Pub Date : 2024-11-18DOI: 10.1186/s13148-024-01767-y
Hannes Frederik Bode, Liang He, Jacob V B Hjelmborg, Jaakko Kaprio, Miina Ollikainen
Background: Assessment of breast cancer (BC) risk generally relies on mammography, family history, reproductive history, and genotyping of major mutations. However, assessing the impact of environmental factors, such as lifestyle, health-related behavior, or external exposures, is still challenging. DNA methylation (DNAm), capturing both genetic and environmental effects, presents a promising opportunity. Previous studies have identified associations and predicted the risk of BC using DNAm in blood; however, these studies did not distinguish between genetic and environmental contributions to these DNAm sites. In this study, associations between DNAm and BC are assessed using paired twin models, which control for shared genetic and environmental effects, allowing testing for associations between DNAm and non-shared environmental exposures and behavior.
Results: Pre-diagnosis blood samples of 32 monozygotic (MZ) and 76 dizygotic (DZ) female twin pairs discordant for BC were collected at the mean age of 56.0 years, with the mean age at diagnosis 66.8 years and censoring 75.2 years. We identified 212 CpGs (p < 6.4*10-8) and 15 DMRs associated with BC risk across all pairs using paired Cox proportional hazard models. All but one of the BC risks associated with CpGs were hypomethylated, and 198/212 CpGs had their DNAm associated with BC risk independent of genetic effects. According to previous literature, at least five of the top CpGs were related to estrogen signaling. Following a comprehensive two-sample Mendelian randomization analysis, we found evidence supporting a dual causal impact of DNAm at cg20145695 (gene body of NXN, rs480351) with increased risk for estrogen receptor positive BC and decreased risk for estrogen receptor negative BC.
Conclusion: While causal effects of DNAm on BC risk are rare, most of the identified CpGs associated with the risk of BC appear to be independent of genetic effects. This suggests that DNAm could serve as a valuable biomarker for environmental risk factors for BC, and may offer potential benefits as a complementary tool to current risk assessment procedures.
背景:乳腺癌(BC)风险评估通常依赖于乳房 X 线照相术、家族史、生育史和主要基因突变的基因分型。然而,评估生活方式、健康相关行为或外部暴露等环境因素的影响仍具有挑战性。DNA 甲基化(DNAm)能同时捕捉遗传和环境的影响,是一个很有前景的机会。以前的研究已经发现了相关性,并利用血液中的 DNAm 预测了 BC 的风险;但是,这些研究并没有区分遗传和环境对这些 DNAm 位点的贡献。在本研究中,使用配对双胞胎模型评估了DNAm与BC之间的关联,该模型控制了共同的遗传和环境影响,从而可以测试DNAm与非共同环境暴露和行为之间的关联:我们收集了32对单卵(MZ)和76对双卵(DZ)雌性孪生子的诊断前血样,这两对孪生子的平均年龄为56.0岁,诊断时的平均年龄为66.8岁,普查时的平均年龄为75.2岁。我们使用配对 Cox 比例危险模型确定了所有配对中与 BC 风险相关的 212 个 CpGs(p -8)和 15 个 DMRs。除一个CpGs外,所有与BC风险相关的CpGs都是低甲基化的,198/212个CpGs的DNAm与BC风险相关,与遗传效应无关。根据以往的文献,至少有五个顶级 CpGs 与雌激素信号转导有关。经过全面的双样本孟德尔随机分析,我们发现有证据支持cg20145695(NXN基因体,rs480351)的DNAm具有双重因果影响,即雌激素受体阳性的BC风险增加,而雌激素受体阴性的BC风险降低:虽然 DNAm 对 BC 风险的因果效应并不多见,但大多数已确定的与 BC 风险相关的 CpGs 似乎与遗传效应无关。这表明 DNAm 可作为 BC 环境风险因素的一种有价值的生物标志物,并可作为当前风险评估程序的一种补充工具,提供潜在的益处。
{"title":"Pre-diagnosis blood DNA methylation profiling of twin pairs discordant for breast cancer points to the importance of environmental risk factors.","authors":"Hannes Frederik Bode, Liang He, Jacob V B Hjelmborg, Jaakko Kaprio, Miina Ollikainen","doi":"10.1186/s13148-024-01767-y","DOIUrl":"10.1186/s13148-024-01767-y","url":null,"abstract":"<p><strong>Background: </strong>Assessment of breast cancer (BC) risk generally relies on mammography, family history, reproductive history, and genotyping of major mutations. However, assessing the impact of environmental factors, such as lifestyle, health-related behavior, or external exposures, is still challenging. DNA methylation (DNAm), capturing both genetic and environmental effects, presents a promising opportunity. Previous studies have identified associations and predicted the risk of BC using DNAm in blood; however, these studies did not distinguish between genetic and environmental contributions to these DNAm sites. In this study, associations between DNAm and BC are assessed using paired twin models, which control for shared genetic and environmental effects, allowing testing for associations between DNAm and non-shared environmental exposures and behavior.</p><p><strong>Results: </strong>Pre-diagnosis blood samples of 32 monozygotic (MZ) and 76 dizygotic (DZ) female twin pairs discordant for BC were collected at the mean age of 56.0 years, with the mean age at diagnosis 66.8 years and censoring 75.2 years. We identified 212 CpGs (p < 6.4*10<sup>-8</sup>) and 15 DMRs associated with BC risk across all pairs using paired Cox proportional hazard models. All but one of the BC risks associated with CpGs were hypomethylated, and 198/212 CpGs had their DNAm associated with BC risk independent of genetic effects. According to previous literature, at least five of the top CpGs were related to estrogen signaling. Following a comprehensive two-sample Mendelian randomization analysis, we found evidence supporting a dual causal impact of DNAm at cg20145695 (gene body of NXN, rs480351) with increased risk for estrogen receptor positive BC and decreased risk for estrogen receptor negative BC.</p><p><strong>Conclusion: </strong>While causal effects of DNAm on BC risk are rare, most of the identified CpGs associated with the risk of BC appear to be independent of genetic effects. This suggests that DNAm could serve as a valuable biomarker for environmental risk factors for BC, and may offer potential benefits as a complementary tool to current risk assessment procedures.</p>","PeriodicalId":10366,"journal":{"name":"Clinical Epigenetics","volume":"16 1","pages":"160"},"PeriodicalIF":4.8,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11574988/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142667454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-18DOI: 10.1186/s13148-024-01776-x
Soyeon Kim, Yidi Qin, Hyun Jung Park, Rebecca I Caldino Bohn, Molin Yue, Zhongli Xu, Erick Forno, Wei Chen, Juan C Celedón
Background: DNA methylation is a critical regulatory mechanism of gene expression, influencing various human diseases and traits. While traditional expression quantitative trait loci (eQTL) studies have helped elucidate the genetic regulation of gene expression, there is a growing need to explore environmental influences on gene expression. Existing methods such as PrediXcan and FUSION focus on genotype-based associations but overlook the impact of environmental factors. To address this gap, we present MOSES (methylation-based gene association), a novel approach that utilizes DNA methylation to identify environmentally regulated genes associated with traits or diseases without relying on measured gene expression.
Results: MOSES involves training, imputation, and association testing. It employs elastic-net penalized regression models to estimate the influence of CpGs and SNPs (if available) on gene expression. We developed and compared four MOSES versions incorporating different methylation and genetic data: (1) cis-DNA methylation within 1 Mb of promoter regions, (2) both cis-SNPs and cis-CpGs, 3) both cis- and a part of trans- CpGs (±5Mb away) from promoter regions), and 4) long-range DNA methylation (±10 Mb away) from promoter regions. Our analysis using nasal epithelium and white blood cell data from the Epigenetic Variation and Childhood Asthma in Puerto Ricans (EVA-PR) study demonstrated that MOSES, particularly the version incorporating long-range CpGs (MOSES-DNAm 10 M), significantly outperformed existing methods like PrediXcan, MethylXcan, and Biomethyl in predicting gene expression. MOSES-DNAm 10 M identified more differentially expressed genes (DEGs) associated with atopic asthma, particularly those involved in immune pathways, highlighting its superior performance in uncovering environmentally regulated genes. Further application of MOSES to lung tissue data from idiopathic pulmonary fibrosis (IPF) patients confirmed its robustness and versatility across different diseases and tissues.
Conclusion: MOSES represents an innovative advancement in gene association studies, leveraging DNA methylation to capture the influence of environmental factors on gene expression. By incorporating long-range CpGs, MOSES-DNAm 10 M provides superior predictive accuracy and gene association capabilities compared to traditional genotype-based methods. This novel approach offers valuable insights into the complex interplay between genetics and the environment, enhancing our understanding of disease mechanisms and potentially guiding therapeutic strategies. The user-friendly MOSES R package is publicly available to advance studies in various diseases, including immune-related conditions like asthma.
背景:DNA 甲基化是基因表达的重要调控机制,影响着人类的各种疾病和性状。虽然传统的表达量性状位点(eQTL)研究有助于阐明基因表达的遗传调控,但人们越来越需要探索环境对基因表达的影响。PrediXcan 和 FUSION 等现有方法侧重于基于基因型的关联,但忽略了环境因素的影响。为了弥补这一缺陷,我们提出了 MOSES(基于甲基化的基因关联),这是一种利用 DNA 甲基化来识别与性状或疾病相关的环境调控基因的新方法,而无需依赖测量的基因表达:结果:MOSES 包括训练、估算和关联测试。它采用弹性网惩罚回归模型来估计 CpGs 和 SNPs(如果有的话)对基因表达的影响。我们开发并比较了四种包含不同甲基化和遗传数据的 MOSES 版本:(1)启动子区域 1 Mb 范围内的顺式 DNA 甲基化;(2)顺式 SNP 和顺式 CpGs;(3)顺式 CpGs 和部分反式 CpGs(距离启动子区域 ±5 Mb);(4)距离启动子区域的长程 DNA 甲基化(距离启动子区域 ±10 Mb)。我们利用波多黎各人表观遗传变异和儿童哮喘(EVA-PR)研究中的鼻上皮细胞和白细胞数据进行的分析表明,MOSES,尤其是包含长程 CpGs 的版本(MOSES-DNAm 10 M),在预测基因表达方面明显优于 PrediXcan、MethylXcan 和 Biomethyl 等现有方法。MOSES-DNAm 10 M 发现了更多与特应性哮喘相关的差异表达基因(DEGs),尤其是那些参与免疫通路的基因,这凸显了它在发现环境调控基因方面的卓越性能。MOSES 在特发性肺纤维化(IPF)患者肺组织数据中的进一步应用证实了它在不同疾病和组织中的稳健性和通用性:MOSES代表了基因关联研究的创新进步,它利用DNA甲基化捕捉环境因素对基因表达的影响。通过结合长程 CpGs,MOSES-DNAm 10 M 与传统的基于基因型的方法相比,具有更高的预测准确性和基因关联能力。这种新方法为我们深入了解遗传与环境之间复杂的相互作用提供了宝贵的视角,增强了我们对疾病机制的理解,并有可能为治疗策略提供指导。用户友好的 MOSES R 软件包已公开发布,可用于推进各种疾病的研究,包括哮喘等免疫相关疾病。
{"title":"MOSES: a methylation-based gene association approach for unveiling environmentally regulated genes linked to a trait or disease.","authors":"Soyeon Kim, Yidi Qin, Hyun Jung Park, Rebecca I Caldino Bohn, Molin Yue, Zhongli Xu, Erick Forno, Wei Chen, Juan C Celedón","doi":"10.1186/s13148-024-01776-x","DOIUrl":"10.1186/s13148-024-01776-x","url":null,"abstract":"<p><strong>Background: </strong>DNA methylation is a critical regulatory mechanism of gene expression, influencing various human diseases and traits. While traditional expression quantitative trait loci (eQTL) studies have helped elucidate the genetic regulation of gene expression, there is a growing need to explore environmental influences on gene expression. Existing methods such as PrediXcan and FUSION focus on genotype-based associations but overlook the impact of environmental factors. To address this gap, we present MOSES (methylation-based gene association), a novel approach that utilizes DNA methylation to identify environmentally regulated genes associated with traits or diseases without relying on measured gene expression.</p><p><strong>Results: </strong>MOSES involves training, imputation, and association testing. It employs elastic-net penalized regression models to estimate the influence of CpGs and SNPs (if available) on gene expression. We developed and compared four MOSES versions incorporating different methylation and genetic data: (1) cis-DNA methylation within 1 Mb of promoter regions, (2) both cis-SNPs and cis-CpGs, 3) both cis- and a part of trans- CpGs (±5Mb away) from promoter regions), and 4) long-range DNA methylation (±10 Mb away) from promoter regions. Our analysis using nasal epithelium and white blood cell data from the Epigenetic Variation and Childhood Asthma in Puerto Ricans (EVA-PR) study demonstrated that MOSES, particularly the version incorporating long-range CpGs (MOSES-DNAm 10 M), significantly outperformed existing methods like PrediXcan, MethylXcan, and Biomethyl in predicting gene expression. MOSES-DNAm 10 M identified more differentially expressed genes (DEGs) associated with atopic asthma, particularly those involved in immune pathways, highlighting its superior performance in uncovering environmentally regulated genes. Further application of MOSES to lung tissue data from idiopathic pulmonary fibrosis (IPF) patients confirmed its robustness and versatility across different diseases and tissues.</p><p><strong>Conclusion: </strong>MOSES represents an innovative advancement in gene association studies, leveraging DNA methylation to capture the influence of environmental factors on gene expression. By incorporating long-range CpGs, MOSES-DNAm 10 M provides superior predictive accuracy and gene association capabilities compared to traditional genotype-based methods. This novel approach offers valuable insights into the complex interplay between genetics and the environment, enhancing our understanding of disease mechanisms and potentially guiding therapeutic strategies. The user-friendly MOSES R package is publicly available to advance studies in various diseases, including immune-related conditions like asthma.</p>","PeriodicalId":10366,"journal":{"name":"Clinical Epigenetics","volume":"16 1","pages":"161"},"PeriodicalIF":4.8,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11574994/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142667453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-14DOI: 10.1186/s13148-024-01754-3
Katherine Beigel, Xiao-Min Wang, Li Song, Kelly Maurer, Christopher Breen, Deanne Taylor, Daniel Goldman, Michelle Petri, Kathleen E Sullivan
Background: Systemic lupus erythematosus (SLE) is an autoimmune disease with protean manifestations. There is little understanding of why some organs are specifically impacted in patients and the mechanisms of disease persistence remain unclear. While much work has been done characterizing the DNA methylation status in SLE, there is less information on histone modifications, a more dynamic epigenetic feature. This study identifies two histone marks of activation and the binding of p300 genome-wide in three cell types and three clinical subsets to better understand cell-specific effects and differences across clinical subsets.
Results: We examined 20 patients with SLE and 8 controls and found that individual chromatin marks varied considerably across T cells, B cells, and monocytes. When pathways were examined, there was far more concordance with conservation of TNF, IL-2/STAT5, and KRAS pathways across multiple cell types and ChIP data sets. Patients with cutaneous lupus and lupus nephritis generally had less dramatically altered chromatin than the general SLE group. Signals also demonstrated significant overlap with GWAS signals in a manner that did not implicate one cell type more than the others.
Conclusions: The pathways identified by altered histone modifications and p300 binding are pathways known to be important from RNA expression studies and recognized pathogenic mechanisms of disease. NFκB and classical inflammatory pathways were strongly associated with increased peak heights across all cell types but were the highest-ranking pathway for all three antibodies in monocytes according to fgsea analysis. IL-6 Jak/STAT3 signaling was the most significant pathway association in T cells marked by H3K27ac change. Therefore, each cell type experiences the disease process distinctly although in all cases there was a strong theme of classical inflammatory pathways. Importantly, this NFκB pathway, so strongly implicated in the patients with generalized SLE, was much less impacted in monocytes when cutaneous lupus was compared to the general SLE cohort and also less impacted in lupus nephritis compared to general SLE. These studies define important cell type differences and emphasize the breadth of the inflammatory effects in SLE.
背景:系统性红斑狼疮(SLE)是一种具有多种表现的自身免疫性疾病。人们对患者某些器官受到特殊影响的原因知之甚少,对疾病持续存在的机制也仍不清楚。尽管对系统性红斑狼疮患者的 DNA 甲基化状态进行了大量研究,但关于组蛋白修饰这一更具动态性的表观遗传特征的信息却较少。本研究在三种细胞类型和三个临床亚群中确定了两种组蛋白激活标记和 p300 的全基因组结合,以更好地了解细胞特异性效应和不同临床亚群之间的差异:我们对 20 名系统性红斑狼疮患者和 8 名对照组进行了研究,发现 T 细胞、B 细胞和单核细胞的染色质标记差异很大。在研究通路时,TNF、IL-2/STAT5 和 KRAS 通路在多种细胞类型和 ChIP 数据集中的一致性更高。与一般系统性红斑狼疮患者相比,皮肤狼疮和狼疮肾炎患者的染色质通常变化较小。这些信号还与 GWAS 信号有明显的重叠,但并不意味着一种细胞类型比其他细胞类型有更大的牵连:结论:组蛋白修饰和 p300 结合改变所确定的通路是 RNA 表达研究和公认的疾病致病机制中已知的重要通路。NFκB和经典炎症通路与所有细胞类型的峰高增加密切相关,但根据fgsea分析,NFκB和经典炎症通路是单核细胞中三种抗体的最高级通路。在以 H3K27ac 变化为标志的 T 细胞中,IL-6 Jak/STAT3 信号转导是最重要的关联途径。因此,每种细胞类型都经历了不同的疾病过程,尽管在所有病例中,经典的炎症通路都是一个强烈的主题。重要的是,NFκB通路在全身性系统性红斑狼疮患者中的影响非常大,但与全身性系统性红斑狼疮患者相比,皮肤狼疮对单核细胞的影响要小得多,狼疮性肾炎对单核细胞的影响也小于全身性系统性红斑狼疮。这些研究确定了重要的细胞类型差异,并强调了系统性红斑狼疮炎症影响的广泛性。
{"title":"Comparison of cell type and disease subset chromatin modifications in SLE.","authors":"Katherine Beigel, Xiao-Min Wang, Li Song, Kelly Maurer, Christopher Breen, Deanne Taylor, Daniel Goldman, Michelle Petri, Kathleen E Sullivan","doi":"10.1186/s13148-024-01754-3","DOIUrl":"10.1186/s13148-024-01754-3","url":null,"abstract":"<p><strong>Background: </strong>Systemic lupus erythematosus (SLE) is an autoimmune disease with protean manifestations. There is little understanding of why some organs are specifically impacted in patients and the mechanisms of disease persistence remain unclear. While much work has been done characterizing the DNA methylation status in SLE, there is less information on histone modifications, a more dynamic epigenetic feature. This study identifies two histone marks of activation and the binding of p300 genome-wide in three cell types and three clinical subsets to better understand cell-specific effects and differences across clinical subsets.</p><p><strong>Results: </strong>We examined 20 patients with SLE and 8 controls and found that individual chromatin marks varied considerably across T cells, B cells, and monocytes. When pathways were examined, there was far more concordance with conservation of TNF, IL-2/STAT5, and KRAS pathways across multiple cell types and ChIP data sets. Patients with cutaneous lupus and lupus nephritis generally had less dramatically altered chromatin than the general SLE group. Signals also demonstrated significant overlap with GWAS signals in a manner that did not implicate one cell type more than the others.</p><p><strong>Conclusions: </strong>The pathways identified by altered histone modifications and p300 binding are pathways known to be important from RNA expression studies and recognized pathogenic mechanisms of disease. NFκB and classical inflammatory pathways were strongly associated with increased peak heights across all cell types but were the highest-ranking pathway for all three antibodies in monocytes according to fgsea analysis. IL-6 Jak/STAT3 signaling was the most significant pathway association in T cells marked by H3K27ac change. Therefore, each cell type experiences the disease process distinctly although in all cases there was a strong theme of classical inflammatory pathways. Importantly, this NFκB pathway, so strongly implicated in the patients with generalized SLE, was much less impacted in monocytes when cutaneous lupus was compared to the general SLE cohort and also less impacted in lupus nephritis compared to general SLE. These studies define important cell type differences and emphasize the breadth of the inflammatory effects in SLE.</p>","PeriodicalId":10366,"journal":{"name":"Clinical Epigenetics","volume":"16 1","pages":"159"},"PeriodicalIF":4.8,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11566291/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-14DOI: 10.1186/s13148-024-01764-1
Luciano Calzari, Davide Fernando Dragani, Lucia Zanotti, Elvira Inglese, Romano Danesi, Rebecca Cavagnola, Alberto Brusati, Francesco Ranucci, Anna Maria Di Blasio, Luca Persani, Irene Campi, Sara De Martino, Antonella Farsetti, Veronica Barbi, Michela Gottardi Zamperla, Giulia Nicole Baldrighi, Carlo Gaetano, Gianfranco Parati, Davide Gentilini
{"title":"Correction: Epigenetic patterns, accelerated biological aging, and enhanced epigenetic drift detected 6 months following COVID‑19 infection: insights from a genome‑wide DNA methylation study.","authors":"Luciano Calzari, Davide Fernando Dragani, Lucia Zanotti, Elvira Inglese, Romano Danesi, Rebecca Cavagnola, Alberto Brusati, Francesco Ranucci, Anna Maria Di Blasio, Luca Persani, Irene Campi, Sara De Martino, Antonella Farsetti, Veronica Barbi, Michela Gottardi Zamperla, Giulia Nicole Baldrighi, Carlo Gaetano, Gianfranco Parati, Davide Gentilini","doi":"10.1186/s13148-024-01764-1","DOIUrl":"10.1186/s13148-024-01764-1","url":null,"abstract":"","PeriodicalId":10366,"journal":{"name":"Clinical Epigenetics","volume":"16 1","pages":"158"},"PeriodicalIF":4.8,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11566271/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-13DOI: 10.1186/s13148-024-01772-1
Xing-Xuan Dong, Dong-Ling Chen, Hui-Min Chen, Dan-Lin Li, Dan-Ning Hu, Carla Lanca, Andrzej Grzybowski, Chen-Wei Pan
Background: This study aimed to identify DNA methylation biomarkers associated with myopia using summary-data-based Mendelian randomization (SMR).
Methods: A systematic search of the PubMed, Web of Science, Cochrane Library, and Embase databases was conducted up to March 27, 2024. SMR analyses were performed to integrate genome-wide association study (GWAS) with methylation quantitative trait loci (mQTL) and expression quantitative trait loci (eQTL) studies. The heterogeneity in the dependent instrument (HEIDI) test was utilized to distinguish pleiotropic associations from linkage disequilibrium.
Results: The systematic review identified 26 DNA methylation biomarkers in five studies, with no overlap observed among those identified by different studies. After integrating GWAS with multi-omics data of mQTL and eQTL, six genes were significantly associated with myopia: PRMT6 (cg00944433 and cg15468180), SH3YL1 (cg03299269, cg11361895, and cg13354988), ZKSCAN4 (cg01192291), GATS (cg17830204), NPAT (cg04826772), and UBE2I (cg03545757 and cg08025960).
Conclusions: We identified six methylation biomarkers associated with the risk of myopia that may be helpful to elucidate the etiology mechanisms of myopia. Further experimental validation studies are required to corroborate these findings.
{"title":"DNA methylation biomarkers and myopia: a multi-omics study integrating GWAS, mQTL and eQTL data.","authors":"Xing-Xuan Dong, Dong-Ling Chen, Hui-Min Chen, Dan-Lin Li, Dan-Ning Hu, Carla Lanca, Andrzej Grzybowski, Chen-Wei Pan","doi":"10.1186/s13148-024-01772-1","DOIUrl":"10.1186/s13148-024-01772-1","url":null,"abstract":"<p><strong>Background: </strong>This study aimed to identify DNA methylation biomarkers associated with myopia using summary-data-based Mendelian randomization (SMR).</p><p><strong>Methods: </strong>A systematic search of the PubMed, Web of Science, Cochrane Library, and Embase databases was conducted up to March 27, 2024. SMR analyses were performed to integrate genome-wide association study (GWAS) with methylation quantitative trait loci (mQTL) and expression quantitative trait loci (eQTL) studies. The heterogeneity in the dependent instrument (HEIDI) test was utilized to distinguish pleiotropic associations from linkage disequilibrium.</p><p><strong>Results: </strong>The systematic review identified 26 DNA methylation biomarkers in five studies, with no overlap observed among those identified by different studies. After integrating GWAS with multi-omics data of mQTL and eQTL, six genes were significantly associated with myopia: PRMT6 (cg00944433 and cg15468180), SH3YL1 (cg03299269, cg11361895, and cg13354988), ZKSCAN4 (cg01192291), GATS (cg17830204), NPAT (cg04826772), and UBE2I (cg03545757 and cg08025960).</p><p><strong>Conclusions: </strong>We identified six methylation biomarkers associated with the risk of myopia that may be helpful to elucidate the etiology mechanisms of myopia. Further experimental validation studies are required to corroborate these findings.</p>","PeriodicalId":10366,"journal":{"name":"Clinical Epigenetics","volume":"16 1","pages":"157"},"PeriodicalIF":4.8,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11562087/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-10DOI: 10.1186/s13148-024-01768-x
Teodor G Calina, Eilís Perez, Elena Grafenhorst, Jamal Benhamida, Simon Schallenberg, Adrian Popescu, Ines Koch, Tobias Janik, BaoQing Chen, Jana Ihlow, Stephanie Roessler, Benjamin Goeppert, Bruno Sinn, Marcus Bahra, George A Calin, Eliane T Taube, Uwe Pelzer, Christopher C M Neumann, David Horst, Erik Knutsen, David Capper, Mihnea P Dragomir
Background: We have recently constructed a DNA methylation classifier that can discriminate between pancreatic ductal adenocarcinoma (PAAD) liver metastasis and intrahepatic cholangiocarcinoma (iCCA) with high accuracy (PAAD-iCCA-Classifier). PAAD is one of the leading causes of cancer of unknown primary and diagnosis is based on exclusion of other malignancies. Therefore, our focus was to investigate whether the PAAD-iCCA-Classifier can be used to diagnose PAAD metastases from other sites.
Methods: For this scope, the anomaly detection filter of the initial classifier was expanded by 8 additional mimicker carcinomas, amounting to a total of 10 carcinomas in the negative class. We validated the updated version of the classifier on a validation set, which consisted of a biological cohort (n = 3579) and a technical one (n = 15). We then assessed the performance of the classifier on a test set, which included a positive control cohort of 16 PAAD metastases from various sites and a cohort of 124 negative control samples consisting of 96 breast cancer metastases from 18 anatomical sites and 28 carcinoma metastases to the brain.
Results: The updated PAAD-iCCA-Classifier achieved 98.21% accuracy on the biological validation samples, and on the technical validation ones it reached 100%. The classifier also correctly identified 15/16 (93.75%) metastases of the positive control as PAAD, and on the negative control, it correctly classified 122/124 samples (98.39%) for a 97.85% overall accuracy on the test set. We used this DNA methylation dataset to explore the organotropism of PAAD metastases and observed that PAAD liver metastases are distinct from PAAD peritoneal carcinomatosis and primary PAAD, and are characterized by specific copy number alterations and hypomethylation of enhancers involved in epithelial-mesenchymal-transition.
Conclusions: The updated PAAD-iCCA-Classifier (available at https://classifier.tgc-research.de/ ) can accurately classify PAAD samples from various metastatic sites and it can serve as a diagnostic aid.
{"title":"DNA methylation classifier to diagnose pancreatic ductal adenocarcinoma metastases from different anatomical sites.","authors":"Teodor G Calina, Eilís Perez, Elena Grafenhorst, Jamal Benhamida, Simon Schallenberg, Adrian Popescu, Ines Koch, Tobias Janik, BaoQing Chen, Jana Ihlow, Stephanie Roessler, Benjamin Goeppert, Bruno Sinn, Marcus Bahra, George A Calin, Eliane T Taube, Uwe Pelzer, Christopher C M Neumann, David Horst, Erik Knutsen, David Capper, Mihnea P Dragomir","doi":"10.1186/s13148-024-01768-x","DOIUrl":"10.1186/s13148-024-01768-x","url":null,"abstract":"<p><strong>Background: </strong>We have recently constructed a DNA methylation classifier that can discriminate between pancreatic ductal adenocarcinoma (PAAD) liver metastasis and intrahepatic cholangiocarcinoma (iCCA) with high accuracy (PAAD-iCCA-Classifier). PAAD is one of the leading causes of cancer of unknown primary and diagnosis is based on exclusion of other malignancies. Therefore, our focus was to investigate whether the PAAD-iCCA-Classifier can be used to diagnose PAAD metastases from other sites.</p><p><strong>Methods: </strong>For this scope, the anomaly detection filter of the initial classifier was expanded by 8 additional mimicker carcinomas, amounting to a total of 10 carcinomas in the negative class. We validated the updated version of the classifier on a validation set, which consisted of a biological cohort (n = 3579) and a technical one (n = 15). We then assessed the performance of the classifier on a test set, which included a positive control cohort of 16 PAAD metastases from various sites and a cohort of 124 negative control samples consisting of 96 breast cancer metastases from 18 anatomical sites and 28 carcinoma metastases to the brain.</p><p><strong>Results: </strong>The updated PAAD-iCCA-Classifier achieved 98.21% accuracy on the biological validation samples, and on the technical validation ones it reached 100%. The classifier also correctly identified 15/16 (93.75%) metastases of the positive control as PAAD, and on the negative control, it correctly classified 122/124 samples (98.39%) for a 97.85% overall accuracy on the test set. We used this DNA methylation dataset to explore the organotropism of PAAD metastases and observed that PAAD liver metastases are distinct from PAAD peritoneal carcinomatosis and primary PAAD, and are characterized by specific copy number alterations and hypomethylation of enhancers involved in epithelial-mesenchymal-transition.</p><p><strong>Conclusions: </strong>The updated PAAD-iCCA-Classifier (available at https://classifier.tgc-research.de/ ) can accurately classify PAAD samples from various metastatic sites and it can serve as a diagnostic aid.</p>","PeriodicalId":10366,"journal":{"name":"Clinical Epigenetics","volume":"16 1","pages":"156"},"PeriodicalIF":4.8,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11550539/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-09DOI: 10.1186/s13148-024-01771-2
Qiang Gao, Kefeng Shen, Min Xiao
TET2 is a critical gene that regulates DNA methylation, encoding a dioxygenase protein that plays a vital role in the regulation of genomic methylation and other epigenetic modifications, as well as in hematopoiesis. Mutations in TET2 are present in 7%-28% of adult acute myeloid leukemia (AML) patients. Despite this, the precise mechanisms by which TET2 mutations contribute to malignant transformation and how these insights can be leveraged to enhance treatment strategies for AML patients with TET2 mutations remain unclear. In this review, we provide an overview of the functions of TET2, the effects of its mutations, its role in clonal hematopoiesis, and the possible mechanisms of leukemogenesis. Additionally, we explore the mutational landscape across different AML subtypes and present recent promising preclinical research findings.
{"title":"TET2 mutation in acute myeloid leukemia: biology, clinical significance, and therapeutic insights.","authors":"Qiang Gao, Kefeng Shen, Min Xiao","doi":"10.1186/s13148-024-01771-2","DOIUrl":"10.1186/s13148-024-01771-2","url":null,"abstract":"<p><p>TET2 is a critical gene that regulates DNA methylation, encoding a dioxygenase protein that plays a vital role in the regulation of genomic methylation and other epigenetic modifications, as well as in hematopoiesis. Mutations in TET2 are present in 7%-28% of adult acute myeloid leukemia (AML) patients. Despite this, the precise mechanisms by which TET2 mutations contribute to malignant transformation and how these insights can be leveraged to enhance treatment strategies for AML patients with TET2 mutations remain unclear. In this review, we provide an overview of the functions of TET2, the effects of its mutations, its role in clonal hematopoiesis, and the possible mechanisms of leukemogenesis. Additionally, we explore the mutational landscape across different AML subtypes and present recent promising preclinical research findings.</p>","PeriodicalId":10366,"journal":{"name":"Clinical Epigenetics","volume":"16 1","pages":"155"},"PeriodicalIF":4.8,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11550532/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Assay of Transposase Accessible Chromatin Sequencing (ATAC-seq) is a high-throughput sequencing technique that detects open chromatin regions across the genome. These regions are critical in facilitating transcription factor binding and subsequent gene expression. Herein, we utilized ATAC-seq to identify key molecular targets regulating the development and progression of hepatocellular carcinoma (HCC) and elucidate the underlying mechanisms.
Methods: We first compared chromatin accessibility profiles between HCC and normal tissues. Subsequently, RNA-seq data was employed to identify differentially expressed genes (DEGs). Integrating ATAC-seq and RNA-seq data allowed the identification of transcription factors and their putative target genes associated with differentially accessible regions (DARs). Finally, functional experiments were conducted to investigate the effects of the identified regulatory factors and corresponding targets on HCC cell proliferation and migration.
Results: Enrichment analysis of DARs between HCC and adjacent normal tissues revealed distinct signaling pathways and regulatory factors. Upregulated DARs in HCC were enriched in genes related to the MAPK and FoxO signaling pathways and associated with transcription factor families like ETS and AP-1. Conversely, downregulated DARs were associated with the TGF-β, cAMP, and p53 signaling pathways and the CTCF family. Integration of the datasets revealed a positive correlation between specific DARs and DEGs. Notably, PRPF3 emerged as a gene associated with DARs in HCC, and functional assays demonstrated its ability to promote HCC cell proliferation and migration. To the best of our knowledge, this is the first report highlighting the oncogenic role of PRPF3 in HCC. Furthermore, ZNF93 expression positively correlated with PRPF3, and ChIP-seq data indicated its potential role as a transcription factor regulating PRPF3 by binding to its promoter region.
Conclusion: This study provides a comprehensive analysis of the epigenetic landscape in HCC, encompassing both chromatin accessibility and the transcriptome. Our findings reveal that ZNF93 promotes the proliferation and motility of HCC cells through transcriptional regulation of a novel oncogene, PRPF3.
{"title":"Integrative analysis based on ATAC-seq and RNA-seq reveals a novel oncogene PRPF3 in hepatocellular carcinoma.","authors":"Yi Bai, Xiyue Deng, Dapeng Chen, Shuangqing Han, Zijie Lin, Zhongmin Li, Wen Tong, Jinming Li, Tianze Wang, Xiangyu Liu, Zirong Liu, Zilin Cui, Yamin Zhang","doi":"10.1186/s13148-024-01769-w","DOIUrl":"10.1186/s13148-024-01769-w","url":null,"abstract":"<p><strong>Background: </strong>Assay of Transposase Accessible Chromatin Sequencing (ATAC-seq) is a high-throughput sequencing technique that detects open chromatin regions across the genome. These regions are critical in facilitating transcription factor binding and subsequent gene expression. Herein, we utilized ATAC-seq to identify key molecular targets regulating the development and progression of hepatocellular carcinoma (HCC) and elucidate the underlying mechanisms.</p><p><strong>Methods: </strong>We first compared chromatin accessibility profiles between HCC and normal tissues. Subsequently, RNA-seq data was employed to identify differentially expressed genes (DEGs). Integrating ATAC-seq and RNA-seq data allowed the identification of transcription factors and their putative target genes associated with differentially accessible regions (DARs). Finally, functional experiments were conducted to investigate the effects of the identified regulatory factors and corresponding targets on HCC cell proliferation and migration.</p><p><strong>Results: </strong>Enrichment analysis of DARs between HCC and adjacent normal tissues revealed distinct signaling pathways and regulatory factors. Upregulated DARs in HCC were enriched in genes related to the MAPK and FoxO signaling pathways and associated with transcription factor families like ETS and AP-1. Conversely, downregulated DARs were associated with the TGF-β, cAMP, and p53 signaling pathways and the CTCF family. Integration of the datasets revealed a positive correlation between specific DARs and DEGs. Notably, PRPF3 emerged as a gene associated with DARs in HCC, and functional assays demonstrated its ability to promote HCC cell proliferation and migration. To the best of our knowledge, this is the first report highlighting the oncogenic role of PRPF3 in HCC. Furthermore, ZNF93 expression positively correlated with PRPF3, and ChIP-seq data indicated its potential role as a transcription factor regulating PRPF3 by binding to its promoter region.</p><p><strong>Conclusion: </strong>This study provides a comprehensive analysis of the epigenetic landscape in HCC, encompassing both chromatin accessibility and the transcriptome. Our findings reveal that ZNF93 promotes the proliferation and motility of HCC cells through transcriptional regulation of a novel oncogene, PRPF3.</p>","PeriodicalId":10366,"journal":{"name":"Clinical Epigenetics","volume":"16 1","pages":"154"},"PeriodicalIF":4.8,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11539654/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142582319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-04DOI: 10.1186/s13148-024-01766-z
Tina Draškovič, Branislava Ranković, Nina Zidar, Nina Hauptman
<p><strong>Background: </strong>DNA methylation biomarkers are one of the most promising tools for the diagnosis and differentiation of adenocarcinomas of the liver, which are among the most common malignancies worldwide. Their differentiation is important because of the different prognoses and treatment options. This study aimed to validate previously identified DNA methylation biomarkers that successfully differentiate between liver adenocarcinomas, including the two most common primary liver cancers, hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), as well as two common metastatic liver cancers, colorectal liver metastases (CRLM) and pancreatic ductal adenocarcinoma liver metastases (PCLM), and translate them to the methylation-sensitive high-resolution melting (MS-HRM) and digital PCR (dPCR) platforms.</p><p><strong>Methods: </strong>Our study included a cohort of 149 formalin-fixed, paraffin-embedded tissue samples, including 19 CRLMs, 10 PCLMs, 15 HCCs, 15 CCAs, 15 colorectal adenocarcinomas (CRCs), 15 pancreatic ductal adenocarcinomas (PDACs) and their paired normal tissue samples. The methylation status of the samples was experimentally determined by MS-HRM and methylation-specific dPCR. Previously determined methylation threshold were adjusted according to dPCR data and applied to the same DNA methylation array datasets (provided by The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO)) used to originally identify the biomarkers for the included cancer types and additional CRLM projects. The sensitivities, specificities and diagnostic accuracies of the panels for individual cancer types were calculated.</p><p><strong>Results: </strong>In the dPCR experiment, the DNA methylation panels identified HCC, CCA, CRC, PDAC, CRLM and PCLM with sensitivities of 100%, 66.7%, 100%, 86.7%, 94.7% and 80%, respectively. The panels differentiate between HCC, CCA, CRLM, PCLM and healthy liver tissue with specificities of 100%, 100%, 97.1% and 94.9% and with diagnostic accuracies of 100%, 94%, 97% and 93%, respectively. Reevaluation of the same bioinformatic data with new additional CRLM projects demonstrated that the lower dPCR methylation threshold still effectively differentiates between the included cancer types. The bioinformatic data achieved sensitivities for HCC, CCA, CRC, PDAC, CRLM and PCLM of 88%, 64%, 97.4%, 75.5%, 80% and 84.6%, respectively. Specificities between HCC, CCA, CRLM, PCLM and healthy liver tissue were 98%, 93%, 86.6% and 98.2% and the diagnostic accuracies were 94%, 91%, 86% and 98%, respectively. Moreover, we confirmed that the methylation of the investigated promoters is preserved from primary CRC and PDAC to their liver metastases.</p><p><strong>Conclusions: </strong>The cancer-specific methylation biomarker panels exhibit high sensitivities, specificities and diagnostic accuracies and enable differentiation between primary and metastatic adenocarcinomas of the liver using methylation-specific dPCR. High
{"title":"DNA methylation biomarker panels for differentiating various liver adenocarcinomas, including hepatocellular carcinoma, cholangiocarcinoma, colorectal liver metastases and pancreatic adenocarcinoma liver metastases.","authors":"Tina Draškovič, Branislava Ranković, Nina Zidar, Nina Hauptman","doi":"10.1186/s13148-024-01766-z","DOIUrl":"10.1186/s13148-024-01766-z","url":null,"abstract":"<p><strong>Background: </strong>DNA methylation biomarkers are one of the most promising tools for the diagnosis and differentiation of adenocarcinomas of the liver, which are among the most common malignancies worldwide. Their differentiation is important because of the different prognoses and treatment options. This study aimed to validate previously identified DNA methylation biomarkers that successfully differentiate between liver adenocarcinomas, including the two most common primary liver cancers, hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), as well as two common metastatic liver cancers, colorectal liver metastases (CRLM) and pancreatic ductal adenocarcinoma liver metastases (PCLM), and translate them to the methylation-sensitive high-resolution melting (MS-HRM) and digital PCR (dPCR) platforms.</p><p><strong>Methods: </strong>Our study included a cohort of 149 formalin-fixed, paraffin-embedded tissue samples, including 19 CRLMs, 10 PCLMs, 15 HCCs, 15 CCAs, 15 colorectal adenocarcinomas (CRCs), 15 pancreatic ductal adenocarcinomas (PDACs) and their paired normal tissue samples. The methylation status of the samples was experimentally determined by MS-HRM and methylation-specific dPCR. Previously determined methylation threshold were adjusted according to dPCR data and applied to the same DNA methylation array datasets (provided by The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO)) used to originally identify the biomarkers for the included cancer types and additional CRLM projects. The sensitivities, specificities and diagnostic accuracies of the panels for individual cancer types were calculated.</p><p><strong>Results: </strong>In the dPCR experiment, the DNA methylation panels identified HCC, CCA, CRC, PDAC, CRLM and PCLM with sensitivities of 100%, 66.7%, 100%, 86.7%, 94.7% and 80%, respectively. The panels differentiate between HCC, CCA, CRLM, PCLM and healthy liver tissue with specificities of 100%, 100%, 97.1% and 94.9% and with diagnostic accuracies of 100%, 94%, 97% and 93%, respectively. Reevaluation of the same bioinformatic data with new additional CRLM projects demonstrated that the lower dPCR methylation threshold still effectively differentiates between the included cancer types. The bioinformatic data achieved sensitivities for HCC, CCA, CRC, PDAC, CRLM and PCLM of 88%, 64%, 97.4%, 75.5%, 80% and 84.6%, respectively. Specificities between HCC, CCA, CRLM, PCLM and healthy liver tissue were 98%, 93%, 86.6% and 98.2% and the diagnostic accuracies were 94%, 91%, 86% and 98%, respectively. Moreover, we confirmed that the methylation of the investigated promoters is preserved from primary CRC and PDAC to their liver metastases.</p><p><strong>Conclusions: </strong>The cancer-specific methylation biomarker panels exhibit high sensitivities, specificities and diagnostic accuracies and enable differentiation between primary and metastatic adenocarcinomas of the liver using methylation-specific dPCR. High","PeriodicalId":10366,"journal":{"name":"Clinical Epigenetics","volume":"16 1","pages":"153"},"PeriodicalIF":4.8,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11536859/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142575425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-02DOI: 10.1186/s13148-024-01763-2
Junyu Chen, Qin Hui, Boghuma K Titanji, Kaku So-Armah, Matthew Freiberg, Amy C Justice, Ke Xu, Xiaofeng Zhu, Marta Gwinn, Vincent C Marconi, Yan V Sun
Inflammation underlies many conditions causing excess morbidity and mortality among people with HIV (PWH). A handful of single-trait epigenome-wide association studies (EWAS) have suggested that inflammation is associated with DNA methylation (DNAm) among PWH. Multi-trait EWAS may further improve statistical power and reveal pathways in common between different inflammatory markers. We conducted single-trait EWAS of three inflammatory markers (soluble CD14, D-dimers and interleukin-6) in the Veterans Aging Cohort Study (n = 920). The study population was all male PWH with an average age of 51 years, and 82.3% self-reported as Black. We then applied two multi-trait EWAS methods-CPASSOC and OmniTest-to combine single-trait EWAS results. CPASSOC and OmniTest identified 189 and 157 inflammation-associated DNAm sites, respectively, of which 112 overlapped. Among the identified sites, 56% were not significant in any single-trait EWAS. Top sites were mapped to inflammation-related genes including IFITM1, PARP9 and STAT1. These genes were significantly enriched in pathways such as "type I interferon signaling" and "immune response to virus." We demonstrate that multi-trait EWAS can improve the discovery of inflammation-associated DNAm sites, genes and pathways. These DNAm sites might hold the key to addressing persistent inflammation in PWH.
{"title":"A multi-trait epigenome-wide association study identified DNA methylation signature of inflammation among men with HIV.","authors":"Junyu Chen, Qin Hui, Boghuma K Titanji, Kaku So-Armah, Matthew Freiberg, Amy C Justice, Ke Xu, Xiaofeng Zhu, Marta Gwinn, Vincent C Marconi, Yan V Sun","doi":"10.1186/s13148-024-01763-2","DOIUrl":"10.1186/s13148-024-01763-2","url":null,"abstract":"<p><p>Inflammation underlies many conditions causing excess morbidity and mortality among people with HIV (PWH). A handful of single-trait epigenome-wide association studies (EWAS) have suggested that inflammation is associated with DNA methylation (DNAm) among PWH. Multi-trait EWAS may further improve statistical power and reveal pathways in common between different inflammatory markers. We conducted single-trait EWAS of three inflammatory markers (soluble CD14, D-dimers and interleukin-6) in the Veterans Aging Cohort Study (n = 920). The study population was all male PWH with an average age of 51 years, and 82.3% self-reported as Black. We then applied two multi-trait EWAS methods-CPASSOC and OmniTest-to combine single-trait EWAS results. CPASSOC and OmniTest identified 189 and 157 inflammation-associated DNAm sites, respectively, of which 112 overlapped. Among the identified sites, 56% were not significant in any single-trait EWAS. Top sites were mapped to inflammation-related genes including IFITM1, PARP9 and STAT1. These genes were significantly enriched in pathways such as \"type I interferon signaling\" and \"immune response to virus.\" We demonstrate that multi-trait EWAS can improve the discovery of inflammation-associated DNAm sites, genes and pathways. These DNAm sites might hold the key to addressing persistent inflammation in PWH.</p>","PeriodicalId":10366,"journal":{"name":"Clinical Epigenetics","volume":"16 1","pages":"152"},"PeriodicalIF":4.8,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11531128/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142564061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}