Mielke, Michelle M.

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.

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 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 We hypothesized that poorer cerebral perfusion could impair mobility, particularly at lower systolic blood pressure (SBP). Cerebral perfusion was measured via arterial spin-labelled (ASL)-MRI in community-dwelling adults of the Mayo Clinic Study of Aging. Usual-pace gait speed was assessed over 5.6 meters on an electronic mat. Linear regression models estimated cross-sectional gait speed associations with ASL and modifying effects of age and SBP, adjusting for sex and body mass index. Results report differences in gait speed (meter/second) per standard deviation (SD) lower ASL or SBP (mean=139.1 mmHg, SD=19.7 mmHg). Among 479 participants (aged 31-94 years; mean age 67.6 years; 44% women; mean gait speed 1.17m/s), relationships of ASL with gait speed varied by age and SBP (ASL-x-age interaction: p&lt;.007; ASL-x-SBP interaction: p&lt;.007). At age 65, 75 or 85 years and a SBP of 120mmHg, each SD lower ASL was associated with a 0.04 m/s (0.01,0.07), 0.07 m/s (0.04,0.10), and 0.09 m/s (0.05,0.13) slower gait speed at respective ages. At age 65, 75 or 85 years with low ASL (1 SD below the mean), each SD lower SBP was associated with 0.06 (0.02,0.09) m/s, 0.03 (0.01,0.06) m/s or .01 (-0.02,0.04) m/s slower gait speed, respectively. With high ASL (mean ASL+1SD), lower SBP trended towards faster gait at older age, e.g. estimated gait speed was 0.04 m/s (0.00,0.09) faster for each SD lower SBP at age 85years. Poorer cerebral perfusion may contribute to slower gait, particularly with lower SBP. The interrelations of cerebral perfusion, SBP, and age with mobility merit further study.

Abstract Opioids are frequently prescribed to alleviate pain symptoms in older adults, yet the relationships between prescription opioid availability and long-term cognitive function are incompletely defined. We evaluated the associations between prescription opioid availability and neuropsychological function and incident mild cognitive impairment (MCI) by performing a secondary analysis of the Mayo Clinic Study of Aging (MCSA), a longitudinal population-based observational cohort study with participants enrolled between 11/1/2004 and 4/1/2019 aged 65 years or older at the time of enrollment and without dementia. A total of 4,218 participants (51% male) were included with median age of 76 (interquartile range 72, 82) years. In multivariable analyses, each receipt of an opioid prescription, regardless of duration, resulted in an additional -0.007 (95% CI: -0.009, -0.005) change in global cognitive z-score (p&lt; 0.001), with significant effects seen in the domains of memory (-0.005, 95% CI: -0.007, -0.003; p&lt; 0.001), language (-0.002, 95% CI -0.003, 0.000; p=0.024) and attention (-0.004, 95% CI: -0.006, -0.002; p&lt; 0.001) but not visual-spatial function (0.000, 95% CI: -0.001, 0.001; p=0.897). Among 2,963 cognitively unimpaired subjects with longitudinal follow-up, 769 (26%) developed incident MCI. Receipt of any opioid prescription during follow-up was associated with incident MCI in adjusted analysis (hazard ratio 1.21, 95% CI: 1.04, 1.42; p=0.014). In conclusion, prescription opioid availability was associated with cognitive decline across multiple domains and with incident MCI. These findings suggest that prescription opioid availability may have long-term effects on cognitive function.

AbstractBackgroundAmyloidosis‐driven tau deposition has been a significant focus of imaging research in Alzheimer’s disease (AD). However, the 3R/4R tau seen in AD can be observed in the transentorhinal/entorhinal regions (Braak I/II) in the absence of amyloidosis. The underlying drivers of this phenomenon are not well understood. Our goal was to examine amyloid‐independent pathways of longitudinal Tau‐PET SUVR progression in the entorhinal cortex (ERC) using a broad range of risk and protective factors.MethodWe identified 449 participants from the population‐based sample of Mayo Clinic Study of Aging >50 years old with baseline amyloid PET and at least two serial tau PET scans (mean number of scans=2.3; mean follow‐up time=3.2 years). Using an amyloid SUVR cut‐point of 1.48, we categorized participants into A+ (n=167; mean age=77.5 years; 56% male; baseline ERC tau=1.20; 83% cognitively unimpaired) and A‐ (n=282; mean age=67.5; 56% male; baseline ERC tau=1.07; 92% cognitively unimpaired). We used an ERC tau SUVR cut‐point of 1.21 to determine T+. We fit mixed effects and growth curve models with age, sex, baseline amyloid, risk factors (midlife activities, sleep, stress, education/occupation, cardiovascular metabolic conditions) as predictors and longitudinal ERC tau as the outcome. We fit separate models in A‐, A+, and all participants.ResultsFor models of all participants and A+ participants, the only predictors of higher rates of ERC tau deposition were increasing age and amyloid SUVR (p<0.05). In the A‐ models (figure below), amyloid SUVR and age were predictors of baseline, but not longitudinal ERC tau. However, a greater number of cardiovascular metabolic conditions predicted a higher rate of ERC tau accumulation (0.007 (0.002), p<0.05). Only 13% of the 23 A‐T+ participants were APOE4 carriers (compared to 31% in the overall sample), suggesting the role of non‐APOE4 pathways to tau deposition.ConclusionOur results support previous evidence that significant amyloidosis is causal to higher rates of tau deposition. However, in those without significant amyloidosis, cardiovascular metabolic conditions predicted higher rates of ERC tau accumulation. Further work is warranted to investigate the mechanisms through which genetics, comorbidities, and lifestyle may play a role in early tau deposition.

AbstractBackgroundA major benefit of the use of blood‐based biomarkers in screening for Alzheimer’s disease (AD) pathology, or diagnosing AD dementia, is that the collection of blood is less invasive and costly than cerebrospinal fluid or neuroimaging markers. Blood biomarkers are also more feasible and available at the primary care levels, where most individuals will present with cognitive symptoms. However, most studies examining blood‐based biomarkers of amyloid, phosphorylated tau, or neurodegeneration for screening or diagnosis have been conducted in neurology or memory clinics. Patients that reach these clinics often have less comorbidities and are younger than those seen and followed in primary care. Thus, there is a need to assess the utility of these blood‐biomarkers in diverse, community‐based cohorts of older ages, with multiple comorbidities, and with brain co‐pathologies (i.e., cerebrovascular disease).MethodUsing examples from the Mayo Clinic Study on Aging and other community‐based studies, we will synthesize the impact of demographics, comorbidities, and co‐pathologies on blood measures of amyloid‐beta, phosphorylated tau, neurofilament light chain (NfL), total tau, and glial fibrillary acid protein (GFAP). Additional discussion will focus on how these factors may impact cut‐points and the interpretation of the blood biomarkers across the AD clinical spectrum, as well as potential methods to better elucidate the biomarker results for clinical care.ResultBlood measures of amyloid‐beta, phosphorylated tau, NfL, total tau, and GFAP are differentially affected by age and sex and some comorbidities (e.g., chronic kidney disease, stroke, myocardial infarction, diabetes, body mass index). Although adjusting for covariates has been a method used in some research studies, adjustment will not work on an individualized level for patients seen in primary care. Different cutpoints may be needed based on age and the presence or absence of specific comorbidities. In addition, when interpreting the results for diagnosis and prognosis, co‐occurring co‐pathologies (e.g., cerebrovascular disease) must be considered.ConclusionSeveral studies have shown the promise of blood‐based biomarkers for screening and diagnosing AD in memory clinics. However, several considerations and steps are needed before these blood biomarkers can be implemented for use at the population level and in primary care.BackgroundWhen and how to communicate effectively the results of genetic and biomarker based prediction, detection, and quantification of the brain substrates of dementia involve important ethical and legal issues critical for precision medicine. AGREEDementia is an open working group that focuses on informed discussions and development of educational material to support communication and use of this information.MethodMembers attend two meetings monthly via videoteleconference. One meeting is a targeted working group that focuses on the following: 1. People with Symptoms, 2. People without Symptoms, 3. Research, 4. Ethics/Healthcare Law, 5. Diversity. Members also attend a monthly “all hands” meeting where they receive updates from other groups, partner organizations, and hear presentations on emerging research and resources.ResultOver the past few years AGREEDementia has produced several collaborative papers, webinars, and decision tools for people considering undergoing biomarker testing that will be discussed. Membership continues to grow to over 120 though level of involvement varies. The group is largely comprised of academic researchers (76%) including neurologists, neuropsychologists, clinical trial coordinators, ethicists, and healthcare lawyers. The second largest subgroup was from advocacy groups and stakeholders (18%) and 6% are students. Collaborations with other organizations including the NIA, Alzheimer’s Association/ISTAART, the Lewy Body Dementia Association, Association for Frontotemporal Dementia, and Cohen Veterans Bioscience greatly enrich the group by publicizing conferences and collaborating on papers and products. The Alzheimer’s & Dementia Outreach, Recruitment & Engagement at NIA also disseminates decision tools and other materials. Over time, the stakeholder group developed from an audience providing consultation to a creative force that pioneered a program to support people with cognitive dysfunction attending AAIC and other scientific conferences. The Diversity workgroup was added in order to mentor and teach research staff in sensitive outreach to diverse cohorts. The ongoing, monthly, lecture series and links to all these materials are hosted at a website, AGREEDementia.com.ConclusionWith controversies around how best to integrate biomarker and genetic information into clinical care, when to share research data with the public, and implement novel biomarker‐based therapies, AGREEDementia has provided an open forum for all to visit and consult.

AbstractBackgroundBlood‐based biomarkers of amyloid and neurodegeneration are increasingly used in clinical trials and entering clinical use. Differentially mapping the plasma markers to post‐mortem neuropathology in a community‐based sample is critical for interpretation.MethodWe identified 64 Mayo Clinic Study of Aging (MCSA) participants with antemortem plasma markers (Aβ42, Aβ40, NfL, T‐tau, Aβ42/40 ratio) measured on the Quanterix Simoa HD‐1 analyzer and with postmortem neuropathologic assessments of Alzheimer’s pathology (Braak tangle stage, Thal phase, neuritic plaque burden) and cerebrovascular pathology (Strozyk scale focused on macrovascular brain changes and Kalaria scale focused on detailed micro‐ and macro‐ vascular brain changes). Weighted linear regression models with adjustment for time between plasma markers and death were conducted with exact permutation tests to evaluate the relationships between antemortem plasma and postmortem neuropathology markers.ResultHigher plasma NfL levels and Aβ42/40 ratio were associated with both cerebrovascular neuropathologic scales (p<0.05) but were not associated with Braak neurofibrillary tangle stage, neuritic plaque score, or Thal stage (p>0.5). Plasma T‐tau was not associated with any pathological assessment. Plasma Aβ42/40 and NfL explained up to 18% of the variability in cerebrovascular neuropathologic scales.ConclusionIn this community sample of participants predominantly without dementia, plasma markers for amyloid (Aβ42/40) and neurodegeneration (NfL) were associated with cerebrovascular neuropathology at autopsy. NfL is a non‐specific marker of brain injury, therefore, its association with cerebrovascular neuropathology was in the expected direction. The association between greater cerebrovascular neuropathology and elevated Aβ42/40 requires further investigation. These findings provide evidence that cerebrovascular disease may significantly influence levels of plasma biomarkers proposed for Alzheimer’s disease. This information will be important to consider for accurate clinical interpretation of the proposed biomarkers.

AbstractBackgroundNeurofilament light chain (NfL) is an emerging blood‐based biomarker useful for assessing neuro‐axonal injury in several neurological conditions. Plasma NfL concentrations reflect the extent of axonal damage, making it a general marker of neurodegenerative disease progression. This study evaluates the analytical performance characteristics of the Quanterix NfL Advantage method in EDTA‐plasma.MethodThe assay was performed per manufacturer’s instructions on the Quanterix Simoa HD‐X Analyzer. Analytical validation included analyte stability, imprecision, lower limit of quantification (LLOQ), analytical measurement range (AMR), accuracy, and interferences. One‐sided reference intervals were established using quantile regression methods among 1100 cognitive normal individuals, age 20 to 95 years without known chronic kidney disease, stroke, or myocardial infarction.ResultNfL was stable in plasma three days ambient, seven days refrigerate, 90 days frozen (‐20C), and over 3 freeze/thaw cycles. Intra and inter‐assay imprecision, expressed as % coefficient of variation (%CV), ranged from 3.4 – 6.0% and 5.9 – 11.6% respectively. The LLOQ was evaluated using patient plasma pools at concentrations of 1.7 and 3.6 pg/mL. %CVs were 16.8% and 9.7% respectively, and the LLOQ was set at 3.0 pg/mL. Accuracy was assessed by spiking 5 plasma samples with NfL calibratoran 87% average recovery (range 81‐94%) was observed. The AMR of 3.0 – 1500 pg/mL was verified with a regression slope of 0.93 and r2 > 0.99. Additionally, plasma admixtures covering the AMR showed acceptable linear response (slope of 1.02 and r² >0.99). The assay was not affected by icterus to 100 mg/dL, lipemia to 1000 mg/dL, hemolysis to 1000 mg/dL at NfL concentrations >30 pg/mL or to 200 mg/dL at NfL concentrations ≤30 pg/mL. NfL increased with age but did not differ by sex. The data supported age‐based reference intervals broken down into 10‐year intervals. The 97.5th percentile limits were: 20s: ≤8.4 pg/mL, 30s: ≤11.4 pg/mL, 40s: ≤15.4 pg/mL, 50s: ≤20.8 pg/mL, 60s: ≤28.0 pg/mL, 70s: ≤37.9 pg/mL, 80+: ≤51.2 pg/mL.ConclusionThe analytical performance characteristics of the plasma Quanterix NfL advantage assay were deemed acceptable for clinical laboratory implementation. The establishment of NfL reference intervals will aid in the clinical interpretation of patient plasma NfL concentrations.