(1) Background: Osteoarthritis (OA) is a heterogeneous disorder, and subgroup classification of OA remains elusive. The aim of our study was to identify endotypes of hip OA and investigate the altered pathways in the different endotypes. (2) Methods: Metabolomic profiling and genome-wide genotyping were performed on fasting blood. Transcriptomic profiling was performed on RNA extracted from cartilage samples. Machine learning methods were used to identify endotypes of hip OA. Pathway analysis was used to identify the altered pathways between hip endotypes and controls. GWAS was performed on each of the identified metabolites. Transcriptomic data was used to examine the expression levels of identified genes in cartilage. (3) Results: 180 hip OA patients and 120 OA-free controls were classified into three clusters based on metabolomic data. The combination of arginine, ornithine, and the average value of 7 lysophosphatidylcholines had an area under the curve (AUC) of 0.97 (95% CI: 0.96-0.99) to discriminate hip OA from controls, and the combination of γ-aminobutyric acid, spermine, aconitic acid, and succinic acid had an AUC of 0.96 (95% CI: 0.94-0.99) to distinguish two hip OA endotypes. GWAS identified 236 SNPs to be associated with identified metabolites at GWAS significance level. Pro-inflammatory cytokine levels were significantly different between two endotypes (all < 0.05). (4) Conclusions: Hip OA could be classified into two distinct molecular endotypes. The primary differences between the two endotypes involve changes in pro-inflammatory factors and energy metabolism.
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http://dx.doi.org/10.3390/metabo14090480 | DOI Listing |
Metabolites
September 2024
Human Genetics & Genomics, Division of BioMedical Sciences, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL A1B 3V6, Canada.
(1) Background: Osteoarthritis (OA) is a heterogeneous disorder, and subgroup classification of OA remains elusive. The aim of our study was to identify endotypes of hip OA and investigate the altered pathways in the different endotypes. (2) Methods: Metabolomic profiling and genome-wide genotyping were performed on fasting blood.
View Article and Find Full Text PDFBiochem Biophys Res Commun
April 2024
Department of Biological and Environmental Sciences, Carroll College, Helena, MT, 59625, United States. Electronic address:
Osteoarthritis is the most common chronic joint disease, characterized by the abnormal remodeling of joint tissues including articular cartilage and subchondral bone. However, there are currently no therapeutic drug targets to slow the progression of disease because disease pathogenesis is largely unknown. Thus, the goals of this study were to identify metabolic differences between articular cartilage and subchondral bone, compare the metabolic shifts in osteoarthritic grade III and IV tissues, and spatially map metabolic shifts across regions of osteoarthritic hip joints.
View Article and Find Full Text PDFClin Transl Med
April 2023
Institute of Inflammation and Ageing, MRC-ARUK Centre for Musculoskeletal Ageing Research, University of Birmingham, Birmingham, UK.
Background: Osteoarthritis (OA), a multifaceted condition, poses a significant challenge for the successful clinical development of therapeutics due to heterogeneity. However, classifying molecular endotypes of OA pathogenesis could provide invaluable phenotype-directed routes for stratifying subgroups of patients for targeted therapeutics, leading to greater chances of success in trials. This study establishes endotypes in OA soft joint tissue driven by obesity in both load-bearing and non-load bearing joints.
View Article and Find Full Text PDFJ Allergy Clin Immunol
October 2022
Children's National Hospital, George Washington University School of Medicine and Health Sciences, Washington, DC. Electronic address:
Background: Obesity-related complications including visceral fat, metabolic abnormalities, nutrient deficiencies, and immune perturbations are interdependent but have been individually associated with childhood asthma.
Objective: We sought to endotype childhood obesity-related asthma by quantifying contributions of obesity-related complications to symptoms and pulmonary function.
Methods: Multiomics analysis using Similarity Network Fusion followed by mediation analysis were performed to quantify prediction of obese asthma phenotype by different combinations of anthropometric, metabolic, nutrient, and T-cell transcriptome and DNA methylome data sets.
Rheumatology (Oxford)
June 2021
Division of Biomedical Sciences (Genetics), Faculty of Medicine, Memorial University of Newfoundland, St John's, NL, Canada.
Objective: To identify endotypes of osteoarthritis (OA) by a metabolomics analysis.
Methods: Study participants included hip/knee OA patients and controls. Fasting plasma samples were metabolomically profiled.
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