Evidence map›Paper›PMID 34930827›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Leveraging cell-type-specific regulatory networks to interpret genetic variants in abdominal aortic aneurysm.

Shining Ma, Xi Chen, Xiang Zhu, Philip S Tsao, Wing Hung Wong

Open access · hybridAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
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

7 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Contextual AI models for single-cell protein biology.bioRxiv : the preprint server for biology · 2024
    Article
  3. Using Genomics to Identify Novel Therapeutic Targets for Aortic Disease.Arteriosclerosis, thrombosis, and vascular biology · 2024
    Review
  4. Article
  5. Article
  6. Article
  7. Review
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

5 authors at 3 institutions in 1 country.

Shining MaDepartment of Statistics, Stanford University, Stanford, CA 94305.
Xi ChenDepartment of Statistics, Stanford University, Stanford, CA 94305.
Xiang ZhuDepartment of Statistics, Pennsylvania State University, University Park, PA 16802.ORCID 0000-0003-1134-6413
Philip S TsaoVA Palo Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto Health Care System, Palo Alto, CA 94304; ptsao@stanford.edu whwong@stanford.edu.ORCID 0000-0001-7274-9318
Wing Hung WongDepartment of Statistics, Stanford University, Stanford, CA 94305; ptsao@stanford.edu whwong@stanford.edu.ORCID 0000-0001-7466-2339
Stanford University · USPennsylvania State University · USVA Palo Alto Health Care System · US

Funding

Special EquipmentP50HG007735 · NHGRI · STANFORD UNIVERSITY · PI CHANG, HOWARD Y · 2014 to 2018
$15.2M
Center for Personal Dynamic RegulomesRM1HG007735 · NHGRI · STANFORD UNIVERSITY · PI CHANG, HOWARD Y · 2019 to 2023
$13.8M
DNA Variants and AAA DiseaseR01HL101388 · NHLBI · STANFORD UNIVERSITY · PI TSAO, PHILIP S · 2010 to 2013
$1.6M
Statistical methods for gene regulatory analysis and single cell genomicsR01HG010359 · NHGRI · STANFORD UNIVERSITY · PI WONG, WING H. · 2019 to 2022
$1.5M
MicroRNA Regulation of Nicotine Accelerated AAAsR01HL122939 · NHLBI · PALO ALTO VETERANS INSTIT FOR RESEARCH · PI TSAO, PHILIP S · 2014 to 2017
$1.4M
High Throughput DNA Sequencer UpgradeS10OD018220 · OD · STANFORD UNIVERSITY · PI COLLER, JOHN · 2014 to 2014
$596k
Genetics of Cardiometabolic Diseases in the VA PopulationI01BX003362 · VA · VETERANS ADMIN PALO ALTO HEALTH CARE SYS · PI Kyong-Mi Chang, Philip S Tsao · 2017 to 2026
–
BLRD VA I01 BX003362NHGRI NIH HHS P50 HG007735NHGRI NIH HHS R01 HG010359NHGRI NIH HHS RM1 HG007735NHLBI NIH HHS R01 HL101388NHLBI NIH HHS R01 HL122939NIH HHS S10 OD018220
6 · The paper itself

Abstract

Abdominal aortic aneurysm (AAA) is a common degenerative cardiovascular disease whose pathobiology is not clearly understood. The cellular heterogeneity and cell-type-specific gene regulation of vascular cells in human AAA have not been well-characterized. Here, we performed analysis of whole-genome sequencing data in AAA patients versus controls with the aim of detecting disease-associated variants that may affect gene regulation in human aortic smooth muscle cells (AoSMC) and human aortic endothelial cells (HAEC), two cell types of high relevance to AAA disease. To support this analysis, we generated H3K27ac HiChIP data for these cell types and inferred cell-type-specific gene regulatory networks. We observed that AAA-associated variants were most enriched in regulatory regions in AoSMC, compared with HAEC and CD4

Indexed as

Gene Regulatory NetworksAortic Aneurysm, AbdominalCase-Control StudiesCells, CulturedDown-RegulationHumansInterleukin-6Kruppel-Like Transcription FactorsTranscriptional Regulator ERGERG protein, humanIL6 protein, humanInterleukin-6Kruppel-Like Transcription FactorsTranscriptional Regulator ERGabdominal aortic aneurysmcell-type-specific regulationHiChIPsmooth muscle cellswhole-genome sequencing

Identifiers

PMID34930827
PMCPMC8740683
OpenAlexW4200501776

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.