Cardiovascular disease is the leading cause of death in the United States, killing one person every 33 seconds. In 2019, heart disease cost the United States approximately $240 billion. The good news is that this disease is linked to genetics, so with the right tools and information, it is predictable and preventable. Researchers are using next-generation sequencing and data analysis software to improve our understanding of this seemingly ubiquitous disease state.

Bioinformaticians on Illumina’s DRAGEN secondary analysis team have devised an innovative method to measure long repetitive DNA sequences within genes. LPAis known to affect cardiovascular health.

Dr. Samuel Strom, Illumina Research and Development Principal Scientist, presented these findings at this year’s American College of Medical Genetics and Genomics (ACMG) Clinical Genetics Conference in Toronto.

gene LPA encodes lipoprotein a. Elevated levels of lipoprotein a are correlated with an increased risk of developing a heart attack or stroke, and these levels are determined by repetitive DNA sequences embedded in lipoprotein a levels. LPA It is called variable number tandem repeat (VNTR). VNTR lengths vary. LPAis about 5500 base pairs long, and humans can have between 1 and 60 copies of it.

“These alleles can be over 300 kilobases, which is much longer than the read lengths of Illumina and other technologies,” Strom says. “If you use historical variant callers, the reads from that region aren’t unique, so they don’t even get mapped. For years, that data has been thrown away.”

But the bioinformatics team working on DRAGEN has found a way to analyze these reads, which would normally be discarded. The method they developed can accurately detect and quantify her VNTR in the body. LPA.

The VNTR detection method created by the DRAGEN team also reduces the need to study VNTR. LPA According to Strom, genes are based solely on polymorphisms. This is important because some mutations may be prevalent only in patients of certain ethnic backgrounds and not in patients of other ethnic backgrounds. After applying their method to a study cohort of more than 2,300 people of African, European, and Hispanic descent, Strom et al. found that the DRAGEN analysis was “more effective at examining this region than at single nucleotides. I found it to be a fair method. It’s a variation,” he says.

Since this method is part of a secondary analysis step, it can be applied to genomic data already available in shared databases. Strom said this new analysis could be carried out in population studies, such as the UK Biobank, to quantify risk levels in a population and allow further research, especially as researchers begin to recognize the role of VNTRs in health and disease. I envision it becoming something like this.

Decoding and understanding VNTR LPA This provides proof of principle that DRAGEN can handle long repetitive sequences without discarding them.

“This is just the tip of the iceberg for whole-genome VNTR research,” Strom says. “No lab has done this before because it’s technically very difficult. Illumina technology does a great job, even with very complex things, if you know how to look for them.” He will do it for you.”

He believes there may be many other clinically relevant repeat sequences similar to these. LPA;Ability to evaluate VNTR in general, not just VNTR; LPA, which holds a lot of excitement and potential for the scientific community. “This is a dark part of the genome,” Strom says. “One of his next steps with the DRAGEN team is working on generalizing this method to be able to detect other he VNTRs.”

He hopes this and future methods developed by Illumina will shed new light on rare disease and oncology research.

If you would like to learn more about how this VNTR detection method works and the methods used to test it, please see below. This article is by Jonathan Belyeu, Vitor Onuchic, Mitchell Bekritsky At Illumina’s Genomics Research Hub.