A genome wide association study of mathematical ability reveals an association at chromosome 3q29, a locus associated with autism and learning difficulties: a preliminary study

Mathematical ability is heritable, but few studies have directly investigated its molecular genetic basis. Here we aimed to identify specific genetic contributions to variation in mathematical ability. We carried out a genome wide association scan using pooled DNA in two groups of U.K. samples, based on end of secondary/high school national academic exam achievement: high (n = 419) versus low (n = 183) mathematical ability while controlling for their verbal ability. Significant differences in allele frequencies between these groups were searched for in 906,600 SNPs using the Affymetrix GeneChip Human Mapping version 6.0 array. After meeting a threshold of p<1.5×10-5, 12 SNPs from the pooled association analysis were individually genotyped in 542 of the participants and analyzed to validate the initial associations (lowest p-value 1.14 ×10-6). In this analysis, one of the SNPs (rs789859) showed significant association after Bonferroni correction, and four (rs10873824, rs4144887, rs12130910 rs2809115) were nominally significant (lowest p-value 3.278 × 10-4). Three of the SNPs of interest are located within, or near to, known genes (FAM43A, SFT2D1, C14orf64). The SNP that showed the strongest association, rs789859, is located in a region on chromosome 3q29 that has been previously linked to learning difficulties and autism. rs789859 lies 1.3 kbp downstream of LSG1, and 700 bp upstream of FAM43A, mapping within the potential promoter/regulatory region of the latter. To our knowledge, this is only the second study to investigate the association of genetic variants with mathematical ability, and it highlights a number of interesting markers for future study.

A pooled genome-wide association study of Asperger Syndrome

Asperger Syndrome (AS) is a neurodevelopmental condition characterized by impairments in social interaction and communication, alongside the presence of unusually repetitive, restricted interests and stereotyped behaviour. Individuals with AS have no delay in cognitive and language development. It is a subset of Autism Spectrum Conditions (ASC), which are highly heritable and has a population prevalence of approximately 1%. Few studies have investigated the genetic basis of AS. To address this gap in the literature, we performed a genome-wide pooled DNA association study to identify candidate loci in 612 individuals (294 cases and 318 controls) of Caucasian ancestry, using the Affymetrix GeneChip Human Mapping version 6.0 array. We identified 11 SNPs that had a p-value below 1x10-5. These SNPs were independently genotyped in the same sample. Three of the SNPs (rs1268055, rs7785891 and rs2782448) were nominally significant, though none remained significant after Bonferroni correction. Two of our top three SNPs (rs7785891 and rs2782448) lie in loci previously implicated in ASC. However, investigation of the three SNPs in the ASC genome-wide association dataset from the Psychiatric Genomics Consortium indicated that these three SNPs were not significantly associated with ASC. The effect sizes of the variants were modest, indicating that our study was not sufficiently powered to identify causal variants with precision.

Genome-wide association study of response to cognitive behavioural therapy in children with anxiety disorders

Background Anxiety disorders are common, and cognitive–behavioural therapy (CBT) is a first-line treatment. Candidate gene studies have suggested a genetic basis to treatment response, but findings have been inconsistent. Aims To perform the first genome-wide association study (GWAS) of psychological treatment response in children with anxiety disorders (n = 980). Method Presence and severity of anxiety was assessed using semi-structured interview at baseline, on completion of treatment (post-treatment), and 3 to 12 months after treatment completion (follow-up). DNA was genotyped using the Illumina Human Core Exome-12v1.0 array. Linear mixed models were used to test associations between genetic variants and response (change in symptom severity) immediately post-treatment and at 6-month follow-up. Results No variants passed a genome-wide significance threshold (P = 5×10−8) in either analysis. Four variants met criteria for suggestive significance (P<5×10−6) in association with response post-treatment, and three variants in the 6-month follow-up analysis. Conclusions This is the first genome-wide therapygenetic study. It suggests no common variants of very high effect underlie response to CBT. Future investigations should maximise power to detect single-variant and polygenic effects by using larger, more homogeneous cohorts.

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.

Analysis of genome-wide association study data using the protein knowledge base

Article 98

Candidate disease gene prediction using Gentrepid: application to a genome-wide association study on coronary artery disease

Current single-locus-based analyses and candidate disease gene prediction methodologies used in genome-wide association studies (GWAS) do not capitalize on the wealth of the underlying genetic data, nor functional data available from molecular biology. Here, we analyzed GWAS data from the Wellcome Trust Case Control Consortium (WTCCC) on coronary artery disease (CAD). Gentrepid uses a multiple-locus-based approach, drawing on protein pathway- or domain-based data to make predictions. Known disease genes may be used as additional information (seeded method) or predictions can be based entirely on GWAS single nucleotide polymorphisms (SNPs) (ab initio method). We looked in detail at specific predictions made by Gentrepid for CAD and compared these with known genetic data and the scientific literature. Gentrepid was able to extract known disease genes from the candidate search space and predict plausible novel disease genes from both known and novel WTCCC-implicated loci. The disease gene candidates are consistent with known biological information. The results demonstrate that this computational approach is feasible and a valuable discovery tool for geneticists.

Novel therapeutics for cononary artery disease from genome-wide association study data

Abstract
Background: Coronary artery disease (CAD), one of the leading causes of death globally, is influenced by both environmental and genetic risk factors. Gene-centric genome-wide association studies (GWAS) involving cases and controls have been remarkably successful in identifying genetic loci contributing to CAD. Modern in silico platforms, such as candidate gene prediction tools, permit a systematic analysis of GWAS data to identify candidate genes for complex diseases like CAD. Subsequent integration of drug-target data from drug databases with the predicted candidate genes can potentially identify novel therapeutics suitable for repositioning towards treatment of CAD.
Methods: Previously, we were able to predict 264 candidate genes and 104 potential therapeutic targets for CAD using Gentrepid (www.gentrepid.org), a candidate gene prediction platform with two bioinformatic modules to reanalyze Wellcome Trust Case-Control Consortium GWAS data. In an expanded study, using five bioinformatics modules on the same data, Gentrepid predicted 647 candidate genes and successfully replicated 55% of the candidate genes identified by the more powerful CARDIoGRAMplusC4D consortium meta-analysis. Hence, Gentrepid was capable of enhancing lower quality genotype-phenotype data, using an independent knowledgebase of existing biological data. Here, we used our methodology to integrate drug data from three drug databases: the Therapeutic Target Database, PharmGKB and Drug Bank, with the 647 candidate gene predictions from Gentrepid. We utilized known CAD targets, the scientific literature, existing drug data and the CARDIoGRAMplusC4D meta-analysis study as benchmarks to validate Gentrepid predictions for CAD.
Results: Our analysis identified a total of 184 predicted candidate genes as novel therapeutic targets for CAD, and 981 novel therapeutics feasible for repositioning in clinical trials towards treatment of CAD. The benchmarks based on known CAD targets and the scientific literature showed that our results were significant (p < 0.05).
Conclusions: We have demonstrated that available drugs may potentially be repositioned as novel therapeutics for the treatment of CAD. Drug repositioning can save valuable time and money spent on preclinical and phase I clinical studies.

Genetic association study between Interleukin 10 gene and dental implant loss

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach

Background: Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal's life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality.Results: The set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism.Conclusions: These results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle. © 2013 Mokry et al.; licensee BioMed Central Ltd.

Genome-wide association study for birth weight in Nellore cattle points to previously described orthologous genes affecting human and bovine height

Background: Birth weight (BW) is an economically important trait in beef cattle, and is associated with growth- and stature-related traits and calving difficulty. One region of the cattle genome, located on Bos primigenius taurus chromosome 14 (BTA14), has been previously shown to be associated with stature by multiple independent studies, and contains orthologous genes affecting human height. A genome-wide association study (GWAS) for BW in Brazilian Nellore cattle (Bos primigenius indicus) was performed using estimated breeding values (EBVs) of 654 progeny-tested bulls genotyped for over 777,000 single nucleotide polymorphisms (SNPs).Results: The most significant SNP (rs133012258, PGC = 1.34 × 10-9), located at BTA14:25376827, explained 4.62% of the variance in BW EBVs. The surrounding 1 Mb region presented high identity with human, pig and mouse autosomes 8, 4 and 4, respectively, and contains the orthologous height genes PLAG1, CHCHD7, MOS, RPS20, LYN, RDHE2 (SDR16C5) and PENK. The region also overlapped 28 quantitative trait loci (QTLs) previously reported in literature by linkage mapping studies in cattle, including QTLs for birth weight, mature height, carcass weight, stature, pre-weaning average daily gain, calving ease, and gestation length.Conclusions: This study presents the first GWAS applying a high-density SNP panel to identify putative chromosome regions affecting birth weight in Nellore cattle. These results suggest that the QTLs on BTA14 associated with body size in taurine cattle (Bos primigenius taurus) also affect birth weight and size in zebu cattle (Bos primigenius indicus). © 2013 Utsunomiya et al.; licensee BioMed Central Ltd.

Genome-wide association study for feedlot average daily gain in Nellore cattle (Bos indicus)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)