Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
0numbers the graph read from it
0cells of the map it votes in
4citing 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.
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.
Sanghun LeeDepartment of Medical Consilience, Division of Medicine, Graduate School, Dankook University, Yongin-si, South Korea.ORCID 0000-0002-0573-9555
Rachel S KellyChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0003-3023-1822
Kevin M MendezChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-8832-2607
Dmitry ProkopenkoGenetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0002-1844-5652
Georg HahnDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0001-6008-2720
Sharon M LutzDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, MA, USA.
Juan C CeledónDivision of Pediatric Pulmonary Medicine, Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0002-6139-5320
Scott T WeissChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-7196-303X
Christoph LangeChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0003-2620-1030
Jessica A Lasky-SuChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-6236-4705
Julian HeckerChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-7918-089X
NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
Funding
Genetic Epidemiology of COPDU01HL089897 · NHLBI · NATIONAL JEWISH HEALTH · PI CRAPO, JAMES D · 2007 to 2021
$56.9M
ROLE OF DIETARY CONSTITUENTS ON GENE EXPRESSION IN INTESTINAL EPITHELIUMP30DK040561 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI CHRISTOPHER P DUGGAN · 1994 to 2026
$31.6M
Genetic Epidemiology of COPDU01HL089856 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2007 to 2021
$20.7M
The Genetic Epidemiology of Asthma in Costa RicaR37HL066289 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI WEISS, SCOTT T · 2007 to 2015
$14.6M
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
Systems Biology of Airway DiseaseP01HL132825 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI DEMEO, DAWN L · 2016 to 2020
$12.6M
Physics of collective cellular migration in lung health and diseaseP01HL120839 · NHLBI · HARVARD SCHOOL OF PUBLIC HEALTH · PI FREDBERG, JEFFREY J · 2014 to 2018
$12.2M
Studies of Rare Genetic Variation in the Isolated Population of SardiniaR01HL117626 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2013 to 2016
$10.5M
Proteomics and Metabolomics Core: IDEAL shapes vaccine response, susceptibility to respiratory infectious disease and asthmaU19AI168643 · NIAID · BOSTON CHILDREN'S HOSPITAL · PI OFER LEVY · 2022 to 2026
$10.0M
Rare variants and NHLBI traits in deeply phenotyped cohortsR01HL120393 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M, RICE, KENNETH M. · 2014 to 2016
$8.9M
Integrative Metabolomics of Asthma SeverityR01HL123915 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LASKY-SU, JESSICA A · 2014 to 2023
$7.0M
Rare variants and NHLBI traits in deeply phenotyped cohortsU01HL120393 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M, RICE, KENNETH M. · 2017 to 2018
Metabolomic genome-wide association studies (mGWASs), or metabolomic quantitative trait locus (metQTL) analyses, are gaining growing attention. However, robust methods and analysis guidelines, vital to address the complexity of metabolomic data, remain to be established. Here, we use whole-genome sequencing and metabolomic data from two independent studies to compare different approaches. We adopted three popular data transformation methods for metabolite levels-(i) log
Indexed as
Genome-Wide Association StudyMetabolomeMetabolomicsQuantitative Trait LociComputer SimulationHumansPolymorphism, Single NucleotideResearch Design
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.
On the analysis of metabolite quantitative trait loci: Impact of different data transformations and study designs. · full record | OpenQuestion