AbstractBackgroundUsing an objective mathematical algorithm to assess corticolimbic involvement of neurofibrillary tangle pathology, we identified three AD subtypes: hippocampal sparing (HpSp) AD, typical AD, and limbic predominant AD. Typical AD brains were representative of the expected patterns of hippocampal and cortical involvement as outlined by Braak tangle stage. In contrast, we discovered an extreme phenotype that exists outside of the Braakian‐concept of neurofibrillary tangle patterns. Hippocampal sparing AD cases demonstrate unexpected sparing of the hippocampus relative to severely involved association cortices and limbic predominant AD cases demonstrate inundation of the hippocampus relative to mildly involved association cortices. Using these AD subtypes, our objective was to leverage our understanding of disease spectrum to uncover transcriptomic changes that underlie selective vulnerability of the hippocampus in AD.MethodWe performed RNA‐sequencing in 40 neuropathologically diagnosed AD cases (10 HpSp, 20 Typical and 10 Limbic) and 15 controls to uncover gene expression changes associated with phenotype differences allowing us to prioritize 44 genes for further exploration. Validation with NanoString and quantification with digital pathology were performed in an expanded cohort of 158 AD cases (36 HpSp, 79 Typical and 35 Limbic) and 32 controls. We quantified digital pathology measures of early tangle pathology (CP13), mature tangle pathology (Ab39), amyloid‐β (33.1.1). In addition, we measured cellular markers for microglia (CD68), endothelia (CD34), and astroglia (GFAP). Deep learning based prediction models were employed, which nominated the SLC38A2 gene as a predictor of AD.ResultThe SLC38A2 gene was originally prioritized in our RNA‐sequencing data based upon differential expression between controls and typical AD. We observed upregulation of SLC38A2 in all AD subtypes. RNA‐seq gene expression measures validated well with NanoString for SLC38A2 (R=0.97, p<0.001). Regression analysis identified early tangle (p=0.011) and late tangle measures (p=0.026) as significant predictors of gene expression, but not amyloid measures (p=0.74). Microgliosis approached significance (p=0.052), but with no contribution from endothelial cell burden (p=0.17) or astrogliosis (p=0.58). Age approached significance (p=0.06), but not sex (p=0.88) or APOE‐ε4 status (p=0.10).ConclusionOur data supports consideration of intra‐disease divergence with regard to case stratification and may reveal genes previously masked by heterogeneity of cohorts.
Structural Features of Small Molecules Targeting the RNA Repeat Expansion That Causes Genetically Defined ALS/FTD
ACS Chemical Biology | November 16, 2020 | Volume: 15 | Issue: 12 | Pages: 3112-3123
Abstract Introduction The cytoprotective PTEN‐induced kinase 1 (PINK1)‐parkin RBR E3 ubiquitin protein ligase (PRKN) pathway selectively labels damaged mitochondria with phosphorylated ubiquitin (pS65‐Ub) for their autophagic removal (mitophagy). Because dysfunctions of mitochondria and degradation pathways are early features of Alzheimer's disease (AD), mitophagy impairments may contribute to the pathogenesis. Methods Morphology, levels, and distribution of the mitophagy tag pS65‐Ub were evaluated by biochemical analyses combined with tissue and single cell imaging in AD autopsy brain and in transgenic mouse models. Results Analyses revealed significant increases of pS65‐Ub levels in AD brain, which strongly correlated with granulovacuolar degeneration (GVD) and early phospho‐tau deposits, but were independent of amyloid beta pathology. Single cell analyses revealed predominant co‐localization of pS65‐Ub with mitochondria, GVD bodies, and/or lysosomes depending on the brain region analyzed. Discussion Our study highlights mitophagy alterations in AD that are associated with early tau pathology, and suggests that distinct mitochondrial, autophagic, and/or lysosomal failure may contribute to the selective vulnerability in disease.
C9orf72 poly GA RAN-translated protein plays a key role in amyotrophic lateral sclerosis via aggregation and toxicity
Human Molecular Genetics | September 4, 2020 | Volume: 30 | Issue: 3-4 | Pages: 318-320
Abstract Alzheimer’s disease is characterized by the presence of amyloid-β and tau deposition in the brain, hippocampal atrophy and increased rates of hippocampal atrophy over time. Another protein, TAR DNA binding protein 43 (TDP-43) has been identified in up to 75% of cases of Alzheimer’s disease. TDP-43, tau and amyloid-β have all been linked to hippocampal atrophy. TDP-43 and tau have also been linked to hippocampal atrophy in cases of primary age-related tauopathy, a pathological entity with features that strongly overlap with those of Alzheimer’s disease. At present, it is unclear whether and how TDP-43 and tau are associated with early or late hippocampal atrophy in Alzheimer’s disease and primary age-related tauopathy, whether either protein is also associated with faster rates of atrophy of other brain regions and whether there is evidence for protein-associated acceleration/deceleration of atrophy rates. We therefore aimed to model how these proteins, particularly TDP-43, influence non-linear trajectories of hippocampal and neocortical atrophy in Alzheimer’s disease and primary age-related tauopathy. In this longitudinal retrospective study, 557 autopsied cases with Alzheimer’s disease neuropathological changes with 1638 ante-mortem volumetric head MRI scans spanning 1.0–16.8 years of disease duration prior to death were analysed. TDP-43 and Braak neurofibrillary tangle pathological staging schemes were constructed, and hippocampal and neocortical (inferior temporal and middle frontal) brain volumes determined using longitudinal FreeSurfer. Bayesian bivariate-outcome hierarchical models were utilized to estimate associations between proteins and volume, early rate of atrophy and acceleration in atrophy rates across brain regions. High TDP-43 stage was associated with smaller cross-sectional brain volumes, faster rates of brain atrophy and acceleration of atrophy rates, more than a decade prior to death, with deceleration occurring closer to death. Stronger associations were observed with hippocampus compared to temporal and frontal neocortex. Conversely, low TDP-43 stage was associated with slower early rates but later acceleration. This later acceleration was associated with high Braak neurofibrillary tangle stage. Somewhat similar, but less striking, findings were observed between TDP-43 and neocortical rates. Braak stage appeared to have stronger associations with neocortex compared to TDP-43. The association between TDP-43 and brain atrophy occurred slightly later in time (∼3 years) in cases of primary age-related tauopathy compared to Alzheimer’s disease. The results suggest that TDP-43 and tau have different contributions to acceleration and deceleration of brain atrophy rates over time in both Alzheimer’s disease and primary age-related tauopathy.
Utility of FDG-PET in diagnosis of Alzheimer-related TDP-43 proteinopathy
Neurology | June 9, 2020 | Volume: 95 | Issue: 1 | Pages: No page available
AbstractIntroductionBehavioral variant frontotemporal dementia (bvFTD) may present sporadically or due to an autosomal dominant mutation. Characterization of both forms will improve understanding of the generalizability of assessments and treatments.MethodsA total of 135 sporadic (s‐bvFTD; mean age 63.3 years; 34% female) and 99 familial (f‐bvFTD; mean age 59.9; 48% female) bvFTD participants were identified. f‐bvFTD cases included 43 with known or presumed chromosome 9 open reading frame 72 (C9orf72) gene expansions, 28 with known or presumed microtubule‐associated protein tau (MAPT) mutations, 14 with known progranulin (GRN) mutations, and 14 with a strong family history of FTD but no identified mutation.ResultsParticipants with f‐bvFTD were younger and had earlier age at onset. s‐bvFTD had higher total Neuropsychiatric Inventory Questionnaire (NPI‐Q) scores due to more frequent endorsement of depression and irritability.Discussionf‐bvFTD and s‐bvFTD cases are clinically similar, suggesting the generalizability of novel biomarkers, therapies, and clinical tools developed in either form to the other.