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An unresolved question for the understanding of Alzheimer’s disease (AD) pathophysiology is why a significant percentage of amyloid-β (Aβ)-positive cognitively unimpaired (CU) individuals do not develop detectable downstream tau pathology and, consequently, clinical deterioration. In vitro evidence suggests that reactive astrocytes unleash Aβ effects in pathological tau phosphorylation. Here, in a biomarker study across three cohorts (n = 1,016), we tested whether astrocyte reactivity modulates the association of Aβ with tau phosphorylation in CU individuals. We found that Aβ was associated with increased plasma phosphorylated tau only in individuals positive for astrocyte reactivity (Ast+). Cross-sectional and longitudinal tau–positron emission tomography analyses revealed an AD-like pattern of tau tangle accumulation as a function of Aβ only in CU Ast+ individuals. Our findings suggest astrocyte reactivity as an important upstream event linking Aβ with initial tau pathology, which may have implications for the biological definition of preclinical AD and for selecting CU individuals for clinical trials.

Animal studies suggest that the apolipoprotein E ε4 ( APOE ε4) allele is a culprit of early microglial activation in Alzheimer’s disease (AD). Here, we tested the association between APOE ε4 status and microglial activation in living individuals across the aging and AD spectrum. We studied 118 individuals with positron emission tomography for amyloid-β (Aβ; [ 18 F]AZD4694), tau ([ 18 F]MK6240), and microglial activation ([ 11 C]PBR28). We found that APOE ε4 carriers presented increased microglial activation relative to noncarriers in early Braak stage regions within the medial temporal cortex accounting for Aβ and tau deposition. Furthermore, microglial activation mediated the Aβ-independent effects of APOE ε4 on tau accumulation, which was further associated with neurodegeneration and clinical impairment. The physiological distribution of APOE mRNA expression predicted the patterns of APOE ε4-related microglial activation in our population, suggesting that APOE gene expression may regulate the local vulnerability to neuroinflammation. Our results support that the APOE ε4 genotype exerts Aβ-independent effects on AD pathogenesis by activating microglia in brain regions associated with early tau deposition.

Objective:To test the utility of longitudinal changes in plasma phosphorylated tau 181 (p-tau181) and neurofilament light chain (NfL) as surrogate markers for clinical trials targeting cognitively unimpaired (CU) populations.Methods:We estimated the sample size needed to test a 25% drug effect with 80% of power at a 0.05 level on reducing changes in plasma markers in CU participants from ADNI database.Results:We included 257 CU individuals [45.5% males; mean age = 73 (6) years; 32% amyloid-beta (Aβ) positive]. Changes in plasma NfL were associated with age, while changes in plasma p-tau181 with progression to amnestic mild cognitive impairment. Clinical trials using p-tau181 and NfL would require 85% and 63% smaller sample sizes, respectively, for a 24-month than a 12-month follow-up. A population enrichment strategy using intermediate levels of Aβ positron emission tomography (Centiloid 20-40) further reduced the sample size of 24-month clinical trial using p-tau181 (73%) and NfL (59%) as a surrogate.Discussion:Plasma p-tau181/NfL can potentially be used to monitor large-scale population interventions in CU individuals. The enrollment of CU with intermediate Aβ levels constitutes the alternative with the largest effect size and most cost-effective for trials testing drug effect on changes in plasma p-tau181 and NfL.

Purpose Advances in functional imaging allowed us to visualize brain glucose metabolism in vivo and non-invasively with [18F]fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) imaging. In the past decades, FDG-PET has been instrumental in the understanding of brain function in health and disease. The source of the FDG-PET signal has been attributed to neuronal uptake, with hypometabolism being considered as a direct index of neuronal dysfunction or death. However, other brain cells are also metabolically active, including astrocytes. Based on the astrocyte-neuron lactate shuttle hypothesis, the activation of the glutamate transporter 1 (GLT-1) acts as a trigger for glucose uptake by astrocytes. With this in mind, we investigated glucose utilization changes after pharmacologically downregulating GLT-1 with clozapine (CLO), an antipsychotic drug. Methods Adult male Wistar rats (control, n = 14; CLO, n = 12) received CLO (25/35mg kg−1) for six weeks. CLO effects were evaluated in vivo with FDG-PET and cortical tissue was used to evaluate glutamate uptake, GLT-1 and GLAST levels. CLO treatment effects were also assessed in cortical astrocyte cultures (glucose and glutamate uptake, GLT-1 and GLAST levels) and in cortical neuronal cultures (glucose uptake). Results CLO markedly reduced in vivo brain glucose metabolism in several brain areas, especially in the cortex. Ex vivo analyses demonstrated decreased cortical glutamate transport along with GLT-1 mRNA and protein downregulation. In astrocyte cultures, CLO decreased GLT-1 density as well as glutamate and glucose uptake. By contrast, in cortical neuronal cultures, CLO did not affect glucose uptake. Conclusion This work provides in vivo demonstration that GLT-1 downregulation induces astrocyte-dependent cortical FDG-PET hypometabolism - mimicking the hypometabolic signature seen in people developing dementia - and adds further evidence that astrocytes are key contributors of the FDG-PET signal.

An unresolved question for the understanding of Alzheimer’s disease (AD) pathophysiology is why a significant percentage of amyloid β (Aβ)-positive cognitively unimpaired (CU) individuals do not develop detectable downstream tau pathology and, consequently, clinical deterioration. In vitro evidence suggests that reactive astrocytes are key to unleashing Aβ effects in pathological tau phosphorylation. In a large study (n=1,016) across three cohorts, we tested whether astrocyte reactivity modulates the association of Aβ with plasma tau phosphorylation in CU people. We found that Aβ pathology was associated with increased plasma phosphorylated tau levels only in individuals positive for astrocyte reactivity (Ast+). Cross-sectional and longitudinal tau-PET analysis revealed that tau tangles accumulated as a function of Aβ burden only in CU Ast+ individuals with a topographic distribution compatible with early AD. Our findings suggest that increased astrocyte reactivity is an important upstream event linking Aβ burden with initial tau pathology which might have implications for the biological definition of preclinical AD and for selecting individuals for early preventive clinical trials.

ImportanceThe recent proliferation of phosphorylated tau (p-tau) biomarkers has raised questions about their preferential association with the hallmark pathologies of Alzheimer disease (AD): amyloid-β plaques and tau neurofibrillary tangles.ObjectiveTo determine whether cerebrospinal fluid (CSF) and plasma p-tau biomarkers preferentially reflect cerebral β-amyloidosis or neurofibrillary tangle aggregation measured with positron emission tomography (PET).Design, Setting, and ParticipantsThis was a cross-sectional study of 2 observational cohorts: the Translational Biomarkers in Aging and Dementia (TRIAD) study, with data collected between October 2017 and August 2021, and the Alzheimer’s Disease Neuroimaging Initiative (ADNI), with data collected between September 2015 and November 2019. TRIAD was a single-center study, and ADNI was a multicenter study. Two independent subsamples were derived from TRIAD. The first TRIAD subsample comprised individuals assessed with CSF p-tau (p-tau181, p-tau217, p-tau231, p-tau235), [18F]AZD4694 amyloid PET, and [18F]MK6240 tau PET. The second TRIAD subsample included individuals assessed with plasma p-tau (p-tau181, p-tau217, p-tau231), [18F]AZD4694 amyloid PET, and [18F]MK6240 tau PET. An independent cohort from ADNI comprised individuals assessed with CSF p-tau181, [18F]florbetapir PET, and [18F]flortaucipir PET. Participants were included based on the availability of p-tau and PET biomarker assessments collected within 9 months of each other. Exclusion criteria were a history of head trauma or magnetic resonance imaging/PET safety contraindications. No participants who met eligibility criteria were excluded.ExposuresAmyloid PET, tau PET, and CSF and plasma assessments of p-tau measured with single molecule array (Simoa) assay or enzyme-linked immunosorbent assay.Main Outcomes and MeasuresAssociations between p-tau biomarkers with amyloid PET and tau PET.ResultsA total of 609 participants (mean [SD] age, 66.9 [13.6] years; 347 female [57%]; 262 male [43%]) were included in the study. For all 4 phosphorylation sites assessed in CSF, p-tau was significantly more closely associated with amyloid-PET values than tau-PET values (p-tau181 difference, 13%; 95% CI, 3%-22%; P = .006; p-tau217 difference, 11%; 95% CI, 3%-20%; P = .003; p-tau231 difference, 15%; 95% CI, 5%-22%; P 235 difference, 9%; 95% CI, 1%-19%; P = .02) . These results were replicated with plasma p-tau181 (difference, 11%; 95% CI, 1%-22%; P = .02), p-tau217 (difference, 9%; 95% CI, 1%-19%; P = .02), p-tau231 (difference, 13%; 95% CI, 3%-24%; P = .009), and CSF p-tau181 (difference, 9%; 95% CI, 1%-21%; P = .02) in independent cohorts.Conclusions and RelevanceResults of this cross-sectional study of 2 observational cohorts suggest that the p-tau abnormality as an early event in AD pathogenesis was associated with amyloid-β accumulation and highlights the need for careful interpretation of p-tau biomarkers in the context of the amyloid/tau/neurodegeneration, or A/T/(N), framework.

The mechanisms by which the apolipoprotein E ε4 (APOEε4) allele influences Alzheimer’s disease (AD) pathophysiological progression are poorly understood. Here, we tested the association of APOEε4 carriership and amyloid-β (Aβ) burden with longitudinal tau pathology progression. We studied 104 individuals across the aging and AD spectrum who underwent clinical assessments, APOE genotyping, magnetic resonance imaging, positron emission tomography (PET) for Aβ ([18F]AZD4694) and tau ([18F]MK-6240) at baseline, as well as a follow-up tau-PET scan (mean follow-up, 2.4 years). We further assessed longitudinal changes in tau phosphorylation (plasma phosphorylated tau at threonine 217 [p-tau217+]), brain atrophy (gray matter density), and clinical function (clinical dementia rating scale sum of boxes). We found that APOEε4 carriership potentiates Aβ effects on longitudinal tau tangle accumulation over two years. The APOEε4-potentiated Aβ effects on tangles were mediated by longitudinal plasma p-tau217+ increase. This longitudinal tau accumulation as measured by PET was accompanied by brain atrophy and clinical decline. Our results support a model in which the APOEε4 allele plays a key role in Aβ downstream effects on the aggregation of phosphorylated tau in the form of neurofibrillary tangles in the living human brain.

Objective To investigate the relationship between the topography of amyloid‐β plaques, tau neurofibrillary tangles, and the overlap between the two, with cognitive dysfunction in individuals without dementia. Methods We evaluated 154 individuals who were assessed with amyloid‐β PET with [18F]AZD4694, tau‐PET with [18F]MK6240, structural MRI, and neuropsychological testing. We also evaluated an independent cohort of 240 individuals who were assessed with amyloid‐β PET with [18F]Florbetapir, tau‐PET with [18F]Flortaucipir, structural MRI, and neuropsychological testing. Using the VoxelStats toolbox, we conducted voxel‐wise linear regressions between amyloid‐PET, tau‐PET, and their interaction with cognitive function, correcting for age, sex, and years of education. Results In both cohorts, we observed that tau‐PET standardized uptake value ratio in medial temporal lobes was associated with clinical dementia rating Sum of Boxes (CDR‐SoB) scores independently of local amyloid‐PET uptake (FWE corrected at p

BackgroundPositron emission tomography (PET) imaging has greatly improved the diagnosis and monitoring of Alzheimer’s disease (AD). The recently developed neuroinformatic field is expanding analytical and computational strategies to study multimodal neuroscience data. One approach is integrating PET imaging and omics to provide new insights into AD pathophysiology.MethodsHippocampal and blood transcriptomic data of cognitively unimpaired (CU) and cognitively impaired (CI) individuals were obtained from Gene Expression Omnibus (GEO) databases and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We used the differentially expressed genes (DEGs) from these datasets to implement a modular dimension reduction approach based on Gene Ontology (GO) and reverse engineering of transcriptional networks centered on transcription factors (TF). GO clusters and regulatory units of TF were selected to undergo integration with [18F]Fluorodeoxyglucose ([18F]FDG)-PET images using voxel-wise linear regression models adjusted for age, gender, years of education, andAPOEε4 status.ResultsThe GO semantic similarity resulted in 16 GO clusters enriched with overlapping DEGs in blood and the brain. Voxel-wise analysis revealed a strong association between the cluster related to the regulation of protein serine/threonine kinase activity and the [18F]FDG-PET signal in the brain. The master regulator analysis showed 61 regulatory units of TF significantly enriched with DEGs. The voxel-wise analysis of these regulons showed that zinc-finger-related regulatory units had the closest association with brain glucose metabolism.ConclusionWe identified multiple biological processes and regulatory units of TF associated with [18F]FDG-PET metabolism in the brain of individuals across the aging and AD clinical spectrum. Furthermore, the prominent enrichment of protein serine/threonine kinase activity-related GO cluster and the zinc-finger-related regulatory units highlight the potential gene signatures associated with changes in glucose metabolism due to AD pathology.

Microglial activation is an early phenomenon in Alzheimer’s disease (AD) that may occur prior to and independently of amyloid-β (Aβ) aggregation. Recent studies in transgenic animal models suggest that the apolipoprotein E ε4 (APOEε4) allele may be a culprit of early microglial activation in AD. However, it is unclear whether the APOEε4 genotype is associated with microglial reactivity in the living human brain. Here, we tested whether APOEε4 carriership is associated with microglial activation in individuals across the aging and AD spectrum. We studied 118 individuals who had positron emission tomography (PET) for Aβ ([18F]AZD4694), tau ([18F]MK6240), and microglial activation ([11C]PBR28), as well as clinical, genetic, and magnetic resonance imaging data. We found that APOEε4 carriership was associated with increased microglial activation mainly in early Braak-staging regions within the medial temporal cortex, and this effect of APOEε4 was independent of Aβ and tau deposition. Furthermore, microglial activation mediated the Aβ-independent effects of APOEε4 on downstream tau accumulation, neurodegeneration, and clinical impairment. Interestingly, the physiological distribution of APOE mRNA expression, obtained from the Allen Human Atlas, predicted the patterns of APOEε4-related microglial activation in our population, suggesting that the deleterious effects of APOEε4 occur at the level of gene expression. These results support a model in which the APOEε4 has Aβ-independent effects on AD pathogenesis by activating microglia in brain regions associated with early tau deposition. Our findings provide a rationale for the development of novel AD therapies targeting the interplay between ApoE and neuroinflammation.

ObjectiveTo perform a systematic review and meta-analysis to determine whether fluid and imaging astrocyte biomarkers are altered in Alzheimer disease (AD).MethodsPubMed and Web of Science databases were searched for articles reporting fluid or imaging astrocyte biomarkers in AD. Pooled effect sizes were determined with standardized mean differences (SMDs) using the Hedge G method with random effects to determine biomarker performance. Adapted questions from the Quality Assessment of Diagnostic Accuracy Studies were applied for quality assessment. A protocol for this study has been previously registered in PROSPERO (registration number: CRD42020192304).ResultsThe initial search identified 1,425 articles. After exclusion criteria were applied, 33 articles (a total of 3,204 individuals) measuring levels of glial fibrillary acidic protein (GFAP), S100B, chitinase-3-like protein 1 (YKL-40), and aquaporin 4 in the blood and CSF, as well as monoamine oxidase-B indexed by PET 11C-deuterium-l-deprenyl, were included. GFAP (SMD 0.94, 95% confidence interval [CI] 0.71–1.18) and YKL-40 (SMD 0.76, 95% CI 0.63–0.89) levels in the CSF and S100B levels in the blood (SMD 2.91, 95% CI 1.01–4.8) were found to be significantly increased in patients with AD.ConclusionsDespite significant progress, applications of astrocyte biomarkers in AD remain in their early days. This meta-analysis demonstrated that astrocyte biomarkers are consistently altered in AD and supports further investigation for their inclusion in the AD clinical research framework for observational and interventional studies.

IntroductionIn Alzheimer’s disease clinical research, glial fibrillary acidic protein (GFAP) released into the cerebrospinal fluid and blood is widely measured and perceived as a biomarker of reactive astrogliosis. However, it was demonstrated that GFAP levels differ in individuals presenting with amyloid-β (Aβ) or tau pathology. The molecular underpinnings behind this specificity are unexplored. Here we investigated biomarker and transcriptomic associations of GFAP-positive astrocytes with Aβ and tau pathologies in humans and mouse models.MethodsWe studied 90 individuals with plasma GFAP, Aβ- and Tau-PET to investigate the association between biomarkers. Then, transcriptomic analysis in hippocampal GFAP-positive astrocytes isolated from mouse models presenting Aβ (PS2APP) or tau (P301S) pathologies was applied to explore differentially expressed genes (DEGs), Gene Ontology processes, and protein-protein interaction networks associated with each phenotype.ResultsIn humans, we found that plasma GFAP associates with Aβ but not tau pathology. Unveiling the unique nature of GFAP-positive astrocytic responses to Aβ or tau pathology, mouse transcriptomics showed scarce overlap of DEGs between the Aβ and tau mouse models, While Aβ GFAP-positive astrocytes were overrepresented with genes associated with proteostasis and exocytosis-related processes, tau hippocampal GFAP-positive astrocytes presented greater abnormalities in functions related to DNA/RNA processing and cytoskeleton dynamics.ConclusionOur results offer insights into Aβ- and tau-driven specific signatures in GFAP-positive astrocytes. Characterizing how different underlying pathologies distinctly influence astrocyte responses is critical for the biological interpretation of astrocyte-related biomarker and suggests the need to develop context-specific astrocyte targets to study AD.FundingThis study was supported by Instituto Serrapilheira, Alzheimer’s Association, CAPES, CNPq and FAPERGS.

IntroductionPlasma amyloid-β (Aβ), phosphorylated tau (p-tau), and glial fibrillar acid protein (GFAP) can identify Alzheimer’s disease (AD) pathophysiology with high accuracy. However, comparing their performance in the same individuals remains under-explored.MethodsWe compared the predictive performance of plasma Aβ42/40, p-tau(at threonine 181 and 231), neurofilament light (NfL), and GFAP to identify Aβ- and tau-PET positivity in 138 cognitive unimpaired (CU) and 87 cognitive impaired (CI) individuals.ResultsIn CU, plasma p-tau231 had the best performance to identify both Aβ- and tau-PET positivity. In CI, plasma GFAP showed the best predictive accuracy to identify both Aβ and tau-PET positivity.DiscussionOur results support plasma p-tau231 as a marker of early AD pathology and, that GFAP best identifies both PET Aβ and tau abnormalities in the brain of CI individuals. These findings highlight that the performance of blood-based protein biomarkers to identify the presence of AD pathophysiology is disease-stage dependent.

Astrocytes can adopt multiple molecular phenotypes in the brain of Alzheimer’s disease (AD) patients. Here, we studied the associations of cerebrospinal fluid (CSF) glial fibrillary acidic protein (GFAP) and chitinase-3-like protein 1 (YKL-40) levels with brain amyloid-β (Aβ) and tau pathologies. We assessed 121 individuals across the aging and AD clinical spectrum with positron emission tomography (PET) brain imaging for Aβ ([18F]AZD4694) and tau ([18F]MK-6240), as well as CSF GFAP and YKL-40 measures. We observed that higher CSF GFAP levels were associated with elevated Aβ-PET but not tau-PET load. By contrast, higher CSF YKL-40 levels were associated with elevated tau-PET but not Aβ-PET burden. Structural equation modeling revealed that CSF GFAP and YKL-40 mediate the effects of Aβ and tau, respectively, on hippocampal atrophy, which was further associated with cognitive impairment. Our results suggest the existence of distinct astrocyte biomarker signatures in response to brain Aβ and tau accumulation, which may contribute to our understanding of the complex link between reactive astrogliosis heterogeneity and AD progression.

Background: Changes in soluble amyloid-beta (Aβ) levels in cerebrospinal fluid (CSF) are detectable at early preclinical stages of Alzheimer's disease (AD). However, whether Aβ levels can predict downstream AD pathological features in cognitively unimpaired (CU) individuals remains unclear. With this in mind, we aimed at investigating whether a combination of soluble Aβ isoforms can predict tau pathology (T+) and neurodegeneration (N+) positivity. Methods: We used CSF measurements of three soluble Aβ peptides (Aβ1‑38, Aβ1‑40 and Aβ1‑42) in CU individuals (n = 318) as input features in machine learning (ML) models aiming at predicting T+ and N+. Input data was used for building 2046 tuned predictive ML models with a nested cross-validation technique. Additionally, proteomics data was employed to investigate the functional enrichment of biological processes altered in T+ and N+ individuals. Results: Our findings indicate that Aβ isoforms can predict T+ and N+ with an area under the curve (AUC) of 0.929 and 0.936, respectively. Additionally, proteomics analysis identified 17 differentially expressed proteins (DEPs) in individuals wrongly classified by our ML algorithm. More specifically, enrichment analysis of gene ontology biological processes revealed an upregulation in myelinization and glucose metabolism-related processes in CU individuals wrongly predicted as T+. A significant enrichment of DEPs in pathways including biosynthesis of amino acids, glycolysis/gluconeogenesis, carbon metabolism, cell adhesion molecules and prion disease was also observed. Conclusions: Our results demonstrate that, by applying a refined ML analysis, a combination of Ab isoforms can predict T+ and N+ with a high AUC. CSF proteomics analysis highlighted a promising group of proteins that can be further explored for improving T+ and N+ prediction.

Alzheimer9s disease (AD) is a multifactorial pathology responsible for most cases of dementia worldwide. Only a small percentage of AD cases are due to autosomal dominant mutations, while the vast majority have a sporadic presentation. Yet, preclinical research studies relied for decades on animal models that overexpress human genes found in AD autosomal dominant patients. Thus, one could argue that these models do not recapitulate sporadic AD. To avoid human gene overexpression artifacts, knock-in (KI) models have been developed, such as the novel hAβ-KI mouse model, which are still in early phases of characterization. We hypothesize that comparisons at the transcriptomic level may elucidate critical similarities and differences between transgenic/KI models and AD patients. Thus, we aimed at comparing the hippocampal transcriptomic profiling of overexpression (5xFAD and APP/PS1) and KI (hAβ-KI) mouse models with early- (EOAD) and late- (LOAD) onset AD patients. We first evaluated differentially expressed genes (DEGs) and Gene Ontology biological processes (GOBP) overlapping cross-species. After, we explored a network-based strategy to identify master regulators (MR) and the similarities of such elements among models and AD subtypes. A multiple sclerosis (MS) dataset was included to test the molecular specificity of the mouse models to AD. Our analysis revealed that all three mouse models presented more DEGs, GOBP terms and enriched signaling pathways in common with LOAD than with EOAD subjects. Furthermore, semantic similarity of enriched GOBP terms showed mouse model-specific biological alterations, and protein-protein interaction analysis of DEGs identified clusters of genes exclusively shared between hAβ-KI mice and LOAD. Furthermore, we identified 17 transcription factor candidates potentially acting as MR of AD in all three models. Finally, though all mouse models showed transcriptomic similarities to LOAD, hAβ-KI mice presented a remarkable specificity to this AD subtype, which might support the use of the novel hAβ-KI mouse model to advance our understanding of sporadic LOAD.

Background: Previous studies suggested that individuals with a maternal history of Alzheimer’s Disease(AD) are at higher risk of developing AD than individuals with a paternal history of AD. One could suggest that intra-uterine interactions might be responsible for elevating this risk. In this context, AD rodent models are highly suited for improving our understanding of this matter since animals reach adulthood in a few months. Objective: Here, we aimed at investigating changes in memory-related processes and brain metabolism on the offspring born to transgenic mothers harboring human APP/PS1 mutations. Methods: Rats born to F344-AD(Tg-AD) and WT mothers were evaluated in two different time-points: ~5.5, and ~9.5 months. Y-maze test was used to evaluate spatial working memory and micro-PET [18F]FDG was used to assess brain glucose metabolism. Results: Y-maze test demonstrated that rats born to transgenic mothers presented memory disturbances, indexed by spontaneous alternation, at ~5.5 months and ~9.5 months (figure 1A), while rats born to WT mothers and Tg-AD fathers exhibited a decline in spontaneous alternation only at ~9.5 months. rats born to AD-Tg mothers present brain glucose hypermetabolism at ~9,5 months. Conclusion: Our findings demonstrate that rats born to AD-Tg mothers harboring APP/PS1 mutations present cognitive decline and brain glucose metabolism abnormalities earlier than those born to WT mothers. Further studies are needed to understand the biological basis behind this phenomenon.

Background: Transgenic models of Alzheimer’s disease (AD) overexpress human APP, PS1 or PS2 mutations. These models present amyloid-beta pathology but do not recapitulate the complexity of AD. Interestingly, the transgenic rat model TgF344-AD, which overpresses human APP and PS1 mutations, seems to follow a more similar disease progression, manifesting progressive tau tangle-like pathology and late cognitive impairment. Yet, whether they develop energy metabolism changes as we see in AD remains unclear. Objective: Here, we investigated brain bioenergetics in 6-7 months F344-AD/WT rats, an age where animals present early amyloid pathology but no memory impairment - mimicking the human preclinical AD. Methods: We used high-resolution respirometry to assess mitochondrial oxidative phosphorylation capacity (OXPHOS), electron transfer capacity (ET), respiratory control ratio (RCR) and reserve capacity (R) in brain homogenates of male and female F344-AD and WT rats (n = 6-8, per group). Results: The results were analyzed by Welch’s t test: 1. Frontal cortex a)OXPHOS (p=0.307); b)ET (p=0.99); c)RCR (p=0.138); d)R (p=0.482). 2. Hippocampus a)OXPHOS (p=0.446); b)ET (p=0.409); c)RCR (p=0.952); d)R (p=0.503). Conclusion: In conclusion, at 6-7 months, changes in the respirometry in the brain of F344-AD rats were not observed. We hypothesize that these measures will be altered at older ages.