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



Lopez de Maturana, Evangelina, Rodriguez, Juan Antonio, Alonso, Lola, Lao, Oscar, Molina-Montes, Esther, Martin-Antoniano, Isabel Adoracion, Gomez-Rubio, Paulina, Lawlor, Rita, Carrato, Alfredo, Hidalgo, Manuel
et al (show 65 more authors) (2021) A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer. GENOME MEDICINE, 13 (1). 15-.

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Abstract

<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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 NR5A2 (rs3790840) with a meta-analysis p 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 CASC8-a lncRNA associated with pancreatic carcinogenesis-with a lowest p value = 6.91E-05. Importantly, two new PC loci were identified both by 2D and 3D approaches: SIAH3 (LMI = 18.24), CTRB2/BCAR1 (LMI = 6.03), in addition to a chromatin interacting region in XBP1-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.<h4>Conclusions</h4>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.

Item Type: Article
Uncontrolled Keywords: Pancreatic cancer risk, Genome-wide association analysis, Genetic susceptibility, 3D genomic structure, Local indices of genome spatial autocorrelation
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User: Symplectic Admin
Date Deposited: 17 Nov 2021 09:49
Last Modified: 18 Jan 2023 21:24
DOI: 10.1186/s13073-020-00816-4
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3143283