guest ::
| Home > Publications database > Individual and joint performance of DNA methylation profiles, genetic risk scores and environmental risk scores for predicting breast cancer risk. |
| Home > Publications database > Individual and joint performance of DNA methylation profiles, genetic risk scores and environmental risk scores for predicting breast cancer risk. |
| Journal Article | DKFZ-2019-02540 |
; ; ; ; ; ;
2020
John Wiley & Sons, Inc.
Hoboken, NJ
This record in other databases: 
Please use a persistent id in citations: doi:10.1002/1878-0261.12594
Abstract: DNA methylation patterns in the blood, genetic risk scores (GRSs) and environmental risk factors can potentially improve breast cancer (BC) risk prediction. We assessed the individual and joint predictive performance of methylation, GRS and environmental risk factors for BC incidence in a prospective cohort study. In a cohort of 5462 women aged 50-75 from Germany, 101 BC cases were identified during 14 years of follow-up and were compared to 263 BC-free controls in a nested case-control design. Three previously suggested methylation risk scores (MRSs) based on methylation of 423, 248 and 131 cytosine-phosphate-guanine (CpG) loci, and a GRS based on the risk alleles from 269 recently identified single-nucleotide polymorphisms were constructed. Additionally, multiple previously proposed environmental risk scores (ERSs) were built based on environmental variables. Areas under the receiver operating characteristic curves (AUCs) were estimated for evaluating BC risk prediction performance. MRS and ERS showed limited accuracy in predicting BC incidence, with AUCs ranging from 0.52 to 0.56 and from 0.52 to 0.59, respectively. The GRS predicted BC incidence with a higher accuracy (AUC=0.61). Adjusted odds ratios per standard deviation increase (95% confidence interval) were 1.07 (0.84-1.36) and 1.40 (1.09-1.80) for the best performing MRS and ERS, respectively, and 1.48 (1.16-1.90) for the GRS. A full risk model combining the MRS, GRS and ERS predicted BC incidence with the highest accuracy (AUC=0.64), and might be useful for identifying high-risk populations for BC screening.
; 
; 
; BIOSIS Previews ; Clarivate Analytics Master Journal List ; DOAJ Seal ; IF >= 5 ; JCR ; NCBI Molecular Biology Database ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
|
The record appears in these collections: |
