Relating Lipoprotein(a) Concentrations to Cardiovascular Event Risk After Acute Coronary Syndrome: A Comparison of 3 Tests.

BACKGROUND: Lipoprotein(a) is a risk factor for cardiovascular events and modifies the benefit of PCSK9 (proprotein convertase subtilisin/kexin type 9) inhibitors. Lipoprotein(a) concentration can be measured with immunoassays reporting mass or molar concentration or a reference measurement system using mass spectrometry. Whether the relationships between lipoprotein(a) concentrations and cardiovascular events in a high-risk cohort differ across lipoprotein(a) methods is unknown. We compared the prognostic and predictive value of these types of lipoprotein(a) tests for major adverse cardiovascular events (MACE). METHODS: The ODYSSEY OUTCOMES trial (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) compared the PCSK9 inhibitor alirocumab with placebo in patients with recent acute coronary syndrome. We compared risk of a MACE in the placebo group and MACE risk reduction with alirocumab according to baseline lipoprotein(a) concentration measured by Siemens N-latex nephelometric immunoassay (IA-mass; mg/dL), Roche Tina-Quant turbidimetric immunoassay (IA-molar; nmol/L), and a noncommercial mass spectrometry-based test (MS; nmol/L). Lipoprotein(a) values were transformed into percentiles for comparative modeling. Natural cubic splines estimated continuous relationships between baseline lipoprotein(a) and outcomes in each treatment group. Event rates were also determined across baseline lipoprotein(a) quartiles defined by each assay. RESULTS: Among 11 970 trial participants with results from all 3 tests, baseline median (Q1, Q3) lipoprotein(a) concentrations were 21.8 (6.9, 60.0) mg/dL, 45.0 (13.2, 153.8) nmol/L, and 42.2 (14.3, 143.1) nmol/L for IA-mass, IA-molar, and MS, respectively. The strongest correlation was between IA-molar and MS (r=0.990), with nominally weaker correlations between IA-mass and MS (r=0.967) and IA-mass and IA-molar (r=0.972). Relationships of lipoprotein(a) with MACE risk in the placebo group were nearly identical with each test, with estimated cumulative incidences differing by ≤0.4% across lipoprotein(a) percentiles, and all were incrementally prognostic after accounting for low-density lipoprotein cholesterol levels (all spline P≤0.0003). Predicted alirocumab treatment effects were also nearly identical for each of the 3 tests, with estimated treatment hazard ratios differing by ≤0.07 between tests across percentiles and nominally less relative risk reduction by alirocumab at lower percentiles for all 3 tests. Absolute risk reduction with alirocumab increased with increasing lipoprotein(a) measured by each test, with significant linear trends across quartiles. CONCLUSIONS: In patients with recent acute coronary syndrome, 3 lipoprotein(a) tests were similarly prognostic for MACE in the placebo group and predictive of MACE reductions with alirocumab at the cohort level. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01663402.

Closing the gaps in patient management of dyslipidemia: stepping into cardiovascular precision diagnostics with apolipoprotein profiling.

In persons with dyslipidemia, a high residual risk of cardiovascular disease remains despite lipid lowering therapy. Current cardiovascular risk prediction mainly focuses on low-density lipoprotein cholesterol (LDL-c) levels, neglecting other contributing risk factors. Moreover, the efficacy of LDL-c lowering by statins resulting in reduced cardiovascular risk is only partially effective. Secondly, from a metrological viewpoint LDL-c falls short as a reliable measurand. Both direct and calculated LDL-c tests produce inaccurate test results at the low end under aggressive lipid lowering therapy. As LDL-c tests underperform both clinically and metrologically, there is an urging need for molecularly defined biomarkers. Over the years, apolipoproteins have emerged as promising biomarkers in the context of cardiovascular disease as they are the functional workhorses in lipid metabolism. Among these, apolipoprotein B (ApoB), present on all atherogenic lipoprotein particles, has demonstrated to clinically outperform LDL-c. Other apolipoproteins, such as Apo(a) - the characteristic apolipoprotein of the emerging risk factor lipoprotein(a) -, and ApoC-III - an inhibitor of triglyceride-rich lipoprotein clearance -, have attracted attention as well. To support personalized medicine, we need to move to molecularly defined risk markers, like the apolipoproteins. Molecularly defined diagnosis and molecularly targeted therapy require molecularly measured biomarkers. This review provides a summary of the scientific validity and (patho)physiological role of nine serum apolipoproteins, Apo(a), ApoB, ApoC-I, ApoC-II, ApoC-III, ApoE and its phenotypes, ApoA-I, ApoA-II, and ApoA-IV, in lipid metabolism, their association with cardiovascular disease, and their potential as cardiovascular risk markers when measured in a multiplex apolipoprotein panel.

An LC-MS-based designated comparison method with similar performance to the Lp(a) reference measurement procedure to guide molar Lp(a) standardization.

BACKGROUND: The 2022 consensus statement of the European Atherosclerosis Society (EAS) on lipoprotein(a) (Lp(a)) recognizes the role of Lp(a) as a relevant genetically determined risk factor and recommends its measurement at least once in an individual's lifetime. It also strongly urges that Lp(a) test results are expressed as apolipoprotein (a) (apo(a)) amount of substance in molar units and no longer in confounded Lp(a) mass units (mg/dL or mg/L). Therefore, IVD manufacturers should transition to molar units. A prerequisite for this transition is the availability of an Lp(a) Reference Measurement Procedure (RMP) that allows unequivocal molecular detection and quantification of apo(a) in Lp(a). To that end an ISO 17511:2020 compliant LC-MS based and IFCC-endorsed RMP has been established that targets proteotypic peptides of apolipoprotein(a) (apo(a)) in Lp(a). The RMP is laborious and requires highly skilled operators. To guide IVD-manufacturers of immunoassay-based Lp(a) test kits in the transition from mass to molar units, a Designated Comparison Method (DCM) has been developed and evaluated. METHODS: To assess whether the DCM provides equivalent results compared to the RMP, the procedural designs were compared and the analytical performance of DCM and RMP were first evaluated in a head-to-head comparison. Subsequently, apo(a) was quantified in 153 human clinical serum samples. Both DCM and RMP were calibrated using external native calibrators that produce results traceable to SRM2B. Measurement uncertainty (MU) was checked against predefined allowable MU. RESULTS: The major difference in the design of the DCM for apo(a) is the use of only one enzymatic digestion step. The analytical performance of the DCM and RMP for apo(a) is highly similar. In a direct method comparison, equivalent results were obtained with a median regression slope 0.997 of and a median bias of - 0.2 nmol/L (- 0.2%); the intermediate imprecision of the test results was within total allowable error (TEa) (CVa of 10.2% at 90 nmol/L). CONCLUSIONS: The semi-automated, higher throughput, LC-MS-based method for Lp(a) meets the predefined analytical performance specifications and allowable MU and is hence applicable as a higher order Designated Comparison Method, which is ideally suited to guide IVD manufacturers in the transition from Lp(a) mass to molar units.

Developing an SI-traceable Lp(a) reference measurement system: a pilgrimage to selective and accurate apo(a) quantification.

In the past decade a remarkable rebirth of serum/plasma lipoprotein(a) (Lp(a)) as an independent risk factor of cardiovascular disease (CVD) occurred. Updated evidence for a causal continuous association in different ethnic groups between Lp(a) concentrations and cardiovascular outcomes has been published in the latest European Atherosclerosis Society (EAS) Lp(a) consensus statement. Interest in measuring Lp(a) at least once in a person's lifetime moreover originates from the development of promising new Lp(a) lowering drugs. Accurate and clinically effective Lp(a) tests are of key importance for the timely detection of high-risk individuals and for future evaluation of the therapeutic effects of Lp(a) lowering medication. To this end, it is necessary to improve the performance and standardization of existing Lp(a) tests, as is also noted in the Lp(a) consensus statement. Consequently, a state-of-the-art internationally endorsed reference measurement system (RMS) must be in place that allows for performance evaluation of Lp(a) field tests in order to certify their validity and accuracy. An ELISA-based RMS from Northwest Lipid Research Laboratory (University of Washington, Seattle, USA) has been available since the 1990s. A next-generation apo(a)/Lp(a) RMS is now being developed by a working group from the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). The envisioned apo(a) RMS is based on the direct measurement of selected proteotypic fragments generated after proteolytic digestion using quantitative protein mass spectrometry (MS). The choice for an MS-based RMS enables selective measurement of the proteotypic peptides and is by design apo(a) isoform insensitive. Clearly, the equimolar conversion of apo(a) into the surrogate peptide measurands is required to obtain accurate Lp(a) results. The completeness of proteolysis under reaction conditions from the candidate reference measurement procedure (RMP) has been demonstrated for the quantifying apo(a) peptides. Currently, the candidate apo(a) RMP is endorsed by the IFCC and recommendations for suitable secondary reference materials have been made in a recent commutability study paper. Ongoing efforts toward a complete apo(a) RMS that is listed by the Joint Committee on Traceability in Laboratory Medicine (JCTLM) are focused on the peptide-based calibration and the establishment of a network of calibration laboratories running the apo(a) RMS in a harmonized way. Once completed, it will be the holy grail for evaluation and certification of Lp(a) field methods.

Urinary Kidney Injury Biomarkers Are Associated with Ischemia-Reperfusion Injury Severity in Kidney Allograft Recipients.

BACKGROUND: We explored the potential of emerging and conventional urinary kidney injury biomarkers in recipients of living donor (LD) or donation after circulatory death (DCD) kidney transplantation, patients with chronic kidney disease (CKD), and individuals from the general population. METHODS: Urine samples from kidney allograft recipients with mild (LD; n = 199) or severe (DCD; n = 71) ischemia-reperfusion injury (IRI) were analyzed for neutrophil gelatinase-associated lipocalin (NGAL), insulin-like growth factor-binding protein 7 (IGFBP7), tissue inhibitor of metalloproteinases 2 (TIMP2), kidney injury molecule-1 (KIM-1), chemokine C-X-C motif (CXCL9), solute carrier family 22 member 2 (SLC22A2), nephrin, and uromodulin (UMOD) by quantitative multiplex LC-MS/MS analysis. The fold-change in biomarker levels was determined in mild and severe IRI and in patients with CKD stage 1-2 (n = 127) or stage ≥3 (n = 132) in comparison to the general population (n = 1438). Relationships between the biomarkers and total protein, ß2-microglobulin (B2M), creatinine, and osmolality were assessed. RESULTS: NGAL, IGFBP7, TIMP2, KIM-1, CXCL9, and UMOD were quantifiable, whereas nephrin and SLC22A2 were below the limit of detection. Kidney injury biomarkers were increased up to 6.2-fold in allograft recipients with mild IRI and 8.3-fold in recipients with severe IRI, compared to the reference population, with the strongest response observed for NGAL and B2M. In CKD stage 1-2, B2M, NGAL, IGFBP7, TIMP2, KIM-1, UMOD, and CXCL9 were not altered, but in individuals with CKD stage ≥3, B2M, NGAL, and KIM-1 were increased up to 1.3-fold. IGFBP7, TIMP2, NGAL, and CXCL9 were strongly correlated (all r ≥ 0.8); correlations with B2M and TP were smaller (all r ≤ 0.6). CONCLUSIONS: IRI, but not stable CKD, was associated with increased urinary levels of kidney injury biomarkers determined by LC-MS/MS. Absolute and multiplexed protein quantitation by LC-MS/MS is an effective strategy for biomarker panel evaluation for translation toward the clinical laboratory.

Development of an LC-MRM-MS-Based Candidate Reference Measurement Procedure for Standardization of Serum Apolipoprotein (a) Tests.

BACKGROUND: Medical results generated by European CE Marking for In Vitro Diagnostic or in-house tests should be traceable to higher order reference measurement systems (RMS), such as International Federation of Clinical Chemistry and Laboratory Medicine (IFCC)-endorsed reference measurement procedures (RMPs) and reference materials. Currently, serum apolipoprotein (a) [apo(a)] is recognized as a novel risk factor for cardiovascular risk assessment and patient management. The former RMS for serum apo(a) is no longer available; consequently, an International System of Units (SI)-traceable, ideally multiplexed, and sustainable RMS for apo(a) is needed. METHODS: A mass spectrometry (MS)-based candidate RMP (cRMP) for apo(a) was developed using quantitative bottom-up proteomics targeting 3 proteotypic peptides. The method was provisionally validated according to ISO 15193 using a single human serum based calibrator traceable to the former WHO-IFCC RMS. RESULTS: The quantitation of serum apo(a) was by design independent of its size polymorphism, was linear from 3.8 to 456 nmol/L, and had a lower limit of quantitation for apo(a) of 3.8 nmol/L using peptide LFLEPTQADIALLK. Interpeptide agreement showed Pearson Rs of 0.987 and 0.984 for peptides GISSTVTGR and TPENYPNAGLTR, and method comparison indicated good correspondence (slopes 0.977, 1.033, and 1.085 for LFLEPTQADIALLK, GISSTVTGR, and TPENYPNAGLTR). Average within-laboratory imprecision of the cRMP was 8.9%, 11.9%, and 12.8% for the 3 peptides. CONCLUSIONS: A robust, antibody-independent, MS-based cRMP was developed as higher order RMP and an essential part of the apo(a) traceability chain and future RMS. The cRMP fulfils predefined analytical performance specifications, making it a promising RMP candidate in an SI-traceable MS-based RMS for apo(a).

Commutability Assessment of Candidate Reference Materials for Lipoprotein(a) by Comparison of a MS-based Candidate Reference Measurement Procedure with Immunoassays.

BACKGROUND: Elevated concentrations of lipoprotein(a) [Lp(a)] are directly related to an increased risk of cardiovascular diseases, making it a relevant biomarker for clinical risk assessment. However, the lack of global standardization of current Lp(a) measurement procedures (MPs) leads to inconsistent patient care. The International Federation for Clinical Chemistry and Laboratory Medicine working group on quantitating apolipoproteins by mass spectrometry (MS) aims to develop a next-generation SI (International system of units)-traceable reference measurement system consisting of a MS-based, peptide-calibrated reference measurement procedure (RMP) and secondary serum-based reference materials (RMs) certified for their apolipoprotein(a) [apo(a)] content. To reach measurement standardization through this new measurement system, 2 essential requirements need to be fulfilled: a sufficient correlation among the MPs and appropriate commutability of future serum-based RMs. METHODS: The correlation among the candidate RMP (cRMP) and immunoassay-based MPs was assessed by measuring a panel of 39 clinical samples (CS). In addition, the commutability of 14 different candidate RMs was investigated. RESULTS: Results of the immunoassay-based MPs and the cRMPs demonstrated good linear correlations for the CS but some significant sample-specific differences were also observed. The results of the commutability study show that RMs based on unspiked human serum pools can be commutable with CS, whereas human pools spiked with recombinant apo(a) show different behavior compared to CS. CONCLUSIONS: The results of this study show that unspiked human serum pools are the preferred candidate secondary RMs in the future SI-traceable Lp(a) Reference Measurement System.

Quantitative protein mass-spectrometry requires a standardized pre-analytical phase.

OBJECTIVES: Quantitative protein mass-spectrometry (QPMS) in blood depends on tryptic digestion of proteins and subsequent measurement of representing peptides. Whether serum and plasma can be used interchangeably and whether in-vitro anticoagulants affect the recovery is unknown. In our laboratory serum samples are the preferred matrix for QPMS measurement of multiple apolipoproteins. In this study, we investigated the effect of different matrices on apolipoprotein quantification by mass spectrometry. METHODS: Blood samples were collected from 44 healthy donors in Beckton Dickinson blood tubes simultaneously for serum (with/without gel) and plasma (heparin, citrate or EDTA). Nine apolipoproteins were quantified according to standard operating procedure using value-assigned native serum calibrators for quantitation. Tryptic digestion kinetics were investigated in the different matrices by following formation of peptides for each apolipoprotein in time, up to 22 h. RESULTS: In citrate plasma recovery of apolipoproteins showed an overall reduction with a bias of -14.6%. For heparin plasma only -0.3% bias was found compared to serum, whereas for EDTA-plasma reduction was more pronounced (-5.3% bias) and variable with >14% reduction for peptides of apoA-I, A-II and C-III. Digestion kinetics revealed that especially slow forming peptides showed reduced formation in EDTA-plasma. CONCLUSIONS: Plasma anticoagulants affect QPMS test results. Heparin plasma showed comparable results to serum. Reduced concentrations in citrate plasma can be explained by dilution, whereas reduced recovery in EDTA-plasma is dependent on altered proteolytic digestion efficiency. The results highlight the importance of a standardized pre-analytical phase for accurate QPMS applications in clinical chemistry.

Development and Provisional Validation of a Multiplex LC-MRM-MS Test for Timely Kidney Injury Detection in Urine.

Kidney injury is a complication frequently encountered in hospitalized patients. Early detection of kidney injury prior to loss of renal function is an unmet clinical need that should be targeted by a protein-based biomarker panel. In this study, we aim to quantitate urinary kidney injury biomarkers at the picomolar to nanomolar level by liquid chromatography coupled to tandem mass spectrometry in multiple reaction monitoring mode (LC-MRM-MS). Proteins were immunocaptured from urinary samples, denatured, reduced, alkylated, and digested into peptides before LC-MRM-MS analysis. Stable-isotope-labeled peptides functioned as internal standards, and biomarker concentrations were attained by an external calibration strategy. The method was evaluated for selectivity, carryover, matrix effects, linearity, and imprecision. The LC-MRM-MS method enabled the quantitation of KIM-1, NGAL, TIMP2, IGFBP7, CXCL9, nephrin, and SLC22A2 and the detection of TGF-ß1, cubilin, and uromodulin. Two to three peptides were included per protein, and three transitions were monitored per peptide for analytical selectivity. The analytical carryover was <1%, and minimal urine matrix effects were observed by combining immunocapture and targeted LC-MRM-MS analysis. The average total CV of all quantifier peptides was 26%. The linear measurement range was determined per measurand and found to be 0.05-30 nmol/L. The targeted MS-based method enables the multiplex quantitation of low-abundance urinary kidney injury biomarkers for future clinical evaluation.

Glycan biomarkers of autoimmunity and bile acid-associated alterations of the human glycome: Primary biliary cirrhosis and primary sclerosing cholangitis-specific glycans.

We have recently introduced multiple reaction monitoring (MRM) mass spectrometry as a novel tool for glycan biomarker research and discovery. Herein, we employ this technique to characterize the site-specific glycan alterations associated with primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). Glycopeptides associated with disease severity were also identified. Multinomial regression modelling was employed to construct and validate multi-analyte diagnostic models capable of accurately distinguishing PBC, PSC, and healthy controls from one another (AUC = 0.93 ± 0.03). Finally, to investigate how disease-relevant environmental factors can influence glycosylation, we characterized the ability of bile acids known to be differentially expressed in PBC to alter glycosylation. We hypothesize that this could be a mechanism by which altered self-antigens are generated and become targets for immune attack. This work demonstrates the utility of the MRM method to identify diagnostic site-specific glycan classifiers capable of distinguishing even related autoimmune diseases from one another.

Towards an SI-Traceable Reference Measurement System for Seven Serum Apolipoproteins Using Bottom-Up Quantitative Proteomics: Conceptual Approach Enabled by Cross-Disciplinary/Cross-Sector Collaboration.

Current dyslipidemia management in patients with atherosclerotic cardiovascular disease (ASCVD) is based on traditional serum lipids. Yet, there is some indication from basic research that serum apolipoproteins A-I, (a), B, C-I, C-II, C-III, and E may give better pathophysiological insight into the root causes of dyslipidemia. To facilitate the future adoption of clinical serum apolipoprotein (apo) profiling for precision medicine, strategies for accurate testing should be developed in advance. Recent discoveries in basic science and translational medicine set the stage for the IFCC Working Group on Apolipoproteins by Mass Spectrometry. Main drivers were the convergence of unmet clinical needs in cardiovascular disease (CVD) patients with enabling technology and metrology. First, the residual cardiovascular risk after accounting for established risk factors demonstrates that the current lipid panel is too limited to capture the full complexity of lipid metabolism in patients. Second, there is a need for accurate test results in highly polymorphic and atherogenic apolipoproteins such as apo(a). Third, sufficient robustness of mass spectrometry technology allows reproducible protein quantification at the molecular level. Fourth, several calibration hierarchies in the revised ISO 17511:2020 guideline facilitate metrological traceability of test results, the highest achievable standard being traceability to SI. This article outlines the conceptual approach aimed at achieving a novel, multiplexed Reference Measurement System (RMS) for seven apolipoproteins based on isotope dilution mass spectrometry and peptide-based calibration. This RMS should enable standardization of existing and emerging apolipoprotein assays to SI, within allowable limits of measurement uncertainty, through a sustainable network of Reference Laboratories.

HILIC-MRM-MS for Linkage-Specific Separation of Sialylated Glycopeptides to Quantify Prostate-Specific Antigen Proteoforms.

Elevated serum prostate-specific antigen (PSA) levels in body fluids may indicate prostate cancer (PCa), but it is noted that the clinical performance is rather poor. Specificity and sensitivity values of 20 and 94% at a cutoff value of 4.1 ng/mL, respectively, result in overdiagnosis and unnecessary interventions. Previous exploratory studies have indicated that the glycosylation of PSA potentially leads to improved PCa diagnosis based on qualitative analyses. However, the applied methods are not suited for a quantitative evaluation or implementation in a medical laboratory. Therefore, in this proof-of-principle study, we have evaluated the use of hydrophilic interaction liquid chromatography (HILIC) in combination with targeted quantitative mass spectrometry for the sialic acid linkage-specific analysis of PSA glyco-proteoforms based on either trypsin or ArgC peptides. The efficiency of PSA proteolysis was optimized as well as the glycopeptide separation conditions (buffer type, strength, and pH). The HILIC-based analysis of PSA glyco-proteoforms presented here has the potential for the clinical validation of patient cohorts. The method shows the feasibility of the use of a HILIC stationary phase for the separation of isomeric glycopeptides to detect specific glyco-proteoforms. This is the first step toward the development and evaluation of PSA glyco-proteoforms for use in a clinical chemistry setting aiming for improved PCa diagnosis or screening.

Mass Spectrometry Approaches to Glycomic and Glycoproteomic Analyses.

Glycomic and glycoproteomic analyses involve the characterization of oligosaccharides (glycans) conjugated to proteins. Glycans are produced through a complicated nontemplate driven process involving the competition of enzymes that extend the nascent chain. The large diversity of structures, the variations in polarity of the individual saccharide residues, and the poor ionization efficiencies of glycans all conspire to make the analysis arguably much more difficult than any other biopolymer. Furthermore, the large number of glycoforms associated with a specific protein site makes it more difficult to characterize than any post-translational modification. Nonetheless, there have been significant progress, and advanced separation and mass spectrometry methods have been at its center and the main reason for the progress. While glycomic and glycoproteomic analyses are still typically available only through highly specialized laboratories, new software and workflow is making it more accessible. This review focuses on the role of mass spectrometry and separation methods in advancing glycomic and glycoproteomic analyses. It describes the current state of the field and progress toward making it more available to the larger scientific community.

Effects of imputation on correlation: implications for analysis of mass spectrometry data from multiple biological matrices.

With expanded access to, and decreased costs of, mass spectrometry, investigators are collecting and analyzing multiple biological matrices from the same subject such as serum, plasma, tissue and urine to enhance biomarker discoveries, understanding of disease processes and identification of therapeutic targets. Commonly, each biological matrix is analyzed separately, but multivariate methods such as MANOVAs that combine information from multiple biological matrices are potentially more powerful. However, mass spectrometric data typically contain large amounts of missing values, and imputation is often used to create complete data sets for analysis. The effects of imputation on multiple biological matrix analyses have not been studied. We investigated the effects of seven imputation methods (half minimum substitution, mean substitution, k-nearest neighbors, local least squares regression, Bayesian principal components analysis, singular value decomposition and random forest), on the within-subject correlation of compounds between biological matrices and its consequences on MANOVA results. Through analysis of three real omics data sets and simulation studies, we found the amount of missing data and imputation method to substantially change the between-matrix correlation structure. The magnitude of the correlations was generally reduced in imputed data sets, and this effect increased with the amount of missing data. Significant results from MANOVA testing also were substantially affected. In particular, the number of false positives increased with the level of missing data for all imputation methods. No one imputation method was universally the best, but the simple substitution methods (Half Minimum and Mean) consistently performed poorly.

Human Plasma N-glycosylation as Analyzed by Matrix-Assisted Laser Desorption/Ionization-Fourier Transform Ion Cyclotron Resonance-MS Associates with Markers of Inflammation and Metabolic Health.

Glycosylation is an abundant co- and post-translational protein modification of importance to protein processing and activity. Although not template-defined, glycosylation does reflect the biological state of an organism and is a high-potential biomarker for disease and patient stratification. However, to interpret a complex but informative sample like the total plasma N-glycome, it is important to establish its baseline association with plasma protein levels and systemic processes. Thus far, large-scale studies (n >200) of the total plasma N-glycome have been performed with methods of chromatographic and electrophoretic separation, which, although being informative, are limited in resolving the structural complexity of plasma N-glycans. MS has the opportunity to contribute additional information on, among others, antennarity, sialylation, and the identity of high-mannose type species.Here, we have used matrix-assisted laser desorption/ionization (MALDI)-Fourier transform ion cyclotron resonance (FTICR)-MS to study the total plasma N-glycome of 2144 healthy middle-aged individuals from the Leiden Longevity Study, to allow association analysis with markers of metabolic health and inflammation. To achieve this, N-glycans were enzymatically released from their protein backbones, labeled at the reducing end with 2-aminobenzoic acid, and following purification analyzed by negative ion mode intermediate pressure MALDI-FTICR-MS. In doing so, we achieved the relative quantification of 61 glycan compositions, ranging from Hex4HexNAc2 to Hex7HexNAc6dHex1Neu5Ac4, as well as that of 39 glycosylation traits derived thereof. Next to confirming known associations of glycosylation with age and sex by MALDI-FTICR-MS, we report novel associations with C-reactive protein (CRP), interleukin 6 (IL-6), body mass index (BMI), leptin, adiponectin, HDL cholesterol, triglycerides (TG), insulin, gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT), and smoking. Overall, the bisection, galactosylation, and sialylation of diantennary species, the sialylation of tetraantennary species, and the size of high-mannose species proved to be important plasma characteristics associated with inflammation and metabolic health.

Targeted On-line SPE-LC-MS/MS Assay for the Quantitation of 12 Apolipoproteins from Human Blood.

Laborious sample pretreatment of biological samples represents the most limiting factor for the translation of targeted proteomics assays from research to clinical routine. An optimized method for the simultaneous quantitation of 12 major apolipoproteins (apos) combining on-line SPE and fast LC-MS/MS analysis in 6.5 min total run time was developed, reducing the manual sample pretreatment time of 3 µL serum or plasma by 60%. Within-run and between-day imprecisions below 10 and 15% (n = 10) and high recovery rates (94-131%) were obtained applying the high-throughput setup. High-quality porcine trypsin was used, which outperformed cost-effective bovine trypsin regarding digestion efficiency. Comparisons with immunoassays and another LC-MS/MS assay demonstrated good correlation (Pearson's R: 0.81-0.98). Further, requirements on sample quality concerning sampling, processing, and long-term storage up to 1 year were investigated revealing significant influences of the applied sampling material and coagulant on quantitation results. Apo profiles of 1339 subjects of the LIFE-Adult-Study were associated with lifestyle and physiological parameters as well as establish parameters of lipid metabolism (e.g., triglycerides, cholesterol). Besides gender effects, most significant impact was seen regarding lipid-lowering medication. In conclusion, this novel highly standardized, high-throughput targeted proteomics assay utilizes a fast, simultaneous analysis of 12 apos from least sample amounts.

Multiple Reaction Monitoring for the Quantitation of Serum Protein Glycosylation Profiles: Application to Ovarian Cancer.

Protein glycosylation fingerprints are widely recognized as potential markers for disease states, and indeed differential glycosylation has been identified in multiple types of autoimmune diseases and several types of cancer. However, releasing the glycans leave the glycoproteins unknown; therefore, there exists a need for high-throughput methods that allow quantification of site- and protein-specific glycosylation patterns from complex biological mixtures. In this study, a targeted multiple reaction monitoring (MRM)-based method for the protein- and site-specific quantitation involving serum proteins immunoglobulins A, G and M, alpha-1-antitrypsin, transferrin, alpha-2-macroglobulin, haptoglobin, alpha-1-acid glycoprotein and complement C3 was developed. The method is based on tryptic digestion of serum glycoproteins, followed by immediate reverse phase UPLC-QQQ-MS analysis of glycopeptides. To quantitate protein glycosylation independent of the protein serum concentration, a nonglycosylated peptide was also monitored. Using this strategy, 178 glycopeptides and 18 peptides from serum glycoproteins are analyzed with good repeatability (interday CVs of 3.65-21-92%) in a single 17 min run. To assess the potential of the method, protein glycosylation was analyzed in serum samples from ovarian cancer patients and controls. A training set consisting of 40 cases and 40 controls was analyzed, and differential analyses were performed to identify aberrant glycopeptide levels. All findings were validated in an independent test set (n = 44 cases and n = 44 controls). In addition to the differential glycosylation on the immunoglobulins, which was reported previously, aberrant glycosylation was also observed on each of the glycoproteins, which could be corroborated in the test set. This report shows the development of a method for targeted protein- and site-specific glycosylation analysis and the potential of such methods in biomarker development.

Multivariate two-part statistics for analysis of correlated mass spectrometry data from multiple biological specimens.

MOTIVATION: High through-put mass spectrometry (MS) is now being used to profile small molecular compounds across multiple biological sample types from the same subjects with the goal of leveraging information across biospecimens. Multivariate statistical methods that combine information from all biospecimens could be more powerful than the usual univariate analyses. However, missing values are common in MS data and imputation can impact between-biospecimen correlation and multivariate analysis results. RESULTS: We propose two multivariate two-part statistics that accommodate missing values and combine data from all biospecimens to identify differentially regulated compounds. Statistical significance is determined using a multivariate permutation null distribution. Relative to univariate tests, the multivariate procedures detected more significant compounds in three biological datasets. In a simulation study, we showed that multi-biospecimen testing procedures were more powerful than single-biospecimen methods when compounds are differentially regulated in multiple biospecimens but univariate methods can be more powerful if compounds are differentially regulated in only one biospecimen. AVAILABILITY AND IMPLEMENTATION: We provide R functions to implement and illustrate our method as supplementary information CONTACT: sltaylor@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Serum glycosylation characterization of osteonecrosis of the femoral head by mass spectrometry.

Osteonecrosis of the femoral head is a recalcitrant and paralyzing disease often discovered in the end stage at the time of diagnosis, which is often performed by physical examination and diagnostic imaging. Osteonecrosis of the femoral head is typically caused by trauma or long-term steroid use. There are over 30 million patients in the US taking steroids, and roughly 40% will develop osteonecrosis of the femoral head. However, the exact pathophysiological process is not well understood. This study aims to examine the alteration in serum glycosylation of osteonecrosis of the femoral head using the state-of-the-art analytical tools to provide more chemical data for pathophysiology research and possibly biomarker discovery. A training set containing 27 serum samples from steroid-induced osteonecrosis of the femoral head patients and 25 from gender- and age-matched controls was collected and analyzed. Glycosylation of whole serum and site-specific glycosylation of immunoglobulins are characterized using electrospray ionization-Q-time of flight and electrospray ionization-Triple-Quadruple via multiple reaction monitoring, respectively. The whole serum glycosylation analysis yielded 14 N-glycan compositions and multiple reaction monitoring yielded eight glycopeptides that were altered between cases and controls with statistical significance. The increase of nonsialylated, nonfucosylated N-glycans and decrease of fucosylated N-glycans are associated with the development of osteonecrosis of the femoral head. Glycosylation is a posttranslational protein modification and is apparently affected by osteonecrosis of the femoral head. Future studies with a larger cohort and patients from earlier stage will be performed to assess these potential markers' value in disease onset.

Protein-Specific Differential Glycosylation of Immunoglobulins in Serum of Ovarian Cancer Patients.

Previous studies indicated that glycans in serum may serve as biomarkers for diagnosis of ovarian cancer; however, it was unclear to which proteins these glycans belong. We hypothesize that protein-specific glycosylation profiles of the glycans may be more informative of ovarian cancer and can provide insight into biological mechanisms underlying glycan aberration in serum of diseased individuals. Serum samples from women diagnosed with epithelial ovarian cancer (EOC, n = 84) and matched healthy controls (n = 84) were obtained from the Gynecologic Oncology Group. Immunoglobulin (IgG, IgA, and IgM) concentrations and glycosylation profiles were quantified using multiple reaction monitoring mass spectrometry. Differential and classification analyses were performed to identify aberrant protein-specific glycopeptides using a training set. All findings were validated in an independent test set. Multiple glycopeptides from immunoglubins IgA, IgG, and IgM were found to be differentially expressed in serum of EOC patients compared with controls. The protein-specific glycosylation profiles showed their potential in the diagnosis of EOC. In particular, IgG-specific glycosylation profiles are the most powerful in discriminating between EOC case and controls. Additional studies of protein- and site-specific glycosylation profiles of immunoglobulins and other proteins will allow further elaboration on the characteristics of biological functionality and causality of the differential glycosylation in ovarian cancer and thus ultimately lead to increased sensitivity and specificity of diagnosis.