Multivariable logistic and linear regression models for identification of clinically useful biomarkers for osteoarthritis

Methods in DNA methylation array dataset analysis: A review

Understanding the intricate relationships between gene expression levels and epigenetic modifications in a genome is crucial to comprehending the pathogenic mechanisms of many diseases. With the advancement of DNA Methylome Profiling techniques, the emphasis on identifying Differentially Methylated Regions (DMRs/DMGs) has become crucial for biomarker discovery, offering new insights into the etiology of illnesses. This review surveys the current state of computational tools/algorithms for the analysis of microarray-based DNA methylation profiling datasets, focusing on key concepts underlying the diagnostic/prognostic CpG site extraction. It addresses methodological frameworks, algorithms, and pipelines employed by various authors, serving as a roadmap to address challenges and understand changing trends in the methodologies for analyzing array-based DNA methylation profiling datasets derived from diseased genomes. Additionally, it highlights the importance of integrating gene expression and methylation datasets for accurate biomarker identification, explores prognostic prediction models, and discusses molecular subtyping for disease classification. The review also emphasizes the contributions of machine learning, neural networks, and data mining to enhance diagnostic workflow development, thereby improving accuracy, precision, and robustness.

The Impact of Weight-bearing Exercise, Non-Weight-bearing Exercise, and Cardiovascular Stress on Biochemical Markers of Cartilage Turnover in Patients With Mild to Moderate Knee Osteoarthritis: A Sequential, Cross-Over, Clinical Study

OBJECTIVE

To investigate how running, cycling, and sedentary cardiovascular stress impact biomarkers of cartilage turnover acutely in subjects with knee osteoarthritis (OA).

DESIGN

This was a sequential, cross-over, clinical study. Forty subjects with primary knee OA underwent moderate-to-high-intensity cycling, running, and adrenaline infusion on separate days. Blood was sampled before, during, and at 6-time points after intervention. On a control day, similar samples were taken. Biomarkers of type II collagen degradation (C2M, T2CM, Coll2-1, Coll2-1NO2), formation (PRO-C2), and aggrecan degradation (ARGS) were measured.

RESULTS

Mean age was 60.4 years, 40% were male, 45% had cumulated Kellgren-Lawrence (KL)-grade (Right + Left knee) of 2 to 3 and 55% had 4 to 6. Analyzing overall changes, area under the curve was significantly lower compared with resting values for ARGS and C2M after cycling and for ARGS after running. Considering individual time points, peak changes in biomarker levels showed reduction in C2M shortly following cycling (T20min = -12.3%, 95% confidence interval [CI]: -19.3% to -5.2%). PRO-C2 increased during cycling (T10min = 14.0%, 95% CI = 4.1% to 23.8%) and running (T20min = 16.5%, 95% CI = 4.3% to 28.6%). T2CM decreased after cycling (T50min = -19.9%, 95% CI = -29.2% to -10.6%), running (T50min = -22.8%, 95% CI = -32.1% to -13.5%), and infusion of adrenaline (peak, T50min = -9.8%, 95% CI = -20.0% to 0.4%). A latent increase was seen in Coll2-1 240 minutes after running (T260min = 21.7%, 95% CI = -1.6% to 45.1%).

CONCLUSION

Exercise had an impact on cartilage markers, but it did not suggest any detrimental effect on cartilage. Changes following adrenaline infusion suggest a sympathomimetic influence on the serological composition of biomarkers.

Load-induced blood marker kinetics in patients with medial knee compartment osteoarthritis are associated with accumulated load and patient reported outcome measures

Background

This study aimed to quantify the mechanoresponse of 10 blood marker candidates for joint metabolism to a walking stress test in patients with knee osteoarthritis and to determine the association among marker kinetics and with accumulated load and patient reported outcomes.

Methods

24 patients with knee osteoarthritis completed questionnaires, and a 30-minute walking stress test with six blood serum samples and gait analysis. Concentrations of cartilage oligomeric matrix protein (COMP), matrix metalloproteinases (MMP)-1, -3, and -9, epitope resulting from cleavage of type II collagen by collagenases (C2C), type II procollagen (CPII), interleukin (IL)-6, proteoglycan (PRG)-4, A disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS)-4, and resistin were determined by enzyme-linked immunosorbent assays, Joint load (moments and compartmental forces) was estimated using musculoskeletal modeling using gait analysis data.

Results

COMP and MMP-3 showed an immediate increase after the walking stress followed by a decrease. MMP-9 and resistin showed a delayed decrease below pre-stress levels. ∆COMP correlated with ∆MMP-3 for most time points. ∆MMP-9 correlated with ∆resistin for most time points. The load-induced increase in blood marker levels correlated among blood markers and time points. C2C and resistin correlated positively and C2C/CPII and MMP2 correlated negatively with load during gait. Immediate relative ∆CPII and ∆MMP1 and delayed relative ∆COMP, ∆IL6, ∆C2C, ∆CPII, ∆MMP1 and ∆MMP3 correlated with the load accumulated during the walking stress. Baseline C2C levels correlated with Knee Osteoarthritis Outcome Score (KOOS) subscales and load-induced changes in MMP-3 with KOOS and Short Form 36 quality of life subscores (P<0.05).

Conclusions

The distinct and differentiated physiological response to the walking stress depends on accumulated load and appears relevant for patient reported osteoarthritis outcome and quality of life and warrants further investigation in the context of disease progression.ClinicalTrials.gov registration: NCT02622204.

Biomarker discovery process at binomial decision point (2BDP): Analytical pipeline to construct biomarker panel

A clinical incident is typically manifested by several molecular events; therefore, it seems logical that a successful diagnosis, prognosis, or stratification of a clinical landmark require multiple biomarkers. In this report, we presented a machine learning pipeline, namely "Biomarker discovery process at binomial decision point" (2BDP) that took an integrative approach in systematically curating independent variables (e.g., multiple molecular markers) to explain an output variable (e.g., clinical landmark) of binary in nature. In a logical sequence, 2BDP includes feature selection, unsupervised model development and cross validation. In the present work, the efficiency of 2BDP was demonstrated by finding three biomarker panels that independently explained three stages of Alzheimer's disease (AD) marked as Braak stages I, II and III, respectively. We designed three assortments from the entire cohort based on these Braak stages; subsequently, each assortment was split into two populations at Braak score I, II or III. 2BDP systematically integrated random forest and logistic regression fitting model to find biomarker panels with minimum features that explained these three assortments, e.g., significantly differentiated two populations segregated by Braak stage I, II or III, respectively. Thereafter, the efficacies of these panels were measured by the area under the curve (AUC) values of the receiver operating characteristic (ROC) plot. The AUC-ROC was calculated by two cross-validation methods. Final set of gene markers was a mix of novel and a priori established AD signatures. These markers were weighted by unique coefficients and linearly connected in a group of 2-10 to explain Braak stage I, II or III by AUC ≥ 0.8. Small sample size and a lack of distinctly recruited Training and Test sets were the limitations of the present undertaking; yet 2BDP demonstrated its capability to curate a panel of optimum numbers of biomarkers to describe the outcome variable with high efficacy.

An Atlas of the Knee Joint Proteins and Their Role in Osteoarthritis Defined by Literature Mining

Osteoarthritis (OA) is the most prevalent rheumatic pathology. However, OA is not simply a process of wear and tear affecting articular cartilage but rather a disease of the entire joint. One of the most common locations of OA is the knee. Knee tissues have been studied using molecular strategies, generating a large amount of complex data. As one of the goals of the Rheumatic and Autoimmune Diseases initiative of the Human Proteome Project, we applied a text-mining strategy to publicly available literature to collect relevant information and generate a systematically organized overview of the proteins most closely related to the different knee components. To this end, the PubPular literature-mining software was employed to identify protein-topic relationships and extract the most frequently cited proteins associated with the different knee joint components and OA. The text-mining approach searched over eight million articles in PubMed up to November 2022. Proteins associated with the six most representative knee components (articular cartilage, subchondral bone, synovial membrane, synovial fluid, meniscus, and cruciate ligament) were retrieved and ranked by their relevance to the tissue and OA. Gene ontology analyses showed the biological functions of these proteins. This study provided a systematic and prioritized description of knee-component proteins most frequently cited as associated with OA. The study also explored the relationship of these proteins to OA and identified the processes most relevant to proper knee function and OA pathophysiology.

Evaluation of mechanistic serum and urine biomarkers for secondary osteoarthritis associated with developmental dysplasia of the hip

Objective

Determine measurable differences for mechanistic urine and serum biomarkers in patients with developmental dysplasia of the hip (DDH) prior to, and following, secondary hip osteoarthritis (OA) when compared to controls.

Design

Urine and serum were collected from individuals with developmental dysplasia of the hip (n = 39), prior to (Pre-OA DDH, n = 32) and following diagnosis of secondary hip OA (Post-OA DDH, n = 7), age-matched Pre-OA controls (n = 35), and age-matched Post-OA controls (n = 12). Samples were analyzed for protein biomarkers with potential for differentiation of hip status through a Mann-Whitney U test with a Benjamini-Hochberg correction.

Results

Several interleukin and degradation related proteins were found to be differentially expressed when comparing DDH-related hip status prior to and following diagnosis of hip OA. In addition, MCP-1 and TIMP-1 were significantly different between younger and older patients in the control cohorts.

Conclusion

These results provide initial evidence for serum and urine protein biomarkers that define clinically relevant stages of symptomatic DDH and its progression to secondary hip osteoarthritis categorized by known mechanisms of disease.

Level of evidence

III.

Unlocking the Potential of Circulating miRNAs in the Breast Cancer Neoadjuvant Setting: A Systematic Review and Meta-Analysis

The potential role of circulating microRNAs (miRNAs) as biomarkers in breast cancer (BC) management has been widely reported. However, the numerous discrepancies between studies in this regard hinders the implementation of circulating miRNAs in routine clinical practice. In the context of BC patients undergoing neoadjuvant chemotherapy (NAC), the possibility of predicting NAC response may lead to prognostic improvements by individualizing post-neoadjuvant therapy. In this context, the present meta-analysis aims to clarify circulating miRNAs' predictive role with respect to NAC response among BC patients. We conducted a comprehensive literature search on five medical databases until 16 February 2023. We pooled the effect sizes of each study by applying a random-effects model. Cochran's Q test (p-level of significance set at 0.05) scores and I² values were assessed to determine between-study heterogeneity. The PROBAST (Prediction Model Risk of Bias Assessment Tool) tool was used to evaluate the selected studies' risk of bias. Overall, our findings support the hypothesis that circulating miRNAs, specifically miR-21-5p and miR-155-5p, may act as predictive biomarkers in the neoadjuvant setting among BC patients. However, due to the limited number of studies included in this meta-analysis and the high degrees of clinical and statistical heterogeneity, further research is required to confirm the predictive power of circulating miR-21-5p and miR-155-5p.

Emerging molecular biomarkers in osteoarthritis pathology

Osteoarthritis (OA) is the most common form of arthritis resulting in joint discomfort and disability, culminating in decline in life quality. Attention has been drawn in recent years to disease-associated molecular biomarkers found in readily accessible biofluids due to low invasiveness of acquisition and their potential to detect early pathological molecular changes not observed with traditional imaging methodology. These biochemical markers of OA have been found in synovial fluid, blood, and urine. They include emerging molecular classes, such as metabolites and noncoding RNAs, as well as classical biomarkers, like inflammatory mediators and by-products of degradative processes involving articular cartilage. Although blood-based biomarkers tend to be most studied, the use of synovial fluid, a more isolated biofluid in the synovial joint, and urine as an excreted fluid containing OA biomarkers can offer valuable information on local and overall disease activity, respectively. Furthermore, larger clinical studies are required to determine relationships between biomarkers in different biofluids, and their impacts on patient measures of OA. This narrative review provides a concise overview of recent studies of OA using these four classes of biomarkers as potential biomarker for measuring disease incidence, staging, prognosis, and therapeutic intervention efficacy.

The role of apoptosis in the pathogenesis of osteoarthritis

PURPOSE

Apoptosis is an important physiological process, making a great difference to development and tissue homeostasis. Osteoarthritis (OA) is a chronic joint disease characterized by degeneration and destruction of articular cartilage and bone hyperplasia. This purpose of this study is to provide an updated review of the role of apoptosis in the pathogenesis of osteoarthritis.

METHODS

A comprehensive review of the literature on osteoarthritis and apoptosis was performed, which mainly focused on the regulatory factors and signaling pathways associated with chondrocyte apoptosis in osteoarthritis and other pathogenic mechanisms involved in chondrocyte apoptosis.

RESULTS

Inflammatory mediators such as reactive oxygen species (ROS), nitric oxide (NO), IL-1β, tumor necrosis factor-α (TNF-α), and Fas are closely related to chondrocyte apoptosis. NF-κB signaling pathway, Wnt signaling pathway, and Notch signaling pathway activate proteins and gene targets that promote or inhibit the progression of osteoarthritis disease, including chondrocyte apoptosis and ECM degradation. Long non-coding RNAs (LncRNAs) and microRNAs (microRNAs) have gradually replaced single and localized research methods and become the main research approaches. In addition, the relationship between cellular senescence, autophagy, and apoptosis was also briefly explained.

CONCLUSION

This review offers a better molecular delineation of apoptotic processes that may help in designing new therapeutic options for OA treatment.

Risk Factors for the Progression of Varus Ankle Osteoarthritis

Background

With the increase in life expectancy, the prevalence of ankle osteoarthritis (OA) is also expected to increase in the future. Functional disability and diminished quality of life associated with end-stage ankle OA are comparable to those associated with end-stage hip or knee OA. However, there are few reports on the natural history and progression of patients with ankle OA. Hence, this study aimed to evaluate the risk factors for progression in patients with varus ankle OA.

Methods

We evaluated 68 ankles from 58 patients diagnosed with varus ankle OA using radiography performed at intervals over at least 60 months. The mean follow-up period was 99 ± 40 months. Narrowing of the joint space and increasing osteophyte formation were defined as ankle OA progression. Multivariate analysis was performed using logistic regression to predict the odds of progression; the model included 2 clinical variables and 7 radiographic variables.

Results

Of the 68 ankles, 39 (57%) progressed. In multivariable logistic regression analyses, patient's age (odds ratio [OR] 0.92, 95% CI 0.85-0.99, P < .03), and the talar tilt (TT; OR 2.2, 95% CI 1.39-3.42, P = .001) were found to be independent factors for progression. The area under the curve (AUC) of the receiver operating characteristic curve for TT was 0.844, and the cutoff value was 2.0 degrees.

Conclusion

TT was found to be a primary factor associated with varus ankle OA progression. The risk appeared higher in patients with a TT more than 2.0 degrees.

Level of Evidence

Level III, retrospective case control study.

Associations between biomarkers of matrix metabolism and inflammation with pain and fatigue in participants suspected of early hip and or knee osteoarthritis: data from the CHECK study

OBJECTIVES

To assess the associations of biomarkers in serum [highsensitivity C-reactive protein (hs-CRP), serum cartilage oligomeric protein (sCOMP), serum propeptide of type I procollagen (sPINP) and serum osteocalcin (sOC)] and urine [urinary type II collagen telopeptide (uCTX-2)] with the extent and progression of nocturnal pain, pain while walking, and fatigue in participants with hip and/or knee pain suspected to be early stage osteoarthritis (OA).

METHODS

hs-CRP, uCTX-2, sCOMP, sPINP and sOC were measured at baseline in 1,002 participants of the Cohort Hip and Cohort Knee (CHECK). Nocturnal pain, pain while walking and fatigue were assessed by self-reported questionnaires at baseline and 2-year follow-up. Associations between these biomarkers and symptoms were examined using logistic and linear regression analyses.

RESULTS

hs-CRP was significantly associated with mild nocturnal pain (OR 1.18 95% CI 1.01-1.37), with mild and moderate pain while walking (OR 1.17 95% CI 1.01-1.35 and OR 1.56 95% CI 1.29-1.90, respectively) and with progression of nocturnal pain (OR 1.25 95% CI 1.07-1.46). uCTX-2 was associated with mild nocturnal pain (OR 1.40 95% CI 1.05-1.85) and with mild and severe-extreme pain while walking (OR 1.35 95% CI 1.04-1.75 and OR 2.55 95% CI 1.03-6.34, respectively). sPINP was associated with severe-extreme nocturnal pain (OR 0.45 95% CI 0.25-0.82). No significant associations were found for sCOMP and sOC, nor for any of the biomarkers and fatigue.

CONCLUSION

This study of biomarkers in a large cohort of participants with hip and/or knee pain suspected to reflect early stage hip and/or knee OA suggests that inflammation and cartilage matrix degeneration play a role in pain, but not in fatigue.

Clinical monitoring in osteoarthritis: Biomarkers

OBJECTIVE

The purpose of this overview of osteoarthritis (OA) biomarkers is to provide the non-specialist with a toolbox, based on experience acquired by biomarker researchers over many years, to understand biomarkers in general and their use in the OA field.

METHODS

We provide an update on this subject since the OARSI Primer on osteoarthritis (OA) nearly a decade ago.

RESULTS

Since the last update, the importance of molecular biomarkers has been increasingly recognized in the field, but no OA-related biomarkers have been adopted for routine use in clinical practice. The current lack of chondroprotective treatments for OA impairs the assessment, validation and qualification of the potential role of biomarkers as tools for monitoring disease status and patient responses to treatment of OA. Yet there is no lack of an evolving compendium of OA-related biomarkers, ever more fit-for-purpose, that could currently facilitate drug development for OA. We provide an abbreviated update and overview of specific soluble OA-related biomarkers for this new OARSI Primer on OA with OA-relevant examples encompassing the concepts of biomarker nomenclature, qualification, interpretation, measurement, reporting requirements, application to research, drug discovery and clinical care, and future needs for biomarker advancement.

CONCLUSION

Appropriate biomarkers should play a role at all stages of OA diagnosis, prognosis, drug development, and treatment. The future of OA biomarker research and development holds great promise as its foundation is increasingly robust.

Plasma proteomics identifies CRTAC1 as a biomarker for osteoarthritis severity and progression

OBJECTIVES

The aim of this study was to identify biomarkers for radiographic OA severity and progression acting within the inflammation and metabolic pathways.

METHODS

For 3517 Rotterdam Study participants, 184 plasma protein levels were measured using Olink inflammation and cardiometabolic panels. We studied associations with severity and progression of knee, hip and hand OA and a composite overall OA burden score by multivariable regression models, adjusting for age, sex, cell counts and BMI.

RESULTS

We found 18 significantly associated proteins for overall OA burden, of which 5 stayed significant after multiple testing correction: circulating cartilage acidic protein 1 (CRTAC1), cartilage oligomeric matrix protein (COMP), thrombospondin 4, IL-18 receptor 1 (IL-18R1) and TNF ligand superfamily member 14. These proteins were also associated with progression of knee OA, with the exception of IL-18R1. The strongest association was found for the level of CRTAC1, with 1 s.d. increase in protein level resulting in an increase of 0.09 (95% CI 0.06, 0.12) in the overall OA Kellgren-Lawrence sum score (P = 2.9 × 10-8) in the model adjusted for age, sex, BMI and cell counts. This association was also present with the severity of OA in all three joints and progression of knee OA and was independent of BMI. We observed a stronger association for CRTAC1 with OA than for the well-known OA biomarker COMP.

CONCLUSION

We identified several compelling biomarkers reflecting the overall OA burden and the increased risk for OA progression. CRTAC1 was the most compelling and robust biomarker for OA severity and progression. Such a biomarker may be used for disease monitoring.

Association between osteoarthritis-related serum biochemical markers over 11 years and knee MRI-based imaging biomarkers in middle-aged adults

OBJECTIVE

To describe the associations between osteoarthritis (OA)-related biochemical markers (COMP, MMP-3, HA) and MRI-based imaging biomarkers in middle-aged adults over 10-13 years.

METHODS

Blood serum samples collected during the Childhood Determinants of Adult Health (CDAH)-1 study (year:2004-06; n = 156) and 10-13 year follow-up at CDAH-3 (n = 167) were analysed for COMP, MMP-3, and HA using non-isotopic ELISA. Knee MRI scans obtained during the CDAH-knee study (year:2008-10; n = 313) were assessed for cartilage volume and thickness, subchondral bone area, cartilage defects, and BML.

RESULTS

In a multivariable linear regression model describing the association of baseline biochemical markers with MRI-markers (assessed after 4-years), we found a significant negative association of standardised COMP with medial femorotibial compartment cartilage thickness (β:-0.070; 95%CI:-0.138,-0.001), and standardised MMP-3 with patellar cartilage volume (β:-141.548; 95%CI:-254.917,-28.179) and total bone area (β:-0.729; 95%CI:-1.340,-0.118). In multivariable Tobit regression model, there was a significant association of MRI-markers with biochemical markers (assessed after 6-9 years); a significant negative association of patellar cartilage volume (β:-0.001; 95%CI:-0.002,-0.00004), and total bone area (β:-0.158; 95%CI-0.307,-0.010) with MMP-3, and total cartilage volume (β:-0.001; 95%CI:-0.001,-0.0001) and total bone area (β:-0.373; 95%CI:-0.636,-0.111) with COMP. No significant associations were observed between MRI-based imaging biomarkers and HA.

CONCLUSION

COMP and MMP-3 levels were negatively associated with knee cartilage thickness and volume assessed 4-years later, respectively. Knee cartilage volume and bone area were negatively associated with COMP and MMP-3 levels assessed 6-9 years later. These results suggest that OA-related biochemical markers and MRI-markers are interrelated in early 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.

Gender-Related Aspects in Osteoarthritis Development and Progression: A Review

Osteoarthritis (OA) is a common degenerative joint disease treated mostly symptomatically before approaching its definitive treatment, joint arthroplasty. The rapidly growing prevalence of OA highlights the urgent need for a more efficient treatment strategy and boosts research into the mechanisms of OA incidence and progression. As a multifactorial disease, many aspects have been investigated as contributors to OA onset and progression. Differences in gender appear to play a role in the natural history of the disease, since female sex is known to increase the susceptibility to its development. The aim of the present review is to investigate the cues associated with gender by analyzing various hormonal, anatomical, molecular, and biomechanical parameters, as well as their differences between sexes. Our findings reveal the possible implications of gender in OA onset and progression and provide evidence for gaps in the current state of art, thus suggesting future research directions.

Osteoarthritis in year 2021: biochemical markers

OBJECTIVE

To summarize recent scientific advances in protein-derived soluble biomarkers of osteoarthritis.

DESIGN

A systematic search on the PubMed electronic database of clinical studies on protein-derived soluble biochemical markers of osteoarthritis in humans that were published between January 1st 2020 and March 31th 2021. The studies were selected on the basis of objective criteria and summarized in a table. Then they were described in a narrative review.

RESULTS

Out of 1971 publications, 48 fulfilled all selection criteria and 16 were selected by the author for the narrative review. The papers were classified according their clinical significance as defined in the BIPEDS classification. Two papers investigated the "burden of disease", two were dedicated to "investigative biomarkers", four papers question the "prognosis", three the "efficacy of treatment" and five the "diagnosis and phenotyping" value of protein-derived biomarkers.

CONCLUSIONS

Currently, biomarkers research is focused on their use as tools to identify molecular endotypes and clinical phenotypes and to facilitate patient screening and monitoring in clinical trials. This approach should allow a more targeted management of patients suffering from osteoarthritis.

Blood and urine biomarkers in osteoarthritis - an update on cartilage associated type II collagen and aggrecan markers

PURPOSE OF REVIEW

Osteoarthritis (OA) is a painful disease for which drug development has proven difficult. One major reason for this is the heterogeneity of the disease and the current lack of operationalized means to distinguish various disease endotypes (molecular subtypes). Biomarkers measured in blood or urine, reflecting joint tissue turnover, have been developed and tested during the last decades. In this narrative review, we provide highlights on biomarkers derived from the two most studied and abundant cartilage proteins - type II collagen and aggrecan.

RECENT FINDINGS

Multiple biomarkers assessing type II collagen degradation and formation, and aggrecan turnover have been developed. Several markers, such as uCTX-II, have been validated for their association with disease severity and prognosis, as well as pharmacodynamically used to describe the mode of action and efficacy of drugs in development. There is a great need for biomarkers for subdividing patients (i.e., endotyping) and recent scientific advances have not yet come closer to achieving this goal.

SUMMARY

There is strong support for using biomarkers for understanding OA, reflecting degradation and formation of the joint tissues, focused on type II collagen and aggrecan. There is still a lack of in vitro diagnostics, in all contexts of use.

Directly and Simultaneously Expressing Absolute and Relative Treatment Effects in Medical Data Models and Applications

Logistic regression is widely used in the analysis of medical data with binary outcomes to study treatment effects through (absolute) treatment effect parameters in the models. However, the indicative parameters of relative treatment effects are not introduced in logistic regression models, which can be a severe problem in efficiently modeling treatment effects and lead to the wrong conclusions with regard to treatment effects. This paper introduces a new enhanced logistic regression model that offers a new way of studying treatment effects by measuring the relative changes in the treatment effects and also incorporates the way in which logistic regression models the treatment effects. The new model, called the Absolute and Relative Treatment Effects (AbRelaTEs) model, is viewed as a generalization of logistic regression and an enhanced model with increased flexibility, interpretability, and applicability in real data applications than the logistic regression. The AbRelaTEs model is capable of modeling significant treatment effects via an absolute or relative or both ways. The new model can be easily implemented using statistical software, with the logistic regression model being treated as a special case. As a result, the classical logistic regression models can be replaced by the AbRelaTEs model to gain greater applicability and have a new benchmark model for more efficiently studying treatment effects in clinical trials, economic developments, and many applied areas. Moreover, the estimators of the coefficients are consistent and asymptotically normal under regularity conditions. In both simulation and real data applications, the model provides both significant and more meaningful results.

Zika virus infection and microcephaly: spatial analysis and socio-environmental determinants in a region of high Aedes aegypti infestation in the Central-West Region of Brazil

Background

More than 5 years after the Zika virus (ZIKV) epidemic, Zika infection remains a major concern in regions with high Aedes infestation. The objectives of this study were (i) to identify clusters of ZIKV infection and microcephaly, and/or central nervous system (CNS) alterations associated with congenital infection during the epidemic peak in 2016 and subsequently, in 2017 and 2018; (ii) to measure the non-spatial correlation between ZIKV infection and microcephaly and/or CNS alterations associated with congenital infection; and (iii) to analyse the sociodemographic/economic, health, and environmental determinants associated with the incidence of ZIKV in a region of high infestation by Aedes aegypti in the Central-West Region of Brazil.

Methods

This ecological study analysed 246 municipalities in the state of Goiás (6.9 million inhabitants). The data were obtained from the Information System for Notifiable Diseases (ZIKV cases) and the Public Health Event Registry (microcephaly and/or CNS alterations associated with congenital infection). Incidence rates and prevalence of ZIKA infection were smoothed by an empirical Bayesian estimator (LEbayes), producing the local empirical Bayesian rate (LEBR). In the spatial analysis, ZIKV infection and microcephaly cases were georeferenced by the municipality of residence for 2016 and grouped for 2017 and 2018. Global Moran's I and the Hot Spot Analysis tool (Getis-Ord Gi* statistics) were used to analyse the spatial autocorrelation and clusters of ZIKV infection and microcephaly, respectively. A generalised linear model from the Poisson family was used to assess the association between ecological determinants and the smoothing incidence rate of ZIKV infection.

Results

A total of 9892 cases of acute ZIKV infection and 121 cases of microcephaly were confirmed. The mean LEBR of the ZIKV infection in the 246 municipalities was 22.3 cases/100,000 inhabitants in 2016, and 10.3 cases/100,000 inhabitants in 2017 and 2018. The LEBR of the prevalence rate of microcephaly and/or CNS alterations associated with congenital infection was 7 cases/10,000 live births in 2016 and 2 cases/10,000 live births during 2017–2018. Hotspots of ZIKV infection and microcephaly cases were identified in the capital and neighbouring municipalities in 2016, with new clusters in the following years. In a multiple regression Poisson analysis, ZIKV infection was associated with higher population density, the incidence of dengue, Aedes larvae infestation index, and average rainfall. The important determinant of ZIKV infection incidence reduction was the increase in households attended by endemic disease control agents.

Conclusions

Our analyses were able to capture, in a more granular way, aspects that make it possible to inform public managers of the sentinel areas identified in the post-epidemic hotspots.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06805-1.

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.

Characterizing the alkaptonuria joint and spine phenotype and assessing the effect of homogentisic acid lowering therapy in a large cohort of 87 patients

A large alkaptonuria (AKU) cohort was studied to better characterize the poorly understood spondyloarthropathy of rare disease AKU. Eighty-seven patients attended the National Alkaptonuria Centre (NAC) between 2007 and 2020. Seven only attended once. Fifty-seven attended more than once and received nitisinone 2 mg daily. Twenty-three attended at least twice without receiving nitisinone. Assessments included questionnaire analysis, ^18F Positron emission tomography computerised tomography (PETCT), as well as photographs of ochronotic pigment in eyes and ears at baseline when 2 mg nitisinone was commenced and yearly thereafter. Blood and urine samples were collected for chemical measurement. The prevalence of ochronosis, as well as pain, PETCT and combined pain and PETCT scores, was greatly increased at 90.5%, 85.7%, 100%, and 100%, respectively. Joint pain scores were greatest in proximal joints in upper and lower limbs. PETCT joint scores were higher in proximal joints in upper limb but higher in distal joints in the lower limb. Spine pain scores were highest in lumbar, followed by cervical, thoracic, and cervical regions at 77.4%, 59.5%, 46.4%, and 25%, respectively. PETCT spine scores were highest in thoracic followed by lumbar, cervical, and sacroiliac regions at 74.4%, 70.7%, 64.6%, and 47.8% respectively; ochronosis associated closely with spondyloarthropathy scores (R = .65; P < .0001). Nitisinone reversed ochronosis significantly, with a similar pattern of decreased joint and spine disease. Spondyloarthropathy is a highly prevalent feature in this NAC cohort. Ochronosis appears to be associated with spondyloarthropathy. Nitisinone decreases ochronosis and had a similar nonsignificant effect pattern on spondyloarthropathy.

Data Integration Reveals the Potential Biomarkers of Circulating MicroRNAs in Osteoarthritis

The abnormal expression of circulating miRNAs (c-miRNAs) has become an emerging field in the development of miRNAs-based diagnostic and therapeutic tools for human diseases, including osteoarthritis (OA). OA is the most common form of arthritis leading to disability and a major socioeconomic burden. The abnormal expression of miRNAs plays important roles in the pathogenesis of OA. Unraveling the role of miRNAs in the pathogenesis of OA will throw light on the potential for the development of miRNAs-based diagnostic and therapeutic tools for OA. This article reviews and highlights recent advances in the study of miRNAs in OA, with specific demonstration of the functions of miRNA, especially c-miRNA, in OA pathogenesis as well as its potential implication in the treatment of OA. Based on a systematic literature search using online databases, we figured out the following main points: (1) the integrative systematic review of c-mRNAs and its target genes related to OA pathogenesis; (2) the potential use of c-miRNAs for OA diagnosis purposes as potential biomarkers; and (3) for therapeutic purposes, and we also highlight certain remedies that regulate microRNA expression based on its target genes.