青少年肌阵挛性癫痫的潜在认知表型:临床、社会人口学和神经影像学关联。

IF 6.6 1区 医学 Q1 CLINICAL NEUROLOGY Epilepsia Pub Date : 2024-11-02 DOI:10.1111/epi.18167
Aaron F Struck, Camille Garcia-Ramos, Vivek Prabhakaran, Veena Nair, Nagesh Adluru, Anusha Adluru, Dace Almane, Jana E Jones, Bruce P Hermann
{"title":"青少年肌阵挛性癫痫的潜在认知表型:临床、社会人口学和神经影像学关联。","authors":"Aaron F Struck, Camille Garcia-Ramos, Vivek Prabhakaran, Veena Nair, Nagesh Adluru, Anusha Adluru, Dace Almane, Jana E Jones, Bruce P Hermann","doi":"10.1111/epi.18167","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Application of cluster analytic procedures has advanced understanding of the cognitive heterogeneity inherent in diverse epilepsy syndromes and the associated clinical and neuroimaging features. Application of this unsupervised machine learning approach to the neuropsychological performance of persons with juvenile myoclonic epilepsy (JME) has yet to be attempted, which is the intent of this investigation.</p><p><strong>Methods: </strong>A total of 77 JME participants, 19 unaffected siblings, and 44 unrelated controls, 12 to 25 years of age, were administered a comprehensive neuropsychological battery (intelligence, language, memory, executive function, and processing speed), which was subjected to factor analysis followed by K-means clustering of the resultant factor scores. Identified cognitive phenotypes were characterized and related to clinical, family, sociodemographic, and cortical and subcortical imaging features.</p><p><strong>Results: </strong>Factor analysis revealed three underlying cognitive dimensions (general ability, speed/response inhibition, and learning/memory), with JME participants performing worse than unrelated controls across all factor scores, and unaffected siblings performing worse than unrelated controls on the general mental ability and learning/memory factors, with no JME vs sibling differences. K-means clustering of the factor scores revealed three latent groups including above average (31.4% of participants), average (52.1%), and abnormal performance (16.4%). Participant groups differed in their distributions across the latent groups (p < 0.001), with 23% JME, 22% siblings, and 2% unrelated controls in the abnormal performance group; and 18% JME, 21% siblings, and 59% unrelated controls in the above average group. Clinical epilepsy variables were unassociated with cluster membership, whereas family factors (lower parental education) and abnormally increased thickness and/or volume in the frontal, parietal, and temporal-occipital regions were associated with the abnormal cognition group.</p><p><strong>Significance: </strong>Distinct cognitive phenotypes characterize the spectrum of neuropsychological performance of patients with JME for which there is familial (sibling) aggregation. Phenotypic membership was associated with parental (education) and imaging characteristics (increased cortical thickness and volume) but not basic clinical seizure features.</p>","PeriodicalId":11768,"journal":{"name":"Epilepsia","volume":null,"pages":null},"PeriodicalIF":6.6000,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Latent cognitive phenotypes in juvenile myoclonic epilepsy: Clinical, sociodemographic, and neuroimaging associations.\",\"authors\":\"Aaron F Struck, Camille Garcia-Ramos, Vivek Prabhakaran, Veena Nair, Nagesh Adluru, Anusha Adluru, Dace Almane, Jana E Jones, Bruce P Hermann\",\"doi\":\"10.1111/epi.18167\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Application of cluster analytic procedures has advanced understanding of the cognitive heterogeneity inherent in diverse epilepsy syndromes and the associated clinical and neuroimaging features. Application of this unsupervised machine learning approach to the neuropsychological performance of persons with juvenile myoclonic epilepsy (JME) has yet to be attempted, which is the intent of this investigation.</p><p><strong>Methods: </strong>A total of 77 JME participants, 19 unaffected siblings, and 44 unrelated controls, 12 to 25 years of age, were administered a comprehensive neuropsychological battery (intelligence, language, memory, executive function, and processing speed), which was subjected to factor analysis followed by K-means clustering of the resultant factor scores. Identified cognitive phenotypes were characterized and related to clinical, family, sociodemographic, and cortical and subcortical imaging features.</p><p><strong>Results: </strong>Factor analysis revealed three underlying cognitive dimensions (general ability, speed/response inhibition, and learning/memory), with JME participants performing worse than unrelated controls across all factor scores, and unaffected siblings performing worse than unrelated controls on the general mental ability and learning/memory factors, with no JME vs sibling differences. K-means clustering of the factor scores revealed three latent groups including above average (31.4% of participants), average (52.1%), and abnormal performance (16.4%). Participant groups differed in their distributions across the latent groups (p < 0.001), with 23% JME, 22% siblings, and 2% unrelated controls in the abnormal performance group; and 18% JME, 21% siblings, and 59% unrelated controls in the above average group. Clinical epilepsy variables were unassociated with cluster membership, whereas family factors (lower parental education) and abnormally increased thickness and/or volume in the frontal, parietal, and temporal-occipital regions were associated with the abnormal cognition group.</p><p><strong>Significance: </strong>Distinct cognitive phenotypes characterize the spectrum of neuropsychological performance of patients with JME for which there is familial (sibling) aggregation. Phenotypic membership was associated with parental (education) and imaging characteristics (increased cortical thickness and volume) but not basic clinical seizure features.</p>\",\"PeriodicalId\":11768,\"journal\":{\"name\":\"Epilepsia\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.6000,\"publicationDate\":\"2024-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Epilepsia\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/epi.18167\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epilepsia","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/epi.18167","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0

摘要

目的:聚类分析程序的应用增进了人们对各种癫痫综合征固有的认知异质性以及相关临床和神经影像学特征的了解。将这种无监督机器学习方法应用于青少年肌阵挛性癫痫(JME)患者的神经心理学表现尚未尝试过,而这正是本次调查的目的所在:共对 77 名 12 至 25 岁的 JME 患者、19 名未受影响的兄弟姐妹和 44 名无亲属关系的对照组患者进行了全面的神经心理测试(智力、语言、记忆、执行功能和处理速度),并对测试结果进行了因子分析和 K-means 聚类分析。对确定的认知表型进行了特征描述,并将其与临床、家庭、社会人口学、皮层和皮层下成像特征联系起来:因子分析揭示了三个潜在的认知维度(一般能力、速度/反应抑制和学习/记忆),在所有因子得分上,JME参与者的表现都比非相关对照组差,而在一般心智能力和学习/记忆因子上,未受影响的兄弟姐妹的表现比非相关对照组差,JME与兄弟姐妹之间没有差异。因子得分的 K-means 聚类显示了三个潜在的组别,包括高于平均水平组(31.4% 的参与者)、平均水平组(52.1%)和表现异常组(16.4%)。在各潜在组别中,参与者组别的分布存在差异(p 显著性):不同的认知表型描述了存在家族(兄弟姐妹)聚集现象的 JME 患者的神经心理学表现。表型成员与父母(教育程度)和成像特征(皮质厚度和体积增加)有关,但与基本临床发作特征无关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Latent cognitive phenotypes in juvenile myoclonic epilepsy: Clinical, sociodemographic, and neuroimaging associations.

Objective: Application of cluster analytic procedures has advanced understanding of the cognitive heterogeneity inherent in diverse epilepsy syndromes and the associated clinical and neuroimaging features. Application of this unsupervised machine learning approach to the neuropsychological performance of persons with juvenile myoclonic epilepsy (JME) has yet to be attempted, which is the intent of this investigation.

Methods: A total of 77 JME participants, 19 unaffected siblings, and 44 unrelated controls, 12 to 25 years of age, were administered a comprehensive neuropsychological battery (intelligence, language, memory, executive function, and processing speed), which was subjected to factor analysis followed by K-means clustering of the resultant factor scores. Identified cognitive phenotypes were characterized and related to clinical, family, sociodemographic, and cortical and subcortical imaging features.

Results: Factor analysis revealed three underlying cognitive dimensions (general ability, speed/response inhibition, and learning/memory), with JME participants performing worse than unrelated controls across all factor scores, and unaffected siblings performing worse than unrelated controls on the general mental ability and learning/memory factors, with no JME vs sibling differences. K-means clustering of the factor scores revealed three latent groups including above average (31.4% of participants), average (52.1%), and abnormal performance (16.4%). Participant groups differed in their distributions across the latent groups (p < 0.001), with 23% JME, 22% siblings, and 2% unrelated controls in the abnormal performance group; and 18% JME, 21% siblings, and 59% unrelated controls in the above average group. Clinical epilepsy variables were unassociated with cluster membership, whereas family factors (lower parental education) and abnormally increased thickness and/or volume in the frontal, parietal, and temporal-occipital regions were associated with the abnormal cognition group.

Significance: Distinct cognitive phenotypes characterize the spectrum of neuropsychological performance of patients with JME for which there is familial (sibling) aggregation. Phenotypic membership was associated with parental (education) and imaging characteristics (increased cortical thickness and volume) but not basic clinical seizure features.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Epilepsia
Epilepsia 医学-临床神经学
CiteScore
10.90
自引率
10.70%
发文量
319
审稿时长
2-4 weeks
期刊介绍: Epilepsia is the leading, authoritative source for innovative clinical and basic science research for all aspects of epilepsy and seizures. In addition, Epilepsia publishes critical reviews, opinion pieces, and guidelines that foster understanding and aim to improve the diagnosis and treatment of people with seizures and epilepsy.
期刊最新文献
Histopathological substrate of increased T2 signal in the anterior temporal lobe white matter in temporal lobe epilepsy associated with hippocampal sclerosis. Imaging blood-brain barrier dysfunction in drug-resistant epilepsy: A multi-center feasibility study. Long-term neuroplasticity in language networks after anterior temporal lobe resection. Eating habits and behaviors in children with Dravet syndrome: A case-control study. Machine learning for forecasting initial seizure onset in neonatal hypoxic-ischemic encephalopathy.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1