Amyotrophic lateral sclerosis--the tools of the trait

The aim of this review is to analyze how our knowledge on the etiology, pathology, and treatment of amyotrophic lateral sclerosis (ALS) has profited from the application of biotechnology tools for the identification of disease markers, the development of animal disease models, and the design of innovative therapeutics. In humans, ALS-specific clinical, genetic or protein biomarkers, or panels of biomarkers stemming from genomics and proteomics analyses can be critical for early diagnosis, monitoring of disease progression, drug validation in clinical trials, and identification of therapeutic targets for subsequent drug development. At the same time, animal models representing a number of human superoxide dismutase 1 mutations, intermediate-filament disorganization or axonal-transport defects have been invaluable in unraveling aspects of the pathophysiology of the disease; in each case, these only represent a small proportion of all ALS patients. Preclinical and clinical trials, although at present heavily concentrating on pharmacological approaches, are embracing the emerging alternative strategies of stem-cell and gene therapy. In combination with a further subcategorization of patients and the development of corresponding model systems for functional analyses, they will significantly influence the already changing face of ALS therapy.     

Amyotrophic lateral sclerosis multiprotein biomarkers in peripheral blood mononuclear cells

Background

Amyotrophic lateral sclerosis (ALS) is a fatal progressive motor neuron disease, for which there are still no diagnostic/prognostic test and therapy. Specific molecular biomarkers are urgently needed to facilitate clinical studies and speed up the development of effective treatments.

Methodology/Principal Findings

We used a two-dimensional difference in gel electrophoresis approach to identify in easily accessible clinical samples, peripheral blood mononuclear cells (PBMC), a panel of protein biomarkers that are closely associated with ALS. Validations and a longitudinal study were performed by immunoassays on a selected number of proteins. The same proteins were also measured in PBMC and spinal cord of a G93A SOD1 transgenic rat model. We identified combinations of protein biomarkers that can distinguish, with high discriminatory power, ALS patients from healthy controls (98%), and from patients with neurological disorders that may resemble ALS (91%), between two levels of disease severity (90%), and a number of translational biomarkers, that link responses between human and animal model. We demonstrated that TDP-43, cyclophilin A and ERp57 associate with disease progression in a longitudinal study. Moreover, the protein profile changes detected in peripheral blood mononuclear cells of ALS patients are suggestive of possible intracellular pathogenic mechanisms such as endoplasmic reticulum stress, nitrative stress, disturbances in redox regulation and RNA processing.

Conclusions/Significance

Our results indicate that PBMC multiprotein biomarkers could contribute to determine amyotrophic lateral sclerosis diagnosis, differential diagnosis, disease severity and progression, and may help to elucidate pathogenic mechanisms.     

Plasma and cerebrospinal fluid-based protein biomarkers for motor neuron disease

Motor neuron diseases (MNDs) and, in particular, amyotrophic lateral sclerosis (ALS), are a heterogeneous group of neurologic disorders characterized by the progressive loss of motor function. In ALS, a selective and relentless degeneration of both upper and lower motor neurons occurs, culminating in mortality typically within 5 years of symptom onset. However, survival rates vary among individual patients and can be from a few months to >10 years from diagnosis. Inadequacies in disease detection and treatment, along with a lack of diagnostic and prognostic tools, have prompted many to turn to proteomics-based biomarker discovery efforts. Proteomics refers to the study of the proteins expressed by a genome at a particular time, and the proteome can respond to and reflect the status of an organism, including health and disease states. Although an emerging field, proteomic applications promise to uncover biomarkers critical for differentiating patients with ALS and other MNDs from healthy individuals and from patients affected by other diseases. Ideally, these studies will also provide mechanistic information to facilitate identification of new drug targets for subsequent therapeutic development. In addition to proper experimental design, standard operating procedures for sample acquisition, preprocessing, and storage must be developed. Biological samples typically analyzed in proteomic studies of neurologic diseases include both plasma and cerebrospinal fluid (CSF). Recent studies have identified individual proteins and/or protein panels from blood plasma and CSF that represent putative biomarkers for ALS, although many of these proteins are not unique to this disease. Continued investigations are required to validate these initial findings and to further pursue the role of these proteins as diagnostic biomarkers or surrogate markers of disease progression. Protein biomarkers specific to ALS will additionally function to evaluate drug efficacy in clinical trials and to identify novel targets for drug design. It is hoped that proteomic technologies will soon integrate the basic biology of ALS with mechanistic disease information to achieve success in the clinical setting.     

Cystatin C: a candidate biomarker for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurologic disease characterized by progressive motor neuron degeneration. Clinical disease management is hindered by both a lengthy diagnostic process and the absence of effective treatments. Reliable panels of diagnostic, surrogate, and prognostic biomarkers are needed to accelerate disease diagnosis and expedite drug development. The cysteine protease inhibitor cystatin C has recently gained interest as a candidate diagnostic biomarker for ALS, but further studies are required to fully characterize its biomarker utility. We used quantitative enzyme-linked immunosorbent assay (ELISA) to assess initial and longitudinal cerebrospinal fluid (CSF) and plasma cystatin C levels in 104 ALS patients and controls. Cystatin C levels in ALS patients were significantly elevated in plasma and reduced in CSF compared to healthy controls, but did not differ significantly from neurologic disease controls. In addition, the direction of longitudinal change in CSF cystatin C levels correlated to the rate of ALS disease progression, and initial CSF cystatin C levels were predictive of patient survival, suggesting that cystatin C may function as a surrogate marker of disease progression and survival. These data verify prior results for reduced cystatin C levels in the CSF of ALS patients, identify increased cystatin C levels in the plasma of ALS patients, and reveal correlations between CSF cystatin C levels to both ALS disease progression and patient survival.     

Plasma Peptide Biomarker Discovery for Amyotrophic Lateral Sclerosis by MALDI –TOF Mass Spectrometry Profiling

The diagnostic of Amyotrophic lateral sclerosis (ALS) remains based on clinical and neurophysiological observations. The actual delay between the onset of the symptoms and diagnosis is about 1 year, preventing early inclusion of patients into clinical trials and early care of the disease. Therefore, finding biomarkers with high sensitivity and specificity remains urgent. In our study, we looked for peptide biomarkers in plasma samples using reverse phase magnetic beads (C18 and C8) and MALDI-TOF mass spectrometry analysis. From a set of ALS patients (n=30) and healthy age-matched controls (n=30), C18- or C8-SVM-based models for ALS diagnostic were constructed on the base of the minimum of the most discriminant peaks. These two SVM-based models end up in excellent separations between the 2 groups of patients (recognition capability overall classes > 97%) and classify blinded samples (10 ALS and 10 healthy age-matched controls) with very high sensitivities and specificities (>90%). Some of these discriminant peaks have been identified by Mass Spectrometry (MS) analyses and correspond to (or are fragments of) major plasma proteins, partly linked to the blood coagulation.     

Monitoring CSF Proteome Alterations in Amyotrophic Lateral Sclerosis: Obstacles and Perspectives in Translating a Novel Marker Panel to the Clinic

Background

Amyotrophic lateral sclerosis (ALS) is a fatal disorder of the motor neuron system with poor prognosis and marginal therapeutic options. Current clinical diagnostic criteria are based on electrophysiological examination and exclusion of other ALS-mimicking conditions. Neuroprotective treatments are, however, most promising in early disease stages. Identification of disease-specific CSF biomarkers and associated biochemical pathways is therefore most relevant to monitor disease progression, response to neuroprotective agents and to enable early inclusion of patients into clinical trials.

Methods and Findings

CSF from 35 patients with ALS diagnosed according to the revised El Escorial criteria and 23 age-matched controls was processed using paramagnetic bead chromatography for protein isolation and subsequently analyzed by MALDI-TOF mass spectrometry. CSF protein profiles were integrated into a Random Forest model constructed from 153 mass peaks. After reducing this peak set to the top 25%, a classifier was built which enabled prediction of ALS with high accuracy, sensitivity and specificity. Further analysis of the identified peptides resulted in a panel of five highly sensitive ALS biomarkers. Upregulation of secreted phosphoprotein 1 in ALS-CSF samples was confirmed by univariate analysis of ELISA and mass spectrometry data. Further quantitative validation of the five biomarkers was achieved in an 80-plex Multiple Reaction Monitoring mass spectrometry assay.

Conclusions

ALS classification based on the CSF biomarker panel proposed in this study could become a valuable predictive tool for early clinical risk stratification. Of the numerous CSF proteins identified, many have putative roles in ALS-related metabolic processes, particularly in chromogranin-mediated secretion signaling pathways. While a stand-alone clinical application of this classifier will only be possible after further validation and a multicenter trial, it could be readily used to complement current ALS diagnostics and might also provide new insights into the pathomechanisms of this disease in the future.     

ALS, what new 144 years after Charcot?

The most important challenge of ALS remains finding biomarkers. Clinical features remain of key importance in the diagnosis and for follow up. Neurophysiology remains difficult to use in clinical trials. Neuroimaging have some utility for upper motor neuron integrity and function. Among proteins and chemical markers, one of the most promising marker is the level of Nogo in muscle biopsy. In CSF, many candidate proteins have been suggested but their sensitivity and specificity remains disappointing. Recently, -omics technologies have been applied to try to discover biomarkers in ALS, including genomic, proteomic and metabolomic methodologies.     

Plasma neurofilament heavy chain levels correlate to markers of late stage disease progression and treatment response in SOD1(G93A) mice that model ALS

Background

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disorder characterised by progressive degeneration of motor neurons leading to death, typically within 3–5 years of symptom onset. The diagnosis of ALS is largely reliant on clinical assessment and electrophysiological findings. Neither specific investigative tools nor reliable biomarkers are currently available to enable an early diagnosis or monitoring of disease progression, hindering the design of treatment trials.

Methodology/Principal Findings

In this study, using the well-established SOD1^G93A mouse model of ALS and a new in-house ELISA method, we have validated that plasma neurofilament heavy chain protein (NfH) levels correlate with both functional markers of late stage disease progression and treatment response. We detected a significant increase in plasma levels of phosphorylated NfH during disease progression in SOD1^G93A mice from 105 days onwards. Moreover, increased plasma NfH levels correlated with the decline in muscle force, motor unit survival and, more significantly, with the loss of spinal motor neurons in SOD1 mice during this critical period of decline. Importantly, mice treated with the disease modifying compound arimoclomol had lower plasma NfH levels, suggesting plasma NfH levels could be validated as an outcome measure for treatment trials.

Conclusions/Significance

These results show that plasma NfH levels closely reflect later stages of disease progression and therapeutic response in the SOD1^G93A mouse model of ALS and may potentially be a valuable biomarker of later disease progression in ALS.     

Towards a TDP-43-Based Biomarker for ALS and FTLD

TDP-43 accumulates in nerve cells of nearly all cases of amyotrophic lateral sclerosis (ALS; the commonest form of motor neuron disease) and in the majority of Tau-negative frontotemporal lobar degeneration (FTLD). There is currently no biochemical test or marker of disease activity for ALS or FTLD, and the clinical diagnosis depends on the opinion of an experienced neurologist. TDP-43 has a key role in the pathogenesis of ALS/FTLD. Measuring TDP-43 in easily accessible biofluids, such as blood or cerebrospinal fluid, might reduce diagnostic delay and offer a readout for use in future drug trials. However, attempts at measuring disease-specific forms of TDP-43 in peripheral biofluids of ALS and FTLD patients have not yielded consistent results, and only some of the pathological biochemical features of TDP-43 found in human brain tissue have been detected in clinical biofluids to date. Reflecting on the molecular pathology of TDP-43, this review provides a critical overview on biofluid studies and future directions to develop a TDP-43-based clinical biomarker for ALS and FTLD.     

Biomarker discovery and validation: technologies and integrative approaches

The emerging field of biomarkers has applications in the diagnosis, staging, prognosis and monitoring of disease progression, as well as in the monitoring of clinical responses to a therapeutic intervention and the development and delivery of personalized treatments to reduce attrition in clinical trials. Moreover, biomarkers have a positive impact on health economics. The word "biomarker" has been used extensively across therapeutic areas and many disciplines, and its nature takes into consideration clinical, physiological, biochemical, developmental, morphological and molecular measures. In drug trials, biomarkers have been proposed for use in efficacy determination and patient population stratification, in deducing pharmacokinetic-pharmacodynamic relationships and in safety monitoring. The interfacing and integration of different technologies for data collection and analysis are pivotal to biomarker identification, characterization, validation and application. "Integrative functional informatics" represents a novel direction in such technology integration.     

Proteomic profiling of cerebrospinal fluid identifies biomarkers for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is characterized by degeneration of motor neurons. We tested the hypothesis that proteomic analysis will identify protein biomarkers that provide insight into disease pathogenesis and are diagnostically useful. To identify ALS specific biomarkers, we compared the proteomic profile of cerebrospinal fluid (CSF) from ALS and control subjects using surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS). We identified 30 mass ion peaks with statistically significant (p < 0.01) differences between control and ALS subjects. Initial analysis with a rule-learning algorithm yielded biomarker panels with diagnostic predictive value as subsequently assessed using an independent set of coded test subjects. Three biomarkers were identified that are either decreased (transthyretin, cystatin C) or increased (carboxy-terminal fragment of neuroendocrine protein 7B2) in ALS CSF. We validated the SELDI-TOF-MS results for transthyretin and cystatin C by immunoblot and immunohistochemistry using commercially available antibodies. These findings identify a panel of CSF protein biomarkers for ALS.     

Proteomics in clinical trials and practice: present uses and future promise

The study of clinical proteomics is a promising new field that has the potential to have many applications, including the identification of biomarkers and monitoring of disease, especially in the field of oncology. Expression proteomics evaluates the cellular production of proteins encoded by a particular gene and exploits the differential expression and post-translational modifications of proteins between healthy and diseased states. These biomarkers may be applied towards early diagnosis, prognosis, and prediction of response to therapy. Functional proteomics seeks to decipher protein-protein interactions and biochemical pathways involved in disease biology and targeted by newer molecular therapeutics. Advanced spectrometry technologies and new protein array formats have improved these analyses and are now being applied prospectively in clinical trials. Further advancement of proteomics technology could usher in an era of personalized molecular medicine, where diseases are diagnosed at earlier stages and where therapies are more effective because they are tailored to the protein expression of a patient's malignancy.     

The impact of cerebrospinal fluid biomarkers on the diagnosis of Alzheimer's disease

The cerebrospinal fluid (CSF) biomarkers β-amyloid(1-42) (Aβ(1-42)), total tau protein (T-tau), and tau phosphorylated at threonine 181 (P-tau(181P)) are gradually finding their way into routine clinical practice as an affirmative diagnostic tool for Alzheimer's disease (AD). These biomarkers have also been implemented in the revised diagnostic criteria for AD. The combination of the CSF biomarkers Aβ(1-42), T-tau, and P-tau(181P) leads to high (around 80%) levels of sensitivity, specificity, and diagnostic accuracy for discrimination between AD and controls (including psychiatric disorders like depression) and can be applied for diagnosing AD in the predementia phases of the disease (mild cognitive impairment). The added value of CSF biomarkers could lie within those cases in which the clinical diagnostic work-up is not able to discriminate between AD and non-AD dementias. However, their discriminatory power for the differential diagnosis of dementia is suboptimal. Other CSF biomarkers, especially those that are reflective of the pathology of non-AD dementia etiologies, could improve the accuracy of differential dementia diagnosis. CSF biomarkers will be of help to establish a correct and early AD diagnosis, even in the preclinical stages of the disease, which will be of importance once disease-modifying drugs for AD become available. Variation in biomarker measurements still jeopardize the introduction of CSF biomarkers into routine clinical practice and clinical trials, but several national and international standardization initiatives are ongoing.     

Effect of mesenchymal stromal cell transplantation on long-term survival in amyotrophic lateral sclerosis

Background aimsThanks to their immunomodulatory, tissue-protective and regenerative properties, mesenchymal stromal cells (MSCs) are a promising approach for amyotrophic lateral sclerosis (ALS); however, trials are limited and few follow-up studies have been published. This post-hoc analysis aims to describe the potential long-term effects of MSCs in ALS, analyzing data from two phase 1 clinical trials in ALS patients conducted by our group in 2002 and 2006.MethodsWe conducted two consecutive phase 1 prospective, open, pilot clinical trials, enrolling a total of 19 ALS patients. We followed patients for the duration of the disease. For each patient, we used the European Network to Cure ALS (ENCALS) survival prediction model to retrospectively calculate the expected survival at diagnosis. We then compared the predicted disease duration with the observed survival, analyzing patients at a single-patient level.ResultsUsing the ENCALS model, we predicted short survival in one patient, intermediate survival in three patients, long survival in three patients and very long survival in 12 patients. The difference between predicted and observed survival for the whole group was significant and demonstrated a mean predicted survival of 70.79 months (standard deviation [SD], 27.53) and a mean observed survival of 118.8 months (SD, 89.26) (P = 0.016). Based on the monthly ALS Functional Rating Scale–Revised progression rate (median, 0.64/month), we considered 10 of 19 patients slow progressors and nine of 19 patients fast progressors. Of the slow progressors, eight of 10 (80%) had significantly increased disease duration compared with predicted, and only two (20%) had decreased estimated disease duration. By contrast, five of nine (55%) fast progressors had increased disease duration, whereas four (45%) had decreased disease duration. To date, four patients are still alive.ConclusionsThe current study represents the first very long-term analysis of survival as an effect of MSC focal transplantation in the central nervous system of ALS patients, demonstrating that MSC transplantation could potentially slow down ALS progression and improve survival. Due to the interindividual variability in clinical course, at the current state of our knowledge, we cannot generalize the results, but these data provide new insights for planning the next generation of efficacy MSC clinical trials in ALS.     

Biomarkers of neurodegenerative disorders： How good are they？

Biomarkers are very important indicators of normal and abnormal biological processes. Specific changes in pathologies,biochemistries and genetics can give us comprehensive information regarding the nature of any particular disease. A good biomarker should be precise and reliable, distinguishable between normal and interested disease, and differentiable between different diseases. It is believed that biomarkers have great potential in predicting chances for diseases, aiding in early diagnosis, and setting standards for the development of new remedies to treat diseases. New technologies have enabled scientists to identify biomarkers of several different neurodegenerative diseases. The followings, for instance,are only a few of the many new biomarkers that have been recently identified: the phosphorylated tau protein and aggregated β-amyloid peptide for Alzheimer‘s disease (AD), α-synuclein contained Lewy bodies and altered dopamine transporter (DAT) imaging for Parkinson‘s disease (PD), SOD mutations for familial amyotrophic lateral sclerosis (ALS), and CAG repeats resulted from Huntington‘s gene mutations in Huntington‘s disease (HD). This article will focus on the most-recent findings of biomarkers belonging to the four mentioned neurodegenerative diseases.     

Clinical neurophysiology in ALS

Amyotrophic lateral sclerosis (ALS) belongs to a group of disorders known as motor neuron diseases. Despite being one of the most devastating diseases known, there is little evidence for diagnosing and managing patients with ALS. Clinical neurophysiologic tests are essential, when no biological marker exists to aid early diagnosis, not only in relation to diagnosis, but also in the development of disease progression, and perhaps, in the future, in measuring patients' response to therapy. The electrophysiological features used in the diagnosis of ALS are based on Awaji-shima consensus recommendations for the application of electrophysiological tests, as applied to the revised El Escorial Criteria. Measurements of axonal excitability through nerve conduction study (ENG) is useful to evaluate axonal degeneration. Electromyography (EMG) recordings with needle examination are essential for confirming lower motor neuron involvement in the initial diagnosis of ALS. EMG abnormalities are frequent and these include fibrillation potentials or positive sharp wave potentials, or both, with fasciculation potentials in resting muscle, and an incomplete interference pattern, with abnormal motor unit potentials. Collateral or terminal nerve sprouting is common in ALS and is frequent large macro-motor unit potentials (MUPs). Motor unit number estimation (MUNE) may be useful in measuring loss of functioning motor units and is an attractive endpoint measure in clinical drug trials in ALS because it directly assesses loss of lower motor neurons and is sensitive to disease progression. Transcortical magnetic stimulation protocols, and cortical excitability may be useful to assess the involvement of upper motor neuron system. In this chapter the advantages, limitations and promise of these various methods are discussed, in order to indicate the direction for further neurophysiological studies in this disorder.     

Amyotrophic lateral sclerosis (motor neuron disease): proposed mechanisms and pathways to treatment

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterised by loss of motor neurons. The cause of disease is unknown other than in the rare cases of familial disease arising from mutations in the superoxide dismutase 1 gene. Many theories for pathogenesis have been proposed - including oxidative stress, excitotoxicity, mitochondrial dysfunction and abnormal protein aggregation - based on studies of human post mortem tissue, research on animal models, and in vitro work. Here we review the evidence for the main pathogenic mechanisms and outline how they might interact to cause motor neuron death. Clinical trials have as yet failed to identify any truly effective therapies in ALS, with only riluzole providing a modest improvement in survival. Ongoing trials are exploring the value of antiglutamatergic agents, including the cephalosporin antibiotic ceftriaxone, as well as antioxidants, mitochondrial enhancers and anti-apoptotic drugs. It is likely that effective therapy will involve combinations of agents acting on different mechanisms. Gene therapy with neurotrophic factors will soon be in clinical trials, while work on stem cell therapy remains preclinical. In addition to finding effective therapies, research also needs to identify early disease markers because therapy is likely to be of most benefit when given early in the course of disease.     

Proteomics in clinical interventions: achievements and limitations in biomarker development

Development of toxicological and clinical biomarkers for disease diagnosis, quantification of toxicant/drug responses and rapid patient care are major concerns in modern biology. Even after human genome sequencing, identification of specific molecular signatures for unambiguous correlation with toxicity and clinical interventions is a challenging task. Differential protein expression patterns and protein-protein interaction studies have started unraveling rigorous molecular explanation of multi-factorial and toxicant borne diseases. Proteome profiling is extensively used to investigate etiology of diseases, develop predictive biomarkers for toxicity and therapeutic interventions and potential strategies for treatment of complex and toxicant mediated diseases. In this review, achievements and limitations of proteomics in developing predictive biomarkers for toxicological and clinical interventions have been discussed.     

Biomarkers in rare neuromuscular diseases

Neuromuscular diseases (NMDs) comprise a range of rare disorders that include both hereditary peripheral neuropathies and myopathies. The heterogeneity and rarity of neuromuscular disorders are challenges for researchers seeking to develop effective diagnosis and treatment strategies. In particular, clinical trials of new therapies are made more difficult due to lack of reliable and monitorable clinical outcome measures. Biomarkers could be a way to speed up research in this field, shedding light on the pathophysiological mechanisms behind such diseases and providing invaluable tools for monitoring their progression, prognosis and response to drug treatment. Furthermore, biomarkers could represent a surrogate endpoint for clinical trials, enabling better stratification of patient cohorts through more accurate diagnosis and prognosis prediction.