Multi-omics integration of scRNA-seq time series data predicts new intervention points for Parkinson's disease

• Published in: Scientific reports Vol. 14; no. 1; p. 10983
• Main Authors: Mihajlović, Katarina, Ceddia, Gaia, Malod-Dognin, Noël, Novak, Gabriela, Kyriakis, Dimitrios, Skupin, Alexander, Pržulj, Nataša
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 14.05.2024; Nature Publishing Group UK; Nature Portfolio
• Subjects: Cell differentiation; Cell Differentiation - genetics; Clustering; Data analysis; Datasets; Disease; Dopamine receptors; Dopaminergic Neurons - metabolism; Dopaminergic Neurons - pathology; Encyclopaedias; Gene Regulatory Networks; Genes; Genomes; Humans; Induced Pluripotent Stem Cells - metabolism; Mesencephalon; Mesencephalon - metabolism; Mesencephalon - pathology; Metabolism; Methods; Molecular modelling; Movement disorders; Multiomics; Mutation; Neurodegenerative diseases; Neurons; Parkinson Disease - genetics; Parkinson Disease - pathology; Parkinson's disease; Pluripotency; Proteins; PTEN-induced putative kinase; RNA-Seq - methods; Single-Cell Gene Expression Analysis; Stem cells; Therapeutic targets; Time series
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-61844-3

Parkinson's disease (PD) is a complex neurodegenerative disorder without a cure. The onset of PD symptoms corresponds to 50% loss of midbrain dopaminergic (mDA) neurons, limiting early-stage understanding of PD. To shed light on early PD development, we study time series scRNA-seq datasets of mDA neurons obtained from patient-derived induced pluripotent stem cell differentiation. We develop a new data integration method based on Non-negative Matrix Tri-Factorization that integrates these datasets with molecular interaction networks, producing condition-specific "gene embeddings". By mining these embeddings, we predict 193 PD-related genes that are largely supported (49.7%) in the literature and are specific to the investigated PINK1 mutation. Enrichment analysis in Kyoto Encyclopedia of Genes and Genomes pathways highlights 10 PD-related molecular mechanisms perturbed during early PD development. Finally, investigating the top 20 prioritized genes reveals 12 previously unrecognized genes associated with PD that represent interesting drug targets.