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A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer
Journal article   Open access   Peer reviewed

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

Evangelina López de Maturana, Juan Antonio Rodríguez, Lola Alonso, Oscar Lao, Esther Molina-Montes, Isabel Adoración Martín-Antoniano, Paulina Gómez-Rubio, Rita Lawlor, Alfredo Carrato, Manuel Hidalgo, …
Genome medicine, Vol.13(1), pp.15-15
02/01/2021
DOI: 10.1186/s13073-020-00816-4
PMCID: PMC7849104
PMID: 33517887
url
https://doi.org/10.1186/s13073-020-00816-4View
Published (Version of record) Open Access

Abstract

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. 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. 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. 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.
Biomarkers, Tumor - genetics Cell Line, Tumor Computer Simulation Gene Regulatory Networks Genetic Predisposition to Disease Genome, Human Genome-Wide Association Study Humans Linkage Disequilibrium - genetics Pancreatic Neoplasms - genetics Reproducibility of Results Signal Transduction - genetics

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