Browsing by Author "Huynh, Kevin"

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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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    Circulating lipid profiles are associated with cross-sectional and longitudinal changes of central biomarkers for Alzheimer's disease
    (medRxiv, 2023-06-21) Kim, Jun Pyo; Nho, Kwangsik; Wang, Tingting; Huynh, Kevin; Arnold, Matthias; Risacher, Shannon L.; Bice, Paula J.; Han, Xianlin; Kristal, Bruce S.; Blach, Colette; Baillie, Rebecca; Kastenmüller, Gabi; Meikle, Peter J.; Saykin, Andrew J.; Kaddurah-Daouk, Rima; Alzheimer’s Disease Neuroimaging Initiative; Alzheimer’s Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of Medicine
    Investigating the association of lipidome profiles with central Alzheimer's disease (AD) biomarkers, including amyloid/tau/neurodegeneration (A/T/N), can provide a holistic view between the lipidome and AD. We performed cross-sectional and longitudinal association analysis of serum lipidome profiles with AD biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort (N=1,395). We identified lipid species, classes, and network modules that were significantly associated with cross-sectional and longitudinal changes of A/T/N biomarkers for AD. Notably, we identified the lysoalkylphosphatidylcholine (LPC(O)) as associated with "A/N" biomarkers at baseline at lipid species, class, and module levels. Also, GM3 ganglioside showed significant association with baseline levels and longitudinal changes of the "N" biomarkers at species and class levels. Our study of circulating lipids and central AD biomarkers enabled identification of lipids that play potential roles in the cascade of AD pathogenesis. Our results suggest dysregulation of lipid metabolic pathways as precursors to AD development and progression.
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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.
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    Multi-Omic analyses characterize the ceramide/sphingomyelin pathway as a therapeutic target in Alzheimer's disease
    (Springer Nature, 2022-10-08) Baloni, Priyanka; Arnold, Matthias; Buitrago, Luna; Nho, Kwangsik; Moreno, Herman; Huynh, Kevin; Brauner, Barbara; Louie, Gregory; Kueider-Paisley, Alexandra; Suhre, Karsten; Saykin, Andrew J.; Ekroos, Kim; Meikle, Peter J.; Hood, Leroy; Price, Nathan D.; The Alzheimer’s Disease Metabolomics Consortium; Doraiswamy, P. Murali; Funk, Cory C.; Hernández, A. Iván; Kastenmüller, Gabi; Baillie, Rebecca; Han, Xianlin; Kaddurah-Daouk, Rima; Radiology and Imaging Sciences, School of Medicine
    Dysregulation of sphingomyelin and ceramide metabolism have been implicated in Alzheimer's disease. Genome-wide and transcriptome-wide association studies have identified various genes and genetic variants in lipid metabolism that are associated with Alzheimer's disease. However, the molecular mechanisms of sphingomyelin and ceramide disruption remain to be determined. We focus on the sphingolipid pathway and carry out multi-omics analyses to identify central and peripheral metabolic changes in Alzheimer's patients, correlating them to imaging features. Our multi-omics approach is based on (a) 2114 human post-mortem brain transcriptomics to identify differentially expressed genes; (b) in silico metabolic flux analysis on context-specific metabolic networks identified differential reaction fluxes; (c) multimodal neuroimaging analysis on 1576 participants to associate genetic variants in sphingomyelin pathway with Alzheimer's disease pathogenesis; (d) plasma metabolomic and lipidomic analysis to identify associations of lipid species with dysregulation in Alzheimer's; and (e) metabolite genome-wide association studies to define receptors within the pathway as a potential drug target. We validate our hypothesis in amyloidogenic APP/PS1 mice and show prolonged exposure to fingolimod alleviated synaptic plasticity and cognitive impairment in mice. Our integrative multi-omics approach identifies potential targets in the sphingomyelin pathway and suggests modulators of S1P metabolism as possible candidates for Alzheimer's disease treatment.
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    Peripheral inflammation is associated with brain atrophy and cognitive decline linked to mild cognitive impairment and Alzheimer's disease
    (Springer Nature, 2024-07-29) Liang, Nuanyi; Nho, Kwangsik; Newman, John W.; Arnold, Matthias; Huynh, Kevin; Meikle, Peter J.; Borkowski, Kamil; Kaddurah‑Daouk, Rima; Alzheimer’s Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of Medicine
    Inflammation is an important factor in Alzheimer’s disease (AD). An NMR measurement in plasma, glycoprotein acetyls (GlycA), captures the overall level of protein production and glycosylation implicated in systemic inflammation. With its additional advantage of reducing biological variability, GlycA might be useful in monitoring the relationship between peripheral inflammation and brain changes relevant to AD. However, the associations between GlycA and these brain changes have not been fully evaluated. Here, we performed Spearman’s correlation analyses to evaluate these associations cross-sectionally and determined whether GlycA can inform AD-relevant longitudinal measurements among participants in the Alzheimer’s Disease Neuroimaging Initiative (n = 1506), with additional linear models and stratification analyses to evaluate the influences of sex or diagnosis status and confirm findings from Spearman’s correlation analyses. We found that GlycA was elevated in AD patients compared to cognitively normal participants. GlycA correlated negatively with multiple concurrent regional brain volumes in females diagnosed with late mild cognitive impairment (LMCI) or AD. Baseline GlycA level was associated with executive function decline at 3–9 year follow-up in participants diagnosed with LMCI at baseline, with similar but not identical trends observed in the future decline of memory and entorhinal cortex volume. Results here indicated that GlycA is an inflammatory biomarker relevant to AD pathogenesis and that the stage of LMCI might be relevant to inflammation-related intervention.
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    Sex and APOE ε4 genotype modify the Alzheimer’s disease serum metabolome
    (Springer Nature, 2020) Arnold, Matthias; Nho, Kwangsik; Kueider-Paisley, Alexandra; Massaro, Tyler; Huynh, Kevin; Brauner, Barbara; MahmoudianDehkordi, Siamak; Louie, Gregory; Moseley, M. Arthur; Thompson, J. Will; St. John-Williams, Lisa; Tenenbaum, Jessica D.; Blach, Colette; Chang, Rui; Brinton, Roberta D.; Baillie, Rebecca; Han, Xianlin; Trojanowski, John Q.; Shaw, Leslie M.; Martins, Ralph; Weiner, Michael W.; Trushina, Trushina; Toledo, Jon B.; Meikle, Peter J.; Bennett, David A.; Krumsiek, Jan; Doraiswamy, P. Murali; Saykin, Andrew J.; Kaddurah-Daouk, Rima; Kastenmüller, Gabi; Radiology and Imaging Sciences, School of Medicine
    Late-onset Alzheimer’s disease (AD) can, in part, be considered a metabolic disease. Besides age, female sex and APOE ε4 genotype represent strong risk factors for AD that also give rise to large metabolic differences. We systematically investigated group-specific metabolic alterations by conducting stratified association analyses of 139 serum metabolites in 1,517 individuals from the AD Neuroimaging Initiative with AD biomarkers. We observed substantial sex differences in effects of 15 metabolites with partially overlapping differences for APOE ε4 status groups. Several group-specific metabolic alterations were not observed in unstratified analyses using sex and APOE ε4 as covariates. Combined stratification revealed further subgroup-specific metabolic effects limited to APOE ε4+ females. The observed metabolic alterations suggest that females experience greater impairment of mitochondrial energy production than males. Dissecting metabolic heterogeneity in AD pathogenesis can therefore enable grading the biomedical relevance for specific pathways within specific subgroups, guiding the way to personalized medicine.