Inference of genetic ancestry from a multi-gene cancer panel in Colombian women with cancer
Yina T Zambrano-O1,2, Alejandro Mejía-Garcia3, P Daniela Morales4,5
1Grupo de Investigación en Biología del Cáncer, Instituto Nacional de Cancerología, Cl. 1 #9-85, Bogotá, Colombia. ytzambrano@cancer.edu.co.
Introduction:
Cancer health disparities among racial and ethnic populations significantly burden health systems due to unequal access to early detection, treatment, and healthcare resources. These disparities lead to worse outcomes and increased costs from delayed diagnoses, advanced treatments, and prolonged care. Genetic differences can also influence cancer susceptibility and treatment response, thus analyzing genetic ancestry is essential for uncovering genetic factors that may contribute to these disparities. Utilizing data from clinical multigene cancer panels to infer genetic ancestry offers a valuable approach to understand population structure and the impact of individual ancestries in development of complex diseases.
Aim:
To evaluate the accuracy of global ancestry inference using genetic markers from the TruSight™ Hereditary Cancer Panel, which was used to investigate hereditary cancer syndromes in a cohort of 116 female cancer patients at the Colombian National Cancer Institute. Additionally, to compare these results with genetic ancestry estimations from traditional genome-wide markers.
Results:
Our results demonstrate a strong correlation between global genetic ancestry inferred with markers captured from TruSightTM panel (4785 markers) and Whole Genome Sequencing (WGS, 8 million markers in admixed populations. The correlation values were 0.96 (p < 0.0001) for the Native American and European ancestry components, and 0.99 (p < 0.0001) for the African ancestry fraction. Genetic ancestry mean proportions in the Colombian cohort were 45.7%, 46.2%, and 8.11% for the European, the Native American, and the African components, respectively.
Conclusion:
This study demonstrates the accuracy of ancestry inference from clinical panel data offering a promising approach for understanding cancer health disparities in admixed populations.
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