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Xing F, Han F, Wu Y, Lv B, Tian H, Wang W, Tian X, Xu C, Duan H, Zhang D, Wu Y. An epigenome-wide association study of waist circumference in Chinese monozygotic twins. Int J Obes (Lond) 2024; 48:1148-1156. [PMID: 38773251 DOI: 10.1038/s41366-024-01538-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 05/05/2024] [Accepted: 05/09/2024] [Indexed: 05/23/2024]
Abstract
OBJECTIVES Central obesity poses significant health risks because it increases susceptibility to multiple chronic diseases. Epigenetic features such as DNA methylation may be associated with specific obesity traits, which could help us understand how genetic and environmental factors interact to influence the development of obesity. This study aims to identify DNA methylation sites associated with the waist circumference (WC) in Northern Han Chinese population, and to elucidate potential causal relationships. METHODS A total of 59 pairs of WC discordant monozygotic twins (ΔWC >0) were selected from the Qingdao Twin Registry in China. Generalized estimated equation model was employed to estimate the methylation levels of CpG sites on WC. Causal relationships between methylation and WC were assessed through the examination of family confounding factors using FAmiliaL CONfounding (ICE FALCON). Additionally, the findings of the epigenome-wide analysis were corroborated in the validation stage. RESULTS We identified 26 CpG sites with differential methylation reached false discovery rate (FDR) < 0.05 and 22 differentially methylated regions (slk-corrected p < 0.05) strongly linked to WC. These findings provided annotations for 26 genes, with notable emphasis on MMP17, ITGA11, COL23A1, TFPI, A2ML1-AS1, MRGPRE, C2orf82, and NINJ2. ICE FALCON analysis indicated the DNA methylation of ITGA11 and TFPI had a causal effect on WC and vice versa (p < 0.05). Subsequent validation analysis successfully replicated 10 (p < 0.05) out of the 26 identified sites. CONCLUSIONS Our research has ascertained an association between specific epigenetic variations and WC in the Northern Han Chinese population. These DNA methylation features can offer fresh insights into the epigenetic regulation of obesity and WC as well as hints to plausible biological mechanisms.
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Affiliation(s)
- Fangjie Xing
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Fulei Han
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Yan Wu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Bosen Lv
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Huimin Tian
- Zhonglou District Center for Disease Control and Prevention, Changzhou, Jiangsu, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Yili Wu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China.
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Liu J, Wang W, Luo J, Duan H, Xu C, Tian X, Chen S, Ge L, Zhang D. Mediation role of DNA methylation in association between handgrip strength and cognitive function in monozygotic twins. J Hum Genet 2024; 69:357-363. [PMID: 38649436 DOI: 10.1038/s10038-024-01247-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 03/19/2024] [Accepted: 03/20/2024] [Indexed: 04/25/2024]
Abstract
Handgrip strength is a crucial indicator to monitor the change of cognitive function over time, but its mechanism still needs to be further explored. We sampled 59 monozygotic twin pairs to explore the potential mediating effect of DNA methylation (DNAm) on the association between handgrip strength and cognitive function. The initial step was the implementation of an epigenome-wide association analysis (EWAS) in the study participants, with the aim of identifying DNAm variations that are associated with handgrip strength. Following that, we conducted an assessment of the mediated effect of DNAm by the use of mediation analysis. In order to do an ontology enrichment study for CpGs, the GREAT program was used. There was a significant positive association between handgrip strength and cognitive function (β = 0.194, P < 0.001). The association between handgrip strength and DNAm of 124 CpGs was found to be statistically significant at a significance level of P < 1 × 10-4. Fifteen differentially methylated regions (DMRs) related to handgrip strength were found in genes such as SNTG2, KLB, CDH11, and PANX2. Of the 124 CpGs, 4 within KRBA1, and TRAK1 mediated the association between handgrip strength and cognitive function: each 1 kg increase in handgrip strength was associated with a potential decrease of 0.050 points in cognitive function scores, mediated by modifications in DNAm. The parallel mediating effect of these 4 CpGs was -0.081. The presence of DNAm variation associated with handgrip strength may play a mediated role in the association between handgrip strength and cognitive function.
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Affiliation(s)
- Jin Liu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China
| | - Jia Luo
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Shumin Chen
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China
| | - Lin Ge
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China.
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Chen YC, Liaw YC, Nfor ON, Hsiao CH, Zhong JH, Wu SL, Liaw YP. Epigenetic associations of GPNMB rs199347 variant with alcohol consumption in Parkinson's disease. Front Psychiatry 2024; 15:1377403. [PMID: 39091454 PMCID: PMC11293056 DOI: 10.3389/fpsyt.2024.1377403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 06/27/2024] [Indexed: 08/04/2024] Open
Abstract
Introduction Alcohol consumption can induce a neuroinflammatory response and contribute to the progression of neurodegeneration. However, its association with Parkinson's disease (PD), the second most common neurodegenerative disorder, remains undetermined. Recent studies suggest that the glycoprotein non-metastatic melanoma protein B (GPNMB) is a potential biomarker for PD. We evaluated the association of rs199347, a variant of the GPNMB gene, with alcohol consumption and methylation upstream of GPNMB. Methods We retrieved genetic and DNA methylation data obtained from participants enrolled in the Taiwan Biobank (TWB) between 2008 and 2016. After excluding individuals with incomplete or missing information about potential PD risk factors, we included 1,357 participants in our final analyses. We used multiple linear regression to assess the association of GPNMB rs199347 and chronic alcohol consumption (and other potential risk factors) with GPNMB cg17274742 methylation. Results There was no difference between the distribution of GPNMB rs199347 genotypes between chronic alcohol consumers and the other study participants. A significant interaction was observed between the GPNMB rs199347 variant and alcohol consumption (p = 0.0102) concerning cg17274742 methylation. Compared to non-chronic alcohol consumers with the AA genotype, alcohol drinkers with the rs199347 GG genotype had significantly lower levels (hypomethylation) of cg17274742 (p = 0.0187). Conclusion Alcohol consumption among individuals with the rs199347 GG genotype was associated with lower levels of cg17274742 methylation, which could increase expression of the GPNMB gene, an important neuroinflammatory-related risk gene for PD.
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Affiliation(s)
- Yen-Chung Chen
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
- Department of Neurology, Changhua Christian Hospital, Changhua, Taiwan
| | - Yi-Chia Liaw
- Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Oswald Ndi Nfor
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
| | - Chih-Hsuan Hsiao
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
| | - Ji-Han Zhong
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
| | - Shey-Lin Wu
- Department of Neurology, Changhua Christian Hospital, Changhua, Taiwan
- Department of Electrical Engineering, National Changhua University of Education, Changhua, Taiwan
| | - Yung-Po Liaw
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan
- Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan
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Sayer M, Ng DQ, Chan R, Kober K, Chan A. Current evidence supporting associations of DNA methylation measurements with survivorship burdens in cancer survivors: A scoping review. Cancer Med 2024; 13:e7470. [PMID: 38963018 PMCID: PMC11222976 DOI: 10.1002/cam4.7470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 05/27/2024] [Accepted: 06/27/2024] [Indexed: 07/05/2024] Open
Abstract
INTRODUCTION Identifying reliable biomarkers that reflect cancer survivorship symptoms remains a challenge for researchers. DNA methylation (DNAm) measurements reflecting epigenetic changes caused by anti-cancer therapy may provide needed insights. Given lack of consensus describing utilization of DNAm data to predict survivorship issues, a review evaluating the current landscape is warranted. OBJECTIVE Provide an overview of current studies examining associations of DNAm with survivorship burdens in cancer survivors. METHODS A literature review was conducted including studies if they focused on cohorts of cancer survivors, utilized peripheral blood cell DNAm data, and evaluated the associations of DNAm and survivorship issues. RESULTS A total of 22 studies were identified, with majority focused on breast (n = 7) or childhood cancer (n = 9) survivors, and half studies included less than 100 patients (n = 11). Survivorship issues evaluated included those related to neurocognition (n = 5), psychiatric health (n = 3), general wellness (n = 9), chronic conditions (n = 5), and treatment specific toxicities (n = 4). Studies evaluated epigenetic age metrics (n = 10) and DNAm levels at individual CpG sites or regions (n = 12) for their associations with survivorship issues in cancer survivors along with relevant confounding factors. Significant associations of measured DNAm in the peripheral blood samples of cancer survivors and survivorship issues were identified. DISCUSSION/CONCLUSION Studies utilizing epigenetic age metrics and differential methylation analysis demonstrated significant associations of DNAm measurements with survivorship burdens. Associations were observed encompassing diverse survivorship outcomes and timeframes relative to anti-cancer therapy initiation. These findings underscore the potential of these measurements as useful biomarkers in survivorship care and research.
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Affiliation(s)
- Michael Sayer
- School of Pharmacy and Pharmaceutical SciencesUniversity of California IrvineIrvineCaliforniaUSA
| | - Ding Quan Ng
- School of Pharmacy and Pharmaceutical SciencesUniversity of California IrvineIrvineCaliforniaUSA
| | - Raymond Chan
- School of Nursing and Health SciencesFlinders UniversityAdelaideSouth AustraliaAustralia
| | - Kord Kober
- School of NursingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Alexandre Chan
- School of Pharmacy and Pharmaceutical SciencesUniversity of California IrvineIrvineCaliforniaUSA
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Yap CX, Vo DD, Heffel MG, Bhattacharya A, Wen C, Yang Y, Kemper KE, Zeng J, Zheng Z, Zhu Z, Hannon E, Vellame DS, Franklin A, Caggiano C, Wamsley B, Geschwind DH, Zaitlen N, Gusev A, Pasaniuc B, Mill J, Luo C, Gandal MJ. Brain cell-type shifts in Alzheimer's disease, autism, and schizophrenia interrogated using methylomics and genetics. SCIENCE ADVANCES 2024; 10:eadn7655. [PMID: 38781333 PMCID: PMC11114225 DOI: 10.1126/sciadv.adn7655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 03/14/2024] [Indexed: 05/25/2024]
Abstract
Few neuropsychiatric disorders have replicable biomarkers, prompting high-resolution and large-scale molecular studies. However, we still lack consensus on a more foundational question: whether quantitative shifts in cell types-the functional unit of life-contribute to neuropsychiatric disorders. Leveraging advances in human brain single-cell methylomics, we deconvolve seven major cell types using bulk DNA methylation profiling across 1270 postmortem brains, including from individuals diagnosed with Alzheimer's disease, schizophrenia, and autism. We observe and replicate cell-type compositional shifts for Alzheimer's disease (endothelial cell loss), autism (increased microglia), and schizophrenia (decreased oligodendrocytes), and find age- and sex-related changes. Multiple layers of evidence indicate that endothelial cell loss contributes to Alzheimer's disease, with comparable effect size to APOE genotype among older people. Genome-wide association identified five genetic loci related to cell-type composition, involving plausible genes for the neurovascular unit (P2RX5 and TRPV3) and excitatory neurons (DPY30 and MEMO1). These results implicate specific cell-type shifts in the pathophysiology of neuropsychiatric disorders.
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Affiliation(s)
- Chloe X. Yap
- Mater Research Institute, University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel D. Vo
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Lifespan Brain Institute at Penn Medicine and The Children’s Hospital of Philadelphia, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew G. Heffel
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Institute for Data Science in Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Cindy Wen
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Yuanhao Yang
- Mater Research Institute, University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Kathryn E. Kemper
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Jian Zeng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Zhihong Zhu
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- The National Centre for Register-based Research, Aarhus University, Denmark
| | - Eilis Hannon
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Dorothea Seiler Vellame
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Alice Franklin
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Christa Caggiano
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
| | - Brie Wamsley
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel H. Geschwind
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, Los Angeles, CA, USA
| | - Noah Zaitlen
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Alexander Gusev
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham & Women’s Hospital, Boston, MA, USA
- Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Bogdan Pasaniuc
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jonathan Mill
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Chongyuan Luo
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Michael J. Gandal
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Lifespan Brain Institute at Penn Medicine and The Children’s Hospital of Philadelphia, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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6
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Nguyen H, Nguyen H, Tran D, Draghici S, Nguyen T. Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges. Nucleic Acids Res 2024; 52:4761-4783. [PMID: 38619038 PMCID: PMC11109966 DOI: 10.1093/nar/gkae267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 03/01/2024] [Accepted: 04/02/2024] [Indexed: 04/16/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-Seq) is a recent technology that allows for the measurement of the expression of all genes in each individual cell contained in a sample. Information at the single-cell level has been shown to be extremely useful in many areas. However, performing single-cell experiments is expensive. Although cellular deconvolution cannot provide the same comprehensive information as single-cell experiments, it can extract cell-type information from bulk RNA data, and therefore it allows researchers to conduct studies at cell-type resolution from existing bulk datasets. For these reasons, a great effort has been made to develop such methods for cellular deconvolution. The large number of methods available, the requirement of coding skills, inadequate documentation, and lack of performance assessment all make it extremely difficult for life scientists to choose a suitable method for their experiment. This paper aims to fill this gap by providing a comprehensive review of 53 deconvolution methods regarding their methodology, applications, performance, and outstanding challenges. More importantly, the article presents a benchmarking of all these 53 methods using 283 cell types from 30 tissues of 63 individuals. We also provide an R package named DeconBenchmark that allows readers to execute and benchmark the reviewed methods (https://github.com/tinnlab/DeconBenchmark).
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Affiliation(s)
- Hung Nguyen
- Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA
| | - Ha Nguyen
- Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA
| | - Duc Tran
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Sorin Draghici
- Department of Computer Science, Wayne State University, Detroit, MI, USA
- Advaita Bioinformatics, Ann Arbor, MI, USA
| | - Tin Nguyen
- Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA
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7
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Lee MK, Azizgolshani N, Zhang Z, Perreard L, Kolling FW, Nguyen LN, Zanazzi GJ, Salas LA, Christensen BC. Associations in cell type-specific hydroxymethylation and transcriptional alterations of pediatric central nervous system tumors. Nat Commun 2024; 15:3635. [PMID: 38688903 PMCID: PMC11061294 DOI: 10.1038/s41467-024-47943-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 04/16/2024] [Indexed: 05/02/2024] Open
Abstract
Although intratumoral heterogeneity has been established in pediatric central nervous system tumors, epigenomic alterations at the cell type level have largely remained unresolved. To identify cell type-specific alterations to cytosine modifications in pediatric central nervous system tumors, we utilize a multi-omic approach that integrated bulk DNA cytosine modification data (methylation and hydroxymethylation) with both bulk and single-cell RNA-sequencing data. We demonstrate a large reduction in the scope of significantly differentially modified cytosines in tumors when accounting for tumor cell type composition. In the progenitor-like cell types of tumors, we identify a preponderance differential Cytosine-phosphate-Guanine site hydroxymethylation rather than methylation. Genes with differential hydroxymethylation, like histone deacetylase 4 and insulin-like growth factor 1 receptor, are associated with cell type-specific changes in gene expression in tumors. Our results highlight the importance of epigenomic alterations in the progenitor-like cell types and its role in cell type-specific transcriptional regulation in pediatric central nervous system tumors.
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Affiliation(s)
- Min Kyung Lee
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
| | - Nasim Azizgolshani
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- Department of Surgery, Columbia University Medical Center, New York, NY, USA
| | - Ze Zhang
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Laurent Perreard
- Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Fred W Kolling
- Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Lananh N Nguyen
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - George J Zanazzi
- Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- Department of Pathology and Laboratory Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
- Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
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8
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Lee HS, Kim B, Park T. Genome- and epigenome-wide association studies identify susceptibility of CpG sites and regions for metabolic syndrome in a Korean population. Clin Epigenetics 2024; 16:60. [PMID: 38685121 PMCID: PMC11059751 DOI: 10.1186/s13148-024-01671-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 04/13/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND While multiple studies have investigated the relationship between metabolic syndrome (MetS) and its related traits (fasting glucose, triglyceride, HDL cholesterol, blood pressure, waist circumference) and DNA methylation, our understanding of the epigenetic mechanisms in MetS remains limited. Therefore, we performed an epigenome-wide meta-analysis of blood DNA methylation to identify differentially methylated probes (DMPs) and differentially methylated regions (DMRs) associated with MetS and its components using two independent cohorts comprising a total of 2,334 participants. We also investigated the specific genetic effects on DNA methylation, identified methylation quantitative trait loci (meQTLs) through genome-wide association studies and further utilized Mendelian randomization (MR) to assess how these meQTLs subsequently influence MetS status. RESULTS We identified 40 DMPs and 27 DMRs that are significantly associated with MetS. In addition, we identified many novel DMPs and DMRs underlying inflammatory and steroid hormonal processes. The most significant associations were observed in 3 DMPs (cg19693031, cg26974062, cg02988288) and a DMR (chr1:145440444-145441553) at the TXNIP, which are involved in lipid metabolism. These CpG sites were identified as coregulators of DNA methylation in MetS, TG and FAG levels. We identified a total of 144 cis-meQTLs, out of which only 13 were found to be associated with DMPs for MetS. Among these, we confirmed the identified causal mediators of genetic effects at CpG sites cg01881899 at ABCG1 and cg00021659 at the TANK genes for MetS. CONCLUSIONS This study observed whether specific CpGs and methylated regions act independently or are influenced by genetic effects for MetS and its components in the Korean population. These associations between the identified DNA methylation and MetS, along with its individual components, may serve as promising targets for the development of preventive interventions for MetS.
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Affiliation(s)
- Ho-Sun Lee
- Forensic Toxicology Division, Daegu Institute, National Forensic Service, Chilgok-gun, 39872, Gyeongsangbuk-do, Korea.
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea.
| | - Boram Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea
| | - Taesung Park
- Forensic Toxicology Division, Daegu Institute, National Forensic Service, Chilgok-gun, 39872, Gyeongsangbuk-do, Korea
- Department of Statistics, Seoul National University, Seoul, 08826, Korea
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9
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Pan Y, Wang X, Sun J, Liu C, Peng J, Li Q. Multimodal joint deconvolution and integrative signature selection in proteomics. Commun Biol 2024; 7:493. [PMID: 38658803 PMCID: PMC11043077 DOI: 10.1038/s42003-024-06155-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 04/08/2024] [Indexed: 04/26/2024] Open
Abstract
Deconvolution is an efficient approach for detecting cell-type-specific (cs) transcriptomic signals without cellular segmentation. However, this type of methods may require a reference profile from the same molecular source and tissue type. Here, we present a method to dissect bulk proteome by leveraging tissue-matched transcriptome and proteome without using a proteomics reference panel. Our method also selects the proteins contributing to the cellular heterogeneity shared between bulk transcriptome and proteome. The deconvoluted result enables downstream analyses such as cs-protein Quantitative Trait Loci (cspQTL) mapping. We benchmarked the performance of this multimodal deconvolution approach through CITE-seq pseudo bulk data, a simulation study, and the bulk multi-omics data from human brain normal tissues and breast cancer tumors, individually, showing robust and accurate cell abundance quantification across different datasets. This algorithm is implemented in a tool MICSQTL that also provides cspQTL and multi-omics integrative visualization, available at https://bioconductor.org/packages/MICSQTL .
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Affiliation(s)
- Yue Pan
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Xusheng Wang
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Genetics, Genomics & Informatics, University of Tennessee Health Science Center, Memphis, TN, 38105, USA
| | - Jiao Sun
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Chunyu Liu
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, 13210, USA
| | - Junmin Peng
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Qian Li
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
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Luo J, Wang W, Li J, Duan H, Xu C, Tian X, Zhang D. Epigenome-wide association study identifies DNA methylation loci associated with handgrip strength in Chinese monozygotic twins. Front Cell Dev Biol 2024; 12:1378680. [PMID: 38633108 PMCID: PMC11021642 DOI: 10.3389/fcell.2024.1378680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 03/22/2024] [Indexed: 04/19/2024] Open
Abstract
Background: The decline in muscle strength and function with aging is well recognized, but remains poorly characterized at the molecular level. Here, we report the epigenetic relationship between genome-wide DNA methylation and handgrip strength (HGS) among Chinese monozygotic (MZ) twins. Methods: DNA methylation (DNAm) profiling was conducted in whole blood samples through Reduced Representation Bisulfite Sequencing method. Generalized estimating equation was applied to regress the DNAm of each CpG with HGS. The Genomic Regions Enrichment of Annotations Tool was used to perform enrichment analysis. Differentially methylated regions (DMRs) were detected using comb-p. Causal inference was performed using Inference about Causation through Examination of Familial Confounding method. Finally, we validated candidate CpGs in community residents. Results: We identified 25 CpGs reaching genome-wide significance level. These CpGs located in 9 genes, especially FBLN1, RXRA, and ABHD14B. Many enriched terms highlighted calcium channels, neuromuscular junctions, and skeletal muscle organ development. We identified 21 DMRs of HGS, with several DMRs within FBLN1, SLC30A8, CST3, and SOCS3. Causal inference indicated that the DNAm of 16 top CpGs within FBLN1, RXRA, ABHD14B, MFSD6, and TYW1B might influence HGS, while HGS influenced DNAm at two CpGs within FBLN1 and RXRA. In validation analysis, methylation levels of six CpGs mapped to FLBN1 and one CpG mapped to ABHD14B were negatively associated with HGS weakness in community population. Conclusion: Our study identified multiple DNAm variants potentially related to HGS, especially CpGs within FBLN1 and ABHD14B. These findings provide new clues to the epigenetic modification underlying muscle strength decline.
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Affiliation(s)
- Jia Luo
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, Shandong, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, Shandong, China
| | - Jingxian Li
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, Shandong, China
| | - Haiping Duan
- Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong, China
- Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Chunsheng Xu
- Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong, China
- Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Xiaocao Tian
- Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong, China
- Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, Shandong, China
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Ferro dos Santos MR, Giuili E, De Koker A, Everaert C, De Preter K. Computational deconvolution of DNA methylation data from mixed DNA samples. Brief Bioinform 2024; 25:bbae234. [PMID: 38762790 PMCID: PMC11102637 DOI: 10.1093/bib/bbae234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 03/30/2024] [Accepted: 04/30/2024] [Indexed: 05/20/2024] Open
Abstract
In this review, we provide a comprehensive overview of the different computational tools that have been published for the deconvolution of bulk DNA methylation (DNAm) data. Here, deconvolution refers to the estimation of cell-type proportions that constitute a mixed sample. The paper reviews and compares 25 deconvolution methods (supervised, unsupervised or hybrid) developed between 2012 and 2023 and compares the strengths and limitations of each approach. Moreover, in this study, we describe the impact of the platform used for the generation of methylation data (including microarrays and sequencing), the applied data pre-processing steps and the used reference dataset on the deconvolution performance. Next to reference-based methods, we also examine methods that require only partial reference datasets or require no reference set at all. In this review, we provide guidelines for the use of specific methods dependent on the DNA methylation data type and data availability.
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Affiliation(s)
- Maísa R Ferro dos Santos
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Edoardo Giuili
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Andries De Koker
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Celine Everaert
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Katleen De Preter
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
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12
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Li Z, Wang W, Li W, Duan H, Xu C, Tian X, Ning F, Zhang D. Co-methylation analyses identify CpGs associated with lipid traits in Chinese discordant monozygotic twins. Hum Mol Genet 2024; 33:583-593. [PMID: 38142287 DOI: 10.1093/hmg/ddad207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/29/2023] [Accepted: 12/05/2023] [Indexed: 12/25/2023] Open
Abstract
To control genetic background and early life milieu in genome-wide DNA methylation analysis for blood lipids, we recruited Chinese discordant monozygotic twins to explore the relationships between DNA methylations and total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). 132 monozygotic (MZ) twins were included with discordant lipid levels and completed data. A linear mixed model was conducted in Epigenome-wide association study (EWAS). Generalized estimating equation model was for gene expression analysis. We conducted Weighted correlation network analysis (WGCNA) to build co-methylated interconnected network. Additional Qingdao citizens were recruited for validation. Inference about Causation through Examination of Familial Confounding (ICE FALCON) was used to infer the possible direction of these relationships. A total of 476 top CpGs reached suggestively significant level (P < 10-4), of which, 192 CpGs were significantly associated with TG (FDR < 0.05). They were used to build interconnected network and highlight crucial genes from WGCNA. Finally, four CpGs in GATA4 were validated as risk factors for TC; six CpGs at ITFG2-AS1 were negatively associated with TG; two CpGs in PLXND1 played protective roles in HDL-C. ICE FALCON indicated abnormal TC was regarded as the consequence of DNA methylation in CpGs at GATA4, rather than vice versa. Four CpGs in ITFG2-AS1 were both causes and consequences of modified TG levels. Our results indicated that DNA methylation levels of 12 CpGs in GATA4, ITFG2-AS1, and PLXND1 were relevant to TC, TG, and HDL-C, respectively, which might provide new epigenetic insights into potential clinical treatment of dyslipidemia.
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Affiliation(s)
- Zhaoying Li
- Department of Epidemiology and Health Statistics, The College of Public Health of Qingdao University, No. 308 Ning Xia Street, Qingdao 266071, Shandong Province, People's Republic of China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, The College of Public Health of Qingdao University, No. 308 Ning Xia Street, Qingdao 266071, Shandong Province, People's Republic of China
| | - Weilong Li
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, J.B. Winsløws Vej 9 B, st. tv. Odense C DK-5000, Denmark
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
- Qingdao Institute of Preventive Medicine, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
- Qingdao Institute of Preventive Medicine, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
- Qingdao Institute of Preventive Medicine, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
| | - Feng Ning
- Qingdao Municipal Center for Disease Control and Prevention, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
- Qingdao Institute of Preventive Medicine, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, The College of Public Health of Qingdao University, No. 308 Ning Xia Street, Qingdao 266071, Shandong Province, People's Republic of China
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Yao J, Ning F, Wang W, Zhang D. DNA Methylation Mediated the Association of Body Mass Index With Blood Pressure in Chinese Monozygotic Twins. Twin Res Hum Genet 2024; 27:18-29. [PMID: 38291711 DOI: 10.1017/thg.2024.3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Obesity is an established risk factor for hypertension, but the mechanisms are only partially understood. We examined whether body mass index (BMI)-related DNA methylation (DNAm) variation would mediate the association of BMI with blood pressure (BP). We first conducted a genomewide DNA methylation analysis in monozygotic twin pairs to detect BMI-related DNAm variation and then evaluated the mediating effect of DNAm on the relationship between BMI and BP levels using the causal inference test (CIT) method and mediation analysis. Ontology enrichment analysis was performed for CpGs using the GREAT tool. A total of 60 twin pairs for BMI and systolic blood pressure (SBP) and 58 twin pairs for BMI and diastolic blood pressure (DBP) were included. BMI was positively associated with SBP (β = 1.86, p = .0004). The association between BMI and DNAm of 85 CpGs reached p < 1×10-4 level. Eleven BMI-related differentially methylated regions (DMRs) within LNCPRESS1, OGDHL, RNU1-44P, NPHS1, ECEL1P2, LLGL2, RNY4P15, MOGAT3, PHACTR3, and BAI2 were found. Of the 85 CpGs, 9 mapped to C10orf71-AS1, NDUFB5P1, KRT80, BAI2, ABCA2, PEX11G and FGF4 were significantly associated with SBP levels. Of the 9 CpGs, 2 within ABCA2 negatively mediated the association between BMI and SBP, with a mediating effect of -0.24 (95% CI [-0.65, -0.01]). BMI was also positively associated with DBP (β = 0.60, p = .0495). The association between BMI and DNAm of 193 CpGs reached p < 1×10-4 level. Twenty-five BMI-related DMRs within OGDHL, POU4F2, ECEL1P2, TTC6, SMPD4, EP400, TUBA1C and AGAP2 were found. Of the 193 CpGs, 33 mapped to ABCA2, ADORA2B, CTNNBIP1, KDM4B, NAA60, RSPH6A, SLC25A19 and STIL were significantly associated with DBP levels. Of the 33 CpGs, 12 within ABCA2, SLC25A19, KDM4B, PTPRN2, DNASE1, TFCP2L1, LMNB2 and C10orf71-AS1 negatively mediated the association between BMI and DBP, with a total mediation effect of -0.66 (95% CI [-1.07, -0.30]). Interestingly, BMI might also negatively mediate the association between the DNAm of most CpG mediators mentioned above and BP. The mediating effect of DNAm was also found when stratified by sex. In conclusion, DNAm variation may partially negatively mediate the association of BMI with BP. Our findings may provide new clues to further elucidate the pathogenesis of obesity to hypertension and identify new diagnostic biomarkers and therapeutic targets for hypertension.
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Affiliation(s)
- Jie Yao
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China
- Jiangsu Health Development Research Center, Nanjing, Jiangsu Province, China
| | - Feng Ning
- Qingdao Centers for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, Shandong, China
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14
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Wang C, Wang J, Chen S, Li K, Wan S, Yang L. COL10A1 as a Prognostic Biomarker in Association with Immune Infiltration in Prostate Cancer. Curr Cancer Drug Targets 2024; 24:340-353. [PMID: 37592784 DOI: 10.2174/1568009623666230817101809] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 03/19/2023] [Accepted: 06/06/2023] [Indexed: 08/19/2023]
Abstract
BACKGROUND The collagen type X alpha 1 (COL10A1) has recently been found to play an important role in the development and progression of cancer. However, the link between COL10A1 and the tumor immune microenvironment remains understood scantily. METHODS In the current study, the pan-cancer data of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were used to investigate the expression mode, the clinical prognostic and diagnostic value of COL10A1 in different tumors. We used TCGA data to assess the correlations between COL10A1 and clinical symptoms of prostate cancer. The R packages "edgR" and "clusterProfiler" were used for differential expression gene and enrichment analysis of COL10A1. Immunohistochemistry was further employed to corroborate the expression of COL10A1 gene in prostate cancer. After that, we used TIMER to evaluate the pertinence of COL10A1 expression to immune infiltration level in prostate cancer. RESULTS On the whole, COL10A1 was expressed at significantly higher levels in a variety of tumor tissues than in the corresponding normal tissues. Besides, significant correlations with tumor prognosis and relative exactitude in predicting tumors show that COL10A1 may be a probable prognostic and diagnostic biomarker of prostate cancer. In addition, the evidence indicates a significant correlation between COL10A1 and clinical symptoms of prostate cancer. Furthermore, the main molecular functions of COL10A1 included humoral immune response, complement activation, immunoglobulin, regulation of complement activation, and regulation of humoral immune response. Finally, we found that COL10A1 expression is positively correlated with enhanced macrophage and M2 macrophage infiltration in prostate cancer. CONCLUSION The study indicates that COL10A1 might participate in M2 macrophage polarization in prostate cancer. COL10A1 might be an innovative biomarker to evaluate tumor microenvironment immune cell infiltration and prognosis in prostate cancer.
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Affiliation(s)
- Chenyang Wang
- Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, China
- Gansu Province Clinical Research Center for Urology, Lanzhou, China
| | - Jirong Wang
- Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, China
- Gansu Province Clinical Research Center for Urology, Lanzhou, China
| | - Siyu Chen
- Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, China
- Gansu Province Clinical Research Center for Urology, Lanzhou, China
| | - Kunpeng Li
- Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, China
- Gansu Province Clinical Research Center for Urology, Lanzhou, China
| | - Shun Wan
- Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, China
- Gansu Province Clinical Research Center for Urology, Lanzhou, China
| | - Li Yang
- Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, China
- Gansu Province Clinical Research Center for Urology, Lanzhou, China
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15
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Zeng Y, Jain R, Lam M, Ahmed M, Guo H, Xu W, Zhong Y, Wei GH, Xu W, He HH. DNA methylation modulated genetic variant effect on gene transcriptional regulation. Genome Biol 2023; 24:285. [PMID: 38066556 PMCID: PMC10709945 DOI: 10.1186/s13059-023-03130-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 11/28/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Expression quantitative trait locus (eQTL) analysis has emerged as an important tool in elucidating the link between genetic variants and gene expression, thereby bridging the gap between risk SNPs and associated diseases. We recently identified and validated a specific case where the methylation of a CpG site influences the relationship between the genetic variant and gene expression. RESULTS Here, to systematically evaluate this regulatory mechanism, we develop an extended eQTL mapping method, termed DNA methylation modulated eQTL (memo-eQTL). Applying this memo-eQTL mapping method to 128 normal prostate samples enables identification of 1063 memo-eQTLs, the majority of which are not recognized as conventional eQTLs in the same cohort. We observe that the methylation of the memo-eQTL CpG sites can either enhance or insulate the interaction between SNP and gene expression by altering CTCF-based chromatin 3D structure. CONCLUSIONS This study demonstrates the prevalence of memo-eQTLs paving the way to identify novel causal genes for traits or diseases associated with genetic variations.
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Affiliation(s)
- Yong Zeng
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada.
| | - Rahi Jain
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Magnus Lam
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Musaddeque Ahmed
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Haiyang Guo
- Department of Clinical Laboratory, the Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250033, Shandong, China
| | - Wenjie Xu
- MOE Key Laboratory of Metabolism and Molecular Medicine and Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, Fudan University Shanghai Cancer Center, Shanghai Medical College of Fudan University, Shanghai, China
| | - Yuan Zhong
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Gong-Hong Wei
- MOE Key Laboratory of Metabolism and Molecular Medicine and Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, Fudan University Shanghai Cancer Center, Shanghai Medical College of Fudan University, Shanghai, China
- Biocenter Oulu & Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu, Finland
| | - Wei Xu
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
| | - Housheng Hansen He
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada.
- Department of Medical Biophysics, University of Toronto, Toronto, Canada.
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Ng JWY, Felix JF, Olson DM. A novel approach to risk exposure and epigenetics-the use of multidimensional context to gain insights into the early origins of cardiometabolic and neurocognitive health. BMC Med 2023; 21:466. [PMID: 38012757 PMCID: PMC10683259 DOI: 10.1186/s12916-023-03168-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 11/09/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Each mother-child dyad represents a unique combination of genetic and environmental factors. This constellation of variables impacts the expression of countless genes. Numerous studies have uncovered changes in DNA methylation (DNAm), a form of epigenetic regulation, in offspring related to maternal risk factors. How these changes work together to link maternal-child risks to childhood cardiometabolic and neurocognitive traits remains unknown. This question is a key research priority as such traits predispose to future non-communicable diseases (NCDs). We propose viewing risk and the genome through a multidimensional lens to identify common DNAm patterns shared among diverse risk profiles. METHODS We identified multifactorial Maternal Risk Profiles (MRPs) generated from population-based data (n = 15,454, Avon Longitudinal Study of Parents and Children (ALSPAC)). Using cord blood HumanMethylation450 BeadChip data, we identified genome-wide patterns of DNAm that co-vary with these MRPs. We tested the prospective relation of these DNAm patterns (n = 914) to future outcomes using decision tree analysis. We then tested the reproducibility of these patterns in (1) DNAm data at age 7 and 17 years within the same cohort (n = 973 and 974, respectively) and (2) cord DNAm in an independent cohort, the Generation R Study (n = 686). RESULTS We identified twenty MRP-related DNAm patterns at birth in ALSPAC. Four were prospectively related to cardiometabolic and/or neurocognitive childhood outcomes. These patterns were replicated in DNAm data from blood collected at later ages. Three of these patterns were externally validated in cord DNAm data in Generation R. Compared to previous literature, DNAm patterns exhibited novel spatial distribution across the genome that intersects with chromatin functional and tissue-specific signatures. CONCLUSIONS To our knowledge, we are the first to leverage multifactorial population-wide data to detect patterns of variability in DNAm. This context-based approach decreases biases stemming from overreliance on specific samples or variables. We discovered molecular patterns demonstrating prospective and replicable relations to complex traits. Moreover, results suggest that patterns harbour a genome-wide organisation specific to chromatin regulation and target tissues. These preliminary findings warrant further investigation to better reflect the reality of human context in molecular studies of NCDs.
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Affiliation(s)
- Jane W Y Ng
- Department of Pediatrics, Cummings School of Medicine, University of Calgary, 28 Oki Drive NW, Calgary, AB, T3B 6A8, Canada
| | - Janine F Felix
- The Generation F Study Group, Erasmus MC University Medical Center Rotterdam, Postbus, 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - David M Olson
- Departments of Obstetrics and Gynecology, Physiology, and Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, 220 HMRC, Edmonton, AB, T6G2S2, Canada.
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Tian H, Qiao H, Han F, Kong X, Zhu S, Xing F, Duan H, Li W, Wang W, Zhang D, Wu Y. Genome-wide DNA methylation analysis of body composition in Chinese monozygotic twins. Eur J Clin Invest 2023; 53:e14055. [PMID: 37392072 DOI: 10.1111/eci.14055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 06/06/2023] [Accepted: 06/20/2023] [Indexed: 07/02/2023]
Abstract
BACKGROUND Little is currently known about epigenetic alterations associated with body composition in obesity. Thus, we aimed to explore epigenetic relationships between genome-wide DNA methylation levels and three common traits of body composition as measured by body fat percentage (BF%), fat mass (FM) and lean body mass (LBM) among Chinese monozygotic twins. METHODS Generalized estimated equation model was used to regress the methylation level of CpG sites on body composition. Inference about Causation Through Examination Of Familial Confounding was used to explore the evidence of a causal relationship. Gene expression analysis was further performed to validate the results of differentially methylated genes. RESULTS We identified 32, 22 and 28 differentially methylated CpG sites (p < 10-5 ) as well as 20, 17 and eight differentially methylated regions (slk-corrected p < 0.05) significantly associated with BF%, FM and LBM which were annotated to 65 genes, showing partially overlapping. Causal inference demonstrated bidirectional causality between DNA methylation and body composition (p < 0.05). Gene expression analysis revealed significant correlations between expression levels of five differentially methylated genes and body composition (p < 0.05). CONCLUSIONS These DNA methylation signatures will contribute to increased knowledge about the epigenetic basis of body composition and provide new strategies for early prevention and treatment of obesity and its related diseases.
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Affiliation(s)
- Huimin Tian
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Haofei Qiao
- Qingdao Mental Health Centre, Qingdao, China
| | - Fulei Han
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Xiangjie Kong
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Shuai Zhu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Fangjie Xing
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Haiping Duan
- Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, China
| | - Weilong Li
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Yili Wu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
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Perez-Garcia J, Pino-Yanes M, Plender EG, Everman JL, Eng C, Jackson ND, Moore CM, Beckman KB, Medina V, Sharma S, Winnica DE, Holguin F, Rodríguez-Santana J, Villar J, Ziv E, Seibold MA, Burchard EG. Epigenomic response to albuterol treatment in asthma-relevant airway epithelial cells. Clin Epigenetics 2023; 15:156. [PMID: 37784136 PMCID: PMC10546710 DOI: 10.1186/s13148-023-01571-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 09/25/2023] [Indexed: 10/04/2023] Open
Abstract
BACKGROUND Albuterol is the first-line asthma medication used in diverse populations. Although DNA methylation (DNAm) is an epigenetic mechanism involved in asthma and bronchodilator drug response (BDR), no study has assessed whether albuterol could induce changes in the airway epithelial methylome. We aimed to characterize albuterol-induced DNAm changes in airway epithelial cells, and assess potential functional consequences and the influence of genetic variation and asthma-related clinical variables. RESULTS We followed a discovery and validation study design to characterize albuterol-induced DNAm changes in paired airway epithelial cultures stimulated in vitro with albuterol. In the discovery phase, an epigenome-wide association study using paired nasal epithelial cultures from Puerto Rican children (n = 97) identified 22 CpGs genome-wide associated with repeated-use albuterol treatment (p < 9 × 10-8). Albuterol predominantly induced a hypomethylation effect on CpGs captured by the EPIC array across the genome (probability of hypomethylation: 76%, p value = 3.3 × 10-5). DNAm changes on the CpGs cg23032799 (CREB3L1), cg00483640 (MYLK4-LINC01600), and cg05673431 (KSR1) were validated in nasal epithelia from 10 independent donors (false discovery rate [FDR] < 0.05). The effect on the CpG cg23032799 (CREB3L1) was cross-tissue validated in bronchial epithelial cells at nominal level (p = 0.030). DNAm changes in these three CpGs were shown to be influenced by three independent genetic variants (FDR < 0.05). In silico analyses showed these polymorphisms regulated gene expression of nearby genes in lungs and/or fibroblasts including KSR1 and LINC01600 (6.30 × 10-14 ≤ p ≤ 6.60 × 10-5). Additionally, hypomethylation at the CpGs cg10290200 (FLNC) and cg05673431 (KSR1) was associated with increased gene expression of the genes where they are located (FDR < 0.05). Furthermore, while the epigenetic effect of albuterol was independent of the asthma status, severity, and use of medication, BDR was nominally associated with the effect on the CpG cg23032799 (CREB3L1) (p = 0.004). Gene-set enrichment analyses revealed that epigenomic modifications of albuterol could participate in asthma-relevant processes (e.g., IL-2, TNF-α, and NF-κB signaling pathways). Finally, nine differentially methylated regions were associated with albuterol treatment, including CREB3L1, MYLK4, and KSR1 (adjusted p value < 0.05). CONCLUSIONS This study revealed evidence of epigenetic modifications induced by albuterol in the mucociliary airway epithelium. The epigenomic response induced by albuterol might have potential clinical implications by affecting biological pathways relevant to asthma.
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Grants
- R01 ES015794 NIEHS NIH HHS
- R01 HL120393 NHLBI NIH HHS
- R01ES015794, R21ES24844 NIEHS NIH HHS
- UM1 HG008901 NHGRI NIH HHS
- R01MD010443, R56MD013312 NIMHD NIH HHS
- R01 HL135156 NHLBI NIH HHS
- R01 HL128439 NHLBI NIH HHS
- R01 HL117004 NHLBI NIH HHS
- R21 ES024844 NIEHS NIH HHS
- R01 HL117626 NHLBI NIH HHS
- R56 MD013312 NIMHD NIH HHS
- R01 MD010443 NIMHD NIH HHS
- R01 HL155024 NHLBI NIH HHS
- R01HL155024-01, HHSN268201600032I, 3R01HL-117626-02S1, HHSN268201800002I, 3R01HL117004-02S3, 3R01HL-120393-02S1, R01HL117004, R01HL128439, R01HL135156, X01HL134589 NHLBI NIH HHS
- HHSN268201600032C NHLBI NIH HHS
- U24 HG008956 NHGRI NIH HHS
- Ministerio de Universidades
- Ministerio de Ciencia e Innovación
- Instituto de Salud Carlos III
- National Heart, Lung, and Blood Institute
- National Human Genome Research Institute
- National Institute of Environmental Health Sciences
- National Institute on Minority Health and Health Disparities
- The Centers for Common Disease Genomics of the Genome Sequencing Program
- Tobacco-Related Disease Research Program
- Sandler Family Foundation
- American Asthma Foundation
- Amos Medical Faculty Development Program from the Robert Wood Johnson Foundation
- Harry Wm. and Diana V. Hind Distinguished Professor in Pharmaceutical Sciences II
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Affiliation(s)
- Javier Perez-Garcia
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology, and Genetics, Universidad de La Laguna (ULL), La Laguna, Tenerife, Canary Islands, Spain.
| | - Maria Pino-Yanes
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology, and Genetics, Universidad de La Laguna (ULL), La Laguna, Tenerife, Canary Islands, Spain.
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain.
- Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna (ULL), La Laguna, Spain.
| | - Elizabeth G Plender
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
| | - Jamie L Everman
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
| | - Celeste Eng
- Department of Medicine, University of California San Francisco (UCSF), San Francisco, CA, USA
| | - Nathan D Jackson
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
| | - Camille M Moore
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
- Department of Biomedical Research, National Jewish Health, Denver, CO, USA
- Department of Biostatistics and Informatics, University of Colorado, Denver, CO, USA
| | - Kenneth B Beckman
- University of Minnesota Genomics Center (UMNGC), Minneapolis, MN, USA
| | | | - Sunita Sharma
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Daniel Efrain Winnica
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Fernando Holguin
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | | | - Jesús Villar
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Multidisciplinary Organ Dysfunction Evaluation Research Network (MODERN), Research Unit, Hospital Universitario Dr. Negrín, Las Palmas de Gran Canaria, Spain
- Li Ka Shing Knowledge Institute at the St. Michael's Hospital, Toronto, ON, Canada
| | - Elad Ziv
- Institute for Human Genetics, University of California San Francisco (UCSF), San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco School of Medicine, San Francisco, CA, USA
| | - Max A Seibold
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Pediatrics, National Jewish Health, Denver, CO, USA
| | - Esteban G Burchard
- Department of Medicine, University of California San Francisco (UCSF), San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco (UCSF), San Francisco, CA, USA
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19
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Yi H, Lin Y, Chang Q, Jin W. A fast and globally optimal solution for RNA-seq quantification. Brief Bioinform 2023; 24:bbad298. [PMID: 37595963 DOI: 10.1093/bib/bbad298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/25/2023] [Accepted: 07/31/2023] [Indexed: 08/20/2023] Open
Abstract
Alignment-based RNA-seq quantification methods typically involve a time-consuming alignment process prior to estimating transcript abundances. In contrast, alignment-free RNA-seq quantification methods bypass this step, resulting in significant speed improvements. Existing alignment-free methods rely on the Expectation-Maximization (EM) algorithm for estimating transcript abundances. However, EM algorithms only guarantee locally optimal solutions, leaving room for further accuracy improvement by finding a globally optimal solution. In this study, we present TQSLE, the first alignment-free RNA-seq quantification method that provides a globally optimal solution for transcript abundances estimation. TQSLE adopts a two-step approach: first, it constructs a k-mer frequency matrix A for the reference transcriptome and a k-mer frequency vector b for the RNA-seq reads; then, it directly estimates transcript abundances by solving the linear equation ATAx = ATb. We evaluated the performance of TQSLE using simulated and real RNA-seq data sets and observed that, despite comparable speed to other alignment-free methods, TQSLE outperforms them in terms of accuracy. TQSLE is freely available at https://github.com/yhg926/TQSLE.
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Affiliation(s)
- Huiguang Yi
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, 97 Buxin Rd, Shenzhen, 518000, Guangdong, China
- School of Life Sciences, Southern University of Science and Technology, 1088 Xueyuan Blvd, Shenzhen 518055, Guangdong, China
| | - Yanling Lin
- School of Life Sciences, Southern University of Science and Technology, 1088 Xueyuan Blvd, Shenzhen 518055, Guangdong, China
| | - Qing Chang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, 97 Buxin Rd, Shenzhen, 518000, Guangdong, China
| | - Wenfei Jin
- School of Life Sciences, Southern University of Science and Technology, 1088 Xueyuan Blvd, Shenzhen 518055, Guangdong, China
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20
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Zheng Y, Jun J, Brennan K, Gevaert O. EpiMix is an integrative tool for epigenomic subtyping using DNA methylation. CELL REPORTS METHODS 2023; 3:100515. [PMID: 37533639 PMCID: PMC10391348 DOI: 10.1016/j.crmeth.2023.100515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 04/12/2023] [Accepted: 06/01/2023] [Indexed: 08/04/2023]
Abstract
DNA methylation (DNAme) is a major epigenetic factor influencing gene expression with alterations leading to cancer and immunological and cardiovascular diseases. Recent technological advances have enabled genome-wide profiling of DNAme in large human cohorts. There is a need for analytical methods that can more sensitively detect differential methylation profiles present in subsets of individuals from these heterogeneous, population-level datasets. We developed an end-to-end analytical framework named "EpiMix" for population-level analysis of DNAme and gene expression. Compared with existing methods, EpiMix showed higher sensitivity in detecting abnormal DNAme that was present in only small patient subsets. We extended the model-based analyses of EpiMix to cis-regulatory elements within protein-coding genes, distal enhancers, and genes encoding microRNAs and long non-coding RNAs (lncRNAs). Using cell-type-specific data from two separate studies, we discover epigenetic mechanisms underlying childhood food allergy and survival-associated, methylation-driven ncRNAs in non-small cell lung cancer.
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Affiliation(s)
- Yuanning Zheng
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - John Jun
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Kevin Brennan
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Olivier Gevaert
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
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21
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Wang W, Yao W, Tan Q, Li S, Duan H, Tian X, Xu C, Zhang D. Identification of key DNA methylation changes on fasting plasma glucose: a genome-wide DNA methylation analysis in Chinese monozygotic twins. Diabetol Metab Syndr 2023; 15:159. [PMID: 37461060 PMCID: PMC10351111 DOI: 10.1186/s13098-023-01136-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 07/09/2023] [Indexed: 07/21/2023] Open
Abstract
BACKGROUND Elevated fasting plasma glucose (FPG) levels can increase morbidity and mortality even when it is below the diagnostic threshold of type 2 diabetes mellitus (T2DM). We conducted a genome-wide DNA methylation analysis to detect DNA methylation (DNAm) variants potentially related to FPG in Chinese monozygotic twins. METHODS Genome-wide DNA methylation profiling in whole blood of twins was performed using Reduced Representation Bisulfite Sequencing (RRBS), yielding 551,447 raw CpGs. Association between DNAm of single CpG and FPG was tested using a generalized estimation equation. Differentially methylated regions (DMRs) were identified using comb-P approach. ICE FALCON method was utilized to perform the causal inference. Candidate CpGs were quantified and validated using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data from twins. RESULTS The mean age of 52 twin pairs was 52 years (SD: 7). The relationship between DNAm of 142 CpGs and FPG reached the genome-wide significance level. Thirty-two DMRs within 24 genes were identified, including TLCD1, MRPS31P5, CASZ1, and CXADRP3. The causal relationship of top CpGs mapped to TLCD1, MZF1, PTPRN2, SLC6A18, ASTN2, IQCA1, GRIN1, and PDE2A genes with FPG were further identified using ICE FALCON method. Pathways potentially related to FPG were also identified, such as phospholipid-hydroperoxide glutathione peroxidase activity and mitogen-activated protein kinase p38 binding. Three CpGs mapped to SLC6A18 gene were validated in a community population, with a hypermethylated direction in diabetic patients. The expression levels of 18 genes (including SLC6A18 and TLCD1) were positively correlated with FPG levels. CONCLUSIONS We detect many DNAm variants that may be associated with FPG in whole blood, particularly the loci within SLC6A18 gene. Our findings provide important reference for the epigenetic regulation of elevated FPG levels and diabetes.
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Affiliation(s)
- Weijing Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, No. 308 Ningxia Road, Qingdao, 266071 Shandong Province China
| | - Wenqin Yao
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, No. 308 Ningxia Road, Qingdao, 266071 Shandong Province China
- Shandong Province Center for Disease Control and Prevention, Shandong, China
| | - Qihua Tan
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Shuxia Li
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, No. 308 Ningxia Road, Qingdao, 266071 Shandong Province China
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22
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Mohanraj L, Lapato DM, Toor A, Swift-Scanlan T. DNA Methylation Research in Autologous Hematopoietic Stem Cell Transplant Population. Biol Res Nurs 2023; 25:220-226. [PMID: 36242509 DOI: 10.1177/10998004221132251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Despite increased sophistication in DNA methylation (DNAm) measurement and methods, conducting studies in specific populations such as the hematopoietic stem cell transplant (HCT) population, presents unique challenges and study design considerations. In this article, we explain the motivation for investigating DNAm in the HCT population, highlighting important study design features and key findings in a longitudinal prospective pilot study of DNAm in 32 patients undergoing autologous HCT in Central Virginia, USA. We also discuss limitations and challenges to generating robust results. We observed that HCT does not prevent high-quality DNA from being extracted from whole blood for DNAm research and that longitudinal prospective studies that span pre- and 2-months post-HCT are feasible. Critically, we did not observe significant impacts of cancer diagnosis, time since transplant, age, or chromosomal sex on overall DNAm data dimensionality. These observations demonstrate that while extreme care is required to ensure generalizable, accurate, and interpretable results, researchers should not avoid HCT-DNAm research simply for fear that the transplant procedure or presence of a cancer diagnosis will prevent meaningful conclusions from being drawn. DNAm is an attractive biomarker that is understudied in patients undergoing HCT and needs to expand to improve precise prediction of HCT outcomes.
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Affiliation(s)
- Lathika Mohanraj
- Department of Adult Health and Nursing Systems, 16197VCU School of Nursing, Richmond, VA, USA
| | - Dana M Lapato
- Department of Human and Molecular Genetics, VCU School of Medicine, Richmond, VA, USA
| | - Amir Toor
- Department of Internal Medicine, VCU School of Medicine, Richmond, VA, USA
| | - Theresa Swift-Scanlan
- Endowed Professor and Director, Biobehavioral Research Lab, 16197VCU School of Nursing, Richmond, VA, USA
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23
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Jumentier B, Barrot CC, Estavoyer M, Tost J, Heude B, François O, Lepeule J. High-Dimensional Mediation Analysis: A New Method Applied to Maternal Smoking, Placental DNA Methylation, and Birth Outcomes. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:47011. [PMID: 37058433 PMCID: PMC10104171 DOI: 10.1289/ehp11559] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 02/22/2023] [Accepted: 02/23/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND High-dimensional mediation analysis is an extension of unidimensional mediation analysis that includes multiple mediators, and increasingly it is being used to evaluate the indirect omics-layer effects of environmental exposures on health outcomes. Analyses involving high-dimensional mediators raise several statistical issues. Although many methods have recently been developed, no consensus has been reached about the optimal combination of approaches to high-dimensional mediation analyses. OBJECTIVES We developed and validated a method for high-dimensional mediation analysis (HDMAX2) and applied it to evaluate the causal role of placental DNA methylation in the pathway between exposure to maternal smoking (MS) during pregnancy and gestational age (GA) and birth weight of the baby at birth. METHODS HDMAX2 combines latent factor regression models for epigenome-wide association studies with max2 tests for mediation and considers CpGs and aggregated mediator regions (AMRs). HDMAX2 was carefully evaluated using simulated data and compared to state-of-the-art multidimensional epigenetic mediation methods. Then, HDMAX2 was applied to data from 470 women of the Etude des Déterminants pré et postnatals du développement de la santé de l'Enfant (EDEN) cohort. RESULTS HDMAX2 demonstrated increased power in comparison with state-of-the-art multidimensional mediation methods and identified several AMRs not identified in previous mediation analyses of exposure to MS on birth weight and GA. The results provided evidence for a polygenic architecture of the mediation pathway with a posterior estimate of the overall indirect effect of CpGs and AMRs equal to 44.5g lower birth weight representing 32.1% of the total effect [standard deviation (SD)=60.7g]. HDMAX2 also identified AMRs having simultaneous effects both on GA and on birth weight. Among the top hits of both GA and birth weight analyses, regions located in COASY, BLCAP, and ESRP2 also mediated the relationship between GA and birth weight, suggesting reverse causality in the relationship between GA and the methylome. DISCUSSION HDMAX2 outperformed existing approaches and revealed an unsuspected complexity of the potential causal relationships between exposure to MS and birth weight at the epigenome-wide level. HDMAX2 is applicable to a wide range of tissues and omic layers. https://doi.org/10.1289/EHP11559.
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Affiliation(s)
- Basile Jumentier
- Université Grenoble-Alpes, Centre National de la Recherche Scientifique, Grenoble INP, TIMC CNRS UMR 5525, Grenoble, France
| | - Claire-Cécile Barrot
- Université Grenoble-Alpes, Centre National de la Recherche Scientifique, Grenoble INP, TIMC CNRS UMR 5525, Grenoble, France
| | - Maxime Estavoyer
- Université Grenoble-Alpes, Centre National de la Recherche Scientifique, Grenoble INP, TIMC CNRS UMR 5525, Grenoble, France
| | - Jorg Tost
- Laboratory for Epigenetics and Environment, Centre National de Recherche en Genomique Humaine, CEA – Institut de Biologie François Jacob, University Paris Saclay, Evry, France
| | - Barbara Heude
- Université Paris Cité et Université Sorbonne Paris Nord, Inserm, INRAE, Centre de Recherche en Épidémiologie et StatistiqueS (CRESS), F-75004 Paris, France
| | - Olivier François
- Université Grenoble-Alpes, Centre National de la Recherche Scientifique, Grenoble INP, TIMC CNRS UMR 5525, Grenoble, France
- Inria Grenoble – Rhône-Alpes Inovallée, Montbonnot, France
| | - Johanna Lepeule
- Université Grenoble-Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Development and Respiratory Health, Institute for Advanced Biosciences, Grenoble, France
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24
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Tan Q, Møller AMJ, Qiu C, Madsen JS, Shen H, Bechmann T, Delaisse JM, Kristensen BW, Deng HW, Karasik D, Søe K. A variability in response of osteoclasts to zoledronic acid is mediated by smoking-associated modification in the DNA methylome. Clin Epigenetics 2023; 15:42. [PMID: 36915112 PMCID: PMC10012449 DOI: 10.1186/s13148-023-01449-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 02/15/2023] [Indexed: 03/14/2023] Open
Abstract
BACKGROUND Clinical trials have shown zoledronic acid as a potent bisphosphonate in preventing bone loss, but with varying potency between patients. Human osteoclasts ex vivo reportedly displayed a variable sensitivity to zoledronic acid > 200-fold, determined by the half-maximal inhibitory concentration (IC50), with cigarette smoking as one of the reported contributors to this variation. To reveal the molecular basis of the smoking-mediated variation on treatment sensitivity, we performed a DNA methylome profiling on whole blood cells from 34 healthy female blood donors. Multiple regression models were fitted to associate DNA methylation with ex vivo determined IC50 values, smoking, and their interaction adjusting for age and cell compositions. RESULTS We identified 59 CpGs displaying genome-wide significance (p < 1e-08) with a false discovery rate (FDR) < 0.05 for the smoking-dependent association with IC50. Among them, 3 CpGs have p < 1e-08 and FDR < 2e-03. By comparing with genome-wide association studies, 15 significant CpGs were locally enriched (within < 50,000 bp) by SNPs associated with bone and body size measures. Furthermore, through a replication analysis using data from a published multi-omics association study on bone mineral density (BMD), we could validate that 29 out of the 59 CpGs were in close vicinity of genomic sites significantly associated with BMD. Gene Ontology (GO) analysis on genes linked to the 59 CpGs displaying smoking-dependent association with IC50, detected 18 significant GO terms including cation:cation antiporter activity, extracellular matrix conferring tensile strength, ligand-gated ion channel activity, etc. CONCLUSIONS: Our results suggest that smoking mediates individual sensitivity to zoledronic acid treatment through epigenetic regulation. Our novel findings could have important clinical implications since DNA methylation analysis may enable personalized zoledronic acid treatment.
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Affiliation(s)
- Qihua Tan
- grid.10825.3e0000 0001 0728 0170Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, 5000 Odense C, Denmark
| | - Anaïs Marie Julie Møller
- grid.10825.3e0000 0001 0728 0170Clinical Cell Biology, Pathology Research Unit, Department of Clinical Research, University of Southern Denmark, J. B. Winsløvs Vej 25, 1st Floor, 5000 Odense C, Denmark
- grid.10825.3e0000 0001 0728 0170Clinical Cell Biology, Department of Regional Health Research, University of Southern Denmark, 7100 Vejle, Denmark
| | - Chuan Qiu
- grid.265219.b0000 0001 2217 8588Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane Center of Biomedical Informatics and Genomics, Tulane University, New Orleans, LA 70112 USA
| | - Jonna Skov Madsen
- grid.7143.10000 0004 0512 5013Department of Biochemistry and Immunology, Lillebaelt Hospital, University Hospital of Southern Denmark, 7100 Vejle, Denmark
- grid.10825.3e0000 0001 0728 0170Department of Regional Health Research, University of Southern Denmark, 5000 Odense C, Denmark
| | - Hui Shen
- grid.265219.b0000 0001 2217 8588Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane Center of Biomedical Informatics and Genomics, Tulane University, New Orleans, LA 70112 USA
| | - Troels Bechmann
- grid.7143.10000 0004 0512 5013Department of Oncology, Lillebaelt Hospital, University Hospital of Southern Denmark, 7100 Vejle, Denmark
- grid.452681.c0000 0004 0639 1735Department of Oncology, Regional Hospital West Jutland, 7400 Herning, Denmark
| | - Jean-Marie Delaisse
- grid.10825.3e0000 0001 0728 0170Clinical Cell Biology, Pathology Research Unit, Department of Clinical Research, University of Southern Denmark, J. B. Winsløvs Vej 25, 1st Floor, 5000 Odense C, Denmark
- grid.7143.10000 0004 0512 5013Department of Pathology, Odense University Hospital, 5000 Odense C, Denmark
| | - Bjarne Winther Kristensen
- grid.7143.10000 0004 0512 5013Department of Pathology, Odense University Hospital, 5000 Odense C, Denmark
- grid.10825.3e0000 0001 0728 0170Pathology Research Unit, Department of Clinical Research, University of Southern Denmark, 5000 Odense C, Denmark
| | - Hong-Wen Deng
- grid.265219.b0000 0001 2217 8588Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane Center of Biomedical Informatics and Genomics, Tulane University, New Orleans, LA 70112 USA
| | - David Karasik
- grid.22098.310000 0004 1937 0503Azrieli Faculty of Medicine, Bar-Ilan University, 130010 Safed, Israel
| | - Kent Søe
- grid.10825.3e0000 0001 0728 0170Clinical Cell Biology, Pathology Research Unit, Department of Clinical Research, University of Southern Denmark, J. B. Winsløvs Vej 25, 1st Floor, 5000 Odense C, Denmark
- grid.7143.10000 0004 0512 5013Department of Pathology, Odense University Hospital, 5000 Odense C, Denmark
- grid.10825.3e0000 0001 0728 0170Department of Molecular Medicine, University of Southern Denmark, 5000 Odense C, Denmark
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25
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Wang W, Yao J, Li W, Wu Y, Duan H, Xu C, Tian X, Li S, Tan Q, Zhang D. Epigenome-wide association study in Chinese monozygotic twins identifies DNA methylation loci associated with blood pressure. Clin Epigenetics 2023; 15:38. [PMID: 36869404 PMCID: PMC9985232 DOI: 10.1186/s13148-023-01457-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 02/24/2023] [Indexed: 03/05/2023] Open
Abstract
BACKGROUND Hypertension is a crucial risk factor for developing cardiovascular disease and reducing life expectancy. We aimed to detect DNA methylation (DNAm) variants potentially related to systolic blood pressure (SBP) and diastolic blood pressure (DBP) by conducting epigenome-wide association studies in 60 and 59 Chinese monozygotic twin pairs, respectively. METHODS Genome-wide DNA methylation profiling in whole blood of twins was performed using Reduced Representation Bisulfite Sequencing, yielding 551,447 raw CpGs. Association between DNAm of single CpG and blood pressure was tested by applying generalized estimation equation. Differentially methylated regions (DMRs) were identified by comb-P approach. Inference about Causation through Examination of Familial Confounding was utilized to perform the causal inference. Ontology enrichment analysis was performed using Genomic Regions Enrichment of Annotations Tool. Candidate CpGs were quantified using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data. RESULTS The median age of twins was 52 years (95% range 40, 66). For SBP, 31 top CpGs (p < 1 × 10-4) and 8 DMRs were identified, with several DMRs within NFATC1, CADM2, IRX1, COL5A1, and LRAT. For DBP, 43 top CpGs (p < 1 × 10-4) and 12 DMRs were identified, with several DMRs within WNT3A, CNOT10, and DAB2IP. Important pathways, such as Notch signaling pathway, p53 pathway by glucose deprivation, and Wnt signaling pathway, were significantly enriched for SBP and DBP. Causal inference analysis suggested that DNAm at top CpGs within NDE1, MYH11, SRRM1P2, and SMPD4 influenced SBP, while SBP influenced DNAm at CpGs within TNK2. DNAm at top CpGs within WNT3A influenced DBP, while DBP influenced DNAm at CpGs within GNA14. Three CpGs mapped to WNT3A and one CpG mapped to COL5A1 were validated in a community population, with a hypermethylated and hypomethylated direction in hypertension cases, respectively. Gene expression analysis by WGCNA further identified some common genes and enrichment terms. CONCLUSION We detect many DNAm variants that may be associated with blood pressure in whole blood, particularly the loci within WNT3A and COL5A1. Our findings provide new clues to the epigenetic modification underlying hypertension pathogenesis.
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Affiliation(s)
- Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China
| | - Jie Yao
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China
- Jiangsu Health Development Research Center, Nanjing, Jiangsu, China
| | - Weilong Li
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Yili Wu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Shuxia Li
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Qihua Tan
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China.
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Carlsen LN, Hansen CS, Kogelman LJA, Werge TM, Ullum H, Bybjerg-Grauholm J, Hansen TF, Jensen RH. DNA-methylation and immunological response in medication overuse headache. Cephalalgia 2023; 43:3331024221147482. [PMID: 36786322 DOI: 10.1177/03331024221147482] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Abstract
OBJECTIVE To investigate whether medication-overuse headache patients have differential DNA-methylation pattern. METHODS We collected blood samples from 120 medication-overuse headache-patients, 57 controls (29 episodic migraine patients and 28 healthy controls) in a hypothesis-generating cross-sectional case-control pilot study; 100 of the medication-overuse headache-patients were followed for six months and samples were collected at two and six months for the longitudinal methylation analyses. Blood cell proportions of leucocytes (neutrophils, NK-cells, monocytes, CD8+ and CD4+ T-cells, and B-cells) and the neutrophile-lymphocyte ratio were estimated using methylation data as a measure for immunological analysis and a cell type-specific epigenome wide association study was conducted between medication-overuse headache-patients and controls, and longitudinally for reduction in headache days/month among medication-overuse headache-patients. RESULTS We found a higher neutrophile-lymphocyte ratio in medication-overuse headache-patients compared to controls, indicating a higher immunological response in medication-overuse headache-patients (false discovery rate (adjusted p-value)<0.001). Reduction in headache days/month (9.8; 95% CI 8.1-11.5) was associated with lower neutrophile-lymphocyte ratio (false discovery rate adjusted p-value = 0.041).Three genes (CORIN, CCKBR and CLDN9) were hypermethylated in specific cell types in medication-overuse headache-patients compared to controls. No methylation differences were associated with reduction in headache days in medication-overuse headache-patients after six months. CONCLUSION This pilot study was consistent with higher immunological response in medication-overuse headache-patients which decreased with a reduction in headache days in longitudinal analysis. medication-overuse headache-patients exhibited differential methylation in innate immune cells but did not exhibit longitudinal differences with alterations in headache days. Our study creates hypotheses for further biomarker searches.ClinicalTrials.gov Identifier: NCT02993289.
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Affiliation(s)
| | | | | | - Thomas Mears Werge
- Novo Nordisk Foundation Center for Protein Research, Copenhagen University, Denmark
| | | | | | - Thomas Folkmann Hansen
- Danish Headache Center, Rigshospitalet, Denmark.,Novo Nordisk Foundation Center for Protein Research, Copenhagen University, Denmark
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Lee MK, Azizgolshani N, Zhang Z, Perreard L, Kolling FW, Nguyen LN, Zanazzi GJ, Salas LA, Christensen BC. Hydroxymethylation alterations in progenitor-like cell types of pediatric central nervous system tumors are associated with cell type-specific transcriptional changes. RESEARCH SQUARE 2023:rs.3.rs-2517758. [PMID: 36909536 PMCID: PMC10002842 DOI: 10.21203/rs.3.rs-2517758/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Although intratumoral heterogeneity has been established in pediatric central nervous system tumors, epigenomic alterations at the cell type level have largely remained unresolved. To identify cell type-specific alterations to cytosine modifications in pediatric central nervous system tumors we utilized a multi-omic approach that integrated bulk DNA cytosine modification data (methylation and hydroxymethylation) with both bulk and single-cell RNA-sequencing data. We demonstrate a large reduction in the scope of significantly differentially modified cytosines in tumors when accounting for tumor cell type composition. In the progenitor-like cell types of tumors, we identified a preponderance differential CpG hydroxymethylation rather than methylation. Genes with differential hydroxymethylation, like HDAC4 and IGF1R, were associated with cell type-specific changes in gene expression in tumors. Our results highlight the importance of epigenomic alterations in the progenitor-like cell types and its role in cell type-specific transcriptional regulation in pediatric CNS tumors.
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Affiliation(s)
- Min Kyung Lee
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Nasim Azizgolshani
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- Department of Cardiothoracic Surgery, Columbia University Medical Center, New York, NY, USA
| | - Ze Zhang
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Laurent Perreard
- Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Fred W Kolling
- Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Lananh N Nguyen
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - George J Zanazzi
- Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- Department of Pathology and Laboratory Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
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Martin-Almeida M, Perez-Garcia J, Herrera-Luis E, Rosa-Baez C, Gorenjak M, Neerincx AH, Sardón-Prado O, Toncheva AA, Harner S, Wolff C, Brandstetter S, Valletta E, Abdel-Aziz MI, Hashimoto S, Berce V, Corcuera-Elosegui P, Korta-Murua J, Buntrock-Döpke H, Vijverberg SJH, Verster JC, Kerssemakers N, Hedman AM, Almqvist C, Villar J, Kraneveld AD, Potočnik U, Kabesch M, der Zee AHMV, Pino-Yanes M, Consortium OBOTS. Epigenome-Wide Association Studies of the Fractional Exhaled Nitric Oxide and Bronchodilator Drug Response in Moderate-to-Severe Pediatric Asthma. Biomedicines 2023; 11:biomedicines11030676. [PMID: 36979655 PMCID: PMC10044864 DOI: 10.3390/biomedicines11030676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 02/14/2023] [Accepted: 02/18/2023] [Indexed: 02/25/2023] Open
Abstract
Asthma is the most prevalent pediatric chronic disease. Bronchodilator drug response (BDR) and fractional exhaled nitric oxide (FeNO) are clinical biomarkers of asthma. Although DNA methylation (DNAm) contributes to asthma pathogenesis, the influence of DNAm on BDR and FeNO is scarcely investigated. This study aims to identify DNAm markers in whole blood associated either with BDR or FeNO in pediatric asthma. We analyzed 121 samples from children with moderate-to-severe asthma. The association of genome-wide DNAm with BDR and FeNO has been assessed using regression models, adjusting for age, sex, ancestry, and tissue heterogeneity. Cross-tissue validation was assessed in 50 nasal samples. Differentially methylated regions (DMRs) and enrichment in traits and biological pathways were assessed. A false discovery rate (FDR) < 0.1 and a genome-wide significance threshold of p < 9 × 10−8 were used to control for false-positive results. The CpG cg12835256 (PLA2G12A) was genome-wide associated with FeNO in blood samples (coefficient= −0.015, p = 2.53 × 10−9) and nominally associated in nasal samples (coefficient = −0.015, p = 0.045). Additionally, three CpGs were suggestively associated with BDR (FDR < 0.1). We identified 12 and four DMRs associated with FeNO and BDR (FDR < 0.05), respectively. An enrichment in allergic and inflammatory processes, smoking, and aging was observed. We reported novel associations of DNAm markers associated with BDR and FeNO enriched in asthma-related processes.
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Affiliation(s)
- Mario Martin-Almeida
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology, and Genetics, Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Spain
| | - Javier Perez-Garcia
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology, and Genetics, Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Spain
| | - Esther Herrera-Luis
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology, and Genetics, Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Spain
| | - Carlos Rosa-Baez
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology, and Genetics, Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Spain
| | - Mario Gorenjak
- Center for Human Molecular Genetics and Pharmacogenomics, Faculty of Medicine, University of Maribor, 2000 Maribor, Slovenia
| | - Anne H. Neerincx
- Department of Respiratory Medicine, Amsterdam University Medical Centres—Loc. AMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Olaia Sardón-Prado
- Division of Pediatric Respiratory Medicine, Donostia University Hospital, 20014 San Sebastián, Spain
- Department of Pediatrics, University of the Basque Country (UPV/EHU), 48013 San Sebastián, Spain
| | - Antoaneta A. Toncheva
- Department of Pediatric Pneumology and Allergy, University Children’s Hospital Regensburg (KUNO) at the Hospital St. Hedwig of the Order of St. John, University of Regensburg, D-93049 Regensburg, Germany
| | - Susanne Harner
- Department of Pediatric Pneumology and Allergy, University Children’s Hospital Regensburg (KUNO) at the Hospital St. Hedwig of the Order of St. John, University of Regensburg, D-93049 Regensburg, Germany
| | - Christine Wolff
- Department of Pediatric Pneumology and Allergy, University Children’s Hospital Regensburg (KUNO) at the Hospital St. Hedwig of the Order of St. John, University of Regensburg, D-93049 Regensburg, Germany
| | - Susanne Brandstetter
- Department of Pediatric Pneumology and Allergy, University Children’s Hospital Regensburg (KUNO) at the Hospital St. Hedwig of the Order of St. John, University of Regensburg, D-93049 Regensburg, Germany
| | - Elisa Valletta
- Department of Pediatric Pneumology and Allergy, University Children’s Hospital Regensburg (KUNO) at the Hospital St. Hedwig of the Order of St. John, University of Regensburg, D-93049 Regensburg, Germany
| | - Mahmoud I. Abdel-Aziz
- Department of Respiratory Medicine, Amsterdam University Medical Centres—Loc. AMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
- Department of Clinical Pharmacy, Faculty of Pharmacy, Assiut University, Assiut 71515, Egypt
| | - Simone Hashimoto
- Department of Respiratory Medicine, Amsterdam University Medical Centres—Loc. AMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
- Department of Pediatric Respiratory Medicine, Emma Children’s Hospital, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
| | - Vojko Berce
- Center for Human Molecular Genetics and Pharmacogenomics, Faculty of Medicine, University of Maribor, 2000 Maribor, Slovenia
- Clinic of Pediatrics, University Medical Centre Maribor, 2000 Maribor, Slovenia
| | - Paula Corcuera-Elosegui
- Division of Pediatric Respiratory Medicine, Donostia University Hospital, 20014 San Sebastián, Spain
| | - Javier Korta-Murua
- Division of Pediatric Respiratory Medicine, Donostia University Hospital, 20014 San Sebastián, Spain
- Department of Pediatrics, University of the Basque Country (UPV/EHU), 48013 San Sebastián, Spain
| | - Heike Buntrock-Döpke
- Department of Pediatric Pneumology and Allergy, University Children’s Hospital Regensburg (KUNO) at the Hospital St. Hedwig of the Order of St. John, University of Regensburg, D-93049 Regensburg, Germany
| | - Susanne J. H. Vijverberg
- Department of Respiratory Medicine, Amsterdam University Medical Centres—Loc. AMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Joris C. Verster
- Division of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, 3584 CG Utrecht, The Netherlands
- Centre for Human Psychopharmacology, Swinburne University, Melbourne, VIC 3122, Australia
| | - Nikki Kerssemakers
- Division of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, 3584 CG Utrecht, The Netherlands
| | - Anna M Hedman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, 171 77 Stockholm, Sweden
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, 171 77 Stockholm, Sweden
| | - Jesús Villar
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, 28029 Madrid, Spain
- Multidisciplinary Organ Dysfunction Evaluation Research Network, Research Unit, Hospital Universitario Dr. Negrín, 35010 Las Palmas de Gran Canaria, Spain
| | - Aletta D. Kraneveld
- Division of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, 3584 CG Utrecht, The Netherlands
| | - Uroš Potočnik
- Center for Human Molecular Genetics and Pharmacogenomics, Faculty of Medicine, University of Maribor, 2000 Maribor, Slovenia
- Clinic of Pediatrics, University Medical Centre Maribor, 2000 Maribor, Slovenia
- Laboratory for Biochemistry, Molecular Biology, and Genomics, Faculty of Chemistry and Chemical Engineering, University of Maribor, 2000 Maribor, Slovenia
| | - Michael Kabesch
- Department of Pediatric Pneumology and Allergy, University Children’s Hospital Regensburg (KUNO) at the Hospital St. Hedwig of the Order of St. John, University of Regensburg, D-93049 Regensburg, Germany
| | - Anke H. Maitland-van der Zee
- Department of Respiratory Medicine, Amsterdam University Medical Centres—Loc. AMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
- Department of Pediatric Respiratory Medicine, Emma Children’s Hospital, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
| | - Maria Pino-Yanes
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology, and Genetics, Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, 28029 Madrid, Spain
- Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Spain
- Correspondence: ; Tel.: +34-9223-16502-6343
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Nabais MF, Gadd DA, Hannon E, Mill J, McRae AF, Wray NR. An overview of DNA methylation-derived trait score methods and applications. Genome Biol 2023; 24:28. [PMID: 36797751 PMCID: PMC9936670 DOI: 10.1186/s13059-023-02855-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 01/17/2023] [Indexed: 02/18/2023] Open
Abstract
Microarray technology has been used to measure genome-wide DNA methylation in thousands of individuals. These studies typically test the associations between individual DNA methylation sites ("probes") and complex traits or diseases. The results can be used to generate methylation profile scores (MPS) to predict outcomes in independent data sets. Although there are many parallels between MPS and polygenic (risk) scores (PGS), there are key differences. Here, we review motivations, methods, and applications of DNA methylation-based trait prediction, with a focus on common diseases. We contrast MPS with PGS, highlighting where assumptions made in genetic modeling may not hold in epigenetic data.
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Affiliation(s)
- Marta F Nabais
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
| | - Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Eilis Hannon
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
| | - Jonathan Mill
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia.
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Gorla A, Sankararaman S, Burchard E, Flint J, Zaitlen N, Rahmani E. Phenotypic subtyping via contrastive learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.05.522921. [PMID: 36711575 PMCID: PMC9881932 DOI: 10.1101/2023.01.05.522921] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Defining and accounting for subphenotypic structure has the potential to increase statistical power and provide a deeper understanding of the heterogeneity in the molecular basis of complex disease. Existing phenotype subtyping methods primarily rely on clinically observed heterogeneity or metadata clustering. However, they generally tend to capture the dominant sources of variation in the data, which often originate from variation that is not descriptive of the mechanistic heterogeneity of the phenotype of interest; in fact, such dominant sources of variation, such as population structure or technical variation, are, in general, expected to be independent of subphenotypic structure. We instead aim to find a subspace with signal that is unique to a group of samples for which we believe that subphenotypic variation exists (e.g., cases of a disease). To that end, we introduce Phenotype Aware Components Analysis (PACA), a contrastive learning approach leveraging canonical correlation analysis to robustly capture weak sources of subphenotypic variation. In the context of disease, PACA learns a gradient of variation unique to cases in a given dataset, while leveraging control samples for accounting for variation and imbalances of biological and technical confounders between cases and controls. We evaluated PACA using an extensive simulation study, as well as on various subtyping tasks using genotypes, transcriptomics, and DNA methylation data. Our results provide multiple strong evidence that PACA allows us to robustly capture weak unknown variation of interest while being calibrated and well-powered, far superseding the performance of alternative methods. This renders PACA as a state-of-the-art tool for defining de novo subtypes that are more likely to reflect molecular heterogeneity, especially in challenging cases where the phenotypic heterogeneity may be masked by a myriad of strong unrelated effects in the data.
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Affiliation(s)
- Aditya Gorla
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sriram Sankararaman
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Esteban Burchard
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jonathan Flint
- Department of Psychiatry and Behavioral Sciences, Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, USA
| | - Noah Zaitlen
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Elior Rahmani
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
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Zheng Y, Jun J, Brennan K, Gevaert O. EpiMix: an integrative tool for epigenomic subtyping using DNA methylation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.03.522660. [PMID: 36711917 PMCID: PMC9881910 DOI: 10.1101/2023.01.03.522660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
DNA methylation (DNAme) is a major epigenetic factor influencing gene expression with alterations leading to cancer, immunological, and cardiovascular diseases. Recent technological advances enable genome-wide quantification of DNAme in large human cohorts. So far, existing methods have not been evaluated to identify differential DNAme present in large and heterogeneous patient cohorts. We developed an end-to-end analytical framework named "EpiMix" for population-level analysis of DNAme and gene expression. Compared to existing methods, EpiMix showed higher sensitivity in detecting abnormal DNAme that was present in only small patient subsets. We extended the model-based analyses of EpiMix to cis-regulatory elements within protein-coding genes, distal enhancers, and genes encoding microRNAs and lncRNAs. Using cell-type specific data from two separate studies, we discovered novel epigenetic mechanisms underlying childhood food allergy and survival-associated, methylation-driven non-coding RNAs in non-small cell lung cancer.
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Affiliation(s)
- Yuanning Zheng
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - John Jun
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Kevin Brennan
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Olivier Gevaert
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
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32
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Mediation by DNA methylation on the association of BMI and serum uric acid in Chinese monozygotic twins. Gene 2023; 850:146957. [DOI: 10.1016/j.gene.2022.146957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 09/06/2022] [Accepted: 10/03/2022] [Indexed: 02/13/2023]
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Yang MN, Huang R, Zheng T, Dong Y, Wang WJ, Xu YJ, Mehra V, Zhou GD, Liu X, He H, Fang F, Li F, Fan JG, Zhang J, Ouyang F, Briollais L, Li J, Luo ZC. Genome-wide placental DNA methylations in fetal overgrowth and associations with leptin, adiponectin and fetal growth factors. Clin Epigenetics 2022; 14:192. [PMID: 36585686 PMCID: PMC9801645 DOI: 10.1186/s13148-022-01412-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 12/15/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Fetal overgrowth "programs" an elevated risk of type 2 diabetes in adulthood. Epigenetic alterations may be a mechanism in programming the vulnerability. We sought to characterize genome-wide alterations in placental gene methylations in fetal overgrowth and the associations with metabolic health biomarkers including leptin, adiponectin and fetal growth factors. RESULTS Comparing genome-wide placental gene DNA methylations in large-for-gestational-age (LGA, an indicator of fetal overgrowth, n = 30) versus optimal-for-gestational-age (OGA, control, n = 30) infants using the Illumina Infinium Human Methylation-EPIC BeadChip, we identified 543 differential methylation positions (DMPs; 397 hypermethylated, 146 hypomethylated) at false discovery rate < 5% and absolute methylation difference > 0.05 after adjusting for placental cell-type heterogeneity, maternal age, pre-pregnancy BMI and HbA1c levels during pregnancy. Twenty-five DMPs annotated to 20 genes (QSOX1, FCHSD2, LOC101928162, ADGRB3, GCNT1, TAP1, MYO16, NAV1, ATP8A2, LBXCOR1, EN2, INCA1, CAMTA2, SORCS2, SLC4A4, RPA3, UMAD1,USP53, OR2L13 and NR3C2) could explain 80% of the birth weight variations. Pathway analyses did not detect any statistically significant pathways after correcting for multiple tests. We validated a newly discovered differentially (hyper-)methylated gene-visual system homeobox 1 (VSX1) in an independent pyrosequencing study sample (LGA 47, OGA 47). Our data confirmed a hypermethylated gene-cadherin 13 (CDH13) reported in a previous epigenome-wide association study. Adiponectin in cord blood was correlated with its gene methylation in the placenta, while leptin and fetal growth factors (insulin, IGF-1, IGF-2) were not. CONCLUSIONS Fetal overgrowth may be associated with a large number of altered placental gene methylations. Placental VSX1 and CDH13 genes are hypermethylated in fetal overgrowth. Placental ADIPOQ gene methylations and fetal circulating adiponectin levels were correlated, suggesting the contribution of placenta-originated adiponectin to cord blood adiponectin.
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Affiliation(s)
- Meng-Nan Yang
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China ,grid.17063.330000 0001 2157 2938Lunenfeld-Tanenbaum Research Institute, Prosserman Centre for Population Health Research, Department of Obstetrics and Gynecology, Mount Sinai Hospital, Faculty of Medicine, University of Toronto, L5-240, Murray Street 60, Toronto, ON M5G 1X5 Canada
| | - Rong Huang
- grid.17063.330000 0001 2157 2938Lunenfeld-Tanenbaum Research Institute, Prosserman Centre for Population Health Research, Department of Obstetrics and Gynecology, Mount Sinai Hospital, Faculty of Medicine, University of Toronto, L5-240, Murray Street 60, Toronto, ON M5G 1X5 Canada
| | - Tao Zheng
- grid.16821.3c0000 0004 0368 8293Department of Obstetrics and Gynecology, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China
| | - Yu Dong
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China
| | - Wen-Juan Wang
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China
| | - Ya-Jie Xu
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China
| | - Vrati Mehra
- grid.17063.330000 0001 2157 2938Lunenfeld-Tanenbaum Research Institute, Prosserman Centre for Population Health Research, Department of Obstetrics and Gynecology, Mount Sinai Hospital, Faculty of Medicine, University of Toronto, L5-240, Murray Street 60, Toronto, ON M5G 1X5 Canada
| | - Guang-Di Zhou
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China
| | - Xin Liu
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China
| | - Hua He
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China
| | - Fang Fang
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China
| | - Fei Li
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China
| | - Jian-Gao Fan
- grid.16821.3c0000 0004 0368 8293Center for Fatty Liver, Shanghai Key Lab of Pediatric Gastroenterology and Nutrition, Department of Gastroenterology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200092 China
| | - Jun Zhang
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China
| | - Fengxiu Ouyang
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China
| | - Laurent Briollais
- grid.17063.330000 0001 2157 2938Lunenfeld-Tanenbaum Research Institute, Prosserman Centre for Population Health Research, Department of Obstetrics and Gynecology, Mount Sinai Hospital, Faculty of Medicine, University of Toronto, L5-240, Murray Street 60, Toronto, ON M5G 1X5 Canada
| | - Jiong Li
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China ,grid.7048.b0000 0001 1956 2722Department of Clinical Medicine-Department of Clinical Epidemiology, Aarhus University, Olof Palmes Allé 43-45, 8200 Aathus, Denmark
| | - Zhong-Cheng Luo
- grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Early Life Health Institute, Department of Pediatrics, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200092 China ,grid.17063.330000 0001 2157 2938Lunenfeld-Tanenbaum Research Institute, Prosserman Centre for Population Health Research, Department of Obstetrics and Gynecology, Mount Sinai Hospital, Faculty of Medicine, University of Toronto, L5-240, Murray Street 60, Toronto, ON M5G 1X5 Canada
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Nickels EM, Li S, Morimoto L, Kang AY, de Smith AJ, Metayer C, Wiemels JL. Periconceptional folate intake influences DNA methylation at birth based on dietary source in an analysis of pediatric acute lymphoblastic leukemia cases and controls. Am J Clin Nutr 2022; 116:1553-1564. [PMID: 36178055 PMCID: PMC9761733 DOI: 10.1093/ajcn/nqac283] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 09/28/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Periconceptional folate intake is associated with the establishment of DNA methylation in offspring; however, variations in this relation by food sources compared with folic acid supplements are not described. Also, maternal folate intake is associated with decreased risk of pediatric acute lymphoblastic leukemia (ALL), but the mechanism is not known. OBJECTIVES We evaluated the relation between periconceptional folate intake by source and DNA methylation at birth in a cohort of pediatric ALL cases and controls in an epigenome-wide association study. METHODS Genome-wide DNA methylation status obtained from archived neonatal blood spots from pediatric ALL cases (n = 189) and controls (n = 205) in the California Childhood Leukemia Study (CCLS) from 1995-2008 was compared with periconceptional folate from total, food, and supplemental sources using multivariable linear regression. Further stratification was performed by income, education, ethnicity, and total folate intake. We evaluated variable DNA methylation response to periconceptional folate by ALL case status through an interaction term. RESULTS Two significant differentially methylated probes (DMPs) were associated with food and supplemental periconceptional folate intake in all subjects (n = 394). The top differentially methylated region at the promoter region of DUSP22(dual specificity phosphatase 22) demonstrated DNA hypermethylation in ALL cases but not in controls in response to total and food folate intake. We further identified 8 interaction term DMPs with variable DNA methylation response to folate intake by ALL case status. Further stratification of the cohort by education and ethnicity revealed a substantially higher number of DMPs associated with supplemental folic acid intake in Hispanic subjects with lower income and educational level. CONCLUSIONS We identified modest associations between periconceptional folate intake and DNA methylation differing by source, including variation by ALL case status. Hispanic subjects of lower income and education appear uniquely responsive to periconceptional folate supplementation.
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Affiliation(s)
- Eric M Nickels
- Children's Hospital Los Angeles, Center for Blood Disease Institute, Los Angeles, CA, USA
- University of Southern California Keck School of Medicine, Center for Genetic Epidemiology, Los Angeles, CA, USA
| | - Shaobo Li
- University of Southern California Keck School of Medicine, Center for Genetic Epidemiology, Los Angeles, CA, USA
| | - Libby Morimoto
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Alice Y Kang
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Adam J de Smith
- University of Southern California Keck School of Medicine, Center for Genetic Epidemiology, Los Angeles, CA, USA
| | - Catherine Metayer
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Joseph L Wiemels
- University of Southern California Keck School of Medicine, Center for Genetic Epidemiology, Los Angeles, CA, USA
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Zhou X, Zhang H, Duan Y, Zhu J, Dai H. m6A-related long noncoding RNAs predict prognosis and indicate therapeutic response in endometrial carcinoma. J Clin Lab Anal 2022; 37:e24813. [PMID: 36525280 PMCID: PMC9833960 DOI: 10.1002/jcla.24813] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 12/01/2022] [Accepted: 12/02/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND N6-methyladenosine (m6A) has been identified as the most common, abundant, and conserved internal transcriptional modification. Long noncoding RNAs (lncRNAs) are noncoding RNAs consisting of more than 200 nucleotides, and the expression of various lncRNAs may affect cancer prognosis. The impact of m6A-associated lncRNAs on uterine corpus endometrial carcinoma (UCEC) prognosis is unknown. METHODS In this study, UCEC prognosis-related m6A lncRNAs were screened, bioinformatics analysis was performed, and experimental validation was conducted. Endometrial carcinoma (EC) and normal tissue samples were obtained from The Cancer Genome Atlas. The prognosis-related m6A lncRNAs screened by the least absolute shrinkage and selection operator method were used for multivariate Cox proportional risk regression modeling. Principal component analysis and Gene Ontology, immune function difference, and drug sensitivity analyses of the prognostic models were performed. Prognostic analysis was conducted for m6A-associated lncRNAs. The immune infiltration relationship of m6A-associated lncRNAs in EC was identified using the ssGSEA immune infiltration algorithm. A competing endogenouse RNA network was constructed using the LncACTdb database. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) assays were used to validate the differences in m6A-related lncRNA expression in normal and EC cells. RESULTS CDKN2B-AS1 and MIR924HG were found to be risk factors for EC. RAB11B-AS1 was a protective factor in EC patients. MIR924HG expression was upregulated in KLE and RL95-2 endometrial cancer cell lines. Prognostic models involved RAB11B-AS1, LINC01812, HM13-IT1, TPM1-AS, SLC16A1-AS1, LINC01936, and CDKN2B-AS1. The high-risk group was more sensitive to five compounds (ABT.263, ABT.888, AP.24534, ATRA, and AZD.0530) than the low-risk group. CONCLUSION These findings contribute to understanding of the function of m6A-related lncRNAs in UCEC and provide promising therapeutic strategies for UCEC.
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Affiliation(s)
- Xinying Zhou
- Department of Obstetrics and GynecologyShanghai Pudong Hospital, Fudan University Pudong Medical CenterShanghaiChina
| | - Hu Zhang
- Department of Obstetrics and GynecologyShanghai Pudong Hospital, Fudan University Pudong Medical CenterShanghaiChina
| | - Yingchun Duan
- Department of Obstetrics and GynecologyShanghai Pudong Hospital, Fudan University Pudong Medical CenterShanghaiChina
| | - Jianlong Zhu
- Department of Obstetrics and GynecologyShanghai Pudong Hospital, Fudan University Pudong Medical CenterShanghaiChina
| | - Haiyan Dai
- Department of Obstetrics and GynecologyShanghai Pudong Hospital, Fudan University Pudong Medical CenterShanghaiChina
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Targeted Methylation Profiling of Single Laser-Capture Microdissected Post-Mortem Brain Cells by Adapted Limiting Dilution Bisulfite Pyrosequencing (LDBSP). Int J Mol Sci 2022; 23:ijms232415571. [PMID: 36555213 PMCID: PMC9779089 DOI: 10.3390/ijms232415571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 11/28/2022] [Accepted: 11/29/2022] [Indexed: 12/13/2022] Open
Abstract
A reoccurring issue in neuroepigenomic studies, especially in the context of neurodegenerative disease, is the use of (heterogeneous) bulk tissue, which generates noise during epigenetic profiling. A workable solution to this issue is to quantify epigenetic patterns in individually isolated neuronal cells using laser capture microdissection (LCM). For this purpose, we established a novel approach for targeted DNA methylation profiling of individual genes that relies on a combination of LCM and limiting dilution bisulfite pyrosequencing (LDBSP). Using this approach, we determined cytosine-phosphate-guanine (CpG) methylation rates of single alleles derived from 50 neurons that were isolated from unfixed post-mortem brain tissue. In the present manuscript, we describe the general workflow and, as a showcase, demonstrate how targeted methylation analysis of various genes, in this case, RHBDF2, OXT, TNXB, DNAJB13, PGLYRP1, C3, and LMX1B, can be performed simultaneously. By doing so, we describe an adapted data analysis pipeline for LDBSP, allowing one to include and correct CpG methylation rates derived from multi-allele reactions. In addition, we show that the efficiency of LDBSP on DNA derived from LCM neurons is similar to the efficiency obtained in previously published studies using this technique on other cell types. Overall, the method described here provides the user with a more accurate estimation of the DNA methylation status of each target gene in the analyzed cell pools, thereby adding further validity to this approach.
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Wu Y, Tian H, Wang W, Li W, Duan H, Zhang D. DNA methylation and waist-to-hip ratio: an epigenome-wide association study in Chinese monozygotic twins. J Endocrinol Invest 2022; 45:2365-2376. [PMID: 35882828 DOI: 10.1007/s40618-022-01878-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 07/19/2022] [Indexed: 11/27/2022]
Abstract
PURPOSE Epigenetic signatures such as DNA methylation may be associated with specific obesity traits. We performed an epigenome-wide association study (EWAS) by combining with the waist-to-hip ratio (WHR)-discordant monozygotic (MZ) twin design in an attempt to identify genetically independent DNA methylation marks associated with abdominal obesity in Northern Han Chinese and to determine the causation underlying. METHODS A total of 60 WHR discordant MZ twin pairs were selected from the Qingdao Twin Registry, China. Generalized estimated equation (GEE) model was used to regress the methylation level of CpG sites on WHR. The Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) was used to assess the temporal relationship between methylation and WHR. Gene expression analysis was conducted to validate the results of differentially methylated analyses. RESULTS EWAS identified 92 CpG sites with the level of P < 10 - 4 which were annotated to 32 genes, especially CADPS2, TUSC5, ZCCHC14, CORO7, COL23A1, CACNA1C, CYP26B1, and BCAT1. ICE FALCON showed significant causality between DNA methylation of several genes and WHR (P < 0.05). In region-based analysis, 14 differentially methylated regions (DMRs) located at 15 genes (slk-corrected P < 0.05) were detected. The gene expression analysis identified the significant correlation between expression levels of 5 differentially methylated genes and WHR (P < 0.05). CONCLUSIONS Our study identifies the associations between specific epigenetic variations and WHR in Northern Han Chinese. These DNA methylation signatures may have value as diagnostic biomarkers and provide novel insights into the molecular mechanisms of pathogenesis.
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Affiliation(s)
- Y Wu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, NO. 308 Ningxia Road, 266071, Qingdao, Shandong, China.
| | - H Tian
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, NO. 308 Ningxia Road, 266071, Qingdao, Shandong, China
| | - W Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, NO. 308 Ningxia Road, 266071, Qingdao, Shandong, China
| | - W Li
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - H Duan
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - D Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, NO. 308 Ningxia Road, 266071, Qingdao, Shandong, China
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Li L, Konigsberg IR, Bhargava M, Liu S, MacPhail K, Mayer A, Davidson EJ, Liao SY, Lei Z, Mroz PM, Fingerlin TE, Yang IV, Maier LA. Multiomic Signatures of Chronic Beryllium Disease Bronchoalveolar Lavage Cells Relate to T-Cell Function and Innate Immunity. Am J Respir Cell Mol Biol 2022; 67:632-640. [PMID: 35972918 PMCID: PMC9743181 DOI: 10.1165/rcmb.2022-0077oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 08/16/2022] [Indexed: 12/15/2022] Open
Abstract
Chronic beryllium disease (CBD) is a Th1 granulomatous lung disease preceded by sensitization to beryllium (BeS). We profiled the methylome, transcriptome, and selected proteins in the lung to identify molecular signatures and networks associated with BeS and CBD. BAL cell DNA and RNA were profiled using microarrays from CBD (n = 30), BeS (n = 30), and control subjects (n = 12). BAL fluid proteins were measured using Olink Immune Response Panel proteins from CBD (n = 22) and BeS (n = 22) subjects. Linear models identified features associated with CBD, adjusting for covariation and batch effects. Multiomic integration methods identified correlated features between datasets. We identified 1,546 differentially expressed genes in CBD versus control subjects and 204 in CBD versus BeS. Of the 101 shared transcripts, 24 have significant cis relationships between gene expression and DNA methylation, assessed using expression quantitative trait methylation analysis, including genes not previously identified in CBD. A multiomic model of top DNA methylation and gene expression features demonstrated that the first component separated CBD from other samples and the second component separated control subjects from remaining samples. The top features on component one were enriched for T-lymphocyte function, and the top features on component two were enriched for innate immune signaling. We identified six differentially abundant proteins in CBD versus BeS, with two (SIT1 and SH2D1A) selected as important RNA features in the multiomic model. Our integrated analysis of DNA methylation, gene expression, and proteins in the lung identified multiomic signatures of CBD that differentiated it from BeS and control subjects.
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Affiliation(s)
- Li Li
- Division of Environmental and Occupational Health Sciences, Department of Medicine, and
- Division of Pulmonary and Critical Care Sciences
| | - Iain R. Konigsberg
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, School of Medicine
| | - Maneesh Bhargava
- Pulmonary, Allergy, Critical Care and Sleep, Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Sucai Liu
- Division of Environmental and Occupational Health Sciences, Department of Medicine, and
| | - Kristyn MacPhail
- Division of Environmental and Occupational Health Sciences, Department of Medicine, and
| | - Annyce Mayer
- Division of Environmental and Occupational Health Sciences, Department of Medicine, and
- Department of Environmental and Occupational Health
| | - Elizabeth J. Davidson
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, School of Medicine
| | - Shu-Yi Liao
- Division of Environmental and Occupational Health Sciences, Department of Medicine, and
- Division of Pulmonary and Critical Care Sciences
- Department of Environmental and Occupational Health
| | - Zhe Lei
- Division of Environmental and Occupational Health Sciences, Department of Medicine, and
| | - Peggy M. Mroz
- Division of Environmental and Occupational Health Sciences, Department of Medicine, and
| | - Tasha E. Fingerlin
- Department of Immunology and Genomic Medicine, National Jewish Health, Denver, Colorado
- Department of Biostatistics and Bioinformatics, and
| | - Ivana V. Yang
- Division of Pulmonary and Critical Care Sciences
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, School of Medicine
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado; and
| | - Lisa A. Maier
- Division of Environmental and Occupational Health Sciences, Department of Medicine, and
- Division of Pulmonary and Critical Care Sciences
- Department of Environmental and Occupational Health
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Xu K, Li S, Pandey P, Kang AY, Morimoto LM, Mancuso N, Ma X, Metayer C, Wiemels JL, de Smith AJ. Investigating DNA methylation as a mediator of genetic risk in childhood acute lymphoblastic leukemia. Hum Mol Genet 2022; 31:3741-3756. [PMID: 35717575 PMCID: PMC9616572 DOI: 10.1093/hmg/ddac137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 04/28/2022] [Accepted: 06/13/2022] [Indexed: 11/14/2022] Open
Abstract
Genome-wide association studies have identified a growing number of single nucleotide polymorphisms (SNPs) associated with childhood acute lymphoblastic leukemia (ALL), yet the functional roles of most SNPs are unclear. Multiple lines of evidence suggest that epigenetic mechanisms may mediate the impact of heritable genetic variation on phenotypes. Here, we investigated whether DNA methylation mediates the effect of genetic risk loci for childhood ALL. We performed an epigenome-wide association study (EWAS) including 808 childhood ALL cases and 919 controls from California-based studies using neonatal blood DNA. For differentially methylated CpG positions (DMPs), we next conducted association analysis with 23 known ALL risk SNPs followed by causal mediation analyses addressing the significant SNP-DMP pairs. DNA methylation at CpG cg01139861, in the promoter region of IKZF1, mediated the effects of the intronic IKZF1 risk SNP rs78396808, with the average causal mediation effect (ACME) explaining ~30% of the total effect (ACME P = 0.0031). In analyses stratified by self-reported race/ethnicity, the mediation effect was only significant in Latinos, explaining ~41% of the total effect of rs78396808 on ALL risk (ACME P = 0.0037). Conditional analyses confirmed the presence of at least three independent genetic risk loci for childhood ALL at IKZF1, with rs78396808 unique to non-European populations. We also demonstrated that the most significant DMP in the EWAS, CpG cg13344587 at gene ARID5B (P = 8.61 × 10-10), was entirely confounded by the ARID5B ALL risk SNP rs7090445. Our findings provide new insights into the functional pathways of ALL risk SNPs and the DNA methylation differences associated with risk of childhood ALL.
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Affiliation(s)
- Keren Xu
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90033, USA
| | - Shaobo Li
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90033, USA
| | - Priyatama Pandey
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90033, USA
| | - Alice Y Kang
- School of Public Health, University of California, Berkeley, Berkeley, CA 94704, USA
| | - Libby M Morimoto
- School of Public Health, University of California, Berkeley, Berkeley, CA 94704, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90033, USA
| | - Xiaomei Ma
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT 06510, USA
| | - Catherine Metayer
- School of Public Health, University of California, Berkeley, Berkeley, CA 94704, USA
| | - Joseph L Wiemels
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90033, USA
| | - Adam J de Smith
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90033, USA
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Li W, Zhou R, Sun B, Jin X, Chen Y, Xu X. Prognostic significance of lncRNA AP004608.1 in prostate cancer. Front Oncol 2022; 12:1017635. [PMID: 36249054 PMCID: PMC9556701 DOI: 10.3389/fonc.2022.1017635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 09/12/2022] [Indexed: 12/04/2022] Open
Abstract
This study aimed to screen and determine the value of AP004608.1 expression as a biomarker for Prostate cancer (PCa) survival. We investigated the expression and prognosis of AP004608.1 through bioinformatics analysis. Low AP004608.1 expression predicted favorable Overall survival (OS) and Progression-free survival (PFS) in PCa patients, according to the Cancer Genome Atlas (TCGA) database. Cox regression demonstrated that low AP004608.1 expression were in-dependent biomarkers for OS. Moreover, Gene Expression Omnibus (GEO) database was utilized to verify the prognostic role of AP004608.1 in PCa, and the similar results were reached. A meta-analysis revealed that low AP004608.1 expression was closely relevant to better OS. AP004608.1 could constitute a promising prognostic biomarker, and probably plays an important role in PCa.
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Affiliation(s)
- Wei Li
- Jiangsu Key Laboratory for Pharmacology and Safety Evaluation of Chinese Materia Medica, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China
- Institute of Traditional Chinese medicine (TCM)-Related Comorbid Depression, School of Chinese Medicine & School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
- *Correspondence: Wei Li, ; Xuefen Xu,
| | - Runze Zhou
- Institute of Traditional Chinese medicine (TCM)-Related Comorbid Depression, School of Chinese Medicine & School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Bo Sun
- Institute of Traditional Chinese medicine (TCM)-Related Comorbid Depression, School of Chinese Medicine & School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Xin Jin
- Department of Pharmacy, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Yuan Chen
- Department of Pharmacology, School of Medicine and Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Xuefen Xu
- Department of Pharmacology, School of Medicine and Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing, China
- *Correspondence: Wei Li, ; Xuefen Xu,
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Guo L, Wang W, Song W, Cao H, Tian H, Wang Z, Ren J, Ning F, Zhang D, Duan H. Genome-wide DNA methylation analysis of middle-aged and elderly monozygotic twins with age-related hearing loss in Qingdao, China. Gene 2022; 849:146918. [PMID: 36179964 DOI: 10.1016/j.gene.2022.146918] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 09/20/2022] [Accepted: 09/21/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE To explore the differences in DNA methylation associated with age-related hearing loss in a study of 57 twin pairs from China. DESIGN Monozygotic twins were identified through the Qingdao Twin Registration system. The median age of participants was >50 years. Their hearing thresholds were measured using a multilevel pure-tone audiometry assessment. The pure-tone audiometry was calculated at low frequencies (0.5, 1.0, and 2.0 kHz), speech frequencies (0.5, 1.0, 2.0, and 4.0kHz), and high frequencies (4.0 and 8 kHz). The CpG sites were tested using a linear mixed-effects model, and the function of the cis-regulatory regions and ontological enrichments were predicted using the online Genomic Regions Enrichment of Annotations Tool. The differentially methylated regions were identified using a comb-p python library approach. RESULTS In each of the PTA categories (low-, speech-, high-frequency), age-related hearing loss was detected in 25.9%, 19.3%, and 52.8% of participants. In the low-, speech- and high-frequency categories we identified 18, 42, and 12 individual CpG sites and 6, 11, and 6 differentially methylated regions. The CpG site located near DUSP4 had the strongest association with low- and speech-frequency, while the strongest association with high-frequency was near C21orf58. We identified associations of ALG10 with high-frequency hearing, C3 and LCK with low- and speech-frequency hearing, and GBX2 with low-frequency hearing. Top pathways that may be related to hearing, such as the Notch signaling pathway, were also identified. CONCLUSION Our study is the first of its kind to identify these genes and their associated with DNA methylation may play essential roles in the hearing process. The results of our epigenome-wide association study on twins clarify the complex mechanisms underlying age-related hearing loss.
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Affiliation(s)
- Longzi Guo
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Wanxue Song
- Qingdao Maternal and Child Health and Family Planning Service Center, Qingdao, China
| | - Hainan Cao
- Department of Otorhinolaryngology, Qingdao Municipal Hospital, Qingdao, China
| | - Huimin Tian
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Zhaoguo Wang
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, China
| | - Jifeng Ren
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Feng Ning
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, China.
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Miao R, Dang Q, Cai J, Huang HH, Xie SL, Liang Y. Sparse principal component analysis based on genome network for correcting cell type heterogeneity in epigenome-wide association studies. Med Biol Eng Comput 2022; 60:2601-2618. [DOI: 10.1007/s11517-022-02599-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 04/30/2022] [Indexed: 10/17/2022]
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Desale H, Buekens P, Alger J, Cafferata ML, Harville EW, Herrera C, Truyens C, Dumonteil E. Epigenetic signature of exposure to maternal Trypanosoma cruzi infection in cord blood cells from uninfected newborns. Epigenomics 2022; 14:913-927. [PMID: 36039408 PMCID: PMC9475499 DOI: 10.2217/epi-2022-0153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aims: To assess the epigenetic effects of in utero exposure to maternal Trypanosoma cruzi infection. Methods: We performed an epigenome-wide association study to compare the DNA methylation patterns of umbilical cord blood cells from uninfected babies from chagasic and uninfected mothers. DNA methylation was measured using Infinium EPIC arrays. Results: We identified a differential DNA methylation signature of fetal exposure to maternal T. cruzi infection, in the absence of parasite transmission, with 12 differentially methylated sites in B cells and CD4+ T cells, including eight protein-coding genes. Conclusion: These genes participate in hematopoietic cell differentiation and the immune response and may be involved in immune disorders. They also have been associated with several developmental disorders and syndromes.
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Affiliation(s)
- Hans Desale
- Department of Tropical Medicine, Tulane University School of Public Health & Tropical Medicine & Tulane University Vector-Borne & Infectious Disease Research Center, New Orleans, LA 70112, USA
| | - Pierre Buekens
- Department of Epidemiology, Tulane University School of Public Health & Tropical Medicine, New Orleans, LA 70112, USA
| | - Jackeline Alger
- Instituto de Enfermedades Infecciosas y Parasitologia Antonio Vidal, Tegucigalpa, Honduras.,Ministry of Health, Hospital Escuela, Tegucigalpa, Honduras
| | - Maria Luisa Cafferata
- Unidad de Investigación Clínica y Epidemiológica Montevideo (UNICEM), Hospital de Clínicas, Montevideo, 11600, Uruguay
| | - Emily Wheeler Harville
- Department of Epidemiology, Tulane University School of Public Health & Tropical Medicine, New Orleans, LA 70112, USA
| | - Claudia Herrera
- Department of Tropical Medicine, Tulane University School of Public Health & Tropical Medicine & Tulane University Vector-Borne & Infectious Disease Research Center, New Orleans, LA 70112, USA
| | - Carine Truyens
- Laboratory of Parasitology, Faculty of Medicine, & ULB Center for Research in Immunology (UCRI), Université Libre de Bruxelles, Brussels, Belgium
| | - Eric Dumonteil
- Department of Tropical Medicine, Tulane University School of Public Health & Tropical Medicine & Tulane University Vector-Borne & Infectious Disease Research Center, New Orleans, LA 70112, USA
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Thompson M, Hill BL, Rakocz N, Chiang JN, Geschwind D, Sankararaman S, Hofer I, Cannesson M, Zaitlen N, Halperin E. Methylation risk scores are associated with a collection of phenotypes within electronic health record systems. NPJ Genom Med 2022; 7:50. [PMID: 36008412 PMCID: PMC9411568 DOI: 10.1038/s41525-022-00320-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 07/18/2022] [Indexed: 12/20/2022] Open
Abstract
Inference of clinical phenotypes is a fundamental task in precision medicine, and has therefore been heavily investigated in recent years in the context of electronic health records (EHR) using a large arsenal of machine learning techniques, as well as in the context of genetics using polygenic risk scores (PRS). In this work, we considered the epigenetic analog of PRS, methylation risk scores (MRS), a linear combination of methylation states. We measured methylation across a large cohort (n = 831) of diverse samples in the UCLA Health biobank, for which both genetic and complete EHR data are available. We constructed MRS for 607 phenotypes spanning diagnoses, clinical lab tests, and medication prescriptions. When added to a baseline set of predictive features, MRS significantly improved the imputation of 139 outcomes, whereas the PRS improved only 22 (median improvement for methylation 10.74%, 141.52%, and 15.46% in medications, labs, and diagnosis codes, respectively, whereas genotypes only improved the labs at a median increase of 18.42%). We added significant MRS to state-of-the-art EHR imputation methods that leverage the entire set of medical records, and found that including MRS as a medical feature in the algorithm significantly improves EHR imputation in 37% of lab tests examined (median R2 increase 47.6%). Finally, we replicated several MRS in multiple external studies of methylation (minimum p-value of 2.72 × 10−7) and replicated 22 of 30 tested MRS internally in two separate cohorts of different ethnicity. Our publicly available results and weights show promise for methylation risk scores as clinical and scientific tools.
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Affiliation(s)
- Mike Thompson
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA.
| | - Brian L Hill
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA.
| | - Nadav Rakocz
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA
| | - Jeffrey N Chiang
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Daniel Geschwind
- Institute of Precision Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Sriram Sankararaman
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA.,Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Human Genetics, University of California Los Angeles, Los Angeles, CA, USA
| | - Ira Hofer
- Department of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Maxime Cannesson
- Department of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noah Zaitlen
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
| | - Eran Halperin
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA. .,Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA. .,Department of Human Genetics, University of California Los Angeles, Los Angeles, CA, USA. .,Department of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, CA, USA.
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He D, Chen M, Wang W, Song C, Qin Y. Deconvolution of tumor composition using partially available DNA methylation data. BMC Bioinformatics 2022; 23:355. [PMID: 36002797 PMCID: PMC9400327 DOI: 10.1186/s12859-022-04893-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 08/16/2022] [Indexed: 11/10/2022] Open
Abstract
Background Deciphering proportions of constitutional cell types in tumor tissues is a crucial step for the analysis of tumor heterogeneity and the prediction of response to immunotherapy. In the process of measuring cell population proportions, traditional experimental methods have been greatly hampered by the cost and extensive dropout events. At present, the public availability of large amounts of DNA methylation data makes it possible to use computational methods to predict proportions. Results In this paper, we proposed PRMeth, a method to deconvolve tumor mixtures using partially available DNA methylation data. By adopting an iteratively optimized non-negative matrix factorization framework, PRMeth took DNA methylation profiles of a portion of the cell types in the tissue mixtures (including blood and solid tumors) as input to estimate the proportions of all cell types as well as the methylation profiles of unknown cell types simultaneously. We compared PRMeth with five different methods through three benchmark datasets and the results show that PRMeth could infer the proportions of all cell types and recover the methylation profiles of unknown cell types effectively. Then, applying PRMeth to four types of tumors from The Cancer Genome Atlas (TCGA) database, we found that the immune cell proportions estimated by PRMeth were largely consistent with previous studies and met biological significance. Conclusions Our method can circumvent the difficulty of obtaining complete DNA methylation reference data and obtain satisfactory deconvolution accuracy, which will be conducive to exploring the new directions of cancer immunotherapy. PRMeth is implemented in R and is freely available from GitHub (https://github.com/hedingqin/PRMeth). Supplementary Information The online version contains supplementary material available at 10.1186/s12859-022-04893-7.
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Affiliation(s)
- Dingqin He
- College of Information Technology, Shanghai Ocean University, Hucheng Ring Road, Shanghai, China.,Key Laboratory of Fisheries Information Ministry of Agriculture, Shanghai, China
| | - Ming Chen
- College of Information Technology, Shanghai Ocean University, Hucheng Ring Road, Shanghai, China.,Key Laboratory of Fisheries Information Ministry of Agriculture, Shanghai, China
| | - Wenjuan Wang
- College of Information Technology, Shanghai Ocean University, Hucheng Ring Road, Shanghai, China.,Key Laboratory of Fisheries Information Ministry of Agriculture, Shanghai, China
| | - Chunhui Song
- College of Information Technology, Shanghai Ocean University, Hucheng Ring Road, Shanghai, China.,Key Laboratory of Fisheries Information Ministry of Agriculture, Shanghai, China
| | - Yufang Qin
- College of Information Technology, Shanghai Ocean University, Hucheng Ring Road, Shanghai, China. .,Key Laboratory of Fisheries Information Ministry of Agriculture, Shanghai, China.
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Oberhofer A, Bronkhorst AJ, Uhlig C, Ungerer V, Holdenrieder S. Tracing the Origin of Cell-Free DNA Molecules through Tissue-Specific Epigenetic Signatures. Diagnostics (Basel) 2022; 12:diagnostics12081834. [PMID: 36010184 PMCID: PMC9406971 DOI: 10.3390/diagnostics12081834] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 07/15/2022] [Accepted: 07/25/2022] [Indexed: 12/11/2022] Open
Abstract
All cell and tissue types constantly release DNA fragments into human body fluids by various mechanisms including programmed cell death, accidental cell degradation and active extrusion. Particularly, cell-free DNA (cfDNA) in plasma or serum has been utilized for minimally invasive molecular diagnostics. Disease onset or pathological conditions that lead to increased cell death alter the contribution of different tissues to the total pool of cfDNA. Because cfDNA molecules retain cell-type specific epigenetic features, it is possible to infer tissue-of-origin from epigenetic characteristics. Recent research efforts demonstrated that analysis of, e.g., methylation patterns, nucleosome occupancy, and fragmentomics determined the cell- or tissue-of-origin of individual cfDNA molecules. This novel tissue-of origin-analysis enables to estimate the contributions of different tissues to the total cfDNA pool in body fluids and find tissues with increased cell death (pathologic condition), expanding the portfolio of liquid biopsies towards a wide range of pathologies and early diagnosis. In this review, we summarize the currently available tissue-of-origin approaches and point out the next steps towards clinical implementation.
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Ferroptosis-Related lncRNA for the Establishment of Novel Prognostic Signature and Therapeutic Response Prediction to Endometrial Carcinoma. BIOMED RESEARCH INTERNATIONAL 2022; 2022:2056913. [PMID: 35937391 PMCID: PMC9352484 DOI: 10.1155/2022/2056913] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 06/16/2022] [Accepted: 07/08/2022] [Indexed: 01/07/2023]
Abstract
Background Ferroptosis is a recently described form of intentional cellular damage that is iron-dependent and separate from apoptosis, cellular necrosis, and autophagy. It has been demonstrated to be adequately regulated by long noncoding RNAs (lncRNAs) in various cancers. However, the predictive profile of ferroptosis-related lncRNAs (FRLs) in endometrial carcinoma (EC) is unknown. Herein, FRLs associated with uterine corpus endometrial carcinoma (UCEC) prognosis were screened to predict treatment response in EC. Methods Samples of EC and adjacent normal tissues were obtained from The Cancer Genome Atlas (TCGA) dataset repository. Limma and survival packages in R software were used to screen FRLs associated with the prognosis of EC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) chord and circle plots of FRLs were also plotted. Next, FRLs screened by the least absolute shrinkage and selection operator (LASSO) method were applied to construct and validate a multivariate Cox proportional risk regression model. Nomogram plots were created to forecast the outcome of UCEC patients, and gene set enrichment analysis (GSEA), principal component analysis (PCA), and immunoassays were performed on the prognostic models. Finally, limma, ggpubr, pRRophetic, and ggplot2 programs were used for drug sensitivity analysis of the prognostic models. Results A signature based on nine FRLs (CFAP58-DT, LINC00443, EMSLR, HYI-AS1, ADIRF-AS1, LINC02474, CDKN2B-AS1, LINC01629, and LINC00942) was constructed. The developed FRL prognostic model effectively discriminated UCEC patients into low-risk and high-risk groups. Immunological checkpoints CD80 and CD40 were strongly expressed in the high-risk group. In addition, the nine FRLs were all more expressed in the high-risk group compared to the low-risk group. Conclusion These findings significantly contribute to the understanding of the function of FRLs in UCEC and provide promising therapeutic strategies for UCEC.
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Lee AG, Tignor N, Cowell W, Colicino E, Bozack A, Baccarelli A, Wang P, Wright RJ. Associations between antenatal maternal asthma status and placental DNA methylation. Placenta 2022; 126:184-195. [PMID: 35858526 PMCID: PMC9679966 DOI: 10.1016/j.placenta.2022.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 06/09/2022] [Accepted: 06/17/2022] [Indexed: 11/16/2022]
Abstract
INTRODUCTION Maternal asthma in pregnancy is associated with adverse perinatal and child health outcomes; however, mechanisms are poorly understood. METHODS The PRogramming of Intergenerational Stress Mechanisms (PRISM) prospective pregnancy cohort characterized asthma history during pregnancy via questionnaires and quantified placental DNAm using the Illumina Infinium HumanMethylation450 BeadChip. We performed epigenome-wide association analyses (n = 223) to estimate associations between maternal active or inactive asthma, as compared to never asthma, and placental differentially methylated positions (DMPs) and differentially variable positions (DVPs). Models adjusted for maternal pre-pregnancy body mass index, smoking status, parity, age and education level and child sex. P-values were FDR-adjusted. RESULTS One hundred and fifty-nine (71.3%) pregnant women reported no history of asthma (never asthma), 15 (6.7%) reported inactive, and 49 (22%) reported active antenatal asthma. Women predominantly self-identified as Black/Hispanic Black [88 (39.5%)] and Hispanic/non-Black [42 (18.8%)]. We identified 10 probes at FDR<0.05 and 4 probes at FDR<0.10 characterized by higher variability in maternal active asthma compared to never asthma mapping to GPX3, LHPP, PECAM1, ATAD3C, and ARHGEF4 and 2 probes characterized by lower variation mapping to CHMP4A and C5orf24. Amongst women with inactive asthma, we identified 52 probes, 41 at FDR<0.05 and an additional 11 at FDR <0.10, with higher variability compared to never asthma; BMP4, LHPP, PHYHIPL, and ZSCAN23 were associated with multiple DVPs. No associations were observed with DMPs. DISCUSSION We observed alterations in placental DNAm in women with antenatal asthma, as compared to women without a history of asthma. Further research is needed to understand the impact on fetal development.
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Affiliation(s)
- Alison G Lee
- Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Nicole Tignor
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Whitney Cowell
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Elena Colicino
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Anne Bozack
- Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Andrea Baccarelli
- Environmental Health Sciences, Mailman School of Public Health at Columbia University, New York, NY, USA
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rosalind J Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Fischer MA, Mahajan A, Cabaj M, Kimball TH, Morselli M, Soehalim E, Chapski DJ, Montoya D, Farrell CP, Scovotti J, Bueno CT, Mimila NA, Shemin RJ, Elashoff D, Pellegrini M, Monte E, Vondriska TM. DNA Methylation-Based Prediction of Post-operative Atrial Fibrillation. Front Cardiovasc Med 2022; 9:837725. [PMID: 35620521 PMCID: PMC9127230 DOI: 10.3389/fcvm.2022.837725] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 03/17/2022] [Indexed: 12/14/2022] Open
Abstract
BackgroundAtrial fibrillation (AF) is the most common sustained cardiac arrhythmia and post-operative atrial fibrillation (POAF) is a major healthcare burden, contributing to an increased risk of stroke, kidney failure, heart attack and death. Genetic studies have identified associations with AF, but no molecular diagnostic exists to predict POAF based on pre-operative measurements. Such a tool would be of great value for perioperative planning to improve patient care and reduce healthcare costs. In this pilot study of epigenetic precision medicine in the perioperative period, we carried out bisulfite sequencing to measure DNA methylation status in blood collected from patients prior to cardiac surgery to identify biosignatures of POAF.MethodsWe enrolled 221 patients undergoing cardiac surgery in this prospective observational study. DNA methylation measurements were obtained from blood samples drawn from awake patients prior to surgery. After controlling for clinical and methylation covariates, we analyzed DNA methylation loci in the discovery cohort of 110 patients for association with POAF. We also constructed predictive models for POAF using clinical and DNA methylation data. We subsequently performed targeted analyses of a separate cohort of 101 cardiac surgical patients to measure the methylation status solely of significant methylation loci in the discovery cohort.ResultsA total of 47 patients in the discovery cohort (42.7%) and 43 patients in the validation cohort (42.6%) developed POAF. We identified 12 CpGs that were statistically significant in the discovery cohort after correcting for multiple hypothesis testing. Of these sites, 6 were amenable to targeted bisulfite sequencing and chr16:24640902 was statistically significant in the validation cohort. In addition, the methylation POAF prediction model had an AUC of 0.79 in the validation cohort.ConclusionsWe have identified DNA methylation biomarkers that can predict future occurrence of POAF associated with cardiac surgery. This research demonstrates the use of precision medicine to develop models combining epigenomic and clinical data to predict disease.
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Affiliation(s)
- Matthew A. Fischer
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
- *Correspondence: Matthew A. Fischer
| | - Aman Mahajan
- Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Maximilian Cabaj
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Todd H. Kimball
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Marco Morselli
- Department of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Elizabeth Soehalim
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Douglas J. Chapski
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Dennis Montoya
- Department of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Colin P. Farrell
- Department of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Jennifer Scovotti
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Claudia T. Bueno
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Naomi A. Mimila
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Richard J. Shemin
- Division of Cardiac Surgery, Department of Surgery, University of California, Los Angeles, Los Angeles, CA, United States
| | - David Elashoff
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Matteo Pellegrini
- Department of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Emma Monte
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Thomas M. Vondriska
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Physiology, University of California, Los Angeles, Los Angeles, CA, United States
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Controlling Batch Effect in Epigenome-Wide Association Study. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2022; 2432:73-84. [PMID: 35505208 DOI: 10.1007/978-1-0716-1994-0_6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Methylation data, similar to other omics data, is susceptible to various technical issues that are potentially associated with unexplained or unrelated factors. Any difference in the measurement of DNA methylation, such as laboratory operation and sequencing platform, may lead to batch effects. With the accumulation of large-scale omics data, scientists are making joint efforts to generate and analyze omics data to answer various scientific questions. However, batch effects are inevitable in practice, and careful adjustment is needed. Multiple statistical methods for controlling bias and inflation between batches have been developed either by correcting based on known batch factors or by estimating directly from the output data. In this chapter, we will review and demonstrate several popular methods for batch effect correction and make practical recommendations in epigenome-wide association studies (EWAS).
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