Clinical application of tear proteomics: Present and future prospects

Human tear fluid is charactered with very small volume and complex protein constitutes with a very large orders of magnitude. The tear proteome analysis provides a unique dataset (i.e., specific protein markers or protein patterns) that may be correlated to more effective diagnosis, prognosis, and response to therapy. Compared to less than 100 tear proteins obtained by the traditional methods, more than 400 proteins have been found in human tear fluid by current proteomic technologies. Many proteomics techniques, such as 2-DE, MALDI-TOF-MS, LC-MS, SELDI-TOF-MS, protein arrays, have been used to perform tear proteome analysis in healthy and/or disease subjects. The clinical application of tear proteomics needs suitable tear collection methods, standard tear handling procedures, and more sensitive and reliable proteomic technologies.     

Lysosomal proteomics and disease

A recent trend in proteomic studies has been to analyze macromolecular complexes such as subcellular organelles instead of complete cells or tissues. This "divide and conquer" approach circumvents some of the formidable problems associated with whole proteome analyses and allows focus on a subset of proteins that may be involved in a particular process or disease of interest. One organelle that has been the focus of considerable attention in proteomic studies is the lysosome, an acidic, membrane-delimited compartment that plays an essential role in the degradation and recycling of biological macromolecules. Lysosomal proteomics have been driven in part by the well-established involvement of this organelle in numerous human diseases, but also by the availability of approaches to selectively visualize and/or isolate subsets of lysosomal proteins. In terms of clinical application, proteomic studies of the lysosome have led to the identification of gene defects in three human hereditary diseases. This review summarizes past progress, current limitations and future directions in the field of lysosomal proteomics.     

Exploring the potential of platelet proteomics in children

Proteomics is a rapidly evolving ‘‘post-genomic’’ science utilizing advanced technologies in protein separation, identification, quantitation and heavily relying on bioinformatics. Proteomic research in pediatrics is important and most of the successes thus far are seen in research that utilize samples that require less invasive procedures and focus on prevailing childhood diseases such as acute lymphoblastic leukaemia and neuroblastoma. Recent advances in proteomics are helping to elucidate platelet processes that are relevant to bleeding and clotting disorders, as well as other important roles of platelets such as in angiogenesis and inflammation. Nevertheless, most of platelet proteome data obtained to date are derived from the adult population and the potential of platelet proteomic application in children has not yet been explored. As it happens in all research fields, there are additional challenges in studying children such as procuring sufficient biological samples and access to less common disease cohorts as compared to in adults. Furthermore, many of the prevalent platelet-mediated diseases in adults, such as coronary heart disease and atherosclerotic lesions, are believed to have origins during childhood. Hence, platelet proteomic research in children may reveal some important information on how platelet plays a role in the pathogenesis of disease. In this article, we refer to the current knowledge from platelet proteomic research strategies in adults and address the specific concerns in the study of pediatric samples.     

How to get proteomics to the clinic? Issues in clinical proteomics,exemplified by CE‐MS

Clinical proteomics is defined as application of proteome analysis aiming at improving the current clinical situation. As such, the success of clinical proteomics should be assessed based on the clinical impact following implementation of the findings. While we have experienced significant technological advancements in mass spectrometry in the last years, based on the above measure, this has not at all resulted in similar advancements in clinical proteomics. Although a large number of proteomic biomarkers have been described, most of them were not subsequently validated, and certainly have had no impact in clinical decision making as yet. Under the current conditions, it appears likely that the situation will not change significantly: we will be flooded by reports on biomarkers, but not see any implementation. In this article, some key issues in proteomic biomarker research are pinpointed, based on the experience with CE‐MS, likely also holding true for biomarkers resulting from other analysis domains.     

Proteomics of human cerebrospinal fluid - the good, the bad, and the ugly

The development of MALDI ESI in the late 1980s has revolutionized the biological sciences and facilitated the emergence of a new discipline called proteomics. Application of proteomics to human cerebrospinal fluid (CSF) has greatly hastened the advancement of characterizing the CSF proteome as well as revealing novel protein biomarkers that are diagnostic of various neurological diseases. While impressive progressions have been made in this field, it has become increasingly clear that proteomics results generated by various laboratories are highly variable. The underlying issues are vast, including limitations and complications with heterogeneity of patients/testing subjects, experimental design, sample processing, as well as current proteomics technology. Accordingly, this review not only summarizes the current status of characterization of the human CSF proteome and biomarker discovery for major neurodegenerative disorders, i.e., Alzheimer's disease and Parkinson's disease, but also addresses a few essential caveats involved in several steps of CSF proteomics that may contribute to the variable/contradicting results reported by different laboratories. The potential future directions of CSF proteomics are also discussed with this analysis.     

Is the time ripe for kidney tissue proteomics?

In this viewpoint article, the importance of renal tissue proteomics in health and disease is explored. The analysis of the urinary proteome and the potential clinical application of these findings are progressing. However, additional benefit would be gained from a detailed parallel exploration of the proteome of the renal parenchyma, both in models and clinical samples. With this aim, we will briefly summarize the existing literature, compare the findings and propose future tasks. Special emphasis is placed on the importance of studying specific cellular compartments and cell types within the kidney. Recent technical advances are also discussed. It is anticipated that the combination of such technologies, especially proteomic analysis of material extracted by laser capture microdissection from paraffin embedded tissue or direct mass spectrometrical tissue imaging, will revolutionize the field.     

Biomarker discovery in glomerular diseases using urinary proteomics

Renal biopsy remains the gold standard test for definitive diagnosis of glomerular diseases. This invasive procedure; however, has a potential risk for serious complications and is contraindicated in some patients. It is therefore essential to search for noninvasive biomarkers for the diagnosis and prognosis of glomerular diseases. The urine is the most appropriate sample for biomarker discovery in glomerular diseases. Urinary proteomics has thus gained a wide acceptance and has been extensively applied to this area. This review focuses mainly on applications of proteomic technologies to urinary proteome profiling for biomarker discovery in various glomerular diseases, including diabetic nephropathy, IgA nephropathy, membranous nephropathy, focal segmental glomerulosclerosis, primary membranoproliferative glomerulonephritis, lupus nephritis, antiglomerular basement membrane disease, minimal change disease, and pediatric nephrotic syndrome. Recent findings from these studies are summarized and discussed. These data clearly underline the great promise of urinary proteomics in biomarker discovery for glomerular diseases.     

Application of proteomic techniques to the study of urine and renal tissue

The increasing application of proteomic methods to biomedical research is providing us with important new information; it holds particular promise in advancing basic and clinical renal research, but whether proteomics can ever become a routine diagnostic tool in nephrology is still uncertain. Currently, proteomic techniques are used by many groups in the search for "biomarkers" of disease, especially kidney disease, because of the ready availability of urine as an "end-product" of renal function. However, the question as to whether any disease-specific biomarkers exist or can be identified by proteomics is also uncertain. A growing application of proteomics in biomedical research is to understand the mechanism(s) of disease. This brief review is selective; in it we consider examples of proteomic studies of human urine for biomarkers, others that have explored renal physiology, and still others that have begun to probe the proteome of organelles. No single approach is sufficiently comprehensive, and the pooled application of proteomics to renal research will undoubtedly improve our understanding of renal function and enable us to explore in more detail subcellular structures, and to characterize cellular processes at the molecular level. When combined with other techniques in renal research, proteomics, and related analytical methods could prove indispensable in modeling renal function, and perhaps also in diagnosis and management of renal disease.     

Impact of the General Data Protection Regulation on Clinical Proteomics Research

The recently implemented General Data Protection Regulation (GDPR) has promising attributes for ensuring the protection of personal data collected and processed for clinical proteomic investigations. However, there exist ever increasing alarming concerns regarding its implications upon the future of clinical proteomics research both within and beyond the European Union. The main issues of concern regard GDPR legislative requirements for informed consent for study subjects’ data collection and processing, data anonymization, and data storage and/or sharing, particularly in research areas which readily utilize databanks and biobanks, such as clinical proteomics investigations. The potential impacts of the aforementioned issues upon on‐going and future clinical proteomics investigations are detailed, whilst recommendations for potentially resolving these emerging issues are proposed. Consensus between government, legislative, and research stakeholders, as well as impact assessments of final measures to be applied for medical research, is necessary so as to ensure the favorable perpetuation of clinical proteomics investigations and subsequent impact upon optimal patient health.     

Proteomic analysis of serum, plasma, and lymph for the identification of biomarkers

Probably no topic has generated more excitement in the world of proteomics than the search for biomarkers. This excitement has been generated by two realities: the constant need for better biomarkers that can be used for disease diagnosis and prognosis, and the recent developments in proteomic technologies that are capable of scanning the individual proteins within varying complex clinical samples. Ideally a biomarker would be assayable from a noninvasively collected sample, therefore, much of the focus in proteomics has been on the analysis of biofluids such as serum, plasma, urine, cerebrospinal fluid, lymph, etc. While the discovery of biomarkers has been elusive, there have been many advances made in the understanding of the proteome content of various biofluids, and in the technologies used for their analysis, that continues to point the research community toward new methods for achieving the ultimate goal of identifying novel disease-specific biomarkers. In this review, we will describe and discuss many of the proteomic approaches taken in an attempt to find novel biomarkers in serum, plasma, and lymph.     

Proteomics and the lung: Analysis of bronchoalveolar lavage fluid

Our knowledge of the complex bronchoalveolar lavage fluid (BALF) proteome has increased significantly over the last decade; but still, there remain many aspects of the BALF proteome that need characterization. Current proteomic methodologies resolve proteins within limited dynamic ranges: thereby, being limited in their ability to examine important areas of the BALF proteome, such as low molecular weight, low abundance proteins. To ensure proper coverage of these proteins in the BALF proteome, a refined 2-DE standard operation protocol is presented, highlighting important issues in sample collection, sample preparation, and 2-D DIGE analysis. It is hoped that this will help advance the field of BALF proteomics, BALFomics, which has lagged behind similar biofluids such as plasma and serum.     

Quantitative proteomics for investigating psychiatric disorders

The underlying pathophysiology of psychiatric disorders remains elusive. The use of quantitative proteomics to investigate disease-specific protein signatures holds great promise to improve the understanding of psychiatric disorders and identify relevant biomarkers. In this review, we discuss quantitative proteomic approaches for elucidating molecular mechanisms of psychiatric disorders, i.e. anxiety, schizophrenia, bipolar disorder and depression, by studying specimens from animal models and patients. We present gel-based, label-free and stable isotope-labeling methodologies and evaluate their strengths and limitations in the context of psychiatric research, with a focus on (15)N metabolic labeling of live animals due to its increased accuracy and potential for future applications. We also review biomarker candidate validation methods and present quantitative proteomic studies from the literature that aim to disentangle the molecular pathobiology of psychiatric disorders and identify candidate biomarkers. Finally, we explore the applicability of implementing proteomic methods as a routine diagnostic tool in the clinical laboratory.     

Proteomic and biomarker studies and neurological complications of pediatric sickle cell disease

Biomarker analysis and proteomic discovery in pediatric sickle cell disease has the potential to lead to important discoveries and improve care. The aim of this review article is to describe proteomic and biomarker articles involving neurological and developmental complications in this population. A systematic review was conducted to identify relevant research publications. Articles were selected for children under the age of 21 years with the most common subtypes of sickle cell disease. Included articles focused on growth factors (platelet-derived growth factor), intra and extracellular brain proteins (glial fibrillary acidic protein, brain-derived neurotrophic factor), and inflammatory and coagulation markers (interleukin-1β, l -selectin, thrombospondin-1, erythrocyte, and platelet-derived microparticles). Positive findings include increases in plasma brain-derived neurotrophic factor and platelet-derived growth factor with elevated transcranial Dopplers velocities, increases in platelet-derived growth factor isoform AA with overt stroke, and increases in glial fibrillary acidic protein with acute brain injury. These promising potential neuro-biomarkers provide insight into pathophysiologic processes and clinical events, but their clinical utility is yet to be established. Additional proteomics research is needed, including broad-based proteomic discovery of plasma constituents and blood cell proteins, as well as urine and cerebrospinal fluid components, before, during and after neurological and developmental complications.     

Changing the concepts of immune-mediated glomerular diseases through proteomics

Standard classification of glomerular diseases is based on histopathologic abnormalities. The recent application of proteomic technologies has resulted in paradigm changes in the understanding and classification of idiopathic membranous nephropathy and membranoproliferative glomerulonephritis. Those examples provide evidence that proteomics will lead to advances in understanding of the molecular basis of other glomerular diseases, such as lupus nephritis. Proof of principle experiments show that proteomics can be applied to patient renal biopsy specimens. This viewpoint summarizes the advances in immune-mediated glomerular diseases that have relied on proteomics, and potential future applications are discussed.     

Analysis of biofluids for biomarker research

While many of the developments made in high-throughput proteomics were originally applied to procaryotic and simple eucaryotic organisms, the analysis of biofluids became increasingly important as the prospect of using proteomics to discover novel biomarkers became realized. Biofluids have represented a unique challenge to proteomics as they are often present only in small amounts and, particularly in the cases of serum and plasma, can have protein concentration ranges that differ by ten orders of magnitude. While the discovery of authentic, clinically useful biomarkers in the proteomics era has been lacking, there have been a number of significant developments in the ability to more comprehensively characterize biofluid proteomes. The rapid pace of these developments suggest that the eventual discovery of clinically validate biomarkers using proteomic technologies still has a bright future.     

Identification of proteins in human substantia nigra

Characterization of the human brain proteome is a critical area of research. While examination of the human cortex has provided some insight, very little is known about the proteome of the human midbrain, which demonstrates substantial loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) in Parkinson's disease (PD). Therefore, characterization of this region is essential to a better understanding of the pathogenesis of PD. This dataset paper reports two separate studies, where human SNpc was collected from PD and control subjects and 1263 proteins were identified using MALDI-TOF/TOF as well as linear ion trap MS platforms. With gene ontology analysis, the proteins were categorized according to their biological processes, as well as cellular components. These data were also compared with previous proteomic characterization of the human frontal and temporal cortex, and cerebrospinal fluid to establish shared proteins of relevance. The present dataset is the most extensive survey of the human SNpc proteome, to date. Further characterization of the SNpc proteome will significantly facilitate our understanding of the function and expression of proteins involved in PD, as well as provide potential proteins that may be utilized as biomarkers.     

Proteomic studies in animal models of diabetes

The aim of this review is to provide an overview of proteomic studies in animal models of diabetes and to give some insight into the different methods available today in the rapidly developing field of proteomics. A summary of 31 papers published between 1997 and 2007 is presented. For instance, proteomics has been used to study the development of both type 1 and type 2 diabetes, diabetic complications in tissues like heart, kidney and retina and changes after treatment with anti-diabetic drugs like peroxisome proliferator-activated receptors agonists. Together, these studies give a good overview of a number of experimental approaches. Proteomics holds the promise of providing major contributions to the field of diabetes research. However, to achieve this, a number of issues need to be resolved. Appropriate data representation to facilitate data comparison, exchange, and verification is required, as well as improved statistical assessment of proteomic experiments. In addition, it is important to follow up the results with functional studies to be able to make biologically relevant conclusions. The potential of proteomics to dissect complex human disorders is now beginning to be realized. In the future, this will result in new important information concerning diabetes.