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Ciantar J, Marttila S, Rajić S, Kostiniuk D, Mishra PP, Lyytikäinen LP, Mononen N, Kleber ME, März W, Kähönen M, Raitakari O, Lehtimäki T, Raitoharju E. Identification and functional characterisation of DNA methylation differences between East- and West-originating Finns. Epigenetics 2024; 19:2397297. [PMID: 39217505 PMCID: PMC11382697 DOI: 10.1080/15592294.2024.2397297] [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: 04/29/2024] [Revised: 08/14/2024] [Accepted: 08/22/2024] [Indexed: 09/04/2024] Open
Abstract
Eastern and Western Finns show a striking difference in coronary heart disease-related mortality; genetics is a known contributor for this discrepancy. Here, we discuss the potential role of DNA methylation in mediating the discrepancy in cardiometabolic disease-risk phenotypes between the sub-populations. We used data from the Young Finns Study (n = 969) to compare the genome-wide DNA methylation levels of East- and West-originating Finns. We identified 21 differentially methylated loci (FDR < 0.05; Δβ >2.5%) and 7 regions (smoothed FDR < 0.05; CpGs ≥ 5). Methylation at all loci and regions associates with genetic variants (p < 5 × 10-8). Independently of genetics, methylation at 11 loci and 4 regions associates with transcript expression, including genes encoding zinc finger proteins. Similarly, methylation at 5 loci and 4 regions associates with cardiometabolic disease-risk phenotypes including triglycerides, glucose, cholesterol, as well as insulin treatment. This analysis was also performed in LURIC (n = 2371), a German cardiovascular patient cohort, and results replicated for the association of methylation at cg26740318 and DMR_11p15 with diabetes-related phenotypes and methylation at DMR_22q13 with triglyceride levels. Our results indicate that DNA methylation differences between East and West Finns may have a functional role in mediating the cardiometabolic disease discrepancy between the sub-populations.
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Affiliation(s)
- Joanna Ciantar
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Saara Marttila
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Gerontology Research Center, Tampere University, Tampere, Finland
- Tays Research Services, Wellbeing Services County of Pirkanmaa, Tampere University Hospital, Tampere, Finland
| | - Sonja Rajić
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Daria Kostiniuk
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Nina Mononen
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Marcus E Kleber
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, Heidelberg University, Mannheim, Germany
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Winfried März
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, Heidelberg University, Mannheim, Germany
- Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim, Germany
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Emma Raitoharju
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories, Tampere, Finland
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Bian X, Jiang H, Meng Y, Li YP, Fang J, Lu Z. Regulation of gene expression by glycolytic and gluconeogenic enzymes. Trends Cell Biol 2022; 32:786-799. [PMID: 35300892 DOI: 10.1016/j.tcb.2022.02.003] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 02/08/2022] [Accepted: 02/11/2022] [Indexed: 12/15/2022]
Abstract
Gene transcription and cell metabolism are two fundamental biological processes that mutually regulate each other. Upregulated or altered expression of glucose metabolic genes in glycolysis and gluconeogenesis is a major driving force of enhanced aerobic glycolysis in tumor cells. Importantly, glycolytic and gluconeogenic enzymes in tumor cells acquire moonlighting functions and directly regulate gene expression by modulating chromatin or transcriptional complexes. The mutual regulation between cellular metabolism and gene expression in a feedback mechanism constitutes a unique feature of tumor cells and provides specific molecular and functional targets for cancer treatment.
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Affiliation(s)
- Xueli Bian
- The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao Cancer Institute, Qingdao 266071, China; Institute of Biomedical Sciences, Nanchang University Medical College, Nanchang 330031, China
| | - Hongfei Jiang
- The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao Cancer Institute, Qingdao 266071, China
| | - Ying Meng
- Zhejiang Provincial Key Laboratory of Pancreatic Disease of The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310029, China
| | - Ying-Ping Li
- Shanxi Academy of Advanced Research and Innovation, Taiyuan 030032, China
| | - Jing Fang
- The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao Cancer Institute, Qingdao 266071, China.
| | - Zhimin Lu
- Zhejiang Provincial Key Laboratory of Pancreatic Disease of The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310029, China; Cancer Center, Zhejiang University, Hangzhou, Zhejiang 310029, China.
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Yu KH, Levine DA, Zhang H, Chan DW, Zhang Z, Snyder M. Predicting Ovarian Cancer Patients' Clinical Response to Platinum-Based Chemotherapy by Their Tumor Proteomic Signatures. J Proteome Res 2016; 15:2455-65. [PMID: 27312948 PMCID: PMC8718213 DOI: 10.1021/acs.jproteome.5b01129] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Ovarian cancer is the deadliest gynecologic malignancy in the United States with most patients diagnosed in the advanced stage of the disease. Platinum-based antineoplastic therapeutics is indispensable to treating advanced ovarian serous carcinoma. However, patients have heterogeneous responses to platinum drugs, and it is difficult to predict these interindividual differences before administering medication. In this study, we investigated the tumor proteomic profiles and clinical characteristics of 130 ovarian serous carcinoma patients analyzed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), predicted the platinum drug response using supervised machine learning methods, and evaluated our prediction models through leave-one-out cross-validation. Our data-driven feature selection approach indicated that tumor proteomics profiles contain information for predicting binarized platinum response (P < 0.0001). We further built a least absolute shrinkage and selection operator (LASSO)-Cox proportional hazards model that stratified patients into early relapse and late relapse groups (P = 0.00013). The top proteomic features indicative of platinum response were involved in ATP synthesis pathways and Ran GTPase binding. Overall, we demonstrated that proteomic profiles of ovarian serous carcinoma patients predicted platinum drug responses as well as provided insights into the biological processes influencing the efficacy of platinum-based therapeutics. Our analytical approach is also extensible to predicting response to other antineoplastic agents or treatment modalities for both ovarian and other cancers.
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Affiliation(s)
| | - Douglas A Levine
- Department of Surgery, Memorial Sloan Kettering Cancer Center , New York, New York 10065, United States
| | - Hui Zhang
- Department of Pathology, Johns Hopkins Medical Institutions , Baltimore, Maryland 21287, United States
| | - Daniel W Chan
- Department of Pathology, Johns Hopkins Medical Institutions , Baltimore, Maryland 21287, United States
| | - Zhen Zhang
- Department of Pathology, Johns Hopkins Medical Institutions , Baltimore, Maryland 21287, United States
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