PBAP: a pipeline for file processing and quality control of pedigree data with dense genetic markers.

MOTIVATION: Huge genetic datasets with dense marker panels are now common. With the availability of sequence data and recognition of importance of rare variants, smaller studies based on pedigrees are again also common. Pedigree-based samples often start with a dense marker panel, a subset of which may be used for linkage analysis to reduce computational burden and to limit linkage disequilibrium between single-nucleotide polymorphisms (SNPs). Programs attempting to select markers for linkage panels exist but lack flexibility. RESULTS: We developed a pedigree-based analysis pipeline (PBAP) suite of programs geared towards SNPs and sequence data. PBAP performs quality control, marker selection and file preparation. PBAP sets up files for MORGAN, which can handle analyses for small and large pedigrees, typically human, and results can be used with other programs and for downstream analyses. We evaluate and illustrate its features with two real datasets. AVAILABILITY AND IMPLEMENTATION: PBAP scripts may be downloaded from http://faculty.washington.edu/wijsman/software.shtml. CONTACT: wijsman@uw.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Whole exome sequencing in extended families with autism spectrum disorder implicates four candidate genes.

Autism spectrum disorders (ASDs) 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.

Clinicians adopting evidence based guidelines: a case study with thromboprophylaxis.

BACKGROUND: Venous Thromboembolism (VTE) is a cause of hospital mortality and managing its morbidity is associated with significant expenditure. Uptake of evidenced based guideline recommendations intended to prevent VTE in hospital settings is sub-optimal. This study was conducted to explore clinicians' attitudes and the clinical environment in which they work to understand their reluctance to adopt VTE prophylaxis guidelines. METHODS: Between February and November 2009, 40 hospital employed doctors from 2 Australian metropolitan hospitals were interviewed in depth. Qualitative data were analysed according to thematic methodology. RESULTS: Analysis of interviews revealed that barriers to evidence based practice include i) the fragmented system of care delivery where multiple members of teams and multiple teams are responsible for each patient's care, and in the case of VTE, where everyone shares responsibility and no-one in particular is responsible; ii) the culture of practice where team practice is tailored to that of the team head, and where medicine is considered an 'art' in which guidelines should be adapted to each patient rather than applied universally. Interviewees recommend clear allocation of responsibility and reminders to counteract VTE risk assessment being overlooked. CONCLUSIONS: Senior clinicians are the key enablers for practice change. They will need to be convinced that guideline compliance adds value to their patient care. Then with the support of systems in the organisation designed to minimize the effects of care fragmentation, they will drive practice changes in their teams. We believe that evidence based practice is only possible with a coordinated program that addresses individual, cultural and organisational constraints.

Genome-scan for IQ discrepancy in autism: evidence for loci on chromosomes 10 and 16.

Performance IQ (PIQ) greater than verbal IQ (VIQ) is often observed in studies of the cognitive abilities of autistic individuals. This characteristic is correlated with social and communication impairments, key parts of the autism diagnosis. We present the first genetic analyses of IQ discrepancy (PIQ-VIQ) as an autism-related phenotype. We performed genome-wide joint linkage and segregation analyses on 287 multiplex families, using a Markov chain Monte Carlo approach. Genetic data included a genome-scan of 387 micro-satellite markers in 210 families augmented with additional markers added in a subset of families. Empirical P values were calculated for five interesting regions. Linkage analysis identified five chromosomal regions with substantial regional evidence of linkage; 10p12 [P = 0.001; genome-wide (gw) P = 0.05], 16q23 (P = .015; gw P = 0.53), 2p21 (P = 0.03, gw P = 0.78), 6q25 (P = 0.047, gw P = 0.91) and 15q23-25 (P = 0.053, gw P = 0.93). The location of the chromosome 10 linkage signal coincides with a region noted in a much earlier genome-scan for autism, and the chromosome 16 signal coincides exactly with a linkage signal for non-word repetition in specific language impairment. This study provides strong evidence for a QTL influencing IQ discrepancy in families with autistic individuals on chromosome 10, and suggestive evidence for a QTL on chromosome 16. The location of the chromosome 16 signal suggests a candidate gene, CDH13, a T-cadherin expressed in the brain, which has been implicated in previous SNP studies of autism and ADHD.

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.

Venous thromboembolism - management in general practice.

The diagnosis, treatment and management of venous thromboembolism prophylaxis are increasingly becoming the responsibility of the general practitioner. Effective treatments exist, as do guidelines for management of hospitalised patients. However, very little research has been done into the implementation of management strategies in community based patients. In 2008, an estimated 15 000-23 000 Australians experienced venous thromboembolism (VTE), which includes deep vein thrombosis (DVT) and pulmonary embolism (PE). Retrospective studies report mortality rates following VTE of 5-23%, although in symptomatic patients with adequate anticoagulation, mortality is 1-2%.

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 LOD(max) 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.

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.

Segregation analysis of a complex quantitative trait: approaches for identifying influential data points.

BACKGROUND/AIMS: Complex traits pose a particular challenge to standard methods for segregation analysis (SA), and for such traits it is difficult to assess the ability of complex SA (CSA) to approximate the true mode of inheritance. Here we use an oligogenic Bayesian Markov chain Monte Carlo method for SA (OSA) to verify results from a single-locus likelihood-based CSA for data on a quantitative measure of reading ability. METHODS: We compared the profile likelihood from CSA, maximized over the trait allele frequency, to the posterior distribution of genotype effects from OSA to explore differences in the overall parameter estimates from SA on the original phenotype data and the same data Winsorized to reduce the potential influence of three outlying data points. RESULTS: Bayesian OSA revealed two modes of inheritance, one of which coincided with the QTL model from CSA. Winsorizing abolished the model originally estimated by CSA; both CSA and OSA identified only the second OSA model. CONCLUSION: Differences between the results from the two methods alerted us to the presence of influential data points, and identified the QTL model best supported by the data. Thus, the Bayesian OSA proved a valuable tool for assessing and verifying inheritance models from CSA.

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.

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.

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.

The effect of population history on the lengths of ancestral chromosome segments.

An isolated population is a group of individuals who are descended from a founding population who lived some time ago. If the founding individuals are assumed to be noninbred and unrelated, a chromosome sampled from the population can be represented as a mosaic of segments of the original ancestral types. A population in which chromosomes are made up of a few long segments will exhibit linkage disequilibrium due to founder effect over longer distances than a population in which the chromosomes are made up of many short segments. We study the length of intact ancestral segments by obtaining the expected number of junctions (points where DNA of two distinct ancestral types meet) in a chromosome. Assuming random mating, we study analytically the effects of population age, growth patterns, and internal structure on the expected number of junctions in a chromosome. We demonstrate that the type of growth a population has experienced can influence the expected number of junctions, as can population subdivision. These effects are substantial only when population sizes are very small. We also develop an approximation to the variance of the number of junctions and show that the variance is large.