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2. The healthy elderly brain: MRI predictors for later development of MCI. A first analysis comparing
developing MCI (El cerebro de las personas whole-brain grey-matter density (GMD) in these
mayores sanas: predictores de RM para el “converters” relative to a matched control group se-
desarrollo de DCL). lected from the large sample – at visit 1 (when both
Principal Investigator: Dr. Bryan Strange (UPM groups are healthy) – has already shown fascinating
and FCIEN) differences specific to the entorhinal cortex. The
same type of analysis will now be extended to mea-
The problem addressed in this proposal is the current sures of white matter integrity, perfusion and resting
lack of a technique to predict whether a healthy el- functional networks to provide a comprehensive
derly individual will develop AD. This is important, picture of brain abnormalities present before MCI
given that any treatment for this progressive neuro- develops.
degenerative disorder is more likely to be successful
if administered as early as possible in the disease pro- Whereas the first analyses speak to group differen-
cess. The proposed project will interrogate data from ces in MRI data, this proposal aims to develop a me-
a large sample of 1,213 healthy elderly individuals thod that – for a given healthy elderly individual –
(70-85 yrs; male and female) as they are followed up provides predictive value regarding whether that
in a 5-year longitudinal study. At each yearly visit, vo- person will subsequently develop MCI. For this pur-
lunteers undergo detailed neuropsychological and pose, we will include demographic, neuropsycholo-
clinical evaluation, serum biochemistry analysis, as gical, biochemical and genetic data in our
well as a comprehensive magnetic resonance ima- analyses, in addition to MRI data from all sequences
ging (MRI) protocol, with genetic data acquired on described above. We will adopt a “machine lear-
visit 1. On follow-up, some volunteers go from he- ning” approach to generate a statistical algorithm
althy to a state of mild cognitive impairment (MCI). to determine the likelihood (or odds ratio) of a he-
The goal of the project is to retrospectively deter- althy individual developing MCI in a given time pe-
mine biomarkers in healthy individuals which predict riod. Furthermore, it is expected that some volunteers
subsequent development of MCI. By contrast to the will progress from MCI to AD, thus furnishing a test of
extensive research effort into determining MRI para- whether these biomarkers extend to predicting AD
meters predicting conversion of MCI to AD, much development from the healthy state.
less is known about specific brain biomarkers that
predict the preceding step: going from healthy to Determining the brain imaging biomarkers that in he-
MCI. The novelty of this proposal, and the significant althy people predicts development of MCI will have
advance, is that we will identify changes in the brain significant impact on the field of dementia. That re-
present in groups of healthy elderly people that are latively routinely acquired data can give an indivi-
indistinguishable in the clinical setting, and that differ dual an index of risk of MCI development will provide
only subsequently in the development of MCI. that individual with immediate motivation for ad-
dressing modifiable risk factors for dementia (e.g.
We have acquired structural (T1, T2 weighted), dif- smoking cessation, reduced alcohol intake, choles-
fusion-weighted (DWI), functional (resting state func- terol reduction).
tional MRI) and perfusion scans (arterial
spin-labeling, ASL) in approximately 1,000 volunteers. Furthermore, in the hopeful situation that novel de-
The first goal of this proposal is to examine the MRI mentia treatments will be available soon, it will most
parameters in healthy elderly individuals that predict likely increase therapeutic efficacy if this treatment
CIEN Foundation Annual Report 2017 / 110
