scholarly journals 11. A finite-locus threshold model for estimating the mutation component of multifactorial diseases

1999 ◽  
Vol 29 (3-4) ◽  
pp. 97-117
Keyword(s):  
Threshold Model ◽  
Multifactorial Diseases ◽  
Finite Locus

Risk estimation for multifactorial diseases

1999 ◽  
Vol 29 (3-4) ◽  
pp. 1-2 ◽  
Keyword(s):  
Diabetes Mellitus ◽  
Coronary Heart Disease ◽  
Population Genetic ◽  
Threshold Model ◽  
Genetic Models ◽  
Multifactorial Disease ◽  
Induced Mutations ◽  
Multifactorial Diseases ◽  
Radiation Induced ◽  
The Impact

This report reviews data on naturally-occurring multifactorial diseases and develops a mathematical model to predict the impact of radiation-induced mutations on the frequencies of these diseases in the population. It provides an outline of the aetiological features and examples of multifactorial diseases, interpreted to arise as a result of the joint action of genetic and environmental factors. Examples include common congenital abnormalities (such as neural tube defects, cardiovascular malformations, cleft lip±palate etc.) and chronic diseases (such as coronary heart disease, essential hypertension, diabetes mellitus etc.). These diseases are not readily explained on the basis of simple mendelian patterns of inheritance. The report considers the concepts and models used to explain the inheritance patterns of multifactorial diseases with particular emphasis on the multifactorial threshold model (MTM) of disease liability. The MTM is useful for predicting risk to relatives of those affected from information on their population frequencies. In these predictions, the heritability ( h2) provides a measure of the relative importance of transmissible genetic effects in the overall phenotypic variation. Conceptual differences between mendelian and multifactorial diseases are discussed. The genetic basis of a multifactorial disease is that a genetically susceptible individual may or may not develop the disease depending on the interaction of a number of risk factors, both genetic and environmental. Three chronic multifactorial disease entities are reviewed in depth, viz. diabetes mellitus, essential hypertension, and coronary heart disease. The report considers briefly mechanistic population genetic models developed to explain polygenic variation. The basic conclusion is that the concepts of liability and threshold (underlying the MTM model) and that of mutation-selection balance (from population genetic models) together provide a basis for developing a model for assessing the impact of radiation-induced mutations on the frequencies of multifactorial diseases in the population. The mutation component (MC) of genetic diseases quantifies the responsiveness of the genetic component of a disease to an increase in mutation rate (e.g. after radiation exposure). This report integrates the concepts of liability and threshold (from the MTM model) and of mutation-selection equilibrium (from mechanistic population genetic models) into the ‘Finite Locus Threshold Model’ (FLTM) for estimating MC for multifactorial diseases and the relationship between MC and h 2 of these diseases. Computer simulation studies illustrate the effects of one-time or a permanent increase in mutation rate on MC for multifactorial diseases. Finally, the report addresses the estimation of the radiation risk of multifactorial diseases. A formal revision of the estimates of risk of multifactorial diseases (and also of mendelian diseases) contained in the 1990 Recommendations of ICRP, Publication 60, must await the results of studies currently underway. While future genetic risk estimates are likely to be lower than those in current use, until the new ones become available, those provided in Publication 60 may be regarded as being adequate for use in radiological protection- they are unlikely to underestimate risk.

Hyperstimulation of the immune system as a cause of autoimmune diseases

2020 ◽  
Vol 75 (3) ◽  
pp. 204-213
Author(s):  
Varvara A. Ryabkova ◽  
Leonid P. Churilov ◽  
Yehuda Shoenfeld
Keyword(s):  
Immune System ◽  
Autoimmune Diseases ◽  
Genetic Basis ◽  
Threshold Model ◽  
Subsequent Development ◽  
Threshold Effect ◽  
Successful Management ◽  
Polygenic Inheritance ◽  
Autoimmune Pathology ◽  
The Common

The pathogenesis of autoimmune diseases is very complex and multi-factorial. The concept of Mosaics of Autoimmunity was introduced to the scientific community 30 years ago by Y. Shoenfeld and D.A. Isenberg, and since then new tiles to the puzzle are continuously added. This concept specifies general pathological ideas about the multifactorial threshold model for polygenic inheritance with a threshold effect by the action of a number of external causal factors as applied to the field of autoimmunology. Among the external factors that can excessively stimulate the immune system, contributing to the development of autoimmune reactions, researchers are particularly interested in chemical substances, which are widely used in pharmacology and medicine. In this review we highlight the autoimmune dynamics i.e. a multistep pathogenesis of autoimmune diseases and the subsequent development of lymphoma in some cases. In this context several issues are addressed namely, genetic basis of autoimmunity; environmental immunostimulatory risk factors; gene/environmental interaction; pre-clinical autoimmunity with the presence of autoantibodies; and the mechanisms, underlying lymphomagenesis in autoimmune pathology. We believe that understanding the common model of the pathogenesis of autoimmune diseases is the first step to their successful management.

Threshold square model of the dependence of radiation effects on radiation dose

2020 ◽  
Vol 89 ◽  
pp. 65-74
Author(s):  
A. G. Zavorotnyy ◽  
Keyword(s):  
Radiation Dose ◽  
Emergency Services ◽  
Least Squares Method ◽  
Threshold Model ◽  
Operating Conditions ◽  
Quadratic Model ◽  
Modern World ◽  
Stochastic Effects ◽  
Radiation Accidents ◽  
Increased Risk

Introduction. Operation of radiation hazardous facilities is a reality of the modern world, and the future of the world economy is impossible without the development of nuclear and radiation technologies. At the same time, the widespread use of atomic energy puts forward an important and responsible task of ensuring the safety of the population and the environment in conditions of an increased risk of exposure to ionizing radiation and radioactive substances. In accordance with clause 3.2.1 of the "Radiation Safety Standards NRB-99/2009", the planned increased exposure of persons involved in emergency rescue operations related to the elimination of the consequences of radiation accidents is allowed for men, as a rule, over 30 years old only with their voluntary written consent, after informing about possible radiation doses and health risks. Increased exposure refers to exposure in excess of the basic dose limits under controlled (normal) operating conditions of radiation sources. Goals and objectives. The aim of the study is to increase the functionality of emergency services and fire and rescue subdivisions to perform tasks as intended in the elimination of radiation accidents. The tasks include the construction and substantiation of a model that allows converting the risks of deterministic effects into stochastic effects risks. Methods. When calculating the probability of output of stochastic and deterministic effects depending on the radiation dose and developing a threshold quadratic model, the least squares method and the probabilistic-statistical method were used. Results and discussion. The article shows that a linear non-threshold model of the interaction of radiation with matter greatly overestimates the risk of a stochastic effect emerging at doses of radiation. For example, this overestimation is 8,13 at a dose of D = 0,2 Sv/year. In this regard, a threshold quadratic model has been developed and proposed to be replaced by a threshold quadratic model, which makes it possible to increase the planned irradiation of personnel of emergency services and fire and rescue units during the elimination of radiation accidents in an effective dose from 0,2 Sv to 0,57 Sv, moreover, the probability of emergence of stochastic effects P2 = 0,0084 remains the same for both models. Conclusions. An increase in the maximum permissible dose of radiation for personnel of emergency services and fire and rescue units from 0,2 Sv/year to 0,5 Sv/year will make it possible to increase the functionality of the emergency services and fire and rescue units to perform tasks as intended by 2,5 times when elimination of radiation accidents. For example, the scope of rescue operations may be increased from 100 %, performed at a dose of D = 0,2 Sv/year, to 250 %, performed at a dose of D = 0,5 Sv/year. Key words: emergency services, fire and rescue units, radiation accidents, irradiation, linear no-threshold model, threshold quadratic model.

A Threshold Model for Respondent Heterogeneity

2010 ◽  
Author(s):  
Sandeep R. Chandukala ◽  
S. Long-Tolbert ◽  
Greg M. Allenby
Keyword(s):  
Threshold Model

scholarly journals Bayesian Mapping of Quantitative Trait Loci for Complex Binary Traits

Genetics ◽  
2000 ◽  
Vol 155 (3) ◽  
pp. 1391-1403
Author(s):  
Nengjun Yi ◽  
Shizhong Xu
Keyword(s):  
Quantitative Trait Loci ◽  
Bayesian Statistics ◽  
Quantitative Trait ◽  
Data Augmentation ◽  
Threshold Model ◽  
Binary Trait ◽  
Monte Carlo Algorithm ◽  
Binary Traits ◽  
Trait Loci ◽  
Bayesian Mapping

Abstract A complex binary trait is a character that has a dichotomous expression but with a polygenic genetic background. Mapping quantitative trait loci (QTL) for such traits is difficult because of the discrete nature and the reduced variation in the phenotypic distribution. Bayesian statistics are proved to be a powerful tool for solving complicated genetic problems, such as multiple QTL with nonadditive effects, and have been successfully applied to QTL mapping for continuous traits. In this study, we show that Bayesian statistics are particularly useful for mapping QTL for complex binary traits. We model the binary trait under the classical threshold model of quantitative genetics. The Bayesian mapping statistics are developed on the basis of the idea of data augmentation. This treatment allows an easy way to generate the value of a hypothetical underlying variable (called the liability) and a threshold, which in turn allow the use of existing Bayesian statistics. The reversible jump Markov chain Monte Carlo algorithm is used to simulate the posterior samples of all unknowns, including the number of QTL, the locations and effects of identified QTL, genotypes of each individual at both the QTL and markers, and eventually the liability of each individual. The Bayesian mapping ends with an estimation of the joint posterior distribution of the number of QTL and the locations and effects of the identified QTL. Utilities of the method are demonstrated using a simulated outbred full-sib family. A computer program written in FORTRAN language is freely available on request.

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