Joie, Renaud La

AbstractBackgroundLarge‐scale studies comparing sporadic early‐onset AD (EOAD, age<65) and late‐onset AD (LOAD, age = 65) are lacking. We compared amyloid‐PET outcomes (positivity rate and amyloid burden) between patients clinically diagnosed with sporadic EOAD vs LOAD, leveraging data from the Longitudinal Early‐Onset AD Study (LEADS) and the Alzheimer’s Disease Neuroimaging Initiative 3 (ADNI3).Method731 patients meeting the 2011 NIA‐AA criteria for AD dementia or MCI were included (505 early‐onset from LEADS, 226 late‐onset from ADNI3, Table 1). All participants underwent amyloid‐PET with [18F]Florbetaben or [18F]Florbetapir. Amyloid positivity was centrally determined by a process involving a visual read by a trained expert and PET‐only quantification; in case of a discrepancy, a read from an independent physician acted as a tiebreaker. Logistic regressions in each cohort examined relations between amyloid positivity and age, sex, MMSE and APOE4 genotype. Amyloid burden was independently quantified in Centiloids using an MRI‐based pipeline. Mean Centiloids in LEADS and ADNI were compared with two‐way ANOVA, for visually positive and visually negative scans.ResultAmyloid positivity rate was higher in LEADS (76%) than ADNI (64%, p<0.001, Figure 1A). Lower MMSE and APOE4 genotype increased odds of amyloid positivity in both cohorts, although the APOE4 effect was stronger in ADNI than LEADS (OR = 10.1 versus 2.4, p = 0.007, Table 2). Amyloid positivity was more common in females across cohorts, but this effect was only statistically significant in LEADS (Table 2). Centiloids were bimodally distributed in both cohorts, although the separation between positive and negative scans was more prominent in LEADS (Figure 1B). Visually positive scans had significantly higher Centiloids in LEADS than in ADNI, whereas no cohort difference was observed for visually negative scans (Figure 1C). Sensitivity analyses showed that this effect was driven by patients with MCI (CDR = 0.5; Figure 1D‐E).ConclusionThe lower amyloid positivity rate in ADNI might be due to AD‐mimicking pathologies being more common at an older age. The higher amyloid burden in early‐onset, amyloid‐positive patients could reflect younger patients being diagnosed later in the disease course compared to typical, late‐onset patients. Alternatively, younger patients might tolerate higher neuropathology burden due to higher brain reserve or fewer co‐pathologies.

AbstractBackgroundDiagnosing sporadic early‐onset AD (EOAD, age‐at‐onset<65) is challenging: in the multi‐center Longitudinal Early‐onset Alzheimer’s Disease Study, ∼25% of patients with clinically diagnosed EOAD are amyloid‐PET‐negative. Here we used FDG‐PET to characterize the heterogeneity of hypometabolic profiles in these patients and better identify underlying etiologies.MethodSeventy‐four amyloid‐PET‐negative patients with clinical diagnosis of sporadic EOAD (MCI or mild dementia stage) underwent FDG‐PET. Patients were classified as having normal or hypometabolic FDG‐PET based on a data‐driven approach that compared each patient to a group of 61 age‐matched amyloid‐PET‐negative controls using 12 methodological combinations (3 reference regions, 2 voxel‐level thresholds, 2 outlier detection methods). We then assessed clinical and demographic differences between patients with normal versus hypometabolic FDG‐PET, and further compared groups using independent biomarkers of neurodegeneration (structural MRI and fluid biomarkers). Finally, we applied hierarchical clustering to hypometabolic FDG‐PET scans to identify patterns of hypometabolism.ResultThirty‐six amyloid‐negative patients (49%) had hypometabolic FDG‐PET scans. They were older and more severely impaired across most cognitive domains than patients with normal FDG‐PET (Table 1). They also had reduced hippocampal volumes and cortical thickness (Figure 1A), higher plasma and CSF neurofilament light chain (NfL) levels, and elevated plasma GFAP compared to patients with normal FDG‐PET (Figure 1B). In contrast, the latter, who had intermediate cognitive scores between hypometabolic patients and controls, had MRI and fluid biomarker levels in the range of controls (Figure 1). In hypometabolic patients, hierarchical clustering identified four profiles: i) anterior temporal extending to temporo‐parietal and frontal regions (n = 5), ii) anterior temporal and orbitofrontal (n = 11), iii) occipito‐parietal (n = 6), and iv) lateral frontal and parietal (n = 14) (Figure 2). Genetic testing identified two patients with Frontotemporal Lobar Degeneration (FTLD)‐associated pathogenic variants, both considered hypometabolic and assigned to the first (MAPT) and second (c9orf72) metabolic profiles.ConclusionFifty‐one percent of amyloid‐negative patients had normal FDG‐PET: they had milder clinical impairment, normal MRI measures, and normal NfL values, suggesting non‐neurodegenerative etiologies. Patients with abnormal FDG showed heterogeneous hypometabolic patterns suggestive of multiple etiologies including Lewy body disease, FTLD or corticobasal degeneration. Longitudinal follow‐up to autopsy will ultimately clarify the amyloid‐negative clinical mimics of sporadic EOAD.

AbstractBackgroundMedial temporal lobe (MTL) atrophy is an early feature of multiple neurodegenerative diseases. In genetic frontotemporal lobar degeneration (FTLD, i.e. individuals carrying GRN, MAPT, or C9orf72 mutations), MTL atrophy can occur 10‐15 years before symptom onset. We aimed to better characterize MTL atrophy patterns in presymptomatic and symptomatic genetic FTLD using a multi‐atlas segmentation pipeline that allows precise measurement of MTL subregions.MethodParticipants included a diagnostically mixed sample of familial FTLD mutation carriers (MAPT: N = 87; C9orf72: N = 117; GRN: N = 65) and 142 non‐carrier family member controls from the ALLFTD study cohort (Table 1). T1‐weighted MRIs were preprocessed using a multi‐atlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS]) to segment the amygdala, anterior and posterior hippocampus, and MTL cortices: entorhinal cortex (ERC), perirhinal cortex or Brodmann areas (BA) 35 and 36, and parahippocampal cortex (PHC). Following rigorous quality control and manual correction (Figure 1), we assessed bilateral volume differences in mutation carriers compared to controls, adjusted for age, sex, and total intracranial volume. Analyses were conducted separately for symptomatic (FTLD‐Clinical Dementia Rating Global Score≥0.5) and presymptomatic (Global Score = 0) mutation carriers.ResultOut of 413 scans, 317 (76.8%) segmentations passed quality control while 94 (22.8%) needed some manual edits—this was more common in symptomatic than presymptomatic carriers (32% versus 15%, p = 0.001). Three scans were excluded (<1%; 2 complete scans, 1 for selected subregions) due to insufficient landmark visibility in symptomatic GRN and MAPT carriers. In symptomatic carriers, all MTL subregions demonstrated reduced volume compared to controls, although MAPT carriers exhibited particularly marked atrophy, especially in anterior MTL subregions (Table 2; amygdala, ERC, BA35, hippocampus). Presymptomatic MAPT and C9orf72 carriers also exhibited significant atrophy of primarily anterior MTL cortices, while presymptomatic GRN carriers only exhibited significantly smaller ERC volume compared to controls.ConclusionMTL atrophy is present in genetic FTLD across mutation carriers, even at the presymptomatic stage. Anterior MTL subregions, which are also susceptible to neuropathologic accumulation in early Alzheimer’s disease and Limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC), tend to be more vulnerable than posterior subregions. Unsurprisingly, MAPT carriers show the greatest MTL atrophy compared to controls across groups.

AbstractBackgroundThe Uniform Data Set (UDS) neuropsychological battery, administered across Alzheimer’s Disease Centers (ADC), includes memory tests but lacks a list‐learning paradigm. ADCs often supplement the UDS with their own preferred list‐learning task. Given the importance of list‐learning for characterizing memory, we aimed to develop a harmonized memory score that incorporates UDS memory tests while allowing centers to contribute differing list‐learning tasks.MethodWe applied item‐banking confirmatory factor analysis to develop a composite memory score in 5,287 participants (mean age 67.1; SD = 12.2) recruited through 18 ADCs and four consortia (DiverseVCID, MarkVCID, ALLFTD, LEADS) who completed UDS memory tasks (used as linking‐items) and one of five list‐learning tasks. All analyses used linear regression. We tested whether memory scores were affected by which list‐learning task was administered. To assess construct validity, we tested associations of memory scores with demographics, disease severity (CDR Box Score), an independent memory task (TabCAT Favorites, n = 675), and hippocampal volume (n = 811). We compared performances between cognitively unimpaired (n = 279), AD‐biomarker+ MCI (n = 26), and AD‐biomarker+ dementia (n = 98). In a subsample with amyloid‐ and tau‐PET (n = 49), we compared memory scores from participants with positive vs negative scans determined using established quantitative cutoffs.ResultModel fit indices were excellent (e.g., CFI = 0.998) and factor loadings were strong (0.43‐0.93). Differences in list‐learning task had a negligible effect on scores (average Cohen’s d = 0.11). Higher memory scores were significantly (p’s<.001) correlated with younger age (β = ‐0.18), lower CDR Box Scores (β = ‐0.63), female sex (β = 0.12), higher education (β = 0.19), larger hippocampal volume (β = 0.42), and an independent memory task (β = 0.71, p<0.001). The memory composite declined in a stepwise fashion by diagnosis (cognitively unimpaired>MCI>AD dementia, p<0.001). On average, amyloid‐PET positivity was associated with lower composite scores, but was not statistically significant (β = ‐0.34; p = 0.25; d = 0.40). Tau‐PET positivity was associated with worse performance, demonstrating a large effect size (β = ‐0.75; p<0.002; d = 0.91).ConclusionThe harmonized memory score developed in a large national sample was stable regardless of contributing list‐learning task and its validity for cross‐cohort ADRD research is supported by expected associations with demographics, clinical measures, and Alzheimer’s biomarkers. A processing script will be made available to enhance cross‐cohort ADRD research.

Abstract INTRODUCTION Early‐onset Alzheimer's disease (EOAD) manifests prior to the age of 65, and affects 4%–8% of patients with Alzheimer's disease (AD). The current analyses sought to examine longitudinal cognitive trajectories of participants with early‐onset dementia. METHODS Data from 307 cognitively normal (CN) volunteer participants and those with amyloid‐positive EOAD or amyloid‐negative cognitive impairment (EOnonAD) were compared. Cognitive trajectories across a comprehensive cognitive battery spanning 42 months were examined using mixed‐effects modeling. RESULTS The EOAD group displayed worse cognition at baseline relative to EOnonAD and CN groups, and more aggressive declines in cognition over time. The largest effects were observed on measures of executive functioning domains, while memory declines were blunted in EOAD. DISCUSSION EOAD declined 2–4× faster than EOnonAD, and EOAD pathology is not restricted to memory networks. Early identification of deficits is critical to ensure that individuals with sporadic EOAD can be considered for treatment using disease‐modifying medications. Highlights Represents the most comprehensive longitudinal characterization of sporadic EOAD to date. The trajectory of cognitive declines was steep for EOAD participants and worse than for other groups. Executive functioning measures exhibited the greatest declines over time in EOAD.

Abstract INTRODUCTION Early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD) share similar amyloid etiology, but evidence from smaller‐scale studies suggests that they manifest differently clinically. Current analyses sought to contrast the cognitive profiles of EOAD and LOAD. METHODS Z‐ score cognitive‐domain composites for 311 amyloid‐positive sporadic EOAD and 314 amyloid‐positive LOAD participants were calculated from baseline data from age‐appropriate control cohorts. Z‐ score composites were compared between AD groups for each domain. RESULTS After controlling for cognitive status, EOAD displayed worse visuospatial, executive functioning, and processing speed/attention skills relative to LOAD, and LOAD displayed worse language, episodic immediate memory, and episodic delayed memory. DISCUSSION Sporadic EOAD possesses distinct cognitive profiles relative to LOAD. Clinicians should be alert for non‐amnestic impairments in younger patients to ensure proper identification and intervention using disease‐modifying treatments. Highlights Both early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD) participants displayed widespread cognitive impairments relative to their same‐aged peers. Cognitive impairments were more severe for EOAD than for LOAD participants in visuospatial and executive domains. Memory and language impairments were more severe for LOAD than for EOAD participants Results were comparable after removing clinical phenotypes of posterior cortical atrophy (PCA), primary progressive aphasia (lv‐PPA), and frontal‐variant AD.

Abstract Approximately 5% of Alzheimer’s disease patients develop symptoms before age 65 (early-onset Alzheimer’s disease), with either sporadic (sporadic early-onset Alzheimer’s disease) or dominantly inherited (dominantly inherited Alzheimer’s disease) presentations. Both sporadic early-onset Alzheimer’s disease and dominantly inherited Alzheimer’s disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer’s disease and dominantly inherited Alzheimer’s disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer’s disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer’s Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer’s disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50–70 cerebellar grey reference and FDG30–60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer’s disease, sporadic early-onset Alzheimer’s disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen’s d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer’s V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer’s disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer’s disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer’s disease versus sporadic early-onset Alzheimer’s disease. Sporadic early-onset Alzheimer’s disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer’s disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer’s disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer’s disease.

AbstractBackgroundWe examined neuropsychiatric symptoms (NPS) and psychotropic medication use at the midway point of data collection of the Longitudinal Early‐onset Alzheimer’s Disease Study (LEADS). We compared amyloid‐positive early‐onset Alzheimer’s disease (EOAD) participants and amyloid‐negative early‐onset non‐Alzheimer’s disease [EOnonAD]) participants across NPS domains and psychotropic medication categories.Method282 participants enrolled in LEADS were compared across diagnostic groups – amyloid‐positive EOAD (n = 212) and amyloid‐negative EOnonAD (n = 70). All participants were between ages 40 and 64 at baseline. NPS were measured with the Neuropsychiatric Inventory – Questionnaire (NPI‐Q) and Geriatric Depression Scale – Short Form (GDS‐SF). Medications were categorized into psychotropic category (e.g., antidepressants, antipsychotics, benzodiazepines). Groups were compared on NPI‐Q using binary logistic regression adjusting for sex and disease severity, on GDS‐SF using linear regression adjusting for sex and disease severity, and on psychotropic medication use using Chi square or Fisher’s exact test.ResultDemographic data are presented in Table 1. Average total NPI‐Q score was higher in EOnonAD than EOAD (p = .002, ŋp 2 = .03). Regardless of diagnostic group, informants endorsed Affective behaviors most frequently (76.2%). EOAD informants endorsed fewer Distress‐Tension behaviors (p = .02, OR = .498) and Impulse Control behaviors (p = .01, OR = .438). EOAD informants also endorsed apathy (p < .001, OR = .316), irritability (p = .02, OR = .498), and disinhibition (p = .04, OR = .476) at lower frequency than EOnonAD. GDS‐SF showed that the EOnonAD participants self‐reported more symptoms of depression than the EOAD group (p = .002, ŋp 2 = .03). (Table 2A). A minority of participants, regardless of diagnostic group, reported psychotropic medication use (35%). There was higher use in EOnonAD (38%) than EOAD (24%) (p = .03, Cohen W = .14) (Table 2B).ConclusionNPS burden and psychotropic medication use were higher in EOnonAD than EOAD participants, despite EOnonAD being less severely impaired. LEADS continues to collect data. Future studies will examine etiologies that may be larger drivers of NPS than AD neuropathology, mediators (e.g., race, ethnicity) in the association between NPS and diagnostic group classication, compare NPS in EOAD vs. LOAD, and examine longitudinal changes in neuropsychiatric profiles.

AbstractBackgroundApproximately 10‐25% of amnestic early‐onset dementia are negative for amyloid (Early‐onset non‐Alzheimer’s Disease, EOnonAD). EOnonAD is a heterogenous group with various etiologies. In order to better understand the traits of EOnonAD, we clustered amnestic EOnonAD individuals according to cognitive patterns.MethodCognitive data of 62 EOnonAD individuals from the Longitudinal Early‐onset AD study (LEADS) were Z‐normalized to 91 intact individuals after adjusting for age, sex, and education. This led to domain‐averaged composite Z‐scores for memory, language, speed/attention, visuospatial, and executive function. Cluster analysis using the Ward method on the residuals for the five composites was performed. We used Scree plot using the pseudo T‐squared to determine the optimal number of clusters. We compared demographics, imaging biomarkers (amyloid and tau PET SUVR, hippocampal volume), plasma (pTau231, Aß40, Aß42, glial fibrillary acidic protein, and neurofilament light chain (NfL)), and cerebrospinal fluid (CSF) biomarkers (Aß42/40, NfL, Neurogranin, Visinin‐like protein, YKL‐40, and Synaptosome Associated Protein 25) across the clusters after adjusting for age, sex, and education. We compared gray matter density of each EOnonAD cluster to controls (n = 84) using voxel‐wise multiple linear regressions in SPM12, adjusting for age, sex, education, and intracranial volume.ResultScree plot using the pseudo‐T‐squared suggested three clusters. Cluster 1 (38/62, 61.3%) was characterized by having the mildest cognitive impairment in all domains. Cluster 2 (19/62, 30.6%) was characterized by more severe memory and language impairment. Cluster 3 (5/62, 8.1%) was characterized by more severe impairment in speed/attention, visuospatial, and executive function (Table 1). Cluster 3 showed significantly higher NfL for both plasma (Cluster 1 vs 3, p<0.001; Cluster 2 vs 3, p < 0.004) and CSF (Cluster 1 vs 3, p = 0.001). Other biomarkers did not show significant difference (Table 1). Only Cluster 3 showed significant atrophy in the bilateral fronto‐parietal areas at p<0.01, uncorrected (Figure 1).ConclusionWe identified heterogeneity in cognitive patterns among amnestic EOnonAD individuals. Cluster 1 had mildest cognitive impairment; Cluster 2 had predominant impairment in memory and language; and Cluster 3 had predominant impairment in speed/attention, visuospatial, and executive function, with significant fronto‐parietal atrophy and high NfL indicating active neurodegeneration.

Abstract Approximately 5% of Alzheimer’s disease cases have an early age at onset (&lt;65 years), with 5–10% of these cases attributed to dominantly inherited mutations and the remainder considered as sporadic. The extent to which dominantly inherited and sporadic early-onset Alzheimer’s disease overlap is unknown. In this study, we explored the clinical, cognitive and biomarker profiles of early-onset Alzheimer’s disease, focusing on commonalities and distinctions between dominantly inherited and sporadic cases. Our analysis included 117 participants with dominantly inherited Alzheimer’s disease enrolled in the Dominantly Inherited Alzheimer Network and 118 individuals with sporadic early-onset Alzheimer’s disease enrolled at the University of California San Francisco Alzheimer’s Disease Research Center. Baseline differences in clinical and biomarker profiles between both groups were compared using t-tests. Differences in the rates of decline were compared using linear mixed-effects models. Individuals with dominantly inherited Alzheimer’s disease exhibited an earlier age-at-symptom onset compared with the sporadic group [43.4 (SD ± 8.5) years versus 54.8 (SD ± 5.0) years, respectively, P &lt; 0.001]. Sporadic cases showed a higher frequency of atypical clinical presentations relative to dominantly inherited (56.8% versus 8.5%, respectively) and a higher frequency of APOE-ε4 (50.0% versus 28.2%, P = 0.001). Compared with sporadic early onset, motor manifestations were higher in the dominantly inherited cohort [32.5% versus 16.9% at baseline (P = 0.006) and 46.1% versus 25.4% at last visit (P = 0.001)]. At baseline, the sporadic early-onset group performed worse on category fluency (P &lt; 0.001), Trail Making Test Part B (P &lt; 0.001) and digit span (P &lt; 0.001). Longitudinally, both groups demonstrated similar rates of cognitive and functional decline in the early stages. After 10 years from symptom onset, dominantly inherited participants experienced a greater decline as measured by Clinical Dementia Rating Sum of Boxes [3.63 versus 1.82 points (P = 0.035)]. CSF amyloid beta-42 levels were comparable [244 (SD ± 39.3) pg/ml dominantly inherited versus 296 (SD ± 24.8) pg/ml sporadic early onset, P = 0.06]. CSF phosphorylated tau at threonine 181 levels were higher in the dominantly inherited Alzheimer’s disease cohort (87.3 versus 59.7 pg/ml, P = 0.005), but no significant differences were found for t-tau levels (P = 0.35). In summary, sporadic and inherited Alzheimer’s disease differed in baseline profiles; sporadic early onset is best distinguished from dominantly inherited by later age at onset, high frequency of atypical clinical presentations and worse executive performance at baseline. Despite these differences, shared pathways in longitudinal clinical decline and CSF biomarkers suggest potential common therapeutic targets for both populations, offering valuable insights for future research and clinical trial design.