Pub Date : 2025-11-01DOI: 10.1016/j.neurol.2025.09.001
C. Guémy , C. Lefeuvre , E. Berling , A. Rouyer , G. Nicolas , P. Laforêt
Late-onset Pompe disease (LOPD) is a genetic myopathy causing severe limb girdle and diaphragmatic weakness. Pre-symptomatic diagnosis of LOPD is increasing. Enzyme replacement therapy (ERT) has shown dramatic efficacy in infantile-onset forms of the disease, supporting early diagnosis and treatment initiation, whereas the benefit of ERT on muscle weakness and respiratory insufficiency is moderate and not sustained over time in LOPD, raising questions about presymptomatic screening. Here, we present three presymptomatic cases of LOPD, showing that clinical symptoms can occur long after the diagnosis, resulting in a close monitoring without the need for treatment over several years. Several tests, such as walking tests, pulmonary function tests or whole-body muscle magnetic resonance imaging are sensitive for detecting early disease progression. Current guidelines provide no clear recommendations regarding the optimal timing of treatment initiation in presymptomatic patients. Nevertheless, in the context of a disease with a highly variable course, regular clinical, physiological and radiological assessments of each patient may allow for early detection of disease progression and support the decision to initiate treatment.
{"title":"Presymptomatic late-onset Pompe disease: Optimizing the timing of treatment","authors":"C. Guémy , C. Lefeuvre , E. Berling , A. Rouyer , G. Nicolas , P. Laforêt","doi":"10.1016/j.neurol.2025.09.001","DOIUrl":"10.1016/j.neurol.2025.09.001","url":null,"abstract":"<div><div>Late-onset Pompe disease (LOPD) is a genetic myopathy causing severe limb girdle and diaphragmatic weakness. Pre-symptomatic diagnosis of LOPD is increasing. Enzyme replacement therapy (ERT) has shown dramatic efficacy in infantile-onset forms of the disease, supporting early diagnosis and treatment initiation, whereas the benefit of ERT on muscle weakness and respiratory insufficiency is moderate and not sustained over time in LOPD, raising questions about presymptomatic screening. Here, we present three presymptomatic cases of LOPD, showing that clinical symptoms can occur long after the diagnosis, resulting in a close monitoring without the need for treatment over several years. Several tests, such as walking tests, pulmonary function tests or whole-body muscle magnetic resonance imaging are sensitive for detecting early disease progression. Current guidelines provide no clear recommendations regarding the optimal timing of treatment initiation in presymptomatic patients. Nevertheless, in the context of a disease with a highly variable course, regular clinical, physiological and radiological assessments of each patient may allow for early detection of disease progression and support the decision to initiate treatment.</div></div>","PeriodicalId":21321,"journal":{"name":"Revue neurologique","volume":"181 9","pages":"Pages 922-928"},"PeriodicalIF":2.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145486175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.neurol.2025.06.017
M. Cohen
Most of widely available consumer devices like smartphones and tablets are equipped with various sensors that allow for detection of subtle and undetectable neurological impairment of various neurological functions like motricity, coordination, cognition, visual function or eye movements. This opens the perspective of earlier diagnosis of neurological diseases, even at the preclinical stage, which could allow for earlier therapeutic intervention and improved long term outcomes. In this article, we review how technology can enhance the clinician's examination skills and the current level of evidence in the field of preclinical diseases detection, in diseases like Parkinson's disease, Alzheimer's disease or multiple sclerosis. Many studies reported subtle impairment regarding fine motricity, eye movements, cognition, voice features and speech. We will also discuss current limitations regarding scientific evidence and practical implementation in the daily practice, as well as future perspectives.
{"title":"Digital health in presymptomatic diseases","authors":"M. Cohen","doi":"10.1016/j.neurol.2025.06.017","DOIUrl":"10.1016/j.neurol.2025.06.017","url":null,"abstract":"<div><div>Most of widely available consumer devices like smartphones and tablets are equipped with various sensors that allow for detection of subtle and undetectable neurological impairment of various neurological functions like motricity, coordination, cognition, visual function or eye movements. This opens the perspective of earlier diagnosis of neurological diseases, even at the preclinical stage, which could allow for earlier therapeutic intervention and improved long term outcomes. In this article, we review how technology can enhance the clinician's examination skills and the current level of evidence in the field of preclinical diseases detection, in diseases like Parkinson's disease, Alzheimer's disease or multiple sclerosis. Many studies reported subtle impairment regarding fine motricity, eye movements, cognition, voice features and speech. We will also discuss current limitations regarding scientific evidence and practical implementation in the daily practice, as well as future perspectives.</div></div>","PeriodicalId":21321,"journal":{"name":"Revue neurologique","volume":"181 9","pages":"Pages 937-943"},"PeriodicalIF":2.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145486257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.neurol.2025.07.011
T. Soulier , N. Burgos , R. Hassanaly , M. Pitombeira , M. Solal , H. Roy , M. Hamzaoui , A. Yazdan-Panah , D. de Paula Faria , C. Louapre , B. Bodini , M. Bottlaender , N. Ayache , O. Colliot , B. Stankoff
Presymptomatic neurological diseases are marked by early pathological changes that occur before overt clinical symptoms. These stages, which include prodromes such as REM sleep behavior disorder in Parkinson's or mild cognitive impairment in Alzheimer's, offer critical opportunities for early intervention. However, their detection remains challenging due to the subtlety of changes and the overlap with normal interindividual variability. Artificial intelligence (AI), especially machine learning (ML) and deep learning (DL), offers new tools to uncover hidden signatures in complex biomedical data. First, we explore how supervised ML models can detect known prodromal patterns across diverse modalities, including EEG, cognitive scores, and structural imaging. Depending on the input, various model types — such as tree-based algorithms for structured data and convolutional or transformer networks for images and signals — can extract predictive features of early neurodegeneration. These approaches have demonstrated success in identifying at-risk individuals before clinical thresholds are reached. Yet, detecting only known patterns limits the scope of early intervention. Many individuals who will go on to develop neurological disease may not yet exhibit any recognized prodromal syndrome. Bridging this gap requires moving beyond predefined labels toward models capable of identifying subtle, unknown anomalies in individuals still considered healthy. Second, we address the detection of latent anomalies among individuals not yet considered at risk without identifiable known prodromal patterns. By mining clinical records, free-text medical notes, and population-level health databases (e.g., UK Biobank, EDS-AP–HP), and by analyzing sensor data from smartphones or wearables, AI can flag deviations from healthy patterns long before symptom onset or formal diagnosis. This approach holds promise for scalable, low-burden, ecological screening. Finally, we introduce the concept of pseudo-healthy twins — synthetic, personalized baselines generated from structural data such as MRI, to improve anomaly detection. These models predict a patient's expected healthy signal in another modality, such as PET, enabling the subtraction of normal anatomical and physiological variability to isolate disease-specific effects. Generative models like GANs and VAEs have shown promise in producing these cross-modal references, enhancing early anomaly detection in diseases like Alzheimer's and multiple sclerosis. Together, these approaches show how AI can bridge the gap between normal variation and early pathology, enabling more sensitive, personalized, and population-scalable detection of presymptomatic neurological disease.
{"title":"Artificial intelligence in presymptomatic neurological diseases: Bridging normal variation and prodromal signatures","authors":"T. Soulier , N. Burgos , R. Hassanaly , M. Pitombeira , M. Solal , H. Roy , M. Hamzaoui , A. Yazdan-Panah , D. de Paula Faria , C. Louapre , B. Bodini , M. Bottlaender , N. Ayache , O. Colliot , B. Stankoff","doi":"10.1016/j.neurol.2025.07.011","DOIUrl":"10.1016/j.neurol.2025.07.011","url":null,"abstract":"<div><div>Presymptomatic neurological diseases are marked by early pathological changes that occur before overt clinical symptoms. These stages, which include prodromes such as REM sleep behavior disorder in Parkinson's or mild cognitive impairment in Alzheimer's, offer critical opportunities for early intervention. However, their detection remains challenging due to the subtlety of changes and the overlap with normal interindividual variability. Artificial intelligence (AI), especially machine learning (ML) and deep learning (DL), offers new tools to uncover hidden signatures in complex biomedical data. First, we explore how supervised ML models can detect known prodromal patterns across diverse modalities, including EEG, cognitive scores, and structural imaging. Depending on the input, various model types — such as tree-based algorithms for structured data and convolutional or transformer networks for images and signals — can extract predictive features of early neurodegeneration. These approaches have demonstrated success in identifying at-risk individuals before clinical thresholds are reached. Yet, detecting only known patterns limits the scope of early intervention. Many individuals who will go on to develop neurological disease may not yet exhibit any recognized prodromal syndrome. Bridging this gap requires moving beyond predefined labels toward models capable of identifying subtle, unknown anomalies in individuals still considered healthy. Second, we address the detection of latent anomalies among individuals not yet considered at risk without identifiable known prodromal patterns. By mining clinical records, free-text medical notes, and population-level health databases (e.g., UK Biobank, EDS-AP–HP), and by analyzing sensor data from smartphones or wearables, AI can flag deviations from healthy patterns long before symptom onset or formal diagnosis. This approach holds promise for scalable, low-burden, ecological screening. Finally, we introduce the concept of pseudo-healthy twins — synthetic, personalized baselines generated from structural data such as MRI, to improve anomaly detection. These models predict a patient's expected healthy signal in another modality, such as PET, enabling the subtraction of normal anatomical and physiological variability to isolate disease-specific effects. Generative models like GANs and VAEs have shown promise in producing these cross-modal references, enhancing early anomaly detection in diseases like Alzheimer's and multiple sclerosis. Together, these approaches show how AI can bridge the gap between normal variation and early pathology, enabling more sensitive, personalized, and population-scalable detection of presymptomatic neurological disease.</div></div>","PeriodicalId":21321,"journal":{"name":"Revue neurologique","volume":"181 9","pages":"Pages 944-950"},"PeriodicalIF":2.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145486258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.neurol.2025.06.012
L. Grass , S. Grimaldi , P. Damier
The neurodegenerative process responsible for Parkinson's disease (PD) begins years before the level of dopamine denervation of the basal ganglia leads to the characteristic clinical phenotype of the disease. During the past 20 years, numerous symptoms that may occur during the prodromal stage of the disease have been identified: subtle motor symptoms, psychocognitive disorders, sleep disorders, sensorial dysfunction, and dysautonomia. Among them, rapid eye movement sleep behaviour disorder (RBD) is one of the most specific. The follow-up of cohorts of subjects affected by this disorder has provided valuable information about the prodromal stage, including evidence of various biological or imaging biomarkers associated with the pre-clinical stage of the disease. From all the knowledge acquired about this stage of the disease, criteria for diagnosing prodromal PD have been proposed and have progressively improved in sensitivity and specificity. The strong focus on the RBD-associated prodromal stage has, however, tended to conceal other, less florid forms of prodromal PD, such as those beginning with mild cognitive impairment or mild motor symptoms, which affected subjects are less likely to notice. Here, we review the various symptoms observed in the prodromal stage of PD, progress on identifying relevant imaging and biological biomarkers, and recent insights into the pathogenesis of a disease having such a wide spectrum of presentation and progression. Advances in knowledge about prodromal PD will lead to earlier diagnosis and better identification of prognostic factors, and, subsequently, to the capacity to initiate personalized treatment and potentially slow down the degenerative process.
{"title":"Prodromal Parkinson's disease","authors":"L. Grass , S. Grimaldi , P. Damier","doi":"10.1016/j.neurol.2025.06.012","DOIUrl":"10.1016/j.neurol.2025.06.012","url":null,"abstract":"<div><div>The neurodegenerative process responsible for Parkinson's disease (PD) begins years before the level of dopamine denervation of the basal ganglia leads to the characteristic clinical phenotype of the disease. During the past 20<!--> <!-->years, numerous symptoms that may occur during the prodromal stage of the disease have been identified: subtle motor symptoms, psychocognitive disorders, sleep disorders, sensorial dysfunction, and dysautonomia. Among them, rapid eye movement sleep behaviour disorder (RBD) is one of the most specific. The follow-up of cohorts of subjects affected by this disorder has provided valuable information about the prodromal stage, including evidence of various biological or imaging biomarkers associated with the pre-clinical stage of the disease. From all the knowledge acquired about this stage of the disease, criteria for diagnosing prodromal PD have been proposed and have progressively improved in sensitivity and specificity. The strong focus on the RBD-associated prodromal stage has, however, tended to conceal other, less florid forms of prodromal PD, such as those beginning with mild cognitive impairment or mild motor symptoms, which affected subjects are less likely to notice. Here, we review the various symptoms observed in the prodromal stage of PD, progress on identifying relevant imaging and biological biomarkers, and recent insights into the pathogenesis of a disease having such a wide spectrum of presentation and progression. Advances in knowledge about prodromal PD will lead to earlier diagnosis and better identification of prognostic factors, and, subsequently, to the capacity to initiate personalized treatment and potentially slow down the degenerative process.</div></div>","PeriodicalId":21321,"journal":{"name":"Revue neurologique","volume":"181 9","pages":"Pages 863-880"},"PeriodicalIF":2.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145486264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.neurol.2025.08.004
M. Rival , E. Thouvenot
Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS) often exhibit a prolonged presymptomatic phase during which neuropathological changes silently progress. Recent advances in biomarker research have revealed molecular and imaging signatures that precede clinical onset by years, offering a critical window for early intervention. This review synthesizes current knowledge on the most promising presymptomatic biomarkers across these conditions, highlighting their biological origins, diagnostic performance, and clinical utility. Particular emphasis is placed on the development and validation of biomarker panels, which combine multiple markers to enhance diagnostic sensitivity and specificity, enabling more accurate detection of disease in its earliest stages. Minimally invasive approaches, such as blood-based assays, are also discussed for their potential to facilitate widespread screening and longitudinal monitoring. As these biomarkers begin to integrate into clinical workflows, particularly in AD and MS, international collaboration will be essential to standardize methodologies and ensure equitable implementation. Ultimately, presymptomatic biomarkers hold transformative potential for shifting neurology toward a proactive and precision-based paradigm.
{"title":"Tracing Neurological Diseases in the presymptomatic phase: moving forward a detection panel","authors":"M. Rival , E. Thouvenot","doi":"10.1016/j.neurol.2025.08.004","DOIUrl":"10.1016/j.neurol.2025.08.004","url":null,"abstract":"<div><div>Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS) often exhibit a prolonged presymptomatic phase during which neuropathological changes silently progress. Recent advances in biomarker research have revealed molecular and imaging signatures that precede clinical onset by years, offering a critical window for early intervention. This review synthesizes current knowledge on the most promising presymptomatic biomarkers across these conditions, highlighting their biological origins, diagnostic performance, and clinical utility. Particular emphasis is placed on the development and validation of biomarker panels, which combine multiple markers to enhance diagnostic sensitivity and specificity, enabling more accurate detection of disease in its earliest stages. Minimally invasive approaches, such as blood-based assays, are also discussed for their potential to facilitate widespread screening and longitudinal monitoring. As these biomarkers begin to integrate into clinical workflows, particularly in AD and MS, international collaboration will be essential to standardize methodologies and ensure equitable implementation. Ultimately, presymptomatic biomarkers hold transformative potential for shifting neurology toward a proactive and precision-based paradigm.</div></div>","PeriodicalId":21321,"journal":{"name":"Revue neurologique","volume":"181 9","pages":"Pages 821-828"},"PeriodicalIF":2.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145486261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-31DOI: 10.1016/j.neurol.2025.10.004
E Oprea
Sexual difficulties are common but under-recognized in Parkinson's disease (PD), significantly affecting quality of life. They include both sexual dysfunction (SD) - a non-motor symptom - and hypersexuality (HS) - an impulse control disorder (ICD). SD often presents as reduced libido, arousal issues, or orgasmic problems, while HS involves compulsive sexual thoughts or behaviors, often linked to dopamine agonists. These opposing symptoms may coexist, adding to diagnostic complexity. Sexual health in PD is influenced by neurological, vascular, endocrine, psychological, and medication-related factors. Despite its impact, sexual difficulties are rarely discussed in clinical settings due to limited time and patient reluctance. A proactive, nonjudgmental approach is essential. This review aims to equip neurologists with practical, time-efficient strategies to identify and manage sexual difficulties in both men and women with PD.
{"title":"Addressing sexual difficulties in Parkinson's disease.","authors":"E Oprea","doi":"10.1016/j.neurol.2025.10.004","DOIUrl":"https://doi.org/10.1016/j.neurol.2025.10.004","url":null,"abstract":"<p><p>Sexual difficulties are common but under-recognized in Parkinson's disease (PD), significantly affecting quality of life. They include both sexual dysfunction (SD) - a non-motor symptom - and hypersexuality (HS) - an impulse control disorder (ICD). SD often presents as reduced libido, arousal issues, or orgasmic problems, while HS involves compulsive sexual thoughts or behaviors, often linked to dopamine agonists. These opposing symptoms may coexist, adding to diagnostic complexity. Sexual health in PD is influenced by neurological, vascular, endocrine, psychological, and medication-related factors. Despite its impact, sexual difficulties are rarely discussed in clinical settings due to limited time and patient reluctance. A proactive, nonjudgmental approach is essential. This review aims to equip neurologists with practical, time-efficient strategies to identify and manage sexual difficulties in both men and women with PD.</p>","PeriodicalId":21321,"journal":{"name":"Revue neurologique","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145426794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-03DOI: 10.1016/j.neurol.2025.06.014
M. Renouil , I.I. Grigorashvili-Coin , M.-L. Jacquemont , A. Gelot , V. Trommsdorff , A. Pervillé , F. Darcel , M. Bintner , A. Choumert
Introduction
RAVINE leukoencephalopathy (RLE) is a hereditary autosomal recessive disease characterized by typical clinical and radiological signs that has so far been observed only in patients of Reunionese origin. The term RAVINE is a French acronym for the main clinical features of the disease: Réunion, Anorexie, Vomissements Incoercibles, signes NEurologiques (Reunion, Anorexia, Intractable Vomiting, NEurological signs). Patients with RLE carry the IVS1-1778A>G mutation of the SLC7A2 gene in the homozygous state. Here we present the first complete clinical description and natural history of RLE.
Material and methods
The medical records of all patients born to Reunionese parents and presenting with suspected RLE were reviewed. The diagnosis of RLE was confirmed by detection of the homozygous mutation IVS1-1178A>G of the SLC7A2 gene. The clinical and paraclinical data of patients with genetically confirmed RLE were retrospectively analyzed to determine the clinical presentation and natural history of the disease.
Results
Our retrospective analysis of the clinical and paraclinical data of 40 patients with genetically confirmed RLE distinguished 3 types of the disease based on the evolution of symptoms. Symptoms were classified into 4 stages of development: stage A, or digestive-like stage, characterized by digestive symptoms and to a lesser extent by neurological symptoms; stage B, or clinically latent stage; stage C, or exacerbation stage, marked by attacks of neurological symptoms; and stage D, or decline stage, characterized by loss of walking ability and progression towards death. Patients with type I RLE (37.5%), or monophasic RLE, experience only the severe stage A. Death occurs before the age of 28 months in a very narrow time window (23.0 ± 2.2 months). Patients with type II RLE (16.7%), or biphasic RLE, move directly from stage A to stage D. Patients with type III RLE (45.8%), or multiphasic RLE, experience all 4 stages with varying degrees of symptom severity. This is the most frequent type of RLE. The joint occurrence of central apnea and vocal cord paralysis during stage A is indicative of unfavorable prognosis. Corticosteroid therapy seems to be effective during stage A and in some cases during stage C.
Discussion
This retrospective study provides the first complete clinical description and natural history of RLE. Three types of the disease were distinguished based on the evolution of symptoms. The diagnosis of RLE can be established outside of Reunion Island as many Reunionese couples have emigrated to other parts of the world.
{"title":"Clinical presentation and natural history of RAVINE leukoencephalopathy in Reunion Island","authors":"M. Renouil , I.I. Grigorashvili-Coin , M.-L. Jacquemont , A. Gelot , V. Trommsdorff , A. Pervillé , F. Darcel , M. Bintner , A. Choumert","doi":"10.1016/j.neurol.2025.06.014","DOIUrl":"10.1016/j.neurol.2025.06.014","url":null,"abstract":"<div><h3>Introduction</h3><div>RAVINE leukoencephalopathy (RLE) is a hereditary autosomal recessive disease characterized by typical clinical and radiological signs that has so far been observed only in patients of Reunionese origin. The term RAVINE is a French acronym for the main clinical features of the disease: <em>Réunion, Anorexie, Vomissements Incoercibles, signes NEurologiques</em> (Reunion, Anorexia, Intractable Vomiting, NEurological signs). Patients with RLE carry the IVS1-1778A>G mutation of the <em>SLC7A2</em> gene in the homozygous state. Here we present the first complete clinical description and natural history of RLE.</div></div><div><h3>Material and methods</h3><div>The medical records of all patients born to Reunionese parents and presenting with suspected RLE were reviewed. The diagnosis of RLE was confirmed by detection of the homozygous mutation IVS1-1178A>G of the <em>SLC7A2</em> gene. The clinical and paraclinical data of patients with genetically confirmed RLE were retrospectively analyzed to determine the clinical presentation and natural history of the disease.</div></div><div><h3>Results</h3><div>Our retrospective analysis of the clinical and paraclinical data of 40 patients with genetically confirmed RLE distinguished 3 types of the disease based on the evolution of symptoms. Symptoms were classified into 4 stages of development: stage A, or digestive-like stage, characterized by digestive symptoms and to a lesser extent by neurological symptoms; stage B, or clinically latent stage; stage C, or exacerbation stage, marked by attacks of neurological symptoms; and stage D, or decline stage, characterized by loss of walking ability and progression towards death. Patients with type I RLE (37.5%), or monophasic RLE, experience only the severe stage A. Death occurs before the age of 28<!--> <!-->months in a very narrow time window (23.0<!--> <!-->±<!--> <!-->2.2<!--> <!-->months). Patients with type II RLE (16.7%), or biphasic RLE, move directly from stage A to stage D. Patients with type III RLE (45.8%), or multiphasic RLE, experience all 4 stages with varying degrees of symptom severity. This is the most frequent type of RLE. The joint occurrence of central apnea and vocal cord paralysis during stage A is indicative of unfavorable prognosis. Corticosteroid therapy seems to be effective during stage A and in some cases during stage C.</div></div><div><h3>Discussion</h3><div>This retrospective study provides the first complete clinical description and natural history of RLE. Three types of the disease were distinguished based on the evolution of symptoms. The diagnosis of RLE can be established outside of Reunion Island as many Reunionese couples have emigrated to other parts of the world.</div></div>","PeriodicalId":21321,"journal":{"name":"Revue neurologique","volume":"181 8","pages":"Pages 775-789"},"PeriodicalIF":2.3,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145134922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-25DOI: 10.1016/j.neurol.2025.06.011
G. Fillebeen , M. Ocampo-Pineda , E. Ruberte , L. Melie-Garcia , J. Kuhle , F.T. Kurz , K.-O. Lovblad , P.H. Lalive , A.M. Lascano
Background
Previous studies exploring the anatomical correlates of pain in multiple sclerosis (MS) have relied on structural magnetic resonance imaging (MRI) and descriptive methodologies.
Objective
To establish radiological correlates of neuropathic pain in MS patients through the objective segmentation and analysis of brain MRI.
Methods
This exploratory pilot study included three distinct groups: MS patients with neuropathic pain (n = 8), MS patients without pain (n = 11), and individuals with small fiber neuropathy (SFN, n = 6). Neuropathic pain was confirmed using laser-evoked potentials (LEPs), ensuring an objective assessment of pain function. All participants underwent brain MRI, with MS patients additionally undergoing spinal MRI. Brain region segmentation was conducted using two advanced automated tools: SAMSEG (Sequence Adaptive Multimodal SEGmentation) and SynthSEG. Pain-related brain regions, including the thalamus, brainstem, basal ganglia, prefrontal cortex, and somatosensory cortex, were analyzed and compared amongst the three groups.
Results
The volume of the right pallidum was significantly reduced in MS patients with pain compared to those without pain, as measured by SynthSeg but not with SAMSEG. Individual analysis of regions of interest showed significant results of diffusion tensor imaging analysis in the external capsule, internal capsule, posterior thalamic radiation, and superior longitudinal fasciculus. Quantitative analysis of spinal cord lesions revealed no significant differences between the groups.
Conclusions
These findings highlight a potential of advanced neuroimaging techniques to uncover brain-based correlates of neuropathic pain in MS, though further studies with larger sample sizes are warranted for validation.
{"title":"Investigating neuroanatomical correlates of neuropathic pain in multiple sclerosis: A pilot comparative study using advanced MRI techniques","authors":"G. Fillebeen , M. Ocampo-Pineda , E. Ruberte , L. Melie-Garcia , J. Kuhle , F.T. Kurz , K.-O. Lovblad , P.H. Lalive , A.M. Lascano","doi":"10.1016/j.neurol.2025.06.011","DOIUrl":"10.1016/j.neurol.2025.06.011","url":null,"abstract":"<div><h3>Background</h3><div>Previous studies exploring the anatomical correlates of pain in multiple sclerosis (MS) have relied on structural magnetic resonance imaging (MRI) and descriptive methodologies.</div></div><div><h3>Objective</h3><div>To establish radiological correlates of neuropathic pain in MS patients through the objective segmentation and analysis of brain MRI.</div></div><div><h3>Methods</h3><div>This exploratory pilot study included three distinct groups: MS patients with neuropathic pain (<em>n</em> <!-->=<!--> <!-->8), MS patients without pain (<em>n</em> <!-->=<!--> <!-->11), and individuals with small fiber neuropathy (SFN, <em>n</em> <!-->=<!--> <!-->6). Neuropathic pain was confirmed using laser-evoked potentials (LEPs), ensuring an objective assessment of pain function. All participants underwent brain MRI, with MS patients additionally undergoing spinal MRI. Brain region segmentation was conducted using two advanced automated tools: SAMSEG (Sequence Adaptive Multimodal SEGmentation) and SynthSEG. Pain-related brain regions, including the thalamus, brainstem, basal ganglia, prefrontal cortex, and somatosensory cortex, were analyzed and compared amongst the three groups.</div></div><div><h3>Results</h3><div>The volume of the right pallidum was significantly reduced in MS patients with pain compared to those without pain, as measured by SynthSeg but not with SAMSEG. Individual analysis of regions of interest showed significant results of diffusion tensor imaging analysis in the external capsule, internal capsule, posterior thalamic radiation, and superior longitudinal fasciculus. Quantitative analysis of spinal cord lesions revealed no significant differences between the groups.</div></div><div><h3>Conclusions</h3><div>These findings highlight a potential of advanced neuroimaging techniques to uncover brain-based correlates of neuropathic pain in MS, though further studies with larger sample sizes are warranted for validation.</div></div>","PeriodicalId":21321,"journal":{"name":"Revue neurologique","volume":"181 8","pages":"Pages 765-774"},"PeriodicalIF":2.3,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144967011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-14DOI: 10.1016/j.neurol.2025.07.012
J.-B. Brunet de Courssou , L. Gorza , M. Babin , G. Nasser , C. Ancelet , C. Labeyrie , C. Denier , C. Cauquil
Background
Hereditary transthyretin amyloidosis (ATTRv) is the most common hereditary amyloidosis, affecting mainly the peripheral nervous system and the heart. Central nervous system (CNS) involvement is regarded as rare, apart in some TTR variants, although leptomeningeal amyloid deposit had been described in the frequent Val30Met variant. Cerebral amyloid angiopathy (CAA) is a neurovascular disease characterized by amyloid deposits in brain vasculature, leading to ischemic and hemorrhagic events. The main cause is sporadic CAA with β-amyloid deposits but hereditary causes are possible.
Methods
We analyzed a cohort of ATTRv symptomatic patients treated at Bicêtre university hospital who underwent brain magnetic resonance imaging (MRI) regardless of indication.
Results
Twenty out of 64 ATTRv patients (31%) fulfilled radiological criteria of possible or probable CAA (suspected CAA) according to the modified Boston criteria with an unusually high 77% (10/13) frequency of leptomeningeal enhancement. Clinically, suspected CAA patients tended to have more focal central neurological symptoms, seizures and memory complaints than ATTRv patients without those MRI features.
Conclusion
ATTRv-related CAA should be considered in case of CAA with suggestive systemic features or familial history, as specific treatments and genetic counseling now exist for ATTRv. Conversely, CNS symptoms and brain MRI abnormalities should be sought in ATTRv patients.
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Pub Date : 2025-08-13DOI: 10.1016/j.neurol.2025.08.001
A. Verger , P. Payoux , S. Heyer , M.O. Habert , A. Flaus , M. Ribeiro , N. De Leiris , J. Pariente , D. Wallon , M. Ceccaldi , S. Bombois , E. Guedj , Groupe de travail « neurologie » de la Société française de médecine nucléaire (GT neurologie SFMN)
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