Vrillon, Agathe

Objective Early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD) differ in many respects. Here, we address the issue of possible differences in fibrillar amyloid pathology as measured by positron emission tomography (PET), which remains unresolved due to the lack of large‐scale comparative studies. Methods Three hundred ninety‐nine cognitively impaired participants younger than 65 years of age from the multicenter Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) and 450 cognitively impaired participants older than 65 years from the Alzheimer's Disease Neuroimaging Initiative (ADNI) underwent clinical assessment, brain magnetic resonance imaging (MRI), and amyloid PET and were included in this study. We compared amyloid PET outcomes (positivity rate based on visual read and quantified tracer uptake expressed as Centiloids [CLs]) between the 2 cohorts and studied their association with age, sex, APOE genotype, and cognition. Results The amyloid positivity rate was higher in LEADS (78%, 95% confidence interval [CI] = 74–82) than in ADNI (71%, 95% CI = 67–75, p = 0.02). Lower Mini‐Mental State Examination (MMSE) and APOE4 genotype increased the odds of amyloid positivity in both cohorts. Visually positive scans had higher CLs in LEADS (EOAD, mean = 95.3 ± 26.1) than in ADNI (LOAD, mean = 80.9 ± 36.8, p < 0.0001), predominantly in parietal cortex/precuneus, superior temporal, and frontal cortices. In amyloid‐positive patients, (1) CLs were higher in female patients in both cohorts; (2) APOE4 carriership was associated with lower CLs in EOAD, which was not observed in LOAD; and (3) correlations between CLs and MMSE scores were significantly stronger in EOAD than in LOAD. Interpretation Differences in the burden of amyloid pathology may contribute to differences in clinical and anatomic patterns in sporadic EOAD and LOAD, and have implications for optimizing therapeutic strategies in each group. ANN NEUROL 2025;98:236–248

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.

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.

AbstractBackgroundBlood phosphorylated tau (p‐tau) has proven to be the primary candidate as an accessible and scalable biomarker for Alzheimer’s disease (AD). Both p‐tau181 and p‐tau217 are highly accurate to detect AD within dementia cases. Our recent work in cerebrospinal fluid, however, indicates p‐tau231 to be associated to incipient AD pathology. In light of this, we developed a Single molecule array (Simoa) to detect plasma p‐tau231 and assessed its performance in multiple domains, specifically, its ability to detect preclinical AD.MethodIn all cohorts, plasma p‐tau231 was quantified using an in‐house Simoa method developed at the Clinical Neurochemistry Laboratory, Gothenburg University, Sweden. Data presented in this study are samples acquired from Translational Biomarkers of Aging and Dementia (TRIAD, n=503), King’s College London (n=55), Mayo Clinic Study of Aging (n=145), KARVIAH (n=140), Baltimore Longitudinal Study of Aging (n=430), University College London (n=70), Paris University (n=213), PREVENT‐AD (n=257), University of California (n=309) and ALFA+ (n=385).ResultIn the TRIAD cohort, plasma p‐tau231 demonstrated high accuracy in determining AD from young individuals (AUC=0.95), Aβ‐ elderly (AUC=0.92), Aβ‐ MCI (AUC=0.88) and other neurodegenerative disorders (AUC=0.92). In an autopsy study, plasma p‐tau231 could detect neuropathologically confirmed AD amongst dementia cases (AUC=0.99). In comparing healthy elderly Aβ‐ and Aβ+ individuals, p‐tau231 predicted preclinical Aβ pathology (AUC=0.83). Furthermore, inflection points of the weighted regression curves demonstrate that increases in plasma p‐tau231 occur before plasma p‐tau181 as a function of Aβ deposition load. Plasma p‐tau231 data from additional cohorts will focus on cross‐sectional and longitudinal preclinical datasets. In addition, further data will show the performance of p‐tau231 in symptomatic and presymptomatic PSEN1/APP mutation carriers, memory clinic cohorts, longitudinal neuropathology confirmed and acute neurological injury.ConclusionPlasma p‐tau231 is a new biomarker specific for AD pathology and at higher concentrations relative to p‐tau181 and p‐tau217. Our initial results indicate that plasma p‐tau231 is equivalent to p‐tau181 in diagnostic utility but has greater potential as a biomarker to monitor emerging Aβ pathology. This presentation will give an overview of novel cross‐sectional and longitudinal plasma p‐tau231 data, in more than 3000 individuals, that encompasses the AD continuum, familial AD and other neurological conditions.