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The identification of a neurodegenerative disorders distributed pattern of atrophy-or atrophy signature-can lend insights into the cortical networks that degenerate in individuals with specific constellations of symptoms. In addition, this signature can be used as a biomarker to support early diagnoses and to potentially reveal pathological changes associated with said disorder. Here, we characterized the cortical atrophy signature of behavioural variant frontotemporal dementia (bvFTD). We used a data-driven approach to estimate cortical thickness using surface-based analyses in two independent, sporadic bvFTD samples (n = 30 and n = 71, total n = 101), using age- and gender-matched cognitively and behaviourally normal individuals. We found highly similar patterns of cortical atrophy across the two independent samples, supporting the reliability of our bvFTD signature. Next, we investigated whether our bvFTD signature targets specific large-scale cortical networks, as is the case for other neurodegenerative disorders. We specifically asked whether the bvFTD signature topographically overlaps with the salience network, as previous reports have suggested. We hypothesized that because phenotypic presentations of bvFTD are diverse, this would not be the case, and that the signature would cross canonical network boundaries. Consistent with our hypothesis, the bvFTD signature spanned rostral portions of multiple networks, including the default mode, limbic, frontoparietal control and salience networks. We then tested whether the signature comprised multiple anatomical subtypes, which themselves overlapped with specific networks. To explore this, we performed a hierarchical clustering analysis. This yielded three clusters, only one of which extensively overlapped with a canonical network (the limbic network). Taken together, these findings argue against the hypothesis that the salience network is preferentially affected in bvFTD, but rather suggest that-at least in patients who meet diagnostic criteria for the full-blown syndrome-neurodegeneration in bvFTD encompasses a distributed set of prefrontal, insular and anterior temporal nodes of multiple large-scale brain networks, in keeping with the phenotypic diversity of this disorder.

IntroductionMagnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early-onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker.MethodsWe analyzed MRI scans to define the sporadic EOAD-signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early-onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment.ResultsThe EOAD-signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD-signature atrophy was associated with the severity of cognitive impairment.DiscussionThe EOAD-signature atrophy is a reliable and clinically valid biomarker of AD-related neurodegeneration that could be used in clinical trials for EOAD.HighlightsWe developed an early-onset Alzheimer's disease (EOAD)-signature of atrophy based on magnetic resonance imaging (MRI) scans. EOAD signature was robustly reproducible across two independent patient cohorts. EOAD signature included prominent atrophy in parietal and posterior temporal cortex. The EOAD-signature atrophy was associated with the severity of cognitive impairment. EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.

The article discusses the concept of "superagers," older adults who exhibit memory function comparable to younger adults. It highlights the variability in defining superagers based on age ranges, neuropsychological tests, and longitudinal measures. The study by Powell et al. in International Psychogeriatrics shows that the prevalence of superagers in a sample varies depending on specific criteria, with implications for functional impairment, neuroimaging features, and dementia incidence. The findings suggest that superagers may have lower dementia risk and resilience to Alzheimer's disease, but further research is needed to understand the trajectory of cognitive and brain aging in diverse populations and cultural contexts. [Extracted from the article]

Background: Early‐onset Alzheimer's disease (EOAD) manifests prior to the age of 65. Clinical presentation of EOAD is distinct from that of late‐onset Alzheimer's disease, and is characterized as having a more aggressive disease course with greater heterogeneity. Recent publications from the Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS) described their sample as predominantly amnestic, though this phenotypic description was based solely on clinical judgment. To better understand the range of EOAD presentation, we applied a neuropsychological data‐driven method to phenotypic subtyping within the LEADS cohort. Method: Data from 169 amyloid‐positive EOAD participants with composite data in all cognitive domains (Episodic Memory, Executive Functioning, Speed/Attention, Language, and Visuospatial) were analyzed. Our approach consisted of comparing the relative levels of baseline impairment in each cognitive domain. Education‐corrected normative comparisons were made using a sample of 98 aged‐matched cognitively normal participants. A cut‐off of 1 SD below all other composite domain scores was applied to indicate a phenotype of "predominant" impairment in a given cognitive domain. Individuals were otherwise considered to have a phenotype best characterized by multidomain impairment. Result: We identified 6 phenotypic subtypes of EOAD (Table 1): Dysexecutive‐predominant (22% of sample), Amnestic‐predominant (11%), Language‐predominant (11%), Visuospatial‐predominant (15%), Mixed Amnestic/Dysexecutive‐predominant (11%), and Multidomain (30%). These subtypes did not differ on age, age‐at‐symptom‐onset, sex, or overall clinical severity (p>0.05). Groups differed on global cognitive functioning (MMSE) such that the Amnestic‐predominant group performed better than other domain‐predominant subtypes of EOAD (p>0.05). In contrast to the heterogeneity observed from our data‐driven approach, diagnostic classifications for this same sample based solely on clinical judgment indicated that 82% of individuals were amnestic‐predominant, 9% were non‐amnestic, 4% were visuospatial‐predominant, and 5% were language‐predominant. Conclusion: Applying a neuropsychological data‐driven method of phenotyping EOAD individuals uncovered a more detailed understanding of the diversity of presenting heterogeneity in this atypical AD group compared to clinical judgment alone. These results suggest that clinicians and patients may over‐prioritize memory dysfunction during subjective reporting at the expense of non‐memory symptoms, which has important implications for diagnostic accuracy and treatment considerations. We plan to investigate the patterns of cortical atrophy and network dysfunction subserving this heterogeneity. [ABSTRACT FROM AUTHOR]

Background: "SuperAgers" (SA) are older adults who perform significantly better than their peers and comparable to young adults on objective memory measures. Longitudinal studies show that many do not maintain their SA status over time. The fluctuation in SA stability may reflect changes in executive functioning, hypothesized to contribute to variance of episodic memory scores in SA. In the present study we analyzed longitudinal neuropsychological performance of SAs in the Selective Aging After Elective Surgery (SAGES) study to examine SA stability. We hypothesized that losing SA status over time will reflect a decline in executive function. Methods: 17 SAs (criteria defined by Katsumi, Wong et al., 2022) (mean age 75.4, 12 females) identified in the SAGES Study were tested annually (up to 84 months). Neuropsychological data for baseline and follow‐up at years 1, 2, and 3 were analyzed. Performance of SAs who no longer met SA criteria after baseline (non‐stable SAs) were compared to that of SAs who maintained their status (stable SAs). A mixed factorial ANOVA was run with Trail Making Test B (TMTB) scores as the dependent variable to determine differences over time between stable and non‐stable SAs. Results: 7/17 non‐stable SAs were identified. Analyses revealed a significant group x timepoint interaction [F(3, 39) = 3.152, p < 0.05]. Assessment of the coefficient of variation calculated across time points revealed that non‐stable SAs showed greater variability in TMB performance (M = 0.21, SD = 0.059) than stable SAs (M = 0.15, SD = 0.064). A significant difference was found between stable SA and non‐stable SA for TMT‐B performance [F(1, 13) = 13.237, p < 0.01. Both groups were similar in age at baseline (p < 0.19). Conclusions: These findings suggest that current SA definitions need refinement as SA reflects more than superior memory. Ongoing analyses include 7‐year data from the current sample, replication of findings in an independent SA cohort, and examination of the neuroanatomical correlates of the observed differences between stable and non‐stable SAs. Enhancing our understanding of SAs will deepen our knowledge of resilience to decline in aging. [ABSTRACT FROM AUTHOR]