Comparative transcriptomic analysis of in the hindbrain of olive flounder (Paralichthys olivaceus) with distinct personality and oxygen metabolism
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ABSTRACT:
ORGANISM(S): Paralichthys olivaceus
PROVIDER: GSE164165 | GEO | 2021/12/31
REPOSITORIES: GEO
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Project description:Borderline personality disorder (BPD) is a complex psychiatric disease with an increased impact in the last years. While the diagnosis and therapy are well established, little is known on the pathogenesis of borderline personality disorder. Previously, a significant increase in DNA methylation of relevant neuropsychiatric genes in BPD patients has been reported. In our study we performed genome wide methylation analysis and revealed specific CpG sites that exhibited increased methylation in 26 BPD patients compared to 11 healthy controls. Bead chip technology and quantitative bisulfite pyrosequencing showed a significantly increased methylation at CpG sites of APBA2 (1.1 fold) and APBA3 (1.1 fold), KCNQ1 (1.6 fold), MCF2 (1.1 fold) and NINJ2 (1.2 fold) in BPD patients. For the CpG sites of GATA4 an increase in DNA methylation was observed, but was only significant in the bead chip assay. Moreover genome wide methylation levels of blood samples of BPD patients and control samples are similar. In summary, our results show a significant 1.26 fold average increase in methylation at the analyzed gene associated CpG sites in the blood of BPD patients compared to controls samples (p<0.001). This data may provide new insights into epigenetic mechanisms underlying the pathogenesis of BPD.
2014-02-01 | GSE52222 | GEO
Project description:Borderline personality disorder (BPD) is a complex psychiatric disease with an increased impact in the last years. While the diagnosis and therapy are well established, little is known on the pathogenesis of borderline personality disorder. Previously, a significant increase in DNA methylation of relevant neuropsychiatric genes in BPD patients has been reported. In our study we performed genome wide methylation analysis and revealed specific CpG sites that exhibited increased methylation in 26 BPD patients compared to 11 healthy controls. Bead chip technology and quantitative bisulfite pyrosequencing showed a significantly increased methylation at CpG sites of APBA2 (1.1 fold) and APBA3 (1.1 fold), KCNQ1 (1.6 fold), MCF2 (1.1 fold) and NINJ2 (1.2 fold) in BPD patients. For the CpG sites of GATA4 an increase in DNA methylation was observed, but was only significant in the bead chip assay. Moreover genome wide methylation levels of blood samples of BPD patients and control samples are similar. In summary, our results show a significant 1.26 fold average increase in methylation at the analyzed gene associated CpG sites in the blood of BPD patients compared to controls samples (p<0.001). This data may provide new insights into epigenetic mechanisms underlying the pathogenesis of BPD. Whole blood samples for 26 BPD patients and 11 controls were obtained from the Psychiatric Hospital in Münsterlingen, Switzerland. All patients signed informed consent at initial clinical investigation. The study was approved by the local ethic committee. Diagnosis of BPD was established by an experienced psychiatrist (Dr. G. W. Dammann). Clincopathological parameter of the patients and controls are summarized in table S1 (for details see (Dammann et al, 2011)). Genomic DNA from whole blood was isolated by Nucleo Spin XL Blood (Macherey and Nagel, Düren, Germany). For the bead chip array 500 ng of genomic DNA was treated with bisulfite (Dammann et al, 2011).
2014-02-01 | E-GEOD-52222 | biostudies-arrayexpress
Project description:Individual differences in basal leukocyte gene expression profiles as a function of Big 5 personality dimensions Gene expression profiling was carried out on peripheral blood mononuclear cell RNA samples collected from 119 healthy adults measured for the 5 major dimensions of human personality (Neuroticism, Extraversion, Openness, Agreeableness, Conscientiousness) using the NEO-FFI 60-item personality inventory. Personality measures are z-score standardized. Analyses control for major demographic characteristics (age, sex, Caucasian vs Non-Caucasian race) as well as Body Mass Index (BMI), smoking (CigDay), alcohol consumption (AlcDay), and physical activity (ExerDay, hours per day). Additional secondary analyses controlled for the presence of minor physical symptoms (MinorSymptom, e.g.,hayfever, headache), medication use (BirthControl, Antidepressant, OtherMedication), and negative affective states (NegativeAffect, standardized values of PANAS Negative Affect scale). Experiment type: Risk prediction
2015-01-28 | E-GEOD-60491 | biostudies-arrayexpress
Project description:Individual differences in basal leukocyte gene expression profiles as a function of Big 5 personality dimensions
2015-01-28 | GSE60491 | GEO
Project description:Background: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N=1 phenotypes. Methods: Whole blood samples from 4 African American women, 4 Caucasian women, and 4 Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNASeq, miRNASeq, and Illumina Methyl-450 arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure that is among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. Results: Longitudinal omic profiles are in general highly consistent over time, with an average of 67% of the variance in transcript abundance, 42% of CpG methylation level (but 88% for the most differentiated CpG per gene), and 50% of miRNA abundance among individuals, which are all comparable to 74% of the variance among individuals for 74 clinical traits. One third of the variance can be attributed to differential blood cell type abundance, which is also fairly stable over time, and a lesser amount to eQTL effects, whereas seven conserved axes of covariance that capture diverse aspects of immune function explain over half of the variance. These axes also explain a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that are significantly up- or down-regulated in each person and are in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes have individually divergent methylation levels, but these do not overlap with the transcripts, and fewer than 20% of genes have significantly correlated methylation and gene expression. Conclusions: People express an “omic personality” consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions. Whole blood samples from 12 subjects drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNASeq, miRNASeq, and Illumina Methyl-450 arrays.
2015-07-01 | E-GEOD-67488 | biostudies-arrayexpress
Project description:Background: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N=1 phenotypes. Methods: Whole blood samples from 4 African American women, 4 Caucasian women, and 4 Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNASeq, miRNASeq, and Illumina Methyl-450 arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure that is among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. Results: Longitudinal omic profiles are in general highly consistent over time, with an average of 67% of the variance in transcript abundance, 42% of CpG methylation level (but 88% for the most differentiated CpG per gene), and 50% of miRNA abundance among individuals, which are all comparable to 74% of the variance among individuals for 74 clinical traits. One third of the variance can be attributed to differential blood cell type abundance, which is also fairly stable over time, and a lesser amount to eQTL effects, whereas seven conserved axes of covariance that capture diverse aspects of immune function explain over half of the variance. These axes also explain a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that are significantly up- or down-regulated in each person and are in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes have individually divergent methylation levels, but these do not overlap with the transcripts, and fewer than 20% of genes have significantly correlated methylation and gene expression. Conclusions: People express an “omic personality” consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions. Whole blood samples from 12 subjects drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNASeq, miRNASeq, and Illumina Methyl-450 arrays.
2015-07-01 | E-GEOD-67489 | biostudies-arrayexpress
Project description:Background: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N=1 phenotypes. Methods: Whole blood samples from 4 African American women, 4 Caucasian women, and 4 Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNASeq, miRNASeq, and Illumina Methyl-450 arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure that is among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. Results: Longitudinal omic profiles are in general highly consistent over time, with an average of 67% of the variance in transcript abundance, 42% of CpG methylation level (but 88% for the most differentiated CpG per gene), and 50% of miRNA abundance among individuals, which are all comparable to 74% of the variance among individuals for 74 clinical traits. One third of the variance can be attributed to differential blood cell type abundance, which is also fairly stable over time, and a lesser amount to eQTL effects, whereas seven conserved axes of covariance that capture diverse aspects of immune function explain over half of the variance. These axes also explain a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that are significantly up- or down-regulated in each person and are in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes have individually divergent methylation levels, but these do not overlap with the transcripts, and fewer than 20% of genes have significantly correlated methylation and gene expression. Conclusions: People express an “omic personality” consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions. Whole blood samples from 12 subjects drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNASeq, miRNASeq, and Illumina Methyl-450 arrays.
2015-07-01 | E-GEOD-67490 | biostudies-arrayexpress
Project description:Graves’ ophthalmopathy (GO) is an extrathyroidal complication of Graves’ hyperthyroidism. Orbital fibroblast, an important cell in the pathogenesis of GO, is responsible for GO characteristics during active and inactive stages; however, information on the extensive profiles and the mechanistic regulations behind orbital fibroblast phenotypes are currently limited. The aim of this study was to compare the proteome profile of orbital fibroblasts isolated from inactive GO, active GO and healthy control. The proteome profile was further integrated with global DNA methylation data to identify this epigenetics regulation involved in the pathogenesis of GO. Methods Orbital fibroblasts culture isolated from five inactive GO, four active GO and five controls were cultured for total protein and DNA extraction. The labelled and fractionated proteins were analyzed with a liquid chromatography tandem-mass spectrometer (LC-MS/MS). On the other hand, the bisulphite-treated DNA was measured with the Illumina Infinium Human Methylation 450K beadchip. Proteome and methylation data were validated by real-time quantitative (RQ)-PCR. Network, pathway and functional analysis were performed by Ingenuity (Qiagen). Results Orbital fibroblasts from active GO displayed overexpression of proteins typically involved with inflammation, cellular proliferation, hyaluronan synthesis and adipogenesis, while several proteins linked to extracellular matrix (ECM) biology and fibrotic disease were overexpressed in orbital fibroblasts from inactive GO. The DNA methylation patterns were similar in healthy control and inactive GO orbital fibroblasts which were distinct from active GO orbital fibroblasts. In orbital fibroblasts from active GO hypermethylated genes link to inflammation while those genes hypomethylated are involved in adipogenesis and autoimmune-related genes. For the network analysis, overlapped between hypermethylated and hypomethylated genes were observed including NF-B, ERK1/2, Alp, RNA polymerase II, Akt and IFNα. In addition, NF-κB, Akt and IFNα were also identified in networks from the differentially expressed proteins. In general, poor correlation between protein expression, DNA methylation and mRNA expression in our study was observed.
2021-01-27 | PXD022257 | Pride
Project description:Background: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N=1 phenotypes. Methods: Whole blood samples from 4 African American women, 4 Caucasian women, and 4 Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNASeq, miRNASeq, and Illumina Methyl-450 arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure that is among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. Results: Longitudinal omic profiles are in general highly consistent over time, with an average of 67% of the variance in transcript abundance, 42% of CpG methylation level (but 88% for the most differentiated CpG per gene), and 50% of miRNA abundance among individuals, which are all comparable to 74% of the variance among individuals for 74 clinical traits. One third of the variance can be attributed to differential blood cell type abundance, which is also fairly stable over time, and a lesser amount to eQTL effects, whereas seven conserved axes of covariance that capture diverse aspects of immune function explain over half of the variance. These axes also explain a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that are significantly up- or down-regulated in each person and are in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes have individually divergent methylation levels, but these do not overlap with the transcripts, and fewer than 20% of genes have significantly correlated methylation and gene expression. Conclusions: People express an “omic personality” consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions.
2015-07-01 | GSE67488 | GEO
Project description:Background: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N=1 phenotypes. Methods: Whole blood samples from 4 African American women, 4 Caucasian women, and 4 Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNASeq, miRNASeq, and Illumina Methyl-450 arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure that is among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. Results: Longitudinal omic profiles are in general highly consistent over time, with an average of 67% of the variance in transcript abundance, 42% of CpG methylation level (but 88% for the most differentiated CpG per gene), and 50% of miRNA abundance among individuals, which are all comparable to 74% of the variance among individuals for 74 clinical traits. One third of the variance can be attributed to differential blood cell type abundance, which is also fairly stable over time, and a lesser amount to eQTL effects, whereas seven conserved axes of covariance that capture diverse aspects of immune function explain over half of the variance. These axes also explain a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that are significantly up- or down-regulated in each person and are in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes have individually divergent methylation levels, but these do not overlap with the transcripts, and fewer than 20% of genes have significantly correlated methylation and gene expression. Conclusions: People express an “omic personality” consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions.
2015-07-01 | GSE67490 | GEO