A mutant allele of the beta-chemokine receptor gene CCR5 bearing a 32-basepair (bp) deletion (denoted delta ccr5) which prevents cell invasion by the primary transmitting strain of HIV-1 has recently been characterized. Homozygotes for the mutation are resistant to infection, even after repeated high-risk exposures, but this resistance appears not to be total, as isolated cases of HIV-positive deletion homozygotes are now emerging. The consequence of the heterozygous state is not clear, but it may delay the progression to AIDS in infected individuals. A gene frequency of approximately 10% was found for delta ccr5 in populations of European descent, but no mutant alleles were reported in indigenous non-European populations. As the total number of non-European samples surveyed was small in comparison with the Europeans the global distribution of this mutation is far from clear. We have devised a rapid PCR assay for delta ccr5 and used it to screen 3,342 individuals from a globally-distributed range of populations. We find that delta ccr5 is not confined to people of European descent but is found at frequencies of 2-5% throughout Europe, the Middle East and the Indian subcontinent (Fig. 1). Isolated occurrences are seen elsewhere throughout the world, but these most likely represent recent European gene flow into the indigenous populations. The inter-population differences in delta ccr5 frequency may influence the pattern of HIV transmission and so will need to be incorporated into future predictions of HIV levels.

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.

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.

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.

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 ¼ 2.65) and MCMC methods (intensity ratio (IR) ¼ 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 ¼ 3.0 and IR ¼ 59.6 at D2S1399. Parametric analyses of PDE, using a model obtained by complex segregation analysis, provided a multipoint maximum LOD ¼ 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. Molecular Psychiatry (2005) 10, 699-711.

Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders, characterized by impairment in communication and social interactions, and by repetitive behaviors. ASDs are highly heritable, and estimates of the number of risk loci range from hundreds to > 1000. We considered 7 extended families (size 12 – 47 individuals), each with ≥ 3 individuals affected by ASD. All individuals were genotyped with dense SNP panels. A small subset of each family was typed with whole exome sequence (WES). We used a 3-step approach for variant identification. First, we used family-specific parametric linkage analysis of the SNP data to identify regions of interest. Second, we filtered variants in these regions based on frequency and function, obtaining exactly 200 candidates. Third, we compared two approaches to narrowing this list further. We used information from the SNP data to impute exome variant dosages into those without WES. We regressed affected status on variant allele dosage, using pedigree-based kinship matrices to account for relationships. The p-value for the test of the null hypothesis that variant allele dosage is unrelated to phenotype was used to indicate strength of evidence supporting the variant. A cutoff of p=0.05 gave 28 variants. As an alternative third filter, we required Mendelian inheritance in those with WES, resulting in 70 variants. The imputation and association based approach was effective. We identified four strong candidate genes for ASD (SEZ6L, HISPPD1, FEZF1, SAMD11), all of which have been previously implicated in other studies, or have a strong biological argument for their relevance.

No abstract

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 followup 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 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. 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 segregation analysis 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.