Pancreatic cancer and autoimmune diseases: An association sustained by computational and epidemiological case-control approaches

Deciphering the underlying genetic basis behind pancreatic cancer (PC) and its associated multimorbidities will enhance our knowledge toward PC control. The study investigated the common genetic background of PC and different morbidities through a computational approach and further evaluated the les...

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Detalles Bibliográficos
Autores: Gomez-Rubio P, Piñero J, Molina-Montes E, Gutiérrez-Sacristán A, Marquez M, Rava M, Michalski CW, Farré A, Molero X, Löhr M, Perea J, Greenhalf W, O'Rorke M, Tardón A, Gress T, Barberá VM, Crnogorac-Jurcevic T, Muñoz-Bellvís L, Domínguez-Muñoz E, Balsells J, Costello E, Yu J, Iglesias M, Ilzarbe L, Kleeff J, Kong B, Mora J, Murray L, O'Driscoll D, Poves I, Lawlor RT, Ye W, Hidalgo M, Scarpa A, Sharp L, Carrato A, Real FX, Furlong LI, Malats N, PanGenEU Study Investigators
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Institución:Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)
Repositorio:r-FISABIO. Repositorio Institucional de Producción Científica
OAI Identifier:oai:fisabio.fundanetsuite.com:p3089
Acceso en línea:https://fisabio.portalinvestigacion.com/publicaciones/3089
Access Level:acceso abierto
Palabra clave:pancreatic cancer risk
autoimmune diseases
multimorbidity
genetic network
gene-disease associations
case-control study
Descripción
Sumario:Deciphering the underlying genetic basis behind pancreatic cancer (PC) and its associated multimorbidities will enhance our knowledge toward PC control. The study investigated the common genetic background of PC and different morbidities through a computational approach and further evaluated the less explored association between PC and autoimmune diseases (AIDs) through an epidemiological analysis. Gene-disease associations (GDAs) of 26 morbidities of interest and PC were obtained using the DisGeNET public discovery platform. The association between AIDs and PC pointed by the computational analysis was confirmed through multivariable logistic regression models in the PanGen European case-control study population of 1,705 PC cases and 1,084 controls. Fifteen morbidities shared at least one gene with PC in the DisGeNET database. Based on common genes, several AIDs were genetically associated with PC pointing to a potential link between them. An epidemiologic analysis confirmed that having any of the nine AIDs studied was significantly associated with a reduced risk of PC (Odds Ratio (OR) = 0.74, 95% confidence interval (CI) 0.58-0.93) which decreased in subjects having >= 2 AIDs (OR = 0.39, 95%CI 0.21-0.73). In independent analyses, polymyalgia rheumatica, and rheumatoid arthritis were significantly associated with low PC risk (OR = 0.40, 95%CI 0.19-0.89, and OR = 0.73, 95%CI 0.53-1.00, respectively). Several inflammatory-related morbidities shared a common genetic component with PC based on public databases. These molecular links could shed light into the molecular mechanisms underlying PC development and simultaneously generate novel hypotheses. In our study, we report sound findings pointing to an association between AIDs and a reduced risk of PC.

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