Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.     

Variations in DNA elucidate molecular networks that cause disease

Identifying variations in DNA that increase susceptibility to disease is one of the primary aims of genetic studies using a forward genetics approach. However, identification of disease-susceptibility genes by means of such studies provides limited functional information on how genes lead to disease. In fact, in most cases there is an absence of functional information altogether, preventing a definitive identification of the susceptibility gene or genes. Here we develop an alternative to the classic forward genetics approach for dissecting complex disease traits where, instead of identifying susceptibility genes directly affected by variations in DNA, we identify gene networks that are perturbed by susceptibility loci and that in turn lead to disease. Application of this method to liver and adipose gene expression data generated from a segregating mouse population results in the identification of a macrophage-enriched network supported as having a causal relationship with disease traits associated with metabolic syndrome. Three genes in this network, lipoprotein lipase (Lpl), lactamase beta (Lactb) and protein phosphatase 1-like (Ppm1l), are validated as previously unknown obesity genes, strengthening the association between this network and metabolic disease traits. Our analysis provides direct experimental support that complex traits such as obesity are emergent properties of molecular networks that are modulated by complex genetic loci and environmental factors.     

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.     

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.     

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   

Mapping determinants of human gene expression by regional and genome-wide association

To study the genetic basis of natural variation in gene expression, we previously carried out genome-wide linkage analysis and mapped the determinants of approximately 1,000 expression phenotypes. In the present study, we carried out association analysis with dense sets of single-nucleotide polymorphism (SNP) markers from the International HapMap Project. For 374 phenotypes, the association study was performed with markers only from regions with strong linkage evidence; these regions all mapped close to the expressed gene. For a subset of 27 phenotypes, analysis of genome-wide association was performed with >770,000 markers. The association analysis with markers under the linkage peaks confirmed the linkage results and narrowed the candidate regulatory regions for many phenotypes with strong linkage evidence. The genome-wide association analysis yielded highly significant results that point to the same locations as the genome scans for about 50% of the phenotypes. For one candidate determinant, we carried out functional analyses and confirmed the variation in cis-acting regulatory activity. Our findings suggest that association studies with dense SNP maps will identify susceptibility loci or other determinants for some complex traits or diseases.     

A variant associated with nicotine dependence, lung cancer and peripheral arterial disease

Smoking is a leading cause of preventable death, causing about 5 million premature deaths worldwide each year. Evidence for genetic influence on smoking behaviour and nicotine dependence (ND) has prompted a search for susceptibility genes. Furthermore, assessing the impact of sequence variants on smoking-related diseases is important to public health. Smoking is the major risk factor for lung cancer (LC) and is one of the main risk factors for peripheral arterial disease (PAD). Here we identify a common variant in the nicotinic acetylcholine receptor gene cluster on chromosome 15q24 with an effect on smoking quantity, ND and the risk of two smoking-related diseases in populations of European descent. The variant has an effect on the number of cigarettes smoked per day in our sample of smokers. The same variant was associated with ND in a previous genome-wide association study that used low-quantity smokers as controls, and with a similar approach we observe a highly significant association with ND. A comparison of cases of LC and PAD with population controls each showed that the variant confers risk of LC and PAD. The findings provide a case study of a gene-environment interaction, highlighting the role of nicotine addiction in the pathology of other serious diseases.     

LOD score exclusion analyses for candidate disease susceptibility genes using case-parents design

The focus of almost all the association studies of candidate genes is to test for their importance. We recently developed a LOD score approach that can be used to test against the importance of candidate genes for complex diseases and quantitative traits in random samples. As a complementary method to regular association analyses, our LOD score approach is powerful but still affected by the population admixture, though it is more conservative. To control the confounding effect of population heterogeneity, we develop here a LOD score exclusion analysis using case?parents design, the basic design of the transmission disequilibrium test (TDT) approach that is immune to population admixture. In the analysis, specific genetic effects and inheritance models at candidate genes can be analyzed and if a LOD score is ≤-2.0, the locus can be excluded from having an effect larger than that specified. Simulations show that this approach has reasonable power to exclude a candidate gene having small genetic effects if it is not a disease susceptibility locus (DSL) with sample size often employed in TDT studies. Similar to association analyses with the TDT in nuclear families, our exclusion analyses are generally not affected by population admixture. The exclusion analyses may be implemented to rule out candidate genes with no or minor genetic effects as supplemental analyses for the TDT. The utility of the approach is illustrated with an application to test the importance of vitamin D receptor (VDR) gene underlying the differential risk to osteoporosis.     

利用位点信息分析遗传疾病与基因的关联性

人体的许多遗传疾病都与其基因包含的多个位点(SNPs)相关联。因此定位与遗传疾病相关联基因在染色体中的位置,能帮助研究人员了解疾病的遗传机理,预防某些遗传病的发生。利用全基因组关联分析方法,对两类样本(患病,未患病)各个位点上的碱基进行卡方检验,找出某种遗传病最有可能的致病位点,定位其所在的致病基因。利用连锁不平衡系数,得出最可能相关的致病基因,并通过聚类算法检验结论的合理性。     

A genome-wide association study identifies novel risk loci for type 2 diabetes

Type 2 diabetes mellitus results from the interaction of environmental factors with a combination of genetic variants, most of which were hitherto unknown. A systematic search for these variants was recently made possible by the development of high-density arrays that permit the genotyping of hundreds of thousands of polymorphisms. We tested 392,935 single-nucleotide polymorphisms in a French case-control cohort. Markers with the most significant difference in genotype frequencies between cases of type 2 diabetes and controls were fast-tracked for testing in a second cohort. This identified four loci containing variants that confer type 2 diabetes risk, in addition to confirming the known association with the TCF7L2 gene. These loci include a non-synonymous polymorphism in the zinc transporter SLC30A8, which is expressed exclusively in insulin-producing beta-cells, and two linkage disequilibrium blocks that contain genes potentially involved in beta-cell development or function (IDE-KIF11-HHEX and EXT2-ALX4). These associations explain a substantial portion of disease risk and constitute proof of principle for the genome-wide approach to the elucidation of complex genetic traits.     

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.     

Fine mapping of the awn gene on chromosome 4 in rice by association and linkage analyses

Awnness is a key trait in rice domestication, yet no studies have been conducted on fine mapping or association mapping of the rice awn gene. In this study, we investigated the awnness and genotype of a core collection of 303 cultivated rice varieties and a BC5F2 segregating population of 200 individuals. Combining association and linkage analyses, we mapped the awnness related genes to chromosome 4. Primary association analysis using 24 SSR markers revealed five loci significantly associated with awnness on chromosome 4. The associated markers cover previously identified regions. Fine association mapping was conducted using another 29 markers within a 4-Mb region, covering the associated marker in34, which is close to the awn gene Awn4.1. Seven associated markers were revealed, distributed over an 870-kb region. Combining the fine association mapping and linkage analysis of awnness in the 200 BC5F2 segregating population, we finally identified a 330-kb region as the candidate region for Awn4.1. The results indicate that combining association mapping and linkage mapping provides an efficient and precise approach to both genome-wide mapping and fine mapping of rice genes.     

脑脊液中t-tau蛋白的全基因组网络辅助分析和富集研究

一些基因变异已被发现与阿尔茨海默病典型表型脑脊液相关,但这些发现忽略了小效应风险的变体、基因座内部关联以及与外部环境之间的相互关系.为此,作者利用基于功能网络和基于通路信息的方法从系统生物学角度对遗传变异进行识别.将反映阿尔茨海默症早期病理特点的CSF t-tau作为表型,在全基因组关联分析的基础上提出一种基于权重调整的PageRank网络功能模块挖掘策略.该策略不仅挖掘到广泛研究的与t-tau相关的遗传变异,挖掘到的子网也富集在如神经退行性疾病,神经系统和信号转导等通路中,表明在系统生物学层面,策略识别的特征优先子网与表型具有一定的功能关联.     

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.     

基于IMPUTE2的全基因组关联性研究的基因型填补

多数全基因组关联性研究(GWAS)采用不同的分型芯片,导致遗传变异位点的数目及选择准则不同。基因型填补可以依据已有的基因分型数据,对未分型的位点进行填补。在应用IMPUTE2软件对基因型和表型数据库(db Ga P)中胃癌GWAS数据进行全基因组填补,以详细介绍全基因组填补的原理和过程。以第九号染色体为例,使用1000 Genome Project模板介绍全基因组填补的过程,包括填补前的质量控制、Pre-phasing、填补过程、填补的质量评估及填补后的关联性分析。第九号染色体在填补前有21 033个位点;而在填补后有1 630 406个SNP;其中INFO0.3的SNP位点有817 494个;而填补质量较高(INFO0.5)的位点数目有584 755个。IMPUTE2软件可以快速准确的对未分型的基因型进行填补,从而可以将多个GWAS数据整合到相同的位点数和密度上,再进行联合分析可以提高检验的把握度以便发现新的遗传易感性位点。     

基于神经网络和粒子群算法的遗传位点与患病信息的关联性分析

基于遗传疾病与某些遗传基因位点存在的较强关联性，并考虑到位点间存在交互作用的情形，提出了关联性最强的位点组合的筛选方法。将每个候选位点组合对应的基于神经网络的预报准确率作为评价标准，用粒子群算法（PSO）通过迭代逼近找出最优的位点组合，并与神经网络权重分析法进行比较。结果表明，由本文方法得到的位点组合预报精度更高，对患病情况有着较好的识别效果，可为遗传疾病诊断等提供参考方法。     

A common sex-dependent mutation in a RET enhancer underlies Hirschsprung disease risk

The identification of common variants that contribute to the genesis of human inherited disorders remains a significant challenge. Hirschsprung disease (HSCR) is a multifactorial, non-mendelian disorder in which rare high-penetrance coding sequence mutations in the receptor tyrosine kinase RET contribute to risk in combination with mutations at other genes. We have used family-based association studies to identify a disease interval, and integrated this with comparative and functional genomic analysis to prioritize conserved and functional elements within which mutations can be sought. We now show that a common non-coding RET variant within a conserved enhancer-like sequence in intron 1 is significantly associated with HSCR susceptibility and makes a 20-fold greater contribution to risk than rare alleles do. This mutation reduces in vitro enhancer activity markedly, has low penetrance, has different genetic effects in males and females, and explains several features of the complex inheritance pattern of HSCR. Thus, common low-penetrance variants, identified by association studies, can underlie both common and rare diseases.