| Title |
Biomarker patterns of inflammatory and metabolic pathways are associated with risk of colorectal cancer: results from the European Prospective Investigation into Cancer and Nutrition (EPIC)
|
|---|---|
| Published in |
European Journal of Epidemiology, May 2014
|
| DOI | 10.1007/s10654-014-9901-8 |
| Pubmed ID | |
| Authors |
Krasimira Aleksandrova, Mazda Jenab, H. Bas Bueno-de-Mesquita, Veronika Fedirko, Rudolf Kaaks, Annekatrin Lukanova, Fränzel J. B. van Duijnhoven, Eugene Jansen, Sabina Rinaldi, Isabelle Romieu, Pietro Ferrari, Neil Murphy, Marc J. Gunter, Elio Riboli, Sabine Westhpal, Kim Overvad, Anne Tjønneland, Jytte Halkjær, Marie-Christine Boutron-Ruault, Laure Dossus, Antoine Racine, Antonia Trichopoulou, Christina Bamia, Philippos Orfanos, Claudia Agnoli, Domenico Palli, Salvatore Panico, Rosario Tumino, Paolo Vineis, Petra H. Peeters, Eric J. Duell, Esther Molina-Montes, J. Ramón Quirós, Miren Dorronsoro, Maria-Dolores Chirlaque, Aurelio Barricarte, Ingrid Ljuslinder, Richard Palmqvist, Ruth C. Travis, Kay-Tee Khaw, Nicholas Wareham, Tobias Pischon, Heiner Boeing |
| Abstract |
A number of biomarkers of inflammatory and metabolic pathways are individually related to higher risk of colorectal cancer (CRC); however, the association between biomarker patterns and CRC incidence has not been previously evaluated. Our study investigates the association of biomarker patterns with CRC in a prospective nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC). During median follow-up time of 7.0 (3.7-9.4) years, 1,260 incident CRC cases occurred and were matched to 1,260 controls using risk-set sampling. Pre-diagnostic measurements of C-peptide, glycated hemoglobin, triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), C-reactive protein (CRP), reactive oxygen metabolites (ROM), insulin-like growth factor 1, adiponectin, leptin and soluble leptin receptor (sOB-R) were used to derive biomarker patterns from principal component analysis (PCA). The relation with CRC incidence was assessed using conditional logistic regression models. We identified four biomarker patterns 'HDL-C/Adiponectin fractions', 'ROM/CRP', 'TG/C-peptide' and 'leptin/sOB-R' to explain 60 % of the overall biomarker variance. In multivariable-adjusted logistic regression, the 'HDL-C/Adiponectin fractions', 'ROM/CRP' and 'leptin/sOB-R' patterns were associated with CRC risk [for the highest quartile vs the lowest, incidence rate ratio (IRR) = 0.69, 95 % CI 0.51-0.93, P-trend = 0.01; IRR = 1.70, 95 % CI 1.30-2.23, P-trend = 0.002; and IRR = 0.79, 95 % CI 0.58-1.07; P-trend = 0.05, respectively]. In contrast, the 'TG/C-peptide' pattern was not associated with CRC risk (IRR = 0.75, 95 % CI 0.56-1.00, P-trend = 0.24). After cases within the first 2 follow-up years were excluded, the 'ROM/CRP' pattern was no longer associated with CRC risk, suggesting potential influence of preclinical disease on these associations. By application of PCA, the study identified 'HDL-C/Adiponectin fractions', 'ROM/CRP' and 'leptin/sOB-R' as biomarker patterns representing potentially important pathways for CRC development. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Poland | 2 | 3% |
| Finland | 1 | 1% |
| United States | 1 | 1% |
| Canada | 1 | 1% |
| Unknown | 74 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 19% |
| Student > Ph. D. Student | 9 | 11% |
| Student > Master | 8 | 10% |
| Student > Bachelor | 7 | 9% |
| Student > Postgraduate | 6 | 8% |
| Other | 13 | 16% |
| Unknown | 21 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 28 | 35% |
| Nursing and Health Professions | 7 | 9% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Agricultural and Biological Sciences | 3 | 4% |
| Environmental Science | 2 | 3% |
| Other | 10 | 13% |
| Unknown | 25 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 November 2017.
All research outputs
#13,505,102
of 23,299,593 outputs
Outputs from European Journal of Epidemiology
#1,212
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Outputs of similar age
#111,309
of 228,962 outputs
Outputs of similar age from European Journal of Epidemiology
#20
of 28 outputs
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