SBMI Associate Professor Degui Zhi, PhD and his fellow researchers were recently awarded a new grant from the National Institute on Aging, which is part of the NIH. The research team’s $5.98 million, five-year project will focus on using artificial intelligence (AI) to advance Alzheimer's disease research.
“Alzheimer’s disease puts a tremendous burden and increasing demand on patients, caregivers, and healthcare resources,” said Zhi. “I look forward to working with a very talented research team to better understand this devastating disease and determine new treatment options.”
Zhi will collaborate with several fellow researchers for the project titled “Genetics of deep-learning-derived neuroimaging endophenotypes for Alzheimer's Disease.” Myriam Fornage, PhD from the McGovern School of Medicine at UTHealth and Shuiwang Ji, PhD from Texas A&M University are co-investigators. Additionally, SBMI Assistant Professors Han Chen, PhD, Luca Giancardo, PhD, and Assaf Gottlieb, PhD are part of the research team.
“This investigation is only possible with an incredible, multidisciplinary team,” he said. “The researchers on the team have extensive expertise in bioinformatics, brain MRI data analysis, and genome-wide association study (GWAS) in Alzheimer’s disease, and deep learning.”
According to the Centers for Disease Control and Prevention (CDC), as many as 5.8 million Americans were living with Alzheimer’s disease in 2020. The CDC projects that the number of Americans suffering from the severe neurodegenerative disease could nearly triple to 14 million people by 2060.
The researchers plan to use the grant funds to develop new, deep learning-based approaches for deriving Alzheimer's disease-relevant biological markers from neuroimaging data and associating these markers, known as endophenotypes, to genetic data. Endophenotypes are biological traits or markers that are easier to detect than genetic sequences. With their approach, Zhi and his colleagues expect to discover new genes relevant to Alzheimer's disease. This discovery may lead to understanding the molecular basis of the disease and new potential treatment.
“While neuroimaging has been a target for genetic association studies for Alzheimer's disease research, existing approaches generally focus on relatively few imaging phenotypes developed by neuroradiologists. Our goal is to use state-of-the-art deep neural networks to discover intricate patterns from large volumetric neuroimaging data that link genes with Alzheimer’s disease,” noted Zhi.
The project period began on July 1 and will conclude in June of 2026.
published on 07/12/2021 at 09:00 a.m.