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PubMed2006

Thematic review series: systems biology approaches to metabolic and cardiovascular disorders. Multi-organ whole-genome measurements and reverse engineering to uncover gene networks underlying complex traits.

Together with computational analysis and modeling, the development of whole-genome measurement technologies holds the potential to fundamentally change research on complex disorders such as coronary artery disease. With these tools, the stage has been set to reveal the full repertoire of biological components (genes, proteins, and metabolites) in complex diseases and their interplay in modules and networks. Here we review how network identification based on reverse engineering, as applied to whole-genome datasets from simpler organisms, is now being adapted to more complex settings such as datasets from human cell lines and organs in relation to physiological and pathological states. Our focus is on the use of a systems biological approach to identify gene networks in coronary atherosclerosis. We also address how gene networks will probably play a key role in the development of early diagnostics and treatments for complex disorders in the coming era of individualized medicine.

Animals↗
PubMed2006

PolymiRTS Database: linking polymorphisms in microRNA target sites with complex traits.

Polymorphism in microRNA Target Site (PolymiRTS) database is a collection of naturally occurring DNA variations in putative microRNA target sites. PolymiRTSs may affect gene expression and cause variations in complex phenotypes. The database integrates sequence polymorphism, phenotype and expression microarray data, and characterizes PolymiRTSs as potential candidates responsible for the quantitative trait locus (QTL) effects. It is a resource for studying PolymiRTSs and their implications in phenotypic variations. PolymiRTS database can be accessed at http://compbio.utmem.edu/miRSNP/.

Animals↗
PubMed2006

Natural variation for carbohydrate content in Arabidopsis. Interaction with complex traits dissected by quantitative genetics.

Besides being a metabolic fuel, carbohydrates play important roles in plant growth and development, in stress responses, and as signal molecules. We exploited natural variation in Arabidopsis (Arabidopsis thaliana) to decipher the genetic architecture determining carbohydrate content. A quantitative trait locus (QTL) approach in the Bay-0 x Shahdara progeny grown in two contrasting nitrogen environments led to the identification of 39 QTLs for starch, glucose, fructose, and sucrose contents representing at least 14 distinct polymorphic loci. A major QTL for fructose content (FR3.4) and a QTL for starch content (ST3.4) were confirmed in heterogeneous inbred families. Several genes associated with carbon (C) metabolism colocalize with the identified QTL. QTLs for senescence-related traits, and for flowering time, water status, and nitrogen-related traits, previously detected with the same genetic material, colocalize with C-related QTLs. These colocalizations reflect the complex interactions of C metabolism with other physiological processes. QTL fine-mapping and cloning could thus lead soon to the identification of genes potentially involved in the control of different connected physiological processes.

Arabidopsis↗
PubMed2003

Genetic analysis of a complex trait in the Utah Genetic Reference Project: a major locus for PTC taste ability on chromosome 7q and a secondary locus on chromosome 16p.

The ability to taste phenylthiocarbamide (PTC) shows complex inheritance in humans. We obtained a quantitative measure of PTC tasting ability in 267 members of 26 large three-generation families that were part of a set of CEPH families that had been used for genetic mapping. Significant bimodality was found for the distribution of age and gender adjusted scores (P<0.001), with estimated means of 3.16 (SD=1.80) and 9.26 (SD=1.54). Using the extensive genotyping available in these families from the genetic mapping efforts, we performed a genome scan by using 1324 markers with an average spacing of 4 cM. Analyses were first carried out with a recessive genetic model that has traditionally been assumed for the trait, and a threshold score of 8.0 delineating tasters from non-tasters. In this qualitative analysis, the maximum genome-wide lod score was 4.74 at 246 cM on chromosome 7; 17 families showed segregation of the dichotomous PTC phenotype. No other lod scores were significant; the next highest score was on chromosome 10 (lod=1.64 at 85 cM), followed by chromosome 3 (lod=1.29 at 267 cM). Because PTC taste ability exhibited substantial quantitative variation, the quantitative trait was also analyzed by using a variance components approach in SOLAR. The maximum quantitative genome-wide lod score was 8.85 at 246 cM on chromosome 7. Evidence for other possible quantitative loci was found on chromosomes 1 (lod=2.31 at 344 cM) and 16 (lod=2.01 at 14 cM). A subsequent two-locus whole-genome scan conditional on the chromosome 7 quantitative trait locus identified the chromosome 16 locus (two-locus lod=3.33 at 14 cM).

Adolescent↗
PubMed1997

Unravelling a complex trait: the genetics of insulin-dependent diabetes mellitus.

Insulin-dependent diabetes mellitus (IDDM), also known as type 1 or juvenile diabetes, is one of the first disorders with a complex genetic basis that researchers have begun to unravel. More than 20 years ago, the HLA region was found to contain a major locus that influences predisposition to IDDM, and a decade ago a locus with a smaller effect was identified in the insulin-gene region. With the advent of numerous microsatellite markers suitable for genome screening, an additional 6 loci that influence susceptibility to IDDM have been reported since late 1994. This paper summarizes that progress, with particular emphasis on research conducted by Field and associates. Some of the new loci appear to predispose people to IDDM independently of HLA and may be important factors in families with IDDM who lack strong HLA susceptibility. Other loci may interact to cause susceptibility, and specific combinations may be especially diabetogenic. Although isolating the actual predisposing genes in IDDM is more difficult than isolating those involved in single-locus genetic disorders, the fact that the genes can be identified with the use of a reasonable number of families is very encouraging for future research on other genetically complex disorders.

Diabetes Mellitus, Type 1↗
PubMed1999

Alcoholism as a complex trait: comparison of genetic models and role of epidemiological risk factors.

A genetic component for alcoholism appears likely, but the genes involved have yet to be identified. The mode of inheritance is probably more complex than for traditional mendelian disorders. In particular, there are marked differences in alcoholism by gender, parent-of-origin effects, ethnicity, and other epidemiological factors. We investigated the evidence for the presence of susceptibility genes for alcohol dependence in the Collaborative Study on the Genetics of Alcoholism data set.

Adolescent↗
PubMed2007

The mouse as a model for human biology: a resource guide for complex trait analysis.

The mouse has been a powerful force in elucidating the genetic basis of human physiology and pathophysiology. From its beginnings as the model organism for cancer research and transplantation biology to the present, when dissection of the genetic basis of complex disease is at the forefront of genomics research, an enormous and remarkable mouse resource infrastructure has accumulated. This review summarizes those resources and provides practical guidelines for their use, particularly in the analysis of quantitative traits.

Animals↗
PubMed1999

Exploring genetic analysis of complex traits through the paradigm of alcohol dependence: summary of GAW11 contributions.

We discuss the Genetic Analysis Workshop 11 analyses of data from the Collaborative Study on the Genetics of Alcoholism from a methodological perspective, concentrating on approaches and issues relevant to linkage and association studies of complex human phenotypes. Genome screening by parametric linkage, nonparametric linkage, association, and combined linkage/association methods are discussed. Issues particular to complex disease include etiologic heterogeneity, multivariate phenotype modeling, and parent-of-origin effects. Other methodological topics discussed are new and enhanced methods, ascertainment, weighting of nonindependent sib pairs, and data cleaning and validation.

Alcoholism↗
PubMed2000

Use of population isolates for mapping complex traits.

Geneticists have repeatedly turned to population isolates for mapping and cloning Mendelian disease genes. Population isolates possess many advantages in this regard. Foremost among these is the tendency for affected individuals to share ancestral haplotypes derived from a handful of founders. These haplotype signatures have guided scientists in the fine mapping of scores of rare disease genes. The past successes with Mendelian disorders using population isolates have prompted unprecedented interest among medical researchers in both the public and private sectors. Despite the obvious genetic and environmental complications, geneticists have targeted several population isolates for mapping genes for complex diseases.

Animals↗
PubMed1999

Approaches toward the genetic analysis of complex traits: asthma and atopy.

With the challenges emerging from the analysis and interpretation of the human genome, and the specific issues pertinent to pursuing the Genome Project itself, it is truly an exciting time in the development of the biological sciences. The occasion is certainly ripe for the emergence of new concepts and ideas, as the theories of complexity, natural selection, and reductionism become integrated into a new whole. We need to learn how to approach the analyses of the complex data sets that will be generated by the Genome Project and address, more generally, the problems inherent in the analysis of the complex diseases such as asthma. Finally, we need to consider how the recent advances in genetics and genomics will affect biomedical research reaching into the next millennium and beyond.

Asthma↗
PubMed1997

Approaches toward the genetic analysis of complex traits: asthma and atopy.

With the challenges emerging from the analysis and interpretation of the human genome, and the specific issues pertinent to pursuing the Genome Project itself, it is truly an exciting time in the development of the biological sciences. The occasion is certainly ripe for the emergence of new concepts and ideas, as the theories of complexity, natural selection, and reductionism become integrated into a new whole. We need to learn how to approach the analysis of the complex data sets that will be generated by the Genome Project and address, more generally, the problems inherent in the analysis of the complex diseases such as asthma. Finally, we need to consider how the recent advances in genetics and genomics will affect biomedical research into the next millennium and beyond.

Asthma↗
PubMed2025

Leveraging local ancestry and cross-ancestry genetic architecture to improve genetic prediction of complex traits in admixed populations.

The broader application of polygenic risk score (PRS) is hindered by the limited transferability of PRS developed in Europeans to non-European populations. While many statistical methods have been developed to improve the performance of PRS in non-European populations, most of them focused on discrete genetic ancestry clusters and did not consider admixed individuals. Admixed individuals pose a unique challenge for PRS calculation due to the complexity of local ancestry and cross-ancestry effect sizes. Here, we present a statistical method called SDPR_admix for calculating PRS in admixed individuals. SDPR_admix characterizes the joint distribution of the effect sizes of a genetic variant with two ancestries to be both zero, ancestry enriched, or shared with correlation. SDPR_admix outperformed other methods in simulations and improved the prediction of real traits in European-African admixed individuals in UK Biobank when trained on the Population Architecture using Genomics and Epidemiology (PAGE) dataset (N = 13,000). Deployment of SDPR_admix on All of Us (N = 52,000) further increased the prediction accuracy by approximately 5-fold on average compared with training on PAGE. This enhancement was achieved with manageable computational time and cost, demonstrating the feasibility of training PRS models on large-scale All of Us data. We provided several examples demonstrating that both ancestral-enriched and shared effects, as included in the SDPR_admix prediction model, are helpful for improving polygenic prediction in admixed populations. We also applied SDPR_admix to construct PRS for admixed Americans with mixture of European and Amerindigenous ancestries and showed that SDPR_admix overall outperformed other methods.

Humans↗
PubMed2002

Bay-0 x Shahdara recombinant inbred line population: a powerful tool for the genetic dissection of complex traits in Arabidopsis.

Natural genetic variation in Arabidopsis is considerable, but has not yet been used extensively as a source of variants to identify new genes of interest. From the cross between two genetically distant ecotypes, Bay-0 and Shahdara, we generated a Recombinant Inbred Line (RIL) population dedicated to Quantitative Trait Locus (QTL) mapping. A set of 38 physically anchored microsatellite markers was created to construct a robust genetic map from the 420 F6 lines. These markers, evenly distributed throughout the five chromosomes, revealed a remarkable equilibrium in the segregation of parental alleles in the genome. As a model character, we have analysed the genetic basis of variation in flowering time in two different environments. The simultaneous mapping of both large- and small-effect QTLs responsible for this variation explained 90% of the total genotypic variance. Two of the detected QTLs colocalize very precisely with FRIGIDA and FLOWERING LOCUS C genes; we provide information on the polymorphism of genes confirming this hypothesis. Another QTL maps in a region where no QTL had been found previously for this trait. This confirms the accuracy of QTL detection using the Bay-0 x Shahdara RIL population, which constitutes the largest in size available so far in Arabidopsis. As an alternative to mutant analysis, this population represents a powerful tool which is currently being used to undertake the genetic dissection of complex metabolic pathways.

Journal Article↗
PubMed2005

The use of race variables in genetic studies of complex traits and the goal of reducing health disparities: a transdisciplinary perspective.

The use of racial variables in genetic studies has become a matter of intense public debate, with implications for research design and translation into practice. Using research on smoking as a springboard, the authors examine the history of racial categories, current research practices, and arguments for and against using race variables in genetic analyses. The authors argue that the sociopolitical constructs appropriate for monitoring health disparities are not appropriate for use in genetic studies investigating the etiology of complex diseases. More powerful methods for addressing population structure exist, and race variables are unacceptable as gross proxies for numerous social/environmental factors that disproportionately affect minority populations. The authors conclude with recommendations for genetic researchers and policymakers, aimed at facilitating better science and producing new knowledge useful for reducing health disparities.

Health Status↗
PubMed2002

Anterior segment dysgenesis and the developmental glaucomas are complex traits.

Glaucoma refers to a heterogeneous group of disorders that involve retinal ganglion cell death, optic nerve damage, and loss of visual field. Glaucoma is a leading cause of vision loss worldwide, affecting an estimated 67 million people. Elevated intraocular pressure is a major risk factor for glaucoma. Individuals with malformations of structures of the anterior segment of the eye frequently develop elevated intraocular pressure and glaucoma. In this review, we focus on the developmental glaucomas, the subset of glaucomas associated with anterior segment dysgenesis. To minimize overlap with other reviews in this issue and elsewhere, we highlight the complex, multifactorial nature of these diseases and recent advances using mice.

Animals↗
PubMed2005

The role of parametric linkage methods in complex trait analyses using microsatellites.

Many investigators of complexly inherited familial traits bypass classical segregation analysis to perform model-free genome-wide linkage scans. Because model-based or parametric linkage analysis may be the most powerful means to localize genes when a model can be approximated, model-free statistics may result in a loss of power to detect linkage. We performed limited segregation analyses on the electrophysiological measurements that have been collected for the Collaborative Study on the Genetics of Alcoholism. The resulting models are used in whole-genome scans. Four genomic regions provided a model-based LOD > 2 and only 3 of these were detected (p < 0.05) by a model-free approach. We conclude that parametric methods, using even over-simplified models of complex phenotypes, may complement nonparametric methods and decrease false positives.

Chromosome Mapping↗
PubMed2005

Modeling the effect of a genetic factor for a complex trait in a simulated population.

Genetic Analysis Workshop 14 simulated data have been analyzed with MASC(marker association segregation chi-squares) in which we implemented a bootstrap procedure to provide the variation intervals of parameter estimates. We model here the effect of a genetic factor, S, for Kofendrerd Personality Disorder in the region of the marker C03R0281 for the Aipotu population. The goodness of fit of several genetic models with two alleles for one locus has been tested. The data are not compatible with a direct effect of a single-nucleotide polymorphism (SNP) (SNP 16, 17, 18, 19 of pack 153) in the region. Therefore, we can conclude that the functional polymorphism has not been typed and is in linkage disequilibrium with the four studied SNPs. We obtained very large variation intervals both of the disease allele frequency and the degree of dominance. The uncertainty of the model parameters can be explained first, by the method used, which models marginal effects when the disease is due to complex interactions, second, by the presence of different sub-criteria used for the diagnosis that are not determined by S in the same way, and third, by the fact that the segregation of the disease in the families was not taken into account. However, we could not find any model that could explain the familial segregation of the trait, namely the higher proportion of affected parents than affected sibs.

Alleles↗
PubMed2003

Fine mapping of complex trait genes combining pedigree and linkage disequilibrium information: a Bayesian unified framework.

We present a Bayesian method that combines linkage and linkage disequilibrium (LDL) information for quantitative trait locus (QTL) mapping. This method uses jointly all marker information (haplotypes) and all available pedigree information; i.e., it is not restricted to any specific experimental design and it is not required that phases are known. Infinitesimal genetic effects or environmental noise ("fixed") effects can equally be fitted. A diallelic QTL is assumed and both additive and dominant effects can be estimated. We have implemented a combined Gibbs/Metropolis-Hastings sampling to obtain the marginal posterior distributions of the parameters of interest. We have also implemented a Bayesian variant of usual disequilibrium measures like D' and r(2) between QTL and markers. We illustrate the method with simulated data in "simple" (two-generation full-sib families) and "complex" (four-generation) pedigrees. We compared the estimates with and without using linkage disequilibrium information. In general, using LDL resulted in estimates of QTL position that were much better than linkage-only estimates when there was complete disequilibrium between the mutant QTL allele and the marker. This advantage, however, decreased when the association was only partial. In all cases, additive and dominant effects were estimated accurately either with or without disequilibrium information.

Bayes Theorem↗