Bundle-specific associations between white matter microstructure and Aβ and tau pathology in preclinical Alzheimer\u27s disease

Beta-amyloid (Aβ) and tau proteins, the pathological hallmarks of Alzheimer\u27s disease (AD), are believed to spread through connected regions of the brain. Combining diffusion imaging and positron emission tomography, we investigated associations between white matter microstructure specifically in bundles connecting regions where Aβ or tau accumulates and pathology. We focused on free-water-corrected diffusion measures in the anterior cingulum, posterior cingulum, and uncinate fasciculus in cognitively normal older adults at risk of sporadic AD and presymptomatic mutation carriers of autosomal dominant AD. In Aβ-positive or tau-positive groups, lower tissue fractional anisotropy and higher mean diffusivity related to greater Aβ and tau burden in both cohorts. Associations were found in the posterior cingulum and uncinate fasciculus in preclinical sporadic AD, and in the anterior and posterior cingulum in presymptomatic mutation carriers. These results suggest that microstructural alterations accompany pathological accumulation as early as the preclinical stage of both sporadic and autosomal dominant AD

Trait Mindfulness Is Associated With Less Amyloid, Tau, and Cognitive Decline in Individuals at Risk for Alzheimer's Disease

BACKGROUND: Mindfulness, defined as nonjudgmental awareness of the present moment, has been associated with an array of mental and physical health benefits. Mindfulness may also represent a protective factor for Alzheimer's disease (AD). Here, we tested the potential protective effect of trait mindfulness on cognitive decline and AD pathology in older adults at risk for AD dementia. METHODS: Measures of trait mindfulness, longitudinal cognitive assessments, and amyloid-β (Aβ) and tau positron emission tomography scans were collected in 261 nondemented older adults with a family history of AD dementia from the PREVENT-AD (Pre-symptomatic Evaluation of Experimental or Novel Treatments for AD) observational cohort study. Multivariate partial least squares analyses were used to examine relationships between combinations of different facets of trait mindfulness and 1) cognitive decline, 2) Aβ, and 3) tau. RESULTS: Higher levels of mindful nonjudgment, describing, and nonreactivity were associated with less cognitive decline in attention, global cognition, and immediate and delayed memory. Higher levels of mindful nonjudgment and nonreactivity were related to less Aβ positron emission tomography signal in bilateral medial and lateral temporoparietal and frontal regions. Higher levels of mindful acting with awareness, describing, nonjudgment, and nonreactivity were associated with less tau positron emission tomography signal in bilateral medial and lateral temporal regions. CONCLUSIONS: Trait mindfulness was associated with less cognitive decline and less Aβ and tau in the brain in older adults at risk for AD dementia. Longitudinal studies examining the temporal relationship between trait mindfulness and AD markers, along with mindfulness intervention studies, will be important for further clarifying the potential protective benefits of mindfulness on AD risk

Combining plasma phospho-tau and accessible measures to evaluate progression to Alzheimer’s dementia in mild cognitive impairment patients

BACKGROUND: Up to now, there are no clinically available minimally invasive biomarkers to accurately identify mild cognitive impairment (MCI) patients who are at greater risk to progress to Alzheimer's disease (AD) dementia. The recent advent of blood-based markers opens the door for more accessible biomarkers. We aimed to identify which combinations of AD related plasma biomarkers and other easily accessible assessments best predict progression to AD dementia in patients with mild cognitive impairment (MCI). METHODS: We included patients with amnestic MCI (n = 110) followed prospectively over 3 years to assess clinical status. Baseline plasma biomarkers (amyloid-β 42/40, phosphorylated tau217 [p-tau217], neurofilament light and glial fibrillary acidic protein), hippocampal volume, APOE genotype, and cognitive tests were available. Logistic regressions with conversion to amyloid-positive AD dementia within 3 years as outcome was used to evaluate the performance of different biomarkers measured at baseline, used alone or in combination. The first analyses included only the plasma biomarkers to determine the ones most related to AD dementia conversion. Second, hippocampal volume, APOE genotype and a brief cognitive composite score (mPACC) were combined with the best plasma biomarker. RESULTS: Of all plasma biomarker combinations, p-tau217 alone had the best performance for discriminating progression to AD dementia vs all other combinations (AUC 0.84, 95% CI 0.75-0.93). Next, combining p-tau217 with hippocampal volume, cognition, and APOE genotype provided the best discrimination between MCI progressors vs. non-progressors (AUC 0.89, 0.82-0.95). Across the few best models combining different markers, p-tau217 and cognition were consistently the main contributors. The most parsimonious model including p-tau217 and cognition had a similar model fit, but a slightly lower AUC (0.87, 0.79-0.95, p = 0.07). CONCLUSION: We identified that combining plasma p-tau217 and a brief cognitive composite score was strongly related to greater risk of progression to AD dementia in MCI patients, suggesting that these measures could be key components of future prognostic algorithms for early AD. TRIAL REGISTRATION: NCT01028053 , registered December 9, 2009

Repetitive negative thinking is associated with amyloid, tau, and cognitive decline

International audienceIntroduction: The Cognitive Debt hypothesis proposes that repetitive negative thinking(RNT), a modifiable process common to many psychological risk factors for Alzheimer’sdisease (AD) may itself increase risk. We sought to empirically examine relationshipsbetween RNT and markers of AD, compared with anxiety and depression symptoms.Methods: Two hundred and ninety-two older adults with longitudinal cognitive assessments, including 113 with amyloid-positron emission tomography (PET) and tau-PETscans, from the PREVENT-AD cohort and 68 adults with amyloid-PET scans from theIMAP+ cohort were included. All participants completed RNT, anxiety, and depressionquestionnaires.Results: RNT was associated with decline in global cognition (P = .02); immediate (P =.03) and delayed memory (P = .04); and global amyloid (PREVENT-AD: P = .01; IMAP+:P = .03) and entorhinal tau (P = .02) deposition. Relationships remained after adjustingfor potential confounders.Discussion: RNT was associated with decline in cognitive domains affected early inAD and with neuroimaging AD biomarkers. Future research could investigate whethermodifying RNT reduces AD risk

Combining plasma phospho-tau and accessible measures to evaluate progression to Alzheimer’s dementia in mild cognitive impairment patients

Background: Up to now, there are no clinically available minimally invasive biomarkers to accurately identify mild cognitive impairment (MCI) patients who are at greater risk to progress to Alzheimer’s disease (AD) dementia. The recent advent of blood-based markers opens the door for more accessible biomarkers. We aimed to identify which combinations of AD related plasma biomarkers and other easily accessible assessments best predict progression to AD dementia in patients with mild cognitive impairment (MCI). Methods: We included patients with amnestic MCI (n = 110) followed prospectively over 3 years to assess clinical status. Baseline plasma biomarkers (amyloid-β 42/40, phosphorylated tau217 [p-tau217], neurofilament light and glial fibrillary acidic protein), hippocampal volume, APOE genotype, and cognitive tests were available. Logistic regressions with conversion to amyloid-positive AD dementia within 3 years as outcome was used to evaluate the performance of different biomarkers measured at baseline, used alone or in combination. The first analyses included only the plasma biomarkers to determine the ones most related to AD dementia conversion. Second, hippocampal volume, APOE genotype and a brief cognitive composite score (mPACC) were combined with the best plasma biomarker. Results: Of all plasma biomarker combinations, p-tau217 alone had the best performance for discriminating progression to AD dementia vs all other combinations (AUC 0.84, 95% CI 0.75–0.93). Next, combining p-tau217 with hippocampal volume, cognition, and APOE genotype provided the best discrimination between MCI progressors vs. non-progressors (AUC 0.89, 0.82–0.95). Across the few best models combining different markers, p-tau217 and cognition were consistently the main contributors. The most parsimonious model including p-tau217 and cognition had a similar model fit, but a slightly lower AUC (0.87, 0.79–0.95, p = 0.07). Conclusion: We identified that combining plasma p-tau217 and a brief cognitive composite score was strongly related to greater risk of progression to AD dementia in MCI patients, suggesting that these measures could be key components of future prognostic algorithms for early AD. Trial registration: NCT01028053, registered December 9, 2009

Confounding factors of Alzheimer's disease plasma biomarkers and their impact on clinical performance

Introduction: Plasma biomarkers will likely revolutionize the diagnostic work-up of Alzheimer's disease (AD) globally. Before widespread use, we need to determine if confounding factors affect the levels of these biomarkers, and their clinical utility. Methods: Participants with plasma and CSF biomarkers, creatinine, body mass index (BMI), and medical history data were included (BioFINDER-1: n = 748, BioFINDER-2: n = 421). We measured beta-amyloid (Aβ42, Aβ40), phosphorylated tau (p-tau217, p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). Results: In both cohorts, creatinine and BMI were the main factors associated with NfL, GFAP, and to a lesser extent with p-tau. However, adjustment for BMI and creatinine had only minor effects in models predicting either the corresponding levels in CSF or subsequent development of dementia. Discussion: Creatinine and BMI are related to certain plasma biomarkers levels, but they do not have clinically relevant confounding effects for the vast majority of individuals. Highlights: Creatinine and body mass index (BMI) are related to certain plasma biomarker levels. Adjusting for creatinine and BMI has minor influence on plasma-cerebrospinal fluid (CSF) associations. Adjusting for creatinine and BMI has minor influence on prediction of dementia using plasma biomarkers

A biomarker profile of elevated CSF p-tau with normal tau PET is associated with increased tau accumulation rates on PET in early Alzheimer’s disease

Background: Different tau biomarkers become abnormal at different stages of Alzheimer’s disease (AD), with CSF p-tau typically being elevated at subthreshold levels of tau-PET binding. To capitalize on the temporal order of tau biomarker-abnormality and capture the earliest changes of tau accumulation, we selected a group of amyloid-β-positive (A+) individuals with elevated CSF p-tau levels but negative tau-PET scans and assessed longitudinal changes in tau-PET, cortical thickness and cognitive decline. Method: Individuals without dementia (i.e., cognitively unimpaired (CU) or mild cognitive impairment, n=231) were selected from the BioFINDER-2 study. These subjects were categorized into biomarker groups based on Gaussian mixture modelling to determine cut-offs for abnormal CSF Aβ42/40 (A; 110 pg/ml) and [18F]RO948 tau-PET SUVR within a temporal meta-ROI (T; SUVR >1.40). Resulting groups were: A+P-T- (concordant, n=30), A+P+T- (discordant, n=48) and A+P+T+ (concordant, n=18). We additionally used 135 A- CU individuals (A- CU) as a reference group (Tables 1 and 2). Differences in annual change in regional tau-PET SUVR, cortical thickness and cognition between the A+P+T- group and the other groups were assessed using general linear models, adjusted for age, sex, clinical diagnosis and (for cognitive measures) education. Result: Longitudinal change in tau-PET was faster in the A+P+T- group than in the A- CU and A+P-T- groups across medial temporal and neocortical regions, with the medial temporal increases being more pronounced. The A+P+T- group showed slower rate of increases in tau-PET compared to the A+P+T+ group, primarily in neocortical regions (Figures 1 and 2). We did not detect differences in yearly change in cortical thickness (Figure 3) or in cognitive decline (Figure 3) between the A+P+T- and A+P-T- groups. The A+P+T+ group, however, showed faster cognitive decline compared to all other groups. Conclusion: These findings suggest that the A+P+T- biomarker profile is associated with early tau accumulation, and with relative sparing of cortical thinning and cognitive decline compared to A+P+T+ individuals. Therefore, the A+P+T- group represents an interesting target-group for early anti-tau interventions and for examining the emergence of tau aggregates in early AD

Age-related tau-PET uptake and its downstream effects extend beyond the medial temporal lobe in cognitively normal older adults

Background: Amyloid-beta (Aβ) is hypothesized to facilitate the spread of tau pathology beyond the medial temporal lobe (MTL). However, there is evidence that age-related Aβ-independent tau pathology is present outside the MTL (Kaufman et al., Acta Neuropathol, 2018). We examine tau deposition determined by positron emission tomography (PET) in regions typically involved earlier/later in AD and downstream effects on neurodegeneration and cognition in cognitively unimpaired older adults and a low-Aβ subgroup. Methods: We included 488 adults (40-91 years; low-Aβ: n=355, 65.2±11.5 years) from the BioFINDER-2 study. MTL volumes (dentate gyrus, subiculum (SUB), cornu ammonis 1) and thickness (entorhinal cortex, Brodmann areas (BA)35/36, and parahippocampal cortex) were obtained, using Automated Segmentation for Hippocampal Subfields packages for T1- and T2-weighted magnetic resonance images. Thickness of early/late neocortical AD-regions (anterior cingulate, precuneus/posterior cingulate (PPC), orbitofrontal, inferior parietal cortex; and middle frontal, lateral occipital, and precentral/postcentral gyrus) was determined using FreeSurfer. [18F]RO948- and [18F]flutemetamol-PET standardized uptake value ratios (SUVRs) were calculated for local tau and global/local Aβ. Aβ status was determined using Aβ-PET or cerebrospinal fluid Aβ-42/40 ratio. Global cognition was measured using delayed word-list recall, trail making test B, and animal fluency. Results: Increasing age was associated with higher tau-PET SUVRs primarily in MTL/frontal/parietal regions. A significant association between age and local tau-PET remained even when including Aβ-PET as a mediator (Fig. 1). Age and local tau-PET, but not Aβ-PET, where negatively associated with structure in most examined regions (Figs. 2-3). Age-structure associations were serially mediated via tau-PET in regions with early AD pathology (SUB/BA35/PPC). Also, in the low-Aβ subgroup, tau-PET mediated the age-structure (SUB/BA35/PPC) associations (Fig. 3D). Finally, the age-global cognition relationship was serially mediated via MTL tau-PET and subiculum volume, even when including global Aβ-PET as additional mediator (Fig. 4). Conclusion: We observe partially Aβ-independent associations between age and tau-PET signal across the neocortex. Interestingly, partially Aβ-independent tau-PET signal appears to mediate the age-structure associations in and outside the MTL (PPC), also in the low-Aβ group, and the age-MTL structure-cognition associations. This potentially provides in vivo support for Primary Age-related Tauopathy downstream effects on structure, beyond the MTL, and cognition

Phospho-tau with subthreshold tau-PET predicts increased tau accumulation rates in amyloid-positive individuals

Different tau biomarkers become abnormal at different stages of Alzheimer's disease, with CSF phospho-tau typically becoming elevated at subthreshold levels of tau-PET binding. To capitalize on the temporal order of tau biomarker-abnormality and capture the earliest changes of tau accumulation, we implemented an observational study design to examine longitudinal changes in Tau-PET, cortical thickness and cognitive decline in amyloid-β-positive (A+) individuals with elevated CSF P-tau levels (P+) but subthreshold Tau-PET retention (T-). To this end, individuals without dementia (i.e., cognitively unimpaired or mild cognitive impairment, N = 231) were selected from the BioFINDER-2 study. Amyloid-β-positive (A+) individuals were categorized into biomarker groups based on cut-offs for abnormal CSF P-tau217 and [18F]RO948 (Tau) PET, yielding groups of tau-concordant-negative (A + P-T-; n = 30), tau-discordant (i.e., A + P+T-; n = 48) and tau-concordant-positive (A + P+T+; n = 18) individuals. In addition, 135 amyloid-β-negative, tau-negative, cognitively unimpaired individuals served as controls. Differences in annual change in regional Tau-PET, cortical thickness and cognition between the groups were assessed using general linear models, adjusted for age, sex, clinical diagnosis and (for cognitive measures only) education. Mean follow-up time was ∼2 years. Longitudinal increase in Tau-PET was faster in the A + P+T- group than in the control and A + P-T- groups across medial temporal and neocortical regions, with the highest accumulation rates in the medial temporal lobe. The A + P+T- group showed a slower rate of increases in tau-PET compared to the A + P+T+ group, primarily in neocortical regions. We did not detect differences in yearly change in cortical thickness or in cognitive decline between the A + P+T- and A + P-T- groups. The A + P+T+ group, however, showed faster cognitive decline compared to all other groups. Altogether, these findings suggest that the A + P+T- biomarker profile in persons without dementia is associated with an isolated effect on increased Tau-PET accumulation rates but not on cortical thinning and cognitive decline. While this suggests that the tau-discordant biomarker profile is not strongly associated with short-term clinical decline, this group does represent an interesting population for monitoring effects of interventions with disease modifying agents on tau accumulation in early Alzheimer's disease, and for examining the emergence of tau aggregates in Alzheimer's disease. Further, we suggest to update the AT(N) criteria for Alzheimer's disease biomarker classification to APT(N)

Amyloid-associated increases in soluble tau is a key driver in accumulation of tau aggregates and cognitive decline in early Alzheimer

Background: For optimal design of anti-amyloid-β (Aβ) and anti-tau clinical trials, it is important to understand how Aβ and soluble phosphorylated tau (p-tau) relate to the accumulation of tau aggregates assessed with positron emission tomography (PET) and subsequent cognitive decline across the Alzheimer's disease (AD) continuum. Method: We included 327 participants from the Swedish BioFINDER-2 cohort with cerebrospinal fluid (CSF) p-tau217, Aβ-PET, longitudinal tau-PET, and longitudinal cognition. The main groups of interest were Aβ-positive non-demented participants and AD dementia patients (Table 1 and Figure 1), and analyses were conducted separately in each group. First, we investigated how soluble p-tau217 and regional Aβ-PET were associated with tau-PET rate of change across the 200 brain parcels from the Schaefer atlas. We also tested the mediating effect of p-tau217 between Aβ-PET and tau-PET change. Second, we investigated how soluble p-tau217 and tau-PET change related to change in cognition, and mediation between these variables. Result: In early AD stages (non-demented participants), increased concentration of soluble p-tau217 was the main driver of accumulation of insoluble tau aggregates across the brain (measured as tau-PET rate of change), beyond the effect of regional Aβ-PET and baseline tau-PET (Figure 2A-C). Further, averaged across all regions, soluble p-tau217 mediated 54% of the association between Aβ and tau aggregation (Figure 2D). Higher soluble p-tau217 concentrations were also associated with cognitive decline, which was mediated by faster increase of tau aggregates (Figure 3). Repeating the same analyses in the AD dementia group, results were different. In late stage of AD, when Aβ fibrils and soluble p-tau levels have plateaued, soluble p-tau217 was not associated with accumulation of tau aggregates beyond baseline tau-PET (Figure 4A), and cognitive decline was driven by the accumulation rate of insoluble tau aggregates and not soluble p-tau217 (Figure 4B-C). Conclusion: Soluble p-tau is a main driver of tau aggregation and future cognitive decline in earlier stages of AD, whereas tau aggregation accumulation is more likely an important driver of disease in later stages. Overall, our data suggest that therapeutic approaches reducing soluble p-tau levels might be most favorable in early AD