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Guo S, Zhu W, Bian Y, Li Z, Zheng H, Li W, Yang Y, Ji X, Zhang B. Developing diagnostic biomarkers for Alzheimer's disease based on histone lactylation-related gene. Heliyon 2024; 10:e37807. [PMID: 39315143 PMCID: PMC11417585 DOI: 10.1016/j.heliyon.2024.e37807] [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: 04/10/2024] [Revised: 09/09/2024] [Accepted: 09/10/2024] [Indexed: 09/25/2024] Open
Abstract
Background Research underscores the significant influence of histone lactylation pathways in the progression of Alzheimer's disease (AD), though the molecular mechanisms associated with histone lactylation-related genes (HLRGs) in AD are still insufficiently investigated. Methods This study employed datasets GSE85426 and GSE97760 to identify candidate genes by intersecting weighted gene co-expression network analysis (WGCNA) module genes with AD-control differentially expressed genes (DEGs). Subsequently, machine learning refined key genes, validated by receiver operating characteristic (ROC) curve performance. Gene-set enrichment analysis (GSEA) explored the molecular mechanisms of these diagnostic markers. Concurrently, the association between the diagnostic genes and both differential immune cells and immune responses was examined. Furthermore, a ceRNA and gene-drug network was developed. Finally, the expression of the selected genes was validated using brain tissues from AD model mice. Results This study identified five genes (ARID5B, NSMCE4A, SESN1, THADA, and XPA) with significant diagnostic utility, primarily enriched in olfactory transduction and N-glycan biosynthesis pathways. Correlation analysis demonstrated a strong positive association between all diagnostic genes and naive B cells. The ceRNA regulatory network comprised 7 miRNAs, 2 mRNAs, and 25 lncRNAs. Additionally, 33 drugs targeting the diagnostic genes were predicted. Following expression validation through training and validation sets, three genes (ARID5B, SESN1, XPA) were ultimately confirmed as biomarkers for this study. RT-qPCR and Western blot analyses revealed upregulated expression of ARID5B, SESN1, and XPA in the cerebral tissue of AD model mice. Conclusion Three histone lactylation-linked genes (ARID5B, SESN1, XPA) were identified as potential AD biomarkers, indicating a strong association with disease progression.
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Affiliation(s)
- Shaobo Guo
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Geriatric, Nanjing, China
- Key Laboratory for Metabolic Diseases in Chinese Medicine, First College of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, China
- Jiangsu Provincial Hospital of Traditional Chinese Medicine, Nanjing, China
| | - Wenhui Zhu
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Geriatric, Nanjing, China
- Key Laboratory for Metabolic Diseases in Chinese Medicine, First College of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, China
- Jiangsu Provincial Hospital of Traditional Chinese Medicine, Nanjing, China
| | - Yuting Bian
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Geriatric, Nanjing, China
- Jiangsu Provincial Hospital of Traditional Chinese Medicine, Nanjing, China
| | - Zhikai Li
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Geriatric, Nanjing, China
- Jiangsu Provincial Hospital of Traditional Chinese Medicine, Nanjing, China
| | - Heng Zheng
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Geriatric, Nanjing, China
- Jiangsu Provincial Hospital of Traditional Chinese Medicine, Nanjing, China
- Zhenjiang Hospital of Chinese Traditional And Western Medicine, Zhenjiang, China
| | - Wenlong Li
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Geriatric, Nanjing, China
- Jiangsu Provincial Hospital of Traditional Chinese Medicine, Nanjing, China
- Liyang Hospital of Chinese Medicine, Liyang, China
| | - Yi Yang
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Geriatric, Nanjing, China
- Jiangsu Provincial Hospital of Traditional Chinese Medicine, Nanjing, China
| | - Xuzheng Ji
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Geriatric, Nanjing, China
- Jiangsu Provincial Hospital of Traditional Chinese Medicine, Nanjing, China
| | - Biao Zhang
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Geriatric, Nanjing, China
- Jiangsu Provincial Hospital of Traditional Chinese Medicine, Nanjing, China
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Cinar MU, Oliveira RD, Hadfield TS, Lichtenwalner A, Brzozowski RJ, Settlemire CT, Schoenian SG, Parker C, Neibergs HL, Cockett NE, White SN. Genome-wide association with footrot in hair and wool sheep. Front Genet 2024; 14:1297444. [PMID: 38288162 PMCID: PMC10822918 DOI: 10.3389/fgene.2023.1297444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 12/31/2023] [Indexed: 01/31/2024] Open
Abstract
Ovine footrot is an infectious disease with important contributions from Dichelobacter nodosus and Fusobacterium necrophorum. Footrot is characterized by separation of the hoof from underlying tissue, and this causes severe lameness that negatively impacts animal wellbeing, growth, and profitability. Large economic losses result from lost production as well as treatment costs, and improved genetic tools to address footrot are a valuable long-term goal. Prior genetic studies had examined European wool sheep, but hair sheep breeds such as Katahdin and Blackbelly have been reported to have increased resistance to footrot, as well as to intestinal parasites. Thus, footrot condition scores were collected from 251 U.S. sheep including Katahdin, Blackbelly, and European-influenced crossbred sheep with direct and imputed genotypes at OvineHD array (>500,000 single nucleotide polymorphism) density. Genome-wide association was performed with a mixed model accounting for farm and principal components derived from animal genotypes, as well as a random term for the genomic relationship matrix. We identified three genome-wide significant associations, including SNPs in or near GBP6 and TCHH. We also identified 33 additional associated SNPs with genome-wide suggestive evidence, including a cluster of 6 SNPs in a peak near the genome-wide significance threshold located near the glutamine transporter gene SLC38A1. These findings suggest genetic susceptibility to footrot may be influenced by genes involved in divergent biological processes such as immune responses, nutrient availability, and hoof growth and integrity. This is the first genome-wide study to investigate susceptibility to footrot by including hair sheep and also the first study of any kind to identify multiple genome-wide significant associations with ovine footrot. These results provide a foundation for developing genetic tests for marker-assisted selection to improve resistance to ovine footrot once additional steps like fine mapping and validation are complete.
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Affiliation(s)
- Mehmet Ulas Cinar
- Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, WA, United States
- Department of Animal Science, Faculty of Agriculture, Erciyes University, Kayseri, Turkiye
| | - Ryan D. Oliveira
- Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, WA, United States
| | - Tracy S. Hadfield
- Department of Animal, Agricultural Experiment Station, Dairy and Veterinary Sciences, Utah State University, Logan, UT, United States
| | - Anne Lichtenwalner
- School of Food and Agriculture, University of Maine, Orono, ME, United States
- Cooperative Extension, University of Maine, Orono, ME, United States
| | | | | | - Susan G. Schoenian
- Western Maryland Research and Education Center, University of Maryland, College Park, MD, United States
| | - Charles Parker
- Department of Animal Sciences, Professor Emeritus, The Ohio State University, Columbus, OH, United States
| | - Holly L. Neibergs
- Department of Animal Science, Washington State University, Pullman, WA, United States
| | - Noelle E. Cockett
- Department of Animal, Agricultural Experiment Station, Dairy and Veterinary Sciences, Utah State University, Logan, UT, United States
| | - Stephen N. White
- Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, WA, United States
- Animal Disease Research Unit, Agricultural Research Service, U.S. Department of Agriculture, Pullman, WA, United States
- Center for Reproductive Biology, Washington State University, Pullman, WA, United States
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3
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Kavousi M, Bos MM, Barnes HJ, Lino Cardenas CL, Wong D, Lu H, Hodonsky CJ, Landsmeer LPL, Turner AW, Kho M, Hasbani NR, de Vries PS, Bowden DW, Chopade S, Deelen J, Benavente ED, Guo X, Hofer E, Hwang SJ, Lutz SM, Lyytikäinen LP, Slenders L, Smith AV, Stanislawski MA, van Setten J, Wong Q, Yanek LR, Becker DM, Beekman M, Budoff MJ, Feitosa MF, Finan C, Hilliard AT, Kardia SLR, Kovacic JC, Kral BG, Langefeld CD, Launer LJ, Malik S, Hoesein FAAM, Mokry M, Schmidt R, Smith JA, Taylor KD, Terry JG, van der Grond J, van Meurs J, Vliegenthart R, Xu J, Young KA, Zilhão NR, Zweiker R, Assimes TL, Becker LC, Bos D, Carr JJ, Cupples LA, de Kleijn DPV, de Winther M, den Ruijter HM, Fornage M, Freedman BI, Gudnason V, Hingorani AD, Hokanson JE, Ikram MA, Išgum I, Jacobs DR, Kähönen M, Lange LA, Lehtimäki T, Pasterkamp G, Raitakari OT, Schmidt H, Slagboom PE, Uitterlinden AG, Vernooij MW, Bis JC, Franceschini N, Psaty BM, Post WS, Rotter JI, Björkegren JLM, O'Donnell CJ, Bielak LF, Peyser PA, Malhotra R, van der Laan SW, Miller CL. Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification. Nat Genet 2023; 55:1651-1664. [PMID: 37770635 PMCID: PMC10601987 DOI: 10.1038/s41588-023-01518-4] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 08/29/2023] [Indexed: 09/30/2023]
Abstract
Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.
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Affiliation(s)
- Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
| | - Maxime M Bos
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Hanna J Barnes
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Christian L Lino Cardenas
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Doris Wong
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Haojie Lu
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Chani J Hodonsky
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Lennart P L Landsmeer
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Adam W Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea
| | - Natalie R Hasbani
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Center at Houston, Houston, TX, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Center at Houston, Houston, TX, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Sandesh Chopade
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- University College London British Heart Foundation Research Accelerator Centre, London, UK
| | - Joris Deelen
- Biomedical Data Sciences, Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Max Planck Institute for Biology of Aging, Cologne, Germany
| | - Ernest Diez Benavente
- Laboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Edith Hofer
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University of Graz, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | | | - Sharon M Lutz
- Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care, Boston, MA, USA
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Lotte Slenders
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Albert V Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Icelandic Heart Association, Kopavogur, Iceland
| | - Maggie A Stanislawski
- Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Jessica van Setten
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Quenna Wong
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Diane M Becker
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marian Beekman
- Biomedical Data Sciences, Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Matthew J Budoff
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Mary F Feitosa
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Chris Finan
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- University College London British Heart Foundation Research Accelerator Centre, London, UK
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | | | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jason C Kovacic
- Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia
- St Vincent's Clinical School, University of NSW, Sydney, New South Wales, Australia
- The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Brian G Kral
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences and Data Science, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Shaista Malik
- Susan Samueli Integrative Health Institute, Department of Medicine, University of California Irvine, Irvine, CA, USA
| | | | - Michal Mokry
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Laboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Reinhold Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University of Graz, Graz, Austria
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - James G Terry
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeroen van der Grond
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Joyce van Meurs
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jianzhao Xu
- Department of Biochemistry, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Kendra A Young
- Department of Epidemiology, University of Colorado, Anschutz Medical Campus, Denver, CO, USA
| | | | - Robert Zweiker
- Department of Internal Medicine, Division of Cardiology, Medical University of Graz, Graz, Austria
| | - Themistocles L Assimes
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Lewis C Becker
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Bos
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - J Jeffrey Carr
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - L Adrienne Cupples
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - Dominique P V de Kleijn
- Department of Vascular Surgery, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Menno de Winther
- Department of Medical Biochemistry, Experimental Vascular Biology, Amsterdam Cardiovascular Sciences: Atherosclerosis and Ischemic syndromes, Amsterdam Infection and Immunity: Inflammatory diseases, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Hester M den Ruijter
- Laboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Myriam Fornage
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Barry I Freedman
- Department of Internal Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, School of Public Health, University of Iceland, Reykjavik, Iceland
| | - Aroon D Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- University College London British Heart Foundation Research Accelerator Centre, London, UK
| | - John E Hokanson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Ivana Išgum
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Leslie A Lange
- Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Olli T 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
| | - Helena Schmidt
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Medical University of Graz, Graz, Austria
| | - P Eline Slagboom
- Biomedical Data Sciences, Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Vascular Surgery, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Departments of Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Wendy S Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
- Department of Medicine, Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge, Sweden
| | - Christopher J O'Donnell
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Cardiology Section, Department of Medicine, Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Rajeev Malhotra
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Clint L Miller
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA.
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA.
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4
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Gonzalez-Covarrubias V, Sánchez-Ibarra H, Lozano-Gonzalez K, Villicaña S, Texis T, Rodríguez-Dorantes M, Cortés-Ramírez S, Lavalle-Gonzalez F, Soberón X, Barrera-Saldaña H. Transporters, TBC1D4, and ARID5B Variants to Explain Glycated Hemoglobin Variability in Patients with Type 2 Diabetes. Pharmacology 2021; 106:588-596. [PMID: 34265779 DOI: 10.1159/000517462] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Accepted: 05/15/2021] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Genetic variants could aid in predicting antidiabetic drug response by associating them with markers of glucose control, such as glycated hemoglobin (HbA1c). However, pharmacogenetic implementation for antidiabetics is still under development, as the list of actionable markers is being populated and validated. This study explores potential associations between genetic variants and plasma levels of HbA1c in 100 patients under treatment with metformin. METHODS HbA1c was measured in a clinical chemistry analyzer (Roche), genotyping was performed in an Illumina-GSA array and data were analyzed using PLINK. Association and prediction models were developed using R and a 10-fold cross-validation approach. RESULTS We identified genetic variants on SLC47A1, SLC28A1, ABCG2, TBC1D4, and ARID5B that can explain up to 55% of the interindividual variability of HbA1c plasma levels in diabetic patients under treatment. Variants on SLC47A1, SLC28A1, and ABCG2 likely impact the pharmacokinetics (PK) of metformin, while the role of the two latter can be related to insulin resistance and regulation of adipogenesis. CONCLUSIONS Our results confirm previous genetic associations and point to previously unassociated gene variants for metformin PK and glucose control.
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Affiliation(s)
| | | | | | - Sergio Villicaña
- Pharmacogenomics Laboratory, Instituto Nacional de Medicina Genómica, CDMX, Mexico
| | - Tomas Texis
- Pharmacogenomics Laboratory, Instituto Nacional de Medicina Genómica, CDMX, Mexico
| | | | | | - Fernando Lavalle-Gonzalez
- University Hospital Dr. José E. González, Endocrinology, Universidad Autónoma de Nuevo León, San Nicolás de los Garza, Mexico
| | - Xavier Soberón
- Instituto de Biotecnología, Universidad Autónoma de México, UNAM, Cuernavaca, Mexico
| | - Hugo Barrera-Saldaña
- Genetics Laboratory, Vitagénesis, Monterrey, Mexico.,Medicine and Health Sciences Department, Tecnológico de Monterrey, Monterrey, Mexico
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5
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Whitson RH, Li SL, Zhang G, Larson GP, Itakura K. Mice with Fabp4-Cre ablation of Arid5b are resistant to diet-induced obesity and hepatic steatosis. Mol Cell Endocrinol 2021; 528:111246. [PMID: 33757861 PMCID: PMC8956154 DOI: 10.1016/j.mce.2021.111246] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 02/19/2021] [Accepted: 03/15/2021] [Indexed: 11/29/2022]
Abstract
Mice with global deletion of Arid5b expression are lean and resistant to diet-induced obesity, and Arid5b is required for adipogenesis in a variety of in vitro models. To determine whether the lean phenotype of Arid5b-/- mice can be explained by its absence in adipose tissues, we generated mice with Fabp4-mediated ablation of Arid5b. Arid5b expression was ablated in adipocytes, from Fabp4-CREpos; Arid5bFLOX/FLOX (FSKO) mice. FSKO mice were not lean when maintained on standard chow, but males were resistant to weight gains when placed on high-fat diets (HFD). This was mainly due to decreased lipid accumulation in subcutaneous (inguinal) white adipose tissue (IWAT), and the liver. Lipid accumulation proceeded normally in gonadal WAT (GWAT) and glucose intolerance developed to the same degree in FSKO and WT controls when subjected to HFD. CD68-positive macrophages were also significantly reduced in both inguinal and gonadal fat depots. RNA-Seq analysis of IWAT adipocytes from FSKO mice on HFD revealed significant decreases in the expression of genes associated with inflammation. Although Arid5b expression was normal in livers of FSKO mice, tissue weight gains and triglyceride accumulation, and expression of genes involved in lipid metabolism were markedly reduced in livers of FSKO mice on HFD. These results suggest that Arid5b plays a critical role in lipid accumulation in specific WAT depots, and in the inflammatory signaling from WAT depots to liver that lead to lipid accumulation and hepatic steatosis.
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Affiliation(s)
- Robert H Whitson
- Department of Molecular and Cellular Biology, Beckman Research Institute of City of Hope, Duarte, CA, 91010, USA
| | - Shu-Lian Li
- Department of Molecular and Cellular Biology, Beckman Research Institute of City of Hope, Duarte, CA, 91010, USA
| | - Guoxiang Zhang
- Department of Molecular and Cellular Biology, Beckman Research Institute of City of Hope, Duarte, CA, 91010, USA
| | - Garrett P Larson
- Department of Molecular and Cellular Biology, Beckman Research Institute of City of Hope, Duarte, CA, 91010, USA.
| | - Keiichi Itakura
- Department of Molecular and Cellular Biology, Beckman Research Institute of City of Hope, Duarte, CA, 91010, USA
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6
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Smyth LJ, Kilner J, Nair V, Liu H, Brennan E, Kerr K, Sandholm N, Cole J, Dahlström E, Syreeni A, Salem RM, Nelson RG, Looker HC, Wooster C, Anderson K, McKay GJ, Kee F, Young I, Andrews D, Forsblom C, Hirschhorn JN, Godson C, Groop PH, Maxwell AP, Susztak K, Kretzler M, Florez JC, McKnight AJ. Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease: an exploratory study. Clin Epigenetics 2021; 13:99. [PMID: 33933144 PMCID: PMC8088646 DOI: 10.1186/s13148-021-01081-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 04/15/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this exploratory investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing to identify potential blood-based biomarkers. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina's Infinium MethylationEPIC BeadChip arrays (n = 862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p ≤ × 10-8 and fold change ± 2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM. RESULTS Top-ranked genes within which several dmCpGs were located and supported by functional data with methylation look-ups in other cohorts include: AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9 and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation. CONCLUSIONS Epigenetic alterations provide a dynamic link between an individual's genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.
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Affiliation(s)
- L J Smyth
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK.
| | - J Kilner
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - V Nair
- Internal Medicine, Department of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - H Liu
- Department of Department of Medicine/ Nephrology, Department of Genetics, Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - E Brennan
- Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Dublin 4, Ireland
| | - K Kerr
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - N Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - J Cole
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - E Dahlström
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - A Syreeni
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - R M Salem
- Department of Family Medicine and Public Health, UC San Diego, San Diego, CA, USA
| | - R G Nelson
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - H C Looker
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - C Wooster
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - K Anderson
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - G J McKay
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - F Kee
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - I Young
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - D Andrews
- Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Dublin 4, Ireland
| | - C Forsblom
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - J N Hirschhorn
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - C Godson
- Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Dublin 4, Ireland
| | - P H Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - A P Maxwell
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
- Regional Nephrology Unit, Belfast City Hospital, Belfast, Northern Ireland, UK
| | - K Susztak
- Department of Department of Medicine/ Nephrology, Department of Genetics, Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - M Kretzler
- Internal Medicine, Department of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - J C Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - A J McKnight
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
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7
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Xu H, Zhao X, Bhojwani D, E S, Goodings C, Zhang H, Seibel NL, Yang W, Li C, Carroll WL, Evans WE, Yang JJ. ARID5B Influences Antimetabolite Drug Sensitivity and Prognosis of Acute Lymphoblastic Leukemia. Clin Cancer Res 2019; 26:256-264. [PMID: 31573954 DOI: 10.1158/1078-0432.ccr-19-0190] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 06/13/2019] [Accepted: 09/26/2019] [Indexed: 02/07/2023]
Abstract
PURPOSE Treatment outcomes for childhood acute lymphoblastic leukemia (ALL) have improved steadily, but a significant proportion of patients still experience relapse due to drug resistance, which is partly explained by inherited and/or somatic genetic alternations. Recently, we and others have identified genetic variants in the ARID5B gene associated with susceptibility to ALL and also with relapse. In this study, we sought to characterize the molecular pathway by which ARID5B affects antileukemic drug response in patients with ALL. EXPERIMENTAL DESIGN We analyzed association of ARID5B expression in primary human ALL blasts with molecular subtypes and treatment outcome. Subsequent mechanistic studies were performed in ALL cell lines by manipulating ARID5B expression isogenically, in which we evaluated drug sensitivity, metabolism, and molecular signaling events. RESULTS ARID5B expression varied substantially by ALL subtype, with the highest level being observed in hyperdiploid ALL. Lower ARID5B expression at diagnosis was associated with the risk of ALL relapse, and further reduction was noted at ALL relapse. In isogenic ALL cell models in vitro, ARID5B knockdown led to resistance specific to antimetabolite drugs (i.e., 6-mercaptopurine and methotrexate), without significantly affecting sensitivity to other antileukemic agents. ARID5B downregulation significantly inhibited ALL cell proliferation and caused partial cell-cycle arrest. At the molecular level, the cell-cycle checkpoint regulator p21 (encoded by CDKN1A) was most consistently modulated by ARID5B, plausibly as its direct transcription regulation target. CONCLUSIONS Our data indicate that ARID5B is an important molecular determinant of antimetabolite drug sensitivity in ALL, in part, through p21-mediated effects on cell-cycle progression.
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Affiliation(s)
- Heng Xu
- Department of Laboratory Medicine, Precision Medicine Center, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xujie Zhao
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Deepa Bhojwani
- Division of Hematology, Oncology, Blood and Marrow Transplantation, Children's Hospital Los Angeles, Los Angeles, California
| | - Shuyu E
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Charnise Goodings
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Hui Zhang
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee.,Department of Pediatric Hematology and Oncology, Guangzhou Women and Children's Medical Center, Guangzhou, Guangdong, China
| | - Nita L Seibel
- Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, Maryland
| | - Wentao Yang
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Chunliang Li
- Department of Tumor Cell Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - William L Carroll
- Departments of Pediatrics and Pathology, New York University Langone Medical Center, New York, New York
| | - William E Evans
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee.,Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Jun J Yang
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee. .,Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, Tennessee
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8
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Sun LL, Zhang SJ, Chen MJ, Elena K, Qiao H. Relationship between Modulator Recognition Factor 2/AT-rich Interaction Domain 5B Gene Variations and Type 2 Diabetes Mellitus or Lipid Metabolism in a Northern Chinese Population. Chin Med J (Engl) 2018; 130:1055-1061. [PMID: 28469100 PMCID: PMC5421175 DOI: 10.4103/0366-6999.204926] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Background: Four single nucleotide polymorphisms (SNPs) in the modulator recognition factor 2/AT-rich interaction domain 5B (MRF2/ARID5B) gene located at chromosome 10q21.2 have been shown to be associated with both type 2 diabetes mellitus (T2DM) and coronary artery disease in a Japanese cohort. This study aimed to investigate the relationship between these SNPs (rs2893880, rs10740055, rs7087507, rs10761600) and new-onset T2DM and lipid metabolism in a Northern Chinese population. Methods: This was a case-control study. The rs2893880, rs10740055, rs7087507, and rs10761600 genetic variants were genotyped by SNPscan and analyzed in relation to T2DM susceptibility in 2000 individuals (999 with newly diagnosed T2DM and 1001 controls without diabetes mellitus). Associations between the MRF2/ARID5B genetic models and T2DM were determined by multivariate logistic regression. Results: Regarding the rs10740055 SNP, AA was associated with a higher risk of T2DM compared with codominant-type CC (adjusted by sex, age, and body mass index [BMI], P = 0.041, odds ratio [OR] = 1.421, 95% confidence interval [CI] 1.014–1.991). Meanwhile, AA individuals were at increased risk of presenting with T2DM compared with individuals with CC or a single C (adjusted by sex, age, and BMI, P = 0.034, OR = 1.366, 95% CI 1.023–1.824). With respect to rs10761600, AT contributed to a higher risk of T2DM compared with AA (adjusted by sex, age, and BMI, P = 0.013, OR = 1.585, 95% CI 1.101–2.282), while TT also increased the risk of presenting with T2DM compared with AA or A (adjusted by sex, age, and BMI, P = 0.004, OR = 1.632, 95% CI 1.166–2.284). High-density lipoprotein cholesterol (HDL-C) levels were significantly different among the three genotypes of rs7087507 in the controls (P = 0.048) (GG>GA). Conclusions: The present results identified MRF2/ARID5B as a potential susceptibility gene for new-onset T2DM in a Northern Chinese population, while the rs7087507 SNP was associated with HDL-C levels. Further larger studies are required to validate these findings.
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Affiliation(s)
- Lu-Lu Sun
- Department of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150000, China
| | - Si-Jia Zhang
- Department of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150000, China
| | - Mei-Jun Chen
- Department of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150000, China
| | - Kazakova Elena
- Department of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150000, China
| | - Hong Qiao
- Department of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150000, China
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9
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Hoffman ML, Reed SA, Pillai SM, Jones AK, McFadden KK, Zinn SA, Govoni KE. PHYSIOLOGY AND ENDOCRINOLOGY SYMPOSIUM:The effects of poor maternal nutrition during gestation on offspring postnatal growth and metabolism. J Anim Sci 2017; 95:2222-2232. [PMID: 28727021 DOI: 10.2527/jas.2016.1229] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Poor maternal nutrition during gestation has been linked to poor growth and development, metabolic dysfunction, impaired health, and reduced productivity of offspring in many species. Poor maternal nutrition can be defined as an excess or restriction of overall nutrients or specific macro- or micronutrients in the diet of the mother during gestation. Interestingly, there are several reports that both restricted- and over-feeding during gestation negatively affect offspring postnatal growth with reduced muscle and bone deposition, increased adipose accumulation, and metabolic dysregulation through reduced leptin and insulin sensitivity. Our laboratory and others have used experimental models of restricted- and over-feeding during gestation to evaluate effects on early postnatal growth of offspring. Restricted- and over-feeding during gestation alters body size, circulating growth factors, and metabolic hormones in offspring postnatally. Both restricted- and over-feeding alter muscle growth, increase lipid content in the muscle, and cause changes in expression of myogenic factors. Although the negative effects of poor maternal nutrition on offspring growth have been well characterized in recent years, the mechanisms contributing to these changes are not well established. Our laboratory has focused on elucidating these mechanisms by evaluating changes in gene and protein expression, and stem cell function. Through RNA-Seq analysis, we observed changes in expression of genes involved in protein synthesis, metabolism, cell function, and signal transduction in muscle tissue. We recently reported that satellite cells, muscle stem cells, have altered expression of myogenic factors in offspring from restricted-fed mothers. Bone marrow derived mesenchymal stem cells, multipotent cells that contribute to development and maintenance of several tissues including bone, muscle, and adipose, have a 50% reduction in cell proliferation and altered metabolism in offspring from both restricted- and over-fed mothers. These findings indicate that poor maternal nutrition may alter offspring postnatal growth by programming stem cell populations. In conclusion, poor maternal nutrition during gestation negatively affects offspring postnatal growth, potentially through impaired stem and satellite cell function. Therefore, determining the mechanisms that contribute to fetal programming is critical to identifying effective management interventions for these offspring and improving efficiency of production.
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10
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Hirose-Yotsuya L, Okamoto F, Yamakawa T, Whitson RH, Fujita-Yamaguchi Y, Itakura K. Knockdown of AT-rich interaction domain (ARID) 5B gene expression induced AMPKα2 activation in cardiac myocytes. Biosci Trends 2016; 9:377-85. [PMID: 26781795 DOI: 10.5582/bst.2015.01159] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
This study demonstrated that ARID5B mRNA is present in mouse cardiomyocyte HL-1 cells, and that ARID5B siRNA constantly knocked down ARID5B gene expression to the 40% level of control. AMPKα2 protein was elevated in such ARID5B knockdown HL-1 cells, and this was accompanied by an increase in the level of phosphorylated AMPKα. Since AMPKα2 mRNA levels did not change in ARID5B knockdown cells, the stability of AMPKα2 protein was investigated using inhibitors for protein synthesis and proteasomal degradation. Treatment of HL-1 cells with either cycloheximide or MG132 caused an appreciable increase in the amount of AMPKα2 protein in ARID5B knockdown cells, which suggests that knockdown of ARID5B mRNA extends the half-life of AMPKα2 protein in HL-1 cells via yet unidentified mechanisms. As for the expected downstream consequences of AMPKα2 activation, we found thus far that glucose uptake, fatty acid uptake, or fatty acid oxidation remained unchanged in HL-1 cells after knockdown of ARID5B. Further studies are required to understand the mechanisms for ARID5B knockdown and resulting AMPKα2 activation, and also to identify which metabolic pathways are affected by AMPKα2 activation in these cells. In summary, this study provided the foundation for an in vitro cell culture system to study possible roles of ARID5B in cardiomyocytes.
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Affiliation(s)
- Lisa Hirose-Yotsuya
- Department of Molecular & Cellular Biology, Beckman Research Institute of City of Hope
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11
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Hoffman ML, Peck KN, Wegrzyn JL, Reed SA, Zinn SA, Govoni KE. Poor maternal nutrition during gestation alters the expression of genes involved in muscle development and metabolism in lambs1. J Anim Sci 2016; 94:3093-9. [DOI: 10.2527/jas.2016-0570] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
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12
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Banerji J. Asparaginase treatment side-effects may be due to genes with homopolymeric Asn codons (Review-Hypothesis). Int J Mol Med 2015; 36:607-26. [PMID: 26178806 PMCID: PMC4533780 DOI: 10.3892/ijmm.2015.2285] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2015] [Accepted: 07/15/2015] [Indexed: 12/14/2022] Open
Abstract
The present treatment of childhood T-cell leukemias involves the systemic administration of prokary-otic L-asparaginase (ASNase), which depletes plasma Asparagine (Asn) and inhibits protein synthesis. The mechanism of therapeutic action of ASNase is poorly understood, as are the etiologies of the side-effects incurred by treatment. Protein expression from genes bearing Asn homopolymeric coding regions (N-hCR) may be particularly susceptible to Asn level fluctuation. In mammals, N-hCR are rare, short and conserved. In humans, misfunctions of genes encoding N-hCR are associated with a cluster of disorders that mimic ASNase therapy side-effects which include impaired glycemic control, dislipidemia, pancreatitis, compromised vascular integrity, and neurological dysfunction. This paper proposes that dysregulation of Asn homeostasis, potentially even by ASNase produced by the microbiome, may contribute to several clinically important syndromes by altering expression of N-hCR bearing genes. By altering amino acid abundance and modulating ribosome translocation rates at codon repeats, the microbiomic environment may contribute to genome decoding and to shaping the proteome. We suggest that impaired translation at poly Asn codons elevates diabetes risk and severity.
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Affiliation(s)
- Julian Banerji
- Center for Computational and Integrative Biology, MGH, Simches Research Center, Boston, MA 02114, USA
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13
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Jiang L, Wu J, Li W, Du J, Wang W, Zhu Z, Gao J, Sheng Y, Yin X, Zheng X, Li H, Li Y, Meng L, Fan X, Liu S, Zeng M, Wang Z, Cui Y, Tang H, Sun L, Yang S, Zhang X. Rs4948496 withinARID5Bgene is associated with clinical features of systemic lupus erythematosus in the Chinese Han population. J Dermatol 2015; 42:608-12. [PMID: 25808444 DOI: 10.1111/1346-8138.12841] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Accepted: 02/03/2015] [Indexed: 01/20/2023]
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14
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Liu S, Lorenzen ED, Fumagalli M, Li B, Harris K, Xiong Z, Zhou L, Korneliussen TS, Somel M, Babbitt C, Wray G, Li J, He W, Wang Z, Fu W, Xiang X, Morgan CC, Doherty A, O'Connell MJ, McInerney JO, Born EW, Dalén L, Dietz R, Orlando L, Sonne C, Zhang G, Nielsen R, Willerslev E, Wang J. Population genomics reveal recent speciation and rapid evolutionary adaptation in polar bears. Cell 2014; 157:785-94. [PMID: 24813606 PMCID: PMC4089990 DOI: 10.1016/j.cell.2014.03.054] [Citation(s) in RCA: 244] [Impact Index Per Article: 22.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2013] [Revised: 12/20/2013] [Accepted: 03/04/2014] [Indexed: 12/22/2022]
Abstract
Polar bears are uniquely adapted to life in the High Arctic and have undergone drastic physiological changes in response to Arctic climates and a hyper-lipid diet of primarily marine mammal prey. We analyzed 89 complete genomes of polar bear and brown bear using population genomic modeling and show that the species diverged only 479-343 thousand years BP. We find that genes on the polar bear lineage have been under stronger positive selection than in brown bears; nine of the top 16 genes under strong positive selection are associated with cardiomyopathy and vascular disease, implying important reorganization of the cardiovascular system. One of the genes showing the strongest evidence of selection, APOB, encodes the primary lipoprotein component of low-density lipoprotein (LDL); functional mutations in APOB may explain how polar bears are able to cope with life-long elevated LDL levels that are associated with high risk of heart disease in humans.
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Affiliation(s)
- Shiping Liu
- BGI-Shenzhen, Shenzhen 518083, China; School of Bioscience and Biotechnology, South China University of Technology, Guangzhou 510641, China
| | - Eline D Lorenzen
- Department of Integrative Biology, 3060 Valley Life Sciences Building, University of California, Berkeley, CA 94720, USA; Centre for GeoGenetics, Natural History Museum, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen K, Denmark
| | - Matteo Fumagalli
- Department of Integrative Biology, 3060 Valley Life Sciences Building, University of California, Berkeley, CA 94720, USA
| | - Bo Li
- BGI-Shenzhen, Shenzhen 518083, China
| | - Kelley Harris
- Department of Mathematics, 970 Evans Hall, University of California, Berkeley, CA 94720, USA
| | | | - Long Zhou
- BGI-Shenzhen, Shenzhen 518083, China
| | - Thorfinn Sand Korneliussen
- Centre for GeoGenetics, Natural History Museum, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen K, Denmark
| | - Mehmet Somel
- Department of Integrative Biology, 3060 Valley Life Sciences Building, University of California, Berkeley, CA 94720, USA
| | - Courtney Babbitt
- Department of Biology, 124 Science Drive, Duke Box # 90338, Duke University, Durham, NC 27708, USA; Institute for Genome Sciences & Policy, 101 Science Drive, DUMC Box 3382, Duke University, Durham, NC 27708, USA
| | - Greg Wray
- Department of Biology, 124 Science Drive, Duke Box # 90338, Duke University, Durham, NC 27708, USA; Institute for Genome Sciences & Policy, 101 Science Drive, DUMC Box 3382, Duke University, Durham, NC 27708, USA
| | | | - Weiming He
- BGI-Shenzhen, Shenzhen 518083, China; School of Bioscience and Biotechnology, South China University of Technology, Guangzhou 510641, China
| | - Zhuo Wang
- BGI-Shenzhen, Shenzhen 518083, China
| | | | - Xueyan Xiang
- BGI-Shenzhen, Shenzhen 518083, China; College of Life Sciences, Sichuan University, Chengdu 610064, China
| | - Claire C Morgan
- Bioinformatics and Molecular Evolution Group, School of Biotechnology, Dublin City University, Glasnevin, Dublin 9, Ireland
| | - Aoife Doherty
- Bioinformatics and Molecular Evolution Unit, Department of Biology, National University of Ireland, Maynooth, Co. Kildare, Ireland
| | - Mary J O'Connell
- Bioinformatics and Molecular Evolution Group, School of Biotechnology, Dublin City University, Glasnevin, Dublin 9, Ireland
| | - James O McInerney
- Bioinformatics and Molecular Evolution Unit, Department of Biology, National University of Ireland, Maynooth, Co. Kildare, Ireland
| | - Erik W Born
- Greenland Institute of Natural Resources, c/o Government of Greenland Representation in Denmark, Strandgade 91, 3. Floor, PO Box 2151, 1016 Copenhagen K, Denmark
| | - Love Dalén
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, PO Box 50007, 10405, Stockholm, Sweden
| | - Rune Dietz
- Department of Bioscience, Arctic Research Centre, Aarhus University, Frederiksborgvej 399, PO Box 358, 4000 Roskilde, Denmark
| | - Ludovic Orlando
- Centre for GeoGenetics, Natural History Museum, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen K, Denmark
| | - Christian Sonne
- Department of Bioscience, Arctic Research Centre, Aarhus University, Frederiksborgvej 399, PO Box 358, 4000 Roskilde, Denmark
| | - Guojie Zhang
- BGI-Shenzhen, Shenzhen 518083, China; Centre for Social Evolution, Department of Biology, University of Copenhagen, Universitetsparken 15, 2100 Copenhagen, Denmark
| | - Rasmus Nielsen
- BGI-Shenzhen, Shenzhen 518083, China; Department of Integrative Biology, 3060 Valley Life Sciences Building, University of California, Berkeley, CA 94720, USA; Department of Statistics, 367 Evans Hall, University of California, Berkeley, CA 94720, USA; Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200 Copenhagen Ø, Denmark.
| | - Eske Willerslev
- Centre for GeoGenetics, Natural History Museum, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen K, Denmark.
| | - Jun Wang
- BGI-Shenzhen, Shenzhen 518083, China; Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200 Copenhagen Ø, Denmark; Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia; Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau 999078, China; Department of Medicine, University of Hong Kong, Sassoon Road, Pokfulam, Hong Kong.
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Engel SM, Joubert BR, Wu MC, Olshan AF, Håberg SE, Ueland PM, Nystad W, Nilsen RM, Vollset SE, Peddada SD, London SJ. Neonatal genome-wide methylation patterns in relation to birth weight in the Norwegian Mother and Child Cohort. Am J Epidemiol 2014; 179:834-42. [PMID: 24561991 DOI: 10.1093/aje/kwt433] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Although epigenetic regulation plays a critical role in embryonic development, few studies have examined the relationship of epigenome-wide methylation with fetal growth. Using the Infinium HumanMethylation450 BeadChip (Illumina, Inc., San Diego, California) in a substudy of 1,046 infants from the Norwegian Mother and Child Cohort Study (MoBa) enrolled between 1999 and 2008, we examined epigenome-wide cord blood DNA methylation in relation to birth weight. In multivariable-adjusted robust linear regression models, we identified differential methylation at 19 cytosine-guanine dinucleotides (CpGs) associated with either decreased (AT-rich interactive domain 5B (MRF1-like) (ARID5B), 2 CpGs) or increased (x-ray repair complementing defective repair in Chinese hamster cells 3 (XRCC3), 4 CpGs) birth weight. ARID5B knockout mice have less adipose tissue and significantly lower weight in the postnatal period. XRCC3 plays a key role in the maintenance of chromosome stability and the repair of DNA damage. Although there are fewer data on the other implicated genes, many of these genes have been shown to have roles in developmental processes. This constitutes the largest and most robust study of birth weight using an epigenome-wide methylation platform and offers potential insights into epigenetic mechanisms of fetal growth.
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