Gene Expression Signature of Traumatic Brain Injury

Age-related changes after intracerebral hemorrhage: a comparative proteomics analysis of perihematomal tissue

The risk factors and causes of intracerebral hemorrhage (ICH) and the degree of functional recovery after ICH are distinct between young and elderly patients. The increasing incidence of ICH in young adults has become a concern; however, research on the molecules and pathways involved ICH in subjects of different ages is lacking. In this study, tandem mass tag (TMT)-based proteomics was utilized to examine the protein expression profiles of perihematomal tissue from young and aged mice 24 h after collagenase-induced ICH. Among the 5,129 quantified proteins, ICH induced 108 and 143 differentially expressed proteins (DEPs) in young and aged mice, respectively; specifically, there were 54 common DEPs, 54 unique DEPs in young mice and 89 unique DEPs in aged mice. In contrast, aging altered the expression of 58 proteins in the brain, resulting in 39 upregulated DEPs and 19 downregulated DEPs. Bioinformatics analysis indicated that ICH activated different proteins in complement pathways, coagulation cascades, the acute phase response, and the iron homeostasis signaling pathway in mice of both age groups. Protein-protein interaction (PPI) analysis and ingenuity pathway analysis (IPA) demonstrated that the unique DEPs in the young and aged mice were related to lipid metabolism and carbohydrate metabolism, respectively. Deeper paired-comparison analysis demonstrated that apolipoprotein M exhibited the most significant change in expression as a result of both aging and ICH. These results help illustrate age-related protein expression changes in the acute phase of ICH.

rDNA Transcription in Developmental Diseases and Stem Cells

As the first and rate-limiting step in ribosome biogenesis, rDNA transcription undergoes significant dynamic changes during cell pluripotency alteration. Over the past decades, rDNA activity has demonstrated dynamic changes, but most people view it as passive compliance with cellular needs. The evidence for rDNA transcriptional activity determining stem cell pluripotency is growing as research advances, resulting in the arrest of embryonic development and impairment of stem cell lines stemness by rDNA transcription inhibition. The exact mechanism by which rDNA activation influences pluripotency remains unknown. The first objective of this opinion article is to describe rDNA changes in the pathological and physiological course of life, including developmental diseases, tumor genesis, and stem cell differentiation. After that, we propose three hypotheses regarding rDNA regulation of pluripotency: 1) Specialized ribosomes synthesized from rDNA variant, 2) Nucleolar stress induced by the drop of rDNA transcription, 3) Interchromosomal interactions between rDNA and other genes. The pluripotency regulatory center is expected to focus strongly on rDNA. A small molecule inhibitor of rDNA is used to treat tumors caused by abnormal pluripotency activation. By understanding how rDNA regulates pluripotency, we hope to treat developmental diseases and safely apply somatic cell reprogramming in clinical settings.

Effects of metformin on modulating the expression of brain-related genes of APP/PS1 transgenic mice based on Single Cell Sequencing

BACKGROUND

Alzheimer's disease is the most common form of dementia, affecting millions of people worldwide.

METHODS

Here, we analyzed the effects of metformin on APP/PS1 transgenic mice by behavioral test and single-cell sequencing. Results showed that metformin can improve the spatial learning, memory function, and anxiety mood of APP/PS1 transgenic mice. We identified transcriptionally distinct subpopulations of nine major brain cell types. Metformin increased the differentiation of stem cells, decreased the proportion of cells in the G2 phase, enhanced the generation of neural stem cells and oligodendrocyte progenitor cells, and the tendency of neural stem cells to differentiate into astrocytes. Notably, 253 genes expressed abnormally in APP/PS1 transgenic mice and were reversed by metformin. Ttr, Uba52, and Rps21 are the top 3 genes in the cell-gene network with the highest node degree. Moreover, histochemistry showed the expressions of RPS15, UBA52, and RPL23a were consistent with the data from single-cell sequencing. Pathway and biological process enrichment analysis indicated metformin was involved in nervous system development and negative regulation of the apoptotic process.

CONCLUSION

Overall, metformin might play an important role in the differentiation and development and apoptotic process of the central nervous system by regulating the expression of Ttr, Uba52, Rps21, and other genes to improve cognition of APP/PS1 transgenic mice. These results provided a clue for elaborating on the molecular and cellular basis of metformin on AD.

Exploring the pathogenesis linking traumatic brain injury and epilepsy via bioinformatic analyses

Traumatic brain injury (TBI) is a serious disease that could increase the risk of epilepsy. The purpose of this article is to explore the common molecular mechanism in TBI and epilepsy with the aim of providing a theoretical basis for the prevention and treatment of post-traumatic epilepsy (PTE). Two datasets of TBI and epilepsy in the Gene Expression Omnibus (GEO) database were downloaded. Functional enrichment analysis, protein–protein interaction (PPI) network construction, and hub gene identification were performed based on the cross-talk genes of aforementioned two diseases. Another dataset was used to validate these hub genes. Moreover, the abundance of infiltrating immune cells was evaluated through Immune Cell Abundance Identifier (ImmuCellAI). The common microRNAs (miRNAs) between TBI and epilepsy were acquired via the Human microRNA Disease Database (HMDD). The overlapped genes in cross-talk genes and target genes predicted through the TargetScan were obtained to construct the common miRNAs–mRNAs network. A total of 106 cross-talk genes were screened out, including 37 upregulated and 69 downregulated genes. Through the enrichment analyses, we showed that the terms about cytokine and immunity were enriched many times, particularly interferon gamma signaling pathway. Four critical hub genes were screened out for co-expression analysis. The miRNA–mRNA network revealed that three miRNAs may affect the shared interferon-induced genes, which might have essential roles in PTE. Our study showed the potential role of interferon gamma signaling pathway in pathogenesis of PTE, which may provide a promising target for future therapeutic interventions.

Role of statins in regulating molecular pathways following traumatic brain injury: A system pharmacology study

Traumatic brain injury (TBI) is a serious disorder with debilitating physical and psychological complications. Previous studies have indicated that genetic factors have a critical role in modulating the secondary phase of injury in TBI. Statins have interesting pleiotropic properties such as antiapoptotic, antioxidative, and anti-inflammatory effects, which make them a suitable class of drugs for repurposing in TBI. In this study, we aimed to explore how statins modulate proteins and pathways involved in TBI using system pharmacology. We first explored the target associations with statins in two databases to discover critical clustering groups, candidate hub and critical hub genes in the network of TBI, and the possible connections of statins with TBI-related genes. Our results showed 1763 genes associated with TBI. Subsequently, the analysis of centralities in the PPI network displayed 55 candidate hub genes and 15 hub genes. Besides, MCODE analysis based on threshold score:10 determined four modular clusters. Intersection analysis of genes related to TBI and statins demonstrated 204 shared proteins, which suggested that statins influence 31 candidate hub and 9 hub genes. Moreover, statins had the highest interaction with MCODE1. The biological processes of the 31 shared proteins are related to gene expression, inflammation, antioxidant activity, and cell proliferation. Biological enriched pathways showed Programmed Cell Death proteins, AGE-RAGE signaling pathway, C-type lectin receptor signalling pathway, and MAPK signaling pathway as top clusters. In conclusion, statins could target several critical post-TBI genes mainly involved in inflammation and apoptosis, supporting the previous research results as a potential therapeutic agent.

Construction and external validation of a 5-gene random forest model to diagnose non-obstructive azoospermia based on the single-cell RNA sequencing of testicular tissue

Non-obstructive azoospermia (NOA) is among the most severe factors for male infertility, but our understandings of the latent biological mechanisms remain insufficient. The single-cell RNA sequencing (scRNA-seq) data of 432 testicular cells isolated from the patient with NOA was analyzed, and the cell samples were grouped into 5 cell clusters. A sum of 455 cell markers was identified and then included in the protein-protein interaction network. The Top 5 most critical genes in the network, including CCT8, CDC6, PSMD1, RPS4X, RPL36A, were selected for the diagnosis model construction through the random forest (RF). The RF model was a strong classifier for NOA and obstructive azoospermia (OA), which was validated in the training cohort (n = 58, AUC = 1) and external validation cohort (n = 20, AUC = 0.9). We collected the seminal plasma samples and testicular biopsy samples from 20 OA and 20 NOA cases from the local hospital, and the gene expression was detected via Real-Time quantitative Polymerase Chain Reaction (RT-qPCR) and Immunohistochemistry. The RF model also exhibited high accuracy (AUC = 0.725) in the local cohort. In summary, a novel gene signature was developed and externally validated based on scRNA-seq analysis, providing some new biomarkers to uncover the underlying mechanisms and a promising clinical tool for diagnosis in NOA.