Most Rare Missense Alleles Are Deleterious in Humans: Implications for Complex Disease and Association Studies (original) (raw)
Related papers
Evolutionary evidence of the effect of rare variants on disease etiology
Clinical Genetics, 2011
The common disease/common variant hypothesis has been popular for describing the genetic architecture of common human diseases for several years. According to the originally stated hypothesis, one or a few common genetic variants with a relatively large effect size control the risk of common diseases. A growing body of evidence, however, suggests that rare singlenucleotide polymorphisms (SNPs), i.e., those with a minor allele frequency of less than 5%, are also an important component of the genetic architecture of common human diseases. In this study, we analyzed the relevance of rare SNPs to the risk of common disease from an evolutionary perspective and found that rare SNPs are more likely than common SNPs to be functional and tend to have a stronger effect size than do common SNPs. This observation, plus the fact that most of the SNPs in the human genome are rare, suggests that rare SNPs are a crucial element of the genetic architecture of common human diseases. We propose that the next generation of genomic studies should focus on analyzing rare SNPs. Further, targeting patients with a family history of the disease, an extreme phenotype, or early disease onset may facilitate the detection of riskassociated rare SNPs.
Assessing the Evolutionary Impact of Amino Acid Mutations in the Human Genome
PLoS Genetics, 2008
Quantifying the distribution of fitness effects among newly arising mutations in the human genome is key to resolving important debates in medical and evolutionary genetics. Here, we present a method for inferring this distribution using Single Nucleotide Polymorphism (SNP) data from a population with non-stationary demographic history (such as that of modern humans). Application of our method to 47,576 coding SNPs found by direct resequencing of 11,404 protein codinggenes in 35 individuals (20 European Americans and 15 African Americans) allows us to assess the relative contribution of demographic and selective effects to patterning amino acid variation in the human genome. We find evidence of an ancient population expansion in the sample with African ancestry and a relatively recent bottleneck in the sample with European ancestry. After accounting for these demographic effects, we find strong evidence for great variability in the selective effects of new amino acid replacing mutations. In both populations, the patterns of variation are consistent with a leptokurtic distribution of selection coefficients (e.g., gamma or log-normal) peaked near neutrality. Specifically, we predict 27-29% of amino acid changing (nonsynonymous) mutations are neutral or nearly neutral (|s|,0.01%), 30-42% are moderately deleterious (0.01%,|s|,1%), and nearly all the remainder are highly deleterious or lethal (|s|.1%). Our results are consistent with 10-20% of amino acid differences between humans and chimpanzees having been fixed by positive selection with the remainder of differences being neutral or nearly neutral. Our analysis also predicts that many of the alleles identified via whole-genome association mapping may be selectively neutral or (formerly) positively selected, implying that deleterious genetic variation affecting disease phenotype may be missed by this widely used approach for mapping genes underlying complex traits.
Human genomic disease variants: A neutral evolutionary explanation
2012
Abstract Many perspectives on the role of evolution in human health include nonempirical assumptions concerning the adaptive evolutionary origins of human diseases. Evolutionary analyses of the increasing wealth of clinical and population genomic data have begun to challenge these presumptions. In order to systematically evaluate such claims, the time has come to build a common framework for an empirical and intellectual unification of evolution and modern medicine.
Evidence for Hitchhiking of Deleterious Mutations within the Human Genome
Deleterious mutations present a significant obstacle to adaptive evolution. Deleterious mutations can inhibit the spread of linked adaptive mutations through a population; conversely, adaptive substitutions can increase the frequency of linked deleterious mutations and even result in their fixation. To assess the impact of adaptive mutations on linked deleterious mutations, we examined the distribution of deleterious and neutral amino acid polymorphism in the human genome. Within genomic regions that show evidence of recent hitchhiking, we find fewer neutral but a similar number of deleterious SNPs compared to other genomic regions. The higher ratio of deleterious to neutral SNPs is consistent with simulated hitchhiking events and implies that positive selection eliminates some deleterious alleles and increases the frequency of others. The distribution of disease-associated alleles is also altered in hitchhiking regions. Disease alleles within hitchhiking regions have been associated with auto-immune disorders, metabolic diseases, cancers, and mental disorders. Our results suggest that positive selection has had a significant impact on deleterious polymorphism and may be partly responsible for the high frequency of certain human disease alleles.
Genetics of complex diseases: An evolutionary perspective
Topics in current genetics
The advent of the human genome project and the subsequent technological advances in genomic research have provided an unprecedented opportunity, not only to dissect the genetic basis of complex diseases, but has also provided researchers with the means to study the impact of evolution on the genomic architecture of the human genome. In this context, evolution can be defined as a gradual change of genetic information across generations, resulting in an adaptation to the current environmental conditions. From an evolutionary perspective, disease associated mutations should be removed from the population over time. However, recent advances in genomics have shown that various diseases causing mutations have been fixed within the population or are the result of recent adaptations to an ever changing environment. In this review, we provide an overview of the different layers of evolutionary changes affecting the manifestation of disease variants within and between populations. We highligh...
Journal of Medical Genetics, 2005
Background: The haplotype based association method offers a powerful approach to complex disease gene mapping. In this method, a few common haplotypes that account for the vast majority of chromosomes in the populations are usually examined for association with disease phenotypes. This brings us to a critical question of whether rare haplotypes play an important role in influencing disease susceptibility and thus should not be ignored in the design and execution of association studies. Methods: To address this question we surveyed, in a large sample of 1873 white subjects, six candidate genes for osteoporosis (a common late onset bone disorder), which had 29 SNPs, an average marker density of 13 kb, and covered a total of 377 kb of the DNA sequence. Results: Our empirical data demonstrated that two rare haplotypes of the parathyroid hormone (PTH)/PTH related peptide receptor type 1 and vitamin D receptor genes (PTHR1 and VDR) with frequencies of 1.1% and 2.9%, respectively, had significant effects on osteoporosis phenotypes (p = 4.2 6 10 26 and p = 1.6 6 10 24 , respectively). Large phenotypic differences (4.0,5.0%) were observed between carriers of these rare haplotypes and non-carriers. Carriers of the two rare haplotypes showed quantitatively continuous variation in the population and were derived from a wide spectrum rather than from one extreme tail of the population phenotype distribution. Conclusions: These findings indicate that rare haplotypes/variants are important for disease susceptibility and cannot be ignored in genetics studies of complex diseases. The study has profound implications for association studies and applications of the HapMap project.
2013
Background. Natural selection operates on genetically influenced phenotypic variations that confer differential survival or reproductive advantages. Common diseases are frequently associated with increased mortality and disability and complex heritable factors play an important role in their pathogenesis. Hence, common diseases should trigger the process of natural selection with subsequent population genetic response. However, empirical impact of natural selection on genetics of complex diseases is poorly understood. In this paper, I hypothesize that negative selection of diseased individuals leads to systemic genetic differences between common diseases that primarily occur before or during the reproductive years (early onset) and those that occur after the reproductive years (late onset). Methods. To test this hypothesis, a comprehensive literature survey of highly penetrant (80% or more) nonpleiotropic, nonsyndromic susceptibility genes (hereafter defined as Mendelian phenocopies...
Genome biology and evolution, 2014
To date, numerous studies have been attempted to determine the extent of variation in evolutionary rates between human disease and nondisease (ND) genes. In our present study, we have considered human autosomal monogenic (Mendelian) disease genes, which were classified into two groups according to the number of phenotypic defects, that is, specific disease (SPD) gene (one gene: one defect) and shared disease (SHD) gene (one gene: multiple defects). Here, we have compared the evolutionary rates of these two groups of genes, that is, SPD genes and SHD genes with respect to ND genes. We observed that the average evolutionary rates are slow in SHD group, intermediate in SPD group, and fast in ND group. Group-to-group evolutionary rate differences remain statistically significant regardless of their gene expression levels and number of defects. We demonstrated that disease genes are under strong selective constraint if they emerge through edgetic perturbation or drug-induced perturbation...
Evolutionary Applications, 2009
There is an increasing interest in detecting genes, or genomic regions, that have been targeted by natural selection. Indeed, the evolutionary approach for inferring the action of natural selection in the human genome represents a powerful tool for predicting regions of the genome potentially associated with disease and of interest in epidemiological genetic studies. Here, we review several examples going from candidate gene studies associated with specific phenotypes, including nutrition, infectious disease and climate adaptation, to whole genome scans for natural selection. All these studies illustrate the power of the evolutionary approach in identifying regions of the genome having played a major role in human survival and adaptation.
Quantifying the Intragenic Distribution of Human Disease Mutations
Annals of Human Genetics, 2003
A wide variety of functional domains exist within human genes. Since different domains vary in their roles regarding overall gene function, the ability for a mutation in a gene region to produce disease varies among domains. We tested two hypotheses regarding distributions of mutations among functional domains by using (1) sets of single nucleotide disease mutations for six genes (CFTR, TSC2, G6PD, PAX6, RS1, and PAH) and (2) sets of polymorphic replacement and silent mutations found in two genes (CFTR and TSC2). First, we tested the null hypothesis that sets of mutations are uniformly distributed among functional domains within genes. Second, we tested the null hypothesis that disease mutations are distributed among gene regions according to expectations derived from the distribution of evolutionary conserved and variable amino acid sites throughout each gene. In contrast to the mainly uniform distribution of sets of silent and polymorphic mutations, sets of disease mutations generally rejected the null hypotheses of both uniform and evolutionary-influenced distributions. Although the disease mutation data showed a better agreement with the evolutionary-derived expectations, disease mutations were found to be statistically overabundant in conserved domains, and under-represented in variable regions, even after accounting for amino acid site variability of domains over long-term evolutionary history. This finding suggests that there is a nonadditive influence of amino acid site conservation on the observed intragenic distribution of disease mutations, and underscores the importance of understanding the patterns of neutral amino acid substitutions permitted in a gene over long-term evolutionary history.