Single Nucleotide Polymorphisms In High Linkage Disequilibrium Research Articles

General intelligence and executive functioning are overlapping but separable at genetic and molecular pathway levels: An analytical review of existing GWAS findings.

Understanding the genomic architecture and molecular mechanisms of cognitive functioning in healthy individuals is critical for developing tailored interventions to enhance cognitive functioning, as well as for identifying targets for treating impaired cognition. There has been substantial progress in uncovering the genetic composition of the general cognitive ability (g). However, there is an ongoing debate whether executive functioning (EF)–another key predictor of cognitive health and performance, is separable from general g. To provide an analytical review on existing findings on genetic influences on the relationship between g and EF, we re-analysed a subset of genome-wide association studies (GWAS) from the GWAS catalogue that used measures of g and EF as outcomes in non-clinical populations. We identified two sets of single nucleotide polymorphisms (SNPs) associated with g (1,372 SNPs across 12 studies), and EF (300 SNPs across 5 studies) at p<5x10-6. A comparative analysis of GWAS-identified g and EF SNPs in high linkage disequilibrium (LD), followed by pathway enrichment analyses suggest that g and EF are overlapping but separable at genetic variant and molecular pathway levels, however more evidence is required to characterize the genetic overlap/distinction between the two constructs. While not without limitations, these findings may have implications for navigating further research towards translatable genetic findings for cognitive remediation, enhancement, and augmentation.

PB1969: FUNCTIONAL CHARACTERIZATION OF SUSCEPTIBILITY LOCI TO MULTIPLE MYELOMA

Background: Multiple myeloma (MM) is the second most common blood malignancy, caused by an uncontrolled growth of plasma cells in the bone marrow, accounting for 20% of all newly diagnosed hematological cancers. Although the current 5-year survival rate is ranging between 40-60%, MM is still considered an incurable disease since most of the patients eventually relapse. While the causes of MM are incompletely understood, several genome-wide association studies (GWAS) have been conducted to identify germline variants that predispose to MM. Up to date, a total of 24 loci were found to be associated with MM risk, but very little information is available about their functional role. Aims: The principal goal is to explore in silico the function of the germline variants associated with MM risk. As we do not know if the GWAS-identified SNPs are the causal variants or just markers of risk, the functional characterization of the causal risk variants would lead to a better understanding of disease development. Methods: GWAS design takes advantage of the linkage disequilibrium (LD) structure of the human genome, thus the main GWAS findings are single-nucleotide polymorphisms (SNPs) that show the strongest association with MM risk (measured as the lowest p-values), but they are not necessarily the functionally causal variants. In this project, we used bioinformatics tools (GTEx, HaploReg v4.1, Roadmap, LDlinke, SNPnexus, RegulomeDB 2.0.3, SNP2TFBS, miRNASNP v3, GeneMANIA) to perform fine mapping of all GWAS-identified loci and to prioritize in each locus the polymorphism with the highest chance of being functionally relevant. In particular, we focused on the loci with the smallest number of SNPs in high LD (r2>0.8) in order to maximize the probability to capture the casual variant. Results: Four of the 24 MM risk loci had a relatively small number of SNPs in high LD and within them we found that the locus located at chromosome 16 contained the greatest number of functionally annotated SNPs. Of particular functional interest was rs3747481 (chr16:30666367 C/T) due to the following reasons: it is a missense variant (protein change: P359L), it is located in the PRR14 gene, that contributes to chromatin hierarchical organization and has a role in gene regulation, has a high CADD PHRED score (22.1). Additionally, according to GTEx portal, rs3747481 is associated with the expression level of the RNF40 gene (which plays a central role in histone code and gene regulation) in whole blood cells (p=3.02-12). It has a score of “1d” in RegulomeDB (eQTL+ TF binding + any motif + DNase peak), meaning that this variant has a high likelihood to affect binding of transcription factors. Some other SNPs (like rs35629860 and rs67128646) in the same LD block show the co-occurrence of H3K4me3 and H3K27me3 histone marks (associated with gene activation and repression, respectively) in promoters and enhancers in B lymphocytes. rs6565197 is predicted to affect the binding of the KLF4 and KLF5 transcription factors which play key roles in cell cycle regulation. Summary/Conclusion: Through a fine mapping of MM risk loci by bioinformatics tools, we found a variant in the locus 16p11.2 that shows in silico a very high probability to have biological role in the risk disease.

Functional characterization of T2D-associated SNP effects on baseline and ER stress-responsive \u03b2 cell transcriptional activation

Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) at >250 loci in the human genome to type 2 diabetes (T2D) risk. For each locus, identifying the functional variant(s) among multiple SNPs in high linkage disequilibrium is critical to understand molecular mechanisms underlying T2D genetic risk. Using massively parallel reporter assays (MPRA), we test the cis-regulatory effects of SNPs associated with T2D and altered in vivo islet chromatin accessibility in MIN6 β cells under steady state and pathophysiologic endoplasmic reticulum (ER) stress conditions. We identify 1,982/6,621 (29.9%) SNP-containing elements that activate transcription in MIN6 and 879 SNP alleles that modulate MPRA activity. Multiple T2D-associated SNPs alter the activity of short interspersed nuclear element (SINE)-containing elements that are strongly induced by ER stress. We identify 220 functional variants at 104 T2D association signals, narrowing 54 signals to a single candidate SNP. Together, this study identifies elements driving β cell steady state and ER stress-responsive transcriptional activation, nominates causal T2D SNPs, and uncovers potential roles for repetitive elements in β cell transcriptional stress response and T2D genetics.

Functional Genomic Analyses of the 21q22.3 Locus Identifying Functional Variants and Candidate Gene YBEY for Breast Cancer Risk.

Simple SummaryPrevious research has revealed a genetic predisposition to breast carcinogenesis. Thus, identifying causal genetic variants and their associated gene networks may improve breast cancer diagnostics and risk assessment. Our study investigated YBEY, an uncharacterized gene in humans, and its functions in breast cancer risk and progression. We identified two genetic variants associated with YBEY expression that may have causal functions in breast cancer risk. We performed in vitro functional assays using MCF-7, T47D, and MDA-MB-231 breast cancer cell lines and showed that knockdown of YBEY expression significantly inhibited proliferation, colony formation, and invasion/migration. We utilized RNA sequencing to identify gene networks associated with YBEY knockdown including inflammation and metabolic pathways. Further, we used data available in The Cancer Genome Atlas to explore trends in YBEY expression patterns in normal and tumor tissues. Our study provides a role for YBEY in breast carcinogenesis, and further studies investigating its mechanistic functions are warranted.We previously identified a locus at 21q22.3, tagged by the single nucleotide polymorphism (SNP) rs35418111, being associated with breast cancer risk at a genome-wide significance level; however, the underlying causal functional variants and gene(s) responsible for this association are unknown. We performed functional genomic analyses to identify potential functional variants and target genes that may mediate this association. Functional annotation for SNPs in high linkage disequilibrium (LD, r2 > 0.8) with rs35418111 in Asians showed evidence of promoter and/or enhancer activities, including rs35418111, rs2078203, rs8134832, rs57385578, and rs8126917. These five variants were assessed for interactions with nuclear proteins by electrophoretic mobility shift assays. Our results showed that the risk alleles for rs2078203 and rs35418111 altered DNA-protein interaction patterns. Cis-expression quantitative loci (cis-eQTL) analysis, using data from the Genotype-Tissue Expression database (GTEx) European-ancestry female normal breast tissue, indicated that the risk allele of rs35418111 was associated with a decreased expression of the YBEY gene, a relatively uncharacterized endoribonuclease in humans. We investigated the biological effects of YBEY on breast cancer cell lines by transient knock-down of YBEY expression in MCF-7, T47D, and MDA-MB-231 cell lines. Knockdown of YBEY mRNA in breast cancer cell lines consistently decreased cell proliferation, colony formation, and migration/invasion, regardless of estrogen receptor status. We performed RNA sequencing in MDA-MB-231 cells transfected with siRNA targeting YBEY and subsequent gene set enrichment analysis to identify gene networks associated with YBEY knockdown. These data indicated YBEY was involved in networks associated with inflammation and metabolism. Finally, we showed trends in YBEY expression patterns in breast tissues from The Cancer Genome Atlas (TCGA); early-stage breast cancers had elevated YBEY expression compared with normal tissue, but significantly decreased expression in late-stage disease. Our study provides evidence of a significant role for the human YBEY gene in breast cancer pathogenesis and the association between the rs35418111/21q22.3 locus and breast cancer risk, which may be mediated through functional SNPs, rs35418111 and rs2078203, that regulate expression of YBEY.

Association of common variation in ADD3 and GPC1 with biliary atresia susceptibility.

Biliary atresia (BA) is an idiopathic neonatal cholestatic disease. Recent genome-wide association study (GWAS) revealed that common variation of ADD3, GPC1, ARF6, and EFEMP1 gene was associated with BA susceptibility. We aimed to evaluate the association of these genes with BA in Chinese population. Twenty single nucleotide polymorphisms (SNPs) in these four genes were genotyped in 340 BA patients and 1,665 controls. Three SNPs in ADD3 were significantly associated with BA, and rs17095355 was the top SNP (PAllele = 3.23×10-6). Meta-analysis of published data and current data indicated that rs17095355 was associated with BA susceptibility in Asians and Caucasians. Three associated SNPs were expression quantitative trait loci (eQTL) for ADD3. Two GPC1 SNPs in high linkage disequilibrium (LD) showed nominal association with BA susceptibility (PAllele = 0.03 for rs6707262 and PAllele = 0.04 for rs6750380), and were eQTL of GPC1. Haplotype harboring these two SNPs almost reached the study-wide significance (P = 0.0035). No association for ARF6 and EFEMP1 was found with BA risk in the current population. Our study validated associations of ADD3 and GPC1 SNPs with BA risk in Chinese population and provided evidence of epistatic contributions of genetic factors to BA susceptibility.

Selecting Closely-Linked SNPs Based on Local Epistatic Effects for Haplotype Construction Improves Power of Association Mapping.

Genome-wide association studies (GWAS) have gained central importance for the identification of candidate loci underlying complex traits. Single nucleotide polymorphism (SNP) markers are mostly used as genetic variants for the analysis of genotype-phenotype associations in populations, but closely linked SNPs that are grouped into haplotypes are also exploited. The benefit of haplotype-based GWAS approaches vs. SNP-based approaches is still under debate because SNPs in high linkage disequilibrium provide redundant information. To overcome some constraints of the commonly-used haplotype-based GWAS in which only consecutive SNPs are considered for haplotype construction, we propose a new method called functional haplotype-based GWAS (FH GWAS). FH GWAS is featured by combining SNPs into haplotypes based on the additive and epistatic effects among SNPs. Such haplotypes were termed functional haplotypes (FH). As shown by simulation studies, the FH GWAS approach clearly outperformed the SNP-based approach unless the minor allele frequency of the SNPs making up the haplotypes is low and the linkage disequilibrium between them is high. Applying FH GWAS for the trait flowering time in a large Arabidopsis thaliana population with whole-genome sequencing data revealed its potential empirically. FH GWAS identified all candidate regions which were detected in SNP-based and two other haplotype-based GWAS approaches. In addition, a novel region on chromosome 4 was solely detected by FH GWAS. Thus both the results of our simulation and empirical studies demonstrate that FH GWAS is a promising method and superior to the SNP-based approach even if almost complete genotype information is available.

Improvement of genomic prediction by integrating additional single nucleotide polymorphisms selected from imputed whole genome sequencing data

The availability of whole genome sequencing (WGS) data enables the discovery of causative single nucleotide polymorphisms (SNPs) or SNPs in high linkage disequilibrium with causative SNPs. This study investigated effects of integrating SNPs selected from imputed WGS data into the data of 54K chip on genomic prediction in Danish Jersey. The WGS SNPs, mainly including peaks of quantitative trait loci, structure variants, regulatory regions of genes, and SNPs within genes with strong effects predicted with variant effect predictor, were selected in previous analyses for dairy breeds in Denmark–Finland–Sweden (DFS) and France (FRA). Animals genotyped with 54K chip, standard LD chip, and customized LD chip which covered selected WGS SNPs and SNPs in the standard LD chip, were imputed to 54K together with DFS and FRA SNPs. Genomic best linear unbiased prediction (GBLUP) and Bayesian four-distribution mixture models considering 54K and selected WGS SNPs as one (a one-component model) or two separate genetic components (a two-component model) were used to predict breeding values. For milk production traits and mastitis, both DFS (0.025) and FRA (0.029) sets of additional WGS SNPs improved reliabilities, and inclusions of all selected WGS SNPs generally achieved highest improvements of reliabilities (0.034). A Bayesian four-distribution model yielded higher reliabilities than a GBLUP model for milk and protein, but extra gains in reliabilities from using selected WGS SNPs were smaller for a Bayesian four-distribution model than a GBLUP model. Generally, no significant difference was observed between one-component and two-component models, except for using GBLUP models for milk.

Variation at the TRIM11 locus modifies progressive supranuclear palsy phenotype.

ObjectiveThe basis for clinical variation related to underlying progressive supranuclear palsy (PSP) pathology is unknown. We performed a genome‐wide association study (GWAS) to identify genetic determinants of PSP phenotype.MethodsTwo independent pathological and clinically diagnosed PSP cohorts were genotyped and phenotyped to create Richardson syndrome (RS) and non‐RS groups. We carried out separate logistic regression GWASs to compare RS and non‐RS groups and then combined datasets to carry out a whole cohort analysis (RS = 367, non‐RS = 130). We validated our findings in a third cohort by referring to data from 100 deeply phenotyped cases from a recent GWAS. We assessed the expression/coexpression patterns of our identified genes and used our data to carry out gene‐based association testing.ResultsOur lead single nucleotide polymorphism (SNP), rs564309, showed an association signal in both cohorts, reaching genome‐wide significance in our whole cohort analysis (odds ratio = 5.5, 95% confidence interval = 3.2–10.0, p = 1.7 × 10−9). rs564309 is an intronic variant of the tripartite motif‐containing protein 11 (TRIM11) gene, a component of the ubiquitin proteasome system (UPS). In our third cohort, minor allele frequencies of surrogate SNPs in high linkage disequilibrium with rs564309 replicated our findings. Gene‐based association testing confirmed an association signal at TRIM11. We found that TRIM11 is predominantly expressed neuronally, in the cerebellum and basal ganglia.InterpretationOur study suggests that the TRIM11 locus is a genetic modifier of PSP phenotype and potentially adds further evidence for the UPS having a key role in tau pathology, therefore representing a target for disease‐modifying therapies. Ann Neurol 2018;84:485–496

Genetic variants of GCH1 associate with chronic and acute crisis pain in African Americans with sickle cell disease

The multidimensional nature of pain in sickle cell disease (SCD) has rendered its therapeutic management extremely challenging. In this study, we explored the role of five single nucleotide polymorphisms (SNPs) of candidate gene GCH1 in SCD pain. Composite pain index (CPI) scores and acute care utilization rates were used as phenotype markers. Rs8007267 was associated with chronic pain (additive model: B = -3.76, p = 0.037; dominant model: B = -5.61, p = 0.021) and rs3783641 (additive model: incident rate ratio [IRR] = 1.37, p = 0.024; recessive model: IRR = 1.81, p = 0.018) with utilization rate. These associations persisted when subjects with HbSS and HbSβ° genotype only were analyzed. We also identified two haploblocks (rs10483639[G>C]-rs752688[C>T]-rs4411417[T>C] and rs3783641[T>A]-rs8007267[T>C]) with SNPs in high linkage disequilibrium. Of these, haplotype T-C of haploblock rs3783641-rs8007267 showed significant association with rate of utilization (odds ratio [OR] = 0.31, p = 0.001). Our study indicates potential contribution of GCH1 polymorphisms to the variability of pain in African Americans with SCD.

SNPrune: an efficient algorithm to prune large SNP array and sequence datasets based on high linkage disequilibrium

BackgroundHigh levels of pairwise linkage disequilibrium (LD) in single nucleotide polymorphism (SNP) array or whole-genome sequence data may affect both performance and efficiency of genomic prediction models. Thus, this warrants pruning of genotyping data for high LD. We developed an algorithm, named SNPrune, which enables the rapid detection of any pair of SNPs in complete or high LD throughout the genome.MethodsLD, measured as the squared correlation between phased alleles (r2), can only reach a value of 1 when both loci have the same count of the minor allele. Sorting loci based on the minor allele count, followed by comparison of their alleles, enables rapid detection of loci in complete LD. Detection of loci in high LD can be optimized by computing the range of the minor allele count at another locus for each possible value of the minor allele count that can yield LD values higher than a predefined threshold. This efficiently reduces the number of pairs of loci for which LD needs to be computed, instead of considering all pairwise combinations of loci. The implemented algorithm SNPrune considered bi-allelic loci either using phased alleles or allele counts as input. SNPrune was validated against PLINK on two datasets, using an r2 threshold of 0.99. The first dataset contained 52k SNP genotypes on 3534 pigs and the second dataset contained simulated whole-genome sequence data with 10.8 million SNPs and 2500 animals.ResultsSNPrune removed a similar number of SNPs as PLINK from the pig data but SNPrune was almost 12 times faster than PLINK. From the simulated sequence data with 10.8 million SNPs, SNPrune removed 6.4 and 1.4 million SNPs due to complete and high LD. Results were very similar regardless of whether phased alleles or allele counts were used. Using allele counts and multi-threading with 10 threads, SNPrune completed the analysis in 21 min. Using a sliding window of up to 500,000 SNPs, PLINK removed ~ 43,000 less SNPs (0.6%) in the sequence data and SNPrune was 24 to 170 times faster, using one or ten threads, respectively.ConclusionsThe SNPrune algorithm developed here is able to remove SNPs in high LD throughout the genome very efficiently in large datasets.

Calcium-Sensing Receptor Genotype and Response to Cinacalcet in Patients Undergoing Hemodialysis.

We tested the hypothesis that single nucleotide polymorphisms (SNPs) in the calcium-sensing receptor (CASR) alter the response to the calcimimetic cinacalcet. We analyzed DNA samples in the Evaluation of Cinacalcet HCl Therapy to Lower Cardiovascular Events (EVOLVE) trial, a randomized trial comparing cinacalcet to placebo on a background of usual care. Of the 3883 patients randomized, 1919 (49%) consented to DNA collection, and samples from 1852 participants were genotyped for 18 CASR polymorphisms. The European ancestry (EA; n=1067) and African ancestry (AfAn; n=405) groups were assessed separately. SNPs in CASR were tested for their association with biochemical measures of mineral metabolism at baseline, percent change from baseline to 20 weeks, and risk of clinical fracture as dependent variables. There were modest associations of CASR SNPs with increased baseline serum parathyroid hormone and bone alkaline phosphatase primarily with the minor allele in the EA group (all P≤0.03), but not in the AfAn sample. In contrast, there was a modest association of decreased baseline serum calcium and FGF23 with CASR SNPs (P=0.04) primarily with the minor allele in the AfAn but not in the EA sample. The minor allele of two SNPs was associated with decreased percent reduction in parathyroid hormone from baseline to 20 weeks in the EA population (P<0.04) and this was not altered with cinacalcet. In both EA and AfAn, the same SNP (rs9740) was associated with decreased calcium with cinacalcet treatment (EA and AfAn P≤0.03). Three SNPs in high linkage disequilibrium were associated with a higher risk of clinical fracture that was attenuated by cinacalcet treatment in the EA sample (P<0.04). These modest associations, if validated, may provide explanations for differences in CKD-mineral bone disorder observed in EA and AfAn populations, and for differential biochemical responses to calcimimetics.

Functional germline variants in driver genes of breast cancer.

Germline mutations in tumour suppressor genes cause various cancers. These genes are also somatically mutated in sporadic tumours. We hypothesized that there may also be cancer-related germline variants in the genes commonly mutated in sporadic breast tumours. After excluding the well-characterized breast cancer (BC) genes, we screened 15 novel genes consistently classified as BC driver genes in next-generation sequencing approaches for single nucleotide polymorphisms (SNPs). Altogether 40 SNPs located in the core promoter, 5'- and 3'-UTR or which were nonsynonymous SNPs were genotyped in 782 Swedish incident BC cases and 1,559 matched controls. After statistical analyses, further evaluations related to functional prediction and signatures of selection were performed. TBX3 was associated with BC risk (rs2242442: OR = 0.76, 95% CI 0.64-0.92, dominant model) and with less aggressive tumour characteristics. An association with BC survival and aggressive tumour characteristics was detected for the genes ATR (rs2227928: HR = 1.63; 95% CI 1.00-2.64, dominant model), RUNX1 (rs17227210: HR = 3.50, 95% CI 1.42-8.61, recessive model) and TTN (rs2303838: HR = 2.36; 95% CI 1.04-5.39; rs2042996: HR = 2.28; 95% CI 1.19-4.37, recessive model). According to the experimental ENCODE data all these SNPs themselves or SNPs in high linkage disequilibrium with them (r 2 ≥ 0.80) were located in regulatory regions. RUNX1 and TTN showed also several signatures of positive selection. The study gave evidence that germline variants in BC driver genes may have impact on BC risk and/or survival. Future studies could discover further germline variants in known or so far unknown driver genes which contribute to cancer development.

Genome-wide association study in takotsubo syndrome — Preliminary results and future directions

BackgroundTakotsubo syndrome (TS) is an acute non-ischemic cardiomyopathy characterized by transient regional systolic dysfunction of the left and/or right ventricle with still unknown etiology. The aim of the current study was to conduct for the first time a genome-wide association study (GWAS) in a cohort of TS patients to identify potential genetic risk variants. MethodsThis single-center study was conducted at the University Heart Center Lübeck from 2008 to 2016. DNA isolation was done according to standard protocols. Imputation of genotypes were performed at the Michigan Imputation Server (https://imputationserver.sph.umich.edu) using the 1000G Phase 3 v5 reference panel. ResultsThe study population consisted of 96 TS patients (91 females, 5 males) with a mean age of 71.9±10.4years and 475 healthy controls (268 males, 207 females). The results of GWAS analysis showed several promising candidate loci (68 loci after applying threshold of p<5∗10−4 and MAF>5%). Of these 68 loci, 18 loci contained top single nucleotide polymorphisms (SNPs) that were supported by SNPs in high Linkage Disequilibrium (r2>0.8) with p<10−3. Two out of the 18 loci contained SNP with hits in the GWAS catalog (traits: blood pressure, thyroid stimulating hormone). ConclusionThis first GWAS analysis in a larger cohort of patients with TS showed promising preliminary results. Further intensive research efforts of international collaborators are now necessary to enable deep-phenotyping of TS patients to ultimately assess a potential genetic cause of TS.

Transcription Factor KLF5 Binds a Cyclin E1 Polymorphic Intronic Enhancer to Confer Increased Bladder Cancer Risk.

A polymorphic KLF5 binding site near the CCNE1 gene explains genetic risk identified through GWAS. Mol Cancer Res; 14(11); 1078-86. ©2016 AACR.

A Genome-Wide Association Meta-Analysis of Attention-Deficit/Hyperactivity Disorder Symptoms in Population-Based Pediatric Cohorts

The aims of this study were to elucidate the influence of common genetic variants on childhood attention-deficit/hyperactivity disorder (ADHD) symptoms, to identify genetic variants that explain its high heritability, and to investigate the genetic overlap of ADHD symptom scores with ADHD diagnosis. Within the EArly Genetics and Lifecourse Epidemiology (EAGLE) consortium, genome-wide single nucleotide polymorphisms (SNPs) and ADHD symptom scores were available for 17,666 children (<13 years of age) from nine population-based cohorts. SNP-based heritability was estimated in data from the three largest cohorts. Meta-analysis based on genome-wide association (GWA) analyses with SNPs was followed by gene-based association tests, and the overlap in results with a meta-analysis in the Psychiatric Genomics Consortium (PGC) case-control ADHD study was investigated. SNP-based heritability ranged from 5% to 34%, indicating that variation in common genetic variants influences ADHD symptom scores. The meta-analysis did not detect genome-wide significant SNPs, but three genes, lying close to each other with SNPs in high linkage disequilibrium (LD), showed a gene-wide significant association (p values between 1.46× 10(-6) and 2.66× 10(-6)). One gene, WASL, is involved in neuronal development. Both SNP- and gene-based analyses indicated overlap with the PGC meta-analysis results with the genetic correlation estimated at 0.96. The SNP-based heritability for ADHD symptom scores indicates a polygenic architecture, and genes involved in neurite outgrowth are possibly involved. Continuous and dichotomous measures of ADHD appear to assess a genetically common phenotype. A next step is to combine data from population-based and case-control cohorts in genetic association studies to increase sample size and to improve statistical power for identifying genetic variants.

Functional Characterization of Schizophrenia-Associated Variation in CACNA1C.

Calcium channel subunits, including CACNA1C, have been associated with multiple psychiatric disorders. Specifically, genome wide association studies (GWAS) have repeatedly identified the single nucleotide polymorphism (SNP) rs1006737 in intron 3 of CACNA1C to be strongly associated with schizophrenia and bipolar disorder. Here, we show that rs1006737 marks a quantitative trait locus for CACNA1C transcript levels. We test 16 SNPs in high linkage disequilibrium with rs1007637 and find one, rs4765905, consistently showing allele-dependent regulatory function in reporter assays. We find allele-specific protein binding for 13 SNPs including rs4765905. Using protein microarrays, we identify several proteins binding ≥3 SNPs, but not control sequences, suggesting possible functional interactions and combinatorial haplotype effects. Finally, using circular chromatin conformation capture, we show interaction of the disease-associated region including the 16 SNPs with the CACNA1C promoter and other potential regulatory regions. Our results elucidate the pathogenic relevance of one of the best-supported risk loci for schizophrenia and bipolar disorder.

The association of JAK2 polymorphisms with prognosis in castration-resistant prostate cancer (CRPC).

313 Background: We evaluated variation in candidate genes implicated in either initiation or progression of prostate cancer with survival in CRPC stage. Methods: Germline DNA was extracted from peripheral blood mononuclear cells of CRPC patients enrolled in a clinically annotated registry. Fourteen candidate genes were tagged using single nucleotide polymorphisms (SNPs) from HapMap with minor allele frequency of &gt; 5%. The primary endpoint was overall survival (OS), defined as time from development of CRPC to death. Principal component analysis was used for gene levels tests of significance. For SNP level results the per allele hazard ratios (HR) and 95% confidence intervals (CI) under the additive allele model using Cox regression adjusted for age at CRCP and Gleason score (GS) were used. Results: Two hundred and forty five CRPC patients who met the criteria of having adequate DNA were genotyped (14 genes, 84 SNPs). The median age of the cohort was 69 years (range 43-93). The GS distribution was 55% with GS≥8, 32% with GS = 7 and 13% with GS &lt; 7 or unknown. Median time from castration resistance to death for the cohort was 2.67 years (IQ range: 1.6-4.07, 144 deaths). At the gene level JAK2 was detected to be associated with OS. Six of 18 JAK2 SNPs were associated with OS after adjustment for age and GS as well as pruning of SNPs in high linkage disequilibrium with each other (see table). In our multivariate model including age, GS, rs2149556, and rs4372063, the adjusted HRs for rs2149556 and rs4372063 were 0.67 (95% CI 0.38-1.18) and 2.17 (95% CI 1.25-3.76), respectively. The protective effect of rs2149556 appears after adjusting for the presence of minor alleles for rs4372063 in this dataset. Conclusions: Germline variation in the JAK2gene is associated with survival in CRPC stage and warrants further validation as a potential prognostic biomarker. [Table: see text]

Genomic structure and expression of the human serotonin 2A receptor gene (HTR2A) locus: identification of novel HTR2A and antisense (HTR2A-AS1) exons

BackgroundThe serotonin 2A receptor is widely implicated in genetic association studies and remains an important drug target for psychiatric, neurological, and cardiovascular conditions. RNA sequencing redefined the architecture of the serotonin 2A receptor gene (HTR2A), revealing novel mRNA transcript isoforms utilizing unannotated untranslated regions of the gene. Expression of these untranslated regions is modulated by common single nucleotide polymorphisms (SNPs), namely rs6311. Previous studies did not fully capture the complexity of the sense- and antisense-encoded transcripts with respect to novel exons in the HTR2A gene locus. Here, we comprehensively catalogued exons and RNA isoforms for both HTR2A and HTR2A-AS1 using RNA-Seq from human prefrontal cortex and multiple mouse tissues. We subsequently tested associations between expression of newfound gene features and common SNPs in humans.ResultsWe find that the human HTR2A gene spans ~66 kilobases and consists of 7, rather than 4 exons. Furthermore, the revised human HTR2A-AS1 gene spans ~474 kilobases and consists of 18, rather than 3 exons. Three HTR2A exons directly overlap with HTR2A-AS1 exons, suggesting potential for complementary nucleotide interactions. The repertoire of possible mouse Htr2a splice isoforms is remarkably similar to humans and we also find evidence for overlapping sense-antisense transcripts in the same relative positions as the human transcripts. rs6311 and SNPs in high linkage disequilibrium are associated with HTR2A-AS1 expression, in addition to previously described associations with expression of the extended 5’ untranslated region of HTR2A.ConclusionsOur proposed HTR2A and HTR2A-AS1 gene structures dramatically differ from current annotations, now including overlapping exons on the sense and anti-sense strands. We also find orthologous transcript isoforms expressed in mice, providing opportunities to elucidate the biological roles of the human isoforms using a model system. Associations between rs6311 and expression of HTR2A and HTR2A-AS1 suggest this polymorphism is capable of modulating the expression of the sense or antisense transcripts. Still unclear is whether these SNPs act directly on the expression of the sense or antisense transcripts and whether overlapping exons are capable of interacting through complimentary base-pairing. Additional studies are necessary to determine the extent and nature of interactions between the SNPs and the transcripts prior to interpreting these findings in the context of phenotypes associated with HTR2A.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-015-0325-6) contains supplementary material, which is available to authorized users.

Making sense of GWAS: using epigenomics and genome engineering to understand the functional relevance of SNPs in non-coding regions of the human genome.

Considerable progress towards an understanding of complex diseases has been made in recent years due to the development of high-throughput genotyping technologies. Using microarrays that contain millions of single-nucleotide polymorphisms (SNPs), Genome Wide Association Studies (GWASs) have identified SNPs that are associated with many complex diseases or traits. For example, as of February 2015, 2111 association studies have identified 15,396 SNPs for various diseases and traits, with the number of identified SNP-disease/trait associations increasing rapidly in recent years. However, it has been difficult for researchers to understand disease risk from GWAS results. This is because most GWAS-identified SNPs are located in non-coding regions of the genome. It is important to consider that the GWAS-identified SNPs serve only as representatives for all SNPs in the same haplotype block, and it is equally likely that other SNPs in high linkage disequilibrium (LD) with the array-identified SNPs are causal for the disease. Because it was hoped that disease-associated coding variants would be identified if the true casual SNPs were known, investigators have expanded their analyses using LD calculation and fine-mapping. However, such analyses also identified risk-associated SNPs located in non-coding regions. Thus, the GWAS field has been left with the conundrum as to how a single-nucleotide change in a non-coding region could confer increased risk for a specific disease. One possible answer to this puzzle is that the variant SNPs cause changes in gene expression levels rather than causing changes in protein function. This review provides a description of (1) advances in genomic and epigenomic approaches that incorporate functional annotation of regulatory elements to prioritize the disease risk-associated SNPs that are located in non-coding regions of the genome for follow-up studies, (2) various computational tools that aid in identifying gene expression changes caused by the non-coding disease-associated SNPs, and (3) experimental approaches to identify target genes of, and study the biological phenotypes conferred by, non-coding disease-associated SNPs.

An in silico Approach Reveals Associations between Genetic and Epigenetic Factors within Regulatory Elements in B Cells from Primary Sjögren's Syndrome Patients.

Recent advances in genetics have highlighted several regions and candidate genes associated with primary Sjögren’s syndrome (SS), a systemic autoimmune epithelitis that combines exocrine gland dysfunctions, and focal lymphocytic infiltrations. In addition to genetic factors, it is now clear that epigenetic deregulations are present during SS and restricted to specific cell type subsets, such as lymphocytes and salivary gland epithelial cells. In this study, 72 single nucleotide polymorphisms (SNPs) associated with 43 SS gene risk factors were selected from publicly available and peer reviewed literature for further in silico analysis. SS risk variant location was tested revealing a broad distribution in coding sequences (5.6%), intronic sequences (55.6%), upstream/downstream genic regions (30.5%), and intergenic regions (8.3%). Moreover, a significant enrichment of regulatory motifs (promoter, enhancer, insulator, DNAse peak, and expression quantitative trait loci) characterizes SS risk variants (94.4%). Next, screening SNPs in high linkage disequilibrium (r2 ≥ 0.8 in Caucasians) revealed 645 new variants including 5 SNPs with missense mutations, and indicated an enrichment of transcriptionally active motifs according to the cell type (B cells > monocytes > T cells ≫ A549). Finally, we looked at SS risk variants for histone markers in B cells (GM12878), monocytes (CD14+) and epithelial cells (A548). Active histone markers were associated with SS risk variants at both promoters and enhancers in B cells, and within enhancers in monocytes. In conclusion and based on the obtained in silico results that need further confirmation, associations were observed between SS genetic risk factors and epigenetic factors and these associations predominate in B cells, such as those observed at the FAM167A–BLK locus.