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AbstractBackgroundWhite matter signal abnormalities (WMSA) are frequently observed on magnetic resonance imaging (MRI) scans of people with frontotemporal dementia (FTD). We hypothesized that carriers of mutations in progranulin (GRN+), chromosome 9 open reading frame 72 (C9orf72+) and microtubule associated protein tau (MAPT+) have increased rates of progression of WMSA compared to non‐carrier individuals prior to onset of dementia, and that different mutations may have different rates of WMSA accumulation.MethodParticipants were recruited through the ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) Study. We selected participants with Clinical Dementia Rating scale (CDR) scores of 0 and 0.5. If a participant developed FTD during the follow‐up, we only analyzed observations collected before the conversion. WMSA were defined as hyperintensities on FLAIR MRI. Total WMSA volumes were normalized to the respective intracranial volumes. We used a linear mixed effects model, with random intercepts and slopes, to compare the baseline burden and the longitudinal progression of total WMSA volumes between mutation carriers and controls. The model was adjusted for baseline age, sex, education, baseline Montreal Cognitive Assessment (MoCA) scores, and MRI acquisition sites.ResultWe analyzed MRI data from 199 participants who had at least two MRI visits (46 C9orf72+, 17 GRN+, 35 MAPT+, 101 non‐carrier controls; up to five years of follow‐up). We did not find significant group differences in baseline demographic features, except that MAPT+ was younger than non‐carrier controls (average age: C9orf72+=47, GRN+=56, MAPT+=40, controls=47). Baseline WMSA volumes were not significantly different between mutation carriers and controls. Longitudinally, the rates of WMSA volume increase in C9orf72+ and MAPT+ were comparable to controls; whereas, GRN+ had higher rates of WMSA volume increases compared to controls (p=0.01).ConclusionWMSA may accumulate at higher rates in GRN+ prior to the onset of FTD, which is consistent with the frequent presence of white matter diseases observed in symptomatic FTD patients with GRN mutations. Future work is warranted to investigate the association between white matter structural changes and cognitive/psychiatric changes in FTD mutation carriers.

AbstractBackgroundFluorodeoxyglucose positron emission tomography (FDG‐PET) is an established modality for differential diagnosis of dementia. Deriving phenotypic signatures from FDG‐PET via machine learning is challenging due to the high dimensional nature of brain images relative to the generally small number of labeled examples available for training, the class imbalance among those labels, and the cooccurrence of multiple pathologies. In this study, we developed a multi‐class, multi‐label framework to address these challenges.MethodA database of clinically acquired PET/CT images from 3,000 unique patients was used to develop a latent space model using matrix decomposition. This model was then applied to images from a separate cohort of Mayo Clinic Alzheimer’s Disease Research Center participants (n=1,745) labeled as cognitively unimpaired (CU) (n=1,436) or with the following potentially co‐occurring phenotypes: Alzheimer’s disease (AD) (n=165), Lewy body dementia (DLB) (n=92), behavioral variant frontotemporal dementia (bvFTD) (n=43), semantic (svPPA) (n=10) and logopenic (lvPPA) (n=13) variant PPA, and posterior cortical atrophy (PCA) (n=17). A k‐nearest neighbors classifier that is robust to these imbalanced and overlapping labels was then trained on these examples. The resulting classifier was evaluated by area under receiver‐operator characteristic curve (ROC‐AUC) via leave one out cross validation, using clinical diagnosis as the gold standard.ResultROC curves and AUC scores for each phenotype are illustrated in Fig. 1a. Because the classifier is based on a k‐nearest neighbors connectivity matrix, it has a convenient graphical representation, where images are nodes and edges are drawn between an image and its set of nearest neighbors in latent space. A self‐organizing force directed graph constructed in this way is illustrated in Fig 1b, highlighting the strong separation of CU and degenerative images, as well as the segregation of each phenotype within the neurodegenerative region of the graph.ConclusionIn this study, we developed a machine learning framework for classification of neurodegenerative disease based on k‐nearest neighbor analysis in a low dimensional latent space projection of FDG‐PET images. By leveraging low‐dimensional representations and k‐nearest neighbors analysis, this framework is robust in multi‐class, multi‐label tasks with strong class imbalance and provides a highly interpretable graphical representation.

AbstractIntroductionAlzheimer's disease (AD) patients ≥70 years show smaller medial temporal volumes despite less 18F‐flortaucipir‐positron emission tomography (PET) uptake than younger counterparts. We investigated whether TAR DNA‐binding protein 43 (TDP‐43) was contributing to this volume‐uptake mismatch.MethodsSeventy‐seven participants with flortaucipir‐PET and volumetric magnetic resonance imaging underwent postmortem AD and TDP‐43 pathology assessments. Bivariate‐response linear regression estimated the effect of age and TDP‐43 pathology on volume and/or flortaucipir standardized uptake volume ratios of the hippocampus, amygdala, entorhinal, inferior temporal, and midfrontal cortices.ResultsOlder participants had lower hippocampal volumes and overall flortaucipir uptake. TDP‐43‐immunoreactivity correlated with reduced medial temporal volumes but was unrelated to flortaucipir uptake. TDP‐43 effect size was consistent across the age spectrum. However, at older ages, the cohort mean volumes moved toward those of TDP‐43‐positives, reflecting the increasing TDP‐43 pathology frequency with age.DiscussionTDP‐43 pathology is a relevant contributor driving the volume‐uptake mismatch in older AD participants.Highlights TDP‐43 pathology affects medial temporal volume loss but not tau radiotracer uptake. Greater TDP‐43 pathology effect is seen in old age due to its increasing frequency. TDP‐43 pathology is a relevant driver of the volume‐uptake mismatch in old AD patients.

ImportancePhysical activity is associated with cognitive health, even in autosomal dominant forms of dementia. Higher physical activity is associated with slowed cognitive and functional declines over time in adults carrying autosomal dominant variants for frontotemporal lobar degeneration (FTLD), but whether axonal degeneration is a potential neuroprotective target of physical activity in individuals with FTLD is unknown.ObjectiveTo examine the association between physical activity and longitudinal neurofilament light chain (NfL) trajectories in individuals with autosomal dominant forms of FTLD.Design, Setting, and ParticipantsThis cohort study included individuals from the ALLFTD Consortium, which recruited patients from sites in the US and Canada. Symptomatic and asymptomatic adults with pathogenic variants in one of 3 common genes associated with FTLD (GRN, C9orf72, or MAPT) who reported baseline physical activity levels and completed annual blood draws were assessed annually for up to 4 years. Genotype, clinical measures, and blood draws were collected between December 2014 and June 2019; data were analyzed from August 2021 to January 2022. Associations between reported baseline physical activity and longitudinal plasma NfL changes were assessed using generalized linear mixed-effects models adjusting for baseline age, sex, education, functional severity, and motor symptoms.ExposuresBaseline physical activity levels reported via the Physical Activity Scale for the Elderly. To estimate effect sizes, marginal means were calculated at 3 levels of physical activity: 1 SD above the mean represented high physical activity, 0 SD represented average physical activity, and 1 SD below the mean represented low physical activity.Main Outcomes and MeasuresAnnual plasma NfL concentrations were measured with single-molecule array technology.ResultsOf 160 included FTLD variant carriers, 84 (52.5%) were female, and the mean (SD) age was 50.7 (14.7) years. A total of 51 (31.8%) were symptomatic, and 77 carried the C9orf72 variant; 39, GRN variant; and 44, MAPT variant. Higher baseline physical activity was associated with slower NfL trajectories over time. On average, NfL increased 45.8% (95% CI, 22.5 to 73.7) over 4 years in variant carriers. Variant carriers with high physical activity demonstrated 14.0% (95% CI, −22.7 to −4.3) slower NfL increases compared with those with average physical activity and 30% (95% CI, −52.2 to −8.8) slower NfL increases compared with those with low physical activity. Within genotype, C9orf72 and MAPT carriers with high physical activity evidenced 18% to 21% (95% CI, −43.4 to −7.2) attenuation in NfL, while the association between physical activity and NfL trajectory was not statistically significant in GRN carriers. Activities associated with higher cardiorespiratory and cognitive demands (sports, housework, and yardwork) were most strongly correlated with slower NfL trajectories (vs walking and strength training).Conclusions and RelevanceIn this study, higher reported physical activity was associated with slower progression of an axonal degeneration marker in individuals with autosomal dominant FTLD. Physical activity may serve as a primary prevention target in FTLD.

Abstract Study Objectives Isolated REM sleep behavior disorder (iRBD) carries a high lifetime risk for phenoconversion to a defined neurodegenerative disease (NDD) including Parkinson disease, dementia with Lewy bodies, and multiple system atrophy. We aimed to examine iRBD patient values and preferences regarding prognostic counseling. Methods One hundred thirteen iRBD patient participants enrolled in the Mayo Clinic iRBD Patient Registry were sent an email survey concerning their values and preferences concerning NDD prognostic counseling and their experiences following diagnosis with iRBD. Results Of 81 respondents (71.7% response rate), the majority were men (74.0%) with an average age of 65.7 (±9.7) years. Responses indicated a strong preference toward receiving prognostic information about possible future NDD development. 92.5% of respondents felt knowledge concerning personal NDD risk was important, while 87.6% indicated prognostic discussions were important to maintaining trust in their physician. 95.7% indicated a desire for more information, while only 4.3% desired less information regarding their NDD prognostic risk. Most respondents strongly agreed that prognostic information was important to discuss with their family and friends and inform future life planning, and most expressed interest in learning more about future neuroprotective therapies and symptomatic treatments for parkinsonism and dementia. Conclusions Most iRBD patients indicated strong preferences for disclosure of NDD prognostic risk and indicated that prognostic information was important for family discussions and future life planning. Future broader surveys and qualitative studies of clinic-based and ultimately community dwelling iRBD patients’ values and preferences are needed to guide appropriately tailored and individualized prognostic counseling approaches following iRBD diagnosis.

AbstractBackgroundGlobular glial tauopathy (GGT) has been associated with frontotemporal dementia syndromes; little is known about the clinical and imaging characteristics of GGT and how they differ from other non‐globular glial 4‐repeat tauopathies (N4GT) such as progressive supranuclear palsy (PSP) or corticobasal degeneration (CBD).MethodsFor this case–control study the Mayo Clinic brain banks were queried for all cases with an autopsy‐confirmed diagnosis of GGT between 1 January 2011 and 31 October 2021. Fifty patients with N4GT (30 PSP, 20 CBD) were prospectively recruited and followed by the Neurodegenerative Research Group at Mayo Clinic, Minnesota. Magnetic resonance imaging was used to characterize patterns of gray/white matter atrophy, MR‐parkinsonism index, midbrain volume, and white matter hyperintensities.18F‐Fluorodeoxyglucose‐, 11C Pittsburg compound‐, and 18F‐flortaucipir‐positron emission tomography scans were reviewed.ResultsTwelve patients with GGT were identified: 83% were women compared to 42% in NG4T (p = 0.02) with median age at death 76.5 years (range: 55–87). The most frequent clinical features were eye movement abnormalities, parkinsonism, behavioral changes followed by pyramidal tract signs and motor speech abnormalities. Lower motor neuron involvement was present in 17% and distinguished GGT from NG4T (p = 0.035). Primary progressive apraxia of speech was the most frequent initial diagnosis (25%); 50% had a Parkinson‐plus syndrome before death. Most GGT patients had asymmetric frontotemporal atrophy with matching hypometabolism. GGT patients had more gray matter atrophy in temporal lobes, normal MR‐parkinsonism index, and larger midbrain volumes.ConclusionsFemale sex, lower motor neuron involvement in the context of a frontotemporal dementia syndrome, and asymmetric brain atrophy with preserved midbrain might be suggestive of underlying GGT.

Abstract Dementia with Lewy bodies (DLB) is clinically defined by the presence of visual hallucinations, fluctuations, rapid eye movement (REM) sleep behavioral disorder, and parkinsonism. Neuropathologically, it is characterized by the presence of Lewy pathology. However, neuropathological studies have demonstrated the high prevalence of coexistent Alzheimer's disease, TAR DNA‐binding protein 43 (TDP‐43), and cerebrovascular pathologic cases. Due to their high prevalence and clinical impact on DLB individuals, clinical trials should account for these co‐pathologies in their design and selection and the interpretation of biomarkers values and outcomes. Here we discuss the frequency of the different co‐pathologies in DLB and their cross‐sectional and longitudinal clinical impact. We then evaluate the utility and possible applications of disease‐specific and disease‐nonspecific biomarkers and how co‐pathologies can impact these biomarkers. We propose a framework for integrating multi‐modal biomarker fingerprints and step‐wise selection and assessment of DLB individuals for clinical trials, monitoring target engagement, and interpreting outcomes in the setting of co‐pathologies.

Background: Dementia, vascular disease, and cancer increase with age, enabling complex comorbid interactions. Understanding vascular and cancer contributions to dementia risk and neuropathology in oldest-old may improve risk modification and outcomes. Objective: Investigate the contributions of vascular factors and cancer to dementia and neuropathology. Methods: Longitudinal clinicopathologic study of prospectively followed Mayo Clinic participants dying≥95 years-old who underwent autopsy. Participants were stratified by dementia status and compared according to demographics, vascular risk factors, cancer, and neuropathology. Results: Participants (n = 161; 83% female; 99% non-Hispanic whites)≥95 years (95–106 years-old) with/without dementia did not differ based on demographics. APOE ɛ2 frequency was higher in no dementia (20/72 [28%]) versus dementia (11/88 [12%]; p = 0.03), but APOE ɛ4 frequency did not differ. Coronary artery disease was more frequent in no dementia (31/72 [43%]) versus dementia (23/89 [26%]; p = 0.03) associated with 56% lower dementia odds (odds ratio [OR] = 0.44 [confidence interval (CI) = 0.19–0.98]; p = 0.04) and fewer neuritic/diffuse plaques. Diabetes had an 8-fold increase in dementia odds (OR = 8.42 [CI = 1.39–163]; p = 0.02). Diabetes associated with higher cerebrovascular disease (Dickson score; p = 0.05). Cancer associated with 63% lower dementia odds (OR = 0.37 [CI = 0.17–0.78]; p < 0.01) and lower Braak stage (p = 0.01). Conclusion: Cancer exposure in the oldest-old was associated with lower odds of dementia and tangle pathology, whereas history of coronary artery disease was associated with lower odds of dementia and amyloid-β plaque pathology. History of diabetes mellitus was associated with increased odds of dementia and cerebrovascular disease pathology. Cancer-related mechanisms and vascular risk factor reduction strategies may alter dementia risk and neuropathology in oldest-old.

Abstract Background. Dementia with Lewy bodies (DLB) is a neurodegenerative disorder with a wide heterogeneity of symptoms, which suggests the existence of different subtypes. Objectives. We used data-driven analysis of MRI data to investigate DLB subtypes. Methods. We included 165 probable DLB from the Mayo Clinic and 3 centers from the European DLB consortium and performed a hierarchical cluster analysis to identify subtypes based on gray matter (GM) volumes. To characterize the subtypes, we used demographic and clinical data, as well as β-amyloid and cerebrovascular biomarkers at baseline, and cognitive decline over three years. Results. We identified 3 subtypes: an older subtype with reduced cortical GM volumes, worse cognition, and faster cognitive decline (n=49, 30%); a subtype with low GM volumes in fronto-occipital regions (n=76, 46%); and a subtype of younger patients with the highest cortical GM volumes, proportionally lower GM volumes in basal ganglia and the highest frequency of cognitive fluctuations (n=40, 24%). Conclusions. This study shows the existence of MRI subtypes in DLB, which may have implications for clinical workout, research, and therapeutic decisions.