Regional Hypometabolism Research Articles

Functional correlates of executive dysfunction in primary progressive aphasia: a systematic review

IntroductionRecent research has recognized executive dysfunction as another component affected in Primary Progressive Aphasia (PPA). This systematic review aimed to examine what information distinctive neurophysiological markers can provide in the evaluation of executive function (EF) deficits in PPA, and to what effect executive function deficits can be assessed through the characteristics of functional markers.MethodsWe conducted a systematic literature search following the PRISMA guidelines across studies that employed neuropsychological assessments and neurophysiological imaging techniques (EEG, MEG; PET, SPECT, fMRI, fNIRS) to investigate executive dysfunction correlates in PPA.ResultsFindings from nine articles including a total number of 111 individuals with PPA met our inclusion criteria and were synthesized. Although research on the neural correlates of EF deficits is scarce, MEG studies revealed widespread oscillatory slowing, with increased delta and decreased alpha power, where alterations in alpha, theta, and beta activities were significant predictors of executive function deficits. PET findings demonstrated significant correlations between executive dysfunction and hypometabolism in frontal brain regions. fMRI results indicated elevated homotopic connectivity in PPA patients, with a broader and more anterior distribution of abnormal hippocampal connections of which were associated with reduced executive performance.ConclusionOur study provides indirect support for the assumption regarding the significance of the frontal regions and inferior frontal junction in executive control and demonstrates that neurophysiological tools can be a useful aid to further investigate clinical-neurophysiological correlations in PPA.

PET/CT/MRI in Clinical Trials of Alzheimer's Disease.

With the advent of PET imaging in 1976, 2-deoxy-2-[18F]fluoro-D-glucose (FDG)-PET became the preferred method for in vivo investigation of cerebral processes, including regional hypometabolism in Alzheimer's disease. With the emergence of amyloid-PET tracers, [11C]Pittsburgh Compound-B in 2004 and later [18F]florbetapir, [18F]florbetaben, and [18F]flumetamol, amyloid-PET has replaced FDG-PET in Alzheimer's disease anti-amyloid clinical trial treatments to ensure "amyloid positivity" as an entry criterion, and to measure treatment-related decline in cerebral amyloid deposits. MRI has been used to rule out other brain diseases and screen for 'amyloid-related imaging abnormalities' (ARIAs) of two kinds, ARIA-E and ARIA-H, characterized by edema and micro-hemorrhage, respectively, and, to a lesser extent, to measure changes in cerebral volumes. While early immunotherapy trials of Alzheimer's disease showed no clinical effects, newer monoclonal antibody trials reported decreases of 27% to 85% in the cerebral amyloid-PET signal, interpreted by the Food and Drug Administration as amyloid removal expected to result in a reduction in clinical decline. However, due to the lack of diagnostic specificity of amyloid-PET tracers, amyloid positivity cannot prevent the inclusion of non-Alzheimer's patients and even healthy subjects in these clinical trials. Moreover, the "decreasing amyloid accumulation" assessed by amyloid-PET imaging has questionable quantitative value in the presence of treatment-related brain damage (ARIAs). Therefore, future Alzheimer's clinical trials should disregard amyloid-PET imaging and focus instead on assessment of regional brain function by FDG-PET and MRI monitoring of ARIAs and brain volume loss in all trial patients.

18F]FDG PET for mapping the cerebral glucose metabolic characteristics of drug-sensitive and drug-resistant epilepsy in pediatric patients.

This study aimed to investigate [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET) mapping for cerebral glucose metabolism in drug-sensitive and drug-resistant pediatric epilepsy patients. This retrospective study enrolled 40 patients and 25 controls. Patients were categorized into drug-sensitive epilepsy (n = 22) and drug-resistant epilepsy (n = 18) according to the seizure frequency at follow-up. All patients underwent two [18F]FDG PET scans separated by a minimum of one year. Absolute asymmetry index (|AI|) was calculated for assessing metabolic differences and changes in epileptic foci. Statistical Parametric Mapping (SPM) was utilized to reveal voxel-wise metabolic characteristics and alterations throughout the brain. Network analysis based on graph theory was used to investigate network-level differences between the two patient groups. The drug-sensitive group showed a lower |AI| at both baseline (P = 0.038) and follow-up (P = 0.003) PET scans than the drug-resistant group. |AI| decreased in the drug-sensitive group and increased in the drug-resistant group across scans, but these trends were not statistically significant (P = 0.240 and P = 0.450, respectively). Both groups exhibited hypometabolism at baseline. The drug-sensitive group showed less hypometabolic brain regions than the drug-resistant group. The drug-sensitive maintained stable level of hypometabolism between the two scans, whereas the drug-resistant group showed an increasing hypometabolism. Network analysis demonstrated that the drug-sensitive group had a higher global efficiency, average degree, and clustering, along with a shorter characteristic path length compared to the drug-resistant group. For the first time, this study revealed in vivo cerebral glucose metabolic pattern of nonsurgical pediatric epilepsy patients treated by antiepileptic drugs. Especially, drug-resistant epilepsy patients represented significantly extensive and progressive hypometabolism with inefficient brain network connectivity compared with drug-sensitive epilepsy. [18F]FDG PET imaging may be a potential visual approach for theranostics of epilepsy patients.

Evaluating the Efficacy of CortexID Quantitative Analysis in Localization of the Epileptogenic Zone in Patients with Temporal Lobe Epilepsy.

There remains a critical need for precise localization of the epileptogenic foci in individuals with drug-resistant epilepsy (DRE). 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) imaging can reveal hypometabolic regions during the interval between seizures in patients with epilepsy. However, visual-based qualitative analysis is time-consuming and strongly influenced by physician experience. CortexID Suite is a quantitative analysis software that helps to evaluate PET imaging of the human brain. Therefore, we aimed to evaluate the efficacy of CortexID quantitative analysis in the localization of the epileptogenic zone in patients with temporal lobe epilepsy (TLE). A total of 102 patients with epilepsy who underwent 18F-FDG-PET examinations were included in this retrospective study. The PET visual analysis was interpreted by two nuclear medicine physicians, and the quantitative analysis was performed automatically using CortexID analysis software. The assumed epileptogenic zone was evaluated comprehensively by two skilled neurologists in the preoperative assessment of epilepsy. The accuracy of epileptogenic zone localization in PET visual analysis was compared with that in CortexID quantitative analysis. The diagnostic threshold for the difference in the metabolic Z-score between the right and left sides of medial temporal lobe epilepsy (MTLE) was calculated as 0.87, and that for lateral temporal lobe epilepsy (LTLE) was 2.175. In patients with MTLE, the area under the curve (AUC) was 0.922 for PET visual analysis, 0.853 for CortexID quantitative analysis, and 0.971 for the combined diagnosis. In patients with LTLE, the AUC was 0.842 for PET visual analysis, 0.831 for CortexID quantitative analysis, and 0.897 for the combined diagnosis. These results indicate that the diagnostic efficacy of CortexID quantitative analysis is not inferior to PET visual analysis (p > 0.05), while combined analysis significantly increases diagnostic efficacy (p < 0.05). Among the 23 patients who underwent surgery, the sensitivity and specificity of PET visual analysis for localization were 95.4% and 66.7%, and the sensitivity and specificity of CortexID quantitative analysis were 100% and 50%. The diagnostic efficacy of CortexID quantitative analysis is comparable to PET visual analysis in the localization of the epileptogenic zone in patients with TLE. CortexID quantitative analysis combined with visual analysis can further improve the accuracy of epileptogenic zone localization.

Do Tau Deposition and Glucose Metabolism Dissociate in Alzheimer's Disease Trajectory?

Tau aggregation demonstrates close associations with hypometabolism in Alzheimer's disease (AD), although differing pathophysiological processes may underlie their development. To establish whether tau deposition and glucose metabolism have different trajectories in AD progression and evaluate the utility of global measures of these pathological hallmarks in predicting cognitive deficits. 279 participants with amyloid-β (Aβ) status, and T1-weighted MRI scans, were selected from the Alzheimer's Disease Neuroimaging Initiative (http://adni.loni.usc.edu). We created the standard uptake value ratio images using Statistical Parametric Mapping 12 for [18F]AV1451-PET (tau) and [18F]FDG-PET (glucose metabolism) scans. Voxel-wise group and single-subject level SPM analysis evaluated the relationship between global [18F]FDG-PET and [18F]AV1451-PET depending on the Aβ status. Linear models assessed whether tau deposition or glucose metabolism better predicted clinical progression. There was a dissociation between global cerebral glucose hypometabolism and global tau load in amyloid-positive AD and amyloid-negative mild cognitive impairment (MCI) (p > 0.05). Global hypometabolism was only associated with global cortical tau in amyloid-positive MCI. Voxel-level single subject tau load better predicted neuropsychological performance, Alzheimer's disease assessment scale-cognitive (ADAS-Cog) 13 score, and one-year change compared with regional and global hypometabolism. A dissociation between tau pathology and glucose metabolism at a global level in AD could imply that other pathological processes influence glucose metabolism. Furthermore, as tau is a better predictor of clinical progression, these processes may have independent trajectories and require independent consideration in the context of therapeutic interventions.

Deformation-based morphometry applied to FDG PET data reveals hippocampal atrophy in Alzheimer’s disease

Cerebral atrophy is a key finding in patients with dementia and usually determined on MRI. We tested whether cerebral atrophy can be imaged with FDG PET by applying deformation-based morphometry (DBM). We retrospectively identified 26 patients with a biomarker-supported clinical diagnosis of Alzheimer’s disease (AD) who had received FDG PET on a fully-digital PET/CT system and structural MRI and compared them to 13 healthy elderly controls (HEC). We performed DBM with FDG PET data (FDG-DBM). As a reference standard for determining atrophy we used voxel-based morphometry of MRI data (MRI-VBM). For conventional analysis of hypometabolism, scaled FDG PET scans (reference: brain parenchyma) were compared between groups. Receiver operating characteristic (ROC) analyses were performed. ROI read-outs were tested for associations with cognitive test performance. FDG-DBM showed abnormalities in AD mainly in the bilateral hippocampi. Similarly, MRI-VBM showed hippocampal atrophy. By contrast, conventional FDG PET analysis revealed reduced bilateral temporo-parietal FDG uptake (all p < 0.05, FWE-corrected). FDG-DBM measures of the hippocampus significantly separated AD from HEC with an AUC of 0.81; MRI-VBM achieved an AUC of 0.87; the difference between the two ROC curves was not significant (p = 0.40). Whereas FDG uptake of the hippocampus did not separate AD from HEC, FDG uptake of the Landau Meta-ROI achieved an AUC of 0.88. Verbal memory was significantly associated with FDG-DBM measures of the hippocampus (p = 0.009), but not of the Landau Meta-ROI (p > 0.1). The opposite held true for conventional FDG uptake (p > 0.1 and p = 0.001, respectively). Hippocampal atrophy in AD can be detected by applying DBM to clinical, fully-digital FDG PET. It correlates with cognitive performance and might constitute a biomarker of neurodegeneration that is complementary to conventional FDG PET analysis of regional hypometabolism.

Contribution of alpha-synuclein pathology to cerebral glucose metabolism in patients with amnestic MCI.

The in vivo detection of mixed Alzheimer's disease (AD) and α-synuclein (αSyn) pathology is important for clinical management and prognostic stratification. We investigated the contribution of αSyn pathology, detected by cerebrospinal fluid (CSF) seed amplification assay (αSyn SAA), on [18F]-fluorodeoxyglucose positron emission tomography (FDG PET) pattern in subjects with amnestic mild cognitive impairment (aMCI). We included 562 aMCI participants and 204 cognitively normalcontrols (CN) with available αSyn SAA and cerebral metabolic rate for glucose utilization (rCMRgl) data. 24% of aMCI cases were positive (+) for CSF αSyn SAA. Compared to CN, both αSyn+ and negative (-) aMCI participants showed reductions in rCMRgl within AD typical regions. αSyn+ aMCI had lower rCMRgl within AD and dementia with Lewy bodies (DLB) typical regions compared to αSyn- aMCI, even after stratification according to the CSF AT(N) system. αSyn pathology contributes to a distinct FDG PET pattern in aMCI. αSyn pathology can be detected in vivo by CSF αSyn SAA. We investigated the FDG PET pattern in aMCI patients with CSF αSyn SAA positivity. αSyn+ aMCI showed a marked brain hypometabolism in AD and DLB typical regions.

Molecular neuroimaging in dominantly inherited versus sporadic early-onset Alzheimer's disease.

Approximately 5% of Alzheimer's disease patients develop symptoms before age 65 (early-onset Alzheimer's disease), with either sporadic (sporadic early-onset Alzheimer's disease) or dominantly inherited (dominantly inherited Alzheimer's disease) presentations. Both sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer's disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer's Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer's disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50-70 cerebellar grey reference and FDG30-60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer's disease, sporadic early-onset Alzheimer's disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen's d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer's V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer's disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer's disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer's disease versus sporadic early-onset Alzheimer's disease. Sporadic early-onset Alzheimer's disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer's disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer's disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer's disease.

Relationship between neuroimaging and cognition in frontotemporal dementia: An FDG-PET and structural MRI study.

Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative condition with a prevalence comparable to Alzheimer's disease for patients under 65 years of age. Limited studies have examined the association between cognition and neuroimaging in FTD using different imaging modalities. We examined the association of cognition using Montreal Cognitive Assessment (MoCA) with both gray matter (GM) volume and glucose metabolism using magnetic resonance imaging and fluorodeoxyglucose (FDG)-PET in 21 patients diagnosed with FTD. Standardized uptake value ratio (SUVR) using the brainstem as a reference region was the primary outcome measure for FDG-PET. Partial volume correction was applied to PET data to account for disease-related atrophy. Significant positive associations were found between whole-cortex GM volume and MoCA scores (r = 0.46, p =.04). The association between whole-cortex FDG SUVR and MoCA scores was not significant (r = 0.37, p =.09). GM volumes of the frontal cortex (r = 0.54, p =.01), caudate (r = 0.62, p<.01), and insula (r = 0.57, p<.01) were also significantly correlated with MoCA, as were SUVR values of the insula (r = 0.51, p =.02), thalamus (r = 0.48, p =.03), and posterior cingulate cortex (PCC) (r = 0.47, p =.03). Whole-cortex atrophy is associated with cognitive dysfunction, and this association is larger than for whole-cortex hypometabolism as measured with FDG-PET. At the regional level, focal atrophy and/or hypometabolism in the frontal cortex, insula, PCC, thalamus, and caudate seem to be important for the decline of cognitive function in FTD. Furthermore, these results highlight how functional and structural changes may not overlap and might contribute to cognitive dysfunction in FTD in different ways.

FDG PET in Neurological Manifestations of COVID-19.

Both the central and peripheral nervous systems can be affected in COVID-19. Although MRI is the primary investigative tool for neurological imaging, FDG PET may show additional areas of involvement in the brain in the form of regional hypometabolism or hypermetabolism, secondary to synaptic dysfunction and electrical or glial activation. We present a case series of 4 patients who had neurological symptoms attributable to COVID-19 infection with abnormalities in the brain FDG PET scan.

PETSurfer-Based Brain Segmentation in Patients with Temporal Lobe Epilepsy and Associated Hippocampal Sclerosis

PurposeIn a homogeneous cohort of mesial temporal lobe epilepsy (mTLE) patients with hippocampal sclerosis (HS), this study utilizes the PETSurfer method to quantify and localize areas of cerebral hypometabolism. MethodsWe selected patients from the University Clinical Center of Serbia who all underwent anterior temporal lobectomy with amygdalohippocampectomy and achieved seizure freedom (Engel class I). Our analysis involved integrating FDG-PET and MRI imaging to compare glucose metabolism between the hemispheres ipsilateral and contralateral to HS. ResultsThe quantitative PETSurfer approach identified significant hypometabolism restricted to the ipsilateral temporal lobe structures—the amygdala, hippocampus, temporal pole, superior and middle temporal gyrus—and the ipsilateral thalamus. The lack of significant hypometabolism in extratemporal regions indicates that these 'pure' mTLE cases may not involve the broader network disruptions typically associated with more extensive epileptic pathologies. The effect sizes ranged from small to medium, indicating variable degrees of metabolic reduction across different structures. ConclusionThese findings highlight the localized nature of the epileptogenic focus in HS-related mTLE with good surgical outcome. However, the small sample size and potential cohort bias, necessitate caution in generalizing these results. Future research would benefit from a comparative approach incorporating a control group, providing a broader context for interpreting these hypometabolic patterns.

Real-word application of the AT(N) classification and disease-modifying treatment eligibility in a hospital-based cohort.

The AT(N) classification system stratifies patients based on biomarker profiles, including amyloid-beta deposition (A), tau pathology (T), and neurodegeneration (N). This study aims to apply the AT(N) classification to a hospital-based cohort of patients with cognitive decline and/or dementia, within and outside the Alzheimer's disease (AD) continuum, to enhance our understanding of the multidimensional aspects of AD and related disorders. Furthermore, we wish to investigate how many cases from our cohort would be eligible for the available disease modifying treatments, such as aducanemab and lecanemab. We conducted a retrospective evaluation of 429 patients referred to the Memory Center of IRCCS San Raffaele Hospital in Milan. Patients underwent clinical/neuropsychological assessments, lumbar puncture, structural brain imaging, and positron emission tomography (FDG-PET). Patients were stratified according to AT(N) classification, group comparisons were performed and the number of eligible cases for anti-β amyloid monoclonal antibodies was calculated. Sociodemographic and clinical features were similar across groups. The most represented group was A + T + N + accounting for 38% of cases, followed by A + T - N + (21%) and A - T - N + (20%). Although the clinical presentation was similar, the A + T + N + group showed more severe cognitive impairment in memory, language, attention, executive, and visuospatial functions compared to other AT(N) groups. Notably, T + patients demonstrated greater memory complaints compared to T - cases. FDG-PET outperformed MRI and CT in distinguishing A + from A - patients. Although 61% of the observed cases were A + , only 17% of themwere eligible for amyloid-targeting treatments. The AT(N) classification is applicable in a real-world clinical setting. The classification system provided insights into clinical management and treatment strategies. Low cognitive performance and specific regional FDG-PET hypometabolism at diagnosis are highly suggestive for A + T + or A - T + profiles. This work provides also a realistic picture of the proportion of AD patients eligible for disease modifying treatments emphasizing the need for early detection.

Spatial transcriptomics reveals that metabolic characteristics define the tumor immunosuppression microenvironment via iCAF transformation in oral squamous cell carcinoma

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment. Oral squamous cell carcinoma (OSCC), a representative hypoxic tumor, has a heterogeneous internal metabolic environment. To clarify the relationship between different metabolic regions and the tumor immune microenvironment (TME) in OSCC, Single cell (SC) and spatial transcriptomics (ST) sequencing of OSCC tissues were performed. The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data. The metabolic activity of each spot was calculated using scMetabolism, and k-means clustering was used to classify all spots into hyper-, normal-, or hypometabolic regions. CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others. Through CellPhoneDB and NicheNet cell-cell communication analysis, it was found that in the hypermetabolic region, fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts (iCAFs), and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12. The secretion of CXCL12 recruits regulatory T cells (Tregs), leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment. This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC, ST and TCGA bulk data, and highlights potential targets for therapy.

The Brain Structure of Patients with Borderline Personality Disorder: A Review of Positron Emission Tomography and Structural Magnetic Resonance Imaging

Borderline personality disorder (BPD) is a severe mental disorder characterized by a consistent pattern of emotional inconsistency, poor impulse management, unstable personal relationships, and a constantly fluctuating self-image. Researchers have lately made significant progress in grasping the potential neurobiological underpinnings of BPD, and neuroimaging has emerged as a pivotal instrument in examining differences between BPD patients and healthy controls. This article will explore past studies on neuroimaging of patients with bipolar disorder, including PET and sMRI. BPD patients are likely to display hypometabolism in prefrontal regions and metabolic changes in temporal and parietal lobes. There are also studies pointing to the significance of anterior cingulate cortex (ACC) and structural volume. However, the results are mainly inconsistent. The limiting sample sizes may be one of the reasons for such a high level of variance. Therefore, studies with larger and more inclusive sample sizes are needed to reach firm conclusions. Moreover, the relationship between medication/therapy and the changes in BPD patients brain activities also needed to be explored.

The brain network hub degeneration in Alzheimer's disease.

Alzheimer's disease (AD) has been conceptualized as a syndrome of brain network dysfunction. Recent imaging connectomics studies have provided unprecedented opportunities to map structural and functional brain networks in AD. By reviewing molecular, imaging, and computational modeling studies, we have shown that highly connected brain hubs are primarily distributed in the medial and lateral prefrontal, parietal, and temporal regions in healthy individuals and that the hubs are selectively and severely affected in AD as manifested by increased amyloid-beta deposition and regional atrophy, hypo-metabolism, and connectivity dysfunction. Furthermore, AD-related hub degeneration depends on the imaging modality with the most notable degeneration in the medial temporal hubs for morphological covariance networks, the prefrontal hubs for structural white matter networks, and in the medial parietal hubs for functional networks. Finally, the AD-related hub degeneration shows metabolic, molecular, and genetic correlates. Collectively, we conclude that the brain-network-hub-degeneration framework is promising to elucidate the biological mechanisms of network dysfunction in AD, which provides valuable information on potential diagnostic biomarkers and promising therapeutic targets for the disease.

Comparing Symmetric Dimethylarginine and Amyloid-β42 as Predictors of Alzheimer's Disease Development.

Physicians may soon be able to diagnose Alzheimer's disease (AD) in its early stages using fluid biomarkers like amyloid. However, it is acknowledged that additional biomarkers need to be characterized which would facilitate earlier monitoring of AD pathogenesis. To determine if a potential novel inflammation biomarker for AD, symmetric dimethylarginine, has utility as a baseline serum biomarker for discriminating prodromal AD from cognitively unimpaired controls in comparison to cerebrospinal fluid amyloid-β42 (Aβ42). Data including demographics, magnetic resonance imaging and fluorodeoxyglucose-positron emission tomography scans, Mini-Mental State Examination and Functional Activities Questionnaire scores, and biomarker concentrations were obtained from the Alzheimer's Disease Neuroimaging Initiative for a total of 146 prodromal AD participants and 108 cognitively unimpaired controls. Aβ42 (p = 0.65) and symmetric dimethylarginine (p = 0.45) were unable to predict age-matched cognitively unimpaired controls and prodromal AD participants. Aβ42 was negatively associated with regional brain atrophy and hypometabolism as well as cognitive and functional decline in cognitively unimpaired control participants (p < 0.05) that generally decreased in time. There were no significant associations between Aβ42 and symmetric dimethylarginine with imaging or neurocognitive biomarkers in prodromal AD patients. Correlations were smaller between Aβ42 and neuropathological biomarkers over time and were absent in prodromal AD participants, suggesting a plateau effect dependent on age and disease stage. Evidence supporting symmetric dimethylarginine as a novel biomarker for AD as a single measurement was not found.

A ROI-based quantitative pipeline for 18F-FDG PET metabolism and pCASL perfusion joint analysis: Validation of the 18F-FDG PET line

In Mild Cognitive Impairment (MCI), the study of brain metabolism, provided by 18F-FluoroDeoxyGlucose Positron Emission Tomography (18F-FDG PET) can be integrated with brain perfusion through pseudo-Continuous Arterial Spin Labeling Magnetic Resonance sequences (MR pCASL). Cortical hypometabolism identification generally relies on wide control group datasets; pCASL control groups are instead not publicly available yet, due to lack of standardization in the acquisition parameters. This study presents a quantitative pipeline to be applied to PET and pCASL data to coherently analyze metabolism and perfusion inside 16 matching cortical regions of interest (ROIs) derived from the AAL3 atlas. The PET line is tuned on 36 MCI patients and 107 healthy control subjects, to agree in identifying hypometabolic regions with clinical reference methods (visual analysis supported by a vendor tool and Statistical Parametric Mapping, SPM, with two parametrizations here identified as SPM-A and SPM-B). The analysis was conducted for each ROI separately. The proposed PET analysis pipeline obtained accuracy 78 % and Cohen's к 60 % vs visual analysis, accuracy 79 % and Cohen's к 58 % vs SPM-A, accuracy 77 % and Cohen's к 54 % vs SPM-B. Cohen's к resulted not significantly different from SPM-A and SPM-B Cohen's к when assuming visual analysis as reference method (p-value 0.61 and 0.31 respectively). Considering SPM-A as reference method, Cohen's к is not significantly different from SPM-B Cohen's к as well (p-value = 1.00). The complete PET-pCASL pipeline was then preliminarily applied on 5 MCI patients and metabolism-perfusion regional correlations were assessed. The proposed approach can be considered as a promising tool for PET-pCASL joint analyses in MCI, even in the absence of a pCASL control group, to perform metabolism-perfusion regional correlation studies, and to assess and compare perfusion in hypometabolic or normo-metabolic areas.

The relationship between [18F]FDG‐PET signal and key‐players of brain glucose metabolism

AbstractBackgroundNeuronal activity is supported by activity‐dependent lactate production from astrocytes, as postulated by the astrocyte–neuron lactate shuttle (ANLS) hypothesis. Indeed, astrocytic glutamate uptake is a main trigger for brain glucose consumption. [18F]fluorodeoxyglucose (FDG)‐PET showing a hypometabolic signature has been used as an index of neurodegeneration in Alzheimer’s disease (AD). In the early stages of the disease, soluble amyloid‐beta (Aβ) has been associated with neuronal hyperactivity due to decreased astrocytic glutamate uptake. It is hypothesized that this phenomenon occurs especially in regions with high ongoing baseline activity. Over time, neurodegeneration and hypometabolism in such regions may contribute to the progress of the AD continuum. Thus, we investigated whether the [18F]FDG‐PET signal in typical hypometabolic regions in AD is associated with the expression of ANLS transporters and enzymes in the healthy brain.MethodGene expression of GLUT1, GLUT3, MCT1, MCT2, MCT4, LDHA, and LDHB (ANLS genes) from postmortem brain tissue of healthy individuals were obtained from the Allen Human Brain Atlas. [18F]FDG‐PET data from cognitively unimpaired individuals were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Pearson correlations were performed between the mean gene expression and the mean [18F]FDG‐PET SUVr across typically hypometabolic brain regions in AD (precuneus, angular and temporal gyri, and parietal and cingulate regions) and non‐vulnerable regions (uncorrected p‐value &lt; 0.05).ResultsThe expression of ANLS genes had a stronger positive correlation with [18F]FDG‐PET SUVr across the AD hypometabolic regions than the non‐vulnerable regions (p &lt; 0.05). Of note, the astrocytic glucose transporter GLUT1 presented a stronger correlation with [18F]FDG‐PET than the neuronal transporter GLUT3 in AD‐vulnerable regions. Figure 1 presents all correlations.ConclusionOur results show that the physiological expression of transporters and enzymes responsible for the brain glucose metabolism correlate more with the [18F]FDG‐PET signal in typical brain regions of the AD hypometabolic signature. This suggests these regions present a higher baseline activity and may be more susceptible to Aβ‐induced hyperactivation in early AD, which could lead to a bioenergetic collapse in later disease stages, as shown in the [18F]FDG‐PET of AD individuals.

Increased Genetic Risk for ADHD Potentiates Cognitive Impairment and Brain Hypometabolism in Alzheimer’s Disease Patients

AbstractBackgroundRecent epidemiological studies showed that patients with attention‐deficit/hyperactivity disorder (ADHD) are more likely to be diagnosed with Alzheimer’s Disease (AD). Additionally, increased genetic risk for ADHD, measured with ADHD polygenic risk scores (ADHD‐PRS), was associated with amyloid‐dependent cognitive decline in older adults. However, it is unclear whether higher genetic risk for ADHD is associated with worse cognitive function in patients with AD dementia.MethodWe used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to investigate the association between cognitive function (Preclinical Alzheimer Cognitive Composite [PACC], executive function, and memory) and ADHD‐PRS in subjects with AD dementia. Additionally, we tested whether ADHD‐PRS potentiated brain hypometabolism measured with [18F]FDG‐PET. Analyses were controlled by age, sex, years of study, and number of APOE ε4 alleles.ResultWe evaluated baseline data from 264 AD patients (114 women [43.2%], mean [SD] age of 75 [7.6] years). ADHD‐PRS was associated with decreased cognitive function (p‐value = .04, η2 = .01, Figure 1a), more specifically in executive function (p‐value = .04, η2 = .01, Figure 1c). Higher ADHD‐PRS was associated with brain hypometabolism in frontal, parietal, and temporal regions (Figure 2a,b). Brain hypometabolism correlated with worse cognitive function in the following regions: postcentral gyrus (p‐value = .01, η2 = .03), superior parietal gyrus (p‐value = .001, η2 = .07), precentral gyrus (p‐value = .004, η2 = .05), and fusiform gyrus (p‐value&lt;.0001, η2 = .08, Figure 2c,d,e,f). Finally, decreased metabolism in these four regions mediated the effect of ADHD‐PRS on cognitive function (Figure 3).ConclusionFindings indicate that a higher genetic risk for ADHD is correlated with impaired cognitive function with small effect sizes. Moreover, the effects of the genetic risk of ADHD on cognitive function were mediated by hypometabolism in frontal, parietal, and temporal brain regions, which could point to a decrease resilience to AD pathology in individuals with ADHD. Clinically, our findings suggest that patients with comorbid ADHD and AD dementia have a more severe disease phenotype, with potential implications for prognosis and treatment.

GABA transporters gene expression associates with [18F]FDG‐PET signal in regions typically hypometabolic in Alzheimer’s disease

AbstractBackgroundIt is suggested that the [18F]fluorodeoxyglucose(FDG)‐PET signal reflects astrocyte and neuronal activity, with the excitatory glutamate uptake by astrocytes as the trigger for brain glucose metabolism. The inhibitory neurotransmitter γ‐aminobutyric acid (GABA) is taken up by neurons and astrocytes through the GABA transporters (GAT) 1 and 3. However, its role in the [18F]FDG‐PET signal in healthy aging and Alzheimer’s disease (AD) remains poorly investigated. Thus, we aimed to explore associations between neuronal and astrocytic GABA transporters gene expression with [18F]FDG‐PET in cognitively unimpaired (CU) and AD individuals.MethodWe obtained [18F]FDG‐PET imaging data of CU and AD from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (Table 1). GAT1 and GAT3 gene expression in the brain was obtained from the Allen Brain Atlas (Table 1, Figure 1). We extracted SUVr (pons as reference region) and mRNA values using the RMINC package and performed Pearson’s correlation to test the association between [18F]FDG‐PET and GABA transporters mRNA (p‐value &lt; 0.05).ResultIn brain regions typically hypometabolic in AD, we observed a strong positive association of [18F]FDG‐PET SUVr with GAT1 and GAT3 gene expression in CU (GAT1: r = 0.93; p &lt; 0.0001; Figure 2A, GAT3: r = 0.94; p &lt; 0.0001; Figure 2B) and AD individuals (GAT1: r = 0.9; p &lt; 0.0001; Figure 2A, GAT3: r = 0.92; p &lt; 0.0001; Figure 2B). By contrast, in brain regions typically resilient, we found a weak correlation with CU individuals (GAT1: r = 0.32; p = 0.016; Figure 2C, GAT3: r = 0.26; p = 0.04; Figure 2D) and no significant correlation in AD patients (GAT1: r = 0.24; p = 0.07; Figure 2C, GAT3: r = 0.24; p = 0.059; Figure 2D).ConclusionOur results demonstrate a significant strong positive association between [18F]FDG‐PET SUVr and GABA transporters gene expression in CU and AD in hypometabolic regions. These findings suggest that GABA transporters are involved with brain glucose metabolism in regions classically vulnerable to AD pathology.