Article in Metabolites, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 39% 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
1 citing paper in PubMed, 1 citations in OpenAlex.
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
12 authors at 3 institutions in 1 country.
Tim VigersDepartment of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO 80045, USA.ORCID 0000-0001-7087-8570
Lauren A VanderlindenDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO 80045, USA.
Randi K JohnsonDivision of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Aurora, CO 80045, USA.ORCID 0000-0001-9345-4439
Patrick M CarryBarbara Davis Center for Diabetes, University of Colorado, Aurora, CO 80045, USA.
Ivana YangDivision of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Aurora, CO 80045, USA.
Brian C DeFeliceWest Coast Metabolomics Center, University of California, Davis, CA 95616, USA.ORCID 0000-0001-8243-0300
Alexander M KaizerDepartment of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO 80045, USA.
Laura PyleDepartment of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO 80045, USA.
Marian RewersDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO 80045, USA.
Oliver FiehnWest Coast Metabolomics Center, University of California, Davis, CA 95616, USA.ORCID 0000-0002-6261-8928
Jill M NorrisBarbara Davis Center for Diabetes, University of Colorado, Aurora, CO 80045, USA.
Katerina KechrisDepartment of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO 80045, USA.ORCID 0000-0002-3725-5459
Colorado School of Public Health · USUniversity of Colorado Anschutz Medical Campus · USUniversity of California, Davis · US
Funding
University of Colorado Anschutz Medical Campus DRCP30DK116073 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI LORI SUSSEL · 2020 to 2026
$10.8M
Natural History of Pre-Diabetic Autoimmunity (DAISY)R01DK032493 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI REWERS, MARIAN J · 1986 to 2024
$9.3M
Nutrigenetics & -genomics of Vitamin D and Omega-3 Fatty Acids in Type 1 DiabetesR01DK104351 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI NORRIS, JILL M · 2014 to 2018
$2.9M
Addressing Sparsity in Metabolomics Data AnalysisU01CA235488 · NCI · UNIVERSITY OF COLORADO DENVER · PI GHOSH, DEBASHIS, KECHRIS-MAYS, KATHERINA · 2018 to 2021
$1.8M
Islet Autoimmunity Reversion as a Model of T1D ResiliencyR21AI142483 · NIAID · UNIVERSITY OF COLORADO DENVER · PI NORRIS, JILL M · 2019 to 2020
$428k
National Institute of Allergy and Infectious Diseases R21AI142483NCI NIH HHS U01 CA235488NIAID NIH HHS R21 AI142483NIDDK NIH HHS P30 DK116073NIDDK NIH HHS R01 DK032493NIDDK NIH HHS R01 DK104351NIDDK NIH HHS R01DK104351
6 · The paper itself
Abstract
Environmental factors including viruses, diet, and the metabolome have been linked with the appearance of islet autoimmunity (IA) that precedes development of type 1 diabetes (T1D). We measured global DNA methylation (DNAm) and untargeted metabolomics prior to IA and at the time of seroconversion to IA in 92 IA cases and 91 controls from the Diabetes Autoimmunity Study in the Young (DAISY). Causal mediation models were used to identify seven DNAm probe-metabolite pairs in which the metabolite measured at IA mediated the protective effect of the DNAm probe measured prior to IA against IA risk. These pairs included five DNAm probes mediated by histidine (a metabolite known to affect T1D risk), one probe (cg01604946) mediated by phostidyl choline p-32:0 or o-32:1, and one probe (cg00390143) mediated by sphingomyelin d34:2. The top 100 DNAm probes were over-represented in six reactome pathways at the FDR <0.1 level (
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.
A Mediation Approach to Discovering Causal Relationships between the Metabolome and DNA Methylation in Type 1 Diabetes. · full record | OpenQuestion