Epigenetic prediction of complex traits and death

Daniel L. McCartney; Robert Hillary; Anna J. Stevenson; Stuart J. Ritchie; Rosie M. Walker; Qian Zhang; Stewart W. Morris; Mairead L. Bermingham; Archie Campbell; Alison D. Murray; Heather C. Whalley; Catharine R. Gale; David J. Porteous; Chris S. Haley; Allan F. McRae; Naomi R. Wray; Peter M. Visscher; Andrew M. McIntosh; Kathryn L. Evans; Ian J. Deary; Riccardo E. Marioni

doi:10.1186/s13059-018-1514-1

Epigenetic prediction of complex traits and death

Daniel L. McCartney, Robert Hillary, Anna J. Stevenson, Stuart J. Ritchie, Rosie M. Walker, Qian Zhang, Stewart W. Morris, Mairead L. Bermingham, Archie Campbell, Alison D. Murray, Heather C. Whalley, Catharine R. Gale, David J. Porteous, Chris S. Haley, Allan F. McRae, Naomi R. Wray, Peter M. Visscher, Andrew M. McIntosh, Kathryn L. Evans, Ian J. DearyRiccardo E. Marioni

Research output: Contribution to journal › Article › peer-review

Abstract

Background
Genome-wide DNA methylation (DNAm) profiling has allowed for the development of molecular predictors for a multitude of traits and diseases. Such predictors may be more accurate than the self-reported phenotypes and could have clinical applications.

Results
Here, penalized regression models are used to develop DNAm predictors for ten modifiable health and lifestyle factors in a cohort of 5087 individuals. Using an independent test cohort comprising 895 individuals, the proportion of phenotypic variance explained in each trait is examined for DNAm-based and genetic predictors. Receiver operator characteristic curves are generated to investigate the predictive performance of DNAm-based predictors, using dichotomized phenotypes. The relationship between DNAm scores and all-cause mortality (n = 212 events) is assessed via Cox proportional hazards models. DNAm predictors for smoking, alcohol, education, and waist-to-hip ratio are shown to predict mortality in multivariate models. The predictors show moderate discrimination of obesity, alcohol consumption, and HDL cholesterol. There is excellent discrimination of current smoking status, poorer discrimination of college-educated individuals and those with high total cholesterol, LDL with remnant cholesterol, and total:HDL cholesterol ratios.

Conclusions
DNAm predictors correlate with lifestyle factors that are associated with health and mortality. They may supplement DNAm-based predictors of age to identify the lifestyle profiles of individuals and predict disease risk.

Original language	English
Article number	136
Journal	Genome Biology
Volume	19
DOIs	https://doi.org/10.1186/s13059-018-1514-1
Publication status	Published - 27 Sept 2018

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10.1186/s13059-018-1514-1Licence: Creative Commons: Attribution (CC-BY)

Epigenetic prediction of complex traitsFinal published version, 856 KBLicence: Creative Commons: Attribution (CC-BY)
2018-08-17 GB Accepted Manuscript

5 Finished

Brain imaging and cognitive ageing in the Lothian Birth Cohort 1936: III
Wardlaw, J. (Principal Investigator), Bastin, M. (Co-investigator) & Deary, I. (Co-investigator)
MRC
1/05/15 → 30/04/19
Project: Research
Stratifying Resilience and Depression Longitudinally
McIntosh, A. (Principal Investigator), Deary, I. (Co-investigator), Evans, K. (Co-investigator), Haley, C. (Co-investigator) & Porteous, D. (Co-investigator)
UK-based charities
1/01/15 → 30/06/21
Project: Research
RA2661 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2. Main Budget.
Deary, I. (Principal Investigator), Gale, C. (Co-investigator), Holmes, M. (Co-investigator), Logie, P. (Co-investigator), Maclullich, A. (Co-investigator), Porteous, D. (Co-investigator), Seckl, J. (Co-investigator), Starr, J. (Co-investigator), Wardlaw, J. (Co-investigator) & Okely, J. (Researcher)
1/09/13 → 31/08/19
Project: Research

1 Doctoral Thesis

A multi–omics approach to understand the role of plasma proteins in cognitive ageing and dementia
Hillary, R., 2021
Research output: Thesis › Doctoral Thesis

Riccardo Marioni
- Centre for Genomic and Experimental Medicine
- Edinburgh Neuroscience
- School of Genetics and Cancer - Personal Chair of Molecular Epidemiology of Ageing
Person: Academic: Research Active

Cite this

McCartney, D. L., Hillary, R., Stevenson, A. J., Ritchie, S. J., Walker, R. M., Zhang, Q., Morris, S. W., Bermingham, M. L., Campbell, A., Murray, A. D., Whalley, H. C., Gale, C. R., Porteous, D. J., Haley, C. S., McRae, A. F., Wray, N. R., Visscher, P. M., McIntosh, A. M., Evans, K. L., ... Marioni, R. E. (2018). Epigenetic prediction of complex traits and death. Genome Biology, 19, Article 136. https://doi.org/10.1186/s13059-018-1514-1

@article{505ee09c59ab457d87c2b81ea85d6450,

title = "Epigenetic prediction of complex traits and death",

abstract = "BackgroundGenome-wide DNA methylation (DNAm) profiling has allowed for the development of molecular predictors for a multitude of traits and diseases. Such predictors may be more accurate than the self-reported phenotypes and could have clinical applications.ResultsHere, penalized regression models are used to develop DNAm predictors for ten modifiable health and lifestyle factors in a cohort of 5087 individuals. Using an independent test cohort comprising 895 individuals, the proportion of phenotypic variance explained in each trait is examined for DNAm-based and genetic predictors. Receiver operator characteristic curves are generated to investigate the predictive performance of DNAm-based predictors, using dichotomized phenotypes. The relationship between DNAm scores and all-cause mortality (n = 212 events) is assessed via Cox proportional hazards models. DNAm predictors for smoking, alcohol, education, and waist-to-hip ratio are shown to predict mortality in multivariate models. The predictors show moderate discrimination of obesity, alcohol consumption, and HDL cholesterol. There is excellent discrimination of current smoking status, poorer discrimination of college-educated individuals and those with high total cholesterol, LDL with remnant cholesterol, and total:HDL cholesterol ratios.ConclusionsDNAm predictors correlate with lifestyle factors that are associated with health and mortality. They may supplement DNAm-based predictors of age to identify the lifestyle profiles of individuals and predict disease risk.",

author = "McCartney, {Daniel L.} and Robert Hillary and Stevenson, {Anna J.} and Ritchie, {Stuart J.} and Walker, {Rosie M.} and Qian Zhang and Morris, {Stewart W.} and Bermingham, {Mairead L.} and Archie Campbell and Murray, {Alison D.} and Whalley, {Heather C.} and Gale, {Catharine R.} and Porteous, {David J.} and Haley, {Chris S.} and McRae, {Allan F.} and Wray, {Naomi R.} and Visscher, {Peter M.} and McIntosh, {Andrew M.} and Evans, {Kathryn L.} and Deary, {Ian J.} and Marioni, {Riccardo E.}",

year = "2018",

month = sep,

day = "27",

doi = "10.1186/s13059-018-1514-1",

language = "English",

volume = "19",

journal = "Genome Biology",

issn = "1465-6906",

publisher = "BioMed Central",

}

McCartney, DL , Hillary, R, Stevenson, AJ, Ritchie, SJ, Walker, RM, Zhang, Q, Morris, SW, Bermingham, ML, Campbell, A, Murray, AD, Whalley, HC, Gale, CR, Porteous, DJ, Haley, CS, McRae, AF, Wray, NR, Visscher, PM, McIntosh, AM , Evans, KL , Deary, IJ & Marioni, RE 2018, 'Epigenetic prediction of complex traits and death', Genome Biology, vol. 19, 136. https://doi.org/10.1186/s13059-018-1514-1

TY - JOUR

T1 - Epigenetic prediction of complex traits and death

AU - McCartney, Daniel L.

AU - Hillary, Robert

AU - Stevenson, Anna J.

AU - Ritchie, Stuart J.

AU - Walker, Rosie M.

AU - Zhang, Qian

AU - Morris, Stewart W.

AU - Bermingham, Mairead L.

AU - Campbell, Archie

AU - Murray, Alison D.

AU - Whalley, Heather C.

AU - Gale, Catharine R.

AU - Porteous, David J.

AU - Haley, Chris S.

AU - McRae, Allan F.

AU - Wray, Naomi R.

AU - Visscher, Peter M.

AU - McIntosh, Andrew M.

AU - Evans, Kathryn L.

AU - Deary, Ian J.

AU - Marioni, Riccardo E.

PY - 2018/9/27

Y1 - 2018/9/27

N2 - BackgroundGenome-wide DNA methylation (DNAm) profiling has allowed for the development of molecular predictors for a multitude of traits and diseases. Such predictors may be more accurate than the self-reported phenotypes and could have clinical applications.ResultsHere, penalized regression models are used to develop DNAm predictors for ten modifiable health and lifestyle factors in a cohort of 5087 individuals. Using an independent test cohort comprising 895 individuals, the proportion of phenotypic variance explained in each trait is examined for DNAm-based and genetic predictors. Receiver operator characteristic curves are generated to investigate the predictive performance of DNAm-based predictors, using dichotomized phenotypes. The relationship between DNAm scores and all-cause mortality (n = 212 events) is assessed via Cox proportional hazards models. DNAm predictors for smoking, alcohol, education, and waist-to-hip ratio are shown to predict mortality in multivariate models. The predictors show moderate discrimination of obesity, alcohol consumption, and HDL cholesterol. There is excellent discrimination of current smoking status, poorer discrimination of college-educated individuals and those with high total cholesterol, LDL with remnant cholesterol, and total:HDL cholesterol ratios.ConclusionsDNAm predictors correlate with lifestyle factors that are associated with health and mortality. They may supplement DNAm-based predictors of age to identify the lifestyle profiles of individuals and predict disease risk.

AB - BackgroundGenome-wide DNA methylation (DNAm) profiling has allowed for the development of molecular predictors for a multitude of traits and diseases. Such predictors may be more accurate than the self-reported phenotypes and could have clinical applications.ResultsHere, penalized regression models are used to develop DNAm predictors for ten modifiable health and lifestyle factors in a cohort of 5087 individuals. Using an independent test cohort comprising 895 individuals, the proportion of phenotypic variance explained in each trait is examined for DNAm-based and genetic predictors. Receiver operator characteristic curves are generated to investigate the predictive performance of DNAm-based predictors, using dichotomized phenotypes. The relationship between DNAm scores and all-cause mortality (n = 212 events) is assessed via Cox proportional hazards models. DNAm predictors for smoking, alcohol, education, and waist-to-hip ratio are shown to predict mortality in multivariate models. The predictors show moderate discrimination of obesity, alcohol consumption, and HDL cholesterol. There is excellent discrimination of current smoking status, poorer discrimination of college-educated individuals and those with high total cholesterol, LDL with remnant cholesterol, and total:HDL cholesterol ratios.ConclusionsDNAm predictors correlate with lifestyle factors that are associated with health and mortality. They may supplement DNAm-based predictors of age to identify the lifestyle profiles of individuals and predict disease risk.

U2 - 10.1186/s13059-018-1514-1

DO - 10.1186/s13059-018-1514-1

M3 - Article

SN - 1465-6906

VL - 19

JO - Genome Biology

JF - Genome Biology

M1 - 136

ER -

Epigenetic prediction of complex traits and death

Abstract

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Projects

Brain imaging and cognitive ageing in the Lothian Birth Cohort 1936: III

Stratifying Resilience and Depression Longitudinally

RA2661 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2. Main Budget.

Research output

A multi–omics approach to understand the role of plasma proteins in cognitive ageing and dementia

Profiles

Riccardo Marioni

Cite this