Human metabolic individuality in biomedical and pharmaceutical research

Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.     

TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis

Although there has been much success in identifying genetic variants associated with common diseases using genome-wide association studies (GWAS), it has been difficult to demonstrate which variants are causal and what role they have in disease. Moreover, the modest contribution that these variants make to disease risk has raised questions regarding their medical relevance. Here we have investigated a single nucleotide polymorphism (SNP) in the TNFRSF1A gene, that encodes tumour necrosis factor receptor 1 (TNFR1), which was discovered through GWAS to be associated with multiple sclerosis (MS), but not with other autoimmune conditions such as rheumatoid arthritis, psoriasis and Crohn’s disease. By analysing MS GWAS data in conjunction with the 1000 Genomes Project data we provide genetic evidence that strongly implicates this SNP, rs1800693, as the causal variant in the TNFRSF1A region. We further substantiate this through functional studies showing that the MS risk allele directs expression of a novel, soluble form of TNFR1 that can block TNF. Importantly, TNF-blocking drugs can promote onset or exacerbation of MS, but they have proven highly efficacious in the treatment of autoimmune diseases for which there is no association with rs1800693. This indicates that the clinical experience with these drugs parallels the disease association of rs1800693, and that the MS-associated TNFR1 variant mimics the effect of TNF-blocking drugs. Hence, our study demonstrates that clinical practice can be informed by comparing GWAS across common autoimmune diseases and by investigating the functional consequences of the disease-associated genetic variation.     

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods-recursive partitioning and regression-to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; P(combined) = 2.01 x 10(-19) and 2.35 x 10(-13), respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes.     

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined approximately 2,000 individuals for each of 7 major diseases and a shared set of approximately 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 x 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals (including 58 loci with single-point P values between 10(-5) and 5 x 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.     

Functional epistasis on a common MHC haplotype associated with multiple sclerosis

Genes in the major histocompatibility complex (MHC) encode proteins important in activating antigen-specific immune responses. Alleles at adjacent MHC loci are often in strong linkage disequilibrium; however, little is known about the mechanisms responsible for this linkage disequilibrium. Here we report that the human MHC HLA-DR2 haplotype, which predisposes to multiple sclerosis, shows more extensive linkage disequilibrium than other common caucasian HLA haplotypes in the DR region and thus seems likely to have been maintained through positive selection. Characterization of two multiple-sclerosis-associated HLA-DR alleles at separate loci by a functional assay in humanized mice indicates that the linkage disequilibrium between the two alleles may be due to a functional epistatic interaction, whereby one allele modifies the T-cell response activated by the second allele through activation-induced cell death. This functional epistasis is associated with a milder form of multiple-sclerosis-like disease. Such epistatic interaction might prove to be an important general mechanism for modifying exuberant immune responses that are deleterious to the host and could also help to explain the strong linkage disequilibrium in this and perhaps other HLA haplotypes.     

Cancer genetics

Cancer genetics has for many years focused on mutational events that have their primary effect within the cancer cell. Recently that focus has widened, with evidence of the importance of epigenetic events and of cellular interactions in cancer development. The role of common genetic variation in determining the range of individual susceptibility within the population is increasingly recognized, and will be addressed using information from the Human Genome Project. These new research directions will highlight determinants of cancer that lie outside the cancer cell, suggest new targets for intervention, and inform the design of strategies for prevention in groups at increased risk.     

全基因组关联分析显示基因ANXA8和C10orf11为影响肌少症的候选基因

为了寻找与瘦体重(lean body mass,LBM)相关的单核苷酸多态性(single nucleotide polymorphism, SNP)位点及易感基因,在1 000个不相关的白人中采用Affymetix 500K芯片扫描了500 000个SNPs,并进行全基因组关联分析(genome-wide association study,GWAS),显著结果在1 625个中国人样本和2 283个欧洲白人样本中进行验证,并将验证结果与研究结果进行荟萃分析。研究发现SNPsrs7905603,rs9416083,rs4409772,rs2894310与LBM关联,其中rs7905603位于基因ANXA8,其他3个SNPs位于基因C10orf11。荟萃分析得到的合并p值分别为2.08×10-5,7.44×10~(-6),6.73×10~(-6),6.76×10~(-6)。ANXA8和C10orf11基因是影响LBM变异的候选基因,这对肌少症的认识提供了新的理论依据。     

一种分析全基因组上位性的新方法

传统基于单位点的全基因组关联研究存在重复性低、难以解释性等缺陷,而采用基于机器学习的上位性分析中面临计算复杂度高、预测准确度不足等问题.本文提出一种分析全基因组上位性的新方法,该方法采用二阶段框架的上位性分析方法,它包含特征过滤阶段以及上位性组合优化阶段,在特征过滤阶段提出了多准则融合策略,从多个不同角度评价遗传变异位点,以保证易感的弱效位点能被保留,然后采用多准测排序融合策略剔除与疾病状态关联程度低的遗传变异,进一步在上位性组合优化阶段采用贪婪算法启发式地搜索组合空间,以降低时间复杂度,最后采用支持向量机作为上位性评价模型.实验中采用不同的连锁不平衡参数与经典算法SNPruler与ACO的性能进行对比,实验结果表明:本文方法能有效保留弱效位点,一定程度上提高了疾病预测的正确度.     

Genome-Wide Interaction-Based Association of Human Diseases—A Survey

Genome-Wide Association Studies（GWASs） aim to identify genetic variants that are associated with disease by assaying and analyzing hundreds of thousands of Single Nucleotide Polymorphisms（SNPs）. Although traditional single-locus statistical approaches have been standardized and led to many interesting findings, a substantial number of recent GWASs indicate that for most disorders, the individual SNPs explain only a small fraction of the genetic causes. Consequently, exploring multi-SNPs interactions in the hope of discovering more significant associations has attracted more attentions. Due to the huge search space for complicated multilocus interactions, many fast and effective methods have recently been proposed for detecting disease-associated epistatic interactions using GWAS data. In this paper, we provide a critical review and comparison of eight popular methods, i.e., BOOST, TEAM, epi Forest, EDCF, SNPHarvester, epi MODE, MECPM, and MIC, which are used for detecting gene-gene interactions among genetic loci. In views of the assumption model on the data and searching strategies, we divide the methods into seven categories. Moreover, the evaluation methodologies,including detecting powers, disease models for simulation, resources of real GWAS data, and the control of false discover rate, are elaborated as references for new approach developers. At the end of the paper, we summarize the methods and discuss the future directions in genome-wide association studies for detecting epistatic interactions.     

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P?相似文献   

Genome-wide association study identifies novel breast cancer susceptibility loci

Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2 > 0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P < 10(-7)). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P < 0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach.     

Identification and mapping to chromosome 1 of a susceptibility locus for periinsulitis in non-obese diabetic mice

Insulin-dependent diabetes mellitus (IDDM) is a polygenic disease caused by autoimmune destruction of insulin-producing beta cells in the islets of Langerhans. Its onset is preceded by a long and variable period in which lymphoid cells infiltrate the pancreas but first remain outside the islets (peri-insulitis) before invading them (insulitis). Among susceptibility loci, only the major histocompatibility complex (MHC) has been clearly assigned. Genetic study of the nonobese diabetic (NOD) mouse model for insulin-dependent diabetes mellitus has revealed genetic linkage of insulitis and of early onset diabetes with two non-MHC loci mapping to chromosome 3 and 11 respectively. Here we report a close association of periinsulitis with a third non-MHC locus mapping to chromosome 1. Successive stages in the progression of diabetic disease thus appear to be controlled by distinct genes or sets of genes.     

A genome-wide association study identifies KIAA0350 as a type 1 diabetes gene

Type 1 diabetes (T1D) in children results from autoimmune destruction of pancreatic beta cells, leading to insufficient production of insulin. A number of genetic determinants of T1D have already been established through candidate gene studies, primarily within the major histocompatibility complex but also within other loci. To identify new genetic factors that increase the risk of T1D, we performed a genome-wide association study in a large paediatric cohort of European descent. In addition to confirming previously identified loci, we found that T1D was significantly associated with variation within a 233-kb linkage disequilibrium block on chromosome 16p13. This region contains KIAA0350, the gene product of which is predicted to be a sugar-binding, C-type lectin. Three common non-coding variants of the gene (rs2903692, rs725613 and rs17673553) in strong linkage disequilibrium reached genome-wide significance for association with T1D. A subsequent transmission disequilibrium test replication study in an independent cohort confirmed the association. These results indicate that KIAA0350 might be involved in the pathogenesis of T1D and demonstrate the utility of the genome-wide association approach in the identification of previously unsuspected genetic determinants of complex traits.     

MHC II DRB variation and trans-species polymorphism in the golden snub-nosed monkey (Rhinopithecus roxellana)

Genetic variation is generally believed to be important in studying endangered species’ adaptive potential.Early studies assessed genetic diversity using nearly neutral markers,such as microsatellite loci and mitochondrial DNA(mtDNA),which are very informative for phylogenetic and phylogeographic reconstructions.However,the variation at these loci cannot provide direct information on selective processes involving the interaction of individuals with their environment,or on the capability to resist continuously evolving pathogens and parasites.The importance of genetic diversity at informative adaptive markers,such as major histocompatibility complex(MHC) genes,is increasingly being realized,especially in endangered,isolated species.Small population size and isolation make the golden snub-nosed monkey(Rhinopithecus roxellana) particularly susceptible to genetic variation losses through inbreeding and restricted gene flow.In this study,we compared the genetic variation and population structure of microsatellites,mtDNA,and the most relevant adaptive region of the MHC II-DRB genes in the golden snub-nosed monkey.We examined three Chinese R.roxellana populations and found the same variation patterns in all gene regions,with the population from Shennongjia population,Hubei Province,showing the lowest polymorphism among three populations.Genetic drift that outweighed balancing selection and the founder effect in these populations may explain the similar genetic variation pattern found in these neutral and adaptive genes.     

MHC polymorphism and disease-resistance to Edwardsiella tarda in six turbot (Scophthalmus maximus) families

This study examined genetic variation in the major histocompatibility complex(MHC) Class II B gene in turbot(Scophthalmus maximus) by virulent bacterial pathogen challenge.One hundred fry from each of six families were infected with Edwardsiella tarda by intraperitoneal injection.Family mortality ranged from 28.0% to 83.3%.Complete exon 2 and intron 1 sequences of MHC Class II B genes were amplified from five survivor and five non-survivor individuals per family using the clone-sequence method.Thirty-seven sequences from 60 individuals revealed 37 different alleles,25 of which were unique to this study.The 25 unique alleles belonged to 16 major allele types.Nine alleles were used to examine the association between alleles and resistance/susceptibility to disease.Five alleles were present in an individual,suggesting a minimum of three loci or copies of the turbot MHC Class II B gene.The rate of non-synonymous substitution(d N) was 2.30 and 1.58 times higher than synonymous substitution(d S) in the peptide-binding regions(PBR) and non-PBR in whole families,respectively,which suggested balancing selection on exon 2 of the MHC Class II B gene in turbot.One allele,Scma-DBB1*02,was significantly more prevalent in survivor stock than in non-survivor stock(P=0.001).Therefore,this allele might be associated with resistance to bacteria.A second allele,Scma-DBB1*10,was significantly more prevalent in non-survivor stock(P=0.021),and is likely associated with susceptibility to bacteria.     

Correlation between a DNA restriction fragment length polymorphism and C4A6 protein

The fourth component of complement (C4) in man, is coded for by two separate but closely linked loci (C4A and C4B) within the major histocompatibility region (MHC), on the short arm of chromosome 6. Like class I and II loci of this region, the C4 genes are highly polymorphic with more than 30 alleles, including null alleles, assigned to the two loci. This extensive polymorphism, based mainly on electrophoretic mobility, provides a useful marker for studies of disease susceptibility. Several disorders, including systemic lupus erythematosus and type I diabetes, show associations with C4 phenotypes. We have used the technique of Southern with a C4 specific probe to examine the genomic DNA of individuals typed for C4 by protein electrophoresis. We have identified 10.7 and 3.8 kilobase (kb) BglII restriction fragments in each of 9 unrelated individuals with a C4A6 allele, and in none of 22 unrelated individuals in whom this allele was not expressed. This clear correlation of restriction fragment length polymorphism with C4 phenotype provides a precise basis for analysis of C4 polymorphism. It is likely to be of value in clinical investigations of autoimmune disease.     

Epistasis and balanced polymorphism influencing complex trait variation

Complex traits such as human disease, growth rate, or crop yield are polygenic, or determined by the contributions from numerous genes in a quantitative manner. Although progress has been made in identifying major quantitative trait loci (QTL), experimental constraints have limited our knowledge of small-effect QTL, which may be responsible for a large proportion of trait variation. Here, we identified and dissected a one-centimorgan chromosome interval in Arabidopsis thaliana without regard to its effect on growth rate, and examined the signature of historical sequence polymorphism among Arabidopsis accessions. We found that the interval contained two growth rate QTL within 210 kilobases. Both QTL showed epistasis; that is, their phenotypic effects depended on the genetic background. This amount of complexity in such a small area suggests a highly polygenic architecture of quantitative variation, much more than previously documented. One QTL was limited to a single gene. The gene in question displayed a nucleotide signature indicative of balancing selection, and its phenotypic effects are reversed depending on genetic background. If this region typifies many complex trait loci, then non-neutral epistatic polymorphism may be an important contributor to genetic variation in complex traits.     

MHC antigens in urine as olfactory recognition cues

The classical class I antigens of the major histocompatibility complex (MHC) are cell-surface glycoproteins which were originally discovered because they cause rapid rejection of cells or tissues grafted between unrelated individuals. These molecules are encoded by the K, D and L loci of the mouse MHC (and analogous loci in other species) which show extreme species polymorphism and a large number of alleles. In an outbreeding population 3.6 X 10(9) unique MHC class I phenotypes can be encoded by the 100 alleles at each of the K and D loci and the 6 alleles at the L locus. This level of polymorphism ensures that the cells and tissues of each unrelated individual are uniquely identified by their class I membrane-bound antigens. Like other membrane bound proteins, these class I molecules are anchored in the lipid bilayer by a hydrophobic domain encoded by exon 5. However, there have been reports of the occurrence of classical class I molecules in true solution in the blood of humans, mice, and rats. We report here that classical polymorphic class I molecules in normal rats are constitutively excreted in the urine and that untrained rats can distinguish the smell of urine samples taken from normal donors that differ only at the class I MHC locus and therefore excrete different allelomorphs of class I molecules in their urine.     

Copy-number variations associated with neuropsychiatric conditions

Neuropsychiatric conditions such as autism and schizophrenia have long been attributed to genetic alterations, but identifying the genes responsible has proved challenging. Microarray experiments have now revealed abundant copy-number variation--a type of variation in which stretches of DNA are duplicated, deleted and sometimes rearranged--in the human population. Genes affected by copy-number variation are good candidates for research into disease susceptibility. The complexity of neuropsychiatric genetics, however, dictates that assessment of the biomedical relevance of copy-number variants and the genes that they affect needs to be considered in an integrated context.