Stability of the Human Plasma Proteome to Pre-analytical Variability as Assessed by an Aptamer-Based Approach

Aptamer-based sensors for fluid biopsies of protein disease markers

Fluid biopsy technology, characterized by its minimally invasive nature, speed, and continuity, has become a rapidly advancing and widely applied real-time diagnostic technique. Among various biomarkers, proteins represent the most abundant class of disease indicators. The sensitive and accurate detection of protein markers in bodily fluids is significantly influenced by the control exerted by recognition ligands. Aptamers, which are structurally dynamic functional oligonucleotides, exhibit high affinity, specific recognition of targets, and notable characteristics of high editability and modularity. These features make aptamer universal "recognition-capture" components, contribute to a significant leap in their applications within the biosensor domain. In this context, we provide a comprehensive review of the extensive application of aptamer-based biosensors in fluid biopsy. We systematically compile the characteristics and construction strategies of aptamer-based biosensors tailored for fluid biopsy, including aptamer sequences, affinity (KD), fluid background, sensing technologies, sensor construction strategies, incubation time, detection performance, and influencing factors. Furthermore, a comparative analysis of their advantages and disadvantages was conducted. In conclusion, we delineate and deliberate on prospective research trajectories and challenges that lie ahead in the realm of aptamer-based biosensors for fluid biopsy.

Large-scale circulating proteome association study (CPAS) meta-analysis identifies circulating proteins and pathways predicting incident hip fractures

Hip fractures are associated with significant disability, high cost, and mortality. However, the exact biological mechanisms underlying susceptibility to hip fractures remain incompletely understood. In an exploratory search of the underlying biology as reflected through the circulating proteome, we performed a comprehensive Circulating Proteome Association Study (CPAS) meta-analysis for incident hip fractures. Analyses included 6430 subjects from two prospective cohort studies (Cardiovascular Health Study and Trøndelag Health Study) with circulating proteomics data (aptamer-based 5 K SomaScan version 4.0 assay; 4979 aptamers). Associations between circulating protein levels and incident hip fractures were estimated for each cohort using age and sex-adjusted Cox regression models. Participants experienced 643 incident hip fractures. Compared with the individual studies, inverse-variance weighted meta-analyses yielded more statistically significant associations, identifying 23 aptamers associated with incident hip fractures (conservative Bonferroni correction 0.05/4979, P < 1.0 × 10-5). The aptamers most strongly associated with hip fracture risk corresponded to two proteins of the growth hormone/insulin growth factor system (GHR and IGFBP2), as well as GDF15 and EGFR. High levels of several inflammation-related proteins (CD14, CXCL12, MMP12, ITIH3) were also associated with increased hip fracture risk. Ingenuity pathway analysis identified reduced LXR/RXR activation and increased acute phase response signaling to be overrepresented among those proteins associated with increased hip fracture risk. These analyses identified several circulating proteins and pathways consistently associated with incident hip fractures. These findings underscore the usefulness of the meta-analytic approach for comprehensive CPAS in a similar manner as has previously been observed for large-scale human genetic studies. Future studies should investigate the underlying biology of these potential novel drug targets.

Analytical validation of the PROphet test for treatment decision-making guidance in metastatic non-small cell lung cancer

The blood proteome, consisting of thousands of proteins engaged in various biological processes, acts as a valuable source of potential biomarkers for various medical applications. PROphet is a plasma proteomics-based test that serves as a decision-support tool for non-small cell lung cancer (NSCLC) patients, combining proteomic profiling using SomaScan technology and subsequent computational algorithm. PROphet was implemented as a laboratory developed test (LDT). Under the Clinical Laboratory Improvement Amendments (CLIA) and Commission on Office Laboratory Accreditation (COLA) regulations, prior to releasing patient test results, a clinical laboratory located in the United States employing an LDT must examine its performance characteristics with regard to analytical validity. This study describes the experimental and computational analytical validity of the PROphet test, as required by CLIA/COLA regulations. Experimental precision analysis displayed a median coefficient of variation (CV) of 3.9 % and 4.7 % for intra-plate and inter-plate examination, respectively, and the median accuracy rate between sites was 88 %. Computational precision exhibited a high accuracy rate, with 93 % of samples displaying complete concordance in results. A cross-platform comparison between SomaScan and other proteomics platforms yielded a median Spearman's rank correlation coefficient of 0.51, affirming the consistency and reliability of the SomaScan platform as used under the PROphet test. Our study presents a robust framework for evaluating the analytical validity of a platform that combines an experimental assay with subsequent computational algorithms. When applied to the PROphet test, strong analytical performance of the test was demonstrated.

A uniform data processing pipeline enables harmonized nanoparticle protein corona analysis across proteomics core facilities

Protein corona, a layer of biomolecules primarily comprising proteins, forms dynamically on nanoparticles in biological fluids and is crucial for predicting nanomedicine safety and efficacy. The protein composition of the corona layer is typically analyzed using liquid chromatography-mass spectrometry (LC-MS/MS). Our recent study, involving identical samples analyzed by 17 proteomics facilities, highlighted significant data variability, with only 1.8% of proteins consistently identified across these centers. Here, we implement an aggregated database search unifying parameters such as variable modifications, enzyme specificity, number of allowed missed cleavages and a stringent 1% false discovery rate at the protein and peptide levels. Such uniform search dramatically harmonizes the proteomics data, increasing the reproducibility and the percentage of consistency-identified unique proteins across distinct cores. Specifically, out of the 717 quantified proteins, 253 (35.3%) are shared among the top 5 facilities (and 16.2% among top 11 facilities). Furthermore, we note that reduction and alkylation are important steps in protein corona sample processing and as expected, omitting these steps reduces the number of total quantified peptides by around 20%. These findings underscore the need for standardized procedures in protein corona analysis, which is vital for advancing clinical applications of nanoscale biotechnologies.

Pre-analytical processing of plasma and serum samples for combined proteome and metabolome analysis

Metabolomic and proteomic analyses of human plasma and serum samples harbor the power to advance our understanding of disease biology. Pre-analytical factors may contribute to variability and bias in the detection of analytes, especially when multiple labs are involved, caused by sample handling, processing time, and differing operating procedures. To better understand the impact of pre-analytical factors that are relevant to implementing a unified proteomic and metabolomic approach in a clinical setting, we assessed the influence of temperature, sitting times, and centrifugation speed on the plasma and serum metabolomes and proteomes from six healthy volunteers. We used targeted metabolic profiling (497 metabolites) and data-independent acquisition (DIA) proteomics (572 proteins) on the same samples generated with well-defined pre-analytical conditions to evaluate criteria for pre-analytical SOPs for plasma and serum samples. Time and temperature showed the strongest influence on the integrity of plasma and serum proteome and metabolome. While rapid handling and low temperatures (4°C) are imperative for metabolic profiling, the analyzed proteomics data set showed variability when exposed to temperatures of 4°C for more than 2 h, highlighting the need for compromises in a combined analysis. We formalized a quality control scoring system to objectively rate sample stability and tested this score using external data sets from other pre-analytical studies. Stringent and harmonized standard operating procedures (SOPs) are required for pre-analytical sample handling when combining proteomics and metabolomics of clinical samples to yield robust and interpretable data on a longitudinal scale and across different clinics. To ensure an adequate level of practicability in a clinical routine for metabolomics and proteomics studies, we suggest keeping blood samples up to 2 h on ice (4°C) prior to snap-freezing as a compromise between stability and operability. Finally, we provide the methodology as an open-source R package allowing the systematic scoring of proteomics and metabolomics data sets to assess the stability of plasma and serum samples.

Measurements of heterogeneity in proteomics analysis of the nanoparticle protein corona across core facilities

Robust characterization of the protein corona-the layer of proteins that spontaneously forms on the surface of nanoparticles immersed in biological fluids-is vital for prediction of the safety, biodistribution, and diagnostic/therapeutic efficacy of nanomedicines. Protein corona identity and abundance characterization is entirely dependent on liquid chromatography coupled to mass spectroscopy (LC-MS/MS), though the variability of this technique for the purpose of protein corona characterization remains poorly understood. Here we investigate the variability of LC-MS/MS workflows in analysis of identical aliquots of protein coronas by sending them to different proteomics core-facilities and analyzing the retrieved datasets. While the shared data between the cores correlate well, there is considerable heterogeneity in the data retrieved from different cores. Specifically, out of 4022 identified unique proteins, only 73 (1.8%) are shared across the core facilities providing semiquantitative analysis. These findings suggest that protein corona datasets cannot be easily compared across independent studies and more broadly compromise the interpretation of protein corona research, with implications in biomarker discovery as well as the safety and efficacy of our nanoscale biotechnologies.

Tracking the Stability of Clinically Relevant Blood Plasma Proteins with Delta-S-Cys-Albumin-A Dilute-and-Shoot LC/MS-Based Marker of Specimen Exposure to Thawed Conditions

Biomolecular integrity can be compromised when blood plasma/serum (P/S) specimens are improperly handled. Compromised analytes can subsequently produce erroneous results-without any indication of having done so. We recently introduced an LC/MS-based marker of P/S exposure to thawed conditions called ΔS-Cys-Albumin which, aided by an established rate law, quantitatively tracks exposure of P/S to temperatures greater than their freezing point of -30 °C. The purposes of this study were to (1) evaluate ΔS-Cys-Albumin baseline values in gastrointestinal cancer patients and cancer-free control donors, (2) empirically assess the kinetic profiles of ΔS-Cys-Albumin at 23 °C, 4 °C, and -20 °C, and (3) empirically link ΔS-Cys-Albumin to the stability of clinically relevant proteins. ΔS-Cys-Albumin was measured at ≥ 9 different time points per exposure temperature in serum and K₂EDTA plasma samples from 24 separate donors in aliquots kept separately at 23 °C, 4 °C, and -20 °C. Twenty-one clinically relevant plasma proteins were measured at four time points per temperature via a multiplexed immunoassay on the Luminex platform. Protein stability was assessed by mixed effects models. Coordinated shifts in stability between ΔS-Cys-Albumin and the unstable proteins were documented by repeated measures and Pearson correlations. Plasma ΔS-Cys-Albumin dropped from approximately 20% to under 5% within 96 h at 23 °C, 28 days at 4 °C, and 65 days at -20 °C. On average, 22% of the 21 proteins significantly changed in apparent concentration at each exposure temperature (p < 0.0008 with >10% shift). A linear inverse relationship was found between the percentage of proteins destabilized and ΔS-Cys-Albumin (r = -0.61; p < 0.0001)-regardless of the specific time/temperature of exposure. ΔS-Cys-Albumin tracks cumulative thawed-state exposure. These results now enable ΔS-Cys-Albumin to approximate the percentage of clinically relevant proteins that have been compromised by incidental plasma exposure to thawed-state conditions.

Effects of ex vivo blood anticoagulation and preanalytical processing time on the proteome content of platelets

BACKGROUND

Ex vivo assays of platelet function critically inform mechanistic and clinical hematology studies, where effects of divergent blood processing methods on platelet composition are apparent, but unspecified.

OBJECTIVE

Here, we evaluate how different blood anticoagulation options and processing times affect platelet function and protein content ex vivo.

METHODS

Parallel blood samples were collected from healthy human donors into sodium citrate, acid citrate dextrose, EDTA or heparin, and processed over an extended time course for functional and biochemical experiments, including platelet proteome quantification with multiplexed tandem mass tag (TMT) labeling and triple quadrupole mass spectrometry (MS).

RESULTS

Each anticoagulant had time-dependent effects on platelet function in whole blood. For instance, heparin enhanced platelet agonist reactivity, platelet-monocyte aggregate formation and platelet extracellular vesicle release, while EDTA increased platelet α-granule secretion. Following platelet isolation, TMT-MS quantified 3357 proteins amongst all prepared platelet samples. Altogether, >400 proteins were differentially abundant in platelets isolated from blood processed at 24 h versus 1 h post-phlebotomy, including proteins pertinent to membrane trafficking and exocytosis. Anticoagulant-specific effects on platelet proteomes included increased complement system and decreased α-granule proteins in platelets from EDTA-anticoagulated blood. Platelets prepared from heparinized blood had higher levels of histone and neutrophil-associated proteins in a manner related to neutrophil extracellular trap (NET) formation and platelet:NET interactions in whole blood ex vivo.

CONCLUSION

Our results demonstrate that different anticoagulants routinely used for blood collection have varying effects on platelets ex vivo, where methodology-associated alterations in platelet proteome may influence mechanistic, translational and biomarker studies.

Introduction of BD Vacutainer® Barricor™ tubes in clinical biobanking and application of amino acid and cytokine quality indicators to Barricor plasma

OBJECTIVES

The use of BD Vacutainer® Barricor™ tubes (BAR) can reduce turnaround time (TAT) and improve separation of plasma from cellular components using a specific mechanical separator. Concentrations of amino acids (AAs) and cytokines, known to be labile during pre-analytical time delays, were compared in heparin (BAR, BD Heparin standard tube [PST]), EDTA and serum gel tubes (SER) to validate previously identified quality indicators (QIs) in BAR.

METHODS

Samples of healthy individuals (n=10) were collected in heparin, EDTA and SER tubes and exposed to varying pre- and post-centrifugation delays at room temperature (RT). Cytokines (interleukin [IL]-8, IL-16 and sCD40L) were analyzed by enzyme-linked immunosorbent assay (ELISA) and AAs were characterized by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS).

RESULTS

All QIs, AAs/AA ratio and cytokines increased during prolonged blood storage in heparin plasma (PST, BAR) and SER tubes. Comparison of 53 h/1 h pre-centrifugation delay resulted in an increase in taurine (Tau) and glutamic acid (Glu) concentrations by more than three times, soluble CD40L increased by 13.6, 9.2 and 4.3 fold in PST, BAR-CTRL and BAR-FAST, and IL-8 increased even more by 112.8 (PST), 266.1 (BAR-CTRL), 268.1 (BAR-FAST) and 70.0 (SER) fold, respectively. Overall, compared to prolonged blood storage, effects of post-centrifugation delays were less pronounced in all tested materials.

CONCLUSIONS

BAR tubes are compatible with the use of several established QIs and can therefore be used in clinical biobanking to reduce pre-analytical TAT without compromising QIs and thus pre-analytical sample quality analysis.

Proteins associated with future suicide attempts in bipolar disorder: A large-scale biomarker discovery study

Suicide is a major cause of death worldwide. Several biological systems have been implicated in suicidal behavior but studies of candidate biomarkers have failed to produce clinically relevant biomarkers for suicide prediction. The objective of the present study was to identify novel candidate biomarkers for suicidal behavior. We used a nested case-control study design where a large cohort of patients with bipolar disorder (N = 5 110) were followed up to 8 years after blood sampling. We included patients that attempted suicide during follow-up (N = 348) and matched bipolar disorder patients from the same cohort who did not attempt suicide during the study period (N = 348) and analyzed a total of 92 proteins with a neuro exploratory multiplex panel. Using a multivariate classification algorithm devised to minimize bias in variable selection, we identified a parsimonious set of proteins that best discriminated bipolar disorder patients with and without prospective suicide attempts. The algorithm selected 16 proteins for the minimal-optimal classification model, which outperformed 500 models with permuted outcome (p = 0.0004) but had low sensitivity (53%) and specificity (64%). The candidate proteins were then entered in separate logistic regression models to calculate protein-specific associations with prospective suicide attempts. In individual analyses, three of these proteins were significantly associated with prospective suicide attempt (SCGB1A1, ANXA10, and CETN2). Most of the candidate proteins are novel to suicide research.

Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients

BACKGROUND

AKI requiring dialysis (AKI-D) is associated with prolonged hospitalization, mortality, and progressive CKD among survivors. Previous studies have examined only select urine or serum biomarkers for predicting kidney recovery from AKI.

METHODS

Serum samples collected on day 8 of randomized RRT from 72 patients enrolled in the Veteran's Affairs/National Institutes of Health Acute Renal Failure Trial Network study were analyzed by the SOMAscan proteomic platform to profile 1305 proteins in each sample. Of these patients, 38 recovered kidney function and dialysis was discontinued, whereas another 34 patients remained on dialysis by day 28.

RESULTS

Differential serum levels of 119 proteins, with 53 higher and 66 lower, were detected in samples from patients who discontinued dialysis, compared with patients who remained on dialysis by day 28. Patients were classified into tertiles on the basis of SOMAscan protein measurements for the 25 proteins most differentially expressed. The association of serum levels of each protein with kidney recovery was further evaluated using logistic regression analysis. Higher serum levels of CXCL11, CXCL2/CXCL3, CD86, Wnt-7a, BTK, c-Myc, TIMP-3, CCL5, ghrelin, PDGF-C, survivin, CA2, IL-9, EGF, and neuregulin-1, and lower levels of soluble CXCL16, IL1RL1, stanniocalcin-1, IL-6, and FGF23 when classified in tertiles were significantly associated with better kidney recovery. This significant association persisted for each of these proteins after adjusting for potential confounding risk factors including age, sex, cardiovascular SOFA score, congestive heart failure, diabetes, modality of intensive dialysis treatment, cause of AKI, baseline serum creatinine, day 8 urine volume, and estimated 60-day mortality risk.

CONCLUSIONS

These results suggest concerted changes between survival-related proteins and immune-regulatory chemokines in regulating angiogenesis, endothelial and epithelial remodeling, and kidney cell regeneration, illustrating potential mechanisms of kidney recovery. Thus, this study identifies potential novel predictive biomarkers of kidney recovery in patients with AKI-D.

Impact of Storage Conditions on the Breast Milk Peptidome

Human donor milk (HDM) provides appropriate nutrition and offers protective functions in preterm infants. The aim of the study is to examine the impact of different storage conditions on the stability of the human breast milk peptidome. HDM was directly frozen at −80 °C or stored at −20 °C (120 h), 4 °C (6 h), or room temperature (RT for 6 or 24 h). The milk peptidome was profiled by mass spectrometry after peptide collection by ultrafiltration. Profiling of the peptidome covered 3587 peptides corresponding to 212 proteins. The variance of the peptidome increased with storage temperature and time and varied for different peptides. The highest impact was observed when samples were stored at RT. Smaller but significant effects were still observed in samples stored at 4 °C, while samples showed highest similarity to those immediately frozen at −80 °C when stored at −20 °C. Peptide structures after storage at RT for 24 h point to the increased activity of thrombin and other proteases cleaving proteins at lysine/arginine. The results point to an ongoing protein degradation/peptide production by milk-derived proteases. They underline the need for immediate freezing of HDM at −20 °C or −80 °C to prevent degradation of peptides and enable reproducible investigation of prospectively collected samples.

Genetics meets proteomics: perspectives for large population-based studies

Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.

Aptamers and Antisense Oligonucleotides for Diagnosis and Treatment of Hematological Diseases

Aptamers or chemical antibodies are single-stranded DNA or RNA oligonucleotides that bind proteins and small molecules with high affinity and specificity by recognizing tertiary or quaternary structures as antibodies. Aptamers can be easily produced in vitro through a process known as systemic evolution of ligands by exponential enrichment (SELEX) or a cell-based SELEX procedure. Aptamers and modified aptamers, such as slow, off-rate, modified aptamers (SOMAmers), can bind to target molecules with less polar and more hydrophobic interactions showing slower dissociation rates, higher stability, and resistance to nuclease degradation. Aptamers and SOMAmers are largely employed for multiplex high-throughput proteomics analysis with high reproducibility and reliability, for tumor cell detection by flow cytometry or microscopy for research and clinical purposes. In addition, aptamers are increasingly used for novel drug delivery systems specifically targeting tumor cells, and as new anticancer molecules. In this review, we summarize current preclinical and clinical applications of aptamers in malignant and non-malignant hematological diseases.

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

The proteomic analysis of human blood and blood-derived products (e.g., plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g., interindividual variability) and analysis of biospecimens (e.g., sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing, and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest while enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.