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Struck AF, Garcia-Ramos C, Nair VA, Prabhakaran V, Dabbs K, Conant LL, Binder JR, Loring D, Meyerand M, Hermann BP. The relevance of Spearman's g for epilepsy. Brain Commun 2024; 6:fcae176. [PMID: 38883806 PMCID: PMC11179110 DOI: 10.1093/braincomms/fcae176] [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: 11/02/2023] [Revised: 04/18/2024] [Accepted: 06/10/2024] [Indexed: 06/18/2024] Open
Abstract
Whilst the concept of a general mental factor known as 'g' has been of longstanding interest, for unknown reasons, it has never been interrogated in epilepsy despite the 100+ year empirical history of the neuropsychology of epilepsy. This investigation seeks to identify g within a comprehensive neuropsychological data set and compare participants with temporal lobe epilepsy to controls, characterize the discriminatory power of g compared with domain-specific cognitive metrics, explore the association of g with clinical epilepsy and sociodemographic variables and identify the structural and network properties associated with g in epilepsy. Participants included 110 temporal lobe epilepsy patients and 79 healthy controls between the ages of 19 and 60. Participants underwent neuropsychological assessment, clinical interview and structural and functional imaging. Cognitive data were subjected to factor analysis to identify g and compare the group of patients with control participants. The relative power of g compared with domain-specific tests was interrogated, clinical and sociodemographic variables were examined for their relationship with g, and structural and functional images were assessed using traditional regional volumetrics, cortical surface features and network analytics. Findings indicate (i) significantly (P < 0.005) lower g in patients compared with controls; (ii) g is at least as powerful as individual cognitive domain-specific metrics and other analytic approaches to discriminating patients from control participants; (iii) lower g was associated with earlier age of onset and medication use, greater number of antiseizure medications and longer epilepsy duration (Ps < 0.04); and lower parental and personal education and greater neighbourhood deprivation (Ps < 0.012); and (iv) amongst patients, lower g was linked to decreased total intracranial volume (P = 0.019), age and intracranial volume adjusted total tissue volume (P = 0.019) and age and intracranial volume adjusted total corpus callosum volume (P = 0.012)-particularly posterior, mid-posterior and anterior (Ps < 0.022) regions. Cortical vertex analyses showed lower g to be associated specifically with decreased gyrification in bilateral medial orbitofrontal regions. Network analysis of resting-state data with focus on the participation coefficient showed g to be associated with the superior parietal network. Spearman's g is reduced in patients, has considerable discriminatory power compared with domain-specific metrics and is linked to a multiplex of factors related to brain (size, connectivity and frontoparietal networks), environment (familial and personal education and neighbourhood disadvantage) and disease (epilepsy onset, treatment and duration). Greater attention to contemporary models of human cognition is warranted in order to advance the neuropsychology of epilepsy.
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Affiliation(s)
- Aaron F Struck
- Department of Neurology, University of Wisconsin-Madison, Madison, WI 53726, USA
- Department of Neurology, William S. Middleton Veterans Administration Hospital, Madison, WI 53705, USA
| | - Camille Garcia-Ramos
- Department of Neurology, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Veena A Nair
- Department of Radiology, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Vivek Prabhakaran
- Department of Radiology, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Kevin Dabbs
- Department of Neurology, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Lisa L Conant
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Jeffrey R Binder
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - David Loring
- Department of Neurology and Pediatrics, Emory University, Atlanta, GA 30322, USA
| | - Mary Meyerand
- Department of Medical Physics, Wisconsin-Madison, Madison, WI 53726, USA
| | - Bruce P Hermann
- Department of Neurology, University of Wisconsin-Madison, Madison, WI 53726, USA
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Du Y, Nie J, Zhang J, Fang Y, Wei W, Wang J, Zhang S, Wang J, Li X. Disrupted topological organization of the default mode network in mild cognitive impairment with subsyndromal depression: A graph theoretical analysis. CNS Neurosci Ther 2024; 30:e14547. [PMID: 38105496 PMCID: PMC11017411 DOI: 10.1111/cns.14547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 10/26/2023] [Accepted: 11/20/2023] [Indexed: 12/19/2023] Open
Abstract
AIMS Subsyndromal depression (SSD) is common in mild cognitive impairment (MCI). However, the neural mechanisms underlying MCI with SSD (MCID) are unclear. The default mode network (DMN) is associated with cognitive processes and depressive symptoms. Therefore, we aimed to explore the topological organization of the DMN in patients with MCID. METHODS Forty-two MCID patients, 34 MCI patients without SSD (MCIND), and 36 matched healthy controls (HCs) were enrolled. The resting-state functional connectivity of the DMN of the participants was analyzed using a graph theoretical approach. Correlation analyses of network topological metrics, depressive symptoms, and cognitive function were conducted. Moreover, support vector machine (SVM) models were constructed based on topological metrics to distinguish MCID from MCIND. Finally, we used 10 repeats of 5-fold cross-validation for performance verification. RESULTS We found that the global efficiency and nodal efficiency of the left anterior medial prefrontal cortex (aMPFC) of the MCID group were significantly lower than the MCIND group. Moreover, small-worldness and global efficiency were negatively correlated with depressive symptoms in MCID, and the nodal efficiency of the left lateral temporal cortex and left aMPFC was positively correlated with cognitive function in MCID. In cross-validation, the SVM model had an accuracy of 0.83 [95% CI 0.79-0.87], a sensitivity of 0.88 [95% CI 0.86-0.90], a specificity of 0.75 [95% CI 0.72-0.78] and an area under the curve of 0.88 [95% CI 0.85-0.91]. CONCLUSIONS The coexistence of MCI and SSD was associated with the greatest disrupted topological organization of the DMN. The network topological metrics could identify MCID and serve as biomarkers of different clinical phenotypic presentations of MCI.
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Affiliation(s)
- Yang Du
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Jing Nie
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Jian‐Ye Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yuan Fang
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Wen‐Jing Wei
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Jing‐Hua Wang
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Shao‐Wei Zhang
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Jin‐Hong Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Xia Li
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
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Miziak B, Czuczwar SJ. Approaches for the discovery of drugs that target K Na 1.1 channels in KCNT1-associated epilepsy. Expert Opin Drug Discov 2022; 17:1313-1328. [PMID: 36408599 DOI: 10.1080/17460441.2023.2150164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
INTRODUCTION There are approximately 70 million people with epilepsy and about 30% of patients are not satisfactorily treated. A link between gene mutations and epilepsy is well documented. A number of pathological variants of KCNT1 gene (encoding the weakly voltage-dependent sodium-activated potassium channel - KNa 1.1) mutations has been found. For instance, epilepsy of infancy with migrating focal seizures, autosomal sleep-related hypermotor epilepsy or Ohtahara syndrome have been associated with KCNT1 gene mutations. AREAS COVERED Several methods for studies on KNa 1.1 channels have been reviewed - patch clamp analysis, Förster resonance energy transfer spectroscopy and whole-exome sequencing. The authors also review available drugs for the management of KCNT1 epilepsies. EXPERT OPINION The current methods enable deeper insights into electrophysiology of KNa 1.1 channels or its functioning in different activation states. It is also possible to identify a given KCNT1 mutation. Quinidine and cannabidiol show variable efficacy as add-on to baseline antiepileptic drugs so more effective treatments are required. A combined approach with the methods shown above, in silico methods and the animal model of KCNT1 epilepsies seems likely to create personalized treatment of patients with KCNT1 gene mutations.
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Affiliation(s)
- Barbara Miziak
- Department of Pathophysiology, Medical University of Lublin, Lublin, Poland
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