Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

biochemistry, genetics and molecular biology

Genetic variants demonstrating flip-flop phenomenon and breast cancer risk prediction among women of African ancestry

Breast Cancer Research and Treatment, Volume 168, No. 3, Year 2018

Background Few studies have evaluated the performance of existing breast cancer risk prediction models among women of African ancestry. In replication studies of genetic variants, a change in direction of the risk association is a common phenomenon. Termed flip-flop, it means that a variant is risk factor in one population but protective in another, affecting the performance of risk prediction models. Methods We used data from the genome-wide association study (GWAS) of breast cancer in the African diaspora (The Root consortium), which included 3686 participants of African ancestry from Nigeria, USA, and Barbados. Polygenic risk scores (PRSs) were constructed from the published odds ratios (ORs) of four sets of susceptibility loci for breast cancer. Discrimination capacity was measured using the area under the receiver operating characteristic curve (AUC). Results Flip-flop phenomenon was observed among 30~40% of variants across studies. Using the 34 variants with consistent directionality among previous studies, we constructed a PRS with AUC of 0.531 (95% confidence interval [CI]: 0.512–0.550), which is similar to the PRS using 93 variants and ORs from European ancestry populations (AUC = 0.525, 95% CI: 0.506–0.544). Additionally, we found the 34-variant PRS has good discriminative accuracy in women with family history of breast cancer (AUC = 0.586, 95% CI: 0.532–0.640). Conclusions We found that PRS based on variants identified from prior GWASs conducted in women of European and Asian ancestries did not provide a comparable degree of risk stratification for women of African ancestry. Further large-scale fine-mapping studies in African ancestry populations are desirable to discover population-specific genetic risk variants.
Statistics
Citations: 41
Authors: 13
Affiliations: 8
Identifiers
Research Areas
Cancer
Genetics And Genomics
Study Design
Cross Sectional Study
Study Locations
Nigeria
Participants Gender
Female