Multi-omics profiling reveals dysregulated ribosome biogenesis and impaired cell proliferation following knockout of CDR2L.

BACKGROUND: Cerebellar degeneration-related (CDR) proteins are associated with paraneoplastic cerebellar degeneration (PCD) - a rare, neurodegenerative disease caused by tumour-induced autoimmunity against neural antigens resulting in degeneration of Purkinje neurons in the cerebellum. The pathogenesis of PCD is unknown, in large part due to our limited understanding of the functions of CDR proteins. To this end, we performed an extensive, multi-omics analysis of CDR-knockout cells focusing on the CDR2L protein, to gain a deeper understanding of the properties of the CDR proteins in ovarian cancer. METHODS: Ovarian cancer cell lines lacking either CDR1, CDR2, or CDR2L were analysed using RNA sequencing and mass spectrometry-based proteomics to assess changes to the transcriptome, proteome and secretome in the absence of these proteins. RESULTS: For each knockout cell line, we identified sets of differentially expressed genes and proteins. CDR2L-knockout cells displayed a distinct expression profile compared to CDR1- and CDR2-knockout cells. Knockout of CDR2L caused dysregulation of genes involved in ribosome biogenesis, protein translation, and cell cycle progression, ultimately causing impaired cell proliferation in vitro. Several of these genes showed a concurrent upregulation at the transcript level and downregulation at the protein level. CONCLUSIONS: Our study provides the first integrative multi-omics analysis of the impact of knockout of the CDR genes, providing both new insights into the biological properties of the CDR proteins in ovarian cancer, and a valuable resource for future investigations into the CDR proteins.

Differential transcript usage in the Parkinson's disease brain.

Studies of differential gene expression have identified several molecular signatures and pathways associated with Parkinson's disease (PD). The role of isoform switches and differential transcript usage (DTU) remains, however, unexplored. Here, we report the first genome-wide study of DTU in PD. We performed RNA sequencing following ribosomal RNA depletion in prefrontal cortex samples of 49 individuals from two independent case-control cohorts. DTU was assessed using two transcript-count based approaches, implemented in the DRIMSeq and DEXSeq tools. Multiple PD-associated DTU events were detected in each cohort, of which 23 DTU events in 19 genes replicated across both patient cohorts. For several of these, including THEM5, SLC16A1 and BCHE, DTU was predicted to have substantial functional consequences, such as altered subcellular localization or switching to non-protein coding isoforms. Furthermore, genes with PD-associated DTU were enriched in functional pathways previously linked to PD, including reactive oxygen species generation and protein homeostasis. Importantly, the vast majority of genes exhibiting DTU were not differentially expressed at the gene-level and were therefore not identified by conventional differential gene expression analysis. Our findings provide the first insight into the DTU landscape of PD and identify novel disease-associated genes. Moreover, we show that DTU may have important functional consequences in the PD brain, since it is predicted to alter the functional composition of the proteome. Based on these results, we propose that DTU analysis is an essential complement to differential gene expression studies in order to provide a more accurate and complete picture of disease-associated transcriptomic alterations.

The STRAT-PARK cohort: A personalized initiative to stratify Parkinson's disease.

The STRAT-PARK initiative aims to provide a platform for stratifying Parkinson's disease (PD) into biological subtypes, using a bottom-up, multidisciplinary biomarker-based and data-driven approach. PD is a heterogeneous entity, exhibiting high interindividual clinicopathological variability. This diversity suggests that PD may encompass multiple distinct biological entities, each driven by different molecular mechanisms. Molecular stratification and identification of disease subtypes is therefore a key priority for understanding and treating PD. STRAT-PARK is a multi-center longitudinal cohort aiming to recruit a total of 2000 individuals with PD and neurologically healthy controls from Norway and Canada, for the purpose of identifying molecular disease subtypes. Clinical assessment is performed annually, whereas biosampling, imaging, and digital and neurophysiological phenotyping occur every second year. The unique feature of STRAT-PARK is the diversity of collected biological material, including muscle biopsies and platelets, tissues particularly useful for mitochondrial biomarker research. Recruitment rate is ∼150 participants per year. By March 2023, 252 participants were included, comprising 204 cases and 48 controls. STRAT-PARK is a powerful stratification initiative anticipated to become a global research resource, contributing to personalized care in PD.

Altered transcriptome-proteome coupling indicates aberrant proteostasis in Parkinson's disease.

Aberrant proteostasis is thought to be implicated in Parkinson's disease (PD), but patient-derived evidence is scant. We hypothesized that impaired proteostasis is reflected as altered transcriptome-proteome correlation in the PD brain. We integrated transcriptomic and proteomic data from prefrontal cortex of PD patients and young and aged controls to assess RNA-protein correlations across samples. The aged brain showed a genome-wide decrease in mRNA-protein correlation. Genes encoding synaptic vesicle proteins showed negative correlations, likely reflecting spatial separation of mRNA and protein into soma and synapses. PD showed a broader transcriptome-proteome decoupling, consistent with a proteome-wide decline in proteostasis. Genes showing negative correlation in PD were enriched for proteasome subunits, indicating accentuated spatial separation of transcript and protein in PD neurons. In addition, PD showed positive correlations for mitochondrial respiratory chain genes, suggesting a tighter regulation in the face of mitochondrial dysfunction. Our results support the hypothesis that aberrant proteasomal function is implicated in PD pathogenesis.

Common gene expression signatures in Parkinson's disease are driven by changes in cell composition.

The etiology of Parkinson's disease is largely unknown. Genome-wide transcriptomic studies in bulk brain tissue have identified several molecular signatures associated with the disease. While these studies have the potential to shed light into the pathogenesis of Parkinson's disease, they are also limited by two major confounders: RNA post-mortem degradation and heterogeneous cell type composition of bulk tissue samples. We performed RNA sequencing following ribosomal RNA depletion in the prefrontal cortex of 49 individuals from two independent case-control cohorts. Using cell type specific markers, we estimated the cell type composition for each sample and included this in our analysis models to compensate for the variation in cell type proportions. Ribosomal RNA depletion followed by capture by random primers resulted in substantially more even transcript coverage, compared to poly(A) capture, in post-mortem tissue. Moreover, we show that cell type composition is a major confounder of differential gene expression analysis in the Parkinson's disease brain. Accounting for cell type proportions attenuated numerous transcriptomic signatures that have been previously associated with Parkinson's disease, including vesicle trafficking, synaptic transmission, immune and mitochondrial function. Conversely, pathways related to endoplasmic reticulum, lipid oxidation and unfolded protein response were strengthened and surface as the top differential gene expression signatures in the Parkinson's disease prefrontal cortex. Our results indicate that differential gene expression signatures in Parkinson's disease bulk brain tissue are significantly confounded by underlying differences in cell type composition. Modeling cell type heterogeneity is crucial in order to unveil transcriptomic signatures that represent regulatory changes in the Parkinson's disease brain and are, therefore, more likely to be associated with underlying disease mechanisms.