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The major determinant of disease severity in Duchenne muscular dystrophy (DMD) or milder Becker muscular dystrophy (BMD) is whether the dystrophin gene (DMD) mutation truncates the mRNA reading frame or allows expression of a partially functional protein. However, even in the complete absence of dystrophin, variability in disease severity is observed, and candidate gene studies have implicated several genes as modifiers. Here we present the largest genome-wide search to date for loci influencing severity in N= 419 DMD patients. Availability of subjects for such studies is quite limited, leading to modest sample sizes, which present a challenge for GWAS design. We have therefore taken special steps to minimize heterogeneity within our dataset at the DMDlocus itself, taking a novel approach to mutation classification to effectively exclude the possibility of residual dystrophin expression, and utilized statistical methods that are well adapted to smaller sample sizes, including the use of a novel linear regression-like residual for time to ambulatory loss and the application of evidential statistics for the GWAS approach. Finally, we applied an unbiased in silico pipeline, utilizing functional genomic datasets to explore the potential impact of the best supported SNPs. In all, we obtained eight SNPs (out of 1,385,356 total) with posterior probability of trait-marker association (PPLD) ≥ 0.4, representing six distinct loci. Our analysis prioritized likely non-coding SNP regulatory effects on six genes (ETAA1, PARD6G, GALNTL6, MAN1A1, ADAMTS19, and NCALD), each with plausibility as a DMD modifier. These results support both recurrent and potentially new pathways for intervention in the dystrophinopathies.

Autism spectrum disorder (ASD) is a relatively common childhood onset neurodevelopmental disorder with a complex genetic etiology. While progress has been made in identifying the de novo mutational landscape of ASD, the genetic factors that underpin the ASD's tendency to run in families are not well understood. In this study, nine extended pedigrees each with three or more individuals with ASD, and others with a lesser autism phenotype, were phenotyped and genotyped in an attempt to identify heritable copy number variants (CNVs). Although these families have previously generated linkage signals, no rare CNV segregated with these signals in any family. A small number of clinically relevant CNVs were identified. Only one CNV was identified that segregated with ASD phenotype; namely, a duplication overlapping DLGAP2in three male offspring each with an ASD diagnosis. This gene encodes a synaptic scaffolding protein, part of a group of proteins known to be pathologically implicated in ASD. On the whole, however, the heritable nature of ASD in the families studied remains poorly understood.

To apply phenotypic and statistical methods designed to account for heterogeneity to linkage analyses of the autism Collaborative Linkage Study of Autism (CLSA) affected sibling pair families.

Autism is a highly heritable neurodevelopmental syndrome with a complex genetic etiology for which no disease genes have yet been definitively identified. We ascertained three subjects with autism spectrum disorders and chromosome 2q37.3 terminal deletions, and refined the deletion breakpoint regions using polymorphism mapping and fluorescence in situ hybridization (FISH) probes. We then genotyped polymorphic markers downstream from the breakpoint region in a sample of autism affected sibling pair families. Both the chromosomal breakpoints and linkage analyses focused our attention on the gene centaurin gamma‐2 (CENTG2), an attractive candidate gene based also on its function and pattern of expression. We therefore assessed CENTG2 for its involvement in autism by (1) screening its exons for variants in 199 autistic and 160 non‐autistic individuals, and (2) genotyping and assessing intra‐genic polymorphisms for linkage and linkage disequilibrium (LD). The exon screen revealed a Ser → Gly substitution in one proband, an Arg → Gly substitution in another, and a number of additional variants unique to the autism families. No unique variants were found in the control subjects. The genotyping produced strong evidence for linkage from two intronic polymorphisms, with a maximum two‐point HLOD value of 3.96 and a posterior probability of linkage (PPL) of 51%. These results were contradicted, however, by substantially weaker evidence for linkage from multi‐point analyses and by no evidence of LD. We conclude, therefore, that 2q37.3 continues to be a region of interest for autism susceptibility, and that CENTG2 is an intriguing candidate gene that merits further scrutiny for its role in autism. © 2005 Wiley‐Liss, Inc.

The posterior probability of linkage (PPL) is a Bayesian statistic which directly measures the probability of linkage between a trait locus and a marker (in the 2-point case) or a genomic region (in the multipoint case). It has several benefits, including ease of interpretation, the ability to incorporate prior genomic information, and a mathematically rigorous and robust procedure for accumulating linkage information across multiple heterogeneous datasets. To date, the majority of work on the PPL has focused on the development of the 2-point statistic, with only preliminary attempts at the development of an equivalent multipoint version. In this paper we present a new way of computing of the multipoint PPL. This new version imputes to each genomic point an estimate of the 2-point PPL we would have obtained from a fully informative marker giving similar evidence for linkage. This version, which we call the imputed PPL, is shown to be superior to previously developed versions.

Specific language impairment is a neurodevelopmental disorder characterized by impairments essentially restricted to the domain of language and language learning skills. This contrasts with autism, which is a pervasive developmental disorder defined by multiple impairments in language, social reciprocity, narrow interests and/or repetitive behaviors. Genetic linkage studies and family data suggest that the two disorders may have genetic components in common. Two samples, from Canada and the US, selected for specific language impairment were genotyped at loci where such common genes are likely to reside. Significant evidence for linkage was previously observed at chromosome 13q21 in our Canadian sample (HLOD 3.56) and was confirmed in our US sample (HLOD 2.61). Using the posterior probability of linkage (PPL) to combine evidence for linkage across the two samples yielded a PPL over 92%. Two additional loci on chromosome 2 and 7 showed weak evidence for linkage. However, a marker in the cystic fibrosis transmembrane conductance regulator (7q31) showed evidence for association to SLI, confirming results from another group (O’Brien et al. 2003). Our results indicate that using samples selected for components of the autism phenotype may be a useful adjunct to autism genetics.

This article presents a Bayesian re-analysis of a linkage study of panic disorder Crowe et al. [2001: Am J Med Genet (Neuropsychiatr Genet) 105:105–109]. In the initial analysis Crowe et al. failed to find compelling evidence for linkage based on either LOD scores or NPL scores anywhere in the genome. The maximum LOD score was 2.23 on chromosome 7 at marker D7S2846 (57.79 cM according to Marshfield). Over the past several years we have been developing a Bayesian alternative approach to linkage analysis, based on direct measurement of the posterior probability of linkage (PPL), and have shown elsewhere that this approach has several advantages over the available alternatives for mapping complex-disease genes Vieland [1998: Am J Med Genet 63:947–954]; Wang et al. [1999: Genet Epidemiol 17(Suppl 1):S749–S754]; Wang et al. [2000: Ann Hum Genet 64:533–553]; and Vieland et al. [2001: Hum Hered 51:199–208]. One limitation of this approach in previous applications has been that it required the investigator to specify a fixed genetic model for the trait. We employ a new implementation of the PPL that treats the unknown trait model as a vector of nuisance parameters, which is integrated out of the PPL equation. When we apply this new model-integrated version of the PPL to the data of Crowe et al. [2001: Am J Med Genet (Neuropsychiatr Genet) 105:105–109] we obtain much clearer evidence than previously reported for a locus on chromosome 7, with an 80% probability of linkage to marker D7S521. A second location is also identified on chromosome 16 near marker D16S749 (PPL = 24%). The results for the remainder of the genome are consistently low. The two loci identified here are also supported by independent evidence from other studies. © 2003 Wiley-Liss, Inc.

A mutation in the gene FOXP2 was recently identified as being responsible for a complicated speech and language phenotype in a single large extended pedigree. This gene is of interest to autism because it lies in one of the most consistently linked autism chromosomal regions of interest. We therefore tested this gene for its involvement in autism in a large sample of autism families. We completely sequenced the exon containing the mutation, screened the remaining coding sequence using SSCP technology, and identified and genotyped two novel intronic tetranucleotide repeat polymorphisms that were then analyzed for evidence of linkage and linkage disequilibrium (LD). We identified two families in which heterozygous deletions of a small number of glutamines in a long poly-glutamine stretch were found in one parent and the autistic probands; no other non-conservative coding sequence changes were identified. Linkage and LD analyses were performed in 75 affected sibling pair families and in two subgroups of this sample defined by the presence/absence of severe language impairment. One allele appeared to have an opposite pattern of transmission in the language based subgroups, but otherwise the linkage and LD analyses were negative. We conclude that FOXP2 is unlikely to contribute significantly to autism susceptibility. © 2002 Wiley-Liss, Inc.

AbstractMaximizing the homogeneity lod is known to be an appropriate procedure for estimating parameters of the trait model in an approximately ‘ascertainment assumption free’ (AAF) manner. We have investigated whether this same property also holds for the heterogeneity lod (HLOD). We show that, when the genetic models at linked and unlinked loci differ, HLODs are not AAF, and maximizing the HLOD yields parameter estimates that are for all practical purposes meaningless; indeed, the admixture parameter α does not even measure the proportion of linked families within the sample, as is commonly supposed. In spite of this, our results confirm a large body of evidence supporting the use of HLODs as robust tools for linkage detection, and suggest further that maximizing the HLOD over both α and parameters of the trait model can improve accuracy in estimation of the recombination fraction θ. These findings have important implications for the optimal handling of nuisance parameters in linkage analysis, particularly when evaluating the evidence for or against linkage based on multiple independent heterogeneous sets of data.Copyright © 2002 S. Karger AG, Basel

AbstractIt is well known that the asymptotic null distribution of the homogeneity lod score (LOD) does not depend on the genetic model specified in the analysis. When appropriately rescaled, the LOD is asymptotically distributed as 0.5 =χ20+ 0.5 =χ21, regardless of the assumed trait model. However, because locus heterogeneity is a common phenomenon, the heterogeneity lod score (HLOD), rather than the LOD itself, is often used in gene mapping studies. We show here that, in contrast with the LOD, the asymptotic null distribution of the HLOD does depend upon the genetic model assumed in the analysis. In affected sib pair (ASP) data, this distribution can be worked out explicitly as (0.5 – c)=χ20+ 0.5=χ21+ c=χ22, where cdepends on the assumed trait model. E.g., for a simple dominant model (HLOD/D), c is a function of the disease allele frequency p: for p= 0.01, c= 0.0006; while for p= 0.1, c= 0.059. For a simple recessive model (HLOD/R), c= 0.098 independently of p. This latter (recessive) distribution turns out to be the same as the asymptotic distribution of the MLS statistic under the possible triangle constraint, which is asymptotically equivalent to the HLOD/R. The null distribution of the HLOD/D is close to that of the LOD, because the weight con the =χ22component is small. These results mean that the cutoff value for a test of size αwill tend to be smaller for the HLOD/D than the HLOD/R. For example, the α= 0.0001 cutoff (on the lod scale) for the HLOD/D with p= 0.05 is 3.01, while for the LOD it is 3.00, and for the HLOD/R it is 3.27. For general pedigrees, explicit analytical expression of the null HLOD distribution does not appear possible, but it will still depend on the assumed genetic model.Copyright © 2001 S. Karger AG, Basel

We examined WNT2 as a candidate disease gene for autism for the following reasons. First, the WNT family of genes influences the development of numerous organs and systems, including the central nervous system. Second, WNT2 is located in the region of chromosome 7q31–33 linked to autism and is adjacent to a chromosomal breakpoint in an individual with autism. Third, a mouse knockout of Dvl1, a member of a gene family essential for the function of the WNT pathway, exhibits a behavioral phenotype characterized primarily by diminished social interaction. We screened the WNT2 coding sequence for mutations in a large number of autistic probands and found two families containing nonconservative coding sequence variants that segregated with autism in those families. We also identified linkage disequilibrium (LD) between a WNT2 3'UTR SNP and our sample of autism-affected sibling pair (ASP) families and trios. The LD arose almost exclusively from a subgroup of our ASP families defined by the presence of severe language abnormalities and was also found to be associated with the evidence for linkage to 7q from our previously published genomewide linkage screen. Furthermore, expression analysis demonstrated WNT2 expression in the human thalamus. Based on these findings, we hypothesize that rare mutations occur in the WNT2 gene that significantly increase susceptibility to autism even when present in single copies, while a more common WNT2 allele (or alleles) not yet identified may exist that contributes to the disorder to a lesser degree. © 2001 Wiley-Liss, Inc.

AbstractEarlier work [Knapp et al.: Hum Hered 1994;44:44–51] focusing on affected sib pair (ASP) data established the equivalence between the mean test and a test based on a simple recessive lod score, as well as equivalences between certain forms of the maximum likelihood score (MLS) statistic [Risch: Am J Hum Genet 1990;46:242–253] and particular forms of the lod score. Here we extend the results of Knapp et al. [1994] by reconsidering these equivalences for ASP data, but in the presence of locus heterogeneity. We show that Risch’s MLS statistic under the possible triangle constraints [Holmans: Am J Hum Genet 1993;52:362–374] is locally equivalent to the ordinary heterogeneity lod score assuming a simple recessive model (HLOD/R); while the one-parameter MLS assuming no dominance variance is locally equivalent to the (homogeneity) recessive lod. The companion paper (this issue, pp 199–208) showed that when considering multiple data sets in the presence of locus heterogeneity, the HLOD can suffer appreciable losses in power. We show here that in ASP data, these equivalences ensure that this same loss in power is incurred by both forms of the MLS statistic as well. The companion paper also introduced an adaptation of the lod, the compound lod score (HLOD/C). We confirm that the HLOD/C maintains higher power than these ‘model-free’ methods when applied to multiple heterogeneous data sets, even when it is calculated assuming the wrong genetic model.Copyright © 2001 S. Karger AG, Basel

AbstractThe development of rigorous methods for evaluating the overall strength of evidence for genetic linkage based on multiple sets of data is becoming increasingly important in connection with genomic screens for complex disorders. We consider here what happens when we attempt to increase power to detect linkage by pooling multiple independently collected sets of families under conditions of variable levels of locus heterogeneity across samples. We show that power can be substantially reduced in pooled samples when compared to the most informative constituent subsamples considered alone, in spite of the increased sample size afforded by pooling. We demonstrate that for affected sib pair data, a simple adaptation of the lod score (which we call the compound lod), which allows for intersample admixture differences can afford appreciably higher power than the ordinary heterogeneity lod; and also, that a statistic we have proposed elsewhere, the posterior probability of linkage, performs at least as well as the compound lod while having considerable computational advantages. The companion paper (this issue, pp 217–225) shows further that in application to multiple data sets, familiar model-free methods are in some sense equivalent to ordinary lod scores based on data pooling, and that they therefore will also suffer dramatic losses in power for pooled data in the presence of locus heterogeneity and other complicating factors.Copyright © 2001 S. Karger AG, Basel