Top-ranked Single Nucleotide Polymorphisms Research Articles

A machine learning approach to predict the most and the least feed–efficient groups in beef cattle

The present study evaluated three strategies to find the optimum subset of DNA markers from the 50 K Illumina Bovine panel to classify beef cattle into the most and the least feed-efficient groups without using individual feed intake and performance measures. Residual feed intake (RFI) and 50 K single nucleotide polymorphisms (SNPs) genotype data of 4,057 beef animals from research and commercial herds were included. Initially, all cattle were ranked based on their phenotypic RFI values. Then different datasets were created by selecting animals from the 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, and 45% range of top and bottom of the ranked RFI values. SNP subsets were selected based on the top-ranked SNPs contributing to the variance of RFI (first strategy), selecting SNPs from the SNP subsets created in the first strategy (strategy 2), and extracting SNPs from 50k SNPs (strategy 3). Then eleven ML algorithms were employed to classify the most and the least feed-efficient groups using 260 datasets generated by combinations of ten RFI phenotype percentage groups and 6, 18, and 2 SNP subsets in the first, second and third strategies, respectively. There was a high degree of accuracy (>69%) for classifying animals in the range of 1% for all ML algorithms under the three strategies and different SNP subsets. Implementing the linear Support Vector Machine algorithm for 15 K SNPs obtained in the first strategy predicted the 1% of the most and the least feed-efficient animals with an accuracy of 84%. In the second strategy, selecting 524 SNPs from the 15 K SNPs subset outperformed the other strategies with an accuracy of 81% for 1% of the population using the Naive Bayes algorithm. It was concluded that a smaller number of SNPs (524) could be used to predict the most and the least feed-efficient animals with an acceptable accuracy to reduce the cost of selection for RFI using genomic information.

Genetic Variants and Their Associations to Type 2 Diabetes Mellitus Complications in the United Arab Emirates.

AimType 2 Diabetes Mellitus (T2DM) is associated with microvascular complications, including diabetic retinopathy (DR), diabetic nephropathy (DNp), and diabetic peripheral neuropathy (DPN). In this study, we investigated genetic variations and Single Nucleotide Polymorphisms (SNPs) associated with DR, DNp, DPN and their combinations among T2DM patients of Arab origin from the United Arab Emirates, to establish the role of genes in the progression of microvascular diabetes complications.MethodsA total of 158 Emirati patients with T2DM were recruited in this study. The study population was divided into 8 groups based on the presence of single, dual, or all three complications. SNPs were selected for association analyses through a search of publicly available databases, specifically genome-wide association study (GWAS) catalog, infinome genome interpretation platform, and GWAS Central database. A multivariate logistic regression analysis and association test were performed to evaluate the association between 83 SNPs and DR, DNp, DPN, and their combinations.ResultsEighty-three SNPs were identified as being associated with T2DM and 18 SNPs had significant associations to one or more diabetes complications. The most strongly significant association for DR was rs3024997 SNP in the VEGFA gene. The top-ranked SNP for DPN was rs4496877 in the NOS3 gene. A trend towards association was detected at rs833068 and rs3024998 in the VEGFA gene with DR and rs743507 and rs1808593 in the NOS3 gene with DNp. For dual complications, the rs833061, rs833068 and rs3024997 in the VEGFA gene and the rs4149263 SNP in the ABCA1 gene were also with borderline association with DR/DNp and DPN/DNp, respectively. Diabetic with all of the complications was significantly associated with rs2230806 in the ABCA1 gene. In addition, the highly associated SNPs rs3024997 of the VEGFA gene and rs4496877 of the NOS3 gene were linked to DR and DPN after adjusting for the effects of other associated markers, respectively.ConclusionsThe present study reports associations of different genetic polymorphisms with microvascular complications and their combinations in Emirati T2DM patients, reporting new associations, and corroborating previous findings. Of interest is that some SNPs/genes were only present if multiple comorbidities were present and not associated with any single complication.

A two-stage genome-wide association study of radiation-induced acute toxicity in head and neck cancer

BackgroundMost head and neck cancer (HNC) patients receive radiotherapy (RT) and develop toxicities. This genome-wide association study (GWAS) was designed to identify single nucleotide polymorphisms (SNPs) associated with common acute radiation-induced toxicities (RITs) in an HNC cohort.MethodsA two-stage GWAS was performed in 1279 HNC patients treated with RT and prospectively scored for mucositis, xerostomia, sticky saliva, and dysphagia. The area under the curve (AUC) was used to estimate the average load of toxicity during RT. At the discovery study, multivariate linear regression was used in 957 patients, and the top-ranking SNPs were tested in 322 independent replication cohort. Next, the discovery and the replication studies were meta-analyzed.ResultsA region on 5q21.3 containing 16 SNPs showed genome-wide (GW) significance association at P-value < 5.0 × 10–8 with patient-rated acute xerostomia in the discovery study. The top signal was rs35542 with an adjusted effect size of 0.17*A (95% CI 0.12 to 0.23; P-value < = 3.78 × 10–9). The genome wide significant SNPs were located within three genes (EFNA5, FBXL17, and FER). In-silico functional analysis showed these genes may be involved in DNA damage response and co-expressed in minor salivary glands. We found 428 suggestive SNPs (P-value < 1.0 × 10–5) for other toxicities, taken to the replication study. Eleven of them showed a nominal association (P-value < 0.05).ConclusionsThis GWAS suggested novel SNPs for patient-rated acute xerostomia in HNC patients. If validated, these SNPs and their related functional pathways could lead to a predictive assay to identify sensitive patients to radiation, which may eventually allow a more individualized RT treatment.

Genomic predictions and genome-wide association studies based on RAD-seq of quality-related metabolites for the genomics-assisted breeding of tea plants

Effectively using genomic information greatly accelerates conventional breeding and applying it to long-lived crops promotes the conversion to genomic breeding. Because tea plants are bred using conventional methods, we evaluated the potential of genomic predictions (GPs) and genome-wide association studies (GWASs) for the genetic breeding of tea quality-related metabolites using genome-wide single nucleotide polymorphisms (SNPs) detected from restriction site-associated DNA sequencing of 150 tea accessions. The present GP, based on genome-wide SNPs, and six models produced moderate prediction accuracy values (r) for the levels of most catechins, represented by ( −)-epigallocatechin gallate (r = 0.32–0.41) and caffeine (r = 0.44–0.51), but low r values for free amino acids and chlorophylls. Integrated analysis of GWAS and GP detected potential candidate genes for each metabolite using 80–160 top-ranked SNPs that resulted in the maximum cumulative prediction value. Applying GPs and GWASs to tea accession traits will contribute to genomics-assisted tea breeding.

Possible Modifying Effect of Hemoglobin A1c on Genetic Susceptibility to Severe Diabetic Retinopathy in Patients With Type 2 Diabetes.

PurposeGlycemic control has been recognized as an important modifiable risk factor for diabetic retinopathy (DR). Whether hemoglobin A1c (HbA1c), as an indicator of glycemic control, could modify the genetic susceptibility to severe DR remains to be investigated. This study aimed to investigate whether HbA1c could modulate the genetic susceptibility to severe DR in Chinese patients with type 2 diabetes.MethodsA total of 3,093 Chinese individuals with type 2 diabetes were included in the cross-sectional case-control study: 1,051 with sight-threatening DR (STDR) and 2,042 without STDR. Sixty-nine top-ranked single nucleotide polymorphisms (SNPs) identified from previous genome-wide association studies were examined for their associations with STDR and proliferative DR as a subgroup analysis. SNPs showing suggestive associations with DR were examined in the stratified analysis by dichotomized HbA1c (<7% vs. ≥7%). An interaction analysis was performed by including an interaction term of SNP × HbA1c in the regression model.ResultsFour SNPs showed suggestive associations with STDR. In the stratified analysis, patients with adequate glycemic control (HbA1c <7%) had a 42% lower risk of STDR for carrying each additional protective C allele of COL5A1 rs59126004 (P = 1.76 × 10−4; odds ratio, 0.58; 95% confidence interval, 0.44–0.77). rs59126004 demonstrated a significant interaction with dichotomized HbA1c on the risk of STDR (Pinteraction = 1.733 × 10−3). In the subgroup analysis for proliferative DR, the protective effect of rs59126004 was even more pronouncedly demonstrated (P = 8.35 × 10−5; odds ratio, 0.37; 95% confidence interval, 0.22–0.60) and it showed similar interactions with dichotomized HbA1c (Pinteraction = 1.729 × 10−3).ConclusionsOur data provided evidence for possible interactions between HbA1c and COL5A1 rs59126004 on the risk of severe DR. These findings may provide new insight into the pathophysiologic mechanism of DR.

Genome-Wide Association Study for Serum Omega-3 and Omega-6 Polyunsaturated Fatty Acids: Exploratory Analysis of the Sex-Specific Effects and Dietary Modulation in Mediterranean Subjects with Metabolic Syndrome.

Many early studies presented beneficial effects of polyunsaturated fatty acids (PUFA) on cardiovascular risk factors and disease. However, results from recent meta-analyses indicate that this effect would be very low or nil. One of the factors that may contribute to the inconsistency of the results is that, in most studies, genetic factors have not been taken into consideration. It is known that fatty acid desaturase (FADS) gene cluster in chromosome 11 is a very important determinant of plasma PUFA, and that the prevalence of the single nucleotide polymorphisms (SNPs) varies greatly between populations and may constitute a bias in meta-analyses. Previous genome-wide association studies (GWAS) have been carried out in other populations and none of them have investigated sex and Mediterranean dietary pattern interactions at the genome-wide level. Our aims were to undertake a GWAS to discover the genes most associated with serum PUFA concentrations (omega-3, omega-6, and some fatty acids) in a scarcely studied Mediterranean population with metabolic syndrome, and to explore sex and adherence to Mediterranean diet (MedDiet) interactions at the genome-wide level. Serum PUFA were determined by NMR spectroscopy. We found strong robust associations between various SNPs in the FADS cluster and omega-3 concentrations (top-ranked in the adjusted model: FADS1-rs174547, p = 3.34 × 10−14; FADS1-rs174550, p = 5.35 × 10−14; FADS2-rs1535, p = 5.85 × 10−14; FADS1-rs174546, p = 6.72 × 10−14; FADS2-rs174546, p = 9.75 × 10−14; FADS2-rs174576, p = 1.17 × 10−13; FADS2-rs174577, p = 1.12 × 10−12, among others). We also detected a genome-wide significant association with other genes in chromosome 11: MYRF (myelin regulatory factor)-rs174535, p = 1.49 × 10−12; TMEM258 (transmembrane protein 258)-rs102275, p = 2.43 × 10−12; FEN1 (flap structure-specific endonuclease 1)-rs174538, p = 1.96 × 10−11). Similar genome-wide statistically significant results were found for docosahexaenoic fatty acid (DHA). However, no such associations were detected for omega-6 PUFAs or linoleic acid (LA). For total PUFA, we observed a consistent gene*sex interaction with the DNTTIP2 (deoxynucleotidyl transferase terminal interacting protein 2)-rs3747965 p = 1.36 × 10−8. For adherence to MedDiet, we obtained a relevant interaction with the ME1 (malic enzyme 1) gene (a gene strongly regulated by fat) in determining serum omega-3. The top-ranked SNP for this interaction was ME1-rs3798890 (p = 2.15 × 10−7). In the regional-wide association study, specifically focused on the FADS1/FASD2/FADS3 and ELOVL (fatty acid elongase) 2/ELOVL 5 regions, we detected several statistically significant associations at p < 0.05. In conclusion, our results confirm a robust role of the FADS cluster on serum PUFA in this population, but the associations vary depending on the PUFA. Moreover, the detection of some sex and diet interactions underlines the need for these associations/interactions to be studied in all specific populations so as to better understand the complex metabolism of PUFA.

Detecting Weak Signals by Combining Small P-Values in Genetic Association Studies.

We approach the problem of combining top-ranking association statistics or P-values from a new perspective which leads to a remarkably simple and powerful method. Statistical methods, such as the rank truncated product (RTP), have been developed for combining top-ranking associations, and this general strategy proved to be useful in applications for detecting combined effects of multiple disease components. To increase power, these methods aggregate signals across top ranking single nucleotide polymorphisms (SNPs), while adjusting for their total number assessed in a study. Analytic expressions for combined top statistics or P-values tend to be unwieldy, which complicates interpretation and practical implementation and hinders further developments. Here, we propose the augmented rank truncation (ART) method that retains main characteristics of the RTP but is substantially simpler to implement. ART leads to an efficient form of the adaptive algorithm, an approach where the number of top ranking SNPs is varied to optimize power. We illustrate our methods by strengthening previously reported associations of μ-opioid receptor variants with sensitivity to pain.

The Fas Signaling Pathway Is a Common Genetic Risk Factor for Severe Cutaneous Drug Adverse Reactions Across Diverse Drugs.

PurposeHuman leukocyte antigen (HLA) has been recognized as the most important genetic risk factor for severe cutaneous adverse drug reactions (SCARs) caused by certain drugs. However, cumulated observations suggest the presence of genetic risk factors for SCARs other than drug-specific HLA. We aimed to identify a common genetic risk factor of SCARs across multiple drugs.MethodsWe performed 2 independent genome-wide association studies (GWASs). A total of 68 and 38 subjects with a diagnosis of SCAR were enrolled in each GWAS. Their allele frequencies were compared to those of healthy subjects in Korea.ResultsNo single nucleotide polymorphism (SNP) with genome-wide significance was found in either GWAS. We next selected and annotated the 200 top-ranked SNPs from each GWAS. These 2 sets of annotated genes were then entered into the web interface of ConsensusPathDB for a pathway-level analysis. The Fas signaling pathway was significantly over-represented in each gene set from the 2 GWASs.ConclusionsOur observations suggest that the Fas signaling pathway may be a common genetic risk factor for SCARs across multiple drugs.

Identification of novel alleles associated with insulin resistance in childhood obesity using pooled-DNA genome-wide association study approach

Background:Recently, we witnessed great progress in the discovery of genetic variants associated with obesity and type 2 diabetes (T2D), especially in adults. Much less is known regarding genetic variants associated with insulin resistance (IR). We hypothesized that novel IR genes could be efficiently detected in a population of obese children and adolescents who may not exhibit comorbidities and other confounding factors.Objectives:This study aimed to determine whether a genome-wide association study (GWAS), using a DNA-pooling approach, could identify novel genes associated with IR.Subjects:The pooled-DNA GWAS analysis included Slovenian obese children and adolescents with and without IR matched for body mass index, gender and age. A replication study was conducted in another independent cohort with or without IR.Methods:For the pooled-DNA GWAS, we used HumanOmni5-Quad SNP array (Illumina). Allele frequency distributions were compared with modified t-tests and χ2-tests and ranked using PLINK. Top single nucleotide polymorphisms (SNPs) were validated using individual genotyping by high-resolution melting analysis and TaqMan assay.Results:We identified five top-ranking SNPs from the pooled-DNA GWAS analysis within the ECE1, IL1R2, GNPDA1, HLA-J and PYGB loci. All except SNP rs9261108 (HLA-J locus) were confirmed in the validation phase using individual genotyping. The SNP rs2258617 within PYGB remained statistically significant for both recessive and additive models in both cohorts and in a merged analysis of both cohorts and present the strongest novel candidate gene for IR.Conclusion:We report for the first time a pooled-DNA GWAS approach to identify five novel SNPs or genes for IR in a paediatric population. The four loci confirmed in the second validation phase study warrant further studies, especially the strongest SNP rs2258617 within PYGB, and provide targets for further basic research of IR mechanisms and for the development of potential new IR and T2D therapies.

Association of CD8+ T-cells with bone erosion in patients with rheumatoid arthritis.

Bone erosion is a major problem worsening quality of rheumatoid arthritis (RA) patients' lives. However, causal factors responsible for bone erosion in RA have remained unclear. We aimed to examine genetic variants conferring bone erosion in RA using a Korean genome-wide association study (GWAS) and to search for possible biological mechanisms underlying the development of bone erosion. We obtained genome-wide single nucleotide polymorphism (SNP) data for 711 Korean RA patients using Illumina HapMap 550v3/660W arrays. Associations between SNPs and bone erosion status based on the Steinbrocker staging system were examined using multivariate logistic regression. Cell-type-specific enrichment of the epigenomic chromatin annotation H3K4me3 at the bone erosion associated variants was further investigated using National Institute of Health Roadmap Epigenomics data. As we tested the associations between 439 289 SNPs and bone erosion in 385 patients with erosive RA and 326 with non-erosive RA, none of the tested SNPs reached the genome-wide significance threshold, although many loci showed modest genetic effect on bone erosion status with suggestive association (e.g., rs2741200 [P = 3.75 × 10-6 ] in the SLA-TG locus and rs12422918 [P = 4.13 × 10-6 ] in SRGAP1). However, the top-ranked SNPs and their linked proxies, which were mostly located in non-coding variants, were significantly co-localized with the highly tissue-specific regulatory marker H3K4me3 in CD8+ memory T-cells (P = 0.014). Although, there was no large-effect variants associated with bone erosion in our GWAS, we have shown that CD8+ memory T-cells may have relevance with bone erosion in patients with RA through the analysis of ChiP-seq data.

Leveraging cell type specific regulatory regions to detect SNPs associated with tissue factor pathway inhibitor plasma levels.

Tissue factor pathway inhibitor (TFPI) regulates the formation of intravascular blood clots, which manifest clinically as ischemic heart disease, ischemic stroke, and venous thromboembolism (VTE). TFPI plasma levels are heritable, but the genetics underlying TFPI plasma level variability are poorly understood. Herein we report the first genome-wide association scan (GWAS) of TFPI plasma levels, conducted in 251 individuals from five extended French-Canadian Families ascertained on VTE. To improve discovery, we also applied a hypothesis-driven (HD) GWAS approach that prioritized single nucleotide polymorphisms (SNPs) in (1) hemostasis pathway genes, and (2) vascular endothelial cell (EC) regulatory regions, which are among the highest expressers of TFPI. Our GWAS identified 131 SNPs with suggestive evidence of association (P-value < 5 × 10-8 ), but no SNPs reached the genome-wide threshold for statistical significance. Hemostasis pathway genes were not enriched for TFPI plasma level associated SNPs (global hypothesis test P-value = 0.147), but EC regulatory regions contained more TFPI plasma level associated SNPs than expected by chance (global hypothesis test P-value = 0.046). We therefore stratified our genome-wide SNPs, prioritizing those in EC regulatory regions via stratified false discovery rate (sFDR) control, and reranked the SNPs by q-value. The minimum q-value was 0.27, and the top-ranked SNPs did not show association evidence in the MARTHA replication sample of 1,033 unrelated VTE cases. Although this study did not result in new loci for TFPI, our work lays out a strategy to utilize epigenomic data in prioritization schemes for future GWAS studies.

Pooled genome wide association detects association upstream of FCRL3 with Graves' disease.

BackgroundGraves’ disease is an autoimmune thyroid disease of complex inheritance. Multiple genetic susceptibility loci are thought to be involved in Graves’ disease and it is therefore likely that these can be identified by genome wide association studies. This study aimed to determine if a genome wide association study, using a pooling methodology, could detect genomic loci associated with Graves’ disease.ResultsNineteen of the top ranking single nucleotide polymorphisms including HLA-DQA1 and C6orf10, were clustered within the Major Histo-compatibility Complex region on chromosome 6p21, with rs1613056 reaching genome wide significance (p = 5 × 10−8). Technical validation of top ranking non-Major Histo-compatablity complex single nucleotide polymorphisms with individual genotyping in the discovery cohort revealed four single nucleotide polymorphisms with p ≤ 10−4. Rs17676303 on chromosome 1q23.1, located upstream of FCRL3, showed evidence of association with Graves’ disease across the discovery, replication and combined cohorts. A second single nucleotide polymorphism rs9644119 downstream of DPYSL2 showed some evidence of association supported by finding in the replication cohort that warrants further study.ConclusionsPooled genome wide association study identified a genetic variant upstream of FCRL3 as a susceptibility locus for Graves’ disease in addition to those identified in the Major Histo-compatibility Complex. A second locus downstream of DPYSL2 is potentially a novel genetic variant in Graves’ disease that requires further confirmation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3276-z) contains supplementary material, which is available to authorized users.

Previous GWAS hits in relation to young-onset breast cancer.

Genome-wide association studies (GWAS) have identified dozens of single-nucleotide polymorphisms (SNPs) associated with breast cancer. Few studies focused on young-onset breast cancer, which exhibits etiologic and tumor-type differences from older-onset disease. Possible confounding by prenatal effects of the maternal genome has also not been considered. Using a family-based design for breast cancer before age 50, we assessed the relationship between breast cancer and 77 GWAS-identified breast cancer risk SNPs. We estimated relative risks (RR) for inherited and maternally mediated genetic effects. We also used published RR estimates to calculate genetic risk scores and model joint effects. Seventeen of the candidate SNPs were nominally associated with young-onset breast cancer in our 1296 non-Hispanic white affected families (uncorrected p value <0.05). Top-ranked SNPs included rs3803662-A (TOX3, RR=1.39; p=7.0×10-6), rs12662670-G (ESR1, RR=1.56; p=5.7×10-4), rs2981579-A (FGFR2, RR=1.24; p=0.002), and rs999737-G (RAD51B, RR=1.37; p=0.003). No maternally mediated effects were found. A risk score based on all 77 SNPs indicated that their overall relationship to young-onset breast cancer risk was more than additive (additive-fit p=2.2×10-7) and consistent with a multiplicative joint effect (multiplicative-fit p=0.27). With the multiplicative formulation, the case sister's genetic risk score exceeded that of her unaffected sister in 59% of families. The results of this family-based study indicate that no effects of previously identified risk SNPs were explained by prenatal effects of maternal variants. Many of the known breast cancer risk variants were associated with young-onset breast cancer, with evidence that TOX3, ESR1, FGFR2, and RAD51B are important for young-onset disease.

Ranking factors involved in diabetes remission after bariatric surgery using machine-learning integrating clinical and genomic biomarkers.

As weight-loss surgery is an effective treatment for the glycaemic control of type 2 diabetes in obese patients, yet not all patients benefit, it is valuable to find predictive factors for this diabetic remission. This will help elucidating possible mechanistic insights and form the basis for prioritising obese patients with dysregulated diabetes for surgery where diabetes remission is of interest. In this study, we combine both clinical and genomic factors using heuristic methods, informed by prior biological knowledge in order to rank factors that would have a role in predicting diabetes remission, and indeed in identifying patients who may have low likelihood in responding to bariatric surgery for improved glycaemic control. Genetic variants from the Illumina CardioMetaboChip were prioritised through single-association tests and then seeded a larger selection from protein–protein interaction networks. Artificial neural networks allowing nonlinear correlations were trained to discriminate patients with and without surgery-induced diabetes remission, and the importance of each clinical and genetic parameter was evaluated. The approach highlighted insulin treatment, baseline HbA1c levels, use of insulin-sensitising agents and baseline serum insulin levels, as the most informative variables with a decent internal validation performance (74% accuracy, area under the curve (AUC) 0.81). Adding information for the eight top-ranked single nucleotide polymorphisms (SNPs) significantly boosted classification performance to 84% accuracy (AUC 0.92). The eight SNPs mapped to eight genes — ABCA1, ARHGEF12, CTNNBL1, GLI3, PROK2, RYBP, SMUG1 and STXBP5 — three of which are known to have a role in insulin secretion, insulin sensitivity or obesity, but have not been indicated for diabetes remission after bariatric surgery before.

Association of Polymorphisms in MACRO Domain Containing 2 With Thyroid-Associated Orbitopathy

Thyroid-associated orbitopathy (TO) is an autoimmune-mediated orbital inflammation that can lead to disfigurement and blindness. Multiple genetic loci have been associated with Graves' disease, but the genetic basis for TO is largely unknown. This study aimed to identify loci associated with TO in individuals with Graves' disease, using a genome-wide association scan (GWAS) for the first time to our knowledge in TO. Genome-wide association scan was performed on pooled DNA from an Australian Caucasian discovery cohort of 265 participants with Graves' disease and TO (cases) and 147 patients with Graves' disease without TO (controls). Top-ranked single nucleotide polymorphisms (SNPs) then were genotyped in individual DNA samples from the discovery cohort, and two replication cohorts totaling 584 cases and 367 controls. In the GWAS of pooled DNA samples, several SNPs showed suggestive association with TO at genome-wide P ≤ 10-6; rs953128 located on chr10q21.1, rs2867161 on chr7q11.22, rs13360861 on chr5q12.3, rs7636326 on chr3q26.2, rs10266576 on chr 7q11.22, rs60457622 on chr3q23, and rs6110809 on chr20p12.1. However, the only SNP consistently associated with TO on individual genotyping in the discovery and replication cohorts was rs6110809, located within MACROD2 on chromosome 20p12.1. On combined analysis of discovery and replication cohorts, the minor A allele of rs6110809 was more frequent in TO than in Graves' disease controls without TO (P = 4.35 × 10-5; odds ratio [OR] = 1.77; 95% confidence interval [CI], 1.35-2.32) after adjusting for age, sex, duration of Graves' disease, and smoking. In patients with Graves' disease, a common genetic variant in MACROD2 may increase susceptibility for thyroid-associated orbitopathy. This association now requires confirmation in additional independent cohorts.

Genome-Wide Association of the Laboratory-Based Nicotine Metabolite Ratio in Three Ancestries.

Introduction:Metabolic enzyme variation and other patient and environmental characteristics influence smoking behaviors, treatment success, and risk of related disease. Population-specific variation in metabolic genes contributes to challenges in developing and optimizing pharmacogenetic interventions. We applied a custom genome-wide genotyping array for addiction research (Smokescreen), to three laboratory-based studies of nicotine metabolism with oral or venous administration of labeled nicotine and cotinine, to model nicotine metabolism in multiple populations. The trans-3′-hydroxycotinine/cotinine ratio, the nicotine metabolite ratio (NMR), was the nicotine metabolism measure analyzed.Methods:Three hundred twelve individuals of self-identified European, African, and Asian American ancestry were genotyped and included in ancestry-specific genome-wide association scans (GWAS) and a meta-GWAS analysis of the NMR. We modeled natural-log transformed NMR with covariates: principal components of genetic ancestry, age, sex, body mass index, and smoking status.Results:African and Asian American NMRs were statistically significantly (P values ≤ 5E-5) lower than European American NMRs. Meta-GWAS analysis identified 36 genome-wide significant variants over a 43 kilobase pair region at CYP2A6 with minimum P = 2.46E-18 at rs12459249, proximal to CYP2A6. Additional minima were located in intron 4 (rs56113850, P = 6.61E-18) and in the CYP2A6-CYP2A7 intergenic region (rs34226463, P = 1.45E-12). Most (34/36) genome-wide significant variants suggested reduced CYP2A6 activity; functional mechanisms were identified and tested in knowledge-bases. Conditional analysis resulted in intergenic variants of possible interest (P values < 5E-5).Conclusions:This meta-GWAS of the NMR identifies CYP2A6 variants, replicates the top-ranked single nucleotide polymorphism from a recent Finnish meta-GWAS of the NMR, identifies functional mechanisms, and provides pan-continental population biomarkers for nicotine metabolism.Implications:This multiple ancestry meta-GWAS of the laboratory study-based NMR provides novel evidence and replication for genome-wide association of CYP2A6 single nucleotide and insertion–deletion polymorphisms. We identify three regions of genome-wide significance: proximal, intronic, and distal to CYP2A6. We replicate the top-ranking single nucleotide polymorphism from a recent GWAS of the NMR in Finnish smokers, identify a functional mechanism for this intronic variant from in silico analyses of RNA-seq data that is consistent with CYP2A6 expression measured in postmortem lung and liver, and provide additional support for the intergenic region between CYP2A6 and CYP2A7.

Evidence for contribution of common genetic variants within chromosome 8p21.2-8p21.1 to restricted and repetitive behaviors in autism spectrum disorders.

BackgroundRestricted and Repetitive Behaviors (RRB), one of the core symptom categories for Autism Spectrum Disorders (ASD), comprises heterogeneous groups of behaviors. Previous research indicates that there are two or more factors (subcategories) within the RRB domain. In an effort to identify common variants associated with RRB, we have carried out a genome-wide association study (GWAS) using the Autism Genetic Resource Exchange (AGRE) dataset (n = 1,335, all ASD probands of European ancestry) for each identified RRB subcategory, while allowing for comparisons of associated single nucleotide polymorphisms (SNPs) with associated SNPs in the same set of probands analyzed using all the RRB subcategories as phenotypes in a multivariate linear mixed model. The top ranked SNPs were then explored in an independent dataset.ResultsUsing principal component analysis of item scores obtained from Autism Diagnostic Interview-Revised (ADI-R), two distinct subcategories within Restricted and Repetitive Behaviors were identified: Repetitive Sensory Motor (RSM) and Insistence on Sameness (IS). Quantitative RSM and IS scores were subsequently used as phenotypes in a GWAS using the AGRE ASD cohort. Although no associated SNPs with genome-wide significance (P < 5.0E-08) were detected when RSM or IS were analyzed independently, three SNPs approached genome-wide significance when RSM and IS were considered together using multivariate association analysis. These included the top IS-associated SNP, rs62503729 (P-value = 6.48E-08), which is located within chromosome 8p21.2-8p21.1, a locus previously linked to schizophrenia. Notably, all of the most significantly associated SNPs are located in close proximity to STMN4 and PTK2B, genes previously shown to function in neuron development. In addition, several of the top-ranked SNPs showed correlations with STMN4 mRNA expression in adult CEU (Caucasian and European descent) human prefrontal cortex. However, the association signals within chromosome 8p21.2-8p21.1 failed to replicate in an independent sample of 2,588 ASD probands; the insufficient sample size and between-study heterogeneity are possible explanations for the non-replication.ConclusionsOur analysis indicates that RRB in ASD can be represented by two distinct subcategories: RSM and IS. Subsequent univariate and multivariate genome-wide association studies of these RRB subcategories enabled the detection of associated SNPs at 8p21.2-8p21.1. Although these results did not replicate in an independent ASD dataset, genomic features of this region and pathway analysis suggest that common variants in 8p21.2-8p21.1 may contribute to RRB, particularly IS. Together, these observations warrant future studies to elucidate the possible contributions of common variants in 8p21.2-8p21.1 to the etiology of RSM and IS in ASD.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2475-y) contains supplementary material, which is available to authorized users.

GenoWAP: GWAS signal prioritization through integrated analysis of genomic functional annotation.

Genome-wide association study (GWAS) has been a great success in the past decade. However, significant challenges still remain in both identifying new risk loci and interpreting results. Bonferroni-corrected significance level is known to be conservative, leading to insufficient statistical power when the effect size is moderate at risk locus. Complex structure of linkage disequilibrium also makes it challenging to separate causal variants from nonfunctional ones in large haplotype blocks. Under such circumstances, a computational approach that may increase signal replication rate and identify potential functional sites among correlated markers is urgently needed. We describe GenoWAP, a GWAS signal prioritization method that integrates genomic functional annotation and GWAS test statistics. The effectiveness of GenoWAP is demonstrated through its applications to Crohn's disease and schizophrenia using the largest studies available, where highly ranked loci show substantially stronger signals in the whole dataset after prioritization based on a subset of samples. At the single nucleotide polymorphism (SNP) level, top ranked SNPs after prioritization have both higher replication rates and consistently stronger enrichment of eQTLs. Within each risk locus, GenoWAP may be able to distinguish functional sites from groups of correlated SNPs. GenoWAP is freely available on the web at http://genocanyon.med.yale.edu/GenoWAP.

Genome-wide Gene-Asbestos Exposure Interaction Association Study Identifies a Common Susceptibility Variant on 22q13.31 Associated with Lung Cancer Risk.

Occupational asbestos exposure has been found to increase lung cancer risk in epidemiologic studies. We conducted an asbestos exposure-gene interaction analyses among several Caucasian populations who were current or ex-smokers. The discovery phase included 833 Caucasian cases and 739 Caucasian controls, and used a genome-wide association study (GWAS) to identify single-nucleotide polymorphisms (SNP) with gene-asbestos interaction effects. The top ranked SNPs from the discovery phase were replicated within the International Lung and Cancer Consortium (ILCCO). First, in silico replication was conducted in those groups that had GWAS and asbestos exposure data, including 1,548 cases and 1,527 controls. This step was followed by de novo genotyping to replicate the results from the in silico replication, and included 1,539 cases and 1,761 controls. Multiple logistic regression was used to assess the SNP-asbestos exposure interaction effects on lung cancer risk. We observed significantly increased lung cancer risk among MIRLET7BHG (MIRLET7B host gene located at 22q13.31) polymorphisms rs13053856, rs11090910, rs11703832, and rs12170325 heterozygous and homozygous variant allele(s) carriers (P < 5 × 10(-7) by likelihood ratio test; df = 1). Among the heterozygous and homozygous variant allele(s) carriers of polymorphisms rs13053856, rs11090910, rs11703832, and rs12170325, each unit increase in the natural log-transformed asbestos exposure score was associated with age-, sex-, smoking status, and center-adjusted ORs of 1.34 [95% confidence interval (CI), 1.18-1.51], 1.24 (95% CI, 1.14-1.35), 1.28 (95% CI, 1.17-1.40), and 1.26 (95% CI, 1.15-1.38), respectively, for lung cancer risk. Our findings suggest that MIRLET7BHG polymorphisms may be important predictive markers for asbestos exposure-related lung cancer. To our knowledge, our study is the first report using a systematic genome-wide analysis in combination with detailed asbestos exposure data and replication to evaluate asbestos-associated lung cancer risk.

Resampling to Address the Winner's Curse in Genetic Association Analysis of Time to Event.

ABSTRACTThe “winner's curse” is a subtle and difficult problem in interpretation of genetic association, in which association estimates from large‐scale gene detection studies are larger in magnitude than those from subsequent replication studies. This is practically important because use of a biased estimate from the original study will yield an underestimate of sample size requirements for replication, leaving the investigators with an underpowered study. Motivated by investigation of the genetics of type 1 diabetes complications in a longitudinal cohort of participants in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Genetics Study, we apply a bootstrap resampling method in analysis of time to nephropathy under a Cox proportional hazards model, examining 1,213 single‐nucleotide polymorphisms (SNPs) in 201 candidate genes custom genotyped in 1,361 white probands. Among 15 top‐ranked SNPs, bias reduction in log hazard ratio estimates ranges from 43.1% to 80.5%. In simulation studies based on the observed DCCT/EDIC genotype data, genome‐wide bootstrap estimates for false‐positive SNPs and for true‐positive SNPs with low‐to‐moderate power are closer to the true values than uncorrected naïve estimates, but tend to overcorrect SNPs with high power. This bias‐reduction technique is generally applicable for complex trait studies including quantitative, binary, and time‐to‐event traits.