09 November 2020 1 7K Report

Can the potential of plasma LIPIDMICS improve the diagnosis and understanding of metabolic changes in various neurodegenerative diseases (Parkinson’s disease, Huntington’s disease, Mutiple Sclerosis, Alzheimer’s disease etc) ?

RELEVANCE TO NUTRITIONAL TREATMENT ON BRAIN SENESCENCE, AGEING SCIENCE AND GLOBAL NEURODEGENERATIVE DISEASE

We have performed one of the most comprehensive lipidomic analysis of AD to date by utilising two large, independent clinical studies in AD. We have provided a holistic picture of lipid dysregulation associated with both prevalent and incident AD. Our plasma lipid dataset expands the scientific literature by providing greater resolution and allowing fine-granular analysis of the lipidome. Here we have highlighted specific changes to the ether lipid pathway, where plasmalogens are not the only drivers of ether lipid associations. Class-wide and species-specific changes highlight the necessity of a broad and detailed assay to capture these minute differences in the lipidome. We have demonstrated the potential of plasma lipids as the markers to improve assessment of prevalent and incident AD, highlighting the importance of these small molecules in both disease prognostics and understanding the metabolic changes occurring with the disease.

RELEVANT REFERENCES:

1. Kevin Huynh et al. Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer’s disease. Nature Communications. 2020.

2. Nutritional and Genotoxic Stress Contributes to Diabetes and Neurodegenerative Diseases such as Parkinson's and Alzheimer's Diseases. - Frontiers in Clinical Drug Research -CNS and Neurological Disorders. Volume 3 Editor: Atta-ur-Rahman Pp. 158-192 (35) 2015

3. Anti-Aging Genes Improve Appetite Regulation and Reverse Cell Senescence and Apoptosis in Global Populations. Advances in Aging Research, 2016, 5, 9-26.

4. Early diagnosis of neuron mitochondrial dysfunction may reverse global metabolic and neurodegenerative disease. Global Journal of Medical Research. 2016;2: 1-8.

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