Boeve, Bradley F.

AbstractBackgroundMedial temporal lobe (MTL) atrophy is an early feature of multiple neurodegenerative diseases. In genetic frontotemporal lobar degeneration (FTLD, i.e. individuals carrying GRN, MAPT, or C9orf72 mutations), MTL atrophy can occur 10‐15 years before symptom onset. We aimed to better characterize MTL atrophy patterns in presymptomatic and symptomatic genetic FTLD using a multi‐atlas segmentation pipeline that allows precise measurement of MTL subregions.MethodParticipants included a diagnostically mixed sample of familial FTLD mutation carriers (MAPT: N=87; C9orf72: N=117; GRN: N=65) and 142 non‐carrier family member controls from the ALLFTD study cohort (Table 1). T1‐weighted MRIs were preprocessed using a multi‐atlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS]) to segment the amygdala, anterior and posterior hippocampus, and MTL cortices: entorhinal cortex (ERC), perirhinal cortex or Brodmann areas (BA) 35 and 36, and parahippocampal cortex (PHC). Following rigorous quality control and manual correction (Figure 1), we assessed bilateral volume differences in mutation carriers compared to controls, adjusted for age, sex, and total intracranial volume. Analyses were conducted separately for symptomatic (FTLD‐Clinical Dementia Rating Global Score&ge;0.5) and presymptomatic (Global Score=0) mutation carriers.ResultOut of 413 scans, 317 (76.8%) segmentations passed quality control while 94 (22.8%) needed some manual edits—this was more common in symptomatic than presymptomatic carriers (32% versus 15%, p=0.001). Three scans were excluded (<1%; 2 complete scans, 1 for selected subregions) due to insufficient landmark visibility in symptomatic GRN and MAPT carriers. In symptomatic carriers, all MTL subregions demonstrated reduced volume compared to controls, although MAPT carriers exhibited particularly marked atrophy, especially in anterior MTL subregions (Table 2; amygdala, ERC, BA35, hippocampus). Presymptomatic MAPT and C9orf72 carriers also exhibited significant atrophy of primarily anterior MTL cortices, while presymptomatic GRN carriers only exhibited significantly smaller ERC volume compared to controls.ConclusionMTL atrophy is present in genetic FTLD across mutation carriers, even at the presymptomatic stage. Anterior MTL subregions, which are also susceptible to neuropathologic accumulation in early Alzheimer’s disease and Limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC), tend to be more vulnerable than posterior subregions. Unsurprisingly, MAPT carriers show the greatest MTL atrophy compared to controls across groups.

AbstractBackgroundDementia with Lewy bodies (DLB) frequently co‐occurs with Alzheimer’s disease (AD) pathologies, exacerbating disease progression. Biophysical models of diffusion imaging data, such as Neurite Orientation Dispersion and Density Imaging (NODDI), may reveal novel insights into the neurobiological substrates of AD on cortical and white matter microstructural injury.MethodA cohort of 57 DLB patients on the DLB spectrum (33 clinically probable DLB and 14 prodromal DLB) and 57 cognitively unimpaired (CU) controls underwent NODDI and PET imaging with [18F]‐Flortaucipir and [11C]‐PiB (Table 1). NODDI parameters were derived from white matter tracts and grey matter regions using the JHU “Eve” and Mayo Clinic Adult Lifespan Template atlases, respectively. Conditional logistic models were used to compare these parameters between the two groups, accounting for the 1:1 matching on age and sex. The associations of tau and amyloid‐β with NODDI parameters across the white matter tracts were examined with linear regressions. A region‐by‐region approach was adopted to evaluate the relationships of tau and amyloid‐β with grey matter NODDI, adjusting for age, APOE, and local grey matter volumes.ResultDLB spectrum patients exhibited extensive white matter abnormalities relative to CU, including lower fractional anisotropy, higher mean diffusivity (MD), and lower tissue‐weighted neurite density (tNDI). In grey matter, these deficits were paralleled with higher MD and lower tNDI and ODI, primarily in the temporoparietal and posterior cortices. Regression models revealed significant associations of elevated [18F]‐Flortaucipir uptake with deficits in temporal and limbic white matter tracts and a temporal‐lobe pattern of higher MD and lower tNDI in the cortex (Figure 1). No associations were observed with [11C]‐PiB in the DLB spectrum.ConclusionThese findings demonstrated an in vivo relationship between tau deposition and neurite deficits that spatially aligned with the canonical AD “cortical signature” of neurodegeneration in both white matter tracts and grey matter regions in DLB. Our study underscores the detrimental impact of AD pathology in DLB and provides a rationale for further investigations into the underlying mechanisms of AD in DLB. Future longitudinal studies tracking the progression of these changes could inform therapeutic strategies for DLB in the presence of AD pathologies

AbstractBackgroundPatterns of regional atrophy and hypometabolism have been observed in dementia with Lewy bodies (DLB). However, determinants of regional vulnerability to structural and functional neurodegeneration remain largely unexplored. First, we investigated the association between regional gene expression and grey matter volumes in probable DLB patients. Since hypometabolism presumably precedes overt brain atrophy, we additionally investigate the association between regional gene expression and hypometabolism in DLB.MethodTo investigate the association between gene expression and regional volumes, 165 DLB patients along with 165 age‐ and sex‐matched healthy controls from three European centres and the Mayo Clinic (USA) were included. Regional volumes were quantified from MRI using SPM12 in 112 cortical, subcortical, and cerebellar brain regions, and compared between groups, using w‐scores. Regional expression data of seven genes involved in the formation and degradation of pathological protein aggregates (APOE, APP, BIN1, GBA, MAPT, SNCA, TMEM175) was extracted from six healthy donors from the Allen Human Brain Atlas and correlated with regional volumetric w‐scores. To assess the predictive value of regional gene expression on regional volumes we used Gaussian stepwise backwards linear regression including all seven genes as predictors. To investigate the association between gene expression and hypometabolism, we are currently applying the same analysis pipeline to FDG‐PET data of 139 DLB patients from 8 European centres.ResultMost brain regions showed lower volumes in DLB patients compared to healthy controls, with differences being most pronounced in occipital and parietal lobes. Regional expression of APOE correlated positively with regional volumes in DLB. Conversely, regional expression of MAPT correlated negatively with regional volumes. Both APOE and MAPT gene expression were significant predictors of regional volumes in the regression analysis. None of the other gene expression values was significantly associated with regional volumes in DLB.ConclusionOur findings show that regional expression of genes associated with the abnormal accumulation of amyloid and tau, common co‐pathologies in DLB, partially account for the brain atrophy pattern observed in DLB patients. Analyses are ongoing for the hypometabolism pattern. Our finding emphasises the relevance of co‐pathologies in predicting atrophy progression and identifying potential targets for future disease‐modifying treatments.

AbstractBackgroundLate‐Onset Alzheimer’s Disease (LOAD) is characterized by genetic heterogeneity and there is no single model explaining the genetic mode of inheritance. To date, more than 70 genetic loci associated with AD have been identified but they explain only a small proportion of AD heritability. Structural variants (SVs) may explain some of the missing AD heritability, and specifically, their segregation in AD families has yet to be investigated.MethodWe analyzed WGS data from 197 NHW families (926 subjects, 58.5% affected) and 214 CH families (1,340 subjects, 59.17% affected). Manta, Absinthe, and MELT were used for large insertions/deletions calling from short‐read WGS, combined with Sniffles2 calls from 4 ONT‐sequenced genomes and an external SV call set from HGSVC on 32 PacBio‐sequenced genomes from the 1000 Genomes Project. Genotyping produced a unified project‐level VCF. We identified 45,251 insertions and 76,566 deletions genome‐wide. Variants were tested for segregation and pathogenicity using Annot‐SV, cadd‐SV, and Variant Effect Predictor. Segregation required SV presence in all affected family members and only in unaffected members five years younger than average disease onset.ResultWe identified 453 insertions and 598 deletions segregating in 78.68% and 87.31% of NHW families, respectively. In CH families, 432 insertions and 460 deletions were segregating in 75.23% and 72.90% of the families, respectively. Genes overlapping with the SVs exhibited high expression levels in brain tissues. Notably, around 93% of insertions and 76% of deletions segregating in NHW and CH families were less than 1 kilobase pair (1kbp) in length. A total of 79 insertions and 96 deletions were found to be segregating in both NHW and CH families. Interestingly, a segregating insertion was observed in CH families overlapping within the CACNA2D3 gene, which was previously reported in a CH GWAS for clinical AD. A deletion segregating in NHW overlapped with the PSEN1, and another in a CH family overlapped with the PTK2B gene.ConclusionOur findings suggested that there are several SVs associated with familial AD across CH and NHW families. Prioritizing the SVs based on their effects on gene function and expression will be helpful in understanding their contributions in AD.

AbstractBackgroundUnderstanding the relationship between AβPET and AβCSF biomarkers will define their potential utility in Aβ treatment. Few longitudinal or neuropathological comparisons have been reported. We assessed the relationship of AβPET and AβCSF biomarkers in a large community cohort.MethodParticipants 50+ years with coincident AβPET and AβCSF biomarkers (pTau181/Aβ42, n=505, and Aβ42/40, n=54) were included. Of these participants, a subgroup was identified that had neuropathology data (n=47) of which many had longitudinal AβPET and CSF testing. The relationships of AβPET and CSF biomarkers were assessed cross‐sectionally in all participants and longitudinally in those with autopsy data. Analyses were performed using AβPET Meta‐ROI and AβPET early‐Aβ‐deposition ROIs (ROIs with early Aβ deposition: fusiform, angular, inferior temporal, middle temporal, middle occipital, and calcarine).ResultIn biomarker tests performed at the same time, more participants were AβPET+ and CSF‐ than AβPET‐ and CSF+ using Meta‐ROI AβPET. This discordance occurred more frequently when using early‐Aβ‐deposition regions (Figure 1). Of 47 participants with autopsy data, 35 had Thal stage ≥1. The sensitivity for earliest detection of cortical Aβ neuropathology by AβPET was 89% (31/35) and by CSF was 66%, (23/35). Eight of these 35 had positive AβPET findings and negative coincident CSF tests at the first time tested. Of these, 5/8 were Meta‐ROI and early AβPET ROI positive. The other 3/8 were only positive on early‐Aβ AβPET ROIs. Four of the 8 with negative CSF and positive AβPET had subsequent testing and 2/4 became positive on CSF tests after 1.5 years while 2/4 continued to be negative on subsequent testing.ConclusionAβPET is more sensitive for detection of early cortical Aβ deposition than CSF biomarkers in cross‐sectional or autopsy data. While the assessment of AβPET by standard Meta‐ROI AβPET methods showed cortical Aβ deposition occurring when not indicated by CSF biomarkers, AβPET ROIs for early Aβ deposition detected additional participants that were AβPET positive and AβCSF negative. These findings have implications for detecting early Aβ neuropathology among CU participants in Aβ prevention trials when robust detection is needed. Further work is needed to compare Aβ plasma biomarkers and AβPET using these methods.

AbstractBackgroundAutopsy studies in Lewy Body Disease (LBD) indicate that cardiac sympathetic denervation precedes Lewy body pathology and neuronal loss in the brain. Myocardial 123I‐metaiodobenzylguanidine (MIBG) scintigraphy noninvasively assesses postganglionic cardiac sympathetic denervation in LBD and is considered an important biomarker in the international diagnostic criteria of Dementia with Lewy Bodies and Parkinson’s Disease (PD). Despite the internationally recognized importance of MIBG scintigraphy in LBD, its use in neurodegenerative disorders is not FDA approved for this indication and is rarely used in the US for neurological research. We sought to add MIBG scintigraphy to our multimodal imaging research in prodromal LBD. We launched pilot MIBG scintigraphy study in isolated REM Sleep Behavior Disorder (iRBD) individuals, who are typically regarded as representing evolving LBD.MethodWe conducted MIBG scintigraphy and 123I‐FP‐CIT SPECT in seven individuals with iRBD including two RBD with mild cognitive impairment (MCI), one with PD, and one healthy control (mean age of 71.5±8.3). Heart‐to‐mediastinum (H/M) ratio of the MIBG uptake on delayed image (3‐4 hours after Adreview® injection) was calculated with MIM. Cutoff value of 1.68 was used for determining abnormal H/M ratio (Yoshita et al, 2006). Nigrostriatal dopamine transporter uptake was evaluated with DaTQUANT 2.0 software.ResultFour iRBD participants including two RBD with MCI had abnormal MIBG scintigraphy (mean age 73.5±8.6, delayed H/M ratio 1.25±0.29)) and three iRBD participants had a normal scan (mean age 67.8±4.5, delayed H/M ratio 2.57±0.25). Delayed H/M ratio was 1.00 for the PD participant and 2.60 for healthy control participant. Among the four iRBD participants with abnormal MIBG scintigraphy, one participant had 123I‐FP‐CIT SPECT with DaTQUANT putamen z‐score <‐2.0 and three participants had z‐score in the range of ‐1.5 and ‐1.0. All iRBD participants with normal MIBG scintigraphy had normal 123I‐FP‐CIT SPECT with DaTQUANT putamen z‐score >‐1.0.ConclusionMIBG scintigraphy was abnormal in half of this small cohort. Our preliminary data suggests its utility in detecting early signs of evolving LBD. Increasing the number of the MIBG scintigraphy in iRBD participants and controls are planned to determine if MIBG scintigraphy can facilitate early detection of progression for use in clinical trials targeting LBD.

AbstractBackgroundMedial temporal lobe (MTL) atrophy is an early feature of multiple neurodegenerative diseases. In genetic frontotemporal lobar degeneration (FTLD, i.e. individuals carrying GRN, MAPT, or C9orf72 mutations), MTL atrophy can occur 10‐15 years before symptom onset. We aimed to better characterize MTL atrophy patterns in presymptomatic and symptomatic genetic FTLD using a multi‐atlas segmentation pipeline that allows precise measurement of MTL subregions.MethodParticipants included a diagnostically mixed sample of familial FTLD mutation carriers (MAPT: N = 87; C9orf72: N = 117; GRN: N = 65) and 142 non‐carrier family member controls from the ALLFTD study cohort (Table 1). T1‐weighted MRIs were preprocessed using a multi‐atlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS]) to segment the amygdala, anterior and posterior hippocampus, and MTL cortices: entorhinal cortex (ERC), perirhinal cortex or Brodmann areas (BA) 35 and 36, and parahippocampal cortex (PHC). Following rigorous quality control and manual correction (Figure 1), we assessed bilateral volume differences in mutation carriers compared to controls, adjusted for age, sex, and total intracranial volume. Analyses were conducted separately for symptomatic (FTLD‐Clinical Dementia Rating Global Score≥0.5) and presymptomatic (Global Score = 0) mutation carriers.ResultOut of 413 scans, 317 (76.8%) segmentations passed quality control while 94 (22.8%) needed some manual edits—this was more common in symptomatic than presymptomatic carriers (32% versus 15%, p = 0.001). Three scans were excluded (<1%; 2 complete scans, 1 for selected subregions) due to insufficient landmark visibility in symptomatic GRN and MAPT carriers. In symptomatic carriers, all MTL subregions demonstrated reduced volume compared to controls, although MAPT carriers exhibited particularly marked atrophy, especially in anterior MTL subregions (Table 2; amygdala, ERC, BA35, hippocampus). Presymptomatic MAPT and C9orf72 carriers also exhibited significant atrophy of primarily anterior MTL cortices, while presymptomatic GRN carriers only exhibited significantly smaller ERC volume compared to controls.ConclusionMTL atrophy is present in genetic FTLD across mutation carriers, even at the presymptomatic stage. Anterior MTL subregions, which are also susceptible to neuropathologic accumulation in early Alzheimer’s disease and Limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC), tend to be more vulnerable than posterior subregions. Unsurprisingly, MAPT carriers show the greatest MTL atrophy compared to controls across groups.

Abstract Background Many proposed clinical decision support systems (CDSS) require multiple disparate data elements as input, which makes implementation difficult, and furthermore have a black‐box nature leading to low interpretability. Fluorodeoxyglucose Positron Emission Tomography (FDG‐PET) is an established modality for the diagnosis of dementia, and a CDSS that uses only an FDG‐PET image to produce a reliable and understandable result would ease both of these challenges to clinical application. Method A deep variational autoencoder (VAE) was used to extract a latent representation of each image through prior training from FDG‐PET brain images (n=2000). This unsupervised VAE has a novel graph convolutional architecture that makes it applicable to masked template space images. A logistic regression model was used to classify each image. A parametric study of the latent space revealed the imaging features that were used in the logistic regression model to differentiate each class. A separate dataset of participants labeled with their clinical diagnosis (n=1239) was used to assess the logistic regression model’s diagnostic accuracy of cognitively unimpaired (CU) (n=679) and between common dementia subtypes: Alzheimer’s disease (AD) (n=310), Lewy body dementia (DLB) (n=151), and behavioral variant frontotemporal dementia (bvFTD) (n=99). The logistic regression classifier was evaluated using receiver‐operator characteristic (ROC‐AUC) curves. Result ROC‐AUC curves for CU and each dementia subtype are illustrated in Figure 1a. A k nearest neighbors model was used to develop a graphical representation of the latent space where nodes are images and edges are drawn between nearest neighbors, illustrated in Figure 1b. The graph of the latent space demonstrates a comparison between dementia subtypes and CU images. Conclusion In this study, we developed a proof‐of‐concept VAE that can achieve differential diagnosis with 84.8% balanced accuracy. The model architecture provides visual interpretability, and shows that the hippocampi, parietal lobes, and cerebellum, were useful for distinguishing AD, the frontal lobe, posterior cingulate cortex, and hippocampi were useful for distinguishing DLB, and prefrontal pole, subcortical structures, and occipital lobe were useful for distinguishing bvFTD. These regions of metabolism align with clinical pathology and metabolic patterns.

AbstractClinical outcome assessments (COAs) are an integral part of clinical trials. A fit‐for‐purpose COA with well‐selected endpoints can help determine the efficacy of a therapeutic intervention in the condition studied. The selection of the appropriate outcome measures depends not only on the condition but also on the disease stage and type of intervention studied.In Alzheimer’s disease (AD) the clinical benefit of anti‐amyloid therapies has been assessed using outcomes that are specifically designed to measure the progression of Alzheimer’s disease during the early stages of the disease.The enthusiasm to develop similar studies in Lewy body dementia (LBD) needs to be tempered with caution as there is no COA LBD that fully captures the progression of LBD, full symptom array, or impact of these upon function. This limitation has been partly met by the reliance on COAs developed for Alzheimer’s or Parkinson’s disease. However, these may not be valid or sensitive to treatment changes in LBD.The impact of LBD on other domains beyond cognition including behavior, movement, and sleep represents one of the major challenges when considering the development of an LBD‐specific scale that encapsulates the severity of the disease as a whole.During this presentation, we will discuss the limitations of the current outcome measures in LBD trials and what those developing a clinical trial focused on LBD in the near future need to be taken into consideration when deciding on a COA for disease‐modifying and symptomatic trials. We will also report on the current efforts to develop the Lewy Body Dementia‐Domain Rating Scale (LBD‐DRS), an LBD‐specific scale to be utilized in disease‐modifying therapy trials.

AbstractBackgroundThe earliest cognitive manifestations of asymptomatic and prodromal familial frontotemporal dementia (f‐FTD) mutation carriers are still being characterized. Patients with symptomatic FTD are known to be error prone, particularly on tasks of executive function, but little is known about the frequency or predictive utility of these errors in the earliest stages of f‐FTD. The current study compared error rates on executive functioning tasks in controls and asymptomatic and prodromal mutation carriers and investigated whether errors predict worsening clinical status as follow up.MethodThis study included 90 participants (mean age = 48.57, SD = 13.30; 51.1% female; 86.67% white) with pathogenic FTD mutations (C9orf72, n = 45; GRN, n = 30; or MAPT, n = 15) who were asymptomatic or prodromal (Clinical Dementia Rating plus FTLD; CDR®+NACC‐FTLD ≤ 0.5). Propensity score matching identified (CDR®+NACC‐FTLD = 0) who did not carry pathogenic mutation but were matched on age, education, and sex. Regressions were used to compare controls and mutation carriers on error scores (rule violations and/or repetitions) from three executive functioning tasks: design fluency, lexical fluency, and Stroop inhibition. Mutation carriers with longitudinal data within 1.5 years were binarized as stable (n = 35) or progressors (n = 13) based on whether their CDR®+NACC‐FTLD sum of boxes score was worse at follow up (mean follow up = 1.07 years). Regressions were fit to evaluate the relationship between baseline error scores and group (i.e., stable vs. progressor).ResultMutation carriers committed significantly more errors than controls on the Stroop task (β = 0.67, p = 0.03) and lexical fluency (repetitions: β = 0.27, p = 0.02). The groups did not significantly differ in errors on the remaining tasks. A greater number of Stroop errors predicted mutation carriers who progressed at follow up (β = 1.04, p<0.001). When introducing the primary outcome from each task as a covariate (e.g., correct responses), the fluency task (repetitions: β = 0.10, p = 0.03) and Stroop task (errors: β = 0.82, p<0.001) were significantly associated with progression.ConclusionErrors on executive tasks may be early cognitive features in familial FTD. Importantly, errors were uniquely predictive above and beyond total scores. Research in larger samples will enable investigations of genetic differences in error rates.