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Determinants of accelerated metabolomic and epigenetic aging in a UK cohort |
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| Author: | Robinson, Oliver1; Chadeau Hyam, Marc1; Karaman, Ibrahim1; |
| Organizations: |
1MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK 2Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland 3NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
4Laboratory of Biostatistics, Department of Biomedical Sciences, University of Sassari, Sassari, Italy
5Italian Institute for Genomic Medicine (IIGM, former HuGeF), Candiolo, Italy 6Center for Life Course Health Research, Faculty of Medicine, University of Oulu and Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland 7Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Uxbridge, UK 8National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK |
| Format: | article |
| Version: | published version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 1.1 MB) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe2020091069236 |
| Language: | English |
| Published: |
John Wiley & Sons,
2020
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| Publish Date: | 2020-09-10 |
| Description: |
AbstractMarkers of biological aging have potential utility in primary care and public health. We developed a model of age based on untargeted metabolic profiling across multiple platforms, including nuclear magnetic resonance spectroscopy and liquid chromatography–mass spectrometry in urine and serum, within a large sample (N = 2,239) from the UK Airwave cohort. We validated a subset of model predictors in a Finnish cohort including repeat measurements from 2,144 individuals. We investigated the determinants of accelerated aging, including lifestyle and psychological risk factors for premature mortality. The metabolomic age model was well correlated with chronological age (mean r = 0.86 across independent test sets). Increased metabolomic age acceleration (mAA) was associated after false discovery rate (FDR) correction with overweight/obesity, diabetes, heavy alcohol use and depression. DNA methylation age acceleration measures were uncorrelated with mAA. Increased DNA methylation phenotypic age acceleration (N = 1,110) was associated after FDR correction with heavy alcohol use, hypertension and low income. In conclusion, metabolomics is a promising approach for the assessment of biological age and appears complementary to established epigenetic clocks. see all
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| Series: |
Aging cell |
| ISSN: | 1474-9718 |
| ISSN-E: | 1474-9728 |
| ISSN-L: | 1474-9718 |
| Volume: | 19 |
| Issue: | 6 |
| Article number: | e13149 |
| DOI: | 10.1111/acel.13149 |
| OADOI: | https://oadoi.org/10.1111/acel.13149 |
| Type of Publication: |
A1 Journal article – refereed |
| Field of Science: |
3121 General medicine, internal medicine and other clinical medicine |
| Subjects: | |
| Funding: |
OR was supported by an MRC Early Career Fellowship and a UKRI Future Leaders Fellowship. This study was partly supported by the European Commission grant to the LIFEPATH project (Horizon 2020 grant number 633666) and DynaHEALTH (Horizon 2020 grant number 633595). The Airwave Health Monitoring Study is funded by the Home Office (grant number 780‐TETRA) with additional support from the National Institute for Health Research (NIHR) Biomedical Research Centre. The Airwave Study uses the computing resources of the UK MEDical BIOinformatics Partnership (UK MED‐BIO: supported by the Medical Research Council MR/L01632X/1). This work was supported by the Medical Research Council and National Institute for Health Research [grant number MC_PC_12025] and infrastructure support was provided by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (BRC). We thank all Airwave participants for their contributions. We thank the late professor Paula Rantakallio (launch of NFBC1966), the NFBC participants in the 31/46 years studies and the NFBC project centre. NFBC1966 received financial support from Academy of Finland (EGEA, grant no. 285547), University of Oulu Grants no. 24000692, 65354, Oulu University Hospital Grants no.2/97,8/97, 24301140, ERDF European Regional Development Fund Grant no. 539/2010 A31592, EU H2020 LifeCycle Action (grant no 733206), EU‐H2020 EDCMET (grant no. 825762) and EUCAN Connect (grant no 824989) , the Medical Research Council, UK (grants no. MR/M013138/1, MRC/BBSRC MR/S03658X/1 (JPI HDHL)). I.K. acknowledges support from the EU PhenoMeNal project (Horizon 2020, 654241). MAK was supported by a research grant from the Sigrid Juselius Foundation, Finland. |
| EU Grant Number: |
(633595) DYNAHEALTH - Understanding the dynamic determinants of glucose homeostasis and social capability to promote Healthy and active aging (733206) LIFECYCLE - Early-life stressors and LifeCycle health (825762) EDCMET - Metabolic effects of Endocrine Disrupting Chemicals: novel testing METhods and adverse outcome pathways (824989) EUCAN-Connect - A federated FAIR platform enabling large-scale analysis of high-value cohort data connecting Europe and Canada in personalized health |
| Academy of Finland Grant Number: |
285547 |
| Detailed Information: |
285547 (Academy of Finland Funding decision) |
| Copyright information: |
© 2020 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
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https://creativecommons.org/licenses/by/4.0/ |