Review of WGS integration in Emirati genome program reveals high breast cancer variant prevalence and risk stratification utility

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medRxiv Published April 18, 2026 Medically reviewed April 25, 2026 Study authors: Sanchez, D. M.; Khan, F.; Rawashdeh, R.; Alshehhi, A.; Abdurlahman, W. M.; Jha, A.; Saad, A.; Al Awa… DOI ↗ By Dr. Julia Lee, PhD · Oncology, Genomics & Drug Development

Key Takeaway

Note that Emirati breast cancer variant prevalence is high, with allele frequencies up to tenfold higher than global references.

This publication is an observational review examining the integration of whole-genome sequencing with electronic health records within the Emirati Genome Program. The study scope encompasses 436,780 individuals, including 229,309 women, to evaluate the prevalence and penetrance of pathogenic and likely pathogenic variants alongside the performance of polygenic risk scores. The setting is the United Arab Emirates, utilizing global reference datasets as a comparator to highlight population-specific genetic differences.

The analysis reports that the prevalence of pathogenic and likely pathogenic variants in women is 0.84%, contributing to 5.2% of breast cancer cases. The mean age of women with these variants was 45.9 +/- 11.1 years. Age-specific cumulative risk for BRCA1 c.4065_4068del reached 37.6% by age 60, while the corresponding risk for BRCA2 c.2808_2811del was 31%.

Allele frequency comparisons showed values up to tenfold higher in the Emirati population than in global reference datasets. Furthermore, the European-derived polygenic risk score model advanced the prediction of 10-year breast cancer risk onset for women in the top decile by a decade. Even within sister pairs, higher polygenic risk was observed, suggesting significant familial aggregation.

The authors acknowledge that the genetic architecture of breast cancer in Arab populations remains largely understudied. Consequently, the integration of monogenic, polygenic, and familial data defines a national framework for risk stratification, identifying disease-free women potentially eligible for targeted prevention. Clinicians should interpret these findings as descriptive of this specific cohort rather than causal evidence for broader populations.

Study Details

EvidenceLevel 5

PublishedApr 2026

View Original Abstract ↓

The genetic architecture of Breast Cancer (BC) in Arab populations remains largely understudied, limiting the precision of current prevention and screening programs. The Emirati Genome Program (EGP), one of the world's first nation-wide sequencing initiatives, offers an unprecedented opportunity to delineate inherited BC risk across an entire population. We analyzed 436,780 EGP individuals, including 229,309 women, integrating whole-genome sequencing (WGS) with electronic health records (EHRs). We quantified the prevalence and penetrance of pathogenic and likely pathogenic (P/LP) variants across 13 NCCN-recommended BC genes, evaluated the performance of established polygenic risk scores (PRS), and reconstructed >48,000 pedigrees to measure familial aggregation. P/LP variants were identified in 0.84% of women, accounting for 5.2% of BC cases (mean age of 45.9+/- 11.1 years). Highly penetrant BRCA1 c.4065_4068del (p.Asn1355fs) and BRCA2 c.2808_2811del (p.Ala938Profs) variants showed age-specific cumulative risks of 37.6% and 31% by age 60, respectively, and allele frequencies up to tenfold higher in the Emirati population than in global reference datasets. The European-derived PRS model (PGS000004) demonstrated strong performance, advancing 10-year BC risk onset by a decade for women in the top decile. Family-based PRS discriminated affected from unaffected individuals, revealing higher polygenic risk even within sister pairs. Integration of monogenic, polygenic, and familial data defined a national framework for risk stratification, identifying disease-free women potentially eligible for targeted prevention. Nation-scale genome sequencing reveals, for the first time, the comprehensive landscape of inherited BC susceptibility within a Middle Eastern population. The integration of monogenic, polygenic, and familial data establishes a national framework for genomic risk stratification- transforming population genomics into a foundation for precision prevention and early detection in the UAE and beyond.