Petersen, Ronald C.

AbstractBackgroundRecent advances in the development of novel Alzheimer’s disease (AD) measures of amyloid, tau, and neurodegeneration in cerebrospinal fluid (CSF) and blood have enabled a better understanding of the links between amyloid‐beta (Aβ), tau species and neurodegeneration in the brain, CSF, and blood. The discoveries of novel tau species in CSF and blood, including specific phospho‐tau (p‐tau) and truncated species containing the microtubule binding region of tau (MTBR‐tau) which aggregates in tau tangles, have greatly expanded our understanding of tau biology and tau target development. The longitudinal Aβ, tau, and neurofilament light chain (NfL) changes previously measured in CSF are now being measured accurately in blood, enabling interpretation and understanding of AD progression in much larger and more robust populations.MethodWe analyzed longitudinal CSF and/or blood plasma mass spectrometry measures of Aβ42/Aβ40, multiple p‐tau species (including p‐tau217, 231, 181, 205, etc.), total tau, MTBR‐tau (e.g., MTBR‐tau243, MTBR‐tau299, and MTBR‐tau354), and NfL in sporadic AD and dominantly inherited AD cohorts. Mass spectrometry results were compared to amyloid and tau aggregation measures by Positron Emission Tomography (PET) scans and clinical and cognitive measures in local and international clinical cohorts including ADNI, AIBL, BioFINDER, Mayo Clinic, the Knight ADRC, and the DIAN.ResultThe longitudinal results indicate that a pathophysiological cascade of events begin with altered CSF and blood plasma Aβ42/Aβ40 ratio, followed by increases in amyloid plaques as measured by amyloid PET, associated with increased phosphorylation of specific CSF tau species (e.g., p‐tau217, p‐tau181, etc.), before increases in p‐tau205, NfL, total tau concentrations, hypometabolism, and atrophy. Finally, some species of MTBR‐tau increase before or with tau aggregation by tau PET and onset of clinical symptoms and correlate with longitudinal tau aggregation and clinical progression.ConclusionThese findings indicate that CSF and blood plasma Aβ, p‐tau, MTBR‐tau and NfL measures are highly precise biomarkers of brain amyloidosis, tauopathy, and neurodegeneration and can accurately identify stages of preclinical and clinical AD.

AbstractBackgroundBlood phosphorylated tau (p‐tau) has proven to be the primary candidate as an accessible and scalable biomarker for Alzheimer’s disease (AD). Both p‐tau181 and p‐tau217 are highly accurate to detect AD within dementia cases. Our recent work in cerebrospinal fluid, however, indicates p‐tau231 to be associated to incipient AD pathology. In light of this, we developed a Single molecule array (Simoa) to detect plasma p‐tau231 and assessed its performance in multiple domains, specifically, its ability to detect preclinical AD.MethodIn all cohorts, plasma p‐tau231 was quantified using an in‐house Simoa method developed at the Clinical Neurochemistry Laboratory, Gothenburg University, Sweden. Data presented in this study are samples acquired from Translational Biomarkers of Aging and Dementia (TRIAD, n=503), King’s College London (n=55), Mayo Clinic Study of Aging (n=145), KARVIAH (n=140), Baltimore Longitudinal Study of Aging (n=430), University College London (n=70), Paris University (n=213), PREVENT‐AD (n=257), University of California (n=309) and ALFA+ (n=385).ResultIn the TRIAD cohort, plasma p‐tau231 demonstrated high accuracy in determining AD from young individuals (AUC=0.95), Aβ‐ elderly (AUC=0.92), Aβ‐ MCI (AUC=0.88) and other neurodegenerative disorders (AUC=0.92). In an autopsy study, plasma p‐tau231 could detect neuropathologically confirmed AD amongst dementia cases (AUC=0.99). In comparing healthy elderly Aβ‐ and Aβ+ individuals, p‐tau231 predicted preclinical Aβ pathology (AUC=0.83). Furthermore, inflection points of the weighted regression curves demonstrate that increases in plasma p‐tau231 occur before plasma p‐tau181 as a function of Aβ deposition load. Plasma p‐tau231 data from additional cohorts will focus on cross‐sectional and longitudinal preclinical datasets. In addition, further data will show the performance of p‐tau231 in symptomatic and presymptomatic PSEN1/APP mutation carriers, memory clinic cohorts, longitudinal neuropathology confirmed and acute neurological injury.ConclusionPlasma p‐tau231 is a new biomarker specific for AD pathology and at higher concentrations relative to p‐tau181 and p‐tau217. Our initial results indicate that plasma p‐tau231 is equivalent to p‐tau181 in diagnostic utility but has greater potential as a biomarker to monitor emerging Aβ pathology. This presentation will give an overview of novel cross‐sectional and longitudinal plasma p‐tau231 data, in more than 3000 individuals, that encompasses the AD continuum, familial AD and other neurological conditions.

AbstractBackgroundBlood‐based biomarkers of amyloid pathology and neurodegeneration are entering clinical use. It is critical to understand what factors affect these plasma marker levels for accurate clinical interpretation. Herein we examined factors associated with plasma Ab42, Ab40, neurofilament light (NfL), total tau (T‐tau), and the ratio of Ab42 to Ab40 (Ab42/40).MethodThe plasma markers were measured for 996 participants (859 cognitively unimpaired [CU], 133 mild cognitive impairment [MCI], 4 dementia) from the Mayo Clinic Study of Aging (MCSA), aged 51 to 95 years. The Quanterix Simoa® HD‐1 analyzer was employed to measure the plasma markers using the Simoa® Neurology 3‐Plex A (N3PA) (T‐tau, Ab42, Ab40) (catalog #101995) and the Simoa® NF‐light (catalog #103180). All other data was collected during in‐person MCSA visits or abstracted from the medical record. Statistical significance was determined using an alpha level of 0.05.ResultAmong CU, all of the plasma markers showed correlation with age. T‐tau (Spearman’s rho = 0.113, p<0.001) showed the weakest correlation and NfL (rho = 0.695, p<0.001) had the strongest. Women had higher levels of T‐tau (Median women: 2.782 vs. 2.390, p<0.001) and lower Ab42/40 (0.033 vs. 0.035, p=0.024) compared to men. In linear regression models predicting z‐scored plasma markers and adjusted for age and sex, several statistically significant predictors were found. For example, higher Charlson comorbidity index and chronic kidney disease were associated with higher levels of all markers; slower gait speed was associated with higher levels for all but Ab42/40 where no relationship was seen. A higher BMI was associated with higher levels of Ab42, Ab40, and T‐tau whereas NfL tended to be lower with increased BMI. Among participants with MCI or dementia, the relationship between gait speed or chronic kidney disease with NfL and T‐tau strengthened considerably.ConclusionMultiple variables affect plasma markers of amyloid pathology and neurodegeneration among CU in the general population. Some relationships differed among MCI and dementia participants. Incorporating this information is critical for accurate interpretation of the marker levels and for the development of reference ranges.

AbstractBackgroundDecreased amyloid β1‐42 (Aβ42) and increased tau (t‐Tau and p‐Tau) concentrations in cerebrospinal fluid (CSF) reflect the pathological changes of Alzheimer’s disease (AD) and aid in the diagnosis of AD dementia. In the United States, the ADmark® assay has been almost exclusively used for the measurement of these biomarkers in clinical practice. Recently, our institution switched from the ADmark® assay to the Roche Elecsys assays. The goal of this study was to determine if differences exist between these methods in classification of patients as having changes indicative of AD pathology.MethodPatients undergoing ADMark® testing (n= 73) were recruited to participate in this IRB‐approved study. Two simultaneous CSF aliquots were obtained. For ADMark®, 2.0mL were collected into a 5mL polypropylene (PP) tube and shipped frozen to Athena Diagnostics per collection instructions for testing (Innotest® immunoassays for Aβ42, t‐Tau, and p‐Tau). For the Roche Elecsys assays (Aβ42, t‐Tau, and p‐Tau), 2.0mL were collected into a 2.5mL low bind PP tube, frozen, and then tested at Mayo Clinic Laboratories. Comparative analysis was performed between the two testing methodologies and to clinical findings.ResultOverall concordance between the ADMark® Aβ42/t‐Tau index (ATI) and Roche p‐Tau/Aβ42 was 89% with 8 (11%) discrepant cases. Four cases were classified as normal by the Roche p‐Tau/Aβ42 but borderline (n=3) or abnormal (n=1) by ADMark® ATI. Four cases were classified as abnormal by the Roche p‐Tau/Aβ42 and borderline by ADMark® ATI. In these cases, the normal Roche p‐Tau/Aβ42 result was most consistent with clinical diagnosis. When compared to clinical diagnosis, cases with clinical suspicion of AD dementia were abnormal in 84% and 92% of cases with the ADMark® ATI and the Roche p‐Tau/Aβ42, respectively. In cases without clinical suspicion of AD dementia, results were abnormal in 19% and 21% of cases with the ADMark® ATI and the Roche p‐Tau/Aβ42, respectively. There were 2 cases with clinical suspicion of AD dementia and 5 cases without suspicion of AD dementia that were classified as borderline by ADMark® ATI.ConclusionRoche p‐Tau/Aβ42 showed comparable performance to ADMark® ATI when correlating results to clinical diagnosis of AD dementia.

AbstractBackgroundThe Neurodegenerative Research Group (NRG) at Mayo clinic has followed patients with degenerative speech and/or language disorders for over a decade. In this presentation I will present data from this cohort to inform a broader discussion about the importance of apraxia of speech (AOS) and its subtypes, heterogeneity within the agrammatic PPA variant, and perils of mixed phenotypes.MethodWe reviewed the NRG database to identify patients who initially presented with isolated (PPAOS), AOS in conjunction with agrammatic aphasia (AOS‐PAA), isolated agrammatic aphasia (PAA), and patients who had PAA or AOS overlapping with another degenerative diagnosis. Data from the following clinical instruments were abstracted: WAB AQ (aphasia severity), UPDRS III (parkinsonism), WAB Praxis (ideomotor apraxia), and the MoCA (cognitive ability). We assessed the effect of baseline diagnosis and AOS subtype on these outcomes over time using Bayesian linear mixed effects models. We qualitatively reviewed longitudinal diagnostic trajectories. Preliminary analyses were done on available autopsy data.ResultPAA was associated with greater aphasia at baseline and more rapid decline; PPAOS was associated with normal language at baseline and slow decline; and PAA‐AOS with intermediate baseline aphasia and decline. However, for those with AOS longitudinal decline differed based on AOS subtype: prosodic PPAOS was associated with the slowest decline and phonetic PAA‐AOS with the fastest. Some patients met criteria for non‐PPA disorders during follow up. However, compared to patients who met criteria for these disorders at enrollment, the speech/language‐first patients remained qualitatively distinct, and neither resembled the cases that were mixed at onset. Preliminary autopsy data suggests that AOS is predictive of tau and that the specific tauopathy may be related to the initial syndrome and AOS subtype.ConclusionThe differences between PAA, PAA‐AOS and PPAOS suggest that these disorders should not be lumped. In fact, the longitudinal trajectories are sufficiently different that doing so would add noise to observational and interventional studies. Instead, more detailed phenotyping, including AOS subtype, can aid prognostication and may improve prediction of the underlying pathology. Finally, caution should be exercised when considering PPAOS and PPA patients for other FTLD diagnostic categories.

AbstractBackgroundAdvancing age is an important risk factor for dementia and cancer. An inverse association between these conditions has been described, yet caution from potential biases/confounders is warranted. Dementia and cancer may represent a spectrum of opposing dysregulated degenerative (apoptosis) and growth (proliferative) pathways respectively (Driver, 2014). Risk or resiliency factors affecting these pathways may influence cognitive outcomes in the oldest‐old. We sought to investigate demographics, clinical characteristics, and the impact of medical comorbidity on possible risk‐resiliency factors for neurodegeneration in nondemented and demented oldest‐old who died and underwent autopsy.MethodMedical records of 161 decedents (female n=134) from the Mayo Clinic 95+ year‐old cohort (age range 95‐106 years‐old) were reviewed. Groups consisting of nondemented (n=72) and demented (n=89) decedents were stratified and compared according to demographics and clinical variables, including history of cancer. Autopsy and neuropathologic evaluation was also conducted.ResultAge at death, sex, race, and education showed no differences between nondemented and demented decedents. History of cancer was higher in nondemented (57%) compared to demented decedents (30%) (p=0.002). APOE ε4 allele presence did not differ amongst groups, while APOE ε2 allele was more common in the nondemented group (p=0.026). History of coronary artery disease was higher in the nondemented (p=0.033). No differences were observed in other vascular risk factors, alcohol use, or depression. Smoking history approached significance and was higher in nondemented compared to demented (p=0.068). MMSE scores were higher in the nondemented group (p<0.001). Neuropathology findings included a lower Braak tangle staging in nondemented (median=III) compared to demented (median=V) groups (p<0.001) and less frequent diffuse plaques observed in the nondemented (67%) compared with those demented (93%) (p<0.001).ConclusionDementia is less frequent among cancer survivors in the 95+ oldest‐old. Disease‐related mechanisms associated with malignancy and surviving it may be protective against neurodegeneration in the oldest old.

AbstractBackgroundImpaired olfaction has been associated with neurodegenerative diseases and may be a useful tool to aid in diagnosis or track disease progression. We sought to compare olfaction in participants with the clinical diagnoses of idiopathic REM sleep behavior disorder (RBD), dementia with Lewy bodies (DLB), or Alzheimer’s disease dementia (AD).MethodParticipants from the Mayo Clinic Alzheimer’s Disease Research Center database who had a diagnosis of RBD (n=27, 56% male), DLB (n=51, 84% male), or AD (n=83, 47% male), and were given the Brief Smell Identification Test (B‐SIT) were included in this analysis. The B‐SIT score was calculated as the sum of correct responses (12 possible). Scores were categorized as reflecting anosmia (<6), hyposmia (6‐10), and normal olfactory function (>10). All participants underwent clinical and neuropsychological evaluations.ResultGlobal cognition was lower in AD and DLB than RBD (MMSE 21.5 ±4.9 in AD, 23.3 ±4.3 in DLB, 28.8 ± 1.2 in RBD; p <0.001). The mean B‐SIT total score was significantly lower for DLB (4.5 ± 3.1) compared to RBD (7.5 ± 3.0) or AD (7.0 ± 2.7) (p<0.001) using an ANOVA F‐test. Anosmia was present in 76% of DLB, which compared to 32% in RBD, and 32% in AD (p=0.9). Hyposmia was present in 18% of DLB, 47% of RBD, and 52% of AD (p=ns). Of 22 patients with normal olfaction, X% were DLB, X% RBD, and X% AD (p=X). An item analysis illustrated that participants with DLB were less likely to identify Menthol, Clove, Strawberry, Smoke, and Soap than those with RBD and AD. On serial examination, 12 RBD (60%) patients’ B‐SIT score decreased by at least one point at their most recent visit compared to their baseline visit.ConclusionThese findings suggest that impaired olfactory function is frequent in RBD, DLB and AD, with olfaction being worst in DLB in this cohort. Olfaction was declining in most of those with RBD who underwent serial evaluations. Further analyses are needed to determine if any scents are more sensitive to phenotype, progression, and degree of cognitive impairment. Supported by: NIH grants AG016574, NS100620, AG056639, AG015866

AbstractBackgroundNeocortical tau can be present in over half of patients with Lewy body disease at autopsy, and may influence the timing of when a diagnosis of Dementia with Lewy bodies (DLB) can be made. We examined whether the core features, onset age and latency of probable DLB diagnosis differ by pathological subgroups.MethodAll patients (n=176) met clinical criteria for probable DLB, underwent autopsy and were classified as transitional or diffuse Lewy body disease (TLBD, DLBD). The TLBD and DLBD groups were further subdivided based on the absence of neocortical tangles represented by a low (L) Braak NFT stage of 0‐III or by the presence of neocortical tangles represented by a high (H) Braak NFT stage of IV‐VI. Onset age and latency from cognitive symptom onset to probable DLB were compared for TLBD‐L (n=30), DLBD‐L (n=47), DLBD‐H (n=78) and TLBD‐H (n=21).ResultThe TLBD‐H group met criteria for DLB at an older age (median 76 years) compared to TLBD‐L, DLBD‐L or DLBD‐H groups (median age 70 years, p<0.001). The latency to probable DLB from cognitive onset was shortest for TLBD‐L and DLBD‐L (median < 1 year), which was shorter than DLBD‐H (median 2 years; p=0.016), each of which were shorter than TLBD‐H (median 7.3 years; p<0.001). RBD was more common in men (79% men vs. 40% women, p<0.001) and in patients without neocortical tangles (86% vs. 57%, p<0.001). Patients with RBD met criteria for probable DLB at a younger age than those without a history of RBD (median 69 years vs. 76 years, p<0.001). Men had a shorter latency to probable DLB than women (median 1.0 year vs. 2.8 years, p<0.01), but this was related to RBD status that was more common in men.ConclusionPresence of RBD in both sexes led to a younger onset age and shorter latency to diagnosis of probable DLB. Patients with more widespread tau relative to α‐synuclein pathology (TLBD‐H) were older when probable DLB was diagnosed compared to those with so‐called pure Lewy body disease (TLBD‐L, DLBD‐L) or those with diffuse α‐synuclein and tau pathology (DLBD‐H).

AbstractBackgroundThere have been no standard definitions of successful cognitive aging (SA). Our goal was to apply different SA definitions to the 80+ population in the Mayo Clinic Study of Aging (MCSA) on the basis of (i) cross‐sectional vs longitudinal cognition (“Exceptionality” vs “Maintenance”) and (ii) memory vs global cognitive scores and explore the participant characteristics for each SA definition on the basis of baseline imaging markers and mid/late‐life health.MethodWe included 2157 participants from the MCSA, all ≥80 years at baseline and classified them into two SA definitions using memory z‐scores or global z‐scores: “Exceptionality” when high cognitive performance was observed (z‐scores ≥ 1 SD), “Maintenance” when cognitive function was preserved over time (Slope ≥ ‐0.1/year using mixed‐effect models). Our imaging markers were: PET‐based amyloid positivity (A+), MRI‐based neurodegeneration positivity (N+), WMH, FDG‐PET SUVR markers of resilience (anterior cingulate, ACC) and AD‐related areas (posterior cingulate). We also examined APOE4 status and other health characteristics. Group comparison was performed within each definition (e.g. exceptional vs non‐exceptional memory) using ANCOVA and binary logistic regressions with adjustments for age, sex, and education.ResultA lower number of participants met the “Exceptionality” criteria (10%: memory and 4%: global). A greater number met the “Maintenance” criteria (53%: memory and 32%: global). Less than 7% showed both “Exceptional” cognition and “Maintenance” over time. Participants across SA definitions were in general younger, more often women, with a higher education/occupation and less often APOE4 carriers. All SA groups showed higher ACC metabolism and lower N+ compared to the corresponding non‐SA group. More than 50% of the participants in the “Exceptional” groups were A+ (57%: memory, 50%: global). A+ frequency was significantly lower in the “Maintainers” (<42%). Better mid/late‐life health indicators were observed in the SA groups, including lower cardio‐metabolic conditions, higher mid‐life cognitive activities, lower depressive symptomatology, lower hypersomnolence and better self‐perception of health.ConclusionDifferent SA definitions identified mainly non‐overlapping 80+ groups that showed several common features including higher education/occupation, percent of women, better lifestyles, lower N+ frequency, and higher ACC metabolism. Lower A+ frequency was a key distinct feature of “Maintenance”.

AbstractBackgroundThe Mayo Clinic Study of Aging and Alzheimer’s Disease Research Center used GE scanners exclusively for MRI from 2005‐2017, employing consistent imaging parameters throughout. In 2017 the MRI protocol was updated and migrated to Siemens Prisma scanners; 113 participants were scanned with each configuration. The GE protocol included a 2D FLAIR. The Siemens protocol includes 3D FLAIR and T2‐weighted images. Both vendor protocols included a 3D T1. Experience with multi‐center trials suggests such changes may introduce systematic variations.MethodsGE scanning was carried out on 3T scanners with 12 channel phased array head coils. Siemens Prisma scanning was carried out with 64 channel head/neck coils. Imaging sequences and parameters are given in Table 1. We used the MCALT template and priors to perform standard six‐class segmentation on T1‐weighted (T1w) images. SPM12 unified segmentation supports the simultaneous use of multiple input contrasts; segmentation of multi‐contrast inputs was done using eight tissue classes including deep grey and white matter hyperintensity (WMH) priors. For a given MRI study (either GE or Siemens) all images were registered and resampled to the study’s T1w image. Two‐channel (T1+FLAIR) segmentation was performed on GE scans. Two and three‐channel segmentations were performed on Siemens scans. Comparisons included total intracranial volume, total tissue volume and total grey matter volumes, as well as hippocampal volumes and grey matter volume in a temporal lobe meta‐ROI.ResultsFour participants were excluded for poor image quality: one poor GE T1w quality, one poor Siemens T1, T2 and FLAIR quality, and two poor Siemens T2 quality. Comparisons were made among 109 participants aged 34–97 (Table 2). By visual assessment, adding T2‐weighted images always improved intracranial volume correctness. Using the combination of single‐channel GE and three‐channel Siemens generally improved cross‐vendor agreement on grey matter volumes with the exceptions of hippocampal and intracranial volume estimates.ConclusionRequiring multiple input channels increases the likelihood that the result of a study being excluded. Combining T1w, FLAIR and T2w images allows the delineation of WMH and deep grey matter probability outputs but may introduce differences in GM volumes.