Eloyan, Ani

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.

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.

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.

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

AbstractINTRODUCTIONWe used sex and apolipoprotein E ε4 (APOE ε4) carrier status as predictors of pathologic burden in early‐onset Alzheimer's disease (EOAD).METHODSWe included baseline data from 77 cognitively normal (CN), 230 EOAD, and 70 EO non‐Alzheimer's disease (EOnonAD) participants from the Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS). We stratified each diagnostic group by males and females, then further subdivided each sex by APOE ε4 carrier status and compared imaging biomarkers in each stratification. Voxel‐wise multiple linear regressions yielded statistical brain maps of gray matter density, amyloid, and tau PET burden.RESULTSEOAD females had greater amyloid and tau PET burdens than males. EOAD female APOE ε4 non‐carriers had greater amyloid PET burdens and greater gray matter atrophy than female ε4 carriers. EOnonAD female ε4 non‐carriers also had greater gray matter atrophy than female ε4 carriers.DISCUSSIONThe effects of sex and APOE ε4 must be considered when studying these populations.HIGHLIGHTS Novel analysis examining the effects of biological sex and apolipoprotein E ε4 (APOE ε4) carrier status on neuroimaging biomarkers among early‐onset Alzheimer's disease (EOAD), early‐onset non‐AD (EOnonAD), and cognitively normal (CN) participants. Female sex is associated with greater pathology burden in the EOAD cohort compared to male sex. The effect of APOE ε4 carrier status on pathology burden was the most impactful in females across all cohorts.

Abstract INTRODUCTION We compared white matter hyperintensities (WMHs) in early‐onset Alzheimer's disease (EOAD) with cognitively normal (CN) and early‐onset amyloid‐negative cognitively impaired (EOnonAD) groups in the Longitudinal Early‐Onset Alzheimer's Disease Study. METHODS We investigated the role of increased WMH in cognition and amyloid and tau burden. We compared WMH burden of 205 EOAD, 68 EOnonAD, and 89 CN participants in lobar regions using t ‐tests and analyses of covariance. Linear regression analyses were used to investigate the association between WMH and cognitive impairment and that between amyloid and tau burden. RESULTS EOAD showed greater WMHs compared with CN and EOnonAD participants across all regions with no significant differences between CN and EOnonAD groups. Greater WMHs were associated with worse cognition. Tau burden was positively associated with WMH burden in the EOAD group. DISCUSSION EOAD consistently showed higher WMH volumes. Overall, greater WMHs were associated with worse cognition and higher tau burden in EOAD. Highlights This study represents a comprehensive characterization of WMHs in sporadic EOAD. WMH volumes are associated with tau burden from positron emission tomography (PET) in EOAD, suggesting WMHs are correlated with increasing burden of AD. Greater WMH volumes are associated with worse performance on global cognitive tests. EOAD participants have higher WMH volumes compared with CN and early‐onset amyloid‐negative cognitively impaired (EOnonAD) groups across all brain regions.

AbstractIntroductionOne goal of the Longitudinal Early Onset Alzheimer's Disease Study (LEADS) is to define the fluid biomarker characteristics of early‐onset Alzheimer's disease (EOAD).MethodsCerebrospinal fluid (CSF) concentrations of Aβ1‐40, Aβ1‐42, total tau (tTau), pTau181, VILIP‐1, SNAP‐25, neurogranin (Ng), neurofilament light chain (NfL), and YKL‐40 were measured by immunoassay in 165 LEADS participants. The associations of biomarker concentrations with diagnostic group and standard cognitive tests were evaluated.ResultsBiomarkers were correlated with one another. Levels of CSF Aβ42/40, pTau181, tTau, SNAP‐25, and Ng in EOAD differed significantly from cognitively normal and early‐onset non‐AD dementia; NfL, YKL‐40, and VILIP‐1 did not. Across groups, all biomarkers except SNAP‐25 were correlated with cognition. Within the EOAD group, Aβ42/40, NfL, Ng, and SNAP‐25 were correlated with at least one cognitive measure.DiscussionThis study provides a comprehensive analysis of CSF biomarkers in sporadic EOAD that can inform EOAD clinical trial design.