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Dagenais, F.

Publications and source records attributed to Dagenais, F..

3 recordsLinked to original sources

Decoding causal genes and programs from regulatory variants in aortic valve disease

Aortic valve disease is common, yet its regulatory mechanisms remain poorly understood. We performed multi-omic profiling of human aortic valve interstitial cells (HAVICs), identifying 11,891 allele-specific chromatin accessibility QTLs (as-caQTLs), 48% novel to this cell type. These variants were enriched in active enhancers, disrupted transcription factor (TF) motifs, particularly AP-1, TEAD and GATA families, and were validated by allele-specific TF binding assays. A fine-tuned deep DNA sequence model prioritized common and rare variants at risk loci predicted to impact chromatin accessibility. Single-cell CRISPRi perturbation of 247 variants identified cis-target genes at 55 as-caQTL elements, including loci without eQTLs. We demonstrate that common regulatory variants controlling elastin and fibrillin impact the development of the aortic valve apparatus. We provide genetic evidence and a mechanistic framework for the contribution of a reduced aortic root size to CAVD risk. Perturbations identified core cell programs led by upstream regulators AHNAK, PDIA6, and RNFT1 converging on extracellular matrix production and iron transport.

genetics↗

Genetic association analyses highlight IL6, ALPL, and NAV1 as three new susceptibility genes underlying calcific aortic valve stenosis

To date, only two replicated loci, LPA and PALMD, have been identified as causal genes for calcific aortic valve stenosis (CAVS) using genome-wide and transcriptome-wide association study (TWAS). To identify additional susceptibility genes for CAVS, we performed a GWAS meta-analysis totaling 5,115 cases and 354,072 controls of European descent. Four loci achieved genome-wide significance, including two new loci: IL6 (interleukin 6) on 7p15.3 and ALPL (alkaline phosphatase) on 1p36.12. A TWAS integrating an eQTL study of 233 human aortic valves identified NAV1 (neuron navigator 1) on 1q32.1 as a new candidate causal gene. The CAVS risk alleles were associated with higher mRNA expression of NAV1 in valve tissues. Association results at the genome-wide scale showed genetic correlation with coronary artery disease and cardiovascular risk factors. Our study highlights three new loci implicating inflammation, mineralization and blood vessel integrity in CAVS pathogenesis and supports shared genetic etiology with cardiovascular traits.

genomics↗

A transcriptome-wide association study identifies PALMD as a susceptibility gene for calcific aortic valve stenosis

Calcific aortic valve stenosis (CAVS) is a common and life-threatening heart disease with no drug that can stop or delay its progression. Elucidating the genetic factors underpinning CAVS is an urgent priority to find new therapeutic targets1. Major landmarks in genetics of CAVS include the discoveries of NOTCH12 and LPA3. However, genetic variants in these genes accounted for a small number of cases and low population-attributable risk. Here we mapped a new susceptibility locus for CAVS on chromosome 1p21.2 and identified PALMD (palmdelphin) as the causal gene. PALMD was revealed using a transcriptome-wide association study (TWAS)4, which combines a genome-wide association study (GWAS) of 1,009 cases and 1,017 ethnically-matched controls with the first large-scale expression quantitative trait loci (eQTL) mapping study on human aortic valve tissues (n=233). The CAVS risk alleles and increasing disease severity were both associated with lowered mRNA expression levels of PALMD in valve tissues. The top variant explained up to 12.5% of the population-attributable risk and showed similar effect and strong association with CAVS (P=1.53 x 10-10) in UK Biobank comparing 1,391 cases and 352,195 controls. The identification of PALMD as a susceptibility gene for CAVS provides new insights about the genetic nature of this disease and opens new avenues to investigate its etiology and develop much-needed therapeutic options.

genomics↗