人系统性红斑狼疮的候选基因

人系统性红斑狼疮(systemic lupus erythematosus,SLE)是一种复合性多基因的自身免疫性疾病,遗传因素在SLE的发病机制中发挥重要作用。该文介绍近几年对SLE候选基因(经典的和新发现的候选基因)的研究成果;分析遗传因素与疾病的易感性、临床表型和病程进展的密切关系,为SLE的预防、诊断和治疗提供参考。     

遗传性白内障动物模型的研究进展

白内障是严重影响公众健康的重大疾病。人群中, 大部分遗传性白内障是外显率较高的常染色体显性遗传, 但也有X连锁和常染色体隐性遗传存在。随着分子生物学技术的发展, 出现了许多白内障遗传动物模型, 这些模型有助于揭示白内障的发病机制, 为晶状体的发育和生理学研究提供新的见解, 还有助于进一步了解遗传、环境和营养等因素对晶状体的作用方式, 并为白内障遗传病的诊断和治疗提供依据。文章综述了遗传性白内障动物模型的相关基因、突变形式及其研究进展。     

面肩肱型肌营养不良症的分子机制和治疗方法研究进展

面肩肱型肌营养不良症(facioscapulohumeral muscular dystrophy, FSHD)是世界范围内位列第三的肌营养不良症,呈常染色体显性遗传。FSHD以肌肉坏死为特征,在疾病表现、进展和发病年龄方面具有显著的家族内和家庭间变异性。在不同的年龄段,FSHD的症状表现程度各不相同,通常在青少年时期发病,20岁前的外显率达95%。本文综述了FSHD的发病机制、诊断和治疗的现状,并重点阐述了与治疗相关的研究进展,为今后该疾病的机制研究和临床治疗提供了参考。     

冠心病易感基因的筛选

作为一种多基因疾病 ,冠心病是由遗传和环境因素共同作用的结果 ,在许多国家是主要的死因之一。由于目前冠心病的发病机制尚不十分清楚 ,阻碍了其易感基因的定位分离研究。冠心病遗传因素的确定 ,显然将有助于其易感基因定位分离研究。迄今除发现了个别的相关基因外 ,绝大部分的遗传易感性相关基因尚未被发现 ,其研究仍然存在许多问题。为此 ,本文就其易感基因可能的研究策略和方法作一综述。这些方法同样也适用于诸如中风、外周血管阻塞、高血压、心力衰竭等心血管疾病以及其它多基因疾病     

牛疾病相关基因的DNA变异及遗传控制

牛基因组中一些重要基因的DNA突变通过改变基因的表达和蛋白质功能来影响机体对疾病的抗性或易感性。控制牛疾病的DNA变异主要分为单基因座及多基因座两类。导致疾病的单基因座类型亦称因果突变,其遗传基础较简单,突变一般位于基因编码区或非编码区,多为单碱基或少数几个碱基的突变,这些突变导致氨基酸的错义突变、翻译提前终止或部分外显子缺失等。相比而言,多基因相关疾病的遗传基础较为复杂,遗传-病原体-环境间的互作是导致这类复杂疾病的主要原因。文章综述了由单基因座和多基因座遗传变异所控制的牛主要疾病的研究和应用现状,以及在牛育种及生产中为降低这些疾病的发生所采用的遗传控制策略。     

人类基因组SNPs的研究现状及应用前景

基因组DNA是生物体各种生理、病理性状的物质基础,人类DNA序列变异约90%表现为单核苷酸多态性(singlenucleotidepolymorphisms,SNPs),这是一种常见的遗传变异类型,在人类基因组中广泛存在,被认为是人类疾病易感性和药物反应的决定性因素。本文主要介绍了SNPs的分类及特点、人类基因组SNPs的研究现状、SNPs在实践中的应用,以及SNPs在遗传作图、医药、遗传易感性、个体化医疗等方面的研究前景,并探讨了当前SNPs研究中存在的问题。     

人音猬因子相互作用蛋白基因与慢性阻塞性肺疾病

慢性阻塞性肺疾病是呼吸系统常见慢性疾病。该疾病的发病与环境及多基因变异有关。近年的研究显示,人音猬因子相互作用蛋白基因参与多个系统疾病的发生发展,尤其对于呼吸系统该基因与慢性阻塞性肺疾病发病密切相关,该基因上某些单核苷酸多态性与慢性阻塞性肺疾病易感性相关,且在慢性阻塞性肺疾病患者肺组织内存在该基因低表达。另外,该基因与FEV1和FEV1/FVC关系密切,对肺功能有保护作用。目前的研究提示该基因和音猬信号通路在肺胚胎发育、基因表达调控、细胞增殖、细胞凋亡和平滑肌修复等方面发挥着重要调控作用,为慢性阻塞性肺疾病发病机制的研究指明了方向。本文就人音猬因子相互作用蛋白基因与慢性阻塞性肺疾病相关性的研究进展作一综述。     

炎症性肠病发病机制研究进展

炎症性肠病(IBD)是一种慢性复发性肠道炎症性疾病,其病因未明,发病率逐年增高。目前研究表明,IBD的发病机制是遗传易感性和环境对菌群相互作用的结果,通过削弱肠道屏障导致肠道免疫过度激活引起的疾病。本文将从遗传、环境、肠道屏障和免疫学的角度,综述IBD的发病机制。     

遗传风险评分在复杂疾病遗传学研究中的应用

心血管疾病、2型糖尿病、原发性高血压、哮喘、肥胖、肿瘤等复杂疾病在全球范围内流行,并成为人类死亡的主要原因。越来越多的人开始关注遗传易感性在复杂疾病发病机制中的作用。至今,与复杂疾病相关的易感基因和基因序列变异仍未完全清楚。人们希望通过遗传关联研究来阐明复杂疾病的遗传基础。近年来,全基因组关联研究和候选基因研究发现了大量与复杂疾病有关的基因序列变异。这些与复杂疾病有因果和(或)关联关系的基因序列变异的发现促进了复杂疾病预测和防治方法的产生和发展。遗传风险评分(Genetic risk score,GRS)作为探索单核苷酸多态(Single nucleotide polymorphisms,SNPs)与复杂疾病临床表型之间关系的新兴方法,综合了若干SNPs的微弱效应,使基因多态对疾病的预测性大幅度提升。该方法在许多复杂疾病遗传学研究中得到成功应用。本文重点介绍了GRS的计算方法和评价标准,简要列举了运用GRS取得的系列成果,并对运用过程中所存在的局限性进行了探讨,最后对遗传风险评分的未来发展方向进行了展望。     

原发性高血压相关基因DNA甲基化的研究进展

高血压是常见的慢性疾病,也是心脑血管病最主要的风险因素。原发性高血压是由多基因和环境因素共同作用引起的复杂疾病,但具体的发病机制仍不清楚。随着研究的深入,DNA甲基化等表观遗传学因素在原发性高血压病理过程中起到的作用逐渐受到重视。本文总结了部分原发性高血压关联基因中DNA甲基化在其患病中的研究进展,阐述可受环境因素影响的DNA甲基标记与原发性高血压的关系,进一步了解高血压的发病机制。     

Gene SNPs and mutations in clinical genetic testing: haplotype-based testing and analysis

Haplotype-based analysis using high-density single nucleotide polymorphism (SNP) markers have gained increasing attention in evaluating candidate genes in various clinical situations. For example, haplotype information is useful for predicting the severity and prognosis of certain genetic disorders. The intragenic cis-interactions between the common polymorphisms and the pathogenic mutations of prion protein (PRNP) and cystic fibrosis transmembrane conductance regulator (CFTR) genes greatly influence the phenotypes and the disease penetrance of hereditary Creutzfeldt-Jakob disease and cystic fibrosis. Merits of haplotype study are more evident in the fine mapping of complex diseases and in identifying genetic variations that influence individual's response to drugs. Knowledge-based approaches and/or linkage analyses using SNP tagged haplotypes are effective tools in detecting genetic associations. For example, haplotype studies in the inflammatory bowel disease susceptibility loci revealed diverse cis and trans gene-gene interactions, which can affect the clinical outcomes. Although currently, we have very limited knowledge on haplotype-phenotypic characterizations of most genes, these examples demonstrate that increased understanding of the clinically relevant haplotypes will provide better results in the diagnosis and possibly in the treatment of both monogenic and polygenic diseases.     

The effect of genetic diversity on angiogenesis

Angiogenesis is the process by which new blood vessels are formed from existing vessels. Mammalian populations harbor genetic variations that alter angiogenesis. Some of these changes result in Mendelian traits of variable penetrance, with telangiectasia being a common symptom. Other more subtle variations exist, with promoter variations in the VEGF gene being of particular interest. Genetic diversity in angiogenesis-regulating genes has been linked to increased susceptibility to multiple angiogenesis-dependent diseases in humans. These diseases include cancer, arthritis, atherosclerosis, and cardiovascular disease, endometriosis, diabetic retinopathy, retinopathy of prematurity, psoriasis, and sarcoidosis. Also, multiple disturbances in pregnancy including miscarriage, spontaneous preterm delivery, and severe pre-eclampsia have been linked to alterations in angiogenesis-regulating genes. Present efforts to dissect the complexity of the genetic diversity that regulates angiogenesis have used laboratory animals due to the availability of genome sequence for many species and the ability to perform high volume controlled breeding. Ongoing mapping studies have identified multiple loci that control angiogenic responsiveness in several mouse models. Genetic alterations responsible for discrete angiogenic alterations will then be studied in appropriate mouse disease models.     

Varying coefficient model for gene-environment interaction: a non-linear look

MOTIVATION: The genetic basis of complex traits often involves the function of multiple genetic factors, their interactions and the interaction between the genetic and environmental factors. Gene-environment (G×E) interaction is considered pivotal in determining trait variations and susceptibility of many genetic disorders such as neurodegenerative diseases or mental disorders. Regression-based methods assuming a linear relationship between a disease response and the genetic and environmental factors as well as their interaction is the commonly used approach in detecting G×E interaction. The linearity assumption, however, could be easily violated due to non-linear genetic penetrance which induces non-linear G×E interaction. RESULTS: In this work, we propose to relax the linear G×E assumption and allow for non-linear G×E interaction under a varying coefficient model framework. We propose to estimate the varying coefficients with regression spline technique. The model allows one to assess the non-linear penetrance of a genetic variant under different environmental stimuli, therefore help us to gain novel insights into the etiology of a complex disease. Several statistical tests are proposed for a complete dissection of G×E interaction. A wild bootstrap method is adopted to assess the statistical significance. Both simulation and real data analysis demonstrate the power and utility of the proposed method. Our method provides a powerful and testable framework for assessing non-linear G×E interaction.     

Genetic mapping of common diseases: the challenges of manic-depressive illness and schizophrenia

Advances in genetic mapping of human diseases have led to the identification of single locus susceptibility for several common disorders. There have been a number of reports of linkage for the psychiatric disorders manic-depressive illness and schizophrenia, but none of these linkage reports is uncontested. Nonetheless, it appears promising to continue attempts to map these psychiatric disorders, since linkage can now be detected even when the inheritance is complex and includes genetic heterogeneity and variable penetrance.     

Epigenetic silencing of genomic structural variations

A great amount of copy number variations (CNVs) are identified in the human genome. Most of them are neutral; nevertheless, the role of CNVs in the pathogenesis of hereditary diseases is still significant. Especially, this is important for neuropsychiatric disorders, such as intellectual disability and autism. When analyzing the CNV-associated diseases, the controversial question is to distinguish the pathogenic CNVs among common polymorphic variants and to predict the disease risk in other children of the family. Unfortunately, the mechanisms of phenotypic expression and incomplete penetrance of CNVs remain largely unknown. Currently, incomplete penetrance and variable expressivity of CNVs are attributed mainly to allelic interaction of different genetic variations. However, epigenetic mechanisms of gene expression regulation in the context of structural variation of the genome are poorly explored. It is possible that epigenetic modifications of the genome regions with CNVs may underlie the understanding of ways of phenotypic manifestations of structural variations in the human genome.     

Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease

Some individuals with a particular disease-causing mutation or genotype fail to express most if not all features of the disease in question, a phenomenon that is known as ‘reduced (or incomplete) penetrance’. Reduced penetrance is not uncommon; indeed, there are many known examples of ‘disease-causing mutations’ that fail to cause disease in at least a proportion of the individuals who carry them. Reduced penetrance may therefore explain not only why genetic diseases are occasionally transmitted through unaffected parents, but also why healthy individuals can harbour quite large numbers of potentially disadvantageous variants in their genomes without suffering any obvious ill effects. Reduced penetrance can be a function of the specific mutation(s) involved or of allele dosage. It may also result from differential allelic expression, copy number variation or the modulating influence of additional genetic variants in cis or in trans. The penetrance of some pathogenic genotypes is known to be age- and/or sex-dependent. Variable penetrance may also reflect the action of unlinked modifier genes, epigenetic changes or environmental factors. At least in some cases, complete penetrance appears to require the presence of one or more genetic variants at other loci. In this review, we summarize the evidence for reduced penetrance being a widespread phenomenon in human genetics and explore some of the molecular mechanisms that may help to explain this enigmatic characteristic of human inherited disease.     

Evidence that autoimmunity in man is a Mendelian dominant trait.

Family studies of autoimmune diseases are consistent with multifactorial etiology. However, familial occurrence of the autoimmune trait as defined by the presence of autoimmune disease and/or high titer autoantibody supports the hypothesis that autoimmunity is inherited as an autosomal dominant trait. Based on genetic analysis of 18 autoimmune kindreds, the population frequency of this primary autoimmune gene is approximately .10 with penetrance estimates of 92% in females and 49% in males. The estimated high penetrance of the autoimmune gene in females suggests that the interacting genetic and/or environmental factors must be numerous or ubiquitous. Sex, age, and specific major histocompatibility complex (MHC) antigens are among the genetic and physiological factors known to influence autoimmunity. A genetic model is proposed that takes these factors into account. Inherent in the hypothesis of a primary autoimmune gene is that it is epistatic to other, secondary, genes that influence the autoimmune phenotype. The genetic model further postulates that the secondary genes, including those of the MHC, confer specificity to the phenotype. The effects of the secondary genes can be modulated by gonadal steroids and, over time, may be abrogated by environmental challenges, such as viral infections.     

The influence of foliar diseases and their control by selective fungicides on a range of groundnut (Arachis hypogaea L.) genotypes

Twenty groundnut genotypes were grown with various spray treatments which controlled either, only rust, or only leaf spot diseases, or all of these diseases or none of them. The genotypes varied in their resistance to these diseases, some having resistance to only one disease and some having resistance or susceptibility to all the diseases. Chemical control of the diseases resulted in variations in leaf area protection and in yield which were specific to each genotype. For some genotypes the diseases had little influence on yield and foliage, while for others yield and remaining green leaf were varied greatly by the control of diseases. For many of the genotypes the yield achieved was well related to variations in the green leaf remaining at maturity as a result of the spray treatments. Genotypes with good levels of genetic resistance did not have high yield potentials while those with the best yields when diseases were controlled were the most susceptible to these diseases.     

Genomics: implications for toxicology

The primary goal of the Environmental Genome Project (EGP) is the identification of human polymorphisms indicative of susceptibility to specific environmental agents. Despite evidence for a substantial genetic contribution to disease variation in the population, progress towards identifying specific genes has been slow. To date, most of the advances in our understanding of human diseases has come from genetic analyses of monogenic diseases that affect a relatively small portion of the population. The principal strategy of the EGP involves resequencing DNA samples from populations representative of the US racial and ethnic groups to develop a database of variations. Polymorphisms in specific genes may also be detected by gene-expression profiling. The identification of polymorphisms by resequencing is straightforward, and can be accomplished with minimal difficulty. Gene-expression profiling is still problematic; however, determining the functional significance of the allelic variations will be a monumental challenge involving sophisticated proteomics and population-based and animal model studies. These studies will change radically the practice of public health and clinical medicine, and the approach to the development of pharmaceuticals.     

Pathway analysis of seven common diseases assessed by genome-wide association

Recent genome-wide association studies (GWAS) have identified DNA sequence variations that exhibit unequivocal statistical associations with many common chronic diseases. However, the vast majority of these studies identified variations that explain only a very small fraction of disease burden in the population at large, suggesting that other factors, such as multiple rare or low-penetrance variations and interacting environmental factors, are major contributors to disease susceptibility. Identifying multiple low-penetrance variations (or "polygenes") contributing to disease susceptibility will be difficult. We present a pathway analysis approach to characterizing the likely polygenic basis of seven common diseases using the Wellcome Trust Case Control Consortium (WTCCC) GWAS results. We identify numerous pathways implicated in disease predisposition that would have not been revealed using standard single-locus GWAS statistical analysis criteria. Many of these pathways have long been assumed to contain polymorphic genes that lead to disease predisposition. Additionally, we analyze the genetic relationships between the seven diseases, and based upon similarities with respect to the associated genes and pathways affected in each, propose a new way of categorizing the diseases.