Exploratory Analysis of IPSCS-Derived Neuronal Cells As Predictors of Diagnosis and Treatment of Alzheimer Disease

Overview

Journal Brain Sci

Publisher MDPI

Date 2020 Mar 19

PMID 32183090

Citations 11

Authors

Eugenio Cavalli

Giuseppe Battaglia

Maria Sofia Basile

Valeria Bruno

Maria Cristina Petralia

Salvo Danilo Lombardo

Manuela Pennisi

Reni Kalfin

Lyubka Tancheva

Paolo Fagone

Ferdinando Nicoletti

Katia Mangano

Affiliations

Soon will be listed here.

Abstract

Alzheimer's disease (AD) represents the most common neurodegenerative disorder, with 47 million affected people worldwide. Current treatment strategies are aimed at reducing the symptoms and do slow down the progression of the disease, but inevitably fail in the long-term. Induced pluripotent stem cells (iPSCs)-derived neuronal cells from AD patients have proven to be a reliable model for AD pathogenesis. Here, we have conducted an in silico analysis aimed at identifying pathogenic gene-expression profiles and novel drug candidates. The GSE117589 microarray dataset was used for the identification of Differentially Expressed Genes (DEGs) between iPSC-derived neuronal progenitor (NP) cells and neurons from AD patients and healthy donors. The Discriminant Analysis Module (DAM) algorithm was used for the identification of biomarkers of disease. Drugs with anti-signature gene perturbation profiles were identified using the L1000FWD software. DAM analysis was used to identify a list of potential biomarkers among the DEGs, able to discriminate AD patients from healthy people. Finally, anti-signature perturbation analysis identified potential anti-AD drugs. This study set the basis for the investigation of potential novel pharmacological strategies for AD. Furthermore, a subset of genes for the early diagnosis of AD is proposed.

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