Association between prostinogen (KLK15) genetic variants and prostate cancer risk and aggressiveness in Australia and a meta-analysis of GWAS data

Background: Kallikrein 15 (KLK15)/Prostinogen is a plausible candidate for prostate cancer susceptibility. Elevated KLK15 expression has been reported in prostate cancer and it has been described as an unfavorable prognostic marker for the disease. Objectives: We performed a comprehensive analysis of association of variants in the KLK15 gene with prostate cancer risk and aggressiveness by genotyping tagSNPs, as well as putative functional SNPs identified by extensive bioinformatics analysis. Methods and Data Sources: Twelve out of 22 SNPs, selected on the basis of linkage disequilibrium pattern, were analyzed in an Australian sample of 1,011 histologically verified prostate cancer cases and 1,405 ethnically matched controls. Replication was sought from two existing genome wide association studies (GWAS): the Cancer Genetic Markers of Susceptibility (CGEMS) project and a UK GWAS study. Results: Two KLK15 SNPs, rs2659053 and rs3745522, showed evidence of association (p, 0.05) but were not present on the GWAS platforms. KLK15 SNP rs2659056 was found to be associated with prostate cancer aggressiveness and showed evidence of association in a replication cohort of 5,051 patients from the UK, Australia, and the CGEMS dataset of US samples. A highly significant association with Gleason score was observed when the data was combined from these three studies with an Odds Ratio (OR) of 0.85 (95% CI = 0.77-0.93; p = 2.7610 24). The rs2659056 SNP is predicted to alter binding of the RORalpha transcription factor, which has a role in the control of cell growth and differentiation and has been suggested to control the metastatic behavior of prostate cancer cells. Conclusions: Our findings suggest a role for KLK15 genetic variation in the etiology of prostate cancer among men of European ancestry, although further studies in very large sample sets are necessary to confirm effect sizes.

Five years of GWAS discovery

The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section. © 2012 The American Society of Human Genetics.

GWAS of 126,559 individuals identifies genetic variants associated with educational attainment

A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) approximately 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for approximately 2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

GWAS of butyrylcholinesterase activity identifies four novel loci, independent effects within BCHE and secondary associations with metabolic risk factors

Serum butyrylcholinesterase (BCHE) activity is associated with obesity, blood pressure and biomarkers of cardiovascular and diabetes risk. We have conducted a genome-wide association scan to discover genetic variants affecting BCHE activity, and to clarify whether the associations between BCHE activity and cardiometabolic risk factors are caused by variation in BCHE or whether BCHE variation is secondary to the metabolic abnormalities. We measured serum BCHE in adolescents and adults from three cohorts of Australian twin and family studies. The genotypes from approximately 2.4 million single-nucleotide polymorphisms (SNPs) were available in 8791 participants with BCHE measurements. We detected significant associations with BCHE activity at three independent groups of SNPs at the BCHE locus (P = 5.8 x 10(-262), 7.8 x 10(-47), 2.9 x 10(-12)) and at four other loci: RNPEP (P = 9.4 x 10(-16)), RAPH1-ABI2 (P = 4.1 x 10(-18)), UGT1A1 (P = 4.0 x 10(-8)) and an intergenic region on chromosome 8 (P = 1.4 x 10(-8)). These loci affecting BCHE activity were not associated with metabolic risk factors. On the other hand, SNPs in genes previously associated with metabolic risk had effects on BCHE activity more often than can be explained by chance. In particular, SNPs within FTO and GCKR were associated with BCHE activity, but their effects were partly mediated by body mass index and triglycerides, respectively. We conclude that variation in BCHE activity is due to multiple variants across the spectrum from uncommon/large effect to common/small effect, and partly results from (rather than causes) metabolic abnormalities.

Identification of a novel prostate cancer susceptibility variant in the KLK3 gene transcript

Abstract Genome-wide association studies (GWAS) have identified more than 30 prostate cancer (PrCa) susceptibility loci. One of these (rs2735839) is located close to a plausible candidate susceptibility gene, KLK3, which encodes prostate-specific antigen (PSA). PSA is widely used as a biomarker for PrCa detection and disease monitoring. To refine the association between PrCa and variants in this region, we used genotyping data from a two-stage GWAS using samples from the UK and Australia, and the Cancer Genetic Markers of Susceptibility (CGEMS) study. Genotypes were imputed for 197 and 312 single nucleotide polymorphisms (SNPs) from HapMap2 and the 1000 Genome Project, respectively. The most significant association with PrCa was with a previously unidentified SNP, rs17632542 (combined P = 3.9 × 10−22). This association was confirmed by direct genotyping in three stages of the UK/Australian GWAS, involving 10,405 cases and 10,681 controls (combined P = 1.9 × 10−34). rs17632542 is also shown to be associated with PSA levels and it is a non-synonymous coding SNP (Ile179Thr) in KLK3. Using molecular dynamic simulation, we showed evidence that this variant has the potential to introduce alterations in the protein or affect RNA splicing. We propose that rs17632542 may directly influence PrCa risk.

Genetic polymorphisms in the human tissue kallikrein (KLK) locus and their implication in various malignant and non-malignant diseases

The Kallikrein (KLK) gene locus encodes a family of serine proteases and is the largest contiguous cluster of protease-encoding genes attributed an evolutionary age of 330 million years. The KLK locus has been implicated as a high susceptibility risk loci in numerous cancer studies through the last decade. The KLK3 gene already has established clinical relevance as a biomarker in prostate cancer prognosis through its encoded protein, prostate-specific antigen. Data mined through genome-wide association studies (GWAS) and next-generation sequencing point to many important candidate single nucleotide polymorphisms (SNPs) in KLK3 and other KLK genes. SNPs in the KLK locus have been found to be associated with several diseases including cancer, hypertension, cardiovascular disease and atopic dermatitis. Moreover, introducing a model incorporating SNPs to improve the efficiency of prostate-specific antigen in detecting malignant states of prostate cancer has been recently suggested. Establishing the functional relevance of these newly-discovered SNPs, and their interactions with each other, through in silico investigations followed by experimental validation, can accelerate the discovery of diagnostic and prognostic biomarkers. In this review, we discuss the various genetic association studies on the KLK loci identified either through candidate gene association studies or at the GWAS and post-GWAS front to aid researchers in streamlining their search for the most significant, relevant and therapeutically promising candidate KLK gene and/or SNP for future investigations.

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.

Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping

Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10−8). More than 70 prostate cancer susceptibility loci, explaining ~30% of the familial risk for this disease, have now been identified. On the basis of combined risks conferred by the new and previously known risk loci, the top 1% of the risk distribution has a 4.7-fold higher risk than the average of the population being profiled. These results will facilitate population risk stratification for clinical studies.

Investigation of lymphotoxin α genetic variants in migraine

Migraine is a common neurological disease with a genetic basis affecting approximately 12% of the population. Pain during a migraine attack is associated with activation of the trigeminal nerve system, which carries pain signals from the meninges and the blood vessels infusing the meninges to the trigeminal nucleus in the brain stem. The release of inflammatory mediators following cortical spreading depression (CSD) may further promote and sustain the activation and sensitization of meningeal nociceptors, inducing the persistent throbbing headache characterised in migraine. Lymphotoxin α (LTA) is a cytokine secreted by lymphocytes and is a member of the tumour necrosis factor (TNF) family. Genetic variation with the TNF and LTA genes may contribute to threshold brain excitability, propagation of neuronal hyperexcitability and thus initiation and maintenance of a migraine attack. Three LTA variants rs2009658, rs2844482 and rs2229094 were identified in a recent pGWAS study conducted in the Norfolk Island population as being potentially implicated in migraine with nominally significant p values of p = 0.0093, p = 0.0088 and p = 0.033 respectively. To determine whether these SNPs played a role in migraine in a general outbred population these SNPs were gentoyped in a large case control Australian Caucasian population and tested for association with migraine. All three SNPs showed no association in our cohort (p > 0.05). Validation of GWAS data in independent case-controls cohorts is essential to establish risk validity within specific population groups. The importance of cytokines in modulating neural inflammation and pain threshold in addition to other studies showing associations between TNF-α and SNPs in the LTA gene with migraine, suggests that LTA could be an important factor contributing to migraine. Although the present study did not support a role for the tested LTA variants in migraine, investigation of other variants within the LTA gene is still warranted.

Molecular genetics of migraine

Migraine is a common neurological disorder with a significantly heritable component. It is a complex disease and despite numerous molecular genetic studies, the exact pathogenesis causing the neurological disturbance remains poorly understood. Although several known molecular mechanisms have been associated with an increased risk for developing migraine, there remains significant scope for future studies. The majority of studies have investigated the most plausible candidate genes involved in common migraine pathogenesis utilising criteria that takes into account a combination of physiological functionality in conjunction with regions of genomic association. Thus, far genes involved in neurological, vascular or hormonal pathways have been identified and investigated on this basis. Genome-wide association studies (GWAS) studies have helped to identify novel regions that may be associated with migraine and have aided in providing the basis for further molecular investigations. However, further studies utilising sequencing technologies are required to characterise the genetic basis for migraine.

A genome-wide analysis of 'Bounty' descendants implicates several novel variants in migraine susceptibility

Migraine is a common neurological disease with a complex genetic aetiology. The disease affects ~12% of the Caucasian population and females are three times more likely than males to be diagnosed. In an effort to identify loci involved in migraine susceptibility, we performed a pedigree-based genome-wide association study of the isolated population of Norfolk Island, which has a high prevalence of migraine. This unique population originates from a small number of British and Polynesian founders who are descendents of the Bounty mutiny and forms a very large multigenerational pedigree (Bellis et al.; Human Genetics, 124(5):543-5542, 2008). These population genetic features may facilitate disease gene mapping strategies (Peltonen et al.; Nat Rev Genet, 1(3):182-90, 2000. In this study, we identified a high heritability of migraine in the Norfolk Island population (h (2) = 0.53, P = 0.016). We performed a pedigree-based GWAS and utilised a statistical and pathological prioritisation approach to implicate a number of variants in migraine. An SNP located in the zinc finger protein 555 (ZNF555) gene (rs4807347) showed evidence of statistical association in our Norfolk Island pedigree (P = 9.6 × 10(-6)) as well as replication in a large independent and unrelated cohort with >500 migraineurs. In addition, we utilised a biological prioritisation to implicate four SNPs, in within the ADARB2 gene, two SNPs within the GRM7 gene and a single SNP in close proximity to a HTR7 gene. Association of SNPs within these neurotransmitter-related genes suggests a disrupted serotoninergic system that is perhaps specific to the Norfolk Island pedigree, but that might provide clues to understanding migraine more generally.

Genome-wide meta-analysis identifies novel multiple sclerosis susceptibility loci

Objective: To perform a 1-stage meta-analysis of genome-wide association studies (GWAS) of multiple sclerosis (MS) susceptibility and to explore functional consequences of new susceptibility loci. Methods: We synthesized 7 MS GWAS. Each data set was imputed using HapMap phase II, and a per single nucleotide polymorphism (SNP) meta-analysis was performed across the 7 data sets. We explored RNA expression data using a quantitative trait analysis in peripheral blood mononuclear cells (PBMCs) of 228 subjects with demyelinating disease. Results: We meta-analyzed 2,529,394 unique SNPs in 5,545 cases and 12,153 controls. We identified 3 novel susceptibility alleles: rs170934T at 3p24.1 (odds ratio [OR], 1.17; p ¼ 1.6 � 10�8) near EOMES, rs2150702G in the second intron of MLANA on chromosome 9p24.1 (OR, 1.16; p ¼ 3.3 � 10�8), and rs6718520A in an intergenic region on chromosome 2p21, with THADA as the nearest flanking gene (OR, 1.17; p ¼ 3.4 � 10�8). The 3 new loci do not have a strong cis effect on RNA expression in PBMCs. Ten other susceptibility loci had a suggestive p < 1 � 10�6, some of these loci have evidence of association in other inflammatory diseases (ie, IL12B, TAGAP, PLEK, and ZMIZ1). Interpretation: We have performed a meta-analysis of GWAS in MS that more than doubles the size of previous gene discovery efforts and highlights 3 novel MS susceptibility loci. These and additional loci with suggestive evidence of association are excellent candidates for further investigations to refine and validate their role in the genetic architecture of MS.

Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

Background: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. Methods: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. Results: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/ signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). Conclusions: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics.

Genome-wide association study identifies new multiple sclerosis susceptibility loci on chromosomes 12 and 20

To identify multiple sclerosis (MS) susceptibility loci, we conducted a genome-wide association study (GWAS) in 1,618 cases and used shared data for 3,413 controls. We performed replication in an independent set of 2,256 cases and 2,310 controls, for a total of 3,874 cases and 5,723 controls. We identified risk-associated SNPs on chromosome 12q13-14 (rs703842, P = 5.4 x 10(-11); rs10876994, P = 2.7 x 10(-10); rs12368653, P = 1.0 x 10(-7)) and upstream of CD40 on chromosome 20q13 (rs6074022, P = 1.3 x 10(-7); rs1569723, P = 2.9 x 10(-7)). Both loci are also associated with other autoimmune diseases. We also replicated several known MS associations (HLA-DR15, P = 7.0 x 10(-184); CD58, P = 9.6 x 10(-8); EVI5-RPL5, P = 2.5 x 10(-6); IL2RA, P = 7.4 x 10(-6); CLEC16A, P = 1.1 x 10(-4); IL7R, P = 1.3 x 10(-3); TYK2, P = 3.5 x 10(-3)) and observed a statistical interaction between SNPs in EVI5-RPL5 and HLA-DR15 (P = 0.001).

Genome-wide association study identifies a possible susceptibility locus for endometrial cancer

Background: Genome-wide association studies (GWAS) have identified more than 100 genetic loci for various cancers. However, only one is for endometrial cancer. Methods: We conducted a three-stage GWAS including 8,492 endometrial cancer cases and 16,596 controls. After analyzing 585,963 single-nucleotide polymorphisms (SNP) in 832 cases and 2,682 controls (stage I) from the Shanghai Endometrial Cancer Genetics Study, we selected the top 106 SNPs for in silico replication among 1,265 cases and 5,190 controls from the Australian/British Endometrial Cancer GWAS (stage II). Nine SNPs showed results consistent in direction with stage I with P < 0.1. These nine SNPs were investigated among 459 cases and 558 controls (stage IIIa) and six SNPs showed a direction of association consistent with stages I and II. These six SNPs, plus two additional SNPs selected on the basis of linkage disequilibrium and P values in stage II, were investigated among 5,936 cases and 8,166 controls from an additional 11 studies (stage IIIb). Results: SNP rs1202524, near the CAPN9 gene on chromosome 1q42.2, showed a consistent association with endometrial cancer risk across all three stages, with ORs of 1.09 [95% confidence interval (CI), 1.03–1.16] for the A/G genotype and 1.17 (95% CI, 1.05–1.30) for the G/G genotype (P = 1.6 × 10−4 in combined analyses of all samples). The association was stronger when limited to the endometrioid subtype, with ORs (95% CI) of 1.11 (1.04–1.18) and 1.21 (1.08–1.35), respectively (P = 2.4 × 10−5). Conclusions: Chromosome 1q42.2 may host an endometrial cancer susceptibility locus. Impact: This study identified a potential genetic locus for endometrial cancer risk