Measuring cortical connectivity in Alzheimer's disease as a brain neural network pathology: Toward clinical applications

Objectives: The objective was to review the literature on diffusion tensor imaging as well as resting-state functional magnetic resonance imaging and electroencephalography (EEG) to unveil neuroanatomical and neurophysiological substrates of Alzheimer’s disease (AD) as a brain neural network pathology affecting structural and functional cortical connectivity underlying human cognition. Methods: We reviewed papers registered in PubMed and other scientific repositories on the use of these techniques in amnesic mild cognitive impairment (MCI) and clinically mild AD dementia patients compared to cognitively intact elderly individuals (Controls). Results: Hundreds of peer-reviewed (cross-sectional and longitudinal) papers have shown in patients with MCI and mild AD compared to Controls (1) impairment of callosal (splenium), thalamic, and anterior–posterior white matter bundles; (2) reduced correlation of resting state blood oxygen level-dependent activity across several intrinsic brain circuits including default mode and attention-related networks; and (3) abnormal power and functional coupling of resting state cortical EEG rhythms. Clinical applications of these measures are still limited. Conclusions: Structural and functional (in vivo) cortical connectivity measures represent a reliable marker of cerebral reserve capacity and should be used to predict and monitor the evolution of AD and its relative impact on cognitive domains in pre-clinical, prodromal, and dementia stages of AD. (JINS, 2016, 22, 138–163

ApoE4 effects on the structural covariance brain networks topology in Mild Cognitive Impairment

The Apolipoprotein E isoform E4 (ApoE4) is consistently associated with an elevated risk of developing late-onset Alzheimer's Disease (AD). However, little is known about his potential genetic modulation on the structural covariance brain networks during prodromal stages like Mild Cognitive Impairment (MCI). The covariance phenomenon is based on the observation that regions correlating in morphometric descriptors are often part of the same brain system. In a first study, I assessed the ApoE4-related changes on the brain network topology in 256 MCI patients, using the regional cortical thickness to define the covariance network. The cross-sectional sample selected from the ADNI database was subdivided into ApoE4-positive (Carriers) and negative (non-Carriers). At the group-level, the results showed a significant decrease in characteristic path length, clustering index, local efficiency, global connectivity, modularity, and increased global efficiency for Carriers compared to non-Carriers. Overall, I found that ApoE4 in MCI shaped the topological organization of cortical thickness covariance networks. In the second project, I investigated the impact of ApoE4 on the single-subject gray matter networks in a sample of 200 MCI from the ADNI database. The patients were classified based on clinical outcome (stable MCI versus converters to AD) and ApoE4 status (Carriers versus non-Carriers). The effects of ApoE4 and disease progression on the network measures at baseline and rate of change were explored. The topological network attributes were correlated with AD biomarkers. The main findings showed that gray matter network topology is affected independently by ApoE4 and the disease progression (to AD) in late-MCI. The network measures alterations showed a more random organization in Carriers compared to non-Carriers. Finally, as additional research, I investigated whether a network-based approach combined with the graph theory is able to detect cerebrovascular reactivity (CVR) changes in MCI. Our findings suggest that this experimental approach is more sensitive to identifying subtle cerebrovascular alterations than the classical experimental designs. This study paves the way for a future investigation on the ApoE4-cerebrovascular interaction effects on the brain networks during AD progression. In summary, my thesis results provide evidence of the value of the structural covariance brain network measures to capture subtle neurodegenerative changes associated with ApoE4 in MCI. Together with other biomarkers, these variables may help predict disease progression, providing additional reliable intermediate phenotypes

Neural mechanisms of cognitive reserve in Alzheimer's disease

Alzheimer’s disease (AD) is the most common cause of age-related dementia, where neuropathological changes develop gradually over years before the onset of dementia symptoms. Yet, despite the progression of AD pathology, the decline in cognitive abilities such as episodic memory can be relatively slow. A slower decline of cognition and delayed onset of dementia relative to the progression of neuropathology has been associated with particular intellectual and lifestyle factors such as more years of education and IQ. Thus education and IQ are seen as protective factors that are associated with an increased ability to cope with brain pathology, i.e. cognitive reserve. While numerous studies showed that education, IQ and other lifestyle factors are associated with relatively high cognitive abilities in AD, little is known about the underlying brain mechanisms of reserve. Most previous studies tested the association between protective factors such as education or IQ and differences in brain structure and function in order to identify brain mechanisms underlying reserve. Since such protective factors are global in nature and unspecific with regard to reserve, the results were highly variable. So far, there is a lack of knowledge of brain features that are associated with a higher ability to maintain cognition in the face of AD pathology. The overall aim of this dissertation was to test a priori selected functional network features that may underlie cognitive reserve. We focused on resting-state functional networks, and in particular the fronto-parietal control network as correlate of cognitive reserve. Such functional networks are thought to be composed of brain regions that are co-activated during a particular task, where the interaction between brain regions may be critical to support cognitive function. During task-free resting-state periods, the different and often distant brain regions of such network show correlated activity, i.e. functional connectivity. For the fronto-parietal control network, and in particular its globally connected hub in the left frontal cortex (LFC), higher resting-state connectivity has been previously shown to be associated with higher cognitive abilities as well as higher education and IQ, i.e. protective factors associated with reserve. Since that network and its LFC hub are relatively spared in AD, in contrast to more posterior parietal networks, we investigated whether higher connectivity of the fronto-parietal control network is associated with higher reserve in AD. We argued that the fronto-parietal control network is relatively stable during the initial stages of AD and may thus be well posited to subserve reserve in AD. In contrast, networks like the default mode network (DMN) that cover midline brain structures including the medial frontal lobe and the posterior cingulate may be highly vulnerable to AD pathology, given the previous observations of altered DMN connectivity and posterior parietal FDG-PET hypometabolism in AD. In particular, the resting-state connectivity between the DMN and the dorsal attention network (DAN) may be predictive of lower episodic memory in AD. Both networks interact in a competitive (i.e. anti-correlated) way during task and resting-state, which is critical for cognitive processes such as episodic memory. In a first step, we tested whether the resting-state connectivity between the DMN and theDAN (i.e. anti-correlated activity) is associated with lower episodic memory in subjects with amnestic mild cognitive impairment (MCI), i.e. subjects at increased risk to convertto AD dementia. Furthermore, we tested whether protective factors such as higher education moderate the association between the DMN-DAN anti-correlation andcognition. Here, the DMN-DAN anti-correlation was a measure of AD relatedpathological change rather than a substrate of reserve.We could show in two independent samples of patients at risk of AD dementia that a weaker DMN-DAN anti-correlation was associated with lower episodic memory, where the decrements in episodic memory were however weaker in subjects with higher education or IQ (interaction DMN-DAN x education/IQ). These results suggest that MCI subjects with higher protective factors (education, IQ) maintain episodic memory relatively well at a given level of AD-related brain changes. In the second step, we sought to identify those network differences that support cognitive reserve, i.e. that may explain the association between higher education and milder cognitive impairment in AD. Here, we could show that greater resting-state fMRI assessed global connectivity of the LFC, i.e. a key hub of the fronto-parietal control network, was associated with greater education and attenuated effects of neurodegeneration (measured by parietal FDG-PET hypometabolism) on memory in prodromal AD. Together, these results support the idea that global connectivity of a fronto-parietal control network hub supports cognitive reserve in AD. Based on this finding, we developed a novel restingstate fMRI index of fronto-parietal control network connectivity as a functional imaging marker of cognitive reserve. This marker is highly correlated with education and may thus be used as an imaging-based index of cognitive reserve. Together, our results provide for the first time evidence that cognitive reserve in AD is supported by higher functional connectivity of the fronto-parietal control network, in particular its LFC hub

Neural mechanisms of cognitive reserve in Alzheimer's disease

Alzheimer’s disease (AD) is the most common cause of age-related dementia, where neuropathological changes develop gradually over years before the onset of dementia symptoms. Yet, despite the progression of AD pathology, the decline in cognitive abilities such as episodic memory can be relatively slow. A slower decline of cognition and delayed onset of dementia relative to the progression of neuropathology has been associated with particular intellectual and lifestyle factors such as more years of education and IQ. Thus education and IQ are seen as protective factors that are associated with an increased ability to cope with brain pathology, i.e. cognitive reserve. While numerous studies showed that education, IQ and other lifestyle factors are associated with relatively high cognitive abilities in AD, little is known about the underlying brain mechanisms of reserve. Most previous studies tested the association between protective factors such as education or IQ and differences in brain structure and function in order to identify brain mechanisms underlying reserve. Since such protective factors are global in nature and unspecific with regard to reserve, the results were highly variable. So far, there is a lack of knowledge of brain features that are associated with a higher ability to maintain cognition in the face of AD pathology. The overall aim of this dissertation was to test a priori selected functional network features that may underlie cognitive reserve. We focused on resting-state functional networks, and in particular the fronto-parietal control network as correlate of cognitive reserve. Such functional networks are thought to be composed of brain regions that are co-activated during a particular task, where the interaction between brain regions may be critical to support cognitive function. During task-free resting-state periods, the different and often distant brain regions of such network show correlated activity, i.e. functional connectivity. For the fronto-parietal control network, and in particular its globally connected hub in the left frontal cortex (LFC), higher resting-state connectivity has been previously shown to be associated with higher cognitive abilities as well as higher education and IQ, i.e. protective factors associated with reserve. Since that network and its LFC hub are relatively spared in AD, in contrast to more posterior parietal networks, we investigated whether higher connectivity of the fronto-parietal control network is associated with higher reserve in AD. We argued that the fronto-parietal control network is relatively stable during the initial stages of AD and may thus be well posited to subserve reserve in AD. In contrast, networks like the default mode network (DMN) that cover midline brain structures including the medial frontal lobe and the posterior cingulate may be highly vulnerable to AD pathology, given the previous observations of altered DMN connectivity and posterior parietal FDG-PET hypometabolism in AD. In particular, the resting-state connectivity between the DMN and the dorsal attention network (DAN) may be predictive of lower episodic memory in AD. Both networks interact in a competitive (i.e. anti-correlated) way during task and resting-state, which is critical for cognitive processes such as episodic memory. In a first step, we tested whether the resting-state connectivity between the DMN and theDAN (i.e. anti-correlated activity) is associated with lower episodic memory in subjects with amnestic mild cognitive impairment (MCI), i.e. subjects at increased risk to convertto AD dementia. Furthermore, we tested whether protective factors such as higher education moderate the association between the DMN-DAN anti-correlation andcognition. Here, the DMN-DAN anti-correlation was a measure of AD relatedpathological change rather than a substrate of reserve.We could show in two independent samples of patients at risk of AD dementia that a weaker DMN-DAN anti-correlation was associated with lower episodic memory, where the decrements in episodic memory were however weaker in subjects with higher education or IQ (interaction DMN-DAN x education/IQ). These results suggest that MCI subjects with higher protective factors (education, IQ) maintain episodic memory relatively well at a given level of AD-related brain changes. In the second step, we sought to identify those network differences that support cognitive reserve, i.e. that may explain the association between higher education and milder cognitive impairment in AD. Here, we could show that greater resting-state fMRI assessed global connectivity of the LFC, i.e. a key hub of the fronto-parietal control network, was associated with greater education and attenuated effects of neurodegeneration (measured by parietal FDG-PET hypometabolism) on memory in prodromal AD. Together, these results support the idea that global connectivity of a fronto-parietal control network hub supports cognitive reserve in AD. Based on this finding, we developed a novel restingstate fMRI index of fronto-parietal control network connectivity as a functional imaging marker of cognitive reserve. This marker is highly correlated with education and may thus be used as an imaging-based index of cognitive reserve. Together, our results provide for the first time evidence that cognitive reserve in AD is supported by higher functional connectivity of the fronto-parietal control network, in particular its LFC hub

A Novel Joint Brain Network Analysis Using Longitudinal Alzheimer's Disease Data.

There is well-documented evidence of brain network differences between individuals with Alzheimer's disease (AD) and healthy controls (HC). To date, imaging studies investigating brain networks in these populations have typically been cross-sectional, and the reproducibility of such findings is somewhat unclear. In a novel study, we use the longitudinal ADNI data on the whole brain to jointly compute the brain network at baseline and one-year using a state of the art approach that pools information across both time points to yield distinct visit-specific networks for the AD and HC cohorts, resulting in more accurate inferences. We perform a multiscale comparison of the AD and HC networks in terms of global network metrics as well as at the more granular level of resting state networks defined under a whole brain parcellation. Our analysis illustrates a decrease in small-worldedness in the AD group at both the time points and also identifies more local network features and hub nodes that are disrupted due to the progression of AD. We also obtain high reproducibility of the HC network across visits. On the other hand, a separate estimation of the networks at each visit using standard graphical approaches reveals fewer meaningful differences and lower reproducibility

Loss of brain inter-frequency hubs in Alzheimer's disease

Alzheimer's disease (AD) causes alterations of brain network structure and function. The latter consists of connectivity changes between oscillatory processes at different frequency channels. We proposed a multi-layer network approach to analyze multiple-frequency brain networks inferred from magnetoencephalographic recordings during resting-states in AD subjects and age-matched controls. Main results showed that brain networks tend to facilitate information propagation across different frequencies, as measured by the multi-participation coefficient (MPC). However, regional connectivity in AD subjects was abnormally distributed across frequency bands as compared to controls, causing significant decreases of MPC. This effect was mainly localized in association areas and in the cingulate cortex, which acted, in the healthy group, as a true inter-frequency hub. MPC values significantly correlated with memory impairment of AD subjects, as measured by the total recall score. Most predictive regions belonged to components of the default-mode network that are typically affected by atrophy, metabolism disruption and amyloid-beta deposition. We evaluated the diagnostic power of the MPC and we showed that it led to increased classification accuracy (78.39%) and sensitivity (91.11%). These findings shed new light on the brain functional alterations underlying AD and provide analytical tools for identifying multi-frequency neural mechanisms of brain diseases.Comment: 27 pages, 6 figures, 3 tables, 3 supplementary figure

Redes cerebrales en quejas subjetivas de memoria y deterioro cognitivo leve: caracterización de las etapas de pre-demencia mediante magnetoencefalografía

Tesis de la Universidad Complutense de Madrid, Facultad de Psicología, leída el 22/03/2018. Tesis formato europeo (compendio de artículos)La demencia es un cuadro que puede ser originado por múltiples causas, produciendo un deterioro cognitivo muy marcado y limitando la independencia del paciente. La causa más común de demencia es la Enfermedad de Alzheimer (EA) que representa aproximadamente el 60% de los casos totales. Aunque existen numerosos factores que parecen modular el riesgo de desarrollar EA tales como factores genéticos (APOE, PS1, etc.) o variables relacionadas con el estilo de vida (estudios, ocupación, dieta, etc.), la edad es sin duda la variable más influyente y el mayor factor de riesgo ante la aparición de la EA. Por este motivo, el número de personas mayores afectadas por esta enfermedad no ha parado de aumentar durante las últimas décadas, y se espera que aumente su incidencia aún más. Debido al fracaso generalizado de los ensayos farmacológicos, numerosos esfuerzos en investigación se centran ahora en la detección temprana de la EA. El curso de la EA es lento e insidioso, y la acumulación de neuropatología puede comenzar hasta 15 años antes de su diagnóstico. A lo largo de esta etapa preclínica los pacientes atraviesan un estadio conocido como deterioro cognitivo leve (DCL). Esta etapa se caracteriza por alteraciones en uno o varios dominios cognitivos que no genera aún graves alteraciones del funcionamiento diario. Este estadio está altamente asociado al desarrollo posterior de EA y por tanto se considera bajo determinadas condiciones una etapa prodrómica de la enfermedad. Las personas mayores con DCL suelen presentar alteraciones a nivel cerebral o metabólico característicos de la EA, tales como atrofia cortical, alteraciones sinápticas o acumulación de proteínas relacionadas con la fisiopatología de la EA. La literatura científica reciente ha descrito una etapa anterior incluso al DCL que podría asociarse al desarrollo de demencia futuro. Las quejas subjetivas de memoria (QSM) se caracterizarían por la presencia de un sentimiento subjetivo de deterioro cognitivo en ausencia de afectación objetiva, es decir, la evaluación neuropsicológica de estas personas mayores se encuentra en el rango normal. Sin embargo, el estado de la actividad cerebral en esta etapa, o su integridad estructural aún no ha sido apenas descrito. Existen resultados contradictorios con respecto a si la presencia de QSM en personas mayores se asocia a un riesgo más elevado de desarrollar demencia. Además, mientras algunos estudios reportan alteraciones a nivel cerebral compatibles con EA en esta etapa, otros no encuentran tales signos. El objetivo fundamental de esta tesis es la caracterización de las alteraciones en las redes cerebrales en personas mayores sanas, personas mayores con QSM y personas mayores con DCL. El estado actual de la literatura nos permite anticipar la presencia de alteraciones cerebrales relacionadas con EA en el grupo con DCL, sin embargo este trabajo pretende estudiar si dichas alteraciones, o formas más sutiles, se encuentran presentes en el grupo con QSM. Esto nos permitirá en primer lugar clarificar si las QSM tienen alguna relevancia clínica y si se encuentran asociadas a cambios objetivos en la actividad cerebral. Además, se podrá describir el curso exacto de las alteraciones que tienen lugar a lo largo de las etapas preclínicas en la EA gracias a la inclusión del grupo con DCL, caracterizando así en cada estudio las dos etapas que anteceden a la EA descritas a día de hoy...Dementia is a clinical entity producing major cognitive impairment that interferes with daily living activities that can be caused by a variety of conditions. Among them, Alzheimer´s Disease (AD) represents around a 60% of the total dementia cases. AD risk is modulated by multiple variables such as genotype (APOE, PS1, etc.) or lifestyle variables (studies, occupation, dietary patterns, etc.), although age is the most crucial risk factor for AD development. As a consequence, the number of AD patients has rapidly grown over the last few decades and is expected to increase even more dramatically in the near future. Given the poor results obtained in pharmacological trials to cure or slow AD progression, early AD detection is receiving increasing research efforts over the last few years. Considering the slow and insidious progression of AD, brain pathology starts accumulating in the brain as soon as 15 years before clinical symptoms are severe enough to establish an AD diagnostic. Before reaching AD dementia, patients develop mild cognitive impairment (MCI). This stage is characterized by the presence of a significant cognitive impairment affecting one or more domains. However, this cognitive decline does not significantly limit patients’ daily functioning. MCI patients are known to show increased conversion rates to AD with respect to healthy elders and thus this stage is commonly accepted as a prodromal stage of AD according to recent MCI criteria. MCI patients are known to exhibit AD-like brain and metabolic alterations such as cortical atrophy or AD-related protein accumulation. Recent scientific literature has described a stage preceding MCI which could be associated with future dementia development. Subjective cognitive decline is defined by the presence of a subjective feeling of cognitive worsening in the absence of objective impairment in classical neuropsychological assessment. However, the integrity of brain activity or structure has been scarcely described yet. Furthermore, there exist some contradictory results regarding whether the presence of cognitive concerns is truly related to increased dementia risk. In the same vein, some studies have found brain alterations in SCD patients resembling of those associated with AD while others failed to find such signs. The main objective of this thesis is characterizing brain network alterations in healthy elders, elders with SCD and elders with MCI. The current state-of-the-art lets us anticipate the presence of brain disruption in the MCI group, nonetheless, this work aims to provide evidence of whether similar alterations are already present in the SCD stage. The results presented in this thesis will clarify the clinical relevance of SCD by discerning whether cognitive concerns are truly mediated by network disruption or not. Moreover, the exact course and development of electrophysiological brain alterations during the preclinical stages of the disease will be described by including also MCI patients. By including these three groups we will be able to characterize brain function in the different AD preclinical stages considered in current literature...Fac. de PsicologíaTRUEunpu

Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset