Analysis of C-reactive protein from finger stick dried blood spot to predict high risk of cardiovascular disease

C-reactive protein (CRP) is an acute-phase protein involved in inflammation. Furthermore, CRP is an important biomarker used in diagnostics to predict risk of cardiovascular disease (CVD) in addition to monitoring bacterial and viral infections. To measure plasma CRP, venipuncture is still necessitated and has to be performed by trained phlebotomists. As a solution, dried blood spots (DBS) are used for minimally invasive at-home sampling of blood and can be send to diagnostic laboratories by regular mail. In this study, we included 53 patients that presented to the outpatient clinic of the University Medical Center Utrecht. Capillary finger stick was used to spot blood on a filter paper card and allowed to dry. After extraction of DBS, CRP was analyzed on an automated high-throughput chemistry analyzer. Additional validation steps regarding stability, effect of hematocrit, precision, and limits of blank and quantitation were conducted according to corresponding Clinical and Laboratory Standards Institute standards. An excellent regression analysis of R2 (95% confidence interval) = 0.986 (0.982–0.989) was found. This enabled correct classification for high CVD risk of all 25 cases with sensitivity (95% CI) of 1.00 (1.00–1.00) and specificity (95% CI) of 0.96 (0.89–1.03) and correct diagnosis of inflammation of 12/13 cases with sensitivity (95% CI) of 0.92 (0.77–1.07) and specificity (95% CI) of 1.00 (1.00–1.00). Furthermore, CRP was found to be stable for 31 days and observed hematocrit variation amongst patients was clinically acceptable. CRP from DBS can be accurately measured on an automated high-throughput chemistry analyzer and used to diagnose inflammation and classify high CVD risk. This method enables individuals to engage in at-home sampling of blood on DBS for (tele)diagnostics, screening programs, patient follow-up, and medication management

Requirements for Proper Immunosuppressive Regimens to Limit Translational Failure of Cardiac Cell Therapy in Preclinical Large Animal Models

Various cell-based therapies are currently investigated in an attempt to tackle the high morbidity and mortality associated with heart failure. The need for these therapies to move towards the clinic is pressing. Therefore, preclinical large animal studies that use non-autologous cells are needed to evaluate their potential. However, non-autologous cells are highly immunogenic and trigger immune rejection responses resulting in potential loss of efficacy. To overcome this issue, adequate immunosuppressive regimens are of imminent importance but clear guidelines are currently lacking. In this review, we assess the immunological barriers regarding non-autologous cell transplantation and immune modulation with immunosuppressive drugs. In addition, we provide recommendations with respect to immunosuppressive regimens in preclinical cardiac cell-replacement studies

Association of low testosterone with changes in non-cardiovascular biomarkers in adult men

Testosterone has effects on many organs and systems. The purpose of this study was to test the hypothesis that low testosterone is associated with changes in various non-cardiovascular biomarkers in men older than 40 who were tested for possible hypogonadism. We extracted data from 9939 outpatient men who were over 40 years old (median age 56) and who also had concurrent laboratory measurements of total testosterone and one or more biomarkers of interest: estradiol, uric acid, prostate-specific antigen (PSA), sex-hormone binding globulin (SHBG), luteinizing hormone, creatinine, bone alkaline phosphatase (BAP), creatine kinase, hemoglobin A1c, and 25-hydroxy-vitamin D, and body mass index (BMI). In a smaller exploratory study of 19 otherwise healthy men presenting for evaluation of possible hypogonadism, pre-albumin (a.k.a.transthyretin, a marker of anabolism) and testosterone were measured. Men with lower levels of testosterone had significantly (p < 0.001) lower mean levels of PSA, SHBG, luteinizing hormone, and estradiol. Overall, men with low levels of testosterone also had significantly (p < 0.001) higher mean levels of LDH and BAP, but these associations varied between men who were younger or older than 56 years. There was a moderate but statistically significant positive correlation (r = 0.63, p < 0.05) between testosterone levels and pre-albumin. These results confirm our hypothesis that testosterone deficiency is associated with a broad range of systemic changes demonstrable in hormonal and non-hormonal serum assays in men over 40 years old being tested for possible hypogonadism

Prognostic Value of Circulating Fibrosis Biomarkers in Dilated Cardiomyopathy (DCM): Insights into Clinical Outcomes

Background: Dilated cardiomyopathy (DCM) involves myocardial remodeling, characterized by significant fibrosis and extracellular matrix expansion. These changes impair heart function, increasing the risk of heart failure and sudden cardiac death. This study investigates the prognostic value of circulating fibrosis biomarkers as a less invasive method in DCM patients. Methods: Plasma samples from 185 patients with confirmed DCM were analyzed to measure 13 circulating biomarkers using Luminex bead-based multiplex assays and ELISA. The prognostic value of these biomarkers was evaluated concerning heart failure-associated events and all-cause mortality. Results: Elevated MMP-2 levels (>1519.3 ng/mL) were linked to older age, higher diabetes prevalence, lower HDL, increased NT-proBNP and hs-TnT levels, and severe systolic dysfunction. High TIMP-1 levels (>124.9 ng/mL) correlated with elevated NT-proBNP, more atrial fibrillation, reduced exercise capacity, and larger right ventricles. Increased GDF-15 levels (>1213.9 ng/mL) were associated with older age, systemic inflammation, renal impairment, and poor exercise performance. Elevated OPN levels (>81.7 ng/mL) were linked to higher serum creatinine and NT-proBNP levels. Over a median follow-up of 32.4 months, higher levels of these biomarkers predicted worse outcomes, including increased risks of heart failure-related events and mortality. Conclusions: Circulating fibrosis biomarkers, particularly MMP-2, TIMP-1, GDF-15, and OPN, are valuable prognostic tools in DCM. They reflect the severity of myocardial remodeling and systemic disease burden, aiding in risk stratification and therapeutic intervention. Integrating these biomarkers into clinical practice could improve DCM management and patient prognosis

Longitudinal profile of circulating endothelial cells in post-acute coronary syndrome patients

Introduction Patients who have experienced an acute coronary syndrome (ACS) are at risk of a recurrent event, but their level of risk varies. Because of their close temporal relationship with vascular injury, longitudinal measurements of circulating endothelial cells (CECs) carry potential to improve individual risk assessment. Methods We conducted an explorative nested case-control study within our multicenter, prospective, observational biomarker study (BIOMArCS) of 844 ACS patients. Following an index ACS, high-frequency blood sampling was performed during 1-year follow-up. CECs were identified using flow cytometric analyses in 15 cases with recurrent event, and 30 matched controls. Results Cases and controls had a median (25th-75thpercentile) age of 64.1 (58.1-75.1) years and 80% were men. During the months preceding the endpoint, the mean (95%CI) CEC concentration in cases was persistently higher than in controls (12.8 [8.2-20.0] versus 10.0 [7.0-14.4] cells/ml), although this difference was non-significant (P = 0.339). In controls, the mean cell concentration was significantly (P = 0.030) lower in post 30-day samples compared to samples collected within one day after index ACS: 10.1 (7.5-13.6) versus 17.0 (10.8-26.6) cells/ml. Similar results were observed for CEC subsets co-expressing CD133 and CD309 (VEGFR-2) or CD106 (VCAM-1). Conclusion Despite their close relation to vascular damage, no increase in cell concentrations were found prior to the occurrence of a secondary adverse cardiac event

Central Multifocal Choroiditis: Platelet Granularity as a Potential Marker for Treatment With Steroid-Sparing Immunomodulatory Therapy

Purpose: We aimed to evaluate the blood cell composition in patients with central multifocal choroiditis (cMFC), a rare form of posterior uveitis predominantly affecting young myopic women. Methods: In this retrospective observational case-control study, a 104-parameter automated hematocytometry was conducted by the Cell-Dyn Sapphire hematology analyzer for 122 cases and 364 age- and sex-matched controls. Cox proportional regression analysis was used to assess the relation between the blood cell composition and the time between disease onset (first visit) and the start of systemic corticosteroid-sparing immunomodulatory therapy (IMT). Results: At a false discovery rate of 5% (Padj), we identified a decrease of blood monocytes in cases with cMFC, which could be attributed to disease activity. Cox proportional hazard analysis including age and sex revealed that increased platelet granularity (measured by mean intermediate angle scatter) was an independent risk factor for treatment with IMT (hazard ratio = 2.3 [95% confidence interval = 1.28 - 4.14], Padj = 0.049). The time between the first presentation and the start of IMT was 0.3 years in the group with an increased platelet granularity and 3.4 years in the group without increased platelet granularity. Conclusions: Patients with cMFC demonstrated a decrease in blood monocytes. Moreover, platelet granularity could potentially be used as a marker for treatment with IMT

Microarray testing in patients with systemic lupus erythematosus identifies a high prevalence of CpG DNA-binding antibodies

OBJECTIVE: Many autoantibodies are known to be associated with SLE, although their role in clinical practice is limited because of low sensitivity and weak associations with clinical manifestations. There has been great interest in the discovery of new autoantibodies to use in clinical practice. In this study, we investigated 57 new and known antibodies and their potential for diagnostics or risk stratification. METHODS: Between 2014 and 2017, residual sera of all anti-dsDNA tests in the UMC Utrecht were stored in a biobank. This included sera of patients with SLE, patients with a diagnosis of another immune-mediated inflammatory disease (IMID), patients with low (non-IMID) or medium levels of clinical suspicion of SLE but no IMID diagnosis (Rest), and self-reported healthy blood bank donors. Diagnosis and (presence of) symptoms at each blood draw were retrospectively assessed in the patient records with the Utrecht Patient-Oriented Database using a newly developed text mining algorithm. Sera of patients were analysed for the presence of 57 autoantibodies with a custom-made immunofluorescent microarray. Signal intensity cut-offs for all antigens on the microarray were set to the 95th percentile of the non-IMID control group. Differences in prevalence of autoantibodies between patients with SLE and control groups were assessed. RESULTS: Autoantibody profiles of 483 patients with SLE were compared with autoantibody profiles of 1397 patients from 4 different control groups. Anti-dsDNA was the most distinguishing feature between patients with SLE and other patients, followed by antibodies against Cytosine-phosphate-Guanine (anti-CpG) DNA motifs (p<0.0001). Antibodies against CMV (cytomegalovirus) and ASCA (anti-Saccharomyces cerevisiae antibodies) were more prevalent in patients with SLE with (a history of) lupus nephritis than patients with SLE without nephritis. CONCLUSION: Antibodies against CpG DNA motifs are prevalent in patients with SLE. Anti-CMV antibodies are associated with lupus nephritis

Treatment variation in stent choice in patients with stable or unstable coronary artery disease

Aim: Variations in treatment are the result of differences in demographic and clinical factors (e.g. anatomy), but physician and hospital factors may also contribute to treatment variation. The choice of treatment is considered important since it could lead to differences in long-term outcomes. This study explores the associations with stent choice: i.e. drug-eluting stent (DES) versus bare-metal stents (BMS) for Dutch patients diagnosed with stable or unstable coronary artery disease (CAD). Methods & results: Associations with treatment decisions were based on a prospective cohort of 692 patients with stable or unstable CAD. Of those patients, 442 patients were treated with BMS or DES. Multiple logistic regression analyses were performed to identify variables associated with stent choice. Bivariate analyses showed that NYHA class, number of diseased vessels, previous percutaneous coronary intervention, smoking, diabetes, and the treating hospital were associated with stent type. After correcting for other associations the treating hospital remained significantly associated with stent type in the stable CAD population. Conclusions: This study showed that several factors were associated with stent choice. While patients generally appear to receive the most optimal stent given their clinical characteristics, stent choice seems partially determined by the treating hospital, which may lead to differences in longterm outcome

Text Mining of Electronic Health Records Can Accurately Identify and Characterize Patients With Systemic Lupus Erythematosus

Objective: Electronic health records (EHR) are increasingly being recognized as a major source of data reusable for medical research and quality monitoring, although patient identification and assessment of symptoms (characterization) remain challenging, especially in complex diseases such as systemic lupus erythematosus (SLE). Current coding systems are unable to assess information recorded in the physician’s free-text notes. This study shows that text mining can be used as a reliable alternative. Methods: In a multidisciplinary research team of data scientists and medical experts, a text mining algorithm on 4607 patient records was developed to assess the diagnosis of 14 different immune-mediated inflammatory diseases and the presence of 18 different symptoms in the EHR. The text mining algorithm included key words in the EHR, while mining the context for exclusion phrases. The accuracy of the text mining algorithm was assessed by manually checking the EHR of 100 random patients suspected of having SLE for diagnoses and symptoms and comparing the outcome with the outcome of the text mining algorithm. Results: After evaluation of 100 patient records, the text mining algorithm had a sensitivity of 96.4% and a specificity of 93.3% in assessing the presence of SLE. The algorithm detected potentially life-threatening symptoms (nephritis, pleuritis) with good sensitivity (80%-82%) and high specificity (97%-97%). Conclusion: We present a text mining algorithm that can accurately identify and characterize patients with SLE using routinely collected data from the EHR. Our study shows that using text mining, data from the EHR can be reused in research and quality control