Genome-wide association studies and Crohn's disease

The development of genome-wide association scanning (GWAS) has revolutionized the search for genetic loci associated with complex diseases. Crohn's disease (CD), together with ulcerative colitis, has been a principal beneficiary of this technology with a recent meta-analysis from the International IBD Genetics Consortium increasing the number of confirmed CD susceptibility loci to 71. When one considers that prior to the development of GWAS only three susceptibility loci had been identified, the degree of progress becomes obvious. In this article we will summarize the principal discoveries that have been made in CD genetics and explain how these have contributed to our improved understanding of disease pathogenesis.     

Genome-wide association studies and type 2 diabetes

In recent years, the search for genetic determinants of type 2 diabetes (T2D) has changed dramatically. Although linkage and small-scale candidate gene studies were highly successful in the identification of genes, which, when mutated, caused monogenic forms of T2D, they were largely unsuccessful when applied to the more common forms of the disease. To date, these approaches have only identified two loci (PPARG, KCNJ11) robustly implicated in T2D susceptibility. The ability to perform large-scale association analysis, including genome-wide association studies (GWAS) in many thousands of samples from different populations, and subsequently, the shift to form large international collaborations to perform meta-analyses across many studies has taken the number of independent loci showing genome-wide significant associations with T2D to 44. This number includes six loci identified initially through the analysis of quantitative glycaemic phenotypes, illustrating the usefulness of this approach both to identify new disease genes and gain insight into the mechanisms leading to disease. Combined, these loci still only account for ～10% of the observed familial clustering in Europeans, leaving much of the variance unexplained. In this review, we will describe what GWAS have taught us about the genetic basis of T2D and discuss possible next steps to uncover the remaining heritability.     

Genome-wide association studies and susceptibility to infectious diseases

Progress in genomics and the associated technological, statistical and bioinformatics advances have facilitated the successful implementation of genome-wide association studies (GWAS) towards understanding the genetic basis of common diseases. Infectious diseases contribute significantly to the global burden of disease and there is robust epidemiological evidence that host genetic factors are important determinants of the outcome of interactions between host and pathogen. Indeed, infectious diseases have exerted profound selective pressure on human evolution. However, the application of GWAS to infectious diseases has been relatively limited compared with non-communicable diseases. Here we review GWAS findings for important infectious diseases, including malaria, tuberculosis and HIV. We highlight some of the pitfalls recognized more generally for GWAS, as well as issues specific to infection, including the role of the pathogen which also has a genome. We also discuss the challenges encountered when studying African populations which are genetically more ancient and more diverse that other populations and disproportionately bear the main global burden of serious infectious diseases.     

Genome-wide association studies: theoretical and practical concerns

To fully understand the allelic variation that underlies common diseases, complete genome sequencing for many individuals with and without disease is required. This is still not technically feasible. However, recently it has become possible to carry out partial surveys of the genome by genotyping large numbers of common SNPs in genome-wide association studies. Here, we outline the main factors - including models of the allelic architecture of common diseases, sample size, map density and sample-collection biases - that need to be taken into account in order to optimize the cost efficiency of identifying genuine disease-susceptibility loci.     

Genome-wide association studies for sperm traits in Assaf sheep breed

Sperm quality traits routinely collected by artificial insemination (AI) center for rams progeny test are related with the capacity to produce sperm doses for AI and, in more or less grade, with males' fertility. Low-quality ejaculates are unuseful to perform AI sperm doses, which suppose high economic loses for the AI center. Moreover, sperm quality traits have low heritability values which make traditional genetic selection little efficient to its improvement. In this work, a genome-wide association study (GWAS) was conducted by using sperm quality traits data and 50 K Affymetrix custom chip genotypes of 429 rams of Assaf breed from OVIGEN AI centre. Furthermore, 47 of these rams were also genotyped with the Illumina HD Ovine BeadChip, and therefore HD genotypes were imputed for all rams with phenotype data. Previous to the GWAS, a linear regression model was fitted including sperm traits as dependent variables; the flock of origin, date of sperm collection, and jump number as fixed effects; rams age at collection in months as covariate; and ram permanent effect as random. Pseudo-phenotypes obtained from this model were used as input for GWAS. Associations at the chromosome-wise level (FDR 10%) of 76 single-nucleotide polymorphisms (SNPs) in 4 chromosomes for ejaculate concentration (CON), 20 SNPs in 3 chromosomes for ejaculate volume (VOL), 32 SNPs in 1 chromosome for ejaculate number of spermatozoa (SPZ), and 23 SNPs for spermatozoa mass motility (MOT) in 17 chromosomes were found. Only SNPs associated with MOT overcame the genome-wide significance level. Some candidate genes for sperm traits variability were SLC9C1 (OAR1), TSN (OAR2), and FUT10 (OAR26) for MOT;. DOCK2, CPLANE1, SPEF2, and RAI14 (OAR16) for CON; SCAPER and PSMA4 (OAR18) for VOL; and PARM1 and LOC101110593 (OAR6) for SPZ. SNPs associated with sperm traits were not found to be correlated with milk production genetic variation; however, the high frequencies of some SNPs with negative effect over sperm traits found in animals at the top milk yield estimated breeding values (EBVs) ranking would allow to exert some selective presure to improve rams sperm performances. Effects and frequencies of some of the SNPs detected over sperm quality traits make these variants good candidates to be used in marker-assisted selection to improve sperm characteristics of Assaf rams and AI center efficiency to produce sperm doses.     

Genome-wide association studies in systemic lupus erythematosus: a perspective

Genome-wide association studies (GWAS) have been shown to be a powerful way of identifying novel susceptibility genes in systemic lupus erythematosus (SLE), as demonstrated by a series of publications in the past year. Lupus has been a late-comer to the GWAS community, being preceded by success stories for the GWAS approach in other autoimmune diseases, including type I diabetes, ankylosing spondylitis, rheumatoid arthritis, Crohn's disease and ulcerative colitis. The paper by Suarez-Gestal and colleagues seeks to exploit the wealth of data available from a total of four GWAS in SLE, three in European-American populations and one in a Swedish population. The authors describe replication of ten lupus susceptibility alleles in a Spanish SLE case-control study.     

Genome-wide association studies of the PR interval in African Americans

The PR interval on the electrocardiogram reflects atrial and atrioventricular nodal conduction time. The PR interval is heritable, provides important information about arrhythmia risk, and has been suggested to differ among human races. Genome-wide association (GWA) studies have identified common genetic determinants of the PR interval in individuals of European and Asian ancestry, but there is a general paucity of GWA studies in individuals of African ancestry. We performed GWA studies in African American individuals from four cohorts (n = 6,247) to identify genetic variants associated with PR interval duration. Genotyping was performed using the Affymetrix 6.0 microarray. Imputation was performed for 2.8 million single nucleotide polymorphisms (SNPs) using combined YRI and CEU HapMap phase II panels. We observed a strong signal (rs3922844) within the gene encoding the cardiac sodium channel (SCN5A) with genome-wide significant association (p<2.5×10⁻⁸) in two of the four cohorts and in the meta-analysis. The signal explained 2% of PR interval variability in African Americans (beta  = 5.1 msec per minor allele, 95% CI  = 4.1–6.1, p = 3×10⁻²³). This SNP was also associated with PR interval (beta = 2.4 msec per minor allele, 95% CI = 1.8–3.0, p = 3×10⁻¹⁶) in individuals of European ancestry (n = 14,042), but with a smaller effect size (p for heterogeneity <0.001) and variability explained (0.5%). Further meta-analysis of the four cohorts identified genome-wide significant associations with SNPs in SCN10A (rs6798015), MEIS1 (rs10865355), and TBX5 (rs7312625) that were highly correlated with SNPs identified in European and Asian GWA studies. African ancestry was associated with increased PR duration (13.3 msec, p = 0.009) in one but not the other three cohorts. Our findings demonstrate the relevance of common variants to African Americans at four loci previously associated with PR interval in European and Asian samples and identify an association signal at one of these loci that is more strongly associated with PR interval in African Americans than in Europeans.     

Genome-wide association studies for common diseases and complex traits

Genetic factors strongly affect susceptibility to common diseases and also influence disease-related quantitative traits. Identifying the relevant genes has been difficult, in part because each causal gene only makes a small contribution to overall heritability. Genetic association studies offer a potentially powerful approach for mapping causal genes with modest effects, but are limited because only a small number of genes can be studied at a time. Genome-wide association studies will soon become possible, and could open new frontiers in our understanding and treatment of disease. However, the execution and analysis of such studies will require great care.     

Genome-wide association studies in multiple sclerosis: lessons and future prospects

Multiple sclerosis (MS) is an inflammatory neurodegenerative disease with complex aetiology. A haplotype within the major histocompatibility region is the major risk factor for MS, but despite clear evidence for a genetic component additional risk variants were not identified until the recent advent of genome-wide association studies (GWAS). At present, 10 GWAS have been conducted in MS, and together with follow-up studies these have confirmed 16 loci with genome-wide significance. Many of these common risk variants are located at or near genes with central immunological functions and the majority are associated with other autoimmune diseases. However, evidence from pathway analyses on more modestly associated variants also supports the involvement of neurological genes. Although the mechanisms by which the associated variants exert their effects are still poorly understood, some have been shown to correlate with expression of nearby genes. Further studies are required to define the functionally relevant variants in the identified regions and to investigate their effects at the molecular and cellular level. Finally, many genetic risk variants for MS remain to be identified. In order to expose some of the loci with more modest effects, a GWAS in nearly 10,000 MS patients has recently been completed.     

Genome-wide association studies: a new window into immune-mediated diseases

Given the recent explosion of genetic discoveries, 2007 is becoming known to human geneticists as the year of genome-wide association studies. In fact, more genetic risk factors for common diseases were identified in this one year than had been collectively reported before 2007. In particular, 2007 witnessed the discovery of many genes that influence susceptibility to individual immune-mediated diseases, as well as other genes that are associated with susceptibility to more than one disease. Although much work remains to be done, in this Review we discuss what effect these studies are having on our understanding of disease pathogenesis and their potential impact on future immunology studies.     

Genome-wide association studies and systems biology: together at last

Following the widespread use of genome-wide association studies to elucidate the genetic architectures of complex phenotypes, there has been a push to augment existing observational studies with additional layers of molecular information. The resulting high-dimensional data have led the emergence of research in integrative systems biology. Here, we examine recent progress in characterizing biological networks as well as the corresponding conceptual and analytical challenges. Using examples from metabolomics, we contend that integrative systems biology should prompt a re-examination of conventional phenotypic measures where heterogeneous or correlated phenotypes can be fine-mapped. Although still in its infancy, it is apparent that the large-scale characterization of molecular systems will transform our understanding of phenotype, biology and pathogenesis.     

Genome-wide association studies on HIV susceptibility, pathogenesis and pharmacogenomics

ABSTRACT: Susceptibility to HIV-1 and the clinical course after infection show a substantial heterogeneity between individuals. Part of this variability can be attributed to host genetic variation. Initial candidate gene studies have revealed interesting host factors that influence HIV infection, replication and pathogenesis. Recently, genome-wide association studies (GWAS) were utilized for unbiased searches at a genome-wide level to discover novel genetic factors and pathways involved in HIV-1 infection. This review gives an overview of findings from the GWAS performed on HIV infection, within different cohorts, with variable patient and phenotype selection. Furthermore, novel techniques and strategies in research that might contribute to the complete understanding of virus-host interactions and its role on the pathogenesis of HIV infection are discussed.     

Genome-wide association studies uncover genes associated with litter traits in the pig

Litter traits are critical economic variables in the pig industry as they represent a production indicator that can serve to determine sow fertility. In this study, a genome-wide association study on litter traits, including total number born (TNB), number born alive (NBA), litter birth weight (LBW), average birth weight (ABW), and piglet uniformity (PU), was carried out on two pig breeds (Yorkshire and Landrace). A total of 3 637 pigs of both breeds were genotyped using the GeneSeek GGP Porcine 50K SNP BeadChip. A mixed linear model (MLM) and fixed and random model circulating probability unification (FarmCPU) were employed in the genome-wide association studies for litter traits using combined data from the two pig breeds and data from each breed separately. Additionally, the heritability of traits was estimated using three methods—pedigree-based best linear unbiased prediction (PBLUP), genomic best linear unbiased prediction (GBLUP), and single-step best linear unbiased prediction (ssGBLUP)—and was found to lie between 0.065 and 0.1289, 0.0478 and 0.0938, 0.0793 and 0.0935, 0.1862 and 0.2163, and 0.0327 and 0.0419 for TNB, NBA, LBW, ABW, and PU, respectively. We also compared the genomic prediction accuracies and unbiasedness for litter traits of the three BLUP models. Our results indicated that the ssGBLUP method provided higher predictive accuracies and more rational unbiasedness compared with the PBLUP and GBLUP methodologies. Furthermore, based on their possible roles, eight candidate genes (INHBA, LEPR, HDHD2, CTNND2, RNF216, HMX1, PAPPA2, and NTN1) were identified as being linked with litter traits. In the middle of the test, these genes were found to be connected with pig metabolism and ovulation rate. Our results provide the insights into the genetic architecture of litter traits in pigs, and the potential single nucleotide polymorphisms (SNPs) and candidate genes identified may benefit economic profits in pig-breeding industry and contribute to improve litter traits.     

Genome-wide association studies for multiple diseases of the German Shepherd Dog

The German Shepherd Dog (GSD) is a popular working and companion breed for which over 50 hereditary diseases have been documented. Herein, SNP profiles for 197 GSDs were generated using the Affymetrix v2 canine SNP array for a genome-wide association study to identify loci associated with four diseases: pituitary dwarfism, degenerative myelopathy (DM), congenital megaesophagus (ME), and pancreatic acinar atrophy (PAA). A locus on Chr 9 is strongly associated with pituitary dwarfism and is proximal to a plausible candidate gene, LHX3. Results for DM confirm a major locus encompassing SOD1, in which an associated point mutation was previously identified, but do not suggest modifier loci. Several SNPs on Chr 12 are associated with ME and a 4.7 Mb haplotype block is present in affected dogs. Analysis of additional ME cases for a SNP within the haplotype provides further support for this association. Results for PAA indicate more complex genetic underpinnings. Several regions on multiple chromosomes reach genome-wide significance. However, no major locus is apparent and only two associated haplotype blocks, on Chrs 7 and 12 are observed. These data suggest that PAA may be governed by multiple loci with small effects, or it may be a heterogeneous disorder.     

Genome-wide association studies in plants: the missing heritability is in the field

Genome-wide association studies (GWAS) have been even more successful in plants than in humans. Mapping approaches can be extended to dissect adaptive genetic variation from structured background variation in an ecological context.     

Genome-wide association studies provide new insights into type 2 diabetes aetiology

Human geneticists are currently in the middle of a race. Thanks to a new technology in the form of 'genome-wide chips', investigators can potentially find many novel disease genes in one large experiment. Type 2 diabetes has been hot out of the blocks with six recent publications that together provide convincing evidence for six new gene regions involved in the condition. Together with candidate approaches, these studies have identified 11 confirmed genomic regions that alter the risk of type 2 diabetes in the European population. One of these regions, the fat mass and obesity associated gene (FTO), represents by far the best example of an association between common variation and fat mass in the general population.