By using genetic and molecular approaches, we investigate the underlying processes leading to the development of complex cardiovascular disorders (CVDs), which are major contributors to morbidity and mortality worldwide. We have interests into how common noncoding gene variants control gene expression and drive network signalling pathways leading to vascular atheroma and heart valve fibrocalcification. We use prioritization of potential novel therapeutic targets and causal inference to track the molecular phenome of CVDs.
1. Integrative Mapping and Network Organization. Genome-wide association (GWA) studies and electronic health record databanks generate a wealth of genetic association data. However, for a vast majority of loci, causal gene variants and dysregulated genes remain unknown. We have developed several approaches to probe loci. We are interested into how functional annotation combined with Bayesian analyses and 3D genome mapping can decipher the genetic architecture of complex CVDs such as atheroma and heart valve disorders (HVDs) (Arnaud Chignon and Zhonglin Li). One important question we are probing is how haplotype-resolved data at loci may help identify causal gene variants and their targets. Complex trait disorders affect the expression of a large number of genes. Integration of data in network organization identify ‘hub genes’, which are often enriched in potential therapeutic targets. We are thus investigating how CVDs modify the landscape of gene networks and we look into how these approaches help prioritize ‘hub genes’ for follow-up functional studies.
2. Molecular quantitative traits and causal inference by using genetic association data. Multi ‘omics’ data, including several molecular quantitative traits (QTLs), offer opportunities for multidimensional mapping and causal inference (Arnaud Chignon and Valentin Bon-Baret). We are using several epigenetic and expression QTLs to further assess how gene variants impact the molecular phenome of CVDs. Integration of expression and protein QTLs with genetic association data allows causal inference by Mendelian Randomization (MR). By using MR, we are interested into how causal inference may help identify key causal genes in network prioritized pathways. Furthermore, by using Phenome-wide association analyses, we investigate how pleiotropy is acting on CVDs. For instance, how pleiotropy is manifested in inflammatory disorders and CVDs and affect longevity (Mickael Rosa).
3. Functional Genomics and Molecular Pathway Characterization. One key central question we are probing is how common noncoding gene variants associated with complex trait disorders alter transcription factors (TFs), drivers of cell identity and fate, binding to DNA. Several algorithms are used in the lab to predict and prioritize causal variants based on their ability to modify TF binding sites (TFBS). Sequence information-based approaches as well as machine-learning algorithms are used to prioritize gene variants that may alter TF’s functions. Atomic-resolution data derived from published crystallographic studies are used to model potential molecular processes whereby a variant may affect protein-DNA interaction. We are interested into how these data may help predict experimental binding of TFs to DNA and their functional impacts. We explore several techniques such as DNA-binding, reporter assays and chromatin immunoprecipitation to functionally validate our models (Romain DeVillers). At the cell level, we are probing how altered gene expression affects the function of vascular and valve cells (Marie-Chloé Boulanger). We exploit several cell and molecular assays to identify the interactome of dysregulated genes and its impact on cell function.
4. Control of gene expression. The transcriptional process is tightly regulated by several molecular complexes that affect the initiation, elongation and termination steps. One key question we are addressing is how gene transcription is regulated in complex disorders by epigenome regulators, gene variants and noncoding RNAs and how it interacts with genome looping. Both transcription and chromatin looping are intertwined in complex interactions, which may affect chromatin condensation. We explore how pause release of RNA Polymerase II is controlled by epigenome modifiers and noncoding RNAs at distant-acting enhancer and how it may impact on genome 3D organization (Deborah Argaud). In addition, we investigate how novel protein complex may impact pause release and the production of nascent transcripts.
Congratulations to Arnaud for his paper in Communications Biology: Single-cell expression and Mendelian randomization analyses identify blood genes associated with lifespan and chronic disease.
Congratulations to Mickael for his paper in npg Genomic Medicine: A Mendelian randomization study of IL6 signaling in cardiovascular diseases, immune-related disorsers and longevity.
Congratulations to Déborah for her paper recently accepted in Nucleic Acids Res on the control of transcription by a novel protein complex. We look forward to reading the work when published!
Congratulations to Arnaud and Déborah for their recent presentation at the IUCPQ research meeting on their innovative work on the causal inference for cytokine signalling in CVDs-longevity and molecular genetics of a novel mechanism that control pause release of RNA polymerase.
Great news, Mickael recently won a prize for its work on the locus 1p21 in CAVS at the Printemps de la Cardiologie in Lille, France. Bravo Mickael!