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Peter M Visscher

Publications and source records attributed to Peter M Visscher.

At least 37 records · Page 2Linked to original sources
PubMed2005

Robust estimation of experimentwise P values applied to a genome scan of multiple asthma traits identifies a new region of significant linkage on chromosome 20q13.

Over 30 genomic regions show linkage to asthma traits. Six asthma genes have been cloned, but the putative loci in many linked regions have not been identified. To search for asthma susceptibility loci, we performed genomewide univariate linkage analyses of seven asthma traits, using 202 Australian families ascertained through a twin proband. House-dust mite sensitivity (Dpter) exceeded the empirical threshold for significant linkage at 102 cM on chromosome 20q13, near marker D20S173 (empirical pointwise P = .00001 and genomewide P = .005, both uncorrected for multiple-trait testing). Atopy, bronchial hyperresponsiveness (BHR), and forced expiratory volume in 1 s (FEV1) were also linked to this region. In addition, 16 regions were linked to at least one trait at the suggestive level, including 12q24, which has consistently shown linkage to asthma traits in other studies. Some regions were expected to be false-positives arising from multiple-trait testing. To address this, we developed a new approach to estimate genomewide significance that accounts for multiple-trait testing and for correlation between traits and that does not require a Bonferroni correction. With this approach, Dpter remained significantly linked to 20q13 (empirical genomewide P = .042), and airway obstruction remained linked to 12q24 at the suggestive level. Finally, we extended this method to show that the linkage of Dpter, atopy, BHR, FEV1, asthma, and airway obstruction to chromosome 20q13 is unlikely to be due to chance and may result from a quantitative trait locus in this region that affects several of these traits.

Adult↗
PubMed2005

Quantitative trait locus analysis of longitudinal quantitative trait data in complex pedigrees.

There is currently considerable interest in genetic analysis of quantitative traits such as blood pressure and body mass index. Despite the fact that these traits change throughout life they are commonly analyzed only at a single time point. The genetic basis of such traits can be better understood by collecting and effectively analyzing longitudinal data. Analyses of these data are complicated by the need to incorporate information from complex pedigree structures and genetic markers. We propose conducting longitudinal quantitative trait locus (QTL) analyses on such data sets by using a flexible random regression estimation technique. The relationship between genetic effects at different ages is efficiently modeled using covariance functions (CFs). Using simulated data we show that the change in genetic effects over time can be well characterized using CFs and that including parameters to model the change in effect with age can provide substantial increases in power to detect QTL compared with repeated measure or univariate techniques. The asymptotic distributions of the methods used are investigated and methods for overcoming the practical difficulties in fitting CFs are discussed. The CF-based techniques should allow efficient multivariate analyses of many data sets in human and natural population genetics.

Chromosome Mapping↗
PubMed2005

Modeling linkage disequilibrium in natural populations: the example of the Soay sheep population of St. Kilda, Scotland.

The use of linkage disequilibrium to localize the genes underlying quantitative traits has received considerable attention in the livestock genetics community over the past few years. This has resulted in the investigation of linkage disequilibrium structures of several domestic livestock populations to assess their potential use in fine-mapping efforts. However, the linkage disequilibrium structure of free-living populations has been less well investigated. As the direct evaluation of linkage disequilibrium can be both time consuming and expensive the use of simulations that include as many aspects of population history as possible is advocated as an alternative. A simulation of the linkage disequilibrium structure of the Soay sheep population of St. Kilda, Scotland, is provided as an example. The simulated population showed significant decline of linkage disequilibrium with genetic distance and low levels of background linkage disequilibrium, indicating that the Soay sheep population is a viable resource for linkage disequilibrium fine mapping of quantitative trait loci.

Age Factors↗
PubMed2005

Mapping quantitative trait loci using linkage disequilibrium: marker- versus trait-based methods.

Two approaches for mapping quantitative trait loci (QTL) using linkage disequilibrium at the population level were investigated. In the trait-based (TB) approach, the frequencies of marker alleles (or genotypes) are compared in individuals selected from the two tails of the trait distribution. The TB approach uses phenotypic information only in the selection step. In the marker-based (MB) approach, the quantitative trait values for the marker genotypes in the selected individuals are compared. The MB approach uses both the difference in marker allele (or genotype) frequencies and the phenotypic values of each marker genotype in the selected samples. We quantify the power of each approach and show that the power of the MB approach is greater than or equal to that of the TB approach. The advantage of the former is expected to increase with increasing number of traits phenotyped. Our accurate predictions obviate the need for elaborate simulation studies.

Humans↗
PubMed2005

Large, consistent estimates of the heritability of cognitive ability in two entire populations of 11-year-old twins from Scottish mental surveys of 1932 and 1947.

Twin studies provide estimates of genetic and environmental contributions to cognitive ability differences, but could be based on biased samples. Here we report whole-population estimates using twins from unique mental surveys in Scotland. The Scottish Mental Surveys of 1st June 1932 (SMS1932) and 4th June 1947 (SMS1947), respectively, administered the same validated verbal reasoning test to almost everyone born in 1921 or 1936 and attending school in Scotland. There were 572 twin pairs from the SMS1932, and 517 pairs from the SMS1947. Information on zygosity was unavailable. A novel application of a mixture distribution was used to estimate genetic and environmental components of verbal reasoning variation by maximum likelihood. We found consistent heritability (approximately 0.70) and shared environment (approximately 0.21) estimates. The estimates did not change substantially when additional quantitative traits (height and weight) were added in a multivariate analysis. More generally for studies in genetics, the methodological innovation developed here implies that large (national) data collections can provide sufficient information on twin pairs to estimate genetic parameters, even without zygosity.

Analysis of Variance↗
PubMed2005

Genome-wide linkage disequilibrium from 100,000 SNPs in the East Finland founder population.

Information about linkage disequilibrium (LD) is important in understanding the genome structure and has its applications in association studies. Here we present the first genome-wide LD study based on a founder population (East Finland). The LD data consist of 118 unrelated individuals and around 480,000 SNP pairs genotyped with the Affymetrix 100K genotyping assay. Using the minor allele frequency (MAF) limit of .05, the squared correlation coefficient between two loci (r(2)) was .48, .37, .28, and .20 for distances of 5, 10, 20, and 40 kb respectively. MAF had a significant effect on the mean r(2) so that the extent of useful LD (r(2) > .3) varied from 17 kb to 80 kb depending on the limit set for the MAF. For D' the effect of MAF was smaller but reflected the possible age of the mutation: SNPs with high MAF had lower D' than those with low MAF. The X chromosome showed higher D' values than autosomes and the extent of useful LD (r(2) > .3) was twice as long on the X chromosome than on the autosomes. Based on the results, LD varies across the genome and is correlated to local recombination rate between and within chromosomes. However, the recombination rate does not explain all the variation found in LD. We also report a number of long chromosomal regions where exceptionally high or low LD were detected.

Alleles↗
PubMed2005

Estimation of the rate of SNP genotyping errors from DNA extracted from different tissues.

High density single nucleotide polymorphism (SNP) genotyping panels provide an alternative to microsatellite markers for genome scans. However, genotype errors have a major impact on power to detect linkage or association and are difficult to detect for SNPs. We estimated error rates with the Affymetrix GeneChip SNP platform in samples from a family with a mixed set of monozygotic (MZ) and dizygotic (DZ) triplets using lymphocyte, buccal DNA and samples from whole genome amplification using the multiple displacement amplification (MDA) technique. The average call rate from 58,960 SNPs for five genomic samples was 99.48%. Comparison of results for the MZ twins showed only three discordant genotypes (concordance rate 99.995%). The mean concordance rate for comparisons of samples from lymphocyte and buccal DNA was 99.97%. Mendelian inconsistencies were identified in 46 SNPs with errors in one or more family members, a rate of 0.022%. Observed genotype concordance rates between parents, between parents and children, and among siblings were consistent with previously reported allele frequencies and Hardy-Weinberg equilibrium. Using the MDA technique, results for two samples had equivalent high accuracy to results with genomic samples. However, the SNP call rate for the remaining seven samples varied from 72.5% to 99.5%, with an average of 86.11%. Quality of the DNA sample following the MDA reaction appears to be the critical factor in SNP call rate for MDA samples. Our results demonstrate highly accurate and reproducible genotyping for the Affymetrix GeneChip Human Mapping Set in lymphocyte and buccal DNA samples.

Adolescent↗
PubMed2004

Theoretical and empirical power of regression and maximum-likelihood methods to map quantitative trait loci in general pedigrees.

Both theoretical calculations and simulation studies have been used to compare and contrast the statistical power of methods for mapping quantitative trait loci (QTLs) in simple and complex pedigrees. A widely used approach in such studies is to derive or simulate the expected mean test statistic under the alternative hypothesis of a segregating QTL and to equate a larger mean test statistic with larger power. In the present study, we show that, even when the test statistic under the null hypothesis of no linkage follows a known asymptotic distribution (the standard being chi(2)), it cannot be assumed that the distribution under the alternative hypothesis is noncentral chi(2). Hence, mean test statistics cannot be used to indicate power differences, and a comparison between methods that are based on simulated average test statistics may lead to the wrong conclusion. We illustrate this important finding, through simulations and analytical derivations, for a recently proposed new regression method for the analysis of general pedigrees to map quantitative trait loci. We show that this regression method is not necessarily more powerful nor computationally more efficient than a maximum-likelihood variance-component approach. We advocate the use of empirical power to compare trait-mapping methods.

Chromosome Mapping↗
PubMed2004

Power of direct vs. indirect haplotyping in association studies.

Haplotype analysis is essential to studies of the genetic factors underlying human disease, but requires a large sample size of phase-known data. Recently, directly haplotyping individuals was suggested as a means of maximizing the phase-known data from a sample. Haplotyping, however, is much more labor-intensive than indirectly inferring haplotypes from genotypes (genotyping). This study uses simulations to compare the power of each methodology to detect associations between a haplotype and a trait or disease locus under conditions of varying linkage disequilibrium. The relative power of haplotyping over genotyping in association studies increases with decreasing sample size, decreasing linkage disequilibrium, increasing [corrected] numbers of marker loci, and decreasing numbers of different haplotypes. In addition, the frequency of the haplotype of interest and the magnitude of its association with the disease affect the power. From a cost-benefit standpoint, genotyping would be favored with large multiplicative risks (relative risk of haplotype >2.5). If case numbers are limiting rather than cost, haplotyping would maximize the information obtained. At small haplotype frequencies (e.g., <0.05), haplotyping is relatively more efficient, but there is little absolute power to detect associations under either methodology. Given the much larger laboratory resources required for direct haplotyping, genotyping would probably be favored under most conditions, but this must be balanced against the unit costs associated with recruitment and phenotyping. In the context of multipurpose, prospective cohort studies (e.g., the UK Biobank study), there may be a general value in establishing a series of directly haplotyped individuals to serve as controls for a number of alternative studies.

Algorithms↗
PubMed2004

Prediction of the confidence interval of quantitative trait Loci location.

In 1997, Darvasi and Soller presented empirical predictions of the confidence interval of quantitative trait loci (QTL) location for dense marker maps in experimental crosses. They showed from simulation results for backcross and F2 populations from inbred lines that the 95% confidence interval was a simple function of sample size and the effect of the QTL. In this study, we derive by theory simple equations that can be used to predict any confidence interval and show that for the 95% confidence interval, they are in good agreement with the empirical results given by Darvasi and Soller. A general form of the confidence interval is given that also applies to other population structures (e.g., collections of sib pairs). Furthermore, the expected shape of the likelihood-ratio-test around the true QTL location is derived, which is shown to be extremely leptokurtic. It is shown that this shape explains why confidence intervals from the Log of Odds (LOD) drop-off method and bootstrap results frequently differ for real data sets.

Animals↗
PubMed2004

Apolipoprotein e gene variability and cognitive functions at age 79: a follow-up of the Scottish mental survey of 1932.

Apolipoprotein E (APOE) genotype is a possible influence on nonpathological cognitive aging. The authors studied 462 community-dwelling, 79-year-old people born in 1921, whose childhood IQ had been assessed in the Scottish Mental Survey of 1932 (Scottish Council for Research in Education, 1933). Adjusting for sex, childhood IQ, and self-reported illnesses, the authors found that those with an APOE e4 allele had significantly lower Wechsler Logical Memory (D. Wechsler, 1987) scores than those without an e4 allele. Those people with APOE s2/e3 genotypes had significantly higher Wechsler Logical Memory scores than e3/s3, who were significantly higher than e3/e4. Neither nonverbal reasoning nor verbal fluency were affected. In this sample, APOE genotype contributed to verbal memory in old age.

Aged↗
PubMed2004

Power of the classical twin design revisited.

Statistical power of the classical twin design was revisited. The approximate sampling variances of a least-squares estimate of the heritability in a univariate analysis and estimate of the genetic correlation coefficient in a bivariate analysis were derived analytically for the ACE model. Statistical power to detect additive genetic variation under the ACE model was derived analytically for least-squares, goodness-of-fit and maximum likelihood-based test statistics. The noncentrality parameter for the likelihood ratio test statistic is shown to be a simple function of the MZ and DZ intraclass correlation coefficients and the proportion of MZ and DZ twin pairs in the sample. All theoretical results were validated using simulation. The derived expressions can be used to calculate power of the classical twin design in a simple and rapid manner.

Analysis of Variance↗
PubMed2004

The use of linear mixed models to estimate variance components from data on twin pairs by maximum likelihood.

It is shown that maximum likelihood estimation of variance components from twin data can be parameterized in the framework of linear mixed models. Standard statistical packages can be used to analyze univariate or multivariate data for simple models such as the ACE and CE models. Furthermore, specialized variance component estimation software that can handle pedigree data and user-defined covariance structures can be used to analyze multivariate data for simple and complex models, including those where dominance and/or QTL effects are fitted. The linear mixed model framework is particularly useful for analyzing multiple traits in extended (twin) families with a large number of random effects.

Algorithms↗
PubMed2004

Linkage disequilibrium in the domesticated pig.

This study investigated the extent of linkage disequilibrium (LD) in two genomic regions (on chromosomes 4 and 7) in five populations of domesticated pigs. LD was measured with D' and tested for significance with the Fisher exact test. Effects of genetic (linkage) distance, chromosome, population, and their interactions on D' were tested both through a linear model analysis of covariance and by a theoretical nonlinear model. The overall result was that (1) the distance explained most of the variability of D', (2) the effect of chromosome was significant, and (3) the effect of population was significant. The significance of the chromosome effect may have resulted from selection and the significance of the population effect illustrates the effects of population structures and effective population sizes on LD. These results suggest that mapping methods based on LD may be valuable even with only moderately dense marker spacing in pigs.

Alleles↗
PubMed2003

Longitudinal variance-components analysis of the Framingham Heart Study data.

The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of the data simultaneously, a mixed-model- based random-regression (RR) approach was used. The RR accounted for the variation in genetic effects (including marker-specific quantitative trait locus (QTL) effects) across time by fitting polynomials of age. The use of a mixed model allowed both fixed (such as sex) and random (such as familial environment) effects to be accounted for appropriately. Using this method we performed a QTL analysis of all of the available adult phenotype data (26,106 phenotypic records). In addition to RR, conventional univariate variance component techniques were applied. The traits of interest were BMI, HDLC, total cholesterol, and height. The longitudinal method allowed the characterization of the change in QTL effects with aging. A QTL affecting BMI was shown to act mainly at early ages.

Adult↗
PubMed2003

Lack of association between polymorphisms in angiotensin-converting-enzyme and methylenetetrahydrofolate reductase genes and normal cognitive ageing in humans.

The hypothesis that polymorphisms at two candidate genes that code for angiotensin-converting-enzyme (ACE) and methylenetetrahydrofolate reductase (MTHFR) are associated with normal cognitive ageing was tested using a sample (n=536) of healthy 80-year-old people who were born in 1921 and whose cognitive ability at age 11 was measured in the Scottish Mental Survey 1932. Cognitive ability at age 11 and age 80 was assessed using the Moray House Test. Cognitive ageing was defined as the change in IQ from age 11 to 80. There was no significant association between the tested ACE and MTHFR polymorphisms and IQ score at age 11, IQ at age 80, and IQ change (all P>0.05). The ACE genotypes deviated significantly from Hardy-Weinberg equilibrium proportions (P=0.02), which could indicate that this gene is under selection. Polymorphisms at the two studied genes are unlikely to be risk factors for normal cognitive ageing.

Aged↗
PubMed2003

Genome scan meta-analysis of schizophrenia and bipolar disorder, part III: Bipolar disorder.

Genome scans of bipolar disorder (BPD) have not produced consistent evidence for linkage. The rank-based genome scan meta-analysis (GSMA) method was applied to 18 BPD genome scan data sets in an effort to identify regions with significant support for linkage in the combined data. The two primary analyses considered available linkage data for "very narrow" (i.e., BP-I and schizoaffective disorder-BP) and "narrow" (i.e., adding BP-II disorder) disease models, with the ranks weighted for sample size. A "broad" model (i.e., adding recurrent major depression) and unweighted analyses were also performed. No region achieved genomewide statistical significance by several simulation-based criteria. The most significant P values (<.01) were observed on chromosomes 9p22.3-21.1 (very narrow), 10q11.21-22.1 (very narrow), and 14q24.1-32.12 (narrow). Nominally significant P values were observed in adjacent bins on chromosomes 9p and 18p-q, across all three disease models on chromosomes 14q and 18p-q, and across two models on chromosome 8q. Relatively few BPD pedigrees have been studied under narrow disease models relative to the schizophrenia GSMA data set, which produced more significant results. There was no overlap of the highest-ranked regions for the two disorders. The present results for the very narrow model are promising but suggest that more and larger data sets are needed. Alternatively, linkage might be detected in certain populations or subsets of pedigrees. The narrow and broad data sets had considerable power, according to simulation studies, but did not produce more highly significant evidence for linkage. We note that meta-analysis can sometimes provide support for linkage but cannot disprove linkage in any candidate region.

Bipolar Disorder↗