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Digital pathology (DP) has transformative potential, especially for Alzheimer disease and related disorders. However, infrastructure barriers may limit adoption. To provide benchmarks and insights into implementation barriers, a survey was conducted in 2019 within National Institutes of Health's Alzheimer's Disease Centers (ADCs). Questions covered infrastructure, funding sources, and data management related to digital pathology. Of the 35 ADCs to which the survey was sent, 33 responded. Most respondents (81%) stated that their ADC had digital slide scanner access, with the most frequent brand being Aperio/Leica (62.9%). Approximately a third of respondents stated there were fees to utilize the scanner. For DP and machine learning (ML) resources, 41% of respondents stated none was supported by their ADC. For scanner purchasing and operations, 50% of respondents stated they received institutional support. Some were unsure of the file size of scanned digital images (37%) and total amount of storage space files occupied (50%). Most (76%) were aware of other departments at their institution working with ML; a similar (76%) percentage were unaware of multiuniversity or industry partnerships. These results demonstrate many ADCs have access to a digital slide scanner; additional investigations are needed to further understand hurdles to implement DP and ML workflows.

Alzheimer’s disease (AD) is neuropathologically characterized by the intracellular accumulation of hyperphosphorylated tau and the extracellular deposition of amyloid-β plaques, which affect certain brain regions in a progressive manner. The locus coeruleus (LC), a small nucleus in the pons of the brainstem, is widely recognized as one of the earliest sites of neurofibrillary tangle formation in AD. Patients with AD exhibit significant neuronal loss in the LC, resulting in a marked reduction of its size and function. The LC, which vastly innervates several regions of the brain, is the primary source of the neurotransmitter norepinephrine (NE) in the central nervous system. Considering that NE is a major modulator of behavior, contributing to neuroprotection and suppression of neuroinflammation, degeneration of the LC in AD and the ultimate dysregulation of the LC–NE system has detrimental effects in the brain. In this review, we detail the neuroanatomy and function of the LC, its essential role in neuroprotection, and how this is dysregulated in AD. We discuss AD-related neuropathologic changes in the LC and mechanisms by which LC neurons are selectively vulnerable to insult. Further, we elucidate the neurotoxic effects of LC de-innervation both locally and at projection sites, and how this augments disease pathology, progression and severity. We summarize how preservation of the LC–NE system could be used in the treatment of AD and other neurodegenerative diseases affected by LC degeneration.

Additional file 1: Table S1. Search strategy. Table S2. Strategies followed to reduce the risk of bias. Table S3. List of fields covered for the collection of the data (data extraction template). Table S4. Reasons for excluding candidate records (inclusion stage in the study-selection flow). Table S5. Frequency of the hippocampal-sparing AD subtype – comparison of findings when using hippocampus versus entorhinal cortex for subtyping.

Additional file 1: Table S1. Single biomarker models evaluating the utility of neuroimaging measures for predicting cognitive performance after accounting for age, sex, education, and number of clinical visits.

Additional file 1.

Poster presented at the 10th International Congress on Non-Motor Dysfunctions in Parkinson’s Disease and Related Disorders.ABSTRACT[Background] Multiple system atrophy (MSA) is pathologically classified as an a-synucleinopathy. Patients with a-synucleinopathies commonly present with symptoms such as parkinsonism, autonomic dysfunction, or rapid eye movement sleep behavior disorder (RBD). Unlike Parkinson disease dementia or dementia with Lewy body patients, cognitive impairment is not a common feature of MSA. Focusing on RBD, we compared clinicopathologic features of MSA with or without RBD.[Method] We retrospectively analyzed clinical information on 125 consecutive MSA patients in the Mayo Clinic Jacksonville Brain Bank. 33 cases were excluded because of insufficient clinical records. 92 patients were divided into two groups; with or without RBD. We defined RBD patients as a polysomnography-confirmed or clinically probable RBD. All cases underwent a standardized neuropathology assessment for a-synuclein, amyloid b, and tau pathologies.[Results] 33 patients presented with RBD (36%). Patients with RBD had an earlier onset of symptoms (55.4 ± 7.3 vs 60.8 ± 10.8 years, P = 0.011) and longer disease duration (9.4 ± 4.0 vs 6.9 ± 3.1 years, P = 0.005). Patients with RBD had more frequent cognitive dysfunction (58% vs 27%, P = 0.004), visual hallucinations (21% vs 7%, P = 0.042), and pathologic laughing and/or crying (27% vs 3%, P = 0.007). Braak neurofibrillary tangle stage, Thal b-amyloid phase, or presence of Lewy body pathology did not differ between groups. [Conclusion] In our series, MSA patients with RBD differed clinically from MSA patient without RBD. Interestingly, cognitive dysfunction could not be explained by coexisting Alzheimer or Lewy body pathology.

Additional file 1: Supplementary Text This file includes detailed methods on the acquisition of the neuropathology phenotypes

Frontotemporal lobar degeneration with neuronal inclusions of the TAR DNA-binding protein 43 (FTLD-TDP) represents the most common pathological subtype of FTLD. We established the international FTLD-TDP whole-genome sequencing consortium to thoroughly characterize the known genetic causes of FTLD-TDP and identify novel genetic risk factors. Through the study of 1131 unrelated Caucasian patients, we estimated that C9orf72 repeat expansions and GRN loss-of-function mutations account for 25.5% and 13.9% of FTLD-TDP patients, respectively. Mutations in TBK1 (1.5%) and other known FTLD genes (1.4%) were rare, and the disease in 57.7% of FTLD-TDP patients was unexplained by the known FTLD genes. To unravel the contribution of common genetic factors to the FTLD-TDP etiology in these patients, we conducted a two-stage association study comprising the analysis of whole-genome sequencing data from 517 FTLD-TDP patients and 838 controls, followed by targeted genotyping of the most associated genomic loci in 119 additional FTLD-TDP patients and 1653 controls. We identified three genome-wide significant FTLD-TDP risk loci: one new locus at chromosome 7q36 within the DPP6 gene led by rs118113626 (p value = 4.82e-08, OR = 2.12), and two known loci: UNC13A, led by rs1297319 (p value = 1.27e-08, OR = 1.50) and HLA-DQA2 led by rs17219281 (p value = 3.22e-08, OR = 1.98). While HLA represents a locus previously implicated in clinical FTLD and related neurodegenerative disorders, the association signal in our study is independent from previously reported associations. Through inspection of our whole-genome sequence data for genes with an excess of rare loss-of-function variants in FTLD-TDP patients (n ≥ 3) as compared to controls (n = 0), we further discovered a possible role for genes functioning within the TBK1-related immune pathway (e.g., DHX58, TRIM21, IRF7) in the genetic etiology of FTLD-TDP. Together, our study based on the largest cohort of unrelated FTLD-TDP patients assembled to date provides a comprehensive view of the genetic landscape of FTLD-TDP, nominates novel FTLD-TDP risk loci, and strongly implicates the immune pathway in FTLD-TDP pathogenesis.

IntroductionWe sought to establish the relationships between standard postmortem measures of AD neuropathology and antemortem [11C]PIB-positron emission tomography ([11C]PIB-PET) analyzed with the Centiloid (CL) method, a standardized scale for Aβ-PET quantification.MethodsFour centers contributed 179 participants encompassing a broad range of clinical diagnoses, PET data, and autopsy findings.ResultsCL values increased with each CERAD neuritic plaque score increment (median -3 CL for no plaques and 92 CL for frequent plaques) and nonlinearly with Thal Aβ phases (increases were detected starting at phase 2) with overlap between scores/phases. PET-pathology associations were comparable across sites and unchanged when restricting the analyses to the 56 patients who died within 2years of PET. A threshold of 12.2 CL detected CERAD moderate-to-frequent neuritic plaques (area under the curve=0.910, sensitivity=89.2%, specificity=86.4%), whereas 24.4 CL identified intermediate-to-high AD neuropathological changes (area under the curve=0.894, sensitivity=84.1%, specificity=87.9%).DiscussionOur study demonstrated the robustness of a multisite Centiloid [11C]PIB-PET study and established a range of pathology-based CL thresholds.

Figure S1 a Module-trait relationships are presented for patients with an expanded C9orf72 repeat and patients without this repeat (C9Plus vs. C9Minus). b For patients with an expansion and control subjects (C9Plus vs. Control), module-trait relationships are plotted. These plots are generated with weighted gene co-expression network analysis (WGCNA) to find groups of genes that go up (red) or down (blue) together. A unique color has been assigned to each of these groups, also called a module. Correlations and p-values are shown for variables of interest, including disease group (C9Plus, C9Minus, and/or Control; arrow), neurons, microglia, astrocytes, oligodendrocytes, endothelial cells, RNA integrity number (RIN), age at death, sex, and plate. The strongest correlations (brightest colors) are observed for cell types. Notably, both module-trait relationship plots are based on residuals obtained without adjustment for cell-type-specific markers. Figure S2 a With adjustment for cell-type-specific markers, a cluster dendrogram is shown for C9orf72 expansion carriers and control subjects. b For the same comparison, a cluster dendrogram is displayed without adjustment for cell-type-specific markers. The branches in these dendrograms correspond to specific modules. A unique color has been assigned to each of these modules. Additionally, variables of interest are included, such as the disease group, neurons, microglia, astrocytes, oligodendrocytes, endothelial cells, RNA integrity number (RIN), age at death, sex, and plate. High levels are shown in red and low levels in blue. After adjustment, no striking differences are observed based on cell type; without adjustment, however, modules appear to be associated with certain cell types (e.g., turquoise and neurons). Figure S3 a For patients harboring a C9orf72 repeat expansion and those without this expansion (C9Plus vs. C9Minus; module membership > 0.6 and significance < 1.0E-05), a gene network is displayed. b A gene network is visualized when examining expansion carriers and controls (C9Plus vs. Control; module membership > 0.6 and significance < 1.0E-05). In these network plots, the connectivity of each gene is represented by the size of its node, the module to which it has been assigned by its color, and the strength of the correlation by the thickness of its edges; the C9orf72 gene is denoted by an arrow. Of note, the plots in this figure have been generated without adjustment for cell-type-specific markers. Figure S4 a-d Trends are displayed for patients carrying a C9orf72 repeat expansion. a The first plot shows VEGFA and age at onset. b CDKL1 and C9orf72 expansion size are shown in the second plot. c The third plot displays EEF2K and poly(GP) levels. In these three plots, the solid blue line denotes the linear regression line, while each individual is represented by a solid dark grey circle. d The last plot shows SGSM3 levels and survival after onset, when comparing the bottom 50% (solid salmon line) to the top 50% (solid turquoise line). These plots have been created using residuals unadjusted for differences in cellular composition. Figure S5 a-h The expression levels of VEGFA, CDKL1, EEF2K, and SGSM3 are shown for all disease groups: patients with a C9orf72 repeat expansion (C9Plus), patients without this expansion (C9Minus), and control subjects (Control), both with and without adjustment for cell-type-specific markers. For each box plot, the median is represented by a solid black line, and each box spans the interquartile range (IQR; 25th percentile to 75th percentile). Figure S6 a-h This figure displays the correlation between our expression assays (relative expression) and RNA sequencing data (residuals). a-b The first two plots show correlations for VEGFA, either with or without adjustment for cell-type-specific markers. c-d The next two plots visualize correlations for CDKL1, both with and without adjustment for cellular composition. e-f EEF2K is displayed on the next plots, again with and without adjustment for surrogate markers. g-h The last two plots show correlations for SGSM3 with and without adjustment for cellular composition. For each of these plots, the solid blue line denotes the linear regression line, while each individual is represented by a solid dark grey circle. (PDF 2894 kb)

BackgroundLoss-of-function mutations in GRN cause frontotemporal lobar degeneration (FTLD). Patients with GRN mutations present with a uniform subtype of TAR DNA-binding protein 43 (TDP-43) pathology at autopsy (FTLD-TDP type A); however, age at onset and clinical presentation are variable, even within families. We aimed to identify potential genetic modifiers of disease onset and disease risk in GRN mutation carriers.MethodsThe study was done in three stages: a discovery stage, a replication stage, and a meta-analysis of the discovery and replication data. In the discovery stage, genome-wide logistic and linear regression analyses were done to test the association of genetic variants with disease risk (case or control status) and age at onset in patients with a GRN mutation and controls free of neurodegenerative disorders. Suggestive loci (p

Figures S1 through S10. Figure S1. Transcript expression of Tmem106b in Tmem106b deficiency mice at different ages. Figure S2. Tmem106b reduction does not alter the expression of its family members. Figure S3. Tmem106b immunoreactivity in mice with Tmem106b gene interruption using an additional antibody. Figure S4. The body weight of 2R and 66R injected mouse. Figure S5. Tmem106b reduction alone induces astrogliosis. Figure S6. Heterozygous loss of Tmem106b partially rescues 66R injection-induced neuronal loss. Figure S7. pTdp-43 immunoreactivity in 2R and 66R injected mouse brain. Figure S8. Endogenous C9orf72 protein levels in 2R- and 66R-injected mouse brain. Figure S9. Validation of (GGGGCC)66 repeat overexpression and C9ORF72 knockdown. Figure S10. The effect of (GGGGCC)66 overexpression or C9ORF72 knockdown on TMEM106B protein levels in U251 cells. (DOCX 26231 kb)

Table S1. Quantitative assessment of DPR density by color deconvolution algorithm in clinicopathologic subgroups of C9ORF72-related disease. In frontal cortex, p = 0.019, FTLD vs. FTLD-MND. In CA4, p = 0.055, FTLD vs. FTLD-MND. In CA2/3, p = 0.03, FTLD vs. FTLD-MND. Significant p-values (

ObjectiveTo assess the efficacy of [18F]AV1451 PET in visualizing tau pathology in vivo in a patient with frontotemporal dementia (FTD) associated with the V337M microtubule-associated protein tau (MAPT) mutation.MethodsMAPT mutations are associated with the deposition of hyperphosphorylated tau protein in neurons and glia. The PET tracer [18F]AV1451 binds with high affinity to paired helical filaments tau that comprises neurofibrillary tangles in Alzheimer disease (AD), while postmortem studies suggest lower or absent binding to the tau filaments of the majority of non-AD tauopathies. We describe clinical, structural MRI, and [18F]AV1451 PET findings in a V337M MAPT mutation carrier affected by FTD and pathologic findings in his affected mother and in an unrelated V337M MAPT carrier also affected with FTD. The biochemical similarity between paired helical filament tau in AD and MAPT V337M predicts that the tau pathology associated with this mutation constitutes a compelling target for [18F]AV1451 imaging.ResultsWe found a strong association between topography and degree of [18F]AV1451 tracer retention in the proband and distribution of tau pathology in the brain of the proband's mother and the unrelated V337M mutation carrier. We also found a significant correlation between the degree of regional MRI brain atrophy and the extent of [18F]AV1451 binding in the proband and a strong association between the proband's clinical presentation and the extent of regional brain atrophy and tau accumulation as assessed by structural brain MRI and [18F]AV1451PET.ConclusionOur study supports the usefulness of [18F]AV1451 to characterize tau pathology in at least a subset of pathogenic MAPT mutations.

Detailed Patient Demographics and Results of ARG Scoring. (PDF 74 kb)

Alzheimer's disease (AD) researchers commonly use MRI as a quantitative measure of disease severity. Historically, hippocampal volume has been favored. Recently, "AD signature" measurements of gray matter (GM) volumes or cortical thicknesses have gained attention. Here, we systematically evaluate multiple thickness- and volume-based candidate-methods side-by-side, built using the popular FreeSurfer, SPM, and ANTs packages, according to the following criteria: (a) ability to separate clinically normal individuals from those with AD; (b) (extent of) correlation with head size, a nuisance covariatel (c) reliability on repeated scans; and (d) correlation with Braak neurofibrillary tangle stage in a group with autopsy. We show that volume- and thickness-based measures generally perform similarly for separating clinically normal from AD populations, and in correlation with Braak neurofibrillary tangle stage at autopsy. Volume-based measures are generally more reliable than thickness measures. As expected, volume measures are highly correlated with head size, while thickness measures are generally not. Because approaches to statistically correcting volumes for head size vary and may be inadequate to deal with this underlying confound, and because our goal is to determine a measure which can be used to examine age and sex effects in a cohort across a large age range, we thus recommend thickness-based measures. Ultimately, based on these criteria and additional practical considerations of run-time and failure rates, we recommend an AD signature measure formed from a composite of thickness measurements in the entorhinal, fusiform, parahippocampal, mid-temporal, inferior-temporal, and angular gyrus ROIs using ANTs with input segmentations from SPM12.

We describe a recently recognized disease entity, limbic-predominant age-related TDP-43 encephalopathy (LATE). LATE neuropathological change (LATE-NC) is defined by a stereotypical TDP-43 proteinopathy in older adults, with or without coexisting hippocampal sclerosis pathology. LATE-NC is a common TDP-43 proteinopathy, associated with an amnestic dementia syndrome that mimicked Alzheimer's-type dementia in retrospective autopsy studies. LATE is distinguished from frontotemporal lobar degeneration with TDP-43 pathology based on its epidemiology (LATE generally affects older subjects), and relatively restricted neuroanatomical distribution of TDP-43 proteinopathy. In community-based autopsy cohorts, ∼25% of brains had sufficient burden of LATE-NC to be associated with discernible cognitive impairment. Many subjects with LATE-NC have comorbid brain pathologies, often including amyloid-β plaques and tauopathy. Given that the 'oldest-old' are at greatest risk for LATE-NC, and subjects of advanced age constitute a rapidly growing demographic group in many countries, LATE has an expanding but under-recognized impact on public health. For these reasons, a working group was convened to develop diagnostic criteria for LATE, aiming both to stimulate research and to promote awareness of this pathway to dementia. We report consensus-based recommendations including guidelines for diagnosis and staging of LATE-NC. For routine autopsy workup of LATE-NC, an anatomically-based preliminary staging scheme is proposed with TDP-43 immunohistochemistry on tissue from three brain areas, reflecting a hierarchical pattern of brain involvement: amygdala, hippocampus, and middle frontal gyrus. LATE-NC appears to affect the medial temporal lobe structures preferentially, but other areas also are impacted. Neuroimaging studies demonstrated that subjects with LATE-NC also had atrophy in the medial temporal lobes, frontal cortex, and other brain regions. Genetic studies have thus far indicated five genes with risk alleles for LATE-NC: GRN, TMEM106B, ABCC9, KCNMB2, and APOE. The discovery of these genetic risk variants indicate that LATE shares pathogenetic mechanisms with both frontotemporal lobar degeneration and Alzheimer's disease, but also suggests disease-specific underlying mechanisms. Large gaps remain in our understanding of LATE. For advances in prevention, diagnosis, and treatment, there is an urgent need for research focused on LATE, including in vitro and animal models. An obstacle to clinical progress is lack of diagnostic tools, such as biofluid or neuroimaging biomarkers, for ante-mortem detection of LATE. Development of a disease biomarker would augment observational studies seeking to further define the risk factors, natural history, and clinical features of LATE, as well as eventual subject recruitment for targeted therapies in clinical trials.

Alzheimer's disease and related dementias (ADRDs) are a global crisis facing the aging population and society as a whole. With the numbers of people with ADRDs predicted to rise dramatically across the world, the scientific community can no longer neglect the need for research focusing on ADRDs among underrepresented ethnoracial diverse groups. The Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART; alz.org/ISTAART) comprises a number of professional interest areas (PIAs), each focusing on a major scientific area associated with ADRDs. We leverage the expertise of the existing international cadre of ISTAART scientists and experts to synthesize a cross-PIA white paper that provides both a concise “state-of-the-science” report of ethnoracial factors across PIA foci and updated recommendations to address immediate needs to advance ADRD science across ethnoracial populations.

TDP-43 is a well known RNA binding protein involved in the pathogenesis of Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Lobar Dementia (FTLD). In physiological conditions, TDP-43 mainly localizes in the nucleus and shuttles, at least in neurons, to the cytoplasm to form TDP-43 RNA granules. In the nucleus, TDP-43 participates to the expression and splicing of RNAs, while in the cytoplasm its functions range from transport to translation of specific mRNAs. However, if loss or gain of these TDP-43 functions are affected in ALS/FTLD pathogenesis is not clear. Here, we report that TDP-43 localizes on ribosomes not only in primary neurons but also in SH-SY5Y human neuroblastoma cells. We find that binding of TDP-43 to the translational machinery is mediated by an interaction with a specific ribosomal protein, RACK1, and that an increase in cytoplasmic TDP-43 represses global protein synthesis, an effect which is rescued by overexpression of RACK1. Ribosomal loss of RACK1, which excludes TDP-43 from the translational machinery, remarkably reduces formation of TDP-43 cytoplasmic inclusions in neuroblastoma cells. Finally, we corroborate the interaction between TDP-43 and RACK1 on polyribosomes of neuroblastoma cells with mis-localization of RACK1 on TDP-43 positive cytoplasmic inclusions in motor neurons of ALS patients. In conclusions, results from this study suggest that TDP-43 represents a translational repressor not only for specific mRNAs but for overall translation and that its binding to polyribosomes through RACK1 may promote, under conditions inducing ALS pathogenesis, the formation of cytoplasmic inclusions.