The genetics underlying neurodegenerative disorders are typically complex polygenic traits. Researchers have relied on genome-wide association studies (GWAS) to identify genetic variants that increase the risk for these diseases. However, the functional roles of these genes remain largely unknown.
Now, researchers have identified multiple new risk genes for Alzheimer’s disease and a rare, related brain disorder called progressive supranuclear palsy (PSP) by using a combination of new testing methods allowing for mass screening of genetic variants in a single experiment. More specifically, they used “massively parallel reporter assays to screen noncoding variants reported in genome-wide association studies of two neurodegenerative disorders, followed by functional validation in neurons and microglia.” In doing so, they identified regulatory variants in several different genes that play functional roles in disease pathogenesis as well as interactions between these genes, providing a roadmap for future research in this field.
The study, titled “Functional regulatory variants implicate distinct transcriptional networks in dementia,” is published in Science.
For this study, the researchers conducted one of the first known uses of high-throughput testing to study neurodegenerative disease. They ran massively parallel reporter assays (MPRAs) to simultaneously test 5,706 genetic variants in 25 loci associated with Alzheimer’s and nine loci associated with PSP, a neurological disease that is much rarer than Alzheimer’s but has a similar pathology.
With high confidence, they were able to identify 320 genetic functional variants. To validate the results, they ran a pooled CRISPR screen on 42 of those high-confidence variants in multiple cell types.
“We combined multiple advances that allow one to conduct high-throughput biology, in which instead of doing one experiment at a time, one does thousands of experiments in parallel in a kind of pooled format. This allows us to approach this challenge of how to move from thousands of genetic variants associated with a disease to identifying which are functional and which genes they impact,” said Dan Geschwind, MD, PhD, professor of human genetics, neurology, and psychiatry at UCLA.
Their data provided evidence implicating several new risk genes for Alzheimer’s, including C4A, PVRL2, and APOC1, and other new risk genes for PSP (PLEKHM1 and KANSL1). The authors were also able to validate several previously identified risk loci. The next steps would be studying how newly identified risk genes interact in cells and model systems, Geschwind said.
The study provides proof of principle that high-throughput testing can provide a “very efficient” roadmap for further research, Geschwind said, but he stressed that those approaches must be thoughtfully paired with more targeted experiments, as they were in this study.
“This success does not mean that we can jettison the kind of detailed, careful experimentation studying individual genes in model systems,” he said. “This just provides a key step between the GWAS and understanding disease mechanisms.”
Yonatan Cooper, an MD/PhD student at UCLA’s David Geffen School of Medicine, who completed his graduate work in the Geschwind lab, said the combination of approaches the researchers took gave them greater confidence in their findings, while it also highlighted the challenge inherent to interpreting human genetic variation.
“We believe that integration of multiple methodologies will be critical for future work annotating disease-relevant variation in both the research and clinical domains,” said Cooper.
The authors were also able to show in PSP at least one mechanism in which multiple loci associated with the disease acted additively to disrupt a core set of transcription factors, which essentially turn genes on and off, that are known to work together in specific cell types. Geschwind said this indicated that common genetic variation located across the genome was affecting specific regulatory networks in specific cell types. That finding, he said, identifies new potential drug targets and suggests that rather than targeting one gene, targeting a network of genes could be an effective approach.
“We’re entering a new stage of therapies—it’s beginning to be plausible to think about targeting networks,” Geschwind said.