Jaffe, Allan S.

Abstract Background/Introduction Macrotroponin refers to high-molecular-weight troponin complexes bound to immunoglobulins, shown to cause persistently elevated troponin values often unrelated to myocardial injury. We hypothesized that its frequency might increase with age and differ between men and women, reflecting potential age-related cardiac changes and sex-specific risk profiles. Purpose To assess whether macrotroponin frequency varies across age groups and by sex within the upper sex-specific 90th percentile of troponin values in a healthy Danish reference population. Methods Among 1,307 participant samples with normal-range NT-proBNP, HbA1c, and eGFR ≥90 mL/min/1.73m2, 147 samples with troponin I within the upper levels of the sex-specific 90th percentile for the Siemens Atellica assay were further tested for macrotroponin I using Protein A/G immunoglobulin depletion and sucrose gradient ultracentrifugation. Samples were only deemed macrotroponin-positive by concordantly positive results. After excluding 29 samples with low troponin values due to analytical dilution constraints, 118 participants remained. Macrotroponin I frequency was compared across three age groups (<40, 40–60, and >60 years) and between sexes. Logistic regression was used to adjust for creatinine levels. Results Of 118 samples tested (48% females), macrotroponin I was present in 88 (75%), with similar frequencies in women (80%) and men (77%). Macrotroponin I frequency did not differ significantly across age groups (p=0.26) or between sexes (p>0.5) (Table 1, Figure 1). Logistic regression revealed no significant associations between macrotroponin I and age group, sex, or creatinine levels (all p > 0.5). Conclusion Macrotroponin I was highly frequent in the highest troponin ranges in a healthy reference population and showed no relationship with age or sex. The presence of macrotroponin I may impact clinical management in a considerable number of patients, but further investigation is required in clinical studies.

Abstract Background Measurement of cardiac troponin (cTn) using high-sensitivity assays is recommended for the diagnosis of myocardial infarction. We determined sex-specific and uniform 99th percentile upper reference limits (URLs) using the new Elecsys® Troponin T high-sensitivity Gen 6 assay in a global, healthy reference range cohort. Methods Lithium-heparin plasma and serum samples were prospectively collected from apparently healthy individuals aged ≥20 years across 34 global sites in the United States, Europe, China, and Japan. cTnT was measured using the Troponin T high-sensitivity Gen 6 assay on the Cobas® e 801 analyzer. Exclusion criteria were defined according to the 2022 IFCC guidance. Uniform and sex-specific 99th percentile URLs and nonparametric 95% CIs were determined in plasma and serum separately and combined. Results The final study population comprised 4147 participants (52.5% female) with a median (25th–75th percentiles) age of 48.0 (33.0–59.0) years; 45.8%, 47.9%, 5.2%, and 1.1% were White, Asian, Black, and other/unknown, respectively. For sample matrices combined (n = 8294), 81.0% and 99.2% of cTnT values were above the limit of detection in females and males, respectively. Sex-specific 99th percentile URLs (95% CI) were 18 (16–23) ng/L for females and 32 (28–35) ng/L for males; the uniform 99th percentile URL was 27 (24–31) ng/L. URLs were comparable in plasma and serum samples. Conclusions This study determined sex-specific and uniform 99th percentile URLs for the Troponin T high-sensitivity Gen 6 assay that were comparable irrespective of the matrix used in a large, global, healthy reference population.

Abstract Object Transdermal biosensors may provide an alternative to conventional blood-based biomarker measurement. Our purpose was to determine the binary correlation between transdermal (Infrasensor™; RCE, Inc, Carlsbad, CA) and conventional blood-based measurements. Methods This was a secondary analysis from a previously published observational cardiac troponin I (cTnI) study performed to establish the upper reference level of cTnI, at 10 US hospitals. After obtaining informed consent, 2 cohorts of patients were enrolled: 1) those who completed a health assessment questionnaire and appeared healthy, and 2) those with a known elevated cTnI per the local hospital standard assay. All blood lab analyses were performed at the University of Maryland Medical Center, Baltimore, MD. Normal was defined as cTnI <53.48 ng/L (male) or 34.11 ng/L (female) using the Siemens Atellica IM assay (Siemens Medical Solutions, Mountain View, CA), NT-proBNP <450 pg/mL (>75 years) or <124 pg/mL (<75 years), creatinine >1.17 mg/dL (male) or >0.95 mg/dL (female), and HbA1c <6.4%. The Infrasensor was placed on the patient’s wrist for measurement and blood drawn for analysis at approximately the same time. Results Of 840 enrolled patients, the median (IQR) age was 46 (30,57), 416 (49.5%) were female, 10.36% Hispanic, 6.7% Asian, 12.9% African American, and 69.1% White. Elevated lab tests were 102 hscTnI’s, 156 NTproBNP’s, 37 HbA1C’s, and 163 creatinine’s. Significant binary correlations were found between all transdermal signals and the corresponding lab blood levels Conclusion Infrasensor transcutaneous measurement demonstrates similar results as that obtained from blood testing in the central laboratory. Capsule The Infrasensor (RCE, Inc, Carlsbad, CA, USA) is rapid point of care transcutaneous biomarker measurement device. This study evaluated its ability to provide qualitative results for troponin I, NTproBNP, creatinine, and HbA1c levels in 840 patients. Significant correlations were found between all transdermal signals and the corresponding binary lab blood levels.

Abstract Background Dipeptidyl peptidase 3 (DPP3) is a peptidase released from dying cells. It cleaves proteins in the renin–angiotensin pathway, which can result in hemodynamic instability. At elevated concentrations DPP3 is associated with worse outcomes, particularly in patients with shock. Herein we describe the assay performance of a DPP3 assay (4TEEN4 Pharmaceuticals GmbH) in human plasma. Methods DPP3 concentration was measured using the DPP3 immunoluminometric assay (4TEEN4 Pharmaceuticals GmbH) and the signal was read using a luminometer (Berthold Centro LB963). Analytical performance was established for precision, linearity, accuracy, detection limit, analytical specificity, reference interval, kit lot-to-lot comparison, specimen type, and sample stability. Results Limit of detection was verified at 1.6 ng/mL in EDTA plasma with a coefficient of variation (CV) of &lt;10%. Precision studies revealed a CV ≤ 6% at 28.5 ng/mL and 59.4 ng/mL and comparability with a manufacturer performed assay was demonstrated between 7.7 and 195.2 ng/mL. An upper 97.5% limit of 22 ng/mL without age or sex associations was verified in healthy donors. The assay was not susceptible to interference from lipemia or bilirubin. However, measured DPP3 concentrations increased linearly with increasing hemolysis. DPP3 concentrations are stable in EDTA plasma for up to 24 h and at least 11 months when stored ambient or at −80°C, respectively. Conclusions DPP3 can be measured precisely in EDTA plasma using the immunoluminometric DPP3 assay. Given the potential clinical use of DPP3 in critical care patients, caution should be taken to avoid inducing pre-analytical hemolysis during sample collection.

Abstract Background Insulin resistance leads to changes in lipid and lipoprotein metabolism prior to developing prediabetes, including an increase in the concentration of large very-low-density lipoprotein particles (LVLDL-p), the mean size of VLDL (VLDL-s), and the concentration of small low-density lipoprotein particles (sLDL-p). Conversely, there is a decrease in the concentration of large high-density lipoprotein particles (LHDL-p), mean size of HDL (HDL-s), and mean size of LDL (LDL-s). Clinically validated studies show that proton nuclear magnetic resonance (NMR) can measure these six parameters and derive a lipoprotein insulin resistance (LP-IR) score, ranging from 0 to 100, with higher scores indicating greater risk for insulin resistance. The reference method for calculating LP-IR relies on a proprietary NMR spectrometer, spectral deconvolution method, and algorithm. This study seeks to determine if lipoprotein subfraction parameters measured from a commercially available NMR system can produce LP-IR scores comparable to the reference method. Methods Serum lipoprotein NMR spectra were collected using a Bruker Ascend 600 MHz magnet, Bruker Avance NEO 500 spectrometer, and the Numares AXINON lipoFIT System to report the six LP-IR score parameters between January 2023 and January 2025 (Cohort A, n = 2,474). During the same period, LP-IR score and parameters were collected using the Vantera Clinical Analyzer (400 MHz) with the LipoProfile LP4 method (Cohort B, n = 2,959). Linear regression of decile-matched data for each parameter yielded adjustment equations to align lipoFIT values with the LipoProfile method. LP-IR scores were then calculated for both adjusted and unadjusted values using a previously published LP-IR scoring algorithm. Finally, LP-IR scores were compared for sera with measures from both instruments was (Cohort C, n = 108). Results The median concentrations of sLDL-p, LDL-s, VLDL-s, HDL-S matched between Cohort A and B (&lt;1% difference). Significant differences were noted for LVLDL-p and LHDL-p, with percent differences of 21.5% and 23.5%, respectively. Despite closely matching medians, the distributions varied greatly, with a mean interquartile range (IQR) percent difference across measures of 31.2% (Table 1). After distribution matching, all parameter median and mean IQR percent differences fell to &lt;5% and &lt;10%, respectively, between Cohort A and Cohort B. In Cohort C the LP-IR score matched well (y=1.1x-15, r=0.92; 95%CI 0.88, 0.94). Following distribution matching adjustment of lipoFIT values for Cohort C, new calculated LP-IR scores matched with reduced bias (y=0.94x-1.2) while correlation was slightly reduced (r=0.88 [0.83, 0.92]). By comparison, adjustments made via scaling lipoFIT values proportionally by the ratio of the medians between Cohort A and Cohort B yielded calculated LP-IR scores in Cohort C that maintained a similar bias prior to adjustments (y=1.2x-21), highlighting the ability of distribution matching to reduce bias. Conclusion Adjustments to measured lipoprotein parameters from a commercially available NMR spectrometer can be achieved via distribution matching. These adjustments greatly reduce the bias between a commercially available method and algorithm compared to the reference method, allowing for wider adoption of LP-IR score reporting.

Abstract Background This study simulates how assay-specific bias influences the diagnostic performance of 0/1-h accelerated diagnostic protocols (ADPs) for 3 different high-sensitivity cardiac troponin (hs-cTn) assays. Methods We included 1493 patients presenting with chest pain. hs-cTnT (Roche Diagnostics), hs-cTnI from Abbott Diagnostics (hs-cTnI-A), and Siemens Healthineers (hs-cTnI-S) were measured at admission. The absolute total error observed in a state-of-the-art EQA study were added to the admission concentrations, producing 6 new variables being adjusted for maximum possible bias (if analytical variation is 0) (+biasmean, +biasmax95%CI, +biasmin95%CI, −biasmean, −biasmax95%CI, −biasmin95%CI). The influence of this “worst-case scenario” bias was compared after calculating sensitivity, specificity, negative and positive predictive values, and rule-out proportion for 30-day myocardial infarction or death for the observed and bias-adjusted hs-cTn concentrations. Results For 0-h rule-out, hs-cTnI-S and hs-cTnT had a sensitivity of &gt;99.0%, compared to 97.7% for hs-cTnI-A. After adding the bias, sensitivity was unchanged for hs-cTnI-S (99.5%), but lower for hs-cTnT (95.5%), and hs-cTnI-A (96.2%). For the 0-/1-h algorithm, adding bias reduced sensitivity to 95.5% for hs-cTnT, while both hs-cTnI algorithms were unchanged (100.0%). Rule-out proportions for 0 h ranged from 0% to 60.0% for hs-cTnT, 28.2%–62.7% for hs-cTnI-A, and 3.5%–35.5% for hs-cTnI-S. For the 0-/1-h algorithm, ranges were 57.7%–75.8% (hs-cTnT), 52.8%–67.5% (hs-cTnI-A), and 45.7%–61.2% (hs-cTnI-S), Conclusion Analytical bias of hs-cTn assays affects the clinical rule-out rate of the 0/1-h ADPs more than the diagnostic sensitivity. Bias may have a greater influence on the proportion of patients requiring hospital admission and may contribute to the heterogeneity of the reported rule-out rates of current ADPs. ClinicalTrials.gov Registration Number: NCT02620202

Abstract Background Several guidelines groups have made recommendations about how to use natriuretic peptides (NPs) to screen patients with diabetes for incipient heart failure. This group is at risk for undetected and stage B heart failure, where structural heart disease is present despite the absence of clinical signs and symptoms. These recommendations are based on trial data that suggest there are therapeutic options to benefit these patients. Content These guidelines do not adequately account for the marked analytic differences between NP assays nor their high degree of biological and analytical variability. Thus, without additional data and guidance, these recommendations could lead to excessive testing for some groups but might disadvantage others. In addition, these issues could lead to difficulties in the interpretation of values. Accordingly, the Committee on Clinical Applications of Cardiac Bio Markers of the International Federation of Clinical Chemistry has developed a consensus educational document to describe these difficulties and define areas where additional data are needed. Clinicians should be cognizant of differences in the assays for NPs, the high degree of variability of values, differences in sex and ethnicity and the need to factor in a variety of clinical and treatment variables in interpreting NP values. Summary These suggestions for diabetes eventually will include others at high risk. They will require close attention to the issues involved in measuring and interpreting NP values.

Abstract Background Low-density lipoprotein cholesterol (LDL-C) is directly associated with coronary artery disease (CAD) risk. Subfractionation of LDL enables differentiation between large-buoyant LDL (&gt;20.5 nm) and small-dense LDL (≤20.5 nm). Small-dense LDL reportedly increases CAD risk, as do LDL-C and LDL particle (LDL-P) concentrations. Nuclear magnetic resonance spectroscopy (NMR) reports LDL-C, LDL-P, and LDL size (LDL-s). We investigated associations between these outputs and their agreement on CAD risk information. Methods Associations between LDL-P, LDL-C, and LDL-s measured by NMR were evaluated in serum from clinically ordered samples (n = 26 710), and a subset of patients with CAD evaluation from coronary angiography (n = 356). Correlations were determined using Spearman ρ, and clinical classifications were compared using the following thresholds for increased risk: LDL-C &gt; 160 mg/dL, LDL-P &gt; 1600 nmol/L, and LDL-S &lt; 20.5 nm. Results The large laboratory NMR data set showed LDL-C was highly correlated with LDL-P (ρ = 0.87), and moderately with LDL-s (ρ = 0.51). Correlation between LDL-P and LDL-s was weakest (ρ = 0.21). When comparing pairwise high- and low-risk laboratory values, concordant values were observed in 99.8%, 43%, and 25% of cases for LDL-P/LDL-C, LDL-s/LDL-P, and LDL-C/LDL-s, respectively. In patients with angiography and NMR results, CAD was diagnosed in 40% (6/15) of patients with concordant high-risk LDL-C and small-dense LDL-s in the smaller patient cohort, but only 19% (6/31) of CAD-positive patients with high-risk LDL-C had small-dense LDL-s. Conclusions LDL-s and LDL-C are frequently discordant at established LDL-C risk cutoffs. CAD diagnosis was found in similar numbers regardless of LDL-s phenotype.

Background: In the emergency setting, many diagnostic pathways incorporate change in high-sensitivity cardiac troponin (hs-cTn) concentrations (i.e., the delta) to classify patients as low-risk (rule-out) or high-risk (rule-in) for possible myocardial infarction (MI). However, the impact of analytical variation on the delta for correct classification is unknown, especially at concentrations below and around the 99th percentile. Our objective was to assess the impact of delta variation for correct risk classification across the European Society of Cardiology (ESC 0/1 h and 0/2 h), the High-STEACS, and the common change criteria (3C) pathways. Methods: A yearlong accuracy study for hs-cTnT was performed where laboratories across Canada tested three patient-based samples (level 1 target value = 6 ng/L, level 2 target value = 9 ng/L, level 3 target value = 12 ng/L) monthly across 41 different analyzers. The assigned low-delta between levels 1 and 2 was 3 ng/L (i.e., 9 − 6 = 3 ng/L) and the assigned high-delta between levels 1 and 3 was 6 ng/L (i.e., 12 − 6 = 6 ng/L). The low- and high-deltas for each analyzer were determined monthly from the measured values, with the difference calculated from the assigned deltas. The obtained deltas were then assessed via the different pathways on correct classification (i.e., percent correct with 95% confidence intervals, CI) and using non-parametric analyses. Results: The median (interquartile range) difference between the measured versus assigned low-delta (n = 436) and high-delta (n = 439) was −1 ng/L (−1 to 0). The correct classification differed among the pathways. The ESC 0/1 h pathway yielded the lowest percentage of correct classification at 35.3% (95% CI: 30.8 to 40.0) for the low-delta and 90.0% (95% CI: 86.8 to 92.6) for the high-delta. The 3C and ESC 0/2 h pathways yielded higher and equivalent estimates on correct classification: 95.2% (95% CI: 92.7 to 97.0) for the low-delta and 98.2% (95% CI: 96.4 to 99.2) for the high-delta. The High-STEACS pathway yielded 99.5% (95% CI: 98.4 to 99.9) of correct classifications for the high-delta but only 36.2% (95% CI: 31.7 to 40.9) for the low-delta. Conclusions: Analytical variation will impact risk classification for MI when using hs-cTn deltas alone per the pathways. The 3C and ESC 0/2 h pathways have <5% misclassification when using deltas for hs-cTnT in this dataset. Additional studies with different hs-cTnI assays at concentrations below and near the 99th percentile are warranted to confirm these findings.