Biological variation estimates of Alzheimer's disease plasma biomarkers in healthy individuals.

INTRODUCTION: Blood biomarkers have proven useful in Alzheimer's disease (AD) research. However, little is known about their biological variation (BV), which improves the interpretation of individual-level data. METHODS: We measured plasma amyloid beta (Aß42, Aß40), phosphorylated tau (p-tau181, p-tau217, p-tau231), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) in plasma samples collected weekly over 10 weeks from 20 participants aged 40 to 60 years from the European Biological Variation Study. We estimated within- (CVI ) and between-subject (CVG ) BV, analytical variation, and reference change values (RCV). RESULTS: Biomarkers presented considerable variability in CVI and CVG . Aß42/Aß40 had the lowest CVI (≈ 3%) and p-tau181 the highest (≈ 16%), while others ranged from 6% to 10%. Most RCVs ranged from 20% to 30% (decrease) and 25% to 40% (increase). DISCUSSION: BV estimates for AD plasma biomarkers can potentially refine their clinical and research interpretation. RCVs might be useful for detecting significant changes between serial measurements when monitoring early disease progression or interventions. Highlights Plasma amyloid beta (Aß42/Aß40) presents the lowest between- and within-subject biological variation, but also changes the least in Alzheimer's disease (AD) patients versus controls. Plasma phosphorylated tau variants significantly vary in their within-subject biological variation, but their substantial fold-changes in AD likely limits the impact of their variability. Plasma neurofilament light chain and glial fibrillary acidic protein demonstrate high between-subject variation, the impact of which will depend on clinical context. Reference change values can potentially be useful in monitoring early disease progression and the safety/efficacy of interventions on an individual level. Serial sampling revealed that unexpectedly high values in heathy individuals can be observed, which urges caution when interpreting AD plasma biomarkers based on a single test result.

Albumin determined by bromocresol green leads to erroneous results in routine evaluation of patients with chronic kidney disease.

OBJECTIVES: Measurement of plasma albumin is pivotal for clinical decision-making in patients with chronic kidney disease (CKD). Routinely used methods as bromocresol green (BCG) and bromocresol purple (BCP) can suffer from aselectivity, but the impact of aselectivity on the accuracy of plasma albumin results of CKD-patients is still unknown. Therefore, we evaluated the performance of BCG-, BCP- and JCTLM-endorsed immunological methods in patients with various stages of CKD. METHODS: We evaluated the performance of commonly used albumin methods in patients with CKD stages G1 through G5, the latter divided in two groups based on whether they received hemodialysis treatment. In total, 163 patient plasma samples were measured at 14 laboratories, on six different BCG and BCP-platforms, and four different immunological platforms. The results were compared with an ERM-DA-470k-corrected nephelometric assay. The implications on outcome is evaluated by the proportion of patient results <38 g/L for the diagnosis of protein energy wasting. RESULTS: Albumin results determined with BCP- and immunological methods showed the best agreement with the target value (92.7 and 86.2 %, respectively vs. 66.7 % for BCG, namely due to overestimation). The relative agreement of each method with the target value was platform-dependent, with larger variability in agreement between platforms noted for BCG and immunological methods (3.2-4.6 and 2.6-5.3 %) as opposed to BCP (0.7-1.5 %). The stage of CKD had similar effects on the variability in agreement for the three method-groups (0.6-1.8 % vs. 0.7-1.5 % vs. 0.4-1.6 %). The differences between methods cause discrepancies in clinical decision-making, as structurally fewer patients were diagnosed with protein energy wasting upon using BCG-based albumin results. CONCLUSIONS: Our study shows that BCP is fit for the intended use to measure plasma albumin levels in CKD patients from all stages, including patients on hemodialysis. In contrast, most BCG-based platforms falsely overestimate the plasma albumin concentration.

Transformation of Sequential Hospital and Outpatient Laboratory Data into Between-Day Reference Change Values.

BACKGROUND: Serial differences between intrapatient consecutive measurements can be transformed into Taylor series of variation vs time with the intersection at time = 0 (y0) equal to the total variation (analytical + biological + preanalytical). With small preanalytical variation, y0, expressed as a percentage of the mean, is equal to the variable component of the reference change value (RCV) calculation: (CVA2 + CVI2)1/2. METHODS: We determined the between-day RCV of patient data for 17 analytes and compared them to healthy participants' RCVs. We analyzed 653 consecutive days of Dartmouth-Hitchcock Roche Modular general chemistry data (4.2 million results: 60% inpatient, 40% outpatient). The serial patient values of 17 analytes were transformed into 95% 2-sided RCV (RCVAlternate), and 3 sets of RCVhealthy were calculated from 3 Roche Modular analyzers' quality control summaries and CVI derived from biological variation (BV) studies using healthy participants. RESULTS: The RCVAlternate values are similar to RCVhealthy derived from known components of variation. For sodium, chloride, bicarbonate calcium, magnesium, phosphate, alanine aminotransferase, albumin, and total protein, the RCVs are equivalent. As expected, increased variation was found for glucose, aspartate aminotransferase, creatinine, and potassium. Direct bilirubin and urea demonstrated lower variation. CONCLUSIONS: Our RCVAlternate values integrate known and unknown components of analytic, biologic, and preanalytic variation, and depict the variations observed by clinical teams that make medical decisions based on the test values. The RCVAlternate values are similar to the RCVhealthy values derived from known components of variation and suggest further studies to better understand the results being generated on actual patients tested in typical laboratory environments.

Filling in the GAPS: validation of anion gap (AGAP) measurement uncertainty estimates for use in clinical decision making.

OBJECTIVES: We compare measurement uncertainty (MU) calculations to real patient result variation observed by physicians using as our model anion gap (AGAP) sequentially measured on two different instrument types. An approach for discretely quantifying the pre-analytical contributions and validating AGAP MU estimates for interpretation of patient results is proposed. METHODS: AGAP was calculated from sodium, chloride, and bicarbonate reported from chemistry or blood gas analyzers which employ different methodologies and specimen types. AGAP MU was calculated using a top-down approach both assuming no correlation between measurands and alternatively, including consideration of measurand correlation. MU-derived reference change values (RCV) were calculated between chemistry and blood gas analyzers results. Observational paired AGAP data (n=39,626 subjects) was obtained from retrospectively analyzed specimens from five urban tertiary care hospitals in Calgary, Alberta, Canada. RESULTS: The MU derived AGAP RCV for paired specimen data by the two platforms was 5.2-6.1 mmol/L assuming no correlation and 2.6-3.1 mmol/L assuming correlation. From the paired chemistry and blood gas data, total observed variation on a reported AGAP has a 95% confidence interval of ±6.0 mmol/L. When the MU-derived RCV assuming correlation is directly compared against the observed distribution of patient results, we obtained a pre-analytical variation contribution of 2.9-3.5 mmol/L to the AGAP observed variation. In contrast, assuming no correlation leads to a negligible pre-analytical contribution (<1.0 mmol/L). CONCLUSIONS: MU estimates assuming no correlation are more representative of the total variation seen in real patient data. We present a pragmatic approach for validating an MU calculation to inform clinical decisions and determine the pre-analytical contribution to MU in this system.

Lot-to-lot reagent verification: challenges and possible solutions.

Lot-to-lot verification is an important laboratory activity that is performed to monitor the consistency of analytical performance over time. In this opinion paper, the concept, clinical impact, challenges and potential solutions for lot-to-lot verification are exained.

Personalized Reference Intervals in Laboratory Medicine: A New Model Based on Within-Subject Biological Variation.

BACKGROUND: The concept of personalized medicine has received widespread attention in the last decade. However, personalized medicine depends on correct diagnosis and monitoring of patients, for which personalized reference intervals for laboratory tests may be beneficial. In this study, we propose a simple model to generate personalized reference intervals based on historical, previously analyzed results, and data on analytical and within-subject biological variation. METHODS: A model using estimates of analytical and within-subject biological variation and previous test results was developed. We modeled the effect of adding an increasing number of measurement results on the estimation of the personal reference interval. We then used laboratory test results from 784 adult patients (>18 years) considered to be in a steady-state condition to calculate personalized reference intervals for 27 commonly requested clinical chemistry and hematology measurands. RESULTS: Increasing the number of measurements had little impact on the total variation around the true homeostatic set point and using ≥3 previous measurement results delivered robust personalized reference intervals. The personalized reference intervals of the study participants were different from one another and, as expected, located within the common reference interval. However, in general they made up only a small proportion of the population-based reference interval. CONCLUSIONS: Our study shows that, if using results from patients in steady state, only a few previous test results and reliable estimates of within-subject biological variation are required to calculate personalized reference intervals. This may be highly valuable for diagnosing patients as well as for follow-up and treatment.

Analytical assessment of ortho clinical diagnostics high-sensitivity cardiac troponin I assay.

OBJECTIVES: To analytically evaluate Ortho Clinical Diagnostics VITROS high-sensitivity cardiac troponin I (hs-cTnI) assay in specific matrices with comparison to other hs-cTn assays. METHODS: The limit of detection (LoD), imprecision, interference and stability testing for both serum and lithium heparin (Li-Hep) plasma for the VITROS hs-cTnI assay was determined. We performed Passing-Bablok regression analyses between sample types for the VITROS hs-cTnI assay and compared them to the Abbott ARCHITECT, Beckman Access and the Siemens ADVIA Centaur hs-cTnI assays. We also performed Receiver-operating characteristic curve analyses with the area under the curve (AUC) determined in an emergency department (ED)-study population (n=131) for myocardial infarction (MI). RESULTS: The VITROS hs-cTnI LoD was 0.73 ng/L (serum) and 1.4 ng/L (Li-Hep). Stability up to five freeze-thaws was observed for the Ortho hs-cTnI assay, with the analyte stability at room temperature in serum superior to Li-Hep with gross hemolysis also affecting Li-Hep plasma hs-cTnI results. Comparison of Li-Hep to serum concentrations (n=202), yielded proportionally lower concentrations in plasma with the VITROS hs-cTnI assay (slope=0.85; 95% confidence interval [CI]:0.83-0.88). In serum, the VITROS hs-cTnI concentrations were proportionally lower compared to other hs-cTnI assays, with similar slopes observed between assays in samples frozen <-70 °C for 17 years (ED-study) or in 2020. In the ED-study, the VITROS hs-cTnI assay had an AUC of 0.974 (95%CI:0.929-0.994) for MI, similar to the AUCs of other hs-cTn assays. CONCLUSIONS: Lack of standardization of hs-cTnI assays across manufacturers is evident. The VITROS hs-cTnI assay yields lower concentrations compared to other hs-cTnI assays. Important differences exist between Li-Hep plasma and serum, with evidence of stability and excellent clinical performance comparable to other hs-cTn assays.

Analytical Performance Specifications for Lipoprotein(a), Apolipoprotein B-100, and Apolipoprotein A-I Using the Biological Variation Model in the EuBIVAS Population.

BACKGROUND: With increased interest in lipoprotein(a) (Lp[a]) concentration as a target for risk reduction and growing clinical evidence of its impact on cardiovascular disease (CVD) risk, rigorous analytical performance specifications (APS) and accuracy targets for Lp(a) are required. We investigated the biological variation (BV) of Lp(a), and 2 other major biomarkers of CVD, apolipoprotein A-I (apoA-I) and apolipoprotein B-100 (apoB), in the European Biological Variation Study population. METHOD: Serum samples were drawn from 91 healthy individuals for 10 consecutive weeks at 6 European laboratories and analyzed in duplicate on a Roche Cobas 8000 c702. Outlier, homogeneity, and trend analysis were performed, followed by CV-ANOVA to determine BV estimates and their 95% CIs. These estimates were used to calculate APS and reference change values. For Lp(a), BV estimates were determined on normalized concentration quintiles. RESULTS: Within-subject BV estimates were significantly different between sexes for Lp(a) and between women aged <50 and >50 years for apoA-I and apoB. Lp(a) APS was constant across concentration quintiles and, overall, lower than APS based on currently published data, whereas results were similar for apoA-I and apoB. CONCLUSION: Using a fully Biological Variation Data Critical Appraisal Checklist (BIVAC)-compliant protocol, our study data confirm BV estimates of Lp(a) listed in the European Federation of Clinical Chemistry and Laboratory Medicine database and reinforce concerns expressed in recent articles regarding the suitability of older APS recommendations for Lp(a) measurements. Given the heterogeneity of Lp(a), more BIVAC-compliant studies on large numbers of individuals of different ethnic groups would be desirable.

Repeatability and reproducibility of lipoprotein particle profile measurements in plasma samples by ultracentrifugation.

Background Characterization of lipoprotein particle profiles (LPPs) (including main classes and subclasses) by means of ultracentrifugation (UC) is highly requested given its clinical potential. However, rapid methods are required to replace the very labor-intensive UC method and one solution is to calibrate rapid nuclear magnetic resonance (NMR)-based prediction models, but the reliability of the UC-response method required for the NMR calibration has been largely overlooked. Methods This study provides a comprehensive repeatability and reproducibility study of various UC-based lipid measurements (cholesterol, triglycerides [TGs], free cholesterol, phospholipids, apolipoprotein [apo]A1 and apoB) in different main classes and subclasses of 25 duplicated fresh plasma samples and of 42 quality control (QC) frozen pooled plasma samples of healthy individuals. Results Cholesterol, apoA1 and apoB measurements were very repeatable in all classes (intraclass correlation coefficient [ICC]: 92.93%-99.54%). Free cholesterol and phospholipid concentrations in main classes and subclasses and TG concentrations in high-density lipoproteins (HDL), HDL subclasses and low-density lipoproteins (LDL) subclasses, showed worse repeatability (ICC: 19.21%-99.08%) attributable to low concentrations, variability introduced during UC and assay limitations. On frozen QC samples, the reproducibility of cholesterol, apoA1 and apoB concentrations was found to be better than for the free cholesterol, phospholipids and TGs concentrations. Conclusions This study shows that for LPPs measurements near or below the limit of detection (LOD) in some of the subclasses, as well as the use of frozen samples, results in worsened repeatability and reproducibility. Furthermore, we show that the analytical assay coupled to UC for free cholesterol and phospholipids have different repeatability and reproducibility. All of this needs to be taken into account when calibrating future NMR-based models.

Sample matrix and high-sensitivity cardiac troponin I assays.

Background Manufacturers of high-sensitivity cardiac troponin (hs-cTn) assays have restricted use of what sample types or matrices are acceptable to use for measurement. Our goal was to evaluate the comparability of the Siemens ADVIA Centaur hs-cTnI assay across different matrices and under different storage conditions. Methods Three different QC-plasma matrices were evaluated for imprecision <10 ng/L. Passing-Bablok regression and difference plots were determined for cTnI concentrations spanning the reference interval (limit of quantification to male 99th-percentile: 2.5 ng/L to <60 ng/L) between serum and lithium heparin plasma, lithium heparin and EDTA plasma and between the Siemens and Abbott hs-cTnI assays. Stability at room temperature (RT) and 2-8 °C was also assessed across the three matrices. Results Over 16-weeks the SDs were ≤1.0 ng/L for QCs ranging from 5.0 to 8.3 ng/L. Across the reference interval there was excellent agreement between lithium heparin plasma and serum for the Siemens hs-cTnI assay (slope=0.98/intercept=-0.1), however, cTnI concentrations were proportionally lower in EDTA as compared to lithium heparin plasma (slope=0.90, 95% CI: 0.88-0.92). In lithium heparin plasma the Siemens hs-cTnI concentrations were higher than the Abbott hs-cTnI concentrations (slope=1.26/intercept=-0.2). Stability of cTnI in lithium heparin plasma as compared in serum and EDTA plasma appeared more labile, with decreases ≥20% in concentrations evident as early as 1-day in storage at RT. Conclusions There is excellent agreement in concentrations between lithium heparin plasma and serum with the Siemens ADVIA Centaur hs-cTnI assay; however, cTnI concentrations in EDTA plasma are lower. Reference intervals and clinical studies in EDTA plasma for the Centaur hs-cTnI assay are required before clinical use.

Assessing matrix, interferences and comparability between the Abbott Diagnostics and the Beckman Coulter high-sensitivity cardiac troponin I assays.

BACKGROUND: Analytical evaluation of high-sensitivity cardiac troponin (hs-cTn) assays, with particular attention to imprecision, interferences and matrix effects, at normal cTn concentrations, is of utmost importance as many different clinical algorithms use concentration cutoffs <10 ng/L for decision-making. The objective for the present analytical study was to compare the new Beckman Coulter hs-cTnI assay (Access hsTnI) to Abbott's hs-cTnI assay in different matrices and for different interferences, with a focus on concentrations <10 ng/L. METHODS: The limit of blank (LoB) and the limit of detection (LoD) were determined in different matrices for the Beckman hs-cTnI assay. Passing-Bablok regression and difference plots were determined for 200 matched lithium heparin and EDTA plasma samples for the Beckman assay and 200 lithium heparin samples for the Abbott assay. Both EDTA and heparin plasma samples were also evaluated for stability under refrigerated conditions, for endogenous alkaline phosphatase interference and for hemolysis and icterus. RESULTS: The Beckman hs-cTnI assay LoB was 0.5 ng/L with the following range of LoDs=0.8-1.2 ng/L, with EDTA plasma yielding lower concentrations as compared to lithium heparin plasma (mean difference=-14.9%; 95% CI=-16.9 to 12.9). Below 10 ng/L, lithium heparin cTnI results from the Beckman assay were on average 1.1 ng/L (95% CI=0.7 to 1.5) higher than the Abbott results, with no difference between the methods when using EDTA plasma (mean difference =-0.1 ng/L; 95% CI=-0.3 to 0.2). Low cTnI concentrations were less effected by interferences in EDTA plasma. CONCLUSIONS: The Access hsTnI method can reliably detect normal cTnI concentrations with both lithium heparin and EDTA plasma being suitable matrices.

Analytical and between-subject variation of thrombin generation measured by calibrated automated thrombography on plasma samples.

BACKGROUND: The Calibrated Automated Thrombography (CAT) is an in vitro thrombin generation (TG) assay that holds promise as a valuable tool within clinical diagnostics. However, the technique has a considerable analytical variation, and we therefore, investigated the analytical and between-subject variation of CAT systematically. Moreover, we assess the application of an internal standard for normalization to diminish variation. METHODS: 20 healthy volunteers donated one blood sample which was subsequently centrifuged, aliquoted and stored at -80 °C prior to analysis. The analytical variation was determined on eight runs, where plasma from the same seven volunteers was processed in triplicates, and for the between-subject variation, TG analysis was performed on plasma from all 20 volunteers. The trigger reagents used for the TG assays included both PPP reagent containing 5 pM tissue factor (TF) and PPPlow with 1 pM TF. Plasma, drawn from a single donor, was applied to all plates as an internal standard for each TG analysis, which subsequently was used for normalization. RESULTS: The total analytical variation for TG analysis performed with PPPlow reagent is 3-14% and 9-13% for PPP reagent. This variation can be minimally reduced by using an internal standard but mainly for ETP (endogenous thrombin potential). The between-subject variation is higher when using PPPlow than PPP and this variation is considerable higher than the analytical variation. CONCLUSION: TG has a rather high inherent analytical variation but considerable lower than the between-subject variation when using PPPlow as reagent.

Biological Variation and Reference Change Value Data for Serum Neuron-Specific Enolase in a Turkish Population.

BACKGROUND: Neuron-specific enolase (NSE) is a recognized biomarker for the assessment of cerebral injury in neurological disorders. This study aims to report a definitive assessment of the biological variation (BV) components of this biomarker, including within-subject BV (CVI), between-subject BV (CVG), index of individuality (II), and reference change value (RCV), in a cohort of Turkish participants using an experimental protocol. METHODS: Six blood specimens were collected from each of the 13 apparently healthy volunteers (seven women, six men; ranging in age from 23 to 36) on the same day, every 2 weeks for 2 months. Serum specimens were stored at -20°C until analysis. Neuron-specific enolase levels were evaluated in serum samples using an electrochemiluminescence (ECLIA) immunoassay kit with a Roche Cobas e 411 auto-analyser. ANOVA test was used to calculate the variations. RESULTS: The CVI and CVG for NSE were 21.5% and 28.8%, respectively. Analytical variation (CVA) was calculated as 10.2%. Additionally, II and RCV were calculated as 0.74 and 66% (95% confident interval, CI), respectively. CONCLUSION: As the performance index (PI) was found to be less than 2 (PI = 0.95), it is concluded that the NSE measurements have a desirable performance for analytical imprecision. Since the II was found to be less than 1 (II: 0.74), the reference values will be of little use. Thus, RCV would provide better information for deciding whether a significant change has occurred.

Biological variations of some analytes in renal posttransplant patients: a different way to assess routine parameters.

BACKGROUND: Biological variation (BV) data of analytes have been used to evaluate the significant changes in serial results (reference change value, RCV) of healthy individuals in clinical laboratories. However, BV data of healthy subjects may not be identical to the analytes of patients with ongoing clinical condition. The aim of this study was to calculate intra-(CVw) (coefficient of variation for intra-individual BV) and inter-individual (CVg) BV, index of individuality, and RCV of nine serum analytes of renal posttransplant patients. METHODS: Six serum specimens were obtained in an interval of two months in a one-year period from 70 transplant patients who had been stable for three years. Each time creatinine, uric acid, urea, sodium, potassium, calcium, inorganic phosphate, total protein, and albumin of these patients were analyzed with an integrated clinical chemistry/immunoassay auto-analyzer. ANOVA tests were used to calculate the variations. Results were compared with the data of healthy subjects obtained from BV database. RESULTS: CVw of all nine analytes of the renal transplant patients were higher than the healthy subjects. RCVs of these analytes were calculated as 14.5% for creatinine, 16.5% for urea, 13.7% for urate, 12.57% for albumin, 8.26% for total protein, 3.25% for sodium, 12.81% for potassium, 5.88% for calcium, and 21.57% for inorganic phosphate. CONCLUSION: RCV concept for predicting the clinical status in posttransplant population represents an optimization of laboratory reporting and could be a valuable tool for clinical decision.

The Uncertainty of the eGFR.

The estimated glomerular filtration rate (eGFR) is a parameter derived from the serum creatinine, patient age and gender and is used to ascertain renal function. It is subject to variation because of the analytical error of the creatinine measurement and biological variation. The widespread use of the eGFR to classify renal disease has led to the identification of more patients with marginal chronic kidney disease but because of the uncertainty of the eGFR it has also led to over-diagnosis of some kidney disease. There is a well described age relation with eGFR.The uncertainty of the eGFR at the critical decision level of 60 mL/min/1.73 m(2) is calculated to be 11. Caution needs to be exercised when interpreting an eGFR between 49 and 71 mL/min/1.73 m(2).

Instrumental Drift in Untargeted Metabolomics: Optimizing Data Quality with Intrastudy QC Samples.

Untargeted metabolomics is an important tool in studying health and disease and is employed in fields such as biomarker discovery and drug development, as well as precision medicine. Although significant technical advances were made in the field of mass-spectrometry driven metabolomics, instrumental drifts, such as fluctuations in retention time and signal intensity, remain a challenge, particularly in large untargeted metabolomics studies. Therefore, it is crucial to consider these variations during data processing to ensure high-quality data. Here, we will provide recommendations for an optimal data processing workflow using intrastudy quality control (QC) samples that identifies errors resulting from instrumental drifts, such as shifts in retention time and metabolite intensities. Furthermore, we provide an in-depth comparison of the performance of three popular batch-effect correction methods of different complexity. By using different evaluation metrics based on QC samples and a machine learning approach based on biological samples, the performance of the batch-effect correction methods were evaluated. Here, the method TIGER demonstrated the overall best performance by reducing the relative standard deviation of the QCs and dispersion-ratio the most, as well as demonstrating the highest area under the receiver operating characteristic with three different probabilistic classifiers (Logistic regression, Random Forest, and Support Vector Machine). In summary, our recommendations will help to generate high-quality data that are suitable for further downstream processing, leading to more accurate and meaningful insights into the underlying biological processes.