Predicted and actual 2-year structural and pain progression in the IMI-APPROACH knee osteoarthritis cohort

OBJECTIVES

The IMI-APPROACH knee osteoarthritis study used machine learning (ML) to predict structural and/or pain progression, expressed by a structural (S) and pain (P) predicted-progression score, to select patients from existing cohorts. This study evaluates the actual 2-year progression within the IMI-APPROACH, in relation to the predicted-progression scores.

METHODS

Actual structural progression was measured using minimum joint space width (minJSW). Actual pain (progression) was evaluated using the Knee injury and Osteoarthritis Outcomes Score (KOOS) pain questionnaire. Progression was presented as actual change (Δ) after 2 years, and as progression over 2 years based on a per patient fitted regression line using 0, 0.5, 1 and 2-year values. Differences in predicted-progression scores between actual progressors and non-progressors were evaluated. Receiver operating characteristic (ROC) curves were constructed and corresponding area under the curve (AUC) reported. Using Youden's index, optimal cut-offs were chosen to enable evaluation of both predicted-progression scores to identify actual progressors.

RESULTS

Actual structural progressors were initially assigned higher S predicted-progression scores compared with structural non-progressors. Likewise, actual pain progressors were assigned higher P predicted-progression scores compared with pain non-progressors. The AUC-ROC for the S predicted-progression score to identify actual structural progressors was poor (0.612 and 0.599 for Δ and regression minJSW, respectively). The AUC-ROC for the P predicted-progression score to identify actual pain progressors were good (0.817 and 0.830 for Δ and regression KOOS pain, respectively).

CONCLUSION

The S and P predicted-progression scores as provided by the ML models developed and used for the selection of IMI-APPROACH patients were to some degree able to distinguish between actual progressors and non-progressors.

TRIAL REGISTRATION

ClinicalTrials.gov, https://clinicaltrials.gov, NCT03883568.

OP0224 DISCOVERY PROTEOMICS ANALYSIS IN THE IMI-APPROACH COHORT SHOWS THE DIFFERENTIAL MODULATION AT 24 MONTHS OF PROTEIN PROFILES ASSOCIATED WITH STRUCTURAL OR PAIN PROGRESSION IN OSTEOARTHRITIS

Background

The characterization of differential molecular endotypes in osteoarthritis (OA) is essential for enabling patient stratification to enhance clinical trials, facilitate the development of targeted and individualized treatments.

Objectives

This study aimed to characterize the profile and dynamics over 24 months (24M) of proteins present in the sera from patients in the IMI-Applied Public-Private Research enabling OsteoArthritis Clinical Headway (APPROACH) cohort who exhibited structural (radiographic) and pain progression compared to participants who did not progressed during this period.

Methods

Forty-five patients enrolled in the IMI-APPROACH cohort were selected for the proteomic analysis. Among these, 15 showed the highest structural progression (group S) and 15 the highest pain progression (group P) at 24M, according to the APPROACH criteria [1], while 15 did not progressed neither in S nor in P. Baseline (BL) and 24M serum samples were depleted of the top 14 most abundant proteins and then analysed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) on a nanoElute-LC coupled to a high-resolution TIMS-QTOF (timsTOF Pro, Bruker Daltonics). Proteins were identified and quantified using the LFQ algorithm of MaxQuant software. Further statistical and bioinformatic analyses were performed using Perseus and OmicsAnalyst software.

Results

The proteomic analysis resulted in the identification of 558 proteins (10,466 peptides) in the serum samples. A label-free quantification algorithm was employed to quantify 468 proteins in the samples. Hierarchical clustering of the data showed the differences in protein abundance were more relevant longitudinally (BL to 24M) than in cross-sectional comparisons between the three groups under study (N, P or S). Sixty-three proteins were significantly altered (fold change >=1.5, p<0.05) when comparing BL to 24M in the N group (15 increased and 48 decreased), 53 in the P group (20 increased and 33 decreased) and 93 in the S group (19 increased and 74 decreased). Interestingly, two different endotypes were detected at baseline in the N and S groups, based on these protein modulations.

The overlapping of these proteomic profiles was analyzed between groups and is shown in the Figure 1. Proteins modulated specifically in the N group may be associated with mechanisms related with joint repair. On the other hand, six proteins (including two apolipoproteins) were increased at 24M only in the P group. Finally, 30 proteins were modulated only in the S group: five of them increased and 25 decreased. Remarkably, this latter group includes lubricin, chaperones and proteins related with proteoglycan binding, such as COMP, fibronectin or histidine-rich glycoprotein.

Figure 1.

Circulating proteins identified as modulated after 24M follow-up in 45 patients from the APPROACH cohort that progressed in structure (S group; n=15), pain (P group; n=15) or did not progressed (N group; n=15). The numbers with arrows indicate those proteins that decrease (arrow pointing down) or increase (arrow pointing up) compared to baseline.

Conclusion

The modulation of specific protein profiles in serum were identified as associated with the progression in structure, pain or non-progression in patients from the APPROACH cohort. Proteomic changes found specifically in the S group may be interesting circulating markers of the structural affectation occurring in the joint.

References

[1]van Helvoort EM, et al., BMJ Open. 2020 Jul 28;10(7):e035101. doi: 10.1136/bmjopen-2019-035101.

Disclosure of Interests

Cristina Ruiz-Romero: None declared, Patrik Önnerfjord: None declared, Valentina Calamia: None declared, Patricia Fernández Puente: None declared, Lucía Lourido: None declared, Rocío Paz González: None declared, Pawel Widera: None declared, Jaume Bacardit: None declared, Anne-Christine Bay-Jensen Shareholder of: Nordic Bioscience, Employee of: Nordic Bioscience, Francis Berenbaum Consultant of: AstraZeneca, Boehringer, Bone Therapeutics, CellProthera, Expanscience, Galapagos, Gilead, Grunenthal, GSK, Eli Lilly, Merck Sereno, MSD, Nordic, Nordic Bioscience, Novartis, Pfizer, Roche, Sandoz, Sanofi, Servier, UCB, Peptinov, 4P Pharma, 4Moving Biotech, Grant/research support from: TRB Chemedica, Ida K. Haugen Consultant of: Abbvie and Novartis, Grant/research support from: Pfizer, Margreet Kloppenburg Consultant of: Abbvie, Pfizer, Levicept, GlaxoSmithKline, Merck-Serono, Kiniksa, Flexion, Galapagos, Jansen, CHDR, Novartis, UCB, Simon Mastbergen: None declared, Jonathan Larkin Shareholder of: GlaxoSmithKline, Employee of: GlaxoSmithKline, Ali Mobasheri Consultant of: Merck KGaA, Kolon TissueGene, Pfizer Inc., Galapagos-Servier, Image Analysis Group (IAG), Artialis SA, Aché Laboratórios Farmacêuticos, AbbVie, Guidepoint Global, Alphasights, Science Branding Communications, GSK, Flexion Therapeutics, Pacira Biosciences, Sterifarma, Bioiberica, SANOFI, Genacol, Kolon Life Science, BRASIT/BRASOS, GEOS, MCI Group, Alcimed, Abbot, Laboratoires Expansciences, SPRIM Communications, Frontiers Media and University Health Network (UHN) Toronto, Grant/research support from: Merck KGaA, Kolon TissueGene, Pfizer Inc., Galapagos-Servier, Image Analysis Group (IAG), Artialis SA, Aché Laboratórios Farmacêuticos, AbbVie, Guidepoint Global, Alphasights, Science Branding Communications, GSK, Flexion Therapeutics, Pacira Biosciences, Sterifarma, Bioiberica, SANOFI, Genacol, Kolon Life Science, BRASIT/BRASOS, GEOS, MCI Group, Alcimed, Abbot, Laboratoires Expansciences, SPRIM Communications, Frontiers Media and University Health Network (UHN) Toronto, Francisco J. Blanco Consultant of: Gedeon Richter Plc., Bristol-Myers Squibb International Corporation (BMSIC), Sun Pharma Global FZE, Celgene Corporation, Janssen Cilag International N.V, Janssen Research & Development, Viela Bio, Inc., Astrazeneca AB, UCB BIOSCIENCES GMBH, UCB BIOPHARMA SPRL, AbbVie Deutschland GmbH & Co.KG, Merck KGaA, Amgen, Inc., Novartis Farmacéutica, S.A., Boehringer Ingelheim España, S.A, CSL Behring, LLC, Glaxosmithkline Research & Development Limited, Pfizer Inc, Lilly S.A., Corbus Pharmaceuticals Inc., Biohope Scientific Solutions for Human Health S.L., Centrexion Therapeutics Corp., Sanofi, TEDEC-MEIJI FARMA S.A., Kiniksa Pharmaceuticals, Ltd., Fundación para la Investigación Biomédica Del Hospital Clínico San Carlos, Grünenthal and Galapagos, Grant/research support from: Pfizer

Baseline clinical characteristics of predicted structural and pain progressors in the IMI-APPROACH knee OA cohort

OBJECTIVES

To describe the relations between baseline clinical characteristics of the Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) participants and their predicted probabilities for knee osteoarthritis (OA) structural (S) progression and/or pain (P) progression.

METHODS

Baseline clinical characteristics of the IMI-APPROACH participants were used for this study. Radiographs were evaluated according to Kellgren and Lawrence (K&L grade) and Knee Image Digital Analysis. Knee Injury and Osteoarthritis Outcome Score (KOOS) and Numeric Rating Scale (NRS) were used to evaluate pain. Predicted progression scores for each individual were determined using machine learning models. Pearson correlation coefficients were used to evaluate correlations between scores for predicted progression and baseline characteristics. T-tests and χ² tests were used to evaluate differences between participants with high versus low progression scores.

RESULTS

Participants with high S progressions score were found to have statistically significantly less structural damage compared with participants with low S progression scores (minimum Joint Space Width, minJSW 3.56 mm vs 1.63 mm; p<0.001, K&L grade; p=0.028). Participants with high P progression scores had statistically significantly more pain compared with participants with low P progression scores (KOOS pain 51.71 vs 82.11; p<0.001, NRS pain 6.7 vs 2.4; p<0.001).

CONCLUSIONS

The baseline minJSW of the IMI-APPROACH participants contradicts the idea that the (predicted) course of knee OA follows a pattern of inertia, where patients who have progressed previously are more likely to display further progression. In contrast, for pain progressors the pattern of inertia seems valid, since participants with high P score already have more pain at baseline compared with participants with a low P score.

Transcriptional dynamics of two seed compartments with opposing roles in Arabidopsis seed germination

Seed germination is a critical stage in the plant life cycle and the first step toward successful plant establishment. Therefore, understanding germination is of important ecological and agronomical relevance. Previous research revealed that different seed compartments (testa, endosperm, and embryo) control germination, but little is known about the underlying spatial and temporal transcriptome changes that lead to seed germination. We analyzed genome-wide expression in germinating Arabidopsis (Arabidopsis thaliana) seeds with both temporal and spatial detail and provide Web-accessible visualizations of the data reported (vseed.nottingham.ac.uk). We show the potential of this high-resolution data set for the construction of meaningful coexpression networks, which provide insight into the genetic control of germination. The data set reveals two transcriptional phases during germination that are separated by testa rupture. The first phase is marked by large transcriptome changes as the seed switches from a dry, quiescent state to a hydrated and active state. At the end of this first transcriptional phase, the number of differentially expressed genes between consecutive time points drops. This increases again at testa rupture, the start of the second transcriptional phase. Transcriptome data indicate a role for mechano-induced signaling at this stage and subsequently highlight the fates of the endosperm and radicle: senescence and growth, respectively. Finally, using a phylotranscriptomic approach, we show that expression levels of evolutionarily young genes drop during the first transcriptional phase and increase during the second phase. Evolutionarily old genes show an opposite pattern, suggesting a more conserved transcriptome prior to the completion of germination.

Suppression of blastogenic transformation of lymphocytes by Bacteroides fragilis in vitro and in vivo

Bacteroides species and Enterobacteriaceae are known to cause synergistic infections. However, the mechanisms behind this synergy are not completely understood. Several authors have shown that Bacteroides species may inhibit the phagocytosis of Enterobacteriaceae by polymorphonuclear leukocytes as well as by macrophages. With the present study we have addressed the question of whether Bacteroides fragilis (BF) is also capable of suppressing specific immune functions. When incubated together with murine lymphocytes, BF significantly inhibited the blastogenic transformation of these cells stimulated by Escherichia coli-lipopolysaccharide (LPS) or concanavalin A. This effect was dose dependent and was not mediated by prostaglandins. Other bacteria such as E. coli or Listeria monocytogenes did not show such an extensive suppression, while Streptococcus pneumoniae was equally active. BF also inhibited the pokeweed mitogen induced blastogenic transformation of human lymphocytes. Moreover, lymphocytes from BF-injected animals obtained 3 to 12 hours after infection proved to be partly refractory for LPS-stimulation. Finally, BF injections also affected T-cell dependent immunity as judged from the aggravation of an experimental listeriosis in mice.

Sarcocystis gigantea lectin--mitogen and polyclonal B-cell activator

The present study further examined the in vitro response of human mononuclear cells (MNC) to the Sarcocystis gigantea lectin (SGL). The results confirm our previous report that SGL is mitogenic for human MNC. We now report that SGL is not only a potent mitogen but also a polyclonal activator for human peripheral B cells. As was true for pokeweed mitogen (PWM, 2 micrograms/ml), the addition of SGL (25 micrograms protein/ml) to cultures of MNC caused lymphocyte proliferation and B-cell maturation, indicated by a marked increase in IgG and IgM production. As measured by the [3H]-thymidine incorporation assay, SGL induced significantly higher proliferative responses than PWM (P less than 0.01, n = 24). The values obtained by SGL and PWM for IgG and IgM synthesis were essentially identical. As opposed to SGL, the sarcotoxin-containing fraction (SGTF) did not induce antibody formation or proliferative responses in human MNC.

Interactions between Sarcocystis gigantea lectin and toxin-containing fractions in human lymphocyte cultures

Sarcocystis gigantea extract (SGE) was separated by affinity chromatography into one lectin-containing fraction (SGL) that was mitogenic to mononuclear cells (MNC) and another that lacked this lectin activity. The SGL-depleted Sarcocystis extract (SGTF) contained the so-called Sarcotoxin, inducing only a slight increase in MNC proliferation. Furthermore, preincubation of MNC with SGTF for 60 min suppressed the mitogenic capacity of SGL by 60%-90%. The results presented indicate that SGTF interacts with human MNC differently than SGL, particularly by interfering with the mitogenic lectin. These findings suggest that SGL and SGTF may be involved in different immunomechanisms induced by the parasite.