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Fabian P, Blander G, Deehan R, Torkamani A, Nogal B. Causal impact of genetically-determined fish and fish oil intake on epigenetic age acceleration and related serum markers. Hum Genomics 2025; 19:61. [PMID: 40410862 PMCID: PMC12102828 DOI: 10.1186/s40246-025-00756-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 04/15/2025] [Indexed: 05/25/2025] Open
Abstract
BACKGROUND The interplay between diet and healthspan is a topic of great interest in biomedical research. Toward this end, consumption of marine omega-3 fatty acids is of particular significance, as reports suggest that diets focused on seafood can prolong the disease-free portion of the human lifespan. Fish consumption has also been linked to reduced biological aging as measured by epigenetic clocks, but there is no conclusive evidence of a causal relationship. Moreover, fish oils reduce triglycerides, and may affect other lipid profiles, as well as systemic inflammation. To investigate further, we used two-sample Mendelian randomization to investigate potential causality between fish intake and healthspan markers. METHODS Bidirectional Mendelian randomization was performed in the two-sample setting with publicly available GWAS summary statistics. GWAS data from the UK Biobank for oily fish consumption (n = 460,443) and fish oil supplementation (n = 461,384) were used as the primary exposures. First-generation epigenetic clocks Hannum age and intrinsic epigenetic age acceleration (IEAA), as well as second-generation clocks GrimAge and PhenoAge were collected from an independent dataset of individuals of European ancestry (n = [34,449-34,667]). Finally, data from the Integrative Epidemiology Unit database was used for serum proxies of lipidemia and systemic inflammation (n = [61,308-78,700]). Additional sensitivity analyses, such as reverse causation testing and the Cochran's Q test were performed for exposure-outcome pairs where the inverse variance weighted (IVW) method was significant (p-value < 0.05), and where the MR Egger method indicated an effect in the same direction as the IVW result. RESULTS We report that oily fish consumption appears to decrease PhenoAge acceleration (p < 0.0086), whereas fish oil supplementation appears to decrease GrimAge (p = 0.037). Both omega-3 exposures modify the epigenetic clocks in the expected negative, or age-decelerating, direction. For the serum biomarkers, we find evidence that fish oil consumption leads to a reduction in triglycerides (p = 0.004), although HDL and LDL were not significantly modified. Finally, we also detected a suggestive inverse relationship between oily fish consumption and hsCRP (p = 0.064). CONCLUSIONS Our analysis shows that consuming fish oil, whether through whole food or as a supplement, can have a rejuvenating impact as measured by PhenoAge and GrimAge acceleration. We have also provided evidence further linking fish oil intake and lower triglyceride levels. These results, based on robust MR-based analyses, emphasize the effectiveness of dietary choices in modifying emerging measures of healthspan.
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Affiliation(s)
- Paul Fabian
- InsideTracker, One Broadway, 14 th 10 Fl, Cambridge, MA, 02142, USA
| | - Gil Blander
- InsideTracker, One Broadway, 14 th 10 Fl, Cambridge, MA, 02142, USA
| | - Renee Deehan
- InsideTracker, One Broadway, 14 th 10 Fl, Cambridge, MA, 02142, USA
| | - Ali Torkamani
- The Scripps Translational Science Institute, The Scripps Research Institute, La Jolla, CA, 92037, USA
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Bartek Nogal
- InsideTracker, One Broadway, 14 th 10 Fl, Cambridge, MA, 02142, USA.
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037, USA.
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Jin B, Li Y, Li D, Jing C, Sheng Q. Causal associations between epigenetic age and thromboembolism: a bi-directional two-sample Mendelian randomization study. Clin Epigenetics 2025; 17:75. [PMID: 40325450 PMCID: PMC12051321 DOI: 10.1186/s13148-025-01875-3] [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: 01/16/2025] [Accepted: 04/08/2025] [Indexed: 05/07/2025] Open
Abstract
BACKGROUND Thromboembolism is one of the most prevalent cardiovascular conditions affecting the elder population. The associations between epigenetic aging and thromboembolism risks remain incompletely elucidated. Through Mendelian randomization (MR), this research seeks to assess the causal links between genetically determined epigenetic aging factors and thromboembolism. RESULTS Genetic variants were extracted from genome-wide association studies (GWAS) under stringent threshold as instrumental variables (IVs). Bi-directional two-sample MR analyses were conducted to determine the direction of causal associations. We employed the inverse variance weighted (IVW), weighted median, weighted mode and MR Egger to estimate the causal effect, with sensitivity analyses such as Cochran's Q tests, MR-PRESSO and leave-one-out performed to avoid potential heterogeneity and pleiotropy. Our MR analysis revealed a causal association between intrinsic epigenetic age acceleration and deep vein thrombosis of lower extremities (IVW: OR 0.963, 95% CI 0.934-0.992, P = 0.014), and between the genetically determined levels of plasminogen activator inhibitor-1 and other arterial embolism and thrombosis (IVW: OR 1.000, 95% CI 1.000-1.0005, P = 0.029). Causality was also identified between the genetically predicted levels of FGF23 and other arterial embolism and thrombosis (IVW: OR: 1.661, 95% CI 1.051-2.624, P = 0.029) and arterial embolism and thrombosis of lower extremity artery (IVW: OR 1.68, 95% CI 1.031-2.725, P = 0.037). Moreover, bi-directional MR showed reverse effects between portal vein thrombosis and PhenoAge (IVW: OR 0.871, 95% CI 0.765-0.992, P = 0.037) and between venous thromboembolism and GrimAge (IVW: OR 1.186, 95% CI 1.048-1.341, P = 0.007). Sensitivity analysis using Cochran's Q tests, MR-PRESSO and leave-one-out excluded the influence of heterogeneity, horizontal pleiotropy, and outliers. CONCLUSION Our results identified a causal association between genetically predicted epigenetic aging factors and thromboembolism. The findings highlight the necessity for further exploration into the underlying etiology of thromboembolism.
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Affiliation(s)
- Bowen Jin
- Department of Cardiovascular Surgery, Wuhan Asia Heart Hospital, Wuhan City, 430000, Hubei Province, China.
| | - Yunyan Li
- Department of Cardiovascular Surgery, Wuhan Asia Heart Hospital, Wuhan City, 430000, Hubei Province, China
| | - Dingyang Li
- Department of Cardiovascular Surgery, Wuhan Asia Heart Hospital, Wuhan City, 430000, Hubei Province, China
| | - Chi Jing
- Department of Cardiovascular Surgery, Wuhan Asia Heart Hospital, Wuhan City, 430000, Hubei Province, China
| | - Qunshan Sheng
- Department of Cardiovascular Surgery, Wuhan Asia Heart Hospital, Wuhan City, 430000, Hubei Province, China
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Zhao Z, Liang Y. Association between triglyceride-glucose index and phenotypic age acceleration: a cross-sectional study based on NHANES database. Front Physiol 2025; 16:1548690. [PMID: 40376115 PMCID: PMC12078276 DOI: 10.3389/fphys.2025.1548690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2024] [Accepted: 04/14/2025] [Indexed: 05/18/2025] Open
Abstract
Objective To investigate the association between triglyceride-glucose (TyG) index and phenotypic age acceleration (PhenoAgeAccel), given the emerging importance of biological aging as a health determinant and the role of insulin resistance in aging-related processes. Methods This cross-sectional study analyzed data from 13,291 adults aged ≥20 years in the National Health and Nutrition Examination Survey (1999-2010). The TyG index served as the exposure variable, calculated from fasting triglycerides and glucose levels. PhenoAgeAccel, derived from clinical biomarkers, was the outcome variable. Analyses adjusted for demographic, socioeconomic, and health-related covariates. Results A significant non-linear relationship was observed between TyG index and PhenoAgeAccel, with an inflection point at 9.60. In the fully adjusted model, each unit increase in TyG index was associated with 2.21 years increase in PhenoAgeAccel (95% CI: 1.99, 2.43). The association was stronger above the inflection point (β = 8.21, 95% CI: 7.59, 8.82) compared to below it (β = 0.56, 95% CI: 0.29, 0.83). Conclusion Higher TyG index levels are significantly associated with accelerated biological aging, particularly above a threshold of 9.60. These findings suggest the importance of metabolic health in biological aging processes and potential interventional strategies.
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Affiliation(s)
- Zhili Zhao
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
- West China School of Nursing, Sichuan University, Chengdu, China
| | - Yan Liang
- West China School of Nursing, Sichuan University, Chengdu, China
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
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Ayesh H, Nasser SA, Ferdinand KC, Carranza Leon BG. Sex-Specific Factors Influencing Obesity in Women: Bridging the Gap Between Science and Clinical Practice. Circ Res 2025; 136:594-605. [PMID: 40080532 DOI: 10.1161/circresaha.124.325535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2024] [Revised: 01/21/2025] [Accepted: 01/21/2025] [Indexed: 03/15/2025]
Abstract
Obesity in women is a significant public health issue with serious implications for cardiovascular-kidney-metabolic syndrome and cardiovascular disease. This complex challenge is influenced by physiological, hormonal, socioeconomic, and cultural factors. Women face unique weight management challenges due to hormonal changes during pregnancy, perimenopause, and menopause, which affect fat distribution and increase cardiovascular-kidney-metabolic syndrome risk. Current clinical guidelines often overlook these sex-specific factors, potentially limiting the effectiveness of obesity management strategies in women. This review explores the sex-specific aspects of obesity's pathophysiology, epidemiological trends, and associated comorbidities, focusing on cardiovascular and metabolic complications. This review synthesizes literature on obesity in women, emphasizing sex-specific factors influencing its development and progression. It examines the limitations of body mass index as an obesity measure and explores alternative classification methods. Additionally it investigates the relationship between obesity and comorbidities such as diabetes, hypertension, and dyslipidemia, with a focus on postmenopausal women. Obesity in women is linked to increased risks of cardiovascular-kidney-metabolic syndrome and cardiovascular disease. Hormonal fluctuations throughout life contribute to weight gain and fat distribution patterns specific to women, increasing cardiovascular disease risk. Effective obesity management strategies in women must account for these sex-specific variations. Postmenopausal women are particularly affected by obesity-related complications. Lifestyle interventions, pharmacotherapy, and bariatric surgery have shown efficacy in weight management, though success rates vary. Addressing obesity in women requires a comprehensive approach that considers sex-specific physiological factors, life-stage challenges, and sociocultural barriers. Integrating precision medicine and emerging therapies offers potential for more personalized and effective interventions. Personalized strategies that consider women's biological and life-stage challenges can enhance obesity management and improve cardiovascular outcomes. Future research and clinical practice should focus on developing tailored strategies that address women's unique vulnerabilities to obesity and its associated health risks and on validating sex-specific interventions to improve obesity management in women.
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Affiliation(s)
- Hazem Ayesh
- Deaconess Clinic Endocrinology, Deaconess Health System, Evansville, IN (H.A.)
| | - Samar A Nasser
- Department of Clinical Research and Leadership, School of Medicine and Health Sciences, The George Washington University, Washington, DC (S.A.N.)
| | - Keith C Ferdinand
- Section of Cardiology, Tulane University School of Medicine, New Orleans, LA (K.C.F.)
| | - Barbara Gisella Carranza Leon
- Division of Diabetes, Endocrinology and Metabolism, Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, TN (B.G.C.L.)
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Ediriweera MK, Gayashani Sandamalika WM. The epigenetic impact of fatty acids as DNA methylation modulators. Drug Discov Today 2025; 30:104277. [PMID: 39710232 DOI: 10.1016/j.drudis.2024.104277] [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: 07/31/2024] [Revised: 11/12/2024] [Accepted: 12/17/2024] [Indexed: 12/24/2024]
Abstract
DNA methylation is a key epigenetic mechanism that regulates gene expression. Fatty acids, the building blocks of many essential lipids, play a crucial role in various biological events. Aberrant acetylation and methylation profiles are linked to a number of non-communicable diseases. Various fatty acids have been identified as potential 'epi-drugs' because of their ability to correct aberrant acetylation and methylation profiles in a number of non-communicable diseases, enhancing the value of their biochemical properties. This review summarizes the effects of selected saturated and unsaturated fatty acids and fatty-acid-rich food items on disease-associated DNA methylation profiles, aiming to justify the classification of fatty acids as DNA methylation modulators.
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Affiliation(s)
- Meran Keshawa Ediriweera
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Colombo, Kynsey Road, Colombo 8, Sri Lanka.
| | - W M Gayashani Sandamalika
- Department of Aquaculture and Fisheries, Faculty of Livestock, Fisheries and Nutrition, Wayamba University of Sri Lanka, Sri Lanka
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Russo L, Babboni S, Andreassi MG, Daher J, Canale P, Del Turco S, Basta G. Treating Metabolic Dysregulation and Senescence by Caloric Restriction: Killing Two Birds with One Stone? Antioxidants (Basel) 2025; 14:99. [PMID: 39857433 PMCID: PMC11763027 DOI: 10.3390/antiox14010099] [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: 12/20/2024] [Revised: 01/07/2025] [Accepted: 01/14/2025] [Indexed: 01/27/2025] Open
Abstract
Cellular senescence is a state of permanent cell cycle arrest accompanied by metabolic activity and characteristic phenotypic changes. This process is crucial for developing age-related diseases, where excessive calorie intake accelerates metabolic dysfunction and aging. Overnutrition disturbs key metabolic pathways, including insulin/insulin-like growth factor signaling (IIS), the mammalian target of rapamycin (mTOR), and AMP-activated protein kinase. The dysregulation of these pathways contributes to insulin resistance, impaired autophagy, exacerbated oxidative stress, and mitochondrial dysfunction, further enhancing cellular senescence and systemic metabolic derangements. On the other hand, dysfunctional endothelial cells and adipocytes contribute to systemic inflammation, reduced nitric oxide production, and altered lipid metabolism. Numerous factors, including extracellular vesicles, mediate pathological communication between the vascular system and adipose tissue, amplifying metabolic imbalances. Meanwhile, caloric restriction (CR) emerges as a potent intervention to counteract overnutrition effects, improve mitochondrial function, reduce oxidative stress, and restore metabolic balance. CR modulates pathways such as IIS, mTOR, and sirtuins, enhancing glucose and lipid metabolism, reducing inflammation, and promoting autophagy. CR can extend the health span and mitigate age-related diseases by delaying cellular senescence and improving healthy endothelial-adipocyte interactions. This review highlights the crosstalk between endothelial cells and adipocytes, emphasizing CR potential in counteracting overnutrition-induced senescence and restoring vascular homeostasis.
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Affiliation(s)
- Lara Russo
- Institute of Clinical Physiology, National Research Council, Via Moruzzi 1, 56124 Pisa, Italy; (L.R.); (S.B.); (M.G.A.); (P.C.); (G.B.)
| | - Serena Babboni
- Institute of Clinical Physiology, National Research Council, Via Moruzzi 1, 56124 Pisa, Italy; (L.R.); (S.B.); (M.G.A.); (P.C.); (G.B.)
| | - Maria Grazia Andreassi
- Institute of Clinical Physiology, National Research Council, Via Moruzzi 1, 56124 Pisa, Italy; (L.R.); (S.B.); (M.G.A.); (P.C.); (G.B.)
| | - Jalil Daher
- Department of Biology, Faculty of Arts and Sciences, University of Balamand, El-Koura 100, Lebanon;
| | - Paola Canale
- Institute of Clinical Physiology, National Research Council, Via Moruzzi 1, 56124 Pisa, Italy; (L.R.); (S.B.); (M.G.A.); (P.C.); (G.B.)
| | - Serena Del Turco
- Institute of Clinical Physiology, National Research Council, Via Moruzzi 1, 56124 Pisa, Italy; (L.R.); (S.B.); (M.G.A.); (P.C.); (G.B.)
| | - Giuseppina Basta
- Institute of Clinical Physiology, National Research Council, Via Moruzzi 1, 56124 Pisa, Italy; (L.R.); (S.B.); (M.G.A.); (P.C.); (G.B.)
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Huang Y, Zhou A, Huang Y, Wang Y, Liu X, Liu X. Association between phenotypic age and mortality risk in individuals with obesity: a retrospective cohort study. Front Public Health 2024; 12:1505066. [PMID: 39717032 PMCID: PMC11663737 DOI: 10.3389/fpubh.2024.1505066] [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: 10/02/2024] [Accepted: 11/25/2024] [Indexed: 12/25/2024] Open
Abstract
Objective This study investigates the association between phenotypic age acceleration (PAA) and all-cause and cause-specific mortality in obese individuals. Methods Data were drawn from the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018, including 9,925 obese adults (BMI ≥ 30 kg/m2). PAA, defined as phenotypic age exceeding chronological age, was assessed using clinical biomarkers. Kaplan-Meier survival analysis and Cox proportional hazards models were used to assess the relationship between PAA and all-cause, cardiovascular, and cancer mortality, adjusting for covariates such as age, gender, race, lifestyle, and health status. Subgroup and sensitivity analyses were performed to ensure the robustness of the findings. Results During a median follow-up of 10.6 years, 1,537 deaths were recorded, including 419 from cardiovascular disease and 357 from cancer. PAA was significantly associated with all-cause mortality (HR = 1.84, 95% CI: 1.64-2.06), cardiovascular mortality (HR = 1.86, 95% CI: 1.50-2.31), and cancer mortality (HR = 1.47, 95% CI: 1.17-1.85). These associations remained significant after adjusting for multiple variables, and sensitivity analyses confirmed the robustness of the results. Conclusion PAA is an independent predictor of all-cause, cardiovascular, and cancer mortality in obese individuals. This study highlights the importance of PAA in mortality risk assessment and health management in the obese population.
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Affiliation(s)
- Yingxuan Huang
- Department of Gastroenterology, First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Apei Zhou
- Department of Gastroenterology, First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Yisen Huang
- Department of Gastroenterology, First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Yubin Wang
- Department of Gastroenterology, First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Xiaobo Liu
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Xiaoqiang Liu
- Department of Gastroenterology, First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, Fujian, China
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Glaser S, Kretzmer H, Kolassa I, Schlesner M, Fischer A, Fenske I, Siebert R, Ammerpohl O. Navigating Illumina DNA methylation data: biology versus technical artefacts. NAR Genom Bioinform 2024; 6:lqae181. [PMID: 39703427 PMCID: PMC11655293 DOI: 10.1093/nargab/lqae181] [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: 07/09/2024] [Revised: 11/25/2024] [Accepted: 12/05/2024] [Indexed: 12/21/2024] Open
Abstract
Illumina-based BeadChip arrays have revolutionized genome-wide DNA methylation profiling, pushing it into diagnostics. However, comprehensive quality assessment remains challenging within a wide range of available tissue materials and sample preparation methods. This study tackles two critical issues: differentiating between biological effects and technical artefacts in suboptimal quality samples and the impact of the first sample on the Illumina-like normalization algorithm. We introduce three quality control scores based on global DNA methylation distribution (DB-Score), bin distance from copy number variation analysis (BIN-Score) and consistently methylated CpGs (CM-Score) that rely on biological features rather than internal array controls. These scores, designed to be adjustable for different analysis tools and sample cohort characteristics, were explored and benchmarked across independent cohorts. Additionally, we reveal deviations in beta values caused by different sample rankings with the Illumina-like normalization algorithm, verified these with whole-genome methylation sequencing data and showed effects on differential DNA methylation analysis. Our findings underscore the necessity of consistently utilizing a pre-defined normalization sample within the ranking process to boost reproducibility of the Illumina-like normalization algorithm. Overall, our study delivers valuable insights, practical recommendations and R functions designed to enhance reproducibility and quality assurance of DNA methylation analysis, particularly for challenging sample types.
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Affiliation(s)
- Selina Glaser
- Institute of Human Genetics, Ulm University and Ulm University Medical Center, Albert-Einstein-Allee 11, Ulm 89081, Germany
| | - Helene Kretzmer
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, Ihnestraße 63-73, Berlin 14195, Germany
- Digital Health Cluster, Hasso Plattner Institute for Digital Engineering, Digitial Engineering Faculty, University of Potdsdam, Prof.-Dr.-Helmert-Str. 2-3, Potsdam 14482, Germany
| | - Iris Tatjana Kolassa
- Clinical and Biological Psychology, Institute of Psychology and Education, Ulm University, Albert-Einstein-Allee 47, Ulm 89081, Germany
| | - Matthias Schlesner
- Biomedical Informatics, Data Mining and Data Analytics, Faculty of Applied Computer Science and Medical Faculty, University of Augsburg, Alter Postweg 101, Augsburg 86159, Germany
| | - Anja Fischer
- Institute of Human Genetics, Ulm University and Ulm University Medical Center, Albert-Einstein-Allee 11, Ulm 89081, Germany
| | - Isabell Fenske
- Institute of Human Genetics, Ulm University and Ulm University Medical Center, Albert-Einstein-Allee 11, Ulm 89081, Germany
| | - Reiner Siebert
- Institute of Human Genetics, Ulm University and Ulm University Medical Center, Albert-Einstein-Allee 11, Ulm 89081, Germany
| | - Ole Ammerpohl
- Institute of Human Genetics, Ulm University and Ulm University Medical Center, Albert-Einstein-Allee 11, Ulm 89081, Germany
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Cancello R, Vigna L, DI Maggio A, Capodaglio P, Bertoli S, Brunani A. Obesity prevention across the lifespan: assessing the efficacy of intervention studies and discussing future challenges. Minerva Endocrinol (Torino) 2024; 49:457-478. [PMID: 39382548 DOI: 10.23736/s2724-6507.24.04077-6] [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] [Indexed: 10/10/2024]
Abstract
INTRODUCTION Obesity is intricately linked with metabolic conditions that disrupt hormones and metabolism, often resulting in weight-related challenges. Given the heightened mortality rates associated with cardiovascular and metabolic disorders linked to obesity, there is a pressing call to mobilize medical professionals, researchers, and policymakers towards advocating for healthy lifestyles and preventing obesity. Traditionally, obesity prevention and treatment have been viewed as separate endeavors, with prevention primarily falling under public health initiatives and treatment within the purview of clinicians. However, this division has led to significant healthcare costs without a substantial reduction in obesity rates. EVIDENCE ACQUISITION Our search encompassed published articles focused on prevention, excluding any mention of "treatment". Data was gathered from diverse sources including academic databases, government health agency websites like the CDC, research organizations, clinical trials registries, and public health campaigns. EVIDENCE SYNTHESIS Due to the diverse range of interventions (encompassing dietary modifications, physical activity promotion, policy initiatives, education, and community-based programs, either independently or in combination), and the variability in study design and population demographics, we conducted a narrative review to systematically present and critically analyze evidence on preventing overweight and obesity across different age groups. CONCLUSIONS Effectively addressing obesity prevention necessitates a comprehensive, multidisciplinary approach that establishes an environment where healthier choices are accessible and viable for all. This requires collaborative efforts between individuals, communities, healthcare providers, policymakers, and industries to institute enduring change. Furthermore, there remains a critical need for national and international guidelines tailored to age-related risk factors, paving the way for innovative precision medicine approaches centered on salutogenesis rather than pathogenesis.
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Affiliation(s)
- Raffaella Cancello
- Obesity Unit and Laboratory of Nutrition and Obesity Research, Department of Endocrine and Metabolic Diseases, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Luisella Vigna
- Obesity and Work Center, Occupational Medicine Unit-Clinica del Lavoro L. Devoto, Fondazione IRCCS Ca' Granda Maggiore Polyclinic Hospital, Milan, Italy
| | - Antonella DI Maggio
- Obesity and Work Center, Occupational Medicine Unit-Clinica del Lavoro L. Devoto, Fondazione IRCCS Ca' Granda Maggiore Polyclinic Hospital, Milan, Italy
| | - Paolo Capodaglio
- Laboratory of Biomechanics, Rehabilitation and Ergonomics, IRCCS Istituto Auxologico Italiano, Piancavallo, Verbania, Italy
- Department of Surgical Sciences, Physical Medicine and Rehabilitation, University of Turin, Turin, Italy
| | - Simona Bertoli
- Obesity Unit and Laboratory of Nutrition and Obesity Research, Department of Endocrine and Metabolic Diseases, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Amelia Brunani
- Laboratory of Biomechanics, Rehabilitation and Ergonomics, IRCCS Istituto Auxologico Italiano, Piancavallo, Verbania, Italy -
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Stein RA, Gomaa FE, Raparla P, Riber L. Now and then in eukaryotic DNA methylation. Physiol Genomics 2024; 56:741-763. [PMID: 39250426 DOI: 10.1152/physiolgenomics.00091.2024] [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: 07/01/2024] [Accepted: 09/06/2024] [Indexed: 09/11/2024] Open
Abstract
Since the mid-1970s, increasingly innovative methods to detect DNA methylation provided detailed information about its distribution, functions, and dynamics. As a result, new concepts were formulated and older ones were revised, transforming our understanding of the associated biology and catalyzing unprecedented advances in biomedical research, drug development, anthropology, and evolutionary biology. In this review, we discuss a few of the most notable advances, which are intimately intertwined with the study of DNA methylation, with a particular emphasis on the past three decades. Examples of these strides include elucidating the intricacies of 5-methylcytosine (5-mC) oxidation, which are at the core of the reversibility of this epigenetic modification; the three-dimensional structural characterization of eukaryotic DNA methyltransferases, which offered insights into the mechanisms that explain several disease-associated mutations; a more in-depth understanding of DNA methylation in development and disease; the possibility to learn about the biology of extinct species; the development of epigenetic clocks and their use to interrogate aging and disease; and the emergence of epigenetic biomarkers and therapies.
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Affiliation(s)
- Richard A Stein
- Department of Chemical and Biomolecular Engineering, NYU Tandon School of Engineering, Brooklyn, New York, United States
| | - Faris E Gomaa
- Department of Chemical and Biomolecular Engineering, NYU Tandon School of Engineering, Brooklyn, New York, United States
| | - Pranaya Raparla
- Department of Chemical and Biomolecular Engineering, NYU Tandon School of Engineering, Brooklyn, New York, United States
| | - Leise Riber
- Department of Plant and Environmental Sciences, University of Copenhagen, Frederiksberg, Denmark
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Guimarães JR, de Souza BF, Filho JMCV, Damascena LCL, Valença AMG, Persuhn DC, de Oliveira NFP. Epigenetic mechanisms and oral mucositis in children with acute lymphoblastic leukaemia. Eur J Oral Sci 2024; 132:e13009. [PMID: 39075736 DOI: 10.1111/eos.13009] [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: 04/10/2024] [Accepted: 07/12/2024] [Indexed: 07/31/2024]
Abstract
This study aimed to investigate the relationship between epigenetic mechanisms and oral mucositis (OM) in paediatric patients with acute lymphoblastic leukaemia. Oral cells were collected from 76 participants, including 15 healthy individuals, 10 patients with acute lymphoblastic leukaemia but without a history of OM and 51 acute lymphoblastic leukaemia patients with a history of OM (35 with active OM and 16 who had recovered from OM). Global DNA methylation in the miR-9-1 and miR-9-3 genes was performed. Seven polymorphisms rs1801131, rs1801133 (MTHFR), rs2228611 (DNMT1), rs7590760, rs1550117 (DNMT3A), rs6087990, rs2424913 (DNMT3B) were genotyped and an analysis of association with global DNA methylation was performed. The global methylation levels were lower in cancer patients recovered from OM than in the other groups. A higher frequency of unmethylated profile for miR-9-1 and partially methylated profile for miR-9-3 was observed in cancer patients regardless of OM history compared to healthy patients. The GG genotype of the rs2228611 (DNMT1) polymorphism was associated with higher levels of global methylation in cancer patients irrespective of OM. It was concluded that global methylation is associated with mucosal recovery. The effect of DNMT1 genotype on the global DNA methylation profile, as well as the methylation profile of miR-9-1 and miR-9-3 in cancer patients is independent of OM.
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Affiliation(s)
- Juliana Ramalho Guimarães
- Postgraduate Program in Dentistry, Health Sciences Center, Federal University of Paraíba, - UFPB, João Pessoa, Paraíba, Brazil
| | - Beatriz Fernandes de Souza
- Postgraduate Program in Dentistry, Health Sciences Center, Federal University of Paraíba, - UFPB, João Pessoa, Paraíba, Brazil
| | | | - Lecidamia Cristina Leite Damascena
- Postgraduate Program in Decision Models and Health, Center for Exact and Natural Sciences, Federal University of Paraíba, João Pessoa, Paraíba, Brazil
| | - Ana Maria Gondim Valença
- Postgraduate Program in Decision Models and Health, Center for Exact and Natural Sciences, Federal University of Paraíba, João Pessoa, Paraíba, Brazil
| | - Darlene Camati Persuhn
- Department of Molecular Biology, Center for Exact and Natural Sciences, Federal University of Paraíba, - UFPB, João Pessoa, Paraíba, Brazil
| | - Naila Francis Paulo de Oliveira
- Postgraduate Program in Dentistry, Health Sciences Center, Federal University of Paraíba, - UFPB, João Pessoa, Paraíba, Brazil
- Department of Molecular Biology, Center for Exact and Natural Sciences, Federal University of Paraíba, - UFPB, João Pessoa, Paraíba, Brazil
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12
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Li L, Chen R, Zhang H, Li J, Huang H, Weng J, Tan H, Guo T, Wang M, Xie J. The epigenetic modification of DNA methylation in neurological diseases. Front Immunol 2024; 15:1401962. [PMID: 39376563 PMCID: PMC11456496 DOI: 10.3389/fimmu.2024.1401962] [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: 03/16/2024] [Accepted: 09/03/2024] [Indexed: 10/09/2024] Open
Abstract
Methylation, a key epigenetic modification, is essential for regulating gene expression and protein function without altering the DNA sequence, contributing to various biological processes, including gene transcription, embryonic development, and cellular functions. Methylation encompasses DNA methylation, RNA methylation and histone modification. Recent research indicates that DNA methylation is vital for establishing and maintaining normal brain functions by modulating the high-order structure of DNA. Alterations in the patterns of DNA methylation can exert significant impacts on both gene expression and cellular function, playing a role in the development of numerous diseases, such as neurological disorders, cardiovascular diseases as well as cancer. Our current understanding of the etiology of neurological diseases emphasizes a multifaceted process that includes neurodegenerative, neuroinflammatory, and neurovascular events. Epigenetic modifications, especially DNA methylation, are fundamental in the control of gene expression and are critical in the onset and progression of neurological disorders. Furthermore, we comprehensively overview the role and mechanism of DNA methylation in in various biological processes and gene regulation in neurological diseases. Understanding the mechanisms and dynamics of DNA methylation in neural development can provide valuable insights into human biology and potentially lead to novel therapies for various neurological diseases.
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Affiliation(s)
- Linke Li
- The Center of Obesity and Metabolic Diseases, Department of General Surgery, The Third People’s Hospital of Chengdu and The Affiliated Hospital of Southwest Jiaotong University, Chengdu, China
- College of Medicine, Southwest Jiaotong University, Chengdu, China
| | - Rui Chen
- The Center of Obesity and Metabolic Diseases, Department of General Surgery, The Third People’s Hospital of Chengdu and The Affiliated Hospital of Southwest Jiaotong University, Chengdu, China
- College of Medicine, Southwest Jiaotong University, Chengdu, China
- Department of Stomatology, The Third People’s Hospital of Chengdu and The Affiliated Hospital of Southwest Jiaotong University, Chengdu, China
| | - Hui Zhang
- Department of Stomatology, The Third People’s Hospital of Chengdu and The Affiliated Hospital of Southwest Jiaotong University, Chengdu, China
- College of Materials Science and Engineering, Southwest Jiaotong University, Chengdu, China
| | - Jinsheng Li
- College of Materials Science and Engineering, Southwest Jiaotong University, Chengdu, China
| | - Hao Huang
- College of Materials Science and Engineering, Southwest Jiaotong University, Chengdu, China
| | - Jie Weng
- College of Materials Science and Engineering, Southwest Jiaotong University, Chengdu, China
| | - Huan Tan
- College of Medicine, Southwest Jiaotong University, Chengdu, China
| | - Tailin Guo
- College of Medicine, Southwest Jiaotong University, Chengdu, China
| | - Mengyuan Wang
- The Center of Obesity and Metabolic Diseases, Department of General Surgery, The Third People’s Hospital of Chengdu and The Affiliated Hospital of Southwest Jiaotong University, Chengdu, China
- College of Medicine, Southwest Jiaotong University, Chengdu, China
- Department of Stomatology, The Third People’s Hospital of Chengdu and The Affiliated Hospital of Southwest Jiaotong University, Chengdu, China
| | - Jiang Xie
- Key Laboratory of Drug Targeting and Drug Delivery of Ministry of Education (MOE), Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, West China School of Pharmacy, Sichuan University, Chengdu, China
- Department of Pediatrics, Chengdu Third People’s Hospital, Chengdu, China
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13
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Espeland MA, Harada ASM, Ross J, Bancks MP, Pajewski NM, Simpson FR, Walkup M, Davis I, Huckfeldt PJ, Action for Health in Diabetes Aging Study Group. Cross-sectional and longitudinal associations among healthcare costs and deficit accumulation. J Am Geriatr Soc 2024; 72:2759-2769. [PMID: 38946518 PMCID: PMC11368617 DOI: 10.1111/jgs.19053] [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: 01/31/2024] [Revised: 05/27/2024] [Accepted: 06/09/2024] [Indexed: 07/02/2024]
Abstract
BACKGROUND Type 2 diabetes mellitus and overweight/obesity increase healthcare costs. Both are also associated with accelerated aging. However, the contributions of this accelerated aging to increased healthcare costs are unknown. METHODS We use data from a 8-year longitudinal cohort followed at 16 U.S. clinical research sites. Participants were adults aged 45-76 years with established type 2 diabetes and overweight or obesity who had enrolled in the Action for Health in Diabetes clinical trial. They were randomly (1:1) assigned to either an intensive lifestyle intervention focused on weight loss versus a comparator of diabetes support and education. A validated deficit accumulation frailty index (FI) was used to characterize biological aging. Discounted annual healthcare costs were estimated using national databases in 2012 dollars. Descriptive characteristics were collected by trained and certified staff. RESULTS Compared with participants in the lowest tertile (least frail) of baseline FI, those in the highest tertile (most frail) at Year 1 averaged $714 (42%) higher medication costs, $244 (22%) higher outpatient costs, and $800 (134%) higher hospitalization costs (p < 0.001). At Years 4 and 8, relatively greater increases in FI (third vs. first tertile) were associated with an approximate doubling of total healthcare costs (p < 0.001). Mean (95% confidence interval) relative annual savings in healthcare costs associated with randomization to the intensive lifestyle intervention were $437 ($195, $579) per year during Years 1-4 and $461 ($232, $690) per year during Years 1-8. These were attenuated and the 95% confidence interval no longer excluded $0 after adjustment for the annual FI differences from baseline. CONCLUSIONS Deficit accumulation frailty tracks well with healthcare costs among adults with type 2 diabetes and overweight or obesity. It may serve as a useful marker to project healthcare needs and as an intermediate outcome in clinical trials.
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Affiliation(s)
- Mark A. Espeland
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Ann S. M. Harada
- Leonard D. Schaeffer Center for Health Policy & Economics, University of Southern California, Los Angeles, California
- Sol Price School of Public Policy, University of Southern California, Los Angeles, California
| | - Johnathan Ross
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina
- Department of Mathematics, Winston-Salem State University, Winston-Salem, North Carolina
| | - Michael P. Bancks
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Nicholas M. Pajewski
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Felicia R. Simpson
- Department of Mathematics, Winston-Salem State University, Winston-Salem, North Carolina
| | - Michael Walkup
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Ian Davis
- School of Pharmacy, University of Southern California, Los Angeles, California
| | - Peter J. Huckfeldt
- Division of Health Policy and Management, University of Minnesota School of Public Health, Minneapolis, Minnesota
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14
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Xu GE, Yu P, Hu Y, Wan W, Shen K, Cui X, Wang J, Wang T, Cui C, Chatterjee E, Li G, Cretoiu D, Sluijter JPG, Xu J, Wang L, Xiao J. Exercise training decreases lactylation and prevents myocardial ischemia-reperfusion injury by inhibiting YTHDF2. Basic Res Cardiol 2024; 119:651-671. [PMID: 38563985 DOI: 10.1007/s00395-024-01044-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Revised: 02/19/2024] [Accepted: 03/02/2024] [Indexed: 04/04/2024]
Abstract
Exercise improves cardiac function and metabolism. Although long-term exercise leads to circulating and micro-environmental metabolic changes, the effect of exercise on protein post-translational lactylation modifications as well as its functional relevance is unclear. Here, we report that lactate can regulate cardiomyocyte changes by improving protein lactylation levels and elevating intracellular N6-methyladenosine RNA-binding protein YTHDF2. The intrinsic disorder region of YTHDF2 but not the RNA m6A-binding activity is indispensable for its regulatory function in influencing cardiomyocyte cell size changes and oxygen glucose deprivation/re-oxygenation (OGD/R)-stimulated apoptosis via upregulating Ras GTPase-activating protein-binding protein 1 (G3BP1). Downregulation of YTHDF2 is required for exercise-induced physiological cardiac hypertrophy. Moreover, myocardial YTHDF2 inhibition alleviated ischemia/reperfusion-induced acute injury and pathological remodeling. Our results here link lactate and lactylation modifications with RNA m6A reader YTHDF2 and highlight the physiological importance of this innovative post-transcriptional intrinsic regulation mechanism of cardiomyocyte responses to exercise. Decreasing lactylation or inhibiting YTHDF2/G3BP1 might represent a promising therapeutic strategy for cardiac diseases.
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Affiliation(s)
- Gui-E Xu
- Institute of Geriatrics (Shanghai University), Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), School of Life Science, Shanghai University, Nantong, 226011, China
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Pujiao Yu
- Department of Cardiology, Shanghai Gongli Hospital, Shanghai, 200135, China
| | - Yuxue Hu
- Institute of Geriatrics (Shanghai University), Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), School of Life Science, Shanghai University, Nantong, 226011, China
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Wensi Wan
- Institute of Geriatrics (Shanghai University), Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), School of Life Science, Shanghai University, Nantong, 226011, China
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Keting Shen
- Institute of Geriatrics (Shanghai University), Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), School of Life Science, Shanghai University, Nantong, 226011, China
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Xinxin Cui
- Institute of Geriatrics (Shanghai University), Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), School of Life Science, Shanghai University, Nantong, 226011, China
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Jiaqi Wang
- Institute of Geriatrics (Shanghai University), Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), School of Life Science, Shanghai University, Nantong, 226011, China
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Tianhui Wang
- Institute of Geriatrics (Shanghai University), Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), School of Life Science, Shanghai University, Nantong, 226011, China
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Caiyue Cui
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Emeli Chatterjee
- Cardiovascular Division of the Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Guoping Li
- Cardiovascular Division of the Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Dragos Cretoiu
- Department of Medical Genetics, Carol Davila University of Medicine and Pharmacy, 020031, Bucharest, Romania
- Materno-Fetal Assistance Excellence Unit, Alessandrescu-Rusescu National Institute for Mother and Child Health, 011062, Bucharest, Romania
| | - Joost P G Sluijter
- Department of Cardiology, Laboratory of Experimental Cardiology, University Medical Center Utrecht, 3508GA, Utrecht, The Netherlands
- UMC Utrecht Regenerative Medicine Center, Circulatory Health Research Center, University Medical Center Utrecht, Utrecht University, Utrecht, 3508GA, The Netherlands
| | - Jiahong Xu
- Department of Cardiology, Shanghai Gongli Hospital, Shanghai, 200135, China.
| | - Lijun Wang
- Institute of Geriatrics (Shanghai University), Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), School of Life Science, Shanghai University, Nantong, 226011, China.
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Medicine, Shanghai University, Shanghai, 200444, China.
| | - Junjie Xiao
- Institute of Geriatrics (Shanghai University), Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), School of Life Science, Shanghai University, Nantong, 226011, China.
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Medicine, Shanghai University, Shanghai, 200444, China.
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15
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Grootswagers P, Bach D, Biemans Y, Behrouzi P, Horvath S, Kramer CS, Liu S, Manson JE, Shadyab AH, Stewart JD, Whitsel E, Yang B, de Groot L. Discovering the direct relations between nutrients and epigenetic ageing. J Nutr Health Aging 2024; 28:100324. [PMID: 39067141 DOI: 10.1016/j.jnha.2024.100324] [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: 06/14/2024] [Revised: 07/12/2024] [Accepted: 07/22/2024] [Indexed: 07/30/2024]
Abstract
BACKGROUND Along with the ageing of society, the absolute prevalence of age-related diseases is expected to rise, leading to a substantial burden on healthcare systems and society. Thus, there is an urgent need to promote healthy ageing. As opposed to chronological age, biological age was introduced to accurately represent the ageing process, as it considers physiological deterioration that is linked to morbidity and mortality risk. Furthermore, biological age responds to various factors, including nutritional factors, which have the potential to mitigate the risk of age-related diseases. As a result, a promising biomarker of biological age known as the epigenetic clock has emerged as a suitable measure to investigate the direct relations between nutritional factors and ageing, thereby identifying potential intervention targets to improve healthy ageing. METHODS In this study, we analysed data from 3,969 postmenopausal women from the Women's Health Initiative to identify nutrients that are associated with the rate of ageing by using an accurate measure of biological age called the PhenoAge epigenetic clock. We used Copula Graphical Models, a data-driven exploratory analysis tool, to identify direct relationships between nutrient intake and age-acceleration, while correcting for every variable in the dataset. RESULTS We revealed that increased dietary intakes of coumestrol, beta-carotene and arachidic acid were associated with decelerated epigenetic ageing. In contrast, increased intakes of added sugar, gondoic acid, behenic acid, arachidonic acid, vitamin A and ash were associated with accelerated epigenetic ageing in postmenopausal women. CONCLUSION Our study discovered direct relations between nutrients and epigenetic ageing, revealing promising areas for follow-up studies to determine the magnitude and causality of our estimated diet-epigenetic relationships.
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Affiliation(s)
- Pol Grootswagers
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, Netherlands.
| | - Daimy Bach
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, Netherlands
| | - Ynte Biemans
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, Netherlands
| | - Pariya Behrouzi
- Biometris, Mathematical and Statistical Methods, Wageningen University and Research, Wageningen, Netherlands
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, USA; Altos Labs, San Diego Institute of Science, San Diego, CA, USA; Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, USA
| | - Charlotte S Kramer
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, Netherlands
| | - Simin Liu
- Department of Epidemiology and Center for Global Cardiometabolic Health, School of Public Health, Departments of Medicine and Surgery, Alpert School of Medicine, Brown University, Providence, RI, USA
| | - JoAnn E Manson
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Aladdin H Shadyab
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA
| | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Eric Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Bo Yang
- Department of Epidemiology and Center for Global Cardiometabolic Health, School of Public Health, Brown University, Providence, RI, USA
| | - Lisette de Groot
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, Netherlands
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16
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Marinello D, Favero C, Albetti B, Barbuto D, Vigna L, Pesatori AC, Bollati V, Ferrari L. Investigating the Relationship between Epigenetic Age and Cardiovascular Risk in a Population with Overweight/Obesity. Biomedicines 2024; 12:1631. [PMID: 39200095 PMCID: PMC11351200 DOI: 10.3390/biomedicines12081631] [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: 06/19/2024] [Revised: 07/12/2024] [Accepted: 07/14/2024] [Indexed: 09/01/2024] Open
Abstract
Introduction: Cardiovascular diseases stand as the leading global cause of mortality. Major modifiable risk factors encompass overweight/obese conditions, high blood pressure, elevated LDL cholesterol, diabetes, smoking, secondhand smoke exposure, unhealthy diet, and physical inactivity. In the present study, we explored the relationship between cardiovascular risk factors and epigenetic age (DNAm age), an estimate reflecting an individual's actual physiological functionality and overall health. Additionally, we assessed the association between DNAm age acceleration and cardiovascular risk, as evaluated through the Framingham risk score (FRS). Methods: The study includes 190 subjects with overweight/obese conditions. We calculated their DNAm age using Zbieć-Piekarska et al.'s DNAm age estimator on five sets of CpGs analyzed in the peripheral leucocytes. Linear regression models were employed to test the associations. Results: Various parameters contributing to increased cardiovascular risk were associated with DNAm age acceleration, such as systolic blood pressure (β = 0.045; SE = 0.019; p = 0.019), heart rate (β = 0.096; SE = 0.032; p = 0.003), blood glucose (β = 0.025; SE = 0.012; p = 0.030), glycated hemoglobin (β = 0.105; SE = 0.042; p = 0.013), diabetes (β = 2.247; SE = 0.841; p = 0.008), and menopausal conditions (β = 2.942; SE = 1.207; p = 0.016), as well as neutrophil (β = 0.100; SE = 0.042; p = 0.018) and granulocyte (β = 0.095; SE = 0.044; p = 0.033) counts. Moreover, DNAm age acceleration raised the FRS (∆% 5.3%, 95% CI 0.8; 9.9, p = 0.019). Conclusion: For the first time, we report that cardiovascular risk factors accelerated DNAm age in a selected population of hypersusceptible individuals with overweight or obesity. Our results highlight the potential of DNAm age acceleration as a biomarker of cumulative effects in cardiovascular risk assessment.
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Affiliation(s)
- Davide Marinello
- EPIGET LAB, Department of Clinical Sciences and Community Health, Dipartimento di Eccellenza 2024–2027, University of Milan, 20122 Milan, Italy
| | - Chiara Favero
- EPIGET LAB, Department of Clinical Sciences and Community Health, Dipartimento di Eccellenza 2024–2027, University of Milan, 20122 Milan, Italy
| | - Benedetta Albetti
- EPIGET LAB, Department of Clinical Sciences and Community Health, Dipartimento di Eccellenza 2024–2027, University of Milan, 20122 Milan, Italy
| | - Davide Barbuto
- EPIGET LAB, Department of Clinical Sciences and Community Health, Dipartimento di Eccellenza 2024–2027, University of Milan, 20122 Milan, Italy
| | - Luisella Vigna
- Occupational Health Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Angela Cecilia Pesatori
- EPIGET LAB, Department of Clinical Sciences and Community Health, Dipartimento di Eccellenza 2024–2027, University of Milan, 20122 Milan, Italy
- Occupational Health Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Valentina Bollati
- EPIGET LAB, Department of Clinical Sciences and Community Health, Dipartimento di Eccellenza 2024–2027, University of Milan, 20122 Milan, Italy
- Occupational Health Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Luca Ferrari
- EPIGET LAB, Department of Clinical Sciences and Community Health, Dipartimento di Eccellenza 2024–2027, University of Milan, 20122 Milan, Italy
- Occupational Health Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
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17
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Liang Y, Kaushal D, Wilson RB. Cellular Senescence and Extracellular Vesicles in the Pathogenesis and Treatment of Obesity-A Narrative Review. Int J Mol Sci 2024; 25:7943. [PMID: 39063184 PMCID: PMC11276987 DOI: 10.3390/ijms25147943] [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: 05/30/2024] [Revised: 07/04/2024] [Accepted: 07/17/2024] [Indexed: 07/28/2024] Open
Abstract
This narrative review explores the pathophysiology of obesity, cellular senescence, and exosome release. When exposed to excessive nutrients, adipocytes develop mitochondrial dysfunction and generate reactive oxygen species with DNA damage. This triggers adipocyte hypertrophy and hypoxia, inhibition of adiponectin secretion and adipogenesis, increased endoplasmic reticulum stress and maladaptive unfolded protein response, metaflammation, and polarization of macrophages. Such feed-forward cycles are not resolved by antioxidant systems, heat shock response pathways, or DNA repair mechanisms, resulting in transmissible cellular senescence via autocrine, paracrine, and endocrine signaling. Senescence can thus affect preadipocytes, mature adipocytes, tissue macrophages and lymphocytes, hepatocytes, vascular endothelium, pancreatic β cells, myocytes, hypothalamic nuclei, and renal podocytes. The senescence-associated secretory phenotype is closely related to visceral adipose tissue expansion and metaflammation; inhibition of SIRT-1, adiponectin, and autophagy; and increased release of exosomes, exosomal micro-RNAs, pro-inflammatory adipokines, and saturated free fatty acids. The resulting hypernefemia, insulin resistance, and diminished fatty acid β-oxidation lead to lipotoxicity and progressive obesity, metabolic syndrome, and physical and cognitive functional decline. Weight cycling is related to continuing immunosenescence and exposure to palmitate. Cellular senescence, exosome release, and the transmissible senescence-associated secretory phenotype contribute to obesity and metabolic syndrome. Targeted therapies have interrelated and synergistic effects on cellular senescence, obesity, and premature aging.
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Affiliation(s)
- Yicong Liang
- Bankstown Hospital, University of New South Wales, Sydney, NSW 2560, Australia;
| | - Devesh Kaushal
- Campbelltown Hospital, Western Sydney University, Sydney, NSW 2560, Australia;
| | - Robert Beaumont Wilson
- School of Clinical Medicine, University of New South Wales, High St., Kensington, Sydney, NSW 2052, Australia
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18
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Martínez-Magaña JJ, Hurtado-Soriano J, Rivero-Segura NA, Montalvo-Ortiz JL, Garcia-delaTorre P, Becerril-Rojas K, Gomez-Verjan JC. Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology. Arch Med Res 2024; 55:103033. [PMID: 38955096 DOI: 10.1016/j.arcmed.2024.103033] [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: 01/10/2024] [Revised: 05/10/2024] [Accepted: 06/17/2024] [Indexed: 07/04/2024]
Abstract
Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.
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Affiliation(s)
- José Jaime Martínez-Magaña
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; U.S. Department of Veterans Affairs National Center for Post-Traumatic Stress Disorder, Clinical Neuroscience Division, West Haven, CT, USA; VA Connecticut Healthcare System, West Haven, CT, USA
| | | | | | - Janitza L Montalvo-Ortiz
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; U.S. Department of Veterans Affairs National Center for Post-Traumatic Stress Disorder, Clinical Neuroscience Division, West Haven, CT, USA; VA Connecticut Healthcare System, West Haven, CT, USA
| | - Paola Garcia-delaTorre
- Unidad de Investigación Epidemiológica y en Servicios de Salud, Área de Envejecimiento, Centro Médico Nacional, Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
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19
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Filoglu G, Sımsek SZ, Ersoy G, Can K, Bulbul O. Epigenetic-based age prediction in blood samples: Model development. J Forensic Sci 2024; 69:869-879. [PMID: 38308398 DOI: 10.1111/1556-4029.15478] [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: 09/11/2023] [Revised: 01/19/2024] [Accepted: 01/22/2024] [Indexed: 02/04/2024]
Abstract
Aging is a complex process influenced by genetic, epigenetic, and environmental factors that lead to tissue deterioration and frailty. Epigenetic mechanisms, such as DNA methylation, play a significant role in gene expression regulation and aging. This study presents a new age estimation model developed for the Turkish population using blood samples. Eight CpG sites in loci TOM1L1, ELOVL2, ASPA, FHL2, C1orf132, CCDC102B, cg07082267, and RASSF5 were selected based on their correlation with age. Methylation patterns of these sites were analyzed in blood samples from 100 volunteers, grouped into age categories (20-35, 36-55, and ≥56). Sensitivity analysis indicated a reliable performance with DNA inputs ≥1 ng. Statistical modeling, utilizing Multiple Linear Regression, underscores the reliability of the primary 6-CpG model, excluding cg07082267 and TOM1L1. This model demonstrates strong correlations with chronological age (r = 0.941) and explains 88% of the age variance with low error rates (MAE = 4.07, RMSE = 5.73 years). Validation procedures, including a training-test split and fivefold cross-validation, consistently confirm the model's accuracy and consistency. The study indicates minimal variation in error scores across age cohorts and no significant gender differences. The developed model showed strong predictive accuracy, with the ability to estimate age within certain prediction intervals. This study contributes to the age prediction by using DNA methylation patterns, which can have disparate applications, including forensic and clinical assessments.
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Affiliation(s)
- Gonul Filoglu
- Department of Science, Institute of Forensic Sciences and Legal Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Sumeyye Zulal Sımsek
- Department of Science, Institute of Forensic Sciences and Legal Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Gokhan Ersoy
- Department of Forensic Medicine, Institute of Forensic Sciences and Legal Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Kadriye Can
- Department of Science, Institute of Forensic Sciences and Legal Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Ozlem Bulbul
- Department of Science, Institute of Forensic Sciences and Legal Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
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20
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Li DL, Hodge AM, Cribb L, Southey MC, Giles GG, Milne RL, Dugué PA. Body Size, Diet Quality, and Epigenetic Aging: Cross-Sectional and Longitudinal Analyses. J Gerontol A Biol Sci Med Sci 2024; 79:glae026. [PMID: 38267386 PMCID: PMC10953795 DOI: 10.1093/gerona/glae026] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Indexed: 01/26/2024] Open
Abstract
Epigenetic age is an emerging marker of health that is highly predictive of disease and mortality risk. There is a lack of evidence on whether lifestyle changes are associated with changes in epigenetic aging. We used data from 1 041 participants in the Melbourne Collaborative Cohort Study with blood DNA methylation measures at baseline (1990-1994, mean age: 57.4 years) and follow-up (2003-2007, mean age: 68.8 years). The Alternative Healthy Eating Index-2010 (AHEI-2010), the Mediterranean Dietary Score, and the Dietary Inflammatory Index were used as measures of diet quality, and weight, waist circumference, and waist-to-hip ratio as measures of body size. Five age-adjusted epigenetic aging measures were considered: GrimAge, PhenoAge, PCGrimAge, PCPhenoAge, and DunedinPACE. Multivariable linear regression models including restricted cubic splines were used to assess the cross-sectional and longitudinal associations of body size and diet quality with epigenetic aging. Associations between weight and epigenetic aging cross-sectionally at both time points were positive and appeared greater for DunedinPACE (per SD: β ~0.24) than for GrimAge and PhenoAge (β ~0.10). The longitudinal associations with weight change were markedly nonlinear (U-shaped) with stable weight being associated with the lowest epigenetic aging at follow-up, except for DunedinPACE, for which only weight gain showed a positive association. We found negative, linear associations for AHEI-2010 both cross-sectionally and longitudinally. Other adiposity measures and dietary scores showed similar results. In middle-aged to older adults, declining diet quality and weight gain may increase epigenetic age, while the association for weight loss may require further investigation. Our study sheds light on the potential of weight management and dietary improvement in slowing aging processes.
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Affiliation(s)
- Danmeng Lily Li
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Allison M Hodge
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Lachlan Cribb
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - Graham G Giles
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Roger L Milne
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Pierre-Antoine Dugué
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
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21
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Lagarde CB, Kavalakatt J, Benz MC, Hawes ML, Arbogast CA, Cullen NM, McConnell EC, Rinderle C, Hebert KL, Khosla M, Belgodere JA, Hoang VT, Collins-Burow BM, Bunnell BA, Burow ME, Alahari SK. Obesity-associated epigenetic alterations and the obesity-breast cancer axis. Oncogene 2024; 43:763-775. [PMID: 38310162 DOI: 10.1038/s41388-024-02954-0] [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: 09/19/2023] [Revised: 01/18/2024] [Accepted: 01/22/2024] [Indexed: 02/05/2024]
Abstract
Both breast cancer and obesity can regulate epigenetic changes or be regulated by epigenetic changes. Due to the well-established link between obesity and an increased risk of developing breast cancer, understanding how obesity-mediated epigenetic changes affect breast cancer pathogenesis is critical. Researchers have described how obesity and breast cancer modulate the epigenome individually and synergistically. In this review, the epigenetic alterations that occur in obesity, including DNA methylation, histone, and chromatin modification, accelerated epigenetic age, carcinogenesis, metastasis, and tumor microenvironment modulation, are discussed. Delineating the relationship between obesity and epigenetic regulation is vital to furthering our understanding of breast cancer pathogenesis.
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Affiliation(s)
- Courtney B Lagarde
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Joachim Kavalakatt
- Department of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA
| | - Megan C Benz
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Mackenzie L Hawes
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Carter A Arbogast
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Nicole M Cullen
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Emily C McConnell
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Caroline Rinderle
- Department of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA
| | - Katherine L Hebert
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Maninder Khosla
- Department of Biochemistry and Molecular Biology, LSU Health Science Center School of Medicine, New Orleans, LA, 70112, USA
| | - Jorge A Belgodere
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
- Department of Biological and Agricultural Engineering, Louisiana State University and Agricultural Center, Baton Rouge, LA, 70803, USA
| | - Van T Hoang
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Bridgette M Collins-Burow
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Bruce A Bunnell
- Department of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA
| | - Matthew E Burow
- Department of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, New Orleans, LA, 70112, USA.
| | - Suresh K Alahari
- Department of Biochemistry and Molecular Biology, LSU Health Science Center School of Medicine, New Orleans, LA, 70112, USA.
- Stanley S. Scott Cancer Center, LSU Health Science Center School of Medicine, New Orleans, LA, 70112, USA.
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22
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Almohtasib Y, Fancher AJ, Sawalha K. Emerging Trends in Atherosclerosis: Time to Address Atherosclerosis From a Younger Age. Cureus 2024; 16:e56635. [PMID: 38646335 PMCID: PMC11032087 DOI: 10.7759/cureus.56635] [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] [Accepted: 03/21/2024] [Indexed: 04/23/2024] Open
Abstract
Over the past two decades, research efforts into cardiovascular disease (CVD) have uncovered findings that fundamentally challenge our understanding of CVD, particularly atherosclerosis. Atherosclerosis was primarily attributed to the well-described abnormal lipid accumulation theory, involving plaque growth with subsequent plaque hemorrhage resulting in acute vessel thrombosis that may or may not rupture. This perspective has now evolved to encompass more complex pathways, wherein the accumulation of abnormal products of oxidation and inflammation is the most likely factor mediating atherosclerotic plaque growth. Furthermore, atherosclerosis was traditionally thought of as a disease in patients aged 40 and older. However, mounting evidence has demonstrated that significant atherosclerosis and CVD events are more prevalent in younger patients than previously realized and accelerating in incidence. With this alarming trend among younger individuals, our review sought to explore why this trend may be happening and what can be done about this developing problem.
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Affiliation(s)
- Yazan Almohtasib
- Internal Medicine, University of Missouri Kansas City School of Medicine, Kansas City, USA
| | - Andrew J Fancher
- Internal Medicine, University of Kansas School of Medicine-Wichita, Wichita, USA
| | - Khalid Sawalha
- Cardiometabolic Medicine, University of Missouri Kansas City School of Medicine, Kansas City, USA
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23
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Damiescu R, Efferth T, Dawood M. Dysregulation of different modes of programmed cell death by epigenetic modifications and their role in cancer. Cancer Lett 2024; 584:216623. [PMID: 38246223 DOI: 10.1016/j.canlet.2024.216623] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 12/19/2023] [Accepted: 01/07/2024] [Indexed: 01/23/2024]
Abstract
Modifications of epigenetic factors affect our lives and can give important information regarding one's state of health. In cancer, epigenetic modifications play a crucial role, as they influence various programmed cell death types. The purpose of this review is to investigate how epigenetic modifications, such as DNA methylation, histone modifications, and non-coding RNAs, influence various cell death processes in suppressing or promoting cancer development. Autophagy and apoptosis are the most investigated programmed cell death modes, as based on the tumor stage these cell death types can either promote or prevent cancer evolution. Therefore, our discussion focuses on how epigenetic modifications affect autophagy and apoptosis, as well as their diagnostic and therapeutical potential in combination with available chemotherapeutics. Additionally, we summarize the available data regarding the role of epigenetic modifications on other programmed cell death modes, such as ferroptosis, necroptosis, and parthanatos in cancer and discuss current advancements.
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Affiliation(s)
- R Damiescu
- Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, Mainz, Germany
| | - T Efferth
- Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, Mainz, Germany
| | - M Dawood
- Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, Mainz, Germany.
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24
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Dutta S, Goodrich JM, Dolinoy DC, Ruden DM. Biological Aging Acceleration Due to Environmental Exposures: An Exciting New Direction in Toxicogenomics Research. Genes (Basel) 2023; 15:16. [PMID: 38275598 PMCID: PMC10815440 DOI: 10.3390/genes15010016] [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: 11/27/2023] [Revised: 12/14/2023] [Accepted: 12/20/2023] [Indexed: 01/27/2024] Open
Abstract
Biological clock technologies are designed to assess the acceleration of biological age (B-age) in diverse cell types, offering a distinctive opportunity in toxicogenomic research to explore the impact of environmental stressors, social challenges, and unhealthy lifestyles on health impairment. These clocks also play a role in identifying factors that can hinder aging and promote a healthy lifestyle. Over the past decade, researchers in epigenetics have developed testing methods that predict the chronological and biological age of organisms. These methods rely on assessing DNA methylation (DNAm) levels at specific CpG sites, RNA levels, and various biomolecules across multiple cell types, tissues, and entire organisms. Commonly known as 'biological clocks' (B-clocks), these estimators hold promise for gaining deeper insights into the pathways contributing to the development of age-related disorders. They also provide a foundation for devising biomedical or social interventions to prevent, reverse, or mitigate these disorders. This review article provides a concise overview of various epigenetic clocks and explores their susceptibility to environmental stressors.
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Affiliation(s)
- Sudipta Dutta
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA;
| | - Jaclyn M. Goodrich
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA; (J.M.G.); (D.C.D.)
| | - Dana C. Dolinoy
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA; (J.M.G.); (D.C.D.)
- Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Douglas M. Ruden
- C. S. Mott Center for Human Health and Development, Department of Obstetrics and Gynecology, Institute of Environmental Health Sciences, Wayne State University, Detroit, MI 48202, USA
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25
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Shi Y, Qi W. Histone Modifications in NAFLD: Mechanisms and Potential Therapy. Int J Mol Sci 2023; 24:14653. [PMID: 37834101 PMCID: PMC10572202 DOI: 10.3390/ijms241914653] [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: 08/10/2023] [Revised: 09/03/2023] [Accepted: 09/09/2023] [Indexed: 10/15/2023] Open
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a progressive condition that encompasses a spectrum of liver disorders, beginning with the simple steatosis, progressing to nonalcoholic steatohepatitis (NASH), and possibly leading to more severe diseases, including liver cirrhosis and hepatocellular carcinoma (HCC). In recent years, the prevalence of NAFLD has increased due to a shift towards energy-dense dietary patterns and a sedentary lifestyle. NAFLD is also strongly associated with metabolic disorders such as obesity and hyperlipidemia. The progression of NAFLD could be influenced by a variety of factors, such as diet, genetic factors, and even epigenetic factors. In contrast to genetic factors, epigenetic factors, including histone modifications, exhibit dynamic and reversible features. Therefore, the epigenetic regulation of the initiation and progression of NAFLD is one of the directions under intensive investigation in terms of pathogenic mechanisms and possible therapeutic interventions. This review aims to discuss the possible mechanisms and the crucial role of histone modifications in the framework of epigenetic regulation in NAFLD, which may provide potential therapeutic targets and a scientific basis for the treatment of NAFLD.
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Affiliation(s)
- Yulei Shi
- Gene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Wei Qi
- Gene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
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26
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Chen X, Hou C, Yao L, Li J, Gui M, Wang M, Zhou X, Lu B, Fu D. Dietary inflammation index is associated with dyslipidemia: evidence from national health and nutrition examination survey, 1999-2019. Lipids Health Dis 2023; 22:149. [PMID: 37689717 PMCID: PMC10492364 DOI: 10.1186/s12944-023-01914-z] [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: 09/02/2023] [Indexed: 09/11/2023] Open
Abstract
BACKGROUND AND AIMS This study aimed to investigate the association between the Dietary Inflammatory Index (DII) and dyslipidemia, as well as to evaluate the mortality risk associated with DII in participants with dyslipidemia. METHODS Data from the National Health and Nutrition Examination Survey database were divided into dyslipidemia and non-dyslipidemia groups. The association between DII and dyslipidemia was investigated using the weighted chi-square test, weighted t-test, and weighted logistic regression. Weighted Cox proportional hazards models were used to estimate the hazard ratios and 95% confidence intervals for all-cause and cardiovascular disease-related mortality within the dyslipidemia group. RESULTS A total of 17,820 participants, including 4,839 without and 12,981 with dyslipidemia were analyzed in this study. The results showed that DII was higher in the dyslipidemia group compared to the non-dyslipidemia group (1.42 ± 0.03 vs. 1.23 ± 0.04, P < 0.01). However, for energy, protein, carbohydrates, total fat, saturated fat, and iron, DII was lower in participants with dyslipidemia. Logistic regression analysis revealed a strong positive association between DII and dyslipidemia. The odds ratios for dyslipidemia from Q1 to Q4 were 1.00 (reference), 1.12 (0.96-1.31), 1.23 (1.04-1.44), and 1.33 (1.11-1.59), respectively. In participants with dyslipidemia, a high DII was associated with high all-cause and cardiovascular mortality. CONCLUSION DII was closely associated with dyslipidemia. A pro-inflammatory diet may play a role in unfavorable consequences and is linked to both all-cause mortality and cardiovascular death in patients with dyslipidemia. Participants with dyslipidemia should pay attention to their anti-inflammatory dietary patterns.
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Affiliation(s)
- Xiaozhe Chen
- Department of Cardiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chunlei Hou
- Department of Cardiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Lei Yao
- Department of Cardiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jianhua Li
- Department of Cardiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Mingtai Gui
- Department of Cardiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Mingzhu Wang
- Department of Cardiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xunjie Zhou
- Department of Cardiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Bo Lu
- Department of Cardiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
| | - Deyu Fu
- Department of Cardiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
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27
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Hu D, Zhao J, Zhang H, Wang G, Gu Z. Fecal Microbiota Transplantation for Weight and Glycemic Control of Obesity as Well as the Associated Metabolic Diseases: Meta-Analysis and Comprehensive Assessment. Life (Basel) 2023; 13:1488. [PMID: 37511862 PMCID: PMC10381135 DOI: 10.3390/life13071488] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 06/15/2023] [Accepted: 06/17/2023] [Indexed: 07/30/2023] Open
Abstract
Objectives: An analysis of the weight and blood glucose management associated with fecal microbiota transplantation (FMT) as well as metabolic diseases associated with FMT was conducted by the authors in order to provide clinical recommendations regarding the treatment of nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM). Methods: We searched PubMed, Embase, and the Cochrane Library for papers that were published between the creation of the database and October 2022. We reviewed research that investigated how FMT affected weight and glycemic management in cases of obesity and metabolic conditions that are related to obesity. Studies that were published more than once, lacked the entire text, included insufficient information, or were impossible to extract data from were excluded. Additionally, case reports, reviews, and systematic reviews were excluded from the analysis. In order to analyze the data, STATA 15.1 was used. Outcomes: When we combined all of our findings, we discovered that pooled outcomes showed that weight levels (WMD equals -4.77, 95%CI: -7.40~-2.14), BMI levels (WMD equals -1.59, 95%CI: -2.21~-0.97), HOMA-IR (WMD equals -0.79, 95%CI: -1.57~-0.00), and HbA1c (WMD equals -0.65, 95%CI: -0.75~-0.55) after FMT treatment were significantly lower than before treatment. However, FMT treatment may have no effect on glucose and insulin levels in obese patients at fasting and related metabolic diseases. Additionally, subgroup analysis outcomes found that FMT significantly reduced fasting blood glucose in people with diabetes. Conclusions: As a weight loss and glycemic control therapy, FMT helps to prevent and treat metabolic problems linked to obesity, and is a viable alternative to bariatric surgery for patients who do not wish to undergo the procedure.
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Affiliation(s)
- Diangeng Hu
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Jianxin Zhao
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- National Engineering Research Center for Functional Food, Jiangnan University, Wuxi 214122, China
- (Yangzhou) Institute of Food Biotechnology, Jiangnan University, Yangzhou 225004, China
| | - Hao Zhang
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- National Engineering Research Center for Functional Food, Jiangnan University, Wuxi 214122, China
- (Yangzhou) Institute of Food Biotechnology, Jiangnan University, Yangzhou 225004, China
| | - Gang Wang
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- National Engineering Research Center for Functional Food, Jiangnan University, Wuxi 214122, China
- (Yangzhou) Institute of Food Biotechnology, Jiangnan University, Yangzhou 225004, China
| | - Zhennan Gu
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
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28
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Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, et alBao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. SCIENCE CHINA. LIFE SCIENCES 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Show More Authors] [Citation(s) in RCA: 167] [Impact Index Per Article: 83.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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Affiliation(s)
- Hainan Bao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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Sawalha K, Norgard N, López-Candales A. Epigenetic Regulation and its Effects on Aging and Cardiovascular Disease. Cureus 2023; 15:e39395. [PMID: 37362531 PMCID: PMC10286850 DOI: 10.7759/cureus.39395] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/23/2023] [Indexed: 06/28/2023] Open
Abstract
Cardiovascular disease (CVD), specifically coronary atherosclerosis, is regulated by an interplay between genetic and lifestyle factors. Most recently, a factor getting much attention is the role epigenetics play in atherosclerosis; particularly the development of coronary artery disease. Furthermore, it is important to understand the intricate interaction between the environment and each individual genetic material and how this interaction affects gene expression and consequently influences the development of atherosclerosis. Our main goal is to discuss epigenetic regulations; particularly, the factors contributing to coronary atherosclerosis and their role in aging and longevity. We reviewed the current literature and provided a simplified yet structured and reasonable appraisal of this topic. This role has also been recently linked to longevity and aging. Epigenetic regulations (modifications) whether through histone modifications or DNA or RNA methylation have been shown to be regulated by environmental factors such as social stress, smoking, chemical contaminants, and diet. These sensitive interactions are further aggravated by racial health disparities that ultimately impact cardiovascular disease outcomes through epigenetic interactions. Certainly, limiting our exposure to such causative events at younger ages seems our "golden opportunity" to tackle the incidence of coronary atherosclerosis and probably the answer to longevity.
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Affiliation(s)
- Khalid Sawalha
- Cardiometabolic Diseases, Truman Medical Centers - University of Missouri Kansas City, Kansas City, USA
| | - Nicholas Norgard
- Pharmacology and Therapeutics, Truman Medical Centers - University of Missouri Kansas City, Kansas City, USA
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30
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Li Piani L, Vigano' P, Somigliana E. Epigenetic clocks and female fertility timeline: A new approach to an old issue? Front Cell Dev Biol 2023; 11:1121231. [PMID: 37025178 PMCID: PMC10070683 DOI: 10.3389/fcell.2023.1121231] [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: 12/11/2022] [Accepted: 03/03/2023] [Indexed: 04/08/2023] Open
Abstract
Worldwide increase in life expectancy has boosted research on aging. Overcoming the concept of chronological age, higher attention has been addressed to biological age, which reflects a person's real health state, and which may be the resulting combination of both intrinsic and environmental factors. As epigenetics may exert a pivotal role in the biological aging, epigenetic clocks were developed. They are based on mathematical models aimed at identifying DNA methylation patterns that can define the biological age and that can be adopted for different clinical scopes (i.e., estimation of the risks of developing age-related disorders or predicting lifespan). Recently, epigenetic clocks have gained a peculiar attention in the fertility research field, in particular in the female counterpart. The insight into the possible relations between epigenetic aging and women's infertility might glean additional information about certain conditions that are still not completely understood. Moreover, they could disclose significant implications for health promotion programs in infertile women. Of relevance here is that the impact of biological age and epigenetics may not be limited to fertility status but could translate into pregnancy issues. Indeed, epigenetic alterations of the mother may transfer into the offspring, and pregnancy itself as well as related complications could contribute to epigenetic modifications in both the mother and newborn. However, even if the growing interest has culminated in the conspicuous production of studies on these topics, a global overview and the availability of validated instruments for diagnosis is still missing. The present narrative review aims to explore the possible bonds between epigenetic aging and fertility timeline. In the "infertility" section, we will discuss the advances on epigenetic clocks focusing on the different tissues examined (endometrium, peripheral blood, ovaries). In the "pregnancy" section, we will discuss the results obtained from placenta, umbilical cord and peripheral blood. The possible role of epigenetic aging on infertility mechanisms and pregnancy outcomes represents a question that may configure epigenetic clock as a bond between two apparently opposite worlds: infertility and pregnancy.
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Affiliation(s)
- Letizia Li Piani
- Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, Milan, Italy
| | - Paola Vigano'
- Infertility Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Edgardo Somigliana
- Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, Milan, Italy
- Infertility Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
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Chrono-Nutrition: Circadian Rhythm and Personalized Nutrition. Int J Mol Sci 2023; 24:ijms24032571. [PMID: 36768893 PMCID: PMC9916946 DOI: 10.3390/ijms24032571] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 01/23/2023] [Accepted: 01/25/2023] [Indexed: 01/31/2023] Open
Abstract
The human circadian system has a period of approximately 24 h and studies on the consequences of "chornodisruption" have greatly expanded. Lifestyle and environmental factors of modern societies (i.e., artificial lighting, jetlag, shift work, and around-the-clock access to energy-dense food) can induce disruptions of the circadian system and thereby adversely affect individual health. Growing evidence demonstrates a complex reciprocal relationship between metabolism and the circadian system, in which perturbations in one system affect the other one. From a nutritional genomics perspective, genetic variants in clock genes can both influence metabolic health and modify the individual response to diet. Moreover, an interplay between the circadian rhythm, gut microbiome, and epigenome has been demonstrated, with the diet in turn able to modulate this complex link suggesting a remarkable plasticity of the underlying mechanisms. In this view, the study of the impact of the timing of eating by matching elements from nutritional research with chrono-biology, that is, chrono-nutrition, could have significant implications for personalized nutrition in terms of reducing the prevalence and burden of chronic diseases. This review provides an overview of the current evidence on the interactions between the circadian system and nutrition, highlighting how this link could in turn influence the epigenome and microbiome. In addition, possible nutritional strategies to manage circadian-aligned feeding are suggested.
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