A recent communication from the University of Texas at Arlington reported that computer scientists led by Professor Heng Huang won a $2 million grant funded by the National Institutes of Health to investigate the possibility of predicting whether a person is predisposed to develop Alzheimer’s disease by analyzing complex genomics data.
Alzheimer’s is a chronic neurodegenerative disorder which destroys memory and other vital mental functions. The disease usually progresses over time and during early stages, patients may suffer from mild symptoms like difficulties in remembering recent events. As the disease progresses, a number of other symptoms appear in patients that includes language problems, difficulty in thinking and understanding, changes in mood, and behavioral problems.
At advanced stages of the disease, patients are often unable to recognize common things and could detach from family and society. Though the speed of disease progression varies from one patient to another, main life expectancy after the diagnosis is estimated to be between three to nine years. In the US, more than 3 million cases are recorded every year and statistics suggest that the number should quadruple by 2050. The causes of Alzheimer’s disease are mostly unknown but evidence and hypotheses collected to date suggest a number of risk factors like genetic predisposition (1% to 5% of cases), reduced synthesis of the neurotransmitter acetylcholine, tau protein abnormalities, herpes simplex virus, and deposition of extracellular amyloid beta (Aβ) plaques, among others.
Unfortunately, there is no cure for Alzheimer’s, but the disease can be managed by medications, psychological intervention, caregiving, and feeding tubes in patients who have difficulties in swallowing food. On the other hand, early detection and prediction of Alzheimer’s disease would be beneficial as the latter may give hope to prevent or even reverse the effects of the disease. With this goal in mind, the team of scientists from the University of Texas at Arlington wants to investigate if biomarkers of early signs of Alzheimer’s disease could be identified using genomics. In this process, the researchers plan to build computational models and software to incorporate biological knowledge into existing data sets. The information will be updated every six months or so to fit with charges occurred in the brain. The study will also include identification of the genetic information responsible to transform mild cognitive impairment into Alzheimer’s. Part of the study will be performed in collaboration with researchers from the University of North Carolina at Chapel Hill where clinical studies and results verification will be performed.
This research would create the opportunity to acquire substantial knowledge of the genome technique, neuroimaging as well as advanced algorithms that will provide a better understanding of human brain function. Furthermore, identifying the mechanisms of progression from mild cognitive impairment to Alzheimer’s would have the potential to change the way the disease is viewed and how it could be treated. The latter would decline the number of patients affected by Alzheimer’s and would help people live longer, healthier, and happier lives. “The support of government for understanding the brain and brain diseases has created many opportunities for research into diseases such as Alzheimer’s,” Behbehani said. “Dr. Huang’s novel approach to studying mild cognitive impairment could contribute significantly to a better understanding of the human brain.”