Over the years, studies have documented numerous potential gene variations involved with lupus. A number of those early gene discoveries were made by researchers at Cincinnati Children’s from a lab led by John Harley, MD, PhD.
In 2018, a team led by Weirauch, Kottyan, and Harley reported that lupus was one of seven common chronic diseases that appear strongly linked to prior infections with the Epstein-Barr virus (EBV)—best known for causing mononucleosis. The team found that transcriptional regulators from the virus can greatly influence human gene expression levels, especially within the immune system. The increased disease risk that results for infected people varies according to which part of the genetic code was affected by the invader.
In several ways, the new study in Nature Communications expands upon that 2018 work.
For women battling lupus, this study boiled down more than 3,000 potentially important genetic variants to just 51, many of which appear related to B cell function, a core component of our immune systems.
The new genetic information provides immediate new ideas that could lead to more effective ways to prevent lupus-related complications, Kottyan says.
WHY IS A NEW GENETIC SCREENING APPROACH IMPORTANT?
Longer-term, the successful development of massively parallel gene screening has potential application for finding the genetic connections to virtually any disease. Here’s how:
For nearly two decades, scientists have been using genome-wide association studies (GWAS) to uncover large sets of clues about gene variations that might be causing a disease. The process compares entire genomes (3 billion base pairs) between people with a disease and others without that disease. The results include long lists of single-nucleotide polymorphisms (SNPs) that differ between the healthy and unhealthy people—only some of which are relevant to the disease being studied.
GWAS basically converts the proverbial hunt for a needle in a haystack into hunting for the right needle in a large box of interesting needles collected from many haystacks. Hunting through such boxes has produced major discoveries for a growing list of diseases, from Huntington’s disease to the BRCA-1 gene that increases breast cancer risk.
But some of the boxes of needles are huge. In conditions such as heart disease, diabetes or asthma, dozens or even hundreds of gene variations may be involved, all interacting with each other in exceeding complex patterns. In these situations, screening every needle in the box would take years.
Since GWAS emerged, researchers have devoted years to developing shortcuts that can help sort through the noise. For example, scientists often use databases that use the latest assumptions about likely areas of genetic activity to point investigators towards the most promising corner of the box of needles.
The major limitation: many studies continue to find relevant SNPs in unexpected places. The potential impact of MPRAs: Scientists now have an extremely fast tool for evaluating all the needles in the box.
“The sheer scale of the data that can be analyzed is astonishing,” Kottyan says. “For example, in 2019, I published a paper based on one reporter assay experiment. This paper includes the results of over 150,000 reporter assay experiments.”
Before using this method, it often took at least two years for scientists to understand the molecular mechanisms at work in a single genetic locus (or region of the genome) that may contain disease-causing SNPs. This study also took more than two years—but the team was able to analyze all 91 genetic loci known to increase lupus risk.
Crucially, the same screening process can be used to sift suspected genetic associations for nearly any complex disease.
“This is a huge acceleration of discovery,” Kottyan says.