Evidence map›Paper›PMID 40890166›Full record

ArticleScientific data2025

A spatial transcriptomics dataset of pancreas sections in normal glucose tolerance and type 2 diabetic donors.

Nick Howell, Zoe Weiss, Lori L Bonnycastle, Caleb M Grenko, Davide Randazzo, Christopher H Dampier, Neelam Sinha, Narisu Narisu, Amy J Swift, Michael R Erdos and 4 more

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
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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

14 authors.

Nick Howell *Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.ORCID 0009-0004-2255-073X
Zoe Weiss *Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Lori L Bonnycastle *Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Caleb M GrenkoCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Davide RandazzoOffice of Science and Technology, Light Imaging Section, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD, 20892, USA.
Christopher H DampierLaboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Neelam SinhaCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Narisu NarisuCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Amy J SwiftCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Michael R ErdosCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA. mikee@mail.nih.gov.
Leslie G BieseckerCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Francis S CollinsCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA. francis.collins@gmail.com.
Catherine C RobertsonCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
D Leland TaylorCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.

Funding

GENETIC ANALYSIS OF TYPE II DIABETES IN FINNISH POPULATIONZ01HG000024 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI COLLINS, FRANCIS S. · 1995 to 2008
$6.2M
Intramural NIH HHS Z01 HG000024U.S. Department of Health & Human Services | National Institutes of Health (NIH) HG000024-30
6 · The paper itself

Abstract

Understanding the spatial distribution of gene expression in the pancreas is essential for establishing the molecular basis of pancreatic function in healthy and disease contexts. Recent platforms offer a robust method for quantifying gene expression within a spatial context. Here, we report spatial transcriptomic profiling from pancreas samples obtained from three donors with type 2 diabetes (T2D) and three donors with normal glucose tolerance (NGT). Our analysis identified a major technical challenge: substantial transcript bleed of highly abundant genes (e.g., INS and GCG) into adjacent tissue regions. We demonstrate that this bleed can be computationally corrected using probabilistic models. Our analysis highlights the importance of incorporating bleed-correction techniques in the preprocessing of spatial transcriptomic profiling data. In summary, this study provides a dataset, methods, and resources to investigate the spatial regulation of gene expression in normal and T2D-affected human pancreas.

Indexed as

Diabetes Mellitus, Type 2PancreasTranscriptomeGene Expression ProfilingHumans

Identifiers

PMID40890166
PMCPMC12402493

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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.