1
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Calanca N, Faldoni FLC, Souza CP, Souza JS, de Souza Alves BE, Soares MBP, Wong DVT, Lima-Junior RCP, Marchi FA, Rainho CA, Rogatto SR. Inflammatory breast cancer microenvironment repertoire based on DNA methylation data deconvolution reveals actionable targets to enhance the treatment efficacy. J Transl Med 2024; 22:735. [PMID: 39103878 DOI: 10.1186/s12967-024-05553-5] [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: 05/17/2024] [Accepted: 07/28/2024] [Indexed: 08/07/2024] Open
Abstract
BACKGROUND Although the clinical signs of inflammatory breast cancer (IBC) resemble acute inflammation, the role played by infiltrating immune and stromal cells in this aggressive disease is uncharted. The tumor microenvironment (TME) presents molecular alterations, such as epimutations, prior to morphological abnormalities. These changes affect the distribution and the intricate communication between the TME components related to cancer prognosis and therapy response. Herein, we explored the global DNA methylation profile of IBC and surrounding tissues to estimate the microenvironment cellular composition and identify epigenetically dysregulated markers. METHODS We used the HiTIMED algorithm to deconvolve the bulk DNA methylation data of 24 IBC and six surrounding non-tumoral tissues (SNT) (GSE238092) and determine their cellular composition. The prognostic relevance of cell types infiltrating IBC and their relationship with clinicopathological variables were investigated. CD34 (endothelial cell marker) and CD68 (macrophage marker) immunofluorescence staining was evaluated in an independent set of 17 IBC and 16 non-IBC samples. RESULTS We found lower infiltration of endothelial, stromal, memory B, dendritic, and natural killer cells in IBC than in SNT samples. Higher endothelial cell (EC) and stromal cell content were related to better overall survival. EC proportions positively correlated with memory B and memory CD8+ T infiltration in IBC. Immune and EC markers exhibited distinct DNA methylation profiles between IBC and SNT samples, revealing hypermethylated regions mapped to six genes (CD40, CD34, EMCN, HLA-G, PDPN, and TEK). We identified significantly higher CD34 and CD68 protein expression in IBC compared to non-IBC. CONCLUSIONS Our findings underscored cell subsets that distinguished patients with better survival and dysregulated markers potentially actionable through combinations of immunotherapy and epigenetic drugs.
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Affiliation(s)
- Naiade Calanca
- Department of Clinical Genetics, University Hospital of Southern Denmark, Beriderbakken 4, Vejle, DK, 7100, Denmark
- Department of Chemical and Biological Sciences, Institute of Biosciences, São Paulo State University (UNESP), Botucatu, SP, 18618-689, Brazil
| | - Flavia Lima Costa Faldoni
- Department of Clinical Genetics, University Hospital of Southern Denmark, Beriderbakken 4, Vejle, DK, 7100, Denmark
| | - Cristiano Pádua Souza
- Medical Oncology Department, Barretos Cancer Hospital, Pio XII Foundation, Barretos, SP, 14784-400, Brazil
| | | | - Bianca Elen de Souza Alves
- Department of Physiology and Pharmacology, Drug Research and Development Center (NPDM), Faculty of Medicine, Federal University of Ceará, Fortaleza, 60430-270, Brazil
| | - Milena Botelho Pereira Soares
- Health Technology Institute, SENAI CIMATEC, Salvador, BA, 41650-010, Brazil
- Gonçalo Moniz Institute, FIOCRUZ, Salvador, BA, 40296-710, Brazil
| | - Deysi Viviana Tenazoa Wong
- Department of Physiology and Pharmacology, Drug Research and Development Center (NPDM), Faculty of Medicine, Federal University of Ceará, Fortaleza, 60430-270, Brazil
| | - Roberto César Pereira Lima-Junior
- Department of Physiology and Pharmacology, Drug Research and Development Center (NPDM), Faculty of Medicine, Federal University of Ceará, Fortaleza, 60430-270, Brazil
| | - Fabio Albuquerque Marchi
- Department of Head and Neck Surgery, University of São Paulo Medical School, São Paulo, SP, 05402-000, Brazil
- Center for Translational Research in Oncology, Cancer Institute of the State of São Paulo (ICESP), São Paulo, SP, 01246-000, Brazil
| | - Claudia Aparecida Rainho
- Department of Chemical and Biological Sciences, Institute of Biosciences, São Paulo State University (UNESP), Botucatu, SP, 18618-689, Brazil
| | - Silvia Regina Rogatto
- Department of Clinical Genetics, University Hospital of Southern Denmark, Beriderbakken 4, Vejle, DK, 7100, Denmark.
- Institute of Regional Health Research, University of Southern Denmark, Odense, 5000, Denmark.
- Botucatu Medical School Hospital, São Paulo State University (UNESP), Botucatu, SP, Brazil.
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2
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Alsup A, Nissen E, Salas LA, Molinaro AM, Reiner A, Liu S, Madsen TE, Liu L, Auer PL, Christensen BC, Wiencke JK, Kelsey KT, Koestler DC. An assessment of compositional methods for the analysis of DNA methylation-based deconvolution estimates. Epigenomics 2024:1-14. [PMID: 39093129 DOI: 10.1080/17501911.2024.2379242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 07/09/2024] [Indexed: 08/04/2024] Open
Abstract
DNA methylation (DNAm)-based deconvolution estimates contain relative data, forming a composition, that standard methods (testing directly on cell proportions) are ill-suited to handle. In this study we examined the performance of an alternative method, analysis of compositions of microbiomes (ANCOM), for the analysis of DNAm-based deconvolution estimates. We performed two different simulation studies comparing ANCOM to a standard approach (two sample t-test performed directly on cell proportions) and analyzed a real-world data from the Women's Health Initiative to evaluate the applicability of ANCOM to DNAm-based deconvolution estimates. Our findings indicate that ANCOM can effectively account for the compositional nature of DNAm-based deconvolution estimates. ANCOM adequately controls the false discovery rate while maintaining statistical power comparable to that of standard methods.
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Affiliation(s)
- Alexander Alsup
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Emily Nissen
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Alexander Reiner
- Division of Public Health Science, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Simin Liu
- Department of Emergency Medicine, Alpert Medical School of Brown University and Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02903, USA
| | - Tracy E Madsen
- Department of Emergency Medicine, Alpert Medical School of Brown University and Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02903, USA
| | - Longjian Liu
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA 19104, USA
| | - Paul L Auer
- Division of Biostatistics, Institute for Health & Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - John K Wiencke
- Department of Neurological Surgery, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Karl T Kelsey
- Department of Emergency Medicine, Alpert Medical School of Brown University and Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02903, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
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3
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Marttila S, Rajić S, Ciantar J, Mak JKL, Junttila IS, Kummola L, Hägg S, Raitoharju E, Kananen L. Biological aging of different blood cell types. GeroScience 2024:10.1007/s11357-024-01287-w. [PMID: 39060678 DOI: 10.1007/s11357-024-01287-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
Biological age (BA) captures detrimental age-related changes. The best-known and most-used BA indicators include DNA methylation-based epigenetic clocks and telomere length (TL). The most common biological sample material for epidemiological aging studies, whole blood, is composed of different cell types. We aimed to compare differences in BAs between blood cell types and assessed the BA indicators' cell type-specific associations with chronological age (CA). An analysis of DNA methylation-based BA indicators, including TL, methylation level at cg16867657 in ELOVL2, as well as the Hannum, Horvath, DNAmPhenoAge, and DunedinPACE epigenetic clocks, was performed on 428 biological samples of 12 blood cell types. BA values were different in the majority of the pairwise comparisons between cell types, as well as in comparison to whole blood (p < 0.05). DNAmPhenoAge showed the largest cell type differences, up to 44.5 years and DNA methylation-based TL showed the lowest differences. T cells generally had the "youngest" BA values, with differences across subsets, whereas monocytes had the "oldest" values. All BA indicators, except DunedinPACE, strongly correlated with CA within a cell type. Some differences such as DNAmPhenoAge-difference between naïve CD4 + T cells and monocytes were constant regardless of the blood donor's CA (range 20-80 years), while for DunedinPACE they were not. In conclusion, DNA methylation-based indicators of BA exhibit cell type-specific characteristics. Our results have implications for understanding the molecular mechanisms underlying epigenetic clocks and underscore the importance of considering cell composition when utilizing them as indicators for the success of aging interventions.
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Affiliation(s)
- Saara Marttila
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
- Gerontology Research Center, Tampere University, Tampere, Finland.
- Tays Research Services, Wellbeing Services County of Pirkanmaa, Tampere University Hospital, Tampere, Finland.
| | - Sonja Rajić
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Joanna Ciantar
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Ilkka S Junttila
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories, Tampere, Finland
- Northern Finland Laboratory Centre (NordLab), Oulu, Finland
- Research Unit of Biomedicine, University of Oulu, Oulu, Finland
| | - Laura Kummola
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Emma Raitoharju
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Tays Research Services, Wellbeing Services County of Pirkanmaa, Tampere University Hospital, Tampere, Finland
| | - Laura Kananen
- Gerontology Research Center, Tampere University, Tampere, Finland.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
- Faculty of Social Sciences (Health Sciences), Tampere University, Tampere, Finland.
- Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institute, Stockholm, Sweden.
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4
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Nguyen TH, Doan NNT, Tran TH, Huynh LAK, Doan PL, Nguyen THH, Nguyen VTC, Nguyen GTH, Nguyen HN, Giang H, Tran LS, Phan MD. Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks. J Transl Med 2024; 22:618. [PMID: 38961476 PMCID: PMC11223394 DOI: 10.1186/s12967-024-05416-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: 01/03/2024] [Accepted: 06/19/2024] [Indexed: 07/05/2024] Open
Abstract
BACKGROUND Cell free DNA (cfDNA)-based assays hold great potential in detecting early cancer signals yet determining the tissue-of-origin (TOO) for cancer signals remains a challenging task. Here, we investigated the contribution of a methylation atlas to TOO detection in low depth cfDNA samples. METHODS We constructed a tumor-specific methylation atlas (TSMA) using whole-genome bisulfite sequencing (WGBS) data from five types of tumor tissues (breast, colorectal, gastric, liver and lung cancer) and paired white blood cells (WBC). TSMA was used with a non-negative least square matrix factorization (NNLS) deconvolution algorithm to identify the abundance of tumor tissue types in a WGBS sample. We showed that TSMA worked well with tumor tissue but struggled with cfDNA samples due to the overwhelming amount of WBC-derived DNA. To construct a model for TOO, we adopted the multi-modal strategy and used as inputs the combination of deconvolution scores from TSMA with other features of cfDNA. RESULTS Our final model comprised of a graph convolutional neural network using deconvolution scores and genome-wide methylation density features, which achieved an accuracy of 69% in a held-out validation dataset of 239 low-depth cfDNA samples. CONCLUSIONS In conclusion, we have demonstrated that our TSMA in combination with other cfDNA features can improve TOO detection in low-depth cfDNA samples.
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Affiliation(s)
| | | | - Trung Hieu Tran
- Medical Genetics Institute, Gene Solutions, Ho Chi Minh, Vietnam
| | - Le Anh Khoa Huynh
- Medical Genetics Institute, Gene Solutions, Ho Chi Minh, Vietnam
- Department of Biostatistics, School of Medicine, Virginia Commonwealth University, Richmond, USA
| | - Phuoc Loc Doan
- Medical Genetics Institute, Gene Solutions, Ho Chi Minh, Vietnam
| | | | | | | | | | - Hoa Giang
- Medical Genetics Institute, Gene Solutions, Ho Chi Minh, Vietnam
| | - Le Son Tran
- Medical Genetics Institute, Gene Solutions, Ho Chi Minh, Vietnam
| | - Minh Duy Phan
- Medical Genetics Institute, Gene Solutions, Ho Chi Minh, Vietnam.
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5
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Azuma I, Mizuno T, Kusuhara H. GLDADec: marker-gene guided LDA modeling for bulk gene expression deconvolution. Brief Bioinform 2024; 25:bbae315. [PMID: 38982642 PMCID: PMC11233176 DOI: 10.1093/bib/bbae315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 05/21/2024] [Accepted: 06/14/2024] [Indexed: 07/11/2024] Open
Abstract
Inferring cell type proportions from bulk transcriptome data is crucial in immunology and oncology. Here, we introduce guided LDA deconvolution (GLDADec), a bulk deconvolution method that guides topics using cell type-specific marker gene names to estimate topic distributions for each sample. Through benchmarking using blood-derived datasets, we demonstrate its high estimation performance and robustness. Moreover, we apply GLDADec to heterogeneous tissue bulk data and perform comprehensive cell type analysis in a data-driven manner. We show that GLDADec outperforms existing methods in estimation performance and evaluate its biological interpretability by examining enrichment of biological processes for topics. Finally, we apply GLDADec to The Cancer Genome Atlas tumor samples, enabling subtype stratification and survival analysis based on estimated cell type proportions, thus proving its practical utility in clinical settings. This approach, utilizing marker gene names as partial prior information, can be applied to various scenarios for bulk data deconvolution. GLDADec is available as an open-source Python package at https://github.com/mizuno-group/GLDADec.
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Affiliation(s)
- Iori Azuma
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1, Bunkyo-ku 113-0033, Japan
| | - Tadahaya Mizuno
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1, Bunkyo-ku 113-0033, Japan
| | - Hiroyuki Kusuhara
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1, Bunkyo-ku 113-0033, Japan
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6
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Campbell TL, Xie LY, Johnson RH, Hultman CM, van den Oord EJCG, Aberg KA. Investigating neonatal health risk variables through cell-type specific methylome-wide association studies. Clin Epigenetics 2024; 16:69. [PMID: 38778395 PMCID: PMC11112760 DOI: 10.1186/s13148-024-01681-3] [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: 11/06/2023] [Accepted: 05/15/2024] [Indexed: 05/25/2024] Open
Abstract
Adverse neonatal outcomes are a prevailing risk factor for both short- and long-term mortality and morbidity in infants. Given the importance of these outcomes, refining their assessment is paramount for improving prevention and care. Here we aim to enhance the assessment of these often correlated and multifaceted neonatal outcomes. To achieve this, we employ factor analysis to identify common and unique effects and further confirm these effects using criterion-related validity testing. This validation leverages methylome-wide profiles from neonatal blood. Specifically, we investigate nine neonatal health risk variables, including gestational age, Apgar score, three indicators of body size, jaundice, birth diagnosis, maternal preeclampsia, and maternal age. The methylomic profiles used for this research capture data from nearly all 28 million methylation sites in human blood, derived from the blood spot collected from 333 neonates, within 72 h post-birth. Our factor analysis revealed two common factors, size factor, that captured the shared effects of weight, head size, height, and gestational age and disease factor capturing the orthogonal shared effects of gestational age, combined with jaundice and birth diagnosis. To minimize false positives in the validation studies, validation was limited to variables with significant cumulative association as estimated through an in-sample replication procedure. This screening resulted in that the two common factors and the unique effects for gestational age, jaundice and Apgar were further investigated with full-scale cell-type specific methylome-wide association analyses. Highly significant, cell-type specific, associations were detected for both common effect factors and for Apgar. Gene Ontology analyses revealed multiple significant biologically relevant terms for the five fully investigated neonatal health risk variables. Given the established links between adverse neonatal outcomes and both immediate and long-term health, the distinct factor effects (representing the common and unique effects of the risk variables) and their biological profiles confirmed in our work, suggest their potential role as clinical biomarkers for assessing health risks and enhancing personalized care.
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Affiliation(s)
- Thomas L Campbell
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, 1112 East Clay Street, P. O. Box 980533, Richmond, VA, 23298-0581, USA
| | - Lin Y Xie
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, 1112 East Clay Street, P. O. Box 980533, Richmond, VA, 23298-0581, USA
| | - Ralen H Johnson
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, 1112 East Clay Street, P. O. Box 980533, Richmond, VA, 23298-0581, USA
| | - Christina M Hultman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Edwin J C G van den Oord
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, 1112 East Clay Street, P. O. Box 980533, Richmond, VA, 23298-0581, USA
| | - Karolina A Aberg
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, 1112 East Clay Street, P. O. Box 980533, Richmond, VA, 23298-0581, USA.
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7
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Lee MK, Zhang Z, Sehgal K, Butler R, Stolrow H, Ramush G, Shirai K, Koestler DC, Salas LA, Wiencke JK, Haddad R, Kelsey KT, Christensen BC. Immunomethylomic profiles of long-term head and neck squamous cell carcinoma survivors on immune checkpoint inhibitors. Epigenomics 2024:1-9. [PMID: 38869472 DOI: 10.1080/17501911.2024.2343274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Accepted: 04/11/2024] [Indexed: 06/14/2024] Open
Abstract
Aim: This study addresses the challenge of predicting the response of head and neck squamous cell carcinoma (HNSCC) patients to immunotherapy. Methods: Using DNA methylation cytometry, we analyzed the immune profiles of six HNSCC patients who showed a positive response to immunotherapy over a year without disease progression. Results: There was an initial increase in CD8 T memory cells and natural killer cells during the first four cycles of immunotherapy, which then returned to baseline levels after a year. Baseline CD8 T cell levels were lower in HNSCC immunotherapy responders but became similar to those in healthy subjects after immunotherapy. Conclusion: These findings suggest that monitoring fluctuations in immune profiles could potentially identify biomarkers for immunotherapy response in HNSCC patients.
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Affiliation(s)
- Min Kyung Lee
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03755, USA
| | - Ze Zhang
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03755, USA
| | - Kartik Sehgal
- Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA 02215, USA
| | - Rondi Butler
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02903, USA
- Department of Pathology & Laboratory Medicine, Brown University School of Medicine, Providence, RI 02903, USA
| | - Hannah Stolrow
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03755, USA
| | - Geat Ramush
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02903, USA
- Department of Pathology & Laboratory Medicine, Brown University School of Medicine, Providence, RI 02903, USA
| | - Keisuke Shirai
- Department of Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH 03766, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66103, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03755, USA
| | - John K Wiencke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Robert Haddad
- Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA 02215, USA
| | - Karl T Kelsey
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02903, USA
- Department of Pathology & Laboratory Medicine, Brown University School of Medicine, Providence, RI 02903, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03755, USA
- Department of Molecular & Systems Biology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03755,USA
- Department of Community & Family Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH 03755, USA
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8
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De Ridder K, Che H, Leroy K, Thienpont B. Benchmarking of methods for DNA methylome deconvolution. Nat Commun 2024; 15:4134. [PMID: 38755121 PMCID: PMC11099101 DOI: 10.1038/s41467-024-48466-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: 10/20/2023] [Accepted: 04/30/2024] [Indexed: 05/18/2024] Open
Abstract
Defining the number and abundance of different cell types in tissues is important for understanding disease mechanisms as well as for diagnostic and prognostic purposes. Typically, this is achieved by immunohistological analyses, cell sorting, or single-cell RNA-sequencing. Alternatively, cell-specific DNA methylome information can be leveraged to deconvolve cell fractions from a bulk DNA mixture. However, comprehensive benchmarking of deconvolution methods and modalities was not yet performed. Here we evaluate 16 deconvolution algorithms, developed either specifically for DNA methylome data or more generically. We assess the performance of these algorithms, and the effect of normalization methods, while modeling variables that impact deconvolution performance, including cell abundance, cell type similarity, reference panel size, method for methylome profiling (array or sequencing), and technical variation. We observe differences in algorithm performance depending on each these variables, emphasizing the need for tailoring deconvolution analyses. The complexity of the reference, marker selection method, number of marker loci and, for sequencing-based assays, sequencing depth have a marked influence on performance. By developing handles to select the optimal analysis configuration, we provide a valuable source of information for studies aiming to deconvolve array- or sequencing-based methylation data.
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Affiliation(s)
- Kobe De Ridder
- Laboratory for Functional Epigenetics, Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium
| | - Huiwen Che
- Laboratory for Functional Epigenetics, Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium
| | - Kaat Leroy
- Laboratory for Functional Epigenetics, Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium
| | - Bernard Thienpont
- Laboratory for Functional Epigenetics, Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium.
- KU Leuven Institute for Single Cell Omics (LISCO), KU Leuven, 3000, Leuven, Belgium.
- KU Leuven Cancer Institute (LKI), KU Leuven, 3000, Leuven, Belgium.
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9
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Semancik CS, Zhao N, Koestler DC, Boerwinkle E, Bressler J, Buchsbaum RJ, Kelsey KT, Platz EA, Michaud DS. DNA Methylation-Derived Immune Cell Proportions and Cancer Risk, Including Lung Cancer, in Black Participants. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.09.24307118. [PMID: 38766207 PMCID: PMC11100922 DOI: 10.1101/2024.05.09.24307118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Prior cohort studies assessing cancer risk based on immune cell subtype profiles have predominantly focused on White populations. This limitation obscures vital insights into how cancer risk varies across race. Immune cell subtype proportions were estimated using deconvolution based on leukocyte DNA methylation markers from blood samples collected at baseline on participants without cancer in the Atherosclerosis Risk in Communities (ARIC) Study. Over a mean of 17.5 years of follow-up, 668 incident cancers were diagnosed in 2,467 Black participants. Cox proportional hazards regression was used to examine immune cell subtype proportions and overall cancer incidence and site-specific incidence (lung, breast, and prostate cancers). Higher T regulatory cell proportions were associated with statistically significantly higher lung cancer risk (hazard ratio = 1.22, 95% confidence interval = 1.06-1.41 per percent increase). Increased memory B cell proportions were associated with significantly higher risk of prostate cancer (1.17, 1.04-1.33) and all cancers (1.13, 1.05-1.22). Increased CD8+ naïve cell proportions were associated with significantly lower risk of all cancers in participants ≥55 years (0.91, 0.83-0.98). Other immune cell subtypes did not display statistically significant associations with cancer risk. These results in Black participants align closely with prior findings in largely White populations. Findings from this study could help identify those at high cancer risk and outline risk stratifying to target patients for cancer screening, prevention, and other interventions. Further studies should assess these relationships in other cancer types, better elucidate the interplay of B cells in cancer risk, and identify biomarkers for personalized risk stratification.
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Affiliation(s)
- Christopher S. Semancik
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Naisi Zhao
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Devin C. Koestler
- The University of Kansas Cancer Center, Kansas City, KS, USA
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Karl T. Kelsey
- Department of Epidemiology, Brown University, Providence, RI, USA
- Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA
| | - Elizabeth A. Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA
| | - Dominique S. Michaud
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
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10
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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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11
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Stanley KE, Jatsenko T, Tuveri S, Sudhakaran D, Lannoo L, Van Calsteren K, de Borre M, Van Parijs I, Van Coillie L, Van Den Bogaert K, De Almeida Toledo R, Lenaerts L, Tejpar S, Punie K, Rengifo LY, Vandenberghe P, Thienpont B, Vermeesch JR. Cell type signatures in cell-free DNA fragmentation profiles reveal disease biology. Nat Commun 2024; 15:2220. [PMID: 38472221 PMCID: PMC10933257 DOI: 10.1038/s41467-024-46435-0] [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: 08/10/2023] [Accepted: 02/21/2024] [Indexed: 03/14/2024] Open
Abstract
Circulating cell-free DNA (cfDNA) fragments have characteristics that are specific to the cell types that release them. Current methods for cfDNA deconvolution typically use disease tailored marker selection in a limited number of bulk tissues or cell lines. Here, we utilize single cell transcriptome data as a comprehensive cellular reference set for disease-agnostic cfDNA cell-of-origin analysis. We correlate cfDNA-inferred nucleosome spacing with gene expression to rank the relative contribution of over 490 cell types to plasma cfDNA. In 744 healthy individuals and patients, we uncover cell type signatures in support of emerging disease paradigms in oncology and prenatal care. We train predictive models that can differentiate patients with colorectal cancer (84.7%), early-stage breast cancer (90.1%), multiple myeloma (AUC 95.0%), and preeclampsia (88.3%) from matched controls. Importantly, our approach performs well in ultra-low coverage cfDNA datasets and can be readily transferred to diverse clinical settings for the expansion of liquid biopsy.
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Affiliation(s)
- Kate E Stanley
- Department of Human Genetics, Laboratory for Cytogenetics and Genome Research, KU Leuven, Leuven, Belgium
- Department of Biosciences and Nutrition, Karolinska Institute, Huddinge, Sweden
| | - Tatjana Jatsenko
- Department of Human Genetics, Laboratory for Cytogenetics and Genome Research, KU Leuven, Leuven, Belgium
| | - Stefania Tuveri
- Department of Human Genetics, Laboratory for Cytogenetics and Genome Research, KU Leuven, Leuven, Belgium
| | - Dhanya Sudhakaran
- Department of Human Genetics, Laboratory for Cytogenetics and Genome Research, KU Leuven, Leuven, Belgium
| | - Lore Lannoo
- Department of Gynecology and Obstetrics, University Hospitals Leuven, Leuven, Belgium
| | - Kristel Van Calsteren
- Department of Gynecology and Obstetrics, University Hospitals Leuven, Leuven, Belgium
| | - Marie de Borre
- Department of Human Genetics, Laboratory for Functional Epigenetics, KU Leuven, Leuven, Belgium
| | - Ilse Van Parijs
- Center for Human Genetics, University Hospitals Leuven, Leuven, Belgium
| | - Leen Van Coillie
- Center for Human Genetics, University Hospitals Leuven, Leuven, Belgium
| | | | | | - Liesbeth Lenaerts
- Department of Oncology, Gynecological Oncology, KU Leuven, Leuven, Belgium
| | - Sabine Tejpar
- Department of Oncology, Molecular Digestive Oncology, KU Leuven, Leuven, Belgium
| | - Kevin Punie
- Multidisciplinary Breast Centre, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium
| | - Laura Y Rengifo
- Department of Human Genetics, Laboratory of Genetics of Malignant Diseases, KU Leuven, Leuven, Belgium
| | - Peter Vandenberghe
- Department of Human Genetics, Laboratory of Genetics of Malignant Diseases, KU Leuven, Leuven, Belgium
- Department of Hematology, University Hospitals Leuven, Leuven, Belgium
| | - Bernard Thienpont
- Department of Human Genetics, Laboratory for Functional Epigenetics, KU Leuven, Leuven, Belgium
| | - Joris Robert Vermeesch
- Department of Human Genetics, Laboratory for Cytogenetics and Genome Research, KU Leuven, Leuven, Belgium.
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12
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Zhang X, Hu Y, Vandenhoudt RE, Yan C, Marconi VC, Cohen MH, Wang Z, Justice AC, Aouizerat BE, Xu K. Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts. PLoS Pathog 2024; 20:e1012063. [PMID: 38466776 PMCID: PMC10957090 DOI: 10.1371/journal.ppat.1012063] [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: 10/11/2023] [Revised: 03/21/2024] [Accepted: 02/20/2024] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND Epigenome-wide association studies (EWAS) have identified CpG sites associated with HIV infection in blood cells in bulk, which offer limited knowledge of cell-type specific methylation patterns associated with HIV infection. In this study, we aim to identify differentially methylated CpG sites for HIV infection in immune cell types: CD4+ T-cells, CD8+ T-cells, B cells, Natural Killer (NK) cells, and monocytes. METHODS Applying a computational deconvolution method, we performed a cell-type based EWAS for HIV infection in three independent cohorts (Ntotal = 1,382). DNA methylation in blood or in peripheral blood mononuclear cells (PBMCs) was profiled by an array-based method and then deconvoluted by Tensor Composition Analysis (TCA). The TCA-computed CpG methylation in each cell type was first benchmarked by bisulfite DNA methylation capture sequencing in a subset of the samples. Cell-type EWAS of HIV infection was performed in each cohort separately and a meta-EWAS was conducted followed by gene set enrichment analysis. RESULTS The meta-analysis unveiled a total of 2,021 cell-type unique significant CpG sites for five inferred cell types. Among these inferred cell-type unique CpG sites, the concordance rate in the three cohorts ranged from 96% to 100% in each cell type. Cell-type level meta-EWAS unveiled distinct patterns of HIV-associated differential CpG methylation, where 74% of CpG sites were unique to individual cell types (false discovery rate, FDR <0.05). CD4+ T-cells had the largest number of unique HIV-associated CpG sites (N = 1,624) compared to any other cell type. Genes harboring significant CpG sites are involved in immunity and HIV pathogenesis (e.g. CD4+ T-cells: NLRC5, CX3CR1, B cells: IFI44L, NK cells: IL12R, monocytes: IRF7), and in oncogenesis (e.g. CD4+ T-cells: BCL family, PRDM16, monocytes: PRDM16, PDCD1LG2). HIV-associated CpG sites were enriched among genes involved in HIV pathogenesis and oncogenesis that were enriched among interferon-α and -γ, TNF-α, inflammatory response, and apoptotic pathways. CONCLUSION Our findings uncovered computationally inferred cell-type specific modifications in the host epigenome for people with HIV that contribute to the growing body of evidence regarding HIV pathogenesis.
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Affiliation(s)
- Xinyu Zhang
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, United States of America
- VA Connecticut Healthcare System, West Haven, Connecticut, United States of America
| | - Ying Hu
- Center for Biomedical Information and Information Technology, National Cancer Institute, Rockville, Maryland, United States of America
| | - Ral E. Vandenhoudt
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, United States of America
- VA Connecticut Healthcare System, West Haven, Connecticut, United States of America
| | - Chunhua Yan
- Center for Biomedical Information and Information Technology, National Cancer Institute, Rockville, Maryland, United States of America
| | - Vincent C. Marconi
- Division of Infectious Diseases, Emory University School of Medicine and Department of Global Health, Rollins School of Public Health, Emory University, Georgia, United States of America
- Atlanta Veterans Affairs Healthcare System, Decatur, Georgia, United States of America
| | - Mardge H. Cohen
- Department of Medicine, Stroger Hospital of Cook County, Chicago, Illinois, United States of America
| | - Zuoheng Wang
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Amy C. Justice
- VA Connecticut Healthcare System, West Haven, Connecticut, United States of America
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Bradley E. Aouizerat
- Translational Research Center, College of Dentistry, New York University, New York, New York, United States of America
- Department of Oral and Maxillofacial Surgery, College of Dentistry, New York University, New York, New York, United States of America
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, United States of America
- VA Connecticut Healthcare System, West Haven, Connecticut, United States of America
- Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, Connecticut, United States of America
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13
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Zhang Z, Reynolds SR, Stolrow HG, Chen J, Christensen BC, Salas LA. Deciphering the role of immune cell composition in epigenetic age acceleration: Insights from cell-type deconvolution applied to human blood epigenetic clocks. Aging Cell 2024; 23:e14071. [PMID: 38146185 PMCID: PMC10928575 DOI: 10.1111/acel.14071] [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: 08/17/2023] [Revised: 12/04/2023] [Accepted: 12/05/2023] [Indexed: 12/27/2023] Open
Abstract
Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health-related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA. We investigated associations of 12 immune cell types measured by cell-type deconvolution with EAA predicted by six widely-used DNA methylation clocks in data from >10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis. Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research. Our detailed map of immune cell type contributions serves as a resource for studies utilizing epigenetic clocks across diverse research fields, including aging-related diseases, precision medicine, and therapeutic interventions.
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Affiliation(s)
- Ze Zhang
- Department of EpidemiologyGeisel School of Medicine at DartmouthLebanonNew HampshireUSA
- Dartmouth Cancer CenterDartmouth‐Hitchcock Medical CenterLebanonNew HampshireUSA
- Quantitative Biomedical Sciences ProgramGuarini School of Graduate and Advanced StudiesHanoverNew HampshireUSA
| | - Samuel R. Reynolds
- Department of EpidemiologyGeisel School of Medicine at DartmouthLebanonNew HampshireUSA
| | - Hannah G. Stolrow
- Department of EpidemiologyGeisel School of Medicine at DartmouthLebanonNew HampshireUSA
- Dartmouth Cancer CenterDartmouth‐Hitchcock Medical CenterLebanonNew HampshireUSA
| | - Ji‐Qing Chen
- Department of EpidemiologyGeisel School of Medicine at DartmouthLebanonNew HampshireUSA
- Molecular and Cellular Biology ProgramGuarini School of Graduate and Advanced StudiesHanoverNew HampshireUSA
| | - Brock C. Christensen
- Department of EpidemiologyGeisel School of Medicine at DartmouthLebanonNew HampshireUSA
- Dartmouth Cancer CenterDartmouth‐Hitchcock Medical CenterLebanonNew HampshireUSA
- Quantitative Biomedical Sciences ProgramGuarini School of Graduate and Advanced StudiesHanoverNew HampshireUSA
- Molecular and Cellular Biology ProgramGuarini School of Graduate and Advanced StudiesHanoverNew HampshireUSA
| | - Lucas A. Salas
- Department of EpidemiologyGeisel School of Medicine at DartmouthLebanonNew HampshireUSA
- Dartmouth Cancer CenterDartmouth‐Hitchcock Medical CenterLebanonNew HampshireUSA
- Quantitative Biomedical Sciences ProgramGuarini School of Graduate and Advanced StudiesHanoverNew HampshireUSA
- Molecular and Cellular Biology ProgramGuarini School of Graduate and Advanced StudiesHanoverNew HampshireUSA
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14
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Kresovich JK, O’Brien KM, Xu Z, Weinberg CR, Sandler DP, Taylor JA. Circulating Leukocyte Subsets Before and After a Breast Cancer Diagnosis and Therapy. JAMA Netw Open 2024; 7:e2356113. [PMID: 38358741 PMCID: PMC10870180 DOI: 10.1001/jamanetworkopen.2023.56113] [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: 10/24/2023] [Accepted: 12/21/2023] [Indexed: 02/16/2024] Open
Abstract
Importance Changes in leukocyte composition often precede chronic disease onset. Patients with a history of breast cancer (hereinafter referred to as breast cancer survivors) are at increased risk for subsequent chronic diseases, but the long-term changes in peripheral leukocyte composition following a breast cancer diagnosis and treatment remain unknown. Objective To examine longitudinal changes in peripheral leukocyte composition in women who did and did not develop breast cancer and identify whether differences in breast cancer survivors were associated with specific treatments. Design, Setting, and Participants In this prospective cohort study, paired blood samples were collected from 2315 women enrolled in The Sister Study, a US-nationwide prospective cohort study of 50 884 women, at baseline (July 2003 to March 2009) and follow-up (October 2013 to March 2015) home visits, with a mean (SD) follow-up interval of 7.6 (1.4) years. By design, approximately half of the included women had been diagnosed and treated for breast cancer after enrollment and before the second blood draw. A total of 410 women were included in the present study, including 185 breast cancer survivors and 225 who remained free of breast cancer over a comparable follow-up period. Data were analyzed from April 21 to September 9, 2022. Exposures Breast cancer status and, among breast cancer survivors, cancer treatment type (chemotherapy, radiotherapy, endocrine therapy, or surgery). Main Outcomes and Measures Blood DNA methylation data were generated in 2019 using a genome-wide methylation screening tool and deconvolved to estimate percentages of 12 circulating leukocyte subsets. Results Of the 410 women included in the analysis, the mean (SD) age at enrollment was 56 (9) years. Compared with breast cancer-free women, breast cancer survivors had decreased percentages of circulating eosinophils (-0.45% [95% CI, -0.87% to -0.03%]; P = .03), total CD4+ helper T cells (-1.50% [95% CI, -2.56% to -0.44%]; P = .01), and memory B cells (-0.22% [95% CI, -0.34% to -0.09%]; P = .001) and increased percentages of circulating naive B cells (0.46% [95% CI, 0.17%-0.75%]; P = .002). In breast cancer survivor-only analyses, radiotherapy was associated with decreases in total CD4+ T cell levels, whereas chemotherapy was associated with increases in naive B cell levels. Surgery and endocrine therapy were not meaningfully associated with leukocyte changes. Conclusions and Relevance In this cohort study of 410 women, breast cancer survivors experienced lasting changes in peripheral leukocyte composition compared with women who remained free of breast cancer. These changes may be related to treatment with chemotherapy or radiotherapy and could influence future chronic disease risk.
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Affiliation(s)
- Jacob K. Kresovich
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida
- Department of Breast Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health (NIH), Research Triangle Park, North Carolina
| | - Katie M. O’Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health (NIH), Research Triangle Park, North Carolina
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health (NIH), Research Triangle Park, North Carolina
| | - Clarice R. Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, North Carolina
| | - Dale P. Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health (NIH), Research Triangle Park, North Carolina
| | - Jack A. Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health (NIH), Research Triangle Park, North Carolina
- Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, North Carolina
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15
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Gómez-Vilarrubla A, Mas-Parés B, Carreras-Badosa G, Bonmatí-Santané A, Martínez-Calcerrada JM, Niubó-Pallàs M, de Zegher F, Ibáñez L, López-Bermejo A, Bassols J. DNA Methylation Signatures in Paired Placenta and Umbilical Cord Samples: Relationship with Maternal Pregestational Body Mass Index and Offspring Metabolic Outcomes. Biomedicines 2024; 12:301. [PMID: 38397903 PMCID: PMC10886657 DOI: 10.3390/biomedicines12020301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 01/24/2024] [Accepted: 01/25/2024] [Indexed: 02/25/2024] Open
Abstract
An epigenomic approach was used to study the impact of maternal pregestational body mass index (BMI) on the placenta and umbilical cord methylomes and their potential effect on the offspring's metabolic phenotype. DNA methylome was assessed in 24 paired placenta and umbilical cord samples. The differentially methylated CpGs associated with maternal pregestational BMI were identified and the metabolic pathways and the potentially related diseases affected by their annotated genes were determined. Two top differentially methylated CpGs were studied in 90 additional samples and the relationship with the offspring's metabolic phenotype was determined. The results showed that maternal pregestational BMI is associated with the methylation of genes involved in endocrine and developmental pathways with potential effects on type 2 diabetes and obesity. The methylation and expression of HADHA and SLC2A8 genes in placenta and umbilical cord were related to several metabolic parameters in the offspring at 6 years (weight SDS, height SDS, BMI SDS, Δ BW-BMI SDS, FM SDS, waist, SBP, TG, HOMA-IR, perirenal fat; all p < 0.05). Our data suggest that epigenetic analysis in placenta and umbilical cord may be useful for identifying individual vulnerability to later metabolic diseases.
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Affiliation(s)
- Ariadna Gómez-Vilarrubla
- Maternal-Fetal Metabolic Research Group, Girona Institute for Biomedical Research (IDIBGI), 17190 Salt, Spain
| | - Berta Mas-Parés
- Pediatric Endocrinology Research Group, Girona Institute for Biomedical Research (IDIBGI), 17190 Salt, Spain
| | - Gemma Carreras-Badosa
- Pediatric Endocrinology Research Group, Girona Institute for Biomedical Research (IDIBGI), 17190 Salt, Spain
| | | | | | - Maria Niubó-Pallàs
- Maternal-Fetal Metabolic Research Group, Girona Institute for Biomedical Research (IDIBGI), 17190 Salt, Spain
| | - Francis de Zegher
- Department of Development & Regeneration, University of Leuven, 3000 Leuven, Belgium;
| | - Lourdes Ibáñez
- Endocrinology, Pediatric Research Institute, Sant Joan de Déu Children’s Hospital, 08950 Esplugues de Llobregat, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Health Institute Carlos III (ISCIII), 28029 Madrid, Spain
| | - Abel López-Bermejo
- Pediatric Endocrinology Research Group, Girona Institute for Biomedical Research (IDIBGI), 17190 Salt, Spain
- Department of Pediatrics, Dr. Josep Trueta Hospital, 17007 Girona, Spain
| | - Judit Bassols
- Maternal-Fetal Metabolic Research Group, Girona Institute for Biomedical Research (IDIBGI), 17190 Salt, Spain
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16
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Pike SC, Havrda M, Gilli F, Zhang Z, Salas LA. Immunological shifts during early-stage Parkinson's disease identified with DNA methylation data on longitudinally collected blood samples. NPJ Parkinsons Dis 2024; 10:21. [PMID: 38212355 PMCID: PMC10784484 DOI: 10.1038/s41531-023-00626-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 12/18/2023] [Indexed: 01/13/2024] Open
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disease in the United States. Decades before motor symptoms manifest, non-motor symptoms such as hyposmia and rapid eye movement (REM) sleep behavior disorder are highly predictive of PD. Previous immune profiling studies have identified alterations to the proportions of immune cells in the blood of clinically defined PD patients. However, it remains unclear if these phenotypes manifest before the clinical diagnosis of PD. We utilized longitudinal DNA methylation (DNAm) microarray data from the Parkinson's Progression Marker's Initiative (PPMI) to perform immune profiling in clinically defined PD and prodromal PD patients (Prod). We identified previously reported changes in neutrophil, monocyte, and T cell numbers in PD patients. Additionally, we noted previously unrecognized decreases in the naive B cell compartment in the defined PD and Prod patient group. Over time, we observed the proportion of innate immune cells in PD blood increased, but the proportion of adaptive immune cells decreased. We identified decreases in T and B cell subsets associated with REM sleep disturbances and early cognitive decline. Lastly, we identified increases in B memory cells associated with both genetic (LRRK2 genotype) and infectious (cytomegalovirus seropositivity) risk factors of PD. Our analysis shows that the peripheral immune system is dynamic as the disease progresses. The study provides a platform to understand how and when peripheral immune alterations occur in PD and whether intervention at particular stages may be therapeutically advantageous.
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Affiliation(s)
- Steven C Pike
- Integrative Neuroscience at Dartmouth, Guarini School of Graduate and Advanced Studies at Dartmouth College, Hanover, NH, USA.
- Department of Epidemiology, Geisel School of Medicine at Dartmouth College, Lebanon, NH, USA.
- Department of Neurology, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA.
| | - Matthew Havrda
- Integrative Neuroscience at Dartmouth, Guarini School of Graduate and Advanced Studies at Dartmouth College, Hanover, NH, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth College, Hanover, NH, USA
| | - Francesca Gilli
- Integrative Neuroscience at Dartmouth, Guarini School of Graduate and Advanced Studies at Dartmouth College, Hanover, NH, USA
- Department of Neurology, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA
| | - Ze Zhang
- Department of Epidemiology, Geisel School of Medicine at Dartmouth College, Lebanon, NH, USA
| | - Lucas A Salas
- Integrative Neuroscience at Dartmouth, Guarini School of Graduate and Advanced Studies at Dartmouth College, Hanover, NH, USA.
- Department of Epidemiology, Geisel School of Medicine at Dartmouth College, Lebanon, NH, USA.
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17
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Chen JQ, Salas LA, Wiencke JK, Koestler DC, Molinaro AM, Andrew AS, Seigne JD, Karagas MR, Kelsey KT, Christensen BC. Matched analysis of detailed peripheral blood and tumor immune microenvironment profiles in bladder cancer. Epigenomics 2024; 16:41-56. [PMID: 38221889 PMCID: PMC10804212 DOI: 10.2217/epi-2023-0358] [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: 12/11/2023] [Indexed: 01/16/2024] Open
Abstract
Background: Bladder cancer and therapy responses hinge on immune profiles in the tumor microenvironment (TME) and blood, yet studies linking tumor-infiltrating immune cells to peripheral immune profiles are limited. Methods: DNA methylation cytometry quantified TME and matched peripheral blood immune cell proportions. With tumor immune profile data as the input, subjects were grouped by immune infiltration status and consensus clustering. Results: Immune hot and cold groups had different immune compositions in the TME but not in circulating blood. Two clusters of patients identified with consensus clustering had different immune compositions not only in the TME but also in blood. Conclusion: Detailed immune profiling via methylation cytometry reveals the significance of understanding tumor and systemic immune relationships in cancer patients.
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Affiliation(s)
- Ji-Qing Chen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
| | - John K Wiencke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Angeline S Andrew
- Department of Neurology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
| | - John D Seigne
- Department of Surgery, Section of Urology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
| | - Margaret R Karagas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
| | - Karl T Kelsey
- Departments of Epidemiology & Pathology & Laboratory Medicine, Brown University, Providence, RI 02912, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
- Departments of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
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18
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Banila C, Green D, Katsanos D, Viana J, Osmaston A, Menendez Vazquez A, Lynch M, Kaveh S. A noninvasive method for whole-genome skin methylome profiling. Br J Dermatol 2023; 189:750-759. [PMID: 37658851 DOI: 10.1093/bjd/ljad316] [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: 04/27/2023] [Revised: 08/24/2023] [Accepted: 08/25/2023] [Indexed: 09/05/2023]
Abstract
BACKGROUND Ageing, disease and malignant transformation of the skin are associated with changes in DNA methylation. So far, mostly invasive methodologies such as biopsies have been applied in collecting DNA methylation signatures. Tape stripping offers a noninvasive option for skin diagnostics. It enables the easy but robust capture of biologic material in large numbers of participants without the need for specialized medical personnel. OBJECTIVES To design and validate a methodology for noninvasive skin sample collection using tape stripping for subsequent DNA -methylation analysis. METHODS A total of 175 participants were recruited and provided tape-stripping samples from a sun-exposed area; 92 provided matched tape-stripping samples from a sun-protected area, and an additional 5 provided matched skin-shave biopsies from the same area. Using -enzymatic conversion and whole-genome Illumina sequencing, we generated genome-wide DNA methylation profiles that were used to evaluate the feasibility of noninvasive data acquisition, to compare with established sampling approaches and to investigate biomarker identification for age and ultraviolet (UV) exposure. RESULTS We found that tape-stripping samples showed strong concordance in their global DNA methylation landscapes to those of conventional invasive biopsies. Moreover, we showed sample reproducibility and consistent global methylation profiles in skin tape-stripping samples collected from different areas of the body. Using matched samples from sun-protected and sun-exposed areas of the body we were able to validate the capacity of our method to capture the effects of environmental changes and ageing in a cohort covering various ages, ethnicities and skin types. We found DNA methylation changes on the skin resulting from UV exposure and identified significant age-related hypermethylation of CpG islands, with a pronounced peak effect at 50-55 years of age, including methylation changes in well-described markers of ageing. CONCLUSIONS These data demonstrate the feasibility of using tape stripping combined with whole-genome sequencing as a noninvasive approach to measuring DNA methylation changes in the skin. In addition, they outline a viable experimental framework for the use of skin tape stripping, particularly when it is performed in large cohorts of patients to identify biomarkers of skin ageing, UV damage and, possibly, to track treatment response to therapeutic interventions.
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Affiliation(s)
| | - Daniel Green
- Mitra Bio, Translation and Innovation Hub, London, UK
| | | | - Joana Viana
- Mitra Bio, Translation and Innovation Hub, London, UK
| | - Alice Osmaston
- Centre for Infectious Disease Epidemiology, University College London, London, UK
| | | | - Magnus Lynch
- Centre for Gene Therapy and Regenerative Medicine, King's College London, London, UK
| | - Shakiba Kaveh
- Mitra Bio, Translation and Innovation Hub, London, UK
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19
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Khan A, Inkster AM, Peñaherrera MS, King S, Kildea S, Oberlander TF, Olson DM, Vaillancourt C, Brain U, Beraldo EO, Beristain AG, Clifton VL, Del Gobbo GF, Lam WL, Metz GAS, Ng JWY, Price EM, Schuetz JM, Yuan V, Portales-Casamar É, Robinson WP. The application of epiphenotyping approaches to DNA methylation array studies of the human placenta. Epigenetics Chromatin 2023; 16:37. [PMID: 37794499 PMCID: PMC10548571 DOI: 10.1186/s13072-023-00507-5] [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: 06/15/2023] [Accepted: 09/15/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Genome-wide DNA methylation (DNAme) profiling of the placenta with Illumina Infinium Methylation bead arrays is often used to explore the connections between in utero exposures, placental pathology, and fetal development. However, many technical and biological factors can lead to signals of DNAme variation between samples and between cohorts, and understanding and accounting for these factors is essential to ensure meaningful and replicable data analysis. Recently, "epiphenotyping" approaches have been developed whereby DNAme data can be used to impute information about phenotypic variables such as gestational age, sex, cell composition, and ancestry. These epiphenotypes offer avenues to compare phenotypic data across cohorts, and to understand how phenotypic variables relate to DNAme variability. However, the relationships between placental epiphenotyping variables and other technical and biological variables, and their application to downstream epigenome analyses, have not been well studied. RESULTS Using DNAme data from 204 placentas across three cohorts, we applied the PlaNET R package to estimate epiphenotypes gestational age, ancestry, and cell composition in these samples. PlaNET ancestry estimates were highly correlated with independent polymorphic ancestry-informative markers, and epigenetic gestational age, on average, was estimated within 4 days of reported gestational age, underscoring the accuracy of these tools. Cell composition estimates varied both within and between cohorts, as well as over very long placental processing times. Interestingly, the ratio of cytotrophoblast to syncytiotrophoblast proportion decreased with increasing gestational age, and differed slightly by both maternal ethnicity (lower in white vs. non-white) and genetic ancestry (lower in higher probability European ancestry). The cohort of origin and cytotrophoblast proportion were the largest drivers of DNAme variation in this dataset, based on their associations with the first principal component. CONCLUSIONS This work confirms that cohort, array (technical) batch, cell type proportion, self-reported ethnicity, genetic ancestry, and biological sex are important variables to consider in any analyses of Illumina DNAme data. We further demonstrate the specific utility of epiphenotyping tools developed for use with placental DNAme data, and show that these variables (i) provide an independent check of clinically obtained data and (ii) provide a robust approach to compare variables across different datasets. Finally, we present a general framework for the processing and analysis of placental DNAme data, integrating the epiphenotype variables discussed here.
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Affiliation(s)
- A Khan
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6H 3N1, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada
- Princess Margaret Cancer Center, Toronto, ON, M5G 2C4, Canada
| | - A M Inkster
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6H 3N1, Canada
| | - M S Peñaherrera
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6H 3N1, Canada
| | - S King
- Department of Psychiatry, McGill University, Montreal, QC, H3A 1A1, Canada
- Psychosocial Research Division, Douglas Hospital Research Centre, Montreal, QC, H4H 1R3, Canada
| | - S Kildea
- Mater Research Institute, University of Queensland, Brisbane, QLD, 4101, Australia
- Molly Wardaguga Research Centre, Charles Darwin University, Brisbane, QLD, 4000, Australia
| | - T F Oberlander
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, BC, V6H 3V4, Canada
| | - D M Olson
- Department of Obstetrics and Gynecology, University of Alberta, 220 HMRC, Edmonton, AB, T6G 2S2, Canada
| | - C Vaillancourt
- Centre Armand Frappier Santé Biotechnologie - INRS and University of Quebec Intersectorial Health Research Network, Laval, QC, H7V 1B7, Canada
| | - U Brain
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, BC, V6H 3V4, Canada
| | - E O Beraldo
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6H 3N1, Canada
| | - A G Beristain
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada
- Department of Obstetrics & Gynecology, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - V L Clifton
- Mater Research Institute, University of Queensland, Brisbane, QLD, 4101, Australia
- Faculty of Medicine, The University of Queensland, Herston, QLD, 4006, Australia
| | - G F Del Gobbo
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6H 3N1, Canada
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, ON, K1H 5B2, Canada
| | - W L Lam
- British Columbia Cancer Research Centre, Vancouver, BC, V5Z 1L3, Canada
| | - G A S Metz
- Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, University of Lethbridge, Lethbridge, AB, T1K 3M4, Canada
| | - J W Y Ng
- Faculty of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - E M Price
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6H 3N1, Canada
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, ON, K1H 5B2, Canada
| | - J M Schuetz
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6H 3N1, Canada
| | - V Yuan
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6H 3N1, Canada
| | - É Portales-Casamar
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada.
- Centre de Recherche du CHU Sainte-Justine, 3175 Côte-Sainte-Catherine Road, Montréal, QC, H3T 1C5, Canada.
| | - W P Robinson
- BC Children's Hospital Research Institute (BCCHR), 950 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada.
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6H 3N1, Canada.
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20
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Jain SS, McNamara ME, Varghese RS, Ressom HW. Deconvolution of immune cell composition and biological age of hepatocellular carcinoma using DNA methylation. Methods 2023; 218:125-132. [PMID: 37574160 PMCID: PMC10529003 DOI: 10.1016/j.ymeth.2023.08.004] [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: 04/21/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/15/2023] Open
Abstract
Hepatocellular carcinoma (HCC) has been an approved indication for the administration of immunotherapy since 2017, but biomarkers that predict therapeutic response have remained limited. Understanding and characterizing the tumor immune microenvironment enables better classification of these tumors and may reveal biomarkers that predict immunotherapeutic efficacy. In this paper, we applied a cell-type deconvolution algorithm using DNA methylation array data to investigate the composition of the tumor microenvironment in HCC. Using publicly available and in-house datasets with a total cohort size of 57 patients, each with tumor and matched normal tissue samples, we identified key differences in immune cell composition. We found that NK cell abundance was significantly decreased in HCC tumors compared to adjacent normal tissue. We also applied DNA methylation "clocks" which estimate phenotypic aging and compared these findings to expression-based determinations of cellular senescence. Senescence and epigenetic aging were significantly increased in HCC tumors, and the degree of age acceleration and senescence was strongly associated with decreased NK cell abundance. In summary, we found that NK cell infiltration in the tumor microenvironment is significantly diminished, and that this loss of NK abundance is strongly associated with increased senescence and age-related phenotype. These findings point to key interactions between NK cells and the senescent tumor microenvironment and offer insights into the pathogenesis of HCC as well as potential biomarkers of therapeutic efficacy.
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Affiliation(s)
- Sidharth S Jain
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA
| | - Megan E McNamara
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA
| | - Rency S Varghese
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA
| | - Habtom W Ressom
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA.
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21
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Gupta MK, Peng H, Li Y, Xu CJ. The role of DNA methylation in personalized medicine for immune-related diseases. Pharmacol Ther 2023; 250:108508. [PMID: 37567513 DOI: 10.1016/j.pharmthera.2023.108508] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/13/2023]
Abstract
Epigenetics functions as a bridge between host genetic & environmental factors, aiding in human health and diseases. Many immune-related diseases, including infectious and allergic diseases, have been linked to epigenetic mechanisms, particularly DNA methylation. In this review, we summarized an updated overview of DNA methylation and its importance in personalized medicine, and demonstrated that DNA methylation has excellent potential for disease prevention, diagnosis, and treatment in a personalized manner. The future implications and limitations of the DNA methylation study have also been well-discussed.
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Affiliation(s)
- Manoj Kumar Gupta
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - He Peng
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Yang Li
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany; Department of Internal Medicine and Radboud Institute for Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Cheng-Jian Xu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany; Department of Internal Medicine and Radboud Institute for Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.
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22
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Shi H, Chen S, Meng FW, Ossip DJ, Yan C, Li D. Epigenome-wide DNA methylation profiling in comparison between pathological and physiological hypertrophy of human cardiomyocytes. Front Genet 2023; 14:1264382. [PMID: 37829282 PMCID: PMC10565041 DOI: 10.3389/fgene.2023.1264382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 09/11/2023] [Indexed: 10/14/2023] Open
Abstract
Background: Physiological and pathological stimuli result in distinct forms of cardiac hypertrophy, but the molecular regulation comparing the two, especially at the DNA methylation level, is not well understood. Methods: We conducted an in vitro study using human cardiomyocytes exposed to angiotensin II (AngII) and insulin-like growth factor 1 (IGF-1) to mimic pathologically and physiologically hypertrophic heart models, respectively. Whole genome DNA methylation patterns were profiled by the Infinium human MethylationEPIC platform with >850 K DNA methylation loci. Two external datasets were used for comparisons and qRT-PCR was performed for examining expression of associated genes of those identified DNA methylation loci. Results: We detected 194 loci that are significantly differentially methylated after AngII treatment, and 206 significant loci after IGF-1 treatment. Mapping the significant loci to genes, we identified 158 genes corresponding to AngII treatment and 175 genes to IGF-1 treatment. Using the gene-set enrichment analysis, the PI3K-Akt signaling pathway was identified to be significantly enriched for both AngII and IGF-1 treatment. The Hippo signaling pathway was enriched after IGF-1 treatment, but not for AngII treatment. CDK6 and RPTOR are components of the PI3K-Akt pathway but have different DNA methylation patterns in response to AngII and IGF-1. qRT-PCR confirmed the different gene expressions of CDK6 and PRTOR. Conclusion: Our study is pioneering in profiling epigenome DNA methylation changes in adult human cardiomyocytes under distinct stress conditions: pathological (AngII) and physiological (IGF-1). The identified DNA methylation loci, genes, and pathways might have the potential to distinguish between pathological and physiological cardiac hypertrophy.
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Affiliation(s)
- Hangchuan Shi
- Department of Clinical and Translational Research, University of Rochester Medical Center, Rochester, NY, United States
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, United States
| | - Si Chen
- Aab Cardiovascular Research Institute, University of Rochester, School of Medicine and Dentistry, Rochester, NY, United States
| | - Fanju W. Meng
- Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, NY, United States
| | - Deborah J. Ossip
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, United States
| | - Chen Yan
- Aab Cardiovascular Research Institute, University of Rochester, School of Medicine and Dentistry, Rochester, NY, United States
| | - Dongmei Li
- Department of Clinical and Translational Research, University of Rochester Medical Center, Rochester, NY, United States
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23
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Van Asselt AJ, Beck JJ, Finnicum CT, Johnson BN, Kallsen N, Hottenga JJ, de Geus EJC, Boomsma DI, Ehli EA, van Dongen J. Genome-Wide DNA Methylation Profiles in Whole-Blood and Buccal Samples-Cross-Sectional, Longitudinal, and across Platforms. Int J Mol Sci 2023; 24:14640. [PMID: 37834090 PMCID: PMC10572275 DOI: 10.3390/ijms241914640] [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: 08/21/2023] [Revised: 09/22/2023] [Accepted: 09/24/2023] [Indexed: 10/15/2023] Open
Abstract
The field of DNA methylation research is rapidly evolving, focusing on disease and phenotype changes over time using methylation measurements from diverse tissue sources and multiple array platforms. Consequently, identifying the extent of longitudinal, inter-tissue, and inter-platform variation in DNA methylation is crucial for future advancement. DNA methylation was measured in 375 individuals, with 197 of those having 2 blood sample measurements ~10 years apart. Whole-blood samples were measured on Illumina Infinium 450K and EPIC methylation arrays, and buccal samples from a subset of 58 participants were measured on EPIC array. The data were analyzed with the aims to examine the correlation between methylation levels in longitudinal blood samples in 197 individuals, examine the correlation between methylation levels in the blood and buccal samples in 58 individuals, and examine the correlation between blood methylation profiles assessed on the EPIC and 450K arrays in 83 individuals. We identified 136,833, 7674, and 96,891 CpGs significantly and strongly correlated (>0.50) longitudinally, across blood and buccal samples as well as array platforms, respectively. A total of 3674 of these CpGs were shared across all three sets. Analysis of these shared CpGs identified previously found associations with aging, ancestry, and 7016 mQTLs as well.
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Affiliation(s)
- Austin J. Van Asselt
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | - Jeffrey J. Beck
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
| | - Casey T. Finnicum
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
| | - Brandon N. Johnson
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
| | - Noah Kallsen
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | - Eco J. C. de Geus
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | | | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | - Erik A. Ehli
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
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24
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Zhao M, Lin Z, Zheng Z, Yao D, Yang S, Zhao Y, Chen X, Aweya JJ, Zhang Y. The mechanisms and factors that induce trained immunity in arthropods and mollusks. Front Immunol 2023; 14:1241934. [PMID: 37744346 PMCID: PMC10513178 DOI: 10.3389/fimmu.2023.1241934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Accepted: 08/25/2023] [Indexed: 09/26/2023] Open
Abstract
Besides dividing the organism's immune system into adaptive and innate immunity, it has long been thought that only adaptive immunity can establish immune memory. However, many studies have shown that innate immunity can also build immunological memory through epigenetic reprogramming and modifications to resist pathogens' reinfection, known as trained immunity. This paper reviews the role of mitochondrial metabolism and epigenetic modifications and describes the molecular foundation in the trained immunity of arthropods and mollusks. Mitochondrial metabolism and epigenetic modifications complement each other and play a key role in trained immunity.
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Affiliation(s)
- Mingming Zhao
- Institute of Marine Sciences and Guangdong Provincial Key Laboratory of Marine Biotechnology, Shantou University, Shantou, China
| | - Zhongyang Lin
- Institute of Marine Sciences and Guangdong Provincial Key Laboratory of Marine Biotechnology, Shantou University, Shantou, China
| | - Zhihong Zheng
- Institute of Marine Sciences and Guangdong Provincial Key Laboratory of Marine Biotechnology, Shantou University, Shantou, China
| | - Defu Yao
- Institute of Marine Sciences and Guangdong Provincial Key Laboratory of Marine Biotechnology, Shantou University, Shantou, China
| | - Shen Yang
- College of Ocean Food and Biological Engineering, Fujian Provincial Key Laboratory of Food Microbiology and Enzyme Engineering, Jimei University, Xiamen, Fujian, China
| | - Yongzhen Zhao
- Guangxi Academy of Fishery Sciences, Guangxi Key Laboratory of Aquatic Genetic Breeding and Healthy Aquaculture, Nanning, China
| | - Xiuli Chen
- Guangxi Academy of Fishery Sciences, Guangxi Key Laboratory of Aquatic Genetic Breeding and Healthy Aquaculture, Nanning, China
| | - Jude Juventus Aweya
- Institute of Marine Sciences and Guangdong Provincial Key Laboratory of Marine Biotechnology, Shantou University, Shantou, China
- College of Ocean Food and Biological Engineering, Fujian Provincial Key Laboratory of Food Microbiology and Enzyme Engineering, Jimei University, Xiamen, Fujian, China
| | - Yueling Zhang
- Institute of Marine Sciences and Guangdong Provincial Key Laboratory of Marine Biotechnology, Shantou University, Shantou, China
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25
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Wang J, Lu L, Zheng S, Wang D, Jin L, Zhang Q, Li M, Zhang Z. DeCOOC Deconvoluted Hi-C Map Characterizes the Chromatin Architecture of Cells in Physiologically Distinctive Tissues. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2301058. [PMID: 37515382 PMCID: PMC10520690 DOI: 10.1002/advs.202301058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 07/06/2023] [Indexed: 07/30/2023]
Abstract
Deciphering variations in chromosome conformations based on bulk three-dimensional (3D) genomic data from heterogenous tissues is a key to understanding cell-type specific genome architecture and dynamics. Surprisingly, computational deconvolution methods for high-throughput chromosome conformation capture (Hi-C) data remain very rare in the literature. Here, a deep convolutional neural network (CNN), deconvolve bulk Hi-C data (deCOOC) that remarkably outperformed all the state-of-the-art tools in the deconvolution task is developed. Interestingly, it is noticed that the chromatin accessibility or the Hi-C contact frequency alone is insufficient to explain the power of deCOOC, suggesting the existence of a latent embedded layer of information pertaining to the cell type specific 3D genome architecture. By applying deCOOC to in-house-generated bulk Hi-C data from visceral and subcutaneous adipose tissues, it is found that the characteristic chromatin features of M2 cells in the two anatomical loci are distinctively bound to different physiological functionalities. Taken together, deCOOC is both a reliable Hi-C data deconvolution method and a powerful tool for functional extraction of 3D genome architecture.
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Affiliation(s)
- Junmei Wang
- CAS Key Laboratory of Genome Sciences and InformationBeijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijing100101China
- School of Life ScienceUniversity of Chinese Academy of SciencesBeijing100049China
| | - Lu Lu
- Livestock and Poultry Multiomics Key Laboratory of Ministry of Agriculture and Rural AffairsCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
- Animal Breeding and Genetics Key Laboratory of Sichuan ProvinceInstitute of Animal Genetics and BreedingSichuan Agricultural UniversityChengdu611130China
| | - Shiqi Zheng
- CAS Key Laboratory of Genome Sciences and InformationBeijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijing100101China
- School of Life ScienceUniversity of Chinese Academy of SciencesBeijing100049China
| | - Danyang Wang
- CAS Key Laboratory of Genome Sciences and InformationBeijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijing100101China
- School of Life ScienceUniversity of Chinese Academy of SciencesBeijing100049China
- Sars‐Fang Centre & MOE Key Laboratory of Marine Genetics and BreedingCollege of Marine Life SciencesOcean University of ChinaQingdao266100China
| | - Long Jin
- Livestock and Poultry Multiomics Key Laboratory of Ministry of Agriculture and Rural AffairsCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
- Animal Breeding and Genetics Key Laboratory of Sichuan ProvinceInstitute of Animal Genetics and BreedingSichuan Agricultural UniversityChengdu611130China
| | - Qing Zhang
- CAS Key Laboratory of Genome Sciences and InformationBeijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijing100101China
| | - Mingzhou Li
- Livestock and Poultry Multiomics Key Laboratory of Ministry of Agriculture and Rural AffairsCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
- Animal Breeding and Genetics Key Laboratory of Sichuan ProvinceInstitute of Animal Genetics and BreedingSichuan Agricultural UniversityChengdu611130China
| | - Zhihua Zhang
- CAS Key Laboratory of Genome Sciences and InformationBeijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijing100101China
- School of Life ScienceUniversity of Chinese Academy of SciencesBeijing100049China
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26
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Vasileva D, Greenwood CMT, Daley D. A Review of the Epigenetic Clock: Emerging Biomarkers for Asthma and Allergic Disease. Genes (Basel) 2023; 14:1724. [PMID: 37761864 PMCID: PMC10531327 DOI: 10.3390/genes14091724] [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: 08/01/2023] [Revised: 08/22/2023] [Accepted: 08/23/2023] [Indexed: 09/29/2023] Open
Abstract
DNA methylation (DNAm) is a dynamic, age-dependent epigenetic modification that can be used to study interactions between genetic and environmental factors. Environmental exposures during critical periods of growth and development may alter DNAm patterns, leading to increased susceptibility to diseases such as asthma and allergies. One method to study the role of DNAm is the epigenetic clock-an algorithm that uses DNAm levels at select age-informative Cytosine-phosphate-Guanine (CpG) dinucleotides to predict epigenetic age (EA). The difference between EA and calendar age (CA) is termed epigenetic age acceleration (EAA) and reveals information about the biological capacity of an individual. Associations between EAA and disease susceptibility have been demonstrated for a variety of age-related conditions and, more recently, phenotypes such as asthma and allergic diseases, which often begin in childhood and progress throughout the lifespan. In this review, we explore different epigenetic clocks and how they have been applied, particularly as related to childhood asthma. We delve into how in utero and early life exposures (e.g., smoking, air pollution, maternal BMI) result in methylation changes. Furthermore, we explore the potential for EAA to be used as a biomarker for asthma and allergic diseases and identify areas for further study.
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Affiliation(s)
- Denitsa Vasileva
- Centre for Heart Lung Innovation, University of British Columbia and Saint Paul’s Hospital, Vancouver, BC V6Z 1Y6, Canada;
| | - Celia M. T. Greenwood
- Lady Davis Institute for Medical Research, Montreal, QC H3T 1E2, Canada;
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC H3A 0G4, Canada
- Gerald Bronfman Department of Oncology, McGill University, Montreal, QC H3A 0G4, Canada
- Department of Human Genetics, McGill University, Montreal, QC H3A 0G4, Canada
| | - Denise Daley
- Centre for Heart Lung Innovation, University of British Columbia and Saint Paul’s Hospital, Vancouver, BC V6Z 1Y6, Canada;
- Department of Medicine, Respiratory Division, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
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Aurich S, Müller L, Kovacs P, Keller M. Implication of DNA methylation during lifestyle mediated weight loss. Front Endocrinol (Lausanne) 2023; 14:1181002. [PMID: 37614712 PMCID: PMC10442821 DOI: 10.3389/fendo.2023.1181002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 07/18/2023] [Indexed: 08/25/2023] Open
Abstract
Over the past 50 years, the number of overweight/obese people increased significantly, making obesity a global public health challenge. Apart from rare monogenic forms, obesity is a multifactorial disease, most likely resulting from a concerted interaction of genetic, epigenetic and environmental factors. Although recent studies opened new avenues in elucidating the complex genetics behind obesity, the biological mechanisms contributing to individual's risk to become obese are not yet fully understood. Non-genetic factors such as eating behaviour or physical activity are strong contributing factors for the onset of obesity. These factors may interact with genetic predispositions most likely via epigenetic mechanisms. Epigenome-wide association studies or methylome-wide association studies are measuring DNA methylation at single CpGs across thousands of genes and capture associations to obesity phenotypes such as BMI. However, they only represent a snapshot in the complex biological network and cannot distinguish between causes and consequences. Intervention studies are therefore a suitable method to control for confounding factors and to avoid possible sources of bias. In particular, intervention studies documenting changes in obesity-associated epigenetic markers during lifestyle driven weight loss, make an important contribution to a better understanding of epigenetic reprogramming in obesity. To investigate the impact of lifestyle in obesity state specific DNA methylation, especially concerning the development of new strategies for prevention and individual therapy, we reviewed 19 most recent human intervention studies. In summary, this review highlights the huge potential of targeted interventions to alter disease-associated epigenetic patterns. However, there is an urgent need for further robust and larger studies to identify the specific DNA methylation biomarkers which influence obesity.
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Affiliation(s)
- Samantha Aurich
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany
| | - Luise Müller
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
| | - Peter Kovacs
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
- Deutsches Zentrum für Diabetesforschung e.V., Neuherberg, Germany
| | - Maria Keller
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany
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28
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Zhang Z, Wiencke JK, Kelsey KT, Koestler DC, Molinaro AM, Pike SC, Karra P, Christensen BC, Salas LA. Hierarchical deconvolution for extensive cell type resolution in the human brain using DNA methylation. Front Neurosci 2023; 17:1198243. [PMID: 37404460 PMCID: PMC10315586 DOI: 10.3389/fnins.2023.1198243] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 05/30/2023] [Indexed: 07/06/2023] Open
Abstract
Introduction The human brain comprises heterogeneous cell types whose composition can be altered with physiological and pathological conditions. New approaches to discern the diversity and distribution of brain cells associated with neurological conditions would significantly advance the study of brain-related pathophysiology and neuroscience. Unlike single-nuclei approaches, DNA methylation-based deconvolution does not require special sample handling or processing, is cost-effective, and easily scales to large study designs. Existing DNA methylation-based methods for brain cell deconvolution are limited in the number of cell types deconvolved. Methods Using DNA methylation profiles of the top cell-type-specific differentially methylated CpGs, we employed a hierarchical modeling approach to deconvolve GABAergic neurons, glutamatergic neurons, astrocytes, microglial cells, oligodendrocytes, endothelial cells, and stromal cells. Results We demonstrate the utility of our method by applying it to data on normal tissues from various brain regions and in aging and diseased tissues, including Alzheimer's disease, autism, Huntington's disease, epilepsy, and schizophrenia. Discussion We expect that the ability to determine the cellular composition in the brain using only DNA from bulk samples will accelerate understanding brain cell type composition and cell-type-specific epigenetic states in normal and diseased brain tissues.
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Affiliation(s)
- Ze Zhang
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
| | - John K. Wiencke
- Department of Neurological Surgery, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, United States
| | - Karl T. Kelsey
- Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI, United States
| | - Devin C. Koestler
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, United States
| | - Annette M. Molinaro
- Department of Neurological Surgery, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, United States
| | - Steven C. Pike
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
- Department of Neurology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
| | - Prasoona Karra
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
| | - Brock C. Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
- Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
| | - Lucas A. Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
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Villar JD, Stavrum AK, Spindola LM, Torsvik A, Bjella T, Steen NE, Djurovic S, Andreassen OA, Steen VM, Le Hellard S. Differences in white blood cell proportions between schizophrenia cases and controls are influenced by medication and variations in time of day. Transl Psychiatry 2023; 13:211. [PMID: 37330513 DOI: 10.1038/s41398-023-02507-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 05/27/2023] [Accepted: 06/01/2023] [Indexed: 06/19/2023] Open
Abstract
Cases with schizophrenia (SCZ) and healthy controls show differences in white blood cell (WBC) counts and blood inflammation markers. Here, we investigate whether time of blood draw and treatment with psychiatric medications are related to differences in estimated WBC proportions between SCZ cases and controls. DNA methylation data from whole blood was used to estimate proportions of six subtypes of WBCs in SCZ patients (n = 333) and healthy controls (n = 396). We tested the association of case-control status with estimated cell-type proportions and the neutrophil-to-lymphocyte ratio (NLR) in 4 models: with/without adjusting for time of blood draw, and then compared results from blood samples drawn during a 12-h (07:00-19:00) or 7-h (07:00-14:00) period. We also investigated WBC proportions in a subgroup of medication-free patients (n = 51). Neutrophil proportions were significantly higher in SCZ cases (mean=54.1%) vs. controls (mean=51.1%; p = <0.001), and CD8+T lymphocyte proportions were lower in SCZ cases (mean=12.1%) vs. controls (mean=13.2%; p = 0.001). The effect sizes in the 12-h sample (07:00-19:00) showed a significant difference between SCZ vs. controls for neutrophils, CD4+T, CD8+T, and B-cells, which remained significant after adjusting for time of blood draw. In the samples matched for time of blood draw during 07.00-14.00, we also observed an association with neutrophils, CD4+T, CD8+T, and B-cells that was unaffected by further adjustment for time of blood draw. In the medication-free patients, we observed differences that remained significant in neutrophils (p = 0.01) and CD4+T (p = 0.01) after adjusting for time of day. The association of SCZ with NLR was significant in all models (range: p < 0.001 to p = 0.03) in both medicated and unmedicated patients. In conclusion, controlling for pharmacological treatment and circadian cycling of WBC is necessary for unbiased estimates in case-control studies. Nevertheless, the association of WBC with SCZ remains, even after adjusting for the time of day.
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Affiliation(s)
- Jonelle D Villar
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway.
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway.
| | - Anne-Kristin Stavrum
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Leticia M Spindola
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Anja Torsvik
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Thomas Bjella
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Niels Eiel Steen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Vidar M Steen
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Stephanie Le Hellard
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway.
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway.
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30
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Gaitsch H, Franklin RJM, Reich DS. Cell-free DNA-based liquid biopsies in neurology. Brain 2023; 146:1758-1774. [PMID: 36408894 PMCID: PMC10151188 DOI: 10.1093/brain/awac438] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 10/26/2022] [Accepted: 11/10/2022] [Indexed: 11/22/2022] Open
Abstract
This article reviews recent developments in the application of cell-free DNA-based liquid biopsies to neurological diseases. Over the past few decades, an explosion of interest in the use of accessible biofluids to identify and track molecular disease has revolutionized the fields of oncology, prenatal medicine and others. More recently, technological advances in signal detection have allowed for informative analysis of biofluids that are typically sparse in cells and other circulating components, such as CSF. In parallel, advancements in epigenetic profiling have allowed for novel applications of liquid biopsies to diseases without characteristic mutational profiles, including many degenerative, autoimmune, inflammatory, ischaemic and infectious disorders. These events have paved the way for a wide array of neurological conditions to benefit from enhanced diagnostic, prognostic, and treatment abilities through the use of liquid biomarkers: a 'liquid biopsy' approach. This review includes an overview of types of liquid biopsy targets with a focus on circulating cell-free DNA, methods used to identify and probe potential liquid biomarkers, and recent applications of such biomarkers to a variety of complex neurological conditions including CNS tumours, stroke, traumatic brain injury, Alzheimer's disease, epilepsy, multiple sclerosis and neuroinfectious disease. Finally, the challenges of translating liquid biopsies to use in clinical neurology settings-and the opportunities for improvement in disease management that such translation may provide-are discussed.
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Affiliation(s)
- Hallie Gaitsch
- NIH-Oxford-Cambridge Scholars Program, Wellcome-MRC Cambridge Stem Cell Institute and Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 1TN, UK
| | | | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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31
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van den Oord EJCG, Xie LY, Zhao M, Campbell TL, Turecki G, Kähler AK, Dean B, Mors O, Hultman CM, Staunstrup NH, Aberg KA. Genes implicated by a methylome-wide schizophrenia study in neonatal blood show differential expression in adult brain samples. Mol Psychiatry 2023; 28:2088-2094. [PMID: 37106120 DOI: 10.1038/s41380-023-02080-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/13/2023] [Accepted: 04/17/2023] [Indexed: 04/29/2023]
Abstract
Schizophrenia is a disabling disorder involving genetic predisposition in combination with environmental influences that likely act via dynamic alterations of the epigenome and the transcriptome but its detailed pathophysiology is largely unknown. We performed cell-type specific methylome-wide association study of neonatal blood (N = 333) from individuals who later in life developed schizophrenia and controls. Suggestively significant associations (P < 1.0 × 10-6) were detected in all cell-types and in whole blood with methylome-wide significant associations in monocytes (P = 2.85 × 10-9-4.87 × 10-9), natural killer cells (P = 1.72 × 10-9-7.82 × 10-9) and B cells (P = 3.8 × 10-9). Validation of methylation findings in post-mortem brains (N = 596) from independent schizophrenia cases and controls showed significant enrichment of transcriptional differences (enrichment ratio = 1.98-3.23, P = 2.3 × 10-3-1.0 × 10-5), with specific highly significant differential expression for, for example, BDNF (t = -6.11, P = 1.90 × 10-9). In addition, expression difference in brain significantly predicted schizophrenia (multiple correlation = 0.15-0.22, P = 3.6 × 10-4-4.5 × 10-8). In summary, using a unique design combining pre-disease onset (neonatal) blood methylomic data and post-disease onset (post-mortem) brain transcriptional data, we have identified genes of likely functional relevance that are associated with schizophrenia susceptibility, rather than confounding disease associated artifacts. The identified loci may be of clinical value as a methylation-based biomarker for early detection of increased schizophrenia susceptibility.
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Affiliation(s)
- Edwin J C G van den Oord
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Lin Y Xie
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Min Zhao
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Thomas L Campbell
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Gustavo Turecki
- Douglas Mental Health University Institute and McGill University, Montréal, Québec, Canada
| | - Anna K Kähler
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Brian Dean
- Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Ole Mors
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Psychosis Research Unit, Aarhus University Hospital - Psychiatry, Risskov, Denmark
- Center for Genomics and Personalized Medicine, University of Aarhus, Aarhus, Denmark
| | - Christina M Hultman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nicklas H Staunstrup
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, University of Aarhus, Aarhus, Denmark
- Department of Biomedicine, University of Aarhus, Aarhus C, Denmark
| | - Karolina A Aberg
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, Richmond, VA, USA.
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32
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Zhang Z, Stolrow HG, Christensen BC, Salas LA. Down Syndrome Altered Cell Composition in Blood, Brain, and Buccal Swab Samples Profiled by DNA-Methylation-Based Cell-Type Deconvolution. Cells 2023; 12:cells12081168. [PMID: 37190077 DOI: 10.3390/cells12081168] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 04/10/2023] [Accepted: 04/11/2023] [Indexed: 05/17/2023] Open
Abstract
Down syndrome (DS) is a genetic disorder caused by an extra copy of chromosome 21 that presents developmental dysfunction and intellectual disability. To better understand the cellular changes associated with DS, we investigated the cell composition in blood, brain, and buccal swab samples from DS patients and controls using DNA methylation-based cell-type deconvolution. We used genome-scale DNA methylation data from Illumina HumanMethylation450k and HumanMethylationEPIC arrays to profile cell composition and trace fetal lineage cells in blood samples (DS N = 46; control N = 1469), brain samples from various regions (DS N = 71; control N = 101), and buccal swab samples (DS N = 10; control N = 10). In early development, the number of cells from the fetal lineage in the blood is drastically lower in DS patients (Δ = 17.5%), indicating an epigenetically dysregulated maturation process for DS patients. Across sample types, we observed significant alterations in relative cell-type proportions for DS subjects compared with the controls. Cell-type proportion alterations were present in samples from early development and adulthood. Our findings provide insight into DS cellular biology and suggest potential cellular interventional targets for DS.
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Affiliation(s)
- Ze Zhang
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756, USA
| | - Hannah G Stolrow
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756, USA
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33
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Bell-Glenn S, Salas LA, Molinaro AM, Butler RA, Christensen BC, Kelsey KT, Wiencke JK, Koestler DC. Calculating detection limits and uncertainty of reference-based deconvolution of whole-blood DNA methylation data. Epigenomics 2023; 15:435-451. [PMID: 37337720 PMCID: PMC10308256 DOI: 10.2217/epi-2023-0006] [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: 01/07/2023] [Accepted: 05/16/2023] [Indexed: 06/21/2023] Open
Abstract
DNA methylation (DNAm)-based cell mixture deconvolution (CMD) has become a quintessential part of epigenome-wide association studies where DNAm is profiled in heterogeneous tissue types. Despite being introduced over a decade ago, detection limits, which represent the smallest fraction of a cell type in a mixed biospecimen that can be reliably detected, have yet to be determined in the context of DNAm-based CMD. Moreover, there has been little attention given to approaches for quantifying the uncertainty associated with DNAm-based CMD. Here, analytical frameworks for determining both cell-specific limits of detection and quantification of uncertainty associated with DNAm-based CMD are described. This work may contribute to improved rigor, reproducibility and replicability of epigenome-wide association studies involving CMD.
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Affiliation(s)
- Shelby Bell-Glenn
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, NH 03756, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Rondi A Butler
- Departments of Epidemiology & Pathology & Laboratory Medicine, Brown University, Providence, RI 02912, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, NH 03756, USA
- Department of Molecular & Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
- Department of Community & Family Medicine, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - Karl T Kelsey
- Departments of Epidemiology & Pathology & Laboratory Medicine, Brown University, Providence, RI 02912, USA
| | - John K Wiencke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
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Wyatt RC, Olek S, De Franco E, Samans B, Patel K, Houghton J, Walter S, Schulze J, Bacchetta R, Hattersley AT, Flanagan SE, Johnson MB. FOXP3 TSDR Measurement Could Assist Variant Classification and Diagnosis of IPEX Syndrome. J Clin Immunol 2023; 43:662-669. [PMID: 36600150 PMCID: PMC9957900 DOI: 10.1007/s10875-022-01428-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 12/21/2022] [Indexed: 01/06/2023]
Abstract
Pathogenic FOXP3 variants cause immune dysregulation polyendocrinopathy enteropathy X-linked (IPEX) syndrome, a progressive autoimmune disease resulting from disruption of the regulatory T cell (Treg) compartment. Assigning pathogenicity to novel variants in FOXP3 is challenging due to the heterogeneous phenotype and variable immunological abnormalities. The number of cells with demethylation at the Treg cell-specific demethylated region (TSDR) is an independent biomarker of IPEX. We aimed to investigate if diagnosing IPEX at presentation with isolated diabetes could allow for effective monitoring of disease progression and assess whether TSDR analysis can aid FOXP3 variant classification and predict disease course. We describe a large genetically diagnosed IPEX cohort (n = 65) and 13 individuals with other monogenic autoimmunity subtypes in whom we quantified the proportion of cells with FOXP3 TSDR demethylation, normalized to the number with CD4 demethylation (%TSDR/CD4) and compare them to 29 unaffected controls. IPEX patients presenting with isolated diabetes (50/65, 77%) often later developed enteropathy (20/50, 40%) with a median interval of 23.5 weeks. %TSDR/CD4 was a good discriminator of IPEX vs. unaffected controls (ROC-AUC 0.81, median 13.6% vs. 8.5%, p < 0.0001) with higher levels of demethylation associated with more severe disease. Patients with other monogenic autoimmunity had a similar %TSDR/CD4 to controls (median 8.7%, p = 1.0). Identifying increased %TSDR/CD4 in patients with novel FOXP3 mutations presenting with isolated diabetes facilitates diagnosis and could offer an opportunity to monitor patients and begin immune modulatory treatment before onset of severe enteropathy.
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Affiliation(s)
- Rebecca C Wyatt
- Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Sven Olek
- Ivana Türbachova Laboratory of Epigenetics, Precision for Medicine GmbH, Berlin, Germany
| | - Elisa De Franco
- Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Bjoern Samans
- Ivana Türbachova Laboratory of Epigenetics, Precision for Medicine GmbH, Berlin, Germany
| | - Kashyap Patel
- Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Jayne Houghton
- Exeter Genomics Laboratory, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Steffi Walter
- Research & Development, Epimune Diagnostics, Berlin, Germany
| | - Janika Schulze
- Research & Development, Epimune Diagnostics, Berlin, Germany
| | - Rosa Bacchetta
- Department of Pediatrics, Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Center for Definitive and Curative Medicine (CDCM), Stanford University, Stanford, USA
| | - Andrew T Hattersley
- Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Sarah E Flanagan
- Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Matthew B Johnson
- Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
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Treble-Barna A, Heinsberg LW, Stec Z, Breazeale S, Davis TS, Kesbhat AA, Chattopadhyay A, VonVille HM, Ketchum AM, Yeates KO, Kochanek PM, Weeks DE, Conley YP. Brain-derived neurotrophic factor (BDNF) epigenomic modifications and brain-related phenotypes in humans: A systematic review. Neurosci Biobehav Rev 2023; 147:105078. [PMID: 36764636 PMCID: PMC10164361 DOI: 10.1016/j.neubiorev.2023.105078] [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: 09/13/2022] [Revised: 01/17/2023] [Accepted: 02/04/2023] [Indexed: 02/11/2023]
Abstract
Epigenomic modifications of the brain-derived neurotrophic factor (BDNF) gene have been postulated to underlie the pathogenesis of neurodevelopmental, psychiatric, and neurological conditions. This systematic review summarizes current evidence investigating the association of BDNF epigenomic modifications (DNA methylation, non-coding RNA, histone modifications) with brain-related phenotypes in humans. A novel contribution is our creation of an open access web-based application, the BDNF DNA Methylation Map, to interactively visualize specific positions of CpG sites investigated across all studies for which relevant data were available. Our literature search of four databases through September 27, 2021 returned 1701 articles, of which 153 met inclusion criteria. Our review revealed exceptional heterogeneity in methodological approaches, hindering the identification of clear patterns of robust and/or replicated results. We summarize key findings and provide recommendations for future epigenomic research. The existing literature appears to remain in its infancy and requires additional rigorous research to fulfill its potential to explain BDNF-linked risk for brain-related conditions and improve our understanding of the molecular mechanisms underlying their pathogenesis.
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Affiliation(s)
- Amery Treble-Barna
- Department of Physical Medicine & Rehabilitation, School of Medicine, University of Pittsburgh, PA 15261, USA.
| | - Lacey W Heinsberg
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Zachary Stec
- Department of Physical Medicine & Rehabilitation, School of Medicine, University of Pittsburgh, PA 15261, USA.
| | - Stephen Breazeale
- Department of Health and Human Development, School of Nursing, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Tara S Davis
- Department of Health Promotion and Development, School of Nursing, University of Pittsburgh, PA 15261, USA.
| | | | - Ansuman Chattopadhyay
- Molecular Biology Information Service, Health Sciences Library System, University of Pittsburgh, USA
| | - Helena M VonVille
- Health Sciences Library System, University of Pittsburgh, PA 15261, USA.
| | - Andrea M Ketchum
- Emeritus Health Sciences Library System, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Keith Owen Yeates
- Department of Psychology, Alberta Children's Hospital Research Institute and Hotchkiss Brain Institute, University of Calgary, Calgary, AB T2N1N4, Canada.
| | - Patrick M Kochanek
- Safar Center for Resuscitation Research, Department of Critical Care Medicine, School of Medicine, University of Pittsburgh, PA 15261, USA.
| | - Daniel E Weeks
- Department of Human Genetics and Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Yvette P Conley
- Department of Human Genetics, School of Nursing, University of Pittsburgh, Pittsburgh, PA 15261, USA.
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Zhang X, Hu Y, Vandenhoudt RE, Yan C, Marconi VC, Cohen MH, Justice AC, Aouizerat BE, Xu K. Cell-type specific EWAS identifies genes involved in HIV pathogenesis and oncogenesis among people with HIV infection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.21.533691. [PMID: 36993343 PMCID: PMC10055405 DOI: 10.1101/2023.03.21.533691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Epigenome-wide association studies (EWAS) of heterogenous blood cells have identified CpG sites associated with chronic HIV infection, which offer limited knowledge of cell-type specific methylation patterns associated with HIV infection. Applying a computational deconvolution method validated by capture bisulfite DNA methylation sequencing, we conducted a cell type-based EWAS and identified differentially methylated CpG sites specific for chronic HIV infection among five immune cell types in blood: CD4+ T-cells, CD8+ T-cells, B cells, Natural Killer (NK) cells, and monocytes in two independent cohorts (N total =1,134). Differentially methylated CpG sites for HIV-infection were highly concordant between the two cohorts. Cell-type level meta-EWAS revealed distinct patterns of HIV-associated differential CpG methylation, where 67% of CpG sites were unique to individual cell types (false discovery rate, FDR <0.05). CD4+ T-cells had the largest number of HIV-associated CpG sites (N=1,472) compared to any other cell type. Genes harboring statistically significant CpG sites are involved in immunity and HIV pathogenesis (e.g. CX3CR1 in CD4+ T-cells, CCR7 in B cells, IL12R in NK cells, LCK in monocytes). More importantly, HIV-associated CpG sites were overrepresented for hallmark genes involved in cancer pathology ( FDR <0.05) (e.g. BCL family, PRDM16, PDCD1LGD, ESR1, DNMT3A, NOTCH2 ). HIV-associated CpG sites were enriched among genes involved in HIV pathogenesis and oncogenesis such as Kras-signaling, interferon-α and -γ, TNF-α, inflammatory, and apoptotic pathways. Our findings are novel, uncovering cell-type specific modifications in the host epigenome for people with HIV that contribute to the growing body of evidence regarding pathogen-induced epigenetic oncogenicity, specifically on HIV and its comorbidity with cancers.
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Kupsco A, Bloomquist TR, Hu H, Reddam A, Tang D, Goldsmith J, Rundle AG, Baccarelli AA, Herbstman JB. Mitochondrial DNA copy number dynamics and associations with the prenatal environment from birth through adolescence in a population of Dominican and African American children. Mitochondrion 2023; 69:140-146. [PMID: 36804466 PMCID: PMC10006332 DOI: 10.1016/j.mito.2023.02.008] [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: 10/24/2022] [Revised: 01/17/2023] [Accepted: 02/13/2023] [Indexed: 02/18/2023]
Abstract
Mitochondrial DNA copy number (mtDNAcn) dynamics throughout childhood are poorly understood. We profiled mtDNAcn from birth through adolescence and evaluated how the prenatal environment influences mtDNAcn across childhood. Data were collected from children from New York City followed through 18 years. Using duplexed qRT-PCR, we quantified mtDNAcn relative to nuclear DNA in blood collected from the umbilical cord (n = 450), children aged 5-7 (n = 510), and adolescents aged 15-18 (n = 278). We examined mtDNAcn across childhood with linear mixed-effects models (LMM). Relative mtDNAcn was lowest at birth (mean ± SD: 0.67 ± 0.35) and increased in childhood (1.24 ± 0.50) then slightly declined in adolescence (1.13 ± 0.44). We observed no differences in mtDNAcn by sex or race/ethnicity. mtDNAcn was positively associated with prenatal environmental tobacco smoke exposure (0.077 [ 0.01, 0.14] change in relative mtDNAcn) but negatively associated with maternal completion of high school (-0.066 [-0.13, 0.00]), with the receipt of public assistance at birth (-0.074 [-0.14, -0.01]), and when mother born outside the U.S (-0.061 [-0.13, 0.003]). Infant birth outcomes were not associated with mtDNAcn. MtDNAcn levels were dynamic through childhood and associated with some prenatal factors, underscoring the need for the investigation of longitudinal mtDNAcn for human health research.
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Affiliation(s)
- Allison Kupsco
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States.
| | - Tessa R Bloomquist
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States
| | - Heng Hu
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States
| | - Aalekhya Reddam
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States
| | - Deliang Tang
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States
| | - Jeff Goldsmith
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States
| | - Andrew G Rundle
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States
| | - Julie B Herbstman
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States
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Haftorn KL, Denault WRP, Lee Y, Page CM, Romanowska J, Lyle R, Næss ØE, Kristjansson D, Magnus PM, Håberg SE, Bohlin J, Jugessur A. Nucleated red blood cells explain most of the association between DNA methylation and gestational age. Commun Biol 2023; 6:224. [PMID: 36849614 PMCID: PMC9971030 DOI: 10.1038/s42003-023-04584-w] [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: 07/03/2022] [Accepted: 02/13/2023] [Indexed: 03/01/2023] Open
Abstract
Determining if specific cell type(s) are responsible for an association between DNA methylation (DNAm) and a given phenotype is important for understanding the biological mechanisms underlying the association. Our EWAS of gestational age (GA) in 953 newborns from the Norwegian MoBa study identified 13,660 CpGs significantly associated with GA (pBonferroni<0.05) after adjustment for cell type composition. When the CellDMC algorithm was applied to explore cell-type specific effects, 2,330 CpGs were significantly associated with GA, mostly in nucleated red blood cells [nRBCs; n = 2,030 (87%)]. Similar patterns were found in another dataset based on a different array and when applying an alternative algorithm to CellDMC called Tensor Composition Analysis (TCA). Our findings point to nRBCs as the main cell type driving the DNAm-GA association, implicating an epigenetic signature of erythropoiesis as a likely mechanism. They also explain the poor correlation observed between epigenetic age clocks for newborns and those for adults.
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Affiliation(s)
- Kristine L Haftorn
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway.
- Institute of Health and Society, University of Oslo, Oslo, Norway.
| | - William R P Denault
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Yunsung Lee
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Physical Health and Ageing, Division of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Julia Romanowska
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, , University of Bergen, Bergen, Norway
| | - Robert Lyle
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Øyvind E Næss
- Institute of Health and Society, University of Oslo, Oslo, Norway
- Division of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Dana Kristjansson
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway
| | - Per M Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Jon Bohlin
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Division for Infection Control and Environmental Health, Department of Infectious Disease Epidemiology and Modelling, Norwegian Institute of Public Health, Oslo, Norway
| | - Astanand Jugessur
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, , University of Bergen, Bergen, Norway
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Lin WY. Epigenetic clocks derived from western samples differentially reflect Taiwanese health outcomes. Front Genet 2023; 14:1089819. [PMID: 36814906 PMCID: PMC9939687 DOI: 10.3389/fgene.2023.1089819] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 01/23/2023] [Indexed: 02/09/2023] Open
Abstract
Introduction: Several epigenetic clocks have been developed, with five measures of epigenetic age acceleration (EAA) especially receiving extensive investigations: HannumEAA, IEAA, PhenoEAA, GrimEAA, and DunedinPACE. These epigenetic clocks were mainly developed by individuals of European or Hispanic ancestry. It remains unclear whether they can reflect disease morbidity and physiological conditions in Asian populations. Methods: I here investigated five measures of EAA of 2,474 Taiwan Biobank participants with DNA methylation data. Using logistic regressions, I sequentially regressed various health outcomes on each of the five measures of EAA while adjusting for chronological age, sex, body mass index, the number of smoking pack-years, drinking status, regular exercise, educational attainment, and six cell-type proportions. Results: Except for IEAA, all measures of EAA reflected the obesity of Taiwanese (p < 4.0E-4). Diabetes was reflected by DunedinPACE (p = 5.4E-6) and GrimEAA (p = 5.8E-5). Moreover, DunedinPACE was associated with dyslipidemia, including hypertriglyceridemia (p = 1.1E-5), low high-density lipoprotein cholesterol (HDL-C) (p = 4.0E-5), and high triglyceride to HDL-C ratio (p = 1.6E-7). Discussion: This is one of the first studies to show that epigenetic clocks (developed by individuals of European or Hispanic ancestry) can reflect Taiwanese physiological conditions. DunedinPACE was associated with more Taiwanese health outcomes than the other four measures of EAA.
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Affiliation(s)
- Wan-Yu Lin
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan,Master of Public Health Degree Program, College of Public Health, National Taiwan University, Taipei, Taiwan,Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan,*Correspondence: Wan-Yu Lin,
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40
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Meijer M, Franke B, Sandi C, Klein M. Epigenome-wide DNA methylation in externalizing behaviours: A review and combined analysis. Neurosci Biobehav Rev 2023; 145:104997. [PMID: 36566803 DOI: 10.1016/j.neubiorev.2022.104997] [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: 08/08/2022] [Revised: 11/24/2022] [Accepted: 12/09/2022] [Indexed: 12/24/2022]
Abstract
DNA methylation (DNAm) is one of the most frequently studied epigenetic mechanisms facilitating the interplay of genomic and environmental factors, which can contribute to externalizing behaviours and related psychiatric disorders. Previous epigenome-wide association studies (EWAS) for externalizing behaviours have been limited in sample size, and, therefore, candidate genes and biomarkers with robust evidence are still lacking. We 1) performed a systematic literature review of EWAS of attention-deficit/hyperactivity disorder (ADHD)- and aggression-related behaviours conducted in peripheral tissue and cord blood and 2) combined the most strongly associated DNAm sites observed in individual studies (p < 10-3) to identify candidate genes and biological systems for ADHD and aggressive behaviours. We observed enrichment for neuronal processes and neuronal cell marker genes for ADHD. Astrocyte and granulocytes cell markers among genes annotated to DNAm sites were relevant for both ADHD and aggression-related behaviours. Only 1 % of the most significant epigenetic findings for ADHD/ADHD symptoms were likely to be directly explained by genetic factors involved in ADHD. Finally, we discuss how the field would greatly benefit from larger sample sizes and harmonization of assessment instruments.
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Affiliation(s)
- Mandy Meijer
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Laboratory of Behavioural Genetics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Barbara Franke
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Carmen Sandi
- Laboratory of Behavioural Genetics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Marieke Klein
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Psychiatry, University of California, La Jolla, San Diego, CA, 92093, USA.
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41
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KIDD JOHN, RAULERSON CHELSEAK, MOHLKE KARENL, LIN DANYU. Mediation analysis of multiple mediators with incomplete omics data. Genet Epidemiol 2023; 47:61-77. [PMID: 36125445 PMCID: PMC10423053 DOI: 10.1002/gepi.22504] [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: 03/10/2022] [Revised: 06/29/2022] [Accepted: 08/16/2022] [Indexed: 02/01/2023]
Abstract
There is an increasing interest in using multiple types of omics features (e.g., DNA sequences, RNA expressions, methylation, protein expressions, and metabolic profiles) to study how the relationships between phenotypes and genotypes may be mediated by other omics markers. Genotypes and phenotypes are typically available for all subjects in genetic studies, but typically, some omics data will be missing for some subjects, due to limitations such as cost and sample quality. In this article, we propose a powerful approach for mediation analysis that accommodates missing data among multiple mediators and allows for various interaction effects. We formulate the relationships among genetic variants, other omics measurements, and phenotypes through linear regression models. We derive the joint likelihood for models with two mediators, accounting for arbitrary patterns of missing values. Utilizing computationally efficient and stable algorithms, we conduct maximum likelihood estimation. Our methods produce unbiased and statistically efficient estimators. We demonstrate the usefulness of our methods through simulation studies and an application to the Metabolic Syndrome in Men study.
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Affiliation(s)
- JOHN KIDD
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, U.S.A
| | - CHELSEA K. RAULERSON
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, U.S.A
| | - KAREN L. MOHLKE
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, U.S.A
| | - DAN-YU LIN
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, U.S.A
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Loyfer N, Magenheim J, Peretz A, Cann G, Bredno J, Klochendler A, Fox-Fisher I, Shabi-Porat S, Hecht M, Pelet T, Moss J, Drawshy Z, Amini H, Moradi P, Nagaraju S, Bauman D, Shveiky D, Porat S, Dior U, Rivkin G, Or O, Hirshoren N, Carmon E, Pikarsky A, Khalaileh A, Zamir G, Grinbaum R, Abu Gazala M, Mizrahi I, Shussman N, Korach A, Wald O, Izhar U, Erez E, Yutkin V, Samet Y, Rotnemer Golinkin D, Spalding KL, Druid H, Arner P, Shapiro AMJ, Grompe M, Aravanis A, Venn O, Jamshidi A, Shemer R, Dor Y, Glaser B, Kaplan T. A DNA methylation atlas of normal human cell types. Nature 2023; 613:355-364. [PMID: 36599988 PMCID: PMC9811898 DOI: 10.1038/s41586-022-05580-6] [Citation(s) in RCA: 131] [Impact Index Per Article: 131.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 11/18/2022] [Indexed: 01/05/2023]
Abstract
DNA methylation is a fundamental epigenetic mark that governs gene expression and chromatin organization, thus providing a window into cellular identity and developmental processes1. Current datasets typically include only a fraction of methylation sites and are often based either on cell lines that underwent massive changes in culture or on tissues containing unspecified mixtures of cells2-5. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing, allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell type are more than 99.5% identical, demonstrating the robustness of cell identity programmes to environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny and identifies methylation patterns retained since embryonic development. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hypermethylated loci are rare and are enriched for CpG islands, Polycomb targets and CTCF binding sites, suggesting a new role in shaping cell-type-specific chromatin looping. The atlas provides an essential resource for study of gene regulation and disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.
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Affiliation(s)
- Netanel Loyfer
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Judith Magenheim
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ayelet Peretz
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | | | | | - Agnes Klochendler
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ilana Fox-Fisher
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Sapir Shabi-Porat
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Merav Hecht
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Tsuria Pelet
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Joshua Moss
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
- Sharett Institute of Oncology, Hadassah Hebrew University Medical Center, Jerusalem, Israel
| | - Zeina Drawshy
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | | | | | | | - Dvora Bauman
- Department of Obstetrics and Gynecology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - David Shveiky
- Department of Obstetrics and Gynecology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Shay Porat
- Department of Obstetrics and Gynecology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Uri Dior
- Department of Obstetrics and Gynecology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Gurion Rivkin
- Department of Orthopedics, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Omer Or
- Department of Orthopedics, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Nir Hirshoren
- Department of Otolaryngology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Einat Carmon
- Department of General Surgery, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Surgery, Samson Assuta Ashdod University Hospital, Ashdod, Israel
| | - Alon Pikarsky
- Surgery Division, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Abed Khalaileh
- Department of General Surgery, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Gideon Zamir
- Department of General Surgery, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ronit Grinbaum
- Department of General Surgery, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Machmud Abu Gazala
- Department of General Surgery, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ido Mizrahi
- Department of General Surgery, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Noam Shussman
- Department of General Surgery, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Amit Korach
- Department of Cardiothoracic Surgery, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ori Wald
- Department of Cardiothoracic Surgery, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Uzi Izhar
- Department of Cardiothoracic Surgery, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Eldad Erez
- Department of Cardiothoracic Surgery, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Vladimir Yutkin
- Department of Urology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yaacov Samet
- Department of Vascular Surgery, Shaare Zedek Medical Center, Jerusalem, Israel
| | - Devorah Rotnemer Golinkin
- Department of Endocrinology and Metabolism, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Kirsty L Spalding
- Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden
| | - Henrik Druid
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Department of Forensic Medicine, The National Board of Forensic Medicine, Stockholm, Sweden
| | - Peter Arner
- Department of Medicine (H7) and Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
| | - A M James Shapiro
- Department of Surgery and the Clinical Islet Transplant Program, University of Alberta, Edmonton, Alberta, Canada
| | - Markus Grompe
- Papé Family Pediatric Research Institute, Oregon Health & Science University, Portland, OR, USA
| | - Alex Aravanis
- GRAIL, Inc., Menlo Park, CA, USA
- Illumina, Inc., San Diego, CA, USA
| | | | | | - Ruth Shemer
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yuval Dor
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Benjamin Glaser
- Department of Endocrinology and Metabolism, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Tommy Kaplan
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
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Lang AL, Eulalio T, Fox E, Yakabi K, Bukhari SA, Kawas CH, Corrada MM, Montgomery SB, Heppner FL, Capper D, Nachun D, Montine TJ. Methylation differences in Alzheimer's disease neuropathologic change in the aged human brain. Acta Neuropathol Commun 2022; 10:174. [PMID: 36447297 PMCID: PMC9710143 DOI: 10.1186/s40478-022-01470-0] [Citation(s) in RCA: 10] [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: 09/23/2022] [Accepted: 10/24/2022] [Indexed: 12/05/2022] Open
Abstract
Alzheimer's disease (AD) is the most common cause of dementia with advancing age as its strongest risk factor. AD neuropathologic change (ADNC) is known to be associated with numerous DNA methylation changes in the human brain, but the oldest old (> 90 years) have so far been underrepresented in epigenetic studies of ADNC. Our study participants were individuals aged over 90 years (n = 47) from The 90+ Study. We analyzed DNA methylation from bulk samples in eight precisely dissected regions of the human brain: middle frontal gyrus, cingulate gyrus, entorhinal cortex, dentate gyrus, CA1, substantia nigra, locus coeruleus and cerebellar cortex. We deconvolved our bulk data into cell-type-specific (CTS) signals using computational methods. CTS methylation differences were analyzed across different levels of ADNC. The highest amount of ADNC related methylation differences was found in the dentate gyrus, a region that has so far been underrepresented in large scale multi-omic studies. In neurons of the dentate gyrus, DNA methylation significantly differed with increased burden of amyloid beta (Aβ) plaques at 5897 promoter regions of protein-coding genes. Amongst these, higher Aβ plaque burden was associated with promoter hypomethylation of the Presenilin enhancer 2 (PEN-2) gene, one of the rate limiting genes in the formation of gamma-secretase, a multicomponent complex that is responsible in part for the endoproteolytic cleavage of amyloid precursor protein into Aβ peptides. In addition to novel ADNC related DNA methylation changes, we present the most detailed array-based methylation survey of the old aged human brain to date. Our open-sourced dataset can serve as a brain region reference panel for future studies and help advance research in aging and neurodegenerative diseases.
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Affiliation(s)
- Anna-Lena Lang
- Department of Neuropathology, Charité–Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Tiffany Eulalio
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305 USA
| | - Eddie Fox
- Department of Pathology, Stanford University, 300 Pasteur Drive, Stanford, CA 94305 USA
| | - Koya Yakabi
- Department of Pathology, Stanford University, 300 Pasteur Drive, Stanford, CA 94305 USA
| | - Syed A. Bukhari
- Department of Pathology, Stanford University, 300 Pasteur Drive, Stanford, CA 94305 USA
| | - Claudia H. Kawas
- Department of Neurology, University of California Irvine, Orange, CA 92868-4280 USA
- Department of Neurobiology and Behavior, University of California, Irvine, CA 92697 USA
| | - Maria M. Corrada
- Department of Neurology, University of California Irvine, Orange, CA 92868-4280 USA
- Department of Epidemiology, University of California, Irvine, CA 92617 USA
| | - Stephen B. Montgomery
- Department of Pathology, Stanford University, 300 Pasteur Drive, Stanford, CA 94305 USA
- Department of Genetics, Stanford University, Stanford, CA 94305 USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305 USA
| | - Frank L. Heppner
- Department of Neuropathology, Charité–Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE), 10117 Berlin, Germany
- Cluster of Excellence, NeuroCure, 10117 Berlin, Germany
| | - David Capper
- Department of Neuropathology, Charité–Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Daniel Nachun
- Department of Genetics, Stanford University, Stanford, CA 94305 USA
| | - Thomas J. Montine
- Department of Pathology, Stanford University, 300 Pasteur Drive, Stanford, CA 94305 USA
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Song J, Kuan PF. A systematic assessment of cell type deconvolution algorithms for DNA methylation data. Brief Bioinform 2022; 23:bbac449. [PMID: 36242584 PMCID: PMC9947552 DOI: 10.1093/bib/bbac449] [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: 05/24/2022] [Revised: 08/11/2022] [Accepted: 09/20/2022] [Indexed: 12/14/2022] Open
Abstract
We performed systematic assessment of computational deconvolution methods that play an important role in the estimation of cell type proportions from bulk methylation data. The proposed framework methylDeConv (available as an R package) integrates several deconvolution methods for methylation profiles (Illumina HumanMethylation450 and MethylationEPIC arrays) and offers different cell-type-specific CpG selection to construct the extended reference library which incorporates the main immune cell subsets, epithelial cells and cell-free DNAs. We compared the performance of different deconvolution algorithms via simulations and benchmark datasets and further investigated the associations of the estimated cell type proportions to cancer therapy in breast cancer and subtypes in melanoma methylation case studies. Our results indicated that the deconvolution based on the extended reference library is critical to obtain accurate estimates of cell proportions in non-blood tissues.
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Affiliation(s)
- Junyan Song
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY
| | - Pei-Fen Kuan
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY
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Zhang Z, Wiencke JK, Kelsey KT, Koestler DC, Christensen BC, Salas LA. HiTIMED: hierarchical tumor immune microenvironment epigenetic deconvolution for accurate cell type resolution in the tumor microenvironment using tumor-type-specific DNA methylation data. J Transl Med 2022; 20:516. [DOI: 10.1186/s12967-022-03736-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Accepted: 10/30/2022] [Indexed: 11/11/2022] Open
Abstract
Abstract
Background
Cellular compositions of solid tumor microenvironments are heterogeneous, varying across patients and tumor types. High-resolution profiling of the tumor microenvironment cell composition is crucial to understanding its biological and clinical implications. Previously, tumor microenvironment gene expression and DNA methylation-based deconvolution approaches have been shown to deconvolve major cell types. However, existing methods lack accuracy and specificity to tumor type and include limited identification of individual cell types.
Results
We employed a novel tumor-type-specific hierarchical model using DNA methylation data to deconvolve the tumor microenvironment with high resolution, accuracy, and specificity. The deconvolution algorithm is named HiTIMED. Seventeen cell types from three major tumor microenvironment components can be profiled (tumor, immune, angiogenic) by HiTIMED, and it provides tumor-type-specific models for twenty carcinoma types. We demonstrate the prognostic significance of cell types that other tumor microenvironment deconvolution methods do not capture.
Conclusion
We developed HiTIMED, a DNA methylation-based algorithm, to estimate cell proportions in the tumor microenvironment with high resolution and accuracy. HiTIMED deconvolution is amenable to archival biospecimens providing high-resolution profiles enabling to study of clinical and biological implications of variation and composition of the tumor microenvironment.
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Blackwell AD, Garcia AR. Ecoimmunology in the field: Measuring multiple dimensions of immune function with minimally invasive, field-adapted techniques. Am J Hum Biol 2022; 34:e23784. [PMID: 35861267 PMCID: PMC9786696 DOI: 10.1002/ajhb.23784] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 06/29/2022] [Accepted: 07/08/2022] [Indexed: 01/25/2023] Open
Abstract
OBJECTIVE Immune function is multifaceted and characterizations based on single biomarkers may be uninformative or misleading, particularly when considered across ecological contexts. However, measuring the many facets of immunity in the field can be challenging, since many measures cannot be obtained on-site, necessitating sample preservation and transport. Here we assess state-of-the-art methods for measuring immunity, focusing on measures that require a minimal blood sample obtained from a finger prick, which can be: (1) dried on filter paper, (2) frozen in liquid nitrogen, or (3) stabilized with chemical reagents. RESULTS We review immune measures that can be obtained from point-of-care devices or from immunoassays of dried blood spots (DBSs), field methods for flow cytometry, the use of RNA or DNA sequencing and quantification, and the application of immune activation assays under field conditions. CONCLUSIONS Stable protein products, such as immunoglobulins and C-reactive protein are reliably measured in DBSs. Because less stable proteins, such as cytokines, may be problematic to measure even in fresh blood, mRNA from stabilized blood may provide a cleaner measure of cytokine and broader immune-related gene expression. Gene methylation assays or mRNA sequencing also allow for the quantification of many other parameters, including the inference of leukocyte subsets, though with less accuracy than with flow cytometry. Combining these techniques provides an improvement over single-marker studies, allowing for a more nuanced understanding of how social and ecological variables are linked to immune measures and disease risk in diverse populations and settings.
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Affiliation(s)
- Aaron D. Blackwell
- Department of AnthropologyWashington State UniversityPullmanWashingtonUSA
| | - Angela R. Garcia
- Research DepartmentPhoenix Children's HospitalPhoenixArizonaUSA,Department of Child HealthUniversity of Arizona College of MedicinePhoenixArizonaUSA
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Liang C, Liu N, Zhang Q, Deng M, Ma J, Lu J, Yin Y, Wang J, Miao Y, She B, Li Q, Hou G. A detection panel of novel methylated DNA markers for malignant pleural effusion. Front Oncol 2022; 12:967079. [PMID: 36176402 PMCID: PMC9513209 DOI: 10.3389/fonc.2022.967079] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 08/19/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundCytology remains the gold standard for the detection of malignant cells in pleural effusion. However, its sensitivity is limited. The aim of this study was to establish a novel panel of cancer-specific methylated genes for the differential diagnosis of malignant pleural effusion (MPE).MethodsA cohort of 100 cancer patients (68 lung cancer, 32 other malignant tumors) and 48 patients with benign disease presenting with pleural effusion was prospectively enrolled. Pleural effusion was evaluated by means of cytopathological investigation and DNA methylation of SHOX2, RASSF1A, SEPTIN9 and HOXA9 in the cellular fraction. DNA methylation in bisulfite-converted DNA was determined using quantitative methylation-specific real-time PCR (MS-PCR). Cytopathological and DNA methylation results were evaluated with regard to the final clinical diagnosis.ResultsThe LungMe® SHOX2 and RASSF1A Assay (Tellgen Corporation, China) has been reported to be highly sensitive and specific for lung cancer using bronchial aspirates. As expected, LungMe® detected metastases of lung cancer (sensitivity: 76.5%) as well as metastases of other malignant tumors (sensitivity: 68.8%). OncoMe, a novel combination of SHOX2, RASSF1A, SEPTIN9 and HOXA9 methylation, led to an additional 11% increase in the detection rate of MPE, resulting in a sensitivity of 85% and a specificity of 96%. Overall, OncoMe showed a higher positive detection rate in SCLC (100%), LUAC (87%), OC (100%), BC (92.9%), GC (80.0%), and MESO (80%) than in LUSC (50%). Cytopathological analyses only detected 23 positive samples, which were all positively measured by both LungMe® and OncoMe.ConclusionOncoMe has potential for use as a biomarker for the detection of MPE, even not limited to lung cancer.
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Affiliation(s)
- Chaonan Liang
- Department of Cardio-Pulmonary Function, Henan Provincial People’s Hospital, Zhengzhou University People’s Hospital, Henan University People’s Hospital, Zhengzhou, Henan, China
- Department of Pulmonary and Critical Care Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Nan Liu
- Department of Pathology, The First Hospital and College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Qin Zhang
- Department of Pulmonary and Critical Care Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Mingming Deng
- Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital, National Center of Respiratory Medicine, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, National Clinical Research Center for Respiratory Diseases, Beijing, China
| | - Jiangwei Ma
- Department of Pulmonary and Critical Care Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Jingwen Lu
- Department of Pulmonary and Critical Care Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Yan Yin
- Department of Pulmonary and Critical Care Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Jian Wang
- Department of Pathology, The First Hospital and College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Yuan Miao
- Department of Pathology, The First Hospital and College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Bin She
- Academic Development, Tellgen Corporation, Shanghai, China
| | - Qingchang Li
- Department of Pathology, The First Hospital and College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Gang Hou
- Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital, National Center of Respiratory Medicine, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, National Clinical Research Center for Respiratory Diseases, Beijing, China
- *Correspondence: Gang Hou,
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Ma Z, Wang Y, Quan Y, Wang Z, Liu Y, Ding Z. Maternal obesity alters methylation level of cytosine in CpG island for epigenetic inheritance in fetal umbilical cord blood. Hum Genomics 2022; 16:34. [PMID: 36045397 PMCID: PMC9429776 DOI: 10.1186/s40246-022-00410-2] [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: 03/12/2022] [Accepted: 08/22/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Over the past few decades, global maternal obesity prevalence has rapidly increased. This condition may induce long-lasting pathophysiological effects on either fetal or infant health that could be attributable to unknown unique changes in the umbilical blood composition. METHODS A total of 34 overweight/obese and 32 normal-weight pregnant women were recruited. Fifteen umbilical blood samples including 8 overweight/obese subjects and 7 normal weight women were sequenced using Targeted Bisulfite Sequencing technology to detect the average methylation level of cytosine and identify the differentially methylated region (DMR). GO and KEGG analyses were then employed to perform pathway enrichment analysis of DMR-related genes and promoters. Moreover, the mRNA levels of methylation-related genes histone deacetylases (HDACs) and DNA methyltransferases (DNMTs) were characterized in the samples obtained from these two groups. RESULTS Average methylated cytosine levels in both the CpG islands (CGI) and promoter significantly decreased in overweight/obese groups. A total of 1669 DMRs exhibited differences in their DNA methylation status between the overweight/obese and control groups. GO and KEGG analyses revealed that DMR-related genes and promoters were enriched in the metabolism, cancer and cardiomyopathy signaling pathways. Furthermore, the HDACs and DNMTs mRNA levels trended to decline in overweight/obese groups. CONCLUSIONS Decreased methylated cytosine levels in overweight/obese women induce the gene expression activity at a higher level than in the control group. DMRs between these two groups in the fetal blood may contribute to the changes in gene transcription that underlie the increased risk of metabolic disorders, cancers and cardiomyopathy in their offspring.
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Affiliation(s)
- Zhuoyao Ma
- Department of Histology, Embryology, Genetics and Developmental Biology, Shanghai Key Laboratory for Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, No.280, Chongqing Road (South), Shanghai, 200025, China
| | - Yingjin Wang
- Department of Obstetrics and Gynecology, Shanghai Eighth People's Hospital, Shanghai, 200235, China
| | - Yanmei Quan
- Department of Histology, Embryology, Genetics and Developmental Biology, Shanghai Key Laboratory for Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, No.280, Chongqing Road (South), Shanghai, 200025, China
| | - Zhijie Wang
- Department of Obstetrics and Gynecology, Shanghai Eighth People's Hospital, Shanghai, 200235, China.
| | - Yue Liu
- Department of Histology, Embryology, Genetics and Developmental Biology, Shanghai Key Laboratory for Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, No.280, Chongqing Road (South), Shanghai, 200025, China.
| | - Zhide Ding
- Department of Histology, Embryology, Genetics and Developmental Biology, Shanghai Key Laboratory for Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, No.280, Chongqing Road (South), Shanghai, 200025, China.
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Niehues A, Bizzarri D, Reinders MJT, Slagboom PE, van Gool AJ, van den Akker EB, 't Hoen PAC. Metabolomic predictors of phenotypic traits can replace and complement measured clinical variables in population-scale expression profiling studies. BMC Genomics 2022; 23:546. [PMID: 35907790 PMCID: PMC9339202 DOI: 10.1186/s12864-022-08771-7] [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: 03/17/2022] [Accepted: 07/12/2022] [Indexed: 11/10/2022] Open
Abstract
Population-scale expression profiling studies can provide valuable insights into biological and disease-underlying mechanisms. The availability of phenotypic traits is essential for studying clinical effects. Therefore, missing, incomplete, or inaccurate phenotypic information can make analyses challenging and prevent RNA-seq or other omics data to be reused. A possible solution are predictors that infer clinical or behavioral phenotypic traits from molecular data. While such predictors have been developed based on different omics data types and are being applied in various studies, metabolomics-based surrogates are less commonly used than predictors based on DNA methylation profiles.In this study, we inferred 17 traits, including diabetes status and exposure to lipid medication, using previously trained metabolomic predictors. We evaluated whether these metabolomic surrogates can be used as an alternative to reported information for studying the respective phenotypes using expression profiling data of four population cohorts. For the majority of the 17 traits, the metabolomic surrogates performed similarly to the reported phenotypes in terms of effect sizes, number of significant associations, replication rates, and significantly enriched pathways.The application of metabolomics-derived surrogate outcomes opens new possibilities for reuse of multi-omics data sets. In studies where availability of clinical metadata is limited, missing or incomplete information can be complemented by these surrogates, thereby increasing the size of available data sets. Additionally, the availability of such surrogates could be used to correct for potential biological confounding. In the future, it would be interesting to further investigate the use of molecular predictors across different omics types and cohorts.
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Affiliation(s)
- Anna Niehues
- Center for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Geert Grooteplein Zuid 26-28, Nijmegen, 6525 GA, Netherlands.,Translational Metabolic Laboratory, Department Laboratory Medicine, Radboud university medical center, Geert Grooteplein Zuid 10, Nijmegen, 6525 GA, Netherlands
| | - Daniele Bizzarri
- Molecular Epidemiology, LUMC, Einthovenweg 20, Leiden, 2333 ZC, Netherlands.,Leiden Computational Biology Center, LUMC, Einthovenweg 20, Leiden, 2333 ZC, Netherlands
| | - Marcel J T Reinders
- Leiden Computational Biology Center, LUMC, Einthovenweg 20, Leiden, 2333 ZC, Netherlands.,Delft Bioinformatics Lab, TU Delft, Van Mourik Broekmanweg 6, Delft, 2628 XE, Netherlands
| | - P Eline Slagboom
- Molecular Epidemiology, LUMC, Einthovenweg 20, Leiden, 2333 ZC, Netherlands.,Max Planck Institute for the Biology of Ageing, Cologne, Germany
| | - Alain J van Gool
- Translational Metabolic Laboratory, Department Laboratory Medicine, Radboud university medical center, Geert Grooteplein Zuid 10, Nijmegen, 6525 GA, Netherlands
| | - Erik B van den Akker
- Molecular Epidemiology, LUMC, Einthovenweg 20, Leiden, 2333 ZC, Netherlands.,Leiden Computational Biology Center, LUMC, Einthovenweg 20, Leiden, 2333 ZC, Netherlands.,Delft Bioinformatics Lab, TU Delft, Van Mourik Broekmanweg 6, Delft, 2628 XE, Netherlands
| | | | | | - Peter A C 't Hoen
- Center for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Geert Grooteplein Zuid 26-28, Nijmegen, 6525 GA, Netherlands.
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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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