Meta-analysis of Association Studies of Selenoprotein Gene Polymorphism and Kashin-Beck Disease: an Updated Systematic Review

Plasma metabolites and inflammatory proteins profiling predict outcome of Fufang Duzhong Jiangu granules treating Kashin-Beck disease

To investigate predictive biomarkers that could be used to identify patients' response to treatment, plasma metabolomics and proteomics analyses were performed in Kashin-Beck disease (KBD) patients treated with Fufang Duzhong Jiangu Granules (FDJG). Plasma was collected from 12 KBD patients before treatment and 1 month after FDJG treatment. LC-MS and olink proteomics were employed for obtaining plasma metabolomics profiling and inflammatory protein profiles. Patients were classified into responders and non-responders based on drug efficacy. Enrichment analyses of differential metabolites and proteins of the responders at baseline and after treatment were conducted to study the mechanism of drug action. Differential metabolites and proteins between the two groups were screened as biomarkers to predict the drug efficacy. The receiver operating characteristic curve was used to evaluate the prediction accuracy of biomarkers. The changes in metabolites and inflammatory proteins in responders after treatment reflected the mechanism of FDJG treatment for KBD, which may act on glycerophospholipid metabolism, d-glutamine and d-glutamate metabolism, nitrogen metabolism and NF-kappa B signaling pathway. Three metabolites were identified as potential predictors: N-undecanoylglycine, β-aminopropionitrile and PC [18:3(6Z,9Z,12Z)/20:4(8Z,11Z,14Z,17Z)]. For inflammatory protein, interleukin-8 was identified as a predictive biomarker to detect responders. Combined use of these four biomarkers had high predictive ability (area under the curve = 0.972).

Association of SOX6 gene polymorphisms with Kashin-Beck disease risk in the Chinese Han population

Kashin-Beck disease (KBD) is an endemic osteochondropathy. A specific gene called SRY-box transcription factor 6 (SOX6) is important for forming cartilage. This study aims to explore the potential correlation between SOX6 single nucleotide polymorphisms (SNPs) and KBD risk for the first time. In the case-control study, 735 unrelated Chinese Han individuals were enrolled. The four mutation sites of the SOX6 gene (rs4539287 G/A, rs3203295 C/A, rs7928675 C/A, and rs10832681 A/G) were screened and genotyped on the Agena MassARRAY platform. The correlation between SOX6 SNPs and KBD risk was explored based on logistic regression analysis. The interaction between SNP and SNP was analyzed based on the multi-factor dimensionality reduction (MDR) method. Overall analysis revealed a remarkable correlation between rs7928675 and rs10832681 and the reduction of KBD risk (p < 0.05). Subgroup analyses further indicated that these two SNPs have a significant protective effect on KBD risk among participants aged ≤65 years, males, and non-smokers (p < 0.05). MDR displayed a marked interaction between rs3203295 and rs10832681. Our study revealed that SOX6 rs7928675 and rs10832681 are markedly correlated with a reduced risk of KBD in the Chinese Han population, providing a new direction for the prevention, diagnosis, and treatment of KBD.

A Metabolomics Study of Feces Revealed That a Disturbance of Selenium-Centered Metabolic Bioprocess Was Involved in Kashin-Beck Disease, an Osteoarthropathy Endemic to China

Background: Kashin-Beck disease (KBD) is a distinct osteoarthropathy in China with an unclear pathogenesis. This study aims to explore whether perturbations in the intestine metabolome could be linked to KBD individuals. Methods: An investigation was conducted in KBD endemic villages and fecal samples were collected. After applying inclusion and exclusion criteria, a total of 75 subjects were enrolled for this study, including 46 KBD (including 19 Grade I KBD and 27 Grade II KBD) and 29 controls. Untargeted metabolomics analysis was performed on the platform of UHPLC-MS. PLS-DA and OPLS-DA were conducted to compare the groups and identify the differential metabolites (DMs). Pathway analysis was conducted on MPaLA platform to explore the functional implication of the DMs. Results: Metabolomics analysis showed that compared with the control group, KBD individuals have a total of 584 differential metabolites with dysregulated levels such as adrenic acid (log2FC = -1.87, VIP = 4.84, p = 7.63 × 10-7), hydrogen phosphate (log2FC = -2.57, VIP = 1.27, p = 1.02 × 10-3), taurochenodeoxycholic acid (VIP = 1.16, log2FC = -3.24, p = 0.03), prostaglandin E3 (VIP = 1.17, log2FC = 2.67, p = 5.61 × 10-4), etc. Pathway analysis revealed several significantly perturbed pathways associated with KBD such as selenium micronutrient network (Q value = 3.11 × 10-3, Wikipathways), metabolism of lipids (Q value = 8.43 × 10-4, Reactome), free fatty acid receptors (Q value = 3.99 × 10-3, Reactome), and recycling of bile acids and salts (Q value = 2.98 × 10-3, Reactome). Subgroup comparisons found a total of 267 differential metabolites were shared by KBD vs. control, KBD II vs. control, and KBD I vs. control, while little difference was found between KBD II and KBD I (only one differential metabolite detected). Conclusions: KBD individuals showed distinct metabolic features characterized by perturbations in lipid metabolism and selenium-related bioprocesses. Our findings suggest that the loss of nutrients metabolism balance in intestine was involved in KBD pathogenesis. Linking the nutrients metabolism (especially selenium and lipid) to KBD cartilage damage should be a future direction of KBD study.

The Physiological Functions and Polymorphisms of Type II Deiodinase

Type II deiodinase (DIO2) is thought to provide triiodothyronine (T3) to the nucleus to meet intracellular needs by deiodinating the prohormone thyroxine. DIO2 is expressed widely in many tissues and plays an important role in a variety of physiological processes, such as controlling T3 content in developing tissues (e.g., bone, muscles, and skin) and the adult brain, and regulating adaptive thermogenesis in brown adipose tissue (BAT). However, the identification and cloning of DIO2 have been challenging. In recent years, several clinical investigations have focused on the Thr92Ala polymorphism, which is closely correlated with clinical syndromes such as type 2 diabetes, obesity, hypertension, and osteoarthritis. Thr92Ala-DIO2 was also found to be related to bone and neurodegenerative diseases and tumors. However, relatively few reviews have synthesized research on individual deiodinases, especially DIO2, in the past 5 years. This review summarizes current knowledge regarding the physiological functions of DIO2 in thyroid hormone signaling and adaptive thermogenesis in BAT and the brain, as well as the associations between Thr92Ala-DIO2 and bone and neurodegenerative diseases and tumors. This discussion is expected to provide insights into the physiological functions of DIO2 and the clinical syndromes associated with Thr92Ala-DIO2.