PET Neuroimaging Research Articles

Effects of chronic treatment with metformin on brain glucose hypometabolism and central insulin actions in transgenic mice with tauopathy

Brain glucose hypometabolism and insulin alterations are common features of many neurological diseases. Herein we sought to corroborate the brain glucose hypometabolism that develops with ageing in 12-months old Tau-VLW transgenic mice, a model of tauopathy, as well as to determine whether this model showed signs of altered peripheral glucose metabolism. Our results demonstrated that 12-old months Tau mice exhibited brain glucose hypometabolism as well as basal hyperglycemia, impaired glucose tolerance, hyperinsulinemia, and signs of insulin resistance. Then, we further studied the effect of chronic metformin treatment (9 months) in Tau-VLW mice from 9 to 18 months of age. Longitudinal PET neuroimaging studies revealed that chronic metformin altered the temporal profile in the progression of brain glucose hypometabolism associated with ageing. Besides, metformin altered the content and/or phosphorylation of key components of the insulin signal transduction pathway in the frontal cortex leading to significant changes in the content of the active forms. Thus, metformin increased the expression of pAKT-Y474 while reducing pmTOR-S2448 and pGSK3β. These changes might be related, at least partially, to a slow progression of ageing, neurological damage, and cognitive decline. Metformin also improved the peripheral glucose tolerance and the ability of the Tau-VLW mice to maintain their body weight through ageing. Altogether our study shows that the tau-VLW mice could be a useful model to study the potential interrelationship between tauopathy and central and peripheral glucose metabolism alterations. More importantly our results suggest that chronic metformin treatment may have direct beneficial central effects by post-transcriptional modulation of key components of the insulin signal transduction pathway.

An In Vivo High-Resolution Human Brain Atlas of Synaptic Density.

Synapses are fundamental to the function of the central nervous system and are implicated in a number of brain disorders. Despite their pivotal role, a comprehensive imaging resource detailing the distribution of synapses in the human brain has been lacking until now. Here, we employ high-resolution PET neuroimaging in healthy humans (17F/16M) to create a 3D atlas of the synaptic marker Synaptic Vesicle glycoprotein 2A (SV2A). Calibration to absolute density values (pmol/ml) was achieved by leveraging postmortem human brain autoradiography data. The atlas unveils distinctive cortical and subcortical gradients of synapse density that reflect functional topography and hierarchical order from core sensory to higher-order integrative areas-a distribution that diverges from SV2A mRNA patterns. Furthermore, we found a positive association between IQ and SV2A density in several higher-order cortical areas. This new resource will help advance our understanding of brain physiology and the pathogenesis of brain disorders, serving as a pivotal tool for future neuroscience research.

Association of Loneliness with Functional Connectivity MRI, Amyloid-β PET, and Tau PET Neuroimaging Markers of Vulnerability for Alzheimer's Disease.

Loneliness has been declared an "epidemic" associated with negative physical, mental, and cognitive health outcomes such as increased dementia risk. Less is known about the relationship between loneliness and advanced neuroimaging correlates of Alzheimer's disease (AD). To assess whether loneliness was associated with advanced neuroimaging markers of AD using neuroimaging data from Framingham Heart Study (FHS) participants without dementia. In this cross-sectional observational analysis, we used functional connectivity MRI (fcMRI), amyloid-β (Aβ) PET, and tau PET imaging data collected between 2016 and 2019 on eligible FHS cohort participants. Loneliness was defined as feeling lonely at least one day in the past week. The primary fcMRI marker was Default Mode Network intra-network connectivity. The primary PET imaging markers were Aβ deposition in precuneal and FLR (frontal, lateral parietal and lateral temporal, retrosplenial) regions, and tau deposition in the amygdala, entorhinal, and rhinal regions. Of 381 participants (mean age 58 [SD 10]) who met inclusion criteria for fcMRI analysis, 5% were classified as lonely (17/381). No association was observed between loneliness status and network changes. Of 424 participants (mean age 58 [SD = 10]) meeting inclusion criteria for PET analyses, 5% (21/424) were lonely; no associations were observed between loneliness and either Aβ or tau deposition in primary regions of interest. In this cross-sectional study, there were no observable associations between loneliness and select fcMRI, Aβ PET, and tau PET neuroimaging markers of AD risk. These findings merit further investigation in prospective studies of community-based cohorts.

Neuroinflammation in post-acute sequelae of COVID-19 (PASC) as assessed by [11C]PBR28 PET correlates with vascular disease measures

The COVID-19 pandemic caused by SARS-CoV-2 has triggered a consequential public health crisis of post-acute sequelae of COVID-19 (PASC), sometimes referred to as long COVID. The mechanisms of the heterogeneous persistent symptoms and signs that comprise PASC are under investigation, and several studies have pointed to the central nervous and vascular systems as being potential sites of dysfunction. In the current study, we recruited individuals with PASC with diverse symptoms, and examined the relationship between neuroinflammation and circulating markers of vascular dysfunction. We used [11C]PBR28 PET neuroimaging, a marker of neuroinflammation, to compare 12 PASC individuals versus 43 normative healthy controls. We found significantly increased neuroinflammation in PASC versus controls across a wide swath of brain regions including midcingulate and anterior cingulate cortex, corpus callosum, thalamus, basal ganglia, and at the boundaries of ventricles. We also collected and analyzed peripheral blood plasma from the PASC individuals and found significant positive correlations between neuroinflammation and several circulating analytes related to vascular dysfunction. These results suggest that an interaction between neuroinflammation and vascular health may contribute to common symptoms of PASC.

PCA and logistic regression in 2-[18F]FDG PET neuroimaging as an interpretable and diagnostic tool for Alzheimer’s disease

Objective. to develop an optimization and training pipeline for a classification model based on principal component analysis and logistic regression using neuroimages from PET with 2-[18F]fluoro-2-deoxy-D-glucose (FDG PET) for the diagnosis of Alzheimer’s disease (AD). Approach. as training data, 200 FDG PET neuroimages were used, 100 from the group of patients with AD and 100 from the group of cognitively normal subjects (CN), downloaded from the repository of the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Regularization methods L1 and L2 were tested and their respective strength varied by the hyperparameter C. Once the best combination of hyperparameters was determined, it was used to train the final classification model, which was then applied to test data, consisting of 192 FDG PET neuroimages, 100 from subjects with no evidence of AD (nAD) and 92 from the AD group, obtained at the Centro de Diagnóstico por Imagem (CDI). Main results. the best combination of hyperparameters was L1 regularization and C ≈ 0.316. The final results on test data were accuracy = 88.54%, recall = 90.22%, precision = 86.46% and AUC = 94.75%, indicating that there was a good generalization to neuroimages outside the training set. Adjusting each principal component by its respective weight, an interpretable image was obtained that represents the regions of greater or lesser probability for AD given high voxel intensities. The resulting image matches what is expected by the pathophysiology of AD. Significance. our classification model was trained on publicly available and robust data and tested, with good results, on clinical routine data. Our study shows that it serves as a powerful and interpretable tool capable of assisting in the diagnosis of AD in the possession of FDG PET neuroimages. The relationship between classification model output scores and AD progression can and should be explored in future studies.

Association between Trust of Researchers and Interest in Participation in Alzheimer’s Disease Biomarker Research

AbstractBackgroundThe study examined whether trust in researchers affects interest in AD (Alzheimer’s disease) biomarker research participation, specifically AD blood biomarkers and MRI and PET neuroimaging, and whether this was independent of other factors commonly associated with hesitancy to participate in research, including race and knowledge of AD.Methods258 community‐dwelling Black and 141 non‐Hispanic White adults (age ≥ 55) who had never participated in AD research completed a survey about their perceptions of AD biomarker research. The survey asked participants to select one of three responses, “Yes,” “Unsure,” and “No” to 6 trust statements, with yes being the highest level of trust. Questions specifically assessed whether survey participants trusted researchers to keep information confidential, be honest, component, not cause harm, treat them equally, and share results with them and their community. Those who answered yes to all 6 questions were categorized as having very high trust, and those who answered no or unsure to any of the 6 questions were categorized as having lower trust. Ordinal logistic regression models were used for the analysis of outcome variables with three possible responses (i.e. interest in participation in an AD biomarker study and individual procedures, motivators for research participation). We adjusted for age, education, sex, race, and knowledge about AD.ResultParticipants with very high trust in researchers were less hesitant about doing AD biomarker research (OR 0.32 (95% CI (0.20‐0.52), P < 0.001). Participants with concerns about confidentiality, study risks, and being treated equally had greater hesitancy about doing AD biomarker research (P’s < 0.05). Concerns about researchers’ competency were associated specifically with lower interest in doing neuroimaging procedures (P’s < 0.05). Very high trust in researchers was associated with greater interest in return of results, particularly brain scans (OR 1.92 (95% CI 1.06‐3.48), P = 0.032).ConclusionEven after other factors known to affect AD research participation, trust remains a highly significant factor affecting the interest in AD research participation in blood biomarker neuroimaging procedures. Recruitment strategies for AD biomarker research may need to address participants’ trust concerns, specifically confidentiality, study risks, and equity.

Association between lipopolysaccharide, immune biomarkers and cerebral amyloid‐beta deposition in older adults with mild cognitive impairment & major depressive disorder

AbstractBackgroundInflammatory activation and increased immune response to lipopolysaccharide (LPS, a cell wall component of gut bacteria) is observed in both depression and cognitive decline. Depression is associated with accelerated cognitive decline, and persistent inflammatory activation may link depression and cognitive decline in later life. We determined if LPS is associated with inflammatory activation and cerebral deposition of amyloid‐beta (Abeta) in older adults with Mild Cognitive Impairment (MCI) and/or remitted Major Depressive Disorder (rMDD).MethodSerum samples of LPS, LPS‐binding protein (LBP, which enhances the inflammatory response to LPS), and inflammatory markers (Interleukin 6 [Il‐6], C‐reactive protein [CRP], Monocyte Chemoattractant Protein 1 [MCP‐1]) were measured using ELISA. Abeta deposition was measured using PET neuroimaging using [11C]‐PIB radiotracer. Global amyloid burden was calculated using a composite Standardized Uptake Value Ratio (SUVR) score with the cerebellar cortex as the reference region. Multivariable linear regression analyses, adjusting for significant demographic and genetic variables, were conducted to determine if LPS, LBP, inflammatory biomarkers, MCI and rMDD were independently associated with global cerebral deposition of Abeta.ResultAmong 155 study participants (79 with MCI only, 54 with both MCI and rMDD, 22 with rMDD only) we found a median Abeta SUVR of 1.41 (IQR 0.57). There was no significant association between LPS (beta ‐1.28, 95% CI ‐11.69, 9.13, p = 0.8) or LBP (beta ‐0.02, 95% CI ‐0.05, 0.006, p = 0.12) and global deposition of Abeta, following adjustment for age, sex, and APOE genotype. LBP was positively correlated with inflammatory biomarkers: CRP (r = 0.49, p < 0.001) and IL‐6 (r = 0.21, p = 0.01) but no inflammatory biomarker was significantly associated with Abeta deposition. Having a history of rMDD (beta ‐0.09, 95% CI ‐0.26, 0.08, p = 0.28) or MCI alone (beta ‐0.11, 95% CI ‐0.47, 0.049, p = 0.11) was not associated with deposition of Abeta.ConclusionIn this cross‐sectional analysis, we did not find an association between LPS/LBP, immune biomarkers, remitted MDD and global deposition of Abeta. Future analyses should examine the longitudinal relationships between peripheral and central biomarkers of immune activation with cerebral Abeta deposition in patients and controls.

Neuroinflammation is linked to dementia risk in Parkinson's disease.

The development of dementia is a devastating aspect of Parkinson's disease (PD), affecting nearly half of patients within 10 years post-diagnosis. For effective therapies to prevent and slow progression to PD dementia (PDD), the key mechanisms that determine why some people with PD develop early dementia, while others remain cognitively unaffected, need to be understood. Neuroinflammation and tau protein accumulation have been demonstrated in post-mortem PD brains, and in many other neurodegenerative disorders leading to dementia. However, whether these processes mediate dementia risk early on in the PD disease course is not established. To this end, we used PET neuroimaging with 11C-PK11195 to index neuroinflammation and 18F-AV-1451 for misfolded tau in early PD patients, stratified according to dementia risk in our 'Neuroinflammation and Tau Accumulation in Parkinson's Disease Dementia' (NET-PDD) study. The NET-PDD study longitudinally assesses newly-diagnosed PD patients in two subgroups at low and high dementia risk (stratified based on pentagon copying, semantic fluency, MAPT genotype), with comparison to age- and sex-matched controls. Non-displaceable binding potential (BPND) in 43 brain regions (Hammers' parcellation) was compared between groups (pairwise t-tests), and associations between BPND of the tracers tested (linear-mixed-effect models). We hypothesized that people with higher dementia risk have greater inflammation and/or tau accumulation in advance of significant cognitive decline. We found significantly elevated neuroinflammation (11C-PK11195 BPND) in multiple subcortical and restricted cortical regions in the high dementia risk group compared with controls, while in the low-risk group this was limited to two cortical areas. The high dementia risk group also showed significantly greater neuroinflammation than the low-risk group concentrated on subcortical and basal ganglia regions. Neuroinflammation in most of these regions was associated with worse cognitive performance (Addenbrooke's Cognitive Examination-III score). Overall neuroinflammation burden also correlated with serum levels of pro-inflammatory cytokines. In contrast, increases in 18F-AV-1451 (tau) BPND in PD versus controls were restricted to subcortical regions where off-target binding is typically seen, with no relationship to cognition found. Whole-brain 18F-AV-1451 burden correlated with serum phosphorylated tau181 levels. Although there was minimal regional tau accumulation in PD, regional neuroinflammation and tau burden correlated in PD participants, with the strongest association in the high dementia risk group, suggesting possible co-localization of these pathologies. In conclusion, our findings suggest that significant regional neuroinflammation in early PD might underpin higher risk for PDD development, indicating neuroinflammation as a putative early modifiable aetiopathological disease factor to prevent or slow dementia development using immunomodulatory strategies.

P15.13.B DEVELOPMENT OF [18F]AG-120 AS AN IMAGING AGENT FOR THE DETECTION OF THE MUTANT ISOCITRATE DEHYDROGENASE 1 IN GLIOMA BY PET

Abstract BACKGROUND Gliomas are highly invasive and infiltrative solid tumors that present significant clinical challenges in terms of achieving complete surgical resection. These tumors often harbor mutated isocitrate dehydrogenase enzymes (mIDH), making them attractive theranostic targets. Therefore, accurately assessing mIDH status is essential for effective patient management. Currently, the presence of mIDH1 is determined either by invasive biopsy or indirectly by measuring the mIDH-derived oncometabolite 2-hydroxyglutarate (2-HG) using magnetic resonance spectroscopy (MRS). The availability of mIDH-targeted radioligands would allow for PET neuroimaging to detect the mIDH1 protein directly and non-invasively. MATERIAL AND METHODS The study involved obtaining 18F-labeled AG-120 (Ivosidenib), an FDA-approved small molecule inhibitor of mIDH, by Cu-mediated radiofluorination of a corresponding diastereomerically pure stannyl precursor. The researchers studied the internalization of [18F]AG-120 in vitro in U251 human glioblastoma cells stably transfected with IDH1 or IDH1R132H. Brain uptake and metabolism of [18F]AG-120 were investigated in healthy CD-1 mice by dynamic PET-MR imaging and radio-chromatographic analyses of plasma and brain tissue. Dynamic PET-CT imaging studies were performed in nude rats bearing U251-IDH1 or U251-IDH1R132H glioblastoma. RESULTS The (S,S)-enantiomer of [18F]AG-120 was successfully prepared, and the procedure was implemented into a remotely-controlled radiosynthesis module. A considerably higher uptake of activity was observed in U251-IDH1R132H cells compared to U251-IDH1 cells (0.422 vs. 0.014% applied activity/μg protein after 120 min incubation). The percentage of non-metabolized [18F]AG-120 in the mouse 30 min post i.v. injection was 85% in plasma and 91% in the brain, respectively. Dynamic PET studies showed limited blood-brain barrier permeation of [18F]AG-120 (SUV < 0.1 within the first 5 min post i.v. injection), which could be significantly increased by inhibiting the p-glycoprotein 1 with cyclosporine A. PET studies with glioblastoma rats indicated slightly higher tumor-to-blood ratios in IDH1R132H-tumors compared to IDH1-tumors (~1.7 vs. ~1.3 at 40-60 min p.i.). CONCLUSION For the first time, pure (S,S)-[18F]AG-120 has been synthesized. In addition, GMP-compliant production is facilitated by the established automated radiosynthesis. Despite limited BBB permeation, [18F]AG-120 shows target-specific internalization in vitro and high metabolic stability in vivo. Furthermore, the slightly higher accumulation of [18F]AG-120 in IDH1R132H-glioblastoma compared to IDH1-glioblastoma in vivo encourages further evaluation of mIDH inhibitors for the noninvasive detection of IDH1R132H in glioma by PET. SUPPORT European-Regional-Development-Fund ERDF and Sächsische-Aufbaubank SAB (#100364142).

Functional PET Neuroimaging in Consciousness Evaluation: Study Protocol.

Ensuring a robust and reliable evaluation of coma deepness and prognostication of neurological outcome is challenging. We propose to develop PET neuroimaging as a new diagnostic and prognosis tool for comatose patients using a recently published methodology to perform functional PET (fPET). This exam permits the quantification of task-specific changes in neuronal metabolism in a single session. The aim of this protocol is to determine whether task-specific changes in glucose metabolism during the acute phase of coma are able to predict recovery at 18 months. Participation will be proposed for all patients coming for a standard PET-CT in our center in order to evaluate global cerebral metabolism during the comatose state. Legally appointed representative consent will be obtained to slightly modify the exam protocol: (1) 18F-fluorodeoxyglucose (18F-FDG) bolus plus continuous infusion instead of a simple bolus and (2) more time under camera to perform dynamic acquisition. Participants will undergo a 55-min fPET session with a 20% bolus + 80% infusion protocol. Two occurrences of three block (5-min rest, 10-min auditory stimulation and 10-min emotional auditory stimulation) will be performed after reaching equilibrium of FDG arterial concentration. We will compare the regional brain metabolism at rest and during the sessions of auditory and emotional auditory stimulation to search for a determinant of coma recovery (18 months of follow-up after the exam). Emotional auditory stimulation should induce an activation of: the auditory cortex, the consciousness areas and the neural circuitry for emotion (function to coma deepness). An activation analysis will be carried out to highlight regional brain activation using dedicated custom-made software based on Python statistical and image processing toolboxes. The association between activation levels and the Coma Recovery Scale-Revisited (CRS-R) will be assessed using multivariate analysis. If successful, the results from this study will help improve coma prognosis evaluation based on the pattern of neuronal metabolism at the onset of the pathology. The study protocol, rationale and methods are described in this paper.

Textural properties of microglial activation in Alzheimer's disease as measured by (R)-[11C]PK11195 PET.

Alzheimer's disease is the most common form of dementia worldwide, accounting for 60-70% of diagnosed cases. According to the current understanding of molecular pathogenesis, the main hallmarks of this disease are the abnormal accumulation of amyloid plaques and neurofibrillary tangles. Therefore, biomarkers reflecting these underlying biological mechanisms are recognized as valid tools for an early diagnosis of Alzheimer's disease. Inflammatory mechanisms, such as microglial activation, are known to be involved in Alzheimer's disease onset and progression. This activated state of the microglia is associated with increased expression of the translocator protein 18 kDa. On that account, PET tracers capable of measuring this signature, such as (R)-[11C]PK11195, might be instrumental in assessing the state and evolution of Alzheimer's disease. This study aims to investigate the potential of Gray Level Co-occurrence Matrix-based textural parameters as an alternative to conventional quantification using kinetic models in (R)-[11C]PK11195 PET images. To achieve this goal, kinetic and textural parameters were computed on (R)-[11C]PK11195 PET images of 19 patients with an early diagnosis of Alzheimer's disease and 21 healthy controls and submitted separately to classification using a linear support vector machine. The classifier built using the textural parameters showed no inferior performance compared to the classical kinetic approach, yielding a slightly larger classification accuracy (accuracy of 0.7000, sensitivity of 0.6957, specificity of 0.7059 and balanced accuracy of 0.6967). In conclusion, our results support the notion that textural parameters may be an alternative to conventional quantification using kinetic models in (R)-[11C]PK11195 PET images. The proposed quantification method makes it possible to use simpler scanning procedures, which increase patient comfort and convenience. We further speculate that textural parameters may also provide an alternative to kinetic analysis in (R)-[11C]PK11195 PET neuroimaging studies involving other neurodegenerative disorders. Finally, we recognize that the potential role of this tracer is not in diagnosis but rather in the assessment and progression of the diffuse and dynamic distribution of inflammatory cell density in this disorder as a promising therapeutic target.

Identification of a Putative α-synuclein Radioligand Using an in silico Similarity Search.

Previous studies from our lab utilized an ultra-high throughput screening method to identify compound 1 as a small molecule that binds to alpha-synuclein (α-synuclein) fibrils. The goal of the current study was to conduct a similarity search of 1 to identify structural analogs having improved in vitro binding properties for this target that could be labeled with radionuclides for both in vitro and in vivo studies for measuring α-synuclein aggregates. Using 1 as a lead compound in a similarity search, isoxazole derivative 15 was identified to bind to α-synuclein fibrils with high affinity in competition binding assays. A photocrosslinkable version was used to confirm binding site preference. Derivative 21, the iodo-analog of 15, was synthesized, and subsequently radiolabeled isotopologs [125I]21 and [11C]21 were successfully synthesized for use in in vitro and in vivo studies, respectively. [125I]21 was used in radioligand binding studies in post-mortem Parkinson's disease (PD) and Alzheimer's disease (AD) brain homogenates. In vivo imaging of an α-synuclein mouse model and non-human primates was performed with [11C]21. In silico molecular docking and molecular dynamic simulation studies for a panel of compounds identified through a similarity search, were shown to correlate with Ki values obtained from in vitro binding studies. Improved affinity of isoxazole derivative 15 for α-synuclein binding site 9 was indicated by photocrosslinking studies with CLX10. Design and successful (radio)synthesis of iodo-analog 21 of isoxazole derivative 15 enabled further in vitro and in vivo evaluation. Kd values obtained in vitro with [125I]21 for α-synuclein and Aβ42 fibrils were 0.48 ± 0.08 nM and 2.47 ± 1.30 nM, respectively. [125I]21 showed higher binding in human postmortem PD brain tissue compared with AD tissue, and low binding in control brain tissue. Lastly, in vivo preclinical PET imaging showed elevated retention of [11C]21 in PFF-injected mouse brain. However, in PBS-injected control mouse brain, slow washout of the tracer indicates high non-specific binding. [11C]21 showed high initial brain uptake in a healthy non-human primate, followed by fast washout that may be caused by rapid metabolic rate (21% intact [11C]21 in blood at 5 min p.i.). Through a relatively simple ligand-based similarity search, we identified a new radioligand that binds with high affinity (<10 nM) to α-synuclein fibrils and PD tissue. Although the radioligand has suboptimal selectivity for α-synuclein towards Aβ and high non-specific binding, we show here that a simple in silico approach is a promising strategy to identify novel ligands for target proteins in the CNS with the potential to be radiolabeled for PET neuroimaging studies.

Detection of Alzheimer's disease onset using MRI and PET neuroimaging: longitudinal data analysis and machine learning.

The scientists are dedicated to studying the detection of Alzheimer's disease onset to find a cure, or at the very least, medication that can slow the progression of the disease. This article explores the effectiveness of longitudinal data analysis, artificial intelligence, and machine learning approaches based on magnetic resonance imaging and positron emission tomography neuroimaging modalities for progression estimation and the detection of Alzheimer's disease onset. The significance of feature extraction in highly complex neuroimaging data, identification of vulnerable brain regions, and the determination of the threshold values for plaques, tangles, and neurodegeneration of these regions will extensively be evaluated. Developing automated methods to improve the aforementioned research areas would enable specialists to determine the progression of the disease and find the link between the biomarkers and more accurate detection of Alzheimer's disease onset.

Integrated Approach of Brain Disorder Analysis by Using Deep Learning Based on DNA Sequence

In order to research brain problems using MRI, PET, and CT neuroimaging, a correct understanding of brainfunction is required. This has been considered in earlier times with the support of traditional algorithms. Deep learning process has also been widely considered in these genomics data processing system. In this research, brain disorder illness incliding Alzheimer’s disease, Schizophrenia and Parkinson’s diseaseis is analyzed owing to misdetection of disorders in neuroimaging data examined by means fo traditional methods. Moeover, deep learning approach is incorporated here for classification purpose of brain disorder with the aid of Deep Belief Networks (DBN). Images are stored in a secured manner by using DNA sequence based on JPEG Zig Zag Encryption algorithm (DBNJZZ) approach. The suggested approach is executed and tested by using the performance metric measure such as accuracy, root mean square error, Mean absolute error and mean absolute percentage error. Proposed DBNJZZ gives better performance than previously available methods.

Identification and Prioritization of PET Neuroimaging Targets for Microglial Phenotypes Associated with Microglial Activity in Alzheimer's Disease.

Activation of microglial cells accompanies the progression of many neurodegenerative disorders, including Alzheimer's disease (AD). Development of molecular imaging tools specific to microglia can help elucidate the mechanism through which microglia contribute to the pathogenesis and progression of neurodegenerative disorders. Through analysis of published genetic, transcriptomic, and proteomic data sets, we identified 19 genes with microglia-specific expression that we then ranked based on association with the AD characteristics, change in expression, and potential druggability of the target. We believe that the process we used to identify and rank microglia-specific genes is broadly applicable to the identification and evaluation of targets in other disease areas and for applications beyond molecular imaging.

Polymorphisms in the WWOX gene are associated with brain glucose metabolism and influence cerebrospinal fluid p‐tau181 levels

AbstractBackgroundGenome‐wide association studies (GWAS) studies can be a powerful tool for identifying new single nucleotide polymorphisms (SNPs) associated with multifactorial diseases. Previous GWAS have identified more than 20 genes as potential factors of genetic susceptibility in Alzheimer’s disease (AD). One of them is the protein coding gene WW Domain Containing Oxidoreductase (WWOX), which is highly expressed in mature astrocytes and neurons. Here, we investigated the association between WWOX SNPs, 18F‐FDG PET neuroimaging and cerebrospinal fluid (CSF) levels of tau phosphorylated at threonine 181 (p‐tau181) in elderly individuals from the Alzheimer’s Disease Neuroimaging Initiative (ADNI).MethodsData was acquired from 537 participants (CU= 195; MCI= 314; AD= 28) of the ADNI database. The brain glucose metabolism was estimated using the standard uptake value ratio (SUVr, cerebellum as reference) of FDG‐PET. The presence of the SNPs were integrated to FDG PET images using voxel‐wise generalized linear regression models adjusted for age, gender, diagnostic status, and years of education (RMINC package). Through the Wilcoxon test we determined if the SNPs presence influenced p‐tau181 levels in CSF. All statistical analyzes were performed in the R statistical computing software (version 4.1.2) (significance level of p &lt; 0.05).ResultsSixty‐seven WWOX SNPs were statistically associated with 18F‐FDG PET signal. Voxel‐wise analyses demonstrated that the top ten WWOX SNPs with the highest number of voxels altered in the FDG‐PET images were associated with cortical hypermetabolism (Figure 1, top three). Thirteen WWOX SNPs were significantly associated with lower p‐tau181 concentration in the CSF, including rs7193539 (p = 0.0004), rs7206890 (p = 0.0061), and rs11859281 (p = 0.0009), compared to the reference genotype.ConclusionSeveral SNPs of the WWOX gene were significantly correlated to brain metabolism. The presence of the SNPs can influence p‐tau181 levels, suggesting a role of WWOX in AD, as reported in other previous studies. Our findings suggest a protective effect of these WWOX gene variants. Additional studies are needed to better understand the biological implications of our findings.

Loneliness and subjective cognitive impairment in preclinical Alzheimer’s disease and healthy aging

AbstractBackgroundLoneliness is associated with increased dementia risk, and greater amyloid‐β (Aβ) and tau accumulation in cognitively normal older adults. However, the potential for loneliness to influence cognitive dysfunction during the preclinical disease stage has not yet been examined. Subjective cognitive complaints are an early indicator of cognitive dysfunction in Alzheimer’s disease, and may provide a sensitive endpoint to evaluate the influence of loneliness during the preclinical disease stage. This study evaluated the relationships between loneliness, subjective cognition, and Aβ status in cognitively unimpaired older adults.MethodParticipants were 112 older adults aged 60–81 years (68% female, 89% White) recruited from the Butler Hospital Alzheimer’s Prevention Registry (BAPR). A cut off score of ≥34 on a modified Telephone Interview for Cognitive Status (TICSm) was used to establish unimpaired cognition. All participants completed the 3‐item version of the UCLA Loneliness Scale and the Cognitive Function Index (CFI) to assess loneliness and subjective cognition respectively. At the time of this analysis, a subsample (n = 63) had also undergone PET neuroimaging for classification of Aß status, of which 40% were classified as Aß+.ResultOf the total sample, 28% reported mild‐moderate levels of loneliness, and another 8% reported severe loneliness. Subjective cognitive function was significantly associated with loneliness group, H(2) = 6.66, p = .036, with post hoc analyses indicating a significant trend for subjective cognitive complaints to increase with loneliness severity. Among the PET subsample, there was no significant difference observed between Aß groups in level of loneliness (p = .754) or subjective cognition (p = .852). However, there was a significant association between Aß status and loneliness group (p = .023), with Aß+ individuals being more likely to a be severely lonely (12%, n = 3) relative to the Aß‐ group (0%, n = 0).ConclusionThe results of this study highlight the potential for loneliness to be involved in the preclinical stages of AD by demonstrating associations with both subjective cognitive function and Aß status. Prospective investigations are needed to further disentangle whether loneliness may be an indicator of, or a risk factor for, emerging disease.

Verbal recognition declines in later Braak Stages compared to verbal delayed recall

AbstractBackgroundEpisodic memory decline is a hallmark of cognitive impairment due to Alzheimer’s Disease (AD). Literature has consistently indicated that delayed recall is compromised early in the disease. Recognition memory seems disrupted at late stages, although findings are mixed. Recent PET studies have demonstrated that the presence of tau in the medial temporal lobe (MTL) relates to early deterioration of delayed recall, but no PET studies have assessed how recognition memory relates to tau. We sought to investigate this relationship across the Braak staging continuum.MethodTau PET ([18F]‐MK6240) was acquired for 140 cognitively unimpaired elderly (CU), 54 MCI patients and 33 AD patients. Participants were segregated into Braak stages, based on in vivo PET neuroimaging of tau. Episodic memory was assessed using RAVLT delayed recall and recognition tests. MRI were segmented into probabilistic grey (GM) and white (WM) maps, non‐linearly registered to the ADNI template using Dartel and smoothed with an 8mm FWHM gaussian kernel. Independent samples t‐tests or their nonparametric counterparts were conducted to evaluate differences in memory scores by Braak stage. Voxel‐wise linear regression models were applied, using VoxelStats, with either delayed recall or recognition scores as dependent variables and tau PET as a predictor. Global amyloid, age, sex, education and APOE genotype were entered as covariates.ResultsPairwise comparisons revealed that recognition memory is spared in early Braak stages. Voxel‐wise analyses in the whole sample unveiled that delayed recall and recognition memory relate to tau in virtually the same cortical areas. However, the strength of the relationships widely varied by memory type. Tau‐PET in anterior MTL and posterior hippocampus shows stronger associations with delayed recall, while tau binding in lateral temporal, temporooccipital and posterior areas exhibits stronger associations with recognition memory.ConclusionOur findings support the differentiation between delayed recall and recognition across the AD spectrum. Relationships between delayed recall and tau in the MTL are in concordance with previous research. Moreover, the contrast in the strength of the associations between memory and tau aggregation further supports the notion that delayed recall is already impaired in early Braak stages while recognition is damaged in later Braak stages.

Designing drug occupancy studies with PET neuroimaging: Sample size, occupancy ranges and analytical methods

Molecular neuroimaging is today considered essential for evaluation of novel CNS drugs; it is used to quantify blood-brain barrier permeability, verify interaction with key target and determine the drug dose resulting in 50% occupancy, IC50. In spite of this, there has been limited data available to inform on how to optimize study designs.Through simulations, we here evaluate how IC50 estimation is affected by the (i) range of drug doses administered, (ii) number of subjects included, and (iii) level of noise in the plasma drug concentration measurements. Receptor occupancy is determined from PET distribution volumes using two different methods: the Lassen plot and Likelihood estimation of occupancy (LEO). We also introduce and evaluate a new likelihood-based estimator for direct estimation of IC50 from PET distribution volumes.For estimation of IC50, we find very limited added benefit in scanning individuals who are given drug doses corresponding to less than 40% receptor occupancy. In the range of typical PET sample sizes (5–20 subjects) each extra individual clearly reduces the error of the IC50 estimate.In all simulations, likelihood-based methods gave more precise IC50 estimates than the Lassen plot; four times the number of subjects were required for the Lassen plot to reach the same IC50 precision as LEO.

Early-Stage Alzheimer's Disease Categorization Using PET Neuroimaging Modality and Convolutional Neural Networks in the 2D and 3D Domains.

Alzheimer’s Disease (AD) is a health apprehension of significant proportions that is negatively impacting the ageing population globally. It is characterized by neuronal loss and the formation of structures such as neurofibrillary tangles and amyloid plaques in the early as well as later stages of the disease. Neuroimaging modalities are routinely used in clinical practice to capture brain alterations associated with AD. On the other hand, deep learning methods are routinely used to recognize patterns in underlying data distributions effectively. This work uses Convolutional Neural Network (CNN) architectures in both 2D and 3D domains to classify the initial stages of AD into AD, Mild Cognitive Impairment (MCI) and Normal Control (NC) classes using the positron emission tomography neuroimaging modality deploying data augmentation in a random zoomed in/out scheme. We used novel concepts such as the blurring before subsampling principle and distant domain transfer learning to build 2D CNN architectures. We performed three binaries, that is, AD/NC, AD/MCI, MCI/NC and one multiclass classification task AD/NC/MCI. The statistical comparison revealed that 3D-CNN architecture performed the best achieving an accuracy of 89.21% on AD/NC, 71.70% on AD/MCI, 62.25% on NC/MCI and 59.73% on AD/NC/MCI classification tasks using a five-fold cross-validation hyperparameter selection approach. Data augmentation helps in achieving superior performance on the multiclass classification task. The obtained results support the application of deep learning models towards early recognition of AD.