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Abstract Background Multiple lines of evidence support peripheral organs in the initiation or progression of Lewy body disease (LBD), a spectrum of neurodegenerative diagnoses that include Parkinson’s Disease (PD) without or with dementia (PDD) and dementia with Lewy bodies (DLB). However, the potential contribution of the peripheral immune response to LBD remains unclear. This study aims to characterize peripheral immune responses unique to participants with LBD at single-cell resolution to highlight potential biomarkers and increase mechanistic understanding of LBD pathogenesis in humans. Methods In a case–control study, peripheral mononuclear cell (PBMC) samples from research participants were randomly sampled from multiple sites across the United States. The diagnosis groups comprise healthy controls (HC, n = 159), LBD (n = 110), Alzheimer’s disease dementia (ADD, n = 97), other neurodegenerative disease controls (NDC, n = 19), and immune disease controls (IDC, n = 14). PBMCs were activated with three stimulants (LPS, IL-6, and IFNa) or remained at basal state, stained by 13 surface markers and 7 intracellular signal markers, and analyzed by flow cytometry, which generated 1,184 immune features after gating. Results The model classified LBD from HC with an AUROC of 0.87 ± 0.06 and AUPRC of 0.80 ± 0.06. Without retraining, the same model was able to distinguish LBD from ADD, NDC, and IDC. Model predictions were driven by pPLCγ2, p38, and pSTAT5 signals from specific cell populations under specific activation. The immune responses characteristic for LBD were not associated with other common medical conditions related to the risk of LBD or dementia, such as sleep disorders, hypertension, or diabetes. Conclusions and Relevance Quantification of PBMC immune response from multisite research participants yielded a unique pattern for LBD compared to HC, multiple related neurodegenerative diseases, and autoimmune diseases thereby highlighting potential biomarkers and mechanisms of disease.

Abstract Background We have proposed that cognitive resilience (CR) counteracts brain damage from Alzheimer’s disease (AD) or AD-related dementias such that older individuals who harbor neurodegenerative disease burden sufficient to cause dementia remain cognitively normal. However, CR traditionally is considered a binary trait, capturing only the most extreme examples, and is often inconsistently defined. Methods This study addressed existing discrepancies and shortcomings of the current CR definition by proposing a framework for defining CR as a continuous variable for each neuropsychological test. The linear equations clarified CR’s relationship to closely related terms, including cognitive function, reserve, compensation, and damage. Primarily, resilience is defined as a function of cognitive performance and damage from neuropathologic damage. As such, the study utilized data from 844 individuals (age = 79 ± 12, 44% female) in the National Alzheimer’s Coordinating Center cohort that met our inclusion criteria of comprehensive lesion rankings for 17 neuropathologic features and complete neuropsychological test results. Machine learning models and GWAS then were used to identify medical and genetic factors that are associated with CR. Results CR varied across five cognitive assessments and was greater in female participants, associated with longer survival, and weakly associated with educational attainment or APOE ε4 allele. In contrast, damage was strongly associated with APOE ε4 allele (P value

Abstract Assay for Transposase Accessible Chromatin by sequencing (ATAC-seq) accurately depicts the chromatin regulatory state and altered mechanisms guiding gene expression in disease. However, bulk sequencing entangles information from different cell types and obscures cellular heterogeneity. To address this, we developed Cellformer, a deep learning method that deconvolutes bulk ATAC-seq into cell type-specific expression across the whole genome. Cellformer enables cost-effective cell type-specific open chromatin profiling in large cohorts. Applied to 191 bulk samples from 3 brain regions, Cellformer identifies cell type-specific gene regulatory mechanisms involved in resilience to Alzheimer’s disease, an uncommon group of cognitively healthy individuals that harbor a high pathological load of Alzheimer’s disease. Cell type-resolved chromatin profiling unveils cell type-specific pathways and nominates potential epigenetic mediators underlying resilience that may illuminate therapeutic opportunities to limit the cognitive impact of the disease. Cellformer is freely available to facilitate future investigations using high-throughput bulk ATAC-seq data.

Abstract Comparing brain structure across species and regions enables key functional insights. Leveraging publicly available data from a novel mass cytometry-based method, synaptometry by time of flight (SynTOF), we applied an unsupervised machine learning approach to conduct a comparative study of presynapse molecular abundance across three species and three brain regions. We used neural networks and their attractive properties to model complex relationships among high dimensional data to develop a unified, unsupervised framework for comparing the profile of more than 4.5 million single presynapses among normal human, macaque, and mouse samples. An extensive validation showed the feasibility of performing cross-species comparison using SynTOF profiling. Integrative analysis of the abundance of 20 presynaptic proteins revealed near-complete separation between primates and mice involving synaptic pruning, cellular energy, lipid metabolism, and neurotransmission. In addition, our analysis revealed a strong overlap between the presynaptic composition of human and macaque in the cerebral cortex and neostriatum. Our unique approach illuminates species- and region-specific variation in presynapse molecular composition.

Background: Epigenetic remodeling is emerging as a critical process for both the onset and progression of Alzheimer’s disease (AD), the most common form of neurodegenerative dementia. However, it is not clear to what extent the distribution of histone modifications is involved in AD. Methods: To investigate histone H3 modifications in AD, we compared the genome-wide distributions of H3K4me3 and H3K27me3 in entorhinal cortices from severe sporadic AD patients and from age-matched healthy individuals of both sexes. Results: AD samples were characterized by typical average levels and distributions of the H3K4me3 and H3K27me3 signals. However, AD patients showed a lower H3K4me3 and higher H3K27me3 signal, particularly in males. Interestingly, the genomic sites found differentially trimethylated at the H3K4 between healthy and AD samples involve promoter regions of genes belonging to AD-related pathways such as glutamate receptor signaling. Conclusions: The signatures of H3K4me3 and H3K27me3 identified in AD patients validate the role of epigenetic chromatin remodeling in neurodegenerative disease and shed light on the genomic adaptive mechanisms involved in AD.

Abstract Introduction There is increasing evidence linking periodontal infections to Alzheimer's disease (AD). Saliva sampling can reveal information about the host and pathogen interactions that can inform about physiological and pathological brain states. Methods A cross‐sectional cohort of age‐matched participants (78) was segmented according to their chemosensory (University of Pennsylvania Smell Identification Test; UPSIT) and cognitive scores (Mini‐Mental State Exam; MMSE and clinical dementia rating; CDR). Mid‐morning saliva was sampled from each participant and processed for microbiome composition and cytokine analysis. Linear discriminant analysis (LDA) was used to unravel specific changes in microbial and immunological signatures and logistic regression analysis (LRA) was employed to identify taxa that varied in abundance among patient groups. Results Using olfaction we distinguish in the cognitively normal population a segment with high chemosensory scores (CNh, 27) and another segment with chemosensory scores (CNr, 16) as low as mild cognitive impairment (MCI, 21) but higher than the AD group (17). We could identify stage‐specific microbial signatures changes but no clearly distinct cytokine profiles. Periodontal pathogen species as Filifactor villosus decline with the increasing severity of AD, whereas opportunistic oral bacteria such as Leptotrichia wadei show a significant enrichment in MCI. Conclusions The salivary microbiome indicates stage‐dependent changes in oral bacteria favoring opportunistic species at the expense of periodontal bacteria, whereas the inflammatory profiles remain mainly unchanged in the sampled population.

Chromatin immunoprecipitation (ChIP) is an assay developed in order to define the dynamic nature of transcription processes. This method has been widely employed to identify methylated and acetylated DNA sequences in a variety of organs both in animals and humans. Nevertheless, this technique is significantly less employed to study transcriptional targets of specific nuclear signaling factors (TFs) and the data published so far have mainly used cell culture material and have been hardly reproduced in ex-vivo tissue. As nuclear signaling underlies important adaptive and maladaptive responses in chronic conditions such as cancer and neurodegeneration, there is a need for streamlining the upfront workflow of TF-ChIP for subsequent target sequencing. Based on the typical low concentration of the signaling transcriptional complex and the complexity/length of the ChIP Seq protocol, the field of cellular signaling has been confronted with a major roadblock in identifying clinically relevant targets of pathological and physiological signaling pathways. The present protocol offers a standardized procedure for detecting signaling targets in any whole tissue or specific dissected regions. The advantages of the protocol compared to the existing published methods are: (1) the small amount of starting material; appropriate for tissue subregions; (2) the optimization of DNA fragmentation from whole tissue; (3) suitability for sparsely populated tissues (i.e., brain); (4) the specificity of the TF-targeting readout; and (5) high DNA quality for sequencing or hybridization. The present protocol is highly detailed and can be reproduced using both fresh and fresh-frozen tissue. This is particularly relevant in the clinical setting, where specimen integrity is often the limiting step and where transcriptional target profiling is therapeutically relevant. The method is centered on Notch signaling but can be applied to a variety of nuclear signaling pathways as long as specific antibodies are available for pull down. Taken the superior yield/readout of this procedure, ChIP may finally provide relevant information about dynamic downstream gene changes in vivo for use in both basic research and clinical applications.