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Luciano C, Fernando DD, Lucia Z, Elvira I, Romano D, Rebecca C, Alberto B, Francesco R, Maria DBA, Luca P, Irene C, Sara DM, Antonella F, Veronica B, Michela GZ, Nicole BG, Carlo G, Gianfranco P, Davide G. Epigenetic patterns, accelerated biological aging, and enhanced epigenetic drift detected 6 months following COVID-19 infection: insights from a genome-wide DNA methylation study. Clin Epigenetics 2024; 16:112. [PMID: 39164752 PMCID: PMC11337605 DOI: 10.1186/s13148-024-01724-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Accepted: 08/08/2024] [Indexed: 08/22/2024] Open
Abstract
BACKGROUND The epigenetic status of patients 6-month post-COVID-19 infection remains largely unexplored. The existence of long-COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), suggests potential long-term changes. Long-COVID includes symptoms like fatigue, neurological issues, and organ-related problems, regardless of initial infection severity. The mechanisms behind long-COVID are unclear, but virus-induced epigenetic changes could play a role. METHODS AND RESULTS Our study explores the lasting epigenetic impacts of SARS-CoV-2 infection. We analyzed genome-wide DNA methylation patterns in an Italian cohort of 96 patients 6 months after COVID-19 exposure, comparing them to 191 healthy controls. We identified 42 CpG sites with significant methylation differences (FDR < 0.05), primarily within CpG islands and gene promoters. Dysregulated genes highlighted potential links to glutamate/glutamine metabolism, which may be relevant to PASC symptoms. Key genes with potential significance to COVID-19 infection and long-term effects include GLUD1, ATP1A3, and ARRB2. Furthermore, Horvath's epigenetic clock showed a slight but significant age acceleration in post-COVID-19 patients. We also observed a substantial increase in stochastic epigenetic mutations (SEMs) in the post-COVID-19 group, implying potential epigenetic drift. SEM analysis identified 790 affected genes, indicating dysregulation in pathways related to insulin resistance, VEGF signaling, apoptosis, hypoxia response, T-cell activation, and endothelin signaling. CONCLUSIONS Our study provides valuable insights into the epigenetic consequences of COVID-19. Results suggest possible associations with accelerated aging, epigenetic drift, and the disruption of critical biological pathways linked to insulin resistance, immune response, and vascular health. Understanding these epigenetic changes could be crucial for elucidating the complex mechanisms behind long-COVID and developing targeted therapeutic interventions.
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Affiliation(s)
- Calzari Luciano
- Bioinformatics and Statistical Genomics Unit, IRCCS Istituto Auxologico Italiano, Cusano Milanino, Milan, Italy
| | - Dragani Davide Fernando
- Bioinformatics and Statistical Genomics Unit, IRCCS Istituto Auxologico Italiano, Cusano Milanino, Milan, Italy
| | - Zanotti Lucia
- Department of Cardiology, S. Luca Hospital, IRCCS, Istituto Auxologico Italiano, Milan, Italy
| | - Inglese Elvira
- Clinical Chemistry Unit, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Via Bassi 21, Pavia, Italy
| | - Danesi Romano
- Clinical Chemistry Unit, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milano, Milan, Italy
| | - Cavagnola Rebecca
- Department of Brain and Behavioral Sciences, University of Pavia, Via Bassi 21, Pavia, Italy
| | - Brusati Alberto
- Department of Brain and Behavioral Sciences, University of Pavia, Via Bassi 21, Pavia, Italy
| | - Ranucci Francesco
- Department of Brain and Behavioral Sciences, University of Pavia, Via Bassi 21, Pavia, Italy
| | - Di Blasio Anna Maria
- Molecular Biology Laboratory, IRCCS Istituto Auxologico Italiano, Cusano Milanino, Milan, Italy
| | - Persani Luca
- Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, Italy
- Department of Endocrine and Metabolic Diseases, Lab of Endocrine and Metabolic Research, San Luca Hospital, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Campi Irene
- Department of Endocrine and Metabolic Diseases, Lab of Endocrine and Metabolic Research, San Luca Hospital, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - De Martino Sara
- Consiglio Nazionale delle Ricerche (CNR) - IASI, Rome, Italy
| | | | - Barbi Veronica
- Laboratorio di Epigenetica, Istituti Clinici Scientifici Maugeri IRCCS, Via Maugeri 4, 27100, Pavia, Italy
| | - Gottardi Zamperla Michela
- Laboratorio di Epigenetica, Istituti Clinici Scientifici Maugeri IRCCS, Via Maugeri 4, 27100, Pavia, Italy
| | - Baldrighi Giulia Nicole
- Department of Brain and Behavioral Sciences, University of Pavia, Via Bassi 21, Pavia, Italy
| | - Gaetano Carlo
- Laboratorio di Epigenetica, Istituti Clinici Scientifici Maugeri IRCCS, Via Maugeri 4, 27100, Pavia, Italy
| | - Parati Gianfranco
- Department of Cardiology, S. Luca Hospital, IRCCS, Istituto Auxologico Italiano, Milan, Italy
- Department of Medicine and Surgery, University of Milan-Bicocca, Milan, Italy
| | - Gentilini Davide
- Bioinformatics and Statistical Genomics Unit, IRCCS Istituto Auxologico Italiano, Cusano Milanino, Milan, Italy.
- Department of Brain and Behavioral Sciences, University of Pavia, Via Bassi 21, Pavia, Italy.
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Markov Y, Levine M, Higgins-Chen AT. Reliable detection of stochastic epigenetic mutations and associations with cardiovascular aging. GeroScience 2024:10.1007/s11357-024-01191-3. [PMID: 38736015 DOI: 10.1007/s11357-024-01191-3] [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: 02/29/2024] [Accepted: 05/01/2024] [Indexed: 05/14/2024] Open
Abstract
Stochastic epigenetic mutations (SEMs) have been proposed as novel aging biomarkers to capture heterogeneity in age-related DNA methylation changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. Because SEMs are defined by their outlier status, it is critical to differentiate extreme values due to technical noise or data artifacts from those due to real biology. Using technical replicate data, we found SEM detection is not reliable: across 3 datasets, 24 to 39% of hypoSEM and 46 to 67% of hyperSEM are not shared between replicates. We identified factors influencing SEM reliability-including blood cell type composition, probe beta-value statistics, genomic location, and presence of SNPs. We used these factors in a training dataset to build a machine learning-based filter that removes unreliable SEMs, and found this filter enhances reliability in two independent validation datasets. We assessed associations between SEM loads and aging phenotypes in the Framingham Heart Study and discovered that associations with aging outcomes were in large part driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations were preserved after filtering out unreliable SEMs and were enhanced after adjusting for blood cell composition. Finally, we utilized these insights to formulate best practices for SEM detection and introduce a novel R package, SEMdetectR, which uses parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.
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Affiliation(s)
- Yaroslav Markov
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Morgan Levine
- Altos Labs, San Diego Institute of Sciences, San Diego, CA, USA
| | - Albert T Higgins-Chen
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA.
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Markov Y, Levine M, Higgins-Chen AT. Stochastic Epigenetic Mutations: Reliable Detection and Associations with Cardiovascular Aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.12.571149. [PMID: 38168247 PMCID: PMC10760000 DOI: 10.1101/2023.12.12.571149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Stochastic Epigenetic Mutations (SEMs) have been proposed as novel aging biomarkers that have the potential to capture heterogeneity in age-related DNA methylation (DNAme) changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide (CpG) sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. While individual SEMs are rarely consistent across subjects, the SEM load - the total number of SEMs - increases with age. However, given poor technical reliability of measurement for many DNA methylation sites, we posited that many outliers might represent technical noise. Our study of whole blood samples from 36 individuals, each measured twice, found that 23.3% of hypoSEM and 45.6% hyperSEM are not shared between replicates. This diminishes the reliability of SEM loads, where intraclass correlation coefficients are 0.96 for hypoSEM and 0.90 for hyperSEM. We linked SEM reliability to multiple factors, including blood cell type composition, probe beta-value statistics, and presence of SNPs. A machine learning approach, leveraging these factors, filtered unreliable SEMs, enhancing reliability in a separate dataset of technical replicates from 128 individuals. Analysis of the Framingham Heart Study confirmed previously reported SEM association with mortality and revealed novel connections to cardiovascular disease. We discover that associations with aging outcomes are primarily driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations are preserved after filtering out unreliable SEMs and are enhanced after adjusting for blood cell composition. Finally, we utilize these insights to formulate best practices for SEM detection and introduce a novel R package, SEMdetectR, which utilizes parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.
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Affiliation(s)
- Yaroslav Markov
- Program in Computational Biology & Bioinformatics, Yale Graduate School of Arts and Sciences, New Haven, CT, USA
| | - Morgan Levine
- Altos Labs, San Diego Institute of Sciences, San Diego, CA, USA
| | - Albert T Higgins-Chen
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
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Duarte Folle A, Flores M, Kusters C, Paul K, Del Rosario I, Zhang K, Ruiz C, Castro E, Bronstein J, Ritz B, Keener A. Ethnicity and Parkinson's Disease: Motor and Nonmotor Features and Disease Progression in Latino Patients Living in Rural California. J Gerontol A Biol Sci Med Sci 2023; 78:1258-1268. [PMID: 36645401 PMCID: PMC10329232 DOI: 10.1093/gerona/glad016] [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: 09/09/2022] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Parkinson's disease (PD) is the second most common neurodegenerative disorder among older adults worldwide. Currently, studies of PD progression rely primarily on White non-Latino (WNL) patients. Here, we compare clinical profiles and PD progression in Latino and WNL patients enrolled in a community-based study in rural Central California. METHOD PD patients within 5 years of diagnosis were identified from 3 counties between 2001 and 2015. During up to 3 visits, participants were examined by movement disorders specialists and interviewed. We analyzed cross-sectional differences in PD clinical features severity at each study visit and used linear mixed models and Cox proportional hazards models to compare motor, nonmotor, and disability progression longitudinally and to assess time to death in Latinos compared to WNL patients. RESULTS Of 775 patients included, 138 (18%) self-identified as Latino and presented with earlier age at diagnosis (63.6 vs 68.9) and death (78.6 vs 81.5) than WNL. Motor (hazard ratio [HR] = 1.17 [0.71, 1.94]) and nonmotor symptoms did not progress faster in Latino versus WNL patients after accounting for differences in baseline symptom severity. However, Latino patients progressed to disability stages according to Hoehn and Yahr faster than WNL (HR = 1.81 [1.11, 2.96]). Motor and nonmotor symptoms in Latino patients were also medically managed less well than in WNL. CONCLUSIONS Our PD study with a large proportion of Latino enrollees and progression data reveals disparities in clinical features and progression by ethnicity that may reflect healthcare access and structural socioeconomic disadvantages in Latino patients with PD.
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Affiliation(s)
- Aline Duarte Folle
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, California, USA
| | - Marie E S Flores
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, California, USA
- Altamed, Pico Rivera, California, USA
| | - Cynthia Kusters
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Kimberly C Paul
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Irish Del Rosario
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, California, USA
| | - Keren Zhang
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, California, USA
| | - Cristina Ruiz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, California, USA
| | - Emily Castro
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, California, USA
| | - Jeff Bronstein
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Beate Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, California, USA
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Adrienne M Keener
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
- Department of Neurology, Veterans Administration Greater Los Angeles Health Care System, Los Angeles, California, USA
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