Biology subjects

Tanzi, R. E.

Publications and source records attributed to Tanzi, R. E..

13 recordsLinked to original sources

bioRxiv2026

Genedex: Contextualizing gene signatures across Alzheimer's disease pathology, cell types, and brain regions

Systematic prioritization of candidate Alzheimer's disease (AD) genes and their target functions for therapeutic intervention requires a consistent understanding of their brain location, cell-type-specific expression, relationships with pathology, and direction of change. Defining the role of a gene in AD requires interrogation of multiple publications, each providing a different context. Often, it is also unclear whether a gene is up- or downregulated across these contexts. However, the narrow diversity of contexts in which they have been assayed and described limits interpretation. We integrated 1,562 gene signatures from 34 studies, annotated for pathological process, cell type, brain region, and direction of change, and showed that Genedex recovers established AD biology. Genedex addresses cellular and regional unexplained directional contradictions from 10,657 discordant genes in the published AD literature. We investigated the role of heat-shock chaperones and neurotrophic signaling in cognitive resilience using Genedex. Heat-shock chaperone genes are broadly upregulated with tau burden; but, in the presence of amyloid pathology, their expression diverges, showing upregulation in excitatory neurons and downregulation in glia and during A{beta} clearance. LINGO1, a regulator of BDNF, is upregulated with neuritic plaque load, tau burden, and selective vulnerability in cortical regions. Notably, in tau-affected RORB excitatory neurons, LINGO1 expression is inversely correlated with neurotrophic genes BDNF and NTRK2. A prioritized interneuronal resilience signature shows correlated pathway co-expression with somatostatin and parvalbumin interneuronal signatures. Vulnerability-associated signatures separate by cellular context: neuronal programs are positively correlated with vulnerable interneurons, while glial and vascular cells are predominantly anti-correlated. By systematically mapping genes across functional, cellular, spatial, and directional axes, Genedex provides a platform for discovery of contextualized targets and mechanistic hypotheses. Genedex is freely available at hidelab.github.io/genedex-app.

neuroscience↗

bioRxiv2025

Discovery of Abundant Nano-scale Lymphatic-like Vessels in Brains

As one of the most metabolically active organs, the brain requires an exceptionally efficient system for waste clearance to sustain its high metabolic demands. However, whether such a system exists--and, if so, what structural features enable its efficiency--remains incompletely understood. More than a decade ago, the "glymphatic system" was proposed to describe neurofluid transport through cerebrospinal fluid (CSF) and perivascular spaces (PVS), in conjunction with dural and meningeal lymphatic pathways. Nevertheless, it remains unresolved whether neurofluid transport is organized as a structured, vessel-like flow network. Moreover, in stark contrast to the dense network of blood capillaries in the brain, only a sparse population of lymphatic vessels has been identified, raising doubts as to whether the currently recognized lymphatic architecture alone can support efficient metabolic waste clearance. By combining expansion microscopy with CRANAD-3, a pan-{beta}-amyloid fluorescent probe, we discovered abundant nanoscale lymphatic-like vessels (NLVs) within the brain parenchyma of both mice and humans. The majority of these structures have diameters below 1,000 nm and exhibit moderate positivity for multiple lymphatic markers, including LYVE-1, Prox-1, PDPN, and VEGFR3. NLVs frequently coil around blood vessels, and putative connections between vascular structures were observed. Notably, some NLVs traverse multiple cortical layers and display distinct orientation patterns that vary across cortical laminae. This discovery reveals a previously "hidden" vascular network in the brain parenchyma and raises the possibility that an abundant, highly organized system of nanoscale tubular structures may provide an efficient conduit for metabolic waste clearance. Such a system could represent a critical, previously unrecognized component supporting the brains extraordinary metabolic demands.

neuroscience↗

bioRxiv2025

Context-dependent regulatory variants in Alzheimer's disease

Noncoding genetic variants underlie many complex diseases, yet identifying and interpreting their functional impacts remains challenging. Late-onset Alzheimers disease (LOAD), a polygenic neurodegenerative disorder, exemplifies this challenge. The disease is strongly associated with noncoding variation, including common variants enriched in microglial enhancers and rare variants nominated at loci implicated in neurodevelopment and synaptic function. These variants may perturb regulatory sequences by disrupting transcription factor (TF) motifs or altering local regulatory sequence context, with potential consequences for gene expression and chromatin accessibility. However, assessing their impact is complicated by the context-dependent functions of regulatory sequences, underscoring the need to systematically examine variant effects across diverse tissues, cell types, and cellular states. Here, we combined in vitro and in vivo massively parallel reporter assays (MPRAs) with interpretable machine-learning models to systematically characterize common and rare variants across myeloid and neuron-enriched neural contexts. Parallel profiling of variants in four immune states in vitro and three mouse brain regions in vivo revealed that individual variants can differentially and even oppositely modulate reporter activity across cellular contexts, while a subset showed immune-state-dependent effects. Within the assayed candidate set, the relative effect sizes of common and rare variants reversed between contexts, with common variants showing larger effects in THP-1 macrophages and rare variants in brain tissue. Interpretable sequence-to-function models prioritized context-biased variants and generated motif-level hypotheses, including predicted transcription-factor motif disruption and subtler changes in local motif context. To probe endogenous consequences at a prioritized locus, we used CRISPR interference to perturb a rare-variant-containing enhancer at the SEC63-OSTM1 locus, revealing metabolic and biosynthetic transcriptional programs resembling those induced by SEC63 promoter perturbation, together with a stimulation-specific interferon response. These findings show that LOAD-associated noncoding variants exhibit context-dependent effects on reporter activity and predicted chromatin accessibility, and provide a framework for linking genetic association to regulatory activity, sequence grammar and endogenous transcriptional state.

genomics↗

bioRxiv2025

Inhibition of Acyl-CoA: Cholesterol Acyltransferase 1 Promotes Shedding of Soluble TREM2 and LRP1-Dependent Phagocytosis of Amyloid β Protein in Microglia

Lipid regulation plays a major role in the pathogenesis of Alzheimers disease (AD). In AD patients and transgenic mice, microglia exhibit increased expression of SOAT1, encoding Acyl-CoA: Cholesterol Acyltransferase 1 (ACAT1), which catalyzes the production of cholesteryl esters in lipid droplets. ACAT1 Inhibition has been reported to reduce {beta}-amyloid pathology. However, the molecular mechanism underlying this effect remains unknown. Here, we show ACAT1 inhibition in mouse and human iPSC- derived microglia upregulates LRP1 levels and shedding of soluble TREM2 (sTREM2) owing to enhanced cleavage of TREM2 by ADAM10/17. Knocking out TREM2 or preventing sTREM2 release abrogated the ability of ACAT1 inhibition to enhance microglial uptake of amyloid {beta} (A{beta}). This could be rescued by the addition of recombinant sTREM2, but only in the presence of LRP1. Collectively, these data indicate ACAT1 inhibition increases microglial uptake of A{beta} in a sTREM2- and LRP1-dependent manner suggesting new avenues for treating and preventing AD.

cell biology↗

bioRxiv2025

Highly sensitive chemiluminescence imaging of misfolded proteins in neurodegenerative models

Visualizing misfolded proteins would greatly facilitate early diagnosis, etiology elucidation, and therapy monitoring of neurodegeneration. Although several probes have been reported, simple and versatile detection in vivo is still challenging. We demonstrated that both generic and precise detection of misfolded proteins could be achieved with a chemiluminescence probe, ADLumin-1. For the generic aspect, ADLumin-1 was highly sensitive to various misfolded proteins, showing up to 127.73-fold higher signal-to-noise ratio than Thioflavin T. ADLumin-1 could also non-invasively visualize misfolded proteins in mouse models of Parkinsons disease, Alzheimers disease and amyotrophic lateral sclerosis. Furthermore, ADLumin-1 displayed precise detection value for -synuclein by combining with PMCA in vitro and bioorthogonal ChRET imaging technology in vivo. ADLumin-1 can selectively detect -synuclein in CSF at the femtomolar level and enables in situ monitoring of misfolded -synuclein in vivo. Combining generality and precision, our findings could be widely applied in preclinical and clinical studies of neurodegenerative diseases. TeaserA highly sensitive chemiluminescence probe enables both generic and precise detection of various misfolded proteins

biochemistry↗

bioRxiv2025

Molecular hallmarks of excitatory and inhibitory neuronal resilience and resistance to Alzheimer's disease

BackgroundA significant proportion of individuals maintain healthy cognitive function despite having extensive Alzheimers disease (AD) pathology, known as cognitive resilience. Understanding the molecular mechanisms that protect these individuals can identify therapeutic targets for AD dementia. This study aims to define molecular and cellular signatures of cognitive resilience, protection and resistance, by integrating genetics, bulk RNA, and single-nucleus RNA sequencing data across multiple brain regions from AD, resilient, and control individuals. MethodsWe analyzed data from the Religious Order Study and the Rush Memory and Aging Project (ROSMAP), including bulk (n=631) and multi-regional single nucleus (n=48) RNA sequencing. Subjects were categorized into AD, resilient, and control based on {beta}-amyloid and tau pathology, and cognitive status. We identified and prioritized protected cell populations using whole genome sequencing-derived genetic variants, transcriptomic profiling, and cellular composition distribution. ResultsTranscriptomic results, supported by GWAS-derived polygenic risk scores, place cognitive resilience as an intermediate state in the AD continuum. Tissue-level analysis revealed 43 genes enriched in nucleic acid metabolism and signaling that were differentially expressed between AD and resilience. Only GFAP (upregulated) and KLF4 (downregulated) showed differential expression in resilience compared to controls. Cellular resilience involved reorganization of protein folding and degradation pathways, with downregulation of Hsp90 and selective upregulation of Hsp40, Hsp70, and Hsp110 families in excitatory neurons. Excitatory neuronal subpopulations in the entorhinal cortex (ATP8B1+ and MEF2Chigh) exhibited unique resilience signaling through neurotrophin (modulated by LINGO1) and angiopoietin (ANGPT2/TEK) pathways. We identified MEF2C, ATP8B1, and RELN as key markers of resilient excitatory neuronal populations, characterized by selective vulnerability in AD. Protective rare variant enrichment highlighted vulnerable populations, including somatostatin (SST) inhibitory interneurons, validated through immunofluorescence showing co-expression of rare variant associated RBFOX1 and KIF26B in SST+ neurons in the dorsolateral prefrontal cortex. The maintenance of excitatory-inhibitory balance emerges as a key characteristic of resilience. ConclusionsWe identified molecular and cellular hallmarks of cognitive resilience, an intermediate state in the AD continuum. Resilience mechanisms include preservation of neuronal function, maintenance of excitatory/inhibitory balance, and activation of protective signaling pathways. Specific excitatory neuronal populations appear to play a central role in mediating cognitive resilience, while a subset of vulnerable SST interneurons likely provide compensation against AD-associated dysregulation. This study offers a framework to leverage natural protective mechanisms to mitigate neurodegeneration and preserve cognition in AD.

neuroscience↗

bioRxiv2024

Polygenic hazard score models for the prediction of Alzheimer's free survival using the lasso for Cox's proportional hazards model

The prediction of the susceptibility of an individual to a certain disease is an important and timely research area. An established technique is to estimate the risk of an individual with the help of an integrated risk model, that is a polygenic risk score with added epidemiological covariates. However, integrated risk models do not capture any time dependence, and may provide a point estimate of the relative risk with respect to a reference population. The aim of this work is twofold. First, we explore and advocate the idea of predicting the time dependent hazard and survival (defined as disease free time) of an individual for the onset of a disease. This provides a practitioner with a much more differentiated view of the absolute survival as a function of time. Second, to compute the time dependent risk of an individual, we use published methodology to fit a Coxs proportional hazard model to data from a genetic SNP study of time to Alzheimers disease (AD) onset, using the lasso to incorporate further epidemiological variables such as sex, APOE (apolipoprotein E, a genetic risk factor for AD) status, ten leading principal components, and selected genomic loci. We apply the lasso for Coxs proportional hazards to a dataset of 6792 AD patients (composed of 4102 cases and 2690 controls) and 87 covariates. We demonstrate that fitting a lasso model for Coxs proportional hazards allows one to obtain more accurate survival curves than with state-of-the-art (likelihood-based) methods. Moreover, the methodology allows one to obtain personalized survival curves for a patient, thus giving a much more differentiated view of the expected progression of a disease than the view offered by integrated risk models. The runtime to compute personalized survival curves is under a minute for the entire dataset of AD patients, thus enabling it to handle datasets with 60, 000 to 100, 000 subjects in less than one hour.

bioinformatics↗

bioRxiv2023

Endogenous recapitulation of Alzheimers disease neuropathology through human 3D direct neuronal reprogramming

Alzheimers disease (AD) is a neurodegenerative disorder that primarily affects elderly individuals, and is characterized by hallmark neuronal pathologies including extracellular amyloid-{beta} (A{beta}) plaque deposition, intracellular tau tangles, and neuronal death. However, recapitulating these age-associated neuronal pathologies in patient-derived neurons has remained a significant challenge, especially for late-onset AD (LOAD), the most common form of the disorder. Here, we applied the high efficiency microRNA-mediated direct neuronal reprogramming of fibroblasts from AD patients to generate cortical neurons in three-dimensional (3D) Matrigel and self-assembled neuronal spheroids. Our findings indicate that neurons and spheroids reprogrammed from both autosomal dominant AD (ADAD) and LOAD patients exhibited AD-like phenotypes linked to neurons, including extracellular A{beta} deposition, dystrophic neurites with hyperphosphorylated, K63-ubiquitin-positive, seed-competent tau, and spontaneous neuronal death in culture. Moreover, treatment with {beta}- or {gamma}-secretase inhibitors in LOAD patient-derived neurons and spheroids before A{beta} deposit formation significantly lowered A{beta} deposition, as well as tauopathy and neurodegeneration. However, the same treatment after the cells already formed A{beta} deposits only had a mild effect. Additionally, inhibiting the synthesis of age-associated retrotransposable elements (RTEs) by treating LOAD neurons and spheroids with the reverse transcriptase inhibitor, lamivudine, alleviated AD neuropathology. Overall, our results demonstrate that direct neuronal reprogramming of AD patient fibroblasts in a 3D environment can capture age-related neuropathology and reflect the interplay between A{beta} accumulation, tau dysregulation, and neuronal death. Moreover, miRNA-based 3D neuronal conversion provides a human-relevant AD model that can be used to identify compounds that can potentially ameliorate AD-associated pathologies and neurodegeneration.

neuroscience↗

bioRxiv2021

Rapid Biomarker Screening of Alzheimer's Disease by Machine Learning and Graphene-Assisted Raman Spectroscopy

As the most common cause of dementia, the study of Alzheimers disease (AD) faces challenges in terms of understanding the cause, monitoring the pathogenesis, and developing early diagnosis and effective treatment. Rapid and accurate identification of AD biomarkers in the brain is critical to provide key insights into AD and facilitate the development of early diagnosis methods. In this work, we developed a platform that enables a rapid screening of AD biomarkers by employing graphene-assisted Raman spectroscopy and machine learning interpretation in AD transgenic animal brains. Specifically, we collected Raman spectra on slices of mouse brains with and without AD and used machine learning to classify AD and non-AD spectra. By contacting monolayer graphene with the brain slices, the accuracy was significantly increased from 77% to 98% in machine learning classification. Further, using linear supporting vector machine (SVM), we identified a spectral feature importance map that reveals the importance of each Raman wavenumber in classifying AD and non-AD spectra. Based on this spectral feature importance map, we identified AD biomarkers including A{beta} and tau proteins, and other potential biomarkers, such as triolein, phosphatidylcholine, and actin, which have been confirmed by other biochemical studies. Our Raman-machine learning integrated method with interpretability is promising to greatly accelerate the study of AD and can be extended to other tissues, biofluids, and for various other diseases.

neuroscience↗

bioRxiv2020

TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels

BackgroundNeurofilament light (NF-L), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are utilized as biomarkers for Alzheimers disease (AD), to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. Here we performed genome-wide association study (GWAS) analyses using all three biomarkers as outcome. MethodsDNA and cerebrospinal fluid (CSF) samples originated from the European Medical Information Framework AD Multimodal Biomarker Discovery (EMIF-AD MBD) study. Overlapping genotype/phenotype data were available for n=671 (NF-L), 677 (YKL-40), and 672 (Ng) individuals. GWAS analyses applied linear regression models adjusting for relevant covariates. FindingsWe identify novel genome-wide significant associations with markers in TMEM106B and CSF levels of NF-L. Additional novel signals were observed with DNA variants in CPOX and CSF levels of YKL-40. Lastly, we confirmed previous work suggesting that YKL-40 levels are regulated by cis protein quantitative trait loci (pQTL) in CHI3L1. InterpretationOur study provides important new insights into the genetic architecture underlying inter-individual variation in all three tested AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.

genomics↗

bioRxiv2019

A screening platform based on epitope editing for drug discovery

The interaction between an antibody and its epitope has been daily utilized in various biological studies; however it has been rarely explored whether small molecules can alter the interaction. We discovered that small molecules could alter/edit surface properties of amyloid beta (A{beta}) epitopes, and consequently inhibit or enhance corresponding antibody recognition. Remarkably, this editing effect could generate functional changes including protein aggregation behaviors, cell cytokine secreting and in vivo microglia activation. According to this discovery, we proposed a screen platform based on epitope editing for drug discovery (SPEED). With a small library of compounds, we validated that SPEED could be used to seek new leads for A{beta} species. We also demonstrated that this platform could potentially be extended to other targets including tau protein and PD-L1 protein. The SPEED is a simple, fast and label-free screening method. We believe that the SPEED strategy could be universally applicable for seeking and validating drug candidates and imaging ligands.

biochemistry↗

bioRxiv2019

Dedifferentiation orchestrated through remodeling of the chromatin landscape defines PSEN1 mutation-induced Alzheimer's Disease

Early-Onset Familial Alzheimers Disease (EOFAD) is a dominantly inherited neurodegenerative disorder elicited by mutations in the PSEN1, PSEN2, and APP genes1. Hallmark pathological changes and symptoms observed, namely the accumulation of misfolded Amyloid-{beta} (A{beta}) in plaques and Tau aggregates in neurofibrillary tangles associated with memory loss and cognitive decline, are understood to be temporally accelerated manifestations of the more common sporadic Late-Onset Alzheimers Disease. The complete penetrance of EOFAD-causing mutations has allowed for experimental models which have proven integral to the overall understanding of AD2. However, the failure of pathology-targeting therapeutic development suggests that the formation of plaques and tangles may be symptomatic and not describe the etiology of the disease3,4. Here, we use an integrative, multi-omics approach and systems-level analysis in hiPSC-derived neurons to generate a mechanistic disease model for EOFAD. Using patient-specific cells from donors harboring mutations in PSEN1 differentiated into neurons, we characterize the disease-related gene expression and chromatin accessibility changes by RNA- Seq, ATAC-Seq, and histone methylation ChIP-Seq. We show that the defining disease-causing mechanism of EOFAD is dedifferentiation, primarily through the REST-mediated repression of neuronal lineage specification gene programs and the activation of non-specific germ layer precursor gene programs concomitant with modifications in chromatin accessibility. These gene signature profiles and changes in chromatin topology illustrate that EOFAD neurons traverse the chromatin landscape from an ectodermal origin to a mixed germ lineage state. Further, a reanalysis of existing transcriptomic data from PSEN1 patient brain samples demonstrates that the mechanisms identified in our experimental system recapitulate EOFAD in the human brain. Our results comprise a disease model which describes the mechanisms culminating in dedifferentiation that precede amyloid and tau pathology formation and engender neurodegeneration.

neuroscience↗

bioRxiv2018

Alteration of Vascular Endothelial Cadherin in Alzheimer’s Disease Patient and Mouse Model

Alzheimers disease (AD) is characterized by amyloid plaques and pathologic cerebrovascular remodeling. Cerebrovascular abnormalities may contribute to the pathology of AD, but the molecular mechanisms are not fully understood. In this study, we evaluated blood-brain barrier (BBB) disruption and the role of VE-cadherin in the progression of amyloid pathology. Here, we determined that levels of VE-cadherin are decreased in brain vessels of AD patients and mouse model of AD. In vitro experiments showed that the disappearance of VE-cadherin by beta-amyloid at the endothelial cell surface was due to cleavage of VE-cadherin. VE-cadherin cleavage was inhibited by a {gamma}-secretase and ADAM10 inhibitor. The disappearance of VE-cadherin in brain vessels was also seen in amyloid precursor protein transgenic mice. In the postmortem brain of individuals with AD, furthermore, levels of VE-cadherin were significantly reduced in vessels. Dementia patients showed a distinct blood biochemical profile characterized by high soluble VE-cadherin (sVEC). There was a strong association between plasma sVEC (adjusted odds ratio = 3.41, P < 0.001) and dementia. These results suggest that measurements of plasma VE-cadherin could have the potential for predicting the risk of progressive AD.

neuroscience↗