Genome wide association study of nonsynonymous Single Nucleotide Polymorphisms for seven common diseases

Background: Associations of several Single Nucleotide Polymorphisms (SNPs) with common diseases like Coronary Artery Disease (CAD), Crohn’s Disease (CD), Hypertension (HT), Bipolar Disorder (BD), Type 1 Diabetes (T1D), Type 2 Diabetes (T2D) and Rheumatoid Arthritis (RA) were identified in a study conducted by the Wellcome Trust Case Control Consortium (WTCCC) (1). WTCCC study compared the effects of genetic variations in 14,000 cases and 3000 shared controls and identified 24 independent associations with the diseases mentioned above using the genotype information of approximately 500,000 directly genotyped SNPs and genotype information simulated at 2.8 million loci studied by the International Hapmap Project(2). We hypothesize that there are more chances of finding association of rare SNPs with diseases by refined analysis of non-synonymous SNPs (nsSNPs) in genome wide association studies. In the present study we analyzed the association of 12,660 nsSNPs using a case control study in the WTCCC population. Materials and methods: We simulated the genotypes at 10,798 nsSNP loci studied by the Stage 2 HapMap project using the genotype information from WTCCC for all 14,000 individuals studied for seven diseases and in 3000 controls. These simulations were done using the genetic recombination map of the respective regions obtained from the haplotypes of Hapmap European population. We performed these simulations or imputations using two widely used programs called IMPUTE(3) and MACH. All the genotyped SNPs used to impute missing genotypes passed quality control tests for Hardy Weinberg equilibrium (p\u3c10-2), Minor allele frequency (MAF\u3c10-2), missing genotypes per marker (more than 10%) performed using programs in PLINK genome wide analysis package. Subsequent case control association of 10,798 imputed nsSNPs and 1,862 genotyped nsSNPs was performed using an additive model and genotype model in a frequentist and bayesian framework. Results: We found 2 nsSNPs associated with BD, 2 with Coronary Artery Disease, 7 with CD, 1 with HT, 22 with RA, 17 with T1D and 2 with T2D. In total, 53 new associations with the seven diseases (p \u3c 5 x 10-6) studied by WTCCC. We also developed a pipeline which summarizes quality control measures which should be considered to minimize false associations in genome wide association studies. In any such large scale genome wide association studies, there are chances of getting false positives which show association at loci imputed using genetic information from Hapmap. This can arise due to the genotype quality of tag SNPs which are in high linkage disequilibrium (LD) in the region where the missing genotype is simulated. Such false associations can be ruled out by visually inspecting the cluster plots of genotyped SNPs which are in high LD in respective regions. A comprehensive quality control will be performed at this stage by visually inspecting cluster plots of all genotyped SNPs which are in high LD with the imputed SNPs associated with each disease which will count out any such influences on new associations identified in our study

Distribution and Effects of Nonsense Polymorphisms in Human Genes

BACKGROUND: A great amount of data has been accumulated on genetic variations in the human genome, but we still do not know much about how the genetic variations affect gene function. In particular, little is known about the distribution of nonsense polymorphisms in human genes despite their drastic effects on gene products. METHODOLOGY/PRINCIPAL FINDINGS: To detect polymorphisms affecting gene function, we analyzed all publicly available polymorphisms in a database for single nucleotide polymorphisms (dbSNP build 125) located in the exons of 36,712 known and predicted protein-coding genes that were defined in an annotation project of all human genes and transcripts (H-InvDB ver3.8). We found a total of 252,555 single nucleotide polymorphisms (SNPs) and 8,479 insertion and deletions in the representative transcripts in these genes. The SNPs located in ORFs include 40,484 synonymous and 53,754 nonsynonymous SNPs, and 1,258 SNPs that were predicted to be nonsense SNPs or read-through SNPs. We estimated the density of nonsense SNPs to be 0.85x10(-3) per site, which is lower than that of nonsynonymous SNPs (2.1x10(-3) per site). On average, nonsense SNPs were located 250 codons upstream of the original termination codon, with the substitution occurring most frequently at the first codon position. Of the nonsense SNPs, 581 were predicted to cause nonsense-mediated decay (NMD) of transcripts that would prevent translation. We found that nonsense SNPs causing NMD were more common in genes involving kinase activity and transport. The remaining 602 nonsense SNPs are predicted to produce truncated polypeptides, with an average truncation of 75 amino acids. In addition, 110 read-through SNPs at termination codons were detected. CONCLUSION/SIGNIFICANCE: Our comprehensive exploration of nonsense polymorphisms showed that nonsense SNPs exist at a lower density than nonsynonymous SNPs, suggesting that nonsense mutations have more severe effects than amino acid changes. The correspondence of nonsense SNPs to known pathological variants suggests that phenotypic effects of nonsense SNPs have been reported for only a small fraction of nonsense SNPs, and that nonsense SNPs causing NMD are more likely to be involved in phenotypic variations. These nonsense SNPs may include pathological variants that have not yet been reported. These data are available from Transcript View of H-InvDB and VarySysDB (http://h-invitational.jp/varygene/)

Silent Nucleotide Polymorphisms and a Phylogeny for Mycobacterium tuberculosis

Population diversity of genetically silent nucleotide polymorphisms produces a unifying phylogeny for Mycobacterium tuberculosis

Genetic relationships between A20/TNFAIP3, chronic inflammation and autoimrnune disease

A20 [also known as TNFAIP3 (tumour necrosis factor a-induced protein 3)] restricts and terminates inflammatory responses through modulation of the ubiquitination status of central components in NF-kappa B (nuclear factor kappa B), IRF3 (interferon regulatory factor 3) and apoptosis signalling cascades. The phenotype of mice with full or conditional A20 deletion illustrates that A20 expression is essential to prevent chronic inflammation and autoimmune pathology. In addition, polymorphisms within the A20 genomic locus have been associated with multiple inflammatory and autoimmune disorders, including SLE (systemic lupus erythaematosis), RA (rheumatoid arthritis), Crohn's disease and psoriasis. A20 has also been implicated as a tumour suppressor in several subsets of B-cell lymphomas. The present review outlines recent findings that illustrate the effect of A20 defects in disease pathogenesis and summarizes the identified A20 polymorphisms associated with different immunopathologies

Genetic Factors of Autoimmune Thyroid Diseases in Japanese

Autoimmune thyroid diseases (AITDs), including Graves' disease (GD) and Hashimoto's thyroiditis (HT), are caused by immune response to self-thyroid antigens and affect approximately 2–5% of the general population. Genetic susceptibility in combination with external factors, such as smoking, viral/bacterial infection, and chemicals, is believed to initiate the autoimmune response against thyroid antigens. Abundant epidemiological data, including family and twin studies, point to a strong genetic influence on the development of AITDs. Various techniques have been employed to identify genes contributing to the etiology of AITDs, including candidate gene analysis and whole genome screening. These studies have enabled the identification of several loci (genetic regions) that are linked to AITDs, and, in some of these loci, putative AITD susceptibility genes have been identified. Some of these genes/loci are unique to GD and HT and some are common to both diseases, indicating that there is a shared genetic susceptibility to GD and HT. Known AITD-susceptibility genes are classified into three groups: HLA genes, non-HLA immune-regulatory genes (e.g., CTLA-4, PTPN22, and CD40), and thyroid-specific genes (e.g., TSHR and Tg). In this paper, we will summarize the latest findings on AITD susceptibility genes in Japanese

Genetic Variation in an Individual Human Exome

There is much interest in characterizing the variation in a human individual, because this may elucidate what contributes significantly to a person's phenotype, thereby enabling personalized genomics. We focus here on the variants in a person's ‘exome,’ which is the set of exons in a genome, because the exome is believed to harbor much of the functional variation. We provide an analysis of the ∼12,500 variants that affect the protein coding portion of an individual's genome. We identified ∼10,400 nonsynonymous single nucleotide polymorphisms (nsSNPs) in this individual, of which ∼15–20% are rare in the human population. We predict ∼1,500 nsSNPs affect protein function and these tend be heterozygous, rare, or novel. Of the ∼700 coding indels, approximately half tend to have lengths that are a multiple of three, which causes insertions/deletions of amino acids in the corresponding protein, rather than introducing frameshifts. Coding indels also occur frequently at the termini of genes, so even if an indel causes a frameshift, an alternative start or stop site in the gene can still be used to make a functional protein. In summary, we reduced the set of ∼12,500 nonsilent coding variants by ∼8-fold to a set of variants that are most likely to have major effects on their proteins' functions. This is our first glimpse of an individual's exome and a snapshot of the current state of personalized genomics. The majority of coding variants in this individual are common and appear to be functionally neutral. Our results also indicate that some variants can be used to improve the current NCBI human reference genome. As more genomes are sequenced, many rare variants and non-SNP variants will be discovered. We present an approach to analyze the coding variation in humans by proposing multiple bioinformatic methods to hone in on possible functional variation

Allelic spectrum of the natural variation in CRP

With the recent completion of the International HapMap Project, many tools are in hand for genetic association studies seeking to test the common variant/common disease hypothesis. In contrast, very few tools and resources are in place for genotype–phenotype studies hypothesizing that rare variation has a large impact on the phenotype of interest. To create these tools for rare variant/common disease studies, much interest is being generated towards investing in re-sequencing either large sample sizes of random chromosomes or smaller sample sizes of patients with extreme phenotypes. As a case study for rare variant discovery in random chromosomes, we have re-sequenced ~1,000 chromosomes representing diverse populations for the gene C-reactive protein (CRP). CRP is an important gene in the fields of cardiovascular and inflammation genetics, and its size (~2 kb) makes it particularly amenable medical or deep re-sequencing. With these data, we explore several issues related to the present-day candidate gene association study including the benefits of complete SNP discovery, the effects of tagSNP selection across diverse populations, and completeness of dbSNP for CRP. Also, we show that while deep re-sequencing uncovers potentially medically relevant coding SNPs, these SNPs are fleetingly rare when genotyped in a population-based survey of 7,000 Americans (NHANES III). Collectively, these data suggest that several different types re-sequencing and genotyping approaches may be required to fully understand the complete spectrum of alleles that impact human phenotypes. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary material is available for this article at http://dx.doi.org/10.1007/s00439-006-0160-y and is accessible for authorized users

Polymorphisms

Polymorphism or variation in DNA sequence can affect individual phenotypes such as color of skin or eyes, susceptible to diseases, and respond to drug, vaccine, chemical, and pathogen. It occurs more often than mutations (frequency ≥ 1%). The common polymorphism is single nucleotide polymorphism (SNP) which is a single base change in a DNA sequence that occurs most commonly in the human genome. SNPs have been used as molecular markers in a wide range of studies. Genome-wide association studies (GWAS) searches for SNPs that occur more frequently in person with a particular disease than in person without the disease and pinpoint genes or regions that may contribute to a risk of disease. This topic describes about polymorphisms, SNPs, GWAS, linkage disequilibrium (LD), minor allele frequency, haplotype, method for SNP genotyping, and application of SNPs and genome-wide association study in human diseases and drug development

Evaluation of association tests for rare variants using simulated data sets in the Genetic Analysis Workshop 17 data

We evaluate four association tests for rare variants—the combined multivariate and collapsing (CMC) method, two weighted-sum methods, and a variable threshold method—by applying them to the simulated data sets of unrelated individuals in the Genetic Analysis Workshop 17 (GAW17) data. The family-wise error rate (FWER) and average power are used as criteria for evaluation. Our results show that when all nonsynonymous SNPs (rare variants and common variants) in a gene are jointly analyzed, the CMC method fails to control the FWER; when only rare variants (single-nucleotide polymorphisms with minor allele frequency less than 0.05) are analyzed, all four methods can control FWER well. All four methods have comparable power, which is low for the analysis of the GAW17 data sets. Three of the methods (not including the CMC method) involve estimation of p-values using permutation procedures that either can be computationally intensive or generate inflated FWERs. We adapt a fast permutation procedure into these three methods. The results show that using the fast permutation procedure can produce FWERs and average powers close to the values obtained from the standard permutation procedure on the GAW17 data sets. The standard permutation procedure is computationally intensive

Replication Study and Meta-Analysis in European Samples Supports Association of the 3p21.1 Locus with Bipolar Disorder

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