Citations

Background: The National Institute on Aging-Alzheimer’s Association Research Framework proposes defining Alzheimer’s disease by grouping imaging and fluid biomarkers by their respective pathologic processes. The AT(N) structure proposes several neurodegenerative fluid biomarkers (N) including total tau (t-tau), neurogranin (Ng), and neurofilament light chain (NfL). However, pathologic drivers influencing each biomarker remain unclear. Objective: To determine whether cerebrospinal fluid (CSF)-neurodegenerative biomarkers (N) map differentially to Alzheimer’s disease pathology measured by Aβ 42 (an indicator of amyloidosis, [A]), p-tau (an indicator of tau deposition, [T]), and MRI vascular pathology indicators (measured by white-matter integrity, infarcts, and microbleeds [V]). Methods: Participants were from Mayo Clinic Study of Aging (MCSA) with CSF measures of NfL, Ng, t-tau, Aβ 42 , and p-tau and available MRI brain imaging. Linear models assessed associations between CSF neurodegeneration (N) markers, amyloid markers (A), tau (T), and vascular pathology (V). Results: Participants ( n = 408) had a mean age of 69.2±10.7; male, 217 (53.2%); cognitively unimpaired, 359 (88%). All three neurodegeneration biomarkers correlated with age ( p < 0.001 for NfL and t-tau, p = 0.018 for Ng). Men had higher CSF-NfL levels; women had higher Ng ( p < 0.001). NfL and t-tau levels correlated with infarcts ( p = 0.009, p = 0.034 respectively); no biomarkers correlated with white-matter integrity. N biomarkers correlated with p-tau levels (T, p < 0.001). Higher Aβ 42 levels associated with higher N-biomarker levels but only among cognitively unimpaired (A, p < 0.001). Conclusion: The influence of vascular pathology in the general population on CSF (N) biomarkers is modest, with greater influence of infarcts than white-matter disruption. Neurodegeneration markers more closely correlated with tau than amyloid markers.

Abstract Staging the severity of Alzheimer’s disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer’s Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer’s clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1–2, 3–4, 5–6) and a combined amyloid and tau PET stage (none/low versus intermediate/high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1–42 and Aβ1–40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78–0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72–0.85 versus C = 0.73–0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer’s disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.

Introduction: Cardiovascular health may be used for prevention of cerebral vascular disease. We evaluated whether improvement of cardiovascular health within midlife and from midlife to late-life were each associated with lower prevalence of MRI markers of cerebral vascular disease at late-life. Methods: 1,638 participants from the Atherosclerosis Risk in Communities (ARIC) Study took part in two visits at midlife (mean ages 53 at ARIC visit 1 and 59 at visit 3), and a late-life visit (mean age 76). A cardiovascular health Life’s Simple 7 score (range 0-12/0-14, depending on diet availability) including six/seven items was calculated at each visit, with weight assigned to each item as poor (0), intermediate (1), or ideal (2). Participants underwent 3T brain MRI scans in 2011-2013 (late-life visit). Outcomes were white matter hyperintensity volume, microbleeds, and lacunar, subcortical, and cortical infarcts at late-life. Linear and logistic regression models were used to assess the associations of cardiovascular health with MRI markers of cerebral vascular disease. Results: Thirty nine percent of participants had high cardiovascular health at midlife visit 1, 32% at midlife visit 3, and 33% at late-life. Improvement of cardiovascular health within midlife and from midlife to late-life were each associated with a lower prevalence of cerebral vascular disease markers. For example, improvement in cardiovascular health (per point) from midlife to late-life was associated with smaller white matter hyperintensity volume (Beta:-0.07 [95%CI:-0.10,-0.04]), and lower odds of microbleeds (OR:0.93 [0.90,0.97]), lacunar (OR:0.93 [0.89,0.97)], subcortical (OR:0.93 [0.89,0.97])], and cortical infarcts (OR:0.92 [0.87,0.97)] (Figure). Conclusions: Improving cardiovascular health within midlife and from midlife to late-life may prevent development of cerebral vascular disease.

AbstractAlterations of cerebral glucose metabolism can be detected in patients with isolated rapid eye movement sleep behaviour disorder, a prodromal feature of neurodegenerative diseases with α-synuclein pathology. However, metabolic characteristics that determine clinical progression in isolated rapid eye movement sleep behaviour disorder and their association with other biomarkers need to be elucidated. We investigated the pattern of cerebral glucose metabolism on 18F-fluorodeoxyglucose PET in patients with isolated rapid eye movement sleep behaviour disorder, differentiating between those who clinically progressed and those who remained stable over time. Second, we studied the association between 18F-fluorodeoxyglucose PET and lower dopamine transporter availability in the putamen, another hallmark of synucleinopathies. Patients with isolated rapid eye movement sleep behaviour disorder from the Mayo Clinic Alzheimer’s Disease Research Center and Center for Sleep Medicine (n = 22) and age-and sex-matched clinically unimpaired controls (clinically unimpaired; n = 44) from the Mayo Clinic Study of Aging were included. All participants underwent 18F-fluorodeoxyglucose PET and dopamine transporter imaging with iodine 123-radiolabeled 2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl) nortropane on single-photon emission computerized tomography. A subset of patients with isolated rapid eye movement sleep behaviour disorder with follow-up evaluations (n = 17) was classified as isolated rapid eye movement sleep behaviour disorder progressors (n = 7) if they developed mild cognitive impairment or Parkinson’s disease; or isolated rapid eye movement sleep behaviour disorder stables (n = 10) if they remained with a diagnosis of isolated rapid eye movement sleep behaviour disorder with no cognitive impairment. Glucose metabolic abnormalities in isolated rapid eye movement sleep behaviour disorder were determined by comparing atlas-based regional 18F-fluorodeoxyglucose PET uptake between isolated rapid eye movement sleep behaviour disorder and clinically unimpaired. Associations between 18F-fluorodeoxyglucose PET and dopamine transporter availability in the putamen were analyzed with Pearson’s correlation within the nigrostriatal pathway structures and with voxel-based analysis in the cortex. Patients with isolated rapid eye movement sleep behaviour disorder had lower glucose metabolism in the substantia nigra, retrosplenial cortex, angular cortex, and thalamus, and higher metabolism in the amygdala and entorhinal cortex compared with clinically unimpaired. Patients with isolated rapid eye movement sleep behaviour disorder who clinically progressed over time were characterized by higher glucose metabolism in the amygdala and entorhinal cortex, and lower glucose metabolism in the cerebellum compared with clinically unimpaired. Lower dopamine transporter availability in the putamen was associated with higher glucose metabolism in the pallidum within the nigrostriatal pathway; and with higher 18F-fluorodeoxyglucose uptake in the amygdala, insula, and temporal pole on a voxel-based analysis, although these associations did not survive after correcting for multiple comparisons. Our findings suggest that cerebral glucose metabolism in isolated rapid eye movement sleep behaviour disorder is characterized by hypometabolism in regions frequently affected during the prodromal stage of synucleinopathies, potentially reflecting synaptic dysfunction. Hypermetabolism is also seen in isolated rapid eye movement sleep behaviour disorder, suggesting that synaptic metabolic disruptions may be leading to a lack of inhibition, compensatory mechanisms, or microglial activation, especially in regions associated with nigrostriatal degeneration.

Abstract Dysexecutive Alzheimer’s disease (dAD) manifests as a progressive dysexecutive syndrome without prominent behavioral features, and previous studies suggest clinico-radiological heterogeneity within this syndrome. We uncovered this heterogeneity using unsupervised machine learning in 52 dAD patients with multimodal imaging and cognitive data. A spectral decomposition of covariance between FDG-PET images yielded six latent factors (“eigenbrains”) accounting for 48% of variance in patterns of hypometabolism. These eigenbrains differentially related to age at onset, clinical severity, and cognitive performance. A hierarchical clustering on the eigenvalues of these eigenbrains yielded four dAD subtypes, i.e. “left-dominant,” “right-dominant,” “bi-parietal-dominant,” and “heteromodal-diffuse.” Patterns of FDG-PET hypometabolism overlapped with those of tau-PET distribution and MRI neurodegeneration for each subtype, whereas patterns of amyloid deposition were similar across subtypes. Subtypes differed in age at onset and clinical severity where the heteromodal-diffuse exhibited a worse clinical picture, and the bi-parietal had a milder clinical presentation. We propose a conceptual framework of executive components based on the clinico-radiological associations observed in dAD. We demonstrate that patients with dAD, despite sharing core clinical features, are diagnosed with variability in their clinical and neuroimaging profiles. Our findings support the use of data-driven approaches to delineate brain–behavior relationships relevant to clinical practice and disease physiology.

Background: Phosphorylated cytoplasmic tau inclusions correlate with and precede cognitive deficits in Alzheimer’s disease (AD). However, pathological tau accumulation and relationships to synaptic changes remain unclear. Objective: To address this, we examined postmortem brain from 50 individuals with the full spectrum of AD (clinically and neuropathologically). Total tau, pTau231, and AMPA GluR1 were compared across two brain regions (entorhinal and middle frontal cortices), as well as clinically stratified groups (control, amnestic mild cognitive impairment, AD dementia), NIA-AA Alzheimer’s Disease Neuropathologic Change designations (Not, Low, Intermediate, High), and Braak tangle stages (1–6). Significant co-existing pathology was excluded to isolate changes attributed to pathologic AD. Methods: Synaptosomal fractionation and staining were performed to measure changes in total Tau, pTau231, and AMPA GluR1. Total Tau and pTau231 were quantified in synaptosomal fractions using Quanterix Simoa HD-X. Results: Increasing pTau231 in frontal postsynaptic fractions correlated positively with increasing clinical and neuropathological AD severity. Frontal cortex is representative of early AD, as it does not become involved by tau tangles until late in AD. Entorhinal total tau was significantly higher in the amnestic mild cognitive impairment group when compared to AD, but only after accounting for AD associated synaptic changes. Alterations in AMPA GluR1 observed in the entorhinal cortex, but not middle frontal cortex, suggest that pTau231 mislocalization and aggregation in postsynaptic structures may impair glutamatergic signaling by promoting AMPA receptor dephosphorylation and internalization. Conclusion: Results highlight the potential effectiveness of early pharmacological interventions targeting pTau231 accumulation at the postsynaptic density.

Abstract Neurofilament light chain, a putative measure of neuronal damage, is measurable in blood and CSF and is predictive of cognitive function in individuals with Alzheimer’s disease. There has been limited prior work linking neurofilament light and functional connectivity, and no prior work has investigated neurofilament light associations with functional connectivity in autosomal dominant Alzheimer’s disease. Here, we assessed relationships between blood neurofilament light, cognition, and functional connectivity in a cross-sectional sample of 106 autosomal dominant Alzheimer’s disease mutation carriers and 76 non-carriers. We employed an innovative network-level enrichment analysis approach to assess connectome-wide associations with neurofilament light. Neurofilament light was positively correlated with deterioration of functional connectivity within the default mode network and negatively correlated with connectivity between default mode network and executive control networks, including the cingulo-opercular, salience, and dorsal attention networks. Further, reduced connectivity within the default mode network and between the default mode network and executive control networks was associated with reduced cognitive function. Hierarchical regression analysis revealed that neurofilament levels and functional connectivity within the default mode network and between the default mode network and the dorsal attention network explained significant variance in cognitive composite scores when controlling for age, sex, and education. A mediation analysis demonstrated that functional connectivity within the default mode network and between the default mode network and dorsal attention network partially mediated the relationship between blood neurofilament light levels and cognitive function. Our novel results indicate that blood estimates of neurofilament levels correspond to direct measurements of brain dysfunction, shedding new light on the underlying biological processes of Alzheimer’s disease. Further, we demonstrate how variation within key brain systems can partially mediate the negative effects of heightened total serum neurofilament levels, suggesting potential regions for targeted interventions. Finally, our results lend further evidence that low-cost and minimally invasive blood measurements of neurofilament may be a useful marker of brain functional connectivity and cognitive decline in Alzheimer’s disease.

Abstract Introduction We aimed to define a Mayo Preclinical Alzheimer's disease Cognitive Composite (Mayo‐PACC) that prioritizes parsimony and use of public domain measures to facilitate clinical translation. Methods Cognitively unimpaired participants aged 65 to 85 at baseline with amyloid PET imaging were included, yielding 428 amyloid negative (A‐) and 186 amyloid positive (A+) individuals with 7 years mean follow‐up. Sensitivity to amyloid‐related cognitive decline was examined using slope estimates derived from linear mixed models (difference in annualized change across A+ and A‐ groups). We compared differences in rates of change between Mayo‐PACC and other composites (A+ > A‐ indicating more significant decline in A+). Results All composites showed sensitivity to amyloid‐related longitudinal cognitive decline (A+ > A‐ annualized change p < 0.05). Comparisons revealed that Mayo‐PACC (AVLT sum of trials 1‐5+6+delay, Trails B, animal fluency) showed comparable longitudinal sensitivity to other composites. Discussion Mayo‐PACC performs similarly to other composites and can be directly translated to the clinic.

Abstract Speech-in-noise performance is fundamental to daily communications and comprehensive characterization is needed. We studied 590 dementia-free participants aged 70-84 years, including 428 hearing-impaired participants from the Aging and Cognitive Health Evaluation in Elders (ACHIEVE) study baseline (2018-19), which is a randomized controlled trial partially nested within the Atherosclerosis Risk in Communities (ARIC) Study, and 162 normal-hearing ARIC Visit 6/7 (2016-17/2018-19) participants. The Quick Speech-in-Noise (QuickSIN) test was used to measure speech-in-noise performance. Predictors included (1) Four-frequency better-ear pure-tone average (PTA); (2) Magnetic resonance imaging (MRI) measures (total and lobar volumes, diffusion tensor imaging, white matter hyperintensities); (3) Global and domain-specific (language, memory, executive function) cognitive performance. All predictors were standardized to Z-scores. We used multivariable-adjusted linear regression, adjusting for demographic and disease covariates. PTA and cognitive performance, but not MRI measures, were independently associated with speech-in-noise performance, with PTA explaining the largest variance, indicating the promising role of hearing aids.