Molecular genetic approaches for studying the etiology of diabetic nephropathy

A critical challenge faced by clinical nephrologists today is the escalating number of patients developing end stage renal disease, a major proportion of which is attributed to diabetic nephropathy (DN). The need for new measures to prevent and treat this disease cannot be overemphasized. To this end, modern genetic approaches provide powerful tools to investigate the etiology of DN. Human studies have already established the importance of genetic susceptibility for DN. Several major susceptibility loci have been identified using linkage studies. In addition, linkage studies in rodents have pinpointed promising chromosomal segments that influence renal traits. Besides augmenting our understanding of disease pathogenesis, these animal studies may facilitate the cloning of disease susceptibility genes in man through the identification of homologous regions that contribute to renal disease. In human diabetes, various genes have been evaluated for their risk contribution to DN. This widespread strategy has been propelled by our knowledge of the glucose-activated pathways underlying DN. Evidence has emerged that a true association does indeed exist for some candidate genes. Furthermore, the in vivo manipulation of gene expression has shown that these genes can modify features of DN in transgenic and knockout rodent models, thus corroborating the findings from human association studies. Still, the exact molecular mechanisms involving these genes remain to be fully elucidated. This formidable task may be accomplished by continuing to harness the synergy between human and experimental genetic approaches. In this respect, our review provides a first synthesis of the current literature to facilitate this challenging effort.     

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     

Multifactorial diseases: a nightmare for the geneticist

Common diseases are often familial, but they do not show in most families, a simple pattern of inheritance. In a few families these diseases may be caused by a mutation in a single gene. In most families these diseases are multifactorial, they result from a complex interaction between a genetic component which is often polygenic and many environmental factors. Two major, model free, methods are used to locate and identify susceptibility genes that predispose to multifactorial diseases. The first is a non parametric linkage analysis that relies on affected sib pairs, or an affected pedigree member, the second method is association studies which looks for increase frequency of particular alleles or genotypes in affected compared with unaffected individuals in the population. Most of the results have not been replicated, identifying susceptibility genes is proving much more difficult than most geneticists imagined 20 years ago. The main reason for this irreproducibility is genetic heterogeneity.     

Deep resequencing identifies candidate functional genes in leprosy GWAS loci

Leprosy is the second most prevalent mycobacterial disease globally. Despite the existence of an effective therapy, leprosy incidence has consistently remained above 200,000 cases per year since 2010. Numerous host genetic factors have been identified for leprosy that contribute to the persistently high case numbers. In the past decade, genetic epidemiology approaches, including genome-wide association studies (GWAS), identified more than 30 loci contributing to leprosy susceptibility. However, GWAS loci commonly encompass multiple genes, which poses a challenge to define causal candidates for each locus. To address this problem, we hypothesized that genes contributing to leprosy susceptibility differ in their frequencies of rare protein-altering variants between cases and controls. Using deep resequencing we assessed protein-coding variants for 34 genes located in GWAS or linkage loci in 555 Vietnamese leprosy cases and 500 healthy controls. We observed 234 nonsynonymous mutations in the targeted genes. A significant depletion of protein-altering variants was detected for the IL18R1 and BCL10 genes in leprosy cases. The IL18R1 gene is clustered with IL18RAP and IL1RL1 in the leprosy GWAS locus on chromosome 2q12.1. Moreover, in a recent GWAS we identified an HLA-independent signal of association with leprosy on chromosome 6p21. Here, we report amino acid changes in the CDSN and PSORS1C2 genes depleted in leprosy cases, indicating them as candidate genes in the chromosome 6p21 locus. Our results show that deep resequencing can identify leprosy candidate susceptibility genes that had been missed by classic linkage and association approaches.     

Introduction to Deep Sequencing and Its Application to Drug Addiction Research with a Focus on Rare Variants

Through linkage analysis, candidate gene approach, and genome-wide association studies (GWAS), many genetic susceptibility factors for substance dependence have been discovered such as the alcohol dehydrogenase gene (ALDH2) for alcohol dependence (AD) and nicotinic acetylcholine receptor (nAChR) subunit variants on chromosomes 8 and 15 for nicotine dependence (ND). However, these confirmed genetic factors contribute only a small portion of the heritability responsible for each addiction. Among many potential factors, rare variants in those identified and unidentified susceptibility genes are supposed to contribute greatly to the missing heritability. Several studies focusing on rare variants have been conducted by taking advantage of next-generation sequencing technologies, which revealed that some rare variants of nAChR subunits are associated with ND in both genetic and functional studies. However, these studies investigated variants for only a small number of genes and need to be expanded to broad regions/genes in a larger population. This review presents an update on recently developed methods for rare-variant identification and association analysis and on studies focused on rare-variant discovery and function related to addictions.     

The Comparative Toxicogenomics Database (CTD): a resource for comparative toxicological studies

The etiology of most chronic diseases involves interactions between environmental factors and genes that modulate important biological processes (Olden and Wilson, 2000. Nat Rev Genet 1(2):149-153). We are developing the publicly available Comparative Toxicogenomics Database (CTD) to promote understanding about the effects of environmental chemicals on human health. CTD identifies interactions between chemicals and genes and facilitates cross-species comparative studies of these genes. The use of diverse animal models and cross-species comparative sequence studies has been critical for understanding basic physiological mechanisms and gene and protein functions. Similarly, these approaches will be valuable for exploring the molecular mechanisms of action of environmental chemicals and the genetic basis of differential susceptibility.     

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.     

Gene variants for osteoporosis and their pleiotropic effects in aging

The prevalence of osteoporosis is raising worldwide as improving conditions of living and treatment of other common diseases continuously increases life expectancy. Thus, osteoporosis affects most women above 80 years of age and, at the age of 50, the lifetime risk of suffering an osteoporosis-related fracture approaches 50% in women and 20% in men. Numerous genetic, hormonal, nutritional and life-style factors contribute to the acquisition and maintenance of bone mass. Among them, genetic variations explain as much as 70% of the variance for bone mineral density (BMD) in the population. Dozens of quantitative trait loci (QTLs) for BMD have been identified by genome screening and linkage approaches in humans and mice, and more than 100 candidate gene polymorphisms tested for association with BMD and/or fracture. Sequence variants in the vitamin D receptor (VDR), collagen 1 alpha 1 chain (Col1A1), estrogen receptor alpha (ESR1), interleukin-6 (IL-6) and LDL receptor-related protein 5 (LRP5) genes were all found to be significantly associated with differences in BMD and/or fracture risk in multiple replication studies. Moreover, some genes, such as VDR and IL-6, were shown to interact with non-genetic factors, i.e. calcium intake and estrogens, to modulate BMD. Since these gene variants have also been associated with other complex disorders, including cancer and coronary heart disease, they may represent common genetic susceptibility factors exerting pleiotropic effects during the aging process.     

Genetics of preeclampsia: an approach to genetic linkage studies

Due to its high prevalence during pregnancies, preeclampsia is considered an important public health problem. Many investigators agree in that its expression is related to the interaction between genetic and environmental factors. Many studies have searched for genetic factors, attempting to identify chromosomal regions or candidate genes whose variants may be related to high preeclampsia susceptibility. Several studies have associated a number of susceptibility genes to preeclampsia, but the results have not been replicated consistently in all populations. Mapping of genes and chromosomal regions by linkage analysis has located potential markers on chromosomes 2 and 4. Identification of the genes located in these candidate regions will pinpoint the genetic risk factors, will lead to a better understanding of the syndrome, and will provide clues for its prevention and treatment.     

Effects of measured susceptibility genes on cancer risk in family studies

Numerous family studies have been performed to assess the associations between cancer incidence and genetic and non-genetic risk factors and to quantitatively evaluate the cancer risk attributable to these factors. However, mathematical models that account for a measured hereditary susceptibility gene have not been fully explored in family studies. In this report, we proposed statistical approaches to precisely model a measured susceptibility gene fitted to family data and simultaneously determine the combined effects of individual risk factors and their interactions. Our approaches are structured for age-specific risk models based on Cox proportional hazards regression methods. They are useful for analyses of families and extended pedigrees in which measured risk genotypes are segregated within the family and are robust even when the genotypes are available only in some members of a family. We exemplified these methods by analyzing six extended pedigrees ascertained through soft-tissue sarcoma patients with p53 germ-line mutations. Our analyses showed that germ-line p53 mutations and sex had significant interaction effects on cancer risk. Our proposed methods in family studies are accurate and robust for assessing age-specific cancer risk attributable to a measured hereditary susceptibility gene, providing valuable inferences for genetic counseling and clinical management.     

Genetic risk factors of venous thrombosis

Venous thrombosis, whose main clinical presentations include deep vein thrombosis and pulmonary embolism, represents a major health problem worldwide. Numerous conditions are known to predispose to venous thrombosis and these conditions are commonly referred to as risk indicators or risk factors. Generally accepted or "classically" acquired risk factors for venous thromboembolism include advanced age, prolonged immobilisation, surgery, fractures, use of oral contraceptives and hormone replacement therapy, pregnancy, puerperium, cancer and antiphospholipid syndrome. In addition to these well-established risk factors for venous thrombosis, several lines of evidence that have emerged over the past few decades indicate a role of novel genetic risk factors, mainly related to the haemostatic system, in influencing thrombotic risk. The most significant breakthrough has been the confirmation of the concept that inherited hypercoagulable conditions are present in a large proportion of patients with venous thromboembolic disease. These include mutations in the genes that encode antithrombin, protein C and protein S, and the factor V Leiden and factor II G20210 A mutations. Moreover, plasmatic risk indicators, such as hyperhomocysteinemia and elevated concentrations of factors II, VIII, IX, XI and fibrinogen, have also been documented. This extensive list of genetic and acquired factors serves to illustrate that a single cause of venous thrombosis does not exist and that this condition should be considered as a complex or multifactorial trait. Complex traits can be understood by assuming an interaction between different mutations in candidate susceptibility genes. The risk that is associated with each genetic defect may be relatively low in isolation but the simultaneous presence of several mutations may dramatically increase disease susceptibility. Moreover, environmental factors may interact with one or more genetic variations to add further to the risk. The analysis of genetic risk factors and plasmatic factors, together with private life style and environmental factors, has contributed significantly to our understanding of the genetic predisposition to venous thrombosis.     

Current strategies in the search for low penetrance genes in cancer

The genetic etiology of most cancers remains largely unclear and it has been hypothesised that common genetic variants with modest effects on disease susceptibility cause the bulk of this unexplained risk. Case-control association studies are considered the most effective strategy to identify these low-penetrance genes. While traditionally, such studies have focused on putative functional single nucleotide polymorphisms (SNPs) in candidate genes, a more comprehensive approach can now be taken, as a result of a number of recent developments: the mapping of the human genome, including the identification of almost ten million SNPs; and the development of high-throughput genotyping technologies that enable hundreds of thousands of SNPs to be genotyped in a single reaction, in multiple subjects and at an affordable cost. All common genomic variation can be captured by genotyping SNPs in gene-, pathway- or genome-wide-based strategies and these are now being applied to many diseases, including cancer. We present an outline of each of these approaches, including recent published examples, and discuss a number of challenges that remain to be addressed.     

Getting under the skin: the immunogenetics of psoriasis

Psoriasis is a chronic inflammatory disorder of the skin that is mediated by T cells, dendritic cells and inflammatory cytokines. We now understand many of the cellular alterations that underlie this disease, and genomic approaches have recently been used to assess the alterations of gene expression in psoriatic skin lesions. Genetic susceptibility factors that contribute to predisposition to psoriasis are now also being identified. It is hoped that we will soon be able to correlate the cellular pathogenesis that occurs in psoriasis with these genetic factors. In this Review article, we describe what is known about genes that confer increased susceptibility to psoriasis, and we integrate this with what is known about the molecular and cellular mechanisms that occur in other inflammatory and autoimmune disorders.     

The genetic epidemiology of multiple sclerosis

Epidemiological studies have implicated an interplay between genetic and environmental factors in the aetiology of multiple sclerosis (MS). There is a familial recurrence rate of approximately 15%. Meta-analysis of the recurrence risk shows that the rate is highest overall for siblings, then parents and children, with lower rates in second- and third-degree relatives. Recurrence is highest for monozygotic twins. Conversely, the frequency in adoptees is similar to the population lifetime risk. The age-adjusted risk for half siblings is also less than for full siblings. Recurrence is higher in the children of conjugal pairs with MS than the offspring of single affected. These classical genetic observations suggest that MS is a complex trait in which susceptibility is determined by several genes acting independently or epistatically. Comparisons between co-affected sibling pairs provide no evidence for correlation with age or year at onset and mode of presentation or disability. Thus far, the identification of susceptibility genes has proved elusive but genetic strategies are now in place which should illuminate the problem. The main dividend will be an improved understanding of the pathogenesis. To date, population studies have demonstrated an association between the class II major histocompatibility complex (MHC) alleles DR15 and DQ6 and their corresponding genotypes. An association with DR4, with or without the primary DR15 link, is seen in some Mediterranean populations. Candidate gene approaches have otherwise proved unrewarding. Four groups of investigators have undertaken a systematic search of the genome. In common with most other complex traits, no major susceptibility gene has been identified but regions of interest have been provisionally identified. These genetic analyses are predicated on the assumption that MS is one disease. Genotypic and phenotypic analyses are beginning to question this assumption. A major part of future studies in the genetics of MS will be to resolve the question of disease heterogeneity.     

Genetic and genomic insights into the molecular basis of atherosclerosis

Atherosclerosis is a complex disease involving genetic and environmental risk factors, acting on their own or in synergy. Within the general population, polymorphisms within genes in lipid metabolism, inflammation, and thrombogenesis are probably responsible for the wide range of susceptibility to myocardial infarction, a fatal consequence of atherosclerosis. Genetic linkage studies have been carried out in both humans and mouse models to identify these polymorphisms. Approximately 40 quantitative trait loci for atherosclerotic disease have been found in humans, and approximately 30 in mice. Recently, genome-wide association studies have been used to identify atherosclerosis-susceptibility polymorphisms. Although discovering new atherosclerosis genes through these approaches remains challenging, the pace at which these polymorphisms are being found is accelerating due to rapidly improving bioinformatics resources and biotechnologies. The outcome of these efforts will not only unveil the molecular basis of atherosclerosis but also facilitate the discovery of drug targets and individualized medication against the disease.     

Molecular and genetic mechanisms of obesity: implications for future management

Obesity has become a worldwide public health problem affecting millions of people. A disruption of the balance between energy intake and energy expenditure is believed to be the major cause of obesity. Substantial progress has been made in deciphering the pathogenesis of energy homeostasis over the past few years. The fact that obesity is under strong genetic control has been well established. Human monogenic obesity is rare in large populations, the most common form of obesity is considered to be a polygenic disorder arising from the interaction of multiple genetic and environmental factors. Here, we attempt to briefly review the most recent understanding of molecular mechanisms involved in energy homeostasis and adipogenesis. We discuss the advantages and disadvantages of various approaches commonly used in search for susceptibility genes for obesity. The main results from these genetic studies are summarized, with comments made on the most striking or representative findings. Finally, the implications of the recent advances in the understanding of molecular genetic mechanisms of body weight regulation on prevention and therapeutic intervention of obesity will be discussed.     

Recent advances in the genetics of osteoporosis

It has been known for over 20 years that osteoporosis is highly influenced by genetic factors. Bone mineral density (BMD) has also been shown to be highly heritable. Other known risk factors for osteoporotic fractures such as reduced bone quality, femoral neck geometry and bone turnover are now also known to be heritable. Susceptibility to osteoporosis is mediated, in all likelihood, by multiple genes each having small effect. Different approaches are being used currently to identify the many genes responsible. These include linkage studies in man and experimental animals as well as candidate gene studies and alterations in gene expression. Linkage studies have identified multiple quantitative trait loci (QTL) for regulation of BMD and, with twin studies, have indicated that the effects of these loci are partly site-dependent and sex-specific. On the whole, the genes responsible for BMD regulation at these QTL have not yet been isolated. Most studies have used the candidate gene approach. The vitamin D receptor gene (VDR), the collagen type I alpha 1 gene (COLIA1) and estrogen receptor gene (ER) alpha have been most widely investigated and found to play a role in regulating BMD, but the effects are modest and together probably account for less than 5% of the heritable contribution to BMD. Genes may vary in their influence of particular intermediate phenotypes, and we now know that not all genes influencing BMD will be important in fracture. In addition, the study of other diseases such as osteoarthritis and metabolic bone syndromes may prove fruitful in highlighting genes which overlap to osteoporosis as well. As large scale genetic testing becomes more cost-effective, recent findings have illustrated the potential of novel approaches. These include combining large multi-national populations for candidate gene analysis, meta-analyses, DNA pooling studies and gene expression studies.     

Limited evidence that cancer susceptibility regions are preferential targets for somatic mutation

BackgroundGenome wide-association studies have successfully identified several hundred independent loci harboring common cancer susceptibility alleles that are distinct from the more than 110 cancer predisposition genes. The latter are generally characterized by disruptive mutations in coding genes that have been established as ‘drivers’ of cancer in large somatic sequencing studies. We set out to determine whether, similarly, common cancer susceptibility loci map to genes that have altered frequencies of mutation.ResultsIn our analysis of the intervals defined by the cancer susceptibility markers, we observed that cancer susceptibility regions have gene mutation frequencies comparable to background mutation frequencies. Restricting analyses to genes that have been determined to be pleiotropic across cancer types, genes affected by expression quantitative trait loci, or functional genes indicates that most cancer susceptibility genes classified into these subgroups do not display mutation frequencies that deviate from those expected. We observed limited evidence that cancer susceptibility regions that harbor common alleles with small estimated effect sizes are preferential targets for altered somatic mutation frequencies.ConclusionsOur findings suggest a complex interplay between germline susceptibility and somatic mutation, underscoring the cumulative effect of common variants on redundant pathways as opposed to driver genes. Complex biological pathways and networks likely link these genetic features of carcinogenesis, particularly as they relate to distinct polygenic models for each cancer type.     

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。     

Identification of molecular genetic factors that influence migraine

Migraine is a common neurological disorder with a strong genetic basis. However, the complex nature of the disorder has meant that few genes or susceptibility loci have been identified and replicated consistently to confirm their involvement in migraine. Approaches to genetic studies of the disorder have included analysis of the rare migraine subtype, familial hemiplegic migraine with several causal genes identified for this severe subtype. However, the exact genetic contributors to the more common migraine subtypes are still to be deciphered. Genome-wide studies such as genome-wide association studies and linkage analysis as well as candidate genes studies have been employed to investigate genes involved in common migraine. Neurological, hormonal and vascular genes are all considered key factors in the pathophysiology of migraine and are a focus of many of these studies. It is clear that the influence of individual genes on the expression of this disorder will vary. Furthermore, the disorder may be dependent on gene–gene and gene–environment interactions that have not yet been considered. In addition, identifying susceptibility genes may require phenotyping methods outside of the International Classification of Headache Disorders II criteria, such as trait component analysis and latent class analysis to better define the ambit of migraine expression.