Onyike, Chiadi U.

AbstractBackgroundThe overarching goal of the Longitudinal Early‐onset Alzheimer Disease study (LEADS) is to optimally characterize early‐onset AD (EOAD) and establish an EOAD clinical trials network. Here we report the baseline demographic and imaging biomarker comparisons of the LEADS cohort to late‐onset AD (LOAD) subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI3).Method123 amyloid‐positive EOAD, 47 amyloid‐negative EOnonAD, 60 cognitively normal young controls were compared to 130 amyloid‐positive LOAD, 110 amyloid‐negative LOnonAD and 286 amyloid‐negative cognitively normal older controls. To account for the effect of cognitive aging between EO and LO populations, each cognitive measure was Z‐transformed. Cortical and hippocampal atrophy were quantified using W‐scores adjusted for age, sex and total intracranial volume. Z‐scores and W‐scores were compared using t‐test or Wilcoxson rank test as appropriate. All p‐values were corrected for multiple comparisons using the false discovery rate correction.ResultEOAD showed greater pathology burden and greater cortical atrophy (AD signature) relative to LOAD. EOAD also showed greater cognitive impairment across all cognitive tests. EOAD showed greater functional impairment, more depression but less neuropsychiatric behaviors overall compared to LOAD (Table 1 and Figure 1, all ps<0.05). Repeating the analyses stratified by cognitive stage (MCI/dementia) or CDR global rating (0.5/1) did not result in any major differences.EOnonAD differed from LOnonAD by also showing greater impairment on all cognitive and functional measures There were no significant differences in amyloid and tau burden, or atrophy W‐scores between these groups. EOnonAD were more depressed and showed more functional impairment compared to LOnonAD (Table 2 and Figure 2, all ps<0.05). Repeating the analyses split by cognitive stage (MCI/dementia) or CDR global rating (0.5/1) did not result in any major differences.ConclusionConsistent with our preexisting hypotheses, EOAD and EOnonAD perform much worse relative to their LO counterparts. EOAD also show greater pathological burden as expected. The reported analyses were done in chronological rather than disease time (time since disease onset). Benchmarking individuals along the disease spectrum might prove to be a better strategy especially when conducting analyses on rate of disease progression.

AbstractIntroductionCaregivers of patients with frontotemporal lobar degeneration (FTLD) spectrum disorders experience tremendous burden, which has been associated with the neuropsychiatric and behavioral features of the disorders.MethodsIn a sample of 558 participants with FTLD spectrum disorders, we performed multiple‐variable regressions to identify the behavioral features that were most strongly associated with caregiver burden, as measured by the Zarit Burden Interview, at each stage of disease.ResultsApathy and disinhibition, as rated by both clinicians and caregivers, as well as clinician‐rated psychosis, showed the strongest associations with caregiver burden, a pattern that was consistent when participants were separated cross‐sectionally by disease stage. In addition, behavioral features appeared to contribute most to caregiver burden in patients with early dementia.DiscussionCaregivers should be provided with early education on the management of the behavioral features of FTLD spectrum disorders. Interventions targeting apathy, disinhibition, and psychosis may be most useful to reduce caregiver burden.

Abstract At present, no research criteria exist for the diagnosis of prodromal behavioural variant frontotemporal dementia (bvFTD), though early detection is of high research importance. Thus, we sought to develop and validate a proposed set of research criteria for prodromal bvFTD, termed ‘mild behavioural and/or cognitive impairment in bvFTD’ (MBCI-FTD). Participants included 72 participants deemed to have prodromal bvFTD; this comprised 55 carriers of a pathogenic mutation known to cause frontotemporal lobar degeneration, and 17 individuals with autopsy-confirmed frontotemporal lobar degeneration. All had mild behavioural and/or cognitive changes, as judged by an evaluating clinician. Based on extensive clinical workup, the prodromal bvFTD group was divided into a Development Group (n = 22) and a Validation Group (n = 50). The Development Group was selected to be the subset of the prodromal bvFTD group for whom we had the strongest longitudinal evidence of conversion to bvFTD, and was used to develop the MBCI-FTD criteria. The Validation Group was the remainder of the prodromal bvFTD group and was used as a separate sample on which to validate the criteria. Familial non-carriers were included as healthy controls (n = 165). The frequencies of behavioural and neuropsychiatric features, neuropsychological deficits, and social cognitive dysfunction in the prodromal bvFTD Development Group and healthy controls were assessed. Based on sensitivity and specificity analyses, seven core features were identified: apathy without moderate-severe dysphoria, behavioural disinhibition, irritability/agitation, reduced empathy/sympathy, repetitive behaviours (simple and/or complex), joviality/gregariousness, and appetite changes/hyperorality. Supportive features include a neuropsychological profile of impaired executive function or naming with intact orientation and visuospatial skills, reduced insight for cognitive or behavioural changes, and poor social cognition. Three core features or two core features plus one supportive feature are required for the diagnosis of possible MBCI-FTD; probable MBCI-FTD requires imaging or biomarker evidence, or a pathogenic genetic mutation. The proposed MBCI-FTD criteria correctly classified 95% of the prodromal bvFTD Development Group, and 74% of the prodromal bvFTD Validation Group, with a false positive rate of &lt;10% in healthy controls. Finally, the MBCI-FTD criteria were tested on a cohort of individuals with prodromal Alzheimer’s disease, and the false positive rate of diagnosis was 11–16%. Future research will need to refine the sensitivity and specificity of these criteria, and incorporate emerging biomarker evidence.

AbstractPatients with early‐onset Alzheimer's disease (EOAD) are commonly excluded from large‐scale observational and therapeutic studies due to their young age, atypical presentation, or absence of pathogenic mutations. The goals of the Longitudinal EOAD Study (LEADS) are to (1) define the clinical, imaging, and fluid biomarker characteristics of EOAD; (2) develop sensitive cognitive and biomarker measures for future clinical and research use; and (3) establish a trial‐ready network. LEADS will follow 400 amyloid beta (Aβ)‐positive EOAD, 200 Aβ‐negative EOnonAD that meet National Institute on Aging–Alzheimer's Association (NIA‐AA) criteria for mild cognitive impairment (MCI) or AD dementia, and 100 age‐matched controls. Participants will undergo clinical and cognitive assessments, magnetic resonance imaging (MRI), [18F]Florbetaben and [18F]Flortaucipir positron emission tomography (PET), lumbar puncture, and blood draw for DNA, RNA, plasma, serum and peripheral blood mononuclear cells, and post‐mortem assessment. To develop more effective AD treatments, scientists need to understand the genetic, biological, and clinical processes involved in EOAD. LEADS will develop a public resource that will enable future planning and implementation of EOAD clinical trials.

AbstractBackgroundPrevious research has suggested that, compared to males, females are at greater risk for and have greater pathology burden in late onset. However, sex differences in early onset AD (EOAD) have not yet been studied.MethodWe included 167 participants [28 cognitively normal (CN, 68% females), 98 early onset AD (EOAD, 55% females), and 41 cognitively impaired amyloid‐negative (EOnonAD, 31% females] subjects from the Longitudinal Early‐Onset AD Study (LEADS) with available Flortaucipir PET, Florbetaben PET, and MRI data. Multiple linear regression (MLR) models including age and MMSE as covariates were used in the pooled sample to examine the effects of sex on hippocampal and white matter hyperintensity volume, mean cortical thickness, mean tau distribution by Braak regions and mean cortical amyloid SUVR. We also ran voxelwise MLR with sex as the predictor and cortical thickness, amyloid SUVR normalized to whole cerebellum, tau SUVR normalized to cerebellar crus, respectively, as the outcome measures while controlling for age, MMSE, and total intracranial volume (MRI only). Results are displayed at a cluster‐level FWE correction of p<0.05.ResultThere were no significant demographic differences between males and females in any diagnostic group. Across the pooled sample females showed significantly greater atrophy of the hippocampus (p=0.0001), greater tau SUVR in Braak regions 3&4 (p=0.05) and 5&6 (p=0.04) and trend for greater global amyloid uptake (p=0.074) (Table 2). The analyses in imaging space confirmed these findings and showed that the effects are driven by the EOAD group. Females showed greater amyloid deposition globally and greater tau deposition in the frontal, inferior parietal and temporal lobes (Figure 3).ConclusionFemale sex is associated with greater pathology burden in EOAD. Longitudinal studies will be needed to establish whether such difference translates in faster rates of progression in women relative to men.

AbstractBackgroundApproximately 5% of the 5.6 million (∼280,000) Americans with Alzheimer’s disease (AD) develop symptoms at age 65 or younger and are classified as having early‐onset AD (EOAD). Although EOAD and late‐onset AD (LOAD) share the same pathologic substrate, there are notable differences in their clinical and biological phenotypes. The Longitudinal Early‐onset AD study (LEADS) is a multi‐site, observational clinical and biomarker study of EOAD. In the present study we utilized the currently available LEADS imaging data to explore the spatial extent and magnitude of neurodegeneration EOADMethod95 amyloid positive patients with EOAD, 37 amyloid negative cognitively impaired patients (EOnonAD) , and 55 cognitively unimpaired controls (CNs) were included in the analysis. The magnitude of cortical thinning in the EOAD and EOnonAD groups was estimated using whole‐brain GLMs compared to the CN group. In addition, w‐scores were derived for each EOAD patient for these ROIs: average cortical thickness, hippocampal volume, AD‐signature cortical thickness (typically used in LOAD), and precuneus cortical thickness controlling for age, sex, and acquisition site. The utility of each ROI to differentiate EOAD patients from CNs was assessed by calculating the percentage of patients falling below a W‐threshold of ‐1.5.ResultIn EOAD, a distributed pattern of cortical thinning was observed in lateral temporal, parietal, and frontal cortex (p<.01), and was most prominent in the precuneus (Cohen’s d’ = 1.5). In the EOnonAD group, cortical thinning was observed but was highly variable across individuals. The w‐score analysis in the EOAD group yielded the following results: Mean Cortical thickness: Mean = ‐3.34, SD = 2.97, Classification = 72%.; Hippocampal volume: Mean = ‐2.96, SD = 2.39, Classification = 74%; AD Signature: Mean = ‐4.63, SD = 3.07, Classification = 80%; Precuneus: Mean = ‐5.98, SD = 4.1, Classification = 90%.ConclusionOur results are consistent with previous findings demonstrating cortical thinning in lateral parietal, precuneus, and lateral temporal lobes in EOAD with relatively less involvement of the medial temporal lobes. Our results also suggest that the precuneus may be especially vulnerable to neurodegeneration in patients with EOAD and may serve as a useful biomarker for patient classification.

AbstractBackgroundMeasuring changes in the earliest phases of familial frontotemporal lobar degeneration (f‐FTLD) and estimating symptom onset has important implications for clinical care. Early stage clinical trials have begun for f‐FTD, but the low prevalence of f‐FTLD mutation carriers and heterogeneous symptomology challenges trial design. Bayesian disease progression models (DPM) incorporate clinical data, neuroimaging metrics, and fluid biomarker concentrations to estimate latent disease age, providing estimates of symptom onset and progression status. Such models may facilitate enrollment in studies (i.e., inclusion of presymptomatic individuals) and provide more powerful analysis methods for trials.MethodA Bayesian latent variable repeated measures model was used to estimate disease progression, conditional on latent disease age (proximity to symptom onset), in 275 participants with mutations in GRN (n=68), MAPT (n=80) and C9orf72 (n=127). Median follow‐up was one year (range: 0‐4). Jointly modeled longitudinal variables included neuropsychological scores, CDR®+NACC‐FTLD box score, 3T MRI frontotemporal brain volumes, and plasma levels of neurofilament light chain (NfL). Sample size estimates for detecting treatment effects were generated by varying thresholds of estimated proximity to symptom onset.ResultThe Bayesian DPM provided a clear picture of clinical and neurological progression within each mutation group. Neuroimaging and NfL captured early progression rates (1 SD from controls) 5‐10 years before symptom onset. After symptom onset, CDR®+NACC‐FTLD box score was the most sensitive measure of disease progression. GRN mutation carriers had the largest annual progression rates (and lowest variability) compared to MAPT and C9orf72. Between 5 years pre‐ and 10 years post‐onset, CDR®+NACC‐FTLD box score progressed by 2 units/year (SD=2.7) in GRN mutation carriers ‐ almost twice the rate of progression in MAPT (M=1.2;SD=2.5) and C9orf72 (M=1.1;SD=2.2) mutation carriers. Compared to a trial enrolling only early symptomatic cases (CDR®+NACC‐FTLD=0.5 or 1), utilizing latent disease age would facilitate enrollment of asymptomatic cases with the same power.ConclusionBased on an estimation of symptom onset, Bayesian DPMs suggest clinical trials in GRN mutation carriers would require the smallest sample sizes. Furthermore, leveraging these DPMs would allow novel, powerful trial designs that may facilitate greater participant enrollment.

AbstractBackgroundPlasma NfL is a sensitive marker of axonal injury that is elevated in symptomatic FTLD and asymptomatic carriers of FTLD‐associated genetic mutations at short‐term risk of phenoconversion to mild behavioral or cognitive impairment or dementia. In carriers of FTLD‐associated genetic mutations, NfL is associated with clinical measures of disease severity.MethodPlasma NfL was measured using single molecule array technology in baseline blood samples from 290 participants in the ARTFL/LEFFTDS consortia. Participants included 181 asymptomatic mutation carriers (C9orf72, GRN, and MAPT); 45 with mild impairment (MBI/MCI), and 64 with dementia. 103 family members without FTLD‐associated mutations served as asymptomatic controls. Social cognition scales were obtained through clinical evaluation at baseline, year 1, and year 2. Stepwise linear regressions assessed NfL relationships with baseline social cognition measures. Linear mixed models were used to test the ability of baseline NfL to predict longitudinal changes. Analyses corrected for age, sex, and genotype.ResultAt baseline, plasma NfL correlated with all measures of social cognition, regardless of genotype. Associations were strongest for the Revised Self‐monitoring Scale (RSMS;β = ‐.50, p < .001), total score of the Social Norms questionnaire (β= .48, p < .001), and caregiver burden (Zarit burden;β = .55, p < .001). Regardless of disease severity, baseline NfL related to worse RSMS scores over time (‐3.7 points at year 2/ LogNfL unit increase, 95% CI ‐1.7 to ‐5.7, p < .001). In MBI/MCI, higher baseline NfL was associated with worse longitudinal scores on the Social Norms questionnaire (‐5.9 points at year 2/LogNfL unit increase, 95% CI ‐1.1 to ‐10.7, p = .016). No associations were seen in asymptomatic non‐carriers.ConclusionIn this familial FTLD cohort, plasma NfL is correlated with clinical measures of social cognition and caregiver burden. Higher baseline plasma NfL concentrations are associated with worsening self‐monitoring and social norms scores over time. These associations suggest that NfL is correlated with clinically meaningful measures that may be relevant to therapeutic development.

AbstractBackgroundWhite matter (WM) hypointensity volume in T1 MRI correlates strongly with T2 hyperintensities and both are typically associated with advancing age and vascular brain injury (VBI). Recent research has suggested that Alzheimer’s Disease (AD) neuropathologic changes (ADNC) also increases WM hypointensity volume. Sporadic early onset AD (EOAD) patients provide a unique model to examine the relationship between ADNC biomarkers and WM hypointensity volume in the absence of advanced age, cardiovascular injury, or autosomal dominant genetic mutations.MethodIncluded in the analysis were sporadic EOAD patients (n = 75) and cognitively normal controls (n = 39) from the Longitudinal Alzheimer’s Disease Study (LEADS) for whom full demographic and health information were available. WM hypointensity volume in T1 MRI was segmented by Freesurfer and corrected for total white matter volume. Multiple‐factor ANOVA models with logarithmic transformations were used to determine the effects of age, cohort, and presence of cardiovascular conditions on WM hypointensity volume. Further multiple‐factor ANOVA models assessed whether the addition of covariates improved the model fit.ResultIn a reproduction of prior research, WM hypointensity volume was correlated with age for controls (p < 0.05), but not for EOAD patients. We additionally found an effect of cohort, such that EOAD patients had a higher mean WM hypointensity volume than controls when accounting for age (p < 0.05). No difference in the presence or number of cardiovascular conditions was found between groups. Additionally, no correlation was found between WM hypointensity volume and the presence or number of cardiovascular conditions. Including cardiovascular condition as a covariate failed to improve the model fit, even when accounting for interaction effects.ConclusionThese results support the hypothesis that patients with ADNC have higher WM hypointensity volume beyond what would be expected based on aging or cardiovascular risk factors. Further research is needed to assess the co‐localization of WM hypointensities with cortical degradation, amyloid pathology, and tau pathology.

AbstractBackgroundPrevious studies have reported that age modifies the distribution and burden of tau (and, to a lesser extent, amyloid) pathology in sporadic Alzheimer’s disease (AD). Here we present preliminary baseline amyloid and tau PET results from the Longitudinal Early‐Onset Alzheimer’s Disease Study (LEADS), a multi‐site longitudinal study of sporadic early‐onset AD.Method135 patients meeting clinical criteria for MCI or probable AD and 50 cognitively normal controls (all age<65 at enrollment) were enrolled at 12 US centers between August 2018 and December 2019 (Table 1). 18F‐Florbetaben amyloid‐PET (FBB) was used to assign patients to EOAD (amyloid‐positive) or EOnonAD (amyloid‐negative) subgroups based on visual rating and semi‐quantification. 130 patients and all controls had 18F‐Flortaucipir tau‐PET (FTP). Regional Standardized Uptake Value Ratios (SUVR) for FBB (whole cerebellum reference) and FTP (inferior cerebellar gray reference) were extracted using co‐registered 3T‐MRI.Result98 patients (72.6%) were amyloid PET‐positive (EOAD) and 37 (27.4%) were amyloid PET‐negative (EOnonAD). Compared to EOAD, EOnonAD patients had higher MMSE, MOCA and CDR sum‐of‐boxes (CDR‐SB) and were more frequently male (Table 1). Patients with EOAD showed elevated FBB and FTP SUVR in temporoparietal and frontal cortex compared to CN and EOnonAD (Figures 1‐2). In EOAD, MMSE, MOCA and CDR‐SB were significantly correlated with FTP SUVR (Figure 3), while no significant correlations were found with FBB SUVR. EOnonAD patients showed variable FTP binding ranging from negative to mildly elevated binding in anterior temporal and frontal cortex and underlying white matter. Two EOnonAD cases showed intense FTP binding comparable to typical EOAD cases, despite visually and quantitatively negative FBB scans.ConclusionPatients with clinically mild, sporadic EOAD typically show an extensive distribution and burden of tau pathology in the setting of positive amyloid PET. Global clinical measures correlate with tau but not amyloid PET. Over 25% of patients meeting clinical criteria for early‐onset MCI/probable AD have negative amyloid PET, suggesting alternative etiologies for cognitive decline. These findings will inform future design of drug trials in this important and under‐studied population.