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The COVID‐19 coronavirus is now spreading worldwide. Its pathogen, SARS‐CoV‐2, has been shown to use angiotensin‐converting enzyme 2 (ACE2) as its host cell receptor, same as the severe acute respiratory syndrome coronavirus (SARS‐CoV) in 2003. Epidemiology studies found males although only slightly more likely to be infected than females account for the majority of the severely ill and fatality, which also bias for people older than 60 years or with metabolic and cardiovascular diseases. Here by analyzing GTEx and other public data in 30 tissues across thousands of individuals, we found a significantly higher level in Asian females, an age‐dependent decrease in all ethnic groups, and a highly significant decrease in type II diabetic patients of ACE2 expression. Consistently, the most significant expression quantitative loci (eQTLs) contributing to high ACE2 expression are close to 100% in East Asians, >30% higher than other ethnic groups. A shockingly common enrichment of viral infection pathways was found among ACE2 anti‐expressed genes, and multiple binding sites of virus infection related transcription factors and sex hormone receptors locate at ACE2 regulatory regions. Human and mice data analysis further revealed ACE2 expression is reduced in T2D patients and with inflammatory cytokine treatment and upregulated by estrogen and androgen (both decrease with age). Our findings revealed a negative correlation between ACE2 expression and COVID‐19 fatality at both population and molecular levels. These results will be instrumental when designing potential prevention and treatment strategies for ACE2 binding coronaviruses in general. This study revealed the negative correlation of high basal ACE2 level with CoVID‐19 severity/fatality at the population level and its anticorrelation with virus infection pathway expression levels, upregulation by sex hormones and suppression by inflammatory cytokine at the molecular level.

[This corrects the article DOI: 10.3389/fimmu.2022.947549.].

Background Little RSV activity was observed during the first expected RSV season since the COVID‐19 pandemic. Multiple countries later experienced out‐of‐season RSV resurgences, yet their association with non‐pharmaceutical interventions (NPIs) is unclear. This study aimed to describe the changes in RSV epidemiology during the COVID‐19 pandemic and to estimate the association between individual NPIs and the RSV resurgences. Methods RSV activity from Week (W)12‐2020 to W44‐2021 was compared with three pre‐pandemic seasons using RSV surveillance data from Brazil, Canada, Chile, France, Israel, Japan, South Africa, South Korea, Taiwan, the Netherlands and the United States. Changes in nine NPIs within 10 weeks before RSV resurgences were described. Associations between NPIs and RSV activity were assessed with linear mixed models. Adherence to NPIs was not taken into account. Results Average delay of the first RSV season during the COVID‐19 pandemic was 39 weeks (range: 13–88 weeks). Although the delay was <40 weeks in six countries, a missed RSV season was observed in Brazil, Chile, Japan, Canada and South Korea. School closures, workplace closures, and stay‐at‐home requirements were most commonly downgraded before an RSV resurgence. Reopening schools and lifting stay‐at‐home requirements were associated with increases of 1.31% (p = 0.04) and 2.27% (p = 0.06) in the deviation from expected RSV activity. Conclusion The first RSV season during the COVID‐19 pandemic was delayed in the 11 countries included. Reopening of schools was consistently associated with increased RSV activity. As NPIs were often changed concomitantly, the association between RSV activity and school closures may be partly attributed to other NPIs.

There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease‐19 (COVID‐19). We aimed to a) identify complement‐related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) predicting these outcomes and c) validate whether complement‐related variants are associated with an impaired complement phenotype. We prospectively recruited consecutive adult patients of Caucasian origin, hospitalized due to COVID‐19. Through targeted next‐generation sequencing, we identified variants in complement factor H/CFH, CFB, CFH‐related, CFD, CD55, C3, C5, CFI, CD46, thrombomodulin/THBD, and A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS13). Among 381 variants in 133 patients, we identified 5 critical variants associated with severe COVID‐19: rs2547438 (C3), rs2250656 (C3), rs1042580 (THBD), rs800292 (CFH) and rs414628 (CFHR1). Using age, gender and presence or absence of each variant, we developed an ANN predicting morbidity and mortality in 89.47% of the examined population. Furthermore, THBD and C3a levels were significantly increased in severe COVID‐19 patients and those harbouring relevant variants. Thus, we reveal for the first time an ANN accurately predicting ICU hospitalization and death in COVID‐19 patients, based on genetic variants in complement genes, age and gender. Importantly, we confirm that genetic dysregulation is associated with impaired complement phenotype.

Complement inhibition has shown promise in various disorders, including COVID‐19. A prediction tool including complement genetic variants is vital. This study aims to identify crucial complement‐related variants and determine an optimal pattern for accurate disease outcome prediction. Genetic data from 204 COVID‐19 patients hospitalized between April 2020 and April 2021 at three referral centres were analysed using an artificial intelligence‐based algorithm to predict disease outcome (ICU vs. non‐ICU admission). A recently introduced alpha‐index identified the 30 most predictive genetic variants. DERGA algorithm, which employs multiple classification algorithms, determined the optimal pattern of these key variants, resulting in 97% accuracy for predicting disease outcome. Individual variations ranged from 40 to 161 variants per patient, with 977 total variants detected. This study demonstrates the utility of alpha‐index in ranking a substantial number of genetic variants. This approach enables the implementation of well‐established classification algorithms that effectively determine the relevance of genetic variants in predicting outcomes with high accuracy.

Multisystem inflammatory syndrome in neonates (MIS-N) is hypothesised to be caused either following transplacental transfer of SARS-CoV2 antibodies or antibodies developed in the neonate after infection with SARS-CoV-2. In this paper, we aim to discuss the clinical manifestations, laboratory features, and management of neonates diagnosed with MIS-N. We collated information from five participating hospitals in western India. A cohort of newborn infants presenting with multi-system involvement, along with the presence of SARS-CoV2 antibodies, was identified. Current proposed international diagnostic criteria for MIS-N were used to group the cases into three categories of Most likely, Possible, and Unlikely MIS-N. A total of 20 cases were reported with a diagnosis of MIS-N, all having high titres of SARS CoV2 IgG antibodies and negative for SARS CoV2 antigens. Most likely MIS ( n  = 5) cases presented with respiratory distress (4/5), hypotension and shock (4/5), and encephalopathy (2/5). Inflammatory markers like CRP (1/5), Procalcitonin (1/5), Ferritin (3/5), D-dimer (4/5), and LDH (2/5) were found to be elevated, and four of them had significantly high levels of proBNP. The majority of them (4/5) responded to immunomodulators, three neonates were discharged home, and two died. Possible MIS infants ( n  = 9) presented with fever (7/9), respiratory distress (4/9), refusal to feed (6/9), lethargy (5/9), and tachycardia (3/9). ProBNP as a marker of cardiac dysfunction was noted to be elevated in four (4/9) infants, correlating with abnormal echocardiography findings in two. In the Unlikely MIS ( n  = 6) category, three (3/6) infants presented with respiratory distress, one (1/6) with shock and cardiac dysfunction, and only one (1/6) with fever. All of them had elevated inflammatory markers. However, there were other potential diagnoses that could have been responsible for the clinical scenarios in these six cases.    Conclusion : MIS-N requires a high index of suspicion and should be considered in a neonate presenting with two or more systems involvement, in the presence of SARS-CoV2 antibodies, along with elevated inflammatory markers, once other common neonatal conditions have been ruled out. What is Known: •  Severe acute respiratory syndrome coronavirus-2 (SARS-CoV2) associated multisystem inflammatory syndrome in children (MIS-C) is  widely reported in paediatric population, however only few reports of newborn affection. • MIS-C is known to cause by virus-induced post-infective antibody mediated immune dysregulation with severe multi-system affection. What is New: •  MIS-N may present with varied clinical manifestations with multi-system involvement of variable severity with milder disease in term and severe disease with cardiac dysfunction in preterm newborns. • Multisystem inflammatory syndrome in newborns (MIS-N) is postulated to occur following immune dysregulation associated with transplacental transfer of SARS-CoV2 antibodies or antibodies developed in the neonate after infection with SARS-CoV-2.

Objective The ongoing pandemic of coronavirus disease (2019 coronavirus disease [COVID‐19]), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) virus, is highly contagious with high morbidity and mortality. The role of the nasal and paranasal sinus cavities is increasingly recognized for COVID‐19 symptomatology and transmission. We therefore conducted a systematic review, synthesizing existing scientific evidence about sinonasal pathophysiology in COVID‐19. Study Design Systematic review. Methods Systematic searches were performed of all indexed studies in PubMed/Medline and Cochrane databases through 28 March 2020 and studies searchable on preprints.com (including ArXiv and Scilit repositories) through 30 March 2020. Data extraction focused on sinonasal pathophysiology in COVID‐19. Results A total of 19 studies were identified. The sinonasal cavity may be a major site of infection by SARS‐CoV‐2, where susceptibility genes required for infection are expressed at high levels and may be modulated by environmental and host factors. Viral shedding appears to be highest from the nose, therefore reflecting a major source for transmission. This has been highlighted by multiple reports of health care‐associated infection (HAI) during rhinologic procedures, which are now consequently considered to be high risk for SARS‐CoV‐2 transmission to health care workers. While sinonasal symptomatology, such as rhinorrhea or congestion, appears to be a rarer symptom of COVID‐19, anosmia without nasal obstruction is reported as highly specific predictor of COVID‐19+ patients. Conclusion Sinonasal pathophysiology is increasingly important in our understanding of COVID‐19. The sinonasal tract may be an important site of infection while sinonasal viral shedding may be an important transmission mechanism—including HAI. Anosmia without nasal obstruction may be a highly specific indicator of COVID‐19. Level of Evidence 2a.

To reduce transmission of SARS-CoV-2, it is important to identify those who are infectious. However, little is known about what proportion of infectious people are asymptomatic and potential \"silent\" transmitters. We evaluated the value of COVID-19 symptoms as a marker for SARS-CoV-2 infection from a representative English survey. We used data from the Office for National Statistics Coronavirus (COVID-19) Infection Survey pilot study. We estimated sensitivity, specificity, the proportion of asymptomatic cases (1 - sensitivity), positive predictive value (PPV) and negative predictive value (NPV) of COVID-19 symptoms as a marker of infection using results of the SARS-CoV-2 test as the \"gold standard\". In total, there were 36,061 individuals with a SARS-CoV-2 test between 26 April and 27 June 2020. Of these, 625 (1.7%) reported symptoms on the day of the test. There were 115 (0.32%) with a positive SARS-CoV-2 test result. Of the 115, there were 27 (23.5%) who were symptomatic and 88 (76.5%) who were asymptomatic on the day of the test. Focusing on those with specific symptoms (cough, and/or fever, and/or loss of taste/smell), there were 158 (0.43%) with such symptoms on the day of the test. Of the 115 with a positive SARS-CoV-2, there were 16 (13.9%) reporting symptoms. In contrast, 99 (86.1%) did not report specific symptoms on the day of the test. The PPV for all symptoms was 4.3% and for the specific symptoms 10.1%. The specificity and NPV of symptoms were above 98%. COVID-19 symptoms are poor markers of SARS-CoV-2. Thus, 76.5% of this random sample who tested positive reported no symptoms, and 86.1% reported none of those specific to COVID-19. A more widespread testing programme is necessary to capture \"silent\" transmission and potentially prevent and reduce future outbreaks.

Abstract Delta has outcompeted most preexisting variants of SARS-CoV-2, becoming the globally predominant lineage by mid-2021. Its subsequent evolution has led to the emergence of multiple sublineages, most of which are well-mixed between countries. By contrast, here we show that nearly the entire Delta epidemic in Russia has probably descended from a single import event, or from multiple closely timed imports from a single poorly sampled geographic location. Indeed, over 90 per cent of Delta samples in Russia are characterized by the nsp2:K81N + ORF7a:P45L pair of mutations which is rare outside Russia, putting them in the AY.122 sublineage. The AY.122 lineage was frequent in Russia among Delta samples from the start, and has not increased in frequency in other countries where it has been observed, suggesting that its high prevalence in Russia has probably resulted from a random founder effect rather than a transmission advantage. The apartness of the genetic composition of the Delta epidemic in Russia makes Russia somewhat unusual, although not exceptional, among other countries.

COVID-19 caused by SARS CoV2 emerged in China at the end of 2019 and soon become a pandemic. Since the virus is novel, pre-existing CoV2-specific immunity is not expected to exist in humans, although studies have shown presence of CoV2 cross-reactive T cells in unexposed individuals. Lack of effective immunity in most individuals along with high infectiousness of the virus has resulted in massive global public health emergency. Intense efforts are on to study viral pathogenesis and immune response to help guide prophylactic and therapeutic interventions as well as epidemiological assessments like transmission modeling. To develop an effective vaccine or biologic therapeutic, it is critical to understand the immune correlates of COVID-19 control. At the same time, whether immunity in recovered individuals is effective for preventing re-infection will be important for informing interventions like social distancing. Key questions that are being investigated regarding immune response in COVID-19 which will help these efforts include, investigations of immune response that distinguishes patients with severe versus mild infection or those that recover relative to those that succumb, durability of immunity in recovered patients and relevance of developed immunity in a cured patient for protection against re-infection as well as value of convalescent plasma from recovered patients as a potential therapeutic modality. This is a broad and rapidly evolving area and multiple reports on status of innate and adaptive immunity against SARS-CoV2 are emerging on a daily basis. While many questions remain unanswered for now, the purpose of this focused review is to summarize the current understanding regarding immune correlates of COVID-19 severity and resolution in order to assist researchers in the field to pursue new directions in prevention and control.