Cartilage Acidic Protein 1 in Plasma Associates With Prevalent Osteoarthritis and Predicts Future Risk as Well as Progression to Joint Replacements: Results From the UK Biobank Resource

Acyl-coenzyme a binding protein (ACBP) - a risk factor for cancer diagnosis and an inhibitor of immunosurveillance

BACKGROUND

The plasma concentrations of acyl coenzyme A binding protein (ACBP, also known as diazepam-binding inhibitor, DBI, or 'endozepine') increase with age and obesity, two parameters that are also amongst the most important risk factors for cancer.

METHODS

We measured ACBP/DBI in the plasma from cancer-free individuals, high-risk patients like the carriers of TP53 or BRCA1/2 mutations, and non-syndromic healthy subjects who later developed cancer. In mice, the neutralization of ACBP/DBI was used in models of non-small cell lung cancer (NSCLC) and breast cancer development and as a combination treatment with chemoimmunotherapy (chemotherapy + PD-1 blockade) in the context of NSCLC and sarcomas. The anticancer T cell response upon ACBP/DBI neutralization was characterized by flow cytometry and single-cell RNA sequencing.

RESULTS

Circulating levels of ACBP/DBI were higher in patients with genetic cancer predisposition (BRCA1/2 or TP53 germline mutations) than in matched controls. In non-syndromic cases, high ACBP/DBI levels were predictive of future cancer development, and especially elevated in patients who later developed lung cancer. In preclinical models, ACBP/DBI neutralization slowed down breast cancer and NSCLC development and enhanced the efficacy of chemoimmunotherapy in NSCLC and sarcoma models. When combined with chemoimmunotherapy, the neutralizing monoclonal antibody against ACBP/DBI reduced the frequency of regulatory T cells in the tumor bed, modulated the immune checkpoint profile, and increased activation markers.

CONCLUSION

These findings suggest that ACBP/DBI acts as an endogenous immune suppressor. We conclude that elevation of ACBP/DBI constitutes a risk factor for the development of cancer and that ACBP/DBI is an actionable target for improving cancer immunosurveillance.

Label-Free and Ultrasensitive Detection of Cartilage Acidic Protein 1 in Osteoarthritis Using a Single-Walled Carbon Nanotube Field-Effect Transistor Biosensor

Osteoarthritis (OA), a prevalent degenerative joint disease, significantly affects the well-being of afflicted individuals and compromises the standard functionality of human joints. The emerging biomarker, Cartilage acidic protein 1 (CRTAC1), intricately associates with OA initiation and serves as a prognostic indicator for the trajectory toward joint replacement. However, existing diagnostic methods for CRTAC1 are hampered by the limited abundance, thus restricting the precision and specificity. Herein, a novel approach utilizing a single-walled carbon nanotube field-effect transistor (SWCNTs FET) biosensor is reported for the direct label-free detection of CRTAC1. High-purity semiconducting carbon nanotube films, functionalized with antibodies of CRTAC1, provide excellent electrical and sensing properties. The SWCNTs FET biosensor exhibits high sensitivity, notable reproducibility, and a wide linear detection range (1 fg/mL to 100 ng/mL) for CRTAC1 with a theoretical limit of detection (LOD) of 0.2 fg/mL. Moreover, the SWCNTs FET biosensor is capable of directly detecting human serum samples, showing excellent sensing performance in differentiating clinical samples from OA patients and healthy populations. Comparative analysis with traditional enzyme-linked immunosorbent assay (ELISA) reveals that the proposed biosensor demonstrates faster detection speeds, higher sensitivity/accuracy, and lower errors, indicating high potential for the early OA diagnosis. Furthermore, the SWCNTs FET biosensor has good scalability for the combined diagnosis and measurement of multiple disease markers, thereby significantly expanding the application of SWCNTs FETs in biosensing and clinical diagnostics.

Blood and urine biomarkers for the diagnosis of early stages of knee osteoarthritis: A systematic review

Purpose

To identify biomarkers in human blood or urine at an early stage of knee osteoarthritis (OA) and to elucidate if any can accurately differentiate between healthy controls and early knee OA patients and be considered as a candidate for widespread clinical use for early diagnosis of the disease.

Methods

Medline, Embase and Web of Science were screened to identify comparative studies measuring differences in blood or urine biomarkers between healthy controls and knee OA patients at an early stage (grade 1 or 2 Kellgren-Laurence). Two independent reviewers screened the abstracts for eligibility, reviewed the full texts, assessed the methodological quality and extracted the data. The Joanna Briggs Institute critical appraisal tool for diagnostic test accuracy studies was used to assess the quality of the included studies. Due to relevant heterogeneity, meta-analysis was not appropriate.

Results

Five studies met the eligibility criteria. The examined biomarkers were adropin, collagen type II metabolite, C-terminal cross-linked telopeptide of type II collagen, C-terminal cross-linked telopeptide of type I collagen, cartilage oligomeric matrix protein, matrix metalloproteinase 3, N-terminal propeptide of procollagen type IIA, type I procollagen N-terminal propeptides, N-terminal osteocalcin, angiopoietin-2, follistatin, granulocyte colony-stimulating factor, hepatocyte growth factor, interleukin-8, leptin, platelet-derived growth factor-BB, platelet endothelial cell adhesion molecule-1, vascular endothelial growth factor and calprotectin and totalling 19 biomarkers. All of the biomarkers were studied only once in the selected papers.

Conclusions

There is no reliable biomarker available to differentiate between early knee OA in patients and healthy controls, but a potential role of a cluster of biomarkers to close this gap. There are several limitations, including inappropriate study designs, small sample sizes, nonconsecutive patient groups and inadequate statistical methods for evaluating biomarker performance in studies included.

Level of Evidence

Level III.

Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies

OBJECTIVE

Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades.

DESIGN

We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease.

RESULTS

Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues.

CONCLUSIONS

Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions.

Development and Validation of a Deep-Learning Model to Predict Total Hip Replacement on Radiographs: The Total Hip Replacement Prediction (THREP) Model

BACKGROUND

There are few methods for accurately assessing the risk of total hip arthroplasty (THA) in patients with osteoarthritis. A novel and reliable method that could play a substantial role in research and clinical routine should be investigated. The purpose of the present study was to develop a deep-learning model that can reliably predict the risk of THA with use of radiographic images and clinical symptom data.

METHODS

This retrospective, multicenter, case-control study assessed hip joints on weighted-bearing anteroposterior pelvic radiographs obtained from Osteoarthritis Initiative (OAI) participants. Participants who underwent THA were matched to controls according to age, sex, body mass index, and ethnicity. Cases and controls were uniformly split into training, validation, and testing data sets at proportions of 72% (n = 528), 14% (n = 104), and 14% (n = 104), respectively. Images and clinical symptom data were passed through a detection model and a deep convolutional neural network (DCNN) model to predict the probability of THA within 9 years as well as the most likely time period for THA (0 to 2 years, 3 to 5 years, 6 to 9 years). Model performance was assessed with use of the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity in the testing set.

RESULTS

A total of 736 participants were evaluated, including 184 cases and 552 controls. The prediction model achieved an overall accuracy, sensitivity, and specificity of 91.35%, 92.59% and 86.96%, respectively, with an AUC of 0.944, for THA within 9 years. The AUC of the DCNN model for assessing the most likely time period was 0.907 for 0 to 2 years, 0.916 for 3 to 5 years, and 0.841 for 6 to 9 years. Gradient-weighted class activation mapping closely corresponded to regions affecting the prediction of the DCNN model.

CONCLUSIONS

The proposed DCNN model is a reliable and valid method to predict the probability of THA-within limitations. It could assist clinicians in patient counseling and decision-making regarding the timing of the intervention. In the future, by increasing the size of the data set, enhancing the ethnic and socioeconomic diversity of the participants, and improving the follow-up rate, the quality of the conclusions can be further improved.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Plasma Cartilage Acidic Protein 1 Measured by ELISA Is Associated With the Progression to Total Joint Replacement in Postmenopausal Women

OBJECTIVE

To investigate the association of plasma cartilage acidic protein 1 (CRTAC1), a novel biochemical marker of osteoarthritis (OA), and total joint replacement (TJR) in postmenopausal women.

METHODS

The association of plasma CRTAC1 with the incidence of TJR was investigated in a prospective cohort including 478 postmenopausal women. A total of 38 women underwent a TJR for OA during a median follow-up of 18 years. Every one of the TJR cases were age- and BMI (kg/m2)-matched with 2 controls with no TJR from the same cohort. Plasma CRTAC1 was measured before TJR. The association between CRTAC1 and TJR incidence was investigated by conditional logistic regression.

RESULTS

Increased CRTAC1 was associated with a higher risk of TJR with an odds ratio (OR) of 1.80 (95% CI 1.11-2.92) for 1 SD increase, which remained significant after adjusting for Western Ontario and McMaster Universities Osteoarthritis Index, knee OA baseline severity (Kellgren-Lawrence grade), hip OA, and hip bone mineral density. Urinary crosslinked C-telopeptide of type II collagen (CTX-II) was also associated with a higher risk of TJR with an adjusted OR of 1.83 (95% CI 1.11-3.00). When CRTAC1 and CTX-II were included in the same model, both markers were significantly associated with TJR with similar ORs.

CONCLUSION

CRTAC1 is a new risk indicator of TJR for OA in postmenopausal women. Combined with knee and hip OA and CTX-II, it may help to identify subjects at risk for TJR.

Proteomic profiling of human menisci from mild joint degeneration and end-stage osteoarthritis versus healthy controls

Objective

To gain new insight into the molecular changes of the meniscus by comparing the proteome profiles of healthy controls with mild degeneration and end-stage osteoarthritis (OA).

Method

We obtained tissue plugs from lateral and medial menisci of 37 individuals (central part of the posterior horn) classified as healthy (n ​= ​12), mild signs of joint damage (n ​= ​13) and end-stage OA (n ​= ​12). The protein profile was analysed by nano-liquid chromatography-mass spectrometry using data-independent acquisition and quantified by Spectronaut. Linear-mixed effects modelling was applied to extract the between-group comparisons.

Results

A similar protein profile was observed for the mild group as compared to healthy controls while the most different group was end-stage OA mainly for the medial compartment. When a pattern of gradual change in protein levels from healthy to end-stage OA was required, a 42-proteins panel was identified, suggesting a potential role in OA development. The levels of QSOX1 were lower and G6PD higher in the mild group following the proposed protein abundance pattern. Qualitative protein changes suggest lower levels of CYTL1 as a potential biomarker of early joint degradation.

Conclusion

For future targeted proteomic approaches, we propose a candidate panel of 42 proteins based on gradually altered meniscal posterior horn protein abundance patterns associated with joint degradation.

Acyl coenzyme A binding protein (ACBP): An aging- and disease-relevant "autophagy checkpoint"

Acyl coenzyme A binding protein (ACBP), also known as diazepam-binding inhibitor (DBI), is a phylogenetically ancient protein present in some eubacteria and the entire eukaryotic radiation. In several eukaryotic phyla, ACBP/DBI transcends its intracellular function in fatty acid metabolism because it can be released into the extracellular space. This ACBP/DBI secretion usually occurs in response to nutrient scarcity through an autophagy-dependent pathway. ACBP/DBI and its peptide fragments then act on a range of distinct receptors that diverge among phyla, namely metabotropic G protein-coupled receptor in yeast (and likely in the mammalian central nervous system), a histidine receptor kinase in slime molds, and ionotropic gamma-aminobutyric acid (GABA)A receptors in mammals. Genetic or antibody-mediated inhibition of ACBP/DBI orthologs interferes with nutrient stress-induced adaptations such as sporulation or increased food intake in multiple species, as it enhances lifespan or healthspan in yeast, plant leaves, nematodes, and multiple mouse models. These lifespan and healthspan-extending effects of ACBP/DBI suppression are coupled to the induction of autophagy. Altogether, it appears that neutralization of extracellular ACBP/DBI results in "autophagy checkpoint inhibition" to unleash the anti-aging potential of autophagy. Of note, in humans, ACBP/DBI levels increase in various tissues, as well as in the plasma, in the context of aging, obesity, uncontrolled infection or cardiovascular, inflammatory, neurodegenerative, and malignant diseases.

Decreased plasma cartilage acidic protein 1 in COVID-19

Cartilage acidic protein-1 (CRTAC1) is produced by several cell types, including Type 2 alveolar epithelial (T2AE) cells that are targeted by SARS-CoV2. Plasma CRTAC1 is known based on proteomic surveys to be low in patients with severe COVID-19. Using an ELISA, we found that patients treated for COVID-19 in an ICU almost uniformly had plasma concentrations of CRTAC1 below those of healthy controls. Magnitude of decrease in CRTAC1 distinguished COVID-19 from other causes of acute respiratory decompensation and correlated with established metrics of COVID-19 severity. CRTAC1 concentrations below those of controls were found in some patients a year after hospitalization with COVID-19, long COVID after less severe COVID-19, or chronic obstructive pulmonary disease. Decreases in CRTAC1 in severe COVID-19 correlated (r = 0.37, p = 0.0001) with decreases in CFP (properdin), which interacts with CRTAC1. Thus, decreases of CRTAC1 associated with severe COVID-19 may result from loss of production by T2AE cells or co-depletion with CFP. Determination of significance of and reasons behind decreased CRTAC1 concentration in a subset of patients with long COVID will require analysis of roles of preexisting lung disease, impact of prior acute COVID-19, age, and other confounding variables in a larger number of patients.

Could Osteopontin be a useful biomarker in the diagnosis and severity assessment of osteoarthritis? A systematic review and meta-analysis of recent evidence

PURPOSE

Osteoarthritis (OA) patients demonstrated higher Osteopontin (OPN) plasma, serum, and synovial fluid concentrations than healthy individuals. In the present study, we aimed to investigate whether OPN could be used as a diagnostic or prognostic marker for OA symptom/disease severity.

METHODS

Using Web of Science, PubMed, Scopus, and Embase, we conducted a systematic review and meta-analysis of studies that measured OPN levels in OA patients' plasma, serum, or synovial fluid. After setting the eligibility criteria, data extraction, and quality assessment of the identified studies, we performed statistical analysis using Revman 5.4 and Open Meta analyst.

RESULTS

OPN has been found to be associated with advanced knee joint damage in OA patients. In addition, higher expression of OPN is thought to be associated with disease progression. Nevertheless, further studies should examine the role of other markers of chronic bone damage, such as leptin and sclerostin. This systematic review and meta-analysis included 14 studies with a total of 776 cases and 530 controls. OPN was significantly elevated in osteoarthritis patients' plasma, serum, and synovial fluid samples, with significant heterogeneity between studies.

CONCLUSION

We recommend that OPN plasma and synovial fluid levels be measured as a diagnostic and prognostic marker to determine the severity of OA symptoms.