Brain Aβ Research Articles

Accumulation of amyloid-β in the brain of mouse models of Alzheimer's disease is modified by altered gene expression in the presence of human apoE isoforms during aging

Apolipoprotein E4 (apoE4) is a risk factor for Alzheimer's disease (AD). Here, we investigated brain amyloid-β (Aβ) accumulation throughout the aging process in an amyloid precursor protein (APP) knock-in (KI) mouse model of AD that expresses human APPNL-G-F with or without human apoE4 or apoE3. Brain Aβ42 levels were significantly lower in 9-month-old mice that express human isoforms of apoE than in age-matched APP-KI control mice. Linear accumulation of Aβ42 began in 5-month-old apoE4 mice, and a strong increase in Aβ42 levels was observed in 21-month-old apoE3 mice. Aβ42 levels in cerebroventricular fluid were higher in apoE3 than in apoE4 mice at 6–7 months of age, suggesting that apoE3 is more efficient at clearing Aβ42 than apoE4 at these ages. However, apoE3 protein levels were lower than apoE4 protein levels in the brains of 21-month-old apoE3 and apoE4 mice, respectively, which may explain the rapid increase in brain Aβ42 burden in apoE3 mice. We identified genes that were downregulated in a human apoE-dependent (apoE4 > apoE3) and age-dependent (apoE3 = apoE4) manner, which may regulate brain Aβ burden and/or AD progression. Analysis of gene expression in AD mouse models helps identify molecular mechanisms of pleiotropy by the human APOE gene during aging.

Brain pharmacokinetics of mono- and bispecific amyloid-β antibodies in wild-type and Alzheimer’s disease mice measured by high cut-off microdialysis

BackgroundTreatment with amyloid-β (Aβ) targeting antibodies is a promising approach to remove Aβ brain pathology in Alzheimer's disease (AD) and possibly even slow down or stop progression of the disease. One of the main challenges of brain immunotherapy is the restricted delivery of antibodies to the brain. However, bispecific antibodies that utilize the transferrin receptor (TfR) as a shuttle for transport across the blood–brain barrier (BBB) can access the brain better than traditional monospecific antibodies. Previous studies have shown that bispecific Aβ targeting antibodies have higher brain distribution, and can remove Aβ pathology more efficiently than monospecific antibodies. Yet, there is only limited information available on brain pharmacokinetics, especially regarding differences between mono- and bispecific antibodies.MethodsThe aim of the study was to compare brain pharmacokinetics of Aβ-targeting monospecific mAb3D6 and its bispecific version mAb3D6-scFv8D3 that also targets TfR. High cut-off microdialysis was used to measure intravenously injected radiolabelled mAb3D6 and mAb3D6-scFv8D3 antibodies in the interstitial fluid (ISF) of hippocampus in wild-type mice and the AppNL−G−F mouse model of AD. Distribution of the antibodies in the brain and the peripheral tissue was examined by ex vivo autoradiography and biodistribution studies.ResultsBrain concentrations of the bispecific antibody were elevated compared to the monospecific antibody in the hippocampal ISF measured by microdialysis and in the brain tissue at 4–6 h after an intravenous injection. The concentration of the bispecific antibody was approximately twofold higher in the ISF dialysate compared to the concentration of monospecific antibody and eightfold higher in brain tissue 6 h post-injection. The ISF dialysate concentrations for both antibodies were similar in both wild-type and AppNL−G−F mice 24 h post-injection, although the total brain tissue concentration of the bispecific antibody was higher than that of the monospecific antibody at this time point. Some accumulation of radioactivity around the probe area was observed especially for the monospecific antibody indicating that the probe compromised the BBB to some extent at the probe insertion site.ConclusionThe BBB-penetrating bispecific antibody displayed higher ISF concentrations than the monospecific antibody. The concentration difference between the two antibodies was even larger in the whole brain than in the ISF. Further, the bispecific antibody, but not the monospecific antibody, displayed higher total brain concentrations than ISF concentrations, indicating association to brain tissue.

Genetic risk for attention-deficit/hyperactivity disorder predicts cognitive decline and development of Alzheimer's disease pathophysiology in cognitively unimpaired older adults.

Attention-deficit/hyperactivity disorder (ADHD) persists in older age and is postulated as a risk factor for cognitive impairment and Alzheimer's Disease (AD). However, these findings rely primarily on electronic health records and can present biased estimates of disease prevalence. An obstacle to investigating age-related cognitive decline in ADHD is the absence of large-scale studies following patients with ADHD into older age. Alternatively, this study aimed to determine whether genetic liability for ADHD, as measured by a well-validated ADHD polygenic risk score (ADHD-PRS), is associated with cognitive decline and the development of AD pathophysiology in cognitively unimpaired (CU) older adults. We calculated a weighted ADHD-PRS in 212 CU individuals without a clinical diagnosis of ADHD (55-90 years). These individuals had baseline amyloid-β (Aβ) positron emission tomography, longitudinal cerebrospinal fluid (CSF) phosphorylated tau at threonine 181 (p-tau181), magnetic resonance imaging, and cognitive assessments for up to 6 years. Linear mixed-effects models were used to test the association of ADHD-PRS with cognition and AD biomarkers. Higher ADHD-PRS was associated with greater cognitive decline over 6 years. The combined effect between high ADHD-PRS and brain Aβ deposition on cognitive deterioration was more significant than each individually. Additionally, higher ADHD-PRS was associated with increased CSF p-tau181 levels and frontoparietal atrophy in CU Aβ-positive individuals. Our results suggest that genetic liability for ADHD is associated with cognitive deterioration and the development of AD pathophysiology. Findings were mostly observed in Aβ-positive individuals, suggesting that the genetic liability for ADHD increases susceptibility to the harmful effects of Aβ pathology.

Associations of Naturally Occurring Antibodies to Presenilin-1 with Brain Amyloid-β Load and Cognitive Impairment in Alzheimer's Disease.

Imbalance between the production and clearance of amyloid-β (Aβ) promotes the development of Alzheimer's disease (AD). Presenilin-1 (PS1) is the catalytic subunit of γ-secretase, which is involved in the process of Aβ production. The profiles of autoantibodies are dysregulated in AD patients. This study aims to investigate the relative levels and clinical relevance of naturally occurring antibodies to PS1 (NAbs-PS1) in AD. A total of 55 subjects with AD (including both dementia and mild cognitive impairment due to AD), 28 subjects with cognitive impairment (including both dementia and mild cognitive impairment) not due to AD (non-AD CI), and 70 cognitively normal (CN) subjects were recruited. One-site ELISA was utilized to determine the relative levels of NAbs-PS1 in plasma. AD subjects had lower plasma levels of NAbs-PS1 than CN and non-AD CI subjects. Plasma NAbs-PS1 were negatively associated with the brain Aβ load, as reflected by PET-PiB SUVR, and were positively associated with cognitive functions of participants. Plasma NAbs-PS1 discriminated AD patients from CN with an area under the curve (AUC) of 0.730, a sensitivity of 69.09%, and a specificity of 67.14%, and they discriminated AD patients from non-AD CI subjects with an AUC of 0.750, a specificity of 70.91%, and a sensitivity of 71.43%. This study found an aberrant immunological phenotype in AD patients. Further investigations are needed to determine the pathophysiological functions of NAbs-PS1 in AD.

Blood–brain barrier penetrating neprilysin degrades monomeric amyloid-beta in a mouse model of Alzheimer’s disease

BackgroundAggregation of the amyloid-β (Aβ) peptide in the brain is one of the key pathological events in Alzheimer’s disease (AD). Reducing Aβ levels in the brain by enhancing its degradation is one possible strategy to develop new therapies for AD. Neprilysin (NEP) is a membrane-bound metallopeptidase and one of the major Aβ-degrading enzymes. The secreted soluble form of NEP (sNEP) has been previously suggested as a potential protein-therapy degrading Aβ in AD. However, similar to other large molecules, peripherally administered sNEP is unable to reach the brain due to the presence of the blood–brain barrier (BBB).MethodsTo provide transcytosis across the BBB, we recombinantly fused the TfR binding moiety (scFv8D3) to either sNEP or a previously described variant of NEP (muNEP) suggested to have higher degradation efficiency of Aβ compared to other NEP substrates, but not per se to degrade Aβ more efficiently. To provide long blood half-life, an Fc-based antibody fragment (scFc) was added to the designs, forming sNEP-scFc-scFv8D3 and muNEP-scFc-scFv8D3. The ability of the mentioned recombinant proteins to degrade Aβ was first evaluated in vitro using synthetic Aβ peptides followed by sandwich ELISA. For the in vivo studies, a single injection of 125-iodine-labelled sNEP-scFc-scFv8D3 and muNEP-scFc-scFv8D3 was intravenously administered to a tg-ArcSwe mouse model of AD, using scFc-scFv8D3 protein that lacks NEP as a negative control. Different ELISA setups were applied to quantify Aβ concentration of different conformations, both in brain tissues and blood samples.ResultsWhen tested in vitro, sNEP-scFc-scFv8D3 retained sNEP enzymatic activity in degrading Aβ and both constructs efficiently degraded arctic Aβ. When intravenously injected, sNEP-scFc-scFv8D3 demonstrated 20 times higher brain uptake compared to sNEP. Both scFv8D3-fused NEP proteins significantly reduced aggregated Aβ levels in the blood of tg-ArcSwe mice, a transgenic mouse model of AD, following a single intravenous injection. In the brain, monomeric and oligomeric Aβ were significantly reduced. Both scFv8D3-fused NEP proteins displayed a fast clearance from the brain.ConclusionA one-time injection of a BBB-penetrating NEP shows the potential to reduce, the likely most toxic, Aβ oligomers in the brain in addition to monomers. Also, Aβ aggregates in the blood were reduced.

Investigating the role of neuronal hyperactivity in stress susceptibility and brain beta‐amyloid deposition

AbstractBackgroundBoth animal and human literature have suggested a relationship between stress responses and an increased susceptibility to extracellular beta‐amyloid (Aβ) plaque aggregation, one of the pathological features of Alzheimer’s Disease (AD), as well as clinical symptoms of AD. Despite this evidence, a neuro‐mechanistic pathway that underlies the relationship between the psychological stress response and brain Aβ pathology remains poorly understood. We examined the hypothesis that increased stress responses are associated with neuronal hyperactivity and increased brain Aβ deposition along the spectrum of AD.MethodWe included 35 Cognitively Normal (CN) and 21 Significant Memory Concern (SMC) individuals and 81 patients with Mild Cognitive Impairment (MCI), and 29 AD patients from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Neuropsychiatric Inventory (NPI‐Q) total scores were used to indicate stress responses. The amplitude of low frequency fluctuations (ALFF) was calculated using resting‐state fMRI (rsfMRI) scans as a measure of neuronal activity. AV45‐SUVR measures were downloaded from the ADNI study. In SPM12, general linear models were performed on normalized ALFF maps to examine the associations of stress responses and brain Aβ deposition with neuronal activity, while controlling for age, sex, and APOE4 carrier status.ResultNPIQ scores were significantly associated with brain Aβ indices across the entire cohort spanning from cognitively normal (CN) older adults to AD patients. The CN group exhibited significant increases in ALFF in the anterior cingulate, caudate, and inferior occipital cortices in relation to increased NPI‐Q scores, while AD participants exhibited decreased ALFF in multiple regions including medial and lateral frontal cortices. Moreover, with higher brain Aβ load, CN participants showed increased ALFF in medial and lateral frontal cortices, while AD participants showed decreased ALFF in medial frontal, temporo‐parietal junction, and inferior parietal cortices.ConclusionThese results indicate a potential link between heightened stress responses and increased susceptibility to the development of AD pathologies through neuronal hyperactivity, especially in the early stages of AD. These findings provide neural mechanisms underlying the relationship between stress as a risk factor for AD by highlighting the role of neuronal hyperactivity in this association, while validating the use of rsfMRI for these analyses.

An oligomer‐directed Aβ antibody decreases synaptotoxic oligomeric Aβ in brain and improves behavioral abnormality in humanized APP knock‐in mice

AbstractBackgroundThere is strong evidence that soluble oligomers of amyloid beta protein (oAβ) help initiate the pathogenic cascade of Alzheimer’s disease (AD), which suggests therapeutic strategies targeting oAβ over monomeric or fibrillar Aβ. A new antibody, 71A1, is 1∼00‐fold more sensitive for oAβ than synthetic monomers. The material that 71A1 specifically immunoprecipitates from AD soluble brain extracts impairs synaptic function as much as does the full extract. In accord, pre‐incubating brain extracts with 71A1 neutralizes its synaptotoxicity. 71A1 has potentially unique activities against disease‐relevant oAβ, making it a novel candidate for treating AD.Methods15 mg/kg 71A1 or anti‐KLH (negative control) was administered i.p. to 45 humanized APP knock‐in mice (APPNLGF/NLGF) weekly from 8 to 20 weeks of age. Cognition was assessed by spontaneous alternation (Y‐maze). Brains were harvested at age 21‐wk for biochemical, electrophysiological and immunohistochemical analyses. Diffusible (“soaking”) extracts of the brains were prepared to measure monomeric and oligomeric Aβ using homebrew ultra‐sensitive assays. Aliquots of the same soaking extracts were used to treat wild‐type mouse hippocampal slices and measure long‐term potentiation (LTP) to assess synaptotoxicity in the APPNLGF/NLGF brains post‐treatment.Results71A1 recognized oAβ and neutralized its synaptotoxicity in APPNLGF/NLGF mouse brain extracts. 71A1 effectively treated male APPNLGF/NLGF mice, which improved cognition significantly. The antibody reduced brain Aβ (1‐42) and oAβ levels with a trend toward statistical significance. Mouse brains with less oAβ had less synaptotoxicity as assessed by LTP.ConclusionsThese results demonstrate 71A1 is an oligomer‐preferring monoclonal antibody as a therapeutic candidate for AD, decreasing brain oAβ and oAβ‐induced synaptotoxicity. We believe this provides the first proof‐of‐concept mouse trial using an antibody that has been carefully characterized as oAβ‐preferring. We observed 1) a correlation between oAβ concentration and its synaptotoxicity; and 2) that 71A1 ameliorated aspects of cognitive impairment in APPNLGF/NLGF mice by targeting oAβ.

Suboptimal sleep efficiency and duration predicts rate of accumulation of Aβ‐ Amyloid in cognitively normal older adults

AbstractBackgroundThere is increasing evidence of a bidirectional relationship between suboptimal sleep and brain Aβ‐amyloid (Aβ) accumulation. Suboptimal sleep is suggested to both result from and contribute to the accumulation of brain Aβ. This study tested whether aspects of self‐reported sleep quality predict the longitudinal accumulation of brain Aβ.MethodLinear mixed effect model analyses were conducted on 192 cognitively normal older adults (M = 73.8 years, SD = 5.8, 51.6% female). These individuals, drawn from the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study of Ageing, had self‐reported sleep characteristics assessed at baseline and positron emission tomography‐determined brain Aβ burden measured over a minimum of three AIBL timepoints (range 33.3‐73.9 months). Analyses included random slopes and intercepts, interaction for apolipoprotein E (APOE) ε4 allele status and time, adjusting for sex and baseline age.ResultSleep duration of <5 hours and sleep efficiency of <65% both significantly forecast the longitudinal trajectory of Aβ accumulation in the whole cohort (sleep duration <5 hrs β = 4.70 ± 1.58, p = 0.003; sleep efficiency <65% β = 2.94 ± 0.91, p = 0.001) and in APOE ε4 non‐carriers (sleep duration <5 hrs β = 4.70 ± 1.53, p = 0.003; sleep efficiency <65% β = 2.90 ± 0.87, p = 0.001) but not in APOE ε4 carriers.ConclusionThese findings indicate a role for self‐reported suboptimal sleep efficiency and duration in the accumulation of Alzheimer's disease neuropathology in cognitively normal individuals. Individuals with suboptimal sleep may benefit from an intervention to improve these sleep parameters to lessen future Alzheimer's risk. Our findings also suggest the potential utility of self‐report screening for sleep efficiency and duration as a predictor of risk of Aβ accumulation.

Highly specific plasma β‐amyloid assays on the fully automated platform predict brain β‐amyloid pathology determined by a Centiloid threshold of amyloid PET

AbstractBackgroundThe U.S. Food and Drug Administration approved aducanumab for the treatment of Alzheimer’s disease (AD) under the accelerated approval pathway and several new drug candidates are currently in development or have been submitted for marketing authorization in the U.S. and other countries. Consequently, the necessity of pathological diagnosis of AD by confirming brain β‐amyloid (Aβ) pathology in routine clinical practice is increasing to ensure that appropriate AD patients can access these drugs. We reported the development of the fully automated plasma Aβ40 and Aβ42 immunoassays that showed high performance for predicting brain Aβ pathology defined by amyloid PET. Here, we present the effect of several markers on the performance of our plasma Aβ assays.MethodsPlasma Aβ40 and Aβ42 levels were measured using a fully automated platform (HISCLTM series). To assess the performance of plasma Aβ42/Aβ40 ratio for predicting brain Aβ pathology, two studies (discovery and validation studies) were performed using plasma samples obtained from the elenbecestat phase 3 program. Brain Aβ pathology was determined by amyloid PET Centiloid scale. A cut‐off of Centiloid unit was determined as 32.21 by performing a receiver operating characteristic (ROC) analysis and determination of the Youden Index using visual reads as the standard. To evaluate the clinical performance of our assays, area under the curve (AUC) was obtained by performing a ROC analysis. The model, incorporating age and APOE ε4 status, was also evaluated.ResultsPlasma Aβ42/Aβ40 ratio predicted brain Aβ pathology defined by amyloid PET with AUCs of 0.93 and 0.92 in the discovery and validation studies, respectively. The sensitivity and specificity were calculated as 97.5% and 80.8% in the discovery study and 94.5% and 78.0% in the validation study. The model incorporating age and APOE ε4 status didn’t show significant improvement for predicting brain Aβ pathology.ConclusionsPlasma Aβ42/Aβ40 ratio measured by our immunoassays achieved high accuracy to predict brain Aβ pathology, and age and APOE ε4 status didn’t contribute to improve the accuracy unlike most past reports from other groups. Our assays may contribute to a high‐throughput, less invasive diagnostic method for detecting brain Aβ pathology in routine clinical practice.

Comparison of plasma amyloid, tau, and astrocyte biomarkers to identify AD pathophysiology

AbstractBackgroundAlthough it has been alredy demonstrated that plasma amyloid‐β (Aβ), phosphorylated tau (p‐tau), and glial fibrillar protein (GFAP) can predict with high accuracy Alzheimer's disease (AD) pathophysiology, no previous study has compared their performance in the same set of individuals. Here, we compare the performance of plasma Aβ42/40, p‐tau, GFAP, and NfL against Aβ and tau PET across the AD spectrum.MethodWe used the ROC curve to test the predictive performance of Simoa plasma Aβ42/40, p‐tau (at threonine 181 and 231), NfL, and GFAP to identify Aβ and Pau PET positivity in 138 cognitive unimpaired (CU) and 87 cognitive impaired (CI) from the McGill TRIAD cohort. Pearson correlation and linear regression tested the association between markers.ResultWe showed that plasma p‐tau231, p‐tau181, GFAP, and NfL correlated with each other (Figure 1), while Aβ42/40 did not. In CU, voxel‐wise linear regressions (Figure 2A) showed that p‐tau231, p‐tau181, and GFAP concentrations were significantly associated with Aβ‐PET (Figure 2A). While for Tau‐PET (Figure 2B), there was a significant association only with p‐tau231 and p‐tau181 (Figure 2B). P‐tau231 outperformed the other plasma biomarkers to identify both Aβ‐ and Tau‐PET positivity (AUC 0.877 and 0.796, respectively) in CU individuals. In CI, Aβ‐ and Tau‐PET were significantly associated with p‐tau231, p‐tau181, and GFAP, whereas NfL was only associated with Tau‐PET. The discriminative accuracy of GFAP in identifying both Aβ‐PET and Tau positivity (AUC 0.936 and 0.944, respectively) outperformed the other plasma biomarkers in CI individuals (Figure 3, Table 1).ConclusionWe showed that plasma p‐tau231, a novel biomarker of early AD, best depicted AD pathophysiology in CU individuals. Interestingly, GFAP, an astrocyte reactivity marker, was better associated with brain Aβ and tau pathologies than plasma p‐tau and Aβ markers in CI individuals. Our results highlight that the performance of the novel plasma biomarkers of amyloid, tau and neuroinflammation to detect brain AD pathophysiology is disease stage specific.

Associations of erythrocyte omega-3 fatty acids with cognition, brain imaging and biomarkers in the Alzheimer’s disease neuroimaging initiative: cross-sectional and longitudinal retrospective analyses

The association between omega-3 (ω-3) PUFAs and cognition, brain imaging and biomarkers is still not fully established. The aim was to analyze the cross-sectional and retrospective longitudinal associations between erythrocyte ω-3 index and cognition, brain imaging, and biomarkers among older adults. A total of 832 Alzheimer's Disease Neuroimaging Initiative 3 (ADNI-3) participants, with a mean (SD) age of 74.0 (7.9) y, 50.8% female, 55.9% cognitively normal, 32.7% with mild cognitive impairment, and 11.4% with Alzheimer disease (AD) were included. A low ω-3 index (%EPA + %DHA) was defined as the lowest quartile (≤3.70%). Cognitive tests [composite score, AD Assessment Scale Cognitive (ADAS-Cog), Wechsler Memory Scale (WMS), Trail Making Test, Category Fluency, Mini-Mental State Examination, Montreal Cognitive Assessment] and brain variables [hippocampal volume, white matter hyperintensities (WMHs), positron emission tomography (PET) amyloid-β (Aβ) and tau] were considered as outcomes in regression models. Low ω-3 index was not associated with cognition, hippocampal, and WMH volume or brain Aβ and tau after adjustment for demographics, ApoEε4, cardiovascular disease, BMI, and total intracranial volume in the cross-sectional analysis. In the retrospective analysis, low ω-3 index was associated with greater Aβ accumulation (adjusted β = 0.02; 95% CI: 0.01, 0.03; P=0.003). The composite cognitive score did not differ between groups; however, low ω-3 index was significantly associated with greater WMS-delayed recall cognitive decline (adjusted β = -1.18; 95% CI: -2.16, -0.19; P=0.019), but unexpectedly lower total ADAS-Cog cognitive decline. Low ω-3 index was cross-sectionally associated with lower WMS performance (adjusted β = -1.81, SE=0.73, P=0.014) and higher tau accumulation among ApoE ε4 carriers. Longitudinally, low ω-3 index was associated with greater Aβ accumulation and WMS cognitive decline but unexpectedly with lower total ADAS-Cog cognitive decline. Although no associations were cross-sectionally found in the whole population, low ω-3 index was associated with lower WMS cognition and higher tau accumulation among ApoE ε4 carriers. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is registered at clinicaltrials.gov as NCT00106899.

Associations of erythrocyte omega‐3 fatty acids with cognition, brain imaging and biomarkers in the Alzheimer’s Disease Neuroimaging Initiative

AbstractBackgroundThe association between ω‐3 polyunsaturated fatty acids and cognition, brain imaging and biomarkers is still not fully established. We aimed to analyze the cross‐sectional and retrospective longitudinal associations between erythrocyte ω‐3 index and cognition, brain imaging and biomarkers among older adults.Method832 participants from the Alzheimer’s Disease Neuroimaging Initiative 3, mean (SD) age 74.0 (7.9) years, 50.8% female, 55.9% cognitively normal, 32.7% with mild cognitive impairment and 11.4% with Alzheimer’s disease (AD) were included. Low ω‐3 index (% eicosapentaenoic acid EPA + % docosahexaenoic acid DHA) was defined as the lowest quartile (≤3.70%). Cognitive tests (composite score; AD Assessment Scale cognitive (ADAS‐Cog) subscale; Wechsler Memory Scale (WMS); Trail Making Test A and B; Category fluency; Mini Mental State Examination; Montreal Cognitive Assessment; Clinical Dementia Rating) and brain variables (hippocampal volume, white matter hyperintensities (WMH), PET amyloid‐β and Tau) were considered as outcomes in regression models.ResultLow ω‐3 index was not associated with cognition, hippocampal and WMH volume, brain Aβ and Tau after adjustment for age, education, ApoE ε4, cardiovascular disease, BMI and total intracranial volume in the cross‐sectional analysis. In the retrospective analysis, low ω‐3 index was associated with greater Aβ accumulation over time. The composite cognitive score did not differ between groups; however, low ω‐3 index was associated with greater cognitive decline on the WMS‐Delayed recall but unexpectedly lower cognitive decline on the total ADAS‐Cog. Low ω‐3 index was cross‐sectionally associated with lower performance on WMS tests and higher Tau accumulation among ApoE ε4 carriers.ConclusionLongitudinally, low ω‐3 index was associated with greater Aβ accumulation over time and cognitive decline on the WMS but unexpectedly with lower cognitive decline on the total ADAS‐Cog. Low ω‐3 index was associated with lower cognition on the WMS and higher Tau accumulation among ApoE ε4 carriers in the cross‐sectional analysis.

Comparison of plasma amyloid, tau, and astrocyte biomarkers to identify AD pathophysiology

AbstractBackgroundAlthough it has been already demonstrated that plasma amyloid‐β (Aβ), phosphorylated tau (p‐tau), and glial fibrillar protein (GFAP) can predict with high accuracy Alzheimer's disease (AD) pathophysiology, no previous study has compared their performance in the same set of individuals. Here, we compare the performance of plasma Aβ42/40, p‐tau, GFAP, and NfL against Aβ and tau PET across the AD spectrum.MethodWe used the ROC curve to test the predictive performance of Simoa plasma Aβ42/40, p‐tau (at threonine 181 and 231), NfL, and GFAP to identify Aβ and Pau PET positivity in 138 cognitive unimpaired (CU) and 87 cognitive impaired (CI) from the McGill TRIAD cohort. Pearson correlation and linear regression tested the association between markers.ResultWe showed that plasma p‐tau231, p‐tau181, GFAP, and NfL correlated with each other (Figure 1), while Aβ42/40 did not. In CU, voxel‐wise linear regressions (Figure 2A) showed that p‐tau231, p‐tau181, and GFAP concentrations were significantly associated with Aβ‐PET (Figure 2A). While for Tau‐PET (Figure 2B), there was a significant association only with p‐tau231 and p‐tau181 (Figure 2B). P‐tau231 outperformed the other plasma biomarkers to identify both Aβ‐ and Tau‐PET positivity (AUC 0.877 and 0.796, respectively) in CU individuals. In CI, Aβ‐ and Tau‐PET were significantly associated with p‐tau231, p‐tau181, and GFAP, whereas NfL was only associated with Tau‐PET. The discriminative accuracy of GFAP in identifying both Aβ‐PET and Tau positivity (AUC 0.936 and 0.944, respectively) outperformed the other plasma biomarkers in CI individuals (Figure 3, Table 1).ConclusionWe showed that plasma p‐tau231, a novel biomarker of early AD, best depicted AD pathophysiology in CU individuals. Interestingly, GFAP, an astrocyte reactivity marker, was better associated with brain Aβ and tau pathologies than plasma p‐tau and Aβ markers in CI individuals. Our results highlight that the performance of the novel plasma biomarkers of amyloid, tau and neuroinflammation to detect brain AD pathophysiology is disease stage specific.

Alzheimer brains: increased soluble amyloid peptides, but decreased lipid rafts

AbstractBackgroundPET imaging studies of AD patients show progressive increases of fibrillar Aβ‐ amyloid. Because current PET ligands underestimate non‐fibrillar forms, we assayed soluble Aβ in AD and controls. To identify mechanisms responsible for soluble Aβ in AD brains, we examined lipid rafts (LR), where APP is enzymatically processed. Frontal cortex was compared with cerebellum, which has minimal AD pathology.MethodPostmortem samples (N=48) were age‐and sex matched for Braak scores. Soluble Aβ was extracted from homogenates of full thickness frontal cortex by isotonic buffer and mild detergent (RIPA; 1% NP40) and centrifuged (10,000g/1h). Supernates were assayed by dot blots with antibodies for Aβ40 and Aβ42 (Biolegend, San Diego, CA). Aβ was assayed as relative fluorescent units per gm brain. LR fractions were isolated from these same brains by kit (Invent Biotechnologies; LR‐039), validated by ultracentrifugal fractionation.ResultCompared with cognitively normal controls (Braak 0‐1), elevations of soluble Aβ40 and Aβ42 were similar for intermediate and later stage AD (Braak 2‐3 and 4‐6). Clinical grade AD had greater increase of soluble Aβ40 (+400%) than Aβ42 (+50%) (p<0.05). LR raft yield per gram AD frontal cortex was 20% below controls (p<0.05), while cerebellar LR did not differ by Braak score. The composition of LR had a similar pattern, with 35% AD decreases of total protein and cholesterol (p<0.05); cerebellar LR again did not differ by Braak score. However, LR 4‐HNE, a marker of oxidative damage, was similarly increased in AD cortex and AD cerebellum.ConclusionThe extensive overlap of soluble Aβ levels in controls with AD contrasts with the PET findings on fibrillar Aβ. These findings further support fibrillar Aβ as a biomarker for AD treatments and show the need for more detailed postmortem analysis of diverse soluble and insoluble Aβ aggregates in relation to PET. The decreased LR in AD frontal cortex is consistent with its extensive neuronal loss, in contrast to the cerebellum. Further studies will examine LR enzymes of APP processing as a source of the increased soluble Aβ in AD, and subcellular clearance processes, which may be impaired in association with the oxidative damage indicated by increased 4‐HNE.

Exploring Combination Therapies in AD: Additive Effects of the QPCT Inhibitor Varoglutamstat and Aducanumab on Aβ Pathology and Biomarkers In Vivo

AbstractBackgroundPyroglutamate‐3Aβ (N3pE), a toxic Aβ variant formed by the activity of glutaminyl gyclase (QPCT) has been shown to play a pivotal role in the development and progression of Alzheimer’s disease (AD). Recently, we demonstrated that a combination of the QPCT inhibitor varoglutamstat (PQ912) with the N3pE‐specific antibody m6 has an additive effect on lowering of N3pE in vivo. Here, we analyzed whether a similar additive effect could be achieved when combining varoglutamstat with the Aβ‐aggregate‐specific antibody aducanumab.MethodNine‐months old APPxhQC mice were treated with either varoglutamstat (1.6 g/kg chow, ad libitum), chimeric aducanumab (chAdu, ≈10 mg/kg i.p. weekly) or a combination of both for 16 weeks. Brain Aβ accumulation (ELISA and immunohistochemistry) and AD biomarkers in the water‐soluble brain fractions (neurogranin, BACE‐1, YKL‐40; ELISA) were analyzed and compared to a vehicle‐treated group.ResultTreatment with either varoglutamstat or chAdu significantly reduced the accumulation of both total Aβ and N3pE in the brain. The effect of chAdu was more pronounced for total Aβ (‐35% vs. ‐21% for varoglutamstat), while varoglutamstat treatment resulted in a stronger decrease of N3pE (‐28% vs. ‐19% for chAdu). The combination treatment generally led to a stronger decrease of Aβ vs. single agent treatment (Bliss combination index (CI) = 0.88 for soluble Aβ42 and 1.23 for insoluble Aβ42). For insoluble N3pE, the observed effect was nearly additive (CI = 1.09). Treatment with chAdu, varoglutamstat or both had different effects on the analyzed AD biomarkers. chAdu treatment significantly decreased BACE‐1 protein levels (‐30%), while varoglutamstat treatment significantly reduced levels of the brain inflammation marker YKL‐40 (‐27%), which is in line with earlier clinical Phase 2a study results.ConclusionOur data indicate that a combination of agents with different modes of action such as aducanumab, an Aβ aggregate‐specific antibody and varoglutamstat, a small molecule designed to block formation of toxic, aggregation‐prone N3pE, can act additively to decrease total Aβ and N3pE levels in the brain. Our results also provide a rationale for investigating different potential combination regimens, including an initial antibody‐mediated Aβ clearance followed by long‐term suppression of N3pE formation and inflammation by varoglutamstat (“treat and maintain”).

TREM2 differentially modulates parenchymal and vascular pathology in a mouse model of cerebral amyloid angiopathy

AbstractBackgroundCerebral amyloid angiopathy (CAA) features cerebral vascular deposition of pathological amyloid‐beta protein (Aβ) and plays an important role in the multimorbidity of aging brains including Alzheimer’s disease (AD), but it is less understood compared to parenchymal Aβ plaques. Triggering receptor expressed on myeloid cells 2 (TREM2), a key player in innate immune response, is exclusively expressed in microglia in the brain and mediates Aβ clearance and subsequently alleviates neuroinflammation. Loss‐of‐function mutations in TREM2 increase the risk of AD. Recent studies on TREM2 function using TREM2 knockout (KO) in transgenic (Tg) AD mice have shown that TREM2 modulates parenchymal Aβ deposition in the brain, although the direction of the effect depends on the specific Tg background and the stage of the disease development. However, the impact of TREM2 on CAA had not been investigated.MethodsTREM2 KO mice were crossed with SwDI mice (C57BL/6‐Tg(Thy1‐APPSwDutIowa)BWevn/Mmjax), a model of CAA and AD, to generate SwDI/TREM2WT, SwDI/TREM2Het, and SwDI/TREM2KO mice. At the age of 16 months, the mice were euthanized for tissue collection. ELISA was utilized for the assessment of Aβ40 and Aβ42 levels in brain tissue homogenates, and histochemical and immunohistochemical or immunofluorescent assays were used to evaluate amyloid deposition, astrogliosis, and microgliosis. All results were analyzed using GraphPad Prism 9.ResultsTREM2 deficiency markedly increased overall Aβ load in SwDI/TREM2KO mice compared to SwDI/TREM2WT or SwDI/TREM2Het in the cortex, hippocampus, and thalamus. Intriguingly, TREM2 deletion led to a dramatic decrease in CAA in vasculature‐enriched regions, such as thalamus, along with reduced microglial association with CAA. Consistent with previous reports, Aβ plaque‐associated microglia were significantly reduced in SwDI/TREM2KO mice. Additional experiments are underway to explore the molecular mechanisms underlying the distinct impact of TREM2 deficiency on Aβ plaques and CAA.ConclusionDeletion of TREM2 increases the overall brain Aβ load whereas decreases CAA, suggesting the differential role of TREM2 in the regulation of parenchymal versus vascular deposition of Aβ in the brain.

Development and validation of AI‐based tools for brain amyloid‐β detection using MRI

AbstractBackgroundNon‐invasive methods for brain amyloid‐b (Ab) detection are needed for effective patient care, and for faster and more cost‐effective screening of patients in clinical trials. Using MRI and other patient screening data from internal clinical trials, we employ artificial intelligence (AI) algorithms to develop brain Aβ positivity detection tools and validate their performance in independent datasets.MethodTraining dataset included structural MRI and several cognitive assessments obtained during screening of 1960 patients from a clinical trial. Volumetric measures from 207 brain regions were generated by BioClinica using their proprietary imaging pipeline. Over 85% of these patients had mild cognitive impairment (MCI), and approximately 50% were Aβ positive based PET visual read (mostly using Florbetaben).Signatures for detecting brain Aβ positivity were derived via several AI algorithms such as Bayesian elastic‐net, neural network, regularized random forests, and stochastic gradient boosting. These models included demographics and clinical features, and the added value of ApoE and MRI features were assessed. Performance accuracy was first assessed via 10‐fold cross‐validation within the training set. Signatures from the best performing algorithm were evaluated in two independent test sets: a clinical trial cohort (n=1853) and an ADNI cohort (n=1092).ResultSignatures using cognitive assessments and demographics achieved 62.2% accuracy for detecting brain Aβ positivity when evaluated via cross‐validation, which improved to 75.2% when adding ApoE, and to 77.9% when including MRI.When tested in two independent cohorts, signatures with cognitive assessments and demographics achieved accuracy of 64.5% and 65.8% respectively, which improved to 71.9% and 74.3% when adding ApoE, to 76.7% and 77.5% when including MRI, and to 83.6% and 84.8% when considering 2/3 of the test‐sets that were predicted with high‐confidence (i.e., subjects predicted with > 70% probability as brain Aβ positive or negative).ConclusionThese results demonstrate the potential of non‐invasive AI tools based on cognitive assessments, ApoE and MRI for detecting brain Aβ positivity in clinical trials and patient care. Results reported here may be refined further using impending additional data prior to final presentation.

Plasma glial fibrillary acidic protein is associated with reactive astrogliosis assessed via 18F‐SMBT‐1 PET

AbstractBackgroundReactive astrogliosis is an early event along the Alzheimer’s disease (AD) continuum. We have shown that plasma glial fibrillary acidic protein (GFAP), reflecting reactive astrogliosis, is elevated in cognitively unimpaired individuals with preclinical AD (Chatterjee et al., 2021). We reported similar findings using 18F‐SMBT‐1, a PET tracer for monoamine oxidase B (MAO‐B) (Villemagne et al., 2022). To provide further evidence of their relationship with reactive astrogliosis we investigated the association between GFAP and 18F‐SMBT‐1 in the same participants.MethodPlasma GFAP, Aβ42 and Aβ40 levels were measured using the Single Molecule Array platform in 71 participants comprising 54 healthy controls (12 Aβ+ and 42 Aβ‐), 11 MCI(3 Aβ+ and 8 Aβ‐) and 6 probable AD(5 Aβ+ and 1 Aβ‐) patients from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing cohort. These participants also underwent 18F‐SMBT‐1 and Aβ PET imaging. Aβ imaging results were expressed in Centiloids (CL; ≥20 CL classified as Aβ+). 18F‐SMBT‐1 Standard Uptake Value Ratio (SUVR) were generated using the subcortical white matter as reference region. Linear regression analyses were carried out using plasma GFAP levels as the dependent variable and regional 18F‐SMBT‐1 SUVR as the independent variable, before and after adjusting for age, sex, soluble Aβ (plasma Aβ1‐42/Aβ1‐40 ratio) and insoluble Aβ (Aβ PET).ResultPlasma GFAP was significantly associated with 18F‐SMBT‐1 SUVR in brain regions of early Aβ deposition, such as the supramarginal gyrus (SG, β=.361, p=.002), posterior cingulate (PC, β=.308, p=.009), lateral temporal (LT, β=.299, p=.011), lateral occipital (LO, β=.313, p=.008) before adjusting for any covariates. After adjusting for covariates age, sex and soluble Aβ, GFAP was significantly associated with 18F‐SMBT‐1 PET signal in the SG (β=.333, p<.001), PC (β=.278, p=.005), LT (β=.256, p=.009), LO (β=.296, p=.004) and superior parietal (SP, β=.243, p=.016). On adjusting for age, sex and insoluble Aβ, GFAP was significantly associated with SMBT‐1 PET in the SG (β=.211, p=.037) however only a trend towards significance was observed in the PC (β=.186, p=.052) and LT (β=.171, p=.067) (Figure 1).ConclusionThere is an association between plasma GFAP and regional SMBT‐1 PET that is primarily driven by brain Aβ load.

Quantifying AD‐related brain amyloid with linearised progression models: model‐based vs. data‐based.

AbstractBackgroundBrain amyloid‐β (Aβ) is the pathological hallmark of Alzheimer's disease (AD). In logistic disease models, Aβ accumulation is a sigmoid function of time‐since‐disease‐onset (TSDO) (figure 1). Previous positron emission tomography (PET)‐based models vary accumulation onset(t50) and duration(r) globally; capacity(K) and baseline(NS) regionally (Whittington2018). We confirm existing approaches and propose a more powerful ICA‐based approach to quantify disease severity and estimate TSDO.MethodWe used 1071 18F‐florbetapir standard uptake value ratio (SUVR) images from the ADNI‐2 study (adni.loni.usc.edu/data‐samples/data‐types/pet). Images were mapped into MNI space. Averages were extracted using the Harvard‐Oxford brain‐atlas. Whole‐brain tracer‐specific sigmoid parameters (Jack2013) obtained from the literature were used to estimate TSDO.Of 16 models of regional Aβ accumulation (each of the 4 regional sigmoid parameters varied either regionally or globally), the optimal Bayesian information criterion was found with global t50 and r, and regional NS and K (figure 1) with global values r=6.16y and t50=4.10y.Linearised maps of NS and K were obtained by regressing the SUVR maps onto the global sigmoid. We also estimated these maps as independent components, using a 2‐component ICA on the SUVR maps. Both outcomes were used to quantify Aβ accumulation from SUVR images as weighting factors of the accumulation map.We compared the weights from the logistic model and the ICA model in ADNI, using effect size measured with Hedges' g between cognitively normal (CN), subjective memory complaints (SMC), mild cognitive impairment (EMCI/MCI/LMCI) and AD groups. We compared 3 longitudinal visits (N=112) in the OASIS‐3 study (see www.oasis‐brains.org) with both methods, global SUVR and Centiloid (Klunk2015) using 11C‐PiB PET SUVR images.ResultMaps of accumulation capacity from both models had spatial correlation of 0.86 (figure 2); baseline maps had spatial correlation of 0.95. Hedges' g between ADNI groups was 2.25 for K, and 2.42 for ICA (1.46 for global SUVR). In OASIS‐3, Hedges' g between visits was 1.24 for K, 1.46 for ICA (global SUVR 0.15, Centiloid 0.4).ConclusionWe demonstrate that linear accumulation models can be used to quantify brain Aβ with PET; maps obtained by ICA yield larger effect sizes than the logistic method for differentiating groups and measuring changes between visits.

In vivo downregulation of pancreatic amylin improves brain function and reduces brain β amyloid pathology in APP/PS1 mice

AbstractBackgroundAmylin is a systemic hormone that is co‐secreted with insulin from pancreatic β‐cells. Amylin co‐aggregates with brain parenchymal and vascular b‐amyloid in persons with Alzheimer’s dementia. Cross‐sectional data show higher CSF and blood amylin levels are associated with increased frequency of cognitive impairment. The present study sought to determine how in vivo downregulation of amylin influences brain function during the development of Aβ pathology.MethodBecause mouse amylin is nonamyloidogenic, we developed an APP/PS1 mouse model in which the mouse amylin gene is replaced by the human amylin gene and is conditionally regulated by tamoxifen (TMX) injection, intraperitonially. At 3 months of age, human amylin‐expressing male mice were randomly assigned to either amylin downregulation group or control group (maintained amylin expression) (n = 10/group). Two months later, we assessed brain function with the novel object recognition test and performed comparative immunochemical Aβ analyses of hippocampal tissue by using MSD ELISA and immunohistochemistry (IHC).ResultMice with downregulated human amylin show enhanced recognition memory index (p < 0.001) and lower plasma amylin levels (p < 0.001) compared to those that continued to express human amylin. This was associated with decreased hippocampal levels of Aβ42 (p < 0.05) measured by MSD ELISA and decreased number of plaques (P < 0.01) measured by IHC.ConclusionAmylin downregulation in APP/PS1 mice improves memory. Molecular processes associated with improved memory involve decreased hippocampal Aβ pathology. Further studies are needed to understand how altered secretion of pancreatic amylin may influences the balance between brain Aβ accumulation and Aβ elimination from the brain.