The Vallecas Project: A Cohort to Identify Early Markers and Mechanisms of Alzheimer's Disease.
BACKGROUND
Alzheimer's disease (AD) is a major threat for the well-being of an increasingly aged world population. The physiopathological mechanisms of late-onset AD are multiple, possibly heterogeneous, and not well understood. Different combinations of variables from several domains (i.e., clinical, neuropsychological, structural, and biochemical markers) may predict dementia conversion, according to distinct physiopathological pathways, in different groups of subjects.


METHODS
We launched the Vallecas Project (VP), a cohort study of non-demented people aged 70-85, to characterize the social, clinical, neuropsychological, structural, and biochemical underpinnings of AD inception. Given the exploratory nature of the VP, multidimensional and machine learning techniques will be applied, in addition to the traditional multivariate statistical methods.


RESULTS
A total of 1169 subjects were recruited between October 2011 and December 2013. Mean age was 74.4 years (SD 3.9), 63.5% of the subjects were women, and 17.9% of the subjects were carriers of at least one ε4 allele of the apolipoprotein E gene. Cognitive diagnoses at inclusion were as follows: normal cognition 93.0% and mild cognitive impairment (MCI) 7.0% (3.1% amnestic MCI, 0.1% non-amnestic MCI, 3.8% mixed MCI). Blood samples were obtained and stored for future determinations in 99.9% of the subjects and 3T magnetic resonance imaging study was conducted in 89.9% of the volunteers. The cohort is being followed up annually for 4 years after the baseline.


CONCLUSIONS
We have established a valuable homogeneous single-center cohort which, by identifying groups of variables associated with high risk of MCI or dementia conversion, should help to clarify the early physiopathological mechanisms of AD and should provide avenues for prompt diagnosis and AD prevention.
Gregorio Marañón University Hospital , Madrid , Spain.
Javier
J
Olazarán
Alzheimer's Center Reina Sofía Foundation - CIEN Foundation and CIBERNED, Carlos III Institute of Health , Madrid , Spain.
Meritxell
M
Valentí
Alzheimer's Center Reina Sofía Foundation - CIEN Foundation and CIBERNED, Carlos III Institute of Health , Madrid , Spain.
Belén
B
Frades
Alzheimer's Center Reina Sofía Foundation - CIEN Foundation and CIBERNED, Carlos III Institute of Health , Madrid , Spain.
María Ascensión
MA
Zea-Sevilla
Alzheimer's Center Reina Sofía Foundation - CIEN Foundation and CIBERNED, Carlos III Institute of Health , Madrid , Spain.
Marina
M
Ávila-Villanueva
Alzheimer's Center Reina Sofía Foundation - CIEN Foundation and CIBERNED, Carlos III Institute of Health , Madrid , Spain.
Miguel Ángel
MÁ
Fernández-Blázquez
Alzheimer's Center Reina Sofía Foundation - CIEN Foundation and CIBERNED, Carlos III Institute of Health , Madrid , Spain.
Miguel
M
Calero
Alzheimer's Center Reina Sofía Foundation - CIEN Foundation and CIBERNED, Carlos III Institute of Health , Madrid , Spain.
José Luis
JL
Dobato
Laboratory of Medical Imaging Analysis and Biometrics, Rey Juan Carlos University , Móstoles , Spain.
Juan Antonio
JA
Hernández-Tamames
Alzheimer's Center Reina Sofía Foundation - CIEN Foundation and CIBERNED, Carlos III Institute of Health , Madrid , Spain.
Beatriz
B
León-Salas
Alzheimer's Center Reina Sofía Foundation - CIEN Foundation and CIBERNED, Carlos III Institute of Health , Madrid , Spain.
Luis
L
Agüera-Ortiz
Alzheimer's Center Reina Sofía Foundation - CIEN Foundation and CIBERNED, Carlos III Institute of Health , Madrid , Spain.
Jorge
J
López-Álvarez
Department of Artificial Intelligence, Technical University of Madrid , Boadilla del Monte , Spain.
Pedro
P
Larrañaga
Department of Artificial Intelligence, Technical University of Madrid , Boadilla del Monte , Spain.
Concha
C
Bielza
Department of Neuroimaging, Hospital Ruber Internacional , Madrid , Spain.
Juan
J
Álvarez-Linera
National Center of Epidemiology and CIBERNED, Carlos III Institute of Health , Madrid , Spain.
Pablo
P
Martínez-Martín
Alzheimer’s disease; cohort study; early detection; mild cognitive impairment; risk factors