Diagnosis of early stage knee osteoarthritis based on early clinical course: data from the CHECK cohort

Comparison of definitions of early knee osteoarthritis for likelihood of progression at 2-year and 5-year follow-up: the Multicenter Osteoarthritis Study

BACKGROUND

Preventing worsening osteoarthritis (OA) in persons with early OA is a major treatment goal. We evaluated if different early OA definitions yielded enough cases of worsening OA within 2-5 years to make trial testing treatments feasible.

METHODS

We assessed different definitions of early OA using data from Multicenter Osteoarthritis (MOST) Study participants who were followed up longitudinally. We defined early OA as having at least minimal knee pain (WOMAC (Western Ontario and McMaster Universities Osteoarthritis Index) pain ≥3/20) with different levels of pre-radiographic OA. For MRI, we required knee pain and used MRI definitions with combinations of cartilage damage, osteophytes, bone marrow lesions and meniscus damage. The primary outcome, worsening OA at 2 or 5 years, combined structural (Kellgren and Lawrence grade ≥2 with joint space narrowing ≥1) and symptom (WOMAC pain ≥6 with increase ≥2 from baseline) outcomes. We also examined structural and symptom outcomes separately.

RESULTS

For worsening OA at 2 years, we included 750 participants (mean age 65 years, 60% female, 90% white, mean body mass index 29.2 kg/m2). Fewer than 10% of early OA knees had the combined outcome at 2 or 5 years. At 2 years, for several early OA definitions, roughly 20% of knees had either structural or symptom worsening outcomes. Two-year trials of either, but not both, outcomes would need to recruit over 1200 patients.

CONCLUSION

Most knees with early OA are stable and do not progress. Some painful knees experience worse pain but not structural progression and vice versa. Trial testing treatments to prevent OA illness or disease will be challenging.

Planned or recent first consultation with the general practitioner for knee complaints: Is it indicative of early-stage knee osteoarthritis?

Objective

No established definition for early-stage knee osteoarthritis (KOA) is available, nor classification criteria. Identifying the characteristics of individuals presenting with early-stage KOA symptoms can enhance diagnosis to prevent progression. This study aimed to describe clinical and structural features of individuals presenting with knee complaints within two years after their first consultation, while exploring differences in the duration of knee complaints.

Method

Baseline data was used from the LITE randomized controlled trial, assessing the effectiveness of a lifestyle intervention for individuals with knee complaints and overweight in primary care. Baseline assessments included questionnaires, clinical assessment, and MRI of the most symptomatic knee. Differences between groups with varying durations of knee complaints (<12, ≥12-<24, ≥24 months) were evaluated.

Results

Participants (N ​= ​218, 65% female, mean age 59 ​± ​6 years, mean BMI 32 ​± ​5 ​kg/m2) had a median knee complaint duration of 14 months, with an average KOOS pain score of 60 ​± ​17.46% reported their symptoms as unacceptable. Structural MRI-defined KOA was observed in 71% of participants. There were no significant differences in clinical or structural MRI features between different durations of knee complaints.

Conclusion

Within 24 months of initial consultation, over two-thirds of participants displayed MRI-defined structural KOA, and nearly half reported unacceptable symptom states. This study found no association between the duration of knee complaints and symptoms severity or structural KOA presence, underscoring the complexity of identifying stages of KOA among individuals with overweight. Future studies should explore additional features beyond current considerations to facilitate early-stage KOA diagnosis, specifically for individuals with overweight.

Identification of HTRA1, DPT and MXRA5 as potential biomarkers associated with osteoarthritis progression and immune infiltration

BACKGROUND

Our study aimed to identify potential specific biomarkers for osteoarthritis (OA) and assess their relationship with immune infiltration.

METHODS

We utilized data from GSE117999, GSE51588, and GSE57218 as training sets, while GSE114007 served as a validation set, all obtained from the GEO database. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed to identify hub modules and potential functions of genes. We subsequently screened for potential OA biomarkers within the differentially expressed genes (DEGs) of the hub module using machine learning methods. The diagnostic accuracy of the candidate genes was validated. Additionally, single gene analysis and ssGSEA was performed. Then, we explored the relationship between biomarkers and immune cells. Lastly, we employed RT-PCR to validate our results.

RESULTS

WGCNA results suggested that the blue module was the most associated with OA and was functionally associated with extracellular matrix (ECM)-related terms. Our analysis identified ALB, HTRA1, DPT, MXRA5, CILP, MPO, and PLAT as potential biomarkers. Notably, HTRA1, DPT, and MXRA5 consistently exhibited increased expression in OA across both training and validation cohorts, demonstrating robust diagnostic potential. The ssGSEA results revealed that abnormal infiltration of DCs, NK cells, Tfh, Th2, and Treg cells might contribute to OA progression. HTRA1, DPT, and MXRA5 showed significant correlation with immune cell infiltration. The RT-PCR results also confirmed these findings.

CONCLUSIONS

HTRA1, DPT, and MXRA5 are promising biomarkers for OA. Their overexpression strongly correlates with OA progression and immune cell infiltration.

[Identification of Osteoarthritis Inflamm-Aging Biomarkers by Integrating Bioinformatic Analysis and Machine Learning Strategies and the Clinical Validation]

Objective

To identify inflamm-aging related biomarkers in osteoarthritis (OA).

Methods

Microarray gene profiles of young and aging OA patients were obtained from the Gene Expression Omnibus (GEO) database and aging-related genes (ARGs) were obtained from the Human Aging Genome Resource (HAGR) database. The differentially expressed genes of young OA and older OA patients were screened and then intersected with ARGs to obtain the aging-related genes of OA. Enrichment analysis was performed to reveal the potential mechanisms of aging-related markers in OA. Three machine learning methods were used to identify core senescence markers of OA and the receiver operating characteristic (ROC) curve was used to assess their diagnostic performance. Peripheral blood mononuclear cells were collected from clinical OA patients to verify the expression of senescence-associated secretory phenotype (SASP) factors and senescence markers.

Results

A total of 45 senescence-related markers were obtained, which were mainly involved in the regulation of cellular senescence, the cell cycle, inflammatory response, etc. Through the screening with the three machine learning methods, 5 core senescence biomarkers, including FOXO3, MCL1, SIRT3, STAG1, and S100A13, were obtained. A total of 20 cases of normal controls and 40 cases of OA patients, including 20 cases in the young patient group and 20 in the elderly patient group, were enrolled. Compared with those of the young patient group, C-reactive protein (CRP), interleukin (IL)-6, and IL-1β levels increased and IL-4 levels decreased in the elderly OA patient group (P<0.01); FOXO3, MCL1, and SIRT3 mRNA expression decreased and STAG1 and S100A13 mRNA expression increased (P<0.01). Pearson correlation analysis demonstrated that the selected markers were associated with some indicators, including erythrocyte sedimentation rate (ESR), IL-1β, IL-4, CRP, and IL-6. The area under the ROC curve of the 5 core aging genes was always greater than 0.8 and the C-index of the calibration curve in the nomogram prediction model was 0.755, which suggested the good calibration ability of the model.

Conclusion

FOXO3, MCL1, SIRT3, STAG1, and S100A13 may serve as novel diagnostic biomolecular markers and potential therapeutic targets for OA inflamm-aging.

Alcoholic drink produced by pea is a risk factor for incident knee surgery in patients with knee osteoarthritis

Objective

The objective of this study is to investigate whether alcohol exposure and specific alcoholic drinks are independent risk factors for incident knee surgery in knee osteoarthritis (KOA) patients.

Methods

We identified all patients who were clinically diagnosed as KOA between January 2010 and January 2018 in our outpatient department. Demographic, clinical, and radiographic data were collected from the database of our hospital. Next, we analyzed the association between alcohol consumption and incident knee surgery.

Results

A total of 4,341 KOA patients completed the current study and were included in the final analysis. Incident knee surgery for the purpose of treating osteoarthritis was observed in 242 patients. Incident knee surgery was significantly associated with age (OR [95%CI], 1.023 [1.009-1.039], P = 0.002), BMI (OR [95%CI], 1.086 [1.049-1.123], P < 0.001), baseline K-L grade 3 (OR [95%CI], 1.960 [1.331-2.886], P = 0.001), baseline K-L grade 4 (OR [95%CI], 1.966 [1.230-3.143], P = 0.005), 7.1-14 drinks per week (OR [95%CI], 2.013 [1.282-3.159], P = 0.002), >14 standard drinks per week (OR [95%CI], 2.556 [1.504-4.344], P = 0.001), and the most common alcoholic drink produced by pea (OR [95%CI], 3.133 [1.715-5.723], P < 0.001).

Conclusion

KOA patients who consumed more than seven standard drinks per week were at substantial risk of incident knee surgery. In addition, alcoholic drink produced by pea is also an independent risk factor.

Glucagon-like peptide-1 receptor agonists as a disease-modifying therapy for knee osteoarthritis mediated by weight loss: findings from the Shanghai Osteoarthritis Cohort

OBJECTIVE

Obesity is a risk factor for knee osteoarthritis (KOA) development and progression. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are indicated for type 2 diabetes mellitus (T2DM) and obesity. However, whether KOA patients can benefit from GLP-1RA therapies has not been sufficiently investigated, especially in the long term.

METHODS

The Shanghai Osteoarthritis Cohort study is a prospective, observational, multicentre study of >40 000 adults with clinically diagnosed osteoarthritis aged >45 years in Shanghai. We identified all KOA participants with comorbid T2DM enrolled from 1 January 2011 to 1 January 2017. Primary outcome was incidence of knee surgery after enrolment. Secondary outcomes included pain-relieving medication use, number of intra-articular therapies, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and medial femorotibial joint cartilage thickness. To evaluate the effects of GLP-1RA, we performed before-and-after comparison and comparison with participants who had no GLP-1RA exposure.

RESULTS

For an intergroup comparison (non-GLP-1RA vs GLP-1RA), more weight loss (adjusted mean difference in weight change from baseline -7.29 kg (95% CI -8.07 to -6.50 kg), p<0.001) and lower incidence of knee surgery (93/1574 (5.9%) vs 4/233 (1.7%), adjusted p=0.014) were observed in the GLP-1RA group. Statistically significant differences in mean change from baseline for the WOMAC total and pain subscale scores were observed (adjusted mean difference in WOMAC total score -1.46 (95% CI -2.84 to -0.08), p=0.038; adjusted mean difference in WOMAC pain subscore -3.37 (95% CI -5.79 to -0.94), p=0.007). Cartilage-loss velocity of the medial femorotibial joint was significantly lower in the GLP-1RA group postadjustment for baseline characteristics (adjusted mean difference -0.02 mm (95% CI -0.03 to -0.002 mm), p=0.004). For the before-and-after comparison within the GLP-1RA group, we observed a significant decrease of symptom-relieving medication consumption and cartilage loss velocity of medial femorotibial joint (after-treatment vs before-treatment: -0.03±0.05 vs -0.05±0.07 mm/year, p<0.001). The association between GLP-1RA exposure and decreased incidence of knee surgery was mediated by weight reduction (mediation proportion: 32.1%), instead of glycaemic control (too small to calculate).

CONCLUSION

With sufficient treatment duration, GLP-1RA therapies might be disease-modifying for KOA patients with comorbid T2DM, possibly mediated by weight loss. Further investigation is needed to elucidate effects of GLP-1RA on disease process, joint structure and patient-reported outcomes of osteoarthritis.

Six macrophage-associated genes in synovium constitute a novel diagnostic signature for osteoarthritis

Background

Synovial macrophages play important roles in the formation and progression of osteoarthritis (OA). This study aimed to explore the biological and clinical significance of macrophage-associated genes (MAGs) in OA.

Methods

The OA synovial gene expression profiles GSE89408 and GSE82107 were obtained from the GEO database. Single-sample gene set enrichment analysis (ssGSEA) and GSEA were employed to decipher differences in immune infiltration and macrophage-associated biological pathways, respectively. Protein–protein interaction (PPI) network analysis and machine learning were utilized to establish a macrophage-associated gene diagnostic signature (MAGDS). RT-qPCR was performed to test the expression of key MAGs in murine models.

Results

OA synovium presented high levels of immune infiltration and activation of macrophage-associated biological pathways. A total of 55 differentially expressed MAGs were identified. Using PPI analysis and machine learning, a MAGDS consisting of IL1B, C5AR1, FCGR2B, IL10, IL6, and TYROBP was established for OA diagnosis (AUC = 0.910) and molecular pathological evaluation. Patients with high MAGDS scores may possess higher levels of immune infiltration and expression of matrix metalloproteinases (MMPs), implying poor biological alterations. The diagnostic value of MAGDS was also validated in an external cohort (AUC = 0.886). The expression of key MAGs was validated in a murine model using RT-qPCR. Additionally, a competitive endogenous RNA network was constructed to reveal the potential posttranscriptional regulatory mechanisms.

Conclusions

We developed and validated a MAGDS model with the ability to accurately diagnose and characterize biological alterations in OA. The six key MAGs may also be latent targets for immunoregulatory therapy.