Association Analysis Of Single Nucleotide Polymorphisms Research Articles

Associations of single nucleotide polymorphisms with mucinous colorectal cancer: genome-wide common variant and gene-based rare variant analyses

BackgroundColorectal cancer has significant impact on individuals and healthcare systems. Many genes have been identified to influence its pathogenesis. However, the genetic basis of mucinous tumor histology, an aggressive subtype of colorectal cancer, is currently not well-known. This study aimed to identify common and rare genetic variations that are associated with the mucinous tumor phenotype.MethodsGenome-wide single nucleotide polymorphism (SNP) data was investigated in a colorectal cancer patient cohort (n = 505). Association analyses were performed for 729,373 common SNPs and 275,645 rare SNPs. Common SNP association analysis was performed using univariable and multivariable logistic regression under different genetic models. Rare-variant association analysis was performed using a multi-marker test.ResultsNo associations reached the traditional genome-wide significance. However, promising genetic associations were identified. The identified common SNPs significantly improved the discriminatory accuracy of the model for mucinous tumor phenotype. Specifically, the area under the receiver operating characteristic curve increased from 0.703 (95% CI: 0.634–0.773) to 0.916 (95% CI: 0.873–0.960) when considering the most significant SNPs. Additionally, the rare variant analysis identified a number of genetic regions that potentially contain causal rare variants associated with the mucinous tumor phenotype.ConclusionsThis is the first study applying both common and rare variant analyses to identify genetic associations with mucinous tumor phenotype using a genome-wide genotype data. Our results suggested novel associations with mucinous tumors. Once confirmed, these results will not only help us understand the biological basis of mucinous histology, but may also help develop targeted treatment options for mucinous tumors.

Genome-wide association study and meta-analysis identify loci associated with ventricular and supraventricular ectopy

The genetic basis of supraventricular and ventricular ectopy (SVE, VE) remains largely uncharacterized, despite established genetic mechanisms of arrhythmogenesis. To identify novel genetic variants associated with SVE/VE in ancestrally diverse human populations, we conducted a genome-wide association study of electrocardiographically identified SVE and VE in five cohorts including approximately 43,000 participants of African, European and Hispanic/Latino ancestry. In thirteen ancestry-stratified subgroups, we tested multivariable-adjusted associations of SVE and VE with single nucleotide polymorphism (SNP) dosage. We combined subgroup-specific association estimates in inverse variance-weighted, fixed-effects and Bayesian meta-analyses. We also combined fixed-effects meta-analytic t-test statistics for SVE and VE in multi-trait SNP association analyses. No loci reached genome-wide significance in trans-ethnic meta-analyses. However, we found genome-wide significant SNPs intronic to an apoptosis-enhancing gene previously associated with QRS interval duration (FAF1; lead SNP rs7545860; effect allele frequency = 0.02; P = 2.0 × 10−8) in multi-trait analysis among European ancestry participants and near a locus encoding calcium-dependent glycoproteins (DSC3; lead SNP rs8086068; effect allele frequency = 0.17) in meta-analysis of SVE (P = 4.0 × 10−8) and multi-trait analysis (P = 2.9 × 10−9) among African ancestry participants. The novel findings suggest several mechanisms by which genetic variation may predispose to ectopy in humans and highlight the potential value of leveraging pleiotropy in future studies of ectopy-related phenotypes.

Candidate gene association analyses for ketosis resistance in Holsteins

High-yielding dairy cattle are susceptible to ketosis, a metabolic disease that negatively affects the health, fertility, and milk production of the cow. Interest in breeding for more robust dairy cattle with improved resistance to disease is global; however, genetic evaluations for ketosis would benefit from the additional information provided by genetic markers. Candidate genes that are proposed to have a biological role in the pathogenesis of ketosis were investigated in silico and a custom panel of 998 putative single nucleotide polymorphism (SNP) markers was developed. The objective of this study was to test the associations of these new markers with deregressed estimated breeding values (EBV) for ketosis. A sample of 653 Canadian Holstein cows that had been previously genotyped with a medium-density SNP chip were regenotyped with the custom panel. The EBV for ketosis in first and later lactations were obtained for each animal and deregressed for use as pseudo-phenotypes for association analyses. Results of the mixed inheritance model for single SNP association analyses suggested 15 markers in 6 unique candidate genes were associated with the studied trait. Genes encoding proteins involved in metabolic processes, including the synthesis and degradation of fatty acids and ketone bodies, gluconeogenesis, lipid mobilization, and the citric acid cycle, were identified to contain SNP associated with ketosis resistance. This work confirmed the presence of previously described quantitative trait loci for dairy cattle, suggested novel markers for ketosis-resistance, and provided insight into the underlying biology of this disease.

ILDgenDB: integrated genetic knowledge resource for interstitial lung diseases (ILDs).

Interstitial lung diseases (ILDs) are a diverse group of ∼200 acute and chronic pulmonary disorders that are characterized by variable amounts of inflammation, fibrosis and architectural distortion with substantial morbidity and mortality. Inaccurate and delayed diagnoses increase the risk, especially in developing countries. Studies have indicated the significant roles of genetic elements in ILDs pathogenesis. Therefore, the first genetic knowledge resource, ILDgenDB, has been developed with an objective to provide ILDs genetic data and their integrated analyses for the better understanding of disease pathogenesis and identification of diagnostics-based biomarkers. This resource contains literature-curated disease candidate genes (DCGs) enriched with various regulatory elements that have been generated using an integrated bioinformatics workflow of databases searches, literature-mining and DCGs–microRNA (miRNAs)–single nucleotide polymorphisms (SNPs) association analyses. To provide statistical significance to disease-gene association, ILD-specificity index and hypergeomatric test scores were also incorporated. Association analyses of miRNAs, SNPs and pathways responsible for the pathogenesis of different sub-classes of ILDs were also incorporated. Manually verified 299 DCGs and their significant associations with 1932 SNPs, 2966 miRNAs and 9170 miR-polymorphisms were also provided. Furthermore, 216 literature-mined and proposed biomarkers were identified. The ILDgenDB resource provides user-friendly browsing and extensive query-based information retrieval systems. Additionally, this resource also facilitates graphical view of predicted DCGs–SNPs/miRNAs and literature associated DCGs–ILDs interactions for each ILD to facilitate efficient data interpretation. Outcomes of analyses suggested the significant involvement of immune system and defense mechanisms in ILDs pathogenesis. This resource may potentially facilitate genetic-based disease monitoring and diagnosis.Database URL: http://14.139.240.55/ildgendb/index.php

On the impact of relatedness on SNP association analysis

BackgroundWhen testing for SNP (single nucleotide polymorphism) associations in related individuals, observations are not independent. Simple linear regression assuming independent normally distributed residuals results in an increased type I error and the power of the test is also affected in a more complicate manner. Inflation of type I error is often successfully corrected by genomic control. However, this reduces the power of the test when relatedness is of concern. In the present paper, we derive explicit formulae to investigate how heritability and strength of relatedness contribute to variance inflation of the effect estimate of the linear model. Further, we study the consequences of variance inflation on hypothesis testing and compare the results with those of genomic control correction. We apply the developed theory to the publicly available HapMap trio data (N=129), the Sorbs (a self-contained population with N=977 characterised by a cryptic relatedness structure) and synthetic family studies with different sample sizes (ranging from N=129 to N=999) and different degrees of relatedness.ResultsWe derive explicit and easily to apply approximation formulae to estimate the impact of relatedness on the variance of the effect estimate of the linear regression model. Variance inflation increases with increasing heritability. Relatedness structure also impacts the degree of variance inflation as shown for example family structures. Variance inflation is smallest for HapMap trios, followed by a synthetic family study corresponding to the trio data but with larger sample size than HapMap. Next strongest inflation is observed for the Sorbs, and finally, for a synthetic family study with a more extreme relatedness structure but with similar sample size as the Sorbs. Type I error increases rapidly with increasing inflation. However, for smaller significance levels, power increases with increasing inflation while the opposite holds for larger significance levels. When genomic control is applied, type I error is preserved while power decreases rapidly with increasing variance inflation.ConclusionsStronger relatedness as well as higher heritability result in increased variance of the effect estimate of simple linear regression analysis. While type I error rates are generally inflated, the behaviour of power is more complex since power can be increased or reduced in dependence on relatedness and the heritability of the phenotype. Genomic control cannot be recommended to deal with inflation due to relatedness. Although it preserves type I error, the loss in power can be considerable. We provide a simple formula for estimating variance inflation given the relatedness structure and the heritability of a trait of interest. As a rule of thumb, variance inflation below 1.05 does not require correction and simple linear regression analysis is still appropriate.

Disease-miRNAdb: a manually-curated database for the investigation of the microRNA-human disease relationship

MicroRNAs (miRNA) of approximately 22 nucleotides are fundamental molecules in cellular biology that act by modulating target gene expression. As a post-transcriptional/translational regulator, the role of miRNAs in human disease is highly expected. Recently, a rising number of miRNAs that are associated with a variety of human diseases have been reported in the literature. Aiming to provide a comprehensive of resource of miRNAs that are related to the human disease, we built the Disease miRNA Database (Disease-miRNAdb). MiRNAs from three groups of diseases including kidney disease, cancer, and metabolic disease were manually curated in the current version of database located on a user-friendly online website ( http://disease-miRNAdb.hallym.ac.kr ). In addition, this database also includes information regarding single nucleotide polymorphisms (SNPs) located in pre-miRNAs, miRNA flanking regions, and 3′-UTRs of miRNA target genes. The generation of genetic variation in these regions may result in a loss or gain of miRNA-target gene interactions, which may influence the development of disease. Thus, information regarding miRNA-related SNPs will be useful in the discovery of disease-associated miRNAs in human populations by employing SNP association analysis for the disease of interest. Disease-miRNAdb will be continually maintained with up-to-date information to provide a current and valuable resource for investigating the roles of miRNAs in human disease.

Genome-Wide Association Meta-Analysis Reveals Novel Juvenile Idiopathic Arthritis Susceptibility Loci.

Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease and has a strong genomic component. To date, JIA genetic association studies have had limited sample sizes, usedheterogeneous patient populations, or included only candidate regions. The aim of this study was to identify new associations between JIA patients with oligoarticular disease and those with IgM rheumatoid factor (RF)-negative polyarticular disease, which are clinically similar and the most prevalent JIA disease subtypes. Three cohorts comprising 2,751 patients with oligoarticular or RF-negative polyarticular JIA were genotyped using the Affymetrix Genome-Wide SNP Array 6.0 or the Illumina HumanCoreExome-12+ Array. Overall, 15,886 local and out-of-study controls, typed on these platforms or the Illumina HumanOmni2.5, were used forassociation analyses. High-quality single-nucleotide polymorphisms (SNPs) were used for imputation to 1000 Genomes prior to SNP association analysis. Meta-analysis showed evidence of association (P < 1 × 10-6 ) at 9 regions: PRR9_LOR (P = 5.12 × 10-8 ), ILDR1_CD86 (P = 6.73 × 10-8 ), WDFY4 (P = 1.79 × 10-7 ), PTH1R (P = 1.87 × 10-7 ), RNF215 (P = 3.09 × 10-7 ), AHI1_LINC00271 (P = 3.48 × 10-7 ), JAK1 (P = 4.18 × 10-7 ), LINC00951 (P = 5.80 × 10-7 ), and HBP1 (P = 7.29 × 10-7 ). Of these, PRR9_LOR, ILDR1_CD86, RNF215, LINC00951, and HBP1 were shown, for the first time, to be autoimmune disease susceptibility loci. Furthermore, associated SNPs included cis expression quantitative trait loci for WDFY4, CCDC12, MTP18, SF3A1, AHI1, COG5, HBP1, and GPR22. This study provides evidence of both unique JIA risk loci and risk loci overlapping between JIA and other autoimmune diseases. These newly associated SNPs are shown to influence gene expression, and their bounding regions tie into molecular pathways of immunologic relevance. Thus, they likely represent regions that contribute to the pathology of oligoarticular JIA and RF-negative polyarticular JIA.

Evaluating the Association of Common Variants of the SLC44A4 Gene with Ulcerative Colitis Susceptibility in the Han Chinese Population

The SLC44A4 gene was recently reported to be associated with ulcerative colitis (UC) susceptibility in the Indian and Japanese populations. The aim of our study was to investigate the association of common variants within the SLC44A4 gene and the susceptibility to UC among the Han Chinese. We examined 16 tag single nucleotide polymorphisms (SNPs) within the SLC44A4 gene in a Han Chinese population that consisted of 311 UC patients and 675 healthy controls; both SNP and haplotypic association analyses were performed. We found that rs2736428 was significantly associated with UC risk (allelic p = 0.0004), and the CT and TT genotypes of rs2736428 had a higher distribution compared with the CC genotypes (genotypic p = 0.001), suggesting that the T allele was a risk allele (odds ratio = 1.45, 95% confidence interval = 1.18-1.78). Moreover, one haplotype block that included rs2736428 was found to be strongly associated with UC risk as well (global p < 0.001). Our results provide further supportive evidence for an important role of the SLC44A4 gene in the pathogenesis of UC.

Genome-wide association study discovered candidate genes of Verticillium wilt resistance in upland cotton (Gossypium hirsutum L.).

SummaryVerticillium wilt (VW), caused by infection by Verticillium dahliae, is considered one of the most yield‐limiting diseases in cotton. To examine the genetic architecture of cotton VW resistance, we performed a genome‐wide association study (GWAS) using a panel of 299 accessions and 85 630 single nucleotide polymorphisms (SNPs) detected using the specific‐locus amplified fragment sequencing (SLAF‐seq) approach. Trait–SNP association analysis detected a total of 17 significant SNPs at P < 1.17 × 10–5 (P = 1/85 630, –log10 P = 4.93); the peaks of SNPs associated with VW resistance on A10 were continuous and common in three environments (RDIG2015, RDIF2015 and RDIF2016). Haplotype block structure analysis predicted 22 candidate genes for VW resistance based on A10_99672586 with a minimum P‐value (–log10 P = 6.21). One of these genes (CG02) was near the significant SNP A10_99672586 (0.26 Mb), located in a 372‐kb haplotype block, and its Arabidopsis AT3G25510 homologues contain TIR‐NBS‐LRR domains that may be involved in disease resistance response. Real‐time quantitative PCR and virus‐induced gene silencing (VIGS) analysis showed that CG02 was specific to up‐regulation in the resistant (R) genotype Zhongzhimian2 (ZZM2) and that silenced plants were more susceptible to V. dahliae. These results indicate that CG02 is likely the candidate gene for resistance against V. dahliae in cotton. The identified locus or gene may serve as a promising target for genetic engineering and selection for improving resistance to VW in cotton.

Association analysis of SNPs in the porcine CYP2E1 gene with skatole, indole, and androstenone levels in backfat of a crossbred pig population

The occurrence of boar taint in meat from uncastrated males may significantly affect the economics of pork production. The aim of this study was to analyse associations of four single nucleotide polymorphisms (SNPs) in the porcine CYP2E1 gene with skatole, indole, and androstenone levels in the Czech Large White–Czech Landrace commercial crossbreds. The SNPs were: g.2412C>T, c.1422C>T, c.1423G>A and c.*14G>T. Skatole, indole and androstenone levels were estimated by HPLC, and genotypes at the SNPs were determined by PCR–RFLP. SNPs c.1423G>A and c.*14G>T were in complete linkage disequilibrium. In boars, all SNPs were associated with the indole levels (P<0.05; P<0.01). There also were differences in the skatole levels in different genotypes, but these were not significant. No associations with androstenone levels were found. The associations of the SNPs with indole compounds should be studied in other commercial populations of boars to verify the favourable alleles and genotypes, with the prospect for their application in marker-assisted selection.

SNPs in bone-related miRNAs are associated with the osteoporotic phenotype

Biogenesis and function of microRNAs can be influenced by genetic variants in the pri-miRNA sequences leading to phenotypic variability. This study aims to identify single nucleotide polymorphisms (SNPs) affecting the expression levels of bone-related mature microRNAs and thus, triggering an osteoporotic phenotype. An association analysis of SNPs located in pri-miRNA sequences with bone mineral density (BMD) was performed in the OSTEOMED2 cohort (n = 2183). Functional studies were performed for assessing the role of BMD-associated miRNAs in bone cells. Two SNPs, rs6430498 in the miR-3679 and rs12512664 in the miR-4274, were significantly associated with femoral neck BMD. Further, we measured these BMD-associated microRNAs in trabecular bone from osteoporotic hip fractures comparing to non-osteoporotic bone by qPCR. Both microRNAs were found overexpressed in fractured bone. Increased matrix mineralization was observed after miR-3679-3p inhibition in human osteoblastic cells. Finally, genotypes of rs6430498 and rs12512664 were correlated with expression levels of miR-3679 and miR-4274, respectively, in osteoblasts. In both cases, the allele that generated higher microRNA expression levels was associated with lower BMD values. In conclusion, two osteoblast-expressed microRNAs, miR-3679 and miR-4274, were associated with BMD; their overexpression could contribute to the osteoporotic phenotype. These findings open new areas for the study of bone disorders.

Single nucleotide polymorphisms and genotypes of transient receptor potential ion channel and acetylcholine receptor genes from isolated B lymphocytes in myalgic encephalomyelitis/chronic fatigue syndrome patients.

ObjectiveThe pathomechanism of chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) is unknown; however, a small subgroup of patients has shown muscarinic antibody positivity and reduced symptom presentation following anti-CD20 intervention. Given the important roles of calcium (Ca2+) and acetylcholine (ACh) signalling in B cell activation and potential antibody development, we aimed to identify relevant single nucleotide polymorphisms (SNPs) and genotypes in isolated B cells from CFS/ME patients.MethodsA total of 11 CFS/ME patients (aged 31.82 ± 5.50 years) and 11 non-fatigued controls (aged 33.91 ± 5.06 years) were included. Flow cytometric protocols were used to determine B cell purity, followed by SNP and genotype analysis for 21 mammalian TRP ion channel genes and nine mammalian ACh receptor genes. SNP association and genotyping analysis were performed using ANOVA and PLINK analysis software.ResultsSeventy-eight SNPs were identified in nicotinic and muscarinic acetylcholine receptor genes in the CFS/ME group, of which 35 were in mAChM3. The remaining SNPs were identified in nAChR delta (n = 12), nAChR alpha 9 (n = 5), TRPV2 (n = 7), TRPM3 (n = 4), TRPM4 (n = 1) mAChRM3 2 (n = 2), and mAChRM5 (n = 3) genes. Nine genotypes were identified from SNPs in TRPM3 (n = 1), TRPC6 (n = 1), mAChRM3 (n = 2), nAChR alpha 4 (n = 1), and nAChR beta 1 (n = 4) genes, and were located in introns and 3′ untranslated regions. Odds ratios for these specific genotypes ranged between 7.11 and 26.67 for CFS/ME compared with the non-fatigued control group.ConclusionThis preliminary investigation identified a number of SNPs and genotypes in genes encoding TRP ion channels and AChRs from B cells in patients with CFS/ME. These may be involved in B cell functional changes, and suggest a role for Ca2+ dysregulation in AChR and TRP ion channel signalling in the pathomechanism of CFS/ME.

Fine mapping of a QTL on bovine chromosome 6 using imputed full sequence data suggests a key role for the group-specific component (GC) gene in clinical mastitis and milk production.

BackgroundClinical mastitis is an inflammation of the mammary gland and causes significant costs to dairy production. It is unfavourably genetically correlated to milk production, and, thus, knowledge of the mechanisms that underlie these traits would be valuable to improve both of them simultaneously through breeding. A quantitative trait locus (QTL) that affects both clinical mastitis and milk production has recently been fine-mapped to around 89 Mb on bovine chromosome 6 (BTA6), but identification of the gene that underlies this QTL was not possible due to the strong linkage disequilibrium between single nucleotide polymorphisms (SNPs) within this region. Our aim was to identify the gene and, if possible, the causal polymorphism(s) responsible for this QTL through association analysis of high-density SNPs and imputed full sequence data in combination with analyses of transcript and protein levels of the identified candidate gene.ResultsAssociations between SNPs and the studied traits were strongest for SNPs that were located within and immediately upstream of the group-specific component (GC) gene. This gene encodes the vitamin D-binding protein (DBP) and has multiple roles in immune defense and milk production. A 12-kb duplication that was identified downstream of this gene covered its last exon and segregated with the QTL allele that is associated with increased mastitis susceptibility and milk production. However, analyses of GC mRNA levels on the available samples revealed no differences in expression between animals having or lacking this duplication. Moreover, we detected no differences in the concentrations of DBP and its ligand vitamin D between the animals with different GC genotypes that were available for this study.ConclusionsOur results suggest GC as the gene that underlies the QTL for clinical mastitis and milk production. However, since only healthy animals were sampled for transcription and expression analyses, we could not draw any final conclusion on the absence of quantitative differences between animals with different genotypes. Future studies should investigate GC RNA expression and protein levels in cows with different genotypes during an infection.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0257-2) contains supplementary material, which is available to authorized users.

P2X7R Gene Polymorphisms are Associated with Increased Risk of Pulmonary Tuberculosis in the Tibetan Chinese Population.

In this study, we aim to explore the correlation between single nucleotide polymorphisms (SNPs) in the P2X7R gene and pulmonary tuberculosis (PTB) susceptibility in the Tibetan Chinese population in China. We examined 467 patients with active PTB and 504 healthy controls living in Xi'an and the surrounding area. Eight P2X7R SNPs were genotyped, and association analysis was performed. Odds ratios (ORs) and 95% confidence intervals (CIs) were tested by unconditional logistic regression analysis to evaluate the effects of the polymorphisms on PTB risk. P2X7R SNP association analyses were performed using SPSS 17.0 statistical packages and Microsoft Excel, SNP statistics software, Haploview software package (version 4.2), and SHEsis software platform. The results show that the "C" allele of rs656612 in the P2X7R gene was associated with an increased PTB risk by the additive model (OR = 1.307, 95% CI = 1.088-1.570, P = 0.004) and dominant model (rs656612, OR = 1.490, 95% CI = 1.153-1.926, P = 0.002). The "A" allele of rs208290 showed an increased PTB risk by the additive model (OR = 1.418, 95% CI = 1.179-1.706, P < 0.001) and dominant model (OR = 1.680, 95% CI = 1.297-2.177, P < 0.001), whereas the "A" allele of rs7958311 showed an increased risk by the additive model (rs7958311, OR = 1.260, 95% CI = 1.055-1.505, P = 0.011) and recessive model (OR = 1.609, 95% CI = 1.200-2.158, P = 0.001). After Bonferroni correction, rs208290 was found to be associated with PTB in the allele, dominant, and genotype models. In conclusion, our study revealed a significant association between three P2X7R gene polymorphisms (rs656612, rs208290, and rs7958311) and PTB in a Tibetan Chinese population.

Vitamin D receptor gene associations with pulmonary tuberculosis in a Tibetan Chinese population.

BackgroundThe vitamin D receptor (VDR) mediates the immunological function of vitamin D3, which activates macrophages, and vitamin D deficiency has been linked to tuberculosis risk. Single nucleotide polymorphisms (SNPs) in VDR may influence the function of vitamin D and susceptibility to tuberculosis.MethodsThis study included 217 patients with pulmonary tuberculosis (PTB) and 383 healthy subjects in a Tibetan Chinese population living in and near Xi’an. Association analyses of SNPs in VDR were performed with the SPSS 17.0 statistical packages, SNP stats software, Haploview software package (version 4.2), and the SHEsis software platform.ResultsOur results revealed a correlation between three SNPs (rs11574143, odds ratio [OR]: 1.47, 95 % confidence interval [CI]: 1.11 - 1.94, p = 0.006, p-adjust = 0.030; rs11574079, OR: 0.48, 95 % CI: 0.25 - 0.92, p = 0.023, p-adjust = 0.115; rs11168287, OR: 2.55, 95 % CI: 2.00 - 3.25, p = 1.730E-14, p-adjust = 0.865E-13) and PTB based on Chi-square tests. We observed the allele “A” of rs11574143 and rs11168287 increased the PTB risk and the allele “A” of rs11574079 provided a protective effect against PTB.ConclusionsThe goal of this study was the identification of putative associations between five SNPs (rs11574143, rs7975232, rs11574079, rs3819545 and rs11168287) in VDR and susceptibility to PTB. Our findings demonstrated associations between VDR polymorphisms and PTB development.

DNA methylation within melatonin receptor 1A (MTNR1A) mediates paternally transmitted genetic variant effect on asthma plus rhinitis

Asthma and allergic rhinitis (AR) are common allergic comorbidities with a strong genetic component in which epigenetic mechanisms might be involved. We aimed to identify novel risk loci for asthma and AR while accounting for parent-of-origin effect. We performed a series of genetic analyses, taking into account the parent-of-origin effect in families ascertained through asthma: (1) genome-wide linkage scan of asthma and AR in 615 European families, (2) association analysis with 1233 single nucleotide polymorphisms (SNPs) covering the significant linkage region in 162 French Epidemiological Study on the Genetics and Environment of Asthma families with replication in 154 Canadian Saguenay-Lac-Saint-Jean asthma study families, and (3) association analysis of disease and significant SNPs with DNA methylation (DNAm) at CpG sites in 40 Saguenay-Lac-Saint-Jean asthma study families. We detected a significant paternal linkage of the 4q35 region to asthma and allergic rhinitis comorbidity (AAR; P=7.2×10(-5)). Association analysis in this region showed strong evidence for the effect of the paternally inherited G allele of rs10009104 on AAR (P=1.1×10(-5), reaching the multiple-testing corrected threshold). This paternally inherited allele was also significantly associated with DNAm levels at the cg02303933 site (P=1.7×10(-4)). Differential DNAm at this site was found to mediate the identified SNP-AAR association. By integrating genetic and epigenetic data, we identified that a differentially methylated CpG site within the melatonin receptor 1A (MTNR1A) gene mediates the effect of a paternally transmitted genetic variant on the comorbidity of asthma and AR. This study provides a novel insight into the role of epigenetic mechanisms in patients with allergic respiratory diseases.

Dissecting the Genetic Susceptibility to Graves' Disease in a Cohort of Patients of Italian Origin.

Graves’ disease (GD) is an autoimmune oligogenic disorder with a strong hereditary component. Several GD susceptibility genes have been identified and confirmed during the last two decades. However, there are very few studies that evaluated susceptibility genes for GD in specific geographic subsets. Previously, we mapped a new locus on chromosome 3q that was unique to GD families of Italian origin. In the present study, we used association analysis of single-nucleotide polymorphism (SNPs) at the 3q locus in a cohort of GD patients of Italian origin in order to prioritize the best candidates among the known genes in this locus to choose the one(s) best supported by the association. DNA samples were genotyped using the Illumina GoldenGate genotyping assay analyzing 690 SNP in the linked 3q locus covering all 124 linkage disequilibrium blocks in this locus. Candidate non-HLA (human-leukocyte-antigen) genes previously reported to be associated with GD and/or other autoimmune disorders were analyzed separately. Three SNPs in the 3q locus showed a nominal association (p < 0.05): rs13097181, rs763313, and rs6792646. Albeit these could not be further validated by multiple comparison correction, we were prioritizing candidate genes at a locus already known to harbor a GD-related gene, not hypothesis testing. Moreover, we found significant associations with the thyroid-stimulating hormone receptor (TSHR) gene, the cytotoxic T-lymphocyte antigen-4 (CTLA-4) gene, and the thyroglobulin (TG) gene. In conclusion, we identified three SNPs on chromosome 3q that may map a new GD susceptibility gene in this region which is unique to the Italian population. Furthermore, we confirmed that the TSHR, the CTLA-4, and the TG genes are associated with GD in Italians. Our findings highlight the influence of ethnicity and geographic variations on the genetic susceptibility to GD.

SMAD7, an antagonist of TGF-beta signaling, is a candidate of prenatal skeletal muscle development and weaning weight in pigs.

SMAD7 promotes and enhances skeletal muscle differentiation by inhibiting transforming growth factor beta (TGF-β)/activin signaling and bone morphogenetic protein (BMP) pathways. However, its function, the mechanism regulating its translation, and its association with production meat traits remain unclear in pigs. In this study, we explored SMAD7 gene spatio-temporal and tissue distribution, conducted a single nucleotide polymorphism association analysis, and examined regulation of its expression during skeletal muscle development. We found that SMAD7 was positively related to TGF-β pathway genes and mainly expressed in prenatal developing muscle, and dual luciferase and western blot assays demonstrated that SMAD7 expression was regulated by miRNA-21 at the protein level via inhibition of mRNA translation. Finally, the association analysis showed that a single nucleotide mutation (Exon 4_28816;C/A) was significantly associated with the weaning weight of piglets among Yorkshire pigs. These data indicate that SMAD7 plays a potentially important role in mammalian prenatal skeletal muscle development and is a candidate gene for promoting greater weaning weight in pig breeding.

Abstract P1-08-03: Association analysis of single-nucleotide polymorphisms in FANCD2-DNA damage repair pathway genes with breast cancer risk

Abstract Purpose: The aim of the study was to estimate breast cancer risk conferred by individual single-nucleotide polymorphisms (SNPs) of breast cancer susceptibility genes in the monoubiquitinated FANCD2–DNA damage repair pathway. Methods: We selected 48 tagging SNPs (tSNPs) from eight breast cancer susceptibility genes (TP53,PTEN,NBS1,BRIP1,PALB2,ATM,CHEK2 and RAD50) involved in the monoubiquitinated FANCD2–DNA damage repair pathway.The 48 tSNPs were genetyped by SNPscan in 734 women with breast cancer(534 sporadic cases and 200 early-onset and familial cases) and 672 sex- and age-matched healthy controls from Hunan and Sichuan Province of China.The odds ratio were calculated by logistic regression analysis under co-dominant model ,dominant model and recessive model respectively. Results: Forty-five tSNPs were successfully genotyped by SNPscan, and the call rates for each tSNP were above 98.9%. We found that 13 tSNPs of five genes (PALB2, TP53, NBS1, PTEN, and BRIP1) were significantly associated with breast cancer risk. A total of five tSNPs (rs2299941 of PTEN, rs2735385, rs6999227, rs1805812, and rs1061302 of NBS1) were tightly associated with breast cancer risk in sporadic cases, and five other tSNPs (rs1042522 of TP53, rs2735343 of PTEN, rs7220719, rs16945628, and rs11871753 of BRIP1) were tightly associated with breast cancer risk in early-onset and familial cases. We have not found significant tSNPs in the other three genes (ATM, RAD50, and CHEK2).Three tSNPs of TP53(rs12951053, rs1042522 and rs8064946),three tSNPs of BRIP1(rs16945628, rs7220719 and rs11871753) and rs2735343 of PTEN can significantly increase the risk of breast cancer,and most of these were under the analysis of early-onset and familial cases.Four tSNPs of NBS1(rs2735385, rs6999227, rs1805812 and rs1061302),rs2299941 of PTEN and rs513313 of PALB2 can significantly decrease the risk of breast cancer,and most of these were under the analysis of sporadic cases. Conclusions: Some of the tSNPs of five breast cancer susceptibility genes (PALB2, TP53, NBS1, PTEN, and BRIP1) involved in the monoubiquitinated FANCD2–DNA damage repair pathway were significantly associated with breast cancer risk in women from Hunan and Sichuan Province of China.Some locuses can increase breast cancer risk,and others can decrease breast cancer risk.But the majority of the tSNPs are located in the intron domain and their functions are unknown, so larger studies are needed to research the functions of these genes further. Citation Format: Chen F, Tang L, Huang J. Association analysis of single-nucleotide polymorphisms in FANCD2-DNA damage repair pathway genes with breast cancer risk. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P1-08-03.

Gene expression in large pedigrees: analytic approaches

BackgroundWe currently have the ability to quantify transcript abundance of messenger RNA (mRNA), genome-wide, using microarray technologies. Analyzing genotype, phenotype and expression data from 20 pedigrees, the members of our Genetic Analysis Workshop (GAW) 19 gene expression group published 9 papers, tackling some timely and important problems and questions. To study the complexity and interrelationships of genetics and gene expression, we used established statistical tools, developed newer statistical tools, and developed and applied extensions to these tools.MethodsTo study gene expression correlations in the pedigree members (without incorporating genotype or trait data into the analysis), 2 papers used principal components analysis, weighted gene coexpression network analysis, meta-analyses, gene enrichment analyses, and linear mixed models. To explore the relationship between genetics and gene expression, 2 papers studied expression quantitative trait locus allelic heterogeneity through conditional association analyses, and epistasis through interaction analyses. A third paper assessed the feasibility of applying allele-specific binding to filter potential regulatory single-nucleotide polymorphisms (SNPs). Analytic approaches included linear mixed models based on measured genotypes in pedigrees, permutation tests, and covariance kernels. To incorporate both genotype and phenotype data with gene expression, 4 groups employed linear mixed models, nonparametric weighted U statistics, structural equation modeling, Bayesian unified frameworks, and multiple regression.Results and discussionRegarding the analysis of pedigree data, we found that gene expression is familial, indicating that at least 1 factor for pedigree membership or multiple factors for the degree of relationship should be included in analyses, and we developed a method to adjust for familiality prior to conducting weighted co-expression gene network analysis. For SNP association and conditional analyses, we found FaST-LMM (Factored Spectrally Transformed Linear Mixed Model) and SOLAR-MGA (Sequential Oligogenic Linkage Analysis Routines –Major Gene Analysis) have similar type 1 and type 2 errors and can be used almost interchangeably. To improve the power and precision of association tests, prior knowledge of DNase-I hypersensitivity sites or other relevant biological annotations can be incorporated into the analyses. On a biological level, eQTL (expression quantitative trait loci) are genetically complex, exhibiting both allelic heterogeneity and epistasis. Including both genotype and phenotype data together with measurements of gene expression was found to be generally advantageous in terms of generating improved levels of significance and in providing more interpretable biological models.ConclusionsPedigrees can be used to conduct analyses of and enhance gene expression studies.