Methylationepic array

WID-qEC test regions were discovered in an epigenome-wide approach (approximately 850,000 methylation sites). Cervicovaginal samples from 572 controls and 144 women with EC (FORECEE study) were subjected to the Illumina MethylationEPIC array following a previously established pipeline.^{24 (link)} The epigenome-wide study and details of the methylation-specific PCR-based MethyLight assay^{11 (link)} are described in the Data Supplement.

Illumina Infinium MethylationEPIC array was performed for 66 MB cases in this cohort series as described in a previous study [8 (link)]. Raw data files were read and preprocessed using minfi [71 (link)] and ChAMP [72 (link)] package in R environment. For clustering, unsupervised clustering analysis was performed based on the 10,000 most differential probes using consensus clustering and validated by 11 subgroup-specific signature probes [73 (link)].

Frozen resected tumor material was retrieved from the Department of Neuropathology in Heidelberg and reviewed by a board-certified neuropathologist. Diagnoses were molecularly confirmed according to the recent WHO classification and methylation profiles were confirmed with methylation EPIC array (#WG-317-1003, Illumina, San Diego, California, USA).
Due to the frozen nature of the obtained tissue, we needed to employ snRNA-Seq instead of scRNA-Seq. For single nuclei isolation, resected tumor material underwent the following quality control. Only material with a tumor content ≥ 70% and a low percentage of necrosis, as determined on hematoxylin and eosin-stained sections by a board-certified neuropathologist (Department of Neuropathology, University Hospital Heidelberg, Germany) was considered for further processing. Clinical and pathological characterization of patients are summarized in Supplementary Table 4. Human patient samples were manually anonymized.

DNA was isolated from peripheral blood samples. In both cohorts, genotypes were assayed on the Illumina HumanOmni2.5–8 array and DNAm on the Illumina Infinium MethylationEPIC array. Genotyping and DNAm quality control methods are described in the Supplementary Materials, as are the calculation procedures for GrimAge, other DNAm age estimates, and ancestry principal components (PCs). An index of age-adjusted GrimAge was created by regressing GrimAge on chronological age and saving the residuals (“GrimAge residuals”). Conceptually, positive residual values index mortality risk that is elevated compared to chronological age, while negative residual values suggest reduced mortality risk relative to age. Blood sample white blood cell proportions (CD8-T and CD4-T cells, natural killer cells, b-cells, monocytes) were calculated from the methylation data [35 (link), 36 (link)] and included as covariates (technical confounders) in analyses with GrimAge residuals as the outcome. As cell type composition may be confounded with DNAm, even when DNAm-based variables are the exogenous variable, we created a second GrimAge residual variable for use in follow-up analyses of models in which GrimAge was the independent variable in which variance associated with chronological age and cell type estimates was regressed out from raw GrimAge estimates.