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Compelling experimental evidence suggests that microglial activation is involved in the spread of tau tangles over the neocortex in Alzheimer’s disease (AD). We tested the hypothesis that the spatial propagation of microglial activation and tau accumulation colocalize in a Braak-like pattern in the living human brain. We studied 130 individuals across the aging and AD clinical spectrum with positron emission tomography brain imaging for microglial activation ([ 11 C]PBR28), amyloid-β (Aβ) ([ 18 F]AZD4694) and tau ([ 18 F]MK-6240) pathologies. We further assessed microglial triggering receptor expressed on myeloid cells 2 ( TREM2 ) cerebrospinal fluid (CSF) concentrations and brain gene expression patterns. We found that [ 11 C]PBR28 correlated with CSF soluble TREM2 and showed regional distribution resembling TREM2 gene expression. Network analysis revealed that microglial activation and tau correlated hierarchically with each other following Braak-like stages. Regression analysis revealed that the longitudinal tau propagation pathways depended on the baseline microglia network rather than the tau network circuits. The co-occurrence of Aβ, tau and microglia abnormalities was the strongest predictor of cognitive impairment in our study population. Our findings support a model where an interaction between Aβ and activated microglia sets the pace for tau spread across Braak stages. Microglial activation and tau accumulation propagate together in patients with Alzheimer’s disease, suggesting an interaction that determines disease progression.

Blood-based biomarkers for screening may guide tau positrion emissition tomography (PET) scan referrals to optimize prognostic evaluation in Alzheimer’s disease. Plasma Aβ42/Aβ40, pTau181, pTau217, pTau231, NfL, and GFAP were measured along with tau-PET in memory clinic patients with subjective cognitive decline, mild cognitive impairment or dementia, in the Swedish BioFINDER-2 study (n = 548) and in the TRIAD study (n = 179). For each plasma biomarker, cutoffs were determined for 90%, 95%, or 97.5% sensitivity to detect tau-PET-positivity. We calculated the percentage of patients below the cutoffs (who would not undergo tau-PET; “saved scans”) and the tau-PET-positivity rate among participants above the cutoffs (who would undergo tau-PET; “positive predictive value”). Generally, plasma pTau217 performed best. At the 95% sensitivity cutoff in both cohorts, pTau217 resulted in avoiding nearly half tau-PET scans, with a tau-PET-positivity rate among those who would be referred for a scan around 70%. And although tau-PET was strongly associated with subsequent cognitive decline, in BioFINDER-2 it predicted cognitive decline only among individuals above the referral cutoff on plasma pTau217, supporting that this workflow could reduce prognostically uninformative tau-PET scans. In conclusion, plasma pTau217 may guide selection of patients for tau-PET, when accurate prognostic information is of clinical value. A screening strategy with plasma p-tau217, evaluated in two independent cohorts from Sweden and Canada, showed that this biomarker may effectively streamline tau-PET referrals in memory clinic settings, optimizing the prognostic work-up of Alzheimer’s disease.

Alzheimer’s disease (AD) is a brain network disorder where pathological proteins accumulate through networks and drive cognitive decline. Yet, the role of network connectivity in facilitating this accumulation remains unclear. Using in-vivo multimodal imaging, we show that the distribution of tau and reactive microglia in humans follows spatial patterns of connectivity variation, the so-called gradients of brain organization. Notably, less distinct connectivity patterns (“gradient contraction”) are associated with cognitive decline in regions with greater tau, suggesting an interaction between reduced network differentiation and tau on cognition. Furthermore, by modeling tau in subject-specific gradient space, we demonstrate that tau accumulation in the frontoparietal and temporo-occipital cortices is associated with greater baseline tau within their functionally and structurally connected hubs, respectively. Our work unveils a role for both functional and structural brain organization in pathology accumulation in AD, and supports subject-specific gradient space as a promising tool to map disease progression. In Alzheimer’s disease, the role of connectivity in facilitating pathology accumulation remains unclear. Using in-vivo neuroimaging, the authors show that tau and reactive microglia follow connectome gradients, underlying cognitive decline.

Previous studies suggest glial and neuronal changes may trigger synaptic dysfunction in Alzheimer’s disease (AD), but the link between their markers and synaptic abnormalities in the living brain remains unclear. We investigated the association between glial reactivity and synaptic dysfunction biomarkers in cerebrospinal fluid (CSF) from 478 individuals in cognitively unimpaired (CU) and cognitively impaired (CI) individuals. We measured amyloid-β (Aβ), phosphorylated tau (pTau181), astrocyte reactivity (GFAP), microglial activation (sTREM2), and synaptic markers (GAP43, neurogranin). CSF GFAP levels were associated with presynaptic and postsynaptic dysfunction, independent of cognitive status or Aβ presence. CSF sTREM2 levels were related to presynaptic markers in cognitively unimpaired and impaired Aβ+ individuals, and to postsynaptic markers in cognitively impaired Aβ+ individuals. Notably, CSF pTau mediated the relationships between GFAP or sTREM2 and synaptic dysfunction. Our findings, validated in two independent cohorts (TRIAD and ADNI), reveal a distinct pattern of glial contribution to synaptic degeneration. This study shows that glial reactivity is linked to synaptic dysfunction in aging and Alzheimer’s disease, with tau pathology mediating these effects–highlighting the potential of synaptic biomarkers track disease progression.

In AD research, word-learning tests are often used interchangeably despite using distinct learning protocols. This study verified the equivalence of the Rey Auditory Learning Test (RAVLT) and Free and Cued Selective Reminding Test (FCSRT) when investigating medial temporal lobe (MTL) changes and AD-related tau pathology. We obtained the FCSRT and RAVLT immediate and delayed free recalls from 286 participants aged 51+. We segmented MTL regions to obtain the volume and tau-PET signal using the [ 18 F]MK-6240 tracer. Tau-PET Braak stages and plasma p-tau 181 , p-tau 217 and p-tau 231 quantifications were also acquired. Using partial correlations, we compared FCSRT to RAVLT as well as their ability to detect the cognitive status the AD biomarker results. FCSRT and RAVLT were strongly correlated to one another ( R  > 0.779), with similar differentiation of cognitively impaired and cognitively unimpaired individuals (AUC > 0.810). Both predicted MTL volume, MTL tau-PET accumulation, plasma p-tau and Braak stages similarly, with no significant effect size differences. For all tests, a subtle memory impairment was found at tau-PET Braak stage III, while more robust impairments were found at stage IV onward. Despite their differences, both the RAVLT and FCSRT are equivalent at detecting AD-related pathology and symptoms, suggesting that, in these contexts, they may be used interchangeably. However, these results should be interpreted with care since the sample is not representative of a global population.

Background Antibody-based immunoassays have enabled quantification of very low concentrations of phosphorylated tau (p-tau) protein forms in cerebrospinal fluid (CSF), aiding in the diagnosis of AD. Mass spectrometry enables absolute quantification of multiple p-tau variants within a single run. The goal of this study was to compare the performance of mass spectrometry assessments of p-tau 181 , p-tau 217 and p-tau 231 with established immunoassay techniques. Methods We measured p-tau 181 , p-tau 217 and p-tau 231 concentrations in CSF from 173 participants from the TRIAD cohort and 394 participants from the BioFINDER-2 cohort using both mass spectrometry and immunoassay methods. All subjects were clinically evaluated by dementia specialists and had amyloid-PET and tau-PET assessments. Bland–Altman analyses evaluated the agreement between immunoassay and mass spectrometry p-tau 181 , p-tau 217 and p-tau 231 . P-tau associations with amyloid-PET and tau-PET uptake were also compared. Receiver Operating Characteristic (ROC) analyses compared the performance of mass spectrometry and immunoassays p-tau concentrations to identify amyloid-PET positivity. Results Mass spectrometry and immunoassays of p-tau 217 were highly comparable in terms of diagnostic performance, between-group effect sizes and associations with PET biomarkers. In contrast, p-tau 181 and p-tau 231 concentrations measured using antibody-free mass spectrometry had lower performance compared with immunoassays. Conclusions Our results suggest that while similar overall, immunoassay-based p-tau biomarkers are slightly superior to antibody-free mass spectrometry-based p-tau biomarkers. Future work is needed to determine whether the potential to evaluate multiple biomarkers within a single run offsets the slightly lower performance of antibody-free mass spectrometry-based p-tau quantification.

Background Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity. Methods We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n  = 124), mild cognitive impairment (MCI; n  = 58), AD dementia ( n  = 34), and non-AD dementia ( n  = 26) patients all characterized by [ 18 F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 ( p -tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m 2 , based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models. Results Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values. Conclusions We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

The molecular mechanisms underlying neuronal dysfunction in Alzheimer’s disease (AD) remain uncharacterized. Here, we identify genes, molecular pathways and cellular components associated with whole-brain dysregulation caused by amyloid-beta (Aβ) and tau deposits in the living human brain. We obtained in-vivo resting-state functional MRI (rs-fMRI), Aβ- and tau-PET for 47 cognitively unimpaired and 16 AD participants from the Translational Biomarkers in Aging and Dementia cohort. Adverse neuronal activity impacts by Aβ and tau were quantified with personalized dynamical models by fitting pathology-mediated computational signals to the participant’s real rs-fMRIs. Then, we detected robust brain-wide associations between the spatial profiles of Aβ-tau impacts and gene expression in the neurotypical transcriptome (Allen Human Brain Atlas). Within the obtained distinctive signature of in-vivo neuronal dysfunction, several genes have prominent roles in microglial activation and in interactions with Aβ and tau. Moreover, cellular vulnerability estimations revealed strong association of microglial expression patterns with Aβ and tau’s synergistic impact on neuronal activity ( q < 0.001). These results further support the central role of the immune system and neuroinflammatory pathways in AD pathogenesis. Neuronal dysregulation by AD pathologies also associated with neurotypical synaptic and developmental processes. In addition, we identified drug candidates from the vast LINCS library to halt or reduce the observed Aβ-tau effects on neuronal activity. Top-ranked pharmacological interventions target inflammatory, cancer and cardiovascular pathways, including specific medications undergoing clinical evaluation in AD. Our findings, based on the examination of molecular-pathological-functional interactions in humans, may accelerate the process of bringing effective therapies into clinical practice.

Introduction Cerebrospinal fluid (CSF) tau biomarkers are reliable diagnostic markers for Alzheimer’s disease (AD). However, their strong association with amyloid pathology may limit their reliability as specific markers of tau neurofibrillary tangles. A recent study showed evidence that a ratio of CSF C-terminally truncated tau (tau368, a tangle-enriched tau species), especially in ratio with total tau (t-tau), correlates strongly with tau PET tracer uptake. In this study, we set to evaluate the performance of the tau368/t-tau ratio in capturing tangle pathology, as indexed by a high-affinity tau PET tracer, as well as its association with severity of clinical symptoms. Methods In total, 125 participants were evaluated cross-sectionally from the Translational Biomarkers of Aging and Dementia (TRIAD) cohort (21 young, 60 cognitively unimpaired [CU] elderly [15 Aβ+], 10 Aβ+ with mild cognitive impairment [MCI], 14 AD dementia patients, and 20 Aβ− individuals with non-AD cognitive disorders). All participants underwent amyloid and tau PET scanning, with [ 18 F]-AZD4694 and [ 18 F]-MK6240, respectively, and had CSF measurements of p-tau181, p-tau217, and t-tau. CSF concentrations of tau368 were quantified in all individuals with an in-house single molecule array assay. Results CSF tau368 concentration was not significantly different across the diagnostic groups, although a modest increase was observed in all groups as compared with healthy young individuals (all P < 0.01). In contrast, the CSF tau368/t-tau ratio was the lowest in AD dementia, being significantly lower than in CU individuals (Aβ−, P < 0.001; Aβ+, P < 0.01), as well as compared to those with non-AD cognitive disorders ( P < 0.001). Notably, in individuals with symptomatic AD, tau368/t-tau correlated more strongly with [ 18 F]-MK6240 PET SUVR as compared to the other CSF tau biomarkers, with increasing associations being seen in brain regions associated with more advanced disease (isocortical regions > limbic regions > transentorhinal regions). Importantly, linear regression models indicated that these associations were not confounded by Aβ PET SUVr. CSF tau368/t-tau also tended to continue to become more abnormal with higher tau burden, whereas the other biomarkers plateaued after the limbic stage. Finally, the tau368/t-tau ratio correlated more strongly with cognitive performance in individuals with symptomatic AD as compared to t-tau, p-tau217 and p-tau181. Conclusion The tau368/t-tau ratio captures novel aspects of AD pathophysiology and disease severity in comparison to established CSF tau biomarkers, as it is more closely related to tau PET SUVR and cognitive performance in the symptomatic phase of the disease.

Background While the temporal profile of amyloid (Aβ) and tau cerebrospinal fluid (CSF) biomarkers along the Alzheimer’s disease (AD) continuum is well-studied, chronological changes of CSF proteins reflecting other disease-relevant processes, denoted ‘X’ in the ATX(N) framework, remain poorly understood. Methods Using an untargeted mass spectrometric approach termed tandem mass tag (TMT), we quantified over 1500 CSF proteins across the AD continuum in three independent cohorts, finely staged by Aβ/tau positron emission tomography (PET), fluid biomarkers, or brain biopsy. Weighted protein co-expression network analysis identified clusters of proteins robustly correlating in all three cohorts which sequentially changed with AD progression. Obtained protein clusters were correlated with fluid biomarker measurements (phosphorylated tau (p-tau) species including p-tau 181 , p-tau 217 , and p-tau 205 , as well as Aβ), Aβ/tau PET imaging, and clinical parameters to discern disease-relevant clusters which were modelled across the AD continuum. Results Neurodegeneration-related proteins (e.g . , 14–3-3 proteins, PPIA), derived from different brain cell types, strongly correlated with fluid as well as imaging biomarkers and increased early in the AD continuum. Among them, the proteins SMOC1 and CNN3 were highly associated with Aβ pathology, while the 14–3-3 proteins YWHAZ and YWHAE as well as PPIA demonstrated a strong association with both Aβ and tau pathology as indexed by PET. Endo-lysosomal proteins (e.g., HEXB, TPP1, SIAE) increased early in abundance alongside neurodegeneration-related proteins, and were followed by increases in metabolic proteins such as ALDOA, MDH1, and GOT1 at the mild cognitive impairment (MCI) stage. Finally, later AD stages were characterized by decreases in synaptic/membrane proteins (e.g., NPTX2). Conclusions Our study identified proxies of Aβ and tau pathology, indexed by PET, (SMOC1, YWHAE, CNN3) and highlighted the dynamic fluctuations of the CSF proteome over the disease course, identifying candidate biomarkers for disease staging beyond Aβ and tau.