Researchers from Baylor College of Medicine and Texas Children’s Neurological Research Institute (NRI) have created a potent new tool in the Genome Aggregation Database (gnomAD) to improve the precision of genetic testing. This discovery has immediate ramifications for patient diagnosis and treatment across the globe.
To provide more precise insights into genetic differences, the work, which was published in Nature Communications, uses a technique known as local ancestry inference (LAI), which divides the genome into ancestry-specific parts.
“This research updates our genomic resources to better reflect the full spectrum of genetic variation,” stated Dr. Elizabeth Atkinson, assistant professor in the Department of Molecular and Human Genetics at Baylor College of Medicine and principal investigator at the NRI at Texas Children’s. “By refining allele frequency estimates for admixed populations, we can improve the accuracy of genetic diagnoses and reduce the risk of misclassification—ultimately benefitting patients across all backgrounds.”
The study “Improved Allele Frequencies in gnomAD through Local Ancestry Inference” represents a significant advancement in genetic testing and personalized medicine. Pragati Kore and Michael Wilson are co-first authors of the paper, with Dr. Atkinson serving as its senior author.
One effective method of disease diagnosis is genetic testing. Genetic variations are more likely to be benign if they are prevalent in the general population. However, the majority of population frequency estimates derive from averages over sizable groups. This aggregate technique can obscure significant variations between the ancestral components of individuals whose genetic background indicates ancestry from various continents, such as those who are classed as African/African American or Latino/Admixed American in gnomAD.
To solve this issue, Dr. Atkinson’s group used local ancestry inference, or LAI. LAI divides the genome into sections that trace back to various continental ancestries (African, European, or Indigenous American, for example) rather than examining the genome as a whole. Next, the group determined the prevalence of each variation within each ancestral segment. This procedure showed that a large number of variations that are considered uncommon in global data are actually prevalent in specific ancestry groups.
“These differences are not just academic,” stated Dr. Atkinson. “They have clinical consequences.”
Researchers discovered that over 80% of genomic loci in the African/African American and Latino/Admixed American populations were more frequently detected in at least one ancestry-specific tract than had been previously documented. This raises the variant’s level above a critical clinical threshold that the American College of Medical Genetics and Genomics (ACMG) uses to determine whether a variant is benign in specific circumstances. Variants that could otherwise be misunderstood may be reclassified more accurately as a result.
Through gnomAD, the new ancestry-specific data is now publicly accessible, giving genetic testing labs, researchers, and physicians worldwide a more accurate tool for analyzing c.
“Ancestry is complex, and putting a single label on patients is not the most accurate way to diagnose them,” stated Dr. Atkinson. “With this research, we are moving toward a more nuanced consideration of ancestry.”
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