Scientists must expand their search in gene studies to identify rare but potent disease-causing mutations, a novel study has revealed.
In the study, researchers from two large genome research centres at The Children's Hospital of Philadelphia and at Duke University, described what they call "synthetic genome-wide associations."
"We believe our analysis will encourage genetics researchers to reinterpret findings from genome-wide association studies, which will also enable all of us to generate more meaningful diagnostic results for patients," said co-author Dr. Hakon Hakonarson, director of the Center for Applied Genomics at The Children's Hospital of Philadelphia.
To date, genome-wide association studies (GWAS) have detected many common gene variants associated with particular diseases, but those variants have shown only modest effects, accounting for a very small percentage of the genetic contribution to the disease.
"GWAS is a very powerful tool to identify disease genes, but for complex disorders, these common variants may not reflect true effect sizes. We may need to look farther away from those common variants to find variants that are individually rare but have strong causative effects," said Hakonarson.
The genetic variants being tested, also referred to as single-nucleotide polymorphisms (SNPs), are changes in a single chemical base of DNA that act as markers for a disease, without causing the disease.
In the current study, the researchers performed a computer simulation in which rare variants were distributed throughout 10,000 genotypes (models of DNA data simulating those collected from human study subjects).
Their analysis yielded "synthetic associations"- statistical connections between the rare variants and the common variants that produced signals similar to those found in actual disease studies.
They then tested their approach on two large sample sets for well-characterized disorders, sickle cell disease and genetic hearing loss, in which causative genes were already known.
They found a similar pattern of synthetic associations between rare and common gene variants.
"Under conventional interpretations, GWAS found only modest contributions for associations with the gene that we know causes hearing loss," said Hakonarson.
"Our study shows that conventional interpretation may undervalue the contribution of such gene variants in hearing loss, and we suggest that similar underrepresentation of effect sizes by common variants may occur in many other genetic disorders," he added.
The researchers claimed that the work may improve diagnostic evaluation for patients, furthering the goal of personalized medicine tailored to a patient's genetic profile.
At the same time, technological advances in automated gene sequencing will enable researchers to work faster as well as smarter.
The study has been published in the online journal Public Library of Science Biology (PLoS Biology).