Familial aggregation of seizure outcomes in four familial epilepsy cohorts.

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.

Use of Recommended Neurodiagnostic Evaluation Among Patients With Drug-Resistant Epilepsy.

Importance: Interdisciplinary practice parameters recommend that patients with drug-resistant epilepsy (DRE) undergo comprehensive neurodiagnostic evaluation, including presurgical assessment. Reporting from specialized centers suggests long delays to referral and underuse of surgery; however, longitudinal data are limited to characterize neurodiagnostic evaluation among patients with DRE in more diverse US settings and populations. Objective: To examine the rate and factors associated with neurodiagnostic studies and comprehensive evaluation among patients with DRE within 3 US cohorts. Design, Setting, and Participants: A retrospective cross-sectional study was conducted using the Observational Medical Outcomes Partnership Common Data Model including US multistate Medicaid data, commercial claims data, and Columbia University Medical Center (CUMC) electronic health record data. Patients meeting a validated computable phenotype algorithm for DRE between January 1, 2015, and April 1, 2020, were included. No eligible participants were excluded. Exposure: Demographic and clinical variables were queried. Main Outcomes and Measures: The proportion of patients receiving a composite proxy for comprehensive neurodiagnostic evaluation, including (1) magnetic resonance or other advanced brain imaging, (2) video electroencephalography, and (3) neuropsychological evaluation within 2 years of meeting the inclusion criteria. Results: A total of 33 542 patients with DRE were included in the Medicaid cohort, 22 496 in the commercial insurance cohort, and 2741 in the CUMC database. A total of 31 516 patients (53.6%) were women. The proportion of patients meeting the comprehensive evaluation main outcome in the Medicaid cohort was 4.5% (n = 1520); in the commercial insurance cohort, 8.0% (n = 1796); and in the CUMC cohort, 14.3% (n = 393). Video electroencephalography (24.9% Medicaid, 28.4% commercial, 63.2% CUMC) and magnetic resonance imaging of the brain (35.6% Medicaid, 43.4% commercial, 52.6% CUMC) were performed more regularly than neuropsychological evaluation (13.0% Medicaid, 16.6% commercial, 19.2% CUMC) or advanced imaging (3.2% Medicaid, 5.4% commercial, 13.1% CUMC). Factors independently associated with greater odds of evaluation across all 3 data sets included the number of inpatient and outpatient nonemergency epilepsy visits and focal rather than generalized epilepsy. Conclusions and Relevance: The findings of this study suggest there is a gap in the use of diagnostic studies to evaluate patients with DRE. Care setting, insurance type, frequency of nonemergency visits, and epilepsy type are all associated with evaluation. A common data model can be used to measure adherence with best practices across a variety of observational data sources.

Risk factors for developing both primary breast and primary ovarian cancer: A systematic review.

OBJECTIVE: Women with breast cancer have an increased risk of primary ovarian cancer (BR→OV), and women with ovarian cancer have an increased risk of primary breast cancer (OV→BR). This systematic review summarizes risk factors for developing BR→OV and OV→BR. METHODS: We searched PubMed and Embase until June 2022. RESULTS: We identified 23 articles meeting our inclusion criteria. Studies observed a lower risk of BR→OV for Black versus White women, alcohol consumption, radiotherapy and hormone therapy, BRCA2 versus BRCA1, and ER/PR positive versus negative breast tumors, and a higher risk with family history of breast/ovarian cancer, triple negative versus luminal breast cancer, and higher grade breast tumors. There was an increased risk of OV→BR with family history of cancer. CONCLUSIONS: Tumor characteristics, and genetic and familial factors are associated with risk of BR→OV and OV→BR. These results could aid clinicians in decision-making for breast and ovarian cancer patients, including risk-reducing strategies.

Association of antiseizure medication adherence with illness perceptions in adults with epilepsy.

OBJECTIVE: We assessed the relationship of epilepsy illness perceptions to antiseizure medication (ASM) adherence. METHODS: Surveys were completed by 644 adult patients with epilepsy of unknown cause. We used the Morisky Medication Adherence Scale-8 (MMAS-8) to define "high" adherence (score = 8) and "low-medium" adherence (score < 8). We evaluated epilepsy illness perceptions using seven items from the Brief Illness Perception Questionnaire (BIPQ), each scored from 0-10, measuring participants' views of the overall effect of epilepsy on their lives, how long it would last, how much control they had over their epilepsy, the effectiveness of their treatment, level of concern about epilepsy, level of understanding of epilepsy, and emotional impact of epilepsy. We investigated the association of each BIPQ item with medication adherence using logistic regression models that controlled for potential confounders (age, race/ethnicity, income, and time since the last seizure). RESULTS: One hundred forty-nine patients (23%) gave responses indicating high adherence. In the adjusted models, for each 1-unit increase in participants' BIPQ item scores, the odds of high adherence increased by 17% for understanding of their epilepsy (OR = 1.17, 95% CI 1.07-1.27, p < 0.001), decreased by 11% for overall life impact of epilepsy (OR = 0.89, 95% CI 0.82-0.97, p = 0.01) and decreased by 6% for emotional impact of epilepsy (OR = 0.94, 95% CI 0.86-0.99, p = 0.03). No other illness perception was associated with high adherence. Depression, anxiety, and stigma mediated the inverse relationships of high adherence to the overall life impact of epilepsy and the emotional impact of epilepsy. These measures did not mediate the relationship of high adherence to the perceived understanding of epilepsy. CONCLUSION: These results indicate that a greater perceived understanding of epilepsy is independently associated with high ASM adherence. Programs aimed at improving patients' understanding of their epilepsy may help improve medication adherence.

Knowledge and beliefs about epilepsy genetics among Hispanic and non-Hispanic patients.

OBJECTIVE: Hispanics continue to face challenges when trying to access health care, including epilepsy care and genetic-related health care services. This study examined epilepsy genetic knowledge and beliefs in this historically underserved population. METHODS: Questionnaires were completed by 641 adults with epilepsy without identified cause, of whom 122 self-identified as Hispanic or Latino and 519 as non-Hispanic. Participants were asked about their views on the contribution of genetics to the cause of their epilepsy ("genetic attribution"), optimism for advancements in epilepsy genetic research ("genetic optimism"), basic genetic knowledge, and epilepsy-specific genetic knowledge. Generalized linear models were used to compare the two groups in the means of quantitative measures and percents answered correctly for individual genetic knowledge items. Analyses were adjusted for age, sex, education, religion, family history of epilepsy, and time since last seizure. RESULTS: Hispanics did not differ from non-Hispanics in genetic attribution, genetic optimism, or number of six basic genetic knowledge items answered correctly. The number of nine epilepsy-specific genetic knowledge items answered correctly was significantly lower for Hispanics than non-Hispanics (adjusted mean = 6.0 vs. 6.7, p < .001). After adjustment for education and other potential mediators, the proportion answered correctly was significantly lower for Hispanics than non-Hispanics for only two items related to family history and penetrance of epilepsy-related genes. Only 54% of Hispanics and 61% of non-Hispanics answered correctly that "If a person has epilepsy, his or her relatives have an increased chance of getting epilepsy." SIGNIFICANCE: Despite large differences in sociodemographic variables including education, most attitudes and beliefs about genetics were similar in Hispanics and non-Hispanics. Epilepsy-specific genetic knowledge was lower among Hispanics than non-Hispanics, and this difference was mostly mediated by differences in demographic variables. Genetic counseling should address key concepts related to epilepsy genetics to ensure they are well understood by both Hispanic and non-Hispanic patients.

Whole genome sequencing identifies candidate genes for familial essential tremor and reveals biological pathways implicated in essential tremor aetiology.

BACKGROUND: Essential tremor (ET), one of the most common neurological disorders, has a phenotypically heterogeneous presentation characterized by bilateral kinetic tremor of the arms and, in some patients, tremor involving other body regions (e.g., head, voice). Genetic studies suggest that ET is genetically heterogeneous. METHODS: We analyzed whole genome sequence data (WGS) generated on 104 multi-generational white families with European ancestry affected by ET. Genome-wide parametric linkage and association scans were analyzed using adjusted logistic regression models through the application of the Pseudomarker software. To investigate the additional contribution of rare variants in familial ET, we also performed an aggregate variant non-parametric linkage (NPL) analysis using the collapsed haplotype method implemented in CHP-NPL software. FINDINGS: Parametric linkage analysis of common variants identified several loci with significant evidence of linkage (HLOD ≥3.6). Among the gene regions within the strongest ET linkage peaks were BTC (4q13.3, HLOD=4.53), N6AMT1 (21q21.3, HLOD=4.31), PCDH9 (13q21.32, HLOD=4.21), EYA1 (8q13.3, HLOD=4.04), RBFOX1 (16p13.3, HLOD=4.02), MAPT (17q21.31, HLOD=3.99) and SCARB2 (4q21.1, HLOD=3.65). CHP-NPL analysis identified fifteen additional genes with evidence of significant linkage (LOD ≥3.8). These genes include TUBB2A, VPS33B, STEAP1B, SPINK5, ZRANB1, TBC1D3C, PDPR, NPY4R, ETS2, ZNF736, SPATA21, ARL17A, PZP, BLK and CCDC94. In one ET family contributing to the linkage peak on chromosome 16p13.3, we identified a likely pathogenic heterozygous canonical splice acceptor variant in exon 2 of RBFOX1 (ENST00000547372; c.4-2A>G), that co-segregated with the ET phenotype in the family. INTERPRETATION: Linkage and association analyses of WGS identified several novel ET candidate genes, which are implicated in four major pathways that include 1) the epidermal growth factor receptor-phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha-AKT serine/threonine kinase 1 (EGFR-PI3K-AKT) and Mitogen-activated protein Kinase 1 (ERK) pathways, 2) Reactive oxygen species (ROS) and DNA repair, 3) gamma-aminobutyric acid-ergic (GABAergic) system and 4) RNA binding and regulation of RNA processes. Our study provides evidence for a possible overlap in the genetic architecture of ET, neurological disease, cancer and aging. The genes and pathways identified can be prioritized in future genetic and functional studies. FUNDING: National Institutes of Health, NINDS, NS073872 (USA) and NIA AG058131(USA).

Identification of patients with drug-resistant epilepsy in electronic medical record data using the Observational Medical Outcomes Partnership Common Data Model.

OBJECTIVE: More than one third of appropriately treated patients with epilepsy have continued seizures despite two or more medication trials, meeting criteria for drug-resistant epilepsy (DRE). Accurate and reliable identification of patients with DRE in observational data would enable large-scale, real-world comparative effectiveness research and improve access to specialized epilepsy care. In the present study, we aim to develop and compare the performance of computable phenotypes for DRE using the Observational Medical Outcomes Partnership (OMOP) Common Data Model. METHODS: We randomly sampled 600 patients from our academic medical center's electronic health record (EHR)-derived OMOP database meeting previously validated criteria for epilepsy (January 2015-August 2021). Two reviewers manually classified patients as having DRE, drug-responsive epilepsy, undefined drug responsiveness, or no epilepsy as of the last EHR encounter in the study period based on consensus definitions. Demographic characteristics and codes for diagnoses, antiseizure medications (ASMs), and procedures were tested for association with DRE. Algorithms combining permutations of these factors were applied to calculate sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for DRE. The F1 score was used to compare overall performance. RESULTS: Among 412 patients with source record-confirmed epilepsy, 62 (15.0%) had DRE, 163 (39.6%) had drug-responsive epilepsy, 124 (30.0%) had undefined drug responsiveness, and 63 (15.3%) had insufficient records. The best performing phenotype for DRE in terms of the F1 score was the presence of ≥1 intractable epilepsy code and ≥2 unique non-gabapentinoid ASM exposures each with ≥90-day drug era (sensitivity = .661, specificity = .937, PPV = .594, NPV = .952, F1 score = .626). Several phenotypes achieved higher sensitivity at the expense of specificity and vice versa. SIGNIFICANCE: OMOP algorithms can identify DRE in EHR-derived data with varying tradeoffs between sensitivity and specificity. These computable phenotypes can be applied across the largest international network of standardized clinical databases for further validation, reproducible observational research, and improving access to appropriate care.

Reproduction and genetic causal attribution of epilepsy.

OBJECTIVE: This study addresses the contribution of genetics-related concerns to reduced childbearing among people with epilepsy. METHODS: Surveys were completed by 606 adult patients with epilepsy of unknown cause at our medical center. Poisson regression analysis was used to assess the relations of number of offspring to: (1) genetic attribution (GA: participants' belief that genetics was a cause of their epilepsy), assessed via a novel scale developed from four survey items (Cronbach's alpha = .89), (2) participants' estimates of epilepsy risk in the child of a parent with epilepsy (1%, 5%-10%, 25%, and 50%-100%), and (3) participants' reports of the influence on their reproductive decisions of "the chance of having a child with epilepsy" (none/weak/moderate, strong/very strong). Analyses were adjusted for age, education, race/ethnicity, religion, type of epilepsy (generalized, focal, and both/unclassifiable), and age at epilepsy onset (<10, 10-19, and ≥20 years). RESULTS: Among participants 18-45 years of age, the number of offspring decreased significantly with increasing GA (highest vs lowest GA quartile rate ratio [RR] = .5, p < .001), and increasing estimated epilepsy risk in offspring (with 5%-10% as referent because it is closest to the true value, RR for 25%: .7, p = .05; RR for 50%-100%: .6, p = .03). Number of offspring was not related to the reported influence of "the chance of having a child with epilepsy" on reproductive decisions. Among participants >45 years of age, the number of offspring did not differ significantly according to GA quartile or estimated offspring epilepsy risk. However, those reporting a strong/very strong influence on their reproductive decisions of "the chance of having a child with epilepsy" had only 60% as many offspring as others. SIGNIFICANCE: These findings suggest that overestimating the risk of epilepsy in offspring can have important consequences for people with epilepsy. Patient and provider education about recurrence risks and genetic testing options to clarify risks are critical, given their potential influence on reproductive decisions.

Common risk variants for epilepsy are enriched in families previously targeted for rare monogenic variant discovery.

BACKGROUND: The epilepsies are highly heritable conditions that commonly follow complex inheritance. While monogenic causes have been identified in rare familial epilepsies, most familial epilepsies remain unsolved. We aimed to determine (1) whether common genetic variation contributes to familial epilepsy risk, and (2) whether that genetic risk is enriched in familial compared with non-familial (sporadic) epilepsies. METHODS: Using common variants derived from the largest epilepsy genome-wide association study, we calculated polygenic risk scores (PRS) for patients with familial epilepsy (n = 1,818 from 1,181 families), their unaffected relatives (n = 771), sporadic patients (n = 1,182), and population controls (n = 15,929). We also calculated separate PRS for genetic generalised epilepsy (GGE) and focal epilepsy. Statistical analyses used mixed-effects regression models to account for familial relatedness, sex, and ancestry. FINDINGS: Patients with familial epilepsies had higher epilepsy PRS compared to population controls (OR 1·20, padj = 5×10-9), sporadic patients (OR 1·11, padj = 0.008), and their own unaffected relatives (OR 1·12, padj = 0.01). The top 1% of the PRS distribution was enriched 3.8-fold for individuals with familial epilepsy when compared to the lowest decile (padj = 5×10-11). Familial PRS enrichment was consistent across epilepsy type; overall, polygenic risk was greatest for the GGE clinical group. There was no significant PRS difference in familial cases with established rare variant genetic etiologies compared to unsolved familial cases. INTERPRETATION: The aggregate effects of common genetic variants, measured as polygenic risk scores, play an important role in explaining why some families develop epilepsy, why specific family members are affected while their relatives are not, and why families manifest specific epilepsy types. Polygenic risk contributes to the complex inheritance of the epilepsies, including in individuals with a known genetic etiology. FUNDING: National Health and Medical Research Council of Australia, National Institutes of Health, American Academy of Neurology, Thomas B and Jeannette E Laws McCabe Fund, Mirowski Family Foundation.

Patient characteristics and antiseizure medication pathways in newly diagnosed epilepsy: Feasibility and pilot results using the common data model in a single-center electronic medical record database.

INTRODUCTION: Efforts to characterize variability in epilepsy treatment pathways are limited by the large number of possible antiseizure medication (ASM) regimens and sequences, heterogeneity of patients, and challenges of measuring confounding variables and outcomes across institutions. The Observational Health Data Science and Informatics (OHDSI) collaborative is an international data network representing over 1 billion patient records using common data standards. However, few studies have applied OHDSI's Common Data Model (CDM) to the population with epilepsy and none have validated relevant concepts. The goals of this study were to demonstrate the feasibility of characterizing adult patients with epilepsy and ASM treatment pathways using the CDM in an electronic health record (EHR)-derived database. METHODS: We validated a phenotype algorithm for epilepsy in adults using the CDM in an EHR-derived database (2001-2020) against source records and a prospectively maintained database of patients with confirmed epilepsy. We obtained the frequency of all antecedent conditions and procedures for patients meeting the epilepsy phenotype criteria and characterized ASM exposure sequences over time and by age and sex. RESULTS: The phenotype algorithm identified epilepsy with 73.0-85.0% positive predictive value and 86.3% sensitivity. Many patients had neurologic conditions and diagnoses antecedent to meeting epilepsy criteria. Levetiracetam incrementally replaced phenytoin as the most common first-line agent, but significant heterogeneity remained, particularly in second-line and subsequent agents. Drug sequences included up to 8 unique ingredients and a total of 1,235 unique pathways were observed. CONCLUSIONS: Despite the availability of additional ASMs in the last 2 decades and accumulated guidelines and evidence, ASM use varies significantly in practice, particularly for second-line and subsequent agents. Multi-center OHDSI studies have the potential to better characterize the full extent of variability and support observational comparative effectiveness research, but additional work is needed to validate covariates and outcomes.

Reproductive decision-making in families containing multiple individuals with epilepsy.

OBJECTIVE: This study evaluated factors influencing reproductive decision-making in families containing multiple individuals with epilepsy. METHODS: One hundred forty-nine adults with epilepsy and 149 adult biological relatives without epilepsy from families containing multiple affected individuals completed a self-administered questionnaire. Participants answered questions regarding their belief in a genetic cause of epilepsy (genetic attribution) and estimated risk of epilepsy in offspring of an affected person. Participants rated factors for their influence on their reproductive plans, with responses ranging from "much more likely" to "much less likely" to want to have a child. Those with epilepsy were asked, "Do you think you would have wanted more (or any) children if you had not had epilepsy?" RESULTS: Participants with epilepsy had fewer offspring than their unaffected relatives (mean = 1.2 vs. 1.9, p = .002), and this difference persisted among persons who had been married. Estimates of risk of epilepsy in offspring of an affected parent were higher among participants with epilepsy than among relatives without epilepsy (mean = 27.2 vs. 19.6, p = .002). Nineteen percent of participants with epilepsy responded that they would have wanted more children if they had not had epilepsy. Twenty-five percent of participants with epilepsy responded that "the chance of having a child with epilepsy" or "having epilepsy in your family" made them less likely to want to have a child. Having these genetic concerns was significantly associated with greater genetic attribution and estimated risk of epilepsy in offspring of an affected parent. SIGNIFICANCE: People with epilepsy have fewer children than their biological relatives without epilepsy. Beliefs about genetic causes of epilepsy contribute to concerns and decisions to limit childbearing. These beliefs should be addressed in genetic counseling to ensure that true risks to offspring and reproductive options are well understood.

Mixed Motor Disorder: Essential Tremor Families With Heterogeneous Motor Phenomenology.

BACKGROUND AND OBJECTIVES: Essential tremor (ET) is one of the most prevalent movement disorders. Because ET is so common, individuals with other neurologic disorders may also have ET. There is evidence, however, that the cooccurrence of ET with Parkinson disease (PD) and/or dystonia is not merely a chance cooccurrence. We have observed combinations of these 3 movement disorders within individuals and across individuals within families containing multiple individuals with ET. This observation has a number of implications. Our objective is to present 4 ET families in whom motor phenomenology was heterogeneous and discuss the implications of this finding. METHODS: ET cases and their relatives were enrolled in the Family Study of Essential Tremor (2015-present). Phenotyping was performed by a senior movement disorders neurologist based on neurologic examination. RESULTS: We present 4 families, including 14 affected individuals, among whom assigned diagnoses were ET, PD, ET + PD, and ET + dystonia. In those with ET and another movement disorder, the predominant and earliest phenotype was ET. DISCUSSION: There are assortments of these 3 involuntary motor disorders, ET, dystonia, and PD, both within individuals and in different individuals within ET families. This observation has mechanistic implications. Furthermore, we believe that the concept of the mixed motor disorder should enter into and inform the clinical dialogue. In assigning diagnoses, clinicians are swayed by family history information, and they should be prepared to observe a mix of different motor disorders to manifest within particular families.

Epilepsy risk in offspring of affected parents; a cohort study of the "maternal effect" in epilepsy.

OBJECTIVE: To assess whether the risk of epilepsy is higher in offspring of mothers with epilepsy than in offspring of fathers with epilepsy. METHODS: In a prospective population-based register study, we considered all singletons born in Denmark between 1981 and 2016 (N = 1,754,742). From the Danish National Patient Register since 1977, we identified epilepsy diagnoses in all study participants and their family members. Cox regression models were used to estimate hazard ratios (HRs) and corresponding 95% confidence intervals (CI), adjusted for relevant confounders. RESULTS: We included 1,754,742 individuals contributing > 30 million person-years of follow-up. The incidence rate of epilepsy in offspring of unaffected parents was 78.8 (95% CI: 77.8-79.8) per 100,000 person-years, while the corresponding rate in offspring with an affected father was 172 per 100,000 person-years (95% CI: 156-187) and in offspring with an affected mother was 260 per 100,000 person-years (95% CI: 243-277). Having an affected mother was associated with a 1.45-fold (95% CI: 1.30-1.63) higher risk of epilepsy in the offspring, compared to having an affected father. This maternal effect was found both in male (HR = 1.39, 95% CI: 1.19-1.62) and female offspring (HR = 1.53, 95% CI: 1.30-1.80), and across various ages at onset in the offspring. The maternal effect was also found in familial epilepsies (i.e. where the affected parent had an affected sibling; HR = 1.50, 95% CI: 1.04-2.16). INTERPRETATION: We found a clear maternal effect on offspring risk of epilepsy in this nationwide cohort study.

Generalized, focal, and combined epilepsies in families: New evidence for distinct genetic factors.

OBJECTIVE: To determine the roles of shared and distinct genetic influences on generalized and focal epilepsy operating in individuals who manifest features of both types (combined epilepsies), and in families manifesting both generalized and focal epilepsies in separate individuals (mixed families). METHODS: We analyzed the deeply phenotyped Epi4K cohort of multiplex families (≥3 affected individuals per family) using methods that quantify the aggregation of phenotypes within families and the relatedness of individuals with different phenotypes within family pedigrees. RESULTS: The cohort included 281 families containing 1021 individuals with generalized (n = 484), focal (304), combined (51), or unclassified (182) epilepsies. The odds of combined epilepsy was higher in relatives of participants with combined epilepsy than in relatives of those with other epilepsy types (odds ratio [OR] 5.2, 95% confidence interval [CI] 1.7-16.1, P = .004). Individuals with combined epilepsy co-occurred in families more often than expected by chance (P = .03). Within mixed families, individuals with each type of epilepsy were more closely related to relatives with the same type than to relatives with other types (P < .001). SIGNIFICANCE: These findings suggest that distinct genetic influences underlie the recently recognized entity of combined epilepsies, just as generalized epilepsies and focal epilepsies each have distinct genetic influences. Mixed families may in part reflect chance co-occurrence of these distinct genetic influences. These conclusions have important implications for molecular genetic studies aimed at identifying genetic determinants of the epilepsies.

Impact of patient education videos on genetic counseling outcomes after exome sequencing.

OBJECTIVE: Growing use of clinical exome sequencing (CES) has led to an increased burden of genomic education. Self-guided educational tools can minimize the educational burden for genetic counselors (GCs). The effectiveness of these tools must be evaluated. METHODS: Parents of patients offered CES were randomized to watch educational videos before their visit or to receive routine care. Parents and GCs were surveyed about their experiences following the sessions. The responses of the video (n = 102) and no-video (n = 105) groups were compared. RESULTS: GCs reported no significant differences between parents in the video and no-video groups on genetics knowledge or CES knowledge. In contrast, parents' scores on genetics knowledge questions were lower in the video than no-video group (p = 0.007). Most parents reported the videos were informative, and the groups did not differ in satisfaction with GCs or decisions to have CES. CONCLUSION: GCs and parents perceived the videos to be beneficial. However, lower scores on genetics knowledge questions highlight the need for careful development of educational tools. PRACTICE IMPLICATIONS: Educational tools should be developed and assessed for effectiveness with the input of all stakeholders before widespread implementation. Better measures of the effectiveness of these educational tools are needed.

The "maternal effect" on epilepsy risk: Analysis of familial epilepsies and reassessment of prior evidence.

OBJECTIVE: Previous studies have observed that epilepsy risk is higher among offspring of affected women than offspring of affected men. We tested whether this "maternal effect" was present in familial epilepsies, which are enriched for genetic factors that contribute to epilepsy risk. METHODS: We assessed evidence of a maternal effect in a cohort of families containing ≥3 persons with epilepsy using 3 methods: (1) "downward-looking" analysis, comparing the rate of epilepsy in offspring of affected women versus men; (2) "upward-looking" analysis, comparing the rate of epilepsy among mothers versus fathers of affected individuals; and (3) lineage analysis, comparing the proportion of affected individuals with family history of epilepsy on the maternal versus paternal side. RESULTS: Downward-looking analysis revealed no difference in epilepsy rates among offspring of affected mothers versus fathers (prevalence ratio = 1.0, 95% confidence interval [CI] = 0.8-1.2). Upward-looking analysis revealed more affected mothers than affected fathers; this effect was similar for affected and unaffected sibships (odds ratio = 0.8, 95% CI = 0.5-1.2) and was explained by a combination of differential fertility and participation rates. Lineage analysis revealed no significant difference in the likelihood of maternal versus paternal family history of epilepsy. INTERPRETATION: We found no evidence of a maternal effect on epilepsy risk in this familial epilepsy cohort. Confounding sex imbalances can create the appearance of a maternal effect in upward-looking analyses and may have impacted prior studies. We discuss possible explanations for the lack of evidence, in familial epilepsies, of the maternal effect observed in population-based studies. ANN NEUROL 2020;87:132-138.

Genetic attribution and perceived impact of epilepsy in multiplex epilepsy families.

OBJECTIVE: Studies have found that affected individuals who believe the cause of their disorder is genetic may react in various ways, including optimism for improved treatments and pessimism due to perceived permanence of the condition. This study assessed the psychosocial impact of genetic attribution among people with epilepsy. METHODS: Study participants were 165 persons with epilepsy from multiplex epilepsy families who completed a self-administered survey. Psychosocial impact of epilepsy was assessed with the Impact of Epilepsy Scale, containing items about relationships, employment, overall health, self-esteem, and standard of living. Genetic attribution was assessed using a scale derived from three items asking about the role of genetics in causing epilepsy in the family, the chance of having an epilepsy-related mutation, and the influence of genetics in causing the participant's epilepsy. We estimated prevalence ratios (PRs) for impact of epilepsy above the median using Poisson regression with robust standard errors, adjusting for number of lifetime seizures and time since last seizure. RESULTS: Participants' age averaged 51 years; 87% were non-Hispanic white, 63% were women, and 54% were college graduates. The genetic attribution scale was significantly associated with having a high impact of epilepsy (adjusted PR = 1.4, 95% confidence interval = 1.07-1.91, P = .02). One of the three genetic attribution questions was also significantly associated with a high impact of epilepsy (belief that genetics had a big role in causing epilepsy in the family, adjusted PR = 1.8). SIGNIFICANCE: These findings reflect an association between the psychosocial impact of epilepsy and the belief that epilepsy has a genetic cause, among people with epilepsy in families containing multiple affected individuals. This association could arise either because belief in a genetic cause leads to increased psychosocial impacts, or because a greater psychosocial impact of epilepsy leads some to believe their epilepsy is genetic.

Whole genome sequencing and rare variant analysis in essential tremor families.

Essential tremor (ET) is one of the most common movement disorders. The etiology of ET remains largely unexplained. Whole genome sequencing (WGS) is likely to be of value in understanding a large proportion of ET with Mendelian and complex disease inheritance patterns. In ET families with Mendelian inheritance patterns, WGS may lead to gene identification where WES analysis failed to identify the causative single nucleotide variant (SNV) or indel due to incomplete coverage of the entire coding region of the genome, in addition to accurate detection of larger structural variants (SVs) and copy number variants (CNVs). Alternatively, in ET families with complex disease inheritance patterns with gene x gene and gene x environment interactions enrichment of functional rare coding and non-coding variants may explain the heritability of ET. We performed WGS in eight ET families (n = 40 individuals) enrolled in the Family Study of Essential Tremor. The analysis included filtering WGS data based on allele frequency in population databases, rare SNV and indel classification and association testing using the Mixed-Model Kernel Based Adaptive Cluster (MM-KBAC) test. A separate analysis of rare SV and CNVs segregating within ET families was also performed. Prioritization of candidate genes identified within families was performed using phenolyzer. WGS analysis identified candidate genes for ET in 5/8 (62.5%) of the families analyzed. WES analysis in a subset of these families in our previously published study failed to identify candidate genes. In one family, we identified a deleterious and damaging variant (c.1367G>A, p.(Arg456Gln)) in the candidate gene, CACNA1G, which encodes the pore forming subunit of T-type Ca(2+) channels, CaV3.1, and is expressed in various motor pathways and has been previously implicated in neuronal autorhythmicity and ET. Other candidate genes identified include SLIT3 which encodes an axon guidance molecule and in three families, phenolyzer prioritized genes that are associated with hereditary neuropathies (family A, KARS, family B, KIF5A and family F, NTRK1). Functional studies of CACNA1G and SLIT3 suggest a role for these genes in ET disease pathogenesis.

Epilepsy in families: Age at onset is a familial trait, independent of syndrome.

OBJECTIVE: We tested 2 hypotheses regarding age at onset within familial epilepsies: (1) family members with epilepsy tend to have similar ages at onset, independent of epilepsy syndrome; and (2) age at onset is younger in successive generations after controlling for sampling bias. METHODS: We analyzed clinical data collected by the Epi4K Consortium (303 multiplex families, 1,120 individuals). To test hypothesis 1, we used both linear mixed models commonly used for heritability analysis and Cox regression models with frailty terms to assess clustering of onset within families after controlling for other predictors. To test hypothesis 2, we used mixed effects models, pairwise analyses, and survival analysis to address sampling-related bias that may mimic anticipation. RESULTS: Regarding hypothesis 1, age at seizure onset was significantly heritable (intraclass correlation coefficient = 0.17, p < 0.001) after adjusting for epilepsy type, sex, site, history of febrile seizure, and age at last observation. This finding remained significant after adjusting for epilepsy syndromes, and was robust across statistical methods in all families and in generalized families. Regarding hypothesis 2, the mean age at onset decreased in successive generations (p < 0.001). After adjusting for age at last observation, this effect was not significant in mixed effects models (p = 0.14), but remained significant in pairwise (p = 0.0003) and survival analyses (p = 0.02). INTERPRETATION: Age at seizure onset is an independent familial trait, and may have genetic determinants distinct from the determinants of particular epilepsy syndromes. Younger onsets in successive generations can be explained in part by sampling bias, but the presence of genetic anticipation cannot be excluded. ANN NEUROL 2019.