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Comprehensive Identification of Pleiotropic Associations for Clonal Haematopoiesis of Indeterminate Potential
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Edité par CCSD -
International audience. Background:Clonal haematopoiesis of indeterminate potential (CHIP) is an age-related pre-clinical condition, defined by the presence of driver somatic mutations in leukemia-associated genes occurring in hematopoietic stem cells. It is associated with an increased risk of developing hematologic and non-hematologic disorders including leukemia, solid cancers or cardiovascular diseases. Still, knowledge about the inherited and environmental actors shaping CHIP epidemiology is incomplete. Recently, genomewide associations studies (GWAS) have reported several predisposing rare and common variants associated with CHIP across multiple genomic loci, as a background facilitating its emergence.Aims:Although associations with diverse phenotypes have been reported from epidemiological and mendelian randomization studies, the contribution of all the genotypic features underpinning the spectrum of possible CHIP-associated traits remains poorly explored. Here we catalogued single nucleotide polymorphisms (SNPs) associated with CHIP and explored their pleiotropic potential.Methods:Starting from the NHGRI-EBI GWAS Catalog, we identified studies including large cohorts of European individuals (4 studies including in total: 483.551, 65.461, 184.121, and 32.058 European individuals) and inventoried all the SNPs reaching genome-wide significance (p<5x10-8) for their association with CHIP. We augmented this list with the proxy SNPs (pSNPs) in strong to perfect linkage disequilibrium (LD, r² > 0.9) with the lead SNPs (lSNPs) formally identified. CHIP-associated genetic blocks were defined as an agglomeration of SNPs in LD with the lSNPs (r² ≥ 0.1). We then investigated all other significant associations between human traits and the inventoried lSNPs + pSNPs. These were summarized into cross-trait categories for which we reported enrichments and over-representation statistics (Fisher’s exact test), and the direction of effects with CHIP (Figure A).Results:Four case-control GWAS, reporting 110 lSNPs (p<5x10-8) in strong LD with another 960 pSNPs have been selected and used for determining 330 phenotypic associations with CHIP. These were summarized into 14 trait categories (Figure 1B), 12 of which showing significant enrichments, either positive or negative, against random expectancy. The highly enriched associations concerned cancers including glioma (mostly glioblastoma; p=3.4e-28), lung carcinoma, melanoma and colorectal cancer (grouped p=2.6e-17), sex-specific cancers (breast, prostate and testicular, p=8.2e-7), and lymphoid leukemia (p=0.02). Pre-malignant states (p=4.1e-3), inflammation (p=1.8e-16), and aging parameters including telomere length (p=1.5e-12) were also over-represented. Cardiometabolic traits (type 2 diabetes, cholesterol measurements) are here found significantly associated (p=8e-16) but strongly depleted against background (Figure B). We will further augment these results by building the protein/protein interaction network around the causal genes identified with the geneticblocks to decipher the biological modules and pathways underlying CHIP condition and explaining the links with these cross-phenotypes.Summary/Conclusion:Here we revisited the accumulated knowledge obtained through genotype-phenotype association studies and reconstruct the pleiotropic associations around CHIP genetic architecture. We confirmed results that have already been noted in observational studies, others that have been reported physiologically, and new associations, providing a wider network surrounding CHIP condition.
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