Polygenic prediction of breast cancer: comparison of genetic predictors and implications for risk stratification.

Polygenic prediction of breast cancer: comparison of genetic predictors and implications for risk stratification.

Publication date: Jun 10, 2019

Published genetic risk scores for breast cancer (BC) so far have been based on a relatively small number of markers and are not necessarily using the full potential of large-scale Genome-Wide Association Studies. This study aimed to identify an efficient polygenic predictor for BC based on best available evidence and to assess its potential for personalized risk prediction and screening strategies.

Four different genetic risk scores (two already published and two newly developed) and their combinations (metaGRS) were compared in the subsets of two population-based biobank cohorts: the UK Biobank (UKBB, 3157 BC cases, 43,827 controls) and Estonian Biobank (EstBB, 317 prevalent and 308 incident BC cases in 32,557 women). In addition, correlations between different genetic risk scores and their associations with BC risk factors were studied in both cohorts.

The metaGRS that combines two genetic risk scores (metaGRS – based on 75 and 898 Single Nucleotide Polymorphisms, respectively) had the strongest association with prevalent BC status in both cohorts. One standard deviation difference in the metaGRS corresponded to an Odds Ratio = 1.6 (95% CI 1.54 to 1.66, p = 9.7*10) in the UK Biobank and accounting for family history marginally attenuated the effect (Odds Ratio = 1.58, 95% CI 1.53 to 1.64, p = 7.8*10). In the EstBB cohort, the hazard ratio of incident BC for the women in the top 5% of the metaGRS compared to women in the lowest 50% was 4.2 (95% CI 2.8 to 6.2, p = 8.1*10). The different GRSs were only moderately correlated with each other and were associated with different known predictors of BC. The classification of genetic risk for the same individual varied considerably depending on the chosen GRS.

We have shown that metaGRS that combined on the effects of more than 900 SNPs, provided best predictive ability for breast cancer in two different population-based cohorts. The strength of the effect of metaGRS indicates that the GRS could potentially be used to develop more efficient strategies for breast cancer screening for genotyped women.

Open Access PDF

L”all, K., Lepamets, M., Palover, M., Esko, T., Metspalu, A., T~onisson, N., Padrik, P., M”agi, R., and Fischer, K. Polygenic prediction of breast cancer: comparison of genetic predictors and implications for risk stratification. 04771. 2019 BMC Cancer (19):1.

Concepts Keywords
Biobank Polygenic breast cancer
BMC Branches of biology
Breast Biological databases
Breast Cancer Academic disciplines
Breast Screening Genetics
Cohort Applied genetics
Estonian RTT
Genetic Biobank
Polygenic Risk factor
Single Nucleotide Polymorphisms Polygenic score
SNPs Breast cancer
Standard Deviation Mammography
Stratification

Semantics

Type Source Name
gene UNIPROT LAT2
gene UNIPROT GTF2IRD1
disease MESH familial
gene UNIPROT PDP1
gene UNIPROT BRD2
disease DOID bipolar disorder
disease MESH bipolar disorder
disease DOID heart disease
disease MESH heart disease
gene UNIPROT COL9A3
gene UNIPROT COMP
gene UNIPROT COL9A1
gene UNIPROT COL9A2
gene UNIPROT SCN8A
gene UNIPROT INTU
gene UNIPROT ERAL1
gene UNIPROT ESR1
gene UNIPROT TFPI
disease DOID Cancer
disease MESH Cancer
gene UNIPROT RITA1
gene UNIPROT ZNF331
gene UNIPROT SSRP1
gene UNIPROT TNFSF14
gene UNIPROT TNF
disease MESH dif
disease MESH community
disease MESH multi
gene UNIPROT USP9X
drug DRUGBANK Hyaluronic acid
disease MESH live birth
gene UNIPROT REST
drug DRUGBANK Flunarizine
gene UNIPROT AMACR
gene UNIPROT COX5A
gene UNIPROT COX8A
gene UNIPROT CPOX
gene UNIPROT DEPP1
gene UNIPROT GOPC
gene UNIPROT ELL
disease MESH men
gene UNIPROT RAN
drug DRUGBANK Ranitidine
gene UNIPROT BANK1
drug DRUGBANK Coenzyme M
gene UNIPROT BRCA1
gene UNIPROT RORC
gene UNIPROT FANCC
gene UNIPROT AICDA
disease MESH diagnosis
disease MESH death
gene UNIPROT BCL2A1
gene UNIPROT THOP1
disease MESH risk factors
gene UNIPROT BEST1
gene UNIPROT LARGE1
pathway BSID Breast cancer
disease DOID breast cancer
disease MESH breast cancer

Original Article

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