Targeted Abeta proteomics - A tool to study the pathogenesis of Alzheimer’s disease
Alzheimer’s disease (AD) is an age-related progressive neurodegenerative disorder of the central nervous system. Diagnosis and monitoring of sporadic AD has long depended on clinical examination of individuals with end-stage disease. The accumulation of amyloid-? (A?) peptides in specific brain regions is believed to represent the earliest event in the pathogenesis of the disease and there is developing consensus for the use of cerebrospinal fluid (CSF) A? as a core biomarker for the mild cognitive impairment stage of AD. A? has been the subject of extensive research aimed at identifying markers for the disrupted balance between the production and clearance of the peptide. Many studies on A? in plasma, cell media, and CSF have been based on immunoassays such as enzyme-linked immunosorbent assays where specific antibodies are used to discriminate between for example the 40- and 42-amino acid long A? peptides (A?1-40 and A?1-42, respectively). The aim of this thesis was to develop a targeted A? proteomic approach using immunoprecipitation (IP) and mass spectrometry (MS). To study A? in CSF, a highly specific IP was developed and combined with MS. Using various A? specific antibodies with different epitopes, more than 20 A? isoforms have so far been identified and verified. Furthermore, a relative abundance pattern including A?1-16, and A?1-42 in CSF, distinguished sporadic AD patients from non-demented control subjects with a high degree of accuracy in two independent studies. The IP-MS method was automated and further optimized which improved the speed of sample preparation and thus sample capacity. By adding isotopically labelled internal standards, variations in the IP and the MS desorption/ionization processes were diminished. This increased the possibility of using the method in AD diagnostics and of estimating the concentration of the A? isoforms present in CSF. To address from which processing pathways the shorter isoforms arise, for example A?1-15/16/17, a cell model accurately reflecting the A? isoform pattern in CSF was developed. The optimized and automated IP-MS method was used to determine changes in the A? isoform pattern induced by alpha-, ?-, and gamma-secretase inhibitor treatment. All isoforms longer than and including A?1-17 were gamma-secretase dependent, whereas shorter isoforms were gamma-secretase independent. These shorter isoforms, including A?1-15, were reduced by treatment with alpha- and ?-secretase inhibitors, suggesting the existence of a third and previously unknown APP processing pathway. The described APP processing pathway was further investigated by exploring the effects of gamma-secretase inhibition on the A? isoform pattern in brain and CSF from transgenic mice. As in the cell model, all fragments longer than and including A?1-17 decreased upon gamma-secretase inhibition, whereas the shorter isoforms, e.g. A?1-15, increased. These data, together with the cell model data, strongly suggest that A?1-15 and A?1-16 may be generated through a third metabolic pathway by concerted beta- and alpha-secretase cleavage of APP.
Source Type:Doctoral Dissertation
Keywords:MEDICINE; Alzheimer’s disease; Cerebrospinal fluid; Immunoprecipitation; Mass spectrometry; beta-amyloid
Date of Publication:01/01/2009