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MP2PRT Genomic and molecular characterization of biomarkers associated with self reported race/ethnicity in high risk endometrial cancers from NRG Oncology/GOG protocol 210, molecular staging of endometrial cancer

ABSTRACT: MP2PRT Genomic and molecular characterization of biomarkers associated with self reported race/ethnicity in high risk endometrial cancers from NRG Oncology/GOG protocol 210, molecular staging of endometrial cancer

PROVIDER: PRJNA850071 | ENA |

REPOSITORIES: ENA

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MP2PRT Genomic and molecular characterization of biomarkers associated with self reported race/ethnicity in high risk endometrial cancers from NRG Oncology/GOG protocol 210, molecular staging of endometrial cancer

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Accurate ethnicity prediction from placental DNA methylation data

Project description:The influence of genetics on DNA methylation (DNAme) variation is well documented, yet confounding from population stratification is often unaccounted for in DNAme association studies. Existing approaches have been developed to address confounding by population stratification by directly using DNAme data, but have not been validated in additional human populations or tissues, such as the placenta. Results: To aid future placental DNAme studies in assessing population stratification, we developed an ethnicity classifier, PLANET (placental elastic net DNAme ethnicity classifier), on combined Infinium Human Methylation 450k BeadChip array (HM450k) data from placental samples. We used data from five North American cohorts from private and public repositories (n = 509) and show that PLANET can not only accurately predict (accuracy = 0.9379, kappa = 0.8227) major classes of self-reported ethnicity/race (African: n = 58, Asian: n = 53, Caucasian: n = 389), but can also produce probabilities that are highly correlated with genetic ancestry inferred from genome-wide SNP (>2.5 million SNP) and ancestry informative markers (n=50) data. We found that PLANET’s ethnicity classification relies on 1860 DNAme microarray sites, and over half of these were also linked to nearby genetic polymorphisms (n=955). Lastly, we found our placental-optimized method outperforms existing approaches in assessing population stratification in our placental samples from individuals of Asian, African, and Caucasian ethnicities. Conclusion: PLANET outperforms existing methods and heavily relies on the genetic signal present in DNAme microarray data. PLANET can be used to address population stratification in future placental DNAme association studies, and will be especially useful when ethnicity information is missing and genotyping markers are unavailable.

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