ORCID Profile
0000-0002-5122-5547
Current Organisation
Baker IDI Heart and Diabetes Institute
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Publisher: Springer Science and Business Media LLC
Date: 07-10-2023
Publisher: Cold Spring Harbor Laboratory
Date: 28-05-2020
DOI: 10.1101/2020.05.26.20114215
Abstract: Changes to lipid metabolism are tightly associated with the onset and pathology of Alzheimer’s disease (AD). Lipids are complex molecules comprising of many isomeric and isobaric species, necessitating detailed analysis to enable interpretation of biological significance. Our expanded targeted lipidomics platform (569 lipid species across 32 lipid (sub)classes) allows for detailed isomeric and isobaric lipid separation. We applied the methodology to examine plasma s les from the Australian Imaging, Biomarkers and Lifestyle flagship study of aging (AIBL, n = 1112) and serum from the Alzheimer’s Disease Neuroimaging Initiative (ADNI, n = 800) studies. Cross sectional analysis using both cohorts identified concordant unique peripheral signatures associated with AD. Specific pathways include sphingolipids, including G M3 gangliosides, where their acyl composition drove the major associations, and lipids previously associated with dysfunctional lipid metabolism in cardiometabolic disease including the phosphatidylethanolamine and triglyceride classes. Infomation derived from improved isomeric seperation highlighted pathway-specific changes with ether lipids including plasmalogens implicating perixosmal dysfunction in disease pathology. Longitudinal analysis revealed similar lipid signitures in both AIBL and ADNI cohorts with future disease onset. We utilised the two independent studies to train and validate multivariate lipid models that significantly improved disease classification and prediction. Together our results provide a holistic view of the lipidome and its relationship with AD using a comprehensive lipidomics approach, providing targets for further mechanistic investigation.
Publisher: Research Square Platform LLC
Date: 21-04-2023
DOI: 10.21203/RS.3.RS-2809465/V1
Abstract: Obesity is a risk factor for type 2 diabetes and cardiovascular disease. However, a substantial proportion of patients with these conditions have a seemingly normal body mass index (BMI). Conversely, not all obese in iduals present with metabolic disorders giving rise to the concept of “metabolically healthy obese”. Using comprehensive lipidomic datasets from two large independent population cohorts in Australia (n = 14,831), we developed models that predicted BMI and calculated a metabolic BMI score (mBMI) as a measure of metabolic dysregulation associated with obesity. We postulated that the mBMI score would be an independent metric for defining obesity and help identify a hidden risk for metabolic disorders regardless of the measured BMI. Based on the difference between mBMI and BMI (mBMI delta “mBMIΔ”), we identified in iduals with a similar BMI but differing in their metabolic health profiles. Participants in the top quintile of mBMIΔ (Q5) were more than four times more likely to be newly diagnosed with T2DM (OR = 4.5 95% CI = 3.1–6.6), more than two times more likely to develop T2DM over a five year follow up period (OR = 2.5 CI = 1.5–4.1) and had higher odds of cardiovascular disease (heart attack or stroke) (OR = 2.1 95% CI = 1.5–3.1) relative to those in the bottom quintile (Q1). Exercise and diet were associated with mBMIΔ suggesting the ability to modify mBMI with lifestyle intervention. In conclusion, our findings show that, the mBMI score captures information on metabolic dysregulation that is independent of the measured BMI and so provides an opportunity to assess metabolic health to identify in iduals at risk for targeted intervention and monitoring.
Publisher: Springer Science and Business Media LLC
Date: 06-06-2022
DOI: 10.1038/S41467-022-30875-7
Abstract: 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 in iduals 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 in iduals 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.
Publisher: Public Library of Science (PLoS)
Date: 28-09-2020
No related grants have been discovered for Gavriel Olshansky.