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GNPS - Multi-omics Evaluation of Human iPSCs and iPSC-derived Neurons

ABSTRACT: The granulin (GRN) gene stands out as a prominent player in frontotemporal degeneration (FTD). Progranulin (PGRN) is a protein encoded by the GRN gene. Mutations in the GRN gene leading to PGRN deficiency are associated with lysosomal storage diseases and various neurodegenerative diseases. Despite the significance of GRN function, the specific impact of GRN-/- condition on diverse biomolecules such as proteins, lipids, and metabolites remain unclear. This study employs a multi-omics approach, integrating proteomics, lipidomics, and metabolomics analyses for comprehensively unraveling the molecular alterations by GRN-/- condition. Proteins, lipids, and metabolites were obtained from the same sample using a single extraction method. Our result reveals distinct molecular profiles between iPSC and neurons, emphasizing upregulated synaptic proteins such as SYN1, SYT1, VAMP2, and SV2A in proteomics, decreased cardiolipin (CL) containing 16:0 and 18:1 acyl chain in lipidomics, and shifts in acetylcholine and amino acid in metabolomics. Furthermore, the GRN-/- condition induces significant alterations across the proteome, lipidome, and metabolome of induced pluripotent stem cells (iPSC) and iPSC-derived neurons, unveiling unique metabolic pathways. Although this study was conducted at a whole cell level, this comprehensive perspective contributes to our understanding of the intricate interplay among proteins, lipids, and metabolites in neurodevelopment and neurodegenerative diseases.

INSTRUMENT(S): Q Exactive HF-X

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Ling Hao

PROVIDER: MSV000093388 | GNPS | Mon Nov 13 16:17:00 GMT 2023

REPOSITORIES: GNPS

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Project description:Parkinson disease (PD) is a neurodegenerative disease characterized by the accumulation of alpha-synuclein (SNCA) and other proteins in aggregates termed âLewy Bodiesâ within neurons. PD has both genetic and environmental risk factors, and while processes leading to aberrant protein aggregation are unknown, past work points to abnormal levels of SNCA and other proteins. Although several genome-wide studies have been performed for PD, these have focused on DNA sequence variants by genome-wide association studies (GWAS) and on RNA levels (microarray transcriptomics), while genome-wide proteomics analysis has been lacking. After appropriate filters, proteomics identified 3,558 unique proteins and 283 of these (7.9%) were significantly different between PD and controls (q-value<0.05). RNA-sequencing identified 17,580 protein-coding genes and 1,095 of these (6.2%) were significantly different (FDR p-value<0.05), but only 166 of the FDR significant protein-coding genes (0.94%) were present among the 3,558 proteins characterized. Of these 166, eight genes (4.8%) were significant in both studies, with the same direction of effect. Functional enrichment analysis of the proteomics results strongly supports mitochondrial-related pathways, while comparable analysis of the RNA-sequencing results implicates protein folding pathways and metallothioneins. Ten of the implicated genes or proteins co-localized to GWAS loci. Evidence implicating SNCA was stronger in proteomics than in RNA-sequencing analyses. Notably, differentially expressed protein-coding genes were more likely to not be characterized in the proteomics analysis, which lessens the ability to compare across platforms. Combining multiple genome-wide platforms offers novel insights into the pathological processes responsible for this disease by identifying pathways implicated across methodologies. The study consists of mRNA-Seq (29 PD, 44 neurologically normal controls) and three-stage Mass Spectrometry Tandem Mass Tag Proteomics (12 PD, 12 neurologically normal controls) performed in post-mortem BA9 brain tissue. The proteomics samples are a subset of the RNA-Seq samples.

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GNPS - Multi-omics Evaluation of Human iPSCs and iPSC-derived Neurons

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