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Biomedical subjects

V J Vieland

Publications and source records attributed to V J Vieland.

At least 19 recordsLinked to original sources
PubMed2001

Evidence supporting WNT2 as an autism susceptibility gene.

We examined WNT2 as a candidate disease gene for autism for the following reasons. First, the WNT family of genes influences the development of numerous organs and systems, including the central nervous system. Second, WNT2 is located in the region of chromosome 7q31-33 linked to autism and is adjacent to a chromosomal breakpoint in an individual with autism. Third, a mouse knockout of Dvl1, a member of a gene family essential for the function of the WNT pathway, exhibits a behavioral phenotype characterized primarily by diminished social interaction. We screened the WNT2 coding sequence for mutations in a large number of autistic probands and found two families containing nonconservative coding sequence variants that segregated with autism in those families. We also identified linkage disequilibrium (LD) between a WNT2 3'UTR SNP and our sample of autism-affected sibling pair (ASP) families and trios. The LD arose almost exclusively from a subgroup of our ASP families defined by the presence of severe language abnormalities and was also found to be associated with the evidence for linkage to 7q from our previously published genomewide linkage screen. Furthermore, expression analysis demonstrated WNT2 expression in the human thalamus. Based on these findings, we hypothesize that rare mutations occur in the WNT2 gene that significantly increase susceptibility to autism even when present in single copies, while a more common WNT2 allele (or alleles) not yet identified may exist that contributes to the disorder to a lesser degree.

Amino Acid Sequence↗
PubMed2001

Power comparisons between the TDT and two likelihood-based methods.

We compare the statistical power of the transmission disequilibrium test (TDT) with that of two likelihood-based linkage tests, the classical LOD score and a modified LOD score in which a linkage disequilibrium (LD) parameter is incorporated into the likelihood (LD-LOD). We hypothesize that, when LD is present, the LD-LOD will have the greatest power of the three tests because the TDT breaks a multiplex pedigree into triads, and the LOD score has previously been shown to have lower power when LD is present but not accounted for. We test this hypothesis using a simulation study in which we generate affected sib-pair (ASP) pedigrees under a range of genetic models, varying the genotypic relative risk (GRR) from 6 to 16. Because the likelihood-based tests require that a genetic model be specified, we compare the tests under two scenarios. First, we assume the true genetic model in the analysis, and second, we compare the tests when the LD-LOD (LOD) is maximized over two wrong genetic models. For the generating models we considered, we find that the LD-LOD has greater power than the TDT even when the genetic models is mis-specified and the results corrected for multiple tests. Extreme differences occur under the multiplicative and dominant models, for which the difference in power is as high as 40% at complete LD. The LOD score provides the lowest power in the presence of LD for the range of GRR considered here.

Adult↗
PubMed2001

Power to detect linkage based on multiple sets of data in the presence of locus heterogeneity: comparative evaluation of model-based linkage methods for affected sib pair data.

The development of rigorous methods for evaluating the overall strength of evidence for genetic linkage based on multiple sets of data is becoming increasingly important in connection with genomic screens for complex disorders. We consider here what happens when we attempt to increase power to detect linkage by pooling multiple independently collected sets of families under conditions of variable levels of locus heterogeneity across samples. We show that power can be substantially reduced in pooled samples when compared to the most informative constituent subsamples considered alone, in spite of the increased sample size afforded by pooling. We demonstrate that for affected sib pair data, a simple adaptation of the lod score (which we call the compound lod), which allows for intersample admixture differences can afford appreciably higher power than the ordinary heterogeneity lod; and also, that a statistic we have proposed elsewhere, the posterior probability of linkage, performs at least as well as the compound lod while having considerable computational advantages. The companion paper (this issue, pp 217-225) shows further that in application to multiple data sets, familiar model-free methods are in some sense equivalent to ordinary lod scores based on data pooling, and that they therefore will also suffer dramatic losses in power for pooled data in the presence of locus heterogeneity and other complicating factors.

Chromosome Mapping↗
PubMed2001

Comparison of 'model-free' and 'model-based' linkage statistics in the presence of locus heterogeneity: single data set and multiple data set applications.

Earlier work [Knapp et al.: Hum Hered 1994;44:44-51] focusing on affected sib pair (ASP) data established the equivalence between the mean test and a test based on a simple recessive lod score, as well as equivalences between certain forms of the maximum likelihood score (MLS) statistic [Risch: Am J Hum Genet 1990;46:242-253] and particular forms of the lod score. Here we extend the results of Knapp et al. [1994] by reconsidering these equivalences for ASP data, but in the presence of locus heterogeneity. We show that Risch's MLS statistic under the possible triangle constraints [Holmans: Am J Hum Genet 1993;52:362-374] is locally equivalent to the ordinary heterogeneity lod score assuming a simple recessive model (HLOD/R); while the one-parameter MLS assuming no dominance variance is locally equivalent to the (homogeneity) recessive lod. The companion paper (this issue, pp 199-208) showed that when considering multiple data sets in the presence of locus heterogeneity, the HLOD can suffer appreciable losses in power. We show here that in ASP data, these equivalences ensure that this same loss in power is incurred by both forms of the MLS statistic as well. The companion paper also introduced an adaptation of the lod, the compound lod score (HLOD/C). We confirm that the HLOD/C maintains higher power than these 'model-free' methods when applied to multiple heterogeneous data sets, even when it is calculated assuming the wrong genetic model.

Chromosome Mapping↗
PubMed2000

Drawbacks of GENEHUNTER for larger pedigrees: application to panic disorder.

Large pedigrees can pose a problem for GENEHUNTER linkage analysis software. Differences in two-point and multipoint lodscores were observed when comparing GENEHUNTER to other linkage software. Careful consideration must be given when selecting linkage analysis programs. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:781-783, 2000.

Chromosome Mapping↗
PubMed2000

Effect of allelic heterogeneity on the power of the transmission disequilibrium test.

Due in part to an influential paper by Risch and Merikangas [(1996) Science 273:1516-1517], which suggested that disequilibrium tests would have greater power to detect genes of small effect than would linkage tests, interest in the use of the Transmission Disequilibrium Test (TDT) as an analysis tool for genomewide studies is steadily growing. However, the paper by Risch and Merikangas made several simplifying assumptions. One such assumption was that the underlying gene showed allelic homogeneity, and another was that the allele being measured was the actual susceptibility allele. Here we investigate the effect of allelic heterogeneity on the power of the TDT using multiplicative, additive, dominant, and recessive modes of inheritances in the context of a genomewide study. We further distinguish two cases: first, that the marker alleles are the actual susceptibility alleles, and second, that alleles are measured at a marker linked to the disease gene with zero recombination. We consider two family structures, either a single affected offspring (SAO) and two parents, or an affected sib-pair (ASP) and two parents. We find that, as expected, the power of the TDT declines as the number of susceptibility alleles at the locus being tested increases and the effect on power can be substantial. When a linked marker is measured rather than a susceptibility allele itself, sample sizes reach unattainable levels when as few as two susceptibility alleles are present. Across all the models we consider, the required number of families for a TDT with ASP sampling varies from 19 to over a million families. Thus, the TDT may not be an optimal test in the context of genomic screens under more biologically realistic assumptions.

Alleles↗
PubMed2000

The consistency of the posterior probability of linkage.

When searching for trait loci along the genome, properly incorporating prior genomic information into the analysis will almost certainly increase the chance of success. Recently, we devised a method that utilizes such prior information in the mapping of trait genes for complex disorders (Vieland, 1998; Wang el al. 1999; Vieland et al. 2000). This method uses the posterior probability of linkage (PPL) based on the admixture model as a measure of linkage information. In this paper, we study the consistency of the PPL. It is shown that, as the number of pedigrees increases, the PPL converges in probability to 1 when there is linkage between the marker and a trait locus, and converges to 0 otherwise. This conclusion is shown to be true for general pedigrees and trait models, even, when the likelihood functions are based on misspecified trait models. As part of the effort to prove this conclusion, it is shown that when there is no linkage, the maximum likelihood estimator of the recombination fraction in the admixture model is asymptotically 0.5, even when the admixture model misrepresents the true model.

Computer Simulation↗
PubMed1999

Further evidence for the increased power of LOD scores compared with nonparametric methods.

In genetic analysis of diseases in which the underlying model is unknown, "model free" methods-such as affected sib pair (ASP) tests-are often preferred over LOD-score methods, although LOD-score methods under the correct or even approximately correct model are more powerful than ASP tests. However, there might be circumstances in which nonparametric methods will outperform LOD-score methods. Recently, Dizier et al. reported that, in some complex two-locus (2L) models, LOD-score methods with segregation analysis-derived parameters had less power to detect linkage than ASP tests. We investigated whether these particular models, in fact, represent a situation that ASP tests are more powerful than LOD scores. We simulated data according to the parameters specified by Dizier et al. and analyzed the data by using a (a) single locus (SL) LOD-score analysis performed twice, under a simple dominant and a recessive mode of inheritance (MOI), (b) ASP methods, and (c) nonparametric linkage (NPL) analysis. We show that SL analysis performed twice and corrected for the type I-error increase due to multiple testing yields almost as much linkage information as does an analysis under the correct 2L model and is more powerful than either the ASP method or the NPL method. We demonstrate that, even for complex genetic models, the most important condition for linkage analysis is that the assumed MOI at the disease locus being tested is approximately correct, not that the inheritance of the disease per se is correctly specified. In the analysis by Dizier et al., segregation analysis led to estimates of dominance parameters that were grossly misspecified for the locus tested in those models in which ASP tests appeared to be more powerful than LOD-score analyses.

Genes, Dominant↗
PubMed1998

Results of a genome-wide genetic screen for panic disorder.

Panic disorder is characterized by spontaneous and recurrent panic attacks, often accompanied by agoraphobia. The results of family, twin, and segregation studies suggest a genetic role in the etiology of the illness. We have genotyped up to 23 families that have a high density of panic disorder with 540 microsatellite DNA markers in a first-pass genomic screen. The thirteen best families (ELOD > 6.0 under the dominant genetic model) have been genotyped with an ordered set of markers encompassing all the autosomes, at an average marker density of 11 cM. Over 110,000 genotypes have been generated on the whole set of families, and the data have been analyzed under both a dominant and a recessive model, and with the program SIBPAIR. No lod scores exceed 2.0 for either parametric model. Two markers give lod scores over 1.0 under the dominant model (chromosomes 1p and 20p), and four do under the recessive model (7p, 17p, 20q, and X/Y). One of these (20p) may be particularly promising. Analysis with SIBPAIR yielded P values equivalent to a lod score of 1.0 or greater (i.e., P < .016, one-sided, uncorrected for multiple tests) for 11 marker loci (2, 7p, 8p, 8q, 9p, 11q, 12q, 16p, 20p and 20q).

Adolescent↗
PubMed1998

Statistical evaluation of age-at-onset anticipation: a new test and evaluation of its behavior in realistic applications.

The discovery that microsatellite repeat expansions can cause clinical disease has fostered renewed interest in testing for age-at-onset anticipation (AOA). A commonly used procedure is to sample affected parent-child pairs (APCPs) from available data sets and to test for a difference in mean age at onset between the parents and the children. However, standard statistical methods fail to take into account the right truncation of both the parent and child age-at-onset distributions under this design, with the result that type I error rates can be inflated substantially. Previously, we had introduced a new test, based on the correct, bivariate right-truncated, age-at-onset distribution. We showed that this test has the correct type I error rate for random APCPs, even for quite small samples. However, in that paper, we did not consider two key statistical complications that arise when the test is applied to realistic data. First, affected pairs usually are sampled from pedigrees preferentially selected for the presence of multiple affected individuals. In this paper, we show that this will tend to inflate the type I error rate of the test. Second, we consider the appropriate probability model under the alternative hypothesis of true AOA due to an expanding microsatellite mechanism, and we show that there is good reason to believe that the power to detect AOA may be quite small, even for substantial effect sizes. When the type I error rate of the test is high relative to the power, interpretation of test results becomes problematic. We conclude that, in many applications, AOA tests based on APCPs may not yield meaningful results.

Age Factors↗
PubMed1997

Investigating the numerical effects of ascertainment bias in linkage analysis: development of methods and preliminary results.

It is general practice to have nonsingle ascertainment of pedigrees for linkage studies, along with intrafamilial sampling that is dependent on who among the related individuals was initially ascertained (Proband dependent or PD sampling). Vieland and Hodge [1995; 1996] have shown that under these conditions, the likelihood used in calculating the lod score is not strictly correct and can produce asymptotically biased estimates of the recombination fraction, theta. However they speculated that this bias would be small in most applications. This paper presents preliminary work aimed at quantifying the numerical magnitude of the bias introduced by PD sampling and nonsingle ascertainment in linkage analysis. We considered five generating models where we varied the ascertainment procedure, intrafamilial sampling scheme, and the sample size for each model. In this limited initial set of simulations, asymptotic bias in theta appears to be trivial, while PD sampling procedures can increase the efficiency of theta. These preliminary results support the view that the advantages of unsystematic ascertainment may offset any small estimation bias that may arise.

Bias↗
PubMed1996

New segregation analysis of panic disorder.

We performed simple segregation analyses of panic disorder using 126 families of probands with DSM-III-R panic disorder who were ascertained for a family study of anxiety disorders at an anxiety disorders research clinic. We present parameter estimates for dominant, recessive, and arbitrary single major locus models without sex effects, as well as for a nongenetic transmission model, and compare these models to each other and to models obtained by other investigators. We rejected the nongenetic transmission model when comparing it to the recessive model. Consistent with some previous reports, we find comparable support for dominant and recessive models, and in both cases estimate nonzero phenocopy rates. The effect of restricting the analysis to families of probands without any lifetime history of comorbid major depression (MDD) was also examined. No notable differences in parameter estimates were found in that subsample, although the power of that analysis was low. Consistency between the findings in our sample and in another independently collected sample suggests the possibility of pooling such samples in the future in order to achieve the necessary power for more complex analyses.

Adult↗
PubMed1996

The essence of single ascertainment.

We propose a fundamental new definition of single ascertainment, namely, that single ascertainment is any ascertainment scheme in which P[pedigree is ascertained/true structure of pedigree] alpha p(theta), where p(theta) is some function of genetic parameters theta but is not a function of pedigree structure. Stated in words: Under single ascertainment, all pedigrees have equal (or proportional with respect to genetic parameters) probabilities of being ascertained, independent of pedigree size or structure. This new definition of single ascertainment allows us to show several results: (1) The correct likelihood consists of the probability of the data conditioned on the observed pedigree, divided by the function p(theta), whether sampling is "proband-independent" or "proband-dependent." (2) More-familiar definitions of single ascertainment all represent special cases of our definition. (3) When p(theta) represents the prevalence of the trait being studied, our definition corresponds to "classical" single ascertainment, i.e., ascertainment through a single "proband." However, the concept of p(theta) can also be generalized to represent the population frequency of configurations of affected relatives (such as affected sib pairs); we call this "generalized single ascertainment."

Mathematical Computing↗
PubMed1996

The problem of ascertainment for linkage analysis.

It is generally believed that ascertainment corrections are unnecessary in linkage analysis, provided individuals are selected for study solely on the basis of trait phenotype and not on the basis of marker genotype. The theoretical rationale for this is that standard linkage analytic methods involve conditioning likelihoods on all the trait data, which may be viewed as an application of the ascertainment assumption-free (AAF) method of Ewens and Shute. In this paper, we show that when the observed pedigree structure depends on which relatives within a pedigree happen to have been the probands (proband-dependent, or PD, sampling) conditioning on all the trait data is not a valid application of the AAF method and will result in asymptotically biased estimates of genetic parameters (except under single ascertainment). Furthermore, this result holds even if the recombination fraction R is the only parameter of interest. Since the lod score is proportional to the likelihood of the marker data conditional on all the trait data, this means that when data are obtained under PD sampling the lod score will yield asymptotically biased estimates of R, and that so-called mod scores (i.e., lod scores maximized over both R and parameters theta of the trait distribution) will yield asymptotically biased estimates of R and theta. Furthermore, the problem appears to be intractable, in the sense that it is not possible to formulate the correct likelihood conditional on observed pedigree structure. In this paper we do not investigate the numerical magnitude of the bias, which may be small in many situations. On the other hand, virtually all linkage data sets are collected under PD sampling. Thus, the existence of this bias will be the rule rather than the exception in the usual applications.

Bias↗
PubMed1995

Identification and mapping of Mendelian subtypes of disease.

We took as our working hypothesis the premise that there could be a single locus of major effect underlying a subset of cases in the simulated Problem 2 data set, and took as our primary goal the task of mapping that locus. Treating the disease as dichotomous and using discriminant function analysis, we were able to separate affected individuals into two disease categories: Disease Type I (DT-I) cases, whose disease was by hypothesis caused by the major locus; and Disease Type II (DT-II) cases, whose disease was by hypothesis produced by other causes. Segregation analysis showed evidence of simple recessive inheritance among the DT-I individuals. Linkage analysis under the best-fitting recessive model gave clear evidence of linkage to D1G2. In the generating model, this marker is linked to a major gene for disease with recombination fraction theta = 0, and the mode of inheritance at that locus is recessive (when the trait is considered as a dichotomy). We conclude that when the true model is complex, focussing on subtypes of disease that show evidence of simple Mendelian inheritance may be a useful first step in determining the underlying model and mapping major genes.

Algorithms↗