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Ann Oncol. 2017 Jul 1;28(7):1618-1624. doi: 10.1093/annonc/mdx167.

A systems approach identifies time-dependent associations of multimorbidities with pancreatic cancer risk.

Author information

1
Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Center (CNIO), Madrid, and CIBERONC, Spain.
2
Branch of Medical Statistics, Biometry and Epidemiology "G.A. Maccacaro," Department of Clinical Sciences and Community Health, University of Milan, Milan.
3
Unit of Medical Statistics, Biometry and Bioinformatics, National Cancer Institute, IRCCS Foundation, Milan.
4
Department of Epidemiology, Mario Negri Institute for Pharmacological Research-IRCCS, Milan, Italy.
5
Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute (IMIM), Pompeu Fabra Univeristy (UPF), Barcelona, Spain.
6
Department of Surgery, Technical University of Munich, Munich.
7
Department of Surgery, University of Heidelberg, Heidelberg, Germany.
8
Department of Gastroenterology, Santa Creu i Sant Pau Hospital, Barcelona.
9
Exocrine Pancreas Research Unit and Vall d'Hebron Research Institute (VHIR), Vall d'Hebron University Hospital, Barcelona.
10
Department of Medicine, Universitat Autònoma de Barcelona, Barcelona.
11
Network of Biomedical Research Centres (CIBER), Hepatic and Digestive Diseases and Epidemiology and Public Health, Madrid, Spain.
12
Gastrocentrum, Karolinska Institutet and University Hospital, Stockholm, Sweden.
13
Department of Gastroenterology, Parc de Salut Mar University Hospital, Barcelona.
14
Department of Surgery, 12 de Octubre University Hospital, Madrid, Spain.
15
Department of Molecular and Clinical Cancer Medicine, The Royal Liverpool University Hospital, Liverpool.
16
Centre for Public Health, Queen's University Belfast, Belfast, UK.
17
Department of Medicine, University Institute of Oncology of Asturias, Oviedo, Spain.
18
Department of Gastroenterology, University Hospital of Giessen and Marburg, Marburg, Germany.
19
Molecular Genetics Laboratory, General University Hospital of Elche, Elche, Spain.
20
Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, London, UK.
21
General and Digestive Surgery Department, Salamanca University Hospital, Salamanca.
22
Department of Gastroenterology, Clinical University Hospital of Santiago de Compostela, Santiago de Compostela.
23
Department of Oncology, Ramón y Cajal Hospital, Madrid, and CIBERONC, Spain.
24
Research Programme, National Cancer Registry Ireland.
25
ARC-Net Centre for Applied Research on Cancer and Department of Pathology and Diagnostics, University and Hospital trust of Verona, Verona, Italy.
26
Clara Campal Integrated Oncological Centre, Sanchinarro Hospital, Madrid, Spain.
27
Institute of Health & Society, Newcastle University, UK.
28
Epithelial Carcinogenesis Group, Spanish National Cancer Research Centre (CNIO), Madrid, and CIBERONC.
29
Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain.

Abstract

Background:

Pancreatic ductal adenocarcinoma (PDAC) is usually diagnosed in late adulthood; therefore, many patients suffer or have suffered from other diseases. Identifying disease patterns associated with PDAC risk may enable a better characterization of high-risk patients.

Methods:

Multimorbidity patterns (MPs) were assessed from 17 self-reported conditions using hierarchical clustering, principal component, and factor analyses in 1705 PDAC cases and 1084 controls from a European population. Their association with PDAC was evaluated using adjusted logistic regression models. Time since diagnosis of morbidities to PDAC diagnosis/recruitment was stratified into recent (<3 years) and long term (≥3 years). The MPs and PDAC genetic networks were explored with DisGeNET bioinformatics-tool which focuses on gene-diseases associations available in curated databases.

Results:

Three MPs were observed: gastric (heartburn, acid regurgitation, Helicobacter pylori infection, and ulcer), metabolic syndrome (obesity, type-2 diabetes, hypercholesterolemia, and hypertension), and atopic (nasal allergies, skin allergies, and asthma). Strong associations with PDAC were observed for ≥2 recently diagnosed gastric conditions [odds ratio (OR), 6.13; 95% confidence interval CI 3.01-12.5)] and for ≥3 recently diagnosed metabolic syndrome conditions (OR, 1.61; 95% CI 1.11-2.35). Atopic conditions were negatively associated with PDAC (high adherence score OR for tertile III, 0.45; 95% CI, 0.36-0.55). Combining type-2 diabetes with gastric MP resulted in higher PDAC risk for recent (OR, 7.89; 95% CI 3.9-16.1) and long-term diagnosed conditions (OR, 1.86; 95% CI 1.29-2.67). A common genetic basis between MPs and PDAC was observed in the bioinformatics analysis.

Conclusions:

Specific multimorbidities aggregate and associate with PDAC in a time-dependent manner. A better characterization of a high-risk population for PDAC may help in the early diagnosis of this cancer. The common genetic basis between MP and PDAC points to a mechanistic link between these conditions.

KEYWORDS:

multimorbidity; pancreatic cancer; risk

PMID:
28383714
DOI:
10.1093/annonc/mdx167
[Indexed for MEDLINE]

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