Interregional causal influences of brain metabolic activity reveal the spread of aging effects during normal aging

Brain connectomics: time for a molecular imaging perspective?

In the past two decades brain connectomics has evolved into a major concept in neuroscience. However, the current perspective on brain connectivity and how it underpins brain function relies mainly on the hemodynamic signal of functional magnetic resonance imaging (MRI). Molecular imaging provides unique information inaccessible to MRI-based and electrophysiological techniques. Thus, positron emission tomography (PET) has been successfully applied to measure neural activity, neurotransmission, and proteinopathies in normal and pathological cognition. Here, we position molecular imaging within the brain connectivity framework from the perspective of timeliness, validity, reproducibility, and resolution. We encourage the neuroscientific community to take an integrative approach whereby MRI-based, electrophysiological techniques, and molecular imaging contribute to our understanding of the brain connectome.

The older adult brain is less modular, more integrated, and less efficient at rest: A systematic review of large-scale resting-state functional brain networks in aging

The literature on large-scale resting-state functional brain networks across the adult lifespan was systematically reviewed. Studies published between 1986 and July 2021 were retrieved from PubMed. After reviewing 2938 records, 144 studies were included. Results on 11 network measures were summarized and assessed for certainty of the evidence using a modified GRADE method. The evidence provides high certainty that older adults display reduced within-network and increased between-network functional connectivity. Older adults also show lower segregation, modularity, efficiency and hub function, and decreased lateralization and a posterior to anterior shift at rest. Higher-order functional networks reliably showed age differences, whereas primary sensory and motor networks showed more variable results. The inflection point for network changes is often the third or fourth decade of life. Age effects were found with moderate certainty for within- and between-network altered patterns and speed of dynamic connectivity. Research on within-subject bold variability and connectivity using glucose uptake provides low certainty of age differences but warrants further study. Taken together, these age-related changes may contribute to the cognitive decline often seen in older adults.

Hemodynamic and metabolic correspondence of resting-state voxel-based physiological metrics in healthy adults

Voxel-based physiological (VBP) variables derived from blood oxygen level dependent (BOLD) fMRI time-course variations include: amplitude of low frequency fluctuations (ALFF), fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity (ReHo). Although these BOLD-derived variables can detect between-group (e.g. disease vs control) spatial pattern differences, physiological interpretations are not well established. The primary objective of this study was to quantify spatial correspondences between BOLD VBP variables and PET measurements of cerebral metabolic rate and hemodynamics, being well-validated physiological standards. To this end, quantitative, whole-brain PET images of metabolic rate of glucose (MRGlu; 18FDG) and oxygen (MRO2; 15OO), blood flow (BF; H215O) and blood volume (BV; C15O) were obtained in 16 healthy controls. In the same subjects, BOLD time-courses were obtained for computation of ALFF, fALFF and ReHo images. PET variables were compared pair-wise with BOLD variables. In group-averaged, across-region analyses, ALFF corresponded significantly only with BV (R = 0.64; p < 0.0001). fALFF corresponded most strongly with MRGlu (R = 0.79; p < 0.0001), but also significantly (p < 0.0001) with MRO2 (R = 0.68), BF (R = 0.68) and BV (R=0.68). ReHo performed similarly to fALFF, with significant strong correspondence (p < 0.0001) with MRGlu (R = 0.78), MRO2 (R = 0.54), and, but less strongly with BF (R = 0.50) and BV (R=0.50). Mutual information analyses further clarified these physiological interpretations. When conditioned by BV, ALFF retained no significant MRGlu, MRO2 or BF information. When conditioned by MRGlu, fALFF and ReHo retained no significant MRO2, BF or BV information. Of concern, however, the strength of PET-BOLD correspondences varied markedly by brain region, which calls for future investigation on physiological interpretations at a regional and per-subject basis.

Gender-Related Differences in Regional Cerebral Glucose Metabolism in Normal Aging Brain

Objectives: This study was aimed to investigate the gender-related differences of regional cerebral glucose metabolism in healthy people along the age using 18F-FDG PET/CT.

Methods: We recruited 344 healthy volunteers, including 217 males and 127 females (age range: 40–89 years old). All subjects underwent fluorine-18 fluorodeoxyglucose(18F-FDG) positron emission tomography (PET). All the data were divided into four groups for every 10 years old. Each participant was carefully screened from PET, MR, and other examinations in order to exclude the abnormalities, such as neurodegenerative or psychiatric disorders, alcohol/abuse, cerebral vascular disorders, metabolic diseases like diabetes mellitus and hyperthyroidism, and other systemic malignancies. The 40–50 years old group was set as the baseline group. Statistical parametric mapping (SPM) analysis was employed to illustrate the differences among groups.

Results: Compared to the baseline group, whether in a cohort or different gender groups, the decrease of brain glucose metabolism was shown in the bilateral frontal lobe, anterior cingulate gyrus, and the bilateral temporal lobe. In males, the regions of decreased metabolism were bilateral frontal lobe, caudate nucleus, and cingulate gyrus, whereas that of females were left occipital lobe, cerebellum, and the thalamus. However, the overall decrease of brain metabolism in men and women began from the age of 60s, an aggravated decrease from 70s was only observed in males.

Conclusion: (1) An obviously decreased brain metabolism was found from 60 years old, especially in the bilateral frontal lobe, bilateral temporal lobe, and inferior cingulate gyrus; (2) We found specific brain metabolic differences between genders, including the caudate nucleus region in males and the occipital lobe region in females; and (3) The aging trend is different between genders.

Regional changes with global brain hypometabolism indicates a physiological triage phenomenon and can explain shared pathophysiological events in Alzheimer's & small vessel diseases and delirium

While reduced global brain metabolism is known in aging, Alzheimer's disease (AD), small vessel disease (SVD) and delirium, explanation of regional brain metabolic (rBM) changes is a challenge. We hypothesized that this may be explained by "triage phenomenon", to preserve metabolic supply to vital brain areas. We studied changes in rBM in 69 patients with at least 5% decline in global brain metabolism during active lymphoma. There was significant decline in the rBM of the inferior parietal, precuneus, superior parietal, lateral occipital, primary visual cortices (P<0.001) and in the right lateral prefrontal cortex (P=0.01). Some areas showed no change; multiple areas had significantly increased rBM (e.g. medial prefrontal, anterior cingulate, pons, cerebellum and mesial temporal cortices; P<0.001). We conclude the existence of a physiological triage phenomenon and argue a new hypothetical model to explain the shared events in the pathophysiology of aging, AD, SVD and delirium.

Frontal lobe hypometabolism associated with Sudden Unexpected Death in Epilepsy (SUDEP) risk: An objective PET study

OBJECTIVE

Abnormalities of brain structures and neuronal networks have been identified in MRI studies of patients with Sudden Unexpected Death in Epilepsy (SUDEP) as well as in those at elevated risk. The goal of this study was to identify common patterns of objectively detected brain glucose metabolic abnormalities associated with SUDEP patients and those at high SUDEP risk.

METHODS

Patients with refractory epilepsy (n = 78, age: 16-61 years, 44 females), who underwent comprehensive presurgical evaluation, were assessed for their risk of SUDEP using the revised SUDEP-7 inventory. From the 57 patients with low SUDEP risk, 35 were selected to match their demographic and clinical characteristics to those with high SUDEP risk (n = 21). [¹⁸F]fluoro-deoxy-glucose positron emission tomography (FDG-PET) abnormalities were evaluated in the high- and low-SUDEP risk subgroups compared to FDG-PET scans of a healthy adult control group using statistical parametric mapping (SPM). Individual FDG-PET scans of 4 additional patients, who died from SUDEP, were also analyzed by SPM.

RESULTS

Mean SUDEP-7 score was 6.1 in the high and 2.7 in the low SUDEP risk group. MRI showed no lesion in 36 patients (64%). Statistical parametric mapping analysis of the high SUDEP risk subgroup showed bilateral medial frontal and inferior frontal hypometabolism as a common pattern. The low-risk group showed no specific common metabolic abnormalities on SPM group analysis. Individual PET scans of all 4 patients who died from SUDEP also showed bilateral frontal lobe hypometabolism.

CONCLUSIONS

These data show that bilateral frontal lobe involvement on FDG-PET, especially the medial and inferior frontal cortex, may be a common metabolic pattern associated with high SUDEP risk and SUDEP itself, in patients with refractory focal epilepsy.

Identifying brain networks in synaptic density PET (11C-UCB-J) with independent component analysis

BACKGROUND

The human brain is inherently organized into distinct networks, as reported widely by resting-state functional magnetic resonance imaging (rs-fMRI), which are based on blood-oxygen-level-dependent (BOLD) signal fluctuations. ¹¹C-UCB-J PET maps synaptic density via synaptic vesicle protein 2A, which is a more direct structural measure underlying brain networks than BOLD rs-fMRI.

METHODS

The aim of this study was to identify maximally independent brain source networks, i.e., "spatial patterns with common covariance across subjects", in ¹¹C-UCB-J data using independent component analysis (ICA), a data-driven analysis method. Using a population of 80 healthy controls, we applied ICA to two 40-sample subsets and compared source network replication across samples. We examined the identified source networks at multiple model orders, as the ideal number of maximally independent components (IC) is unknown. In addition, we investigated the relationship between the strength of the loading weights for each source network and age and sex.

RESULTS

Thirteen source networks replicated across both samples. We determined that a model order of 18 components provided stable, replicable components, whereas estimations above 18 were not stable. Effects of sex were found in two ICs. Nine ICs showed age-related change, with 4 remaining significant after correction for multiple comparison.

CONCLUSION

This study provides the first evidence that human brain synaptic density can be characterized into organized covariance patterns. Furthermore, we demonstrated that multiple synaptic density source networks are associated with age, which supports the potential utility of ICA to identify biologically relevant synaptic density source networks.

Interregional causal influences of brain metabolic activity reveal the spread of aging effects during normal aging

During healthy brain aging, different brain regions show anatomical or functional declines at different rates, and some regions may show compensatory increases in functional activity. However, few studies have explored interregional influences of brain activity during the aging process. We proposed a causality analysis framework combining high dimensionality independent component analysis (ICA), Granger causality, and least absolute shrinkage and selection operator regression on longitudinal brain metabolic activity data measured by Fludeoxyglucose positron emission tomography (FDG-PET). We analyzed FDG-PET images from healthy old subjects, who were scanned for at least five sessions with an averaged intersession interval of 1 year. The longitudinal data were concatenated across subjects to form a time series, and the first-order autoregressive model was used to measure interregional causality among the independent sources of metabolic activity identified using ICA. Several independent sources with reduced metabolic activity in aging, including the anterior temporal lobe and orbital frontal cortex, demonstrated causal influences over many widespread brain regions. On the other hand, the influenced regions were more distributed, and had smaller age-related declines or even relatively increased metabolic activity. The current data demonstrated interregional spreads of aging on metabolic activity at the scale of a year, and have identified key brain regions in the aging process that have strong influences over other regions.