Identification of potential modifiers of Alzheimer’s disease pathology by quantitative mass spectrometry and drosophila genetics


      Alzheimer’s disease (AD) is the most common form of dementia in the elderly, affecting around 24.3 million people worldwide. As a consequence of the rapid demographic ageing, AD has become one of the most severe progressive socio-economical and medical burdens facing countries all over the world. AD brains are characterized by the presence of extracellular deposits of amyloid-b-containing plaques and intracellular neurofibrillary tangles (NFTs) composed of paired helical filaments of hyperphosphorylated Tau protein. AD is considered to be the result of complex events involving both genetic and environmental factors. Among them, two remarkable factors are oxidative stress and mitochondrial damage.


      To gain further insights into this complexity, we recently identified differentially expressed proteins in AD brains by iTRAQ-protein labeling and tandem mass spectrometry.


      Compared to control samples, we identified more than 721 polypeptides, 61 of which were found over-expressed including Ferritin heavy chain, HSP70 and Phosphoglucomutase-1(PGM1). On the other hand, 71 proteins were found under expressed like RhoA, Sideroflexin-1 (SFXN1) and HSP60. To validate our results, we conducted semi-quantitative analyses with WB using specific antibodies against selected proteins. In addition, their homologue genes were manipulated in Drosophila models of Abeta- and Tau-induced pathology to assess their specific involvement in the disease. After inspection of eye phenotypes in such fly models.


      We found that some proteins do not appear to modify Abeta or Tau insults. However, other proteins can either modify Abeta toxicity, Tau toxicity or both, suggesting specific interactions with different pathways. This approach illustrates the potential of Drosophila models to validate hits after mass spectrometry studies and suggest that model organisms must be included in the pipeline to identify relevant targets. We anticipate that the results of this work may have important therapeutic implications for AD and related disorders.