Evidence map›Paper›PMID 42656584›Full record

ReviewFrontiers in cell and developmental biology2026

Harnessing iPSC technology for population-level human disease/traits modeling -where are we?

P K Suresh

Abstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 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

1 author.

P K SureshSchool of Bio Sciences & Technology, VIT, Vellore, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This mini review highlights the major developments in iPSC research and the importance of dissecting the contribution of epigenetic factors in resetting the epigenome and their correlation to the stage-wise transitions to the dedifferentiated state. Since the need of the hour is to identify multiple genetic variants at the population level that are the major contributors to the heterogeneity in the inter-individual response (combination of environmental and/or genetic influences), it is necessary to adopt methodologies (in human iPSC cell lines) including DNA sequencing methods, SNP genotyping arrays, and other variants identification methods to identify, quantify these micro-level changes and correlate them with the disease phenotype. Further, studies (including scRNA-based approaches) need to be performed to compare variants at the transcriptomic level to trace it back to the specific individual/human cohort, thereby unraveling the context-dependent masked effects at the population level and fill in the gaps between the clinical aspects and e-localization signals. Further, village-in-a-dish (co-culture of heterogeneous cell types differentiated from the different iPSC cell lines isolated from human donors) and humanity-in-a dish model strategies will benefit from ongoing methods to generate an atlas of genetic variants that can explain genetic diversity globally. Parallel efforts to improve the scalability, automation and throughput in the development of mature human cells as well as refine strategies to better correlate and perform QTL mapping studies will complement the existing body of clinical and molecular data and unravel the relative role played by environmental factors to the overall disease risk, phenotype and drug response.

Indexed as

diversity-in-a-dishhumanity-in-a-dishinduced pluripotent stem cells (iPSCs)population and cell-based modelingquantitative expression loci (QTL)single cell RNA sequencing (scRNA)village-in-a-dish

Identifiers

PMID42656584
PMCPMC13507525

What OpenQuestion holds

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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 OpenQuestion graph.