Disease-driven detection of differential inherited SNP modules from SNP network

Detection of the synergetic effects between variants, such as single-nucleotide polymorphisms (SNPs), is crucial for understanding the genetic characters of complex diseases. Here, we proposed a two-step approach to detect differentially inherited SNP modules (synergetic SNP units) from a SNP network. First, SNP-SNP interactions are identified based on prior biological knowledge, such as their adjacency on the chromosome or degree of relatedness between the functional relationships of their genes. These interactions form SNP networks. Second, disease-risk SNP modules (or sub-networks) are prioritised by their differentially inherited properties in IBD (Identity by Descent) profiles of affected and unaffected sibpairs. The search process is driven by the disease information and follows the structure of a SNP network. Simulation studies have indicated that this approach achieves high accuracy and a low false-positive rate in the identification of known disease-susceptible SNPs. Applying this method to an alcoholism dataset, we found that flexible patterns of susceptible SNP combinations do play a role in complex diseases, and some known genes were detected through these risk SNP modules. One example is GRM7, a known alcoholism gene successfully detected by a SNP module comprised of two SNPs, but neither of the two SNPs was significantly associated with the disease in single-locus analysis. These identified genes are also enriched in some pathways associated with alcoholism, including the calcium signalling pathway, axon guidance and neuroactive ligand-receptor interaction. The integration of network biology and genetic analysis provides putative functional bridges between genetic variants and candidate genes or pathways, thereby providing new insight into the aetiology of complex diseases.     

Selecting SNPs for association studies based on population frequencies: a novel interactive tool and its application to polygenic diseases

Common complex polygenic diseases as autoimmune diseases have not been completely understood on a molecular level. While many genes are known to be involved in the pathways responsible for the phenotype, explicit causes for the susceptibility of the disease remain to be elucidated. The susceptibility to disease is thought to be the result of genetic epistatic interactions between common polymorphic genes. This polymorphism is mostly caused by single nucleotide polymorphisms (SNPs). Human subpopulations are known to differ in the susceptibility to the diseases and generally in the distribution of single nucleotide polymorphisms. The here presented approach retrieves SNPs with the most divergent frequencies for selected human subpopulations to help defining properties for the experimental verification of SNPs within defined regions. A web-accessible program implementing this approach was evaluated for multiple sclerosis (MS), a common human polygenic disease. A link to a summary of data from "The SNP Consortium" (TSC) with sex-dependencies of SNPs is available. Associations of SNPs to genes, genetic markers and chromosomal loci are retrieved from the Ensembl project. This tool is recommended to be used in conjunction with microarray analyses or marker association studies that link genes or chromosomal loci to particular diseases.     

Regulatory SNPs in complex diseases: their identification and functional validation

Finding the genetic causes for complex diseases is a challenge. Expression studies have shown that the level of expression of many genes is altered in disease compared with normal conditions, but what lies behind these changes? Linkage studies provide hints as to where in the genome the genetic triggers--the mutations--might be located. Fine-mapping and association studies can give yet more information about which genes, and which changes in the genes, are involved in the disease. Recent examples show that single-nucleotide polymorphisms (SNPs), which are variations at the single-nucleotide level within an individual's DNA, in the regulatory regions of some genes constitute susceptibility factors in many complex diseases. This article discusses the nature of regulatory SNPs (rSNPs) and techniques for their functional validation, and looks towards what rSNPs can tell us about complex diseases.     

Sequence diversity in 36 candidate genes for cardiovascular disorders.

Two strategies involving whole-genome association studies have been proposed for the identification of genes involved in complex diseases. The first one seeks to characterize all common variants of human genes and to test their association with disease. The second one seeks to develop dense maps of single-nucleotide polymorphisms (SNPs) and to detect susceptibility genes through linkage disequilibrium. We performed a molecular screening of the coding and/or flanking regions of 36 candidate genes for cardiovascular diseases. All polymorphisms identified by this screening were further genotyped in 750 subjects of European descent. In the whole set of genes, the lengths explored spanned 53.8 kb in the 5' regions, 68.4 kb in exonic regions, and 13 kb in the 3' regions. The strength of linkage disequilibrium within candidate regions suggests that genomewide maps of SNPs might be efficient ways to identify new disease-susceptibility genes, provided that the maps are sufficiently dense. However, the relatively large number of polymorphisms within coding and regulatory regions of candidate genes raises the possibility that several of them might be functional and that the pattern of genotype-phenotype association might be more complex than initially envisaged, as actually has been observed in some well-characterized genes. These results argue in favor of both genomewide association studies and detailed studies of the overall sequence variation of candidate genes, as complementary approaches.     

Genotype patterns and characteristics of PRNP in the Korean population

Creutzfeldt-Jakob disease (CJD), included in the human transmissible spongiform encephalopathies (TSE), is widely known to be caused by an abnormal accumulation of misfolding prion protein in the brain. Human prion protein gene (PRNP) is mapped in chromosome 20p13 and many single nucleotide polymorphisms (SNPs) in PRNP have been discovered. However, the functionality of SNPs in PRNP is yet unclear, though several SNPs have been known as important mutation related with susceptibility human prion diseases. Our aim is to identify specific genotype patterns and characteristics in the PRNP genomic region and to understand susceptibility among Korean discriminated prion disease patients, suspected CJD patients and the KARE data group. Here, we have researched genotypes and SNPs allele frequencies in PRNP in discriminated prion disease patients group (n = 22), suspected prion diseases patients group (n = 163) and the Korea Association REsource (KARE) data group (n = 296) in Korea. The sequencing regions were promoter region, exon1 and exon2 with their junction parts among 481 samples. A total of 25 SNPs were shown in this study. Nucleotide frequencies of all SNPs are exceedingly tended to bias toward dominant homozygote types except in rs2756271. Genotype frequencies at codon 129 and 219 coding region were similar with previous studies in Korea and Japan. Pathogenic mutations such as 102P/L, 200E/K and 203V/I were observed in discriminated CJD patients group, and 180V/I and 232M/R were shown in suspected prion disease patients group and the KARE data group. A total of 10 SNPs were newly identified, six in the promoter region, one in exon 2 and three in the 3′ UTR. The strong and unique linkage disequilibrium (D' = 0.94, r² = 0.89) was observed between rs57633656 and rs1800014 which is located in codon 219 coding region. We expect that these data can be provided to determine specific susceptibility and a protective factor of prion diseases not only in Koreans but also in East Asians.     

Current strategies in the search for low penetrance genes in cancer

The genetic etiology of most cancers remains largely unclear and it has been hypothesised that common genetic variants with modest effects on disease susceptibility cause the bulk of this unexplained risk. Case-control association studies are considered the most effective strategy to identify these low-penetrance genes. While traditionally, such studies have focused on putative functional single nucleotide polymorphisms (SNPs) in candidate genes, a more comprehensive approach can now be taken, as a result of a number of recent developments: the mapping of the human genome, including the identification of almost ten million SNPs; and the development of high-throughput genotyping technologies that enable hundreds of thousands of SNPs to be genotyped in a single reaction, in multiple subjects and at an affordable cost. All common genomic variation can be captured by genotyping SNPs in gene-, pathway- or genome-wide-based strategies and these are now being applied to many diseases, including cancer. We present an outline of each of these approaches, including recent published examples, and discuss a number of challenges that remain to be addressed.     

Characterization of a 320-kb region containing the HEXA gene on bovine chromosome 10 and analysis of its association with BSE susceptibility

Bovine spongiform encephalopathy (BSE) belongs to a group of neurodegenerative diseases known as transmissible prion diseases. Recently, variants in the promoter region of the prion protein ( PRNP ) gene have been shown to have a considerable effect on the susceptibility to BSE. However, a previous genome scan revealed other putative BSE-susceptibility loci. Here, we analysed such a region on BTA10, which contains the functional candidate gene HEXA . Three hundred and twenty kilobases that, besides HEXA , also contain ARIH1 , BRUNOL6 and PARP6 were characterized and screened for polymorphisms. Genotyping of 38 SNPs in Holstein–Friesian animals from the UK (350 diseased and 270 controls) revealed two intronic SNPs that were associated with BSE incidence, with experiment-wise P -values of 3.5 × 10⁻³ and 7.7 × 10⁻³ respectively. Both SNPs were in strong linkage disequilibrium and the rare alleles had a protective effect. These alleles were contained in a haplotype dubbed 'UK-protective' that was significantly overrepresented in the controls with a permuted P -value of 2 × 10⁻³. An association study in German Holstein animals (73 diseased and 627 controls) revealed an opposite effect of the 'UK-protective' haplotype in this population, i.e. it was overrepresented in the diseased animals, although not significant after correction for multiple testing. These findings indicate a causal variant for BSE susceptibility on BTA10 in linkage disequilibrium with the markers studied. Candidate gene analyses of the surrounding region and additional association studies will help to clarify the origin of the protective effects and to identify causal variants for BSE susceptibility on BTA10.     

A catalog of polymorphisms falling in microRNA-binding regions of cancer genes

Recent evidence indicates that small, nonprotein-coding RNA molecules, called microRNAs (miRNAs), control cell growth, differentiation, and apoptosis, and are also involved in tumorigenesis. miRNAs can bind to the 3' untranslated regions (3'UTRs) of messenger RNAs and interfere with their translation. We hypothesized that common polymorphisms within their genes or within their targets could have an important impact for an individual's risk to develop complex diseases. In this study, we selected the 3'UTRs of 129 genes involved in pathways commonly acknowledged as important for cancer, and we identified putative miRNA-binding sites by means of specialized algorithms (PicTar, DIANA-MicroT, miRBase, miRanda, TargetScan, and MicroInspector). Then we investigated 79 single-nucleotide polymorphisms (SNPs) within the putative binding sites for their ability to affect or impair the binding with the miRNA by assessing the DeltaDeltaG, the variation of DeltaG (Gibbs free energy), through comparing the wild-type and their corresponding variant alleles. Moreover, we reported seven identified SNPs in seven pre-miRNA hairpin regions and one SNP in the mature sequence of miR-608. Considering the validation status of the SNPs and their frequencies, we found at least 23 candidate polymorphisms of biological relevance that we propose for further investigation in case-control association studies.