Claudia Carvallo, PhD| Centro de investigación e innovación en Gerontología Aplicada ; Max Chacón, PhD; Felipe Bello, PhD; Andrés Ledezma, PhD; Javier Palma, MS
Competition Sponsor: Chile Agencia Nacional de Investigacion y Desarrollo
Awardee Year: 2022
There is one diagnosis of dementia every three seconds worldwide and by 2030, the cost in dementia care will increase up to USD$2 trillion. Risk factors such as metabolic syndrome (MetS) are associated with the progression of dementia where insulin resistance, diabetes and obesity correlate with mild cognitive impairment and progression to Alzheimer’s, by accumulation of β-amyloid and increased in tau phosphorylation. However, it remains unclear which specific proteins may play relevant roles in these pathophysiological processes. The use of proteomic data can be an efficient solution to improve public health standards in neurodegenerative diseases. The evolution of metabolic risk factors is expected to induce differential changes in these proteins, thus becoming potential and effective biomarkers of dementia. Our goal is the design of Aging MetS Platform, a tool that integrates data-based models through computational intelligence techniques and proteomics, enabling visualization of correlations between MetS and dementia in aging. This will allow the finding of recurrent patterns, biomarkers and predicting the evolution of risk factors associated with metabolism and early detection of some types of dementia, adding value to the clinical data of patients. This opens new opportunities for transformation and innovation of public health policies in dementia.
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