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.     

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.     

Mapping rare and common causal alleles for complex human diseases

Advances in genotyping and sequencing technologies have revolutionized the genetics of complex disease by locating rare and common variants that influence an individual's risk for diseases, such as diabetes, cancers, and psychiatric disorders. However, to capitalize on these data for prevention and therapies requires the identification of causal alleles and a mechanistic understanding for how these variants contribute to the disease. After discussing the strategies currently used to map variants for complex diseases, this Primer explores how variants may be prioritized for follow-up functional studies and the challenges and approaches for assessing the contributions of rare and common variants to disease phenotypes.     

Five years of GWAS discovery

The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section.     

A generic research paradigm for identification and validation of early molecular diagnostics and new therapeutics in common disorders

Genetically complex disorders continue to confound investigators because of their many underlying factors, both genetic and environmental. In order to tease apart the heritable from the non-heritable contributions to disease, clinicians are relying on researchers in the rapidly expanding fields of high-throughput genomics to identify surrogate clinical endpoints, called biomarkers, that provide a measure of the probability that an individual will succumb to the disease in question. The goals of current biomedical research into complex disorders are to identify and utilize these biomarkers, not only for early detection, but also for personalized treatment with knowledge-guided therapeutics. As the identification of these biomarkers is basically a problem of discovery, we discuss new insights into biomarker detection utilizing the most current genomic technologies available. Additionally, we present here a generic paradigm for the validation of such molecular diagnostics as well as new treatment modalities for complex and increasingly common diseases. Lastly, we delve into the ways genomic biomarkers might be implemented in a clinical setting to allow the subsequent application of targeted therapeutics, which can help the ever expanding groups of individuals experiencing these insidious diseases.     

Chinese National Twin Registry as a resource for genetic epidemiologic studies of common and complex diseases in China.

Twins, due to their unique genetic and environmental relationships, have provided crucial insight in our understanding of genetic contributions to numerous etiologically complex disorders in developed countries. As the leading cause of death and adult disability, cardio- and cerebrovascular diseases are common in China, followed by cancer. Obesity and psychological disorders are increasing. The overall goal of this program is to develop a resource for genetic epidemiologic studies of these and other common and complex diseases in China. Our initial focus is to delineate the genetic and environmental determinants of vascular diseases in general, coronary artery disease (CAD) and stroke in particular. To date, we have over 4500 twin pairs registered and about 700 twin pairs studied for various metabolic traits (e.g., lipids, glucose, insulin, etc.). The long-term plan of this program is to (1) establish a population-based twin registry from several selected regions in China for future studies of specific common complex diseases; (2) conduct detailed phenotyping for clinical and intermediate traits related to cardiovascular diseases; (3) expand studies of twins to twin families by including their parents, siblings, and offspring for genetic linkage and association studies; and (4) follow up twins in the registry longitudinally. The goals of the program are health education and promotion of healthy behavior, early identification of cases to provide timely medical attention, and the evaluation of long-term effects of identified risk factors. We want to develop collaborations with investigators who have expertise in cancer, psychological disorders, and other disease areas.     

Polygenic modeling of genome-wide association studies: an application to prostate and breast cancer

Genome-wide association studies (GWAS) have successfully detected and replicated associations with numerous diseases, including cancers of the prostate and breast. These findings are helping clarify the genomic basis of such diseases, but appear to explain little of disease heritability. This limitation might reflect the focus of conventional GWAS on a small set of the most statistically significant associations with disease. More information might be obtained by analyzing GWAS using a polygenic model, which allows for the possibility that thousands of genetic variants could impact disease. Furthermore, there may exist common polygenic effects between potentially related phenotypes (e.g., prostate and breast cancer). Here we present and apply a polygenic model to GWAS of prostate and breast cancer. Our results indicate that the polygenic model can explain an increasing--albeit low--amount of heritability for both of these cancers, even when excluding the most statistically significant associations. In addition, nonaggressive prostate cancer and breast cancer appear to share a common polygenic model, potentially reflecting a similar underlying biology. This supports the further development and application of polygenic models to genomic data.     

Network-Based Interpretation of Genomic Variation Data

Advances in sequencing technologies are allowing genome-wide association studies at an ever-growing scale. The interpretation of these studies requires dealing with statistical and combinatorial challenges, owing to the multi-factorial nature of human diseases and the huge space of genomic markers that are being monitored. Recently, it was proposed that using protein–protein interaction network information could help in tackling these challenges by restricting attention to markers or combinations of markers that map to close proteins in the network. In this review, we survey techniques for integrating genomic variation data with network information to improve our understanding of complex diseases and reveal meaningful associations.     

Detection of disease-associated deletions in case–control studies using SNP genotypes with application to rheumatoid arthritis

Genomic deletions have long been known to play a causative role in microdeletion syndromes. Recent whole-genome genetic studies have shown that deletions can increase the risk for several psychiatric disorders, suggesting that genomic deletions play an important role in the genetic basis of complex traits. However, the association between genomic deletions and common, complex diseases has not yet been systematically investigated in gene mapping studies. Likelihood-based statistical methods for identifying disease-associated deletions have recently been developed for familial studies of parent-offspring trios. The purpose of this study is to develop statistical approaches for detecting genomic deletions associated with complex disease in case–control studies. Our methods are designed to be used with dense single nucleotide polymorphism (SNP) genotypes to detect deletions in large-scale or whole-genome genetic studies. As more and more SNP genotype data for genome-wide association studies become available, development of sophisticated statistical approaches will be needed that use these data. Our proposed statistical methods are designed to be used in SNP-by-SNP analyses and in cluster analyses based on combined evidence from multiple SNPs. We found that these methods are useful for detecting disease-associated deletions and are robust in the presence of linkage disequilibrium using simulated SNP data sets. Furthermore, we applied the proposed statistical methods to SNP genotype data of chromosome 6p for 868 rheumatoid arthritis patients and 1,197 controls from the North American Rheumatoid Arthritis Consortium. We detected disease-associated deletions within the region of human leukocyte antigen in which genomic deletions were previously discovered in rheumatoid arthritis patients.     

The relationship between oxidative/nitrative stress and pathological inclusions in Alzheimer's and Parkinson's diseases

Alzheimer's (AD) and Parkinson's diseases (PD) are late-onset neurodegenerative diseases that have tremendous impact on the lives of affected individuals, their families, and society as a whole. Remarkable efforts are being made to elucidate the dominant factors that result in the pathogenesis of these disorders. Extensive postmortem studies suggest that oxidative/nitrative stresses are prominent features of these diseases, and several animal models support this notion. Furthermore, it is likely that protein modifications resulting from oxidative/nitrative damage contribute to the formation of intracytoplasmic inclusions characteristic of each disease. The frequent presentation of both AD and PD in individuals and the co-occurrence of inclusions characteristic of AD and PD in several other neurodegenerative diseases suggests the involvement of a common underlying aberrant process. It can be surmised that oxidative/nitrative stress, which is cooperatively influenced by environmental factors, genetic predisposition, and senescence, may be a link between these disorders.     

Involvement of Mitochondria in Neurodegeneration in Multiple Sclerosis

Functional disruption and neuronal loss followed by progressive dysfunction of the nervous system underlies the pathogenesis of numerous disorders defined as “neurodegenerative diseases”. Multiple sclerosis, a chronic inflammatory demyelinating disease of the central nervous system resulting in serious neurological dysfunctions and disability, is one of the most common neurodegenerative diseases. Recent studies suggest that disturbances in mitochondrial functioning are key factors leading to neurodegeneration. In this review, we consider data on mitochondrial dysfunctions in multiple sclerosis, which were obtained both with patients and with animal models. The contemporary data indicate that the axonal degeneration in multiple sclerosis largely results from the activation of Ca²⁺-dependent proteases and from misbalance of ion homeostasis caused by energy deficiency. The genetic studies analyzing association of mitochondrial DNA polymorphic variants in multiple sclerosis suggest the participation of mitochondrial genome variability in the development of this disease, although questions of the involvement of individual genomic variants are far from being resolved.     

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.     

A systematic approach to understand the functional consequences of non-protein coding risk regions

A primary goal of genetic association studies is to elucidate genes and novel biological mechanisms involved in disease. Recently, genome-wide association studies have identified many common genetic variants that are significantly associated with complex diseases such as cancer. In contrast to mutation-causing Mendelian disorders, a sizable fraction of the variants lies outside known protein-coding regions; therefore, understanding their biological consequences presents a major challenge in human genetics. Here we describe an integrated framework to allow non-protein coding loci to be annotated with respect to regulatory functions. This will facilitate identification of target genes as well as prioritize variants for functional testing.     

Genetic susceptibility to ageing-associated diseases

The constant and rapid increase of life expectancy in western countries is associated with a major ageing of our populations. In these conditions, we can expect an epidemic progression of most chronic diseases, especially cardiovascular, neurodegenerative and metabolic disorders, the main causes of death in the world. The global burden of these diseases will have a dramatic impact on the health and on the socio-economical context of our societies. From a global point of view, the occurrence and progression of these multifactorial diseases rely upon the nature and intensity of the environmental determinants we are exposed to all life long, but also to our individual genetic susceptibility. Through the determination of this higher susceptibility to an environmental risk factor and the understanding of its mechanisms of action, prevention and management efforts will be better focused. In such multifactorial affections, the development and the transmission of the disease do not follow the simple laws of monogenic Mendelian models. The complexity of this transmission is associated with the influence, at various degrees, of several genes and of a close interaction between this particular genetic susceptibility and environmental risk factors. With the recent development of automated and high throughput molecular biology techniques and their use in epidemiological studies, gene expression regulation and post genomic studies, the determination of sub-groups facing a higher individual genetic susceptibility has begun. This determination will offer new clues for a better-targeted disease management.