Gatsonis, Constantine

AbstractBackgroundThe Longitudinal Early‐onset Alzheimer Disease study (LEADS) aims to robustly characterize biomarkers of early‐onset AD (EOAD). Here we quantified white matter hyperintensities (WMH) in EOAD and compared the volume of WMH with that of cognitively normal (CN) and amyloid‐negative early‐onset dementia (EOnonAD) groups.MethodsWe compared WMH of 194 amyloid‐positive EOAD, 59 amyloid‐negative EOnonAD, and 88 cognitively normal participants. WMH in left and right frontal, temporal, parietal, and occipital regions was compared between the group, as well as the sum total in each hemisphere. For distributional considerations, the logarithm of the WMHs was used in the analyses. Group comparisons were performed using t‐tests. Analyses of variance were used to compare the groups after correcting for the effects of age, sex, and education. Linear regression analyses were used to investigate the association between cognitive impairment and WMH using age, sex, and education as covariates. Cognitive impairment was measured using the Mini‐Mental State Exam (MMSE) and Clinical Dementia Rating (CDR) scale sum of boxes (CDR‐sb). All p‐values were corrected for multiple comparisons using the false discovery rate method.ResultsEOAD showed greater WMH compared with both CN and EOnonAD groups across all regions. This relationship holds after correcting for the effects of age, sex, and education (see Figure 1 and Table 1, all p‐values < 0.05). No significant differences were observed between WMHs of CN and EOnonAD groups. Higher WMH values were associated with greater cognitive impairment: MMSE (b = ‐1.69, p‐value <0.0001) and CDR‐sb (b = 0.45, p‐value <0.0001).ConclusionsEOAD consistently show higher WMH compared to their CN and EOnonAD peers. The extent of WMH in CN and EOnonAD groups is similar. No differences in regional distribution were observed, with EOAD having higher WMH across all brain regions. Higher WMHs were associated with worse cognitive impairment measured both using MMSE and CDR sum of boxes.

AbstractBackgroundPreviously, we found that female sex is associated with greater pathology burden in early‐onset Alzheimer’s disease (EOAD) in the Longitudinal EOAD Study (LEADS). Here, we have expanded our analyses by adding APOE‐ε4 carrier status as a further predictor of EOAD pathologic burden.MethodWe included 180 EOAD LEADS participants with available APOE genotype, Flortaucipir PET, Florbetaben PET, and MRI data. Demographic and biomarker differences were analyzed using ANOVA. EOAD participants were split by sex and APOE‐ε4 carrier status. Box plots were created in R and a voxel‐wise multiple linear regression in SPM12 yielded statistical brain maps of gray matter density (GMD), amyloid and tau burden.ResultCompared to males, EOAD females showed significantly greater global amyloid uptake (mean SUVR, p=0.002) and greater tau SUVR in the MetaROI, Braak 3&4 and 5&6 regions (p=0.0007, p=0.001, p=0.01, resp., Table 1). Female APOE‐ε4 carriers showed greater tau SUVR in Braak regions 1&2 than female non‐carriers (p<0.01, Figure 2B). Male APOE‐ε4 carriers showed trend‐level thinner entorhinal cortex than male non‐carriers (p=0.06, Figure 1). Interestingly however, femaleAPOE‐ε4 non‐carriers showed greater global amyloid SUVR than female carriers (p<0.01, Figure 2A). Further, APOE‐ε4 non‐carriers showed significantly thinner medial temporal cortices than carriers in both sexes (M, p<0.05; F, p<0.01). Male APOE‐ε4 non‐carriers also showed significantly lower mean cortical thickness than male carriers (p<0.05, Figure 1). Female APOE‐ε4 non‐carriers showed trend‐level lower mean cortical thickness than female carriers (p=0.06, Figure 1). The FWE corrected SPM12 maps showed significantly greater GM atrophy in the right temporal lobe and greater amyloid burden in a right lateralized occipitoparietal pattern in female APOE‐ε4 non‐carriers compared to female carriers. Further, male APOE‐ε4 non‐carriers showed greater tau uptake in the left frontal lobe than male carriers (Figure 3).ConclusionThese results suggest that APOE‐ε4 non‐carrier status is associated with greater atrophy, amyloid and tau deposition in EOAD. This might be due to the presence of other strong genetic drivers of disease pathology in EOAD.

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.

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.

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.

Purpose To compare magnetic resonance imaging (MRI) and computed tomography (CT) with each other and to International Federation of Gynecology and Obstetrics (FIGO) clinical staging in the pretreatment evaluation of early invasive cervical cancer, using surgicopathologic findings as the reference standard. Patients and Methods This prospective multicenter clinical study was conducted by the American College of Radiology Imaging Network and the Gynecologic Oncology Group from March 2000 to November 2002; 25 United States health centers enrolled 208 consecutive patients with biopsy-confirmed cervical cancer of FIGO stage ≥ IB who were scheduled for surgery based on clinical assessment. Patients underwent FIGO clinical staging, helical CT, and MRI. Surgicopathologic findings constituted the reference standard for statistical analysis. Results Complete data were available for 172 patients; surgicopathologic findings were consistent with FIGO stages IA to IIA in 76% and stage ≥ IIB in 21%. For the detection of advanced stage (≥ IIB), sensitivity was poor for FIGO clinical staging (29%), CT (42%), and MRI (53%); specificity was 99% for FIGO clinical staging, 82% for CT, and 74% for MRI; and negative predictive value was 84% for FIGO clinical staging, 84% for CT, and 85% for MRI. MRI (area under the receiver operating characteristic curve [AUC], 0.88) was significantly better than CT (AUC, 0.73) for detecting cervical tumors (P = .014). For 85% of patients, FIGO clinical staging forms were submitted after MRI and/or CT was performed. Conclusion CT and MRI performed similarly; both had lower staging accuracy than in prior single-institution studies. Accuracy of FIGO clinical staging was higher than previously reported. The temporal data suggest that FIGO clinical staging was influenced by CT and MRI findings.