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Riva N, Domi T, Pozzi L, Lunetta C, Schito P, Spinelli EG, Cabras S, Matteoni E, Consonni M, Bella ED, Agosta F, Filippi M, Calvo A, Quattrini A. Update on recent advances in amyotrophic lateral sclerosis. J Neurol 2024; 271:4693-4723. [PMID: 38802624 PMCID: PMC11233360 DOI: 10.1007/s00415-024-12435-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 05/07/2024] [Accepted: 05/09/2024] [Indexed: 05/29/2024]
Abstract
In the last few years, our understanding of disease molecular mechanisms underpinning ALS has advanced greatly, allowing the first steps in translating into clinical practice novel research findings, including gene therapy approaches. Similarly, the recent advent of assistive technologies has greatly improved the possibility of a more personalized approach to supportive and symptomatic care, in the context of an increasingly complex multidisciplinary line of actions, which remains the cornerstone of ALS management. Against this rapidly growing background, here we provide an comprehensive update on the most recent studies that have contributed towards our understanding of ALS pathogenesis, the latest results from clinical trials as well as the future directions for improving the clinical management of ALS patients.
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Affiliation(s)
- Nilo Riva
- 3Rd Neurology Unit and Motor Neuron Disease Centre, Fondazione IRCCS "Carlo Besta" Neurological Insitute, Milan, Italy.
| | - Teuta Domi
- Experimental Neuropathology Unit, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Laura Pozzi
- Experimental Neuropathology Unit, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Christian Lunetta
- Istituti Clinici Scientifici Maugeri IRCCS, Neurorehabilitation Unit of Milan Institute, 20138, Milan, Italy
| | - Paride Schito
- Experimental Neuropathology Unit, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Department of Neurology, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Edoardo Gioele Spinelli
- Department of Neurology, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neuroimaging Research Unit, Department of Neurology, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Sara Cabras
- ALS Centre, 'Rita Levi Montalcini' Department of Neuroscience, University of Turin; SC Neurologia 1U, AOU città della Salute e della Scienza di Torino, Turin, Italy
| | - Enrico Matteoni
- ALS Centre, 'Rita Levi Montalcini' Department of Neuroscience, University of Turin; SC Neurologia 1U, AOU città della Salute e della Scienza di Torino, Turin, Italy
| | - Monica Consonni
- 3Rd Neurology Unit and Motor Neuron Disease Centre, Fondazione IRCCS "Carlo Besta" Neurological Insitute, Milan, Italy
| | - Eleonora Dalla Bella
- 3Rd Neurology Unit and Motor Neuron Disease Centre, Fondazione IRCCS "Carlo Besta" Neurological Insitute, Milan, Italy
| | - Federica Agosta
- Department of Neurology, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neuroimaging Research Unit, Department of Neurology, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute Huniversity, Milan, Italy
| | - Massimo Filippi
- Department of Neurology, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neuroimaging Research Unit, Department of Neurology, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute Huniversity, Milan, Italy
| | - Andrea Calvo
- ALS Centre, 'Rita Levi Montalcini' Department of Neuroscience, University of Turin; SC Neurologia 1U, AOU città della Salute e della Scienza di Torino, Turin, Italy
| | - Angelo Quattrini
- Experimental Neuropathology Unit, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
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Vaage AM, Benth JŠ, Meyer HE, Holmøy T, Nakken O. Premorbid lipid levels and long-term risk of ALS-a population-based cohort study. Amyotroph Lateral Scler Frontotemporal Degener 2024; 25:358-366. [PMID: 38117120 DOI: 10.1080/21678421.2023.2295455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 12/11/2023] [Indexed: 12/21/2023]
Abstract
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.
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Affiliation(s)
- Anders Myhre Vaage
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jūratė Šaltytė Benth
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Health Services Research Unit, Akershus University Hospital, Lørenskog, Norway
| | - Haakon E Meyer
- Department of Physical Health and Ageing, Norwegian Institute of Public Health, Oslo, Norway, and
- Department of Community Medicine and Global Health, University of Oslo, Oslo, Norway
| | - Trygve Holmøy
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ola Nakken
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
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Yu W, Yu F, Li M, Yang F, Wang H, Song H, Huang X. Quantitative association between lead exposure and amyotrophic lateral sclerosis: a Bayesian network-based predictive study. Environ Health 2024; 23:2. [PMID: 38166850 PMCID: PMC10763408 DOI: 10.1186/s12940-023-01041-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 12/13/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Environmental lead (Pb) exposure have been suggested as a causative factor for amyotrophic lateral sclerosis (ALS). However, the role of Pb content of human body in ALS outcomes has not been quantified clearly. The purpose of this study was to apply Bayesian networks to forecast the risk of Pb exposure on the disease occurrence. METHODS We retrospectively collected medical records of ALS inpatients who underwent blood Pb testing, while matched controlled inpatients on age, gender, hospital ward and admission time according to the radio of 1:9. Tree Augmented Naïve Bayes (TAN), a semi-naïve Bayes classifier, was established to predict probability of ALS or controls with risk factors. RESULTS A total of 140 inpatients were included in this study. The whole blood Pb levels of ALS patients (57.00 μg/L) were more than twice as high as the controls (27.71 μg/L). Using the blood Pb concentrations to calculate probability of ALS, TAN produced the total coincidence rate of 90.00%. The specificity, sensitivity of Pb for ALS prediction was 0.79, or 0.74, respectively. CONCLUSION Therefore, these results provided quantitative evidence that Pb exposure may contribute to the development of ALS. Bayesian networks may be used to predict the ALS early onset with blood Pb levels.
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Affiliation(s)
- Wenxiu Yu
- Medical School of Chinese PLA, Beijing, 100853, China
- Neurological Department of the First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Fangfang Yu
- Department of Medical Innovation Research, PLA General Hospital, Beijing, 100853, China
| | - Mao Li
- Neurological Department of the First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Fei Yang
- Neurological Department of the First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Hongfen Wang
- Medical School of Chinese PLA, Beijing, 100853, China
- Neurological Department of the First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Han Song
- Department of Health Service, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Xusheng Huang
- Medical School of Chinese PLA, Beijing, 100853, China.
- Neurological Department of the First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China.
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Ansari U, Wen J, Taguinod I, Nadora D, Nadora D, Lui F. Exploring dietary approaches in the prevention and management of Amyotrophic Lateral Sclerosis: A literature review. AIMS Neurosci 2023; 10:376-387. [PMID: 38188002 PMCID: PMC10767066 DOI: 10.3934/neuroscience.2023028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 11/22/2023] [Accepted: 11/26/2023] [Indexed: 01/09/2024] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal and complex neurodegenerative disease of upper and lower motor neurons of the central nervous system. The pathogenesis of this multifaceted disease is unknown. However, diet has emerged as a modifiable risk factor that has neuroprotective effects towards other neurological disorders such as Alzheimer's, Parkinson's and dementia. Thus, this review aims to explore how diet can potentially influence ALS onset and/or progression. In this review, five popular diets (Mediterranean, Vegan, Carnivore, Paleolithic and Ketogenic) and their distinct macromolecule composition, nutritional profile, biochemical pathways and their potential therapeutic effects for ALS are thoroughly examined. However, the composition of these diets varies, and the data is controversial, with conflicting studies on the effectiveness of nutrient intake of several of these diets. Although these five diets show that a higher intake of foods containing anti-inflammatory and antioxidant compounds have a positive correlation towards reducing the oxidative stress of ALS, further research is needed to directly compare the effects of these diets and the mechanisms leading to ALS and its progression.
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Affiliation(s)
- Ubaid Ansari
- California Northstate University College of Medicine, USA
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Goutman SA, Savelieff MG, Jang DG, Hur J, Feldman EL. The amyotrophic lateral sclerosis exposome: recent advances and future directions. Nat Rev Neurol 2023; 19:617-634. [PMID: 37709948 PMCID: PMC11027963 DOI: 10.1038/s41582-023-00867-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/08/2023] [Indexed: 09/16/2023]
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal disease of motor neuron degeneration with typical survival of only 2-5 years from diagnosis. The causes of ALS are multifactorial: known genetic mutations account for only around 70% of cases of familial ALS and 15% of sporadic cases, and heritability estimates range from 8% to 61%, indicating additional causes beyond genetics. Consequently, interest has grown in environmental contributions to ALS risk and progression. The gene-time-environment hypothesis posits that ALS onset occurs through an interaction of genes with environmental exposures during ageing. An alternative hypothesis, the multistep model of ALS, suggests that several hits, at least some of which could be environmental, are required to trigger disease onset, even in the presence of highly penetrant ALS-associated mutations. Studies have sought to characterize the ALS exposome - the lifetime accumulation of environmental exposures that increase disease risk and affect progression. Identifying the full scope of environmental toxicants that enhance ALS risk raises the prospect of preventing disease by eliminating or mitigating exposures. In this Review, we summarize the evidence for an ALS exposome, discussing the strengths and limitations of epidemiological studies that have identified contributions from various sources. We also consider potential mechanisms of exposure-mediated toxicity and suggest future directions for ALS exposome research.
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Affiliation(s)
- Stephen A Goutman
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, MI, USA
| | - Masha G Savelieff
- Department of Biomedical Sciences, University of North Dakota, Grand Forks, ND, USA
| | - Dae-Gyu Jang
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, MI, USA
| | - Junguk Hur
- Department of Biomedical Sciences, University of North Dakota, Grand Forks, ND, USA
| | - Eva L Feldman
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA.
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, MI, USA.
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