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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.

AbstractBackgroundIn EOAD, the localization of neurodegeneration is often more prominent in posterior lateral temporal, lateral and medial parietal, frontal, or occipital cortex relative to the medial and ventral temporal cortical localization of typical LOAD. Convergently, neuropathological investigations have identified a “hippocampal‐sparing” form of AD that is often present in younger patients. For these reasons, imaging biomarkers of neurodegeneration in EOAD, such as Magnetic Resonance Imaging (MRI) measures of atrophy, likely need to be different than those of neurodegeneration in typical LOAD. Although prior neuroimaging work has advanced our understanding of anatomical abnormalities in EOAD, these studies have included small samples, most composed of amnestic EOAD dementia and none focused on developing an MRI biomarker specific to EOAD. Such a disease‐signature MRI biomarker has been established and validated in LOAD dementia and has proven to be powerful in predicting progressive decline in people with MCI or who were cognitively unimpaired and in predicting molecular biomarker status. An a priori‐defined regional atrophy signature may also be helpful in constraining the analysis of MRI data in studies of putative disease‐modifying therapies.MethodLEADS is an observational study which includes annual MRI. In this analysis, we used FreeSurfer to define the sporadic EOAD atrophy signature in a small sample of MGH EOAD patients, and investigated its reproducibility in LEADS, as well as the magnitude of atrophy and its relationship to clinical measures.ResultThe EOAD signature is robustly reproducible across the two independent patient cohorts, with prominent atrophy in caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortex, with relative sparing of medial temporal lobe structures. Comparing patients to controls, Cohen’s d effect sizes within various regions ranged from 0.99 to 1.98.ConclusionThis study demonstrates the specific cortical regions with most prominent atrophy in patients with sporadic EOAD; this signature of regional atrophy will be used to examine longitudinal change.

AbstractBackgroundMulticentric initiatives to study brain cognition in the elderly offers us a unique collection of brain imaging data accompanied by detailed neuroclinical and neuropsychological evaluations. U.S. POINTER and LatAm‐FINGERS, part of the World Wide FINGERS, are both large‐scale investigations of lifestyle interventions and its impact on cognitive function. These large‐scale detailed data may offer an unprecedented opportunity to compare diverse populations.MethodBaseline MRI of subjects from multiple US centers (POINTER‐US), distributed in 5 geographical regions, and from 9 latin‐american countries (LatAm‐FINGERS). The protocols vary from basic (3D T1, 3D FLAIR,T2* GRE, Cor T2 hippocampus, DWI) to advanced which also included ASL, rs‐FMRI and DTI. Demographic information and clinical, cognitive and neuropsychological assessment were also included.ResultMRI data was collected from 662 participants in the United States (about 65% of the total anticipated U.S. POINTER neuroimaging sample) and from 542 subjects from 9 countries in latin‐america (about 80% of the total anticipated LatAm‐FINGERS neuroimaging sample), with around 1200 participants scanned (table1).All participants have 3D T1, 3D FLAIR, T2* GRE images and either DWI or DTI images.Comparative demographics from the 2 datasets shows similar mean age, a predominance of females, and slight differences in education (table 2). This will allow us to compare multiethnic and multicultural volumetric and functional brain MRI information, as well as disease markers, associated with thorough neurological and clinical assessment. Reasons for not acquiring MRI were mainly due to claustrophobia or scanner unavailability.ConclusionThis is an exceptional opportunity to have comparative large‐scale databases, with anatomical and functional brain imaging from different populations, allowing us to study real world diverse brain data and better understand its relationships with demographics, health and risk characteristics, and cognition.

AbstractBackgroundThe Alzheimer’s Association and Society for Nuclear Medicine and Molecular Imaging convened a Workgroup to update previous Appropriate Use Criteria (AUC) for amyloid PET (Johnson 2013) and develop the first AUC for tau PET. The AUC represent general guidelines and should not be considered a substitute for clinical judgment exercised in the care of individual patients.MethodThe Workgroup included 14 researchers with multidisciplinary expertise. Meetings were held between June 2020 and August 2021. Key research questions were identified using the PICOTS framework, triggering an independent systematic literature review. Using established methods (Fitch 2001), the Workgroup identified 17 clinical scenarios in which amyloid/tau PET may be considered. Appropriateness of amyloid and tau PET as independent, stand‐alone modalities were ranked for each scenario using a 9‐point scale (Table 1). Consensus was achieved using a modified Delphi process. Online surveys were completed iteratively by Workgroup members, followed by discussion, until all votes for each scenario fell within one of the following categories: Appropriate/Uncertain/Rarely Appropriate.ResultAs an over‐arching principle, amyloid/tau PET should be considered in patients who: (1) have undergone a comprehensive assessment by a dementia expert; (2) Alzheimer’s disease (AD) is a diagnostic possibility but uncertainty remains; and (3) knowledge of amyloid/tau PET results is expected to help establish diagnosis and guide patient management. Consensus ratings for clinical scenarios are shown in Table 2. More evidence was available to inform recommendations for amyloid than tau PET. Amyloid PET was considered “Appropriate” to inform diagnosis of MCI or dementia due to suspected AD; clarify diagnosis when CSF biomarkers are equivocal; to inform prognosis in MCI; and to determine eligibility for amyloid‐targeting therapies. Tau PET was considered “Appropriate” to clarify diagnosis in patients with MCI/dementia under age 65 or those with atypical presentations; and to inform prognosis in MCI or dementia due to suspected AD.ConclusionThe updated AUC highlight a growing role for amyloid PET and an emerging role for tau PET in the clinical evaluation of cognitively impaired patients. AUC are expected to further evolve based on data from ongoing studies of clinical utility and a rapidly developing therapeutic landscape.

Abstract Alzheimer's disease (AD) staging criteria lack standardized, empirical description. Well‐defined AD staging criteria are an important consideration in protocol design, influencing a more standardized inclusion/exclusion criteria and defining what constitutes meaningful differentiation among the stages. However, many trials are being designed on the basis of biomarker features and the two need to be coordinated. The Alzheimer's Association Research Roundtable (AARR) Spring 2021 meeting discussed the implementation of preclinical AD staging criteria, and provided recommendations for how they may best be incorporated into clinical trials research. Discussion also included what currently available tools for global clinical trials may best define populations in preclinical AD trials, and if are we able to differentiate preclinical from clinical stages of the disease. Well‐defined AD staging criteria are key to improving early detection, diagnostics, clinical trial enrollment, and identifying statistically significant clinical changes, and researchers discussed how emerging blood biomarkers may help with more efficient screening in preclinical stages.

Abstract INTRODUCTION Magnetic 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. METHODS We 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. RESULTS The 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. DISCUSSION The EOAD‐signature atrophy is a reliable and clinically valid biomarker of AD‐related neurodegeneration that could be used in clinical trials for EOAD. Highlights We 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.

ImportanceIncreased white matter hyperintensity (WMH) volume is a common magnetic resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) and late-onset Alzheimer disease (LOAD), but it remains unclear whether increased WMH along the AD continuum is reflective of AD-intrinsic processes or secondary to elevated systemic vascular risk factors.ObjectiveTo estimate the associations of neurodegeneration and parenchymal and vessel amyloidosis with WMH accumulation and investigate whether systemic vascular risk is associated with WMH beyond these AD-intrinsic processes.Design, Setting, and ParticipantsThis cohort study used data from 3 longitudinal cohort studies conducted in tertiary and community-based medical centers—the Dominantly Inherited Alzheimer Network (DIAN; February 2010 to March 2020), the Alzheimer’s Disease Neuroimaging Initiative (ADNI; July 2007 to September 2021), and the Harvard Aging Brain Study (HABS; September 2010 to December 2019).Main Outcome and MeasuresThe main outcomes were the independent associations of neurodegeneration (decreases in gray matter volume), parenchymal amyloidosis (assessed by amyloid positron emission tomography), and vessel amyloidosis (evidenced by cerebral microbleeds [CMBs]) with cross-sectional and longitudinal WMH.ResultsData from 3960 MRI sessions among 1141 participants were included: 252 pathogenic variant carriers from DIAN (mean [SD] age, 38.4 [11.2] years; 137 [54%] female), 571 older adults from ADNI (mean [SD] age, 72.8 [7.3] years; 274 [48%] female), and 318 older adults from HABS (mean [SD] age, 72.4 [7.6] years; 194 [61%] female). Longitudinal increases in WMH volume were greater in individuals with CMBs compared with those without (DIAN: t = 3.2 [P = .001]; ADNI: t = 2.7 [P = .008]), associated with longitudinal decreases in gray matter volume (DIAN: t = −3.1 [P = .002]; ADNI: t = −5.6 [P &amp;lt; .001]; HABS: t = −2.2 [P = .03]), greater in older individuals (DIAN: t = 6.8 [P &amp;lt; .001]; ADNI: t = 9.1 [P &amp;lt; .001]; HABS: t = 5.4 [P &amp;lt; .001]), and not associated with systemic vascular risk (DIAN: t = 0.7 [P = .40]; ADNI: t = 0.6 [P = .50]; HABS: t = 1.8 [P = .06]) in individuals with ADAD and LOAD after accounting for age, gray matter volume, CMB presence, and amyloid burden. In older adults without CMBs at baseline, greater WMH volume was associated with CMB development during longitudinal follow-up (Cox proportional hazards regression model hazard ratio, 2.63; 95% CI, 1.72-4.03; P &amp;lt; .001).Conclusions and RelevanceThe findings suggest that increased WMH volume in AD is associated with neurodegeneration and parenchymal and vessel amyloidosis but not with elevated systemic vascular risk. Additionally, increased WMH volume may represent an early sign of vessel amyloidosis preceding the emergence of CMBs.

AbstractIntroductionOne goal of the Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) is to investigate the genetic etiology of early onset (40–64 years) cognitive impairment. Toward this goal, LEADS participants are screened for known pathogenic variants.MethodsLEADS amyloid‐positive early‐onset Alzheimer's disease (EOAD) or negative early‐onset non‐AD (EOnonAD) cases were whole exome sequenced (N = 299). Pathogenic variant frequency in APP, PSEN1, PSEN2, GRN, MAPT, and C9ORF72 was assessed for EOAD and EOnonAD. Gene burden testing was performed in cases compared to similar‐age cognitively normal controls in the Parkinson's Progression Markers Initiative (PPMI) study.ResultsPreviously reported pathogenic variants in the six genes were identified in 1.35% of EOAD (3/223) and 6.58% of EOnonAD (5/76). No genes showed enrichment for carriers of rare functional variants in LEADS cases.DiscussionResults suggest that LEADS is enriched for novel genetic causative variants, as previously reported variants are not observed in most cases.Highlights Sequencing identified eight cognitively impaired pathogenic variant carriers. Pathogenic variants were identified in PSEN1, GRN, MAPT, and C9ORF72. Rare variants were not enriched in APP, PSEN1/2, GRN, and MAPT. The Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) is a key resource for early‐onset Alzheimer's genetic research

Abstract INTRODUCTION We aimed to describe baseline amyloid‐beta (Aβ) and tau‐positron emission tomograrphy (PET) from Longitudinal Early‐onset Alzheimer's Disease Study (LEADS), a prospective multi‐site observational study of sporadic early‐onset Alzheimer's disease (EOAD). METHODS We analyzed baseline [18F]Florbetaben (Aβ) and [18F]Flortaucipir (tau)‐PET from cognitively impaired participants with a clinical diagnosis of mild cognitive impairment (MCI) or AD dementia aged < 65 years. Florbetaben scans were used to distinguish cognitively impaired participants with EOAD (Aβ+) from EOnonAD (Aβ−) based on the combination of visual read by expert reader and image quantification. RESULTS 243/321 (75.7%) of participants were assigned to the EOAD group based on amyloid‐PET; 231 (95.1%) of them were tau‐PET positive (A+T+). Tau‐PET signal was elevated across cortical regions with a parietal‐predominant pattern, and higher burden was observed in younger and female EOAD participants. DISCUSSION LEADS data emphasizes the importance of biomarkers to enhance diagnostic accuracy in EOAD. The advanced tau‐PET binding at baseline might have implications for therapeutic strategies in patients with EOAD. HIGHLIGHTS 72% of patients with clinical EOAD were positive on both amyloid‐ and tau‐PET. Amyloid‐positive patients with EOAD had high tau‐PET signal across cortical regions. In EOAD, tau‐PET mediated the relationship between amyloid‐PET and MMSE. Among EOAD patients, younger onset and female sex were associated with higher tau‐PET.

AbstractINTRODUCTIONThe Rey Auditory Verbal Learning Test (RAVLT) is a useful neuropsychological test for describing episodic memory impairment in dementia. However, there is limited research on its utility in early‐onset Alzheimer's disease (EOAD). We assess the influence of amyloid and diagnostic syndrome on several memory scores in EOAD.METHODSWe transcribed RAVLT recordings from 303 subjects in the Longitudinal Early‐Onset Alzheimer's Disease Study. Subjects were grouped by amyloid status and syndrome. Primacy, recency, J‐curve, duration, stopping time, and speed score were calculated and entered into linear mixed effects models as dependent variables.RESULTSCompared with amyloid negative subjects, positive subjects exhibited effects on raw score, primacy, recency, and stopping time. Inter‐syndromic differences were noted with raw score, primacy, recency, J‐curve, and stopping time.DISCUSSIONRAVLT measures are sensitive to the effects of amyloid and syndrome in EOAD. Future work is needed to quantify the predictive value of these scores.Highlights RAVLT patterns characterize various presentations of EOAD and EOnonAD Amyloid impacts raw score, primacy, recency, and stopping time Timing‐based scores add value over traditional count‐based scores