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.

Gene co-expression analysis identifies brain regions and cell types involved in migraine pathophysiology: a GWAS-based study using the Allen Human Brain Atlas - Else Eising; Sjoerd M. H. Huisman; Ahmed Mahfouz; Lisanne S. Vijfhuizen; Verneri Anttila; Bendik S. Winsvold; Tobias Kurth; M. Arfan Ikram; Tobias Freilinger; Jaakko Kaprio; Dorret I. Boomsma; Cornelia M. van Duijn; et al. (Human Genetics, 2016)

Progressive genome‐wide introgression in agricultural Campylobacter coli - Samuel K. Sheppard; Xavier Didelot; Keith A. Jolley; Aaron E. Darling; Ben Pascoe; Guillaume Meric; David J. Kelly; Alison Cody; Frances M. Colles; Norval J. C. Strachan; Iain D. Ogden; Ken Forbes; et al. (Molecular Ecology, 2013)
Hybridization between distantly related organisms can facilitate rapid adaptation to novel environments, but is potentially constrained by epistatic fitness interactions among cell components. The zoonotic pathogens C ampylobacter coli and C . jejuni differ from each other by around 15% at the nucleotide level, corresponding to an average of nearly 40 amino acids per protein‐coding gene. Using whole genome sequencing, we show that a single C. coli lineage, which has successfully colonized an agricultural niche, has been progressively accumulating C. jejuni DNA . Members of this lineage belong to two groups, the ST ‐828 and ST ‐1150 clonal complexes. The ST ‐1150 complex is less frequently isolated and has undergone a substantially greater amount of introgression leading to replacement of up to 23% of the C. coli core genome as well as import of novel DNA . By contrast, the more commonly isolated ST ‐828 complex bacteria have 10–11% introgressed DNA , and C. jejuni and nonagricultural C. coli lineages each have C. coli that colonize agriculture, and consequently cause most human disease, have hybrid origin, but this cross‐species exchange has so far not had a substantial impact on the gene pools of either C. jejuni or nonagricultural C. coli . These findings also indicate remarkable interchangeability of basic cellular machinery after a prolonged period of independent evolution.