The rs696880 Polymorphism in the Nogo-A Receptor Gene (RTN4R) Is Associated With Susceptibility to Sporadic Amyotrophic Lateral Sclerosis in the Chinese Population

Unveiling the modulation of Nogo receptor in neuroregeneration and plasticity: Novel aspects and future horizon in a new frontier

Neurodegenerative diseases (NDs) such as Alzheimer's, Parkinson's, Multiple Sclerosis, Hereditary Spastic Paraplegia, and Amyotrophic Lateral Sclerosis have emerged as the most dreaded diseases due to a lack of precise diagnostic tools and efficient therapies. Despite the fact that the contributing factors of NDs are still unidentified, mounting evidence indicates the possibility that genetic and cellular changes may lead to the significant production of abnormally misfolded proteins. These misfolded proteins lead to damaging effects thereby causing neurodegeneration. The association between Neurite outgrowth factor (Nogo) with neurological diseases and other peripheral diseases is coming into play. Three isoforms of Nogo have been identified Nogo-A, Nogo-B and Nogo-C. Among these, Nogo-A is mainly responsible for neurological diseases as it is localized in the CNS (Central Nervous System), whereas Nogo-B and Nogo-C are responsible for other diseases such as colitis, lung, intestinal injury, etc. Nogo-A, a membrane protein, had first been described as a CNS-specific inhibitor of axonal regeneration. Several recent studies have revealed the role of Nogo-A proteins and their receptors in modulating neurite outgrowth, branching, and precursor migration during nervous system development. It may also modulate or affect the inhibition of growth during the developmental processes of the CNS. Information about the effects of other ligands of Nogo protein on the CNS are yet to be discovered however several pieces of evidence have suggested that it may also influence the neuronal maturation of CNS and targeting Nogo-A could prove to be beneficial in several neurodegenerative diseases.

Ameliorative effect of Gastrodia elata Blume extracts on depression in zebrafish and cellular models through modulating reticulon 4 receptors and apoptosis

ETHNOPHARMACOLOGICAL RELEVANCE

Gastrodia elata Blume (G. elata), a traditional Chinese herb, known as "Tian Ma", is widely used as a common medicine and diet ingredient for treating or preventing neurological disorders for thousands of years in China. However, the anti-depressant effect of G. elata and the underlying mechanism have not been fully evaluated.

AIM OF THE STUDY

The study is aimed to investigate the anti-depressant effect and the molecular mechanism of G. elata in vitro and in vivo using PC12 cells and zebrafish model, respectively.

MATERIAL AND METHODS

Network pharmacology was performed to explore the potential active ingredients and action targets of G. elata Blume extracts (GBE) against depression. The cell viability and proliferation were determined by MTT and EdU assay, respectively. TUNEL assay was used to examine the anti-apoptotic effect of GBE. Immunofluorescence and Western blot were used to detect the protein expression level. In addition, novel tank diving test was used to investigate the anti-depressant effect in zebrafish depression model. RT-PCR was used to analyze the mRNA expression levels of genes.

RESULTS

G. elata against depression on the reticulon 4 receptors (RTN4R) and apoptosis-related targets, which were predicted by network pharmacology. Furthermore, GBE enhanced cell viability and inhibited the apoptosis in PC12 cells against CORT treatment. GBE relieved depression-like symptoms in adult zebrafish, included increase of exploratory behavior and regulation of depression related genes. Mechanism studies showed that the GBE inhibited the expression of RTN4R-related and apoptosis-related genes.

CONCLUSION

Our studies show the ameliorative effect of G. elata against depression. The mechanism may be associated with the inhibition of RTN4R-related and apoptosis pathways.

Genetic Variants Were Associated With the Prognosis of Head and Neck Squamous Carcinoma

Background: As the sixth most common cancer of worldwide, head and neck cancers (HNC) are springing from oral cavity, pharynx and larynx and there is no strong biomarker for prognosis. Rates of 5 years survival with HNC remain relatively low in decades with improvement of treatments. Evidence that single nucleotide polymorphisms (SNPs) play a part in cancer prognosis is growing.

Methods: We conducted an exome-wide association study among 261 patients with head and neck squamous cell carcinoma (HNSCC) and then validated in The Cancer Genome Atlas (TCGA) database for survival by using the Cox proportional hazards regression models and Kaplan–Meier analyses.

Results: After combining the result of the two stages, 4 SNPs were significantly associated with HNSCC survival (rs16879870 at 6q14.3: adjusted HR = 2.02, 95%CI = 1.50–2.73, P = 3.88 × 10⁻⁶; rs2641256 at 17p13.2: adjusted HR = 0.67, 95%CI = 0.56–0.80, P = 7.51 × 10⁻⁶; rs2761591 at 11p13: adjusted HR = 2.07, 95%CI = 1.50–2.87, P = 1.16 × 10⁻⁵; and rs854936 at 22q11.21: adjusted HR = 1.92, 95%CI = 1.43–2.57, P = 1.27 × 10⁻⁵). Besides, we constructed a receiver operating characteristic (ROC) model to estimate predictive effect of the novel SNPs combined with clinical stage in HNSCC prognosis (AUC = 0.715). We also found the genotype of rs16879870 and rs854936 was significantly associated with the expression of gene GJB7 (P = 0.013) and RTN4R (P = 0.047) in cancer tissues of TCGA, respectively.

Conclusion: Our findings suggested that the SNPs (rs16879870, rs2641256, rs2761591, rs854936) might play a crucial role in prognosis of HNSCC.

Metabolic Alteration and Amyotrophic Lateral Sclerosis Outcome: A Systematic Review

Background: The development of strategies that could not only efficiently detect the onset of Amyotrophic Lateral Sclerosis (ALS), a fatal neurodegenerative disorder with no cure but also predict its development and evaluate therapeutic intervention would be of great value. In this respect, the metabolic status of ALS patients has called attention. Hence, this study aimed to investigate the potential correlation between changes in ALS's metabolic parameters with the disease outcome in a systematic review. Methods: The manuscripts were manually searched within different databases (PubMed, Web of Science and Cochrane). The inclusion criteria were original articles and reviews about individuals with ALS and its survival, disease prognosis and metabolism (weight, cholesterol, hypertension, BMI, and glycaemia). The authors also established three different exclusion criteria: studies including ALS and other degenerative disorders, works including animal models and published before the year 2000. Results: In total, 29 papers were selected. From all manuscripts, only 82.8% ensured the participation of sALS patients. Also, 27.6% of selected studies described the presence of a genetic mutation. Regarding ALS prognosis, patient's age, the age of ALS onset, ALS duration and survival, <50% of the papers addressed these issues. Specifically, regarding metabolism, 65.5% of articles mentioned BMI, 20.7% mentioned any data concerning hypertension, 6.89% cardiovascular risk, 10.3% obesity, 13.78% diabetes and 10.3% glycaemia. Concerning lipid metabolism, more results were gathered, but still, they did not suffice to establish a correlation with ALS development. Conclusions: Altogether, the authors concluded that available information is not enough to establish a link between ALS and metabolism. In reality, less than half of the manuscripts evaluated show an association between both factors. Nonetheless, it is worth mentioning that metabolism does influence ALS, but not in a unique manner. There is a debate about patients' hypo- and hypermetabolism. Thus, to provide a reliable record, a public policy in which all research and clinical centers might assess the parameters discussed herein is suggested. Accordingly, this systematic review attempts to provide a comprehensible database to facilitate multicentered collaboration, validation, and clinical translation.

LncRNA MALAT1 gene polymorphisms in coronary artery disease: a case-control study in a Chinese population

Background: Coronary artery disease (CAD) is one of the main fatal diseases all over the world. CAD is a complex disease, which has multiple risk factors mechanisms. In recent years, genome-wide association study (GWAS) had revealed single nucleotide polymorphism genes (SNPs) which were closely related with CAD risks. The relationship between long non-coding RNA (lncRNA) MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) and CAD risk is largely unknown. To our knowledge, this is the first study which demonstrated the interaction effects of SNP-SNP and SNP-environment with CAD risk. In general, our case-control study is to detect the association between MALAT1 (rs619586, rs4102217) SNPs and CAD risk. Methods: Three hundred and sixty-five CAD patients and three hundred and eighty-four matched control participants blood samples were collected in Liaoning province, China. Two polymorphisms (rs619586, rs4102217) in lncRNA MALAT1 were genotyped by KASP platform. Results: In a stratified analysis, we found that non-drinkers with GC genotype and the recessive model of rs4102217 had higher CAD risk (P=0.010, odds ratio (OR): 1.96, 95% confidence interval (CI) = 1.17-3.28; P=0.026, OR: 1.73, 95% CI = 1.07-2.79) and diabetes mellitus (DM) history group (P=0.010, OR: 4.07, 95% CI = 1.41-11.81; P=0.019, OR: 3.29, 95% CI = 1.22-8.88). In SNP-SNP interactions analysis between MALAT1 and CAD risk, we found rs4102217 had an increase in smokers (GG: OR: 2.04, 95% CI = 1.42-2.92; CC+GC: OR: 2.64, 95% CI = 1.64-4.26) and a decrease in drinkers (CC+GC: OR: 0.33, 95% CI = 0.20-0.55). Smokers with MALAT1 rs619586 AA genotype (OR: 2.20, 95% CI = 1.57-3.07) and GG+AG genotype (OR: 2.11, 95% CI = 1.17-3.81) had a higher risk of CAD. Moreover, drinkers with AA genotype (OR: 0.22, 95% CI = 0.10-0.48) and GG+AG genotype (OR: 0.38, 95% CI = 0.22-0.65) had a lower risk of CAD. According to the MDR software, MALAT1 rs4102217 polymorphism-smoking-drinking was the best interaction model, which has higher risk of CAD (Testing Bal.ACC. = 0.6979). Conclusion: Our study demonstrated that the GC genotype and the recessive model of rs4102217 potentially increased CAD risk in some specific group.