An Elastic Net Regression Model for Identifying Long COVID Patients Using Health Administrative Data: A Population-Based Study.

Background: Long coronavirus disease (COVID) patients experience persistent symptoms after acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Healthcare utilization data could provide critical information on the disease burden of long COVID for service planning; however, not all patients are diagnosed or assigned long COVID diagnostic codes. We developed an algorithm to identify individuals with long COVID using population-level health administrative data from British Columbia (BC), Canada. Methods: An elastic net penalized logistic regression model was developed to identify long COVID patients based on demographic characteristics, pre-existing conditions, COVID-19-related data, and all symptoms/conditions recorded >28-183 days after the COVID-19 symptom onset/reported (index) date of known long COVID patients (n = 2430) and a control group (n = 24 300), selected from all adult COVID-19 cases in BC with an index date on/before October 31, 2021 (n = 168 111). Known long COVID cases were diagnosed in a clinic and/or had the International Classification of Diseases, Tenth Revision, Canada (ICD-10-CA) code for "post COVID-19 condition" in their records. Results: The algorithm retained known symptoms/conditions associated with long COVID, demonstrating high sensitivity (86%), specificity (86%), and area under the receiver operator curve (93%). It identified 25 220 (18%) long COVID patients among the remaining 141 381 adult COVID-19 cases, >10 times the number of known cases. Known and predicted long COVID patients had comparable demographic and health-related characteristics. Conclusions: Our algorithm identified long COVID patients with a high level of accuracy. This large cohort of long COVID patients will serve as a platform for robust assessments on the clinical course of long COVID, and provide much needed concrete information for decision-making.

Spike Mutation Profiles Associated With SARS-CoV-2 Breakthrough Infections in Delta Emerging and Predominant Time Periods in British Columbia, Canada.

Background: COVID-19 vaccination is a key public health measure in the pandemic response. The rapid evolution of SARS-CoV-2 variants introduce new groups of spike protein mutations. These new mutations are thought to aid in the evasion of vaccine-induced immunity and render vaccines less effective. However, not all spike mutations contribute equally to vaccine escape. Previous studies associate mutations with vaccine breakthrough infections (BTI), but information at the population level remains scarce. We aimed to identify spike mutations associated with SARS-CoV-2 vaccine BTI in a community setting during the emergence and predominance of the Delta-variant. Methods: This case-control study used both genomic, and epidemiological data from a provincial COVID-19 surveillance program. Analyses were stratified into two periods approximating the emergence and predominance of the Delta-variant, and restricted to primary SARS-CoV-2 infections from either unvaccinated individuals, or those infected ≥14 days after their second vaccination dose in a community setting. Each sample's spike mutations were concatenated into a unique spike mutation profile (SMP). Penalized logistic regression was used to identify spike mutations and SMPs associated with SARS-CoV-2 vaccine BTI in both time periods. Results and Discussion: This study reports population level relative risk estimates, between 2 and 4-folds, of spike mutation profiles associated with BTI during the emergence and predominance of the Delta-variant, which comprised 19,624 and 17,331 observations, respectively. The identified mutations cover multiple spike domains including the N-terminal domain (NTD), receptor binding domain (RBD), S1/S2 cleavage region, fusion peptide and heptad regions. Mutations in these different regions imply various mechanisms contribute to vaccine escape. Our profiling method identifies naturally occurring spike mutations associated with BTI, and can be applied to emerging SARS-CoV-2 variants with novel groups of spike mutations.

Effect of preexamination conditions in a centralized-testing model of non-invasive prenatal screening.

OBJECTIVES: Non-invasive prenatal testing requires the presence of fetal DNA in maternal plasma. Understanding how preexamination conditions affect the integrity of cell-free DNA (cfDNA) and fetal fraction (FF) are a prerequisite for test implementation. Therefore, we examined the adjusted effect that EDTA and Streck tubes have on the cfDNA quantity and FF. METHODS: A total of 3,568 maternal blood samples across Canada were collected in either EDTA, or Streck tubes, and processing metrics, maternal body mass index (BMI), gestational age and fetal karyotype and sex were recorded. Plasma samples were sequenced using two different sequencing platforms in separate laboratories. Sequencing data were processed with SeqFF to estimate FF. Linear regression and multivariate imputation by chained equations were used to estimate the adjusted effect of tube type on cfDNA and FF. RESULTS: We found a positive association between cfDNA quantity and blood shipment time in EDTA tubes, which is significantly reduced with the use of Streck tubes. Furthermore, we show the storage of plasma at -80 °C is associated with a 4.4% annual relative decrease in cfDNA levels. FF was not associated with collection tube type when controlling for confounding variables. However, FF was positively associated with gestational age and trisomy 21, while negatively associated with BMI, male fetus, trisomy 18, Turners syndrome and triploidy. CONCLUSIONS: Preexamination, maternal and fetal variables are associated with cfDNA quantity and FF. The consideration of these variables in future studies may help to reduce the number of pregnant women with inconclusive tests as a result of low FF.

Genomic Epidemiology of Major Extraintestinal Pathogenic Escherichia coli Lineages Causing Urinary Tract Infections in Young Women Across Canada.

BACKGROUND: A few extraintestinal pathogenic Escherichia coli (ExPEC) multilocus sequence types (STs) cause the majority of community-acquired urinary tract infections (UTIs). We examine the genomic epidemiology of major ExPEC lineages, specifically factors associated with intestinal acquisition. METHODS: A total of 385 women with UTI caused by E. coli across Canada were asked about their diet, travel, and other exposures. Genome sequencing was used to determine both ST and genomic similarity. Logistic regression was used to identify factors associated with the acquisition of and infection with major ExPEC STs relative to minor ExPEC STs. RESULTS: ST131, ST69, ST73, ST127, and ST95 were responsible for 54% of all UTIs. Seven UTI clusters were identified, but genomes from the ST95, ST127, and ST420 clusters exhibited as few as 3 single nucleotide variations across the entire genome, suggesting recent acquisition. Furthermore, we identified a cluster of UTIs caused by 6 genetically-related ST1193 isolates carrying mutations in gyrA and parC. The acquisition of and infection with ST69, ST95, ST127, and ST131 were all associated with increased travel. The consumption of high-risk foods such as raw meat or vegetables, undercooked eggs, and seafood was associated with acquisition of and infection with ST69, ST127, and ST131, respectively. CONCLUSIONS: Reservoirs may aid in the dissemination of pandemic ExPEC lineages in the community. Identifying ExPEC reservoirs may help prevent future emergence and dissemination of high-risk lineages within the community setting.

Global Extraintestinal Pathogenic Escherichia coli (ExPEC) Lineages.

Extraintestinal pathogenic Escherichia coli (ExPEC) strains are responsible for a majority of human extraintestinal infections globally, resulting in enormous direct medical and social costs. ExPEC strains are comprised of many lineages, but only a subset is responsible for the vast majority of infections. Few systematic surveillance systems exist for ExPEC. To address this gap, we systematically reviewed and meta-analyzed 217 studies (1995 to 2018) that performed multilocus sequence typing or whole-genome sequencing to genotype E. coli recovered from extraintestinal infections or the gut. Twenty major ExPEC sequence types (STs) accounted for 85% of E. coli isolates from the included studies. ST131 was the most common ST from 2000 onwards, covering all geographic regions. Antimicrobial resistance-based isolate study inclusion criteria likely led to an overestimation and underestimation of some lineages. European and North American studies showed similar distributions of ExPEC STs, but Asian and African studies diverged. Epidemiology and population dynamics of ExPEC are complex; summary proportion for some STs varied over time (e.g., ST95), while other STs were constant (e.g., ST10). Persistence, adaptation, and predominance in the intestinal reservoir may drive ExPEC success. Systematic, unbiased tracking of predominant ExPEC lineages will direct research toward better treatment and prevention strategies for extraintestinal infections.

Human Sertoli cells support high levels of Zika virus replication and persistence.

Zika virus is a teratogenic mosquito-transmitted flavivirus that is associated with birth defects in newborns and Guillain-Barré syndrome in adults. The virus can also be sexually transmitted, but currently, very little is known about the cell types supporting virus replication and persistence in human testes. Using primary cell cultures, we observed that Sertoli but not Leydig cells are highly susceptible to Zika virus infection, a process that is dependent on the TAM family receptor Axl. In cell culture, Sertoli cells could be productively infected with Zika virus for at least 6-weeks. Infection of Sertoli cells resulted in dramatic changes to the transcriptional profile of these cells. The most upregulated mRNA in infected cells was basic fibroblast growth factor (FGF2), a cytokine that was found to enhance Zika virus replication and support viral persistence. Together these findings provide key insights into understanding how Zika virus persists in the male reproductive tract and in turn may aid in developing antiviral therapies or strategies to minimize sexual transmission of this pathogen.

Recombinant IL-4/13A and IL-4/13B induce arginase activity and down-regulate nitric oxide response of primary goldfish (Carassius auratus L.) macrophages.

We report on the expression analysis and functional characterization of IL-4/13A and IL-4/13B in goldfish. Quantitative analysis indicated the highest expression in the heart, spleen, brain, and kidney, with comparable expression patterns for both IL-4/13A and IL-4/13B. The mRNA levels of IL-4/13A and IL-4/13B in the immune cells examined were highest in macrophage and monocytes. Assessment of spleen mRNA following infection with Trypanosoma carassii, a prominent protozoan pathogen of fish, revealed decrease in IL-4/13B and arginase expression 14 days post infection, followed by an increase in IL-4/13B and arginase-2 at 28 days post infection. Recombinant forms of IL-4/13A and IL-4/13B induced an increase in arginase activity in macrophages in a dose-dependent manner. Recombinant IL-4/13A and IL-4/13B also induced significant increase in mRNA levels of arginase -2 in macrophages at 6, 12, 18 and 24 h after treatment. Furthermore, treatment with both IL-4/13 recombinants interfered with the IFNγ-induced nitric oxide response of macrophages. Our results suggest a conserved role of IL-4/IL-13 in induction of alternative activation phenotype in teleost macrophages.