Training a model for estimating leukocyte composition using whole-blood DNA methylation and cell counts as reference.
Epigenomics
; 9(1): 13-20, 2017 01.
Article
en En
| MEDLINE
| ID: mdl-27884066
AIM: Whole-blood DNA methylation depends on the underlying leukocyte composition and confounding hereby is a major concern in epigenome-wide association studies. Cell counts are often missing or may not be feasible. Computational approaches estimate leukocyte composition from DNA methylation based on reference datasets of purified leukocytes. We explored the possibility to train such a model on whole-blood DNA methylation and cell counts without the need for purification. MATERIALS & METHODS: Using whole-blood DNA methylation and corresponding five-part cell counts from 2445 participants from the London Life Sciences Prospective Population Study, a model was trained on a subset of 175 subjects and evaluated on the remaining. RESULTS: Correlations between cell counts and estimated cell proportions were high (neutrophils 0.85, eosinophils 0.88, basophils 0.02, lymphocytes 0.84, monocytes 0.55) and estimated proportions explained more variance in whole-blood DNA methylation levels than counts. CONCLUSION: Our model provided precise estimates for the common cell types.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Metilación de ADN
/
Leucocitos
Tipo de estudio:
Prognostic_studies
Límite:
Adult
/
Aged
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Female
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Humans
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Male
/
Middle aged
Idioma:
En
Revista:
Epigenomics
Año:
2017
Tipo del documento:
Article
País de afiliación:
Alemania