Hope and foresight for your patients with ALS

Blockade of the neurite outgrowth inhibitor Nogo-A in amyotrophic lateral sclerosis

Although prior studies have suggested a role of cardiometabolic health on pathogenesis of amyotrophic lateral sclerosis (ALS), the association with diabetes mellitus has not been widely examined. Amyotrophic lateral sclerosis is the most common motor neuron disorder. Several vascular risk factors have been associated with decreased risk for ALS. Although diabetes is also a risk factor for vascular disease, the few studies of diabetes and ALS have been inconsistent. To examine the association between diabetes and obesity, each identified through International Statistical Classification of Diseases, Eighth or Tenth Revision codes in a hospital registry, and ALS using data from the Danish National Registers. Population-based nested case-control study of 3650 Danish residents diagnosed as having ALS between January 1, 1982, and December 31, 2009, and 365,000 controls (100 for each ALS case) matched on age and sex. The analysis was conducted in September and October 2014. Adjusted odds ratio for ALS associated with diabetes or obesity diagnoses at least 3 years prior to the ALS diagnosis date. When considering diabetes and our obesity indicator together, the estimated odds ratio for ALS was 0.61 (95% CI, 0.46-0.80) for diabetes and 0.81 (95% CI, 0.57-1.16) for obesity. We observed no effect modification on the association with diabetes by sex. We did find a significant modification by age at ALS diagnosis and age at first mention of diabetes in the hospital registers. The protective association was stronger with increasing age at ALS diagnosis (P = .01), and the odds ratio for first mention of diabetes was 1.66 (95% CI, 0.85-3.21) before age 40 years but 0.52 (95% CI, 0.39-0.70) for older ages. These results are consistent with different associations for type 1 vs type 2 diabetes. In this Danish nationwide study to investigate the association between diabetes and ALS diagnosis, our findings are in agreement with previous reports of a protective association between vascular risk factors and ALS and suggest that type 2 diabetes, but not type 1, is protective for ALS.

Background Amyotrophic lateral sclerosis (ALS) is a fatal disease whose diagnosis and early management can improve survival. The most used diagnostic criteria are the revised El Escorial criteria (rEEC) and Awaji criteria (AC). The comparison of their sensitivities showed contradictory results. Our study aimed to compare the sensitivities of these two criteria in the diagnosis of definite ALS, at first visit, in a Tunisian hospital cohort. Materials and Methods This was a retrospective study including 173 patients diagnosed with ALS at the Department of Neurology of the Razi Hospital between January 2003 and April 2018.After studying the clinical features of the disease in our study population,each patient was categorized according to the rEEC and AC based on data collected in his medical record during his first visit to our department. Then, we compared the sensitivities of these two criteria in the diagnosis of definite ALS. Results Our Tunisian cohort was characterized by a slower disease progression. The sensitivity of the AC (69.4%) was significantly higher than that of the rEEC (40.5%) (p < 0.001). When the clinical signs evolved for less than 6 months, the sensitivities were 61% for AC and 12% for rEEC (p < 0.001). After 24 months of disease progression, the sensitivities were 78.2% for AC and 69.1% for rEEC (p = 0.063). It was impossible to categorize seventeen patients by the two criteria. Conclusion Our study demonstrated that patients in AC are more sensitive than rEEC in the early diagnosis of ALS in our Tunisian cohort. However, this superiority is gradually reduced during the evolution of the disease.

To evaluate the incremental value of FDG-PET over clinical tests in: (i) diagnosis of amyotrophic lateral sclerosis (ALS); (ii) picking early signs of neurodegeneration in patients with a genetic risk of Huntington's disease (HD); and detecting metabolic changes related to cognitive impairment in (iii) ALS and (iv) HD patients. Four comprehensive literature searches were conducted using the PICO model to extract evidence from relevant studies. An expert panel then voted using the Delphi method on these four diagnostic scenarios. The availability of evidence was good for FDG-PET utility to support the diagnosis of ALS, poor for identifying presymptomatic subjects carrying HD mutation who will convert to HD, and lacking for identifying cognitive-related metabolic changes in both ALS and HD. After the Delphi consensual procedure, the panel did not support the clinical use of FDG-PET for any of the four scenarios. Relative to other neurodegenerative diseases, the clinical use of FDG-PET in ALS and HD is still in its infancy. Once validated by disease-control studies, FDG-PET might represent a potentially useful biomarker for ALS diagnosis. FDG-PET is presently not justified as a routine investigation to predict conversion to HD, nor to detect evidence of brain dysfunction justifying cognitive decline in ALS and HD.

The distribution of muscle involvement, assessed clinically and electromyographically, was analyzed prospectively in 55 consecutive amyotrophic lateral sclerosis (ALS) patients and in 54 patients with other predominantly motor syndromes, some of whom were referred with suspected ALS. In ALS patients, distal limb muscles and thoracic paraspinal muscles were affected most frequently, more so than proximal limb and cranial muscles. The incidence of bulbar symptoms in ALS was greater in women than in men. These patterns suggest selective vulnerability of specific neuronal populations. The vulnerability of truncal muscles, illustrated by thoracic paraspinal wasting or head and shoulder drooping, was a helpful differential sign in diagnosing ALS. Thoracic paraspinal electromyography was especially valuable in distinguishing ALS from other disorders, such as combined cervical and lumbar spondylotic amyotrophy or polymyositis, which may masquerade as ALS. The finding of denervation atrophy on biopsy of thoracic paraspinal muscles was diagnostic in difficult cases. Because the thoracic paraspinal muscles are frequently affected in ALS and spared in spondylotic amyotrophy, their assessment provides a practical strategy in differentiating ALS from other motor syndromes.

An objective biomarker for early identification and accurate differential diagnosis of amyotrophic lateral sclerosis (ALS) is lacking. (18)F-FDG PET brain imaging with advanced statistical analysis may provide a tool to facilitate this. The objective of this work was to validate volume-of-interest (VOI) and voxel-based (using a support vector machine [SVM] approach) (18)F-FDG PET analysis methods to differentiate ALS from controls in an independent prospective large cohort, using a priori-derived classifiers. Furthermore, the prognostic value of (18)F-FDG PET was evaluated. A prospective cohort of patients with a suspected diagnosis of a motor neuron disorder (n = 119; mean age ± SD, 61 ± 12 y; 81 men and 38 women) was recruited. One hundred five patients were diagnosed with ALS (mean age ± SD, 61.0 ± 12 y; 74 men and 31 women) (group 2), 10 patients with primary lateral sclerosis (mean age ± SD, 55.5 ± 12 y; 3 men and 7 women), and 4 patients with progressive muscular atrophy (mean age ± SD, 59.2 ± 5 y; 4 men). The mean disease duration of all patients was 15.0 ± 13.4 mo at diagnosis, with PET conducted 15.2 ± 13.3 mo after the first symptoms. Data were compared with a previously gathered dataset of 20 screened healthy subjects (mean age ± SD, 62.4 ± 6.4 y; 12 men and 8 women) and 70 ALS patients (mean age ± SD, 62.2 ± 12.5 y; 44 men and 26 women) (group 1). Data were spatially normalized and analyzed on a VOI basis (statistical software (using the Hammers atlas) and voxel basis using statistical parametric mapping. Discriminant analysis and SVM were used to classify new cases based on the classifiers derived from group 1. Compared with controls, ALS patients showed a nearly identical pattern of hypo- and hypermetabolism in groups 1 and 2. VOI-based discriminant analysis resulted in an 88.8% accuracy in predicting the new ALS cases. For the SVM approach, this accuracy was 100%. Brain metabolism between ALS and primary lateral sclerosis patients was nearly identical and not separable on an individual basis. Extensive frontotemporal hypometabolism was predictive for a lower survival using a Kaplan-Meier survival analysis (P < 0.001). On the basis of a previously acquired training set, (18)F-FDG PET with advanced discriminant analysis methods is able to accurately distinguish ALS from controls and aids in assessing individual prognosis. Further validation on multicenter datasets and ALS-mimicking disorders is needed to fully assess the general applicability of this approach.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive and selective degeneration of motor neurons in the motor cortex of brain and spinal cord. Ferroptosis is a newly discovered form of cell death and reported to mediate selective motor neuron death in the mouse model of ALS. The growing awareness of ferroptosis and iron metabolism dysfunction in ALS prompted us to investigate the expression pattern of ferroptosis and iron metabolism-related genes (FIRGs) in ALS. Here, we performed a conjoint analysis of bulk-RNA sequence and single-nucleus RNA sequence data using the datasets from Gene Expression Omnibus (GEO) to reveal the role of FIRGs in ALS, especially in selective motor neuron death of ALS. We first investigated the differentially expressed genes (DEGs) between ALS and non-neurological controls. Weighted gene co-expression network analysis constructed the gene co-expression network and identified three modules closely associated with ALS. Fifteen FIRGs was identified as target genes based on least absolute shrinkage and selection operator regression analysis as follows: ACSL4, ANO6, ATP6V0E1, B2M, CD44, CHMP5, CYBB, CYBRD1, HIF1A, MOSPD1, NCF2, SDCBP, STEAP2, TMEM14C, ULK1. These genes could differentiate ALS patients from non-neurological controls (p < 2.2e−16) and had a valid value in predicting and diagnosing ALS (AUC = 0.881 in primary dataset and AUC = 0.768 in validation dataset). Then we performed the functional enrichment analysis of DEGs between ALS cases, the most significantly influenced by target genes, and non-neurological controls. The result indicated that the most significantly influenced functions in ALS pathogenesis by these identified FIRGs are synapse pathways, calcium signaling pathway, cAMP signaling pathway, and phagosome and several immune pathways. At last, the analysis of single- nuclear seq found that CHMP5, one of the 15 FIRGs identified by bulk single-nucleus RNA-seq data, was expressed significantly higher in ALS than pathologically normal (PN), specifically in excitatory neuron populations with layer 2 and layer 3 markers (Ex L2_L3), layer 3 and layer 5 markers (Ex L3_L5). Taken together, our study indicates the positive correlation between FIRGs and ALS, presents potential markers for ALS diagnosis and provides new research directions of CHMP5 function in selective motor neuron death in ALS.

EAAT2 is a high affinity, Na+-dependent glutamate transporter with predominant astroglial localization. It accounts for the clearance of the bulk of glutamate released at central nervous system synapses and therefore has a crucial role in shaping glutamatergic neurotransmission and limiting excitotoxicity. Caspase-3 activation and impairment in expression and activity of EAAT2 are two distinct molecular mechanisms occurring in human amyotrophic lateral sclerosis (ALS) and in the transgenic rodent model of the disease. Excitotoxicity caused by down-regulation of EAAT2 is thought to be a contributing factor to motor neuron death in ALS. In this study, we report the novel evidence that caspase-3 cleaves EAAT2 at a unique site located in the cytosolic C-terminal domain of the transporter, a finding that links excitotoxicity and activation of caspase-3 as converging mechanisms in the pathogenesis of ALS. Caspase-3 cleavage of EAAT2 leads to a drastic and selective inhibition of this transporter. Heterologous expression of mutant SOD1 proteins linked to the familial form of ALS leads to inhibition of EAAT2 through a mechanism that largely involves activation of caspase-3 and cleavage of the transporter. In addition, we found evidence in spinal cord homogenates of mutant SOD1 ALS mice of a truncated form of EAAT2, likely deriving from caspase-3-mediated proteolytic cleavage, which appeared concurrently to the loss of EAAT2 immunoreactivity and to increased expression of activated caspase-3. Taken together, our findings suggest that caspase-3 cleavage of EAAT2 is one mechanism responsible for the impairment of glutamate uptake in mutant SOD1-linked ALS.

Epidural Anesthesia and Pulmonary Function in a Patient with Amyotrophic Lateral Sclerosis

TDP-43 (43-kDa TAR DNA-binding domain protein) is a major constituent of ubiquitin-positive cytoplasmic aggregates present in neurons of patients with fronto-temporal lobular dementia and amyotrophic lateral sclerosis (ALS). The pathologic significance of TDP-43 aggregation is not known; however, dominant mutations in TDP-43 cause a subset of ALS cases, suggesting that misfolding and/or altered trafficking of TDP-43 is relevant to the disease process. Here, we show that the presenilin-binding protein ubiquilin 1 (UBQLN) plays a role in TDP-43 aggregation. TDP-43 interacted with UBQLN both in yeast and in vitro, and the carboxyl-terminal ubiquitin-associated domain of UBQLN was both necessary and sufficient for binding to polyubiquitylated forms of TDP-43. Overexpression of UBQLN recruited TDP-43 to detergent-resistant cytoplasmic aggregates that colocalized with the autophagosomal marker, LC3. UBQLN-dependent aggregation required the UBQLN UBA domain, was mediated by non-overlapping regions of TDP-43, and was abrogated by a mutation in UBQLN previously linked to Alzheimer disease. Four ALS-associated alleles of TDP-43 also coaggregated with UBQLN, and the extent of aggregation correlated with in vitro UBQLN binding affinity. Our findings suggest that UBQLN is a polyubiquitin-TDP-43 cochaperone that mediates the autophagosomal delivery and/or proteasome targeting of TDP-43 aggregates.

Frequency of euthanasia, factors associated with end-of-life practices, and quality of end-of-life care in patients with amyotrophic lateral sclerosis in the Netherlands: a population-based cohort study

Purpose: To describe i) nurse’s utilisation and associated costs during 4-year tele-assistance in amyotrophic lateral sclerosis (ALS) ii) optimal time for initiating tele-assistance. Method: 73 ALS patients after hospital discharge were followed up on voice by phone calls conducted by a nurse through a clinical card which was tested for feasibility, efficacy and utility. Number of patients simultaneously assisted/month, calls/patient, fixed and variable costs were calculated. Results: Time between disease’s diagnosis and the beginning of tele-assistance was 720 ± 971 days. ALS patients’ percentage managed by nurses through tele-assistance increased over time by 628%. Tele-assistance integrated care (TAIC) followed up patients with a total of 5073 telephone calls. Steady state activity was reached at the 3rd year employing 5 ± 3 calls/pt/month (time/call 64 ± 44 min). Implementing the card was feasible, useful and effective by operator. Survival from diagnosis of ALS was 1224 ± 1150 days. Survival was related to tracheotomy. Conclusion: TAIC is a feasible tool to manage up to 25 ALS patients/month/nurse and costs about €105.00 per patient per month. Tele-assistance is proposed at 2/3 of time course of the disease.Implications for RehabilitationPeople with ALS have a complex time course of their disease necessitating important clinical decisions.Individually structured holistic and rehabilitative programmes are required.Tele-assistance has been demonstrated to be useful to follow-up providing autonomy of care, psychosocial monitoring, interventions and a source of information.Tele-assistance integrated care is a feasible tool to manage up to 25 ALS patients/month/nurse.Tele-assistance costs about €105.00 per patient per month.Tele-assistance is proposed at 2/3 of time course of the disease.

BackgroundWidespread cortical atrophy in Amyotrophic Lateral Sclerosis (ALS) has been described in neuropathological studies. The presence of cortical atrophy in conventional and scientific neuroimaging has been a matter of debate. In studies using computertomography, positron emission tomography, proton magnetic resonance spectroscopy and conventional T2-weighted and proton-weighted images, results have been variable. Recent morphometric studies by magnetic resonance imaging have produced conflicting results regarding the extent of grey and white matter involvement in ALS patients.MethodsThe authors used optimized voxel-based morphometry as an unbiased whole brain approach to detect differences between regional grey and white matter volumes. Seventeen patients with a diagnosis of ALS according to El-Escorial criteria and seventeen age-matched controls received a high resolution anatomical T1 scan.ResultsIn ALS patients regional grey matter volume (GMV) reductions were found in the pre- and postcentral gyrus bilaterally which extended to premotor, parietal and frontal regions bilaterally compared with controls (p < 0.05, corrected for the entire volume). The revised ALS functional rating scale showed a positive correlation with GMV reduction of the right medial frontal gyrus corresponding to the dorsolateral prefrontal cortex. No significant differences were found for white matter volumes or when grey and white matter density images were investigated. There were no further correlations with clinical variables found.ConclusionIn ALS patients, primary sensorimotor cortex atrophy can be regarded as a prominent feature of the disease. Supporting the concept of ALS being a multisytem disorder, our study provides further evidence for extramotor involvement which is widespread. The lack of correlation with common clinical variables probably reflects the fact that heterogeneous disease processes underlie ALS. The discrepancy within all published morphometric studies in ALS so far may be related to differences in patient cohorts and several methodological factors of the data analysis process. Longitudinal studies are required to further clarify the time course and distribution of grey and white matter pathology during the course of ALS.

The El Escorial criteria for diagnosis of amyotrophic lateral sclerosis (ALS) have been in use for almost a decade. A revised set of criteria, meant to supersede the original set, was developed at a 1998 World Federation of Neurology (WFN) ALS meeting at Airlie House in Warrenton, Virginia, USA. This revised document, nicknamed El Escorial Revisited, has been published on the WFN-ALS website. El Escorial has proven useful in standardizing diagnostic criteria for entry into research trials and it is expected that El Escorial Revisited will help to liberalize such entry requirements. However, general neurologists and neuromuscular clinicians have found El Escorial to be unwieldy and generally unhelpful in achieving an earlier, accurate diagnosis of ALS. The El Escorial Revisited document is a step toward lessening these problems, but more 'user-friendly' criteria may be necessary for clinicians and those not conducting research. Such ALS criteria would improve categorization of ALS patients, would allow clinicians more latitude in beginning ALS treatment, and would educate practitioners to differentiate ALS from other motor neuron and non-motor neuron diseases. Intensive education of physicians will help improve earlier patient referral and accurate ALS diagnosis. There remains a group of 'difficult cases' that will continue to challenge the neuromuscular specialist. Earlier diagnosis in this latter group will require significant advances in the fields of electrodiagnosis, neuroimaging, immunobiochemistry, and neurogenetics.

PND53 Predictive Models Leveraging Machine Learning and Real-World Data for Early Diagnosis: An Application in Amyotrophic Lateral Sclerosis