Biology subjects

Arbustini, E.

Publications and source records attributed to Arbustini, E..

3 recordsLinked to original sources

bioRxiv2025

Uncovering genetic architecture of the heart via genetic association studies of unsupervised deep learning derived endophenotypes

Recent genome-wide association studies (GWAS) have effectively linked genetic variants to quantitative traits derived from time-series cardiac magnetic resonance imaging, revealing insights into cardiac morphology and function. Deep learning approach generally requires extensive supervised training on manually annotated data. In this study, we developed a novel framework using a 3D U-architecture autoencoder (cineMAE) to learn deep image phenotypes from cardiac magnetic resonance (CMR) imaging for genetic discovery, focusing on long-axis two-chamber and four-chamber views. We trained a masked autoencoder to develop Unsupervised Derived Image Phenotypes for heart (Heart-UDIPs). These representations were found to be informative to indicate various heart-specific phenotypes (e.g., left ventricular hypertrophy) and diseases (e.g., hypertrophic cardiomyopathy). GWAS on Heart UDIP identified 323 lead SNP and 628 SNP-prioritized genes, which exceeded previous methods. The genes identified by method described herein, exhibited significant associations with cardiac function and showed substantial enrichment in pathways related to cardiac disorders. These results underscore the utility of our Heart-UDIP approach in enhancing the discovery potential for genetic associations, without the need for clinically defined phenotypes or manual annotations.

bioinformatics↗

bioRxiv2021

A genetic variant alters the secondary structure of the lncRNA H19 and is associated with Dilated Cardiomyopathy

lncRNAs are at the core of many regulatory processes and have also been recognized to be involved in various complex diseases. They affect gene regulation through direct interactions with RNA, DNA or proteins. Accordingly, lncRNAs structure is likely to be essential for their regulatory function. Point mutations, which manifest as SNPs (single nucleotide polymorphisms) in genome screens, can substantially alter their function and, subsequently, the expression of their down-stream regulated genes. To test the effect of SNPs on structure, we investigated lncRNAs associated with dilated cardiomyopathy. Among 322 human candidate lncRNAs we demonstrate first the significant association of a SNP located in lncRNA H19 using data from 1084 diseased and 751 control patients. H19 is generally highly expressed in the heart, with a complex expression pattern during heart development. Next, we used MFE (minimum free energy) folding to demonstrate a significant refolding in the secondary structure of this 861 nt long lncRNA. Since MFE folding may overlook the importance of sub-optimal structures, we showed that this refolding also manifests in the overall Boltzmann structure ensemble. There, the composition of structures is tremendously affected in their thermodynamic probabilities through the genetic variant. Finally, we confirmed these results experimentally, using SHAPE-Seq, corroborating that SNPs affecting such structures may explain hidden genetic variance not accounted for through genome wide association studies. Our results suggest that structural changes in lncRNAs, and lncRNA H19 in particular, affect regulatory processes and represent optimal targets for further in-depth studies probing their molecular interactions.

genetics↗

bioRxiv2020

Genome wide association analysis in dilated cardiomyopathy reveals two new key players in systolic heart failure on chromosome 3p25.1 and 22q11.23

We present the results of the largest genome wide association study (GWAS) performed so far in dilated cardiomyopathy (DCM), a leading cause of systolic heart failure and cardiovascular death, with 2,719 cases and 4,440 controls in the discovery population. We identified and replicated two new DCM-associated loci, one on chromosome 3p25.1 (lead SNP rs62232870, p = 8.7 x 10-11 and 7.7 x 10-4 in the discovery and replication step, respectively) and the second on chromosome 22q11.23 (lead SNP rs7284877, p = 3.3 x 10-8 and 1.4 x 10-3 in the discovery and replication step, respectively) while confirming two previously identified DCM loci on chromosome 10 and 1, BAG3 and HSPB7. The genetic risk score constructed from the number of lead risk-alleles at these four DCM loci revealed that individuals with 8 risk-alleles were at a 27% increased risk of DCM compared to individuals with 5 risk alleles (median of the referral population). We estimated the genome wide heritability at 31% {+/-} 8%. In silico annotation and functional 4C-sequencing analysis on iPSC-derived cardiomyocytes strongly suggest SLC6A6 as the most likely DCM gene at the 3p25.1 locus. This gene encodes a taurine and beta-alanine transporter whose involvement in myocardial dysfunction and DCM is supported by recent observations in humans and mice. Although less easy to discriminate the better candidate at the 22q11.23 locus, SMARCB1 appears as the strongest one. This study provides both a better understanding of the genetic architecture of DCM and new knowledge on novel biological pathways underlying heart failure, with the potential for a therapeutic perspective.

genomics↗