Inflation of polygenic risk scores caused by sample overlap and relatedness: Examples of a major risk of bias.

Polygenic risk scores (PRSs) are an important tool for understanding the role of common genetic variants in human disease. Standard best practices recommend that PRSs be analyzed in cohorts that are independent of the genome-wide association study (GWAS) used to derive the scores without sample overlap or relatedness between the two cohorts. However, identifying sample overlap and relatedness can be challenging in an era of GWASs performed by large biobanks and international research consortia. Although most genomics researchers are aware of best practices and theoretical concerns about sample overlap and relatedness between GWAS and PRS cohorts, the prevailing assumption is that the risk of bias is small for very large GWASs. Here, we present two real-world examples demonstrating that sample overlap and relatedness is not a minor or theoretical concern but an important potential source of bias in PRS studies. Using a recently developed statistical adjustment tool, we found that excluding overlapping and related samples was equal to or more powerful than adjusting for overlap bias. Our goal is to make genomics researchers aware of the magnitude of risk of bias from sample overlap and relatedness and to highlight the need for mitigation tools, including independent validation cohorts in PRS studies, continued development of statistical adjustment methods, and tools for researchers to test their cohorts for overlap and relatedness with GWAS cohorts without sharing individual-level data.

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.

Beliefs About the Causes of Alzheimer's Disease Among Latinos in New York City.

Latinos face health disparities in Alzheimer's disease (AD), with high disease prevalence relative to non-Latino whites and barriers to healthcare access. Several studies have found misconceptions about AD among Latinos that were linked to reduced preventative or help-seeking behavior. To improve understanding of illness perceptions among Latinos, we examined beliefs about the causes of AD, one of the five dimensions of illness representations from Leventhal's Self-Regulation Theory, among a sample of N = 216 Latinos. We conducted in-depth, semi-structured interviews with participants aged 40 to 64 (average age 53 years) living in northern Manhattan. Seven distinct causes of AD were identified, though participants demonstrated a general understanding of AD as a multifactorial disease. Genetics was found to be the most endorsed cause of AD, followed by unhealthy lifestyle factors. Most Latinos who believed psychosocial factors played a critical role in AD development were first-generation immigrants. No participants attributed AD to a normal process of aging, and few ascribed the disease to brain damage from stroke or head injuries. Several participants expressed the belief that environmental contaminants can cause AD, which has received little mention in prior studies. Though only a small number thought AD could occur by chance, most participants remained uncertain about the exact causes of the disease and used lay knowledge to explain their beliefs. Our findings help identify areas where educational interventions would be beneficial in improving community knowledge and offer perspectives that can foster cultural competency in healthcare.

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.

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.

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.

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.

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.

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.

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.

Concordance for Parkinson's disease in twins: A 20-year update.

During the 1990s, we estimated the genetic contribution to Parkinson's disease risk in a large, population-based twin registry. Because many unaffected twins were still alive, previous concordance estimates were based on incomplete information. Ninety-five percent of twins are now deceased. Here, we update concordance and heritability through 2015 using National Death Index data. In total, we identified 30 concordant and 193 discordant pairs. Proband-wise concordance was 0.20 in monozygotic and 0.13 in dizygotic pairs. Heritability was 0.27 overall, 0.83 in pairs diagnosed ≤50, and 0.19 in pairs diagnosed >50. High concordance in dizygotic twins suggests shared effects of early childhood environment. Ann Neurol 2019;85:600-605.

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.

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.

De novo mutations in epileptic encephalopathies.

Epileptic encephalopathies are a devastating group of severe childhood epilepsy disorders for which the cause is often unknown. Here we report a screen for de novo mutations in patients with two classical epileptic encephalopathies: infantile spasms (n = 149) and Lennox-Gastaut syndrome (n = 115). We sequenced the exomes of 264 probands, and their parents, and confirmed 329 de novo mutations. A likelihood analysis showed a significant excess of de novo mutations in the ∼4,000 genes that are the most intolerant to functional genetic variation in the human population (P = 2.9 × 10(-3)). Among these are GABRB3, with de novo mutations in four patients, and ALG13, with the same de novo mutation in two patients; both genes show clear statistical evidence of association with epileptic encephalopathy. Given the relevant site-specific mutation rates, the probabilities of these outcomes occurring by chance are P = 4.1 × 10(-10) and P = 7.8 × 10(-12), respectively. Other genes with de novo mutations in this cohort include CACNA1A, CHD2, FLNA, GABRA1, GRIN1, GRIN2B, HNRNPU, IQSEC2, MTOR and NEDD4L. Finally, we show that the de novo mutations observed are enriched in specific gene sets including genes regulated by the fragile X protein (P < 10(-8)), as has been reported previously for autism spectrum disorders.

Heterozygous reelin mutations cause autosomal-dominant lateral temporal epilepsy.

Autosomal-dominant lateral temporal epilepsy (ADLTE) is a genetic epilepsy syndrome clinically characterized by focal seizures with prominent auditory symptoms. ADLTE is genetically heterogeneous, and mutations in LGI1 account for fewer than 50% of affected families. Here, we report the identification of causal mutations in reelin (RELN) in seven ADLTE-affected families without LGI1 mutations. We initially investigated 13 ADLTE-affected families by performing SNP-array linkage analysis and whole-exome sequencing and identified three heterozygous missense mutations co-segregating with the syndrome. Subsequent analysis of 15 small ADLTE-affected families revealed four additional missense mutations. 3D modeling predicted that all mutations have structural effects on protein-domain folding. Overall, RELN mutations occurred in 7/40 (17.5%) ADLTE-affected families. RELN encodes a secreted protein, Reelin, which has important functions in both the developing and adult brain and is also found in the blood serum. We show that ADLTE-related mutations significantly decrease serum levels of Reelin, suggesting an inhibitory effect of mutations on protein secretion. We also show that Reelin and LGI1 co-localize in a subset of rat brain neurons, supporting an involvement of both proteins in a common molecular pathway underlying ADLTE. Homozygous RELN mutations are known to cause lissencephaly with cerebellar hypoplasia. Our findings extend the spectrum of neurological disorders associated with RELN mutations and establish a link between RELN and LGI1, which play key regulatory roles in both the developing and adult brain.

Mood disorders in familial epilepsy: A test of shared etiology.

OBJECTIVE: Mood disorders are the most common comorbid conditions in epilepsy, but the cause remains unclear. One possible explanation is a shared genetic susceptibility to epilepsy and mood disorders. We tested this hypothesis by evaluating lifetime prevalence of mood disorders in relatives with and without epilepsy in families containing multiple individuals with epilepsy, and comparing the findings with rates from a general population sample. METHODS: The Composite International Diagnostic Interview was administered to 192 individuals from 60 families, including 110 participants with epilepsy of unknown cause (50 focal epilepsy [FE], 42 generalized epilepsy [GE], 6 FE and GE, 12 unclassifiable) and 82 relatives without epilepsy (RWOE). Odds ratios (ORs) for lifetime prevalence of mood disorders in participants with versus without epilepsy were computed through logistic regression, using generalized estimation equations to account for familial clustering. Standardized prevalence ratios (SPRs) were used to compare prevalence in family members with general population rates. RESULTS: Compared with RWOE, ORs for mood disorders were significantly increased in participants with FE (OR = 2.4, 95% confidence interval [CI] = 1.1-5.2) but not in those with GE (OR = 1.0, 95% CI = 0.4-2.2). In addition, prevalence of mood disorders was increased in individuals with epilepsy who had ≥1 relative with FE. Compared with general population rates, mood disorders were significantly increased in individuals with FE but not in those with GE. Rates were also increased in RWOE, but not significantly so (SPR = 1.4, P = .14). SIGNIFICANCE: These findings are consistent with the hypothesis of shared genetic susceptibility to epilepsy and mood disorders, but suggest (1) the effect may be restricted to FE, and (2) the shared genetic effect on risk of mood disorders and epilepsy may be restricted to individuals with epilepsy, that is, to those in whom the genetic risk for epilepsy is "penetrant."

Return of individual results in epilepsy genomic research: A view from the field.

Genomic findings are emerging rapidly in 2 large, closely related epilepsy research consortia: the Epilepsy Phenome/Genome Project and Epi4K. Disclosure of individual results to participants in genomic research is increasingly viewed as an ethical obligation, but strategies for return of results were not included in the design of these consortia, raising complexities in establishing criteria for which results to offer, determining participant preferences, managing the large number of sites involved, and covering associated costs. Here, we describe the challenges faced, alternative approaches considered, and progress to date. Experience from these 2 consortia illustrates the importance, for genomic research in epilepsy and other disorders, of including a specific plan for return of results in the study design, with financial support for obtaining clinical confirmation and providing ongoing support for participants. Participant preferences for return of results should be established at the time of enrollment, and methods for allowing future contacts with participants should be included. In addition, methods should be developed for summarizing meaningful, comprehensible information about findings in the aggregate that participants can access in an ongoing way.

Familial aggregation of major depressive disorder in an African-American community.

BACKGROUND: African Americans (AAs) with major depressive disorder (MDD) experience more impairment and poorer treatment outcomes relative to Whites, yet are underrepresented in family studies of MDD. This is the first study to investigate the familial aggregation of major depression among AAs. METHODS: Participants' reports of depression from clinical and family history (FH) interviews were used to examine depression rates among 435 first-degree relatives and half-siblings of 63 depressed cases and 222 relatives of 33 nondepressed controls. Binary logistic regression was used to compute odds ratios (ORs) for FH of MDD and level of trauma exposure (high and low) in cases versus controls. Poisson regression models with generalized estimating equations were used to assess MDD in relatives of cases versus relatives of controls. RESULTS: Cases and controls did not differ in either FH of MDD (OR = 1.2, 95% confidence interval [CI] = 0.5-2.9), or prevalence of MDD in relatives (relative risk [RR] = 1.5, 95% CI = 0.8-2.5). However, exposure to high trauma was associated with increased risk of MDD (OR = 3.0, 95% CI = 1.22-7.17) and the combined effect of FH and trauma was greater than expected under an additive model. Similarly, the RR for MDD among relatives of cases with high-trauma levels was 2.2 (1.24-4.2), compared to relatives of controls with low trauma. CONCLUSION: The effect of FH of MDD appears to be exacerbated among individuals exposed to high trauma. Replication and further research on the chronology and subtypes of trauma and MDD, and their interactions, remain essential in AA populations.

Familial Aggregation and Co-Aggregation of Essential Tremor and Parkinson's Disease.

BACKGROUND: Current data suggest that the 2 common tremor disorders, essential tremor (ET) and Parkinson's disease (PD), may be associated with one another. Familial aggregation studies allow one to further explore their relatedness. METHODS: Probands with ET (n = 110), PD (n = 130) or both ET and PD (n = 27) and control probands (n = 177) reported whether they had relatives with these diseases or with non-specific tremor. RESULTS: A greater proportion of ET probands than control probands reported relatives with ET (30.0 vs. 2.8%, p < 0.001), non-specific tremor (38.2 vs. 13.6%, p < 0.001) and both ET and PD in different relatives (6.4 vs. 0.6%, p = 0.004). A greater proportion of PD probands than control probands reported relatives with PD (20.0 vs. 8.5%, p = 0.003), ET (11.5 vs. 2.8%, p = 0.002) and both ET and PD in different relatives (6.9 vs. 0.6%, p = 0.002). CONCLUSIONS: This study provides evidence for the aggregation of ET in ET families and PD in PD families, and the familial co-aggregation of ET and PD.