X射线损伤修复交叉互补基因1(XRCC1)单核苷酸多态性与神经胶质瘤易感性关系的meta分析(英文)

目的:采用meta分析方法探讨X射线损伤修复交叉互补基因1(XRCC1)单核苷酸多态性与神经胶质瘤易感性的关系。方法:研究检索了PubMed、EMBASE、ISIWeb ofsciences、ScienceDirect及CNKI数据库从建库至2012年9月关于XRCC1基因多态性与神经胶质瘤相关性的相关文献。合并的OR值及其95%CI用于评估不同基因模型与神经胶质瘤风险的关联强度。采用亚组分析和meta回归分析来探索潜在的异质性来源。结果:研究最终纳入12篇Arg399Gln、8篇Arg194Trp和5篇Arg280His XRCC1位点多态性与神经胶质瘤关系文章用于meta分析。Arg399Gln位点多态性在所有基因模型下合并OR值均有显著意义;Arg194Trp位点多态性在纯合子基因模型和隐性基因模型下合并OR值具有显著意义;未发现Arg280His位点多态性与神经胶质瘤风险相关基因模型。亚组分析和meta回归分析显示Arg399Gln位点多态性的所有基因模型风险仅在亚洲人群当中具有显著意义,亚洲人群的风险显著高于白种人群。Arg194Trp对照组人群不符合Hardy-Weinberg平衡(HWE)可能高估了风险。结论:本研究结果显示XRCC1 Arg399Gln基因多态性仅为亚洲人群的神经胶质瘤风险的候选基因,Arg194Trp基因多态性的风险可能是由于对照组不符合HWE的研究所导致的。     

X射线损伤修复交叉互补基因1（XRCC1）单核苷酸多态性与神经胶质瘤易感性关系的meta分析

目的：采用meta 分析方法探讨X 射线损伤修复交叉互补基因1（XRCC1）单核苷酸多态性与神经胶质瘤易感性的关系。方法：研究检索了PubMed、EMBASE、ISI Web of sciences、ScienceDirect 及CNKI 数据库从建库至2012 年9 月关于XRCC1 基因多态性与神经胶质瘤相关性的相关文献。合并的OR 值及其95%CI用于评估不同基因模型与神经胶质瘤风险的关联强度。采用亚组分析和meta 回归分析来探索潜在的异质性来源。结果：研究最终纳入12 篇Arg399Gln、8 篇Arg194Trp 和5 篇Arg280HisXRCC1 位点多态性与神经胶质瘤关系文章用于meta 分析。Arg399Gln 位点多态性在所有基因模型下合并OR 值均有显著意义;Arg194Trp 位点多态性在纯合子基因模型和隐性基因模型下合并OR 值具有显著意义;未发现Arg280His 位点多态性与神经胶质瘤风险相关基因模型。亚组分析和meta 回归分析显示Arg399Gln 位点多态性的所有基因模型风险仅在亚洲人群当中具有显著意义,亚洲人群的风险显著高于白种人群。Arg194Trp对照组人群不符合Hardy-Weinberg平衡（HWE）可能高估了风险。结论：本研究结果显示XRCC1 Arg399Gln 基因多态性仅为亚洲人群的神经胶质瘤风险的候选基因,Arg194Trp 基因多态性的风险可能是由于对照组不符合HWE 的研究所导致的。     

Acrylamide: a review of its genotoxicity and an assessment of heritable genetic risk

An updated review of the genotoxicity studies with acrylamide is provided. Then, using data from the studies generating quantitative information concerning heritability of genetic effects, an assessment of the heritable genetic risk presented by acrylamide is presented. The review offers a discussion of the reactions and possible mechanisms of genotoxic action by acrylamide and its epoxide metabolite glycidamide. Several genetic risk approaches are discussed, including the parallelogram, direct (actually a modified direct), and doubling dose approaches. Using data from the specific-locus and heritable translocation assays, the modified direct and doubling dose approaches are utilized to quantitate genetic risk. Exposures of male parents to acrylamide via inhalation, ingestion, and dermal routes are also quantitated. With these approaches and measurements and their underlying assumptions concerning extrapolation factors (including germ cell stage specificity, DNA repair variability, locus specificity), number of human loci associated with dominant disease alleles, and spontaneous mutation rates, an assessment of heritable genetic risk for humans is calculated for the three exposure scenarios. The calculated estimates for offspring from fathers exposed to acrylamide via drinking water are up to three offspring potentially affected with induced genetic disease per 10⁸ offspring. Estimates for inhalation or dermal exposures suggest higher risks for induced genetic disease in offspring from fathers exposed in occupational settings.     

Optimal screening for genetic diseases

Screening for genetic diseases is performed in many regions and/or ethnic groups where there is a high prevalence of possibly malign genes. The propagation of such genes can be considered a dynamic externality. Given that many of these diseases are untreatable and give rise to truly tragic outcomes, they are a source of societal concern, and the screening process should perhaps be regulated. This paper incorporates a standard model of genetic propagation into an economic model of dynamic management to derive cost benefit rules for optimal screening. The highly non-linear nature of genetic dynamics gives rise to perhaps surprising results that include discontinuous controls and threshold effects. One insight is that any screening program that is in place for any amount of time should screen all individuals in a target population. The incorporation of genetic models may prove to be useful to several emerging fields in economics such as genoeconomics, neuroeconomics and paleoeconomics.     

Improving Power for Testing Genetic Association in Case–Control Studies by Reducing the Alternative Space

Summary .  To detect association between a genetic marker and a disease in case–control studies, the Cochran–Armitage trend test is typically used. The trend test is locally optimal when the genetic model is correctly specified. However, in practice, the underlying genetic model, and hence the optimal trend test, are usually unknown. In this case, Pearson's chi-squared test, the maximum of three trend test statistics (optimal for the recessive, additive, and dominant models), and the test based on genetic model selection (GMS) are useful. In this article, we first modify the existing GMS method so that it can be used when the risk allele is unknown. Then we propose a new approach by excluding a genetic model that is not supported by the data. Using either the model selection or exclusion, the alternative space is reduced conditional on the observed data, and hence the power to detect a true association can be increased. Simulation results are reported and the proposed methods are applied to the genetic markers identified from the genome-wide association studies conducted by the Wellcome Trust Case–Control Consortium. The results demonstrate that the genetic model exclusion approach usually performs better than existing methods under its worst situation across scientifically plausible genetic models we considered.     

Strategies for performing genotype–phenotype association studies in nonhuman primates

Anthropoid primate models offer opportunities to study genetic influence on alcohol consumption and alcohol-related intermediate phenotypes in socially and behaviorally complex animal models that are closely related to humans, and in which functionally equivalent or orthologous genetic variants exist. This review will discuss the methods commonly used for performing candidate gene-based studies in rhesus macaques in order to model how functional genetic variation moderates risk for human psychiatric disorders. Various in silico and in vitro approaches to identifying functional genetic variants for performance of these studies will be discussed. Next, I will provide examples of how this approach can be used for performing candidate gene-based studies and for examining gene by environment interactions. Finally, these approaches will then be placed in the context of how function-guided studies can inform us of genetic variants that may be under selection across species, demonstrating how functional genetic variants that may have conferred selective advantage at some point in the evolutionary history of humans could increase risk for addictive disorders in modern society.     

Analytical Relationship between Family History and Genetic and Environmental risks,with Application to Female Breast Cancer

It is well established in genetic epidemiology that family history is an important indicator of familial aggregation of disease in a family. A strong genetic risk factor or an environmental risk factor with high familial correlation can result in a strong family history. In this paper, family history refers to the number of first‐degree relatives affected with the disease. Cui and Hopper (Journal of Epidemiology and Biostatistics 2001; 6 : 331–342) proposed an analytical relationship between family history and relevant genetic parameters. In this paper we expand the relationship to both genetic and environmental risk factors. We established a closed‐form formula for family history as a function of genetic and environmental parameters which include genetic and environmental relative risks, genotype frequency, prevalence and familial correlation of the environmental risk factor. The relationship is illustrated by an example of female breast cancer in Australia. For genetic and environmental relative risks less than 10, most of the female breast cancer cases occur between the age of 40 and 60 years. A higher genetic or environmental relative risk will move the peak of the distribution to a younger age. A more common disease allele or more prevalent environmental risk factor will move the peak to an older age. For a proband with breast cancer, it is most likely (with probability ≥80%) that none of her first‐degree relatives is affected with the disease. To enable the probability of having a positive family history to reach 50%, the environmental relative risks must be extremely as high as 100, the familial correlation as high as 0.8 and the prevalence as low as 0.1. For genetic risk alone, even the relative risk is as high as 100, the probability of having a positive family history can only reach about 30%. This suggests that the environmental risk factor seems to play a more important role in determining a strong family history than the genetic risk factor. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Five-Year Prognosis Model of Esophageal Cancer Based on Genetic Algorithm Improved Deep Neural Network

ObjectivesEsophageal cancer is a high occult malignant tumor. Even with good diagnosis and treatment, the 5-year survival rate of esophageal cancer patients is still less than 30%. Considering the influence of clinical characteristics on postoperative esophageal cancer patients, the construction of a neural network model will help improve the poor prognosis of patients in the five years.Material and methodsIn this study, genetic algorithm optimized deep neural network is exploited to the clinical dataset of esophageal cancer. The independent prognostic factors are screened by Relief algorithm and Cox proportional risk regression. FTD prognostic staging system is established to assess the risk level of esophageal cancer patients.ResultsFTD staging system and independent prognostic factors are integrated into the genetic algorithm optimized deep neural network. The Area Under Curve (AUC) of FTD staging system is 0.802. FTD staging system is verified by the Kaplan-Meier survival curve, and the median survival time is divided for different risk grades. The FTD staging system is superior to the TNM stages in the prognosis effect. The AUC of deep neural network optimized by genetic algorithm is 0.91.ConclusionThe deep neural network optimized by genetic algorithm has good performance in predicting the 5-year survival status of esophageal cancer patients. The FTD staging system has a significant prognostic effect. The FTD staging system and genetic algorithm optimized deep neural network can be successfully availed in clinical diagnosis and treatment.     

Association of loganin contents with the genetic characterization of natural populations of Palicourea rigida Kunth determined by AFLP molecular markers

Extracts of the medicinal plant Palicourea rigida Kunth, popularly known as douradinha, are widely used for treating urinary tract disorders. Unfortunately, nowadays this is one of the species endemic to Brazilian Cerrado that is at greatest risk of extinction.The aim of the this work was to use AFLP molecular markers to determine the genetic structure and diversity of eight natural populations of P. rigida and to associate their genetic characteristics with loganin production in order to obtain provide relevant information to promote programs for the conservation of this valuable medicinal plant.A total of 120 polymorphic bands were scored and higher proportion of genetic diversity was found in inter-populations (64%) rather than in intra-populations (36%). F_st value was found to be significantly greater than zero (0.3601), demonstrating the complex genetic structure of P. rigida populations. Accessions collected from Cristalina, GO, showed higher percentage of polymorphic loci (65.5%) and the highest genetic diversity. Analysis of Molecular variance (AMOVA) demonstrated 63.9% of intra-population genetic variation. The lowest genetic variability was detected among accessions from the population found in Sacramento, MG. No spatial standard was observed for P. rigida population, suggesting a partially isolated island model. It was observed a minor but significant positive correlation (r = 0.22) between chemical and genetic matrices. The association between chemical and genetic data indicated that environmental factors promoted the loganin production in populations growing in Luziânia, GO, and therefore accessions from those populations should be considered as prime material for initiating the conservation process of P. rigida.     

植物种质群体遗传结构改变的测度

本文旨在探讨植物种质资源保存中由于人为和自然缘故导致遗传结构改变的评价指标和评价方法.在介绍植物种质资源保存研究一些基本概念的基础上,归纳了测度种质库(收集品)遗传潜势的6种遗传多样性统计指标,包括同一变异层次的类型数、类型分布均衡度、遗传相似性与遗传距离、遗传方差与遗传变异系数、多元变异指数以及亲本系数.指出若无遗传丰富度相伴,单有遗传离散度并未提供遗传多样性的完整测度.探讨了人为条件导致植物种质资源遗传结构改变的遗传流失、环境胁迫所致植物种质资源遗传结构改变的遗传脆弱性和种子扩繁所引发的植物种质资源遗传结构改变的遗传漂变和遗传漂移等的统计指标.文末给出了自花授粉植物和异花授粉植物群体适宜样本容量研究的个例.     

Cellular automaton simulation examining progenitor hierarchy structure effects on mammary ductal carcinoma in situ

A computer simulation is used to model ductal carcinoma in situ, a form of non-invasive breast cancer. The simulation uses known histological morphology, cell types, and stochastic cell proliferation to evolve tumorous growth within a duct. The ductal simulation is based on a hybrid cellular automaton design using genetic rules to determine each cell's behavior. The genetic rules are a mutable abstraction that demonstrate genetic heterogeneity in a population. Our goal was to examine the role (if any) that recently discovered mammary stem cell hierarchies play in genetic heterogeneity, DCIS initiation and aggressiveness. Results show that simpler progenitor hierarchies result in greater genetic heterogeneity and evolve DCIS significantly faster. However, the more complex progenitor hierarchy structure was able to sustain the rapid reproduction of a cancer cell population for longer periods of time.     

Estimates of marker-associated QTL effects in Monte Carlo backcross generations using multiple regression

Summary The decision of whether or not to use QTLassociated markers in breeding programs needs further information about the magnitude of the additive and dominance effects that can be estimated. The objectives of this paper are (1) to apply some of the Moreno-Gonzalez (1993) genetic models to backcross simulation data generated by the Monte Carlo method, and (2) to get simulation information about the number of testing progenies and mapping density in relation to the magnitude of gene effect estimates. Results of the Monte Carlo study show that the stepwise regression analysis was able to detect relatively small additive and dominance effects when the QTL are independently segregating. When testing selfed families derived from backcross individuals, dominance effects had a larger error standard deviation and were estimated at a lower frequency. Linked QTL require a higher marker mapping density on the genome and a larger number of progenies to detect small genetic effects. Reduction of the environmental error variance by evaluating selfed backcross families in replicate experiments increased the power of the test. Expressions of the number of progenies for detecting significant additive effects were developed for some genetic situations. The ratio of the within-backcross genetic variance to the square of a gene effect estimate is a function of the number of progenies, the heritability of the trait, the marker map density and the portion of the genetic variance explained by the model. Different values (from 0 to 1) assigned to (relative position of the QTL in the marker segment) did not cause a large shift in the residual mean square of the model.     

The sense and nonsense of direct-to-consumer genetic testing for cardiovascular disease

Expectations are high that increasing knowledge of the genetic basis of cardiovascular disease will eventually lead to personalised medicine—to preventive and therapeutic interventions that are targeted to at-risk individuals on the basis of their genetic profiles. Most cardiovascular diseases are caused by a complex interplay of many genetic variants interacting with many non-genetic risk factors such as diet, exercise, smoking and alcohol consumption. Since several years, genetic susceptibility testing for cardiovascular diseases is being offered via the internet directly to consumers. We discuss five reasons why these tests are not useful, namely: (1) the predictive ability is still limited; (2) the risk models used by the companies are based on assumptions that have not been verified; (3) the predicted risks keep changing when new variants are discovered and added to the test; (4) the tests do not consider non-genetic factors in the prediction of cardiovascular disease risk; and (5) the test results will not change recommendations of preventive interventions. Predictive genetic testing for multifactorial forms of cardiovascular disease clearly lacks benefits for the public. Prevention of disease should therefore remain focused on family history and on non-genetic risk factors as diet and physical activity that can have the strongest impact on disease risk, regardless of genetic susceptibility.     

Genotoxicity risk assessment: a proposed classification strategy

Recent advances in genetic toxicity (mutagenicity) testing methods and in approaches to performing risk assessment are prompting a renewed effort to harmonize genotoxicity risk assessment across the world. The US Environmental Protection Agency (EPA) first published Guidelines for Mutagenicity Risk Assessment in 1986 that focused mainly on transmissible germ cell genetic risk. Somatic cell genetic risk has also been a risk consideration, usually in support of carcinogenicity assessments. EPA and other international regulatory bodies have published mutagenicity testing requirements for agents (pesticides, pharmaceuticals, etc.) to generate data for use in genotoxicity risk assessments. The scheme that follows provides a proposed harmonization approach in which genotoxicity assessments are fully developed within the risk assessment paradigm used by EPA, and sets out a process that integrates newer thinking in testing battery design with the risk assessment process. A classification strategy for agents based on inherent genotoxicity, dose-responses observed in the data, and an exposure analysis is proposed. The classification leads to an initial level of concern for genotoxic risk to humans. A total risk characterization is performed using all relevant toxicity data and a comprehensive exposure evaluation in association with the genotoxicity data. The result of this characterization is ultimately used to generate a final level of concern for genotoxic risk to humans. The final level of concern and characterized genotoxicity risk assessment are communicated to decision makers for possible regulatory action(s) and to the public.     

Adenomas – Genetic factors in colorectal cancer prevention

Colorectal cancer is the second most common type of cancer both in Europe and Poland. During the last 30 years more than a 3-fold increase has been observed in Poland due to environmental and genetic factors. Almost all colorectal malignancies are related to the formation and malignant transformation of colorectal dysplasia and adenoma. Efforts aiming to decrease the number of colorectal cancer deaths are focused on the disease early detection. Genetic diagnosis for hereditary syndromes predisposing to colorectal cancer has been developed and is a part of the routine treatment. Most cancers are sporadic. They often develop from polyps in the colon. In addition to the genetic events described in the 1990s, showing the adenoma transformation into carcinoma that has been a prime example of malignant transformation for a long time, there are also other possibilities of neoplastic transformation. The recognition of colorectal cancer risk factors make sense as their nature is lifestyle- and diet-related. In this review paper those risk factors are presented and the prevention of colorectal cancer is discussed taking into account genetic factors.     

人类疾病遗传易感性研究方法进展

遗传易感性是指基于个人遗传背景的多基因遗传病发病风险,即来源于父母一方或双方的特定遗传变异在某些情况下会诱发疾病。在特定疾病的发病机制中某些高外显率的遗传变异发挥重要作用,此类疾病通过患病家系分析即可定位疾病相关遗传变异;但另一些低外显率变异的作用则不明显,需要大规模患病人群分析来解析遗传机制。近年来,随着二代测序和多组学分析技术的发展和基因组数据的大量积累,癌症、代谢性疾病、心脑血管疾病和精神疾病等疾病遗传易感性研究中取得了显著进展,为疾病的早期筛查和诊断治疗提供了参考。     

Genetics of Vesicoureteral Reflux

Vesicoureteral reflux (VUR) is the retrograde passage of urine from the bladder to the upper urinary tract. It is the most common congenital urological anomaly affecting 1-2% of children and 30-40% of patients with urinary tract infections. VUR is a major risk factor for pyelonephritic scarring and chronic renal failure in children. It is the result of a shortened intravesical ureter with an enlarged or malpositioned ureteric orifice. An ectopic embryonal ureteric budding development is implicated in the pathogenesis of VUR, which is a complex genetic developmental disorder. Many genes are involved in the ureteric budding formation and subsequently in the urinary tract and kidney development. Previous studies demonstrate an heterogeneous genetic pattern of VUR. In fact no single major locus or gene for primary VUR has been identified. It is likely that different forms of VUR with different genetic determinantes are present. Moreover genetic studies of syndromes with associated VUR have revealed several possible candidate genes involved in the pathogenesis of VUR and related urinary tract malformations. Mutations in genes essential for urinary tract morphogenesis are linked to numerous congenital syndromes, and in most of those VUR is a feature. The Authors provide an overview of the developmental processes leading to the VUR. The different genes and signaling pathways controlling the embryonal urinary tract development are analyzed. A better understanding of VUR genetic bases could improve the management of this condition in children.     

An equivalence between models of restricted selection and genetic groups

Summary An equivalence between a model of restricted selection and a model of genetic groups is presented. This correspondence leads to a realization of how genetic groups account for selection. Specifically, genetic groups act to remove the covariance between predictions of sire merit and functions of the true selection differentials. Further results illustrate a correspondence between models of selection on random effects and models of selection on residuals. Application of the results is useful, not in establishing concrete definitions for the structure of genetic groups, but in the analysis of how groups account for selection.     

Genetic polymorphism in varietal identification and genetic improvement

Summary New sources of genetic polymorphisms promise significant additions to the number of useful genetic markers in agricultural plants and animals, and prompt this review of potential applications of polymorphic genetic markers in plant and animal breeding. Two major areas of application can be distinguished. The first is based on the utilization of genetic markers to determine genetic relationships. These applications include varietal identification, protection of breeder's rights, and parentage determination. The second area of application is based on the use of genetic markers to identify and map loci affecting quantitative traits, and to monitor these loci during introgression or selection programs. A variety of breeding applications based on these possibilities can be envisaged for Selfers, particularly for those species having a relatively small genome size. These applications include: (i) screening genetic resources for useful quantitative trait alleles, and introgression of chromosome segments containing these alleles from resource strain to commercial variety; (ii) development of improved pure lines out of a cross between two existing commercial varieties; and (iii) development of crosses showing increased hybrid vigor. Breeding applications in segregating populations are more limited, particularly in species with a relatively large genome size. Potential applications, however, include: (i) preliminary selection of young males in dairy cattle on the basis of evaluated chromosomes of their proven sire; (ii) genetic analysis of resource strains characterized by high values for a particular quantitative trait, and introgression of chromosome segments carrying alleles contributing to the high values from resource strain to recipient strain.Contribution from The Agricultural Research Organization, The Volcani Center, Bet Dagan, Israel, No. 767-E, 1983 Series