Medicine (Austin & Northern Health) - Research Publications

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    Fifteen 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
    Fowler, C ; Rainey-Smith, SR ; Bird, S ; Bomke, J ; Bourgeat, P ; Brown, BM ; Burnham, SC ; Bush, A ; Chadunow, C ; Collins, S ; Doecke, J ; Dore, V ; Ellis, KA ; Evered, L ; Fazlollahi, A ; Fripp, J ; Gardener, SL ; Gibson, S ; Grenfell, R ; Harrison, E ; Head, R ; Jin, L ; Kamer, A ; Lamb, F ; Lautenschlager, NT ; Laws, SM ; Li, Q-X ; Lim, L ; Lim, YY ; Louey, A ; Macaulay, SL ; Mackintosh, L ; Martins, RN ; Maruff, P ; Masters, CL ; McBride, S ; Milicic, L ; Peretti, M ; Pertile, K ; Porter, T ; Radler, M ; Rembach, A ; Robertson, J ; Rodrigues, M ; Rowe, CC ; Rumble, R ; Salvado, O ; Savage, G ; Silbert, B ; Soh, M ; Sohrabi, HR ; Taddei, K ; Taddei, T ; Thai, C ; Trounson, B ; Tyrrell, R ; Vacher, M ; Varghese, S ; Villemagne, VL ; Weinborn, M ; Woodward, M ; Xia, Y ; Ames, D (IOS PRESS, 2021-01-01)
    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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    Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer's disease
    Huynh, K ; Lim, WLF ; Giles, C ; Jayawardana, KS ; Salim, A ; Mellett, NA ; Smith, AAT ; Olshansky, G ; Drew, BG ; Chatterjee, P ; Martins, I ; Laws, SM ; Bush, AI ; Rowe, CC ; Villemagne, VL ; Ames, D ; Masters, CL ; Arnold, M ; Nho, K ; Saykin, AJ ; Baillie, R ; Han, X ; Kaddurah-Daouk, R ; Martins, RN ; Meikle, PJ (NATURE RESEARCH, 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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    Risk prediction of late-onset Alzheimer's disease implies an oligogenic architecture
    Zhang, Q ; Sidorenko, J ; Couvy-Duchesne, B ; Marioni, RE ; Wright, MJ ; Goate, AM ; Marcora, E ; Huang, K-L ; Porter, T ; Laws, SM ; Sachdev, PS ; Mather, KA ; Armstrong, NJ ; Thalamuthu, A ; Brodaty, H ; Yengo, L ; Yang, J ; Wray, NR ; McRae, AF ; Visscher, PM (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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    Plasma High Density Lipoprotein Small Subclass is Reduced in Alzheimer's Disease Patients and Correlates with Cognitive Performance
    Pedrini, S ; Hone, E ; Gupta, VB ; James, I ; Teimouri, E ; Bush, A ; Rowe, CC ; Villemagne, VL ; Ames, D ; Masters, CL ; Rainey-Smith, S ; Verdile, G ; Sohrabi, HR ; Raida, MR ; Wenk, MR ; Taddei, K ; Chatterjee, P ; Martins, I ; Laws, SM ; Martins, RN ; Pasinetti, G (IOS PRESS, 2020-01-01)
    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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    Relationships Between Plasma Lipids Species, Gender, Risk Factors, and Alzheimer's Disease
    Lim, WLF ; Huynh, K ; Chatterjee, P ; Martins, I ; Jayawardana, KS ; Giles, C ; Mellett, NA ; Laws, SM ; Bush, AI ; Rowe, CC ; Villemagne, VL ; Ames, D ; Drew, BG ; Masters, CL ; Meikle, PJ ; Martins, RN ; Götz, J (IOS PRESS, 2020-01-01)
    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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    Cerebrospinal fluid neurofilament light concentration predicts brain atrophy and cognition in Alzheimer's disease
    Dhiman, K ; Gupta, VB ; Villemagne, VL ; Eratne, D ; Graham, PL ; Fowler, C ; Bourgeat, P ; Li, Q-X ; Collins, S ; Bush, A ; Rowe, CC ; Masters, CL ; Ames, D ; Hone, E ; Blennow, K ; Zetterberg, H ; Martins, RN (WILEY, 2020-01-01)
    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.