EDITOR’S NOTE, Nov. 17, 2021 – This publication was selected by the International Genetic Epidemiology Society (IGES) as a Featured Publication.
Guillaume Paré
Rare variants, which are numerous, may underline a considerable amount of complex disease risk. However, identifying them has technical and population-level biases and other challenges for researchers using an external datset as control data.
PHRI Senior Scientist Guillaume Paré, and his team in the CRLB-GMEL laboratory, have shown that rare variant burden over a large number of genes can be combined into a predictive rare variant genetic risk score (RVGRS).
Their new method, Rare Variant – EXome CALIBration using External Repositories (RV-EXCALIBER), aggregates and robustly calibrates the effect of rare variant burden across many risk genes.
These findings were published today in Nature Communications as “Calibrated rare variant genetic risk scores for complex disease prediction using large exome sequence repositories.”
Unlike existing methodologies that assess the contribution of rare variants to complex disease using external control databases, “our workflow systematically calibrates rare variant burden between individual test samples and reference databases,” the authors write.
The publication discusses how a calibrated RVGRS strongly associates with coronary artery disease (CAD) in European and South Asian populations by capturing the aggregate effect of rare variants through a polygenic model of inheritance.
Ricky Lali
“We leverage this method to construct the very first rare variant genetic risk score (RVGRS), which aggregates the effect of rare variant burden across many risk genes,” says the publication’s first author, Ricky Lali, a PhD student in McMaster’s department of health research methods, evidence and impact.
The RVGRS was shown to be predictive for early-onset coronary artery disease in a manner that was completely independent of traditional common variant genetic risk scores, Mendelian mutations, and environmental risk factors.
“Our findings further validate the increased role of inheritance in modulating early disease risk,” the authors write, “and make a strong case for large sequencing studies of common, complex traits and diseases.
The authors add that their RV-EXCALIBER method could be extended to whole-genome sequencing. Lali admits the name fit the method, but also was a nod to the epic story of Excalibur. “You could say we are pulling the genetic sword from the stone.”
Read the whole article (open access) at Nature Communications.
