Chondrocytes are the key target cells of the cartilage degeneration that occurs in Kashin–Beck disease (KBD) and osteoarthritis (OA). However, the heterogeneity of articular cartilage cell types present in KBD and OA patients and healthy controls is still unknown, which has prevented the study of the pathophysiology of the mechanisms underlying the roles of different populations of chondrocytes in the processes leading to KBD and OA. Here, we aimed to identify the transcriptional programmes and all major cell populations in patients with KBD, patients with OA and healthy controls to identify the markers that discriminate among chondrocytes in these three groups. Single-cell RNA sequencing was performed to identify chondrocyte populations and their gene signatures in KBD, OA and healthy cells to investigate their differences as related to the pathogenetic mechanisms of these two osteochondral diseases. We performed immunohistochemistry and quantitative reverse-transcription PCR (qRT-PCR) assays to validate the markers for chondrocyte population. Ten clusters were labelled by cell type according to the expression of previously described markers, and one novel population was identified according to the expression of a new set of markers. The homeostatic and mitochondrial chondrocyte populations, which were identified by the expression of the unknown markers MT1X and MT2A and MT-ND1 and MT-ATP6, were markedly expanded in KBD. The regulatory chondrocyte population, identified by the expression of CHI3L1, was markedly expanded in OA. Our study allows us to better understand the heterogeneity of chondrocytes in KBD and OA and provides new evidence of differences in the pathogenetic mechanisms between these two diseases.
Background Osteoarthritis (OA) and Kashin-Beck disease (KBD) both are two severe osteochondral disorders. In this study, we aimed to compare the gut microbiota structure between OA and KBD patients. Methods Fecal samples collected from OA and KBD patients were used to characterize the gut microbiota using 16S rDNA gene sequencing. To identify whether gut microbial changes at the species level are associated with the genes or functions of the gut bacteria between OA and KBD groups, metagenomic sequencing of fecal samples from OA and KBD subjects was performed. Results The OA group was characterized by elevated Epsilonbacteraeota and Firmicutes levels. A total of 52 genera were identified to be significantly differentially abundant between the two groups. The genera Raoultella, Citrobacter, Flavonifractor, g__Lachnospiraceae_UCG-004, and Burkholderia-Caballeronia-Paraburkholderia were more abundant in the OA group. The KBD group was characterized by higher Prevotella_9, Lactobacillus, Coprococcus_2, Senegalimassilia, and Holdemanella. The metagenomic sequencing showed that the Subdoligranulum_sp._APC924/74, Streptococcus_parasanguinis, and Streptococcus_salivarius were significantly increased in abundance in the OA group compared to those in the KBD group, and the species Prevotella_copri, Prevotella_sp._CAG:386, and Prevotella_stercorea were significantly decreased in abundance in the OA group compared to those in the KBD group by using metagenomic sequencing. Conclusion Our study provides a comprehensive landscape of the gut microbiota between OA and KBD patients and provides clues for better understanding the mechanisms underlying the pathogenesis of OA and KBD.
Kashin-Beck disease (KBD) is a severe osteochondral disorder that may be driven by the interaction between genetic and environmental factors. We aimed to improve our understanding of the gut microbiota structure in KBD patients of different grades and the relationship between the gut microbiota and serum metabolites. Fecal and serum samples collected from KBD patients and normal controls (NCs) were used to characterize the gut microbiota using 16S rDNA gene and metabolomic sequencing via liquid chromatography-mass spectrometry (LC/MS). To identify whether gut microbial changes at the species level are associated with the genes or functions of the gut bacteria in the KBD patients, metagenomic sequencing of fecal samples from grade I KBD, grade II KBD and NC subjects was performed. The KBD group was characterized by elevated levels of Fusobacteria and Bacteroidetes. A total of 56 genera were identified to be significantly differentially abundant between the two groups. The genera Alloprevotella, Robinsoniella, Megamonas, and Escherichia_Shigella were more abundant in the KBD group. Consistent with the 16S rDNA analysis at the genus level, most of the differentially abundant species in KBD subjects belonged to the genus Prevotella according to metagenomic sequencing. Serum metabolomic analysis identified some differentially abundant metabolites among the grade I and II KBD and NC groups that were involved in lipid metabolism metabolic networks, such as that for unsaturated fatty acids and glycerophospholipids. Furthermore, we found that these differences in metabolite levels were associated with altered abundances of specific species. Our study provides a comprehensive landscape of the gut microbiota and metabolites in KBD patients and provides substantial evidence of a novel interplay between the gut microbiome and metabolome in KBD pathogenesis.
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