ACE2 SARS-CoV-2 Infection tracing Transmission network Outbreak investigation Multivariable analysis Poisson regression model Negative binomial regression |
| Content Type | Text |
| Resource Type | Article |
| Subject | Infectious Diseases |
| Journal Impact Factor | 3.4/2023 |
| 5-Year Journal Impact Factor | 3.3/2023 |
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