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PURPOSE: An early genetic diagnosis can guide the time-sensitive treatment of individuals with genetic epilepsies. However, most genetic diagnoses occur long after disease onset. We aimed to identify early clinical features suggestive of genetic diagnoses in individuals with epilepsy through large-scale analysis of full-text electronic medical records (EMR). METHODS: We extracted 89 million time-stamped standardized clinical annotations using Natural Language Processing from 4,572,783 clinical notes from 32,112 individuals with childhood epilepsy, including 1,925 individuals with known or presumed genetic epilepsies. We applied these features to train random forest models to predict SCN1A-related disorders and any genetic diagnosis. RESULTS: We identified 47,774 age-dependent associations of clinical features with genetic etiologies a median of 3.6 years prior to molecular diagnosis. Across all 710 genetic etiologies identified in our cohort, neurodevelopmental differences between 6-9 months increased the likelihood of a later molecular diagnosis fivefold (P<0.0001, 95% CI=3.55-7.42). A later diagnosis of SCN1A-related disorders (AUC=0.91) or an overall positive genetic diagnosis (AUC=0.82) could be reliably predicted using random forest models. CONCLUSION: Clinical features predictive of genetic epilepsies precede molecular diagnoses by up to several years in conditions with known precision treatments. An earlier diagnosis facilitated by automated EMR analysis has the potential for earlier targeted therapeutic strategies in the genetic epilepsies.
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OBJECTIVE: To assess the possible effects of genetics on seizure outcome by estimating the familial aggregation of three outcome measures: seizure remission, history of ≥4 tonic-clonic seizures, and seizure control for individuals taking antiseizure medication. METHODS: We analyzed families containing multiple persons with epilepsy in four previously collected retrospective cohorts. Seizure remission was defined as being 5 and 10 years seizure-free at last observation. Total number of tonic-clonic seizures was dichotomized at <4 and ≥4 seizures. Seizure control in patients taking antiseizure medication was defined as no seizures for 1, 2, and 3 years. We used Bayesian generalized linear mixed-effects model (GLMM) to estimate the intraclass correlation coefficient (ICC) of the family-specific random effect, controlling for epilepsy type, age at epilepsy onset, and age at last data collection as fixed effects. We analyzed each cohort separately and performed meta-analysis using GLMMs. RESULTS: The combined cohorts included 3644 individuals with epilepsy from 1463 families. A history of ≥4 tonic-clonic seizures showed strong familial aggregation in three separate cohorts and meta-analysis (ICC .28, 95% confidence interval [CI] .21-.35, Bayes factor 8 × 1016). Meta-analyses did not reveal significant familial aggregation of seizure remission (ICC .08, 95% CI .01-.17, Bayes factor 1.46) or seizure control for individuals taking antiseizure medication (ICC .13, 95% CI 0-.35, Bayes factor 0.94), with heterogeneity among cohorts. SIGNIFICANCE: A history of ≥4 tonic-clonic seizures aggregated strongly in families, suggesting a genetic influence, whereas seizure remission and seizure control for individuals taking antiseizure medications did not aggregate consistently in families. Different seizure outcomes may have different underlying biology and risk factors. These findings should inform the future molecular genetic studies of seizure outcomes.
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Anticonvulsivantes , Convulsiones , Humanos , Femenino , Masculino , Estudios de Cohortes , Anticonvulsivantes/uso terapéutico , Convulsiones/genética , Convulsiones/tratamiento farmacológico , Adulto , Teorema de Bayes , Estudios Retrospectivos , Epilepsia/genética , Epilepsia/tratamiento farmacológico , Adulto Joven , Adolescente , Persona de Mediana Edad , Resultado del Tratamiento , NiñoRESUMEN
BACKGROUND AND AIMS: Prior to next-generation sequencing (NGS), the evaluation of a patient with neuropathy typically consisted of screening for acquired causes, followed by clinical genetic testing of PMP22, MFN2, GJB1, and MPZ in patients with a positive family history and symptom onset prior to age 50. In this study, we examined the clinical utility of NGS in a large cohort of patients analyzed in a commercial laboratory. METHODS: A cohort of 6849 adult patients underwent clinician-ordered peripheral neuropathy multigene panel testing ranging from 66 to 111 genes that included NGS and intragenic deletion/duplication analysis. RESULTS: A molecular diagnosis was identified for 8.4% of the cohort (n = 573/6849). Variants in PMP22, MFN2, GJB1, MPZ, and TTR accounted for 73.8% of molecular diagnoses. Results had potential clinical actionability for 398 (69.5%) patients. Our results suggest that 225/573 (39.3%) of molecular diagnoses and 113/398 (28.4%) of clinical interventions would have been missed if the testing approach had been restricted to older guidelines. INTERPRETATION: Our results highlight the need for expanded genetic testing guidelines that account for the increased number of genes associated with hereditary neuropathy, address the overlap of acquired and hereditary neuropathy, and provide broader access to genetic diagnosis for patients.
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Temporal encephaloceles (TE) are an under-identified, potentially intervenable cause of epilepsy. This systematic review consolidates the current data to identify the major clinical, neuroimaging, and EEG features and surgical outcomes of epilepsy associated with TE. Literature searches were carried out using MEDLINE, Embase, PsycINFO, Scopus, and Cochrane Library databases from inception to December 7, 2023. Studies were included if they described clinical, neuroimaging, EEG, or surgical data in ≥5 patients with TE and epilepsy. Of 562 studies identified in the search, 24 met the eligibility criteria, reporting 423 unique patients with both epilepsy and TE. Compared to epilepsy patients without TE, those with TE had a higher mean age of seizure onset and were less likely to have a history of febrile seizures. Seizure semiologies were variable, but primarily mirrored temporal lobe onset patterns. Epilepsy patients with TE had a higher likelihood of having clinical or radiographic features of idiopathic intracranial hypertension (IIH) than those without. Brain MRI may show ipsilateral mesial temporal sclerosis (16 %). CT scans of the skull base usually revealed bony defects near the TE (90 %). Brain PET scans primarily showed ipsilateral temporal lobe hypometabolism (80 %), mostly in the anterior temporal lobe (67 %). Scalp EEG mostly lateralized ipsilateral to the implicated TE (92 % seizure onset) and localized to the temporal lobe (96 %). Intracranial EEG revealed seizure onset near the TE (11 of 12 cases including TE-adjacent electrodes) with variable timing of spread to the ipsilateral hippocampus. After surgical treatment of the TE, the rate of Engel I or ILAE 1 outcomes at one year was 75 % for lesionectomy, 85 % for anterior temporal lobectomy (ATL), and 80 % for ATL with amygdalohippocampectomy. Further studies are needed to better elucidate the relationship between IIH, TE, and epilepsy, improve the identification of TE, and optimize surgical interventions.
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BACKGROUND: Visual impairment (VI) is associated with dementia and other neuropsychiatric outcomes, but previous studies have not considered genetic sources of confounding or effect modification. METHODS: We analysed data from the Health and Retirement Study, an ongoing nationally representative survey of older US adults, a subset of whom underwent genetic testing from 2006 to 2012 (n = 13 465). Using discrete time proportional hazards models and generalised estimating equations, we measured the association between VI and dementia, depression and hallucinations adjusting for demographics and comorbidities, ancestry-specific principal components and polygenic risk scores (PRS) for Alzheimer's disease, major depressive disorder or schizophrenia. Effect modification was assessed using VI-PRS interaction terms and stratified analyses. RESULTS: VI was associated with dementia, depression and hallucinations after adjusting polygenic risk and other confounders. There was no VI-PRS interaction for dementia or depression. However, the association between VI and hallucinations varied by genetic risk of schizophrenia. Within the bottom four quintiles of schizophrenia PRS, VI was not associated with hallucinations among White (OR 1.16, 95% CI: 0.87-1.55) or Black participants (OR 0.96, 95% CI: 0.49-1.89). In contrast, VI was strongly associated with hallucinations among White (OR 2.08, 95% CI: 1.17-3.71) and Black (OR 10.63, 95% CI: 1.74-65.03) participants in the top quintile of schizophrenia PRS. CONCLUSIONS: The association between VI and neuropsychiatric outcomes is not explained by shared genetic risk factors, and there is a significant interaction between VI and polygenic risk of hallucinations in older adults.
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Demencia , Predisposición Genética a la Enfermedad , Alucinaciones , Trastornos Psicóticos , Trastornos de la Visión , Humanos , Masculino , Femenino , Anciano , Demencia/genética , Demencia/epidemiología , Demencia/psicología , Demencia/diagnóstico , Factores de Riesgo , Estados Unidos/epidemiología , Trastornos de la Visión/genética , Trastornos de la Visión/epidemiología , Trastornos de la Visión/psicología , Alucinaciones/genética , Alucinaciones/epidemiología , Alucinaciones/psicología , Alucinaciones/diagnóstico , Trastornos Psicóticos/genética , Trastornos Psicóticos/epidemiología , Trastornos Psicóticos/psicología , Herencia Multifactorial , Medición de Riesgo , Factores de Edad , Persona de Mediana Edad , Anciano de 80 o más Años , Esquizofrenia/genética , Esquizofrenia/epidemiologíaRESUMEN
OBJECTIVE: Large-language models (LLMs) can potentially revolutionize health care delivery and research, but risk propagating existing biases or introducing new ones. In epilepsy, social determinants of health are associated with disparities in care access, but their impact on seizure outcomes among those with access remains unclear. Here we (1) evaluated our validated, epilepsy-specific LLM for intrinsic bias, and (2) used LLM-extracted seizure outcomes to determine if different demographic groups have different seizure outcomes. MATERIALS AND METHODS: We tested our LLM for differences and equivalences in prediction accuracy and confidence across demographic groups defined by race, ethnicity, sex, income, and health insurance, using manually annotated notes. Next, we used LLM-classified seizure freedom at each office visit to test for demographic outcome disparities, using univariable and multivariable analyses. RESULTS: We analyzed 84 675 clinic visits from 25 612 unique patients seen at our epilepsy center. We found little evidence of bias in the prediction accuracy or confidence of outcome classifications across demographic groups. Multivariable analysis indicated worse seizure outcomes for female patients (OR 1.33, P ≤ .001), those with public insurance (OR 1.53, P ≤ .001), and those from lower-income zip codes (OR ≥1.22, P ≤ .007). Black patients had worse outcomes than White patients in univariable but not multivariable analysis (OR 1.03, P = .66). CONCLUSION: We found little evidence that our LLM was intrinsically biased against any demographic group. Seizure freedom extracted by LLM revealed disparities in seizure outcomes across several demographic groups. These findings quantify the critical need to reduce disparities in the care of people with epilepsy.
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Epilepsia , Disparidades en Atención de Salud , Convulsiones , Humanos , Femenino , Masculino , Adulto , Persona de Mediana Edad , Procesamiento de Lenguaje Natural , Determinantes Sociales de la Salud , Adolescente , Adulto Joven , LenguajeRESUMEN
BACKGROUND: Germline genetic testing is recommended for an increasing number of conditions with underlying genetic etiologies, the results of which impact medical management. However, genetic testing is underutilized in clinics due to system, clinician, and patient level barriers. Behavioral economics provides a framework to create implementation strategies, such as nudges, to address these multi-level barriers and increase the uptake of genetic testing for conditions where the results impact medical management. METHODS: Patients meeting eligibility for germline genetic testing for a group of conditions will be identified using electronic phenotyping algorithms. A pragmatic, type 3 hybrid cluster randomization study will test nudges to patients and/or clinicians, or neither. Clinicians who receive nudges will be prompted to either refer their patient to genetics or order genetic testing themselves. We will use rapid cycle approaches informed by clinician and patient experiences, health equity, and behavioral economics to optimize these nudges before trial initiation. The primary implementation outcome is uptake of germline genetic testing for the pre-selected health conditions. Patient data collected through the electronic health record (e.g. demographics, geocoded address) will be examined as moderators of the effect of nudges. DISCUSSION: This study will be one of the first randomized trials to examine the effects of patient- and clinician-directed nudges informed by behavioral economics on uptake of genetic testing. The pragmatic design will facilitate a large and diverse patient sample, allow for the assessment of genetic testing uptake, and provide comparison of the effect of different nudge combinations. This trial also involves optimization of patient identification, test selection, ordering, and result reporting in an electronic health record-based infrastructure to further address clinician-level barriers to utilizing genomic medicine. The findings may help determine the impact of low-cost, sustainable implementation strategies that can be integrated into health care systems to improve the use of genomic medicine. TRIAL REGISTRATION: ClinicalTrials.gov. NCT06377033. Registered on March 31, 2024. https://clinicaltrials.gov/study/NCT06377033?term=NCT06377033&rank=1.
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Pruebas Genéticas , Genómica , Humanos , Pruebas Genéticas/métodos , Genómica/métodos , Registros Electrónicos de Salud , Economía del Comportamiento , Ciencia de la ImplementaciónRESUMEN
BACKGROUND AND OBJECTIVES: Genetic testing is now the standard of care for many neurologic conditions. Health care disparities are unfortunately widespread in the US health care system, but disparities in the utilization of genetic testing for neurologic conditions have not been studied. We tested the hypothesis that access to and results of genetic testing vary according to race, ethnicity, sex, socioeconomic status, and insurance status for adults with neurologic conditions. METHODS: We analyzed retrospective data from patients who underwent genetic evaluation and testing through our institution's neurogenetics program. We tested for differences between demographic groups in 3 steps of a genetic evaluation pathway: (1) attending a neurogenetic evaluation, (2) completing genetic testing, and (3) receiving a diagnostic result. We compared patients on this genetic evaluation pathway with the population of all neurology outpatients at our institution, using univariate and multivariable logistic regression analyses. RESULTS: Between 2015 and 2022, a total of 128,440 patients were seen in our outpatient neurology clinics and 2,540 patients underwent genetic evaluation. Black patients were less than half as likely as White patients to be evaluated (odds ratio [OR] 0.49, p < 0.001), and this disparity was similar after controlling for other demographic factors in multivariable analysis. Patients from the least wealthy quartile of zip codes were also less likely to be evaluated (OR 0.67, p < 0.001). Among patients who underwent evaluation, there were no disparities in the likelihood of completing genetic testing, nor in the likelihood of a diagnostic result after adjusting for age. Analyses restricted to specific indications for genetic testing supported these findings. DISCUSSION: We observed unequal utilization of our clinical neurogenetics program for patients from marginalized and minoritized demographic groups, especially Black patients. Among patients who do undergo evaluation, all groups benefit similarly from genetic testing when it is indicated. Understanding and removing barriers to accessing genetic testing will be essential to health care equity and optimal care for all patients with neurologic disorders.