Molecular insights for an anti-osteoporotic properties of Litsea glutinosa on Saos-2 cells: An in-vitro approach

Ethnomedicinal Uses, Phytochemistry, and Therapeutic Potentials of Litsea glutinosa (Lour.) C. B. Robinson: A Literature-Based Review

Litsea glutinosa (Lour.) C. B. Robinson, belonging to the family Lauraceae, is a multipurpose and fast-growing evergreen or deciduous tree that has been traditionally used for numerous purposes such as treatment for diarrhea, dysentery, abdominal pain, indigestion, gastroenteritis, edema, traumatic injuries, colds, arthritis, asthma, diabetes, pain relief, and poignant sexual power. This study aimed to summarize the chemical reports, folk values, and phytopharmacological activities of L. glutinosa, based on available information screened from diverse databases. An up-to-date electronic-based search was accomplished to obtain detailed information, with the help of several databases such as Google Scholar, Scopus, SpringerLink, Web of Science, ScienceDirect, ResearchGate, PubMed, ChemSpider, Elsevier, BioMed Central, and the USPTO, CIPO, INPI, Google Patents, and Espacenet, using relevant keywords. Outcomes advocate that, up to the present time, alkaloids, glycosides, and terpenoids are abundant in, and the most bioactive constituents of, this natural plant. Results demonstrated that L. glutinosa has various remarkable biological activities, including antioxidant, anti-inflammatory, anti-microbial, anticancer, antipyretic, anti-diabetic, analgesic, hepatoprotective, and wound-healing activity. One study revealed that L. glutinosa exhibited significant aphrodisiac and anti-infertility activity. Nevertheless, no clinical studies have been cited. Taken together, L. glutinosa may be one of the significant sources of bioactive constituents that could potentially lead to different effective pharmacological activities. On the other hand, future research should focus on clinical studies and several toxicity evaluations, such as sub-chronic toxicity, teratogenicity, and genotoxicity.

Prognostic analysis and validation of diagnostic marker genes in patients with osteoporosis

Backgrounds

As a systemic skeletal dysfunction, osteoporosis (OP) is characterized by low bone mass and bone microarchitectural damage. The global incidences of OP are high.

Methods

Data were retrieved from databases like Gene Expression Omnibus (GEO), GeneCards, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Gene Expression Profiling Interactive Analysis (GEPIA2), and other databases. R software (version 4.1.1) was used to identify differentially expressed genes (DEGs) and perform functional analysis. The Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression and random forest algorithm were combined and used for screening diagnostic markers for OP. The diagnostic value was assessed by the receiver operating characteristic (ROC) curve. Molecular signature subtypes were identified using a consensus clustering approach, and prognostic analysis was performed. The level of immune cell infiltration was assessed by the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm. The hub gene was identified using the CytoHubba algorithm. Real-time fluorescence quantitative PCR (RT-qPCR) was performed on the plasma of osteoporosis patients and control samples. The interaction network was constructed between the hub genes and miRNAs, transcription factors, RNA binding proteins, and drugs.

Results

A total of 40 DEGs, eight OP-related differential genes, six OP diagnostic marker genes, four OP key diagnostic marker genes, and ten hub genes (TNF, RARRES2, FLNA, STXBP2, EGR2, MAP4K2, NFKBIA, JUNB, SPI1, CTSD) were identified. RT-qPCR results revealed a total of eight genes had significant differential expression between osteoporosis patients and control samples. Enrichment analysis showed these genes were mainly related to MAPK signaling pathways, TNF signaling pathway, apoptosis, and Salmonella infection. RT-qPCR also revealed that the MAPK signaling pathway (p38, TRAF6) and NF-kappa B signaling pathway (c-FLIP, MIP1β) were significantly different between osteoporosis patients and control samples. The analysis of immune cell infiltration revealed that monocytes, activated CD4 memory T cells, and memory and naïve B cells may be related to the occurrence and development of OP.

Conclusions

We identified six novel OP diagnostic marker genes and ten OP-hub genes. These genes can be used to improve the prognostic of OP and to identify potential relationships between the immune microenvironment and OP. Our research will provide insights into the potential therapeutic targets and pathogenesis of osteoporosis.