Evidence map›Paper›PMID 42405209›Full record

ReviewImmune network2026

Decoding Immune Regulation: From Genetic Variation to Mechanism Through Single-Cell Genomics.

Jung Hee Koh, Chun Jimmie Ye

Abstract readReview
In one paragraph

Review in Immune network, 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

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

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

2 authors.

Jung Hee KohDivision of Rheumatology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.ORCID https://orcid.org/0000-0002-6617-1449
Chun Jimmie YeDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA 94143, USA.ORCID https://orcid.org/0000-0001-6560-3783

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune cell states are not fixed. Rather, they emerge from dynamic transcriptional programs shaped by genetic variation, cellular context, and gene regulatory networks (GRNs). Single-cell and multi-omic technologies now enable population-scale immune profiling across molecular layers, revealing that cell-to-cell transcriptional variability is a functional feature that diversifies immune responses. Distribution-aware and tensor-based analytical frameworks capture this variability beyond mean expression, resolving coordinated gene programs across cell types, individuals, and conditions. Integrating human genetics with single-cell genomics demonstrates that genetic effects on gene expression, splicing, and chromatin accessibility are highly dependent on cell type, activation state, and differentiation trajectory. These variant-level signals converge on GRNs in which key transcription factors orchestrate context-dependent immune programs. High-throughput perturbation screens enable scalable functional validation of these networks, linking genetic variation to cellular function. Together, these integrative approaches translate molecular discoveries into clinical applications, from patient stratification to therapeutic target prioritization. Emerging spatial multi-omics and

Indexed as

Gene regulatory networksGenetics, HumanImmunogenetic phenomenaQuantitative trait lociSingle-cell gene expression analysis

Identifiers

PMID42405209
PMCPMC13333242

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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 Socratic graph.