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Johnson P.,CSIRO | Vandewater L.,CSIRO | Wilson W.,CSIRO | Wilson W.,Cooperative Research Center for Mental Health | And 18 more authors.
BMC Bioinformatics | Year: 2014

Background: Assessment of risk and early diagnosis of Alzheimer's disease (AD) is a key to its prevention or slowing the progression of the disease. Previous research on risk factors for AD typically utilizes statistical comparison tests or stepwise selection with regression models. Outcomes of these methods tend to emphasize single risk factors rather than a combination of risk factors. However, a combination of factors, rather than any one alone, is likely to affect disease development. Genetic algorithms (GA) can be useful and efficient for searching a combination of variables for the best achievement (eg. accuracy of diagnosis), especially when the search space is large, complex or poorly understood, as in the case in prediction of AD development. Results: Multiple sets of neuropsychological tests were identified by GA to best predict conversions between clinical categories, with a cross validated AUC (area under the ROC curve) of 0.90 for prediction of HC conversion to MCI/AD and 0.86 for MCI conversion to AD within 36 months. Conclusions: This study showed the potential of GA application in the neural science area. It demonstrated that the combination of a small set of variables is superior in performance than the use of all the single significant variables in the model for prediction of progression of disease. Variables more frequently selected by GA might be more important as part of the algorithm for prediction of disease development. © 2014 Johnson et al.

Rembach A.,University of Melbourne | Watt A.D.,University of Melbourne | Wilson W.J.,CSIRO | Rainey-Smith S.,Sir James McCusker Alzheimers Disease Research Unit | And 10 more authors.
Journal of Neuroimmunology | Year: 2014

Inflammation is a hallmark of Alzheimer's disease (AD). Whether directly involved in the pathogenesis, or a downstream consequence of neuronal death, the blood neutrophil-lymphocyte ratio (NLR) is reported to be a putative, non-invasive peripheral biomarker for AD. The aim of this study was to re-evaluate the diagnostic utility of longitudinal measures of the NLR. The NLR was stable across all time-points and weakly correlated with neocortical amyloid burden (R. = 0.21 at baseline, 0.27 at 18. months, 0.20 at 36. months and 0.10 at 54. months). Cross-sectionally, the NLR was significantly elevated in AD participants as compared to HC participants at baseline (p< 0.0001), 18. months (p< 0.0001), 36. months (p= 0.002) and at 54. months (p= 0.007), however only prior to adjustment for age, sex and APOEε4 allele status (p> 0.05 at all time-points except for 18. months; p< 0.0001). Longitudinally, the NLR was not significantly different between HC and AD participants (p> 0.05) adjusted for age, sex and APOEε4 allele status. Comparing the NLR between cognitive transition groups over time (transition towards an AD type dementia), there was no significant difference in the NLR levels between those participants, who did not transition and those participants who did transition, or those in the stable AD group after adjusting for age, sex and APOEε4 allele status (p> 0.05). Despite inflammation being a hallmark in AD and previous reports showing that the NLR can discriminate HC from AD patients, our results suggest that the sensitivity of the NLR itself is not robust enough for diagnostic utility. We identified significant relationships cross sectionally (p< 0.05 at baseline, 18. months and 36. months) between the NLR and neocortical amyloid burden, but this relationship was lost after longitudinal analyses (p> 0.5). The NLR also had limited association with cognitive decline, although in our cohort, the number of participants transitioning was relatively small. In conclusion, the NLR may reflect AD-related inflammatory processes in the periphery, but age and sex are dominant covariates which need to be controlled for in population-based screening. © 2014 Elsevier B.V.

Barr R.K.,Edith Cowan University | Barr R.K.,Alzhyme Pty Ltd. | Verdile G.,Curtin University Australia | Verdile G.,Sir James McCusker Alzheimers Disease Research Unit | And 17 more authors.
Journal of Biological Chemistry | Year: 2016

Although the formation of β-amyloid (Aβ) deposits in the brain is a hallmark of Alzheimer disease (AD), the soluble oligomers rather than the mature amyloid fibrils most likely contribute to Aβ toxicity and neurodegeneration. Thus, the discovery of agents targeting soluble Aβ oligomers is highly desirable for early diagnosis prior to the manifestation of a clinical AD phenotype and also more effective therapies. We have previously reported that a novel 15-amino acid peptide (15-mer), isolated via phage display screening, targeted Aβ and attenuated its neurotoxicity (Taddei, K., Laws, S. M., Verdile, G., Munns, S., D'Costa, K., Harvey, A. R., Martins, I. J., Hill, F., Levy, E., Shaw, J. E., and Martins, R. N. (2010) Neurobiol. Aging 31, 203-214). The aim of the current study was to generate and biochemically characterize analogues of this peptide with improved stability and therapeutic potential. We demonstrated that a stable analogue of the 15-amino acid peptide (15M S.A.) retained the activity and potency of the parent peptide and demonstrated improved proteolytic resistance in vitro (stable to t = 300 min, c.f. t = 30 min for the parent peptide). This candidate reduced the formation of soluble Aβ42 oligomers, with the concurrent generation of non-toxic, insoluble aggregates measuring up to 25-30 nm diameter as determined by atomic force microscopy. The 15M S.A. candidate directly interacted with oligomeric Aβ42, as shown by coimmunoprecipitation and surface plasmon resonance/Biacore analysis, with an affinity in the low micromolar range. Furthermore, this peptide bound fibrillar Aβ42 and also stained plaques ex vivo in brain tissue from AD model mice. Given its multifaceted ability to target monomeric and aggregated Aβ42 species, this candidate holds promise for novel preclinical AD imaging and therapeutic strategies. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc. Published in the U.S.A.

Rembach A.,University of Melbourne | Stingo F.C.,University of Texas M. D. Anderson Cancer Center | Peterson C.,Stanford University | Vannucci M.,Rice University | And 10 more authors.
Journal of Alzheimer's Disease | Year: 2015

With different approaches to finding prognostic or diagnostic biomarkers for Alzheimer's disease (AD), many studies pursue only brief lists of biomarkers or disease specific pathways, potentially dismissing information from groups of correlated biomarkers. Using a novel Bayesian graphical network method, with data from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, the aim of this study was to assess the biological connectivity between AD associated blood-based proteins. Briefly, three groups of protein markers (18, 37, and 48 proteins, respectively) were assessed for the posterior probability of biological connection both within and between clinical classifications. Clinical classification was defined in four groups: high performance healthy controls (hpHC), healthy controls (HC), participants with mild cognitive impairment (MCI), and participants with AD. Using the smaller group of proteins, posterior probabilities of network similarity between clinical classifications were very high, indicating no difference in biological connections between groups. Increasing the number of proteins increased the capacity to separate both hpHC and HC apart from the AD group (0 for complete separation, 1 for complete similarity), with posterior probabilities shifting from 0.89 for the 18 protein group, through to 0.54 for the 37 protein group, and finally 0.28 for the 48 protein group. Using this approach, we identified beta-2 microglobulin (β2M) as a potential master regulator of multiple proteins across all classifications, demonstrating that this approach can be used across many data sets to identify novel insights into diseases like AD. © 2015 -IOS Press and the authors. All rights reserved.

Sutton T.A.,University of Western Australia | Sohrabi H.R.,University of Western Australia | Sohrabi H.R.,Edith Cowan University | Sohrabi H.R.,Sir James McCusker Alzheimers Disease Research Unit | And 11 more authors.
Translational Psychiatry | Year: 2015

Individual biological differences may contribute to the variability of outcomes, including cognitive effects, observed following electroconvulsive treatment (ECT). A narrative review of the research literature on carriage of the apolipoprotein E ϵ4 allele (APOE-ϵ4) and the protein biomarker beta amyloid (Aβ) with ECT cognitive outcome was undertaken. ECT induces repeated brain seizures and there is debate as to whether this causes brain injury and long-term cognitive disruption. The majority of ECT is administered to the elderly (over age 65 years) with drug-resistant depression. Depression in the elderly may be a symptom of the prodromal stage of Alzheimer's disease (AD). Carriage of the APOE-ϵ4 allele and raised cerebral Aβ are consistently implicated in AD, but inconsistently implicated in brain injury (and related syndromes) recovery rates. A paucity of brain-related recovery, genetic and biomarker research in ECT responses in the elderly was found: three studies have examined the effect of APOE-ϵ4 allele carriage on cognition in the depressed elderly receiving ECT, and two have examined Aβ changes after ECT, with contradictory findings. Cognitive changes in all studies of ECT effects were measured by a variety of psychological tests, making comparisons of such changes between studies problematic. Further, psychological test data-validity measures were not routinely administered, counter to current testing recommendations. The methodological issues of the currently available literature as well as the need for well-designed, hypothesis driven, longitudinal studies are discussed.

Rembach A.,University of Melbourne | Rembach A.,CSIRO | Doecke J.D.,Australian alth Research Center | Doecke J.D.,CSIRO | And 20 more authors.
Journal of Alzheimer's Disease | Year: 2013

Background: Several studies have reported that peripheral levels of copper and ceruloplasmin (CP) can differentiate patients with Alzheimer's disease (AD) from non-AD cases. The aim of this study was to determine the diagnostic value of serum copper, CP, and non-CP copper levels in a large cohort of AD subjects. Methods: Serum copper and CP concentrations were measured at baseline and at 18-months in participants from the Australian Imaging Biomarkers and Lifestyle Study of Ageing. Cross-sectional and longitudinal analyses were conducted using both univariate and multivariate testing adjusting for age, gender, total protein, and ApoE ε4 genotype status. Results: There was no significant difference in levels of serum copper or CP between the AD and healthy control groups, however, we identified a near-significant decrease in non-CP copper in the mild cognitive impairment and AD groups at baseline (p = 0.02) that was significant at 18-months (p = 0.003). Conclusion: Our results suggest that there may be decreased non-CP copper levels in mild cognitive impairment and AD, which is consistent with diminished copper-dependent biochemical activities described in AD. © 2013 - IOS Press and the authors. All rights reserved.

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