Impact of MIF Gene Promoter Polymorphism on F508del Cystic Fibrosis Patients

Macrophage migration Inhibitory Factor (MIF) is a pro-inflammatory cytokine sustaining the acute response to gram-negative bacteria and a regulatory role for MIF in Cystic Fibrosis has been suggested by the presence of a functional, polymorphic, four-nucleotide repeat in this gene's promoter at position -794, with the 5-repeat allele displaying lower promoter activity. We aimed at assessing the association of this polymorphism with disease severity in a group of Cystic Fibrosis patients homozygous for F508del CFTR gene mutation. Genotype frequencies were determined in 189 Cystic Fibrosis and 134 control subjects; key clinical features of patients were recorded and compared among homozygous 5-allele patients and the other MIF genotypes. Patients homozygous for the 5-repeat allele of MIF promoter displayed a slower rate of lung function decline (p\u200a=\u200a0.027) at multivariate survival analysis. Multiple regression analysis on age-normalized respiratory volume showed no association of the homozygous 5-repeat genotype with lung function under stable conditions and no correlation with P.aeruginosa chronic colonization. Therefore, only the Homozygous 5-repeat genotype at MIF -794 is associated with milder disease in F508del Cystic Fibrosis patients

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

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)