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EFHC1 variants are the most common mutations in inherited myoclonic and grand mal clonic-tonic-clonic (CTC) convulsions of juvenile myoclonic epilepsy (JME). We reanalyzed 54 EFHC1 variants associated with epilepsy from 17 cohorts based on National Human Genome Research Institute (NHGRI) and American College of Medical Genetics and Genomics (ACMG) guidelines for interpretation of sequence variants. We calculated Bayesian LOD scores for variants in coinheritance, unconditional exact tests and odds ratios (OR) in case–control associations, allele frequencies in genome databases, and predictions for conservation/pathogenicity. We reviewed whether variants damage EFHC1 functions, whether efhc1−/− KO mice recapitulate CTC convulsions and “microdysgenesis” neuropathology, and whether supernumerary synaptic and dendritic phenotypes can be rescued in the fly model when EFHC1 is overexpressed. We rated strengths of evidence and applied ACMG combinatorial criteria for classifying variants. Nine variants were classified as “pathogenic,” 14 as “likely pathogenic,” 9 as “benign,” and 2 as “likely benign.” Twenty variants of unknown significance had an insufficient number of ancestry-matched controls, but ORs exceeded 5 when compared with racial/ethnic-matched Exome Aggregation Consortium (ExAC) controls. NHGRI gene-level evidence and variant-level evidence establish EFHC1 as the first non–ion channel microtubule–associated protein whose mutations disturb R-type VDCC and TRPM2 calcium currents in overgrown synapses and dendrites within abnormally migrated dislocated neurons, thus explaining CTC convulsions and “microdysgenesis” neuropathology of JME. Genet Med 19 2, 144–156.

GAW20 provided a platform for developing and evaluating statistical methods to analyze human lipid-related phenotypes, DNA methylation, and single-nucleotide markers in a study involving a pharmaceutical intervention. In this article, we present an overview of the data sets and the contributions analyzing these data. The data, donated by the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) investigators, included data from 188 families (N = 1105) which included genome-wide DNA methylation data before and after a 3-week treatment with fenofibrate, single-nucleotide polymorphisms, metabolic syndrome components before and after treatment, and a variety of covariates. The contributions from individual research groups were extensively discussed prior, during, and after the Workshop in groups based on discussion themes, before being submitted for publication.

In juvenile myoclonic epilepsy, data are limited on the genetic basis of networks promoting convulsions with diffuse polyspikes on electroencephalography (EEG) and the subtle microscopic brain dysplasia called microdysgenesis.Using Sanger sequencing, we sequenced the exomes of six members of a large family affected with juvenile myoclonic epilepsy and confirmed cosegregation in all 37 family members. We screened an additional 310 patients with this disorder for variants on DNA melting-curve analysis and targeted real-time DNA sequencing of the gene encoding intestinal-cell kinase ( ICK). We calculated Bayesian logarithm of the odds (LOD) scores for cosegregating variants, odds ratios in case-control associations, and allele frequencies in the Genome Aggregation Database. We performed functional tests of the effects of variants on mitosis, apoptosis, and radial neuroblast migration in vitro and conducted video-EEG studies in mice lacking a copy of Ick.A variant, K305T (c.914A→C), cosegregated with epilepsy or polyspikes on EEG in 12 members of the family affected with juvenile myoclonic epilepsy. We identified 21 pathogenic ICK variants in 22 of 310 additional patients (7%). Four strongly linked variants (K220E, K305T, A615T, and R632X) impaired mitosis, cell-cycle exit, and radial neuroblast migration while promoting apoptosis. Tonic-clonic convulsions and polyspikes on EEG resembling seizures in human juvenile myoclonic epilepsy occurred more often in knockout heterozygous mice than in wild-type mice (P=0.02) during light sleep with isoflurane anesthesia.Our data provide evidence that heterozygous variants in ICK caused juvenile myoclonic epilepsy in 7% of the patients included in our analysis. Variant ICK affects cell processes that help explain microdysgenesis and polyspike networks observed on EEG in juvenile myoclonic epilepsy. (Funded by the National Institutes of Health and others.).

Juvenile myoclonic epilepsy (JME), the most common genetic epilepsy, remains enigmatic because it is considered one disease instead of several diseases. We ascertained three large multigenerational/multiplex JME pedigrees from Honduras with differing JME subsyndromes, including Childhood Absence Epilepsy evolving to JME (CAE/JME; pedigree 1), JME with adolescent onset pyknoleptic absence (JME/pA; pedigree 2), and classic JME (cJME; pedigree 3). All phenotypes were validated, including symptomatic persons with various epilepsies, asymptomatic persons with EEG 3.5–6.0 Hz polyspike waves, and asymptomatic persons with normal EEGs. Two‐point parametric linkage analyses were performed with 5185 single‐nucleotide polymorphisms on individual pedigrees and pooled pedigrees using four diagnostic models based on epilepsy/EEG diagnoses. Haplotype analyses of the entire genome were also performed for each individual. In pedigree 1, haplotyping identified a 34 cM region in 2q21.2–q31.1 cosegregating with all affected members, an area close to 2q14.3 identified by linkage (Z max = 1.77; pedigree 1). In pedigree 2, linkage and haplotyping identified a 44 cM cosegregating region in 13q13.3–q31.2 (Z max = 3.50 at 13q31.1; pooled pedigrees). In pedigree 3, haplotyping identified a 6 cM cosegregating region in 17q12. Possible cosegregation was also identified in 13q14.2 and 1q32 in pedigree 3, although this could not be definitively confirmed due to the presence of uninformative markers in key individuals. Differing chromosome regions identified in specific JME subsyndromes may contain separate JME disease‐causing genes, favoring the concept of JME as several distinct diseases. Whole‐exome sequencing will likely identify a CAE/JME gene in 2q21.2–2q31.1, a JME/pA gene in 13q13.3–q31.2, and a cJME gene in 17q12.

With the advance of next-generation sequencing technologies in recent years, rare genetic variant data have now become available for genetic epidemiology studies. For family samples, however, only a few statistical methods for association analysis of rare genetic variants have been developed. Rare variant approaches are of great interest, particularly for family data, because samples enriched for trait-relevant variants can be ascertained and rare variants are putatively enriched through segregation. To facilitate the evaluation of existing and new rare variant testing approaches for analyzing family data, Genetic Analysis Workshop 18 (GAW18) provided genotype and next-generation sequencing data and longitudinal blood pressure traits from extended pedigrees of Mexican American families from the San Antonio Family Study. Our GAW18 group members analyzed real and simulated phenotype data from GAW18 by using generalized linear mixed-effects models or principal components to adjust for familial correlation or by testing binary traits using a correction factor for familial effects. With one exception, approaches dealt with the extended pedigrees in their original state using information based on the kinship matrix or alternative genetic similarity measures. For simulated data our group demonstrated that the family-based kernel machine score test is superior in power to family-based single-marker or burden tests, except in a few specific scenarios. For real data three contributions identified significant associations. They substantially reduced the number of tests before performing the association analysis. We conclude from our real data analyses that further development of strategies for targeted testing or more focused screening of genetic variants is strongly desirable.

Genetic Analysis Workshop 19 provided a platform for developing and evaluating statistical methods to analyze whole-genome sequence and gene expression data from a pedigree-based sample, as well as whole-exome sequence data from a large cohort of unrelated individuals. In this article we present an overview of the data sets, the GAW experience, and summaries of the contributions arranged into nine methodological themes.

Summary Purpose: The β3 subunit of the γ-aminobutyric acid type A receptors (GABAA–Rs) is an essential component of GABAA–Rs in fetal, perinatal, and adult mammalian brain. Various transcripts of the β3 subunit gene (GABRB3) produce various proteins with different N-termini. Rare variants in this N-terminus (exon 1A and exon 2) of GABRB3 protein segregate in affected family members of two multigeneration-multiplex families with remitting childhood absence epilepsy (rCAE), suggesting GABRB3 is a major Mendelian epilepsy gene for rare families with CAE. Therefore, the N-terminus of GABRB3 could be important for GABRB3 regulation in development, and its alteration could produce rCAE. Herein we determine if single nucleotide polymorphisms (SNPs) within the 1,148-bp region upstream from exon 1A influence the expression of GABRB3. Methods: We studied luciferase reporter expression for promoter activity, 1,148-bp upstream from exon 1A, using human embryonic kidney 293 cells. We generated constructs of the promoter region and compared different SNP haplotypes in 48 patients with rCAE. Next, we compared frequencies of rs20317, located in the core promoter region, and rs4906902, located in the enhancer region between 48 patients with rCAE and >500 healthy controls matched for ethnicity and ancestral origin. Key Findings: Highest luciferase expression occurred 230-bp upstream of exon 1A. The construct that excluded this region lost luciferase activity. Therefore, this region contains the core promoter of exon 1A. Allele C but not allele G (rs20317) significantly increased luciferase expression activity. Allele C creates binding motifs for cMYB and EGR-3. Longer constructs overlapping this region have a binding motif for REST (RE1-silencing transcription factor), a critical epigenetic modulator for neuronal genes. REST represses expression of neuronal genes in nonneuronal tissues, resulting in reduced luciferase expression activity. Even in the suppressed condition, the longer construct enhanced luciferase expression activity of the shorter construct, which excluded the distal end containing rs4906902. However, allele frequencies of rs20317 and rs4906902 were not significantly associated with 48 rCAE patients in comparison to >500 controls matched for ethnicity and ancestral origin. Significance: Common SNPs in the promoter region increase luciferase expression activity. An epigenetic modulator, REST, specifically alters expression of GABRB3 exon 1A transcripts, suggesting epigenetic regulation by REST dominantly controls the expression of GABRB3 variant 2 transcript in early life GABAA signaling. Abnormal epigenetic regulation could be involved in absence seizures.

Genotyping of rare variants on a large scale is now possible using next-generation sequencing. Sample selection is a crucial step in designing the genetic study of a complex disease, and knowledge of the efficiency and limitations of population-based and family-based designs can help researchers make the appropriate choice. The nine contributions to Group 5 of Genetic Analysis Workshop 17 evaluate population-based and family-based designs by comparing the results obtained with various methods applied to the mini-exome simulations. These simulations consisted of 200 replicates composed of unrelated individuals and eight extended pedigrees with genotypes and various phenotypes. The methods tested for association with a population-based and/or a family-based design, tested for linkage with a family-based design, or estimated heritability. We summarize the strengths and weaknesses of both designs. Although population-based designs seem more suitable for detecting the effect of multiple rare variants, family-based designs can potentially enrich the sample in rare variants, for which the effect would be concealed at the population level. However, as of today, the main limitation is still the high cost of next-generation sequencing. Genet. Epidemiol. 35:S41–S47, 2011. © 2011 Wiley Periodicals, Inc.

Juvenile myoclonic epilepsy (JME) is the most common cause of primary grand mal seizures and accounts for at least 3 to 12% of all epilepsies. JME can be inherited as a Mendelian autosomal dominant or autosomal recessive trait or as a non-Mendelian complex genetic trait. Three mutation-harboring Mendelian genes for JME have been reported. Mutations in α1 subunit of γ-aminobutyric acid receptor subtype A on chromosome 5q34 segregated with nine affected individuals of a three-generation French Canadian family with JME (Cossette et al., 2002). Mutations in a chloride-channel gene, CLCN2 on chromosome 3q26 segregated with five affected members of a three-generation German family with JME (Haug et al., 2003). Our group first mapped a JME locus in chromosome 6p12 (Liu et al., 1995, 1996; Serratosa et al., 1996; Bai et al., 2002) and identified a mutation-harboring Mendelian gene that encodes a protein with one EF-hand motif. Hence, we called the gene EFHC1. We reported one doubly heterozygous and three heterozygous missense mutations segregated in 21 clinical and electroencephalography (EEG) affected members of six unrelated two- to four-generation JME Hispanic families from California (U.S.A.) and Mexico (Suzuki et al., 2004). The 6p12 JME locus was again mapped independently by two separate groups; first, by a genome-wide linkage study of JME families from various countries of Europe (Hempelmann et al., 2006) and second by a chromosome 6p12 replication genetic linkage study in a smaller cohort of 18 Dutch families (Pinto et al., 2004). Similar and novel missense mutations in EFHC1 were reported in Caucasian JME patients from Tennessee (U.S.A.), Italy, and Austria (Ma et al., 2006; Stogmann et al., 2006; Annesi et al., 2007). Therefore the causality of the gene in a Mendelian JME has been established, but the influence of common functional single nucleotide polymorphisms (SNPs) in JME with complex genetics has not been established. Pinto et al. (2006) reported three SNPs of EFHC1 that were not associated with JME in a case-control study of 112 unrelated patients and 180 controls. In our present study, we chose the most common four coding SNPs of EFHC1 and performed both case-control and family-based association studies to determine if they contribute to the complex genetics of JME.

High-density genetic marker data, especially sequence data, imply an immense multiple testing burden. This can be ameliorated by filtering genetic variants, exploiting or accounting for correlations between variants, jointly testing variants, and by incorporating informative priors. Priors can be based on biological knowledge or predicted variant function, or even be used to integrate gene expression or other omics data. Based on Genetic Analysis Workshop (GAW) 19 data, this article discusses diversity and usefulness of functional variant scores provided, for example, by PolyPhen2, SIFT, or RegulomeDB annotations. Incorporating functional scores into variant filters or weights and adjusting the significance level for correlations between variants yielded significant associations with blood pressure traits in a large family study of Mexican Americans (GAW19 data set). Marker rs218966 in gene PHF14 and rs9836027 in MAP4 significantly associated with hypertension; additionally, rare variants in SNUPN significantly associated with systolic blood pressure. Variant weights strongly influenced the power of kernel methods and burden tests. Apart from variant weights in test statistics, prior weights may also be used when combining test statistics or to informatively weight p values while controlling false discovery rate (FDR). Indeed, power improved when gene expression data for FDR-controlled informative weighting of association test p values of genes was used. Finally, approaches exploiting variant correlations included identity-by-descent mapping and the optimal strategy for joint testing rare and common variants, which was observed to depend on linkage disequilibrium structure. peerReviewed

Non-human primates (NHP) provide crucial research models. Their strong similarities to humans make them particularly valuable for understanding complex behavioral traits and brain structure and function. We report here the genetic mapping of an NHP nervous system biologic trait, the cerebrospinal fluid (CSF) concentration of the dopamine metabolite homovanillic acid (HVA), in an extended inbred vervet monkey ( Chlorocebus aethiops sabaeus ) pedigree. CSF HVA is an index of CNS dopamine activity, which is hypothesized to contribute substantially to behavioral variations in NHP and humans. For quantitative trait locus (QTL) mapping, we carried out a two-stage procedure. We first scanned the genome using a first-generation genetic map of short tandem repeat markers. Subsequently, using >100 SNPs within the most promising region identified by the genome scan, we mapped a QTL for CSF HVA at a genome-wide level of significance (peak logarithm of odds score >4) to a narrow well delineated interval (

The 2001 classification subcommittee of the International League Against Epilepsy (ILAE) proposed to 'group JME, juvenile absence epilepsy, and epilepsy with tonic clonic seizures only under the sole heading of idiopathic generalized epilepsies (IGE) with variable phenotype'. The implication is that juvenile myoclonic epilepsy (JME) does not exist as the sole phenotype of family members and that it should no longer be classified by itself or considered a distinct disease entity. Although recognized as a common form of epilepsy and presumed to be a lifelong trait, a long-term follow-up of JME has not been performed. To address these two issues, we studied 257 prospectively ascertained JME patients and encountered four groups: (i) classic JME (72%), (ii) CAE (childhood absence epilepsy) evolving to JME (18%), (iii) JME with adolescent absence (7%), and (iv) JME with astatic seizures (3%). We examined clinical and EEG phenotypes of family members and assessed clinical course over a mean of 11 +/- 6 years and as long as 52 years. Forty per cent of JME families had JME as their sole clinical phenotype. Amongst relatives of classic JME families, JME was most common (40%) followed by grand mal (GM) only (35%). In contrast, 66% of families with CAE evolving to JME expressed the various phenotypes of IGE in family members. Absence seizures were more common in family members of CAE evolving to JME than in those of classic JME families (P < 0.001). Female preponderance, maternal transmission and poor response to treatment further characterized CAE evolving to JME. Only 7% of those with CAE evolving to JME were seizure-free compared with 58% of those with classic JME (P < 0.001), 56% with JME plus adolescent pyknoleptic absence and 62% with JME plus astatic seizures. Long-term follow-up (1-40 years for classic JME; 5-52 years for CAE evolving to JME, 5-26 years for JME with adolescent absence and 3-18 years for JME with astatic seizures) indicates that all subsyndromes are chronic and perhaps lifelong. Seven chromosome loci, three epilepsy-causing mutations and two genes with single nucleotide polymorphisms (SNPs) associating with JME reported in literature provide further evidence for JME as a distinct group of diseases.

Summary: Idiopathic generalized epilepsies (IGEs) comprise at least 40% of epilepsies in the United States, 20% in Mexico, and 8% in Central America. Here, we review seizure phenotypes across IGE syndromes, their response to treatment and advances in molecular genetics that influence nosology. Our review included the Medline database from 1945 to 2005 and our prospectively collected Genetic Epilepsy Studies (GENESS) Consortium database. Generalized seizures occur with different and similar semiologies, frequencies, and patterns, ages at onset, and outcomes in different IGEs, suggesting common neuroanatomical pathways for seizure phenotypes. However, the same seizure phenotypes respond differently to the same treatments in different IGEs, suggesting different molecular defects across syndromes. De novo mutations in SCN1A in sporadic Dravet syndrome and germline mutations in SCN1A, SCN1B, and SCN2A in generalized epilepsies with febrile seizures plus have unraveled the heterogenous myoclonic epilepsies of infancy and early childhood. Mutations in GABRA1, GABRG2, and GABRB3 are associated with absence seizures, while mutations in CLCN2 and myoclonin/EFHC1 substantiate juvenile myoclonic epilepsy as a clinical entity. Refined understanding of seizure phenotypes, their semiology, frequencies, and patterns together with the identification of molecular lesions in IGEs continue to accelerate the development of molecular epileptology.

Understanding the latest advances in the molecular genetics of the epilepsies is important, as it provides a basis for comprehending the new practice of epileptology. Epilepsies have traditionally been classified and subtyped on the basis of clinical and neurophysiologic concepts. However, the complexity and variability of phenotypes and overlapping clinical features limit the resolution of phenotype-based classification and confound epilepsy nosology. Identification of tightly linked epilepsy DNA markers and discovery of epilepsy-causing mutations provide a basis for refining the classification of epilepsies. Recent discoveries regarding the genetics surrounding certain epilepsy types (including Lafora's progressive myoclonic epilepsy, the severe myoclonic epilepsy of infancy of Dravet, and idiopathic generalized epilepsies) may be the beginning of a better understanding of how rare Mendelian epilepsy genes and their genetic architecture can explain some complexities of the common epilepsies.

Evidence that the dopamine D4 receptor is a susceptibility gene in attention deficit hyperactivity disorder

Genetic Analysis Workshop 18 provided a platform for developing and evaluating statistical methods to analyze whole-genome sequence data from a pedigree-based sample. In this article we present an overview of the data sets and the contributions that analyzed these data. The family data, donated by the Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Ethnic Samples Consortium, included sequence-level genotypes based on sequencing and imputation, genome-wide association genotypes from prior genotyping arrays, and phenotypes from longitudinal assessments. The contributions from individual research groups were extensively discussed before, during, and after the workshop in theme-based discussion groups before being submitted for publication.

Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop.

Considerable attention has been paid to identifying genetic influences and gene-environment interactions that increase vulnerability to environmental stressors, with promising but inconsistent results. A nonhuman primate model is presented here that allows assessment of genetic influences in response to a stressful life event for a behavioural trait with relevance for psychopathology. Genetic and environmental influences on free-choice novelty seeking behaviour were assessed in a pedigreed colony of vervet monkeys before and after relocation from a low stress to a higher stress environment. Heritability of novelty seeking scores, and genetic correlations within and between environments were conducted using variance components analysis. The results showed that novelty seeking was markedly inhibited in the higher stress environment, with effects persisting across a 2-year period for adults but not for juveniles. There were significant genetic contributions to novelty seeking scores in each year (h(2) = 0.35-0.43), with high genetic correlations within each environment (rhoG > 0.80) and a lower genetic correlation (rhoG = 0.35, non-significant) between environments. There were also significant genetic contributions to individual change scores from before to after the move (h(2) = 0.48). These results indicate that genetic regulation of novelty seeking was modified by the level of environmental stress, and they support a role for gene-environment interactions in a behavioural trait with relevance for mental health.

Chronic activation of the hypothalamic-pituitary adrenal (HPA) system is a risk factor for a variety of physical and mental disorders, and yet the complexity of the system has made it difficult to define the role of genetic and environmental factors in producing long term individual differences in HPA activity. Cortisol levels in hair have been suggested as a marker of total HPA activation over a period of several months. This study takes advantage of a pedigreed nonhuman primate colony to investigate genetic and environmental influences on hair cortisol levels before and after an environmental change. A sample of 226 adult female vervet monkeys (age 3–18) living in multigenerational, matrilineal social groups at the Vervet Research Colony were sampled in a stable low stress baseline environment and 6 months after the entire colony was moved to a new facility with more frequent handling and group disturbances (higher stress environment). Variance components analysis using the extended colony pedigree was applied to determine heritability of hair cortisol levels in the two environments. Bivariate genetic correlation assessed degree of overlap in genes influencing hair cortisol levels in the low and higher stress environments. The results showed that levels of cortisol in hair of female vervets increased significantly from the baseline to the post-move environment. Hair cortisol levels were heritable in both environments (h2 = 0.31), and there was a high genetic correlation across environments (rhoG = 0.79), indicating substantial overlap in the genes affecting HPA activity in low and higher stress environments. This is the first study to demonstrate that the level of cortisol in hair is a heritable trait. It shows the utility of hair cortisol as a marker for HPA activation, and a useful tool for identifying genetic influences on long term individual differences in HPA activity. The results provide support for an additive model of the effects of genes and environment on this measure of long term HPA activity.

KAVANAGH, KYLIE, LYNN A. FAIRBANKS, JULIA N. BAILEY, MATTHEW J. JORGENSEN, MARTHA WILSON, LI ZHANG, LAWRENCE L. RUDEL, AND JANICE D. WAGNER. Characterization and heritability of obesity and associated risk factors in vervet monkeys. Obesity. 2007;15:1666–1674. Objective: The objective was to determine the prevalence and heritability of obesity and risk factors associated with metabolic syndrome (MS) in a pedigreed colony of vervet monkeys. Design: A cross-sectional study of plasma lipid and lipoprotein concentrations, glycemic indices, and morphometric measures with heritability calculated from pedigree analysis. A selected population of females was additionally assessed for insulin sensitivity and glucose tolerance. Subjects: All mature male (n 98), pregnant (n 40) and non-pregnant female (n 157) vervet monkeys were included in the study. Seven non-pregnant females were selected on the basis of high or average glycated hemoglobin (GHb) for further characterization of carbohydrate metabolism. Measurements: Morphometric measurements included body weight, length, waist circumference, and calculated BMI. Plasma lipids [total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C)] and glycemic measures (fasting blood glucose, insulin, and GHb) were measured. A homeostasis model assessment index was further reported. Glucose tolerance testing and hyperinsulinemic-euglycemic clamps were performed on 7 selected females. Conclusion: Vervet monkeys demonstrate obesity, insulin resistance, and associated changes in plasma lipids even while consuming a low-fat (chow) diet. Furthermore, these parameters are heritable. Females are at particular risk for central obesity and an unfavorable lipid profile (higher TG, TC, and no estrogen-related increase in HDL-C). Selection of females by elevated GHb indicated impaired glucose tolerance and was associated with central obesity. This colony provides a unique opportunity to study the development of obesity-related disorders, including both genetic and environmental influences, across all life stages.

The purpose of these analyses was to determine if incorporating or adjusting for covariates in genetic analyses helped or hindered in genetic analyses, specifically heritability and linkage analyses. To study this question, two types of covariate models were used in the simulated Genetic Analysis Workshop 14 dataset in which the true gene locations are known. All four populations of one replicate were combined for the analyses. The first model included typical covariates of sex and cohort (population) and the second included the typical covariates and also those related endophenotypes that are thought to be associated with the trait (phenotypes A, B, C, D, E, F, G, H, I, J, K, and L). A final best fit model produced in the heritability analyses was used for linkage. Linkage for disease genes D1, D3, and D4 were localized using models with and without the covariates. The use of inclusion of covariates did not appear to have any consistent advantage or disadvantage for the different phenotypes in regards to gene localization or false positive rate.

Tuberous sclerosis complex (TSC) is an autosomal dominant disorder (OMIM 191092) characterised by autism, seizures, mental retardation, benign tumours of the brain, heart, kidney, lung, and skin, and malignant tumours of the kidney.1 TSC has a wide range of phenotypic variability, with some subjects severely affected and others only mildly affected. There are two TSC genes, TSC1 on chromosome 9q342 and TSC2 on chromosome 16p13.3Approximately two thirds of cases of TSC appear to result from de novo germline mutations. In 1994, an extended four generation family with 19 affected members was reported in which 34 members (17 affected with TSC and 17 unaffected) underwent both physical and psychiatric assessments.4 The majority of the affected subjects had mild physical expression of TSC, but there was significant clustering of neuropsychiatric disorders among affected subjects compared with their unaffected relatives. The disorders that were over-represented included mood disorder, anxiety disorder, and autism. The largest difference was observed in anxiety disorder, which was seen in 10 of the affected subjects and in two of the unaffected subjects (p=0.016). One affected child had pervasive developmental disorder and one had autism. Analysis of this family suggested that TSC could present phenotypically with mild physical signs and symptoms, but with significant neuropsychiatric disease. Linkage to the TSC2 gene locus on chromosome 16p13.3 was shown with a lod score of over 3.4 We report here the identification of a missense mutation in exon 34 of the TSC2 gene in affected members of this family. We also examined a second four generation family5from the same geographical area as the …

ss Open Acce Introduction Genetic Analysis Workshop 14: microsatellite and single-nucleotide polymorphism marker loci for genome-wide scans Joan E Bailey-Wilson*1, Laura Almasy2, Mariza de Andrade3, Julia Bailey4, Heike Bickeboller5, Heather J Cordell6, E Warwick Daw7, Lynn Goldin8, Ellen L Goode9, Courtney Gray-McGuire10, Wayne Hening11, Gail Jarvik12, Brion S Maher13, Nancy Mendell14, Andrew D Paterson15, John Rice16, Glen Satten17, Brian Suarez16, Veronica Vieland18, Marsha Wilcox19, Heping Zhang20, Andreas Ziegler21 and Jean W MacCluer2

Childhood absence epilepsy (CAE) accounts for 10% to 12% of epilepsy in children under 16 years of age. We screened for mutations in the GABA(A) receptor (GABAR) beta 3 subunit gene (GABRB3) in 48 probands and families with remitting CAE. We found that four out of 48 families (8%) had mutations in GABRB3. One heterozygous missense mutation (P11S) in exon 1a segregated with four CAE-affected persons in one multiplex, two-generation Mexican family. P11S was also found in a singleton from Mexico. Another heterozygous missense mutation (S15F) was present in a singleton from Honduras. An exon 2 heterozygous missense mutation (G32R) was present in two CAE-affected persons and two persons affected with EEG-recorded spike and/or sharp wave in a two-generation Honduran family. All mutations were absent in 630 controls. We studied functions and possible pathogenicity by expressing mutations in HeLa cells with the use of Western blots and an in vitro translation and translocation system. Expression levels did not differ from those of controls, but all mutations showed hyperglycosylation in the in vitro translation and translocation system with canine microsomes. Functional analysis of human GABA(A) receptors (alpha 1 beta 3-v2 gamma 2S, alpha 1 beta 3-v2[P11S]gamma 2S, alpha 1 beta 3-v2[S15F]gamma 2S, and alpha 1 beta 3-v2[G32R]gamma 2S) transiently expressed in HEK293T cells with the use of rapid agonist application showed that each amino acid transversion in the beta 3-v2 subunit (P11S, S15F, and G32R) reduced GABA-evoked current density from whole cells. Mutated beta 3 subunit protein could thus cause absence seizures through a gain in glycosylation of mutated exon 1a and exon 2, affecting maturation and trafficking of GABAR from endoplasmic reticulum to cell surface and resulting in reduced GABA-evoked currents.

Purpose The purpose of this study was to identify the prevalence of mutations in the Myoclonin1 / EFHC1 gene in Mexican patients with juvenile myoclonic epilepsy (JME). Method We studied forty-one patients at the National Institute of Neurology and Neurosurgery in Mexico City and 100 healthy controls. DNA was extracted from the peripheral venous blood of all participants. The exons of EFHC1 were then amplified and sequenced. Results We found three new putative mutations, all of which were heterozygous missense mutations located in exon 3. The first identified mutation, 352C>T, produces a R118C change in the protein and cosegregated in the patient's affected father and brother. The second identified mutation, 544C>T, produces a R182L change in the protein and was found in the patient's asymptomatic father. The third identified mutation, 458>A, produces a R153Q change in the protein and was also found in the patient's father. These mutations were not found in controls. Conclusions The frequency of Myoclonin1 / EFHC1 mutations in our sample is 7.3%. Thus, we conclude that mutations in the Myoclonin1 / EFHC1 gene are an important cause of JME in Mexican patients.

Mutations in the EPM2A gene encoding a dual-specificity phosphatase (laforin) cause an autosomal recessive fatal disorder called Lafora's disease (LD) classically described as an adolescent-onset stimulus-sensitive myoclonus, epilepsy and neurologic deterioration. Here we related mutations in EPM2A with phenotypes of 22 patients (14 families) and identified two subsyndromes: (i) classical LD with adolescent-onset stimulus-sensitive grand mal, absence and myoclonic seizures followed by dementia and neurologic deterioration, and associated mainly with mutations in exon 4 (P = 0.0007); (ii) atypical LD with childhood-onset dyslexia and learning disorder followed by epilepsy and neurologic deterioration, and associated mainly with mutations in exon 1 (P = 0.0015). To understand the two subsyndromes better, we investigated the effect of five missense mutations in the carbohydrate-binding domain (CBD-4; coded by exon 1) and three missense mutations in the dual phosphatase domain (DSPD; coded by exons 3 and 4) on laforin's intracellular localization in HeLa cells. Expression of three mutant proteins (T194I, G279S and Y294N) in DSPD formed ubiquitin-positive cytoplasmic aggregates, suggesting that they were folding mutants set for degradation. In contrast, none of the three CBD-4 mutants showed cytoplasmic clumping. However, CBD-4 mutants W32G and R108C targeted both cytoplasm and nucleus, suggesting that laforin had diminished its usual affinity for polysomes. Our data, thus, represent the first report of a novel childhood syndrome for LD. Our results also provide clues for distinct roles for the CBD-4 and DSP domains of laforin in the etiology of two subsyndromes of LD.

Background The regulation of gene expression is an emerging area of investigation. Increased knowledge can deepen our understanding of the genetic contributions to variations in complex traits. The purpose of this study is to explore the feasibility of detecting regulatory elements of gene expression with multivariate analyses. Methods Peripheral blood lymphocyte expression levels of 30 genes on chromosome 5 and a single gene, DEAD, on chromosome 22 were analyzed in single-point variance-component linkage analyses in multiplex families to identify putative regulatory regions. To explore the possibility of regulatory regions having individual relationships with the expression levels of a single gene, we utilized stepwise regression. To explore the possibility of pleiotropy of a single regulatory locus for multiple genes, bivariate linkage analysis was applied. Results Twenty-one loci were linked to five expression levels. The two most significant were for the known region on chromosome 22 (LOD = 4.62). On chromosome 5 a LOD of 4.57 was found for the gene leukocyte-derived arginine aminopeptidase (LRAP) with a single-nucleotide polymorphism (SNP) within 5 Mb. Both genes showed evidence of linkage to multiple SNPs. When 194 family members were treated as independent, stepwise regression identified fewer single-nucleotide polymorphisms with significant predictive values (p < 0.05), providing evidence for multiple regulatory regions of unequal effect. However, when corrections for non-independence were applied these results could no longer be detected. Conclusion The complex nature of gene regulation can be explored by linkage analysis with single-nucleotide polymorphisms followed by multivariate methods to explore co-regulation.