In December 2019, an initial cluster of interstitial bilateral pneumonia emerged in Wuhan, China. A human-to-human transmission was assumed and a previously unrecognized entity, termed coronavirus disease-19 (COVID-19) due to a novel coronavirus (SARS-CoV-2) was described. The infection has rapidly spread out all over the world and Italy has been the first European country experiencing the endemic wave with unexpected clinical severity in comparison with Asian countries. It has been shown that SARS-CoV-2 utilizes angiotensin converting enzyme 2 (ACE2) as host receptor and host proteases for cell surface binding and internalization. Thus, a predisposing genetic background can give reason for interindividual disease susceptibility and/or severity. Taking advantage of the Network of Italian Genomes (NIG), here we mined whole-exome sequencing data of 6930 Italian control individuals from five different centers looking for ACE2 variants. A number of variants with a potential impact on protein stability were identified. Among these, three more common missense changes, p.(Asn720Asp), p.(Lys26Arg), and p.(Gly211Arg) were predicted to interfere with protein structure and stabilization. Rare variants likely interfering with the internalization process, namely p.(Leu351Val) and p.(Pro389His), predicted to interfere with SARS-CoV-2 spike protein binding, were also observed. Comparison of ACE2 WES data between a cohort of 131 patients and 258 controls allowed identifying a statistically significant (P value < 0.029) higher allelic variability in controls compared with patients. These findings suggest that a predisposing genetic background may contribute to the observed interindividual clinical variability associated with COVID-19, allowing an evidence-based risk assessment leading to personalized preventive measures and therapeutic options.

Data availabilitySummary statistics generated by COVID-19 Host Genetics Initiative are available online (https://www.covid19hg.org/results/r6/). The analyses described here use the freeze 6 data. The COVID-19 Host Genetics Initiative continues to regularly release new data freezes. Summary statistics for samples from individuals of non-European ancestry are not currently available owing to the small individual sample sizes of these groups, but the results for 23 loci lead variants are reported in Supplementary Table 3. Individual-level data can be requested directly from the authors of the contributing studies, listed in Supplementary Table 1.

Purpose of review To investigate the association between the olfactory dysfunction and the more typical symptoms (fever, cough, dyspnoea) within the Sars-CoV-2 infection (COVID-19) in hospitalized and non-hospitalized patients. Recent findings PubMed, Scopus and Web of Science databases were reviewed from May 5, 2020, to June 1, 2020. Inclusion criteria included English, French, German, Spanish or Italian language studies containing original data related to COVID19, anosmia, fever, cough, and dyspnoea, in both hospital and non-hospital settings. Two investigators independently reviewed all manuscripts and performed quality assessment and quantitative meta-analysis using validated tools. A third author arbitrated full-text disagreements. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), 11 of 135 studies fulfilled eligibility. Anosmia was estimated less prevalent than fever and cough (respectively rate difference = − 0.316, 95% CI: − 0.574 to − 0.058, Z = − 2.404, p G 0.016, k = 11 and rate difference = − 0.249, 95% CI: − 0.402 to − 0.096, Z = − 3.185, p G 0.001, k = 11); the analysis between anosmia and dyspnoea was not significant (rate difference = − 0.008, 95% CI: − 0.166 to 0.150, Z = − 0.099, p G 0.921, k = 8). The typical symptoms were significantly more frequent than anosmia in hospitalized more critical patients than in non-hospitalized ones (respectively [Q(1) = 50.638 p G 0.000, Q(1) = 52.520 p G 0.000, Q(1) = 100.734 p G 0.000). Summary Patient with new onset olfactory dysfunction should be investigated for COVID-19. Anosmia is more frequent in non-hospitalized COVID-19 patients than in hospitalized ones.

IntroductionThe impairment of the sense of smell is often related to chronic rhinosinusitis (CRS) with or without nasal polyps (CRSwNP, CRSsNP). CRSwNP is a frequent condition that drastically worsens the quality of life of those affected; it has a higher prevalence than CRSsNP. CRSwNP patients experience severe loss of smell with earlier presentation and are more likely to experience recurrence of their symptoms, often requiring revision surgery.MethodsThe present study performed a multicentric data collection, enrolling 811 patients with CRS divided according to the inflammatory endotype (Type 2 and non-Type 2). All patients were referred for nasal endoscopy for the assessment of nasal polyposis using nasal polyp score (NPS); Sniffin’ Sticks olfactory test were performed to measure olfactory function, and SNOT-22 (22-item sinonasal outcome test) questionnaire was used to assess patients’ quality of life; allergic status was evaluated with skin prick test and nasal cytology completed the evaluation when available.ResultsData showed that Type 2 inflammation is more common than non-type 2 (656 patients versus 155) and patients suffer from worse quality of life and nasal polyp score. Moreover, 86.1% of patients with Type 2 CRSwNP were affected by a dysfunction of the sense of smell while it involved a lesser percentage of non-Type 2 patients. Indeed, these data give us new information about type-2 inflammation patients’ characteristics.DiscussionThe present study confirms that olfactory function weights on patients’ QoL and it represents an important therapeutic goal that can also improve patients’ compliance when achieved. In a future – and present – perspective of rhinological precision medicine, an impairment of the sense of smell could help the clinician to characterize patients better and to choose the best treatment available.

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as “Respiratory or thoracic disease”, supporting their link with COVID-19 severity outcome.