Browsing by Author "Wang, Tingting"

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    Asparagine restriction enhances CD8+ T cell metabolic fitness and antitumoral functionality through an NRF2-dependent stress response
    (Springer Nature, 2023) Gnanaprakasam, J. N. Rashida; Kushwaha, Bhavana; Liu, Lingling; Chen, Xuyong; Kang, Siwen; Wang, Tingting; Cassel, Teresa A.; Adams, Christopher M.; Higashi, Richard M.; Scott, David A.; Xin, Gang; Li, Zihai; Yang, Jun; Lane, Andrew N.; Fan, Teresa W. M.; Zhang, Ji; Wang, Ruoning; Pediatrics, School of Medicine
    Robust and effective T cell immune surveillance and cancer immunotherapy require proper allocation of metabolic resources to sustain energetically costly processes, including growth and cytokine production. Here, we show that asparagine (Asn) restriction on CD8+ T cells exerted opposing effects during activation (early phase) and differentiation (late phase) following T cell activation. Asn restriction suppressed activation and cell cycle entry in the early phase while rapidly engaging the nuclear factor erythroid 2-related factor 2 (NRF2)-dependent stress response, conferring robust proliferation and effector function on CD8+ T cells during differentiation. Mechanistically, NRF2 activation in CD8+ T cells conferred by Asn restriction rewired the metabolic program by reducing the overall glucose and glutamine consumption but increasing intracellular nucleotides to promote proliferation. Accordingly, Asn restriction or NRF2 activation potentiated the T cell-mediated antitumoral response in preclinical animal models, suggesting that Asn restriction is a promising and clinically relevant strategy to enhance cancer immunotherapy. Our study revealed Asn as a critical metabolic node in directing the stress signaling to shape T cell metabolic fitness and effector functions.
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    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.