Abstract
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.
Keywords: osteoarthritis, meta-analysis, knee, genetics, molecular biology
Rheumatology key messages
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Results from the Cohort Hip and Cohort Knee cohort replicate previous findings from the Osteoarthritis Initiative.
Specific mtDNA polymorphisms in the superhaplogroup JT associate with a lower risk of OA progression.
The mtDNA haplogroups emerge as potential complementary genetic biomarkers for disease progression in OA.
Introduction
OA is a chronic progressive disorder involving movable joints that is characterized by cell stress and extracellular matrix degradation initiated by micro- and macro-injury that activates maladaptive repair responses including pro-inflammatory pathways of innate immunity. The disease manifests first as a molecular derangement (abnormal tissue metabolism) followed by anatomic and/or physiologic derangements (characterized by cartilage degradation, bone remodelling, osteophyte formation, joint inflammation and loss of normal joint function) that can culminate in illness [1]. OA is also the leading cause of work incapacitation and one of the most common reasons to visit primary care physicians. The prevalence of the disease increases with age and is expected to become a major health care concern in the near future as life expectancy increases [2].
The identification of risk factors that accelerate disease progression is critical since these factors could be potential targets for disease modification [3]. Therefore, from a point of view of prevention, it is important to diagnose the disease at an early stage in large and well-characterized prospective cohorts that permit identification of prognostic factors that predict the course of OA [4]. In this sense, both the OA Initiative (OAI) and Cohort Hip and Cohort Knee (CHECK) cohorts stand out.
Although the pathogenesis of the disease is still unclear due to the interaction of modifiable and non-modifiable factors, it is widely accepted that genetics plays a main role in its development [5] and risk prediction tools combining both clinical and genetic information have been proposed [6–8]. Also, during the last few years mitochondria and the mtDNA haplogroups have emerged as key factors in the pathogenesis of OA [2, 9].
The mtDNA haplogroups have been shaped by climate selection when humans migrated into colder climates, resulting in maternally inherited mutations in the mtDNA acquired throughout human history [10]. Each of the mtDNA haplogroups harbours specific polymorphisms in the mtDNA sequence that influence both the behaviour of mitochondria [11] and the way in which the nuclear genome behaves [12]. These mtDNA variants influence our health today, as some of them have been associated with degenerative disorders [13] and metabolic diseases [14]. They have even been linked to increased longevity [15] and lower prevalence of OA [16, 17].
Recent studies have also shown significant associations of specific mtDNA variants with a lower rate of radiographic progression over time in different study cohorts worldwide, such as the OAI [18] and one Spanish cohort [19]. Hence, in an attempt to ascertain the correlation of mtDNA haplogroups and the rate of radiographic progression of OA, in this work we aim to perform a replication study of mtDNA haplogroups on the rate of radiographic progression at 96 months in subjects from CHECK. In addition, a meta-analysis of radiographic progression of OA was subsequently conducted to synthetize the information obtained from individual studies involving subjects from OAI, CHECK and one Spanish cohort.
Methods
Radiographic progression study in subjects from CHECK
Participants
From October 2002 to September 2005 the CHECK cohort registered 1002 participants with pain and/or stiffness of the knee and/or hip; these individuals are to be followed prospectively for a period of at least 10 years. The study was approved by the medical ethics committees of the 12 participant centres, and all participants gave their written informed consent according to the Declaration of Helsinki before entering the study. Individuals were eligible if they had pain or stiffness of the knee or hip, were between 45 and 65 years of age and had not yet consulted their physician for these symptoms or the first consultation was within 6 months before entry [4].
For the present study we included longitudinal data in terms of the Kellgren and Lawrence (KL) grade of those CHECK participants that met the eligibility criteria for a study of radiographic progression monitored at baseline and 2, 5 and 8 years. Participants with missing data were excluded from the analysis. Knee radiographs were made in a weight-bearing anteroposterior view, semi-flexed, and were scored by five trained observers according to KL grade, in a paired fashion, with known sequence.
Radiographic progression criteria
Radiographic progression was defined on the joint level (knees separately) following the proposed criteria for the CHECK cohort according to the early stage OA of these subjects [20]. Present radiographic knee OA at baseline was defined as a KL grade of 1, therefore radiographic progression was defined as an increase of ⩾1 KL grade for the left and/or right knee [20]. Since radiographic progression was analysed in those subjects that did show radiographic knee OA at baseline (KL grade ⩾1 for the left and/or right knee), we thus analysed 431 subjects from the entire cohort.
mtDNA haplogroup genotyping
The mtDNA haplogroups were assigned in 431 CHECK participants following a previously described assay [21]. Briefly, a multiplex PCR was performed to amplify six mtDNA fragments that contain the informative single-nucleotide polymorphisms (SNPs) that characterize the most common Caucasian mtDNA haplogroups (H, UK, J and T), as well as the less common ones (<5%) pooled into a group called Others. The resulting PCR fragments were purified and analysed by single-base extension assay to further visualize the informative SNPs after loading the purified single-base extension product into an ABI 3130XL genetic analyser (Applied Biosystems, Foster City, CA, USA). The assigned mtDNA haplogroups were verified by direct sequencing, in 30% of the samples, of regions that include key SNPs described in PhyloTree (http://www.phylotree.org).
Sample size and statistical analysis
The available sample size of 431 subjects allows the probability of OA progression to be estimated with ±4.7% precision using a 95% CI. In addition, protective hazard ratios (HRs) ⩽0.49 associated with mtDNA haplogroups with a frequency of at least 10% in the population will be detected as statistically significant with 80% power using a significance level of 0.05. This assumes a censoring probability of 60%. All the approaches were also performed analysing the mtDNA clusters (or superhaplogroups), which consisted of pooled mtDNA haplogroups that share a common phylogenetic origin [10].
All the statistical analyses were performed using IBM-SPSS software, release 19 (IBM, Armonk, NY, USA) and R software, version 3.1.2 (R Foundation for Statistical Computing, Vienna, Austria). All comparisons were two-sided, with P-values <0.05 defined as statistically significant.
To avoid potential biases associated with the use of standard survival analysis in this context, interval-censored data analysis methods were used. Turnbull’s extension of the Kaplan–Meier curve to interval-censored data was used to estimate the cumulative probability of radiographic knee OA progression over time according to the mtDNA haplogroups. An extended Cox proportional hazard model was used for multivariate analysis adjusting for the confounder effects of gender, age, BMI, WOMAC (total) and bilateral OA (KL grade ⩾1) at baseline. Statistical significance was tested by CIs for the HRs by means of resampling methods. CIs were obtained using the bootstrap methodology (1000 replicates) with improved percentile method.
The multivariate analysis was performed by comparisons between haplogroups, considering the most common haplogroup H (or mtDNA cluster HV) as the reference group. Therefore, in order to introduce haplogroups (or mtDNA clusters) in the models, dummy coding was used with the haplogroup H (or mtDNA cluster HV) as the reference group. Since there was no interest in all possible pairwise comparisons, no additional adjusting for multiple comparisons was done.
Meta-analysis
The meta-analysis conducted in this work was developed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. In order to find relevant studies to include in the meta-analysis we performed a computerized search strategy.
Accordingly, we identified relevant studies published in English or Chinese by a computerized search via two databases, PubMed and Web of Science. In addition, non-published studies were also searched in the OpenSIGLE database [22]. The search strategy involved the use of the following key words: OA and (mtDNA or mitochondrial DNA) and (haplogroup or haplotype or genotype or genetic predisposition or SNP or polymorphism or variant or genetic susceptibility or genetics or allele) and (progression or radiographic progression).
We only selected studies that met the following inclusion criteria: evaluating the association between mtDNA haplogroups and the rate of radiographic OA progression over time and having sufficient data provided to calculate HRs with their corresponding 95% CIs. Those studies analysing the correlation between mtDNA haplogroups and the prevalence/incidence/risk of OA as well as those studies analysing other mtDNA mutations with progression were excluded.
The following data were extracted from each study: name of the author, year of publication, sample size, country, ethnicity, age of subjects, type of study, type of OA, progression criteria, genotyping method, confounder variables and conclusion of the study.
The random-effects model described by DerSimonian and Laird [23] was used to calculate a summary statistic and its 95% CI. The adjusted HR was used as the effect size measure for the association between mtDNA haplogroups and OA progression. Meta-analysis results were presented on a forest plot graph. To explore heterogeneity, the I2 index was computed. Meta-analysis was carried out using the Meta package of the R software program (version 3.2.2). A two-tailed P-value <0.05 was considered to be significant.
Meta-analysis was planned to be performed on k = 3 studies, with an estimated statistical power of 90.4% to detect as statistically significant an HR ⩽0.5 associated to haplogroup T with a P = 0.05 two-tailed significance level. In order to validate the stability of the results in the meta-analysis we additionally performed a sensitivity analysis by removing individual studies each time.
Results
mtDNA haplogroups and radiographic progression in CHECK subjects
No significant differences were detected in the distribution of age, gender, BMI and bilateral OA among patients with different haplogroups; however, significant differences in the WOMAC index (Physical function and total WOMAC) at baseline were detected (P = 0.037) (Table 1).
Table 1.
Demographic and clinical characteristics of the CHECK cohort at baseline
| mtDNA haplogroups | H [n = 182 (42.2%)] | UK [n = 90 (20.9%)] | T [n = 53 (12.3%)] | J [n = 44 (10.2%)] | Othersa [n = 62 (14.4%)] | P-value | Total (n = 431) |
|---|---|---|---|---|---|---|---|
| Age at baseline, mean (s.d.), years | 56.1 (5.1) | 56.6 (4.8) | 56.2 (5.4) | 56.9 (5.5) | 55.2 (4.8) | 0.397b | 56.2 (5.1) |
| Gender, n (%) | 0.522c | ||||||
| Male | 37 (20.3) | 18 (20.0) | 12 (22.6) | 5 (11.4) | 9 (14.5) | 81 (18.8) | |
| Female | 145 (79.7) | 72 (80.0) | 41 (77.4) | 39 (88.6) | 53 (85.5) | 350 (81.2) | |
| BMI, mean (s.d.), kg/m2 | 27.1 (4.8) | 26.8 (3.9) | 26.7 (4.8) | 26.4 (4.1) | 26.3 (3.6) | 0.902b | 26.8 (4.4) |
| WOMAC, mean (s.d.) | |||||||
| Pain | 5.1 (3.3) | 5.5 (3.6) | 4.9 (3.0) | 5.6 (3.8) | 3.9 (3.0) | 0.057b | 5.0 (3.4) |
| Stiffness | 2.6 (1.6) | 2.8 (1.6) | 2.6 (1.7) | 3.2 (1.7) | 2.3 (1.6) | 0.156b | 2.6 (1.6) |
| Physical function | 15.3 (11.4) | 17.9 (11.7) | 14.4 (11.5) | 18.7 (12.0) | 13.4 (10.6) | 0.037b | 15.8 (11.5) |
| Total | 22.9 (15.4) | 26.3 (16.2) | 21.9 (14.9) | 27.0 (15.9) | 19.6 (14.4) | 0.037b | 23.4 (15.5) |
| Bilateral OA at baseline (KL ≥ 1), n (%) | 93 (51.1) | 49 (54.4) | 27 (50.9) | 19 (43.2) | 34 (54.8) | 0.768c | 222 (51.5) |
Significant P-values are in bold.
The group Others includes mtDNA variants with a frequency <5%.
Kruskal–Wallis non-parametric test for comparison between mtDNA haplogroups.
Chi-square test.
The cumulative probability of radiographic knee OA progression at 96 months was 65.8%. After adjusting for age, gender, BMI, total WOMAC and bilateral OA at baseline, subjects with the haplogroup T showed the lowest rate of radiographic knee OA progression over time, 52.8% [HR 0.645 (95% CI 0.419, 0.978); P < 0.05]. In addition, both BMI [HR 1.046 (95% CI 1.018, 1.073); P < 0.05] and bilateral knee OA [HR 2.266 (95% CI 1.733, 2.954); P < 0.05] at baseline were risk factors for radiographic progression during the follow-up period (Table 2).
Table 2.
Cumulative probability of OA progression in CHECK patients according to mtDNA haplogroups and clusters
| Variables | Cumulative knee OA progression at 96 months, n (%)a | Adjusted HR (95% CIb) |
|---|---|---|
| Gender (male) | 0.847 (0.580, 1.172) | |
| Age | 1.018 (0.993, 1.045) | |
| BMI | 1.046 (1.018, 1.073*) | |
| WOMAC (total) | 1.005 (0.997, 1.013) | |
| Bilateral OA at baseline | 2.266 (1.733, 2.954*) | |
| mtDNA haplogroups (n = 431) | ||
| H (n = 182) | 124 (68.1) | 1 |
| UK (n = 90) | 62 (68.8) | 0.927 (0.675, 1.276) |
| T (n = 53) | 28 (52.8) | 0.645 (0.419, 0.978*) |
| J (n = 44) | 25 (56.8) | 0.776 (0.507, 1.218) |
| Othersc (n = 62) | 43 (69.3) | 0.979 (0.682, 1.395) |
| Gender (male) | 0.848 (0.595, 1.229) | |
| Age | 1.018 (0.994, 1.045) | |
| BMI | 1.046 (1.017, 1.072*) | |
| WOMAC (total) | 1.005 (0.997, 1.013) | |
| Bilateral OA at baseline | 2.257 (1.730, 2.940*) | |
| mtDNA clusters (n = 431) | ||
| HV (n = 202) | 138 (68.3) | 1 |
| KU (n = 90) | 62 (68.8) | 0.935 (0.678, 1.300) |
| JT (n = 97) | 53 (54.6) | 0.707 (0.501, 0.965*) |
| Others (n = 42) | 29 (69.0) | 1.017 (0.654, 1.492) |
Cumulative knee OA progression rate from baseline to follow-up.
CIs for the HRs obtained using the bootstrap methodology by the improved percentile method.
The group Others includes mtDNA variants with a frequency <5%. *Statistical significance (in bold) declared at P ≤ 0.05.
The analysis of the mtDNA clusters showed the same trend. Subjects in the mtDNA cluster JT had the lowest rate of radiographic progression, 54.6% [HR 0.707 (95% CI 0.501, 0.965); P < 0.05]. As for the above described analysis, both BMI [HR 1.046 (95% CI 1.017, 1.072); P < 0.05] and bilateral OA [HR 2.257 (95% CI 1.730, 2.940); P < 0.05] at baseline remained significant as risk factors after mtDNA cluster analysis (Table 2).
Meta-analysis
The search process identified a total of 11 non-duplicated papers and no unpublished articles. After reading the titles and abstracts, only three papers remained for further full-text analysis. Finally, two papers were selected for meta-analysis after exclusion due to overlapping patients. In addition, we included in the meta-analysis the data presented in this work.
The included studies (Table 3) consisted of study cohorts of Caucasian subjects, both prospective and retrospective, in which the influence of the mtDNA haplogroups and/or clusters in the radiographic progression of OA was analysed. Progression criteria slightly differed depending on the cohort analysed. In subjects from the very early OA CHECK cohort, progression was defined as a change from KL grade 1 to any higher grade [20] during 96 months; in subjects from the OAI, progression was defined as a change from KL grade ⩾2 to any higher grade [24]. The Spanish cohort is the only retrospective cohort and the progression criterion was defined as a change from KL grade 1 to any higher grade during at least 36 months between visits.
Table 3.
Characteristics of studies included in the meta-analysis
| Reference | Year | Sample size | Country | Ethnicity | Mean age, years | Type of study | Type of OA | Progression criteria | Genotyping method | Controlled confounder variables | Conclusion |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Soto-Hermida et al. [18] | 2014 | 891 | USA | Caucasian | 62 | Progression, prospective at 48 months | Knee OA | Change from KL grade 2 to any higher grade | SBE and PCR/RFLP | Gender, age, BMI, previous surgery, worst knee at baseline | Haplogroup T associates with decreased risk |
| Soto-Hermida et al. [19] | 2015 | 281 | Spain | Caucasian | 62 | Progression, retrospective, at least 36 months between visits | Hip/knee OA | Change from KL grade 1 to any higher grade | SBE and PCR/ RFLP | Gender, age, BMI | Cluster JT associates with decreased risk |
| Current study | 2016 | 431 | Netherlands | Caucasian | 56 | Progression, prospective at 96 months | Knee OA | Change from KL grade 1 to any higher grade | SBE and PCR/RFLP | Gender, age, BMI, WOMAC, bilateral OA | Haplogroup T and cluster JT associate with decreased risk |
RFLP: restriction fragment length polymorphism; SBE: single-base extension.
These studies generated information for 1603 subjects to analyse the influence of mtDNA haplogroup T and mtDNA cluster JT in the risk of radiographic OA progression over time.
No between-study heterogeneity was detected for any of the mtDNA variants analysed (haplogroup T and cluster JT) (I2 = 0%, P = 0.702 for haplogroup T; I2 = 0%, P = 0.833 for cluster JT) using the random effects model. The results obtained showed that the mtDNA haplogroup T [HR 0.612 (95% CI 0.454, 0.824); P = 0.001] (Fig. 1A) and cluster JT [HR 0.765 (95% CI 0.624, 0.938); P = 0.009] (Fig. 1B) significantly associate with a decreased risk of radiographic progression over time.
Fig. 1.
Rate of radiographic OA progression of mtDNA haplogroup T and cluster JT
(A) Forest plot showing the meta-analysis of the association between mtDNA haplogroup T and the rate of radiographic OA progression. The adjusted HR for potential confounders is used as the effect measure. (B) Forest plot showing the meta-analysis of the association between mtDNA superhaplogroup JT and the rate of radiographic OA progression. The adjusted HR for potential confounders is used as the effect measure.
The sensitivity analysis was performed by removing one study at each time. For the haplogroup T, removing any study does not impact on the significance of the results, with HRs (95% CIs) ranging from 0.581 (0.383, 0.883) to 0.660 (0.466, 0.935). For mtDNA cluster JT, only by removing the study of CHECK did the results borderline on statistical significance [HR 0.804 (95% CI 0.622, 1.042); P = 0.099], while omitting the study of the OAI [HR 0.735 (95% CI 0.563, 0.961); P = 0.024] and Spain [HR 0.758 (95% CI 0.604, 0.951); P = 0.017] cohorts the results remained significant.
Discussion
In this article we report on a replication study addressing the influence of mtDNA haplogroups in the radiographic OA progression in the CHECK cohort. In addition, a subsequent meta-analysis consisted of data from three independent studies of different well-characterized cohorts worldwide, including the OAI, CHECK and Spanish cohorts.
The three cohorts analysed in this study are geographically different but consisted of Caucasian subjects. Both OAI and CHECK are prospective cohorts and focus on the early phase of OA, although CHECK represents participants in an even earlier state of the disease [4] whereby the progression criteria [20] slightly differ from those proposed by Felson et al. [24] in subjects of the OAI; the Spanish cohort is retrospective, with a minimum between-visit interval not <36 months. The individual results of these studies showed that mtDNA variants in the superhaplogroup JT associate with a lower rate of radiographic progression, with the haplogroup T being the protective factor in the OAI [18] and CHECK cohorts and the mtDNA cluster JT being the protective factor against radiographic progression in the Spanish [19] and CHECK cohorts. The results of the meta-analysis indicate that the associations are likely robust and reveal that subjects carrying the haplogroup T or belonging to the mtDNA cluster JT show a lower cumulative probability of radiographic OA progression over time in terms of KL grade.
Involvement of the mtDNA haplogroups in the context of OA is not new. Recent studies revealed that mtDNA variants in the superhaplogroup JT associate with a decreased risk of knee and/or hip OA in different geographic populations [16, 25]; variants into this superhaplogroup also correlate with lower serum levels of type II collagen biomarkers [26] and metalloproteinases [27] as well as with higher telomere length and lower nitric oxide production in articular chondrocytes [28]. Also, Asian haplogroup B4 has been described as a protective factor for the prevalence of OA in a population from southern China [17]. In contrast, a recent study by Hudson et al. [29] found no evidence of an association between mtDNA variants and the risk of OA; although this may seem a discrepancy, the main point that could clarify this is the fact that control subjects used in the above-mentioned study, although very large, are population-based controls with only symptomatic information and without radiographic data. The discrepancy between radiographic signs and OA symptoms is well documented and up to 50% of OA patients without joint symptoms may have radiographic damage [30]. This could be one of the reasons why previous associations involving other genetic polymorphisms described in OA, such as rs143383 of the GDF5 gene or rs11842874 of the MCF2L gene, failed to be replicated at genome-wide significance levels (P ⩽ 5.0 × 10−8) using these population-based controls [31].
mtDNA haplogroups J and T are considered sister haplogroups that share a set of common uncoupling polymorphisms [10, 32] that make them biochemically different from other mitochondrial variants, especially haplogroup H [33, 34]. This could explain the association of the superhaplogroup JT with the lower rate of radiographic progression after meta-analyses of three independent cohorts. The genetic composition of this superhaplogroup alters the behaviour of mitochondria as well as the mitochondria–nuclear interactions when compared with the most common and energy-efficient haplogroup H. Lower maximal oxygen uptake [34], lower mtDNA damage [35], reduced mitochondrial reactive oxygen species generation [36], decreased performance in the oxidative phosphorylation system [37], higher capacity to cope with oxidative stress [38], alteration of the expression pattern of nuclear genes [39, 40], including some cytokines such as the IL-6 [41], and increased lactate production [42] are some of the functional consequences related to the genetic composition of the superhaplogroup JT and other OA-protective mtDNA variants [17].
Some of these above-mentioned features were analysed through the design and use of transmitochondrial cybrids, indicating that mitochondrial genetic composition alters both the mitochondrial function and the intracellular mitochondrial signals [42]. In-depth sequencing of the entire mtDNA in subjects from these cohorts will provide a more detailed map of the mitochondrial polymorphisms involved in the progression of OA.
Several studies supported a key role of the mitochondria in the pathogenesis of OA [2, 9, 43]. The results presented herein demonstrate that mtDNA variants in the superhaplogroup JT significantly reduce the rate of radiographic OA progression and, despite the fact that only three cohorts were combined, the results obtained were robust. The three cohorts are well-characterized and constructed with rigorous methodology in which patients were evaluated using objective methods. This should help minimize information biases and strengthen the final conclusions of the study.
In summary, the findings described in this study are of special interest because the results of CHECK replicate previous associations involving the haplogroup T with the lower rate of radiographic progression in the OAI cohort and also point to the mtDNA variants as potential complementary genetic OA biomarkers, as they could improve the identification of patients predisposed to rapid OA progression.
Acknowledgements
We would like to thank the participants of the three cohorts described in this work: CHECK, Osteoarthritis Initiative (OAI) and Spanish participants, as well as principal investigators, co-investigators and staff of OAI, CHECK and Spain. The OAI is a public–private partnership comprised of five contracts (N01-AR-2-2258, N01-AR-2-2259, N01-AR-2-2260, N01-AR-2-2261, N01-AR-2-2262) funded by the National Institutes of Health (NIH), a branch of the Department of Health and Human Services, and conducted by the OAI Study Investigators. Private funding partners include Pfizer, Novartis, Merck and GlaxoSmithKline. Private sector funding for the OAI is managed by the Foundation for the National Institutes of Health. This article was prepared using an OAI public use data set and does not necessarily reflect the opinions or views of the OAI investigators, the NIH or the private funding partners. The CHECK study is funded by the Dutch Arthritis Association. It is led by a steering committee comprising 16 members with expertise in different fields of OA. It is chaired by Professor J.W.J. Bijlsma and coordinated by J. Wesseling. The following institutions are involved: Erasmus Medical Center Rotterdam; Kennemer Gasthuis Haarlem; Leiden University Medical Center; Maastrich University Medical Center; Martini Hospital Groningen/Allied Health Care Center for Rheum and Rehabilitation Groningen; Medical Spectrum Twente Enschede/Ziekenhuisgroep Twente Almelo; Reade, formerly Jan van Breemen Institute/VU Medical Center Amsterdam; St Maartens-kliniek Nijmegen; University Medical Center Utrecht and Wilhelmina Hospital Assen. The Proteomics Unit belongs to ProteoRed (PRB2-ISCIII), supported by grant PT13/000, with a contribution of funds from FEDER (European Community). I.R.P. is supported by Contrato Miguel Servet-Fondo de Investigación Sanitaria (CP12/03192).
Funding: This study was supported by grants from Fondo de Investigación Sanitaria CIBERCB06/01/0040-Spain, RETIC-RIER-RD12/0009/0018 and PI14/01254, integrated in the National Plan for Scientific Program, Development and Technological Innovation 2013-2016 and funded by the ISCIII, General Subdirection of Assessment and Promotion of Research, European Regional Development Fund (FEDER) ‘A way of making Europe’.
Disclosure statement: The authors have declared no conflicts of interest.
Footnotes
Francisco J. Blanco and Ignacio Rego-Pérez contributed equally to this study.
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