Previous fracture and subsequent fracture risk: a meta-analysis to update FRAX.

A large international meta-analysis using primary data from 64 cohorts has quantified the increased risk of fracture associated with a previous history of fracture for future use in FRAX. INTRODUCTION: The aim of this study was to quantify the fracture risk associated with a prior fracture on an international basis and to explore the relationship of this risk with age, sex, time since baseline and bone mineral density (BMD). METHODS: We studied 665,971 men and 1,438,535 women from 64 cohorts in 32 countries followed for a total of 19.5 million person-years. The effect of a prior history of fracture on the risk of any clinical fracture, any osteoporotic fracture, major osteoporotic fracture, and hip fracture alone was examined using an extended Poisson model in each cohort. Covariates examined were age, sex, BMD, and duration of follow-up. The results of the different studies were merged by using the weighted ß-coefficients. RESULTS: A previous fracture history, compared with individuals without a prior fracture, was associated with a significantly increased risk of any clinical fracture (hazard ratio, HR = 1.88; 95% CI = 1.72-2.07). The risk ratio was similar for the outcome of osteoporotic fracture (HR = 1.87; 95% CI = 1.69-2.07), major osteoporotic fracture (HR = 1.83; 95% CI = 1.63-2.06), or for hip fracture (HR = 1.82; 95% CI = 1.62-2.06). There was no significant difference in risk ratio between men and women. Subsequent fracture risk was marginally downward adjusted when account was taken of BMD. Low BMD explained a minority of the risk for any clinical fracture (14%), osteoporotic fracture (17%), and for hip fracture (33%). The risk ratio for all fracture outcomes related to prior fracture decreased significantly with adjustment for age and time since baseline examination. CONCLUSION: A previous history of fracture confers an increased risk of fracture of substantial importance beyond that explained by BMD. The effect is similar in men and women. Its quantitation on an international basis permits the more accurate use of this risk factor in case finding strategies.

A Genetic Validation of the Neurodegeneration Biomarkers Tau-A and Tau-C - A Mendelian Randomization Study.

BACKGROUND: Disease modifying treatments for dementia are only just surfacing, and their development is still significantly hindered by the lack of validated tools for identification of subjects with subclinical disease. Much interest has been taken in developing accessible non-invasive serum biomarkers of neurodegeneration. Recent studies have identified caspase-3-cleaved tau (Tau-C), and ADAM-10 cleaved tau (Tau-A) as possible markers of preclinical neurodegenerative disease. OBJECTIVES: To explore if serum levels of Tau-A and Tau-C change as a consequence of neurodegeneration. DESIGN AND SETTING: Cohort study with measurement of biomarkers and genome sequencing at baseline with follow-up after an average of 14 years. PARTICIPANTS: Postmenopausal Danish women from the Prospective Epidemiological Risk Factor (PERF) cohort (n=4968) Methods: Genotyping data was used to perform a Mendelian randomization analysis of serum levels of Tau-A and Tau-C in relation to a diagnosis of dementia at follow-up. A dementia diagnosis was defined as a composite of an all-cause dementia diagnosis derived from the Danish National Health registries, a self-reported diagnosis of dementia and/or cognitive test scores suggestive of dementia. Serum levels of Tau-A and Tau-C were measured blinded in samples from baseline in a CAP certified lab. The association with dementia was assessed using bi-directional one- and two- sample Mendelian randomization. RESULTS: A lead single nucleotide polymorphism (SNP) was identified for Tau-A (rs10414043) and Tau-C (rs429358), respectively were identified. Both were located in the APOE/C1 cluster on chromosome 19. APOE and EPOC1 variants were associated with lower levels of Tau-A and Tau-C levels - effect size -0.13, 95%CI [-0.17 - -0.09] log2 (ng/mL), p=7.05e-11 for rs10414043 association with Tau-A and effect size -0.12, 95%CI [-0.15 - -0.08] log2 (ng/mL), p=2e-11 for rs429358 association with Tau-C. When incorporating genetic data from a larger genetic study we found that Alzheimer's disease was marginally associated with a decreased Tau-A and Tau-C levels (Odds Ratio 0.97, 95%CI [0.93 - 1.00]. No association was found in the forward Mendelian randomization analysis. CONCLUSIONS: By combining genotype data with serum measurements of the novel biomarkers Tau-A and Tau-C, we conclude that Tau-A and Tau-C levels change because of neurodegeneration. We also conclude that lower serum-values of the biomarkers are associated with the presence of genetic variants commonly found in individuals suffering from late-onset Alzheimer's Dementia. These findings add to the growing data pointing towards Tau-A and Tau-C as valuable biomarkers for neurodegeneration.

Update of the fracture risk prediction tool FRAX: a systematic review of potential cohorts and analysis plan.

We describe the collection of cohorts together with the analysis plan for an update of the fracture risk prediction tool FRAX with respect to current and novel risk factors. The resource comprises 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. INTRODUCTION: The availability of the fracture risk assessment tool FRAX® has substantially enhanced the targeting of treatment to those at high risk of fracture with FRAX now incorporated into more than 100 clinical osteoporosis guidelines worldwide. The aim of this study is to determine whether the current algorithms can be further optimised with respect to current and novel risk factors. METHODS: A computerised literature search was performed in PubMed from inception until May 17, 2019, to identify eligible cohorts for updating the FRAX coefficients. Additionally, we searched the abstracts of conference proceedings of the American Society for Bone and Mineral Research, European Calcified Tissue Society and World Congress of Osteoporosis. Prospective cohort studies with data on baseline clinical risk factors and incident fractures were eligible. RESULTS: Of the 836 records retrieved, 53 were selected for full-text assessment after screening on title and abstract. Twelve cohorts were deemed eligible and of these, 4 novel cohorts were identified. These cohorts, together with 60 previously identified cohorts, will provide the resource for constructing an updated version of FRAX comprising 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. For each known and candidate risk factor, multivariate hazard functions for hip fracture, major osteoporotic fracture and death will be tested using extended Poisson regression. Sex- and/or ethnicity-specific differences in the weights of the risk factors will be investigated. After meta-analyses of the cohort-specific beta coefficients for each risk factor, models comprising 10-year probability of hip and major osteoporotic fracture, with or without femoral neck bone mineral density, will be computed. CONCLUSIONS: These assembled cohorts and described models will provide the framework for an updated FRAX tool enabling enhanced assessment of fracture risk (PROSPERO (CRD42021227266)).

Considerations for understanding protein measurements: Identification of formation, degradation and more pathological relevant epitopes.

OBJECTIVES: There is a need for precision medicine and an unspoken promise of an optimal approach for identification of the right patients for value-based medicine based on big data. However, there may be a misconception that measurement of proteins is more valuable than measurement of fewer selected biomarkers. In population-based research, variation may be somewhat eliminated by quantity. However, this fascination of numbers may limit the attention to and understanding of the single. This review highlights that protein measurements (with collagens as examples) may mean different things depending on the targeted epitope - formation or degradation of tissues, and even signaling potential of proteins. DESIGN AND METHODS: PubMed was searched for collagen, neo-epitope, biomarkers. RESULTS: Ample examples of assays with specific epitopes, either pathological such as HbA1c, or domain specific such as pro-peptides, which total protein arrays would not have identified were evident. CONCLUSIONS: We suggest that big data may be considered as the funnel of data points, in which most important parameters will be selected. If the technical precision is low or the biological accuracy is limited, and we include suboptimal quality of biomarkers, disguised as big data, we may not be able to fulfill the promise of helping patients searching for the optimal treatment. Alternatively, if the technical precision of the total protein quantification is high, but we miss the functional domains with the most considerable biological meaning, we miss the most important and valuable information of a given protein. This review highlights that measurements of the same protein in different ways may provide completely different meanings. We need to understand the pathological importance of each epitope quantified to maximize protein measurements.

Identification of heterogenous treatment response trajectories to anti-IL6 receptor treatment in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic inflammatory disease with fluctuating course of progression. Despite substantial improvement in treatments in recent years, treatment response is still not guaranteed. The aim of this study was to identify variation in Disease Activity Score 28 (DAS28) of RA patients in response to Tocilizumab, and to investigate both molecular and clinical factors influencing response. Clinical and biochemical data for 485 RA patients receiving Tocilizumab in combination with methotrexate were extracted from the LITHE phase III clinical study (NCT00106535), and post-hoc analysis conducted. Latent class mixed models were used to identify statistically distinct trajectories of DAS28 after the initiation of treatment. Biomarker measurements were then analysed cross-sectionally and temporally, to characterise patients by serological biomarkers and clinical factors. We identified three distinct trajectories of drug response: class 1 (n = 85, 17.5%), class 2 (n = 338, 69.7%) and class 3 (n = 62, 12.8%). All groups started with high DAS28 on average (DAS28 > 5.1). Class 1 showed the least reduction in DAS28, with significantly more patients seeking escape therapy (p < 0.001). Class 3 showed significantly higher rates of improvement in DAS28, with 58.1% achieving ACR response levels compared to 2.4% in class 1 (p < 0.0001). Biomarkers of inflammation, MMP-3, CRP, C1M, showed greater reduction in class 3 compared to the other classes. Identification of more homogenous patient sub-populations of drug response may allow for more targeted therapeutic treatment regimens and a better understanding of disease aetiology.

Identification of pathological RA endotypes using blood-based biomarkers reflecting tissue metabolism. A retrospective and explorative analysis of two phase III RA studies.

There is an increasing demand for accurate endotyping of patients according to their pathogenesis to allow more targeted treatment. We explore a combination of blood-based joint tissue metabolites (neoepitopes) to enable patient clustering through distinct disease profiles. We analysed data from two RA studies (LITHE (N = 574, follow-up 24 and 52 weeks), OSKIRA-1 (N = 131, follow-up 24 weeks)). Two osteoarthritis (OA) studies (SMC01 (N = 447), SMC02 (N = 81)) were included as non-RA comparators. Specific tissue-derived neoepitopes measured at baseline, included: C2M (cartilage degradation); CTX-I and PINP (bone turnover); C1M and C3M (interstitial matrix degradation); CRPM (CRP metabolite) and VICM (macrophage activity). Clustering was performed to identify putative endotypes. We identified five clusters (A-E). Clusters A and B were characterized by generally higher levels of biomarkers than other clusters, except VICM which was significantly higher in cluster B than in cluster A (p<0.001). Biomarker levels in Cluster C were all close to the median, whilst Cluster D was characterised by low levels of all biomarkers. Cluster E also had low levels of most biomarkers, but with significantly higher levels of CTX-I compared to cluster D. There was a significant difference in ΔSHP score observed at 52 weeks (p<0.05). We describe putative RA endotypes based on biomarkers reflecting joint tissue metabolism. These endotypes differ in their underlining pathogenesis, and may in the future have utility for patient treatment selection.

A serological marker of the N-terminal neoepitope generated during LOXL2 maturation is elevated in patients with cancer or idiopathic pulmonary fibrosis.

OBJECTIVES: Lysyl oxidase like 2 (LOXL2) is associated with poor prognosis in idiopathic pulmonary disease (IPF) and cancer. We developed an Enzyme-linked immunosorbent assay (ELISA) targeting the LOXL2 neo-epitope generated through the release of the signal peptide during LOXL2 maturation. DESIGN AND METHODS: An ELISA targeting the N-terminal site of the human LOXL2 was developed including technical optimization and validation steps. Serum LOXL2 was measured in patients with breast, colorectal, lung, ovarian, pancreatic and prostate cancer, melanoma, IPF and in healthy controls (n = 16). RESULTS: A technically robust and specific assay was developed. LOXL2 was detectable in serum from healthy controls and showed reactivity towards recombinant LOXL2. Compared to controls, LOXL2 levels were significantly (p < 0.001-0.05) elevated in serum from patients with breast, colerectal, lung, ovarian and pancreatic cancer (mean range: 49-84 ng/mL), but not in prostate cancer (mean: 36 ng/mL) and malignant melanoma patients (41 ng/mL). Serum LOXL2 was elevated in IPF patients compared to healthy controls (mean: 76.5 vs 46.8 ng/mL; p > 0.001). CONCLUSIONS: A specific ELISA towards the N-terminal neo-epitope site in LOXL2 was developed which detected significantly elevated serum levels from patients with above-mentioned cancer types or IPF compared to healthy controls.

Cathepsin-S degraded decorin are elevated in fibrotic lung disorders - development and biological validation of a new serum biomarker.

BACKGROUND: Decorin is one of the most abundant proteoglycans of the extracellular matrix and is mainly secreted and deposited in the interstitial matrix by fibroblasts where it plays an important role in collagen turnover and tissue homeostasis. Degradation of decorin might disturb normal tissue homeostasis contributing to extracellular matrix remodeling diseases. Here, we present the development and validation of a competitive enzyme-linked immunosorbent assay (ELISA) quantifying a specific fragment of degraded decorin, which has potential as a novel non-invasive serum biomarker for fibrotic lung disorders. METHODS: A fragment of decorin cleaved in vitro using human articular cartilage was identified by mass-spectrometry (MS/MS). Monoclonal antibodies were raised against the neo-epitope of the cleaved decorin fragment and a competitive ELISA assay (DCN-CS) was developed. The assay was evaluated by determining the inter- and intra-assay precision, dilution recovery, accuracy, analyte stability and interference. Serum levels were assessed in lung cancer patients, patients with idiopathic pulmonary fibrosis (IPF), patients with chronic obstructive pulmonary disease (COPD) and healthy controls. RESULTS: The DCN-CS ELISA was technically robust and was specific for decorin cleaved by cathepsin-S. DCN-CS was elevated in lung cancer patients (p < 0.0001) and IPF patients (p < 0.001) when compared to healthy controls. The diagnostic power for differentiating lung cancer patients and IPF patients from healthy controls was 0.96 and 0.77, respectively. CONCLUSION: Cathepsin-S degraded decorin could be quantified in serum using the DCN-CS competitive ELISA. The clinical data indicated that degradation of decorin by cathepsin-S is an important part of the pathology of lung cancer and IPF.

Quantification of fibronectin as a method to assess ex vivo extracellular matrix remodeling.

Altered architecture, composition and quality of the extracellular matrix (ECM) are pathological hallmarks of several inflammatory and fibro-proliferative pathological processes such as osteoarthritis (OA), rheumatoid arthritis (RA), fibrosis and cancer. One of the most important components of the ECM is fibronectin. Fibronectin serves as an adhesion molecule anchoring cells to the underlying basement membrane through direct interaction with integrin receptors. Fibronectin hereby modulates the properties of the ECM and affects cellular processes. Quantification of fibronectin remodeling could therefore be used to assess the changes in the ECM that occur during progression of fibro-proliferative pathologies. Ex vivo models are becoming state-of-the-art tools to study ECM remodeling as the cellular composition and the organization of the ECM are preserved. Ex vivo models may therefore be a valuable tool to study the ECM remodeling that occurs during progression of fibro-proliferative pathologies. The aim of this study was to quantify fibronectin remodeling in ex vivo models of cartilage and cancer. A competitive The enzyme-linked immunosorbent assay (ELISA) against the C-terminus of fibronectin was developed (FBN-C). The assay was evaluated in relation to specificity, technical performance and as a marker for quantification of fibronectin in cartilage and cancer ex vivo models. The ELISA was specific and technically stable. Cleavage of tumor tissue with MMP-2 released significantly higher levels of FBN-C compared to tissue with buffer only and western blot analysis revealed that FBN-C recognizes both full length and degraded fibronectin. When ex vivo cartilage cultures were stimulated with the anabolic factor TGFß and catabolic factors TNF-α and OSM, significantly higher levels of FBN-C were found in the conditioned media. Lastly, FBN-C was released from a cancer ex vivo model. In conclusion, we were able to quantify fibronectin remodeling in ex vivo models of cartilage and cancer. Quantification of fibronectin remodeling could be a valuable tool to understand ECM remodeling in ex vivo models of fibro-proliferative pathologies.

Collagen degradation products measured in serum can separate ovarian and breast cancer patients from healthy controls: A preliminary study.

BACKGROUND: During cancer the otherwise tightly controlled homeostasis of the extracellular matrix (ECM) is disturbed. The protein composition changes, the ECM stiffens and increased levels of proteases are secreted. The combination of these processes result in release of specific protein fragments (e.g. collagens) to the circulation, which when measured may reflect disease pathogenesis. OBJECTIVE: To investigate if biomarkers of protease-degraded collagen could differentiate ovarian and breast cancer patients from healthy controls when measured in serum. METHODS: The levels of markers reflecting MMP-degradation of type I (C1M), type III (C3M) and type IV (C4M, C4M12) collagen were assessed in serum from ovarian cancer patients (n= 10), breast cancer patients (n= 14) and healthy controls (n= 49) using validated ELISAs. The markers were compared using one way ANOVA and AUC was calculated. RESULTS: All markers were significantly elevated in serum from ovarian cancer patients (p< 0.0001) and breast cancer patients (p< 0.04-0.0001) compared to healthy controls. Furthermore, diagnostically the markers were able to differentiate ovarian (AUROC 90%-93%) and breast cancer patients (AUROC 76%-93%) from healthy controls, with C1M being the strongest differentiator of disease vs. CONCLUSION: Four serum biomarkers reflecting altered MMP-mediated collagen turnover were able to differentiate ovarian and breast cancer patients from healthy controls.