1. The Vista of Application of Specific Anaphylaxis Accurate Diagnosis Based on DNA Single-Nucleotide Methylation Sites
- Author
-
Peng Wu, Xiang-jie Guo, Yan Feng, Hua-Lin Guo, Jianguo Li, Liqin Zhai, Keming Yun, Cai-rong Gao, Yaqin Bai, and Hao Li
- Subjects
chemistry.chemical_classification ,Genetics ,Article Subject ,Nucleotides ,Atopic Rhinitis ,Genome-wide association study ,Methylation ,DNA Methylation ,Biology ,medicine.disease ,chemistry.chemical_compound ,chemistry ,DNA methylation ,Medical technology ,medicine ,Humans ,CpG Islands ,Radiology, Nuclear Medicine and imaging ,Nucleotide ,Epigenetics ,R855-855.5 ,Anaphylaxis ,DNA ,Research Article - Abstract
Anaphylaxis has rapidly spread around the world in the last several decades. Environmental factors seem to play a major role, and epigenetic marks, especially DNA methylation, get more attention. We discussed several GEO opening data classifications with TOP 100 specific methylation region values (normalized M-values on line) by machine learning, which are remarkable to classify specific anaphylaxis after monoallergen exposure. Then, we sequenced the whole-genome DNA methylation of six people (3 wormwood monoallergen atopic rhinitis patients and 3 normal-immune people) during the pollen season and analyzed the difference of the single nucleotide and DNA region. The results’ divergences were obvious (the differential single nucleotides were mostly distributed in nongene regions but the differential DNA regions of GWAS, on the other hand), which may have caused most single nucleotides to be concealed in the regions’ sequences. Therefore, we suggest that we should conduct more “pragmatic” and directly find special single-nucleotide changes after exposure to atopic allergens instead of complex correlativity. It is possible to try to use DNA methylation marks to accurately diagnose anaphylaxis and form a machine learning classification based on the single methylated CpGs.
- Published
- 2021
- Full Text
- View/download PDF