scholarly journals Landscape of genome-wide age-related DNA methylation in breast tissue

Oncotarget ◽  
2017 ◽  
Vol 8 (70) ◽  
pp. 114648-114662 ◽  
Author(s):  
Min-Ae Song ◽  
Theodore M. Brasky ◽  
Daniel Y. Weng ◽  
Joseph P. McElroy ◽  
Catalin Marian ◽  
...  
2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Shoghag Panjarian ◽  
Jozef Madzo ◽  
Kelsey Keith ◽  
Carolyn M. Slater ◽  
Carmen Sapienza ◽  
...  

Abstract Background DNA methylation alterations have similar patterns in normal aging tissue and in cancer. In this study, we investigated breast tissue-specific age-related DNA methylation alterations and used those methylation sites to identify individuals with outlier phenotypes. Outlier phenotype is identified by unsupervised anomaly detection algorithms and is defined by individuals who have normal tissue age-dependent DNA methylation levels that vary dramatically from the population mean. Methods We generated whole-genome DNA methylation profiles (GSE160233) on purified epithelial cells and used publicly available Infinium HumanMethylation 450K array datasets (TCGA, GSE88883, GSE69914, GSE101961, and GSE74214) for discovery and validation. Results We found that hypermethylation in normal breast tissue is the best predictor of hypermethylation in cancer. Using unsupervised anomaly detection approaches, we found that about 10% of the individuals (39/427) were outliers for DNA methylation from 6 DNA methylation datasets. We also found that there were significantly more outlier samples in normal-adjacent to cancer (24/139, 17.3%) than in normal samples (15/228, 5.2%). Additionally, we found significant differences between the predicted ages based on DNA methylation and the chronological ages among outliers and not-outliers. Additionally, we found that accelerated outliers (older predicted age) were more frequent in normal-adjacent to cancer (14/17, 82%) compared to normal samples from individuals without cancer (3/17, 18%). Furthermore, in matched samples, we found that the epigenome of the outliers in the pre-malignant tissue was as severely altered as in cancer. Conclusions A subset of patients with breast cancer has severely altered epigenomes which are characterized by accelerated aging in their normal-appearing tissue. In the future, these DNA methylation sites should be studied further such as in cell-free DNA to determine their potential use as biomarkers for early detection of malignant transformation and preventive intervention in breast cancer.


Epigenetics ◽  
2020 ◽  
pp. 1-15
Author(s):  
Maeve Kiely ◽  
Lap Ah Tse ◽  
Hela Koka ◽  
Difei Wang ◽  
Priscilla Lee ◽  
...  

PLoS ONE ◽  
2015 ◽  
Vol 10 (3) ◽  
pp. e0120388 ◽  
Author(s):  
Fu-Hui Xiao ◽  
Yong-Han He ◽  
Qi-Gang Li ◽  
Huan Wu ◽  
Long-Hai Luo ◽  
...  

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2367-2367
Author(s):  
Mira Jeong ◽  
Deqiang Sun ◽  
Min Luo ◽  
Aysegul Ergen ◽  
Hongcang Gu ◽  
...  

Abstract Abstract 2367 Hematopoietic stem cell (HSC) Aging is a complex process linked to number of changes in gene expression and functional decline of self-renewal and differentiation potential. While epigenetic changes have been implicated in HSC aging, little direct evidence has been generated. DNA methylation is one of the major underlying mechanisms associated with the regulation of gene expression, but changes in DNA methylation patterns with HSC aging have not been characterized. We hypothesize that revealing the genome-wide DNA methylation and transcriptome signatures will lead to a greater understanding of HSC aging. Here, we report the first genome-scale study of epigenomic dynamics during normal mouse HSC aging. We isolated SP-KSL-CD150+ HSC populations from 4, 12, 24 month-old mouse bone marrow and carried out genome-wide reduced representative bisulfite sequencing (RRBS) and identified aging-associated differentially methylated CpGs. Three biological samples were sequenced from each aging group and we obtained 30–40 million high-quality reads with over 30X total coverage on ∼1.1M CpG sites which gives us adequate statistical power to infer methylation ratios. Bisulfite conversion rate of non-CpG cytosines was >99%. We analyzed a variety of genomic features to find that CpG island promoters, gene bodies, 5'UTRs, and 3'UTRs generally were associated with hypermethylation in aging HSCs. Overall, out of 1,777 differentially methylated CpGs, 92.8% showed age-related hypermethylation and 7.2% showed age-related hypomethylation. Gene ontology analyses have revealed that differentially methylated CpGs were significantly enriched near genes associated with alternative splicing, DNA binding, RNA-binding, transcription regulation, Wnt signaling and pathways in cancer. Most interestingly, over 579 splice variants were detected as candidates for age-related hypermethylation (86%) and hypomethylation (14%) including Dnmt3a, Runx1, Pbx1 and Cdkn2a. To quantify differentially expressed RNA-transcripts across the entire transcriptome, we performed RNA-seq and analyzed exon arrays. The Spearman's correlation between two different methods was good (r=0.80). From exon arrays, we identified 586 genes that were down regulated and 363 gene were up regulated with aging (p<0.001). Most interestingly, overall expression of DNA methyl transferases Dnmt1, Dnmt3a, Dnmt3b were down regulated with aging. We also found that Dnmt3a2, the short isoform of Dnmt3a, which lacks the N-terminal region of Dnmt3a and represents the major isoform in ES cells, is more expressed in young HSC. For the RNA-seq analysis, we focused first on annotated transcripts derived from cloned mRNAs and we found 307 genes were down regulated and 1015 gene were up regulated with aging (p<0.05). Secondly, we sought to identify differentially expressed isoforms and also novel transcribed regions (antisense and novel genes). To characterize the genes showing differential regulation, we analyzed their functional associations and observed that the highest scoring annotation cluster was enriched in genes associated with translation, the immune network and hematopoietic cell lineage. We expect that the results of these experiments will reveal the global effect of DNA methylation on transcript stability and the translational state of target genes. Our findings will lend insight into the molecular mechanisms responsible for the pathologic changes associated with aging in HSCs. Disclosures: No relevant conflicts of interest to declare.


2020 ◽  
Author(s):  
Jinwei Xin ◽  
Zhixin Chai ◽  
Chengfu Zhang ◽  
Qiang Zhang ◽  
Yong Zhu ◽  
...  

Abstract Background Domestic yaks play an indispensable role in sustaining the livelihood of Tibetans and other ethnic groups on the Qinghai-Tibetan Plateau (QTP), by providing milk and meat, and have evolved numerous physiological adaptabilities to high-altitude landscape, such as strong capacity of blood oxygen transportation and high metabolism. The role of DNA methylation and network of gene expression underlying milk production and adaptation to high altitudes of yak need further exploration. Results We performed genome-wide DNA methylome and transcriptome analyses of breast, lungs, and gluteal muscle from yaks of different ages. We identified differentially methylated regions (DMRs) across age groups within the each tissue, and breast tissue had considerably more differentially methylated regions than that from the three younger age groups. Hypomethylated genes with high expression level might regulate milk production by influencing protein processing in the endoplasmic reticulum. Weighted gene correlation network analysis revealed that the “hub” gene ZGPAT was highly expressed in post-mature breast tissue and that it potentially regulated the transcription of 280 genes, which play roles in regulating protein synthesis, processing, and secretion. Besides, Tissue network analysis indicates that high expression of HIF1A regulates energy metabolism in the lung. Conclusions The results of this comprehensive study provide a solid basis for understanding the epigenetic mechanisms underlying milk production in yaks, which could be helpful to breeding programs aimed at improving milk production.


2017 ◽  
Author(s):  
Kevin C. Johnson ◽  
E. Andres Houseman ◽  
Jessica E. King ◽  
Brock C. Christensen

AbstractBackgroundThe underlying biological mechanisms through which epidemiologically defined breast cancer risk factors contribute to disease risk remain poorly understood. Identification of the molecular changes associated with cancer risk factors in normal tissues may aid in determining the earliest events of carcinogenesis and informing cancer prevention strategies.ResultsHere we investigated the impact cancer risk factors have on the normal breast epigenome by analyzing DNA methylation genome-wide (Infinium 450K array) in cancer-free women from the Susan G. Komen Tissue Bank (n = 100). We tested the relation of established breast cancer risk factors: age, body mass index, parity, and family history of disease with DNA methylation adjusting for potential variation in cell-type proportions. We identified 787 CpG sites that demonstrated significant associations (Q-value < 0.01) with subject age. Notably, DNA methylation was not strongly associated with the other evaluated breast cancer risk factors. Age-related DNA methylation changes are primarily increases in methylation enriched at breast epithelial cell enhancer regions (P = 7.1E-20), and binding sites of chromatin remodelers (MYC and CTCF). We validated the age-related associations in two independent populations of normal breast tissue (n = 18) and normal-adjacent to tumor tissue (n = 97). The genomic regions classified as age-related were more likely to be regions altered in cancer in both pre-invasive (n = 40, P=3.0E-03) and invasive breast tumors (n = 731, P=1.1E-13).ConclusionsDNA methylation changes with age occur at regulatory regions, and are further exacerbated in cancer suggesting that age influences breast cancer risk in part through its contribution to epigenetic dysregulation in normal breast tissue.


2020 ◽  
Author(s):  
Jinwei Xin ◽  
Zhixin Chai ◽  
Chengfu Zhang ◽  
Qiang Zhang ◽  
Yong Zhu ◽  
...  

Abstract Background Domestic yaks play an indispensable role in sustaining the livelihood of Tibetans and other ethnic groups on the Qinghai-Tibetan Plateau (QTP), by providing milk and meat. They have evolved numerous physiological adaptabilities to high-altitude environment, such as the strong capacity of blood oxygen transportation and high metabolism. The role of DNA methylation and network of gene expression underlying milk production and adaptation to high altitudes of yak need further exploration. Results We performed genome-wide DNA methylome and transcriptome analyses of breast, lung, and biceps brachii muscle from yaks of different ages. We identified differentially methylated regions (DMRs) across age groups within the each tissue. The breast tissue had considerably more differentially methylated regions than that from the three younger age groups. Hypomethylated genes with high expression level might regulate milk production by influencing protein processing in the endoplasmic reticulum. Weighted gene correlation network analysis revealed that the “hub” gene ZGPAT was highly expressed in the post-mature breast tissue. It potentially regulated the transcription of 280 genes, which play roles in regulating protein synthesis, processing, and secretion. Besides, Tissue network analysis indicates that high expression of HIF1A regulates energy metabolism in the lung. Conclusions The results of this comprehensive study provide a solid basis for understanding the epigenetic mechanisms underlying milk production in yaks, which could be helpful to breeding programs aimed at improving milk production.


AGE ◽  
2014 ◽  
Vol 36 (3) ◽  
Author(s):  
Wilma T. Steegenga ◽  
Mark V. Boekschoten ◽  
Carolien Lute ◽  
Guido J. Hooiveld ◽  
Philip J. de Groot ◽  
...  

2017 ◽  
Author(s):  
Yunzhang Wang ◽  
Robert Karlsson ◽  
Erik Lampa ◽  
Qian Zhang ◽  
Åsa K. Hedman ◽  
...  

AbstractAge-related changes in DNA methylation have been observed in many cross-sectional studies, but longitudinal evidence is still very limited. Here, we aimed to characterize longitudinal age-related methylation patterns (Illumina HumanMethylation450 array) using 1011 blood samples collected from 385 old Swedish twins (mean age of 69 at baseline) up to five times over 20 years. We identified 1316 age-associated methylation sites (p<1.3×10−7) using a longitudinal epigenome-wide association study design. We measured how estimated cellular compositions changed with age and how much they confounded the age effect. We validated the results in two independent longitudinal cohorts, where 118 CpGs were replicated in PIVUS (p<3.9×10−5) and 594 were replicated in LBC (p<5.1×10−5). Functional annotation of age-associated CpGs showed enrichment in CCCTC-binding factor (CTCF) and other unannotated transcription factor binding sites. We further investigated genetic influences on methylation (methylation quantitative trait loci) and found no interaction between age and genetic effects in the 1316 age-associated CpGs. Moreover, in the same CpGs, methylation differences within twin pairs increased over time, where monozygotic twins had smaller intra-pair differences than dizygotic twins. We show that age-related methylation changes persist in a longitudinal perspective, and are fairly stable across cohorts. Moreover, the changes are under genetic influence, although this effect is independent of age. In addition, inter-individual methylation variations increase over time, especially in age-associated CpGs, indicating the increase of environmental contributions on DNA methylation with age.


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