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Updated: Sep 2, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Gene-Based Variant Analysis of Whole-Exome Sequencing in Relation to Eosinophil Count
Julia Höglund1, Fatemeh Hadizadeh1, Weronica E Ek1
1Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Abstract:
Eosinophils play important roles in the release of cytokine mediators in response to inflammation. Many associations between common genetic variants and eosinophils have already been reported, using single nucleotide polymorphism (SNP) array data. Here, we have analyzed 200,000 whole-exome sequences (WES) from the UK Biobank cohort and performed gene-based analyses of eosinophil count. We defined five different variant weighting schemes to incorporate information on both deleteriousness and frequency. A total of 220 genes in 55 distinct (>10 Mb apart) genomic regions were found to be associated with eosinophil count, of which seven genes (ALOX15, CSF2RB, IL17RA, IL33, JAK2, S1PR4, and SH2B3) are driven by rare variants, independent of common variants identified in genome-wide association studies. Two additional genes, NPAT and RMI1, have not been associated with eosinophil count before and are considered novel eosinophil loci. These results increase our knowledge about the effect of rare variants on eosinophil count, which can be of great value for further identification of therapeutic targets.
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