Methylation haplotypes of the insulin gene promoter in children and adolescents with type 1 diabetes: Can a dimensionality reduction approach predict the disease?
CpG
adolescents
children
epigenetics
insulin gene
methylation
type 1 diabetes
Journal
Experimental and therapeutic medicine
ISSN: 1792-1015
Titre abrégé: Exp Ther Med
Pays: Greece
ID NLM: 101531947
Informations de publication
Date de publication:
Oct 2023
Oct 2023
Historique:
received:
20
01
2023
accepted:
09
06
2023
medline:
4
9
2023
pubmed:
4
9
2023
entrez:
4
9
2023
Statut:
epublish
Résumé
DNA methylation of cytosine-guanine sites (CpGs) is associated with type 1 diabetes (T1D). The sequence of methylated and non-methylated sites in a specific genetic region constitutes its methyl-haplotype. The aim of the present study was to identify insulin gene promoter (IGP) methyl-haplotypes among children and adolescents with T1D and suggest a predictive model for the discrimination of cases and controls according to methyl-haplotypes. A total of 40 individuals (20 T1D) participated. The IGP region from peripheral whole blood DNA of 40 participants (20 T1D) was sequenced using next-generation sequencing, sequences were read using FASTQ files and methylation status was calculated by python-based pipeline for targeted deep bisulfite sequenced amplicons (ampliMethProfiler). Methylation profile at 10 CpG sites proximal to transcription start site of the IGP was recorded and coded as 0 for unmethylation or 1 for methylation. A single read could result in '1111111111' methyl-haplotype (all methylated), '000000000' methyl-haplotype (all unmethylated) or any other combination. Principal component analysis was applied to the generated methyl-haplotypes for dimensionality reduction, and the first three principal components were employed as features with five different classifiers (random forest, decision tree, logistic regression, Naive Bayes, support vector machine). Naive Bayes was the best-performing classifier, with 0.9 accuracy. Predictive models were evaluated using receiver operating characteristics (AUC 0.96). Methyl-haplotypes '1111111111', '1111111011', '1110111111', '1111101111' and '1110101111' were revealed to be the most significantly associated with T1D according to the dimensionality reduction method. Methylation-based biomarkers such as IGP methyl-haplotypes could serve to identify individuals at high risk for T1D.
Identifiants
pubmed: 37664671
doi: 10.3892/etm.2023.12160
pii: ETM-26-4-12160
pmc: PMC10469396
doi:
Types de publication
Journal Article
Langues
eng
Pagination
461Informations de copyright
Copyright © 2020, Spandidos Publications.
Déclaration de conflit d'intérêts
The authors declare that they have no competing interests.
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