In one paragraphArticle in bioRxiv : the preprint server for biology, 2026. 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 itWhat 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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
14 authors.
Aditya SriramDepartment of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0001-7303-9529 Soyeon KimDivision of Pulmonary Medicine, Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0003-1573-2733 Rebecca Caldino BohnDepartment of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0009-0009-5584-8483 Wei ChenDivision of Pulmonary Medicine, Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0001-7196-8703 Tianhao LiuDivision of Pulmonary Medicine, Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Molin YueDivision of Pulmonary Medicine, Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Niyati JainDepartment of Public Health Sciences, University of Chicago, Chicago, IL, USA.
Roby JoehanesPopulation Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0001-5549-9054 Daniel LevyPopulation Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0003-1843-8724 Hyun Jung ParkDepartment of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0002-8324-2624 Juan C CeledónDivision of Pulmonary Medicine, Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0002-6139-5320 Funding
VECTOR CORE FACILITYP30CA047904 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CHRISTOPHER J. BAKKENIST · 1988 to 2026
$158.0MProject 5: Microenvironment manipulation using anti-angiogenics to improve immunotherapy in melanomaP50CA254865 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI WANG, HONG · 2021 to 2025
$10.4MEpigenetic Variation and Childhood Asthma in Puerto RicansR01HL117191 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CELEDON, JUAN CARLOS · 2013 to 2020
$5.8MInflammation Phenotypes in Pediatric Sepsis Induced Multiple Organ Failure RenewalR01GM108618 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI JOSEPH A CARCILLO · 2014 to 2026
$5.4MGenes, Home Allergens and Asthma Puerto Rican ChildrenR01HL079966 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CELEDON, JUAN CARLOS · 2006 to 2010
$3.8MExposure to violence during childhood and Th2-high asthma in young Puerto Rican adultsR01HL168539 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Juan Carlos Celedon · 2023 to 2026
$2.6MExposure to violence, epigenetic variation, and asthma in Puerto Rican childrenR01MD011764 · NIMHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CELEDON, JUAN CARLOS · 2017 to 2020
$1.3MIdentifying Genetic and Epigenetic Risk Factors Regulating Gene Expression for Childhood AsthmaK01HL153792 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KIM, SOYEON · 2020 to 2025
$699kHigh-Throughput Computing for Genomics and Bioinformatics ResearchS10OD028483 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LEE, ADRIAN V · 2021 to 2021
$574kMulti-omics Analysis of Childhood Asthma in HispanicsR21HL150431 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CELEDON, JUAN CARLOS, CHEN, WEI · 2020 to 2021
$235kNCI NIH HHS P30 CA047904NCI NIH HHS P50 CA254865NHLBI NIH HHS K01 HL153792NHLBI NIH HHS R01 HL079966NHLBI NIH HHS R01 HL117191NHLBI NIH HHS R01 HL168539NHLBI NIH HHS R21 HL150431NIGMS NIH HHS R01 GM108618NIH HHS S10 OD028483NIMHD NIH HHS R01 MD011764
6 · The paper itselfAbstract
Motivation: Epigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. Results: We developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG- searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. Availability and implementation: The eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/. The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas.
Indexed as
DNA methylationeQTMExpression quantitative trait methylationgene expressiongene regulation
Identifiers
PMID42327319
PMCPMC13278183
What OpenQuestion holds
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