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Yang X, Wei J, Sun L, Zhong Q, Zhai X, Chen Y, Luo S, Tang C, Wang L. Causal relationship between iron status and preeclampsia-eclampsia: a Mendelian randomization analysis. Clin Exp Hypertens 2024; 46:2321148. [PMID: 38471132 DOI: 10.1080/10641963.2024.2321148] [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: 10/16/2023] [Accepted: 02/15/2024] [Indexed: 03/14/2024]
Abstract
BACKGROUND Preeclampsia/eclampsia is a severe pregnancy-related disorder associated with hypertension and organ damage. While observational studies have suggested a link between maternal iron status and preeclampsia/eclampsia, the causal relationship remains unclear. The aim of this study was to investigate the genetic causality between iron status and preeclampsia/eclampsia using large-scale genome-wide association study (GWAS) summary data and Mendelian randomization (MR) analysis. METHODS Summary data for the GWAS on preeclampsia/eclampsia and genetic markers related to iron status were obtained from the FinnGen Consortium and the IEU genetic databases. The "TwoSampleMR" software package in R was employed to test the genetic causality between these markers and preeclampsia/eclampsia. The inverse variance weighted (IVW) method was primarily used for MR analysis. Heterogeneity, horizontal pleiotropy, and potential outliers were evaluated for the MR analysis results. RESULTS The random-effects IVW results showed that ferritin (OR = 1.11, 95% CI: .89-1.38, p = .341), serum iron (OR = .90, 95% CI: .75-1.09, p = .275), TIBC (OR = .98, 95% CI: .89-1.07, p = .613), and TSAT (OR = .94, 95% CI: .83-1.07, p = .354) have no genetic causal relationship with preeclampsia/eclampsia. There was no evidence of heterogeneity, horizontal pleiotropy, or possible outliers in our MR analysis (p > .05). CONCLUSIONS Our study did not detect a genetic causal relationship between iron status and preeclampsia/eclampsia. Nonetheless, this does not rule out a relationship between the two at other mechanistic levels.
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Affiliation(s)
- Xiaofeng Yang
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Jiachun Wei
- Department of Obstetrics and Gynecology, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Lu Sun
- Department of Obstetrics and Gynecology, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Qimei Zhong
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaoxuan Zhai
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Ya Chen
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Shujuan Luo
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Chunyan Tang
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Lan Wang
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
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Carbonneau M, Li Y, Prescott B, Liu C, Huan T, Joehanes R, Murabito JM, Heard-Costa NL, Xanthakis V, Levy D, Ma J. Epigenetic Age Mediates the Association of Life's Essential 8 With Cardiovascular Disease and Mortality. J Am Heart Assoc 2024; 13:e032743. [PMID: 38808571 DOI: 10.1161/jaha.123.032743] [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: 09/18/2023] [Accepted: 03/25/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND Life's Essential 8 (LE8) is an enhanced metric for cardiovascular health. The interrelations among LE8, biomarkers of aging, and disease risks are unclear. METHODS AND RESULTS LE8 score was calculated for 5682 Framingham Heart Study participants. We implemented 4 DNA methylation-based epigenetic age biomarkers, with older epigenetic age hypothesized to represent faster biological aging, and examined whether these biomarkers mediated the associations between the LE8 score and cardiovascular disease (CVD), CVD-specific mortality, and all-cause mortality. We found that a 1 SD increase in the LE8 score was associated with a 35% (95% CI, 27-41; P=1.8E-15) lower risk of incident CVD, a 36% (95% CI, 24-47; P=7E-7) lower risk of CVD-specific mortality, and a 29% (95% CI, 22-35; P=7E-15) lower risk of all-cause mortality. These associations were partly mediated by epigenetic age biomarkers, particularly the GrimAge and the DunedinPACE scores. The potential mediation effects by epigenetic age biomarkers tended to be more profound in participants with higher genetic risk for older epigenetic age, compared with those with lower genetic risk. For example, in participants with higher GrimAge polygenic scores (greater than median), the mean proportion of mediation was 39%, 39%, and 78% for the association of the LE8 score with incident CVD, CVD-specific mortality, and all-cause mortality, respectively. No significant mediation was observed in participants with lower GrimAge polygenic score. CONCLUSIONS DNA methylation-based epigenetic age scores mediate the associations between the LE8 score and incident CVD, CVD-specific mortality, and all-cause mortality, particularly in individuals with higher genetic predisposition for older epigenetic age.
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Affiliation(s)
- Madeleine Carbonneau
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute National Institutes of Health Bethesda MD
- Framingham Heart Study Framingham MA
| | - Yi Li
- Department of Biostatistics Boston University School of Public Health Boston MA
| | - Brenton Prescott
- Section of Preventive Medicine and Epidemiology Boston University School of Medicine Boston MA
| | - Chunyu Liu
- Department of Biostatistics Boston University School of Public Health Boston MA
| | - Tianxiao Huan
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute National Institutes of Health Bethesda MD
- Framingham Heart Study Framingham MA
| | - Roby Joehanes
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute National Institutes of Health Bethesda MD
- Framingham Heart Study Framingham MA
| | - Joanne M Murabito
- Framingham Heart Study Framingham MA
- Department of Medicine Section of General Internal Medicine Boston University Chobanian & Avedisian School of Medicine, Boston, MA and Boston Medical Center Boston MA
| | - Nancy L Heard-Costa
- Department of Medicine Section of General Internal Medicine Boston University Chobanian & Avedisian School of Medicine, Boston, MA and Boston Medical Center Boston MA
| | - Vanessa Xanthakis
- Framingham Heart Study Framingham MA
- Department of Biostatistics Boston University School of Public Health Boston MA
- Section of Preventive Medicine and Epidemiology Boston University School of Medicine Boston MA
| | - Daniel Levy
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute National Institutes of Health Bethesda MD
- Framingham Heart Study Framingham MA
| | - Jiantao Ma
- Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and Policy Tufts University Boston MA
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Gao H, Li J, Ma Q, Zhang Q, Li M, Hu X. Causal Associations of DNA Methylation and Cardiovascular Disease: A Two-Sample Mendelian Randomization Study. Glob Heart 2024; 19:48. [PMID: 38765775 PMCID: PMC11100526 DOI: 10.5334/gh.1324] [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: 12/12/2023] [Accepted: 04/16/2024] [Indexed: 05/22/2024] Open
Abstract
Background There is growing evidence that concentrations of DNA methylation are associated with cardiovascular disease; however, it is unclear whether this association reflects a causal relationship. Methods We utilized a two-sample Mendelian randomization (MR) approach to investigate whether DNA methylation can affect the risk of developing cardiovascular disease in human life. We primarily performed the inverse variance weighted (IVW) method to analyze the causal effect of DNA methylation on multiple cardiovascular diseases. Additionally, to ensure the robustness of our findings, we conducted several sensitivity analyses using alternative methodologies. These analysis methods included maximum likelihood, MR-Egger regression, weighted median method, and weighted model methods. Results Inverse variance weighted estimates suggested that an SD increase in DNA methylation Hannum age acceleration exposure increased the risk of cardiac arrhythmias (OR = 1.03, 95% CI 1.00-1.05, p = 0.0290) and atrial fibrillation (OR = 1.03, 95% CI 1.00-1.05, p = 0.0022). We also found that an SD increase in DNA methylation PhenoAge acceleration exposure increased the risk of heart failure (OR = 1.01, 95% CI 1.00-1.03, p = 0.0362). Exposure to DNA methylation-estimated granulocyte proportions was found to increase the risk of hypertension (OR = 1.00, 95% CI 1.00-1.0001, p = 0.0291). Exposure to DNA methylation-estimated plasminogen activator inhibitor-1 levels was found to increase the risk of heart failure (OR = 1.00, 95% CI 1.00-1.00, p = 0.0215). Conclusion This study reveals a causal relationship between DNA methylation and CVD. Exposed to high levels of DNA methylation Hannum age acceleration inhabitants with an increased risk of cardiac arrhythmias and atrial fibrillation. DNA methylation PhenoAge acceleration levels exposure levels were positively associated with the increased risk of developing heart failure. This has important implications for the prevention of cardiovascular diseases.
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Affiliation(s)
- Hui Gao
- Department of Cardiovascular Medicine, The First People’s Hospital of Shangqiu, Shangqiu 476000, China
- Graduate School, Dalian Medical University, Dalian, 116044, China
| | - Jiahai Li
- Department of Cardiovascular Medicine, The First People’s Hospital of Qinzhou, Qinzhou 535000, China
| | - Qiaoli Ma
- Department of Cardiovascular Medicine, Central Hospital of Zibo, Zibo 255000, China
| | - Qinghui Zhang
- Department of Hypertension, Henan Provincial People’s Hospital, Zhengzhou 450000, China
| | - Man Li
- Department of Cardiovascular Medicine, The First People’s Hospital of Shangqiu, Shangqiu 476000, China
| | - Xiaoliang Hu
- Department of Cardiovascular Medicine, The First People’s Hospital of Shangqiu, Shangqiu 476000, China
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Fan J, Liu Q, Liu X, Gong M, Leong II, Tsang Y, Xu X, Lei S, Duan L, Zhang Y, Liao M, Zhuang L. The effect of epigenetic aging on neurodegenerative diseases: a Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1372518. [PMID: 38800486 PMCID: PMC11116635 DOI: 10.3389/fendo.2024.1372518] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 04/19/2024] [Indexed: 05/29/2024] Open
Abstract
Background Aging has always been considered as a risk factor for neurodegenerative diseases, but there are individual differences and its mechanism is not yet clear. Epigenetics may unveil the relationship between aging and neurodegenerative diseases. Methods Our study employed a bidirectional two-sample Mendelian randomization (MR) design to assess the potential causal association between epigenetic aging and neurodegenerative diseases. We utilized publicly available summary datasets from several genome-wide association studies (GWAS). Our investigation focused on multiple measures of epigenetic age as potential exposures and outcomes, while the occurrence of neurodegenerative diseases served as potential exposures and outcomes. Sensitivity analyses confirmed the accuracy of the results. Results The results show a significant decrease in risk of Parkinson's disease with GrimAge (OR = 0.8862, 95% CI 0.7914-0.9924, p = 0.03638). Additionally, we identified that HannumAge was linked to an increased risk of Multiple Sclerosis (OR = 1.0707, 95% CI 1.0056-1.1401, p = 0.03295). Furthermore, we also found that estimated plasminogen activator inhibitor-1(PAI-1) levels demonstrated an increased risk for Alzheimer's disease (OR = 1.0001, 95% CI 1.0000-1.0002, p = 0.04425). Beyond that, we did not observe any causal associations between epigenetic age and neurodegenerative diseases risk. Conclusion The findings firstly provide evidence for causal association of epigenetic aging and neurodegenerative diseases. Exploring neurodegenerative diseases from an epigenetic perspective may contribute to diagnosis, prognosis, and treatment of neurodegenerative diseases.
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Affiliation(s)
- Jingqi Fan
- Institute of Neurology, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Qing Liu
- Institute of Neurology, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xin Liu
- Institute of Neurology, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Mengjiao Gong
- Institute of Neurology, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ian I. Leong
- Institute of Neurology, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - YauKeung Tsang
- Institute of Neurology, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xiaoyan Xu
- Institute of Neurology, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Suying Lei
- Institute of Neurology, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Lining Duan
- Institute of Neurology, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yifan Zhang
- Institute of Neurology, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Muxi Liao
- The First Affiliated Hospital of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Lixing Zhuang
- The First Affiliated Hospital of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
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Middeldorp CM, Doyle AE. Editorial: Can Improving Youth Mental Health Reduce Mortality? J Am Acad Child Adolesc Psychiatry 2024:S0890-8567(24)00236-3. [PMID: 38718974 DOI: 10.1016/j.jaac.2024.04.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2024] [Accepted: 04/29/2024] [Indexed: 05/20/2024]
Abstract
It is well established that mental health conditions, including substance use disorders, are associated with premature mortality. A meta-analysis1 has demonstrated that this association holds across a range of diagnoses. Although the effect is stronger for schizophrenia, depression and anxiety contribute to more deaths overall because of their high prevalence rates. Moreover, more than two-thirds of associated deaths were explained by natural causes.1 The next logical questions, then, are as follows: which mechanisms underlie this association, and can they can be mitigated? In the current issue of JAACAP, Clark et al.2 aim to tie mental health symptoms and substance use to the acceleration of biological aging.
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Affiliation(s)
- Christel M Middeldorp
- Amsterdam UMC, Child Psychiatry and Psychology, Amsterdam Reproduction and Development Research Institute, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Arkin Mental Health Care, Amsterdam, the Netherlands; Child Health Research Centre, University of Queensland, Brisbane, Australia; Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, Brisbane, Australia; Levvel, Academic Center for Child and Adolescent Psychiatry, Amsterdam, The Netherlands.
| | - Alysa E Doyle
- Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Center for Genomic Medicine, MGH, Boston, Massachusetts
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Drouard G, Mykkänen J, Heiskanen J, Pohjonen J, Ruohonen S, Pahkala K, Lehtimäki T, Wang X, Ollikainen M, Ripatti S, Pirinen M, Raitakari O, Kaprio J. Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data. BMC Med Inform Decis Mak 2024; 24:116. [PMID: 38698395 PMCID: PMC11064347 DOI: 10.1186/s12911-024-02521-3] [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: 11/04/2022] [Accepted: 04/29/2024] [Indexed: 05/05/2024] Open
Abstract
BACKGROUND Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little is known about which ML classifier, omics data, or upstream dimension reduction strategy has the strongest influence on prediction quality in such settings. Our study aimed to illustrate and compare different machine learning strategies to predict CVD risk factors under different scenarios. METHODS We compared the use of six ML classifiers in predicting CVD risk factors using blood-derived metabolomics, epigenetics and transcriptomics data. Upstream omic dimension reduction was performed using either unsupervised or semi-supervised autoencoders, whose downstream ML classifier performance we compared. CVD risk factors included systolic and diastolic blood pressure measurements and ultrasound-based biomarkers of left ventricular diastolic dysfunction (LVDD; E/e' ratio, E/A ratio, LAVI) collected from 1,249 Finnish participants, of which 80% were used for model fitting. We predicted individuals with low, high or average levels of CVD risk factors, the latter class being the most common. We constructed multi-omic predictions using a meta-learner that weighted single-omic predictions. Model performance comparisons were based on the F1 score. Finally, we investigated whether learned omic representations from pre-trained semi-supervised autoencoders could improve outcome prediction in an external cohort using transfer learning. RESULTS Depending on the ML classifier or omic used, the quality of single-omic predictions varied. Multi-omics predictions outperformed single-omics predictions in most cases, particularly in the prediction of individuals with high or low CVD risk factor levels. Semi-supervised autoencoders improved downstream predictions compared to the use of unsupervised autoencoders. In addition, median gains in Area Under the Curve by transfer learning compared to modelling from scratch ranged from 0.09 to 0.14 and 0.07 to 0.11 units for transcriptomic and metabolomic data, respectively. CONCLUSIONS By illustrating the use of different machine learning strategies in different scenarios, our study provides a platform for researchers to evaluate how the choice of omics, ML classifiers, and dimension reduction can influence the quality of CVD risk factor predictions.
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Affiliation(s)
- Gabin Drouard
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
| | - Juha Mykkänen
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Jarkko Heiskanen
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Joona Pohjonen
- Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland
| | - Saku Ruohonen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Katja Pahkala
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Paavo Nurmi Centre & Unit for Health and Physical Activity, University of Turku, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland
| | - Xiaoling Wang
- Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
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Feng Y, Lin H, Tan H, Liu X. Heterogeneity of aging and mortality risk among individuals with hypertension: Insights from phenotypic age and phenotypic age acceleration. J Nutr Health Aging 2024; 28:100203. [PMID: 38460315 DOI: 10.1016/j.jnha.2024.100203] [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: 11/01/2023] [Revised: 02/20/2024] [Accepted: 02/21/2024] [Indexed: 03/11/2024]
Abstract
OBJECTIVES Hypertension, a key contributor to mortality, is impacted by biological aging. We investigated the relationship between novel biological aging metrics - Phenotypic Age (PA) and Phenotypic Age Acceleration (PAA) - and mortality in individuals with hypertension, exploring the mediating effects of arterial stiffness (estimated Pulse Wave Velocity, ePWV), and Heart/Vascular Age (HVA). METHODS Using data from 62,160 National Health and Nutrition Examination Survey (NHANES) participants (1999-2010), we selected 4,228 individuals with hypertension and computed PA, PAA, HVA, and ePWV. Weighted, multivariable Cox regression analysis yielded Hazard Ratios (HRs) relating PA, PAA to mortality, and mediation roles of ePWV, PAA, HVA were evaluated. Mendelian randomization (MR) analysis was employed to investigate causality between genetically inferred PAA and hypertension. RESULTS Over a 12-year median follow-up, PA and PAA were tied to increased mortality risks in individuals with hypertension. All-cause mortality hazard ratios per 10-year PA and PAA increments were 1.96 (95% CI, 1.81-2.11) and 1.67 (95% CI, 1.52-1.85), respectively. Cardiovascular mortality HRs were 2.32 (95% CI, 1.97-2.73) and 1.93 (95% CI, 1.65-2.26) for PA and PAA, respectively. ePWV, PAA, and HVA mediated 42%, 30.3%, and 6.9% of PA's impact on mortality, respectively. Mendelian randomization highlighted a causal link between PAA genetics and hypertension (OR = 1.002; 95% CI, 1.000-1.003). CONCLUSION PA and PAA, enhancing cardiovascular risk scores by integrating diverse biomarkers, offer vital insights for aging and mortality evaluation in individuals with hypertension, suggesting avenues for intensified aging mitigation and cardiovascular issue prevention. Validations in varied populations and explorations of underlying mechanisms are warranted.
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Affiliation(s)
- Yuntao Feng
- Department of Cardiology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - Hao Lin
- Department of Cardiology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - Hongwei Tan
- Department of Cardiology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China.
| | - Xuebo Liu
- Department of Cardiology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China.
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Zhang T, Liu J, Liu X, Wang Q, Zhang H. The causal impact of gut microbiota on circulating adipokine concentrations: a two-sample Mendelian randomization study. Hormones (Athens) 2024:10.1007/s42000-024-00553-y. [PMID: 38564143 DOI: 10.1007/s42000-024-00553-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 03/19/2024] [Indexed: 04/04/2024]
Abstract
PURPOSE Evidence from previous experimental and observational research demonstrates that the gut microbiota is related to circulating adipokine concentrations. Nevertheless, the debate as to whether gut microbiome composition causally influences circulating adipokine concentrations remains unresolved. This study aimed to take an essential step in elucidating this issue. METHODS We used two-sample Mendelian randomization (MR) to causally analyze genetic variation statistics for gut microbiota and four adipokines (including adiponectin, leptin, soluble leptin receptor [sOB-R], and plasminogen activator inhibitor-1 [PAI-1]) from large-scale genome-wide association studies (GWAS) datasets. A range of sensitivity analyses was also conducted to assess the stability and reliability of the results. RESULTS The composite results of the MR and sensitivity analyses revealed 22 significant causal associations. In particular, there is a suggestive causality between the family Clostridiaceae1 (IVW: β = 0.063, P = 0.034), the genus Butyrivibrio (IVW: β = 0.029, P = 0.031), and the family Alcaligenaceae (IVW: β=-0.070, P = 0.014) and adiponectin. Stronger causal effects with leptin were found for the genus Enterorhabdus (IVW: β=-0.073, P = 0.038) and the genus Lachnospiraceae (NK4A136 group) (IVW: β=-0.076, P = 0.01). Eight candidate bacterial groups were found to be associated with sOB-R, with the phylum Firmicutes (IVW: β = 0.235, P = 0.03) and the order Clostridiales (IVW: β = 0.267, P = 0.028) being of more interest. In addition, the genus Roseburia (IVW: β = 0.953, P = 0.022) and the order Lactobacillales (IVW: β=-0.806, P = 0.042) were suggestive of an association with PAI-1. CONCLUSION This study reveals a causal relationship between the gut microbiota and circulating adipokines and may help to offer novel insights into the prevention of abnormal concentrations of circulating adipokines and obesity-related diseases.
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Affiliation(s)
- Tongxin Zhang
- Department of Ultrasound, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China
| | - Jingyu Liu
- Department of Ultrasound, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China
| | - Xiao Liu
- Department of Ultrasound, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China
| | - Qian Wang
- Department of Ultrasound, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China.
| | - Huawei Zhang
- Department of Ultrasound, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China.
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Noroozi R, Rudnicka J, Pisarek A, Wysocka B, Masny A, Boroń M, Migacz-Gruszka K, Pruszkowska-Przybylska P, Kobus M, Lisman D, Zielińska G, Iljin A, Wiktorska JA, Michalczyk M, Kaczka P, Krzysztofik M, Sitek A, Ossowski A, Spólnicka M, Branicki W, Pośpiech E. Analysis of epigenetic clocks links yoga, sleep, education, reduced meat intake, coffee, and a SOCS2 gene variant to slower epigenetic aging. GeroScience 2024; 46:2583-2604. [PMID: 38103096 PMCID: PMC10828238 DOI: 10.1007/s11357-023-01029-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/23/2023] [Indexed: 12/17/2023] Open
Abstract
DNA methylation (DNAm) clocks hold promise for measuring biological age, useful for guiding clinical interventions and forensic identification. This study compared the commonly used DNAm clocks, using DNA methylation and SNP data generated from nearly 1000 human blood or buccal swab samples. We evaluated different preprocessing methods for age estimation, investigated the association of epigenetic age acceleration (EAA) with various lifestyle and sociodemographic factors, and undertook a series of novel genome-wide association analyses for different EAA measures to find associated genetic variants. Our results highlighted the Skin&Blood clock with ssNoob normalization as the most accurate predictor of chronological age. We provided novel evidence for an association between the practice of yoga and a reduction in the pace of aging (DunedinPACE). Increased sleep and physical activity were associated with lower mortality risk score (MRS) in our dataset. University degree, vegetable consumption, and coffee intake were associated with reduced levels of epigenetic aging, whereas smoking, higher BMI, meat consumption, and manual occupation correlated well with faster epigenetic aging, with FitAge, GrimAge, and DunedinPACE clocks showing the most robust associations. In addition, we found a novel association signal for SOCS2 rs73218878 (p = 2.87 × 10-8) and accelerated GrimAge. Our study emphasizes the importance of an optimized DNAm analysis workflow for accurate estimation of epigenetic age, which may influence downstream analyses. The results support the influence of genetic background on EAA. The associated SOCS2 is a member of the suppressor of cytokine signaling family known for its role in human longevity. The reported association between various risk factors and EAA has practical implications for the development of health programs to improve quality of life and reduce premature mortality associated with age-related diseases.
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Affiliation(s)
- Rezvan Noroozi
- Doctoral School of Exact and Natural Sciences, Jagiellonian University, Krakow, Poland
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joanna Rudnicka
- Doctoral School of Exact and Natural Sciences, Jagiellonian University, Krakow, Poland
- Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
| | - Aleksandra Pisarek
- Institute of Zoology and Biomedical Research of the Jagiellonian University, Krakow, Poland
| | - Bożena Wysocka
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | | | - Michał Boroń
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | | | | | - Magdalena Kobus
- Institute of Biological Sciences, Faculty of Biology and Environmental Sciences, Cardinal Stefan Wyszynski University in Warsaw, Warsaw, Poland
| | - Dagmara Lisman
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Grażyna Zielińska
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Aleksandra Iljin
- Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Lodz, Lodz, Poland
| | | | - Małgorzata Michalczyk
- Department of Sport Nutrition, The Jerzy Kukuczka Academy of Physical Education in Katowice, Katowice, Poland
| | - Piotr Kaczka
- Department of Sport Nutrition, The Jerzy Kukuczka Academy of Physical Education in Katowice, Katowice, Poland
| | - Michał Krzysztofik
- Department of Sport Nutrition, The Jerzy Kukuczka Academy of Physical Education in Katowice, Katowice, Poland
| | - Aneta Sitek
- Department of Anthropology, University of Lodz, Lodz, Poland
| | - Andrzej Ossowski
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | | | - Wojciech Branicki
- Institute of Zoology and Biomedical Research of the Jagiellonian University, Krakow, Poland
- Institute of Forensic Research, Krakow, Poland
| | - Ewelina Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland.
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland.
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10
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Yang X, QimeiZhong, Huang M, Li L, Tang C, Luo S, Wang L, Qi H. Causal relationship between gestational diabetes and preeclampsia: A bidirectional mendelian randomization analysis. Diabetes Res Clin Pract 2024; 210:111643. [PMID: 38548111 DOI: 10.1016/j.diabres.2024.111643] [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: 02/27/2024] [Revised: 03/19/2024] [Accepted: 03/25/2024] [Indexed: 04/01/2024]
Abstract
AIMS The study aimed to explore the potential causal link between gestational diabetes mellitus (GDM) and preeclampsia (PE) using a bidirectional mendelian randomization (MR) analysis. MATERIALS We conducted a bidirectional MR analysis to investigate the causal relationship between GDM and PE. Data from public genome-wide association studies (GWAS) for GDM and PE were obtained from the FinnGen consortium. Various MR methods were employed, including inverse-variance weighted (IVW), MR-Egger, and sensitivity analyses. Additionally, a knowledge-based approach identified genes underlying this potential connection. RESULTS The IVW method revealed a lack of significant association between GDM and PE (OR: 1.04, 95 % CI: 0.96-1.14; p = 0.275). Conversely, IVW analysis indicated a causal connection from PE to GDM (OR: 1.14, 95 % CI: 1.06-1.23; p < 0.001). Molecular pathway analysis identified 20 key genes, including ASAP2, central to the PE-GDM relationship. Tissue enrichment analysis showed pertinent gene expression in significant tissues. Moreover, lower ASAP2 expression was detected in PE patients' placentas. CONCLUSIONS Our bidirectional MR analysis offers evidence supporting a causal link between PE and GDM, elucidating their interconnected pathogenesis. Genetic and knowledge-based insights facilitate a deeper comprehension of these complex pregnancy complications.
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Affiliation(s)
- Xiaofeng Yang
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, No.120 Longshan Road, Yubei District, Chongqing, 401147, China; Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, No.120 Longshan Road, Yubei District, Chongqing, 401147, China
| | - QimeiZhong
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, No.120 Longshan Road, Yubei District, Chongqing, 401147, China; Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, No.120 Longshan Road, Yubei District, Chongqing, 401147, China
| | - Mengwei Huang
- Department of Obstetrics and Gynecology, Chengdu First People 's Hospital, No.18 Wanxiang North Road, Chengdu High-tech Zone, Sichuan Province 610095, China
| | - Li Li
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, No.120 Longshan Road, Yubei District, Chongqing, 401147, China; Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, No.120 Longshan Road, Yubei District, Chongqing, 401147, China
| | - Chunyan Tang
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, No.120 Longshan Road, Yubei District, Chongqing, 401147, China; Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, No.120 Longshan Road, Yubei District, Chongqing, 401147, China
| | - Shujuan Luo
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, No.120 Longshan Road, Yubei District, Chongqing, 401147, China; Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, No.120 Longshan Road, Yubei District, Chongqing, 401147, China
| | - Lan Wang
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, No.120 Longshan Road, Yubei District, Chongqing, 401147, China; Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, No.120 Longshan Road, Yubei District, Chongqing, 401147, China.
| | - Hongbo Qi
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children, No.120 Longshan Road, Yubei District, Chongqing, 401147, China; Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, No.120 Longshan Road, Yubei District, Chongqing, 401147, China.
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11
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Li Y, Chen J, Sun T, Chen Y, Fu R, Liu X, Xue F, Liu W, Ju M, Dai X, Dong H, Li H, Wang W, Chi Y, Zhang L. Genetically determined telomere length and risk for haematologic diseases: results from large prospective cohorts and Mendelian Randomization analysis. Blood Cancer J 2024; 14:48. [PMID: 38499533 PMCID: PMC10948832 DOI: 10.1038/s41408-024-01035-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 02/29/2024] [Accepted: 03/07/2024] [Indexed: 03/20/2024] Open
Affiliation(s)
- Yang Li
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Jia Chen
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Ting Sun
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Yunfei Chen
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Rongfeng Fu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Xiaofan Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Feng Xue
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Wei Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Mankai Ju
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Xinyue Dai
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Huan Dong
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Huiyuan Li
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Wentian Wang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Ying Chi
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Lei Zhang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin, 300020, China.
- Tianjin Institutes of Health Science, Tianjin, 301600, China.
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
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12
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Constantinescu AE, Hughes DA, Bull CJ, Fleming K, Mitchell RE, Zheng J, Kar S, Timpson NJ, Amulic B, Vincent EE. A genome-wide association study of neutrophil count in individuals associated to an African continental ancestry group facilitates studies of malaria pathogenesis. Hum Genomics 2024; 18:26. [PMID: 38491524 PMCID: PMC10941368 DOI: 10.1186/s40246-024-00585-w] [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: 10/19/2023] [Accepted: 02/12/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND 'Benign ethnic neutropenia' (BEN) is a heritable condition characterized by lower neutrophil counts, predominantly observed in individuals of African ancestry, and the genetic basis of BEN remains a subject of extensive research. In this study, we aimed to dissect the genetic architecture underlying neutrophil count variation through a linear-mixed model genome-wide association study (GWAS) in a population of African ancestry (N = 5976). Malaria caused by P. falciparum imposes a tremendous public health burden on people living in sub-Saharan Africa. Individuals living in malaria endemic regions often have a reduced circulating neutrophil count due to BEN, raising the possibility that reduced neutrophil counts modulate severity of malaria in susceptible populations. As a follow-up, we tested this hypothesis by conducting a Mendelian randomization (MR) analysis of neutrophil counts on severe malaria (MalariaGEN, N = 17,056). RESULTS We carried out a GWAS of neutrophil count in individuals associated to an African continental ancestry group within UK Biobank, identifying 73 loci (r2 = 0.1) and 10 index SNPs (GCTA-COJO loci) associated with neutrophil count, including previously unknown rare loci regulating neutrophil count in a non-European population. BOLT-LMM was reliable when conducted in a non-European population, and additional covariates added to the model did not largely alter the results of the top loci or index SNPs. The two-sample bi-directional MR analysis between neutrophil count and severe malaria showed the greatest evidence for an effect between neutrophil count and severe anaemia, although the confidence intervals crossed the null. CONCLUSION Our GWAS of neutrophil count revealed unique loci present in individuals of African ancestry. We note that a small sample-size reduced our power to identify variants with low allele frequencies and/or low effect sizes in our GWAS. Our work highlights the need for conducting large-scale biobank studies in Africa and for further exploring the link between neutrophils and severe malaria.
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Affiliation(s)
- Andrei-Emil Constantinescu
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- School of Translational Health Sciences, University of Bristol, Bristol, UK
| | - David A Hughes
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- Louisiana State University, Louisiana, USA
| | - Caroline J Bull
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- School of Translational Health Sciences, University of Bristol, Bristol, UK
- Health Data Research UK, London, UK
| | - Kathryn Fleming
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - Ruth E Mitchell
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases, National Health Commission, Shanghai, People's Republic of China
- Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Siddhartha Kar
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- Early Cancer Insitute, University of Cambridge, Cambridge, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Borko Amulic
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK.
| | - Emma E Vincent
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK.
- School of Translational Health Sciences, University of Bristol, Bristol, UK.
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13
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Pan W, Huang Q, Zhou L, Lin J, Du X, Qian X, Jiang T, Chen W. Epigenetic age acceleration and risk of aortic valve stenosis: a bidirectional Mendelian randomization study. Clin Epigenetics 2024; 16:41. [PMID: 38475866 PMCID: PMC10936111 DOI: 10.1186/s13148-024-01647-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 02/19/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND Aortic valve stenosis (AVS) is the most prevalent cardiac valve lesion in developed countries, and pathogenesis is closely related to aging. DNA methylation-based epigenetic clock is now recognized as highly accurate predictor of the aging process and associated health outcomes. This study aimed to explore the causal relationship between epigenetic clock and AVS by conducting a bidirectional Mendelian randomization (MR) analysis. METHODS Summary genome-wide association study statistics of epigenetic clocks (HannumAge, HorvathAge, PhenoAge, and GrimAge) and AVS were obtained and assessed for significant instrumental variables from Edinburgh DataShare (n = 34,710) and FinnGen biobank (cases = 9870 and controls = 402,311). The causal association between epigenetic clock and AVS was evaluated using inverse variance weighted (IVW), weighted median (WM), and MR-Egger methods. Multiple analyses (heterogeneity analysis, pleiotropy analysis, and sensitivity analysis) were performed for quality control assessment. RESULTS The MR analysis showed that the epigenetic age acceleration of HorvathAge and PhenoAge was associated with an increased risk of AVS (HorvathAge: OR = 1.043, P = 0.016 by IVW, OR = 1.058, P = 0.018 by WM; PhenoAge: OR = 1.058, P = 0.005 by IVW, OR = 1.053, P = 0.039 by WM). Quality control assessment proved our findings were reliable and robust. However, there was a lack of evidence supporting a causal link from AVS to epigenetic aging. CONCLUSION The present MR analysis unveiled a causal association between epigenetic clocks, especially HorvathAge and PhenoAge, with AVS. Further research is required to elucidate the underlying mechanisms and develop strategies for potential interventions.
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Affiliation(s)
- Wanqian Pan
- Department of Cardiology, The First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou, 215006, Jiangsu, People's Republic of China
| | - Qi Huang
- Department of Cardiology, The First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou, 215006, Jiangsu, People's Republic of China
| | - Le Zhou
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, 215000, Jiangsu Province, People's Republic of China
| | - Jia Lin
- Department of Cardiology, The First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou, 215006, Jiangsu, People's Republic of China
| | - Xiaojiao Du
- Department of Cardiology, The First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou, 215006, Jiangsu, People's Republic of China
| | - Xiaodong Qian
- Department of Cardiology, The First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou, 215006, Jiangsu, People's Republic of China.
| | - Tingbo Jiang
- Department of Cardiology, The First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou, 215006, Jiangsu, People's Republic of China.
| | - Weixiang Chen
- Department of Cardiology, The First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou, 215006, Jiangsu, People's Republic of China.
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Don J, Schork AJ, Glusman G, Rappaport N, Cummings SR, Duggan D, Raju A, Hellberg KLG, Gunn S, Monti S, Perls T, Lapidus J, Goetz LH, Sebastiani P, Schork NJ. The relationship between 11 different polygenic longevity scores, parental lifespan, and disease diagnosis in the UK Biobank. GeroScience 2024:10.1007/s11357-024-01107-1. [PMID: 38451433 DOI: 10.1007/s11357-024-01107-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 02/21/2024] [Indexed: 03/08/2024] Open
Abstract
Large-scale genome-wide association studies (GWAS) strongly suggest that most traits and diseases have a polygenic component. This observation has motivated the development of disease-specific "polygenic scores (PGS)" that are weighted sums of the effects of disease-associated variants identified from GWAS that correlate with an individual's likelihood of expressing a specific phenotype. Although most GWAS have been pursued on disease traits, leading to the creation of refined "Polygenic Risk Scores" (PRS) that quantify risk to diseases, many GWAS have also been pursued on extreme human longevity, general fitness, health span, and other health-positive traits. These GWAS have discovered many genetic variants seemingly protective from disease and are often different from disease-associated variants (i.e., they are not just alternative alleles at disease-associated loci) and suggest that many health-positive traits also have a polygenic basis. This observation has led to an interest in "polygenic longevity scores (PLS)" that quantify the "risk" or genetic predisposition of an individual towards health. We derived 11 different PLS from 4 different available GWAS on lifespan and then investigated the properties of these PLS using data from the UK Biobank (UKB). Tests of association between the PLS and population structure, parental lifespan, and several cancerous and non-cancerous diseases, including death from COVID-19, were performed. Based on the results of our analyses, we argue that PLS are made up of variants not only robustly associated with parental lifespan, but that also contribute to the genetic architecture of disease susceptibility, morbidity, and mortality.
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Affiliation(s)
- Janith Don
- Translational Genomics Research Institute (TGen), Phoenix, AZ, USA
| | - Andrew J Schork
- The Institute of Biological Psychiatry, Copenhagen University Hospital, Copenhagen, Denmark
- GLOBE Institute, Copenhagen University, Copenhagen, Denmark
| | | | | | - Steve R Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - David Duggan
- Translational Genomics Research Institute (TGen), Phoenix, AZ, USA
| | - Anish Raju
- Translational Genomics Research Institute (TGen), Phoenix, AZ, USA
| | - Kajsa-Lotta Georgii Hellberg
- The Institute of Biological Psychiatry, Copenhagen University Hospital, Copenhagen, Denmark
- GLOBE Institute, Copenhagen University, Copenhagen, Denmark
| | - Sophia Gunn
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Stefano Monti
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Thomas Perls
- Department of Medicine, Section of Geriatrics, Boston University, Boston, MA, USA
| | - Jodi Lapidus
- Department of Biostatistics, Oregon Health & Science University, Portland, OR, USA
| | - Laura H Goetz
- Translational Genomics Research Institute (TGen), Phoenix, AZ, USA
- Veterans Affairs Loma Linda Health Care, Loma Linda, CA, USA
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA
- Tufts University School of Medicine and Data Intensive Study Center, Boston, MA, USA
| | - Nicholas J Schork
- Translational Genomics Research Institute (TGen), Phoenix, AZ, USA.
- The City of Hope National Medical Center, Duarte, CA, USA.
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15
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Xu Z, Qi L, Zhang H, Yu D, Shi Y, Yu Y, Zhu T. Smoking and BMI mediate the causal effect of education on lower back pain: observational and Mendelian randomization analyses. Front Endocrinol (Lausanne) 2024; 15:1288170. [PMID: 38390198 PMCID: PMC10882710 DOI: 10.3389/fendo.2024.1288170] [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: 09/03/2023] [Accepted: 01/10/2024] [Indexed: 02/24/2024] Open
Abstract
Objective Low back pain (LBP) has been associated with education in previous observational studies, but the causality remains unclear. This study aims to assess the impact of education on LBP and to explore mediation by multiple lifestyle factors. Design Univariable Mendelian randomization (MR) was performed to examine the overall effect of education on LBP. Subsequently, multivariable MR was conducted to assess both the direct effect of education on LBP and the influence of potential mediators. Indirect effects were estimated using either the coefficient product method or the difference method, and the proportion of mediation was calculated by dividing the indirect effect by the total effect. The observational study utilized data from the NHANES database collected between 1999 and 2004, and included 15,580 participants aged 20 years and above. Results Increasing education by 4.2 years leads to a 48% reduction in the risk of LBP (OR=0.52; 95% CI: 0.46 to 0.59). Compared to individuals with less than a high school education, those with education beyond high school have a 28% lower risk of LBP (OR=0.72; 95% CI: 0.63 to 0.83). In the MR study, smoking accounts for 12.8% (95% CI: 1.04% to 20.8%) of the total effect, while BMI accounts for 5.9% (95% CI: 2.99% to 8.55%). The combined mediation effect of smoking and BMI is 27.6% (95% CI: 23.99% to 32.7%). In the NHANES study, only smoking exhibits a mediating effect, accounting for 34.3% (95% CI: 21.07% to 41.65%) of the effect, while BMI does not demonstrate a mediating role. Conclusions Higher levels of education provide a protective effect against the risk of LBP. Additionally, implementing interventions to reduce smoking and promote weight loss among individuals with lower levels of education can also decrease this risk.
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Affiliation(s)
- Zhangmeng Xu
- Department of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Luming Qi
- Department of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Huiwu Zhang
- Department of Sports Medicine, Sichuan Province Orthopedic Hospital, Chengdu, Sichuan, China
| | - Duoduo Yu
- Department of Sports Medicine, Sichuan Province Orthopedic Hospital, Chengdu, Sichuan, China
| | - Yushan Shi
- Department of Medical Laboratory, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Yaming Yu
- Department of Sports Medicine, Sichuan Province Orthopedic Hospital, Chengdu, Sichuan, China
| | - Tianmin Zhu
- Department of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
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16
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Qin S, Sheng Z, Chen C, Cao Y. Genetic relationship between ageing and coronary heart disease: a Mendelian randomization study. Eur Geriatr Med 2024; 15:159-167. [PMID: 37948032 DOI: 10.1007/s41999-023-00888-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 10/18/2023] [Indexed: 11/12/2023]
Abstract
PURPOSE Genetic relationship between ageing and coronary heart disease has not been well investigated. The aim of the study was to explore the association of several ageing biomarkers with the risk of several types of coronary heart disease using the Mendelian randomization approach. METHODS Summary data for telomere length, four epigenetic clocks (such as intrinsic epigenetic age acceleration), four types of coronary heart disease (such as myocardial infarction) were collected from the most updated and available genome-wide association studies. Instrumental variables were extracted from the exposure-related summary data according to correlation, independence and exclusivity assumptions. Three Mendelian randomization methods (such as inverse variance weighted) were used for causal inference. Four sensitivity analyses (such as MR-Egger intercept) were performed to prevent horizontal pleiotropy. RESULTS Inverse variance weighted reported that longer telomere length was related to the lower risk of myocardial infarction, angina pectoris, unstable angina pectoris and coronary atherosclerosis (P = 8.840e-11, P = 9.830e-04, P = 1.539e-05, P = 2.607e-09). Inverse variance weighted also reported that four epigenetic clocks might be not implicated in the risk of these coronary heart diseases. Furthermore, there was not enough evidence to confirm the effect of coronary heart disease on these ageing biomarkers. CONCLUSION Longer telomere length, but not the epigenetic clock changes, genetically decreased the risk of coronary heart disease. Considering that telomere length and epigenetic clocks were two independent ageing biomarkers, the correlation between ageing and coronary heart disease might be redefined at the genetic level.
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Affiliation(s)
- Sirun Qin
- Department of Cardiovascular Medicine, The Third Xiangya Hospital of Central South University, No. 138, Tongzipo Road, Changsha, 410013, Hunan Province, China
| | - Zhe Sheng
- Department of Cardiovascular Medicine, The Third Xiangya Hospital of Central South University, No. 138, Tongzipo Road, Changsha, 410013, Hunan Province, China
| | - Chenyang Chen
- Department of Cardiovascular Medicine, The Third Xiangya Hospital of Central South University, No. 138, Tongzipo Road, Changsha, 410013, Hunan Province, China
| | - Yu Cao
- Department of Cardiovascular Medicine, The Third Xiangya Hospital of Central South University, No. 138, Tongzipo Road, Changsha, 410013, Hunan Province, China.
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Niu J, Jiao Q, Cui D, Dou R, Guo Y, Yu G, Zhang X, Sun F, Qiu J, Dong L, Cao W. Age-associated cortical similarity networks correlate with cell type-specific transcriptional signatures. Cereb Cortex 2024; 34:bhad454. [PMID: 38037843 DOI: 10.1093/cercor/bhad454] [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: 09/25/2023] [Accepted: 11/07/2023] [Indexed: 12/02/2023] Open
Abstract
Human brain structure shows heterogeneous patterns of change across adults aging and is associated with cognition. However, the relationship between cortical structural changes during aging and gene transcription signatures remains unclear. Here, using structural magnetic resonance imaging data of two separate cohorts of healthy participants from the Cambridge Centre for Aging and Neuroscience (n = 454, 18-87 years) and Dallas Lifespan Brain Study (n = 304, 20-89 years) and a transcriptome dataset, we investigated the link between cortical morphometric similarity network and brain-wide gene transcription. In two cohorts, we found reproducible morphometric similarity network change patterns of decreased morphological similarity with age in cognitive related areas (mainly located in superior frontal and temporal cortices), and increased morphological similarity in sensorimotor related areas (postcentral and lateral occipital cortices). Changes in morphometric similarity network showed significant spatial correlation with the expression of age-related genes that enriched to synaptic-related biological processes, synaptic abnormalities likely accounting for cognitive decline. Transcription changes in astrocytes, microglia, and neuronal cells interpreted most of the age-related morphometric similarity network changes, which suggest potential intervention and therapeutic targets for cognitive decline. Taken together, by linking gene transcription signatures to cortical morphometric similarity network, our findings might provide molecular and cellular substrates for cortical structural changes related to cognitive decline across adults aging.
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Affiliation(s)
- Jinpeng Niu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an 271000, China
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an 271016, China
| | - Qing Jiao
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an 271000, China
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an 271016, China
| | - Dong Cui
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an 271000, China
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an 271016, China
| | - Ruhai Dou
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an 271000, China
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an 271016, China
| | - Yongxin Guo
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an 271000, China
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an 271016, China
| | - Guanghui Yu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an 271000, China
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an 271016, China
| | - Xiaotong Zhang
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an 271016, China
| | - Fengzhu Sun
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an 271016, China
| | - Jianfeng Qiu
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an 271016, China
| | - Li Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Weifang Cao
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an 271000, China
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an 271016, China
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18
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Zhang Z, Liu N, Pan X, Zhang C, Yang Y, Li X, Shao Y. Assessing causal associations between neurodegenerative diseases and neurological tumors with biological aging: a bidirectional Mendelian randomization study. Front Neurosci 2023; 17:1321246. [PMID: 38169680 PMCID: PMC10758410 DOI: 10.3389/fnins.2023.1321246] [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: 10/13/2023] [Accepted: 11/29/2023] [Indexed: 01/05/2024] Open
Abstract
Background Aging is a significant risk factor for many neurodegenerative diseases and neurological tumors. Previous studies indicate that the frailty index, facial aging, telomere length (TL), and epigenetic aging clock acceleration are commonly used biological aging proxy indicators. This study aims to comprehensively explore potential relationships between biological aging and neurodegenerative diseases and neurological tumors by integrating various biological aging proxy indicators, employing Mendelian randomization (MR) analysis. Methods Two-sample bidirectional MR analyses were conducted using genome-wide association study (GWAS) data. Summary statistics for various neurodegenerative diseases and neurological tumors, along with biological aging proxy indicators, were obtained from extensive meta-analyses of GWAS. Genetic single-nucleotide polymorphisms (SNPs) associated with the exposures were used as instrumental variables, assessing causal relationships between three neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis), two benign neurological tumors (vestibular schwannoma and meningioma), one malignant neurological tumor (glioma), and four biological aging indicators (frailty index, facial aging, TL, and epigenetic aging clock acceleration). Sensitivity analyses were also performed. Results Our analysis revealed that genetically predicted longer TL reduces the risk of Alzheimer's disease but increases the risk of vestibular schwannoma and glioma (All Glioma, GBM, non-GBM). In addition, there is a suggestive causal relationship between some diseases (PD and GBM) and DNA methylation GrimAge acceleration. Causal relationships between biological aging proxy indicators and other neurodegenerative diseases and neurological tumors were not observed. Conclusion Building upon prior investigations into the causal relationships between telomeres and neurodegenerative diseases and neurological tumors, our study validates these findings using larger GWAS data and demonstrates, for the first time, that Parkinson's disease and GBM may promote epigenetic age acceleration. Our research provides new insights and evidence into the causal relationships between biological aging and the risk of neurodegenerative diseases and neurological tumors.
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Affiliation(s)
- Zhiyun Zhang
- Department of Plastic and Reconstructive Surgery, The First Hospital of Jilin University, Changchun, China
| | - Ningfang Liu
- Department of Anesthesiology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Xuyang Pan
- Department of Plastic and Reconstructive Surgery, The First Hospital of Jilin University, Changchun, China
| | - Chuyi Zhang
- Department of Plastic and Reconstructive Surgery, The First Hospital of Jilin University, Changchun, China
| | - Yifan Yang
- The Second Hospital of Jilin University, Changchun, Jilin, China
| | - Xinyun Li
- Infection Department, The First Bethune Hospital of Jilin University, Changchun, China
| | - Ying Shao
- Department of Plastic and Reconstructive Surgery, The First Hospital of Jilin University, Changchun, China
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Koch Z, Li A, Evans DS, Cummings S, Ideker T. Somatic mutation as an explanation for epigenetic aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.08.569638. [PMID: 38106096 PMCID: PMC10723383 DOI: 10.1101/2023.12.08.569638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
DNA methylation marks have recently been used to build models known as "epigenetic clocks" which predict calendar age. As methylation of cytosine promotes C-to-T mutations, we hypothesized that the methylation changes observed with age should reflect the accrual of somatic mutations, and the two should yield analogous aging estimates. In analysis of multimodal data from 9,331 human individuals, we find that CpG mutations indeed coincide with changes in methylation, not only at the mutated site but also with pervasive remodeling of the methylome out to ±10 kilobases. This one-to-many mapping enables mutation-based predictions of age that agree with epigenetic clocks, including which individuals are aging faster or slower than expected. Moreover, genomic loci where mutations accumulate with age also tend to have methylation patterns that are especially predictive of age. These results suggest a close coupling between the accumulation of sporadic somatic mutations and the widespread changes in methylation observed over the course of life.
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Affiliation(s)
- Zane Koch
- Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla CA, 92093, USA
| | - Adam Li
- Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla CA, 92093, USA
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco CA 94158, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, 94158
| | - Steven Cummings
- California Pacific Medical Center Research Institute, San Francisco CA 94158, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, 94158
| | - Trey Ideker
- Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla CA, 92093, USA
- Department of Medicine, University of California San Diego, La Jolla California, 92093, USA
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20
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Qiu W, Chen H, Kaeberlein M, Lee SI. ExplaiNAble BioLogical Age (ENABL Age): an artificial intelligence framework for interpretable biological age. THE LANCET. HEALTHY LONGEVITY 2023; 4:e711-e723. [PMID: 37944549 DOI: 10.1016/s2666-7568(23)00189-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 08/10/2023] [Accepted: 08/30/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND Biological age is a measure of health that offers insights into ageing. The existing age clocks, although valuable, often trade off accuracy and interpretability. We introduce ExplaiNAble BioLogical Age (ENABL Age), a computational framework that combines machine-learning models with explainable artificial intelligence (XAI) methods to accurately estimate biological age with individualised explanations. METHODS To construct the ENABL Age clock, we first predicted an age-related outcome (eg, all-cause or cause-specific mortality), and then rescaled these predictions to estimate biological age, using UK Biobank and National Health and Nutrition Examination Survey (NHANES) datasets. We adapted existing XAI methods to decompose individual ENABL Ages into contributing risk factors. For broad accessibility, we developed two versions: ENABL Age-L, based on blood tests, and ENABL Age-Q, based on questionnaire characteristics. Finally, we validated diverse ageing mechanisms captured by each ENABL Age clock through genome-wide association studies (GWAS) association analyses. FINDINGS Our ENABL Age clock was significantly correlated with chronological age (r=0·7867, p<0·0001 for UK Biobank; r=0·7126, p<0·0001 for NHANES). These clocks distinguish individuals who are healthy (ie, their ENABL Age is lower than their chronological age) from those who are unhealthy (ie, their ENABL Age is higher than their chronological age), predicting mortality more effectively than existing clocks. Groups of individuals who were unhealthy showed approximately three to 12 times higher log hazard ratio than healthy groups, as per ENABL Age. The clocks achieved high mortality prediction power with an area under the receiver operating characteristic curve of 0·8179 for 5-year mortality and 0·8115 for 10-year mortality on the UK Biobank dataset, and 0·8935 for 5-year mortality and 0·9107 for 10-year mortality on the NHANES dataset. The individualised explanations that revealed the contribution of specific characteristics to ENABL Age provided insights into the important characteristics for ageing. An association analysis with risk factors and ageing-related morbidities and GWAS results on ENABL Age clocks trained on different mortality causes showed that each clock captures distinct ageing mechanisms. INTERPRETATION ENABL Age brings an important leap forward in the application of XAI for interpreting biological age clocks. ENABL Age also carries substantial potential in practical settings, assisting medical professionals in untangling the complexity of ageing mechanisms, and potentially becoming a valuable tool in informed clinical decision-making processes. FUNDING National Science Foundation and National Institutes of Health.
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Affiliation(s)
- Wei Qiu
- Paul G Allen School of Computer Science and Engineering, University of Washington, Washington, DC, USA
| | - Hugh Chen
- Paul G Allen School of Computer Science and Engineering, University of Washington, Washington, DC, USA
| | - Matt Kaeberlein
- Department of Laboratory Medicine and Pathology, University of Washington, Washington, DC, USA
| | - Su-In Lee
- Paul G Allen School of Computer Science and Engineering, University of Washington, Washington, DC, USA.
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21
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Luo X, Ruan Z, Liu L. Causal relationship between depression and aging: a bidirectional two-sample Mendelian randomization study. Aging Clin Exp Res 2023; 35:3179-3187. [PMID: 37999829 DOI: 10.1007/s40520-023-02596-4] [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: 08/22/2023] [Accepted: 10/16/2023] [Indexed: 11/25/2023]
Abstract
BACKGROUND The causal relationship and the direction of the effect between depression and aging remain controversial. METHODS We used a bidirectional two-sample Mendelian randomization analysis to examine the relationship between depression and age proxy indicators. We obtained pooled statistics from genome-wide association studies (GWAS) on depression and the age proxy indicators. We employed five MR analysis methods to address potential biases and ensure robustness of our results, with the inverse variance weighted (IVW) method being the primary outcome. We also conducted outlier exclusion using Radial MR, MRPRESSO, and MR Steiger filters. Additionally, sensitivity analyses were performed to assess heterogeneity and pleiotropy. RESULTS Our MR analysis revealed that depression causally leads to shortened telomere length (β = - 0.014; P = 0.038), increased frailty index (β = 0.076; P = 0.000), and accelerated GrimAge (β = 0.249; P = 0.024). Furthermore, our findings showed that the frailty index (OR = 1.679; P = 0.001) was causally associated with an increased risk of depression. Additionally, we found that appendicular lean mass (OR = 0.929; P = 0.000) and left-hand grip strength (OR = 0.836; P = 0.014) were causally associated with a reduced risk of depression. Sensitivity analyses demonstrated the robustness of our findings. CONCLUSIONS Our study provides evidence that depression contributes to the accelerated aging process, resulting in decreased telomere length, increased frailty index, and accelerated GrimAge. Additionally, we found that the frailty index increases the risk of depression, while appendicular lean mass and left-handed grip strength reduce the risk of depression.
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Affiliation(s)
- Xinxin Luo
- Jiangxi Provincial People's Hospital and The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
| | - Zhichao Ruan
- Beijing University of Chinese Medicine, Beijing, China
| | - Ling Liu
- Jiangxi Provincial People's Hospital and The First Affiliated Hospital of Nanchang Medical College, Nanchang, China.
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22
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Liang X, Shi W, Zhang X, Pang R, Zhang K, Xu Q, Xu C, Wan X, Cui W, Li D, Jiang Z, Liu Z, Li H, Zhang H, Li Z. Causal association of epigenetic aging and osteoporosis: a bidirectional Mendelian randomization study. BMC Med Genomics 2023; 16:275. [PMID: 37919683 PMCID: PMC10623745 DOI: 10.1186/s12920-023-01708-3] [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: 04/27/2023] [Accepted: 10/18/2023] [Indexed: 11/04/2023] Open
Abstract
BACKGROUND The relationship between aging and osteoporosis is well established. However, the relationship between the body's physiological age, i.e. epigenetic age, and osteoporosis is not known. Our goal is to analyze the bidirectional causal relationship between epigenetic clocks and osteoporosis using a bidirectional Mendelian randomization study. METHODS We used SNPs closely associated with GrimAge, Hannum, PhenoAge, and HorvathAge in epigenetic age and SNPs closely associated with femoral neck bone mineral density, lumbar spine bone mineral density, and forearm bone mineral density as instrumental variables, respectively, using the inverse variance weighting method and several other MR methods to assess the bidirectional causal relationship between epigenetic age and osteoporosis. RESULT There was no evidence of a clear causal relationship of epigenetic age (GrimAge, Hannum, PhenoAge, and HorvathAge) on femoral neck bone mineral density, lumbar spine bone mineral density, and forearm bone mineral density. In reverse Mendelian randomization analysis showed a significant causal effect of lumbar spine bone mineral density on GrimAge: odds ratio (OR) = 0.692, 95% confidence interval (CI) = (0.538-0.890), p = 0.004. The results suggest that a decrease in lumbar spine bone mineral density promotes an acceleration of GrimAge. CONCLUSION There was no significant bidirectional causal relationship between epigenetic age and osteoporosis A decrease in lumbar spine bone density may lead to an acceleration of the epigenetic clock "GrimAge". Our study provides partial evidence for a bidirectional causal effect between epigenetic age and Osteoporosis.
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Affiliation(s)
- Xinyu Liang
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, People's Republic of China
| | - Wei Shi
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, People's Republic of China
| | - Xinglong Zhang
- Department of Orthopedics, Tianjin Hospital of ITCWM Nankai Hospital, Tianjin, People's Republic of China
| | - Ran Pang
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, People's Republic of China
- Department of Orthopedics, Tianjin Hospital of ITCWM Nankai Hospital, Tianjin, People's Republic of China
| | - Kai Zhang
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, People's Republic of China
| | - Qian Xu
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
| | - Chunlei Xu
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, People's Republic of China
| | - Xin Wan
- Department of Orthopedics, Tian-Jin Union Medical Centre, Nankai University People's Hospital, Tianjin, China
| | - Wenhao Cui
- Department of Pharmacology, Kyoto Prefectural University of Medicine, Kyoto, Japan
- R&D Center, Youjia (Hangzhou) Biomedical Technology Co., Ltd, Hangzhou, China
| | - Dong Li
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, People's Republic of China
| | - Zhaohui Jiang
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, People's Republic of China
- Department of Orthopaedic, Wenzhou Central Hospital, Wenzhou, China
| | - Zhengxuan Liu
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, People's Republic of China
| | - Hui Li
- Department of Orthopedics, Tianjin Hospital of ITCWM Nankai Hospital, Tianjin, People's Republic of China
| | - Huafeng Zhang
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, People's Republic of China.
| | - Zhijun Li
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, 300052, People's Republic of China.
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23
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Huang Y, Chen X, Ye J, Yi H, Zheng X. Causal effect of gut microbiota on DNA methylation phenotypic age acceleration: a two-sample Mendelian randomization study. Sci Rep 2023; 13:18830. [PMID: 37914897 PMCID: PMC10620208 DOI: 10.1038/s41598-023-46308-4] [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: 08/18/2023] [Accepted: 10/30/2023] [Indexed: 11/03/2023] Open
Abstract
The causal relationship between gut microbiota and DNA methylation phenotypic age acceleration remains unclear. This study aims to examine the causal effect of gut microbiota on the acceleration of DNA methylation phenotypic age using Mendelian randomization. A total of 212 gut microbiota were included in this study, and their 16S rRNA sequencing data were obtained from the Genome-wide Association Study (GWAS) database. The GWAS data corresponding to DNA methylation phenotypic age acceleration were selected as the outcome variable. Two-sample Mendelian randomization (TSMR) was conducted using R software. During the analysis process, careful consideration was given to address potential biases arising from linkage disequilibrium and weak instrumental variables. The results from inverse-variance weighting (IVW) analysis revealed significant associations (P < 0.05) between single nucleotide polymorphisms (SNPs) corresponding to 16 gut microbiota species and DNA methylation phenotypic age acceleration. Out of the total, 12 gut microbiota species exhibited consistent and robust causal effects. Among them, 7 displayed a significant positive correlation with the outcome while 5 species showed a significant negative correlation with the outcome. This study utilized Mendelian randomization to unravel the intricate causal effects of various gut microbiota species on DNA methylation phenotypic age acceleration.
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Affiliation(s)
- Yedong Huang
- College of Clinical Medicine for Obstetrics and Gynecology & Pediatrics, Fujian Medical University, Fuzhou, China
- National Key Gynecology Clinical Specialty Construction Institution of China, Fujian Provincial Key Gynecology Clinical Specialty, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Xiaoyun Chen
- Department of Respiratory Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Jingwen Ye
- Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huan Yi
- College of Clinical Medicine for Obstetrics and Gynecology & Pediatrics, Fujian Medical University, Fuzhou, China.
- National Key Gynecology Clinical Specialty Construction Institution of China, Fujian Provincial Key Gynecology Clinical Specialty, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, China.
| | - Xiangqin Zheng
- College of Clinical Medicine for Obstetrics and Gynecology & Pediatrics, Fujian Medical University, Fuzhou, China.
- National Key Gynecology Clinical Specialty Construction Institution of China, Fujian Provincial Key Gynecology Clinical Specialty, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, China.
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24
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Iannuzzi V, Sarno S, Sazzini M, Abondio P, Sala C, Bacalini MG, Gentilini D, Calzari L, Masciotta F, Garagnani P, Castellani G, Moretti E, Dasso MC, Sevini F, Franceschi ZA, Franceschi C, Pettener D, Luiselli D, Giuliani C. Epigenetic aging differences between Wichí and Criollos from Argentina: Insights from genomic history and ecology. Evol Med Public Health 2023; 11:397-414. [PMID: 37954982 PMCID: PMC10632719 DOI: 10.1093/emph/eoad034] [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: 09/19/2022] [Revised: 10/07/2023] [Indexed: 11/14/2023] Open
Abstract
Background and objectives Epigenetic estimators based on DNA methylation levels have emerged as promising biomarkers of human aging. These estimators exhibit natural variations across human groups, but data about indigenous populations remain underrepresented in research. This study aims to investigate differences in epigenetic estimators between two distinct human populations, both residing in the Gran Chaco region of Argentina, the Native-American Wichí, and admixed Criollos who are descendants of intermarriages between Native Americans and the first European colonizers, using a population genetic approach. Methodology We analyzed 24 Wichí (mean age: 39.2 ± 12.9 yo) and 24 Criollos (mean age: 41.1 ± 14.0 yo) for DNA methylation levels using the Infinium MethylationEPIC (Illumina) to calculate 16 epigenetic estimators. Additionally, we examined genome-wide genetic variation using the HumanOmniExpress BeadChip (Illumina) to gain insights into the genetic history of these populations. Results Our results indicate that Native-American Wichí are epigenetically older compared to Criollos according to five epigenetic estimators. Analyses within the Criollos population reveal that global ancestry does not influence the differences observed, while local (chromosomal) ancestry shows positive associations between specific SNPs located in genomic regions over-represented by Native-American ancestry and measures of epigenetic age acceleration (AgeAccelHannum). Furthermore, we demonstrate that differences in population ecologies also contribute to observed epigenetic differences. Conclusions and implications Overall, our study suggests that while the genomic history may partially account for the observed epigenetic differences, non-genetic factors, such as lifestyle and ecological factors, play a substantial role in the variability of epigenetic estimators, thereby contributing to variations in human epigenetic aging.
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Affiliation(s)
- Vincenzo Iannuzzi
- Department of Biological, Geological and Environmental Sciences, Laboratory of Molecular Anthropology & Centre for Genome Biology, University of Bologna, Bologna, Italy
| | - Stefania Sarno
- Department of Biological, Geological and Environmental Sciences, Laboratory of Molecular Anthropology & Centre for Genome Biology, University of Bologna, Bologna, Italy
| | - Marco Sazzini
- Department of Biological, Geological and Environmental Sciences, Laboratory of Molecular Anthropology & Centre for Genome Biology, University of Bologna, Bologna, Italy
- Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), Interdepartmental Centre, University of Bologna, Bologna, Italy
| | - Paolo Abondio
- Department of Cultural Heritage (DBC), University of Bologna, Ravenna Campus, Ravenna, Italy
| | - Claudia Sala
- Department of Medical and Surgical Science (DIMEC), University of Bologna, Bologna, Italy
| | | | - Davide Gentilini
- Department of Brain and Behavioral Sciences, Università di Pavia, Pavia, Italy
- Bioinformatics and Statistical Genomics Unit, Istituto Auxologico Italiano IRCCS, Cusano Milanino, Milan, Italy
| | - Luciano Calzari
- Bioinformatics and Statistical Genomics Unit, Istituto Auxologico Italiano IRCCS, Cusano Milanino, Milan, Italy
| | - Federica Masciotta
- Department of Statistical Sciences ‘Paolo Fortunati’, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Paolo Garagnani
- Department of Medical and Surgical Science (DIMEC), University of Bologna, Bologna, Italy
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Gastone Castellani
- Department of Medical and Surgical Science (DIMEC), University of Bologna, Bologna, Italy
| | - Edgardo Moretti
- Facultad de Ciencias Médicas, Universidad Nacional de Córdoba, Instituto de Biología y Medicina Experimental de Cuyo, CCT CONICET, Argentina
| | - Maria Cristina Dasso
- Centro de Investigaciones en Antropología Filosófica y Cultural (CIAFIC), Buenos Aires, Argentina
| | - Federica Sevini
- Department of Medical and Surgical Science (DIMEC), University of Bologna, Bologna, Italy
| | | | - Claudio Franceschi
- Laboratory of Systems Medicine of Healthy Aging and Department of Applied Mathematics, Lobachevsky University, Nizhny Novgorod, Russia
| | - Davide Pettener
- Department of Biological, Geological and Environmental Sciences, Laboratory of Molecular Anthropology & Centre for Genome Biology, University of Bologna, Bologna, Italy
| | - Donata Luiselli
- Department of Cultural Heritage (DBC), University of Bologna, Ravenna Campus, Ravenna, Italy
| | - Cristina Giuliani
- Department of Biological, Geological and Environmental Sciences, Laboratory of Molecular Anthropology & Centre for Genome Biology, University of Bologna, Bologna, Italy
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Dugué PA, Yu C, Hodge AM, Wong EM, Joo JE, Jung CH, Schmidt D, Makalic E, Buchanan DD, Severi G, English DR, Hopper JL, Milne RL, Giles GG, Southey MC. Reply to: Comments on "Methylation scores for smoking, alcohol consumption and body mass index and risk of seven types of cancer". Int J Cancer 2023; 153:1545-1546. [PMID: 37387529 DOI: 10.1002/ijc.34644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 05/23/2023] [Indexed: 07/01/2023]
Affiliation(s)
- 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
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Chenglong Yu
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Allison M Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
| | - JiHoon E Joo
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
| | - Chol-Hee Jung
- Melbourne Bioinformatics, University of Melbourne, Parkville, Victoria, Australia
| | - Daniel Schmidt
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
- Department of Data Science and AI, Faculty of IT, Monash University, Clayton, Victoria, Australia
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Daniel D Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
- Melbourne Bioinformatics, University of Melbourne, Parkville, Victoria, Australia
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Gianluca Severi
- Centre de Recherche en Epidémiologie et Santé des Populations (CESP, Inserm U1018), Facultés de Médecine Universités Paris-Saclay, UVSQ, Gustave Roussy, Villejuif, France
| | - Dallas R English
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, 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
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, 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
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
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Wang Z, Liu Y, Zhang S, Yuan Y, Chen S, Li W, Zuo M, Xiang Y, Li T, Yang W, Yang Y, Liu Y. Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study. Clin Epigenetics 2023; 15:159. [PMID: 37805541 PMCID: PMC10559596 DOI: 10.1186/s13148-023-01575-w] [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: 05/18/2023] [Accepted: 09/29/2023] [Indexed: 10/09/2023] Open
Abstract
BACKGROUND Epigenetic clocks constructed from DNA methylation patterns have emerged as excellent predictors of aging and aging-related health outcomes. Iron, a crucial element, is meticulously regulated within organisms, a phenomenon referred as iron homeostasis. Previous researches have demonstrated the sophisticated connection between aging and iron homeostasis. However, their causal relationship remains relatively unexplored. RESULTS Through two-sample Mendelian randomization (MR) utilizing the random effect inverse variance weighted (IVW) method, each standard deviation (SD) increase in serum iron was associated with increased GrimAge acceleration (GrimAA, BetaIVW = 0.27, P = 8.54E-03 in 2014 datasets; BetaIVW = 0.31, P = 1.25E-02 in 2021 datasets), HannumAge acceleration (HannumAA, BetaIVW = 0.32, P = 4.50E-03 in 2014 datasets; BetaIVW = 0.32, P = 8.03E-03 in 2021 datasets) and Intrinsic epigenetic age acceleration (IEAA, BetaIVW = 0.34, P = 5.33E-04 in 2014 datasets; BetaIVW = 0.49, P = 9.94E-04 in 2021 datasets). Similar results were also observed in transferrin saturation. While transferrin manifested a negative association with epigenetic age accelerations (EAAs) sensitivity analyses. Besides, lack of solid evidence to support a causal relationship from EAAs to iron-related biomarkers. CONCLUSIONS The results of present investigation unveiled the causality of iron overload on acceleration of epigenetic clocks. Researches are warranted to illuminate the underlying mechanisms and formulate strategies for potential interventions.
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Affiliation(s)
- Zhihao Wang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Liu
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China
| | - Shuxin Zhang
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Yunbo Yuan
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Siliang Chen
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Wenhao Li
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Mingrong Zuo
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Yufan Xiang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Tengfei Li
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Wanchun Yang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Yuan Yang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Yanhui Liu
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China.
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Zhang F, Deng S, Zhang J, Xu W, Xian D, Wang Y, Zhao Q, Liu Y, Zhu X, Peng M, Zhang L. Causality between heart failure and epigenetic age: a bidirectional Mendelian randomization study. ESC Heart Fail 2023; 10:2903-2913. [PMID: 37452462 PMCID: PMC10567637 DOI: 10.1002/ehf2.14446] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 05/01/2023] [Accepted: 06/08/2023] [Indexed: 07/18/2023] Open
Abstract
AIMS Heart failure (HF) is a prevalent age-related cardiovascular disease with poor prognosis in the elderly population. This study aimed to establish the causal relationship between ageing and HF by conducting a bidirectional Mendelian randomization (MR) analysis on epigenetic age (a marker of ageing) and HF. METHODS AND RESULTS Genome-wide association study data for epigenetic age (GrimAge, HorvathAge, HannumAge, and PhenoAge) and HF were collected and assessed for significant genetic variables. A bidirectional MR analysis was carried out using the random-effects inverse-variance weighted (IVW) method as the primary approach, while other methods (MR-Egger, weighted median, simple mode, and weighted mode) and multiple sensitivity analyses (heterogeneity analysis, leave-one-out sensitivity analysis, and horizontal pleiotropy analysis) were employed to evaluate the impact of epigenetic age on HF and vice versa. Bidirectional MR analysis of two samples revealed that the epigenetic PhenoAge clock increased the risk of HF [IVW odds ratio (OR) 1.015, 95% confidence interval (CI) 1.002-1.028, P = 0.028 and weighted median OR 1.020, 95% CI 1.001-1.038, P = 0.039]. Other results were not statistically significant. CONCLUSIONS The bidirectional MR analysis demonstrated a causal link between genetically predicted epigenetic age and HF in individuals of European descent. Further research into epigenetic age in other populations and additional genetic information related to HF is warranted.
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Affiliation(s)
- Fengjun Zhang
- College of Acupuncture and MassageShandong University of Traditional Chinese MedicineJinanChina
| | - Shanshan Deng
- Non‐Coding RNA and Drug Discovery Key Laboratory of Sichuan ProvinceChengdu Medical CollegeChengduChina
- School of Basic Medical SciencesChengdu Medical CollegeChengduChina
| | - Jing Zhang
- Department of PediatricsShandong Second Provincial General HospitalJinanChina
| | - Wenchang Xu
- College of Acupuncture and MassageShandong University of Traditional Chinese MedicineJinanChina
| | - Dexian Xian
- College of Acupuncture and MassageShandong University of Traditional Chinese MedicineJinanChina
| | - Yuxuan Wang
- College of Traditional Chinese MedicineShandong University of Traditional Chinese MedicineJinanChina
| | - Qiong Zhao
- Department of Traditional Chinese MedicineShandong Provincial Hospital Affiliated to Shandong First Medical UniversityJinanChina
| | - Yuan Liu
- Department of Traditional Chinese MedicineShandong Provincial Hospital Affiliated to Shandong First Medical UniversityJinanChina
| | - Xiuli Zhu
- Department of Radiation Oncology and Shandong Province Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinanChina
| | - Min Peng
- Department of Traditional Chinese MedicineShandong Provincial Hospital Affiliated to Shandong First Medical UniversityJinanChina
| | - Lin Zhang
- Department of Clinical Pharmacy, Shaoxing People's Hospital, Shaoxing HospitalZhejiang University School of MedicineShaoxingChina
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Zhang B, Yuan Q, Luan Y, Xia J. Effect of women's fertility and sexual development on epigenetic clock: Mendelian randomization study. Clin Epigenetics 2023; 15:154. [PMID: 37770973 PMCID: PMC10540426 DOI: 10.1186/s13148-023-01572-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: 05/12/2023] [Accepted: 09/25/2023] [Indexed: 09/30/2023] Open
Abstract
BACKGROUND AND OBJECTIVES In observational studies, women's fertility and sexual development traits may have implications for DNA methylation patterns, and pregnancy-related risk factors can also affect maternal DNA methylation patterns. The aim of our study is to disentangle any potential causal associations between women's fertility and sexual development traits and epigenetic clocks, as well as to search for probable mediators by using the Mendelian randomization (MR) method. METHODS Instrumental variables for exposures, mediators, and outcomes were adopted from genome-wide association studies data of European ancestry individuals. The potential causal relationship between women's fertility and sexual development traits and four epigenetic clocks were evaluated by inverse variance weighted method and verified by other two methods. Furthermore, we employed multivariable MR (MVMR) adjusting for hypertension, hyperglycemia, BMI changes, and insomnia. Then, combining the MVMR results and previous research, we performed two-step MR to explore the mediating effects of BMI, AFS, and AFB. Multiple sensitivity analyses were further performed to verify the robustness of our findings. RESULTS Leveraging two-sample MR analysis, we observed statistically significant associations between earlier age at first birth (AFB) with a higher HannumAge, PhenoAge and GrimAge acceleration(β = - 0.429, 95% CI [- 0.781 to - 0.077], p = 0.017 for HannumAge; β = - 0.571, 95% CI [- 1.006 to - 0.136], p = 0.010 for PhenoAge, and β = - 1.136, 95% CI [- 1.508 to - 0.765], p = 2.03E-09 for GrimAge respectively) and age at first sexual intercourse (AFS) with a higher HannumAge and GrimAge acceleration(β = - 0.175, 95% CI [- 0.336 to - 0.014], p = 0.033 for HannumAge; β = - 0.210, 95% CI [- 0.350 to - 0.070], p = 0.003 for GrimAge, respectively). Further analyses indicated that BMI, AFB and AFS played mediator roles in the path from women's fertility and sexual development traits to epigenetic aging. CONCLUSIONS Our study suggested that AFS and AFB are associated with epigenetic aging. These findings may prove valuable in informing the development of prevention strategies and interventions targeted towards women's fertility and sexual development experiences and their relationship with epigenetic aging-related diseases.
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Affiliation(s)
- Boxin Zhang
- Department of Neurology, Xiangya Hospital, Central South University, 87 Xiangya Road of Kaifu District, Changsha, 410008, China
- Hunan Clinical Research Center for Cerebrovascular Disease, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Qizhi Yuan
- Department of Neurology, Xiangya Hospital, Central South University, 87 Xiangya Road of Kaifu District, Changsha, 410008, China
- Hunan Clinical Research Center for Cerebrovascular Disease, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yining Luan
- Department of Neurology, Xiangya Hospital, Central South University, 87 Xiangya Road of Kaifu District, Changsha, 410008, China
- Hunan Clinical Research Center for Cerebrovascular Disease, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jian Xia
- Department of Neurology, Xiangya Hospital, Central South University, 87 Xiangya Road of Kaifu District, Changsha, 410008, China.
- Hunan Clinical Research Center for Cerebrovascular Disease, Changsha, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China.
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Fang X, Liu D, Zhao J, Li X, He T, Liu B. Using proteomics and metabolomics to identify therapeutic targets for senescence mediated cancer: genetic complementarity method. Front Endocrinol (Lausanne) 2023; 14:1255889. [PMID: 37745724 PMCID: PMC10514473 DOI: 10.3389/fendo.2023.1255889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 08/18/2023] [Indexed: 09/26/2023] Open
Abstract
Background Senescence have emerged as potential factors of lung cancer risk based on findings from many studies. However, the underlying pathogenesis of lung cancer caused by senescence is not clear. In this study, we try to explain the potential pathogenesis between senescence and lung cancer through proteomics and metabonomics. And try to find new potential therapeutic targets in lung cancer patients through network mendelian randomization (MR). Methods The genome-wide association data of this study was mainly obtained from a meta-analysis and the Transdisciplinary Research in Cancer of the Lung Consortium (TRICL), respectively.And in this study, we mainly used genetic complementarity methods to explore the susceptibility of aging to lung cancer. Additionally, a mediation analysis was performed to explore the potential mediating role of proteomics and metabonomics, using a network MR design. Results GNOVA analysis revealed a shared genetic structure between HannumAge and lung cancer with a significant genetic correlation estimated at 0.141 and 0.135, respectively. MR analysis showed a relationship between HannumAge and lung cancer, regardless of smoking status. Furthermore, genetically predicted HannumAge was consistently associated with the proteins C-type lectin domain family 4 member D (CLEC4D) and Retinoic acid receptor responder protein 1 (RARR-1), indicating their potential role as mediators in the causal pathway. Conclusion HannumAge acceleration may increase the risk of lung cancer, some of which may be mediated by CLEC4D and RARR-1, suggestion that CLEC4D and RARR-1 may serve as potential drug targets for the treatment of lung cancer.
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Affiliation(s)
- Xiaolu Fang
- Department of Clinical Laboratory, Xiangyang No.1 People’s Hospital, Hubei University of Medicine, Xiangyang, China
| | - Deyang Liu
- Department of Rehabilitation Medicine, Xiangyang No.1 People’s Hospital, Hubei University of Medicine, Xiangyang, China
| | - Jianzhong Zhao
- Department of Clinical Laboratory, Xiangyang No.1 People’s Hospital, Hubei University of Medicine, Xiangyang, China
| | - Xiaojia Li
- Department of Respiratory, Jiulongpo District People’s Hospital of Chongqing, Chongqing, China
| | - Ting He
- Department of Respiratory, Jiulongpo District People’s Hospital of Chongqing, Chongqing, China
| | - Baishan Liu
- Department of Respiratory, Jiulongpo District People’s Hospital of Chongqing, Chongqing, China
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Rosoff DB, Mavromatis LA, Bell AS, Wagner J, Jung J, Marioni RE, Davey Smith G, Horvath S, Lohoff FW. Multivariate genome-wide analysis of aging-related traits identifies novel loci and new drug targets for healthy aging. NATURE AGING 2023; 3:1020-1035. [PMID: 37550455 PMCID: PMC10432278 DOI: 10.1038/s43587-023-00455-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 06/07/2023] [Indexed: 08/09/2023]
Abstract
The concept of aging is complex, including many related phenotypes such as healthspan, lifespan, extreme longevity, frailty and epigenetic aging, suggesting shared biological underpinnings; however, aging-related endpoints have been primarily assessed individually. Using data from these traits and multivariate genome-wide association study methods, we modeled their underlying genetic factor ('mvAge'). mvAge (effective n = ~1.9 million participants of European ancestry) identified 52 independent variants in 38 genomic loci. Twenty variants were novel (not reported in input genome-wide association studies). Transcriptomic imputation identified age-relevant genes, including VEGFA and PHB1. Drug-target Mendelian randomization with metformin target genes showed a beneficial impact on mvAge (P value = 8.41 × 10-5). Similarly, genetically proxied thiazolidinediones (P value = 3.50 × 10-10), proprotein convertase subtilisin/kexin 9 inhibition (P value = 1.62 × 10-6), angiopoietin-like protein 4, beta blockers and calcium channel blockers also had beneficial Mendelian randomization estimates. Extending the drug-target Mendelian randomization framework to 3,947 protein-coding genes prioritized 122 targets. Together, these findings will inform future studies aimed at improving healthy aging.
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Affiliation(s)
- Daniel B Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
- NIH-Oxford-Cambridge Scholars Program; Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Lucas A Mavromatis
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Andrew S Bell
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Josephin Wagner
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Jeesun Jung
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Steve Horvath
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- San Diego Institute of Science, Alto Labs, San Diego, CA, USA
| | - Falk W Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
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Li H, He X, Kurowski L, Zhang R, Zhao D, Zeng J. Improving comparative analyses of Hi-C data via contrastive self-supervised learning. Brief Bioinform 2023; 24:bbad193. [PMID: 37287135 DOI: 10.1093/bib/bbad193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 04/12/2023] [Accepted: 04/27/2023] [Indexed: 06/09/2023] Open
Abstract
Hi-C is a widely applied chromosome conformation capture (3C)-based technique, which has produced a large number of genomic contact maps with high sequencing depths for a wide range of cell types, enabling comprehensive analyses of the relationships between biological functionalities (e.g. gene regulation and expression) and the three-dimensional genome structure. Comparative analyses play significant roles in Hi-C data studies, which are designed to make comparisons between Hi-C contact maps, thus evaluating the consistency of replicate Hi-C experiments (i.e. reproducibility measurement) and detecting statistically differential interacting regions with biological significance (i.e. differential chromatin interaction detection). However, due to the complex and hierarchical nature of Hi-C contact maps, it remains challenging to conduct systematic and reliable comparative analyses of Hi-C data. Here, we proposed sslHiC, a contrastive self-supervised representation learning framework, for precisely modeling the multi-level features of chromosome conformation and automatically producing informative feature embeddings for genomic loci and their interactions to facilitate comparative analyses of Hi-C contact maps. Comprehensive computational experiments on both simulated and real datasets demonstrated that our method consistently outperformed the state-of-the-art baseline methods in providing reliable measurements of reproducibility and detecting differential interactions with biological meanings.
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Affiliation(s)
- Han Li
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Xuan He
- Machine Learning Department, Silexon AI Technology Co., Ltd., 210000 Nanjing, China
| | - Lawrence Kurowski
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Ruotian Zhang
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Dan Zhao
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Jianyang Zeng
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
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Kong L, Ye C, Wang Y, Hou T, Zheng J, Zhao Z, Li M, Xu Y, Lu J, Chen Y, Xu M, Wang W, Ning G, Bi Y, Wang T. Genetic Evidence for Causal Effects of Socioeconomic, Lifestyle, and Cardiometabolic Factors on Epigenetic-Age Acceleration. J Gerontol A Biol Sci Med Sci 2023; 78:1083-1091. [PMID: 36869809 DOI: 10.1093/gerona/glad078] [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: 09/25/2022] [Indexed: 03/05/2023] Open
Abstract
GrimAge acceleration (GrimAgeAccel) and PhenoAge acceleration (PhenoAgeAccel) are DNA methylation-based markers of accelerated biological aging, standing out in predicting mortality and age-related cardiometabolic morbidities. Causal risk factors for GrimAgeAccel and PhenoAgeAccel are unclear. In this study, we performed 2-sample univariable and multivariable Mendelian randomization (MR) to investigate causal associations of 19 modifiable socioeconomic, lifestyle, and cardiometabolic factors with GrimAgeAccel and PhenoAgeAccel. Instrument variants representing 19 modifiable factors were extracted from genome-wide association studies (GWASs) with up to 1 million Europeans. Summary statistics for GrimAgeAccel and PhenoAgeAccel were derived from a GWAS of 34 710 Europeans. We identified 12 and 8 factors causally associated with GrimAgeAccel and PhenoAgeAccel, respectively. Smoking was the strongest risk factor (β [standard error {SE}]: 1.299 [0.107] year) for GrimAgeAccel, followed by higher alcohol intake, higher waist circumference, daytime napping, higher body fat percentage, higher body mass index, higher C-reactive protein, higher triglycerides, childhood obesity, and type 2 diabetes; whereas education was the strongest protective factor (β [SE]: -1.143 [0.121] year), followed by household income. Furthermore, higher waist circumference (β [SE]: 0.850 [0.269] year) and education (β [SE]: -0.718 [0.151] year) were the leading causal risk and protective factors for PhenoAgeAccel, respectively. Sensitivity analyses strengthened the robustness of these causal associations. Multivariable MR analyses further demonstrated independent effects of the strongest risk and protective factors on GrimAgeAccel and PhenoAgeAccel, respectively. In conclusion, our findings provide novel quantitative evidence on modifiable causal risk factors for accelerated epigenetic aging, suggesting promising intervention targets against age-related morbidity and improving healthy longevity.
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Affiliation(s)
- Lijie Kong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chaojie Ye
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiying Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianzhichao Hou
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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33
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Lake J, Warly Solsberg C, Kim JJ, Acosta-Uribe J, Makarious MB, Li Z, Levine K, Heutink P, Alvarado CX, Vitale D, Kang S, Gim J, Lee KH, Pina-Escudero SD, Ferrucci L, Singleton AB, Blauwendraat C, Nalls MA, Yokoyama JS, Leonard HL. Multi-ancestry meta-analysis and fine-mapping in Alzheimer's disease. Mol Psychiatry 2023; 28:3121-3132. [PMID: 37198259 PMCID: PMC10615750 DOI: 10.1038/s41380-023-02089-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 03/27/2023] [Accepted: 03/31/2023] [Indexed: 05/19/2023]
Abstract
Genome-wide association studies (GWAS) of Alzheimer's disease are predominantly carried out in European ancestry individuals despite the known variation in genetic architecture and disease prevalence across global populations. We leveraged published GWAS summary statistics from European, East Asian, and African American populations, and an additional GWAS from a Caribbean Hispanic population using previously reported genotype data to perform the largest multi-ancestry GWAS meta-analysis of Alzheimer's disease and related dementias to date. This method allowed us to identify two independent novel disease-associated loci on chromosome 3. We also leveraged diverse haplotype structures to fine-map nine loci with a posterior probability >0.8 and globally assessed the heterogeneity of known risk factors across populations. Additionally, we compared the generalizability of multi-ancestry- and single-ancestry-derived polygenic risk scores in a three-way admixed Colombian population. Our findings highlight the importance of multi-ancestry representation in uncovering and understanding putative factors that contribute to risk of Alzheimer's disease and related dementias.
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Affiliation(s)
- Julie Lake
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Caroline Warly Solsberg
- Pharmaceutical Sciences and Pharmacogenomics, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Jonggeol Jeffrey Kim
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Preventive Neurology Unit, Centre for Prevention Diagnosis and Detection, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Juliana Acosta-Uribe
- Neuroscience Research Institute and the department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA
- Neuroscience Group of Antioquia, University of Antioquia, Medellín, Colombia
| | - Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
| | - Zizheng Li
- Pharmaceutical Sciences and Pharmacogenomics, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Kristin Levine
- Data Tecnica International LLC, Washington, DC, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Peter Heutink
- Alector, Inc. 131 Oyster Point Blvd, Suite 600, South San Francisco, CA, 94080, USA
| | - Chelsea X Alvarado
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Washington, DC, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Dan Vitale
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Washington, DC, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Sarang Kang
- Gwangju Alzheimer's disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, 61452, Korea
- BK FOUR Department of Integrative Biological Sciences, Chosun University, Gwangju, 61452, Korea
| | - Jungsoo Gim
- Gwangju Alzheimer's disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, 61452, Korea
- BK FOUR Department of Integrative Biological Sciences, Chosun University, Gwangju, 61452, Korea
- Department of Biomedical Science, Chosun University, Gwangju, 61452, Korea
| | - Kun Ho Lee
- Gwangju Alzheimer's disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, 61452, Korea
- BK FOUR Department of Integrative Biological Sciences, Chosun University, Gwangju, 61452, Korea
- Department of Biomedical Science, Chosun University, Gwangju, 61452, Korea
- Korea Brain Research Institute, Daegu, 41062, Korea
| | - Stefanie D Pina-Escudero
- Pharmaceutical Sciences and Pharmacogenomics, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Cornelis Blauwendraat
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
- Integrative Neurogenomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Washington, DC, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer S Yokoyama
- Pharmaceutical Sciences and Pharmacogenomics, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Hampton L Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.
- Data Tecnica International LLC, Washington, DC, USA.
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA.
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.
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Bafei SEC, Shen C. Biomarkers selection and mathematical modeling in biological age estimation. NPJ AGING 2023; 9:13. [PMID: 37393295 DOI: 10.1038/s41514-023-00110-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 05/08/2023] [Indexed: 07/03/2023]
Abstract
Biological age (BA) is important for clinical monitoring and preventing aging-related disorders and disabilities. Clinical and/or cellular biomarkers are measured and integrated in years using mathematical models to display an individual's BA. To date, there is not yet a single or set of biomarker(s) and technique(s) that is validated as providing the BA that reflects the best real aging status of individuals. Herein, a comprehensive overview of aging biomarkers is provided and the potential of genetic variations as proxy indicators of the aging state is highlighted. A comprehensive overview of BA estimation methods is also provided as well as a discussion of their performances, advantages, limitations, and potential approaches to overcome these limitations.
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Affiliation(s)
- Solim Essomandan Clémence Bafei
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Chong Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China.
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35
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Huang Z, Vlasschaert C, Robinson-Cohen C, Pan Y, Sun X, Lash JP, Kestenbaum B, Kelly TN. Emerging evidence on the role of clonal hematopoiesis of indeterminate potential in chronic kidney disease. Transl Res 2023; 256:87-94. [PMID: 36586535 PMCID: PMC10101890 DOI: 10.1016/j.trsl.2022.12.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/21/2022] [Accepted: 12/22/2022] [Indexed: 12/29/2022]
Abstract
Chronic kidney disease (CKD) was responsible for 1.2 million deaths globally in 2016. Despite the large and growing burden of CKD, treatment options are limited and generally only preserve kidney function. Characterizing molecular precursors to incident and progressive CKD could point to critically needed prevention and treatment strategies. Clonal hematopoiesis of indeterminate potential (CHIP) is typically characterized by the clonal expansion of blood cells carrying somatic mutations in specific driver genes. An age-related disorder, CHIP is rare in the young but common in older adults. Recent studies have identified causal associations between CHIP and atherosclerotic cardiovascular disease which are most likely mediated by inflammation, a hallmark of CKD. Animal evidence has supported causal effects of CHIP on kidney injury, inflammation, and fibrosis, providing impetus for human research. Although prospective epidemiologic studies investigating associations of CHIP with development and progression of CKD are few, intriguing findings have been reported. CHIP was significantly associated with kidney function decline and end stage kidney disease in the general population, although effect sizes were modest. Recent work suggests larger associations of CHIP with kidney disease progression in CKD patients, but further investigations in this area are needed. In addition, the accumulating literature has identified some heterogeneity in associations between CHIP and kidney endpoints across study populations, but reasons for these differences remain unclear. The current review provides an in-depth exploration into this nascent area of research, develops a conceptual framework linking CHIP to CKD, and discusses the clinical and public health implications of this work.
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Affiliation(s)
- Zhijie Huang
- Department of Epidemiology, Tulane University, New Orleans, Louisiana
| | | | - Cassianne Robinson-Cohen
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Yang Pan
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Xiao Sun
- Department of Epidemiology, Tulane University, New Orleans, Louisiana; Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - James P Lash
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Bryan Kestenbaum
- Division of Nephrology, Department of Medicine, Kidney Research Institute, University of Washington, Seattle, Washington
| | - Tanika N Kelly
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois.
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Gao C, Amador C, Walker RM, Campbell A, Madden RA, Adams MJ, Bai X, Liu Y, Li M, Hayward C, Porteous DJ, Shen X, Evans KL, Haley CS, McIntosh AM, Navarro P, Zeng Y. Phenome-wide analyses identify an association between the parent-of-origin effects dependent methylome and the rate of aging in humans. Genome Biol 2023; 24:117. [PMID: 37189164 PMCID: PMC10184337 DOI: 10.1186/s13059-023-02953-6] [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: 10/05/2022] [Accepted: 04/26/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND The variation in the rate at which humans age may be rooted in early events acting through the genomic regions that are influenced by such events and subsequently are related to health phenotypes in later life. The parent-of-origin-effect (POE)-regulated methylome includes regions enriched for genetically controlled imprinting effects (the typical type of POE) and regions influenced by environmental effects associated with parents (the atypical POE). This part of the methylome is heavily influenced by early events, making it a potential route connecting early exposures, the epigenome, and aging. We aim to test the association of POE-CpGs with early and later exposures and subsequently with health-related phenotypes and adult aging. RESULTS We perform a phenome-wide association analysis for the POE-influenced methylome using GS:SFHS (Ndiscovery = 5087, Nreplication = 4450). We identify and replicate 92 POE-CpG-phenotype associations. Most of the associations are contributed by the POE-CpGs belonging to the atypical class where the most strongly enriched associations are with aging (DNAmTL acceleration), intelligence, and parental (maternal) smoking exposure phenotypes. A proportion of the atypical POE-CpGs form co-methylation networks (modules) which are associated with these phenotypes, with one of the aging-associated modules displaying increased within-module methylation connectivity with age. The atypical POE-CpGs also display high levels of methylation heterogeneity, fast information loss with age, and a strong correlation with CpGs contained within epigenetic clocks. CONCLUSIONS These results identify the association between the atypical POE-influenced methylome and aging and provide new evidence for the "early development of origin" hypothesis for aging in humans.
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Affiliation(s)
- Chenhao Gao
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Rosie M Walker
- Centre for Clinical Brain Sciences, Chancellor's Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- School of Psychology, University of Exeter, Perry Road, Exeter, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | | | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Xiaomeng Bai
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Ying Liu
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Miaoxin Li
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Chris S Haley
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | | | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
- Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK.
| | - Yanni Zeng
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China.
- Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China.
- Guangdong Province Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China.
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37
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Guo Y, Li D, Hu Y. Appraising the associations between systemic iron status and epigenetic clocks: A genetic correlation and bidirectional Mendelian Randomization study. Am J Clin Nutr 2023:S0002-9165(23)48897-1. [PMID: 37146762 DOI: 10.1016/j.ajcnut.2023.05.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 04/25/2023] [Accepted: 05/01/2023] [Indexed: 05/07/2023] Open
Abstract
BACKGROUND Genetic correlations and bidirectional causal effects between systemic iron status and epigenetic clocks have not been fully investigated, although observational studies have suggested systemic iron status is associated with human aging. OBJECTIVES We explored the genetic correlations and bidirectional causal effects between systemic iron status and epigenetic clocks. METHODS Leveraging large-scale genome-wide association study summary-level statistics for four systemic iron status biomarkers (ferritin, serum iron, transferrin, transferrin saturation) (N = 48,972) and four measures for epigenetic age (GrimAge, PhenoAge, IEAA, HannumAge) (N = 34,710), genetic correlations and bidirectional causal effects were estimated between them mainly by applying linkage disequilibrium score (LDSC) regression, Mendelian randomization (MR), and MR based on Bayesian model averaging (MR-BMA). The main analyses were conducted employing multiplicative random effects inverse variance weighted MR. MR-Egger, weighted median, weighted mode, and MR-PRESSO were performed as sensitivity analyses to support the robustness of causal effects. RESULTS The LDSC results illustrated genetic correlations (Rg) between serum iron and PhenoAge (Rg = 0.1971, p = 0.048) and between transferrin saturation and PhenoAge (Rg = 0.196, p = 0.0469). We found that increased ferritin and transferrin saturation significantly increased all four measures of epigenetic age acceleration (all p < 0.0125, beta > 0). Each standard deviation genetically increases in serum iron only significantly associated with increased IEAA acceleration (beta = 0.36, 95% CI 0.16-0.57, p = 6.01E-04) and increased HannumAge acceleration (beta = 0.32, 95% CI 0.11-0.52, p = 2.69E-03). Evidence showed a suggestively significant causal effect of transferrin on epigenetic age acceleration (all 0.0125 < p <0.05). Additionally, reverse MR study indicated no significant causal effect of epigenetic clocks on systemic iron status. CONCLUSIONS All four iron status biomarkers had a significant or suggestively significant causal effect on epigenetic clocks, whereas reverse MR studies did not.
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Affiliation(s)
- Yu Guo
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150086, China
| | - Dahe Li
- Beidahuang Industry Group General Hospital, Harbin, China
| | - Yang Hu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150086, China.
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38
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Lin B, Mu Y, Ding Z. Assessing the Causal Association between Biological Aging Biomarkers and the Development of Cerebral Small Vessel Disease: A Mendelian Randomization Study. BIOLOGY 2023; 12:biology12050660. [PMID: 37237474 DOI: 10.3390/biology12050660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/09/2023] [Accepted: 04/19/2023] [Indexed: 05/28/2023]
Abstract
Biological aging biomarkers, such as leukocyte telomere length (LTL) and epigenetic clocks, have been associated with the risk of cerebral small vessel disease (CSVD) in several observational studies. However, it is unclear whether LTL or epigenetic clocks play causal roles as prognostic biomarkers in the development of CSVD. We performed a Mendelian randomization (MR) study of LTL and four epigenetic clocks on ten subclinical and clinical CSVD measures. We obtained genome-wide association (GWAS) data for LTL from the UK Biobank (N = 472,174). Data on epigenetic clocks were derived from a meta-analysis (N = 34,710), and CSVD data (N cases =1293-18,381; N controls = 25,806-105,974) were extracted from the Cerebrovascular Disease Knowledge Portal. We found that genetically determined LTL and epigenetic clocks were not individually associated with ten measures of CSVD (IVW p > 0.05), and this result was consistent across sensitivity analyses. Our findings imply that LTL and epigenetic clocks may not help in predicting CSVD development as causal prognostic biomarkers. Further studies are needed to illustrate the potential of reverse biological aging in serving as an effective form of preventive therapy for CSVD.
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Affiliation(s)
- Biying Lin
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, 261 Huansha Rd., Hangzhou 310006, China
| | - Yuzhu Mu
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, 261 Huansha Rd., Hangzhou 310006, China
- Department of Radiology, The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou 310006, China
| | - Zhongxiang Ding
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, 261 Huansha Rd., Hangzhou 310006, China
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Mavromatis LA, Rosoff DB, Bell AS, Jung J, Wagner J, Lohoff FW. Multi-omic underpinnings of epigenetic aging and human longevity. Nat Commun 2023; 14:2236. [PMID: 37076473 PMCID: PMC10115892 DOI: 10.1038/s41467-023-37729-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 03/28/2023] [Indexed: 04/21/2023] Open
Abstract
Biological aging is accompanied by increasing morbidity, mortality, and healthcare costs; however, its molecular mechanisms are poorly understood. Here, we use multi-omic methods to integrate genomic, transcriptomic, and metabolomic data and identify biological associations with four measures of epigenetic age acceleration and a human longevity phenotype comprising healthspan, lifespan, and exceptional longevity (multivariate longevity). Using transcriptomic imputation, fine-mapping, and conditional analysis, we identify 22 high confidence associations with epigenetic age acceleration and seven with multivariate longevity. FLOT1, KPNA4, and TMX2 are novel, high confidence genes associated with epigenetic age acceleration. In parallel, cis-instrument Mendelian randomization of the druggable genome associates TPMT and NHLRC1 with epigenetic aging, supporting transcriptomic imputation findings. Metabolomics Mendelian randomization identifies a negative effect of non-high-density lipoprotein cholesterol and associated lipoproteins on multivariate longevity, but not epigenetic age acceleration. Finally, cell-type enrichment analysis implicates immune cells and precursors in epigenetic age acceleration and, more modestly, multivariate longevity. Follow-up Mendelian randomization of immune cell traits suggests lymphocyte subpopulations and lymphocytic surface molecules affect multivariate longevity and epigenetic age acceleration. Our results highlight druggable targets and biological pathways involved in aging and facilitate multi-omic comparisons of epigenetic clocks and human longevity.
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Affiliation(s)
- Lucas A Mavromatis
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Daniel B Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
- NIH-Oxford-Cambridge Scholars Program, University of Oxford, Oxford, UK
| | - Andrew S Bell
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Jeesun Jung
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Josephin Wagner
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Falk W Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
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Pan Y, Sun X, Huang Z, Zhang R, Li C, Anderson AH, Lash JP, Kelly TN. Effects of epigenetic age acceleration on kidney function: a Mendelian randomization study. Clin Epigenetics 2023; 15:61. [PMID: 37031184 PMCID: PMC10082992 DOI: 10.1186/s13148-023-01476-y] [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: 06/24/2022] [Accepted: 03/29/2023] [Indexed: 04/10/2023] Open
Abstract
BACKGROUND Previous studies have reported cross-sectional associations between measures of epigenetic age acceleration (EAA) and kidney function phenotypes. However, the temporal and potentially causal relationships between these variables remain unclear. We conducted a bidirectional two-sample Mendelian randomization study of EAA and kidney function. Genetic instruments for EAA and estimate glomerular filtration rate (eGFR) were identified from previous genome-wide association study (GWAS) meta-analyses of European-ancestry participants. Causal effects of EAA on kidney function and kidney function on EAA were assessed through summary-based Mendelian randomization utilizing data from the CKDGen GWAS meta-analysis of log-transformed estimated glomerular filtration rate (log-eGFR; n = 5,67,460) and GWAS meta-analyses of EAA (n = 34,710). An allele score-based Mendelian randomization leveraging individual-level data from UK Biobank participants (n = 4,33,462) further examined the effects of EAA on kidney function. RESULTS Using summary-based Mendelian randomization, we found that each 5 year increase in intrinsic EAA (IEAA) and GrimAge acceleration (GrimAA) was associated with - 0.01 and - 0.02 unit decreases in log-eGFR, respectively (P = 0.02 and P = 0.09, respectively), findings which were strongly supported by allele-based Mendelian randomization study (both P < 0.001). Summary-based Mendelian randomization identified 24% increased odds of CKD with each 5-unit increase in IEAA (P = 0.05), with consistent findings observed in allele score-based analysis (P = 0.07). Reverse-direction Mendelian randomization identified potentially causal effects of decreased kidney function on HannumAge acceleration (HannumAA), GrimAA, and PhenoAge acceleration (PhenoAA), conferring 3.14, 1.99, and 2.88 year decreases in HanumAA, GrimAA, and PhenoAA, respectively (P = 0.003, 0.05, and 0.002, respectively) with each 1-unit increase in log-eGFR. CONCLUSION This study supports bidirectional causal relationships between EAA and kidney function, pointing to potential prevention and therapeutic strategies.
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Affiliation(s)
- Yang Pan
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, 820 S Wood Street, Chicago, IL, 60607, USA
| | - Xiao Sun
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, 820 S Wood Street, Chicago, IL, 60607, USA
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Zhijie Huang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Ruiyuan Zhang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Changwei Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Amanda H Anderson
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - James P Lash
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, 820 S Wood Street, Chicago, IL, 60607, USA
| | - Tanika N Kelly
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, 820 S Wood Street, Chicago, IL, 60607, USA.
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.
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Xiao W, Li J, Feng T, Jin L. Circulating adipokine concentrations and the risk of venous thromboembolism: A Mendelian randomization and mediation analysis. Front Genet 2023; 14:1113111. [PMID: 37056282 PMCID: PMC10086141 DOI: 10.3389/fgene.2023.1113111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/13/2023] [Indexed: 03/30/2023] Open
Abstract
Background: Previous observational studies have suggested that circulating adipokine concentrations are related to a greater risk of venous thromboembolism (VTE). However, it remained unclear whether these observations reflect causality.Objective: This study aimed to investigate the causal relationship between circulating adipokine concentrations (including adiponectin, leptin, PAI-1, MCP-1, leptin receptor, and RETN) and the risk of VTE and its subtypes (DVT and PE) and to determine whether circulating adipokine concentrations are a mediator of venous thromboembolic events in obese patients.Methods: We used Mendelian randomization (MR) analyses to determine the effects of the body mass index (BMI), adiponectin, leptin, PAI-1, MCP-1, leptin receptor, and RETN levels on VTE, DVT, and PE in a cohort of 11,288 VTE cases, 5,632 DVT cases, 5,130 PE cases, and 254,771 controls. We then assessed the proportion of the effect of obesity on VTE, DVT, and PE explained by circulating leptin levels.Result: Genetically predicted higher BMI was related to increased VTE (OR = 1.45, p < 0.001), DVT (OR = 1.63, p < 0.001), and PE (OR = 1.37, p < 0.001) risk, and higher circulating leptin levels increase odds of VTE (OR = 1.96, q < 0.001), DVT (OR = 2.52, q < 0.001), and PE (OR = 2.26, q = 0.005). In addition, we found that the causal effect between elevated serum adiponectin and the decreased risk of VTE (OR = 0.85, p = 0.013, q = 0.053) and PE (OR = 0.81, p = 0.032, q = 0.083) and between MCP-1 and the reduced risk of VTE (OR = 0.88, p = 0.048, q = 0.143) is no longer significant after FDR adjustment. In MR mediation analysis, the mediation effect of circulating leptin levels in the causal pathway from BMI to PE was estimated to be 1.28 (0.95–1.71, p = 0.10), accounting for 39.14% of the total effect.Conclusion: The circulating leptin level is a risk factor for VTE, DVT, and PE, but it might be a potential mediator of BMI on the risk of PE, and thus, interventions on the circulating leptin level in obesity might reduce the risk of PE. Adiponectin is a potential protective factor for both VTE and PE.
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Affiliation(s)
- Weizhong Xiao
- Department of Interventional Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Jian Li
- Department of Interventional Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Tianyuyi Feng
- The Department of Radiology of the Fifth People’s Hospital of Shanghai, Fudan University, Shanghai, China
| | - Long Jin
- Department of Interventional Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
- *Correspondence: Long Jin,
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Ziyatdinov A, Hobbs BD, Kanaan-Izquierdo S, Moll M, Sakornsakolpat P, Shrine N, Chen J, Song K, Bowler RP, Castaldi PJ, Tobin MD, Kraft P, Silverman EK, Julienne H, Aschard H, Cho MH. Identifying COPD subtypes using multi-trait genetics. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.20.23286186. [PMID: 36865145 PMCID: PMC9980243 DOI: 10.1101/2023.02.20.23286186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Chronic Obstructive Pulmonary Disease (COPD) has a simple physiological diagnostic criterion but a wide range of clinical characteristics. The mechanisms underlying this variability in COPD phenotypes are unclear. To investigate the potential contribution of genetic variants to phenotypic heterogeneity, we examined the association of genome-wide associated lung function, COPD, and asthma variants with other phenotypes using phenome-wide association results derived in the UK Biobank. Our clustering analysis of the variants-phenotypes association matrix identified three clusters of genetic variants with different effects on white blood cell counts, height, and body mass index (BMI). To assess the potential clinical and molecular effects of these groups of variants, we investigated the association between cluster-specific genetic risk scores and phenotypes in the COPDGene cohort. We observed differences in steroid use, BMI, lymphocyte counts, chronic bronchitis, and differential gene and protein expression across the three genetic risk scores. Our results suggest that multi-phenotype analysis of obstructive lung disease-related risk variants may identify genetically driven phenotypic patterns in COPD.
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Affiliation(s)
- Andrey Ziyatdinov
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Brian D Hobbs
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Samir Kanaan-Izquierdo
- Centre de Recerca en Enginyeria Biomèdica, Universitat Politècnica de Catalunya, Barcelona 08028, Spain
- CIBER of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Catalonia, Spain
- Institut de Recerca Sant Joan de Deu, Esplugues de Llobregat, Spain
| | - Matthew Moll
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Phuwanat Sakornsakolpat
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Nick Shrine
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Jing Chen
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Kijoung Song
- Human Genetics, GlaxoSmithKline, Collegeville, PA, USA
| | - Russell P Bowler
- Division of Pulmonary and Critical Care, Dept. Med, National Jewish Health, Denver, CO, USA
| | - Peter J Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Hanna Julienne
- Institut Pasteur, Université Paris Cité, Department of Computational Biology, F-75015 Paris, France
| | - Hugues Aschard
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Institut Pasteur, Université Paris Cité, Department of Computational Biology, F-75015 Paris, France
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
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Kim J, Lee J, Nam K, Lee S. Investigation of genetic variants and causal biomarkers associated with brain aging. Sci Rep 2023; 13:1526. [PMID: 36707530 PMCID: PMC9883521 DOI: 10.1038/s41598-023-27903-x] [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: 09/25/2022] [Accepted: 01/10/2023] [Indexed: 01/29/2023] Open
Abstract
Delta age is a biomarker of brain aging that captures differences between the chronological age and the predicted biological brain age. Using multimodal data of brain MRI, genomics, and blood-based biomarkers and metabolomics in UK Biobank, this study investigates an explainable and causal basis of high delta age. A visual saliency map of brain regions showed that lower volumes in the fornix and the lower part of the thalamus are key predictors of high delta age. Genome-wide association analysis of the delta age using the SNP array data identified associated variants in gene regions such as KLF3-AS1 and STX1. GWAS was also performed on the volumes in the fornix and the lower part of the thalamus, showing a high genetic correlation with delta age, indicating that they share a genetic basis. Mendelian randomization (MR) for all metabolomic biomarkers and blood-related phenotypes showed that immune-related phenotypes have a causal impact on increasing delta age. Our analysis revealed regions in the brain that are susceptible to the aging process and provided evidence of the causal and genetic connections between immune responses and brain aging.
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Affiliation(s)
- Jangho Kim
- Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea
| | - Junhyeong Lee
- Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea
| | - Kisung Nam
- Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea
| | - Seunggeun Lee
- Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea.
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Gao C, Amador C, Walker RM, Campbell A, Madden RA, Adams MJ, Bai X, Liu Y, Li M, Hayward C, Porteous DJ, Shen X, Evans KL, Haley CS, McIntosh AM, Navarro P, Zeng Y. Phenome-wide analysis identifies parent-of-origin effects on the human methylome associated with changes in the rate of aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.18.524653. [PMID: 36711749 PMCID: PMC9882261 DOI: 10.1101/2023.01.18.524653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Variation in the rate at which humans age may be rooted in early life events acting through genomic regions that are influenced by such events and subsequently are related to health phenotypes in later life. The parent-of-origin-effect (POE)-regulated methylome includes regions either enriched for genetically controlled imprinting effects (the typical type of POE) or atypical POE introduced by environmental effects associated with parents. This part of the methylome is heavily influenced by early life events, making it a potential route connecting early environmental exposures, the epigenome and the rate of aging. Here, we aim to test the association of POE-influenced methylation of CpG dinucleotides (POE-CpG sites) with early and later environmental exposures and subsequently with health-related phenotypes and adult aging phenotypes. We do this by performing phenome-wide association analyses of the POE-influenced methylome using a large family-based population cohort (GS:SFHS, Ndiscovery=5,087, Nreplication=4,450). At the single CpG level, 92 associations of POE-CpGs with phenotypic variation were identified and replicated. Most of the associations were contributed by POE-CpGs belonging to the atypical class and the most strongly enriched associations were with aging (DNAmTL acceleration), intelligence and parental (maternal) smoking exposure phenotypes. We further found that a proportion of the atypical-POE-CpGs formed co-methylation networks (modules) which are associated with these phenotypes, with one of the aging-associated modules displaying increased internal module connectivity (strength of methylation correlation across constituent CpGs) with age. Atypical POE-CpGs also displayed high levels of methylation heterogeneity and epigenetic drift (i.e. information loss with age) and a strong correlation with CpGs contained within epigenetic clocks. These results identified associations between the atypical-POE-influenced methylome and aging and provided new evidence for the "early development of origin" hypothesis for aging in humans.
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Affiliation(s)
- Chenhao Gao
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| | - Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Rosie M. Walker
- Centre for Clinical Brain Sciences, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- School of Psychology, University of Exeter, Perry Road, Exeter, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Rebecca A Madden
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark J. Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Xiaomeng Bai
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| | - Ying Liu
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| | - Miaoxin Li
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Chris S. Haley
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Andrew M. McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Yanni Zeng
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
- Guangdong Province Translational Forensic Medicine Engineering Technology Research Center Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
- Guangdong Province Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
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Wu L, Pei H, Zhang Y, Zhang X, Feng M, Yuan L, Guo M, Wei Y, Tang Z, Xiang X. Association between Dried Fruit Intake and DNA Methylation: A Multivariable Mendelian Randomization Analysis. J Nutr Health Aging 2023; 27:1132-1139. [PMID: 37997736 DOI: 10.1007/s12603-023-2030-x] [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: 05/12/2023] [Accepted: 11/04/2023] [Indexed: 11/25/2023]
Abstract
OBJECTIVES Observational studies have reported associations between dried fruit intake and DNA methylation(DNAm). However, inherent flaws in observational study designs make them susceptible to confounding and reverse causality bias. Consequently, it is unclear whether a causal association exists. In the present study, we aimed to investigate the causal associations between dried fruit intake and DNAm. METHODS We performed two-sample Mendelian randomization (MR) using the IEU Open GWAS database aggregated data. Forty-three single nucleotide polymorphisms (SNPs) associated with dried fruit intake as instrumental variables (IVs) were selected as exposure. DNAm outcomes include Gran (estimated granulocyte proportions); AgeAccelGrim(GrimAge acceleration); Hannum (Hannum age acceleration); IEAA(Intrinsic epigenetic age acceleration), AgeAccelPheno( PhenoAge acceleration), and DNAmPAIadjAge (DNAm-estimated plasminogen activator inhibitor-1 levels). We used the MR pleiotropy residual sum and outlier test (MRPRESSO) and Radial-MR test to identify any level of multi-effect outliers and assessed the causal effect estimates(after removing outliers). The primary causal effects were estimated using inverse-variance weighted (IVW) method and undertook sensitivity analyses using MR methods robust to horizontal pleiotropy.The direct effects of dried fruit intake on DNAm were estimated using multivariable mendelian randomization (MVMR). RESULTS Leveraging two-sample MR analysis, we observed statistically significant associations between dried fruit intake with a lower AgeAccelGrim(β=-1.365, 95% confidence intervals [CI] -2.266 to -0.464, PIVW=2.985×10-3) and AgeAccelPheno (β= -1.933, 95% CI -3.068 to -0.798, PIVW=8.371×10-4). By contrast, the effects level on Gran (β=0.008, PIVW=0.430), Hannum(β=-0.430, PIVW=0.357), IEAA(β=-0.184, PIVW=0.700), and DNAmPAIadjAge (β=-1.861, PIVW=0.093) were not statistically significant. MVMR results adjusting for the potential effects of confounders showed that the causal relationship between dried fruit intake and AgeAccelGrim(β= -1.315, 95% CI -2.373 to -0.258, PIVW=1.480×10-2) and AgeAccelPheno(β= -1.595, 95% CI -2.987 to -0.202, PIVW=2.483×10-2) persisted. No significant horizontal polymorphism was found in the sensitivity analysis. CONCLUSION Our MR study suggested that increased dried fruit intake is associated with slower AgeAccelGrim and AgeAccelPheno. It can providing a promising avenue for exploring the beneficial effects of dried fruit intake on lifespan extension.
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Affiliation(s)
- L Wu
- Xiqiao Xiang. Department of PET Imaging Center, Shanghai Jiaotong University Affiliated Sixth People Hospital South Campus. Shanghai, 201499, China. E-mail:
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Guo Y, Zhang Y, Hu Y. COVID-19 subgroups may slow down biological age acceleration. J Infect 2023; 86:66-117. [PMID: 36273644 PMCID: PMC9584757 DOI: 10.1016/j.jinf.2022.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 09/28/2022] [Accepted: 10/02/2022] [Indexed: 02/04/2023]
Affiliation(s)
- Yu Guo
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Ying Zhang
- Beidahuang Industry Group General Hospital, Harbin, China
| | - Yang Hu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China,Corresponding author
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Genetic Variants in Telomerase Reverse Transcriptase Contribute to Solar Lentigines. J Invest Dermatol 2022; 143:1062-1072.e25. [PMID: 36572090 DOI: 10.1016/j.jid.2022.11.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 10/01/2022] [Accepted: 11/11/2022] [Indexed: 12/26/2022]
Abstract
Solar lentigines (SLs) are a hallmark of human skin aging. They result from chronic exposure to sunlight and other environmental stressors. Recent studies also imply genetic factors, but findings are partially conflicting and lack of replication. Through a multi-trait based analysis strategy, we discovered that genetic variants in telomerase reverse transcriptase were significantly associated with non-facial SL in two East Asian (Taizhou longitudinal cohort, n = 2,964 and National Survey of Physical Traits, n = 2,954) and one Caucasian population (SALIA, n = 462), top SNP rs2853672 (P-value for Taizhou longitudinal cohort = 1.32 × 10‒28 and P-value for National Survey of Physical Traits = 3.66 × 10‒17 and P-value for SALIA = 0.0007 and Pmeta = 4.93 × 10‒44). The same variants were nominally associated with facial SL but not with other skin aging or skin pigmentation traits. The SL-enhanced allele/haplotype upregulated the transcription of the telomerase reverse transcriptase gene. Of note, well-known telomerase reverse transcriptase‒related aging markers such as leukocyte telomere length and intrinsic epigenetic age acceleration were not associated with SL. Our results indicate a previously unrecognized role of telomerase reverse transcriptase in skin aging‒related lentigines formation.
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Lu AT, Binder AM, Zhang J, Yan Q, Reiner AP, Cox SR, Corley J, Harris SE, Kuo PL, Moore AZ, Bandinelli S, Stewart JD, Wang C, Hamlat EJ, Epel ES, Schwartz JD, Whitsel EA, Correa A, Ferrucci L, Marioni RE, Horvath S. DNA methylation GrimAge version 2. Aging (Albany NY) 2022; 14:9484-9549. [PMID: 36516495 PMCID: PMC9792204 DOI: 10.18632/aging.204434] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 11/21/2022] [Indexed: 12/15/2022]
Abstract
We previously described a DNA methylation (DNAm) based biomarker of human mortality risk DNAm GrimAge. Here we describe version 2 of GrimAge (trained on individuals aged between 40 and 92) which leverages two new DNAm based estimators of (log transformed) plasma proteins: high sensitivity C-reactive protein (logCRP) and hemoglobin A1C (logA1C). We evaluate GrimAge2 in 13,399 blood samples across nine study cohorts. After adjustment for age and sex, GrimAge2 outperforms GrimAge in predicting mortality across multiple racial/ethnic groups (meta P=3.6x10-167 versus P=2.6x10-144) and in terms of associations with age related conditions such as coronary heart disease, lung function measurement FEV1 (correlation= -0.31, P=1.1x10-136), computed tomography based measurements of fatty liver disease. We present evidence that GrimAge version 2 also applies to younger individuals and to saliva samples where it tracks markers of metabolic syndrome. DNAm logCRP is positively correlated with morbidity count (P=1.3x10-54). DNAm logA1C is highly associated with type 2 diabetes (P=5.8x10-155). DNAm PAI-1 outperforms the other age-adjusted DNAm biomarkers including GrimAge2 in correlating with triglyceride (cor=0.34, P=9.6x10-267) and visceral fat (cor=0.41, P=4.7x10-41). Overall, we demonstrate that GrimAge version 2 is an attractive epigenetic biomarker of human mortality and morbidity risk.
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Affiliation(s)
- Ake T. Lu
- Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA,San Diego Institute of Science, Altos Labs, San Diego, CA 92121, USA
| | - Alexandra M. Binder
- Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI 96813, USA,Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA 90095, USA
| | - Joshua Zhang
- Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Qi Yan
- San Diego Institute of Science, Altos Labs, San Diego, CA 92121, USA
| | - Alex P. Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Simon R. Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, Scotland, UK
| | - Janie Corley
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, Scotland, UK
| | - Sarah E. Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, Scotland, UK
| | - Pei-Lun Kuo
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Ann Z. Moore
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Stefania Bandinelli
- Geriatric Unit, Local Health Unit Tuscany Centre, Firenze, Tuscany 40125, Italy
| | - James D. Stewart
- Dept. of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27516-8050, USA
| | - Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Elissa J. Hamlat
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143-0848, USA
| | - Elissa S. Epel
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143-0848, USA
| | - Joel D. Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Eric A. Whitsel
- Dept. of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27516-8050, USA,Dept. of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Adolfo Correa
- Departments of Medicine and Population Health Science, Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, Scotland, UK
| | - Steve Horvath
- Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA,San Diego Institute of Science, Altos Labs, San Diego, CA 92121, USA,Dept. of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, USA
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Jiang R, Hauser ER, Kwee LC, Shah SH, Regan JA, Huebner JL, Kraus VB, Kraus WE, Ward-Caviness CK. The association of accelerated epigenetic age with all-cause mortality in cardiac catheterization patients as mediated by vascular and cardiometabolic outcomes. Clin Epigenetics 2022; 14:165. [PMID: 36461124 PMCID: PMC9719253 DOI: 10.1186/s13148-022-01380-x] [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: 10/20/2022] [Accepted: 11/16/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Epigenetic age is a DNA methylation-based biomarker of aging that is accurate across the lifespan and a range of cell types. The difference between epigenetic age and chronological age, termed age acceleration (AA), is a strong predictor of lifespan and healthspan. The predictive capabilities of AA for all-cause mortality have been evaluated in the general population; however, its utility is less well evaluated in those with chronic conditions. Additionally, the pathophysiologic pathways whereby AA predicts mortality are unclear. We hypothesized that AA predicts mortality in individuals with underlying cardiovascular disease; and the association between AA and mortality is mediated, in part, by vascular and cardiometabolic measures. METHODS We evaluated 562 participants in an urban, three-county area of central North Carolina from the CATHGEN cohort, all of whom received a cardiac catheterization procedure. We analyzed three AA biomarkers, Horvath epigenetic age acceleration (HAA), phenotypic age acceleration (PhenoAA), and Grim age acceleration (GrimAA), by Cox regression models, to assess whether AAs were associated with all-cause mortality. We also evaluated if these associations were mediated by vascular and cardiometabolic outcomes, including left ventricular ejection fraction (LVEF), blood cholesterol concentrations, angiopoietin-2 (ANG2) protein concentration, peripheral artery disease, coronary artery disease, diabetes, and hypertension. The total effect, direct effect, indirect effect, and percentage mediated were estimated using pathway mediation tests with a regression adjustment approach. RESULTS PhenoAA (HR = 1.05, P < 0.0001), GrimAA (HR = 1.10, P < 0.0001) and HAA (HR = 1.03, P = 0.01) were all associated with all-cause mortality. The association of mortality and PhenoAA was partially mediated by ANG2, a marker of vascular function (19.8%, P = 0.016), and by diabetes (8.2%, P = 0.043). The GrimAA-mortality association was mediated by ANG2 (12.3%, P = 0.014), and showed weaker evidence for mediation by LVEF (5.3%, P = 0.065). CONCLUSIONS Epigenetic age acceleration remains strongly predictive of mortality even in individuals already burdened with cardiovascular disease. Mortality associations were mediated by ANG2, which regulates endothelial permeability and angiogenic functions, suggesting that specific vascular pathophysiology may link accelerated epigenetic aging with increased mortality risks.
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Affiliation(s)
- Rong Jiang
- grid.26009.3d0000 0004 1936 7961Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC USA
| | - Elizabeth R. Hauser
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA ,grid.26009.3d0000 0004 1936 7961Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC USA
| | - Lydia Coulter Kwee
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA
| | - Svati H. Shah
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA ,grid.26009.3d0000 0004 1936 7961Division of Cardiology, Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC USA
| | - Jessica A. Regan
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA ,grid.26009.3d0000 0004 1936 7961Division of Cardiology, Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC USA
| | - Janet L. Huebner
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA
| | - Virginia B. Kraus
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA ,grid.26009.3d0000 0004 1936 7961Division of Rheumatology, Department of Medicine, Duke University School of Medicine, Durham, NC USA
| | - William E. Kraus
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA ,grid.26009.3d0000 0004 1936 7961Division of Cardiology, Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC USA
| | - Cavin K. Ward-Caviness
- grid.418698.a0000 0001 2146 2763Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC USA
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50
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Abstract
Age is the key risk factor for diseases and disabilities of the elderly. Efforts to tackle age-related diseases and increase healthspan have suggested targeting the ageing process itself to 'rejuvenate' physiological functioning. However, achieving this aim requires measures of biological age and rates of ageing at the molecular level. Spurred by recent advances in high-throughput omics technologies, a new generation of tools to measure biological ageing now enables the quantitative characterization of ageing at molecular resolution. Epigenomic, transcriptomic, proteomic and metabolomic data can be harnessed with machine learning to build 'ageing clocks' with demonstrated capacity to identify new biomarkers of biological ageing.
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Affiliation(s)
- Jarod Rutledge
- Department of Genetics, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Paul F. Glenn Center for the Biology of Ageing, Stanford University School of Medicine, Stanford, CA, USA
| | - Hamilton Oh
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Paul F. Glenn Center for the Biology of Ageing, Stanford University School of Medicine, Stanford, CA, USA
- Graduate Program in Stem Cell and Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - Tony Wyss-Coray
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
- Paul F. Glenn Center for the Biology of Ageing, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.
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