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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.

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.

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.

Background and Aims: Oncostatin M (OSM) signaling is implicated in atherosclerosis, however the mechanism remains unclear. We investigated the impact of common genetic variants in OSM and its receptors, OSMR and LIFR, on overall plaque vulnerability, plaque phenotype, intraplaque OSMR and LIFR expression, coronary artery calcification burden and cardiovascular disease susceptibility.Methods and Results: We queried Genotype-Tissue Expression data and found that rs13168867 (C allele) was associated with decreased OSMR expression and that rs10491509 (A allele) was associated with increased LIFR expression in arterial tissues. No variant was significantly associated with OSM expression.We associated these two variants with plaque characteristics from 1,443 genotyped carotid endarterectomy patients in the Athero-Express Biobank Study. After correction for multiple testing, rs13168867 was significantly associated with an increased overall plaque vulnerability (β = 0.118 ± s.e. = 0.040, p = 3.00 × 10−3, C allele). Looking at individual plaque characteristics, rs13168867 showed strongest associations with intraplaque fat (β = 0.248 ± s.e. = 0.088, p = 4.66 × 10−3, C allele) and collagen content (β = −0.259 ± s.e. = 0.095, p = 6.22 × 10−3, C allele), but these associations were not significant after correction for multiple testing. rs13168867 was not associated with intraplaque OSMR expression. Neither was intraplaque OSMR expression associated with plaque vulnerability and no known OSMR eQTLs were associated with coronary artery calcification burden, or cardiovascular disease susceptibility. No associations were found for rs10491509 in the LIFR locus.Conclusions: Our study suggests that rs1316887 in the OSMR locus is associated with increased plaque vulnerability, but not with coronary calcification or cardiovascular disease risk. It remains unclear through which precise biological mechanisms OSM signaling exerts its effects on plaque morphology. However, the OSM-OSMR/LIFR pathway is unlikely to be causally involved in lifetime cardiovascular disease susceptibility.

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.

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.

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

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 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).

BACKGROUND AND AIMS:With the intention to gain support for the hypothesis that incident ischemic complications of atherosclerotic disease involve a stochastic aspect, we performed a histological, qualitative evaluation of the epidemiology of coronary atherosclerotic disease in a cohort of aortic valve donors. PATIENTS AND METHODS:Donors (n = 695, median age 54, range 11-65 years) were dichotomized into a non-cardiovascular (non-CVD) and a cardiovascular disease death (CVD) group. Consecutive 5 mm proximal left coronary artery segments were Movat stained, and the atherosclerotic burden for each segment was graded (revised AHA-classification). RESULTS:Non-CVD and CVD groups showed steep increase of atherosclerosis severity beyond the age of 40, resulting in an endemic presence of advanced atherosclerosis in men over 40 and women over 50 years. In fact, only 19% of the non-CVD and 6% of the CVD donors over 40 years were classified with a normal LCA or a so called non-progressive lesion type. Fibrous calcified plaques (FCP), the consolidated remnants of earlier ruptured lesions, dominated in both non-CVD and CVD donors. Estimates of the atherosclerosis burden (i.e. average lesion grade, proportion of FCPs, and average number of FCPs per cross-section) were all higher in the CVD group (p

Few biomarkers progress from discovery to become validated tools or diagnostics. To bridge this gap, three European biomedical research infrastructures — EATRIS-ERIC (focused on translational medicine), BBMRI-ERIC (focused on biobanking) and ELIXIR (focused on data sharing) — are paving the way to developing and sharing best practices for biomarker validation. Few biomarkers progress from discovery to become validated tools or diagnostics. To bridge this gap, three European biomedical research infrastructures — EATRIS-ERIC (focused on translational medicine), BBMRI-ERIC (focused on biobanking) and ELIXIR (focused on data sharing) — are paving the way to developing and sharing best practices for biomarker validation.

Biomarkers have become a buzzword in the biomedical field and are expected to enable much innovation in the years to come. Their predominant promise resides in two application areas: translational medicine and personalized medicine, whose activities are strongly aimed to improve the management of disease. However, to many the ultimate potential of biomarkers is to change disease management (reactive mode) into health management (preventive mode), in other words keeping healthy people healthy rather than curing diseased patients. Key drivers for such change are molecular biomarkers that allow earlier and more sensitive detection of onset of disease, better molecular classification of disease, improved personalized treatment, and improved monitoring of treatment effects. Many lessons can be learned from pharmaceutical industry where for considerable time biomarkers have been key drivers in drug development projects. This experience in biomarker discovery, validation, development and implementation can potentially be applied to other areas of human medicine including nutriceuticals. We here review the role of biomarkers in pharmaceutical drug development, focussing on translational and personalized medicine, and discuss trends, challenges and opportunities in this field.

Item does not contain fulltext To identify response biomarkers for pharmaceutical treatment of multiple sclerosis, we induced experimental autoimmune encephalomyelitis (EAE) in rats and treated symptomatic animals with minocycline. Cerebrospinal fluid (CSF) samples were collected 14 days after EAE induction at the peak of neurological symptoms, and proteomics analysis was performed using nano-LC-Orbitrap mass spectrometry. Additionally, the minocycline concentration in CSF was determined using quantitative matrix-assisted laser desorption/ionization-triple-quadrupole tandem mass spectrometry (MALDI-MS/MS) in the selected reaction monitoring (SRM) mode. Fifty percent of the minocycline-treated EAE animals did not show neurological symptoms on day 14 ("responders"), while the other half displayed neurological symptoms ("nonresponders"), indicating that minocycline delayed disease onset and attenuated disease severity in some, but not all, animals. Neither CSF nor plasma minocycline concentrations correlated with the onset of symptoms or disease severity. Analysis of the proteomics data resulted in a list of 20 differentially abundant proteins between the untreated animals and the responder group of animals. Two of these proteins, complement C3 and carboxypeptidase B2, were validated by quantitative LC-MS/MS in the SRM mode. Differences in the CSF proteome between untreated EAE animals and minocycline-treated responders were similar to the differences between minocycline-treated responders and nonresponders (70% overlap). Six proteins that remained unchanged in the minocycline-treated animals but were elevated in untreated EAE animals may be related to the mechanism of action of minocycline.

Multiple Sclerosis (MScl) is a neurodegenerative disease of the CNS, associated with chronic neuroinflammation. Cerebrospinal fluid (CSF), being in closest interaction with CNS, was used to profile neuroinflammation to discover disease-specific markers. We used the commonly accepted animal model for the neuroinflammatory aspect of MScl: the experimental autoimmune/allergic encephalomyelitis (EAR). A combination of advanced (1)H NMR spectroscopy and pattern recognition methods was used to establish the metabolic profile of CSF of EAE-affected rats (representing neuroinflammation) and of two control groups (healthy and peripherally inflamed) to detect specific markers for early neuroinflammation. We found that the CSF metabolic profile for neuroinflammation is distinct from healthy and peripheral inflammation and characterized by changes in concentrations of metabolites such as creatine, arginine, and lysine. Using these disease-specific markers, we were able to detect early stage neuroinflammation, with high accuracy in a second independent set of animals. This confirms the predictive value of these markers. These findings from the EAE model may help to develop a molecular diagnosis for the early stage MScl in humans.

The pharmaceutical industry must find ways to improve the unacceptably high attrition rate during drug development. Clearly, pharma has moved away from treat-and-see testing of new drugs in patients, with a strong current focus on generating translational biomarkers early in the research process to enable more predictive evaluation of drug action in clinical trials. Underlying such a translational medicine approach is the intensive search for and use of high-quality biomarkers indicative of successful drug target engagement, pharmacological effects, efficacy or safety. This review outlines our rational question-based drug development strategy in which biomarker data drive decisions on which drug candidates to progress to clinical testing.