Evidence map›Paper›PMID 41952336›Full record

ArticleHGG advances2026

Using a modular massively parallel reporter assay to discover context-dependent regulatory activity in type 2 diabetes-linked noncoding regions.

Adelaide Tovar, Yasuhiro Kyono, Kirsten Nishino, Maya Bose, Arushi Varshney, Stephen C J Parker, Jacob O Kitzman

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PubMed Full text at PMC Publisher
In one paragraph

Article in HGG advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Adelaide TovarGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Yasuhiro KyonoGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Kirsten NishinoGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Maya BoseGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Arushi VarshneyGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Stephen C J ParkerGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: scjp@umich.edu.
Jacob O KitzmanGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: kitzmanj@umich.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most complex trait association signals reside in the noncoding genome, where defining function is challenging. MPRAs (massively parallel reporter assays) offer a scalable means to test variants' regulatory impacts but are typically cell-type agnostic, pairing cloned fragments with generic "housekeeping" promoters. To explore MPRAs' context sensitivity, we screened a panel of nearly 12,000 fragments across >300 diabetes- and metabolic-trait-associated regions in a pancreatic β cell line model. We compared activity when fragments were placed up- versus downstream of a reporter gene and combined with the synthetic housekeeping promoter super core promoter 1 (SCP1) versus the physiologically relevant human insulin (INS) gene promoter. We identified clear effects of MPRA construct design on regulatory activity. A subset of fragments (n = 702/11,656) displayed positional bias, evenly distributed across up- and downstream preferences. Promoter choice also influenced MPRA activity (n = 698/11,656), mostly biased toward the cell-specific INS promoter (73.4%). A screen for sequence annotations associated with INS promoter preference revealed enrichment for HNF1 binding motifs. HNF1 family transcription factors are key regulators of glucose metabolism disrupted in maturity-onset diabetes of the young (MODY), suggesting genetic convergence between rare coding variants that cause MODY and common type 2 diabetes (T2D)-associated regulatory regions. A follow-up HNF1-focused MPRA highlighted several instances where motif deletion or mutation disrupted regulatory activity specifically in the context of the INS1 promoter and in the β cell model but not in another diabetes-relevant cell type, skeletal muscle. These results identify technical factors that may require careful consideration while designing MPRA experiments.

Indexed as

Diabetes Mellitus, Type 2Gene Expression RegulationGenes, ReporterAnimalsCell LineHepatocyte Nuclear Factor 1-alphaHumansInsulinInsulin-Secreting CellsPromoter Regions, GeneticHepatocyte Nuclear Factor 1-alphaInsulindiabetesgene regulationregulatory elementsreporter assaytranscription factors

Identifiers

PMID41952336
PMCPMC13125165

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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.