The genetics of complex diseases

Genetic factors influence virtually every human disorder, determining disease susceptibility or resistance and interactions with environmental factors. Our recent successes in the genetic mapping and identification of the molecular basis of mendelian traits have been remarkable. Now, attention is rapidly shifting to more-complex, and more-prevalent, genetic disorders and traits that involve multiple genes and environmental effects, such as cardiovascular disease, diabetes, rheumatoid arthritis and schizophrenia. Rather than being due to specific and relatively rare mutations, complex diseases and traits result principally from genetic variation that is relatively common in the general population. Unfortunately, despite extensive efforts by many groups, only a few genetic regions and genes involved in complex diseases have been identified. Completion of the human genome sequence will be a seminal accomplishment, but it will not provide an immediate solution to the genetics of complex traits.     

The genetics of complex diseases

Genetic factors influence virtually every human disorder, determining disease susceptibility or resistance and interactions with environmental factors. Our recent successes in the genetic mapping and identification of the molecular basis of mendelian traits have been remarkable. Now, attention is rapidly shifting to more-complex, and more-prevalent, genetic disorders and traits that involve multiple genes and environmental effects, such as cardiovascular disease, diabetes, rheumatoid arthritis and schizophrenia. Rather than being due to specific and relatively rare mutations, complex diseases and traits result principally from genetic variation that is relatively common in the general population. Unfortunately, despite extensive efforts by many groups, only a few genetic regions and genes involved in complex diseases have been identified. Completion of the human genome sequence will be a seminal accomplishment, but it will not provide an immediate solution to the genetics of complex traits.     

多基因遗传病基因研究的策略和方法

基因在决定个体表型方面起着决定性的作用。虽然单基因疾病的致病基因的克隆工作取得了显著的进展,但对于多基因疾病来说,仍然存在许多问题,同时也是巨大的挑战。本文综述了多基因疾病的遗传特点和多基因疾病易感基因识别、分离和克隆的一般步骤和存在的问题,介绍了人类基因组计划在此过程中的作用和单核苷酸多态性的应用前景,提出 了最有可能克隆出多基因疾病易感基因的策略和方法。     

全基因组关联研究在复杂性疾病遗传研究中的应用

在过去的几年中,人们应用全基因组关联研究(genomewide association studies,GWAS)对多种人类复杂性疾病及性状进行研究,如糖尿病、肿瘤、心血管疾病、神经精神系统疾病、自身免疫性疾病等,且已经鉴定出大量与之密切相关的遗传变异,为进一步探索人类复杂性疾病的遗传特征提供重要线索。但是,由于影响复杂性疾病的因素较多,许多已发现遗传变异对疾病贡献较小,作用机制尚不清楚,现全基因组关联研究亦存在许多问题。今本文就GWAS在复杂性疾病中的应用做一综述,并就其前景做一展望。     

Molecular genetics of atherosclerosis

Atherosclerosis is a complex multifocal arterial disease involving interactions of multiple genetic and environmental factors. Advances in techniques of molecular genetics have revealed that genetic polymorphisms significantly influence susceptibility to atherosclerotic vascular diseases. A large number of candidate genes, genetic polymorphisms and susceptibility loci associated with atherosclerotic diseases have been identified in recent years and their number is rapidly increasing. In this review we focus on some of the major candidate genes and genetic polymorphisms associated with human atherosclerotic vascular diseases.     

Twin-Based DNA Methylation Analysis Takes the Center Stage of Studies of Human Complex Diseases

The etiology of complex diseases is characterized by the interaction between the genome and environmental conditions and the interface of epigenetics may be a central mechanism. Current technologies already allow us high-throughput profiling of epigenetic patterns at genome level. However, our understanding of the epigenetic processes remains limited. Twins are special samples in genetic studies due to their genetic similarity and rearing-environment sharing. In the past decades, twins have made a great contribution in dissecting the genetic and environmental contributions to human diseases and complex traits. In the era of functional genomics, the valuable samples of twins are helping to bridge the gap between gene activity and environmental conditions through epigenetic mechanisms unlimited to DNA sequence variations. We review the recent progresses in using twins to study disease-related molecular epigenetic phenotypes and link them with environmental exposures especially early life events. Various study designs and application issues will be highlighted and discussed with aim at making uses of twins in assessing the environmental impact on epigenetic changes during the development of complex diseases.     

Asthma: a major pediatric health issue

Asthma and associated phenotypes are complex traits most probably caused by an interaction of multiple disease susceptibility genes and environmental factors. Major achievements have occurred in identifying chromosomal regions and polymorphisms in candidate genes linked to or associated with asthma, atopic dermatitis, IgE levels and response to asthma therapy. The aims of this review are to explain the methodology of genetic studies of multifactorial diseases, to summarize chromosomal regions and polymorphisms in candidate genes linked to or associated with asthma and associated traits, to list genetic alterations that may alter response to asthma therapy, and to outline genetic factors that may render individuals more susceptible to asthma and atopy due to environmental changes.     

Interactions between genes and environmental factors in asthma and atopy: new developments

Asthma and associated phenotypes are complex traits most probably caused by an interaction of multiple disease susceptibility genes and environmental factors. Major achievements have occurred in identifying chromosomal regions and polymorphisms in candidate genes linked to or associated with asthma, atopic dermatitis, IgE levels and response to asthma therapy. The aims of this review are to explain the methodology of genetic studies of multifactorial diseases, to summarize chromosomal regions and polymorphisms in candidate genes linked to or associated with asthma and associated traits, to list genetic alterations that may alter response to asthma therapy, and to outline genetic factors that may render individuals more susceptible to asthma and atopy due to environmental changes.     

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.     

A polygenic basis for late-onset disease

The biological basis of late-onset disease has been shaped by genetic factors subject to varying degrees of evolutionary constraint. Late-onset traits are not only more sensitive to environmental variation, owing to the breakdown of homeostatic mechanisms, but they also show higher levels of genetic variation than traits directly influencing reproductive fitness. The origin and nature of this variation suggests that current strategies are poorly suited to identifying genes involved in many complex diseases.     

From genotype to phenotype: genetics and medical practice in the new millennium

The completion of the human genome project will provide a vast amount of information about human genetic diversity. One of the major challenges for the medical sciences will be to relate genotype to phenotype. Over recent years considerable progress has been made in relating the molecular pathology of monogenic diseases to the associated clinical phenotypes. Studies of the inherited disorders of haemoglobin, notably the thalassaemias, have shown how even in these, the simplest of monogenic diseases, there is remarkable complexity with respect to their phenotypic expression. Although studies of other monogenic diseases are less far advanced, it is clear that the same level of complexity will exist. This information provides some indication of the difficulties that will be met when trying to define the genes that are involved in common multigenic disorders and, in particular, in trying to relate disease phenotypes to the complex interactions between many genes and multiple environmental factors.     

Gene-environment interactions in human disease: nuisance or opportunity?

Many environmental risk factors for common, complex human diseases have been revealed by epidemiologic studies, but how genotypes at specific loci modulate individual responses to environmental risk factors is largely unknown. Gene-environment interactions will be missed in genome-wide association studies and could account for some of the 'missing heritability' for these diseases. In this review, we focus on asthma as a model disease for studying gene-environment interactions because of relatively large numbers of candidate gene-environment interactions with asthma risk in the literature. Identifying these interactions using genome-wide approaches poses formidable methodological problems, and elucidating molecular mechanisms for these interactions has been challenging. We suggest that studying gene-environment interactions in animal models, although more tractable, might not be sufficient to shed light on the genetic architecture of human diseases. Lastly, we propose avenues for future studies to find gene-environment interactions.     

Genetic and environmental factors in health-related behaviors: studies on Finnish twins and twin families.

Family, twin and adoption studies have provided evidence for familial and genetic influences on individual differences in disease risk and in human behavior. Attempts to identify individual genes accounting for these differences have not been outstandingly successful to date, and at best, known genes account for only a fraction of the familiality of most traits or diseases. More detailed knowledge of the dynamics of gene action and of specific environmental conditions are needed. Twin and twin-family studies with multiple measurements of risk factors and morbidity over time can permit a much more detailed assessment of the developmental dynamics of disease risk and the unfolding of behavioral risk factors.     

同卵双胞胎在复杂性状DNA甲基化调控机制研究中的应用

同卵双胞胎来源于同一个受精卵,DNA序列基本一致,但在某些重要表型上如复杂疾病,并不完全一样。利用表型不一致的同卵双胞胎进行研究,能在遗传背景、母体效应、年龄性别效应等一致的基础上,深入研究分析复杂性状的表观调控机制。而DNA甲基化是最为稳定的一类表观遗传修饰。在人类中,利用同卵双胞胎对印记异常疾病、精神类疾病、自身免疫病及癌症等疾病的DNA甲基化调控研究已经揭示了多个致病基因,为研究疾病的表观调控以及表观遗传学药物的应用打下了基础。本文着重对同卵双胞胎DNA甲基化状态、DNA甲基化遗传力计算以及复杂性状DNA甲基化调控的研究应用及其进展展开综述,以期为复杂性状表观调控机制研究提供借鉴和参考。     

Power evaluations for family-based tests of association with incomplete parental genotypes

While a variety of methods have been developed to deal with incomplete parental genotype information in family-based association tests, sampling design issues with incomplete parental genotype data still have not received much attention. In this article, we present simulation studies with four genetic models and various sampling designs and evaluate power in family-based association studies. Efficiency depends heavily on disease prevalence. With rare diseases, sampling affecteds and their parents is preferred, and three sibs will be required to have close power if parents are unavailable. With more common diseases, sampling affecteds and two sibs will generally be more efficient than trios. When parents are unavailable, siblings need not be phenotyped if the disease is rare, but a loss of power will result with common diseases. Finally, for a class of complex traits where other genetic and environmental factors also cause phenotypic correlation among siblings, little loss of efficiency occurs to rare disease, but substantial loss of efficiency occurs to common disease.     

Dissecting cause and effect in the pathogenesis of psychiatric disorders: genes, environment and behaviour

It has long been established that the development of psychiatric illness results from a complex interplay between genetic and environmental factors. Postmortem and genetic linkage studies have identified a number of promising candidate genes which have been reinforced by replication and functional studies. However, the fact that concordance rates for monozygotic twins rarely approach 100% highlights the involvement of environmental factors. Whilst epidemiological studies of psychiatric cohorts have demonstrated potential risk factors, such studies are clearly limited and in many cases the potential mechanism linking a given risk factor with pathogenesis remains unclear. A very powerful method of elucidating the mechanisms underlying gene-environment interactions is the use of appropriate animal models of psychiatric pathology. Whilst animals cannot be used to map the entire complexity of diseases such as schizophrenia, dissecting the symptom profile into more simply encapsulated traits or endophenotypes has proved to be a successful approach. Such endophenotypes provide a measurable link between aetiological factors and phenotypic outcome. Given the potential for the careful control and modification of an experimental animal's environment, the combination of studies of candidate genes with investigations of environmental factors is an effective heuristic tool, allowing examination of behavioural endophenotypes in conjunction with cellular and molecular outcomes. This review will consider the extant genetic, molecular, pharmacological and lesion-based models of psychiatric disorders, and the relevant methods of environmental manipulation appearing in the literature. We will discuss studies where such models have been combined, and the potential for future experimentation in this area.     

Progress and promise in understanding the genetic basis of common diseases

Susceptibility to common human diseases is influenced by both genetic and environmental factors. The explosive growth of genetic data, and the knowledge that it is generating, are transforming our biological understanding of these diseases. In this review, we describe the technological and analytical advances that have enabled genome-wide association studies to be successful in identifying a large number of genetic variants robustly associated with common disease. We examine the biological insights that these genetic associations are beginning to produce, from functional mechanisms involving individual genes to biological pathways linking associated genes, and the identification of functional annotations, some of which are cell-type-specific, enriched in disease associations. Although most efforts have focused on identifying and interpreting genetic variants that are irrefutably associated with disease, it is increasingly clear that—even at large sample sizes—these represent only the tip of the iceberg of genetic signal, motivating polygenic analyses that consider the effects of genetic variants throughout the genome, including modest effects that are not individually statistically significant. As data from an increasingly large number of diseases and traits are analysed, pleiotropic effects (defined as genetic loci affecting multiple phenotypes) can help integrate our biological understanding. Looking forward, the next generation of population-scale data resources, linking genomic information with health outcomes, will lead to another step-change in our ability to understand, and treat, common diseases.     

The latest fashions in skin disease.

The complex nature of epidermal tissue homeostasis is borne out by the range of diseases affecting this tissue. Indeed, mutations in proteins involved in intracellular integrity and cell-cell or cell-matrix adhesion can cause disease in an appropriate epidermal compartment. The most important realization in epidermal disease in the last two years has been that point mutations in key structural genes can result in filaments collapsing, cell cytolysis, or cell adhesion defects; and that these defects can result in severe human skin disease. Now that these associations have been made, the important next step will be to alleviate the suffering of these patients. Animal models will be an important part of these investigations; many molecules including growth factors, oncogenes, and cell adhesion molecules have been targeted to the epidermis of transgenic mice to investigate their role in disease. Such animal models should also elucidate the causes of diseases like psoriasis, a very common skin disease, the molecular basis of which remains elusive. Gene therapy involving the replacement of defective genes or local delivery of therapeutic molecules will be one of the main goals in alleviating these known epidermal diseases. Such protocols in the epidermis are aided by the relative accessibility of the skin and the presence of the "stem cells" in relatively accessible compartments. Indeed, as the last few years have shed much light on the genetic causes of epidermal disease, it is hoped that the next several years will prove as illuminating in the alleviation of these diseases.     

Advances in Bayesian multiple quantitative trait loci mapping in experimental crosses

Many complex human diseases and traits of biological and/or economic importance are determined by interacting networks of multiple quantitative trait loci (QTL) and environmental factors. Mapping QTL is critical for understanding the genetic basis of complex traits, and for ultimate identification of genes responsible. A variety of sophisticated statistical methods for QTL mapping have been developed. Among these developments, the evolution of Bayesian approaches for multiple QTL mapping over the past decade has been remarkable. Bayesian methods can jointly infer the number of QTL, their genomic positions and their genetic effects. Here, we review recently developed and still developing Bayesian methods and associated computer software for mapping multiple QTL in experimental crosses. We compare and contrast these methods to clearly describe the relationships among different Bayesian methods. We conclude this review by highlighting some areas of future research.