Evidence map›Paper›PMID 30113658›Full record

ArticleNucleic acids research2018

INFERNO: inferring the molecular mechanisms of noncoding genetic variants.

Alexandre Amlie-Wolf, Mitchell Tang, Elisabeth E Mlynarski, Pavel P Kuksa, Otto Valladares, Zivadin Katanic, Debby Tsuang, Christopher D Brown, Gerard D Schellenberg, Li-San Wang

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 9% 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

43 citing papers in PubMed, 1 synthesis or guideline pooled it, 63 citations in OpenAlex.

  1. Pooled it
  2. From correlation to causation: cell-type-specific gene regulatory networks in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Exploration of Tools for the Interpretation of Human Non-Coding Variants.International journal of molecular sciences · 2022
    Review
  14. Review
  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

10 authors at 2 institutions in 1 country.

Alexandre Amlie-WolfGenomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Mitchell TangPenn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Elisabeth E MlynarskiPenn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Pavel P KuksaPenn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Otto ValladaresPenn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Zivadin KatanicPenn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Debby TsuangVA Puget Sound Health Care System, Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA.
Christopher D BrownGenomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Gerard D SchellenbergGenomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Li-San WangGenomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
University of Pennsylvania · USUniversity of Washington · US

Funding

Alzheimer's Disease Genetics ConsortiumU01AG032984 · NIA · UNIVERSITY OF PENNSYLVANIA · PI SCHELLENBERG, GERARD DAVID · 2009 to 2024
$60.4M
THE NIA GENETICS OF ALZHEIMER'S DISEASE DATA STORAGE SITEU24AG041689 · NIA · UNIVERSITY OF PENNSYLVANIA · PI LI-SAN WANG · 2012 to 2026
$42.3M
UPenn ADCC Biomarker CoreP30AG010124 · NIA · UNIVERSITY OF PENNSYLVANIA · PI VAN DEERLIN, VIVIANNA M · 1991 to 2020
$35.1M
Genome Center for Alzheimer's Disease (GCAD)U54AG052427 · NIA · UNIVERSITY OF PENNSYLVANIA · PI SCHELLENBERG, GERARD DAVID · 2016 to 2025
$32.8M
Consortium for Alzheimers Sequence Analysis (CASA)UF1AG047133 · NIA · UNIVERSITY OF PENNSYLVANIA · PI FARRER, LINDSAY A., HAINES, JONATHAN L · 2014 to 2014
$12.6M
Training in Alzheimer’s and Age-Related Neurodegenerative DiseasesT32AG000255 · NIA · UNIVERSITY OF PENNSYLVANIA · PI ALICE S CHEN-PLOTKIN, VIRGINIA M LEE · 1997 to 2026
$12.5M
Project 2: Identifying genes and Pathways that impact Tau Toxicity in FTDU54NS100693 · NINDS · MAYO CLINIC JACKSONVILLE · PI DICKSON, DENNIS WILLIAM · 2016 to 2020
$6.2M
Integrated target discovery in Alzheimer's diseaseRF1AG055477 · NIA · UNIVERSITY OF PENNSYLVANIA · PI BROWN, CHRISTOPHER DAVID · 2017 to 2017
$2.9M
Computational genome-wide RNA profiling using next-generation sequencingR01GM099962 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI WANG, LI-SAN · 2012 to 2016
$1.5M
NIA NIH HHS P30 AG010124NIA NIH HHS RF1 AG055477NIA NIH HHS T32 AG000255NIA NIH HHS U01 AG032984NIA NIH HHS U24 AG041689NIA NIH HHS U54 AG052427NIA NIH HHS UF1 AG047133NIGMS NIH HHS R01 GM099962NINDS NIH HHS U54 NS100693
6 · The paper itself

Abstract

The majority of variants identified by genome-wide association studies (GWAS) reside in the noncoding genome, affecting regulatory elements including transcriptional enhancers. However, characterizing their effects requires the integration of GWAS results with context-specific regulatory activity and linkage disequilibrium annotations to identify causal variants underlying noncoding association signals and the regulatory elements, tissue contexts, and target genes they affect. We propose INFERNO, a novel method which integrates hundreds of functional genomics datasets spanning enhancer activity, transcription factor binding sites, and expression quantitative trait loci with GWAS summary statistics. INFERNO includes novel statistical methods to quantify empirical enrichments of tissue-specific enhancer overlap and to identify co-regulatory networks of dysregulated long noncoding RNAs (lncRNAs). We applied INFERNO to two large GWAS studies. For schizophrenia (36,989 cases, 113,075 controls), INFERNO identified putatively causal variants affecting brain enhancers for known schizophrenia-related genes. For inflammatory bowel disease (IBD) (12,882 cases, 21,770 controls), INFERNO found enrichments of immune and digestive enhancers and lncRNAs involved in regulation of the adaptive immune response. In summary, INFERNO comprehensively infers the molecular mechanisms of causal noncoding variants, providing a sensitive hypothesis generation method for post-GWAS analysis. The software is available as an open source pipeline and a web server.

Indexed as

Enhancer Elements, GeneticGenome, HumanSoftwareAdaptive ImmunityCase-Control StudiesFemaleGenetic MarkersGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansInflammatory Bowel DiseasesInternetLinkage DisequilibriumMalePhenotypePolymorphism, Single NucleotideGenetic MarkersRNA, Long Noncoding

Identifiers

PMID30113658
PMCPMC6158604
OpenAlexW2949265370

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.