One of the driving questions in Alzheimer’s research has been its nature—is
AD simply an extension of normal aging, or is it a disease unto itself?
If it is a disease unto itself, what changes over time in the brain
to make the aged tissue so much more vulnerable to attack? Using high-level
bioinformatic approaches, Miller, Oldham, and Geschwind take a closer look
at the interplay between aging and AD using transcriptional profiles from
previously published data sets.
On a technical scale, this work is extremely thorough and careful. It is a
terrific example of a well-reasoned meta-analysis in its truest form, paying
attention to statistical probabilities at each stage of the analyses (e.g.,
probability of overlap between the two studies based on the discovery power
in either). Rather than simply comparing lists of genes from two studies,
the authors stripped the information from each study down to its most
raw form (at least as raw as they could get it, i.e., CEL files from Affymetrix
array scans), and used a consistent probe level algorithm across both
studies to create...