Clinical perspectives of high-resolution mass spectrometry-based proteomics in neuroscience: exemplified in amyotrophic lateral sclerosis biomarker discovery research

From Multi-Omics Approaches to Precision Medicine in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating and fatal neurodegenerative disorder, caused by the degeneration of upper and lower motor neurons for which there is no truly effective cure. The lack of successful treatments can be well explained by the complex and heterogeneous nature of ALS, with patients displaying widely distinct clinical features and progression patterns, and distinct molecular mechanisms underlying the phenotypic heterogeneity. Thus, stratifying ALS patients into consistent and clinically relevant subgroups can be of great value for the development of new precision diagnostics and targeted therapeutics for ALS patients. In the last years, the use and integration of high-throughput "omics" approaches have dramatically changed our thinking about ALS, improving our understanding of the complex molecular architecture of ALS, distinguishing distinct patient subtypes and providing a rational foundation for the discovery of biomarkers and new individualized treatments. In this review, we discuss the most significant contributions of omics technologies in unraveling the biological heterogeneity of ALS, highlighting how these approaches are revealing diagnostic, prognostic and therapeutic targets for future personalized interventions.

Mass spectrometry analysis of plasma from amyotrophic lateral sclerosis and control subjects

Mass spectrometry was used to study blood samples from patients with amyotrophic lateral sclerosis (ALS) and healthy controls. Addenbrooke's cognitive examination-III (ACE-III) was used to test for cognitive impairment (CI). Nano liquid chromatography and time of flight mass spectrometry (MS) were performed on samples from 42 ALS patients and 18 healthy controls. SWATH™ proteomic analysis was utilized to look for differences between groups. Western blot analysis was used to study levels of 4 proteins, selected as being of possible interest in ALS, in the MS discovery cohort and a second validation group of 10 ALS patients and 10 healthy controls. INGENUITY PATHWAY ANALYSIS (IPA) was applied to the final proteomic data. Between ALS patients and controls, there were significant differences in the expression of 30 proteins. Between controls and ALS patients without CI, there were significant differences in 15 proteins. Between controls and ALS patients with CI, there were significant differences in 32 proteins. Changes in levels of gelsolin, clusterin, and CD5L were validated by using western blot analysis in the discovery cohort. Changes in the expression of gelsolin, clusterin, and ficolin 3 were replicated in a validation group. In ALS, the LXR/RXR and coagulation pathways were downregulated whereas the complement pathway was upregulated. The proteomic data were used to produce two new networks, centered on IL1 and on NFkB, which showed altered levels in ALS. This study highlights the usefulness of MS of blood samples as a tool to study ALS.

Neuroproteomics and Systems Biology Approach to Identify Temporal Biomarker Changes Post Experimental Traumatic Brain Injury in Rats

Traumatic brain injury (TBI) represents a critical health problem of which diagnosis, management, and treatment remain challenging. TBI is a contributing factor in approximately one-third of all injury-related deaths in the United States. The Centers for Disease Control and Prevention estimate that 1.7 million people suffer a TBI in the United States annually. Efforts continue to focus on elucidating the complex molecular mechanisms underlying TBI pathophysiology and defining sensitive and specific biomarkers that can aid in improving patient management and care. Recently, the area of neuroproteomics–systems biology is proving to be a prominent tool in biomarker discovery for central nervous system injury and other neurological diseases. In this work, we employed the controlled cortical impact (CCI) model of experimental TBI in rat model to assess the temporal–global proteome changes after acute (1 day) and for the first time, subacute (7 days), post-injury time frame using the established cation–anion exchange chromatography-1D SDS gel electrophoresis LC–MS/MS platform for protein separation combined with discrete systems biology analyses to identify temporal biomarker changes related to this rat TBI model. Rather than focusing on any one individual molecular entity, we used in silico systems biology approach to understand the global dynamics that govern proteins that are differentially altered post-injury. In addition, gene ontology analysis of the proteomic data was conducted in order to categorize the proteins by molecular function, biological process, and cellular localization. Results show alterations in several proteins related to inflammatory responses and oxidative stress in both acute (1 day) and subacute (7 days) periods post-TBI. Moreover, results suggest a differential upregulation of neuroprotective proteins at 7 days post-CCI involved in cellular functions such as neurite growth, regeneration, and axonal guidance. Our study is among the first to assess temporal neuroproteome changes in the CCI model. Data presented here unveil potential neural biomarkers and therapeutic targets that could be used for diagnosis, for treatment and, most importantly, for temporal prognostic assessment following brain injury. Of interest, this work relies on in silico bioinformatics approach to draw its conclusion; further work is conducted for functional studies to validate and confirm the omics data obtained.

Proteomic analysis of cerebrospinal fluid in amyotrophic lateral sclerosis

The present study used comparative proteomic analysis of cerebrospinal fluid (CSF) in amyotrophic lateral sclerosis (ALS) patients in order to identify proteins that may act as diagnostic biomarkers and indicators of the pathogenesis of ALS. This analysis was performed using isobaric tags for relative and absolute quantitation (iTRAQ) technology, coupled with 2-dimensional liquid chromatography/mass spectrometry. Database for Annotation, Visualization and Integrated Discovery software was utilized for bioinformatic analysis of the data. Following this, western blotting was performed in order to examine the expression of 3 candidate proteins in ALS patients compared with healthy individuals [as a normal control (NC) group] or patients with other neurological disease (OND); these proteins were insulin-like growth factor II (IGF-2), glutamate receptor 4 (GRIA4) and leucine-rich α-2-glycoprotein 1 (LRG1). Clinical data, including gender, age, disease duration and ALS functional rating scale (ALSFRS-R) score, were also collected in the ALS patients. Multiple linear regression analysis was performed between the clinical data and the results of western blot analysis. A total of 248 distinct proteins were identified in the ALS and NC groups, amongst which a significant difference could be identified in 35 proteins; of these, 21 proteins were downregulated and 14 were upregulated. These differentially-expressed proteins were thus revealed to be associated with ALS. The western blot analysis confirmed a proportion of the data attained in the iTRAQ analysis, revealing the differential protein expression of IGF-2 and GRIA4 between the ALS and NC groups. IGF-2 was significantly downregulated in ALS patients (P=0.017) and GRIA4 was significantly upregulated (P=0.016). These results were subsequently validated in the 35-patient ALS and OND groups (P=0.002), but no significant difference was identified in LRG1 expression between these groups. GRIA4 protein expression was higher in male than female patients and was positively correlated with the ALSFRS-R score, meaning that GRIA4 expression was negatively correlated with the severity of ALS, while IGF-2 and LRG1 expression did not correlate with any clinical data. The present study thus demonstrated that GRIA4 expression levels, as a marker of severity, may be used as a reference for the timing of treatment, and that IGF-2 may serve as an effective biomarker of ALS progression.

Neuroproteomics tools in clinical practice

Neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) are characterized by neuronal impairment that leads to disease-specific changes in the neuronal proteins. The early diagnosis of these disorders is difficult, thus, the need for identifying, developing and using valid clinically applicable biomarkers that meet the criteria of precision, specificity and repeatability is very vital. The application of rapidly emerging technology such as mass spectrometry (MS) in proteomics has opened new avenues to accelerate biomarker discovery, both for diagnostic as well as for prognostic purposes. This review summarizes the most recent advances in the mass spectrometry-based neuroproteomics and analyses the current and future directions in the biomarker discovery for the neurodegenerative diseases. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

Intricate effects of primary motor neuronopathy on contractile proteins and metabolic muscle enzymes as revealed by label-free mass spectrometry

While the long-term physiological adaptation of the neuromuscular system to changed functional demands is usually reflected by unilateral skeletal muscle transitions, the progressive degeneration of distinct motor neuron populations is often associated with more complex changes in the abundance and/or isoform expression pattern of contractile proteins and metabolic enzymes. In order to evaluate these intricate effects of primary motor neuronopathy on the skeletal muscle proteome, label-free MS was employed to study global alterations in the WR (wobbler) mouse model of progressive neurodegeneration. In motor neuron disease, fibre-type specification and the metabolic weighting of bioenergetic pathways appear to be strongly influenced by both a differing degree of a subtype-specific vulnerability of neuromuscular synapses and compensatory mechanisms of fibre-type shifting. Proteomic profiling confirmed this pathobiochemical complexity of disease-induced changes and showed distinct alterations in 72 protein species, including a variety of fibre-type-specific isoforms of contractile proteins, metabolic enzymes, metabolite transporters and ion-regulatory proteins, as well as changes in molecular chaperones and various structural proteins. Increases in slow myosin light chains and the troponin complex and a decrease in fast MBP (myosin-binding protein) probably reflect the initial preferential loss of the fast type of neuromuscular synapses in motor neuron disease.

The systematic biochemical analysis of muscle from the wobbler mouse model of motor neuron disease suggests that the loss of neuromuscular synapses causes complex changes in the protein profile of contractile tissues, affecting especially the contractile apparatus and energy metabolism.

Proteome analysis of body fluids for amyotrophic lateral sclerosis biomarker discovery

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder of motor neurons leading to death of the patients, mostly within 2-5 years after disease onset. The pathomechanism of motor neuron degeneration is only partially understood and therapeutic strategies based on mechanistic insights are largely ineffective. The discovery of reliable biomarkers of disease diagnosis and progression is the sine qua non of both the revelation of insights into the ALS pathomechanism and the assessment of treatment efficacies. Proteomic approaches are an important pillar in ALS biomarker discovery. Cerebrospinal fluid is the most promising body fluid for differential proteome analyses, followed by blood (serum, plasma), and even urine and saliva. The present study provides an overview about reported peptide/protein biomarker candidates that showed significantly altered levels in certain body fluids of ALS patients. These findings have to be discussed according to proposed pathomechanisms to identify modifiers of disease progression and to pave the way for the development of potential therapeutic strategies. Furthermore, limitations and advantages of proteomic approaches for ALS biomarker discovery in different body fluids and reliable validation of biomarker candidates have been addressed.

Enrichment of Leishmania donovani ATP-binding proteins using a staurosporine capture compound

Trypanosomatid parasites of the genus Leishmania cause severe human diseases collectively termed leishmaniasis. Parasite ATP-binding proteins have emerged as potent targets for chemotherapeutic intervention. However, many parasite-specific ATP-binding proteins may escape current efforts in drug target identification, validation and deconvolution due to the lack of sequence conservation and functional annotation of these proteins in early branching eukaryotic trypanosomatids. Here, we selectively enriched for ATP-binding proteins from Leishmania donovani axenic promastigote and amastigote total protein extracts utilizing a Capture Compound™ (CC) linked to the ATP-competitive inhibitor staurosporine. As judged by in-gel kinase activity assay and competitive inhibition with free staurosporine, the CC specifically enriched for parasite phosphotransferases. Comparative nanoLC-MS(n) analysis identified 70 captured proteins, including 24 conserved protein kinases, and 32 hypothetical proteins with potential ATP-binding function. We identified conserved signature sequence motifs characteristic for staurosporine-binding protein kinases, and identified the hypothetical proteins LinJ.20.0280 and LinJ.09.1630 as novel ATP-binding proteins. Thus, functional enrichment procedures such as described here, combined with bio-informatics analyses and activity assays, provide powerful tools for the discovery of parasite-specific ATP-binding proteins that escape homology-based identification, which can be subsequently targeted for pharmacological intervention.

BIOLOGICAL SIGNIFICANCE

Functional enrichment using a Capture Compound™ linked to the ATP-competitive inhibitor staurosporine provides a powerful new tool for the discovery of parasite-specific ATP-binding proteins that escape homology-based identification, which can be subsequently targeted for pharmacological intervention.

Clinical neuroproteomics and biomarkers: from basic research to clinical decision making

Clinical neuroproteomics aims to advance our understanding of disease and injury affecting the central and peripheral nervous systems through the study of protein expression and the discovery of protein biomarkers to facilitate diagnosis and treatment. The general premise of the biomarker field is that in vivo factors present in either tissue or circulating biofluids, reflect pathological changes, and can be identified and analyzed. This approach offers an opportunity to illuminate changes occurring at both the population and patient levels toward the realization of personalized medicine. This review is intended to provide research-driven clinicians with an overview of protein biomarkers of disease and injury for clinical use and to highlight methodology and potential pitfalls. We examine the neuroproteomic biomarker field and discuss the hallmarks and the challenges of clinically relevant biomarker discovery relating to central nervous system pathology. We discuss the issues in the maturation of potential biomarkers from discovery to Food and Drug Administration approval and review several platforms for protein biomarker discovery, including protein microarray and mass spectrometry-based proteomics. We describe the application of microfluidic technologies to the evolution of a robust clinical test. Finally, we highlight several biomarkers currently in use for cancer, ischemia, and injury in the central nervous system. Future efforts using these technologies will result in the maturation of existing and the identification of de novo biomarkers that could guide clinical decision making and advance diagnostic and therapeutic options for the treatment of neurological disease and injury.

Biological and methodical challenges of blood-based proteomics in the field of neurological research

Biomarker discovery is an application of major importance in today's proteomic research. There is an urgent need for suitable biomarkers to improve diagnostic tools and treatment in various neurological diseases, such as neurodegenerative disorders. Recent years have witnessed an enormous interest in proteomics, which is currently seen as an invaluable tool to shed more light on complex interacting signalling pathways and molecular networks involved in several neuropathological conditions. However, while first results of proteomic research studies have sparked much public attention, the momentum of further proteomic biomarker research in neurological disorders may suffer by its very complex methodology which is sensitive to various sources of artefacts. A major source of variability is proteome perturbation caused by sample handling/preservation (preanalytical phase) and processing/measurement (analytical phase). The aim of the present review is to summarize the current literature focusing on the crucial role played by preanalytical and analytical factors that affect the quality of samples and the reliability of the data produced in blood-based proteomic biomarker research in neurology, which may apply to Alzheimer's disease (AD) as well as other neurological disorders. Procedures for sample preparation and protocols for the analysis of serum and plasma samples will be delineated. Finally, the potential usefulness of bioinformatics--allowing for the assembly, store, and processing of data--as well as its contribution to the execution of proteomic studies will be critically discussed.

Cerebrospinal fluid top-down proteomics evidenced the potential biomarker role of LVV- and VV-hemorphin-7 in posterior cranial fossa pediatric brain tumors

Posterior cranial fossa is the most frequent location of pediatric brain tumors. Its diagnosis is currently performed by postsurgery histopathology and the identification of biomarkers in cerebrospinal fluid (CSF) could provide a less invasive tool. Patient CSF was collected during surgery before the tumor removal (PRE-CSF) and 6 days after the resection (POST-CSF) and analyzed by top down LC-MS proteomics for comparison. The PRE-CSFs generally exhibited a less complex LC-MS profile than the relative POST-CSFs suggesting a suppressive role of the tumor toward proteins and peptides production or release. Particularly, a panel of peptides, identified as alpha- and beta-hemoglobin chains fragments, were generally absent in the PRE-CSF and present in the POST ones independently from contaminant blood hemoglobin. Among them, the LVV- and VV-hemorphin-7 showed the most repeatable trend and with a few remarkable exceptions: their unusual absence in POST surgery CSF was in fact interestingly correlated to the presence of tumor in the patient despite surgery due to metastases or to subtotal resection. These results ascribed a relevant biological role to LVV- and VV-h7 peptides in the disease and a strong potential as biomarkers. Their analysis in POST surgery CSF could be used to predict patient prognosis.

The cerebrospinal fluid proteome in HIV infection: change associated with disease severity

BACKGROUND

Central nervous system (CNS) infection is a nearly universal feature of untreated systemic HIV infection with a clinical spectrum that ranges from chronic asymptomatic infection to severe cognitive and motor dysfunction. Analysis of cerebrospinal fluid (CSF) has played an important part in defining the character of this evolving infection and response to treatment. To further characterize CNS HIV infection and its effects, we applied advanced high-throughput proteomic methods to CSF to identify novel proteins and their changes with disease progression and treatment.

RESULTS

After establishing an accurate mass and time (AMT) tag database containing 23,141 AMT tags for CSF peptides, we analyzed 91 CSF samples by LC-MS from 12 HIV-uninfected and 14 HIV-infected subjects studied in the context of initiation of antiretroviral therapy and correlated abundances of identified proteins a) within and between subjects, b) with all other proteins across the entire sample set, and c) with "external" CSF biomarkers of infection (HIV RNA), immune activation (neopterin) and neural injury (neurofilament light chain protein, NFL). We identified a mean of 2,333 +/- 328 (SD) peptides covering 307 +/-16 proteins in the 91 CSF sample set. Protein abundances differed both between and within subjects sampled at different time points and readily separated those with and without HIV infection. Proteins also showed inter-correlations across the sample set that were associated with biologically relevant dynamic processes. One-hundred and fifty proteins showed correlations with the external biomarkers. For example, using a threshold of cross correlation coefficient (Pearson's) ≤ -0.3 and ≥0.3 for potentially meaningful relationships, a total of 99 proteins correlated with CSF neopterin (43 negative and 56 positive correlations) and related principally to neuronal plasticity and survival and to innate immunity. Pathway analysis defined several networks connecting the identified proteins, including one with amyloid precursor protein as a central node.

CONCLUSIONS

Advanced CSF proteomic analysis enabled the identification of an array of novel protein changes across the spectrum of CNS HIV infection and disease. This initial analysis clearly demonstrated the value of contemporary state-of-the-art proteomic CSF analysis as a discovery tool in HIV infection with likely similar application to other neurological inflammatory and degenerative diseases.

Multiplexing and multivariate analysis in neurodegeneration

Limited sample volume is often an obstacle in clinical research and one way to circumvent this is to use multiplex techniques where several different analytes are simultaneously measured. There is a multitude of different platforms that can be used for multiplexing and their uniqueness and similarities will be described. Multivariate analysis is a powerful tool for extracting information from multiplex data. An introduction to one such algorithm is presented followed by examples from the literature, in the field of neurodegeneration, where multiplex and multivariate methods have been used.

Identifying patient subtypes in multiple sclerosis and tailoring immunotherapy: challenges for the future

The accelerating pace of technological and analytical development in the fields of genetic and phenotypic profiling has ushered in an era of great promise for multiple sclerosis (MS) research. As we continue to identify modest but meaningful associations to MS susceptibility, disease course, treatment response, and other clinical or paraclinical phenotypes, we must begin to (1) embark on the challenging set of studies that will integrate disparate observations into clinical algorithms, and (2) validate their clinical utility. Genetic data are receiving muchofthe attention today, but they are unlikelytobesufficienttooffer a personalized approach to disease management in MS. Rather, the genetic architecture of the disease, once uncovered, will offer a fixed platform upon which more dynamic molecular profiles can be assembled to deconstruct the structure of the patient population that we label with a diagnosis of MS. The tools and methods to gain insight into the heterogeneity of MS patients are available today; we must now realize their potential in enhancing the care of MS patients.

Neuroproteomics: a biochemical means to discriminate the extent and modality of brain injury

Diagnosis and treatment of stroke and traumatic brain injury remain significant health care challenges to society. Patient care stands to benefit from an improved understanding of the interactive biochemistry underlying neurotrauma pathobiology. In this study, we assessed the power of neuroproteomics to contrast biochemical responses following ischemic and traumatic brain injuries in the rat. A middle cerebral artery occlusion (MCAO) model was employed in groups of 30-min and 2-h focal neocortical ischemia with reperfusion. Neuroproteomes were assessed via tandem cation-anion exchange chromatography-gel electrophoresis, followed by reversed-phase liquid chromatography-tandem mass spectrometry. MCAO results were compared with those from a previous study of focal contusional brain injury employing the same methodology to characterize homologous neocortical tissues at 2 days post-injury. The 30-min MCAO neuroproteome depicted abridged energy production involving pentose phosphate, modulated synaptic function and plasticity, and increased chaperone activity and cell survival factors. The 2-h MCAO data indicated near complete loss of ATP production, synaptic dysfunction with degraded cytoarchitecture, more conservative chaperone activity, and additional cell survival factors than those seen in the 30-min MCAO model. The TBI group exhibited disrupted metabolism, but with retained malate shuttle functionality. Synaptic dysfunction and cytoarchitectural degradation resembled the 2-h MCAO group; however, chaperone and cell survival factors were more depressed following TBI. These results underscore the utility of neuroproteomics for characterizing interactive biochemistry for profiling and contrasting the molecular aspects underlying the pathobiological differences between types of brain injuries.

Simultaneous detection of attomolar pathogen DNAs by Bio-MassCode mass spectrometry

A general method is described to analyze pathogen DNAs in homogenous solution by a novel Bio-MassCode probe, using a small organic (namely disulfide) "reporter mass" that self-assembled in oligonucleotide-modified gold nanoparticles. With conventional MALDI TOF MS, the assay simultaneously detected DNAs for HIV, HBV, HCV, and TP with extraordinarily high sensitivity in the low attomolar (10(-18) M) range without any other amplification.

Establishing the proteome of normal human cerebrospinal fluid

Background

Knowledge of the entire protein content, the proteome, of normal human cerebrospinal fluid (CSF) would enable insights into neurologic and psychiatric disorders. Until now technologic hurdles and access to true normal samples hindered attaining this goal.

Methods and Principal Findings

We applied immunoaffinity separation and high sensitivity and resolution liquid chromatography-mass spectrometry to examine CSF from healthy normal individuals. 2630 proteins in CSF from normal subjects were identified, of which 56% were CSF-specific, not found in the much larger set of 3654 proteins we have identified in plasma. We also examined CSF from groups of subjects previously examined by others as surrogates for normals where neurologic symptoms warranted a lumbar puncture but where clinical laboratory were reported as normal. We found statistically significant differences between their CSF proteins and our non-neurological normals. We also examined CSF from 10 volunteer subjects who had lumbar punctures at least 4 weeks apart and found that there was little variability in CSF proteins in an individual as compared to subject to subject.

Conclusions

Our results represent the most comprehensive characterization of true normal CSF to date. This normal CSF proteome establishes a comparative standard and basis for investigations into a variety of diseases with neurological and psychiatric features.

Combinatorial peptide libraries facilitate development of multiple reaction monitoring assays for low-abundance proteins

Low-abundance proteins present in biological fluids are often considered an attractive source of new disease biomarkers. Since such proteins are poorly observed in proteome-scale discovery experiments due to an overwhelming mass of high-abundance proteins, the development of quantitative multiple reaction monitoring (MRM) assays for low-abundance proteins is a challenging task. Here, we present a strategy that facilitates the development of MRM assays for large numbers of unpurified low-abundance proteins. Our discovery strategy is based on the reduction of the dynamic range of protein concentrations in biological fluids by means of one-bead one-compound combinatorial peptide libraries (CPL). Our 2D-LC-MS/MS approach allowed us to identify a total of 484 unique proteins in ovarian cancer ascites, and 216 proteins were assigned as low-abundance ones. Interestingly, 74 of those proteins have never been previously described in ascites fluid. Treatment with CPL allowed identification of a significantly higher number of unique peptides for low-abundance proteins and provided important empirical fragmentation information for development of MRM assays. Finally, we confirmed that MRM assays worked for 30 low-abundance proteins in the unfractionated ascites digest. Using a multiplexed MRM method, relative amounts of five proteins (kallikrein 6, metalloproteinase inhibitor 1, macrophage migration inhibitory factor, follistatin-related protein, and mesothelin) were determined in a set of ovarian cancer ascites. Multiplexed MRM assays targeting large numbers of proteins can be used to develop comprehensive panels of biomarkers with high sensitivity and selectivity, and to study complex protein networks.

The methodology of neuroproteomics

The human central nervous system (CNS) is the most complex organ in nature, composed of ten trillion cells forming complex neural networks using a quadrillion synaptic connections. Proteins, their modifications, and their interactions are integral to CNS function. The emerging field of neuroproteomics provides us with a wide-scope view of posttranslation protein dynamics within the CNS to better our understanding of its function, and more often, its dysfunction consequent to neurodegenerative disorders. This chapter reviews methodology employed in the neurosciences to study the neuroproteome in health and disease. The chapter layout parallels this volume's four parts. Part I focuses on modeling human neuropathology in animals as surrogate, accessible, and controllable platforms in our research. Part II discusses methodology used to focus analysis onto a subneuroproteome. Part III reviews analytical and bioinformatic technologies applied in neuroproteomics. Part IV discusses clinical neuroproteomics, from processing of human biofluids to translation in biomarkers research. Neuroproteomics continues to mature as a discipline, confronting the extreme complexity of the CNS proteome and its dynamics, and providing insight into the molecular mechanisms underlying how our nervous system works and how it is compromised by injury and disease.