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

P Gomez-Rubio; V Rosato; M Márquez; C Bosetti; E Molina-Montes; M Rava; J Piñero; C W Michalski; A Farré; X Molero; M Löhr; L Ilzarbe; J Perea; W Greenhalf; A Tardón; T Gress; V M Barberá; T Crnogorac-Jurcevic; L Muñoz-Bellvís; E Domínguez-Muñoz; A Gutiérrez-Sacristán; J Balsells; E Costello; C Guillén-Ponce; J Huang; M Iglesias; J Kleeff; B Kong; J Mora; L Murray; D O'Driscoll; P Peláez; I Poves; R T Lawlor; A Carrato; M Hidalgo; A Scarpa; L Sharp; L I Furlong; F X Real; C La Vecchia; N Malats; PanGenEU Study Investigators

doi:10.1093/annonc/mdx167

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

P Gomez-Rubio, V Rosato, M Márquez, C Bosetti, E Molina-Montes, M Rava, J Piñero, C W Michalski, A Farré, X Molero, M Löhr, L Ilzarbe, J Perea, W Greenhalf, A Tardón, T Gress, V M Barberá, T Crnogorac-Jurcevic, L Muñoz-Bellvís, E Domínguez-MuñozA Gutiérrez-Sacristán, J Balsells, E Costello, C Guillén-Ponce, J Huang, M Iglesias, J Kleeff, B Kong, J Mora, L Murray, D O'Driscoll, P Peláez, I Poves, R T Lawlor, A Carrato, M Hidalgo, A Scarpa, L Sharp, L I Furlong, F X Real, C La Vecchia, N Malats, PanGenEU Study Investigators

Centre for Public Health

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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.

Original language	English
Pages (from-to)	1618-1624
Number of pages	7
Journal	Annals of Oncology
Volume	28
Issue number	7
Early online date	05 Apr 2017
DOIs	https://doi.org/10.1093/annonc/mdx167
Publication status	Published - 01 Jul 2017

Keywords

Journal Article

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Gomez-Rubio, P., Rosato, V., Márquez, M., Bosetti, C., Molina-Montes, E., Rava, M., Piñero, J., Michalski, C. W., Farré, A., Molero, X., Löhr, M., Ilzarbe, L., Perea, J., Greenhalf, W., Tardón, A., Gress, T., Barberá, V. M., Crnogorac-Jurcevic, T., Muñoz-Bellvís, L., ... PanGenEU Study Investigators (2017). A systems approach identifies time-dependent associations of multimorbidities with pancreatic cancer risk. Annals of Oncology, 28(7), 1618-1624. https://doi.org/10.1093/annonc/mdx167

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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.",

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author = "P Gomez-Rubio and V Rosato and M M{\'a}rquez and C Bosetti and E Molina-Montes and M Rava and J Pi{\~n}ero and Michalski, {C W} and A Farr{\'e} and X Molero and M L{\"o}hr and L Ilzarbe and J Perea and W Greenhalf and A Tard{\'o}n and T Gress and Barber{\'a}, {V M} and T Crnogorac-Jurcevic and L Mu{\~n}oz-Bellv{\'i}s and E Dom{\'i}nguez-Mu{\~n}oz and A Guti{\'e}rrez-Sacrist{\'a}n and J Balsells and E Costello and C Guill{\'e}n-Ponce and J Huang and M Iglesias and J Kleeff and B Kong and J Mora and L Murray and D O'Driscoll and P Pel{\'a}ez and I Poves and Lawlor, {R T} and A Carrato and M Hidalgo and A Scarpa and L Sharp and Furlong, {L I} and Real, {F X} and {La Vecchia}, C and N Malats and {PanGenEU Study Investigators}",

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doi = "10.1093/annonc/mdx167",

language = "English",

volume = "28",

pages = "1618--1624",

journal = "Annals of Oncology",

issn = "0923-7534",

publisher = "Oxford University Press",

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Gomez-Rubio, P, Rosato, V, Márquez, M, Bosetti, C, Molina-Montes, E, Rava, M, Piñero, J, Michalski, CW, Farré, A, Molero, X, Löhr, M, Ilzarbe, L, Perea, J, Greenhalf, W, Tardón, A, Gress, T, Barberá, VM, Crnogorac-Jurcevic, T, Muñoz-Bellvís, L, Domínguez-Muñoz, E, Gutiérrez-Sacristán, A, Balsells, J, Costello, E, Guillén-Ponce, C, Huang, J, Iglesias, M, Kleeff, J, Kong, B, Mora, J, Murray, L, O'Driscoll, D, Peláez, P, Poves, I, Lawlor, RT, Carrato, A, Hidalgo, M, Scarpa, A, Sharp, L, Furlong, LI, Real, FX, La Vecchia, C, Malats, N & PanGenEU Study Investigators 2017, 'A systems approach identifies time-dependent associations of multimorbidities with pancreatic cancer risk', Annals of Oncology, vol. 28, no. 7, pp. 1618-1624. https://doi.org/10.1093/annonc/mdx167

TY - JOUR

T1 - A systems approach identifies time-dependent associations of multimorbidities with pancreatic cancer risk

AU - Gomez-Rubio, P

AU - Rosato, V

AU - Márquez, M

AU - Bosetti, C

AU - Molina-Montes, E

AU - Rava, M

AU - Piñero, J

AU - Michalski, C W

AU - Farré, A

AU - Molero, X

AU - Löhr, M

AU - Ilzarbe, L

AU - Perea, J

AU - Greenhalf, W

AU - Tardón, A

AU - Gress, T

AU - Barberá, V M

AU - Crnogorac-Jurcevic, T

AU - Muñoz-Bellvís, L

AU - Domínguez-Muñoz, E

AU - Gutiérrez-Sacristán, A

AU - Balsells, J

AU - Costello, E

AU - Guillén-Ponce, C

AU - Huang, J

AU - Iglesias, M

AU - Kleeff, J

AU - Kong, B

AU - Mora, J

AU - Murray, L

AU - O'Driscoll, D

AU - Peláez, P

AU - Poves, I

AU - Lawlor, R T

AU - Carrato, A

AU - Hidalgo, M

AU - Scarpa, A

AU - Sharp, L

AU - Furlong, L I

AU - Real, F X

AU - La Vecchia, C

AU - Malats, N

AU - PanGenEU Study Investigators

PY - 2017/7/1

Y1 - 2017/7/1

N2 - 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.

AB - 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.

KW - Journal Article

U2 - 10.1093/annonc/mdx167

DO - 10.1093/annonc/mdx167

M3 - Article

C2 - 28383714

SN - 0923-7534

VL - 28

SP - 1618

EP - 1624

JO - Annals of Oncology

JF - Annals of Oncology

IS - 7

ER -

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

Abstract

Keywords

UN SDGs

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