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Metabolomics reveals a link between homocysteine and lipid metabolism and leukocyte telomere length: the ENGAGE consortium

  • Ashley van der Spek
  • , Linda Broer
  • , Harmen H M Draisma
  • , René Pool
  • , Eva Albrecht
  • , Marian Beekman
  • , Massimo Mangino
  • , Mait Raag
  • , Dale R Nyholt
  • , Harish K Dharuri
  • , Veryan Codd
  • , Najaf Amin
  • , Eco J C de Geus
  • , Joris Deelen
  • , Ayse Demirkan
  • , Idil Yet
  • , Krista Fischer
  • , Toomas Haller
  • , Anjali K Henders
  • , Aaron Isaacs
  • Sarah E Medland, Grant W Montgomery, Simon P Mooijaart, Konstantin Strauch, H Eka D Suchiman, Anika A M Vaarhorst, Diana van Heemst, Rui Wang-Sattler, John B Whitfield, Gonneke Willemsen, Margaret J Wright, Nicholas G Martin, Nilesh J Samani, Andres Metspalu, P Eline Slagboom, Tim D Spector, D.I. Boomsma, Cornelia M van Duijn, Christian Gieger

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Telomere shortening has been associated with multiple age-related diseases such as cardiovascular disease, diabetes, and dementia. However, the biological mechanisms responsible for these associations remain largely unknown. In order to gain insight into the metabolic processes driving the association of leukocyte telomere length (LTL) with age-related diseases, we investigated the association between LTL and serum metabolite levels in 7,853 individuals from seven independent cohorts. LTL was determined by quantitative polymerase chain reaction and the levels of 131 serum metabolites were measured with mass spectrometry in biological samples from the same blood draw. With partial correlation analysis, we identified six metabolites that were significantly associated with LTL after adjustment for multiple testing: lysophosphatidylcholine acyl C17:0 (lysoPC a C17:0, p-value = 7.1 × 10-6), methionine (p-value = 9.2 × 10-5), tyrosine (p-value = 2.1 × 10-4), phosphatidylcholine diacyl C32:1 (PC aa C32:1, p-value = 2.4 × 10-4), hydroxypropionylcarnitine (C3-OH, p-value = 2.6 × 10-4), and phosphatidylcholine acyl-alkyl C38:4 (PC ae C38:4, p-value = 9.0 × 10-4). Pathway analysis showed that the three phosphatidylcholines and methionine are involved in homocysteine metabolism and we found supporting evidence for an association of lipid metabolism with LTL. In conclusion, we found longer LTL associated with higher levels of lysoPC a C17:0 and PC ae C38:4, and with lower levels of methionine, tyrosine, PC aa C32:1, and C3-OH. These metabolites have been implicated in inflammation, oxidative stress, homocysteine metabolism, and in cardiovascular disease and diabetes, two major drivers of morbidity and mortality.

Original languageEnglish
Article number11623
Pages (from-to)11623
JournalScientific Reports
Volume9
Issue number1
DOIs
Publication statusPublished - 12 Aug 2019

Funding

ERF: The ERF study has received funding from the Centre for Medical Systems Biology (CMSB) and Netherlands Consortium for Systems Biology (NCSB), both within the framework of the Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO). ERF study is also a part of EUROSPAN (European Special Populations Research Network) (FP6 STRP grant number 018947 (LSHG-CT-2006-01947)); European Network of Genomic and Genetic Epidemiology (ENGAGE) from the European Community’s Seventh Framework Programme (FP7/2007-2013)/grant agreement HEALTH-F4-2007-201413; “Quality of Life and Management of the Living Resources” of 5th Framework Programme (no. QLG2-CT-2002-01254); FP7 project EUROHEADPAIN (nr 602633), the Internationale Stichting Alzheimer Onderzoek (ISAO); the Hersenstichting Nederland (HSN); and the JNPD under the project PERADES (grant number 733051021, Defining Genetic, Polygenic and Environmental Risk for Alzheimer’s Disease using multiple powerful cohorts, focused Epigenetics and Stem cell metabolomics). A first version of the manuscript has been published in the PhD thesis of Linda Broer “(Genetic) Epidemiology of Aging”112. We are grateful to all general practitioners for their contributions, to P. Veraart for her help in genealogy, J. Vergeer for the supervision of the laboratory work and P. Snijders for his help in data collection. NTR: We thank all participants in the Netherlands Twin Register. Research was funded by the Netherlands Organization for Scientific Research (NWO: MagW/ZonMW grants 904-61-090, 985-10-002,904-61-193,480-04-004, 400-05-717, Addiction-31160008 Middelgroot-911-09-032, Spinozapremie 56-464-14192), Center for Medical Systems Biology (CSMB, NWO Genomics), NBIC/BioAssist/RK(2008.024), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI –NL, 184.021.007), the VU University’s Institute for Health and Care Research (EMGO+), the European Community’s Seventh Framework Program (FP7/2007-2013), ENGAGE (HEALTH-F4-2007-201413) and the European Science Council (ERC - 230374 and ERC-284167). Harmen H.M. Draisma is funded by the Wellcome Trust (WT205915). KORA: KORA was financed by the Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany and supported by grants from the German Federal Ministry of Education and Research (BMBF). Part of this work was financed by the German National Genome Research Network (NGFN; NGFNPlus, project number 01GS0834) and supported within the Munich Center of Health Sciences (MC Health) as part of LMUinnovativ. Telomere assays were funded by the ENGAGE consortium. TwinsUK: The study was funded by the Wellcome Trust; European Community’s Seventh Framework Programme (FP7/2007–2013), ENGAGE project grant agreement (HEALTH-F4-2007-201413). The study also receives support from the Dept of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy’s & St Thomas’ NHS Foundation Trust in partnership with King’s College London. TDS is an NIHR senior Investigator and is holder of an ERC Advanced Principal Investigator award. Genotyping was performed by The Wellcome Trust Sanger Institute, support of the National Eye Institute via an NIH/CIDR genotyping project. EGCUT: EGCUT was supported by Estonian Research Council [IUT20-60, IUT24-6 and PUT1665 to K.F.]; European Union Horizon 2020 [692145 and European Union through the European Regional Development Fund [2014-2020.4.01.15-0012 GENTRANSMED]. We also thank all participants of the Estonian Biobank cohort. EGCUT studies were financed by University of Tartu (grant “Center of Translational Genomics”), by Estonian Goverment (grant #SF0180142s08, grant #ETF9353) and by European Commission through the European Regional Development Fund in the frame of grant “Centre of Excellence in Genomics” and Estonian Research Infrastructure’s Roadmap and through FP7 grant #313010. LLS: We thank all participants of the Leiden Longevity Study. The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007–2011) under grant agreement n° 259679. This study was supported by a grant from the Innovation-Oriented Research Program on Genomics (SenterNovem IGE05007), the Centre for Medical Systems Biology, Biobanking and Biomolecular Resources Research Infrastructure, (BBMRI-NL, 184.021.007) and the Netherlands Consortium for Healthy Ageing (grant 050-060-810), all in the framework of the Netherlands Genomics Initiative, Netherlands Organization for Scientific Research (NWO), and by Unilever Colworth. J. Deelen was financially supported by the Alexander von Humboldt Foundation. QIMR: We thank Marlene Grace and Ann Eldridge for twin recruitment and data collection, Lisa Bardsley for preparation of DNA samples, David Smyth for IT/database support, and the twins and their families for their participation. Data collection was supported by grants to NGM and MJW from the Australian Research Council and Australian National Health and Medical Research Council (NHMRC). Telomere length assessment was co-funded by the European Community’s Seventh Framework Programme (FP7/2007–2013), ENGAGE project, grant agreement HEALTH-F4-2007-201413 and NHMRC-European Union Collaborative Research Grant 496739. GWM and DRN were supported by the NHMRC Fellowship (619667) and ARC Future Fellowship (FT0991022) schemes, respectively.

FundersFunder number
Hersenstichting
Centre for Medical Systems Biology
VU University’s Institute for Health and Care Research
Münchner Zentrum für Gesundheitswissenschaften, Ludwig-Maximilians-Universität München
Biobanking and Biomolecular Resources Research Infrastructure
Internationale Stichting Alzheimer Onderzoek
National Institute for Health Research
Bundesministerium für Bildung und Forschung
European Special Populations Research Network
Tartu Ülikool
European Commission
Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München
Dept of Health
Netherlands Consortium for Systems Biology
National Eye Institute
German National Genome Research Network
Unilever Colworth
BBMRI
Wellcome Trust Sanger Institute
NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
Alexander von Humboldt-Stiftung
Horizon 2020
BBMRI-NL184.021.007
Nederlandse Organisatie voor Wetenschappelijk Onderzoek985-10-002,904-61-193,480-04-004, 904-61-090, 400-05-717
Seventh Framework ProgrammeFP7/2007-2013, 619667, HEALTH-F4-2007-201413
European Science CouncilERC - 230374, ERC-284167
Quality of Life and Management of the Living Resources” of 5th Framework ProgrammeQLG2-CT-2002-01254
Spinozapremie56-464-14192
Wellcome TrustWT205915, 205915
Horizon 2020 Framework Programme692145, 259679, 230374, 313010, 284167, 201413, 602633
ENGAGEHEALTH-F4-2007-201413
NBIC/BioAssist/RK2008.024
JNPD733051021
Netherlands Consortium for Healthy Ageing050-060-810
FP6 STRP018947, LSHG-CT-2006-01947
NGFN01GS0834
Australian Research CouncilFT0991022
Eesti TeadusagentuurIUT20-60, PUT1665, IUT24-6
Estonian Goverment0180142s08, #ETF9353
Innovation-Oriented Research Program on GenomicsIGE05007
European Regional Development Fund2014-2020.4.01.15-0012 GENTRANSMED
National Health and Medical Research Council496739

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Cohort Studies

    • Netherlands Twin Register (NTR)

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