Biomedical subjects

Christopher W Bartlett

Publications and source records attributed to Christopher W Bartlett.

10 recordsLinked to original sources

PubMed2007

Accumulating quantitative trait linkage evidence across multiple datasets using the posterior probability of linkage.

Genome scans for complex disorders are frequently inconclusive, prompting researchers to increase sample size in an effort to obtain stronger evidence. However, increasing sample size in the presence of locus heterogeneity may actually, on average, decrease the linkage signal at a true susceptibility gene. The posterior probability of linkage, or PPL, was specifically designed to address this issue in the context of categorical trait analysis, by appropriately accumulating evidence either for or against linkage as new data are added. We now formulate a quantitative trait (QT) analog, the QT-PPL, which directly measures the evidence that a QT is linked to a genetic marker or location. The new QT-PPL is based on a classical single-locus QT likelihood with the trait parameters (allele frequency, genotypic means and variances) integrated out. We show using simulations that the QT-PPL is robust to two key modeling violations (multiple trait loci and non-normality in the form of excess kurtosis), as well as being inherently ascertainment corrected, and illustrate the advantages of the QT-PPL for accumulating linkage evidence across multiple sets of data compared to other QT linkage methods.

Computer Simulation↗

PubMed2005

Two novel quantitative trait linkage analysis statistics based on the posterior probability of linkage: application to the COGA families.

BACKGROUND: In this paper we apply two novel quantitative trait linkage statistics based on the posterior probability of linkage (PPL) to chromosome 4 from the GAW 14 COGA dataset. Our approaches are advantageous since they use the full likelihood, use full phenotypic information, do not assume normality at the population level or require population/sample parameter estimates; and like other forms of the PPL, they are specifically tailored to accumulate linkage evidence, either for or against linkage, across multiple sets of heterogeneous data. RESULTS: The first statistic uses all quantitative trait (QT) information from the pedigree (QT-posterior probability of linkage, PPL); we applied the QT-PPL to the trait ecb21 (resting electroencephalogram). The second statistic allows simultaneous incorporation of dichotomous trait data into the QT analysis via a threshold model (QTT-PPL); we applied the QTT-PPL to combined data on ecb21 and ALDX1. We obtained a QT-PPL of 96% at GABRB1 and a QT-PPL of 18% at FABP2 while the QTT-PPL was 4% and 2% at the same two loci, respectively. By comparison, the variance-components (VC) method, as implemented in SOLAR, yielded multipoint VC LOD scores of 2.05 and 2.21 at GABRB1 and FABP2, respectively; no other VC LODs were greater than 2. CONCLUSION: The QTT-PPL was only 4% at GABARB1, which might suggest that the underlying ecb21 gene does not also cause ALDX1, although features of the data complicate interpretation of this result.

Alcoholism↗

PubMed2005

Calculation of multipoint likelihoods using flanking marker data: a simulation study.

The calculation of multipoint likelihoods is computationally challenging, with the exact calculation of multipoint probabilities only possible on small pedigrees with many markers or large pedigrees with few markers. This paper explores the utility of calculating multipoint likelihoods using data on markers flanking a hypothesized position of the trait locus. The calculation of such likelihoods is often feasible, even on large pedigrees with missing data and complex structures. Performance characteristics of the flanking marker procedure are assessed through the calculation of multipoint heterogeneity LOD scores on data simulated for Genetic Analysis Workshop 14 (GAW14). Analysis is restricted to data on the Aipotu population on chromosomes 1, 3, and 4, where chromosomes 1 and 3 are known to contain disease loci. The flanking marker procedure performs well, even when missing data and genotyping errors are introduced.

Chromosome Mapping↗

PubMed2005

Evaluation of the chromosome 2q37.3 gene CENTG2 as an autism susceptibility gene.

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.

ADP-Ribosylation Factors↗

PubMed2005

Effects of updating linkage evidence across subsets of data: reanalysis of the autism genetic resource exchange data set.

Results of autism linkage studies have been difficult to interpret across research groups, prompting the use of ever-increasing sample sizes to increase power. However, increasing sample size by pooling disparate collections for a single analysis may, in fact, not increase power in the face of genetic heterogeneity. Here, we applied the posterior probability of linkage (PPL), a method designed specifically to analyze multiple heterogeneous data sets, to the Autism Genetic Resource Exchange collection of families by analyzing six clinically defined subsets of the data and updating the PPL sequentially over the subsets. Our results indicate a substantial probability of linkage to chromosome 1, which had been previously overlooked; our findings also provide a further characterization of the possible parent-of-origin effects at the 17q11 locus that were previously described in this sample. This analysis illustrates that the way in which heterogeneity is addressed in linkage analysis can dramatically affect the overall conclusions of a linkage study.

Autistic Disorder↗

PubMed2004

The search for autism disease genes.

Autism is a heritable disorder characterized by phenotypic and genetic complexity. This review begins by surveying current linkage, gene association, and cytogenetic studies performed with the goal of identifying autism disease susceptibility variants. Though numerous linkages and associations have been identified, they tend to diminish upon closer examination or attempted replication. The review therefore explores challenges to current methodologies presented by the complexities of autism that might underlie some of the current difficulties, and finishes by describing emerging phenotypic, statistical, and molecular investigational approaches that offer hope of overcoming those challenges.

Autistic Disorder↗

PubMed2004

Examination of potential overlap in autism and language loci on chromosomes 2, 7, and 13 in two independent samples ascertained for specific language impairment.

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.

Autistic Disorder↗

PubMed2003

Specific language impairment in families: evidence for co-occurrence with reading impairments.

Two family aggregation studies report the occurrence and co-occurrence of oral language impairments (LIs) and reading impairments (RIs). Study 1 examined the occurrence (rate) of LI and RI in children with specific language impairment (SLI probands), a matched control group, and all nuclear family members. Study 2 included a larger sample of SLI probands, as well as their nuclear and extended family members. Probands and their family members who met specific criteria were classified as language and/or reading impaired based on current testing. In Study 1, the rates of LI and RI for nuclear family members (excluding probands) were significantly higher than those for control family members. In the SLI families, affected family members were more likely to have both LI and RI than either impairment alone. In Study 2, 68% of the SLI probands also met the diagnostic classification for RI. The language and RI rates for the other family members, excluding probands, were 25% and 23% respectively, with a high degree of co-occurrence of LI and RI (46%) in affected individuals. Significant sex ratio differences were found across generations in the families of SLI probands. There were more male than female offspring in these families, and more males than females were found to have both LIs and RIs. Results demonstrate that when LIs occur within families of SLI probands, these impairments generally co-occur with RIs. Our data are also consistent with prior findings that males show impairments more often than females.

Adult↗

PubMed2002

A major susceptibility locus for specific language impairment is located on 13q21.

Children who fail to develop language normally-in the absence of explanatory factors such as neurological disorders, hearing impairment, or lack of adequate opportunity-are clinically described as having specific language impairment (SLI). SLI has a prevalence of approximately 7% in children entering school and is associated with later difficulties in learning to read. Research indicates that genetic factors are important in the etiology of SLI. Studies have consistently demonstrated that SLI aggregates in families. Increased monozygotic versus dizygotic twin concordance rates indicate that heredity, not just shared environment, is the cause of the familial clustering. We have collected five pedigrees of Celtic ancestry that segregate SLI, and we have conducted genomewide categorical linkage analysis, using model-based LOD score techniques. Analysis was conducted under both dominant and recessive models by use of three phenotypic classifications: clinical diagnosis, language impairment (spoken language quotient <85) and reading discrepancy (nonverbal IQ minus non-word reading >15). Chromosome 13 yielded a maximum multipoint LOD score of 3.92 under the recessive reading discrepancy model. Simulation to correct for multiple models and multiple phenotypes indicated that the genomewide empirical P value is <.01. As an alternative measure, we also computed the posterior probability of linkage (PPL), obtaining a PPL of 53% in the same region. One other genomic region yielded suggestive results on chromosome 2 (multipoint LOD score 2.86, genomic P value <.06 under the recessive language impairment model). Our findings underscore the utility of traditional LOD-score-based methods in finding genes for complex diseases, specifically, SLI.

Autistic Disorder↗

PubMedDate not supplied

Three autism candidate genes: a synthesis of human genetic analysis with other disciplines.

Autism is a particularly complex disorder when considered from virtually any methodological framework, including the perspective of human genetics. We first present a review of the genetic analysis principles relevant for discussing autism genetics research. From this body of work we highlight results from three candidate genes, REELIN (RELN), SEROTONIN TRANSPORTER (5HTT), and ENGRAILED 2 (EN2) and discuss the relevant neuroscience, molecular genetics, and statistical results that suggest involvement of these genes in autism susceptibility. As will be shown, the statistical results from genetic analysis, when considered alone, are in apparent conflict across research groups. We use these three candidate genes to illustrate different problems in synthesizing results from non-overlapping research groups examining the same problem. However, when basic genetic principles and results from other scientific disciplines are incorporated into a unified theoretical framework, at least some of the difficulties with interpreting results can be understood and potentially overcome as more data becomes available to the field of autism research. Integrating results from several scientific frameworks provides new hypotheses and alternative data collection strategies for future work.

Autistic Disorder↗