{"paper_id":"2cb032ec-c7f3-493a-af38-863f46277f23","body_text":"Extracellular Vesicle Profiling Reveals Novel Autism Signatures in Patient-Derived Forebrain Organoids | 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 Extracellular Vesicle Profiling Reveals Novel Autism Signatures in Patient-Derived Forebrain Organoids Dilek Colak, Isidora Stankovic, Phillip Smit, Jonathan Cross, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6573757/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Oct, 2025 Read the published version in Translational Psychiatry → Version 1 posted 15 You are reading this latest preprint version Abstract Autism Spectrum Disorder (ASD) affects 1 percent of the world's population with an increased prevalence of 178 percent since 2000. Although altered synaptic function putatively accounts for many of the abnormalities seen in ASD, the specific molecular mechanisms underlying this disorder remain poorly defined. A growing body of evidence suggests that extracellular vesicles (EVs), specifically exosomes, play a critical role in cellular communication within the brain. While they have been implicated in various types of diseases from cancer to neurodegeneration, their involvement in ASD remains largely unexplored. In this study, we utilized patient-derived cortical organoid models to characterize EVs secreted by human three-dimensional (3D) tissue and defined their cargo. Our study reports, for the first time, alterations in ASD organoid-derived EVs in comparison to healthy control cortical EVs. By utilizing small RNA sequencing, proteomics, nanoparticle tracking and microscopy, we provide a comprehensive characterization of the cargo carried by EVs secreted from human 3D forebrain models. Our findings reveal substantial differences both in the RNA and protein content of ASD-derived EVs, providing insight into disease mechanisms as well as highlighting the potential of exosome-based diagnostics and therapies for ASD. Health sciences/Diseases/Psychiatric disorders/Autism spectrum disorders Biological sciences/Neuroscience/Molecular neuroscience Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Full Text Additional Declarations The authors have declared there is NO conflict of interest to disclose Supplementary Files 177DEGdataupdated.xlsx Data Set 1 allsignificantmiRNAs.xlsx Data Set 2 362differentiallyregulatedproteins.xlsx Data Set 3 SupplementaryMaterial.pdf Stankovic_Supplementary Figures Cite Share Download PDF Status: Published Journal Publication published 10 Oct, 2025 Read the published version in Translational Psychiatry → Version 1 posted Editorial decision: revise 24 Jun, 2025 Review # 4 received at journal 26 May, 2025 Review # 3 received at journal 19 May, 2025 Review # 1 received at journal 19 May, 2025 Review # 2 received at journal 16 May, 2025 Reviewer # 5 agreed at journal 09 May, 2025 Reviewer # 4 agreed at journal 09 May, 2025 Reviewer # 3 agreed at journal 05 May, 2025 Reviewer # 2 agreed at journal 05 May, 2025 Reviewer # 1 agreed at journal 05 May, 2025 Reviewers invited by journal 05 May, 2025 Editor assigned by journal 05 May, 2025 Submission checks completed at journal 05 May, 2025 First submitted to journal 03 May, 2025 Unknown event 02 May, 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. 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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-6573757\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":452135783,\"identity\":\"681086a7-4c7c-4b69-ae17-b4c522577735\",\"order_by\":0,\"name\":\"Dilek Colak\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYDCCwwyMDxIMbOSATAOICDtzAwMDG14tzAYfKtKMEVqYGQloOcDAJjnjzOHEBqK18B1nfiDN23Y4fW178waGHxX38vhBWj6UHcapRfIwm4Exb1t67rYzxwoYe84UF0s2MzYwzjiHW4vBYR6GZN4269xtN3IMmBnbEhI3HGZsYAbai1fLYd425nSz+28gWvaDtPzFr4WxccYZ5wSzGzxQW4B+ATLw+sWYARjIhtvOpBUc7DmTkDgDaMvBnnPpOLXwnT/8/AcwKuXNjh/e+OBHRUJif3vzwQc/yqxxakEBBzAYo2AUjIJRMArIAwA+SFtxO4ffwQAAAABJRU5ErkJggg==\",\"orcid\":\"https://orcid.org/0000-0003-4928-3999\",\"institution\":\"Weill Cornell Medicine, Cornell University\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Dilek\",\"middleName\":\"\",\"lastName\":\"Colak\",\"suffix\":\"\"},{\"id\":452135784,\"identity\":\"7f4ce7ad-a69f-41f7-abd3-2af17396b615\",\"order_by\":1,\"name\":\"Isidora Stankovic\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Isidora\",\"middleName\":\"\",\"lastName\":\"Stankovic\",\"suffix\":\"\"},{\"id\":452135785,\"identity\":\"daefa7ae-c5ff-4892-a326-c514d3698a46\",\"order_by\":2,\"name\":\"Phillip Smit\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Phillip\",\"middleName\":\"\",\"lastName\":\"Smit\",\"suffix\":\"\"},{\"id\":452135786,\"identity\":\"2709cbfd-aa75-457e-a812-eef1d57666fa\",\"order_by\":3,\"name\":\"Jonathan Cross\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jonathan\",\"middleName\":\"\",\"lastName\":\"Cross\",\"suffix\":\"\"},{\"id\":452135787,\"identity\":\"67187e21-1aa8-466c-8814-9d8535fe85e6\",\"order_by\":4,\"name\":\"Paul Wolujewicz\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Paul\",\"middleName\":\"\",\"lastName\":\"Wolujewicz\",\"suffix\":\"\"},{\"id\":452135788,\"identity\":\"d95b81b2-252f-4d1b-bc79-4e1cf4407c13\",\"order_by\":5,\"name\":\"David Greening\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0001-7516-485X\",\"institution\":\"Baker Heart and Diabetes Institute\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"David\",\"middleName\":\"\",\"lastName\":\"Greening\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-05-01 18:35:21\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6573757/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6573757/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1038/s41398-025-03607-w\",\"type\":\"published\",\"date\":\"2025-10-10T04:00:00+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":82558613,\"identity\":\"ae314fb0-61bf-4c5b-9117-b2214795db09\",\"added_by\":\"auto\",\"created_at\":\"2025-05-13 01:23:16\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1231120,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eForebrain organoids generated from iPSC lines derived from healthy controls and individuals with ASD\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ea) \\u003c/strong\\u003eSchematic depicting experimental design and timeline. Briefly, forebrain organoids were generated using a previously described protocol (59). At 60 DIV, media was collected, and EVs were isolated, followed by subsequent analysis. \\u003cstrong\\u003eb) \\u003c/strong\\u003eLight microscopy images of representative brain organoids at 60 DIV from all 16 lines used in the study. \\u003cstrong\\u003ec) \\u003c/strong\\u003eBar graph depicts average size of organoids derived from CTRL and ASD lines (\\u003cem\\u003en \\u003c/em\\u003e= 8 lines per group; \\u003cem\\u003en \\u003c/em\\u003e= 3 organoids per line).\\u003c/p\\u003e\\n\\u003cp\\u003ed) Representative images of SOX2 (green), β-III-tubulin (red) and DAPI (blue) immunostaining in CTRL and ASD organoids to assess proliferative and neurogenic zones. \\u003cstrong\\u003ee) \\u003c/strong\\u003eQuantifications of ventricular-like zone density and thickness across 16 organoid lines used in the study (\\u003cem\\u003en \\u003c/em\\u003e= 8 lines per group; \\u003cem\\u003en \\u003c/em\\u003e= 3-10 organoids per line). Scale bar = 0.25 mm for b; 500 µm for d. Data is represented as mean ± SEM, \\u003cem\\u003ep \\u003c/em\\u003e\\u0026lt; 0.05.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure1.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6573757/v1/b8fe451a4d4ba7aa5aab6a67.jpg\"},{\"id\":82558641,\"identity\":\"34eb141a-d9fd-45e3-926e-c03f579e3eee\",\"added_by\":\"auto\",\"created_at\":\"2025-05-13 01:23:22\",\"extension\":\"jpg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1050788,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eExosome abundance in organoid-derived EVs\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ea) \\u003c/strong\\u003eSchematic of exosome validation methods. EVs were isolated from maintenance media of CTRL and ASD dorsal forebrain organoids at 60 DIV using a combination of Exo-isolation kit and centrifugation. EVs were then resuspended in either RIPA or PBS buffers, depending on downstream analysis. \\u003cstrong\\u003eb) \\u003c/strong\\u003eRepresentative Western blot examples in pellet and supernatant samples. Only pellets, not supernatant, were positive for exosome markers (CD9, CD63) indicating high efficiency in EV isolation. \\u003cstrong\\u003ec) \\u003c/strong\\u003eRepresentative graphs of nanoparticle tracking analysis (NTA). The x-axis represents concentration (particles/mL), and the y-axis represents particle size (nm). The top four are representative plots from CTRL lines while the bottom four plots are representative examples from ASD lines. The peaks typically appeared in the \\u0026lt; 200nm range, representative of exosome size. \\u003cstrong\\u003ed) \\u003c/strong\\u003eBar graphs depicting no significant difference in either average particle size or concentration between CTRL and ASD EVs at the NTA analysis. Each point on the graph represents an independent cell line. Data are represented as mean ± SEM.\\u003c/p\\u003e\\n\\u003cp\\u003ee) Representative TEM images of EVs isolated from CTRL and ASD organoid media. Vesicles typically displayed a canonical exosome cup/rose shape and size.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure2.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6573757/v1/17c97c85466ccfd16d24d799.jpg\"},{\"id\":82558644,\"identity\":\"fc4c63ac-b251-4731-b9cd-2962960c7d12\",\"added_by\":\"auto\",\"created_at\":\"2025-05-13 01:23:22\",\"extension\":\"jpg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1036172,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eDifferentially regulated RNAs point to translational control and ubiquitin activity in ASD EVs\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ea) \\u003c/strong\\u003eRNA counts by category per ASD and CTRL sample (n = 16 samples). \\u003cstrong\\u003eb) \\u003c/strong\\u003eVolcano plot displaying significantly expressed genes. Thresholds of significance used included Log2 FC \\u0026gt; +/-1.5 and adjusted log10 Benjamini-Hochberg corrected \\u003cem\\u003ep \\u003c/em\\u003e\\u0026lt; +/- 0.05. \\u003cstrong\\u003ec) \\u003c/strong\\u003eHierarchical and K-means heatmap of the top 50 differentially expressed RNAs in each sample (see supplementary materials for the full list of differentially regulated RNAs). \\u003cstrong\\u003ed) \\u003c/strong\\u003eBar graph of GSEA enrichment terms from the respective pathway database. Terms ordered by descending odds ratio. Significant GSEA categories include i) Gene Ontology: Biological Processes (BP), ii) KEGG Kyoto Encyclopedia of Genes and Genomes, iii) Gene Ontology: Molecular Function (MF), iv) Gene Ontology: Cellular Component (CC). \\u003cstrong\\u003ee) \\u003c/strong\\u003eHierarchical and K-means heatmap of the top 31 differentially expressed miRNAs in each sample; \\u003cem\\u003ep \\u003c/em\\u003e\\u0026lt; 0.05. \\u003cstrong\\u003ef) \\u003c/strong\\u003emiRNA–gene interaction network and hub gene analysis. Node size corresponds to the degree of connectivity, with larger nodes indicating higher numbers of interactions.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure3.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6573757/v1/24d9df0b06c478092f3568c9.jpg\"},{\"id\":82558618,\"identity\":\"84ca3631-28dc-4b2a-bf7c-e68b4aa6603f\",\"added_by\":\"auto\",\"created_at\":\"2025-05-13 01:23:16\",\"extension\":\"jpg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1065595,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAltered protein expression comprises translation and protein degradation related categories in ASD EVs\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ea) \\u003c/strong\\u003eProtein counts by category per ASD and CTRL sample (n = 16 samples). \\u003cstrong\\u003eb) \\u003c/strong\\u003eVolcano plot displaying proteins expressed significantly. Thresholds of significance used included Log2 FC \\u0026gt; +/- 1.5 and adjusted log10 Benjamini-Hochberg corrected \\u003cem\\u003ep \\u003c/em\\u003e\\u0026lt; 0.05. \\u003cstrong\\u003ec) \\u003c/strong\\u003eCoefficient of variance in CV and ASD lines, (n = 16 samples), non-significant. \\u003cstrong\\u003ed) \\u003c/strong\\u003eClustered heatmap of 362 significant proteins based on a Student T-test analysis (\\u003cem\\u003ep \\u003c/em\\u003e\\u0026lt; 0.05). Values based on z-score normalization. \\u003cstrong\\u003ee) \\u003c/strong\\u003eGene ontology analysis of significant proteins using enrichR. Top 10 categories selected (\\u003cem\\u003ep \\u003c/em\\u003e\\u0026lt; 0.05); odds ratio observed between ASD and CTRLs. Terms ordered by descending odds ratio. Significant GSEA categories include i) Gene Ontology: Biological Processes (BP), ii) KEGG Kyoto Encyclopedia of Genes and Genomes, iii) Gene Ontology: Molecular Function (MF), iv) Gene Ontology: Cellular Component (CC).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure4.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6573757/v1/0adc3dd7123b1108882882e7.jpg\"},{\"id\":82558640,\"identity\":\"7a752b68-5971-42b7-bcdc-68af221d47f1\",\"added_by\":\"auto\",\"created_at\":\"2025-05-13 01:23:22\",\"extension\":\"jpg\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1079506,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAltered pathways predicted by network analysis in ASD EVs\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTopology-based network enrichment analysis of differentially expressed genes and proteins in ASD-derived EVs. Top: Gene network analysis revealed 10 significantly enriched categories, including apoptosis, GDP metabolism, and clathrin-mediated endocytosis (\\u003cem\\u003ep \\u003c/em\\u003e\\u0026lt; 0.01). Bottom: Protein network analysis identified highly interconnected enrichment in translation, RNA processing, and biosynthetic pathways (\\u003cem\\u003ep \\u003c/em\\u003e\\u0026lt; 1×10\\u003csup\\u003e-15\\u003c/sup\\u003e). Node size reflects the degree of connectivity within the GO network.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure5.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6573757/v1/14c6b44bd3f04a52dbb61963.jpg\"},{\"id\":82558652,\"identity\":\"63b21ef9-ded6-4c2c-8727-7d47043ba03b\",\"added_by\":\"auto\",\"created_at\":\"2025-05-13 01:23:25\",\"extension\":\"jpg\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":553517,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eDifferentially regulated RNAs and proteins in ASD EVs include ASD risk genes a\\u003c/strong\\u003e) Heatmap of the significant SFARI genes among the differentially expressed mRNAs in each group. Values based on z-score normalization (\\u003cem\\u003ep \\u003c/em\\u003e\\u0026lt; 0.05). \\u003cstrong\\u003eb) \\u003c/strong\\u003eHeatmap of the significant SFARI genes among the differentially expressed proteins. Values based on z-score normalization (\\u003cem\\u003ep \\u003c/em\\u003e\\u0026lt; 0.05). \\u003cstrong\\u003ec) \\u003c/strong\\u003eenrichR gene ontology analysis of the significant SFARI risk genes among the differentially expressed proteins in ASD EVs. Top categories selected (\\u003cem\\u003ep \\u003c/em\\u003e\\u0026lt; 0.05); odds ratio observed between ASD and CTRL.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure6.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6573757/v1/4af9a2dffa58f176e70e76c6.jpg\"},{\"id\":93285732,\"identity\":\"e4f1faf8-1881-4c51-8e56-ce241f3a2f66\",\"added_by\":\"auto\",\"created_at\":\"2025-10-11 07:12:30\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":6647414,\"visible\":true,\"origin\":\"\",\"legend\":\"Article File\",\"description\":\"\",\"filename\":\"StankovicetalApril22.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6573757/v1_covered_777d8266-726b-47aa-a7d7-db6c61cef7de.pdf\"},{\"id\":82558637,\"identity\":\"14ad94b5-cd86-4a51-8aea-fe31064e8b3b\",\"added_by\":\"auto\",\"created_at\":\"2025-05-13 01:23:21\",\"extension\":\"xlsx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":38860,\"visible\":true,\"origin\":\"\",\"legend\":\"Data Set 1\",\"description\":\"\",\"filename\":\"177DEGdataupdated.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6573757/v1/56f6183453c8025d0870dd2e.xlsx\"},{\"id\":82558633,\"identity\":\"aa154207-8ef1-4089-94da-08ea0e58ff8c\",\"added_by\":\"auto\",\"created_at\":\"2025-05-13 01:23:19\",\"extension\":\"xlsx\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":12106,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eData Set 2\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"allsignificantmiRNAs.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6573757/v1/d21aa5b9b94b4d4476e91ea1.xlsx\"},{\"id\":82558616,\"identity\":\"14b377fe-fc18-464e-afe9-b2f8f534e119\",\"added_by\":\"auto\",\"created_at\":\"2025-05-13 01:23:16\",\"extension\":\"xlsx\",\"order_by\":3,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":271809,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eData Set 3\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"362differentiallyregulatedproteins.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6573757/v1/095d983f65eea6198d9e5a9a.xlsx\"},{\"id\":82558642,\"identity\":\"6b287771-5c0d-4498-9e41-6865f081b3c1\",\"added_by\":\"auto\",\"created_at\":\"2025-05-13 01:23:22\",\"extension\":\"pdf\",\"order_by\":4,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":424058,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eStankovic_Supplementary Figures\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"SupplementaryMaterial.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6573757/v1/143d5cc17a274d4389805a99.pdf\"}],\"financialInterests\":\"The authors have declared there is \\u003cb\\u003eNO\\u003c/b\\u003e conflict of interest to disclose\",\"formattedTitle\":\"Extracellular Vesicle Profiling Reveals Novel Autism Signatures in Patient-Derived Forebrain Organoids\",\"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\":\"info@researchsquare.com\",\"identity\":\"translational-psychiatry\",\"isNatureJournal\":false,\"hasQc\":false,\"allowDirectSubmit\":false,\"externalIdentity\":\"tp\",\"sideBox\":\"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)\",\"snPcode\":\"41398\",\"submissionUrl\":\"https://mts-tp.nature.com/cgi-bin/main.plex\",\"title\":\"Translational Psychiatry\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"ejp\",\"reportingPortfolio\":\"Nature AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6573757/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6573757/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"Autism Spectrum Disorder (ASD) affects 1 percent of the world's population with an increased prevalence of 178 percent since 2000. Although altered synaptic function putatively accounts for many of the abnormalities seen in ASD, the specific molecular mechanisms underlying this disorder remain poorly defined. A growing body of evidence suggests that extracellular vesicles (EVs), specifically exosomes, play a critical role in cellular communication within the brain. While they have been implicated in various types of diseases from cancer to neurodegeneration, their involvement in ASD remains largely unexplored. In this study, we utilized patient-derived cortical organoid models to characterize EVs secreted by human three-dimensional (3D) tissue and defined their cargo. Our study reports, for the first time, alterations in ASD organoid-derived EVs in comparison to healthy control cortical EVs. By utilizing small RNA sequencing, proteomics, nanoparticle tracking and microscopy, we provide a comprehensive characterization of the cargo carried by EVs secreted from human 3D forebrain models. Our findings reveal substantial differences both in the RNA and protein content of ASD-derived EVs, providing insight into disease mechanisms as well as highlighting the potential of exosome-based diagnostics and therapies for ASD.\",\"manuscriptTitle\":\"Extracellular Vesicle Profiling Reveals Novel Autism Signatures in Patient-Derived Forebrain Organoids\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-05-13 01:23:08\",\"doi\":\"10.21203/rs.3.rs-6573757/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"revise\",\"date\":\"2025-06-24T09:33:15+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"This content is not available.\",\"date\":\"2025-05-26T14:24:19+00:00\",\"index\":4,\"fulltext\":\"This content is not available.\"},{\"type\":\"editorInvitedReview\",\"content\":\"This content is not 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