Evidence map›Paper›PMID 30459343›Full record

ArticleGenes and immunity2019

Unfolding of hidden white blood cell count phenotypes for gene discovery using latent class mixed modeling.

Taryn O Hall, Ian B Stanaway, David S Carrell, Robert J Carroll, Joshua C Denny, Hakon Hakonarson, Eric B Larson, Frank D Mentch, Peggy L Peissig, Sarah A Pendergrass and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genes and immunity, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

13 authors.

Taryn O HallDepartment of Biomedical Informatics Medical Education, School of Medicine, University of Washington, Seattle, WA, 98109, USA. tohall@uw.edu.
Ian B StanawayDepartment of Biomedical Informatics Medical Education, School of Medicine, University of Washington, Seattle, WA, 98109, USA.
David S CarrellKaiser Permanente Washington Health Research Institute (Formerly Group Health Cooperative-Seattle), Kaiser Permanente, Seattle, WA, 98109, USA.
Robert J CarrollDepartments of Biomedical Informatics and Medicine, Vanderbilt University, Nashville, TN, 37235, USA.ORCID http://orcid.org/0000-0003-3802-8183
Joshua C DennyDepartments of Biomedical Informatics and Medicine, Vanderbilt University, Nashville, TN, 37235, USA.
Hakon HakonarsonChildren's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Eric B LarsonKaiser Permanente Washington Health Research Institute (Formerly Group Health Cooperative-Seattle), Kaiser Permanente, Seattle, WA, 98109, USA.
Frank D MentchChildren's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Peggy L PeissigCenter for Human Genetics, Marshfield Clinic Research Institute, Marshfield, WI, 54449, USA.
Sarah A PendergrassGeisinger Research, Rockville, MD, 20850, USA.
Elisabeth A RosenthalDivision of Medical Genetics, School of Medicine, University of Washington, Seattle, WA, 98105, USA.
Gail P JarvikDivision of Medical Genetics, School of Medicine, University of Washington, Seattle, WA, 98105, USA.
David R CrosslinDepartment of Biomedical Informatics Medical Education, School of Medicine, University of Washington, Seattle, WA, 98109, USA. davidcr@uw.edu.

Funding

JH/CIDR Genotyping for Genome-Wide Association StudiesU01HG004438 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI VALLE, DAVID · 2007 to 2011
$24.2M
A Center for GEI Association StudiesU01HG004424 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GABRIEL, STACEY · 2007 to 2010
$21.4M
University of Washington Biomedical Informatics and Data Science Research Training ProgramT15LM007442 · NLM · UNIVERSITY OF WASHINGTON · PI JOHN H. GENNARI, Andrea L. Hartzler · 2002 to 2026
$19.6M
Genomic Basis of Susceptibility to COVID-19 Infection and its ComplicationsU01HG006379 · NHGRI · MAYO CLINIC ROCHESTER · PI Richard R. Sharp · 2011 to 2026
$16.5M
Finding Genomic Profiles of COVID-19 Phenotypes from the EHRU01HG008685 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIZABETH W KARLSON, Matthew S Lebo · 2015 to 2026
$13.6M
Variation, Function, and Disease Supplement ProgramU01HG008657 · NHGRI · UNIVERSITY OF WASHINGTON · PI David Russell Crosslin, Gail Pairitz Jarvik · 2015 to 2026
$13.4M
OMOP information model for eMERGE phenotypingU01HG008680 · NHGRI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Wendy K Chung, GEORGE M HRIPCSAK · 2015 to 2026
$13.3M
DNA Sequencing Support for the eMERGE NetworkU01HG008664 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI GIBBS, RICHARD A · 2015 to 2019
$10.9M
Global Alliance for Genomic Health (GA4GH)U01HG008676 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI LENNON, NIALL JOHN, REHM, HEIDI L · 2015 to 2019
$8.6M
Vanderbilt Genome-Electronic Records ProjectU01HG004603 · NHGRI · VANDERBILT UNIVERSITY · PI RODEN, DAN M · 2007 to 2011
$7.3M
The Electronic Medical Records and Genomics (eMERGE) Network Phase III Coordinating Center (U01)U01HG008701 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PETERSON, JOSEPH F. · 2015 to 2019
$7.1M
eMERGE Coordinating Center - Administrative SupplementU01HG006385 · NHGRI · VANDERBILT UNIVERSITY · PI HARRIS, PAUL A. · 2011 to 2014
$5.4M
NHGRI NIH HHS U01 HG004424NHGRI NIH HHS U01 HG004438NHGRI NIH HHS U01 HG004599NHGRI NIH HHS U01 HG004603NHGRI NIH HHS U01 HG004608NHGRI NIH HHS U01 HG004609NHGRI NIH HHS U01 HG004610NHGRI NIH HHS U01 HG006375NHGRI NIH HHS U01 HG006378NHGRI NIH HHS U01 HG006379NHGRI NIH HHS U01 HG006380NHGRI NIH HHS U01 HG006382NHGRI NIH HHS U01 HG006385NHGRI NIH HHS U01 HG006388NHGRI NIH HHS U01 HG006389NHGRI NIH HHS U01 HG006828NHGRI NIH HHS U01 HG006830NHGRI NIH HHS U01 HG008657NHGRI NIH HHS U01 HG008664NHGRI NIH HHS U01 HG008666NHGRI NIH HHS U01 HG008672NHGRI NIH HHS U01 HG008673NHGRI NIH HHS U01 HG008676NHGRI NIH HHS U01 HG008679NHGRI NIH HHS U01 HG008680NHGRI NIH HHS U01 HG008684NHGRI NIH HHS U01 HG008685NHGRI NIH HHS U01 HG008701NHGRI NIH HHS U01 HG010233NLM NIH HHS T15 LM007442
6 · The paper itself

Abstract

Resting-state white blood cell (WBC) count is a marker of inflammation and immune system health. There is evidence that WBC count is not fixed over time and there is heterogeneity in WBC trajectory that is associated with morbidity and mortality. Latent class mixed modeling (LCMM) is a method that can identify unobserved heterogeneity in longitudinal data and attempts to classify individuals into groups based on a linear model of repeated measurements. We applied LCMM to repeated WBC count measures derived from electronic medical records of participants of the National Human Genetics Research Institute (NHRGI) electronic MEdical Record and GEnomics (eMERGE) network study, revealing two WBC count trajectory phenotypes. Advancing these phenotypes to GWAS, we found genetic associations between trajectory class membership and regions on chromosome 1p34.3 and chromosome 11q13.4. The chromosome 1 region contains CSF3R, which encodes the granulocyte colony-stimulating factor receptor. This protein is a major factor in neutrophil stimulation and proliferation. The association on chromosome 11 contain genes RNF169 and XRRA1; both involved in the regulation of double-strand break DNA repair.

Indexed as

AdultAgedDatabases, GeneticElectronic Health RecordsFemaleGenome-Wide Association StudyHumansLatent Class AnalysisLeukocyte CountLeukocytesMaleMiddle AgedPhenotypePolymorphism, Single NucleotideProteinsReceptors, Colony-Stimulating FactorCSF3R protein, humanProteinsReceptors, Colony-Stimulating FactorRNF169 protein, humanUbiquitin-Protein LigasesXRRA1 protein, human

Identifiers

PMID30459343
PMCPMC6541537

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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.