Improved prediction of knee osteoarthritis progression by genetic polymorphisms: the Arthrotest Study

Harmonizing hope: navigating the osteoarthritis melody through the CCL2/CCR2 axis for innovative therapeutic avenues

Osteoarthritis (OA) is characterized by a complex interplay of molecular signals orchestrated by the CCL2/CCR2 axis. The pathogenesis of OA has been revealed to be influenced by a multifaceted effect of CCL2/CCR2 signaling on inflammation, cartilage degradation, and joint homeostasis. The CCL2/CCR2 axis promotes immune cell recruitment and tips the balance toward degeneration by influencing chondrocyte behavior. Insights into these intricate pathways will offer novel therapeutic approaches, paving the way for targeted interventions that may redefine OA management in the future. This review article explores the molecular symphony through the lens of the CCL2/CCR2 axis, providing a harmonious blend of current knowledge and future directions on OA treatment. Furthermore, in this study, through a meticulous review of recent research, the key players and molecular mechanisms that amplify the catabolic cascade within the joint microenvironment are identified, and therapeutic approaches to targeting the CCL2/CCR axis are discussed.

Age-dependent genetic regulation of osteoarthritis: independent effects of immune system genes

OBJECTIVES

Osteoarthritis (OA) is a joint disease with a heritable component. Genetic loci identified via genome-wide association studies (GWAS) account for an estimated 26.3% of the disease trait variance in humans. Currently, there is no method for predicting the onset or progression of OA. We describe the first use of the Collaborative Cross (CC), a powerful genetic resource, to investigate knee OA in mice, with follow-up targeted multi-omics analysis of homologous regions of the human genome.

METHODS

We histologically screened 275 mice for knee OA and conducted quantitative trait locus (QTL) mapping in the complete cohort (> 8 months) and the younger onset sub-cohort (8-12 months). Multi-omic analysis of human genetic datasets was conducted to investigate significant loci.

RESULTS

We observed a range of OA phenotypes. QTL mapping identified a genome-wide significant locus on mouse chromosome 19 containing Glis3, the human equivalent of which has been identified as associated with OA in recent GWAS. Mapping the younger onset sub-cohort identified a genome-wide significant locus on chromosome 17. Multi-omic analysis of the homologous region of the human genome (6p21.32) indicated the presence of pleiotropic effects on the expression of the HLA - DPB2 gene and knee OA development risk, potentially mediated through the effects on DNA methylation.

CONCLUSIONS

The significant associations at the 6p21.32 locus in human datasets highlight the value of the CC model of spontaneous OA that we have developed and lend support for an immune role in the disease. Our results in mice also add to the accumulating evidence of a role for Glis3 in OA.

Carbohydrate sulfotransferases: a review of emerging diagnostic and prognostic applications

Carbohydrate sulfotransferases (CHST) catalyse the biosynthesis of proteoglycans that enable physical interactions and signalling between different neighbouring cells in physiological and pathological states. The study aim was to provide an overview of emerging diagnostic and prognostic applications of CHST. PubMed database search was conducted using the keywords "carbohydrate sulfotransferase" together with appropriate inclusion and exclusion criteria, whereby 41 publications were selected. Additionally, 40 records on CHST genetic and biochemical properties were hand-picked from UniProt, GeneCards, InterPro, and neXtProt databases. Carbohydrate sulfotransferases have been applied mainly in diagnostics of connective tissue disorders, cancer and inflammations. The lack of CHST activity was found in congenital connective tissue disorders while CHST overexpression was detected in different malignancies. Mutations of CHST3 gene cause skeletal dysplasia, chondrodysplasia, and autosomal recessive multiple joint dislocations while increased tissue expression of CHST11, CHST12 and CHST15 is an unfavourable prognostic factor in ovarian cancer, glioblastoma and pancreatic cancer, respectively. Recently, CHST11 and CHST15 overexpression in the vascular smooth muscle cells was linked to the severe lung pathology in COVID-19 patients. Promising CHST diagnostic and prognostic applications have been described but larger clinical studies and robust analytical procedures are required for the more reliable diagnostic performance estimations.

Genetic polymorphisms of Ca2+ transport proteins and molecular chaperones in mitochondria-associated endoplasmic reticulum membrane and non-alcoholic fatty liver disease

Background

Non-alcoholic fatty liver disease (NAFLD) is recognized to be closely associated with endoplasmic reticulum stress and mitochondrial dysfunction, while previous studies have emphasized the important role of calcium homeostasis from the mitochondria-associated endoplasmic reticulum membrane (MAM) in the endoplasmic reticulum and mitochondria. This article will assess the association between genetic polymorphisms of Ca2+ transport proteins and molecular chaperones in MAM and NAFLD risk.

Methods

A case-control study was conducted in a community of Nanjing, China during April to December 2020. 2701 subjects were enrolled and genotyped for 6 genetic variants in HSPA5 and ITPR2 genes. Logistic regression analysis was used to assess impact of these variants on NAFLD risk.

Results

After adjusting for age, gender, total cholesterol and glucose, we identified that HSPA5 rs12009 variant genotypes (recessive model: OR= 0.801, 95% CI= 0.652-0.986, P= 0.036), rs430397 variant genotypes (recessive model: OR= 0.546, 95% CI= 0.314-0.950, P= 0.032), and ITPR2 rs11048570 variant genotypes (recessive model: OR= 0.673, 95% CI= 0.453-0.999, P= 0.049) were associated with a reduced risk of NAFLD. Multivariate stepwise regression analysis indicated that gender, glucose, body mass index, triglycerides and favorable alleles were independent influencers of NAFLD (all P< 0.05). The area under the receiver operating characteristic curve was 0.764 (95% CI= 0.745-0.783, P< 0.001).

Conclusion

The variant genotypes of Ca2+ transport-associated genes HSPA5 (rs12009 and rs430397) and ITPR2 (rs11048570) might contribute to the reduction of the NAFLD risk in Chinese Han population, which can provide new insight into NAFLD pathogenesis.

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

Background

Early diagnosis of knee osteoarthritis (OA) is important in managing this disease, but such an early diagnostic tool is still lacking in clinical practice. The purpose of this study was to develop diagnostic models for early stage knee OA based on the first 2-year clinical course after the patient’s initial presentation in primary care and to identify whether these course factors had additive discriminative value over baseline factors.

Methods

We extracted eligible patients’ clinical and radiographic data from the CHECK cohort and formed the first 2-year course factors according to the factors’ changes over the 2 years. Clinical expert consensus-based diagnosis, which was made via evaluating patients’ 5- to 10-year follow-up data, was used as the outcome factor. Four models were developed: model 1, included clinical course factors only; model 2, included clinical and radiographic course factors; model 3, clinical baseline factors + clinical course factors; and model 4, clinical and radiographic baseline factors + clinical and radiographic course factors. All the models were built by a generalized estimating equation with a backward selection method. Area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (CI) were calculated for assessing model discrimination. Delong’s method compared AUCs.

Results

Seven hundred sixty-one patients with 1185 symptomatic knees were included in this study. Thirty-seven percent knees were diagnosed as OA at follow-up. Model 1 contained 6 clinical course factors; model 2: 6 clinical and 3 radiographic course factors; model 3: 6 baseline clinical factors combined with 5 clinical course factors; and model 4: 4 clinical and 1 radiographic baseline factors combined with 5 clinical and 3 radiographic course factors. Model discriminations are as follows: model 1, AUC 0.70 (95% CI 0.67–0.74); model 2, 0.74 (95% CI 0.71–0.77); model 3, 0.77 (95% CI 0.74–0.80); and model 4, 0.80 (95% CI 0.77–0.82). AUCs of model 3 and model 4 were slightly but significantly higher than corresponding baseline-factor models (model 3 0.77 vs 0.75, p = 0.031; model 4 0.80 vs 0.76, p = 0.003).

Conclusions

Four diagnostic models were developed with “fair” to “good” discriminations. First 2-year course factors had additive discriminative value over baseline factors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-021-02598-5.

Development of a model for predicting the 4-year risk of symptomatic knee osteoarthritis in China: a longitudinal cohort study

Objectives

We aimed to develop a model for predicting the 4-year risk of knee osteoarthritis (KOA) based on survey data obtained via a random, nationwide sample of Chinese individuals.

Methods

Data was analyzed from 8193 middle-aged and older adults included in the China Health and Retirement Longitudinal Study (CHARLS). The incident of symptomatic KOA was defined as participants who were free of symptomatic KOA at baseline (CHARLS2011) and diagnosed with symptomatic KOA at the 4-year follow-up (CHARLS2015). The effects of potential predictors on the incident of KOA were estimated using logistic regression models and the final model was internally validated using the bootstrapping technique. Model performance was assessed based on discrimination—area under the receiver operating characteristic curve (AUC)—and calibration.

Results

A total of 815 incidents of KOA were identified at the 4-year follow-up, resulting in a cumulative incidence of approximately 9.95%. The final multivariable model included age, sex, waist circumference, residential area, difficulty with activities of daily living (ADLs)/instrumental activities of daily living (IADLs), history of hip fracture, depressive symptoms, number of chronic comorbidities, self-rated health status, and level of moderate physical activity (MPA). The risk model showed good discrimination with AUC = 0.719 (95% confidence interval [CI] 0.700–0.737) and optimism-corrected AUC = 0.712 after bootstrap validation. A satisfactory agreement was observed between the observed and predicted probability of incident symptomatic KOA. And a simple clinical score model was developed for quantifying the risk of KOA.

Conclusion

Our prediction model may aid the early identification of individuals at the greatest risk of developing KOA within 4 years.

Risk scoring for time to end-stage knee osteoarthritis: data from the Osteoarthritis Initiative

OBJECTIVE

This study constructs a risk score for patients' progression to end-stage knee osteoarthritis (OA) within 4 years.

DESIGN

The Osteoarthritis Initiative (OAI) was a longitudinal study of the onset and progression of knee OA. Using a recent definition of end-stage knee OA, we implement interval-censored survival forests to select predictors of this endpoint. We fit an interval-censored Cox model for time to end-stage knee OA, using the selected predictors. The risk score is the Cox model's fitted linear combination of the nine selected baseline structural and symptomatic knee OA variables.

RESULTS

We fit our models on a training set of 2,701 patients, and we evaluate on an independent test set of 1,436 patients. On the test sample, we observe a concordance index of 0.86 between risk score and time to end-stage, AUC of 0.87 for predicting end-stage within 24, 36, and 48 months, and positive predictive values that increase with the risk score. This risk stratification algorithm could enrich clinical trial patient enrollment. By enrolling test sample patients with scores above a threshold, a trial could have included 91% of test set patients who reach end-stage within 4 years while only enrolling 45% of the test sample.

CONCLUSION

Using statistical methods, we construct and validate an interpretable risk score for time to end-stage knee OA. This score can help disease-modifying OA treatment developers to select candidates with the highest risk of fast-progressing knee OA.

Multifactor dimensionality reduction reveals a strong gene-gene interaction between STC1 and COL11A1 genes as a possible risk factor of knee osteoarthritis

Articular cartilage is an avascular tissue with a structure that allows it to support and cushion the overload of the surfaces in contact. It maintains its metabolic functions due to the contribution of different signaling pathways. However, several factors play a role in its deterioration, allowing to the development of osteoarthritis (OA), and one of the major factors is genetic. Our goal was to identify gene-gene interactions (epistasis) between five signaling pathways involved in the articular cartilage metabolism as possible indicators of OA risk. We applied the Multifactor-Dimensionality Reduction (MDR) method to identify and characterize the epistasis between 115 SNPs located in 73 genes related to HIF-1α, Wnt/β-catenin, cartilage extracellular matrix metabolism, oxidative stress, and uric acid transporters. Ninety three patients diagnosed with primary knee OA and 150 healthy controls were included in the study. Genotyping was performed with the OpenArray system, the statistical analysis was carried out with the STATA software v14, and epistasis was analyzed with the MDR software v3.0.2. The MDR analysis revealed that the best interaction model was between polymorphisms rs17786744 of the STC1 gene and rs2615977 of the COL11A1 gene, with an entropy value of 4.44%, CVC 8/10, OR 5.60, 95% CI 3.27-9.59, p < 0.0001. Under this interaction model, we identified high and low risk genotypes involved in OA development. Our results suggest complex interactions between STC1 and COL11A1 genes that might have an impact on genetic susceptibility to develop OA. Further studies are required to confirm it.

Gene-gene interactions of the Wnt/β-catenin signaling pathway in knee osteoarthritis

This study was designed to investigate whether genetic polymorphisms of the Wnt/β-catenin signaling pathway and its interactions are involved in the development of knee osteoarthritis (KOA). Patients with KOA (n = 131) and healthy individuals (n = 190) with different ancestry from two Mexican populations (Mexico City and Guadalajara City) were analyzed. Twenty-five SNPs from thirteen genes (WISP1, DKK1, SOST, FRZB, LRP1, LRP4, LRP5, LRP6, GSKB, ADAMTS5, GDF5, FMN2 and COL11A1) involved in the Wnt/β-catenin signaling pathway were genotyped. Genetic and allelic frequencies and gene-gene interactions were performed for this study. After adjusting for age, sex, BMI and admixture, significant associations were found for five SNPs in Mexico City: LRP6 rs12314259 (G/G genotype OR 0.22, P = 0.029; and G allele OR 0.48, P = 0.022), SOST rs851054 (C/T genotype OR 0.42, P = 0.027; and T allele OR 0.62, P = 0.026), FMN2 rs986690 (G/A genotype OR 0.42, P = 0.034; and A allele OR 0.50, P = 0.015), FRZB rs409238 (A/G genotype, OR 2.41, P = 0.022), and COL11A1 rs2615977 (A/C genotype OR 2.39, P = 0.024); no associations for Guadalajara City were found. With respect to gene-gene interactions, the pairwise interactions of WISP1-COL11A1, COL11A1-FRZB, FRZB-SOST and WISP1-FMN2 make it possible to visualize the synergistic or antagonistic effect of their genotypes or alleles in both populations. These results suggest that gene-gene interactions in the Wnt/β-catenin signaling pathway play a role in the etiology of KOA.

Prediction of midlife hand osteoarthritis in young men

OBJECTIVES

Improved prediction modeling in osteoarthritis (OA) may encourage risk reduction through calculation of individual and population lifetime risks. There are currently no prediction models for hand OA. Thus, we aimed to 1) develop a prediction model for hand OA in men and 2) to contrast its discriminative performance to a prediction model for lung cancer and chronic obstructive pulmonary disease (COPD).

METHODS

We included 40,118 men aged 18 years undergoing mandatory conscription in Sweden 1969-70. Incident hand OA and lung cancer/COPD were obtained from diagnostic codes in the Swedish National Patient Register 1987-2010, i.e., until subjects were 59 years of age. We studied the strongest candidate predictors from five domains; socioeconomic, local biomechanical, systemic, lifestyle-related and general health factors, using logistic regression with backward elimination of candidate predictors with P > 0.2 to determine final models. To avoid overfitting we used bootstrapping.

RESULTS

The strongest predictors for hand OA were body mass index (BMI), elbow flexor strength, systolic blood pressure, lower education and sleep problems. We observed excellent agreement between observed and predicted values, yet the discrimination was moderate (Area Under the Curve [AUC] = 0.62, 95% CI = 0.58-0.64). The discrimination in the prediction model for lung cancer/COPD was good (AUC = 0.74, 95% CI = 0.72-0.76).

CONCLUSION

This prediction model for hand OA was capable of discriminating between persons with and without hand OA to a similar extent that has been previously reported for knee OA. Still, prediction of OA is more challenging than for chronic pulmonary disease.

A Prediction Model for the 40-Year Risk of Knee Osteoarthritis in Adolescent Men

OBJECTIVE

To simplify the previously published Nottingham 12-year risk prediction model for knee osteoarthritis (OA) and examine whether it can be used to predict the 40-year risk of knee OA in young men.

METHODS

Our cohort included 40,118 men who were 18 years of age and had undergone military conscription in Sweden from 1969 to 1970. Diagnostic OA codes were obtained from the Swedish National Patient Register for persons registered from 1987 to 2010. The original Nottingham model included as predictors age, sex, body mass index (BMI), knee injury, occupational risk, and family history of OA, with a receiver operating characteristic area under the curve (AUC) of 0.70 (95% confidence interval [95% CI] 0.61-0.79) in the model development sample, and AUC 0.60 (95% CI 0.58-0.63) in an external validation sample. In our sample, we used predictors that were available only in adolescence (age, BMI, and knee injury) and evaluated the discrimination of the simplified model using AUC.

RESULTS

The AUC statistic of the modified knee OA model to predict 40-year risk was 0.60 (95% CI 0.59-0.61). Hence, using the reduced model, an 18-year-old man with a BMI of 30 and a knee injury would have 3 times the risk of developing knee OA within 40 years when compared to a man of similar age having a BMI of 25 and no knee injury (predicted risks 22% and 7%, respectively).

CONCLUSION

The 40-year risk of knee OA on individual and population levels can be predicted in 18-year-olds from a few easily measured covariates with moderate discrimination. The discrimination of this simplified model based on data available in adolescents was comparable to that of the full Nottingham model in middle-aged individuals.

What did we learn from 'omics' studies in osteoarthritis

PURPOSE OF REVIEW

'Omics' technologies developed for the massive analysis of the major biologically relevant molecules (genes, proteins, metabolites) have been applied to the study of osteoarthritis (OA) for more than a decade.

RECENT FINDINGS

'Omics' studies have undoubtedly contributed to increase the knowledge on pathogenic processes related with OA and have provided hundreds to thousands of molecules that might have a putative biomarker utility for this disease.

SUMMARY

This review describes the most recent 'omics' studies in OA research, their conclusions, and discuss those remaining challenges. Still many validation studies must be performed in large and well-characterized cohorts for the translation of the findings from 'omics' strategies to clinical applications. The development of tools for the intelligent integration of 'omics' data with clinical and imaging information is also mandatory to take full profit of the work that has been already performed.

Association of SNPs in the TIMP-2 gene and large artery atherosclerotic stroke in southern Chinese Han population

Tissue inhibitor of matrix metalloproteinase 2 (TIMP-2) regulates the extracellular matrix degradation, which involved in vascular remodeling and dysfunction, destabilization of atherosclerotic plaque and many other pathological processes. The rupture of atherosclerotic plaque is the trigger of Large artery atherosclerotic (LAA) stroke. We speculate that the Single nucleotide polymorphisms (SNPs) in TIMP-2 may have an association with LAA stroke. To prove this hypothesis, we conducted this case-control study. 250 LAA stroke patients and 250 healthy controls were collected for the analysis of TIMP-2 polymorphisms. Among six SNPs, we detected no deviation from Hardy-Weinberg equilibrium in control group. There was a significant difference in rs4789936 T allele frequency between patient and control groups (OR = 0.68, 95% CI = 0.51-0.91, P = 0.009), which means lower risk of LAA stroke. We observed the rs4789936 had a decreased risk of LAA stroke according to the codominant (OR = 0.64, 95% CI = 0.44-0.92, P = 0.026), dominant (OR = 0.62, 95% CI = 0.43-0.88, P = 0.008), overdominant (OR = 0.68, 95% CI = 0.48-0.98, P = 0.039), log-additive (OR = 0.68, 95% CI = 0.51-0.91, P = 0.009) models analyses. However, these findings could only validate under dominant model (OR = 0.65, 95% CI = 0.42-1.00, P = 0.049) after adjustment of gender and age. The results indicate a potential association between TIMP-2 variants and LAA stroke risk in southern Chinese Han population.

Development of a clinical prediction algorithm for knee osteoarthritis structural progression in a cohort study: value of adding measurement of subchondral bone density

Background

Risk prediction algorithms increase understanding of which patients are at greatest risk of a harmful outcome. Our goal was to create a clinically useful prediction algorithm for structural progression of knee osteoarthritis (OA), using medial joint space loss as a proxy; and to quantify the benefit of including periarticular bone mineral density (BMD) in the algorithm.

Methods

Participants were from the Osteoarthritis Initiative (OAI) Progression Cohort, with X-ray readings of medial joint space at 36- and 48-month visits, and a 30- or 36-month medial-to-lateral tibial BMD ratio (M:L BMD ratio) value. Loss of medial joint space was the outcome and clinically available factors associated with OA progression were employed in the base prediction algorithm, with M:L BMD ratio added to an enhanced prediction algorithm. The benefit of adding M:L BMD ratio was evaluated by change in area under the ROC curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

Results

Five hundred thirty-three participants were included; 51 (14%) had medial joint space loss; 47% were female; the mean (SD) age was 64.6 (9.2) years and BMI was 29.6 (4.8) kg/m². The base algorithm model included age, BMI, gender, recent injury, knee pain, and hand OA as predictors and had an AUC value of 0.65. The algorithm adding M:L BMD ratio had an AUC value of 0.73, and the AUC, NRI and IDI were all significantly improved (p ≤ 0.002).

Conclusions

This clinical prediction algorithm predicts structural progression in individuals with OA using only clinically available predictors supplemented by the M:L BMD ratio, a biomarker that could be made available at clinical sites.

Osteoarthritis year in review 2016: imaging

PURPOSE

The current narrative review covers original research related to imaging in osteoarthritis (OA) in humans published in English between April 1st 2015 and March 31st 2016, in peer reviewed journals available in Medline via PubMed (http://www.ncbi.nlm.nih.gov/pubmed/).

METHODS

Relevant studies in humans, subjectively decided by the authors, contributing significantly to the OA imaging field, were selected from an extensive Medline search using the terms "Osteoarthritis" in combination with "MRI", "Imaging", "Radiography", "X-rays", "Ultrasound", "Computed tomography", "Nuclear medicine", "PET-CT", "PET-MRI", "Scintigraphy", "SPECT". Publications were sorted according to relevance for the OA imaging research community with an emphasis on high impact special interest journals using the software for systematic reviews www.covidence.org.

RESULTS

An overview of newly published studies compared to studies reported previous years is presented, followed by a review of selected imaging studies of primarily knee, hip and hand OA focussing on (1) results for detection of OA and OA-related pathology (2) studies dealing with treatments and (3) studies focussing on prognosis of disease progression or joint replacement. A record high number of 1420 articles were published, among others, of new technologies and tools for improved morphological and pathophysiological understanding of OA-related changes in joints. Also, imaging data were presented of monitoring treatment effect and prognosis of OA progression, primarily using established radiographic, magnetic resonance imaging (MRI), and ultrasound (US) methods.

CONCLUSION

Imaging continues to play an important role in OA research, where several exciting new technologies and computer aided analysis methods are emerging to complement the conventional imaging approaches.

TIMP-2 SNPs rs7342880 and rs4789936 are linked to risk of knee osteoarthritis in the Chinese Han Population

This study aimed to investigate whether functional polymorphisms in the tissue inhibitors of metalloproteinase-2 (TIMP-2) gene are associated with susceptibility to knee osteoarthritis (OA) in the Chinese Han population. Six TIMP-2 single nucleotide polymorphisms (SNPs) were assayed using MassARRAY in 300 patients clinically and radiographically diagnosed with knee OA and in 428 controls. Allelic and genotypic frequencies were compared between groups. Logistic regression adjusting for age and gender was used to estimate risk associations between specific genotypes and knee OA by computing odds ratios (ORs) and 95% confidence intervals (95% CIs). We found that allele "A" in rs7342880 was significantly associated with increased risk of knee OA (OR = 1.44, 95%CI = 1.09-1.91, p = 0.035). In addition, in the over-dominant model, rs4789936 correlated with reduced risk of knee OA, adjusting for age and gender (OR = 0.69, 95%CI = 0.49-0.98, p = 0.036). Finally, rs7342880 correlated with increased risk of knee OA in females. This study provides evidence that TIMP-2 is a knee OA susceptibility gene in the Chinese population and a potential diagnostic and preventive marker for the disease.

Mitochondrial DNA haplogroups influence the risk of incident knee osteoarthritis in OAI and CHECK cohorts. A meta-analysis and functional study

Objective

To evaluate the influence of the mitochondrial DNA (mtDNA) haplogroups in the risk of incident knee osteoarthritis (OA) and to explain the functional consequences of this association to identify potential diagnostic biomarkers and therapeutic targets.

Methods

Two prospective cohorts contributed participants. The osteoarthritis initiative (OAI) included 2579 subjects of the incidence subcohort, and the cohort hip and cohort knee (CHECK) included 635, both with 8-year follow-up. The analysis included the association of mtDNA haplogroups with the rate of incident knee OA in subjects from both cohorts followed by a subsequent meta-analysis. Transmitochondrial cybrids harbouring haplogroup J or H were constructed to detect differences between them in relation to physiological features including specific mitochondrial metabolic parameters, reactive oxygen species production, oxidative stress and apoptosis.

Results

Compared with H, the haplogroup J associates with decreased risk of incident knee OA in subjects from OAI (HR=0.680; 95% CI 0.470 to 0.968; p<0.05) and CHECK (HR=0.728; 95% CI 0.469 to 0.998; p<0.05). The subsequent meta-analysis including 3214 cases showed that the haplogroup J associates with a lower risk of incident knee OA (HR=0.702; 95% CI 0.541 to 0.912; p=0.008). J cybrids show a lower free radical production, higher cell survival under oxidative stress conditions, lower grade of apoptosis as well as lower expression of the mitochondrially related pro-apoptotic gene BCL2 binding component 3 (BBC3). In addition, J cybrids also show a lower mitochondrial respiration and glycolysis leading to decreased ATP production.

Conclusions

The physiological effects of the haplogroup J are beneficial to have a lower rate of incident knee OA over time. Potential drugs to treat OA could focus on emulating the mitochondrial behaviour of this haplogroup.

A replication study and meta-analysis of mitochondrial DNA variants in the radiographic progression of knee osteoarthritis

OBJECTIVE

To conduct a replication study and meta-analysis involving the study of mtDNA variants in the radiographic progression of OA in different cohorts worldwide, including Cohort Hip and Cohort Knee (CHECK), the OA Initiative and a cohort from Spain.

METHODS

The influence of the haplogroups in the rate of radiographic progression at 96 months in 431 subjects from CHECK was assessed in terms of Kellgren and Lawrence (KL) grade. Progression was defined as a change from KL ⩾ 1 at baseline to any higher grade during the follow-up. Extended Cox proportional hazard models were used to analyse the influence of mtDNA variants in the rate of radiographic knee OA progression. A subsequent meta-analysis of 1603 subjects following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted to combine the data of individual studies. A sensitivity analysis was performed to validate the stability of the results.

RESULTS

CHECK subjects carrying the haplogroup T showed the lowest rate of radiographic knee OA progression [hazard ratio (HR) 0.645 (95% CI 0.419, 0.978); P < 0.05]. When pooled, subjects within the superhaplogroup JT showed the same trend [HR 0.707 (95% CI 0.501, 0.965); P < 0.05]. BMI [HR 1.046 (95% CI 1.018, 1.073); P < 0.05] and bilateral OA [HR 2.266 (95% CI 1.733, 2.954); P < 0.05] at baseline are risk factors for radiographic knee OA progression as well. In the meta-analysis there was a reduced rate of radiographic progression in subjects with haplogroup T [HR 0.612 (95% CI 0.454, 0.824); P = 0.001] or in the superhaplogroup JT [HR 0.765 (95% CI 0.624, 0.938); P = 0.009]. Sensitivity analysis revealed that the results were robust.

CONCLUSION

The mtDNA variants in the superhaplogroup JT associate with a reduced rate of radiographic OA progression. The mtDNA polymorphisms in the superhaplogroup JT emerge as potential complementary genetic biomarkers for disease progression.

Lysophosphatidylcholines to phosphatidylcholines ratio predicts advanced knee osteoarthritis

OBJECTIVE

To identify novel biomarker(s) for predicting advanced knee OA.

METHODS

Study participants were derived from the Newfoundland Osteoarthritis Study and the Tasmania Older Adult Cohort Study. All knee OA cases were patients who underwent total knee replacement (TKR) due to primary OA. Metabolic profiling was performed on fasting plasma. Four thousand and eighteen plasma metabolite ratios that were highly correlated with that in SF in our previous study were generated as surrogates for joint metabolism.

RESULTS

The discovery cohort included 64 TKR cases and 45 controls and the replication cohorts included a cross-sectional cohort of 72 TKR cases and 76 controls and a longitudinal cohort of 158 subjects, of whom 36 underwent TKR during the 10-year follow-up period. We confirmed the previously reported association of the branched chain amino acids to histidine ratio with advanced knee OA (P = 9.3 × 10(-7)) and identified a novel metabolic marker-the lysophosphatidylcholines (lysoPCs) to phosphatidylcholines (PCs) ratio-that was associated with advanced knee OA (P = 1.5 × 10(-7)) after adjustment for age, sex and BMI. When the subjects of the longitudinal cohort were categorized into two groups based on the optimal cut-off of the ratio of 0.09, we found the subjects with the ratio ⩾0.09 were 2.3 times more likely to undergo TKR than those with the ratio <0.09 during the 10-year follow-up (95% CI: 1.2, 4.3, P = 0.02).

CONCLUSION

We identified the ratio of lysoPCs to PCs as a novel metabolic marker for predicting advanced knee OA. Further studies are required to examine whether this ratio can predict early OA change.