Search

Research data is accumulating rapidly, and with it the challenge of irreproducible science. As a consequence, implementation of high quality management of scientific data has become a global priority. The FAIR (Findable, Accesible, Interoperable and Reusable) principles provide practical guidelines for maximizing the value of research data, however, processing data using workflows - systematic executions of a series computational tools - is equally important for good data management. The FAIR principles have recently been adapted to Research Software (FAIR4RS Principles) to promote the reproducibility and reusability of any type of research software. Here we propose a set of 10 quick tips, drafted by experienced workflow developers that will help researchers to apply FAIR4RS principles to workflows. The tips have been arranged according to the FAIR acronym, clarifying the purpose of each tip with respect to the FAIR4RS principles. Altogether, these tips can be seen as practical guidelines for workflow developers who aim to contribute to more reproducible and sustainable computational science, aiming to positively impact the open science and FAIR community.

Objective Fibroblast growth factor 21 (FGF21) is a peptide hormone synthesized by several organs and regulates, among others, energy homeostasis. In obesity, insulin resistance and type 2 diabetes (T2D), higher circulating FGF21 concentrations have been found. Temporal analyses in murine studies demonstrate that FGF21 increases before insulin resistance occurs. The current study aims to investigate in time-to-event analyses whether FGF21 may be an early biomarker in the development of T2D. Research Design and Methods Circulating FGF21 was measured using an immunoassay of the Mesoscale U-PLEX assay platform. The study outcome was incident T2D. Associations of circulating FGF21 concentration with T2D were quantified using Cox proportional hazards models with adjustments for potential confounders. Results We included 5244 participants aged 52 ± 12 years, of whom 50% were male. Median [interquartile range] circulating FGF21 concentration was 860 [525-1329] pg/mL. During 7.3 [6.1-7.7] years of follow-up, 299 (5.7%) participants developed T2D. In fully adjusted analyses, higher circulating FGF21 concentration was associated with an increased risk of incident T2D (hazard ratio per doubling: 1.26 [95% CI, 1.06-1.51]; P = 0.008), with effect modification by fasting plasma glucose, consistent with strengthening of the association at lower fasting glucose (interaction coefficient: −0.12; P = 0.022). Conclusion Higher circulating FGF21 concentrations are independently associated with an increased risk of incident T2D in participants with a low fasting plasma glucose, making circulating FGF21 concentration a potential early biomarker for type 2 diabetes.

MotivationWe are witnessing an enormous growth in the amount of molecular profiling (-omics) data. The integration of multi-omics data is challenging. Moreover, human multi-omics data may be privacy-sensitive and misused to de-anonymize and (re-)identify individuals. Hence, most data is kept in secure and protected silos. Therefore, it remains a challenge to reuse these data without infringing the privacy of the individuals from which the data were derived. Federated analysis of FAIR data is a privacy-preserving solution to make optimal use of these multi-omics data and transform them into actionable knowledge.ResultsThe Netherlands X-omics Initiative is a National Roadmap Large-Scale Research Infrastructure aiming for efficient integration of data generated within X-omics and external datasets. To facilitate this, we developed the FAIR Data Cube (FDCube), which adopts and applies the FAIR principles and helps researchers to create FAIR data and metadata, facilitate reuse of their data, and make their data analysis workflows transparent. The FDCube also meets security-by-design and privacy-by-design principles.Availabilityhttps://github.com/Xomics/FAIRDataCubeContactXiaofeng.Liao@radboudumc.nl,Peter-Bram.tHoen@radboudumc.nlSupplementary informationSupplementary data are available atBioinformaticsonline.

Multiple Myeloma (MM) is a plasma cell malignancy characterized by a monoclonal expansion of plasma cells that secrete a characteristic M-protein. This M-protein is crucial for diagnosis and monitoring of MM in the blood of patients. Recent evidence has emerged suggesting that N-glycosylation of the M-protein variable (Fab) region contributes to M-protein pathogenicity, and that it is a risk factor for disease progression of plasma cell disorders. Current methodologies lack the specificity to provide a site-specific glycoprofile of the Fab regions of M-proteins. Here, we introduce a novel glycoproteogenomics method that allows detailed M-protein glycoprofiling by integrating patient specific Fab region sequences (genomics) with glycoprofiling by glycoproteomics. Genomic analysis uncovered a more than two-fold increase in the Fab Light Chain N-glycosylation of M-proteins of patients with Multiple Myeloma compared to Fab Light Chain N-glycosylation of polyclonal antibodies from healthy individuals. Subsequent glycoproteogenomics analysis of 41 patients enrolled in the IFM 2009 clinical trial revealed that the majority of the Fab N-glycosylation sites were fully occupied with complex type glycans, distinguishable from Fc region glycans due to high levels of sialylation, fucosylation and bisecting structures. Together, glycoproteogenomics is a powerful tool to studyde novoFab N-glycosylation in plasma cell dyscrasias.

Fasting proinsulin levels may serve as a marker of β-cell dysfunction and predict type 2 diabetes (T2D) development. Kidneys have been found to be a major site for the degradation of proinsulin. We aimed to evaluate the predictive value of proinsulin for the risk of incident T2D added to a base model of clinical predictors and examined potential effect modification by variables related to kidney function. Proinsulin was measured in plasma with U-PLEX platform using ELISA immunoassay. We included 5001 participants without T2D at baseline and during a median follow up of 7.2 years; 271 participants developed T2D. Higher levels of proinsulin were associated with increased risk of T2D independent of glucose, insulin, C-peptide, and other clinical factors (hazard ratio (HR): 1.28; per 1 SD increase 95% confidence interval (CI): 1.08–1.52). Harrell’s C-index for the Framingham offspring risk score was improved with the addition of proinsulin (p = 0.019). Furthermore, we found effect modification by hypertension (p = 0.019), eGFR (p = 0.020) and urinary albumin excretion (p = 0.034), consistent with an association only present in participants with hypertension or kidney dysfunction. Higher fasting proinsulin level is an independent predictor of incident T2D in the general population, particularly in participants with hypertension or kidney dysfunction.

Precision Medicine is driven by the idea that the rapidly increasing range of relatively cheap and efficient self-tracking devices make it feasible to collect multiple kinds of phenotypic data. Advocates ofN = 1 research emphasize the countless opportunities personal data provide for optimizing individual health. At the same time, using biomarker data for lifestyle interventions has shown to entail complex challenges. In this paper, we argue that researchers in the field of precision medicine need to address the performative dimension of collecting data. We propose the fun-house mirror as a metaphor for the use of personal health data; each health data source yields a particular type of image that can be regarded as a ‘data mirror’ that is by definition specific and skewed. This requires competence on the part of individuals to adequately interpret the images thus provided.

Background Minimal residual disease (MRD) status assessed on bone marrow aspirates is a major prognostic biomarker in multiple myeloma (MM). In this study we evaluated blood-based targeted mass spectrometry (MS-MRD) as a sensitive, minimally invasive alternative to measure MM disease activity. Methods Therapy response of 41 MM patients in the IFM-2009 clinical trial (NCT01191060) was assessed with MS-MRD on frozen sera and compared to routine state-of-the-art monoclonal protein (M-protein) diagnostics and next-generation sequencing (NGS-MRD) at 2 time points. Results In all 41 patients we were able to identify clonotypic M-protein-specific peptides and perform serum-based MS-MRD measurements. MS-MRD is significantly more sensitive to detect M-protein compared to either electrophoretic M-protein diagnostics or serum free light chain analysis. The concordance between NGS-MRD and MS-MRD status in 81 paired bone marrow/sera samples was 79%. The 50% progression-free survival (PFS) was identical (49 months) for patients who were either NGS-positive or MS-positive directly after maintenance treatment. The 50% PFS was 69 and 89 months for NGS-negative and MS-negative patients, respectively. The longest 50% PFS (96 months) was observed in patients who were MRD-negative for both methods. MS-MRD relapse during maintenance treatment was significantly correlated to poor PFS (P Conclusions Our data indicate proof-of-principle that MS-MRD evaluation in blood is a feasible, patient friendly alternative to NGS-MRD assessed on bone marrow. Clinical validation of the prognostic value of MS-MRD and its complementary value in MRD-evaluation of patients with MM is warranted in an independent larger cohort.

The human plasma glycoproteome holds enormous potential to identify personalized biomarkers to diagnose and understand disease. Recent advances in mass spectrometry and software development are opening novel avenues to mine the glycoproteome for protein- and site-specific glycosylation changes. Here, we describe a novel plasma N-glycoproteomics method for disease diagnosis and evaluated its clinical applicability by performing comparative glycoproteomics in blood plasma of 40 controls and a cohort of 74 patients with 13 different genetic diseases that directly impact the protein N-glycosylation pathway. The plasma glycoproteome yielded high-specificity biomarker signatures for each of the individual genetic defects. Bioinformatic analyses revealed site-specific glycosylation differences that could be explained by underlying glycobiology and in specific diseases by protein-intrinsic factors. Our work illustrates the strong potential of plasma glycoproteomics to significantly increase specificity of glycoprotein biomarkers with direct insights in site-specific glycosylation changes to better understand the mechanisms underlying human disease.

Research consortia in Europe often compete with each other for skills, human and technical resources and, eventually, recognition of the scientific impact of their work. In response to the same EU Horizon2020 call, we received funding for our research project proposals to identify and validate novel drug targets for cardiovascular disease treatment. Each consortium followed a unique and independent research strategy. However, as coordinators of these consortia we envisioned we could increase impact, outcomes and efficiency by intensifying our interaction. At an agreed stage during our projects we chose to share our knowledge, vision and ideas. In this paper we present what we learned, in the hope that future consortia will see the benefits of this approach.

Because positron emission tomography (PET) and optical imaging are very complementary, the combination of these two imaging modalities is very enticing in the oncology field. Such bimodal imaging generally relies on imaging agents bearing two different imaging reporters. In the bioconjugation field, this is mainly performed by successive random conjugations of the two reporters on the protein vector, but these random conjugations can alter the vector properties. In this study, we aimed at abrogating the heterogeneity of the bimodal imaging immunoconjugate and mitigating the impact of multiple random conjugations. A trivalent platform bearing a DFO chelator for

Many patients with primary focal segmental glomerulosclerosis (FSGS) develop recurrence of proteinuria after kidney transplantation. Several circulating permeability factors (CPFs) responsible for recurrence have been suggested, but were never validated. We aimed to find proteins involved in the mechanism of action of CPF(s) and/or potential biomarkers for the presence of CPF(s). Cultured human podocytes were exposed to plasma from patients with FSGS with presumed CPF(s) or healthy and disease controls. Podocyte proteomes were analyzed by LC–MS. Results were validated using flow cytometry, RT-PCR, and immunofluorescence. Podocyte granularity was examined using flow cytometry, electron microscopy imaging, and BODIPY staining. Perilipin-2 protein expression was increased in podocytes exposed to presumed CPF-containing plasmas, and correlated with the capacity of plasma to induce podocyte granularity, identified as lipid droplet accumulation. Elevated podocyte perilipin-2 was confirmed at protein and mRNA level and was also detected in glomeruli of FSGS patients whose active disease plasmas induced podocyte perilipin-2 and lipid droplets. Our study demonstrates that presumably, CPF-containing plasmas from FSGS patients induce podocyte lipid droplet accumulation and perilipin-2 expression, identifying perilipin-2 as a potential biomarker. Future research should address the mechanism underlying CPF-induced alterations in podocyte lipid metabolism, which ultimately may result in novel leads for treatment.

Background Due to improved treatment, more patients with multiple myeloma (MM) reach a state of minimal residual disease (MRD). Different strategies for MM MRD monitoring include flow cytometry, allele-specific oligonucleotide–quantitative PCR, next-generation sequencing, and mass spectrometry (MS). The last 3 methods rely on the presence and the stability of a unique immunoglobulin fingerprint derived from the clonal plasma cell population. For MS-MRD monitoring it is imperative that MS-compatible clonotypic M-protein peptides are identified. To support implementation of molecular MRD techniques, we studied the presence and stability of these clonotypic features in the CoMMpass database. Methods An analysis pipeline based on MiXCR and HIGH-VQUEST was constructed to identify clonal molecular fingerprints and their clonotypic peptides based on transcriptomic datasets. To determine the stability of the clonal fingerprints, we compared the clonal fingerprints during disease progression for each patient. Results The analysis pipeline to establish the clonal fingerprint and MS-suitable clonotypic peptides was successfully validated in MM cell lines. In a cohort of 609 patients with MM, we demonstrated that the most abundant clone harbored a unique clonal molecular fingerprint and that multiple unique clonotypic peptides compatible with MS measurements could be identified for all patients. Furthermore, the clonal immunoglobulin gene fingerprints of both the light and heavy chain remained stable during MM disease progression. Conclusions Our data support the use of the clonal immunoglobulin gene fingerprints in patients with MM as a suitable MRD target for MS-MRD analyses.

Aims: Patients with diabetes have a higher incidence of infections with Candida albicans, Staphylococcus aureus and Mycobacterium tuberculosis, yet factors contributing to this increased risk are largely unknown. We hypothesize that altered innate and adaptive immune responses during diabetes contribute to an increased susceptibility to infections. Materials and methods: We studied cytokine responses to ex vivo pathogenic stimulations in a cohort with type 1 diabetes (n = 243) and non-diabetic healthy control subjects (n = 56) using isolated peripheral blood mononuclear cells (PBMCs). Clinical phenotypical data including BMI, duration of diabetes, and HbA1c levels were collected and related to the cytokine production capacity. Results: Adjusted for age, sex and BMI, the presence of diabetes was associated with significantly lower IL-1β, IL-6, TNF-α, and IL-17 production upon ex vivo stimulation of PBMCs with C. albicans and S. aureus (all, p < 0.05). In response to stimulation with M. tuberculosis only IL-17 (p < 0.001) was lower in patients with diabetes. Patients with the shortest diabetes duration had a significant lower IL-1β, IL-6 and TNF-α production (all, p < 0.01) after M. tuberculosis stimulation. Older patients had a significant lower IFN-γ (p < 0.05) production after stimulation with all three pathogens. HbA1c levels and BMI had no significant impact on cytokine production. Conclusions: PBMCs of patients with type 1 diabetes demonstrate significantly lower cytokine production in response to stimulation with several pathogens, which likely explain, at least in part, the increased susceptibility for these infections.

Contains fulltext : 244088.pdf (Publisher’s version ) (Open Access) Age-related macular degeneration (AMD) is a major cause of vision loss among the elderly in the Western world. The complement system has been identified as one of the main AMD disease pathways. We performed a comprehensive expression analysis of 32 complement proteins in plasma samples of 255 AMD patients and 221 control individuals using mass spectrometry-based semi-quantitative multiplex profiling. We detected significant associations of complement protein levels with age, sex and body-mass index (BMI), and potential associations of C-reactive protein, factor H related-2 (FHR-2) and collectin-11 with AMD. In addition, we confirmed previously described associations and identified new associations of AMD variants with complement levels. New associations include increased C4 levels for rs181705462 at the C2/CFB locus, decreased vitronectin (VTN) levels for rs11080055 at the TMEM97/VTN locus and decreased factor I levels for rs10033900 at the CFI locus. Finally, we detected significant associations between AMD-associated metabolites and complement proteins in plasma. The most significant complement-metabolite associations included increased high density lipoprotein (HDL) subparticle levels with decreased C3, factor H (FH) and VTN levels. The results of our study indicate that demographic factors, genetic variants and circulating metabolites are associated with complement protein components. We suggest that these factors should be considered to design personalized treatment approaches and to increase the success of clinical trials targeting the complement system.

An effective response to the coronavirus disease 2019 (COVID-19) pandemic requires a better understanding of the biology of the infection and the identification of validated biomarker profiles that would increase the availability, accuracy, and speed of COVID-19 testing. Here, we describe the strategic objectives and action lines of the European Alliance of Medical Research Infrastructures (AMRI), established to improve the research process and tackle challenges related to diagnostic tests and biomarker development. Recommendations include: the creation of a European taskforce for validation of novel diagnostic products, the definition and promotion of criteria for COVID-19 samples biobanking, the identification and validation of biomarkers as clinical endpoints for clinical trials, and the definition of immune biomarker signatures at different stages of the disease. An effective management of the COVID-19 pandemic is possible only if there is a high level of knowledge and coordination between the public and private sectors within a robust quality framework., Oldoni et al debate relevant issues related to coronavirus disease 2019 testing and biomarker development. European Medical Research Infrastructures call for a high level of knowledge and coordination between public and private sectors, likewise for quality and reproducibility along the research pipeline.

Parkinson’s disease (PD) and multiple system atrophy (MSA) have overlapping symptoms, challenging a correct early diagnosis. Prognostic information is needed to predict disease progression and provide appropriate counseling. Neuroinflammation plays a role in the pathology of both disorders, as shown in genetic and postmortem tissue studies. Monocyte chemoattractant protein 1 (MCP-1) and neuroleukin (NLK) are two inflammatory proteins with potential to serve as biomarkers of the neuroinflammatory process. Here, we aimed to study the biomarker potential of both MCP-1 and NLK protein levels in cerebrospinal fluid (CSF) from a longitudinal cohort study (Radboudumc, Nijmegen, The Netherlands), consisting of PD patients (n = 46), MSA patients (n = 17) and control subjects (n = 52) using ELISA. We also correlated MCP-1 and NLK levels in CSF to several parameters of disease. We showed that MCP-1 levels in CSF positively correlate with PD progression (ρ = 0.363; p = 0.017) but could not differentiate between PD, MSA, and controls. NLK levels in CSF neither differentiated between PD, MSA, and controls, nor correlated with disease progression. Our results indicate that MCP-1 levels in CSF cannot distinguish between PD, MSA, and controls but correlate with disease progression in PD patients, suggesting that neuroinflammation is associated with clinical progression in PD. The correlation with disease progression was only moderate, so MCP-1 levels in CSF should be included in a larger battery of prognostic biomarkers that also tackle different pathophysiological processes.

Contains fulltext : 225249.pdf (Publisher’s version ) (Open Access) INTRODUCTION: Assessing the specificity of protein binders is an essential first step in protein biomarker assay development. Affimers are novel protein binders and can potentially replace antibodies in multiple protein capture-based assays. Affimers are selected for their high specificity against the target protein and have benefits over antibodies like batch-to-batch reproducibility and are stable across a wide range of chemical conditions. Here we mimicked a typical initial screening of affimers and commercially available monoclonal antibodies against two non-related proteins, IL-37b and proinsulin, to assess the potential of affimers as alternative to antibodies. METHODS: Binding specificity of anti-IL-37b and anti-proinsulin affimers and antibodies was investigated via magnetic bead-based capture of their recombinant protein targets in human plasma. Captured proteins were analyzed using SDS-PAGE, Coomassie blue staining, Western blotting and LC-MS/MS-based proteomics. RESULTS: All affimers and antibodies were able to bind their target protein in human plasma. Gel and LC-MS/MS analysis showed that both affimer and antibody-based captures resulted in co-purified background proteins. However, affimer-based captures showed the highest relative enrichment of IL-37b and proinsulin. CONCLUSIONS: For both proteins tested, affimers show higher specificity in purifying their target proteins from human plasma compared to monoclonal antibodies. These results indicate that affimers are promising antibody-replacement tools for protein biomarker assay development.

Contains fulltext : 225915.pdf (Publisher’s version ) (Open Access) Parkinson's disease (PD) is the most common neurodegenerative disorder of movement worldwide. To date, only symptomatic treatments are available. Implantation of collagen-encapsulated human umbilical cord mesenchymal stem cells (hUC-MSCs) is being developed as a novel therapeutic approach to potentially modify PD progression. However, implanted collagen scaffolds may induce a host tissue response. To gain insight into such response, hUC-MSCs were encapsulated into collagen hydrogels and implanted into the striatum of hemi-Parkinsonian male Sprague-Dawley rats. One or 14 days after implantation, the area of interest was dissected using a cryostat. Total protein extracts were subjected to tryptic digestion and subsequent LC-MS/MS analyses for protein expression profiling. Univariate and multivariate analyses were performed to identify differentially expressed protein profiles with subsequent gene ontology and pathway analysis for biological interpretation of the data; 2,219 proteins were identified by MaxQuant at 1% false discovery rate. A high correlation of label-free quantification (LFQ) protein values between biological replicates (r = .95) was observed. No significant differences were observed between brains treated with encapsulated hUC-MSCs compared to appropriate controls. Proteomic data were highly robust and reproducible, indicating the suitability of this approach to map differential protein expression caused by the implants. The lack of differences between conditions suggests that the effects of implantation may be minimal. Alternatively, effects may only have been focal and/or could have been masked by nonrelevant high-abundant proteins. For follow-up assessment of local changes, a more accurate dissection technique, such as laser micro dissection, and analysis method are recommended.

Aim To investigate whether a history of severe hypoglycaemia (SH) or the associated presence of impaired awareness of hypoglycaemia (IAH) is characterized by a pro‐inflammatory profile in people with type 1 diabetes. Research design and methods We measured circulating inflammatory markers and pro‐ and anti‐inflammatory cytokine production after ex vivo stimulation of peripheral blood mononuclear cells (PBMCs) in a well‐characterized cohort of individuals with type 1 diabetes (n = 239) and in people without diabetes (n = 56). Data were corrected for confounders by using multivariate linear regression models. Results People with type 1 diabetes had higher circulating concentrations of high‐sensitivity C‐reactive protein (hs‐CRP; 0.91 [0.36–2.25] vs. 0.52 [0.20–0.98] pg/mL, P < 0.001 and interleukin‐18‐binding protein (IL‐18BP; 1746 [1304–2112] vs. 1381 [1191–1807] pg/mL; P = 0.001) than those without diabetes. In multivariate analysis, only higher hs‐CRP concentrations persisted. Neither circulating immune cells nor ex vivo cytokine levels produced by PBMCs in response to an extensive panel of stimuli differed in groups defined by awareness state or a history of SH, apart from elevated IL‐18BP in people with, versus those without, history of SH (1524 [1227–1903] vs. 1913 [1459–2408] pg/mL; P < 0.001). Conclusions IAH or history of SH in people with type 1 diabetes was not associated with altered inflammatory profiles, arguing against chronically elevated inflammatory activity mediating the increased cardiovascular risk associated with hypoglycaemia. The finding of higher circulating concentrations of IL‐18BP in individuals with a history of SH requires further investigation.

© 2020 The Author(s)., [Introduction]: The importance of biomarkers for pharmaceutical drug development and clinical diagnostics is more significant than ever in the current shift toward personalized medicine. Biomarkers have taken a central position either as companion markers to support drug development and patient selection, or as indicators aiming to detect the earliest perturbations indicative of disease, minimizing therapeutic intervention or even enabling disease reversal. Protein biomarkers are of particular interest given their central role in biochemical pathways. Hence, capabilities to analyze multiple protein biomarkers in one assay are highly interesting for biomedical research. [Areas covered]: We here review multiple methods that are suitable for robust, high throughput, standardized, and affordable analysis of protein biomarkers in a multiplex format. We describe innovative developments in immunoassays, the vanguard of methods in clinical laboratories, and mass spectrometry, increasingly implemented for protein biomarker analysis. Moreover, emerging techniques are discussed with potentially improved protein capture, separation, and detection that will further boost multiplex analyses. [Expert commentary]: The development of clinically applied multiplex protein biomarker assays is essential as multi-protein signatures provide more comprehensive information about biological systems than single biomarkers, leading to improved insights in mechanisms of disease, diagnostics, and the effect of personalized medicine., This paper was funded by the European cooperation in science and technology - COST action No. CA16113 - CliniMARK: ‘good biomarker practice’ to increase the number of clinically validated biomarkers.

Objectives Complement deficiencies are difficult to diagnose because of the variability of symptoms and the complexity of the diagnostic process. Here, we applied a novel ‘complementomics’ approach to study the impact of various complement deficiencies on circulating complement levels. Methods Using a quantitative multiplex mass spectrometry assay, we analysed 44 peptides to profile 34 complement proteins simultaneously in 40 healthy controls and 83 individuals with a diagnosed deficiency or a potential pathogenic variant in 14 different complement proteins. Results Apart from confirming near or total absence of the respective protein in plasma of complement‐deficient patients, this mass spectrometry‐based profiling method led to the identification of additional deficiencies. In many cases, partial depletion of the pathway up‐ and/or downstream of the absent protein was measured. This was especially found in patients deficient for complement inhibitors, such as angioedema patients with a C1‐inhibitor deficiency. The added value of complementomics was shown in three patients with poorly defined complement deficiencies. Conclusion Our study shows the potential clinical utility of profiling circulating complement proteins as a comprehensive read‐out of various complement deficiencies. Particularly, our approach provides insight into the intricate interplay between complement proteins due to functional coupling, which contributes to the better understanding of the various disease phenotypes and improvement of care for patients with complement‐mediated diseases., In this study, we measured the ‘complementome’ of 83 individuals with various complement deficiencies by means of a quantitative multiplex mass spectrometry‐based assay. We found distinct profiles that provided better insight in the intricate interplay between complement proteins. The potential clinical utility of this approach was shown for three patients with poorly defined complement deficiencies.

C-peptide measurement may represent a better index of pancreatic &beta, cell function compared to insulin. While insulin is mainly cleared by liver, C-peptide is mainly metabolized by kidneys. The aim of our study was to evaluate the association between baseline plasma C-peptide level and the development of type 2 diabetes independent of glucose and insulin levels and to examine potential effect-modification by variables related to kidney function. We included 5176 subjects of the Prevention of Renal and Vascular End-Stage Disease study without type 2 diabetes at baseline. C-peptide was measured in plasma with an electrochemiluminescent immunoassay. Cox proportional hazards regression was used to evaluate the association between C-peptide level and type 2 diabetes development. Median C-peptide was 722 (566&ndash, 935) pmol/L. During a median follow-up of 7.2 (6.0&ndash, 7.7) years, 289 individuals developed type 2 diabetes. In multivariable-adjusted Cox regression models, we observed a significant positive association of C-peptide with the risk of type 2 diabetes independent of glucose and insulin levels (hazard ratio (HR): 2.35, 95% confidence interval (CI): 1.49&ndash, 3.70). Moreover, we found significant effect modification by hypertension and albuminuria (p &lt, 0.001 and p = 0.001 for interaction, respectively), with a stronger association in normotensive and normo-albuminuric subjects and absence of an association in subjects with hypertension or albuminuria. In this population-based cohort, elevated C-peptide levels are associated with an increased risk of type 2 diabetes independent of glucose, insulin levels, and clinical risk factors. Elevated C-peptide level was not independently associated with an increased risk of type 2 diabetes in individuals with hypertension or albuminuria.

Background: Overweight and obesity can lead to adipose tissue inflammation, which causes insulin resistance and on the long-term type 2 diabetes mellitus (T2D). The inflammatory changes of obese-adipose tissue are characterized by macrophage infiltration and activation, but validated circulating biomarkers for adipose tissue inflammation for clinical use are still lacking. One of the most secreted enzymes by activated macrophages is chitotriosidase (CHIT1). Objective: To test whether circulating CHIT1 enzymatic activity levels reflect adipose tissue inflammation. Methods: Plasma and adipose tissue samples of 105 subjects (35 lean, 37 overweight, and 33 T2D patients) were investigated. CHIT1 mRNA levels were determined in adipose tissue-resident innate immune cells. CHIT1 mRNA levels, protein abundance, and plasma enzymatic activity were subsequently measured in adipose tissue biopsies and plasma of control subjects with varying levels of obesity and adipose tissue inflammation as well as in T2D patients. Results: In adipose tissue, CHIT1 mRNA levels were higher in stromal vascular cells compared to adipocytes, and higher in adipose tissue-residing macrophages compared to circulating monocytes (p < 0.001). CHIT1 mRNA levels in adipose tissue were enhanced in overweightcompared to lean subjects and even more in T2D patients (p < 0.05). In contrast, plasma CHIT1 enzymatic activity did not differ between lean, overweight subjects and T2D patients. A mutation of the CHIT1 gene decreases plasma CHIT1 activity. Conclusions: CHIT1 is expressed by adipose tissue macrophages and expression is higher in overweight subjects and T2D patients, indicating its potential as tissue biomarker for adipose tissue inflammation. However, these differences do not translate into different plasma CHIT1 activity levels. Moreover, a common CHIT1 gene mutation causing loss of plasma CHIT1 activity interferes with its use as a biomarker of adipose tissue inflammation. These results indicate that plasma CHIT1 activity is of limited value as a circulating biomarker for adipose tissue inflammation in human subjects.

International audience; Thanks to proteomics investigations, our vision of the role of different protein isoforms in the pathophysiology of diseases has largely evolved. The idea that protein biomarkers like tau, amyloid peptides, ApoE, cystatin, or neurogranin are represented in body fluids as single species is obviously over-simplified, as most proteins are present in different isoforms and subjected to numerous processing and post-translational modifications. Measuring the intact mass of proteins by MS has the advantage to provide information on the presence and relative amount of the different proteoforms. Such Top-Down approaches typically require a high degree of sample pre-fractionation to allow the MS system to deliver optimal performance in terms of dynamic range, mass accuracy and resolution. In clinical studies, however, the requirements for pre-analytical robustness and sample size large enough for statistical power restrict the routine use of a high degree of sample pre-fractionation. In this study, we have investigated the capacities of current-generation Ultra-High Resolution Q-Tof systems to deal with high complexity intact protein samples and have evaluated the approach on a cohort of patients suffering from neurodegenerative disease. Statistical analysis has shown that several proteoforms can be used to distinguish Alzheimer disease patients from patients suffering from other neurodegenerative disease.SIGNIFICANCE:Top-down approaches have an extremely high biological relevance, especially when it comes to biomarker discovery, but the necessary pre-fractionation constraints are not easily compatible with the robustness requirements and the size of clinical sample cohorts. We have demonstrated that intact protein profiling studies could be run on UHR-Q-ToF with limited pre-fractionation. The proteoforms that have been identified as candidate biomarkers in the-proof-of concept study are derived from proteins known to play a role in the pathophysiology process of Alzheimer disease.

Background & Aims The incidence of nonalcoholic steatohepatitis (NASH) is increasing. The pathophysiological mechanisms of NASH and the sequence of events leading to hepatic fibrosis are incompletely understood. The aim of this study was to gain insight into the dynamics of key molecular processes involved in NASH and to rank early markers for hepatic fibrosis. Methods A time-course study in low-density lipoprotein–receptor knockout. Leiden mice on a high-fat diet was performed to identify the temporal dynamics of key processes contributing to NASH and fibrosis. An integrative systems biology approach was used to elucidate candidate markers linked to the active fibrosis process by combining transcriptomics, dynamic proteomics, and histopathology. The translational value of these findings were confirmed using human NASH data sets. Results High-fat-diet feeding resulted in obesity, hyperlipidemia, insulin resistance, and NASH with fibrosis in a time-dependent manner. Temporal dynamics of key molecular processes involved in the development of NASH were identified, including lipid metabolism, inflammation, oxidative stress, and fibrosis. A data-integrative approach enabled identification of the active fibrotic process preceding histopathologic detection using a novel molecular fibrosis signature. Human studies were used to identify overlap of genes and processes and to perform a network biology-based prioritization to rank top candidate markers representing the early manifestation of fibrosis. Conclusions An early predictive molecular signature was identified that marked the active profibrotic process before histopathologic fibrosis becomes manifest. Early detection of the onset of NASH and fibrosis enables identification of novel blood-based biomarkers to stratify patients at risk, development of new therapeutics, and help shorten (pre)clinical experimental time frames., Graphical abstract

Background : Parkinson’s disease (PD) and atypical parkinsonisms (APD) have overlapping symptoms challenging an early diagnosis. Diagnostic accuracy is important because PD and APD have different prognosis and response to treatment. We aimed to identify inflammatory biomarkers in cerebrospinal fluid (CSF) using the multiplex proximity extension assay (PEA) technology to identify diagnostic biomarkers of PD and APD and to study possible correlations of biomarkers with disease progression. Methods : CSF from a longitudinal cohort study consisting of PD and APD patients (PD, n = 46; multiple system atrophy (MSA) , n = 15; vascular parkinsonism (VaP) , n = 9; and PD with VaP, n = 7) and controls (n = 25) were analyzed. Results : Concentrations of CCL28 were elevated in PD compared to controls (p < 0.05). Five other biomarkers differentiated both MSA and PD from controls (p < 0.05) and 10 biomarkers differentiated MSA from controls, of which two proteins, i.e. beta nerve growth factor (β-NGF) and Delta and Notch like epidermal growth factor-related receptor (DNER) , were also present at lower levels in MSA compared to PD (both p = 0.032). Two biomarkers (MCP-1 and MMP-10) positively correlated with PD progression (rho > 0.600; p < 0.01). Conclusions : PEA technique identified potential new CSF biomarkers to help to predict the prognosis of PD. Also, we identified new candidate biomarkers to distinguish MSA from PD.

ObjectivePrevious studies indicate a role for Oncostatin M (OSM) in atherosclerosis and other chronic inflammatory diseases for which inhibitory antibodies are in development. However, to date no intervention studies with OSM have been performed, and its relation to coronary heart disease (CHD) has not been studied.Approach and resultsGene expression analysis on human normal arteries (n = 10) and late stage/advanced carotid atherosclerotic arteries (n = 127) and in situ hybridization on early human plaques (n = 9) showed that OSM, and its receptors, OSM receptor (OSMR) and Leukemia Inhibitory Factor Receptor (LIFR) are expressed in normal arteries and atherosclerotic plaques. Chronic OSM administration in APOE*3Leiden.CETP mice (n = 15/group) increased plasma E-selectin levels and monocyte adhesion to the activated endothelium independently of cholesterol but reduced the amount of inflammatory Ly-6CHigh monocytes and atherosclerotic lesion size and severity. Using aptamer-based proteomics profiling assays high circulating OSM levels were shown to correlate with post incident CHD survival probability in the AGES-Reykjavik study (n = 5457).ConclusionsChronic OSM administration in APOE*3Leiden.CETP mice reduced atherosclerosis development. In line, higher serum OSM levels were correlated with improved post incident CHD survival probability in patients, suggesting a protective cardiovascular effect.

Background Choosing which biomarker tests to select for further research and development is not only a matter of diagnostic accuracy, but also of the clinical and monetary benefits downstream. Early health economic modeling provides tools to assess the potential effects of biomarker innovation and support decision-making. Methods We applied early health economic modeling to the case of diagnosing primary aldosteronism in patients with resistant hypertension. We simulated a cohort of patients using a Markov cohort state-transition model. Using the headroom method, we compared the currently used aldosterone-to-renin ratio to a hypothetical new test with perfect diagnostic properties to determine the headroom based on quality-adjusted life-years (QALYs) and costs, followed by threshold analyses to determine the minimal diagnostic accuracy for a cost-effective product. Results Our model indicated that a perfect diagnostic test would yield 0.027 QALYs and increase costs by €43 per patient. At a cost-effectiveness threshold of €20,000 per QALY, the maximum price for this perfect test to be cost-effective is €498 (95% confidence interval [CI]: €275–€808). The value of the perfect test was most strongly influenced by the sensitivity of the current biomarker test. Threshold analysis showed the novel test needs a sensitivity of at least 0.9 and a specificity of at least 0.7 to be cost-effective. Conclusions Our model-based approach evaluated the added value of a clinical biomarker innovation, prior to extensive investment in development, clinical studies and implementation. We conclude that early health economic modeling can be a valuable tool when prioritizing biomarker innovations in the laboratory.

Background The complement system is a central component of the innate immune system. Constitutive biosynthesis of complement proteins is essential for homeostasis. Dysregulation as a consequence of genetic or environmental cues can lead to inflammatory syndromes or increased susceptibility to infection. However, very little is known about steady state levels in children or its kinetics during infection. Methods With a newly developed multiplex mass spectrometry-based method we analyzed the levels of 32 complement proteins in healthy individuals and in a group of pediatric patients infected with bacterial or viral pathogens. Findings In plasma from young infants we found reduced levels of C4BP, ficolin-3, factor B, classical pathway components C1QA, C1QB, C1QC, C1R, and terminal pathway components C5, C8, C9, as compared to healthy adults; whereas the majority of complement regulating (inhibitory) proteins reach adult levels at very young age. Both viral and bacterial infections in children generally lead to a slight overall increase in complement levels, with some exceptions. The kinetics of complement levels during invasive bacterial infections only showed minor changes, except for a significant increase and decrease of CRP and clusterin, respectively. Interpretation The combination of lower levels of activating and higher levels of regulating complement proteins, would potentially raise the threshold of activation, which might lead to suppressed complement activation in the first phase of life. There is hardly any measurable complement consumption during bacterial or viral infection. Altogether, expression of the complement proteins appears surprisingly stable, which suggests that the system is continuously replenished. Fund European Union's Horizon 2020, project PERFORM, grant agreement No. 668303., Graphical abstract Unlabelled Image

Background Multiple myeloma (MM) is a plasma cell malignancy arising in the bone marrow that is characterized by secretion of a monoclonal immunoglobulin (M-protein). M-protein detection is an integral part of MM diagnostics, performed using electrophoretic methods. This approach is reliable, fast and inexpensive, but not sensitive enough for detecting deeper responses, characterized by low M-protein concentration. Novel therapies have led to an increasing number of patients obtaining complete remission, however no curative therapy is available for MM. Even in remission, minimal residual disease (MRD) is present and can develop towards a relapse. MRD analysis plays an important role as primary endpoint in clinical trials, powerful prognostic marker, and MRD-status is increasingly used to guide therapy-decisions. Methods currently used for MRD detection are based on bone marrow aspirates (e.g. flow cytometry or next generation sequencing (NGS)). Not only are repetitive bone marrow aspirations uncomfortable for the patient, they also introduce a risk of non-representative sampling due to the possible patchy occurrence of the cancer cells in MM. Aim The aim is to measure MRD in a cohort of 41 multiple myeloma patients during follow-up using a targeted mass spectrometry assay. Unique peptides from the M-protein are selected based on RNA sequence information. Patient-specific peptides from M-proteins will be measured using mass spectrometry and MRD status will be compared to available NGS data. Methods Multiple myeloma patients were selected from the IFM 2009 Study (ClinicalTrials.gov number: NCT01191060) with available RNA sequence information and MRD data by NGS. We have selected 41 patients with three serum samples per patient; a baseline serum sample and two follow-up time points for MRD assessment. For each patient we have selected at least two peptides unique for the M-protein that could be observed in the baseline sample using mass spectrometry; one peptide from the light chain, and one from the heavy chain.(Zajec et al, J Proteome Res, 2018) In the case of light chain MM (3 patients in this study), only light chain peptides were selected. Serum samples were diluted 500 times, digested with trypsin and directly measured using targeted Orbitrap mass spectrometry technology. Results For all 41 patients we were successful in selecting and targeting unique peptides for M-protein quantification using mass spectrometry. MRD was assessed in follow-up serum samples (n=82, two time points for each patient) using NGS and mass spectrometry. In these follow-up patients, seven patients were negative by both NGS and mass spectrometry. Additionally, eight patients were negative by NGS but positive by mass spectrometry; and ten patients were negative by mass spectrometry and positive by NGS. The remainder of the follow-up samples (n=57) were positive by both mass spectrometry and NGS. Conclusion Unique peptides of the M-protein were found in all 41 multiple myeloma patients. Using these peptides, it was feasible to measure the M-protein in blood samples from multiple myeloma patients during follow-up. NGS and mass spectrometry MRD assessment have a concordance of 78% (64/82) in the follow-up samples. These are preliminary results without any immunoglobulin enrichment. We expect that further optimization can improve the sensitivity of mass spectrometry measurements. Future perspective Described experiments were performed on non-enriched serum without optimization of mass spectrometry parameters. Future experiments should be adapted accordingly and will increase the sensitivity of the mass spectrometry measurements. Internal standards for the peptides will be synthesized for absolute quantification (g/L value) of the M-protein during MRD. Disclosures No relevant conflicts of interest to declare.

Introduction : Obesity is associated with adipose tissue inflammation which in turn drives insulin resistance and the development of type 2 diabetes. Oxylipins are a collection of lipid metabolites, subdivided in different classes, which are involved in inflammatory cascades. They play important roles in regulating adipose tissue homeostasis and inflammation and are therefore putative biomarkers for obesity-associated adipose tissue inflammation and the subsequent risk of type 2 diabetes onset. The objective for this study is to design an assay for a specific oxylipin class and evaluate these as potential prognostic biomarker for obesity-associated adipose tissue inflammation and type 2 diabetes. Methods : An optimized workflow was developed to extract oxylipins from plasma using solid-phase extraction followed by analysis using ultra-high performance liquid chromatography coupled to a triple quadrupole mass spectrometer in multiple reaction monitoring mode. This workflow was applied to clinical plasma samples obtained from obese-type 2 diabetes patients and from lean and obese control subjects. Results : The assay was analytically validated and enabled reproducible analyses of oxylipins extracted from plasma with acceptable sensitivities. Analysis of clinical samples revealed discriminative values for four oxylipins between the type 2 diabetes patients and the lean and obese control subjects, viz. PGF2α, PGE2, 15-keto-PGE2 and 13,14-dihydro-15-keto-PGE2. The combination of PGF2α and 15-keto-PGE2 had the most predictive value to discriminate type 2 diabetic patients from lean and obese controls. Conclusions : This proof-of-principle study demonstrates the potential value of oxylipins as biomarkers to discriminate obese individuals from obese-type 2 diabetes patients.

Introduction: The onset of type 2 diabetes mellitus (T2DM) is strongly associated with obesity and subsequent perturbations in immuno-metabolic responses. To understand the complexity of these systemic changes and better monitor the health status of people at risk, validated clinical biomarkers are needed. Omics technologies are increasingly applied to measure the interplay of genes, proteins and metabolites in biological systems, which is imperative in understanding molecular mechanisms of disease and selecting the best possible molecular biomarkers for clinical use. Areas covered: This review describes the complex onset of T2DM, the contribution of obesity and adipose tissue inflammation to the T2DM disease mechanism, and the output of current biomarker strategies. A new biomarker approach is described that combines published and new self-generated data to merge multiple -omes (i.e. genome, proteome, metabolome etc.) toward understanding of mechanism of disease on the individual level and design multiparameter biomarker panels that drive significant impacts on personalized healthcare. Expert commentary: We here propose an approach to use cross-omics analyses to contextualize published biomarker data and better understand molecular mechanisms of health and disease. This will improve the current and future innovation gaps in translation of discovered putative biomarkers to clinically applicable biomarker tests. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

Background: Ischemic coronary events relate to qualitative changes in plaque characteristics. Epidemiological data on qualitative aspects of the coronary atherosclerotic process (e.g. plaque progression and destabilization) is missing. Objective: to qualitatively map the epidemiology of atherosclerosis burden in a representative cohort of deceased individuals Methods: this is a systematic, qualitative analysis of atherosclerotic burden in the proximal left coronary artery (LCA) segment of 695 tissue donors (median age 54, range 11-65 years). Based on the cause of death, donors were dichotomized into a non-cardiovascular (non-CVD group) and a cardiovascular disease (CVD) group. Consecutive, 5 mm LCA segments were Movat stained, and the atherosclerotic burden for each segment qualitatively graded (revised AHA-classification). Results: non-CVD and CVD groups show rapid acceleration of atherosclerosis severity after the age of 40; resulting in an almost endemic presence of advanced atherosclerosis in men and women over 40 respectively 50 years. In fact, only 19% of the non-CVD and 6% of the CVD donors over 40 presented with a normal LCA or non-progressive lesion type. The consolidated fibrous calcified plaque (FCP) dominated in both non-CVD and CVD donors over 40. Estimates of atherosclerosis load (i.e. average lesion grade, proportion of FCPs, and average number of FCPs per cross-section were all higher in the CVD group (P-16 , P Conclusions: advanced atherosclerotic disease is endemic in individuals over 40. Dominance of FCP lesions and the higher disease load in CVD donors imply that the atherosclerotic process is repetitive. Abundance of FCPs suggest that complications of plaque rupture are stochastic. This study was in part funded by the European Commission (Cartardis, FP7 HEALTH.2013.2.4.2-1).