Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study

Background:The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system.Methods:We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and ground-level ozone (O₃), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals’ long-term exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage.Results:Among the 151 105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM_2.5 (1.70 μg/m³), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01–1.12), 1.09 (95% CI 0.98–1.21) and 1.00 (95% CI 0.90–1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO₂. We also estimated odds ratios of 1.15 (95% CI 1.06–1.23), 1.30 (95% CI 1.12–1.50) and 1.18 (95% CI 1.02–1.36) per interquartile range increase of 5.14 ppb in O₃ for hospital admission, ICU admission and death, respectively.Interpretation:Chronic exposure to air pollution may contribute to severe outcomes after SARS-CoV-2 infection, particularly exposure to O₃.

By November 2021, COVID-19 had caused more than 5 million deaths globally¹ and more than 29 400 in Canada.² The clinical manifestations of SARS-CoV-2 infection range from being asymptomatic to multiple organ failure and death. Identifying risk factors for COVID-19 severity is important to better understand etiological mechanisms and identify populations to prioritize for screening, vaccination and medical treatment. Risk factors for severity of COVID-19 include male sex, older age, pre-existing medical conditions and being from racialized communities.^3–5 More recently, ambient air pollution has been implicated as a potential driver of COVID-19 severity.^6–10Long-term exposure to ambient air pollution, a major contributor to global disease burden,¹¹ could increase the risk of severe COVID-19 outcomes by several mechanisms. Air pollutants can reduce individuals’ pulmonary immune responses and antimicrobial activities, boosting viral loads.⁸ Air pollution can also induce chronic inflammation and overexpression of the alveolar angiotensin-converting enzyme 2 (ACE) receptor,⁷ the key receptor that facilitates SARS-CoV-2 entry into cells.^12,13 Exposure to air pollution contributes to chronic conditions, such as cardiovascular disease, that are associated with unfavourable COVID-19 prognosis, possibly owing to persistent immune activation and excessive amplification of cytokine development.¹⁰ Thus, greater exposure to long-term air pollution may lead to severe COVID-19 outcomes.Reports exist of positive associations between long-term exposure to particulate matter with diameters equal to or smaller than 2.5 or 10 μm (PM_2.5 and PM₁₀), ground-level ozone (O₃) and nitrogen dioxide (NO₂), and metrics of COVID-19 severity (e.g., mortality and case fatality rate).^8–10 However, most studies to date have used ecological and cross-sectional designs, owing to limited access to individual data, which leads to ambiguity in interpreting the results, thus hindering their influence on policy. ^6,14 Ecological designs do not allow for disentangling the relative impacts of air pollution on individual susceptibility to infection and disease severity.¹⁴ Residual confounding by factors such as population mobility and social interactions is also problematic. Therefore, a cohort study with data on individuals with SARS-CoV-2 is a more appropriate design.^6,14 Studies that have used individual data were conducted in specific subpopulations^15,16 or populations with few severe cases,¹⁷ or had limited data on individual exposure to air pollutants.¹⁸ In Canada, 1 ecological study found a positive association between long-term exposure to PM_2.5 and COVID-19 incidence,¹⁹ but no published study has explored the association between air pollution and COVID-19 severity.We aimed to examine the associations between long-term exposure to 3 common air pollutants (PM_2.5, NO₂ and O₃) and key indicators of COVID-19 severity, including hospital admission, intensive care unit (ICU) admission and death, using a large prospective cohort of people with confirmed SARS-CoV-2 infection in Ontario, Canada, in 2020. The air contaminants PM_2.5, NO₂ and O₃ are regularly monitored by the Canadian government, and are key pollutants that are considered when setting air-quality policies. They originate from varying sources (NO₂ is primarily emitted during combustion of fuel, O₃ is primarily formed in air by chemical reactions of nitrogen oxides and volatile organic compounds, and PM_2.5 can be emitted during combustion or formed by reactions of chemicals like sulphur dioxide and nitrogen oxides in air) and they may affect human health differently.^20,21,22     

Diversity of an ectomycorrhizal fungal community studied by a root tip and total soil DNA approach

Molecular methods based on soil DNA extracts are increasingly being used to study the fungal diversity of ectomycorrhizal (EM) fungal communities in soil. Contrary to EM root tip identification, the use of molecular methods enables identification of extramatrical mycelia in soil. To compare fungal diversity as determined by root tip identification and mycelial identification, six soil samples were analysed. Root tips were extracted from the six samples and after amplification, the basidiomycete diversity on the root tips was analysed by denaturing gradient gel electrophoresis (DGGE). The soil from the six samples was sieved, total soil DNA was extracted and after amplification, the basidiomycete diversity in the soil fractions was analysed by DGGE. Fourteen different bands were excised from the DGGE gel and sequenced; fungal taxon names could be assigned to eight bands. Out of a total of 14 fungal taxa detected in soil, 11 fungal taxa were found on root tips, of which seven were EM fungal taxa. To examine whether the sieving treatment would affect EM species diversity, two different sieve mesh sizes were used and in addition, the organic soil fraction was analysed separately. DGGE analysis showed no differences in banding pattern for the different soil fractions. The organic fraction gave the highest DGGE band intensities. This work demonstrates that there is a high correspondence between basidiomycete diversity detected by molecular analysis of root tips and soil samples, irrespective of the soil fraction being analysed.     

Screening for antimicrobial resistance genes and virulence factors via genome sequencing

Second-generation genome sequencing and alignment of the resulting reads to in silico genomes containing antimicrobial resistance and virulence factor genes were used to screen for undesirable genes in 28 strains which could be used in human nutrition. No virulence factor genes were detected, while several isolates contained antimicrobial resistance genes.     

Mitotic checkpoint gene expression is tuned by codon usage bias

The mitotic checkpoint (also called spindle assembly checkpoint, SAC) is a signaling pathway that safeguards proper chromosome segregation. Correct functioning of the SAC depends on adequate protein concentrations and appropriate stoichiometries between SAC proteins. Yet very little is known about the regulation of SAC gene expression. Here, we show in the fission yeast Schizosaccharomyces pombe that a combination of short mRNA half‐lives and long protein half‐lives supports stable SAC protein levels. For the SAC genes mad2 ⁺ and mad3 ⁺, their short mRNA half‐lives are caused, in part, by a high frequency of nonoptimal codons. In contrast, mad1 ⁺ mRNA has a short half‐life despite a higher frequency of optimal codons, and despite the lack of known RNA‐destabilizing motifs. Hence, different SAC genes employ different strategies of expression. We further show that Mad1 homodimers form co‐translationally, which may necessitate a certain codon usage pattern. Taken together, we propose that the codon usage of SAC genes is fine‐tuned to ensure proper SAC function. Our work shines light on gene expression features that promote spindle assembly checkpoint function and suggests that synonymous mutations may weaken the checkpoint.     

Re-infestation of houses by Triatoma dimidiata after intra-domicile insecticide application in the Yucatán peninsula, Mexico

In most countries, Chagas disease transmission control remains based on domestic insecticide application. We thus evaluated the efficacy of intra-domicile cyfluthrin spraying for the control of Triatoma dimidiata, the only Chagas disease vector in the Yucatán peninsula, Mexico, and monitored potential re-infestation every 15 days for up to 9 months. We found that there was a re-infestation of houses by adult bugs starting 4 months after insecticide application, possibly from sylvatic/peridomicile areas. This points out the need to take into account the potential dispersal of sylvatic/peridomestic adult bugs into the domiciles as well as continuity action for an effective vector control.     

The New York Consortium on Membrane Protein Structure (NYCOMPS): a high-throughput platform for structural genomics of integral membrane proteins

The New York Consortium on Membrane Protein Structure (NYCOMPS) was formed to accelerate the acquisition of structural information on membrane proteins by applying a structural genomics approach. NYCOMPS comprises a bioinformatics group, a centralized facility operating a high-throughput cloning and screening pipeline, a set of associated wet labs that perform high-level protein production and structure determination by x-ray crystallography and NMR, and a set of investigators focused on methods development. In the first three years of operation, the NYCOMPS pipeline has so far produced and screened 7,250 expression constructs for 8,045 target proteins. Approximately 600 of these verified targets were scaled up to levels required for structural studies, so far yielding 24 membrane protein crystals. Here we describe the overall structure of NYCOMPS and provide details on the high-throughput pipeline.