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Thakor P, Siddiqui MQ, Patel TR. Analysis of the interlink between glucose-6-phosphate dehydrogenase (G6PD) and lung cancer through multi-omics databases. Heliyon 2024; 10:e35158. [PMID: 39165939 PMCID: PMC11334843 DOI: 10.1016/j.heliyon.2024.e35158] [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: 05/13/2024] [Revised: 07/16/2024] [Accepted: 07/24/2024] [Indexed: 08/22/2024] Open
Abstract
Glucose-6-Phosphate Dehydrogenase (G6PD) is a crucial enzyme that executes the pentose phosphate pathway. Due to its critical nodal position in the metabolic network, it is associated with different forms of cancer tumorigeneses and progression. Nonetheless, its functional role and molecular mechanism in lung cancer remain unknown. The present study provides intricate information associated with G6PD and Lung Cancer. Varieties of public datasets were retrieved by us, including UALCAN, TCGA, cBioPortal, and the UCSC Xena browser. The data obtained were used to assess the expression of G6PD, its clinical features, epigenetic regulation, relationship with tumour infiltration, tumour mutation burden, microsatellite instability, tumour microenvironment, immune checkpoint genes, genomic alteration, and patient's overall survival rate. The present study revealed that the G6PD expression was correlated with the clinical features of lung cancer including disease stage, race, sex, age, smoking habits, and lymph node metastasis. Moreover, the expression profile of G6PD also imparts epigenetic changes by modulating the DNA promoter methylation activity. Methylation of promoters changes the expression of various transcription factors, genes leading to an influence on the immune system. These events linked with G6PD-related mutational gene alterations (FAM3A, LAG3, p53, KRAS). The entire circumstance influences the patient's overall survival rate and poor prognosis. Functional investigation using STRING, GO, and KEGG found that G6PD primarily engages in hallmark functions (metabolism, immunological responses, proliferation, apoptosis, p53, HIF-1, FOXO, PI3K-AKT signaling). This work provides a wide knowledge of G6PD's function in lung cancer, as well as a theoretical foundation for possible prognostic therapeutic markers.
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Affiliation(s)
- Parth Thakor
- Bapubhai Desaibhai Patel Institute of Paramedical Sciences, Charotar University of Science and Technology, CHARUSAT Campus, Changa, Gujarat, India
- Department of Chemistry and Biochemistry, Alberta RNA Research and Training Institute, University of Lethbridge, Lethbridge, AB, T1K 2E1, Canada
| | - M. Quadir Siddiqui
- Department of Chemistry and Biochemistry, Alberta RNA Research and Training Institute, University of Lethbridge, Lethbridge, AB, T1K 2E1, Canada
| | - Trushar R. Patel
- Department of Chemistry and Biochemistry, Alberta RNA Research and Training Institute, University of Lethbridge, Lethbridge, AB, T1K 2E1, Canada
- Department of Microbiology, Immunology & Infectious Diseases, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada
- Li Ka Shing Institute of Virology, University of Alberta, Edmonton, AB, T6G 2E1, Canada
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Shore CJ, Villicaña S, El-Sayed Moustafa JS, Roberts AL, Gunn DA, Bataille V, Deloukas P, Spector TD, Small KS, Bell JT. Genetic effects on the skin methylome in healthy older twins. Am J Hum Genet 2024:S0002-9297(24)00254-4. [PMID: 39137780 DOI: 10.1016/j.ajhg.2024.07.010] [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: 12/05/2023] [Revised: 05/22/2024] [Accepted: 07/15/2024] [Indexed: 08/15/2024] Open
Abstract
Whole-skin DNA methylation variation has been implicated in several diseases, including melanoma, but its genetic basis has not yet been fully characterized. Using bulk skin tissue samples from 414 healthy female UK twins, we performed twin-based heritability and methylation quantitative trait loci (meQTL) analyses for >400,000 DNA methylation sites. We find that the human skin DNA methylome is on average less heritable than previously estimated in blood and other tissues (mean heritability: 10.02%). meQTL analysis identified local genetic effects influencing DNA methylation at 18.8% (76,442) of tested CpG sites, as well as 1,775 CpG sites associated with at least one distal genetic variant. As a functional follow-up, we performed skin expression QTL (eQTL) analyses in a partially overlapping sample of 604 female twins. Colocalization analysis identified over 3,500 shared genetic effects affecting thousands of CpG sites (10,067) and genes (4,475). Mediation analysis of putative colocalized gene-CpG pairs identified 114 genes with evidence for eQTL effects being mediated by DNA methylation in skin, including in genes implicating skin disease such as ALOX12 and CSPG4. We further explored the relevance of skin meQTLs to skin disease and found that skin meQTLs and CpGs under genetic influence were enriched for multiple skin-related genome-wide and epigenome-wide association signals, including for melanoma and psoriasis. Our findings give insights into the regulatory landscape of epigenomic variation in skin.
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Affiliation(s)
- Christopher J Shore
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| | - Sergio Villicaña
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - Amy L Roberts
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - Veronique Bataille
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Panos Deloukas
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
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Gordon MG, Kathail P, Choy B, Kim MC, Mazumder T, Gearing M, Ye CJ. Population Diversity at the Single-Cell Level. Annu Rev Genomics Hum Genet 2024; 25:27-49. [PMID: 38382493 DOI: 10.1146/annurev-genom-021623-083207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Population-scale single-cell genomics is a transformative approach for unraveling the intricate links between genetic and cellular variation. This approach is facilitated by cutting-edge experimental methodologies, including the development of high-throughput single-cell multiomics and advances in multiplexed environmental and genetic perturbations. Examining the effects of natural or synthetic genetic variants across cellular contexts provides insights into the mutual influence of genetics and the environment in shaping cellular heterogeneity. The development of computational methodologies further enables detailed quantitative analysis of molecular variation, offering an opportunity to examine the respective roles of stochastic, intercellular, and interindividual variation. Future opportunities lie in leveraging long-read sequencing, refining disease-relevant cellular models, and embracing predictive and generative machine learning models. These advancements hold the potential for a deeper understanding of the genetic architecture of human molecular traits, which in turn has important implications for understanding the genetic causes of human disease.
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Affiliation(s)
| | - Pooja Kathail
- Center for Computational Biology, University of California, Berkeley, California, USA
| | - Bryson Choy
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, California, USA
- Institute for Human Genetics, University of California, San Francisco, California, USA
| | - Min Cheol Kim
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, California, USA
- Institute for Human Genetics, University of California, San Francisco, California, USA
| | - Thomas Mazumder
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, California, USA
- Institute for Human Genetics, University of California, San Francisco, California, USA
| | - Melissa Gearing
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, California, USA
- Institute for Human Genetics, University of California, San Francisco, California, USA
| | - Chun Jimmie Ye
- Arc Institute, Palo Alto, California, USA
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, California, USA
- Institute for Human Genetics, University of California, San Francisco, California, USA
- Bakar Computational Health Sciences Institute, Gladstone-UCSF Institute of Genomic Immunology, Parker Institute for Cancer Immunotherapy, Department of Epidemiology and Biostatistics, Department of Microbiology and Immunology, and Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA;
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4
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Huang D, Shang W, Xu M, Wan Q, Zhang J, Tang X, Shen Y, Wang Y, Yu Y. Genome-Wide Methylation Analysis Reveals a KCNK3-Prominent Causal Cascade on Hypertension. Circ Res 2024; 135:e76-e93. [PMID: 38841840 DOI: 10.1161/circresaha.124.324455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 05/22/2024] [Indexed: 06/07/2024]
Abstract
BACKGROUND Despite advances in understanding hypertension's genetic structure, how noncoding genetic variants influence it remains unclear. Studying their interaction with DNA methylation is crucial to deciphering this complex disease's genetic mechanisms. METHODS We investigated the genetic and epigenetic interplay in hypertension using whole-genome bisulfite sequencing. Methylation profiling in 918 males revealed allele-specific methylation and methylation quantitative trait loci. We engineered rs1275988T/C mutant mice using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein 9), bred them for homozygosity, and subjected them to a high-salt diet. Telemetry captured their cardiovascular metrics. Protein-DNA interactions were elucidated using DNA pull-downs, mass spectrometry, and Western blots. A wire myograph assessed vascular function, and analysis of the Kcnk3 gene methylation highlighted the mutation's role in hypertension. RESULTS We discovered that DNA methylation-associated genetic effects, especially in non-cytosine-phosphate-guanine (non-CpG) island and noncoding distal regulatory regions, significantly contribute to hypertension predisposition. We identified distinct methylation quantitative trait locus patterns in the hypertensive population and observed that the onset of hypertension is influenced by the transmission of genetic effects through the demethylation process. By evidence-driven prioritization and in vivo experiments, we unearthed rs1275988 in a cell type-specific enhancer as a notable hypertension causal variant, intensifying hypertension through the modulation of local DNA methylation and consequential alterations in Kcnk3 gene expression and vascular remodeling. When exposed to a high-salt diet, mice with the rs1275988C/C genotype exhibited exacerbated hypertension and significant vascular remodeling, underscored by increased aortic wall thickness. The C allele of rs1275988 was associated with elevated DNA methylation levels, driving down the expression of the Kcnk3 gene by attenuating Nr2f2 (nuclear receptor subfamily 2 group F member 2) binding at the enhancer locus. CONCLUSIONS Our research reveals new insights into the complex interplay between genetic variations and DNA methylation in hypertension. We underscore hypomethylation's potential in hypertension onset and identify rs1275988 as a causal variant in vascular remodeling. This work advances our understanding of hypertension's molecular mechanisms and encourages personalized health care strategies.
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Affiliation(s)
- Dandan Huang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
- School of Food Science and Technology, Jiangnan University, Wuxi, China (D.H.)
| | - Wenlong Shang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Mengtong Xu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Qiangyou Wan
- Academy of Integrative Medicine, Shanghai University of Traditional Chinese Medicine (Q.W.)
| | - Jin Zhang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Xiaofeng Tang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Yujun Shen
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Yan Wang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Ying Yu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
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Patil V, Perez-Carpena P, Lopez-Escamez JA. A systematic review on the contribution of DNA methylation to hearing loss. Clin Epigenetics 2024; 16:88. [PMID: 38970134 PMCID: PMC11227199 DOI: 10.1186/s13148-024-01697-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 06/17/2024] [Indexed: 07/07/2024] Open
Abstract
BACKGROUND DNA methylation may have a regulatory role in monogenic sensorineural hearing loss and complex, polygenic phenotypic forms of hearing loss, including age-related hearing impairment or Meniere disease. The purpose of this systematic review is to critically assess the evidence supporting a functional role of DNA methylation in phenotypes associated with hearing loss. RESULTS The search strategy yielded a total of 661 articles. After quality assessment, 25 records were selected (12 human DNA methylation studies, 5 experimental animal studies and 8 studies reporting mutations in the DNMT1 gene). Although some methylation studies reported significant differences in CpG methylation in diverse gene promoters associated with complex hearing loss phenotypes (ARHI, otosclerosis, MD), only one study included a replication cohort that supported a regulatory role for CpG methylation in the genes TCF25 and POLE in ARHI. Conversely, several studies have independently confirmed pathogenic mutations within exon 21 of the DNMT1 gene, which encodes the DNA (cytosine-5)-methyltransferase 1 enzyme. This methylation enzyme is strongly associated with a rare disease defined by autosomal dominant cerebellar ataxia, deafness and narcolepsy (ADCA-DN). Of note, rare variants in DNMT1 and DNMT3A genes have also been reported in noise-induced hearing loss. CONCLUSIONS Evidence supporting a functional role for DNA methylation in hearing loss is limited to few genes in complex disorders such as ARHI. Mutations in the DNMT1 gene are associated with ADCA-DN, suggesting the CpG methylation in hearing loss genes deserves further attention in hearing research.
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Affiliation(s)
- Vibha Patil
- Meniere's Disease Neuroscience Research Program, Faculty of Medicine and Health, School of Medical Sciences, The Kolling Institute, University of Sydney, Rm 611024, Level 11 Kolling Institute | 10 Westbourne St, St Leonards, Sydney, NSW, 2064, Australia.
| | - Patricia Perez-Carpena
- Division of Otolaryngology, Department of Surgery, Instituto de Investigación Biosanitaria, Ibs.Granada, Universidad de Granada, Granada, Spain
- Otology & Neurotology Group CTS495, Instituto de Investigación Biosanitaria, ibs.GRANADA, Universidad de Granada, Granada, Spain
- Sensorineural Pathology Program, Centro de Investigación Biomédica en Red en Enfermedades Raras, CIBERER, Madrid, Spain
- Department of Otolaryngology, Hospital Universitario San Cecilio, Instituto de Investigacion Biosanitaria, ibs.GRANADA, Granada, Spain
| | - Jose A Lopez-Escamez
- Meniere's Disease Neuroscience Research Program, Faculty of Medicine and Health, School of Medical Sciences, The Kolling Institute, University of Sydney, Rm 611024, Level 11 Kolling Institute | 10 Westbourne St, St Leonards, Sydney, NSW, 2064, Australia
- Division of Otolaryngology, Department of Surgery, Instituto de Investigación Biosanitaria, Ibs.Granada, Universidad de Granada, Granada, Spain
- Otology & Neurotology Group CTS495, Instituto de Investigación Biosanitaria, ibs.GRANADA, Universidad de Granada, Granada, Spain
- Sensorineural Pathology Program, Centro de Investigación Biomédica en Red en Enfermedades Raras, CIBERER, Madrid, Spain
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Chen BH, Zhou W. mLiftOver: harmonizing data across Infinium DNA methylation platforms. BIOINFORMATICS (OXFORD, ENGLAND) 2024; 40:btae423. [PMID: 38963309 PMCID: PMC11233119 DOI: 10.1093/bioinformatics/btae423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 06/07/2024] [Accepted: 07/03/2024] [Indexed: 07/05/2024]
Abstract
MOTIVATION Infinium DNA methylation BeadChips are widely used for genome-wide DNA methylation profiling at the population scale. Recent updates to probe content and naming conventions in the EPIC version 2 (EPICv2) arrays have complicated integrating new data with previous Infinium array platforms, such as the MethylationEPIC (EPIC) and the HumanMethylation450 (HM450) BeadChip. RESULTS We present mLiftOver, a user-friendly tool that harmonizes probe ID, methylation level, and signal intensity data across different Infinium platforms. It manages probe replicates, missing data imputation, and platform-specific bias for accurate data conversion. We validated the tool by applying HM450-based cancer classifiers to EPICv2 cancer data, achieving high accuracy. Additionally, we successfully integrated EPICv2 healthy tissue data with legacy HM450 data for tissue identity analysis and produced consistent copy number profiles in cancer cells. AVAILABILITY AND IMPLEMENTATION mLiftOver is implemented R and available in the Bioconductor package SeSAMe (version 1.21.13+): https://bioconductor.org/packages/release/bioc/html/sesame.html. Analysis of EPIC and EPICv2 platform-specific bias and high-confidence mapping is available at https://github.com/zhou-lab/InfiniumAnnotationV1/raw/main/Anno/EPICv2/EPICv2ToEPIC_conversion.tsv.gz. The source code is available at https://github.com/zwdzwd/sesame/blob/devel/R/mLiftOver.R under the MIT license.
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Affiliation(s)
- Brian H Chen
- California Pacific Medical Center Research Institute, Sutter Health, San Francisco, CA 94143, United States
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, United States
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
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7
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Feng Y, Gao F. bsgenova: an accurate, robust, and fast genotype caller for bisulfite-sequencing data. BMC Bioinformatics 2024; 25:206. [PMID: 38840038 PMCID: PMC11151569 DOI: 10.1186/s12859-024-05821-7] [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: 03/18/2024] [Accepted: 05/30/2024] [Indexed: 06/07/2024] Open
Abstract
BACKGROUND Bisulfite sequencing (BS-Seq) is a fundamental technique for characterizing DNA methylation profiles. Genotype calling from bisulfite-converted BS-Seq data allows allele-specific methylation analysis and the concurrent exploration of genetic and epigenetic profiles. Despite various methods have been proposed, single nucleotide polymorphisms (SNPs) calling from BS-Seq data, particularly for SNPs on chromosome X and in the presence of contaminative data, poses ongoing challenges. RESULTS We introduce bsgenova, a novel SNP caller tailored for bisulfite sequencing data, employing a Bayesian multinomial model. The performance of bsgenova is assessed by comparing SNPs called from real-world BS-Seq data with those from corresponding whole-genome sequencing (WGS) data across three human cell lines. bsgenova is both sensitive and precise, especially for chromosome X, compared with three existing methods. Moreover, in the presence of low-quality reads, bsgenova outperforms other methods notably. In addition, bsgenova is meticulously implemented, leveraging matrix imputation and multi-process parallelization. Compared to existing methods, bsgenova stands out for its speed and efficiency in memory and disk usage. Furthermore, bsgenova integrates bsextractor, a methylation extractor, enhancing its flexibility and expanding its utility. CONCLUSIONS We introduce bsgenova for SNP calling from bisulfite-sequencing data. The source code is available at https://github.com/hippo-yf/bsgenova under license GPL-3.0.
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Affiliation(s)
- Yance Feng
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
| | - Fei Gao
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
- HIM-BGI Omics Center, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences (CAS), Hangzhou, China.
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Caeser R, Chiang J, Tan ES, Tai ES, Ngeow J. Cascade testing for hereditary cancer in Singapore: how population genomics help guide clinical policy. Fam Cancer 2024; 23:133-140. [PMID: 38662262 DOI: 10.1007/s10689-024-00376-1] [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: 03/11/2024] [Accepted: 03/14/2024] [Indexed: 04/26/2024]
Abstract
Hereditary Cancer makes up around 5-10% of all cancers. It is important to diagnose hereditary cancer in a timely fashion, as not only do patients require long-term care from a young age, but their relatives also require management. The main approach to capture at-risk relatives is cascade testing. It involves genetic testing of relatives of the first detected carrier of a pathogenic variant in a family i.e. the proband. The current standard of care for cascade testing is a patient-mediated approach. Probands are then advised to inform and encourage family members to undergo genetic testing. In Singapore, cascade testing is inefficient, around 10-15%, lower than the 30% global average. Here, we describe the cascade testing process and its effort to increase testing in Singapore. Precision Health Research, Singapore (PRECISE), was set up to coordinate Singapore's National Precision Medicine strategy and has awarded five clinical implementation pilots, with one of them seeking to identify strategies for how cascade testing for hereditary cancer can be increased in a safe and cost-efficient manner. Achieving this will be done through addressing barriers such as cost, manpower shortages, exploring a digital channel for contacting at-risk relatives, and getting a deeper insight into why genetic testing gets declined. If successful, it will likely result in care pathways that are a cost-effective public health intervention for identifying individuals at risk. Surveillance and management of those unaffected at-risk individuals, if caught early, will result in improved patient outcomes, and further reduce the healthcare burden for the economy.
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Affiliation(s)
- Rebecca Caeser
- Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre Singapore, Singapore, 169610, Singapore
- Oncology Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
| | - Jianbang Chiang
- Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre Singapore, Singapore, 169610, Singapore
- Oncology Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
| | - Ee Shien Tan
- Duke-National University of Singapore (NUS) Medical School, National University of Singapore, Singapore, Singapore
- Genetics Service, Department of Pediatrics, Kadang Kerbau (KK) Women's and Children's Hospital, Singapore, Singapore
| | - E Shyong Tai
- Duke-National University of Singapore (NUS) Medical School, National University of Singapore, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Precision Health Research, Singapore, Singapore
| | - Joanne Ngeow
- Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre Singapore, Singapore, 169610, Singapore.
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore.
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9
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Kuraz Abebe B, Wang J, Guo J, Wang H, Li A, Zan L. A review of the role of epigenetic studies for intramuscular fat deposition in beef cattle. Gene 2024; 908:148295. [PMID: 38387707 DOI: 10.1016/j.gene.2024.148295] [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: 10/26/2023] [Revised: 01/23/2024] [Accepted: 02/15/2024] [Indexed: 02/24/2024]
Abstract
Intramuscular fat (IMF) deposition profoundly influences meat quality and economic value in beef cattle production. Meanwhile, contemporary developments in epigenetics have opened new outlooks for understanding the molecular basics of IMF regulation, and it has become a key area of research for world scholars. Therefore, the aim of this paper was to provide insight and synthesis into the intricate relationship between epigenetic mechanisms and IMF deposition in beef cattle. The methodology involves a thorough analysis of existing literature, including pertinent books, academic journals, and online resources, to provide a comprehensive overview of the role of epigenetic studies in IMF deposition in beef cattle. This review summarizes the contemporary studies in epigenetic mechanisms in IMF regulation, high-resolution epigenomic mapping, single-cell epigenomics, multi-omics integration, epigenome editing approaches, longitudinal studies in cattle growth, environmental epigenetics, machine learning in epigenetics, ethical and regulatory considerations, and translation to industry practices from perspectives of IMF deposition in beef cattle. Moreover, this paper highlights DNA methylation, histone modifications, acetylation, phosphorylation, ubiquitylation, non-coding RNAs, DNA hydroxymethylation, epigenetic readers, writers, and erasers, chromatin immunoprecipitation followed by sequencing, whole genome bisulfite sequencing, epigenome-wide association studies, and their profound impact on the expression of crucial genes governing adipogenesis and lipid metabolism. Nutrition and stress also have significant influences on epigenetic modifications and IMF deposition. The key findings underscore the pivotal role of epigenetic studies in understanding and enhancing IMF deposition in beef cattle, with implications for precision livestock farming and ethical livestock management. In conclusion, this review highlights the crucial significance of epigenetic pathways and environmental factors in affecting IMF deposition in beef cattle, providing insightful information for improving the economics and meat quality of cattle production.
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Affiliation(s)
- Belete Kuraz Abebe
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China; Department of Animal Science, Werabe University, P.O. Box 46, Werabe, Ethiopia
| | - Jianfang Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Juntao Guo
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Hongbao Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Anning Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China; National Beef Cattle Improvement Center, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China.
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10
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Goldberg DC, Cloud C, Lee SM, Barnes B, Gruber S, Kim E, Pottekat A, Westphal M, McAuliffe L, Majournie E, KalayilManian M, Zhu Q, Tran C, Hansen M, Parker JB, Kohli RM, Porecha R, Renke N, Zhou W. MSA: scalable DNA methylation screening BeadChip for high-throughput trait association studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.17.594606. [PMID: 38826316 PMCID: PMC11142114 DOI: 10.1101/2024.05.17.594606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
The Infinium DNA Methylation BeadChips have significantly contributed to population-scale epigenetics research by enabling epigenome-wide trait association discoveries. Here, we design, describe, and experimentally verify a new iteration of this technology, the Methylation Screening Array (MSA), to focus on human trait screening and discovery. This array utilizes extensive data from previous Infinium platform-based epigenome-wide association studies (EWAS). It incorporates knowledge from the latest single-cell and cell type-resolution whole genome methylome profiles. The MSA is engineered to achieve scalable screening of epigenetics-trait association in an ultra-high sample throughput. Our design encompassed diverse human trait associations, including those with genetic, cellular, environmental, and demographical variables and human diseases such as genetic, neurodegenerative, cardiovascular, infectious, and immune diseases. We comprehensively evaluated this array's reproducibility, accuracy, and capacity for cell-type deconvolution and supporting 5-hydroxymethylation profiling in diverse human tissues. Our first atlas data using this platform uncovered the complex chromatin and tissue contexts of DNA modification variations and genetic variants linked to human phenotypes.
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Affiliation(s)
- David C Goldberg
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | - Cameron Cloud
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | - Sol Moe Lee
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | | | | | - Elliot Kim
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | | | | | | | | | | | | | | | | | - Jared B Parker
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Rahul M Kohli
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | | | | | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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11
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Tang Y, Zhang J, Li W, Liu X, Chen S, Mi S, Yang J, Teng J, Fang L, Yu Y. Identification and characterization of whole blood gene expression and splicing quantitative trait loci during early to mid-lactation of dairy cattle. BMC Genomics 2024; 25:445. [PMID: 38711039 DOI: 10.1186/s12864-024-10346-7] [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: 09/30/2023] [Accepted: 04/25/2024] [Indexed: 05/08/2024] Open
Abstract
BACKGROUND Characterization of regulatory variants (e.g., gene expression quantitative trait loci, eQTL; gene splicing QTL, sQTL) is crucial for biologically interpreting molecular mechanisms underlying loci associated with complex traits. However, regulatory variants in dairy cattle, particularly in specific biological contexts (e.g., distinct lactation stages), remain largely unknown. In this study, we explored regulatory variants in whole blood samples collected during early to mid-lactation (22-150 days after calving) of 101 Holstein cows and analyzed them to decipher the regulatory mechanisms underlying complex traits in dairy cattle. RESULTS We identified 14,303 genes and 227,705 intron clusters expressed in the white blood cells of 101 cattle. The average heritability of gene expression and intron excision ratio explained by cis-SNPs is 0.28 ± 0.13 and 0.25 ± 0.13, respectively. We identified 23,485 SNP-gene expression pairs and 18,166 SNP-intron cluster pairs in dairy cattle during early to mid-lactation. Compared with the 2,380,457 cis-eQTLs reported to be present in blood in the Cattle Genotype-Tissue Expression atlas (CattleGTEx), only 6,114 cis-eQTLs (P < 0.05) were detected in the present study. By conducting colocalization analysis between cis-e/sQTL and the results of genome-wide association studies (GWAS) from four traits, we identified a cis-e/sQTL (rs109421300) of the DGAT1 gene that might be a key marker in early to mid-lactation for milk yield, fat yield, protein yield, and somatic cell score (PP4 > 0.6). Finally, transcriptome-wide association studies (TWAS) revealed certain genes (e.g., FAM83H and TBC1D17) whose expression in white blood cells was significantly (P < 0.05) associated with complex traits. CONCLUSIONS This study investigated the genetic regulation of gene expression and alternative splicing in dairy cows during early to mid-lactation and provided new insights into the regulatory mechanisms underlying complex traits of economic importance.
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Affiliation(s)
- Yongjie Tang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Jinning Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Wenlong Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xueqin Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Siqian Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Siyuan Mi
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Jinyan Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Jinyan Teng
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, 8000, Denmark.
| | - Ying Yu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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12
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Peng Q, Liu X, Li W, Jing H, Li J, Gao X, Luo Q, Breeze CE, Pan S, Zheng Q, Li G, Qian J, Yuan L, Yuan N, You C, Du S, Zheng Y, Yuan Z, Tan J, Jia P, Wang J, Zhang G, Lu X, Shi L, Guo S, Liu Y, Ni T, Wen B, Zeng C, Jin L, Teschendorff AE, Liu F, Wang S. Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits. Nat Genet 2024; 56:846-860. [PMID: 38641644 DOI: 10.1038/s41588-023-01494-9] [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: 11/17/2021] [Accepted: 08/02/2023] [Indexed: 04/21/2024]
Abstract
Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.
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Affiliation(s)
- Qianqian Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xinxuan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Wenran Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Han Jing
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jiarui Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xingjian Gao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Qi Luo
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | | | - Siyu Pan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Qiwen Zheng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Guochao Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Jiaqiang Qian
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Liyun Yuan
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Na Yuan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Chenglong You
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, and Human Phenome Institute, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Ziyu Yuan
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
| | - Jingze Tan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, and Human Phenome Institute, Fudan University, Shanghai, China
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
- Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai, China
| | - Guoqing Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
| | - Xianping Lu
- Shenzhen Chipscreen Biosciences Co. Ltd., Shenzhen, China
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, and Human Phenome Institute, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
| | - Shicheng Guo
- Department of Medical Genetics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Yun Liu
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Ting Ni
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, School of Life Sciences and Huashan Hospital, Fudan University, Shanghai, China
| | - Bo Wen
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, and Human Phenome Institute, Fudan University, Shanghai, China
- The Fifth People's Hospital of Shanghai and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Changqing Zeng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, and Human Phenome Institute, Fudan University, Shanghai, China
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
- Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai, China
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, China.
- Department of Forensic Sciences, College of Criminal Justice, Naif Arab University of Security Sciences, Riyadh, Kingdom of Saudi Arabia.
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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13
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Shen H, Chen Y, Xu M, Zhou J, Huang C, Wang Z, Shao Y, Zhang H, Lu Y, Li S, Fu Z. Cellular senescence gene TACC3 associated with colorectal cancer risk via genetic and DNA methylated alteration. Arch Toxicol 2024; 98:1499-1513. [PMID: 38480537 DOI: 10.1007/s00204-024-03702-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 02/06/2024] [Indexed: 03/27/2024]
Abstract
Cell senescence genes play a vital role in the pathogenesis of colorectal cancer, a process that may involve the triggering of genetic variations and reversible phenotypes caused by epigenetic modifications. However, the specific regulatory mechanisms remain unclear. Using CellAge and The Cancer Genome Atlas databases and in-house RNA-seq data, DNA methylation-modified cellular senescence genes (DMCSGs) were validated by Support Vector Machine and correlation analyses. In 1150 cases and 1342 controls, we identified colorectal cancer risk variants in DMCSGs. The regulatory effects of gene, variant, and DNA methylation were explored through dual-luciferase and 5-azacytidine treatment experiments, complemented by multiple database analyses. Biological functions of key gene were evaluated via cell proliferation assays, SA-β-gal staining, senescence marker detection, and immune infiltration analyses. The genetic variant rs4558926 in the downstream of TACC3 was significantly associated with colorectal cancer risk (OR = 1.35, P = 3.22 × 10-4). TACC3 mRNA expression increased due to rs4558926 C > G and decreased DNA methylation levels. The CpG sites in the TACC3 promoter region were regulated by rs4558926. TACC3 knockdown decreased proliferation and senescence in colorectal cancer cells. In addition, subjects with high-TACC3 expression presented an immunosuppressive microenvironment. These findings provide insights into the involvement of genetic variants of cellular senescence genes in the development and progression of colorectal cancer.
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Affiliation(s)
- Hengyang Shen
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yang Chen
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Menghuan Xu
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jieyu Zhou
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Changzhi Huang
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zhenling Wang
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yu Shao
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongqiang Zhang
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yunfei Lu
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Shuwei Li
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Zan Fu
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
- The First School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.
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14
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Lee SM, Loo C, Prasasya R, Bartolomei M, Kohli R, Zhou W. Low-input and single-cell methods for Infinium DNA methylation BeadChips. Nucleic Acids Res 2024; 52:e38. [PMID: 38407446 PMCID: PMC11040145 DOI: 10.1093/nar/gkae127] [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: 09/11/2023] [Revised: 01/29/2024] [Accepted: 02/10/2024] [Indexed: 02/27/2024] Open
Abstract
The Infinium BeadChip is the most widely used DNA methylome assay technology for population-scale epigenome profiling. However, the standard workflow requires over 200 ng of input DNA, hindering its application to small cell-number samples, such as primordial germ cells. We developed experimental and analysis workflows to extend this technology to suboptimal input DNA conditions, including ultra-low input down to single cells. DNA preamplification significantly enhanced detection rates to over 50% in five-cell samples and ∼25% in single cells. Enzymatic conversion also substantially improved data quality. Computationally, we developed a method to model the background signal's influence on the DNA methylation level readings. The modified detection P-value calculation achieved higher sensitivities for low-input datasets and was validated in over 100 000 public diverse methylome profiles. We employed the optimized workflow to query the demethylation dynamics in mouse primordial germ cells available at low cell numbers. Our data revealed nuanced chromatin states, sex disparities, and the role of DNA methylation in transposable element regulation during germ cell development. Collectively, we present comprehensive experimental and computational solutions to extend this widely used methylation assay technology to applications with limited DNA.
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Affiliation(s)
- Sol Moe Lee
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA 19104, USA
| | - Christian E Loo
- Graduate Group in Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rexxi D Prasasya
- Department of Cell and Developmental Biology, Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Marisa S Bartolomei
- Department of Cell and Developmental Biology, Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Rahul M Kohli
- Department of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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15
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Qin Q, Zhou Y, Guo J, Chen Q, Tang W, Li Y, You J, Li Q. Conserved methylation signatures associate with the tumor immune microenvironment and immunotherapy response. Genome Med 2024; 16:47. [PMID: 38566132 PMCID: PMC10985907 DOI: 10.1186/s13073-024-01318-3] [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: 03/16/2023] [Accepted: 03/20/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Aberrant DNA methylation is a major characteristic of cancer genomes. It remains unclear which biological processes determine epigenetic reprogramming and how these processes influence the variants in the cancer methylome, which can further impact cancer phenotypes. METHODS We performed pairwise permutations of 381,900 loci in 569 paired DNA methylation profiles of cancer tissue and matched normal tissue from The Cancer Genome Atlas (TCGA) and defined conserved differentially methylated positions (DMPs) based on the resulting null distribution. Then, we derived independent methylation signatures from 2,465 cancer-only methylation profiles from the TCGA and 241 cell line-based methylation profiles from the Genomics of Drug Sensitivity in Cancer (GDSC) cohort using nonnegative matrix factorization (NMF). We correlated DNA methylation signatures with various clinical and biological features, including age, survival, cancer stage, tumor immune microenvironment factors, and immunotherapy response. We inferred the determinant genes of these methylation signatures by integrating genomic and transcriptomic data and evaluated the impact of these signatures on cancer phenotypes in independent bulk and single-cell RNA/methylome cohorts. RESULTS We identified 7,364 differentially methylated positions (2,969 Hyper-DMPs and 4,395 Hypo-DMPs) in nine cancer types from the TCGA. We subsequently retrieved three highly conserved, independent methylation signatures (Hyper-MS1, Hypo-MS1, and Hypo-MS4) from cancer tissues and cell lines based on these Hyper and Hypo-DMPs. Our data suggested that Hypo-MS4 activity predicts poor survival and is associated with immunotherapy response and distant tumor metastasis, and Hypo-MS4 activity is related to TP53 mutation and FOXA1 binding specificity. In addition, we demonstrated a correlation between the activities of Hypo-MS4 in cancer cells and the fractions of regulatory CD4 + T cells with the expression levels of immunological genes in the tumor immune microenvironment. CONCLUSIONS Our findings demonstrated that the methylation signatures of distinct biological processes are associated with immune activity in the cancer microenvironment and predict immunotherapy response.
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Affiliation(s)
- Qingqing Qin
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China
- Department of Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, 361003, China
| | - Ying Zhou
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China
- Department of Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, 361003, China
| | - Jintao Guo
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China
- Department of Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, 361003, China
| | - Qinwei Chen
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China
| | - Weiwei Tang
- Department of Medical Oncology, School of Medicine, The First Affiliated Hospital of Xiamen University and Institute of Hematology, Xiamen University, Xiamen, 361003, China
- Xiamen Key Laboratory of Antitumor Drug Transformation Research, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, The School of Clinical Medicine of Fujian, Medical University, Xiamen, 361003, China
| | - Yuchen Li
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China
- Department of Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, 361003, China
| | - Jun You
- Department of Gastrointestinal Oncology Surgery, The First Affiliated Hospital of Xiamen University, Cancer Center, Xiamen, 361003, China
| | - Qiyuan Li
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China.
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China.
- Department of Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, 361003, China.
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16
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Hatton AA, Cheng FF, Lin T, Shen RJ, Chen J, Zheng Z, Qu J, Lyu F, Harris SE, Cox SR, Jin ZB, Martin NG, Fan D, Montgomery GW, Yang J, Wray NR, Marioni RE, Visscher PM, McRae AF. Genetic control of DNA methylation is largely shared across European and East Asian populations. Nat Commun 2024; 15:2713. [PMID: 38548728 PMCID: PMC10978881 DOI: 10.1038/s41467-024-47005-0] [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: 05/29/2023] [Accepted: 03/15/2024] [Indexed: 04/01/2024] Open
Abstract
DNA methylation is an ideal trait to study the extent of the shared genetic control across ancestries, effectively providing hundreds of thousands of model molecular traits with large QTL effect sizes. We investigate cis DNAm QTLs in three European (n = 3701) and two East Asian (n = 2099) cohorts to quantify the similarities and differences in the genetic architecture across populations. We observe 80,394 associated mQTLs (62.2% of DNAm probes with significant mQTL) to be significant in both ancestries, while 28,925 mQTLs (22.4%) are identified in only a single ancestry. mQTL effect sizes are highly conserved across populations, with differences in mQTL discovery likely due to differences in allele frequency of associated variants and differing linkage disequilibrium between causal variants and assayed SNPs. This study highlights the overall similarity of genetic control across ancestries and the value of ancestral diversity in increasing the power to detect associations and enhancing fine mapping resolution.
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Affiliation(s)
- Alesha A Hatton
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Fei-Fei Cheng
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- School of Life Sciences, Westlake University, Hangzhou, 310030, Zhejiang, China
| | - Tian Lin
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Ren-Juan Shen
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, 100008, Beijing, China
- School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, 325027, China
| | - Jie Chen
- School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, 325027, China
| | - Zhili Zheng
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Jia Qu
- School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, 325027, China
| | - Fan Lyu
- School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, 325027, China
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Zi-Bing Jin
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, 100008, Beijing, China
- School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, 325027, China
| | - Nicholas G Martin
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, 4006, Australia
| | - Dongsheng Fan
- Department of Neurology, Peking University Third Hospital, 100191, Beijing, China
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Jian Yang
- School of Life Sciences, Westlake University, Hangzhou, 310030, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, 310024, Zhejiang, China
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
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17
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Li Y, Gong J, Sun Q, Vong EG, Cheng X, Wang B, Yuan Y, Jin L, Gamazon ER, Zhou D, Lai M, Zhang D. Alternative polyadenylation quantitative trait methylation mapping in human cancers provides clues into the molecular mechanisms of APA. Am J Hum Genet 2024; 111:562-583. [PMID: 38367620 PMCID: PMC10940021 DOI: 10.1016/j.ajhg.2024.01.010] [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: 09/12/2023] [Revised: 01/19/2024] [Accepted: 01/22/2024] [Indexed: 02/19/2024] Open
Abstract
Genetic variants are involved in the orchestration of alternative polyadenylation (APA) events, while the role of DNA methylation in regulating APA remains unclear. We generated a comprehensive atlas of APA quantitative trait methylation sites (apaQTMs) across 21 different types of cancer (1,612 to 60,219 acting in cis and 4,448 to 142,349 in trans). Potential causal apaQTMs in non-cancer samples were also identified. Mechanistically, we observed a strong enrichment of cis-apaQTMs near polyadenylation sites (PASs) and both cis- and trans-apaQTMs in proximity to transcription factor (TF) binding regions. Through the integration of ChIP-signals and RNA-seq data from cell lines, we have identified several regulators of APA events, acting either directly or indirectly, implicating novel functions of some important genes, such as TCF7L2, which is known for its involvement in type 2 diabetes and cancers. Furthermore, we have identified a vast number of QTMs that share the same putative causal CpG sites with five different cancer types, underscoring the roles of QTMs, including apaQTMs, in the process of tumorigenesis. DNA methylation is extensively involved in the regulation of APA events in human cancers. In an attempt to elucidate the potential underlying molecular mechanisms of APA by DNA methylation, our study paves the way for subsequent experimental validations into the intricate biological functions of DNA methylation in APA regulation and the pathogenesis of human cancers. To present a comprehensive catalog of apaQTM patterns, we introduce the Pancan-apaQTM database, available at https://pancan-apaqtm-zju.shinyapps.io/pancanaQTM/.
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Affiliation(s)
- Yige Li
- Department of Pathology, and Department of Medical Oncology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China; Department of Pathology, Key Laboratory of Disease Proteomics of Zhejiang Province, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China; Department of Pathology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
| | - Jingwen Gong
- Department of Pathology, and Department of Medical Oncology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China; Department of Pathology, Key Laboratory of Disease Proteomics of Zhejiang Province, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China; Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, Zhejiang Province, China
| | - Qingrong Sun
- Department of Pathology, Key Laboratory of Disease Proteomics of Zhejiang Province, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China; Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, Zhejiang Province, China; Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou, Zhejiang Province, China; College of Information Science and Technology, ZheJiang Shuren University, Hangzhou 310015, ZheJiang, China
| | - Eu Gene Vong
- Department of Pathology, Key Laboratory of Disease Proteomics of Zhejiang Province, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China; Department of Biochemistry and Genetics, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China; The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
| | - Xiaoqing Cheng
- Department of Pathology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
| | - Binghong Wang
- Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
| | - Ying Yuan
- Department of Medical Oncology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China; Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, Chinese National Ministry of Education), the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China; Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai, China
| | - Eric R Gamazon
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Data Science Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dan Zhou
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Maode Lai
- Department of Pathology, Key Laboratory of Disease Proteomics of Zhejiang Province, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China; Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, Zhejiang Province, China; Department of Pathology, Research Unit of Intelligence Classification of Tumor Pathology and Precision Therapy, Chinese Academy of Medical Sciences (2019RU042), Key Laboratory of Disease Proteomics of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.
| | - Dandan Zhang
- Department of Pathology, and Department of Medical Oncology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China; Department of Pathology, Key Laboratory of Disease Proteomics of Zhejiang Province, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China; Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, Zhejiang Province, China; Department of Pathology, Research Unit of Intelligence Classification of Tumor Pathology and Precision Therapy, Chinese Academy of Medical Sciences (2019RU042), Key Laboratory of Disease Proteomics of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.
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18
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Advani J, Mehta PA, Hamel AR, Mehrotra S, Kiel C, Strunz T, Corso-Díaz X, Kwicklis M, van Asten F, Ratnapriya R, Chew EY, Hernandez DG, Montezuma SR, Ferrington DA, Weber BHF, Segrè AV, Swaroop A. QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration. Nat Commun 2024; 15:1972. [PMID: 38438351 PMCID: PMC10912779 DOI: 10.1038/s41467-024-46063-8] [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: 06/08/2023] [Accepted: 02/12/2024] [Indexed: 03/06/2024] Open
Abstract
DNA methylation provides a crucial epigenetic mark linking genetic variations to environmental influence. We have analyzed array-based DNA methylation profiles of 160 human retinas with co-measured RNA-seq and >8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 methylation quantitative trait loci and 12,505 expression quantitative trait loci) and 13,747 DNA methylation loci affecting gene expression, with over one-third specific to the retina. Methylation and expression quantitative trait loci show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration. Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of macular degeneration pathology by genotype-environment interaction in retina.
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Affiliation(s)
- Jayshree Advani
- Neurobiology, Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Puja A Mehta
- Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear, Boston, MA, USA
- Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrew R Hamel
- Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear, Boston, MA, USA
- Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sudeep Mehrotra
- Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear, Boston, MA, USA
- Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Christina Kiel
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
| | - Tobias Strunz
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
| | - Ximena Corso-Díaz
- Neurobiology, Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Madeline Kwicklis
- Neurobiology, Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Freekje van Asten
- Neurobiology, Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rinki Ratnapriya
- Neurobiology, Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Emily Y Chew
- Division of Epidemiology and Clinical Applications, Clinical Trials Branch, National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Dena G Hernandez
- Laboratory of Neurogenetics, National Institute of Aging, National Institutes of Health, Bethesda, MD, USA
| | - Sandra R Montezuma
- Department of Ophthalmology and Visual Neurosciences, University of Minnesota, Minneapolis, MN, USA
| | - Deborah A Ferrington
- Department of Ophthalmology and Visual Neurosciences, University of Minnesota, Minneapolis, MN, USA
- Doheny Eye Institute, Pasadena, CA, USA
| | - Bernhard H F Weber
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
- Institute of Clinical Human Genetics, University Hospital Regensburg, Regensburg, Germany
| | - Ayellet V Segrè
- Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear, Boston, MA, USA.
- Department of Ophthalmology, Harvard Medical School, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Anand Swaroop
- Neurobiology, Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, Bethesda, MD, USA.
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19
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Hu X, Chen S, Ye S, Chen W, Zhou Y. New insights into the role of immunity and inflammation in diabetic kidney disease in the omics era. Front Immunol 2024; 15:1342837. [PMID: 38487541 PMCID: PMC10937589 DOI: 10.3389/fimmu.2024.1342837] [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: 11/22/2023] [Accepted: 02/19/2024] [Indexed: 03/17/2024] Open
Abstract
Diabetic kidney disease (DKD) is becoming the leading cause of chronic kidney disease, especially in the industrialized world. Despite mounting evidence has demonstrated that immunity and inflammation are highly involved in the pathogenesis and progression of DKD, the underlying mechanisms remain incompletely understood. Substantial molecules, signaling pathways, and cell types participate in DKD inflammation, by integrating into a complex regulatory network. Most of the studies have focused on individual components, without presenting their importance in the global or system-based processes, which largely hinders clinical translation. Besides, conventional technologies failed to monitor the different behaviors of resident renal cells and immune cells, making it difficult to understand their contributions to inflammation in DKD. Recently, the advancement of omics technologies including genomics, epigenomics, transcriptomics, proteomics, and metabolomics has revolutionized biomedical research, which allows an unbiased global analysis of changes in DNA, RNA, proteins, and metabolites in disease settings, even at single-cell and spatial resolutions. They help us to identify critical regulators of inflammation processes and provide an overview of cell heterogeneity in DKD. This review aims to summarize the application of multiple omics in the field of DKD and emphasize the latest evidence on the interplay of inflammation and DKD revealed by these technologies, which will provide new insights into the role of inflammation in the pathogenesis of DKD and lead to the development of novel therapeutic approaches and diagnostic biomarkers.
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Affiliation(s)
- Xinrong Hu
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, China
| | - Sixiu Chen
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, China
| | - Siyang Ye
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, China
| | - Wei Chen
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, China
| | - Yi Zhou
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, China
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20
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Kasela S, Aguet F, Kim-Hellmuth S, Brown BC, Nachun DC, Tracy RP, Durda P, Liu Y, Taylor KD, Johnson WC, Van Den Berg D, Gabriel S, Gupta N, Smith JD, Blackwell TW, Rotter JI, Ardlie KG, Manichaikul A, Rich SS, Barr RG, Lappalainen T. Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects. Am J Hum Genet 2024; 111:133-149. [PMID: 38181730 PMCID: PMC10806864 DOI: 10.1016/j.ajhg.2023.11.013] [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: 06/22/2023] [Revised: 11/29/2023] [Accepted: 11/29/2023] [Indexed: 01/07/2024] Open
Abstract
Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of diseases that, in combination with additional functional data, could guide future functional studies. Overall, this study highlights the use of iQTLs to gain insights into the context specificity of regulatory effects.
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Affiliation(s)
- Silva Kasela
- New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA.
| | | | - Sarah Kim-Hellmuth
- New York Genome Center, New York, NY, USA; Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital LMU Munich, Munich, Germany; Computational Health Center, Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
| | - Brielin C Brown
- New York Genome Center, New York, NY, USA; Data Science Institute, Columbia University, New York, NY, USA
| | - Daniel C Nachun
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Russell P Tracy
- Pathology and Laboratory Medicine, The University of Vermont, Larner College of Medicine, Burlington, VT, USA
| | - Peter Durda
- Pathology and Laboratory Medicine, The University of Vermont, Larner College of Medicine, Burlington, VT, USA
| | - Yongmei Liu
- Department of Medicine, Duke University, Durham, NC, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - David Van Den Berg
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | | | - Namrata Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joshua D Smith
- Northwest Genomics Center, University of Washington, Seattle, WA, USA
| | - Thomas W Blackwell
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R Graham Barr
- Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA; Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
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21
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Ohlei O, Sommerer Y, Dobricic V, Homann J, Deecke L, Schilling M, Bartrés-Faz D, Cattaneo G, Düzel S, Fjell AM, Lindenberger U, Pascual-Leone Á, Sedghpour Sabet S, Solé-Padullés C, Tormos JM, Vetter VM, Walhovd KB, Wesse T, Wittig M, Franke A, Demuth I, Lill CM, Bertram L. Genome-wide QTL mapping across three tissues highlights several Alzheimer's and Parkinson's disease loci potentially acting via DNA methylation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.22.23300365. [PMID: 38196633 PMCID: PMC10775408 DOI: 10.1101/2023.12.22.23300365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
DNA methylation (DNAm) is an epigenetic mark with essential roles in disease development and predisposition. Here, we created genome-wide maps of methylation quantitative trait loci (meQTL) in three peripheral tissues and used Mendelian randomization (MR) analyses to assess the potential causal relationships between DNAm and risk for two common neurodegenerative disorders, i.e. Alzheimer's disease (AD) and Parkinson's disease (PD). Genome-wide single nucleotide polymorphism (SNP; ~5.5M sites) and DNAm (~850K CpG sites) data were generated from whole blood (n=1,058), buccal (n=1,527) and saliva (n=837) specimens. We identified between 11 and 15 million genome-wide significant (p<10-14) SNP-CpG associations in each tissue. Combining these meQTL GWAS results with recent AD/PD GWAS summary statistics by MR strongly suggests that the previously described associations between PSMC3, PICALM, and TSPAN14 and AD may be founded on differential DNAm in or near these genes. In addition, there is strong, albeit less unequivocal, support for causal links between DNAm at PRDM7 in AD as well as at KANSL1/MAPT in AD and PD. Our study adds valuable insights on AD/PD pathogenesis by combining two high-resolution "omics" domains, and the meQTL data shared along with this publication will allow like-minded analyses in other diseases.
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Affiliation(s)
- Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Jan Homann
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Laura Deecke
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Marcel Schilling
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
- Gene Regulation of Cell Identity, Regenerative Medicine Program, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, Barcelona, Spain
| | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Gabriele Cattaneo
- Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la UAB, Barcelona, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain
- Fundació Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, Camí de les Escoles, Badalona, Barcelona, Spain
| | - Sandra Düzel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Álvaro Pascual-Leone
- Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Sanaz Sedghpour Sabet
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Cristina Solé-Padullés
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Josep M Tormos
- Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la UAB, Barcelona, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain
- Fundació Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, Camí de les Escoles, Badalona, Barcelona, Spain
| | - Valentin M Vetter
- Biology of Aging Working Group, Department of Endocrinology and Metabolic Diseases, Division of Lipid Metabolism, Charité-Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Tanja Wesse
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Michael Wittig
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Ilja Demuth
- Biology of Aging Working Group, Department of Endocrinology and Metabolic Diseases, Division of Lipid Metabolism, Charité-Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany
- Berlin Institute of Health Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Christina M Lill
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
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22
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Mozhui K, Kim H, Villani F, Haghani A, Sen S, Horvath S. Pleiotropic influence of DNA methylation QTLs on physiological and ageing traits. Epigenetics 2023; 18:2252631. [PMID: 37691384 PMCID: PMC10496549 DOI: 10.1080/15592294.2023.2252631] [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: 05/01/2023] [Revised: 07/31/2023] [Accepted: 08/16/2023] [Indexed: 09/12/2023] Open
Abstract
DNA methylation is influenced by genetic and non-genetic factors. Here, we chart quantitative trait loci (QTLs) that modulate levels of methylation at highly conserved CpGs using liver methylome data from mouse strains belonging to the BXD family. A regulatory hotspot on chromosome 5 had the highest density of trans-acting methylation QTLs (trans-meQTLs) associated with multiple distant CpGs. We refer to this locus as meQTL.5a. Trans-modulated CpGs showed age-dependent changes and were enriched in developmental genes, including several members of the MODY pathway (maturity onset diabetes of the young). The joint modulation by genotype and ageing resulted in a more 'aged methylome' for BXD strains that inherited the DBA/2J parental allele at meQTL.5a. Further, several gene expression traits, body weight, and lipid levels mapped to meQTL.5a, and there was a modest linkage with lifespan. DNA binding motif and protein-protein interaction enrichment analyses identified the hepatic nuclear factor, Hnf1a (MODY3 gene in humans), as a strong candidate. The pleiotropic effects of meQTL.5a could contribute to variations in body size and metabolic traits, and influence CpG methylation and epigenetic ageing that could have an impact on lifespan.
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Affiliation(s)
- Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Hyeonju Kim
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Flavia Villani
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Saunak Sen
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
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23
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Li C, Shao J, Li P, Feng J, Li J, Wang C. Circulating tumor DNA as liquid biopsy in lung cancer: Biological characteristics and clinical integration. Cancer Lett 2023; 577:216365. [PMID: 37634743 DOI: 10.1016/j.canlet.2023.216365] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 08/22/2023] [Accepted: 08/23/2023] [Indexed: 08/29/2023]
Abstract
Lung cancer maintains high morbidity and mortality rate globally despite significant advancements in diagnosis and treatment in the era of precision medicine. Pathological analysis of tumor tissue, the current gold standard for lung cancer diagnosis, is intrusive and intrinsically confined to evaluating the limited amount of tissues that could be physically extracted. However, tissue biopsy has several limitations, including the invasiveness of the procedure and difficulty in obtaining samples for patients at advanced stages., there Additionally,has been no major breakthrough in tumor biomarkers with high specificity and sensitivity, particularly for early-stage lung cancer. Liquid biopsy has been considered a feasible auxiliary tool for tearly dianosis, evaluating treatment responses and monitoring prognosis of lung cancer. Circulating tumor DNA (ctDNA), an ideal biomarker of liquid biopsy, has emerged as one of the most reliable tools for monitoring tumor processes at molecular levels. Herein, this review focuses on tumor heterogeneity to elucidate the superiority of liquid biopsy and retrospectively discussdeciphersolution. We systematically elaborate ctDNA biological characteristics, introduce methods for ctDNA detection, and discuss the current role of plasma ctDNA in lung cancer management. Finally, we summarize the drawbacks of ctDNA analysis and highlight its potential clinical application in lung cancer.
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Affiliation(s)
- Changshu Li
- Department of Pulmonary and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Respiratory Health and Multimorbidity, West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Jun Shao
- Department of Pulmonary and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Respiratory Health and Multimorbidity, West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Peiyi Li
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, China
| | - Jiaming Feng
- West China School of Medicine, Sichuan University, Chengdu, China
| | - Jingwei Li
- Department of Pulmonary and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Respiratory Health and Multimorbidity, West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Chengdi Wang
- Department of Pulmonary and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Respiratory Health and Multimorbidity, West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China.
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24
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Vladimir K, Perišić MM, Štorga M, Mostashari A, Khanin R. Epigenetics insights from perceived facial aging. Clin Epigenetics 2023; 15:176. [PMID: 37924108 PMCID: PMC10623707 DOI: 10.1186/s13148-023-01590-x] [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: 06/01/2023] [Accepted: 10/23/2023] [Indexed: 11/06/2023] Open
Abstract
Facial aging is the most visible manifestation of aging. People desire to look younger than others of the same chronological age. Hence, perceived age is often used as a visible marker of aging, while biological age, often estimated by methylation markers, is used as an objective measure of age. Multiple epigenetics-based clocks have been developed for accurate estimation of general biological age and the age of specific organs, including the skin. However, it is not clear whether the epigenetic biomarkers (CpGs) used in these clocks are drivers of aging processes or consequences of aging. In this proof-of-concept study, we integrate data from GWAS on perceived facial aging and EWAS on CpGs measured in blood. By running EW Mendelian randomization, we identify hundreds of putative CpGs that are potentially causal to perceived facial aging with similar numbers of damaging markers that causally drive or accelerate facial aging and protective methylation markers that causally slow down or protect from aging. We further demonstrate that while candidate causal CpGs have little overlap with known epigenetics-based clocks, they affect genes or proteins with known functions in skin aging, such as skin pigmentation, elastin, and collagen levels. Overall, our results suggest that blood methylation markers reflect facial aging processes, and thus can be used to quantify skin aging and develop anti-aging solutions that target the root causes of aging.
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Affiliation(s)
- Klemo Vladimir
- LifeNome Inc., New York, 10018, NY, USA
- Faculty of Electrical Engineering and Computing, University of Zagreb, 10000, Zagreb, Croatia
| | - Marija Majda Perišić
- LifeNome Inc., New York, 10018, NY, USA
- Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10000, Zagreb, Croatia
| | - Mario Štorga
- LifeNome Inc., New York, 10018, NY, USA
- Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10000, Zagreb, Croatia
| | | | - Raya Khanin
- LifeNome Inc., New York, 10018, NY, USA.
- Bioinformatics Core, Memorial Sloan-Kettering Cancer Center, New York, 10065, NY, USA.
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25
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Fleckhaus J, Bugert P, Al-Rashedi NAM, Rothschild MA. Investigation of the impact of biogeographic ancestry on DNA methylation based age predictions comparing a Middle East and a Central European population. Forensic Sci Int Genet 2023; 67:102923. [PMID: 37598451 DOI: 10.1016/j.fsigen.2023.102923] [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: 04/13/2023] [Revised: 07/10/2023] [Accepted: 08/01/2023] [Indexed: 08/22/2023]
Abstract
DNA methylation based age prediction is a new method in the toolbox of forensic genetics. Typically, the method is applied in the course of police investigation e.g. to predict the age of an unknown person that has left a biological trace at a crime scene. The method can also be used to answer other forensic questions, for example to estimate the age of unknown human bodies in the course of the identification process. In the present study, we tested for a potential impact of biogeographic ancestry (BGA) on age predictions using five age dependent methylated CpG sites within the genetic regions of ELOVL2, MIR29B2CHG, FHL2, KLF14 and TRIM59. We collected 102 blood samples each from donors living in Iraq, Middle East (ME) and Germany, Central Europe (EU). Both sample sets were matched in sex and age ranging from 18 to 68 years with exactly one male and female sample per year of age. All samples were analyzed by bisulfite pyrosequencing applying a multiplex pre-amplification strategy based on a single input of 35 ng converted DNA in the PCR. For the CpGs in MIR29B2CHG, FHL2 and KLF14, we observed significantly different methylation levels between the two populations. While we were able to train two highly accurate prediction models for the respective population with mean absolute deviations between predicted and actual ages (MAD) of 3.34 years for the ME model, and 2.72 years for the EU model, we found an absolute prediction difference between the two population specific models of more than 4 years. A combined model for both populations compensated the methylation difference between the two populations, providing MADs of prediction of only 3.81 years for ME and 3.31 years for EU samples. In total, the results of the present study strongly support the benefit of BGA information for more reliable methylation based age predictions.
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Affiliation(s)
- J Fleckhaus
- Institute of Legal Medicine, Medical Faculty, University Hospital and University of Cologne, Melatenguertel 60-62, D-50823 Cologne, Germany.
| | - P Bugert
- Institute of Transfusion Medicine and Immunology, Heidelberg University, Medical Faculty Mannheim, German Red Cross Blood Service of Baden-Württemberg - Hessen gGmbH, Mannheim, Germany
| | - N A M Al-Rashedi
- Department of Biology, College of Science, Al Muthanna University, Samawah, Iraq
| | - M A Rothschild
- Institute of Legal Medicine, Medical Faculty, University Hospital and University of Cologne, Melatenguertel 60-62, D-50823 Cologne, Germany
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26
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Corradi C, Lencioni G, Gentiluomo M, Felici A, Latiano A, Kiudelis G, van Eijck CHJ, Marta K, Lawlor RT, Tavano F, Boggi U, Dijk F, Cavestro GM, Vermeulen RCH, Hackert T, Petrone MC, Uzunoğlu FG, Archibugi L, Izbicki JR, Morelli L, Zerbi A, Landi S, Stocker H, Talar-Wojnarowska R, Di Franco G, Hegyi P, Sperti C, Carrara S, Capurso G, Gazouli M, Brenner H, Bunduc S, Busch O, Perri F, Oliverius M, Hegyi PJ, Goetz M, Scognamiglio P, Mambrini A, Arcidiacono PG, Kreivenaite E, Kupcinskas J, Hussein T, Ermini S, Milanetto AC, Vodicka P, Kiudelis V, Hlaváč V, Soucek P, Theodoropoulos GE, Basso D, Neoptolemos JP, Nóbrega Aoki M, Pezzilli R, Pasquali C, Chammas R, Testoni SGG, Mohelnikova-Duchonova B, Lucchesi M, Rizzato C, Canzian F, Campa D. Polymorphic variants involved in methylation regulation: a strategy to discover risk loci for pancreatic ductal adenocarcinoma. J Med Genet 2023; 60:980-986. [PMID: 37130759 DOI: 10.1136/jmg-2022-108910] [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: 09/01/2022] [Accepted: 04/04/2023] [Indexed: 05/04/2023]
Abstract
INTRODUCTION Only a small number of risk factors for pancreatic ductal adenocarcinoma (PDAC) has been established. Several studies identified a role of epigenetics and of deregulation of DNA methylation. DNA methylation is variable across a lifetime and in different tissues; nevertheless, its levels can be regulated by genetic variants like methylation quantitative trait loci (mQTLs), which can be used as a surrogate. MATERIALS AND METHODS We scanned the whole genome for mQTLs and performed an association study in 14 705 PDAC cases and 246 921 controls. The methylation data were obtained from whole blood and pancreatic cancer tissue through online databases. We used the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium genome-wide association study (GWAS) data as discovery phase and the Pancreatic Disease Research consortium, the FinnGen project and the Japan Pancreatic Cancer Research consortium GWAS as replication phase. RESULTS The C allele of 15q26.1-rs12905855 showed an association with a decreased risk of PDAC (OR=0.90, 95% CI 0.87 to 0.94, p=4.93×10-8 in the overall meta-analysis), reaching genome-level statistical significance. 15q26.1-rs12905855 decreases the methylation of a 'C-phosphate-G' (CpG) site located in the promoter region of the RCCD1 antisense (RCCD1-AS1) gene which, when expressed, decreases the expression of the RCC1 domain-containing (RCCD1) gene (part of a histone demethylase complex). Thus, it is possible that the rs12905855 C-allele has a protective role in PDAC development through an increase of RCCD1 gene expression, made possible by the inactivity of RCCD1-AS1. CONCLUSION We identified a novel PDAC risk locus which modulates cancer risk by controlling gene expression through DNA methylation.
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Affiliation(s)
| | | | | | | | - Anna Latiano
- Division of Gastroenterology and Research Laboratory, IRCCS Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Gediminas Kiudelis
- Department of Gastroenterology, Institute for Digestive Research, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Casper H J van Eijck
- Department of Surgery, Erasmus Medical Center, Erasmus University, Rotterdam, Netherlands
| | - Katalin Marta
- Center for Traslational Medicine, Semmelweis University, Budapest, Hungary
- Division of Pancreatic Disease, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Rita T Lawlor
- ARC-NET, Centre for Applied Research on Cancer, University and Hospital Trust of Verona, Verona, Italy
| | - Francesca Tavano
- Division of Gastroenterology and Research Laboratory, IRCCS Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Ugo Boggi
- Division of General and Transplant Surgery, Pisa University Hospital, Pisa, Italy
| | - Frederike Dijk
- Department of Pathology, Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam, Netherlands
| | - Giulia Martina Cavestro
- Division of Experimental Oncology, Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | | | - Thilo Hackert
- Department of General Surgery, University of Heidelberg, Heidelberg, Germany
| | - Maria Chiara Petrone
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, IRSSC San Raffaele Scientific Institute, Milan, Italy
| | - Faik Güntac Uzunoğlu
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Livia Archibugi
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, IRSSC San Raffaele Scientific Institute, Milan, Italy
- Digestive and Liver Disease Unit, Sant'Andrea Hospital, Roma, Italy
| | - Jakob R Izbicki
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Luca Morelli
- General Surgery, Department of Translational Research and New Technologies in Medicine and Surgery, Università di Pisa, Pisa, Italy
| | - Alessandro Zerbi
- Pancreatic Unit, IRCCS Humanitas Research Hospital, Rozzano, Italy
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
| | - Stefano Landi
- Department of Biology, University of Pisa, Pisa, Italy
| | - Hannah Stocker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
| | | | - Gregorio Di Franco
- General Surgery, Department of Translational Research and New Technologies in Medicine and Surgery, Università di Pisa, Pisa, Italy
| | - Péter Hegyi
- Center for Traslational Medicine, Semmelweis University, Budapest, Hungary
- Division of Pancreatic Disease, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
- Institute for Translational Medicine, Medical School, University of Pécs, Pecs, Hungary
- Janos Szentagothai Research Center, University of Pecs, Pecs, Hungary
| | - Cosimo Sperti
- Department of Surgery-DiSCOG, Padua University Hospital, Padova, Italy
| | - Silvia Carrara
- Endoscopic Unit, Department of Gastroenterology, IRCCS Humanitas Research Hospital, Rozzano, Italy
| | - Gabriele Capurso
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, IRSSC San Raffaele Scientific Institute, Milan, Italy
- Digestive and Liver Disease Unit, Sant'Andrea Hospital, Roma, Italy
| | - Maria Gazouli
- Laboratory of Biology, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stefania Bunduc
- Center for Traslational Medicine, Semmelweis University, Budapest, Hungary
- Division of Pancreatic Disease, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
- Carol Davila University of Medicine and Pharmacy, Bucarest, Romania
| | - Olivier Busch
- Department of Surgery, Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam, Netherlands
| | - Francesco Perri
- Division of Gastroenterology and Research Laboratory, IRCCS Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Martin Oliverius
- Department of Surgery, Third Faculty of Medicine, University Hospital Kralovske Vinohrady, Charles University, Prague, Czech Republic
| | - Péter Jeno Hegyi
- Center for Traslational Medicine, Semmelweis University, Budapest, Hungary
- Division of Pancreatic Disease, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Mara Goetz
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Pasquale Scognamiglio
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Andrea Mambrini
- Oncology of Massa Carrara, Oncological Department, Azienda USL Toscana Nord Ovest, Pisa, Italy
| | - Paolo Giorgio Arcidiacono
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, IRSSC San Raffaele Scientific Institute, Milan, Italy
| | - Edita Kreivenaite
- Department of Gastroenterology, Institute for Digestive Research, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Juozas Kupcinskas
- Department of Gastroenterology, Institute for Digestive Research, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Tamas Hussein
- Center for Traslational Medicine, Semmelweis University, Budapest, Hungary
- Division of Pancreatic Disease, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Stefano Ermini
- Blood Transfusion Service, Azienda Ospedaliero Universitaria Meyer, Firenze, Italy
| | | | - Pavel Vodicka
- Department of Molecular Biology of Cancer, Institute of Experimental Medicine Czech Academy of Sciences, Prague, Czech Republic
- Biomedical Centre and Department of Surgery, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic
- First Faculty of Medicine, Institute of Biology and Medical Genetics, Charles University, Prague, Czech Republic
| | - Vytautas Kiudelis
- Department of Gastroenterology, Institute for Digestive Research, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Viktor Hlaváč
- Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic
| | - Pavel Soucek
- Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic
| | - George E Theodoropoulos
- First Propaedeutic University Surgery Clinic, Hippocratio General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Daniela Basso
- Department of Medicine-DIMED, Padua University Hospital, Padova, Italy
| | - John P Neoptolemos
- Department of General Surgery, University of Heidelberg, Heidelberg, Germany
| | - Mateus Nóbrega Aoki
- Laboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Curitiba, Brazil
| | | | - Claudio Pasquali
- Department of Surgery-DiSCOG, Padua University Hospital, Padova, Italy
| | - Roger Chammas
- Laboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Curitiba, Brazil
| | - Sabrina Gloria Giulia Testoni
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, IRSSC San Raffaele Scientific Institute, Milan, Italy
| | | | - Maurizio Lucchesi
- Oncology of Massa Carrara, Oncological Department, Azienda USL Toscana Nord Ovest, Pisa, Italy
| | - Cosmeri Rizzato
- Department of Translational Research and new Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Federico Canzian
- Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniele Campa
- Department of Biology, University of Pisa, Pisa, Italy
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27
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Lee SM, Loo CE, Prasasya RD, Bartolomei MS, Kohli RM, Zhou W. Low-input and single-cell methods for Infinium DNA methylation BeadChips. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.18.558252. [PMID: 37786695 PMCID: PMC10541608 DOI: 10.1101/2023.09.18.558252] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
The Infinium BeadChip is the most widely used DNA methylome assay technology for population-scale epigenome profiling. However, the standard workflow requires over 200 ng of input DNA, hindering its application to small cell-number samples, such as primordial germ cells. We developed experimental and analysis workflows to extend this technology to suboptimal input DNA conditions, including ultra-low input down to single cells. DNA preamplification significantly enhanced detection rates to over 50% in five-cell samples and ∼25% in single cells. Enzymatic conversion also substantially improved data quality. Computationally, we developed a method to model the background signal's influence on the DNA methylation level readings. The modified detection p -values calculation achieved higher sensitivities for low-input datasets and was validated in over 100,000 public datasets with diverse methylation profiles. We employed the optimized workflow to query the demethylation dynamics in mouse primordial germ cells available at low cell numbers. Our data revealed nuanced chromatin states, sex disparities, and the role of DNA methylation in transposable element regulation during germ cell development. Collectively, we present comprehensive experimental and computational solutions to extend this widely used methylation assay technology to applications with limited DNA.
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28
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Hatton AA, Hillary RF, Bernabeu E, McCartney DL, Marioni RE, McRae AF. Blood-based genome-wide DNA methylation correlations across body-fat- and adiposity-related biochemical traits. Am J Hum Genet 2023; 110:1564-1573. [PMID: 37652023 PMCID: PMC10502853 DOI: 10.1016/j.ajhg.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: 03/28/2023] [Revised: 08/04/2023] [Accepted: 08/03/2023] [Indexed: 09/02/2023] Open
Abstract
The recent increase in obesity levels across many countries is likely to be driven by nongenetic factors. The epigenetic modification DNA methylation (DNAm) may help to explore this, as it is sensitive to both genetic and environmental exposures. While the relationship between DNAm and body-fat traits has been extensively studied, there is limited literature on the shared associations of DNAm variation across such traits. Akin to genetic correlation estimates, here, we introduce an approach to evaluate the similarities in DNAm associations between traits: DNAm correlations. As DNAm can be both a cause and consequence of complex traits, DNAm correlations have the potential to provide insights into trait relationships above that currently obtained from genetic and phenotypic correlations. Utilizing 7,519 unrelated individuals from Generation Scotland with DNAm from the EPIC array, we calculated DNAm correlations between body-fat- and adiposity-related traits by using the bivariate OREML framework in the OSCA software. For each trait, we also estimated the shared contribution of DNAm between sexes. We identified strong, positive DNAm correlations between each of the body-fat traits (BMI, body-fat percentage, and waist-to-hip ratio, ranging from 0.96 to 1.00), finding larger associations than those identified by genetic and phenotypic correlations. We identified a significant deviation from 1 in the DNAm correlations for BMI between males and females, with sex-specific DNAm changes associated with BMI identified at eight DNAm probes. Employing genome-wide DNAm correlations to evaluate the similarities in the associations of DNAm with complex traits has provided insight into obesity-related traits beyond that provided by genetic correlations.
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Affiliation(s)
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Elena Bernabeu
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Allan F McRae
- Institute for Molecular Bioscience, Brisbane, Australia.
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29
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Liu B, Fu X, Du Y, Feng Z, Chen R, Liu X, Yu F, Zhou G, Ba Y. Pan-cancer analysis of G6PD carcinogenesis in human tumors. Carcinogenesis 2023; 44:525-534. [PMID: 37335542 DOI: 10.1093/carcin/bgad043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/24/2023] [Accepted: 06/18/2023] [Indexed: 06/21/2023] Open
Abstract
Glucose-6-phosphate dehydrogenase (G6PD) is involved in the catalytic pentose phosphate pathway (PPP), which is closely related to energy metabolism. G6PD plays a crucial role in many types of cancer, but the specific molecular mechanisms of G6PD in cancer remain unclear. Therefore, we investigated the potential oncogenic role of G6PD in various tumors based on The Cancer Genome Atlas (TCGA), the cBioPortal datasets, the University of California Santa Cruz (UCSC) Xena browser, and the UALCAN-based online tool. G6PD was highly expressed in several cancer tissues (hepatocellular carcinoma, glioma, and breast cancer) compared with normal tissues and was significantly associated with poor prognosis of hepatocellular carcinoma, clear cell renal cell carcinoma, and breast cancer. Promoter methylation levels of G6PD were lower in Bladder Urothelial Carcinoma (BLCA) (P = 2.77e-02), breast invasive carcinoma (BRCA) (P = 1.62e-12), kidney renal clear cell carcinoma (KIRC) (P = 4.23e-02), kidney renal papillary cell carcinoma (KIRP) (P = 2.64e-03), liver hepatocellular carcinoma (LIHC) (P = 1.76e-02), stomach adenocarcinoma (STAD) (P = 3.50e-02), testicular germ cell tumors (TGCT) (P = 1.62e-12), higher in prostate adenocarcinoma (PRAD) (P = 1.81e-09), and uterine corpus endometrial carcinoma (UCEC) (P = 2.96e-04) compared with corresponding normal tissue samples. G6PD expression was positively correlated with the infiltration level of immune cells in most tumors, suggesting that G6PD may be involved in tumor immune infiltration. In addition, the functional mechanism of G6PD also involves 'Carbon metabolism', 'Glycolysis/Gluconeogenesis', 'Pentose phosphate pathway', and 'Central carbon pathway metabolism in cancer signaling pathway'. This pan-cancer study provides a relatively broad understanding of the oncogenic role of G6PD in various tumors and presents a theoretical basis for the development of G6PD inhibitors as therapeutic drugs for multiple cancers.
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Affiliation(s)
- Bin Liu
- Department of Environmental Health, School of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
| | - Xiaoli Fu
- Department of Environmental Health, School of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
| | - Yuhui Du
- Department of Environmental Health, School of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
| | - Zichen Feng
- Department of Environmental Health, School of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
| | - Ruiqin Chen
- Jinshui District Center for Disease Control and Prevention, Zhengzhou, Henan 450053, P. R. China
| | - Xiaoxue Liu
- Department of Environmental Health, School of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
| | - Fangfang Yu
- Department of Environmental Health, School of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
| | - Guoyu Zhou
- Department of Environmental Health, School of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
| | - Yue Ba
- Department of Environmental Health, School of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
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30
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Azani A, Omran SP, Ghasrsaz H, Idani A, Eliaderani MK, Peirovi N, Dokhani N, Lotfalizadeh MH, Rezaei MM, Ghahfarokhi MS, KarkonShayan S, Hanjani PN, Kardaan Z, Navashenagh JG, Yousefi M, Abdolahi M, Salmaninejad A. MicroRNAs as biomarkers for early diagnosis, targeting and prognosis of prostate cancer. Pathol Res Pract 2023; 248:154618. [PMID: 37331185 DOI: 10.1016/j.prp.2023.154618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 06/09/2023] [Accepted: 06/10/2023] [Indexed: 06/20/2023]
Abstract
Globally, prostate cancer (PC) is leading cause of cancer-related mortality in men worldwide. Despite significant advances in the treatment and management of this disease, the cure rates for PC remains low, largely due to late detection. PC detection is mostly reliant on prostate-specific antigen (PSA) and digital rectal examination (DRE); however, due to the low positive predictive value of current diagnostics, there is an urgent need to identify new accurate biomarkers. Recent studies support the biological role of microRNAs (miRNAs) in the initiation and progression of PC, as well as their potential as novel biomarkers for patients' diagnosis, prognosis, and disease relapse. In the advanced stages, cancer-cell-derived small extracellular vesicles (SEVs) may constitute a significant part of circulating vesicles and cause detectable changes in the plasma vesicular miRNA profile. Recent computational model for the identification of miRNA biomarkers discussed. In addition, accumulating evidence indicates that miRNAs can be utilized to target PC cells. In this article, the current understanding of the role of microRNAs and exosomes in the pathogenesis and their significance in PC prognosis, early diagnosis, chemoresistance, and treatment are reviewed.
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Affiliation(s)
- Alireza Azani
- Department of Medical Genetics, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Sima Parvizi Omran
- Department of Medical Genetics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Haniyeh Ghasrsaz
- Faculty of Medicine, Mazandaran University of Medical Sciences, Mazandaran, Iran
| | - Asra Idani
- Department of Medical Genetics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Niloufar Peirovi
- Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Negar Dokhani
- Student Research Committee, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
| | | | | | | | - Sepideh KarkonShayan
- Social Development and Health Promotion Research Center, Gonabad University of Medical Sciences, Gonabad, Iran
| | - Parisa Najari Hanjani
- Department of Genetics, Faculty of Advanced Technologies in Medicine, Golestan University of Medical Science, Gorgan, Iran
| | - Zahra Kardaan
- Department of Cellular Molecular Biology, Faculty of Life Science and Biotechnology, Shahid Beheshti University, Tehran, Iran
| | | | - Meysam Yousefi
- Department of Medical Genetics, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Mitra Abdolahi
- Department of Pathology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| | - Arash Salmaninejad
- Department of Medical Genetics, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; Regenerative Medicine, Organ Procurement and Transplantation Multi-Disciplinary Center, Razi Hospital, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
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31
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Villicaña S, Castillo-Fernandez J, Hannon E, Christiansen C, Tsai PC, Maddock J, Kuh D, Suderman M, Power C, Relton C, Ploubidis G, Wong A, Hardy R, Goodman A, Ong KK, Bell JT. Genetic impacts on DNA methylation help elucidate regulatory genomic processes. Genome Biol 2023; 24:176. [PMID: 37525248 PMCID: PMC10391992 DOI: 10.1186/s13059-023-03011-x] [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: 10/06/2022] [Accepted: 07/10/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk. RESULTS We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1520 co-localisations across 1325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1 and DOCK7 (total cholesterol levels), and ICOSLG (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis-meQTLs (e.g. through disruption of transcription factor binding sites for CTCF and SMC3) and trans-meQTLs (e.g. through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites). CONCLUSIONS Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk .
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Affiliation(s)
- Sergio Villicaña
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| | | | | | - Colette Christiansen
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jane Maddock
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Christine Power
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - George Ploubidis
- Centre for Longitudinal Studies, Institute of Education, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Rebecca Hardy
- School of Sport, Exercise & Health Sciences, Loughborough University, Loughborough, UK
- UCL Social Research Institute, University College London, London, UK
| | - Alissa Goodman
- Centre for Longitudinal Studies, Institute of Education, University College London, London, UK
| | - Ken K Ong
- MRC Epidemiology Unit and Department of Paediatrics, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
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Kasela S, Aguet F, Kim-Hellmuth S, Brown BC, Nachun DC, Tracy RP, Durda P, Liu Y, Taylor KD, Craig Johnson W, Berg DVD, Gabriel S, Gupta N, Smith JD, Blackwell TW, Rotter JI, Ardlie KG, Manichaikul A, Rich SS, Graham Barr R, Lappalainen T. Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.26.546528. [PMID: 37425716 PMCID: PMC10326995 DOI: 10.1101/2023.06.26.546528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Bulk tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, while context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell type proportions, we demonstrate that cell type iQTLs could be considered as proxies for cell type-specific QTL effects. The interpretation of age iQTLs, however, warrants caution as the moderation effect of age on the genotype and molecular phenotype association may be mediated by changes in cell type composition. Finally, we show that cell type iQTLs contribute to cell type-specific enrichment of diseases that, in combination with additional functional data, may guide future functional studies. Overall, this study highlights iQTLs to gain insights into the context-specificity of regulatory effects.
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Affiliation(s)
- Silva Kasela
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
| | | | - Sarah Kim-Hellmuth
- New York Genome Center, New York, NY, USA
- Department of Pediatrics, Dr. von Hauner Children’s Hospital, University Hospital LMU Munich, Munich, Germany
- Computational Health Center, Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Brielin C. Brown
- New York Genome Center, New York, NY, USA
- Data Science Institute, Columbia University, New York, NY, USA
| | | | - Russell P. Tracy
- Pathology and Laboratory Medicine, The University of Vermont, Larner College of Medicine, Burlington, VT, USA
| | - Peter Durda
- Pathology and Laboratory Medicine, The University of Vermont, Larner College of Medicine, Burlington, VT, USA
| | - Yongmei Liu
- Department of Medicine, Duke University, Durham, NC, USA
| | - Kent D. Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - David Van Den Berg
- Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | | | - Namrata Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joshua D. Smith
- Northwest Genomic Center, University of Washington, Seattle, WA, USA
| | - Thomas W. Blackwell
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Jerome I. Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Ani Manichaikul
- Center for Public health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Stephen S. Rich
- Center for Public health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R. Graham Barr
- Epidemiology and Medicine, Columbia University Medical Center, New York, NY, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
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33
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Advani J, Corso-Diaz X, Kwicklis M, van Asten F, Ratnapriya R, Mehta P, Hamel A, Mahrotra S, Segrè A, Kiel C, Strunz T, Weber B, Chew E, Hernandez D, Montezuma S, Ferrington D, Swaroop A. QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration. RESEARCH SQUARE 2023:rs.3.rs-3011096. [PMID: 37398472 PMCID: PMC10312909 DOI: 10.21203/rs.3.rs-3011096/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
DNA methylation (DNAm) provides a crucial epigenetic mark linking genetic variations to environmental influence. We analyzed array-based DNAm profiles of 160 human retinas with co-measured RNA-seq and > 8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 mQTLs and 12,505 eQTLs) and 13,747 eQTMs (DNAm loci affecting gene expression), with over one-third specific to the retina. mQTLs and eQTMs show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration (AMD). Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of AMD pathology by genotype-environment interaction in retina.
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Affiliation(s)
| | | | | | | | | | - Puja Mehta
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Andrew Hamel
- Department of Ophthalmology, Massachusetts Eye and Ear
| | | | | | | | | | | | - Emily Chew
- National Eye Institute/National Institutes of Health
| | | | | | | | - Anand Swaroop
- National Eye Institute, National Institutes of Health
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34
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Tyler AL, Spruce C, Kursawe R, Haber A, Ball RL, Pitman WA, Fine AD, Raghupathy N, Walker M, Philip VM, Baker CL, Mahoney JM, Churchill GA, Trowbridge JJ, Stitzel ML, Paigen K, Petkov PM, Carter GW. Variation in histone configurations correlates with gene expression across nine inbred strains of mice. Genome Res 2023; 33:857-871. [PMID: 37217254 PMCID: PMC10519406 DOI: 10.1101/gr.277467.122] [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: 11/02/2022] [Accepted: 05/19/2023] [Indexed: 05/24/2023]
Abstract
The Diversity Outbred (DO) mice and their inbred founders are widely used models of human disease. However, although the genetic diversity of these mice has been well documented, their epigenetic diversity has not. Epigenetic modifications, such as histone modifications and DNA methylation, are important regulators of gene expression and, as such, are a critical mechanistic link between genotype and phenotype. Therefore, creating a map of epigenetic modifications in the DO mice and their founders is an important step toward understanding mechanisms of gene regulation and the link to disease in this widely used resource. To this end, we performed a strain survey of epigenetic modifications in hepatocytes of the DO founders. We surveyed four histone modifications (H3K4me1, H3K4me3, H3K27me3, and H3K27ac), as well as DNA methylation. We used ChromHMM to identify 14 chromatin states, each of which represents a distinct combination of the four histone modifications. We found that the epigenetic landscape is highly variable across the DO founders and is associated with variation in gene expression across strains. We found that epigenetic state imputed into a population of DO mice recapitulated the association with gene expression seen in the founders, suggesting that both histone modifications and DNA methylation are highly heritable mechanisms of gene expression regulation. We illustrate how DO gene expression can be aligned with inbred epigenetic states to identify putative cis-regulatory regions. Finally, we provide a data resource that documents strain-specific variation in the chromatin state and DNA methylation in hepatocytes across nine widely used strains of laboratory mice.
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Affiliation(s)
- Anna L Tyler
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Catrina Spruce
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Romy Kursawe
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA
| | - Annat Haber
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA
| | - Robyn L Ball
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Wendy A Pitman
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Alexander D Fine
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | | | - Michael Walker
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Vivek M Philip
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | | | - J Matthew Mahoney
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Gary A Churchill
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | | | - Michael L Stitzel
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA
| | - Kenneth Paigen
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Petko M Petkov
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA;
| | - Gregory W Carter
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
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35
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Shang L, Zhao W, Wang YZ, Li Z, Choi JJ, Kho M, Mosley TH, Kardia SLR, Smith JA, Zhou X. meQTL mapping in the GENOA study reveals genetic determinants of DNA methylation in African Americans. Nat Commun 2023; 14:2711. [PMID: 37169753 PMCID: PMC10175543 DOI: 10.1038/s41467-023-37961-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 04/07/2023] [Indexed: 05/13/2023] Open
Abstract
Identifying genetic variants that are associated with variation in DNA methylation, an analysis commonly referred to as methylation quantitative trait locus (meQTL) mapping, is an important first step towards understanding the genetic architecture underlying epigenetic variation. Most existing meQTL mapping studies have focused on individuals of European ancestry and are underrepresented in other populations, with a particular absence of large studies in populations with African ancestry. We fill this critical knowledge gap by performing a large-scale cis-meQTL mapping study in 961 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. We identify a total of 4,565,687 cis-acting meQTLs in 320,965 meCpGs. We find that 45% of meCpGs harbor multiple independent meQTLs, suggesting potential polygenic genetic architecture underlying methylation variation. A large percentage of the cis-meQTLs also colocalize with cis-expression QTLs (eQTLs) in the same population. Importantly, the identified cis-meQTLs explain a substantial proportion (median = 24.6%) of methylation variation. In addition, the cis-meQTL associated CpG sites mediate a substantial proportion (median = 24.9%) of SNP effects underlying gene expression. Overall, our results represent an important step toward revealing the co-regulation of methylation and gene expression, facilitating the functional interpretation of epigenetic and gene regulation underlying common diseases in African Americans.
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Affiliation(s)
- Lulu Shang
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Yi Zhe Wang
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Zheng Li
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jerome J Choi
- Population Health Sciences, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, 53726, USA
| | - Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Thomas H Mosley
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, 39126, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA.
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA.
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36
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Hong K, Yang Q, Yin H, Wei N, Wang W, Yu B. Comprehensive analysis of ZNF family genes in prognosis, immunity, and treatment of esophageal cancer. BMC Cancer 2023; 23:301. [PMID: 37013470 PMCID: PMC10069130 DOI: 10.1186/s12885-023-10779-5] [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: 10/10/2022] [Accepted: 03/27/2023] [Indexed: 04/05/2023] Open
Abstract
BACKGROUND As a common malignant tumor, esophageal carcinoma (ESCA) has a low early diagnosis rate and poor prognosis. This study aimed to construct the prognostic features composed of ZNF family genes to effectively predict the prognosis of ESCA patients. METHODS The mRNA expression matrix and clinical data were downloaded from TCGA and GEO database. Using univariate Cox analysis, lasso regression and multivariate Cox analysis, we screened six prognosis-related ZNF family genes to construct the prognostic model. We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis of clinical information, and nomogram to evaluate the prognostic value within and across sets, separately and combined. We also validated the prognostic value of the six-gene signature using GSE53624 dataset. The different immune status was observed in the single sample Gene Set Enrichment Analysis (ssGSEA). Finally, real-time quantitative PCR was used to detect the expression of six prognostic ZNF genes in twelve pairs of ESCA and adjacent normal tissues. RESULTS A six prognosis-related ZNF family genes model consisted of ZNF91, ZNF586, ZNF502, ZNF865, ZNF106 and ZNF225 was identified. Multivariable Cox regression analysis revealed that six prognosis-related ZNF family genes were independent prognostic factors for overall survival of ESCA patients in TCGA and GSE53624. Further, a prognostic nomogram including the riskScore, age, gender, T, stage was constructed, and TCGA/GSE53624-based calibration plots indicated its excellent predictive performance. Drug Sensitivity and ssGSEA analysis showed that the six genes model was closely related to immune cells infiltration and could be used as a potential predictor of chemotherapy sensitivity. CONCLUSION We identified six prognosis-related ZNF family genes model of ESCA, which provide evidence for individualized prevention and treatment.
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Affiliation(s)
- Kunqiao Hong
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Wuhan, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan, China
| | - Qian Yang
- Department of Gastroenterology, Guizhou Provincial People's Hospital, Guiyang City, Guizhou province, China
- NHC key Laboratory of Pulmonary Immune-related Disease, Guizhou Provincial People's Hospital, Guiyang City, Guizhou province, China
| | - Haisen Yin
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Wuhan, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan, China
| | - Na Wei
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Wuhan, China
| | - Wei Wang
- Department of Gastroenterology, Affiliated Hospital of Hubei, Xiangyang Central Hospital, University of Arts and Science, Hubei, China.
| | - Baoping Yu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
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37
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Wyns A, Hendrix J, Lahousse A, De Bruyne E, Nijs J, Godderis L, Polli A. The Biology of Stress Intolerance in Patients with Chronic Pain—State of the Art and Future Directions. J Clin Med 2023; 12:jcm12062245. [PMID: 36983246 PMCID: PMC10057496 DOI: 10.3390/jcm12062245] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/07/2023] [Accepted: 03/10/2023] [Indexed: 03/16/2023] Open
Abstract
Stress has been consistently linked to negative impacts on physical and mental health. More specifically, patients with chronic pain experience stress intolerance, which is an exacerbation or occurrence of symptoms in response to any type of stress. The pathophysiological mechanisms underlying this phenomenon remain unsolved. In this state-of-the-art paper, we summarised the role of the autonomic nervous system (ANS) and hypothalamus-pituitary-adrenal (HPA) axis, the two major stress response systems in stress intolerance. We provided insights into such mechanisms based on evidence from clinical studies in both patients with chronic pain, showing dysregulated stress systems, and healthy controls supported by preclinical studies, highlighting the link between these systems and symptoms of stress intolerance. Furthermore, we explored the possible regulating role for (epi)genetic mechanisms influencing the ANS and HPA axis. The link between stress and chronic pain has become an important area of research as it has the potential to inform the development of interventions to improve the quality of life for individuals living with chronic pain. As stress has become a prevalent concern in modern society, understanding the connection between stress, HPA axis, ANS, and chronic health conditions such as chronic pain is crucial to improve public health and well-being.
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Affiliation(s)
- Arne Wyns
- Pain in Motion Research Group (PAIN), Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, 1090 Brussels, Belgium; (A.W.); (A.L.); (J.N.); (A.P.)
| | - Jolien Hendrix
- Pain in Motion Research Group (PAIN), Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, 1090 Brussels, Belgium; (A.W.); (A.L.); (J.N.); (A.P.)
- Department of Public Health and Primary Care, Centre for Environment & Health, KU Leuven, Kapucijnenvoer 35, 3000 Leuven, Belgium;
- Flanders Research Foundation-FWO, 1090 Brussels, Belgium
- Correspondence:
| | - Astrid Lahousse
- Pain in Motion Research Group (PAIN), Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, 1090 Brussels, Belgium; (A.W.); (A.L.); (J.N.); (A.P.)
- Flanders Research Foundation-FWO, 1090 Brussels, Belgium
- Chronic Pain Rehabilitation, Department of Physical Medicine and Physiotherapy, University Hospital, 1090 Brussels, Belgium
- Rehabilitation Research (RERE) Research Group, Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy (KIMA), Vrije Universiteit Brussel, 1090 Brussels, Belgium
| | - Elke De Bruyne
- Department of Hematology and Immunology-Myeloma Center Brussels, Vrije Universiteit Brussel, 1090 Brussels, Belgium;
| | - Jo Nijs
- Pain in Motion Research Group (PAIN), Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, 1090 Brussels, Belgium; (A.W.); (A.L.); (J.N.); (A.P.)
- Chronic Pain Rehabilitation, Department of Physical Medicine and Physiotherapy, University Hospital, 1090 Brussels, Belgium
- Unit of Physiotherapy, Department of Health and Rehabilitation, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden
| | - Lode Godderis
- Department of Public Health and Primary Care, Centre for Environment & Health, KU Leuven, Kapucijnenvoer 35, 3000 Leuven, Belgium;
- External Service for Prevention and Protection at Work, IDEWE, 3001 Heverlee, Belgium
| | - Andrea Polli
- Pain in Motion Research Group (PAIN), Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, 1090 Brussels, Belgium; (A.W.); (A.L.); (J.N.); (A.P.)
- Department of Public Health and Primary Care, Centre for Environment & Health, KU Leuven, Kapucijnenvoer 35, 3000 Leuven, Belgium;
- Flanders Research Foundation-FWO, 1090 Brussels, Belgium
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38
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Chen M, Liu X, Liu Q, Shi D, Li H. 3D genomics and its applications in precision medicine. Cell Mol Biol Lett 2023; 28:19. [PMID: 36879202 PMCID: PMC9987123 DOI: 10.1186/s11658-023-00428-x] [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: 11/16/2022] [Accepted: 02/06/2023] [Indexed: 03/08/2023] Open
Abstract
Three-dimensional (3D) genomics is an emerging discipline that studies the three-dimensional structure of chromatin and the three-dimensional and functions of genomes. It mainly studies the three-dimensional conformation and functional regulation of intranuclear genomes, such as DNA replication, DNA recombination, genome folding, gene expression regulation, transcription factor regulation mechanism, and the maintenance of three-dimensional conformation of genomes. Self-chromosomal conformation capture (3C) technology has been developed, and 3D genomics and related fields have developed rapidly. In addition, chromatin interaction analysis techniques developed by 3C technologies, such as paired-end tag sequencing (ChIA-PET) and whole-genome chromosome conformation capture (Hi-C), enable scientists to further study the relationship between chromatin conformation and gene regulation in different species. Thus, the spatial conformation of plant, animal, and microbial genomes, transcriptional regulation mechanisms, interaction patterns of chromosomes, and the formation mechanism of spatiotemporal specificity of genomes are revealed. With the help of new experimental technologies, the identification of key genes and signal pathways related to life activities and diseases is sustaining the rapid development of life science, agriculture, and medicine. In this paper, the concept and development of 3D genomics and its application in agricultural science, life science, and medicine are introduced, which provides a theoretical basis for the study of biological life processes.
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Affiliation(s)
- Mengjie Chen
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Animal Science and Technology, Guangxi University, Nanning, 530004, Guangxi Province, China
| | - Xingyu Liu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Animal Science and Technology, Guangxi University, Nanning, 530004, Guangxi Province, China
| | - Qingyou Liu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Animal Science and Technology, Guangxi University, Nanning, 530004, Guangxi Province, China.,Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan, 528225, China
| | - Deshun Shi
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Animal Science and Technology, Guangxi University, Nanning, 530004, Guangxi Province, China.
| | - Hui Li
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Animal Science and Technology, Guangxi University, Nanning, 530004, Guangxi Province, China.
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Klughammer J, Romanovskaia D, Nemc A, Posautz A, Seid CA, Schuster LC, Keinath MC, Lugo Ramos JS, Kosack L, Evankow A, Printz D, Kirchberger S, Ergüner B, Datlinger P, Fortelny N, Schmidl C, Farlik M, Skjærven K, Bergthaler A, Liedvogel M, Thaller D, Burger PA, Hermann M, Distel M, Distel DL, Kübber-Heiss A, Bock C. Comparative analysis of genome-scale, base-resolution DNA methylation profiles across 580 animal species. Nat Commun 2023; 14:232. [PMID: 36646694 PMCID: PMC9842680 DOI: 10.1038/s41467-022-34828-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 11/08/2022] [Indexed: 01/18/2023] Open
Abstract
Methylation of cytosines is a prototypic epigenetic modification of the DNA. It has been implicated in various regulatory mechanisms across the animal kingdom and particularly in vertebrates. We mapped DNA methylation in 580 animal species (535 vertebrates, 45 invertebrates), resulting in 2443 genome-scale DNA methylation profiles of multiple organs. Bioinformatic analysis of this large dataset quantified the association of DNA methylation with the underlying genomic DNA sequence throughout vertebrate evolution. We observed a broadly conserved link with two major transitions-once in the first vertebrates and again with the emergence of reptiles. Cross-species comparisons focusing on individual organs supported a deeply conserved association of DNA methylation with tissue type, and cross-mapping analysis of DNA methylation at gene promoters revealed evolutionary changes for orthologous genes. In summary, this study establishes a large resource of vertebrate and invertebrate DNA methylomes, it showcases the power of reference-free epigenome analysis in species for which no reference genomes are available, and it contributes an epigenetic perspective to the study of vertebrate evolution.
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Affiliation(s)
- Johanna Klughammer
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria. .,Gene Center and Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany.
| | - Daria Romanovskaia
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Amelie Nemc
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Annika Posautz
- Research Institute of Wildlife Ecology, University of Veterinary Medicine Vienna, Vienna, Austria
| | - Charlotte A Seid
- Ocean Genome Legacy Center, Northeastern University Marine Science Center, Nahant, USA
| | - Linda C Schuster
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | | | - Juan Sebastian Lugo Ramos
- Max Planck Research Group Behavioral Genomics, Max Planck Institute for Evolutionary Biology, Plön, Germany
| | - Lindsay Kosack
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Ann Evankow
- Ocean Genome Legacy Center, Northeastern University Marine Science Center, Nahant, USA
| | - Dieter Printz
- Children's Cancer Research Institute, St. Anna Kinderkrebsforschung, Vienna, Austria
| | - Stefanie Kirchberger
- Children's Cancer Research Institute, St. Anna Kinderkrebsforschung, Vienna, Austria
| | - Bekir Ergüner
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Paul Datlinger
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Nikolaus Fortelny
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Christian Schmidl
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Matthias Farlik
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | | | - Andreas Bergthaler
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Medical University of Vienna, Center for Pathophysiology Infectiology and Immunology, Institute of Hygiene and Applied Immunology, Vienna, Austria
| | - Miriam Liedvogel
- Max Planck Research Group Behavioral Genomics, Max Planck Institute for Evolutionary Biology, Plön, Germany.,Institute of Avian Research, An der Vogelwarte, Wilhelmshaven, Germany
| | - Denise Thaller
- Department for Pathobiology, University of Veterinary Medicine Vienna, Vienna, Austria
| | - Pamela A Burger
- Research Institute of Wildlife Ecology, University of Veterinary Medicine Vienna, Vienna, Austria
| | - Marcela Hermann
- Medical University of Vienna, Department of Medical Biochemistry, Vienna, Austria
| | - Martin Distel
- Children's Cancer Research Institute, St. Anna Kinderkrebsforschung, Vienna, Austria
| | - Daniel L Distel
- Ocean Genome Legacy Center, Northeastern University Marine Science Center, Nahant, USA
| | - Anna Kübber-Heiss
- Research Institute of Wildlife Ecology, University of Veterinary Medicine Vienna, Vienna, Austria
| | - Christoph Bock
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria. .,Medical University of Vienna, Institute of Artificial Intelligence, Center for Medical Data Science, Vienna, Austria.
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Oliva M, Demanelis K, Lu Y, Chernoff M, Jasmine F, Ahsan H, Kibriya MG, Chen LS, Pierce BL. DNA methylation QTL mapping across diverse human tissues provides molecular links between genetic variation and complex traits. Nat Genet 2023; 55:112-122. [PMID: 36510025 PMCID: PMC10249665 DOI: 10.1038/s41588-022-01248-z] [Citation(s) in RCA: 53] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 10/26/2022] [Indexed: 12/14/2022]
Abstract
Studies of DNA methylation (DNAm) in solid human tissues are relatively scarce; tissue-specific characterization of DNAm is needed to understand its role in gene regulation and its relevance to complex traits. We generated array-based DNAm profiles for 987 human samples from the Genotype-Tissue Expression (GTEx) project, representing 9 tissue types and 424 subjects. We characterized methylome and transcriptome correlations (eQTMs), genetic regulation in cis (mQTLs and eQTLs) across tissues and e/mQTLs links to complex traits. We identified mQTLs for 286,152 CpG sites, many of which (>5%) show tissue specificity, and mQTL colocalizations with 2,254 distinct GWAS hits across 83 traits. For 91% of these loci, a candidate gene link was identified by integration of functional maps, including eQTMs, and/or eQTL colocalization, but only 33% of loci involved an eQTL and mQTL present in the same tissue type. With this DNAm-focused integrative analysis, we contribute to the understanding of molecular regulatory mechanisms in human tissues and their impact on complex traits.
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Affiliation(s)
- Meritxell Oliva
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
| | - Kathryn Demanelis
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yihao Lu
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Meytal Chernoff
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Farzana Jasmine
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Habibul Ahsan
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Comprehensive Cancer Center, University of Chicago, Chicago, IL, USA
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Institute for Population and Precision Health, University of Chicago, Chicago, IL, USA
| | - Muhammad G Kibriya
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
- Institute for Population and Precision Health, University of Chicago, Chicago, IL, USA
| | - Lin S Chen
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
| | - Brandon L Pierce
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
- Department of Human Genetics, University of Chicago, Chicago, IL, USA.
- Comprehensive Cancer Center, University of Chicago, Chicago, IL, USA.
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41
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Wattacheril JJ, Raj S, Knowles DA, Greally JM. Using epigenomics to understand cellular responses to environmental influences in diseases. PLoS Genet 2023; 19:e1010567. [PMID: 36656803 PMCID: PMC9851565 DOI: 10.1371/journal.pgen.1010567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
It is a generally accepted model that environmental influences can exert their effects, at least in part, by changing the molecular regulators of transcription that are described as epigenetic. As there is biochemical evidence that some epigenetic regulators of transcription can maintain their states long term and through cell division, an epigenetic model encompasses the idea of maintenance of the effect of an exposure long after it is no longer present. The evidence supporting this model is mostly from the observation of alterations of molecular regulators of transcription following exposures. With the understanding that the interpretation of these associations is more complex than originally recognised, this model may be oversimplistic; therefore, adopting novel perspectives and experimental approaches when examining how environmental exposures are linked to phenotypes may prove worthwhile. In this review, we have chosen to use the example of nonalcoholic fatty liver disease (NAFLD), a common, complex human disease with strong environmental and genetic influences. We describe how epigenomic approaches combined with emerging functional genetic and single-cell genomic techniques are poised to generate new insights into the pathogenesis of environmentally influenced human disease phenotypes exemplified by NAFLD.
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Affiliation(s)
- Julia J. Wattacheril
- Department of Medicine, Center for Liver Disease and Transplantation, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, New York, United States of America
| | - Srilakshmi Raj
- Division of Genomics, Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - David A. Knowles
- New York Genome Center, New York, New York, United States of America
- Department of Computer Science, Columbia University, New York, New York, United States of America
- Department of Systems Biology, Columbia University, New York, New York, United States of America
| | - John M. Greally
- Division of Genomics, Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, United States of America
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Mahmood U, Li X, Fan Y, Chang W, Niu Y, Li J, Qu C, Lu K. Multi-omics revolution to promote plant breeding efficiency. FRONTIERS IN PLANT SCIENCE 2022; 13:1062952. [PMID: 36570904 PMCID: PMC9773847 DOI: 10.3389/fpls.2022.1062952] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 11/24/2022] [Indexed: 06/17/2023]
Abstract
Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world's food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.
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Affiliation(s)
- Umer Mahmood
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
| | - Xiaodong Li
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
| | - Yonghai Fan
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
| | - Wei Chang
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
| | - Yue Niu
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
| | - Jiana Li
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Chongqing, China
| | - Cunmin Qu
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Chongqing, China
| | - Kun Lu
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Chongqing, China
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Kilanowski A, Merid SK, Abrishamcar S, Feil D, Thiering E, Waldenberger M, Melén E, Peters A, Standl M, Hüls A. DNA methylation and aeroallergen sensitization: The chicken or the egg? Clin Epigenetics 2022; 14:114. [PMID: 36114581 PMCID: PMC9482323 DOI: 10.1186/s13148-022-01332-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 09/05/2022] [Indexed: 11/21/2022] Open
Abstract
Background DNA methylation (DNAm) is considered a plausible pathway through which genetic and environmental factors may influence the development of allergies. However, causality has yet to be determined as it is unknown whether DNAm is rather a cause or consequence of allergic sensitization. Here, we investigated the direction of the observed associations between well-known environmental and genetic determinants of allergy, DNAm, and aeroallergen sensitization using a combination of high-dimensional and causal mediation analyses.
Methods Using prospectively collected data from the German LISA birth cohort from two time windows (6–10 years: N = 234; 10–15 years: N = 167), we tested whether DNAm is a cause or a consequence of aeroallergen sensitization (specific immunoglobulin E > 0.35kU/l) by conducting mediation analyses for both effect directions using maternal smoking during pregnancy, family history of allergies, and a polygenic risk score (PRS) for any allergic disease as exposure variables. We evaluated individual CpG sites (EPIC BeadChip) and allergy-related methylation risk scores (MRS) as potential mediators in the mediation analyses. We applied three high-dimensional mediation approaches (HIMA, DACT, gHMA) and validated results using causal mediation analyses. A replication of results was attempted in the Swedish BAMSE cohort.
Results Using high-dimensional methods, we identified five CpGs as mediators of prenatal exposures to sensitization with significant (adjusted p < 0.05) indirect effects in the causal mediation analysis (maternal smoking: two CpGs, family history: one, PRS: two). None of these CpGs could be replicated in BAMSE. The effect of family history on allergy-related MRS was significantly mediated by aeroallergen sensitization (proportions mediated: 33.7–49.6%), suggesting changes in DNAm occurred post-sensitization. Conclusion The results indicate that DNAm may be a cause or consequence of aeroallergen sensitization depending on genomic location. Allergy-related MRS, identified as a potential cause of sensitization, can be considered as a cross-sectional biomarker of disease. Differential DNAm in individual CpGs, identified as mediators of the development of sensitization, could be used as clinical predictors of disease development. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-022-01332-5.
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Li S, Mancuso N, Metayer C, Ma X, de Smith AJ, Wiemels JL. Incorporation of DNA methylation quantitative trait loci (mQTLs) in epigenome-wide association analysis: application to birthweight effects in neonatal whole blood. Clin Epigenetics 2022; 14:158. [PMID: 36457128 PMCID: PMC9714153 DOI: 10.1186/s13148-022-01385-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 11/22/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Epigenome-wide association studies (EWAS) have helped to define the associations between DNA methylation and many clinicopathologic and developmental traits. Since DNA methylation is affected by genetic variation at certain loci, EWAS associations may be potentially influenced by genetic effects. However, a formal assessment of the value of incorporating genetic variation in EWAS evaluations is lacking especially for multiethnic populations. METHODS Using single nucleotide polymorphism (SNP) from Illumina Omni Express or Affymetrix PMDA arrays and DNA methylation data from the Illumina 450 K or EPIC array from 1638 newborns of diverse genetic ancestries, we generated DNA methylation quantitative trait loci (mQTL) databases for both array types. We then investigated associations between neonatal DNA methylation and birthweight (incorporating gestational age) using EWAS modeling, and reported how EWAS results were influenced by controlling for mQTLs. RESULTS For CpGs on the 450 K array, an average of 15.4% CpGs were assigned as mQTLs, while on the EPIC array, 23.0% CpGs were matched to mQTLs (adjusted P value < 0.05). The CpGs associated with SNPs were enriched in the CpG island shore regions. Correcting for mQTLs in the EWAS model for birthweight helped to increase significance levels for top hits. For CpGs overlapping genes associated with birthweight-related pathways (nutrition metabolism, biosynthesis, for example), accounting for mQTLs changed their regression coefficients more dramatically (> 20%) than for other random CpGs. CONCLUSION DNA methylation levels at circa 20% CpGs in the genome were affected by common SNP genotypes. EWAS model fit significantly improved when taking these genetic effects into consideration. Genetic effects were stronger on CpGs overlapping genetic elements associated with control of gene expression.
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Affiliation(s)
- Shaobo Li
- grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Center for Genetic Epidemiology, University of Southern California, USC Health Sciences Campus, 1520 San Pablo St., Los Angeles, CA USA
| | - Nicholas Mancuso
- grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Center for Genetic Epidemiology, University of Southern California, USC Health Sciences Campus, 1520 San Pablo St., Los Angeles, CA USA
| | - Catherine Metayer
- grid.47840.3f0000 0001 2181 7878School of Public Health, University of California Berkeley, Berkeley, CA USA
| | - Xiaomei Ma
- grid.47100.320000000419368710Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, CT USA
| | - Adam J. de Smith
- grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Center for Genetic Epidemiology, University of Southern California, USC Health Sciences Campus, 1520 San Pablo St., Los Angeles, CA USA
| | - Joseph L. Wiemels
- grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Center for Genetic Epidemiology, University of Southern California, USC Health Sciences Campus, 1520 San Pablo St., Los Angeles, CA USA
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Tang G, Sun C, Lv H, Zhang M, Jiang Y, Xu J. Identification of novel meQTLs strongly associated with rheumatoid arthritis by large-scale epigenome-wide analysis. FEBS Open Bio 2022; 12:2227-2235. [PMID: 36342317 PMCID: PMC9714356 DOI: 10.1002/2211-5463.13517] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/26/2022] [Accepted: 11/07/2022] [Indexed: 11/09/2022] Open
Abstract
Rheumatoid arthritis (RA) is highly heritable, and previous studies have suggested that genetic variation may affect susceptibility to RA by altering epigenetic modifications (e.g. DNA methylation). Here we examined how genetic variation influences DNA methylation (DNAm) in RA by integrating individual genetic variation and DNAm data. Epigenome-wide meQTL (methylation quantitative trait loci) analysis was performed on 354 RA patients and 335 controls, scanning 30,101,744 relationships between 62 SNPs and 485,512 DNA methylation sites. Two regulatory relationship pairs (FDR < 0.05) showed very strong associations with RA risk. One was rs10796216-cg00475509, and the DNAm decreased by 0.0168 per addition of allele rs10796216-A. The other was rs6546473-cg13358873, for which a 0.0365 reduction of DNAm at cg13358873 was observed for each addition of allele rs6546473-A, and lower DNAm was found to be significantly associated with RA risk (P = 2.0407e-28). Moreover, both pairs of meQTL showed a strong regulatory relationship only in RA samples, so they can be subsequently considered as risk markers for RA. In conclusion, our integrated analysis of genetic and epigenetic variation suggests that genetic variation may affect the risk of RA by regulating DNA methylation levels. Alterations of DNAm at cg00475509 and cg13358873 loci conferred by rs10796216-A and rs6546473-A allele may suggest a potential risk for RA. Our results deepen our understanding of the genetic and epigenetic mechanisms of RA and provide novel associations that can be further investigated in future studies.
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Affiliation(s)
- Guoping Tang
- The Fourth Affiliated HospitalZhejiang University School of MedicineChina
| | - Chen Sun
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityChina
| | - Hongchao Lv
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityChina
| | - Mingming Zhang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityChina
| | - Yongshuai Jiang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityChina
| | - Jing Xu
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityChina
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Elucidating the genetic architecture of DNA methylation to identify promising molecular mechanisms of disease. Sci Rep 2022; 12:19564. [PMID: 36380121 PMCID: PMC9664436 DOI: 10.1038/s41598-022-24100-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 11/10/2022] [Indexed: 11/16/2022] Open
Abstract
DNA methylation commonly occurs at cytosine-phosphate-guanine sites (CpGs) that can serve as biomarkers for many diseases. We analyzed whole genome sequencing data to identify DNA methylation quantitative trait loci (mQTLs) in 4126 Framingham Heart Study participants. Our mQTL mapping identified 94,362,817 cis-mQTLvariant-CpG pairs (for 210,156 unique autosomal CpGs) at P < 1e-7 and 33,572,145 trans-mQTL variant-CpG pairs (for 213,606 unique autosomal CpGs) at P < 1e-14. Using cis-mQTL variants for 1258 CpGs associated with seven cardiovascular disease (CVD) risk factors, we found 104 unique CpGs that colocalized with at least one CVD trait. For example, cg11554650 (PPP1R18) colocalized with type 2 diabetes, and was driven by a single nucleotide polymorphism (rs2516396). We performed Mendelian randomization (MR) analysis and demonstrated 58 putatively causal relations of CVD risk factor-associated CpGs to one or more risk factors (e.g., cg05337441 [APOB] with LDL; MR P = 1.2e-99, and 17 causal associations with coronary artery disease (e.g. cg08129017 [SREBF1] with coronary artery disease; MR P = 5e-13). We also showed that three CpGs, e.g., cg14893161 (PM20D1), are putatively causally associated with COVID-19 severity. To assist in future analyses of the role of DNA methylation in disease pathogenesis, we have posted a comprehensive summary data set in the National Heart, Lung, and Blood Institute's BioData Catalyst.
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Hawe JS, Saha A, Waldenberger M, Kunze S, Wahl S, Müller-Nurasyid M, Prokisch H, Grallert H, Herder C, Peters A, Strauch K, Theis FJ, Gieger C, Chambers J, Battle A, Heinig M. Network reconstruction for trans acting genetic loci using multi-omics data and prior information. Genome Med 2022; 14:125. [PMID: 36344995 PMCID: PMC9641770 DOI: 10.1186/s13073-022-01124-9] [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: 06/15/2022] [Accepted: 10/11/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors used or have only been applied to model systems. In this study, we reconstruct the regulatory networks underlying trans-QTL hotspots using human cohort data and data-driven prior information. METHODS We devised a new strategy to integrate QTL with human population scale multi-omics data. State-of-the art network inference methods including BDgraph and glasso were applied to these data. Comprehensive prior information to guide network inference was manually curated from large-scale biological databases. The inference approach was extensively benchmarked using simulated data and cross-cohort replication analyses. Best performing methods were subsequently applied to real-world human cohort data. RESULTS Our benchmarks showed that prior-based strategies outperform methods without prior information in simulated data and show better replication across datasets. Application of our approach to human cohort data highlighted two novel regulatory networks related to schizophrenia and lean body mass for which we generated novel functional hypotheses. CONCLUSIONS We demonstrate that existing biological knowledge can improve the integrative analysis of networks underlying trans associations and generate novel hypotheses about regulatory mechanisms.
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Affiliation(s)
- Johann S Hawe
- Institute of Computational Biology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,German Heart Centre Munich, Department of Cardiology, Technical University Munich, Munich, Germany.,Department of Informatics, Technical University of Munich, Garching, Germany
| | - Ashis Saha
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Sonja Kunze
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Simone Wahl
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,IBE, Faculty of Medicine, LMU Munich, 81377, Munich, Germany.,Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany.,Department of Internal Medicine I (Cardiology), Hospital of the Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Holger Prokisch
- Institute of Human Genetics, School of Medicine, Technische Universität München, Munich, Germany
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,Institute of Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), Neuherberg, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany.,Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Annette Peters
- Institute of Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany.,Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Fabian J Theis
- Department of Informatics, Technical University of Munich, Garching, Germany.,Department of Mathematics, Technical University of Munich, Garching, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,Institute of Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - John Chambers
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.,Lee Kong Chian School of Medicine, Nanyang Technological University, 308232, Singapore, Singapore
| | - Alexis Battle
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Matthias Heinig
- Institute of Computational Biology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany. .,Department of Informatics, Technical University of Munich, Garching, Germany. .,Munich Heart Association, Partner Site Munich, DZHK (German Centre for Cardiovascular Research), 10785, Berlin, Germany.
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48
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The immune factors driving DNA methylation variation in human blood. Nat Commun 2022; 13:5895. [PMID: 36202838 PMCID: PMC9537159 DOI: 10.1038/s41467-022-33511-6] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 09/21/2022] [Indexed: 11/08/2022] Open
Abstract
Epigenetic changes are required for normal development, yet the nature and respective contribution of factors that drive epigenetic variation in humans remain to be fully characterized. Here, we assessed how the blood DNA methylome of 884 adults is affected by DNA sequence variation, age, sex and 139 factors relating to life habits and immunity. Furthermore, we investigated whether these effects are mediated or not by changes in cellular composition, measured by deep immunophenotyping. We show that DNA methylation differs substantially between naïve and memory T cells, supporting the need for adjustment on these cell-types. By doing so, we find that latent cytomegalovirus infection drives DNA methylation variation and provide further support that the increased dispersion of DNA methylation with aging is due to epigenetic drift. Finally, our results indicate that cellular composition and DNA sequence variation are the strongest predictors of DNA methylation, highlighting critical factors for medical epigenomics studies.
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49
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A Methylation Diagnostic Model Based on Random Forests and Neural Networks for Asthma Identification. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:2679050. [PMID: 36213574 PMCID: PMC9534672 DOI: 10.1155/2022/2679050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 09/11/2022] [Accepted: 09/12/2022] [Indexed: 11/17/2022]
Abstract
Background Asthma significantly impacts human life and health as a chronic disease. Traditional treatments for asthma have several limitations. Artificial intelligence aids in cancer treatment and may also accelerate our understanding of asthma mechanisms. We aimed to develop a new clinical diagnosis model for asthma using artificial neural networks (ANN). Methods Datasets (GSE85566, GSE40576, and GSE13716) were downloaded from Gene Expression Omnibus (GEO) and identified differentially expressed CpGs (DECs) enriched by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Random forest (RF) and ANN algorithms further identified gene characteristics and built clinical models. In addition, two external validation datasets (GSE40576 and GSE137716) were used to validate the diagnostic ability of the model. Results The methylation analysis tool (ChAMP) considered DECs that were up-regulated (n =121) and down-regulated (n =20). GO results showed enrichment of actin cytoskeleton organization and cell-substrate adhesion, shigellosis, and serotonergic synapses. RF (random forest) analysis identified 10 crucial DECs (cg05075579, cg20434422, cg03907390, cg00712106, cg05696969, cg22862094, cg11733958, cg00328720, and cg13570822). ANN constructed the clinical model according to 10 DECs. In two external validation datasets (GSE40576 and GSE137716), the Area Under Curve (AUC) for GSE137716 was 1.000, and AUC for GSE40576 was 0.950, confirming the reliability of the model. Conclusion Our findings provide new methylation markers and clinical diagnostic models for asthma diagnosis and treatment.
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50
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Lei MK, Gibbons FX, Gerrard M, Beach SRH, Dawes K, Philibert R. Digital methylation assessments of alcohol and cigarette consumption account for common variance in accelerated epigenetic ageing. Epigenetics 2022; 17:1991-2005. [PMID: 35866695 PMCID: PMC9665121 DOI: 10.1080/15592294.2022.2100684] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Smoking and Heavy Alcohol Consumption (HAC) are established risk factors for myriad complex disorders of ageing. Yet many prior studies of Epigenetic Ageing (EA) have shown only modest effects of smoking and drinking on accelerated ageing. One potential reason for this conundrum might be the reliance of some prior EA studies on self-reported substance use, which may be unreliable in many samples. To test whether novel, non-self-reported indices would show a stronger association of smoking and HAC to EA, we used methylation sensitive digital PCR (MSdPCR) and data from 437 African American subjects from Wave 7 of the Family and Community Health Study Offspring Cohort to examine the effects of subjective and objective measures of smoking and HAC on 7 indices of EA. Because of limited overall correlations between the various EA indices, we examined patterns of association separately for each index. Consistent with expectations, MSdPCR assessments of smoking and HAC, but not self-reported alcohol consumption, were strongly correlated with accelerated EA. MSdPCR assessments of smoking and HAC accounted for 57% of GrimAge acceleration and the shared variance in GrimAge and DunedinPOAM accelerated EA. We conclude that MSdPCR assessments of smoking and HAC are valuable tools for understanding EA, represent directly targetable conditions for the prevention of premature ageing, and substantially improve upon self-reported assessment of smoking and HAC.
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Affiliation(s)
- Man-Kit Lei
- Department of Sociology, University of Georgia, Athens, GA, USA.,Center for Family Research, University of Georgia, Athens, GA, USA
| | - Frederick X Gibbons
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
| | - Meg Gerrard
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
| | - Steven R H Beach
- Center for Family Research, University of Georgia, Athens, GA, USA.,Department of Psychology, University of Georgia, Athens, GA, USA
| | - Kelsey Dawes
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Robert Philibert
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA.,Behavioral Diagnostics LLC, Coralville, IA, USA
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