Machulda, Mary M.

AbstractBackgroundPosterior cortical atrophy (PCA) is one of the atypical Alzheimer's disease variants, characterized by predominant visuospatial and visuoperceptual deficits, with established dorsal and ventral subtypes. A third primary occipital (caudal) variant has been suggested. We aimed to determine its demographics, clinical manifestations, and biomarker findings.MethodsFifty‐two PCA patients were investigated. Patients underwent neuropsychological assessment, magnetic resonance imaging, and fluorodeoxyglucose (FDG)‐, amyloid‐, and tau‐positron emission tomography (tau‐PET) scans. Normalized regional FDG‐PET values were represented as z‐scores relative to a control population. Patients were divided into “primary occipital” and “other PCA” subgroups according to FDG‐PET‐defined criteria, with primary occipital defined as patients in which the z‐scores for occipital subregions were at least one standard deviation lower (SD) (i.e., more abnormal) than the z‐scores in all other brain regions. Global amyloid‐PET, temporo‐parietal FDG‐PET, and temporal tau‐PET regions‐of‐interest (ROIs) were calculated.ResultsNine patients were classified as primary occipital; they were older (p = 0.034) and had more years of education (p = 0.007) than other PCA patients. The primary occipital group performed worse on the Ishihara test for color perception (p < 0.001), while other PCA patients performed worse on the Western Aphasia Battery (WAB) praxis scale (p = 0.005). Overall neuropsychiatric symptom burden was lower in the primary occipital group (p < 0.001). The FDG‐PET meta‐ROI was higher in the primary occipital subtype (p = 0.006), but no differences were observed in amyloid‐ and tau‐PET.ConclusionsOur findings suggest that primary occipital PCA is characterized by an older age at onset, more color perception dysfunction, less severe ideomotor apraxia, and less hypometabolism in temporo‐parietal meta‐ROI compared to established phenotypes.

Abstract Objective Individuals with early-onset dysexecutive Alzheimer’s disease (dAD) have high rates of failed performance validity testing (PVT), which can lead to symptom misinterpretation and misdiagnosis. Method The aim of this retrospective study is to evaluate rates of failure on a common PVT, the test of memory malingering (TOMM), in a sample of clinical patients with biomarker-confirmed early-onset dAD who completed neuropsychological testing. Results We identified seventeen patients with an average age of symptom onset at 52.25 years old. Nearly fifty percent of patients performed below recommended cut-offs on Trials 1 and 2 of the TOMM. Four of six patients who completed outside neuropsychological testing were misdiagnosed with alternative etiologies to explain their symptomatology, with two of these patients’ performances deemed unreliable based on the TOMM. Conclusions Low scores on the TOMM should be interpreted in light of contextual and optimally biological information and do not necessarily rule out a neurodegenerative etiology.

AbstractBackgroundThe apolipoprotein ε4 (APOE4) allele is the most common and well established risk factor for typical late‐onset amnestic Alzheimer’s dementia. Less is known about the role of APOE in patients with atypical clinical presentations of AD, with studies often disagreeing on APOE4 frequencies in these cohorts. We aimed to assess relationships between APOE genotype and age, amyloid‐beta (Aβ) deposition and clinical phenotype in Alzheimer’s disease.Method138 atypical AD patients (57 posterior cortical atrophy and 81 logopenic aphasia) were recruited by the Neurodegenerative Research Group at Mayo Clinic, and underwent APOE testing and Pittsburgh Compound B PET. 318 typical AD patients with APOE genotype and known onset age were identified from ADNI (121 had Aβ‐PET). Aβ‐PET was quantified using the centiloid scale. Logistic regression was used to estimate the proportion of APOE4 carriers by onset age and clinical group. Linear regression was used to estimate mean Aβ centiloid by age, APOE4 status, and clinical group in patients who were Aβ‐positive (centiloid≥19).ResultThe overall frequency of APOE4 carriers was lower in atypical AD (52%) compared to typical AD (66%), particularly for ε4ε4 homozygotes (9% vs 20%). APOE4 frequency increased with age in atypical AD, but showed a bell‐shaped curve in typical AD where highest frequencies were observed between 65‐70 years (Figure). Typical AD showed higher APOE4 frequencies than atypical AD only between the ages of 57 and 69 years. Aβ centiloid was higher in atypical AD compared to typical AD by approximately 16 centiloid units, but did not differ according to APOE4 status (Figure). Aβ centiloid stayed relatively flat with increasing age for both carriers and non‐carriers in atypical AD, but declines with increasing age in typical AD. Relationships between APOE4 and age, as well as centiloid, did not differ between the two atypical AD phenotypes.ConclusionAPOE4 frequency differs between atypical and typical AD but is highly dependent upon age, with higher APOE4 frequency in typical AD only observed between 57 and 69 years. The findings highlight the importance of age and clinical phenotype in understanding the effects of APOE genotype in Alzheimer’s disease.

AbstractBackgroundProton MR Spectroscopy (1H MRS) provides non‐invasive measurements of alterations in brain biochemistry associated with neuronal and glial abnormalities in neurodegeneration. 1H MRS with along with automated voxel placement (AVP) improves the precision of 1H MRS metabolite measurements. Our objective was to investigate the association of 1H MRS metabolites obtained by the advanced sLASER single voxel 1H MRS protocol with early tau deposition as measured by AV‐1451 PET and Aβ deposition as measured by 11C‐Pittsburgh compound B (PiB) PET in cognitively unimpaired older adults.MethodCognitively unimpaired adults with median (range) age of 77 (66, 94) from the population‐based Mayo Clinic Study of Aging (MCSA) participated in the single‐voxel 1H MRS study (n=40). All participants had an MRI, 11C‐PiB and AV‐1451 PET examinations. The posterior cingulate cortex (PCC) and the left hippocampus (LHC) were chosen for the 1H MRS voxel locations because of their vulnerability to early AD pathology. Right hippocampus was not studied due to time constraints of the MR examination. 1H MRS was performed at 3T (Siemens) using an optimized sLASER protocol with AVP. Standardized uptake value ratios (SUVR) were calculated for global cortical and regional (PCC, LHC) PiB and AV‐1451. Associations between log transformed SUVRs and the concentration of MRS‐measured metabolites (µmol/g) were assessed using age‐adjusted Pearson correlations.ResultThe median (range) global PiB SUVR was 1.42 (1.20‐2.81) and AV‐1451 SUVR was 1.20 (0.94, 1.46). In the PCC, higher AV‐1451 SUVR was associated with lower N‐acetylaspartate (NAA) (r=‐0.375; p=0.019) and glutamate (r=‐0.354; p=0.027) concentrations. Higher global PIB SUVR was associated with higher myo‐inositol in the LHC (r=0.361; p=0.039).ConclusionLower levels of NAA, a marker of neuronal health, and the neurotransmitter glutamate are associated with local tau pathology in the PCC, suggesting early neuronal dysfunction in relation to tau accumulation. The association of hippocampal myo‐inositol, a putative glial marker, with the global cortical Aβ pathology suggests that myo‐inositol elevation may be an indicator of neuroinflammatory response to Aβ related pathology.

AbstractBackgroundWhite matter microstructure undergoes progressive changes during the life‐span but the neurobiological underpinnings related to aging and disease remains unclear. We used an advanced diffusion MRI, Neurite Orientation Dispersion and Density Imaging (NODDI), to investigate the microstructural alterations due to demographics, common age‐related pathological processes (amyloid, tau, and white matter hyperintensities (WMH)), and cognition. We also compared NODDI findings to the older Diffusion Tensor Imaging (DTI) model based findings.Method328 participants (264 cognitively unimpaired, 57 mild cognitive impairment (MCI), and 7 dementia with a mean age of 68.3 ±13.1 years) from the Mayo Clinic Study of Aging with multi‐shell diffusion imaging, FLAIR‐MRI as well as amyloid and tau PET scans were included in this study. White matter (WM) tract level diffusion measures (Figure 1) were calculated from DTI and NODDI. Pearson correlation and multiple linear regression analyses were performed with diffusion measures as the outcome and age, sex, education/occupation, WMH, amyloid, and tau as predictors. Analyses were also performed with each dMRI measure as a predictor of cognitive outcomes.ResultAge and WMH were the strongest predictors of all WM diffusion measures with low associations with amyloid and tau (Figure 1). However, neurite density decrease from NODDI was observed with amyloidosis specifically in the temporal lobes (Figure 2). WM integrity (mean diffusivity and free water) in the corpus callosum showed the greatest associations with cognitive measures (Table 1). All diffusion measures provided information about WM aging and WM disease processes and were associated with cognition.ConclusionNODDI and DTI are two different biophysical models that provide distinct information about variation in WM microstructural integrity. NODDI provides additional information about synaptic density, organization, and free water content which may aid in providing mechanistic insights into disease progression.

Background: It has been hypothesized that medial temporal sparing may be related to preserved posterior cingulate metabolism and the cingulate island sign (CIS) on [18F]fluorodeoxyglucose (FDG) PET in posterior cortical atrophy (PCA). Objective: To assess the severity of medial temporal atrophy in PCA and determine whether the presence of a CIS is related to medial temporal sparing. Methods: Fifty-five PCA patients underwent MRI and FDG-PET. The degree and symmetry of medial temporal atrophy on MRI was visually assessed using a five-point scale for both hemispheres. Visual assessments of FDG-PET coded the presence/absence of a CIS and whether the CIS was symmetric or asymmetric. Hippocampal volumes and a quantitative CIS were also measured. Results: Medial temporal atrophy was most commonly mild or moderate, was symmetric in 55% of patients, and when asymmetric was most commonly worse on the right (76%). Older age and worse memory performance were associated with greater medial temporal atrophy. The CIS was observed in 44% of the PCA patients and was asymmetric in 50% of these. The patients with a CIS showed greater medial temporal asymmetry, but did not show lower medial temporal atrophy scores, compared to those without a CIS. Hippocampal volumes were not associated with quantitative CIS. Conclusion: Mild medial temporal atrophy is a common finding in PCA and is associated with memory impairment. However, medial temporal sparing was not related to the presence of a CIS in PCA.

Abstract Introduction The aim of this study was to examine white matter hyperintensities (WMH) and fractional anisotropy (FA) in empirically derived incident mild cognitive impairment (MCI) subtypes. Methods We evaluated 188 participants with incident MCI in the Mayo Clinic Study of Aging (MCSA) identified as having one of four cluster‐derived subtypes: subtle cognitive impairment, amnestic, dysnomic, and dysexecutive. We used linear regression models to evaluate whole brain and regional WMH volumes. We examined fractional anisotropy (FA) on a subset of 63 participants with diffusion tensor imaging. Results Amnestic and dysexecutive subtypes had higher WMH volumes in differing patterns than cognitively unimpaired; the dysexecutive subtype had higher WMH than subtle cognitive impairment. There was widespread WM degeneration in long association and commissural fibers in the amnestic, dysnomic, and dysexecutive subtypes, and corpus callosum FA accounted for significant variability in global cognition. Discussion White matter changes likely contribute to cognitive symptoms in incident MCI.

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.

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.