EDTA Plasma Research Articles

The Impact of the Anticoagulant Type in Blood Collection Tubes on Circulating Extracellular Plasma MicroRNA Profiles Revealed by Small RNA Sequencing.

Pre-analytical factors have a significant influence on circulating microRNA (miRNA) profiling. The aim of this study was a comprehensive assessment of the impact of the anticoagulant type in blood collection tubes on circulating plasma miRNA profiles using small RNA sequencing. Blood from ten healthy participants (five males and five females from 25 to 40 years old) was taken in collection tubes with four different anticoagulants: acid citrate dextrose (ACD-B), sodium citrate, citrate-theophylline-adenosine-dipyridamole (CTAD) and dipotassium-ethylenediaminetetraacetic acid (K2 EDTA). Platelet-free plasma samples were obtained by double centrifugation. EDTA plasma samples had elevated levels of hemolysis compared to samples obtained using other anticoagulants. Small RNA was extracted from plasma samples and small RNA sequencing was performed on the Illumina NextSeq 500 system. A total of 30 samples had been successfully sequenced starting from ~1 M reads mapped to miRNAs, allowing us to analyze their diversity and isoform content. The principal component analysis showed that the EDTA samples have distinct circulating plasma miRNA profiles compared to samples obtained using other anticoagulants. We selected 50 miRNA species that were differentially expressed between the sample groups based on the type of anticoagulant. We found that the EDTA samples had elevated levels of miRNAs which are abundant in red blood cells (RBC) and associated with hemolysis, while the levels of some platelet-specific miRNAs in these samples were lowered. The ratio between RBC-derived and platelet-derived miRNAs differed between the EDTA samples and other sample groups, which was validated by quantitative PCR. This study provides full plasma miRNA profiles of 10 healthy adults, compares them with previous studies and shows that the profile of circulating miRNAs in the EDTA plasma samples is altered primarily due to an increased level of hemolysis.

Biomarkers of Clot Activation and Degradation and Risk of Future Major Cardiovascular Events in Acute Exacerbation of COPD: A Cohort Sub-Study in a Randomized Trial Population.

Cardiovascular diseases are common in patients with chronic obstructive pulmonary disease (COPD). Clot formation and resolution secondary to systemic inflammation may be a part of the explanation. The aim was to determine whether biomarkers of clot formation (products of von Willebrand Factor formation and activation) and clot resolution (product of fibrin degeneration) during COPD exacerbation predicted major cardiovascular events (MACE). The cohort was based on clinical data and biobank plasma samples from a trial including patients admitted with an acute exacerbation of COPD (CORTICO-COP). Neo-epitope biomarkers of formation and the activation of von Willebrand factor (VWF-N and V-WFA, respectively) and cross-linked fibrin degradation (X-FIB) were assessed using ELISAs in EDTA plasma at the time of acute admission, and analyzed for time-to-first MACE within 36 months, using multivariable Cox proportional hazards models. In total, 299/318 participants had samples available for analysis. The risk of MACE for patients in the upper quartile of each biomarker versus the lower quartile was: X-FIB: HR 0.98 (95% CI 0.65–1.48), VWF-N: HR 1.56 (95% CI 1.07–2.27), and VWF-A: HR 0.78 (95% CI 0.52–1.16). Thus, in COPD patients with an acute exacerbation, VWF-N was associated with future MACE and warrants further studies in a larger population.

Elimination of Herpes Simplex Virus-2 and Epstein-Barr Virus With Seraph 100 Microbind Affinity Blood Filter and Therapeutic Plasma Exchange: An Explorative Study in a Patient With Acute Liver Failure

OBJECTIVES:Herpes simplex virus (HSV)-2 is a rare cause of hepatitis that can lead to acute liver failure (ALF) and often death. The earlier the initiation of acyclovir treatment the better the survival. With regard to ALF, controlled randomized data support the use of therapeutic plasma exchange (TPE) both as bridge to recovery or transplantation—possibly by modulating the systemic inflammatory response and by replacing coagulation factors. Seraph 100 Microbind Affinity Blood Filter (Seraph; Ex Thera Medical, Martinez, CA), a novel extracorporeal adsorption device, removes living pathogens by binding to a heparin-coated surface was shown to efficiently clear HSV-2 particles in vitro. Here, we tested the combination of Seraph with TPE to reduce a massive HSV-2 viral load to reach a situation in that liver transplantation would be feasible.DESIGN:Explorative study.SETTING:Academic tertiary care transplant center.PATIENT:Single patient with HSV-2–induced ALF.INTERVENTIONS:TPE + Seraph 100 Microbind Affinity Blood Filter.MEASUREMENTS AND MAIN RESULTS:We report Seraph clearance data of HSV-2 and of Epstein-Barr virus (EBV) in vivo as well as total viral elimination by TPE. Genome copies/mL of HSV-2 and EBV in EDTA plasma were measured by polymerase chain reaction every 60 minutes over 6 hours after starting Seraph both systemically and post adsorber. Also, HSV-2 and EBV were quantified before and after TPE and in the removed apheresis plasma. We found a total elimination of 1.81 × e11 HSV-2 copies and 2.11 × e6 EBV copies with a single TPE (exchange volume of 5L; 1.5× calculated plasma volume). Whole blood clearance of HSV-2 in the first 6 hours of treatment was 6.64 mL/min (4.98–12.92 mL/min). Despite much lower baseline viremia, clearance of EBV was higher 36.62 mL/min (22.67–53.48 mL/min).CONCLUSIONS:TPE was able to remove circulating HSV-2 copies by 25% and EBV copies by 40% from the blood. On the other hand, clearance of HSV-2 by Seraph was clinically irrelevant, but Seraph seemed to be far more effective of removing EBV, implicating a possible use in EBV-associated pathologies, but this requires further study.

Prognosis of Alzheimer's Disease Using Quantitative Mass Spectrometry of Human Blood Plasma Proteins and Machine Learning.

Early recognition of the risk of Alzheimer’s disease (AD) onset is a global challenge that requires the development of reliable and affordable screening methods for wide-scale application. Proteomic studies of blood plasma are of particular relevance; however, the currently proposed differentiating markers are poorly consistent. The targeted quantitative multiple reaction monitoring (MRM) assay of the reported candidate biomarkers (CBs) can contribute to the creation of a consistent marker panel. An MRM-MS analysis of 149 nondepleted EDTA–plasma samples (MHRC, Russia) of patients with AD (n = 47), mild cognitive impairment (MCI, n = 36), vascular dementia (n = 8), frontotemporal dementia (n = 15), and an elderly control group (n = 43) was performed using the BAK 125 kit (MRM Proteomics Inc., Canada). Statistical analysis revealed a significant decrease in the levels of afamin, apolipoprotein E, biotinidase, and serum paraoxonase/arylesterase 1 associated with AD. Different training algorithms for machine learning were performed to identify the protein panels and build corresponding classifiers for the AD prognosis. Machine learning revealed 31 proteins that are important for AD differentiation and mostly include reported earlier CBs. The best-performing classifiers reached 80% accuracy, 79.4% sensitivity and 83.6% specificity and were able to assess the risk of developing AD over the next 3 years for patients with MCI. Overall, this study demonstrates the high potential of the MRM approach combined with machine learning to confirm the significance of previously identified CBs and to propose consistent protein marker panels.

Selective quantification of the 22-kDa isoform of human growth hormone 1 in serum and plasma by immunocapture and LC–MS/MS

The human growth hormone GH1 (22 kDa) is a commonly measured biomarker for diagnosis and during treatment of growth disorders, but its quantification by ligand binding assays may be compromised by the occurrence of a number of isoforms. These can interfere in the assays and lead to differences in results between laboratories and potentially even in the treatment of patients. We present an LC–MS/MS method that is able to distinguish the major growth hormone isoform (GH1, 22 kDa) from other isoforms and quantify it without any interference across the clinically relevant concentration range of 0.5 to 50 ng/mL. Analysis involves purification of a 100-µL serum sample by immunocapture using an anti-GH-directed antibody, tryptic digestion, and LC–MS/MS quantification of an isoform-specific signature peptide for GH1 (22 kDa). A tryptic peptide occurring in all GH isoforms is monitored in the same 16-min analytical run as a read-out for total GH. Stable-isotope-labeled forms of these two peptides are included as internal standards. Full validation of the method according to recent guidelines, against a recombinant form of the analyte in rat plasma calibrators, demonstrated intra-assay and inter-assay imprecision below 6% across the calibration range for both signature peptides and recoveries between 94 and 102%. An excellent correlation was found between nominal and measured concentrations of the WHO reference standard for GH1 (22 kDa). Addition of up to 1000 ng/mL biotin or the presence of a 100-fold excess of GH binding protein did not affect the measurement. Equivalent method performance was found for analysis of GH in serum, EDTA, and heparin plasma. Analyte stability was demonstrated during all normal sample storage conditions. Comparison with the IDS-iSYS GH immunoassay showed a good correlation with the LC–MS/MS method for the isoform-specific signature peptide, but a significant positive bias was observed for the LC–MS/MS results of the peptide representing total GH. This seems to confirm the actual occurrence of other GH isoforms in serum. Finally, in serum from pregnant individuals, no quantifiable GH1 (22 kDa) was found, but relatively high concentrations of total GH.Graphical abstract

Plasma calprotectin – preanalytical stability and interference from hemolysis

As an activation product of neutrophil granulocytes, calprotectin has been widely used in fecal samples for diagnosis and monitoring of patients with inflammatory bowel disease. However, fecal sample collection is cumbersome, and pre-analytical sources of error are plentiful. Therefore, plasma calprotectin is being investigated as a promising new biomarker. To utilize any biomarker, pre-analytical factors such as stability and susceptibility to interference from hemolysis must be established. We present precision estimates, stability results as well as interference study on plasma calprotectin in EDTA-plasma using the Thermo Fischer Phadia 250 EliATM Calprotectin immunoassay. Precision was estimated by the use of patient pools as well as internal quality controls provided by the manufacturer. Coefficients of variance were below 6.9% for patient samples. Calprotectin was stable in EDTA plasma after storage at 5–8 °C for up to 4 days, as well as after long-term storage at −20 °C. Susceptibility to interference from hemolysis was high, especially for low concentrations of calprotectin (<50 ng/mL) where hemoglobin levels above 0.02 mmol/L lead to false increase in calprotectin concentrations of up to 100%.

Stability of direct renin concentration and plasma renin activity in EDTA whole blood and plasma at ambient and refrigerated temperatures from 0 to 72 hours.

The aim of this study was to determine the appropriate transport and storage conditions for blood taken for direct renin concentration and plasma renin activity measurement, and whether cryoactivation of prorenin is seen at time points relevant to clinical practice. Blood was extracted from n=10 volunteers into K2-EDTA tubes. Stability of renin was assessed in whole blood stored at room temperature (15-25°C) and in the refrigerator (2-8°C) at 0h, 8h, and 24h. The stability of renin in plasma was determined under the same conditions at 0h, 24 h and 72h. Stability of plasma renin activity and direct renin concentration in whole blood stored at room temperature was found to be acceptable for up to 24h. At refrigerated temperature, whole blood stability was acceptable for measurement of direct renin concentration up to 8h and plasma renin activity up to 24h. In contrast, plasma renin activity was not stable in plasma stored at either room or refrigerated temperatures up to 24h; however, direct renin concentration had acceptable stability in plasma stored at room temperature for up to 24h, but stability was unacceptable at refrigerated temperatures. Samples collected for plasma renin activity and direct renin concentration should be transported as whole blood to optimise stability. After sample processing, plasma can be kept at room temperature for up to 24h for direct renin concentration, however, for determination of plasma renin activity separated plasma should be analysed or frozen as soon as possible.

Validity test of POCT (Point of Care Testing) method on blood glucose examination using whole blood samples, serum, and EDTA plasma

Medical laboratory services can support disease diagnosis or monitor patient recovery. The reality of the POCT method has been widely used by clinical laboratories. The tool is not only used for screening but is also used to check the diagnosis of diabetes mellitus. This research aims to determine the validity of the POCT method on whole blood, serum, and plasma EDTA samples on blood glucose tests. The research method of this study used the descriptive-analytical method using the POCT method on blood glucose tests using three different types of samples, whole blood, serum, and plasma EDTA. Precision tests were accepted on normal and pathological serum samples with CV% of 2.02% and 2.27%. The accuracy test was accepted on a normal and pathological serum with TE% values ​​of 8.54% and 6.03%. The linearity test is accepted on serum–plasma EDTA samples with an r2 value of 0.998. The sigma values ​​are in the unacceptable area. The use of the POCT tool for blood glucose examination has a valid performance value. The deviation of the examination results is influenced by pre-analytical errors such as sampling and processing samples so that the total error obtained is higher than the total allowed error. The POCT tool can be used for all types of samples.

Effect of olezarsen targeting APOC-III on lipoprotein size and particle number measured by NMR in patients with hypertriglyceridemia

Olezarsen is a hepatocyte-targeted, GalNAc-modified antisense oligonucleotide that decreases plasma levels of apolipoprotein C-III (apoC-III) and triglyceride-rich lipoproteins (TRLs). To define the effect of olezarsen on NMR-derived lipoprotein particle size and concentration. Patients (n=114) with or at risk for atherosclerotic cardiovascular disease and fasting triglycerides ≥200 and <500 mg/dL received olezarsen (10 or 50 mg every 4 weeks, 15 mg every 2 weeks, or 10 mg every week) or saline placebo subcutaneously for 6-12 months. NMR LipoProfile® analysis was performed in frozen EDTA plasma samples collected at baseline and at the primary analysis timepoint (PAT) at 6 months. A dose-dependent relationship was generally noted with increasing cumulative doses of olezarsen in TRL particle (TRLP), LDL particle (LDL-P) and HDL (HDL-P) particle concentrations. In the 50 mg every 4 weeks dose, compared to placebo, olezarsen resulted in a significant reduction in total TRL-P (51%, P<0.0001) with largest reductions in large-size (68%, P<0.0001) and medium-size (63%, P<0.0001) TRL-P. Total LDL-P concentration was not changed, but large LDL-P increased by 186% (p=0.0034), and small LDL-P decreased by 39% (p=0.0713). Total HDL-P concentration increased by 15% (P=0.0006), driven primarily by a 32% increase in small HDL subspecies (diameters <8.3 nm) (P=0.0008). Olezarsen results in favorable changes in lipoprotein concentration and particle size, primarily manifested by reduction in TRLs, remodeling to larger LDL particles, and increase in small HDL-P. These findings suggest that apoC-III inhibition improves the overall atherogenic risk profile.

Assessment of the Stability of Midregional Proadrenomedullin in Different Biological Matrices.

Midregional proadrenomedullin (MR-proADM) has been shown to play a key role in endothelial dysfunction, with increased levels helping to prevent early stages of organ dysfunction. Recent clinical evidence has demonstrated MR-proADM to be a helpful biomarker to identify disease severity in patients with sepsis as well as pneumonia. This biomarker is helpful at triage in emergency departments to assess risk level of patients. The aim of this study is to evaluate the stability of MR-proADM in different biological matrices. The results, obtained by Bland-Altman and scatter plot analyses, demonstrate that deviation of MR-proADM concentration in serum compared to EDTA plasma unequivocally shows that serum should not be used as a sample matrix. Instead, the excellent correlation of heparin plasma vs EDTA plasma samples shows that heparin plasma can be used without reservation in clinical routine and emergency samples.

Abstract 2227: Development and validation of a blood-based protein-only predictor of 5-year lung cancer risk in ever smokers

Abstract Background: Lung cancer is the second most common cancer type and is the leading cause of cancer death globally, with smoking and advancing age as the leading causal risk factors. The USPSTF guidelines for lung cancer screening recommends annual screening for select current or former smokers over 50 years of age. While annual screening via low dose CT has been demonstrated to decrease lung cancer mortality, compliance with screening guidelines remains low. Additional prognostic tools for future lung cancer risk stratification, particularly those without immutable demographic and health history, may be beneficial in increasing screening compliance and monitoring changing risk across time. Methods: Using modified-aptamer proteomics technology, SomaScan® assay v4.0, we scanned ~5000 proteins in 6085 EDTA plasma samples from “Ever Smokers” (current or former smokers, aged 50-73) with no known prevalent cancer at visit 3 of the Atherosclerosis Risk in Communities (ARIC) study, for a total of ~30 million protein measurements. A total of 348 incident lung cancer diagnoses occurred in this sample set, with 75 occurring within 5 years of visit 3 blood-draw. Time to lung cancer diagnosis events were modeled with protein measurements using machine learning methods in 70% of ARIC visit 3 ever smokers. A model was selected based on performance in a 15% holdout sample subset and validated in the remaining 15% ARIC visit 3 samples not used for model training or selection. Results: A 7-feature protein-only accelerated failure time (AFT) Weibull model was successfully developed to predict the probability of a lung cancer diagnosis within 5 years of blood draw. Model performance in training, model selection, and validation datasets was AUC equal to 0.76, 0.72, and 0.83, respectively. Based on predicted probabilities from the model, individuals were stratified into 3 risk bins (low, medium, and high) with a 5-year event rate of 0.49% vs 2.74% in low vs high risk bins. Model performance was additionally assessed in an independent Japanese cohort. Conclusion: We successfully developed a blood-based protein-only model that predicts risk of developing lung cancer in ever smokers. Performance of the protein model out-performs traditional risk factors for lung cancer and given the lack of immutable factors it has the potential to provide real-time risk which can be repeatedly assessed over time. Proteomics-driven risk stratification may have ability to increase adherence to lung cancer screening guidelines and/or influence a positive behavior change in modifiable risk-related behaviors. Citation Format: Clare Paterson, Leigh Alexander, Rachel Ostroff, Joseph Gogain, Yolanda Hagar, Hannah Biegel, Stephen Williams. Development and validation of a blood-based protein-only predictor of 5-year lung cancer risk in ever smokers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2227.

Nafamostat is a Potent Human Diamine Oxidase Inhibitor Possibly Augmenting Hypersensitivity Reactions during Nafamostat Administration.

Nafamostat is an approved short-acting serine protease inhibitor. However, its administration is also associated with anaphylactic reactions. One mechanism to augment hypersensitivity reactions could be inhibition of diamine oxidase (DAO). The chemical structure of nafamostat is related to the potent DAO inhibitors pentamidine and diminazene. Therefore, we tested whether nafamostat is a human DAO inhibitor. Using different activity assays, nafamostat reversibly inhibited recombinant human DAO with an IC50 of 300-400 nM using 200 µM substrate concentrations. The Ki of nafamostat for the inhibition of putrescine and histamine deamination is 27 nM and 138 nM, respectively For both substrates, nafamostat is a mixed mode inhibitor with P values of <0.01 compared with other inhibition types. Using 80-90% EDTA plasma, the IC50 of nafamostat inhibition was approximately 360 nM using 20 µM cadaverine. In 90% EDTA plasma, the IC50 concentrations were 2-3 µM using 0.9 µM and 0.18 µM histamine as substrate. In silico modeling showed a high overlap compared with published diminazene crystallography data, with a preferred orientation of the guanidine group toward topaquinone. In conclusion, nafamostat is a potent human DAO inhibitor and might increase severity of anaphylactic reaction by interfering with DAO-mediated extracellular histamine degradation. SIGNIFICANCE STATEMENT: Treatment with the short-acting anticoagulant nafamostat during hemodialysis, leukocytapheresis, extracorporeal membrane oxygenator procedures, and disseminated intravascular coagulation is associated with severe anaphylaxis in humans. Histamine is a central mediator in anaphylaxis. Potent inhibition of the only extracellularly histamine-degrading enzyme diamine oxidase could augment anaphylaxis reactions during nafamostat treatment.

Immunologic Biomarkers in Peripheral Blood of Persons With Tuberculosis and Advanced HIV.

IntroductionTuberculosis (TB) is a common opportunistic infection among people living with HIV. Diagnostic tests such as culture, Xpert-MTB-RIF, and ULTRA have low sensitivity in paucibacillary TB disease; a blood biomarker could improve TB diagnostic capabilities. We assessed soluble factors to identify biomarkers associated with TB among persons with advanced HIV.MethodsA case-control (1:1) study was conducted, with participants from Rio de Janeiro and Manaus, Brazil. People living with HIV presenting with CD4 count ≤100 cells/mm3 were eligible to participate. Cases had culture-confirmed TB (N=15) (positive for Mycobacterium tuberculosis [Mtb]); controls had HIV-infection only (N=15). Study visits included baseline, month 2 and end of TB therapy, during which samples of peripheral blood were obtained. A panel containing 29 biomarkers including cytokines, chemokines and growth factors was utilized to assess candidate biomarkers using Luminex technology in cryopreserved EDTA plasma samples. We used neural network analysis, based on machine learning, to identify biomarkers (single or in combination) that best distinguished cases from controls. Additional multi-dimensional analyses provided detailed profiling of the systemic inflammatory environment in cases and controls.ResultsMedian CD4 count and HIV-1 RNA load values were similar between groups at all timepoints. Persons with TB had lower body mass index (BMI) (median=19.6, Interquartile Range [IQR]=18.6-22.3) than controls (23.7; IQR: 21.8 = 25.5, p=0.004). TB coinfection was also associated with increased frequency of other comorbidities. The overall profile of plasma cytokines, chemokines and growth factors were distinct between the study groups at all timepoints. Plasma concentrations of IL-15 and IL-10 were on average lower in TB cases than in controls. When used in combination, such markers were able to discriminate between TB cases and controls with the highest degree of accuracy at each study timepoint.ConclusionAmong persons with advanced HIV, plasma concentrations of IL-15 and IL-10 can be used in combination to identify TB disease regardless of time on anti-TB treatment.

Plasma and Urine Metabolomic Response to an Ultra-Processed Dietary Pattern: A Biomarker Discovery Analysis in a Domiciled Randomized Controlled Crossover Feeding Trial

ObjectivesTo identify metabolomic markers that differed between dietary patterns (DP) that are either high in or void of ultra-processed foods (UPFs) according to NOVA. MethodsA secondary analysis of a randomized, crossover, controlled feeding trial in which 20 domiciled, healthy participants (mean ± SD: 31 ± 7 years, BMI 22 ± 11.6, 50% female) consumed a UPF-DP (80% UPFs) and an unprocessed DP (UN-DP; 0% UPFs) for two weeks with no washout. DPs were matched for energy, macronutrients, total fiber, total sugar, and sodium; presented at 200% of energy requirements; and consumed ad libitum. Metabolite levels were measured in EDTA plasma at the end of each DP (wk 2) and in 24-hr and spot urine at wk 1 and 2, using untargeted liquid chromatography with high resolution/tandem mass spectrometry and annotated using Metabolon’s reference library and authentic standards. Metabolites (n = 1000 plasma, n = 1272 24-hr urine, and n = 1281 spot urine) with <80% missing data and coefficients of variation <30% were assigned minimum detected values, scaled to median of 1, and log2-transformed. Linear mixed models in SAS identified metabolites that differed between UPF-DP and UN-DP adjusted for trial, DP sequence, timepoint, and body weight changes, with a subject-specific random intercept and Benjamini-Hochberg multiple comparison correction. ResultsFor plasma, 183 metabolites differed between UPF-DP and UN-DP at wk 2. For 24-hr urine, 461 metabolites differed between UPF-DP and UN-DP at wk 1 and 2, 68 of which also differed at wk 1 and 2 for spot urine. Twenty metabolites consistently differed between UPF-DP and UN-DP at each timepoint and for each sample type. The sub pathways for these 20 metabolites included glutamate metabolism (n = 1 metabolite); ascorbate and aldarate metabolism (n = 1); benzoate metabolism (n = 2); methionine, cysteine, SAM and taurine metabolism (n = 2); secondary bile acid metabolism (n = 2); fatty acid dicarboxylate (n = 1); and plant-food components (n = 2); 9 could not be annotated. ConclusionsWe identified exogenous and endogenous metabolites, representing a range of metabolic pathways, that consistently differed between a UPF-DP and UN-DP. These candidate biomarkers of UPF intake require investigation in larger samples with dietary data sufficient for NOVA classification. Funding SourcesNCI, NIDDK.

Circulating nucleosomes to identify non-smoker subjects at risk of lung cancer and triage them for low-dose CT scan.

e20558 Background: Lung cancer (LC) is the leading cause of cancer death worldwide and the most frequently occurring in men and the second most diagnosed cancer in woman after breast cancer. The primary risk factor leading to LC is tobacco smoke. Nevertheless, several studies in the US, UK and Asia reported an increasing rate of LC in non-smokers. 15-20% of LC patients worldwide are non-smokers with this percentage rising to 60% in non-smoking women in Asia. Current LC screening guidelines recommend a CT scan only for high-risk smokers. Despite there being no guidelines to recommend LC screening in non-smokers those with increased risk factors could be monitored. Therefore, a blood-test could offer a simple way to identify non-smokers at high-risk of LC and triage them to go for low-dose CT scan. Methods: We measured circulating levels of nucleosomes and CEA in 722 non-smoker subjects referred for CT scan at National Taiwan University Hospital. The patients were later confirmed to have either a LC (n = 509, including 401 patients at stage 0-1), non-malignant nodules (n = 142), or no-nodules (n = 71). Whole blood was collected in EDTA plasma tubes for analysis by six different Nu.Q chemiluminescent magnetic microparticle immunoassays (Belgian Volition SRL, Belgium) targeting H3.1-nucleosomes or different histone modifications (H3K9Me3-, H3K27Me3-, H3K36Me3-, H3K9Ac-, H3K14Ac-nucleosomes). CEA was analyzed on the Abbott ARCHITECT analyzer. We defined by logistic regression the best combination of biomarkers to identify LC cases in this non-smoking population in a rule-in approach. Results: At 95% specificity, none of the individual biomarkers exceed 24.8% of sensitivity for LC vs non-malignant nodules and no nodules. A combination of 2 nucleosome biomarkers: H3K9Me3- and H3K9Ac-nucleosomes with CEA in a logistic regression model showed improved sensitivity detecting 32.4% of LC in the non-smoker subjects at 95% specificity for LC vs non-malignant nodules and no nodules (area under the curve (AUC): 0.76, R2: 19.1%). In a non-smoking women sub-group by adding a third nucleosome biomarker: H3K36Me3-nucleosomes to the model we could detect 34.3% of the women who have lung cancer at 95% specificity (AUC: 0.75; R2: 20.2%). Conclusions: Our results indicate that a blood test combining circulating nucleosomes targeting different epigenetic modifications with CEA allow the detection of LC cases in a non-smokers population. This blood test could be part of the screening criteria for the non-smoking population at risk to develop LC and could help to triage them for low-dose CT scan.

High specificity lung cancer test to rule out cancer in non-malignant lung nodules found at LDCT.

e20533 Background: Lung Cancer (LC) is the leading cause of cancer death worldwide and smoking is the leading risk factor. Only 15% of patients with LC are still alive 5 years after diagnosis due to advanced diseases stage at diagnosis. Low-Dose Computed Tomography (LDCT) is the widely accepted standard for screening of individuals at high risk of lung cancer. However, LDCT has several limitations including the high prevalence of non-malignant pulmonary nodules detected leading to overdiagnosis, the potential harms of cumulative radiation dose and poor adherence to recommended follow-up. Therefore, novel blood-based tests could offer a simple follow confirmation approach and this test is designed to find those patients who DO NOT have cancer. Methods: We measured levels of nucleosomes, CEA and CYFRA21-1in a cohort of 912 subjects and report data relating to 184 smoker subjects referred for CT scan at National Taiwan University Hospital. The smoker patients were later confirmed to have either a LC (n = 129, including 59 patients at early stage (stage 0-I), 15 at stage II, 47 at late stage (III and IV) and 8 with unknown stage), or non-malignant nodules (n = 41), or control with no-nodules (n = 14). Whole blood was collected in EDTA plasma tubes for analysis by six different Nu.Q chemiluminescent magnetic microparticle immunoassays (Belgian Volition, Belgium) targeting H3.1-nucleosomes or different histone modifications (H3K9Me3-, H3K27Me3-, H3K36Me3-, H3K9Ac-, H3K14Ac-nucleosomes). CEA was analyzed on the Abbott ARCHITECT analyzer. CYFRA21-1 was analyzed on the Roche Cobas E411 analyzer. We evaluated each biomarker levels individually and in a combinatorial approach by logistic regression for their performance in discriminating subject with a LC vs non-malignant nodules. Results: Among the eight individual markers evaluated, the best area under the curve (AUC) in discriminating LC vs non-malignant nodule were observed for CEA, H3K9Ac-nucleosomes and CYFRA21-1 with an AUC of 0.68, 0.69 and 0.74, respectively and a specificity at 95% sensitivity of 9.5%, 7.3% and 21.4%, respectively. A logistic regression approach defined H3K9Ac-nucleosomes, CEA and CYFRA21-1 as the best panel of biomarkers tested to improve the discrimination between LC and non-malignant nodules relatives to the markers alone, achieving a specificity of 34.1% at 95% sensitivity and an AUC of 0.80. 55 out of the 59 stage 0-I, 25/26 stage III and 20/21 stage IV LC were detected by this combination of markers while 34.1 % of the patients with benign nodules are found negative and not sent to unnecessary biopsy to ascertain the nodule status. Conclusions: Results of our proof-of-concept study indicate that a blood test combining H3K9Ac-nucleosome levels with CEA and CYFRA21-1 levels could help to rule-out patients with a non-malignant nodule offering a non-invasive tool as an aid to the decision-making process of the malignancy status of nodules detected by LDCT.

Prognostic value of hPG80 (circulating progastrin) in IDH-wild type glioblastoma treated with radio-chemotherapy.

2049 Background: hPG80 (circulating progastrin) is a protein secreted by many cancer types, playing a role in tumorigenesis by regulating cancer stem cells, angiogenesis, proliferation/differentiation and decreasing apoptosis. hPG80 is detectable in plasma of cancer patients and previous studies have shown its prognostic role in various cancers. Given the lack of circulating biomarker in glioblastoma, we evaluated the prognostic value of plasma hPG80 in patients with IDH wild type glioblastoma Methods: This multicentric retrospective study included IDHwt glioblastoma patients treated with standard radio-chemotherapy. The ELISA DxPG80.lab kit (Biodena Care, Lausanne, Switzerland) was used to measure hPG80 levels after surgery with a detection threshold of 1 pM in all plasma EDTA samples according to the manufacturer’s instruction. The prognostic impact of hPG80 was evaluated on patient’s progression-free survival (PFS) and overall survival (OS). Results: We included 70 patients (38 males /32 women) with a median age of 64 years (Range 19 - 84). Karnofsky index was &gt; 70% in 52 (91%) of 57 evaluable patients. Tumor biopsy (B), partial resection (PR), complete resection (CR) were performed in 22, 25 and 23 patients respectively. MGMT promotor was methylated in 22 (40%) of the 55 evaluable patients. After surgery, hPG80 was detected in 48 (69%) patients (hPG80+) with a median concentration of 9.52 pM (IQR 5.21 - 21.20). Complete surgery was associated with undetectable levels of hPG80 (52% (CR) vs 28% (PR) vs 14% (B), p = 0.006) and lower concentration if hPG80+ (CR: 5.8 pM [IQR 1.92 - 11.38] vs PR: 12.84 pM [IQR 8.09 - 37.09]; p = 0.04 vs B: 9.86 pM [IQR 4.66 - 21.63]; p = 0.16). With a median follow-up of 39 months (22.4-NR), 86% of patients had progressed and 70% had died. In univariate analysis, hPG80 positivity was associated with PFS (5.6m vs 8.5m, p = 0.053) and OS (14.5 vs 22m, p = 0.04) in hPG80+ vs hPG80- patients respectively. hPG80+ patients with complete surgery had worse median OS than hPG80- patients (14.5 vs 22.0 m; p = 0.051 respectively. Cox proportional hazards model did not fit for covariate analysis. Conclusions: Our findings show that hPG80 could serve as a new circulating prognostic biomarker in IDHwt glioblastoma patients treated with radio-chemotherapy. Further explorations are ongoing in larger cohorts including longitudinal evaluation during the course of the disease.

Circulating cell-free DNA undergoes significant decline in yield after prolonged storage time in both plasma and purified form.

Circulating DNA (cirDNA) is generally purified from plasma that has been biobanked for variable lengths of time. In long-term experiments or clinical trials, the plasma can be stored frozen for up to several years. Therefore, it is crucial to determine the stability of cirDNA to ensure confidence in sample quality upon analysis. Our main objective was to determine the effect of storage for up to 2years on cirDNA yield and fragmentation. We stored frozen EDTA plasma and purified cirDNA from 10 healthy female donors, then quantified cirDNA yield at baseline, and at regular intervals for up to 2years, by qPCR and Qubit. We also compared cirDNA levels in non-haemolysed and haemolysed blood samples after 16months of storage and tested the effect of varying DNA extraction protocol parameters. Storage up to two years caused an annual cirDNA yield decline of 25.5% when stored as plasma and 23% when stored as purified DNA, with short fragments lost more rapidly than long fragments. Additionally, cirDNA yield was impacted by plasma input and cirDNA elution volumes, but not by haemolysis. The design of long-term cirDNA-based studies and clinical trials should factor in the deterioration of cirDNA during storage.

0554 Proteomic Approach for Understanding the Mechanisms of Periodic Limb Movements and Restless Legs Syndrome

Abstract Introduction Periodic limb movements (PLMs) are episodes of involuntary, repetitive muscle movements that are highly associated with restless legs syndrome (RLS). Although PLMs and RLS are reportedly two separate phenomena, both are tightly correlated and may result from a similar pathology. The present study profiled plasma protein biomarkers of PLMs and RLS to contribute to the identification of mechanisms associated with each disorder/trait. Methods The SomaScan highly multiplexed aptamer assay was used to profile 5,000 proteins in 24–48-hour old EDTA plasma samples from the Stanford Technology Analytics and Genomics in Sleep (STAGES) study. PLMs per hour (PLMI) were derived from overnight polysomnography and RLS was classified based on affirmative responses to questions of the Alliance Sleep Questionnaire. Three linear regression models were conducted to examine significant protein markers of 1) PLMI in the sample as a whole; 2) PLMI controlling for the presence of RLS; and 3) RLS without PLMs (i.e.,PLMI&amp;lt;5). All models included log2-normalized relative protein expression as the dependent variable and important covariates such as age, gender, BMI, sample storage time, and blood draw period. False discovery rate (FDR) to control for multiple testing was applied with an a-priori p-value of 0.05 for identifying significant associations. Results PLMI was significantly associated with 253 proteins (219 positive,34 negative). The inclusion of RLS in the model mitigated the significance of most proteins, and only 8 proteins remained significant. Negatively associated proteins (LEAP-1, Ferritin, SELH, Caspase-8) included functions related to iron storage, absorption, and delivery and negative regulation of inflammatory/immune responses. Positively associated proteins (SFRP4, RANTES, CathepsinA, DKK1) included proteins with functions related to immune response, inflammatory response, bone formation, and protein stability. RLS without PLMs was associated with 7 upregulated proteins (megalin, RUFY1, TADBP, ANGL7, LRTM2, SNAPN, STOM) with functions related to vitamin D metabolism, calcium and zinc binding, circadian rhythm regulation, and calcium-dependent neurotransmitter secretion. Conclusion These large proteomic analyses identified independent differential protein expressions for PLMs and RLS that suggest different pathophysiological contributions. Support (If Any) This work was supported, in part, by the National Heart, lung, and Blood institute [T32HL110952] and the Klarman Family Foundation.

0748 Proteomic Biomarkers of Obstructive Sleep Apnea

Abstract Introduction Obstructive sleep apnea (OSA) is characterized by recurrent, partial or complete obstructive respiratory events accompanied by interruptions in sleep with frequent arousals, deoxygenation, and/or sleep disturbance. The present study profiled the largest array of plasma proteins, to date, to contribute to the identification of proteomic biomarkers associated with the presence and severity of OSA. Methods The SomaScan highly multiplexed aptamer assay was used to profile 5,000 proteins in 24–48-hour old EDTA plasma samples from the Stanford Technology Analytics and Genomics in Sleep (STAGES) study. The apnea-hypopnea index (AHI) was derived from overnight polysomnography and all participants provided a blood sample. OSA severity was classified as moderate-to-severe (AHI&amp;gt;15) and controls/mild OSA (AHI&amp;lt;15). Univariate linear regression analyses included log2-normalized relative protein expression as the dependent variable, AHI/OSA as the independent variable, and important covariates such as age, gender, BMI, BMI2, age x gender x BMI, sample storage time, and blood draw period. False discovery rate (FDR) to control for multiple testing was applied with an a-priori p-value of 0.05 for identifying significance. Results Univariate analyses identified 101 (65 upregulated, 36 downregulated) differentially expressed proteins (DEPs) between moderate-to-severe OSA and controls/mild OSA and 120 proteins (69 positive, 51 negative) associated with AHI as a continuous outcome with 70 proteins consistent in both models. Upregulated proteins involved pathways related to complement and coagulation cascades and metabolic processes and downregulated proteins involved pathways related to regulation of insulin-like growth factor, fibrin clot formation, and MAPK signaling. An OSA machine learning classifier (AHI&amp;gt;15 vs AHI&amp;lt;15) trained on relative protein expression performed robustly, achieving 72% accuracy in a validation dataset. Significant contributing features of the classifier included age, BMI, and 134 proteins, including 22 DEPs identified in univariate analyses for OSA categories. Conclusion The present study identified differential protein expression patters associated with OSA and AHI, thereby supporting the potential of proteomic biomarkers in OSA and providing new insight into the mechanisms underlying OSA. Support (If Any) This work was supported, in part, by the National Heart, lung, and Blood institute [T32HL110952] and the Klarman Family Foundation.