Article

Alzheimer's disease And Diabetes: New Insights and Unifying Therapies.

Department of Clinical Science, Section of Biochemistry, School of Medicine. Università Politecnica delle Marche, Via Tronto 10 A, 60020 Ancona, Italy. .
Current diabetes reviews 01/2013; DOI: 10.2174/1573399811309030003
Source: PubMed

ABSTRACT Several research groups have begun to associate the Alzheimer Disease (AD) to Diabetes Mellitus (DM), obesity and cardiovascular disease. This relationship is so close that some authors have defined Alzheimer Disease as Type 3 Diabetes. Numerous studies have shown that people with type 2 diabetes have twice the incidence of sporadic AD. Insulin deficiency or insulin resistance facilitates cerebral β-amyloidogenesis in murine model of AD, accompanied by a significant elevation in APP (Amyloid Precursor Protein) and BACE1 (β-site APP Cleaving Enzime 1). Similarly, deposits of Aβ produce a loss of neuronal surface insulin receptors and directly interfere with the insulin signaling pathway. Furthermore, as it is well known, these disorders are both associated to an increased cardiovascular risk and an altered cholesterol metabolism, so we have analyzed several therapies which recently have been suggested as a remedy to treat together AD and DM. The aim of the present review is to better understand the strengths and drawbacks of these therapies.

3 Followers
 · 
263 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Amyloid plaques and neurofibrillary tangles (NFTs) are the defining pathological hallmarks of Alzheimer's disease (AD). Increasing the quantity of the O-linked N-acetylglucosamine (O-GlcNAc) post-translation modification of nuclear and cytoplasmic proteins slows neurodegeneration and blocks the formation of NFTs in a tauopathy mouse model. It remains unknown, however, if O-GlcNAc can influence the formation of amyloid plaques in the presence of tau pathology.
    Molecular Neurodegeneration 10/2014; 9(1):42. DOI:10.1186/1750-1326-9-42 · 5.29 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Cysteine-selective proteomics approaches simplify complex protein mixtures and improve the chance of detecting low abundant proteins. It is possible that cysteinyl-peptide/protein enrichment methods could be coupled to isotopic labeling and isobaric tagging methods for quantitative proteomics analyses in as few as two or up to 10 samples, respectively. Here we present two novel cysteine-selective proteomics approaches: cysteine-selective dimethyl labeling (cysDML) and cysteine-selective combined precursor isotopic labeling and isobaric tagging (cPILOT). CysDML is a duplex precursor quantification technique that couples cysteinyl-peptide enrichment with on-resin stable-isotope dimethyl labeling. Cysteine-selective cPILOT is a novel 12-plex workflow based on cysteinyl-peptide enrichment, on-resin stable-isotope dimethyl labeling, and iodoTMT tagging on cysteine residues. To demonstrate the broad applicability of the approaches, we applied cysDML and cPILOT methods to liver tissues from an Alzheimer's disease (AD) mouse model and wild-type (WT) controls. From the cysDML experiments, an average of 850 proteins were identified and 594 were quantified, whereas from the cPILOT experiment, 330 and 151 proteins were identified and quantified, respectively. Overall, 2259 unique total proteins were detected from both cysDML and cPILOT experiments. There is tremendous overlap in the proteins identified and quantified between both experiments, and many proteins have AD/WT fold-change values that are within ~20% error. A total of 65 statistically significant proteins are differentially expressed in the liver proteome of AD mice relative to WT. The performance of cysDML and cPILOT are demonstrated and advantages and limitations of using multiple duplex experiments versus a single 12-plex experiment are highlighted.
    Journal of the American Society for Mass Spectrometry 01/2015; DOI:10.1007/s13361-014-1059-9 · 3.19 Impact Factor
  • Source
    Critical Reviews in Eukaryotic Gene Expression 01/2015; DOI:10.1615/CritRevEukaryotGeneExpr.2015013358 · 2.39 Impact Factor

Full-text

Download
363 Downloads
Available from
May 27, 2014