Cognitive phenotypes in temporal lobe epilepsy utilizing data- and clinically driven approaches: Moving toward a new taxonomy

Anny Reyes; Erik Kaestner; Lisa Ferguson; Jana E Jones; Michael Seidenberg; William B Barr; Robyn M Busch; Bruce P Hermann; Carrie R McDonald

doi:10.1111/epi.16528

Cognitive phenotypes in temporal lobe epilepsy utilizing data- and clinically driven approaches: Moving toward a new taxonomy

Epilepsia. 2020 Jun;61(6):1211-1220. doi: 10.1111/epi.16528. Epub 2020 May 4.

Authors

Anny Reyes^{1

2

3}, Erik Kaestner^{2

3}, Lisa Ferguson⁴, Jana E Jones⁵, Michael Seidenberg⁶, William B Barr⁷, Robyn M Busch⁴, Bruce P Hermann⁵, Carrie R McDonald^{1

2

3}

Affiliations

¹ San Diego State University, University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA.
² Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA.
³ Department of Psychiatry, University of California, San Diego, CA, USA.
⁴ Department of Neurology, Cleveland Clinic, Cleveland, OH, USA.
⁵ Department of Neurology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
⁶ Rosalind Franklin University of Medicine and Science, Chicago, IL, USA.
⁷ Departments of Neurology and Psychiatry, NYU-Langone Medical Center and NYU School of Medicine, New York, NY, USA.

Abstract

Objective: To identify cognitive phenotypes in temporal lobe epilepsy (TLE) and test their reproducibility in a large, multi-site cohort of patients using both data-driven and clinically driven approaches.

Method: Four-hundred seven patients with TLE who underwent a comprehensive neuropsychological evaluation at one of four epilepsy centers were included. Scores on tests of verbal memory, naming, fluency, executive function, and psychomotor speed were converted into z-scores based on 151 healthy controls (HCs). For the data-driven method, cluster analysis (k-means) was used to determine the optimal number of clusters. For the clinically driven method, impairment was defined as >1.5 standard deviations below the mean of the HC, and patients were classified into groups based on the pattern of impairment.

Results: Cluster analysis revealed a three-cluster solution characterized by (a) generalized impairment (29%), (b) language and memory impairment (28%), and (c) no impairment (43%). Based on the clinical criteria, the same broad categories were identified, but with a different distribution: (a) generalized impairment (37%), (b) language and memory impairment (30%), and (c) no impairment (33%). There was a 82.6% concordance rate with good agreement (κ = .716) between the methods. Forty-eight patients classified as having a normal profile based on cluster analysis were classified as having generalized impairment (n = 16) or an isolated language/memory impairment (n = 32) based on the clinical criteria. Patients with generalized impairment had a longer disease duration and patients with no impairment had more years of education. However, patients demonstrating the classic TLE profile (ie, language and memory impairment) were not more likely to have an earlier age at onset or mesial temporal sclerosis.

Significance: We validate previous findings from single-site studies that have identified three unique cognitive phenotypes in TLE and offer a means of translating the patterns into a clinical diagnostic criteria, representing a novel taxonomy of neuropsychological status in TLE.

Keywords: cognitive phenotypes; epilepsy; taxonomy.

Publication types

Multicenter Study
Research Support, N.I.H., Extramural

MeSH terms

Adult
Classification
Cluster Analysis
Cognition / physiology*
Databases, Factual / classification*
Epilepsy, Temporal Lobe / classification*
Epilepsy, Temporal Lobe / diagnosis
Epilepsy, Temporal Lobe / psychology*
Female
Humans
Male
Middle Aged
Neuropsychological Tests*
Phenotype*
Young Adult

Abstract

Publication types

MeSH terms

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