Medicine (Austin & Northern Health) - Research Publications
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ItemNo Preview AvailableLipidomic signatures for APOE genotypes provides new insights about mechanisms of resilience in Alzheimer’s disease(Wiley, 2021-12)Background The apolipoprotein E gene (APOE) genotype is the first and strongest genetic risk factor for late‐onset Alzheimer’s disease and has emerged as a novel therapeutic target for AD. The encoded protein (Apolipoprotein E, APOE) is well‐known to be involved in lipoprotein transport and metabolism, but its effect on lipid metabolic pathways and the potential mediating effect of these on disease risk have not been fully defined. Method We performed lipidomic analysis on three independent cohorts (AIBL, n = 693; ADNI, n=207; BHS, n=4,384) and defined the association between APOE polymorphisms (ε4 and ε2) and plasma lipid species. To identify associations independent of lipoprotein metabolism, the analyses was performed with adjustment for clinical lipids (total cholesterol, HDL‐C and triglycerides). Causal mediation analysis was performed to estimate the proportion of risk in the outcome model explained by a direct effect of APOE genotype on prevalent AD — the average direct effect (ADE) — and the proportion that was mediated by lipid species or lipidomic risk models — the average causal mediation effect (ACME). Result We identified multiple associations of species from lipid classes such as ceramide, hexosylceramide, sphingomyelin, plasmalogens, alkyldiacylglycerol and cholesteryl esters with APOE polymorphisms (ε4 and ε2) that were independent of clinical lipoprotein measurements. There were 104 and 237 lipid species associated with APOE ε4 and ε2 respectively which were largely discordant. Of these 116 were also associated with Alzheimer’s disease. Individual lipid species (notably the alkyldiacylglycerol subspecies) or lipidomic risk models of APOE genotypes mediated up to 10% and 30% of APOE ε4 and ε2 treatment effect on AD risks respectively. Conclusion We demonstrate a strong relationship between APOE polymorphisms and peripheral lipid species. Lipids species mediate a proportion of the effects of APOE genotypes in risk of AD, particularly resilience with e2. Our results highlight the involvement of lipids in how APOE e2 mediates its resilience to AD and solidify their involvement with the disease pathway.
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ItemFifteen Years of the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study: Progress and Observations from 2,359 Older Adults Spanning the Spectrum from Cognitive Normality to Alzheimer's Disease(IOS PRESS, 2021)BACKGROUND: The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study commenced in 2006 as a prospective study of 1,112 individuals (768 cognitively normal (CN), 133 with mild cognitive impairment (MCI), and 211 with Alzheimer's disease dementia (AD)) as an 'Inception cohort' who underwent detailed ssessments every 18 months. Over the past decade, an additional 1247 subjects have been added as an 'Enrichment cohort' (as of 10 April 2019). OBJECTIVE: Here we provide an overview of these Inception and Enrichment cohorts of more than 8,500 person-years of investigation. METHODS: Participants underwent reassessment every 18 months including comprehensive cognitive testing, neuroimaging (magnetic resonance imaging, MRI; positron emission tomography, PET), biofluid biomarkers and lifestyle evaluations. RESULTS: AIBL has made major contributions to the understanding of the natural history of AD, with cognitive and biological definitions of its three major stages: preclinical, prodromal and clinical. Early deployment of Aβ-amyloid and tau molecular PET imaging and the development of more sensitive and specific blood tests have facilitated the assessment of genetic and environmental factors which affect age at onset and rates of progression. CONCLUSION: This fifteen-year study provides a large database of highly characterized individuals with longitudinal cognitive, imaging and lifestyle data and biofluid collections, to aid in the development of interventions to delay onset, prevent or treat AD. Harmonization with similar large longitudinal cohort studies is underway to further these aims.
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ItemConcordant peripheral lipidome signatures in two large clinical studies of Alzheimer's disease(NATURE PORTFOLIO, 2020-11-10)Changes to lipid metabolism are tightly associated with the onset and pathology of Alzheimer's disease (AD). Lipids are complex molecules comprising many isomeric and isobaric species, necessitating detailed analysis to enable interpretation of biological significance. Our expanded targeted lipidomics platform (569 species across 32 classes) allows for detailed lipid separation and characterisation. In this study we examined peripheral samples of two cohorts (AIBL, n = 1112 and ADNI, n = 800). We are able to identify concordant peripheral signatures associated with prevalent AD arising from lipid pathways including; ether lipids, sphingolipids (notably GM3 gangliosides) and lipid classes previously associated with cardiometabolic disease (phosphatidylethanolamine and triglycerides). We subsequently identified similar lipid signatures in both cohorts with future disease. Lastly, we developed multivariate lipid models that improved classification and prediction. Our results provide a holistic view between the lipidome and AD using a comprehensive approach, providing targets for further mechanistic investigation.
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ItemRisk prediction of late-onset Alzheimer's disease implies an oligogenic architecture(NATURE RESEARCH, 2020-09-23)Genetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer’s disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimal P-threshold (Poptimal) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and individuals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD.
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ItemPlasma High Density Lipoprotein Small Subclass is Reduced in Alzheimer's Disease Patients and Correlates with Cognitive Performance(IOS PRESS, 2020)BACKGROUND: The link between cholesterol and Alzheimer's disease (AD) has received much attention, as evidence suggests high levels of cholesterol might be an AD risk factor. The carriage of cholesterol and lipids through the body is mediated via lipoproteins, some of which, particularly apolipoprotein E (ApoE), are intimately linked with AD. In humans, high density lipoprotein (HDL) is regarded as a "good" lipid complex due to its ability to enable clearance of excess cholesterol via 'cholesterol reverse transport', although its activities in the pathogenesis of AD are poorly understood. There are several subclasses of HDL; these range from the newly formed small HDL, to much larger HDL. OBJECTIVE: We examined the major subclasses of HDL in healthy controls, mild cognitively impaired, and AD patients who were not taking statins to determine whether there were HDL profile differences between the groups, and whether HDL subclass levels correlated with plasma amyloid-β (Aβ) levels or brain Aβ deposition. METHODS: Samples from AIBL cohort were used in this study. HDL subclass levels were assessed by Lipoprint while Aβ1-42 levels were assessed by ELISA. Brain Aβ deposition was assessed by PET scan. Statistical analysis was performed using parametric and non-parametric tests. RESULTS: We found that small HDL subclass is reduced in AD patients and it correlates with cognitive performance while plasma Aβ concentrations do not correlate with lipid profile or HDL subfraction levels. CONCLUSION: Our data indicate that AD patients exhibit altered plasma HDL profile and that HDL subclasses correlate with cognitive performances.
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ItemRelationships Between Plasma Lipids Species, Gender, Risk Factors, and Alzheimer's Disease(IOS PRESS, 2020)BACKGROUND: Lipid metabolism is altered in Alzheimer's disease (AD); however, the relationship between AD risk factors (age, APOEɛ4, and gender) and lipid metabolism is not well defined. OBJECTIVE: We investigated whether altered lipid metabolism associated with increased age, gender, and APOE status may contribute to the development of AD by examining these risk factors in healthy controls and also clinically diagnosed AD individuals. METHODS: We performed plasma lipidomic profiling (582 lipid species) of the Australian Imaging, Biomarkers and Lifestyle flagship study of aging cohort (AIBL) using liquid chromatography-mass spectrometry. Linear regression and interaction analysis were used to explore the relationship between risk factors and plasma lipid species. RESULTS: We observed strong associations between plasma lipid species with gender and increasing age in cognitively normal individuals. However, APOEɛ4 was relatively weakly associated with plasma lipid species. Interaction analysis identified differential associations of sphingolipids and polyunsaturated fatty acid esterified lipid species with AD based on age and gender, respectively. These data indicate that the risk associated with age, gender, and APOEɛ4 may, in part, be mediated by changes in lipid metabolism. CONCLUSION: This study extends our existing knowledge of the relationship between the lipidome and AD and highlights the complexity of the relationships between lipid metabolism and AD at different ages and between men and women. This has important implications for how we assess AD risk and also for potential therapeutic strategies involving modulation of lipid metabolic pathways.
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ItemCerebrospinal fluid neurofilament light concentration predicts brain atrophy and cognition in Alzheimer's disease(WILEY, 2020)INTRODUCTION: This study assessed the utility of cerebrospinal fluid (CSF) neurofilament light (NfL) in Alzheimer's disease (AD) diagnosis, its association with amyloid and tau pathology, as well as its potential to predict brain atrophy, cognition, and amyloid accumulation. METHODS: CSF NfL concentration was measured in 221 participants from the Australian Imaging, Biomarkers & Lifestyle Flagship Study of Ageing (AIBL). RESULTS: CSF NfL levels as well as NfL/amyloid β (Aβ42) were significantly elevated in AD compared to healthy controls (HC; P < .001), and in mild cognitive impairment (MCI) compared to HC (P = .008 NfL; P < .001 NfL/Aβ42). CSF NfL and NfL/Aβ42 differentiated AD from HC with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.84 and 0.90, respectively. CSF NfL and NfL/Aβ42 predicted cortical amyloid load, brain atrophy, and cognition. DISCUSSION: CSF NfL is a biomarker of neurodegeneration, correlating with cognitive impairment and brain neuropathology.
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ItemThe hypoxia imaging agent CuII(atsm) is neuroprotective and improves motor and cognitive functions in multiple animal models of Parkinson's disease(ROCKEFELLER UNIV PRESS, 2012-04-09)Parkinson's disease (PD) is a progressive, chronic disease characterized by dyskinesia, rigidity, instability, and tremors. The disease is defined by the presence of Lewy bodies, which primarily consist of aggregated α-synuclein protein, and is accompanied by the loss of monoaminergic neurons. Current therapeutic strategies only give symptomatic relief of motor impairment and do not address the underlying neurodegeneration. Hence, we have identified Cu(II)(atsm) as a potential therapeutic for PD. Drug administration to four different animal models of PD resulted in improved motor and cognition function, rescued nigral cell loss, and improved dopamine metabolism. In vitro, this compound is able to inhibit the effects of peroxynitrite-driven toxicity, including the formation of nitrated α-synuclein oligomers. Our results show that Cu(II)(atsm) is effective in reversing parkinsonian defects in animal models and has the potential to be a successful treatment of PD.
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ItemInfluence of BDNF Val66Met on the relationship between physical activity and brain volume(LIPPINCOTT WILLIAMS & WILKINS, 2014-10-07)OBJECTIVE: To investigate the association between habitual physical activity levels and brain temporal lobe volumes, and the interaction with the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism. METHODS: This study is a cross-sectional analysis of 114 cognitively healthy men and women aged 60 years and older. Brain volumes quantified by MRI were correlated with self-reported physical activity levels. The effect of the interaction between physical activity and the BDNF Val66Met polymorphism on brain structure volumes was assessed. Post hoc analyses were completed to evaluate the influence of the APOE ε4 allele on any found associations. RESULTS: The BDNF Val66Met polymorphism interacted with physical activity to be associated with hippocampal (β = -0.22, p = 0.02) and temporal lobe (β = -0.28, p = 0.003) volumes. In Val/Val homozygotes, higher levels of physical activity were associated with larger hippocampal and temporal lobe volumes, whereas in Met carriers, higher levels of physical activity were associated with smaller temporal lobe volume. CONCLUSION: The findings from this study support higher physical activity levels in the potential attenuation of age- and disease-related hippocampal and temporal lobe volume loss in Val/Val homozygotes.
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ItemA plasma protein classifier for predicting amyloid burden for preclinical Alzheimer's disease(AMER ASSOC ADVANCEMENT SCIENCE, 2019-02)A blood-based assessment of preclinical disease would have huge potential in the enrichment of participants for Alzheimer's disease (AD) therapeutic trials. In this study, cognitively unimpaired individuals from the AIBL and KARVIAH cohorts were defined as Aβ negative or Aβ positive by positron emission tomography. Nontargeted proteomic analysis that incorporated peptide fractionation and high-resolution mass spectrometry quantified relative protein abundances in plasma samples from all participants. A protein classifier model was trained to predict Aβ-positive participants using feature selection and machine learning in AIBL and independently assessed in KARVIAH. A 12-feature model for predicting Aβ-positive participants was established and demonstrated high accuracy (testing area under the receiver operator characteristic curve = 0.891, sensitivity = 0.78, and specificity = 0.77). This extensive plasma proteomic study has unbiasedly highlighted putative and novel candidates for AD pathology that should be further validated with automated methodologies.