Graff‐Radford, Jonathan

AbstractBackgroundGiven that a proportion of mild cognitive impaired (MCI) individuals are amyloid negative and have cerebrovascular disease (CVD), there is a need for biomarkers that can complement AD biomarkers (amyloid and neurodegeneration) for the prediction of future cognitive decline in MCI. The aim of our study was to determine the utility of diffusion tensor imaging (DTI) as a CVD marker for prediction of future cognitive decline in individuals with MCI in conjunction with amyloidosis and neurodegeneration.MethodWe identified 132 MCI individuals ≥60 years old (55 % were amyloid positive and 59 % were male) from the population based sample of Mayo Clinic Study of Aging (MCSA) who had structural MRI, DTI, amyloid PET, and at least one clinical follow‐up after the imaging at the time of their clinical visit as MCI. All imaging scans were acquired and processed using in house developed protocols and pipelines. We used fractional anisotropy in the genu of corpus callosum (FAGCC), as a CVD marker, education/occupation score as a resilience variable, and global cognitive z‐score as the cognitive outcome. Using mixed effect models for cognitive decline, we evaluated three models to test the prognostic ability of (i) DTI marker alone, (ii) DTI marker and amyloid PET, (iii) DTI marker, amyloid PET, and neurodegeneration (cortical thickness). The final parsimonious models included the significant interactions of potential predictors with time, main effects nested within those interactions, and other significant main effects. Since the adjustment for conventional CVD measures like WMH was important to determine the utility DTI over traditional measures, we further assessed the value of FAGCC in conjunction with white matter hyper intensity (WMH).ResultWe found: i) FAGCC was associated with cognitive decline after adjusting for amyloid PET neurodegeneration (Figure 1 and Table 1) and ii) FAGCC was associated with cognitive decline even after controlling for WMH and WMH was no longer significant after accounting for FAGCC (Table 2).ConclusionDTI has significant utility for prediction of cognitive decline in MCI from population‐based samples and will provide complementary information to AD biomarkers.

AbstractBackgroundCharacterization of the changes that occur throughout the transition from asymptomatic to symptomatic for those with familial frontotemporal dementia is essential for planning future disease‐modifying trials.MethodWe identified four related microtubule associated protein tau (MAPT) N279K mutation carriers who have phenoconverted from the asymptomatic to the symptomatic state. Key features were as follows: Case 1 (female) initial exam age 36, onset age 44, current age 49; Case 2 (male) initial exam age 39, onset age 43, current age 48; Case 3 (female) initial exam age 41, onset age 47, current age 53; Case 4 (male) initial exam age 36, onset age 37, current age 46. MRI and neuropsychological data were analyzed.ResultStructural MRI was analyzed using Tensor Based Morphometry Symmetric Diffeomorphic Image Normalization (TBM‐SyN) methodology to quantify lobar volumes, which was then analyzed using a Mixed Effects Model to determine the annual change in lobar volumes. The phenoconverters had a greater estimated annual rate of cortical atrophy in temporal (p <0.001), frontal (p <0.01) and parietal (p <0.05) lobes compared to non‐carriers, with the rate of annual change in symptomatic individuals double that of asymptomatic individuals. Annual change in the parietal and occipital lobes was also analyzed and found to be similar to healthy controls of a similar age. Raw scores on neuropsychological measures were converted to z‐scores for analysis. Category fluency, letter fluency, and Trails A and B were all impaired (z‐score <‐1.5) following phenoconversion, but performance on these and other measures was variable across these four in the late asymptomatic state.ConclusionFor each of the four phenoconverters, structural MRI changes preceded symptom onset, whereas neuropsychological performance was more variable and occurred in closer proximity to the time of phenoconversion. Decrements in verbal fluency and cognitive flexibility were observed earlier than other cognitive domains. These findings suggest that changes in frontal and temporal volume on MRI precede symptom onset, with regional brain volumes most consistently tracking the evolution from the asymptomatic to symptomatic state in N279K MAPT mutation carriers. Supported by: AG063911, AG045390, NS092089, AG016976, AG016574, AG062677.

AbstractBackgroundThe LEFFTDS Consortium involves investigators at 8 centers in North America evaluating individuals in kindreds with mutations in microtubule associated protein tau (MAPT), progranulin (GRN), or chromosome 9 open reading frame 72 (C9orf72) genes using a standardized battery of measures. Participants are evaluated annually. We sought to determine possible correlations between FTLD disease progression and neuropsychiatric features.MethodThe Neuropsychiatric Inventory Questionnaire (NPI‐Q) scale is an informant‐based instrument that measures the presence and severity of 12 neuropsychiatric features in patients with dementia. The NPI‐Q was completed at each LEFFTDS visit. The individual NPI questions and total score were analyzed in those with CDR® Dementia Staging Instrument PLUS National Alzheimer Coordinating Center Frontotemporal Lobar Degeneration (CDR®+ NACC FTLD) ratings of 0 (i.e., clinically normal), 0.5 (i.e., questionably/minimally abnormal), 1, 2, and 3.ResultThe 472 participants enrolled to date with a baseline (Visit 1) assessment have the following characteristics: 261 (55.5%) female, mean age 48 (range 18‐80) years, mean education 16 (range 11‐22) years, and 275 participants with a CDR®+NACC FTLD=0 (58%) and known genetic status. Participants with a CDR®+NACC FTLD=0 plus a genetic mutation were compared to those without a mutation and found to have increased severity of apathy (mean score of 0.116 versus 0.035, p=0.0302). Regardless of the specific mutation, those with a CDR®+NACC FTLD=0.5 were reported to have increased severity of apathy, disinhibition, and irritability. For most domains, mean NPI‐Q severity scores increase between groups up to CDR®+NACC FTLD=2. Depression increases in severity up to CDR®+NACC FTLD=1, whereas apathy severity continues to increase with increasing disease severity through CDR®+NACC FTLD=3. Twenty participants converted from CDR®+NACC FTLD 0 to >0 between their baseline and most recent visit; apathy severity almost tripled in these participants. For those that converted, disinhibition, irritability, and NPI total score were different between baseline and most recent visit (Wilcoxon signed rank test, p<0.05).ConclusionKey neuropsychiatric features measured by the NPI‐Q demonstrate differences in apathy severity between clinically normal mutation vs non‐mutation carriers. Key domains differ at different levels of FTLD severity and show dynamic changes with increasing level of FTLD severity. Supported by AG063911, AG045390, NS092089, AG016976.

AbstractBackgroundIt is important to determine the natural history of sporadic and familial frontotemporal lobar degeneration (FTLD) and generate clinical, neuropsychological, neuroimaging and biofluid data for planning disease‐modifying trials.MethodAs part of the ARTFL LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD; U19 AG063911) protocol, investigators at 19 centers in North America will enroll 2100 participants with FTLD over the next 5 years beginning in early 2020.ResultAs of 1/20/20, the ARTFL/LEFFTDS (A/L) Consortium had enrolled 1832 participants, including 850 in kindreds with familial FTLD (239 associated with mutations in MAPT, 192 in GRN, 370 in C9orf72, 4 with mutations in both GRN and C9orf72, and 45 with a mutation in a different gene or no mutation in any known FTLD‐associated gene). Over 500 participants have undergone 2 or more annual visits to date. MRI has been performed in 1105. Biofluid samples have also been collected, with blood (DNA, plasma, serum, mRNA, PBMC) in 1413 and CSF in 303. Over 60 manuscripts using A/L data or samples have been published to date. Five clinical trials involving A/L and ALLFTD participants are in progress or planned. The longitudinal arm in ALLFTD will enroll 500 of existing A/L and 600 future participants for annual assessments with similar methodology to A/L. An additional 1000 FTLD patients will undergo focused one‐time clinical evaluations and biofluid collection.ConclusionThe data/samples from already‐enrolled and planned participants in ALLFTD and findings published to date underscore the utility of evaluating FTLD subjects. The absence of identifiable mutations in some with familial FTLD suggests that other genes are yet to be discovered. ALLFTD data will inform clinical trial design, and many participants will be eligible for future trials. The key data and samples in ALLFTD are available to interested investigators worldwide. Supported by: AG063911, AG045390, NS092089, AG016976, AG21886.

AbstractBackgroundWe report a group of individuals presenting with a progressive dementia syndrome characterized by predominant dysfunction in core executive functions and positive biomarkers for Alzheimer’s pathophysiology.MethodIn this retrospective review, we report on 55 participants with a clinically defined progressive dysexecutive syndrome with 18F‐fluorodeoxyglucose‐positron emission tomography (FDG) and AD biomarker positivity. A subset of these individuals enrolled in our ADRC were compared to other phenotypic variants of AD.ResultSixty‐two percent were female with a mean of 15.2 years of education. Mean age of symptom onset was 53.8 while mean age at diagnosis was 57.2 years. Multi‐domain cognitive impairment was evident in neuropsychological testing with executive dysfunction most consistently and severely affected. The frontal and/or parietal regions demonstrate clear hypometabolism on positron emission tomography in all cases. Genetic testing for autosomal dominant genes was negative in all 8 participants tested and at least one APOE ε4 allele was present in 14/26. EEG was abnormal in 14/17 cases. CSF and neuroimaging biomarkers (PIB‐PET and Tau‐PET) were consistent with Alzheimer’s disease pathophysiology, although CSF p‐tau was normal in 24% of cases. In two participants that came to autopsy, the hippocampus was relatively spared compared to frontal and parietal cortex. Participants presenting with a progressive dysexecutive syndrome and evidence of AD pathology are labeled dAD. Comparing FDG in dAD relative to other AD phenotypes revealed unique areas of relatively greater hypometabolism in parieto‐frontal cortex and relative sparing of medial temporal (vs typical AD), visual (vs PCA), and left temporal (vs lvPPA) (Figure 1). Controlling for age did not alter patterns of regional differences. This demonstrates regional variability related to clinical phenotype not accountable by variation in age, duration, stage, or severity (Figure 2).ConclusionA progressive dysexecutive syndrome should be recognized as a distinct clinical phenotype. This clinical presentation can be due to Alzheimer’s disease but is not specific for any single etiology (non‐AD cases of progressive dysexecutive syndrome will be discussed). Prominent impairment of executive task performance, young‐age of onset, normal CSF p‐tau, and relative preservation of the hippocampus were commonly encountered in this case series of dAD.

AbstractBackgroundWhite matter changes and Alzheimer’s disease pathology frequently co‐exist in the population. Recently we empirically derived subtypes of incident mild cognitive impairment (MCI) and found that there was significant heterogeneity not only in cognitive impairment profiles but also gray matter atrophy suggesting that multiple etiologies may contribute to cognitive impairment in these subtypes. The aim of this study was to examine differences in white matter hyperintensity (WMH) volume in these same MCI subtypes and investigate amyloid deposition in a smaller subset.MethodWe analyzed data from 188 participants with incident MCI enrolled in the population‐based Mayo Clinic Study of Aging (MCSA) identified as having one of four MCI subtypes: subtle cognitive impairment (SCI), amnestic, dysnomic, and dysexecutive. All participants completed 3T imaging at the time of the MCI diagnosis. Using WMH volume scaled by TIV and PIB SUVR, we compared each MCI subtype to 344 cognitively impaired (CU) participants (mean age 78; 46% women) and each other.ResultThe amnestic (n = 83; mean age 80; 43% women), dysnomic (n = 30; mean age 84; 47% women) and dysexecutive subtypes (n = 49; mean age 83; 35% women) had significantly higher WMH volumes compared to CU (p < .02) while the SCI subtype (n = 26; mean age 80; 23% women) did not differ from CU (p = .76). Amongst the MCI subtypes, the amnestic (p = .04) and dysexecutive subtypes (p = .01) had significantly higher WMH volumes than the SCI subtype [Figure 1]. In a smaller subset of individuals who also completed PiB‐PET (17/26 SCI; 39/83 amnestic; 10/30 dysnomic, 28/49 dysexecutive), we found evidence for higher amyloid load in all MCI subgroups except the SCI group (p<0.05) in comparison to CU.ConclusionWe found significantly elevated levels of WMH and amyloid burden in amnestic, dysnomic, and dysexecutive subtypes of incident MCI supporting the notion that both vascular changes and amyloid contribute to the development of clinical symptoms. Surprisingly, WMH and amyloid positivity were not high in SCI suggesting that the pathophysiology in this group needs further investigation.

AbstractBackgroundDementia with Lewy bodies (DLB) is neuropathologically defined by the presence of α‐synuclein aggregations, but many DLB cases show significant Alzheimer’s disease (AD) pathology in the form of β‐amyloid and tau. Our first objective was to investigate the effect of AD co‐pathology on functional network failure in DLB. Secondly, we studied how the distribution of tau relates to functional connectivity in DLB.MethodTwenty‐three DLB, 23 age‐ and sex‐matched AD, and 90 cognitively unimpaired (CU) participants underwent AV1451 tau‐PET, Pittsburgh compound‐B (PiB) PET, and resting state (rs)‐fMRI scans. The rs‐fMRI data were used to calculate the Network Failure Quotient (NFQ), a marker of functional network failure within the default mode network. The NFQ was then correlated with overall cortical tau standardized uptake value ratio (SUVr). The strength of inter‐regional functional connectivity was assessed using the Schaefer100 atlas. Tau‐PET covariance was measured as the correlation in AV1451 SUVr between any two regions across participants. The association between region‐to‐region functional connectivity and tau‐PET covariance was assessed using linear regression. Additionally, we identified the region with highest and the region with lowest tau SUVrs (tau hot‐ and coldspot) and tested whether tau SUVr in all other brain regions was associated with the strength of functional connectivity to these tau hot‐ and coldspots.ResultOverall higher cortical tau‐PET uptake correlated with higher NFQ (i.e. greater functional network failure) in DLB who were PiB+ (N=14, ρ=0.60, p=0.02), but not in DLB who were PiB‐ (N=9, ρ=‐0.06, p=0.87). Higher functional connectivity between regions was associated with higher tau covariance in CU, AD, and DLB, independent of PiB status. Higher functional connectivity of a target region to the tau hotspot (i.e. inferior/medial temporal cortex) was related to higher AV1451 SUVRs in the target region whereas higher functional connectivity to the tau coldspot (i.e. sensory‐motor cortex) was related to lower AV1451 SUVr in the target region.ConclusionGreater tau burden in DLB patients with β‐amyloid co‐pathology is associated with an AD‐like functional network failure. As previously demonstrated within the AD spectrum, functional connectivity may contribute to the spreading of tau across the brain also in DLB.

ObjectiveThe objective of this study was to describe clinical features, [18F]‐fluorodeoxyglucose (FDG)‐positron emission tomography (PET) metabolism and digital pathology in patients with logopenic progressive aphasia (LPA) and pathologic diagnosis of diffuse Lewy body disease (DLBD) and compare to patients with LPA with other pathologies, as well as patients with classical features of probable dementia with Lewy bodies (pDLB).MethodsThis is a clinicopathologic case‐control study of 45 patients, including 20 prospectively recruited patients with LPA among whom 6 were diagnosed with LPA‐DLBD. We analyzed clinical features and compared FDG‐PET metabolism in LPA‐DLBD to an independent group of patients with clinical pDLB and regional α‐synuclein burden on digital pathology to a second independent group of autopsied patients with DLBD pathology and antemortem pDLB (DLB‐DLBD).ResultsAll patients with LPA‐DLBD were men. Neurological, speech, and neuropsychological characteristics were similar across LPA‐DLBD, LPA‐Alzheimer's disease (LPA‐AD), and LPA‐frontotemporal lobar degeneration (LPA‐FTLD). Genetic screening of AD, DLBD, and FTLD linked genes were negative with the exception of APOE ε4 allele present in 83% of LPA‐DLBD patients. Seventy‐five percent of the patients with LPA‐DLBD showed a parietal‐dominant pattern of hy pometabolism; LPA‐FTLD – temporal‐dominant pattern, whereas LPA‐AD showed heterogeneous patterns of hypometabolism. LPA‐DLBD had more asymmetrical hypometabolism affecting frontal lobes, with relatively spared occipital lobe in the nondominantly affected hemisphere, compared to pDLB. LPA‐DLBD had minimal atrophy on gross brain examination, higher cortical Lewy body counts, and higher α‐synuclein burden in the middle frontal and inferior parietal cortices compared to DLB‐DLBD.InterpretationWhereas AD is the most frequent underlying pathology of LPA, DLBD can also be present and may contribute to the LPA phenotype possibly due to α‐synuclein‐associated functional impairment of the dominant parietal lobe. ANN NEUROL 2021;89:520–533

Background: An artificial intelligence (AI) algorithm applied to electrocardiography during sinus rhythm has recently been shown to detect concurrent episodic atrial fibrillation (AF). We sought to characterize the value of AI–enabled electrocardiography (AI-ECG) as a predictor of future AF and assess its performance compared with the CHARGE-AF score (Cohorts for Aging and Research in Genomic Epidemiology–AF) in a population-based sample. Methods: We calculated the probability of AF using AI-ECG, among participants in the population-based Mayo Clinic Study of Aging who had no history of AF at the time of the baseline study visit. Cox proportional hazards models were fit to assess the independent prognostic value and interaction between AI-ECG AF model output and CHARGE-AF score. C statistics were calculated for AI-ECG AF model output, CHARGE-AF score, and combined AI-ECG and CHARGE-AF score. Results: A total of 1936 participants with median age 75.8 (interquartile range, 70.4–81.8) years and median CHARGE-AF score 14.0 (IQR, 13.2–14.7) were included in the analysis. Participants with AI-ECG AF model output of >0.5 at the baseline visit had cumulative incidence of AF 21.5% at 2 years and 52.2% at 10 years. When included in the same model, both AI-ECG AF model output (hazard ratio, 1.76 per SD after logit transformation [95% CI, 1.51–2.04]) and CHARGE-AF score (hazard ratio, 1.90 per SD [95% CI, 1.58–2.28]) independently predicted future AF without significant interaction ( P =0.54). C statistics were 0.69 (95% CI, 0.66–0.72) for AI-ECG AF model output, 0.69 (95% CI, 0.66–0.71) for CHARGE-AF, and 0.72 (95% CI, 0.69–0.75) for combined AI-ECG and CHARGE-AF score. Conclusions: In the present study, both the AI-ECG AF model output and CHARGE-AF score independently predicted incident AF. The AI-ECG may offer a means to assess risk with a single test and without requiring manual or automated clinical data abstraction.

Background: Posterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA) are two of the most common variants of atypical Alzheimer’s disease (AD). Both PCA and LPA are associated with relative sparing of hippocampus compared to neocortex, although hippocampal atrophy is observed. It is unclear whether regional patterns of hippocampal subfield involvement differ between PCA and LPA, and whether they differ from typical AD. Objective: To assess volume of specific subfields of the hippocampus in PCA, LPA, and typical AD. Methods: Fifty-nine patients with PCA and 77 patients with LPA were recruited and underwent T1-weighted MRI and Pittsburgh Compound B (PiB) PET at Mayo Clinic. Thirty-six probable AD patients and 100 controls were identified from the Alzheimer’s Disease Neuroimaging Initiative. Hippocampal subfield volumes were calculated using Freesurfer, and volumes were compared between PCA, LPA, AD, and controls using Kruskal-Wallis and Dunn tests. Results: The LPA and PCA groups both showed the most striking abnormalities in CA4, presubiculum, molecular layer of the hippocampus, molecular and granule cell layers of the dentate gyrus, and the hippocampal-amygdala transition area, although atrophy was left-sided in LPA. PCA showed smaller volume of right presubiculum compared to LPA, with trends for smaller volumes of right parasubiculum and fimbria. LPA showed a trend for smaller volumes of left CA1 compared to PCA. The AD group showed smaller volumes of the right subiculum, CA1, and presubiculum compared to LPA. Conclusion: Patterns of hippocampal subfield atrophy differ across the different syndromic variants of AD.