The fibroblast hormone Endotrophin is a biomarker of mortality in chronic diseases.

Fibrosis, driven by fibroblast activities, is an important contributor to morbidity and mortality in most chronic diseases. Endotrophin, a signaling molecule derived from processing of type VI collagen by highly activated fibroblasts, is involved in fibrotic tissue remodeling. Circulating levels of endotrophin have been associated with an increased risk of mortality in multiple chronic diseases. We conducted a systematic literature review collecting evidence from original papers published between 2012 and January 2023 that reported associations between circulating endotrophin (PROC6) and mortality. Cohorts with data available to the study authors were included in an Individual Patient Data (IPD) meta-analysis that evaluated the association of PROC6 with mortality (PROSPERO registration number: CRD42023340215) after adjustment for age, sex and BMI, where available. In the IPD meta-analysis including sixteen cohorts of patients with different non-communicable chronic diseases (NCCDs) (N = 15,205) the estimated summary hazard ratio for 3-years all-cause mortality was 2.10 (95 % CI 1.75-2.52) for a 2-fold increase in PROC6, with some heterogeneity observed between the studies (I2=70 %). This meta-analysis is the first study documenting that fibroblast activities, as quantified by circulating endotrophin, are independently associated with mortality across a broad range of NCCDs. This indicates that, irrespective of disease, interstitial tissue remodeling, and consequently fibroblast activities, has a central role in adverse clinical outcomes, and should be considered with urgency from drug developers as a target to treat.

The sclerotic component of metabolic syndrome: Fibroblast activities may be the central common denominator driving organ function loss and death.

Fibrosis is a common feature of more than 50 different diseases and the cause of more than 35% of deaths worldwide, of which liver, kidney, skin, heart and, recently, lungs are receiving the most attention. Tissue changes, resulting in loss of organ function, are both a cause and consequence of disease and outcome. Fibrosis is caused by an excess deposition of extracellular matrix proteins, which over time results in impaired organ function and organ failure, and the pathways leading to increased fibroblast activation are many. This narrative review investigated the common denominator of fibrosis, fibroblasts, and the activation of fibroblasts, in response to excess energy consumption in liver, kidney, heart, skin and lung fibrosis. Fibroblasts are the main drivers of organ function loss in lung, liver, skin, heart and kidney disease. Fibroblast activation in response to excess energy consumption results in the overproduction of a range of collagens, of which types I, III and VI seem to be the essential drivers of disease progression. Fibroblast activation may be quantified in serum, enabling profiling and selection of patients. Activation of fibroblasts results in the overproduction of collagens, which deteriorates organ function. Patient profiling of fibroblast activities in serum, quantified as collagen production, may identify an organ death trajectory, better enabling identification of the right treatment for use in different metabolic interventions. As metabolically activated patients have highly elevated risk of kidney, liver and heart failure, it is essential to identify which organ to treat first and monitor organ status to correct treatment regimes. In direct alignment with this, it is essential to identify the right patients with the right organ deterioration trajectory for enrolment in clinical studies.

Biomarker-guided drug development provides value for patients, payers and drug developers: lessons learned from 25 years in the biomarker industry.

INTRODUCTION: There is an urgent, persistent, need for better biomarkers in clinical drug development. More informative biomarkers can increase the likelihood of drug advancement or approval, and implementing biomarkers increases the success rate in drug development. Biomarkers may guide decisions and allow resources to be directed to the projects most likely to succeed. However, biomarkers that are validated to high standards are needed, reflecting biological and pathological processes accurately. Such biomarkers are needed to develop treatments faster, and to improve and guide clinical trial design by selecting and de-selecting patients. METHODS: In this review based on the authors' previous published experience and interaction with pharmaceutical- and biomarker stakeholders, we highlight the use and value of biomarkers in clinical development according to the BEST guidelines. We highlight the value of 3 types of biomarkers that may provide optimal value to stakeholders: diagnostic, prognostic and pharmacodynamic biomarkers. RESULTS: A more appropriate clinical trial design, increasing the ratio between benefits and side effects, may come from a more tailored biomarker-approach identifying suitable molecular endotypes of patients to treat. DISCUSSION: Biomarkers may guide drug developers in selecting the optimal projects to progress, when designing clinical studies and development paths. Biomarkers may aid in the diagnosis and prognostic assessment of patients and assist in matching the molecular endotype to the selected treatment, which improves the success rate of clinical development progression. The aim of this paper is to provide a comprehensive ideation framework for how to utilize biomarkers in clinical development, with a focus on utility for patients, payers and drug developers.

Research alignment in the U.S. national park system: Impact of transformative science policy on the supply and demand for scientific knowledge for protected area management.

The US National Park System encompasses diverse environmental and tourism management regimes, together governed by the 1916 Organic Act and its dual mandate of conservation and provision of public enjoyment. However, with the introduction of transformative science policy in the 2000's, the mission scope has since expanded to promote overarching science-based objectives. Yet despite this paradigm shift instituting "science for parks, parks for science", there is scant research exploring the impact of the National Park Science Policy on the provision of knowledge. We address this gap by developing a spatiotemporal framework for evaluating research alignment, here operationalized via quantifiable measures of supply and demand for scientific knowledge. Specifically, we apply a machine learning algorithm (Latent Dirichlet analysis) to a comprehensive park-specific text corpus (combining official needs statements -i.e. demand- and scientific research metadata -i.e. supply-) to define a joint topic space, which thereby facilitates quantifying the direction and degree of alignment at multiple levels. Results indicate an overall robust degree of research alignment, with misaligned topics tending to be over-researched (as opposed to over-demanded), which may be favorable to many parks, but is inefficient from the park system perspective. Results further indicate that the transformative science policy exacerbated the misalignment in mandated research domains. In light of these results, we argue for improved decision support mechanisms to achieve more timely alignment of research efforts towards distinctive park needs, thereby fostering convergent knowledge co-production and leveraging the full value of National Parks as living laboratories.

Effects of empagliflozin on collagen biomarkers in patients with heart failure: Findings from the EMPEROR trials.

AIMS: Extracellular matrix remodelling is one of the key pathways involved in heart failure (HF) progression. Sodium-glucose cotransporter 2 inhibitors (SGLT2i) may have a role in attenuating myocardial fibrosis. The impact of SGLT2i on blood markers of collagen turnover in humans is not fully elucidated. This study aimed to investigate the effect of empagliflozin on serum markers of collagen turnover in patients enrolled in the EMPEROR-Preserved and EMPEROR-Reduced trials. METHODS AND RESULTS: Overall, 1084 patients (545 in empagliflozin and 539 in placebo) were included in the analysis. Procollagen type I carboxy-terminal propeptide (PICP), a fragment of N-terminal type III collagen (PRO-C3), procollagen type I amino-terminal peptide (PINP), a fragment of C-terminal type VIa3 collagen (PRO-C6), a fragment of type I collagen (C1M), and a fragment of type III collagen (C3M) were measured in serum at baseline, 12 and 52 weeks. A mixed model repeated measurements model was used to evaluate the effect of empagliflozin versus placebo on the analysed biomarkers. Higher baseline PICP, PRO-C6 and PINP levels were associated with older age, a more severe HF presentation, higher levels of natriuretic peptides and high-sensitivity troponin T, and the presence of comorbid conditions such as chronic kidney disease and atrial fibrillation. Higher PICP levels were associated with the occurrence of the study primary endpoint (a composite of HF hospitalization or cardiovascular death), and PRO-C6 and PINP were associated with the occurrence of sustained worsening of kidney function. On the other hand, PRO-C3, C1M, and C3M were not associated with worse HF severity or study outcomes. Compared to placebo, empagliflozin reduced PICP at week 12 by 5% and at week 52 by 8% (week 12: geometric mean ratio = 0.95, 95% confidence interval [CI] 0.91-0.99, p = 0.012; week 52: geometric mean ratio = 0.92, 95% CI 0.88-0.97, p = 0.003). Additionally, empagliflozin reduced PRO-C3 at week 52 by 7% (week 12: geometric mean ratio = 0.98, 95% CI 0.95-1.02, p = 0.42; week 52: geometric mean ratio = 0.93, 95% CI 0.89-0.98, p = 0.003), without impact on other collagen markers. CONCLUSION: Our observations are consistent with experimental observations that empagliflozin down-regulates profibrotic signalling. The importance of such an effect for the clinical benefits of SGLT2i in HF remains to be elucidated.

Endotrophin, a Key Marker and Driver for Fibroinflammatory Disease.

Our overview covers several key areas related to recent results obtained for collagen type VI and endotrophin (ETP): i) An introduction to the history of ETP, including how it was identified, how it is released and its function and potential receptors. ii) An introduction to the collagen family, with a focus on what differentiates collagen type VI from an evolutionary standpoint. iii) An overview of collagen type VI, the six individual chains (COL6A1, A2, A3, A4, A5 and A6), their differences and similarities, as well as their expression profiles and function. iv) A detailed analysis of COL6A3, including the cleaved product endotrophin, and what separates it from the other five collagen 6 molecules, including its suggested function based on insights gained from knockout and gain of function mouse models. v) An introduction to the history of ETP, including how it was identified, how it is released and its function and potential receptors. vi) The pathology of ETP. What leads to its presence and release and what are the consequences thereof? vii) Functional implications of circulating ETP. Here we review the data with the functional roles of ETP in mind. viii) We propose that ETP is a mediator for fibrotic (or fibro-inflammatory? ) disorders. Based on what we know about ETP, we have to consider it as a target for the treatment of fibrotic (or fibro-inflammatory) disorders. What segment(s) of the patient population would most dramatically respond to an ETP-targeted intervention? How can we find the population that would profit most from an intervention? We aim to present a broad overview over the ETP field at large, providing an assessment of where the future research efforts need to be placed to tap into the vast potential of ETP, both as a marker and as a target in different diseases.

Endotrophin, a fibroblast matrikine, may be a driver of fibroblast activation in fibro-inflammatory diseases.

Extracellular matrix proteins harbor signaling domains that once released from the parent molecule can trigger cellular responses. One of these molecules is endotrophin, a type VI collagen derived fragment, whose circulatory levels have been associated to an increased risk of adverse outcome in heart failure with preserved ejection fraction (HFpEF). Here we show that the stimulation of human cardiac fibroblasts by endotrophin upregulates the synthesis of type I collagen, the main interstitial collagen that accumulates in the myocardium during fibrogenesis. These data provide a possible mechanistic explanation for the relation between circulating endotrophin levels and risk of outcome in HFpEF.

Biomarkers of collagen turnover and wound healing in chronic thromboembolic pulmonary hypertension patients before and after pulmonary endarterectomy.

BACKGROUND: In chronic thromboembolic pulmonary hypertension (CTEPH), fibrotic remodeling of tissue and thrombi contributes to disease progression. Removal of the thromboembolic mass by pulmonary endarterectomy (PEA) improves hemodynamics and right ventricular function, but the roles of different collagens before as well as after PEA are not well understood. METHODS: In this study, hemodynamics and 15 different biomarkers of collagen turnover and wound healing were evaluated in 40 CTEPH patients at diagnosis (baseline) and 6 and 18 months after PEA. Baseline biomarker levels were compared with a historical cohort of 40 healthy subjects. RESULTS: Biomarkers of collagen turnover and wound healing were increased in CTEPH patients compared with healthy controls, including a 35-fold increase in the PRO-C4 marker of type IV collagen formation and a 55-fold increase in the C3M marker of type III collagen degradation. PEA reduced pulmonary pressures to almost normal levels 6 months after the procedure, with no further improvement at 18 months. There were no changes in any of the measured biomarkers after PEA. CONCLUSIONS: Biomarkers of collagen formation and degradation are increased in CTEPH suggesting a high collagen turnover. While PEA effectively reduces pulmonary pressures, collagen turnover is not significantly modified by surgical PEA.

Adipose-derived stromal cells increase the formation of collagens through paracrine and juxtacrine mechanisms in a fibroblast co-culture model utilizing macromolecular crowding.

BACKGROUND: Adipose-derived stromal cells (ASCs) possess a multitude of regenerative capabilities, which include immunomodulation, angiogenesis, and stimulation of extracellular matrix (ECM) remodeling. However, the underlying mechanisms leading to ECM remodeling remain largely elusive and highlight the need for functional in vitro models for mode of action studies. Therefore, the purpose of this study was to develop an in vitro co-culture model to investigate the capabilities of ASCs to modulate fibroblasts and ECM. METHODS: An ECM in vitro model with ASCs and normal human dermal fibroblasts (NHDFs) was established utilizing macromolecular crowding, ascorbic acid, and TGF-ß stimulation. Paracrine and juxtacrine co-cultures were created using transwell inserts and cell cultures with direct cell-cell contacts. The cultures were screened using RT2 PCR Profiler Arrays; the protein levels of myofibroblast differentiation marker alpha smooth muscle actin (αSMA) and ECM remodeling enzymes were analyzed using western blot on cell lysates; the formation of collagen type I, III, VI, and fibronectin was investigated using ELISA on culture supernatants; and the deposition of collagens was analyzed using immunocytochemistry. RESULTS: TGF-ß stimulation of NHDF monocultures increased the expression of 18 transcripts relevant for ECM formation and remodeling, the protein levels of αSMA and matrix metalloproteinase-2 (MMP-2), the formation of collagen type I, III, VI, and fibronectin, and the deposition of collagen type I and VI and decreased the protein levels of MMP-14. Inclusion of ASCs in the ECM co-culture model increased the formation of collagen type I and III through paracrine mechanisms and the formation of collagen type VI through juxtacrine mechanisms. CONCLUSIONS: The co-culture model provides effective stimulation of NHDF monocultures by TGF-ß for enhanced formation and deposition of ECM. In the model, ASCs induce changes in ECM by increasing formation of collagen type I, III and VI. The obtained results could guide further investigations of ASCs' capabilities and underlying mechanisms related to ECM formation and remodeling.

Endotrophin, a Collagen VI Formation-Derived Peptide, in Heart Failure.

BACKGROUND: Endotrophin, a collagen type VI-derived peptide, mediates metabolic dysregulation, inflammation, and fibrosis in animal models, but has not been studied in human heart failure (HF). METHODS: We examined the association between circulating endotrophin and outcomes in participants suffering from HF with preserved ejection fraction (HFpEF) enrolled in the TOPCAT trial (n=205). Associations were validated in a participant-level meta-analysis (n=810) that included participants with HFpEF from the PHFS study (United States; n=174), PEOPLE cohort (New Zealand; n=168), a randomized trial of vasodilator therapy (United States; n=45), a cohort from Donostia University Hospital and University of Navarra (Spain; n=171), and the TRAINING-HF trial (Spain; n=47). We also assessed associations in HF with reduced ejection fraction in PHFS (n=1,642). RESULTS: Plasma endotrophin levels at baseline were associated with risk of future death (standardized hazard ratio [HR] = 1.74; 95% confidence interval [CI]=1.36-2.24; P<0.001) and death or HF-related hospital admission (DHFA; standardized HR=2.11; 95% CI= 1.67-2.67; P<0.001) in TOPCAT. Endotrophin improved reclassification and discrimination for these outcomes beyond the MAGGIC risk score and NT-proBNP (N-terminal pro b-type natriuretic peptide). Findings were confirmed in the participant-level meta-analysis. In participants with HF with reduced ejection fraction in PHFS, endotrophin levels were associated with death (standardized HR=1.82; 95% CI=1.66-2.00; P<0.001) and DHFA (standardized HR=1.40; 95% CI=1.31-1.50; P<0.001), but the strength of the latter association was substantially lower than for the MAGGIC risk score (standardized HR=1.93; 95% CI=1.76-2.12) and BNP (standardized HR=1.78; 95% CI=1.66-1.92). CONCLUSIONS: Circulating endotrophin levels are independently associated with future poor outcomes in patients with HF, particularly in HFpEF. (Funded by Bristol Myers Squibb; Instituto de Salud Carlos III [Spain] and European Regional Development Fund; European Commission CRUCIAL project; and the U.S. National Institutes of Health National Heart, Lung, and Blood Institute.).

Circular functional analysis of OCT data for precise identification of structural phenotypes in the eye.

Progressive optic neuropathies such as glaucoma are major causes of blindness globally. Multiple sources of subjectivity and analytical challenges are often encountered by clinicians in the process of early diagnosis and clinical management of these diseases. In glaucoma, the structural damage is often characterized by neuroretinal rim (NRR) thinning of the optic nerve head, and other clinical parameters. Baseline structural heterogeneity in the eyes can play a key role in the progression of optic neuropathies, and present challenges to clinical decision-making. We generated a dataset of Optical Coherence Tomography (OCT) based high-resolution circular measurements on NRR phenotypes, along with other clinical covariates, of 3973 healthy eyes as part of an established clinical cohort of Asian Indian participants. We introduced CIFU, a new computational pipeline for CIrcular FUnctional data modeling and analysis. We demonstrated CIFU by unsupervised circular functional clustering of the OCT NRR data, followed by meta-clustering to characterize the clusters using clinical covariates, and presented a circular visualization of the results. Upon stratification by age, we identified a healthy NRR phenotype cluster in the age group 40-49 years with predictive potential for glaucoma. Our dataset also addresses the disparity of representation of this particular population in normative OCT databases.

Evaluation of a novel biomarker of type XXVIII collagen formation, PRO-C28, in samples from cancer and heart failure with preserved ejection fraction patients.

Increased turnover of extracellular matrix proteins is seen in many different diseases and is an underlying and driving feature of pathogenesis. An increased ratio of formation over degradation of extracellular matrix proteins, such as collagens, leads to accumulation of proteins in the tissues, ultimately impairing organ function. Understanding how this balance is regulated is key to providing deeper insight into high extracellular matrix turnover diseases. Type XXVIII collagen is a novel collagen with limited information available in relation to expression, tissue prevalence and clinical implication. We generated a novel, technically robust ELISA to measure a C-terminal fragment of type XXVIII collagen in plasma and serum (PRO-C28). PRO-C28 was found to be significantly elevated in circulation in patients with heart failure with preserved ejection fraction (HFpEF) and in patients with lung cancer. Additionally, PRO-C28 correlated significantly to NT-proBNP levels in HFpEF patients. PRO-C28 levels were elevated in diseases characterized by high ECM-turnover. This suggests that type XXVIII collagen may play a role in fibroproliferative disorders in the heart and the lungs.

Glucodensities: A new representation of glucose profiles using distributional data analysis.

Biosensor data have the potential to improve disease control and detection. However, the analysis of these data under free-living conditions is not feasible with current statistical techniques. To address this challenge, we introduce a new functional representation of biosensor data, termed the glucodensity, together with a data analysis framework based on distances between them. The new data analysis procedure is illustrated through an application in diabetes with continuous-time glucose monitoring (CGM) data. In this domain, we show marked improvement with respect to state-of-the-art analysis methods. In particular, our findings demonstrate that (i) the glucodensity possesses an extraordinary clinical sensitivity to capture the typical biomarkers used in the standard clinical practice in diabetes; (ii) previous biomarkers cannot accurately predict glucodensity, so that the latter is a richer source of information and; (iii) the glucodensity is a natural generalization of the time in range metric, this being the gold standard in the handling of CGM data. Furthermore, the new method overcomes many of the drawbacks of time in range metrics and provides more in-depth insight into assessing glucose metabolism.

Matrix metalloproteinase-12 cleaved fragment of titin as a predictor of functional capacity in patients with heart failure and preserved ejection fraction.

OBJECTIVES: Serum levels of matrix metalloproteinase-12 cleaved fragment of titin (TIM), a novel circulatory biomarker specific for cardiac titin degradation, has emerged as a potential biomarker in cardiovascular diseases. In this work, we aimed to evaluate the association between TIM and maximal functional capacity assessed by the percentage of predicted peak exercise oxygen uptake (pp-peakVO2) in patients with heart failure and preserved ejection fraction (HFpEF). Design. In this post-hoc study, we included 46 stable symptomatic (New York Heart Association II-III) HFpEF patients enrolled in the TRAINING-HF study (NCT02638961). pp-peak-VO2 was calculated from baseline values. Baseline circulating levels of TIM were measured by competitive ELISA in serum from the TRAINING-HF patients. The independent association between TIM and pp-peakVO2 was evaluated by multivariate linear regression analysis. Results. The mean age of the sample was 73.8 ± 8.7 years, 56.5% were females, and 76.1% were on NYHA II. The medians of pp-peakVO2 and TIM were 60.9% (50.4-69.3), and 130.1 ng/mL (98.1-159.5), respectively. The median of NT-proBNP was 912 pg/mL (302-1826). pp-peakVO2 was significant and inversely correlated with TIM (r= -41, p = .005). In multivariate analysis, after adjusting for NYHA class, hypertension, body mass index, and glomerular filtration rate, higher TIM was significantly associated with lower pp-peak VO2 (p = .029). Conclusions. In this sample of stable and symptomatic HFpEF patients, higher serum levels of TIM identified patients with worse functional status.

Blood Pressure Variability: A New Predicting Factor for Clinical Outcomes of Intracerebral Hemorrhage.

Spontaneous primary intracerebral hemorrhage (ICH) is a stroke subtype associated with the highest mortality rate. High blood pressure (BP) is the most common cause of non-lobar ICH. Recent clinical trials have been inconclusive regarding the efficacy of aggressive BP lowering to improve ICH outcome. The association between high BP and ICH prognosis is rather complex and parameters other than absolute BP levels may be involved. In this regard, there is accruing evidence that BP variability (BPV) plays a major role in ICH outcome. Different BPV indices have been used to predict hematoma growth, neurological deterioration, and functional recovery. This review highlights the available evidence about the relationship between BPV and clinical outcomes among patients. We identified standard deviation (SD), residual SD, coefficient of variation, mean absolute change, average real variability, successive variation, spectral analysis using Fourier analysis, and functional successive variation (FSV) as indices to assess BPV. Most studies have demonstrated the association of BPV with ICH outcome, suggesting a need to monitor and control BP fluctuations in the routine clinical care of ICH patients. When large inter-subject variability exists, FSV is a viable alternative quantification of BPV as its computation is less sensitive to differences in the patient-specific observation schedules for BP than that of traditional indices.

The Magnitude of Blood Pressure Reduction Predicts Poor In-Hospital Outcome in Acute Intracerebral Hemorrhage.

BACKGROUND: Early systolic blood pressure (SBP) reduction is believed to improve outcome after spontaneous intracerebral hemorrhage (ICH), but there has been a limited assessment of SBP trajectories in individual patients. We aimed to determine the prognostic significance of SBP trajectories in ICH. METHODS: We collected routine data on spontaneous ICH patients from two healthcare systems over 10 years. Unsupervised functional principal components analysis (FPCA) was used to characterize SBP trajectories over first 24 h and their relationship to the primary outcome of unfavorable shift on modified Rankin scale (mRS) at hospital discharge, categorized as an ordinal trichotomous variable (mRS 0-2, 3-4, and 5-6 defined as good, poor, and severe, respectively). Ordinal logistic regression models adjusted for baseline SBP and ICH volume were used to determine the prognostic significance of SBP trajectories. RESULTS: The 757 patients included in the study were 65 ± 23 years old, 56% were men, with a median (IQR) Glasgow come scale of 14 (8). FPCA revealed that mean SBP over 24 h and SBP reduction within the first 6 h accounted for 76.8% of the variation in SBP trajectories. An increase in SBP reduction (per 10 mmHg) was significantly associated with unfavorable outcomes defined as mRS > 2 (adjusted-OR = 1.134; 95% CI 1.044-1.233, P = 0.003). Compared with SBP reduction < 20 mmHg, worse outcomes were observed for SBP reduction = 40-60 mmHg (adjusted-OR = 1.940, 95% CI 1.129-3.353, P = 0.017) and > 60 mmHg, (adjusted-OR = 1.965, 95% CI 1.011, 3.846, P = 0.047). Furthermore, the association of SBP reduction and outcome varied according to initial hematoma volume. Smaller SBP reduction was associated with good outcome (mRS 0-2) in small (< 7.42 mL) and medium-size (≥ 7.42 and < 30.47 mL) hematomas. Furthermore, while the likelihood of good outcome was low in those with large hematomas (≥ 30.47 mL), smaller SBP reduction was associated with decreasing probability of severe outcome (mRS 5-6). CONCLUSION: Our analyses suggest that in the first 6 h SBP reduction is significantly associated with the in-hospital outcome that varies with initial hematoma volume, and early SBP reduction > 40 mmHg may be harmful in ICH patients. For early SBP reduction to have an effective therapeutic effect, both target levels and optimum SBP reduction goals vis-à-vis hematoma volume should be considered.

Fibrogenesis and inflammation contribute to the pathogenesis of cirrhotic cardiomyopathy.

BACKGROUND: Fibrogenesis and inflammation contribute to the progression of cirrhosis. However, it is unknown if these processes also contribute to the development of cirrhotic cardiomyopathy (CCM). Novel magnetic resonance imaging with quantification of the extracellular volume (ECV) provides an estimate of the fibrotic remodelling in the liver and heart. AIM: To investigate the relationship between liver and cardiac ECV in cirrhosis and their association with collagen turnover and inflammation. METHODS: A prospective study of 52 patients with cirrhosis and 14 healthy controls. All patients underwent contrast-enhanced MRI with T1-mapping and quantification of myocardial and liver ECV, biochemical assessments of collagen turnover (PRO-C3, PRO-C5, PRO-C6, collagen type IV degradation fragment, collagen type V degradation fragment, LG1M) and inflammation (TNFα, IL-1ß, IL-6, IL-8, IL-18, SDF1α, sCD163, sMR, soluble macrophage mannose receptor). RESULTS: Myocardial and liver ECV were increased in patients compared with healthy controls (myocardial ECV 31.2 ± 5.5% vs 27.4 ± 2.9%, P = 0.037; liver ECV 44.1 ± 9.6% vs 33.7 ± 6.7%, P < 0.001). Myocardial ECV correlated strongly with liver ECV (r = 0.48, P = 0.001) and biomarkers of collagen formation and inflammation (P < 0.005). Similarly, liver ECV correlated with biomarkers of collagen formation and inflammation (P < 0.003). In a multivariate analysis, liver ECV was predicted by biomarkers of collagen formation (PRO-C3 and PRO-C6), whereas myocardial ECV was predicted by biomarkers of collagen formation (PRO-C6) and inflammation (IL-6 and sMR). CONCLUSION: Structural myocardial changes seem closely related to liver fibrosis in patients with cirrhosis. The strong associations with biomarkers of collagen formation and inflammation provide new insight into the role of inflammation and fibrogenesis in the development of structural cardiac abnormalities, potentially leading to CCM.

Atrial fibrillation and cardiac fibrosis: A review on the potential of extracellular matrix proteins as biomarkers.

The involvement of fibrosis as an underlying pathology in heart diseases is becoming increasingly clear. In recent years, fibrosis has been granted a causative role in heart diseases and is now emerging as a major contributor to Atrial Fibrillation (AF) pathogenesis. AF is the most common arrhythmia encountered in the clinic, but the substrate for AF is still being debated. Consensus in the field is a combination of cardiac tissue remodeling, inflammation and genetic predisposition. The extracellular matrix (ECM) is subject of growing investigation, since measuring circulatory biomarkers of ECM formation and degradation provides both diagnostic and prognostic information. However, fibrosis is not just fibrosis. Each specific collagen biomarker holds information on regulatory mechanisms, as well as information about which section of the ECM is being remodeled, providing a detailed description of cardiac tissue homeostasis. This review entails an overview of the implication of fibrosis in AF, the different collagens and their significance, and the potential of using biomarkers of ECM remodeling as tools for understanding AF pathogenesis and identifying patients at risk for further disease progression.

Exploration of Multiparameter Hematoma 3D Image Analysis for Predicting Outcome After Intracerebral Hemorrhage.

BACKGROUND: Rapid diagnosis and proper management of intracerebral hemorrhage (ICH) play a crucial role in the outcome. Prediction of the outcome with a high degree of accuracy based on admission data including imaging information can potentially influence clinical decision-making practice. METHODS: We conducted a retrospective multicenter study of consecutive ICH patients admitted between 2012-2017. Medical history, admission data, and initial head computed tomography (CT) scan were collected. CT scans were semiautomatically segmented for hematoma volume, hematoma density histograms, and sphericity index (SI). Discharge unfavorable outcomes were defined as death or severe disability (modified Rankin Scores 4-6). We compared (1) hematoma volume alone; (2) multiparameter imaging data including hematoma volume, location, density heterogeneity, SI, and midline shift; and (3) multiparameter imaging data with clinical information available on admission for ICH outcome prediction. Multivariate analysis and predictive modeling were used to determine the significance of hematoma characteristics on the outcome. RESULTS: We included 430 subjects in this analysis. Models using automated hematoma segmentation showed incremental predictive accuracies for in-hospital mortality using hematoma volume only: area under the curve (AUC): 0.85 [0.76-0.93], multiparameter imaging data (hematoma volume, location, CT density, SI, and midline shift): AUC: 0.91 [0.86-0.97], and multiparameter imaging data plus clinical information on admission (Glasgow Coma Scale (GCS) score and age): AUC: 0.94 [0.89-0.99]. Similarly, severe disability predictive accuracy varied from AUC: 0.84 [0.76-0.93] for volume-only model to AUC: 0.88 [0.80-0.95] for imaging data models and AUC: 0.92 [0.86-0.98] for imaging plus clinical predictors. CONCLUSIONS: Multiparameter models combining imaging and admission clinical data show high accuracy for predicting discharge unfavorable outcome after ICH.