BACE1 Polymorphisms Do Not Influence Platelet Membrane β-secretase Activity or Genetic Susceptibility for Alzheimer’s Disease in the Northern Irish Population

ß-Site amyloid precursor protein (APP)-cleaving enzyme 1 (BACE1) is a biological and positional candidate gene for Alzheimer’s disease (AD). BACE1 is a protease that catalyses APP cleavage at the ß-secretase site. We evaluated all common and putatively functional polymorphisms in the genomic region encompassing BACE1 for an association with AD, and for functional effects on platelet ß-secretase activity. Tag SNPs (n = 10) derived from phase II of the International HapMap Project, and a nonsynonymous variant, were successfully genotyped in 901 Caucasian individuals from Northern Ireland using Sequenom iPLEX and TaqMan technologies. APOE genotyping was performed by PCR-RFLP. Platelet membrane ß-secretase activity was assayed in a subset of individuals (n = 311). Hardy–Weinberg equilibrium was observed for all variants. Evidence for an association with AD was observed with multi-marker haplotype analyses (P = 0.01), and with rs676134 when stratified for APOE genotype (P = 0.02), however adjusting for multiple testing negated the evidence for association of this variant with AD. ?2 analysis of genotype and allele frequencies in cases versus controls for individual SNPs revealed no evidence for association (5% level). No genetic factors were observed that significantly influenced platelet membrane ß-secretase activity. We have selected an appropriate subset of variants suitable for comprehensive genetic investigation of the BACE1 gene. Our results suggest that common BACE1 polymorphisms and putatively functional variants have no significant influence on genetic susceptibility to AD, or platelet ß-secretase activity, in this Caucasian Northern Irish population.

Investigation of the Human Brain Metabolome to Identify Potential Markers for Early Diagnosis and Therapeutic Targets of Alzheimer’s Disease

A study combining high resolution mass spectrometry (liquid chromatography-quadrupole time-of-flight-mass spectrometry, UPLC-QTof-MS) and chemometrics for the analysis of post-mortem brain tissue from subjects with Alzheimer’s disease (AD) (n = 15) and healthy age-matched controls (n = 15) was undertaken. The huge potential of this metabolomics approach for distinguishing AD cases is underlined by the correct prediction of disease status in 94–97% of cases. Predictive power was confirmed in a blind test set of 60 samples, reaching 100% diagnostic accuracy. The approach also indicated compounds significantly altered in concentration following the onset of human AD. Using orthogonal partial least-squares discriminant analysis (OPLS-DA), a multivariate model was created for both modes of acquisition explaining the maximum amount of variation between sample groups (Positive Mode-R2 = 97%; Q2 = 93%; root mean squared error of validation (RMSEV) = 13%; Negative Mode-R2 = 99%; Q2 = 92%; RMSEV = 15%). In brain extracts, 1264 and 1457 ions of interest were detected for the different modes of acquisition (positive and negative, respectively). Incorporation of gender into the model increased predictive accuracy and decreased RMSEV values. High resolution UPLC-QTof-MS has not previously been employed to biochemically profile post-mortem brain tissue, and the novel methods described and validated herein prove its potential for making new discoveries related to the etiology, pathophysiology, and treatment of degenerative brain disorders.

Metabolic signatures of human Alzheimer's disease (AD): H-1 NMR analysis of the polar metabolome of post-mortem brain tissue

Brain tissue from so-called Alzheimer's disease (AD) mouse models has previously been examined using H-1 NMR-metabolomics, but comparable information concerning human AD is negligible. Since no animal model recapitulates all the features of human AD we undertook the first H-1 NMR-metabolomics investigation of human AD brain tissue. Human post-mortem tissue from 15 AD subjects and 15 age-matched controls was prepared for analysis through a series of lyophilised, milling, extraction and randomisation steps and samples were analysed using H-1 NMR. Using partial least squares discriminant analysis, a model was built using data obtained from brain extracts. Analysis of brain extracts led to the elucidation of 24 metabolites. Significant elevations in brain alanine (15.4 %) and taurine (18.9 %) were observed in AD patients (p ≤ 0.05). Pathway topology analysis implicated either dysregulation of taurine and hypotaurine metabolism or alanine, aspartate and glutamate metabolism. Furthermore, screening of metabolites for AD biomarkers demonstrated that individual metabolites weakly discriminated cases of AD [receiver operating characteristic (ROC) AUC <0.67; p < 0.05]. However, paired metabolites ratios (e.g. alanine/carnitine) were more powerful discriminating tools (ROC AUC = 0.76; p < 0.01). This study further demonstrates the potential of metabolomics for elucidating the underlying biochemistry and to help identify AD in patients attending the memory clinic

Wide-ranging alterations in the brain fatty acid complement of subjects with late Alzheimer’s disease as detected by GC-MS

Disturbed lipid metabolism is a well-established feature of human Alzheimer’s disease (AD). The present study used gas chromatography-mass spectrometry (GC-MS) analysis of fatty acid methyl esters (FAMES) to profile all detectable fatty acid (FA) species present in post-mortem neocortical tissue (Brodmann 7 region). Quantitative targeted analysis was undertaken from 29 subjects (n=15 age-matched controls; n=14 late-stage AD). GC-MS analysis of FAMES detected a total of 24 FAs and of these, 20 were fully quantifiable. The results showed significant and wide ranging elevations in AD brain FA concentrations. A total of 9 FAs were elevated in AD with cis-13,16-docosenoic acid increased most (170%; P=0.033). Intriguingly, docosahexanoic acid (DHA; C22:6) concentrations were elevated (47%; P=0.018) which conflicts with the findings of others (unaltered or decreased) in some brain regions after the onset of AD. Furthermore, our results appear to indicate that subject gender influences brain FA levels in AD subjects (but not in age-matched control subjects). Among AD subjects 7 FA species were significantly higher in males than in females. These preliminary findings pinpoint FA disturbances as potentially important in the pathology of AD. Further work is required to determine if such changes are influenced by disease severity or different types of dementia.

Variation in RTN3 and PPIL2 Genes Does not Influence Platelet Membrane β-Secretase Activity or Susceptibility to Alzheimer’s Disease in the Northern Irish Population

beta-site amyloid precursor protein cleaving enzyme (BACE1) is the rate-limiting enzyme for production of beta-amyloid peptides (A beta), which are proposed to drive the pathological changes found in Alzheimer's disease (AD). Reticulon 3 (RTN3) is a negative modulator of BACE1 (beta-secretase) proteolytic activity, while peptidylprolyl isomerase (cyclophilin)-like 2 (PPIL2) positively regulates BACE1 expression. The present study investigated whether there was any association between genetic variation in RTN3 and PPIL2, and either risk for AD, or levels of platelet beta-secretase activity, in a large Northern Irish case-control sample. Four hundred and sixty-nine patients with a diagnosis of probable AD (NINCDS-ADRDA criteria) and 347 control individuals (MMSE > 28/30) were genotyped. SNPs in both genes were selected by downloading genotype data from the International HapMap Project (Phase II) and tags selected using multimarker approach in Haploview, where r (2) > 0.8 and LOD > 3.0. Non-synonymous SNPs of interest were also included. Genotyping was performed by Sequenom iPLEX and TaqMan technologies. Alleles, genotypes and multi-marker haplotypes were tested for association with AD, and platelet beta-secretase activities were measured for a subset of individuals (n = 231). Eight SNPs in RTN3 and 7 in PPIL2 were genotyped. We found no significant associations between allele, genotype or haplotype frequencies and risk of AD. Further, there was no effect of genotype on platelet membrane beta-secretase activity. We conclude that common or potentially functional genetic variation in these BACE1 interacting proteins does not affect platelet membrane beta-secretase activity or contribute to risk of AD in this population.

Untargeted Metabolomic Analysis of Human Plasma Indicates Differentially Affected Polyamine and L-Arginine Metabolism in Mild Cognitive Impairment Subjects Converting to Alzheimer’s Disease

This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer's disease (MCI_AD; n = 19), and healthy age-matched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7μm x 2.1 x 100 mm) column coupled to a Xevo G2 QTof mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients 'at risk' from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.