A cluster of blood-based protein biomarkers associated with decreased cerebral blood flow relates to future cardiovascular events in patients with cardiovascular disease

Biological processes underlying decreased cerebral blood flow (CBF) in patients with cardiovascular disease (CVD) are largely unknown. We hypothesized that identification of protein clusters associated with lower CBF in patients with CVD may explain underlying processes. In 428 participants (74% cardiovascular diseases; 26% reference participants) from the Heart-Brain Connection Study, we assessed the relationship between 92 plasma proteins from the Olink® cardiovascular III panel and normal-appearing grey matter CBF, using affinity propagation and hierarchical clustering algorithms, and generated a Biomarker Compound Score (BCS). The BCS was related to cardiovascular risk and observed cardiovascular events within 2-year follow-up using Spearman correlation and logistic regression. Thirteen proteins were associated with CBF (ρSpearman range: -0.10 to -0.19, pFDR-corrected <0.05), and formed one cluster. The cluster primarily reflected extracellular matrix organization processes. The BCS was higher in patients with CVD compared to reference participants (pFDR-corrected <0.05) and was associated with cardiovascular risk (ρSpearman 0.42, p < 0.001) and cardiovascular events (OR 2.05, p < 0.01). In conclusion, we identified a cluster of plasma proteins related to CBF, reflecting extracellular matrix organization processes, that is also related to future cardiovascular events in patients with CVD, representing potential targets to preserve CBF and mitigate cardiovascular risk in patients with CVD.

A Wolf in Sheep’s Clothing: Reuse of Routinely Obtained Laboratory Data in Research

Electronic health records (EHRs) contain valuable data for reuse in science, quality evaluations, and clinical decision support. Because routinely obtained laboratory data are abundantly present, often numeric, generated by certified laboratories, and stored in a structured way, one may assume that they are immediately fit for (re)use in research. However, behind each test result lies an extensive context of choices and considerations, made by both humans and machines, that introduces hidden patterns in the data. If they are unaware, researchers reusing routine laboratory data may eventually draw incorrect conclusions. In this paper, after discussing health care system characteristics on both the macro and micro level, we introduce the reader to hidden aspects of generating structured routine laboratory data in 4 steps (ordering, preanalysis, analysis, and postanalysis) and explain how each of these steps may interfere with the reuse of routine laboratory data. As researchers reusing these data, we underline the importance of domain knowledge of the health care professional, laboratory specialist, data manager, and patient to turn routine laboratory data into meaningful data sets to help obtain relevant insights that create value for clinical care.

Untargeted metabolic profiling in dried blood spots identifies disease fingerprint for pyruvate kinase deficiency

The diagnostic evaluation and clinical characterization of rare hereditary anemia (RHA) is to date still challenging. In particular, there is little knowledge on the broad metabolic impact of many of the molecular defects underlying RHA. In this study we explored the potential of untargeted metabolomics to diagnose a relatively common type of RHA: Pyruvate Kinase Deficiency (PKD). In total, 1903 unique metabolite features were identified in dried blood spot samples from 16 PKD patients and 32 healthy controls. A metabolic fingerprint was identified using a machine learning algorithm, and subsequently a binary classification model was designed. The model showed high performance characteristics (AUC 0.990, 95%CI 0.981-0.999) and an accurate class assignment was achieved for all newly added control (13) and patient samples (6), with the exception of one patient (accuracy 94%). Important metabolites in the metabolic fingerprint included glycolytic intermediates, polyamines and several acyl carnitines. In general, the application of untargeted metabolomics in dried blood spots is a novel functional tool that holds promise for diagnostic stratification and studies on disease pathophysiology in RHA.

AG-348 (Mitapivat), an allosteric activator of red blood cell pyruvate kinase, increases enzymatic activity, protein stability, and ATP levels over a broad range of PKLR genotypes

Pyruvate kinase (PK) deficiency is a rare hereditary disorder affecting red blood cell (RBC) glycolysis, causing changes in metabolism including a deficiency in adenosine triphosphate (ATP). This affects red cell homeostasis, promoting premature removal of RBC from the circulation. In this study, we characterized and evaluated the effect of AG-348, an allosteric activator of PK that is currently in clinical trials for treatment of PK deficiency, on RBC and erythroid precursors from PK-deficient patients. In 15 patients, ex vivo treatment with AG-348 resulted in increased enzymatic activity in all patients' cells after 24 hours (h) (mean increase: 1.8-fold; range: 1.2-3.4). ATP levels increased (mean increase: 1.5-fold; range: 1.0-2.2) similar to control cells (mean increase: 1.6-fold; range: 1.4-1.8). Generally, PK thermostability was strongly reduced in PK-deficient RBC. Ex vivo treatment with AG-348 increased residual activity from 1.4- to >10-fold more than residual activity of vehicle-treated samples. Protein analyses suggest that a sufficient level of PK protein is required for cells to respond to AG- 348 treatment ex vivo, as treatment effects were minimal in patient cells with very low or undetectable levels of PK-R. In half of the patients, ex vivo treatment with AG-348 was associated with an increase in RBC deformability. These data support the hypothesis that drug intervention with AG- 348 effectively up-regulates PK enzymatic activity and increases stability in PK-deficient RBC over a broad range of PKLR genotypes. The concomitant increase in ATP levels suggests that glycolytic pathway activity may be restored. AG-348 treatment may represent an attractive way to correct the underlying pathologies of PK deficiency. (AG-348 is currently in clinical trials for the treatment of PK deficiency. Registered at clinicaltrials.gov identifiers: NCT02476916, NCT03853798, NCT03548220, NCT03559699).

Low-Density Lipoprotein Cholesterol Target Attainment in Patients With Established Cardiovascular Disease: Analysis of Routine Care Data

BACKGROUND

Direct feedback on quality of care is one of the key features of a learning health care system (LHS), enabling health care professionals to improve upon the routine clinical care of their patients during practice.

OBJECTIVE

This study aimed to evaluate the potential of routine care data extracted from electronic health records (EHRs) in order to obtain reliable information on low-density lipoprotein cholesterol (LDL-c) management in cardiovascular disease (CVD) patients referred to a tertiary care center.

METHODS

We extracted all LDL-c measurements from the EHRs of patients with a history of CVD referred to the University Medical Center Utrecht. We assessed LDL-c target attainment at the time of referral and per year. In patients with multiple measurements, we analyzed LDL-c trajectories, truncated at 6 follow-up measurements. Lastly, we performed a logistic regression analysis to investigate factors associated with improvement of LDL-c at the next measurement.

RESULTS

Between February 2003 and December 2017, 250,749 LDL-c measurements were taken from 95,795 patients, of whom 23,932 had a history of CVD. At the time of referral, 51% of patients had not reached their LDL-c target. A large proportion of patients (55%) had no follow-up LDL-c measurements. Most of the patients with repeated measurements showed no change in LDL-c levels over time: the transition probability to remain in the same category was up to 0.84. Sequence clustering analysis showed more women (odds ratio 1.18, 95% CI 1.07-1.10) in the cluster with both most measurements off target and the most LDL-c measurements furthest from the target. Timing of drug prescription was difficult to determine from our data, limiting the interpretation of results regarding medication management.

CONCLUSIONS

Routine care data can be used to provide feedback on quality of care, such as LDL-c target attainment. These routine care data show high off-target prevalence and little change in LDL-c over time. Registrations of diagnosis; follow-up trajectory, including primary and secondary care; and medication use need to be improved in order to enhance usability of the EHR system for adequate feedback.

Reducing Test Utilization in Hospital Settings: A Narrative Review

Background

Studies addressing the appropriateness of laboratory testing have revealed approximately 20% overutilization. We conducted a narrative review to (1) describe current interventions aimed at reducing unnecessary laboratory testing, specifically in hospital settings, and (2) provide estimates of their efficacy in reducing test order volume and improving patient-related clinical outcomes.

Methods

The PubMed, Embase, Scopus, Web of Science, and Canadian Agency for Drugs and Technologies in Health-Health Technology Assessment databases were searched for studies describing the effects of interventions aimed at reducing unnecessary laboratory tests. Data on test order volume and clinical outcomes were extracted by one reviewer, while uncertainties were discussed with two other reviewers. Because of the heterogeneity of interventions and outcomes, no meta-analysis was performed.

Results

Eighty-four studies were included. Interventions were categorized into educational, (computerized) provider order entry [(C)POE], audit and feedback, or other interventions. Nearly all studies reported a reduction in test order volume. Only 15 assessed sustainability up to two years. Patient-related clinical outcomes were reported in 45 studies, two of which found negative effects.

Conclusions

Interventions from all categories have the potential to reduce unnecessary laboratory testing, although long-term sustainability is questionable. Owing to the heterogeneity of the interventions studied, it is difficult to conclude which approach was most successful, and for which tests. Most studies had methodological limitations, such as the absence of a control arm. Therefore, well-designed, controlled trials using clearly described interventions and relevant clinical outcomes are needed.

Novel Homozygous Mutation of the Internal Translation Initiation Start Site of VHL is Exclusively Associated with Erythrocytosis: Indications for Distinct Functional Roles of von Hippel-Lindau Tumor Suppressor Isoforms

Congenital secondary erythrocytosis is a rare disorder characterized by increased red blood cell production. An important cause involves defects in the oxygen sensing pathway, in particular the PHD2-VHL-HIF axis. Mutations in VHL are also associated with the von Hippel-Lindau tumor predisposition syndrome. The differences in phenotypic expression of VHL mutations are poorly understood. We report on three patients with erythrocytosis, from two unrelated families. All patients show exceptionally high erythropoietin (EPO) levels, and are homozygous for a novel missense mutation in VHL: c.162G>C p.(Met54Ile). The c.162G>C mutation is the most upstream homozygous VHL mutation described so far in patients with erythrocytosis. It abolishes the internal translational start codon, which directs expression of VHLp19, resulting in the production of only VHLp30. The exceptionally high EPO levels and the absence of VHL-associated tumors in the patients suggest that VHLp19 has a role for regulating EPO levels that VHLp30 does not have, whereas VHLp30 is really the tumor suppressor isoform.

Seasonal changes in gene expression represent cell-type composition in whole blood

Seasonal patterns in behavior and biological parameters are widespread. Here, we examined seasonal changes in whole blood gene expression profiles of 233 healthy subjects. Using weighted gene co-expression network analysis, we identified three co-expression modules showing circannual patterns. Enrichment analysis suggested that this signal stems primarily from red blood cells and blood platelets. Indeed, a large clinical database with 51 142 observations of blood cell counts over 3 years confirmed a corresponding seasonal pattern of counts of red blood cells, reticulocytes and platelets. We found no direct evidence that these changes are linked to genes known to be key players in regulating immune function or circadian rhythm. It is likely, however, that these seasonal changes in cell counts and gene expression profiles in whole blood represent biological and clinical relevant phenomena. Moreover, our findings highlight possible confounding factors relevant to the study of gene expression profiles in subjects collected at geographical locations with disparaging seasonality patterns.

Information comparison of the effects of drugs on laboratory tests in drug labels and Young's book

BACKGROUND

The effects of drugs on laboratory tests may lead to misinterpretation of laboratory data, unnecessary tests, higher costs and missed diagnoses. This study compared the information on drug-laboratory effects (DLE) described in 200 drug labels with that in Young's book.

METHODS

Information on DLE was searched in the drug labels of 200 frequently prescribed drugs using the keywords 'interfer*', 'influence', and 'laborator*'. This information was compared with the information in Young's book. Each item of information scored 1 point if it was specific and exactly the same. Primary outcome was the percentage of DLE with completely the same information.

RESULTS

In 23 (11.5%) of the 200 drug labels 83 DLE were described. Most DLE were described in drug labels of contraceptives (71%) and antibacterials (15%). The most frequently affected laboratory tests were adrenal gland (17%), urine tests (15%), liver tests (10%) and renal function tests (10%). Comparison of six DLE with Young's book was not possible because the information was not described in the book. Twelve (14.5%) DLE of the information in the drug label was identical to that in Young's book. Detailed information about nature of the effect, strength of the effect and body fluid was not described in the drug labels.

CONCLUSIONS

In a limited number of DLE in the drug labels the information was the same as in Young's book. Overall, the information on DLE provided in drug labels is unclear, inconsistent and incomplete and does not support healthcare professionals in making evidence-based monitoring decisions.

Instructions on laboratory monitoring in 200 drug labels

BACKGROUND

Monitoring drug treatment is important to assess the therapeutic effects and to prevent adverse drug reactions. Unfortunately, the clinical evidence for monitoring is often missing. To attain evidence-based laboratory monitoring and to improve patient safety it is mandatory for the clinical chemist to develop effective and rational methods for monitoring. The legal source for this evidence-based information is the drug label. We analysed frequency, nature, and applicability of instructions on laboratory monitoring described in 200 drug labels.

METHODS

The applicability of instructions was assessed with an adapted Systematic Information for Monitoring score. Seven items of information were evaluated: why to monitor, what to monitor (essential), when to start or stop monitoring, how frequently to monitor, critical value (essential) and how to respond (essential). Each item scored one point when information was described specifically, otherwise the score was zero. Instructions were applicable if all three essential items scored.

RESULTS

In 131 drug labels, 566 instructions on laboratory monitoring were identified, an average of 2.8 per drug label. Kidney, liver, electrolyte, and drug monitoring were important biomarker categories (71%). The median applicability score was 2.1 (0-6) and 95 (17%) instructions were applicable. Six determinants were associated with applicable instructions: kidney (OR 7.0; 95% CI 4.4-11.3), creatine phosphokinase (4.5; 1.5-13.6), drug selection (6.8; 4.0-11.7), dose adjustments (2.4; 1.5-3.7), year on the market 2000-2007 (2.6; 1.1-6.1) and statins (4.8; 2.5-9.0).

CONCLUSIONS

Drug labels frequently describe instructions on laboratory monitoring, but these are ambiguous and incomplete and clinical applicability for the professional is limited.