P-566 Addressing ethnic underrepresentation in carrier screening: prioritizing comprehensive variant curation over ClinVar-based automated analysis
Authors: Trujillo I , Feliu A , Palahi M , Martín A , Moret R , Cotán D , Sandalinas M 
Published: July 2024

Abstract

Study question
How does the use of a ClinVar-based approach in Carrier Genetic Screening (CGS) affect the efficiency and accuracy of carrier detection analysis?

Summary answer
For CGS, comprehensive variant curation, not automated analysis alone, addresses risk from under-representation of diverse populations in genetic databases.

What is known already
Next-generation sequencing (NGS) analyses in Carrier Screening (CS) yield numerous variants per patient requiring interpretation for pathogenicity assessment. Public variant databases aid in the curation process, clinical interpretation, and genomic data sharing, reducing error risks and diagnostic delays. Consequently, an increasing number of genetic laboratories are integrating these databases into their workflows. However, over-representation of certain ethnic groups persists due to genetic inequality, as these databases primarily contain variants previously reported in patients and manually recorded. This lack of ethnic diversity in human genomic studies and databases can lead to inaccurate risk assessment and inadequate interventions in under-studied populations.

Study design, size, duration
Retrospective analysis involved 3886 patients of various ethnicities examined between June 2021 and March 2023. They were grouped according to self-reported ethnicity: African(54), Asian(43), Mediterranean(689), European/Caucasian(2402), Latino(449) and not reported(249).

Participants/materials, setting, methods
Patients were categorized based on their self-reported ethnicity after undergoing analysis with a Carrier Screening (CS) panel of 300 genes, which included autosomal recessive and X-linked disorders, using Next-Generation Sequencing (NGS). Complete variant curation (CCV) was conducted using the American College of Medical Genetics and Genomics(ACMG) and ClinGen guidelines for variant interpretation. The average number of variants per patient was calculated for both the automated process using only the ClinVar database and the CCV performed.

Main results and the role of chance
Upon evaluating the number of variants identified per patient,, 1.51 variants/patient (v/p) were observed when CCV, while 1.27 v/p would have been detected using only ClinVar (automated process). In summary, ClinVar accounted for 88% of all variants identified with CCV.
Significant differences in variant detection were observed across ethnicities. The percentage of variants not detected by the automatic process were as follows: 21.95% in Asian ethnicity, 17.84% in African, 13.99% in Latino, 11.88% in Mediterranean, 10.97% in European/Caucasian and 10.70% in patients who did not report ethnicity. Among these, Asian and African ethnic groups had the lowest percentage of variants detected by ClinVar 78.05% and 82.16%, respectively. In the Asian group, 0.95 v/p were identified, while in the African group, 1.70 v/p were identified.

Limitations, reasons for caution
Data was collected based on self-reported ethnicity, which may not always accurately reflect true ancestry. Additionally, the sample size for certain ethnicities was relatively small. Variant classification relied on information available in databases or literature at the time of the study, potentially subject to updates or revisions in the future.

Wider implications of the findings
This study underscores the limitations of automated analysis in detecting all variants identified by CCV across ethnicities, highlighting genetic disparities present in mutation databases like ClinVar. The findings emphasize the importance of implementing CCV in Carrier Screening tests to effectively mitigate reproductive risks across diverse ethnic groups.

Trial registration number
not applicable