Evidence map›Paper›PMID 40470213›Full record

ArticleResearch square2025

Extracellular Vesicle Profiling Reveals Novel Autism Signatures in Patient-Derived Forebrain Organoids.

Isidora Stankovic, Phillip Smit, Jonathan Cross, Paul Wolujewicz, David Greening, Dilek Colak

Abstract readPreprint
In one paragraph

Article in Research square, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Isidora StankovicCenter for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA.
Phillip SmitDepartment of Medical Sciences, Frank H. Netter School of Medicine, Quinnipiac University, North Haven, CT, USA.
Jonathan CrossBaker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia.
Paul WolujewiczCenter for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA.
David GreeningBaker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia.ORCID 0000-0001-7516-485X
Dilek ColakCenter for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA.ORCID 0000-0003-4928-3999

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID40470213
PMCPMC12136235

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.