Person:
Bruña Fernández, Ricardo

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First Name
Ricardo
Last Name
Bruña Fernández
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Medicina
Department
Radiología, Rehabilitación y Fisioterapia
Area
Radiología y Medicina Física
Identifiers
UCM identifierORCIDScopus Author IDWeb of Science ResearcherIDDialnet IDGoogle Scholar ID

Search Results

Now showing 1 - 2 of 2
  • Item
    Searching for Primary Predictors of Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: A Multivariate Follow-Up Study
    (Journal of Alzheimer's Disease, 2016) López García, María Eugenia; Turrero Nogués, Agustín; Cuesta Prieto, Pablo; López Sanz, David; Bruña Fernández, Ricardo; Marcos Dolado, Alberto; Gil Gregorio, Pedro; Yus, Miguel; Barabash Bustelo, Ana; Cabranes Díaz, José Antonio; Maestu Unturbe, Fernando; Fernández Lucas, Alberto Amable
    Recent proposals of diagnostic criteria within the healthy aging-Alzheimer’s disease (AD) continuum stressed the role of biomarker information. More importantly, such information might be critical to predict those mild cognitive impairment (MCI) patients at a higher risk of conversion to AD. Usually, follow-up studies utilize a reduced number of potential markers although the conversion phenomenon may be deemed as multifactorial in essence. In addition, not only biological but also cognitive markers may play an important role. Considering this background, we investigated the role of cognitive reserve, cognitive performance in neuropsychological testing, hippocampal volumes, APOE genotype, and magnetoencephalography power sources to predict the conversion to AD in a sample of 33 MCI patients. MCIs were followed up during a 2-year period and divided into two subgroups according to their outcome: The “stable” MCI group (sMCI, 21 subjects) and the “progressive” MCI group (pMCI, 12 subjects). Baseline multifactorial information was submitted to a hierarchical logistic regression analysis to build a predictive model of conversion to AD. Results indicated that the combination of left hippocampal volume, occipital cortex theta power, and clock drawing copy subtest scores predicted conversion to AD with a 100% of sensitivity and 94.7% of specificity. According to these results it might be suggested that anatomical, cognitive, and neurophysiological markers may be considered as “first order” predictors of progression to AD, while APOE or cognitive reserve proxies might play a more secondary role.
  • Item
    Hypersynchronization in mild cognitive impairment: the ‘X’ model
    (Brain, 2019) Pusil Arce, Sandra Angélica; López García, María Eugenia; Cuesta Prieto, Pablo; Bruña Fernández, Ricardo; Pereda, Ernesto; Maestu Unturbe, Fernando
    Hypersynchronization has been proposed as a synaptic dysfunction biomarker in the Alzheimer's disease continuum, reflecting the alteration of the excitation/inhibition balance. While animal models have verified this idea extensively, there is still no clear evidence in humans. Here we test this hypothesis, evaluating the risk of conversion from mild cognitive impairment (MCI) to Alzheimer's disease in a longitudinal study. We compared the functional resting state eyes-closed magnetoencephalographic networks of 54 patients with MCI who were followed-up every 6 months. According to their clinical outcome, they were split into: (i) the 'progressive' MCI (n = 27) group; and (ii) the 'stable' MCI group (n = 27). They did not differ in gender or educational level. For all participants, two magnetoencephalographic recordings were acquired. Functional connectivity was evaluated using the phase locking value. To extract the functional connectivity network with significant changes between both magnetoencephalographic recordings, we evaluated the functional connectivity ratio, defined as functional connectivity post-/pre-condition, in a network-based statistical model with an ANCOVA test with age as covariate. Two significant networks were found in the theta and beta bands, involving fronto-temporal and fronto-occipital connections, and showing a diminished functional connectivity ratio in the progressive MCI group. These topologies were then evaluated at each condition showing that at baseline, patients with progressive MCI showed higher synchronization than patients with stable MCI, while in the post-condition this pattern was reversed. These results may be influenced by two main factors in the post-condition: the increased synchrony in the stable MCI patients and the network failure in the progressive MCI patients. These findings may be explained as an 'X' form model where the hypersynchrony predicts conversion, leading subsequently to a network breakdown in progressive MCI. Patients with stable MCI showed an opposite phenomenon, which could indicate that they were a step beyond in the Alzheimer's disease continuum. This model would be able to predict the risk for the conversion to dementia in MCI patients.