Association of bronchial steroid inducible methylation quantitative trait loci with asthma and chronic obstructive pulmonary disease treatment response.
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ABSTRACT:
SUBMITTER: Slob EMA
PROVIDER: S-EPMC9421427 | biostudies-literature | 2022 Aug
REPOSITORIES: biostudies-literature
Publications
Association of bronchial steroid inducible methylation quantitative trait loci with asthma and chronic obstructive pulmonary disease treatment response.
Slob Elise M A EMA Faiz Alen A van Nijnatten Jos J Vijverberg Susanne J H SJH Longo Cristina C Kutlu Merve M Chew Fook Tim FT Sio Yang Yie YY Herrera-Luis Esther E Espuela-Ortiz Antonio A Perez-Garcia Javier J Pino-Yanes Maria M Burchard Esteban G EG Potočnik Uroš U Gorenjak Mario M Palmer Colin C Maroteau Cyrielle C Turner Steve S Verhamme Katia K Karimi Leila L Mukhopadhyay Somnath S Timens Wim W Hiemstra Pieter S PS Pijnenburg Mariëlle W MW Neighbors Margaret M Grimbaldeston Michele A MA Tew Gaik W GW Brandsma Corry A CA Berce Vojko V Aliee Hananeh H Theis Fabian F Sin Don D DD Li Xuan X van den Berge Maarten M Maitland-van der Zee Anke H AH Koppelman Gerard H GH
Clinical and translational allergy 20220801 8
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Project description:RationaleAs the third leading cause of death in the United States, the impact of chronic obstructive pulmonary disease (COPD) makes identification of its molecular mechanisms of great importance. Genome-wide association studies (GWASs) have identified multiple genomic regions associated with COPD. However, genetic variation only explains a small fraction of the susceptibility to COPD, and sub-genome-wide significant loci may play a role in pathogenesis.ObjectivesRegulatory annotation with epigenetic evidence may give priority for further investigation, particularly for GWAS associations in noncoding regions. We performed integrative genomics analyses using DNA methylation profiling and genome-wide SNP genotyping from lung tissue samples from 90 subjects with COPD and 36 control subjects.MethodsWe performed methylation quantitative trait loci (mQTL) analyses, testing for SNPs associated with percent DNA methylation and assessed the colocalization of these results with previous COPD GWAS findings using Bayesian methods in the R package coloc to highlight potential regulatory features of the loci.Measurements and main resultsWe identified 942,068 unique SNPs and 33,996 unique CpG sites among the significant (5% false discovery rate) cis-mQTL results. The genome-wide significant and subthreshold (P < 10-4) GWAS SNPs were enriched in the significant mQTL SNPs (hypergeometric test P < 0.00001). We observed enrichment for sites located in CpG shores and shelves, but not CpG islands. Using Bayesian colocalization, we identified loci in regions near KCNK3, EEFSEC, PIK3CD, DCDC2C, TCERG1L, FRMD4B, and IL27.ConclusionsColocalization of mQTL and GWAS loci provides regulatory characterization of significant and subthreshold GWAS findings, supporting a role for genetic control of methylation in COPD pathogenesis.
| S-EPMC5955059 | biostudies-literature
Project description:A genomewide screen for quantitative-trait loci (QTLs) that underlie asthma was performed on 533 Chinese families with asthma, by the unified Haseman-Elston method. Nine asthma-related phenotypes were studied, including forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), airway responsiveness as indicated by methacholine (MTCH)-challenge test, serum total immunoglobulin E (TIgE), serum-specific immunoglobulin E, eosinophil count in peripheral blood, and skin-prick tests with three different allergens (cockroach, Dermatophagoides pteronyssinus, and D. farinae). Our study showed significant linkage between airway responsiveness to MTCH and D2S1780 on chromosome 2 (P<.00002) and provided suggestive evidence (P<.002) for six additional possible QTLs: D10S1435 and D22S685, for FEV1; D16S412, for FVC; D19S433, for airway responsiveness to MTCH; D1S518, for TIgE; and D4S1647, for skin reactivity to cockroach. No significant or suggestive evidence of linkage for the other four traits was found.
| S-EPMC1235539 | biostudies-literature
Project description:DNA methylation may be regulated by genetic variants within a genomic region, referred to as methylation quantitative trait loci (mQTLs). The changes of methylation levels can further lead to alterations of gene expression, and influence the risk of various complex human diseases. Detecting mQTLs may provide insights into the underlying mechanism of how genotypic variations may influence the disease risk. In this article, we propose a methylation random field (MRF) method to detect mQTLs by testing the association between the methylation level of a CpG site and a set of genetic variants within a genomic region. The proposed MRF has two major advantages over existing approaches. First, it uses a beta distribution to characterize the bimodal and interval properties of the methylation trait at a CpG site. Second, it considers multiple common and rare genetic variants within a genomic region to identify mQTLs. Through simulations, we demonstrated that the MRF had improved power over other existing methods in detecting rare variants of relatively large effect, especially when the sample size is small. We further applied our method to a study of congenital heart defects with 83 cardiac tissue samples and identified two mQTL regions, MRPS10 and PSORS1C1, which were colocalized with expression QTL in cardiac tissue. In conclusion, the proposed MRF is a useful tool to identify novel mQTLs, especially for studies with limited sample sizes.
| S-EPMC8575051 | biostudies-literature
Project description:BackgroundIntegration of metabolomics with genetics may advance understanding of disease pathogenesis but has been underused in asthma genetic studies.ObjectiveWe sought to discover new genetic effects in asthma and to characterize the molecular consequences of asthma genetic risk through integration with the metabolome in a homogeneous population.MethodsFrom fasting serum samples collected on 348 Tangier Island residents, we quantified 2612 compounds using untargeted metabolomics. Genotyping was performed using Illumina's MEGA array imputed to the TOPMed reference panel. To prioritize metabolites for genome-wide association analysis, we performed a metabolome-wide association study with asthma, selecting asthma-associated metabolites with heritability q value less than 0.01 for genome-wide association analysis. We also tested the association between all metabolites and 8451 candidate asthma single nucleotide polymorphisms previously associated with asthma in the UK Biobank. We followed up significant associations by characterizing shared genetic signal for metabolites and asthma using colocalization analysis. For detailed Methods, please see this article's Online Repository at www.jacionline.org.ResultsA total of 60 metabolites were associated with asthma (P < .01), including 40 heritable metabolites tested in genome-wide association analysis. We observed a strong association peak for the endocannabinoid linoleoyl ethanolamide on chromosome 6 in VNN1 (P < 2.7 × 10-9). We found strong evidence (colocalization posterior probability >75%) for a shared causal variant between 3 metabolites and asthma, including the polyamine acisoga and variants in LPP, and derivative leukotriene B4 and intergenic variants in chr10p14.ConclusionsWe identified novel metabolite quantitative trait loci with asthma associations. Identification and characterization of these genetically driven metabolites may provide insight into the functional consequences of genetic risk factors for asthma.
| S-EPMC9081120 | biostudies-literature
Project description:Mitochondria have a complex communication network with the surrounding cell and can alter nuclear DNA methylation (DNAm). Variation in the mitochondrial DNA (mtDNA) has also been linked to differential DNAm. Genome-wide association studies have identified numerous DNAm quantitative trait loci, but these studies have not examined the mitochondrial genome. Herein, we quantified nuclear DNAm from blood and conducted a mitochondrial genome-wide association study of DNAm, with an additional emphasis on sex- and prediabetes-specific heterogeneity. We used the Young Finns Study (n = 926) with sequenced mtDNA genotypes as a discovery sample and sought replication in the Ludwigshafen Risk and Cardiovascular Health study (n = 2317). We identified numerous significant associations in the discovery phase (P < 10-9), but they were not replicated when accounting for multiple testing. In total, 27 associations were nominally replicated with a P < 0.05. The replication analysis presented no evidence of sex- or prediabetes-specific heterogeneity. The 27 associations were included in a joint meta-analysis of the two cohorts, and 19 DNAm sites associated with mtDNA variants, while four other sites showed haplogroup associations. An expression quantitative trait methylation analysis was performed for the identified DNAm sites, pinpointing two statistically significant associations. This study provides evidence of a mitochondrial genetic control of nuclear DNAm with little evidence found for sex- and prediabetes-specific effects. The lack of a comparable mtDNA data set for replication is a limitation in our study and further studies are needed to validate our results.
| S-EPMC9122653 | biostudies-literature
Project description:MotivationCpG sites within the same genomic region often share similar methylation patterns and tend to be co-regulated by multiple genetic variants that may interact with one another.ResultsWe propose a multi-trait methylation random field (multi-MRF) method to evaluate the joint association between a set of CpG sites and a set of genetic variants. The proposed method has several advantages. First, it is a multi-trait method that allows flexible correlation structures between neighboring CpG sites (e.g. distance-based correlation). Second, it is also a multi-locus method that integrates the effect of multiple common and rare genetic variants. Third, it models the methylation traits with a beta distribution to characterize their bimodal and interval properties. Through simulations, we demonstrated that the proposed method had improved power over some existing methods under various disease scenarios. We further illustrated the proposed method via an application to a study of congenital heart defects (CHDs) with 83 cardiac tissue samples. Our results suggested that gene BACE2, a methylation quantitative trait locus (QTL) candidate, colocalized with expression QTLs in artery tibial and harbored genetic variants with nominal significant associations in two genome-wide association studies of CHD.Availability and implementationhttps://github.com/chenlyu2656/Multi-MRF.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9364381 | biostudies-literature
Project description:BackgroundSingle variant approaches have been successful in identifying DNA methylation quantitative trait loci (mQTL), although as with complex traits they lack the statistical power to identify the effects from rare genetic variants. We have undertaken extensive analyses to identify regions of low frequency and rare variants that are associated with DNA methylation levels.MethodsWe used repeated measurements of DNA methylation from five different life stages in human blood, taken from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Variants were collapsed across CpG islands and their flanking regions to identify variants collectively associated with methylation, where no single variant was individually responsible for the observed signal. All analyses were undertaken using the sequence kernel association test.ResultsFor loci where no individual variant mQTL was observed based on a single variant analysis, we identified 95 unique regions where the combined effect of low frequency variants (MAF ≤ 5%) provided strong evidence of association with methylation. For loci where there was previous evidence of an individual variant mQTL, a further 3 regions provided evidence of association between multiple low frequency variants and methylation levels. Effects were observed consistently across 5 different time points in the lifecourse and evidence of replication in the TwinsUK and Exeter cohorts was also identified.ConclusionWe have demonstrated the potential of this novel approach to mQTL analysis by analysing the combined effect of multiple low frequency or rare variants. Future studies should benefit from applying this approach as a complementary follow up to single variant analyses.
| S-EPMC5291201 | biostudies-literature
Project description:BackgroundMethylation quantitative trait loci (mQTLs) are the genetic variants that may affect the DNA methylation patterns of CpG sites. However, their roles in influencing the disturbances of smoking-related epigenetic changes have not been well established. This study was conducted to address whether mQTLs exist in the vicinity of smoking-related CpG sites (± 50 kb) and to examine their associations with smoking exposure and all-cause mortality in older adults.ResultsWe obtained DNA methylation profiles in whole blood samples by Illumina Infinium Human Methylation 450 BeadChip array of two independent subsamples of the ESTHER study (discovery set, n = 581; validation set, n = 368) and their corresponding genotyping data using the Illumina Infinium OncoArray BeadChip. After correction for multiple testing (FDR), we successfully identified that 70 out of 151 previously reported smoking-related CpG sites were significantly associated with 192 SNPs within the 50 kb search window of each locus. The 192 mQTLs significantly influenced the active smoking-related DNA methylation changes, with percentage changes ranging from 0.01 to 18.96%, especially for the weakly/moderately smoking-related CpG sites. However, these identified mQTLs were not directly associated with active smoking exposure or all-cause mortality.ConclusionsOur findings clearly demonstrated that if not dealt with properly, the mQTLs might impair the power of epigenetic-based models of smoking exposure to a certain extent. In addition, such genetic variants could be the key factor to distinguish between the heritable and smoking-induced impact on epigenome disparities. These mQTLs are of special importance when DNA methylation markers measured by Illumina Infinium assay are used for any comparative population studies related to smoking-related cancers and chronic diseases.
| S-EPMC5561570 | biostudies-literature
Project description:Genetic dissection of the S rat genome has provided strong evidence for the presence of two interacting blood pressure (BP) quantitative trait loci (QTLs), termed QTL1 and QTL2, on rat chromosome 5. However, the identities of the underlying interacting genetic factors remain unknown. Further experiments targeted to identify the interacting genetic factors by the substitution mapping approach alone are difficult because of the interdependency of natural recombinations to occur at the two QTLs. We hypothesized that the interacting genetic factors underlying these two QTLs may interact at the level of gene transcription and thereby represent expression QTLs (eQTLs). To detect these interacting eQTLs, a custom QTL chip containing the annotated genes within QTL1 and QTL2 was developed and used to conduct a transcriptional profiling study of S and two congenic strains that retain either one or both the QTLs. The results uncovered an interaction between two transcription factors, DMRTA2 and NFIA. Further, the âbiological signatureâ elicited by these two transcription factors was differential between the congenic strain that retained LEW alleles at both QTL1 and 2 compared to the congenic strain that retained LEW alleles at QTL1 alone. A network of transcription factors potentially affecting BP could be traced, lending support to our hypothesis. Pairs of Cy5 and Cy3 labeled targets were co-hybridized onto either a custom long oligonucleotide microarray for the interrogation of 231 genes encompassed by QTL1 and QTL2, or a TIGR rat cDNA array consisting of 26,401 probe elements representing 20,465 unique non-QTL genes. A âflip-dyeâ or âbalanced blockâ design was used as the experimental method of choice to account for potential dye-bias labeling effects. Six âbalanced blockâ normalized files are submitted for the long oligonucleotide array interrogating the hearts from S versus S.LEW(5)x6x9 animals, fourteen âflip-dyeâ hybridizations are submitted for the cDNA array interrogating the hearts from S versus S.LEW(5)x6x9 animals, and twelve âflip-dyeâ hybridizations are submitted for the cDNA array interrogating the hearts from S versus S.LEW(5)x6x11 animals. GPR and MEV files cannot be located.
2010-06-25 | E-GEOD-7628 | biostudies-arrayexpress
Project description:RATIONALE:Systemic glucocorticoids are used therapeutically to treat a variety of medical conditions. Epigenetic processes such as DNA methylation may reflect exposure to glucocorticoids and may be involved in mediating the responses and side effects associated with these medications. OBJECTIVES:To test the hypothesis that differences in DNA methylation are associated with current systemic steroid use. METHODS:We obtained DNA methylation data at 27,578 CpG sites in 14,475 genes throughout the genome in two large, independent cohorts: the International COPD Genetics Network (n(discovery) = 1,085) and the Boston Early Onset COPD study (n(replication) = 369). Sites were tested for association with current systemic steroid use using generalized linear mixed models. MEASUREMENTS AND MAIN RESULTS:A total of 511 sites demonstrated significant differential methylation by systemic corticosteroid use in all three of our primary models. Pyrosequencing validation confirmed robust differential methylation at CpG sites annotated to genes such as SLC22A18, LRP3, HIPK3, SCNN1A, FXYD1, IRF7, AZU1, SIT1, GPR97, ABHD16B, and RABGEF1. Functional annotation clustering demonstrated significant enrichment in intrinsic membrane components, hemostasis and coagulation, cellular ion homeostasis, leukocyte and lymphocyte activation and chemotaxis, protein transport, and responses to nutrients. CONCLUSIONS:Our analyses suggest that systemic steroid use is associated with site-specific differential methylation throughout the genome. Differentially methylated CpG sites were found in biologically plausible and previously unsuspected pathways; these genes and pathways may be relevant in the development of novel targeted therapies.
| S-EPMC3622442 | biostudies-literature