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Helicobacter pylori and its secreted immunomodulator VacA protect against anaphylaxis in experimental models of food allergy.
Kyburz A, Urban S, Altobelli A, Floess S, Huehn J, Cover TL, Müller A
(2017) Clin Exp Allergy 47: 1331-1341
MeSH Terms: Allergens, Anaphylaxis, Animals, Bacterial Proteins, CpG Islands, Cytokines, DNA Methylation, Disease Models, Animal, Food Hypersensitivity, Helicobacter pylori, Immunoglobulin E, Immunologic Factors, Male, Mice, Peanut Hypersensitivity, Spleen, T-Lymphocytes, Regulatory
Show Abstract · Added March 21, 2018
BACKGROUND - Food allergy is an increasingly common health problem in Western populations. Epidemiological studies have suggested both positive and negative associations between food allergy and infection with the gastric bacterium Helicobacter pylori.
OBJECTIVE - The objective of this work was to investigate whether experimental infection with H. pylori, or prophylactic treatment with H. pylori-derived immunomodulatory molecules, affects the onset and severity of food allergy, either positively or negatively.
METHODS - We infected neonatal C57BL/6 or C3H mice with H. pylori or treated animals with H. pylori components (bacterial lysate or the immunomodulator VacA) and subsequently subjected them to four different protocols for food allergy induction, using either ovalbumin or peanut extract as allergens for sensitization and challenge. Readouts included anaphylaxis scoring, quantification of allergen-specific serum IgE and IgG1 and of the mast cell protease MCPT1, as well as splenic T-helper-2 cell-derived cytokine production. Mesenteric lymph node CD4 FoxP3 regulatory T cells were subjected to flow cytometric quantification and sorting followed by qRT-PCR, and to DNA methylation analyses of the Treg-specific demethylated region (TSDR) within the FOXP3 locus.
RESULTS - Mice that had been infected with H. pylori or treated with H. pylori-derived immunomodulators showed reduced anaphylaxis upon allergen sensitization and challenge, irrespective of the allergen used. Most of the immunologic assays confirmed a protective effect of H. pylori. CD4 FoxP3 T cells were more abundant in protected mice and exhibited a stable Treg phenotype characterized by FOXP3 TSDR demethylation.
CONCLUSIONS AND CLINICAL RELEVANCE - Helicobacter pylori confers protection against the anaphylaxis associated with ovalbumin and peanut allergy and affects the epigenome of T cells, thereby promoting stable Treg differentiation and functionality. Prophylactic treatment with H. pylori-derived immunomodulators appears to be a promising strategy for food allergy prevention.
© 2017 John Wiley & Sons Ltd.
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17 MeSH Terms
Comprehensive Molecular Characterization of Papillary Renal-Cell Carcinoma.
Cancer Genome Atlas Research Network, Linehan WM, Spellman PT, Ricketts CJ, Creighton CJ, Fei SS, Davis C, Wheeler DA, Murray BA, Schmidt L, Vocke CD, Peto M, Al Mamun AA, Shinbrot E, Sethi A, Brooks S, Rathmell WK, Brooks AN, Hoadley KA, Robertson AG, Brooks D, Bowlby R, Sadeghi S, Shen H, Weisenberger DJ, Bootwalla M, Baylin SB, Laird PW, Cherniack AD, Saksena G, Haake S, Li J, Liang H, Lu Y, Mills GB, Akbani R, Leiserson MD, Raphael BJ, Anur P, Bottaro D, Albiges L, Barnabas N, Choueiri TK, Czerniak B, Godwin AK, Hakimi AA, Ho TH, Hsieh J, Ittmann M, Kim WY, Krishnan B, Merino MJ, Mills Shaw KR, Reuter VE, Reznik E, Shelley CS, Shuch B, Signoretti S, Srinivasan R, Tamboli P, Thomas G, Tickoo S, Burnett K, Crain D, Gardner J, Lau K, Mallery D, Morris S, Paulauskis JD, Penny RJ, Shelton C, Shelton WT, Sherman M, Thompson E, Yena P, Avedon MT, Bowen J, Gastier-Foster JM, Gerken M, Leraas KM, Lichtenberg TM, Ramirez NC, Santos T, Wise L, Zmuda E, Demchok JA, Felau I, Hutter CM, Sheth M, Sofia HJ, Tarnuzzer R, Wang Z, Yang L, Zenklusen JC, Zhang J, Ayala B, Baboud J, Chudamani S, Liu J, Lolla L, Naresh R, Pihl T, Sun Q, Wan Y, Wu Y, Ally A, Balasundaram M, Balu S, Beroukhim R, Bodenheimer T, Buhay C, Butterfield YS, Carlsen R, Carter SL, Chao H, Chuah E, Clarke A, Covington KR, Dahdouli M, Dewal N, Dhalla N, Doddapaneni HV, Drummond JA, Gabriel SB, Gibbs RA, Guin R, Hale W, Hawes A, Hayes DN, Holt RA, Hoyle AP, Jefferys SR, Jones SJ, Jones CD, Kalra D, Kovar C, Lewis L, Li J, Ma Y, Marra MA, Mayo M, Meng S, Meyerson M, Mieczkowski PA, Moore RA, Morton D, Mose LE, Mungall AJ, Muzny D, Parker JS, Perou CM, Roach J, Schein JE, Schumacher SE, Shi Y, Simons JV, Sipahimalani P, Skelly T, Soloway MG, Sougnez C, Tam A, Tan D, Thiessen N, Veluvolu U, Wang M, Wilkerson MD, Wong T, Wu J, Xi L, Zhou J, Bedford J, Chen F, Fu Y, Gerstein M, Haussler D, Kasaian K, Lai P, Ling S, Radenbaugh A, Van Den Berg D, Weinstein JN, Zhu J, Albert M, Alexopoulou I, Andersen JJ, Auman JT, Bartlett J, Bastacky S, Bergsten J, Blute ML, Boice L, Bollag RJ, Boyd J, Castle E, Chen YB, Cheville JC, Curley E, Davies B, DeVolk A, Dhir R, Dike L, Eckman J, Engel J, Harr J, Hrebinko R, Huang M, Huelsenbeck-Dill L, Iacocca M, Jacobs B, Lobis M, Maranchie JK, McMeekin S, Myers J, Nelson J, Parfitt J, Parwani A, Petrelli N, Rabeno B, Roy S, Salner AL, Slaton J, Stanton M, Thompson RH, Thorne L, Tucker K, Weinberger PM, Winemiller C, Zach LA, Zuna R
(2016) N Engl J Med 374: 135-45
MeSH Terms: Carcinoma, Papillary, CpG Islands, DNA Methylation, Humans, Kidney Neoplasms, MicroRNAs, Mutation, NF-E2-Related Factor 2, Phenotype, Proto-Oncogene Proteins c-met, RNA, Messenger, RNA, Neoplasm, Sequence Analysis, RNA, Signal Transduction
Show Abstract · Added August 8, 2016
BACKGROUND - Papillary renal-cell carcinoma, which accounts for 15 to 20% of renal-cell carcinomas, is a heterogeneous disease that consists of various types of renal cancer, including tumors with indolent, multifocal presentation and solitary tumors with an aggressive, highly lethal phenotype. Little is known about the genetic basis of sporadic papillary renal-cell carcinoma, and no effective forms of therapy for advanced disease exist.
METHODS - We performed comprehensive molecular characterization of 161 primary papillary renal-cell carcinomas, using whole-exome sequencing, copy-number analysis, messenger RNA and microRNA sequencing, DNA-methylation analysis, and proteomic analysis.
RESULTS - Type 1 and type 2 papillary renal-cell carcinomas were shown to be different types of renal cancer characterized by specific genetic alterations, with type 2 further classified into three individual subgroups on the basis of molecular differences associated with patient survival. Type 1 tumors were associated with MET alterations, whereas type 2 tumors were characterized by CDKN2A silencing, SETD2 mutations, TFE3 fusions, and increased expression of the NRF2-antioxidant response element (ARE) pathway. A CpG island methylator phenotype (CIMP) was observed in a distinct subgroup of type 2 papillary renal-cell carcinomas that was characterized by poor survival and mutation of the gene encoding fumarate hydratase (FH).
CONCLUSIONS - Type 1 and type 2 papillary renal-cell carcinomas were shown to be clinically and biologically distinct. Alterations in the MET pathway were associated with type 1, and activation of the NRF2-ARE pathway was associated with type 2; CDKN2A loss and CIMP in type 2 conveyed a poor prognosis. Furthermore, type 2 papillary renal-cell carcinoma consisted of at least three subtypes based on molecular and phenotypic features. (Funded by the National Institutes of Health.).
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14 MeSH Terms
The effects of omega-3 polyunsaturated fatty acids and genetic variants on methylation levels of the interleukin-6 gene promoter.
Ma Y, Smith CE, Lai CQ, Irvin MR, Parnell LD, Lee YC, Pham LD, Aslibekyan S, Claas SA, Tsai MY, Borecki IB, Kabagambe EK, Ordovás JM, Absher DM, Arnett DK
(2016) Mol Nutr Food Res 60: 410-9
MeSH Terms: Adult, CpG Islands, DNA Methylation, Fatty Acids, Omega-3, Female, Humans, Interleukin-6, Male, Middle Aged, Polymorphism, Single Nucleotide, Promoter Regions, Genetic
Show Abstract · Added February 18, 2016
SCOPE - Omega-3 PUFAs (n-3 PUFAs) reduce IL-6 gene expression, but their effects on transcription regulatory mechanisms are unknown. We aimed to conduct an integrated analysis with both population and in vitro studies to systematically explore the relationships among n-3 PUFA, DNA methylation, single nucleotide polymorphisms (SNPs), gene expression, and protein concentration of IL6.
METHODS AND RESULTS - Using data in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study and the Encyclopedia of DNA Elements (ENCODE) consortium, we found that higher methylation of IL6 promoter cg01770232 was associated with higher IL-6 plasma concentration (p = 0.03) and greater IL6 gene expression (p = 0.0005). Higher circulating total n-3 PUFA was associated with lower cg01770232 methylation (p = 0.007) and lower IL-6 concentration (p = 0.02). Moreover, an allele of IL6 rs2961298 was associated with higher cg01770232 methylation (p = 2.55 × 10(-7) ). The association between n-3 PUFA and cg01770232 methylation was dependent on rs2961298 genotype (p = 0.02), but higher total n-3 PUFA was associated with lower cg01770232 methylation in the heterozygotes (p = 0.04) not in the homozygotes.
CONCLUSION - Higher n-3 PUFA is associated with lower methylation at IL6 promoter, which may be modified by IL6 SNPs.
© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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11 MeSH Terms
Intraindividual variation and short-term temporal trend in DNA methylation of human blood.
Shvetsov YB, Song MA, Cai Q, Tiirikainen M, Xiang YB, Shu XO, Yu H
(2015) Cancer Epidemiol Biomarkers Prev 24: 490-7
MeSH Terms: Adult, Aged, Blood Chemical Analysis, Cohort Studies, CpG Islands, DNA, DNA Methylation, Epigenomics, Female, Genome, Human, Humans, Middle Aged, Prospective Studies
Show Abstract · Added April 3, 2018
BACKGROUND - Between- and within-person variation in DNA methylation levels are important parameters to be considered in epigenome-wide association studies. Temporal change is one source of within-person variation in DNA methylation that has been linked to aging and disease.
METHODS - We analyzed CpG-site-specific intraindividual variation and short-term temporal trend in leukocyte DNA methylation among 24 healthy Chinese women, with blood samples drawn at study entry and after 9 months. Illumina HumanMethylation450 BeadChip was used to measure methylation. Intraclass correlation coefficients (ICC) and trend estimates were summarized by genomic location and probe type.
RESULTS - The median ICC was 0.36 across nonsex chromosomes and 0.80 on the X chromosome. There was little difference in ICC profiles by genomic region and probe type. Among CpG loci with high variability between participants, more than 99% had ICC > 0.8. Statistically significant trend was observed in 10.9% CpG loci before adjustment for cell-type composition and in 3.4% loci after adjustment.
CONCLUSIONS - For CpG loci differentially methylated across subjects, methylation levels can be reliably assessed with one blood sample. More samples per subject are needed for low-variability and unmethylated loci. Temporal changes are largely driven by changes in cell-type composition of blood samples, but temporal trend unrelated to cell types is detected in a small percentage of CpG sites.
IMPACT - This study shows that one measurement can reliably assess methylation of differentially methylated CpG loci. Cancer Epidemiol Biomarkers Prev; 24(3); 490-7. ©2014 AACR.
©2014 American Association for Cancer Research.
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Clinically relevant genes and regulatory pathways associated with NRASQ61 mutations in melanoma through an integrative genomics approach.
Jiang W, Jia P, Hutchinson KE, Johnson DB, Sosman JA, Zhao Z
(2015) Oncotarget 6: 2496-508
MeSH Terms: CpG Islands, DNA Methylation, GTP Phosphohydrolases, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Gene Regulatory Networks, Genomics, Humans, Melanoma, Membrane Proteins, MicroRNAs, Models, Genetic, Mutation, Signal Transduction, Skin Neoplasms
Show Abstract · Added February 13, 2015
Therapies such as BRAF inhibitors have become standard treatment for melanoma patients whose tumors harbor activating BRAFV600 mutations. However, analogous therapies for inhibiting NRAS mutant signaling have not yet been well established. In this study, we performed an integrative analysis of DNA methylation, gene expression, and microRNA expression data to identify potential regulatory pathways associated with the most common driver mutations in NRAS (Q61K/L/R) through comparison of NRASQ61-mutated melanomas with pan-negative melanomas. Surprisingly, we found dominant hypomethylation (98.03%) in NRASQ61-mutated melanomas. We identified 1,150 and 49 differentially expressed genes and microRNAs, respectively. Integrated functional analyses of alterations in all three data types revealed important signaling pathways associated with NRASQ61 mutations, such as the MAPK pathway, as well as other novel cellular processes, such as axon guidance. Further analysis of the relationship between DNA methylation and gene expression changes revealed 9 hypermethylated and down-regulated genes and 112 hypomethylated and up-regulated genes in NRASQ61 melanomas. Finally, we identified 52 downstream regulatory cascades of three hypomethylated and up-regulated genes (PDGFD, ZEB1, and THRB). Collectively, our observation of predominant gene hypomethylation in NRASQ61 melanomas and the identification of NRASQ61-linked pathways will be useful for the development of targeted therapies against melanomas harboring NRASQ61 mutations.
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15 MeSH Terms
Modeling DNA methylation dynamics with approaches from phylogenetics.
Capra JA, Kostka D
(2014) Bioinformatics 30: i408-14
MeSH Terms: Animals, Base Sequence, Cell Differentiation, CpG Islands, DNA, DNA Methylation, Genomics, Markov Chains, Mice, Models, Genetic, Phylogeny
Show Abstract · Added April 18, 2017
MOTIVATION - Methylation of CpG dinucleotides is a prevalent epigenetic modification that is required for proper development in vertebrates. Genome-wide DNA methylation assays have become increasingly common, and this has enabled characterization of DNA methylation in distinct stages across differentiating cellular lineages. Changes in CpG methylation are essential to cellular differentiation; however, current methods for modeling methylation dynamics do not account for the dependency structure between precursor and dependent cell types.
RESULTS - We developed a continuous-time Markov chain approach, based on the observation that changes in methylation state over tissue differentiation can be modeled similarly to DNA nucleotide changes over evolutionary time. This model explicitly takes precursor to descendant relationships into account and enables inference of CpG methylation dynamics. To illustrate our method, we analyzed a high-resolution methylation map of the differentiation of mouse stem cells into several blood cell types. Our model can successfully infer unobserved CpG methylation states from observations at the same sites in related cell types (90% correct), and this approach more accurately reconstructs missing data than imputation based on neighboring CpGs (84% correct). Additionally, the single CpG resolution of our methylation dynamics estimates enabled us to show that DNA sequence context of CpG sites is informative about methylation dynamics across tissue differentiation. Finally, we identified genomic regions with clusters of highly dynamic CpGs and present a likely functional example. Our work establishes a framework for inference and modeling that is well suited to DNA methylation data, and our success suggests that other methods for analyzing DNA nucleotide substitutions will also translate to the modeling of epigenetic phenomena.
AVAILABILITY AND IMPLEMENTATION - Source code is available at www.kostkalab.net/software.
© The Author 2014. Published by Oxford University Press.
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11 MeSH Terms
Proteogenomic characterization of human colon and rectal cancer.
Zhang B, Wang J, Wang X, Zhu J, Liu Q, Shi Z, Chambers MC, Zimmerman LJ, Shaddox KF, Kim S, Davies SR, Wang S, Wang P, Kinsinger CR, Rivers RC, Rodriguez H, Townsend RR, Ellis MJ, Carr SA, Tabb DL, Coffey RJ, Slebos RJ, Liebler DC, NCI CPTAC
(2014) Nature 513: 382-7
MeSH Terms: Chromosomes, Human, Pair 20, Colonic Neoplasms, CpG Islands, DNA Copy Number Variations, DNA Methylation, Genomics, Hepatocyte Nuclear Factor 4, Humans, Microsatellite Repeats, Mitochondrial Membrane Transport Proteins, Mutation, Missense, Neoplasm Proteins, Point Mutation, Proteome, Proteomics, Proto-Oncogene Proteins pp60(c-src), RNA, Messenger, RNA, Neoplasm, Rectal Neoplasms, Transcriptome
Show Abstract · Added December 4, 2014
Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA 'microsatellite instability/CpG island methylation phenotype' transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.
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20 MeSH Terms
DNA methyltransferase 3a and mitogen-activated protein kinase signaling regulate the expression of fibroblast growth factor-inducible 14 (Fn14) during denervation-induced skeletal muscle atrophy.
Tajrishi MM, Shin J, Hetman M, Kumar A
(2014) J Biol Chem 289: 19985-99
MeSH Terms: Animals, Base Sequence, Conserved Sequence, CpG Islands, DNA, DNA (Cytosine-5-)-Methyltransferases, DNA Methylation, Gene Expression, Gene Knockdown Techniques, MAP Kinase Signaling System, Mice, Mice, Inbred C57BL, Models, Biological, Molecular Sequence Data, Muscle Denervation, Muscle, Skeletal, Muscular Atrophy, Promoter Regions, Genetic, RNA, Small Interfering, Receptors, Tumor Necrosis Factor, Sequence Homology, Nucleic Acid, Sp1 Transcription Factor, TWEAK Receptor, Transcription Factor AP-1
Show Abstract · Added October 30, 2014
The TWEAK-fibroblast growth factor-inducible 14 (Fn14) system is a critical regulator of denervation-induced skeletal muscle atrophy. Although the expression of Fn14 is a rate-limiting step in muscle atrophy on denervation, mechanisms regulating gene expression of Fn14 remain unknown. Methylation of CpG sites within promoter region is an important epigenetic mechanism for gene silencing. Our study demonstrates that Fn14 promoter contains a CpG island close to transcription start site. Fn14 promoter also contains multiple consensus DNA sequence for transcription factors activator protein 1 (AP1) and specificity protein 1 (SP1). Denervation diminishes overall genomic DNA methylation and causes hypomethylation at specific CpG sites in Fn14 promoter leading to the increased gene expression of Fn14 in skeletal muscle. Abundance of DNA methyltransferase 3a (Dnmt3a) and its interaction with Fn14 promoter are repressed in denervated skeletal muscle of mice. Overexpression of Dnmt3a inhibits the gene expression of Fn14 and attenuates skeletal muscle atrophy upon denervation. Denervation also causes the activation of ERK1/2, JNK1/2, and ERK5 MAPKs and AP1 and SP1, which stimulate the expression of Fn14 in skeletal muscle. Collectively, our study provides novel evidence that Dnmt3a and MAPK signaling regulate the levels of Fn14 in skeletal muscle on denervation.
© 2014 by The American Society for Biochemistry and Molecular Biology, Inc.
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24 MeSH Terms
Differences in DNA methylation signatures reveal multiple pathways of progression from adenoma to colorectal cancer.
Luo Y, Wong CJ, Kaz AM, Dzieciatkowski S, Carter KT, Morris SM, Wang J, Willis JE, Makar KW, Ulrich CM, Lutterbaugh JD, Shrubsole MJ, Zheng W, Markowitz SD, Grady WM
(2014) Gastroenterology 147: 418-29.e8
MeSH Terms: Adenoma, Aged, Case-Control Studies, Cell Transformation, Neoplastic, Cluster Analysis, Colorectal Neoplasms, CpG Islands, DNA Methylation, DNA Mutational Analysis, Disease Progression, Epigenesis, Genetic, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Middle Aged, Mutation, Oligonucleotide Array Sequence Analysis, Phenotype, Proto-Oncogene Proteins, Proto-Oncogene Proteins p21(ras), ras Proteins
Show Abstract · Added January 20, 2015
BACKGROUND & AIMS - Genetic and epigenetic alterations contribute to the pathogenesis of colorectal cancer (CRC). There is considerable molecular heterogeneity among colorectal tumors, which appears to arise as polyps progress to cancer. This heterogeneity results in different pathways to tumorigenesis. Although epigenetic and genetic alterations have been detected in conventional tubular adenomas, little is known about how these affect progression to CRC. We compared methylomes of normal colon mucosa, tubular adenomas, and colorectal cancers to determine how epigenetic alterations might contribute to cancer formation.
METHODS - We conducted genome-wide array-based studies and comprehensive data analyses of aberrantly methylated loci in 41 normal colon tissue, 42 colon adenomas, and 64 cancers using HumanMethylation450 arrays.
RESULTS - We found genome-wide alterations in DNA methylation in the nontumor colon mucosa and cancers. Three classes of cancers and 2 classes of adenomas were identified based on their DNA methylation patterns. The adenomas separated into classes of high-frequency methylation and low-frequency methylation. Within the high-frequency methylation adenoma class a subset of adenomas had mutant KRAS. Additionally, the high-frequency methylation adenoma class had DNA methylation signatures similar to those of cancers with low or intermediate levels of methylation, and the low-frequency methylation adenoma class had methylation signatures similar to that of nontumor colon tissue. The CpG sites that were differentially methylated in these signatures are located in intragenic and intergenic regions.
CONCLUSIONS - Genome-wide alterations in DNA methylation occur during early stages of progression of tubular adenomas to cancer. These findings reveal heterogeneity in the pathogenesis of colorectal cancer, even at the adenoma step of the process.
Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.
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23 MeSH Terms
Genome-wide DNA methylation in neonates exposed to maternal depression, anxiety, or SSRI medication during pregnancy.
Non AL, Binder AM, Kubzansky LD, Michels KB
(2014) Epigenetics 9: 964-72
MeSH Terms: Antidepressive Agents, Anxiety, Case-Control Studies, Cell Division, Cohort Studies, CpG Islands, DNA Methylation, Depression, Female, Fetal Blood, Gene Expression Regulation, Gene Ontology, Genome, Human, Humans, Infant, Newborn, Male, Pregnancy, Pregnancy Complications, Prenatal Exposure Delayed Effects, Protein Biosynthesis, Serotonin Uptake Inhibitors
Show Abstract · Added January 20, 2015
Despite the high prevalence of depression, anxiety, and use of antidepressant medications during pregnancy, there is much uncertainty around the impact of high levels of distress or antidepressant medications on the developing fetus. These intrauterine exposures may lead to epigenetic alterations to the DNA during this vulnerable time of fetal development, which may have important lifetime health consequences. In this study we investigated patterns of genome-wide DNA methylation using the Illumina Infinium Human Methylation450 BeadChip in the umbilical cord blood of neonates exposed to non-medicated maternal depression or anxiety (n = 13), or selective serotonin reuptake inhibitors (SSRIs) during pregnancy (n = 22), relative to unexposed neonates (n = 23). We identified 42 CpG sites with significantly different DNA methylation levels in neonates exposed to non-medicated depression or anxiety relative to controls. CpG site methylation was not significantly different in neonates exposed to SSRIs relative to the controls, after adjusting for multiple comparisons. In neonates exposed either to non-medicated maternal depression or SSRIs, the vast majority of CpG sites displayed lower DNA methylation relative to the controls, but differences were very small. A gene ontology analysis suggests significant clustering of the top genes associated with non-medicated maternal depression/anxiety, related to regulation of transcription, translation, and cell division processes (e.g., negative regulation of translation in response to oxidative stress, regulation of mRNA export from the nucleus, regulation of stem cell division). While the functional consequences of these findings are yet to be determined, these small DNA methylation differences may suggest a possible role for epigenetic processes in the development of neonates exposed to non-medicated maternal depression/anxiety.
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21 MeSH Terms