Genes indicating Alzheimer’s risk identified by new testing methods

A new UCLA-led study used a combination of new testing methods to identify multiple novel risk genes for Alzheimer’s disease and a related rare brain disorder called progressive supranuclear palsy (PSP) by mass screening for genetic variants in a single experiment. . The study, which was published in the journal Science, also includes a new revised model showing how common genetic variants, while individually having very little impact on disease, can collectively increase disease risk by disrupting transcriptional programs. specific throughout the genome. .

Researchers have typically relied on genome-wide association studies (GWAS) in which they examine the genomes of a large group of people to identify genetic variants that increase the risk of disease. This is done by looking at markers along the chromosome, or loci, associated with a disease. Each locus on average has dozens, and sometimes hundreds or thousands, of genetic markers in common that are co-inherited and therefore associated with disease, making it difficult to identify which functional variants actually cause disease. Identifying causative variants and the genes they affect is a major challenge in modern genetics and biomedicine. This study provides an efficient roadmap to address this issue.

For this study, the authors made one of the first known uses of high-throughput testing to study neurodegenerative diseases. The authors conducted massively parallel reporter assays (MPRA) to simultaneously test for 5706 genetic variants at 25 loci associated with Alzheimer’s and nine loci associated with PSP, a neurological disease that is much rarer than Alzheimer’s but has similar pathology. From that test, the authors were able to identify with great confidence 320 genetic variants that were functional. To validate the results, they ran a clustered CRISPR screen on 42 of those high-confidence variants across multiple cell types.

“We combine multiple advancements that enable high-throughput biology, where instead of doing one experiment at a time, you do thousands of experiments in parallel in a sort of blended format. This allows us to address this challenge of how to move from thousands of genetic variants associated with a disease to identify which ones are functional and which genes they affect,” said Dr. Dan Geschwind, corresponding author of the study and the Gordon and Virginia MacDonald Distinguished Professor of Human Genetics, Neurology and Psychiatry at UCLA. Their data provided evidence implicating several novel risk genes for Alzheimer’s disease, including C4A, PVRL2, and APOC1, and other novel risk genes for PSP (PLEKHM1 and KANSL1). The authors were also able to validate several previously identified risk loci. The next steps would be to study 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 future research, Geschwind said, but he stressed that such approaches need to be carefully combined with more targeted experiments, as they were in this study. . “This success does not mean that we can rule out the kind of detailed and careful experimentation that studies individual genes in model systems,” he said. “This alone provides a key step between GWAS and understanding disease mechanisms.”

Yonatan Cooper, the study’s lead author, said the combination of approaches the researchers took gave them greater confidence in their findings, while also highlighting the challenge inherent in interpreting human genetic variation. “We believe that the integration of multiple methodologies will be critical for future work that annotates disease-relevant variation in both research and clinical domains,” said Cooper, who is an MD/PhD candidate in the Scientist Training Program. Physicians at the UCLA David Geffen School of Science. Medicine.

The authors were also able to show in PSP at least one mechanism in which multiple disease-associated loci act cumulatively to disrupt a core set of transcription factors, essentially turning genes on and off, known to function together in types of specific cells. . Geschwind said this indicated that common genetic variation located throughout the genome was affecting specific regulatory networks in specific cell types. That finding, he said, identifies potential new drug targets and suggests that, rather than targeting one gene, targeting a network of genes might be an effective approach. “We are entering a new stage of therapies: it is beginning to be plausible to think of targeting networks,” Geschwind said. (AND ME)

(This story has not been edited by Devdiscourse staff and is automatically generated from a syndicated feed.)

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