Amyotrophic lateral sclerosis & frontotemporal degeneration最新文献

Introduction: Clinical trials location is determined by many factors, including the availability of patient populations, regulatory environment, scientific expertise, and cost considerations. In clinical drug development of amyotrophic lateral sclerosis (ALS), where genetic differences have been described and may be related to geographic setting, this could have implications for the clinical interpretation of results in underrepresented geographic settings. Objective: The aim of this study was to review country participation in ALS clinical research based on available data from clinical trial registries and databases. Methods: We performed a scoping review with available information about clinical trials on ALS in ClinicalTrials.gov (CT), EU clinical trials register (EudraCT), WHO International Clinical Trials Registry Platform (ICTRP) and Web of Science (WOS). Inclusion criteria were clinical trials in phase 2 and 3 to treat ALS, recruiting or active not recruiting, from 23/06/2018 to 23/06/2023. Results: The total number of clinical trials identified were 188; 54 studies in CT, 38 in EudraCT, 47 in ICTRP and 49 in WOS. We identified 77 clinical trials after deleting duplicates and applying exclusion criteria. The countries with most studies conducted were the US with 35 studies (10.9%), followed by the United Kingdom, Belgium, France and Germany with 21 studies each one of them (6.5%). Conclusion: The data obtained in our review showed a non-homogeneous distribution in clinical trials at the international level, which may influence the interpretation of the results obtained.

Background: Accumulating evidence suggests that non-genetic factors have important etiologic roles in amyotrophic lateral sclerosis (ALS), yet identification of specific culprit factors has been challenging. Many medications target biological pathways implicated in ALS pathogenesis, and screening large pharmacologic datasets for signals could greatly accelerate the identification of risk-modulating pharmacologic factors for ALS.

Method: We conducted a high-dimensional screening of patients' history of medication use and ALS risk using an advanced machine learning approach based on gradient-boosted decision trees coupled with Bayesian model optimization and repeated data sampling. Clinical and medication dispensing data were obtained from a large Israeli health fund for 501 ALS cases and 4,998 matched controls using a lag period of 3 or 5 years prior to ALS diagnosis for ascertaining medication exposure.

Results: Of over 1,000 different medication classes, we identified 8 classes that were consistently associated with increased ALS risk across independently trained models, where most are indicated for control of symptoms implicated in ALS. Some suggestive protective effects were also observed, notably for vitamin E.

Discussion: Our results indicate that use of certain medications well before the typically recognized prodromal period was associated with ALS risk. This could result because these medications increase ALS risk or could indicate that ALS symptoms can manifest well before suggested prodromal periods. The results also provide further evidence that vitamin E may be a protective factor for ALS. Targeted studies should be performed to elucidate the possible pathophysiological mechanisms while providing insights for therapeutics design.

Objective: Neuroinflammation is the hallmark of amyotrophic lateral sclerosis (ALS) disease. Regulatory T cells (Tregs) are essential in immune tolerance and neuroinflammation prevention. It has been shown that a significant decrease in Treg and FoxP3 protein expression is observed in ALS patients. The main reason for the FoxP3⁺ Treg loss in ALS is unknown. In this study, the role of autophagy dysregulation in FoxP3⁺ Tregs in ALS was investigated.

Methods: Twenty-three ALS patients and 24 healthy controls were recruited for the study. Mononuclear cells (MNCs) were obtained from peripheral blood, and then Tregs were isolated. Isolated Tregs were stained with FoxP3 and LC3 antibodies and analyzed in flow cytometry to determine autophagy levels in FoxP3⁺ Tregs in patients and controls.

Results: The mean of FoxP3⁺ LC3⁺ cells, were 0.47 and 0.45 in patients and controls, respectively. The mean of FoxP3⁺ LC3- cells was 0.15 in patients and 0.20 in controls, p = 0.030 (p < 0.05). There is no significant correlation between ALSFRS-R decay rate and autophagy level in patients. Also, there is no significant difference between autophagy levels in FoxP3⁺ Tregs in patients with rapidly progressing ALS and slow-progressing ALS.

Conclusion: Excessive autophagy levels in FoxP3⁺ Tregs in ALS patients can potentially be an explanation for an increased cell death and result in worsened neuroinflammation and disease onset. However, the disease progress is not attributable to autophagy levels in FoxP3⁺ Tregs.

Objective: We investigated non-motor symptoms in ALS using sequential questionnaires; here we report the findings of the second questionnaire.

Methods: A social media platform (Twitter, now known as X) was used to publicize the questionnaires. Data were downloaded from SurveyMonkey and analyzed by descriptive statistics, comparison of means, and regression models.

Results: There were 182 people with ALS and 57 controls. The most important non-motor symptoms were cold limbs (60.4% cases, 14% controls, p = 9.67 x 10^-10) and appetite loss (29.7% cases, 5.3% controls, p = 1.6 x 10^-4). The weaker limb was most likely to feel cold (p = 9.67 x 10^-10), and symptoms were more apparent in the evening and night. Appetite loss was reported as due to feeling full and the time taken to eat. People with ALS experienced medium-intensity pain, more usually shock-like pain than burning or cold-like pain, although the most prevalent type of pain was non-differentiated.

Conclusions: Non-motor symptoms are an important feature of ALS. Further investigation is needed to understand their physiological basis and whether they represent phenotypic differences useful for subtyping ALS.

Amyotrophic lateral sclerosis (ALS) is a complex, neurodegenerative disorder in which alterations in structural, physiological, and metabolic parameters act synergistically. Over the last decade there has been a considerable focus on developing drugs to slow the progression of the disease. Despite this, only four disease-modifying therapies are approved in North America. Although additional research is required for a thorough understanding of ALS, we have accumulated a large amount of knowledge that could be better integrated into future clinical trials to accelerate drug development and provide patients with improved treatment options. It is likely that future, successful ALS treatments will take a multi-pronged therapeutic approach, targeting different pathways, akin to personalized medicine in oncology. In this review, we discuss the link between ALS pathophysiology and treatments, looking at the therapeutic failures as learning opportunities that can help us refine and optimize drug development.

Objective: One of the difficulties in developing a novel drug for patients with amyotrophic lateral sclerosis (ALS) is the significant variation in the clinical course. To control this variation, a 12-week run-in period is used in some clinical trials. Based on the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALSFRS-R) change during the run-in period, only moderate progressors are selected in some clinical trials. Some reports showed that the ALSFRS-R progression rate was associated with survival. However, it is unclear whether the ALSFRS-R change in the run-in period is a useful prognostic factor of the ALSFRS-R change from baseline. In addition, we explore the inclusion criteria that could control the variability in ALS-function progression without setting a run-in period.

Methods: We utilized the Japanese and US ALS registry databases (JaCALS and PRO-ACT). Patients were classified into three populations (rapid, moderate, and slow progressors) based on the ALSFRS-R change prior to baseline. We also classified patients into three prognostic populations based on the ALSFRS-R change from baseline. We confirmed whether each of the three populations were matched with their respective three prognostic populations.

Results: Our data showed that the three groups classified by the ALSFRS-R change during the 12 weeks prior to baseline or by the rate of progression from onset to baseline did not accord with the three prognostic groups.

Conclusions: Our results showed that the ALSFRS-R change in the run-in period or from onset to baseline is not useful for stratifying subsequent progression of functional decline in clinical trials.

Objective: To predict ALS progression with varying observation and prediction window lengths, using machine learning (ML).

Methods: We used demographic, clinical, and laboratory parameters from 5030 patients in the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database to model ALS disease progression as fast (at least 1.5 points decline in ALS Functional Rating Scale-Revised (ALSFRS-R) per month) or non-fast, using Extreme Gradient Boosting (XGBoost) and Bayesian Long Short Term Memory (BLSTM). XGBoost identified predictors of progression while BLSTM provided a confidence level for each prediction.

Results: ML models achieved area under receiver-operating-characteristics curve (AUROC) of 0.570-0.748 and were non-inferior to clinician assessments. Performance was similar with observation lengths of a single visit, 3, 6, or 12 months and on a holdout validation dataset, but was better for longer prediction lengths. 21 important predictors were identified, with the top 3 being days since disease onset, past ALSFRS-R and forced vital capacity. Nonstandard predictors included phosphorus, chloride and albumin. BLSTM demonstrated higher performance for the samples about which it was most confident. Patient screening by models may reduce hypothetical Phase II/III clinical trial sizes by 18.3%.

Conclusion: Similar accuracies across ML models using different observation lengths suggest that a clinical trial observation period could be shortened to a single visit and clinical trial sizes reduced. Confidence levels provided by BLSTM gave additional information on the trustworthiness of predictions, which could aid decision-making. The identified predictors of ALS progression are potential biomarkers and therapeutic targets for further research.

Lion's Mane (Hericium erinaceus) has historically been used as traditional medicine in Asia and Europe for its potential benefits in fighting infection and cancer. It has gained interest in the neurodegenerative disease field because of its mechanisms of action; these include anti-inflammation, neuroprotection, and promoting neurite growth demonstrated in various cell and animal models. A very small, double-blind, placebo-controlled trial in patients with mild cognitive impairment showed a temporary improvement in cognitive function; this finding has yet to be replicated. However, there have been no studies in ALS cell or animal models or in humans with ALS. Lion's Mane appears safe and inexpensive when consumed in powder or capsule, but one anaphylactic case was reported after a patient consumed fresh Lion's Mane mushroom. Currently, we do not have enough information to support the use of Lion's Mane for treating ALS. We support further research in ALS disease models and clinical trials to study its efficacy.

ALS is a neurodegenerative disease characterized by loss of motor neurons, resulting in progressive weakness and wasting of muscles. The average survival time is 2-5 years, mostly due to respiratory failure. Since current therapies can prolong survival time by only a few months, multidisciplinary care remains the cornerstone of the management of ALS. At the ALS Expert Centre of University Hospitals Leuven, a large proportion of Belgian ALS patients are seen for diagnosis and a significant number is also in follow-up with the multidisciplinary team. In this retrospective study, we compared the outcome of incident patients who were in follow-up at our site with patients who were not in follow-up. We included 659 patients of which 557 (84.5%) received specialized care at the ALS Expert Centre. After adjusting for clinically relevant prognostic parameters, multidisciplinary follow-up significantly prolonged survival (p = 0.004; HR = 0.683; CI 95% [0.528 - 0.884]). This increase in survival is mainly driven by patients with spinal onset (p = 0.035; HR = 0.746; CI 95% [0.568 - 0.980]), since no significant increased survival time was observed in patients with bulbar onset (p = 0.28; HR = 0.778; CI 95% [0.495 - 1.223]). These data confirm that multidisciplinary follow-up contributes to a better outcome of patients, emphasizing the importance of multidisciplinary specialized care in ALS.

Objective: To assess the temporal relationship between premorbid lipid levels and long-term amyotrophic lateral sclerosis (ALS) risk.

Methods: From Norwegian cardiovascular health surveys (1974-2003), we collected information on total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), glucose, and other cardiovascular risk factors. ALS incidence and mortality were identified through validated Norwegian health registries. The relation between premorbid lipid levels and ALS risk was assessed by Cox regression models.

Results: Out of 640,066 study participants (51.5% females), 974 individuals (43.5% females) developed ALS. Mean follow-up time was 23.7 (SD 7.1) years among ALS cases. One mmol/l increase in LDL-C was associated with 6% increase in risk for ALS (hazard ratio 1.06 [95% CI: 1.01-1.09]). Higher levels of TC and TG were also associated with increased ALS risk, but only within the last 6-7 years prior to ALS diagnosis or death. No association between HDL-C and ALS risk was found. Adjusting for body mass index, birth cohort, smoking, and physical activity did not alter the results.

Conclusions: Higher levels of LDL-C are associated with increased ALS risk over 40 years later, compatible with a causal relationship. The temporal relationship between TG, TC, and ALS risk suggests that increased levels of these lipid biomarkers represent consequences of ALS.