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PMID: 42306961 已发表 · aheadofprint 英语

Reclassification of BRCA1 variants of uncertain significance using ancestry-stratified allele frequencies: A Middle East-focused analysis.

Abujamous L, Razali R, Al-Thawadi H

摘要

Interpreting BRCA1 variants of uncertain significance (VUS) in underrepresented populations presents significant challenges due to the scarcity of ancestry-matched reference data, which can lead to an overestimation of variant rarity. This study evaluates the effectiveness of employing ancestry-stratified allele frequencies, including a subset from the Middle East, within a calibrated ACMG/AMP framework to enhance the interpretation of BRCA1 VUS. We analyzed 626 BRCA1 variants from ClinVar, comprising 608 missense, 15 splice-altering, and 3 nonsense variants categorized as VUS or "not provided." Variants were annotated using gnomAD v4 (both global and ancestry-stratified subsets) and dbNSFP, and subsequently evaluated according to workflows aligned with ACMG/AMP and ClinGen ENIGMA BRCA1/2 guidelines, with cross-validation performed using the Bayesian point system. Our findings revealed that ten variants (1.6%) were reclassified. Nine missense variants were downgraded to benign or likely benign status based on BS1 and BP1 criteria; notably, none of these downgrades would have occurred if evaluated solely on global gnomAD allele frequencies. Among these, five downgrades relied on the Middle East subset, while four depended on other ancestry-stratified subgroups. Additionally, one splice-altering variant (rs1555582723) was upgraded to likely pathogenic status based on PVS1_Very Strong and PM2_Supporting criteria. In conclusion, utilizing ancestry-aware population data modestly improved the resolution of BRCA1 VUS, primarily through benign downgrades. This underscores the necessity for larger regional datasets and further functional or case-based evidence to enhance variant interpretation.

文献信息
期刊
Biomolecules & biomedicine
期刊简称
Biomol Biomed
ISSN
2831-090X
发表日期
2026-06-16
语言
英语
国家/地区
Bosnia and Herzegovina
NLM ID
9918522188506676
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