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ACMG Releases Statement on Biases Affecting Equitable Access to Clinical Genomics Testing

NEW YORK – The American College of Medical Genetics and Genomics (ACMG) on Friday released a statement on points to consider in avoiding biases that reduce equitable access to genetic and genomic testing.

An ACMG working group formed by members of the organization's Social, Ethical, and Legal Issues and the Diversity, Equity, and Inclusion committees called biases that cause health inequities and gaps in medical care “unnecessary, avoidable, unfair, and unjust.”

The working group identified three main categories of bias: environmental, clinical, and technical.

The working group's environmental factors largely centered on the relationship of the medical community to people across socioeconomic and social spectrums. This category addressed the longstanding mistrust that many underrepresented minorities feel toward the medical establishment, stemming from an abusive history involving instances such as the use of genetic samples without consent, and discrimination based on an individual's biology, as has occurred within the LGBTQIA+ community.

This category also addressed insurance discrimination, including the lack of standardization with respect to genetic test coverage, which disproportionately affects underrepresented minorities.

The ACMG working group suggests that moving forward, members of the genetics community recognize historical and ongoing practices that foster mistrust; respect the autonomy, dignity, and traditional beliefs of marginalized peoples; include members of those populations in genetics research; and consider genetic testing as an "integral and indispensable clinical test," which should be fully covered and adequately reimbursed, in line with professional guidelines.

Clinical factors to consider in reducing bias include clinician diversity, access to genetic services, patient and clinician education, and complexities associated with family and/or genetic history.

As points to consider in avoiding clinical biases, the ACMG working group suggests bolstering education around implicit biases, diversifying the genetics workforce, taking into account different communication styles and cultural dynamics, avoiding the use of racial and ethnic categories as proxies for genetic ancestry, and making available educational resources in different languages.

Technical biases mentioned in the statement focus mainly on the interpretation of variants from genetically diverse populations. Genome-wide association study (GWAS) data, for example, is used to estimate polygenic risk scores, which are used to screen for the risk of various disorders. As GWAS data still relies heavily on populations of European ancestry, such tools can be of limited use in other genetic populations.

Points that the working groups recommend be considered to avoid technical bias are that current population databases lack diversity and may not be of the same clinical utility across ancestries, that more people from diverse and underrepresented ancestries be recruited into such databases, that clinical laboratories can help by sharing and analyzing more pan-genome references, and that large ethnic-neutral panels be considered for individuals whose ancestral data is limited.

"This document," the group wrote, "is meant to provide a framework to support a positive and constructive dialogue among all stakeholders and lawmakers to continually address advances in genetic testing and their clinical application, with the goal of recognizing and reducing bias to ensure equitable care and avoid unfair discrimination."