Linagliptin treatment is associated with altered cobalamin (VitB12) homeostasis in mice and humans.

Linagliptin is a dipeptidyl peptidase-4 (DPP-4) inhibitor used for the treatment of type 2 diabetes, with additional beneficial effects for the kidney. Treatment of mice with linagliptin revealed increased storage of cobalamin (Cbl, Vitamin B12) in organs if a standard Cbl diet (30 µg Cbl/kg chow) is given. In order to translate these findings to humans, we determined methylmalonic acid (MMA), a surrogate marker of functional Cbl homeostasis, in human plasma and urine samples (n = 1092) from baseline and end of trial (6 months after baseline) of the previously completed MARLINA-T2D clinical trial. We found that individuals with medium Cbl levels (MMA between 50 and 270 nmol/L for plasma, 0.4 and 3.5 µmol/mmol creatinine for urine, at baseline and end of trial) exhibited higher MMA values at the end of study in placebo compared with linagliptin. Linagliptin might inhibit the N-terminal degradation of the transcobalamin receptor CD320, which is necessary for uptake of Cbl into endothelial cells. Because we demonstrate that linagliptin led to increased organ levels of Cbl in mice, sustained constant medium MMA levels in humans, and inhibited CD320 processing by DPP-4 in-vitro, we speculate that linagliptin promotes intra-cellular uptake of Cbl by prolonging half-life of CD320.

Characterization of combined linagliptin and Y2R agonist treatment in diet-induced obese mice.

Dipeptidyl peptidase IV (DPP-IV) inhibitors improve glycemic control by prolonging the action of glucagon-like peptide-1 (GLP-1). In contrast to GLP-1 analogues, DPP-IV inhibitors are weight-neutral. DPP-IV cleavage of PYY and NPY gives rise to PYY3-36 and NPY3-36 which exert potent anorectic action by stimulating Y2 receptor (Y2R) function. This invites the possibility that DPP-IV inhibitors could be weight-neutral by preventing conversion of PYY/NPY to Y2R-selective peptide agonists. We therefore investigated whether co-administration of an Y2R-selective agonist could unmask potential weight lowering effects of the DDP-IV inhibitor linagliptin. Male diet-induced obese (DIO) mice received once daily subcutaneous treatment with linagliptin (3 mg/kg), a Y2R-selective PYY3-36 analogue (3 or 30 nmol/kg) or combination therapy for 14 days. While linagliptin promoted marginal weight loss without influencing food intake, the PYY3-36 analogue induced significant weight loss and transient suppression of food intake. Both compounds significantly improved oral glucose tolerance. Because combination treatment did not further improve weight loss and glucose tolerance in DIO mice, this suggests that potential negative modulatory effects of DPP-IV inhibitors on endogenous Y2R peptide agonist activity is likely insufficient to influence weight homeostasis. Weight-neutrality of DPP-IV inhibitors may therefore not be explained by counter-regulatory effects on PYY/NPY responses.

Urinary dipeptidyl peptidase-4 protein is increased by linagliptin and is a potential predictive marker of urine albumin-to-creatinine ratio reduction in patients with type 2 diabetes.

Results of a post hoc analysis of urinary dipeptidyl peptidase-4 (DPP-4) protein as a predictor of urine albumin-to-creatinine ratio (UACR) response to linagliptin treatment based on MARLINA-T2D trial data are described. MARLINA was a 24-week, phase 3b, multinational, placebo-controlled clinical trial, in which patients with type 2 diabetes (T2D), HbA1c 6.5%-10.0% and UACR 30-3000 mg/g (n = 360) were treated with linagliptin or placebo. After 24 weeks of treatment, linagliptin significantly inhibited urinary DPP-4 activity and increased urinary DPP-4 protein. Furthermore, medium urinary DPP-4 protein levels (between 5.5 and 7.5 natural logarithmic [ln] µg/g creatinine) at baseline allowed for prediction of improved UACR in linagliptin-treated individuals. In patients with lower or higher levels of urinary DPP-4 protein at baseline, no association between linagliptin treatment and improved UACR was present. This might suggest a varying degree of importance of DPP-4 as a pathophysiological factor in T2D-associated kidney disease. In summary, urinary DPP-4 might be a useful predictive biomarker for UACR improvement by linagliptin.

Mechanisms of GLP-1 receptor-independent renoprotective effects of the dipeptidyl peptidase type 4 inhibitor linagliptin in GLP-1 receptor knockout mice with 5/6 nephrectomy.

Dipeptidyl peptidase type 4 (DPP-4) inhibitors were reported to have beneficial effects in experimental models of chronic kidney disease. The underlying mechanisms are not completely understood. However, these effects could be mediated via the glucagon-like peptide-1 (GLP-1)/GLP-1 receptor (GLP1R) pathway. Here we investigated the renal effects of the DPP-4 inhibitor linagliptin in Glp1r-/- knock out and wild-type mice with 5/6 nephrectomy (5/6Nx). Mice were allocated to groups: sham+wild type+placebo; 5/6Nx+ wild type+placebo; 5/6Nx+wild type+linagliptin; sham+knock out+placebo; 5/6Nx+knock out+ placebo; 5/6Nx+knock out+linagliptin. 5/6Nx caused the development of renal interstitial fibrosis, significantly increased plasma cystatin C and creatinine levels and suppressed renal gelatinase/collagenase, matrix metalloproteinase-1 and -13 activities; effects counteracted by linagliptin treatment in wildtype and Glp1r-/- mice. Two hundred ninety-eight proteomics signals were differentially regulated in kidneys among the groups, with 150 signals specific to linagliptin treatment as shown by mass spectrometry. Treatment significantly upregulated three peptides derived from collagen alpha-1(I), thymosin ß4 and heterogeneous nuclear ribonucleoprotein A1 (HNRNPA1) and significantly downregulated one peptide derived from Y box binding protein-1 (YB-1). The proteomics results were further confirmed using western blot and immunofluorescence microscopy. Also, 5/6Nx led to significant up-regulation of renal transforming growth factor-ß1 and pSMAD3 expression in wild type mice and linagliptin significantly counteracted this up-regulation in wild type and Glp1r-/- mice. Thus, the renoprotective effects of linagliptin cannot solely be attributed to the GLP-1/GLP1R pathway, highlighting the importance of other signaling pathways (collagen I homeostasis, HNRNPA1, YB-1, thymosin ß4 and TGF-ß1) influenced by DPP-4 inhibition.

The effect of DPP-4 inhibition to improve functional outcome after stroke is mediated by the SDF-1α/CXCR4 pathway.

BACKGROUND: Dipeptidyl peptidase-4 (DPP-4) inhibitors (gliptins) are approved drugs for the treatment of hyperglycemia in patients with type 2 diabetes. These effects are mainly mediated by inhibiting endogenous glucagon-like peptide-1 (GLP-1) cleavage. Interestingly, gliptins can also improve stroke outcome in rodents independently from GLP1. However, the underlying mechanisms are unknown. Stromal cell-derived factor-1α (SDF-1α) is a DPP-4 substrate and CXCR4 agonist promoting beneficial effects in injured brains. However, SDF-1α involvement in gliptin-mediated neuroprotection after ischemic injury is unproven. We aimed to determine whether the gliptin linagliptin improves stroke outcome via the SDF-1α/CXCR4 pathway, and identify additional effectors behind the efficacy. METHODS: Mice were subjected to stroke by transient middle cerebral artery occlusion (MCAO). linagliptin was administered for 3 days or 3 weeks from stroke onset. The CXCR4-antagonist AMD3100 was administered 1 day before MCAO until 3 days thereafter. Stroke outcome was assessed by measuring upper-limb function, infarct volume and neuronal survival. The plasma and brain levels of active GLP-1, GIP and SDF-1α were quantified by ELISA. To identify additional gliptin-mediated molecular effectors, brain samples were analyzed by mass spectrometry. RESULTS: Linagliptin specifically increased active SDF-1α but not glucose-dependent insulinotropic peptide (GIP) or GLP-1 brain levels. Blocking of SDF-1α/CXCR4 pathway abolished the positive effects of linagliptin on upper-limb function and histological outcome after stroke. Moreover, linagliptin treatment after stroke decreased the presence of peptides derived from neurogranin and from an isoform of the myelin basic protein. CONCLUSIONS: We showed that linagliptin improves functional stroke outcome in a SDF-1α/CXCR4-dependent manner. Considering that Calpain activity and intracellular Ca2+ regulate neurogranin and myelin basic protein detection, our data suggest a gliptin-mediated neuroprotective mechanism via the SDF-1α/CXCR4 pathway that could involve the regulation of Ca2+ homeostasis and the reduction of Calpain activity. These results provide new insights into restorative gliptin-mediated effects against stroke.

Data Preprocessing, Visualization, and Statistical Analyses of Nontargeted Peptidomics Data from MALDI-MS.

Mass spectrometric (MS) comparative analysis of peptides in biological specimens (nontargeted peptidomics) can result in large amounts of data due to chromatographic separation of a multitude of samples and subsequent MS analysis of numerous chromatographic fractions. Efficient yet effective strategies are needed to obtain relevant information. Combining visual and numerical data analysis offers a suitable approach to retrieve information and to filter data for significant differences as targets for succeeding MS/MS identifications.Visual analysis allows assessing features within a spatial context. Specific patterns are easily recognizable by the human eye. For example, derivatives representing modified forms of signals present are easily identifiable due to an apparent shift in mass and chromatographic retention times. On the other hand numerical data analysis offers the possibility to optimize spectra and to perform high-throughput calculations. A useful tool for such calculations is R, a freely available language and environment for statistical computing. R can be extended via packages to enable functionalities like mzML (open mass spectrometric data format) import and processing. R is capable of parallel processing enabling faster computation using the power of multicore systems.The combination and interplay of both approaches allows evaluating the data in a holistic way, thus helping the researcher to better understand data and experimental outcomes.

The dipeptidyl peptidase inhibitor linagliptin and the angiotensin II receptor blocker telmisartan show renal benefit by different pathways in rats with 5/6 nephrectomy.

Dipeptidyl peptidase (DPP)-4 inhibitors delay chronic kidney disease (CKD) progression in experimental diabetic nephropathy in a glucose-independent manner. Here we compared the effects of the DPP-4 inhibitor linagliptin versus telmisartan in preventing CKD progression in non-diabetic rats with 5/6 nephrectomy. Animals were allocated to 1 of 4 groups: sham operated plus placebo; 5/6 nephrectomy plus placebo; 5/6 nephrectomy plus linagliptin; and 5/6 nephrectomy plus telmisartan. Interstitial fibrosis was significantly decreased by 48% with linagliptin but a non-significant 24% with telmisartan versus placebo. The urine albumin-to-creatinine ratio was significantly decreased by 66% with linagliptin and 92% with telmisartan versus placebo. Blood pressure was significantly lowered by telmisartan, but it was not affected by linagliptin. As shown by mass spectrometry, the number of altered peptide signals for linagliptin in plasma was 552 and 320 in the kidney. For telmisartan, there were 108 peptide changes in plasma and 363 in the kidney versus placebo. Linagliptin up-regulated peptides derived from collagen type I, apolipoprotein C1, and heterogeneous nuclear ribonucleoproteins A2/B1, a potential downstream target of atrial natriuretic peptide, whereas telmisartan up-regulated angiotensin II. A second study was conducted to confirm these findings in 5/6 nephrectomy wild-type and genetically deficient DPP-4 rats treated with linagliptin or placebo. Linagliptin therapy in wild-type rats was as effective as DPP-4 genetic deficiency in terms of albuminuria reduction. Thus, linagliptin showed comparable efficacy to telmisartan in preventing CKD progression in non-diabetic rats with 5/6 nephrectomy. However, the underlying pathways seem to be different.

Collection and handling of blood specimens for peptidomics.

Pre-analytical variables can alter the analysis of blood-derived samples. In particular sample collection and specimen preparation can alter the validity of results obtained by modern multiplex assays (e.g., LC-MS). Low-molecular-weight proteins (peptides) as products of proteolytic cleavage events exhibit a close connection to protease activity. Increased or altered activity of proteases during sample collection, specimen generation, sample storage, and processing is mirrored by alterations in abundance of specific peptides. Awareness of clinical practices in medical laboratories and the current knowledge allow for identification of specific variables that affect the results of a peptidomic study. Knowledge of pre-analytical variables is a prerequisite to understand and control their impact.

Collection and handling of blood specimens for peptidomics.

Pre-analytical variables can alter the analysis of blood-derived samples. In particular, sample collection and specimen preparation can alter the validity of results obtained by modern multiplex assays (e.g., LC-MS). Low-molecular weight proteins (peptides) as products of proteolytic cleavage events exhibit a close connection to protease activity and function. Altered proteolytic activity during sample collection, preparation, handling, and storage is mirrored by alterations in abundance of specific peptides. Awareness of clinical practices in medical laboratories allows for the identification of specific variables that may affect the results of a peptidomic study. Knowledge of pre-analytical variables is a prerequisite to understand and control their impact.

In vivo profiling of DPP4 inhibitors reveals alterations in collagen metabolism and accumulation of an amyloid peptide in rat plasma.

Dipeptidyl peptidase 4 (DPP4) inhibitors represent a novel class of oral anti-hyperglycemic agents. The complete pharmacological profile of these protease inhibitors remains unclear. In order to gain deeper insight into the in vivo effects caused by DPP4 inhibition, two different DPP4 inhibitors (vildagliptin and AB192) were analyzed using differential peptide display. Wistar rats were treated with the DPP4 inhibitors (0.3mgkg(-1); 1mgkg(-1) or 3mgkg(-1) body weight) and DPP4 activity was measured before and at the end of the experiment. One hour after compound administration, blood plasma samples were collected to generate peptide displays and to subsequently identify differentially regulated peptides. A dose-dependent decrease in blood plasma DPP4 activity was measured for both inhibitors. DPP4 inhibition influenced collagen metabolism leading to depletion of collagen derived peptides (e.g. collagen alpha 1 (III) 521-554) and accumulation of related N-terminally extended collagen derived peptides (e.g. collagen alpha 1 (III) 519-554). Furthermore, the intact amyloid rat BRI (1-23) peptide was detected in plasma following in vivo DPP4 inhibition. DPP4 catalyzed cleavage kinetics of the BRI peptide were determined in vitro. The k(cat) and K(m) for cleavage by DPP4 were 5.2s(-1) and 14microM, respectively, resulting in a specificity constant k(cat)/K(m) of 0.36 x 10(6)s(-1)M(-1). Our results demonstrate that differential peptide analysis can be applied to monitor action of DPP4 inhibition in blood plasma. For the first time effects on basal collagen metabolism following DPP4 inhibition in vivo were demonstrated and the BRI amyloid peptide was identified as a novel DPP4 substrate.

Peptidomic analysis of blood plasma after in vivo treatment with protease inhibitors--a proof of concept study.

Native peptides can be regarded as surrogate markers for protease activity in biological samples. Analysis of peptides by peptidomics allows to monitor protease activity in vivo and to describe the influence of protease inhibition. To elucidate the potential of peptides as markers for in vivo protease inhibition we analyzed plasma samples from animals treated with either the indirect FXa inhibitor FONDAPARINUX or the dipeptidylpeptidase IV inhibitor AB192. Signals correlating with the treatment were subsequently identified and assessed with respect to protease-dependent consensus cleavage motifs and occurrence of downstream targets. It could be shown that regulated peptides were either substrates, products or downstream targets of the inhibited protease. The results from the present study demonstrate that the in vivo analysis of peptides by peptidomics has the potential to broaden the knowledge of inhibitor related effects in vivo and that this method may pave the way to develop predictive biomarkers.

Specimen collection and handling: standardization of blood sample collection.

Preanalytical variables can alter the analysis of blood-derived samples. Prior to the analysis of a blood sample, multiple steps are necessary to generate the desired specimen. The choice of blood specimens, its collection, handling, processing, and storage are important aspects since these characteristics can have a tremendous impact on the results of the analysis. The awareness of clinical practices in medical laboratories and the current knowledge allow for identification of specific variables that affect the results of a proteomic study. The knowledge of preanalytical variables is a prerequisite to understand and control their impact.

Peptidomics analysis of human blood specimens for biomarker discovery.

This review addresses the concepts, limitations and perspectives for the application of peptidomics science and technologies to discover putative biomarkers in blood specimens. Peptidomics can be defined as the comprehensive multiplex analysis of endogenous peptides contained within a biological sample under defined conditions to describe the multitude of native peptides in a biological compartment. In addition to the discovery of disease associated biomarkers, an emerging field in peptidomics is the analysis of peptides to describe in vivo effects of protease inhibitors. The development and application of peptidomics technologies represent an arena of biomarker research that has the potential for adding significant clinical value.

Oncopeptidomics--a commentary on opportunities and limitations.

Cancer cells exhibit specific changes in protein expression and alterations in proteolytic activities. Peptides are capable of reflecting these pathological changes and are educible by dedicated analytical technologies. Oncopeptidomics can be defined as the comprehensive multiplexed analysis of endogenous peptides from a biological sample, under defined conditions, to discover probable valid peptide tumor biomarker. Here, mass spectrometry has shown its potential as a comprehensive peptide profiling tool. The efforts to arrive at diagnostically relevant biomarkers may have been underestimated. The establishment of novel cancer biomarkers will necessitate a multidisciplinary effort and presumably require a duration comparable to the drug development process. This review will address current concepts, new perspectives and the developmental process leading to clinically useful peptide tumor markers.

Peptidomic analysis of human peripheral monocytes persistently infected by Chlamydia trachomatis.

Peptidomic analysis using Differential Peptide Display (DPD) of human peripheral blood mononuclear cells (PBMC) mock-infected or persistently infected by Chlamydia trachomatis (CT) revealed 10 peptides, expressed upon CT infection. Analysis of these 10 candidates by tandem mass spectrometry enabled the determination of seven candidates as fragments from the precursors (I) ferritin heavy chain subunit, (II) HLA class II histocompatibility antigen, (III) vimentin, (IV) indoleamine 2,3-dioxygenase, (V and VI) pre-B cell enhancing factor (PBEF), and (VII) Interleukin-8 (CXCL8). The identified candidates proved the presence of anti-bacterial and immunologically active monocytic proteins after CT infection.

Metrological sharp shooting for plasma proteins and peptides: The need for reference materials for accurate measurements in clinical proteomics and in vitro diagnostics to generate reliable results.

Reliable study results are necessary for the assessment of discoveries, including those from proteomics. Reliable study results are also crucial to increase the likelihood of making a successful choice of biomarker candidates for verification and subsequent validation studies, a current bottleneck for the transition to in vitro diagnostic (IVD). In this respect, a major need for improvement in proteomics appears to be accuracy of measurements, including both trueness and precision of measurement. Standardization and total quality management systems (TQMS) help to provide accurate measurements and reliable results. Reference materials are an essential part of standardization and TQMS in IVD and are crucial to provide metrological correct measurements and for the overall quality assurance process. In this article we give an overview on how reference materials are defined, prepared and what role they play in standardization and TQMS to support the generation of reliable results. We discuss how proteomics can support the establishment of reference materials and biomarker tests for IVD applications, how current reference materials used in IVD may be beneficially applied in proteomics, and we provide considerations on the establishment of reference materials specific for proteomics. For clarity, we solely focus on reference materials related to serum and plasma.

Peptidomic analysis of breast cancer reveals a putative surrogate marker for estrogen receptor-negative carcinomas.

Estrogen-receptor status provides a major biomarker in breast cancer classification and has an important impact on prognosis and treatment options. The aim of this study was to investigate peptide profiles of invasive breast cancer with positive (n=39) and negative receptor status (n=41). Peptide profiles were generated by 'Differential Peptide Display', which is an offline-coupled combination of reversed-phase-HPLC and MALDI mass spectrometry. Mass spectrometric data were correlated with the immunohistochemically determined receptor state. Identification of peptides of interest was carried out by additional mass spectrometric methods (eg MALDI-TOF-TOF-MS-MS). Approximately 3000-7000 signals were detected per sample and thymosin alpha-1, an asparaginyl endopeptidase generated cleavage product of the ubiquitous acidic protein prothymosin-alpha, was found to differentiate the tumor samples according to their receptor status with the highest specificity. The concentration of Thymosin alpha-1 was found to be upregulated (n=37) in estrogen-negative cancer samples and downregulated (n=32) in estrogen-positive breast cancer samples. The expression of the precursor protein (Prothymosin-alpha) has been discussed previously as a prognostic factor in breast cancer. It is involved in the ER signal transduction pathway as an anti-coactivator-inhibitor. From our findings we conclude that Thymosin alpha-1 could serve as a surrogate marker in breast cancers and may indicate ER functionality.

Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

HUPO Plasma Proteome Project specimen collection and handling: towards the standardization of parameters for plasma proteome samples.

There is a substantial list of pre-analytical variables that can alter the analysis of blood-derived samples. We have undertaken studies on some of these issues including choice of sample type, stability during storage, use of protease inhibitors, and clinical standardization. As there is a wide range of sample variables and a broad spectrum of analytical techniques in the HUPO PPP effort, it is not possible to define a single list of pre-analytical standards for samples or their processing. We present here a compendium of observations, drawing on actual results and sound clinical theories and practices. Based on our data, we find that (1) platelet-depleted plasma is preferable to serum for certain peptidomic studies; (2) samples should be aliquoted and stored preferably in liquid nitrogen; (3) the addition of protease inhibitors is recommended, but should be incorporated early and used judiciously, as some form non specific protein adducts and others interfere with peptide studies. Further, (4) the diligent tracking of pre-analytical variables and (5) the use of reference materials for quality control and quality assurance, are recommended. These findings help provide guidance on sample handling issues, with the overall suggestion being to be conscious of all possible pre-analytical variables as a prerequisite of any proteomic study.

Peptidomic analysis of human blood specimens: comparison between plasma specimens and serum by differential peptide display.

The human Plasma Proteome Project pilot phase aims to analyze serum and plasma specimens to elucidate specimen characteristics by various proteomic techniques to ensure sufficient sample quality for the HUPO main phase. We used our proprietary peptidomics technologies to analyze the samples distributed by HUPO. Peptidomics summarizes technologies for visualization, quantitation, and identification of the low-molecular-weight proteome (<15 kDa), the "peptidome." We analyzed all four HUPO specimens (EDTA plasma, citrate plasma, heparin plasma, and serum) from African- and Asian-American donors and compared them to in-house collected Caucasian specimens. One main finding focuses on the most suitable method of plasma specimen collection. Gentle platelet removal from plasma samples is beneficial for improved specificity. Platelet contamination or activation of platelets by low temperature prior to their removal leads to distinct and multiple peptide signals in plasma samples. Two different specimen collection protocols for platelet-poor plasma are recommended. Further emphasis is placed on the differences between plasma and serum on a peptidomic level. A large number of peptides, many of them in rather high abundance, are only present in serum and not detectable in plasma. This ex vivo generation of multiple peptides hampers discovery efforts and is caused by a variety of factors: the release of platelet-derived peptides, other peptides derived from cellular components or the clot, enzymatic activities of coagulation cascades, and other proteases. We conclude that specimen collection is a crucial step for successful peptide biomarker discovery in human blood samples. For analysis of the low-molecular-weight proteome, we recommend the use of platelet-depleted EDTA or citrate plasma.