Evidence map›Paper›PMID 42213079›Full record

ArticleBioinformatics (Oxford, England)2026

Genomics-informed approach identifies which cell types regulate the metabolome.

Haim Krupkin, Evin M Padhi, Daniel Nachun, Jessica Kain, Jonathan Z Long, Stephen B Montgomery

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 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 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

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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

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

6 authors.

Haim KrupkinDepartment of Genetics, Stanford University School of Medicine, Stanford, CA 94305, United States.ORCID 0009-0004-3164-0243
Evin M PadhiDepartment of Pathology, Stanford University School of Medicine, Stanford, CA 94305, United States.
Daniel NachunDepartment of Pathology, Stanford University School of Medicine, Stanford, CA 94305, United States.
Jessica KainDepartment of Genetics, Stanford University School of Medicine, Stanford, CA 94305, United States.
Jonathan Z LongDepartment of Pathology, Stanford University School of Medicine, Stanford, CA 94305, United States.
Stephen B MontgomeryDepartment of Genetics, Stanford University School of Medicine, Stanford, CA 94305, United States.ORCID 0000-0002-5200-3903

Funding

NIH HHS R01MH12524
6 · The paper itself

Abstract

motivationMetabolism occurs in a cell type-specific manner, but which cells regulate metabolite levels remains unclear.

resultsHere, we integrate some of the largest metabolite quantitative trait loci datasets, TOPMed and UK Biobank, with one of the most extensive single-cell RNA sequencing resources, Tabula Sapiens. This integration allows us to identify cell types that regulate metabolites body-wide. We find hepatocytes are the primary regulatory cell type for most metabolites, associating with 385/410 (94%) metabolites for whom an association is found. Additionally, our multi-gene approach reveals more metabolite associations with beta cells compared to those identified using a single-gene approach. For example, we identify novel metabolite-cell type associations, such as the association between phenylpropanoic acid and beta cells, this metabolite that was previously thought to be regulated by the microbiome. AVAILABILITY: Code used in this work is available via Github at https://github.com/haimkru/Metabolite-Cell-Type-Associations.

Indexed as

GenomicsMetabolomeHepatocytesHumansQuantitative Trait Loci

Identifiers

PMID42213079
PMCPMC13284994

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.