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PubMed2000

General equations for Pt, Ps, and the power of the TDT and the affected-sib-pair test.

Several equations are highlighted here, whose algebraic symmetries and generality make them very useful for understanding and comparing the properties of the transmission disequilibrium test (TDT) and affected sib-pair test. Methods using the equations are also presented that yield precise estimates of sample sizes needed for genome scans or for testing a single candidate gene, and these power methods are shown to compare favorably with alternative approaches recently described by Knapp (1999) and by Tu and Whittemore (1999). Simple relationships are also noted that summarize the relative sample sizes required for equivalent power to detect association by the TDT or case-control designs. As single-nucleotide polymorphism (SNP) maps revolutionize the search for disease-causing genes, the equations should prove useful for planning and evaluating studies of linkage and association across a broad range of possible disease models and relationships between markers and linked disease loci.

Alleles↗
PubMed2002

A major gene influences variation in large HDL particles and their response to diet in baboons.

Some baboons accumulate appreciable amounts of large apoE-rich HDLs (HDL(1)) which are similar to those reported in humans with several different dyslipoproteinemias. We estimated HDL(1) cholesterol concentrations by gradient gel electrophoresis of serum samples obtained from 634 pedigreed baboons fed with three diets differing in levels of fat and cholesterol. The HDL(1) trait was highly heritable on each diet (0.390< or =h(2)< or =0.528). Segregation analyses yielded significant evidence that a single major gene plus polygenes affected HDL(1) on a high-fat low-cholesterol diet. The major gene explained approximately 56% of total trait variance and 90% of the additive genetic variance in HDL(1) levels in these baboons. Bivariate one-locus segregation analyses indicated that this major gene exerts significant pleiotropic effects on a number of traditional HDL traits on all three diets, including HDL size distributions, and concentrations of HDL-C, apoAI, and apoE. Linkage analyses showed that this major gene was not located in chromosomal regions that contain six candidate genes whose protein products are important to HDL metabolism (LCAT, CETP, APOA1, APOE, ABCA1, LIPC). Our results suggest this major gene in baboons plays a pivotal role in HDL metabolism, but is unlikely to code for any of the proteins previously implicated in studies of human HDL(1).

Animals↗
PubMedDate not supplied

Finding susceptibility genes for developmental disorders of speech: the long and winding road.

UNLABELLED: Finding susceptibility genes for complex disorders is the next major challenge facing genetics researchers. The purpose of this paper is to stimulate creative thinking about the gene-finding process for developmental speech disorders (DSDs), specifically disorders of articulation/phonology and stuttering. The paper will begin with a review of existing behavioral genetic studies of these phenotypes. This will be followed by a discussion of roadblocks that may impede the molecular study of DSDs, research that is in very early stages of development. As a third objective, the small number of molecular genetic studies of DSDs that have been published or presented will be described. The paper concludes with a discussion of research strategies that may maximize the success of molecular studies of speech phenotypes. It will be argued that progress will most likely be enhanced if theories about biological systems and processes can be used to narrow the search for candidate susceptibility genes. LEARNING OUTCOMES: The reader will be introduced to findings and conceptual issues that relate to the behavioral and molecular genetic investigation of DSDs. After completing this paper, readers should be able to (a) identify key epidemiological findings for the three speech phenotypes that were discussed (DAS, speech delay, and stuttering); (b) summarize the findings of the behavioral genetic studies of speech disorders that were presented; (c) identify four specific challenges that may impede future molecular genetic studies of these phenotypes; (d) describe the methodological sequence that led to the discovery of the FOXP2 gene; and (e) summarize the two research strategies that were presented to potentially reduce sample heterogeneity for future molecular genetics research.

Age of Onset↗
PubMed1975

Sex-linked familial reflux.

A family is described in which all 3 brothers and the maternal grandfather had vesicoureteral reflux, whereas the father, mother and 3 daughters were urologically normal. This pedigree strongly suggests and X-linked mode of genetic transmission. Nevertheless, available evidence indicates that familial reflux is usually transmitted by multifactorial polygenic inheritance. Hundreds of additional pedigrees will have to be studied before the methods of inheritance are firmly established.

Adolescent↗
PubMed2001

Genetic dissection of complex traits: an overview.

Genetic dissection of even simple Mendelian traits has been sufficiently challenging. Complex traits are proving to be much more challenging and frustrating than previously thought. The concepts, methods, and strategies discussed in this volume emphasize the critical importance of study design, appropriate methods of analysis, including relatively newer and emerging methods, and issues relating to the interpretation of results from genome scans; some thoughts on the future the new millennium holds are offered, as well. This chapter overviews the key steps involved in the study of complex traits, which are discussed in detail in subsequent chapters. It is suggested that a combination of lumping and splitting strategies is more appropriate for the analysis of complex traits, and large-scale collaborations should make this possible. For example, by pooling data and/or results from multiple studies on a given disease/trait, one may attain a sample size large enough to permit the division of the data into multiple relatively more homogeneous subgroups. The sample size of the subgroups may still be sufficiently large sample, but the genetic dissection within each subgroup should be much less daunting. The expectation is that analyses within subgroups will enhance gene finding, especially when any interacting determinants are taken into account at the time of dividing the data into subgroups. Perhaps the methods are not yet optimum, but the future holds much promise. In the meantime, the cutting-edge methods discussed in this volume by leading experts should help. There is an increasing healthy tendency for investigators to collaborate by pooling materials and results across studies, with the goal of increasing the sample size and thus the power. We believe that such efforts are essential for the genetic dissection of complex traits and should contribute to greater success, especially if there is a real commitment to meaningful collaboration. After all, for most complex traits, the question is not whether there are genes, only when and how they might be found.

Genetic Variation↗
PubMed2001

Familial resemblance and heritability.

Familial resemblance, which arises when members within families are more similar than are unrelated pairs of individuals, may be estimated in terms of correlations (or covariances) among family members. The magnitudes of such correlations generally reflect both the extent of environmental sharing and the degree of biological relationship between the relatives. Heritability, or more appropriately multifactorial heritability or generalized heritability, quantifies the strength of the familial resemblance and represents the percentage of variance ina trait that is due to all additive familial effects including additive genetic effects and those of the familial environment. However, the traditional concept of heritability, which may be more appropriately called the genetic heritability, represents only the percentage of phenotypic variance due to additive genetic effects. Resolving the sources of familial resemblance entails other issues. For example, there may be major gene effects that may be largely or entirely nonadditive, temporal or developmental trends, and gene-gene (epistasis) and gene-environment interactions. The design of a family study determines which of these sources are resolvable. For example, in intact nuclear families consisting of parents and offspring, the genetic and familial environmental effects are not resolvable because these relatives share both genes and environments. However, extended pedigrees and twin and adoption study designs allow separation of the heritable effects and, possibly, more complex etiologies, including interactions. Various factors affect the estimation and interpretability of heritability, for example, assumptions regarding linearity and additivity of the effects, assortative mating, and the underlying distribution of the data. Nonnormality of the data can lead to errors in hypothesis testing, although it yields reasonably unbiased estimates. Fortunately, these and other complications can be directly modeled in many of the sophisticated software packages available today in genetic epidemiology.

Adoption↗
PubMed2003

Where are all the blood-pressure genes?

CONTEXT: The potential for discovery of underlying genetic causes for common conditions, such as hypertension, is a major justification for the human genome project. Hopes have been raised that personalised molecular prognostic and therapeutic strategies will result from genomic studies. STARTING POINT: The largest and most recent searches of the genome (Mark Caulfield and colleagues, Lancet 2003; 361: 2118-23; Michael Province and colleagues, Am J Hypertens 2003; 16: 144-47) have found limited evidence of genes that determine hypertension, and even less evidence for the existence of causative DNA variants (alleles) within these genes. Previous genomic studies did not reach a consensus on the likely location of blood-pressure genes. The difficulty in identifying genetic causes for common conditions might be because the causative alleles are numerous, with small individual impact, and are distributed unevenly between populations. WHERE NEXT?: Without comprehensive and reliable description of the alleles associated with hypertension, using genetics for diagnosis remains tenuous. However, the discovery of a single allele proven to be associated with control of blood pressure could lead to the discovery of relevant and novel physiological targets for the prevention and treatment of hypertension.

Alleles↗
PubMed2003

Toward a molecular architecture of personality.

Epidemiological studies provided a large body of evidence that personality dimensions are influenced by genetic factors and that the genetic component is highly complex, polygenic, and epistatic. However, consistent findings on the genetic basis of personality have yet remained sparse. In recent years, molecular genetics has begun to identify specific genes coding in particular for components of the serotonergic and dopaminergic neurotransmitter systems representing quantitative trait loci (QTLs) for behavioral traits. The QTL concept suggests that complex traits are not attributable to single genes. According to this polygenic model, the genetic basis of personality and behavior and its pathological variations thus results from additive or nonadditive interactions of various genes. As the number of suitable candidate genes constantly increases, the QTL model provides a reasonable explanation for the genetic basis of personality and its disorders. In this review, the current knowledge on the impact of a large number of candidate gene polymorphisms (e.g. variations in serotonin and dopamine receptor and serotonin transporter genes) on personality and temperament is summarized. Additionally, investigations of gene-gene and gene-environment interactions in humans and animals, which currently intensify the identification of genes that underlie behavioral variations, are examined. The findings converge on the notion that a probabilistic rather than deterministic impact of genes on the expression of behavior will contribute to the demystification of behavioral disorders.

Animals↗
PubMed2001

Sensitized polygenic trait analysis.

Genetic variation in many biological processes and evolutionary adaptations is caused by polygenes--genes that act in combination to affect a particular trait. Despite the recent identification of several polygenes, many remain to be found, suggesting that new experimental and analytical methods are needed to facilitate their discovery. Here we discuss sensitized polygenetic trait analysis, a method that has emerged recently for simplifying the genetic analysis of polygenic traits. The method uses a known single gene mutation in linkage testing crosses to 'sensitize' the analysis. By increasing the frequency of affected individuals in segregating populations, linkages are more readily detected. This method has considerable potential, especially given the increasing variety of mutations that can be used to sensitize the genetic analysis of polygenic traits.

Animals↗
PubMed2003

A polygenic basis for late-onset disease.

The biological basis of late-onset disease has been shaped by genetic factors subject to varying degrees of evolutionary constraint. Late-onset traits are not only more sensitive to environmental variation, owing to the breakdown of homeostatic mechanisms, but they also show higher levels of genetic variation than traits directly influencing reproductive fitness. The origin and nature of this variation suggests that current strategies are poorly suited to identifying genes involved in many complex diseases.

Age of Onset↗
PubMed2006

Impacts of QTL x environment interactions on genetic response to marker-assisted selection.

Genotype x environment (GE) interaction is a common characteristic for quantitative traits, and has been a subject of great concern for breeding programs. Simulation studies were conducted to investigate the effects of GE interaction on genetic response to marker-assisted selection (MAS). In our study we demonstrated that MAS is generally more efficient than phenotypic selection in the presence of GE interaction, and this trend is more pronounced for developing broadly adaptable varieties. The utilization of different QTL information dramatically influences MAS efficiency. When MAS is based on QTLs evaluated in a single environment, the causal QTL x environment (QE) interactions usually reduce general response across environments, and the reduction in the cumulative general response is a function of the proportion of QE interactions for the trait studied. However, MAS using QTL information evaluated in multiple environments not only yields higher general response, but the general response obtained is also reasonably robust to QE interactions. The total response achieved by MAS in a specific environment depends largely on the total heritability of traits and is slightly subject to relative changes between general heritability and GE interaction heritability. Two breeding strategies, breeding experiments conducted in one environment throughout and in two environments alternately, were also examined for the implementation of marker-based selection. It was thus concluded that plant breeders should be cautious to utilize QTL information from only one environment and execute breeding studies in another.

Breeding↗
PubMed2006

Optimal multiple trait selection for multiple linked quantitative trait loci.

A method was developed to optimize selection on multiple traits with multiple quantitative trait loci (QTLs) over multiple generations. The basis of the method was to replace in the objective function the genotypic value of a single trait with an aggregate genotypic value of multiple traits weighted by their corresponding economic weight, and to maximize the weighted sum of the selection response in the planning horizon. The optimization was formulated as a multiple stage optimal control problem and solved by a forward and backward iteration cycle. The practical utility of this method was illustrated in an example of pig breeding population, in which the number born alive (NBA) and days to 100 kg (D100) were used as parameters. The selection response of this method was compared with standard QTL selection and regular best linear unbiased prediction (BLUP) selection. Results showed that optimal selection achieved greater selection response than either standard QTL or regular BLUP selections. The influence of economic weight to optimal selection was significant, and the optimization was better as the economic weight of D100 increased. Optimal selection increased the total selection response by two ways: 1) it sacrificed some QTL responses during early generations and 2) it put more emphasis on D100. Optimal cumulative discounted selection gave more weight to D100 than optimal terminal selection in the longer generations.

Algorithms↗
PubMed2006

Changes in variance components of flanking marker genotypes under varying selection intensities.

Selection is practically ubiquitous during marker-QTL linkage analysis with an experimental population. Thus, it is necessary to investigate the impacts of selection upon linkage analyses in order to obtain unbiased estimates of QTL position and effect. In this article, by exploiting flanking markers through the widely applied half-sib design, we have developed the structures of three variance components, i.e., variance component between marker genotypes, polygenic variance component and recombinant variance component within marker genotypes. Changes in these variance components under varying selection intensities were investigated in this study to formulate the effects of selection on various variance components. Results showed clearly that all variance components presented were quite sensitive to changes in selection intensity. As selection intensity increased, all variance components declined by differing extents in a quadratic fashion. Comparatively speaking, the variance between marker genotypes decreased most drastically, followed by the polygenic variance within marker genotypes and then the recombinant variance within marker genotypes, which suggested a decrease of power for QTL linkage analysis. Therefore, steps should be taken to avoid as much as possible the presence of selection in real populations, so as to further eliminate the negative effects of selection on QTL linkage analysis.

Alleles↗
PubMed2006

Optimizing selection on multiple identified quantitative trait loci in population with overlapping generations.

A method was developed to model and optimize selection on multiple identified quantitative trait loci (QTLs) and polygenic estimated breeding value, in order to maximize a weighted sum of cumulative response to selection over multiple years in a population with overlapping generations. The model allows for a population with multiple sex-age classes, different number of age class between sires and dams, and varied genetic contribution of the age class. The optimization problem was formulated as a multiple-stage optimal control problem and solved by a forward and backward iteration loop. The practical utility of this method was illustrated in an example of pig breeding population with overlapping generations. The selection response of this method was compared with standard QTL selection and conventional best linear unbiased prediction (BLUP) selection. Simulation results show that optimal selection achieved greater selection response than either standard QTL or conventional BLUP selections. The influence of population structure on optimal selection was significant. Optimal QTL selection and standard QTL selection were more favorable in a population with overlapping generations than discrete generations, and obtained more benefits relative to conventional BLUP selection in a population with overlapping generations. Optimal QTL selection relative to conventional BLUP selection is also more favorable following increase of genetic contribution of two-year-old boars and sows in a population with overlapping generations.

Algorithms↗
PubMedDate not supplied

Cellular senescence and apoptosis: how cellular responses might influence aging phenotypes.

Aging in complex multi-cellular organisms such as mammals entails distinctive changes in cells and molecules that ultimately compromise the fitness of adult organisms. These cellular and molecular changes lead to the phenotypes we recognize as aging. This review discusses some of the cellular and molecular changes that occur with age, specifically changes that occur as a result of cellular responses that evolved to ameliorate the inevitable damage that is caused by endogenous and environmental insults. Because the force of natural selection declines with age, it is likely that these processes were never optimized during their evolution to benefit old organisms. That is, some age-related changes may be the result of gene activities that were selected for their beneficial effects in young organisms, but the same gene activities may have unselected, deleterious effects in old organisms, a phenomenon termed antagonistic pleiotropy. Two cellular processes, apoptosis and cellular senescence, may be examples of antagonistic pleiotropy. Both processes are essential for the viability and fitness of young organisms, but may contribute to aging phenotypes, including certain age-related diseases.

Aged↗
PubMedDate not supplied

A Darwinian-evolutionary concept of age-related diseases.

Humans and animals are structurally designed as a compromise to guarantee optimal survival until the time of reproduction based on natural selection that is effective until that age. Modern conditions of life including improvement of hygiene, preventive and curative medicine as well as socio-economic and political developments have led to an increase of the mean life expectancy that allows ever larger proportions of the population to reach an age that is far beyond that of the reproductive phase. The concept of a Darwinian-evolutionary basis for the development of age-related diseases in principle postulates that genetic traits that are beneficial in younger years to allow for successful reproduction may become deleterious in the elderly, i.e. when selective pressure does not seem to be effective anymore. Examples for this mechanism of pleiotropic antagonism taken from the work of the Institute for Biomedical Aging Research in Innsbruck, Austria, include atherosclerosis, benign and malignant prostate hypertrophy, Alzheimer's disease and the reciprocal relationship between cellular senescence and cancer.

Adult↗