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1.
Biomedicines ; 11(7)2023 Jun 23.
Artículo en Inglés | MEDLINE | ID: mdl-37509437

RESUMEN

OBJECTIVE: To identify DNA methylation patterns of heavy smokers in oral rinse samples. METHODS: Genome-wide DNA methylation data was imported from Gene Expression Omnibus GSE70977 using the GEOquery package. Two independent sets were analyzed: (a) 71 epigenomes of cancer-free subjects (heavy smokers n = 37 vs. non-smokers n = 31); for concordance assessment (b) 139 oral-cancer patients' epigenomes (heavy smokers n = 92 vs. non-smokers n = 47). Differential DNA methylation for CpG positions and at the regional level was determined using Limma and DMRcate Bioconductor packages. The linear model included sex, age, and alcohol consumption. The statistical threshold was set to p < 0.05. Functional gene prioritization analysis was performed for gene-targeted analysis. RESULTS: In individuals without cancer and heavy smokers, the FAM184B gene was found with two CpG positions differentially hypermethylated (p = 0.012 after FDR adjustment), in a region of 48 bp with an absolute methylation difference >10% between groups (p = 1.76 × 10-8). In the analysis corresponding to oral-cancer patients, we found AHRR differentially hypomethylated cancer patients, but also in subjects without oral cancer in the targeted analyses. Remarkably, ADAMTS2 was found differentially hypermethylated in heavy smokers without a diagnosis of cancer in two consecutive probes cg05575921 (p = 3.13 × 10-7) and cg10208897 (p = 1.36 × 10-5). CONCLUSIONS: Differentially methylated AHRR, ADAMTS2, and FAM184B genes are biomarker candidates in oral rinse samples.

2.
Artículo en Inglés | MEDLINE | ID: mdl-30176603

RESUMEN

Polymerase Chain Reaction (PCR) based techniques for DNA methylation techniques includes the MS-HRM technique. Methylation Sensitive High-Resolution Melting (MS-HRM) primer-design requires a set of necessary recommendations for such DNA methylation assessment. However, there were not any available software that allows an automatic design of this kind primers. We present Softepigen, the first complete MS-HRM primer design software. Softepigen allows to search for primers in a genomic region following Wojdacz's recommendations and targets primer binding regions with high linguistic complexity sequences that increase the specificity of the converted sequence of the human genome. We performed in-silico PCR analysis through BiSearch ePCR tool to validate the specificity of the of the primers designed using Softepigen. Softepigen for MS-HRM performance in our genomic regions of interest show satisfactory specificity measurements, and we implemented it for freely available use in the web-based interface at www.soft-epigen.com.


Asunto(s)
Metilación de ADN/genética , Cartilla de ADN/química , Cartilla de ADN/genética , Genómica/métodos , Reacción en Cadena de la Polimerasa/métodos , Programas Informáticos , Humanos , Internet , Análisis de Secuencia de ADN
3.
Epigenomics ; 10(11): 1365-1382, 2018 11.
Artículo en Inglés | MEDLINE | ID: mdl-30324800

RESUMEN

OBJECTIVE: To study DNA methylation patterns of cortical pyramidal layers susceptible to late-onset Alzheimer's disease (LOAD) neurodegeneration. METHODS: Laser-assisted microdissection to select pyramidal layers' cells in frontal cortex of 32 human brains (18 LOAD) and Infinium DNA Methylation 450K analysis were performed to find differential methylated positions and regions, in addition to the corresponding gene set functional enrichment analyses. RESULTS: Differential hypermethylation in several genomic regions and genes mainly in HOXA3, GSTP1, CXXC1-3 and BIN1. The functional enrichment analysis revealed genes significantly related to oxidative-stress and synapsis. CONCLUSION: The present results indicate the differentially methylated genes related to neural projections, synapsis, oxidative stress and epigenetic regulator genes and represent the first epigenome of cortical pyramidal layers in LOAD.


Asunto(s)
Enfermedad de Alzheimer/genética , Metilación de ADN , Lóbulo Frontal/metabolismo , Proteínas Adaptadoras Transductoras de Señales/genética , Anciano , Anciano de 80 o más Años , Proteínas de Unión al ADN/genética , Femenino , Gutatión-S-Transferasa pi/genética , Proteínas de Homeodominio/genética , Humanos , Captura por Microdisección con Láser , Masculino , Proteínas Nucleares/genética , Estrés Oxidativo , Células Piramidales/metabolismo , Transmisión Sináptica , Transactivadores , Proteínas Supresoras de Tumor/genética
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