Multivariable modeling of biomarker data from the phase 1 Foundation for the NIH Osteoarthritis Biomarkers Consortium

Sexual dimorphism in peri-articular tissue anatomy - More keys to understanding sex-differences in osteoarthritis?

Objective

Osteoarthritis prevalence differs between women and men; whether this is the result of differences in pre-morbid articular or peri-articular anatomical morphotypes remains enigmatic. Albeit sex within humans cannot be reduced to female/male, this review focusses to the sexual dimorphism of peri-articular tissues, given lack of literature on non-binary subjects.

Methods

Based on a Pubmed search and input from experts, we selected relevant articles based on the authors' judgement of relevance, interest, and quality; no "hard" bibliometric measures were used to evaluate the quality or importance of the work. Emphasis was on clinical studies, with most (imaging) data being available for the knee and thigh.

Results

The literature on sexual dimorphism of peri-articular tissues is reviewed: 1) bone size/shape, 2) subchondral/subarticular bone, 3) synovial membrane and infra-patellar fad-pad (IPFP), 4) muscle/adipose tissue, and 5) peri-articular tissue response to treatment.

Conclusions

Relevant sex-specific differences exist for 3D bone shape and IPFP size, even after normalization to body weight. Presence of effusion- and Hoffa-synovitis is associated with greater risk of incident knee osteoarthritis in overweight women, but not in men. When normalized to bone size, men exhibit greater muscle, and women greater adipose tissue measures relative to the opposite sex. Reduced thigh muscle specific strength is associated with incident knee osteoarthritis and knee replacement in women, but not in men. These observations may explain why women with muscle strength deficits have a poorer prognosis than men with similar deficits. A "one size/sex fits all" approach must be urgently abandoned in osteoarthritis research.

Quantitative Cartilage T2 and T1rho Mapping: Is There a Clinical Role? From the AJR Special Series on Quantitative Imaging

Despite more than 20 years of development, the MRI-based cartilage compositional biomarkers T2 and T1rho have not been routinely applied in clinical practice. This review examines these measures' historical development and frames the challenges in the application of these quantitative imaging tools to the care of patients with cartilage injury and osteoarthritis using the hierarchical model of efficacy proposed by Fryback and Thornbury. T2 and T1rho have been validated for the evaluation of early compositional and structural changes in cartilage extracellular matrix. Yet, these biomarkers lack direct correlation with pain or function loss, lack standardization of methods for acquisition and analysis, and have a limited role in guiding therapeutic management given the absence of effective disease-modifying osteoarthritis drugs. These issues present significant challenges in the path to the biomarkers' future implementation in clinical care. Nonetheless, these MRI-based cartilage compositional biomarkers provide an essential tool for musculoskeletal research and can provide important information on the biophysical properties of cartilage that will continue to contribute to our understanding of cartilage injury and osteoarthritis pathogenesis.

30 Years of MRI-based cartilage & bone morphometry in knee osteoarthritis: From correlation to clinical trials

OBJECTIVE

The first publication on morphometric analysis of articular cartilage using magnetic resonance imaging (MRI) in 1994 set the scene for a game change in osteoarthritis (OA) research. The current review highlights milestones in cartilage and bone morphometry, summarizing the rapid progress made in imaging, its application to understanding joint (patho-)physiology, and its use in interventional clinical trials.

METHODS

Based on a Pubmed search of articles from 1994 to 2023, the authors subjectively selected representative work illustrating important steps in the development or application of magnetic resonance-based cartilage and bone morphometry, with a focus on studies in humans, and on the knee. Research on OA-pathophysiology is addressed only briefly, given length constraints. Compositional and semi-quantitative assessment are not covered here.

RESULTS

The selected articles are presented in historical order as well as by content. We review progress in the technical aspects of image acquisition, segmentation and analysis, advances in understanding tissue growth, physiology, function, and adaptation, and a selection of clinical trials examining the efficacy of interventions on knee cartilage and bone. A perspective is provided of how lessons learned may be applied to future research and clinical management.

CONCLUSIONS

Over the past 30 years, MRI-based morphometry of cartilage and bone has contributed to a paradigm shift in understanding articular tissue physiology and OA pathophysiology, and to the development of new treatment strategies. It is likely that these technologies will continue to play a key role in the development and (accelerated) approval of therapy, potentially targeted to different OA phenotypes.

A perspective on the evolution of semi-quantitative MRI assessment of osteoarthritis: Past, present and future

OBJECTIVE

This perspective describes the evolution of semi-quantitative (SQ) magnetic resonance imaging (MRI) in characterizing structural tissue pathologies in osteoarthritis (OA) imaging research over the last 30 years.

METHODS

Authors selected representative articles from a PubMed search to illustrate key steps in SQ MRI development, validation, and application. Topics include main scoring systems, reading techniques, responsiveness, reliability, technical considerations, and potential impact of artificial intelligence (AI).

RESULTS

Based on original research published between 1993 and 2023, this article introduces available scoring systems, including but not limited to Whole-Organ Magnetic Resonance Imaging Score (WORMS) as the first system for whole-organ assessment of the knee and the now commonly used MRI Osteoarthritis Knee Score (MOAKS) instrument. Specific systems for distinct OA subtypes or applications have been developed as well as MRI scoring instruments for other joints such as the hip, the fingers or thumb base. SQ assessment has proven to be valid, reliable, and responsive, aiding OA investigators in understanding the natural history of the disease and helping to detect response to treatment. AI may aid phenotypic characterization in the future. SQ MRI assessment's role is increasing in eligibility and safety evaluation in knee OA clinical trials.

CONCLUSIONS

Evidence supports the validity, reliability, and responsiveness of SQ MRI assessment in understanding structural aspects of disease onset and progression. SQ scoring has helped explain associations between structural tissue damage and clinical manifestations, as well as disease progression. While AI may support human readers to more efficiently perform SQ assessment in the future, its current application in clinical trials still requires validation and regulatory approval.

Imaging Biomarkers of Osteoarthritis

Currently no disease-modifying osteoarthritis drug has been approved for the treatment of osteoarthritis (OA) that can reverse, hold, or slow the progression of structural damage of OA-affected joints. The reasons for failure are manifold and include the heterogeneity of structural disease of the OA joint at trial inclusion, and the sensitivity of biomarkers used to measure a potential treatment effect.This article discusses the role and potential of different imaging biomarkers in OA research. We review the current role of radiography, as well as advances in quantitative three-dimensional morphological cartilage assessment and semiquantitative whole-organ assessment of OA. Although magnetic resonance imaging has evolved as the leading imaging method in OA research, recent developments in computed tomography are also discussed briefly. Finally, we address the experience from the Foundation for the National Institutes of Health Biomarker Consortium biomarker qualification study and the future role of artificial intelligence.

Association of biochemical markers with bone marrow lesion changes on imaging-data from the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium

BACKGROUND

To assess the prognostic value of short-term change in biochemical markers as it relates to bone marrow lesions (BMLs) on MRI in knee osteoarthritis (OA) over 24 months and, furthermore, to assess the relationship between biochemical markers involved with tissue turnover and inflammation and BMLs on MRI.

METHODS

Data from the Foundation for the National Institutes of Health OA Biomarkers Consortium within the Osteoarthritis Initiative (n = 600) was analyzed. BMLs were measured according to the MRI Osteoarthritis Knee Score (MOAKS) system (0-3), in 15 knee subregions. Serum and urinary biochemical markers assessed were as follows: serum C-terminal crosslinked telopeptide of type I collagen (CTX-I), serum crosslinked N-telopeptide of type I collagen (NTX-I), urinary CTX-Iα and CTX-Iβ, urinary NTX-I, urinary C-terminal cross-linked telopeptide of type II collagen (CTX-II), serum matrix metalloproteinase (MMP)-degraded type I, II, and III collagen (C1M, C2M, C3M), serum high sensitivity propeptide of type IIb collagen (hsPRO-C2), and matrix metalloproteinase-generated neoepitope of C-reactive protein (CRPM). The association between change in biochemical markers over 12 months and BMLs over 24 months was examined using regression models adjusted for covariates. The relationship between C1M, C2M, C3M, hsPRO-C2, and CRPM and BMLs at baseline and over 24 months was examined.

RESULTS

Increases in serum CTX-I and urinary CTX-Iβ over 12 months were associated with increased odds of changes in the number of subregions affected by any BML at 24 months. Increase in hsPRO-C2 was associated with decreased odds of worsening in the number of subregions affected by any BML over 24 months. C1M and C3M were associated with BMLs affected at baseline.

CONCLUSIONS

Short-term changes in serum CTX-I, hsPRO-C2, and urinary CTX-Iβ hold the potential to be prognostic of BML progression on MRI. The association of C1M and C3M with baseline BMLs on MRI warrants further investigation.

CartiMorph: A framework for automated knee articular cartilage morphometrics

We introduce CartiMorph, a framework for automated knee articular cartilage morphometrics. It takes an image as input and generates quantitative metrics for cartilage subregions, including the percentage of full-thickness cartilage loss (FCL), mean thickness, surface area, and volume. CartiMorph leverages the power of deep learning models for hierarchical image feature representation. Deep learning models were trained and validated for tissue segmentation, template construction, and template-to-image registration. We established methods for surface-normal-based cartilage thickness mapping, FCL estimation, and rule-based cartilage parcellation. Our cartilage thickness map showed less error in thin and peripheral regions. We evaluated the effectiveness of the adopted segmentation model by comparing the quantitative metrics obtained from model segmentation and those from manual segmentation. The root-mean-squared deviation of the FCL measurements was less than 8%, and strong correlations were observed for the mean thickness (Pearson's correlation coefficient ρ∈[0.82,0.97]), surface area (ρ∈[0.82,0.98]) and volume (ρ∈[0.89,0.98]) measurements. We compared our FCL measurements with those from a previous study and found that our measurements deviated less from the ground truths. We observed superior performance of the proposed rule-based cartilage parcellation method compared with the atlas-based approach. CartiMorph has the potential to promote imaging biomarkers discovery for knee osteoarthritis.

Current status of catabolic, anabolic and inflammatory biomarkers associated with structural and symptomatic changes in the chronic phase of post-traumatic knee osteoarthritis- a systematic review

Post-traumatic OA (PTOA) can occur within 5 years after a significant injury and is a valuable paradigm for identifying biomarkers. This systematic review aims to summarise published literature in human studies on the associations of known serum and synovial fluid biomarkers at least a year from injury to structural, symptomatic changes and underlying PTOA processes. A systematic review was performed using PRISMA guidelines, prospectively registered on PROSPERO (CRD42022371838), for all 'wet' biomarkers a year or more post-injury in 18-45-year-old participants. Three independent reviewers screened search results, extracted data, and performed risk of bias assessments (Newcastle-Ottawa Scale). Study heterogeneity meant a narrative synthesis was undertaken, utilising SWiM guidelines. 952 studies were identified, 664 remaining after deduplication. Following first-round screening, 53 studies underwent second-round screening against pre-determined criteria. Eight studies, with 879 participants (49 ​% male), were included, measuring serum (n ​= ​7), synovial fluid (SF, n ​= ​6), or both (n ​= ​5). The pooled participant mean age was 29.1 (±4). 51 biomarkers were studied (serum ​= ​38, SF ​= ​13), with no correlation between paired serum and SF samples. One serum biomarker, cartilage oligomeric matrix protein (COMP), and four SF biomarkers, interleukin (IL)-1β, IL-6, tumour necrosis factor (TNF), and COMP, were measured in multiple studies. Associations were described between 11 biomarkers related to catabolism (n ​= ​4), anabolism (n ​= ​2), inflammation (n ​= ​4) and non-coding RNA (n ​= ​1), with OA imaging changes (X-ray and MRI), pain, quality of life and function. Widespread differences in study design and methodology prevented meta-analysis, and evidence was generally weak. A unified approach is required before widespread research and clinical biomarker use.

Osteoarthritis year in review 2023: metabolite and protein biomarkers

OBJECTIVE

To highlight the advances over the past year in metabolite/protein biomarkers for osteoarthritis (OA).

METHOD

A literature search of five databases including PubMed, Web of Science, Scopus, Ovid Medline, and Embase was performed for studies on metabolite/protein/peptide/biochemical markers for OA published between April 1st, 2022 and March 31st, 2023. Records were then screened to include only original research articles using directly collected human specimens, in English language, and with full text available. Data from eligible studies were systematically extracted and summarized.

RESULTS

A total of 1600 unique records were extracted, out of which 46 fulfilled the inclusion criteria and were used for data extraction. Forty-one of these 46 studies focused on biomarkers for OA/OA severity/progression, four on OA clustering, and one on OA treatment outcomes. Twenty-nine studied protein markers for OA, thirteen studied metabolite markers, and four studied both. While many studies were the validation of the previously reported biomarkers, a number of novel metabolite/protein biomarkers and biomarker panels were reported in the past year. Biomarker panels might be useful to subset OA patients.

CONCLUSION

The number of studies on OA clustering is rising. Although validation in larger cohorts is needed in order to utilize reported biomarkers in clinical practice, these discoveries help better understand the pathogenesis of OA, provide insights into possible mechanisms underlying poor treatment outcomes, and aid in developing personalized treatment based on OA subtypes.

Update on recent developments in imaging of inflammation in osteoarthritis: a narrative review

Synovitis is an important component of the osteoarthritis (OA) disease process, particularly regarding the "inflammatory phenotype" of OA. Imaging plays an important role in the assessment of synovitis in OA with MRI and ultrasound being the most deployed imaging modalities. Contrast-enhanced (CE) MRI, particularly dynamic CEMRI (DCEMRI) is the ideal method for synovitis assessment, but for several reasons CEMRI is not commonly performed for OA imaging in general. Effusion-synovitis and Hoffa-synovitis are commonly used as surrogate markers of synovitis on non-contrast-enhanced (NCE) MRI and have been used in many epidemiological observational studies of knee OA. Several semiquantitative MRI scoring systems are available for the evaluation of synovitis in knee OA. Synovitis can be a target tissue for disease-modifying OA drug (DMOAD) clinical trials. Both MRI and ultrasound may be used to determine the eligibility and assess the therapeutic efficacy of DMOAD approaches. Ultrasound is mostly used for evaluation of synovitis in hand OA, while MRI is typically used for larger joints, namely knees and hips. The role of other modalities such as CT (including dual-energy CT) and nuclear medicine imaging (such as positron-emission tomography (PET) and its hybrid imaging) is limited in the context of synovitis assessment in OA. Despite research efforts to develop NCEMRI-based synovitis evaluation methods, these typically underestimate the severity of synovitis compared to CEMRI, and thus more research is needed before we can rely only on NCEMRI.

Biomarkers in osteoarthritis: current status and outlook - the FNIH Biomarkers Consortium PROGRESS OA study

Currently, no disease-modifying therapies are approved for osteoarthritis (OA) use. One obstacle to trial success in this field has been our existing endpoints' limited validity and responsiveness. To overcome this impasse, the Foundation for the NIH OA Biomarkers Consortium is focused on investigating biomarkers for a prognostic context of use for subsequent qualification through regulatory agencies. This narrative review describes this activity and the work underway, focusing on the PROGRESS OA study.

Association of quantitative measures of medial meniscal extrusion with structural and symptomatic knee osteoarthritis progression - Data from the OAI FNIH biomarker study

OBJECTIVE

To study the association of quantitative medial meniscal position measures with radiographic and symptomatic knee osteoarthritis (OA) progression over 2-4 years.

METHODS

The FNIH OAI Biomarkers study comprised 600 participants in four subgroups: 194 case knees with combined structural (medial minimum joint space width (minJSW) loss ≥0.7 mm) and symptomatic (persistent Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale increase ≥9 [0-100 scale]) progression; 200 knees with neither structural nor symptomatic progression; 103 knees with isolated structural and 103 with isolated symptomatic progression. Coronal double echo at steady state (DESS) MRIs were used for segmenting five central slices of the medial meniscus. Associations with progression were examined using logistic regression (adjusted for demographic and clinical data).

RESULTS

Greater baseline medial meniscal extrusion was associated with combined structural/symptomatic progression (OR 1.59; 95%CI: [1.25,2.04]). No relationship was observed for tibial plateau coverage or meniscal overlap distance. The two-year increase in meniscal extrusion (OR 1.48 [1.21, 1.83]), and reduction in tibial plateau coverage (OR 0.70 [0.58,0.86]) and overlap distance (OR 0.73 [0.60,0.89]) were associated with combined progression. Greater baseline extrusion was associated with isolated structural and less extrusion with isolated symptomatic progression. The longitudinal increase in meniscal extrusion, and reduction in tibial plateau coverage and overlap distance were associated with structural, but not with symptomatic progression.

CONCLUSION

Baseline measures of medial meniscal extrusion were consistently positively associated with combined radiographic/symptomatic progression and with isolated structural, but not with isolated symptomatic progression. These measures may therefore allow one to assess the risk of structural knee OA progression and to monitor interventions restoring meniscal position and function.

Knee MRI biomarkers associated with structural, functional and symptomatic changes at least a year from ACL injury - A systematic review

Introduction

Osteoarthritis (OA) results from various aetiologies, including joint morphology, biomechanics, inflammation, and injury. The latter is implicated in post-traumatic OA, which offers a paradigm to identify potential biomarkers enabling early identification and intervention. This review aims to describe imaging features associated with structural changes or symptoms at least one year following injury.

Methodology

A systematic review was conducted using PRISMA guidance, prospectively registered on PROSPERO (CRD42022371838). Three independent reviewers screened titles and abstracts, followed by full-texts, performed data extraction, and risk of bias assessments (Newcastle-Ottawa Scale). Inclusion criteria included imaging studies involving human participants aged 18-45 who had sustained a significant knee injury at least a year previously. A narrative synthesis was performed using synthesis without meta-analysis methodology.

Results

Six electronic databases and conference proceedings were searched, identifying 11 studies involving 776 participants. All studies included participants suffering an anterior cruciate ligament (ACL) injury and utilised MRI. Different, and not directly comparable, techniques were used. MRI features could be broadly divided into structural, including joint position and morphology, and compositional. Promising biomarkers for diagnosing and predicting osteoarthritis include T1rho and T2 relaxation time techniques, bone morphology changes and radiomic modelling.

Discussion

As early as 12 months after injury, differences in tibia position, bone morphology, presence of effusion and synovitis, and cartilage/subchondral bone composition can be detected, some of which are linked with worse patient-reported or radiological progression. Standardisation, including MR strength, position, sequence, scoring and comparators, is required to utilise clinical and research OA imaging biomarkers fully.

Worsening of Articular Tissue Damage as Defined by Semi-Quantitative MRI Is Associated With Concurrent Quantitative Cartilage Loss Over 24 Months

OBJECTIVE

To assess the association of worsening of magnetic resonance imaging (MRI) semi-quantitative (SQ) tissue features with concurrent change in quantitative (Q) cartilage thickness measurements over 24 months within the Foundation for the National Institutes of Health (FNIH) Biomarker Consortium study.

METHODS

In all, 599 participants were included. SQ assessment included cartilage damage, meniscal extrusion and damage, osteophytes, bone marrow lesions (BMLs), and effusion- and Hoffa-synovitis. Change in medial compartment Q cartilage thickness was stratified by concurrent ipsicompartmental SQ changes. Between-group comparisons were performed using analysis of covariance (ANCOVA) with adjustment for age, sex, and body mass index (BMI). Results were presented as adjusted mean difference.

RESULTS

Knees with any increase in SQ cartilage scores in the medial compartment (n = 268) showed more Q cartilage loss compared to knees that remained stable (mean adjusted difference [MAD] = -0.16 mm, 95% confidence interval [CI]: [-0.19, -0.13] mm). Knees with any increase in meniscal extrusion in the medial compartment (n = 98) showed more Q cartilage loss than knees without (MAD = -0.18 mm, 95% CI: [-0.22, -0.14] mm. Comparable findings were seen for meniscal damage worsening. Regarding BMLs, an increase by one subregion resulted in a MAD of Q cartilage loss of -0.10 mm, 95% CI: [-0.14, -0.06] mm, while this effect almost tripled for change in two or more subregions. Increase in either effusion- and/or Hoffa-synovitis by one grade resulted in a MAD of -0.07 mm, 95% CI: [-0.10, -0.03] mm.

CONCLUSION

Worsening of SQ cartilage damage, meniscal extrusion and damage, number of subregions affected by BML, maximum size of BMLs and worsening of effusion- and/or Hoffa synovitis is associated with increased Q cartilage loss.

Towards Automatic Cartilage Quantification in Clinical Trials - Continuing from the 2019 IWOAI Knee Segmentation Challenge

Objective

To evaluate whether the deep learning (DL) segmentation methods from the six teams that participated in the IWOAI 2019 Knee Cartilage Segmentation Challenge are appropriate for quantifying cartilage loss in longitudinal clinical trials.

Design

We included 556 subjects from the Osteoarthritis Initiative study with manually read cartilage volume scores for the baseline and 1-year visits. The teams used their methods originally trained for the IWOAI 2019 challenge to segment the 1130 knee MRIs. These scans were anonymized and the teams were blinded to any subject or visit identifiers. Two teams also submitted updated methods. The resulting 9,040 segmentations are available online.The segmentations included tibial, femoral, and patellar compartments. In post-processing, we extracted medial and lateral tibial compartments and geometrically defined central medial and lateral femoral sub-compartments. The primary study outcome was the sensitivity to measure cartilage loss as defined by the standardized response mean (SRM).

Results

For the tibial compartments, several of the DL segmentation methods had SRMs similar to the gold standard manual method. The highest DL SRM was for the lateral tibial compartment at 0.38 (the gold standard had 0.34). For the femoral compartments, the gold standard had higher SRMs than the automatic methods at 0.31/0.30 for medial/lateral compartments.

Conclusion

The lower SRMs for the DL methods in the femoral compartments at 0.2 were possibly due to the simple sub-compartment extraction done during post-processing. The study demonstrated that state-of-the-art DL segmentation methods may be used in standardized longitudinal single-scanner clinical trials for well-defined cartilage compartments.

Quantitative MRI for Evaluation of Musculoskeletal Disease: Cartilage and Muscle Composition, Joint Inflammation, and Biomechanics in Osteoarthritis

ABSTRACT

Magnetic resonance imaging (MRI) is a valuable tool for evaluating musculoskeletal disease as it offers a range of image contrasts that are sensitive to underlying tissue biochemical composition and microstructure. Although MRI has the ability to provide high-resolution, information-rich images suitable for musculoskeletal applications, most MRI utilization remains in qualitative evaluation. Quantitative MRI (qMRI) provides additional value beyond qualitative assessment via objective metrics that can support disease characterization, disease progression monitoring, or therapy response. In this review, musculoskeletal qMRI techniques are summarized with a focus on techniques developed for osteoarthritis evaluation. Cartilage compositional MRI methods are described with a detailed discussion on relaxometric mapping (T 2 , T 2 *, T 1ρ ) without contrast agents. Methods to assess inflammation are described, including perfusion imaging, volume and signal changes, contrast-enhanced T 1 mapping, and semiquantitative scoring systems. Quantitative characterization of structure and function by bone shape modeling and joint kinematics are described. Muscle evaluation by qMRI is discussed, including size (area, volume), relaxometric mapping (T 1 , T 2 , T 1ρ ), fat fraction quantification, diffusion imaging, and metabolic assessment by 31 P-MR and creatine chemical exchange saturation transfer. Other notable technologies to support qMRI in musculoskeletal evaluation are described, including magnetic resonance fingerprinting, ultrashort echo time imaging, ultrahigh-field MRI, and hybrid MRI-positron emission tomography. Challenges for adopting and using qMRI in musculoskeletal evaluation are discussed, including the need for metal artifact suppression and qMRI standardization.

Peripheral Blood DNA Methylation-Based Machine Learning Models for Prediction of Knee Osteoarthritis Progression: Biologic Specimens and Data From the Osteoarthritis Initiative and Johnston County Osteoarthritis Project

OBJECTIVE

The lack of accurate biomarkers to predict knee osteoarthritis (OA) progression is a key unmet need in OA clinical research. The objective of this study was to develop baseline peripheral blood epigenetic biomarker models to predict knee OA progression.

METHODS

Genome-wide buffy coat DNA methylation patterns from 554 individuals from the Osteoarthritis Biomarkers Consortium (OABC) were determined using Illumina Infinium MethylationEPIC 850K arrays. Data were divided into model development and validation sets, and machine learning models were trained to classify future OA progression by knee pain, radiographic imaging, knee pain plus radiographic imaging, and any progression (pain, radiographic, or both). Parsimonious models using the top 13 CpG sites most frequently selected during development were tested on independent samples from participants in the Johnston County Osteoarthritis (JoCo OA) Project (n = 128) and a previously published Osteoarthritis Initiative (OAI) data set (n = 55).

RESULTS

Full models accurately classified future radiographic-only progression (mean ± SEM accuracy 87 ± 0.8%, area under the curve [AUC] 0.94 ± 0.004), pain-only progression (accuracy 89 ± 0.9%, AUC 0.97 ± 0.004), pain plus radiographic progression (accuracy 72 ± 0.7%, AUC 0.79 ± 0.006), and any progression (accuracy 78 ± 0.4%, AUC 0.86 ± 0.004). Pain-only and radiographic-only progressors were not distinguishable (mean ± SEM accuracy 58 ± 1%, AUC 0.62 ± 0.001). Parsimonious models showed similar performance and accurately classified future radiographic progressors in the OABC cohort and in both validation cohorts (mean ± SEM accuracy 80 ± 0.3%, AUC 0.88 ± 0.003 [using JoCo OA Project data], accuracy 80 ± 0.8%, AUC 0.89 ± 0.002 [using previous OAI data]).

CONCLUSION

Our data suggest that pain and structural progression share similar early systemic immune epigenotypes. Further studies should focus on evaluating the pathophysiologic consequences of differential DNA methylation and peripheral blood cell epigenotypes in individuals with knee OA.

Association of Superficial Cartilage Transverse Relaxation Time With Osteoarthritis Disease Progression: Data From the Foundation for the National Institutes of Health Biomarker Study of the Osteoarthritis Initiative

OBJECTIVE

To study whether layer-specific cartilage transverse relaxation time (T2) and/or longitudinal change is associated with clinically relevant knee osteoarthritis (OA) disease progression.

METHODS

The Foundation for the National Institutes of Health Biomarker Consortium was a nested case-control study on 600 knees from 600 Osteoarthritis Initiative participants. Progressor knees had both medial tibiofemoral radiographic joint space width (JSW) loss (≥0.7 mm) and a persistent increase in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score (≥9 on a 0-100 scale) at 24-48 months from baseline (n = 194). Multiecho spin-echo (MESE) magnetic resonance images (MRIs) for cartilage T2 analysis had been acquired in the right knees only (97 progressor knees). These were compared to 104 control knees without JSW or pain progression. Fifty-three knees had JSW progression, and 57 pain progression only. Cartilage thickness segmentations obtained from double-echo steady-state MRI were matched to MESE MRI to extract superficial and deep femorotibial cartilage T2. Superficial medial femorotibial compartment (MFTC) T2 at baseline was the primary, and change in deep MFTC T2 between baseline and 12 months was the secondary analytic outcome of this post hoc exploratory study.

RESULTS

Baseline superficial MFTC T2 was significantly elevated in progressor knees (adjusted mean 47.2 msec [95% confidence interval (95% CI) 46.5, 48.0]) and JSW progression only knees (adjusted mean 47.3 msec [95% CI 46.3, 48.3]), respectively, versus non-progressor knees (45.8 msec [95% CI 45.0, 46.5]) after adjustment for age, sex, body mass index, WOMAC pain score, and medial joint space narrowing grade (analysis of covariance). Change in T2 was not significantly associated with case status.

CONCLUSION

Baseline superficial, but not deep, medial cartilage T2 is associated with clinically relevant disease progression in knee OA.

Biochemical, clinical, demographic and imaging biomarkers for disease progression in knee osteoarthritis

Aim: To identify prognostic biomarker(s) for knee osteoarthritis (OA) in the Osteoarthritis Initiative (OAI) cohort. Methods: Multilevel regression was used to determine the association between baseline biomarkers and change in biomarkers from baseline to 24 months with clinical and radiographic OA progression over 48 months of follow-up. Results: Higher values of baseline urinary CTXII were consistently associated with an increased risk of OA disease progression outcomes: Kellgren & Lawrence grade (odds ratio [OR]: 1.15, 95% CI: 1.03-1.28); medial joint space narrowing (OR: 1.06, 95% CI: 1.02-1.10); lateral osteophytes (OR: 1.05, 95% CI: 1.01-1.10); joint space width (regression coefficient: -0.005, 95% CI: -0.008-0.001); and Western Ontario and McMaster Universities Arthritis Index pain scores (OR: 1.02, 95% CI: 1.01-1.04). Changes in serum PIIANP and serum COMP over 24 months were associated with clinical disease progression. Conclusion: Urinary CTXII showed stronger associations with radiographic OA and appears to be a reliable prognostic marker, while changes in other biomarkers were found in early symptomatic OA, supporting the phasic nature of OA.

Are structural abnormalities on knee MRI associated with osteophyte development? Data from the Osteoarthritis Initiative

OBJECTIVE

To assess which structural abnormalities on knee MRI are associated with development of osteophytes in middle-aged subjects without radiographic knee osteoarthritis.

DESIGN

We included subjects from the Osteoarthritis Initiative, aged 40-55 years, Kellgren & Lawrence grade 0 in both knees, and knee MRIs from both knees available at baseline, 24, 48 and 72 months. Structural exposures on MRI assessed using MOAKS included cartilage damage, bone marrow lesions, meniscal tear, meniscal extrusion, and Hoffa/effusion synovitis. We assessed whether each structural exposure was associated with the development of osteophytes on MRI in the medial and lateral tibiofemoral, and patellofemoral compartment. We estimated hazard ratios (HR) including 95% confidence intervals (CI) for osteophyte development using a mixed complementary log-log regression model adjusted for age, sex, and body mass index.

RESULTS

We included 680 knees from 340 subjects with a mean (SD) age of 50 years (3.0), and 51% men. In the medial tibiofemoral compartment, the absolute risk of osteophyte development in the first 24-month period was 4% in knees without, and 15% in knees with medial meniscal tear. Corresponding adjusted HR was 6.6 (95%CI = 3.4-12.9). In the lateral tibiofemoral compartment, the adjusted HR for developing osteophytes having a lateral meniscal tear was 3.3 (95%CI = 1.3-8.4). In the patellofemoral compartment, patellofemoral cartilage damage was most clearly associated with developing osteophytes (HR = 2.6, 95%CI = 1.8-3.7).

CONCLUSIONS

Meniscal tear seem to be the strongest structural risk factor for the development of tibiofemoral osteophytes, and patellofemoral cartilage damage for the development of patellofemoral osteophytes, respectively. Local biomechanical factors are important in early osteophyte development.

Soluble biological markers in osteoarthritis

In recent years, markers research has focused on the structural components of cartilage matrix. Specifically, a second generation of degradation markers has been developed against type II collagen neoepitopes generated by specific enzymes. A particular effort has been made to measure the degradation of minor collagens III and X of the cartilage matrix. However, because clinical data, including longitudinal controlled studies, are very scarce, it remains unclear whether they will be useful as an alternative to or in combination with current more established collagen biological markers to assess patients with osteoarthritis (OA). In addition, new approaches using high-throughput technologies allowed to detect new types of markers and improve the knowledge about the metabolic changes linked to OA. The relative advances coming from phenotype research are a first attempt to classify the heterogeneity of OA, and several markers could improve the phenotype characterization. These phenotypes could improve the selection of patients in clinical trials limiting the size of the studies by selecting patients with OA characteristics corresponding to the metabolic pathway targeted by the molecules evaluated. In addition, the inclusion of rapid progressors only in clinical trials would facilitate the demonstration of efficacy of the investigative drug to reduce joint degradation. The combination of selective biochemical markers appears as a promising and cost-effective approach to fulfill this unmet clinical need. Among the various potential roles of biomarkers in OA, their ability to monitor drug efficacy is probably one of the most important, in association with clinical and imaging parameters. Biochemical markers have the unique property to detect changes in joint tissue metabolism within a few weeks.

Novel nomogram for predicting the progression of osteoarthritis based on 3D-MRI bone shape: data from the FNIH OA biomarkers consortium

Background

Osteoarthritis(OA) is a major source of pain, disability, and socioeconomic cost in worldwide. However, there is no effective means for the early diagnosis of OA, nor can it accurately predict the progress of OA. To develop and validate a novel nomogram to predict the radiographic progression of mild to moderate OA based on three-dimensional(3D)-MRI bone shape and bone shape change during 24 months.

Method

Analysis of publicly available data from the Foundation for the National Institutes of Health (FNIH) OA Biomarkers Consortium. Radiographic progression was defined as minimum radiographic narrowing of the medial tibiofemoral joint space of ≥ 0.7 mm from baseline at 24, 36, or 48 months. There were 297 knees with radiographic progression and 303 without. The bone shapes of the tibia, femur, and patella were evaluated by 3D-MRI at the baseline and at 24 months. Two nomograms were separately established by multivariate logistic regression analysis using clinical risk factors, bone shape at baseline (nomogram 0), or bone shape change at 24 months (nomogram Δ24). The discrimination, calibration, and usefulness were selected to evaluate the nomograms.

Results

There were significant differences between groups in baseline Kellgren-Lawrence (KL) grade, gender, age, and tibia, femur, and patella shape. The areas under the curve (AUC) of nomogram 0 and nomogram Δ24 were 0.66 and 0.75 (p < 0.05), with accuracy of 0.62 and 0.69, respectively. Both nomograms had good calibration. The decision curve analysis ( DCA) showed that nomogram Δ24 had greater clinical usefulness than nomogram 0 when the risk threshold ranged from 0.04 to 0.86.

Conclusions

Nomograms based on 3D-MRI bone shape change were useful for predicting the radiographic progression of mild to moderate OA.

Early-stage symptomatic osteoarthritis of the knee - time for action

Osteoarthritis (OA) remains the most challenging arthritic disorder, with a high burden of disease and no available disease-modifying treatments. Symptomatic early-stage OA of the knee (the focus of this Review) urgently needs to be identified and defined, as efficient early-stage case finding and diagnosis in primary care would enable health-care providers to proactively and substantially reduce the burden of disease through proper management including structured education, exercise and weight management (when needed) and addressing lifestyle-related risk factors for disease progression. Efforts to define patient populations with symptomatic early-stage knee OA on the basis of validated classification criteria are ongoing. Such criteria, as well as the identification of molecular and imaging biomarkers of disease risk and/or progression, would enable well-designed clinical studies, facilitate interventional trials, and aid the discovery and validation of cellular and molecular targets for novel therapies. Treatment strategies, relevant outcomes and ethical issues also need to be considered in the context of the cost-effective management of symptomatic early-stage knee OA. To move forwards, a multidisciplinary and sustained international effort involving all major stakeholders is required.