Genome-wide Association Studies Single Nucleotide Polymorphisms Research Articles

Connecting the Dots: Potential of Data Integration to Identify Regulatory SNPs in Late-Onset Alzheimer's Disease GWAS Findings

Late-onset Alzheimer's disease (LOAD) is a multifactorial disorder with over twenty loci associated with disease risk. Given the number of genome-wide significant variants that fall outside of coding regions, it is possible that some of these variants alter some function of gene expression rather than tagging coding variants that alter protein structure and/or function. RegulomeDB is a database that annotates regulatory functions of genetic variants. In this study, we utilized RegulomeDB to investigate potential regulatory functions of lead single nucleotide polymorphisms (SNPs) identified in five genome-wide association studies (GWAS) of risk and age-at onset (AAO) of LOAD, as well as SNPs in LD (r2≥0.80) with the lead GWAS SNPs. Of a total 614 SNPs examined, 394 returned RegulomeDB scores of 1–6. Of those 394 variants, 34 showed strong evidence of regulatory function (RegulomeDB score <3), and only 3 of them were genome-wide significant SNPs (ZCWPW1/rs1476679, CLU/rs1532278 and ABCA7/rs3764650). This study further supports the assumption that some of the non-coding GWAS SNPs are true associations rather than tagged associations and demonstrates the application of RegulomeDB to GWAS data.

Multiancestral analysis of inflammation-related genetic variants and C-reactive protein in the population architecture using genomics and epidemiology study.

C-reactive protein (CRP) is a biomarker of inflammation. Genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) associated with CRP concentrations and inflammation-related traits such as cardiovascular disease, type 2 diabetes mellitus, and obesity. We aimed to replicate previous CRP-SNP associations, assess whether these associations generalize to additional race/ethnicity groups, and evaluate inflammation-related SNPs for a potentially pleiotropic association with CRP. We selected and analyzed 16 CRP-associated and 250 inflammation-related GWAS SNPs among 40 473 African American, American Indian, Asian/Pacific Islander, European American, and Hispanic participants from 7 studies collaborating in the Population Architecture using Genomics and Epidemiology (PAGE) study. Fixed-effect meta-analyses combined study-specific race/ethnicity-stratified linear regression estimates to evaluate the association between each SNP and high-sensitivity CRP. Overall, 18 SNPs in 8 loci were significantly associated with CRP (Bonferroni-corrected P<3.1×10(-3) for replication, P<2.0×10(-4) for pleiotropy): Seven of these were specific to European Americans, while 9 additionally generalized to African Americans (1), Hispanics (5), or both (3); 1 SNP was seen only in African Americans and Hispanics. Two SNPs in the CELSR2/PSRC1/SORT1 locus showed a potentially novel association with CRP: rs599839 (P=2.0×10(-6)) and rs646776 (P=3.1×10(-5)). We replicated 16 SNP-CRP associations, 10 of which generalized to African Americans and/or Hispanics. We also identified potentially novel pleiotropic associations with CRP for two SNPs previously associated with coronary artery disease and/or low-density lipoprotein-cholesterol. These findings demonstrate the benefit of evaluating genotype-phenotype associations in multiple race/ethnicity groups and looking for pleiotropic relationships among SNPs previously associated with related phenotypes.

Assessment of common variability and expression quantitative trait loci for genome-wide associations for progressive supranuclear palsy

Progressive supranuclear palsy is a rare parkinsonian disorder with characteristic neurofibrillary pathology consisting of hyperphosphorylated tau protein. Common variation defining the microtubule associated protein tau gene (MAPT) H1 haplotype strongly contributes to disease risk. A recent genome-wide association study (GWAS) revealed 3 novel risk loci on chromosomes 1, 2, and 3 that primarily implicate STX6, EIF2AK3, and MOBP, respectively. Genetic associations, however, rarely lead to direct identification of the relevant functional allele. More often, they are in linkage disequilibrium with the causative polymorphism(s) that could be a coding change or affect gene expression regulatory motifs. To identify any such changes, we sequenced all coding exons of those genes directly implicated by the associations in progressive supranuclear palsy cases and analyzed regional gene expression data from control brains to identify expression quantitative trait loci within 1 Mb of the risk loci. Although we did not find any coding variants underlying the associations, GWAS-associated single-nucleotide polymorphisms at these loci are in complete linkage disequilibrium with haplotypes that completely overlap with the respective genes. Although implication of EIF2AK3 and MOBP could not be fully assessed, we show that the GWAS single-nucleotide polymorphism rs1411478 (STX6) is a strong expression quantitative trait locus with significantly lower expression of STX6 in white matter in carriers of the risk allele.

Susceptibility loci for pigmentation and melanoma in relation to Parkinson's disease

Growing evidence suggests that Parkinson's disease (PD) patients have a lower risk for most types of cancer except for melanoma, which has a modest positive association with PD. Pigmentation genes have been hypothesized to contribute to this association. We therefore examined whether genetic susceptibility loci for pigmentation or melanoma was associated with PD risk in 2 large independent datasets. In the Parkinson's Genes and Environment (PAGE) study, we examined 11 single-nucleotide polymorphisms (SNPs) identified from previous genome-wide association studies (GWAS) of pigmentation or melanoma in relation to PD among 808 PD cases and 1623 controls; furthermore, we also examined the colors of hair, eye, or skin and melanoma in relation to PD. In the International Parkinson's Disease Genomic Consortium (IPDGC), we examined a broader selection of 360 pigmentation or melanoma GWAS SNPs in relation to PD among 5,333 PD cases and 12,019 controls. All participants were non-Hispanic Whites. As expected, in the PAGE study, most SNPs were associated with 1 or more pigmentation phenotypes. However, neither these SNPs nor pigmentation phenotypes were associated with PD risk after Bonferroni correction with the exception of rs4911414 at the ASIP gene (p = .001). A total of 18 PD cases (2.2%) and 26 controls (1.6%) had a diagnosis of melanoma with an odds ratio of 1.3 (95% confidence interval: 0.7–2.4). In the IPDGC analysis, none of the 360 SNPs, including rs4911414, were associated with PD risk after adjusting for multiple comparisons. In conclusion, we did not find significant associations between GWAS SNPs of pigmentation or melanoma and the risk for PD.

Post genome-wide association studies functional characterization of prostate cancer risk loci

BackgroundOver the last decade, genome-wide association studies (GWAS) have discovered many risk associated single nucleotide polymorphisms (SNPs) of prostate cancer (PCa). However, the majority of the associated PCa SNPs, including those in linkage disequilibrium (LD) blocks, are generally not located in protein coding regions. The systematical investigation of the functional roles of these SNPs, especially the non-coding SNPs, becomes very necessary and helpful to the understanding of the molecular mechanism of PCa.ResultsIn this work, we proposed a comprehensive framework at network level to integrate the SNP annotation, target gene assignment, gene ontology (GO) classification, pathway enrichment analysis and regulatory network reconstruction to illustrate the molecular functions of PCa associated SNPs. By LD expansion, we first identified 1828 LD SNPs using 49 reported GWAS SNPs as a start. We carefully annotated these 1828 LD SNPs via either UCSC known genes, UCSC regulation elements, or expression Quantitative Trait Loci (eQTL) data. As a result, we found 1154 SNPs were functionally annotated and obtained 205 unique PCa genes for further enrichment analysis. The enriched GO biological processes and pathways were found mainly related to regulation of cell death, apoptosis, cell proliferation, and metabolic process, which have been proved essential to cancer development. We constructed PCa genes specific transcription regulatory networks, finding several important genetic regulators for PCa, such as IGF-1/IGF-2 receptors, SP1, CREB1, and androgen receptor (AR).ConclusionsA comprehensive framework was proposed for integrative and systematic analysis of PCa SNPs, the analysis can provide essential information for the understanding of the regulatory function of GWAS SNPs in PCa, and will facilitate the discovery of novel candidate biomarkers for diagnosis and prognosis of PCa.

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.

Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study

BackgroundMultiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S.MethodsAs part of the 'Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites.ResultsOverall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 × 10-15), versus 3/9 in AA (p= 0.03 to 6 × 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only.ConclusionsGeneralization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.

Common genetic variants regulating ADD3 gene expression alter biliary atresia risk

Biliary atresia (BA) is a rare and most severe cholestatic disease in neonates, but the pathogenic mechanisms are unknown. Through a previous genome wide association study (GWAS) on Han Chinese, we discovered association of the 10q24.2 region encompassing ADD3 and XPNPEP1 genes, which was replicated in Chinese and Thai populations. This study aims to fully characterize the genetic architecture at 10q24.2 and to reveal the link between the genetic variants and BA. We genotyped 107 single nucleotide polymorphisms (SNPs) in 10q24.2 in 339 Han Chinese patients and 401 matched controls using Sequenom. Exhaustive follow-up studies of the association signals were performed. The combined BA-association p-value of the GWAS SNP (rs17095355) achieved 6.06×10(-10). Further, we revealed the common risk haplotype encompassing 5 tagging-SNPs, capturing the risk-predisposing alleles in 10q24.2 [p=5.32×10(-11); odds ratio, OR: 2.38; confidence interval, CI: (2.14-2.62)]. Through Sanger sequencing, no deleterious rare variants (RVs) residing in the risk haplotype were found, dismissing the theory of "synthetic" association. Moreover, in bioinformatics and in vivo genotype-expression investigations, the BA-associated potentially regulatory SNPs correlated with ADD3 gene expression (n=36; p=0.0030). Remarkably, the risk haplotype frequency coincides with BA incidences in the population, and, positive selection (favoring the derived alleles that arose from mutations) was evident at the ADD3 locus, suggesting a possible role for the BA-associated common variants in shaping the general population diversity. Common genetic variants in 10q24.2 can alter BA risk by regulating ADD3 expression levels in the liver, and may exert an effect on disease epidemiology and on the general population.

Cyclic AMP and c-KIT Signaling in Familial Testicular Germ Cell Tumor Predisposition

Familial testicular germ cell tumors (FTGCTs) are hypothesized to result from the combined interaction of multiple low-penetrance genes. We reported inactivating germline mutations of the cAMP-binding phosphodiesterase 11A (PDE11A) as modifiers of FTGCT risk. Recent genome-wide association studies have identified single-nucleotide polymorphisms in the KITLG gene, the ligand for the cKIT tyrosine kinase receptor, as strong modifiers of susceptibility to both familial and sporadic testicular germ cell tumors. We studied 94 patients with FTGCTs and 50 at-risk male relatives from 63 unrelated kindreds, in whom the PDE11A gene had been sequenced by investigating the association between KITLG genome-wide association study single-nucleotide polymorphisms rs3782179 and rs4474514 and FTGCT risk in these patients and in 692 controls. We also examined cAMP and c-KIT signaling in testicular tissues and cell lines and extended the studies to 2 sporadic cases, one with a PDE11A defect and one without, as a comparison. We found a higher frequency of the KITLG risk alleles in FTGCT patients who also had a PDE11A sequence variant, compared with those with a wild-type PDE11A sequence. In NTERA-2 and Tcam-2 cells transfected with the mutated forms of PDE11A (R52T, F258Y, Y727C, R804H, V820M, R867G, and M878V), cAMP levels were significantly higher, and the relative phosphodiesterase activity was lower than in the wild-type cells. KITLG expression was consistently increased in the presence of PDE11A-inactivating defects, both at the RNA and protein levels, in familial testicular germ cell tumors. The 2 sporadic cases that were studied, one with a PDE11A defect and another without, agreed with the data in FTGTCT and in the cell lines. Patients with FTGCT and PDE11A defects also carry KITLG risk alleles more frequently. There may be an interaction between cAMP and c-KIT signaling in predisposition to testicular germ cell tumors.

Rs2072135, a low-penetrance variant for chronic lymphocytic leukaemia?

Recent multi-stage genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) that are robustly associated with chronic lymphocytic leukaemia (CLL) risk. Given that most of these SNPs map to non-coding regions of the genome, it suggests that the functional basis of many GWAS signals will be through differential gene expression. By referencing publically accessible expression quantitative trait loci (eQTL) data on lymphoblastoid cells lines (LCLs) we have globally demonstrated an association between GWAS P-values and eQTLs, consistent with much of the variation in CLL risk being defined by variants impacting on gene expression. To explore using eQTL data to select GWAS SNPs for replication, we genotyped rs2072135 (GWAS P-value = 0·0024, eQTL P-value = 1·510(-19)) in five independent case-control series totalling 1968 cases and 3538 controls. While not attaining statistical significance (combined P-value = 1 × 10(-4)), rs2072135 defines a promising risk locus for CLL. Incorporating eQTL information offers an attractive strategy for selecting SNPs from GWAS for validation.

All SNPs Are Not Created Equal: Genome-Wide Association Studies Reveal a Consistent Pattern of Enrichment among Functionally Annotated SNPs

Recent results indicate that genome-wide association studies (GWAS) have the potential to explain much of the heritability of common complex phenotypes, but methods are lacking to reliably identify the remaining associated single nucleotide polymorphisms (SNPs). We applied stratified False Discovery Rate (sFDR) methods to leverage genic enrichment in GWAS summary statistics data to uncover new loci likely to replicate in independent samples. Specifically, we use linkage disequilibrium-weighted annotations for each SNP in combination with nominal p-values to estimate the True Discovery Rate (TDR = 1−FDR) for strata determined by different genic categories. We show a consistent pattern of enrichment of polygenic effects in specific annotation categories across diverse phenotypes, with the greatest enrichment for SNPs tagging regulatory and coding genic elements, little enrichment in introns, and negative enrichment for intergenic SNPs. Stratified enrichment directly leads to increased TDR for a given p-value, mirrored by increased replication rates in independent samples. We show this in independent Crohn's disease GWAS, where we find a hundredfold variation in replication rate across genic categories. Applying a well-established sFDR methodology we demonstrate the utility of stratification for improving power of GWAS in complex phenotypes, with increased rejection rates from 20% in height to 300% in schizophrenia with traditional FDR and sFDR both fixed at 0.05. Our analyses demonstrate an inherent stratification among GWAS SNPs with important conceptual implications that can be leveraged by statistical methods to improve the discovery of loci.

Abstract MP58: Type 2 Diabetes Prediction with 17-, 40-, and 62-variant Genotype Risk Scores: The Framingham Offspring Study

Background A recent genome-wide association study (GWAS) meta-analysis for type 2 diabetes (T2D) increased by 50% the number of common T2D-associated single-nucleotide polymorphisms (SNPs). We hypothesized that a genotype risk score (GRS) consisting of more SNPs improves T2D prediction achieved by published 17-SNP and 40-SNP scores. Methods We used data from four 8-year periods of the Framingham Offspring Study to test the association between effect-weighted 17-SNP, 40-SNP, and 62-SNP GRSs and incident T2D, defined by medication use and fasting glucose criteria. We used pooled logistic regression models with generalized estimating equations adjusted for 1) age and sex and 2) age, sex, parental T2D, BMI, systolic blood pressure, fasting glucose, HDL cholesterol, and triglyceride levels. Model improvement by the addition of each GRS was assessed with C statistics, integrated discrimination improvement (IDI) indices, and net reclassification improvement (NRI) indices with category thresholds at 2% and 8% cumulative incidence. Results Mean baseline age was 46, and 46.5% were men. There were 446 cases of incident T2D among 11,358 person-exams. In all models, the inclusion of a GRS resulted in significant T2D risk reclassification (NRI range 22.3-29.8%, see Table). The inclusion of a greater number of SNPs in the GRS increased the C statistics and relative IDI of the age- and sex-adjusted model, but the 62-SNP GRS did not result in a higher NRI than the 40-SNP GRS (28.6% vs. 29.8%). Similarly, the 62-SNP score did not result in a higher NRI for the fully adjusted clinical model than the 40-SNP score (25.6% vs. 29.0%). Conclusions A GRS of common susceptibility SNPs from GWAS improves T2D risk reclassification in a prospective study of adults, but incorporating a greater number of SNPs with smaller individual effect sizes may not result in additional reclassification improvement. Further advances in genotype prediction of T2D may require the identification and incorporation of functional risk variants putatively tagged by GWAS SNPs.

The impact of improved microarray coverage and larger sample sizes on future genome-wide association studies.

Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) associated with complex traits. However, the genetic heritability of most of these traits remains unexplained. To help guide future studies, we address the crucial question of whether future GWAS can detect new SNP associations and explain additional heritability given the new availability of larger GWAS SNP arrays, imputation, and reduced genotyping costs. We first describe the pairwise and imputation coverage of all SNPs in the human genome by commercially available GWAS SNP arrays, using the 1000 Genomes Project as a reference. Next, we describe the findings from 6 years of GWAS of 172 chronic diseases, calculating the power to detect each of them while taking array coverage and sample size into account. We then calculate the power to detect these SNP associations under different conditions using improved coverage and/or sample sizes. Finally, we estimate the percentages of SNP associations and heritability previously detected and detectable by future GWAS under each condition. Overall, we estimated that previous GWAS have detected less than one-fifth of all GWAS-detectable SNPs underlying chronic disease. Furthermore, increasing sample size has a much larger impact than increasing coverage on the potential of future GWAS to detect additional SNP-disease associations and heritability.

Obesity polymorphisms identified in genome-wide association studies interact with n-3 polyunsaturated fatty acid intake and modify the genetic association with adiposity phenotypes in Yup’ik people

n-3 Polyunsaturated fatty acids (n-3 PUFAs) have anti-obesity effects that may modulate risk of obesity, in part, through interactions with genetic factors. Genome-wide association studies (GWAS) have identified genetic variants associated with body mass index (BMI); however, the extent to which these variants influence adiposity through interactions with n-3 PUFAs remains unknown. We evaluated 10 highly replicated obesity GWAS single nucleotide polymorphisms (SNPs) for individual and cumulative associations with adiposity phenotypes in a cross-sectional sample of Yup'ik people (n=1,073) and evaluated whether genetic associations with obesity were modulated by n-3 PUFA intake. A genetic risk score (GRS) was calculated by adding the BMI-increasing alleles across all 10 SNPs. Dietary intake of n-3 PUFAs was estimated using nitrogen stable isotope ratio (δ(15)N) of red blood cells, and genotype-phenotype analyses were tested in linear models accounting for familial correlations. GRS was positively associated with BMI (p=0.012), PBF (p=0.022), ThC (p=0.025), and waist circumference (p=0.038). The variance in adiposity phenotypes explained by the GRS included BMI (0.7%), PBF (0.3%), ThC (0.7%), and WC (0.5%). GRS interactions with n-3 PUFAs modified the association with adiposity and accounted for more than twice the phenotypic variation (~1-2%), relative to GRS associations alone. Obesity GWAS SNPs contribute to adiposity in this study population of Yup'ik people and interactions with n-3 PUFA intake potentiated the risk of fat accumulation among individuals with high obesity GRS. These data suggest the anti-obesity effects of n-3 PUFAs among Yup'ik people may, in part, be dependent upon an individual's genetic predisposition to obesity.

Replication of genetic loci for ages at menarche and menopause in the multi-ethnic Population Architecture using Genomics and Epidemiology (PAGE) study

Do genetic associations identified in genome-wide association studies (GWAS) of age at menarche (AM) and age at natural menopause (ANM) replicate in women of diverse race/ancestry from the Population Architecture using Genomics and Epidemiology (PAGE) Study? We replicated GWAS reproductive trait single nucleotide polymorphisms (SNPs) in our European descent population and found that many SNPs were also associated with AM and ANM in populations of diverse ancestry. Menarche and menopause mark the reproductive lifespan in women and are important risk factors for chronic diseases including obesity, cardiovascular disease and cancer. Both events are believed to be influenced by environmental and genetic factors, and vary in populations differing by genetic ancestry and geography. Most genetic variants associated with these traits have been identified in GWAS of European-descent populations. A total of 42 251 women of diverse ancestry from PAGE were included in cross-sectional analyses of AM and ANM. SNPs previously associated with ANM (n = 5 SNPs) and AM (n = 3 SNPs) in GWAS were genotyped in American Indians, African Americans, Asians, European Americans, Hispanics and Native Hawaiians. To test SNP associations with ANM or AM, we used linear regression models stratified by race/ethnicity and PAGE sub-study. Results were then combined in race-specific fixed effect meta-analyses for each outcome. For replication and generalization analyses, significance was defined at P < 0.01 for ANM analyses and P < 0.017 for AM analyses. We replicated findings for AM SNPs in the LIN28B locus and an intergenic region on 9q31 in European Americans. The LIN28B SNPs (rs314277 and rs314280) were also significantly associated with AM in Asians, but not in other race/ethnicity groups. Linkage disequilibrium (LD) patterns at this locus varied widely among the ancestral groups. With the exception of an intergenic SNP at 13q34, all ANM SNPs replicated in European Americans. Three were significantly associated with ANM in other race/ethnicity populations: rs2153157 (6p24.2/SYCP2L), rs365132 (5q35/UIMC1) and rs16991615 (20p12.3/MCM8). While rs1172822 (19q13/BRSK1) was not significant in the populations of non-European descent, effect sizes showed similar trends. Lack of association for the GWAS SNPs in the non-European American groups may be due to differences in locus LD patterns between these groups and the European-descent populations included in the GWAS discovery studies; and in some cases, lower power may also contribute to non-significant findings. The discovery of genetic variants associated with the reproductive traits provides an important opportunity to elucidate the biological mechanisms involved with normal variation and disorders of menarche and menopause. In this study we replicated most, but not all reported SNPs in European descent populations and examined the epidemiologic architecture of these early reported variants, describing their generalizability and effect size across differing ancestral populations. Such data will be increasingly important for prioritizing GWAS SNPs for follow-up in fine-mapping and resequencing studies, as well as in translational research.

Expression of Novel Alzheimer’s Disease Risk Genes in Control and Alzheimer’s Disease Brains

Late onset Alzheimer’s disease (LOAD) etiology is influenced by complex interactions between genetic and environmental risk factors. Large-scale genome wide association studies (GWAS) for LOAD have identified 10 novel risk genes: ABCA7, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, MS4A6A, MS4A6E, and PICALM. We sought to measure the influence of GWAS single nucleotide polymorphisms (SNPs) and gene expression levels on clinical and pathological measures of AD in brain tissue from the parietal lobe of AD cases and age-matched, cognitively normal controls. We found that ABCA7, CD33, and CR1 expression levels were associated with clinical dementia rating (CDR), with higher expression being associated with more advanced cognitive decline. BIN1 expression levels were associated with disease progression, where higher expression was associated with a delayed age at onset. CD33, CLU, and CR1 expression levels were associated with disease status, where elevated expression levels were associated with AD. Additionally, MS4A6A expression levels were associated with Braak tangle and Braak plaque scores, with elevated expression levels being associated with more advanced brain pathology. We failed to detect an association between GWAS SNPs and gene expression levels in our brain series. The minor allele of rs3764650 in ABCA7 is associated with age at onset and disease duration, and the minor allele of rs670139 in MS4A6E was associated with Braak tangle and Braak plaque score. These findings suggest that expression of some GWAS genes, namely ABCA7, BIN1, CD33, CLU, CR1 and the MS4A family, are altered in AD brains.

MirSNP, a database of polymorphisms altering miRNA target sites, identifies miRNA-related SNPs in GWAS SNPs and eQTLs.

BackgroundNumerous single nucleotide polymorphisms (SNPs) associated with complex diseases have been identified by genome-wide association studies (GWAS) and expression quantitative trait loci (eQTLs) studies. However, few of these SNPs have explicit biological functions. Recent studies indicated that the SNPs within the 3’UTR regions of susceptibility genes could affect complex traits/diseases by affecting the function of miRNAs. These 3’UTR SNPs are functional candidates and therefore of interest to GWAS and eQTL researchers.DescriptionWe developed a publicly available online database, MirSNP (http://cmbi.bjmu.edu.cn/mirsnp), which is a collection of human SNPs in predicted miRNA-mRNA binding sites. We identified 414,510 SNPs that might affect miRNA-mRNA binding. Annotations were added to these SNPs to predict whether a SNP within the target site would decrease/break or enhance/create an miRNA-mRNA binding site. By applying MirSNP database to three brain eQTL data sets, we identified four unreported SNPs (rs3087822, rs13042, rs1058381, and rs1058398), which might affect miRNA binding and thus affect the expression of their host genes in the brain. We also applied the MirSNP database to our GWAS for schizophrenia: seven predicted miRNA-related SNPs (p < 0.0001) were found in the schizophrenia GWAS. Our findings identified the possible functions of these SNP loci, and provide the basis for subsequent functional research.ConclusionMirSNP could identify the putative miRNA-related SNPs from GWAS and eQTLs researches and provide the direction for subsequent functional researches.

Abstract 31: The association between GWAS SNPs and mammographic density in Norwegian postmenopausal women stratified by nongenetic factors.

Abstract Background: Mammographic density (MD) is one of the strongest known breast cancer risk factors. Dense breast tissue is characterized by increased stromal tissue and possibly by increased numbers of breast epithelial cells. Twin studies have suggested that part of the variation in MD is determined by genetic factors, however, it is also clear that non-genetic factors such as hormone use, body weight and reproductive factors play a role. Exactly which genetic factors determine MD is not clear, although several genome-wide association studies (GWAS) conducted over the past few years have suggested a number of variants. We hypothesized that the effect of genetic variants on MD may be strongly modified by non-genetic factors. We therefore evaluated the association between percent MD and 17 single nucleotide polymorphisms (SNPs) identified from several published GWAS of MD/breast cancer by strata defined by non-genetic factors. Methods: We assessed MD on 2036 postmenopausal women aged 50-69 years who participated in the Norwegian Breast Cancer Screening Program (NBCSP) in 2004 using a computer assisted method (Madena, University of Southern California). We used linear regression (additive model) to determine the association between each SNP and MD, adjusting for age and body mass index (BMI). The postmenopausal women were stratified on postmenopausal hormone therapy (HT) use, parity, BMI, and alcohol intake. Results: In all postmenopausal women a variant (rs29815829) in the FGFR2 gene and a variant (rs3734805) in the 6q25.1 gene associated significantly with MD (regression coefficient (beta)=-1.42, p=0.0306 and beta=0.74, p=0.0390). The same variants showed significant associations in never HT users with slightly stronger effect estimates, but not in current combined estrogen and progestin therapy users. We also observed some possible effect modification by parity. In all postmenopausal parous women as well as in parous never HT users, the 6q25.1 and the FGFR2 variants were the most important (lowest p-values). However, in nulliparous never HT users a variant (rs3803662) in the TOX3 gene and a variant (rs1045485) in the CASP8 gene associated significantly with MD (beta=1.41, p=0.0120 and beta= 1.42, p=0.0275). There were no apparent differences between alcohol drinkers or non-drinkers in never HT users, regardless of parity. When examining strata of BMI among never HT users, we found a significant association with MD in the CASP8 gene (rs1746827) in women with a BMI &amp;lt; 25 (beta=0.81, p=0.0507) and in the FGFR2 gene (rs2981582) in women with a BMI &amp;gt;25 &amp;lt;29 (beta=-2.34; p=0.0284). Conclusion: We found some evidence that the associations between variants in the 6q25.1 gene and in the FGFR2 gene and MD were modified by HT use. Further, our results suggest that the genetic determinants of MD may differ between parous and nulliparous women, and across BMI strata. Citation Format: Merete Ellingjord-Dale, Isabel dos Santos Silva, Eunjung Lee, Elisabeth Couto, David Van Den Berg, Solveig Hofvind, Tom Grotmol, Giske Ursin. The association between GWAS SNPs and mammographic density in Norwegian postmenopausal women stratified by nongenetic factors. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr 31.

Estimating the proportion of variation in susceptibility to multiple sclerosis captured by common SNPs

Multiple sclerosis (MS) is a complex disease with underlying genetic and environmental factors. Although the contribution of alleles within the major histocompatibility complex (MHC) are known to exert strong effects on MS risk, much remains to be learned about the contributions of loci with more modest effects identified by genome-wide association studies (GWASs), as well as loci that remain undiscovered. We use a recently developed method to estimate the proportion of variance in disease liability explained by 475,806 single nucleotide polymorphisms (SNPs) genotyped in 1,854 MS cases and 5,164 controls. We reveal that ~30% of MS genetic liability is explained by SNPs in this dataset, the majority of which is accounted for by common variants. These results suggest that the unaccounted for proportion could be explained by variants that are in imperfect linkage disequilibrium with common GWAS SNPs, highlighting the potential importance of rare variants in the susceptibility to MS.

Sex and the single nucleotide polymorphism: Exploring the genetic causes of skeletal sex differences

Skeletal traits are exemplars of sexual dimorphism, with consistent sex differences across populations in bone mineral density (BMD), bone geometry, and osteoporotic fracture risk.(1–3) Heritability of these traits has also been demonstrated, and many common single nucleotide polymorphisms (SNP) have pointed to genes accounting for variability in BMD and fracture risk.(4–6) These observations beg the question whether genetic variation affects the female skeleton differently than it does the male. Because testing such gene-by-sex interactions for common SNPs in genome-wide association studies requires extraordinarily large sample sizes, the analysis has only recently become possible with the collaboration of investigators in the GEFOS consortium and other independent studies.(7) Their report follows on recent triumphs such as the GWAS meta-analysis of BMD in more than 80,000 men and women in GEFOS/GENOMOS cohorts(6) that identified 56 genes, several of which were also associated with fracture. Gene-by-sex interactions could identify new signals not detected in the sex-combined analyses and indicate important sex-dependent skeletal biology. Liu and colleagues(7) report that, in fact, no sex differences in the effects of autosomal SNPs on BMD were found in an analysis of more than 50,000 men and women. The contributions of this well designed study and what remains to be explored—beyond SNPs and BMD—to explain genetic causes of skeletal sexual dimorphism are the focus of our discussion. Multiple reports of sex differences in heritability and genetic associations with human skeletal traits have been reported (reviewed in Karasik and Ferrari(8)), including a large meta-analysis of BMD quantitative trait loci (QTL) in humans and SNP association studies for important candidates such as LRP5 and ESR1. There are well recognized limitations of this body of evidence, several of which are addressed by the study from Liu and colleagues.(7) First, although genetic associations discovered in only one sex might, in fact, point to sex-dependent effects, they may also be the result of a lack of power to detect what is truly the same underlying effect in each of the sex strata. In many cases, sex-specific effects have been reported without formally testing the difference in effect between the sexes. In the current study, the investigators have conducted the most comprehensive and well designed study to test that genetic polymorphisms have a different effect on BMD in men than they have in women. Second, as with many studies of sex differences, few replication studies have been published.(9) Publication bias is a well recognized impediment to the consideration of negative results (ie, findings of no sex differences in QTLs or genetic associations) and, in fact, a few other studies have found no significant sex differences in BMD genetic variance(10) or in genotypic effects on BMD.(7) This bias is a problem that meta-analyses, such as the one by Liu and colleagues, take strides against by aligning multiple cohorts and reporting no evidence of gene-by-sex interactions. It is tempting to imagine that with even larger sample sizes statistically significant gene-by-sex interactions might emerge in human cohorts. However, given the small detectable effect sizes noted by Liu and colleagues (explaining <1% of variation in BMD), it is likely to be more rewarding to turn to explanations for the dimorphism that are not based on differential effects of common autosomal SNPs between the sexes. If sequence analysis delivers on the promise of larger effect sizes, it might indeed be possible to document gene-by-sex interactions in future studies. Studies of several genetic mechanisms that were not explored in the study by Liu and colleagues might provide additional insight.