Spatiotemporal transcriptomic profiling reveals metabolic dysfunction prior to overt tauopathy in the PS19 mouse model

Spatiotemporal transcriptomic profiling reveals metabolic dysfunction prior to overt tauopathy in the PS19 mouse model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Spatiotemporal transcriptomic profiling reveals metabolic dysfunction prior to overt tauopathy in the PS19 mouse model Gopal Thinakaran, Shuai Wang, Moorthi Ponnusamy, Om Patel, Mitchell Hansen, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6941464/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Feb, 2026 Read the published version in Experimental & Molecular Medicine → Version 1 posted 9 You are reading this latest preprint version Abstract Abnormal accumulation of hyperphosphorylated tau in neurofibrillary tangles is a hallmark of neurodegenerative diseases, such as Alzheimer’s disease (AD) and frontotemporal dementia. In AD, tangle pathology characteristically develops in brain regions with heightened vulnerability, such as the entorhinal cortex and hippocampus. Emerging evidence implicates mitochondrial dysfunction and metabolic disturbances in AD progression, yet the relationship between regional vulnerability and pretangle tau-driven transcriptomic changes remains unclear. To address this critical gap, we utilized the tau P301S transgenic mouse model (PS19 line), which develops tau inclusions. Using spatial transcriptomic profiling across the hippocampal and cortical regions at selected disease stages, we captured spatiotemporal transcriptional responses to tauopathy. Our findings reveal that disease-associated microglia and astrocyte phenotypes emerge concurrently with phosphorylated tau accumulation across multiple brain regions. Intriguingly, the expression of Pgk1, a hub gene of the glycolytic pathway, was upregulated along with other metabolic pathway genes in the CA3 region at 2 months of age, preceding the onset of detectable tau tangle pathology, and correlated with tangle severity, suggesting early metabolic dysregulation in vulnerable regions. Further analysis of differentially expressed genes uncovered region-specific and temporally dynamic transcriptional patterns in the cortex and hippocampus. Early saturable alterations in ATP metabolic processes, glycolysis, and oxidative phosphorylation appeared in the hippocampus at two months of age, with delayed engagement in the cortical regions. These results underscore the contributions of metabolic stress and glial activation to tauopathy and regional vulnerability, highlighting spatial transcriptomics as a powerful tool for uncovering region-specific molecular insights into disease mechanisms. Biological sciences/Neuroscience/Diseases of the nervous system/Alzheimer's disease Biological sciences/Molecular biology/Transcriptomics Alzheimer's disease frontotemporal dementia spatial transcriptomics tauopathy metabolic dysfunction Pgk1 glial activation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Full Text Additional Declarations There is no conflict of interest Supplementary Files SI2counttable.xls Supplemental Table SI1figures.pdf Supplemental Figures Cite Share Download PDF Status: Published Journal Publication published 13 Feb, 2026 Read the published version in Experimental & Molecular Medicine → Version 1 posted Editorial decision: revise 01 Aug, 2025 Review # 1 received at journal 30 Jul, 2025 Review # 2 received at journal 20 Jul, 2025 Reviewer # 2 agreed at journal 14 Jul, 2025 Reviewer # 1 agreed at journal 14 Jul, 2025 Reviewers invited by journal 08 Jul, 2025 Submission checks completed at journal 23 Jun, 2025 Editor assigned by journal 20 Jun, 2025 First submitted to journal 20 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6941464","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":482626480,"identity":"84bdea67-82c0-45ca-9c6d-5434d2893d6f","order_by":0,"name":"Gopal Thinakaran","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYDACCcYGBoYDIBYzkLRhgHLwAB6EFrYEBoY0orQwwFTxGBCnxV66ue3BjzN2+fyze75J/khgkOO7kUDAFpmD7YY9N5ItZ9w5u02aJ4HBWJKgFonENgmeD8wGDDdyt0kz/mBI3ECMFsk/H+oN5G/kPAM5rJ4oLdI8Nw4bGNzIYZMAOizBgKCWG0AtMmeOGxjeSDO25kmQMJx55gF+Lewz0p9JvjlWbSB3I/nhzR8JNvJ8xwnYgg4kSFM+CkbBKBgFowA7AABTpUYG2LvZPAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-5523-6780","institution":"Byrd Alzheimer's Institue","correspondingAuthor":true,"prefix":"","firstName":"Gopal","middleName":"","lastName":"Thinakaran","suffix":""},{"id":482626481,"identity":"d65d96ca-056e-4738-897b-046c25e3cb84","order_by":1,"name":"Shuai Wang","email":"","orcid":"https://orcid.org/0000-0002-9252-7496","institution":"Byrd Alzheimer's Center and Research Institue","correspondingAuthor":false,"prefix":"","firstName":"Shuai","middleName":"","lastName":"Wang","suffix":""},{"id":482626482,"identity":"95980048-40a7-445a-9329-2ef5c35bcacc","order_by":2,"name":"Moorthi Ponnusamy","email":"","orcid":"","institution":"Byrd Alzheimer's Center and Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Moorthi","middleName":"","lastName":"Ponnusamy","suffix":""},{"id":482626483,"identity":"076de313-4507-4c5f-8ac0-af97ec688ae3","order_by":3,"name":"Om Patel","email":"","orcid":"","institution":"Byrd Alzheimer's Center and Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Om","middleName":"","lastName":"Patel","suffix":""},{"id":482626484,"identity":"044e3687-69b9-4112-b3bc-63e23e5ddee8","order_by":4,"name":"Mitchell Hansen","email":"","orcid":"","institution":"Byrd Alzheimer's Center and Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Mitchell","middleName":"","lastName":"Hansen","suffix":""},{"id":482626485,"identity":"5e1f78a2-7632-4b9c-8b68-0271dc5eb621","order_by":5,"name":"Lisa Collier","email":"","orcid":"","institution":"Byrd Alzheimer's Center and Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Lisa","middleName":"","lastName":"Collier","suffix":""},{"id":482626486,"identity":"e4baa365-0e31-4496-92ba-676eb603245b","order_by":6,"name":"Shane Collier","email":"","orcid":"","institution":"Byrd Alzheimer's Center and Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Shane","middleName":"","lastName":"Collier","suffix":""}],"badges":[],"createdAt":"2025-06-20 20:40:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6941464/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6941464/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s12276-026-01652-z","type":"published","date":"2026-02-13T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86445118,"identity":"beb169bb-1508-4c99-a510-f466dade5f46","added_by":"auto","created_at":"2025-07-10 17:37:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":4017839,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatiotemporal transcriptomic profiling of the PS19 tauopathy model.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Immunohistochemical analysis of p-tau (pSer202/pThr205) levels in the hippocampus and CA3 region of male PS19 mice at 2, 6, and 8 months of age, analyzed using mAb AT8 staining. (B) Immunofluorescence images show Synaptophysin expression in the hippocampus of 2- month-old WT and PS19 mice. (C) Sampling from WT and PS19 mice at three stages of tau pathology. Regions of interest (ROIs) included hippocampal subfields CA1, CA3, DG, and cortical regions PIR, RSP, and SS. (D) Violin and box plots display the Unique Molecular Identifiers (UMIs) and negative probes per cell for each indicated region. (E) The Pearson correlation for 6842 genes across 190 ROIs is represented as a heatmap. The ROIs were grouped into three clusters: Cluster 1: 8-month severe tau pathology cluster; Cluster 2: Nonpathology hippocampus cluster; Cluster 3: Non-pathology cortex cluster. The coefficient is color-coded, with darker colors indicating a higher Pearson correlation coefficient. The three annotation rows at the top are color-coded for age, genotype, and region, respectively. (F) tdistributed stochastic neighbor embedding (tSNE) plot of all ROIs identified two major transcriptionally distinct clusters. (G) Gene expression levels of spatial markers for six selected regions. Color intensity represents the marker’s expression levels in each ROI\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6941464/v1/39d45f4a1066499ae69278fd.png"},{"id":86445119,"identity":"c5da49da-f85a-4c0c-8503-3f52d2747232","added_by":"auto","created_at":"2025-07-10 17:37:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1182788,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial transcriptomic signatures of PS19 mice at 2 months of age. (A) The results of PCA on 2-month-old ROIs show that the first two principal components account for the specified percentages of data variation along the x- and y-axes, respectively. (B) The UpSet plot illustrates the DEGs from all six regions, with counts for CA1, CA3, DG, PIR, RSP, and SS being 1, 658, 15, 1, 2, and 2, respectively. (C) The volcano plot depicts the DEGs between PS19 and WT mice in the CA3 region at 2 months of age, with color-coded symbols indicating the fold change and p values relative to the thresholds. Green: p \u0026lt; 0.01, and log2 (fold change) \u0026lt; -0.5; Red: p \u0026lt; 0.01, and log2 (fold change) \u0026gt; 0.5; Pink: p \u0026gt; 0.01, and |log2 (fold change) | \u0026gt; 1; Gold: p \u0026lt; 0.01, and |log2 (fold change) | \u0026lt; 0.5; Grey: p \u0026gt; 0.01, and | log2 (fold change) | \u0026lt; 0.5. (D) Donut chart showing cell type annotation on 658 DEGs. (E) SYNGO (Synaptic Gene Ontologies) Biological Process terms from the 658 DEGs in CA3 are depicted as a sunburst plot, with colors indicating the significance levels of the GO domains. (F) The GO Biological Process analysis on all 658 DEGs, with the gene count for each GO term represented by the circle size, where red and blue colors denote the adjusted p values. (G) Disease-specific GO terms derived from AD-associated GO terms defined by the TREAT-AD Center at Emory-Sage-SGC are categorized into ten major domains, with numbers indicating the terms belonging to each domain. (H) The network visualization of tau protein binding, unfolded protein-related, and lysosome-related GO terms from the gene enrichment analysis results, depicted in G, with colors representing the log2(fold change) of the DEGs.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6941464/v1/127d2a698f268c9284fcb647.png"},{"id":86445803,"identity":"c384f867-c291-4562-9126-bd880d0ac1c7","added_by":"auto","created_at":"2025-07-10 17:45:37","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2817987,"visible":true,"origin":"","legend":"\u003cp\u003eTau-driven spatial transcriptomic signatures precede overt tau accumulation. (A) NFT signature scores of genes from a snRNA dataset of AT8+ cells from patients with AD in the regions analyzed in our study. Two-tailed and unpaired t-test. (B) A heatmap depicting the expression levels of the NFT gene set. The NFT genes are grouped into three clusters. Cluster 1: DG-specific NFT gene set; Cluster 2: CA3-specific NFT gene set; Cluster 3: Shared NFT gene set. (C) The correlation between Mapt mRNA levels and NFT signature scores in WT (light green dots) and PS19 (dark green dots) ROIs. (D) Pgk1 gene network visualization of the gene enrichment analysis results. The color indicates the log2(fold change) of each DEG. (E) Pgk1 co-expressed genes based on a co-expression network analysis of RNA-seq data from AD cases and controls (Agora). Each node represents a different gene. The green shade of the circles indicates the frequency of significant co-expression; the red outline of the circles indicates that the gene is among the DEGs in our dataset. (F) Protein-coding genes for 31 glycolytic enzymes in the glycolysis metabolic pathway are illustrated by BioRender. (G) Volcano plot of hit genes from CRISPR screens in the iPSC-derived neuron. Positive hits are in red, and negative in green. MAPT and PGK1 are among the top negative hits. (H) RNAscope staining results for Pgk1 in the CA3 region of 2-month-old WT and PS19 mice.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6941464/v1/3f06cb036a695815b47f1528.png"},{"id":86445122,"identity":"b2e34c38-d005-401b-ad32-71fb0b7e97a5","added_by":"auto","created_at":"2025-07-10 17:37:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1406841,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial transcriptomic profiling of PS19 mice at the severe stage of tau pathology. (A) The PCA results of 8-month-old ROIs. The first two principal components explain the indicated percentages of data variation on the x- and y-axes, respectively. (B) The UpSet plot illustrates the number of DEGs from all six regions in 8-month-old PS19 mice compared to age-matched WT animals. The DEGs for CA1, CA3, DG, PIR, RSP, and SS are 56, 88, 335, 334, 578, and 63, respectively. (C) Results of GO analysis for the 12 DEGs shared by all six brain regions. (D and E) Volcano plots depicting the DEGs between PS19 and WT in the DG (D) and RSP (E) regions at 8 months of age. Color-coded symbols indicate the fold change and p-values, showing whether they are below or above the thresholds. Green: p \u0026lt; 0.01, and log2 (fold change) \u0026lt; -0.5; Red: p \u0026lt; 0.01, and log2 (fold change) \u0026gt; 0.5; Pink: p \u0026gt; 0.01, and |log2 (fold change) | \u0026gt; 1; Gold: p \u0026lt; 0.01, and |log2 (fold change) | \u0026lt; 0.5; Grey: p \u0026gt; 0.01, and | log2 (fold change) | \u0026lt; 0.5. (F) A 3D heatmap depicts the percentage of cell types for the DEGs in six regions, with height and colors indicating the ratio of cell types. (G) The dot heatmap represents the results of the GO analysis for the DEGs from all six regions of 8-month-old mice, with the gene ratio in each GO term represented by the circle. Red and blue colors indicate the p-values. (H) Gene network visualization of the gene enrichment analysisresults. The colors of the center node indicate the regions in which the enriched pathway terms appear, while the node size reflects the number of genes associated with the term\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6941464/v1/4c876479e44d285689cdaf8f.png"},{"id":86446315,"identity":"71ee2385-06cf-4f47-a43d-0f33407b17c4","added_by":"auto","created_at":"2025-07-10 17:53:37","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":374170,"visible":true,"origin":"","legend":"\u003cp\u003eProgressive glial activation in the hippocampus and cortex of P301S tau mice. (A) DAA and DAM signature scores for six brain regions at three stages. Two-way ANOVA was used to determine the differences between ages and genotypes. Only the differences between genotypes are indicated. (B) The correlation between DAA and DAM signature scores in WT (light green dots) and PS19 (dark green dots) ROIs. (C) The Spearman correlation between AT8 intensity and mRNA levels for all ROIs. (D) C1qa was identified as a hub gene for DEGs in the 8-month-old PS19 hippocampus by MEGENA\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6941464/v1/699585adf5d967dbd0772729.png"},{"id":86446316,"identity":"db127d62-d0da-4ab9-9df0-8e2e1ceb9e16","added_by":"auto","created_at":"2025-07-10 17:53:37","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":979876,"visible":true,"origin":"","legend":"\u003cp\u003eSpatiotemporal transcriptomic signatures in P301S reveal regional disease progression.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(A) Illustration of TrendCatcher data processing and GO TimeHeatmap outputs. (B) Venn diagram of DDEGs in six brain regions. (C) Integrated GO TimeHeatmap for six brain regions, where the dot color indicates the average log2(fold change) of genes in the enriched pathway term, and the dot size represents the number of genes associated with that term. (D) ATP metabolic process and oxidative phosphorylation signature scores for six brain regions at three stages. Two-way ANOVA was used to determine the differences between ages and genotypes; only the differences between genotypes are indicated. (E) Summary of the dynamic regulation of ATP metabolic processes, neuroinflammation, cognition, and LTP in the cortex and hippocampus ROIs during tau pathology development in PS19 mice. The curves were generated in BioRender.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-6941464/v1/bfb69fe00116c2d0feda042f.png"},{"id":102654444,"identity":"4d8f51ff-b6b2-48cf-ad38-744120614a53","added_by":"auto","created_at":"2026-02-14 08:07:50","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3412780,"visible":true,"origin":"","legend":"Article File","description":"","filename":"SpatiotemporalWangetalEMM.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6941464/v1_covered_ef580514-7d75-4085-908f-7972588ecdd6.pdf"},{"id":86445131,"identity":"7fba7b51-e4a7-4ec3-b967-42c3920ef2cf","added_by":"auto","created_at":"2025-07-10 17:37:38","extension":"xls","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8297984,"visible":true,"origin":"","legend":"Supplemental Table","description":"","filename":"SI2counttable.xls","url":"https://assets-eu.researchsquare.com/files/rs-6941464/v1/0d0feafdf39292b49a626c42.xls"},{"id":86445133,"identity":"6ed0f304-bcef-4919-a86b-1e67b24780be","added_by":"auto","created_at":"2025-07-10 17:37:38","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":17917375,"visible":true,"origin":"","legend":"Supplemental Figures","description":"","filename":"SI1figures.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6941464/v1/382a81c8498ab14326ec4ca0.pdf"}],"financialInterests":"There is no conflict of interest","formattedTitle":"Spatiotemporal transcriptomic profiling reveals metabolic dysfunction prior to overt tauopathy in the PS19 mouse model","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"experimental-and-molecular-medicine","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"emm","sideBox":"Learn more about [Experimental \u0026 Molecular Medicine](http://www.nature.com/emm/)","snPcode":"12276","submissionUrl":"https://mts-emm.nature.com/cgi-bin/main.plex","title":"Experimental \u0026 Molecular Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Alzheimer's disease, frontotemporal dementia, spatial transcriptomics, tauopathy, metabolic dysfunction, Pgk1, glial activation","lastPublishedDoi":"10.21203/rs.3.rs-6941464/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6941464/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Abnormal accumulation of hyperphosphorylated tau in neurofibrillary tangles is a hallmark of neurodegenerative diseases, such as Alzheimer’s disease (AD) and frontotemporal dementia. In AD, tangle pathology characteristically develops in brain regions with heightened vulnerability, such as the entorhinal cortex and hippocampus. Emerging evidence implicates mitochondrial dysfunction and metabolic disturbances in AD progression, yet the relationship between regional vulnerability and pretangle tau-driven transcriptomic changes remains unclear. To address this critical gap, we utilized the tau P301S transgenic mouse model (PS19 line), which develops tau inclusions. Using spatial transcriptomic profiling across the hippocampal and cortical regions at selected disease stages, we captured spatiotemporal transcriptional responses to tauopathy. Our findings reveal that disease-associated microglia and astrocyte phenotypes emerge concurrently with phosphorylated tau accumulation across multiple brain regions. Intriguingly, the expression of Pgk1, a hub gene of the glycolytic pathway, was upregulated along with other metabolic pathway genes in the CA3 region at 2 months of age, preceding the onset of detectable tau tangle pathology, and correlated with tangle severity, suggesting early metabolic dysregulation in vulnerable regions. Further analysis of differentially expressed genes uncovered region-specific and temporally dynamic transcriptional patterns in the cortex and hippocampus. Early saturable alterations in ATP metabolic processes, glycolysis, and oxidative phosphorylation appeared in the hippocampus at two months of age, with delayed engagement in the cortical regions. These results underscore the contributions of metabolic stress and glial activation to tauopathy and regional vulnerability, highlighting spatial transcriptomics as a powerful tool for uncovering region-specific molecular insights into disease mechanisms.","manuscriptTitle":"Spatiotemporal transcriptomic profiling reveals metabolic dysfunction prior to overt tauopathy in the PS19 mouse model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-10 17:37:33","doi":"10.21203/rs.3.rs-6941464/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-08-01T05:54:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-07-30T04:03:51+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-07-20T05:45:12+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-07-15T02:11:57+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-07-15T01:35:20+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-07-09T00:42:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-23T06:44:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-20T20:36:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Experimental \u0026 Molecular Medicine","date":"2025-06-20T20:36:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"experimental-and-molecular-medicine","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"emm","sideBox":"Learn more about [Experimental \u0026 Molecular Medicine](http://www.nature.com/emm/)","snPcode":"12276","submissionUrl":"https://mts-emm.nature.com/cgi-bin/main.plex","title":"Experimental \u0026 Molecular Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3730861a-4b98-42b5-b666-4fdbb93bc41d","owner":[],"postedDate":"July 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":51243617,"name":"Biological sciences/Neuroscience/Diseases of the nervous system/Alzheimer's disease"},{"id":51243618,"name":"Biological sciences/Molecular biology/Transcriptomics"}],"tags":[],"updatedAt":"2026-02-14T08:07:36+00:00","versionOfRecord":{"articleIdentity":"rs-6941464","link":"https://doi.org/10.1038/s12276-026-01652-z","journal":{"identity":"experimental-and-molecular-medicine","isVorOnly":false,"title":"Experimental \u0026 Molecular Medicine"},"publishedOn":"2026-02-13 05:00:00","publishedOnDateReadable":"February 13th, 2026"},"versionCreatedAt":"2025-07-10 17:37:33","video":"","vorDoi":"10.1038/s12276-026-01652-z","vorDoiUrl":"https://doi.org/10.1038/s12276-026-01652-z","workflowStages":[]},"version":"v1","identity":"rs-6941464","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6941464","identity":"rs-6941464","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}