Dr. Heng Huang, computer scientist and professor in the Computer Science and Engineering Department at the University of Texas at Arlington, has received a National Institutes of Health’s five-year $2 million grant to study the correlation between mild cognitive impairment and Alzheimer’s Disease (AD).
The research will focus on the study of patterns (data mining) and analysis of genotype and phenotype data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), a database that, since 2005, validates the use of biomarkers for diagnostics and clinical trials, and studies brain function, structure and cognition in patients with mild to moderate AD, and different severity degrees of cognitive impairment or memory loss.
Mild cognitive impairment (MCI) describes a set of symptoms related to a decline in cognitive function, such as day-to-day memory, language and attention problems. MCI significantly increases the risk of developing dementia, though not all people who experience MCI decline into AD, some patients remain stable or even improve. There is extensive ongoing research towards identification of people with MCI that will eventually develop AD through different approaches, such as magnetic resonance imaging to detect changes in brain structure and activity, and identification and measurement of concentration of specific proteins in the cerebrospinal fluid that might reveal undergoing changes in brain activity.
Dr. Huang will use computational models that will include biological knowledge on the available data, to study the progression of mild cognitive impairment to AD, identify phenotypic biomarkers that will lead to the early prediction and diagnosis of the disease, and understand the genetic process involved in the conversion of MCI to AD. The clinical studies and validation of results will also be supported by researchers at the University of North Carolina at Chapel Hill.
Dr. Huang further explains the importance and methodology of the research in a news release, “Most people with mild cognitive impairment eventually contract Alzheimer’s , but some go back to normal. We want to predict MCI based on genomic information so that we may accurately predict whether they will get Alzheimer’s or not,” and he added, “From a biomedical standpoint, this is an opportunity to have very good knowledge of the genome technique and neuroimaging. From the computing side, we’ll be using very advanced algorithms to advance and study the brain.”
Ultimately, Dr. Huang’s research could extensively contribute to increase the present knowledge regarding Alzheimer’s disease and the human brain, and significantly improve patient’s quality of live and longevity.