Contributions
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Accolades
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Team Khurana
Molecular, cellular and clinical fingerprinting of established pesticide toxicants in three PD cohorts.
Mechanisms linking exposures to PD risk remain unclear. Here, we will integrate quantitative epidemiological and metabolomic data with unique human stem-cell, alpha-synuclein (ɑS) biomarker and AI toolboxes. We will generate the first molecular and cellular “fingerprints” for PD-relevant pesticides, focusing on ɑS, membrane and inflammatory pathologies. Our study will also be the first to perform integrative analyses of three separate longitudinal PD cohorts (PEG, HBS, PPMI). Finally, our PD customized foundation AI model will shed light on whether and how specific pesticide exposures delineate new PD molecular and clinical subtypes with significant implications for targeted therapeutics.
Tags
Alpha-synucleinArtificial intelligenceComputer modelingDisease modelsEnvironmental toxinsExosomesGene-environment interactionsiPSC neuronsiPSCs (Induced pluripotent stem cells)Machine learningPesticidesSeeding assays
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