Temporal lobe dysfunction in late-onset epilepsy of unknown origin

Clinical, imaging, and biomarker evidence of amyloid- and tau-related neurodegeneration in late-onset epilepsy of unknown etiology

Accumulating evidence suggests amyloid and tau-related neurodegeneration may play a role in development of late-onset epilepsy of unknown etiology (LOEU). In this article, we review recent evidence that epilepsy may be an initial manifestation of an amyloidopathy or tauopathy that precedes development of Alzheimer's disease (AD). Patients with LOEU demonstrate an increased risk of cognitive decline, and patients with AD have increased prevalence of preceding epilepsy. Moreover, investigations of LOEU that use CSF biomarkers and imaging techniques have identified preclinical neurodegeneration with evidence of amyloid and tau deposition. Overall, findings to date suggest a relationship between acquired, non-lesional late-onset epilepsy and amyloid and tau-related neurodegeneration, which supports that preclinical or prodromal AD is a distinct etiology of late-onset epilepsy. We propose criteria for assessing elevated risk of developing dementia in patients with late-onset epilepsy utilizing clinical features, available imaging techniques, and biomarker measurements. Further research is needed to validate these criteria and assess optimal treatment strategies for patients with probable epileptic preclinical AD and epileptic prodromal AD.

Cognitive phenotypes in late-onset epilepsy: results from the atherosclerosis risk in communities study

Introduction

Cognitive phenotyping is a widely used approach to characterize the heterogeneity of deficits in patients with a range of neurological disorders but has only recently been applied to patients with epilepsy. In this study, we identify cognitive phenotypes in older adults with late-onset epilepsy (LOE) and examine their demographic, clinical, and vascular profiles. Further, we examine whether specific phenotypes pose an increased risk for progressive cognitive decline.

Methods

Participants were part of the Atherosclerosis Risk in Communities Study (ARIC), a prospective longitudinal community-based cohort study of 15,792 individuals initially enrolled in 1987-1989. LOE was identified from linked Centers for Medicare and Medicaid Services claims data. Ninety-one participants with LOE completed comprehensive testing either prior to or after seizure onset as part of a larger cohort in the ARIC Neurocognitive Study in either 2011-2013 or 2016-2017 (follow-up mean = 4.9 years). Cognitive phenotypes in individuals with LOE were derived by calculating test-level impairments for each participant (i.e., ≤1 SD below cognitively normal participants on measures of language, memory, and executive function/processing speed); and then assigning participants to phenotypes if they were impaired on at least two tests within a domain. The total number of impaired domains was used to determine the cognitive phenotypes (i.e., Minimal/No Impairment, Single Domain, or Multidomain).

Results

At our baseline (Visit 5), 36.3% met criteria for Minimal/No Impairment, 35% for Single Domain Impairment (with executive functioning/ processing speed impaired in 53.6%), and 28.7% for Multidomain Impairment. The Minimal/No Impairment group had higher education and occupational complexity. There were no differences in clinical or vascular risk factors across phenotypes. Of those participants with longitudinal data (Visit 6; n = 24), 62.5% declined (i.e., progressed to a more impaired phenotype) and 37.5% remained stable. Those who remained stable were more highly educated compared to those that declined.

Discussion

Our results demonstrate the presence of identifiable cognitive phenotypes in older adults with LOE. These results also highlight the high prevalence of cognitive impairments across domains, with deficits in executive function/processing speed the most common isolated impairment. We also demonstrate that higher education was associated with a Minimal/No Impairment phenotype and lower risk for cognitive decline over time.

Cognitive functioning, cerebrospinal fluid Alzheimer's disease biomarkers and cerebral glucose metabolism in late-onset epilepsy of unknown aetiology: A prospective study

Epilepsy is increasing, being more common in older adults, with more than 20% of late-onset cases with unknown aetiology (LOEU). Although epilepsy was associated with cognitive impairment, few studies evaluated the trajectories of cognitive decline in patients with LOEU. The present study aimed at assessing biomarkers of Alzheimer's disease (AD) in patients with LOEU and evaluating their cognitive performance for 12 months. For this study, 55 patients diagnosed with LOEU and 21 controls were included. Participants underwent cognitive evaluation and cerebrospinal fluid (CSF) biomarker analysis (ß-amyloid₄₂ , tau proteins) before starting anti-seizure medication and then repeated the cognitive evaluation at the 12-month follow-up. A subgroup of LOEU patients and controls also performed ¹⁸ F-fluoro-2-deoxy-D-glucose positron emission tomography (¹⁸ F-FDG PET) before starting anti-seizure medication. At baseline, LOEU patients showed lower Mini-Mental State Examination (MMSE) score, worse cognitive performance in several domains, lower β-amyloid₄₂ and higher tau proteins CSF levels than controls. Significantly reduced glucose consumption was observed in the right posterior cingulate cortex and left praecuneus areas in LOEU patients than controls, and this finding correlated with memory impairment. In the longitudinal analysis, a significant decrease in MMSE and an increase in verbal fluency scores were found in LOEU patients. These findings evidence that LOEU patients have a significant cognitive impairment, and alteration of cerebral glucose consumption and CSF AD biomarkers than controls. Moreover, they showed a progressive global cognitive decline at follow-up, although verbal fluency was preserved. Further studies are needed to better understand the pathophysiological aspects of LOEU and its association with AD.

Late-onset seizures and epilepsy: Electroclinical features suggestive of autoimmune etiology

Introduction

Late-onset epilepsy (LOE) has recently become a topic of intense research. Besides stroke, tumors, and dementia, autoimmune encephalitis (AE) has emerged as another possible cause of recurrent seizures in the elderly, and may account for a proportion of cases of LOE of unknown origin (LOEUO). This 24-h ambulatory electroencephalography (AEEG)-based study compared patients with LOEUO and AE to identify features suggestive of immune-mediated seizures in the elderly.

Materials and methods

We retrospectively reviewed 232 AEEG examinations performed in patients over 55 years with ≥6-month follow-up, and selected 21 subjects with AE and 25 subjects with LOEUO. Clinical charts and AEEG recordings were carefully analyzed.

Results

Twenty-five patients with LOEUO (12 women, mean age at onset 67.9 years) and 21 AE subjects (8 women, mean age at onset 65.7 years) were enrolled. High-frequency seizures were reported in 20/21 AE and 7/25 LOEUO cases (p < 0.00001). Focal aware seizures were more common in AE (14/21 vs. 6/25, p = 0.00058), whereas “isolated” focal-to-bilateral tonic-clonic seizures occurred in 5/25 patients with LOEUO only (p = 0.053). AE subjects reported ictal autonomic manifestations more frequently (p = 0.0033). Three-hundred-seventy and 24 seizures were recorded in 13/21 patients with AE and 3/25 patients with LOEUO, respectively (p = 0.0006). Interictal epileptiform discharges were observed in 70% of both groups, but their sleep activation was more common in AE (p = 0.06).

Conclusion

Our study shows that high-frequency focal seizures with autonomic manifestations should raise the suspicion of AE in the elderly with new-onset seizures. It also highlights the relevant contribution of AEEG, which might reduce the diagnostic delay and provide useful clues to recognize AE.

Clinical and Instrumental Characterization of Patients With Late-Onset Epilepsy

Epilepsy is classically considered a childhood disease. However, it represents the third most frequent neurological condition in the elderly, following stroke, and dementia. With the progressive aging of the general population, the number of patients with Late-Onset Epilepsy (LOE) is constantly growing, with important economic and social consequences, in particular for the more developed countries where the percentage of elderly people is higher. The most common causes of LOE are structural, mainly secondary to cerebrovascular or infectious diseases, brain tumors, trauma, and metabolic or toxic conditions. Moreover, there is a growing body of evidence linking LOE with neurodegenerative diseases, particularly Alzheimer's disease (AD). However, despite a thorough characterization, the causes of LOE remain unknown in a considerable portion of patients, thus termed as Late-Onset Epilepsy of Unknown origin (LOEU). In order to identify the possible causes of the disease, with an important impact in terms of treatment and prognosis, LOE patients should always undergo an exhaustive phenotypic characterization. In this work, we provide a detailed review of the main clinical and instrumental techniques for the adequate characterization of LOE patients in the clinical practice. This work aims to provide an easy and effective tool that supports routine activity of the clinicians facing LOE.

Cognitive Decline Risk Stratification in People with Late-Onset Epilepsy of Unknown Etiology: An Electroencephalographic Connectivity and Graph Theory Pilot Study

BACKGROUND

Although people with late onset epilepsy of unknown etiology (LOEU) are at higher risk of cognitive decline compared to the general population, we still lack affordable tools to predict and stratify their risk of dementia.

OBJECTIVE

This pilot-study investigates the potential application of electroencephalography (EEG) network small-world (SW) properties in predicting cognitive decline among patients with LOEU.

METHODS

People diagnosed with LOEU and normal cognitive examination at the time of epilepsy diagnosis were included. Cerebrospinal fluid biomarkers, brain imaging, and neuropsychological assessment were performed at the time of epilepsy diagnosis. Baseline EEG was analyzed for SW properties. Patients were followed-up over time with neuropsychological testing to define the trajectory of cognitive decline.

RESULTS

Over 5.1 years of follow-up, among 24 patients diagnosed with LOEU, 62.5% were female, mean age was 65.3 years, thirteen developed mild cognitive impairment (MCI), and four developed dementia. Patients with LOEU developing MCI had lower values of SW coefficients in the delta (p = 0.03) band and higher SW values in the alpha frequency bands (p = 0.02) compared to patients having normal cognition at last follow-up. The two separate ANOVAs, for low and alpha bands, confirmed an interaction between SW and cognitive decline at follow-up. A similar gradient was confirmed for patients developing dementia compared to those with normal cognitive function as well as to those developing MCI.

CONCLUSION

Baseline EEG analysis through SW is worth investigating as an affordable, widely available tool to stratify LOEU patients for their risk of cognitive decline.