Use of population isolates for mapping complex traits

Geneticists have repeatedly turned to population isolates for mapping and cloning Mendelian disease genes. Population isolates possess many advantages in this regard. Foremost among these is the tendency for affected individuals to share ancestral haplotypes derived from a handful of founders. These haplotype signatures have guided scientists in the fine mapping of scores of rare disease genes. The past successes with Mendelian disorders using population isolates have prompted unprecedented interest among medical researchers in both the public and private sectors. Despite the obvious genetic and environmental complications, geneticists have targeted several population isolates for mapping genes for complex diseases.     

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.     

Introductory Lecture: Genetic Approaches to CNS Disorders with Particular

Abstract

The tools of molecular biology will bring the field of human genetics into a new era by permitting the analysis of the genetic contribution to disease. Most single gene disorders, inherited in a Mendelian fashion, will be molecularly diagnosed. In addition, the genetic susceptibility of common, complex diseases such a schizophrenia can be clarified, even though the conditions are not inherited as Mendelian characteristics. The mapping of the human genome will increase the rate at which new disease genes are identified and isolated. Finally, the development of genetically engineered animal models will help to dissect the steps involved in physiological and pathophysiological processes and thereby enhance our understanding of complex biological systems.     

Genetic approaches to identify disease genes for birth defects with cleft lip/palate as a model

BACKGROUND: Understanding the etiology of birth defects is an important step toward developing improved treatment and preventive strategies. Most birth defects have an underlying genetic basis, ranging from single genes playing dominant or recessive roles in Mendelian disorders to a mixture of contributions from multiple genes and environmental triggers in complex traits. The purpose of this article is to provide an overview of genetic approaches to identifying disease genes for genetically complex birth defects. METHODS: A review of the literature describing successes and limitations for identifying disease genes for complex traits was conducted. RESULTS: Cleft lip and cleft palate are common congenital anomalies with significant medical, psychological, social, and economic ramifications. The Online Mendelian Inheritance in Man catalog (OMIM; http://www3.ncbi.nlm.nih.gov/Omim) lists more than 400 single-gene causes of clefts of the lip and/or palate. Genetic causes of clefting also include chromosomal rearrangements, genetic susceptibility to teratogenic exposures, and complex genetic contributions of multiple genes. CONCLUSIONS: Genetic causes of birth defects can be identified using an increasingly powerful combination of careful sample collection, molecular analytic methods, and statistical evaluations. We will describe a range of approaches to search for genetic factors of birth defects and use our own work with cleft lip and palate as a model.     

Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes

Most common genetic disorders have a complex inheritance and may result from variants in many genes, each contributing only weak effects to the disease. Pinpointing these disease genes within the myriad of susceptibility loci identified in linkage studies is difficult because these loci may contain hundreds of genes. However, in any disorder, most of the disease genes will be involved in only a few different molecular pathways. If we know something about the relationships between the genes, we can assess whether some genes (which may reside in different loci) functionally interact with each other, indicating a joint basis for the disease etiology. There are various repositories of information on pathway relationships. To consolidate this information, we developed a functional human gene network that integrates information on genes and the functional relationships between genes, based on data from the Kyoto Encyclopedia of Genes and Genomes, the Biomolecular Interaction Network Database, Reactome, the Human Protein Reference Database, the Gene Ontology database, predicted protein-protein interactions, human yeast two-hybrid interactions, and microarray co-expressions. We applied this network to interrelate positional candidate genes from different disease loci and then tested 96 heritable disorders for which the Online Mendelian Inheritance in Man database reported at least three disease genes. Artificial susceptibility loci, each containing 100 genes, were constructed around each disease gene, and we used the network to rank these genes on the basis of their functional interactions. By following up the top five genes per artificial locus, we were able to detect at least one known disease gene in 54% of the loci studied, representing a 2.8-fold increase over random selection. This suggests that our method can significantly reduce the cost and effort of pinpointing true disease genes in analyses of disorders for which numerous loci have been reported but for which most of the genes are unknown.     

Genetics of complex disorders

The success stories of identifying genes in Mendelian disorders have stimulated research that aims at identifying the genetic determinants in complex disorders, in which both genetics, environment and chance affect the pathogenetic processes. This review summarizes the brief history and lessons learned from genetic analysis of complex disorders and outlines some landscapes ahead for medical research.     

Revisiting Mendelian disorders through exome sequencing

Over the past several years, more focus has been placed on dissecting the genetic basis of complex diseases and traits through genome-wide association studies. In contrast, Mendelian disorders have received little attention mainly due to the lack of newer and more powerful methods to study these disorders. Linkage studies have previously been the main tool to elucidate the genetics of Mendelian disorders; however, extremely rare disorders or sporadic cases caused by de novo variants are not amendable to this study design. Exome sequencing has now become technically feasible and more cost-effective due to the recent advances in high-throughput sequence capture methods and next-generation sequencing technologies which have offered new opportunities for Mendelian disorder research. Exome sequencing has been swiftly applied to the discovery of new causal variants and candidate genes for a number of Mendelian disorders such as Kabuki syndrome, Miller syndrome and Fowler syndrome. In addition, de novo variants were also identified for sporadic cases, which would have not been possible without exome sequencing. Although exome sequencing has been proven to be a promising approach to study Mendelian disorders, several shortcomings of this method must be noted, such as the inability to capture regulatory or evolutionary conserved sequences in non-coding regions and the incomplete capturing of all exons.     

Exome sequencing of ion channel genes reveals complex profiles confounding personal risk assessment in epilepsy

Ion channel mutations are an important cause of rare Mendelian disorders affecting brain, heart, and other tissues. We performed parallel exome sequencing of 237 channel genes in a well-characterized human sample, comparing variant profiles of unaffected individuals to those with the most common neuronal excitability disorder, sporadic idiopathic epilepsy. Rare missense variation in known Mendelian disease genes is prevalent in both groups at similar complexity, revealing that even deleterious ion channel mutations confer uncertain risk to an individual depending on the other variants with which they are combined. Our findings indicate that variant discovery via large scale sequencing efforts is only a first step in illuminating the complex allelic architecture underlying personal disease risk. We propose that in?silico modeling of channel variation in realistic cell and network models will be crucial to future strategies assessing mutation profile pathogenicity and drug response in individuals with a broad spectrum of excitability disorders.     

Genetics of Obesity: What have we Learned?

Candidate gene and genome-wide association studies have led to the discovery of nine loci involved in Mendelian forms of obesity and 58 loci contributing to polygenic obesity. These loci explain a small fraction of the heritability for obesity and many genes remain to be discovered. However, efforts in obesity gene identification greatly modified our understanding of this disorder. In this review, we propose an overlook of major lessons learned from 15 years of research in the field of genetics and obesity. We comment on the existence of the genetic continuum between monogenic and polygenic forms of obesity that pinpoints the role of genes involved in the central regulation of food intake and genetic predisposition to obesity. We explain how the identification of novel obesity predisposing genes has clarified unsuspected biological pathways involved in the control of energy balance that have helped to understand past human history and to explore causality in epidemiology. We provide evidence that obesity predisposing genes interact with the environment and influence the response to treatment relevant to disease prediction.     

Whole-Genome Sequencing of a Single Proband Together with Linkage Analysis Identifies a Mendelian Disease Gene

Although more than 2,400 genes have been shown to contain variants that cause Mendelian disease, there are still several thousand such diseases yet to be molecularly defined. The ability of new whole-genome sequencing technologies to rapidly indentify most of the genetic variants in any given genome opens an exciting opportunity to identify these disease genes. Here we sequenced the whole genome of a single patient with the dominant Mendelian disease, metachondromatosis (OMIM 156250), and used partial linkage data from her small family to focus our search for the responsible variant. In the proband, we identified an 11 bp deletion in exon four of PTPN11, which alters frame, results in premature translation termination, and co-segregates with the phenotype. In a second metachondromatosis family, we confirmed our result by identifying a nonsense mutation in exon 4 of PTPN11 that also co-segregates with the phenotype. Sequencing PTPN11 exon 4 in 469 controls showed no such protein truncating variants, supporting the pathogenicity of these two mutations. This combination of a new technology and a classical genetic approach provides a powerful strategy to discover the genes responsible for unexplained Mendelian disorders.     

The multifactorial/threshold concept -- uses and misuses.

The common congenital malformations have familial distributions that cannot be accounted for by simple Mendelian models, but can be explained in terms of a continuous variable, "liability," with a threshold value beyond which individuals will be affected. Both genetic and environmental factors determine liability, making the system multifactorial. Cleft palate is a useful experimental model, illustrating a number of factors that contribute to palate closure, the nature of a developmental threshold, and how genes and teratogens can alter the components of liability to increase the probability of cleft palate. The nature of the genetic component to liability in human malformations in not clear, and various possibilities, ranging from polygenic in the strict sense to a major gene with reduced penetrance are compatible with the data -- but the important feature is the threshold. Much of the confusion over the concept results from inconsistent use of terminology. The term "multifactorial" should be used for "determined by a combination of genetic and environmental factors," without reference to the nature of the genetic factor(s). "Polygenic" should be reserved for "a large number of genes, each with a small effect, acting additively." When several genes, with more major effects are involved, "multilocal" can be used. When it is not clear which of these is applicable the term "plurilocal" is suggested, in the sense of "genetic variation more complex than a simple Mendelian difference." Since teratological data often represent threshold characters the concept also has important implications for the interpretation of data on dose-response curves, synergisms, and strain differences in response to teratogens.     

Human genetics of infectious diseases: a unified theory

Since the early 1950s, the dominant paradigm in the human genetics of infectious diseases postulates that rare monogenic immunodeficiencies confer vulnerability to multiple infectious diseases (one gene, multiple infections), whereas common infections are associated with the polygenic inheritance of multiple susceptibility genes (one infection, multiple genes). Recent studies, since 1996 in particular, have challenged this view. A newly recognised group of primary immunodeficiencies predisposing the individual to a principal or single type of infection is emerging. In parallel, several common infections have been shown to reflect the inheritance of one major susceptibility gene, at least in some populations. This novel causal relationship (one gene, one infection) blurs the distinction between patient-based Mendelian genetics and population-based complex genetics, and provides a unified conceptual frame for exploring the molecular genetic basis of infectious diseases in humans.     

The sequences of the human sex chromosomes

The sequences of both of the human sex chromosomes and of a substantial part of the chimpanzee Y chromosome have now been determined, and most of the protein-coding genes have been identified. The X chromosome codes for more than 800 proteins but the Y chromosome for only approximately 60, illustrating their very different evolutionary histories since their origin from an autosomal pair approximately 300 million years ago and explaining their differential importance in disease. These sequences have provided the basis for understanding normal patterns of variation, such as the distribution of SNPs, and patterns of linkage disequilibrium. In addition, they have been useful for identifying variants associated with simple Mendelian disorders such as microphthalmia or mental retardation, and more complex disorders such as osteoporosis.     

Amyotrophic lateral sclerosis as a complex genetic disease

In complex diseases like ALS, there are multiple genetic and environmental factors all contributing to disease liability. The genetic factors causing susceptibility to developing ALS can be considered a spectrum from single genes with large effect sizes causing classical Mendelian ALS, to genes of smaller effect, producing apparently sporadic disease. We examine the statistical genetic principles that underpin this model and review what is known about ALS as a disease with complex genetics.     

Design considerations for massively parallel sequencing studies of complex human disease

Massively Parallel Sequencing (MPS) allows sequencing of entire exomes and genomes to now be done at reasonable cost, and its utility for identifying genes responsible for rare Mendelian disorders has been demonstrated. However, for a complex disease, study designs need to accommodate substantial degrees of locus, allelic, and phenotypic heterogeneity, as well as complex relationships between genotype and phenotype. Such considerations include careful selection of samples for sequencing and a well-developed strategy for identifying the few "true" disease susceptibility genes from among the many irrelevant genes that will be found to harbor rare variants. To examine these issues we have performed simulation-based analyses in order to compare several strategies for MPS sequencing in complex disease. Factors examined include genetic architecture, sample size, number and relationship of individuals selected for sequencing, and a variety of filters based on variant type, multiple observations of genes and concordance of genetic variants within pedigrees. A two-stage design was assumed where genes from the MPS analysis of high-risk families are evaluated in a secondary screening phase of a larger set of probands with more modest family histories. Designs were evaluated using a cost function that assumes the cost of sequencing the whole exome is 400 times that of sequencing a single candidate gene. Results indicate that while requiring variants to be identified in multiple pedigrees and/or in multiple individuals in the same pedigree are effective strategies for reducing false positives, there is a danger of over-filtering so that most true susceptibility genes are missed. In most cases, sequencing more than two individuals per pedigree results in reduced power without any benefit in terms of reduced overall cost. Further, our results suggest that although no single strategy is optimal, simulations can provide important guidelines for study design.     

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.     

Lipoproteinstoffwechsel und koronare Herzkrankheit

A better understanding of complex diseases and their genetics has been gained by investigating genetic disorders of lipoprotein metabolism. This has resulted in the development of ddrugs to prevent atherosclerosis, the most frequent cause of death in industrialized countries. Thus, analysis of familial hypercholesterinemia (FH), the most frequent cause of which are mutations on the LDLR gene, has contributed to the development of HMG-CoA reductase inhibitors (statins). Meanwhile, in genome-wide association studies (GWAS), variants in over 90 genes have been found to influence the concentration of plasma lipids. However, these explain only a small fraction of the genetic variance of the traits. Taking the classical polymorphism of Apo-E as an example, it is discussed that one possible reason for the ??missing heritability?? may be the selection of the SNPs on the arrays used in the GWAS. Further, this polymorphism demonstrates how interactions may mask a connection between a genotype and a disease. Genetic studies based on the principle of ??Mendelian randomization?? have established the causal role of a high Lp(a) concentration as a risk factor for coronary heart disease (CHD). For patients with end-stage renal disease, however, a polymorphism (KIV-2 CNV) is a better predictor for CHD than Lp(a) concentration.