SNP discovery in associating genetic variation with human disease phenotypes

With the completion of the human genome project, attention is now rapidly shifting towards the study of individual genetic variation. The most abundant source of genetic variation in the human genome is represented by single nucleotide polymorphisms (SNPs), which can account for heritable inter-individual differences in complex phenotypes. Identification of SNPs that contribute to susceptibility to common diseases will provide highly accurate diagnostic information that will facilitate early diagnosis, prevention, and treatment of human diseases. Over the past several years, the advancement of increasingly high-throughput and cost-effective methods to discover and measure SNPs has begun to open the door towards this endeavor. Genetic association studies are considered to be an effective approach towards the detection of SNPs with moderate effects, as in most common diseases with complex phenotypes. This requires careful study design, analysis and interpretation. In this review, we discuss genetic association studies and address the prospect for candidate gene association studies, comparing the strengths and weaknesses of indirect and direct study designs. Our focus is on the continuous need for SNP discovery methods and the use of currently available prescreening methods for large-scale genetic epidemiological research until more advanced sequencing methods currently under development will become available.     

New perspectives for the elucidation of genetic disorders

For almost 15 years, genome research has focused on the search for major risk factors in common diseases, with disappointing results. Only recently, whole-genome association studies have begun to deliver because of the introduction of high-density single-nucleotide-polymorphism arrays and massive enlargement of cohort sizes, but most of the risk factors detected account for only a small proportion of the total genetic risk, and their diagnostic value is negligible. There is reason to believe that the complexity of many "multifactorial" disorders is primarily due to genetic heterogeneity, with defects of different genes causing the same disease. Moreover, de novo copy-number variation has been identified as a major cause of mental retardation and other complex disorders, suggesting that new mutations are an important, previously overlooked factor in the etiology of complex diseases. These observations support the notion that research into the previously neglected monogenic disorders should become a priority of genome research. Because of the introduction of novel high-throughput, low-cost sequencing methods, sequencing and genotyping will soon converge, with far-reaching implications for the elucidation of genetic disease and health care.     

Delineating the Hemostaseome as an aid to individualize the analysis of the hereditary basis of thrombotic and bleeding disorders

Next-generation sequencing and genome-wide association studies represent powerful tools to identify genetic variants that confer disease risk within populations. On their own, however, they cannot provide insight into how these variants contribute to individual risk for diseases that exhibit complex inheritance, or alternatively confer health in a given individual. Even in the case of well-characterized variants that confer a significant disease risk, more healthy individuals carry the variant, with no apparent ill effect, than those who manifest disease. Access to low-cost genome sequence data promises to provide an unprecedentedly detailed view of the nature of the hereditary component of complex diseases, but requires the large-scale comparison of sequence data from individuals with and without disease to deliver a clinical calibration. The provision of informatics support remains problematic as there are currently no means to interpret the data generated. Here, we initiate this process, a prerequisite for such a study, by narrowing the focus from an entire genome to that of a single biological system. To this end, we examine the ‘Hemostaseome,’ and more specifically focus on DNA sequence changes pertaining to those human genes known to impact upon hemostasis and thrombosis that can be analyzed coordinately, and on an individual basis, to interrogate how specific combinations of variants act to confer disease predisposition. As a first step, we delineate known members of the Hemostaseome and explore the nature of the genetic variants that may cause disease in individuals whose hemostatic balance has become shifted toward either a prothrombotic or anticoagulant phenotype.     

Current Genomics in Cardiovascular Medicine

Cardiovascular disease (CVD) is a heterogeneous, complex trait that has a major impact on human morbidity and mortality. Common genetic variation may predispose to common forms of CVD in the community, and rare genetic conditions provide unique pathogenetic insights into these diseases. With the advent of the Human Genome Project and the genomic era, new tools and methodologies have revolutionised the field of genetic research in cardiovascular medicine. In this review, we describe the rationale for the current emphasis on large-scale genomic studies, elaborate on genome wide association studies and summarise the impact of genomics on clinical cardiovascular medicine and how this may eventually lead to new therapeutics and personalised medicine.     

人类身高的遗传学研究进展

人类身高是由环境和遗传因素共同决定的,遗传学研究发现遗传因素对身高差异的影响更大。身高是典型的多基因遗传性状,科研人员试图运用传统的连锁分析和关联分析寻找和发现对人类身高具有显著影响的常见DNA序列变异,但进展缓慢。近年来,随着基因分型和DNA测序技术的发展,人类身高的遗传学研究取得了很多突破性进展。全基因组关联分析(GWAS)的应用,发现和证实了上百个与人类身高相关的单核苷酸多态性位点(SNPs),拓展了人们对人类生长和发育的相关遗传学认识,同时也为研究人类其他复杂性状提供了理论依据和借鉴。本文综述了人类身高的遗传学研究进展,探讨了目前该研究领域所存在的问题和未来发展方向,以期为今后人类身高相关的遗传学研究提供参考和借鉴。     

Molecular genetics of schizophrenia: past, present and future

Schizophrenia is a severe neuropsychiatric disorder with a polygenic mode of inheritance which is also governed by non-genetic factors. Candidate genes identified on the basis of biochemical and pharmacological evidence are being tested for linkage and association studies. Neurotransmitters, especially dopamine and serotonin have been widely implicated in its etiology. Genome scan of all human chromosomes with closely spaced polymorphic markers is being used for linkage studies. The completion and availability of the first draft of Human Genome Sequence has provided a treasure-trove that can be utilized to gain insight into the so far inaccessible regions of the human genome. Significant technological advances for identification of single nucleotide polymorphisms (SNPs) and use of microarrays have further strengthened research methodologies for genetic analysis of complex traits. In this review, we summarize the evolution of schizophrenia genetics from the past to the present, current trends and future direction of research.     

Genomics and medicine: an anticipation. From Boolean Mendelian genetics to multifactorial molecular medicine

The major impact of the completion of the human genome sequence will be the understanding of diseases, with deduced therapy. In the field of genetic disorders, we will complete the catalogue of monogenic diseases, also called Mendelian diseases because they obey the Boolean logic of Mendel's laws. The major challenge now is to decipher the polygenic and multifactorial etiology of common diseases, such as cancer, cardio-vascular, nutritional, allergic, auto-immune and degenerative diseases. In fact, every gene, when mutated, is a potential disease gene, and we end up with the new concept of 'reverse medicine'; i.e., deriving new diseases or pathogenic pathways from the knowledge of the structure and function of every gene. By going from sequence to function (functional genomics and proteomics) we will gain insight into basic mechanisms of major functions such as cell proliferation, differentiation and development, which are perturbed in many pathological processes. By learning the meaning of some non-coding and of regulatory sequences our understanding will gain in complexity, generating a molecular and supramolecular integrated physiology, helping to build a molecular patho-physiology of the different syndromes. Besides those cognitive advances, there are also other issues at stake, such as: progress in diagnostic and prediction (predictive medicine); progress in therapy (pharmacogenomics and gene-based therapy); ethical issues; impact on business.     

Direct mutation analysis by high-throughput sequencing: from germline to low-abundant, somatic variants

DNA mutations are the source of genetic variation within populations. The majority of mutations with observable effects are deleterious. In humans mutations in the germ line can cause genetic disease. In somatic cells multiple rounds of mutations and selection lead to cancer. The study of genetic variation has progressed rapidly since the completion of the draft sequence of the human genome. Recent advances in sequencing technology, most importantly the introduction of massively parallel sequencing (MPS), have resulted in more than a hundred-fold reduction in the time and cost required for sequencing nucleic acids. These improvements have greatly expanded the use of sequencing as a practical tool for mutation analysis. While in the past the high cost of sequencing limited mutation analysis to selectable markers or small forward mutation targets assumed to be representative for the genome overall, current platforms allow whole genome sequencing for less than $5000. This has already given rise to direct estimates of germline mutation rates in multiple organisms including humans by comparing whole genome sequences between parents and offspring. Here we present a brief history of the field of mutation research, with a focus on classical tools for the measurement of mutation rates. We then review MPS, how it is currently applied and the new insight into human and animal mutation frequencies and spectra that has been obtained from whole genome sequencing. While great progress has been made, we note that the single most important limitation of current MPS approaches for mutation analysis is the inability to address low-abundance mutations that turn somatic tissues into mosaics of cells. Such mutations are at the basis of intra-tumor heterogeneity, with important implications for clinical diagnosis, and could also contribute to somatic diseases other than cancer, including aging. Some possible approaches to gain access to low-abundance mutations are discussed, with a brief overview of new sequencing platforms that are currently waiting in the wings to advance this exploding field even further.     

Chromatin and heritability: how epigenetic studies can complement genetic approaches

Despite the success in using genome-wide association studies to identify many loci associated with human disease, there are several gaps in understanding of how common genetic diseases are manifested. Epigenetic studies, which focus on DNA and chromatin modifications, have the potential to complement genetic approaches and provide more insight into mechanism, environmental effects and modes of inheritance, including the potential for non-DNA-based heritability. However, there are considerable challenges in designing and interpreting epigenetic studies associated with disease. Here, I review recent studies focused on individual variation in chromatin, and outline how epigenome-based studies can be used to complement genetic studies. In particular, I see more benefit to epigenetic studies being performed in the context of genetic studies, rather than as separate investigations.     

复杂疾病全基因组关联研究进展—— 研究设计和遗传标记

实现全基因组关联研究(Genome-wide association study, GWA)在数年前还是遗传学家们的梦想, 如今它已经变成了现实。自2005年Science杂志报道了第一项有关年龄相关性(视网膜)黄斑变性全基因组关联研究研究以来, 有关与复杂疾病的全基因组关联研究如雨后春笋般层出不穷。文中介绍了近两年来全基因组关联研究在复杂疾病研究领域内的主要发现、全基因组关联研究设计原理、遗传标记的选择、比较及相关商品信息。最后介绍了人类基因组拷贝数变异的研究进展, 总结了人类全基因组关联研究所取得成就和存在的问题, 并对全基因组关联研究未来的研究重点和要解决的问题进行了展望。     

Computational analysis of human genome polymorphism

While genome-era technologies focused on complete genome sequencing in various organisms, post-genome technologies aim at the understanding of the mechanisms of genetic information processing and elucidation of within-species variation. Single nucleotide polymorphisms (SNPs) are the most common source of genome variation in the human population. Nonsynonymous SNPs that occur in coding gene regions and result in amino acid substitutions are of particular interest. It is thought that such SNPs are responsible for phenotypic variation, quantitative traits, and the etiology of common diseases. PolyPhen is a computational tool for the prediction of putatively functional nonsynonymous SNPs by combining information of various types. The application areas of PolyPhen and similar methods include the genetics of complex diseases and congenital defects, the identification of functional mutations in model organisms, and evolutionary genetics.     

Twins. Novel uses to study complex traits and genetic diseases

The challenge faced by research into the genetic basis of complex disease is to identify genes of small relative effect against a background of substantial genetic and environmental variation. This has focused interest on a classical epidemiological design: the study of twins. Through their precise matching for age, the common family environment and background environmental variation, studying diseases in non-identical twins provides a means to enhance the power of conventional strategies to detect genetic influence through linkage and association. The unique matching of identical twins provides researchers with ways to isolate the function of individual genes involved in disease together with approaches to understanding how genes and the environment interact.     

SNP association studies in Alzheimer's disease highlight problems for complex disease analysis.

Genetic linkage and association analyses are two distinct approaches to understanding the genetic etiology of complex disease. Association analysis has become particularly popular in recent times, but the true utility of the strategy remains uncertain. To try to gain better insight into the relevant issues, we have used genetic association analysis to explore the etiology of Alzheimer's disease. Our empirical findings supplement the theoretical debate, illustrating the general doubtfulness of previous positive findings and the limited ability of typical association studies based on candidate genes to discern true medium-sized signals from false positives. Improvements in genotyping technologies and increasing the number of SNPs tested, without sophisticated allowance for all other issues, could simply lead to an unmanageable overload of false-positive signals, themselves obscuring true disease associations.     

Epigenetic modifications in rheumatoid arthritis

Over the last decades, genetic factors for rheumatoid diseases like the HLA haplotypes have been studied extensively. However, during the past years of research, it has become more and more evident that the influence of epigenetic processes on the development of rheumatic diseases is probably as strong as the genetic background of a patient. Epigenetic processes are heritable changes in gene expression without alteration of the nucleotide sequence. Such modifications include chromatin methylation and post-translational modification of histones or other chromatin-associated proteins. The latter comprise the addition of methyl, acetyl, and phosphoryl groups or even larger moieties such as binding of ubiquitin or small ubiquitin-like modifier. The combinatory nature of these processes forms a complex network of epigenetic modifications that regulate gene expression through activation or silencing of genes. This review provides insight into the role of epigenetic alterations in the pathogenesis of rheumatoid arthritis and points out how a better understanding of such mechanisms may lead to novel therapeutic strategies.     

Comparative genomics: the key to understanding the Human Genome Project

The sequencing of the human genome is well underway. Technology has advanced, such that the total genomic sequence is possible, along with an extensive catalogue of genes via comprehensive cDNA libraries. With the recent completion of the Saccharomyces cerevisiae sequencing project and the imminent completion of that of Caenorhabditis elegans, the most frequently asked question is how much can sequence data alone tell us? The answer is that that a DNA sequence taken in isolation from a single organism reveals very little. The vast majority of DNA in most organisms is noncoding. Protein coding sequences or genes cannot function as isolated units without interaction with noncoding DNA and neighboring genes. This genomic environment is specific to each organism. In order to understand this we need to look at similar genes in different organisms, to determine how function and position has changed over the course of evolution. By understanding evolutionary processes we can gain a greater insight into what makes a gene and the wider processes of genetics and inheritance. Comparative genomics (with model organisms), once the poor relation of the human genome project, is starting to provide the key to unlock the DNA code.     

An integrated epigenetic and genetic approach to common human disease

Epigenetic information is heritable during cell division but is not contained within the DNA sequence itself. Despite increasing evidence for and interest in the role of epigenetics in human disease, particularly in cancer, virtually no epigenetic information is routinely or systematically measured at the genome level. The current population-based approach to common disease relates common DNA sequence variants to either disease status or incremental quantitative traits contributing to disease. Although this purely genetic approach is powerful and general, there is currently no conceptual framework to integrate epigenetic information. In this article, we propose an approach to common human disease that incorporates epigenetic variation into genetic studies. Epigenetic variation might also help to explain the late onset and progressive nature of most common diseases, the quantitative nature of complex traits and the role of environment in disease development, which a purely sequence-based approach might not.     

Using single nucleotide polymorphisms as a means to understanding the pathophysiology of asthma

Asthma is the most common chronic childhood disease in the developed nations, and is a complex disease that has high social and economic costs. Studies of the genetic etiology of asthma offer a way of improving our understanding of its pathogenesis, with the goal of improving preventive strategies, diagnostic tools, and therapies. Considerable effort and expense have been expended in attempts to detect specific polymorphisms in genetic loci contributing to asthma susceptibility. Concomitantly, the technology for detecting single nucleotide polymorphisms (SNPs) has undergone rapid development, extensive catalogues of SNPs across the genome have been constructed, and SNPs have been increasingly used as a method of investigating the genetic etiology of complex human diseases. This paper reviews both current and potential future contributions of SNPs to our understanding of asthma pathophysiology.     

The genetics of human personality

Personality traits are the relatively enduring patterns of thoughts, feelings and behaviors that reflect the tendency to respond in certain ways under certain circumstances. Twin and family studies have showed that personality traits are moderately heritable, and can predict various lifetime outcomes, including psychopathology. The Research Domain Criteria characterizes psychiatric diseases as extremes of normal tendencies, including specific personality traits. This implies that heritable variation in personality traits, such as neuroticism, would share a common genetic basis with psychiatric diseases, such as major depressive disorder. Despite considerable efforts over the past several decades, the genetic variants that influence personality are only beginning to be identified. We review these recent and increasingly rapid developments, which focus on the assessment of personality via several commonly used personality questionnaires in healthy human subjects. Study designs covered include twin, linkage, candidate gene association studies, genome‐wide association studies and polygenic analyses. Findings from genetic studies of personality have furthered our understanding about the genetic etiology of personality, which, like neuropsychiatric diseases themselves, is highly polygenic. Polygenic analyses have showed genetic correlations between personality and psychopathology, confirming that genetic studies of personality can help to elucidate the etiology of several neuropsychiatric diseases.     

The human genome project--some implications of extensive "reverse genetic" medicine

Impressive progress has been made during the past several decades in understanding the pathogenesis of human genetic disease. The tools of molecular biology have allowed the isolation of many disease-related genes by forward and a few by reverse genetics, and the imminent completion of a complete human genetic linkage map will accelerate the genetic characterization of many more genetic diseases. The major impacts of the molecular characterization of human genetic diseases will be 1. To increase markedly the number of human diseases that we recognize to have major genetic components. We already understand that genetic diseases are not rare medical curiosities with negligible societal impact, but rather constitute a wide spectrum of both rare and extremely common diseases responsible for an immense amount of suffering in all human societies. The characterization of the human genome will lead to the identification of genetic factors in many more human diseases, even those that now seem too multifactorial or polygenic for ready understanding. 2. To allow the development of powerful new approaches to diagnosis, detection, screening and even therapy of these disorders aimed directly at the mutant genes rather than at the gene products. This should eventually allow much more accurate and specific management of human genetic disease and the genetic factors in many human maladies. The preparation of a fine-structure physical map of the entire human genome together with an overlapping contiguous set of clones spanning entire chromosomes or large portions of chromosomes is rapidly becoming feasible, and the information that will flow from this effort promises eventually to affect the management of many important genetic diseases.(ABSTRACT TRUNCATED AT 250 WORDS)