Correction to: BAL biomarkers' panel for differential diagnosis of interstitial lung diseases

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An explainable model of host genetic interactions linked to COVID-19 severity

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.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Serum amyloid A: a new biomarker in Idiopathic Pulmonary Fibrosis

Background: Lipid metabolism has been demonstrated altered in different interstitial lung diseases (ILDs) including idiopathic pulmonary fibrosis (IPF). Serum amyloid A (SAA) is an acute phase protein mainly produced by the liver in response to proinflammatory cytokines. Few data are available on SAA levels in patients with IPF, a chronic progressive lung disease associated with a poor survival and a radiological and histological pattern of usual interstitial pneumonia (UIP). The clinical course of IPF is unpredictable. To date, we don't have a marker of severity and prognosis capable of establishing the evolution of IPF early. Objectives: We compared SAA serum levels in IPF patients to other ILD groups, to definite the potential value of this protein as a biomarker of fibrosis and its specificity in IPF. Our aim is to demonstrate the role of the lipid metabolism in the fibrotic process, especially the role of the apolipoprotein SAA as a biomarker of IPF that can predict clinical course, prognosis and survival of IPF patients. Materials and methods: We enrolled 185 patients (40 stable IPF, 8 IPF with acute exacerbation, 30 sarcoidosis, 30 chronic HP, 17 cystic ILDs (PLCH&LAM), 6 NSIP, 9 UIP non-IPF, 16 SSc-ILD, 6 COPD with pulmonary emphysema, 6 other ILDs, 17 healthy controls), monitored at Siena Regional Centre for ILDs and at the Respiratory Department of the Saint Anna Hospital at University of Ferrara. IPF patients were prevalently male, ex-smokers and over 65 years of age. Clinical, functional, radiological and immunological data were collected from all patients. Results: IPF patients have significantly higher SAA serum levels than the other ILDs (61,64 ± 8,52 mcg/ml). In the groups IPF, AE-IPF, UIP-non IPF, emphysema and other-ILDs patients were predominantly males and older than the other groups of patients (over 65 years of age). The ANOVA test showed a clear and statistical significant difference between SAA serum levels in the IPF group vs healthy controls (p<0.0002), which indicates that SAA is a disease marker. A ROC curve analysis showed that IPF patients have statistical significance higher SAA serum levels than SSc-ILD with a progressive fibrosis, identifying a cut-off value (45,21 mcg/ml, p<0,0001, AUC 97,6 with specificity 100%). This data indicates that a patient with a progressive fibrosis with serum SAA levels above that cut-off is more likely an IPF than another progressive fibrosis with a pattern UIP or another radiological pattern. The difference in serum SAA concentration in the IPF and AE-IPF groups was statistically significant (p<0.002). By performing a ROC curve of SAA in AE-IPF vs stable IPF we detected a cut-off 48,84 mcg/ml highly specific for acute exacerbation (AUC: 90.4%; p<0,0024; Se: 87,5%; Sp: 92,31%). These results show how serum SAA levels are higher in IPF patients in the stable phase compared to those with acute exacerbation, suggesting a role for SAA as a biomarker of fibrosis. Conclusions: SAA could be considered a potential specific biomarker for IPF that can predict clinical course and prognosis of patients. SAA could discriminate an inflammatory ILD from a pulmonary progressive fibrosis mainly for IPF (which is a progressive fibrosis by definition). Monitoring serum levels could be useful to identify patients with rapidly progressive IPF disease phenotype or at risk of acute exacerbation. SAA may play a crucial role in the regulation of lipid metabolism and production of MMPs in IPF. May be SAA could become a potential target for IPF treatment, including via apolipoproteins

Chilotorace maligno: patogenesi e valore prognostico.

Il chilotorace maligno è una forma rara di versamento pleurico associato a patologia oncologica. La patogenesi del chilotorace maligno comprende meccanismi multipli spesso complessi e che non sempre dipendono dal coinvolgimento diretto della pleura. Infine, la letteratura riporta come la presenza di un chilotorace maligno possa influenzare la prognosi del paziente a seconda dell’istologia della malattia sottostante

Real-life experience of severe asthma patients on Dupilumab treatment in Pordenone’s Hospital.

It is hypothesized that anti-IL-4 and anti-IL-13 therapies could decrease asthma exacerbations by inhibiting eosinophilic and airway inflammation. Reducing asthma exacerbation risk is a key target of disease management. The improvements in asthma-related quality of life with dupilumab treatment may contribute to preventing severe asthma exacerbations, particularly in patients with nasal polyposis

Author reply

These findings highlight the need to explore SAA in patients with interstitial lung involvement associated with SSc. SAA can be considered a bioindicator of fibrotic lung disease, isolated IPF as well as that associated with autoimmune systemic disorders such as SSc

Siero Amiloide A: nuovo potenziale biomarcatore di Fibrosi Polmonare Idiopatica.

L’analisi dei risultati ottenuti suggerisce che la SAA possa essere considerata un potenziale biomarcatore prognostico specifico di Fibrosi Polmonare Idiopatica (IPF). Il nostro centro è il primo che ha studiato la SAA nella IPF: l’aumento di questo biomarcatore, coinvolto nell'infiammazione cronica, rimodellamento della matrice extracellulare e nel metabolismo lipoproteico, suggerisce un potenziale utilizzo della SAA sia come indicatore di severità di malattia che come biomarker prognostico nella IPF. Monitorarne i livelli sierici potrebbe essere utile per individuare i pazienti con fenotipo di malattia IPF rapidamente progressivo, in modo da indirizzare tali pazienti alle terapie farmacologiche e al trapianto polmonare più precocemente

The thin line between sarcoidosis and cancer: can we consider PET as an oncologic screening tool in radiologically stable and asymptomatic sarcoidosis?

Is controversy over whether granulomatous inflammation is a precursor to future malignancy or whether a particular patient is predisposed to develop granulomatous inflammation in the presence of a tumor antigen. Our case report highlights the importance of PET as a diagnostic tool to be performed during the follow-up of asymptomatic patients who have been radiologically stable for years, for oncological screening purposes, considering the risk of developing cancer in sarcoidosis