Evidence map›Paper›PMID 42550898›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

A reference protein atlas of the adult mouse brain vasculature.

Liqun He, Henrik J Johansson, Elisa Vazquez-Liebanas, Jianping Liu, Lars Muhl, Khayrun Nahar, Michael Vanlandewijck, Janne Lehtiö, Christer Betsholtz, Maarja Andaloussi Mäe

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Liqun HeDepartment of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala SE-751 85, Sweden.ORCID 0000-0003-2127-7597
Henrik J JohanssonScience for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Solna SE-171 21, Sweden.
Elisa Vazquez-LiebanasDepartment of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala SE-751 85, Sweden.
Jianping LiuDepartment of Medicine-Huddinge, Karolinska Institutet, Huddinge SE-141 57, Sweden.ORCID 0000-0002-7336-3895
Lars MuhlDepartment of Medicine-Huddinge, Karolinska Institutet, Huddinge SE-141 57, Sweden.
Khayrun NaharDepartment of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala SE-751 85, Sweden.
Michael VanlandewijckDepartment of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala SE-751 85, Sweden.ORCID 0000-0002-0709-7808
Janne LehtiöScience for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Solna SE-171 21, Sweden.
Christer BetsholtzDepartment of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala SE-751 85, Sweden.
Maarja Andaloussi MäeDepartment of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala SE-751 85, Sweden.ORCID 0000-0001-6985-4379

Funding

Cancerfonden (Swedish Cancer Society) 150735EC | European Research Council (ERC) AdG 101200073Fondation Leducq (Leducq Foundation) 22CVD01Fondation Leducq (Leducq Foundation) 23CVD02Knut och Alice Wallenbergs Stiftelse (kawforskning) 2015.0030; 2020.0057Vetenskapsrådet (VR) 2015-00550Vetenskapsrådet (VR) 2023-02655
6 · The paper itself

Abstract

Current methods for assessing low-abundance proteins in individual cells are limited. As a result, cell functions are often inferred from single-cell RNA sequencing (scRNA-seq) data, which can be misleading due to the poor cross-gene correlation (different genes in the same cells) between messenger RNA (mRNA) and protein levels. To address this issue, we used isolated brain vascular fragments to study the blood-brain barrier. We applied a combination of deep bulk proteomic analysis, a proteomic ruler approach, and scRNA-seq, assuming a high within-gene correlation (same gene in different cells) between mRNA and protein. This approach allowed us to estimate protein copy numbers per cell for 9,940 proteins across eight cell types, including endothelium, smooth muscle, pericytes, fibroblasts, and microglia. We also evaluated protein abundance in astrocyte end-feet attached to the vessel fragments. Our data are available through an Online Database, providing a searchable resource and reference protein atlas for future studies of neurovascular proteomics in health and disease.

Indexed as

BrainProteomeProteomicsAnimalsAstrocytesBlood-Brain BarrierMicePericytesRNA, MessengerProteomeRNA, Messengerblood–brain barrierbrainprotein abundanceproteomicsvasculature

Identifiers

PMID42550898
PMCPMC13461961

What OpenQuestion holds

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Registered trials

None linked

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.