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Abnormal DNA methylation patterns in patients with infection?caused leukocytopenia based on methylation microarrays.

ABSTRACT: The present study aimed to investigate the association between gene methylation and leukocytopenia from the perspective of gene regulation. A total of 30 patients confirmed as having post?infection leukocytopenia at People's Hospital of Xinjiang Uygur Autonomous Region between January 2016 and June 2017 were successively recruited as the leukocytopenia group; 30 patients with post?infection leukocytosis were enrolled as the leukocytosis group. In addition, 30 healthy volunteers who received a health examination at the hospital during the same period were included as the normal control group. In each group, four individuals were randomly selected for whole genome methylation screening. After selection of key methylation sites, the remaining samples in each group were used for verification using matrix?assisted laser desorption/ionization?time of flight mass spectrometry. The levels of serum complement factors C3 and C5 in the leukocytopenia group were significantly lower than those in the other two groups (P<0.05). According to whole?genome DNA methylation detection, 66 and 27 methylation loci may be associated with leukocytopenia and leukocytosis, respectively. Most of these abnormal loci are located on chromosomes 2, 6, 7, 1, 17 and 11. The rates of WW domain containing E3 ubiquitin protein ligase 2 gene methylation at cytosine?phosphate?guanine (CpG)_1, CpG_5/6 and CpG_7 in the leukocytopenia group were higher than in the other two groups (P<0.05); the rate of AKT2 CpG_1 methylation was higher in the leukocytopenia group than in the other two groups (P<0.05); the rate of calcium?binding atopy?related autoantigen 1 gene CpG_2 methylation was higher in the leukocytosis group than in the normal control group (P<0.05); and the rate of NADPH oxidase 5 gene CpG_3 methylation was higher in the leukocytosis group than in the normal control group (P<0.05). Chemotactic factor secretion and cell migration abnormalities, ubiquitination modification disorders and reduced oxidative burst may participate in infection?complicated leukocytopenia. The results of this study shed new light on the molecular biological mechanisms of infection?complicated leukocytopenia and provide novel avenues for diagnosis and treatment.

SUBMITTER: Wu C

PROVIDER: S-EPMC7185277 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Abnormal DNA methylation patterns in patients with infection‑caused leukocytopenia based on methylation microarrays.

Wu Chao C Muhataer Xirennayi X Wang Wenyi W Deng Mingqin M Jin Rong R Lian Zhichuang Z Luo Dan D Li Yafang Y Yang Xiaohong X

Molecular medicine reports 20200408 6

The present study aimed to investigate the association between gene methylation and leukocytopenia from the perspective of gene regulation. A total of 30 patients confirmed as having post‑infection leukocytopenia at People's Hospital of Xinjiang Uygur Autonomous Region between January 2016 and June 2017 were successively recruited as the leukocytopenia group; 30 patients with post‑infection leukocytosis were enrolled as the leukocytosis group. In addition, 30 healthy volunteers who received a he ...[more]

PMID: 32323775

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Project description:Background Epigenetics can contribute to lipid disorders in obesity. The DNA methylation pattern can be the cause or consequence of high blood lipids. The aim of the study was to investigate the DNA methylation profile in peripheral leukocytes associated with elevated LDL-cholesterol level in overweight and obese individuals. Methods To identify the differentially methylated genes, genome-wide DNA methylation microarray analysis was performed in leukocytes of obese individuals with high LDL-cholesterol (LDL-CH, ??3.4 mmol/L) versus control obese individuals with LDL-CH, <?3.4 mmol/L. Biochemical tests such as serum glucose, total cholesterol, HDL cholesterol, triglycerides, insulin, leptin, adiponectin, FGF19, FGF21, GIP and total plasma fatty acids content have been determined. Oral glucose and lipid tolerance tests were also performed. Human DNA Methylation Microarray (from Agilent Technologies) containing 27,627 probes for CpG islands was used for screening of DNA methylation status in 10 selected samples. Unpaired t-test and Mann–Whitney U-test were used for biochemical and anthropometric parameters statistics. For microarrays analysis, fold of change was calculated comparing hypercholesterolemic vs control group. The q-value threshold was calculated using moderated Student’s t-test followed by Benjamini–Hochberg multiple test correction FDR. Results In this preliminary study we identified 190 lipid related CpG loci differentially methylated in hypercholesterolemic versus control individuals. Analysis of DNA methylation profiles revealed several loci engaged in plasma lipoprotein formation and metabolism, cholesterol efflux and reverse transport, triglycerides degradation and fatty acids transport and ?-oxidation. Hypermethylation of CpG loci located in promoters of genes regulating cholesterol metabolism: PCSK9, LRP1, ABCG1, ANGPTL4, SREBF1 and NR1H2 in hypercholesterolemic patients has been found. Novel epigenetically regulated CpG sites include ABCG4, ANGPTL4, AP2A2, AP2M1, AP2S1, CLTC, FGF19, FGF1R, HDLBP, LIPA, LMF1, LRP5, LSR, NR1H2 and ZDHHC8 genes. Conclusions Our results indicate that obese individuals with hypercholesterolemia present specific DNA methylation profile in genes related to lipids transport and metabolism. Detailed knowledge of epigenetic regulation of genes, important for lipid disorders in obesity, underlies the possibility to influence target genes by changing diet and lifestyle, as DNA methylation is reversible and depends on environmental factors. These findings give rise for further studies on factors that targets methylation of revealed genes.

Project description:Mammography is used to detect breast cancer (BC), but its sensitivity is limited, especially for dense breasts. Circulating cell-free DNA (cfDNA) methylation tests is expected to compensate for the deficiency of mammography. We derived a specific panel of markers based on computational analysis of the DNA methylation profiles from The Cancer Genome Atlas (TCGA). Through training (n = 160) and validation set (n = 69), we developed a diagnostic prediction model with 26 markers, which yielded a sensitivity of 89.37% and a specificity of 100% for differentiating malignant disease from normal lesions [AUROC = 0.9816 (95% CI: 96.09-100%), and AUPRC = 0.9704 (95% CI: 94.54-99.46%)]. A simplified 4-marker model including cg23035715, cg16304215, cg20072171, and cg21501525 had a similar diagnostic power [AUROC = 0.9796 (95% CI: 95.56-100%), and AUPRC = 0.9220 (95% CI: 91.02-94.37%)]. We found that a single cfDNA methylation marker, cg23035715, has a high diagnostic power [AUROC = 0.9395 (95% CI: 89.72-99.27%), and AUPRC = 0.9111 (95% CI: 88.45-93.76%)], with a sensitivity of 84.90% and a specificity of 93.88%. In an independent testing dataset (n = 104), the obtained diagnostic prediction model discriminated BC patients from normal controls with high accuracy [AUROC = 0.9449 (95% CI: 90.07-98.91%), and AUPRC = 0.8640 (95% CI: 82.82-89.98%)]. We compared the diagnostic power of cfDNA methylation and mammography. Our model yielded a sensitivity of 94.79% (95% CI: 78.72-97.87%) and a specificity of 98.70% (95% CI: 86.36-100%) for differentiating malignant disease from normal lesions [AUROC = 0.9815 (95% CI: 96.75-99.55%), and AUPRC = 0.9800 (95% CI: 96.6-99.4%)], with better diagnostic power and had better diagnostic power than that of using mammography [AUROC = 0.9315 (95% CI: 89.95-96.34%), and AUPRC = 0.9490 (95% CI: 91.7-98.1%)]. In addition, hypermethylation profiling provided insights into lymph node metastasis stratifications (p < 0.05). In conclusion, we developed and tested a cfDNA methylation model for BC diagnosis with better performance than mammography.

Dataset Information

Abnormal DNA methylation patterns in patients with infection?caused leukocytopenia based on methylation microarrays.

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Abnormal DNA methylation patterns in patients with infection‑caused leukocytopenia based on methylation microarrays.

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