Copathologies play an important role in the expression of the AD clinical phenotype and may influence treatment efficacy. Early-onset AD (EOAD), defined as manifesting before age 65, is viewed as a relatively pure form of AD with a more homogeneous neuropathological substrate. We sought to compare the frequency of common neuropathological diagnoses in a consecutive autopsy series of 96 patients with EOAD (median age of onset = 55 years, 44 females) and 48 with late-onset AD (LOAD) (median age of onset = 73 years, 14 females). The UCSF Neurodegenerative Disease Brain Bank database was reviewed to identify patients with a primary pathological diagnosis of AD. Prevalence and stage of Lewy body disease (LBD), limbic age-related TDP-43 encephalopathy (LATE), argyrophilic grain disease (AGD), hippocampal sclerosis (HS), cerebral amyloid angiopathy (CAA), and vascular brain injury (VBI) were compared between the two cohorts. We found at least one non-AD pathological diagnosis in 98% of patients with EOAD (versus 100% of LOAD), and the number of comorbid diagnoses per patient was lower in EOAD than in LOAD (median=2 versus 3, Mann-Whitney Z = 3.00, p = 0.002). LBD and CAA were common in both EOAD and LOAD (CAA: 86% versus 79%, Fisher exact p = 0.33; LBD: 49% versus 42%, p = 0.48, respectively), although amygdala-predominant LBD was more commonly found in EOAD than LOAD (22% versus 6%, p = 0.02). In contrast, LATE (35% versus 8%, p < 0.001), HS (15% versus 3%, p = 0.02), AGD (58% versus 41%, p = 0.052), and VBI (65% versus 39%, p = 0.004) were more common in LOAD than EOAD, respectively. The number of copathologies predicted worse cognitive performance at the time of death on MMSE (1.4 points/pathology (95%CI [-2.5, -0.2]) and Clinical Dementia Rating – Sum of Boxes (1.15 point/pathology, 95%CI [0.45, 1.84]), across the EOAD and the LOAD cohorts. The effect of sex on the number of copathologies was not significant (p = 0.17). Prevalence of at least one APOE ε4 allele was similar across the two cohorts (52% and 54%) and was associated with a greater number of copathologies (+0.40, 95%CI [0.01, 0.79], p = 0.047), independent of age of symptom onset, sex, and disease duration. Females showed higher density of neurofibrillary tangles compared to men, controlling for age of onset, APOE ε4, and disease duration. Our findings suggest that non-AD pathological diagnoses play an important role in the clinical phenotype of EOAD with potentially significant implications for clinical practice and clinical trials design.

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IntroductionRecent studies have shown that pathologically defined subtypes of Alzheimer's disease (AD) represent distinctive atrophy patterns and clinical characteristics. We investigated whether a cortical thickness–based clustering method can reflect such findings.MethodsA total of 77 AD subjects from the Alzheimer's Disease Neuroimaging Initiative 2 data set who underwent 3-T magnetic resonance imaging, [18F]-fluorodeoxyglucose-positron emission tomography (PET), [18F]-Florbetapir PET, and cerebrospinal fluid (CSF) tests were enrolled. After clustering based on cortical thickness, diverse imaging and biofluid biomarkers were compared between these groups.ResultsThree cortical thinning patterns were noted: medial temporal (MT; 19.5%), diffuse (55.8%), and parietal dominant (P; 24.7%) atrophy subtypes. The P subtype was the youngest and represented more glucose hypometabolism in the parietal and occipital cortices and marked amyloid-beta accumulation in most brain regions. The MT subtype revealed more glucose hypometabolism in the left hippocampus and bilateral frontal cortices and less performance in memory tests. CSF test results did not differ between the groups.DiscussionCortical thickness patterns can reflect pathophysiological and clinical changes in AD.

TAR-DNA binding protein 43 (TDP-43) aggregation is the most common pathological hallmark in frontotemporal dementia (FTD) and characterizes nearly all patients with motor neuron disease (MND). The earliest stages of TDP-43 pathobiology are not well characterized, and whether neurodegeneration results from TDP-43 loss-of-function or aggregation remains unclear. In the behavioral variant of FTD (bvFTD), patients undergo selective dropout of von Economo neurons (VENs) and fork cells within the frontoinsular (FI) and anterior cingulate cortices. Here, we examined TDP-43 pathobiology within these vulnerable neurons in the FI across a clinical spectrum including 17 patients with sporadic bvFTD, MND, or both. In an exploratory analysis based on our initial observations, we further assessed 10 patients with C9orf72-associated bvFTD/MND. VENs and fork cells showed early, disproportionate TDP-43 aggregation that correlated with anatomical and clinical severity, including loss of emotional empathy. The presence of a TDP-43 inclusion was associated with striking nuclear and somatodendritic atrophy. An intriguing minority of neurons lacked detectable nuclear TDP-43 despite the apparent absence of a cytoplasmic TDP-43 inclusion. These cells showed neuronal atrophy comparable to inclusion-bearing neurons, suggesting that loss of nuclear TDP-43 function promotes neurodegeneration, even when TDP-43 aggregation is inconspicuous or absent.

We aimed to present the study design of an independent validation cohort from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s disease (AD) (KBASE-V) and to investigate the baseline characteristics of the participants according to the AD clinical spectrum. We recruited 71 cognitively normal (CN) participants, 96 with subjective cognitive decline (SCD), 72 with mild cognitive impairment (MCI), and 56 with AD dementia (ADD). The participants are followed for three years. The Consortium to Establish a Registry for AD scores was significantly different between all of the groups. The logical memory delayed recall scores were significantly different between all groups, except between the MCI and ADD groups. The Mini-Mental State Examination score, hippocampal volume, and cerebrospinal fluid (CSF) amyloid-β42 level were significant difference among the SCD, MCI, and ADD groups. The frequencies of participants with amyloid pathology according to PET or CSF studies were 8.9%, 25.6%, 48.3%, and 90.0% in the CN, SCD, MCI, and ADD groups, respectively. According to ATN classification, A+/T+/N+ or A+/T+/N− was observed in 0%, 15.5%, 31.0%, and 78.3% in the CN, SCD, MCI, and ADD groups, respectively. The KBASE-V showed a clear difference according to the AD clinical spectrum in neuropsychological tests and AD biomarkers.

PDZ domain-mediated interactions have greatly expanded during metazoan evolution, becoming important for controlling signal flow via the assembly of multiple signaling components. The evolutionary history of PDZ domain-mediated interactions has never been explored at the molecular level. It is of great interest to understand how PDZ domain-ligand interactions emerged and how they become rewired during evolution. Here, we constructed the first human PDZ domain-ligand interaction network (PDZNet) together with binding motif sequences and interaction strengths of ligands. PDZNet includes 1,213 interactions between 97 human PDZ proteins and 591 ligands that connect most PDZ protein-mediated interactions (98%) in a large single network via shared ligands. We examined the rewiring of PDZ domain-ligand interactions throughout eukaryotic evolution by tracing changes in the C-terminal binding motif sequences of the PDZ ligands. We found that interaction rewiring by sequence mutation frequently occurred throughout evolution, largely contributing to the growth of PDZNet. The rewiring of PDZ domain-ligand interactions provided an effective means of functional innovations in nervous system development. Our findings provide empirical evidence for a network evolution model that highlights the rewiring of interactions as a mechanism for the development of new protein functions. PDZNet will be a valuable resource to further characterize the organization of the PDZ domain-mediated signaling proteome.

An improved understanding of protein conformational changes has broad implications for elucidating the mechanisms of various biological processes and for the design of protein engineering experiments. Understanding rearrangements of residue interactions is a key component in the challenge of describing structural transitions. Evolutionary properties of protein sequences and structures are extensively studied; however, evolution of protein motions, especially with respect to interaction rearrangements, has yet to be explored. Here, we investigated the relationship between sequence evolution and protein conformational changes and discovered that structural transitions are encoded in amino acid sequences as coevolving residue pairs. Furthermore, we found that highly coevolving residues are clustered in the flexible regions of proteins and facilitate structural transitions by forming and disrupting their interactions cooperatively. Our results provide insight into the evolution of protein conformational changes and help to identify residues important for structural transitions.

Background/Aims: A limited number of studies addressed MRI-based neurodegenerative changes in subjective memory impairment (SMI). We investigated changes in white matter (WM) microstructures as well as gray matter (GM) macrostructures in subjects with SMI of high and low risk for progression. Methods: A modeling scale (score range, 0-6) developed for prediction of SMI progression was used to divide SMI subjects (n = 46) into two groups: a high risk of progression (score ≥3; n = 19) and a low risk of progression (score ≤2; n = 27). Cross-sectional comparisons were performed using a region-of-interest-based diffusion tensor imaging (DTI) analysis, cortical thickness analysis, and hippocampal volumetry. Results: The high-risk group had more microstructural disruption shown by lower fractional anisotropy in the hippocampus, parahippocampal gyrus, supramarginal gyrus, and parts of frontotemporal lobes. On the other hand, GM macrostructural changes did not differ between the groups and were not associated with modeling scale scores. Conclusion: SMI subjects with a high risk of progression had more WM microstructural disruption than those with a low risk, and the changes were not explained by GM atrophy. Our findings suggest that the degree of microstructural alterations in SMI may be distinctive according to the risk factors and may precede GM atrophy.