Asthma and COPD proteomics: Current approaches and future directions

Although asthma and chronic obstructive pulmonary disease COPD represent the two most common chronic respiratory diseases worldwide, the mechanisms underlying their pathobiology need to be further elucidated. Presently, differentiation of asthma and COPD are largely based on clinical and lung function parameters. However, the complexity of these multifactorial diseases may lead to misclassification and to inappropriate management strategies. Recently, tremendous progress in MS has extended the sensitivity, accuracy, and speed of analysis, enabling the identification of thousands of proteins per experiment. Beyond identification, MS has also greatly implemented quantitation issues allowing to assess qualitative–quantitative differences in protein profiles of different samples, in particular diseased versus normal. Herein, we provide a summary of recent proteomics-based investigations in the field of asthma/COPD, highlighting major issues related to sampling and processing procedures for proteomic analyses of specific airway and parenchymal specimens (induced sputum, exhaled breath condensate, epithelial lining fluid, bronchoalveolar and nasal lavage fluid), as well as blood-derived specimen (plasma and serum). Within such a context, together with current difficulties and limitations mainly due to lack of general standardization in preanalytical sampling procedure, our discussion will focus on the challenges and possible benefits of proteomic studies in phenotypic stratification of asthma and COPD.     

Is multidimensional scaling suitable for mapping the input respiratory impedance in subjects and patients?

This paper presents the application of multidimensional scaling (MDS) analysis to data emerging from noninvasive lung function tests, namely the input respiratory impedance. The aim is to obtain a geometrical mapping of the diseases in a 3D space representation, allowing analysis of (dis)similarities between subjects within the same pathology groups, as well as between the various groups. The adult patient groups investigated were healthy, diagnosed chronic obstructive pulmonary disease (COPD) and diagnosed kyphoscoliosis, respectively. The children patient groups were healthy, asthma and cystic fibrosis. The results suggest that MDS can be successfully employed for mapping purposes of restrictive (kyphoscoliosis) and obstructive (COPD) pathologies. Hence, MDS tools can be further examined to define clear limits between pools of patients for clinical classification, and used as a training aid for medical traineeship.     

Proteome analysis of biological fluids from autoimmune-rheumatological disorders

Autoimmune-rheumatological diseases are worldwide distributed disorders and represent a complex array of illnesses characterized by autoreactivity (reactivity against self-antigens) of T-B lymphocytes and by the synthesis of autoantibodies crucial for diagnosis (biomarkers). Yet, the effects of the autoimmune chronic inflammation on the infiltrated tissues and organs generally lead to profound tissue and organ damage with loss of function (i.e., lung, kidney, joints, exocrine glands). Although progresses have been made on the knowledge of these disorders, much still remains to be investigated on their pathogenesis and identification of new biomarkers useful in clinical practice. The rationale of using proteomics in autoimmune-rheumatological diseases has been the unmet need to collect, from biological fluids that are easily obtainable, a summary of the final biochemical events that represent the effects of the interplay between immune cells, mesenchymal cells and endothelial cells. Proteomic analysis of these fluids shows encouraging results and in this review, we addressed four major autoimmune-rheumatological diseases investigated through proteomic techniques and provide evidence-based data on the highlights obtained in systemic sclerosis, primary and secondary Sjogren's syndrome, systemic lupus erythematosus and rheumatoid arthritis.     

Untargeted metabolomics of human plasma reveal lipid markers unique to chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis

Chronic obstructive pulmonary disease (COPD) is characterised by airway inflammation and progressive airflow limitation, whereas idiopathic pulmonary fibrosis (IPF) is characterised by a restrictive pattern due to fibrosis and impaired gas exchange. We undertook metabolomic analysis of blood samples in IPF, COPD and healthy controls (HC) to determine differences in circulating molecules and identify novel pathogenic pathways. An untargeted metabolomics using an ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometer (UHPLC-QTOF-MS) was performed to profile plasma of patients with COPD (n = 21), and IPF (n = 24) in comparison to plasma from healthy controls (HC; n = 20). The most significant features were identified using multiple database matching. One-way ANOVA and variable importance in projection (VIP) scores were also used to highlight metabolites that influence the specific disease groups. Non-polar metabolites such as fatty acids (FA) and membrane lipids were well resolved and a total of 4805 features were identified. The most prominent metabolite composition differences in lipid mediators identified at ∼2–3 fold higher in both diseases compared to HC were palmitoleic acid, oleic acid and linoleic acid; and dihydrotestosterone was lower in both diseases. We demonstrated that COPD and IPF were characterised by systemic changes in lipid constituents such as essential FA sampled from circulating plasma.     

Urine proteomics in kidney and urogenital diseases: Moving towards clinical applications

To date, multiple biomarker discovery studies in urine have been conducted. Nevertheless, the rate of progression of these biomarkers to qualification and even more clinical application is extremely low. The scope of this article is to provide an overview of main clinically relevant proteomic findings from urine focusing on kidney diseases, bladder and prostate cancers. In addition, approaches for promoting the use of urine in clinical proteomics including potential means to facilitate the validation of existing promising findings (biomarker candidates identified from previous studies) and to increase the chances for success for the identification of new biomarkers are discussed.     

Applications of protein microarrays for biomarker discovery

The search for new biomarkers for diagnosis, prognosis, and therapeutic monitoring of diseases continues in earnest despite dwindling success at finding novel reliable markers. Some of the current markers in clinical use do not provide optimal sensitivity and specificity, with the prostate cancer antigen (PSA) being one of many such examples. The emergence of proteomic techniques and systems approaches to study disease pathophysiology has rekindled the quest for new biomarkers. In particular the use of protein microarrays has surged as a powerful tool for large-scale testing of biological samples. Approximately half the reports on protein microarrays have been published in the last two years especially in the area of biomarker discovery. In this review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers.     

Ensembles of protein termini and specific proteolytic signatures as candidate biomarkers of disease

Early accurate diagnosis and personalized treatment are essential in order to treat complex or fatal diseases such as cancer and autoimmune, cardiovascular and neurodegenerative diseases. To realize this vision, new diagnostic and prognostic biomarkers are urgently required. MS-based proteomics is the most promising approach for protein biomarker identification, but suffers in clinical translation of biomarker candidates that show only quantitative differences from normal tissue. Indeed, success in translating proteomic data to biomarkers in the clinic has been disappointing. Here, we propose that protein termini provide a new opportunity for biomarker discovery due to qualitative differences in intact and new protein termini between diseased and normal tissues. Altered proteolysis occurs in most pathologies. Disease- and process-specific protein modifications, including proteolytic processing and subsequent modification of the terminal amino acids, frequently lead to altered protein activity that plays key roles in the disease process. Thus, mapping of ensembles of characteristic protein termini provides a proteolytic signature of high information content that shows both quantitative and most importantly qualitative differences in different diseases and stage of disease. These unique protein biomarkers have the added benefit of being mechanistically informative by revealing the activity state of the bioactive protein. Moreover, proteome-wide isolation of protein termini leads to generalized sample simplification, thereby enabling up to three orders of magnitude lower LODs compared to traditional shotgun proteomic approaches. We introduce the potential of protein termini for biomarker discovery, briefly review methods enabling large-scale studies of protein termini, and discuss how these may be integrated into a termini-oriented biomarker discovery pipeline from discovery to clinical application.     

Bronchoalveolar lavage fluid proteomic patterns of sulfur mustard-exposed patients

Sulfur mustard is an alkylating agent that reacts with ocular, respiratory, cutaneous, and bone marrow tissues. Main late respiratory complications are chronic obstructive pulmonary disease, bronchiectasis, asthma, and bronchiolitis obliterans. The aim of the present study was to identify differentially expressed proteins in bronchoalveolar lavage (BAL) fluid of control healthy and sulfur mustard-exposed lung disease patients. The BAL protein profile of ten healthy and 30 exposed patients with mild, moderate, and severe conditions (ten males in each group) were separated with 2-D SDS-PAGE and differentially expressed protein spots were successfully identified with MALDI TOF TOF MS. Among the differentially expressed proteins we observed a significant increase in vitamin D binding protein isoforms, haptoglobin isoforms, and fibrinogen especially in exposed moderate and severe lung diseases patients (p<0.01). Moreover, compared with healthy controls, significant decreases was noted in calcyphosine, surfactant protein A, and transthyretin in these patients (p<0.01). Apolipoprotein A1 was detected in all patients' BAL fluid but none of the healthy controls. Furthermore, S100 calcium-binding protein A8 was only detected in BAL fluid of moderate and severe groups. These findings will be useful to improve current methods of monitoring and helps to identify new therapeutic targets for treatment of this complicated illness.     

Vascular proteomics

The characterization of patients with acute coronary syndromes (ACS) at the molecular and cellular levels provides a novel vision for understanding the pathological and clinical expression of the disease. Recent advances in proteomic technologies permit the evaluation of systematic changes in protein expression in many biological systems and have been extensively applied to cardiovascular diseases (CVD). The cardiovascular system is in permanent intimate contact with blood, making blood-based biomarker discovery a particularly worthwhile approach. Thus, proteomics can potentially yield novel biomarkers reflecting CVD, establish earlier detection strategies, and monitor response to therapy. Here we review the different proteomic strategies used in the study of atherosclerosis and the novel proteins differentially expressed and secreted by atherosclerotic lesions which constitute novel potential biomarkers (HSP-27, Cathepsin D). Special attention is paid to MS-Imaging of atheroma plaque and the generation, for the first time, of 2-D images of lipids, showing the distribution of these molecules in the different areas of the atherosclerotic lesions. In addition new potential biomarkers have been identified in plasma (amyloid A1α, transtherytin), circulating cells (protein profile in monocytes from ACS patients) and individual cells constituents of atheroma plaques (endothelial, VSMC, macrophages) which provide novel insights into vascular pathophysiology.     

Grand rounds in proteomics at the FDA white oak, silver spring, MD, USA, april 3, 2007

The application of proteomics in drug development could be a major source of novel biomarkers to improve the efficacy and safety of new drugs. Training of US Food and Drug Administration (FDA) reviewers on current applications of proteomics is important for the future review of proteomic data. A Grand Rounds in Proteomics was held on April 3, 2007 at the FDA in White Oak, Silver Spring, MD, USA. The goal of this activity was to contribute to reviewer training as well as to generate discussions regarding the readiness of proteomic platforms in drug development, similar in scope to applications in genomics and metabolomics. Several speakers from industry and academia presented data on proteomic applications in drug development (meeting agenda available in the Supporting Information). An additional goal of this meeting was to encourage proteomic data submissions within the Voluntary eXploratory Data Submissions (VXDS) at the FDA. VXDS meetings represent key venues for exchange between the FDA and sponsors of scientific and clinical data on exploratory biomarkers. The FDA has received a limited number of VXDS submissions containing proteomic data. This meeting was an opportunity to identify possible areas in proteomics where future VXDS submissions may be received. Voluntary submissions have been transformed into regulatory submissions in genomics, and a similar path may also be followed by proteomic data in the future. Proteomic biomarkers may also be suitable for submission to the Pilot Process for Biomarker Qualification at the FDA.     

Capillary zone electrophoresis on-line coupled to mass spectrometry: A perspective application for clinical proteomics

Clinical proteomics, a rapidly growing field, intends to use specific diagnostic proteomic/peptidomic markers for initial diagnosis or prognosis of the progression of various diseases. Analyses of disease-associated markers in defined biological samples can provide valuable molecular diagnostic information for these diseases. This approach relies on sensitive and highly standardized modern analytical techniques. In the recent years, one of these technologies, CZE online coupled to MS (CZE-MS), has been increasingly used for the detection of peptide biomarkers (<20 kDa) in body fluids such as urine. This review presents the most relevant urinary proteomic studies addressing the application of CZE-MS in clinically relevant biomarker research between the years 2006 and 2014.     

Proteomics in chronic kidney disease: The issues clinical nephrologists need an answer for

A growing number of patients are recognised to have chronic kidney disease (CKD). However, only a minority will progress to end-stage renal disease requiring dialysis or transplantation. Currently available diagnostic and staging tools frequently fail to identify those at higher risk of progression or death. Furthermore within specific disease entities there are shortcomings in the prediction of the need for therapeutic interventions or the response to different forms of therapy. Kidney and urine proteomic biomarkers are considered as promising diagnostic tools to predict CKD progression early in diabetic nephropathy, facilitating timely and selective intervention that may reduce the related health-care expenditures. However, independent groups have not validated these findings and the technique is not currently available for routine clinical care. Furthermore, there are gaps in our understanding of predictors of progression or need for therapy in non-diabetic CKD. Presumably, a combination of tissue and urine biomarkers will be more informative than individual markers. This review identifies clinical questions in need of an answer, summarises current information on proteomic biomarkers and CKD, and describes the European Kidney and Urine Proteomics initiative that has been launched to carry out a clinical study aimed at identifying urinary proteomic biomarkers distinguishing between fast and slow progressors among patients with biopsy-proven primary glomerulopathies.     

Proteomics as a research tool in clinical and experimental ophthalmology

It is estimated that 37 million people worldwide suffer from blindness and 124 million people have impaired vision. While the relatively recently developed therapies, antivascular endothelial growth factor inhibitors for the treatment of age-related macular degeneration, and prostaglandin analogues for the treatment of glaucoma are beneficial for some patients, there are many individuals with sight-threatening diseases for whom no effective pharmacological therapy is available. For many of these diseases, the molecular mechanisms remain to be comprehensively elucidated, thus precluding the design of successful therapies against specific pathological targets. The current review summarises recent attempts to elucidate molecular mechanisms of ocular diseases, including diabetic retinal disease, age-related macular degeneration and inherited blindness using proteomic methodologies. A novel hypothesis can be generated from global protein expression analysis of disease tissue, which can then be addressed with cellular and in vivo functional studies. For example, the identification of extracellular carbonic anhydrase from the vitreous of diabetic retinopathy patients using MS based proteomics led to the elucidation of a new pathway involved in intraretinal edema, which could be inhibited by a number of agents targeting different proteins in this pathway in relevant animal models. The potential of protein biomarkers for diagnosis and the identification of novel disease mechanisms are also discussed.     

Diagnosis of hypercritical chronic pulmonary disorders using dense convolutional network through chest radiography

Multimedia Tools and Applications - Lung-related ailments are prevalent all over the world which majorly includes asthma, chronic obstructive pulmonary disease (COPD), tuberculosis, pneumonia,...     

Quantitative proteomic approaches for biomarker discovery

The rapid advances in proteomic technologies have made possible systematic analysis of hundreds to thousands of proteins in clinical samples with the promise of uncovering novel protein biomarkers for various disease conditions. We will discuss in this review article current MS and protein chip-based quantitative proteomic approaches and their application in biomarker discovery. The emphasis will be placed on new quantification strategies employing stable isotopic labeling coupled with MS/MS, and antibody-based protein chips and nanodevices. The strength and weakness of each technology are briefly highlighted.     

Biomarkers for AAA: Encouraging steps but clinical relevance still to be delivered

Potential biomarkers have been investigated using proteomic studies in a variety of diseases. Some biomarkers have central roles in both diagnosis and monitoring of various disorders in clinical medicine, such as troponins, brain natriuretic peptide, and C-reactive protein. Although several biomarkers have been suggested in human abdominal aortic aneurysm (AAA), reliable markers have been lacking. In this issue, Moxon et al. [Proteomics Clin Appl. 2014, 8, 762-772] undertook a broad and systematic proteomic approach toward identification of biomarkers in a commonly used AAA mouse model (AAA created by angiotensin-II infusion). In this mouse model, apolipoprotein C1 and matrix metalloproteinase-9 were identified as novel biomarkers of stable AAA. This finding represents an important step forward, toward a clinically relevant role of biomarkers in AAA. This also encourages for further studies toward the identification of biomarkers (or their combinations) that can predict AAA progression and rupture, which would represent a major progress in AAA management and would establish an AAA biomarker as a much anticipated clinical tool.     

Automated recognition of lung diseases in CT images based on the optimum-path forest classifier

The World Health Organization estimated that around 300 million people have asthma, and 210 million people are affected by Chronic Obstructive Pulmonary Disease (COPD). Also, it is estimated that the number of deaths from COPD increased \(30\%\) in 2015 and COPD will become the third major cause of death worldwide by 2030. These statistics about lung diseases get worse when one considers fibrosis, calcifications and other diseases. For the public health system, the early and accurate diagnosis of any pulmonary disease is mandatory for effective treatments and prevention of further deaths. In this sense, this work consists in using information from lung images to identify and classify lung diseases. Two steps are required to achieve these goals: automatically extraction of representative image features of the lungs and recognition of the possible disease using a computational classifier. As to the first step, this work proposes an approach that combines Spatial Interdependence Matrix (SIM) and Visual Information Fidelity (VIF). Concerning the second step, we propose to employ a Gaussian-based distance to be used together with the optimum-path forest (OPF) classifier to classify the lungs under study as normal or with fibrosis, or even affected by COPD. Moreover, to confirm the robustness of OPF in this classification problem, we also considered Support Vector Machines and a Multilayer Perceptron Neural Network for comparison purposes. Overall, the results confirmed the good performance of the OPF configured with the Gaussian distance when applied to SIM- and VIF-based features. The performance scores achieved by the OPF classifier were as follows: average accuracy of \(98.2\%\), total processing time of 117 microseconds in a common personal laptop, and F-score of 95.2% for the three classification classes. These results showed that OPF is a very competitive classifier, and suitable to be used for lung disease classification.

     

Toxicoproteomics and its application to human health risk assessment

Toxicoproteomics is the use of proteomic technologies to better understand environmental and genetic factors, toxic mechanisms, and modes of action in response to acute exposure to toxicants and in the long-term development of diseases caused or influenced by these exposures. Use of toxicoproteomic technologies to identify key biochemical pathways, mechanisms, and biomarkers of exposure and toxicity will decrease the uncertainties that are associated with human health risk assessments. This review provides an overview of toxicoproteomics from human health risk assessment perspectives. Key toxicoproteomic technologies such as 2-D gel-based proteomic methods and toxicoproteomic approaches are described, and examples of applications of these technologies and methodologies in the risk assessment context are presented. The discussion includes a focus on challenges and future directions.     

Cardiovascular proteomics: translational studies to develop novel biomarkers in heart failure and left ventricular remodeling

Heart failure (HF) remains a severe disease with a poor prognosis. HF biomarkers may include demographic features, cardiac imaging, or genetic polymorphisms but this term is commonly applied to circulating serum or plasma analytes. Biomarkers may have at least three clinical uses in the context of HF: diagnosis, risk stratification, and guidance in the selection of therapy. Proteomic studies on HF biomarkers can be designed as case/control using clinical endpoints; alternatively, left ventricular remodeling can be used as a surrogate endpoint. The type of samples (tissue, cells, serum or plasma) used for proteomic analysis is a key factor in the research of biomarkers. Since the final aim is the discovery of circulating biomarkers, and since plasma and serum samples are easily accessible, proteomic analysis is frequently used for blood samples. However, standardization of sampling and access to low-abundance proteins remains problematic. Although, proteomics is playing a major role in the discovery phase of biomarkers, validation in independent populations is necessary by using more specific methods. The knowledge of new HF biomarkers may allow a more personalized medicine in the future.     

Proteomics in ocular fluids

The focus of this article is to review recent techniques in proteomic analysis of ocular fluids. These fluids include tears, aqueous humor, and vitreous, they will also be compared to serum analysis. Furthermore, we attempt to summarize some disease correlated biomarkers in ocular fluids that were discovered through different proteomic techniques in eye diseases like dry eye, glaucoma, age-related macular degeneration, uveitis, or diabetic retinopathy. This review is trying to point out the importance of these biomarkers for clinical applications.