Evidence of genetic association between TNFRSF1A encoding the p55 tumour necrosis factor receptor, and ankylosing spondylitis in UK Caucasians

Objectives: To replicate the possible genetic association between ankylosing spondylitis (AS) and TNFRSF1A. Methods: TNFRSF1A was re-sequenced in 48 individuals with AS to identify novel polymorphisms. Nine single nucleotide polymorphisms (SNPs) in TNFRSF1A and 5 SNPs in the neighbouring gene SCNN1A were genotyped in 1604 UK Caucasian individuals with AS and 1019 matched controls. An extended study was implemented using additional genotype data on 8 of these SNPs from 1400 historical controls from the 1958 British Birth Cohort. A meta-analysis of previously published results was also undertaken. Results: One novel variant in intron 6 was identified but no new coding variants. No definite associations were seen in the initial study but in the extended study there were weak associations with rs4149576 (p=0.04) and rs4149577 (p=0.007). In the metaanalysis consistent, somewhat stronger associations were seen with rs4149577 (p=0.002) and rs4149578 (p=0.006). Conclusions: These studies confirm the weak genetic associations between AS and TNFRSF1A. In view of the previously reported associations of TNFRSF1A with AS, in Caucasians and Chinese, and the biological plausibility of this candidate gene, replication of this finding in well powered studies is clearly indicated.

permGPU: Using graphics processing units in RNA microarray association studies.

BACKGROUND: Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. RESULTS: We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. CONCLUSIONS: permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.

Genetic association of CD247 (CD3ζ) with SLE in a large-scale multiethnic study

A classic T-cell phenotype in systemic lupus erythematosus (SLE) is the downregulation and replacement of the CD3ζ chain that alters T-cell receptor signaling. However, genetic associations with SLE in the human CD247 locus that encodes CD3ζ are not well established and require replication in independent cohorts. Our aim was therefore to examine, localize and validate CD247-SLE association in a large multiethnic population. We typed 44 contiguous CD247 single-nucleotide polymorphisms (SNPs) in 8922 SLE patients and 8077 controls from four ethnically distinct populations. The strongest associations were found in the Asian population (11 SNPs in intron 1, 4.99 × 10(-4) < P < 4.15 × 10(-2)), where we further identified a five-marker haplotype (rs12141731-rs2949655-rs16859085-rs12144621-rs858554; G-G-A-G-A; P(hap) = 2.12 × 10(-5)) that exceeded the most associated single SNP rs858554 (minor allele frequency in controls = 13%; P = 4.99 × 10(-4), odds ratio = 1.32) in significance. Imputation and subsequent association analysis showed evidence of association (P < 0.05) at 27 additional SNPs within intron 1. Cross-ethnic meta-analysis, assuming an additive genetic model adjusted for population proportions, showed five SNPs with significant P-values (1.40 × 10(-3) < P< 3.97 × 10(-2)), with one (rs704848) remaining significant after Bonferroni correction (P(meta) = 2.66 × 10(-2)). Our study independently confirms and extends the association of SLE with CD247, which is shared by various autoimmune disorders and supports a common T-cell-mediated mechanism.

Genetic clustering on the hippocampal surface for genome-wide association studies

Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.

Genetic association and gene expression studies suggest that genetic variants in the SYNE1 and TNF genes are related to menstrual migraine

BACKGROUND: Menstrual migraine (MM) encompasses pure menstrual migraine (PMM) and menstrually-related migraine (MRM). This study was aimed at investigating genetic variants that are potentially related to MM, specifically undertaking genotyping and mRNA expression analysis of the ESR1, PGR, SYNE1 and TNF genes in MM cases and non-migraine controls. METHODS: A total of 37 variants distributed across 14 genes were genotyped in 437 DNA samples (282 cases and 155 controls). In addition levels of gene expression were determined in 74 cDNA samples (41 cases and 33 controls). Association and correlation analysis were performed using Plink and RStudio. RESULTS: SNPs rs3093664 and rs9371601 in TNF and SYNE1 genes respectively, were significantly associated with migraine in the MM population (p = 0.008; p = 0.009 respectively). Analysis of qPCR results found no significant difference in levels of gene expression between cases and controls. However, we found a significant correlation between the expression of ESR1 and SYNE1, ESR1 and PGR and TNF and SYNE1 in samples taken during the follicular phase of the menstrual cycle. CONCLUSIONS: Our results show that SNPs rs9371601 and rs3093664 in the SYNE1 and TNF genes respectively, are associated with MM. The present study also provides strong evidence to support the correlation of ESR1, PGR, SYNE1 and TNF gene expression in MM.

Genome-wide association and genetic functional studies identify autism susceptibility candidate 2 gene (AUTS2) in the regulation of alcohol consumption

Alcohol consumption is a moderately heritable trait, but the genetic basis in humans is largely unknown, despite its clinical and societal importance. We report a genome-wide association study meta-analysis of approximately 2.5 million directly genotyped or imputed SNPs with alcohol consumption (gram per day per kilogram body weight) among 12 population-based samples of European ancestry, comprising 26,316 individuals, with replication genotyping in an additional 21,185 individuals. SNP rs6943555 in autism susceptibility candidate 2 gene (AUTS2) was associated with alcohol consumption at genome-wide significance (P = 4 x 10(-8) to P = 4 x 10(-9)). We found a genotype-specific expression of AUTS2 in 96 human prefrontal cortex samples (P = 0.026) and significant (P < 0.017) differences in expression of AUTS2 in whole-brain extracts of mice selected for differences in voluntary alcohol consumption. Down-regulation of an AUTS2 homolog caused reduced alcohol sensitivity in Drosophila (P < 0.001). Our finding of a regulator of alcohol consumption adds knowledge to our understanding of genetic mechanisms influencing alcohol drinking behavior.

Genetic variants influencing human aging from late-onset Alzheimer's disease (LOAD) genome-wide association studies (GWAS)

Genetics plays a crucial role in human aging with up to 30% of those living to the mid-80s being determined by genetic variation. Survival to older ages likely entails an even greater genetic contribution. There is increasing evidence that genes implicated in age-related diseases, such as cancer and neuronal disease, play a role in affecting human life span. We have selected the 10 most promising late-onset Alzheimer's disease (LOAD) susceptibility genes identified through several recent large genome-wide association studies (GWAS). These 10 LOAD genes (APOE, CLU, PICALM, CR1, BIN1, ABCA7, MS4A6A, CD33, CD2AP, and EPHA1) have been tested for association with human aging in our dataset (1385 samples with documented age at death [AAD], age range: 58-108 years; mean age at death: 80.2) using the most significant single nucleotide polymorphisms (SNPs) found in the previous studies. Apart from the APOE locus (rs2075650) which showed compelling evidence of association with risk on human life span (p = 5.27 × 10(-4)), none of the other LOAD gene loci demonstrated significant evidence of association. In addition to examining the known LOAD genes, we carried out analyses using age at death as a quantitative trait. No genome-wide significant SNPs were discovered. Increasing sample size and statistical power will be imperative to detect genuine aging-associated variants in the future. In this report, we also discuss issues relating to the analysis of genome-wide association studies data from different centers and the bioinformatic approach required to distinguish spurious genome-wide significant signals from real SNP associations.

Genome-wide Association Studies Identify Genetic Loci Associated with Albuminuria in Diabetes

Elevated concentrations of albumin in the urine, albuminuria, are a hallmark of diabetic kidney disease and associate with increased risk for end-stage renal disease and cardiovascular events. To gain insight into the pathophysiological mechanisms underlying albuminuria, we conducted meta-analyses of genome-wide association studies and independent replication in up to 5,825 individuals of European ancestry with diabetes mellitus and up to 46,061 without diabetes, followed by functional studies. Known associations of variants in CUBN, encoding cubilin, with the urinary albumin-to-creatinine ratio (UACR) were confirmed in the overall sample (p=2.4*10(-10)). Gene-by-diabetes interactions were detected and confirmed for variants in HS6ST1 and near RAB38/CTSC. SNPs at these loci demonstrated a genetic effect on UACR in individuals with but not without diabetes. The change in average UACR per minor allele was 21% for HS6ST1 and 13% for RAB38/CTSC (p=6.3*10(-7) and 5.8*10(-7), respectively). Experiments using streptozotocin-treated diabetic Rab38 knockout and control rats showed higher urinary albumin concentrations and reduced amounts of megalin and cubilin at the proximal tubule cell surface in Rab38 knockout vs. control rats. Relative expression of RAB38 was higher in tubuli of patients with diabetic kidney disease compared to controls. The loci identified here confirm known and highlight novel pathways influencing albuminuria.

Nonparametric Evaluation of Quantitative Traits in Population-Based Association Studies when the Genetic Model is Unknown

Statistical association between a single nucleotide polymorphism (SNP) genotype and a quantitative trait in genome-wide association studies is usually assessed using a linear regression model, or, in the case of non-normally distributed trait values, using the Kruskal-Wallis test. While linear regression models assume an additive mode of inheritance via equi-distant genotype scores, Kruskal-Wallis test merely tests global differences in trait values associated with the three genotype groups. Both approaches thus exhibit suboptimal power when the underlying inheritance mode is dominant or recessive. Furthermore, these tests do not perform well in the common situations when only a few trait values are available in a rare genotype category (disbalance), or when the values associated with the three genotype categories exhibit unequal variance (variance heterogeneity). We propose a maximum test based on Marcus-type multiple contrast test for relative effect sizes. This test allows model-specific testing of either dominant, additive or recessive mode of inheritance, and it is robust against variance heterogeneity. We show how to obtain mode-specific simultaneous confidence intervals for the relative effect sizes to aid in interpreting the biological relevance of the results. Further, we discuss the use of a related all-pairwise comparisons contrast test with range preserving confidence intervals as an alternative to Kruskal-Wallis heterogeneity test. We applied the proposed maximum test to the Bogalusa Heart Study dataset, and gained a remarkable increase in the power to detect association, particularly for rare genotypes. Our simulation study also demonstrated that the proposed non-parametric tests control family-wise error rate in the presence of non-normality and variance heterogeneity contrary to the standard parametric approaches. We provide a publicly available R library nparcomp that can be used to estimate simultaneous confidence intervals or compatible multiplicity-adjusted p-values associated with the proposed maximum test.

A meta-analysis of genome-wide association studies to identify prostate cancer susceptibility loci associated with aggressive and non-aggressive disease

Genome-wide association studies (GWAS) have identified multiple common genetic variants associated with an increased risk of prostate cancer (PrCa), but these explain less than one-third of the heritability. To identify further susceptibility alleles, we conducted a meta-analysis of four GWAS including 5953 cases of aggressive PrCa and 11 463 controls (men without PrCa). We computed association tests for approximately 2.6 million SNPs and followed up the most significant SNPs by genotyping 49 121 samples in 29 studies through the international PRACTICAL and BPC3 consortia. We not only confirmed the association of a PrCa susceptibility locus, rs11672691 on chromosome 19, but also showed an association with aggressive PrCa [odds ratio = 1.12 (95% confidence interval 1.03-1.21), P = 1.4 × 10(-8)]. This report describes a genetic variant which is associated with aggressive PrCa, which is a type of PrCa associated with a poorer prognosis.

Genetic association of the KLK4 locus with risk of prostate cancer

The Kallikrein-related peptidase, KLK4, has been shown to be significantly overexpressed in prostate tumours in numerous studies and is suggested to be a potential biomarker for prostate cancer. KLK4 may also play a role in prostate cancer progression through its involvement in epithelial-mesenchymal transition, a more aggressive phenotype, and metastases to bone. It is well known that genetic variation has the potential to affect gene expression and/or various protein characteristics and hence we sought to investigate the possible role of single nucleotide polymorphisms (SNPs) in the KLK4 gene in prostate cancer. Assessment of 61 SNPs in the KLK4 locus (±10 kb) in approximately 1300 prostate cancer cases and 1300 male controls for associations with prostate cancer risk and/or prostate tumour aggressiveness (Gleason score <7 versus ≥7) revealed 7 SNPs to be associated with a decreased risk of prostate cancer at the Ptrend<0.05 significance level. Three of these SNPs, rs268923, rs56112930 and the HapMap tagSNP rs7248321, are located several kb upstream of KLK4; rs1654551 encodes a non-synonymous serine to alanine substitution at position 22 of the long isoform of the KLK4 protein, and the remaining 3 risk-associated SNPs, rs1701927, rs1090649 and rs806019, are located downstream of KLK4 and are in high linkage disequilibrium with each other (r2≥0.98). Our findings provide suggestive evidence of a role for genetic variation in the KLK4 locus in prostate cancer predisposition.