Evidence map›Paper›PMID 35882830›Full record

ArticleNature communications2022

Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood.

Diptavo Dutta, Yuan He, Ashis Saha, Marios Arvanitis, Alexis Battle, Nilanjan Chatterjee

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
5.6field-weighted citation impact, top 4% 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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 32 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

6 authors at 1 institution in 1 country.

Diptavo DuttaDepartment of Biostatistics, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-6634-9040
Yuan HeDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Ashis SahaDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
Marios ArvanitisDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Alexis Battle *Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA. ajbattle@jhu.edu.ORCID 0000-0002-5287-627X
Nilanjan Chatterjee *Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA. nilanjan@jhu.edu.
Johns Hopkins University · US

Funding

Robust Methods for Polygenic Analysis to Inform Disease Etiology and Enhance Risk PredictionR01HG010480 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI CHATTERJEE, NILANJAN · 2019 to 2023
$2.8M
3/3 Building integrative CNS networks for genomic analysis of autismR01MH109905 · NIMH · JOHNS HOPKINS UNIVERSITY · PI BATTLE, ALEXIS · 2016 to 2020
$1.2M
NHGRI NIH HHS R01 HG010480NIMH NIH HHS R01 MH109905
6 · The paper itself

Abstract

Large scale genetic association studies have identified many trait-associated variants and understanding the role of these variants in the downstream regulation of gene-expressions can uncover important mediating biological mechanisms. Here we propose ARCHIE, a summary statistic based sparse canonical correlation analysis method to identify sets of gene-expressions trans-regulated by sets of known trait-related genetic variants. Simulation studies show that compared to standard methods, ARCHIE is better suited to identify "core"-like genes through which effects of many other genes may be mediated and can capture disease-specific patterns of genetic associations. By applying ARCHIE to publicly available summary statistics from the eQTLGen consortium, we identify gene sets which have significant evidence of trans-association with groups of known genetic variants across 29 complex traits. Around half (50.7%) of the selected genes do not have any strong trans-associations and are not detected by standard methods. We provide further evidence for causal basis of the target genes through a series of follow-up analyses. These results show ARCHIE is a powerful tool for identifying sets of genes whose trans-regulation may be related to specific complex traits.

Indexed as

Genome-Wide Association StudyQuantitative Trait LociGenetic Association StudiesMultifactorial InheritancePhenotypePolymorphism, Single Nucleotide

Identifiers

PMID35882830
PMCPMC9325868
OpenAlexW4288010071

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.