1
|
Zheng X, Chen M, Zhuang Y, Xu J, Zhao L, Qian Y, Shen W. Genetic associations between gut microbiota and allergic rhinitis: an LDSC and MR analysis. Front Microbiol 2024; 15:1395340. [PMID: 38855765 PMCID: PMC11157438 DOI: 10.3389/fmicb.2024.1395340] [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: 03/03/2024] [Accepted: 04/26/2024] [Indexed: 06/11/2024] Open
Abstract
Background Several studies have suggested a potential link between allergic rhinitis (AR) and gut microbiota. In response, we conducted a meta-analysis of Linkage Disequilibrium Score Regression (LDSC) and Mendelian randomization (MR) to detect their genetic associations. Methods Summary statistics for 211 gut microbiota taxa were gathered from the MiBioGen study, while data for AR were sourced from the Pan-UKB, the FinnGen, and the Genetic Epidemiology Research on Aging (GERA). The genetic correlation between gut microbiota and AR was assessed using LDSC. The principal estimate of causality was determined using the Inverse-Variance Weighted (IVW) method. To assess the robustness of these findings, sensitivity analyses were conducted employing methods such as the weighted median, MR-Egger, and MR-PRESSO. The summary effect estimates of LDSC, forward MR and reverse MR were combined using meta-analysis for AR from different data resources. Results Our study indicated a significant genetic correlation between genus Sellimonas (Rg = -0.64, p = 3.64 × 10-5, Adjust_P = 3.64 × 10-5) and AR, and a suggestive genetic correlation between seven bacterial taxa and AR. Moreover, the forward MR analysis identified genus Gordonibacter, genus Coprococcus2, genus LachnospiraceaeUCG010, genus Methanobrevibacter, and family Victivallaceae as being suggestively associated with an increased risk of AR. The reverse MR analysis indicated that AR was suggestively linked to an increased risk for genus Coprococcus2 and genus RuminococcaceaeUCG011. Conclusion Our findings indicate a causal relationship between specific gut microbiomes and AR. This enhances our understanding of the gut microbiota's contribution to the pathophysiology of AR and lays the groundwork for innovative approaches and theoretical models for future prevention and treatment strategies in this patient population.
Collapse
Affiliation(s)
| | | | | | | | | | | | - WenMing Shen
- Emergency Department, Wujin People’s Hospital Affiliated with Jiangsu University and Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu, China
| |
Collapse
|
2
|
Pan C, Cheng B, Qin X, Cheng S, Liu L, Yang X, Meng P, Zhang N, He D, Cai Q, Wei W, Hui J, Wen Y, Jia Y, Liu H, Zhang F. Enhanced polygenic risk score incorporating gene-environment interaction suggests the association of major depressive disorder with cardiac and lung function. Brief Bioinform 2024; 25:bbae070. [PMID: 38436562 DOI: 10.1093/bib/bbae070] [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] [Revised: 01/18/2024] [Accepted: 02/02/2024] [Indexed: 03/05/2024] Open
Abstract
BACKGROUND Depression has been linked to an increased risk of cardiovascular and respiratory diseases; however, its impact on cardiac and lung function remains unclear, especially when accounting for potential gene-environment interactions. METHODS We developed a novel polygenic and gene-environment interaction risk score (PGIRS) integrating the major genetic effect and gene-environment interaction effect of depression-associated loci. The single nucleotide polymorphisms (SNPs) demonstrating major genetic effect or environmental interaction effect were obtained from genome-wide SNP association and SNP-environment interaction analyses of depression. We then calculated the depression PGIRS for non-depressed individuals, using smoking and alcohol consumption as environmental factors. Using linear regression analysis, we assessed the associations of PGIRS and conventional polygenic risk score (PRS) with lung function (N = 42 886) and cardiac function (N = 1791) in the subjects with or without exposing to smoking and alcohol drinking. RESULTS We detected significant associations of depression PGIRS with cardiac and lung function, contrary to conventional depression PRS. Among smokers, forced vital capacity exhibited a negative association with PGIRS (β = -0.037, FDR = 1.00 × 10-8), contrasting with no significant association with PRS (β = -0.002, FDR = 0.943). In drinkers, we observed a positive association between cardiac index with PGIRS (β = 0.088, FDR = 0.010), whereas no such association was found with PRS (β = 0.040, FDR = 0.265). Notably, in individuals who both smoked and drank, forced expiratory volume in 1-second demonstrated a negative association with PGIRS (β = -0.042, FDR = 6.30 × 10-9), but not with PRS (β = -0.003, FDR = 0.857). CONCLUSIONS Our findings underscore the profound impact of depression on cardiac and lung function, highlighting the enhanced efficacy of considering gene-environment interactions in PRS-based studies.
Collapse
Affiliation(s)
- Chuyu Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Xiaoyue Qin
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Na Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Dan He
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Qingqing Cai
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Wenming Wei
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Jingni Hui
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Huan Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| |
Collapse
|
3
|
Higbee DH, Lirio A, Hamilton F, Granell R, Wyss AB, London SJ, Bartz TM, Gharib SA, Cho MH, Wan E, Silverman E, Crapo JD, Lominchar JVT, Hansen T, Grarup N, Dantoft T, Kårhus L, Linneberg A, O'Connor GT, Dupuis J, Xu H, De Vries MM, Hu X, Rich SS, Barr RG, Manichaikul A, Wijnant SRA, Brusselle GG, Lahousse L, Li X, Hernández Cordero AI, Obeidat M, Sin DD, Harris SE, Redmond P, Taylor AM, Cox SR, Williams AT, Shrine N, John C, Guyatt AL, Hall IP, Davey Smith G, Tobin MD, Dodd JW. Genome-wide association study of preserved ratio impaired spirometry (PRISm). Eur Respir J 2024; 63:2300337. [PMID: 38097206 PMCID: PMC10765494 DOI: 10.1183/13993003.00337-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 10/29/2023] [Indexed: 12/24/2023]
Abstract
BACKGROUND Preserved ratio impaired spirometry (PRISm) is defined as a forced expiratory volume in 1 s (FEV1) <80% predicted and FEV1/forced vital capacity ≥0.70. PRISm is associated with respiratory symptoms and comorbidities. Our objective was to discover novel genetic signals for PRISm and see if they provide insight into the pathogenesis of PRISm and associated comorbidities. METHODS We undertook a genome-wide association study (GWAS) of PRISm in UK Biobank participants (Stage 1), and selected single nucleotide polymorphisms (SNPs) reaching genome-wide significance for replication in 13 cohorts (Stage 2). A combined meta-analysis of Stage 1 and Stage 2 was done to determine top SNPs. We used cross-trait linkage disequilibrium score regression to estimate genome-wide genetic correlation between PRISm and pulmonary and extrapulmonary traits. Phenome-wide association studies of top SNPs were performed. RESULTS 22 signals reached significance in the joint meta-analysis, including four signals novel for lung function. A strong genome-wide genetic correlation (rg) between PRISm and spirometric COPD (rg=0.62, p<0.001) was observed, and genetic correlation with type 2 diabetes (rg=0.12, p=0.007). Phenome-wide association studies showed that 18 of 22 signals were associated with diabetic traits and seven with blood pressure traits. CONCLUSION This is the first GWAS to successfully identify SNPs associated with PRISm. Four of the signals, rs7652391 (nearest gene MECOM), rs9431040 (HLX), rs62018863 (TMEM114) and rs185937162 (HLA-B), have not been described in association with lung function before, demonstrating the utility of using different lung function phenotypes in GWAS. Genetic factors associated with PRISm are strongly correlated with risk of both other lung diseases and extrapulmonary comorbidity.
Collapse
Affiliation(s)
- Daniel H Higbee
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Academic Respiratory Unit, University of Bristol, Southmead Hospital, Bristol, UK
| | - Alvin Lirio
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Fergus Hamilton
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
| | - Raquel Granell
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
| | - Annah B Wyss
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Biostatistics and Medicine, University of Washington, Seattle, WA, USA
| | - Sina A Gharib
- Computational Medicine Core, Center for Lung Biology, UW Medicine Sleep Center, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Emily Wan
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Pulmonary and Critical Care Section, Department of Medicine, VA Boston Healthcare System, Boston, MA, USA
| | - Edwin Silverman
- Pulmonary and Critical Care Section, Department of Medicine, VA Boston Healthcare System, Boston, MA, USA
| | - James D Crapo
- Division of Pulmonary, Critical Care and Sleep Medicine, National Jewish Health, Denver, CO, USA
| | - Jesus V T Lominchar
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Dantoft
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
| | - Line Kårhus
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
| | - George T O'Connor
- Pulmonary Center, School of Medicine, Boston University, Boston, MA, USA
- Division of Pulmonary, Allergy, Sleep, and Critical Care Medicine, Boston Medical Center, Boston, MA, USA
| | - Josée Dupuis
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
| | - Hanfie Xu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Maaike M De Vries
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Groningen Research Institute for Asthma and COPD, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Xiaowei Hu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R Graham Barr
- Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Sara R A Wijnant
- Department of Bioanalysis, Ghent University, Ghent, Belgium
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Guy G Brusselle
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
- Department of Epidemiology, Department of Respiratory Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Lies Lahousse
- Department of Bioanalysis, Ghent University, Ghent, Belgium
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Xuan Li
- Centre for Heart Lung Innovation, University of British Columbia, St. Paul's Hospital, Vancouver, BC, Canada
| | - Ana I Hernández Cordero
- Centre for Heart Lung Innovation, University of British Columbia, St. Paul's Hospital, Vancouver, BC, Canada
| | - Ma'en Obeidat
- Centre for Heart Lung Innovation, University of British Columbia, St. Paul's Hospital, Vancouver, BC, Canada
| | - Don D Sin
- Centre for Heart Lung Innovation, University of British Columbia, St. Paul's Hospital, Vancouver, BC, Canada
- Division of Respiratory Medicine, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Adele M Taylor
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Alexander T Williams
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Nick Shrine
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Catherine John
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Anna L Guyatt
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Ian P Hall
- University of Nottingham and NIHR Nottingham Biomedical Research Centre, Nottingham, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
| | - Martin D Tobin
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Leicester NIHR Biomedical Research Centre, Leicester, UK
- Joint senior authors
| | - James W Dodd
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Academic Respiratory Unit, University of Bristol, Southmead Hospital, Bristol, UK
- Joint senior authors
| |
Collapse
|
4
|
Cui G, Li S, Ye H, Yang Y, Jia X, Lin M, Chu Y, Feng Y, Wang Z, Shi Z, Zhang X. Gut microbiome and frailty: insight from genetic correlation and mendelian randomization. Gut Microbes 2023; 15:2282795. [PMID: 37990415 PMCID: PMC10730212 DOI: 10.1080/19490976.2023.2282795] [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: 03/30/2023] [Accepted: 11/08/2023] [Indexed: 11/23/2023] Open
Abstract
Observational studies have shown that the gut microbiome is associated with frailty. However, whether these associations underlie causal effects remains unknown. Thus, this study aimed to assess the genetic correlation and causal relationships between the genetically predicted gut microbiome and frailty using linkage disequilibrium score regression (LDSC) and Mendelian Randomization (MR). Summary statistics for the gut microbiome were obtained from a genome-wide association study (GWAS) meta-analysis of the MiBioGen consortium (N = 18,340). Summary statistics for frailty were obtained from a GWAS meta-analysis, including the UK Biobank and TwinGene (N = 175,226). We used LDSC and MR analyses to estimate the genetic correlation and causality between the genetically predicted gut microbiome and frailty. Our findings indicate a suggestive genetic correlation between Christensenellaceae R-7 and frailty. Moreover, we found evidence for suggestive causal effects of twelve genus-level gut microbes on frailty using at least two MR methods. There was no evidence of horizontal pleiotropy or heterogeneity in the MR analysis. This study provides suggestive evidence for a potential genetic correlation and causal association between several genetically predicted gut microbes and frailty. More population-based observational studies and animal experiments are required to clarify this association and the underlying mechanisms.
Collapse
Affiliation(s)
- Guanghui Cui
- Department of Integrated Traditional Chinese and Western Medicine, Peking University First Hospital; Institute of Integrated Traditional Chinese and Western Medicine, Peking University, Beijing, China
| | - Shaojie Li
- School of Public Health, Peking University, Beijing, China
- China Center for Health Development Studies, Peking University, Beijing, China
| | - Hui Ye
- Department of Integrated Traditional Chinese and Western Medicine, Peking University First Hospital; Institute of Integrated Traditional Chinese and Western Medicine, Peking University, Beijing, China
| | - Yao Yang
- Department of Integrated Traditional Chinese and Western Medicine, Peking University First Hospital; Institute of Integrated Traditional Chinese and Western Medicine, Peking University, Beijing, China
| | - Xiaofen Jia
- Department of Integrated Traditional Chinese and Western Medicine, Peking University First Hospital; Institute of Integrated Traditional Chinese and Western Medicine, Peking University, Beijing, China
| | - Miaomiao Lin
- Department of Integrated Traditional Chinese and Western Medicine, Peking University First Hospital; Institute of Integrated Traditional Chinese and Western Medicine, Peking University, Beijing, China
| | - Yingming Chu
- Department of Integrated Traditional Chinese and Western Medicine, Peking University First Hospital; Institute of Integrated Traditional Chinese and Western Medicine, Peking University, Beijing, China
| | - Yue Feng
- Department of Integrated Traditional Chinese and Western Medicine, Peking University First Hospital; Institute of Integrated Traditional Chinese and Western Medicine, Peking University, Beijing, China
| | - Zicheng Wang
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Zongming Shi
- Department of Integrated Traditional Chinese and Western Medicine, Peking University First Hospital; Institute of Integrated Traditional Chinese and Western Medicine, Peking University, Beijing, China
| | - Xuezhi Zhang
- Department of Integrated Traditional Chinese and Western Medicine, Peking University First Hospital; Institute of Integrated Traditional Chinese and Western Medicine, Peking University, Beijing, China
| |
Collapse
|
5
|
Zhang A, Tian S. Integrative Analyses of Mendelian Randomization and Transcriptomic Data Reveal No Association between Leptin and Chronic Obstructive Pulmonary Disease. COPD 2023; 20:321-326. [PMID: 37812260 DOI: 10.1080/15412555.2023.2260890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 09/13/2023] [Indexed: 10/10/2023]
Abstract
As a key adipokine, leptin has been extensively investigated for its potential role in the pathogenesis of chronic obstructive pulmonary disease (COPD). However, concordant conclusions have not been attained. In this study, we investigated the relationship between leptin and COPD using an integrative analysis that combined a Mendelian randomization (MR) study with transcriptomic data analysis. Here, the MR analysis was performed on the online platform MR-Base, and the bioinformatics analyses were performed with the aid of R Bioconductor packages. No evidence was found by the integrative analysis to support the association of the two attributes. All methods detected a null causal effect of leptin on COPD in the MR analysis. In particular, when the genetically predicted leptin level increased one unit, the risk of developing COPD was estimated as 0.999 (p = 0.943), 0.920 (p = 0.516), 1.002 (p = 0.885), and 1.002 (p = 0.906) by the Inverse Variance Weighted (IVW), MR-Egger, weighted median, and weighted mode method, respectively. Furthermore, no leptin-associated genes except one were identified as being differentially expressed between COPD and control in bioinformatics analysis. The observed association between leptin and COPD in previous observational studies may be attributable to unmeasured confounding effects or reverse causation.
Collapse
Affiliation(s)
- Ao Zhang
- Department of Neurology, The First Hospital of Jilin University, Changchun, Jilin, People's Republic of China
| | - Suyan Tian
- Division of Clinical Research, The First Hospital of Jilin University, Changchun, Jilin, People's Republic of China
| |
Collapse
|
6
|
Molina-Luque R, Molina-Recio G, de-Pedro-Jiménez D, Álvarez Fernández C, García-Rodríguez M, Romero-Saldaña M. The Impact of Metabolic Syndrome Risk Factors on Lung Function Impairment: Cross-Sectional Study. JMIR Public Health Surveill 2023; 9:e43737. [PMID: 37669095 PMCID: PMC10516148 DOI: 10.2196/43737] [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: 10/22/2022] [Revised: 05/17/2023] [Accepted: 07/18/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND Metabolic syndrome (MetS) is a constellation of risk factors increasingly present in the world's population. People with this syndrome are at an increased risk of cardiovascular disease and type 2 diabetes mellitus. Moreover, evidence has shown that it affects different organs. MetS and its risk factors are independently associated with impaired lung function, which can be quantified through spirometric variables. OBJECTIVE This study aims to determine whether a high number of MetS criteria is associated with increased lung function decline. METHODS We conducted a descriptive cross-sectional study with a random sample of 1980 workers. Workers with acute respiratory pathology (eg, influenza), chronic respiratory pathology (eg, chronic bronchitis), or exposure to substances harmful to the lungs (eg, organic and inorganic dust) were not included. MetS was established based on harmonized criteria, and lung function was assessed according to spirometric variables. On the basis of these, classification into restrictive lung disease (RLD), obstructive lung disease, and mixed lung disease (MLD) was performed. In addition, the association between MetS and lung function was established based on analysis of covariance, linear trend analysis, and multiple linear regression. RESULTS MetS was associated with worse lung function according to all the spirometric parameters analyzed (percentage of predicted forced expiratory volume in 1 second: mean 83, SD 13.8 vs mean 89.2, SD 12.8; P<.001 and percentage of predicted forced vital capacity: mean 85.9, SD 11.6 vs mean 92, SD 11.3; P<.001). Moreover, those diagnosed with MetS had a higher prevalence of lung dysfunction (41% vs 21.9%; P<.001), RLD (23.4% vs 11.2%; P<.001), and MLD (7.3% vs 2.2%; P<.001). Furthermore, an increasing number of MetS criteria was associated with a greater impairment of pulmonary mechanics (P<.001). Similarly, with an increasing number of MetS criteria, there was a significant linear trend (P<.001) in the growth of the prevalence ratio of RLD (0 criteria: 1, 1: 1.46, 2: 1.52, 3: 2.53, 4: 2.97, and 5: 5.34) and MLD (0 criteria: 1, 1: 2.68, 2: 6.18, 3: 9.69, and 4: 11.37). Regression analysis showed that the alteration of all MetS risk factors, adjusted for various explanatory variables, was significantly associated with a worsening of spirometric parameters, except for forced expiratory volume in 1 second/forced vital capacity. CONCLUSIONS The findings have shown that an increase in cardiometabolic risk factors is associated with a more significant worsening of spirometric variables and a higher prevalence of RLD and MLD. As spirometry could be a crucial tool for monitoring patients at risk of developing chronic pathologies, we conclude that this inexpensive and easily accessible test could help detect changes in lung function in patients with cardiometabolic disorders. This highlights the need to consider the importance of cardiometabolic health in lung function when formulating public health policies.
Collapse
Affiliation(s)
- Rafael Molina-Luque
- Estilos de Vida, Innovación y Salud, Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Córdoba, Spain
- Departamento de Enfermería, Famarcología y Fisioterapia, Universidad de Córdoba, Córdoba, Spain
| | - Guillermo Molina-Recio
- Estilos de Vida, Innovación y Salud, Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Córdoba, Spain
- Departamento de Enfermería, Famarcología y Fisioterapia, Universidad de Córdoba, Córdoba, Spain
| | - Domingo de-Pedro-Jiménez
- Indorama Ventures Química, Sociedad Limitado Unipersonal, Polígono Industrial Guadarranque, San Roque, Cádiz, Spain
| | | | - María García-Rodríguez
- Departamento de Enfermería y Nutrición, Facultad de Ciencias Biomédicas y de la Salud, Villaviciosa de Odón, Madrid, Spain
| | - Manuel Romero-Saldaña
- Estilos de Vida, Innovación y Salud, Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Córdoba, Spain
- Departamento de Enfermería, Famarcología y Fisioterapia, Universidad de Córdoba, Córdoba, Spain
| |
Collapse
|
7
|
Li Z, Lu F, Liu M, Guo M, Tao L, Wang T, Liu M, Guo X, Liu X. Short-Term Effects of Carbon Monoxide on Morbidity of Chronic Obstructive Pulmonary Disease With Comorbidities in Beijing. GEOHEALTH 2023; 7:e2022GH000734. [PMID: 36992869 PMCID: PMC10042128 DOI: 10.1029/2022gh000734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 02/26/2023] [Accepted: 03/03/2023] [Indexed: 06/19/2023]
Abstract
The association between CO and chronic obstructive pulmonary disease (COPD) has been widely reported; however, the association among patients with type 2 diabetes mellitus (T2DM) or hypertension has remained largely unknown in China. Over-dispersed generalized additive model was adopted to quantity the associations between CO and COPD with T2DM or hypertension. Based on principal diagnosis, COPD cases were identified according to the International Classification of Diseases (J44), and a history of T2DM and hypertension was coded as E12 and I10-15, O10-15, P29, respectively. A total of 459,258 COPD cases were recorded from 2014 to 2019. Each interquartile range uptick in CO at lag 03 corresponded to 0.21% (95%CI: 0.08%-0.34%), 0.39% (95%CI: 0.13%-0.65%), 0.29% (95%CI: 0.13%-0.45%) and 0.27% (95%CI: 0.12%-0.43%) increment in admissions for COPD, COPD with T2DM, COPD with hypertension and COPD with both T2DM and hypertension, respectively. The effects of CO on COPD with T2DM (Z = 0.77, P = 0.444), COPD with hypertension (Z = 0.19, P = 0.234) and COPD with T2DM and hypertension (Z = 0.61, P = 0.543) were insignificantly higher than that on COPD. Stratification analysis showed that females were more vulnerable than males except for T2DM group (COPD: Z = 3.49, P < 0.001; COPD with T2DM: Z = 0.176, P = 0.079; COPD with hypertension: Z = 2.48, P = 0.013; COPD with both T2DM and hypertension: Z = 2.44, P = 0.014); No statistically significant difference could be found between age groups (COPD: Z = 1.63, P = 0.104; COPD with T2DM: Z = 0.23, P = 0.821; COPD with hypertension: Z = 0.53, P = 0.595; COPD with both T2DM and hypertension: Z = 0.71, P = 0.476); Higher effects appeared in cold seasons than warm seasons on COPD (Z = 0.320, P < 0.001). This study demonstrated an increased risk of COPD with comorbidities related to CO exposure in Beijing. We further provided important information on lag patterns, susceptible subgroups, and sensitive seasons, as well as the characteristics of the exposure-response curves.
Collapse
Affiliation(s)
- Zhiwei Li
- School of Public HealthCapital Medical UniversityBeijingChina
- Beijing Municipal Key Laboratory of Clinical EpidemiologyBeijingChina
| | - Feng Lu
- Beijing Municipal Health Commission Information CentreBeijingChina
| | - Mengmeng Liu
- School of Public HealthCapital Medical UniversityBeijingChina
- Beijing Municipal Key Laboratory of Clinical EpidemiologyBeijingChina
- National Institute for Data Science in Health and MedicineCapital Medical UniversityBeijingChina
| | - Moning Guo
- Beijing Municipal Health Commission Information CentreBeijingChina
| | - Lixin Tao
- School of Public HealthCapital Medical UniversityBeijingChina
- Beijing Municipal Key Laboratory of Clinical EpidemiologyBeijingChina
| | - Tianqi Wang
- Beijing Municipal Health Commission Information CentreBeijingChina
| | - Mengyang Liu
- School of Public HealthCapital Medical UniversityBeijingChina
- Beijing Municipal Key Laboratory of Clinical EpidemiologyBeijingChina
- School of Public HealthHebei Medical UniversityShijiazhuangChina
| | - Xiuhua Guo
- School of Public HealthCapital Medical UniversityBeijingChina
- Beijing Municipal Key Laboratory of Clinical EpidemiologyBeijingChina
- National Institute for Data Science in Health and MedicineCapital Medical UniversityBeijingChina
- Centre for Precision HealthSchool of Medical and Health SciencesEdith Cowan UniversityWAJoondalupAustralia
| | - Xiangtong Liu
- School of Public HealthCapital Medical UniversityBeijingChina
- Beijing Municipal Key Laboratory of Clinical EpidemiologyBeijingChina
| |
Collapse
|
8
|
Zhang RQ, Kuo K, Liu FT, Chen SD, Yang YX, Guo Y, Dong Q, Tan L, Zhang C, Yu JT. Shared polygenic risk and causal inferences in Parkinson's disease. BRAIN DISORDERS 2022. [DOI: 10.1016/j.dscb.2022.100048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
|
9
|
Wielscher M, Mandaviya PR, Kuehnel B, Joehanes R, Mustafa R, Robinson O, Zhang Y, Bodinier B, Walton E, Mishra PP, Schlosser P, Wilson R, Tsai PC, Palaniswamy S, Marioni RE, Fiorito G, Cugliari G, Karhunen V, Ghanbari M, Psaty BM, Loh M, Bis JC, Lehne B, Sotoodehnia N, Deary IJ, Chadeau-Hyam M, Brody JA, Cardona A, Selvin E, Smith AK, Miller AH, Torres MA, Marouli E, Gào X, van Meurs JBJ, Graf-Schindler J, Rathmann W, Koenig W, Peters A, Weninger W, Farlik M, Zhang T, Chen W, Xia Y, Teumer A, Nauck M, Grabe HJ, Doerr M, Lehtimäki T, Guan W, Milani L, Tanaka T, Fisher K, Waite LL, Kasela S, Vineis P, Verweij N, van der Harst P, Iacoviello L, Sacerdote C, Panico S, Krogh V, Tumino R, Tzala E, Matullo G, Hurme MA, Raitakari OT, Colicino E, Baccarelli AA, Kähönen M, Herzig KH, Li S, Conneely KN, Kooner JS, Köttgen A, Heijmans BT, Deloukas P, Relton C, Ong KK, Bell JT, Boerwinkle E, Elliott P, Brenner H, Beekman M, Levy D, Waldenberger M, Chambers JC, Dehghan A, Järvelin MR. DNA methylation signature of chronic low-grade inflammation and its role in cardio-respiratory diseases. Nat Commun 2022; 13:2408. [PMID: 35504910 PMCID: PMC9065016 DOI: 10.1038/s41467-022-29792-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 03/31/2022] [Indexed: 02/02/2023] Open
Abstract
We performed a multi-ethnic Epigenome Wide Association study on 22,774 individuals to describe the DNA methylation signature of chronic low-grade inflammation as measured by C-Reactive protein (CRP). We find 1,511 independent differentially methylated loci associated with CRP. These CpG sites show correlation structures across chromosomes, and are primarily situated in euchromatin, depleted in CpG islands. These genomic loci are predominantly situated in transcription factor binding sites and genomic enhancer regions. Mendelian randomization analysis suggests altered CpG methylation is a consequence of increased blood CRP levels. Mediation analysis reveals obesity and smoking as important underlying driving factors for changed CpG methylation. Finally, we find that an activated CpG signature significantly increases the risk for cardiometabolic diseases and COPD.
Collapse
Affiliation(s)
- Matthias Wielscher
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
- Department of Dermatology, Medical University of Vienna, Vienna, Austria.
| | - Pooja R Mandaviya
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
| | - Brigitte Kuehnel
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
| | - Roby Joehanes
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rima Mustafa
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Oliver Robinson
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Barbara Bodinier
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Rory Wilson
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Biomedical Sciences, Chang Gung University, Taoyuan City, Taiwan
| | - Saranya Palaniswamy
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Pentti Kaiteran katu 1, Linnanmaa, Oulu, Finland
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Giovanni Fiorito
- Laboratory of Biostatistics, Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | | | - Ville Karhunen
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Genetics, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Bruce M Psaty
- Cardiovacular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Marie Loh
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Mandalay Road, Singapore, Singapore
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Marc Chadeau-Hyam
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Alexia Cardona
- MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Elizabeth Selvin
- Dept. of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Alicia K Smith
- Departments of Gynecology and Obstetrics & Psychiatry and Behavioral Science, Emory University School of Medicine, Atlanta, GA, USA
| | - Andrew H Miller
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Mylin A Torres
- Department of Radiation Oncology, Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA, USA
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Xin Gào
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Johanna Graf-Schindler
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Resesarch at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Annette Peters
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Wolfgang Weninger
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Matthias Farlik
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Tao Zhang
- Deptarment of Biostatistics, School of Public Health, Shandong University, Jinan, China
| | - Wei Chen
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Yujing Xia
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Macus Doerr
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Toshiko Tanaka
- Translational Gerontology Branch, Biomedical Research Center, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Krista Fisher
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Lindsay L Waite
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Silva Kasela
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Paolo Vineis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Licia Iacoviello
- Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, IS, Italy
- Department of Medicine and Surgery, Research Center in Epidemiology and Preventive Medicine (EPIMED), University of Insubria, Varese-Como, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Citta' della Salute e della Scienza Hospital and Centre for Cancer Prevention, Turin, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia Federico II University, Naples, Italy
| | - Vittorio Krogh
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, "Civic - MPP Arezzo" Hospital, ASP Ragusa, Ragusa, Italy
| | - Evangelia Tzala
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Giuseppe Matullo
- Department of Medical Sciences, University of Turin, Turin, Italy
- AOU Città della Salute e della Scienza di Torino, Torino, Italy
| | - Mikko A Hurme
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli T Raitakari
- 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
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Elena Colicino
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrea A Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Mika Kähönen
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - Karl-Heinz Herzig
- Research Unit of Biomedicine, Medical Research Center, Faculty of Medicine, University of Oulu, and Oulu University Hospital, Oulu, Finland
- Department of Gastroenterology and Metabolism, Institute of Pediatrics, Poznan University of Medical Sciences, Poznan, Poland
| | - Shengxu Li
- Children's Minnesota Research Institute, Children's Minnesota, Minneapolis, MN, USA
| | | | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Jaspal S Kooner
- National Heart and Lung Institute, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Dept. of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Caroline Relton
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ken K Ong
- MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Houston, TX, USA
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Imperial Biomedical Research Centre, Imperial College London, London, UK
- British Heart Foundation, BHF, Centre for Research Excellence, Imperial College London, London, UK
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Marian Beekman
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - John C Chambers
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Mandalay Road, Singapore, Singapore
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College London, London, UK
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Pentti Kaiteran katu 1, Linnanmaa, Oulu, Finland.
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland.
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK.
| |
Collapse
|