Individual- and community-level social determinants of health are associated with cognition in older adults with focal epilepsy.

OBJECTIVE: Epilepsy is associated with significant health disparities, including access to specialized care and adverse outcomes that have been associated with several social determinants of health (SDOH). We sought to examine the relationship between individual- and community-level SDOH and cognitive outcomes in older adults with epilepsy. MATERIALS AND METHODS: We collected clinical, SDOH, and neuropsychological data in 57 older adults with epilepsy. Individual-level SDOH included patient factors (quality of education, income, insurance, marital status) and early-life environmental factors (parental education and occupation, childhood employment). Neighborhood deprivation was measured with the Area Deprivation Index (ADI). Stepwise regressions were conducted to examine the independent contribution of individual-level SDOH to cognitive performance, and Spearman rho correlations were conducted to examine the relationship between ADI and cognitive performance. The SDOH profiles of patients who met the criteria for cognitive impairment were examined. RESULTS: After controlling for clinical variables, patient factors (public health insurance, poorer quality of education) and early-life environmental factors (lower mother's education, lower father's and mother's occupational complexity, history of childhood employment) were significant predictors of lower performance on measures of global cognition, verbal learning and memory, processing speed, and executive function. Higher ADI values (greater disadvantage) were associated with lower scores on global cognitive measures, verbal learning and memory, and executive function. Patients who met criteria for cognitive impairment had, on average, a greater number of adverse SDOH, including lower household incomes and father's education, and higher ADI values compared to those who were cognitively intact. CONCLUSION: We provide new evidence of the role of individual- and community-level SDOH on cognitive outcomes in older adults with epilepsy. This emerging literature highlights the need to examine SDOH beyond epilepsy-related clinical factors. These data could inform the development of interventions focused on increasing access to epilepsy care, education, and resources and promoting brain and cognitive health within the most at-risk communities.

Disadvantage and neurocognitive comorbidities in childhood idiopathic epilepsies.

OBJECTIVE: This study was undertaken to characterize the relationship between neighborhood disadvantage and cognitive function as well as clinical, sociodemographic, and family factors in children with new onset idiopathic epilepsy and healthy controls. METHODS: Research participants were 288 children aged 8-18 years with recent onset epilepsy (CWE; n = 182; mean age = 12.2 ± 3.2 years), healthy first-degree cousin controls (HC; n = 106; mean age = 12.5 ± 3.0), and one biological or adopted parent per child (n = 279). All participants were administered a comprehensive neuropsychological battery (reasoning, language, memory, executive function, motor function, and academic achievement). Family residential addresses were entered into the Neighborhood Atlas to determine each family's Area Deprivation Index (ADI), a metric used to quantify income, education, employment, and housing quality. A combination of parametric and nonparametric (χ2 ) tests examined the effect of ADI by group (epilepsy and controls) across cognitive, academic, clinical, and family factors. RESULTS: Disadvantage (ADI) was equally distributed between groups (p = .63). For CWE, high disadvantage was associated with lower overall intellectual quotient (IQ; p = .04), visual naming/expressive language (p = .03), phonemic (letter) fluency (p < .01), passive inattention (omission errors; p = .03), delayed verbal recall (p = .04), and dominant fine motor dexterity and speed (p < .01). Cognitive status of the HC group did not differ by level of disadvantage (p = .40). CWE exhibited greater academic difficulties in comparison to HC (p < .001), which were exacerbated by disadvantage in CWE (p = .02) but not HC (p < .05). High disadvantage was associated with a threefold risk for academic challenges prior to epilepsy onset (odds ratio = 3.31, p = .024). SIGNIFICANCE: Socioeconomic hardship (increased neighborhood disadvantage) exerts a significant adverse impact on the cognitive and academic status of youth with new and recent onset epilepsies, an impact that needs to be incorporated into etiological models of the neurobehavioral comorbidities of epilepsy.

Neighborhood disadvantage and intellectual development in youth with epilepsy.

RATIONALE: Recent cross-sectional investigations have demonstrated an adverse impact of socioeconomic disadvantage on cognition and behavior in youth and adults with epilepsy. The goal of this study is to investigate the impact of disadvantage on prospective intellectual development in youth with epilepsy. METHOD: Participants were youth, aged 8-18 years, with recent onset epilepsy (n = 182) and healthy first-degree cousin controls (n = 106). The Wechsler Abbreviated Scale of Intelligence (WASI) was administered at baseline and 2 years later. The Neighborhood Atlas identified each family's Area Deprivation Index via state deciles and national percentiles. WASI data were analyzed by mixed group by time ANOVAs followed by regression analysis to identify other baseline predictors of time 2 outcomes. RESULTS: Youth with epilepsy demonstrated significant interactions between group and time for both verbal (F = 4.02, df = 1,215, p =.05) and nonverbal (F = 4.57, df = 1,215, p =.04) reasoning, demonstrating that disadvantage was associated with slower cognitive development compared to advantaged youth with epilepsy. Similar interactions were not observed for controls. CONCLUSIONS: In youth with new and recent onset epilepsies, neighborhood-level disadvantage is associated with a negative impact on the development of verbal and nonverbal reasoning skills.

Neuroticism in temporal lobe epilepsy is associated with altered limbic-frontal lobe resting-state functional connectivity.

Neuroticism, a core personality trait characterized by a tendency towards experiencing negative affect, has been reported to be higher in people with temporal lobe epilepsy (TLE) compared with healthy individuals. Neuroticism is a known predictor of depression and anxiety, which also occur more frequently in people with TLE. The purpose of this study was to identify abnormalities in whole-brain resting-state functional connectivity in relation to neuroticism in people with TLE and to determine the degree of unique versus shared patterns of abnormal connectivity in relation to elevated symptoms of depression and anxiety. Ninety-three individuals with TLE (55 females) and 40 healthy controls (18 females) from the Epilepsy Connectome Project (ECP) completed measures of neuroticism, depression, and anxiety, which were all significantly higher in people with TLE compared with controls. Resting-state functional connectivity was compared between controls and groups with TLE with high and low neuroticism using analysis of variance (ANOVA) and t-test. In secondary analyses, the same analytics were performed using measures of depression and anxiety and the unique variance in resting-state connectivity associated with neuroticism independent of symptoms of depression and anxiety identified. Increased neuroticism was significantly associated with hyposynchrony between the right hippocampus and Brodmann area (BA) 9 (region of prefrontal cortex (PFC)) (p < 0.005), representing a unique relationship independent of symptoms of depression and anxiety. Hyposynchrony of connection between the right hippocampus and BA47 (anterior frontal operculum) was associated with high neuroticism and with higher depression and anxiety scores (p < 0.05), making it a shared abnormal connection for the three measures. In conclusion, increased neuroticism exhibits both unique and shared patterns of abnormal functional connectivity with depression and anxiety symptoms between regions of the mesial temporal and frontal lobe.

Neuroanatomical correlates of personality traits in temporal lobe epilepsy: Findings from the Epilepsy Connectome Project.

Behavioral and personality disorders in temporal lobe epilepsy (TLE) have been a topic of interest and controversy for decades, with less attention paid to alterations in normal personality structure and traits. In this investigation, core personality traits (the Big 5) and their neurobiological correlates in TLE were explored using the Neuroticism Extraversion Openness-Five Factor Inventory (NEO-FFI) and structural magnetic resonance imaging (MRI) through the Epilepsy Connectome Project (ECP). NEO-FFI scores from 67 individuals with TLE (34.6 ±â€¯9.5 years; 67% women) were compared to 31 healthy controls (32.8 ±â€¯8.9 years; 41% women) to assess differences in the Big 5 traits (agreeableness, openness, conscientiousness, neuroticism, and extraversion). Individuals with TLE showed significantly higher neuroticism, with no significant differences on the other traits. Neural correlates of neuroticism were then determined in participants with TLE including cortical and subcortical volumes. Distributed reductions in cortical gray matter volumes were associated with increased neuroticism. Subcortically, hippocampal and amygdala volumes were negatively associated with neuroticism. These results offer insight into alterations in the Big 5 personality traits in TLE and their brain-related correlates.

Contribution of Family Relatedness to Neurobehavioral Comorbidities in Idiopathic Childhood Epilepsies.

OBJECTIVES: Rates of cognitive, academic and behavioral comorbidities are elevated in children with epilepsy. The contribution of environmental and genetic influences to comorbidity risk is not fully understood. This study investigated children with epilepsy, their unaffected siblings, and controls to determine the presence and extent of risk associated with family relatedness across a range of epilepsy comorbidities. METHODS: Participants were 346 children (8-18 years), n=180 with recent-onset epilepsy, their unaffected siblings (n=67), and healthy first-degree cousin controls (n=99). Assessments included: (1) Child Behavior Checklist/6-18 (CBCL), (2) Behavior Rating Inventory of Executive Function (BRIEF), (3) history of education and academic services, and (4) lifetime attention deficit hyperactivity disorder (ADHD) diagnosis. Analyses consisted of linear mixed effect models for continuous variables, and logistic mixed models for binary variables. RESULTS: Differences were detected between the three groups of children across all measures (p<.001). For ADHD, academic problems, and executive dysfunction, children with epilepsy exhibited significantly more problems than unaffected siblings and controls; siblings and controls did not differ statistically significantly from each other. For social competence, children with epilepsy and their unaffected siblings displayed more abnormality compared with controls, with no statistically significant difference between children with epilepsy and unaffected siblings. For behavioral problems, children with epilepsy had more abnormality than siblings and controls, but unaffected siblings also exhibited more abnormalities than controls. CONCLUSIONS: The contribution of epilepsy and family relatedness varies across specific neurobehavioral comorbidities. Family relatedness was not significantly associated with rates of ADHD, academic problems and executive dysfunction, but was associated with competence and behavioral problems. (JINS, 2018, 24, 653-661).

Validity of the MoCA as a cognitive screening tool in epilepsy: Are there implications for global care and research?

OBJECTIVE: This study evaluated the diagnostic performance of a widely available cognitive screener, the Montreal cognitive assessment (MoCA), to detect cognitive impairment in older patients (age ≥ 55) with epilepsy residing in the US, using the International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) as the gold standard. METHODS: Fifty older adults with focal epilepsy completed the MoCA and neuropsychological measures of memory, language, executive function, and processing speed/attention. The IC-CoDE taxonomy divided participants into IC-CoDE Impaired and Intact groups. Sensitivity and specificity across several MoCA cutoffs were examined. Spearman correlations examined relationships between the MoCA total score and clinical and demographic variables and MoCA domain scores and individual neuropsychological tests. RESULTS: IC-CoDE impaired patients demonstrated significantly lower scores on the MoCA total, visuospatial/executive, naming, language, delayed recall, and orientation domain scores (Cohen's d range: 0.336-2.77). The recommended MoCA cutoff score < 26 had an overall accuracy of 72%, 88.2% sensitivity, and 63.6% specificity. A MoCA cutoff score < 24 yielded optimal sensitivity (70.6%) and specificity (78.8%), with overall accuracy of 76%. Higher MoCA total scores were associated with greater years of education (p = 0.016) and fewer antiseizure medications (p = 0.049). The MoCA memory domain was associated with several standardized measures of memory, MoCA language domain with category fluency, and MoCA abstraction domain with letter fluency. SIGNIFICANCE: This study provides initial validation of the MoCA as a useful screening tool for older adults with epilepsy that can be used to identify patients who may benefit from comprehensive neuropsychological testing. Further, we demonstrate that a lower cutoff (i.e., <24) better captures cognitive impairment in older adults with epilepsy than the generally recommended cutoff and provides evidence for construct overlap between MoCA domains and standard neuropsychological tests. Critically, similar efforts in other regions of the world are needed. PLAIN LANGUAGE SUMMARY: The Montreal cognitive assessment (MoCA) can be a helpful tool to screen for cognitive impairment in older adults with epilepsy. We recommend that adults 55 or older with epilepsy who score less than 24 on the MoCA are referred to a neuropsychologist for a comprehensive evaluation to assess any changes in cognitive abilities and mood.

T1-/T2-weighted ratio reveals no alterations to gray matter myelination in temporal lobe epilepsy.

Short-range functional connectivity in the limbic network is increased in patients with temporal lobe epilepsy (TLE), and recent studies have shown that cortical myelin content correlates with fMRI connectivity. We thus hypothesized that myelin may increase progressively in the epileptic network. We compared T1w/T2w gray matter myelin maps between TLE patients and age-matched controls and assessed relationships between myelin and aging. While both TLE patients and healthy controls exhibited increased T1w/T2w intensity with age, we found no evidence for significant group-level aberrations in overall myelin content or myelin changes through time in TLE.

Brain aging in temporal lobe epilepsy: Chronological, structural, and functional.

The association of epilepsy with structural brain changes and cognitive abnormalities in midlife has raised concern regarding the possibility of future accelerated brain and cognitive aging and increased risk of later life neurocognitive disorders. To address this issue we examined age-related processes in both structural and functional neuroimaging among individuals with temporal lobe epilepsy (TLE, N = 104) who were participants in the Epilepsy Connectome Project (ECP). Support vector regression (SVR) models were trained from 151 healthy controls and used to predict TLE patients' brain ages. It was found that TLE patients on average have both older structural (+6.6 years) and functional (+8.3 years) brain ages compared to healthy controls. Accelerated functional brain age (functional - chronological age) was mildly correlated (corrected P = 0.07) with complex partial seizure frequency and the number of anti-epileptic drug intake. Functional brain age was a significant correlate of declining cognition (fluid abilities) and partially mediated chronological age-fluid cognition relationships. Chronological age was the only positive predictor of crystallized cognition. Accelerated aging is evident not only in the structural brains of patients with TLE, but also in their functional brains. Understanding the causes of accelerated brain aging in TLE will be clinically important in order to potentially prevent or mitigate their cognitive deficits.

Network, clinical and sociodemographic features of cognitive phenotypes in temporal lobe epilepsy.

This study explored the taxonomy of cognitive impairment within temporal lobe epilepsy and characterized the sociodemographic, clinical and neurobiological correlates of identified cognitive phenotypes. 111 temporal lobe epilepsy patients and 83 controls (mean ages 33 and 39, 57% and 61% female, respectively) from the Epilepsy Connectome Project underwent neuropsychological assessment, clinical interview, and high resolution 3T structural and resting-state functional MRI. A comprehensive neuropsychological test battery was reduced to core cognitive domains (language, memory, executive, visuospatial, motor speed) which were then subjected to cluster analysis. The resulting cognitive subgroups were compared in regard to sociodemographic and clinical epilepsy characteristics as well as variations in brain structure and functional connectivity. Three cognitive subgroups were identified (intact, language/memory/executive function impairment, generalized impairment) which differed significantly, in a systematic fashion, across multiple features. The generalized impairment group was characterized by an earlier age at medication initiation (P < 0.05), fewer patient (P < 0.001) and parental years of education (P < 0.05), greater racial diversity (P < 0.05), and greater number of lifetime generalized seizures (P < 0.001). The three groups also differed in an orderly manner across total intracranial (P < 0.001) and bilateral cerebellar cortex volumes (P < 0.01), and rate of bilateral hippocampal atrophy (P < 0.014), but minimally in regional measures of cortical volume or thickness. In contrast, large-scale patterns of cortical-subcortical covariance networks revealed significant differences across groups in global and local measures of community structure and distribution of hubs. Resting-state fMRI revealed stepwise anomalies as a function of cluster membership, with the most abnormal patterns of connectivity evident in the generalized impairment group and no significant differences from controls in the cognitively intact group. Overall, the distinct underlying cognitive phenotypes of temporal lobe epilepsy harbor systematic relationships with clinical, sociodemographic and neuroimaging correlates. Cognitive phenotype variations in patient and familial education and ethnicity, with linked variations in total intracranial volume, raise the question of an early and persisting socioeconomic-status related neurodevelopmental impact, with additional contributions of clinical epilepsy factors (e.g., lifetime generalized seizures). The neuroimaging features of cognitive phenotype membership are most notable for disrupted large scale cortical-subcortical networks and patterns of functional connectivity with bilateral hippocampal and cerebellar atrophy. The cognitive taxonomy of temporal lobe epilepsy appears influenced by features that reflect the combined influence of socioeconomic, neurodevelopmental and neurobiological risk factors.

The Timing, Nature, and Range of Neurobehavioral Comorbidities in Juvenile Myoclonic Epilepsy.

BACKGROUND: Accumulating evidence suggests that considerable cognitive and psychiatric comorbidity is associated with juvenile myoclonic epilepsy, for which the etiology remains controversial. Our goal was to comprehensively characterize the status of multiple neurobehavioral comorbidities in youth with new- or recent-onset juvenile myoclonic epilepsy, before effects of chronic seizures and medications. METHODS: A total of 111 children aged eight to 18 years (41 new- or recent-onset juvenile myoclonic epilepsy and 70 first-degree cousin controls) underwent neuropsychological assessment (attention, executive, verbal, perceptual, speed), structured review of need for supportive academic services, parent reports of behavior and executive function (Child Behavior Checklist and Behavior Rating Inventory of Executive Function), and formal structured psychiatric interview and diagnosis (Kiddie Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version). RESULTS: Children with juvenile myoclonic epilepsy performed worse than controls across all tested cognitive domains (F(1,105) = 3.85, P < 0.01), utilized more academic services (47% versus 19%, P = 0.002), had more parent-reported behavioral problems and dysexecutive function with lower competence (P < 0.001), and had a higher prevalence of current Axis I diagnoses (attention-deficit/hyperactivity disorder, depression, and anxiety; 54% versus 23%, P = 0.001). Academic and psychiatric problems occurred antecedent to epilepsy onset compared with comparable timeline in controls. CONCLUSION: Comprehensive assessment of cognitive, academic, behavioral, and psychiatric comorbidities in youth with new- or recent-onset juvenile myoclonic epilepsy reveals a pattern of significantly increased neurobehavioral comorbidities across a broad spectrum of areas. These early evident comorbidities are of clear clinical importance with worrisome implications for future cognitive, behavioral, and social function. It is important for health care providers to avoid delays in intervention by assessing potential comorbidities early in the course of the disorder to optimize their patients' social, academic and behavioral progress.

Cognitive slowing and its underlying neurobiology in temporal lobe epilepsy.

Cognitive slowing is a known but comparatively under-investigated neuropsychological complication of the epilepsies in relation to other known cognitive comorbidities such as memory, executive function and language. Here we focus on a novel metric of processing speed, characterize its relative salience compared to other cognitive difficulties in epilepsy, and explore its underlying neurobiological correlates. Research participants included 55 patients with temporal lobe epilepsy (TLE) and 58 healthy controls from the Epilepsy Connectome Project (ECP) who were administered a battery of tests yielding 14 neuropsychological measures, including selected tests from the NIH Toolbox-Cognitive Battery, and underwent 3T MRI and resting state fMRI. TLE patients exhibited a pattern of generalized cognitive impairment with very few lateralized abnormalities. Using the neuropsychological measures, machine learning (Support Vector Machine binary classification model) classified the TLE and control groups with 74% accuracy with processing speed (NIH Toolbox Pattern Comparison Processing Speed Test) the best predictor. In TLE, slower processing speed was associated predominantly with decreased local gyrification in regions including the rostral and caudal middle frontal gyrus, inferior precentral cortex, insula, inferior parietal cortex (angular and supramarginal gyri), lateral occipital cortex, rostral anterior cingulate, and medial orbital frontal regions, as well as three small regions of the temporal lobe. Slower processing speed was also associated with decreased connectivity between the primary visual cortices in both hemispheres and the left supplementary motor area, as well as between the right parieto-occipital sulcus and right middle insular area. Overall, slowed processing speed is an important cognitive comorbidity of TLE associated with altered brain structure and connectivity.

Using Low-Frequency Oscillations to Detect Temporal Lobe Epilepsy with Machine Learning.

The National Institutes of Health-sponsored Epilepsy Connectome Project aims to characterize connectivity changes in temporal lobe epilepsy (TLE) patients. The magnetic resonance imaging protocol follows that used in the Human Connectome Project, and includes 20 min of resting-state functional magnetic resonance imaging acquired at 3T using 8-band multiband imaging. Glasser parcellation atlas was combined with the FreeSurfer subcortical regions to generate resting-state functional connectivity (RSFC), amplitude of low-frequency fluctuations (ALFFs), and fractional ALFF measures. Seven different frequency ranges such as Slow-5 (0.01-0.027 Hz) and Slow-4 (0.027-0.073 Hz) were selected to compute these measures. The goal was to train machine learning classification models to discriminate TLE patients from healthy controls, and to determine which combination of the resting state measure and frequency range produced the best classification model. The samples included age- and gender-matched groups of 60 TLE patients and 59 healthy controls. Three traditional machine learning models were trained: support vector machine, linear discriminant analysis, and naive Bayes classifier. The highest classification accuracy was obtained using RSFC measures in the Slow-4 + 5 band (0.01-0.073 Hz) as features. Leave-one-out cross-validation accuracies were ∼83%, with receiver operating characteristic area-under-the-curve reaching close to 90%. Increased connectivity from right area posterior 9-46v in TLE patients contributed to the high accuracies. With increased sample sizes in the near future, better machine learning models will be trained not only to aid the diagnosis of TLE, but also as a tool to understand this brain disorder.

Effective Connectivity Within the Default Mode Network in Left Temporal Lobe Epilepsy: Findings from the Epilepsy Connectome Project.

The Epilepsy Connectome Project examines the differences in connectomes between temporal lobe epilepsy (TLE) patients and healthy controls. Using these data, the effective connectivity of the default mode network (DMN) in patients with left TLE compared with healthy controls was investigated using spectral dynamic causal modeling (spDCM) of resting-state functional magnetic resonance imaging data. Group comparisons were made using two parametric empirical Bayes (PEB) models. The first level of each PEB model consisted of each participant's spDCM. Two different second-level models were constructed: the first comparing effective connectivity of the groups directly and the second using the Rey Auditory Verbal Learning Test (RAVLT) delayed free recall index as a covariate at the second level to assess effective connectivity controlling for the poor memory performance of left TLE patients. After an automated search over the nested parameter space and thresholding parameters at 95% posterior probability, both models revealed numerous connections in the DMN, which lead to inhibition of the left hippocampal formation. Left hippocampal formation inhibition may be an inherent result of the left temporal epileptogenic focus as memory differences were controlled for in one model and the same connections remained. An excitatory connection from the posterior cingulate cortex to the medial prefrontal cortex was found to be concomitant with left hippocampal formation inhibition in TLE patients when including RAVLT delayed free recall at the second level.