Somatic variants as a cause of drug-resistant epilepsy including mesial temporal lobe epilepsy with hippocampal sclerosis.

OBJECTIVE: The contribution of somatic variants to epilepsy has recently been demonstrated, particularly in the etiology of malformations of cortical development. The aim of this study was to determine the diagnostic yield of somatic variants in genes that have been previously associated with a somatic or germline epilepsy model, ascertained from resected brain tissue from patients with multidrug-resistant focal epilepsy. METHODS: Forty-two patients were recruited across three categories: (1) malformations of cortical development, (2) mesial temporal lobe epilepsy with hippocampal sclerosis, and (3) nonlesional focal epilepsy. Participants were subdivided based on histopathology of the resected brain. Paired blood- and brain-derived DNA samples were sequenced using high-coverage targeted next generation sequencing to high depth (585× and 1360×, respectively). Variants were identified using Genome Analysis ToolKit (GATK4) MuTect-2 and confirmed using high-coverage Amplicon-EZ sequencing. RESULTS: Sequence data on 41 patients passed quality control. Four somatic variants were validated following amplicon sequencing: within CBL, ALG13, MTOR, and FLNA. The diagnostic yield across 41 patients was 10%, 9% in mesial temporal lobe epilepsy with hippocampal sclerosis and 20% in malformations of cortical development. SIGNIFICANCE: This study provides novel insights into the etiology of mesial temporal lobe epilepsy with hippocampal sclerosis, highlighting a potential pathogenic role of somatic variants in CBL and ALG13. We also report candidate diagnostic somatic variants in FLNA in focal cortical dysplasia, while providing further insight into the importance of MTOR and related genes in focal cortical dysplasia. This work demonstrates the potential molecular diagnostic value of variants in both germline and somatic epilepsy genes.

Futureproofing Medical Education Through Scenario Analysis: Instrumental Case Study.

Developments in technology and climate change, as well as other "megatrends" are having lasting impacts in society and healthcare. A scenario analysis was conducted to explore the impact of megatrends on medical education. Three scenarios were developed for the year 2035, showing varying levels of technological integration and environmental focus. Implications for an updated curricula focus on health inequalities, digital health, and globalization effects.

Cocreating an Automated mHealth Apps Systematic Review Process With Generative AI: Design Science Research Approach.

BACKGROUND: The use of mobile devices for delivering health-related services (mobile health [mHealth]) has rapidly increased, leading to a demand for summarizing the state of the art and practice through systematic reviews. However, the systematic review process is a resource-intensive and time-consuming process. Generative artificial intelligence (AI) has emerged as a potential solution to automate tedious tasks. OBJECTIVE: This study aimed to explore the feasibility of using generative AI tools to automate time-consuming and resource-intensive tasks in a systematic review process and assess the scope and limitations of using such tools. METHODS: We used the design science research methodology. The solution proposed is to use cocreation with a generative AI, such as ChatGPT, to produce software code that automates the process of conducting systematic reviews. RESULTS: A triggering prompt was generated, and assistance from the generative AI was used to guide the steps toward developing, executing, and debugging a Python script. Errors in code were solved through conversational exchange with ChatGPT, and a tentative script was created. The code pulled the mHealth solutions from the Google Play Store and searched their descriptions for keywords that hinted toward evidence base. The results were exported to a CSV file, which was compared to the initial outputs of other similar systematic review processes. CONCLUSIONS: This study demonstrates the potential of using generative AI to automate the time-consuming process of conducting systematic reviews of mHealth apps. This approach could be particularly useful for researchers with limited coding skills. However, the study has limitations related to the design science research methodology, subjectivity bias, and the quality of the search results used to train the language model.

Multimodal Analysis of the Retinal Manifestations of Tuberous Sclerosis Complex: A Case Series.

BACKGROUND AND OBJECTIVE: We used a multi-modal imaging approach including fundus fluorescein angiography (FFA) to assess the retinal lesions in tuberous sclerosis complex (TSC) and evaluate their correlation with intracranial tuber burden on magnetic resonance imaging (MRI). PATIENTS AND METHODS: Participants with TSC underwent bilateral fundus photography, optical coherence tomography (OCT), infrared (IR) imaging, and FFA. Participants' most recent MRI brain scans were analyzed to determine intracranial tuber load. RESULTS: Nine participants were included. OCT identified all retinal astrocytic hamartoma (RAH) lesions, IR identified 75%, fundus photography identified 63%, and FFA detected just 57%. On FFA, 20% of flat-type hamartomas and all multi-nodular and transitional types were hyperfluorescent. There were significant positive correlations between the quantities of intracranial tubers and all TSC-retinal lesions (r = 0.8, P < 0.01) and all RAH lesions (r = 0.8, P = 0.01). CONCLUSIONS: A multimodal imaging-based approach with fundal photography, IR imaging, and OCT should be used to assess the retina in TSC as it may indicate the intracranial tuber burden. [Ophthalmic Surg Lasers Imaging Retina 2024;55:XX-XX.].

Blood-brain barrier disruption and sustained systemic inflammation in individuals with long COVID-associated cognitive impairment.

Vascular disruption has been implicated in coronavirus disease 2019 (COVID-19) pathogenesis and may predispose to the neurological sequelae associated with long COVID, yet it is unclear how blood-brain barrier (BBB) function is affected in these conditions. Here we show that BBB disruption is evident during acute infection and in patients with long COVID with cognitive impairment, commonly referred to as brain fog. Using dynamic contrast-enhanced magnetic resonance imaging, we show BBB disruption in patients with long COVID-associated brain fog. Transcriptomic analysis of peripheral blood mononuclear cells revealed dysregulation of the coagulation system and a dampened adaptive immune response in individuals with brain fog. Accordingly, peripheral blood mononuclear cells showed increased adhesion to human brain endothelial cells in vitro, while exposure of brain endothelial cells to serum from patients with long COVID induced expression of inflammatory markers. Together, our data suggest that sustained systemic inflammation and persistent localized BBB dysfunction is a key feature of long COVID-associated brain fog.

A WORLDWIDE ENIGMA STUDY ON EPILEPSY-RELATED GRAY AND WHITE MATTER COMPROMISE ACROSS THE ADULT LIFESPAN.

Objectives: Temporal lobe epilepsy (TLE) is commonly associated with mesiotemporal pathology and widespread alterations of grey and white matter structures. Evidence supports a progressive condition although the temporal evolution of TLE is poorly defined. This ENIGMA-Epilepsy study utilized multimodal magnetic resonance imaging (MRI) data to investigate structural alterations in TLE patients across the adult lifespan. We charted both grey and white matter changes and explored the covariance of age-related alterations in both compartments. Methods: We studied 769 TLE patients and 885 healthy controls across an age range of 17-73 years, from multiple international sites. To assess potentially non-linear lifespan changes in TLE, we harmonized data and combined median split assessments with cross-sectional sliding window analyses of grey and white matter age-related changes. Covariance analyses examined the coupling of grey and white matter lifespan curves. Results: In TLE, age was associated with a robust grey matter thickness/volume decline across a broad cortico-subcortical territory, extending beyond the mesiotemporal disease epicentre. White matter changes were also widespread across multiple tracts with peak effects in temporo-limbic fibers. While changes spanned the adult time window, changes accelerated in cortical thickness, subcortical volume, and fractional anisotropy (all decreased), and mean diffusivity (increased) after age 55 years. Covariance analyses revealed strong limbic associations between white matter tracts and subcortical structures with cortical regions. Conclusions: This study highlights the profound impact of TLE on lifespan changes in grey and white matter structures, with an acceleration of aging-related processes in later decades of life. Our findings motivate future longitudinal studies across the lifespan and emphasize the importance of prompt diagnosis as well as intervention in patients.