Pub Date : 2024-04-10DOI: 10.1186/s43682-024-00025-9
Su Chen, Miranda Johs, Wilfried Karmaus, John W. Holloway, Parnian Kheirkhah Rahimabad, J. Goodrich, Karen E. Peterson, D. Dolinoy, S. Arshad, S. Ewart
{"title":"Assessing the effect of childbearing on blood DNA methylation through comparison of parous and nulliparous females","authors":"Su Chen, Miranda Johs, Wilfried Karmaus, John W. Holloway, Parnian Kheirkhah Rahimabad, J. Goodrich, Karen E. Peterson, D. Dolinoy, S. Arshad, S. Ewart","doi":"10.1186/s43682-024-00025-9","DOIUrl":"https://doi.org/10.1186/s43682-024-00025-9","url":null,"abstract":"","PeriodicalId":72947,"journal":{"name":"Epigenetics communications","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140717837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-09DOI: 10.1186/s43682-023-00024-2
Marloes M. Oosterhof, Louis Coussement, Alienke van Pijkeren, Marcel Kwiatkowski, M. R. Zwinderman, Frank J. Dekker, Tim de Meyer, Vera A. Reitsema, Rainer Bischoff, Victor Guryev, H. Bouma, Rob H. Henning, Marianne G. Rots
{"title":"Changes in histone lysine acetylation, but not DNA methylation during facultative hibernation in Syrian hamster liver","authors":"Marloes M. Oosterhof, Louis Coussement, Alienke van Pijkeren, Marcel Kwiatkowski, M. R. Zwinderman, Frank J. Dekker, Tim de Meyer, Vera A. Reitsema, Rainer Bischoff, Victor Guryev, H. Bouma, Rob H. Henning, Marianne G. Rots","doi":"10.1186/s43682-023-00024-2","DOIUrl":"https://doi.org/10.1186/s43682-023-00024-2","url":null,"abstract":"","PeriodicalId":72947,"journal":{"name":"Epigenetics communications","volume":"11 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139444150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-01Epub Date: 2024-06-30DOI: 10.1186/s43682-024-00027-7
Jagadeesh Puvvula, Joseph M Braun, Emily A DeFranco, Shuk-Mei Ho, Yuet-Kin Leung, Shouxiong Huang, Xiang Zhang, Ann M Vuong, Stephani S Kim, Zana Percy, Antonia M Calafat, Julianne C Botelho, Aimin Chen
Background: Exposure to environmental chemicals such as phthalates, phenols, and polycyclic aromatic hydrocarbons (PAHs) during pregnancy can increase the risk of adverse newborn outcomes. We explored the associations between maternal exposure to select environmental chemicals and DNA methylation in cord blood mononuclear cells (CBMC) and placental tissue (maternal and fetal sides) to identify potential mechanisms underlying these associations.
Method: This study included 75 pregnant individuals who planned to give birth at the University of Cincinnati Hospital between 2014 and 2017. Maternal urine samples during the delivery visit were collected and analyzed for 37 biomarkers of phenols (12), phthalates (13), phthalate replacements (4), and PAHs (8). Cord blood and placenta tissue (maternal and fetal sides) were also collected to measure the DNA methylation intensities using the Infinium HumanMethylation450K BeadChip. We used linear regression, adjusting for potential confounders, to assess CpG-specific methylation changes in CBMC (n = 54) and placenta [fetal (n = 67) and maternal (n = 68) sides] associated with gestational chemical exposures (29 of 37 biomarkers measured in this study). To account for multiple testing, we used a false discovery rate q-values < 0.05 and presented results by limiting results with a genomic inflation factor of 1±0.5. Additionally, gene set enrichment analysis was conducted using the Kyoto Encyclopedia of Genes and Genomics pathways.
Results: Among the 29 chemical biomarkers assessed for differential methylation, maternal concentrations of PAH metabolites (1-hydroxynaphthalene, 2-hydroxyfluorene, 4-hydroxyphenanthrene, 1-hydroxypyrene), monocarboxyisononyl phthalate, mono-3-carboxypropyl phthalate, and bisphenol A were associated with altered methylation in placenta (maternal or fetal side). Among exposure biomarkers associated with epigenetic changes, 1-hydroxynaphthalene, and mono-3-carboxypropyl phthalate were consistently associated with differential CpG methylation in the placenta. Gene enrichment analysis indicated that maternal 1-hydroxynaphthalene was associated with lipid metabolism and cellular processes of the placenta. Additionally, mono-3-carboxypropyl phthalate was associated with organismal systems and genetic information processing of the placenta.
Conclusion: Among the 29 chemical biomarkers assessed during delivery, 1-hydroxynaphthalene and mono-3-carboxypropyl phthalate were associated with DNA methylation in the placenta.
Supplementary information: The online version contains supplementary material available at 10.1186/s43682-024-00027-7.
{"title":"Gestational exposure to environmental chemicals and epigenetic alterations in the placenta and cord blood mononuclear cells.","authors":"Jagadeesh Puvvula, Joseph M Braun, Emily A DeFranco, Shuk-Mei Ho, Yuet-Kin Leung, Shouxiong Huang, Xiang Zhang, Ann M Vuong, Stephani S Kim, Zana Percy, Antonia M Calafat, Julianne C Botelho, Aimin Chen","doi":"10.1186/s43682-024-00027-7","DOIUrl":"10.1186/s43682-024-00027-7","url":null,"abstract":"<p><strong>Background: </strong>Exposure to environmental chemicals such as phthalates, phenols, and polycyclic aromatic hydrocarbons (PAHs) during pregnancy can increase the risk of adverse newborn outcomes. We explored the associations between maternal exposure to select environmental chemicals and DNA methylation in cord blood mononuclear cells (CBMC) and placental tissue (maternal and fetal sides) to identify potential mechanisms underlying these associations.</p><p><strong>Method: </strong>This study included 75 pregnant individuals who planned to give birth at the University of Cincinnati Hospital between 2014 and 2017. Maternal urine samples during the delivery visit were collected and analyzed for 37 biomarkers of phenols (12), phthalates (13), phthalate replacements (4), and PAHs (8). Cord blood and placenta tissue (maternal and fetal sides) were also collected to measure the DNA methylation intensities using the Infinium HumanMethylation450K BeadChip. We used linear regression, adjusting for potential confounders, to assess CpG-specific methylation changes in CBMC (<i>n</i> = 54) and placenta [fetal (<i>n</i> = 67) and maternal (<i>n</i> = 68) sides] associated with gestational chemical exposures (29 of 37 biomarkers measured in this study). To account for multiple testing, we used a false discovery rate q-values < 0.05 and presented results by limiting results with a genomic inflation factor of 1±0.5. Additionally, gene set enrichment analysis was conducted using the Kyoto Encyclopedia of Genes and Genomics pathways.</p><p><strong>Results: </strong>Among the 29 chemical biomarkers assessed for differential methylation, maternal concentrations of PAH metabolites (1-hydroxynaphthalene, 2-hydroxyfluorene, 4-hydroxyphenanthrene, 1-hydroxypyrene), monocarboxyisononyl phthalate, mono-3-carboxypropyl phthalate, and bisphenol A were associated with altered methylation in placenta (maternal or fetal side). Among exposure biomarkers associated with epigenetic changes, 1-hydroxynaphthalene, and mono-3-carboxypropyl phthalate were consistently associated with differential CpG methylation in the placenta. Gene enrichment analysis indicated that maternal 1-hydroxynaphthalene was associated with lipid metabolism and cellular processes of the placenta. Additionally, mono-3-carboxypropyl phthalate was associated with organismal systems and genetic information processing of the placenta.</p><p><strong>Conclusion: </strong>Among the 29 chemical biomarkers assessed during delivery, 1-hydroxynaphthalene and mono-3-carboxypropyl phthalate were associated with DNA methylation in the placenta.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1186/s43682-024-00027-7.</p>","PeriodicalId":72947,"journal":{"name":"Epigenetics communications","volume":"4 1","pages":"4"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11217138/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141499826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-22DOI: 10.1186/s43682-023-00023-3
Weisen Yu, E. Drzymalla, Matheus Fernandes Gyorfy, M. Khoury, Yan V. Sun, M. Gwinn
{"title":"Navigating epigenetic epidemiology publications","authors":"Weisen Yu, E. Drzymalla, Matheus Fernandes Gyorfy, M. Khoury, Yan V. Sun, M. Gwinn","doi":"10.1186/s43682-023-00023-3","DOIUrl":"https://doi.org/10.1186/s43682-023-00023-3","url":null,"abstract":"","PeriodicalId":72947,"journal":{"name":"Epigenetics communications","volume":"54 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139248187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-12DOI: 10.1186/s43682-023-00022-4
R. Waziry, Y. Gu, O. Williams, S. Hägg
Abstract Background Saliva measures are generally more accessible than blood, especially in vulnerable populations. However, connections between aging biology biomarkers in different body tissues remain unknown. Methods The present study included individuals ( N = 2406) who consented for saliva and blood draw in the Health and Retirement Telomere length study in 2008 and the Venous blood study in 2016 who had complete data for both tissues. We assessed biological aging based on telomere length in saliva and DNA methylation and physiology measures in blood. DNA methylation clocks combine information from CpGs to produce the aging measures representative of epigenetic aging in humans. We analyzed DNA methylation clocks proposed by Horvath (353 CpG sites), Hannum (71 CpG sites), Levine or PhenoAge, (513 CpG sites), GrimAge, (epigenetic surrogate markers for select plasma proteins), Horvath skin and blood (391 CpG sites), Lin (99 CpG sites), Weidner (3 CpG sites), and VidalBralo (8 CpG sites). Physiology measures (referred to as phenotypic age) included albumin, creatinine, glucose, [log] C-reactive protein, lymphocyte percent, mean cell volume, red blood cell distribution width, alkaline phosphatase, and white blood cell count. The phenotypic age algorithm is based on parametrization of Gompertz proportional hazard models. Average telomere length was assayed using quantitative PCR (qPCR) by comparing the telomere sequence copy number in each patient’s sample (T) to a single-copy gene copy number (S). The resulting T/S ratio was proportional to telomere length, mean. Within individual, relationships between aging biology measures in blood and saliva and variations according to sex were assessed. Results Saliva-based telomere length showed inverse associations with both physiology-based and DNA methylation-based aging biology biomarkers in blood. Longer saliva-based telomere length was associated with 1 to 4 years slower biological aging based on blood-based biomarkers with the highest magnitude being Weidner ( β = − 3.97, P = 0.005), GrimAge ( β = − 3.33, P < 0.001), and Lin ( β = − 3.45, P = 0.008) biomarkers of DNA methylation. Conclusions There are strong connections between aging biology biomarkers in saliva and blood in older adults. Changes in telomere length vary with changes in DNA methylation and physiology biomarkers of aging biology. We observed variations in the relationship between each body system represented by physiology biomarkers and biological aging, particularly at the DNA methylation level. These observations provide novel opportunities for integration of both blood-based and saliva-based biomarkers in clinical care of vulnerable and clinically difficult to reach populations where either or both tissues would be accessible for clinical monitoring purposes.
唾液检测通常比血液检测更容易获得,特别是在弱势人群中。然而,不同身体组织中衰老生物学生物标志物之间的联系尚不清楚。方法本研究纳入2008年健康与退休端粒长度研究和2016年静脉血研究中同意唾液和血液采集的个体(N = 2406),这些个体在这两个组织中都有完整的数据。我们根据唾液中的端粒长度和血液中的DNA甲基化和生理测量来评估生物衰老。DNA甲基化时钟结合来自CpGs的信息来产生代表人类表观遗传衰老的衰老措施。我们分析了Horvath(353个CpG位点)、Hannum(71个CpG位点)、Levine或PhenoAge(513个CpG位点)、GrimAge(选择血浆蛋白的表观遗传替代标记)、Horvath皮肤和血液(391个CpG位点)、Lin(99个CpG位点)、Weidner(3个CpG位点)和VidalBralo(8个CpG位点)提出的DNA甲基化时钟。生理指标(称为表型年龄)包括白蛋白、肌酐、葡萄糖、[log] c反应蛋白、淋巴细胞百分比、平均细胞体积、红细胞分布宽度、碱性磷酸酶和白细胞计数。表型年龄算法基于Gompertz比例风险模型的参数化。使用定量PCR (qPCR)通过比较每个患者样本中的端粒序列拷贝数(T)与单拷贝基因拷贝数(S)来测定平均端粒长度。得到的T/S比率与端粒长度(平均值)成正比。在个体内部,评估了血液和唾液中的衰老生物学指标与性别差异之间的关系。结果基于唾液的端粒长度与血液中基于生理和DNA甲基化的衰老生物学标志物呈负相关。基于唾液的端粒长度越长,基于血液的生物标志物的生物衰老速度越慢1至4年,其中幅度最大的是Weidner (β = - 3.97, P = 0.005), GrimAge (β = - 3.33, P <0.001)和Lin (β = - 3.45, P = 0.008) DNA甲基化生物标志物。结论老年人唾液和血液中的衰老生物学标志物之间存在很强的联系。端粒长度的变化随DNA甲基化和衰老生物学生理生物标志物的变化而变化。我们观察到生理生物标志物代表的每个身体系统与生物衰老之间关系的变化,特别是在DNA甲基化水平上。这些观察结果为在临床护理中整合基于血液和基于唾液的生物标志物提供了新的机会,这些生物标志物在临床护理中是脆弱的,并且临床难以到达的人群,其中一种或两种组织都可以用于临床监测目的。
{"title":"Connections between cross-tissue and intra-tissue biomarkers of aging biology in older adults","authors":"R. Waziry, Y. Gu, O. Williams, S. Hägg","doi":"10.1186/s43682-023-00022-4","DOIUrl":"https://doi.org/10.1186/s43682-023-00022-4","url":null,"abstract":"Abstract Background Saliva measures are generally more accessible than blood, especially in vulnerable populations. However, connections between aging biology biomarkers in different body tissues remain unknown. Methods The present study included individuals ( N = 2406) who consented for saliva and blood draw in the Health and Retirement Telomere length study in 2008 and the Venous blood study in 2016 who had complete data for both tissues. We assessed biological aging based on telomere length in saliva and DNA methylation and physiology measures in blood. DNA methylation clocks combine information from CpGs to produce the aging measures representative of epigenetic aging in humans. We analyzed DNA methylation clocks proposed by Horvath (353 CpG sites), Hannum (71 CpG sites), Levine or PhenoAge, (513 CpG sites), GrimAge, (epigenetic surrogate markers for select plasma proteins), Horvath skin and blood (391 CpG sites), Lin (99 CpG sites), Weidner (3 CpG sites), and VidalBralo (8 CpG sites). Physiology measures (referred to as phenotypic age) included albumin, creatinine, glucose, [log] C-reactive protein, lymphocyte percent, mean cell volume, red blood cell distribution width, alkaline phosphatase, and white blood cell count. The phenotypic age algorithm is based on parametrization of Gompertz proportional hazard models. Average telomere length was assayed using quantitative PCR (qPCR) by comparing the telomere sequence copy number in each patient’s sample (T) to a single-copy gene copy number (S). The resulting T/S ratio was proportional to telomere length, mean. Within individual, relationships between aging biology measures in blood and saliva and variations according to sex were assessed. Results Saliva-based telomere length showed inverse associations with both physiology-based and DNA methylation-based aging biology biomarkers in blood. Longer saliva-based telomere length was associated with 1 to 4 years slower biological aging based on blood-based biomarkers with the highest magnitude being Weidner ( β = − 3.97, P = 0.005), GrimAge ( β = − 3.33, P < 0.001), and Lin ( β = − 3.45, P = 0.008) biomarkers of DNA methylation. Conclusions There are strong connections between aging biology biomarkers in saliva and blood in older adults. Changes in telomere length vary with changes in DNA methylation and physiology biomarkers of aging biology. We observed variations in the relationship between each body system represented by physiology biomarkers and biological aging, particularly at the DNA methylation level. These observations provide novel opportunities for integration of both blood-based and saliva-based biomarkers in clinical care of vulnerable and clinically difficult to reach populations where either or both tissues would be accessible for clinical monitoring purposes.","PeriodicalId":72947,"journal":{"name":"Epigenetics communications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136013129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-27DOI: 10.1186/s43682-023-00021-5
Diljeet Kaur, Sol Moe Lee, David Goldberg, Nathan J. Spix, Toshinori Hinoue, Hong-Tao Li, Varun B. Dwaraka, Ryan Smith, Hui Shen, Gangning Liang, Nicole Renke, Peter W. Laird, Wanding Zhou
Abstract Infinium Methylation BeadChips are widely used to profile DNA cytosine modifications in large cohort studies for reasons of cost-effectiveness, accurate quantification, and user-friendly data analysis in characterizing these canonical epigenetic marks. In this work, we conducted a comprehensive evaluation of the updated Infinium MethylationEPIC v2 BeadChip (EPICv2). Our evaluation revealed that EPICv2 offers significant improvements over its predecessors, including expanded enhancer coverage, applicability to diverse ancestry groups, support for low-input DNA down to one nanogram, coverage of existing epigenetic clocks, cell type deconvolution panels, and human trait associations, while maintaining accuracy and reproducibility. Using EPICv2, we were able to identify epigenome and sequence signatures in cell line models of DNMT and SETD2 loss and/or hypomorphism. Furthermore, we provided probe-wise evaluation and annotation to facilitate the use of new features on this array for studying the interplay between somatic mutations and epigenetic landscape in cancer genomics. In conclusion, EPICv2 provides researchers with a valuable tool for studying epigenetic modifications and their role in development and disease.
{"title":"Comprehensive evaluation of the Infinium human MethylationEPIC v2 BeadChip","authors":"Diljeet Kaur, Sol Moe Lee, David Goldberg, Nathan J. Spix, Toshinori Hinoue, Hong-Tao Li, Varun B. Dwaraka, Ryan Smith, Hui Shen, Gangning Liang, Nicole Renke, Peter W. Laird, Wanding Zhou","doi":"10.1186/s43682-023-00021-5","DOIUrl":"https://doi.org/10.1186/s43682-023-00021-5","url":null,"abstract":"Abstract Infinium Methylation BeadChips are widely used to profile DNA cytosine modifications in large cohort studies for reasons of cost-effectiveness, accurate quantification, and user-friendly data analysis in characterizing these canonical epigenetic marks. In this work, we conducted a comprehensive evaluation of the updated Infinium MethylationEPIC v2 BeadChip (EPICv2). Our evaluation revealed that EPICv2 offers significant improvements over its predecessors, including expanded enhancer coverage, applicability to diverse ancestry groups, support for low-input DNA down to one nanogram, coverage of existing epigenetic clocks, cell type deconvolution panels, and human trait associations, while maintaining accuracy and reproducibility. Using EPICv2, we were able to identify epigenome and sequence signatures in cell line models of DNMT and SETD2 loss and/or hypomorphism. Furthermore, we provided probe-wise evaluation and annotation to facilitate the use of new features on this array for studying the interplay between somatic mutations and epigenetic landscape in cancer genomics. In conclusion, EPICv2 provides researchers with a valuable tool for studying epigenetic modifications and their role in development and disease.","PeriodicalId":72947,"journal":{"name":"Epigenetics communications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135538584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.1186/s43682-023-00018-0
S. Zaina
{"title":"Will epigenetics ever be a biosocial science? A reply to Chiapperino and Paneni","authors":"S. Zaina","doi":"10.1186/s43682-023-00018-0","DOIUrl":"https://doi.org/10.1186/s43682-023-00018-0","url":null,"abstract":"","PeriodicalId":72947,"journal":{"name":"Epigenetics communications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42597392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01Epub Date: 2023-01-26DOI: 10.1186/s43682-022-00014-w
Shuwei Liu, Haoyi Fu, Mitali Ray, Lacey W Heinsberg, Yvette P Conley, Cindy M Anderson, Carl A Hubel, James M Roberts, Arun Jeyabalan, Daniel E Weeks, Mandy J Schmella
Background: While preeclampsia (PE) is a leading cause of pregnancy-related morbidity/mortality, its underlying mechanisms are not fully understood. DNA methylation (DNAm) is a dynamic regulator of gene expression that may offer insight into PE pathophysiology and/or serve as a biomarker (e.g., risk, subtype, a therapeutic response). This study's purpose was to evaluate for differences in blood-based DNAm across all trimesters between individuals eventually diagnosed with PE (cases) and individuals who remained normotensive throughout pregnancy, did not develop proteinuria, and birthed a normally grown infant (controls).
Results: In the discovery phase, longitudinal, genome-wide DNAm data were generated across three trimesters of pregnancy in 56 participants (n=28 cases, n=28 controls) individually matched on self-identified race, pre-pregnancy body mass index, smoking, and gestational age at sample collection. An epigenome-wide association study (EWAS) was conducted, using surrogate variable analysis to account for unwanted sources of variation. No CpGs met the genome-wide significance p value threshold of 9×10-8, but 16 CpGs (trimester 1: 5; trimester 2: 1; trimester 3: 10) met the suggestive significance threshold of 1×10-5. DNAm data were also evaluated for differentially methylated regions (DMRs) by PE status. Three DMRs in each trimester were significant after Bonferonni-adjustment. Since only third-trimester samples were available from an independent replication sample (n=64 cases, n=50 controls), the top suggestive hits from trimester 3 (cg16155413 and cg21882990 associated with TRAF3IP2-AS1/TRAF3IP2 genes, which also made up the top DMR) were carried forward for replication. During replication, DNAm data were also generated for validation purposes from discovery phase third trimester samples. While significant associations between DNAm and PE status were observed at both sites in the validation sample, no associations between DNAm and PE status were observed in the independent replication sample.
Conclusions: The discovery phase findings for cg16155413/cg21882990 (TRAF3IP2-AS1/TRAF3IP2) were validated with a new platform but were not replicated in an independent sample. Given the differences in participant characteristics between the discovery and replication samples, we cannot rule out important signals for these CpGs. Additional research is warranted for cg16155413/cg21882990, as well as top hits in trimesters 1-2 and significant DMRs that were not examined in the replication phase.
{"title":"A longitudinal epigenome-wide association study of preeclamptic and normotensive pregnancy.","authors":"Shuwei Liu, Haoyi Fu, Mitali Ray, Lacey W Heinsberg, Yvette P Conley, Cindy M Anderson, Carl A Hubel, James M Roberts, Arun Jeyabalan, Daniel E Weeks, Mandy J Schmella","doi":"10.1186/s43682-022-00014-w","DOIUrl":"10.1186/s43682-022-00014-w","url":null,"abstract":"<p><strong>Background: </strong>While preeclampsia (PE) is a leading cause of pregnancy-related morbidity/mortality, its underlying mechanisms are not fully understood. DNA methylation (DNAm) is a dynamic regulator of gene expression that may offer insight into PE pathophysiology and/or serve as a biomarker (e.g., risk, subtype, a therapeutic response). This study's purpose was to evaluate for differences in blood-based DNAm across all trimesters between individuals eventually diagnosed with PE (cases) and individuals who remained normotensive throughout pregnancy, did not develop proteinuria, and birthed a normally grown infant (controls).</p><p><strong>Results: </strong>In the discovery phase, longitudinal, genome-wide DNAm data were generated across three trimesters of pregnancy in 56 participants (<i>n</i>=28 cases, <i>n</i>=28 controls) individually matched on self-identified race, pre-pregnancy body mass index, smoking, and gestational age at sample collection. An epigenome-wide association study (EWAS) was conducted, using surrogate variable analysis to account for unwanted sources of variation. No CpGs met the genome-wide significance <i>p</i> value threshold of 9×10<sup>-8</sup>, but 16 CpGs (trimester 1: 5; trimester 2: 1; trimester 3: 10) met the suggestive significance threshold of 1×10<sup>-5</sup>. DNAm data were also evaluated for differentially methylated regions (DMRs) by PE status. Three DMRs in each trimester were significant after Bonferonni-adjustment. Since only third-trimester samples were available from an independent replication sample (<i>n</i>=64 cases, <i>n</i>=50 controls), the top suggestive hits from trimester 3 (cg16155413 and cg21882990 associated with <i>TRAF3IP2-AS1/TRAF3IP2</i> genes, which also made up the top DMR) were carried forward for replication. During replication, DNAm data were also generated for validation purposes from discovery phase third trimester samples. While significant associations between DNAm and PE status were observed at both sites in the validation sample, no associations between DNAm and PE status were observed in the independent replication sample.</p><p><strong>Conclusions: </strong>The discovery phase findings for cg16155413/cg21882990 (<i>TRAF3IP2-AS1/TRAF3IP2</i>) were validated with a new platform but were not replicated in an independent sample. Given the differences in participant characteristics between the discovery and replication samples, we cannot rule out important signals for these CpGs. Additional research is warranted for cg16155413/cg21882990, as well as top hits in trimesters 1-2 and significant DMRs that were not examined in the replication phase.</p>","PeriodicalId":72947,"journal":{"name":"Epigenetics communications","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10101051/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9693603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}