Browsing by Author "Giles, Corey"

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    APOE ε2 resilience for Alzheimer's disease is mediated by plasma lipid species: Analysis of three independent cohort studies
    (Wiley, 2022) Wang, Tingting; Huynh, Kevin; Giles, Corey; Mellett, Natalie A.; Duong, Thy; Nguyen, Anh; Lim, Wei Ling Florence; Smith, Alex At; Olshansky, Gavriel; Cadby, Gemma; Hung, Joseph; Hui, Jennie; Beilby, John; Watts, Gerald F.; Chatterjee, Pratishtha; Martins, Ian; Laws, Simon M.; Bush, Ashley I.; Rowe, Christopher C.; Villemagne, Victor L.; Ames, David; Masters, Colin L.; Taddei, Kevin; Doré, Vincent; Fripp, Jürgen; Arnold, Matthias; Kastenmüller, Gabi; Nho, Kwangsik; Saykin, Andrew J.; Baillie, Rebecca; Han, Xianlin; Martins, Ralph N.; Moses, Eric K.; Kaddurah-Daouk, Rima; Meikle, Peter J.; Radiology and Imaging Sciences, School of Medicine
    Introduction: The apolipoprotein E (APOE) genotype is the strongest genetic risk factor for late-onset Alzheimer's disease. However, its effect on lipid metabolic pathways, and their mediating effect on disease risk, is poorly understood. Methods: We performed lipidomic analysis on three independent cohorts (the Australian Imaging, Biomarkers and Lifestyle [AIBL] flagship study, n = 1087; the Alzheimer's Disease Neuroimaging Initiative [ADNI] 1 study, n = 819; and the Busselton Health Study [BHS], n = 4384), and we defined associations between APOE ε2 and ε4 and 569 plasma/serum lipid species. Mediation analysis defined the proportion of the treatment effect of the APOE genotype mediated by plasma/serum lipid species. Results: A total of 237 and 104 lipid species were associated with APOE ε2 and ε4, respectively. Of these 68 (ε2) and 24 (ε4) were associated with prevalent Alzheimer's disease. Individual lipid species or lipidomic models of APOE genotypes mediated up to 30% and 10% of APOE ε2 and ε4 treatment effect, respectively. Discussion: Plasma lipid species mediate the treatment effect of APOE genotypes on Alzheimer's disease and as such represent a potential therapeutic target.
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    Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data
    (Elsevier, 2023) Jo, Taeho; Kim, Junpyo; Bice, Paula; Huynh, Kevin; Wang, Tingting; Arnold, Matthias; Meikle, Peter J.; Giles, Corey; Kaddurah-Daouk, Rima; Saykin, Andrew J.; Nho, Kwangsik; Alzheimer’s Disease Metabolomics Consortium (ADMC); Alzheimer’s Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of Medicine
    Background: Deep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics. Methods: The c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification. Findings: The application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6). Interpretation: Our results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation.
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    Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease
    (Springer Nature, 2022-06-06) Cadby, Gemma; Giles, Corey; Melton, Phillip E.; Huynh, Kevin; Mellett, Natalie A.; Duong, Thy; Nguyen, Anh; Cinel, Michelle; Smith, Alex; Olshansky, Gavriel; Wang, Tingting; Brozynska, Marta; Inouye, Mike; McCarthy, Nina S.; Ariff, Amir; Hung, Joseph; Hui, Jennie; Beilby, John; Dubé, Marie-Pierre; Watts, Gerald F.; Shah, Sonia; Wray, Naomi R.; Lim, Wei Ling Florence; Chatterjee, Pratishtha; Martins, Ian; Laws, Simon M.; Porter, Tenielle; Vacher, Michael; Bush, Ashley I.; Rowe, Christopher C.; Villemagne, Victor L.; Ames, David; Masters, Colin L.; Taddei, Kevin; Arnold, Matthias; Kastenmüller, Gabi; Nho, Kwangsik; Saykin, Andrew J.; Han, Xianlin; Kaddurah-Daouk, Rima; Martins, Ralph N.; Blangero, John; Meikle, Peter J.; Moses, Eric K.; Radiology and Imaging Sciences, School of Medicine
    We integrated lipidomics and genomics to unravel the genetic architecture of lipid metabolism and identify genetic variants associated with lipid species putatively in the mechanistic pathway for coronary artery disease (CAD). We quantified 596 lipid species in serum from 4,492 individuals from the Busselton Health Study. The discovery GWAS identified 3,361 independent lipid-loci associations, involving 667 genomic regions (479 previously unreported), with validation in two independent cohorts. A meta-analysis revealed an additional 70 independent genomic regions associated with lipid species. We identified 134 lipid endophenotypes for CAD associated with 186 genomic loci. Associations between independent lipid-loci with coronary atherosclerosis were assessed in ∼456,000 individuals from the UK Biobank. Of the 53 lipid-loci that showed evidence of association (P < 1 × 10-3), 43 loci were associated with at least one lipid endophenotype. These findings illustrate the value of integrative biology to investigate the aetiology of atherosclerosis and CAD, with implications for other complex diseases.
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    Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer’s disease
    (Nature, 2020-11-10) Huynh, Kevin; Lim, Wei Ling Florence; Giles, Corey; Jayawardana, Kaushala S.; Salim, Agus; Mellett, Natalie A.; Smith, Adam Alexander T.; Olshansky, Gavriel; Drew, Brian G.; Chatterjee, Pratishtha; Martins, Ian; Laws, Simon M.; Bush, Ashley I.; Rowe, Christopher C.; Villemagne, Victor L.; Ames, David; Masters, Colin L.; Arnold, Matthias; Nho, Kwangsik; Saykin, Andrew J.; Baillie, Rebecca; Han, Xianlin; Kaddurah-Daouk, Rima; Martins, Ralph N.; Meikle, Peter J.; BioHealth Informatics, School of Informatics and Computing
    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., The onset and pathology of Alzheimer’s disease (AD) is associated with changes to lipid metabolism. Here, the authors analysed 569 lipids from 32 classes and subclasses in two independent patient cohorts to identify key lipid pathways to link the plasma lipidome with AD and the future onset of AD.