Why we can’t accurately predict genetic diseases in people of African ancestry
Researchers say that current methods used to predict whether or not a person will develop a genetic disease doesn’t work well for people of African origin. This is because the database behind such predictions mostly describes genes of people of European origin.
The GWAS database stands for “Genome-Wide Association Studies”, and scientists use it to look for traits and diseases based on genes. In fact, they can use the GWAS to calculate a person’s genetic risk for a disease or trait. Most of the gene data in GWAS, however, comes from people of European ancestry.
In this study, researchers wanted to see how well the calculation they use to determine genetic disease risk using GWAS works for people of African ancestry. They also wanted to see if a more diverse GWAS, in other words a database that includes more African genetic information, would improve the predictions.
The calculation is known in more scientific terms as the “polygenic risk score”, or PRS.
They used computers to calculate the predicted genetic risks of the African population using the GWAS, and they used medical records of African people to look at certain traits or diseases that might have been caused by changes in genes.
When they used the European GWAS, they found that the genetic risk score was more accurate if people had European ancestry compared to African ancestry for most traits.
They said that the risk scores are quite low between African regions because there is so much diversity amongst the population, which is not in line with what we see for European ancestry. They also said PRS accuracy increases as the African origin decreases.
Ethiopian populations had better predictions for genetic diseases since they are genetically more similar to European populations.
When using a more diverse GWAS that includes people with African origins, the prediction accuracy improved. Predicting blood diseases was particularly more accurate.
Previous studies have shown that PRS is low for African populations, meaning that the GWAS database predicts low risk of genetic diseases for people of African origin. But we know that this is not necessarily true.
This study explains that these low genetic disease risk scores is because African genes are not well represented in the GWAS database, and so current PRS values do not not really help to predict genetic diseases in Africa. Researchers say it would be better to use a more diverse database that includes genetic information from people of African descent.
Further work is therefore needed to diversify GWAS to include African ancestry so that we can more accurately predict the risk of genetic diseases in African populations.
The authors of this study were from Africa, USA and UK.
African populations are vastly underrepresented in genetic studies but have the most genetic variation and face wide-ranging environmental exposures globally. Because systematic evaluations of genetic prediction had not yet been conducted in ancestries that span African diversity, we calculated polygenic risk scores (PRS) in simulations across Africa and in empirical data from South Africa, Uganda, and the UK to better understand the generalizability of genetic studies. PRS accuracy improves with ancestry-matched discovery cohorts more than from ancestry-mismatched studies. Within ancestrally and ethnically diverse South Africans, we find that PRS accuracy is low for all traits but varies across groups. Differences in African ancestries contribute more to variability in PRS accuracy than other large cohort differences considered between individuals in the UK versus Uganda. We computed PRS in African ancestry populations using existing European-only versus ancestrally diverse genetic studies; the increased diversity produced the largest accuracy gains for hemoglobin concentration and white blood cell count, reflecting large-effect ancestry-enriched variants in genes known to influence sickle cell anemia and the allergic response, respectively. Differences in PRS accuracy across African ancestries originating from diverse regions are as large as across out-of-Africa continental ancestries, requiring commensurate nuance.
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