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450k methylation array  (INFINIUM Inc)

 
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    INFINIUM Inc 450k methylation array
    450k Methylation Array, supplied by INFINIUM Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/methylation+array/infinium+humanmethylation450+beadchip/us12359257-884-16-16
    Average 90 stars, based on 1 article reviews
    450k methylation array - by Bioz Stars, 2026-10
    90/100 stars

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    Related Articles

    Methylation:

    Article Title: Chronic Cigarette Smoke-Induced Epigenomic Changes Precede Sensitization of Bronchial Epithelial Cells to Single Step Transformation by KRAS Mutations
    Article Snippet: Predictions were ordered to prefer transcripts with canonical start and stop codons and CCDS or Refseq transcripts over Ensembl when available. .. Generation of box plots for analysis of methylation data from NSCLC samples from TCGA for correlation with mutational and smoking status Infinium methylation array data for primary lung adenocarcinoma and adjacent normal tissue was used to examine the methylation status of the CSC methylated genes in these tumors and normal samples (depicted in ) when separated by mutational status and/or smoking history. ..

    Article Title: Detection of cell-type-specific differentially methylated regions in epigenome-wide association studies
    Article Snippet: .. To mimic genomic locations of CpG sites assayed by typical methylation arrays used in EWAS, we took the genomic locations of the first G = 10 000 CpG sites of Chromosome 1 assayed by Infinium HumanMethylation EPIC array, which can be split into 134 blocks with each block containing 50–100 CpG sites (see ). ..

    Article Title: Epigenome-wide meta-analysis identifies DNA methylation biomarkers associated with diabetic kidney disease
    Article Snippet: Furthermore, the Mendelian randomisation analyses suggested that higher methylation levels at cg23527387 were also causally related to a lower risk of DKD, in line with the direction seen in the EWAS. .. Hypomethylation of cg23527387 has also been observed in a previous methylation analysis on DKD in 226 individuals with T1D using data generated from the Infinium 450 K methylation array (β = 0.86, p FDRadj = 6.0 × 10 −7 ) . ..

    Article Title: Losing DNA methylation at repetitive elements and breaking bad
    Article Snippet: .. However, they have been clustered into two groups, through the analysis of the Infinium methylation array of 15 patients, based on the different methylation status of other genomic loci [ ]. ..

    Article Title: Integrative cBioPortal Analysis Revealed Molecular Mechanisms That Regulate EGFR-PI3K-AKT-mTOR Pathway in Diffuse Gliomas of the Brain
    Article Snippet: Illumina Infinium DNA methylation arrays were applied to collect DNA methylation profiles of three tumor types and histologically normal tumor-adjacent tissue. .. All our samples were profiled on the same methylation array (HumanMethylation450 (HM450) Infinium array) [ ]. ..

    Article Title: Narcolepsy type I-associated DNA methylation and gene expression changes in the human leukocyte antigen region.
    Article Snippet: .. Our previous methylation study of NT1 in blood samples using Infinium 27K methylation array thus removed HLA region from the analyses33. .. Here we suggested a method of rigorous analysis of DNA methylation in the HLA region, and conducted a more precise determination of DNA methylation rates of CD4+ and CD8+ T cells using Infinium methylation EPIC array (> 860K probes).

    Article Title: Methylation marks in blood DNA reveal breast cancer risk in patients fulfilling hereditary disease criteria
    Article Snippet: .. To further support our findings, we assessed the aberrant methylation status of the cg47630224- MSH2 site across three independent cohorts that used the Illumina Infinium 450 K methylation array platform. ..

    Blocking Assay:

    Article Title: Detection of cell-type-specific differentially methylated regions in epigenome-wide association studies
    Article Snippet: .. To mimic genomic locations of CpG sites assayed by typical methylation arrays used in EWAS, we took the genomic locations of the first G = 10 000 CpG sites of Chromosome 1 assayed by Infinium HumanMethylation EPIC array, which can be split into 134 blocks with each block containing 50–100 CpG sites (see ). ..

    Generated:

    Article Title: Epigenome-wide meta-analysis identifies DNA methylation biomarkers associated with diabetic kidney disease
    Article Snippet: Furthermore, the Mendelian randomisation analyses suggested that higher methylation levels at cg23527387 were also causally related to a lower risk of DKD, in line with the direction seen in the EWAS. .. Hypomethylation of cg23527387 has also been observed in a previous methylation analysis on DKD in 226 individuals with T1D using data generated from the Infinium 450 K methylation array (β = 0.86, p FDRadj = 6.0 × 10 −7 ) . ..



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    ( A ) Epigenome-wide association study of dpi in PBMCs based on the entire <t>methylation</t> array. The volcano plots display the −log 10 ( P values) and the directionality of association between CpG sites and infection stages (A, EC, and LC) compared with B: A versus B (left panel), EC versus B (center panel), and LC versus B (right panel). Each dot represents a specific DNAme site. Shown are significantly associated CpG sites ( q < 0.05) with hypomethylation (blue), hypermethylation (red), and nonsignificant (gray). The horizontal axis represents the mean methylation change (i.e., the difference between group means), and the vertical axis represents −log 10 ( P values). ( B ) Changes in EA during each infection stage (A, EC, and LC) relative to B. Biological age analysis was performed based on subsets of clock CpGs. EA at the 3 infection time points was compared with B using mixed-effects linear regression modeling of longitudinal EA changes in PBMCs based on 10 epigenetic clocks. The results are shown separately for young (right) and old (left) RMs. Epigenetic age changes in young (blue) and old (red) RMs are shown. Saturated colors indicate statistically significant changes ( P < 0.05); pale colors indicate nonsignificant changes ( P > 0.05). A statistically significant increase in EA was observed only in young RMs. B–H, Benjamini–Hochberg correction; DMP, differentially methylated positions; dpi, days after infection; RMs, rhesus macaques; B, baseline; A, acute; EC, early chronic; LC, late chronic; EA, epigenetic age.
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    Image Search Results


    ( A ) Epigenome-wide association study of dpi in PBMCs based on the entire methylation array. The volcano plots display the −log 10 ( P values) and the directionality of association between CpG sites and infection stages (A, EC, and LC) compared with B: A versus B (left panel), EC versus B (center panel), and LC versus B (right panel). Each dot represents a specific DNAme site. Shown are significantly associated CpG sites ( q < 0.05) with hypomethylation (blue), hypermethylation (red), and nonsignificant (gray). The horizontal axis represents the mean methylation change (i.e., the difference between group means), and the vertical axis represents −log 10 ( P values). ( B ) Changes in EA during each infection stage (A, EC, and LC) relative to B. Biological age analysis was performed based on subsets of clock CpGs. EA at the 3 infection time points was compared with B using mixed-effects linear regression modeling of longitudinal EA changes in PBMCs based on 10 epigenetic clocks. The results are shown separately for young (right) and old (left) RMs. Epigenetic age changes in young (blue) and old (red) RMs are shown. Saturated colors indicate statistically significant changes ( P < 0.05); pale colors indicate nonsignificant changes ( P > 0.05). A statistically significant increase in EA was observed only in young RMs. B–H, Benjamini–Hochberg correction; DMP, differentially methylated positions; dpi, days after infection; RMs, rhesus macaques; B, baseline; A, acute; EC, early chronic; LC, late chronic; EA, epigenetic age.

    Journal: The Journal of Clinical Investigation

    Article Title: Pathogenic SIV infection is associated with acceleration of epigenetic age in rhesus macaques

    doi: 10.1172/JCI189574

    Figure Lengend Snippet: ( A ) Epigenome-wide association study of dpi in PBMCs based on the entire methylation array. The volcano plots display the −log 10 ( P values) and the directionality of association between CpG sites and infection stages (A, EC, and LC) compared with B: A versus B (left panel), EC versus B (center panel), and LC versus B (right panel). Each dot represents a specific DNAme site. Shown are significantly associated CpG sites ( q < 0.05) with hypomethylation (blue), hypermethylation (red), and nonsignificant (gray). The horizontal axis represents the mean methylation change (i.e., the difference between group means), and the vertical axis represents −log 10 ( P values). ( B ) Changes in EA during each infection stage (A, EC, and LC) relative to B. Biological age analysis was performed based on subsets of clock CpGs. EA at the 3 infection time points was compared with B using mixed-effects linear regression modeling of longitudinal EA changes in PBMCs based on 10 epigenetic clocks. The results are shown separately for young (right) and old (left) RMs. Epigenetic age changes in young (blue) and old (red) RMs are shown. Saturated colors indicate statistically significant changes ( P < 0.05); pale colors indicate nonsignificant changes ( P > 0.05). A statistically significant increase in EA was observed only in young RMs. B–H, Benjamini–Hochberg correction; DMP, differentially methylated positions; dpi, days after infection; RMs, rhesus macaques; B, baseline; A, acute; EC, early chronic; LC, late chronic; EA, epigenetic age.

    Article Snippet: DNAme profiles were generated using a custom Infinium methylation array (HorvathMammalMethylChip40) representing 37,492 CpG highly conserved sites in the mammals, with the NCBI’s Gene Expression Omnibus (GEO) accession number GPL28271 for microarray design ( ).

    Techniques: Methylation, Infection