Individual regional associations between Aß-, tau- and neurodegeneration (ATN) with microglial activation in patients with primary and secondary tauopathies.

ß-amyloid (Aß) and tau aggregation as well as neuronal injury and atrophy (ATN) are the major hallmarks of Alzheimer's disease (AD), and biomarkers for these hallmarks have been linked to neuroinflammation. However, the detailed regional associations of these biomarkers with microglial activation in individual patients remain to be elucidated. We investigated a cohort of 55 patients with AD and primary tauopathies and 10 healthy controls that underwent TSPO-, Aß-, tau-, and perfusion-surrogate-PET, as well as structural MRI. Z-score deviations for 246 brain regions were calculated and biomarker contributions of Aß (A), tau (T), perfusion (N1), and gray matter atrophy (N2) to microglial activation (TSPO, I) were calculated for each individual subject. Individual ATN-related microglial activation was correlated with clinical performance and CSF soluble TREM2 (sTREM2) concentrations. In typical and atypical AD, regional tau was stronger and more frequently associated with microglial activation when compared to regional Aß (AD: ßT = 0.412 ± 0.196 vs. ßA = 0.142 ± 0.123, p < 0.001; AD-CBS: ßT = 0.385 ± 0.176 vs. ßA = 0.131 ± 0.186, p = 0.031). The strong association between regional tau and microglia reproduced well in primary tauopathies (ßT = 0.418 ± 0.154). Stronger individual associations between tau and microglial activation were associated with poorer clinical performance. In patients with 4RT, sTREM2 levels showed a positive association with tau-related microglial activation. Tau pathology has strong regional associations with microglial activation in primary and secondary tauopathies. Tau and Aß related microglial response indices may serve as a two-dimensional in vivo assessment of neuroinflammation in neurodegenerative diseases.

A Residual Marker of Cognitive Reserve Is Associated with Resting-State Intrinsic Functional Connectivity Along the Alzheimer's Disease Continuum.

BACKGROUND: Cognitive reserve (CR) explains inter-individual differences in the impact of the neurodegenerative burden on cognitive functioning. A residual model was proposed to estimate CR more accurately than previous measures. However, associations between residual CR markers (CRM) and functional connectivity (FC) remain unexplored. OBJECTIVE: To explore the associations between the CRM and intrinsic network connectivity (INC) in resting-state networks along the neuropathological-continuum of Alzheimer's disease (ADN). METHODS: Three hundred eighteen participants from the DELCODE cohort were stratified using cerebrospinal fluid biomarkers according to the A(myloid-ß)/T(au)/N(eurodegeneration) classification. CRM was calculated utilizing residuals obtained from a multilinear regression model predicting cognition from markers of disease burden. Using an independent component analysis in resting-state fMRI data, we measured INC of resting-state networks, i.e., default mode network (DMN), frontoparietal network (FPN), salience network (SAL), and dorsal attention network. The associations of INC with a composite memory score and CRM and the associations of CRM with the seed-to-voxel functional connectivity of memory-related were tested in general linear models. RESULTS: CRM was positively associated with INC in the DMN in the entire cohort. The A+T+N+ group revealed an anti-correlation between the SAL and the DMN. Furthermore, CRM was positively associated with anti-correlation between memory-related regions in FPN and DMN in ADN and A+T/N+. CONCLUSION: Our results provide evidence that INC is associated with CRM in ADN defined as participants with amyloid pathology with or without cognitive symptoms, suggesting that the neural correlates of CR are mirrored in network FC in resting-state.

Lifelong experiences as a proxy of cognitive reserve moderate the association between connectivity and cognition in Alzheimer's disease.

Alzheimer's disease (AD) is associated with alterations in functional connectivity (FC) of the brain. The FC underpinnings of CR, that is, lifelong experiences, are largely unknown. Resting-state FC and structural MRI were performed in 76 CSF amyloid-ß (Aß) negative healthy controls and 152 Aß positive individuals as an AD spectrum cohort (ADS; 55 with subjective cognitive decline, SCD; 52 with mild cognitive impairment; 45 with AD dementia). Following a region-of-interest (ROI) FC analysis, intrinsic network connectivity within the default-mode network (INC-DMN) and anti-correlation in INC between the DMN and dorsal attention network (DMN:DAN) were obtained as composite scores. CR was estimated by education and Lifetime Experiences Questionnaire (LEQ). The association between INC-DMN and MEM was attenuated by higher LEQ scores in the entire ADS group, particularly in SCD. In ROI analyses, higher LEQ scores were associated with higher FC within the DMN in ADS group. INC-DMN remains relatively intact despite memory decline in individuals with higher lifetime activity estimates, supporting a role for functional networks in maintaining cognitive function in AD.

Microglial Activation and Connectivity in Alzheimer Disease and Aging.

OBJECTIVE: Alzheimer disease (AD) is characterized by amyloid ß (Aß) plaques and neurofibrillary tau tangles, but increasing evidence suggests that neuroinflammation also plays a key role, driven by the activation of microglia. Aß and tau pathology appear to spread along pathways of highly connected brain regions, but it remains elusive whether microglial activation follows a similar distribution pattern. Here, we assess whether connectivity is associated with microglia activation patterns. METHODS: We included 32 Aß-positive early AD subjects (18 women, 14 men) and 18 Aß-negative age-matched healthy controls (10 women, 8 men) from the prospective ActiGliA (Activity of Cerebral Networks, Amyloid and Microglia in Aging and Alzheimer's Disease) study. All participants underwent microglial activation positron emission tomography (PET) with the third-generation mitochondrial 18 kDa translocator protein (TSPO) ligand [18 F]GE-180 and magnetic resonance imaging (MRI) to measure resting-state functional and structural connectivity. RESULTS: We found that inter-regional covariance in TSPO-PET and standardized uptake value ratio was preferentially distributed along functionally highly connected brain regions, with MRI structural connectivity showing a weaker association with microglial activation. AD patients showed increased TSPO-PET tracer uptake bilaterally in the anterior medial temporal lobe compared to controls, and higher TSPO-PET uptake was associated with cognitive impairment and dementia severity in a disease stage-dependent manner. INTERPRETATION: Microglial activation distributes preferentially along highly connected brain regions, similar to tau pathology. These findings support the important role of microglia in neurodegeneration, and we speculate that pathology spreads throughout the brain along vulnerable connectivity pathways. ANN NEUROL 2022;92:768-781.

Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study.

BACKGROUND: Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer's disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. METHODS: We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. RESULTS: Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. CONCLUSIONS: Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology.