Variant Intestinal-Cell Kinase in Juvenile Myoclonic Epilepsy.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.).

EFHC1 variants in juvenile myoclonic epilepsy: reanalysis according to NHGRI and ACMG guidelines for assigning disease causality.

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Filtering genetic variants and placing informative priors based on putative biological function.

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.

Testing genetic association with rare and common variants in family data.

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.

The quest for juvenile myoclonic epilepsy genes.

Introduced into a specific population, a juvenile myoclonic epilepsy (JME) mutation generates linkage disequilibrium (LD). Linkage disequilibrium is strongest when the JME mutation is of recent origin, still "hitchhiking" alleles surrounding it, as a haplotype into the next thousands of generations. Recombinations decay LD over tens of thousands of generations causing JME alleles to produce smaller genetic displacements, requiring other genes or environment to produce an epilepsy phenotype. Family-based linkage analysis captures rare epilepsy alleles and their "hitchhiking" haplotypes, transmitted as Mendelian traits, supporting the common disease/multiple rare allele model. Genome-wide association studies identify JME alleles whose linkage disequilibrium has decayed through thousands of generations and are sorting out the common disease/common allele versus rare allele models. Five Mendelian JME genes have been identified, namely, CACNB4, CASR, GABRa1, GABRD, and Myoclonin1/EFHC1. Three SNP alleles in BRD2, Cx-36, and ME2 and microdeletions in 15q13.3, 15q11.2, and 16p13.11 also contribute risk to JME.

Mutations in EFHC1 cause juvenile myoclonic epilepsy.

Juvenile myoclonic epilepsy (JME) is the most frequent cause of hereditary grand mal seizures. We previously mapped and narrowed a region associated with JME on chromosome 6p12-p11 (EJM1). Here, we describe a new gene in this region, EFHC1, which encodes a protein with an EF-hand motif. Mutation analyses identified five missense mutations in EFHC1 that cosegregated with epilepsy or EEG polyspike wave in affected members of six unrelated families with JME and did not occur in 382 control individuals. Overexpression of EFHC1 in mouse hippocampal primary culture neurons induced apoptosis that was significantly lowered by the mutations. Apoptosis was specifically suppressed by SNX-482, an antagonist of R-type voltage-dependent Ca(2+) channel (Ca(v)2.3). EFHC1 and Ca(v)2.3 immunomaterials overlapped in mouse brain, and EFHC1 coimmunoprecipitated with the Ca(v)2.3 C terminus. In patch-clamp analysis, EFHC1 specifically increased R-type Ca(2+) currents that were reversed by the mutations associated with JME.

Population-based and family-based designs to analyze rare variants in complex diseases.

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.

Maternal and offspring dopamine D4 receptor genotypes interact to influence juvenile impulsivity in vervet monkeys.

The merging of psychological and genetic methodologies has led to an increasing appreciation of environmental moderators of the relationships between genotype and phenotype. Here we used a nonhuman-primate model to study the moderating effect of the mother's genotype on the association of a dopamine D4 receptor (DRD4) gene polymorphism with juvenile impulsivity, assessed in a standardized social-challenge test. The results showed that juvenile carriers of the rare 5-repeat variant of the exon III 48-base-pair repeat polymorphism scored significantly higher in social impulsivity than juveniles homozygous for the common 6-repeat allele. In addition, juvenile genotype interacted with maternal genotype to influence impulsivity, with the highest rates of impulsivity found in variant offspring with variant mothers. These results highlight the importance of considering the genotype of the parents in studies of early experience and vulnerability genes for impulsivity-related traits.

Effects on promoter activity of common SNPs in 5' region of GABRB3 exon 1A.

PURPOSE: The ß3 subunit of the γ-aminobutyric acid type A receptors (GABA(A) -Rs) is an essential component of GABA(A) -Rs in fetal, perinatal, and adult mammalian brain. Various transcripts of the ß3 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 GABA(A) signaling. Abnormal epigenetic regulation could be involved in absence seizures.

Hyperglycosylation and reduced GABA currents of mutated GABRB3 polypeptide in remitting childhood absence epilepsy.

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.

PTSD and dopaminergic genes, DRD2 and DAT, in multigenerational families exposed to the Spitak earthquake.

The objective of this study was to assess the generality of the association of DRD2 and DAT genes and Post-Traumatic Stress Disorder (PTSD) diagnosis/symptom severity. Two hundred ethnic Armenians from 12 multigenerational families exposed to the catastrophic 1988 Spitak earthquake were studied. Common polymorphisms A1/A2 alleles of the DRD2 and '9' repeat allele of DAT gene were genotyped. Heritability, association and linkage were assessed using variance component genetic analyses. After adjusting for the covariates, the heritabilities of PTSD diagnosis and B and C category symptoms were: 0.37, 0.75 and 0.39 respectively. Category D symptoms were not heritable. Neither the DRD2 nor the DAT polymorphisms explained the variation seen in PTSD diagnosis, total PTSD symptom severity, and categories B and C symptom severities. These findings contradict prior reports of positive associations between both DRD2 and DAT, and PTSD.

DNA variants in coding region of EFHC1: SNPs do not associate with juvenile myoclonic epilepsy.

PURPOSE: Juvenile myoclonic epilepsy (JME) accounts for 3 to 12% of all epilepsies. In 2004, we identified a mutation-harboring Mendelian gene that encodes a protein with one EF-hand motif (EFHC1) in chromosome 6p12. We observed one doubly heterozygous and three heterozygous missense mutations in EFHC1 segregating as an autosomal dominant gene with 21 affected members of six Hispanic JME families from California and Mexico. In 2006, similar and three novel missense mutations were reported in sporadic and familial Caucasian JME from Italy and Austria. In this study, we asked if coding single nucleotide polymorphisms (SNPs) of EFHC1 also contribute as susceptibility alleles to JME with complex genetics. METHODS: We screened using denaturing high-performance liquid chromatography (DHPLC) and then directly sequenced the 11 exons of EFHC1 in 130 unrelated JME probands, their 352 family members, and seven exons of EFHC1 in 400-614 ethnically matched controls. We carried out case-control association studies between 124 unrelated Hispanic JME probands and 552-614 ethnically matched controls using four SNPs, rs3804506, rs3804505, rs1266787, and rs17851770. We also performed family-based association on SNPs rs3804506 and rs3804505 in 84 complete JME families using the Family-Based Association Test (FBAT) program. RESULTS: We found no statistically significant differences between JME probands and controls in case-control association and no genetic transmission disequilibria in family-based association for the tested SNPs. In addition, we identified four new DNA variants in the coding region of EFHC1. CONCLUSION: The four coding SNPs, rs3804506, rs3804505, rs1266787, and rs17851770, of EFHC1 may not be susceptibility alleles for JME.

GAW20: methods and strategies for the new frontiers of epigenetics and pharmacogenomics.

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.

The association of DRD4 and novelty seeking is found in a nonhuman primate model.

OBJECTIVE: The association of novelty seeking with a repeat polymorphism in the coding region of the dopamine D4 receptor gene (DRD4) has been demonstrated in several human populations, but not in others. The objective of this study was to test the generality of the association in a captive nonhuman primate population of known history, using objective methods for assessing novelty seeking and a pedigree-based association design. METHODS: Four hundred and fifty two socially-living vervet monkeys (Cercopithecus aethiops) from a large multigenerational pedigree at the UCLA-VA Vervet Research Colony were studied. Two variants in the 48 base pair repeat in exon III of the DRD4 gene have been found in this population, a six-repeat (92%) and a less common five-repeat (8%). Novelty seeking was measured by the latency to approach a large and potentially threatening novel object placed in the home enclosure. Heritability of novelty seeking and the association of novelty seeking with the DRD4 polymorphism were assessed using variance component modeling as implemented in Sequential Oligogenic Linkage Analysis Routines. RESULTS: The variance component analysis indicated that the DRD4 variant explained a significant portion of the total variance in novelty seeking. The final model included a significant effect of the DRD4 polymorphism (P=0.03), which explained 13% of the phenotypic variance, and a significant remaining genetic effect (h=0. 467+/-0.095, P<0.0001). CONCLUSIONS: The association of DRD4 with novelty seeking has now been replicated in a nonhuman primate species, the vervet monkey.

Juvenile myoclonic epilepsy subsyndromes: family studies and long-term follow-up.

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.

Mutation analyses of genes on 6p12-p11 in patients with juvenile myoclonic epilepsy.

Juvenile myoclonic epilepsy (JME) is a distinct form of idiopathic generalized epilepsy (IGE). One of the candidate regions for human JME has been mapped on chromosome band 6p11-p12 by linkage analyses and is termed EJM1 (MIM 254770). Recently, we reported the reduction of the EJM1 region to 3.5cM that contains 18 genes, the exclusion of three genes (LRRC1, GCLC, KIAA0057) by mutation analyses, and the identification of Myoclonin1/EFHC1 as the EJM1 gene. Here, we describe detailed physical and transcriptome maps of the 3.5cM EJM1 region, and detailed results of mutation analyses for the remained 14 genes (HELO1, GCMA, KIAA0936, FBXO9, GSTA3, GSTA4, PTD011, KIAA0576, LMPB1, IL17F, MCM3, PKHD1, KIAA0105, TFAP2B) in patients with JME. We identified 49 single nucleotide changes in eight genes. Twelve amino acid substitutions occurred in two genes, 11 silent mutations in seven genes, and 26 in the non-coding or intronic regions of seven genes. Twelve amino acid substitutions in the two genes (IL17F, PKHD1) were also observed in healthy control individuals or did not co-segregate with the disease phenotypes in other family members. Thus, the absence of significant and potentially functional mutations in the remaining 14 genes further supports the concept that Myoclonin1/EFHC1 is the EJM1 gene in chromosome 6p12.

Chromosome loci vary by juvenile myoclonic epilepsy subsyndromes: linkage and haplotype analysis applied to epilepsy and EEG 3.5-6.0 Hz polyspike waves.

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.

Genetic Analysis Workshop 19: methods and strategies for analyzing human sequence and gene expression data in extended families and unrelated individuals.

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.

Including endophenotypes as covariates in variance component heritability and linkage analysis.

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.