AbstractBackgroundThe ALLFTD (ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration) study is an NIH‐funded effort to prepare for clinical trials in sporadic (s‐FTLD) and familial (f‐FTLD) FTLD syndromes by characterizing cohorts, developing new clinical trial outcome measures, and evaluating disease progression. To understand disease trajectories in the context of potential preventative or disease‐modifying therapeutic agents, comprehensive evaluation across multiple time‐points is crucial.MethodALLFTD evaluates participants with FTLD spectrum disorders (bvFTD, svPPA, nfvPPA, FTD‐ALS, CBS, PSP), with strong family histories of FTLD, or known FTLD‐associated genetic variants within the family. ALLFTD has expanded to include 28 expert sites in North America conducting clinical and neuropsychological evaluations, MR Imaging, blood draws, and CSF collection in willing participants, providing detailed data on participant status and disease progression. Participants are asked to return for annual evaluations. The central data management staff assist sites in retention efforts by providing monthly reports of follow‐up visits that are pending, due, or overdue, based on a 15‐month period from previous visit.ResultSince enrollment began in January 2020, ALLFTD has conducted 1363 baseline visits, including 339 participants previously enrolled in ALLFTD’s predecessor studies (ARTFL and LEFFTDS). Excluding individuals not anticipated to return due to disease progression (123), participant death (55), or recent enrollment (<15 months; 318), ALLFTD has a retention rate of 83% for a second visit despite early enrollment occurring during COVID restrictions. Retention rates for third and fourth visits are even higher (90% and 97% respectively), suggesting a high degree of engagement in longitudinal participants. Including historic data from ARTFL and LEFFTDS, >1000 participants have multiple visits.ConclusionLongitudinal assessment of clinical and biomarker profiles in f‐FTLD and s‐FTLD can inform models of disease onset and progression, allowing analysis of disease trajectories and identification of the most sensitive clinical outcome measures over time. ALLFTD has been successful at recruiting and retaining a large active cohort to obtain detailed clinical and biomarker characterizations; data are available by request.
Distribution of cognitive domains and neuropathology of cases with mild cognitive impairment
AbstractBackgroundMild Cognitive Impairment (MCI) is a pre‐dementia state where impaired cognitive domains (memory, executive, visuospatial processing, language) may predict underlying pathology, e.g. Alzheimer’s disease(AD), Lewy body (LB), and other. Delineating neuropathological heterogeneity in MCI and their associations with neuropsychological profiles are important in identifying individuals at risk of further deterioration. We aimed to characterize the neuropathological heterogeneity in cases with a diagnosis of MCI.MethodCases with a final consensus cognitive diagnosis of MCI (n = 128) prior to death were selected from the Arizona Study of Aging and Neurodegenerative disorders (AZSAND). Groups were divided into amnestic (aMCI) and non‐amnestic MCI (naMCI), single and multi‐domain impairment, and specific domain impairment (executive, language, visuospatial) was explored. Presence and severity of neuropathology including AD, LB, cerebral white matter rarefaction (CWMR), cerebral amyloid angiopathy (CAA), cerebral infarcts and microinfarcts (cortical and subcortical), TAR DNA‐binding protein 43 (TDP‐43), and apolipoprotein E (ApoE) status were compared between MCI subtypes.ResultThe number of cases meeting neuropathological criteria for AD was not different between aMCI (36.4%) and naMCI (22.6%) while co‐existent PD was less frequent in aMCI (19.5% vs 38.7%). When compared to naMCI (n = 31), the aMCI (n = 85) group had an older age of death (p = 0.001), less educational years (p = 0.04), a higher number of subcortical infarcts (p = 0.012), a higher regional density of neurofibrillary tangles (p = 0.027) and a lower density of LB (p = 0.015) in the temporal lobe, and CWMR in tended to be more severe in the frontal lobe (p = 0.052). Those with single domain aMCI had less CWMR (p = 0.001) compared to the multidomain. Within the naMCI group, those with single domain MCI had higher proportions of CAA (p = 0.042), and lower LB density (p = 0.019) compared to multidomain. CWMR was more severe (p = 0.026) inConclusionA high heterogeneity was observed between MCI subtypes. While AD pathology was similar between groups, regional anatomical differences were observed. Vascular pathology including subcortical infarcts, CWMR and CAA appear to be commonly associated with both aMCI and naMCI respectively while CWMR was associated with executive dysfunctions. CWMR, CAA and LBs appear to be more frequent in multidomain aMCI and naMCI respectively.
Sex differences in familial forms of frontotemporal dementia
AbstractBackgroundSex differences in neurodegenerative diseases can impact accurate diagnosis and management. Emerging data suggest there may be sex differences in frontotemporal dementia (FTD) prevalence and clinical manifestation. However, prior studies lacked longitudinal assessment and were limited in capturing sex differences in earliest stages of disease (e.g., preclinical). We evaluated how sex impacts longitudinal clinical outcomes in individuals carrying autosomal dominant variants for FTD.Method337 participants carrying pathogenic variants in MAPT, GRN, or C9orf72 completed longitudinal evaluations (2.4 average visits, range = 1‐6), including neuropsychological and functional assessments, and plasma analyzed for neurofilament light chain (NfL). FTLD Clinical Dementia Rating Scale (FTLD‐CDR) classified disease stage at study entry (FTLD‐CDR = 0: asymptomatic; FTLD‐CDR = 0.5: MCI; FTLD‐CDR> 0.5: Dementia). Linear mixed‐effects models evaluated the effect of sex on longitudinal clinical trajectories, including the effect of disease stage at study entry.ResultMale and female carriers were similarly distributed with respect to baseline demographics and most clinical outcomes. However, women exhibited higher baseline NfL than men. Not accounting for disease stage, men and women did not show statistical differences on cognitive, functional, or NfL trajectories. However, when accounting for disease stage, there was a significant interaction between baseline disease stage, sex, and time on cognitive, NfL, and functional trajectories. While sex differences were not statistically significant among asymptomatic carriers, women with MCI/dementia evidenced more rapid cognitive, NfL and functional decline over time compared to men. To evaluate the role of pathology burden, we tested the interaction between baseline NfL, sex, and time on clinical outcomes stratified by disease stage. In asymptomatic participants, women showed an attenuated adverse relationship between baseline NfL and clinical trajectories compared to men. No statistically significant sex differences were evident in the relationship between baseline NfL and clinical outcomes in participants with MCI/dementia.ConclusionIn familial FTD, women evidenced steeper clinical declines than men after symptom onset. Accounting for pathology, baseline NfL was a stronger predictor of clinical decline in asymptomatic men compared to women. NfL may be a less sensitive prognostic tool for clinical progression in women with FTD, particularly early in disease. This may reflect early “cognitive resilience” to neurodegeneration in women.
Rapid Identification of Patients with Rapidly Progressive Dementia
AbstractBackgroundPatients with the precipitous onset of cognitive symptoms (i.e., suspected rapid progressive dementia [RPD]) may continue to decline (true RPD) or may stabilize or improve (non‐RPD). Recognizing patients with RPD early in the disease course is important to support clinical care and enrollment in research.MethodPatients referred for the evaluation of suspected RPD were prospectively enrolled and followed for up to 2 years at Mayo Clinic in Florida (Jacksonville, FL; Jan‐2020 – Oct‐2023) and Washington University in St. Louis (Saint Louis, MO; Jun‐2016 – Dec‐2019). Clinical data were independently reviewed by two dementia specialists who established clinical diagnoses, referencing published criteria. Patients were diagnosed with RPD if they progressed to dementia (global Clinical Dementia Rating® [CDR] ≥1) within 1 year or incapacitation (CDR ≥2) within 2 years of symptom onset. Univariate statistics compared demographics, clinical details, and test results between patients with RPD and non‐RPD. Variables with p<0.1 were entered into a multivariate logistic regression model to identify factors associated with RPD.ResultOf 248 patients referred for suspected RPD, 187 (75.4%) met stated criteria for RPD. Patients with RPD were older (62.6±14.4 years vs 55.0±18.3 years; p<0.001), and more likely to be diagnosed with Alzheimer disease or related dementias (28.3% vs 9.8%; p = 0.003) or Creutzfeldt‐Jakob (19.1% vs 4.6%; p = 0.008). Non‐RPD cases were more often attributed to autoimmune/inflammatory disease (42.6% vs 29.4%, p = 0.061) or other causes (e.g., psychiatric, neoplasms, toxic/metabolic; 34.4% vs 16.6%, p = 0.006). After controlling for age, hallucinations (OR, 2.81; 95%CI: 1.21‐6.52), elevated CSF protein (OR, 2.43; 95%CI: 1.17‐5.03), and CSF white blood cell count <5 cells/mm3 (OR, 2.77; 95%CI: 1.32‐5.85) were independently associated with RPD. Cortical visual loss (15/183, 8.2%) and substantial brain atrophy on MRI (27/184, 14.7%) were specific to patients with RPD, representing additional distinguishing features.ConclusionHallucinations, cortical visual loss, substantial atrophy on MRI, elevated CSF protein, and normal CSF white blood cell count were independently associated with RPD. Early detection of these features in patients with suspected RPD may inform clinical care and enrollment in research studies of RPD.
1‐ versus 2‐test criteria for cognitive impairment and associations with CSF and imaging markers in former American football players
AbstractBackgroundClinically meaningful cognitive impairment has typically been defined as a single impaired test score, but this approach is prone to false‐positive errors. Examining two test scores at a lower threshold (i.e., using neuropsychological criteria) can improve diagnostic reliability and has shown stronger associations with biomarkers of Alzheimer’s disease. Cognitive impairment in episodic memory and/or executive functioning is a core feature of traumatic encephalopathy syndrome (TES). However, there remains a need to improve the specificity of TES criteria. We applied 1‐ vs. 2‐test criteria for cognitive impairment in former American football players to examine whether 2‐test criteria showed stronger associations with biomarkers of tau, axonal injury, and neurodegeneration.Method169 male former American football players from the DIAGNOSE CTE Research Project completed neuropsychological assessment, lumbar puncture, and MRI (see Table). Episodic memory measures were delayed recall from Craft Story, Brief Visuospatial Memory Test, and NAB List Learning. Executive functioning measures were FAS, Stroop Interference, NAB Mazes, and Trails B. Cerebrospinal fluid (CSF) was measured using Lumipulse technology (p‐tau, t‐tau) and an in‐house ELISA (neurofilament light [NfL]). Hippocampal volumes were extracted from structural MRI using Freesurfer 7.1. Cognitive impairment was identified by 1‐test criteria (≥1.5 SD below norms on one test in either domain) and 2‐test criteria (>1 SD below norms on two tests within a domain). Regressions adjusting for age, race, education, and APOE ε4 status assessed whether meeting 1‐ or 2‐test criteria, separately, predicted log‐transformed CSF p‐tau181, p‐tau231, t‐tau, and NfL, and hippocampal volumes.Result37 of the 99 football players that were impaired by 1‐test criteria did not meet 2‐test criteria, and four uniquely met 2‐test but not 1‐test criteria (see Figure). Cognitive impairment by 2‐test but not 1‐test criteria predicted higher log‐CSF NfL (2‐test: B = 0.24, p = .007; 1‐test: B = 0.06, p = .53), smaller left hippocampal volume (2‐test: B = ‐195.84, p = .01; 1‐test: B = ‐131.52, p = .08), and smaller right hippocampal volume (2‐test: B = ‐161.19, p = .045; 1‐test: B = ‐134.88, p = .08). Neither criterion predicted p‐tau181, p‐tau231, or t‐tau.Conclusion2‐test criteria demonstrated stronger associations between cognitive impairment and markers of axonal injury and neurodegeneration. Incorporating multiple test scores to identify cognitive impairment could improve diagnostic specificity in TES.
Beyond Traditional Measures: Exploring Cognitive Intraindividual Variability in Traumatic Encephalopathy Syndrome
AbstractBackgroundTraumatic encephalopathy syndrome (TES) is the proposed clinical syndrome of chronic traumatic encephalopathy (CTE), a neurodegenerative disease associated with repetitive head impacts in contact/collision sports. A core clinical feature of TES is cognitive impairment, particularly in memory and executive functions. Cognitive intraindividual variability (IIV) is the extent of variability in neuropsychological test performance (i.e., dispersion of test scores) and is believed to be an indicator of disruption in executive control, linked to altered fronto‐subcortical circuits. Here, we examined cognitive IIV as a method to detect subtle executive dysfunction in TES that may not be captured by traditional neuropsychological measures.MethodThe sample included former American football players (120 professional, 60 college); participants were males, aged 45‐74. Participants completed a baseline neuropsychological test battery (n = 8 excluded for suboptimal performance validity). A multidisciplinary diagnostic consensus conference classified participants using the 2021 NINDS Consensus Diagnostic Criteria for TES (see Table‐1): (1) No‐TES (n = 62); (2) TES‐CTE Suggestive (n = 35); (3) TES‐CTE Possible (n = 21); (4) TES‐CTE Probable (n = 54). TES‐CTE Possible and Probable were combined. The coefficient of variation (CoV) was used to measure cognitive IIV (CoV = iSD/iOTBM, iOTBM = average T‐score across neuropsychological tests; iSD = standard deviation of iOTBM). A higher CoV indicates greater score dispersion. To avoid circularity, memory and executive tests used for classifying TES groups were intentionally excluded from the CoV calculation. Analysis of covariance compared the TES groups on CoV, controlling for age, education, and race.ResultResults showed a significant difference in CoV between TES groups, F(2, 165) = 8.20 p<.001, partial η2 = .09. The TES‐CTE Possible/Probable group had the highest CoV (M = .226, SE = .007), compared with the TES‐no (M = .192, SE = .008, p<.001) and TES‐CTE Suggestive groups (M = .178, SE = .011, p<.001). CoV did not significantly differ between the TES‐no and TES‐CTE suggestive groups (Mdiff = 0.014, SE = .013, p = .293).ConclusionThe TES‐CTE possible/probable group had the highest cognitive IIV with ∼23% dispersion (vs. ∼18‐19% in TES‐no and TES‐CTE suggestive groups), suggesting greater cognitive variability in those with the greatest likelihood for having underlying CTE (based on TES criteria). This finding emphasizes the potential utility of exploring cognitive IIV as a method for detecting nuanced executive dysfunction in TES.
Tau exacerbates the development of distinct neuropsychiatric symptoms in late braak stage – the head study
AbstractBackgroundRecent studies showed that neuroinflammation plays a key role in triggering specific neuropsychiatric symptoms (NPS), such as irritability and agitation, in individuals with Alzheimer’s disease (AD). While prior studies showed an association between tau pathology and all NPS domains, the extent to which tau influences each specific NPS domain remains unclear. Here, we aim to investigate the association of tau and NPS domains in the AD continuum. We hypothesize that tau plays a comparatively greater effect on the emergence of psychotic symptoms compared to other NPS domains.MethodWe assessed 56 individuals (21 cognitively unimpaired (CU), 23 MCI, and 12 AD dementia) from the HEAD study who underwent clinical assessments with the Neuropsychiatry Inventory Questionnaire (NPI‐Q) and had positron emission tomography (PET) for amyloid‐β (Aβ) ([18F]AZD4694 or [11C]PiB), and tau tangles ([18F]MK6240) at the same visit. We selected individuals with an NPI‐Q total score ≥1. Tau SUVR values were tailored with a mask from Braak stages I‐VI, using the inferior cerebellar gray matter as reference region. Leave‐one‐out voxel wise and linear regression tested the association between each NPI‐Q domain and biomarkers accounting for age, sex, cognitive status, and study site.ResultCI individuals had significantly higher NPI‐Q score and Braak VI PET SUVR than CU individuals (Table 1). NPI‐Q score was significantly associated with tau‐PET in the periRolandic and supplementary motor cortex (Figures 1A). Linear regression showed that NPI‐Q associates with tau‐PET in the Braak stage VI (Figure 1B). Leave‐one‐out regression analysis revealed that delusions, motor disturbances, and anxiety contributed most to the association between tau‐PET and NPS (Figure 2A, C). These domains presented a higher magnitude of association compared to each other NPI‐Q domain (Figure 2B). Notably, irritability, agitation, and disinhibition exerted a negative effect to the association, emphasizing that tau may not play a role in the development of these symptoms (Figure 2A, D)ConclusionOur study supports previous evidence suggesting that irritability and agitation may not be triggered by tau, but rather by other pathological process such as neuroinflammation. These findings provide additional rationale for the therapeutics aiming to mitigate irritability and agitation in AD patients.
Development of a composite score to predict Lewy body pathology burden
AbstractBackgroundLewy body (LB) diseases can present with overlapping prodromal, cognitive, motor, autonomic or neuropsychiatric symptoms. Intuitively, greater symptom severity should correlate with greater pathological burden, but this has not been consistently shown. LB pathology does not translate to clinical expression in Incidental LB disease. While several composite scores/toolkits utilize overlapping schemes for diagnosis, a composite data‐derived score to predict LB pathologic burden is lacking. We aimed to utilize an autopsy‐confirmed cohort, and validated, brief, and standardized clinical, functional, pathologic assessments, and machine learning (ML)/quantitative modeling techniques to identify clusters and importance rankings among assessments/measures to predict LB pathologic severity and density.MethodA total of 234 subjects with neuropathological finding of LB at autopsy in the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) who were classified as Cognitively Unimpaired or Mild Cognitive Impairment after their first study clinical evaluation were included. Of these, 145 subjects had complete scores for 32 of 46 measures (clinical, cognitive, behavioral and functional) that were utilized as predictors of LB pathology. Olfactory function was assessed using the University of Pennsylvania Smell Identification Test (UPSIT). LB severity was assessed by the Unified Staging System for Lewy Body Disorders (USSLB). Several ML algorithms and quantitative prediction models were explored and compared: artificial neural network (ANN), partial least square regression (PLSR), support vector regression (SVR), relevance vector regression (RVR) and ensemble forest regression (EFR) with leave‐one‐out (LOO) scheme. Game‐theory based Shapley methods assessed the impact, including rankings, consistency and magnitude, of model predictors.ResultRVR predicted aggregate LB density with large effect size (R2 = 0.691, p<0.00001). ANN predicted USSLB severity stage with large effect size (R2 = 0.74, p<2.5e‐43). All other ML algorithms/models provided substantial prediction. Across all models, UPSIT was the most influential predictor (>65%), followed by Controlled Oral Word Association Test (COWAT) and age.ConclusionThese preliminary and exploratory results support the utilization of ML techniques/models to assess LB pathologic burden with key measures collected in relatively small samples. UPSIT was consistently ranked highest impactful among clinical and functional measures/predictors. Integrated together in ML/data‐derived composites, UPSIT, COWAT and other clinical characteristics may be of antemortem utility to predict USSLB stages.
Longitudinal variability in resting heart rate associates with empathy decline in pre‐symptomatic and symptomatic familial frontotemporal degeneration
AbstractBackgroundAutonomic dysfunction has been linked to empathy deficits in symptomatic frontotemporal degeneration (FTD), but less is known about pre‐symptomatic FTD mutation carriers (preFTD+). Our prior work found that increasing resting heart rate (RHR) over time predicts decline in emotional empathy in preFTD+. Here, we replicate previous findings in a large, multi‐site consortium sample and assess relationships between RHR and empathy loss across disease stages.MethodRHR and Interpersonal Reactivity Index (IRI) were obtained serially for up to 7 years in 348 preFTD+, 202 symptomatic FTD mutation carriers (FTD+), and 311 non‐carrier family members (FTD‐) enrolled in ALLFTD. IRI Perspective Taking (IRI‐PT) and Empathic Concern (IRI‐EC) subscales measured cognitive and emotional empathy, respectively. Separate multiple linear regressions related mutation status and annualized change in RHR to annualized change in IRI subscales and assessed interactions between RHR change and phenoconversion status among mutation carriers. Logistic regression was used to assess the association between change in RHR and phenoconversion among mutation carriers, and Wilcoxon signed‐rank tests were used to examine differences in change in RHR between all study groups.ResultIn asymptomatic participants (preFTD+ and FTD‐), increase in RHR over time was associated with greater decline in IRI‐EC (ß = ‐0.07, p<.001) and IRI‐PT (ß = ‐0.03, p = .011), regardless of mutation status. Among mutation carriers (preFTD+ and FTD+), increase in RHR was associated with greater decline in IRI‐EC (ß = ‐0.04, p = .041), and this effect was stronger in FTD+ compared to PreFTD+ (ß = ‐0.07, p = .038), while an increase in RHR was associated with decline in IRI‐PT only in FTD+ (ß = ‐0.07, p = .046). Change in RHR did not predict phenoconversion in mutation carriers (PreFTD+ and FTD+), but PreFTD+ showed less change in RHR over time relative to FTD+.ConclusionChanges in empathy in asymptomatic preFTD+ and FTD‐ are linked to variability in RHR regardless of genetic status, likely reflecting a non‐specific impact of autonomic functioning on empathy and prosocial behavior. In contrast, increasing RHR predicts decline in cognitive and emotional empathy in FTD mutation carriers but primarily after phenoconversion, suggesting that autonomic contributions to empathy in familial FTD increase with disease progression and could be an early marker of manifest disease.
Remote Naturalistic Speech Analysis as a Tool to Classify Behavioral Variant Frontotemporal Dementia
AbstractBackgroundFrontotemporal dementia (FTD) is a diverse spectrum of neurodegenerative disorders impacting the frontal and temporal lobes, primarily manifesting as behavioral and/or language issues. Accurate diagnosis is crucial for effective management, potential treatment, and care planning. While speech analysis has shown promise in detecting cognitive markers of Alzheimer’s disease (AD), its exploration in FTD is limited. This study examined if linguistic features from remote, app‐based speech collection can differentiate healthy controls (HC) from individuals with behavioral variant FTD (bvFTD), the most common FTD variant.MethodParticipants included 15 bvFTD (mean age = 64.3, SD = 9.1 years) and 19 HC (mean = 55.8, SD = 14.2) from the ALLFTD Consortium. Participants were prompted to talk freely about a happy memory; audio recordings were collected with the ALLFTD Mobile App, transcribed using OpenAI’s large Whisper model, and manually quality‐checked. We extracted 98 linguistic features using our in‐house pipeline (Fig 1). Features were selected for classification analysis if they differed between groups based on a MANCOVA adjusted for age, sex/gender, and education, with feature reduction in case of collinearity. We then determined if these features could classify groups using multi‐variable logistic regression models, and subsequently calculated its ROC‐AUC score to measure sensitivity/specificity.ResultBased on the MANCOVA, three features were selected for classification analysis: average seconds of non‐speech (i.e., silence), ratio of number of complex nominal clauses to total clauses, and number of restarts (i.e., disfluency). The logistic model showed that this set could distinguish between groups (Omnibus p = .001; Nagelkerke R2 = .499), and their saved prediction probabilities indicated a ROC‐AUC score of 84.8% accuracy (Fig 2).ConclusionLeveraging a flexible speech capture app with remote accessibility and state‐of‐the‐art automated speech analysis, we identified linguistic features that can distinguish HC from bvFTD. This approach presents a promising screening tool for detecting bvFTD, offering quick, easily administered assessments with the potential for scalable implementation outside of clinical settings. Next steps are to investigate linguistic changes in presymptomatic mutation carriers and compare speech profiles between FTD and AD. These results hold meaningful implications for addressing current challenges in FTD therapeutics, potentially offering sensitive outcome measures for clinical trials and future tools for personalized cognitive assessment and long‐term monitoring.