House Dust Mite Allergy and the Der p1 Conundrum: A Literature Review and Case Series

The house dustmite (HDM) is globally ubiquitous in human habitats. Thirty-two allergens for Dermatophagoides farinae and 21 for Dermatophagoides pteronyssinus have been detected so far. The present minireview summarizes information about the role of Der p 1 as a key coordinator of the HDM-induced allergic response and reports on a series of Italian patients who are allergic to HDMs. We studied the specific IgE profiles in a population of patients with allergic asthma and rhinitis screened for specific immunotherapy (SIT) for HDMallergies, with the aim of obtaining insights into the pathogenic role of Der p1. Patients co-sensitized to other airborne allergens showed a higher prevalence of asthma (9/12 (75%) vs. 2/7 (29%); p < 0.05) than did HDMmono-sensitized patients. The latter group showed higher Der p1 concentrations than that of the co-sensitized group (p = 0.0360), and a direct correlation between Der p1 and Der p2 (r = 0.93; p = 0.0003) was observed. In conclusion, our study offers insights into the role of Der p1 in a population of patients with allergic rhinitis and asthma who were candidates for SIT. Interestingly, Der p1 positivity was associated with bronchial asthma and co-sensitization

BAL Proteomic Signature of Lung Adenocarcinoma in IPF Patients and Its Transposition in Serum Samples for Less Invasive Diagnostic Procedures

Idiopathic pulmonary fibrosis (IPF) is a form of chronic and irreversible fibrosing interstitial pneumonia of unknown etiology. Although antifibrotic treatments have shown a reduction of lung function decline and a slow disease progression, IPF is characterize by a very high mortality. Emerging evidence suggests that IPF increases the risk of lung carcinogenesis. Both diseases show similarities in terms of risk factors, such as history of smoking, concomitant emphysema, and viral infections, besides sharing similar pathogenic pathways. Lung cancer (LC) diagnosis is often difficult in IPF patients because of the diffuse lung injuries and abnormalities due to the underlying fibrosis. This is reflected in the lack of optimal therapeutic strategies for patients with both diseases. For this purpose, we performed a proteomic study on bronchoalveolar lavage fluid (BALF) samples from IPF, LC associated with IPF (LC-IPF) patients, and healthy controls (CTRL). Molecular pathways involved in inflammation, immune response, lipid metabolism, and cell adhesion were found for the dysregulated proteins in LC-IPF, such as TTHY, APOA1, S10A9, RET4, GDIR1, and PROF1. The correlation test revealed a relationship between inflammation- and lipid metabolism-related proteins. PROF1 and S10A9, related to inflammation, were up-regulated in LC-IPF BAL and serum, while APOA1 and APOE linked to lipid metabolism, were highly abundant in IPF BAL and low abundant in IPF serum. Given the properties of cytokine/adipokine of the nicotinamide phosphoribosyltransferase, we also evaluated its serum abundance, highlighting its down-regulation in LC-IPF. Our retrospective analyses of BAL samples extrapolated some potential biomarkers of LC-IPF useful to improve the management of these contemporary pathologies. Their differential abundance in serum samples permits the measurement of these potential biomarkers with a less invasive procedure

Carriers of ADAMTS13 Rare Variants Are at High Risk of Life-Threatening COVID-19

Thrombosis of small and large vessels is reported as a key player in COVID-19 severity. However, host genetic determinants of this susceptibility are still unclear. Congenital Thrombotic Thrombocytopenic Purpura is a severe autosomal recessive disorder characterized by uncleaved ultra-large vWF and thrombotic microangiopathy, frequently triggered by infections. Carriers are reported to be asymptomatic. Exome analysis of about 3000 SARS-CoV-2 infected subjects of different severities, belonging to the GEN-COVID cohort, revealed the specific role of vWF cleaving enzyme ADAMTS13 (A disintegrin-like and metalloprotease with thrombospondin type 1 motif, 13). We report here that ultra-rare variants in a heterozygous state lead to a rare form of COVID-19 characterized by hyper-inflammation signs, which segregates in families as an autosomal dominant disorder conditioned by SARS-CoV-2 infection, sex, and age. This has clinical relevance due to the availability of drugs such as Caplacizumab, which inhibits vWF-platelet interaction, and Crizanlizumab, which, by inhibiting P-selectin binding to its ligands, prevents leukocyte recruitment and platelet aggregation at the site of vascular damage

Pathogen-sugar interactions revealed by universal saturation transfer analysis

Many pathogens exploit host cell-surface glycans. However, precise analyses of glycan ligands binding with heavily modified pathogen proteins can be confounded by overlapping sugar signals and/or compounded with known experimental constraints. Universal saturation transfer analysis (uSTA) builds on existing nuclear magnetic resonance spectroscopy to provide an automated workflow for quantitating protein-ligand interactions. uSTA reveals that early-pandemic, B-origin-lineage severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike trimer binds sialoside sugars in an “end-on” manner. uSTA-guided modeling and a high-resolution cryo–electron microscopy structure implicate the spike N-terminal domain (NTD) and confirm end-on binding. This finding rationalizes the effect of NTD mutations that abolish sugar binding in SARS-CoV-2 variants of concern. Together with genetic variance analyses in early pandemic patient cohorts, this binding implicates a sialylated polylactosamine motif found on tetraantennary N-linked glycoproteins deep in the human lung as potentially relevant to virulence and/or zoonosis

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

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

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)

Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features

The impact of common and rare variants in COVID-19 host genetics has been widely studied. In particular, in Fallerini et al. (Human genetics, 2022, 141, 147–173), common and rare variants were used to define an interpretable machine learning model for predicting COVID-19 severity. First, variants were converted into 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. After that, the Boolean features, selected by these logistic models, were combined into an Integrated PolyGenic Score (IPGS), which offers a very simple description of the contribution of host genetics in COVID-19 severity.. IPGS leads to an accuracy of 55%–60% on different cohorts, and, after a logistic regression with both IPGS and age as inputs, it leads to an accuracy of 75%. The goal of this paper is to improve the previous results, using not only the most informative Boolean features with respect to the genetic bases of severity but also the information on host organs involved in the disease. In this study, we generalize the IPGS adding a statistical weight for each organ, through the transformation of Boolean features into “Boolean quantum features,” inspired by quantum mechanics. The organ coefficients were set via the application of the genetic algorithm PyGAD, and, after that, we defined two new integrated polygenic scores (IPGSph1 and IPGSph2). By applying a logistic regression with both IPGS, (IPGSph2 (or indifferently IPGSph1) and age as inputs, we reached an accuracy of 84%–86%, thus improving the results previously shown in Fallerini et al. (Human genetics, 2022, 141, 147–173) by a factor of 10%

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

The Effects of Interstitial Lung Diseases on Alveolar Extracellular Vesicles Profile: A Multicenter Study

Diagnosis of interstitial lung diseases (ILD) is difficult to perform. Extracellular vesicles (EVs) facilitate cell-to-cell communication, and they are released by a variety of cells. Our goal aimed to investigate EV markers in bronchoalveolar lavage (BAL) from idiopathic pulmonary fibrosis (IPF), sarcoidosis and hypersensitivity pneumonitis (HP) cohorts. ILD patients followed at Siena, Barcelona and Foggia University Hospitals were enrolled. BAL supernatants were used to isolate the EVs. They were characterized by flow cytometry assay through MACSPlex Exsome KIT. The majority of alveolar EV markers were related to the fibrotic damage. CD56, CD105, CD142, CD31 and CD49e were exclusively expressed by alveolar samples from IPF patients, while HP showed only CD86 and CD24. Some EV markers were common between HP and sarcoidosis (CD11c, CD1c, CD209, CD4, CD40, CD44, CD8). Principal component analysis distinguished the three groups based on EV markers with total variance of 60.08%. This study has demonstrated the validity of the flow cytometric method to phenotype and characterize EV surface markers in BAL samples. The two granulomatous diseases, sarcoidosis and HP, cohorts shared alveolar EV markers not revealed in IPF patients. Our findings demonstrated the viability of the alveolar compartment allowing identification of lung-specific markers for IPF and HP