The Genomic Representation Gap in Pediatric Precision Oncology: Quantifying RB1 Variant Disparities Between a Brazilian Cohort and Global Databases
Fernando Augusto Siuta dos Santos, Pedro Dytz Marin, Giulia Scain, Isabela Alicia Fink, Julia Loureiro Chaves Cé, Stéphanie Klein Brum, Mariana Weremeier Weber, Martina de Sá, Rafaela Sumienski Girardi, Solana de MeloPURPOSE
Eurocentric genomic databases like ClinVar often generate imprecise clinical classifications for admixed populations. This study integrates the Brazilian national genomic database (ABraOM) with global repositories to quantify the clinical underrepresentation of RB1 tumor suppressor variants, highlighting the critical impact of this data gap on retinoblastoma screening in low- and middle-income countries (LMICs).
METHODS
An integrative in-silico analysis was performed. Germline variant data for the RB1 gene were extracted from the Brazilian ABraOM cohort. These variants were systematically cross-referenced with NCBI ClinVar to determine global clinical significance. Ancestry bias was statistically validated by comparing allele frequencies (AF) in the Admixed American (AMR) population against global and European cohorts using gnomAD v4.1.1.
RESULTS
The analysis identified a wide allele frequency spectrum in the Brazilian cohort, ranging from nearly fixed intronic polymorphisms (AF = 0.997, eg, rs2854351 and rs74698729) to rare, high-risk splicing variants (AF = 0.000427, eg, rs1012377281 and rs759188465). Cross-referencing with ClinVar revealed that definitive pathogenic classifications (eg, c.862-1G>A and p.Trp195Ter) frequently rely on limited evidence from single submitters. Quantitative integration with gnomAD (v4.1.1) exposed severe representation disparities: while predictive variants such as c.321A>C show an AF of 0.000072 globally and 0.000079 in Non-Finnish Europeans, they are entirely absent (Allele Count = 0) in the AMR cohort. This quantitative asymmetry demonstrates that oncological guidelines based on European genomic profiles fail to track rare Latin American variants, resulting in critical underreporting and a surplus of inconclusive reports (Variants of Uncertain Significance [VUS]) within the Brazilian health system.
CONCLUSION
Quantitative divergence between ABraOM, ClinVar, and gnomAD proves that global oncology neglects the mutational profile of admixed populations. Reliance on Eurocentric databases severely compromises the genetic diagnosis of retinoblastoma in Brazil, necessitating the urgent integration of local variants into clinical guidelines for LMICs to ensure equitable precision medicine.