Identifying genetic risk factors for osteoporosis

Over the past decades epidemiological research of so-called "complex" diseases, i.e., common age-related disorders such as cancer, cardiovascular disease, diabetes, and osteoporosis, has identified anthropometric, behavioural, and serum parameters as risk factors. Recently, genetic polymorphisms have gained considerable interest, propelled by the Human Genome Project and its sequela that have identified most genes and uncovered a plethora of polymorphic variants, some of which embody the genetic risk factors. In all fields of complex disease genetics (including osteoporosis) progress in identifying these genetic factors has been hampered by often controversial results. Because of the small effect size for each individual risk polymorphism, this is mostly due to low statistical power and limitations of analytical methods. Genome-wide scanning approaches can be used to find the responsible genes. It is by now clear that linkage analysis is not suitable for this, but genome-wide association analysis has much better possibilities, as is illustrated by successful identification of risk alleles for several complex diseases. Candidate gene association analysis followed by replication and prospective multi-centred meta-analysis, is currently the best way forward to identify genetic markers for complex traits, such as osteoporosis. To accomplish this, we need large (global) collaborative studies using standardized methodology and definitions, to quantify by meta-analysis the subtle effects of the responsible gene variants.     

Genome Sequencing of Idiopathic Pulmonary Fibrosis in Conjunction with a Medical School Human Anatomy Course

Even in cases where there is no obvious family history of disease, genome sequencing may contribute to clinical diagnosis and management. Clinical application of the genome has not yet become routine, however, in part because physicians are still learning how best to utilize such information. As an educational research exercise performed in conjunction with our medical school human anatomy course, we explored the potential utility of determining the whole genome sequence of a patient who had died following a clinical diagnosis of idiopathic pulmonary fibrosis (IPF). Medical students performed dissection and whole genome sequencing of the cadaver. Gross and microscopic findings were more consistent with the fibrosing variant of nonspecific interstitial pneumonia (NSIP), as opposed to IPF per se. Variants in genes causing Mendelian disorders predisposing to IPF were not detected. However, whole genome sequencing identified several common variants associated with IPF, including a single nucleotide polymorphism (SNP), rs35705950, located in the promoter region of the gene encoding mucin glycoprotein MUC5B. The MUC5B promoter polymorphism was recently found to markedly elevate risk for IPF, though a particular association with NSIP has not been previously reported, nor has its contribution to disease risk previously been evaluated in the genome-wide context of all genetic variants. We did not identify additional predicted functional variants in a region of linkage disequilibrium (LD) adjacent to MUC5B, nor did we discover other likely risk-contributing variants elsewhere in the genome. Whole genome sequencing thus corroborates the association of rs35705950 with MUC5B dysregulation and interstitial lung disease. This novel exercise additionally served a unique mission in bridging clinical and basic science education.     

Genomics in Neurological Disorders

Neurological disorders comprise a variety of complex diseases in the central nervous system, which can be roughly classified as neurodegenerative diseases and psychiatric disorders. The basic and translational research of neurological disorders has been hindered by the difficulty in accessing the pathological center （i.e., the brain） in live patients. The rapid advancement of sequencing and array technologies has made it possible to investigate the disease mechanism and biomarkers from a systems perspective. In this review, recent progresses in the discovery of novel risk genes, treatment targets and peripheral biomarkers employing genomic technologies will be dis- cussed. Our major focus will be on two of the most heavily investigated neurological disorders, namely Alzheimer＇s disease and autism spectrum disorder.     

Use of next-generation DNA sequencing to analyze genetic variants in rheumatic disease

Next-generation DNA sequencing has revolutionized the field of genetics and genomics, providing researchers with the tools to efficiently identify novel rare and low frequency risk variants, which was not practical with previously available methodologies. These methods allow for the sequence capture of a specific locus or small genetic region all the way up to the entire six billion base pairs of the diploid human genome. Rheumatic diseases are a huge burden on the US population, affecting more than 46 million Americans. Those afflicted suffer from one or more of the more than 100 diseases characterized by inflammation and loss of function, mainly of the joints, tendons, ligaments, bones, and muscles. While genetics studies of many of these diseases (for example, systemic lupus erythematosus, rheumatoid arthritis, and inflammatory bowel disease) have had major successes in defining their genetic architecture, causal alleles and rare variants have still been elusive. This review describes the current high-throughput DNA sequencing methodologies commercially available and their application to rheumatic diseases in both case–control as well as family-based studies.     

Jaundice revisited: recent advances in the diagnosis and treatment of inherited cholestatic liver diseases

Background

Jaundice is a common symptom of inherited or acquired liver diseases or a manifestation of diseases involving red blood cell metabolism. Recent progress has elucidated the molecular mechanisms of bile metabolism, hepatocellular transport, bile ductular development, intestinal bile salt reabsorption, and the regulation of bile acids homeostasis.

Main body

The major genetic diseases causing jaundice involve disturbances of bile flow. The insufficiency of bile salts in the intestines leads to fat malabsorption and fat-soluble vitamin deficiencies. Accumulation of excessive bile acids and aberrant metabolites results in hepatocellular injury and biliary cirrhosis. Progressive familial intrahepatic cholestasis (PFIC) is the prototype of genetic liver diseases manifesting jaundice in early childhood, progressive liver fibrosis/cirrhosis, and failure to thrive. The first three types of PFICs identified (PFIC1, PFIC2, and PFIC3) represent defects in FIC1 (ATP8B1), BSEP (ABCB11), or MDR3 (ABCB4). In the last 5 years, new genetic disorders, such as TJP2, FXR, and MYO5B defects, have been demonstrated to cause a similar PFIC phenotype. Inborn errors of bile acid metabolism also cause progressive cholestatic liver injuries. Prompt differential diagnosis is important because oral primary bile acid replacement may effectively reverse liver failure and restore liver functions. DCDC2 is a newly identified genetic disorder causing neonatal sclerosing cholangitis. Other cholestatic genetic disorders may have extra-hepatic manifestations, such as developmental disorders causing ductal plate malformation (Alagille syndrome, polycystic liver/kidney diseases), mitochondrial hepatopathy, and endocrine or chromosomal disorders. The diagnosis of genetic liver diseases has evolved from direct sequencing of a single gene to panel-based next generation sequencing. Whole exome sequencing and whole genome sequencing have been actively investigated in research and clinical studies. Current treatment modalities include medical treatment (ursodeoxycholic acid, cholic acid or chenodeoxycholic acid), surgery (partial biliary diversion and liver transplantation), symptomatic treatment for pruritus, and nutritional therapy. New drug development based on gene-specific treatments, such as apical sodium-dependent bile acid transporter (ASBT) inhibitor, for BSEP defects are underway.

Short conclusion

Understanding the complex pathways of jaundice and cholestasis not only enhance insights into liver pathophysiology but also elucidate many causes of genetic liver diseases and promote the development of novel treatments.

     

Advances in the discovery of genetic risk factors for complex forms of neurodegenerative disorders: contemporary approaches,success, challenges and prospects

Neurodegenerative diseases constitute a large proportion of disorders in elderly, majority being sporadic in occurrence with \(\sim \)5–10% familial. A strong genetic component underlies the Mendelian forms but nongenetic factors together with genetic vulnerability contributes to the complex sporadic forms. Several gene discoveries in the familial forms have provided novel insights into the pathogenesis of neurodegeneration with implications for treatment. Conversely, findings from genetic dissection of the sporadic forms, despite large genomewide association studies and more recently whole exome and whole genome sequencing, have been limited. This review provides a concise account of the genetics that we know, the pathways that they implicate, the challenges that are faced and the prospects that are envisaged for the sporadic, complex forms of neurodegenerative diseases, taking four most common conditions, namely Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis and Huntington disease as examples. Poor replication across studies, inability to establish genotype–phenotype correlations and the overall failure to predict risk and/or prevent disease in this group poses a continuing challenge. Among others, clinical heterogeneity emerges as the most important impediment warranting newer approaches. Advanced computational and system biology tools to analyse the big data are being generated and the alternate strategy such as subgrouping of case–control cohorts based on deep phenotyping using the principles of Ayurveda to overcome current limitation of phenotype heterogeneity seem to hold promise. However, at this point, with advances in discovery genomics and functional analysis of putative determinants with translation potential for the complex forms being minimal, stem cell therapies are being attempted as potential interventions. In this context, the possibility to generate patient derived induced pluripotent stem cells, mutant/gene/genome correction through CRISPR/Cas9 technology and repopulating the specific brain regions with corrected neurons, which may fulfil the dream of personalized medicine have been mentioned briefly. Understanding disease pathways / biology using this technology, with implications for development of novel therapeutics are optimistic expectations in the near future.     

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.     

Genetic susceptibility in Parkinson's disease

It is hoped that an understanding of the genetic basis of Parkinson's disease (PD) will lead to an appreciation of the molecular pathogenesis of disease, which in turn will highlight potential points of therapeutic intervention. It is also hoped that such an understanding will allow identification of individuals at risk for disease prior to the onset of motor symptoms. A large amount of work has already been performed in the identification of genetic risk factors for PD and some of this work, particularly those efforts that focus on genes implicated in monogenic forms of PD, have been successful, although hard won. A new era of gene discovery has begun, with the application of genome wide association studies; these promise to facilitate the identification of common genetic risk loci for complex genetic diseases. This is the first of several high throughput technologies that promise to shed light on the (likely) myriad genetic factors involved in this complex, late-onset neurodegenerative disorder.     

单细胞转录组测序在药物成瘾研究中的应用

药物成瘾是复杂的中枢神经系统疾病，相关基础与临床研究均证实药物成瘾的神经机制及神经环路在成瘾行为形成的不同阶段逐渐发生改变。利用全基因组关联研究、全基因组测序、全外显子测序或高通量转录组测序等技术的组学研究对包括药物成瘾在内的精神疾病遗传的脆弱性进行了深入研究。上述单核苷酸多态性检测技术或测序技术主要预测疾病的遗传风险位点。然而，许多中枢神经系统疾病的发生与环境因素密切相关，而且在疾病发展的不同阶段，相关基因的表达存在脑区特异性的细胞异质性信息。因此，传统研究对发病机制的解释存在一定的局限性。单细胞转录组测序技术是针对单个细胞进行转录水平的测定，规避了传统测序对细胞群体平均转录水平检测的缺点，可以定量描述细胞异质性。近年来，单细胞转录测序技术在神经精神科学研究中的应用逐渐受到关注，本文总结了该技术在神经科学研究中的重要应用，并以药物成瘾为例，重点阐述说明其在中枢神经系统疾病中的应用价值。     

Matrix-assisted laser desorption/ionisation, time-of-flight mass spectrometry in genomics research

The beginning of this millennium has seen dramatic advances in genomic research. Milestones such as the complete sequencing of the human genome and of many other species were achieved and complemented by the systematic discovery of variation at the single nucleotide (SNP) and whole segment (copy number polymorphism) level. Currently most genomics research efforts are concentrated on the production of whole genome functional annotations, as well as on mapping the epigenome by identifying the methylation status of CpGs, mainly in CpG islands, in different tissues. These recent advances have a major impact on the way genetic research is conducted and have accelerated the discovery of genetic factors contributing to disease. Technology was the critical driving force behind genomics projects: both the combination of Sanger sequencing with high-throughput capillary electrophoresis and the rapid advances in microarray technologies were keys to success. MALDI-TOF MS-based genome analysis represents a relative newcomer in this field. Can it establish itself as a long-term contributor to genetics research, or is it only suitable for niche areas and for laboratories with a passion for mass spectrometry? In this review, we will highlight the potential of MALDI-TOF MS-based tools for resequencing and for epigenetics research applications, as well as for classical complex genetic studies, allele quantification, and quantitative gene expression analysis. We will also identify the current limitations of this approach and attempt to place it in the context of other genome analysis technologies.     

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)     

An international effort towards developing standards for best practices in analysis,interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

Background

There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance.

Results

A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization.

Conclusions

The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.     

Network- and attribute-based classifiers can prioritize genes and pathways for autism spectrum disorders and intellectual disability

Autism spectrum disorders (ASD) are a group of related neurodevelopmental disorders with significant combined prevalence (～1%) and high heritability. Dozens of individually rare genes and loci associated with high-risk for ASD have been identified, which overlap extensively with genes for intellectual disability (ID). However, studies indicate that there may be hundreds of genes that remain to be identified. The advent of inexpensive massively parallel nucleotide sequencing can reveal the genetic underpinnings of heritable complex diseases, including ASD and ID. However, whole exome sequencing (WES) and whole genome sequencing (WGS) provides an embarrassment of riches, where many candidate variants emerge. It has been argued that genetic variation for ASD and ID will cluster in genes involved in distinct pathways and protein complexes. For this reason, computational methods that prioritize candidate genes based on additional functional information such as protein-protein interactions or association with specific canonical or empirical pathways, or other attributes, can be useful. In this study we applied several supervised learning approaches to prioritize ASD or ID disease gene candidates based on curated lists of known ASD and ID disease genes. We implemented two network-based classifiers and one attribute-based classifier to show that we can rank and classify known, and predict new, genes for these neurodevelopmental disorders. We also show that ID and ASD share common pathways that perturb an overlapping synaptic regulatory subnetwork. We also show that features relating to neuronal phenotypes in mouse knockouts can help in classifying neurodevelopmental genes. Our methods can be applied broadly to other diseases helping in prioritizing newly identified genetic variation that emerge from disease gene discovery based on WES and WGS.     

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.     

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。     

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.     

GWASs and the age of human as the model organism for autoimmune genetic research

Genetic studies have identified more than 150 autoimmune loci, and next-generation sequencing will identify more. Is it time to make human the model organism for autoimmune research?Human genetics - linking inherited variation in DNA sequence with traits such as susceptibility to disease - provides prima facie evidence that a gene and a pathway are associated with a disease. The most recent wave of genomic technology has allowed human genomes to be scanned for variant DNA sequences (or alleles) in many people to determine which alleles are associated with a particular disease or phenotype of interest. Termed genome-wide association studies, or GWASs, this approach has identified hundreds of alleles that are associated with a variety of human traits [1,2]. By most accounts, the GWAS approach has been very successful at identifying new regions of the genome (or loci) that are important in disease, even though the effect sizes of most alleles are modest.The GWAS approach has been particularly successful at uncovering risk alleles for autoimmune diseases. Collectively, autoimmune diseases are common, affecting more than 5% of the adult population [3]. These diseases include rheumatoid arthritis (RA), type 1 diabetes (T1D), inflammatory bowel disease (IBD), systemic lupus erythematosus (SLE), multiple sclerosis (MS), psoriasis and celiac disease (among others). RA is a chronic inflammatory disease that destroys free moving joints. T1D is a form of diabetes that results from the destruction of insulin-producing beta cells of the pancreas. IBD is a group of inflammatory conditions of the colon and small intestine; the two major types are Crohn''s disease and ulcerative colitis. In SLE, the immune system attacks a wide variety of organs, including the heart, joints, skin, lungs, blood vessels, liver, kidneys and nervous system. MS is an autoimmune disease in which the fatty myelin sheaths around the axons of the brain and spinal cord are damaged, leading to a broad spectrum of signs and symptoms. Psoriasis is a chronic disease in which the skin develops red, scaly patches, which is the result of areas of inflammation and excessive skin production. Celiac disease is an autoimmune disorder of the small intestine caused by a reaction to storage proteins (called glutens) found in cereal grains; the ensuing excessive immune reaction leads to an attack on the intestinal villi and tissue damage, resulting in malabsorption of nutrients.So far, approximately 150 loci have been identified that increase risk of these autoimmune diseases [4-14]. For each disease, the strongest genetic risk factors reside within the major histocompatibility complex (MHC) region on chromosome 6 [15]. Most associated alleles in other regions are common in the general population, but increase the disease risk by only 10 to 20% (corresponding to an odds ratio (OR) of 1.10 to 1.20 per copy of the risk allele). (The OR is a measure of the strength of association; it refers to the ratio of the odds of an event occurring in one group (such as cases) to the odds of it occurring in another group (such as controls).) For any given autoimmune disease, the known genetic risk alleles explain between 10 and 20% of variance in disease risk, whereas more than 50% of disease risk is estimated to be heritable. The remaining 30% or so of unexplained genetic disease risk is termed the missing heritability.The challenges now are, first, to find the causal mutation responsible for the signal of association; second, to understand which gene is disrupted by the causal mutation and how it is disrupted (that is, whether the mutation results in gain of function, loss of function, or a new function altogether); third, to understand which cell type and biological pathways are altered by these mutations; and finally to find additional mutations that explain the missing heritability [16]. The next wave of genomic technology - next-generation sequencing - will be a powerful ally in this effort. In particular, next-generation sequencing will help localize the causal mutation, as well as help identify rare alleles that confer risk of autoimmune disease.Thus, an important question remains: what is the most appropriate scientific approach to understand function of risk alleles discovered in human genetics research? Is the mouse the most appropriate model organism, or do these genetic discoveries provide new resources to enable functional studies directly in human immune cells?Here, I discuss the confluence of events that create a unique opportunity to use human subjects as the ''model organism'' for the study of autoimmune disease pathogenesis. In addition to GWASs and next-generation sequencing, registries of blood draws from healthy, consenting human volunteers enable functional studies of genetic variants in a wide range of primary human immune cells, and human stem cell technology has advanced to the point at which induced pluripotent stem (iPS) cells can be derived from patients with specific mutations and differentiated into diverse immune lineages. These resources should allow investigators to understand the altered cellular state in diseases that are uniquely human, which should ultimately lead to new therapeutics to treat or prevent the devastating consequences of autoimmune disease.     

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.     

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.