Vasile, Vlad C.

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 <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 Erectile dysfunction (ED) is a known precursor and sequela of cardiovascular disease (CVD), with ED severity predicting CVD severity. Aim This study aimed to evaluate the utility of ceramide levels in patients with ED. Methods We initiated ceramide testing in all patients with ED. We retrospectively analyzed ceramide levels from electronic records and stratified by severity of symptoms using the erectile function domain of the International Index of Erectile Function (IIEF). Outcomes The study aimed to determine whether abnormal ceramide levels were associated with ED severity and increased cardiovascular risk. Results Three hundred and fifty-four patients were reviewed, of whom 253 (71.5%) had moderate or higher ED. A statistically significant difference in abnormal ceramide values was found in patients with moderate to severe symptoms, and the odds of getting an abnormal ceramide test were increased based on the IIEF scoring alone (odds ratio [OR] 2.3 [1.04-5.12]; P-value = .034). Clinical Implications Serum ceramide testing could be beneficial in identifying cardiovascular risk in men with ED, potentially prompting cardiac referrals and lifestyle modifications. Strengths and Limitations The strengths of this study include a large sample size and the use of a well-established scale, while the limitations include the retrospective nature of the study and the need for further research to validate the findings. Conclusion Patients undergoing management for ED may benefit from serum ceramide testing and subsequent cardiac referral.

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 (<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 <5% and <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 Low-density lipoprotein cholesterol (LDL-C) is directly associated with coronary artery disease (CAD) risk. Subfractionation of LDL enables differentiation between large-buoyant LDL (>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 > 160 mg/dL, LDL-P > 1600 nmol/L, and LDL-S < 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.

Lipoprotein a (Lp(a)) is a lipid biomarker that binds cholesterol and bears independent cardiovascular risk. Strategies to lower the level of Lp(a) and mitigate such risk are important both for primary and secondary prevention. Currently there are no approved therapies targeting Lp(a) directly. Lipid lowering therapies prescribed routinely may have no effect on Lp(a) levels. Some agents such as niacin and estrogens can significantly decrease Lp(a), but their use is not recommended due to their adverse safety profile. Statins increase Lp(a) levels by 10–20%, questioning the benefit of such therapy when this biomarker is elevated. The Food and Drug Administration (FDA) endorses new agents to address dyslipidemia such as proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9-i) and Inclisiran, a small interfering RNA. These approaches have been shown to also significantly reduce Lp(a), but more clinical data is needed before implementing their use in clinical practice. Clinical trials are currently ongoing to test the efficacy of newly developed antisense oligonucleotides and small interfering RNAs targeting the gene encoding for Lp(a) in hepatocytes, while other investigations assess small molecules that inhibit Lp(a) assembly. This review summarizes the pathophysiology and clinical implications of Lp(a) elevation, and focuses on proposed Lp(a) therapies and the current state of the clinical trials of such novel agents.

Abstract Background/Introduction The use of a single low high-sensitivity cardiac troponin measurement to rule out myocardial infarction (MI) at presentation is advocated by international guidelines. Studies have not systematically compared high-sensitivity cardiac troponin (hs-cTn) I and T assays to determine which values should be used to rule out MI in patients with suspected acute coronary syndrome. Methods In a pooled analysis from three prospective observational cohort studies the lowest cTn concentration was determined that gave a negative predictive value (NPV) of ≥99.5% for MI or death at 30 days on presentation to the emergency department. EDTA or lithium heparin plasma or serum samples collected at presentation were measured using five hs-cTnI assays (Abbott ARCHITECT i2000, Beckman Coulter Access 2, Siemens Atellica IM, Ortho-Clinical Diagnostics VITROS 5600, LSI Medience PATHFAST) and one hs-cTnT assay (Roche Cobas e411). The diagnostic outcome of MI or death at 30 days was adjudicated according to the Fourth Universal Definition of MI. Optimal thresholds were determined to identify the highest proportion of patients that could be considered for discharge for a NPV of ≥99.5% for each assay. Results Among 941 patients, MI or death at 30 days occurred in 113 (12%). Optimized thresholds varied between assays ranging from <2 to <7 ng/L (Table) that identified between 22% and 60% of patients as low risk (0-1%) for MI or death at 30 days. Conclusions Our data identify differences in the effectiveness of thresholds between hs-cTnI and hs-cTnT assays for the same safety performance to rule out MI on presentation using a single measurement. In some cases, these thresholds differ from those used in clinical practice. Due to lack of assay standardization, optimal decision thresholds should be defined and validated for each high sensitivity cTn assay.

Abstract Background Patients with elevated free glycerol can have falsely elevated triglyceride concentrations known as pseudohypertriglyceridemia. Most clinical laboratory triglycerides methods measure the concentration of glycerol released following the enzymatic hydrolysis of triglycerides to quantitate triglycerides. Thus, increased free glycerol can lead to falsely increased triglyceride concentration. Identifying and measuring the interference is necessary to effectively manage patient care interventions. A glycerol-corrected triglyceride assay was discontinued from Roche Diagnostics in 2021. We created a process to determine glycerol-corrected triglycerides by measuring glycerol directly using an assay from Randox Laboratories. Methods Glycerol (Randox Laboratories) and nonglycerol-blanked triglycerides (Roche Diagnostics) were measured in serum using the Roche Cobas c501. Stability (n=10) and expected values (n=206) were determined using serum from healthy volunteers. Linearity (n=5) and precision (5 replicates on 2 runs over 5 days) were determined using residual clinical serum spiked with exogenous glycerol as necessary to span the analytical measuring range. Glycerol corrected triglyceride concentrations were calculated by subtracting glycerol (mmol/L) from triglyceride (mmol/L) and converting to mg/dL (x88.59). Samples previously measured using the Triglyceride/Glycerol Blanked Reagent (n=53, Roche Diagnostics) were used to assess accuracy. (Figure 1) Results Glycerol measures were stable 3 days refrigerated and 30 days frozen. Precision coefficient of variation was 1.0% within run and 7.1% within lab. Expected values were 10 - 109 mcmol/L, and the method was linear between 2 - 3,971 mcmol/L. The average bias between methods was 11.0% with slope of 1.02 and R2>0.97 (Figure 1). Conclusions Glycerol can be accurately measured using the Randox method and the result can be used to generate an accurate glycerol-corrected triglyceride concentration.

Abstract Background Calculated LDL cholesterol (LDL-C) is a standard component of the lipid panel and an important risk factor in managing atherosclerotic cardiovascular disease (ASCVD). Due to the assumptions in the derivation of the Friedwald formula, fasting (≥8 hours) and triglyceride levels ≤400mg/dL have long been recommended. More recent data have shown that in most cases fasting has minimal effect on results, leading to the endorsement of non-fasting lipid panels for routine evaluation of ASCVD risk in clinical practice guidelines. Furthermore, newer equations (e.g. Sampson-NIH) allow for more accurate estimation of LDL-C even in the presence of hypertriglyceridemia. Mayo Clinic has implemented the Sampson-NIH LDL-C calculation and removed fasting/non-fasting designation from lipid panel orders. We hypothesized that the change to fasting designation would allow more afternoon draws for routine lipid panels and that increased non-fasting collections may increase triglyceride levels, but that the Sampson-NIH equation would prevent bias in LDL-C estimation. In order to test these hypotheses, we analyzed patient data from 1 year prior and 1 year post-implementation. Methods Results of lipid panels performed for one year preceding (n=334,719) and one year after (n=381,804) removal of the fasting/non-fasting designation and implementation of Sampson-NIH equation were collected. Median, 10th, and 90th percentile of draw time, triglyceride, and LDL-C calculated by either Sampson-NIH or Friedwald formulas were compared by quantile regression. Results Draw times shifted post-implementation at the 10th percentile (7:06 vs. 7:10, p<0.0001), median (8:49 vs. 9:08, p<0.0001) and 90th (12:02 vs. 13:46, p<0.0001). No difference in median triglyceride measurement was observed between pre-and post-implementation (110mg/dL), but slight differences were observed in the 10th and 90th percentile values (60 vs 59mg/dL and 224 vs 229mg/dL, p<0.0001). No difference was observed in 10th, 50th, or 90th percentile LDL values when calculated by Sampson-NIH equation (56, 99, 153mg/dL); however, if the Friedwald formula is used, a slight shift is observed in the 10th and 50th percentile LDL values (54 vs. 53, 97 vs. 96; p<0.0001) but not the 90th (150mg/dL). Conclusions Changing to the Sampson/NIH formula for LDL-C and removing fasting vs. non-fasting designation from routine lipid panels had minimal effect on reported triglyceride and LDL-C values, while allowing increased flexibility in draw time and reporting of LDL-C on patients with triglycerides ≥400mg/dL. Patients with TG ≥400mg/dL represented 1.7% of the dataset overall, including 5,387 patients before the change in which LDL-C could not be reported and 6,697 patients in the year post-implementation for whom LDL-C was reported based on the Sampson-NIH formula. Using an equation that is robust in patients with elevated triglyceride levels and removing fasting requirements from routine lipid panels allows greater flexibility and convenience for patients while allowing for more even distribution of phlebotomy workload and reporting of LDL-C results for patients with hypertriglyceridemia without evidence of clinically significant bias in reported results.