Association of Genetic polymorphism of PPARγ-2, ACE,MTHFR, FABP-2 and FTO genes in risk prediction of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a non-autoimmune, complex, heterogeneous and polygenic metabolic disease condition characterized by persistent elevated blood glucose levels (hyperglycemia). India as said to be the diabetic capital of the world is likely to experience the largest increase in T2DM and a greater number of diabetic individuals in the world by the year 2030. Identification of specific genetic variations in a particular ethnic group has a critical role in understanding the risk of developing T2DM in a much efficient way in future. These genetic variations include numerous types of polymorphisms among which single nucleotide polymorphisms (SNPs) is the most frequent. SNPs are basically located within the regulatory elements of several gene sequences. There are scores of genes interacting with various environmental factors affecting various pathways and sometimes even the whole signalling network that cause diseases like T2DM. This review discusses the biomarkers for early risk prediction of T2DM. Such predictions could be used in order to understand the pathogenesis of T2DM and to better diagnostics, treatment, and eventually prevention.     

血脂异常遗传性疾病的研究现状

血脂异常(Dyslipidemia)是指血浆中胆固醇和(或)甘油三酯水平升高, 可导致严重的心血管疾病, 常以冠心病和脑中风为首发表现, 该类疾病严重危害着人们的健康。一些血脂异常疾病具有遗传性, 主要包括孟德尔遗传和多基因遗传。传统检测血脂异常相关基因的方法主要有DNA测序和连锁分析, 适合于孟德尔遗传性血脂异常疾病。最近几年兴起的新一代测序技术(Next-generation sequencing)不仅适用于孟德尔遗传性血脂异常疾病的研究, 同样适用于复杂性血脂异常疾病。2006年至今, 运用全基因组关联分析(Genome wide association study, GWAS)筛出许多与血脂异常疾病相关的基因, 这些基因和早期孟德尔遗传家系确定的基因多数相同。GWAS频谱分析发现, 复杂性疾病相关的基因变异频率存在差异, 并且几乎所有筛查出的与血脂异常疾病相关的单核苷酸多态性(Single nucleotide polymorphisms, SNPs)变异均位于非编码区, 使得人们逐渐对非编码区基因变异展开了研究。血脂异常致病基因的发现和基因变异致病机制的阐明, 为血脂异常疾病提供新的治疗靶点, 并为新一代药物筛选提供新思路。文章对血脂异常遗传性疾病的研究现状进行了综述。     

Genome-wide association study as a method to analyze the genome architecture in polygenic diseases,with the example of multiple sclerosis

Genome-wide association study (GWAS) provides a powerful tool for investigating the genetic architecture of human polygenic diseases and is generally used to identify the genetic factors of disease susceptibility, clinical phenotypes, and treatment response. The differences in allele frequencies of single nucleotide polymorphisms (SNPs) distributed throughout the genome are analyzed with a microarray technique or other technologies that allow simultaneous genotyping at several tens of thousands to several millions of SNPs per sample. Owing to its power to find out highly reliable differences between patients and controls, GWAS became a common approach to identification of the genetic susceptibility factors in complex diseases of a polygenic nature. Using multiple sclerosis (MS) as a prototype complex disease, the review considers the main achievements and challenges of using GWAS to identify the genes involved in the disease and, therefore, to better understand the pathogenetic molecular mechanisms and genetic risk factors.     

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.     

动物转基因新技术研究进展

动物转基因技术是21世纪发展最为迅速的生物高新技术之一, 它是指通过基因工程技术将外源基因整合到受体动物基因组中, 从而使其得以表达和遗传的生物技术。动物转基因的关键限制因素是转基因效率和基因表达的精确调控。目前有多种转基因技术, 每一种技术各有其优缺点, 仍然需要进一步研究。随着研究的深入, 转基因技术必将在探讨基因功能、动物遗传改良、生物反应器、动物疾病模型、器官移植等领域有广阔的应用前景。文章综述了近年发展的提高转基因效率的生殖干细胞法、提高转基因精确性的基因打靶法、RNA干扰(RNAi)介导的基因沉默技术和诱导多能干细胞(iPS)转基因技术。新的转基因技术为转基因动物的研究提供了更好的平台, 可以加快促进人类医药卫生、畜牧生产等领域的发展。     

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。     

A case–control study between interleukin-10 gene variants and periodontal disease in dogs

Periodontal disease (PD) refers to a group of inflammatory diseases that affect the periodontium, the organ which surrounds and supports the teeth. PD is a highly prevalent disease with a multifactorial etiology and, in humans the individual susceptibility is known to be strongly determined by genetic factors. Several candidate genes have been studied, namely genes related with molecules involved in the inflammatory response. Interleukin-10 (IL-10) is a cytokine with important anti-inflammatory and immunomodulatory roles, and several studies indicate an association between IL10 polymorphisms and PD. In dogs, an important animal model in periodontology, PD is also a highly prevalent naturally occurring disease, and only now are emerging the first studies evaluating the genetic predisposition. In this case–control study, a population of 90 dogs (40 dogs with PD and 50 healthy dogs) was used to study the IL10 gene, and seven new genetic variations in this gene were identified. No statistically significant differences were detected in genotype and allele frequencies of these variations between the PD cases and control groups. Nevertheless, one of the variations (IL10/2_g.285G > A) leads to an amino acid change (glycine to arginine) in the putative signal peptide, being predicted a potential influence on IL-10 protein functionality. Further investigations are important to clarify the biological importance of these new findings. The knowledge of these genetic determinants can help to understand properly the complex causal pathways of PD, with important clinical implications.     

The value of animal models in predicting genetic susceptibility to complex diseases such as rheumatoid arthritis

For a long time, genetic studies of complex diseases were most successfully conducted in animal models. However, the field of genetics is now rapidly evolving, and human genetics has also started to produce strong candidate genes for complex diseases. This raises the question of how to continue gene-finding attempts in animals and how to use animal models to enhance our understanding of gene function. In this review we summarize the uses and advantages of animal studies in identification of disease susceptibility genes, focusing on rheumatoid arthritis. We are convinced that animal genetics will remain a valuable tool for the identification and investigation of pathways that lead to disease, well into the future.     

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。     

Global genetic analysis

The introduction of molecular markers in genetic analysis has revolutionized medicine. These molecular markers are genetic variations associated with a predisposition to common diseases and individual variations in drug responses. Identification and genotyping a vast number of genetic polymorphisms in large populations are increasingly important for disease gene identification, pharmacogenetics and population-based studies. Among variations being analyzed, single nucleotide polymorphisms seem to be most useful in large-scale genetic analysis. This review discusses approaches for genetic analysis, use of different markers, and emerging technologies for large-scale genetic analysis where millions of genotyping need to be performed.     

Personalisierte Medizin – Vision oder Fiktion? Beispiel: Altersdiabetes

Typical civilization diseases, such as type II diabetes, are common, complex in the underlying pathogenic mechanisms, heterogenous in the phenotype and multifactorial due to a wide variety of possible combinations of disease susceptibility or protective genes in different relevant tissues and negative or positive environmental factors. This is in sharp contrast to classical inherited diseases, such as Chorea Huntington, which are often caused by complete loss‐ or gain‐of‐function mutations in a single gene. The causative polymorphisms of susceptibility genes, however, are characterized by relative subtle alterations in the function of the corresponding gene product, which per se do not support the pathogenesis, by high frequency, high expenditure for their identification and rather low predictive value. Consequently, the reliable and early diagnosis of civilization diseases depends on the individual determination of all (or as many as possible) polymorphisms of each susceptibility gene together with the corresponding gene products and the metabolites emerging thereof.     

Genetics and genomics of susceptibility and immune response to necrotic enteritis in chicken: a review

Global poultry production is facing many challenges and is currently under pressure due to the presence of several diseases like Necrotic Enteritis (NE). It is estimated that NE-caused global economic losses has increased from 2 billion to 6 billion US$ in 2015 because it is not easy to diagnose and control disease at the earlier stage of occurrence. Additionally, ban on the in-feed antibiotics and some other genetic and non-genetic predisposing factors affect the occurrence of the disease. Though the incidence of the disease can be reduced by minimizing the predisposing factors and through immunization of birds but there is no single remedy to control the disease. Therefore, we suggest that there is need to find out the genetic variants that could help to select the birds resistant to NE. The current review details the pertinent features about the genetic and genomics of susceptibility and immune response of birds to Necrotic Enteritis. We report here the list of candidate gene reported for their involvement with the susceptibility and/or resistance to the disease. However, most of these genes are involved in immune-related functions. For better understanding of the role of Clostridium perfringens and its toxins in the pathogenesis of disease there is need to unveil the association between any specific genetic variation and clinical status of NE. However, the presence of substantial genetic variations among different breeds/strains of chicken shows that it is possible to develop broiler strain with genetic resistant against NE. It would help in the cost-effective and sustainable production of safe broiler meat.     

Thematic review series: systems biology approaches to metabolic and cardiovascular disorders. Reverse engineering gene networks to identify key drivers of complex disease phenotypes

Diseases such as obesity, diabetes, and atherosclerosis result from multiple genetic and environmental factors, and importantly, interactions between genetic and environmental factors. Identifying susceptibility genes for these diseases using genetic and genomic technologies is accelerating, and the expectation over the next several years is that a number of genes will be identified for common diseases. However, the identification of single genes for disease has limited utility, given that diseases do not originate in complex systems from single gene changes. Further, the identification of single genes for disease may not lead directly to genes that can be targeted for therapeutic intervention. Therefore, uncovering single genes for disease in isolation of the broader network of molecular interactions in which they operate will generally limit the overall utility of such discoveries. Several integrative approaches have been developed and applied to reconstructing networks. Here we review several of these approaches that involve integrating genetic, expression, and clinical data to elucidate networks underlying disease. Networks reconstructed from these data provide a richer context in which to interpret associations between genes and disease. Therefore, these networks can lead to defining pathways underlying disease more objectively and to identifying biomarkers and more-robust points for therapeutic intervention.     

Genetic analysis of candidate genes modifying the age-at-onset in Huntington’s disease

The expansion of a polymorphic CAG repeat in the HD gene encoding huntingtin has been identified as the major cause of Huntington’s disease (HD) and determines 42–73% of the variance in the age-at-onset of the disease. Polymorphisms in huntingtin interacting or associated genes are thought to modify the course of the disease. To identify genetic modifiers influencing the age at disease onset, we searched for polymorphic markers in the GRIK2, TBP, BDNF, HIP1 and ZDHHC17 genes and analysed seven of them by association studies in 980 independent European HD patients. Screening for unknown sequence variations we found besides several silent variations three polymorphisms in the ZDHHC17 gene. These and polymorphisms in the GRIK2, TBP and BDNF genes were analysed with respect to their association with the HD age-at-onset. Although some of the factors have been defined as genetic modifier factors in previous studies, none of the genes encoding GRIK2, TBP, BDNF and ZDHHC17 could be identified as a genetic modifier for HD.Electronic Supplementary Material Supplementary material is available to authorised users in the online version of this article at .     

Adaptation, redundancy or resilience

Diversity creates resilience both in ecosystems and living organism. Yet, although genetic diversity protects organisms from many diseases and disorders, it also makes it much harder for geneticist to identify the risk factors that lead to common diseases.The study of the natural environment teaches us that ecological systems rich in biodiversity have greater resilience than less diverse systems, and that resource-poor ecosystems tend to have greater biodiversity to buffer against environmental change. The African savannah, a huge ecosystem, contains an abundance of grasses and other plants, herbivores and their predators. The loss of one species might be compensated for by the presence of others, but if species are relentlessly removed, one after another, the continuing loss will weaken the system until it changes its steady state and eventually collapses.To use another illustrative example of the protection conferred by diversity: modern agriculture uses only six cereal crops as the main basic staples of the human diet. If even one crop were threatened—perhaps by a plant virus or other pathogen—the consequences for humanity would probably be catastrophic. To avoid such a scenario, breeders have created hundreds of cultivars, each with minor phenotypic changes that confer resistance to a biotic or abiotic stressor. Thus, humans too create resilience by increasing biodiversity.In order to improve our understanding of complex diseases, we can extend this notion of diverse ecosystems to organisms. Similarly to the disappearance of one species in an ecosystem with abundant biodiversity, the loss of one gene function might not be immediately apparent, because many such changes can be compensated for, at least partly, by changes in other genes. However, a series of small, cumulative changes in many genes could lead to the breakdown of the phenotype of the organism, rendering it less resilient and more susceptible to disease, especially when it is under environmental or infectious stress. It is like throwing a stone in a pond, which generates small waves; throwing many stones at once causes a more complex disturbance, whereby waves combine to create bigger waves or attenuate each other by interference. Thus, even inherited disorders such as hypertrophic cardiomyopathy show several phenotypes as other genes modify the action of the affected gene.Geneticists have found many genes or whole genomic regions that have multiplied throughout the genome by duplication (Eisenstein, 2010). The repeated sequences might be identical, nearly identical or related, and they can be functional or non-functional, as is the case with pseudogenes. In terms of diversity, repeats have apparently given rise to multigene families, such as the collagens, which encode several structural proteins. Even microorganisms, such as Mycobacterium tuberculosis, have extended gene families or several insertions.It was assumed previously that pseudogenes are unnecessary gene copies and therefore inactivated. Yet, there is increasing evidence that they perform a regulatory role, by influencing the function of the parent gene. The variation in copy number also seems to be as, or even more, important than the number of polymorphisms, particularly in complex diseases or phenotypic traits. One negative example is the gene that codes for glutathione transferase, GSTM1. Roughly half of the population carries a deletion of GSTM1, which reduces their ability to neutralize isothiocyanates. Clearly then, many individuals will have two null alleles and an increased risk of xenobiotic-induced disease. Another fascinating example is that preference for a high-starch diet is associated with multiple copies of the salivary amylase gene, which increases production of this enzyme.Humans show a range of vulnerabilities to complex or infectious diseases, such as pulmonary tuberculosis. Despite an exhaustive search, no obvious, major resistance or susceptibility genes for tuberculosis have been found, although many genes—each with minor effects—have a role in disease susceptibility. Further support for the argument that resilience comes from diversity is found in the confusion around genetic association studies in many complex diseases, in which a given gene might be significantly associated with a condition in one population, but not in others. I suspect that many of these reports can be explained by the fact that susceptibility is caused by cumulative functional changes in many genes along different routes in different groups of humans or animals. In fact, susceptibility to a common disease conferred by a single, major locus would make the organism extremely vulnerable—which is exactly what we see with autosomal-dominant inherited diseases. Thus, it is unlikely that complex diseases are caused by a solitary gene defect, as evolution would select against the high risk of a single dominant effect. Instead, we see a range of conditions and phenotypes, owing to the large number of genes involved.This diversity of genetic factors is a blessing for humanity, as it has equipped us with enormous resilience against many common diseases, from cancer to coronary heart disease, to infectious diseases. But, it is also a bane for the geneticist and the clinical scientists who search for genetic factors that can be used to predict disease susceptibility, or the condition or progress of disease. Complexity and diversity make things far more unpredictable and messy—and therefore more difficult for scientific analysis—but both also ensure our survival against a daily assault of biotic and abiotic stressors.     

Genetic and molecular basis of quantitative trait loci of arthritis in rat: genes and polymorphisms

Rheumatoid arthritis (RA) is an autoimmune disease, the pathogenesis of which is affected by multiple genetic and environmental factors. To understand the genetic and molecular basis of RA, a large number of quantitative trait loci (QTL) that regulate experimental autoimmune arthritis have been identified using various rat models for RA. However, identifying the particular responsible genes within these QTL remains a major challenge. Using currently available genome data and gene annotation information, we systematically examined RA-associated genes and polymorphisms within and outside QTL over the whole rat genome. By the whole genome analysis of genes and polymorphisms, we found that there are significantly more RA-associated genes in QTL regions as contrasted with non-QTL regions. Further experimental studies are necessary to determine whether these known RA-associated genes or polymorphisms are genetic components causing the QTL effect.