Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
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.

Vitality of the cyanolichen Peltigera praetextata exposed around a cement plant (SW Slovakia): a comparison with green algal lichens - Luca Paoli; Anna Guttová; Sergio Sorbo; Alice Grassi; Anna Lackovičová; Adriana Basile; Dušan Senko; Stefano Loppi (Biologia, 2016)

Ecophysiological and ultrastructural effects of dust pollution in lichens exposed around a cement plant (SW Slovakia) - Luca Paoli; Anna Guttová; Alice Grassi; Anna Lackovičová; Dušan Senko; Sergio Sorbo; Adriana Basile; Stefano Loppi (Environmental Science and Pollution Research, 2015)

Efficient automatic classifiers for the detection of A phases of the cyclic alternating pattern in sleep - Sara Mariani; Elena Manfredini; Valentina Rosso; Andrea Grassi; Martin O. Mendez; Alfonso Alba; Matteo Matteucci; Liborio Parrino; Mario G. Terzano; Sergio Cerutti; Anna M. Bianchi (Medical & Biological Engineering & Computing, 2012)

Enhanced Oral Bioavailability of Vinpocetine Through Mechanochemical Salt Formation: Physico-Chemical Characterization and In Vivo Studies - Dritan Hasa; Dario Voinovich; Beatrice Perissutti; Mario Grassi; Alois Bonifacio; Valter Sergo; Cinzia Cepek; Michele R. Chierotti; Roberto Gobetto; Stefano Dall’Acqua; Sergio Invernizzi (Pharmaceutical Research, 2011)

Hydrogeological study of the intensely exploited aquifer of the Santa Croce leather-producing district, Tuscany (central Italy) - Sergio Grassi; Marco Doveri; Gianni Cortecci; Michele Amadori (Hydrogeology Journal, 2011)

Spectroscopic properties and related functions of the stigma measured in living cells of Euglena gracilis - Pier Alberto Benedetti; Giovanni Bianchini; Alessandro Checcucci; Romano Ferrara; Sergio Grassi; Dyana Percival (Archives of Microbiology, 1976)