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Rai G, Sharma S, Bhasin J, Aggarwal K, Ahuja A, Dang S. Nanotechnological advances in the treatment of epilepsy: a comprehensive review. NANOTECHNOLOGY 2024; 35:152002. [PMID: 38194705 DOI: 10.1088/1361-6528/ad1c95] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 01/09/2024] [Indexed: 01/11/2024]
Abstract
Epilepsy is one of the most prevalent chronic neurological disorders characterized by frequent unprovoked epileptic seizures. Epileptic seizures can develop from a broad range of underlying abnormalities such as tumours, strokes, infections, traumatic brain injury, developmental abnormalities, autoimmune diseases, and genetic predispositions. Sometimes epilepsy is not easily diagnosed and treated due to the large diversity of symptoms. Undiagnosed and untreated seizures deteriorate over time, impair cognition, lead to injuries, and can sometimes result in death. This review gives details about epilepsy, its classification on the basis of International League Against Epilepsy, current therapeutics which are presently offered for the treatment of epilepsy. Despite of the fact that more than 30 different anti-epileptic medication and antiseizure drugs are available, large number of epileptic patients fail to attain prolonged seizure independence. Poor onsite bioavailability of drugs due to blood brain barrier poses a major challenge in drug delivery to brain. The present review covers the limitations with the state-of-the-art strategies for managing seizures and emphasizes the role of nanotechnology in overcoming these issues. Various nano-carriers like polymeric nanoparticles, dendrimers, lipidic nanoparticles such as solid lipid nanoparticles, nano-lipid carriers, have been explored for the delivery of anti-epileptic drugs to brain using oral and intranasal routes. Nano-carries protect the encapsulated drugs from degradation and provide a platform to deliver controlled release over prolonged periods, improved permeability and bioavailability at the site of action. The review also emphasises in details about the role of neuropeptides for the treatment of epilepsy.
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Affiliation(s)
- Garima Rai
- Department of Biotechnology, Jaypee Institute of Information Technology, Noida, UP, India
| | - Surbhi Sharma
- Department of Biotechnology, Jaypee Institute of Information Technology, Noida, UP, India
| | - Jasveen Bhasin
- Department of Biotechnology, Jaypee Institute of Information Technology, Noida, UP, India
| | - Kanica Aggarwal
- Department of Biotechnology, Jaypee Institute of Information Technology, Noida, UP, India
| | - Alka Ahuja
- College of Pharmacy, National University of Science and Technology, Muscat, Oman
| | - Shweta Dang
- Department of Biotechnology, Jaypee Institute of Information Technology, Noida, UP, India
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Baka RD, Kuleš J, Beletić A, Farkaš V, Rešetar Maslov D, Ljubić BB, Rubić I, Mrljak V, McLaughlin M, Eckersall D, Polizopoulou Z. Quantitative serum proteome analysis using tandem mass tags in dogs with epilepsy. J Proteomics 2024; 290:105034. [PMID: 37879566 DOI: 10.1016/j.jprot.2023.105034] [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: 08/29/2023] [Revised: 10/09/2023] [Accepted: 10/18/2023] [Indexed: 10/27/2023]
Abstract
This study included four groups of dogs (group A: healthy controls, group B: idiopathic epilepsy receiving antiepileptic medication (AEM), group C: idiopathic epilepsy without AEM, group D: structural epilepsy). Comparative quantitative proteomic analysis of serum samples among the groups was the main target of the study. Samples were analyzed by a quantitative Tandem-Mass-Tags approach on the Q-Exactive-Plus Hybrid Quadrupole-Orbitrap mass-spectrometer. Identification and relative quantification were performed in Proteome Discoverer. Data were analyzed using R. Gene ontology terms were analyzed based on Canis lupus familiaris database. Data are available via ProteomeXchange with identifier PXD041129. Eighty-one proteins with different relative adundance were identified in the four groups and 25 were master proteins (p < 0.05). Clusterin (CLU), and apolipoprotein A1 (APOA1) had higher abundance in the three groups of dogs (groups B, C, D) compared to controls. Amine oxidase (AOC3) was higher in abundance in group B compared to groups C and D, and lower in group A. Adiponectin (ADIPOQ) had higher abundance in groups C compared to group A. ADIPOQ and fibronectin (FN1) had higher abundance in group B compared to group C and D. Peroxidase activity assay was used to quantify HP abundance change, validating and correlating with proteomic analysis (r = 0.8796). SIGNIFICANCE: The proteomic analysis of serum samples from epileptic dogs indicated potential markers of epilepsy (CLU), proteins that may contribute to nerve tissue regeneration (APOA1), and contributing factors to epileptogenesis (AOC3). AEM could alter extracellular matrix proteins (FN1). Illness (epilepsy) severity could influence ADIPOQ abundance.
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Affiliation(s)
- Rania D Baka
- Diagnostic Laboratory, Faculty of Veterinary Medicine, School of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece.
| | - Josipa Kuleš
- Department of Chemistry and Biochemistry, Faculty of Veterinary Medicine, University of Zagreb, Zagreb, Croatia
| | - Anđelo Beletić
- Laboratory of proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Zagreb, Croatia
| | - Vladimir Farkaš
- Laboratory of proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Zagreb, Croatia
| | - Dina Rešetar Maslov
- Laboratory of proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Zagreb, Croatia
| | - Blanka Beer Ljubić
- Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Zagreb, Croatia
| | - Ivana Rubić
- Laboratory of proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Zagreb, Croatia
| | - Vladimir Mrljak
- Laboratory of proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Zagreb, Croatia; Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Zagreb, Croatia
| | - Marκ McLaughlin
- Institute of Biodiversity, Animal Health & Comparative Medicine and School of Veterinary Medicine, College of Medicine, Veterinary Medicine and Life Sciences,University of Glasgow, Glasgow G61 1QH, UK
| | - David Eckersall
- Institute of Biodiversity, Animal Health & Comparative Medicine and School of Veterinary Medicine, College of Medicine, Veterinary Medicine and Life Sciences,University of Glasgow, Glasgow G61 1QH, UK
| | - Zoe Polizopoulou
- Diagnostic Laboratory, Faculty of Veterinary Medicine, School of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
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Rubboli G, Beier CP, Selmer KK, Syvertsen M, Shakeshaft A, Collingwood A, Hall A, Andrade DM, Fong CY, Gesche J, Greenberg DA, Hamandi K, Lim KS, Ng CC, Orsini A, Striano P, Thomas RH, Zarubova J, Richardson MP, Strug LJ, Pal DK. Variation in prognosis and treatment outcome in juvenile myoclonic epilepsy: a Biology of Juvenile Myoclonic Epilepsy Consortium proposal for a practical definition and stratified medicine classifications. Brain Commun 2023; 5:fcad182. [PMID: 37361715 PMCID: PMC10288558 DOI: 10.1093/braincomms/fcad182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 03/21/2023] [Accepted: 06/08/2023] [Indexed: 06/28/2023] Open
Abstract
Reliable definitions, classifications and prognostic models are the cornerstones of stratified medicine, but none of the current classifications systems in epilepsy address prognostic or outcome issues. Although heterogeneity is widely acknowledged within epilepsy syndromes, the significance of variation in electroclinical features, comorbidities and treatment response, as they relate to diagnostic and prognostic purposes, has not been explored. In this paper, we aim to provide an evidence-based definition of juvenile myoclonic epilepsy showing that with a predefined and limited set of mandatory features, variation in juvenile myoclonic epilepsy phenotype can be exploited for prognostic purposes. Our study is based on clinical data collected by the Biology of Juvenile Myoclonic Epilepsy Consortium augmented by literature data. We review prognosis research on mortality and seizure remission, predictors of antiseizure medication resistance and selected adverse drug events to valproate, levetiracetam and lamotrigine. Based on our analysis, a simplified set of diagnostic criteria for juvenile myoclonic epilepsy includes the following: (i) myoclonic jerks as mandatory seizure type; (ii) a circadian timing for myoclonia not mandatory for the diagnosis of juvenile myoclonic epilepsy; (iii) age of onset ranging from 6 to 40 years; (iv) generalized EEG abnormalities; and (v) intelligence conforming to population distribution. We find sufficient evidence to propose a predictive model of antiseizure medication resistance that emphasises (i) absence seizures as the strongest stratifying factor with regard to antiseizure medication resistance or seizure freedom for both sexes and (ii) sex as a major stratifying factor, revealing elevated odds of antiseizure medication resistance that correlates to self-report of catamenial and stress-related factors including sleep deprivation. In women, there are reduced odds of antiseizure medication resistance associated with EEG-measured or self-reported photosensitivity. In conclusion, by applying a simplified set of criteria to define phenotypic variations of juvenile myoclonic epilepsy, our paper proposes an evidence-based definition and prognostic stratification of juvenile myoclonic epilepsy. Further studies in existing data sets of individual patient data would be helpful to replicate our findings, and prospective studies in inception cohorts will contribute to validate them in real-world practice for juvenile myoclonic epilepsy management.
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Affiliation(s)
- Guido Rubboli
- Danish Epilepsy Centre, Filadelfia, Dianalund 4293, Denmark
- Institute of Clinical Medicine, University of Copenhagen, Copenhagen 2200, Denmark
| | - Christoph P Beier
- Department of Neurology, Odense University Hospital, Odense 5000, Denmark
| | - Kaja K Selmer
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo 0372, Norway
- National Centre for Epilepsy, Oslo University Hospital, Oslo 1337, Norway
| | - Marte Syvertsen
- Department of Neurology, Drammen Hospital, Vestre Viken Health Trust, Oslo 3004, Norway
| | - Amy Shakeshaft
- Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SW1H 9NA, UK
| | - Amber Collingwood
- Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Anna Hall
- Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Danielle M Andrade
- Adult Epilepsy Genetics Program, Krembil Research Institute, University of Toronto, Toronto M5T 0S8, Canada
| | - Choong Yi Fong
- Division of Paediatric Neurology, Department of Pediatrics, Faculty of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia
| | - Joanna Gesche
- Department of Neurology, Odense University Hospital, Odense 5000, Denmark
| | - David A Greenberg
- Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus 43215, USA
| | - Khalid Hamandi
- Department of Neurology, Cardiff & Vale University Health Board, Cardiff CF14 4XW, UK
| | - Kheng Seang Lim
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia
| | - Ching Ching Ng
- Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia
| | - Alessandro Orsini
- Department of Clinical and Experimental Medicine, Pisa University Hospital, Pisa 56126, Italy
| | - Pasquale Striano
- Pediatric Neurology and Muscular Disease Unit, IRCCS Istituto ‘G. Gaslini’, Genova 16147, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova 16132, Italy
| | - Rhys H Thomas
- Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne NE7 7DN, UK
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Jana Zarubova
- Department of Neurology, Second Faculty of Medicine, Charles University, Prague 150 06, Czech Republic
- Motol University Hospital, Prague 150 06, Czech Republic
| | - Mark P Richardson
- Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SW1H 9NA, UK
- School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London SE5 8AF, UK
| | - Lisa J Strug
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto M5G 1X8, Canada
- Departments of Statistical Sciences and Computer Science and Division of Biostatistics, The University of Toronto, Toronto M5G 1Z5, Canada
| | - Deb K Pal
- Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SW1H 9NA, UK
- School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London SE5 8AF, UK
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Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records. Sci Rep 2022; 12:19430. [PMID: 36371527 PMCID: PMC9653502 DOI: 10.1038/s41598-022-23101-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 10/25/2022] [Indexed: 11/13/2022] Open
Abstract
Biomedical ontologies are widely used to harmonize heterogeneous data and integrate large volumes of clinical data from multiple sources. This study analyzed the utility of ontologies beyond their traditional roles, that is, in addressing a challenging and currently underserved field of feature engineering in machine learning workflows. Machine learning workflows are being increasingly used to analyze medical records with heterogeneous phenotypic, genotypic, and related medical terms to improve patient care. We performed a retrospective study using neuropathology reports from the German Neuropathology Reference Center for Epilepsy Surgery at Erlangen, Germany. This cohort included 312 patients who underwent epilepsy surgery and were labeled with one or more diagnoses, including dual pathology, hippocampal sclerosis, malformation of cortical dysplasia, tumor, encephalitis, and gliosis. We modeled the diagnosis terms together with their microscopy, immunohistochemistry, anatomy, etiologies, and imaging findings using the description logic-based Web Ontology Language (OWL) in the Epilepsy and Seizure Ontology (EpSO). Three tree-based machine learning models were used to classify the neuropathology reports into one or more diagnosis classes with and without ontology-based feature engineering. We used five-fold cross validation to avoid overfitting with a fixed number of repetitions while leaving out one subset of data for testing, and we used recall, balanced accuracy, and hamming loss as performance metrics for the multi-label classification task. The epilepsy ontology-based feature engineering approach improved the performance of all the three learning models with an improvement of 35.7%, 54.5%, and 33.3% in logistics regression, random forest, and gradient tree boosting models respectively. The run time performance of all three models improved significantly with ontology-based feature engineering with gradient tree boosting model showing a 93.8% reduction in the time required for training and testing of the model. Although, all three models showed an overall improved performance across the three-performance metrics using ontology-based feature engineering, the rate of improvement was not consistent across all input features. To analyze this variation in performance, we computed feature importance scores and found that microscopy had the highest importance score across the three models, followed by imaging, immunohistochemistry, and anatomy in a decreasing order of importance scores. This study showed that ontologies have an important role in feature engineering to make heterogeneous clinical data accessible to machine learning models and also improve the performance of machine learning models in multilabel multiclass classification tasks.
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Löscher W. Dogs as a Natural Animal Model of Epilepsy. Front Vet Sci 2022; 9:928009. [PMID: 35812852 PMCID: PMC9257283 DOI: 10.3389/fvets.2022.928009] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 05/18/2022] [Indexed: 12/13/2022] Open
Abstract
Epilepsy is a common neurological disease in both humans and domestic dogs, making dogs an ideal translational model of epilepsy. In both species, epilepsy is a complex brain disease characterized by an enduring predisposition to generate spontaneous recurrent epileptic seizures. Furthermore, as in humans, status epilepticus is one of the more common neurological emergencies in dogs with epilepsy. In both species, epilepsy is not a single disease but a group of disorders characterized by a broad array of clinical signs, age of onset, and underlying causes. Brain imaging suggests that the limbic system, including the hippocampus and cingulate gyrus, is often affected in canine epilepsy, which could explain the high incidence of comorbid behavioral problems such as anxiety and cognitive alterations. Resistance to antiseizure medications is a significant problem in both canine and human epilepsy, so dogs can be used to study mechanisms of drug resistance and develop novel therapeutic strategies to benefit both species. Importantly, dogs are large enough to accommodate intracranial EEG and responsive neurostimulation devices designed for humans. Studies in epileptic dogs with such devices have reported ictal and interictal events that are remarkably similar to those occurring in human epilepsy. Continuous (24/7) EEG recordings in a select group of epileptic dogs for >1 year have provided a rich dataset of unprecedented length for studying seizure periodicities and developing new methods for seizure forecasting. The data presented in this review substantiate that canine epilepsy is an excellent translational model for several facets of epilepsy research. Furthermore, several techniques of inducing seizures in laboratory dogs are discussed as related to therapeutic advances. Importantly, the development of vagus nerve stimulation as a novel therapy for drug-resistant epilepsy in people was based on a series of studies in dogs with induced seizures. Dogs with naturally occurring or induced seizures provide excellent large-animal models to bridge the translational gap between rodents and humans in the development of novel therapies. Furthermore, because the dog is not only a preclinical species for human medicine but also a potential patient and pet, research on this species serves both veterinary and human medicine.
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Affiliation(s)
- Wolfgang Löscher
- Department of Pharmacology, Toxicology and Pharmacy, University of Veterinary Medicine, Hannover, Germany
- Center for Systems Neuroscience, Hannover, Germany
- *Correspondence: Wolfgang Löscher
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Okada T, Fujimoto K, Fushimi Y, Akasaka T, Thuy DHD, Shima A, Sawamoto N, Oishi N, Zhang Z, Funaki T, Nakamoto Y, Murai T, Miyamoto S, Takahashi R, Isa T. Neuroimaging at 7 Tesla: a pictorial narrative review. Quant Imaging Med Surg 2022; 12:3406-3435. [PMID: 35655840 PMCID: PMC9131333 DOI: 10.21037/qims-21-969] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 02/05/2022] [Indexed: 01/26/2024]
Abstract
Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.
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Affiliation(s)
- Tomohisa Okada
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Koji Fujimoto
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Thai Akasaka
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Dinh H. D. Thuy
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Atsushi Shima
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Nobukatsu Sawamoto
- Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Oishi
- Medial Innovation Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Zhilin Zhang
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takeshi Funaki
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tadashi Isa
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Abstract
PURPOSE OF REVIEW Comorbidities are a common feature in epilepsy, but neither the entire spectrum nor the significance of such comorbidities has been fully explored. We review comorbidities associated with epilepsy and their associated burden, provide an overview of relationships, and discuss a new conceptualization of the comorbidities. RECENT FINDINGS The epidemiology of the comorbidities of epilepsy and effects on health outcomes, healthcare use, and healthcare expenditures have been partly delineated. Distinct mechanisms of the associations have been suggested but not entirely ascertained. Movement from conceptualizing epilepsy as a condition to a symptom-complex has occurred. SUMMARY Comorbidities are common among people with epilepsy and are associated with poorer clinical outcomes and quality of life, greater use of health resources, and increased expenditure. Becoming aware of the associated mechanisms and their uncertainty is central to understanding the relationships between epilepsy and comorbid health conditions, which have implications for diagnosis and screening, medical management, and surgical management. Conceptualizing comorbidities of epilepsy as precipitating factors and epilepsy as the symptom will improve the understanding of epilepsy and catalyze research and improvements in clinical practice.
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Affiliation(s)
- Nathan A Shlobin
- Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Josemir W Sander
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG & Chalfont Centre for Epilepsy, Chalfont St Peter, UK
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede 2103SW, The Netherlands
- Neurology Department, West of China Hospital, Sichuan University, Chengdu, China
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Shlobin NA, Sander JW. The Need for a Pragmatic Seizure Classification in Clinical Trials. Epilepsia 2022; 63:1279-1280. [PMID: 35266147 DOI: 10.1111/epi.17218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 03/07/2022] [Indexed: 02/05/2023]
Affiliation(s)
- Nathan A Shlobin
- Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Josemir W Sander
- UCL Queen Square Institute of Neurology, NIHR University College London Hospitals Biomedical Research Centre, London WC1N 3BG, & Chalfont Centre for Epilepsy, Chalfont St Peter, UK.,Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, the Netherlands.,Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
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Temporal trends in the epilepsy treatment gap in low- and low-middle-income countries: A meta-analysis. J Neurol Sci 2022; 434:120174. [DOI: 10.1016/j.jns.2022.120174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 01/01/2022] [Accepted: 01/24/2022] [Indexed: 11/22/2022]
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Rajakulendran S, Belluzzo M, Novy J, Sisodiya SM, Koepp MJ, Duncan JS, Sander JW. Late-life terminal seizure freedom in drug-resistant epilepsy: "Burned-out epilepsy". J Neurol Sci 2021; 431:120043. [PMID: 34753039 DOI: 10.1016/j.jns.2021.120043] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 10/10/2021] [Accepted: 10/25/2021] [Indexed: 02/05/2023]
Abstract
The course of established epilepsy in late life is not fully known. One key question is whether the resolution of an epileptic diathesis is a natural outcome in some people with long-standing epilepsy. We investigated this with a view to generating a hypothesis. We retrospectively explored whether terminal seizure-freedom occurs in older people with previous drug-resistant epilepsy at the Chalfont Centre for Epilepsy over twenty years. Of the 226 people followed for a median period of 52 years, 39 (17%) achieved late-life terminal seizure-freedom of at least two years before death, which occurred at a median age of 68 years with a median duration of 7 years. Multivariate analysis suggests that a high initial seizure frequency was a negative predictor (p < 0.0005). Our findings indicate that the 'natural' course of long-standing epilepsy in some people is one of terminal seizure freedom. We also consider the concept of "remission" in epilepsy, its definition challenges, and the evolving terminology used to describe the state of seizure freedom. The intersection of ageing and seizure freedom is an essential avenue of future investigation, especially in light of current demographic trends. Gaining mechanistic insights into this phenomenon may help broaden our understanding of the neurobiology of epilepsy and potentially provide targets for therapeutic intervention.
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Affiliation(s)
- S Rajakulendran
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG & Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, United Kingdom
| | - M Belluzzo
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG & Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, United Kingdom; Department of Clinical Neurosciences, Neurology Unit, Santa Maria della Misericordia Hospital, Udine 33100, Italy
| | - J Novy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG & Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, United Kingdom; Department of Clinical Neurosciences, Neurology Service, Lausanne University Hospital (Vaud University Hospital Center) and University of Lausanne, Lausanne, Switzerland
| | - S M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG & Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, United Kingdom
| | - M J Koepp
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG & Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, United Kingdom
| | - J S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG & Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, United Kingdom
| | - J W Sander
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG & Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, United Kingdom; Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, Heemstede 2103SW, Netherlands; Department of Neurology, West China Hospital & Institute of Brain Science & Brain-inspired Technology, Sichuan University, Chengdu 610041, China.
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