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Veronica J Vieland

Publications and source records attributed to Veronica J Vieland.

At least 19 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↗
PubMed2006

Thermometers: something for statistical geneticists to think about.

In human genetics, we measure the strength of statistical evidence using a variety of maximized likelihood ratios, LODs, and empirical p values. I argue here that these statistics have highly undesirable properties as evidence measures when applied to complex disorders. Among other deficiencies, I show that when following up on an interesting finding, they will tend to erroneously indicate diminished evidence as more data are considered (e.g., the LOD will tend to go down at a linked locus as the sample size increases). This violates a fundamental assumption underlying standard linkage and association designs in which we first scan the genome for our best signals, and then follow up at those genomic positions with additional data. I argue here for a coherent theoretical approach to formalizing statistical evidence measures, and derive a set of minimal requirements that any evidence measure should meet, drawing heavily on an analogy with the thermometer. I speculate that measures of evidence that come closer to meeting these requirements will do a better job of finding and characterizing genes, and I propose an alternative evidence metric as a step in this direction.

Genetic Linkage↗
PubMed2006

The incorporation of prior genomic information does not necessarily improve the performance of Bayesian linkage methods: an example involving sex-specific recombination and the two-point PPL.

OBJECTIVE: We continue statistical development of the posterior probability of linkage (PPL). We present a two-point PPL allowing for unequal male and female recombination fractions, thetaM and thetaF, and consider alternative priors on thetaM, thetaF. METHODS: We compare the sex-averaged PPL (PPLSA), assuming thetaM = thetaF, to the sex-specific PPL (PPLSS) in (thetaM, thetaF), in a series of simulations; we also compute the PPLSS using alternative priors on (thetaM, thetaF). RESULTS: The PPLSS based on a prior that ignores prior genomic information on sex specific recombination rates performs essentially identically to the PPLSA, even in the presence of large thetaM, thetaF differences. Moreover, adaptively skewing the prior, to incorporate (correct) genomic information on thetaM, thetaF differences, actually worsens performance of the PPLSS. We demonstrate that this has little to do with the PPLSS per se, but is rather due to extremely high levels of variability in the location of the maximum likelihood estimates of (thetaM, thetaF) in realistic data sets. CONCLUSIONS: Incorporating (correct) prior genomic information is not always helpful. We recommend that the PPLSA be used as the standard form of the PPL regardless of the sex-specific recombination rates in the region of the marker in question.

Bayes Theorem↗
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

Performance comparison of two-point linkage methods using microsatellite markers flanking known disease locations.

The Genetic Analysis Workshop 14 simulated data presents an interesting, challenging, and plausible example of a complex disease interaction in a dataset. This paper summarizes the ease of detection for each of the simulated Kofendrerd Personality Disorder (KPD) genes across all of the replicates for five standard linkage statistics. Using the KPD affection status, we have analyzed the microsatellite markers flanking each of the disease genes, plus an additional 2 markers that were not linked to any of the disease loci. All markers were analyzed using the following two-point linkage methods: 1) a MMLS, which is a standard admixture LOD score maximized over theta, alpha, and mode of inheritance, 2) a MLS calculated by GENEHUNTER, 3) the Kong and Cox LOD score as computed by MERLIN, 4) a MOD score (standard heterogeneity LOD maximized over theta, alpha, and a grid of genetic model parameters), and 5) the PPL, a Bayesian statistic that directly measures the strength of evidence for linkage to a marker. All of the major loci (D1-D4) were detectable with varying probabilities in the different populations. However, the modifier genes (D5 and D6) were difficult to detect, with similar distributions under the null and alternative across populations and statistics. The pooling of the four datasets in each replicate (n = 350 pedigrees) greatly improved the chance of detecting the major genes using all five methods, but failed to increase the chance to detect D5 and D6.

Chromosome Mapping↗
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

The posterior probability of linkage allowing for linkage disequilibrium and a new estimate of disequilibrium between a trait and a marker.

The posterior probability of linkage (PPL) statistic has been developed as a method for the rigorous accumulation of evidence for or against linkage allowing for both intra- and inter-sample heterogeneity. To date, the method has assumed linkage equilibrium between alleles at the trait locus and the marker locus. We now generalize the PPL to allow for linkage disequilibrium (LD), by incorporating variable phase probabilities into the underlying linkage likelihood. This enables us to recover the marginal posterior density of the recombination fraction, integrating out nuisance parameters of the trait model, including the locus heterogeneity (admixture) parameter, as well as a vector of LD parameters. The marginal posterior density can then be updated across data subsets or new data as they become available, while allowing parameters of the trait model to vary between data sets. The method applies immediately to general pedigree structures and to markers with multiple alleles. In the case of SNPs, the likelihood is parameterized in terms of the standard single LD parameter D'; and it therefore affords a mechanism for estimation of D' between the marker and the trait, again, without fixing the parameters of the trait model and allowing for updating across data sets. It is even possible to allow for a different associated allele in different populations, while accumulating information regarding the strength of LD. While a computationally efficient implementation for multi-allelic markers is still in progress, we have implemented a version of this new LD-PPL for SNPs and evaluated its performance in nuclear families. Our simulations show that LD-PPLs tend to be larger than PPLs (stronger evidence in favor of linkage/LD) with increased LD level, under a variety of generating models; while in the absence of linkage and LD, LD-PPLs tend to be smaller than PPLs (stronger evidence against linkage). The estimate of D' also behaves well even in relatively small, heterogeneous samples.

Genes, Dominant↗
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

A case of autism and uniparental disomy of chromosome 1.

We report a male child with autism found to have maternal uniparental disomy (UPD) of chromosome 1. The child met diagnostic criteria for the three symptom domains of autism: language impairment, deficient social communication and excessively rigid and repetitive behaviours. He also had a variety of features often associated with autism, including mild mental retardation, small head circumference, hyperactivity, poor fine motor skills, slightly dysmorphic facial features and a heightened interest in olfactory stimulation. His brother, who did not have chromosome 1 UPD, was also autistic. The mother, but not the father, had a history of psychiatric illness and a number of personality and social traits similar to the core features of autism. The discovery of the cytogenetic abnormality was made during the course of a genome-wide linkage screen, wherein genotypes at 6 out of 17 chromosome 1 markers were non-Mendelian and all transmissions were consistent with UPD. Further genotyping (a total of 54 markers) revealed alternating regions of heterodisomy and isodisomy. Whereas chromosome 1 UPD has not been shown to cause disease by effects on imprinting, numerous reports exist of the abnormality unmasking recessive disease-causing mutations. In agreement with this, one of the regions of isodisomy overlaps an emerging chromosome 1 region of interest in autism located at 150-160 Mb.

Autistic Disorder↗
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↗
PubMed2005

Heterogeneity: GAW Group 15.

This paper summarizes the contributions to Group 15 of Genetic Analysis Workshop (GAW) 14, which focused on methods for dealing with heterogeneity in linkage and association analysis. A variety of methods were employed, ranging from manipulation of the phenotype and/or identification of endophenotypes prior to analysis, to statistical methods allowing for heterogeneity in the analysis of simple dichotomous phenotypes as provided with the data. Overall, it was difficult to draw broad conclusions from these applications. Groups that focused on the simulated data had fairly consistent success in mapping the major genes (but not the two minor genes). However, this appeared to be the case regardless of whether heterogeneity was explicitly modeled, either at the phenotypic or statistical level, with relatively crude statistical methods applied to the simulated simple dichotomous trait Kofendrerd personality disorder also enjoying considerable success.

Alcoholism↗
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↗
PubMed2004

A new method for computing the multipoint posterior probability of linkage.

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.

Bayes Theorem↗
PubMed2003

A model-integrated multipoint Bayesian analysis of hypertension in the Framingham Heart Study data finds little evidence of linkage.

This Genetic Analysis Workshop 13 contribution presents a linkage analysis of hypertension in the Framingham data based on the posterior probability of linkage, or PPL. We dichotomized the phenotype, coding individuals who had been treated for hypertension at any time, as well as those with repeated high blood pressure measurements, as affected. Here we use a new variation on the multipoint PPL that incorporates integration over the genetic model. PPLs were computed for chromosomes 1 through 5, 11, 14, and 17 and remained below the 2% assumed prior probability of linkage for 73% of the locations examined. The maximum PPL of 4.5% was obtained on chromosome 1 at 178 cM. Although this is more than twice the assumed prior probability of linkage, it is well below a level at which we would recommend committing substantial additional resources to molecular follow-up. While the PPL analysis of this data remains inconclusive, Bayesian methodology gives us a clear mechanism for using the information gained here in further studies.

Bayes Theorem↗
PubMed2003

Genome-wide linkage analysis of blood pressure under locus heterogeneity.

We describe a method for mapping quantitative trait loci that allows for locus heterogeneity. A genome-wide linkage analysis of blood pressure was performed using sib-pair data from the Framingham Heart Study. Evidence of linkage was found on four markers (GATA89G08, GATA23D06, GATA14E09, and 049xd2) at a significance level of 0.01. Two of them (GATA14E09 and 049xd2) seem to overlap with linkage signals reported previously, while the other two are not linked to any known signals.

Adult Children↗
PubMed2003

Bayesian analysis of a previously published genome screen for panic disorder reveals new and compelling evidence for linkage to chromosome 7.

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.

Bayes Theorem↗
PubMed2003

Two-locus heterogeneity cannot be distinguished from two-locus epistasis on the basis of affected-sib-pair data.

The observation of multiple linkage signals in the course of conducting genome screens for complex disorders raises the question of whether distinct genes represent independent causes of disease (heterogeneity) or whether they interact to produce the phenotype of interest (epistasis); and there has been a corresponding interest in statistical methods for detecting and/or exploiting the distinction between these two possibilities. At the same time, researchers are increasingly relying on affected-sib-pair (ASP) data. Here, we demonstrate an apparently unrecognized fact about two-locus (2L) models and ASP data, namely, 2L heterogeneity and 2L epistasis cannot, in general, be distinguished from one another on the basis of ASP marker data, as a matter of mathematical principle and therefore regardless of sample size. By the same token, correlations across ASPs in single-locus LOD scores or other measures also cannot be used to distinguish 2L heterogeneity from 2L epistasis. This raises questions about the measurement of gene-gene interactions in terms of patterns of correlation in marker data. Portions of our results carry over to larger pedigree structures as well, as long as only affected individuals are included in analyses; the extent to which our overall findings apply to general pedigrees (including unaffected individuals) remains to be investigated.

Alleles↗