Evaluation of cross-platform compatibility of a DNA methylation-based glucocorticoid response biomarker.
450K versus 850K
Algorithmic biomarker
Cord blood
DNA methylation
Dexamethasone
Glucocorticoid
Whole blood
Journal
Clinical epigenetics
ISSN: 1868-7083
Titre abrégé: Clin Epigenetics
Pays: Germany
ID NLM: 101516977
Informations de publication
Date de publication:
28 10 2022
28 10 2022
Historique:
received:
02
06
2022
accepted:
11
10
2022
entrez:
29
10
2022
pubmed:
30
10
2022
medline:
2
11
2022
Statut:
epublish
Résumé
Identifying blood-based DNA methylation patterns is a minimally invasive way to detect biomarkers in predicting age, characteristics of certain diseases and conditions, as well as responses to immunotherapies. As microarray platforms continue to evolve and increase the scope of CpGs measured, new discoveries based on the most recent platform version and how they compare to available data from the previous versions of the platform are unknown. The neutrophil dexamethasone methylation index (NDMI 850) is a blood-based DNA methylation biomarker built on the Illumina MethylationEPIC (850K) array that measures epigenetic responses to dexamethasone (DEX), a synthetic glucocorticoid often administered for inflammation. Here, we compare the NDMI 850 to one we built using data from the Illumina Methylation 450K (NDMI 450). The NDMI 450 consisted of 22 loci, 15 of which were present on the NDMI 850. In adult whole blood samples, the linear composite scores from NDMI 450 and NDMI 850 were highly correlated and had equivalent predictive accuracy for detecting DEX exposure among adult glioma patients and non-glioma adult controls. However, the NDMI 450 scores of newborn cord blood were significantly lower than NDMI 850 in samples measured with both assays. We developed an algorithm that reproduces the DNA methylation glucocorticoid response score using 450K data, increasing the accessibility for researchers to assess this biomarker in archived or publicly available datasets that use the 450K version of the Illumina BeadChip array. However, the NDMI850 and NDMI450 do not give similar results in cord blood, and due to data availability limitations, results from sample types of newborn cord blood should be interpreted with care.
Sections du résumé
BACKGROUND
Identifying blood-based DNA methylation patterns is a minimally invasive way to detect biomarkers in predicting age, characteristics of certain diseases and conditions, as well as responses to immunotherapies. As microarray platforms continue to evolve and increase the scope of CpGs measured, new discoveries based on the most recent platform version and how they compare to available data from the previous versions of the platform are unknown. The neutrophil dexamethasone methylation index (NDMI 850) is a blood-based DNA methylation biomarker built on the Illumina MethylationEPIC (850K) array that measures epigenetic responses to dexamethasone (DEX), a synthetic glucocorticoid often administered for inflammation. Here, we compare the NDMI 850 to one we built using data from the Illumina Methylation 450K (NDMI 450).
RESULTS
The NDMI 450 consisted of 22 loci, 15 of which were present on the NDMI 850. In adult whole blood samples, the linear composite scores from NDMI 450 and NDMI 850 were highly correlated and had equivalent predictive accuracy for detecting DEX exposure among adult glioma patients and non-glioma adult controls. However, the NDMI 450 scores of newborn cord blood were significantly lower than NDMI 850 in samples measured with both assays.
CONCLUSIONS
We developed an algorithm that reproduces the DNA methylation glucocorticoid response score using 450K data, increasing the accessibility for researchers to assess this biomarker in archived or publicly available datasets that use the 450K version of the Illumina BeadChip array. However, the NDMI850 and NDMI450 do not give similar results in cord blood, and due to data availability limitations, results from sample types of newborn cord blood should be interpreted with care.
Identifiants
pubmed: 36307860
doi: 10.1186/s13148-022-01352-1
pii: 10.1186/s13148-022-01352-1
pmc: PMC9617416
doi:
Substances chimiques
Glucocorticoids
0
naphthalene-1,5-dimaleimide
58487-16-4
Genetic Markers
0
Dexamethasone
7S5I7G3JQL
Types de publication
Journal Article
Research Support, U.S. Gov't, P.H.S.
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
136Subventions
Organisme : NCI NIH HHS
ID : R01 CA139020
Pays : United States
Organisme : NCI NIH HHS
ID : HHSN261201800032I
Pays : United States
Organisme : NCI NIH HHS
ID : HHSN261201800015I
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA082103
Pays : United States
Organisme : NCI NIH HHS
ID : HHSN261201800009I
Pays : United States
Organisme : NCI NIH HHS
ID : R25 CA112355
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA126831
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA216265
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : NU58DP006344
Pays : United States
Organisme : NCI NIH HHS
ID : P50 CA097257
Pays : United States
Organisme : NIGMS NIH HHS
ID : P20 GM130423
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA207360
Pays : United States
Organisme : NCRR NIH HHS
ID : UL1 RR024131
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA253976
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA052689
Pays : United States
Organisme : NIGMS NIH HHS
ID : P20 GM104416
Pays : United States
Informations de copyright
© 2022. The Author(s).
Références
Nucleic Acids Res. 2020 Jan 8;48(D1):D890-D895
pubmed: 31584095
Curr Opin Oncol. 2004 Nov;16(6):593-600
pubmed: 15627023
Nat Methods. 2018 Dec;15(12):1059-1066
pubmed: 30504870
Am J Obstet Gynecol. 2012 Dec;207(6):446-54
pubmed: 22840973
Neuropsychopharmacology. 2018 Feb;43(3):564-570
pubmed: 28975925
Genome Res. 2018 Sep;28(9):1285-1295
pubmed: 30072366
Neuro Oncol. 2006 Jan;8(1):12-26
pubmed: 16443944
Nucleic Acids Res. 2013 Apr;41(7):e90
pubmed: 23476028
PLoS One. 2012;7(1):e30413
pubmed: 22272345
Child Dev. 2010 Jan-Feb;81(1):131-48
pubmed: 20331658
Genome Biol. 2018 May 29;19(1):64
pubmed: 29843789
PLoS One. 2021 Jan 22;16(1):e0245386
pubmed: 33481865
Nat Genet. 2009 Aug;41(8):905-8
pubmed: 19578366
Front Immunol. 2021 Nov 01;12:777927
pubmed: 34790206
Transl Psychiatry. 2014 Mar 04;4:e368
pubmed: 24594779
Bioinformatics. 2014 May 15;30(10):1363-9
pubmed: 24478339
Exp Clin Endocrinol Diabetes. 2017 Nov;125(10):677-683
pubmed: 28407659
Clin Epigenetics. 2021 Aug 26;13(1):165
pubmed: 34446099
Mol Cell. 2013 Jan 24;49(2):359-367
pubmed: 23177740
Trends Endocrinol Metab. 2019 Nov;30(11):807-818
pubmed: 31699238
Neuro Oncol. 2019 Mar 18;21(4):451-461
pubmed: 30624711
N Engl J Med. 2015 Jun 25;372(26):2499-508
pubmed: 26061753
Clin Epigenetics. 2017 Oct 3;9:107
pubmed: 29026448
Infant Behav Dev. 2019 Nov;57:101342
pubmed: 31421390
Eur J Endocrinol. 2022 Jan 13;186(2):297-308
pubmed: 34914631
Genes (Basel). 2014 Sep 16;5(3):821-64
pubmed: 25229548
Genome Biol. 2014 Mar 05;15(3):R50
pubmed: 24598480
Pediatr Endocrinol Rev. 2018 Sep;16(1):186-193
pubmed: 30371037
Genes (Basel). 2017 May 23;8(6):
pubmed: 28545252
J Perinatol. 2009 May;29 Suppl 2:S44-9
pubmed: 19399009
Expert Rev Mol Diagn. 2010 May;10(4):481-8
pubmed: 20465502
Nat Commun. 2022 Sep 20;13(1):5505
pubmed: 36127421
Genome Biol. 2013;14(10):R115
pubmed: 24138928
Nat Genet. 2017 May;49(5):789-794
pubmed: 28346443