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Results: 1 to 10 of 109

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The impact of sex on gene expression across human tissues.
Oliva M, Muñoz-Aguirre M, Kim-Hellmuth S, Wucher V, Gewirtz ADH, Cotter DJ, Parsana P, Kasela S, Balliu B, Viñuela A, Castel SE, Mohammadi P, Aguet F, Zou Y, Khramtsova EA, Skol AD, Garrido-Martín D, Reverter F, Brown A, Evans P, Gamazon ER, Payne A, Bonazzola R, Barbeira AN, Hamel AR, Martinez-Perez A, Soria JM, GTEx Consortium, Pierce BL, Stephens M, Eskin E, Dermitzakis ET, Segrè AV, Im HK, Engelhardt BE, Ardlie KG, Montgomery SB, Battle AJ, Lappalainen T, Guigó R, Stranger BE
(2020) Science 369:
MeSH Terms: Chromosomes, Human, X, Disease, Epigenesis, Genetic, Female, Gene Expression, Gene Expression Regulation, Genetic Variation, Genome-Wide Association Study, Humans, Male, Organ Specificity, Promoter Regions, Genetic, Quantitative Trait Loci, Sex Characteristics, Sex Factors
Show Abstract · Added September 15, 2020
Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.
Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
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15 MeSH Terms
DNA methylation of HPA-axis genes and the onset of major depressive disorder in adolescent girls: a prospective analysis.
Humphreys KL, Moore SR, Davis EG, MacIsaac JL, Lin DTS, Kobor MS, Gotlib IH
(2019) Transl Psychiatry 9: 245
MeSH Terms: Adolescent, CpG Islands, DNA Methylation, Depressive Disorder, Major, Epigenesis, Genetic, Female, Genotype, Humans, Hypothalamo-Hypophyseal System, Pituitary-Adrenal System, Polymorphism, Single Nucleotide, Proportional Hazards Models, Prospective Studies, Receptors, Corticotropin-Releasing Hormone, Receptors, Glucocorticoid
Show Abstract · Added March 3, 2020
The stress response system is disrupted in individuals with major depressive disorder (MDD) as well as in those at elevated risk for developing MDD. We examined whether DNA methylation (DNAm) levels of CpG sites within HPA-axis genes predict the onset of MDD. Seventy-seven girls, approximately half (n = 37) of whom were at familial risk for MDD, were followed longitudinally. Saliva samples were taken in adolescence (M age = 13.06 years [SD = 1.52]) when participants had no current or past MDD diagnosis. Diagnostic interviews were administered approximately every 18 months until the first onset of MDD or early adulthood (M age of last follow-up = 19.23 years [SD = 2.69]). We quantified DNAm in saliva samples using the Illumina EPIC chip and examined CpG sites within six key HPA-axis genes (NR3C1, NR3C2, CRH, CRHR1, CRHR2, FKBP5) alongside 59 genotypes for tagging SNPs capturing cis genetic variability. DNAm levels within CpG sites in NR3C1, CRH, CRHR1, and CRHR2 were associated with risk for MDD across adolescence and young adulthood. To rule out the possibility that findings were merely due to the contribution of genetic variability, we re-analyzed the data controlling for cis genetic variation within these candidate genes. Importantly, methylation levels in these CpG sites continued to significantly predict the onset of MDD, suggesting that variation in the epigenome, independent of proximal genetic variants, prospectively predicts the onset of MDD. These findings suggest that variation in the HPA axis at the level of the methylome may predict the development of MDD.
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15 MeSH Terms
DNA methylation profiles are associated with complex regional pain syndrome after traumatic injury.
Bruehl S, Gamazon ER, Van de Ven T, Buchheit T, Walsh CG, Mishra P, Ramanujan K, Shaw A
(2019) Pain 160: 2328-2337
MeSH Terms: Adult, Case-Control Studies, Combat Disorders, Complex Regional Pain Syndromes, DNA Methylation, Epigenesis, Genetic, Female, Genetic Profile, Hospitals, Veterans, Humans, Male, Veterans
Show Abstract · Added July 17, 2019
Factors contributing to development of complex regional pain syndrome (CRPS) are not fully understood. This study examined possible epigenetic mechanisms that may contribute to CRPS after traumatic injury. DNA methylation profiles were compared between individuals developing CRPS (n = 9) and those developing non-CRPS neuropathic pain (n = 38) after undergoing amputation following military trauma. Linear Models for Microarray (LIMMA) analyses revealed 48 differentially methylated cytosine-phosphate-guanine dinucleotide (CpG) sites between groups (unadjusted P's < 0.005), with the top gene COL11A1 meeting Bonferroni-adjusted P < 0.05. The second largest differential methylation was observed for the HLA-DRB6 gene, an immune-related gene linked previously to CRPS in a small gene expression study. For all but 7 of the significant CpG sites, the CRPS group was hypomethylated. Numerous functional Gene Ontology-Biological Process categories were significantly enriched (false discovery rate-adjusted q value <0.15), including multiple immune-related categories (eg, activation of immune response, immune system development, regulation of immune system processes, and antigen processing and presentation). Differentially methylated genes were more highly connected in human protein-protein networks than expected by chance (P < 0.05), supporting the biological relevance of the findings. Results were validated in an independent sample linking a DNA biobank with electronic health records (n = 126 CRPS phenotype, n = 19,768 non-CRPS chronic pain phenotype). Analyses using PrediXcan methodology indicated differences in the genetically determined component of gene expression in 7 of 48 genes identified in methylation analyses (P's < 0.02). Results suggest that immune- and inflammatory-related factors might confer risk of developing CRPS after traumatic injury. Validation findings demonstrate the potential of using electronic health records linked to DNA for genomic studies of CRPS.
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12 MeSH Terms
Extrinsic and Intrinsic Immunometabolism Converge: Perspectives on Future Research and Therapeutic Development for Obesity.
Caslin HL, Hasty AH
(2019) Curr Obes Rep 8: 210-219
MeSH Terms: Adaptive Immunity, Adipose Tissue, Animals, Energy Metabolism, Epigenesis, Genetic, Humans, Immunity, Immunologic Memory, Iron, Macrophages, Metabolic Diseases, Metabolic Networks and Pathways, MicroRNAs, Obesity
Show Abstract · Added March 3, 2020
PURPOSE OF REVIEW - Research over the past decade has shown that immunologic and metabolic pathways are intricately linked. This burgeoning field of immunometabolism includes intrinsic and extrinsic pathways and is known to be associated with obesity-accelerated metabolic disease. Intrinsic immunometabolism includes the study of fuel utilization and bioenergetic pathways that influence immune cell function. Extrinsic immunometabolism includes the study of immune cells and products that influence systemic metabolism.
RECENT FINDINGS - Th2 immunity, macrophage iron handling, adaptive immune memory, and epigenetic regulation of immunity, which all require intrinsic metabolic changes, play a role in systemic metabolism and metabolic function, linking the two arms of immunometabolism. Together, this suggests that targeting intrinsic immunometabolism can directly affect immune function and ultimately systemic metabolism. We highlight important questions for future basic research that will help improve translational research and provide therapeutic targets to help establish new treatments for obesity and associated metabolic disorders.
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Machine learning selected smoking-associated DNA methylation signatures that predict HIV prognosis and mortality.
Zhang X, Hu Y, Aouizerat BE, Peng G, Marconi VC, Corley MJ, Hulgan T, Bryant KJ, Zhao H, Krystal JH, Justice AC, Xu K
(2018) Clin Epigenetics 10: 155
MeSH Terms: Adult, CpG Islands, DNA Methylation, Epigenesis, Genetic, Female, Frailty, Genome-Wide Association Study, HIV Infections, Humans, Machine Learning, Male, Middle Aged, Mortality, Prognosis, Signal Transduction, Smoking
Show Abstract · Added December 11, 2019
BACKGROUND - The effects of tobacco smoking on epigenome-wide methylation signatures in white blood cells (WBCs) collected from persons living with HIV may have important implications for their immune-related outcomes, including frailty and mortality. The application of a machine learning approach to the analysis of CpG methylation in the epigenome enables the selection of phenotypically relevant features from high-dimensional data. Using this approach, we now report that a set of smoking-associated DNA-methylated CpGs predicts HIV prognosis and mortality in an HIV-positive veteran population.
RESULTS - We first identified 137 epigenome-wide significant CpGs for smoking in WBCs from 1137 HIV-positive individuals (p < 1.70E-07). To examine whether smoking-associated CpGs were predictive of HIV frailty and mortality, we applied ensemble-based machine learning to build a model in a training sample employing 408,583 CpGs. A set of 698 CpGs was selected and predictive of high HIV frailty in a testing sample [(area under curve (AUC) = 0.73, 95%CI 0.63~0.83)] and was replicated in an independent sample [(AUC = 0.78, 95%CI 0.73~0.83)]. We further found an association of a DNA methylation index constructed from the 698 CpGs that were associated with a 5-year survival rate [HR = 1.46; 95%CI 1.06~2.02, p = 0.02]. Interestingly, the 698 CpGs located on 445 genes were enriched on the integrin signaling pathway (p = 9.55E-05, false discovery rate = 0.036), which is responsible for the regulation of the cell cycle, differentiation, and adhesion.
CONCLUSION - We demonstrated that smoking-associated DNA methylation features in white blood cells predict HIV infection-related clinical outcomes in a population living with HIV.
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MeSH Terms
HDAC11 suppresses the thermogenic program of adipose tissue via BRD2.
Bagchi RA, Ferguson BS, Stratton MS, Hu T, Cavasin MA, Sun L, Lin YH, Liu D, Londono P, Song K, Pino MF, Sparks LM, Smith SR, Scherer PE, Collins S, Seto E, McKinsey TA
(2018) JCI Insight 3:
MeSH Terms: Adipose Tissue, Brown, Adipose Tissue, White, Adult, Aged, Aged, 80 and over, Animals, Diet, High-Fat, Disease Models, Animal, Energy Metabolism, Epigenesis, Genetic, Fatty Liver, Female, Gene Expression Regulation, Histone Deacetylases, Humans, Insulin Resistance, Male, Mice, Mice, Knockout, Middle Aged, Obesity, Thermogenesis, Transcription Factors
Show Abstract · Added July 22, 2020
Little is known about the biological function of histone deacetylase 11 (HDAC11), which is the lone class IV HDAC. Here, we demonstrate that deletion of HDAC11 in mice stimulates brown adipose tissue (BAT) formation and beiging of white adipose tissue (WAT). Consequently, HDAC11-deficient mice exhibit enhanced thermogenic potential and, in response to high-fat feeding, attenuated obesity, improved insulin sensitivity, and reduced hepatic steatosis. Ex vivo and cell-based assays revealed that HDAC11 catalytic activity suppresses the BAT transcriptional program, in both the basal state and in response to β-adrenergic receptor signaling, through a mechanism that is dependent on physical association with BRD2, a bromodomain and extraterminal (BET) acetyl-histone-binding protein. These findings define an epigenetic pathway for the regulation of energy homeostasis and suggest the potential for HDAC11-selective inhibitors for the treatment of obesity and diabetes.
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Epigenetic modifiers: activities in renal cell carcinoma.
de Cubas AA, Rathmell WK
(2018) Nat Rev Urol 15: 599-614
MeSH Terms: Carcinoma, Renal Cell, Chromatin, Epigenesis, Genetic, Humans, Kidney Neoplasms, Mutation
Show Abstract · Added October 30, 2019
Renal cell carcinomas (RCCs) are a diverse set of malignancies that have recently been shown to harbour mutations in a number of chromatin modifier genes - including PBRM1, SETD2, BAP1, KDM5C, KDM6A, and MLL2 - through high-throughput sequencing efforts. Current research focuses on understanding the biological activities that chromatin modifiers employ to suppress tumorigenesis and on developing clinical approaches that take advantage of this knowledge. Unsurprisingly, several common themes unify the functions of these epigenetic modifiers, particularly regulation of histone post-translational modifications and nucleosome organization. Furthermore, chromatin modifiers also govern processes crucial for DNA repair and maintenance of genomic integrity as well as the regulation of splicing and other key processes. Many chromatin modifiers have additional non-canonical roles in cytoskeletal regulation, which further contribute to genomic stability, expanding the repertoire of functions that might be essential in tumorigenesis. Our understanding of how mutations in chromatin modifiers contribute to tumorigenesis in RCC is improving but remains an area of intense investigation. Importantly, elucidating the activities of chromatin modifiers offers intriguing opportunities for the development of new therapeutic interventions in RCC.
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Immunity drives regulation in cancer through NF-κB.
Collignon E, Canale A, Al Wardi C, Bizet M, Calonne E, Dedeurwaerder S, Garaud S, Naveaux C, Barham W, Wilson A, Bouchat S, Hubert P, Van Lint C, Yull F, Sotiriou C, Willard-Gallo K, Noel A, Fuks F
(2018) Sci Adv 4: eaap7309
MeSH Terms: Adaptive Immunity, Biomarkers, DNA Methylation, Epigenesis, Genetic, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Humans, Immunity, Immunity, Innate, Mixed Function Oxygenases, NF-kappa B, Neoplasms, Neoplasms, Basal Cell, Promoter Regions, Genetic, Protein Binding, Proto-Oncogene Proteins
Show Abstract · Added March 31, 2020
Ten-eleven translocation enzymes (TET1, TET2, and TET3), which induce DNA demethylation and gene regulation by converting 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC), are often down-regulated in cancer. We uncover, in basal-like breast cancer (BLBC), genome-wide 5hmC changes related to regulation. We further demonstrate that repression is associated with high expression of immune markers and high infiltration by immune cells. We identify in BLBC tissues an anticorrelation between expression and the major immunoregulator family nuclear factor κB (NF-κB). In vitro and in mice, is down-regulated in breast cancer cells upon NF-κB activation through binding of p65 to its consensus sequence in the promoter. We lastly show that these findings extend to other cancer types, including melanoma, lung, and thyroid cancers. Together, our data suggest a novel mode of regulation for in cancer and highlight a new paradigm in which the immune system can influence cancer cell epigenetics.
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Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.
Malta TM, Sokolov A, Gentles AJ, Burzykowski T, Poisson L, Weinstein JN, Kamińska B, Huelsken J, Omberg L, Gevaert O, Colaprico A, Czerwińska P, Mazurek S, Mishra L, Heyn H, Krasnitz A, Godwin AK, Lazar AJ, Cancer Genome Atlas Research Network, Stuart JM, Hoadley KA, Laird PW, Noushmehr H, Wiznerowicz M
(2018) Cell 173: 338-354.e15
MeSH Terms: Carcinogenesis, Cell Dedifferentiation, DNA Methylation, Databases, Genetic, Epigenesis, Genetic, Humans, Machine Learning, MicroRNAs, Neoplasm Metastasis, Neoplasms, Stem Cells, Transcriptome, Tumor Microenvironment
Show Abstract · Added October 30, 2019
Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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Comparative Molecular Analysis of Gastrointestinal Adenocarcinomas.
Liu Y, Sethi NS, Hinoue T, Schneider BG, Cherniack AD, Sanchez-Vega F, Seoane JA, Farshidfar F, Bowlby R, Islam M, Kim J, Chatila W, Akbani R, Kanchi RS, Rabkin CS, Willis JE, Wang KK, McCall SJ, Mishra L, Ojesina AI, Bullman S, Pedamallu CS, Lazar AJ, Sakai R, Cancer Genome Atlas Research Network, Thorsson V, Bass AJ, Laird PW
(2018) Cancer Cell 33: 721-735.e8
MeSH Terms: Adenocarcinoma, Aneuploidy, Chromosomal Instability, DNA Methylation, DNA Polymerase II, DNA-Binding Proteins, Epigenesis, Genetic, Female, Gastrointestinal Neoplasms, Gene Regulatory Networks, Heterogeneous-Nuclear Ribonucleoproteins, Humans, Male, Microsatellite Instability, MutL Protein Homolog 1, Mutation, Poly-ADP-Ribose Binding Proteins, Polymorphism, Single Nucleotide, Proto-Oncogene Proteins p21(ras), RNA-Binding Proteins, SOX9 Transcription Factor
Show Abstract · Added October 30, 2019
We analyzed 921 adenocarcinomas of the esophagus, stomach, colon, and rectum to examine shared and distinguishing molecular characteristics of gastrointestinal tract adenocarcinomas (GIACs). Hypermutated tumors were distinct regardless of cancer type and comprised those enriched for insertions/deletions, representing microsatellite instability cases with epigenetic silencing of MLH1 in the context of CpG island methylator phenotype, plus tumors with elevated single-nucleotide variants associated with mutations in POLE. Tumors with chromosomal instability were diverse, with gastroesophageal adenocarcinomas harboring fragmented genomes associated with genomic doubling and distinct mutational signatures. We identified a group of tumors in the colon and rectum lacking hypermutation and aneuploidy termed genome stable and enriched in DNA hypermethylation and mutations in KRAS, SOX9, and PCBP1.
Copyright © 2018 Elsevier Inc. All rights reserved.
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21 MeSH Terms