Genome Sequence Map to represent genetic testing for rare disease including non-coding variants
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Talking to minority groups and using the information gained to create better targeted recruitment of these population groups into genetic studies and biobanks could help solve some of the known diversity issues with genetic tests, according to researchers.

Paul Appelbaum, a Columbia University professor and psychiatrist, and colleagues cite two initiatives, in the Sephardi Jewish community in New York and in the First Peoples of Canada community, set up to improve representation of these groups in genetic studies in their commentary article published in The American Journal of Human Genetics.

“A great deal of effort goes into broad-based projects that aim to recruit diverse segments of the population,” says first author Appelbaum, ​director of the Center for Research on Ethical, Legal & Social Implications of Psychiatric, Neurologic & Behavioral Genetics at Columbia. “What’s different about our contribution here is the recognition that broad-based recruitment will need to be complemented by more focused efforts that take group concerns into account.”

Although human genomes are 99.9% similar to each other regardless of ethnicity, significant genetic variation—mostly in the form of single nucleotide polymorphisms (SNPs)—occurs in and between different populations.

Knowing more about the type and frequency of these variants can make a big difference to how certain diseases are diagnosed and treated. It can also help healthcare providers advise their patients about disease risk and mitigation strategies.

In order for genetic tests to provide accurate results to those taking them they need to be fed with the right kind of data. Because disease-related SNPs vary in type and distribution between different ethnic populations, the ideal situation would be for the data feeding the genetic tests to be taken from a diverse population that represents that of the people being tested. However, historically the majority of large genetic studies and databases are predominantly made up of people of European origin. Even now, over 95% of participants of published genome wide association studies (GWAS), which feed into polygenic risk scores and other tests, are of European origin according to the GWAS Diversity Monitor.

The reasons for this inequity are multifactorial, but one issue with recruiting people from minority communities to take part in genetic studies has been related to a lack of, or misguided, communication between the researchers and those they are trying to recruit.

Using the Sephardi Jewish community in New York and the First Peoples of Canada as examples, Appelbaum and colleagues discuss this further in their article. “The two communities… have very different concerns about contributing to genomic research and datasets. Sephardi concerns focus on the possible negative effects of genetic findings on the marriage prospects of family members. Canadian Indigenous populations seek control over the research uses to which their genetic data would be put,” write the authors.

Two organizations have encouraged genetic screening in these communities. First, the Dor Yeshorim project, a non-profit set up in Brooklyn in the 1980’s to reduce the incidence of genetic diseases in the Jewish community. Second, the Silent Genomes Project, a project led by the University of British Columbia aiming to reduce healthcare disparities and improve diagnostic success for people with genetic diseases from Indigenous communities in Canada.

“Both of these groups have specific cultural reasons for being hesitant to provide genetic data. By working with them to find ways to address their concerns, we can overcome these hesitations,” Appelbaum suggests.

Both these projects are notable in their attempts to include the community involved and address their concerns, including governance models set up to ensure the data are used primarily to inform clinical test analyses. Both studies also had high levels of recruitment.

Appelbaum encourages researchers hoping to recruit other underrepresented groups to use similar methods to those applied in these two projects, but to understand that each community and its concerns are different. “For each of these groups, we need to recognize the reasons for their underrepresentation and work with them to find ways to address those concerns,” he says.

“It’s crucial to know the frequency of variants in the population. And given differences in variant frequency across population groups and the prevalence of population-specific variants, comparisons with reference data from a specific ancestral group may be crucial. That’s true in both clinical settings and in research.”

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