RESUMEN
A prominent finding of postmortem and molecular imaging studies on Alzheimer's disease (AD) is the accumulation of neuropathological proteins in brain regions of the default mode network (DMN). Molecular models suggest that the progression of disease proteins depends on the directionality of signaling pathways. At network level, effective connectivity (EC) reflects directionality of signaling pathways. We hypothesized a specific pattern of EC in the DMN of patients with AD, related to cognitive impairment. Metabolic connectivity mapping is a novel measure of EC identifying regions of signaling input based on neuroenergetics. We simultaneously acquired resting-state functional MRI and FDG-PET data from patients with early AD (n = 35) and healthy subjects (n = 18) on an integrated PET/MR scanner. We identified two distinct subnetworks of EC in the DMN of healthy subjects: an anterior part with bidirectional EC between hippocampus and medial prefrontal cortex and a posterior part with predominant input into medial parietal cortex. Patients had reduced input into the medial parietal system and absent input from hippocampus into medial prefrontal cortex (p < 0.05, corrected). In a multiple linear regression with unimodal imaging and EC measures (F4,25 = 5.63, p = 0.002, r2 = 0.47), we found that EC (ß = 0.45, p = 0.012) was stronger associated with cognitive deficits in patients than any of the PET and fMRI measures alone. Our approach indicates specific disruptions of EC in the DMN of patients with AD and might be suitable to test molecular theories about downstream and upstream spreading of neuropathology in AD.
Asunto(s)
Enfermedad de Alzheimer/diagnóstico por imagen , Corteza Cerebral , Conectoma/métodos , Red en Modo Predeterminado , Imagen por Resonancia Magnética/métodos , Imagen Multimodal/métodos , Tomografía de Emisión de Positrones/métodos , Anciano , Enfermedad de Alzheimer/metabolismo , Enfermedad de Alzheimer/fisiopatología , Corteza Cerebral/diagnóstico por imagen , Corteza Cerebral/metabolismo , Corteza Cerebral/fisiopatología , Red en Modo Predeterminado/diagnóstico por imagen , Red en Modo Predeterminado/metabolismo , Red en Modo Predeterminado/fisiopatología , HumanosRESUMEN
Directionality of signaling among brain regions provides essential information about human cognition and disease states. Assessing such effective connectivity (EC) across brain states using functional magnetic resonance imaging (fMRI) alone has proven difficult, however. We propose a novel measure of EC, termed metabolic connectivity mapping (MCM), that integrates undirected functional connectivity (FC) with local energy metabolism from fMRI and positron emission tomography (PET) data acquired simultaneously. This method is based on the concept that most energy required for neuronal communication is consumed postsynaptically, i.e., at the target neurons. We investigated MCM and possible changes in EC within the physiological range using "eyes open" versus "eyes closed" conditions in healthy subjects. Independent of condition, MCM reliably detected stable and bidirectional communication between early and higher visual regions. Moreover, we found stable top-down signaling from a frontoparietal network including frontal eye fields. In contrast, we found additional top-down signaling from all major clusters of the salience network to early visual cortex only in the eyes open condition. MCM revealed consistent bidirectional and unidirectional signaling across the entire cortex, along with prominent changes in network interactions across two simple brain states. We propose MCM as a novel approach for inferring EC from neuronal energy metabolism that is ideally suited to study signaling hierarchies in the brain and their defects in brain disorders.
Asunto(s)
Mapeo Encefálico , Encéfalo/fisiología , Metabolómica , Descanso/fisiología , Encéfalo/diagnóstico por imagen , Femenino , Fluorodesoxiglucosa F18 , Humanos , Imagen por Resonancia Magnética , Masculino , Persona de Mediana Edad , Tomografía de Emisión de Positrones , Corteza Prefrontal/fisiologíaRESUMEN
In comparison to other species, the human brain exhibits one of the highest energy demands relative to body metabolism. It remains unclear whether this heightened energy demand uniformly supports an enlarged brain or if specific signaling mechanisms necessitate greater energy. We hypothesized that the regional distribution of energy demands will reveal signaling strategies that have contributed to human cognitive development. We measured the energy distribution within the brain functional connectome using multimodal brain imaging and found that signaling pathways in evolutionarily expanded regions have up to 67% higher energetic costs than those in sensory-motor regions. Additionally, histology, transcriptomic data, and molecular imaging independently reveal an up-regulation of signaling at G-protein-coupled receptors in energy-demanding regions. Our findings indicate that neuromodulator activity is predominantly involved in cognitive functions, such as reading or memory processing. This study suggests that an up-regulation of neuromodulator activity, alongside increased brain size, is a crucial aspect of human brain evolution.
Asunto(s)
Encéfalo , Conectoma , Humanos , Encéfalo/metabolismo , Cognición/fisiología , Memoria , Imagen por Resonancia Magnética/métodosRESUMEN
BACKGROUND: Peptide Recognition Domains (PRDs) are commonly found in signaling proteins. They mediate protein-protein interactions by recognizing and binding short motifs in their ligands. Although a great deal is known about PRDs and their interactions, prediction of PRD specificities remains largely an unsolved problem. RESULTS: We present a novel approach to identifying these Specificity Determining Residues (SDRs). Our algorithm generalizes earlier information theoretic approaches to coevolution analysis, to become applicable to this problem. It leverages the growing wealth of binding data between PRDs and large numbers of random peptides, and searches for PRD residues that exhibit strong evolutionary covariation with some positions of the statistical profiles of bound peptides. The calculations involve only information from sequences, and thus can be applied to PRDs without crystal structures. We applied the approach to PDZ, SH3 and kinase domains, and evaluated the results using both residue proximity in co-crystal structures and verified binding specificity maps from mutagenesis studies. DISCUSSION: Our predictions were found to be strongly correlated with the physical proximity of residues, demonstrating the ability of our approach to detect physical interactions of the binding partners. Some high-scoring pairs were further confirmed to affect binding specificity using previous experimental results. Combining the covariation results also allowed us to predict binding profiles with higher reliability than two other methods that do not explicitly take residue covariation into account. CONCLUSIONS: The general applicability of our approach to the three different domain families demonstrated in this paper suggests its potential in predicting binding targets and assisting the exploration of binding mechanisms.
Asunto(s)
Algoritmos , Aminoácidos/metabolismo , Teoría de la Información , Péptidos/química , Péptidos/metabolismo , Estructura Terciaria de Proteína , Humanos , Modelos Moleculares , Mutagénesis/genética , Posición Específica de Matrices de Puntuación , Unión Proteica , Reproducibilidad de los ResultadosRESUMEN
In Alzheimer's disease (AD), amyloid-ß (Aß) pathology and intrinsic functional connectivity (iFC) interact. Across stages of AD, we expected individual spatial correspondence of Aß and iFC to reveal both Aß accumulation and its detrimental effects on iFC. We used resting-state functional magnetic imaging and Aß imaging in a cross-sectional sample of 90 subjects across stages of AD and healthy older adults. Global and local correspondence of Aß and iFC were assessed within the posterior default mode network (pDMN) by within-subject voxel-wise correlations. Beginning at preclinical stages, global Aß-iFC correspondence was positive for the whole pDMN, showing that Aß accumulates in areas of high connectivity, and reached a plateau at prodromal stages. Starting at preclinical stages, local correspondence was negative in network centers, indicating that Aß reduces connectivity of the pDMN as a function of local plaque concentration, and peaked at prodromal stages. Positive global correspondence suggests that Aß accumulation progresses along iFC, with this effect starting in preclinical stages, and being constant along clinical periods. Negative local correspondence suggests detrimental effects of Aß on iFC in network centers, starting at preclinical stages, and peaking when first symptoms appear. Data reveal a complex trajectory of Aß and iFC correspondence, affecting both Aß accumulation and iFC impairments.