tissue: Peripheral Whole Blood Sex: M race: EA disease: Control
Treatment protocol
A pilot case control study of 50 cases and 50 controls was also conducted at the Duke Memory Clinic. Peripheral whole blood was collected by the lancet and capillary method into lysis buffer and DNA extracted. In total, DNA samples from 17 individuals were randomly selected. Among them, 10 were Alzheimer’s disease cases and 7 were controls. All the samples were processed twice using the Human Imprintome array to assess the performance of the array. Moreover, three more controls were randomly selected to process them with the Human Imprintome array and the EPICv2 array
Extracted molecule
genomic DNA
Extraction protocol
For the preparation of samples, 200 ng of DNA were bisulfite converted using the EZ DNA Methylation kit (Zymo Research, Irvine, CA) according to the manufacturer’s instructions.
Label
Cy3, Cy5
Label protocol
Bisulfite-converted DNA samples were randomly assigned to a chip well on the Human Imprintome array BeadChip (Illumina, Inc., San Diego, CA), amplified, hybridized onto the array, stained, washed, and imaged with the Illumina iScan SQ instrument (Illumina, Inc., San Diego, CA) to obtain raw image intensities.
Hybridization protocol
Bisulfite-converted DNA samples were randomly assigned to a chip well on the Human Imprintome array BeadChip (Illumina, Inc., San Diego, CA), amplified, hybridized onto the array, stained, washed, and imaged with the Illumina iScan SQ instrument (Illumina, Inc., San Diego, CA) to obtain raw image intensities.
Scan protocol
Bisulfite-converted DNA samples were randomly assigned to a chip well on the Human Imprintome array BeadChip (Illumina, Inc., San Diego, CA), amplified, hybridized onto the array, stained, washed, and imaged with the Illumina iScan SQ instrument (Illumina, Inc., San Diego, CA) to obtain raw image intensities.
Data processing
To preprocess the DNA methylation values, we utilized the sesame package due to its compatibility with custom arrays. Specifically, we employed the readIDATpair followed by the getBetas functions, which require the IDAT file locations and the custom manifest to generate a beta value matrix. To visualize the distribution of beta values we employed the densityPlot function from the minfi package
