1
|
Kang J, Castro VM, Ripperger M, Venkatesh S, Burstein D, Linnér RK, Rocha DB, Hu Y, Wilimitis D, Morley T, Han L, Kim RY, Feng YCA, Ge T, Heckers S, Voloudakis G, Chabris C, Roussos P, McCoy TH, Walsh CG, Perlis RH, Ruderfer DM. Genome-Wide Association Study of Treatment-Resistant Depression: Shared Biology With Metabolic Traits. Am J Psychiatry 2024:appiajp20230247. [PMID: 38745458 DOI: 10.1176/appi.ajp.20230247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
OBJECTIVE Treatment-resistant depression (TRD) occurs in roughly one-third of all individuals with major depressive disorder (MDD). Although research has suggested a significant common variant genetic component of liability to TRD, with heritability estimated at 8% when compared with non-treatment-resistant MDD, no replicated genetic loci have been identified, and the genetic architecture of TRD remains unclear. A key barrier to this work has been the paucity of adequately powered cohorts for investigation, largely because of the challenge in prospectively investigating this phenotype. The objective of this study was to perform a well-powered genetic study of TRD. METHODS Using receipt of electroconvulsive therapy (ECT) as a surrogate for TRD, the authors applied standard machine learning methods to electronic health record data to derive predicted probabilities of receiving ECT. These probabilities were then applied as a quantitative trait in a genome-wide association study of 154,433 genotyped patients across four large biobanks. RESULTS Heritability estimates ranged from 2% to 4.2%, and significant genetic overlap was observed with cognition, attention deficit hyperactivity disorder, schizophrenia, alcohol and smoking traits, and body mass index. Two genome-wide significant loci were identified, both previously implicated in metabolic traits, suggesting shared biology and potential pharmacological implications. CONCLUSIONS This work provides support for the utility of estimation of disease probability for genomic investigation and provides insights into the genetic architecture and biology of TRD.
Collapse
Affiliation(s)
- JooEun Kang
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Victor M Castro
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Michael Ripperger
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Sanan Venkatesh
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - David Burstein
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Richard Karlsson Linnér
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Daniel B Rocha
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Yirui Hu
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Drew Wilimitis
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Theodore Morley
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Lide Han
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Rachel Youngjung Kim
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Yen-Chen Anne Feng
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Tian Ge
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Stephan Heckers
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Georgios Voloudakis
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Christopher Chabris
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Panos Roussos
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Thomas H McCoy
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Colin G Walsh
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Roy H Perlis
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| | - Douglas M Ruderfer
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng)
| |
Collapse
|
2
|
Lu Z, Ding L, Jiang X, Zhang S, Yan M, Yang G, Tian X, Wang Q. Single-nucleus RNA transcriptome profiling reveals murine adipose tissue endothelial cell proliferation gene networks involved in obesity development. Arch Biochem Biophys 2024; 757:110029. [PMID: 38729594 DOI: 10.1016/j.abb.2024.110029] [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: 01/10/2024] [Revised: 03/18/2024] [Accepted: 05/07/2024] [Indexed: 05/12/2024]
Abstract
Endothelial cells play an important role in the metabolism of adipose tissue (AT). This study aimed to analyze the changes that adipose tissue in AT endothelial cells undergo during the development of obesity, using single-nucleus RNA sequence (snRNA-seq). Mouse paraepididymal AT cells were subjected to snRNA-seq with the 10X Genomics platform. The cell types were then clustered using t-distributed stochastic neighbor embedding and unbiased computational informatics analyses. Protein-protein interactions network was established using the STRING database and visualized using Cytoscape. The dataset was subjected to differential gene enrichment analysis. In total, 21,333 cells acquired from 24 mouse paraepididymal AT samples were analyzed using snRNA-seq. This study identified 18 distinct clusters and annotated macrophages, fibroblasts, epithelial cells, T cells, endothelial cells, stem cells, neutrophil cells, and neutrophil cell types based on representative markers. Cluster 12 was defined as endothelial cells. The proportion of endothelial cells decreased with the development of obesity. Inflammatory factors, such as Vegfa and Prdm16 were upregulated in the medium obesity group but downregulated in the obesity group. Genes, such as Prox1, Erg, Flt4, Kdr, Flt1, and Pecam1 promoted the proliferation of AT endothelial cells and maintained the internal environment of AT. This study established a reference model and general framework for studying the mechanisms, biomarkers, and therapeutic targets of endothelial cell dysfunction-related diseases at the single-cell level.
Collapse
Affiliation(s)
- Zhimin Lu
- College of Sport and Health, Shandong Sport University, 250102, Jinan, China
| | - Ling Ding
- College of Sport and Health, Shandong Sport University, 250102, Jinan, China
| | - Xing Jiang
- College of Sport and Health, Shandong Sport University, 250102, Jinan, China
| | - Sen Zhang
- College of Sport and Health, Shandong Sport University, 250102, Jinan, China
| | - Min Yan
- College of Sport and Health, Shandong Sport University, 250102, Jinan, China
| | - Guangxin Yang
- College of Sport and Health, Shandong Sport University, 250102, Jinan, China
| | - Xuewen Tian
- College of Sport and Health, Shandong Sport University, 250102, Jinan, China.
| | - Qinglu Wang
- College of Sport and Health, Shandong Sport University, 250102, Jinan, China.
| |
Collapse
|
3
|
Littleton SH, Trang KB, Volpe CM, Cook K, DeBruyne N, Maguire JA, Weidekamp MA, Hodge KM, Boehm K, Lu S, Chesi A, Bradfield JP, Pippin JA, Anderson SA, Wells AD, Pahl MC, Grant SFA. Variant-to-function analysis of the childhood obesity chr12q13 locus implicates rs7132908 as a causal variant within the 3' UTR of FAIM2. CELL GENOMICS 2024; 4:100556. [PMID: 38697123 PMCID: PMC11099382 DOI: 10.1016/j.xgen.2024.100556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 03/21/2024] [Accepted: 04/08/2024] [Indexed: 05/04/2024]
Abstract
The ch12q13 locus is among the most significant childhood obesity loci identified in genome-wide association studies. This locus resides in a non-coding region within FAIM2; thus, the underlying causal variant(s) presumably influence disease susceptibility via cis-regulation. We implicated rs7132908 as a putative causal variant by leveraging our in-house 3D genomic data and public domain datasets. Using a luciferase reporter assay, we observed allele-specific cis-regulatory activity of the immediate region harboring rs7132908. We generated isogenic human embryonic stem cell lines homozygous for either rs7132908 allele to assess changes in gene expression and chromatin accessibility throughout a differentiation to hypothalamic neurons, a key cell type known to regulate feeding behavior. The rs7132908 obesity risk allele influenced expression of FAIM2 and other genes and decreased the proportion of neurons produced by differentiation. We have functionally validated rs7132908 as a causal obesity variant that temporally regulates nearby effector genes and influences neurodevelopment and survival.
Collapse
Affiliation(s)
- Sheridan H Littleton
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Khanh B Trang
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Christina M Volpe
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kieona Cook
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Nicole DeBruyne
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jean Ann Maguire
- Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Mary Ann Weidekamp
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kenyaita M Hodge
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Keith Boehm
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Sumei Lu
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jonathan P Bradfield
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Quantinuum Research LLC, San Diego, CA 92101, USA
| | - James A Pippin
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Stewart A Anderson
- Department of Child and Adolescent Psychiatry, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andrew D Wells
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew C Pahl
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
| |
Collapse
|
4
|
Roumi Z, Salimi Z, Mahmoudi Z, Mobarakeh KA, Ladaninezhad M, Zeinalabedini M, Keshavarz Mohammadian M, Shamsi‐Goushki A, Saeedirad Z, Bahar B, Khoshdooz S, Kalantari N, Azizi Tabesh G, Doaei S, Gholamalizadeh M. Efficacy of a Comprehensive Weight Reduction Intervention in Male Adolescents With Different FTO Genotypes. Endocrinol Diabetes Metab 2024; 7:e00483. [PMID: 38556726 PMCID: PMC10982462 DOI: 10.1002/edm2.483] [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: 12/20/2023] [Revised: 02/29/2024] [Accepted: 03/07/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND The FTO gene polymorphisms may influence the effects of lifestyle interventions on obesity. The present study aimed to assess the influence of the rs9930506 FTO gene polymorphism on the success of a comprehensive weight loss intervention in male adolescents with overweight and obesity. METHODS This study was carried out on 96 adolescent boys with overweight and obesity who were randomly assigned to the intervention (n = 53) and control (n = 43) groups. The blood samples of the participants were collected, and the FTO gene was genotyped for the rs9930506 polymorphism. A comprehensive lifestyle intervention including changes in diet and physical activity was performed for 8 weeks in the intervention group. RESULTS Following the lifestyle intervention, BMI and fat mass decreased significantly in the intervention group compared with the control group (both p < 0.05), while no change was found in weight, height or body muscle percentage between the groups. The participants in the intervention group with the AA/AG genotype and not in carriers of the GG genotype had a significantly higher reduction in BMI (-1.21 vs. 1.87 kg/m2, F = 4.07, p < 0.05) compared with the control group. CONCLUSION The intervention in individuals with the AA/AG genotype has been significantly effective in weight loss compared with the control group. The intervention had no association effect on anthropometric indices in adolescents with the GG genotype of the FTO rs9930506 polymorphism. TRIAL REGISTRATION Name of the registry: National Nutrition and Food Technology Research Institute; Trial registration number: IRCT2016020925699N2; Date of registration: 24/04/2016; URL of trial registry record: https://www.irct.ir/trial/21447.
Collapse
Affiliation(s)
- Zahra Roumi
- Department of Nutrition, Science and Research BranchIslamic Azad UniversityTehranIran
| | - Zahra Salimi
- Nutrition and Metabolic Diseases Research CenterAhvaz Jundishapur University of Medical SciencesAhvazIran
| | - Zahra Mahmoudi
- Department of Nutrition, Science and Research BranchIslamic Azad UniversityTehranIran
| | - Khadijeh Abbasi Mobarakeh
- Food Security Research Center and Department of Community Nutrition, School of Nutrition and Food ScienceIsfahan University of Medical SciencesIsfahanIran
| | - Maryam Ladaninezhad
- School of Nutritional Sciences and DieteticsTehran University of Medical SciencesTehranIran
| | - Mobina Zeinalabedini
- Department of Cellular and Molecular Nutrition, School of Nutritional Sciences and DieteticsTehran University of Medical SciencesTehranIran
| | | | - Ali Shamsi‐Goushki
- Department of Nutrition, School of MedicineMashhad University of Medical SciencesMashhadIran
| | - Zahra Saeedirad
- Department of Clinical Nutrition and DieteticsTehran University of Medical SciencesTehranIran
| | - Bojlul Bahar
- Nutrition Sciences and Applied Food Safety Studies, Research Centre for Global Development, School of Sport & Health SciencesUniversity of Central LancashirePrestonUK
| | - Sara Khoshdooz
- Faculty of MedicineGuilan University of Medical ScienceRashtIran
| | - Naser Kalantari
- Department of Community Nutrition, Faculty of Nutrition and Food TechnologyNational Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical SciencesTehranIran
| | - Ghasem Azizi Tabesh
- Genomic Research CenterShahid Beheshti University of Medical SciencesTehranIran
| | - Saeid Doaei
- Department of Community Nutrition, Faculty of Nutrition and Food TechnologyNational Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical SciencesTehranIran
| | | |
Collapse
|
5
|
Agrawal P, Kaur J, Singh J, Rasane P, Sharma K, Bhadariya V, Kaur S, Kumar V. Genetics, Nutrition, and Health: A New Frontier in Disease Prevention. JOURNAL OF THE AMERICAN NUTRITION ASSOCIATION 2024; 43:326-338. [PMID: 38015713 DOI: 10.1080/27697061.2023.2284997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 11/14/2023] [Indexed: 11/30/2023]
Abstract
The field of nutrition research has traditionally focused on the effects of macronutrients and micronutrients on the body. However, it has become evident that individuals have unique genetic makeups that influence their response to food. Nutritional genomics, which includes nutrigenetics and nutrigenomics, explores the interaction between an individual's genetic makeup, diet, and health outcomes. Nutrigenetics studies the impact of genetic variation on an individual's response to dietary nutrients, while nutrigenomics investigates how dietary components affect gene regulation and expression. These disciplines seek to understand the impact of diet on the genome, transcriptome, proteome, and metabolome. It provides insights into the mechanisms underlying the effect of diet on gene expression. Nutrients can cause the modification of genetic expression through epigenetic changes, such as DNA methylation and histone modifications. The aim of nutrigenomics is to create personalized diets based on the unique metabolic profile of an individual, gut microbiome, and genetic makeup to prevent diseases and promote health. Nutrigenomics has the potential to revolutionize the field of nutrition by combining the practicality of personalized nutrition with knowledge of genetic factors underlying health and disease. Thus, nutrigenomics offers a promising approach to improving health outcomes (in terms of disease prevention) through personalized nutrition strategies based on an individual's genetic and metabolic characteristics.
Collapse
Affiliation(s)
- Piyush Agrawal
- Department of Food Technology and Nutrition, School of Agriculture, Lovely Professional University, Phagwara, India
| | - Jaspreet Kaur
- Department of Food Technology and Nutrition, School of Agriculture, Lovely Professional University, Phagwara, India
| | - Jyoti Singh
- Department of Food Technology and Nutrition, School of Agriculture, Lovely Professional University, Phagwara, India
| | - Prasad Rasane
- Department of Food Technology and Nutrition, School of Agriculture, Lovely Professional University, Phagwara, India
| | - Kartik Sharma
- Faculty of Agro-Industry, Prince of Songkla University, Songkla, Thailand
| | - Vishesh Bhadariya
- School of Chemical Engineering, Oklahoma State University, Stillwater, Oklahoma, USA
| | - Sawinder Kaur
- Department of Food Technology and Nutrition, School of Agriculture, Lovely Professional University, Phagwara, India
| | - Vikas Kumar
- Department of Food Science and Technology, Punjab Agricultural University, Ludhiana, India
| |
Collapse
|
6
|
Chen J, Xiao WC, Zhao JJ, Heitkamp M, Chen DF, Shan R, Yang ZR, Liu Z. FTO genotype and body mass index reduction in childhood obesity interventions: A systematic review and meta-analysis. Obes Rev 2024; 25:e13715. [PMID: 38320834 DOI: 10.1111/obr.13715] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 10/27/2023] [Accepted: 01/07/2024] [Indexed: 04/18/2024]
Abstract
Numerous guidelines have called for personalized interventions to address childhood obesity. The role of fat mass and obesity-associated gene (FTO) in the risk of childhood obesity has been summarized. However, it remains unclear whether FTO could influence individual responses to obesity interventions, especially in children. To address this, we systematically reviewed 12,255 records across 10 databases/registers and included 13 lifestyle-based obesity interventions (3980 children with overweight/obesity) reporting changes in body mass index (BMI) Z-score, BMI, waist circumference, waist-to-hip ratio, and body fat percentage after interventions. These obesity-related outcomes were first compared between children carrying different FTO genotypes (rs9939609 or its proxy) and then synthesized by random-effect meta-analysis models. The results from single-group interventions showed no evidence of associations between FTO risk allele and changes in obesity-related outcomes after interventions (e.g., BMI Z-score: -0.01; 95% CI: -0.04, 0.01). The results from controlled trials showed that associations between the FTO risk allele and changes in obesity-related outcomes did not differ by intervention/control group. To conclude, the FTO risk allele might play a minor role in the response to obesity interventions among children. Future studies might pay more attention to the accumulation effect of multiple genes in the intervention process among children.
Collapse
Affiliation(s)
- Jing Chen
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing, China
| | - Wu-Cai Xiao
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing, China
| | - Jia-Jun Zhao
- Department of Nutrition, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Melanie Heitkamp
- Department of Prevention and Sports Medicine, University Hospital "Klinikum rechts der Isar," Technical University of Munich, Munich, Germany
| | - Da-Fang Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Rui Shan
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing, China
| | - Zhi-Rui Yang
- Department of Hematology, The Fifth Medical Center, The Chinese PLA General Hospital, Beijing, China
| | - Zheng Liu
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing, China
| |
Collapse
|
7
|
Bhattarai KR, Mobley RJ, Barnett KR, Ferguson DC, Hansen BS, Diedrich JD, Bergeron BP, Yoshimura S, Yang W, Crews KR, Manring CS, Jabbour E, Paietta E, Litzow MR, Kornblau SM, Stock W, Inaba H, Jeha S, Pui CH, Cheng C, Pruett-Miller SM, Relling MV, Yang JJ, Evans WE, Savic D. Investigation of inherited noncoding genetic variation impacting the pharmacogenomics of childhood acute lymphoblastic leukemia treatment. Nat Commun 2024; 15:3681. [PMID: 38693155 PMCID: PMC11063049 DOI: 10.1038/s41467-024-48124-4] [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: 02/10/2023] [Accepted: 04/18/2024] [Indexed: 05/03/2024] Open
Abstract
Defining genetic factors impacting chemotherapy failure can help to better predict response and identify drug resistance mechanisms. However, there is limited understanding of the contribution of inherited noncoding genetic variation on inter-individual differences in chemotherapy response in childhood acute lymphoblastic leukemia (ALL). Here we map inherited noncoding variants associated with treatment outcome and/or chemotherapeutic drug resistance to ALL cis-regulatory elements and investigate their gene regulatory potential and target gene connectivity using massively parallel reporter assays and three-dimensional chromatin looping assays, respectively. We identify 54 variants with transcriptional effects and high-confidence gene connectivity. Additionally, functional interrogation of the top variant, rs1247117, reveals changes in chromatin accessibility, PU.1 binding affinity and gene expression, and deletion of the genomic interval containing rs1247117 sensitizes cells to vincristine. Together, these data demonstrate that noncoding regulatory variants associated with diverse pharmacological traits harbor significant effects on allele-specific transcriptional activity and impact sensitivity to antileukemic agents.
Collapse
Affiliation(s)
- Kashi Raj Bhattarai
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Robert J Mobley
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Kelly R Barnett
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Daniel C Ferguson
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Baranda S Hansen
- Center for Advanced Genome Engineering, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Cell and Molecular Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Jonathan D Diedrich
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Brennan P Bergeron
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Satoshi Yoshimura
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Advanced Pediatric Medicine, Tohoku University School of Medicine, Tokyo, Japan
| | - Wenjian Yang
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Kristine R Crews
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Christopher S Manring
- Alliance Hematologic Malignancy Biorepository; Clara D. Bloomfield Center for Leukemia Outcomes Research, Columbus, OH, 43210, USA
| | - Elias Jabbour
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Mark R Litzow
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, 55905, USA
| | - Steven M Kornblau
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Wendy Stock
- Comprehensive Cancer Center, University of Chicago Medicine, Chicago, IL, USA
| | - Hiroto Inaba
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Sima Jeha
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Ching-Hon Pui
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Cheng Cheng
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Shondra M Pruett-Miller
- Center for Advanced Genome Engineering, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Cell and Molecular Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Mary V Relling
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Jun J Yang
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN, 38163, USA
| | - William E Evans
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Daniel Savic
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN, 38163, USA.
| |
Collapse
|
8
|
Goldberg LR, Baskin BM, Adla Y, Beierle JA, Kelliher JC, Yao EJ, Kirkpatrick SL, Reed ER, Jenkins DF, Luong AM, Luttik KP, Scotellaro JA, Drescher TA, Crotts SB, Yazdani N, Ferris MT, Johnson WE, Mulligan MK, Bryant CD. Atp1a2 and Kcnj9 are candidate genes underlying oxycodone behavioral sensitivity and withdrawal in C57BL/6 substrains. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.16.589731. [PMID: 38798314 PMCID: PMC11123399 DOI: 10.1101/2024.04.16.589731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Opioid use disorder is heritable, yet its genetic etiology is largely unknown. Analysis of addiction model traits in rodents (e.g., opioid behavioral sensitivity and withdrawal) can facilitate genetic and mechanistic discovery. C57BL/6J and C57BL/6NJ substrains have extremely limited genetic diversity, yet can show reliable phenotypic diversity which together, can facilitate gene discovery. The C57BL/6NJ substrain was less sensitive to oxycodone (OXY)-induced locomotor activity compared to the C57BL/6J substrain. Quantitative trait locus (QTL) mapping in an F2 cross identified a distal chromosome 1 QTL explaining 7-12% of the variance in OXY locomotor sensitivity and anxiety-like withdrawal in the elevated plus maze. We identified a second QTL for withdrawal on chromosome 5 near the candidate gene Gabra2 (alpha-2 subunit of GABA-A receptor) explaining 9% of the variance. Next, we generated recombinant lines from an F2 founder spanning the distal chromosome 1 locus (163-181 Mb), captured the QTL for OXY sensitivity and withdrawal, and fine-mapped a 2.45-Mb region (170.16-172.61 Mb). There were five striatal cis-eQTL transcripts in this region (Pcp4l1, Ncstn, Atp1a2, Kcnj9, Igsf9), two of which were confirmed at the protein level (KCNJ9, ATP1A2). Kcnj9, a.k.a., GIRK3, codes for a potassium channel that is a major effector of mu opioid receptor signaling. Atp1a2 codes for a subunit of a Na+/K+ ATPase enzyme that regulates neuronal excitability and shows adaptations following chronic opioid administration. To summarize, we identified genetic sources of opioid behavioral differences in C57BL/6 substrains, two of the most widely and often interchangeably used substrains in opioid addiction research.
Collapse
|
9
|
Gedik H, Peterson R, Chatzinakos C, Dozmorov MG, Vladimirov V, Riley BP, Bacanu SA. A novel multi-omics mendelian randomization method for gene set enrichment and its application to psychiatric disorders. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.14.24305811. [PMID: 38699366 PMCID: PMC11065030 DOI: 10.1101/2024.04.14.24305811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Genome-wide association studies (GWAS) of psychiatric disorders (PD) yield numerous loci with significant signals, but often do not implicate specific genes. Because GWAS risk loci are enriched in expression/protein/methylation quantitative loci (e/p/mQTL, hereafter xQTL), transcriptome/proteome/methylome-wide association studies (T/P/MWAS, hereafter XWAS) that integrate xQTL and GWAS information, can link GWAS signals to effects on specific genes. To further increase detection power, gene signals are aggregated within relevant gene sets (GS) by performing gene set enrichment (GSE) analyses. Often GSE methods test for enrichment of "signal" genes in curated GS while overlooking their linkage disequilibrium (LD) structure, allowing for the possibility of increased false positive rates. Moreover, no GSE tool uses xQTL information to perform mendelian randomization (MR) analysis. To make causal inference on association between PD and GS, we develop a novel MR GSE (MR-GSE) procedure. First, we generate a "synthetic" GWAS for each MSigDB GS by aggregating summary statistics for x-level (mRNA, protein or DNA methylation (DNAm) levels) from the largest xQTL studies available) of genes in a GS. Second, we use synthetic GS GWAS as exposure in a generalized summary-data-based-MR analysis of complex trait outcomes. We applied MR-GSE to GWAS of nine important PD. When applied to the underpowered opioid use disorder GWAS, none of the four analyses yielded any signals, which suggests a good control of false positive rates. For other PD, MR-GSE greatly increased the detection of GO terms signals (2,594) when compared to the commonly used (non-MR) GSE method (286). Some of the findings might be easier to adapt for treatment, e.g., our analyses suggest modest positive effects for supplementation with certain vitamins and/or omega-3 for schizophrenia, bipolar and major depression disorder patients. Similar to other MR methods, when applying MR-GSE researchers should be mindful of the confounding effects of horizontal pleiotropy on statistical inference.
Collapse
|
10
|
Choi E, Song J, Lee Y, Jeong Y, Jang W. Prioritizing susceptibility genes for the prognosis of male-pattern baldness with transcriptome-wide association study. Hum Genomics 2024; 18:34. [PMID: 38566255 PMCID: PMC10985920 DOI: 10.1186/s40246-024-00591-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 02/27/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Male-pattern baldness (MPB) is the most common cause of hair loss in men. It can be categorized into three types: type 2 (T2), type 3 (T3), and type 4 (T4), with type 1 (T1) being considered normal. Although various MPB-associated genetic variants have been suggested, a comprehensive study for linking these variants to gene expression regulation has not been performed to the best of our knowledge. RESULTS In this study, we prioritized MPB-related tissue panels using tissue-specific enrichment analysis and utilized single-tissue panels from genotype-tissue expression version 8, as well as cross-tissue panels from context-specific genetics. Through a transcriptome-wide association study and colocalization analysis, we identified 52, 75, and 144 MPB associations for T2, T3, and T4, respectively. To assess the causality of MPB genes, we performed a conditional and joint analysis, which revealed 10, 11, and 54 putative causality genes for T2, T3, and T4, respectively. Finally, we conducted drug repositioning and identified potential drug candidates that are connected to MPB-associated genes. CONCLUSIONS Overall, through an integrative analysis of gene expression and genotype data, we have identified robust MPB susceptibility genes that may help uncover the underlying molecular mechanisms and the novel drug candidates that may alleviate MPB.
Collapse
Affiliation(s)
- Eunyoung Choi
- Department of Life Sciences, Dongguk University, Seoul, 04620, Republic of Korea
| | - Jaeseung Song
- Department of Life Sciences, Dongguk University, Seoul, 04620, Republic of Korea
| | - Yubin Lee
- Department of Life Sciences, Dongguk University, Seoul, 04620, Republic of Korea
| | - Yeonbin Jeong
- Department of Life Sciences, Dongguk University, Seoul, 04620, Republic of Korea
| | - Wonhee Jang
- Department of Life Sciences, Dongguk University, Seoul, 04620, Republic of Korea.
| |
Collapse
|
11
|
Chen Z, Snetkova V, Bower G, Jacinto S, Clock B, Dizehchi A, Barozzi I, Mannion BJ, Alcaina-Caro A, Lopez-Rios J, Dickel DE, Visel A, Pennacchio LA, Kvon EZ. Increased enhancer-promoter interactions during developmental enhancer activation in mammals. Nat Genet 2024; 56:675-685. [PMID: 38509385 DOI: 10.1038/s41588-024-01681-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 02/06/2024] [Indexed: 03/22/2024]
Abstract
Remote enhancers are thought to interact with their target promoters via physical proximity, yet the importance of this proximity for enhancer function remains unclear. Here we investigate the three-dimensional (3D) conformation of enhancers during mammalian development by generating high-resolution tissue-resolved contact maps for nearly a thousand enhancers with characterized in vivo activities in ten murine embryonic tissues. Sixty-one percent of developmental enhancers bypass their neighboring genes, which are often marked by promoter CpG methylation. The majority of enhancers display tissue-specific 3D conformations, and both enhancer-promoter and enhancer-enhancer interactions are moderately but consistently increased upon enhancer activation in vivo. Less than 14% of enhancer-promoter interactions form stably across tissues; however, these invariant interactions form in the absence of the enhancer and are likely mediated by adjacent CTCF binding. Our results highlight the general importance of enhancer-promoter physical proximity for developmental gene activation in mammals.
Collapse
Affiliation(s)
- Zhuoxin Chen
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA
| | - Valentina Snetkova
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Grace Bower
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA
| | - Sandra Jacinto
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA
| | - Benjamin Clock
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA
| | - Atrin Dizehchi
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA
| | - Iros Barozzi
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Center for Cancer Research, Medical University of Vienna, Vienna, Austria
| | - Brandon J Mannion
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Comparative Biochemistry Program, University of California, Berkeley, CA, USA
| | - Ana Alcaina-Caro
- Centro Andaluz de Biología del Desarrollo, CSIC, Universidad Pablo de Olavide, Junta de Andalucía, Seville, Spain
| | - Javier Lopez-Rios
- Centro Andaluz de Biología del Desarrollo, CSIC, Universidad Pablo de Olavide, Junta de Andalucía, Seville, Spain
- School of Health Sciences, Universidad Loyola Andalucía, Seville, Spain
| | - Diane E Dickel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Octant, Inc, Emeryville, CA, USA
| | - Axel Visel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- U.S. Department of Energy Joint Genome Institute, Walnut Creek, CA, USA
- School of Natural Sciences, University of California, Merced, CA, USA
| | - Len A Pennacchio
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Comparative Biochemistry Program, University of California, Berkeley, CA, USA
- U.S. Department of Energy Joint Genome Institute, Walnut Creek, CA, USA
| | - Evgeny Z Kvon
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA.
| |
Collapse
|
12
|
Sakaue S, Weinand K, Isaac S, Dey KK, Jagadeesh K, Kanai M, Watts GFM, Zhu Z, Brenner MB, McDavid A, Donlin LT, Wei K, Price AL, Raychaudhuri S. Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles. Nat Genet 2024; 56:615-626. [PMID: 38594305 DOI: 10.1038/s41588-024-01682-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 02/07/2024] [Indexed: 04/11/2024]
Abstract
Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining noncoding variant function.
Collapse
Affiliation(s)
- Saori Sakaue
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kathryn Weinand
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Shakson Isaac
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Kushal K Dey
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Karthik Jagadeesh
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Masahiro Kanai
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Gerald F M Watts
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Zhu Zhu
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael B Brenner
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrew McDavid
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA
| | - Laura T Donlin
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Kevin Wei
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alkes L Price
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
13
|
Serra F, Nieto-Aliseda A, Fanlo-Escudero L, Rovirosa L, Cabrera-Pasadas M, Lazarenkov A, Urmeneta B, Alcalde-Merino A, Nola EM, Okorokov AL, Fraser P, Graupera M, Castillo SD, Sardina JL, Valencia A, Javierre BM. p53 rapidly restructures 3D chromatin organization to trigger a transcriptional response. Nat Commun 2024; 15:2821. [PMID: 38561401 PMCID: PMC10984980 DOI: 10.1038/s41467-024-46666-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
Activation of the p53 tumor suppressor triggers a transcriptional program to control cellular response to stress. However, the molecular mechanisms by which p53 controls gene transcription are not completely understood. Here, we uncover the critical role of spatio-temporal genome architecture in this process. We demonstrate that p53 drives direct and indirect changes in genome compartments, topologically associating domains, and DNA loops prior to one hour of its activation, which escort the p53 transcriptional program. Focusing on p53-bound enhancers, we report 340 genes directly regulated by p53 over a median distance of 116 kb, with 74% of these genes not previously identified. Finally, we showcase that p53 controls transcription of distal genes through newly formed and pre-existing enhancer-promoter loops in a cohesin dependent manner. Collectively, our findings demonstrate a previously unappreciated architectural role of p53 as regulator at distinct topological layers and provide a reliable set of new p53 direct target genes that may help designs of cancer therapies.
Collapse
Affiliation(s)
- François Serra
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | | | | | | | - Mónica Cabrera-Pasadas
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
- Barcelona Supercomputing Center, Barcelona, Spain
| | | | - Blanca Urmeneta
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | | | - Emanuele M Nola
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | - Andrei L Okorokov
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Peter Fraser
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Mariona Graupera
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
- CIBERONC, Instituto de Salud Carlos III, Madrid, Spain
| | | | - Jose L Sardina
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | - Alfonso Valencia
- Barcelona Supercomputing Center, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Biola M Javierre
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain.
- Institute for Health Science Research Germans Trias i Pujol, Barcelona, Spain.
| |
Collapse
|
14
|
Zhang E, Sun Q, Zhang C, Ma H, Zhang J, Ding Y, Wang G, Jin C, Jin C, Fu Y, Yan C, Zhu M, Wang C, Dai J, Jin G, Hu Z, Shen H, Ma H. Comprehensive functional interrogation of susceptibility loci in GWASs identified KIAA0391 as a novel oncogenic driver via regulating pyroptosis in NSCLC. Cancer Lett 2024; 585:216646. [PMID: 38262497 DOI: 10.1016/j.canlet.2024.216646] [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: 09/13/2023] [Revised: 11/23/2023] [Accepted: 01/05/2024] [Indexed: 01/25/2024]
Abstract
Approximately 51 non-small-cell lung cancer (NSCLC) risk loci have been identified by genome-wide association studies (GWASs). We conducted a high throughput RNA-interference (RNAi) screening to identify the candidate causal genes in NSCLC risk loci. KIAA0391 at 14q13.1 had the highest score and could promote proliferation and metastasis of NSCLC in vitro and in vivo. We next prioritized rs3783313 as a causal variant at 14q13.1, by integrating a large-scale population study consisting of 27,120 lung cancer cases and 27,355 controls, functional annotation, and expression quantitative trait locus (eQTL) analysis. Then we found that rs3783313 could facilitate a promoter-enhancer interaction to upregulate KIAA0391 expression by affecting the affinity of transcription factor NFYA. Mechanistically, KIAA0391 knockdown dramatically influenced pyroptosis-related pathways and increased the expression of CASP1. And KIAA0391 transcriptionally repressed CASP1 by binding to SMAD2 and induced an anti-pyroptosis phenotype, promoting tumorigenesis of NSCLC, which provides new insights and potential target for NSCLC.
Collapse
Affiliation(s)
- Erbao Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Qi Sun
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Chang Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China; The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou Second People's Hospital, Changzhou Medical Center, Nanjing Medical University, Nanjing 211166, China
| | - Huimin Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Jing Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Yue Ding
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Guoqing Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Chen Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Chenying Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Yating Fu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Caiwang Yan
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Cheng Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China; Research Unit of Prospective Cohort of Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100142, China.
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China; Research Unit of Prospective Cohort of Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100142, China.
| |
Collapse
|
15
|
Archana CA, Sekar YS, Suresh KP, Subramaniam S, Sagar N, Rani S, Anandakumar J, Pandey RK, Barman NN, Patil SS. Investigating the Influence of ANTXR2 Gene Mutations on Protective Antigen Binding for Heightened Anthrax Resistance. Genes (Basel) 2024; 15:426. [PMID: 38674361 PMCID: PMC11049084 DOI: 10.3390/genes15040426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 03/14/2024] [Accepted: 03/18/2024] [Indexed: 04/28/2024] Open
Abstract
Bacillus anthracis is the bacterium responsible for causing the zoonotic disease called anthrax. The disease presents itself in different forms like gastrointestinal, inhalation, and cutaneous. Bacterial spores are tremendously adaptable, can persist for extended periods and occasionally endanger human health. The Anthrax Toxin Receptor-2 (ANTXR2) gene acts as membrane receptor and facilitates the entry of the anthrax toxin into host cells. Additionally, mutations in the ANTXR2 gene have been linked to various autoimmune diseases, including Hyaline Fibromatosis Syndrome (HFS), Ankylosing Spondylitis (AS), Juvenile Hyaline Fibromatosis (JHF), and Infantile Systemic Hyalinosis (ISH). This study delves into the genetic landscape of ANTXR2, aiming to comprehend its associations with diverse disorders, elucidate the impacts of its mutations, and pinpoint minimal non-pathogenic mutations capable of reducing the binding affinity of the ANTXR2 gene with the protective antigen. Recognizing the pivotal role of single-nucleotide polymorphisms (SNPs) in shaping genetic diversity, we conducted computational analyses to discern highly deleterious and tolerated non-synonymous SNPs (nsSNPs) in the ANTXR2 gene. The Mutpred2 server determined that the Arg465Trp alteration in the ANTXR2 gene leads to altered DNA binding (p = 0.22) with a probability of a deleterious mutation of 0.808; notably, among the identified deleterious SNPs, rs368288611 (Arg465Trp) stands out due to its significant impact on altering the DNA-binding ability of ANTXR2. We propose these SNPs as potential candidates for hypertension linked to the ANTXR2 gene, which is implicated in blood pressure regulation. Noteworthy among the tolerated substitutions is rs200536829 (Ala33Ser), recognized as less pathogenic; this highlights its potential as a valuable biomarker, potentially reducing side effects on the host while also reducing binding with the protective antigen protein. Investigating these SNPs holds the potential to correlate with several autoimmune disorders and mitigate the impact of anthrax disease in humans.
Collapse
Affiliation(s)
- Chamalapura Ashwathama Archana
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Bengaluru 560064, India; (C.A.A.); (Y.S.S.); (N.S.); (S.R.); (J.A.); (S.S.P.)
| | - Yamini Sri Sekar
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Bengaluru 560064, India; (C.A.A.); (Y.S.S.); (N.S.); (S.R.); (J.A.); (S.S.P.)
| | - Kuralayanapalya Puttahonnappa Suresh
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Bengaluru 560064, India; (C.A.A.); (Y.S.S.); (N.S.); (S.R.); (J.A.); (S.S.P.)
| | | | - Ningegowda Sagar
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Bengaluru 560064, India; (C.A.A.); (Y.S.S.); (N.S.); (S.R.); (J.A.); (S.S.P.)
| | - Swati Rani
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Bengaluru 560064, India; (C.A.A.); (Y.S.S.); (N.S.); (S.R.); (J.A.); (S.S.P.)
| | - Jayashree Anandakumar
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Bengaluru 560064, India; (C.A.A.); (Y.S.S.); (N.S.); (S.R.); (J.A.); (S.S.P.)
| | - Rajan Kumar Pandey
- Department of Medical Biochemistry and Biophysics, Karolinska Institute, 17177 Solna, Sweden;
| | - Nagendra Nath Barman
- College of Veterinary Science, Assam Agricultural University (AAU), Guwahati 781022, India;
| | - Sharanagouda S. Patil
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Bengaluru 560064, India; (C.A.A.); (Y.S.S.); (N.S.); (S.R.); (J.A.); (S.S.P.)
| |
Collapse
|
16
|
Koo HJ, Pan W. Are trait-associated genes clustered together in a gene network? Genet Epidemiol 2024. [PMID: 38472164 DOI: 10.1002/gepi.22557] [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: 10/11/2023] [Revised: 01/25/2024] [Accepted: 02/23/2024] [Indexed: 03/14/2024]
Abstract
Genome-wide association studies (GWAS) have provided an abundance of information about the genetic variants and their loci that are associated to complex traits and diseases. However, due to linkage disequilibrium (LD) and noncoding regions of loci, it remains a challenge to pinpoint the causal genes. Gene network-based approaches, paired with network diffusion methods, have been proposed to prioritize causal genes and to boost statistical power in GWAS based on the assumption that trait-associated genes are clustered in a gene network. Due to the difficulty in mapping trait-associated variants to genes in GWAS, this assumption has never been directly or rigorously tested empirically. On the other hand, whole exome sequencing (WES) data focuses on the protein-coding regions, directly identifying trait-associated genes. In this study, we tested the assumption by leveraging the recently available exome-based association statistics from the UK Biobank WES data along with two types of networks. We found that almost all trait-associated genes were significantly more proximal to each other than randomly selected genes within both networks. These results support the assumption that trait-associated genes are clustered in gene networks, which can be further leveraged to boost the power of GWAS such as by introducing less stringent p value thresholds.
Collapse
Affiliation(s)
- Hyun Jung Koo
- School of Statistics, University of Minnesota, Minneapolis, Minnesota, USA
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Wei Pan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| |
Collapse
|
17
|
Pahl MC, Liu L, Pippin JA, Wagley Y, Boehm K, Hankenson KD, Wells AD, Yang W, Grant SFA. Variant to gene mapping for carpal tunnel syndrome risk loci implicates skeletal muscle regulatory elements. EBioMedicine 2024; 101:105038. [PMID: 38417377 PMCID: PMC10909706 DOI: 10.1016/j.ebiom.2024.105038] [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: 07/25/2023] [Revised: 02/13/2024] [Accepted: 02/14/2024] [Indexed: 03/01/2024] Open
Abstract
BACKGROUND Carpal tunnel syndrome (CTS) is a common disorder caused by compression of the median nerve in the wrist, resulting in pain and numbness throughout the hand and forearm. While multiple behavioural and physiological factors influence CTS risk, a growing body of evidence supports a strong genetic contribution. Recent genome-wide association study (GWAS) efforts have reported 53 independent signals associated with CTS. While GWAS can identify genetic loci conferring risk, it does not determine which cell types drive the genetic aetiology of the trait, which variants are "causal" at a given signal, and which effector genes correspond to these non-coding variants. These obstacles limit interpretation of potential disease mechanisms. METHODS We analysed CTS GWAS findings in the context of chromatin conformation between gene promoters and accessible chromatin regions across cellular models of bone, skeletal muscle, adipocytes and neurons. We identified proxy variants in high LD with the lead CTS sentinel SNPs residing in promoter connected open chromatin in the skeletal muscle and bone contexts. FINDINGS We detected significant enrichment for heritability in skeletal muscle myotubes, as well as a weaker correlation in human mesenchymal stem cell-derived osteoblasts. In myotubes, our approach implicated 117 genes contacting 60 proxy variants corresponding to 20 of the 53 GWAS signals. In the osteoblast context we implicated 30 genes contacting 24 proxy variants coinciding with 12 signals, of which 19 genes shared. We subsequently prioritized BZW2 as a candidate effector gene in CTS and implicated it as novel gene that perturbs myocyte differentiation in vitro. INTERPRETATION Taken together our results suggest that the CTS genetic component influences the size, integrity, and organization of multiple tissues surrounding the carpal tunnel, in particular muscle and bone, to predispose the nerve to being compressed in this disease setting. FUNDING This work was supported by NIH Grant UM1 DK126194 (SFAG and WY), R01AG072705 (SFAG & KDH) and the Center for Spatial and Functional Genomics at CHOP (SFAG & ADW). SFAG is supported by the Daniel B. Burke Endowed Chair for Diabetes Research. WY is supported by the Perelman School of Medicine of the University of Pennsylvania.
Collapse
Affiliation(s)
- Matthew C Pahl
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Lin Liu
- Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA; Department of Cell and Developmental Biology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA; Institute for Diabetes, Obesity & Metabolism, Perelman School of Medicine at the University of Pennsylvania, Philadelphia PA19104, USA
| | - James A Pippin
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Yadav Wagley
- Orthopaedic Research Laboratories, Department of Orthopaedic Surgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Keith Boehm
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kurt D Hankenson
- Orthopaedic Research Laboratories, Department of Orthopaedic Surgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Andrew D Wells
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, 3615 Civic Center Boulevard, Philadelphia, PA, USA; Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, 3615 Civic Center Boulevard, Philadelphia, PA, USA
| | - Wenli Yang
- Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA; Department of Cell and Developmental Biology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA; Institute for Diabetes, Obesity & Metabolism, Perelman School of Medicine at the University of Pennsylvania, Philadelphia PA19104, USA.
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| |
Collapse
|
18
|
Lopez-Yus M, Hörndler C, Borlan S, Bernal-Monterde V, Arbones-Mainar JM. Unraveling Adipose Tissue Dysfunction: Molecular Mechanisms, Novel Biomarkers, and Therapeutic Targets for Liver Fat Deposition. Cells 2024; 13:380. [PMID: 38474344 DOI: 10.3390/cells13050380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 02/14/2024] [Accepted: 02/20/2024] [Indexed: 03/14/2024] Open
Abstract
Adipose tissue (AT), once considered a mere fat storage organ, is now recognized as a dynamic and complex entity crucial for regulating human physiology, including metabolic processes, energy balance, and immune responses. It comprises mainly two types: white adipose tissue (WAT) for energy storage and brown adipose tissue (BAT) for thermogenesis, with beige adipocytes demonstrating the plasticity of these cells. WAT, beyond lipid storage, is involved in various metabolic activities, notably lipogenesis and lipolysis, critical for maintaining energy homeostasis. It also functions as an endocrine organ, secreting adipokines that influence metabolic, inflammatory, and immune processes. However, dysfunction in WAT, especially related to obesity, leads to metabolic disturbances, including the inability to properly store excess lipids, resulting in ectopic fat deposition in organs like the liver, contributing to non-alcoholic fatty liver disease (NAFLD). This narrative review delves into the multifaceted roles of WAT, its composition, metabolic functions, and the pathophysiology of WAT dysfunction. It also explores diagnostic approaches for adipose-related disorders, emphasizing the importance of accurately assessing AT distribution and understanding the complex relationships between fat compartments and metabolic health. Furthermore, it discusses various therapeutic strategies, including innovative therapeutics like adipose-derived mesenchymal stem cells (ADMSCs)-based treatments and gene therapy, highlighting the potential of precision medicine in targeting obesity and its associated complications.
Collapse
Affiliation(s)
- Marta Lopez-Yus
- Adipocyte and Fat Biology Laboratory (AdipoFat), Translational Research Unit, University Hospital Miguel Servet, 50009 Zaragoza, Spain
- Instituto Aragones de Ciencias de la Salud (IACS), 50009 Zaragoza, Spain
- Instituto de Investigación Sanitaria (IIS) Aragon, 50009 Zaragoza, Spain
| | - Carlos Hörndler
- Instituto de Investigación Sanitaria (IIS) Aragon, 50009 Zaragoza, Spain
- Pathology Department, Miguel Servet University Hospital, 50009 Zaragoza, Spain
| | - Sofia Borlan
- General and Digestive Surgery Department, Miguel Servet University Hospital, 50009 Zaragoza, Spain
| | - Vanesa Bernal-Monterde
- Adipocyte and Fat Biology Laboratory (AdipoFat), Translational Research Unit, University Hospital Miguel Servet, 50009 Zaragoza, Spain
- Instituto Aragones de Ciencias de la Salud (IACS), 50009 Zaragoza, Spain
- Gastroenterology Department, Miguel Servet University Hospital, 50009 Zaragoza, Spain
| | - Jose M Arbones-Mainar
- Adipocyte and Fat Biology Laboratory (AdipoFat), Translational Research Unit, University Hospital Miguel Servet, 50009 Zaragoza, Spain
- Instituto Aragones de Ciencias de la Salud (IACS), 50009 Zaragoza, Spain
- Instituto de Investigación Sanitaria (IIS) Aragon, 50009 Zaragoza, Spain
- CIBER Fisiopatología Obesidad y Nutrición (CIBERObn), Instituto Salud Carlos III, 28029 Madrid, Spain
| |
Collapse
|
19
|
Farris KM, Senior AM, Sobreira DR, Mitchell RM, Weber ZT, Ingerslev LR, Barrès R, Simpson SJ, Crean AJ, Nobrega MA. Dietary macronutrient composition impacts gene regulation in adipose tissue. Commun Biol 2024; 7:194. [PMID: 38365885 PMCID: PMC10873408 DOI: 10.1038/s42003-024-05876-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 01/30/2024] [Indexed: 02/18/2024] Open
Abstract
Diet is a key lifestyle component that influences metabolic health through several factors, including total energy intake and macronutrient composition. While the impact of caloric intake on gene expression and physiological phenomena in various tissues is well described, the influence of dietary macronutrient composition on these parameters is less well studied. Here, we use the Nutritional Geometry framework to investigate the role of macronutrient composition on metabolic function and gene regulation in adipose tissue. Using ten isocaloric diets that vary systematically in their proportion of energy from fat, protein, and carbohydrates, we find that gene expression and splicing are highly responsive to macronutrient composition, with distinct sets of genes regulated by different macronutrient interactions. Specifically, the expression of many genes associated with Bardet-Biedl syndrome is responsive to dietary fat content. Splicing and expression changes occur in largely separate gene sets, highlighting distinct mechanisms by which dietary composition influences the transcriptome and emphasizing the importance of considering splicing changes to more fully capture the gene regulation response to environmental changes such as diet. Our study provides insight into the gene regulation plasticity of adipose tissue in response to macronutrient composition, beyond the already well-characterized response to caloric intake.
Collapse
Affiliation(s)
- Kathryn M Farris
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA.
| | - Alistair M Senior
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia
- School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, 2006, Australia
| | - Débora R Sobreira
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Robert M Mitchell
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Zachary T Weber
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Lars R Ingerslev
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, DK-2200, Copenhagen, Denmark
| | - Romain Barrès
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, DK-2200, Copenhagen, Denmark.
- Institut de Pharmacologie Moléculaire et Cellulaire, Université Côte d'Azur & Centre National pour la Recherche Scientifique (CNRS), Valbonne, 06560, France.
| | - Stephen J Simpson
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia.
- School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, 2006, Australia.
| | - Angela J Crean
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia.
| | - Marcelo A Nobrega
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA.
| |
Collapse
|
20
|
Trang KB, Pahl MC, Pippin JA, Su C, Littleton SH, Sharma P, Kulkarni NN, Ghanem LR, Terry NA, O’Brien JM, Wagley Y, Hankenson KD, Jermusyk A, Hoskins JW, Amundadottir LT, Xu M, Brown KM, Anderson SA, Yang W, Titchenell PM, Seale P, Cook L, Levings MK, Zemel BS, Chesi A, Wells AD, Grant SF. 3D genomic features across >50 diverse cell types reveal insights into the genomic architecture of childhood obesity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.08.30.23294092. [PMID: 37693606 PMCID: PMC10491377 DOI: 10.1101/2023.08.30.23294092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
The prevalence of childhood obesity is increasing worldwide, along with the associated common comorbidities of type 2 diabetes and cardiovascular disease in later life. Motivated by evidence for a strong genetic component, our prior genome-wide association study (GWAS) efforts for childhood obesity revealed 19 independent signals for the trait; however, the mechanism of action of these loci remains to be elucidated. To molecularly characterize these childhood obesity loci we sought to determine the underlying causal variants and the corresponding effector genes within diverse cellular contexts. Integrating childhood obesity GWAS summary statistics with our existing 3D genomic datasets for 57 human cell types, consisting of high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq, and RNA-seq, we applied stratified LD score regression and calculated the proportion of genome-wide SNP heritability attributable to cell type-specific features, revealing pancreatic alpha cell enrichment as the most statistically significant. Subsequent chromatin contact-based fine-mapping was carried out for genome-wide significant childhood obesity loci and their linkage disequilibrium proxies to implicate effector genes, yielded the most abundant number of candidate variants and target genes at the BDNF, ADCY3, TMEM18 and FTO loci in skeletal muscle myotubes and the pancreatic beta-cell line, EndoC-BH1. One novel implicated effector gene, ALKAL2 - an inflammation-responsive gene in nerve nociceptors - was observed at the key TMEM18 locus across multiple immune cell types. Interestingly, this observation was also supported through colocalization analysis using expression quantitative trait loci (eQTL) derived from the Genotype-Tissue Expression (GTEx) dataset, supporting an inflammatory and neurologic component to the pathogenesis of childhood obesity. Our comprehensive appraisal of 3D genomic datasets generated in a myriad of different cell types provides genomic insights into pediatric obesity pathogenesis.
Collapse
Affiliation(s)
- Khanh B. Trang
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Matthew C. Pahl
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - James A. Pippin
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Chun Su
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sheridan H. Littleton
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Prabhat Sharma
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nikhil N. Kulkarni
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Louis R. Ghanem
- Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, PA, USA
| | - Natalie A. Terry
- Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, PA, USA
| | - Joan M. O’Brien
- Scheie Eye Institute, Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, PA, USA
- Penn Medicine Center for Ophthalmic Genetics in Complex Disease
| | - Yadav Wagley
- Department of Orthopedic Surgery University of Michigan Medical School Ann Arbor, MI, USA
| | - Kurt D. Hankenson
- Department of Orthopedic Surgery University of Michigan Medical School Ann Arbor, MI, USA
| | - Ashley Jermusyk
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jason W. Hoskins
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Laufey T. Amundadottir
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Mai Xu
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Kevin M Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Stewart A. Anderson
- Department of Child and Adolescent Psychiatry, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Wenli Yang
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul M. Titchenell
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Patrick Seale
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura Cook
- Department of Microbiology and Immunology, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
- Department of Critical Care, Melbourne Medical School, University of Melbourne, Melbourne, VIC, Australia
- Division of Infectious Diseases, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Megan K. Levings
- Department of Surgery, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Babette S. Zemel
- Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew D. Wells
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division Endocrinology and Diabetes, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| |
Collapse
|
21
|
Cui Y, Xiao Q, Wang Z, Zhang Q, Liu Y, Hao W, Jiang J, Meng Q, Wei X. 1,2-bis(2,4,6-tribromophenoxy) ethane, a novel brominated flame retardant, disrupts intestinal barrier function via the IRX3/NOS2 axis in rat small intestine. JOURNAL OF HAZARDOUS MATERIALS 2024; 461:132597. [PMID: 37804762 DOI: 10.1016/j.jhazmat.2023.132597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 09/15/2023] [Accepted: 09/19/2023] [Indexed: 10/09/2023]
Abstract
Novel brominated flame retardants are widely used in electronics, textiles, furniture, and other products; they can enter the human body through ingestion and respiration and cause harm to the human body, and have been proven to have potential biological toxicity and accumulation effects. 1,2-bis(2,4,6-tribromophenoxy) ethane (BTBPE) is a widely used novel brominated flame retardant; however, there is a lack of research on its mechanism of toxicity, particularly that of intestinal toxicity. Currently, studies on the functionality of iroquois homeobox 3 (IRX3) are extremely limited. In our study, BTBPE was administered to Sprague-Dawley (SD) rats and rat small intestinal crypt epithelial cells (IEC6 cells) in vivo and in vitro, respectively, and hematoxylin and eosin (HE), immunohistochemical, Alcian blue-periodic acid-Schiff (AB-PAS), CCK8, acridine orange/ethidium bromide (AO/EB), fluorescent probes, qPCR, western blotting, and immunofluorescence analyses were performed. To explore the damage mechanism of BTBPE, we used siRNA to silence IRX3 and iNOs-IN-1 (yeast extract-peptone-wheat; YPW) to inhibit nitric oxide synthase 2 (NOS2). The results showed that BTBPE exposure caused inflammation and necroptosis in the jejunum and ileum, as well as destruction of the tight junctions and mucus layer. Moreover, BTBPE activated the IRX3/NOS2 axis both in vivo and in vitro. Silencing IRX3 or inhibiting NOS2 inhibits necroptosis and restores tight junctions in IEC6 cells. In conclusion, our study found that in the jejunum, ileum, and IEC6 cells, BTBPE exposure caused necroptosis and tight junction destruction by activating the IRX3/NOS2 axis. Blocking the IRX3/NOS2 axis can effectively inhibit necroptosis and restore tight junction. In addition, BTBPE exposure caused inflammation and loss of the mucous layer in the jejunum and ileum. Our study is the first to explore the mechanism of intestinal damage caused by BTBPE exposure and to discover new biological functions regulated by the IRX3/NOS2 axis, providing new research directions for necroptosis and tight junctions.
Collapse
Affiliation(s)
- Yuan Cui
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, PR China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, PR China
| | - Qianqian Xiao
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, PR China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, PR China
| | - Zhenyu Wang
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, PR China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, PR China
| | - Qiong Zhang
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, PR China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, PR China
| | - Yuetong Liu
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, PR China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, PR China
| | - Weidong Hao
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, PR China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, PR China
| | - Jianjun Jiang
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, PR China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, PR China
| | - Qinghe Meng
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, PR China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, PR China
| | - Xuetao Wei
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, PR China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, PR China.
| |
Collapse
|
22
|
Liu S, Song S, Wang S, Cai T, Qin L, Wang X, Zhu G, Wang H, Yang W, Fang C, Wei Y, Zhou F, Yu Y, Lin S, Peng S, Li L. Hypothalamic FTO promotes high-fat diet-induced leptin resistance in mice through increasing CX3CL1 expression. J Nutr Biochem 2024; 123:109512. [PMID: 37907171 DOI: 10.1016/j.jnutbio.2023.109512] [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: 06/26/2023] [Revised: 10/25/2023] [Accepted: 10/27/2023] [Indexed: 11/02/2023]
Abstract
Long-term consumption of a high-fat diet (HFD) disrupts energy homeostasis and leads to weight gain. The fat mass and obesity-associated (FTO) gene has been consistently identified to be associated with HFD-induced obesity. The hypothalamus is crucial for regulating energy balance, and HFD-induced hypothalamic leptin resistance contributes to obesity. FTO, an N6-methyladenosine (m6A) RNA methylation regulator, may be a key mediator of leptin resistance. However, the exact mechanisms remain unclear. Therefore, the present study aims to investigate the association between FTO and leptin resistance. After HFD or standard diet (SD) feeding in male mice for 22 weeks, m6A-sequencing and western blotting assays were used to identify target genes and assess protein level, and molecular interaction changes. CRISPR/Cas9 gene knockout system was employed to investigate the potential function of FTO in leptin resistance and obesity. Our data showed that chemokine (C-X3-C motif) ligand 1 (CX3CL1) was a direct downstream target of FTO-mediated m6A modification. Furthermore, upregulation of FTO/CX3CL1 and suppressor of cytokine signaling 3 (SOCS3) in the hypothalamus impaired leptin-signal transducer and activator of transcription 3 signaling, resulting in leptin resistance and obesity. Compared to wild-type (WT) mice, FTO deficiency in leptin receptor-expressing neurons of the hypothalamus significantly inhibited the upregulation of CX3CL1 and SOCS3, and partially ameliorating leptin resistance under HFD conditions. Our findings reveal that FTO involved in the hypothalamic leptin resistance and provides novel insight into the function of FTO in the contribution to hypothalamic leptin resistance and obesity.
Collapse
Affiliation(s)
- Shujing Liu
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China
| | - Shiyu Song
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China
| | - Shuan Wang
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China
| | - Tonghui Cai
- The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, P.R. China
| | - Lian Qin
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China
| | - Xinzhuang Wang
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China
| | - Guangming Zhu
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China
| | - Haibo Wang
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China
| | - Wenqi Yang
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China
| | - Chunlu Fang
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China
| | - Yuan Wei
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China
| | - Fu Zhou
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China
| | - Yang Yu
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China; School of Sport and Health Sciences, Guangzhou Sport University, Guangzhou 510500, China
| | - Shaozhang Lin
- The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, P.R. China.
| | - Shuang Peng
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China; School of Sport and Health Sciences, Guangzhou Sport University, Guangzhou 510500, China.
| | - Liangming Li
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, P.R. China; School of Sport and Health Sciences, Guangzhou Sport University, Guangzhou 510500, China.
| |
Collapse
|
23
|
Nemoto S, Kubota T, Ishikura T, Nakayama M, Kobayashi A, Yazaki J, Uchida K, Matsuda M, Kondo T, Ohara O, Koseki H, Koyasu S, Ohno H. Characterization of metabolic phenotypes and distinctive genes in mice with low-weight gain. FASEB J 2024; 38:e23339. [PMID: 38069905 DOI: 10.1096/fj.202301565r] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 11/08/2023] [Accepted: 11/14/2023] [Indexed: 12/18/2023]
Abstract
Being overweight exacerbates various metabolic diseases, necessitating the identification of target molecules for obesity control. In the current study, we investigated common physiological features related to metabolism in mice with low weight gain: (1) G protein-coupled receptor, family C, group 5, member B-knockout; (2) gastric inhibitory polypeptide receptor-knockout; and (3) Iroquois-related homeobox 3-knockout. Moreover, we explored genes involved in metabolism by analyzing differentially expressed genes (DEGs) between low-weight gain mice and the respective wild-type control mice. The common characteristics of the low-weight gain mice were low inguinal white adipose tissue (iWAT) and liver weight despite similar food intake along with lower blood leptin levels and high energy expenditure. The DEGs of iWAT, epididymal (gonadal) WAT, brown adipose tissue, muscle, liver, hypothalamus, and hippocampus common to these low-weight gain mice were designated as candidate genes associated with metabolism. One such gene tetraspanin 7 (Tspan7) from the iWAT was validated using knockout and overexpressing mouse models. Mice with low Tspan7 expression gained more weight, while those with high Tspan7 expression gained less weight, confirming the involvement of the Tspan7 gene in weight regulation. Collectively, these findings suggest that the candidate gene list generated in this study contains potential target molecules for obesity regulation. Further validation and additional data from low-weight gain mice will aid in understanding the molecular mechanisms associated with obesity.
Collapse
Affiliation(s)
- Shino Nemoto
- Laboratory for Intestinal Ecosystem, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Tetsuya Kubota
- Laboratory for Intestinal Ecosystem, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Division of Diabetes and Metabolism, The Institute of Medical Science, Asahi Life Foundation, Tokyo, Japan
- Division of Cardiovascular Medicine, Toho University Ohashi Medical Center, Tokyo, Japan
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Tomoyuki Ishikura
- Laboratory for Developmental Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Manabu Nakayama
- Laboratory of Medical Omics Research, Department of Frontier Research and Development, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Atsuo Kobayashi
- Laboratory for Integrative Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Junshi Yazaki
- Laboratory for Integrative Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kazuyo Uchida
- Laboratory for Intestinal Ecosystem, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masashi Matsuda
- Laboratory for Developmental Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Takashi Kondo
- Laboratory for Developmental Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Osamu Ohara
- Laboratory for Integrative Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Haruhiko Koseki
- Laboratory for Developmental Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shigeo Koyasu
- Laboratory for Immune Cell Systems, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Hiroshi Ohno
- Laboratory for Intestinal Ecosystem, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Immune Regulation, Graduate School of Medical and Pharmaceutical Sciences, Chiba University, Chiba, Japan
- Immunobiology Laboratory, Graduate School of Medical Life Science, Yokohama City University, Yokohama, Japan
| |
Collapse
|
24
|
Zhang M, Wang X, Yang N, Zhu X, Lu Z, Cai Y, Li B, Zhu Y, Li X, Wei Y, Zhang S, Tian J, Miao X. Prioritization of risk genes in colorectal cancer by integrative analysis of multi-omics data and gene networks. SCIENCE CHINA. LIFE SCIENCES 2024; 67:132-148. [PMID: 37747674 DOI: 10.1007/s11427-023-2439-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/26/2023] [Indexed: 09/26/2023]
Abstract
Genome-wide association studies (GWASs) have identified over 140 colorectal cancer (CRC)-associated loci; however, target genes at the majority of loci and underlying molecular mechanisms are poorly understood. Here, we utilized a Bayesian approach, integrative risk gene selector (iRIGS), to prioritize risk genes at CRC GWAS loci by integrating multi-omics data. As a result, a total of 105 high-confidence risk genes (HRGs) were identified, which exhibited strong gene dependencies for CRC and enrichment in the biological processes implicated in CRC. Among the 105 HRGs, CEBPB, located at the 20q13.13 locus, acted as a transcription factor playing critical roles in cancer. Our subsequent assays indicated the tumor promoter function of CEBPB that facilitated CRC cell proliferation by regulating multiple oncogenic pathways such as MAPK, PI3K-Akt, and Ras signaling. Next, by integrating a fine-mapping analysis and three independent case-control studies in Chinese populations consisting of 8,039 cases and 12,775 controls, we elucidated that rs1810503, a putative functional variant regulating CEBPB, was associated with CRC risk (OR=0.90, 95%CI=0.86-0.93, P=1.07×10-7). The association between rs1810503 and CRC risk was further validated in three additional multi-ancestry populations consisting of 24,254 cases and 58,741 controls. Mechanistically, the rs1810503 A to T allele change weakened the enhancer activity in an allele-specific manner to decrease CEBPB expression via long-range promoter-enhancer interactions, mediated by the transcription factor, REST, and thus decreased CRC risk. In summary, our study provides a genetic resource and a generalizable strategy for CRC etiology investigation, and highlights the biological implications of CEBPB in CRC tumorigenesis, shedding new light on the etiology of CRC.
Collapse
Affiliation(s)
- Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China
| | - Xiaoyang Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, 450008, China
| | - Nan Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China
| | - Xu Zhu
- Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Xiangpan Li
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Yongchang Wei
- Department of Gastrointestinal Oncology, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, 430062, China
| | - Shaokai Zhang
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, 450008, China.
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China.
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China.
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China.
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430073, China.
- Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, 211166, China.
| |
Collapse
|
25
|
Garza AB, Garcia R, Solis LM, Halfon MS, Girgis HZ. EnhancerTracker: Comparing cell-type-specific enhancer activity of DNA sequence triplets via an ensemble of deep convolutional neural networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.23.573198. [PMID: 38187673 PMCID: PMC10769370 DOI: 10.1101/2023.12.23.573198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Motivation Transcriptional enhancers - unlike promoters - are unrestrained by distance or strand orientation with respect to their target genes, making their computational identification a challenge. Further, there are insufficient numbers of confirmed enhancers for many cell types, preventing robust training of machine-learning-based models for enhancer prediction for such cell types. Results We present EnhancerTracker , a novel tool that leverages an ensemble of deep separable convolutional neural networks to identify cell-type-specific enhancers with the need of only two confirmed enhancers. EnhancerTracker is trained, validated, and tested on 52,789 putative enhancers obtained from the FANTOM5 Project and control sequences derived from the human genome. Unlike available tools, which accept one sequence at a time, the input to our tool is three sequences; the first two are enhancers active in the same cell type. EnhancerTracker outputs 1 if the third sequence is an enhancer active in the same cell type(s) where the first two enhancers are active. It outputs 0 otherwise. On a held-out set (15%), EnhancerTracker achieved an accuracy of 64%, a specificity of 93%, a recall of 35%, a precision of 84%, and an F1 score of 49%. Availability and implementation https://github.com/BioinformaticsToolsmith/EnhancerTracker. Contact hani.girgis@tamuk.edu.
Collapse
|
26
|
Møller AL, Vasan RS, Levy D, Andersson C, Lin H. Integrated omics analysis of coronary artery calcifications and myocardial infarction: the Framingham Heart Study. Sci Rep 2023; 13:21581. [PMID: 38062110 PMCID: PMC10703905 DOI: 10.1038/s41598-023-48848-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 11/30/2023] [Indexed: 12/18/2023] Open
Abstract
Gene function can be described using various measures. We integrated association studies of three types of omics data to provide insights into the pathophysiology of subclinical coronary disease and myocardial infarction (MI). Using multivariable regression models, we associated: (1) single nucleotide polymorphism, (2) DNA methylation, and (3) gene expression with coronary artery calcification (CAC) scores and MI. Among 3106 participants of the Framingham Heart Study, 65 (2.1%) had prevalent MI and 60 (1.9%) had incident MI, median CAC value was 67.8 [IQR 10.8, 274.9], and 1403 (45.2%) had CAC scores > 0 (prevalent CAC). Prevalent CAC was associated with AHRR (linked to smoking) and EXOC3 (affecting platelet function and promoting hemostasis). CAC score was associated with VWA1 (extracellular matrix protein associated with cartilage structure in endomysium). For prevalent MI we identified FYTTD1 (down-regulated in familial hypercholesterolemia) and PINK1 (linked to cardiac tissue homeostasis and ischemia-reperfusion injury). Incident MI was associated with IRX3 (enhancing browning of white adipose tissue) and STXBP3 (controlling trafficking of glucose transporter type 4 to plasma). Using an integrative trans-omics approach, we identified both putatively novel and known candidate genes associated with CAC and MI. Replication of findings is warranted.
Collapse
Affiliation(s)
- Amalie Lykkemark Møller
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
- Department of Cardiology, Nordsjællands Hospital, Hillerød, Denmark.
| | - Ramachandran S Vasan
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- University of Texas School of Public Health San Antonio, and Departments of Medicine and Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
| | - Daniel Levy
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, Division of Intramural Research, National Institutes of Health, Bethesda, MD, USA
| | - Charlotte Andersson
- Section of Cardiovascular Medicine, Department of Medicine, Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| |
Collapse
|
27
|
Ding Y, Zhao Z, Cai H, Zhou Y, Chen H, Bai Y, Liu Z, Liu S, Zhou W. Single-cell sequencing analysis related to sphingolipid metabolism guides immunotherapy and prognosis of skin cutaneous melanoma. Front Immunol 2023; 14:1304466. [PMID: 38077400 PMCID: PMC10701528 DOI: 10.3389/fimmu.2023.1304466] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 11/07/2023] [Indexed: 12/18/2023] Open
Abstract
Background We explore sphingolipid-related genes (SRGs) in skin melanoma (SKCM) to develop a prognostic indicator for patient outcomes. Dysregulated lipid metabolism is linked to aggressive behavior in various cancers, including SKCM. However, the exact role and mechanism of sphingolipid metabolism in melanoma remain partially understood. Methods We integrated scRNA-seq data from melanoma patients sourced from the GEO database. Through the utilization of the Seurat R package, we successfully identified distinct gene clusters associated with patient survival in the scRNA-seq data. Key prognostic genes were identified through single-factor Cox analysis and used to develop a prognostic model using LASSO and stepwise regression algorithms. Additionally, we evaluated the predictive potential of these genes within the immune microenvironment and their relevance to immunotherapy. Finally, we validated the functional significance of the high-risk gene IRX3 through in vitro experiments. Results Analysis of scRNA-seq data identified distinct expression patterns of 4 specific genes (SRGs) in diverse cell subpopulations. Re-clustering cells based on increased SRG expression revealed 7 subgroups with significant prognostic implications. Using marker genes, lasso, and Cox regression, we selected 11 genes to construct a risk signature. This signature demonstrated a strong correlation with immune cell infiltration and stromal scores, highlighting its relevance in the tumor microenvironment. Functional studies involving IRX3 knockdown in A375 and WM-115 cells showed significant reductions in cell viability, proliferation, and invasiveness. Conclusion SRG-based risk signature holds promise for precise melanoma prognosis. An in-depth exploration of SRG characteristics offers insights into immunotherapy response. Therapeutic targeting of the IRX3 gene may benefit melanoma patients.
Collapse
Affiliation(s)
- Yantao Ding
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune-Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Zhijie Zhao
- Department of Plastic Surgery, The Ninth Affiliated Hospital of Shanghai Jiaotong University, Shanghai, China
| | - Huabao Cai
- Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yi Zhou
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune-Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - He Chen
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yun Bai
- Department of Plastic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Zhenran Liu
- Department of Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Shengxiu Liu
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune-Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Wenming Zhou
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune-Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| |
Collapse
|
28
|
Renganaath K, Albert FW. Trans -eQTL hotspots shape complex traits by modulating cellular states. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.14.567054. [PMID: 38014174 PMCID: PMC10680915 DOI: 10.1101/2023.11.14.567054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Regulatory genetic variation shapes gene expression, providing an important mechanism connecting DNA variation and complex traits. The causal relationships between gene expression and complex traits remain poorly understood. Here, we integrated transcriptomes and 46 genetically complex growth traits in a large cross between two strains of the yeast Saccharomyces cerevisiae . We discovered thousands of genetic correlations between gene expression and growth, suggesting functional connections. Local regulatory variation was a minor source of these genetic correlations. Instead, genetic correlations tended to arise from multiple independent trans -acting regulatory loci. Trans -acting hotspots that affect the expression of numerous genes accounted for particularly large fractions of genetic growth variation and of genetic correlations between gene expression and growth. Genes with genetic correlations were enriched for similar biological processes across traits, but with heterogeneous direction of effect. Our results reveal how trans -acting regulatory hotspots shape complex traits by altering cellular states.
Collapse
|
29
|
Jindal GA, Bantle AT, Solvason JJ, Grudzien JL, D'Antonio-Chronowska A, Lim F, Le SH, Song BP, Ragsac MF, Klie A, Larsen RO, Frazer KA, Farley EK. Single-nucleotide variants within heart enhancers increase binding affinity and disrupt heart development. Dev Cell 2023; 58:2206-2216.e5. [PMID: 37848026 PMCID: PMC10720985 DOI: 10.1016/j.devcel.2023.09.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 06/07/2023] [Accepted: 09/20/2023] [Indexed: 10/19/2023]
Abstract
Transcriptional enhancers direct precise gene expression patterns during development and harbor the majority of variants associated with phenotypic diversity, evolutionary adaptations, and disease. Pinpointing which enhancer variants contribute to changes in gene expression and phenotypes is a major challenge. Here, we find that suboptimal or low-affinity binding sites are necessary for precise gene expression during heart development. Single-nucleotide variants (SNVs) can optimize the affinity of ETS binding sites, causing gain-of-function (GOF) gene expression, cell migration defects, and phenotypes as severe as extra beating hearts in the marine chordate Ciona robusta. In human induced pluripotent stem cell (iPSC)-derived cardiomyocytes, a SNV within a human GATA4 enhancer increases ETS binding affinity and causes GOF enhancer activity. The prevalence of suboptimal-affinity sites within enhancers creates a vulnerability whereby affinity-optimizing SNVs can lead to GOF gene expression, changes in cellular identity, and organismal-level phenotypes that could contribute to the evolution of novel traits or diseases.
Collapse
Affiliation(s)
- Granton A Jindal
- Department of Medicine, Health Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Alexis T Bantle
- Department of Medicine, Health Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Biological Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Joe J Solvason
- Department of Medicine, Health Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Jessica L Grudzien
- Department of Medicine, Health Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | | | - Fabian Lim
- Department of Medicine, Health Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Biological Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Sophia H Le
- Department of Medicine, Health Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Benjamin P Song
- Department of Medicine, Health Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Biological Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Michelle F Ragsac
- Department of Medicine, Health Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Adam Klie
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Reid O Larsen
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Kelly A Frazer
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA; Institute for Genomic Medicine, Health Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Emma K Farley
- Department of Medicine, Health Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA.
| |
Collapse
|
30
|
Huang C, Chen W, Wang X. Studies on the fat mass and obesity-associated (FTO) gene and its impact on obesity-associated diseases. Genes Dis 2023; 10:2351-2365. [PMID: 37554175 PMCID: PMC10404889 DOI: 10.1016/j.gendis.2022.04.014] [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: 12/19/2021] [Revised: 03/29/2022] [Accepted: 04/01/2022] [Indexed: 10/18/2022] Open
Abstract
Obesity has become a major health crisis in the past ∼50 years. The fat mass and obesity-associated (FTO) gene, identified by genome-wide association studies (GWAS), was first reported to be positively associated with obesity in humans. Mice with more copies of the FTO gene were observed to be obese, while loss of the gene in mice was found to protect from obesity. Later, FTO was found to encode an m6A RNA demethylase and has a profound effect on many biological and metabolic processes. In this review, we first summarize recent studies that demonstrate the critical roles and regulatory mechanisms of FTO in obesity and metabolic disease. Second, we discuss the ongoing debates concerning the association between FTO polymorphisms and obesity. Third, since several small molecule drugs and micronutrients have been found to regulate metabolic homeostasis through controlling the expression or activity of FTO, we highlight the broad potential of targeting FTO for obesity treatment. Improving our understanding of FTO and the underlying mechanisms may provide new approaches for treating obesity and metabolic diseases.
Collapse
Affiliation(s)
- Chaoqun Huang
- College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Molecular Animal Nutrition, Zhejiang University, Ministry of Education, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Nutrition and Feed Science (Eastern of China), Ministry of Agriculture and Rural Affairs, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Feed and Nutrition of Zhejiang Province, Hangzhou, Zhejiang 310058, China
| | - Wei Chen
- College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Molecular Animal Nutrition, Zhejiang University, Ministry of Education, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Nutrition and Feed Science (Eastern of China), Ministry of Agriculture and Rural Affairs, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Feed and Nutrition of Zhejiang Province, Hangzhou, Zhejiang 310058, China
| | - Xinxia Wang
- College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Molecular Animal Nutrition, Zhejiang University, Ministry of Education, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Nutrition and Feed Science (Eastern of China), Ministry of Agriculture and Rural Affairs, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Feed and Nutrition of Zhejiang Province, Hangzhou, Zhejiang 310058, China
| |
Collapse
|
31
|
Emfinger CH, Clark LE, Yandell B, Schueler KL, Simonett SP, Stapleton DS, Mitok KA, Merrins MJ, Keller MP, Attie AD. Novel regulators of islet function identified from genetic variation in mouse islet Ca 2+ oscillations. eLife 2023; 12:RP88189. [PMID: 37787501 PMCID: PMC10547476 DOI: 10.7554/elife.88189] [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] [Indexed: 10/04/2023] Open
Abstract
Insufficient insulin secretion to meet metabolic demand results in diabetes. The intracellular flux of Ca2+ into β-cells triggers insulin release. Since genetics strongly influences variation in islet secretory responses, we surveyed islet Ca2+ dynamics in eight genetically diverse mouse strains. We found high strain variation in response to four conditions: (1) 8 mM glucose; (2) 8 mM glucose plus amino acids; (3) 8 mM glucose, amino acids, plus 10 nM glucose-dependent insulinotropic polypeptide (GIP); and (4) 2 mM glucose. These stimuli interrogate β-cell function, α- to β-cell signaling, and incretin responses. We then correlated components of the Ca2+ waveforms to islet protein abundances in the same strains used for the Ca2+ measurements. To focus on proteins relevant to human islet function, we identified human orthologues of correlated mouse proteins that are proximal to glycemic-associated single-nucleotide polymorphisms in human genome-wide association studies. Several orthologues have previously been shown to regulate insulin secretion (e.g. ABCC8, PCSK1, and GCK), supporting our mouse-to-human integration as a discovery platform. By integrating these data, we nominate novel regulators of islet Ca2+ oscillations and insulin secretion with potential relevance for human islet function. We also provide a resource for identifying appropriate mouse strains in which to study these regulators.
Collapse
Affiliation(s)
| | - Lauren E Clark
- Department of Biochemistry, University of Wisconsin-MadisonMadisonUnited States
| | - Brian Yandell
- Department of Statistics, University of Wisconsin-MadisonMadisonUnited States
| | - Kathryn L Schueler
- Department of Biochemistry, University of Wisconsin-MadisonMadisonUnited States
| | - Shane P Simonett
- Department of Biochemistry, University of Wisconsin-MadisonMadisonUnited States
| | - Donnie S Stapleton
- Department of Biochemistry, University of Wisconsin-MadisonMadisonUnited States
| | - Kelly A Mitok
- Department of Biochemistry, University of Wisconsin-MadisonMadisonUnited States
| | - Matthew J Merrins
- Department of Medicine, Division of Endocrinology, University of Wisconsin-MadisonMadisonUnited States
- William S. Middleton Memorial Veterans HospitalMadisonUnited States
| | - Mark P Keller
- Department of Biochemistry, University of Wisconsin-MadisonMadisonUnited States
| | - Alan D Attie
- Department of Biochemistry, University of Wisconsin-MadisonMadisonUnited States
- Department of Medicine, Division of Endocrinology, University of Wisconsin-MadisonMadisonUnited States
- Department of Chemistry, University of Wisconsin-MadisonMadisonUnited States
| |
Collapse
|
32
|
D'Antongiovanni V, Segnani C, Ippolito C, Antonioli L, Colucci R, Fornai M, Bernardini N, Pellegrini C. Pathological Remodeling of the Gut Barrier as a Prodromal Event of High-Fat Diet-Induced Obesity. J Transl Med 2023; 103:100194. [PMID: 37290605 DOI: 10.1016/j.labinv.2023.100194] [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: 02/17/2023] [Revised: 05/29/2023] [Accepted: 05/31/2023] [Indexed: 06/10/2023] Open
Abstract
Intestinal barrier alterations represent a primum movens in obesity and related intestinal dysfunctions. However, whether gut barrier remodeling represents prodromal events in obesity before weight gain, metabolic alterations, and systemic inflammation remains unclear. Herein, we examined morphologic changes in the gut barrier in a mouse model of high-fat diet (HFD) since the earliest phases of diet assumption. C57BL/6J mice were fed with standard diet (SD) or HFD for 1, 2, 4, or 8 weeks. Remodeling of intestinal epithelial barrier, inflammatory infiltrate, and collagen deposition in the colonic wall was assessed by histochemistry and immunofluorescence analysis. Obese mice displayed increased body and epididymal fat weight along with increased plasma resistin, IL-1β, and IL-6 levels after 8 weeks of HFD. Starting from 1 week of HFD, mice displayed (1) a decreased claudin-1 expression in lining epithelial cells, (2) an altered mucus in goblet cells, (3) an increase in proliferating epithelial cells in colonic crypts, (4) eosinophil infiltration along with an increase in vascular P-selectin, and (5) deposition of collagen fibers. HFD intake is associated with morphologic changes in the large bowel at mucosal and submucosal levels. In particular, the main changes include alterations in the mucous layer and intestinal epithelial barrier integrity and activation of mucosal defense-enhanced fibrotic deposition. These changes represent early events occurring before the development of obesity condition that could contribute to compromising the intestinal mucosal barrier and functions, opening the way for systemic dissemination.
Collapse
Affiliation(s)
- Vanessa D'Antongiovanni
- Unit of Histology and Medical Embryology, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Cristina Segnani
- Unit of Histology and Medical Embryology, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Chiara Ippolito
- Unit of Histology and Medical Embryology, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Luca Antonioli
- Unit of Pharmacology and Pharmacovigilance, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Rocchina Colucci
- Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy
| | - Matteo Fornai
- Unit of Pharmacology and Pharmacovigilance, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Nunzia Bernardini
- Unit of Histology and Medical Embryology, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy; Interdepartmental Research Centre "Nutraceuticals and Food for Health," University of Pisa, Pisa, Italy.
| | - Carolina Pellegrini
- Unit of Histology and Medical Embryology, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| |
Collapse
|
33
|
Chen YH, Jiang T, Yasen A, Fan BY, Zhu J, Wang MX, Shen XJ. RNA N6-methyladenosine of DHAPAT and PAP involves in regulation of diapause of Bombyx mori via the lipid metabolism pathway. BULLETIN OF ENTOMOLOGICAL RESEARCH 2023; 113:665-675. [PMID: 37555240 DOI: 10.1017/s0007485323000330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/10/2023]
Abstract
Environment-induced epigenetics are involved in diapause regulation, but the molecular mechanism that epigenetically couples nutrient metabolism to diapause regulation remains unclear. In this study, we paid special attention to the significant differences in the level of N6-adenosine methylation (m6A) of dihydroxyacetone phosphate acyltransferase (DHAPAT) and phosphatidate phosphatase (PAP) genes in the lipid metabolism pathway of the bivoltine silkworm (Bombyx mori) strain Qiufeng developed from eggs incubated at a normal temperature (QFHT, diapause egg producer) compared to those from eggs incubated at a low temperature (QFLT, non-diapause egg producer). We knocked down DHAPAT in the pupal stage of the QFLT group, resulting in the non-diapause destined eggs becoming diapausing eggs. In the PAP knockdown group, the colour of the non-diapause destined eggs changed from light yellow to pink 3 days after oviposition, but they hatched as normal. Moreover, we validated that YTHDF3 binds to m6A-modified DHAPAT and PAP mRNAs to promote their stability and translation. These results suggest that RNA m6A methylation participates in the diapause regulation of silkworm by changing the expression levels of DHAPAT and PAP and reveal that m6A epigenetic modification can be combined with a lipid metabolism signal pathway to participate in the regulation of insect diapause traits, which provides a clearer image for exploring the physiological basis of insect diapause.
Collapse
Affiliation(s)
- Yan-Hua Chen
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, College of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
- Key Laboratory of Silkworm and Mulberry Genetic Improvement, Ministry of Agriculture and Rural Affairs, Sericulture Research Institute, Chinese Academy of Agricultural Sciences, Zhenjiang, Jiangsu 212100, China
| | - Tao Jiang
- Silkworm Egg Institute of Jiangsu Province, Wuxi, Jiangsu 214000, China
| | - Ayinuer Yasen
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, College of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
- Key Laboratory of Silkworm and Mulberry Genetic Improvement, Ministry of Agriculture and Rural Affairs, Sericulture Research Institute, Chinese Academy of Agricultural Sciences, Zhenjiang, Jiangsu 212100, China
| | - Bing-Yan Fan
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, College of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
- Key Laboratory of Silkworm and Mulberry Genetic Improvement, Ministry of Agriculture and Rural Affairs, Sericulture Research Institute, Chinese Academy of Agricultural Sciences, Zhenjiang, Jiangsu 212100, China
| | - Juan Zhu
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, College of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
- Key Laboratory of Silkworm and Mulberry Genetic Improvement, Ministry of Agriculture and Rural Affairs, Sericulture Research Institute, Chinese Academy of Agricultural Sciences, Zhenjiang, Jiangsu 212100, China
| | - Mei-Xian Wang
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, College of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
- Key Laboratory of Silkworm and Mulberry Genetic Improvement, Ministry of Agriculture and Rural Affairs, Sericulture Research Institute, Chinese Academy of Agricultural Sciences, Zhenjiang, Jiangsu 212100, China
| | - Xing-Jia Shen
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, College of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
- Key Laboratory of Silkworm and Mulberry Genetic Improvement, Ministry of Agriculture and Rural Affairs, Sericulture Research Institute, Chinese Academy of Agricultural Sciences, Zhenjiang, Jiangsu 212100, China
| |
Collapse
|
34
|
Anwar MY, Graff M, Highland HM, Smit R, Wang Z, Buchanan VL, Young KL, Kenny EE, Fernandez-Rhodes L, Liu S, Assimes T, Garcia DO, Daeeun K, Gignoux CR, Justice AE, Haiman CA, Buyske S, Peters U, Loos RJF, Kooperberg C, North KE. Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts. Hum Genet 2023; 142:1477-1489. [PMID: 37658231 DOI: 10.1007/s00439-023-02593-7] [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: 02/20/2023] [Accepted: 08/10/2023] [Indexed: 09/03/2023]
Abstract
Inadequate representation of non-European ancestry populations in genome-wide association studies (GWAS) has limited opportunities to isolate functional variants. Fine-mapping in multi-ancestry populations should improve the efficiency of prioritizing variants for functional interrogation. To evaluate this hypothesis, we leveraged ancestry architecture to perform comparative GWAS and fine-mapping of obesity-related phenotypes in European ancestry populations from the UK Biobank (UKBB) and multi-ancestry samples from the Population Architecture for Genetic Epidemiology (PAGE) consortium with comparable sample sizes. In the investigated regions with genome-wide significant associations for obesity-related traits, fine-mapping in our ancestrally diverse sample led to 95% and 99% credible sets (CS) with fewer variants than in the European ancestry sample. Lead fine-mapped variants in PAGE regions had higher average coding scores, and higher average posterior probabilities for causality compared to UKBB. Importantly, 99% CS in PAGE loci contained strong expression quantitative trait loci (eQTLs) in adipose tissues or harbored more variants in tighter linkage disequilibrium (LD) with eQTLs. Leveraging ancestrally diverse populations with heterogeneous ancestry architectures, coupled with functional annotation, increased fine-mapping efficiency and performance, and reduced the set of candidate variants for consideration for future functional studies. Significant overlap in genetic causal variants across populations suggests generalizability of genetic mechanisms underpinning obesity-related traits across populations.
Collapse
Affiliation(s)
- Mohammad Yaser Anwar
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Roelof Smit
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Victoria L Buchanan
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kristin L Young
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Eimear E Kenny
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lindsay Fernandez-Rhodes
- Department of Biobehavioral Health, College of Health and Human Development, Pennsylvania State University, University Park, PA, 16802, USA
| | - Simin Liu
- Department of Epidemiology and Center for Global Cardiometabolic Health, School of Public Health, Brown University, Providence, RI, 02903, USA
| | - Themistocles Assimes
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - David O Garcia
- Department of Health Promotion Sciences, Mel & Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, 85724, USA
| | - Kim Daeeun
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Christopher R Gignoux
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Anne E Justice
- Department of Population Health Sciences, Geisinger Health, Danville, PA, 17822, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Steve Buyske
- Department of Statistics, Rutgers University, Piscataway, NJ, 08854, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| |
Collapse
|
35
|
Malfait J, Wan J, Spicuglia S. Epromoters are new players in the regulatory landscape with potential pleiotropic roles. Bioessays 2023; 45:e2300012. [PMID: 37246247 DOI: 10.1002/bies.202300012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/11/2023] [Accepted: 05/15/2023] [Indexed: 05/30/2023]
Abstract
Precise spatiotemporal control of gene expression during normal development and cell differentiation is achieved by the combined action of proximal (promoters) and distal (enhancers) cis-regulatory elements. Recent studies have reported that a subset of promoters, termed Epromoters, works also as enhancers to regulate distal genes. This new paradigm opened novel questions regarding the complexity of our genome and raises the possibility that genetic variation within Epromoters has pleiotropic effects on various physiological and pathological traits by differentially impacting multiple proximal and distal genes. Here, we discuss the different observations pointing to an important role of Epromoters in the regulatory landscape and summarize the evidence supporting a pleiotropic impact of these elements in disease. We further hypothesize that Epromoter might represent a major contributor to phenotypic variation and disease.
Collapse
Affiliation(s)
- Juliette Malfait
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, LIGUE, Marseille, France
| | - Jing Wan
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, LIGUE, Marseille, France
| | - Salvatore Spicuglia
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, LIGUE, Marseille, France
| |
Collapse
|
36
|
Robert S, Rada-Iglesias A. The interaction between enhancer variants and environmental factors as an overlooked aetiological paradigm in human complex disease. Bioessays 2023; 45:e2300038. [PMID: 37170707 DOI: 10.1002/bies.202300038] [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: 02/23/2023] [Revised: 04/27/2023] [Accepted: 05/03/2023] [Indexed: 05/13/2023]
Abstract
The interactions between genetic and environmental risk factors contribute to the aetiology of complex human diseases. Genome-wide association studies (GWAS) have revealed that most of the genetic variants associated with complex diseases are located in the non-coding part of the genome, preferentially within enhancers. Enhancers are distal cis-regulatory elements composed of clusters of transcription factors binding sites that positively regulate the expression of their target genes. The generation of genome-wide maps for histone marks (e.g., H3K27ac), chromatin accessibility and transcription factor and coactivator (e.g., p300) binding profiles have enabled the identification of enhancers across many human cell types and tissues. Nonetheless, the functional and pathological consequences of the majority of disease-associated genetic variants located within enhancers seem to be rather minor under normal conditions, thus questioning their medical relevance. Here we propose that, due to the prevalence of enhancer redundancy, the pathological effects of many disease-associated non-coding genetic variants might be preferentially (or even only) manifested under environmental stress.
Collapse
Affiliation(s)
- Sarah Robert
- Institute of Biomedicine and Biotechnology of Cantabria (IBBTEC), CSIC/Universidad de, Santander, Cantabria, Spain
| | - Alvaro Rada-Iglesias
- Institute of Biomedicine and Biotechnology of Cantabria (IBBTEC), CSIC/Universidad de, Santander, Cantabria, Spain
| |
Collapse
|
37
|
Kanwischer L, Xu X, Saifuddin AB, Maamari S, Tan X, Alnour F, Tampe B, Meyer T, Zeisberg M, Hasenfuss G, Puls M, Zeisberg EM. Low levels of circulating methylated IRX3 are related to worse outcome after transcatheter aortic valve implantation in patients with severe aortic stenosis. Clin Epigenetics 2023; 15:149. [PMID: 37697352 PMCID: PMC10496273 DOI: 10.1186/s13148-023-01561-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 09/04/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND Aortic stenosis (AS) is one of the most common cardiac diseases and major cause of morbidity and mortality in the elderly. Transcatheter aortic valve implantation (TAVI) is performed in such patients with symptomatic severe AS and reduces mortality for the majority of these patients. However, a significant percentage dies within the first two years after TAVI, such that there is an interest to identify parameters, which predict outcome and could guide pre-TAVI patient selection. High levels of cardiac fibrosis have been identified as such independent predictor of cardiovascular mortality after TAVI. Promoter hypermethylation commonly leads to gene downregulation, and the Iroquois homeobox 3 (IRX3) gene was identified in a genome-wide transcriptome and methylome to be hypermethylated and downregulated in AS patients. In a well-described cohort of 100 TAVI patients in which cardiac fibrosis levels were quantified histologically in cardiac biopsies, and which had a follow-up of up to two years, we investigated if circulating methylated DNA of IRX3 in the peripheral blood is associated with cardiac fibrosis and/or mortality in AS patients undergoing TAVI and thus could serve as a biomarker to add information on outcome after TAVI. RESULTS Patients with high levels of methylation in circulating IRX3 show a significantly increased survival as compared to patients with low levels of IRX3 methylation indicating that high peripheral IRX3 methylation is associated with an improved outcome. In the multivariable setting, peripheral IRX3 methylation acts as an independent predictor of all-cause mortality. While there is no significant correlation of levels of IRX3 methylation with cardiac death, there is a significant but very weak inverse correlation between circulating IRX3 promoter methylation level and the amount of cardiac fibrosis. Higher levels of peripheral IRX3 methylation further correlated with decreased cardiac IRX3 expression and vice versa. CONCLUSIONS High levels of IRX3 methylation in the blood of AS patients at the time of TAVI are associated with better overall survival after TAVI and at least partially reflect myocardial IRX3 expression. Circulating methylated IRX3 might aid as a potential biomarker to help guide both pre-TAVI patient selection and post-TAVI monitoring.
Collapse
Affiliation(s)
- Leon Kanwischer
- Department of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August-University, Robert-Koch-Str. 40, 37075, Göttingen, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Göttingen, Göttingen, Germany
| | - Xingbo Xu
- Department of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August-University, Robert-Koch-Str. 40, 37075, Göttingen, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Göttingen, Göttingen, Germany
| | - Afifa Binta Saifuddin
- Department of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August-University, Robert-Koch-Str. 40, 37075, Göttingen, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Göttingen, Göttingen, Germany
| | - Sabine Maamari
- Department of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August-University, Robert-Koch-Str. 40, 37075, Göttingen, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Göttingen, Göttingen, Germany
| | - Xiaoying Tan
- Department of Nephrology and Rheumatology, University Medical Center Göttingen, Georg-August-University, Göttingen, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Göttingen, Göttingen, Germany
| | - Fouzi Alnour
- Department of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August-University, Robert-Koch-Str. 40, 37075, Göttingen, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Göttingen, Göttingen, Germany
| | - Björn Tampe
- Department of Nephrology and Rheumatology, University Medical Center Göttingen, Georg-August-University, Göttingen, Germany
| | - Thomas Meyer
- Department of Psychosomatic Medicine and Psychotherapy, University Medical Center Göttingen, Georg-August-University, Göttingen, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Göttingen, Göttingen, Germany
| | - Michael Zeisberg
- Department of Nephrology and Rheumatology, University Medical Center Göttingen, Georg-August-University, Göttingen, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Göttingen, Göttingen, Germany
| | - Gerd Hasenfuss
- Department of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August-University, Robert-Koch-Str. 40, 37075, Göttingen, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Göttingen, Göttingen, Germany
| | - Miriam Puls
- Department of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August-University, Robert-Koch-Str. 40, 37075, Göttingen, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Göttingen, Göttingen, Germany
| | - Elisabeth M Zeisberg
- Department of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August-University, Robert-Koch-Str. 40, 37075, Göttingen, Germany.
- DZHK German Center for Cardiovascular Research, Partner Site Göttingen, Göttingen, Germany.
| |
Collapse
|
38
|
Yeh SY, Estill M, Lardner CK, Browne CJ, Minier-Toribio A, Futamura R, Beach K, McManus CA, Xu SJ, Zhang S, Heller EA, Shen L, Nestler EJ. Cell Type-Specific Whole-Genome Landscape of ΔFOSB Binding in the Nucleus Accumbens After Chronic Cocaine Exposure. Biol Psychiatry 2023; 94:367-377. [PMID: 36906500 PMCID: PMC10314970 DOI: 10.1016/j.biopsych.2022.12.021] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 12/16/2022] [Accepted: 12/22/2022] [Indexed: 01/04/2023]
Abstract
BACKGROUND The ability of neurons to respond to external stimuli involves adaptations of gene expression. Induction of the transcription factor ΔFOSB in the nucleus accumbens, a key brain reward region, is important for the development of drug addiction. However, a comprehensive map of ΔFOSB's gene targets has not yet been generated. METHODS We used CUT&RUN (cleavage under targets and release using nuclease) to map the genome-wide changes in ΔFOSB binding in the 2 main types of nucleus accumbens neurons-D1 or D2 medium spiny neurons-after chronic cocaine exposure. To annotate genomic regions of ΔFOSB binding sites, we also examined the distributions of several histone modifications. Resulting datasets were leveraged for multiple bioinformatic analyses. RESULTS The majority of ΔFOSB peaks occur outside promoter regions, including intergenic regions, and are surrounded by epigenetic marks indicative of active enhancers. BRG1, the core subunit of the SWI/SNF chromatin remodeling complex, overlaps with ΔFOSB peaks, a finding consistent with earlier studies of ΔFOSB's interacting proteins. Chronic cocaine use induces broad changes in ΔFOSB binding in both D1 and D2 nucleus accumbens medium spiny neurons of male and female mice. In addition, in silico analyses predict that ΔFOSB cooperatively regulates gene expression with homeobox and T-box transcription factors. CONCLUSIONS These novel findings uncover key elements of ΔFOSB's molecular mechanisms in transcriptional regulation at baseline and in response to chronic cocaine exposure. Further characterization of ΔFOSB's collaborative transcriptional and chromatin partners specifically in D1 and D2 medium spiny neurons will reveal a broader picture of the function of ΔFOSB and the molecular basis of drug addiction.
Collapse
Affiliation(s)
- Szu-Ying Yeh
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Molly Estill
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Casey K Lardner
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Caleb J Browne
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Angelica Minier-Toribio
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Rita Futamura
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Katherine Beach
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Catherine A McManus
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Song-Jun Xu
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Shuo Zhang
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Elizabeth A Heller
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania; Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania; Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Li Shen
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Eric J Nestler
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
| |
Collapse
|
39
|
Asgari Y, Sugier PE, Baghfalaki T, Lucotte E, Karimi M, Sedki M, Ngo A, Liquet B, Truong T. GCPBayes pipeline: a tool for exploring pleiotropy at the gene level. NAR Genom Bioinform 2023; 5:lqad065. [PMID: 37416786 PMCID: PMC10320750 DOI: 10.1093/nargab/lqad065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 05/16/2023] [Accepted: 06/16/2023] [Indexed: 07/08/2023] Open
Abstract
Cross-phenotype association using gene-set analysis can help to detect pleiotropic genes and inform about common mechanisms between diseases. Although there are an increasing number of statistical methods for exploring pleiotropy, there is a lack of proper pipelines to apply gene-set analysis in this context and using genome-scale data in a reasonable running time. We designed a user-friendly pipeline to perform cross-phenotype gene-set analysis between two traits using GCPBayes, a method developed by our team. All analyses could be performed automatically by calling for different scripts in a simple way (using a Shiny app, Bash or R script). A Shiny application was also developed to create different plots to visualize outputs from GCPBayes. Finally, a comprehensive and step-by-step tutorial on how to use the pipeline is provided in our group's GitHub page. We illustrated the application on publicly available GWAS (genome-wide association studies) summary statistics data to identify breast cancer and ovarian cancer susceptibility genes. We have shown that the GCPBayes pipeline could extract pleiotropic genes previously mentioned in the literature, while it also provided new pleiotropic genes and regions that are worthwhile for further investigation. We have also provided some recommendations about parameter selection for decreasing computational time of GCPBayes on genome-scale data.
Collapse
Affiliation(s)
- Yazdan Asgari
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team Exposome and Heredity, 94807 Villejuif, France
| | - Pierre-Emmanuel Sugier
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team Exposome and Heredity, 94807 Villejuif, France
- Laboratoire de Mathématiques et de leurs Applications de Pau, Université de Pau et des Pays de l’Adour, UMR CNRS 5142, E2S-UPPA, 64000 Pau, France
| | | | - Elise Lucotte
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team Exposome and Heredity, 94807 Villejuif, France
| | - Mojgan Karimi
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team Exposome and Heredity, 94807 Villejuif, France
| | - Mohammed Sedki
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team Psychiatrie du développement et trajectoires, 94807 Villejuif, France
| | - Amélie Ngo
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team Exposome and Heredity, 94807 Villejuif, France
| | - Benoit Liquet
- Laboratoire de Mathématiques et de leurs Applications de Pau, Université de Pau et des Pays de l’Adour, UMR CNRS 5142, E2S-UPPA, 64000 Pau, France
- School of Mathematical and Physical Sciences, Macquarie University, Sydney, NSW 2109, Australia
| | - Thérèse Truong
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Team Exposome and Heredity, 94807 Villejuif, France
| |
Collapse
|
40
|
Krejčí J, Arcidiacono OA, Čegan R, Radaszkiewicz K, Pacherník J, Pirk J, Pešl M, Fila P, Bártová E. Cell Differentiation and Aging Lead To Up-Regulation of FTO, While the ALKBH5 Protein Level Was Stable During Aging but Up-Regulated During in vitro-Induced Cardiomyogenesis. Physiol Res 2023; 72:425-444. [PMID: 37795886 PMCID: PMC10634569 DOI: 10.33549/physiolres.935078] [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: 02/07/2023] [Accepted: 05/25/2023] [Indexed: 01/05/2024] Open
Abstract
FTO and ALKBH5 proteins are essential erasers of N6-adenosine methylation in RNA. We studied how levels of FTO and ALKBH5 proteins changed during mouse embryonic development, aging, cardiomyogenesis, and neuroectodermal differentiation. We observed that aging in male and female mice was associated with FTO up-regulation in mouse hearts, brains, lungs, and kidneys, while the ALKBH5 level remained stable. FTO and ALKBH5 proteins were up-regulated during experimentally induced cardiomyogenesis, but the level of ALKBH5 protein was not changed when neuroectodermal differentiation was induced. HDAC1 depletion in mouse ES cells caused FTO down-regulation. In these cells, mRNA, carrying information from genes that regulate histone signature, RNA processing, and cell differentiation, was characterized by a reduced level of N6-adenosine methylation in specific gene loci, primarily regulating cell differentiation into neuroectoderm. Together, when we compared both RNA demethylating proteins, the FTO protein level undergoes the most significant changes during cell differentiation and aging. Thus, we conclude that during aging and neuronal differentiation, m6A RNA demethylation is likely regulated by the FTO protein but not via the function of ALKBH5.
Collapse
Affiliation(s)
- J Krejčí
- Department of Cell Biology and Epigenetics, Institute of Biophysics, Academy of Sciences of the Czech Republic, Brno, Czech Republic.
| | | | | | | | | | | | | | | | | |
Collapse
|
41
|
Zhang Q, Bao X, Cui M, Wang C, Ji J, Jing J, Zhou X, Chen K, Tang L. Identification and validation of key biomarkers based on RNA methylation genes in sepsis. Front Immunol 2023; 14:1231898. [PMID: 37701433 PMCID: PMC10493392 DOI: 10.3389/fimmu.2023.1231898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 08/14/2023] [Indexed: 09/14/2023] Open
Abstract
Background RNA methylation is closely involved in immune regulation, but its role in sepsis remains unknown. Here, we aim to investigate the role of RNA methylation-associated genes (RMGs) in classifying and diagnosing of sepsis. Methods Five types of RMGs (m1A, m5C, m6Am, m7G and Ψ) were used to identify sepsis subgroups based on gene expression profile data obtained from the GEO database (GSE57065, GSE65682, and GSE95233). Unsupervised clustering analysis was used to identify distinct RNA modification subtypes. The CIBERSORT, WGCNA, GO and KEGG analysis were performed to explore immune infiltration pattern and biological function of each cluster. RF, SVM, XGB, and GLM algorithm were applied to identify the diagnostic RMGs in sepsis. Finally, the expression levels of the five key RMGs were verified by collecting PBMCs from septic patients using qRT-PCR, and their diagnostic efficacy for sepsis was verified in combination with clinical data using ROC analysis. Results Sepsis was divided into three subtypes (cluster 1 to 3). Cluster 1 highly expressed NSUN7 and TRMT6, with the characteristic of neutrophil activation and upregulation of MAPK signaling pathways. Cluster 2 highly expressed NSUN3, and was featured by the regulation of mRNA stability and amino acid metabolism. NSUN5 and NSUN6 were upregulated in cluster 3 which was involved in ribonucleoprotein complex biogenesis and carbohydrate metabolism pathways. In addition, we identified that five RMGs (NSUN7, NOP2, PUS1, PUS3 and FTO) could function as biomarkers for clinic diagnose of sepsis. For validation, we determined that the relative expressions of NSUN7, NOP2, PUS1 and PUS3 were upregulated, while FTO was downregulated in septic patients. The area under the ROC curve (AUC) of NSUN7, NOP2, PUS1, PUS3 and FTO was 0.828, 0.707, 0.846, 0.834 and 0.976, respectively. Conclusions Our study uncovered that dysregulation of RNA methylation genes (m1A, m5C, m6Am, m7G and Ψ) was closely involved in the pathogenesis of sepsis, providing new insights into the classification of sepsis endotypes. We also revealed that five hub RMGs could function as novel diagnostic biomarkers and potential targets for treatment.
Collapse
Affiliation(s)
- Qianqian Zhang
- Department of Internal Emergency Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
- School of Medicine, Tongji University, Shanghai, China
| | - Xiaowei Bao
- Department of Internal Emergency Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
- School of Medicine, Tongji University, Shanghai, China
| | - Mintian Cui
- Translational Medical Center for Stem Cell Therapy, Institute for Regenerative Medicine, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China
| | - Chunxue Wang
- Department of Internal Emergency Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
- School of Medicine, Tongji University, Shanghai, China
| | - Jinlu Ji
- Department of Internal Emergency Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
- School of Medicine, Tongji University, Shanghai, China
| | - Jiongjie Jing
- Translational Medical Center for Stem Cell Therapy, Institute for Regenerative Medicine, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China
| | - Xiaohui Zhou
- Research Center for Translational Medicine, Shanghai Heart Failure Research Center, Shanghai East Hospital, Tongji University, Shanghai, China
| | - Kun Chen
- Translational Medical Center for Stem Cell Therapy, Institute for Regenerative Medicine, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, China
| | - Lunxian Tang
- Department of Internal Emergency Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
- School of Medicine, Tongji University, Shanghai, China
| |
Collapse
|
42
|
Littleton SH, Trang KB, Volpe CM, Cook K, DeBruyne N, Ann Maguire J, Ann Weidekamp M, Boehm K, Chesi A, Pippin JA, Anderson SA, Wells AD, Pahl MC, Grant SF. Variant-to-function analysis of the childhood obesity chr12q13 locus implicates rs7132908 as a causal variant within the 3' UTR of FAIM2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.21.553157. [PMID: 37662342 PMCID: PMC10473629 DOI: 10.1101/2023.08.21.553157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
The ch12q13 obesity locus is among the most significant childhood obesity loci identified in genome-wide association studies. This locus resides in a non-coding region within FAIM2; thus, the underlying causal variant(s) presumably influence disease susceptibility via an influence on cis-regulation within the genomic region. We implicated rs7132908 as a putative causal variant at this locus leveraging a combination of our inhouse 3D genomic data, public domain datasets, and several computational approaches. Using a luciferase reporter assay in human primary astrocytes, we observed allele-specific cis-regulatory activity of the immediate region harboring rs7132908. Motivated by this finding, we went on to generate isogenic human embryonic stem cell lines homozygous for either rs7132908 allele with CRISPR-Cas9 homology-directed repair to assess changes in gene expression due to genotype and chromatin accessibility throughout a differentiation to hypothalamic neurons, a key cell type known to regulate feeding behavior. We observed that the rs7132908 obesity risk allele influenced the expression of FAIM2 along with other genes, decreased the proportion of neurons produced during differentiation, up-regulated cell death gene sets, and conversely down-regulated neuron differentiation gene sets. We have therefore functionally validated rs7132908 as a causal obesity variant which temporally regulates nearby effector genes at the ch12q13 locus and influences neurodevelopment and survival.
Collapse
Affiliation(s)
- Sheridan H. Littleton
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Khanh B. Trang
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Christina M. Volpe
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kieona Cook
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Psychiatry, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Nicole DeBruyne
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jean Ann Maguire
- Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Mary Ann Weidekamp
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Keith Boehm
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - James A. Pippin
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Stewart A. Anderson
- Department of Child and Adolescent Psychiatry, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andrew D. Wells
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew C. Pahl
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Endocrinology and Diabetes, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| |
Collapse
|
43
|
Sonti S, Littleton SH, Pahl MC, Zimmerman AJ, Chesi A, Palermo J, Lasconi C, Brown EB, Pippin JA, Wells AD, Doldur-Balli F, Pack AI, Gehrman PR, Keene AC, Grant SFA. Perturbation of the insomnia WDR90 GWAS locus pinpoints rs3752495 as a causal variant influencing distal expression of neighboring gene, PIG-Q. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.17.553739. [PMID: 37645863 PMCID: PMC10462147 DOI: 10.1101/2023.08.17.553739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Although genome wide association studies (GWAS) have been crucial for the identification of loci associated with sleep traits and disorders, the method itself does not directly uncover the underlying causal variants and corresponding effector genes. The overwhelming majority of such variants reside in non-coding regions and are therefore presumed to impact the activity of cis-regulatory elements, such as enhancers. Our previously reported 'variant-to-gene mapping' effort in human induced pluripotent stem cell (iPSC)-derived neural progenitor cells (NPCs), combined with validation in both Drosophila and zebrafish, implicated PIG-Q as a functionally relevant gene at the insomnia 'WDR90' locus. However, importantly that effort did not characterize the corresponding underlying causal variant at this GWAS signal. Specifically, our genome-wide ATAC-seq and high-resolution promoter-focused Capture C datasets generated in this cell setting brought our attention to a shortlist of three tightly neighboring single nucleotide polymorphisms (SNPs) in strong linkage disequilibrium in a candidate intronic enhancer region of WDR90 that contacted the open PIG-Q promoter. The objective of this study was to investigate the influence of the proxy SNPs collectively and then individually on PIG-Q modulation and to pinpoint the causal "regulatory" variant among the three SNPs. Starting at a gross level perturbation, deletion of the entire region harboring all three SNPs in human iPSC-derived neural progenitor cells via CRISPR-Cas9 editing and subsequent RNA sequencing revealed expression changes in specific PIG-Q transcripts. Results from more refined individual luciferase reporter assays for each of the three SNPs in iPSCs revealed that the intronic region with the rs3752495 risk allele induced a ~2.5-fold increase in luciferase expression (n=10). Importantly, rs3752495 also exhibited an allele specific effect, with the risk allele increasing the luciferase expression by ~2-fold compared to the non-risk allele. In conclusion, our variant-to-function approach and subsequent in vitro validation implicates rs3752495 as a causal insomnia risk variant embedded at the WDR90-PIG-Q locus.
Collapse
Affiliation(s)
- Shilpa Sonti
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Sheridan H Littleton
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Matthew C Pahl
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Amber J Zimmerman
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine University of Pennsylvania Perelman School of Medicine Philadelphia PA USA
| | - Justin Palermo
- Department of Biology, Texas A&M University, College Station, TX, USA
| | - Chiara Lasconi
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Elizabeth B Brown
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - James A Pippin
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Andrew D Wells
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Fusun Doldur-Balli
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Allan I Pack
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Phillip R Gehrman
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Alex C Keene
- Department of Biology, Texas A&M University, College Station, TX, USA
| | - S F A Grant
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Divisions of Human Genetics and Endocrinology & Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| |
Collapse
|
44
|
Camera F, Romero-Camarero I, Revell BH, Amaral FM, Sinclair OJ, Simeoni F, Wiseman DH, Stojic L, Somervaille TC. Differentiation block in acute myeloid leukemia regulated by intronic sequences of FTO. iScience 2023; 26:107319. [PMID: 37539037 PMCID: PMC10393733 DOI: 10.1016/j.isci.2023.107319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 05/23/2023] [Accepted: 07/04/2023] [Indexed: 08/05/2023] Open
Abstract
Iroquois transcription factor gene IRX3 is highly expressed in 20-30% of acute myeloid leukemia (AML) and contributes to the pathognomonic differentiation block. Intron 8 FTO sequences ∼220kB downstream of IRX3 exhibit histone acetylation, DNA methylation, and contacts with the IRX3 promoter, which correlate with IRX3 expression. Deletion of these intronic elements confirms a role in positively regulating IRX3. RNAseq revealed long non-coding (lnc) transcripts arising from this locus. FTO-lncAML knockdown (KD) induced differentiation of AML cells, loss of clonogenic activity, and reduced FTO intron 8:IRX3 promoter contacts. While both FTO-lncAML KD and IRX3 KD induced differentiation, FTO-lncAML but not IRX3 KD led to HOXA downregulation suggesting transcript activity in trans. FTO-lncAMLhigh AML samples expressed higher levels of HOXA and lower levels of differentiation genes. Thus, a regulatory module in FTO intron 8 consisting of clustered enhancer elements and a long non-coding RNA is active in human AML, impeding myeloid differentiation.
Collapse
Affiliation(s)
- Francesco Camera
- Leukaemia Biology Laboratory, Cancer Research UK Manchester Institute, The University of Manchester, The Oglesby Cancer Research Centre Building, 555 Wilmslow Road, M20 4GJ Manchester, UK
| | - Isabel Romero-Camarero
- Leukaemia Biology Laboratory, Cancer Research UK Manchester Institute, The University of Manchester, The Oglesby Cancer Research Centre Building, 555 Wilmslow Road, M20 4GJ Manchester, UK
| | - Bradley H. Revell
- Leukaemia Biology Laboratory, Cancer Research UK Manchester Institute, The University of Manchester, The Oglesby Cancer Research Centre Building, 555 Wilmslow Road, M20 4GJ Manchester, UK
| | - Fabio M.R. Amaral
- Leukaemia Biology Laboratory, Cancer Research UK Manchester Institute, The University of Manchester, The Oglesby Cancer Research Centre Building, 555 Wilmslow Road, M20 4GJ Manchester, UK
| | - Oliver J. Sinclair
- Leukaemia Biology Laboratory, Cancer Research UK Manchester Institute, The University of Manchester, The Oglesby Cancer Research Centre Building, 555 Wilmslow Road, M20 4GJ Manchester, UK
| | - Fabrizio Simeoni
- Leukaemia Biology Laboratory, Cancer Research UK Manchester Institute, The University of Manchester, The Oglesby Cancer Research Centre Building, 555 Wilmslow Road, M20 4GJ Manchester, UK
| | - Daniel H. Wiseman
- Epigenetics of Haematopoiesis Group, Oglesby Cancer Research Building, The University of Manchester, M20 4GJ Manchester, UK
| | - Lovorka Stojic
- Centre for Cancer Cell and Molecular Biology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, EC1M 6BQ London, UK
| | - Tim C.P. Somervaille
- Leukaemia Biology Laboratory, Cancer Research UK Manchester Institute, The University of Manchester, The Oglesby Cancer Research Centre Building, 555 Wilmslow Road, M20 4GJ Manchester, UK
| |
Collapse
|
45
|
Zhang J, Wei J, Sun R, Sheng H, Yin K, Pan Y, Jimenez R, Chen S, Cui XL, Zou Z, Yue Z, Emch MJ, Hawse JR, Wang L, He HH, Xia S, Han B, He C, Huang H. A lncRNA from the FTO locus acts as a suppressor of the m 6A writer complex and p53 tumor suppression signaling. Mol Cell 2023; 83:2692-2708.e7. [PMID: 37478845 PMCID: PMC10427207 DOI: 10.1016/j.molcel.2023.06.024] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 04/23/2023] [Accepted: 06/21/2023] [Indexed: 07/23/2023]
Abstract
N6-methyladenosine (m6A) of mRNAs modulated by the METTL3-METTL14-WTAP-RBM15 methyltransferase complex and m6A demethylases such as FTO play important roles in regulating mRNA stability, splicing, and translation. Here, we demonstrate that FTO-IT1 long noncoding RNA (lncRNA) was upregulated and positively correlated with poor survival of patients with wild-type p53-expressing prostate cancer (PCa). m6A RIP-seq analysis revealed that FTO-IT1 knockout increased mRNA m6A methylation of a subset of p53 transcriptional target genes (e.g., FAS, TP53INP1, and SESN2) and induced PCa cell cycle arrest and apoptosis. We further showed that FTO-IT1 directly binds RBM15 and inhibits RBM15 binding, m6A methylation, and stability of p53 target mRNAs. Therapeutic depletion of FTO-IT1 restored mRNA m6A level and expression of p53 target genes and inhibited PCa growth in mice. Our study identifies FTO-IT1 lncRNA as a bona fide suppressor of the m6A methyltransferase complex and p53 tumor suppression signaling and nominates FTO-IT1 as a potential therapeutic target of cancer.
Collapse
Affiliation(s)
- Jianong Zhang
- Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA; Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100 Haining Road, Hongkou District, Shanghai 200080, China.
| | - Jiangbo Wei
- Department of Chemistry, Department of Biochemistry and Molecular Biology, and Institute for Biophysical Dynamics, The University of Chicago, 929 East 57th Street, Chicago, IL 60637, USA; Howard Hughes Medical Institute, The University of Chicago, 929 East 57th Street, Chicago, IL 60637, USA
| | - Rui Sun
- Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Haoyue Sheng
- Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Kai Yin
- Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA; Department of General Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang 212002, China
| | - Yunqian Pan
- Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Rafael Jimenez
- Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
| | - Sujun Chen
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 1L7, Canada
| | - Xiao-Long Cui
- Department of Chemistry, Department of Biochemistry and Molecular Biology, and Institute for Biophysical Dynamics, The University of Chicago, 929 East 57th Street, Chicago, IL 60637, USA; Howard Hughes Medical Institute, The University of Chicago, 929 East 57th Street, Chicago, IL 60637, USA
| | - Zhongyu Zou
- Department of Chemistry, Department of Biochemistry and Molecular Biology, and Institute for Biophysical Dynamics, The University of Chicago, 929 East 57th Street, Chicago, IL 60637, USA; Howard Hughes Medical Institute, The University of Chicago, 929 East 57th Street, Chicago, IL 60637, USA
| | - Zhiying Yue
- Precision Research Center for Refractory Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 201620, China
| | - Michael J Emch
- Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - John R Hawse
- Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Liguo Wang
- Department of Computation Biology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
| | - Housheng Hansen He
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 1L7, Canada
| | - Shujie Xia
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100 Haining Road, Hongkou District, Shanghai 200080, China
| | - Bangmin Han
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100 Haining Road, Hongkou District, Shanghai 200080, China
| | - Chuan He
- Department of Chemistry, Department of Biochemistry and Molecular Biology, and Institute for Biophysical Dynamics, The University of Chicago, 929 East 57th Street, Chicago, IL 60637, USA; Howard Hughes Medical Institute, The University of Chicago, 929 East 57th Street, Chicago, IL 60637, USA.
| | - Haojie Huang
- Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.
| |
Collapse
|
46
|
Arruda AL, Hartley A, Katsoula G, Smith GD, Morris AP, Zeggini E. Genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis. Am J Hum Genet 2023; 110:1304-1318. [PMID: 37433298 PMCID: PMC10432145 DOI: 10.1016/j.ajhg.2023.06.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 06/16/2023] [Accepted: 06/20/2023] [Indexed: 07/13/2023] Open
Abstract
Multimorbidity is a rising public health challenge with important implications for health management and policy. The most common multimorbidity pattern is the combination of cardiometabolic and osteoarticular diseases. Here, we study the genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis. We find genome-wide genetic correlation between the two diseases and robust evidence for association-signal colocalization at 18 genomic regions. We integrate multi-omics and functional information to resolve the colocalizing signals and identify high-confidence effector genes, including FTO and IRX3, which provide proof-of-concept insights into the epidemiologic link between obesity and both diseases. We find enrichment for lipid metabolism and skeletal formation pathways for signals underpinning the knee and hip osteoarthritis comorbidities with type 2 diabetes, respectively. Causal inference analysis identifies complex effects of tissue-specific gene expression on comorbidity outcomes. Our findings provide insights into the biological basis for the type 2 diabetes-osteoarthritis disease co-occurrence.
Collapse
Affiliation(s)
- Ana Luiza Arruda
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, 85764 Neuherberg, Germany; Munich School of Data Science, Helmholtz Zentrum München - German Research Center for Environmental Health, 85764 Neuherberg, Germany; Technical University of Munich (TUM), School of Medicine, Graduate School of Experimental Medicine, 81675 Munich, Germany
| | - April Hartley
- MRC Integrative Epidemiology Unit, University of Bristol, BS8 2BN Bristol, UK
| | - Georgia Katsoula
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, 85764 Neuherberg, Germany; Technical University of Munich (TUM), School of Medicine, Graduate School of Experimental Medicine, 81675 Munich, Germany
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, BS8 2BN Bristol, UK
| | - Andrew P Morris
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, 85764 Neuherberg, Germany; Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, M13 9PT Manchester, UK
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, 85764 Neuherberg, Germany; TUM School of Medicine, Technical University Munich and Klinikum Rechts der Isar, 81675 Munich, Germany.
| |
Collapse
|
47
|
Zhang Z, Chen N, Yin N, Liu R, He Y, Li D, Tong M, Gao A, Lu P, Zhao Y, Li H, Zhang J, Zhang D, Gu W, Hong J, Wang W, Qi L, Ning G, Wang J. The rs1421085 variant within FTO promotes brown fat thermogenesis. Nat Metab 2023; 5:1337-1351. [PMID: 37460841 DOI: 10.1038/s42255-023-00847-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Accepted: 06/14/2023] [Indexed: 08/06/2023]
Abstract
One lead genetic risk signal of obesity-the rs1421085 T>C variant within the FTO gene-is reported to be functional in vitro but lacks evidence at an organism level. Here we recapitulate the homologous human variant in mice with global and brown adipocyte-specific variant knock-in and reveal that mice carrying the C-allele show increased brown fat thermogenic capacity and resistance to high-fat diet-induced adiposity, whereas the obesity-related phenotypic changes are blunted at thermoneutrality. Both in vivo and in vitro data reveal that the C-allele in brown adipocytes enhances the transcription of the Fto gene, which is associated with stronger chromatin looping linking the enhancer region and Fto promoter. Moreover, FTO knockdown or inhibition effectively eliminates the increased thermogenic ability of brown adipocytes carrying the C-allele. Taken together, these findings identify rs1421085 T>C as a functional variant promoting brown fat thermogenesis.
Collapse
Affiliation(s)
- Zhiyin Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Na Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Nan Yin
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Ruixin Liu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Yang He
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Danjie Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Muye Tong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Aibo Gao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Peng Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Yuxiao Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Huabing Li
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junfang Zhang
- Laboratory of Aquacultural Resources and Utilization, Ministry of Education, College of Fishery and Life Science, Shanghai Ocean University, Shanghai, China
| | - Dan Zhang
- Shengjing Hospital of China Medical University, Shenyang, China
| | - Weiqiong Gu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Jie Hong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Jiqiu Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China.
| |
Collapse
|
48
|
Armendariz DA, Sundarrajan A, Hon GC. Breaking enhancers to gain insights into developmental defects. eLife 2023; 12:e88187. [PMID: 37497775 PMCID: PMC10374278 DOI: 10.7554/elife.88187] [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: 03/29/2023] [Accepted: 07/19/2023] [Indexed: 07/28/2023] Open
Abstract
Despite ground-breaking genetic studies that have identified thousands of risk variants for developmental diseases, how these variants lead to molecular and cellular phenotypes remains a gap in knowledge. Many of these variants are non-coding and occur at enhancers, which orchestrate key regulatory programs during development. The prevailing paradigm is that non-coding variants alter the activity of enhancers, impacting gene expression programs, and ultimately contributing to disease risk. A key obstacle to progress is the systematic functional characterization of non-coding variants at scale, especially since enhancer activity is highly specific to cell type and developmental stage. Here, we review the foundational studies of enhancers in developmental disease and current genomic approaches to functionally characterize developmental enhancers and their variants at scale. In the coming decade, we anticipate systematic enhancer perturbation studies to link non-coding variants to molecular mechanisms, changes in cell state, and disease phenotypes.
Collapse
Affiliation(s)
- Daniel A Armendariz
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
| | - Anjana Sundarrajan
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
| | - Gary C Hon
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
- Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, United States
- Lyda Hill Department of Bioinformatics, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, United States
| |
Collapse
|
49
|
Mansoor Q, Ismail M, Ali Ul Qader S. Linkage disequilibrium block single-nucleotide polymorphisms in FTO alpha ketoglutarate dependent dioxygenase gene inference with breast cancer and Type II diabetes in Pakistani female population. PLoS One 2023; 18:e0288934. [PMID: 37471425 PMCID: PMC10358933 DOI: 10.1371/journal.pone.0288934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 07/07/2023] [Indexed: 07/22/2023] Open
Abstract
Breast Cancer and Diabetes Mellitus are top ranked non-communicable life threatening diseases concerned in South Asia. The growing scientific clues witness the involvement of genetic variations which readily serve as risk factors for the disease onset. Comprehending the association of genetic predictors and risk factors in the conserved genome regions can help reveal underlying disease genetics and identify the sustained druggable targets. The present study aims to identify discrete inference of FTO alpha-ketoglutarate dependent dioxygenase gene linkage disequilibrium block SNPs rs9940128 and rs9939609 as prognostic genetic elements in defining the disease course either as BrC or NIDDM in Pakistani population. Clinically abreast female Breast Cancer and Type II (Non-Insulin Dependent) Diabetes Mellitus cases with the healthy controls participated in the study. The genomic study was established on the DNA of cases and controls through Tetra primers ARMS PCR and PCR-RFLP; data were analyzed statistically to reach comprehensive scientific annotation. Breast Cancer incidence was high in post menopause women. Fretful cholesterol, triglycerides, hypertension, sugar profiles and high incidence in females was evident in Type II (Non-Insulin Dependent) Diabetes Mellitus. BMI and family history were meager factor for either of the diseases. FTO gene alpha-ketoglutarate dependent dioxygenase linkage disequilibrium block Single-Nucleotide Polymorphism rs9939609 and rs9940128 threating inference was significant in the cancer and diabetes subjects correspondingly. The conclusion indicates serious clinical derailments in breast cancer and Type II (Non-Insulin Dependent) Diabetes Mellitus auxiliary to disease complication in genetically risk bearing FTO alpha-ketoglutarate dependent dioxygenase gene haplotype/linkage disequilibrium block SNPs prevailing in the affected Pakistani population. These clinical and genetic indicators could decisively be adopted in health care practice to intervene the sky rising disease incidence.
Collapse
Affiliation(s)
- Qaisar Mansoor
- Department of Biochemistry, University of Karachi, Karachi, Pakistan
- Institute of Biomedical and Genetic Engineering (IBGE), Islamabad, Pakistan
| | - Muhammad Ismail
- Institute of Biomedical and Genetic Engineering (IBGE), Islamabad, Pakistan
| | - Shah Ali Ul Qader
- Department of Biochemistry, University of Karachi, Karachi, Pakistan
| |
Collapse
|
50
|
Oliveros W, Delfosse K, Lato DF, Kiriakopulos K, Mokhtaridoost M, Said A, McMurray BJ, Browning JW, Mattioli K, Meng G, Ellis J, Mital S, Melé M, Maass PG. Systematic characterization of regulatory variants of blood pressure genes. CELL GENOMICS 2023; 3:100330. [PMID: 37492106 PMCID: PMC10363820 DOI: 10.1016/j.xgen.2023.100330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 03/29/2023] [Accepted: 04/28/2023] [Indexed: 07/27/2023]
Abstract
High blood pressure (BP) is the major risk factor for cardiovascular disease. Genome-wide association studies have identified genetic variants for BP, but functional insights into causality and related molecular mechanisms lag behind. We functionally characterize 4,608 genetic variants in linkage with 135 BP loci in vascular smooth muscle cells and cardiomyocytes by massively parallel reporter assays. High densities of regulatory variants at BP loci (i.e., ULK4, MAP4, CFDP1, PDE5A) indicate that multiple variants drive genetic association. Regulatory variants are enriched in repeats, alter cardiovascular-related transcription factor motifs, and spatially converge with genes controlling specific cardiovascular pathways. Using heuristic scoring, we define likely causal variants, and CRISPR prime editing finally determines causal variants for KCNK9, SFXN2, and PCGF6, which are candidates for developing high BP. Our systems-level approach provides a catalog of functionally relevant variants and their genomic architecture in two trait-relevant cell lines for a better understanding of BP gene regulation.
Collapse
Affiliation(s)
- Winona Oliveros
- Life Sciences Department, Barcelona Supercomputing Center, 08034 Barcelona, Catalonia, Spain
| | - Kate Delfosse
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Daniella F. Lato
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Katerina Kiriakopulos
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Milad Mokhtaridoost
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Abdelrahman Said
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Brandon J. McMurray
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Jared W.L. Browning
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Kaia Mattioli
- Division of Genetics, Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Guoliang Meng
- Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - James Ellis
- Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Seema Mital
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Ted Rogers Centre for Heart Research, Toronto, ON M5G 1X8, Canada
- Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON M5G 0A4, Canada
| | - Marta Melé
- Life Sciences Department, Barcelona Supercomputing Center, 08034 Barcelona, Catalonia, Spain
| | - Philipp G. Maass
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| |
Collapse
|