Biology subjects

Jin, L.-W.

Publications and source records attributed to Jin, L.-W..

7 recordsLinked to original sources

bioRxiv2026

O-GlcNAcylation effect on Tau in modulating its seeding and cellular transmission in Alzheimer's Disease

Post-translational modifications critically regulate neurodegenerative disease progression. In Alzheimers disease (AD) and tauopathies, Tau hyperphosphorylation promotes aggregation and pathological spreading, whereas O-GlcNAcylation has emerged as a protective modification alongside its interplay with phosphorylation. However, the role of in vitro site-specific and global O-GlcNAcylation in Tau proteinopathy remains elusive. Here, using full-length Tau-441 (2N4R), we showed that O-GlcNAcylated Tau aggregated slowly, formed distinct aggregate morphology and exhibited reduced seeding capacity compared to wild-type (WT) Tau. Under phase-separated conditions, O-GlcNAcylated Tau formed oligomer like condensates. Mutation of the key O-GlcNAc sites reduced O-GlcNAc-transferase (OGT) mediated O-GlcNAcylation, cellular transmission and affected cross-talk with phosphorylation relative to WT. OGT overexpression alleviated WT-Tau toxicity in cells, and O-Tau fibrils were less toxic to primary cortical neurons compared to WT Tau fibrils. Finally, an in-house novel site-specific S422 O-GlcNAc-Tau antibody revealed reduced S422 O-GlcNAcylation in AD brain tissues, highlighting its protective role in AD pathogenesis.

neuroscience↗

bioRxiv2024

Learning precise segmentation of neurofibrillary tangles from rapid manual point annotations

Accumulation of abnormal tau protein into neurofibrillary tangles (NFTs) is a pathologic hallmark of Alzheimer disease (AD). Accurate detection of NFTs in tissue samples can reveal relationships with clinical, demographic, and genetic features through deep phenotyping. However, expert manual analysis is time-consuming, subject to observer variability, and cannot handle the data amounts generated by modern imaging. We present a scalable, open-source, deep-learning approach to quantify NFT burden in digital whole slide images (WSIs) of post-mortem human brain tissue. To achieve this, we developed a method to generate detailed NFT boundaries directly from single-point-per-NFT annotations. We then trained a semantic segmentation model on 45 annotated 2400{micro}m by 1200{micro}m regions of interest (ROIs) selected from 15 unique temporal cortex WSIs of AD cases from three institutions (University of California (UC)-Davis, UC-San Diego, and Columbia University). Segmenting NFTs at the single-pixel level, the model achieved an area under the receiver operating characteristic of 0.832 and an F1 of 0.527 (196-fold over random) on a held-out test set of 664 NFTs from 20 ROIs (7 WSIs). We compared this to deep object detection, which achieved comparable but coarser-grained performance that was 60% faster. The segmentation and object detection models correlated well with expert semi-quantitative scores at the whole-slide level (Spearmans rho {rho}=0.654 (p=6.50e-5) and {rho}=0.513 (p=3.18e-3), respectively). We openly release this multi-institution deep-learning pipeline to provide detailed NFT spatial distribution and morphology analysis capability at a scale otherwise infeasible by manual assessment.

pathology↗

bioRxiv2024

MU-BRAIN: MUltiethnic Brain Rna-seq for Alzheimer INitiative

Alzheimers Disease (AD) exhibits a complex molecular and phenotypic profile. Investigating gene expression plays a crucial role in unraveling the diseases etiology and progression. Transcriptome data across ethnic groups lack, negatively impacting equity in intervention and research. We employed 565 brains across six U.S. brain banks (n=399 non-Hispanic Whites, n=113 Hispanics, n=12 African Americans) to generated bulk RNA sequencing from prefrontal cortex. We sought to identify cross-ancestry and ancestry-specific differentially expressed genes (DEG) across Braak stages, adjusting for sex, age at death, and RNA quality metrics. We further validated our findings using the Religious Orders Study/Memory Aging Project brains (ROS/MAP; n=1,095) and performed metanalysis (n=1,660). We conducted Gene Set and Variation and Enrichment analysis (GSVA; GSEA). We employed a machine-learning approach for phenotype prediction and gene prioritization to construct a polytranscriptomics risk score (PTRS) splitting our sample into training and testing sub-samples, either randomly or by ethnicity ("ancestry-agnostic" and "ancestry-aware", respectively). Lastly, we validated top DEG using single-nucleus RNA sequencing (snRNAseq) data. We identified several DEG associated with Braak staging: AD-known genes VGF (Padj =3.78E- 07) and ADAMTS2 (Pad j=1.21E-04) were consistently differentially expressed across statistical models, ethnicities, and replicated in ROS/MAP. Genes from the heat shock protein (HSP) family, e.g. HSPB7 (Padj =3.78E-07), were the top differentially expressed genes and replicated in ROS/MAP. Ethnic-stratified analyses prioritized TNFSF14 and SPOCD1 as top Hispanics DEG. GSEA highlighted "Alzheimer disease" (Padj =4.24E-06) and "TYROBP causal network in microglia" (Padj =1.68E-08) pathways. Up- and down-regulated genes were enriched in several pathways (e.g. "Immune response activation signal pathways", "Vesicle-mediated transport in synapse", "cognition"). Ancestry-agnostic and ancestry-aware PTRS effectively classified brains (AUC=0.77 and 0.73 respectively) and replicated in ROS/MAP. snRNAseq validated prioritized genes, including VGF (downregulated in neurons; Padj=1.1 E-07). This is the largest diverse AD transcriptome in post-mortem brain tissue, to our knowledge. We identified perturbated genes, pathways and network expressions in AD brains resulting in cross- ethnic and ethnic-specific findings, ultimately highlighting the diversity within AD pathogenesis. The latter underscores the need for an integrative and personalized approach in AD studies.

genetics↗

bioRxiv2024

Age-related memory CD8 T cells induce and track Alzheimers-like neurodegeneration

Cerebral (A{beta}) plaque and (pTau) tangle deposition are hallmarks of Alzheimers disease (AD), yet are insufficient to confer complete AD-like neurodegeneration experimentally. Factors acting upstream of A{beta}/pTau in AD remain unknown, but their identification could enable earlier diagnosis and more effective treatments. T cell abnormalities are emerging AD hallmarks, and CD8 T cells were recently found to mediate neurodegeneration downstream of tangle deposition in hereditary neurodegeneration models. The precise impact of T cells downstream of A{beta}/fibrillar pTau, however, appears to vary depending on the animal model used. Our prior work suggested that antigen-specific memory CD8 T ("hiT") cells act upstream of A{beta}/pTau after brain injury. Here we examine whether hiT cells influence sporadic AD-like pathophysiology upstream of A{beta}/pTau. Examining neuropathology, gene expression, and behavior in our hiT mouse model we show that CD8 T cells induce plaque and tangle-like deposition, modulate AD-related genes, and ultimately result in progressive neurodegeneration with both gross and fine features of sporadic human AD. T cells required Perforin to initiate this pathophysiology, and IFN{gamma} for most gene expression changes and progression to more widespread neurodegenerative disease. Analogous antigen-specific memory CD8 T cells were significantly elevated in the brains of human AD patients, and their loss from blood corresponded to sporadic AD and related cognitive decline better than plasma pTau-217, a promising AD biomarker candidate. Our work is the first to identify an age-related factor acting upstream of A{beta}/pTau to initiate AD-like pathophysiology, the mechanisms promoting its pathogenicity, and its relevance to human sporadic AD. Significance StatementThis study changes our view of Alzheimers Disease (AD) initiation and progression. Mutations promoting cerebral beta-amyloid (A{beta}) deposition guarantee rare genetic forms of AD. Thus, the prevailing hypothesis has been that A{beta} is central to initiation and progression of all AD, despite contrary animal and patient evidence. We show that age-related T cells generate neurodegeneration with compelling features of AD in mice, with distinct T cell functions required for pathological initiation and neurodegenerative progression. Knowledge from these mice was applied to successfully predict previously unknown features of human AD and generate novel tools for its clinical management.

neuroscience↗

bioRxiv2022

L-Fucose is a candidate monosaccharide neuromodulator and mitigates Alzheimer's synaptic deficits

We identified a novel signaling function of L-fucose, a structurally unique monosaccharide. We showed that L-fucose enhanced excitatory neurotransmission and long-term potentiation (LTP) in Schaffer-collateral-CA1 synapses. L-fucose was released by neurons in an activity- and store-dependent manner, and induced rapid signaling changes to enhance presynaptic release. Such effects required L-fucose metabolism through the salvage pathway driven by fucokinase (FUK). Thus, L-fucose could be the first described monosaccharide neuromodulator affecting a metabolic-signaling mechanism. Human Alzheimers disease (AD) and 5xFAD mouse brains showed signs of fucose hypometabolism with impaired L-fucose signaling. Such abnormalities could be corrected by exogenous L-fucose, exemplified by rectification of LTPdeficits in 5xFAD hippocampus. Dietary L-fucose supplement, which increased cerebral free L-fucose levels and upregulated FUK to drive the salvage pathway, mitigated synaptic and behavioral deficits of 5xFAD mice. Our data reveals a therapeutic potential of oral L-fucose for AD, which is safe and easy to comply with.

neuroscience↗

bioRxiv2020

A novel equilibrative nucleoside transporter 1 inhibitor alleviates Tau-mediated neurodegeneration

Tau hyperphosphorylation favors the formation of neurofibrillary tangles and triggers the gradual loss of neuronal functions in tauopathies, including Alzheimers disease. Herein, we demonstrated that chronic treatment with an inhibitor (J4) of equilibrative nucleoside transporter 1 (ENT1), which plays a critical role in controlling adenosine homeostasis and purine metabolism in the brain, exerted beneficial effects in a mouse model of tauopathy (Thy-Tau22, Tau22). Chronic treatment with J4 improved spatial memory deficits, mitochondrial dysfunction, synaptic plasticity impairment, and gliosis. Immunofluorescence assays showed that J4 not only reduced Tau hyperphosphorylation but also normalized the reduction in mitochondrial mass and suppressed the abnormal activation of AMP-activated protein kinase (AMPK), a pathogenic feature that is also observed in the brains of patients with tauopathies. Given that AMPK is an important energy sensor, our findings suggest that energy dysfunction is associated with tauopathy and that J4 may exert its protective effect by improving energy homeostasis. Bulk RNA-seq analysis revealed that J4 also mitigated immune signature associated with Tau pathology including C1q upregulation and A1 astrocyte markers. Collectively, our findings suggest that identifying strategies for normalizing energy and neuroimmune dysfunctions in tauopathies through adenosinergic signaling modulation may pave the way for the development of treatments for Alzheimers disease.

neuroscience↗

bioRxiv2018

Interpretable classification of Alzheimer’s disease pathologies with a convolutional neural network pipeline

Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, however, are coarse-grained and can lack precise neuroanatomic localization. We report a proof-of-concept deep learning pipeline identifying specific neuropathologies--amyloid plaques and cerebral amyloid angiopathy--in immunohistochemical-stained archival slides. Using automated segmentation of stained objects and a cloud-based interface, we annotated >70,000 plaque candidates from 43 whole slide images (WSIs) to train and evaluate convolutional neural networks. Networks achieved strong plaque classification (0.993 and 0.744 areas under the receiver operating characteristic and precision recall curve, respectively) on a 10 WSI hold-out set. Prediction confidence maps visualized morphology distributions from the full-WSI level down to 20x magnification. Resulting plaque-burden scores correlated well with established semi-quantitative scores. Finally, saliency mapping demonstrated that networks learned patterns agreeing with accepted pathologic features. This scalable means to augment a neuropathologists ability may suggest a route to neuropathologic deep phenotyping.

pathology↗