(1) Many studies have attempted to utilize metabolomic approaches to explore potential biomarkers for the early detection of osteoarthritis (OA), but consistent and high-level evidence is still lacking. In this study, we performed a systematic review and meta-analysis of differential small molecule metabolites between OA patients and healthy individuals to screen promising candidates from a large number of samples with the aim of informing future prospective studies. (2) Methods: We searched the EMBASE, the Cochrane Library, PubMed, Web of Science, Wan Fang Data, VIP Date, and CNKI up to 11 August 2022, and selected relevant records based on inclusion criteria. The risk of bias was assessed using the Newcastle–Ottawa quality assessment scale. We performed qualitative synthesis by counting the frequencies of changing directions and conducted meta-analyses using the random effects model and the fixed-effects model to calculate the mean difference and 95% confidence interval. (3) Results: A total of 3798 records were identified and 13 studies with 495 participants were included. In the 13 studies, 132 kinds of small molecule differential metabolites were extracted, 58 increased, 57 decreased and 17 had direction conflicts. Among them, 37 metabolites appeared more than twice. The results of meta-analyses among four studies showed that three metabolites increased, and eight metabolites decreased compared to healthy controls (HC). (4) Conclusions: The main differential metabolites between OA and healthy subjects were amino acids (AAs) and their derivatives, including tryptophan, lysine, leucine, proline, phenylalanine, glutamine, dimethylglycine, citrulline, asparagine, acetylcarnitine and creatinine (muscle metabolic products), which could be potential biomarkers for predicting OA.

(1) Background: Many studies have attempted to explore potential biomarkers for the early detection of gout, but consistent and high levels of evidence are lacking. In this study, metabolomics was used to summarize the changes of metabolites in the literature and explore the potential value of metabolites in predicting the occurrence and development of gout. (2) Methods: We searched the databases including the EMBASE, the Cochrane Library, PubMed, Web of Science, VIP Date, Wanfang Data, and CNKI, and the screening was fulfilled on 30 July 2022. The records were screened according to the inclusion criteria and the risk of bias was assessed. Qualitative analysis was performed for all metabolites, and meta-analysis was performed for metabolite concentrations using random effects to calculate the Std mean difference and 95% confidence interval. (3) Results: A total of 2738 records were identified, 33 studies with 3422 participants were included, and 701 metabolites were identified. The qualitative analysis results showed that compared with the healthy control group, the concentration of 56 metabolites increased, and 22 metabolites decreased. The results of the meta-analysis indicated that 17 metabolites were statistically significant. (4) Conclusions: Metabolites are associated with gout. Some specific metabolites such as uric acid, hypoxanthine, xanthine, KYNA, guanosine, adenosine, creatinine, LB4, and DL-2-Aminoadipic acid have been highlighted in the development of gout.

Intervertebral disc (IVD) degeneration (IDD) is a progressive condition characterized by the deterioration of the intervertebral discs, which serve as cushions between the vertebrae in the spinal column. This degeneration is often associated with aging and can be influenced by various factors, including genetics, mechanical stress, and lifestyle choices. N⁶-methyladenosine (m⁶A) modification has emerged as a critical post-transcriptional regulatory mechanism that influences various biological processes, including cellular differentiation, proliferation, and response to stress. Recent studies suggest that m⁶A modification play significant roles in the pathophysiology of IDD. The dysregulation of m⁶A methylation is linked to the altered expression of genes involved in inflammation, oxidative stress, extracellular matrix remodeling, regulated cell death including apoptosis, autophagy, pyroptosis and ferroptosis, all of which contribute to the IDD. In this review, we summarize the advanced detection technology of m⁶A and the roles of m⁶A in pathological process of IDD, to provide new insights into the molecular mechanisms underlying IDD and identify novel therapeutic targets for intervention. This work underscores the diagnostic and therapeutic potential of targeting m⁶A mechanism in IDD. Clinically, m6A regulators may serve as biomarkers for early IDD detection or progression monitoring. Therapeutically, small-molecule modulators of m⁶A writers/erasers or RNA-based strategies could restore ECM homeostasis, mitigate inflammation, and prevent IVD cell death. Furthermore, advanced m⁶A mapping technologies may enable personalized interventions by decoding patient-specific epitranscriptomic profiles. These insights bridge molecular mechanisms to clinical innovation, offering novel avenues for IDD treatment and regenerative therapies.

Autoimmune rheumatic diseases (ARDs), often characterized by pain, constitute a diverse group of autoimmune conditions involving inflammation-mediated injuries to bones, joints, surrounding connective tissues, and occasionally other organs. RNA methylation is a key epitranscriptomic modification that regulates gene expression by influencing stability, splicing, nuclear translocation and degradation. Recent studies have highlighted the crucial role of RNA modification in the pathogenesis and progression of various ARDs. RNA modification affects critical biologic processes of ARDs, such as inflammation, immune response. This review systematically explores the landscape of RNA modification in ARDs, elucidating its regulatory roles and therapeutic implications, including rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, primary Sjögren’s syndrome, systemic sclerosis. The intricate mechanisms of RNA modification can lead to the development of novel diagnostic biomarkers and therapeutic strategies, ultimately improving patient outcomes.