Nicola H. Chapman

Genome screens using linkage disequilibrium tests: optimal marker characteristics and feasibility.

Linkage disequilibrium (LD) testing has become a popular and effective method of fine-scale disease-gene localization. It has been proposed that LD testing could also be used for genome screening, particularly as dense maps of diallelic markers become available and automation allows inexpensive genotyping of diallelic markers. We compare diallelic markers and multiallelic markers in terms of sample sizes required for detection of LD, by use of a single marker locus in a case-control study, for rare monophyletic diseases with Mendelian inheritance. We extrapolate from our results to discuss the feasibility of single-marker LD screening in more-complex situations. We have used a deterministic population genetic model to calculate the expected power to detect LD as a function of marker density, age of mutation, number of marker alleles, mode of inheritance of a rare disease, and sample size. Our calculations show that multiallelic markers always have more power to detect LD than do diallelic markers (under otherwise equivalent conditions) and that the ratio of the number of diallelic to the number of multiallelic markers needed for equivalent power increases with mutation age and complexity of mode of inheritance. Power equivalent to that achieved by a multiallelic screen can theoretically be achieved by use of a more dense diallelic screen, but mapping panels of the necessary resolution are not currently available and may be difficult to achieve. Genome screening that uses single-marker LD testing may therefore be feasible only for young (<20 generations), rare, monophyletic Mendelian diseases, such as may be found in rapidly growing genetic isolates.

Linkage analyses of four regions previously implicated in dyslexia: Confirmation of a locus on chromosome 15q

Dyslexia is a common, complex disorder, which is thought to have a genetic component. There have been numerous reports of linkage to several regions of the genome for dyslexia and continuous dyslexia‐related phenotypes. We attempted to confirm linkage of continuous measures of (1) accuracy and efficiency of phonological decoding; and (2) accuracy of single word reading (WID) to regions on chromosomes 2p, 6p, 15q, and 18p, using 111 families with a total of 898 members. We used both single‐marker and multipoint variance components linkage analysis and Markov Chain Monte Carlo (MCMC) joint segregation and linkage analysis for initial inspection of these regions. Positive results were followed with traditional parametric lod score analysis using a model estimated by MCMC segregation analysis. No positive linkage signals were found on chromosomes 2p, 6p, or 18p. Evidence of linkage of WID to chromosome 15q was found with both methods of analysis. The maximum single‐marker parametric lod score of 2.34 was obtained at a distance of 3 cM from D15S143. Multipoint analyses localized the putative susceptibility gene to the interval between markers GATA50C03 and D15S143, which falls between a region implicated in a recent genome screen for attention‐deficit/hyperactivity disorder, and DYX1C1, a candidate gene for dyslexia. This apparent multiplicity of linkage signals in the region for developmental disorders may be the result of errors in map and/or model specification obscuring the pleiotropic effect of a single gene on different phenotypes, or it may reflect the presence of multiple genes. This article contains supplementary material, which may be viewed at the American Journal of Medical Genetics website at http://www.interscience.wiley.com/jpages/0148‐7299:1/suppmat/index.html.

Evaluation of candidate genes for DYX1 and DYX2 in families with dyslexia.

Dyslexia is a common heterogeneous disorder with a significant genetic component. Multiple studies have replicated the evidence for linkage between variously defined phenotypes of dyslexia and chromosomal regions on 15q21 (DYX1) and 6p22.2 (DYX2). Based on association studies and the possibility for functional significance of several polymorphisms, candidate genes responsible for the observed linkage signal have been proposed—DYX1C1 for 15q21, and KIAA0319 and DCDC2 for 6p22.2. We investigated the evidence for contribution of these candidate genes to dyslexia in our sample of multigenerational families. Our previous quantitative linkage analyses in this dataset provided supportive evidence for linkage of dyslexia to the locus on chromosome 15, but not to the locus on chromosome 6. In the current study, we used probands from 191 families for a case control analysis, and proband‐parent trios for family‐based TDT analyses. The observation of weak evidence for transmission disequilibrium for one of the two studied polymorphisms in DYX1C1 suggests involvement of this gene in dyslexia in our dataset. We did not find evidence for the association of KIAA0319 or DCDC2 alleles to dyslexia in our sample. We observed a slight tendency for an intronic deletion in DCDC2 to be associated with worse performance on some quantitative measures of dyslexia in the probands in our sample, but not in their parents.

A genome scan in multigenerational families with dyslexia: Identification of a novel locus on chromosome 2q that contributes to phonological decoding efficiency.

Dyslexia is a common and complex developmental disorder manifested by unexpected difficulty in learning to read. Multiple different measures are used for diagnosis, and may reflect different biological pathways related to the disorder. Impaired phonological decoding (translation of written words without meaning cues into spoken words) is thought to be a core deficit. We present a genome scan of two continuous measures of phonological decoding ability: phonemic decoding efficiency (PDE) and word attack (WA). PDE measures both accuracy and speed of phonological decoding, whereas WA measures accuracy alone. Multipoint variance component linkage analyses (VC) and Markov chain Monte-Carlo (MCMC) multipoint joint linkage and segregation analyses were performed on 108 families. A strong signal was observed on chromosome 2 for PDE using both VC (LOD=2.65) and MCMC methods (intensity ratio (IR)=32.1). The IR is an estimate of the ratio of the posterior to prior probability of linkage in MCMC analysis. The chromosome 2 signal was not seen for WA. More detailed mapping with additional markers provided statistically significant evidence for linkage of PDE to chromosome 2, with VC-LOD=3.0 and IR=59.6 at D2S1399. Parametric analyses of PDE, using a model obtained by complex segregation analysis, provided a multipoint maximum LOD=2.89. The consistency of results from three analytic approaches provides strong evidence for a locus on chromosome 2 that influences speed but not accuracy of phonological decoding.

Evaluation of locus heterogeneity and EXT1 mutations in 34 families with hereditary multiple exostoses

Hereditary multiple exostoses (EXT) is an autosomal dominant disorder characterized by growth of benign bone tumors. Three chromosomal loci have been implicated in this genetically heterogeneous disease: EXT1 at 8q24, EXT2 at 11p13, and EXT3 on 19p. EXT1 and EXT2 were recently cloned. We evaluated 34 families with EXT to estimate the proportion of disease attributable to EXT1, EXT2, and EXT3 and to investigate the spectrum of EXT1 mutations. Linkage analyses combined with heterogeneity testing provides strong evidence in favor of linkage of disease to both chromosomes 8 and 11, but does not support evidence of linkage to chromosome 19 in this data set. The 11 EXT1 exons were PCR‐amplified and sequenced in all 11 isolated cases and in 20 of the 23 familial cases. Twelve different novel EXT1 mutations were detected, including 5 frame‐shift deletions or insertions, 1 codon deletion, and 6 single base‐pair substitutions distributed across 8 of the exons. Only 2 of the mutations were detected in more than one family. Three mutations affect sites in which alterations were previously reported. Nonchain‐terminating missense mutations were identified in codons 280 and 340, both coding for conserved arginine residues. These residues may be crucial to the function of this protein. Although the prevalence of EXT has been estimated to be approximately 1/50,000 individuals, the disease has been reported to occur much more frequently in the Chamorro natives on Guam. Our detection of an EXT1 mutation in one Chamorro subject will allow investigation of a possible founder effect in this population. Combined mutational and heterogeneity analyses in this set of families with multiple exostoses suggest that 66% of our total sample, including 45% of isolated and 77% of familial cases, are attributable to abnormalities in EXT1. Hum Mutat 11:231–239, 1998.

Genomewide scan for real-word reading subphenotypes of dyslexia: Novel chromosome 13 locus and genetic complexity

Dyslexia is a common learning disability exhibited as a delay in acquiring reading skills despite adequate intelligence and instruction. Reading single real words (real‐word reading, RWR) is especially impaired in many dyslexics. We performed a genome scan, using variance components (VC) linkage analysis and Bayesian Markov chain Monte Carlo (MCMC) joint segregation and linkage analysis, for three quantitative measures of RWR in 108 multigenerational families, with follow up of the strongest signals with parametric LOD score analyses. We used single‐word reading efficiency (SWE) to assess speed and accuracy of RWR, and word identification (WID) to assess accuracy alone. Adjusting SWE for WID provided a third measure of RWR efficiency. All three methods of analysis identified a strong linkage signal for SWE on chromosome 13q. Based on multipoint analysis with 13 markers we obtained a MCMC intensity ratio (IR) of 53.2 (chromosome‐wide P < 0.004), a VC LOD score of 2.29, and a parametric LOD score of 2.94, based on a quantitative‐trait model from MCMC segregation analysis (SA). A weaker signal for SWE on chromosome 2q occurred in the same location as a significant linkage peak seen previously in a scan for phonological decoding. MCMC oligogenic SA identified three models of transmission for WID, which could be assigned to two distinct linkage peaks on chromosomes 12 and 15. Taken together, these results indicate a locus for efficiency and accuracy of RWR on chromosome 13, and a complex model for inheritance of RWR accuracy with loci on chromosomes 12 and 15.

A model for the length of tracts of identity by descent in finite random mating populations

Linkage disequilibrium (LD) reflects coinheritance of an ancestral segment by chromosomes in a population. To begin to understand the effects of population history on the extent of LD, we model the length of a tract of identity-by-descent (IBD) between two chromosomes in a finite, random mating population. The variance of an IBD tract is large: a model described by (Genet. Res. Cambridge 35 (1980) 131) underestimates this variance. Using Fishers concept of junctions, we predict the mean length of an IBD tract, given the age of the population and the population sizes over time. We derive results also for subdivided populations, given times of subdivision events and sizes of the resulting subpopulations. The model demonstrates that population growth and subdivision strongly affect the expected length of an IBD tract in small populations. These effects are less dramatic in large populations.

Segregation analysis of phenotypic components of learning disabilities. II. Phonological decoding

Dyslexia is a common, complex disorder, which is thought to have a genetic component. The study of the genetics of dyslexia is complicated by a lack of consensus on diagnostic criteria, and the probability of genetic heterogeneity—it is possible that deficits in different language processes are caused by different underlying genes. In order to address these difficulties, we study continuous phenotypes that are part of the psychometric test batteries often used to diagnose dyslexia. Prior to embarking on a linkage study, it is helpful to employ segregation analysis, both to identify phenotypes that may be amenable to mapping by linkage analysis, and to determine the best models to use for model based analyses. We study 409 people in 102 nuclear families, and employ (1) oligogenic segregation analysis to estimate the number of quantitative trait loci (QTLs) contributing to each phenotype, and (2) complex segregation analysis in order to identify the most parsimonious inheritance model. In this paper, we consider two measures of phonological decoding ability—word attack and phonemic decoding efficiency. We find evidence for one or two genes of at least modest effect contributing to phonemic decoding efficiency, and the best fitting model is a dominant major gene model with residual familial correlations. For word attack, we find evidence for one or two genes of at least modest effect, and the variation in the trait is best explained by a polygenic model.

Genome Scan of a Nonword Repetition Phenotype in Families with Dyslexia: Evidence for Multiple Loci

To understand the genetic architecture of dyslexia and identify the locations of genes involved, we performed linkage analyses in multigenerational families using a phonological memory phenotype—Nonword Repetition (NWR). A genome scan was first performed on 438 people from 51 families (DS-1) and linkage was assessed using variance components (VC), Bayesian oligogenic (BO), and parametric analyses. For replication, the genome scan and analyses were repeated on 693 people from 93 families (DS-2). For the combined set (DS-C), analyses were performed with all three methods in the regions that were identified in both samples. In DS-1, regions on chromosomes 4p, 6q, 12p, 17q, and 22q exceeded our initial threshold for linkage, with 17q providing a parametric LOD score of 3.2. Analysis with DS-2 confirmed the locations on chromosomes 4p and 12p. The strongest VC and BO signals in both samples were on chromosome 4p in DS-C, with a parametric multipoint LODmax of 2.36 for the 4p locus. Our linkage analyses of NWR in dyslexia provide suggestive and reproducible evidence for linkage to 4p12 and 12p in both samples, and significant evidence for linkage to 17q in one of the samples. These results warrant further studies of phonological memory and chromosomal regions identified here in other datasets.

Identification of novel susceptibility loci for Guam neurodegenerative disease: Challenges of genome scans in genetic isolates

Amyotrophic lateral sclerosis/parkinsonism-dementia complex (ALS/PDC) is a fatal neurodegenerative disease found in the Chamorro people of Guam and other Pacific Island populations. The etiology is unknown, although both genetic and environmental factors appear important. To identify loci for ALS/PDC, we conducted both genome-wide linkage and association analyses, using approximately 400 microsatellite markers, in the largest sample assembled to date, comprising a nearly complete sample of all living and previously sampled deceased cases. A single, large, complex pedigree was ascertained from a village on Guam, with smaller families and a case-control sample ascertained from the rest of Guam by population-based neurological screening and archival review. We found significant evidence for two regions with novel ALS/PDC loci on chromosome 12 and supportive evidence for the involvement of the MAPT region on chromosome 17. D12S1617 on 12p gave the strongest evidence of linkage (maximum LOD score, Z(max) = 4.03) in our initial scan, with additional support in the complete case-control sample in the form of evidence of allelic association at this marker and another nearby marker. D12S79 on 12q also provided significant evidence of linkage (Z(max) = 3.14) with support from flanking markers. Our results suggest that ALS/PDC may be influenced by as many as three loci, while illustrating challenges that are intrinsic in genetic analyses of isolated populations, as well as analytical strategies that are useful in this context. Elucidation of the genetic basis of ALS/PDC should improve our understanding of related neurodegenerative disorders including Alzheimer disease, Parkinson disease, frontotemporal dementia and ALS.