Person:
Fernández Lucas, Alberto Amable

First Name

Alberto Amable

Last Name

Fernández Lucas

URI

https://hdl.handle.net/20.500.14352/79505

Affiliation

Universidad Complutense de Madrid

Faculty / Institute

Medicina

Department

Medicina Legal, Psiquiatría y Patología

Area

Psiquiatría

Identifiers

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Now showing 1 - 10 of 28

Influence of the APOE ε4 allele and mild cognitive impairment diagnosis in the disruption of the MEG resting state functional connectivity in sources space
(Journal of Alzheimer's Disease, 2015) Cuesta Prieto, Pablo; Garcés, Pilar; Castellanos, Nazareth P; López García, María Eugenia; Aurtenetxe, Sara; Bajo, Ricardo; Pineda-Pardo, José Angel; Bruña Fernández, Ricardo; Marín, Antonio García; Delgado Losada, María Luisa; Barabash Bustelo, Ana; Ancín, Inés; Cabranes Díaz, José Antonio; Fernández Lucas, Alberto Amable; del Pozo, Francisco; Sancho Ruiz, Miguel; Marcos Dolado, Alberto; Nakamura, Akinori; Maestu Unturbe, Fernando
The apolipoprotein E (APOE) ε4 allele constitutes the major genetic risk for the development of late onset Alzheimer's disease (AD). However, its influence on the neurodegeneration that occurs in early AD remains unresolved. In this study, the resting state magnetoencephalography(MEG) recordings were obtained from 27 aged healthy controls and 36 mild cognitive impairment (MCI) patients. All participants were divided into carriers and non-carriers of the ε4 allele. We have calculated the functional connectivity (FC) in the source space along brain regions estimated using the Harvard-Oxford atlas and in the classical bands. Then, a two way ANOVA analysis (diagnosis and APOE) was performed in each frequency band. The diagnosis effect consisted of a diminished FC within the high frequency bands in the MCI patients, affecting medial temporal and parietal regions. The APOE effect produced a decreased long range FC in delta band in ε4 carriers. Finally, the interaction effect showed that the FC pattern of the right frontal-temporal region could be reflecting a compensatory/disruption process within the ε4 allele carriers. Several of these results correlated with cognitive decline and neuropsychological performance. The present study characterizes how the APOE ε4 allele and MCI status affect the brain's functional organization by analyzing the FC patterns in MEG resting state in the sources space. Therefore a combination of genetic, neuropsychological, and neurophysiological information might help to detect MCI patients at higher risk of conversion to AD and asymptomatic subjects at higher risk of developing a manifest cognitive deterioration.
Brain oscillatory complexity across the life span
(Clinical Neurophysiology, 2012) Fernández Lucas, Alberto Amable; Zuluaga Arias, María Del Pilar; Abásolo, Daniel; Gómez, Carlos; Serra González, Anahí María; Méndez, María Andreína; Hornero, Roberto
Objective Considering the increasing use of complexity estimates in neuropsychiatric populations, a normative study is critical to define the ‘normal’ behaviour of brain oscillatory complexity across the life span. Method This study examines changes in resting-state magnetoencephalogram (MEG) complexity – quantified with the Lempel–Ziv complexity (LZC) algorithm – due to age and gender in a large sample of 222 (100 males/122 females) healthy participants with ages ranging from 7 to 84 years. Results A significant quadratic (curvilinear) relationship (p < 0.05) between age and complexity was found, with LZC maxima being reached by the sixth decade of life. Once that peak was crossed, complexity values slowly decreased until late senescence. Females exhibited higher LZC values than males, with significant differences in the anterior, central and posterior regions (p < 0.05). Conclusions These results suggest that the evolution of brain oscillatory complexity across the life span might be considered a new illustration of a ‘normal’ physiological rhythm. Significance Previous and forthcoming clinical studies using complexity estimates might be interpreted from a more complete and dynamical perspective. Pathologies not only cause an ‘abnormal’ increase or decrease of complexity values but they actually ‘break’ the ‘normal’ pattern of oscillatory complexity evolution as a function of age.
Physical activity effects on the individual alpha peak frequency of older adults with and without genetic risk factors for Alzheimer’s Disease: A MEG study
(Clinical Neurophysiology, 2018) De Frutos Lucas, Jaisalmer; López Sanz, David; Zuluaga Arias, María Del Pilar; Rodríguez Rojo, Inmaculada Concepción; Cazorla Luna, Raúl; López García, María Eugenia; Delgado Losada, María Luisa; Marcos Dolado, Alberto; Barabash Bustelo, Ana; López Sánchez, Ramón; Maestu Unturbe, Fernando; Fernández Lucas, Alberto Amable
Objective Since a cure for Alzheimer’s Disease (AD) is yet to be discovered, attention has shifted towards prevention. Physical activity (PA) emerged as a notorious lifestyle factor that could influence brain structure and function. The individual alpha peak frequency (IAPF) is a measure that summarizes the spectral content of brain signals and has been proven to be sensitive to both AD pathology and PA interventions. Therefore, our goal was to unravel whether chronic PA modulates IAPF and if APOE ɛ4 carriage moderates this relationship. Methods We analyzed 4-minutes of resting-state magnetoencephalographic recordings from 100 healthy elders that provided self-reported measures of PA, and the IAPF was calculated. Results We found that IAPF was negatively influenced by age and APOE and positively influenced by PA. The effect of PA on IAPF only remained significant for the ɛ4 non-carriers group. Conclusions PA is positively associated to higher IAPF in healthy older adults and could potentially act as a protective factor against cognitive decline. Nevertheless, such effect is non-significant among elders who are more vulnerable to developing AD due to their genetic carriage. Significance This investigation offers the first neurophysiological evidences on the combined effects of APOE genotype and PA in healthy elders.
BDNF Val66Met polymorphism and gamma band disruption in resting state brain functional connectivity: A magnetoencephalography study in cognitively intact older females
(Frontiers in Neuroscience, 2018) Rodríguez Rojo, Inmaculada Concepción; Cuesta Prieto, Pablo; López García, María Eugenia; De Frutos Lucas, Jaisalmer; Bruña Fernández, Ricardo; Pereda de Pablo, Ernesto; Barabash Bustelo, Ana; Montejo, Pedro; Montenegro Peña, María Mercedes; Marcos Dolado, Alberto; López-Higes, Ramón; Fernández Lucas, Alberto Amable; Maestu Unturbe, Fernando
The pathophysiological processes undermining brain functioning decades before the onset of the clinical symptoms associated with dementia are still not well understood. Several heritability studies have reported that the Brain Derived Neurotrophic Factor (BDNF) Val66Met genetic polymorphism could contribute to the acceleration of cognitive decline in aging. This mutation may affect brain functional connectivity (FC), especially in those who are carriers of the BDNF Met allele. The aim of this work was to explore the influence of the BDNF Val66Met polymorphism in whole brain eyes-closed, resting-state magnetoencephalography (MEG) FC in a sample of 36 cognitively intact (CI) older females. All of them were ε3ε3 homozygotes for the apolipoprotein E (APOE) gene and were divided into two subgroups according to the presence of the Met allele: Val/Met group (n = 16) and Val/Val group (n = 20). They did not differ in age, years of education, Mini-Mental State Examination scores, or normalized hippocampal volumes. Our results showed reduced antero-posterior gamma band FC within the Val/Met genetic risk group, which may be caused by a GABAergic network impairment. Despite the lack of cognitive decline, these results might suggest a selective brain network vulnerability due to the carriage of the BDNF Met allele, which is linked to a potential progression to dementia. This neurophysiological signature, as tracked with MEG FC, indicates that age-related brain functioning changes could be mediated by the influence of particular genetic risk factors.
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.
Dipole density of low-frequency and spike magnetic activity: A reliable procedure in presurgical evaluation of temporal lobe epilepsy
(Journal of Clinical Neurophysiology, 2004) Fernández Lucas, Alberto Amable; de Sola, Rafael G.; Amo, Carlos; Turrero Nogués, Agustín; Zuluaga Arias, María Del Pilar; Maestu Unturbe, Fernando; Campo, Pablo; Ortiz, Tomás
Conventional visual analysis and dipole density analysis of magnetoencephalographic data for both spike and low-frequency magnetic activity were compared for presurgical evaluation in temporal lobe epilepsy (TLE) in a sample of 26 drug-resistant operated TLE patients. A series of logistic regression analyses were performed. Dipole density sensitivity was superior to visual localization analysis. Three separated logistic models were calculated for interictal spikes, low-frequency magnetic activity, and the combination of both measures. A combined interictal spike/low-frequency magnetic activity model predicted correctly the operated temporal lobe in all patients. Clear-cut criteria for the probability model are proposed that are valid for 92.3% of cases in the sample. The quantitative approach proposed by this study is an evidence-based model for presurgical evaluation of temporal lobe epilepsy, which improves previous magnetoencephalographic investigations and establishes working clinical criteria for patient evaluation in TLE.
A multivariate model of time to conversion from mild cognitive impairment to Alzheimer’s disease
(GeroScience, 2020) López García, María Eugenia; Turrero Nogués, Agustín; Cuesta Prieto, Pablo; Rodríguez Rojo, Inmaculada Concepción; Barabash Bustelo, Ana; Marcos Dolado, Alberto; Maestu Unturbe, Fernando; Fernández Lucas, Alberto Amable
The present study was aimed at determining which combination of demographic, genetic, cognitive, neurophysiological, and neuroanatomical factors may predict differences in time to progression from mild cognitive impairment (MCI) to Alzheimer’s disease (AD). To this end, a sample of 121 MCIs was followed up during a 5-year period. According to their clinical outcome, MCIs were divided into two subgroups: (i) the “progressive” MCI group (n = 46; mean time to progression 17 ± 9.73 months) and (ii) the “stable” MCIgroup (n = 75; mean time of follow-up 31.37 ± 14.58 months). Kaplan–Meier survival analyses were applied to explore each variable’s relationship with the progression to AD. Once potential predictors were detected, Cox regression analyses were utilized to calculate a parsimonious model to estimate differences in time to progression. The final model included three variables (in order of relevance): left parahippocampal volume (corrected by intracranial volume, LP_ ICV), delayed recall (DR), and left inferior occipital lobe individual alpha peak frequency (LIOL_IAPF). Those MCIs with LP_ICV volume, DR score, and LIOL_IAPF value lower than the defined cutoff had 6 times, 5.5 times, and 3 times higher risk of progression to AD, respectively. Besides, when the categories of the three variables were “unfavorable” (i.e., values below the cutoff), 100% of cases progressed to AD at the end of follow-up. Our results highlighted the relevance of neurophysiological markers as predictors of conversion (LIOL_IAPF) and the importance of multivariate models that combine markers of different nature to predict time to progression from MCI to dementia.
Complexity Changes in Brain Activity in Healthy Ageing: A Permutation Lempel-Ziv Complexity Study of Magnetoencephalograms
(Entropy, 2018) Shumbayawonda, Elizabeth; Tosun, Pinar; Fernández Lucas, Alberto Amable; Hughes, Michael; Abásolo, Daniel
Maturation and ageing, which can be characterised by the dynamic changes in brain morphology, can have an impact on the physiology of the brain. As such, it is possible that these changes can have an impact on the magnetic activity of the brain recorded using magnetoencephalography. In this study changes in the resting state brain (magnetic) activity due to healthy ageing were investigated by estimating the complexity of magnetoencephalogram (MEG) signals. The main aim of this study was to identify if the complexity of background MEG signals changed significantly across the human lifespan for both males and females. A sample of 177 healthy participants (79 males and 98 females aged between 21 and 80 and grouped into 3 categories i.e., early-, mid- and late-adulthood) was used in this investigation. This investigation also extended to evaluating if complexity values remained relatively stable during the 5 min recording. Complexity was estimated using permutation Lempel-Ziv complexity, a recently introduced complexity metric, with a motif length of 5 and a lag of 1. Effects of age and gender were investigated in the MEG channels over 5 brain regions, i.e., anterior, central, left lateral, posterior, and, right lateral, with highest complexity values observed in the signals recorded by the channels over the anterior and central regions of the brain. Results showed that while changes due to age had a significant effect on the complexity of the MEG signals recorded over 5 brain regions, gender did not have a significant effect on complexity values in all age groups investigated. Moreover, although some changes in complexity were observed between the different minutes of recording, due to the small magnitude of the changes it was concluded that practical significance might outweigh statistical significance in this instance. The results from this study can contribute to form a fingerprint of the characteristics of healthy ageing in MEGs that could be useful when investigating changes to the resting state activity due to pathology.
Sex Differences in the Complexity of Healthy Older Adults’ Magnetoencephalograms
(Entropy, 2019) Shumbayawonda, Elizabeth; Abásolo, Daniel; López Sanz, David; Bruña Fernández, Ricardo; Maestú Unturbe, Fernando; Fernández Lucas, Alberto Amable
The analysis of resting-state brain activity recording in magnetoencephalograms (MEGs) with new algorithms of symbolic dynamics analysis could help obtain a deeper insight into the functioning of the brain and identify potential differences between males and females. Permutation Lempel-Ziv complexity (PLZC), a recently introduced non-linear signal processing algorithm based on symbolic dynamics, was used to evaluate the complexity of MEG signals in source space. PLZC was estimated in a broad band of frequencies (2–45 Hz), as well as in narrow bands (i.e., theta (4–8 Hz), alpha (8–12 Hz), low beta (12–20 Hz), high beta (20–30 Hz), and gamma (30–45 Hz)) in a sample of 98 healthy elderly subjects (49 males, 49 female) aged 65–80 (average age of 72.71 ± 4.22 for males and 72.67 ± 4.21 for females). PLZC was significantly higher for females than males in the high beta band at posterior brain regions including the precuneus, and the parietal and occipital cortices. Further statistical analyses showed that higher complexity values over highly overlapping regions than the ones mentioned above were associated with larger hippocampal volumes only in females. These results suggest that sex differences in healthy aging can be identified from the analysis of magnetoencephalograms with novel signal processing methods.
Complexity analysis of spontaneous brain activity in alzheimer disease and mild cognitive impairment: An MEG study
(Alzheimer Disease & Associated Disorders, 2010) Fernández Lucas, Alberto Amable; Hornero, Roberto; Gómez, Carlos; Turrero Nogués, Agustín; Gil Gregorio, Pedro; Matías Santos, Juan; Ortiz, Tomás
Nonlinear analyses have shown that Alzheimer disease (AD) patients' brain activity is characterized by a reduced complexity and connectivity. The aim of this study is to define complexity patterns of mild cognitive impairment (MCI) patients. Whole-head magnetoencephalography recordings were obtained from 18 diagnosed AD patients, 18 MCI patients, and 18 healthy controls during resting conditions. Lempel-Ziv complexity (LZC) values were calculated. MCI patients exhibited intermediary LZC scores between AD patients and controls. A combination of age and posterior LZC scores allowed ADs-MCIs discrimination with 94.4% sensitivity and specificity, whereas no LZC score allowed MCIs---controls discrimination. AD patients and controls showed a parallel tendency to diminished LZC scores as a function of age, but MCI patients did not exhibit such “normal” tendency. Accordingly, anterior LZC scores allowed MCIs-controls discrimination for subjects below 75 years. MCIs exhibited a qualitatively distinct relationship between aging and complexity reduction, with scores higher than controls in older individuals. This fact might be considered a new example of compensatory mechanism in MCI before fully established dementia.