Bayesian statistics and Bioinformatics for Biomarker validation using Biobanks in Alzheimer’s Disease

Although there is currently no cure for AD, an early diagnosis of the disease would improve a patient’s quality of life and slow down the progression of the disease. At present, the disease can only be conclusively diagnosed by histological examination of the brain after death. The clinical diagnosis of AD is made by conducting neurological and psychiatric examinations, expensive laboratory tests and a brain scan to rule out other conditions with similar symptoms. The definitive AD predictive accuracy of such exams is generally in the range of 75-80 %. Biomarkers that reflect AD pathology before clinical symptoms appear could enormously improve the diagnostic process.

Protein kinases are involved in the early stages of AD and therefore have a high potential as diagnostic markers. Kinase activity profiling using a peptide-based microarray technology (PamChip®) is a fast method, which can be performed with a small sample volume and requires no pre-treatment. The goal of my study is to optimize this technique for the detection of kinase activity in human CSF derived from patients with either AD or subjective memory complaints (SMC) and to identify specific kinases in human cerebrospinal fluid (CSF) which can be used as diagnostic markers.