David Patty and Dr. John SK Kauwe, Biology
Alzheimer’s Disease, the most common form of dementia, affects nearly 6 million Americans. Its effects on the individual range from mild impairment of memory to the complete destruction of the victim’s identity and their ability to perform everyday tasks. They become a heavy burden on their family, requiring constant medical care that often leaves the family with not only emotional problems, but financial stress as well. A study involving a clinical diagnosis of the disease, or case-control study, is limited by the accuracy of a psychiatrist’s judgment of the severity of the disease. This is obtained by a verbal and visual memory test. Classic case-control studies have limited statistical power since a diagnosis can only result in one of five levels of severity for each individual, and are subject to the bias of a psychiatrist.
The disease is known to be caused by a number of proteins within the brain and cerebrospinal fluid (CSF). We measure endophenotypes, or the levels of different proteins within the brain fluids, that have significant correlation to the progression of Alzheimer’s Disease. The measurement of the levels of these proteins lends itself to higher statistical power, since values for the levels of each protein are not limited to a 5 point scale.
My study is based on a recent study of cerebrospinal fluid (CSF) biomarkers in 374 individuals from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). It identified four genome-wide significant SNPs (Single Nucleotide Polymorphism), or places in the genome that differ from person to person. They also reported five other SNPs that showed suggestive association in their study. I attempted to validate each of these specific associations in 891 individuals for whom CSF biomarker measurements have been made.
I performed my study on data collected from three sources, ADNI, University of Washington (UW), and the Knight Alzheimer’s Disease Research Center (Knight ADRC). We used a non-parametric approach of 1 million permutations and compensated for noise within the data by using covariates found by a stepwise regression analysis test. I used BYU’s MaryLou, a supercomputer in the Fulton Supercomputing Lab, to perform the linear regression analyses.
Although my study was biased toward replicating the findings of the previous study by including the entire dataset their study was based on, I failed to detect significant association between the reported SNPs and phenotypes. My conclusion is that their findings were false positive results.
In July 2011, I was privileged to attend the Alzheimer’s Association International Conference on Alzheimer’s Disease (AAICAD) in Paris, France. I travelled with my mentor and other research assistants from my lab. The conference hosted more than 5000 scientists and doctors from around the world, collaborating and presenting their personal research projects and their company’s developments in treatment of the disease. I presented my research in the form of a poster to PhD students and doctors.
Some even asked where I did my PhD program! They were surprised to find out that I was still an undergraduate, and had conducted such advanced research. Meeting and networking with some of the leading scientists in the field of Alzheimer’s Disease has been crucial to my personal development as a scientist, and for helping influence my desire to continue my life-long education.