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Lundin JI, Peters U, Hu Y, Ammous F, Avery CL, Benjamin EJ, Bis JC, Brody JA, Carlson C, Cushman M, Gignoux C, Guo X, Haessler J, Haiman C, Joehanes R, Kasela S, Kenny E, Lapalainien T, Levy D, Liu C, Liu Y, Loos RJ, Lu A, Matise T, North KE, Park SL, Ratliff SM, Reiner A, Rich SS, Rotter JI, Smith JA, Sotoodehnia N, Tracy R, Van den Berg D, Xu H, Ye T, Zhao W, Raffield LM, Kooperberg C. Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations. Epigenetics 2024; 19:2333668. [PMID: 38571307 PMCID: PMC10996836 DOI: 10.1080/15592294.2024.2333668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 03/17/2024] [Indexed: 04/05/2024] Open
Abstract
Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p < 1.2E-7). The downstream pathways affected by DNA methylation included the identification of IFI16 and IRF7 CpG-gene transcript pairs which contributed to the innate immune response gene enrichment pathway along with NLRC5, NOD2, and AIM2. Gene enrichment analysis also identified the nuclear factor-kappaB transcription pathway. Using two-sample Mendelian randomization (MR) we inferred methylation at three CpG sites as causal for CRP levels using both White and Black or African American MR instrument variables. Overall, we identified novel CpG sites and gene transcripts that could be valuable in understanding the specific cellular processes and pathogenic mechanisms involved in inflammation.
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Affiliation(s)
- Jessica I. Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Yao Hu
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Farah Ammous
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Christy L. Avery
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Emelia J. Benjamin
- Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston University School of Public Health, Boston, MA, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Chris Carlson
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Mary Cushman
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT, USA
| | - Chris Gignoux
- Interdisciplinary Quantitative Biology, University of Colorado, Boulder, CO, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jeff Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Chris Haiman
- Department of Environmental Medicine and Public Health, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, Bethesda, MD, USA
| | | | - Eimear Kenny
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, Bethesda, MD, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Yongmei Liu
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | - Ruth J.F. Loos
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ake Lu
- Department of Human Genetics, University of California LA, Los Angeles, CA, USA
| | - Tara Matise
- Department of Genetics, Rutgers University, New Brunswick, NJ, USA
| | - Kari E. North
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Sungshim L. Park
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Alex Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, and Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Harborview Medical Center, Seattle, WA, USA
| | - Russell Tracy
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
| | - David Van den Berg
- Department of Environmental Medicine and Public Health, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Huichun Xu
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ting Ye
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Wei Zhao
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - On Behalf of the PAGE Study
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston University School of Public Health, Boston, MA, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT, USA
- Interdisciplinary Quantitative Biology, University of Colorado, Boulder, CO, USA
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Environmental Medicine and Public Health, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, Bethesda, MD, USA
- New York Genome Center, New York, NY
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
- Department of Human Genetics, University of California LA, Los Angeles, CA, USA
- Department of Genetics, Rutgers University, New Brunswick, NJ, USA
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Epidemiology, School of Public Health, and Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
- Cardiovascular Health Research Unit, Harborview Medical Center, Seattle, WA, USA
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
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Baig MS, Barmpoutsi S, Bharti S, Weigert A, Hirani N, Atre R, Khabiya R, Sharma R, Sarup S, Savai R. Adaptor molecules mediate negative regulation of macrophage inflammatory pathways: a closer look. Front Immunol 2024; 15:1355012. [PMID: 38482001 PMCID: PMC10933033 DOI: 10.3389/fimmu.2024.1355012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 01/22/2024] [Indexed: 04/13/2024] Open
Abstract
Macrophages play a central role in initiating, maintaining, and terminating inflammation. For that, macrophages respond to various external stimuli in changing environments through signaling pathways that are tightly regulated and interconnected. This process involves, among others, autoregulatory loops that activate and deactivate macrophages through various cytokines, stimulants, and other chemical mediators. Adaptor proteins play an indispensable role in facilitating various inflammatory signals. These proteins are dynamic and flexible modulators of immune cell signaling and act as molecular bridges between cell surface receptors and intracellular effector molecules. They are involved in regulating physiological inflammation and also contribute significantly to the development of chronic inflammatory processes. This is at least partly due to their involvement in the activation and deactivation of macrophages, leading to changes in the macrophages' activation/phenotype. This review provides a comprehensive overview of the 20 adaptor molecules and proteins that act as negative regulators of inflammation in macrophages and effectively suppress inflammatory signaling pathways. We emphasize the functional role of adaptors in signal transduction in macrophages and their influence on the phenotypic transition of macrophages from pro-inflammatory M1-like states to anti-inflammatory M2-like phenotypes. This endeavor mainly aims at highlighting and orchestrating the intricate dynamics of adaptor molecules by elucidating the associated key roles along with respective domains and opening avenues for therapeutic and investigative purposes in clinical practice.
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Affiliation(s)
- Mirza S. Baig
- Department of Biosciences and Biomedical Engineering (BSBE), Indian Institute of Technology Indore (IITI), Indore, India
| | - Spyridoula Barmpoutsi
- Lung Microenvironmental Niche in Cancerogenesis, Institute for Lung Health (ILH), Justus Liebig University, Giessen, Germany
- Max Planck Institute for Heart and Lung Research, Member of the German Center for Lung Research (DZL), Member of the Cardio-Pulmonary Institute (CPI), Bad Nauheim, Germany
| | - Shreya Bharti
- Department of Biosciences and Biomedical Engineering (BSBE), Indian Institute of Technology Indore (IITI), Indore, India
| | - Andreas Weigert
- Institute of Biochemistry I, Faculty of Medicine, Goethe University Frankfurt, Frankfurt, Germany
- Frankfurt Cancer Institute (FCI), Goethe University Frankfurt, Frankfurt, Germany
| | - Nik Hirani
- MRC Centre for Inflammation Research, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Rajat Atre
- Department of Biosciences and Biomedical Engineering (BSBE), Indian Institute of Technology Indore (IITI), Indore, India
| | - Rakhi Khabiya
- Department of Biosciences and Biomedical Engineering (BSBE), Indian Institute of Technology Indore (IITI), Indore, India
| | - Rahul Sharma
- Department of Biosciences and Biomedical Engineering (BSBE), Indian Institute of Technology Indore (IITI), Indore, India
| | - Shivmuni Sarup
- Department of Biosciences and Biomedical Engineering (BSBE), Indian Institute of Technology Indore (IITI), Indore, India
| | - Rajkumar Savai
- Lung Microenvironmental Niche in Cancerogenesis, Institute for Lung Health (ILH), Justus Liebig University, Giessen, Germany
- Max Planck Institute for Heart and Lung Research, Member of the German Center for Lung Research (DZL), Member of the Cardio-Pulmonary Institute (CPI), Bad Nauheim, Germany
- Frankfurt Cancer Institute (FCI), Goethe University Frankfurt, Frankfurt, Germany
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Yang S, Kim SH, Kang M, Joo JY. Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges. Arch Pharm Res 2023:10.1007/s12272-023-01450-5. [PMID: 37261600 DOI: 10.1007/s12272-023-01450-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 05/26/2023] [Indexed: 06/02/2023]
Abstract
The relevant study of transcriptome-wide variations and neurological disorders in the evolved field of genomic data science is on the rise. Deep learning has been highlighted utilizing algorithms on massive amounts of data in a human-like manner, and is expected to predict the dependency or druggability of hidden mutations within the genome. Enormous mutational variants in coding and noncoding transcripts have been discovered along the genome by far, despite of the fine-tuned genetic proofreading machinery. These variants could be capable of inducing various pathological conditions, including neurological disorders, which require lifelong care. Several limitations and questions emerge, including the use of conventional processes via limited patient-driven sequence acquisitions and decoding-based inferences as well as how rare variants can be deduced as a population-specific etiology. These puzzles require harnessing of advanced systems for precise disease prediction, drug development and drug applications. In this review, we summarize the pathophysiological discoveries of pathogenic variants in both coding and noncoding transcripts in neurological disorders, and the current advantage of deep learning applications. In addition, we discuss the challenges encountered and how to outperform them with advancing interpretation.
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Affiliation(s)
- Sumin Yang
- Department of Pharmacy, College of Pharmacy, Hanyang University, Rm 407, Bldg.42, 55 Hanyangdaehak-Ro, Sangnok-Gu Ansan, Ansan, Gyeonggi-Do, 15588, Republic of Korea
| | - Sung-Hyun Kim
- Department of Pharmacy, College of Pharmacy, Hanyang University, Rm 407, Bldg.42, 55 Hanyangdaehak-Ro, Sangnok-Gu Ansan, Ansan, Gyeonggi-Do, 15588, Republic of Korea
| | - Mingon Kang
- Department of Computer Science, University of Nevada, Las Vegas, NV, 89154, USA
| | - Jae-Yeol Joo
- Department of Pharmacy, College of Pharmacy, Hanyang University, Rm 407, Bldg.42, 55 Hanyangdaehak-Ro, Sangnok-Gu Ansan, Ansan, Gyeonggi-Do, 15588, Republic of Korea.
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