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At least 289 records · Page 16Linked to original sources
PubMed2003

Use of multivariate linkage analysis for dissection of a complex cognitive trait.

Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits.

Analysis of Variance↗
PubMed2026

Beyond exons: Linking noncoding heritability and polygenicity across complex human traits and disorders.

The genetic architecture of complex traits spans a continuum of polygenicity, yet it remains unclear how differences in polygenicity relate to the functional localization of SNP heritability across the genome. We use a MiXeR-based framework to partition heritability across 74 functional annotations covering exonic, intronic, and intergenic regions for 34 complex traits and introduce a likelihood-based annotation contribution score that quantifies annotation-specific impact on heritability. Exons account for a minority of heritability, and their contribution decreases with increasing polygenicity, from an average of 22% in less-polygenic somatic diseases and biomarkers to 13% in highly polygenic psychiatric and cognitive phenotypes. Intergenic fractions show the opposite trend, whereas intronic fractions remain relatively stable. Analysis of the broader set of functional annotations also reveals systematic differences along the polygenicity axis: highly polygenic traits show stronger contributions from comparative genomics and variant-effect scores, whereas less-polygenic traits show stronger contributions from promoter, transcription, and chromatin annotations. Together, these results indicate that the functional partitioning of heritability systematically varies with polygenicity, shifting from gene-proximal regulatory architectures to architectures shaped by numerous dispersed regulatory effects.

MiXeR↗
PubMed2006

Genetic and genomic analysis of a fat mass trait with complex inheritance reveals marked sex specificity.

The integration of expression profiling with linkage analysis has increasingly been used to identify genes underlying complex phenotypes. The effects of gender on the regulation of many physiological traits are well documented; however, "genetical genomic" analyses have not yet addressed the degree to which their conclusions are affected by sex. We constructed and densely genotyped a large F2 intercross derived from the inbred mouse strains C57BL/6J and C3H/HeJ on an apolipoprotein E null (ApoE-/-) background. This BXH.ApoE-/- population recapitulates several "metabolic syndrome" phenotypes. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of linkage on sex. We detected several thousand liver gene expression quantitative trait loci, a significant proportion of which are sex-biased. We used these analyses to dissect the genetics of gonadal fat mass, a complex trait with sex-specific regulation. We present evidence for a remarkably high degree of sex-dependence on both the cis and trans regulation of gene expression. We demonstrate how these analyses can be applied to the study of the genetics underlying gonadal fat mass, a complex trait showing significantly female-biased heritability. These data have implications on the potential effects of sex on the genetic regulation of other complex traits.

Adipose Tissue↗
PubMed2004

Predictive genomics of adverse events after cardiac surgery.

Significant, yet highly individual, thrombotic and inflammatory responses to surgery provide an excellent opportunity for insight into the genomic impact upon a patient's postoperative course. Cardiac surgery elicits the most profound perioperative disturbance and is associated with the highest incidence of adverse outcomes of any elective surgical procedure. Thus, cardiac surgical patients are an ideal population in which to evaluate the influence of complex traits on perioperative morbidity and mortality. This review describes the application of fundamental genetics upon the occurrence of adverse outcomes after cardiac surgery and cardiac transplantation. Specific emphases include a brief primer of the principles of genetics concentrating on the effects of variation within the human genome upon clinical outcomes and the differences between so-called Mendelian traits and complex traits. Four important clinical diseases dealt with in this review as examples of the impact of genetic factors on clinical outcomes are the genetics of heparin-induced thrombocytopenia, heart transplantation rejection and vasculopathy, atrial fibrillation, and infection.

Atrial Fibrillation↗
PubMed2006

Positional cloning: complex cardiovascular traits.

Cardiovascular traits represent the quintessential complex trait derived from the confluence of numerous genetic and environmental risk factors. Therefore, positional cloning of cardiovascular genes contributing to the common forms of cardiovascular disease is much more challenging than the mapping and isolation of genes contributing to rare Mendelian phenocopies of cardiovascular disease. Success requires careful and systematic phenotyping, large numbers of families that contain multiple patients, and high-quality genotyping covering for both genome scan and the follow-up case-control association study testing the genes and LD blocks within the linkage peaks.

Cardiovascular Diseases↗
PubMed2004

Mapping multiple quantitative trait Loci for ordinal traits.

Many complex traits in humans and other organisms show ordinal phenotypic variation but do not follow a simple Mendelian pattern of inheritance. These ordinal traits are presumably determined by many factors, including genetic and environmental components. Several statistical approaches to mapping quantitative trait loci (QTL) for such traits have been developed based on a single-QTL model. However, statistical methods for mapping multiple QTL are not well studied as continuous traits. In this paper, we propose a Bayesian method implemented via the Markov chain Monte Carlo (MCMC) algorithm to map multiple QTL for ordinal traits in experimental crosses. We model the ordinal traits under the multiple threshold model, which assumes a latent continuous variable underlying the ordinal phenotypes. The ordinal phenotype and the latent continuous variable are linked through some fixed but unknown thresholds. We adopt a standardized threshold model, which has several attractive features. An efficient sampling scheme is developed to jointly generate the threshold values and the values of latent variable. With the simulated latent variable, the posterior distributions of other unknowns, for example, the number, locations, genetic effects, and genotypes of QTL, can be computed using existing algorithms for normally distributed traits. To this end, we provide a unified approach to mapping multiple QTL for continuous, binary, and ordinal traits. Utility and flexibility of the method are demonstrated using simulated data.

Algorithms↗
PubMed2006

Segregation analysis of a complex quantitative trait: approaches for identifying influential data points.

BACKGROUND/AIMS: Complex traits pose a particular challenge to standard methods for segregation analysis (SA), and for such traits it is difficult to assess the ability of complex SA (CSA) to approximate the true mode of inheritance. Here we use an oligogenic Bayesian Markov chain Monte Carlo method for SA (OSA) to verify results from a single-locus likelihood-based CSA for data on a quantitative measure of reading ability. METHODS: We compared the profile likelihood from CSA, maximized over the trait allele frequency, to the posterior distribution of genotype effects from OSA to explore differences in the overall parameter estimates from SA on the original phenotype data and the same data Winsorized to reduce the potential influence of three outlying data points. RESULTS: Bayesian OSA revealed two modes of inheritance, one of which coincided with the QTL model from CSA. Winsorizing abolished the model originally estimated by CSA; both CSA and OSA identified only the second OSA model. CONCLUSION: Differences between the results from the two methods alerted us to the presence of influential data points, and identified the QTL model best supported by the data. Thus, the Bayesian OSA proved a valuable tool for assessing and verifying inheritance models from CSA.

Alleles↗
PubMed2026

Beyond Exons: Linking Noncoding Heritability and Polygenicity across Complex Human Traits and Disorders.

The genetic architecture of complex traits spans a continuum of polygenicity, yet it remains unclear how differences in polygenicity relate to the functional localization of SNP heritability across the genome. We use a MiXeR-based framework to partition heritability across exonic, intronic, and intergenic regions for 34 traits and introduce a likelihood-based annotation contribution score that quantifies annotation-specific impact on heritability. Exons explain a minority of heritability, and their contribution decreases with increasing polygenicity, from an average of 22% in less polygenic somatic diseases and biomarkers to 13% in highly polygenic psychiatric and cognitive phenotypes. Intergenic fractions show the opposite trend, whereas intronic fractions remain relatively stable. Analysis of a broader set of functional annotations reveals systematic differences along the polygenicity axis: highly polygenic traits show stronger contributions from comparative genomics and variant-effect scores, whereas less polygenic traits show stronger contributions in promoter, transcription, and chromatin annotations. Together, these results indicate that the functional partitioning of heritability systematically varies with polygenicity, pointing to a shift from gene-proximal regulatory architectures to architectures shaped by numerous dispersed regulatory effects as a key determinant of differences in polygenicity across traits.

Journal Article↗
PubMed1997

Genetically complex cardiovascular traits. Origins, problems, and potential solutions.

Modern molecular genetic analysis tools are making it possible for researchers to investigate, and in many cases actually disclose, mutations and other genetic factors that contribute to disease susceptibility. However, the ease with which these factors can be identified is dictated by not only the number of factors underlying or influencing the trait, but also by the manner in which these factors interact. Traits that are influenced by multiple genetic and nongenetic factors are termed "complex" genetic traits and are receiving a great deal of attention in the current medical literature. Hypertension and blood pressure regulation are considered paradigmatic complex traits. In this paper, the origin, nature, and dilemmas associated with the analysis of complex traits are considered. Basic biochemical and physiological determinants of blood pressure are described in an effort to show how genetic complexity could arise within an individual, and fundamental concepts in population genetics and evolutionary theory are discussed to expose the reasons certain forms of genetic complexity can emerge and be sustained in the population at large. Methods for approaching the genetic dissection of complex traits and diseases are also enumerated, with simple descriptions of the scientific motivation offered for each. Problems plaguing these approaches are also discussed. Finally, areas for future research are outlined with the hope of sparking further debate on the subject.

Blood Pressure↗
PubMed2006

The sex-specific genetic architecture of quantitative traits in humans.

Mapping genetically complex traits remains one of the greatest challenges in human genetics today. In particular, gene-environment and gene-gene interactions, genetic heterogeneity and incomplete penetrance make thorough genetic dissection of complex traits difficult, if not impossible. Sex could be considered an environmental factor that can modify both penetrance and expressivity of a wide variety of traits. Sex is easily determined and has measurable effects on recognizable morphology; neurobiological circuits; susceptibility to autoimmune disease, diabetes, asthma, cardiovascular and psychiatric disease; and quantitative traits like blood pressure, obesity and lipid levels, among others. In this study, we evaluated sex-specific heritability and genome-wide linkages for 17 quantitative traits in the Hutterites. The results of this study could have important implications for mapping complex trait genes.

Genetic Linkage↗
PubMed2004

Genetic inheritance of gene expression in human cell lines.

Combining genetic inheritance information, for both molecular profiles and complex traits, is a promising strategy not only for detecting quantitative trait loci (QTLs) for complex traits but for understanding which genes, pathways, and biological processes are also under the influence of a given QTL. As a primary step in determining the feasibility of such an approach in humans, we present the largest survey to date, to our knowledge, of the heritability of gene-expression traits in segregating human populations. In particular, we measured expression for 23,499 genes in lymphoblastoid cell lines for members of 15 Centre d'Etude du Polymorphisme Humain (CEPH) families. Of the total set of genes, 2,340 were found to be expressed, of which 31% had significant heritability when a false-discovery rate of 0.05 was used. QTLs were detected for 33 genes on the basis of at least one P value <.000005. Of these, 13 genes possessed a QTL within 5 Mb of their physical location. Hierarchical clustering was performed on the basis of both Pearson correlation of gene expression and genetic correlation. Both reflected biologically relevant activity taking place in the lymphoblastoid cell lines, with greater coherency represented in Kyoto Encyclopedia of Genes and Genomes database (KEGG) pathways than in Gene Ontology database pathways. However, more pathway coherence was observed in KEGG pathways when clustering was based on genetic correlation than when clustering was based on Pearson correlation. As more expression data in segregating populations are generated, viewing clusters or networks based on genetic correlation measures and shared QTLs will offer potentially novel insights into the relationship among genes that may underlie complex traits.

Cell Line↗
PubMed1998

Fluctuating asymmetry and morphometric variation of hand bones.

The major aim of this study was to test three hypotheses: 1) more complex traits of the hand are less prone to developmental insults and therefore show lower fluctuating asymmetry (FA) as compared with simple traits; 2) the manifestation of FA correlates with the variability of the trait (i.e., CV); and 3) FA is an organ-wide property, and therefore a concordance exists between the FA measures of different traits in hand bones. Seventy-two bilateral measurements of hand bones, were made from plain-film radiographs of 365 cadavers. A complex trait was considered as the total length of the three phalanges of a finger and their contiguous metacarpals. Simple traits were considered to be the lengths of individual bone that made up the complex trait. The following results were obtained: 1) on the average simple traits, composing the complex trait, show much higher FA than the corresponding complex trait, but this result is expected if there is no correlation (or low correlation) between FA of simple traits within the complex trait, due to random direction of right-left differences; 2) strong and highly significant correlation was observed between FA and CV of studied traits, regardless of sex and age of individuals; and 3) the majority of FA measurements of hand bones showed no correlation. However, correlations between some sets of FA traits were highly significant. They were interpreted, although not specifically tested, as the result of a tight relationship between traits related not only developmentally but also by active performance of the same function.

Adolescent↗
PubMed2001

Modeling linkage disequilibrium between a polymorphic marker locus and a locus affecting complex dichotomous traits in natural populations.

Linkage disequilibrium is an important topic in evolutionary and population genetics. An issue yet to be settled is the theory required to extend the linkage disequilibrium analysis to complex traits. In this study, we present theoretical analysis and methods for detecting or estimating linkage disequilibrium (LD) between a polymorphic marker locus and any one of the loci affecting a complex dichotomous trait on the basis of samples randomly or selectively collected from natural populations. Statistical properties of these methods were investigated and their powers were compared analytically or by use of Monte Carlo simulations. The results show that the disequilibrium may be detected with a power of 80% by using phenotypic records and marker genotype when both the trait and marker variants are common (30%) and the LD is relatively high (40-100% of the theoretical maximum). The maximum-likelihood approach provides accurate estimates of the model parameters as well as detection of linkage disequilibrium. The likelihood method is preferred for its higher power and reliability in parameter estimation. The approaches developed in this article are also compared to those for analyzing a continuously distributed quantitative trait. It is shown that a larger sample size is required for the dichotomous trait model to obtain the same level of power in detecting linkage disequilibrium as the continuous trait analysis. Potential use of these estimates in mapping the trait locus is also discussed.

Alleles↗
PubMed2001

Genetic risk factors of venous thrombosis.

Venous thrombosis, whose main clinical presentations include deep vein thrombosis and pulmonary embolism, represents a major health problem worldwide. Numerous conditions are known to predispose to venous thrombosis and these conditions are commonly referred to as risk indicators or risk factors. Generally accepted or "classically" acquired risk factors for venous thromboembolism include advanced age, prolonged immobilisation, surgery, fractures, use of oral contraceptives and hormone replacement therapy, pregnancy, puerperium, cancer and antiphospholipid syndrome. In addition to these well-established risk factors for venous thrombosis, several lines of evidence that have emerged over the past few decades indicate a role of novel genetic risk factors, mainly related to the haemostatic system, in influencing thrombotic risk. The most significant breakthrough has been the confirmation of the concept that inherited hypercoagulable conditions are present in a large proportion of patients with venous thromboembolic disease. These include mutations in the genes that encode antithrombin, protein C and protein S, and the factor V Leiden and factor II G20210 A mutations. Moreover, plasmatic risk indicators, such as hyperhomocysteinemia and elevated concentrations of factors II, VIII, IX, XI and fibrinogen, have also been documented. This extensive list of genetic and acquired factors serves to illustrate that a single cause of venous thrombosis does not exist and that this condition should be considered as a complex or multifactorial trait. Complex traits can be understood by assuming an interaction between different mutations in candidate susceptibility genes. The risk that is associated with each genetic defect may be relatively low in isolation but the simultaneous presence of several mutations may dramatically increase disease susceptibility. Moreover, environmental factors may interact with one or more genetic variations to add further to the risk. The analysis of genetic risk factors and plasmatic factors, together with private life style and environmental factors, has contributed significantly to our understanding of the genetic predisposition to venous thrombosis.

Antithrombins↗
PubMed2001

Enhanced efficiency of quantitative trait loci mapping analysis based on multivariate complexes of quantitative traits.

An approach to increase the efficiency of mapping quantitative trait loci (QTL) was proposed earlier by the authors on the basis of bivariate analysis of correlated traits. The power of QTL detection using the log-likelihood ratio (LOD scores) grows proportionally to the broad sense heritability. We found that this relationship holds also for correlated traits, so that an increased bivariate heritability implicates a higher LOD score, higher detection power, and better mapping resolution. However, the increased number of parameters to be estimated complicates the application of this approach when a large number of traits are considered simultaneously. Here we present a multivariate generalization of our previous two-trait QTL analysis. The proposed multivariate analogue of QTL contribution to the broad-sense heritability based on interval-specific calculation of eigenvalues and eigenvectors of the residual covariance matrix allows prediction of the expected QTL detection power and mapping resolution for any subset of the initial multivariate trait complex. Permutation technique allows chromosome-wise testing of significance for the whole trait complex and the significance of the contribution of individual traits owing to: (a) their correlation with other traits, (b) dependence on the chromosome in question, and (c) both a and b. An example of application of the proposed method on a real data set of 11 traits from an experiment performed on an F(2)/F(3) mapping population of tetraploid wheat (Triticum durum x T. dicoccoides) is provided.

Chromosome Mapping↗
PubMed1998

Medical implications of understanding complex disease traits.

The application of genetic mapping to human disease gene identification has led to the definition of many linkages and a few disease genes in complex traits over the past two years. Its application has also increased to include aspects of pharmacogenetics relating to pharmacokinetics and pharmacodynamics.

Animals↗
PubMed1994

Genetic approaches to understanding the pathophysiology of complex human traits.

Genetic approaches to understanding the pathophysiology of complex human traits, for example, hypertension, can complement physiologic analyses and are likely to improve our ability to treat or prevent the disease. A particularly useful approach is to perform linkage analysis with candidate genes using intermediate phenotypes. This has proven successful so far in identifying two genes involved in hypertension. The first was a fusion gene mutation which linked the regulatory region of the 11B-hydroxylase gene to the coding sequence for the protein of aldosterone synthetase. This mutant gene is responsible for the condition glucocorticoid-remediable aldosteronism (GRA). The intermediate phenotype used was increased levels of the adrenal steroids 18-oxo and hydroxycortisol. The gene for GRA was identified using a pedigree approach. It is likely, to identify other genes in hypertension, that the most appropriate population to be affected would be sib pairs, that is, sibling pairs who both have hypertension. In a recent study the angiotensinogen gene also was linked to hypertension in individuals who had severe or early onset hypertension. In addition, a variant of the angiotensinogen gene, substitution of threonine rather than methionine at codon 235, was specifically associated with hypertension. In a separate study, the T235 homozygote of the angiotensinogen gene was associated with the non-modulating intermediate phenotype of essential hypertension. Since converting enzyme inhibitors appear to correct the specific defect underlying the elevated blood pressure in non-modulators, identification of the gene potentially associated with non-modulation raises the strong possibility that genetic screening will allow for more specific therapy.

Alleles↗
PubMed2005

An integrative genomics approach to infer causal associations between gene expression and disease.

A key goal of biomedical research is to elucidate the complex network of gene interactions underlying complex traits such as common human diseases. Here we detail a multistep procedure for identifying potential key drivers of complex traits that integrates DNA-variation and gene-expression data with other complex trait data in segregating mouse populations. Ordering gene expression traits relative to one another and relative to other complex traits is achieved by systematically testing whether variations in DNA that lead to variations in relative transcript abundances statistically support an independent, causative or reactive function relative to the complex traits under consideration. We show that this approach can predict transcriptional responses to single gene-perturbation experiments using gene-expression data in the context of a segregating mouse population. We also demonstrate the utility of this approach by identifying and experimentally validating the involvement of three new genes in susceptibility to obesity.

11-beta-Hydroxysteroid Dehydrogenase Type 1↗