Evidence map›Paper›PMID 21738480›Full record

SynthesisPLoS genetics2011

Multiple loci are associated with white blood cell phenotypes.

Michael A Nalls, David J Couper, Toshiko Tanaka, Frank J A van Rooij, Ming-Huei Chen, Albert V Smith, Daniela Toniolo, Neil A Zakai, Qiong Yang, Andreas Greinacher and 83 more

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PLoS genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 12 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed, 12 pooled it
8.0field-weighted citation impact, top 2% 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

85 citing papers in PubMed, 12 syntheses or guidelines pooled it, 134 citations in OpenAlex.

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  8. Pleiotropic genes for metabolic syndrome and inflammation.Molecular genetics and metabolism · 2014
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25 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

93 authors at 20 institutions in 9 countries.

Michael A NallsLaboratory of Neurogenetics, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America. nallsm@mail.nih.gov
David J Couper
Toshiko Tanaka
Frank J A van Rooij
Ming-Huei Chen
Albert V Smith
Daniela Toniolo
Neil A Zakai
Qiong Yang
Andreas Greinacher
Andrew R Wood
Melissa Garcia
Paolo Gasparini
Yongmei Liu
Thomas Lumley
Aaron R Folsom
Alex P Reiner
Christian Gieger
Vasiliki Lagou
Janine F Felix
Henry Völzke
Natalia A Gouskova
Alessandro Biffi
Angela Döring
Uwe Völker
Sean Chong
Kerri L Wiggins
Augusto Rendon
Abbas Dehghan
Matt Moore
Kent Taylor
James G Wilson
Guillaume Lettre
Albert Hofman
Joshua C Bis
Nicola Pirastu
Caroline S Fox
Christa Meisinger
Jennifer Sambrook
Sampath Arepalli
Matthias Nauck
Holger Prokisch
Jonathan Stephens
Nicole L Glazer
L Adrienne Cupples
Yukinori Okada
Atsushi Takahashi
Yoichiro Kamatani
Koichi Matsuda
Tatsuhiko Tsunoda
Toshihiro Tanaka
Michiaki Kubo
Yusuke Nakamura
Kazuhiko Yamamoto
Naoyuki Kamatani
Michael Stumvoll
Anke Tönjes
Inga Prokopenko
Thomas Illig
Kushang V Patel
Stephen F Garner
Brigitte Kuhnel
Massimo Mangino
Ben A Oostra
Swee Lay Thein
Josef Coresh
H-Erich Wichmann
Stephan Menzel
JingPing Lin
Giorgio Pistis
André G Uitterlinden
Tim D Spector
Alexander Teumer
Gudny Eiriksdottir
Vilmundur Gudnason
Stefania Bandinelli
Timothy M Frayling
Aravinda Chakravarti
Cornelia M van Duijn
David Melzer
Willem H Ouwehand
Daniel Levy
Eric Boerwinkle
Andrew B Singleton
Dena G Hernandez
Dan L Longo
Nicole Soranzo
Jacqueline C M Witteman
Bruce M Psaty
Luigi Ferrucci
Tamara B Harris
Christopher J O'Donnell
Santhi K Ganesh
National Institutes of Health · USHelmholtz Zentrum München · DEUniversity of Washington · USKing's College London · GBErasmus MC · NLErasmus University Rotterdam · NLIcelandic Heart Association · ISNational Institute on Aging · USNational Institute on Drug Abuse · USPeninsula College of Medicine and Dentistry · GBUniversität Greifswald · DEUniversity of Cambridge · GBFramingham Heart Study · USHarvard University · USJohns Hopkins University · USLeipzig University · DENational Health Service · GBNational Heart Lung and Blood Institute · USNetherlands Consortium for Healthy Ageing · NLRIKEN · JP

Funding

Institute for Clinical and Translational Research (UL1)UL1RR025005 · NCRR · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2007 to 2011
$75.8M
Framingham Project/LevyZIAHL006001 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI LEVY, DANIEL · 2009 to 2025
$51.1M
ZINC AND CA EDTA THERAPY OF PLUMBISMM01RR000052 · NCRR · JOHNS HOPKINS UNIVERSITY · PI BELCHER, HAROLYN MILLICENT EDITH · 1985 to 2007
$37.3M
Genome-Wide Association Analysis in Essential Hypertension (FEHGAS study)R01HL086694 · NHLBI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ARAVINDA CHAKRAVARTI · 2007 to 2026
$21.2M
Genotypic Determinants of Aspirin Response in High Risk FamiliesU01HL072518 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI BECKER, LEWIS C · 2002 to 2008
$12.8M
Epidemiology of Venous Thrombosis & Pulmonary EmbolismR01HL059367 · NHLBI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI TANG, WEIHONG · 1998 to 2024
$11.8M
Genomic Epidemiology of Cardiovascular DiseaseZIAHL006002 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI O'DONNELL, CHRISTOPHER · 2009 to 2015
$8.0M
Genome-wide case-only study of antihypertensive drug-gene interactionsR01HL085251 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M · 2007 to 2010
$7.2M
Framingham Heart Study/FoxZIAHL006094 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI FOX, CAROLINE · 2010 to 2015
$6.9M
Healthy Aging Neighborhoods of Diversity Across LifespanZ01AG000513 · NIA · NATIONAL INSTITUTE ON AGING · PI EVANS, MICHELE K · 2001 to 2008
$6.8M
WGA Study to Identify Genetic Variants Associated with CV Events in CHSR01HL087652 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M · 2007 to 2009
$5.1M
JACKSON HEART STUDY--EXAM CENTERN01HC095171 · HC · UNIVERSITY OF MISSISSIPPI MEDICAL CENTER · PI JONES, DANIEL W · 1999 to 2001
$4.6M
Biotechnology and Biological Sciences Research Council G20234British Heart Foundation RG/09/012/28096Intramural NIH HHS Z01 AG000513Intramural NIH HHS Z01 AG000932Medical Research Council G0000111Medical Research Council MC_U105260799NCRR NIH HHS M01 RR000052NCRR NIH HHS M01-RR000052NCRR NIH HHS UL1 RR025005NCRR NIH HHS UL1RR025005NHGRI NIH HHS HHSN268200782096CNHGRI NIH HHS U01 HG004402NHGRI NIH HHS U01HG004402NHLBI NIH HHS HL085251NHLBI NIH HHS HL087652NHLBI NIH HHS N01 HC005187NHLBI NIH HHS N01 HC025195NHLBI NIH HHS N01 HC045134NHLBI NIH HHS N01 HC045204NHLBI NIH HHS N01 HC045205NHLBI NIH HHS N01 HC048047NHLBI NIH HHS N01 HC048048NHLBI NIH HHS N01 HC048049NHLBI NIH HHS N01 HC048050NHLBI NIH HHS N01-HC-05187NHLBI NIH HHS N01 HC055015NHLBI NIH HHS N01 HC055016NHLBI NIH HHS N01 HC055018NHLBI NIH HHS N01 HC055019NHLBI NIH HHS N01 HC055020NHLBI NIH HHS N01 HC055021NHLBI NIH HHS N01 HC055022NHLBI NIH HHS N01 HC065226NHLBI NIH HHS N01 HC095095NHLBI NIH HHS N01 HC095170NHLBI NIH HHS N01 HC095171NHLBI NIH HHS N01 HC095172NHLBI NIH HHS N01-HC-25195NHLBI NIH HHS N01-HC-45204NHLBI NIH HHS N01-HC-45205NHLBI NIH HHS N01-HC-48047NHLBI NIH HHS N01-HC-48048NHLBI NIH HHS N01-HC-48049NHLBI NIH HHS N01-HC-48050NHLBI NIH HHS N01-HC-55015NHLBI NIH HHS N01-HC-55016NHLBI NIH HHS N01-HC-55017NHLBI NIH HHS N01-HC-55018NHLBI NIH HHS N01-HC-55019NHLBI NIH HHS N01-HC-55020NHLBI NIH HHS N01-HC-55021NHLBI NIH HHS N01-HC-55022NHLBI NIH HHS N01-HC-65226NHLBI NIH HHS N01-HC-95095NHLBI NIH HHS N01-HC-95100NHLBI NIH HHS N01-HC-95170NHLBI NIH HHS N01-HC-95171NHLBI NIH HHS N01-HC-95172NHLBI NIH HHS N02-HL-6-4278NHLBI NIH HHS R01 HL059367NHLBI NIH HHS R01 HL-071862NHLBI NIH HHS R01 HL071862NHLBI NIH HHS R01 HL085251NHLBI NIH HHS R01 HL086694NHLBI NIH HHS R01HL086694NHLBI NIH HHS R01 HL087641NHLBI NIH HHS R01HL087641NHLBI NIH HHS R01 HL087652NHLBI NIH HHS R01 HL087698NHLBI NIH HHS R01 HL087698-01NHLBI NIH HHS R01HL59367NHLBI NIH HHS R01HL86694NHLBI NIH HHS U01 HL072518NHLBI NIH HHS U01 HL72518NIA NIH HHS 1R01AG032098-01A1NIA NIH HHS AG000932-02NIA NIH HHS K23 AG000932NIA NIH HHS N01 AG012100NIA NIH HHS N01 AG062101NIA NIH HHS N01 AG062103NIA NIH HHS N01 AG062106NIA NIH HHS N01-AG-821336NIA NIH HHS N01-AG-916413NIA NIH HHS R01 AG024233NIA NIH HHS R01 AG032098NIA NIH HHS R01 AG24233-01NIMHD NIH HHS R01 MD009164NINR NIH HHS R01 NR008153NINR NIH HHS R01 NR08153PHS HHS 24152PHS HHS 32100-2PHS HHS 32105-6PHS HHS 32108-9PHS HHS 32111-13PHS HHS 32115PHS HHS 32118-32119PHS HHS 32122PHS HHS 42107-26PHS HHS 42129-32PHS HHS 44221PHS HHS HHSN268200625226CWellcome TrustWellcome Trust 076113/C/04/ZWellcome Trust 091746/Z/10/ZWHI NIH HHS N01 WH022110
6 · The paper itself

Abstract

White blood cell (WBC) count is a common clinical measure from complete blood count assays, and it varies widely among healthy individuals. Total WBC count and its constituent subtypes have been shown to be moderately heritable, with the heritability estimates varying across cell types. We studied 19,509 subjects from seven cohorts in a discovery analysis, and 11,823 subjects from ten cohorts for replication analyses, to determine genetic factors influencing variability within the normal hematological range for total WBC count and five WBC subtype measures. Cohort specific data was supplied by the CHARGE, HeamGen, and INGI consortia, as well as independent collaborative studies. We identified and replicated ten associations with total WBC count and five WBC subtypes at seven different genomic loci (total WBC count-6p21 in the HLA region, 17q21 near ORMDL3, and CSF3; neutrophil count-17q21; basophil count- 3p21 near RPN1 and C3orf27; lymphocyte count-6p21, 19p13 at EPS15L1; monocyte count-2q31 at ITGA4, 3q21, 8q24 an intergenic region, 9q31 near EDG2), including three previously reported associations and seven novel associations. To investigate functional relationships among variants contributing to variability in the six WBC traits, we utilized gene expression- and pathways-based analyses. We implemented gene-clustering algorithms to evaluate functional connectivity among implicated loci and showed functional relationships across cell types. Gene expression data from whole blood was utilized to show that significant biological consequences can be extracted from our genome-wide analyses, with effect estimates for significant loci from the meta-analyses being highly corellated with the proximal gene expression. In addition, collaborative efforts between the groups contributing to this study and related studies conducted by the COGENT and RIKEN groups allowed for the examination of effect homogeneity for genome-wide significant associations across populations of diverse ancestral backgrounds.

Indexed as

Leukocyte CountLeukocytesPhenotypeGenetic LociGenome-Wide Association StudyHumansMolecular EpidemiologyMultigene FamilyPolymorphism, Single NucleotideUbiquitin-Protein LigasesRNF128 protein, humanUbiquitin-Protein Ligases

Identifiers

PMID21738480
PMCPMC3128114
OpenAlexW2169863448

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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.