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Winblad S, Eliasdottir O, Nordström S, Lindberg C. Neurocognitive disorder in Myotonic dystrophy type 1. Heliyon 2024; 10:e30875. [PMID: 38778932 PMCID: PMC11109806 DOI: 10.1016/j.heliyon.2024.e30875] [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: 08/10/2023] [Revised: 03/08/2024] [Accepted: 05/07/2024] [Indexed: 05/25/2024] Open
Abstract
Cognitive deficits and abnormal cognitive aging have been associated with Myotonic dystrophy type 1 (DM1), but the knowledge of the extent and progression of decline is limited. The aim of this study was to examine the prevalence of signs of neurocognitive disorder (mild cognitive impairment and dementia) in adult patients with DM1. A total of 128 patients with childhood, juvenile, adult, and late onset DM1 underwent a screening using the Montreal Cognitive Assessment (MoCA). Demographic and clinical information was collected. The results revealed that signs of neurocognitive disorder were relatively rare among the participants. However, 23.8 % of patients with late onset DM1 (aged over 60 years) scored below MoCA cut-off (=23), and this group also scored significantly worse compared to patients with adult onset. Age at examination were negatively correlated with MoCA scores, although it only explained a small portion of the variation in test results. Other demographic and clinical factors showed no association with MoCA scores. In conclusion, our findings indicate a low prevalence of signs of neurocognitive disorder in adult patients with DM1, suggesting that cognitive deficits rarely progress to severe disorders over time. However, the performance of patients with late onset DM1 suggests that this phenotype warrants further exploration in future studies, including longitudinal and larger sample analyses.
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Affiliation(s)
- Stefan Winblad
- Icon Lab, Department of Psychology, University of Gothenburg, Gothenburg, Sweden
| | - Olöf Eliasdottir
- Department of Neurology, Neuromuscular Center, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Sara Nordström
- Department of Neurology, Neuromuscular Center, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Christopher Lindberg
- Department of Neurology, Neuromuscular Center, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Neuroscience and Rehabilitation, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
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2
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Wu Y, Wei Q, Lin J, Shang H, Ou R. Cognitive impairment, neuroimaging abnormalities, and their correlations in myotonic dystrophy: a comprehensive review. Front Cell Neurosci 2024; 18:1369332. [PMID: 38638300 PMCID: PMC11024338 DOI: 10.3389/fncel.2024.1369332] [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: 01/26/2024] [Accepted: 03/22/2024] [Indexed: 04/20/2024] Open
Abstract
Myotonic dystrophy (DM) encompasses a spectrum of neuromuscular diseases characterized by myotonia, muscle weakness, and wasting. Recent research has led to the recognition of DM as a neurological disorder. Cognitive impairment is a central nervous system condition that has been observed in various forms of DM. Neuroimaging studies have increasingly linked DM to alterations in white matter (WM) integrity and highlighted the relationship between cognitive impairment and abnormalities in WM structure. This review aims to summarize investigations into cognitive impairment and brain abnormalities in individuals with DM and to elucidate the correlation between these factors and the potential underlying mechanisms contributing to these abnormalities.
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Affiliation(s)
| | | | | | | | - Ruwei Ou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
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3
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Girolamo T, Butler L, Canale R, Aslin RN, Eigsti IM. fNIRS Studies of Individuals with Speech and Language Impairment Underreport Sociodemographics: A Systematic Review. Neuropsychol Rev 2023:10.1007/s11065-023-09618-y. [PMID: 37747652 PMCID: PMC10961255 DOI: 10.1007/s11065-023-09618-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 09/08/2023] [Indexed: 09/26/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) is a promising tool for scientific discovery and clinical application. However, its utility depends upon replicable reporting. We evaluate reporting of sociodemographics in fNIRS studies of speech and language impairment and asked the following: (1) Do refereed fNIRS publications report participant sociodemographics? (2) For what reasons are participants excluded from analysis? This systematic review was preregistered with PROSPERO (CRD42022342959) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. Searches in August 2022 included the terms: (a) fNIRS or functional near-infrared spectroscopy or NIRS or near-infrared spectroscopy, (b) speech or language, and (c) disorder or impairment or delay. Searches yielded 38 qualifying studies from 1997 to present. Eight studies (5%) reported at least partial information on race or ethnicity. Few studies reported SES (26%) or language background (47%). Most studies reported geographic location (100%) and gender/sex (89%). Underreporting of sociodemographics in fNIRS studies of speech and language impairment hinders the generalizability of findings. Replicable reporting is imperative for advancing the utility of fNIRS.
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Affiliation(s)
- Teresa Girolamo
- School of Speech, Language, and Hearing Sciences, San Diego State University, San Diego, CA, USA.
- Institute for the Brain and Cognitive Sciences, Storrs, CT, USA.
| | - Lindsay Butler
- Institute for the Brain and Cognitive Sciences, Storrs, CT, USA
- Department of Speech, Language, and Hearing Sciences, University of Connecticut, Storrs, CT, USA
| | - Rebecca Canale
- Institute for the Brain and Cognitive Sciences, Storrs, CT, USA
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
| | - Richard N Aslin
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
- Child Study Center and Department of Psychology, Yale University, New Haven, CT, USA
| | - Inge-Marie Eigsti
- Institute for the Brain and Cognitive Sciences, Storrs, CT, USA
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
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4
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Zhang J, Zhang J, Ren H, Liu Q, Du Z, Wu L, Sai L, Yuan Z, Mo S, Lin X. A Look Into the Power of fNIRS Signals by Using the Welch Power Spectral Estimate for Deception Detection. Front Hum Neurosci 2021; 14:606238. [PMID: 33536888 PMCID: PMC7848231 DOI: 10.3389/fnhum.2020.606238] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 11/30/2020] [Indexed: 11/13/2022] Open
Abstract
Neuroimaging technologies have improved our understanding of deception and also exhibit their potential in revealing the origins of its neural mechanism. In this study, a quantitative power analysis method that uses the Welch power spectrum estimation of functional near-infrared spectroscopy (fNIRS) signals was proposed to examine the brain activation difference between the spontaneous deceptive behavior and controlled behavior. The power value produced by the model was applied to quantify the activity energy of brain regions, which can serve as a neuromarker for deception detection. Interestingly, the power analysis results generated from the Welch spectrum estimation method demonstrated that the spontaneous deceptive behavior elicited significantly higher power than that from the controlled behavior in the prefrontal cortex. Meanwhile, the power findings also showed significant difference between the spontaneous deceptive behavior and controlled behavior, indicating that the reward system was only involved in the deception. The proposed power analysis method for processing fNIRS data provides us an additional insight to understand the cognitive mechanism of deception.
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Affiliation(s)
- Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Jingyue Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Houhua Ren
- China Mobile (Chengdu) Industrial Research Institute, Chengdu, China
| | - Qihong Liu
- College of Biomedical Engineering, Sichuan University, Chengdu, China
| | - Zhengcong Du
- School of Information Science and Technology, Xichang University, Xichang, China
| | - Lan Wu
- Sichuan Cancer Hospital and Institute, Chengdu, China
| | - Liyang Sai
- Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, China.,Department of Psychology, Zhejiang Normal University, Jinhua, China
| | - Zhen Yuan
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Taipa, China
| | - Site Mo
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Xiaohong Lin
- Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, China
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5
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Simoncini C, Spadoni G, Lai E, Santoni L, Angelini C, Ricci G, Siciliano G. Central Nervous System Involvement as Outcome Measure for Clinical Trials Efficacy in Myotonic Dystrophy Type 1. Front Neurol 2020; 11:624. [PMID: 33117249 PMCID: PMC7575726 DOI: 10.3389/fneur.2020.00624] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 05/28/2020] [Indexed: 01/18/2023] Open
Abstract
Increasing evidences indicate that in Myotonic Dystrophy type 1 (DM1 or Steinert disease), an autosomal dominant multisystem disorder caused by a (CTG)n expansion in DMPK gene on chromosome 19q13. 3, is the most common form of inherited muscular dystrophy in adult patients with a global prevalence of 1/8000, and involvement of the central nervous system can be included within the core clinical manifestations of the disease. Variable in its severity and progression rate over time, likely due to the underlying causative molecular mechanisms; this component of the clinical picture presents with high heterogeneity involving cognitive and behavioral alterations, but also sensory-motor neural integration, and in any case, significantly contributing to the disease burden projected to either specific functional neuropsychological domains or quality of life as a whole. Principle manifestations include alterations of the frontal lobe function, which is more prominent in patients with an early onset, such as in congenital and childhood onset forms, here associated with severe intellectual disabilities, speech and language delay and reduced IQ-values, while in adult onset DM1 cognitive and neuropsychological findings are usually not so severe. Different methods to assess central nervous system involvement in DM1 have then recently been developed, these ranging from more classical psychometric and cognitive functional instruments to sophisticated psycophysic, neurophysiologic and especially computerized neuroimaging techniques, in order to better characterize this disease component, at the same time underlining the opportunity to consider it a suitable marker on which measuring putative effectiveness of therapeutic interventions. This is the reason why, as outlined in the conclusive section of this review, the Authors are lead to wonder, perhaps in a provocative and even paradoxical way to arise the question, whether or not the myologist, by now the popular figure in charge to care of a patient with the DM1, needs to remain himself a neurologist to better appreciate, evaluate and speculate on this important aspect of Steinert disease.
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Affiliation(s)
- Costanza Simoncini
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Giulia Spadoni
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Elisa Lai
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Lorenza Santoni
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | | | - Giulia Ricci
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Gabriele Siciliano
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
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Butler LK, Kiran S, Tager-Flusberg H. Functional Near-Infrared Spectroscopy in the Study of Speech and Language Impairment Across the Life Span: A Systematic Review. AMERICAN JOURNAL OF SPEECH-LANGUAGE PATHOLOGY 2020; 29:1674-1701. [PMID: 32640168 PMCID: PMC7893520 DOI: 10.1044/2020_ajslp-19-00050] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Purpose Functional brain imaging is playing an increasingly important role in the diagnosis and treatment of communication disorders, yet many populations and settings are incompatible with functional magnetic resonance imaging and other commonly used techniques. We conducted a systematic review of neuroimaging studies using functional near-infrared spectroscopy (fNIRS) with individuals with speech or language impairment across the life span. We aimed to answer the following question: To what extent has fNIRS been used to investigate the neural correlates of speech-language impairment? Method This systematic review was preregistered with PROSPERO, the international prospective register of systematic reviews (CRD42019136464). We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol for preferred reporting items for systematic reviews. The database searches were conducted between February and March of 2019 with the following search terms: (a) fNIRS or functional near-infrared spectroscopy or NIRS or near-infrared spectroscopy, (b) speech or language, and (c) disorder or impairment or delay. Results We found 34 fNIRS studies that involved individuals with speech or language impairment across nine categories: (a) autism spectrum disorders; (b) developmental speech and language disorders; (c) cochlear implantation and deafness; (d) dementia, dementia of the Alzheimer's type, and mild cognitive impairment; (e) locked-in syndrome; (f) neurologic speech disorders/dysarthria; (g) stroke/aphasia; (h) stuttering; and (i) traumatic brain injury. Conclusions Though it is not without inherent challenges, fNIRS may have advantages over other neuroimaging techniques in the areas of speech and language impairment. fNIRS has clinical applications that may lead to improved early and differential diagnosis, increase our understanding of response to treatment, improve neuroprosthetic functioning, and advance neurofeedback.
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Affiliation(s)
- Lindsay K. Butler
- Sargent College of Health and Rehabilitation Sciences, Boston University, MA
| | - Swathi Kiran
- Sargent College of Health and Rehabilitation Sciences, Boston University, MA
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Lagrue E, Dogan C, De Antonio M, Audic F, Bach N, Barnerias C, Bellance R, Cances C, Chabrol B, Cuisset JM, Desguerre I, Durigneux J, Espil C, Fradin M, Héron D, Isapof A, Jacquin-Piques A, Journel H, Laroche-Raynaud C, Laugel V, Magot A, Manel V, Mayer M, Péréon Y, Perrier-Boeswillald J, Peudenier S, Quijano-Roy S, Ragot-Mandry S, Richelme C, Rivier F, Sabouraud P, Sarret C, Testard H, Vanhulle C, Walther-Louvier U, Gherardi R, Hamroun D, Bassez G. A large multicenter study of pediatric myotonic dystrophy type 1 for evidence-based management. Neurology 2019; 92:e852-e865. [DOI: 10.1212/wnl.0000000000006948] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Accepted: 10/18/2018] [Indexed: 12/18/2022] Open
Abstract
ObjectiveTo genotypically and phenotypically characterize a large pediatric myotonic dystrophy type 1 (DM1) cohort to provide a solid frame of data for future evidence-based health management.MethodsAmong the 2,697 patients with genetically confirmed DM1 included in the French DM-Scope registry, children were enrolled between January 2010 and February 2016 from 24 centers. Comprehensive cross-sectional analysis of most relevant qualitative and quantitative variables was performed.ResultsWe studied 314 children (52% females, with 55% congenital, 31% infantile, 14% juvenile form). The age at inclusion was inversely correlated with the CTG repeat length. The paternal transmission rate was higher than expected, especially in the congenital form (13%). A continuum of highly prevalent neurodevelopmental alterations was observed, including cognitive slowing (83%), attention deficit (64%), written language (64%), and spoken language (63%) disorders. Five percent exhibited autism spectrum disorders. Overall, musculoskeletal impairment was mild. Despite low prevalence, cardiorespiratory impairment could be life-threatening, and frequently occurred early in the first decade (25.9%). Gastrointestinal symptoms (27%) and cataracts (7%) were more frequent than expected, while endocrine or metabolic disorders were scarce.ConclusionsThe pedDM-Scope study details the main genotype and phenotype characteristics of the 3 DM1 pediatric subgroups. It highlights striking profiles that could be useful in health care management (including transition into adulthood) and health policy planning.
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Ren H, Wang MY, He Y, Du Z, Zhang J, Zhang J, Li D, Yuan Z. A novel phase analysis method for examining fNIRS neuroimaging data associated with Chinese/English sight translation. Behav Brain Res 2018; 361:151-158. [PMID: 30576722 DOI: 10.1016/j.bbr.2018.12.032] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 11/15/2018] [Accepted: 12/17/2018] [Indexed: 11/25/2022]
Abstract
In this study, a phase method for analyzing functional near-infrared spectroscopy (fNIRS) signals was developed, which can extract the phase information of fNIRS data by using Hilbert transform. More importantly, the phase analysis method can be further performed to generate the brain phase activation and to construct the brain networks. Meanwhile, the study of translation between Chinese and English has been exciting and interesting from both the language and neuroscience standpoints due to their drastically different linguistic features. In particular, inspecting the brain phase activation and functional connectivity based on the phase data and phase analysis method will enable us to better understand the neural mechanism associated with Chinese/English translation. Our phase analysis results showed that the left prefrontal cortex, including the dorsolateral prefrontal cortex (DLPFC) and frontopolar area, was involved in the translation process of the language pair. In addition, we also discovered that the most significant brain phase activation difference between translating into non-native (English) vs. native (Chinese) language was identified in the Broca's area. As a result, the proposed phase analysis approach can provide us an additional tool to reveal the complex cognitive mechanism associated with Chinese/English sight translation.
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Affiliation(s)
- Houhua Ren
- College of Electrical Engineering and Information Technology, Sichuan University, Chengdu 610065, China
| | - Meng-Yun Wang
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, China
| | - Yan He
- Centre for Studies of Translation-Interpreting and Cognition, University of Macau, Taipa, Macau SAR, China
| | - Zhengcong Du
- School of Information Science and Technology, XiChang University 615000, China
| | - Jiang Zhang
- College of Electrical Engineering and Information Technology, Sichuan University, Chengdu 610065, China; The Key Laboratory for NeuroInformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China.
| | - Jing Zhang
- College of Electrical Engineering and Information Technology, Sichuan University, Chengdu 610065, China
| | - Defeng Li
- Centre for Studies of Translation-Interpreting and Cognition, University of Macau, Taipa, Macau SAR, China.
| | - Zhen Yuan
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, China
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Downregulation of the Glial GLT1 Glutamate Transporter and Purkinje Cell Dysfunction in a Mouse Model of Myotonic Dystrophy. Cell Rep 2018; 19:2718-2729. [PMID: 28658620 PMCID: PMC8496958 DOI: 10.1016/j.celrep.2017.06.006] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2017] [Revised: 04/27/2017] [Accepted: 05/26/2017] [Indexed: 02/07/2023] Open
Abstract
Brain function is compromised in myotonic dystrophy type 1 (DM1), but the underlying mechanisms are not fully understood. To gain insight into the cellular and molecular pathways primarily affected, we studied a mouse model of DM1 and brains of adult patients. We found pronounced RNA toxicity in the Bergmann glia of the cerebellum, in association with abnormal Purkinje cell firing and fine motor incoordination in DM1 mice. A global proteomics approach revealed downregulation of the GLT1 glutamate transporter in DM1 mice and human patients, which we found to be the result of MBNL1 inactivation. GLT1 downregulation in DM1 astrocytes increases glutamate neurotoxicity and is detrimental to neurons. Finally, we demonstrated that the upregulation of GLT1 corrected Purkinje cell firing and motor incoordination in DM1 mice. Our findings show that glial defects are critical in DM1 brain pathophysiology and open promising therapeutic perspectives through the modulation of glutamate levels. Neural dysfunction in myotonic dystrophy is not fully understood. Using a transgenic mouse model of the disease, Sicot et al. find electrophysiological and motor evidence for cerebellar dysfunction in association with pronounced signs of RNA toxicity in Bergmann glia. Upregulation of a defective glial-specific glutamate transporter corrects cerebellum phenotypes.
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10
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The cognitive profile of myotonic dystrophy type 1: A systematic review and meta-analysis. Cortex 2017; 95:143-155. [DOI: 10.1016/j.cortex.2017.08.008] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Revised: 07/11/2017] [Accepted: 08/05/2017] [Indexed: 12/13/2022]
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Gourdon G, Meola G. Myotonic Dystrophies: State of the Art of New Therapeutic Developments for the CNS. Front Cell Neurosci 2017; 11:101. [PMID: 28473756 PMCID: PMC5397409 DOI: 10.3389/fncel.2017.00101] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2017] [Accepted: 03/27/2017] [Indexed: 12/12/2022] Open
Abstract
Myotonic dystrophies are multisystemic diseases characterized not only by muscle and heart dysfunction but also by CNS alteration. They are now recognized as brain diseases affecting newborns and children for myotonic dystrophy type 1 and adults for both myotonic dystrophy type 1 and type 2. In the past two decades, much progress has been made in understanding the mechanisms underlying the DM symptoms allowing development of new molecular therapeutic tools with the ultimate aim of curing the disease. This review describes the state of the art for the characterization of CNS related symptoms, the development of molecular strategies to target the CNS as well as the available tools for screening and testing new possible treatments.
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Affiliation(s)
- Genevieve Gourdon
- Institut National de la Santé et de la Recherche Médicale UMR1163Paris, France.,Laboratory CTGDM, Institut Imagine, Université Paris Descartes-Sorbonne Paris CitéParis, France
| | - Giovanni Meola
- Department of Biomedical Sciences for Health, Policlinico San Donato (IRCCS), University of MilanMilan, Italy
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