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PubMed1995

Controversies about the genetic model of colorectal tumorigenesis.

According to the genetic model, intestinal tumorigenesis is a result of the ordered in time inactivation of tumor suppressor genes and the activation of oncogenes. A tacit assumption is that both genes involved in the regulation of proliferation and growth factor-inducible genes, although inactivated, would not be changed during that process. The model requires that cancer cell population is homogenous, exists in a deterministic environment, and develops in a teleological manner. Meanwhile, tumorigenesis is rather a combination of both deterministic and stochastic molecular phenomena. Therefore, a novel notion of bifurcating point genes is defined as a generalization of the idea of tumor suppressor genes and oncogenes. Alternative stochastic mechanisms of tumorigenesis are discussed such as a decreased expression of intestinal-specific genes in cancer cells, most likely reflecting adaptation to survival within a heterogeneous, and non-equilibrated cellular population.

Colorectal Neoplasms↗

PubMed1980

Schizophrenia: the systematic construction of genetic models.

Methods are described for the systematic construction of genetic models of schizophrenia with one, two, and four loci. All models are constrained to fit the following three parameters: (1) frequency of schizophrenia in the general population = 0.9%; (2) frequency of schizophrenia in the sibs of schizophrenics = 8%; and (3) frequency of "schizophrenic spectrum" in the sibs of schizophrenics = 15%. In addition, a fourth parameter, the frequency of the allele predisposing to schizophrenia, is freely variable. The problems of correcting for ascertainment bias, and of comparing and testing these genetic models, are discussed.

Alleles↗

PubMed2006

Relative risks and effective number of meioses: a unified approach for general genetic models and phenotypes.

Many common diseases are known to have genetic components, but since they are non-Mendelian, i.e. a large number of genetic factors affect the phenotype, these components are difficult to localize. These traits are often called complex and analysis of siblings is a valuable tool for mapping them. It has been shown that the power of the affected relative pairs method to detect linkage of a disease susceptibility locus depends on the locus contribution to increased risk of relatives compared with population prevalence (Risch, 1990a,b). In this paper we generalize calculation of relative risk to arbitrary phenotypes and genetic models, but also show that the relative risk can be split into the relative risk at the main locus and the relative risk due to interaction between the main locus and loci at other chromosomes. We demonstrate how the main locus contribution to the relative risk is related to probabilities of allele sharing identical by descent at the main locus, as well as power to detect linkage. To this end we use the effective number of meioses, introduced by Hössjer (2005a) as a convenient tool. Relative risks and effective number of meioses are computed for several genetic models with binary or quantitative phenotypes, with or without polygenic effects.

Alleles↗

PubMed2001

Modeling genetic regulatory dynamics in neural development.

We model genetic regulatory networks in the framework of continuous-time recurrent networks. The network parameters are determined from gene expression level time series data using genetic algorithms. We have applied the method to expression data from the development of rat central nervous system, where the active genes cluster into four groups, within which the temporal expression patterns are similar. The data permit us to identify approximately the interactions between these groups of genes. We find that generally a single time series is of limited value in determining the interactions in the network, but multiple time series collected in related tissues or under treatment with different drugs can fix their values much more precisely.

Algorithms↗

PubMed1992

Genetic Tobit factor analysis: quantitative genetic modeling with censored data.

Parameters of quantitative genetic models have traditionally been estimated by either algebraic manipulation of familial correlations (or familial mean squares), biometric model fitting, or multiple-group covariance structure analysis. With few exceptions, researchers who have used these methods for the analysis of twin data have assumed that their data were multinormal and, consequently, have used normal-theory estimation methods. It is shown that normal-theory methods produce biased genetic and environmental parameter estimates when data are censored. Specifically, with censored data, (1) normal-theory estimates of narrow-sense heritability are either positively or negatively biased, whereas (2) estimates of shared-familial environmental variance are always biased downward. An alternative method for estimating genetic and environmental parameters from censored twin data is proposed. The method is called genetic Tobit factor analysis (GTFA) and is an extension of the Tobit factor analysis model developed by Muthén (Br. J. Math. Stat. Psychol. 42, 241-250, 1989). Using a Monte Carlo design, the performance of GTFA is compared to traditional quantitative genetic methods in both large and small data sets. The results of this study suggest that GTFA is the preferred method for the genetic modeling of censored data obtained from twins.

Genetics, Behavioral↗

PubMed2001

Effect of race, genetic population structure, and genetic models in two-locus association studies: clustering of functional renin-angiotensin system gene variants in hypertension association studies.

Previous genetic association studies have overlooked the potential for biased results when analyzing different population structures in ethnically diverse populations. The purpose of the present study was to quantify this bias in two-locus association studies conducted on an admixtured urban population. We studied the genetic structure distribution of angiotensin-converting enzyme insertion/deletion (ACE I/D) and angiotensinogen methionine/threonine (M/T) polymorphisms in 382 subjects from three subgroups in a highly admixtured urban population. Group I included 150 white subjects; group II, 142 mulatto subjects, and group III, 90 black subjects. We conducted sample size simulation studies using these data in different genetic models of gene action and interaction and used genetic distance calculation algorithms to help determine the population structure for the studied loci. Our results showed a statistically different population structure distribution of both ACE I/D (P = 0.02, OR = 1.56, 95% CI = 1.05-2.33 for the D allele, white versus black subgroup) and angiotensinogen M/T polymorphism (P = 0.007, OR = 1.71, 95% CI = 1.14-2.58 for the T allele, white versus black subgroup). Different sample sizes are predicted to be determinant of the power to detect a given genotypic association with a particular phenotype when conducting two-locus association studies in admixtured populations. In addition, the postulated genetic model is also a major determinant of the power to detect any association in a given sample size. The present simulation study helped to demonstrate the complex interrelation among ethnicity, power of the association, and the postulated genetic model of action of a particular allele in the context of clustering studies. This information is essential for the correct planning and interpretation of future association studies conducted on this population.

Alleles↗

PubMed1996

Genetic models in the study of anesthetic drug action.

This chapter reviews the use of genetic models in the study of anesthetic drug action. Genetic model systems provide a novel approach to understanding mechanisms of anesthetic drug action. Many models have been derived using selection processes that emphasize differential drug sensitivity, producing animal lines that differ in their CNS drug response. Studies of vertebrate (rodent) and invertebrate (Drosophila, Caenorhabditis elegans) animal model systems are covered. The review discusses studies employing lines derived from spontaneous and induced mutagenic processes, selectively bred lines, and inbred lines possessing inherent differential drug sensitivities. The primary focus of included studies is the general anesthetic drugs that are commonly used in the clinical setting. These are drugs such as the inhalational agents (halothane, enflurane, isoflurane, nitrous oxide) and the intravenous induction agents (propofol and diazepam). Rodent lines with differential sensitivity to opiates are also discussed. Finally, an approach to identifying and isolating the genes that control anesthetic sensitivity is discussed in a section on mapping quantitative trait loci (QTL) in recombinant inbred lines.

Anesthetics↗

PubMed2005

Familial recurrence rates and genetic models of multiple sclerosis.

Susceptibility to multiple sclerosis (MS) is determined by both inherited and non-inherited factors. The importance of genetic factors is demonstrated by the increased risk of disease in relatives of MS patients. Our objective was to determine the implications of the observed familial recurrence risks for the genetic basis of MS. We developed a computer program which calculates recurrence risks for monozygotic (MZ) twins, siblings, and second degree relatives, and used it to calculate recurrence risks for a wide variety of genetic models. We investigated models with different numbers of genes, different patterns of interaction between the genes, and dominant or recessive inheritance. The models that best reproduced the observed values had multiple loci with strongly synergistic interaction and autosomal dominant (AD) inheritance. At least six loci were required, and we found no upper limit on the number of loci. Models with genetic heterogeneity, where only a fraction of the risk loci are required for disease, are possible. In models with large numbers of loci the "abnormal" alleles conferring risk of disease are the most common allele. We conclude that a variety of genetic models with multiple genes, dominant inheritance, and synergistic interaction between risk genes are consistent with the observed familial recurrence rates in MS.

Algorithms↗

PubMed1991

Scope and contribution of genetic models to an understanding of the epilepsies.

Studies of the genetic models of the epilepsies emphasize that some seizure disorders result from an aberrant "wiring diagram" coupled with abnormal activity of individual neurons. These defects cause the unique seizer-triggering mechanisms operative within the epileptic nervous system but which are inactive or do not exist in normal subjects. Moreover, causes of epilepsy reside not only within the brain area, wherein initial appearance of epileptic EEG discharge occurs, but also outside that region. Etiologically significant neurochemical dysfunctions may be common features of the epileptic condition in genetic models across species. Accordingly, genetically determined convulsive epileptogenesis in rats, baboons, and humans may result partially from noradrenergic and GABAergic deficits. In contrast, genetically derived absence seizures in the rat and perhaps also humans may occur in response to GABAergic excess. The unique features of the genetically epileptic animals emphasize their usefulness in developing novel drugs that selectively ameliorate seizure predisposition.

Animals↗

PubMed1983

Genetic models of carcinogenesis.

The major genetic models of carcinogenesis are critically reviewed to determine their validity and relevance for clinical and experimental oncologists. Of major concern are the "two-hit" theory of Knudson and the host resistance system of Matsunaga. These models may be used to explain the pathobiologic peculiarities of human neoplasms, particularly those occurring in early life. It is proposed that certain benign and regressive tumors encountered in early life are expressions of the activity of the host resistance system.

Adult↗

PubMed1987

A genetic model describing the evolution of levamisole resistance in Trichostrongylus colubriformis, a nematode parasite of sheep.

Data from 21 generations of selection on a levamisole-resistant strain of Trichostrongylus colubriformis, either exposed to selection with the anthelmintics levamisole (LEV) or thiabendazole (TBZ), or unexposed, were used to fit a genetic model describing the evolution of LEV resistance in this parasite species. A statistical model describing the dose-response relationship for a mixed population of susceptible and resistant parasite eggs exposed to anthelmintic was fitted to egg-hatch assay data for each generation and for each selection regimen. Estimated parameters from the statistical model provided the input for the genetic model from which were obtained estimates of the relative fitness of susceptible and resistant genotypes under each selection regimen. The experimental data and the genetic models both indicated that, in this parasite strain, LEV resistance was determined by a single dominant gene, and that TBZ selects for LEV susceptibility. A variety of drug alternation programmes was simulated for this genetic system. The programme that minimized the development of LEV resistance involved alternating the drugs (LEV and TBZ) between each worm generation.

Animals↗

PubMed1992

[Analysis of genetic models and gene effects on main agronomy characters in rapeseed].

According to four different genetic models, the genetic patterns of 8 agronomy traits were analysed by using the data of 24 generations which included positive and negative cross of 81008 x Tower, both of the varieties are of good quality. The results showed that none of 8 characters could fit in with additive-dominance models. Epistasis was found in all of these characters, and it has significant effect on generation means. Seed weight/plant and some other main yield characters are controlled by duplicate interaction genes. The interaction between triple genes or multiple genes needs to be utilized in yield heterosis.

Brassica↗

PubMed2004

Characteristics of genetic epidemiology and genetic models for vitiligo.

BACKGROUND: Vitiligo occurs with a frequency of 0.1% to 2% in various populations and is classified into several subtypes by its clinical presentation. Although genetic factors are thought to be involved in the cause of vitiligo, the genetic models for different phenotypes of vitiligo are unknown. OBJECTIVE: Our purpose was to explore potential genetic models for different phenotypes of vitiligo and analyze genetic epidemiologic characteristics of vitiligo in a Chinese population. METHODS: Information from 2247 patients and members in their families was collected using a uniform questionnaire. Patients' clinical characteristics and their family history were analyzed using software. A complex segregation analysis was conducted to propose potential genetic models for vitiligo. RESULTS: Different subtypes of vitiligo had different ages of disease onset. In relatives of patients with vitiligo, the risk of developing vitiligo increased with increasing relatedness to the patients with vitiligo. A polygenic additive model was the best model for focal vitiligo, vitiligo vulgaris, acrofacial vitiligo, and segmental vitiligo with approximately 50% heritability in each. For universal vitiligo, the best model was an environmental model. CONCLUSION: This study indicated that different phenotypes of vitiligo had different pathogeneses and genetic backgrounds. Onset of vitiligo is possibly affected by both genetic backgrounds and common environmental factors.

Adolescent↗

PubMed2002

[Analyses of genetic model of psoriasis vulgaris].

OBJECTIVE: To explore the possible genetic model of psoriasis vulgaris. METHODS: The complex segregation analysis and heritability calculation were performed with the aid of Penrose method, Falconer regression method and SAGE-REGTL program. RESULTS: It was found that in 1043 patients with psoriasis vulgaris, 305 patients (29.24%) have the family history of psoriasis, and 738 patients have not the family history. A ratio of s/q approached 1/(square root of q) with Penrose method, and the heritability values of psoriasis in the first-degree and second-degree relatives were 67.04%, 46.6% respectively. By complex segregation analysis, Mendelian, non-major-gene model and environment model were rejected for psoriasis. CONCLUSION: The results suggest that psoriasis follows a pattern of polygenetic or multifactorial inheritance rather than single-gene inheritance.

Adolescent↗

PubMed1999

Genetic models with reduced penetrance related to the Y chromosome.

Classical statistical genetics models of a quantitative trait depending on an autosomal gene indicate that father-to-daughter and mother-to-son correlations should be the same. If phenotypes are not sex-dependent, father-to-son and mother-to-daughter correlations also share this common value. On the other hand, if the gene is sex-linked, then the father-to-son correlation is zero. Such models do not explain genetic variation in pulmonary artery pressure (PAP) of cattle--important because cattle with high PAP are known to develop brisket disease, pulmonary heart disease, and congestive heart failure when taken to high altitudes. Data on 966 calves at a ranch in Colorado showed positive correlation (0.2) between sire PAP and male calf PAP but slightly negative correlation (-0.01) between sire PAP and female calf PAP; the dam-to-male calf and dam-to-female calf correlations are both about 0.1. The model presented here postulates an autosomal gene with reduced penetrance (i.e., the trait may remain at a normal level even when the genotype suggests abnormality) and that, in males, the rate of penetrance is related to an abnormality in the Y chromosome and is therefore passed on from father to son. Then under plausible selective breeding assumptions, the pairwise correlation between fathers and daughters can become zero or negative. Explicit formulas are computed for the model covariances, and numerical computations indicate that plausible parameter values can be chosen for the model.

Altitude↗

PubMed2001

The null distribution of the heterogeneity lod score does depend on the assumed genetic model for the trait.

It is well known that the asymptotic null distribution of the homogeneity lod score (LOD) does not depend on the genetic model specified in the analysis. When appropriately rescaled, the LOD is asymptotically distributed as 0.5 chi(2)(0) + 0.5 chi(2)(1), regardless of the assumed trait model. However, because locus heterogeneity is a common phenomenon, the heterogeneity lod score (HLOD), rather than the LOD itself, is often used in gene mapping studies. We show here that, in contrast with the LOD, the asymptotic null distribution of the HLOD does depend upon the genetic model assumed in the analysis. In affected sib pair (ASP) data, this distribution can be worked out explicitly as (0.5 - c)chi(2)(0) + 0.5chi(2)(1) + cchi(2)(2), where c depends on the assumed trait model. E.g., for a simple dominant model (HLOD/D), c is a function of the disease allele frequency p: for p = 0.01, c = 0.0006; while for p = 0.1, c = 0.059. For a simple recessive model (HLOD/R), c = 0.098 independently of p. This latter (recessive) distribution turns out to be the same as the asymptotic distribution of the MLS statistic under the possible triangle constraint, which is asymptotically equivalent to the HLOD/R. The null distribution of the HLOD/D is close to that of the LOD, because the weight c on the chi(2)(2) component is small. These results mean that the cutoff value for a test of size alpha will tend to be smaller for the HLOD/D than the HLOD/R. For example, the alpha = 0.0001 cutoff (on the lod scale) for the HLOD/D with p = 0.05 is 3.01, while for the LOD it is 3.00, and for the HLOD/R it is 3.27. For general pedigrees, explicit analytical expression of the null HLOD distribution does not appear possible, but it will still depend on the assumed genetic model.

Chromosome Mapping↗

PubMed2000

A quantitative genetic model for analyzing species differences in outcrossing species.

A genetic model based on a two-level intra- and interspecific mating design is proposed to estimate the genetic architecture of species differences and heterosis for outcrossing species. The underlying genetic analyses make use of classical quantitative genetic theories and recent results from molecular genetic studies. Gene effects across different quantitative trait loci (QTL) can be approximated by a geometric series. Under natural selection, gene effects are often associated with allele frequencies in a particular way, which can be approximated by the gamma distribution. By incorporating these approximations into family structural analyses in the mating design, we are able to estimate a number of genetic parameters that contribute to quantitative genetic variation based on a nonlinear optimization approach. These parameters include the number of QTL, their gene effects, and their allele frequencies in the parental populations. We perform simulation studies and illustrate an example to demonstrate the statistical property and procedure of the method.

Alleles↗

PubMed2000

A deterministic genetic model for sympatric speciation by sexual selection.

A deterministic haploid genetic model confirms and explores in more detail the results of our previous individual-based simulation model for sympatric speciation by sexual selection. With the deterministic model, we are able to elucidate parameter dependence by phase plane analysis. We clarify how and why sympatric speciation by sexual selection can happen in a number of ways: (1) Female preferences for or against particular types of males have different effects. Whereas the former affects how readily speciation is invoked, the latter changes the stability of speciation equilibrium. (2) When there is no cost on male ornamentations, speciation is triggered regardless of initial haplotype frequencies if sufficient female preference is provided. (3) There exists a threshold for female initial frequencies for speciation to be invoked, but male initial frequencies have little effect. (4) A small cost on female mate choice does not cancel speciation, but when large, it greatly reduces the possibility of speciation.

Animals↗