Targeted rescue of synaptic plasticity improves cognitive decline in sepsis-associated encephalopathy.

Sepsis-associated encephalopathy (SAE) is a frequent complication of severe systemic infection resulting in delirium, premature death, and long-term cognitive impairment. We closely mimicked SAE in a murine peritoneal contamination and infection (PCI) model. We found long-lasting synaptic pathology in the hippocampus including defective long-term synaptic plasticity, reduction of mature neuronal dendritic spines, and severely affected excitatory neurotransmission. Genes related to synaptic signaling, including the gene for activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) and members of the transcription-regulatory EGR gene family, were downregulated. At the protein level, ARC expression and mitogen-activated protein kinase signaling in the brain were affected. For targeted rescue we used adeno-associated virus-mediated overexpression of ARC in the hippocampus in vivo. This recovered defective synaptic plasticity and improved memory dysfunction. Using the enriched environment paradigm as a non-invasive rescue intervention, we found improvement of defective long-term potentiation, memory, and anxiety. The beneficial effects of an enriched environment were accompanied by an increase in brain-derived neurotrophic factor (BDNF) and ARC expression in the hippocampus, suggesting that activation of the BDNF-TrkB pathway leads to restoration of the PCI-induced reduction of ARC. Collectively, our findings identify synaptic pathomechanisms underlying SAE and provide a conceptual approach to target SAE-induced synaptic dysfunction with potential therapeutic applications to patients with SAE.

Validation of the SACOV-19 score for identifying patients at risk of complicated or more severe COVID-19: a prospective study.

PURPOSE: Identification of patients at risk of complicated or more severe COVID-19 is of pivotal importance, since these patients might require monitoring, antiviral treatment, and hospitalization. In this study, we prospectively evaluated the SACOV-19 score for its ability to predict complicated or more severe COVID-19. METHODS: In this prospective multicenter study, we included 124 adult patients with acute COVID-19 in three German hospitals, who were diagnosed in an early, uncomplicated stage of COVID-19 within 72 h of inclusion. We determined the SACOV-19 score at baseline and performed a follow-up at 30 days. RESULTS: The SACOV-19 score's AUC was 0.816. At a cutoff of > 3, it predicted deterioration to complicated or more severe COVID-19 with a sensitivity of 94% and a specificity of 55%. It performed significantly better in predicting complicated COVID-19 than the random tree-based SACOV-19 predictive model, the CURB-65, 4C mortality, or qCSI scores. CONCLUSION: The SACOV-19 score is a feasible tool to aid decision making in acute COVID-19.

Prediction of COVID-19 deterioration in high-risk patients at diagnosis: an early warning score for advanced COVID-19 developed by machine learning.

PURPOSE: While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization. METHODS: We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16). RESULTS: The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface. CONCLUSION: We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.

Targeting Complement C5a Receptor 1 for the Treatment of Immunosuppression in Sepsis.

Complement factor C5a was originally identified as a powerful promoter of inflammation through activation of the C5a receptor 1 (C5ar1). Recent evidence suggests involvement of C5a not only in pro- but also in anti-inflammatory signaling. The present study aims to unveil the role of C5ar1 as potential therapeutic target in a murine sepsis model. Our study discloses a significantly increased survival in models of mild to moderate but not severe sepsis of C5ar1-deficient mice. The decreased mortality of C5ar1-deficient mice is accompanied by improved pathogen clearance and largely preserved liver function. C5ar1-deficient mice exhibited a significantly increased production of the pro-inflammatory mediator interferon-γ (IFN-γ) and a decreased production of the anti-inflammatory cytokine interleukin-10 (IL-10). Together, these data uncover C5a signaling as a mediator of immunosuppressive processes during sepsis and describe the C5ar1 and related changes of the IFN-γ to IL-10 ratio as markers for the immunological (dys)function accompanying sepsis.

Reprogramming of macrophages employing gene regulatory and metabolic network models.

Upon exposure to different stimuli, resting macrophages undergo classical or alternative polarization into distinct phenotypes that can cause fatal dysfunction in a large range of diseases, such as systemic infection leading to sepsis or the generation of an immunosuppressive tumor microenvironment. Investigating gene regulatory and metabolic networks, we observed two metabolic switches during polarization. Most prominently, anaerobic glycolysis was utilized by M1-polarized macrophages, while the biosynthesis of inosine monophosphate was upregulated in M2-polarized macrophages. Moreover, we observed a switch in the urea cycle. Gene regulatory network models revealed E2F1, MYC, PPARγ and STAT6 to be the major players in the distinct signatures of these polarization events. Employing functional assays targeting these regulators, we observed the repolarization of M2-like cells into M1-like cells, as evidenced by their specific gene expression signatures and cytokine secretion profiles. The predicted regulators are essential to maintaining the M2-like phenotype and function and thus represent potential targets for the therapeutic reprogramming of immunosuppressive M2-like macrophages.

Functional surface proteomic profiling reveals the host heat-shock protein A8 as a mediator of Lichtheimia corymbifera recognition by murine alveolar macrophages.

Mucormycosis is an emergent, fatal fungal infection of humans and warm-blooded animals caused by species of the order Mucorales. Immune cells of the innate immune system serve as the first line of defence against inhaled spores. Alveolar macrophages were challenged with the mucoralean fungus Lichtheimia corymbifera and subjected to biotinylation and streptavidin enrichment procedures followed by LC-MS/MS analyses. A total of 28 host proteins enriched for binding to macrophage-L. corymbifera interaction. Among those, the HSP70-family protein Hspa8 was found to be predominantly responsive to living and heat-killed spores of a virulent and an attenuated strain of L. corymbifera. Confocal scanning laser microscopy of infected macrophages revealed colocalization of Hspa8 with phagocytosed spores of L. corymbifera. The amount of detectable Hspa8 was dependent on the multiplicity of infection. Incubation of alveolar macrophages with an anti-Hspa8 antibody prior to infection reduced their capability to phagocytose spores of L. corymbifera. In contrast, anti-Hspa8 antibodies did not abrogate the phagocytosis of Aspergillus fumigatus conidia by macrophages. These results suggest an important contribution of the heat-shock family protein Hspa8 in the recognition of spores of the mucoralean fungus L. corymbifera by host alveolar macrophages and define a potential immunomodulatory therapeutic target.

Linking aberrant chromatin features in chronic lymphocytic leukemia to transcription factor networks.

In chronic lymphocytic leukemia (CLL), a diverse set of genetic mutations is embedded in a deregulated epigenetic landscape that drives cancerogenesis. To elucidate the role of aberrant chromatin features, we mapped DNA methylation, seven histone modifications, nucleosome positions, chromatin accessibility, binding of EBF1 and CTCF, as well as the transcriptome of B cells from CLL patients and healthy donors. A globally increased histone deacetylase activity was detected and half of the genome comprised transcriptionally downregulated partially DNA methylated domains demarcated by CTCF CLL samples displayed a H3K4me3 redistribution and nucleosome gain at promoters as well as changes of enhancer activity and enhancer linkage to target genes. A DNA binding motif analysis identified transcription factors that gained or lost binding in CLL at sites with aberrant chromatin features. These findings were integrated into a gene regulatory enhancer containing network enriched for B-cell receptor signaling pathway components. Our study predicts novel molecular links to targets of CLL therapies and provides a valuable resource for further studies on the epigenetic contribution to the disease.

Modelling TERT regulation across 19 different cancer types based on the MIPRIP 2.0 gene regulatory network approach.

BACKGROUND: Reactivation of the telomerase reverse transcriptase gene TERT is a central feature for unlimited proliferation of the majority of cancers. However, the underlying regulatory processes are only partly understood. RESULTS: We assembled regulator binding information from serveral sources to construct a generic human and mouse gene regulatory network. Advancing our "Mixed Integer linear Programming based Regulatory Interaction Predictor" (MIPRIP) approach, we identified the most common and cancer-type specific regulators of TERT across 19 different human cancers. The results were validated by using the well-known TERT regulation by the ETS1 transcription factor in a subset of melanomas with mutations in the TERT promoter. Our improved MIPRIP2 R-package and the associated generic regulatory networks are freely available at https://github.com/KoenigLabNM/MIPRIP. CONCLUSION: MIPRIP 2.0 identified common as well as tumor type specific regulators of TERT. The software can be easily applied to transcriptome datasets to predict gene regulation for any gene and disease/condition under investigation.

Loss of CCAAT-enhancer-binding protein alpha (CEBPA) is linked to poor prognosis in PTEN deleted and TMPRSS2:ERG fusion type prostate cancers.

BACKGROUND: The transcription factor CCAAT-enhancer-binding protein alpha (CEBPA) is a crucial regulator of cell proliferation and differentiation. Expression levels of CEBPA have been suggested to be prognostic in various tumor types. METHODS: Here, we analyzed the immunohistochemical expression of CEBPA in a tissue microarray containing more than 17 000 prostate cancer specimens with annotated clinical and molecular data including for example TMPRSS2:ERG fusion and PTEN deletion status. RESULTS: Normal prostate glands showed moderate to strong CEBPA staining, while CEBPA expression was frequently reduced (40%) or lost (30%) in prostate cancers. Absence of detectable CEBPA expression was markedly more frequent in ERG negative (45%) as compared to ERG positive cancers (20%, P < 0.0001). Reduced CEBPA expression was linked to unfavorable phenotype (P < 0.0001) and poor prognosis (P = 0.0008). Subgroup analyses revealed, that the prognostic value of CEBPA loss was entirely driven by tumors carrying both TMPRSS2:ERG fusions and PTEN deletions. In this subgroup, CEBPA loss was tightly linked to advanced tumor stage (P < 0.0001), high Gleason grade (P < 0.0001), positive nodal stage (0.0003), and early biochemical recurrence (P = 0.0007), while these associations were absent or markedly diminished in tumors with normal PTEN copy numbers and/or absence of ERG fusion. CONCLUSIONS: CEBPA is down regulated in about one third of prostate cancers, but the clinical impact of CEBPA loss is strictly limited to the subset of about 10% prostate cancers carrying both ERG fusion and deletions of the PTEN tumor suppressor. Our findings challenge the concept that prognostic molecular markers may be generally applicable to all prostate cancers.

Temporal progression of gene regulation of peripheral white blood cells explains gender dimorphism of critically ill patients after trauma.

BACKGROUND: The immune response of the critically ill after severe trauma is sex-specific and may explain the different progression of the disease. This may be explained by a different gene regulatory program of their peripheral immune cells. We investigated the progression of the transcription profiles of peripheral immune cells of the patients to elucidate their distinct physiological response and clinical course. METHODS: We compared transcription profiles of whole blood of male and female patients from a larger longitudinal study of critically ill patients after trauma. We developed a statistical analysis pipeline that synchronized the time lapse of the profiles based on the temporal severity score of each patient. RESULTS: This enabled to categorize the temporal progression of the disease into two pre-acute, an acute and two post-acute phases. Comparing gene regulation of male and female patients at each phase, we identified distinctively regulated molecular processes mainly in the immune response, but also in the regulation of metabolism allowing to cluster these discriminative gene sets into sets of highly related cellular processes. Compared to male patients and healthy controls, female patients showed upregulation of gene sets of innate immunity in the early phase, upregulation of wound healing processes during the acute phase and upregulation of adaptive immunity in the late phase indicating early recovery. In turn, during the pre-acute and acute phase, male patients showed less suppression of gene sets coding for enzymes of energy metabolism and anabolism, most prominently the tricarboxylic acid cycle and ß-oxidation, and cellular maintenance, such as cell cycle, DNA replication and damage response, and RNA metabolism. CONCLUSIONS: A stronger innate immune response at the very early phase of the disease may support early clearance of the pathogen and its associated molecular patterns. Upregulation of wound healing processes may explain reduced multiple organ failure during the acute phase. Down regulated energy metabolism during the acute phase may make female patients less susceptible to oxidative stress, the upregulated adaptive immune system reflects an earlier recovery and rebuilding of the adaptive immune system that may protect them from secondary infections. Follow up studies need to be performed confirming these observations experimentally.

Macrolide combination therapy for patients hospitalised with community-acquired pneumonia? An individualised approach supported by machine learning.

BACKGROUND: The role of macrolide/ß-lactam combination therapy in community-acquired pneumonia (CAP) of moderate severity is a matter of debate. Macrolides expand the coverage to atypical pathogens and attenuate pulmonary inflammation, but have been associated with cardiovascular toxicity and drug interactions. We developed a decision tree based on aetiological and clinical parameters, which are available ex ante to support a personalised decision for or against macrolides for the best clinical outcome of the individual patient. METHODS: We employed machine learning in a cross-validation scheme based on a well-balanced selection of 4898 patients after propensity score matching to data available on admission of 6440 hospitalised patients with moderate severity (non-intensive care unit patients) from the observational, prospective, multinational CAPNETZ study. We aimed to improve the primary outcome of 180-day survival. RESULTS: We found a simple decision tree of patient characteristics comprising chronic cardiovascular and chronic respiratory comorbidities as well as leukocyte counts in the respiratory secretion at enrolment. Specifically, we found that patients without cardiovascular or patients with respiratory comorbidities and high leukocyte counts in the respiratory secretion benefit from macrolide treatment. Patients identified to be treated in compliance with our treatment suggestion had a lower mortality of 27% (OR 1.83, 95% CI 1.48-2.27; p<0.001) compared to the observed standard of care. CONCLUSION: Stratifying macrolide treatment in patients following a simple treatment rule may lead to considerably reduced mortality in CAP. A future randomised controlled trial confirming our result is necessary before implementing this rule into the clinical routine.

Streptococcus pneumoniae From Patients With Hemolytic Uremic Syndrome Binds Human Plasminogen via the Surface Protein PspC and Uses Plasmin to Damage Human Endothelial Cells.

Pneumococcal hemolytic uremic syndrome (HUS) in children is caused by infections with Streptococcus pneumoniae. Because endothelial cell damage is a hallmark of HUS, we studied how HUS-inducing pneumococci derived from infant HUS patients during the acute phase disrupt the endothelial layer. HUS pneumococci efficiently bound human plasminogen. These clinical isolates of HUS pneumococci efficiently bound human plasminogen via the bacterial surface proteins Tuf and PspC. When activated to plasmin at the bacterial surface, the active protease degraded fibrinogen and cleaved C3b. Here, we show that PspC is a pneumococcal plasminogen receptor and that plasmin generated on the surface of HUS pneumococci damages endothelial cells, causing endothelial retraction and exposure of the underlying matrix. Thus, HUS pneumococci damage endothelial cells in the blood vessels and disturb local complement homeostasis. Thereby, HUS pneumococci promote a thrombogenic state that drives HUS pathology.

Acrofacial Dysostosis, Cincinnati Type, a Mandibulofacial Dysostosis Syndrome with Limb Anomalies, Is Caused by POLR1A Dysfunction.

We report three individuals with a cranioskeletal malformation syndrome that we define as acrofacial dysostosis, Cincinnati type. Each individual has a heterozygous mutation in POLR1A, which encodes a core component of RNA polymerase 1. All three individuals exhibit varying degrees of mandibulofacial dysostosis, and two additionally have limb anomalies. Consistent with this observation, we discovered that polr1a mutant zebrafish exhibited cranioskeletal anomalies mimicking the human phenotype. polr1a loss of function led to perturbed ribosome biogenesis and p53-dependent cell death, resulting in a deficiency of neural-crest-derived skeletal precursor cells and consequently craniofacial anomalies. Our findings expand the genotypic and phenotypic heterogeneity of congenital acrofacial disorders caused by disruption of ribosome biogenesis.

Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments.

Fungal biomarker discovery by integration of classifiers.

BACKGROUND: The human immune system is responsible for protecting the host from infection. However, in immunocompromised individuals the risk of infection increases substantially with possible drastic consequences. In extreme, systemic infection can lead to sepsis which is responsible for innumerous deaths worldwide. Amongst its causes are infections by bacteria and fungi. To increase survival, it is mandatory to identify the type of infection rapidly. Discriminating between fungal and bacterial pathogens is key to determine if antifungals or antibiotics should be administered, respectively. For this, in situ experiments have been performed to determine regulation mechanisms of the human immune system to identify biomarkers. However, these studies led to heterogeneous results either due different laboratory settings, pathogen strains, cell types and tissues, as well as the time of sample extraction, to name a few. METHODS: To generate a gene signature capable of discriminating between fungal and bacterial infected samples, we employed Mixed Integer Linear Programming (MILP) based classifiers on several datasets comprised of the above mentioned pathogens. RESULTS: When combining the classifiers by a joint optimization we could increase the consistency of the biomarker gene list independently of the experimental setup. An increase in pairwise overlap (the number of genes that overlap in each cross-validation) of 43% was obtained by this approach when compared to that of single classifiers. The refined gene list was composed of 19 genes and ranked according to consistency in expression (up- or down-regulated) and most of them were linked either directly or indirectly to the ERK-MAPK signalling pathway, which has been shown to play a key role in the immune response to infection. Testing of the identified 12 genes on an unseen dataset yielded an average accuracy of 83%. CONCLUSIONS: In conclusion, our method allowed the combination of independent classifiers and increased consistency and reliability of the generated gene signatures.

SHORT syndrome with partial lipodystrophy due to impaired phosphatidylinositol 3 kinase signaling.

The phosphatidylinositol 3 kinase (PI3K) pathway regulates fundamental cellular processes such as metabolism, proliferation, and survival. A central component in this pathway is the p85α regulatory subunit, encoded by PIK3R1. Using whole-exome sequencing, we identified a heterozygous PIK3R1 mutation (c.1945C>T [p.Arg649Trp]) in two unrelated families affected by partial lipodystrophy, low body mass index, short stature, progeroid face, and Rieger anomaly (SHORT syndrome). This mutation led to impaired interaction between p85α and IRS-1 and reduced AKT-mediated insulin signaling in fibroblasts from affected subjects and in reconstituted Pik3r1-knockout preadipocytes. Normal PI3K activity is critical for adipose differentiation and insulin signaling; the mutated PIK3R1 therefore provides a unique link among lipodystrophy, growth, and insulin signaling.

Femoral facial syndrome associated with a de novo complex chromosome 2q37 rearrangement.

The femoral facial syndrome (FFS) is a rare congenital anomaly syndrome characterized by bilateral femoral hypoplasia and facial dysmorphism. The etiology of FFS is currently unknown but maternal/gestational diabetes has been proposed as a strong risk factor for syndromic femoral hypoplasia. In affected children born to non-diabetic mothers, a genetic contribution to FFS is suspected; however, no chromosomal anomalies or gene mutations have been identified so far. Here, we report on a girl with FFS and a de novo complex chromosome rearrangement of terminal chromosome 2q37.2. Radiographs of the pelvis and lower limbs showed bilateral shortening and bowing of the femur and radiographs of hands and feet revealed a brachydactyly type E (BDE). Using high resolution array-CGH, qPCR, and FISH, we detected a ~1.9 Mb duplication in the chromosomal region 2q37.2 and a ~5.4 Mb deletion on chromosome 2q37.3 that were absent in the parents. The duplication contains six genes and the deletion encompasses 68 genes; the latter has previously been shown to cause BDE (through haploinsufficiency for HDAC4) but not femoral hypoplasia. Therefore, we propose that the duplication 2q37.2 could be causative for the femur phenotype. To the best of our knowledge, our report is the first to propose a genetic cause in a case of FFS.

Functional testing strategy for coding genetic variants of unclear significance in MLH1 in Lynch syndrome diagnosis.

Lynch syndrome is caused by inactivating mutations in the MLH1 gene, but genetic variants of unclear significance frequently preclude diagnosis. Functional testing can reveal variant-conferred defects in gene or protein function. Based on functional defect frequencies and clinical applicability of test systems, we developed a functional testing strategy aimed at efficiently detecting pathogenic defects in coding MLH1 variants. In this strategy, tests of repair activity and expression are prioritized over analyses of subcellular protein localization and messenger RNA (mRNA) formation. This strategy was used for four unclear coding MLH1 variants (p.Asp41His, p.Leu507Phe, p.Gln689Arg, p.Glu605del + p.Val716Met). Expression was analyzed using a transfection system, mismatch repair (MMR) activity by complementation in vitro, mRNA formation by reverse transcriptase-PCR in carrier lymphocyte mRNA, and subcellular localization with dye-labeled fusion constructs. All tests included clinically meaningful controls. The strategy enabled efficient identification of defects in two unclear variants: the p.Asp41His variant showed loss of MMR activity, whereas the compound variant p.Glu605del + p.Val716Met had a defect of expression. This expression defect was significantly stronger than the pathogenic expression reference variant analyzed in parallel, therefore the defect of the compound variant is also pathogenic. Interestingly, the expression defect was caused additively by both of the compound variants, at least one of which is non-pathogenic when occurring by itself. Tests were neutral for p.Leu507Phe and p.Gln689Arg, and the results were consistent with available clinical data. We finally discuss the improved sensitivity and efficiency of the applied strategy and its limitations in analyzing unclear coding MLH1 variants.

Evaluation of reverse phase protein array (RPPA)-based pathway-activation profiling in 84 non-small cell lung cancer (NSCLC) cell lines as platform for cancer proteomics and biomarker discovery.

The reverse phase protein array (RPPA) approach was employed for a quantitative analysis of 71 cancer-relevant proteins and phosphoproteins in 84 non-small cell lung cancer (NSCLC) cell lines and by monitoring the activation state of selected receptor tyrosine kinases, PI3K/AKT and MEK/ERK1/2 signaling, cell cycle control, apoptosis, and DNA damage. Additional information on NSCLC cell lines such as that of transcriptomic data, genomic aberrations, and drug sensitivity was analyzed in the context of proteomic data using supervised and non-supervised approaches for data analysis. First, the unsupervised analysis of proteomic data indicated that proteins clustering closely together reflect well-known signaling modules, e.g. PI3K/AKT- and RAS/RAF/ERK-signaling, cell cycle regulation, and apoptosis. However, mutations of EGFR, ERBB2, RAF, RAS, TP53, and PI3K were found dispersed across different signaling pathway clusters. Merely cell lines with an amplification of EGFR and/or ERBB2 clustered closely together on the proteomic, but not on the transcriptomic level. Secondly, supervised data analysis revealed that sensitivity towards anti-EGFR drugs generally correlated better with high level EGFR phosphorylation than with EGFR abundance itself. High level phosphorylation of RB and high abundance of AURKA were identified as candidates that can potentially predict sensitivity towards the aurora kinase inhibitor VX680. Examples shown demonstrate that the RPPA approach presents a useful platform for targeted proteomics with high potential for biomarker discovery. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.