Transcriptomics,Genomics

Dataset Information

19

Gene expression from iPS derived neurons exposed to plasma from Alzheimer's (AD), pre-symptomatic AD, or control patients.


ABSTRACT: We have established proof of principle for the Indicator Cell Assay Platformé (iCAPé), a broadly applicable tool for blood-based diagnostics that uses specifically-selected, standardized cells as biosensors, relying on their innate ability to integrate and respond to diverse signals present in patientsÕ blood. To develop an assay, indicator cells are exposed in vitro to serum from case or control subjects and their global differential response patterns are used to train reliable, cost-effective disease classifiers based on a small number of features. In a feasibility study, the iCAP detected pre-symptomatic disease in a murine model of amyotrophic lateral sclerosis (ALS) with 94% accuracy (p-Value=3.81E-6) and correctly identified samples from a murine HuntingtonÕs disease model as non-carriers of ALS. In a preliminary human disease assay, the iCAP detected early stage AlzheimerÕs disease with 72% cross-validated accuracy (p-Value=3.10E-3). For both assays, iCAP features were enriched for disease-related genes, supporting the assayÕs relevance for disease research. Overall design: 18 assays from Alzheimer's patients, 20 assays each from pre-symptomatic Alzheimer's and control patients

INSTRUMENT(S): [HuEx-1_0-st] Affymetrix Human Exon 1.0 ST Array [gene-level release 33.1 version]

SUBMITTER: G. Adam Whitney 

PROVIDER: GSE95810 | GEO | 2017-03-17

SECONDARY ACCESSION(S): PRJNA378494

REPOSITORIES: GEO

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We have established proof of principle for the Indicator Cell Assay Platform™ (iCAP™), a broadly applicable tool for blood-based diagnostics that uses specifically-selected, standardized cells as biosensors, relying on their innate ability to integrate and respond to diverse signals present in patients' blood. To develop an assay, indicator cells are exposed in vitro to serum from case or control subjects and their global differential response patterns are used to train reliable, disease classif  ...[more]

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