Shunmei Chen

Accurately quantifying the expression of individual transcript isoforms remains a formidable challenge, especially in contexts such as neurodegenerative diseases and cancers, which are characterized by high isoform diversity. The present study introduces a junction-based method, named differential splicing frequency analysis (DSFA), which enables more sensitive detection of differential splicing using RNA-seq data. Unlike the existing exon-, isoform-, and event-based methods, DSFA quantifies splice junction usage. We applied DSFA to Alzheimer’s disease (AD)-associated genes through large-scale RNA-seq data mining. The present study is the first to establish that the APP770-, APP751-, APP695-, and APP752-encoding isoforms represent major isoforms of the APP gene. Three important findings are: (1) the APP752-encoding isoform exhibits immune cell specificity; (2) the relative proportion of the APP752-encoding isoform increases during the differentiation of induced pluripotent stem cells (iPSCs) into microglia, akin to the increase in relative proportion of the APP695-encoding isoform during iPSC differentiation into neurons; and (3) the APP751-encoding isoform predominates in both cancer and immune cells. Additionally, we identified APP/58417N and App/52804N as differentially expressed splice junctions in humans and mice, respectively. Through over-expression of U1 snRNA in human embryonic stem cell (hESC)-derived neurons, we found that U1 snRNA over-expression decreases the usage of APP/58417N in neurons, similar to the effects observed in AD samples. Our research highlights that the major isoforms of a gene can differ markedly in their expression across tissue and cell types.

Multiple sclerosis (MS) is a chronic disease characterized by inflammation and neurodegeneration of the central nervous system. Despite the significant role of oxidative stress in the pathogenesis of MS, its precise molecular mechanisms remain unclear. This study utilized microarray datasets from the GEO database to analyze differentially expressed oxidative-stress-related genes (DE-OSRGs), identifying 101 DE-OSRGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicate that these genes are primarily involved in oxidative stress and immune responses. Through protein–protein interaction (PPI) network, LASSO regression, and logistic regression analyses, four genes (MMP9, NFKBIA, NFKB1, and SRC) were identified as being closely related to MS. A diagnostic prediction model based on logistic regression demonstrated good predictive power, as shown by the nomogram curve index and DAC results. An immune-cell infiltration analysis using CIBERSORT revealed significant correlations between these genes and immune cell subpopulations. Abnormal oxidative stress and upregulated expression of key genes were observed in the blood and brain tissues of EAE mice. A molecular docking analysis suggested strong binding potentials between the proteins of these genes and several drug molecules, including isoquercitrin, decitabine, benztropine, and curcumin. In conclusion, this study identifies and validates potential diagnostic biomarkers for MS, establishes an effective prediction model, and provides new insights for the early diagnosis and personalized treatment of MS.

During the first waves of the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, olfactory dysfunction (OD) was reported as a frequent clinical sign. The nasal epithelium is one of the front-line protections against viral infections, and the immune responses of the nasal mucosa may be associated with OD. Two mechanisms underlying OD occurrence in COVID-19 have been proposed: the infection of sustentacular cells and the inflammatory reaction of the nasal epithelium. The former triggers OD and the latter likely prolongs OD. These two alternative mechanisms may act in parallel; the infection of sustentacular cells is more important for OD occurrence because sustentacular cells are more likely to be the entry point of SARS-CoV-2 than olfactory neurons and more susceptible to early injury. Furthermore, sustentacular cells abundantly express transmembrane protease, serine 2 (TMPRSS2) and play a major role in the olfactory epithelium. OD occurrence in COVID-19 has revealed crucial roles of sustentacular cells. This review aims to elucidate how immune responses of the nasal epithelium contribute to COVID-19–related OD. Understanding the underlying immune mechanisms of the nasal epithelium in OD may aid in the development of improved medical treatments for COVID-19–related OD.