ObjectivesThe Northwestern University SuperAging Program studies a rare cohort of individuals over age 80 with episodic memory ability at least as good as middle-age adults to determine what factors contribute to their elite memory performance. As psychological well-being is positively correlated with cognitive performance in older adults, the present study examined whether aspects of psychological well-being distinguish cognitive SuperAgers from their cognitively average-for-age, same-age peers.MethodThirty-one SuperAgers and 19 cognitively average-for-age peers completed the Ryff 42-item Psychological Well-Being questionnaire, comprised of 6 subscales: Autonomy, Positive Relations with Others, Environmental Mastery, Personal Growth, Purpose in Life, and Self-Acceptance.ResultsThe groups did not differ on demographic factors, including estimated premorbid intelligence. Consistent with inclusion criteria, SuperAgers had better episodic memory scores. Compared to cognitively average-for-age peers, SuperAgers endorsed greater levels of Positive Relations with Others. The groups did not differ on other PWB-42 subscales.DiscussionWhile SuperAgers and their cognitively average-for-age peers reported similarly high levels of psychological well-being across multiple dimensions, SuperAgers endorsed greater levels of positive social relationships. This psychological feature could conceivably have a biological relationship to the greater thickness of the anterior cingulate gyrus and higher density of von Economo neurons previously reported in SuperAgers.

Introduction: SuperAgers are adults age 80+ with episodic memory performance that is at least as good as that of average middle-aged adults. Understanding the biological determinants of SuperAging may have relevance to preventing age-related cognitive decline and dementia. This study aimed to identify associations between genetic variations and the SuperAging phenotype using Whole Exome Sequencing (WES).Methods: Sequence Kernel Association Combined (SKAT-C) test was conducted at the gene level including both rare and common variants in 56 SuperAgers and 22 cognitively-average controls from the Alzheimer’s disease Neuroimaging Initiative (ADNI).Results: The SuperAging phenotype was associated with variants in the Mitogen-Activated Protein Kinase Kinase 3 (MAP2K3) gene. Three single nucleotide polymorphisms (SNPs) contributed to the significance (rs2363221 [intron 1], rs2230435 [exon 5], rs736103 [intron 7]).Conclusions: MAP2K3 resides in a biological pathway linked to memory. It is in a signaling cascade associated with beta-amyloid mediated apoptosis and has enriched expression in microglia. This preliminary work suggests MAP2K3 may represent a novel therapeutic target for age-related memory decline and perhaps Alzheimer’s disease (AD).

Despite the important role of written language in everyday life, abnormalities in functional written communication have been sparsely investigated in Primary Progressive Aphasia (PPA). Prior studies have analyzed written language separately in the three variants of PPA - nonfluent (nfvPPA), logopenic (lvPPA), and semantic (svPPA) - but have rarely compared them to each other or to spoken language. Manual analysis of written language can be a time-consuming process. We developed a program which uses a language parser and quantifies content units (CU) and total units (U) in written language samples. The program was used to analyze written and spoken descriptions of the WAB Picnic scene, based on a pre-defined CU corpus. We then calculated the ratio of CU to U (CU/U Ratio) as a measure of content density. Our cohort included 115 participants (20 control participants for written, 20 control participants for spoken, 28 participants with nfvPPA, 30 with lvPPA, and 17 with svPPA). We compared written language between patients with PPA and control participants and written to spoken language in patients with the three variants of PPA. Finally, we analyzed CU and U in relation to the Progressive Aphasia Severity Scale Sum of Boxes and the Clinical Dementia Rating Sum of Boxes. Our program identified CU with a validity of 99.7% (95%CI 99.5 to 99.8) compared to manual annotation of the samples. All patients with PPA wrote fewer total units than controls (p<0.001). Patients with lvPPA (p=0.013) and svPPA (0.004) wrote fewer CU than controls. The CU/U Ratio was higher in nfvPPA and svPPA than controls (p=0.019 in both cases), but no different between lvPPA patients and controls (p=0.962). Participants with lvPPA (p<0.001) and svPPA (p=0.04) produced fewer CU in written samples compared to spoken. A two-way ANOVA showed all groups produced fewer units in written samples compared to spoken (p<0.001). However, the decrease in written CU compared to spoken was smaller than the decrease in written units compared to spoken in participants with PPA, resulting in a larger written CU/U Ratio when compared to spoken language (p<0.001). nfvPPA patients produced correlated written and spoken CU (R=0.5, p=0.009) and total units (R=0.64, p<0.001), but this was not the case for lvPPA or svPPA. Considering all PPA patients, fewer CU were produced in those with greater aphasia severity (PASS SoB, R=-0.24, p=0.04) and dementia severity (CDR SoB, R=-0.34, p=0.004). In conclusion, we observed reduced written content in patients with PPA compared to controls, with a preference for content over non-content units in patients with nfvPPA and svPPA. When comparing written to spoken language, we observed a similar "telegraphic" style in both modalities in patients with nfvPPA, which was different from patients with svPPA and lvPPA, who use significantly less non-content units in writing than in speech. Lastly, we show how our program provides a time-efficient tool, which could enable feedback and tracking of writing as an important feature of language and cognition.

Introduction: While cognitive assessment by videoconference has become possible over the past decade, the COVID-19 pandemic underscores the critical need for expansion and examination of these methods, their appropriateness for various patient populations, and their benefits and limitations. Validity and reliability studies of teleneuropsychological testing have been conducted in MCI or mild AD dementia patients (e.g., MMSE=25+); few studies have assessed the feasibility of neurologic examination by video, and none in atypical dementias, assuming that patients with some types (e.g., language, comportment) or greater severity of cognitive-behavioral impairment would be unable to participate. Here we report the feasibility of telehealth services for a multi-disciplinary dementia subspecialty clinic that include cognitive-behavioral and neurologic assessment with patients with atypical neurodegenerative syndromes. Methods: 104 patient-carepartner (P-C) dyads met with providers in the MGH FTD Unit by videoconference (March-December, 2020) for routine clinical care. P-Cs completed validated questionnaires assessing cognition-mood/behavior/function on RED-Cap prior to video clinical interview and cognitive assessment, including the MoCA and Boston Cognitive Exam (BCE2.0), a newly revised brief cognitive assessment battery adapted for telehealth. P-Cs met with a neurologist for a basic neurologic examination (including eye-movement examination), review of assessment results, and discussion of care plan. P-Cs completed a satisfaction survey. Results:The 104 P-Cs included a range of atypical neurodegenerative disorders (bvFTD, PCA, PPA, CBS, PSP, eoAD, Multidomain syndrome) mild-to-severe impairment (CDR range: 0-3). 76% completed the MoCA (25% had CDR=2). 36% also completed the BCEv2. Comparison of remote assessment data to previous in-person testing is ongoing. Of P-Cs who completed a satisfaction survey, all reported being "very satisfied" with the appointment, with 93% open to participating in a remote visit again. 87% found the telehealth visit comparable to an in-person visit. 66% preferred a future combination of remote and in-person visits.Conclusions: Multi-disciplinary telehealth visits appear to be feasible with patients with atypical cognitive-behavioral syndromes of across the severity spectrum. P-Cs

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Despite the important role of written language in everyday life, abnormalities in functional written communication have been sparsely investigated in primary progressive aphasia. Prior studies have analyzed written language separately in each of the three variants of primary progressive aphasia – but have rarely compared them to each other or to spoken language. Manual analysis of written language can be a time-consuming process. We therefore developed a program which quantifies content units and total units in written or transcribed language samples. We analyzed written and spoken descriptions of the Western Aphasia Battery Picnic scene, based on a pre-defined content unit corpus. We calculated the ratio of content units to units as a measure of content density. Our cohort included 115 participants (20 controls for written, 20 controls spoken, 28 participants with nonfluent variant primary progressive aphasia, 30 logopenic variant, 17 semantic variant). Our program identified content units with a validity of 99.7% (95%CI 99.5-99.8). All patients wrote fewer units than controls (p&lt;0.001). Patients with the logopenic variant (p=0.013) and the semantic variant (0.004) wrote fewer content units than controls. The content-unit-to-unit ratio was higher in the nonfluent and semantic variants than controls (p=0.019), but no different in the logopenic variant (p=0.962). Participants with the logopenic (p&lt;0.001) and semantic (p=0.04) variants produced fewer content units in written compared to spoken descriptions. All variants produced fewer units in written samples compared to spoken (p&lt;0.001). However, due to a relatively smaller decrease in written content units, we observed a larger content-unit-to-unit ratio in writing over speech (p&lt;0.001). Written and spoken content units (r=0.5, p=0.009) and total units (r=0.64, p&lt;0.001) were significantly correlated in patients with nonfluent variant, but this was not the case for logopenic or semantic. Considering all patients with primary progressive aphasia, fewer content units were produced in those with greater aphasia severity (Progressive Aphasia Severity Scale Sum of Boxes, r=-0.24, p=0.04) and dementia severity (Clinical Dementia Rating scale Sun of Boxes, r=-0.34, p=0.004). In conclusion, we observed reduced written content in patients with primary progressive aphasia compared to controls, with a preference for content over non-content units in patients with the nonfluent and semantic variants. We observed a similar “telegraphic” style in both language modalities in patients with the nonfluent variant. Lastly, we show how our program provides a time-efficient tool, which could enable feedback and tracking of writing as an important feature of language and cognition.

Background Patients with Primary Progressive Aphasia (PPA) are usually subtyped into one of the three canonical subtypes (nfvPPA, svPPA, lvPPA) based on a neurological and cognitive assessment including their language characteristics typically measured from a battery of confrontational tests. While widely used, this classification system has been criticized, and also the approach makes assumptions about the features of language that are important to measure. Here we use methods from Artificial Intelligence to measure features of speech from naturalistic connected speech samples with the goal of determining how well this data‐driven approach matches independent clinical subtypes and how its results relate to neuroanatomical abnormalities measured from MRI. Method Language data was obtained from 78 PPA patients (28 nfvPPA, 26 lvPPA, 24 svPPA) describing the WAB Picnic Scene. A transformer model, RoBERTa, was used to measure similarities in language features, IVIS to perform dimensionality reduction, and nested k‐means to cluster language samples. We then examined the cortical atrophy patterns of these clusters of PPA patients versus healthy controls (N=25). Result Seven PPA clusters were identified with 88% agreement with the classic classification system. Individuals in Clusters 1 and 2 (mainly nfvPPA) exhibited speech dysfluency and reduced clausal complexity with atrophy in the left pars opercularis, superior and caudal middle frontal gyri. Those in Clusters 3 and 4 (predominantly lvPPA) exhibited difficulties in subject‐verb agreement, demonstratives and tense and shared atrophy in the superior and middle temporal and inferior parietal gyri. Individuals in Clusters 5‐7 (mainly svPPA) exhibited deficits in nouns/verbs access with atrophy in the left temporal pole and inferior and middle temporal gyri. Conclusion Data‐driven Artificial Intelligence methods applied to naturalistic speech samples from PPA patients identify clusters of patients that match well to clinical subtypes, and that exhibit cortical atrophy patterns typical of those subtypes. This suggests that PPA subtypes are natural kinds and that computational analysis of simple speech samples can be used to identify them.