Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “complex trait”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 829 records · Page 46Linked to original sources

Systematic search of susceptibility loci with methods using gametic disequilibrium.

Susceptibility genes are identified for a simulated complex trait by a systematic genome search for linkage between disease and a genetic marker in the presence of gametic disequilibrium. The transmission/disequilibrium tests TDTa or TDTg for multiallelic markers compare transmitted and nontransmitted alleles or the genotypes formed by the two transmitted alleles and the genotypes formed by the two nontransmitted alleles, respectively. With these two tests we were able to identify the two markers D1G31 and D5G23. Under the simulating model these are in fact two susceptibility genes involved in the disease.

Alleles↗

A method for meta-analysis of genome searches: application to simulated data.

Genome searches have been performed for many complex traits, and in some cases several searches have been performed in a single disease. Replication of significant results is rare, and a systematic method of reviewing results from a number of searches is needed. A method for meta-analysis is presented which provides a systematic descriptive overview of the separate analyses while dealing with some of the problems specific to meta-analysis of genome searches. The results of two separate meta-analyses correctly indicate the presence of susceptibility loci on chromosomes 1, 3, and 5 in the GAW11 Problem 2 data.

Genetic Linkage↗

Sex-based linkage analysis of alcoholism.

A high degree of locus heterogeneity is likely in alcoholism, and linkage heterogeneity analysis may be helpful in mapping susceptibility loci. The genetic contribution to alcoholism in females may be higher than in males, and therefore sex of affected individuals was used in linkage analysis. Families with female alcoholics demonstrated evidence for linkage to chromosomes 10p11-p15 and 21q22.1-q22.2 while those with male alcoholics did not provide evidence for linkage to these regions. Sharing of maternal and paternal alleles was also investigated separately, and evidence for linkage of maternal alleles on chromosomes 1 and 8, and paternal alleles on chromosome 2 was observed, suggesting parental origin effects. Mapping of complex traits may benefit from tests of linkage heterogeneity based on sex, and parental origin.

Alcoholism↗

Effects of genotype x sex interaction on linkage analysis of visual event-related evoked potentials.

Autosomal genes contributing to variation in many complex traits are influenced by male or female physiological "environments." Accounting for such genotype-by-sex (G x S) interactions has been shown to be important in quantitative genetic, segregation, and linkage analyses of a number of sexually dimorphic traits. In analyses of data simulated for GAW10, we showed that incorporating sex-specific variance components into a variance components-based linkage method increased the power to detect linkage in a trait that exhibited G x S interaction. The goals of this study of data from the Collaborative Study on the Genetics of Alcoholism (COGA) were to screen the event-related brain potential (ERP) data from COGA participants for G x S interaction, and then to conduct variance components linkage analysis of ERP phenotypes showing evidence of G x S interaction using models incorporating sex-specific variance components. Significant G x S interaction was found in four ERP phenotypes: N100 measured at occipital leads 1 and 2, and P300 measured at occipital leads 1 and 2. In linkage analyses of these traits, the most significant lod score found was that between N100 occipital lead 1 amplitude and marker D7S490. The peak lod score at the D7S490 locus was 2.45 without sex-specific variance components, and 3.25 with sex-specific marker and residual polygenic components.

Alcoholism↗

The effect of genotype and pedigree error on linkage analysis: analysis of three asthma genome scans.

The effects of genotype and relationship errors on linkage results are evaluated in three of the Genetic Analysis Workshop 12 asthma genome scans. A number of errors are detected in the samples. While the evidence for linkage is not striking in any data set with or without error, in some cases the difference in test statistic could support different conclusions. The results provide empirical evidence for the predicted effects of genotype and relationship error and highlight the need for rigorous detection and elimination of data error in complex trait studies.

Adult↗

Using data mining to address heterogeneity in the Southampton data.

When analyzing complex traits such as asthma, heterogeneity needs to be assumed. With this in mind, to identify a more homogeneous group of asthmatic patients, we analyzed the Southampton data using the data mining technique known as the regression tree method and the two most inheritable quantitative phenotypes (LnIgE and RAST) as the target variables. Two-point and multipoint nonparametric linkage analyses were carried out using one of the subgroups as affected. In addition, we performed quantitative trait loci nonparametric linkage analysis using each phenotype as the outcome. The results from the affected-sibpairs method and quantitative linkage analysis were compared.

Adult↗

Linkage analysis of asthma and atopy including models with genomic imprinting.

Asthma and atopy are two closely related, common complex traits in which a number of genetic and environmental factors are suspected to play a role. We have performed parametric and nonparametric multi-marker linkage analysis for the Busselton data set, which is part of problem 1 of Genetic Analysis Workshop 12. In particular, we have focused on the dichotomous trait atopy, as well as on dichotomized versions of the quantitative traits RASTI and loge slope. The lod score analysis with adequate modeling of a parent-of-origin effect, by use of the program GENEHUNTER-IMPRINTING, was a special interest. The most prominent findings are a multipoint mod score of 3.12 at D13S153 for RASTI, and a multipoint mod score of 4.32 at the same locus for atopy, both with four-penetrance imprinting models that point to a gene subject to maternal imprinting. In addition, there are marked differences between imprinting and non-imprinting mod scores. These results corroborate earlier findings of linkage between atopy and D13S153, but add the aspect of paternal gene expression. Furthermore, suggestive evidence for linkage to atopy is found near D6S291, D7S530, and D14S74. The best-fitting models for chromosome 6 and 14 may suggest that genomic imprinting takes plae at these two loci as well.

Adult↗

Life after the screen: making sense of many P-values.

A multiple analytic approach may be useful for analyzing complex traits since different methods extract both similar and distinct, but complementary pieces of information from genome screen data on extended pedigrees. We examined the usefulness of combining p-values both across methods and across adjacent markers, taking into account the observed correlation structure among these p-values. To this end, we employed the recently proposed truncated product method [Zaykin et al., Genet Epidemiol, in press]. It appears that this approach is helpful for visualizing priority regions for follow-up analysis and reducing the number of false-positive linkage signals.

Chromosome Mapping↗

The role of haplotypes in candidate gene studies.

Human geneticists working on systems for which it is possible to make a strong case for a set of candidate genes face the problem of whether it is necessary to consider the variation in those genes as phased haplotypes, or whether the one-SNP-at-a-time approach might perform as well. There are three reasons why the phased haplotype route should be an improvement. First, the protein products of the candidate genes occur in polypeptide chains whose folding and other properties may depend on particular combinations of amino acids. Second, population genetic principles show us that variation in populations is inherently structured into haplotypes. Third, the statistical power of association tests with phased data is likely to be improved because of the reduction in dimension. However, in reality it takes a great deal of extra work to obtain valid haplotype phase information, and inferred phase information may simply compound the errors. In addition, if the causal connection between SNPs and a phenotype is truly driven by just a single SNP, then the haplotype-based approach may perform worse than the one-SNP-at-a-time approach. Here we examine some of the factors that affect haplotype patterns in genes, how haplotypes may be inferred, and how haplotypes have been useful in the context of testing association between candidate genes and complex traits.

Genetic Predisposition to Disease↗

Fine mapping by linkage and association in nuclear family and case-control designs.

This report summarizes the Genetic Analysis Workshop 14 contributions related to fine-mapping strategies, in which examining smaller regions by association with single-nucleotide polymorphisms (SNPs) can yield savings in genotyping and multiple-testing penalties. The aim of the analyses conducted in Group 7 contributions was to localize disease susceptibility loci from either the simulated or the Collaborative Study on the Genetics of Alcoholism (COGA) data within identified regions of linkage. Among the 10 contributions, most groups analyzed the simulated data, one group analyzed the COGA data only, and one group analyzed both data sets. The research questions included evaluation of new methods of analysis, as well as comparisons among alternative methods, analytic strategies, and study designs. Methods of interest included an algorithm for SNP marker ordering, a locally weighted transmission disequilibrium test statistic, a likelihood-ratio test statistic for family-based association in nuclear families, a robust test statistic for case-control association studies, and Bayesian spatial modeling methods for haplotype clustering and association. Evaluations included comparisons among confidence intervals for loci detected via linkage, effects of multiple testing adjustments and trade-offs between type I error and power, comparisons among haplotype-based (multilocus) and genotype-based (multilocus and single-locus) association analyses, and design of fine-mapping and replication studies. While several promising new approaches were identified, further development and evaluation of methods for multiple testing, regression modeling of association with multiple markers and haplotypes, and combined treatment of linkage and association data are necessary if we are to identify many of the genes that contribute to complex traits.

Alcoholism↗

Comparison of methods incorporating quantitative covariates into affected sib pair linkage analysis.

For complex traits, it may be possible to increase the power to detect linkage if one takes advantage of covariate information. Several statistics have been proposed that incorporate quantitative covariate information into affected sib pair (ASP) linkage analysis. However, it is not clear how these statistics perform under different gene-environment (G x E) interactions. We compare representative statistics to each other on simulated data under three biologically-plausible G x E models. We also compared their performance with a model-free method and with quantitative trait locus (QTL) linkage approaches. The statistics considered here are: (1) mixture model; (2) general conditional-logistic model (LODPAL); (3) multinomial logistic regression models (MLRM); (4) extension of the maximum-likelihood-binomial approach (MLB); (5) ordered-subset analysis (OSA); and (6) logistic regression modeling (COVLINK). In all three G x E models, most of these six statistics perform better when using the covariate C1 associated with a G x E interaction effect than when using the environmental risk factor C2 or the random noise covariate C3. Compared with a model-free method without covariates (S(all)), the mixture model performs the best when using C1, with the high-to-low OSA method also performing quite well. Generally, MLB is the least sensitive to covariate choice. However, most of these statistics do not provide better power than S(all). Thus, while inclusion of the "correct" covariate can lead to increased power, careful selection of appropriate covariates is vital for success.

Analysis of Variance↗

Comparison of SNP tagging methods using empirical data: association study of 713 SNPs on chromosome 12q14.3-12q24.21 for asthma and total serum IgE in an African Caribbean population.

Few comparison studies have been performed on single nucleotide polymorphism (SNP) tagging methods to examine their consistency and effectiveness in terms of inferences about association with disease. We applied several SNP tagging methods to SNPs on chromosome 12q (n=713) and compared the utility of these methods to detect association for asthma and serum IgE levels among a sample of African Caribbean families from Barbados selected through asthmatic probands. We found that a high level of information regarding association is retained in Clayton's htSNP, Stram's TagSNP, and de Bakker's Tagger. We also found a high degree of consistency between TagSNP and Tagger. Using this set of 713 SNPs on chromosome 12q, our study provides insight towards analytic strategies for future studies of complex traits.

Asthma↗

The Rise of Plant Pan-Genomes: From Genome Variation to Predictive Breeding.

Plant pan-genomics is entering a new phase beyond genome variation discovery, requiring a shift from cataloguing genomic diversity toward understanding how variation generates biological function and breeding value. Here, we propose that the future of plant pan-genomics will be shaped by three conceptual transitions. First, structural variation (SV), presence-absence variation (PAV), and haplotype diversity should be interpreted not merely as genomic differences, but as regulatory components that influence gene networks, chromatin organization, and complex traits. Second, the expansion from species-level pan-genomes to genus-level super pan-genomes provides an evolutionary framework for uncovering adaptive genetic modules preserved in wild relatives and overlooked during domestication. Third, integrating pan-genomes with pan-omics, three-dimensional genome analyses, and artificial intelligence will enable the transformation of genomic variation into predictive models for crop improvement. We further propose that the ultimate value of pan-genomes lies not in generating increasingly complete genome collections, but in establishing a mechanistic bridge between genome diversity, biological function, and breeding decisions. This transition will move crop improvement from empirical selection toward rational genome design, where evolutionary diversity can be systematically interpreted, predicted, and engineered.

Journal Article↗

The pedigree tool: web-based visualization of a family tree.

We describe the development of a novel tool that facilitates the design and visualization of pedigrees using a special Internet application. The tool is programmed in Java, using a PHP script as an interface. This web-based tool is used to generate, edit, and/or view pedigrees. The advantage of our novel tool is that it is based on a notation that allows the representation of any given number of generations, family members per generation, and multiple clinical or genetic features of an individual family member. In addition, the notation allows us to minimize the storage space by 100% to 500% and to standardize the presentation of family trees and segregation analysis for inheritance of mendelian disorders or even complex traits. This pedigree tool has been implemented with a database of thyroid-stimulating hormone receptor (TSHR) mutations (http://www.uni-leipzig.de/innere/tshr/).

Computer Graphics↗

Single-molecule analysis for molecular haplotyping.

In the genome era, there is great hope that genetic approaches such as linkage equilibrium mapping can be used to study common human disorders using a case-control population association study design. Ideally, the parental chromosomes are marked so that chromosomal regions in the form of haplotypes are compared in these studies to increase the power of association. Determining the haplotypes in a diploid individual is a major technical challenge in genetic studies of complex traits. A molecular approach to haplotyping is therefore highly desirable. Recent advances in DNA preparation, separation, labeling, and image analysis provide hope that a strategy of using a three-dye system coupled with DNA distance measurements between alleles will yield haplotype information of sufficiently high quality for genetic studies. In this work, we present the outline of the major challenges one must meet in developing a robust strategy for SNP detection and molecular haplotyping using single molecule analysis.

Alleles↗

Assessment of multiple displacement amplification for polymorphism discovery and haplotype determination at a highly polymorphic locus, MC1R.

The identification of common genetic variants such as single nucleotide polymorphisms (SNPs) in the human genome has become central in human population genetics and evolution studies, as well as in the study of the genetic basis of complex traits and diseases. Crucial for the accurate identification of genetic variants is the availability of high quality genomic DNA (gDNA). Since popular sources of gDNA (buccal cells, lymphocytes, hair bulb) often do not yield sufficient quantities of DNA for molecular genetic applications, whole genome amplification methods have recently been introduced to generate a renewable source of double-stranded linear DNA. Here, we assess the fidelity of one method, multiple displacement amplification (MDA), which utilizes bacteriophage Phi29 DNA polymerase to generate amplified DNA from an original source of gDNA, in a representative SNP discovery and genetic association study at the melanocortin 1 receptor (MC1R) locus, a highly polymorphic gene in humans involved in skin and hair pigmentation. We observed that MDA has high fidelity for novel SNP discovery and can be a valuable tool in generating a potentially indefinite source of DNA. However, we observed an allele amplification bias that causes genotype miscalls at heterozygous sites. At loci with multiple polymorphic sites in linkage disequilibrium, such as at MC1R, this bias can create a significant number of heterozygote genotype errors that subsequently misrepresents haplotypes.

Alleles↗

Singapore Human Mutation/Polymorphism Database: a country-specific database for mutations and polymorphisms in inherited disorders and candidate gene association studies.

There is a need for country/population-specific databases because the existence of population-specific mutations for single gene disorders is well documented, and there is also good evidence for ethnic differences in the frequencies of genetic variations involved in complex disorders. Thus the Singapore Human Mutation/Polymorphism Database (SHMPD) was created to provide clinicians and scientists access to a central genetic database for the Singapore population. The data catalogued in the database include mutations identified in Singapore for Mendelian diseases, and frequencies of polymorphisms that have been investigated in either healthy controls or samples associated with specific phenotypes. Data from journal articles identified by searches in PubMed and other online resources, and via personal communications with researchers were compiled and assembled into a single database. Genes are categorized alphabetically and are also searchable by name and disease. The information provided for each variant of the gene includes the protein encoded, phenotype association, gender, size, and ethnic origin of the sample, as well as the reported genotype and allele frequencies, and direct links to the corresponding abstracts on PubMed. Our database will facilitate molecular diagnosis of Mendelian disorders and improve study designs for complex traits. It will be useful not only for researchers in Singapore, but also for those in countries with similar ethnic backgrounds, such as China, Taiwan, Hong Kong, Indonesia, and Malaysia.

Alleles↗

Thomas Henry Huxley (1825-1895) puts us in our place.

Thomas Huxley was one of the 19th century's most active defenders of Darwin's idea that life has evolved through natural processes. An anatomist and paleontologist, he extended his energies to science and education policy, the democratization of science, and the broad societal implications of evolution. Since his time the fossil record has greatly improved and the genetic 'revolution' has occurred, deepening our understanding of primate and human evolution in ways that would please Huxley: improved systematics relies heavily on genetic data, and molecular technologies are opening our understanding of the genetic basis of complex traits of traditional anthropological interest-but in ways that are thoroughly dependent on the fact of evolution. A more unified biological synthesis is forming that unites genes, developmental process, structure, and inheritance. But the tempo and mode of evolution remain unresolved. Huxley was one of many who have had trouble accepting Darwin's gradual natural selection as the central evolutionary mechanism, and views spanning the antipodes of gradualism and saltation find advocates even in our genetic era.

Biological Evolution↗