Amyotrophic lateral sclerosis & frontotemporal degeneration最新文献

This study aimed to derive standardized regression-based (SRB) reliable change indices (RCIs) for the cognitive section of the Portuguese Edinburgh Cognitive and Behavioral ALS Screen (ECAS-C). Forty-nine MND patients undergoing the ECAS were followed-up (T1) at 7.2 ± 2 months (range = 5-12). RCIs were derived via an SRB approach by accounting for demographic, motor-functional and test-related variables. Practice effects were detected as to Total and Memory measures; all ECAS-C measures proved to be reliable at retest. Baseline ECAS-C measures predicted their follow-up performances. SRB RCIs herewith delivered will help assess MND patients' cognition over time, although they would benefit from further validation in independent cohorts.

Objective: Amyotrophic lateral sclerosis (ALS) has a poorly understood preclinical phase, particularly concerning diagnostic blood markers. Our objective was to determine whether distinct patterns in routinely collected clinical and laboratory markers exist during the preclinical phase and could be incorporated to facilitate early diagnosis. Methods: We conducted a longitudinal, retrospective, case-control study with health records of prediagnostic ALS patients (PDALS) from health maintenance organizations covering approximately 40% of the Israeli population. We included PDALS with at least 10 clinical visits and a minimal observation period of 36 months prior to the diagnosis date to measure differences between PDALS and controls and analyzed data from 1,810 adult individuals; 362 PDALS and 1,448 age- and sex-matched controls. Results: Significant differences were found in PDALS many months before the diagnosis date. These included biochemical parameters such as urea, creatinine, CK, calcium, iron, and liver enzymes, hematological values, and BMI. Some differences were detectable over 10 years prior to the diagnosis date. Conclusions: This study highlights the potential for early detection of ALS based on blood markers in the years preceding clinical diagnosis. These findings could significantly expedite diagnosis, identify individuals at risk for ALS, and uncover unrecognized disease mechanisms.

Background: Motor neuron disease (MND) profoundly impacts mobility, yet gait-specific dysfunctions due to MND remain poorly understood. Methods: We characterized lower-limb gait alterations in people living with MND (plwMND) using advanced biomechanical tools. Nine plwMND and nine non-neurodegenerative disease controls walked on an instrumented treadmill at self-selected speeds. Ground reaction forces and joint motions were measured to model lower-limb kinetics, kinematics, and energetics. Results: PlwMND had reduced forward propulsive (p < 0.001) and braking (p = 0.002) ground reaction forces. Ankle range of motion was 10.0 ± 3.1° lower (p = 0.035) with peak positive ankle moment and power 33% and 72% lower, respectively (both: p < 0.001), in plwMND compared to controls. Conclusions: These lower-limb impairments highlight the ankle as an early and critical locus of dysfunction, with distal weakness driving compensatory proximal strategies, increasing walking inefficiency and fatigue. Integrating biomechanical and clinical data offers new insights into gait disruption in MND, supporting the development of targeted, personalized interventions to maintain independent mobility.

Introduction: Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by loss of motor neurons. Current medications are largely ineffective, associated with side effects, and hindered by a lack of agreement over treatment pathways. The time-intensive process and high costs further limit the development of therapeutics. Therefore, this research aimed to identify FDA-approved drugs that inhibit three proteins (Casein kinase 1, Protein tyrosine kinase 2, Ephrin type-A receptor 4) associated with ALS.

Methods: A machine learning (ML) model was trained for each protein to identify an inputted compound as an active inhibitor of that protein. The FDA-approved drugs were then screened through these models, and 18 drugs were identified as likely inhibitors for all three proteins. The results were validated through protein-ligand docking of each drug to its respective protein(s).

Results: Risperidone was the most active drug, with an average ML score of 1 and binding affinity of -8.9. The ML scores and binding affinities had a strong correlation, indicating reliability.

Conclusion: This research predicted multiple drugs that can simultaneously target many proteins involved in ALS, creating more effective treatment options at a lower cost. This procedure can be applied to efficiently discover drugs for other diseases in the future.

Objective: Perturbation of iron homeostasis is a potential key mechanism involved in neurodegeneration across many neurological disorders, including amyotrophic lateral sclerosis (ALS). We hypothesized that changes in quantitative susceptibility mapping (QSM) could capture perturbations in brain iron concentration in subgroups of ALS patients stratified by clinical phenotype and disease progression. Method: We enrolled 38 ALS patients (23 males - mean age: 58.7 ± 9.8), screened by clinical (ALS functional rating scale-revised, ALSFRS-R) and neuropsychological scales. Patients were a posteriori classified as fast (n = 16) or slow (n = 22) progressors. Two subgroups were also considered: pyramidal (or upper motor neuron+, UMN+) patients (n = 18), and patients with other phenotypes (n = 20). Results: Comparing fast vs. slow progressors, significant differences in iron deposits were observed in the left (p = 0.028) and right amygdala (p = 0.022), and in susceptibility distribution on the right hippocampus (p = 0.0011). Comparing UMN+ vs. other phenotypes, significant susceptibility differences emerged in the left thalamus (p = 0.0014) and right amygdala (p = 0.001). QSM changes were associated with baseline ALSFRS-R (rho = 0.36, p = 0.026) in the left paracentral cortex, and iron concentration with UMN score (rho = 0.35, p = 0.034). Moreover, the Edinburgh Cognitive and Behavioral ALS Screen (ECAS) was associated with iron deposits in the left thalamus (rho=-0.46, p = 0.0041). Conclusions: We confirmed that QSM alterations in extra-motor areas and subcortical regions may be distinctive hallmarks of neurodegeneration in pure/dominant UMN phenotypes of ALS. Moreover, we showed that QSM could be a valuable tool to differentiate patients with different progression rates and phenotypes, suggesting that QSM may support a prognostically useful early stratification of ALS patients.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that leads to widespread motor deterioration, including significant motor speech impairments. Speech intelligibility is a crucial component of communication affected in ALS, requiring objective, scalable assessment methods as an indicator of disease progression and treatment efficacy. Objective: This study investigates whether speech and bulbar function in ALS could be evaluated and monitored utilizing an automated digital measure of speech intelligibility derived from naturalistic picture descriptions. Methods: Speech recordings from 44 patients living with ALS (plwALS) and 49 matched healthy controls (HC) were analyzed and processed utilizing an automated speech analysis pipeline to extract an intelligibility score. These were part of a cross-sectional and longitudinal study involving two assessments. Results: The findings confirmed that speech intelligibility is significantly reduced in plwALS compared to HC. Those with bulbar-onset ALS have lower intelligibility than those with spinal-onset ALS, and the intelligibility of individuals with bulbar symptoms-regardless of the onset type-is lower than in plwALS without bulbar symptoms. Declining ALS-related speech scores correspond with worsening intelligibility in longitudinal assessments. Intelligibility correlates strongly with bulbar-specific clinical measures but not with global scores, highlighting its role in tracking bulbar progression. In some plwALS, we were able to demonstrate that automated speech analyses are more effective in detecting worsening in intelligibility earlier than standard clinical scoring. Conclusion: Our findings highlight that automated speech intelligibility assessments can be a valuable marker to improve clinical monitoring and facilitate earlier intervention in ALS as a supplement to standard assessments.

Background: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with marked clinical and genetic heterogeneity. Data from India remain scarce, although unique survival patterns and regional genetic variation have been suggested. Objective: To define the genetic spectrum of ALS in an Indian cohort and assess the contribution of known and novel variants. Methods: We recruited 238 patients with clinically confirmed ALS from across India, all negative for C9orf72 repeat expansions. Genetic testing included targeted panels, whole exome sequencing, and screening of ALS-associated gene curated panels. Variants were prioritized using allele frequency thresholds, in silico prediction, and ACMG criteria. Results: Pathogenic or likely pathogenic variants were identified in 13 patients (6.8%). SOD1 mutations were the most frequent, followed by TARDBP, OPTN, and NEK1. Variants of uncertain significance were more common, with recurrent SQSTM1 changes suggesting a potential modifier role. Additional rare or novel variants were detected in genes including SETX, ALS2, DISC1, CNTN4, and MATR3. Conclusion: This is among the largest genetic studies of ALS in India. The predominance of SOD1 mutations underscores population-specific differences and highlights the clinical importance of early genetic testing, particularly as gene-targeted therapies become available. The recurrent identification of SQSTM1 variants suggests modifier effects that require functional validation. These findings expand the genetic landscape of ALS in an underrepresented population and provide a foundation for precision medicine approaches in India.

Objective: Understanding the experiences of people living with amyotrophic lateral sclerosis (plwALS) is necessary to appreciate their unique needs. Age and stage in the life course influence how illness is experienced; however, the extent to which age-specific complexities of living with ALS have been examined remains unexplored. This review aims to map the available evidence exploring age, age-graded role, or life-course transition with regards to the experience of ALS and to identify age-specific gaps in the literature. Methods: A scoping review guided by Joanna Briggs Institute methodology was undertaken. Eligible articles included peer-reviewed primary research studies, published in English from 2010 onward, investigating illness experience of adults with ALS with consideration for how age, age-graded roles, or life-course transitions influenced experience. Database sources included: Ovid's Medline, Embase, and PsycINFO; EBSCO CINAHL; and ProQuest Sociological Abstracts. Findings related to ALS experience and dimensions of age were summarized descriptively and categorized using qualitative content analysis. Results: Six thousand one hundred and eighty individual records were identified and screened. Forty-five articles, reporting 42 studies, were included. Findings regarding thoughts, feelings, or emotions of plwALS were most common and varied depending on whether they were in reference to chronological age or age-graded role. Despite the importance of life-course transitions for illness experience, they were not routinely considered. Conclusion: Numerous aspects of the experience of plwALS have been reported in reference to age; however, the significance of age-graded roles and life-course transitions warrants further examination. Recognition of age-related complexities of living with ALS will facilitate more personalized ALS care.

Objective: Apathy is the most prevalent behavioral impairment or difficulty for people with ALS (pwALS), with Initiation apathy (a lack of motivation for self-generation of thoughts and/or actions) the most common subtype. Self-rated or self-perceived quality of life (sQoL) is impacted for pwALS, but the relationship to apathy subtypes is unknown. The aim was to explore the relationship between sQoL domains and apathy in pwALS. Methods: 32 pwALS were recruited and completed self-rated measures of apathy (Dimensional Apathy Scale), depression, anxiety, and emotional lability. The ALS-specific QoL short-form instrument was used to measure QoL. Cognitive functioning and functional disability were measured. Exploratory, comparative, and predictive multiple hierarchical regression analyses were performed. Results: Initiation apathy was the most common apathy subtype at 37.5% (N = 12). PwALS with Initiation apathy had higher depressive symptoms (p <.05, d = 1.11 large effect) and lower cognitive functioning (p <.05, d = 0.76 medium effect) than those without apathy. PwALS with Initiation apathy had significantly worse sQoL in domains of interaction with people and the environment (p <.05, d = 0.92, large effect) and negative emotions (p <.05, d = 0.80, large effect) than those without apathy. Regression analysis showed Initiation apathy was a significant negative predictor of the sQoL domain of interaction with people and the environment (beta =-.20, p <.01), controlling for confounders (functional disability, depression, cognitive functioning). Conclusions: Initiation apathy was associated with QoL domains of interaction with people and the environment, from the perspective of the pwALS. This emphasizes the importance of self-rating or self-perception for clinical and researcher assessment of apathy and QoL for pwALS.

Survival outcomes are commonly analyzed in studies with data from patients with progressive, neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS). Given the fast progression of ALS, survival analyses are, however, often difficult to perform and interpret. In this methodological article we demonstrate on real-world data how the choices we make in the study design, data collection, and analysis could influence the results. The factors we consider in this study are length of follow-up, sample size, timing of sample collection, and choice of covariables adjusted for in the models. We further discuss the importance of each of these contributing factors and about how to avoid mistakes in interpreting and reporting survival data in ALS and other rare, progressive diseases.