Genome-wide Significance Threshold Research Articles

Whole Exome Sequencing Reveals the Major Genetic Contributors to Nonsyndromic Tetralogy of Fallot

Familial recurrence studies provide strong evidence for a genetic component to the predisposition to sporadic, nonsyndromic Tetralogy of Fallot (TOF), the most common cyanotic congenital heart disease phenotype. Rare genetic variants have been identified as important contributors to the risk of congenital heart disease, but relatively small numbers of TOF cases have been studied to date. We used whole exome sequencing to assess the prevalence of unique, deleterious variants in the largest cohort of nonsyndromic TOF patients reported to date. Eight hundred twenty-nine TOF patients underwent whole exome sequencing. The presence of unique, deleterious variants was determined; defined by their absence in the Genome Aggregation Database and a scaled combined annotation-dependent depletion score of ≥20. The clustering of variants in 2 genes, NOTCH1 and FLT4, surpassed thresholds for genome-wide significance (assigned as P<5×10-8) after correction for multiple comparisons. NOTCH1 was most frequently found to harbor unique, deleterious variants. Thirty-one changes were observed in 37 probands (4.5%; 95% CI, 3.2%-6.1%) and included 7 loss-of-function variants 22 missense variants and 2 in-frame indels. Sanger sequencing of the unaffected parents of 7 cases identified 5 de novo variants. Three NOTCH1 variants (p.G200R, p.C607Y, and p.N1875S) were subjected to functional evaluation, and 2 showed a reduction in Jagged1-induced NOTCH signaling. FLT4 variants were found in 2.4% (95% CI, 1.6%-3.8%) of TOF patients, with 21 patients harboring 22 unique, deleterious variants. The variants identified were distinct to those that cause the congenital lymphoedema syndrome Milroy disease. In addition to NOTCH1, FLT4 and the well-established TOF gene, TBX1, we identified potential association with variants in several other candidates, including RYR1, ZFPM1, CAMTA2, DLX6, and PCM1. The NOTCH1 locus is the most frequent site of genetic variants predisposing to nonsyndromic TOF, followed by FLT4. Together, variants in these genes are found in almost 7% of TOF patients.

Genome-wide Significance Thresholds for Admixture Mapping Studies

Admixture mapping studies have become more common in recent years, due in part to technological advances and growing international efforts to increase the diversity of genetic studies. However, many open questions remain about appropriate implementation of admixture mapping studies, including how best to control for multiple testing, particularly in the presence of population structure. In this study, we develop a theoretical framework to characterize the correlation of local ancestry and admixture mapping test statistics in admixed populations with contributions from any number of ancestral populations and arbitrary population structure. Based on this framework, we develop an analytical approach for obtaining genome-wide significance thresholds for admixture mapping studies. We validate our approach via analysis of simulated traits with real genotype data for 8,064 unrelated African American and 3,425 Hispanic/Latina women from the Women's Health Initiative SNP Health Association Resource (WHI SHARe). In an application to these WHI SHARe data, our approach yields genome-wide significant p value thresholds of 2.1× 10-5 and 4.5× 10-6 for admixture mapping studies in the African American and Hispanic/Latina cohorts, respectively. Compared to other commonly used multiple testing correction procedures, our method is fast, easy to implement (using our publicly available R package), and controls the family-wise error rate even in structured populations. Importantly, we note that the appropriate admixture mapping significance threshold depends on the number of ancestral populations, generations since admixture, and population structure of the sample; as a result, significance thresholds are not, in general, transferable across studies.

Pandemrix-induced narcolepsy is associated with genes related to immunity and neuronal survival.

BackgroundThe incidence of narcolepsy rose sharply after the swine influenza A (H1N1) vaccination campaign with Pandemrix. Narcolepsy is an immune-related disorder with excessive daytime sleepiness. The most frequent form is strongly associated with HLA-DQB1*06:02, but only a minority of carriers develop narcolepsy. We aimed to identify genetic markers that predispose to Pandemrix-induced narcolepsy.MethodsWe tested for genome-wide and candidate gene associations in 42 narcolepsy cases and 4981 controls. Genotyping was performed on Illumina arrays, HLA alleles were imputed using SNP2HLA, and single nucleotide polymorphisms were imputed using the haplotype reference consortium panel. The genome-wide significance threshold was p < 5 × 10−8, and the nominal threshold was p < 0.05. Results were replicated in 32 cases and 7125 controls. Chromatin data was used for functional annotation.FindingsCarrying HLA-DQB1*06:02 was significantly associated with narcolepsy, odds ratio (OR) 39.4 [95% confidence interval (CI) 11.3, 137], p = 7.9 × 10−9. After adjustment for HLA, GDNF-AS1 (rs62360233) was significantly associated, OR = 8.7 [95% CI 4.2, 17.5], p = 2.6 × 10−9, and this was replicated, OR = 3.4 [95% CI 1.2–9.6], p = 0.022. Functional analysis revealed variants in high LD with rs62360233 that might explain the detected association. The candidate immune-gene locus TRAJ (rs1154155) was nominally associated in both the discovery and replication cohorts, meta-analysis OR = 2.0 [95% CI 1.4, 2.8], p = 0.0002.InterpretationWe found a novel association between Pandemrix-induced narcolepsy and the non-coding RNA gene GDNF-AS1, which has been shown to regulate expression of the essential neurotrophic factor GDNF. Changes in regulation of GDNF have been associated with neurodegenerative diseases. This finding may increase the understanding of disease mechanisms underlying narcolepsy. Associations between Pandemrix-induced narcolepsy and immune-related genes were replicated.

A simple and accurate method to determine genomewide significance for association tests in sequencing studies.

Whole-exome sequencing (WES) and whole-genome sequencing (WGS) studies are underway to investigate the impact of genetic variants on complex diseases and traits. It is customary to perform single-variant association tests for common variants and region-based association tests for rare variants. The latter may target variants with similar or opposite effects, interrogate variants with different frequencies or different functional annotations, and examine a variety of regions. The large number of tests that are performed necessitates adjustment for multiple testing. The conventional Bonferroni correction is overly conservative as the test statistics are correlated. To address this challenge, we propose a simple and accurate method based on parametric bootstrap to assess genomewide significance. We show that the correlations of the test statistics are determined primarily by the genotypes, such that the same significance threshold can be used in different studies that share a common sequencing platform. We demonstrate the usefulness of the proposed method with WES data from the National Heart, Lung, and Blood Institute Exome Sequencing Project and WGS data from the 1000 Genomes Project. We recommend the p value of as the genomewide significance threshold for testing all common and low-frequency variants (MAFs 0.1%) in the human genome.

Genome-wide association study in two populations to determine genetic variants associated with Toxoplasma gondii infection and relationship to schizophrenia risk

T. gondii (TOXO) infects over one billion people worldwide, yet the literature lacks a Genome Wide Association Study (GWAS) focused on genetic variants controlling the persistence of TOXO infection.To identify putative T. gondii susceptibility genes, we performed a GWAS using IgG seropositivity as the outcome variable in a discovery sample (n = 790) from an Ashkenazi dataset, and a second sample of predominately African Americans (The Grady Trauma Project, n = 285). We also performed a meta-analyses of the 2 cohorts.None of the SNPs in these analyses was statistically significant after Bonferroni correction for multiple comparisons. In the Ashkenazi population, the gene region of CHIA (chitinase) showed the most nominally significant association with TOXO. Prior studies have shown that the production of chitinase by macrophages in the brain responding to TOXO infection is crucial for controlling the burden of T. gondii cysts. We found a surprising number of genes involved in neurodevelopment and psychiatric disorders among our top hits even though our outcome variable was TOXO infection. In the meta-analysis combining the Ashkenazi and Grady Trauma Project samples, there was enrichment for genes implicated in schizophrenia spectrum disorders (p < .05). Upon limiting our sample to those without mental illness, two schizophrenia related genes (CNTNAP2, GABAR2) still had significant TOXO–associated variants at the p < .05 level, but did not pass the genome wide significance threshold after correction for multiple comparisons.Using Ingenuity Systems molecular network analysis, we identified molecular nodes suggesting that while different genetic variants associated with TOXO in the two population samples, the molecular pathways for TOXO susceptibility nevertheless converged on common pathways. Molecular nodes in these common pathways included NOTCH1, CD44, and RXRA. Prior studies show that CD44 participates in TOXO-induced immunopathology and that RXRA is instrumental in regulating T-helper immune responses. These data provide new insights into the pathophysiology of this common neurotropic parasite.

Collaborative Genome-Wide Association and Copy Number Variation Analysis of Tourette Syndrome

Tourette Syndrome (TS) is a childhood-onset developmental disorder that has one of the highest heritabilities among neuropsychiatric diseases with non-Mendelian inheritance. However, no definitive TS susceptibility genes have been identified to date. We have previously demonstrated that TS is highly polygenic, and that 30-50% of TS heritability can be captured by SNP genotyping arrays.Here, we present the most recent results from the current TS genome-wide association study (GWAS) and copy number variant (CNV) analyses. In the current TS GWAS mega-analysis of 4232 European ancestry TS cases and 8318 ancestry matched controls, one locus on chromosome 2p16 surpassed the genome-wide significant threshold (rs2708146, p=5.1x10-8). This SNP lies within a large 1Mb haplotype containing one transcript, LINC01122, an uncharacterized long, intergenic, non-coding RNA (lincRNA), that is expressed primarily in mid-fetal human brain development (15-16 pcw), with strongest expression in developing cerebral cortex. Pairwise correlational analysis of Brainspan project data across pre-natal time points identified the highest co-expression of LINC01122 with BCL11A, a gene 1 Mb centromeric to LINC01122 that has been found previously to harbor recurrent de novo loss-of-function mutations in individuals with autism-spectrum disorder. Subsequent analyses demonstrate that LINC01122 and BCL11A lie within the same topologically-associated domain (TAD) in human fetal cortex, suggesting that both transcripts are co-regulated.In the CNV analysis of 2,434 European ancestry TS cases and 4,093 ancestry matched controls, we identified a significant global burden of rare (<1% frequency) genic CNVs that was most pronounced in large (>1 Mb), singleton CNVs (OR 2.28 [1.39-3.79], p=1.2x10-3) and in CNVs previously classified as pathogenic by the American College of Medical Genetics (OR 3.03 [1.85-5.07], p=1.5x10-5). Two individual CNV loci surpassed genome-wide significance both for point-wise and gene-based tests, as determined empirically by permutations: deletions in NRXN1-alpha (Pseg=7.0x10-6; Pseg-corr=1.0x10-3; OR 20.3[2.6-156.2]) and duplications across CNTN6 (Pseg=5.4x10-5, Pseg-corr=6.9x10-3; OR=10.1 [2.3-45.4]). 1% of TS cases carried one of these two CNVs, with an additional 0.5% harboring an ACMG pathogenic CNV outside these two loci.In conclusion, we present evidence for one GWAS locus and two rare CNVs that exceed the genome-wide significance threshold, representing the first convincing TS susceptibility loci. The members of this symposium are now preparing for large-scale meta-analyses of GWAS and CNV datasets from 5 international TS genetics consortia in 13,000 TS cases and 37,000 controls.

SU22 - BIVARIATE GAUSSIAN MIXTURE MODEL FOR GWAS SUMMARY STATISTICS

Background Identifying shared genetics is important as it uncovers hidden relationship between complex traits and improves our understanding of disease etiology. Today genetic correlation is commonly used as the principal measure that quantifies genetic overlap. Available methods can calculate genetic correlation from raw genotypes (restricted maximum likelihood, polygenic risk scores), from a set of Single-Nucleotide Polymorphisms (SNPs) that pass genome-wide significance threshold (Mendelian Randomization), or utilizing all data from Genome Wide Association Studies (GWASes) including SNPs that do not reach genome-wide significance (Cross-Trait Linkage Disequilibrium (LD) Score Regression). These methods for evaluating genetic overlap are unable to capture a mixture of effect directions across shared genetic variants (i.e., only reporting overall positive, negative or no genetic correlations), while recent analyses suggest that correlation across polygenic traits in the effect size and directionality of a SNP is not the same across all SNPs. Methods Bivariate Gaussian Mixture Model provides a novel way to detect and quantify shared genetics independently from genetic correlation. In the absence of genetic correlation we use another measure of polygenic overlap, expressed as the proportion of SNPs associated with both traits. To estimate this quantity, we model true per-SNP effect sizes as a mixture of four bivariate normal distributions: two causal components specific to each trait, one causal component of SNPs affecting both traits, and a null component of SNPs with no effect on either trait. We interpret the weight of each component in the mixture as the proportion of SNPs in that component. The parameters of the mixture model are estimated from the summary statistics data by direct optimization of the maximum likelihood. Our statistical model relates observed signed test statistics (GWAS z-scores) to the underlying per-SNP effect sizes, incorporating effects of LD structure, minor allele frequency, sample size, cryptic relationships / sample stratification, and sample overlap, to capture all these effects on GWAS z-scores. Results We show in simulations that our model differentiates cases with no polygenic overlap versus cases with significant overlap in the absence of genetic correlation. We show genetic overlap between schizophrenia, waist-hip-ratio and triglycerides, despite the fact that genetic correlation is close to zero. We apply our model to schizophrenia, bipolar disorder and IQ data, and show that in the presence of genetic correlation our model reports consistent results with those from cross-trait LD score regression. Discussion It appears to be a common practice to interpret the lack of genetic correlation as no relation between traits. However, lack of correlation does not necessarily imply independence - a fact well known from statistics. Thus, we advocate that certain important cases of genetic overlap are not captured by genetic correlation. Our model quantifies genetic overlap between traits both with and without genetic correlation. It controls for the fact that if both traits are highly polygenic then some proportion of SNPs is associated with both traits by chance or due to LD structure. In addition to the insights into genetic architecture our model can improve SNP discovery, by estimating posterior effect size of one trait given observed GWAS z-score in another trait. Further, more accurately estimated effect sizes can be used for improving polygenic risk scores.

Genome wide association study to identify predictors for severe skin toxicity in colorectal cancer patients treated with cetuximab.

EGFR-antibodies are associated with significant skin toxicity, including acneiform rash and folliculitis. It remains impossible to predict the occurrence of severe skin toxicity due to the lack of predictive markers. Here, we present the first genome-wide association study (GWAS) to find single nucleotide polymorphisms (SNPs) associated with EGFR inhibitor-induced skin toxicity using data of the multicentre randomized phase III CAIRO2 trial (clinicaltrials.gov NCT00208546). In this study, advanced or metastatic colorectal cancer patients were treated with capecitabine, oxaliplatin and bevacizumab with or without cetuximab. Germline DNA was available in 282 of the 368 patients in the cetuximab arm. Mild skin toxicity occurred in 195 patients (i.e. CTC grade 1 or 2, respectively 91 and 104 patients) and severe skin toxicity (i.e. grade 3) in 36 patients. Grade 4 skin toxicity did not occur. None of the SNPs reached the formal genome wide threshold for significance of 5x10-8, though SNPs of at least 8 loci did show moderate association (p-value between 5x10-7 and 5x10-5) with the occurrence of grade 3 (severe) skin toxicity. These SNPs did not overlap with SNPs associated with cetuximab efficacy as found in a previous GWAS in the same CAIRO2 cohort. If formally proven by replication, the SNPs associated with severe EGFR induced skin toxicity may be helpful to predict the occurrence and severity of skin toxicity in patients that will receive cetuximab and allow for adequate information on the risk of skin toxicity and prophylactic measurements.

Genome-wide association study of equine herpesvirus type 1-induced myeloencephalopathy identifies a significant single nucleotide polymorphism in a platelet-related gene

Equine herpesvirus type 1 (EHV-1)-induced myeloencephalopathy (EHM) is a neurologic disease of horses that represents one outcome of infection. The neurologic form of disease occurs in a subset of infected horses when virus-induced endothelial cell damage triggers vasculitis and subsequent ischemic insult to the central nervous system. EHM causes considerable animal suffering and economic loss for the horse industry. Virus polymorphisms have been previously associated with disease outcome but cannot fully explain why only some horses develop EHM. This study investigated the role of host genetics in EHM. DNA samples were collected from 129 horses infected with EHV-1 (61 that developed EHM and 68 in which disease resolved without the development of neurologic signs) during natural outbreaks or experimental infections. A genome-wide association study (GWAS) was performed to investigate host genetic variations associated with EHM. Genotyping was performed using the Illumina SNP50 and SNP70 arrays and a custom Sequenom array.Mixed linear model (MLM) analysis using a recessive model identified one marker that surpassed the threshold for genome-wide significance (P<0.001) after Bonferroni correction. The marker (BIEC2_946397) is in an intron of the tetraspanin 9 (TSPAN9) gene, which is expressed in endothelial cells and platelets. The GWAS identified a region in the horse genome that is associated with EHM in the sample population and thus warrants further exploration. Understanding the contribution of host genetic variation to the development of EHM will enhance our knowledge of disease pathophysiology, and lead to improved strategies for treating individual cases and managing outbreaks.

Genome-Wide Association Study (GWAS) Identifies a Significant Acute Myeloid Leukemia (AML) Susceptibility Locus Near BICRA

Introduction: AML is the most common form of acute leukemia in adults, but hereditary predisposition to AML has been insufficiently studied. To date, investigations of AML heritability have focused on families with a clear history of AML and identified rare highly penetrant germline mutations that segregate with disease. However, the role of common polymorphisms in susceptibility to AML is not clear. We therefore conducted the first large-scale GWAS to identify risk alleles for adult de novo AML.Methods: Whole-genome genotyping was performed on two independent American case-control sets, using Illumina Infinium Omni-1 Quad-bead arrays. GWAS quality control measures consisted of excluding samples with <94% genotyping yield or <90% European ancestry, and variants with <94% yield, differences among batches or significant (P<10-6) deviation from Hardy-Weinberg equilibrium. Phasing and imputation yielded a total of 16,058,266 autosomal variants. Association tests were performed using logistic regression including age, sex, and ten principal components as co-variates. Selected variants were genotyped in a German validation case-control set using an Agena MassARRAY System. Results were combined using METAL with fixed effects. P<5x10-8 was considered the threshold for genome-wide significance.Results: Two separate GWASs were performed in a total of 1,183 American AML patients from the Alliance for Clinical Trials in Oncology and 2,369 population- and age-matched controls from independent case-control sets (USA1: 894 cases and 1,714 controls; USA2: 289 cases and 655 controls). After combining the results from these two data sets in a meta-analysis, five independent loci with a total of 11 polymorphisms were suggestively associated with AML (P<10-6), located at: 1q41 (P=7.2x10-7), 13q22.1 (P=3.1x10-7), 18q22.3 (P=7.4x10-7), 19p13.11 (P=4.0x10-7) and 19q13.33 (P=3.0x10-7) (Figure 1). Six variants with the lowest P-values from three loci (13q22.1, 19p13.11 and 19q13.33) were selected and genotyped in an additional 350 German patient samples and compared with 1,600 population- and age-matched controls from the German LIFE-Adult study. In the German sample set alone, both the 19p13.11 and the 19q13.33 loci showed support for association with AML (P<0.05). Results from the three independent sample sets were combined in an overall meta-analysis to calculate the final odds ratios (ORs) and significance (Table 1). The overall P-value for the 19q13.33 variant, rs75797233, was 4.15x10-8 (OR=2.28), which meets the threshold for genome-wide significance (P<5x10-8), making it the first reported common germline variant significantly associated with AML risk, with a risk allele frequency (RAF) in the cases of 3.1% compared to a RAF of 1.8% in the controls.rs75797233 is located 13kb 5′ of the BICRA gene, which encodes a key component in a newly described SWI/SNF chromatin remodeling complex that can impact on cancer cell proliferation. GTEx expression data revealed that individuals who have the rs75797233 AML risk allele (thymine [T]) have significantly lower expression of BICRA in whole blood samples compared with individuals who are homozygous for the non-risk rs75797233 allele (adenine [A]; P=0.0002). As rs75797233 is located in a region of open chromatin marked by histone H3 lysine 4 mono-methylation, we examined ENCODE chromatin immunoprecipitation sequencing (ChIP-seq) data for transcription factor binding. Indeed, the GATA2 transcription factor showed a clear ChIP-seq binding peak that encompassed rs75797233 and the surrounding region. Analysis of transcription factor motifs using MotifbreakR indicated that when the non-risk allele of rs75797233 (A) is present it is in a critical position of a GATA2 binding site; however, GATA2 is not able to bind to this site when the rs75797233 risk allele (T) is present (Figure 2).Conclusions: Our study sheds light on the lower-penetrance heritability of AML and identifies rs75797233 as the first common AML risk allele. rs75797233 might associate with AML risk through mechanisms involving regulation of BICRA by GATA2, and ongoing characterization of the risk locus could yield novel insights into AML disease susceptibility. DisclosuresKolitz:Magellan Health: Consultancy, Honoraria. Powell:Rafael Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Wang:Amgen: Consultancy; Amgen: Consultancy; Jazz: Speakers Bureau; Jazz: Speakers Bureau; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Speakers Bureau; Novartis: Speakers Bureau; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Niederwieser:Miltenyi: Speakers Bureau; Novartis: Research Funding.

Unravelling the genetic loci for growth and carcass traits in Chinese Bamaxiang pigs based on a 1.4 million SNP array.

Bamaxiang pig is from Guangxi province in China, characterized by its small body size and two-end black coat colour. It is an important indigenous breed for local pork market and excellent animal model for biomedical research. In this study, we performed genomewide association studies (GWAS) on 43 growth and carcass traits in 315 purebred Bamaxiang pigs based on a 1.4million SNP array. We observed considerable phenotypic variability in the growth and carcass traits in the Bamaxiang pigs. The corresponding SNP based heritability varied greatly across the 43 traits and ranged from 9.0% to 88%. Through a conditional GWAS, we identified 53 significant associations for 35 traits at p value threshold of 10-6 . Among which, 26 associations on chromosome 3, 7, 14 and X passed a genomewide significance threshold of 5×10-8 . The most remarkable loci were at around 30.6Mb on chromosome 7, which had growth stage-dependent effects on body lengths and cannon circumferences and showed large effects on multiple carcass traits. We discussed HMGA1 NUDT3, EIF2AK1, TMEM132C and AFF2 that near the lead SNP of significant loci as plausible candidate genes for corresponding traits. We also showed that including phenotypic covariate in GWAS can help to reveal additional significant loci for the target traits. The results provide insight into the genetic architecture of growth and carcass traits in Bamaxiang pigs.

Abstract 17111: Genetic Influences on Human Plasma Metabolites That Determine Mortality in Heart Failure Patients

Background: Heart failure with reduced ejection fraction (HFrEF) continues to be a global health burden. We recently reported a strong association of plasma metabolite profile (thirteen different metabolites) with survival among patients with HFrEF but the mechanism of this association is unclear. We studied the genetic associations of plasma metabolite to try to illuminate the disease mechanisms at work. Methods: A prospective genetic registry including 1032 HFrEF with genome-wide genotyping and imputation of single nucleotide polymorphisms (SNP; ~7 millions) and targeted metabolomics profiling. Genome-wide (GW) association analyses were performed to investigate the genetic impact of each SNP on the 13 metabolites of interest. Analyses were performed using linear models stratified by race (European Americans [N=516] and African Americans [N=516] and including the top five principal components (PC) for each population to avoid spurious associations due to population stratification. A fixed-effect meta-analysis was then used to combine results from the two populations. Threshold for GW significance was p&lt;5E-8. As a second step, Cox proportional hazard regression models of overall survival were tested for each SNP that met GW significance. Results: We found at least one SNP reaching GW significance for 6 metabolites metabolites (a-KG, C5.Isovaleryl, Fumarate, Leucine, Succinate and X3.HBA). The most significant SNP (rs77836784, an intronic variant within PACRG) was associated with X3.HBA in African American HF patients (Beta estimate=22.82, P-value=7.14E-14). A cross-checking of SNP associations on both metabolites and HF survival identified 13 independent SNPs that may partially explain the contribution of the metabolites on HF mortality (Table 1) and seem to have biologic plausibility including for example a G-protein coupled receptor (GPR68) and protein kinase C (PRKC1). Conclusion: Genetic variants are associated with predictive plasma metabolites and survival. This may be useful to understand the underlying pathways connecting metabolites to HF progression. A complete investigation of genomic and metabolomics determinants including causal mediation and pathway analyses are on-going.

Bayesian statistical methods in genetic association studies: Empirical examination of statistically non-significant Genome Wide Association Study (GWAS) meta-analyses in cancers: A systematic review

A Bayesian statistical method was developed to assess the noteworthiness of a single nucleotide polymorphism (SNP)-phenotype association that shows statistical significance in various observational studies, but it has seldom been applied to GWAS meta-analyses in cancers. Data (i.e. allelic frequency, odds ratio, 95% confidence interval, etc.) on various SNP-cancer associations were extracted from meta-analysis of GWAS and the National Human Genome Research Institute (NHGRI) Catalog of Published GWAS and were used to compute the false positive report probability (FPRP) and Bayesian false discovery probability (BFDP) to evaluate the noteworthiness of SNP-cancer associations. Independent paired t-tests showed a direct relationship between SNP-cancer P-values and both FPRP and BFDP estimates. However, a discrepancy in the number of noteworthy associations between P-value comparison and either FPRP or BFDP was found using data extracted from meta-analyses of GWAS and the GWAS Catalog. Most P-values of associations with nonsignificant P-values but with noteworthy FPRP and BFDP estimates were within the range of 10−6 to 5 × 10−8. A poorly selected genome-wide significance threshold and inclusion of a nonsignificant SNP-phenotype association into the noteworthy test can, with either noteworthy FPRP or BFDP computation, give a false impression of noteworthiness for a nonsignificant association.

Genome-wide association study of brain amyloid deposition as measured by Pittsburgh Compound-B (PiB)-PET imaging

Deposition of amyloid plaques in the brain is one of the two main pathological hallmarks of Alzheimer’s disease (AD). Amyloid positron emission tomography (PET) is a neuroimaging tool that selectively detects in vivo amyloid deposition in the brain and is a reliable endophenotype for AD that complements cerebrospinal fluid biomarkers with regional information. We measured in vivo amyloid deposition in the brains of ~1000 subjects from three collaborative AD centers and ADNI using 11C-labeled Pittsburgh Compound-B (PiB)-PET imaging followed by meta-analysis of genome-wide association studies, first to our knowledge for PiB-PET, to identify novel genetic loci for this endophenotype. The APOE region showed the most significant association where several SNPs surpassed the genome-wide significant threshold, with APOE*4 being most significant (P-meta = 9.09E-30; β = 0.18). Interestingly, after conditioning on APOE*4, 14 SNPs remained significant at P < 0.05 in the APOE region that were not in linkage disequilibrium with APOE*4. Outside the APOE region, the meta-analysis revealed 15 non-APOE loci with P < 1E-05 on nine chromosomes, with two most significant SNPs on chromosomes 8 (P-meta = 4.87E-07) and 3 (P-meta = 9.69E-07). Functional analyses of these SNPs indicate their potential relevance with AD pathogenesis. Top 15 non-APOE SNPs along with APOE*4 explained 25–35% of the amyloid variance in different datasets, of which 14–17% was explained by APOE*4 alone. In conclusion, we have identified novel signals in APOE and non-APOE regions that affect amyloid deposition in the brain. Our data also highlights the presence of yet to be discovered variants that may be responsible for the unexplained genetic variance of amyloid deposition.

Identification of genetic risk factors of aggressive periodontitis using genomewide association studies in association with those of chronic periodontitis.

To identify the genetic risk factors for aggressive periodontitis (AgP), it is important to understand the progression and pathogenesis of AgP. The purpose of this review was to summarize the genetic risk factors for AgP identified through a case-control genomewide association study (GWAS) and replication study. The initial studies to identify novel AgP risk factors were potentially biased because they relied on previous studies. To overcome this kind of issue, an unbiased GWAS strategy was introduced to identify genetic risk factors for various diseases. Currently, three genes glycosyltransferase 6 domain containing 1 (GLT6D1), defensin α1 and α3 (DEFA1A3), and sialic acid-binding Ig-like lectin 5 (SIGLEC5) that reach the threshold for genomewide significance have been identified as genetic risk factors for AgP through a case-control GWAS.

Association of the CYP4V2 polymorphism rs13146272 with venous thromboembolism in a Chinese population

Genome-wide association studies have identified the CYP4V2 polymorphism (rs13146272) as a risk factor associated with venous thromboembolism (VTE). However, due to the small sample size and variance in genetic analysis models, the relationship between VTE and rs13146272 remains unclear. Here, we performed a case–control study to analyse the associations between rs13146272 and VTE in a Chinese population and to compare the differences among various ethnicities. In this study, 226 VTE patients and 205 healthy controls were recruited, and the allele frequency of variant rs13146272 was analysed by a MassARRAY SNP genotyping assay. In addition, 9 case–control cohorts from 5 studies involving 6667 VTE-affected individuals and 8716 control subjects were included in this meta-analysis. Pooled ORs and 95% CIs were calculated to assess the association between rs13146272 and VTE by using different genetic models. Our case–control study results showed that there was no significant association between VTE and rs13146272 under the additive model (OR = 0.92, 95% CIs: 0.70–1.21, p = 0.55) in this Chinese population. However, the results of the meta-analysis performed by merging all cohorts showed that rs13146272 was significantly associated with VTE under the additive model, recessive model and dominant model. In the additive and recessive models, the association reached the threshold for genome-wide significance (p < 5.0e−08). In conclusion, our pooled systematic study results indicated that individuals with the A allele had a higher risk of developing VTE than those with the C allele of the rs13146272 variant, but the risk was inconsistent among different ethnicities. Further validation of this association with larger sample sizes and multiple ethnicities is warranted.

Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain.

Back pain is the #1 cause of years lived with disability worldwide, yet surprisingly little is known regarding the biology underlying this symptom. We conducted a genome-wide association study (GWAS) meta-analysis of chronic back pain (CBP). Adults of European ancestry were included from 15 cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and from the UK Biobank interim data release. CBP cases were defined as those reporting back pain present for ≥3–6 months; non-cases were included as comparisons (“controls”). Each cohort conducted genotyping using commercially available arrays followed by imputation. GWAS used logistic regression models with additive genetic effects, adjusting for age, sex, study-specific covariates, and population substructure. The threshold for genome-wide significance in the fixed-effect inverse-variance weighted meta-analysis was p<5×10−8. Suggestive (p<5×10−7) and genome-wide significant (p<5×10−8) variants were carried forward for replication or further investigation in the remaining UK Biobank participants not included in the discovery sample. The discovery sample comprised 158,025 individuals, including 29,531 CBP cases. A genome-wide significant association was found for the intronic variant rs12310519 in SOX5 (OR 1.08, p = 7.2×10−10). This was subsequently replicated in 283,752 UK Biobank participants not included in the discovery sample, including 50,915 cases (OR 1.06, p = 5.3×10−11), and exceeded genome-wide significance in joint meta-analysis (OR 1.07, p = 4.5×10−19). We found suggestive associations at three other loci in the discovery sample, two of which exceeded genome-wide significance in joint meta-analysis: an intergenic variant, rs7833174, located between CCDC26 and GSDMC (OR 1.05, p = 4.4×10−13), and an intronic variant, rs4384683, in DCC (OR 0.97, p = 2.4×10−10). In this first reported meta-analysis of GWAS for CBP, we identified and replicated a genetic locus associated with CBP (SOX5). We also identified 2 other loci that reached genome-wide significance in a 2-stage joint meta-analysis (CCDC26/GSDMC and DCC).

Gamma‐aminobutyric acid transaminase genetic polymorphism is a candidate locus for responsiveness to opioid analgesics in patients with cancer pain: An exploratory study

AimCancer pain impairs not only physical functions but also social functions and roles. Consequently, the overall health‐related quality of life of patients with cancer pain deteriorates. Opioid analgesics are recommended for treating moderate to strong cancer pain. Advances in human genome research have fueled a growing interest to understand individual differences in responsiveness to opioid analgesics. This study aimed to explore and identify novel loci for genes predisposing an individual to opioid analgesic responsiveness.MethodsA total of 71 cancer patients rated their pain on an 11‐point numerical rating scale twice before and after increasing opioid analgesics. A genomewide association study focusing on single nucleotide polymorphisms (SNPs) was conducted to associate pain decrease with increased dosage of opioid analgesics based on weight (ie, responsiveness to opioid analgesics). A genomewide significance (P < 5E‐8) was set for multiplicity of analyses to control for false positives.ResultsTwo SNPs passed the genomewide threshold for significance. One exonic SNP (rs1641025) was located in the ABAT [4‐aminobutyrate aminotransaminase (GABA transaminase)] gene on chromosome 16. The other SNP (rs12494691) was located on chromosome 3, which was not associated with any known genes. These SNPs were not associated with opioid‐related adverse effects.ConclusionsOur results preliminarily suggest that both SNPs might be potential candidate loci for responsiveness to opioid analgesics, and GABA transaminase might be a possible target for developing adjuvant pharmacotherapy with opioid analgesics in adjuvant pharmacotherapy. Our results should be validated in a large‐scale study with a larger sample size.

Epigenome wide association study of SNP\u2013CpG\xa0interactions on changes in triglyceride levels after pharmaceutical intervention: a GAW20 analysis

In the search for an understanding of how genetic variation contributes to the heritability of common human disease, the potential role of epigenetic factors, such as methylation, is being explored with increasing frequency. Although standard analyses test for associations between methylation levels at individual cytosine-phosphate-guanine (CpG) sites and phenotypes of interest, some investigators have begun testing for methylation and how methylation may modulate the effects of genetic polymorphisms on phenotypes. In our analysis, we used both a genome-wide and candidate gene approach to investigate potential single-nucleotide polymorphism (SNP)–CpG interactions on changes in triglyceride levels. Although we were able to identify numerous loci of interest when using an exploratory significance threshold, we did not identify any significant interactions using a strict genome-wide significance threshold. We were also able to identify numerous loci using the candidate gene approach, in which we focused on 18 genes with prior evidence of association of triglyceride levels. In particular, we identified GALNT2 loci as containing potential CpG sites that moderate the impact of genetic polymorphisms on triglyceride levels. Further work is needed to provide clear guidance on analytic strategies for testing SNP–CpG interactions, although leveraging prior biological understanding may be needed to improve statistical power in data sets with smaller sample sizes.

Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort

BackgroundHeritability estimates have revealed an important contribution of SNP variants for most common traits; however, SNP analysis by single-trait genome-wide association studies (GWAS) has failed to uncover their impact. In...