Current Technology Enables Scientists to Effectively Detect Common Diseases Inherited from Family Through Genes. But Not the Rare Ones, Research Finds.
By Sida Lai in Week 3
When children are born, they inherit genes from their parents that determine their physical features and characteristics. Sometimes, diseases may also get passed on, caused by hereditary genetic variation and diseases-causing mutation.
Detecting such predisposition to health conditions is crucial for early treatment. Many biotechnology companies, like 23andme and AncestryDNA, in recent years have introduced home DNA test kits. Consumers could understand their ancestry through genes simply by mailing their mouth swabs or saliva. But Can the available technology successfully detect all pathogenic (disease-causing) genetic disorders?
Recent research led by Micheal Weedon from the College of Medicine and Health at the University of Exeter, however, shows both optimistic and discouraging results. While common pathogenic variation could be rather easily and accurately identified, the existing method, using SNP chips, is highly unreliable in identifying relatively rare inherited pathogenic disorders uncommon in the population.
But how does it all work and why?
Simply put, genes are the basic physical and functional unit of heredity, mostly made up of DNA. Single-nucleotide polymorphism (SNP) refers to the variations in these genes. “There are over hundreds of millions of SNPs, and some are pathogenic markers associated with diseases like diabetes or cancers across generations of a family,” said Andreas Pfenning, a Computational Biology Professor at Carnegie Melon University (CMU). Accurately and efficiently identifying them hence become the goal of research and technological developments.
SNP chip, or SNP array, is a type of DNA microarray that is now often used to detect pathogenic SNPs common in the population, often larger than one in every 100 people. The technology is proven effective in studying common genetic variations. This allows scientists to assess ancestry, and discover existing predisposition to complex multifactorial but common diseases such as type two diabetes. Patients hence can receive early clinical follow-up to prevent and treat family diseases.
Many direct-to-consumer companies have also introduced SNP chip designs in recent decades that are argued to be able to detect rare pathogenic variants as well. These variants cause uncommon single-gene disorder diseases. And some of these conditions include breast and ovarian cancer. However, their effectiveness for the rare diseases has not been validated.
Weedon’s research team conducted a population-based diagnostic evaluation of these chips’ performance among about 50,000 people. Their result, however, demonstrates that SNP chips are extremely unreliable for genotyping (genetically detecting) very rare pathogenic variants due to their sensitivity and specificity. In other words, current designs are insufficient in identifying uncommon disease-causing genetic disorders.
Researchers hence argue that patients and clinicians should not rely solely on these chips to guide health decisions without validation. “Negative SNP chip results simply cannot guarantee low risks,” said Frewony Amaha, a computational biology student and researcher at CMU. “Similarly, high risks sometimes do not mean that one will get the disease 100 percent either.”
Detecting Family Diseases Through Our Genes has partially become a reality. However, its effectiveness may only limit to common genetic pathogenic variants. A future for accurately detecting hereditary diseases caused by rare genetic mutations requires further research and validation.
