LEXINGTON, Ky. (July 13, 2021) -- A recently published study co-authored by University of Kentucky Sanders-Brown Center on Aging researcher Justin Miller, Ph.D., identifies 11 rare candidate variants for Alzheimer's disease. Researchers found 19 different families in Utah that suffered from Alzheimer's disease more frequently than what is considered normal.
Miller, an assistant professor in the UK College of Medicine, was a co-first author for the study published in the journal Alzheimer's & Dementia. The work was started at another university, however, some of the computational work was done after Miller arrived at UK in March.
For the study, genetic sequencing was conducted on two cousins from each of the 19 families. Miller says they then identified genetic variants that were shared between both cousins.
"We then used a series of filtering criteria to identify rare genetic variants that were most likely contributing to the excess Alzheimer's disease in each family," he said.
Researchers found 11 rare genetic variants spanning 10 genes, including previously unknown variants in two known Alzheimer's disease risk genes.
"Identifying people with increased risk for Alzheimer's disease before they become symptomatic may lead to earlier and more effective interventions," Miller said. "Additionally, our methodology for analyzing high-risk pedigrees can be used to prioritize rare genetic variants that likely contribute to disease."
Miller says while this discovery will not immediately impact patient care, they do believe identifying genetic variants associated with the disease is the first step to identifying potential drug targets that can be used to develop therapeutics.
This work was funded by the National Institutes of Health, the Huntsman Cancer Institute, Brigham Young University, University of Utah, National Cancer Institute, BrightFocus Foundation, the National Heart, Lung, and Blood Institute, and was a collaboration with Brigham Young University, the University of Utah, and the Alzheimer's Disease Genetics Consortium.
Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Numbers RF1AG054052 and U01AG052411. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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