A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer

Medientyp: E-Artikel
Titel: A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer
Beteiligte: López de Maturana, Evangelina; Rodríguez, Juan Antonio; Alonso, Lola; Lao, Oscar; Molina-Montes, Esther; Martín-Antoniano, Isabel Adoración; Gómez-Rubio, Paulina; Lawlor, Rita; Carrato, Alfredo; Hidalgo, Manuel; Iglesias, Mar; Molero, Xavier; Löhr, Matthias; Michalski, Christopher; Perea, José; O’Rorke, Michael; Barberà, Victor Manuel; Tardón, Adonina; Farré, Antoni; Muñoz-Bellvís, Luís; Crnogorac-Jurcevic, Tanja; Domínguez-Muñoz, Enrique; Gress, Thomas; Greenhalf, William; [...]
Erschienen: Springer Science and Business Media LLC, 2021
Erschienen in: Genome Medicine
Sprache: Englisch
DOI: 10.1186/s13073-020-00816-4
ISSN: 1756-994X
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Beschreibung: <jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>We complemented a new conventional PC GWAS (1D) with genome spatial autocorrelation analysis (2D) permitting to prioritize low frequency variants not detected by GWAS. These were further expanded via Hi-C map (3D) interactions to gain additional insight into the inherited basis of PC. In silico functional analysis of public genomic information allowed prioritization of potentially relevant candidate variants.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>We identified several new variants located in genes for which there is experimental evidence of their implication in the biology and function of pancreatic acinar cells. Among them is a novel independent variant in <jats:italic>NR5A2</jats:italic> (rs3790840) with a meta-analysis <jats:italic>p</jats:italic> value = 5.91E−06 in 1D approach and a Local Moran’s Index (LMI) = 7.76 in 2D approach. We also identified a multi-hit region in <jats:italic>CASC8</jats:italic>—a lncRNA associated with pancreatic carcinogenesis—with a lowest <jats:italic>p</jats:italic> value = 6.91E−05. Importantly, two new PC loci were identified both by 2D and 3D approaches: <jats:italic>SIAH3</jats:italic> (LMI = 18.24), <jats:italic>CTRB2/BCAR1</jats:italic> (LMI = 6.03), in addition to a chromatin interacting region in <jats:italic>XBP1</jats:italic>—a major regulator of the ER stress and unfolded protein responses in acinar cells—identified by 3D; all of them with a strong in silico functional support.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusions</jats:title> <jats:p>This multi-step strategy, combined with an in-depth in silico functional analysis, offers a comprehensive approach to advance the study of PC genetic susceptibility and could be applied to other diseases.</jats:p> </jats:sec>
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