Evidence map›Paper›PMID 36865145›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Identifying COPD subtypes using multi-trait genetics.

Andrey Ziyatdinov, Brian D Hobbs, Samir Kanaan-Izquierdo, Matthew Moll, Phuwanat Sakornsakolpat, Nick Shrine, Jing Chen, Kijoung Song, Russell P Bowler, Peter J Castaldi and 6 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Andrey ZiyatdinovDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Brian D HobbsChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Samir Kanaan-IzquierdoCentre de Recerca en Enginyeria Biomèdica, Universitat Politècnica de Catalunya, Barcelona 08028, Spain.
Matthew MollChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Phuwanat SakornsakolpatChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Nick ShrineDepartment of Health Sciences, University of Leicester, Leicester, UK.
Jing ChenDepartment of Health Sciences, University of Leicester, Leicester, UK.
Kijoung SongHuman Genetics, GlaxoSmithKline, Collegeville, PA, USA.
Russell P BowlerDivision of Pulmonary and Critical Care, Dept. Med, National Jewish Health, Denver, CO, USA.
Peter J CastaldiChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Martin D TobinDepartment of Health Sciences, University of Leicester, Leicester, UK.
Peter KraftDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Edwin K SilvermanChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Hanna JulienneInstitut Pasteur, Université Paris Cité, Department of Computational Biology, F-75015 Paris, France.
Hugues AschardDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Michael H ChoChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.

Funding

Genetic Epidemiology of COPDU01HL089897 · NHLBI · NATIONAL JEWISH HEALTH · PI CRAPO, JAMES D · 2007 to 2021
$56.9M
Genetic Epidemiology of COPDU01HL089856 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2007 to 2021
$20.7M
(2 of 2) Genetic Epidemiology of COPDR01HL089856 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2012 to 2016
$18.9M
Genetic and Genomic Characterization of the Occurrence and Progression of Interstitial Lung AbnormalitiesR01HL135142 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI MICHAEL H. CHO, GARY MATTHEW HUNNINGHAKE · 2017 to 2026
$7.7M
Genetic and Functional Dissection of a Cluster of COPD GWAS Signals on Chromosome 4qR01HL147148 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI CHO, MICHAEL H., SILVERMAN, EDWIN K · 2019 to 2022
$3.5M
Identifying functional variants in COPD GWAS lociR01HL137927 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI CHO, MICHAEL H., SILVERMAN, EDWIN K · 2017 to 2020
$3.5M
Clinical Implications, Genomics, and Transcriptions of Mucus Plugging in SmokersR01HL149861 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI CHO, MICHAEL H., DIAZ, ALEJANDRO · 2020 to 2023
$3.2M
Medical Research Council MC_PC_19004NHLBI NIH HHS R01 HL089856NHLBI NIH HHS R01 HL135142NHLBI NIH HHS R01 HL137927NHLBI NIH HHS R01 HL147148NHLBI NIH HHS R01 HL149861NHLBI NIH HHS U01 HL089856NHLBI NIH HHS U01 HL089897Wellcome Trust 202849/Z/16/Z
6 · The paper itself

Abstract

Chronic Obstructive Pulmonary Disease (COPD) has a simple physiological diagnostic criterion but a wide range of clinical characteristics. The mechanisms underlying this variability in COPD phenotypes are unclear. To investigate the potential contribution of genetic variants to phenotypic heterogeneity, we examined the association of genome-wide associated lung function, COPD, and asthma variants with other phenotypes using phenome-wide association results derived in the UK Biobank. Our clustering analysis of the variants-phenotypes association matrix identified three clusters of genetic variants with different effects on white blood cell counts, height, and body mass index (BMI). To assess the potential clinical and molecular effects of these groups of variants, we investigated the association between cluster-specific genetic risk scores and phenotypes in the COPDGene cohort. We observed differences in steroid use, BMI, lymphocyte counts, chronic bronchitis, and differential gene and protein expression across the three genetic risk scores. Our results suggest that multi-phenotype analysis of obstructive lung disease-related risk variants may identify genetically driven phenotypic patterns in COPD.

Identifiers

PMID36865145
PMCPMC9980243

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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.