DNAm scores for serum GDF15 and NT-proBNP levels associate with a range of traits affecting the body and brain.
Humans
Growth Differentiation Factor 15
/ blood
Natriuretic Peptide, Brain
/ blood
Peptide Fragments
/ blood
Male
Female
Aged
Middle Aged
Diabetes Mellitus, Type 2
/ blood
DNA Methylation
/ genetics
Biomarkers
/ blood
Scotland
Dementia
/ blood
Epigenesis, Genetic
Ischemic Stroke
/ blood
Bayes Theorem
Cohort Studies
Brain
Cardiovascular
DNA methylation
Dementia
Diabetes
Epigenetic
GDF15
NT-proBNP
Risk stratification
Stroke
Journal
Clinical epigenetics
ISSN: 1868-7083
Titre abrégé: Clin Epigenetics
Pays: Germany
ID NLM: 101516977
Informations de publication
Date de publication:
10 Sep 2024
10 Sep 2024
Historique:
received:
18
10
2023
accepted:
23
08
2024
medline:
11
9
2024
pubmed:
11
9
2024
entrez:
10
9
2024
Statut:
epublish
Résumé
Plasma growth differentiation factor 15 (GDF15) and N-terminal proB-type natriuretic peptide (NT-proBNP) are cardiovascular biomarkers that associate with a range of diseases. Epigenetic scores (EpiScores) for GDF15 and NT-proBNP may provide new routes for risk stratification. In the Generation Scotland cohort (N ≥ 16,963), GDF15 levels were associated with incident dementia, ischaemic stroke and type 2 diabetes, whereas NT-proBNP levels were associated with incident ischaemic heart disease, ischaemic stroke and type 2 diabetes (all P EpiScores for serum levels of GDF15 and Nt-proBNP associate with body and brain health traits. These EpiScores are provided as potential tools for disease risk stratification.
Sections du résumé
BACKGROUND
BACKGROUND
Plasma growth differentiation factor 15 (GDF15) and N-terminal proB-type natriuretic peptide (NT-proBNP) are cardiovascular biomarkers that associate with a range of diseases. Epigenetic scores (EpiScores) for GDF15 and NT-proBNP may provide new routes for risk stratification.
RESULTS
RESULTS
In the Generation Scotland cohort (N ≥ 16,963), GDF15 levels were associated with incident dementia, ischaemic stroke and type 2 diabetes, whereas NT-proBNP levels were associated with incident ischaemic heart disease, ischaemic stroke and type 2 diabetes (all P
CONCLUSIONS
CONCLUSIONS
EpiScores for serum levels of GDF15 and Nt-proBNP associate with body and brain health traits. These EpiScores are provided as potential tools for disease risk stratification.
Identifiants
pubmed: 39256775
doi: 10.1186/s13148-024-01734-7
pii: 10.1186/s13148-024-01734-7
doi:
Substances chimiques
Growth Differentiation Factor 15
0
Natriuretic Peptide, Brain
114471-18-0
pro-brain natriuretic peptide (1-76)
0
Peptide Fragments
0
GDF15 protein, human
0
Biomarkers
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
124Subventions
Organisme : Wellcome Trust
ID : 108890/Z/15/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 218493/Z/19/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 104036/Z/14/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 104036/Z/14/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 104036/Z/14/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 221890/Z/20/Z
Pays : United Kingdom
Organisme : British Heart Foundation Intermediate Basic Science Research Fellowship
ID : FS/IBSRF/23/25161
Organisme : Alzheimer's Society
ID : AS-PG-19b-010
Pays : United Kingdom
Organisme : Alzheimer's Society
ID : AS-PG-19b-010
Pays : United Kingdom
Organisme : Scottish funding council
ID : HR03006
Organisme : Scottish funding council
ID : HR03006
Organisme : Scottish funding council
ID : HR03006
Organisme : Chief Scientist Office of the Scottish Government Health Directorate
ID : CZD/16/6
Organisme : Chief Scientist Office of the Scottish Government Health Directorate
ID : CZD/16/6
Organisme : Chief Scientist Office of the Scottish Government Health Directorate
ID : CZD/16/6
Organisme : UK Dementia Research Institute Ltd which is funded by the Medical Research Council, Alzheimer's Society and Alzheimer's Research UK Institute
ID : award no. UKDRI - Edin002, DRIEdi17/18, and MRC MC_PC_17113
Organisme : Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society
ID : 221890/Z/20/Z
Informations de copyright
© 2024. The Author(s).
Références
Hageman SHJ, McKay AJ, Ueda P, Gunn LH, Jernberg T, Hagström E, et al. Estimation of recurrent atherosclerotic cardiovascular event risk in patients with established cardiovascular disease: the updated SMART2 algorithm. Eur Heart J. 2022;43(18):1715–27.
doi: 10.1093/eurheartj/ehac056
pubmed: 35165703
pmcid: 9312860
SCORE2 working group and ESC Cardiovascular risk collaboration. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. Eur Heart J. 2021;42(25):2439–54.
Pence BD. Growth differentiation factor-15 in immunity and aging. Front Aging. 2022;0:8.
Wang Z, Yang F, Ma M, Bao Q, Shen J, Ye F, et al. The impact of growth differentiation factor 15 on the risk of cardiovascular diseases: two-sample Mendelian randomization study. BMC Cardiovasc Disord. 2020;20(1):1–7.
doi: 10.1186/s12872-020-01744-2
Tanaka T, Basisty N, Fantoni G, Candia J, Moore AZ, Biancotto A, et al. Plasma proteomic biomarker signature of age predicts health and life span. eLife. 2020;9:1–24.
Gadd DA, Hillary RF, Kuncheva Z, Mangelis T, Cheng Y, Dissanayake M, et al. Blood protein assessment of leading incident diseases and mortality in the UK Biobank. Nature Aging. 2024;4:39–948.
doi: 10.1038/s43587-024-00655-7
Shrivastava A, Haase T, Zeller T, Schulte C. Biomarkers for heart failure prognosis: proteins, genetic scores and non-coding RNAs. Front Cardiovasc Med. 2020;7:252.
doi: 10.3389/fcvm.2020.601364
Birukov A, Eichelmann F, Kuxhaus O, Polemiti E, Fritsche A, Wirth J, et al. Opposing associations of NT-proBNP with risks of diabetes and diabetes-related complications. Diabetes Care. 2020;43(12):2930–7.
doi: 10.2337/dc20-0553
pubmed: 32816995
pmcid: 7770272
Noveanu M, Breidthardt T, Potocki M, Reichlin T, Twerenbold R, Uthoff H, et al. Direct comparison of serial B-type natriuretic peptide and NT-proBNP levels for prediction of short- and long-term outcome in acute decompensated heart failure. Crit Care. 2011;15(1):1–15.
doi: 10.1186/cc9398
Myhre PL, Vaduganathan M, Claggett B, Packer M, Desai AS, Rouleau JL, et al. B-type natriuretic peptide during treatment with sacubitril/valsartan: the PARADIGM-HF trial. J Am Coll Cardiol. 2019;73(11):1264–72.
doi: 10.1016/j.jacc.2019.01.018
pubmed: 30846338
pmcid: 7955687
Zile MR, Claggett BL, Prescott MF, McMurray JJV, Packer M, Rouleau JL, et al. Prognostic implications of changes in N-terminal pro-B-type natriuretic peptide in patients with heart failure. J Am Coll Cardiol. 2016;68(22):2425–36.
doi: 10.1016/j.jacc.2016.09.931
pubmed: 27908347
Myhre PL, Prebensen C, Strand H, Røysland R, Jonassen CM, Rangberg A, et al. Growth differentiation factor 15 provides prognostic information superior to established cardiovascular and inflammatory biomarkers in unselected patients hospitalized With COVID-19. Circulation. 2020;142(22):2128.
doi: 10.1161/CIRCULATIONAHA.120.050360
pubmed: 33058695
pmcid: 7688084
Gao L, Jiang D, Wen XS, Cheng XC, Sun M, He B, et al. Prognostic value of NT-proBNP in patients with severe COVID-19. Respir Res. 2020;21(1):1–7.
doi: 10.1186/s12931-020-01352-w
McGrath ER, Himali JJ, Levy D, Conner SC, Decarli C, Pase MP, et al. Growth differentiation factor 15 and NT-proBNP as blood-based markers of vascular brain injury and dementia. J Am Heart Assoc. 2020 Oct 6 [cited 2021 Nov 24];9(19). Available from: https://pubmed.ncbi.nlm.nih.gov/32921207/
Walker KA, Chen J, Zhang J, Fornage M, Yang Y, Zhou L, et al. Large-scale plasma proteomic analysis identifies proteins and pathways associated with dementia risk. Nat Aging. 2021;1(5):473–89.
doi: 10.1038/s43587-021-00064-0
pubmed: 37118015
pmcid: 10154040
Gadd DA, Hillary RF, McCartney DL, Zaghlool SB, Stevenson AJ, Nangle C, et al. Epigenetic scores for the circulating proteome as tools for disease prediction. bioRxiv. 2021;8(5):2020.12.01.404681.
Cheng Y, Gadd DA, Gieger C, Monterrubio-Gómez K, Zhang Y, Berta I, et al. DNA Methylation scores augment 10-year risk prediction of diabetes. medRxiv. 2021;2021.11.19.21266469.
Chybowska AD, Gadd DA, Cheng Y, Bernabeu E, Campbell A, Walker RM, et al. Augmenting clinical risk prediction of cardiovascular disease through protein and epigenetic biomarkers. medRxiv; 2022 [cited 2023 Jan 5]. p. 2022.10.21.22281355. https://doi.org/10.1101/2022.10.21.22281355v1
Stevenson AJ, Gadd DA, Hillary RF, Mccartney DL, Campbell A, Walker RM, et al. Creating and validating a DNA methylation-based proxy for interleukin-6. [cited 2021 Mar 9]; https://doi.org/10.1093/gerona/glab046/6141415
Zaghlool SB, Kühnel B, Elhadad MA, Kader S, Halama A, Thareja G, et al. Epigenetics meets proteomics in an epigenome-wide association study with circulating blood plasma protein traits. Nat Commun. 2020;11(1):15.
doi: 10.1038/s41467-019-13831-w
pubmed: 31900413
pmcid: 6941977
Conole ELS, Stevenson AJ, Maniega SM, Harris SE, Green C, Valdés Hernández MDC, et al. DNA methylation and protein markers of chronic inflammation and their associations with brain and cognitive aging. Neurology. 2021;97(23):e2340–52.
doi: 10.1212/WNL.0000000000012997
pubmed: 34789543
pmcid: 8665430
Stevenson AJ, McCartney DL, Hillary RF, Campbell A, Morris SW, Bermingham ML, et al. Characterisation of an inflammation-related epigenetic score and its association with cognitive ability. Clin Epigenetics. 2020;27(12):113.
doi: 10.1186/s13148-020-00903-8
Gadd DA, Hillary RF, McCartney DL, Zaghlool SB, Stevenson AJ, Cheng Y, et al. Epigenetic scores for the circulating proteome as tools for disease prediction. eLife. 2022;11.
Corley J, Cox SR, Harris SE, Hernandez MV, Maniega SM, Bastin ME, et al. Epigenetic signatures of smoking associate with cognitive function, brain structure, and mental and physical health outcomes in the Lothian Birth Cohort 1936. Transl Psychiatry. 2019;9(1).
Bernabeu E, Chybowska AD, Kresovich JK, Suderman M, McCartney DL, Hillary RF, et al. Blood-based DNA methylation study of alcohol consumption. medRxiv; 2024 [cited 2024 Jul 18]. p. 2024.02.26.24303397. https://doi.org/10.1101/2024.02.26.24303397v1
Hamilton OKL, Zhang Q, McRae AF, Walker RM, Morris SW, Redmond P, et al. An epigenetic score for BMI based on DNA methylation correlates with poor physical health and major disease in the Lothian Birth Cohort. Int J Obes 2005. 2019;43(9):1795–802.
Lu AT, Quach A, Wilson JG, Reiner AP, Aviv A, Raj K, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging. 2019;11(2):303–27.
doi: 10.18632/aging.101684
pubmed: 30669119
pmcid: 6366976
Hillary RF, Stevenson AJ, McCartney DL, Campbell A, Walker RM, Howard DM, et al. Epigenetic clocks predict prevalence and incidence of leading causes of death and disease burden. Clin Epigenet. 2020;12(115).
Smith BH, Campbell A, Linksted P, Fitzpatrick B, Jackson C, Kerr SM, et al. Cohort profile: generation scotland: scottish family health study (GS: SFHS). The study, its participants and their potential for genetic research on health and illness. Int J Epidemiol. 2013;42(3):689–700.
Smith BH, Campbell H, Blackwood D, Connell J, Connor M, Deary IJ, et al. Generation Scotland: the Scottish family health study; a new resource for researching genes and heritability. BMC Med Genet. 2006;7:74.
doi: 10.1186/1471-2350-7-74
pubmed: 17014726
pmcid: 1592477
Taylor AM, Pattie A, Deary IJ. Cohort profile update: the Lothian birth cohorts of 1921 and 1936. Int J Epidemiol. 2018;47(4):1042r.
doi: 10.1093/ije/dyy022
Deary IJ, Gow AJ, Pattie A, Starr JM. Cohort profile: the lothian birth cohorts of 1921 and 1936. Int J Epidemiol. 2012;41(6):1576–84.
doi: 10.1093/ije/dyr197
pubmed: 22253310
Trejo Banos D, McCartney DL, Patxot M, Anchieri L, Battram T, Christiansen C, et al. Bayesian reassessment of the epigenetic architecture of complex traits. Nat Commun. 2020;11.
Gadd DA, Hillary RF, McCartney DL, Shi L, Stolicyn A, Robertson N, et al. Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health. Zenodo [Internet]. 2022 Jul 6 [cited 2022 Jul 6]; Available from: https://zenodo.org/record/6801458
Hillary RF, Trejo-Banos D, Kousathanas A, McCartney DL, Harris SE, Stevenson AJ, et al. Multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults. Genome Med. 2020;8(12):60.
doi: 10.1186/s13073-020-00754-1
Hillary RF, McCartney DL, Harris SE, Stevenson AJ, Seeboth A, Zhang Q, et al. Genome and epigenome wide studies of neurological protein biomarkers in the Lothian Birth Cohort 1936. Nat Commun. 2019;10(1):3160.
doi: 10.1038/s41467-019-11177-x
pubmed: 31320639
pmcid: 6639385
Gadd DA, Hillary RF, McCartney DL, Shi L, Stolicyn A, Robertson NA, et al. Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health. Nat Commun. 2022;13(1):4670.
doi: 10.1038/s41467-022-32319-8
pubmed: 35945220
pmcid: 9363452
Zannas AS, Wiechmann T, Gassen NC, Binder EB. Gene–Stress–Epigenetic regulation of FKBP5: clinical and translational implications. Neuropsychopharmacology. 2016;41(1):261–74.
doi: 10.1038/npp.2015.235
pubmed: 26250598
Smyth LJ, Kilner J, Nair V, Liu H, Brennan E, Kerr K, et al. Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease: an exploratory study. Clin Epigenetics. 2021;13(1):99.
doi: 10.1186/s13148-021-01081-x
pubmed: 33933144
pmcid: 8088646
Rawshani A, Kjölhede EA, Rawshani A, Sattar N, Eeg-Olofsson K, Adiels M, et al. Severe COVID-19 in people with type 1 and type 2 diabetes in Sweden: a nationwide retrospective cohort study. Lancet Reg Health – Eur [Internet]. 2021 May 1 [cited 2023 Aug 20];4. Available from: https://www.thelancet.com/journals/lanepe/article/PIIS2666-7762(21)00082-X/fulltext
Ortega E, Corcoy R, Gratacòs M, Claramunt FXC, Mata-Cases M, Puig-Treserra R, et al. Risk factors for severe outcomes in people with diabetes hospitalised for COVID-19: a cross-sectional database study. BMJ Open. 2021;11(7):e051237.
doi: 10.1136/bmjopen-2021-051237
pubmed: 34301668
Hillary RF, Ng HK, McCartney DL, Elliott HR, Walker RM, Campbell A, et al. Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts. Cell Genomics. 2024;4(5):100544.
doi: 10.1016/j.xgen.2024.100544
pubmed: 38692281
pmcid: 11099341
Pietzner M, Wheeler E, Carrasco-Zanini J, Kerrison ND, Oerton E, Koprulu M, et al. Synergistic insights into human health from aptamer- and antibody-based proteomic profiling. Nat Commun. 2021;12(1):1–13.
doi: 10.1038/s41467-021-27164-0
Wilkinson T, Schnier C, Bush K, Rannikmäe K, Henshall DE, Lerpiniere C, et al. Identifying dementia outcomes in UK Biobank: a validation study of primary care, hospital admissions and mortality data. Eur J Epidemiol. 2019;34(6):557–65.
doi: 10.1007/s10654-019-00499-1
pubmed: 30806901
pmcid: 6497624
Mullin DS, Stirland LE, Buchanan E, Convery CA, Cox SR, Deary IJ, et al. Identifying dementia using medical data linkage in a longitudinal cohort study: Lothian Birth Cohort 1936. BMC Psychiatry. 2023;1(23):303.
doi: 10.1186/s12888-023-04797-7
Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinform. 2012;13:86.
doi: 10.1186/1471-2105-13-86
R. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/ . Accessed April 2021. 2020.
Loh PR, Kichaev G, Gazal S, Schoech AP, Price AL. Mixed model association for biobank-scale data sets. Nat Genet. 2018;50(7):906–8.
doi: 10.1038/s41588-018-0144-6
pubmed: 29892013
pmcid: 6309610
Yang J, Ferreira T, Morris AP, Medland SE, Madden PAF, Heath AC, et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat Genet. 2012;44(4):369–75.
doi: 10.1038/ng.2213
pubmed: 22426310
pmcid: 3593158
Euesden J, Lewis CM, O’Reilly PF. PRSice: polygenic risk score software. Bioinformatics. 2015;31(9):1466–8.
doi: 10.1093/bioinformatics/btu848
pubmed: 25550326
Therneau TM. coxme: Mixed Effects Cox Models. R package version 2.2–16. https://CRAN.R-project.org/package=coxme . Accessed April 2021. 2020;
GovScot. Scottish Government. The Scottish Index of Multiple Deprivation (SIMD); 1–20. (2016). Available from: http://www.gov.scot/ Resource/0050/00504809.pdf. Accessed April 2021. 2016.
Bollepalli S, Korhonen T, Kaprio J, Anders S, Ollikainen M. EpiSmokEr: a robust classifier to determine smoking status from DNA methylation data. Epigenomics. 2019;11(13):1469–86.
doi: 10.2217/epi-2019-0206
pubmed: 31466478
Therneau TM. A Package for Survival Analysis in R. R package version 3.2–7, https://CRAN.R-project.org/package=survival . Accessed April 2021. 2020;
Fawns-Ritchie C, Altschul DM, Campbell A, Huggins C, Nangle C, Dawson R, et al. CovidLife: a resource to understand mental health, well-being and behaviour during the COVID-19 pandemic in the UK. Wellcome Open Res 2021 6176. 2021;6:176.
GovScot Scottish Government. Scottish Index of Multiple Deprivation 2006: Technical Report. Available at: https://www.gov.scot/publications/scottish-index-multiple-deprivation-2006-technical-report/ . Accessed August 2023.