Evidence map›Paper›PMID 30804563›Full record

ArticleNature genetics2019

A statistical framework for cross-tissue transcriptome-wide association analysis.

Yiming Hu, Mo Li, Qiongshi Lu, Haoyi Weng, Jiawei Wang, Seyedeh M Zekavat, Zhaolong Yu, Boyang Li, Jianlei Gu, Sydney Muchnik and 11 more

Abstract read
In one paragraph

Article in Nature genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 275 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
275citing papers in PubMed, 6 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

275 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Integrative Multi-omics Analysis for Prioritization of Candidate Genes in Polycystic Ovary Syndrome.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Unveiling novel susceptibility genes for sarcoidosis by a cross-tissue transcriptome-wide association study.Sarcoidosis, vasculitis, and diffuse lung diseases : official journal of WASOG · 2026
    Article
  20. Article

215 more citing papers are in PubMed but not listed here.

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

21 authors.

Yiming Hu *Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.ORCID http://orcid.org/0000-0002-0988-1030
Mo Li *Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Qiongshi Lu *Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA.ORCID http://orcid.org/0000-0002-4514-0969
Haoyi WengDivision of Biostatistics, The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.
Jiawei WangProgram of Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
Seyedeh M ZekavatYale School of Medicine, New Haven, CT, USA.ORCID http://orcid.org/0000-0003-4026-8944
Zhaolong YuProgram of Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
Boyang LiDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.ORCID http://orcid.org/0000-0003-2808-9986
Jianlei GuSJTU-Yale Joint Center for Biostatistics, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiaotong University, Shanghai, China.
Sydney MuchnikDepartment of Genetics, Yale School of Medicine, New Haven, CT, USA.
Yu ShiDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Brian W KunkleJohn P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA.ORCID http://orcid.org/0000-0002-9515-5157
Shubhabrata MukherjeeDepartment of Medicine, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0003-2522-2884
Pradeep NatarajanCardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.ORCID http://orcid.org/0000-0001-8402-7435
Adam NajCenter for Clinical Epidemiology and Biostatistic, and the Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Amanda KuzmaDepartment of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Yi ZhaoDepartment of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Paul K CraneDepartment of Medicine, University of Washington, Seattle, WA, USA.
Alzheimer’s Disease Genetics Consortium,
Hui LuSJTU-Yale Joint Center for Biostatistics, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiaotong University, Shanghai, China.
Hongyu ZhaoDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA. hongyu.zhao@yale.edu.ORCID http://orcid.org/0000-0003-1195-9607

Funding

National Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD)U24AG021886 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI TATIANA M. FOROUD · 2002 to 2026
$119.8M
University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
NATIONAL ALZHEIMERS COORDINATING CENTER (NACC)U01AG016976 · NIA · UNIVERSITY OF WASHINGTON · PI KUKULL, WALTER ANTHONY · 1999 to 2020
$72.8M
Alzheimer's Disease Genetics ConsortiumU01AG032984 · NIA · UNIVERSITY OF PENNSYLVANIA · PI SCHELLENBERG, GERARD DAVID · 2009 to 2024
$60.4M
MEDICAL SCIENTIST TRAINING PROGRAMT32GM007205 · NIGMS · YALE UNIVERSITY · PI KAZMIERCZAK, BARBARA I · 1985 to 2019
$42.9M
THE NIA GENETICS OF ALZHEIMER'S DISEASE DATA STORAGE SITEU24AG041689 · NIA · UNIVERSITY OF PENNSYLVANIA · PI LI-SAN WANG · 2012 to 2026
$42.3M
Furthering scientific understanding of mechanisms underlying resilience to the effects of AD pathology by incorporating state of the art quantification of gliosis, inflammation, & synaptic toxicityU01AG006781 · NIA · UNIVERSITY OF WASHINGTON · PI CRANE, PAUL K, LARSON, ERIC B · 1986 to 2020
$39.3M
Yale Study Support Suite (YES3): Dashboard and Web Portal Software Supporting Research Workflow through integrated, customizable REDCap External ModulesP30AG021342 · NIA · YALE UNIVERSITY · PI Albert C Shaw · 2002 to 2026
$37.9M
Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
CHARGE Consortium: Omics Discovery for CVD and Aging PhenotypesR01HL105756 · NHLBI · UNIVERSITY OF WASHINGTON · PI Bruce M Psaty, NICHOLAS L SMITH · 2011 to 2026
$9.5M
Multidomain Alzheimers Risk Reduction Study (MARRS) PilotR01AG057508 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DUBLIN, SASCHA, YAFFE, KRISTINE · 2017 to 2021
$6.0M
Whole genome sequences in individuals to comprehensively characterize the genetic mechanisms of dyslipidemiasR01HL142711 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI Satoshi Koyama, Gina Marie Peloso · 2019 to 2026
$4.7M
Medical Research Council G0701075Medical Research Council G0901254Medical Research Council MR/K01417X/1Medical Research Council MR/N026004/1NCATS NIH HHS UL1 TR000427NCATS NIH HHS UL1 TR002373NHLBI NIH HHS R01 HL105756NHLBI NIH HHS R01 HL142711NIA NIH HHS K25 AG055620NIA NIH HHS N01 AG012100NIA NIH HHS P30 AG021342NIA NIH HHS R01 AG033193NIA NIH HHS R01 AG042437NIA NIH HHS R01 AG054060NIA NIH HHS R01 AG057508NIA NIH HHS U01 AG006781NIA NIH HHS U01 AG016976NIA NIH HHS U01 AG032984NIA NIH HHS U24 AG021886NIA NIH HHS U24 AG041689NIGMS NIH HHS R01 GM059507NIGMS NIH HHS T32 GM007205Parkinson's UK G-0907Wellcome Trust
6 · The paper itself

Abstract

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes by using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average of 39% improvement in imputation accuracy and generated effective imputation models for an average of 120% more genes. We describe a summary-statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene-trait association. We applied our method, called UTMOST (unified test for molecular signatures), to multiple genome-wide-association results and demonstrate its advantages over single-tissue strategies.

Indexed as

Gene ExpressionGene Expression ProfilingGenome-Wide Association StudyGenotypeHumansModels, GeneticPolymorphism, Single NucleotideTranscriptome

Identifiers

PMID30804563
PMCPMC6788740

What OpenQuestion holds

Textmetadata
LicenceTDM
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.