ObjectivesAtmospheric fine particulate matter (PM2.5) has multiple adverse effects on human health. Global atmospheric levels of PM2.5 increased by 0.55 μg/m3/year (2.1%/year) from 1998 through 2012. There is evidence of a causal relationship between atmospheric PM2.5 and breast cancer (BC) incidence, but few studies have investigated BC mortality and atmospheric PM2.5. We investigated BC mortality in relation to atmospheric PM2.5 levels among patients living in Varese Province, northern Italy.MethodsWe selected female BC cases, archived in the local population-based cancer registry, diagnosed at age 50–69 years, between 2003 and 2009. The geographic coordinates of each woman's place of residence were identified, and individual PM2.5 exposures were assessed from satellite data. Grade, stage, age at diagnosis, period of diagnosis and participation in BC screening were potential confounders. Kaplan-Meir and Nelson-Aalen methods were used to test for mortality differences in relation to PM2.5 quartiles. Multivariable Cox proportional hazards modelling estimated HRs and 95% CIs of BC death in relation to PM2.5 exposure.ResultsOf 2021 BC cases, 325 died during follow-up to 31 December 2013, 246 for BC. Risk of BC death was significantly higher for all three upper quartiles of PM2.5 exposure compared to the lowest, with HRs of death: 1.82 (95% CI 1.15 to 2.89), 1.73 (95% CI 1.12 to 2.67) and 1.72 (95% CI 1.08 to 2.75).ConclusionsOur study indicates that the risk of BC mortality increases with PM2.5 exposure. Although additional research is required to confirm these findings, they are further evidence that PM2.5 exposure is harmful and indicate an urgent need to improve global air quality.

Functional variomics provides the foundation for personalized medicine by linking genetic variation to disease expression, outcome and treatment, yet its utility is dependent on appropriate assays to evaluate mutation impact on protein function. To fully assess the effects of 106 missense and nonsense variants of PTEN associated with autism spectrum disorder, somatic cancer and PTEN hamartoma syndrome (PHTS), we take a deep phenotypic profiling approach using 18 assays in 5 model systems spanning diverse cellular environments ranging from molecular function to neuronal morphogenesis and behavior. Variants inducing instability occur across the protein, resulting in partial-to-complete loss-of-function (LoF), which is well correlated across models. However, assays are selectively sensitive to variants located in substrate binding and catalytic domains, which exhibit complete LoF or dominant negativity independent of effects on stability. Our results indicate that full characterization of variant impact requires assays sensitive to instability and a range of protein functions.

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OBJECTIVES: Severe acute respiratory syndrome–related coronavirus-2 binds and inhibits angiotensin-converting enzyme-2. The frequency of acute cardiac injury in patients with coronavirus disease 2019 is unknown. The objective was to compare the rates of cardiac injury by angiotensin-converting enzyme-2–binding viruses from viruses that do not bind to angiotensin-converting enzyme-2. DATA SOURCES: We performed a systematic review of coronavirus disease 2019 literature on PubMed and EMBASE. STUDY SELECTION: We included studies with ten or more hospitalized adults with confirmed coronavirus disease 2019 or other viral pathogens that described the occurrence of acute cardiac injury. This was defined by the original publication authors or by: 1) myocardial ischemia, 2) new cardiac arrhythmia on echocardiogram, or 3) new or worsening heart failure on echocardiogram. DATA EXTRACTION: We compared the rates of cardiac injury among patients with respiratory infections with viruses that down-regulate angiotensin-converting enzyme-2, including H1N1, H5N1, H7N9, and severe acute respiratory syndrome–related coronavirus-1, to those with respiratory infections from other influenza viruses that do not bind angiotensin-converting enzyme-2, including Influenza H3N2 and influenza B. DATA SYNTHESIS: Of 57 studies including 34,072 patients, acute cardiac injury occurred in 50% (95% CI, 44–57%) of critically ill patients with coronavirus disease 2019. The overall risk of acute cardiac injury was 21% (95% CI, 18–26%) among hospitalized patients with coronavirus disease 2019. In comparison, 37% (95% CI, 26–49%) of critically ill patients with other respiratory viruses that bind angiotensin-converting enzyme-2 (p = 0.061) and 12% (95% CI, 7–22%) of critically ill patients with other respiratory viruses that do not bind angiotensin-converting enzyme-2 (p < 0.001) experienced a cardiac injury. CONCLUSIONS: Acute cardiac injury may be associated with whether the virus binds angiotensin-converting enzyme-2. Acute cardiac injury occurs in half of critically ill coronavirus disease 2019 patients, but only 12% of patients infected by viruses that do not bind to angiotensin-converting enzyme-2.

Background: Acute kidney injury (AKI) is a potentially fatal complication of Coronavirus Disease-2019 (COVID-19). Binding of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, to its viral receptor, angiotensin converting enzyme 2 (ACE2), results in viral entry and may cause AKI. Objectives: We performed a systematic review and meta-analysis of the frequencies of AKI and renal replacement therapy (RRT) in critically ill COVID-19 patients and compared those frequencies with patients who were infected by respiratory viruses that bind or downregulate ACE2 (ACE2-associated viruses) and viruses that do not bind nor downregulate ACE2 (non-ACE2-associated viruses). Design: Systematic review and meta-analysis. Setting: Observational studies on COVID-19 and other respiratory viral infections reporting AKI and RRT were included. The exclusion criteria were non-English articles, non-peer-reviewed articles, review articles, studies that included patients under the age of 18, studies including fewer than 10 patients, and studies not reporting AKI and RRT rates. Patients: Adult COVID-19, Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS), and influenza patients. Measurements: We extracted the following data from the included studies: author, year, study location, age, sex, race, diabetes mellitus, hypertension, chronic kidney disease, shock, vasopressor use, mortality, intensive care unit (ICU) admission, ICU mortality, AKI, and RRT. Methods: We systematically searched PubMed and EMBASE for articles reporting AKI or RRT. AKI was defined by authors of included studies. Critical illness was defined by ICU admission. We performed a random effects meta-analysis to calculate pooled estimates for the AKI and RRT rate within each virus group using a random intercept logistic regression model. Results: Of 23 655 hospitalized, critically ill COVID-19 patients, AKI frequencies were not significantly different between COVID-19 patients (51%, 95% confidence interval [CI]: 44%-57%) and critically ill patients infected with ACE2-associated (56%, 95% CI: 37%-74%, P = .610) or non-ACE2-associated viruses (63%, 95% CI: 43%-79%, P = .255). Pooled RRT rates were also not significantly different between critically ill, hospitalized patients with COVID-19 (20%, 95% CI: 16%-24%) and ACE2-associated viruses (18%, 95% CI: 8%-33%, P = .747). RRT rates for both COVID-19 and ACE2-associated viruses were significantly different ( P < .001 for both) from non-ACE2-associated viruses (49%, 95% CI: 44%-54%). After adjusting for shock or vasopressor use, AKI and RRT rates were not significantly different between groups. Limitations: Limitations of this study include the heterogeneity of definitions of AKI that were used across different virus studies. We could not match severity of infection or do propensity matching across studies. Most of the included studies were conducted in retrospective fashion. Last, we did not include non-English publications. Conclusions: Our findings suggest that viral ACE2 association does not significantly alter the rates of AKI and RRT among critically ill patients admitted to the ICU. However, the rate of RRT is lower in patients with COVID-19 or ACE2-associated viruses when compared with patients infected with non-ACE2-binding viruses, which might partly be due to the lower frequencies of shock and use of vasopressors in these two virus groups. Prospective studies are necessary to demonstrate whether modulation of the ACE2 axis with Renin-Angiotensin System inhibitors impacts the rates of AKI and whether they are beneficial or harmful in COVID-19 patients.

BACKGROUND Angiotensin receptor blockers (ARBs) and/or angiotensin converting enzyme (ACE) inhibitors could alter mortality of COVID-19, but existing meta-analyses which combined crude and adjusted results may be confounded by comorbidities being more common in ARBs/ACE inhibitors users. METHODS We searched PubMed/MEDLINE/Embase for cohort studies and meta-analysis reporting mortality by pre-existing ARB/ACE inhibitor treatment in hospitalized COVID-19 patients. Random effects meta-regression was used to compute pooled odds ratios for mortality adjusted for imbalance in age, sex and prevalence of cardiovascular disease, hypertension, diabetes mellitus and chronic kidney disease between users and non-users of ARBs/ACE inhibitors at the study-level during data synthesis. RESULTS In 30 included studies of 17,281 patients, 22%, 68%, 25%, and 11% had cardiovascular disease, hypertension, diabetes mellitus and chronic kidney disease. ARBs/ACE inhibitors use was associated with significantly lower mortality after controlling for potential confounding factors (OR 0.77 (95% CI: 0.62, 0.96)). In contrast, meta-analysis of ARBs/ACE inhibitors use was not significantly associated with mortality when all studies were combined with no confounder adjustment performed (0.87 (95% CI: 0.71, 1.08)). CONCLUSIONS ARBs/ACE inhibitors use was associated with decreased mortality in cohorts of COVID-19 patients after adjusting for age, sex, cardiovascular disease, hypertension, diabetes and chronic kidney disease. Unadjusted meta-analyses may not be appropriate for determining whether ARBs/ACE inhibitors are associated with mortality of COVID-19 because of indication bias.

Introduction Coronavirus Disease‐2019 (COVID‐19) affects multiple organ systems in the acute phase and also has long‐term sequelae. Research on the long‐term impacts of COVID‐19 is limited. The Post COVID‐19 Interdisciplinary Clinical Care Network (PC‐ICCN), conceived in July 2020, is a provincially funded resource that is modelled as a Learning Health System (LHS), focused on those people with persistent symptoms post COVID‐19 infection. Methods The PC‐ICCN emerged through collaboration among over 60 clinical specialists, researchers, patients, and health administrators. At the core of the network are the post COVID‐19 Recovery Clinics (PCRCs), which provide direct patient care that includes standardized testing and education at regular follow‐up intervals for a minimum of 12 months post enrolment. The PC‐ICCN patient registry captures data on all COVID‐19 patients with confirmed infection, by laboratory testing or epi‐linkage, who have been referred to one of five post COVID‐19 Recovery Clinics at the time of referral, with data stored in a fully encrypted Oracle‐based provincial database. The PC‐ICCN has centralized administrative and operational oversight, multi‐stakeholder governance, purpose built data collection supported through clinical operations geographically dispersed across the province, and research operations including data analytics. Results To date, 5364 patients have been referred, with an increasing number and capacity of these clinics, and 2354 people have had at least one clinic visit. Since inception, the PC‐ICCN has received over 30 research proposal requests. This is aligned with the goal of creating infrastructure to support a wide variety of research to improve care and outcomes for patients experiencing long‐term symptoms following COVID‐19 infection. Conclusions The PC‐ICCN is a first‐in‐kind initiative in British Columbia to enhance knowledge and understanding of the sequelae of COVID‐19 infection over time. This provincial initiative serves as a model for other national and international endeavors to enable care as research and research as care.

ABSTRACTFunctional variomics provides the foundation for personalized medicine by linking genetic variation to disease expression, outcome and treatment, yet its utility is dependent on appropriate assays to evaluate mutation impact on protein function. To fully assess the effects of 106 missense and nonsense variants of PTEN associated with autism spectrum disorder, somatic cancer and PHTS, we take a deep phenotypic profiling approach using 18 assays in 5 model systems spanning diverse cellular environments ranging from molecular function to neuronal morphogenesis and behavior. Variants inducing instability occurred across the protein, resulting in partial to complete loss of function (LoF), which was well correlated across models. However, assays were selectively sensitive to variants located in substrate binding and catalytic domains, which exhibited complete LoF or dominant negativity independent of effects on stability. Our results indicate that full characterization of variant impact requires assays sensitive to instability and a range of protein functions.