The genome revolution and its role in understanding complex diseases

The completion of the human genome sequence in 2003 clearly marked the beginning of a new era for biomedical research. It spurred technological progress that was unprecedented in the life sciences, including the development of high-throughput technologies to detect genetic variation and gene expression. The study of genetics has become “big data science”. One of the current goals of genetic research is to use genomic information to further our understanding of common complex diseases. An essential first step made towards this goal was by the identification of thousands of single nucleotide polymorphisms showing robust association with hundreds of different traits and diseases. As insight into common genetic variation has expanded enormously and the technology to identify more rare variation has become available, we can utilize these advances to gain a better understanding of disease etiology. This will lead to developments in personalized medicine and P4 healthcare. Here, we review some of the historical events and perspectives before and after the completion of the human genome sequence. We also describe the success of large-scale genetic association studies and how these are expected to yield more insight into complex disorders. We show how we can now combine gene-oriented research and systems-based approaches to develop more complex models to help explain the etiology of common diseases. This article is part of a Special Issue entitled: From Genome to Function.     

Modeling human disease in humans: the ciliopathies

Soon, the genetic basis of most human Mendelian diseases will be solved. The next challenge will be to leverage this information to uncover basic mechanisms of disease and develop new therapies. To understand how this transformation is already beginning to unfold, we focus on the ciliopathies, a class of multi-organ diseases caused by disruption of the primary cilium. Through a convergence of data involving mutant gene discovery, proteomics, and cell biology, more than a dozen phenotypically distinguishable conditions are now united as ciliopathies. Sitting at the interface between simple and complex genetic conditions, these diseases provide clues to the future direction of human genetics.     

Insight into Genotype-Phenotype Associations through eQTL Mapping in Multiple Cell Types in Health and Immune-Mediated Disease

Genome-wide association studies (GWAS) have transformed our understanding of the genetics of complex traits such as autoimmune diseases, but how risk variants contribute to pathogenesis remains largely unknown. Identifying genetic variants that affect gene expression (expression quantitative trait loci, or eQTLs) is crucial to addressing this. eQTLs vary between tissues and following in vitro cellular activation, but have not been examined in the context of human inflammatory diseases. We performed eQTL mapping in five primary immune cell types from patients with active inflammatory bowel disease (n = 91), anti-neutrophil cytoplasmic antibody-associated vasculitis (n = 46) and healthy controls (n = 43), revealing eQTLs present only in the context of active inflammatory disease. Moreover, we show that following treatment a proportion of these eQTLs disappear. Through joint analysis of expression data from multiple cell types, we reveal that previous estimates of eQTL immune cell-type specificity are likely to have been exaggerated. Finally, by analysing gene expression data from multiple cell types, we find eQTLs not previously identified by database mining at 34 inflammatory bowel disease-associated loci. In summary, this parallel eQTL analysis in multiple leucocyte subsets from patients with active disease provides new insights into the genetic basis of immune-mediated diseases.     

Identifying host targets for drug development with knowledge from genome-wide studies: lessons from HIV-AIDS

Advances in human genomics are now being effectively applied to the search for host factors underlying susceptibility to common diseases. From the steady stream of studies showing association of host genetic factors with viral diseases, it has become clear that host factors contribute substantially to the variability of viral infections in humans. Candidate gene studies that seek to show associations between single-nucleotide polymorphisms (SNPs) with a disease outcome have predominated, but whole-genome association studies (GWAS) have recently appeared. A major goal of these studies is to understand how human genetic variation contributes to individual differences in susceptibility and to exploit this knowledge for targeted drug development.     

Genetics of autoimmune diseases--disorders of immune homeostasis

In the past few years, our extensive knowledge of the mammalian immune system and our increasing ability to understand the genetic causes of complex human disease have opened a window onto the pathways that lead to autoimmune disorders. In addition to the well-established role of genetic variation that affects the major histocompatibility complex, a number of rare and common variants that affect a range of immunological pathways are now known to have important influences on the phenotypic diversity that is seen among autoimmune diseases. Recent studies have also highlighted a previously unanticipated interplay between the innate and adaptive immune system, providing a new direction for research in this field.     

Gene expression profiling of human diseases by serial analysis of gene expression

Until recently, the approach to understanding the molecular basis of complex syndromes such as cancer, coronary artery disease, and diabetes was to study the behavior of individual genes. However, it is generally recognized that expression of a number of genes is coordinated both spatially and temporally and that this coordination changes during the development and progression of diseases. Newly developed functional genomic approaches, such as serial analysis of gene expression (SAGE) and DNA microarrays have enabled researchers to determine the expression pattern of thousands of genes simultaneously. One attractive feature of SAGE compared to microarrays is its ability to quantify gene expression without prior sequence information or information about genes that are thought to be expressed. SAGE has been successfully applied to the gene expression profiling of a number of human diseases. In this review, we will first discuss SAGE technique and contrast it to microarray. We will then highlight new biological insights that have emerged from its application to the study of human diseases.     

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network(interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy(IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field.     

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)     

Human artificial chromosomes containing chromosome 17 alphoid DNA maintain an active centromere in murine cells but are not stable

Human artificial chromosomes (HACs) are autonomous molecules that can function and segregate as normal chromosomes in human cells. De novo HACs have successfully been used as gene expression vectors to complement genetic deficiencies in human cultured cells. HACs now offer the possibility of studying the regulation and expression of large genes in a variety of cell types from different tissues and correcting gene deficiencies caused by human inherited diseases. Complementary gene expression studies in mice, especially in mouse models of human genetic diseases, are also important in determining if large human transgenes can be expressed appropriately from artificial chromosomes. Toward this aim we are establishing artificial chromosomes in murine cells as novel gene expression vectors. Initially we transferred HAC vectors into murine cells, but were unable to generate de novo HACs at a reasonable frequency. We then transferred HACs previously established in human HT1080 cells to three different murine cell types by microcell fusion, followed by positive selection. We observed that the HACs in murine cells bound centromere protein C (CENP-C), a marker of active centromeres, and were detected under selection but rapidly lost when selection was removed. These results suggest that the HACs maintain at least a partially functional centromere complex in murine cells, but other factors are required for stability and segregation. Artificial chromosomes containing mouse centromeric sequences may be required for better stability and maintenance in murine cells.     

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.     

Concepts and strategies for human gene therapy.

Methods of modern molecular genetics have been developed that allow stable transfer and expression of foreign DNA sequences in human and other mammalian somatic cells. It is therefore no surprise that the methods have been applied in attempts to complement genetic defects and correct disease phenotypes. Two decades of research have now led to the first clinically applicable attempts to introduce genetically modified cells into human beings to cure diseases caused at least partially by genetic defects. We discuss here some of the strategies being followed for both in vitro and in vivo application of therapeutic gene transfer and summarize some of the technical and conceptual difficulties associated with somatic-cell gene therapy.     

A study of CNVs as trait-associated polymorphisms and as expression quantitative trait loci

We conducted a comprehensive study of copy number variants (CNVs) well-tagged by SNPs (r(2)≥ 0.8) by analyzing their effect on gene expression and their association with disease susceptibility and other complex human traits. We tested whether these CNVs were more likely to be functional than frequency-matched SNPs as trait-associated loci or as expression quantitative trait loci (eQTLs) influencing phenotype by altering gene regulation. Our study found that CNV-tagging SNPs are significantly enriched for cis eQTLs; furthermore, we observed that trait associations from the NHGRI catalog show an overrepresentation of SNPs tagging CNVs relative to frequency-matched SNPs. We found that these SNPs tagging CNVs are more likely to affect multiple expression traits than frequency-matched variants. Given these findings on the functional relevance of CNVs, we created an online resource of expression-associated CNVs (eCNVs) using the most comprehensive population-based map of CNVs to inform future studies of complex traits. Although previous studies of common CNVs that can be typed on existing platforms and/or interrogated by SNPs in genome-wide association studies concluded that such CNVs appear unlikely to have a major role in the genetic basis of several complex diseases examined, our findings indicate that it would be premature to dismiss the possibility that even common CNVs may contribute to complex phenotypes and at least some common diseases.     

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.     

Expression discordance of monozygotic twins at birth: Effect of intrauterine environment and a possible mechanism for fetal programming

Within-pair comparison of monozygotic (MZ) twins provides an ideal model for studying factors that regulate epigenetic profile, by controlling for genetic variation. Previous reports have demonstrated epigenetic variability within MZ pairs, but the contribution of early life exposures to this variation remains unclear. As epigenetic marks govern gene expression, we have used gene expression discordance as a proxy measure of epigenetic discordance in MZ twins at birth in two cell types. We found strong evidence of expression discordance at birth in both cell types and some evidence for higher discordance in twin pairs with separate placentas. Genes previously defined as being involved in response to the external environment showed the most variable expression within pairs, independent of cell type, supporting the idea that even slight differences in intrauterine environment can influence expression profile. Focusing on birthweight, previously identified as a predisposing factor for cardiovascular, metabolic and other complex diseases, and using a statistical model that estimated association based on within-pair variation of expression and birthweight, we found some association between birthweight and expression of genes involved in metabolism and cardiovascular function. This study is the first to examine expression discordance in newborn twins. It provides evidence of a link between birthweight and activity of specific cellular pathways and, as evidence points to gene expression profiles being maintained through cell division by epigenetic factors, provides a plausible biological mechanism for the previously described link between low birthweight and increased risk of later complex disease.     

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.