Association between GDF5 single nucleotide polymorphism rs143383 and lumbar disc degeneration

Association between single-nucleotide polymorphism rs145497186 related to NDUFV2 and lumbar disc degeneration: a pilot case–control study

Objective

The association between the single-nucleotide polymorphisms (SNPs) rs28742109, rs12955018, rs987850, rs8093805, rs12965084 and rs145497186 related to gene named NADH dehydrogenase [ubiquinone] flavoprotein 2 (NDUFV2) and lumbar disc degeneration (LDD) was preliminary investigated in a small sample size.

Methods

A total of 46 patients with LDD and 45 controls were recruited at Qilu Hospital of Shandong University, and each participant provided 5 mL peripheral venous blood. NA was extracted from the blood of each participant for further genotyping. The frequency of different genotypes in the case group and control group was determined, and analysis of the risk of LDD associated with different SNP genotypes was performed. The visual analogue scale (VAS) scores of the patients’ degree of chronic low back pain were calculated, and the relationship between VAS scores and SNPs was analysed.

Results

After excluding the influence of sex, age, height, and weight on LDD, a significant association between SNP rs145497186 related to NDUFV2 and LDD persisted (P = 0.006). Simultaneously, rs145497186 was found to be associated with chronic low back pain in LDD populations.

Conclusion

NDUFV2 rs145497186 SNP could be associated with susceptibility to LDD and the degree of chronic low back pain.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13018-022-03368-y.

Integrating multiple microarray dataset analysis and machine learning methods to reveal the key genes and regulatory mechanisms underlying human intervertebral disc degeneration

Intervertebral disc degeneration (IDD), a major cause of lower back pain, has multiple contributing factors including genetics, environment, age, and loading history. Bioinformatics analysis has been extensively used to identify diagnostic biomarkers and therapeutic targets for IDD diagnosis and treatment. However, multiple microarray dataset analysis and machine learning methods have not been integrated. In this study, we downloaded the mRNA, microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA) expression profiles (GSE34095, GSE15227, GSE63492 GSE116726, GSE56081 and GSE67566) associated with IDD from the GEO database. Using differential expression analysis and recursive feature elimination, we extracted four optimal feature genes. We then used the support vector machine (SVM) to make a classification model with the four optimal feature genes. The ROC curve was used to evaluate the model's performance, and the expression profiles (GSE63492, GSE116726, GSE56081, and GSE67566) were used to construct a competitive endogenous RNA (ceRNA) regulatory network and explore the underlying mechanisms of the feature genes. We found that three miRNAs (hsa-miR-4728-5p, hsa-miR-5196-5p, and hsa-miR-185-5p) and three circRNAs (hsa_circRNA_100723, hsa_circRNA_104471, and hsa_circRNA_100750) were important regulators with more interactions than the other RNAs across the whole network. The expression level analysis of the three datasets revealed that BCAS4 and SCRG1 were key genes involved in IDD development. Ultimately, our study proposes a novel approach to determining reliable and effective targets in IDD diagnosis and treatment.

Genetics in Cartilage Lesions: Basic Science and Therapy Approaches

Cartilage lesions have a multifactorial nature, and genetic factors are their strongest determinants. As biochemical and genetic studies have dramatically progressed over the past decade, the molecular basis of cartilage pathologies has become clearer. Several homeostasis abnormalities within cartilaginous tissue have been found, including various structural changes, differential gene expression patterns, as well as altered epigenetic regulation. However, the efficient treatment of cartilage pathologies represents a substantial challenge. Understanding the complex genetic background pertaining to cartilage pathologies is useful primarily in the context of seeking new pathways leading to disease progression as well as in developing new targeted therapies. A technology utilizing gene transfer to deliver therapeutic genes to the site of injury is quickly becoming an emerging approach in cartilage renewal. The goal of this work is to provide an overview of the genetic basis of chondral lesions and the different approaches of the most recent systems exploiting therapeutic gene transfer in cartilage repair. The integration of tissue engineering with viral gene vectors is a novel and active area of research. However, despite promising preclinical data, this therapeutic concept needs to be supported by the growing body of clinical trials.