Evidence map›Paper›PMID 34460823›Full record

ArticlePLoS genetics2021

Multitrait GWAS to connect disease variants and biological mechanisms.

Hanna Julienne, Vincent Laville, Zachary R McCaw, Zihuai He, Vincent Guillemot, Carla Lasry, Andrey Ziyatdinov, Cyril Nerin, Amaury Vaysse, Pierre Lechat and 7 more

Abstract read
In one paragraph

Article in PLoS genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Review
  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. Review
  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

17 authors.

Hanna JulienneDepartment of Computational Biology, Institut Pasteur, Paris, France.ORCID 0000-0001-8214-9412
Vincent LavilleDepartment of Computational Biology, Institut Pasteur, Paris, France.
Zachary R McCawDepartment of Biostatistics, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0002-2006-9828
Zihuai HeDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, United States of America.ORCID 0000-0002-8220-4183
Vincent GuillemotDepartment of Computational Biology, Institut Pasteur, Paris, France.ORCID 0000-0002-7421-0655
Carla LasryDepartment of Computational Biology, Institut Pasteur, Paris, France.
Andrey ZiyatdinovDepartment of Epidemiology, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America.
Cyril NerinDepartment of Computational Biology, Institut Pasteur, Paris, France.
Amaury VaysseDepartment of Computational Biology, Institut Pasteur, Paris, France.ORCID 0000-0003-2397-4230
Pierre LechatDepartment of Computational Biology, Institut Pasteur, Paris, France.ORCID 0000-0003-1050-5582
Hervé MénagerDepartment of Computational Biology, Institut Pasteur, Paris, France.ORCID 0000-0002-7552-1009
Wilfried Le GoffSorbonne Université, INSERM, Institute of Cardiometabolism and Nutrition (ICAN), UMR_S 1166, Paris, France.
Marie-Pierre DubeUniversité de Montréal Beaulieu-Saucier Pharmacogenomics Centre, Montreal Heart Institute, Montreal, Canada.ORCID 0000-0001-8442-4393
Peter KraftDepartment of Biostatistics, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0002-4472-8103
Iuliana Ionita-LazaDepartment of Biostatistics, Columbia University, New York, New York, United States of America.
Bjarni J VilhjálmssonNational Centre for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark.ORCID 0000-0003-2277-9249
Hugues AschardDepartment of Computational Biology, Institut Pasteur, Paris, France.ORCID 0000-0002-7554-6783

Funding

Leveraging Novel Multivariate Methods of Subphenotypes in Genetic Association Studies of Sjogren’s SyndromeR03DE025665 · NIDCR · HARVARD SCHOOL OF PUBLIC HEALTH · PI ASCHARD, HUGUES, ZAITLEN, NOAH A · 2016 to 2017
$494k
NIDCR NIH HHS R03 DE025665
6 · The paper itself

Abstract

Genome-wide association studies (GWASs) have uncovered a wealth of associations between common variants and human phenotypes. Here, we present an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link with biological mechanisms. Our framework incorporates multitrait association mapping along with an investigation of the breakdown of genetic associations into clusters of variants harboring similar multitrait association profiles. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how genetic variants within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster assignment and the success of drug targets in randomized controlled trials.

Indexed as

Polymorphism, Single NucleotideQuantitative Trait LociCluster AnalysisComputational BiologyGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPhenotype

Identifiers

PMID34460823
PMCPMC8437297

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.