Genetic Variation at the Chromosome 16 Chemokine Gene Cluster: Development of a Strategy for Association Studies in Complex Disease

The chemokine gene cluster [CCL22, CX3CL1, CCL17] (previously known as [SCYA22, SCYD1, SCYA17]) is a candidate locus for one of the susceptibility genes for inflammatory bowel disease that are located in the peri‐centromeric region of chromosome 16. Screening for sequence variation at this locus led to the detection of 14 single nucleotide polymorphisms (SNPs). An efficient experimental and computational approach was developed to estimate allele frequencies and pairwise linkage disequilibrium relationships between SNPs at this locus, and to test them for association with inflammatory bowel disease. The 12 common SNPs were assigned to 5 distinct linkage disequilibrium groups. Genotyping of one SNP from each linkage disequilibrium group in a large cohort of families with inflammatory bowel disease did not provide convincing evidence of association with either Crohn's disease or ulcerative colitis. We describe an efficient experimental design from SNP screening to association testing. This strategy can be used to test candidate genes for involvement in susceptibility to complex disease.     

Effect of heterogeneity on the chromosome 10 risk in late-onset Alzheimer disease

With the exception of ApoE (APOE), no universally accepted genetic association has been identified with late-onset Alzheimer disease (AD). A broad region of chromosome 10 has engendered continued interest generated from both preliminary genetic linkage and candidate gene studies. To better examine this region, we combined unbiased genetic linkage with candidate gene association studies. We genotyped 36 SNPs evenly spaced across 80.2 Mb in a family-based data set containing 1,337 discordant sibling pairs in 567 multiplex families to narrow the peak region of linkage using both covariate and subset analyses. Simultaneously, we examined five functional candidate genes (VR22, LRRTM3, PLAU, TNFRSF6, and IDE) that also fell within the broad area of linkage. A total of 50 SNPs were genotyped across the genes in the family-based data set and an independent case-control data set containing 483 cases and 879 controls. Of the 50 SNPs in the five candidate genes, 22 gave nominally significant association results in at least one data set, with at least one positive SNP in each gene. SNPs rs2441718 and rs2456737 in VR22 (67.8 Mb) showed association in both family-based and case-control data sets (both P=0.03). A two-point logarithmic odds (LOD) score of 2.69 was obtained at SNP rs1890739 (45.1 Mb, P=0.03 in 21% of the families) when the families were ordered from low to high by ApoE LOD score using ordered subset analysis (OSA). These data continue to support a role for chromosome 10 loci in AD. However, the candidate gene and linkage analysis results did not converge, suggesting that there is more extensive heterogeneity on chromosome 10 than previously appreciated.     

Objective prioritization of positional candidate genes at a quantitative trait locus for pre-eclampsia on 2q22

Pre-eclampsia/eclampsia (PE/E) is a common, serious medical disorder of human pregnancy. Familial association of PE/E has been recognized for decades, but the genetics are complex and poorly understood. In an attempt to identify PE/E susceptibility genes, we embarked on a positional cloning strategy using 34 Australian and New Zealand PE/E pedigrees. An initial 10-cM resolution genome scan revealed a putative susceptibility locus spanning a broad region on chromosome 2 that overlaps an independently determined linkage signal seen in Icelandic PE pedigrees. Subsequent fine mapping using 25 additional short tandem repeat (STR) markers in this region and non-parametric multipoint linkage analysis did not change the overall position. Under a strict diagnosis of PE, we obtained significant evidence of linkage on 2q with a peak log-of-odds ratio score (LOD) of 3.43 near marker D2S151 at 155 cM. To prioritize positional candidate genes at the 2q locus for detailed analysis, we applied an objective prioritization strategy that integrates quantitative bioinformatics, assessment of differential gene expression and association analysis of single-nucleotide polymorphisms (SNPs). Highest priority was assigned to the activin receptor gene ACVR2. This gene also showed >10-fold differential gene expression in human decidual tissue from normotensive and PE individuals. We genotyped five known SNPs in this gene in our pedigrees and performed tests for association and linkage disequilibrium. One SNP (rs1424954) showed strong preliminary evidence of association with PE (P = 0.007), whereas two others (rs1364658 and rs1895694) exhibited nominal evidence (P < 0.05). Haplotype analysis revealed no additional association information. There was evidence of weak linkage disequilibrium among these SNPs. The highest observed LD occurred between the two strongest associated SNPs, suggesting that the observed signals may be the signature of an observed functional variant.     

DVL2基因多态性与中国汉族人群先天性脊柱侧凸遗传易感性的关联研究

背景：近20年来小鼠的分子胚胎学研究进展获得了大量关于脊椎发育的分子信息,用同线性分析法确立先天性脊柱侧凸的候选基因已成为可能。 目的：通过候选基因DVL2上关键单核苷酸多态性位点的筛查,探索DVL2与中国汉族人群先天性脊柱侧凸及其不同临床表型之间的关联。 方法：采用病例-对照研究,入选127例中国汉族先天性脊柱侧凸患者和127例对照组。根据国际人类基因组单体型图计划提供的基因型数据,应用Haploview 4.1软件选取DVL2的标签和功能单核苷酸多态性。根据椎体畸形特点、畸形部位、畸形受累程度、有无合并肋骨畸形和椎管内畸形将病例组进一步分为不同临床表型。对所有样本应用SNPstream UHT Genotyping系统对所选单核苷酸多态性位点进行基因型鉴定;进一步进行基于基因型/等位基因频率的关联分析,并用Haploview 4.1软件分析对照组单核苷酸多态性位点间是否存在连锁不平衡。 结果与结论：共筛选5个位点：单核苷酸多态性1(rs2074222)、单核苷酸多态性2(rs222837)、单核苷酸多态性3(rs222835)、单核苷酸多态性4(rs10671352)和单核苷酸多态性5(rs222836),其基因型分布在病例和对照组中均符合Hardy-Weinberg平衡;5个位点处于完全连锁不平衡状态;5个位点的基因型/等位基因/单倍体型与先天性脊柱侧凸的发生风险之间不存在相关性。在进一步与先天性脊柱侧凸临床表型的关联分析中没有发现阳性位点。提示在中国汉族人群中DVL2基因可能不是引起先天性脊柱侧凸及其不同临床表型的主要因素,有待于进一步深入研究。     

Further Investigation of Linkage Disequilibrium SNPs and their Ability to Identify Associated Susceptibility Loci

There is currently considerable interest in the use of single‐nucleotide polymorphisms (SNPs) to map disease susceptibility genes. The success of this method will depend on a number of factors including the strength of linkage disequilibrium (LD) between marker and disease loci. We used a data set of SNP genotypings in the region of the APOE disease susceptibility locus to investigate the likely usefulness of SNPs in case‐control studies. Using the estimated haplotype structure surrounding and including the APOE locus, and assuming a codominant disease model, we treated each SNP in turn as if it were a disease susceptibility locus and obtained, for each disease locus and markers, the expected likelihood ratio test (LRT) to assess disease association.We were particularly interested in the power to detect association with the susceptibility polymorphism itself, the power of nearby markers to detect association, and the ability to distinguish between the susceptibility polymorphism and marker loci also showing association. We found that the expected LRT depended critically on disease allele frequencies. For disease loci with a reasonably common allele we were usually able to detect association. However, for only a subset of markers in the close neighbourhood of the disease locus was association detectable. In these cases we were usually, but not always, able to distinguish the disease locus from nearby associated marker loci. For some disease loci, no other loci demonstrated detectable association with the disease phenotype. We conclude that one may need to use very dense SNP maps in order to avoid overlooking polymorphisms affecting susceptibility to a common phenotype.     

Haplotype block partitioning and tag SNP selection using genotype data and their applications to association studies

Recent studies have revealed that linkage disequilibrium (LD) patterns vary across the human genome with some regions of high LD interspersed by regions of low LD. A small fraction of SNPs (tag SNPs) is sufficient to capture most of the haplotype structure of the human genome. In this paper, we develop a method to partition haplotypes into blocks and to identify tag SNPs based on genotype data by combining a dynamic programming algorithm for haplotype block partitioning and tag SNP selection based on haplotype data with a variation of the expectation maximization (EM) algorithm for haplotype inference. We assess the effects of using either haplotype or genotype data in haplotype block identification and tag SNP selection as a function of several factors, including sample size, density or number of SNPs studied, allele frequencies, fraction of missing data, and genotyping error rate, using extensive simulations. We find that a modest number of haplotype or genotype samples will result in consistent block partitions and tag SNP selection. The power of association studies based on tag SNPs using genotype data is similar to that using haplotype data.     

SNP-set analysis replicates acute lung injury genetic risk factors

ABSTRACT: BACKGROUND: We used a gene - based replication strategy to test the reproducibility of prior acute lung injury candidate gene associations. METHODS: We phenotyped 474 patients from a prospective severe trauma cohort study for ALI in the first 5 days following trauma. Genomic DNA from subjects' blood was genotyped using the IBC chip, a multiplex SNP array. Results were filtered for 25 candidate genes present on the IBC platform using prespecified literature search criteria. For each gene, we grouped SNPs according to haplotype blocks and tested the joint effect of all SNPs on susceptibility to ALI using the SNP-set kernel association test. Results were compared to single SNP analysis of the candidate SNPs. Analyses were separate for genetically determined ancestry (African or European). RESULTS: We identified 4 genes in African ancestry and 2 in European ancestry trauma subjects which replicated their associations with ALI. Ours is the first replication of IL6, IL10, IRAK3, and VEGFA associations in non-European populations with ALI. Only one gene - VEGFA - demonstrated association with ALI in both ancestries, with distinct haplotype blocks in each ancestry driving the association. We also report the association between trauma-associated ALI and NFKBIA in European ancestry subjects. CONCLUSIONS: Prior ALI genetic associations are reproducible and replicate in a trauma cohort. Kernel - based SNP-set analysis is a more powerful method to detect ALI association than single SNP analysis, and thus may be more useful for replication testing. Further, gene-based replication can extend candidate gene associations to diverse ethnicities.     

HapMap coverage for SNPs in the Japanese population

The coverage of human genomic variations is known to substantially affect the success of genome-wide association studies. We therefore assessed the SNP coverage in the HapMap database for a total of 1,304 subjects from the Japanese population by combining resequencing and high-density genotyping approaches. First, we resequenced 48 Japanese subjects in 86 genes (572 kb in total), and we then genotyped the subset of tag SNPs and also imputed genotypes for all of the detected SNPs in an additional panel of 1,256 subjects. Subsequently, we genotyped 555,352 tag SNPs selected from the HapMap in 72 Japanese subjects (from the panel of 1,256 subjects) and further imputed genotypes for all SNPs currently included in the HapMap. Of 738 common genic SNPs (1.3 per kb) that we detected by resequencing, 58% had already been genotyped in the HapMap, and 31% were not genotyped but had a proxy SNP in the HapMap with a linkage disequilibrium coefficient r ² ≥ 0.8, whereas 11% were not represented in the current HapMap database. Thus, the HapMap coverage appears to be high although not thorough for SNPs in the Japanese population as compared to its coverage reported in Caucasians, and this needs to be considered when we interpret association results. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Genotypic variants at 2q33 and risk of esophageal squamous cell carcinoma in China: a meta-analysis of genome-wide association studies

Genome-wide association studies have identified susceptibility loci for esophageal squamous cell carcinoma (ESCC). We conducted a meta-analysis of all single-nucleotide polymorphisms (SNPs) that showed nominally significant P-values in two previously published genome-wide scans that included a total of 2961 ESCC cases and 3400 controls. The meta-analysis revealed five SNPs at 2q33 with P< 5 × 10(-8), and the strongest signal was rs13016963, with a combined odds ratio (95% confidence interval) of 1.29 (1.19-1.40) and P= 7.63 × 10(-10). An imputation analysis of 4304 SNPs at 2q33 suggested a single association signal, and the strongest imputed SNP associations were similar to those from the genotyped SNPs. We conducted an ancestral recombination graph analysis with 53 SNPs to identify one or more haplotypes that harbor the variants directly responsible for the detected association signal. This showed that the five SNPs exist in a single haplotype along with 45 imputed SNPs in strong linkage disequilibrium, and the strongest candidate was rs10201587, one of the genotyped SNPs. Our meta-analysis found genome-wide significant SNPs at 2q33 that map to the CASP8/ALS2CR12/TRAK2 gene region. Variants in CASP8 have been extensively studied across a spectrum of cancers with mixed results. The locus we identified appears to be distinct from the widely studied rs3834129 and rs1045485 SNPs in CASP8. Future studies of esophageal and other cancers should focus on comprehensive sequencing of this 2q33 locus and functional analysis of rs13016963 and rs10201587 and other strongly correlated variants.     

Genetic variation in the IGSF6 gene and lack of association with inflammatory bowel disease.

The immunoglobulin superfamily 6 gene (IGSF6) on chromosome 16p11-p12 has been investigated as a positional and functional candidate for inflammatory bowel disease (IBD) susceptibility. Screening of the six exons of IGSF6 for single nucleotide polymorphisms (SNPs) detected four novel SNPs, and validated three of six SNPs listed in the international SNP database (dbSNP). The seven SNPs in IGSF6 formed five distinct linkage disequilibrium groups. There was no evidence for association of the common SNPs with disease in a large cohort of patients with IBD. The novel SNPs and the linkage disequilibrium map will be a useful resource for the analysis of IGSF6 in other immune disorders.     

Evidence for an Association of the Dopamine D5 Receptor Gene on Age at Onset of Attention Deficit Hyperactivity Disorder

The purpose of this study was to determine whether the single nucleotide polymorphisms (SNPs) within candidate genes for attention deficit hyperactivity disorder (ADHD) are associated with the age at onset for ADHD. One hundred and forty-three SNPs were genotyped across five candidate genes ( DRD5 , SLC6A3 , HTR1B , SNAP25 , DRD4 ) for ADHD in 229 families with at least one affected offspring. SNPs with the highest estimated power to detect an association with age at onset were selected for each candidate gene, using a power-based screening procedure that does not compromise the nominal significance level. A time-to-onset analysis for family-based samples was performed on these SNPs to determine if an association exists with age at onset for ADHD. Seven consecutive SNPs surrounding the D5 dopamine receptor gene ( DRD5 ), were associated with the age at onset for ADHD; FDR adjusted q-values ranged from 0.008 to 0.023. This analysis indicates that individuals with the risk genotype develop ADHD earlier than individuals with any other genotype. A haplotype analysis across the 6 significant SNPs that were in linkage disequilibrium with one another, CTCATA , was also found to be significant (p-value = 0.02). We did not observe significant associations with age at onset for the other candidate loci tested. Although definitive conclusions await independent replication, these results suggest that a variant in DRD5 may affect age at onset for ADHD.     

Schistosomal hepatic fibrosis and the interferon gamma receptor: a linkage analysis using single-nucleotide polymorphic markers

A minority of individuals infected with the parasite Schistosoma mansoni develops hepatic fibrosis. HLA studies in Egypt and a candidate gene search in a Sudanese population indicate that the host's genetics contribute to disease susceptibility. In an Egyptian community, 32.7% of individuals 11 years and older had significant fibrosis by WHO ultrasound criteria. Linkage to 10 candidate genes was tested using 89 affected sibling pairs from 40 pedigrees in this community. The candidates included genes that initiate fibrosis, participate in collagen synthesis, or control collagen degradation. Two to four single-nucleotide polymorphisms (SNPs) were genotyped per locus, and 188 individuals were genotyped at 48 markers. Model-free modified Haseman-Elston analysis identified linkage to a SNP in the interferon gamma receptor locus (P=0.000001). There was also weak evidence for linkage to the interleukin 13-4 region and tissue growth factor beta 1.     

The power of genome-wide association studies of complex disease genes: statistical limitations of indirect approaches using SNP markers

Genome-wide association studies using a dense map of single nucleotide polymorphism (SNP) markers seem to enable us to detect a number of complex disease genes. In such indirect association studies, whether susceptibility genes can be detected is dependent not only on the degree of linkage disequilibrium between the disease variant and the SNP marker but also on the difference in their allele frequencies. These factors, as well as penetrance of the disease variant, influence the statistical power of such approaches. However, the power of indirect association studies is not well understood. We calculated the number of individuals necessary for the detection of the disease variant in both direct and indirect association studies with a case-control design. The result shows that a remarkable reduction in the statistical power of indirect studies, compared with that of direct ones, is unavoidable in the genome-wide screening of complex disease genes. If there is a large difference in allele frequency between the disease variant and the marker, the disease variant cannot be detected. Because the frequency of the disease variant is unknown, SNP markers with various allele frequencies, or a large number of SNP markers, must be used in indirect association studies. However, if the number of SNP markers is increased, the obtained P value may not reach the significance level due to the Bonferroni adjustment. Thus, to test a possible association between functional variants and a complex disease directly, we should identify such SNPs in as many genes as possible for use in genome-wide association studies. Reveived: March 27, 2001 / Accepted: April 21, 2001     

Tag SNP selection for candidate gene association studies using HapMap and gene resequencing data

HapMap provides linkage disequilibrium (LD) information on a sample of 3.7 million SNPs that can be used for tag SNP selection in whole-genome association studies. HapMap can also be used for tag SNP selection in candidate genes, although its performance has yet to be evaluated against gene resequencing data, where there is near-complete SNP ascertainment. The Environmental Genome Project (EGP) is the largest gene resequencing effort to date with over 500 resequenced genes. We used HapMap data to select tag SNPs and calculated the proportions of common SNPs (MAF>or=0.05) tagged (rho2>or=0.8) for each of 127 EGP Panel 2 genes where individual ethnic information was available. Median gene-tagging proportions are 50, 80 and 74% for African, Asian, and European groups, respectively. These low gene-tagging proportions may be problematic for some candidate gene studies. In addition, although HapMap targeted nonsynonymous SNPs (nsSNPs), we estimate only approximately 30% of nonsynonymous SNPs in EGP are in high LD with any HapMap SNP. We show that gene-tagging proportions can be improved by adding a relatively small number of tag SNPs that were selected based on resequencing data. We also demonstrate that ethnic-mixed data can be used to improve HapMap gene-tagging proportions, but are not as efficient as ethnic-specific data. Finally, we generalized the greedy algorithm proposed by Carlson et al (2004) to select tag SNPs for multiple populations and implemented the algorithm into a freely available software package mPopTag.     

Information capture using SNPs from HapMap and whole-genome chips differs in a sample of inflammatory and cardiovascular gene-centric regions from genome-wide estimates

Large-scale genetic association studies are now widely conducted using SNPs selected from the International HapMap Project or provided on commercial "whole genome" chips. As only a subset of human genetic variation has been identified, it is unknown what proportion of the total genetic variation can be captured in this way, although recent genome-wide estimates of SNP capture rates have been encouraging. We estimated the expected gene-centric information capture for whole-genome chips using sequence data from 306 inflammatory/cardiovascular genes and found SNP capture rates notably lower than previous genome-wide estimates. Further investigation indicates that a major explanation for these lower capture rates is the aggregation of particular sequence features that influence both linkage disequilibrium and the amenability of SNPs for genotyping within the broad class of inflammatory/ cardiovascular genes. This suggests that the power of genetic association studies in some complex traits will depend not only upon established factors, such as allele frequency and penetrance, but may also be influenced by the distribution of sequence features in the class of genes expected to underlie the disease of interest.     

Where is the causal variant? On the advantage of the family design over the case–control design in genetic association studies

Many associated single-nucleotide polymorphisms (SNPs) have been identified by association studies for numerous diseases. However, the association between a SNP and a disease can result from a causal variant in linkage disequilibrium (LD) with the considered SNP. Assuming that the true causal variant is among the genotyped SNPs, other authors demonstrated that the power to discriminate between it and other SNPs in LD is low. Here, we propose to take advantage of the information provided by family data to improve the inference on the causal variant: we exploit the linkage information provided by affected sib pairs to discriminate the causal variant from the associated SNPs. The family-based approach improves discrimination power requiring up to five times less individuals than its case–control equivalent. However, the main advantage of family design is the possibility to carry out the procedure one step further: the linkage information allows inference on causal variants, which are not genotyped but in LD with tag-SNPs displaying association, which is impossible with case–control design. By means of Bayesian methods, we estimate the LD between the observed SNPs and an unobserved causal variant, as well as the allelic odds ratio at the unobserved causal variant. The proposed procedure is illustrated on a multiple sclerosis (MS) family data set including genotypes of SNPs in IL2RA, confirming the advantage of using a family design to identify causal variants. The results of our method on this data suggest the existence of two distinct causal variants in this gene for the MS.     

Linking disease associations with regulatory information in the human genome

Genome-wide association studies have been successful in identifying single nucleotide polymorphisms (SNPs) associated with a large number of phenotypes. However, an associated SNP is likely part of a larger region of linkage disequilibrium. This makes it difficult to precisely identify the SNPs that have a biological link with the phenotype. We have systematically investigated the association of multiple types of ENCODE data with disease-associated SNPs and show that there is significant enrichment for functional SNPs among the currently identified associations. This enrichment is strongest when integrating multiple sources of functional information and when highest confidence disease-associated SNPs are used. We propose an approach that integrates multiple types of functional data generated by the ENCODE Consortium to help identify "functional SNPs" that may be associated with the disease phenotype. Our approach generates putative functional annotations for up to 80% of all previously reported associations. We show that for most associations, the functional SNP most strongly supported by experimental evidence is a SNP in linkage disequilibrium with the reported association rather than the reported SNP itself. Our results show that the experimental data sets generated by the ENCODE Consortium can be successfully used to suggest functional hypotheses for variants associated with diseases and other phenotypes.     

Genetic variation in the IGSF6 gene and lack of association with inflammatory bowel disease

The immunoglobulin superfamily 6 gene (IGSF6) on chromosome 16p11‐p12 has been investigated as a positional and functional candidate for inflammatory bowel disease (IBD) susceptibility. Screening of the six exons of IGSF6 for single nucleotide polymorphisms (SNPs) detected four novel SNPs, and validated three of six SNPs listed in the international SNP database (dbSNP). The seven SNPs in IGSF6 formed five distinct linkage disequilibrium groups. There was no evidence for association of the common SNPs with disease in a large cohort of patients with IBD. The novel SNPs and the linkage disequilibrium map will be a useful resource for the analysis of IGSF6 in other immune disorders.     

Examination of NRCAM, LRRN3, KIAA0716, and LAMB1 as autism candidate genes

Background

A substantial body of research supports a genetic involvement in autism. Furthermore, results from various genomic screens implicate a region on chromosome 7q31 as harboring an autism susceptibility variant. We previously narrowed this 34 cM region to a 3 cM critical region (located between D7S496 and D7S2418) using the Collaborative Linkage Study of Autism (CLSA) chromosome 7 linked families. This interval encompasses about 4.5 Mb of genomic DNA and encodes over fifty known and predicted genes. Four candidate genes (NRCAM, LRRN3, KIAA0716, and LAMB1) in this region were chosen for examination based on their proximity to the marker most consistently cosegregating with autism in these families (D7S1817), their tissue expression patterns, and likely biological relevance to autism.

Methods

Thirty-six intronic and exonic single nucleotide polymorphisms (SNPs) and one microsatellite marker within and around these four candidate genes were genotyped in 30 chromosome 7q31 linked families. Multiple SNPs were used to provide as complete coverage as possible since linkage disequilibrium can vary dramatically across even very short distances within a gene. Analyses of these data used the Pedigree Disequilibrium Test for single markers and a multilocus likelihood ratio test.

Results

As expected, linkage disequilibrium occurred within each of these genes but we did not observe significant LD across genes. None of the polymorphisms in NRCAM, LRRN3, or KIAA0716 gave p < 0.05 suggesting that none of these genes is associated with autism susceptibility in this subset of chromosome 7-linked families. However, with LAMB1, the allelic association analysis revealed suggestive evidence for a positive association, including one individual SNP (p = 0.02) and three separate two-SNP haplotypes across the gene (p = 0.007, 0.012, and 0.012).

Conclusions

NRCAM, LRRN3, KIAA0716 are unlikely to be involved in autism. There is some evidence that variation in or near the LAMB1 gene may be involved in autism.