. 2019 Jul 4;54(1):1900457.

doi: 10.1183/13993003.00457-2019. Print 2019 Jul.

Epigenome-wide association study of lung function level and its change

Medea Imboden^{1

2

3}, Matthias Wielscher^{4

5

3}, Faisal I Rezwan^{6

3}, André F S Amaral^{4

7

3}, Emmanuel Schaffner^{1

2}, Ayoung Jeong^{1

2}, Anna Beckmeyer-Borowko^{1

2}, Sarah E Harris^{8

9}, John M Starr^{8

10}, Ian J Deary^{8

11}, Claudia Flexeder¹², Melanie Waldenberger^{12

13}, Annette Peters^{12

13}, Holger Schulz^{12

14}, Su Chen¹⁵, Shadia Khan Sunny¹⁶, Wilfried J J Karmaus¹⁶, Yu Jiang¹⁶, Gertraud Erhart¹⁷, Florian Kronenberg¹⁷, Ryan Arathimos^{18

19}, Gemma C Sharp^{18

19

20}, Alexander John Henderson¹⁹, Yu Fu²¹, Päivi Piirilä²², Kirsi H Pietiläinen^{23

24}, Miina Ollikainen²¹, Asa Johansson²⁵, Ulf Gyllensten²⁵, Maaike de Vries^{26

27}, Diana A van der Plaat^{26

27}, Kim de Jong^{26

27}, H Marike Boezen^{26

27}, Ian P Hall^{28

29}, Martin D Tobin^{30

31}, Marjo-Riitta Jarvelin^{5

32

33

34

35

3}, John W Holloway^{6

3}, Deborah Jarvis^{4

7

3}, Nicole M Probst-Hensch^{1

2

3}

Affiliations

¹ Chronic Disease Epidemiology Unit, Dept of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.
² University of Basel, Basel, Switzerland.
³ These authors contributed equally to this work.
⁴ MRC-PHE Centre for Environment and Health, Imperial College London, London, UK.
⁵ Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
⁶ Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK.
⁷ Population Health and Occupational Disease, NHLI, Imperial College London, London, UK.
⁸ Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
⁹ Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK.
¹⁰ Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK.
¹¹ Dept of Psychology, University of Edinburgh, Edinburgh, UK.
¹² Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
¹³ Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
¹⁴ Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany.
¹⁵ Dept of Mathematical Sciences, University of Memphis, Memphis, TN, USA.
¹⁶ Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA.
¹⁷ Division of Genetic Epidemiology, Dept of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria.
¹⁸ MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
¹⁹ Dept of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
²⁰ Bristol Dental School, University of Bristol, Bristol, UK.
²¹ Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
²² Unit of Clinical Physiology, HUS Medical Imaging Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland.
²³ Obesity Research Unit, Research Programs Unit, University of Helsinki, Helsinki, Finland.
²⁴ Abdominal Center, Endocrinology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
²⁵ Dept of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
²⁶ University of Groningen, University Medical Center Groningen, Dept of Epidemiology, Groningen, The Netherlands.
²⁷ Groningen Research Institute for Asthma and COPD (GRIAC), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
²⁸ Division of Respiratory Medicine, University of Nottingham, Nottingham, UK.
²⁹ National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham University Hospitals, Nottingham, UK.
³⁰ Dept of Health Sciences, University of Leicester, Leicester, UK.
³¹ National Institute of Health Research Biomedical Research Centre, University of Leicester, Leicester, UK.
³² Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.
³³ Biocenter Oulu, University of Oulu, Oulu, Finland.
³⁴ Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland.
³⁵ Dept of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK.

PMID: 31073081
PMCID: PMC6610463
DOI: 10.1183/13993003.00457-2019

Epigenome-wide association study of lung function level and its change

Medea Imboden et al. Eur Respir J. 2019.

. 2019 Jul 4;54(1):1900457.

doi: 10.1183/13993003.00457-2019. Print 2019 Jul.

Authors

Affiliations

¹ Chronic Disease Epidemiology Unit, Dept of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.
² University of Basel, Basel, Switzerland.
³ These authors contributed equally to this work.
⁴ MRC-PHE Centre for Environment and Health, Imperial College London, London, UK.
⁵ Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
⁶ Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK.
⁷ Population Health and Occupational Disease, NHLI, Imperial College London, London, UK.
⁸ Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
⁹ Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK.
¹⁰ Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK.
¹¹ Dept of Psychology, University of Edinburgh, Edinburgh, UK.
¹² Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
¹³ Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
¹⁴ Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany.
¹⁵ Dept of Mathematical Sciences, University of Memphis, Memphis, TN, USA.
¹⁶ Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA.
¹⁷ Division of Genetic Epidemiology, Dept of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria.
¹⁸ MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
¹⁹ Dept of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
²⁰ Bristol Dental School, University of Bristol, Bristol, UK.
²¹ Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
²² Unit of Clinical Physiology, HUS Medical Imaging Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland.
²³ Obesity Research Unit, Research Programs Unit, University of Helsinki, Helsinki, Finland.
²⁴ Abdominal Center, Endocrinology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
²⁵ Dept of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
²⁶ University of Groningen, University Medical Center Groningen, Dept of Epidemiology, Groningen, The Netherlands.
²⁷ Groningen Research Institute for Asthma and COPD (GRIAC), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
²⁸ Division of Respiratory Medicine, University of Nottingham, Nottingham, UK.
²⁹ National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham University Hospitals, Nottingham, UK.
³⁰ Dept of Health Sciences, University of Leicester, Leicester, UK.
³¹ National Institute of Health Research Biomedical Research Centre, University of Leicester, Leicester, UK.
³² Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.
³³ Biocenter Oulu, University of Oulu, Oulu, Finland.
³⁴ Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland.
³⁵ Dept of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK.

PMID: 31073081
PMCID: PMC6610463
DOI: 10.1183/13993003.00457-2019

Abstract

Previous reports link differential DNA methylation (DNAme) to environmental exposures that are associated with lung function. Direct evidence on lung function DNAme is, however, limited. We undertook an agnostic epigenome-wide association study (EWAS) on pre-bronchodilation lung function and its change in adults.In a discovery-replication EWAS design, DNAme in blood and spirometry were measured twice, 6-15 years apart, in the same participants of three adult population-based discovery cohorts (n=2043). Associated DNAme markers (p<5×10^-7) were tested in seven replication cohorts (adult: n=3327; childhood: n=420). Technical bias-adjusted residuals of a regression of the normalised absolute β-values on control probe-derived principle components were regressed on level and change of forced expiratory volume in 1 s (FEV₁), forced vital capacity (FVC) and their ratio (FEV₁/FVC) in the covariate-adjusted discovery EWAS. Inverse-variance-weighted meta-analyses were performed on results from discovery and replication samples in all participants and never-smokers.EWAS signals were enriched for smoking-related DNAme. We replicated 57 lung function DNAme markers in adult, but not childhood samples, all previously associated with smoking. Markers not previously associated with smoking failed replication. cg05575921 (AHRR (aryl hydrocarbon receptor repressor)) showed the statistically most significant association with cross-sectional lung function (FEV₁/FVC: p_discovery=3.96×10^-21 and p_combined=7.22×10^-50). A score combining 10 DNAme markers previously reported to mediate the effect of smoking on lung function was associated with lung function (FEV₁/FVC: p=2.65×10^-20).Our results reveal that lung function-associated methylation signals in adults are predominantly smoking related, and possibly of clinical utility in identifying poor lung function and accelerated decline. Larger studies with more repeat time-points are needed to identify lung function DNAme in never-smokers and in children.

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Conflict of interest statement

Conflict of interest: M. Imboden has nothing to disclose. Conflict of interest: M. Wielscher has nothing to disclose. Conflict of interest: F.I. Rezwan has nothing to disclose. Conflict of interest: A.F.S. Amaral has nothing to disclose. Conflict of interest: E. Schaffner has nothing to disclose. Conflict of interest: A. Jeong has nothing to disclose. Conflict of interest: A. Beckmeyer-Borowko has nothing to disclose. Conflict of interest: S.E. Harris reports grants from Medical Research Council, Biotechnology and Biological Sciences Research Council, Age UK and The Wellcome Trust, during the conduct of the study. Conflict of interest: J.M. Starr has nothing to disclose. Conflict of interest: I.J. Deary reports grants from Age UK and Medical Research Council, during the conduct of the study. Conflict of interest: C. Flexeder has nothing to disclose. Conflict of interest: M. Waldenberger has nothing to disclose. Conflict of interest: A. Peters has nothing to disclose. Conflict of interest: H. Schulz reports grants from German Federal Ministry of Education and Research (BMBF), during the conduct of the study. Conflict of interest: S. Chen has nothing to disclose. Conflict of interest: S.K. Sunny has nothing to disclose. Conflict of interest: W.J.J. Karmaus has nothing to disclose. Conflict of interest: Y. Jiang has nothing to disclose. Conflict of interest: G. Erhart has nothing to disclose. Conflict of interest: F. Kronenberg has nothing to disclose. Conflict of interest: R. Arathimos has nothing to disclose. Conflict of interest: G.C. Sharp has nothing to disclose. Conflict of interest: A.J. Henderson reports grants from Medical Research Council and Wellcome Trust, during the conduct of the study. Conflict of interest: Y. Fu has nothing to disclose. Conflict of interest: P. Piirilä has nothing to disclose. Conflict of interest: K.H. Pietiläinen has nothing to disclose. Conflict of interest: M. Ollikainen has nothing to disclose. Conflict of interest: A. Johansson has nothing to disclose. Conflict of interest: U. Gyllensten has nothing to disclose. Conflict of interest: M de Vries has nothing to disclose. Conflict of interest: D.A. van der Plaat has nothing to disclose. Conflict of interest: K. de Jong has nothing to disclose. Conflict of interest: H.M. Boezen has nothing to disclose. Conflict of interest: I.P. Hall reports grants from GSK and Boehringer Ingelheim, outside the submitted work. Conflict of interest: M.D. Tobin reports grants from Pfizer and GSK, outside the submitted work. Conflict of interest: M-R. Jarvelin has nothing to disclose. Conflict of interest: J.W. Holloway reports grants from European Union and National Institutes of Health, during the conduct of the study. Conflict of interest: D. Jarvis reports grants from European Union, Medical Research Council and Asthma UK, during the conduct of the study. Conflict of interest: N.M. Probst-Hensch has nothing to disclose.

Figures

**FIGURE 1**
Flow of the multilevel discovery design of the epigenome-wide association study (EWAS) on lung function parameters: forced expiratory volume in 1 s (FEV₁), forced vital capacity (FVC) and FEV₁/FVC. DNAme1: DNA methylation at time-point 1; DNAme2: DNA methylation at time-point 2. ^#: base model (M_base) EWAS was covariate adjusted for age, age squared, height, squared deviation from the mean of height, sex and interaction terms of age, age squared, height and squared deviation of height with sex, education (low, medium and high), body mass index, spirometer type, study centre, and cell composition. ^¶: smoking model EWAS (M_smok) additionally adjusted for smoking covariates: history of smoking intensity as pack-years smoked up to the time-point of data collection for regressions and for smoking status (current smoker, ex-smoker and never-smoker). EWAS longitudinally predicting the change in lung function (EWAS_predict) was additionally adjusted for lung function at time-point 1.

**FIGURE 2**
a, b) Effect of ageing on the associations between DNA methylation (DNAme) and lung function: quantile–quantile plots of the cross-sectional covariate-adjusted discovery epigenome-wide association study (EWAS) (M_base^#) on forced expiratory volume in 1 s (FEV₁)/forced vital capacity (FVC) at a) time-point 1 and b) time-point 2, all participants. Increase in numbers of signals with ageing. For FEV₁/FVC, we identified 21 CpGs at time-point 2 compared with three CpGs at time-point 1 to be statistically significant. Meta-analyses were performed without genomic control (for time-point 1 inflation factor λ=1.15 and for time-point 2 inflation factor λ=1.14). For analogous figure for cross-sectional associations with FEV₁ and FVC, see supplementary figure S2. c, d) Effect of smoking adjustment on the associations between DNAme and lung function: quantile–quantile plots of c) the repeat cross-sectional covariate-adjusted discovery EWAS (M_base^#; inflation factor λ=1.13) and d) additionally smoking adjusted (M_smok^¶; inflation factor λ=1.05), all participants. Decrease in numbers of signals after smoking adjustment. ^#: base model (M_base) EWAS was covariate adjusted for age, age squared, height, squared deviation from the mean of height, sex and interaction terms of age, age squared, height and squared deviation of height with sex, education (low, medium and high), body mass index, spirometer type, study centre, and cell composition. ^¶: smoking-adjusted model (M_smok): covariates applied for M_base and additionally smoking status and pack-years smoked.

**FIGURE 3**
a) Manhattan and b) quantile–quantile plots of the covariate-adjusted prediction^# epigenome-wide association study (EWAS) (M_base^¶) on forced expiratory volume in 1 s (FEV₁)/forced vital capacity (FVC), all participants. Meta-analysis of the prediction association was performed without genomic control (inflation factor λ=0.95). For analogous figure for associations with change in FEV₁ and FVC, see supplementary figure S4. ^#: predictive associations of DNA methylation at first time-point with change in lung function during follow-up. ^¶: base model (M_base) EWAS was covariate adjusted for age, age squared, height, FEV₁/FVC at time-point 1, squared deviation from the mean of height, sex and interaction terms of age, age squared, height and squared deviation of height with sex, education (low, medium and high), body mass index, spirometer type, study centre, and cell composition.

**FIGURE 4**
Forest plots of cohort-specific results and meta-analyses of the association of the mediation smoking index (Mediation-SI) with forced expiratory volume in 1 s (FEV₁)/forced vital capacity (FVC) and change in FEV₁/FVC in a, b) ever-smokers and c, d) never-smokers in the discovery cohorts: a, c) time-point 2 and b, d) prediction. Associations run applying base model adjustment (M_base^#). ^#: base model (M_base) epigenome-wide association study was covariate adjusted for age, age squared, height, squared deviation from the mean of height, sex and interaction terms of age, age squared, height and squared deviation of height with sex, education (low, medium and high), body mass index, spirometer type, study centre, and cell composition. Prediction models were additionally adjusted for FEV₁/FVC at time-point 1.

**FIGURE 5**
Distribution and association^# of a) mediation smoking index (Mediation-SI)^¶ and b) self-reported smoking history (pack-years) with forced expiratory volume in 1 s (FEV₁)/forced vital capacity (FVC) with 95% confidence intervals (shaded). Box plots of a) Mediation-SI (median (range) 0.3 (−1.7–5.2)) and b) pack-years (median (range) 2.0 (0–145.9)) in all participants of SAPALDIA are shown at the top of each panel. Red dotted lines indicate box plot interquartile range (IQR) borders. Whiskers indicate 1.5 IQR of the lower and upper quartile; outliers are indicated. For analogous figures for associations of Mediation-SI with FEV₁ and FVC, see supplementary figures S6 and S7, respectively. ^#: associations were adjusted for the base model (M_base): age, age squared, height, squared deviation from the mean of height, sex and interaction terms of age, age squared, height and squared deviation of height with sex, education (low, medium and high), body mass index, spirometer type, study centre, and cell composition. ^¶: Mediation-SI can be constructed for all participants irrespective of their smoking status. The M_base-adjusted model explained 17.5% of the variance in the outcome. The M_base-adjusted model additionally adjusted for the Mediation-SI explained 19.6% of the FEV₁/FVC variance (total adjusted R²=0.196) of which 2.8% of the variance was specifically explained by the Mediation-SI variable. This was comparable to the variance explained by the M_base-adjusted model additionally adjusted for pack-years and smoking status corresponding to the M_smok model (R²=0.198, and with 1.6% of the variance specifically explained by the pack-years variable). Model including both smoking adjustments (M_smok and additionally Mediation-SI) explained 20.1% of the FEV₁/FVC variance.

**FIGURE 6**
Distribution of adjusted mediation smoking index (Mediation-SI) in SAPALDIA at time-point 2. a) Smoking status: adjusted for age, sex and education. Never-smokers (n=395), ex-smokers (n=356) and current smokers (n=211). b) Years since quitting: adjusted for age, sex, education, pack-years and cigarettes per day. Ex-smokers (n=356). c) Pack-years: adjusted for age, sex, education and cigarettes per day. Current smokers (n=211). d) Cigarettes per day: adjusted for age, sex, education and pack-years. Current smokers (n=211). Data are presented as median with interquartile range (IQR) (boxes) and 1.5 IQR of the lower and upper quartile (whiskers); outliers are indicated.

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Comment in

Methylation, smoking, and reduced lung function.
London SJ. London SJ. Eur Respir J. 2019 Jul 4;54(1):1900920. doi: 10.1183/13993003.00920-2019. Print 2019 Jul. Eur Respir J. 2019. PMID: 31273037 Free PMC article. No abstract available.

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Epigenome-wide association study of lung function level and its change

Affiliations

Epigenome-wide association study of lung function level and its change

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Comment in

References

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Grants and funding

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Full Text Sources

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