Transcriptomic and methylomic features in asthmatic and nonasthmatic twins.
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ABSTRACT:
SUBMITTER: Dhondalay GKR
PROVIDER: S-EPMC7176546 | biostudies-literature | 2020 Apr
REPOSITORIES: biostudies-literature
Publications
Transcriptomic and methylomic features in asthmatic and nonasthmatic twins.
Dhondalay Gopal Krishna R GKR Bunning Bryan B Bauer Rebecca N RN Barnathan Elliot S ES Maniscalco Christopher C Baribaud Frédéric F Nadeau Kari C KC Andorf Sandra S
Allergy 20200121 4
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Project description:BackgroundHouse dust mites (HDMs) represent one of the most important inducers of respiratory allergies worldwide.ObjectiveWe sought to investigate the IgE and IgG reactivity profiles to a comprehensive panel of HDM allergens in children with allergic asthma and to compare them with those of nonasthmatic atopic children.MethodsSera from clinically well-characterized asthmatic children with HDM allergy (n = 105), nonasthmatic children (n = 53), and nonatopic nonasthmatic children (n = 53) were analyzed for IgE and IgG reactivity to a panel of 7 HDM allergens (nDer p 1, rDer p 2, rDer p 5, rDer p 7, rDer p 10, rDer p 21, and rDer p 23) by means of allergen microarray technology.ResultsAsthmatic children with HDM allergy more frequently showed an IgE response to each of the HDM allergens and recognized more allergens than nonasthmatic children with HDM allergy. Furthermore, IgE levels to certain HDM allergens (nDer p 1, P = .002; rDer p 2, P = .007; rDer p 5, P = .031; and rDer p 23, P < .001) were significantly higher in asthmatic children than in children without asthma. By contrast, fewer asthmatic children showed IgG reactivity to HDM allergens than nonasthmatic children, but allergen-specific IgG levels were comparable.ConclusionThe IgE and IgG reactivity profiles to HDM allergens, as well as IgE levels to certain allergen components, differed considerably between children with and without asthmatic symptoms caused by HDM allergy. In fact, asthmatic children were characterized by an expanded IgE repertoire regarding the numbers of recognized allergen components and by increased specific IgE levels.
| S-EPMC4595482 | biostudies-literature
Project description:Childhood psychotic symptoms are associated with increased rates of schizophrenia, other psychiatric disorders, and suicide attempts in adulthood; thus, elucidating early risk indicators is crucial to target prevention efforts. There is considerable discordance for psychotic symptoms between monozygotic twins, indicating that child-specific non-genetic factors must be involved. Epigenetic processes may constitute one of these factors and have not yet been investigated in relation to childhood psychotic symptoms. Therefore, this study explored whether differences in DNA methylation at age 10 were associated with monozygotic twin discordance for psychotic symptoms at age 12. The Environmental Risk (E-Risk) Longitudinal Twin Study cohort of 2,232 children (1,116 twin pairs) was assessed for age-12 psychotic symptoms and 24 monozygotic twin pairs discordant for symptoms were identified for methylomic comparison. Children provided buccal samples at ages 5 and 10. DNA was bisulfite modified and DNA methylation was quantified using the Infinium HumanMethylation450 array. Differentially methylated positions (DMPs) associated with psychotic symptoms were subsequently tested in post-mortem prefrontal cortex tissue from adult schizophrenia patients and age-matched controls. Site-specific DNA methylation differences were observed at age 10 between monozygotic twins discordant for age-12 psychotic symptoms. Similar DMPs were not found at age 5. The top-ranked psychosis-associated DMP (cg23933044), located in the promoter of the C5ORF42 gene, was also hypomethylated in post-mortem prefrontal cortex brain tissue from schizophrenia patients compared to unaffected controls. These data tentatively suggest that epigenetic variation in peripheral tissue is associated with childhood psychotic symptoms and may indicate susceptibility to schizophrenia and other mental health problems.
| S-EPMC4867769 | biostudies-literature
Project description:BackgroundAdolescent depression is a common neuropsychiatric disorder that often continues into adulthood and is associated with a wide range of poor outcomes including suicide. Although numerous studies have looked at genetic markers associated with depression, the role of epigenetic variation remains relatively unexplored.MethodsMonozygotic (MZ) twins were selected from an adolescent twin study designed to investigate the interplay of genetic and environmental factors in the development of emotional and behavioral difficulties. There were 18 pairs of MZ twins identified in which one member scored consistently higher (group mean within the clinically significant range) on self-rated depression than the other. We assessed genome-wide patterns of DNA methylation in twin buccal cell DNA using the Infinium HumanMethylation450 BeadChip from Illumina. Quality control and data preprocessing was undertaken using the wateRmelon package. Differentially methylated probes (DMPs) were identified using an analysis strategy taking into account both the significance and the magnitude of DNA methylation differences. The top differentially methylated DMP was successfully validated by bisulfite-pyrosequencing, and identified DMPs were tested in postmortem brain samples obtained from patients with major depressive disorder (n = 14) and matched control subjects (n = 15).ResultsTwo reproducible depression-associated DMPs were identified, including the top-ranked DMP that was located within STK32C, which encodes a serine/threonine kinase, of unknown function.ConclusionsOur data indicate that DNA methylation differences are apparent in MZ twins discordant for adolescent depression and that some of the disease-associated variation observed in buccal cell DNA is mirrored in adult brain tissue obtained from individuals with clinical depression.
| S-EPMC4252163 | biostudies-literature
Project description:BackgroundAsthma is the most common chronic inflammatory disorder in children. The aetiology of asthma pathology is complex and highly heterogeneous, involving the interplay between genetic and environmental risk factors that is hypothesized to involve epigenetic processes. Our aim was to explore whether methylomic variation in early childhood is associated with discordance for asthma symptoms within monozygotic (MZ) twin pairs recruited from the Environmental Risk (E-Risk) longitudinal twin study. We also aimed to identify differences in DNA methylation that are associated with asthma that develops in childhood and persists into early adulthood as these may represent useful prognostic biomarkers.ResultsWe examined genome-wide patterns of DNA methylation in buccal cell samples collected from 37 MZ twin pairs discordant for asthma at age 10. DNA methylation at individual CpG sites demonstrated significant variability within discordant MZ twin pairs with the top-ranked nominally significant differentially methylated position (DMP) located in the HGSNAT gene. We stratified our analysis by assessing DNA methylation differences in a sub-group of MZ twin pairs who remained persistently discordant for asthma at age 18. The top-ranked nominally significant DMP associated with persisting asthma is located in the vicinity of the HLX gene, which has been previously implicated in childhood asthma.ConclusionsWe identified DNA methylation differences associated with childhood asthma in peripheral DNA samples from discordant MZ twin pairs. Our data suggest that differences in DNA methylation associated with childhood asthma which persists into early adulthood are distinct from those associated with asthma which remits.
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Project description:Autism spectrum disorder (ASD) defines a group of common, complex neurodevelopmental disorders. Although the aetiology of ASD has a strong genetic component, there is considerable monozygotic (MZ) twin discordance indicating a role for non-genetic factors. Because MZ twins share an identical DNA sequence, disease-discordant MZ twin pairs provide an ideal model for examining the contribution of environmentally driven epigenetic factors in disease. We performed a genome-wide analysis of DNA methylation in a sample of 50 MZ twin pairs (100 individuals) sampled from a representative population cohort that included twins discordant and concordant for ASD, ASD-associated traits and no autistic phenotype. Within-twin and between-group analyses identified numerous differentially methylated regions associated with ASD. In addition, we report significant correlations between DNA methylation and quantitatively measured autistic trait scores across our sample cohort. This study represents the first systematic epigenomic analyses of MZ twins discordant for ASD and implicates a role for altered DNA methylation in autism.
| S-EPMC3906213 | biostudies-literature
Project description:OBJECTIVES:The number of DNA methylome and RNA transcriptome studies is growing, but investigators have to consider the cell type composition of tissues used. In blood samples, the data reflect the picture of a mixture of different cells. Specialized algorithms can address the cell-type heterogeneity issue. We tested if these corrections are correlated between two heterogeneous datasets. RESULTS:We used methylome and transcriptome datasets derived from a cohort of ten individuals whose blood was sampled at two different timepoints. We examined how the cell composition derived from these omics correlated with each other using "CIBERSORT" for the transcriptome and "estimateCellCounts function" in R for the methylome. The correlation coefficients between the two omic datasets ranged from 0.45 to 0.81 but correlations were minimal between two different timepoints. Our results suggest that a posteriori correction of a mixture of cells present in blood samples is reliable. Using an omic dataset to correct a second dataset for relative fractions of cells appears to be applicable, but only when the samples are simultaneously collected. This could be beneficial when there are difficulties to control the cell types in the second dataset, even when the sample size is limited.
| S-EPMC7017605 | biostudies-literature
Project description:Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes for brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top-associated cis-expression or -DNA methylation (DNAm) quantitative trait loci (cis-eQTLs or cis-mQTLs) between brain and blood (r b ). Using publicly available data, we find that genetic effects at the top cis-eQTLs or mQTLs are highly correlated between independent brain and blood samples ([Formula: see text] for cis-eQTLs and [Formula: see text] for cis-mQTLs). Using meta-analyzed brain cis-eQTL/mQTL data (n = 526 to 1194), we identify 61 genes and 167 DNAm sites associated with four brain-related phenotypes, most of which are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = 1980 to 14,115). Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL/mQTL data with large sample sizes.
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Project description:Human leukocyte antigen (HLA)-G, a HLA class Ib molecule, interacts with receptors on lymphocytes such as T cells, B cells, and natural killer cells to influence immune responses. Unlike classical HLA molecules, HLA-G expression is not found on all somatic cells, but restricted to tissue sites, including human bronchial epithelium cells (HBEC). Individual variation in HLA-G expression is linked to its genetic polymorphism and has been associated with many pathological situations such as asthma, which is characterized by epithelium abnormalities and inflammatory cell activation. Studies reported both higher and equivalent soluble HLA-G (sHLA-G) expression in different cohorts of asthmatic patients. In particular, we recently described impaired local expression of HLA-G and abnormal profiles for alternatively spliced isoforms in HBEC from asthmatic patients. sHLA-G dosage is challenging because of its many levels of polymorphism (dimerization, association with β2-microglobulin, and alternative splicing), thus many clinical studies focused on HLA-G single-nucleotide polymorphisms as predictive biomarkers, but few analyzed HLA-G haplotypes. Here, we aimed to characterize HLA-G haplotypes and describe their association with asthmatic clinical features and sHLA-G peripheral expression and to describe variations in transcription factor (TF) binding sites and alternative splicing sites. HLA-G haplotypes were differentially distributed in 330 healthy and 580 asthmatic individuals. Furthermore, HLA-G haplotypes were associated with asthmatic clinical features showed. However, we did not confirm an association between sHLA-G and genetic, biological, or clinical parameters. HLA-G haplotypes were phylogenetically split into distinct groups, with each group displaying particular variations in TF binding or RNA splicing sites that could reflect differential HLA-G qualitative or quantitative expression, with tissue-dependent specificities. Our results, based on a multicenter cohort, thus support the pertinence of HLA-G haplotypes as predictive genetic markers for asthma.
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Project description:Hypertrophic cardiomyopathy (HCM) is a disease of heart muscle, which affects ∼1 in 500 individuals and is characterized by increased left ventricular wall thickness. While HCM is caused by pathogenic variants in any one of eight sarcomere protein genes, clinical expression varies considerably, even among patients with the same pathogenic variant. To determine whether background genetic variation or environmental factors drive these differences, we studied disease progression in 11 pairs of monozygotic HCM twins. The twin pairs were followed for 5 to 14 y, and left ventricular wall thickness, left atrial diameter, and left ventricular ejection fraction were collected from echocardiograms at various time points. All nine twin pairs with sarcomere protein gene variants and two with unknown disease etiologies had discordant morphologic features of the heart, demonstrating the influence of nonhereditable factors on clinical expression of HCM. Whole genome sequencing analysis of the six monozygotic twins with discordant HCM phenotypes did not reveal notable somatic genetic variants that might explain their clinical differences. Discordant cardiac morphology of identical twins highlights a significant role for epigenetics and environment in HCM disease progression.
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Project description:Biological omics data such as transcriptomes and methylomes have the inherent "large p small n" paradigm, i.e., the number of features is much larger than that of the samples. A feature selection (FS) algorithm selects a subset of the transcriptomic or methylomic biomarkers in order to build a better prediction model. The hidden patterns in the FS solution space make it challenging to achieve a feature subset with satisfying prediction performances. Swarm intelligence (SI) algorithms mimic the target searching behaviors of various animals and have demonstrated promising capabilities in selecting features with good machine learning performances. Our study revealed that different SI-based feature selection algorithms contributed complementary searching capabilities in the FS solution space, and their collaboration generated a better feature subset than the individual SI feature selection algorithms. Nine SI-based feature selection algorithms were integrated to vote for the selected features, which were further refined by the dynamic recursive feature elimination framework. In most cases, the proposed Zoo algorithm outperformed the existing feature selection algorithms on transcriptomics and methylomics datasets.
| S-EPMC8621246 | biostudies-literature