Age-related alterations of brain metabolic network based on [18F]FDG-PET of rats

Electroacupuncture modulates abnormal brain connectivity after ischemia reperfusion injury in rats: A graph theory-based approach

BACKGROUND

Electroacupuncture (EA) has been shown to facilitate brain plasticity-related functional recovery following ischemic stroke. The functional magnetic resonance imaging technique can be used to determine the range and mode of brain activation. After stroke, EA has been shown to alter brain connectivity, whereas EA's effect on brain network topology properties remains unclear. An evaluation of EA's effects on global and nodal topological properties in rats with ischemia reperfusion was conducted in this study.

METHODS AND RESULTS

There were three groups of adult male Sprague-Dawley rats: sham-operated group (sham group), middle cerebral artery occlusion/reperfusion (MCAO/R) group, and MCAO/R plus EA (MCAO/R + EA) group. The differences in global and nodal topological properties, including shortest path length, global efficiency, local efficiency, small-worldness index, betweenness centrality (BC), and degree centrality (DC) were estimated. Graphical network analyses revealed that, as compared with the sham group, the MCAO/R group demonstrated a decrease in BC value in the right ventral hippocampus and increased BC in the right substantia nigra, accompanied by increased DC in the left nucleus accumbens shell (AcbSh). The BC was increased in the right hippocampus ventral and decreased in the right substantia nigra after EA intervention, and MCAO/R + EA resulted in a decreased DC in left AcbSh compared to MCAO/R.

CONCLUSION

The results of this study provide a potential basis for EA to promote cognitive and motor function recovery after ischemic stroke.

Brain metabolic network covariance and aging in a mouse model of Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD), the leading cause of dementia worldwide, represents a human and financial impact for which few effective drugs exist to treat the disease. Advances in molecular imaging have enabled assessment of cerebral glycolytic metabolism, and network modeling of brain region have linked to alterations in metabolic activity to AD stage.

METHODS

We performed 18 F-FDG positron emission tomography (PET) imaging in 4-, 6-, and 12-month-old 5XFAD and littermate controls (WT) of both sexes and analyzed region data via brain metabolic covariance analysis.

RESULTS

The 5XFAD model mice showed age-related changes in glucose uptake relative to WT mice. Analysis of community structure of covariance networks was different across age and sex, with a disruption of metabolic coupling in the 5XFAD model.

DISCUSSION

The current study replicates clinical AD findings and indicates that metabolic network covariance modeling provides a translational tool to assess disease progression in AD models.

Resting-State Functional MRI and PET Imaging as Noninvasive Tools to Study (Ab)Normal Neurodevelopment in Humans and Rodents

Neurodevelopmental disorders (NDDs) are a group of complex neurologic and psychiatric disorders. Functional and molecular imaging techniques, such as resting-state functional magnetic resonance imaging (rs-fMRI) and positron emission tomography (PET), can be used to measure network activity noninvasively and longitudinally during maturation in both humans and rodent models. Here, we review the current knowledge on rs-fMRI and PET biomarkers in the study of normal and abnormal neurodevelopment, including intellectual disability (ID; with/without epilepsy), autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD), in humans and rodent models from birth until adulthood, and evaluate the cross-species translational value of the imaging biomarkers. To date, only a few isolated studies have used rs-fMRI or PET to study (abnormal) neurodevelopment in rodents during infancy, the critical period of neurodevelopment. Further work to explore the feasibility of performing functional imaging studies in infant rodent models is essential, as rs-fMRI and PET imaging in transgenic rodent models of NDDs are powerful techniques for studying disease pathogenesis, developing noninvasive preclinical imaging biomarkers of neurodevelopmental dysfunction, and evaluating treatment-response in disease-specific models.

Long-term dietary folic acid supplementation attenuated aging-induced hippocampus atrophy and promoted glucose uptake in 25-month-old rats with cognitive decline

The brain has high energy demand making it sensitive to changes in energy fuel supply. Aging shrinks brain volume, decreases glucose uptake availability of the brain, and finally, causes cognitive dysfunction. Folic acid supplementation delayed cognitive decline and neurodegeneration. However, whether folic acid affects brain energy metabolism and structural changes is unclear. The study aimed to determine if long-term dietary folic acid supplementation could alleviate age-related cognitive decline by attenuating hippocampus atrophy and promoting brain glucose uptake in Sprague-Dawley (SD) rats. According to folic acid levels in diet, three-month-old male SD rats were randomly divided into four intervention groups for 22 months in equal numbers: folic acid-deficient diet (FA-D) group, folic acid-normal diet (FA-N) group, low folic acid-supplemented diet (FA-L) group, and high folic acid-supplemented diet (FA-H) group. The results showed that serum folate concentrations decreased and serum homocysteine (Hcy) concentrations increased with age, and dietary folic acid supplementation increased serum folate concentrations and decreased Hcy concentrations at 11, 18, and 22 months of intervention. Dietary folic acid supplementation attenuated aging-induced hippocampus atrophy, which was showed by higher fractional anisotropy and lower mean diffusivity in the hippocampus, increased brain ¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG) uptake, then stimulated neuronal survival, and alleviated age-related cognitive decline in SD rats. In conclusion, long-term dietary folic acid supplementation alleviated age-related cognitive decline by attenuating hippocampus atrophy and promoting brain glucose uptake in SD rats.

Brain Metabolic Network Redistribution in Patients with White Matter Hyperintensities on MRI Analyzed with an Individualized Index Derived from 18F-FDG-PET/MRI

OBJECTIVE

Whether metabolic redistribution occurs in patients with white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) is unknown. This study aimed 1) to propose a measure of the brain metabolic network for an individual patient and preliminarily apply it to identify impaired metabolic networks in patients with WMHs, and 2) to explore the clinical and imaging features of metabolic redistribution in patients with WMHs.

MATERIALS AND METHODS

This study included 50 patients with WMHs and 70 healthy controls (HCs) who underwent 18F-fluorodeoxyglucose-positron emission tomography/MRI. Various global property parameters according to graph theory and an individual parameter of brain metabolic network called "individual contribution index" were obtained. Parameter values were compared between the WMH and HC groups. The performance of the parameters in discriminating between the two groups was assessed using the area under the receiver operating characteristic curve (AUC). The correlation between the individual contribution index and Fazekas score was assessed, and the interaction between age and individual contribution index was determined. A generalized linear model was fitted with the individual contribution index as the dependent variable and the mean standardized uptake value (SUVmean) of nodes in the whole-brain network or seven classic functional networks as independent variables to determine their association.

RESULTS

The means ± standard deviations of the individual contribution index were (0.697 ± 10.9) × 10-3 and (0.0967 ± 0.0545) × 10-3 in the WMH and HC groups, respectively (p < 0.001). The AUC of the individual contribution index was 0.864 (95% confidence interval, 0.785-0.943). A positive correlation was identified between the individual contribution index and the Fazekas scores in patients with WMHs (r = 0.57, p < 0.001). Age and individual contribution index demonstrated a significant interaction effect on the Fazekas score. A significant direct association was observed between the individual contribution index and the SUVmean of the limbic network (p < 0.001).

CONCLUSION

The individual contribution index may demonstrate the redistribution of the brain metabolic network in patients with WMHs.