Dataset Information

Specific-cytokine associations with outcomes in knee osteoarthritis subgroups: breaking down disease heterogeneity with phenotyping.

ABSTRACT:

Background

Despite existing extensive literature, a comprehensive and clinically relevant classification system for osteoarthritis (OA) has yet to be established. In this study, we aimed to further characterize four knee OA (KOA) inflammatory phenotypes (KOIP) recently proposed by our group, by identifying the inflammatory factors associated with KOA severity and progression in a phenotype-specific manner.

Methods

We performed an analysis within each of the previously defined four KOIP groups, to assess the association between KOA severity and progression and a panel of 13 cytokines evaluated in the plasma and synovial fluid of our cohort's patients. The cohort included 168 symptomatic female KOA patients with persistent joint effusion.

Results

Overall, our analyses showed that associations with KOA outcomes were of higher magnitude within the KOIP groups than for the overall patient series (all p-values < 1.30e-16) and that several of the cytokines showed a KOIP-specific behaviour regarding their associations with KOA outcomes.

Conclusion

Our study adds further evidence supporting KOA as a multifaceted syndrome composed of multiple phenotypes with differing pathophysiological pathways, providing an explanation for inconsistencies between previous studies focussed on the role of cytokines in OA and the lack of translational results to date. Our findings also highlight the potential clinical benefits of accurately phenotyping KOA patients, including improved patient stratification, tailored therapies, and the discovery of novel treatments.

SUBMITTER: Calvet J

PROVIDER: S-EPMC10782658 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Publications

Specific-cytokine associations with outcomes in knee osteoarthritis subgroups: breaking down disease heterogeneity with phenotyping.

Calvet Joan J Berenguer-Llergo Antoni A Orellana Cristóbal C García-Manrique María M Rusiñol Menna M Garcia-Cirera Silvia S Llop Maria M Arévalo Marta M Garcia-Pinilla Alba A Galisteo Carlos C Aymerich Cristina C Gómez Rafael R Serrano Alejandra A Carreras Anna A Gratacós Jordi J

Arthritis research & therapy 20240111 1

<h4>Background</h4>Despite existing extensive literature, a comprehensive and clinically relevant classification system for osteoarthritis (OA) has yet to be established. In this study, we aimed to further characterize four knee OA (KOA) inflammatory phenotypes (KOIP) recently proposed by our group, by identifying the inflammatory factors associated with KOA severity and progression in a phenotype-specific manner.<h4>Methods</h4>We performed an analysis within each of the previously defined four ...[more]

PMID: 38212829

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Project description:ObjectiveSynovial membrane inflammation is common in osteoarthritis (OA) and increases cartilage injury. However, synovial fluid and histology studies suggest that OA inflammatory responses are not homogeneous. Greater understanding of these responses may provide new insights into OA disease mechanisms. We undertook this study to develop a novel multiparameter approach to phenotype synovial responses in knee OA.MethodsCell composition and soluble protein production were measured by flow cytometry and multiplex enzyme-linked immunosorbent assay in synovium collected from OA patients undergoing knee replacement surgery (n = 35).ResultsTesting disaggregation conditions showed that aggressive digestion improved synovial cell yield and mesenchymal staining by flow cytometry, but it negatively impacted CD4+ T cell and CD56+ natural killer cell staining. Less aggressive digestion preserved these markers and showed highly variable T cell infiltration (range 0-43%; n = 32). Correlation analysis identified mesenchymal subpopulations associated with different nonmesenchymal populations, including macrophages and T cells (CD45+CD11b+HLA-DR+ myeloid cells with PDPN+CD73+CD90-CD34- mesenchymal cells [r = 0.65, P < 0.0001]; and CD45+CD3+ T cells with PDPN+CD73+CD90+CD34+ mesenchymal cells [r = 0.50, P = 0.003]). Interleukin-6 (IL-6) measured by flow cytometry strongly correlated with IL-6 released by ex vivo culture of synovial tissue (r = 0.59, P = 0.0012) and was highest in mesenchymal cells coexpressing CD90 and CD34. IL-6, IL-8, complement factor D, and IL-10 release correlated positively with tissue cellularity (P = 0.0042, P = 0.018, P = 0.0012, and P = 0.038, respectively). Additionally, increased CD8+ T cell numbers correlated with retinol binding protein 4 (P = 0.033). Finally, combining flow cytometry and multiplex data identified patient clusters with different types of inflammatory responses.ConclusionWe used a novel approach to analyze OA synovium, identifying patient-specific inflammatory clusters. Our findings indicate that phenotyping synovial inflammation may provide new insights into OA patient heterogeneity and biomarker development.

Project description:ObjectiveKnee osteoarthritis (KOA) is a heterogeneous condition representing a variety of potentially distinct phenotypes. The purpose of this study was to apply innovative machine learning approaches to KOA phenotyping in order to define progression phenotypes that are potentially more responsive to interventions.DesignWe used publicly available data from the Foundation for the National Institutes of Health (FNIH) osteoarthritis (OA) Biomarkers Consortium, where radiographic (medial joint space narrowing of ≥0.7 mm), and pain progression (increase of ≥9 Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC] points) were defined at 48 months, as four mutually exclusive outcome groups (none, both, pain only, radiographic only), along with an extensive set of covariates. We applied distance weighted discrimination (DWD), direction-projection-permutation (DiProPerm) testing, and clustering methods to focus on the contrast (z-scores) between those progressing by both criteria ("progressors") and those progressing by neither ("non-progressors").ResultsUsing all observations (597 individuals, 59% women, mean age 62 years and BMI 31 kg/m2) and all 73 baseline variables available in the dataset, there was a clear separation among progressors and non-progressors (z = 10.1). Higher z-scores were seen for the magnetic resonance imaging (MRI)-based variables than for demographic/clinical variables or biochemical markers. Baseline variables with the greatest contribution to non-progression at 48 months included WOMAC pain, lateral meniscal extrusion, and serum N-terminal pro-peptide of collagen IIA (PIIANP), while those contributing to progression included bone marrow lesions, osteophytes, medial meniscal extrusion, and urine C-terminal crosslinked telopeptide type II collagen (CTX-II).ConclusionsUsing methods that provide a way to assess numerous variables of different types and scalings simultaneously in relation to an outcome of interest enabled a data-driven approach that identified key variables associated with a progression phenotype.

Project description:BackgroundWe recently developed a model of stratified exercise therapy, consisting of (i) a stratification algorithm allocating patients with knee osteoarthritis (OA) into one of the three subgroups ('high muscle strength subgroup' representing a post-traumatic phenotype, 'low muscle strength subgroup' representing an age-induced phenotype, and 'obesity subgroup' representing a metabolic phenotype) and (ii) subgroup-specific exercise therapy. In the present study, we aimed to test the construct validity of this algorithm.MethodsData from five studies (four exercise therapy trial cohorts and one cross-sectional cohort) were used to test the construct validity of our algorithm by 63 a priori formulated hypotheses regarding three research questions: (i) are the proportions of patients in each subgroup similar across cohorts? (15 hypotheses); (ii) are the characteristics of each of the subgroups in line with their proposed underlying phenotypes? (30 hypotheses); (iii) are the effects of usual exercise therapy in the 3 subgroups in line with the proposed effect sizes? (18 hypotheses).ResultsBaseline data from a total of 1211 patients with knee OA were analyzed for the first and second research question, and follow-up data from 584 patients who were part of an exercise therapy arm within a trial for the third research question. In total, the vast majority (73%) of the hypotheses were confirmed. Regarding our first research question, we found similar proportions in each of the three subgroups across cohorts, especially for three cohorts. Regarding our second research question, subgroup characteristics were almost completely in line with the proposed underlying phenotypes. Regarding our third research question, usual exercise therapy resulted in similar, medium to large effect sizes for knee pain and physical function for all three subgroups.ConclusionWe found mixed results regarding the construct validity of our stratification algorithm. On the one hand, it is a valid instrument to consistently allocate patients into subgroups that aligned our hypotheses. On the other hand, in contrast to our hypotheses, subgroups did not differ substantially in effects of usual exercise therapy. An ongoing trial will assess whether this algorithm accompanied by subgroup-specific exercise therapy improves clinical and economic outcomes.

Project description:Background Longitudinal data on the association of quantitative thigh muscle MRI markers with knee osteoarthritis (KOA) outcomes are scarce. These associations are of clinical importance, with potential use for thigh muscle-directed disease-modifying interventions. Purpose To measure KOA-associated longitudinal changes in MRI-derived muscle cross-sectional area (CSA) and adipose tissue and their association with downstream symptom worsening and knee replacement (KR). Materials and Methods In a secondary analysis of the Osteoarthritis Initiative multicenter prospective cohort (February 2004 through October 2015), knees of participants with available good-quality thigh MRI scans at baseline and at least one follow-up visit were included and classified as with and without KOA according to baseline radiographic Kellgren-Lawrence grade of 2 or higher and matched for confounders with use of propensity score matching. An automated deep learning model for thigh MRI two-dimensional segmentation was developed and tested. Markers of muscle CSA and intramuscular adipose tissue (intra-MAT) were measured at baseline and 2nd- and 4th-year follow-up (period 1) and compared between knees with and without KOA by using linear mixed-effect regression models. Furthermore, in knees with KOA, the association of period 1 changes in muscle markers with risk of KR (Cox proportional hazards) and symptom worsening (mixed-effect models) during the 4th to 9th year (period 2) was evaluated. Results This study included 4634 matched thighs (2317 with and 2317 without KOA) of 2344 participants (mean age, 62 years ± 9 [SD]; 1292 women). Compared with those without, knees with KOA had a decrease in quadriceps CSA (mean difference, -8.21 mm2/year; P = .004) and an increase in quadriceps intra-MAT (1.98 mm2/year; P = .007). Decreased CSA and increased intra-MAT of quadriceps during period 1 was predictive of downstream (period 2) KOA symptom worsening (Western Ontario and McMaster Universities Osteoarthritis Index total score: odds ratio, 0.24 [negative association] [P < .001] and 1.38 [P = .012], respectively). Quadriceps CSA changes were negatively associated with higher future KR risk (hazard ratio, 0.70; P < .001). Conclusion Knee osteoarthritis was associated with longitudinal MRI-derived decreased quadriceps cross-sectional area and increased intramuscular adipose tissue. These potentially modifiable risk factors were predictive of downstream symptom worsening and knee replacement. Clinical trial registration no. NCT00080171 © RSNA, 2022 Online supplemental material is available for this article.

Dataset Information

Specific-cytokine associations with outcomes in knee osteoarthritis subgroups: breaking down disease heterogeneity with phenotyping.

Background

Methods

Results

Conclusion

Publications

Specific-cytokine associations with outcomes in knee osteoarthritis subgroups: breaking down disease heterogeneity with phenotyping.

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