Crucial Roles of Ubiquitin Carboxy-Terminal Hydrolase L1 in Motor Neuronal Health by Drosophila Model

Single-cell multiomics analysis reveals cell/tissue-specific associations in bipolar disorder

This study investigates the cellular origin and tissue heterogeneity in bipolar disorder (BD) by integrating multiomics data. Four distinct datasets were employed, including single-cell RNA sequencing (scRNA-seq) data (embryonic and fetal brain, n = 8, 1,266 cells), BD Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data (adult brain, n = 210), BD bulk RNA-seq data (adult brain, n = 314), and BD genome-wide association study (GWAS) summary data (n = 413,466). The integration of scRNA-seq data with multiomics data relevant to BD was accomplished using the single-cell disease relevance score (scDRS) algorithm. We have identified a novel brain cell cluster named ADCY1, which exhibits distinct genetic characteristics. From a high-resolution genetic perspective, glial cells emerge as the primary cytopathology associated with BD. Specifically, astrocytes were significantly related to BD at the RNA-seq level, while microglia showed a strong association with BD across multiple panels, including the transcriptome-wide association study (TWAS), ATAC-seq, and RNA-seq. Additionally, oligodendrocyte precursor cells displayed a significant association with BD in both ATAC-seq and RNA-seq panel. Notably, our investigation of brain regions affected by BD revealed significant associations between BD and all three types of glial cells in the dorsolateral prefrontal cortex (DLPFC). Through comprehensive analyses, we identified several BD-associated genes, including CRMP1, SYT4, UCHL1, and ZBTB18. In conclusion, our findings suggest that glial cells, particularly in specific brain regions such as the DLPFC, may play a significant role in the pathogenesis of BD. The integration of multiomics data has provided valuable insights into the etiology of BD, shedding light on potential mechanisms underlying this complex psychiatric disorder.

Integrative Bioinformatics Analysis Revealed Mitochondrial Dysfunction-Related Genes Underlying Intervertebral Disc Degeneration

Objective

Mitochondrial dysfunction plays an important role in intervertebral disc degeneration (IDD). We aim to explore the pathways and key genes that cause mitochondrial dysfunction during IDD and to further reveal the pathogenesis of IDD based on bioinformatic analyses.

Methods

Datasets GSE70362 and GSE124272 were downloaded from the Gene Expression Omnibus. Differentially expressed genes (DEGs) of mitochondrial dysfunction between IDD patients and healthy controls were screened by package limma package. Critical genes were identified by adopting gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) pathways, and protein-protein interaction (PPI) networks. We collected both degenerated and normal disc tissues obtained surgically, and we performed western blot and qPCR to verify the key DEGs identified in intervertebral disc tissues.

Results

In total, 40 cases of IDD and 24 healthy controls were included. We identified 152 DEGs, including 67 upregulated genes and 85 downregulated genes. Four genes related to mitochondrial dysfunction (SOX9, FLVCR1, NR5A1 and UCHL1) were screened out. Of them, SOX9, FLVCR1, and UCHL1 were down-regulated in peripheral blood and intervertebral disc tissues of IDD patients, while NR5A1 was up-regulated. The analysis of immune infiltration showed the concentrations of mast cells activated were significantly the highest in IDD patients. Compared with the control group, the level of T cells CD4 memory resting was the lowest in the patients. In addition, 24 cases of IDD tissues and 12 cases of normal disc tissues were obtained to verify the results of bioinformatics analysis. Both western blot and qPCR results were consistent with the results of bioinformatics analysis.

Conclusion

We identified four genes (SOX9, FLVCR1, NR5A1 and UCHL1) associated with mitochondrial dysfunction that play an important role in the progress of disc degeneration. The identification of these differential genes may provide new insights for the diagnosis and treatment of IDD.