Evidence map›Paper›PMID 35931050›Full record

ArticleAmerican journal of human genetics2022

Multi-ancestry fine-mapping improves precision to identify causal genes in transcriptome-wide association studies.

Zeyun Lu, Shyamalika Gopalan, Dong Yuan, David V Conti, Bogdan Pasaniuc, Alexander Gusev, Nicholas Mancuso

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of human genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 2 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

48 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Predicted Proteome Association Studies of Breast, Prostate, Ovarian, and Endometrial Cancers Implicate Plasma Protein Regulation in Cancer Susceptibility.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023
    Pooled it
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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

7 authors.

Zeyun LuBiostatistics Division, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA. Electronic address: zeyunlu@usc.edu.
Shyamalika GopalanCenter for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Evolutionary Anthropology, Duke University, Durham, NC, USA.
Dong YuanBiostatistics Division, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.
David V ContiBiostatistics Division, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Bogdan PasaniucBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Alexander GusevDivision of Population Sciences, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA, USA; Division of Genetics, Brigham & Women's Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute, Cambridge, MA, USA.
Nicholas MancusoBiostatistics Division, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA. Electronic address: nicholas.mancuso@med.usc.edu.

Funding

Statistical Methods for Integrative Genomics in CancerP01CA196569 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Paul Marjoram · 2016 to 2026
$25.5M
The Family Blood Pressure Program (GENOA Network)U01HL054481 · NHLBI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI BOERWINKLE, ERIC A · 2000 to 2007
$6.7M
Methods for Genome-wide Association Studies in Admixed PopulationsR01HG006399 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L · 2011 to 2024
$6.3M
Leveraging Prospective Cancer Epidemiology Cohorts and Novel Methods to Improve Polygenic Risk ScoresU01CA261339 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fei Chen, David V Conti · 2021 to 2026
$5.2M
Genomic Predictors of Arteriosclerosis in HypertensivesR01HL087660 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KARDIA, SHARON L · 2007 to 2009
$5.1M
Characterizing the evolutionary architecture of complex disease within and across diverse populationsR01HG012133 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI MANCUSO, NICHOLAS · 2021 to 2025
$3.6M
Haplotype-aware models of gene and isoform expression with application to genetic studies of disease in diverse populationsR01GM140287 · NIGMS · SEATTLE CHILDREN'S HOSPITAL · PI GAMAZON, ERIC R, MOHAMMADI, PEJMAN · 2021 to 2024
$2.8M
GENETIC DETERMINANTS OF HIGH BP IN THREE RACIAL GROUPSU01HL054457 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KARDIA, SHARON L · 2000 to 2004
$2.8M
NHLBI FAMILY BLOOD PRESSURE PROGRAM (GENOA)U01HL054464 · NHLBI · MAYO CLINIC COLL OF MEDICINE, ROCHESTER · PI TURNER, STEPHEN T · 2000 to 2004
$2.6M
An evolutionary framework to elucidate and interpret the genetic architecture of complex traits in diverse populations - diversity supplementR35GM142783 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHIANG, CHARLESTON · 2021 to 2025
$2.2M
Genetic Mechanisms of Arteriosclerosis in Hypertensive SibshipsR01HL119443 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KARDIA, SHARON L · 2014 to 2017
$2.1M
GENETIC DETERMINANTS OF HIGH BP IN THREE RACIAL GROUPSU10HL054457 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SING, CHARLES F · 1995 to 1999
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NCI NIH HHS P01 CA196569NCI NIH HHS U01 CA261339NHGRI NIH HHS R01 HG006399NHGRI NIH HHS R01 HG012133NHLBI NIH HHS R01 HL087660NHLBI NIH HHS R01 HL119443NHLBI NIH HHS U01 HL054457NHLBI NIH HHS U01 HL054464NHLBI NIH HHS U01 HL054481NHLBI NIH HHS U10 HL054457NHLBI NIH HHS U10 HL054464NHLBI NIH HHS U10 HL054481NIGMS NIH HHS R01 GM140287NIGMS NIH HHS R35 GM142783
6 · The paper itself

Abstract

Transcriptome-wide association studies (TWASs) are a powerful approach to identify genes whose expression is associated with complex disease risk. However, non-causal genes can exhibit association signals due to confounding by linkage disequilibrium (LD) patterns and eQTL pleiotropy at genomic risk regions, which necessitates fine-mapping of TWAS signals. Here, we present MA-FOCUS, a multi-ancestry framework for the improved identification of genes underlying traits of interest. We demonstrate that by leveraging differences in ancestry-specific patterns of LD and eQTL signals, MA-FOCUS consistently outperforms single-ancestry fine-mapping approaches with equivalent total sample sizes across multiple metrics. We perform TWASs for 15 blood traits using genome-wide summary statistics (average n

Indexed as

Genome-Wide Association StudyTranscriptomeHumansLinkage DisequilibriumMultifactorial InheritancePolymorphism, Single Nucleotidegene fine-mappingGWASmulti-ancestrystatistical geneticsTWAS

Identifiers

PMID35931050
PMCPMC9388396

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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.