OSCR

TGF-β signaling promotes astroglial activation and TDP-43 proteinopathy in organoid models of frontotemporal lobar degeneration.

Code ↔ Paper

16 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 16 matches
  1. [1] § Results › Precocious neurogenesis and astrogliogenesis in GRN–/– cortical organoids. ↔ B. Clustering_GRNKO.ipynb, lines 540–554 · score 0.89 · CT neuroblasts, mixed identity, early neuroblasts, ependymal cells, radial glia, inhibitory neuron
  2. [2] § Methods › Transcriptomics › Cell-cell communication analysis. ↔ C. Analysis_GRNKO.ipynb, lines 478–559 · score 0.85 · receiver cell, potential target genes, cell communication, cutoff, infer, predict
  3. [3] § Results › GRNR493X cortical organoids phenocopy astroglial phenotypes in GRN–/– cortical organoids. ↔ B. Clustering_GRNKO.ipynb, lines 540–554 · score 0.81 · LGE inhibitory neurons, mixed identity, ependymal cells, radial glia, neuroblasts, OPCs
  4. [4] § Methods › Transcriptomics › Reanalysis of other datasets. ↔ D. Subclustering_Ast_GRNKO.ipynb, lines 398–455 · score 0.78 · FindTransferAnchors, find anchors, reference UMAP, query, Sadick
  5. [5] § Results › GRNR493X cortical organoids phenocopy astroglial phenotypes in GRN–/– cortical organoids. ↔ B. Clustering_R493X.ipynb, lines 517–530 · score 0.72 · LGE inhibitory neurons, ependymal cells, radial glia, neuroblasts, OPCs, glioblasts
  6. [6] § Results › Precocious neurogenesis and astrogliogenesis in GRN–/– cortical organoids. ↔ B. Clustering_R493X.ipynb, lines 517–530 · score 0.69 · ependymal cells, radial glia, inhibitory neuron, neuroblasts, OPC, LGE
  7. [7] § Methods › Transcriptomics › Comparison with Bhaduri et al., 2020. ↔ D. Subclustering_Ast_GRNKO.ipynb, lines 398–455 · score 0.65 · MapQuery, FindTransferAnchors, UMAP
  8. [8] § Methods › Transcriptomics › Astroglia subclustering. ↔ B. Clustering_R493X.ipynb, lines 352–361 · score 0.61 · FindClusters, FindNeighbors, RunUMAP, resolution
  9. [9] § Methods › Transcriptomics › Astroglia subclustering. ↔ B. Clustering_GRNKO.ipynb, lines 148–159 · score 0.61 · FindClusters, FindNeighbors, RunUMAP, resolution
  10. [10] § Methods › Transcriptomics › Clustering and annotation. ↔ B. Clustering_R493X.ipynb, lines 352–361 · score 0.61 · FindClusters, FindNeighbors, RunUMAP, resolution, Clustering
  11. [11] § Methods › Transcriptomics › Clustering and annotation. ↔ B. Clustering_GRNKO.ipynb, lines 148–159 · score 0.61 · FindClusters, FindNeighbors, RunUMAP, resolution, Clustering
  12. [12] § Results › Precocious neurogenesis and astrogliogenesis in GRN–/– cortical organoids. ↔ C. Analysis_GRNKO.ipynb, lines 73–86 · score 0.60 · TMEM106B, EMX2, FOXG1, PSAP, WNT1, STMN2
  13. [13] § Results › Precocious neurogenesis and astrogliogenesis in GRN–/– cortical organoids. ↔ C. Analysis_R493X.ipynb, lines 78–85 · score 0.60 · TMEM106B, EMX2, FOXG1, PSAP, WNT1, STMN2
  14. [14] § Methods › Transcriptomics › Quality control, normalization, and dimensional reduction. ↔ B. Clustering_GRNKO.ipynb, lines 105–121 · score 0.54 · DoubletFinder, variable features, Elbow
  15. [15] § Results › Loss of PGRN leads to aberrant growth in cortical organoids. ↔ B. Clustering_GRNKO.ipynb, lines 484–523 · score 0.51 · S100B, radial glia, NES, progenitor, GFAP, SOX9
  16. [16] § Results › Loss of PGRN leads to aberrant growth in cortical organoids. ↔ B. Clustering_R493X.ipynb, lines 454–497 · score 0.51 · S100B, radial glia, NES, progenitor, GFAP, SOX9

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The authors' code

Jupyter notebook · 634 lines · 37 KB · no license · 6 matches

The registry keeps no copy of this file: its repository has no license, so its authors keep all their rights to it. Your browser shows it from its source, with JavaScript.

It can be read at the source: B. Clustering_GRNKO.ipynb.

Overview

Authors: Arren C. Ramsey1,2,3, Xiao-Yan Tang1,3, Magdalena J. Macias1, Patricia R. Nano4, Rufei Lu1, Brian Benito1, Cameron M. Lau1, Jisu Park1,3, Jiasheng Zhang1,5, Wandy Beatty6, Tanzila Mukhtar7,8, Arnold R. Kriegstein2,3,7,8, Aparna Bhaduri4, Elise Marsan9, Eric J. Huang1,2,3,5
  1. Department of Pathology
  2. BMS Graduate Program, and
  3. Weill Institute for Neurosciences, UCSF, San Francisco, California, USA
  4. Department of Biological Chemistry, UCLA, Los Angeles, California, USA
  5. Department of Pathology & Immunology and
  6. Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, Missouri, USA
  7. The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research and
  8. Department of Neurology, UCSF, San Francisco, California, USA
  9. Center for Alzheimer’s and Related Dementias, NIH, Bethesda, Maryland, USA
Journal: The Journal of clinical investigation, volume 136, issue 14, article e190035
Dates: received 9 December 2024; accepted 2 June 2026; published online 16 June 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1172/jci190035 · PMID 42302828 · PMCID PMC13367973 · OpenAlex W7164938026
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), mouse (organism), Alzheimer's / dementia (population), cellular / molecular (subfield)
Methods: Statistics, Smoothing, state filtering, decompositions
Keywords: Aging, Neuroscience, Dementia, Neurodegeneration, iPS cells
MeSH: Astrocytes*, DNA-Binding Proteins*, Frontotemporal Lobar Degeneration*, Organoids*, Signal Transduction*, Transforming Growth Factor beta*, Animals, Humans, Induced Pluripotent Stem Cells, Mice, Mice, Knockout, Progranulins (* major topic)
Topic: Amyotrophic Lateral Sclerosis Research (Neurology, Medicine), according to OpenAlex
Citations: not cited yet (Europe PMC); 50 references in the paper
Research resources: anti-CD44 RRID:AB_1078467, Donkey anti-chicken AlexaFluor 633 RRID:AB_10853143, anti-TTBK1 RRID:AB_10988089, Donkey anti-mouse AlexaFluor 568 RRID:AB_11180865, Donkey anti-mouse AlexaFluor 488 RRID:AB_141607, Donkey anti-rat AlexaFluor 488 RRID:AB_141709, anti-DCX RRID:AB_1586992, Donkey anti-mouse AlexaFluor 647 RRID:AB_162542, anti-CTIP2 clone 25B6 RRID:AB_2064130, anti-cCas3 RRID:AB_2070042, anti-CTSB RRID:AB_2086949, Peroxidase (HRP) Goat anti-Rabbit IgG RRID:AB_2099233, anti-GORASP2 RRID:AB_2113473, anti-MAP2 RRID:AB_2138153, anti-SOX9 RRID:AB_2194160, anti-TTBK2 RRID:AB_2211507, anti-NES clone 10CS RRID:AB_2251134, anti-CDC7 RRID:AB_2276095, anti-SOX2 RRID:AB_2286686, Donkey anti-chicken AlexaFluor 488 RRID:AB_2340375, Donkey anti-guinea pig AlexaFluor 488 RRID:AB_2340472, Peroxidase (HRP) Donkey anti-Rat IgG RRID:AB_2340638, Donkey anti-goat AlexaFluor 488 RRID:AB_2534102, Donkey anti-goat AlexaFluor 568 RRID:AB_2534104, Donkey anti-rabbit AlexaFluor 488 RRID:AB_2535792, Donkey anti-goat AlexaFluor 647 RRID:AB_2535864, Donkey anti-rabbit AlexaFluor 647 RRID:AB_2536183, anti-S100B RRID:AB_2542496, anti-pTDP-43 RRID:AB_2564934, anti-pSMAD3 clone 16H5L12 RRID:AB_2633004, Donkey anti-rat AlexaFluor 647 RRID:AB_2813835, anti-GAPDH RRID:AB_2833041, anti-ITGAV RRID:AB_2880753, anti-PSD95 RRID:AB_300453, anti-HLA-D clone CR3/43 RRID:AB_306142, Donkey anti-rat AlexaFluor 405 RRID:AB_3099480, anti-pTDP-43 clone 11-9 RRID:AB_3251193, RRID:AB_330924, anti-Ki-67 clone B56 RRID:AB_396287, anti-CytoC clone 6H2.B4 RRID:AB_396416, anti-TDP-43 RRID:AB_615042, anti-GFAP clone 2.2B10 RRID:AB_86543, anti-SATB2 clone SATBA4B10 RRID:AB_882455, anti-BSN RRID:AB_887698, RRID:CVCL_Y803, on R RRID:SCR_001905, Quantifications in were done on Fiji RRID:SCR_002285, RRID:SCR_002798, on Python RRID:SCR_008394, RRID:SCR_014329, RRID:SCR_015058, RRID:SCR_016340, RRID:SCR_016341, RRID:SCR_016387, clusterProfiler RRID:SCR_016884, Using Cell Ranger software suite RRID:SCR_017344, The scvelo package RRID:SCR_018168, DoubletFinder RRID:SCR_018771, RRID:SCR_019715, Harmony RRID:SCR_022206, RRID:SCR_024739, The MultiNicheNet package RRID:SCR_025903

Abstract

Dominant mutations in progranulin (GRN) gene cause frontotemporal lobar degeneration (FTLD-GRN), whereas homozygous GRN mutations lead to neuronal ceroid lipofuscinosis, a childhood neurodegenerative disorder. While recent transcriptomic studies reveal profound glial and neuronal pathology in FTLD-GRN at the disease end stage, the mechanism that disrupts glia-neuron homeostasis remains unclear. Using induced pluripotent stem cell–derived cortical organoids, we showed that GRN–/– and GRNR493X mutations led to precocious astrogliosis that promoted neuronal stress and synaptic loss. Single-cell transcriptomics and histopathology analyses revealed a robust activation in the TGF-β signaling pathway in GRN–/– and GRNR493X/R493X astrocytes, which was accompanied by features of immune activation, loss of synaptic support, and abundant pTDP-43+ fibrils in astroglial cytoplasm, a feature characteristic of FTLD-GRN. Intriguingly, blocking TGF-β signaling mitigated astroglial activation and pTDP-43 proteinopathy in GRN–/– organoids. Together, these results provide insights into the cell-autonomous role of astroglial activation in neurodegeneration caused by progranulin deficiency.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above, with 16 matches between paragraphs and lines of code.

Zenodo 20709533

License: CC-BY-4.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: ggplot2 (10 files), Seurat (10 files), tidyverse (7 files), SingleCellExperiment (5 files), Harmony (2 files), patchwork (2 files)
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
11 files

arrenramsey/ramsey_et_al_2026

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 7da0b9261780f9da662acfc306cbf22121c13adf, 17 June 2026
Languages: Jupyter (10)
Size: 12 files, 10 scripts
Software Heritage: not archived
Found in: the Zenodo archive record
Holds: README, 10 notebooks
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: ggplot2 (10 files), Seurat (10 files), tidyverse (7 files), SingleCellExperiment (5 files), Harmony (2 files), patchwork (2 files)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
11 files, not copied: shown from their source

OSCR keeps no copy of these files: this repository has no license that allows it. The reader above shows each one from its source, fetched by your browser at commit 7da0b92, when its fingerprint is the one OSCR verified. How this works.

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 20 scripts, each with its path and the digest of its content;
  • 16 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability

scRNA-seq data have been deposited at GEO, and the accession number is GSE282668. All original code has been deposited at Zenodo (https://doi.org/10.5281/zenodo.20709533) and is publicly available as of the date of publication. Any additional information required to reanalyze the data reported in this paper is available from the corresponding author upon request. All raw data values are included in the Supporting Data Values file.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 15 authors, 5 keywords, 12 MeSH terms, 5 funders, 50 references, 62 RRIDs.

Cite

This paper

Ramsey, A. C., Tang, X.-Y., Macias, M. J., Nano, P. R., Lu, R., Benito, B., Lau, C. M., Park, J., Zhang, J., Beatty, W., Mukhtar, T., Kriegstein, A. R., Bhaduri, A., Marsan, E., & Huang, E. J. (2026). TGF-β signaling promotes astroglial activation and TDP-43 proteinopathy in organoid models of frontotemporal lobar degeneration. The Journal of clinical investigation, 136(14), e190035. https://doi.org/10.1172/jci190035

BibTeX

@article{ramsey2026tgf,
author = {Ramsey, Arren C. and Tang, Xiao-Yan and Macias, Magdalena J. and Nano, Patricia R. and Lu, Rufei and Benito, Brian and Lau, Cameron M. and Park, Jisu and Zhang, Jiasheng and Beatty, Wandy and Mukhtar, Tanzila and Kriegstein, Arnold R. and Bhaduri, Aparna and Marsan, Elise and Huang, Eric J.},
title = {{TGF-β signaling promotes astroglial activation and TDP-43 proteinopathy in organoid models of frontotemporal lobar degeneration}},
journal = {The Journal of clinical investigation},
year = {2026},
month = jun,
volume = {136},
number = {14},
pages = {e190035},
publisher = {American Society for Clinical Investigation},
issn = {0021-9738},
doi = {10.1172/jci190035},
url = {https://doi.org/10.1172/jci190035},
pmid = {42302828},
pmcid = {PMC13367973}
}

RIS

TY - JOUR
AU - Ramsey, Arren C.
AU - Tang, Xiao-Yan
AU - Macias, Magdalena J.
AU - Nano, Patricia R.
AU - Lu, Rufei
AU - Benito, Brian
AU - Lau, Cameron M.
AU - Park, Jisu
AU - Zhang, Jiasheng
AU - Beatty, Wandy
AU - Mukhtar, Tanzila
AU - Kriegstein, Arnold R.
AU - Bhaduri, Aparna
AU - Marsan, Elise
AU - Huang, Eric J.
TI - TGF-β signaling promotes astroglial activation and TDP-43 proteinopathy in organoid models of frontotemporal lobar degeneration
T2 - The Journal of clinical investigation
J2 - J Clin Invest
PY - 2026
DA - 2026/06/16
VL - 136
IS - 14
SP - e190035
SN - 0021-9738
PB - American Society for Clinical Investigation
DO - 10.1172/jci190035
UR - https://doi.org/10.1172/jci190035
LA - en
ER -

CSL-JSON

{
"id": "10.1172/jci190035",
"type": "article-journal",
"title": "TGF-β signaling promotes astroglial activation and TDP-43 proteinopathy in organoid models of frontotemporal lobar degeneration",
"container-title": "The Journal of clinical investigation",
"author": [
{
"family": "Ramsey",
"given": "Arren C."
},
{
"family": "Tang",
"given": "Xiao-Yan"
},
{
"family": "Macias",
"given": "Magdalena J."
},
{
"family": "Nano",
"given": "Patricia R."
},
{
"family": "Lu",
"given": "Rufei"
},
{
"family": "Benito",
"given": "Brian"
},
{
"family": "Lau",
"given": "Cameron M."
},
{
"family": "Park",
"given": "Jisu"
},
{
"family": "Zhang",
"given": "Jiasheng"
},
{
"family": "Beatty",
"given": "Wandy"
},
{
"family": "Mukhtar",
"given": "Tanzila"
},
{
"family": "Kriegstein",
"given": "Arnold R."
},
{
"family": "Bhaduri",
"given": "Aparna"
},
{
"family": "Marsan",
"given": "Elise"
},
{
"family": "Huang",
"given": "Eric J."
}
],
"container-title-short": "J Clin Invest",
"volume": "136",
"issue": "14",
"page": "e190035",
"DOI": "10.1172/jci190035",
"PMID": "42302828",
"PMCID": "PMC13367973",
"ISSN": "0021-9738",
"publisher": "American Society for Clinical Investigation",
"URL": "https://doi.org/10.1172/jci190035",
"language": "en",
"issued": {
"date-parts": [
[
2026,
6,
16
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1038/s41593-026-02367-0 [code]
A reproducible three-dimensional model of human brain tissue to investigate physiological and disease-associated microglia phenotypes.
Journal: Nature neuroscience
In common: Harmony, SingleCellExperiment, Seurat, 3 other tools, Alzheimer's / dementia, cellular / molecular, 2 references
[2] doi:10.1093/bib/bbag411 [code]
Screening of cell-type-specific meta-programs for drug repurposing in Alzheimer's disease.
Journal: Briefings in bioinformatics
In common: Harmony, SingleCellExperiment, Seurat, 2 other tools, Alzheimer's / dementia, 3 references
[3] doi:10.1016/j.nbd.2026.107475
Human TDP-43 expression worsens FTD-related phenotypes in progranulin-insufficient mice.
Journal: Neurobiology of disease
In common: Alzheimer's / dementia, mouse, cellular / molecular, 6 references
[4] doi:10.1038/s41586-026-10310-3 [code]
DNA damage burden causes selective CUX2 neuron loss in neuroinflammation.
Journal: Nature
In common: Seurat, patchwork, ggplot2, 1 other tool, mouse, cellular / molecular, author Eric J. Huang
[5] doi:10.1038/s41586-026-10612-6 [code]
Acquired genetic and cell-state changes in IDH-mutant glioma progression.
Journal: Nature
In common: Harmony, SingleCellExperiment, Seurat, 3 other tools, cellular / molecular, 1 reference
[6] doi:10.1186/s13024-026-00944-2
TDP-43: [GU]-ardian of the transcriptome.
Journal: Molecular neurodegeneration
In common: cellular / molecular, 6 references
[7] doi:10.1038/s44318-026-00818-9 [code]
FAM134B-mediated ER-phagy degrades APP and suppresses Alzheimer's disease pathology.
Journal: The EMBO journal
In common: Harmony, SingleCellExperiment, Seurat, 3 other tools, Alzheimer's / dementia, mouse, cellular / molecular
[8] doi:10.1038/s41586-026-10414-w [code]
Focal white matter lesions drive grey matter inflammation and synapse loss.
Journal: Nature
In common: Harmony, SingleCellExperiment, Seurat, 3 other tools, Alzheimer's / dementia, mouse, cellular / molecular
[9] doi:10.1007/s10571-026-01743-5 [code]
Adapted Smart-seq3xpress Facilitates Selective Microglial Transcriptomic Profiling From Frozen Brain Tissue.
Journal: Cellular and molecular neurobiology
In common: Seurat, patchwork, ggplot2, 1 other tool, mouse, cellular / molecular, 3 references
[10] doi:10.1038/s41467-026-73007-1 [code]
Single-nucleus epigenomic dysregulation unmasks genetic risk-associated neurodegenerative glia states.
Journal: Nature communications
In common: Seurat, patchwork, ggplot2, 1 other tool, Alzheimer's / dementia, cellular / molecular, 3 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.