A microRNA panel compared to environmental and polygenic scores for colorectal cancer risk prediction.
Aged
Aged, 80 and over
Biomarkers, Tumor
/ blood
Colorectal Neoplasms
/ blood
Female
Gene Expression Regulation, Neoplastic
Humans
Logistic Models
Male
MicroRNAs
/ blood
Middle Aged
Multifactorial Inheritance
/ genetics
Polymorphism, Single Nucleotide
Prospective Studies
ROC Curve
Real-Time Polymerase Chain Reaction
/ methods
Risk Factors
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
10 08 2021
10 08 2021
Historique:
received:
26
11
2020
accepted:
12
07
2021
entrez:
11
8
2021
pubmed:
12
8
2021
medline:
24
8
2021
Statut:
epublish
Résumé
Circulating microRNAs (miRNAs) could improve colorectal cancer (CRC) risk prediction. Here, we derive a blood-based miRNA panel and evaluate its ability to predict CRC occurrence in a population-based cohort of adults aged 50-75 years. Forty-one miRNAs are preselected from independent studies and measured by quantitative-real-time-polymerase-chain-reaction in serum collected at baseline of 198 participants who develop CRC during 14 years of follow-up and 178 randomly selected controls. A 7-miRNA score is derived by logistic regression. Its predictive ability, quantified by the optimism-corrected area-under-the-receiver-operating-characteristic-curve (AUC) using .632+ bootstrap is 0.794. Predictive ability is compared to that of an environmental risk score (ERS) based on known risk factors and a polygenic risk score (PRS) based on 140 previously identified single-nucleotide-polymorphisms. In participants with all scores available, optimism-corrected-AUC is 0.802 for the 7-miRNA score, while AUC (95% CI) is 0.557 (0.498-0.616) for the ERS and 0.622 (0.564-0.681) for the PRS.
Identifiants
pubmed: 34376648
doi: 10.1038/s41467-021-25067-8
pii: 10.1038/s41467-021-25067-8
pmc: PMC8355103
doi:
Substances chimiques
Biomarkers, Tumor
0
MicroRNAs
0
Types de publication
Comparative Study
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4811Informations de copyright
© 2021. The Author(s).
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