Glucose utilization: still in the synapse

PET-based brain molecular connectivity in neurodegenerative disease

PURPOSE OF REVIEW

Molecular imaging has traditionally been used and interpreted primarily in the context of localized and relatively static neurochemical processes. New understanding of brain function and development of novel molecular imaging protocols and analysis methods highlights the relevance of molecular networks that co-exist and interact with functional and structural networks. Although the concept and evidence of disease-specific metabolic brain patterns has existed for some time, only recently has such an approach been applied in the neurotransmitter domain and in the context of multitracer and multimodal studies. This review briefly summarizes initial findings and highlights emerging applications enabled by this new approach.

RECENT FINDINGS

Connectivity based approaches applied to molecular and multimodal imaging have uncovered molecular networks with neurodegeneration-related alterations to metabolism and neurotransmission that uniquely relate to clinical findings; better disease stratification paradigms; an improved understanding of the relationships between neurochemical and functional networks and their related alterations, although the directionality of these relationships are still unresolved; and a new understanding of the molecular underpinning of disease-related alteration in resting-state brain activity.

SUMMARY

Connectivity approaches are poised to greatly enhance the information that can be extracted from molecular imaging. While currently mostly contributing to enhancing understanding of brain function, they are highly likely to contribute to the identification of specific biomarkers that will improve disease management and clinical care.

Thermodynamic Analysis to Evaluate the Effect of Diet on Brain Glucose Metabolism: The Case of Fish Oil

Inefficient glucose metabolism and decreased ATP production in the brain are linked to ageing, cognitive decline, and neurodegenerative diseases (NDDs). This study employed thermodynamic analysis to assess the effect of fish oil supplementation on glucose metabolism in ageing brains. Data from previous studies on glucose metabolism in the aged human brain and grey mouse lemur brains were examined. The results demonstrated that Omega-3 fish oil supplementation in grey mouse lemurs increased entropy generation and decreased Gibbs free energy across all brain regions. Specifically, there was a 47.4% increase in entropy generation and a 47.4 decrease in Gibbs free energy in the whole brain, indicating improved metabolic efficiency. In the human model, looking at the specific brain regions, supplementation with Omega-3 polyunsaturated fatty acids (n-3 PUFAs) reduced the entropy generation difference between elderly and young individuals in the cerebellum and particular parts of the brain cortex, namely the anterior cingulate and occipital lobe, with 100%, 14.29%, and 20% reductions, respectively. The Gibbs free energy difference was reduced only in the anterior cingulate by 60.64%. This research underscores that the application of thermodynamics is a comparable and powerful tool in comprehending the dynamics and metabolic intricacies within the brain.

Short-term consumption of highly processed diets varying in macronutrient content impair the sense of smell and brain metabolism in mice

OBJECTIVE

Food processing greatly contributed to increased food safety, diversity, and accessibility. However, the prevalence of highly palatable and highly processed food in our modern diet has exacerbated obesity rates and contributed to a global health crisis. While accumulating evidence suggests that chronic consumption of such foods is detrimental to sensory and neural physiology, it is unclear whether its short-term intake has adverse effects. Here, we assessed how short-term consumption (<2 months) of three diets varying in composition and macronutrient content influence olfaction and brain metabolism in mice.

METHODS

The diets tested included a grain-based standard chow diet (CHOW; 54% carbohydrate, 32% protein, 14% fat; #8604 Teklad Rodent diet , Envigo Inc.), a highly processed control diet (hpCTR; 70% carbohydrate, 20% protein, 10% fat; #D12450B, Research Diets Inc.), and a highly processed high-fat diet (hpHFD; 20% carbohydrate, 20% protein, 60% fat; #D12492, Research Diets Inc.). We performed behavioral and metabolic phenotyping, electro-olfactogram (EOG) recordings, brain glucose metabolism imaging, and mitochondrial respirometry in different brain regions. We also performed RNA-sequencing (RNA-seq) in the nose and across several brain regions, and conducted differential expression analysis, gene ontology, and network analysis.

RESULTS

We show that short-term consumption of the two highly processed diets, but not the grain-based diet, regardless of macronutrient content, adversely affects odor-guided behaviors, physiological responses to odorants, transcriptional profiles in the olfactory mucosa and brain regions, and brain glucose metabolism and mitochondrial respiration.

CONCLUSIONS

Even short periods of highly processed food consumption are sufficient to cause early olfactory and brain abnormalities, which has the potential to alter food choices and influence the risk of developing metabolic disease.

FDG-PET markers of heterogeneity and different risk of progression in amnestic MCI

INTRODUCTION

Amnestic mild cognitive impairment (aMCI) is emerging as a heterogeneous condition.

METHODS

We looked at a cohort of N = 207 aMCI subjects, with baseline fluorodeoxyglucose positron emission tomography (FDG-PET), T1 magnetic resonance imaging, cerebrospinal fluid (CSF), apolipoprotein E (APOE), and neuropsychological assessment. An algorithm based on FDG-PET hypometabolism classified each subject into subtypes, then compared biomarker measures and clinical progression.

RESULTS

Three subtypes emerged: hippocampal sparing-cortical hypometabolism, associated with younger age and the highest level of Alzheimer's disease (AD)-CSF pathology; hippocampal/cortical hypometabolism, associated with a high percentage of APOE ε3/ε4 or ε4/ε4 carriers; medial-temporal hypometabolism, characterized by older age, the lowest AD-CSF pathology, the most severe hippocampal atrophy, and a benign course. Within the whole cohort, the severity of temporo-parietal hypometabolism, correlated with AD-CSF pathology and marked the rate of progression of cognitive decline.

DISCUSSION

FDG-PET can distinguish clinically comparable aMCI at single-subject level with different risk of progression to AD dementia or stability. The obtained results can be useful for the optimization of pharmacological trials and automated-classification models.

HIGHLIGHTS

Algorithm based on FDG-PET hypometabolism demonstrates distinct subtypes across aMCI; Three different subtypes show heterogeneous biological profiles and risk of progression; The cortical hypometabolism is associated with AD pathology and cognitive decline; MTL hypometabolism is associated with the lowest conversion rate and CSF-AD pathology.

Brain hypometabolism in non-demented microtubule-associated protein tau H1 carriers with Parkinson's disease

BACKGROUND AND PURPOSE

The microtubule-associated protein tau (MAPT) H1 homozygosity (H1/H1 haplotype) is a genetic risk factor for neurodegenerative diseases, such as Parkinson's disease (PD). MAPT H1 homozygosity has been associated with conversion to PD; however, results are conflicting since some studies did not find a strong influence. Cortical hypometabolism is associated with cognitive impairment in PD. In this study, we aimed to evaluate the metabolic pattern in nondemented PD patients MAPT H1/H1 carriers in comparison with MAPT H1/H2 haplotype. In addition, we evaluated domain-specific cognitive differences according to MAPT haplotype.

METHODS

We compared a group of 26 H1/H1 and 20 H1/H2 carriers with late-onset PD. Participants underwent a comprehensive neuropsychological cognitive evaluation and a [18F]-Fluorodeoxyglucose PET-MR scan.

RESULTS

MAPT H1/H1 carriers showed worse performance in the digit span forward test of attention compared to MAPT H1/H2 carriers. In the [18F]-Fluorodeoxyglucose PET comparisons, MAPT H1/H1 displayed hypometabolism in the frontal cortex, parahippocampal, and cingulate gyrus, as well as in the caudate and globus pallidus.

CONCLUSION

PD patients MAPT H1/H1 carriers without dementia exhibit relative hypometabolism in several cortical areas as well as in the basal ganglia, and worse performance in attention than MAPT H1/H2 carriers. Longitudinal studies should assess if lower scores in attention and dysfunction in these areas are predictors of dementia in MAPT H1/H1 homozygotes.

Metabolic remodeling in astrocytes: Paving the path to brain tumor development

The brain is a highly metabolic organ, composed of multiple cell classes, that controls crucial functions of the body. Although neurons have traditionally been the main protagonist, astrocytes have gained significant attention over the last decade. In this regard, astrocytes are a type of glial cells that have recently emerged as critical regulators of central nervous system (CNS) function and play a significant role in maintaining brain energy metabolism. However, in certain scenarios, astrocyte behavior can go awry, which poses a significant threat to brain integrity and function. This is definitively the case for mutations that turn normal astrocytes and astrocytic precursors into gliomas, an aggressive type of brain tumor. In addition, healthy astrocytes can interact with tumor cells, becoming part of the tumor microenvironment and influencing disease progression. In this review, we discuss the recent evidence suggesting that disturbed metabolism in astrocytes can contribute to the development and progression of fatal human diseases such as cancer. Emphasis is placed on detailing the molecular bases and metabolic pathways of this disease and highlighting unique metabolic vulnerabilities that can potentially be exploited to develop successful therapeutic opportunities.

Cerebral electrometabolic coupling in disordered and normal states of consciousness

We assess cerebral integrity with cortical and subcortical FDG-PET and cortical electroencephalography (EEG) within the mesocircuit model framework in patients with disorders of consciousness (DoCs). The mesocircuit hypothesis proposes that subcortical activation facilitates cortical function. We find that the metabolic balance of subcortical mesocircuit areas is informative for diagnosis and is associated with four EEG-based power spectral density patterns, cortical metabolism, and α power in healthy controls and patients with a DoC. Last, regional electrometabolic coupling at the cortical level can be identified in the θ and α ranges, showing positive and negative relations with glucose uptake, respectively. This relation is inverted in patients with a DoC, potentially related to altered orchestration of neural activity, and may underlie suboptimal excitability states in patients with a DoC. By understanding the neurobiological basis of the pathophysiology underlying DoCs, we foresee translational value for diagnosis and treatment of patients with a DoC.

Different pieces of the same puzzle: a multifaceted perspective on the complex biological basis of Parkinson's disease

The biological basis of the neurodegenerative movement disorder, Parkinson's disease (PD), is still unclear despite it being 'discovered' over 200 years ago in Western Medicine. Based on current PD knowledge, there are widely varying theories as to its pathobiology. The aim of this article was to explore some of these different theories by summarizing the viewpoints of laboratory and clinician scientists in the PD field, on the biological basis of the disease. To achieve this aim, we posed this question to thirteen "PD experts" from six continents (for global representation) and collated their personal opinions into this article. The views were varied, ranging from toxin exposure as a PD trigger, to LRRK2 as a potential root cause, to toxic alpha-synuclein being the most important etiological contributor. Notably, there was also growing recognition that the definition of PD as a single disease should be reconsidered, perhaps each with its own unique pathobiology and treatment regimen.

Refueling the post COVID-19 brain: potential role of ketogenic medium chain triglyceride supplementation: an hypothesis

COVID-19 infection causes cognitive changes in the acute phase, but also after apparent recovery. Over fifty post (long)-COVID symptoms are described, including cognitive dysfunction ("brain fog") precluding return to pre-COVID level of function, with rates twice as high in females. Additionally, the predominant demographic affected by these symptoms is younger and still in the workforce. Lack of ability to work, even for six months, has significant socio-economic consequences. This cognitive dysfunction is associated with impaired cerebral glucose metabolism, assessed using 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET), showing brain regions that are abnormal compared to age and sex matched controls. In other cognitive conditions such as Alzheimer's disease (AD), typical patterns of cerebral glucose hypometabolism, frontal hypometabolism and cerebellar hypermetabolism are common. Similar FDG-PET changes have also been observed in post-COVID-19, raising the possibility of a similar etiology. Ketone bodies (B-hydroxybutyrate, acetoacetate and acetone) are produced endogenously with very low carbohydrate intake or fasting. They improve brain energy metabolism in the face of cerebral glucose hypometabolism in other conditions [mild cognitive impairment (MCI) and AD]. Long-term low carbohydrate intake or prolonged fasting is not usually feasible. Medium chain triglyceride (MCT) is an exogenous route to nutritional ketosis. Research has supported their efficacy in managing intractable seizures, and cognitive impairment in MCI and AD. We hypothesize that cerebral glucose hypometabolism associated with post COVID-19 infection can be mitigated with MCT supplementation, with the prediction that cognitive function would also improve. Although there is some suggestion that post COVID-19 cognitive symptoms may diminish over time, in many individuals this may take more than six months. If MCT supplementation is able to speed the cognitive recovery, this will impact importantly on quality of life. MCT is readily available and, compared to pharmaceutical interventions, is cost-effective. Research shows general tolerability with dose titration. MCT is a component of enteral and parenteral nutrition supplements, including in pediatrics, so has a long record of safety in vulnerable populations. It is not associated with weight gain or adverse changes in lipid profiles. This hypothesis serves to encourage the development of clinical trials evaluating the impact of MCT supplementation on the duration and severity of post COVID-19 cognitive symptoms.

Disordered network structure and function in dystonia: pathological connectivity vs. adaptive responses

Primary dystonia is thought to emerge through abnormal functional relationships between basal ganglia and cerebellar motor circuits. These interactions may differ across disease subtypes and provide a novel biomarker for diagnosis and treatment. Using a network mapping algorithm based on resting-state functional MRI (rs-fMRI), a method that is readily implemented on conventional MRI scanners, we identified similar disease topographies in hereditary dystonia associated with the DYT1 or DYT6 mutations and in sporadic patients lacking these mutations. Both networks were characterized by contributions from the basal ganglia, cerebellum, thalamus, sensorimotor areas, as well as cortical association regions. Expression levels for the two networks were elevated in hereditary and sporadic dystonia, and in non-manifesting carriers of dystonia mutations. Nonetheless, the distribution of abnormal functional connections differed across groups, as did metrics of network organization and efficiency in key modules. Despite these differences, network expression correlated with dystonia motor ratings, significantly improving the accuracy of predictions based on thalamocortical tract integrity obtained with diffusion tensor MRI (DTI). Thus, in addition to providing unique information regarding the anatomy of abnormal brain circuits, rs-fMRI functional networks may provide a widely accessible method to help in the objective evaluation of new treatments for this disorder.

Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer's disease-related pattern

BACKGROUND

Alzheimer's disease-related pattern (ADRP) is a metabolic brain biomarker of Alzheimer's disease (AD). While ADRP is being introduced into research, the effect of the size of the identification cohort and the effect of the resolution of identification and validation images on ADRP's performance need to be clarified.

METHODS

240 2-[¹⁸F]fluoro-2-deoxy-D-glucose positron emission tomography images [120 AD/120 cognitive normals (CN)] were selected from the Alzheimer's disease neuroimaging initiative database. A total of 200 images (100 AD/100 CN) were used to identify different versions of ADRP using a scaled subprofile model/principal component analysis. For this purpose, five identification groups were randomly selected 25 times. The identification groups differed in the number of images (20 AD/20 CN, 30 AD/30 CN, 40 AD/40 CN, 60 AD/60 CN, and 80 AD/80 CN) and image resolutions (6, 8, 10, 12, 15 and 20 mm). A total of 750 ADRPs were identified and validated through the area under the curve (AUC) values on the remaining 20 AD/20 CN with six different image resolutions.

RESULTS

ADRP's performance for the differentiation between AD patients and CN demonstrated only a marginal average AUC increase, when the number of subjects in the identification group increases (AUC increase for about 0.03 from 20 AD/20 CN to 80 AD/80 CN). However, the average of the lowest five AUC values increased with the increasing number of participants (AUC increase for about 0.07 from 20 AD/20 CN to 30 AD/30 CN and for an additional 0.02 from 30 AD/30 CN to 40 AD/40 CN). The resolution of the identification images affects ADRP's diagnostic performance only marginally in the range from 8 to 15 mm. ADRP's performance stayed optimal even when applied to validation images of resolution differing from the identification images.

CONCLUSIONS

While small (20 AD/20 CN images) identification cohorts may be adequate in a favorable selection of cases, larger cohorts (at least 30 AD/30 CN images) shall be preferred to overcome possible/random biological differences and improve ADRP's diagnostic performance. ADRP's performance stays stable even when applied to the validation images with a resolution different than the resolution of the identification ones.

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.

Functional brain networks in the evaluation of patients with neurodegenerative disorders

Network analytical tools are increasingly being applied to brain imaging maps of resting metabolic activity (PET) or blood oxygenation-dependent signals (functional MRI) to characterize the abnormal neural circuitry that underlies brain diseases. This approach is particularly valuable for the study of neurodegenerative disorders, which are characterized by stereotyped spread of pathology along discrete neural pathways. Identification and validation of disease-specific brain networks facilitate the quantitative assessment of pathway changes over time and during the course of treatment. Network abnormalities can often be identified before symptom onset and can be used to track disease progression even in the preclinical period. Likewise, network activity can be modulated by treatment and might therefore be used as a marker of efficacy in clinical trials. Finally, early differential diagnosis can be achieved by simultaneously measuring the activity levels of multiple disease networks in an individual patient's scans. Although these techniques were originally developed for PET, over the past several years analogous methods have been introduced for functional MRI, a more accessible non-invasive imaging modality. This advance is expected to broaden the application of network tools to large and diverse patient populations.

Automated differential diagnosis of dementia syndromes using FDG PET and machine learning

BACKGROUND

Metabolic brain imaging with 2-[¹⁸F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG PET) is a supportive diagnostic and differential diagnostic tool for neurodegenerative dementias. In the clinic, scans are usually visually interpreted. However, computer-aided approaches can improve diagnostic accuracy. We aimed to build two machine learning classifiers, based on two sets of FDG PET-derived features, for differential diagnosis of common dementia syndromes.

METHODS

We analyzed FDG PET scans from three dementia cohorts [63 dementia due to Alzheimer's disease (AD), 79 dementia with Lewy bodies (DLB) and 23 frontotemporal dementia (FTD)], and 41 normal controls (NCs). Patients' clinical diagnosis at follow-up (25 ± 20 months after scanning) or cerebrospinal fluid biomarkers for Alzheimer's disease was considered a gold standard. FDG PET scans were first visually evaluated. Scans were pre-processed, and two sets of features extracted: (1) the expressions of previously identified metabolic brain patterns, and (2) the mean uptake value in 95 regions of interest (ROIs). Two multi-class support vector machine (SVM) classifiers were tested and their diagnostic performance assessed and compared to visual reading. Class-specific regional feature importance was assessed with Shapley Additive Explanations.

RESULTS

Pattern- and ROI-based classifier achieved higher overall accuracy than expert readers (78% and 80% respectively, vs. 71%). Both SVM classifiers performed similarly to one another and to expert readers in AD (F1 = 0.74, 0.78, and 0.78) and DLB (F1 = 0.81, 0.81, and 0.78). SVM classifiers outperformed expert readers in FTD (F1 = 0.87, 0.83, and 0.63), but not in NC (F1 = 0.71, 0.75, and 0.92). Visualization of the SVM model showed bilateral temporal cortices and cerebellum to be the most important features for AD; occipital cortices, hippocampi and parahippocampi, amygdala, and middle temporal lobes for DLB; bilateral frontal cortices, middle and anterior cingulum for FTD; and bilateral angular gyri, pons, and vermis for NC.

CONCLUSION

Multi-class SVM classifiers based on the expression of characteristic metabolic brain patterns or ROI glucose uptake, performed better than experts in the differential diagnosis of common dementias using FDG PET scans. Experts performed better in the recognition of normal scans and a combined approach may yield optimal results in the clinical setting.

Morphological, cellular, and molecular basis of brain infection in COVID-19 patients

Although increasing evidence confirms neuropsychiatric manifestations associated mainly with severe COVID-19 infection, long-term neuropsychiatric dysfunction (recently characterized as part of “long COVID-19” syndrome) has been frequently observed after mild infection. We show the spectrum of cerebral impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, ranging from long-term alterations in mildly infected individuals (orbitofrontal cortical atrophy, neurocognitive impairment, excessive fatigue and anxiety symptoms) to severe acute damage confirmed in brain tissue samples extracted from the orbitofrontal region (via endonasal transethmoidal access) from individuals who died of COVID-19. In an independent cohort of 26 individuals who died of COVID-19, we used histopathological signs of brain damage as a guide for possible SARS-CoV-2 brain infection and found that among the 5 individuals who exhibited those signs, all of them had genetic material of the virus in the brain. Brain tissue samples from these five patients also exhibited foci of SARS-CoV-2 infection and replication, particularly in astrocytes. Supporting the hypothesis of astrocyte infection, neural stem cell–derived human astrocytes in vitro are susceptible to SARS-CoV-2 infection through a noncanonical mechanism that involves spike–NRP1 interaction. SARS-CoV-2–infected astrocytes manifested changes in energy metabolism and in key proteins and metabolites used to fuel neurons, as well as in the biogenesis of neurotransmitters. Moreover, human astrocyte infection elicits a secretory phenotype that reduces neuronal viability. Our data support the model in which SARS-CoV-2 reaches the brain, infects astrocytes, and consequently, leads to neuronal death or dysfunction. These deregulated processes could contribute to the structural and functional alterations seen in the brains of COVID-19 patients.

Morphological, cellular, and molecular basis of brain infection in COVID-19 patients

Although increasing evidence confirms neuropsychiatric manifestations associated mainly with severe COVID-19 infection, long-term neuropsychiatric dysfunction (recently characterized as part of "long COVID-19" syndrome) has been frequently observed after mild infection. We show the spectrum of cerebral impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, ranging from long-term alterations in mildly infected individuals (orbitofrontal cortical atrophy, neurocognitive impairment, excessive fatigue and anxiety symptoms) to severe acute damage confirmed in brain tissue samples extracted from the orbitofrontal region (via endonasal transethmoidal access) from individuals who died of COVID-19. In an independent cohort of 26 individuals who died of COVID-19, we used histopathological signs of brain damage as a guide for possible SARS-CoV-2 brain infection and found that among the 5 individuals who exhibited those signs, all of them had genetic material of the virus in the brain. Brain tissue samples from these five patients also exhibited foci of SARS-CoV-2 infection and replication, particularly in astrocytes. Supporting the hypothesis of astrocyte infection, neural stem cell-derived human astrocytes in vitro are susceptible to SARS-CoV-2 infection through a noncanonical mechanism that involves spike-NRP1 interaction. SARS-CoV-2-infected astrocytes manifested changes in energy metabolism and in key proteins and metabolites used to fuel neurons, as well as in the biogenesis of neurotransmitters. Moreover, human astrocyte infection elicits a secretory phenotype that reduces neuronal viability. Our data support the model in which SARS-CoV-2 reaches the brain, infects astrocytes, and consequently, leads to neuronal death or dysfunction. These deregulated processes could contribute to the structural and functional alterations seen in the brains of COVID-19 patients.

Reactive astrogliosis is associated with higher cerebral glucose consumption in the early Alzheimer's continuum

PURPOSE

Glial activation is one of the earliest mechanisms to be altered in Alzheimer's disease (AD). Glial fibrillary acidic protein (GFAP) relates to reactive astrogliosis and can be measured in both cerebrospinal fluid (CSF) and blood. Plasma GFAP has been suggested to become altered earlier in AD than its CSF counterpart. Although astrocytes consume approximately half of the glucose-derived energy in the brain, the relationship between reactive astrogliosis and cerebral glucose metabolism is poorly understood. Here, we aimed to investigate the association between fluorodeoxyglucose ([¹⁸F]FDG) uptake and reactive astrogliosis, by means of GFAP quantified in both plasma and CSF for the same participants.

METHODS

We included 314 cognitively unimpaired participants from the ALFA + cohort, 112 of whom were amyloid-β (Aβ) positive. Associations between GFAP markers and [¹⁸F]FDG uptake were studied. We also investigated whether these associations were modified by Aβ and tau status (AT stages).

RESULTS

Plasma GFAP was positively associated with glucose consumption in the whole brain, while CSF GFAP associations with [¹⁸F]FDG uptake were only observed in specific smaller areas like temporal pole and superior temporal lobe. These associations persisted when accounting for biomarkers of Aβ pathology but became negative in Aβ-positive and tau-positive participants (A + T +) in similar areas of AD-related hypometabolism.

CONCLUSIONS

Higher astrocytic reactivity, probably in response to early AD pathological changes, is related to higher glucose consumption. With the onset of tau pathology, the observed uncoupling between astrocytic biomarkers and glucose consumption might be indicative of a failure to sustain the higher energetic demands required by reactive astrocytes.

Identification and validation of Alzheimer's disease-related metabolic brain pattern in biomarker confirmed Alzheimer's dementia patients

Metabolic brain biomarkers have been incorporated in various diagnostic guidelines of neurodegenerative diseases, recently. To improve their diagnostic accuracy a biologically and clinically homogeneous sample is needed for their identification. Alzheimer's disease-related pattern (ADRP) has been identified previously in cohorts of clinically diagnosed patients with dementia due to Alzheimer's disease (AD), meaning that its diagnostic accuracy might have been reduced due to common clinical misdiagnosis. In our study, we aimed to identify ADRP in a cohort of AD patients with CSF confirmed diagnosis, validate it in large out-of-sample cohorts and explore its relationship with patients' clinical status. For identification we analyzed 2-[18F]FDG PET brain scans of 20 AD patients and 20 normal controls (NCs). For validation, 2-[18F]FDG PET scans from 261 individuals with AD, behavioral variant of frontotemporal dementia, mild cognitive impairment and NC were analyzed. We identified an ADRP that is characterized by relatively reduced metabolic activity in temporoparietal cortices, posterior cingulate and precuneus which co-varied with relatively increased metabolic activity in the cerebellum. ADRP expression significantly differentiated AD from NC (AUC = 0.95) and other dementia types (AUC = 0.76-0.85) and its expression correlated with clinical measures of global cognition and neuropsychological indices in all cohorts.

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.

Assessment of the In Vivo Relationship Between Cerebral Hypometabolism, Tau Deposition, TSPO Expression, and Synaptic Density in a Tauopathy Mouse Model: a Multi-tracer PET Study

Cerebral glucose hypometabolism is a typical hallmark of Alzheimer’s disease (AD), usually associated with ongoing neurodegeneration and neuronal dysfunction. However, underlying pathological processes are not fully understood and reproducibility in animal models is not well established. The aim of the present study was to investigate the regional interrelation of glucose hypometabolism measured by [¹⁸F]FDG positron emission tomography (PET) with various molecular targets of AD pathophysiology using the PET tracers [¹⁸F]PI-2620 for tau deposition, [¹⁸F]DPA-714 for TSPO expression associated with neuroinflammation, and [¹⁸F]UCB-H for synaptic density in a transgenic tauopathy mouse model. Seven-month-old rTg4510 mice (n = 8) and non-transgenic littermates (n = 8) were examined in a small animal PET scanner with the tracers listed above. Hypometabolism was observed throughout the forebrain of rTg4510 mice. Tau pathology, increased TSPO expression, and synaptic loss were co-localized in the cortex and hippocampus and correlated with hypometabolism. In the thalamus, however, hypometabolism occurred in the absence of tau-related pathology. Thus, cerebral hypometabolism was associated with two regionally distinct forms of molecular pathology: (1) characteristic neuropathology of the Alzheimer-type including synaptic degeneration and neuroinflammation co-localized with tau deposition in the cerebral cortex, and (2) pathological changes in the thalamus in the absence of other markers of AD pathophysiology, possibly reflecting downstream or remote adaptive processes which may affect functional connectivity. Our study demonstrates the feasibility of a multitracer approach to explore complex interactions of distinct AD-pathomechanisms in vivo in a small animal model. The observations demonstrate that multiple, spatially heterogeneous pathomechanisms can contribute to hypometabolism observed in AD mouse models and they motivate future longitudinal studies as well as the investigation of possibly comparable pathomechanisms in human patients.

Metabolic imaging and plasticity

Positron emission tomography greatly advanced our understanding on the underlying neural mechanisms of movement disorders. PET with flurodeoxyglucose (FDG) is especially useful as it depicts regional metabolic activity level that can predict patients' symptoms. Multivariate pattern analysis has been used to determine and quantify the co-varying brain networks associated with specific clinical traits of neurodegenerative disease. The result is a biomarker, useful for diagnosis, treatments, and follow up studies. Parkinsonian traits and parkinsonisms are associated with specific spatial pattern of metabolic abnormality useful for differential diagnosis. This approach has also been used for monitoring disease progression and novel treatment responses mostly in Parkinson's disease. In this book chapter, we, illustrate and discuss the significance of the brain networks associated with disease and their modification with neuroplastic changes.

Saturation Transfer MRI for Detection of Metabolic and Microstructural Impairments Underlying Neurodegeneration in Alzheimer's Disease

Alzheimer's disease (AD) is one of the most common causes of dementia and difficult to study as the pool of subjects is highly heterogeneous. Saturation transfer (ST) magnetic resonance imaging (MRI) methods are quantitative modalities with potential for non-invasive identification and tracking of various aspects of AD pathology. In this review we cover ST-MRI studies in both humans and animal models of AD over the past 20 years. A number of magnetization transfer (MT) studies have shown promising results in human brain. Increased computing power enables more quantitative MT studies, while access to higher magnetic fields improves the specificity of chemical exchange saturation transfer (CEST) techniques. While much work remains to be done, results so far are very encouraging. MT is sensitive to patterns of AD-related pathological changes, improving differential diagnosis, and CEST is sensitive to particular pathological processes which could greatly assist in the development and monitoring of therapeutic treatments of this currently incurable disease.

Schizophrenia-associated LRRTM1 regulates cognitive behavior through controlling synaptic function in the mediodorsal thalamus

Reduced activity of the mediodorsal thalamus (MD) and abnormal functional connectivity of the MD with the prefrontal cortex (PFC) cause cognitive deficits in schizophrenia. However, the molecular basis of MD hypofunction in schizophrenia is not known. Here, we identified leucine-rich-repeat transmembrane neuronal protein 1 (LRRTM1), a postsynaptic cell-adhesion molecule, as a key regulator of excitatory synaptic function and excitation-inhibition balance in the MD. LRRTM1 is strongly associated with schizophrenia and is highly expressed in the thalamus. Conditional deletion of Lrrtm1 in the MD in adult mice reduced excitatory synaptic function and caused a parallel reduction in the afferent synaptic activity of the PFC, which was reversed by the reintroduction of LRRTM1 in the MD. Our results indicate that chronic reduction of synaptic strength in the MD by targeted deletion of Lrrtm1 functionally disengages the MD from the PFC and may account for cognitive, social, and sensorimotor gating deficits, reminiscent of schizophrenia.

Synaptic Damage and Its Clinical Correlates in People With Early Huntington Disease: A PET Study

BACKGROUND AND OBJECTIVES

Synaptic damage has been proposed to play a major role in the pathophysiology of Huntington's disease (HD), but in vivo evidence in humans is lacking. We performed a PET imaging study to assess synaptic damage and its clinical correlates in early HD in vivo. METHODS: In this cross-sectional study, premanifest and early manifest (Shoulson-Fahn stage 1 and 2) HD mutation carriers and age- and gender-matched healthy controls underwent clinical assessment of motor and non-motor manifestations and time-of-flight PET with ¹¹C-UCB-J, a radioligand targeting the ubiquitous presynaptic terminal marker SV2A. We also performed ¹⁸F-FDG PET in all subjects, as regional cerebral glucose consumption is thought to largely reflect synaptic activity. Volumes of interest were delineated based on individual 3D T1 MRI. Standardized uptake value ratio (SUVR)-1 images were calculated for ¹¹C-UCB-J with the centrum semiovale as reference region. ¹⁸F-FDG PET activity was normalized to the pons. All PET data were corrected for partial volume effects. Volume of interest- and voxel-based analyses were performed. Correlations between clinical scores and ¹¹C-UCB-J PET data were calculated.

RESULTS

18 HD mutation carriers (51.4 ± 11.6 years; 6 female; 7 premanifest, 11 early manifest) and 15 healthy controls (52.3 ± 3.5 years; 4 female) were included. In the HD group, significant loss of SV2A binding was found in putamen, caudate, pallidum, cerebellum, parietal, temporal and frontal cortex, whereas reduced ¹⁸F-FDG uptake was restricted to caudate and putamen. In the premanifest subgroup, ¹¹C-UCB-J and ¹⁸F-FDG PET showed significant reductions in putamen and caudate only. In the total HD group, SV2A loss in the putamen correlated with motor impairment.

DISCUSSION

Our data reveal loss of presynaptic terminal integrity in early HD, which begins in the striatum in the premanifest phase, spreads extensively to extrastriatal regions in the early manifest phase, and correlates with motor impairment. ¹¹C-UCB-J PET is more sensitive than ¹⁸F-FDG PET for detection of extrastriatal changes in early HD.

CLASSIFICATION OF EVIDENCE

This study provides class III evidence that ¹¹C-UCB-J PET accurately identifies HD from normal controls.

Thioredoxin interacting protein drives astrocytic glucose hypometabolism in corticosterone-induced depressive state

Brain energetics disturbance is a hypothesized cause of depression. Glucose is the predominant fuel of brain energy metabolism, however, the cell-specific change of glucose metabolism and underlying molecular mechanism in depression remain unclear. In this study, we firstly applied ¹⁸ F-FDG PET and observed brain glucose hypometabolism in prefrontal cortex (PFC) of corticosterone-induced depression of rats. Next, astrocytic glucose hypometabolism was identified in PFC slices in in both corticosterone-induced depression of rats and cultured primary astrocytes from newborn rat PFC after stress-level corticosterone (100 nM) stimulation. Furthermore, we found the blockage of glucose uptake and the decrease of plasma membrane (PM) translocation of glucose transporter 1 (GLUT1) in astrocytic glucose hypometabolism under depressive condition. Interestingly, thioredoxin interacting protein (TXNIP), a glucose metabolism sensor and controller, was found to be overexpressed in corticosterone-stimulated astrocytes in vivo and in vitro. High TXNIP level could restrict GLUT1-mediated glucose uptake in primary astrocytes in vitro. Adeno-associated virus vector-mediated astrocytic TXNIP overexpression in rat medial PFC suppressed GLUT1 PM translocation, consequently developed depressive-like behavior. Conversely, TXNIP siRNA facilitated GLUT1 PM translocation to recover glucose hypometabolism in corticosterone-exposed cultured astrocytes. Notably, astrocyte-specific knockdown of TXNIP in medial PFC of rats facilitated astrocytic GLUT1 PM translocation, showing obvious antidepressant activity. These findings provide a new astrocytic energetic perspective in the pathogenesis of depression, more importantly, provide TXNIP as a promising molecular target for novel depression therapy.

In vivo synaptic density relates to glucose metabolism at rest in healthy subjects, but is strongly modulated by regional differences

Preclinical and postmortem studies have suggested that regional synaptic density and glucose consumption (CMRGlc) are strongly related. However, the relation between synaptic density and cerebral glucose metabolism in the human brain has not directly been assessed in vivo. Using [¹¹C]UCB-J binding to synaptic vesicle glycoprotein 2 A (SV2A) as indicator for synaptic density and [¹⁸F]FDG for measuring cerebral glucose consumption, we studied twenty healthy female subjects (age 29.6 ± 9.9 yrs) who underwent a single-day dual-tracer protocol (GE Signa PET-MR). Global measures of absolute and relative CMRGlc and specific binding of [¹¹C]UCB-J were indeed highly significantly correlated (r > 0.47, p < 0.001). However, regional differences in relative [¹⁸F]FDG and [¹¹C]UCB-J uptake were observed, with up to 19% higher [¹¹C]UCB-J uptake in the medial temporal lobe (MTL) and up to 17% higher glucose metabolism in frontal and motor-related areas and thalamus. This pattern has a considerable overlap with the brain regions showing different levels of aerobic glycolysis. Regionally varying energy demands of inhibitory and excitatory synapses at rest may also contribute to this difference. Being unaffected by astroglial and/or microglial energy demands, changes in synaptic density in the MTL may therefore be more sensitive to early detection of pathological conditions compared to changes in glucose metabolism.

Mesenchymal Stem Cell-Derived Exosomes Ameliorate Alzheimer's Disease Pathology and Improve Cognitive Deficits

The accumulation of extracellular β-amyloid (Aβ) plaques within the brain is unique to Alzheimer’s disease (AD) and thought to induce synaptic deficits and neuronal loss. Optimal therapies should tackle the core AD pathophysiology and prevent the decline in memory and cognitive functions. This study aimed to evaluate the therapeutic performance of mesenchymal stem cell-derived exosomes (MSC-exosomes), which are secreted membranous elements encapsulating a variety of MSC factors, on AD. A human neural cell culture model with familial AD (FAD) mutations was established and co-cultured with purified MSC-exosomes. 2-[¹⁸F]Fluoro-2-deoxy-d-glucose ([¹⁸F]FDG) and novel object recognition (NOR) testing were performed before/after treatment to evaluate the therapeutic effect in vivo. The AD-related pathology and the expression of neuronal memory/synaptic plasticity-related genes were also evaluated. The results showed that MSC-exosomes reduced Aβ expression and restored the expression of neuronal memory/synaptic plasticity-related genes in the cell model. [¹⁸F]FDG-PET imaging and cognitive assessment revealed a significant improvement in brain glucose metabolism and cognitive function in AD transgenic mice. The phase of neurons and astrocytes in the brain of AD mice were also found to be regulated after treatment with MSC-exosomes. Our study demonstrates the therapeutic mechanism of MSC-exosomes and provides an alternative therapeutic strategy based on cell-free MSC-exosomes for the treatment of AD.

Brain Molecular Connectivity in Neurodegenerative Conditions

Positron emission tomography (PET) allows for the in vivo assessment of early brain functional and molecular changes in neurodegenerative conditions, representing a unique tool in the diagnostic workup. The increased use of multivariate PET imaging analysis approaches has provided the chance to investigate regional molecular processes and long-distance brain circuit functional interactions in the last decade. PET metabolic and neurotransmission connectome can reveal brain region interactions. This review is an overview of concepts and methods for PET molecular and metabolic covariance assessment with evidence in neurodegenerative conditions, including Alzheimer’s disease and Lewy bodies disease spectrum. We highlight the effects of environmental and biological factors on brain network organization. All of the above might contribute to innovative diagnostic tools and potential disease-modifying interventions.

Brain [F-18]FDG PET for Clinical Dementia Workup: Differential Diagnosis of Alzheimer's Disease and Other Types of Dementing Disorders

PET imaging with [F-18]FDG has been used extensively for research and clinical applications in dementia. In the brain, [F-18]FDG accumulates around synapses and represents local neuronal activity. Patterns of altered [F-18]FDG uptake reflecting local neuronal dysfunction provide differential diagnostic clues for various dementing disorders. Image interpretation can be accomplished by employing statistical brain mapping techniques. Various guidelines have been published to support the appropriate use of [F-18]FDG PET for clinical dementia workup. PET images with [F-18]FDG demonstrate distinct patterns of decreased uptake for Alzheimer's disease (AD), Dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD) as well as its multiple subtypes such as behavioral variant FTD, primary progressive aphasia (PPA), progressive supranuclear palsy, and corticobasal degeneration to aid in the differential diagnoses. Mixed dementia, not only AD + Vascular Dementia, but also AD + other neurodegenerative disorders, should also be considered when interpreting [F-18]FDG PET images. Brain PET imaging with [F-18]FDG remains a valuable component of dementia workup owing to its relatively low cost, differential diagnostic performance, widespread availability, and physicians' experience over more than 40 years since the initial development.

Spectral guided sparse inverse covariance estimation of metabolic networks in Parkinson's disease

In neurodegenerative disorders, a clearer understanding of the underlying aberrant networks facilitates the search for effective therapeutic targets and potential cures. [¹⁸F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging data of brain metabolism reflects the distribution of glucose consumption known to be directly related to neural activity. In FDG PET resting-state metabolic data, characteristic disease-related patterns have been identified in group analysis of various neurodegenerative conditions using principal component analysis of multivariate spatial covariance. Notably, among several parkinsonian syndromes, the identified Parkinson’s disease-related pattern (PDRP) has been repeatedly validated as an imaging biomarker of PD in independent groups worldwide. Although the primary nodal associations of this network are known, its connectivity is not fully understood. Here, we describe a novel approach to elucidate functional principal component (PC) network connections by performing graph theoretical sparse network derivation directly within the disease relevant PC partition layer of the whole brain data rather than by searching for associations retrospectively in whole brain sparse representations. Using sparse inverse covariance estimation of each overlapping PC partition layer separately, a single coherent network is detected for each layer in contrast to more spatially modular segmentation in whole brain data analysis. Using this approach, the major nodal hubs of the PD disease network are identified and their characteristic functional pathways are clearly distinguished within the basal ganglia, midbrain and parietal areas. Network associations are further clarified using Laplacian spectral analysis of the adjacency matrices. In addition, the innate discriminative capacity of the eigenvector centrality of the graph derived networks in differentiating PD versus healthy external data provides evidence of their validity.

Advanced non-invasive MRI of neuroplasticity in ischemic stroke: Techniques and applications

Ischemic stroke represents a serious medical condition which could cause survivors suffer from long-term and even lifetime disabilities. After a stroke attack, the brain would undergo varying degrees of recovery, in which the central nervous system could be reorganized spontaneously or with the help of appropriate rehabilitation. Magnetic resonance imaging (MRI) is a non-invasive technique which can provide comprehensive information on structural, functional and metabolic features of brain tissue. In the last decade, there has been an increased technical advancement in MR techniques such as voxel-based morphological analysis (VBM), diffusion magnetic resonance imaging (dMRI), functional magnetic resonance imaging (fMRI), arterial spin-labeled perfusion imaging (ASL), magnetic sensitivity weighted imaging (SWI), quantitative sensitivity magnetization (QSM) and magnetic resonance spectroscopy (MRS) which have been proven to be a valuable tool to study the brain tissue reorganization. Due to MRI indices of neuroplasticity related to neurological outcome could be translated to the clinic. The ultimate goal of this review is to equip readers with a fundamental understanding of advanced MR techniques and their corresponding clinical application for improving the ability to predict neuroplasticity that are most suitable for stroke management.

Pre- and early postnatal enriched environmental experiences prevent neonatal hypoxia-ischemia late neurodegeneration via metabolic and neuroplastic mechanisms

Prenatal and early postnatal periods are important for brain development and neural function. Neonatal insults such as hypoxia-ischemia (HI) causes prolonged neural and metabolic dysregulation, affecting central nervous system maturation. There is evidence that brain hypometabolism could increase the risk of adult-onset neurodegenerative diseases. However, the impact of non-pharmacologic strategies to attenuate HI-induced brain glucose dysfunction is still underexplored. This study investigated the long-term effects of early environmental enrichment in metabolic, cell, and functional responses after neonatal HI. Thereby, male Wistar rats were divided according to surgical procedure, sham, and HI (performed at postnatal day 3), and the allocation to standard (SC) or enriched condition (EC) during gestation and lactation periods. In-vivo cerebral metabolism was assessed by means of [¹⁸ F]-FDG micro-positron emission tomography, and cognitive, biochemical, and histological analyses were performed in adulthood. Our findings reveal that HI causes a reduction in glucose metabolism and glucose transporter levels as well as hyposynchronicity in metabolic brain networks. However, EC during prenatal or early postnatal period attenuated these metabolic disturbances. A positive correlation was observed between [¹⁸ F]-FDG values and volume ratios in adulthood, indicating that preserved tissue by EC is metabolically active. EC promotes better cognitive scores, as well as down-regulation of amyloid precursor protein in the parietal cortex and hippocampus of HI animals. Furthermore, growth-associated protein 43 was up-regulated in the cortex of EC animals. Altogether, results presented support that EC during gestation and lactation period can reduce HI-induced impairments that may contribute to functional decline and progressive late neurodegeneration.

Cognitive impairment in Parkinson's disease: A clinical and pathophysiological overview

Cognitive dysfunction in Parkinson's disease (PD) has received increasing attention, and, together with other non-motor symptoms, exert a significant functional impact in the daily lives of patients. This article aims to compile and briefly summarize selected published data about clinical features, cognitive evaluation, biomarkers, and pathophysiology of PD-related dementia (PDD). The literature search included articles indexed in the MEDLINE/PubMed database, published in English, over the last two decades. Despite significant progress on clinical criteria and cohort studies for PD-mild cognitive impairment (PD-MCI) and PDD, there are still knowledge gaps about its exact molecular and pathological basis. Here we overview the scientific literature on the role of functional circuits, neurotransmitter systems (monoaminergic and cholinergic), basal forebrain, and brainstem nuclei dysfunction in PD-MCI. Correlations between neuroimaging and cerebrospinal fluid (CSF) biomarkers, clinical outcomes, and pathological results are described to aid in uncovering the neurodegeneration pattern in PD-MCI and PDD.

Alteration of metabolic connectivity in a rat model of deafferentation pain: a 18F-FDG PET/CT study

OBJECTIVE

Refractory deafferentation pain has been evidenced to be related to central nervous system neuroplasticity. In this study, the authors sought to explore the underlying glucose metabolic changes in the brain after brachial plexus avulsion, particularly metabolic connectivity.

METHODS

Rats with unilateral deafferentation following brachial plexus avulsion, a pain model of deafferentation pain, were scanned by small-animal 2-deoxy-[18F]fluoro-d-glucose (18F-FDG) PET/CT to explore the changes of metabolic connectivity among different brain regions. Thermal withdrawal latency (TWL) and mechanical withdrawal threshold (MWT) of the intact forepaw were also measured for evaluating pain sensitization. Brain metabolic connectivity and TWL were compared from baseline to 1 week after brachial plexus avulsion.

RESULTS

Alterations of metabolic connectivity occurred not only within the unilateral hemisphere contralateral to the injured forelimb, but also in the other hemisphere and even in the connections between bilateral hemispheres. Metabolic connectivity significantly decreased between sensorimotor-related areas within the left hemisphere (contralateral to the injured forelimb) (p < 0.05), as well as between areas across bilateral hemispheres (p < 0.05). Connectivity between areas within the right hemisphere (ipsilateral to the injured forelimb) significantly increased (p = 0.034). TWL and MWT of the left (intact) forepaw after surgery were significantly lower than those at baseline (p < 0.001).

CONCLUSIONS

This study revealed that unilateral brachial plexus avulsion facilitates pain sensitization in the opposite limb. A specific pattern of brain metabolic changes occurred in this procedure. Metabolic connectivity reorganized not only in the sensorimotor area corresponding to the affected forelimb, but also in extensive areas involving the bilateral hemispheres. These findings may broaden our understanding of central nervous system changes, as well as provide new information and a potential intervention target for nosogenesis of deafferentation pain.

LRRK2 and GBA Variants Exert Distinct Influences on Parkinson's Disease-Specific Metabolic Networks

The natural history of idiopathic Parkinson's disease (PD) varies considerably across patients. While PD is generally sporadic, there are known genetic influences: the two most common, mutations in the LRRK2 or GBA1 gene, are associated with slower and more aggressive progression, respectively. Here, we applied graph theory to metabolic brain imaging to understand the effects of genotype on the organization of previously established PD-specific networks. We found that closely matched PD patient groups with the LRRK2-G2019S mutation (PD-LRRK2) or GBA1 variants (PD-GBA) expressed the same disease networks as sporadic disease (sPD), but PD-LRRK2 and PD-GBA patients exhibited abnormal increases in network connectivity that were not present in sPD. Using a community detection strategy, we found that the location and modular distribution of these connections differed strikingly across genotypes. In PD-LRRK2, connections were gained within the network core, with the formation of distinct functional pathways linking the cerebellum and putamen. In PD-GBA, by contrast, the majority of functional connections were formed outside the core, involving corticocortical pathways at the network periphery. Strategically localized connections within the core in PD-LRRK2 may maintain PD network activity at lower levels than in PD-GBA, resulting in a less aggressive clinical course.

Brain metabolic signatures across the Alzheimer's disease spectrum

PURPOSE

Given the challenges posed by the clinical diagnosis of atypical Alzheimer's disease (AD) variants and the limited imaging evidence available in the prodromal phases of atypical AD, we assessed brain hypometabolism patterns at the single-subject level in the AD variants spectrum. Specifically, we tested the accuracy of [¹⁸F]FDG-PET brain hypometabolism, as a biomarker of neurodegeneration, in supporting the differential diagnosis of atypical AD variants in individuals with dementia and mild cognitive impairment (MCI).

METHODS

We retrospectively collected N = 67 patients with a diagnosis of typical AD and AD variants according to the IWG-2 criteria (22 typical-AD, 15 frontal variant-AD, 14 logopenic variant-AD and 16 posterior variant-AD). Further, we included N = 11 MCI subjects, who subsequently received a clinical diagnosis of atypical AD dementia at follow-up (21 ± 11 months). We assessed brain hypometabolism patterns at group- and single-subject level, using W-score maps, measuring their accuracy in supporting differential diagnosis. In addition, the regional prevalence of cerebral hypometabolism was computed to identify the most vulnerable core regions.

RESULTS

W-score maps pointed at distinct, specific patterns of hypometabolism in typical and atypical AD variants, confirmed by the assessment of core hypometabolism regions, showing that each variant was characterized by specific regional vulnerabilities, namely in occipital, left-sided, or frontal brain regions. ROC curves allowed discrimination among AD variants and also non-AD dementia (i.e., dementia with Lewy bodies and behavioral variant of frontotemporal dementia), with high sensitivity and specificity. Notably, we provide preliminary evidence that, even in AD prodromal phases, these specific [¹⁸F]FDG-PET patterns are already detectable and predictive of clinical progression to atypical AD variants at follow-up.

CONCLUSIONS

The AD variant-specific patterns of brain hypometabolism, highly consistent at single-subject level and already evident in the prodromal stages, represent relevant markers of disease neurodegeneration, with highly supportive diagnostic and prognostic role.

Application of advanced brain positron emission tomography-based molecular imaging for a biological framework in neurodegenerative proteinopathies

INTRODUCTION

A rapid transition from a clinical-based classification to a pathology-based classification of neurodegenerative conditions, largely promoted by the increasing availability of imaging biomarkers, is emerging. The Framework for Innovative Multi-tracer molecular Brain Imaging, funded by the EU Joint Program - Neurodegenerative Disease Research 2016 "Working Groups for Harmonisation and Alignment in Brain Imaging Methods for Neurodegeneration," aimed at providing a roadmap for the applications of established and new molecular imaging techniques in dementia.

METHODS

We consider current and future implications of adopting a pathology-based framework for the use and development of positron emission tomography techniques.

RESULTS

This approach will enhance efforts to understand the multifactorial etiology of Alzheimer's disease and other dementias.

DISCUSSION

The availability of pathology biomarkers will soon transform clinical and research practice. Crucially, a comprehensive understanding of strengths and caveats of these techniques will promote an informed use to take full advantage of these tools.

Blood Flow and Glucose Metabolism Dissociation in the Putamen Is Predictive of Levodopa Induced Dyskinesia in Parkinson's Disease Patients

Background: The forefront treatment of Parkinson's disease (PD) is Levodopa. When patients are treated with Levodopa cerebral blood flow is increased while cerebral metabolic rate is decreased in key subcortical regions including the putamen. This phenomenon is especially pronounced in patients with Levodopa-induced dyskinesia (LID). Method: To study the effect of clinically-determined anti-parkinsonian medications, 10 PD patients (5 with LID and 5 without LID) have been scanned with FDG-PET (a probe for glucose metabolism) and perfusion MRI (a probe for cerebral blood flow) both when they are ON and OFF medications. Patients additionally underwent resting state fMRI to detect changes in dopamine-mediated cortico-striatal connectivity. The degree of blood flow-glucose metabolism dissociation was quantified by comparing the FDG-PET and perfusion MRI data. Results: A significant interaction effect (imaging modality × medication; blood flow-glucose metabolism dissociation) has been found in the putamen (p = 0.023). Post-hoc analysis revealed that anti-parkinsonian medication consistently normalized the pathologically hyper-metabolic state of the putamen while mixed effects were observed in cerebral blood flow changes. This dissociation was especially predominant in patients with LID compared to those without. Unlike the prior study, this differentiation was not observed when cortico-striatal functional connectivity was assessed. Conclusion: We confirmed striatal neurovascular dissociation between FDG-PET and perfusion MRI in response to clinically determined anti-parkinsonian medication. We further proposed a novel analytical method to quantify the degree of dissociation in the putamen using only the ON condition scans, Putamen-to-thalamus Hyper-perfusion/hypo-metabolism Index (PHI), which may have the potential to be used as a biomarker for LID (correctly classifying 8 out 10 patients). For wider use of PHI, a larger validation study is warranted.

Correlations of Neuropsychological and Metabolic Brain Changes in Parkinson's Disease and Other α-Synucleinopathies

Cognitive impairment is a common feature in Parkinson's disease (PD) and other α-synucleinopathies as 80% of PD patients develop dementia within 20 years. Early cognitive changes in PD patients present as a dysexecutive syndrome, broadly characterized as a disruption of the fronto-striatal dopamine network. Cognitive deficits in other domains (recognition memory, attention processes and visuospatial abilities) become apparent with the progression of PD and development of dementia. In dementia with Lewy bodies (DLB) the cognitive impairment develops early or even precedes parkinsonism and it is more pronounced in visuospatial skills and memory. Cognitive impairment in the rarer α-synucleinopathies (multiple system atrophy and pure autonomic failure) is less well studied. Metabolic brain imaging with positron emission tomography and [¹⁸F]-fluorodeoxyglucose (FDG-PET) is a well-established diagnostic method in neurodegenerative diseases, including dementias. Changes in glucose metabolism precede those seen on structural magnetic resonance imaging (MRI). Reduction in glucose metabolism and atrophy have been suggested to represent consecutive changes of neurodegeneration and are linked to specific cognitive disorders (e.g., dysexecutive syndrome, memory impairment, visuospatial deficits etc.). Advances in the statistical analysis of FDG-PET images enabling a network analysis broadened our understanding of neurodegenerative brain processes. A specific cognitive pattern related to PD was identified by applying voxel-based network modeling approach. The magnitude of this pattern correlated significantly with patients' cognitive skills. Specific metabolic brain changes were observed also in patients with DLB as well as in a prodromal phase of α-synucleinopathy: REM sleep behavior disorder. Metabolic brain imaging with FDG-PET is a reliable biomarker of neurodegenerative brain diseases throughout their course, precisely reflecting their topographic distribution, stage and functional impact.

Neuron-specific deficits of bioenergetic processes in the dorsolateral prefrontal cortex in schizophrenia

Schizophrenia is a devastating illness that affects over 2 million people in the United States and costs society billions of dollars annually. New insights into the pathophysiology of schizophrenia are needed to provide the conceptual framework to facilitate development of new treatment strategies. We examined bioenergetic pathways in the dorsolateral prefrontal cortex (DLPFC) of subjects with schizophrenia and control subjects using western blot analysis, quantitative real-time polymerase chain reaction, and enzyme/substrate assays. Laser-capture microdissection-quantitative polymerase chain reaction was used to examine these pathways at the cellular level. We found decreases in hexokinase (HXK) and phosphofructokinase (PFK) activity in the DLPFC, as well as decreased PFK1 mRNA expression. In pyramidal neurons, we found an increase in monocarboxylate transporter 1 mRNA expression, and decreases in HXK1, PFK1, glucose transporter 1 (GLUT1), and GLUT3 mRNA expression. These results suggest abnormal bioenergetic function, as well as a neuron-specific defect in glucose utilization, in the DLPFC in schizophrenia.

A new perspective for advanced positron emission tomography-based molecular imaging in neurodegenerative proteinopathies

Recent studies in neurodegenerative conditions have increasingly highlighted that the same neuropathology can trigger different clinical phenotypes or, vice-versa, that similar phenotypes can be triggered by different neuropathologies. This evidence has called for the adoption of a pathology spectrum-based approach to study neurodegenerative proteinopathies. These conditions share brain deposition of abnormal protein aggregates, leading to aberrant biochemical, metabolic, functional, and structural changes. Positron emission tomography (PET) is a well-recognized and unique tool for the in vivo assessment of brain neuropathology, and novel PET techniques are emerging for the study of specific protein species. Today, key applications of PET range from early research and clinical diagnostic tools to their use in clinical trials for both participants screening and outcome evaluation. This position article critically reviews the role of distinct PET molecular tracers for different neurodegenerative proteinopathies, highlighting their strengths, weaknesses, and opportunities, with special emphasis on methodological challenges and future applications.

Brain Molecular Connectivity in Neurodegenerative Diseases: Recent Advances and New Perspectives Using Positron Emission Tomography

Positron emission tomography (PET) represents a unique molecular tool to get in vivo access to a wide spectrum of biological and neuropathological processes, of crucial relevance for neurodegenerative conditions. Although most PET findings are based on massive univariate approaches, in the last decade the increasing interest in multivariate methods has paved the way to the assessment of unexplored cerebral features, spanning from resting state brain networks to whole-brain connectome properties. Currently, the combination of molecular neuroimaging techniques with multivariate connectivity methods represents one of the most powerful, yet still emerging, approach to achieve novel insights into the pathophysiology of neurodegenerative diseases. In this review, we will summarize the available evidence in the field of PET molecular connectivity, with the aim to provide an overview of how these studies may increase the understanding of the pathogenesis of neurodegenerative diseases, over and above "traditional" structural/functional connectivity studies. Considering the available evidence, a major focus will be represented by molecular connectivity studies using [18F]FDG-PET, today applied in the major neuropathological spectra, from amyloidopathies and tauopathies to synucleinopathies and beyond. Pioneering studies using PET tracers targeting brain neuropathology and neurotransmission systems for connectivity studies will be discussed, their strengths and limitations highlighted with reference to both applied methodology and results interpretation. The most common methods for molecular connectivity assessment will be reviewed, with particular emphasis on the available strategies to investigate molecular connectivity at the single-subject level, of potential relevance for not only research but also diagnostic purposes. Finally, we will highlight possible future perspectives in the field, with reference in particular to newly available PET tracers, which will expand the application of molecular connectivity to new, exciting, unforeseen possibilities.

Experimental Methods to Inform Diagnostic Approaches for Painful TMJ Osteoarthritis

Temporomandibular joint (TMJ) osteoarthritis (OA) is a degenerative disease of the joint that can produce persistent orofacial pain as well as functional and structural changes to its bone, cartilage, and ligaments. Despite advances in the clinical utility and reliability of the Diagnostic Criteria for Temporomandibular Disorders, clinical tools inadequately predict which patients will develop chronic TMJ pain and degeneration, limiting clinical management. The challenges of managing and treating TMJ OA are due, in part, to a limited understanding of the mechanisms contributing to the development and maintenance of TMJ pain. OA is initiated by multiple factors, including injury, aging, abnormal joint mechanics, and atypical joint shape, which can produce microtrauma, remodeling of joint tissues, and synovial inflammation. TMJ microtrauma and remodeling can increase expression of cytokines, chemokines, and catabolic factors that damage synovial tissues and can activate free nerve endings in the joint. Although studies have separately investigated inflammation-driven orofacial pain, acute activity of the trigeminal nerve, or TMJ tissue degeneration and/or damage, the temporal mechanistic factors leading to chronic TMJ pain are undefined. Limited understanding of the interaction between degeneration, intra-articular chemical factors, and pain has further restricted the development of targeted, disease-modifying drugs to help patients avoid long-term pain and invasive procedures, like TMJ replacement. A range of animal models captures features of intra-articular inflammation, joint overloading, and tissue damage. Although those models traditionally measure peripheral sensitivity as a surrogate for pain, recent studies recognize the brain's role in integrating, modulating, and interpreting nociceptive inputs in the TMJ, particularly in light of psychosocial influences on TMJ pain. The articular and neural contributors to TMJ pain, imaging modalities with clinical potential to identify TMJ OA early, and future directions for clinical management of TMJ OA are reviewed in the context of evidence in the field.

Brain Glucose Metabolism: Integration of Energetics with Function

Glucose is the long-established, obligatory fuel for brain that fulfills many critical functions, including ATP production, oxidative stress management, and synthesis of neurotransmitters, neuromodulators, and structural components. Neuronal glucose oxidation exceeds that in astrocytes, but both rates increase in direct proportion to excitatory neurotransmission; signaling and metabolism are closely coupled at the local level. Exact details of neuron-astrocyte glutamate-glutamine cycling remain to be established, and the specific roles of glucose and lactate in the cellular energetics of these processes are debated. Glycolysis is preferentially upregulated during brain activation even though oxygen availability is sufficient (aerobic glycolysis). Three major pathways, glycolysis, pentose phosphate shunt, and glycogen turnover, contribute to utilization of glucose in excess of oxygen, and adrenergic regulation of aerobic glycolysis draws attention to astrocytic metabolism, particularly glycogen turnover, which has a high impact on the oxygen-carbohydrate mismatch. Aerobic glycolysis is proposed to be predominant in young children and specific brain regions, but re-evaluation of data is necessary. Shuttling of glucose- and glycogen-derived lactate from astrocytes to neurons during activation, neurotransmission, and memory consolidation are controversial topics for which alternative mechanisms are proposed. Nutritional therapy and vagus nerve stimulation are translational bridges from metabolism to clinical treatment of diverse brain disorders.

Testing the diagnostic accuracy of [18F]FDG-PET in discriminating spinal- and bulbar-onset amyotrophic lateral sclerosis

PURPOSE

The role for [18F]FDG-PET in supporting amyotrophic lateral sclerosis (ALS) diagnosis is not fully established. In this study, we aim at evaluating [18F]FDG-PET hypo- and hyper-metabolism patterns in spinal- and bulbar-onset ALS cases, at the single-subject level, testing the diagnostic value in discriminating the two conditions, and the correlations with core clinical symptoms severity.

METHODS

We included 95 probable-ALS patients with [18F]FDG-PET scan and clinical follow-up. [18F]FDG-PET images were analyzed with an optimized voxel-based-SPM method. The resulting single-subject SPM-t maps were used to: (a) assess brain regional hypo- and hyper-metabolism; (b) evaluate the accuracy of regional hypo- and hyper metabolism in discriminating spinal vs. bulbar-onset ALS; (c) perform correlation analysis with motor symptoms severity, as measured by ALS-FRS-R.

RESULTS

Primary motor cortex showed the most frequent hypo-metabolism in both spinal-onset (∼57%) and bulbar-onset (∼64%) ALS; hyper-metabolism was prevalent in the cerebellum in both spinal-onset (∼56.5%) and bulbar-onset (∼55.7%) ALS, and in the occipital cortex in bulbar-onset (∼62.5%) ALS. Regional hypo- and hyper-metabolism yielded a very low accuracy (AUC < 0.63) in discriminating spinal- vs. bulbar-onset ALS, as obtained from single-subject SPM-t-maps. Severity of motor symptoms correlated with hypo-metabolism in sensorimotor cortex in spinal-onset ALS, and with cerebellar hyper-metabolism in bulbar-onset ALS.

CONCLUSIONS

The high variability in regional hypo- and hyper-metabolism patterns, likely reflecting the heterogeneous pathology and clinical phenotypes, limits the diagnostic potential of [18F]FDG-PET in discriminating spinal and bulbar onset patients.

Neurobiology of cognitive remediation in schizophrenia: Effects of EAAT2 polymorphism

Cognitive deficits represent core features of schizophrenia, affecting quality of life and functioning. The excitatory amino acid transporter 2 (EAAT2) is responsible for the majority of glutamate reuptake and its activity is crucial for glutamatergic neurotransmission, prevention of excitotoxic damage and cerebral metabolism. Different studies reported that EAAT2 rs4354668 (-181 T/G) influences cognitive functions and brain structures in patients with schizophrenia. Specifically, the G allele, linked to lower EAAT2 expression, was associated with impaired prefrontal cognitive performance and reduced grey matter volumes. Cognitive remediation therapy (CRT) is one of the best available tool to treat cognitive deficits in schizophrenia, able to induce a neuroplastic modulation of cognitive functions. The present study aims to investigate the effects of rs4354668 on CRT outcome, also considering possible genotype interaction with antipsychotic (AP) treatment, since EAAT2 expression is negatively influenced by clozapine. We examined rs4354668 in 88 clinically stabilized patients with schizophrenia, treated with CRT and assessed at enrolment, at the end of CRT and after 3 months. We observed greater working memory improvements among patients carrying the T/T genotype, regardless of AP treatment. Moreover, we reported a significant interaction between pharmacological treatment and rs4354668 on executive functions, with greater improvements among T/T patients treated with APs other than clozapine. These observations suggest that impaired EAAT2 expression may attenuate CRT outcome. Moreover, our results indicate the possibility that rs4354668 could also differentially influence the response to CRT depending on the AP treatment.

Potential neuroprotective role of astroglial exosomes against smoking-induced oxidative stress and HIV-1 replication in the central nervous system

INTRODUCTION

HIV-1-infected smokers are at risk of oxidative damage to neuronal cells in the central nervous system by both HIV-1 and cigarette smoke. Since neurons have a weak antioxidant defense system, they mostly depend on glial cells, particularly astrocytes, for protection against oxidative damage and neurotoxicity. Astrocytes augment the neuronal antioxidant system by supplying cysteine-containing products for glutathione synthesis, antioxidant enzymes such as SOD and catalase, glucose for antioxidant regeneration via the pentose-phosphate pathway, and by recycling of ascorbic acid. Areas covered: The transport of antioxidants and energy substrates from astrocytes to neurons could possibly occur via extracellular nanovesicles called exosomes. This review highlights the neuroprotective potential of exosomes derived from astrocytes against smoking-induced oxidative stress, HIV-1 replication, and subsequent neurotoxicity observed in HIV-1-positive smokers. Expert opinion: During stress conditions, the antioxidants released from astrocytes either via extracellular fluid or exosomes to neurons may not be sufficient to provide neuroprotection. Therefore, we put forward a novel strategy to combat oxidative stress in the central nervous system, using synthetically developed exosomes loaded with antioxidants such as glutathione and the anti-aging protein Klotho.