Evidence map›Paper›PMID 41827860›Full record

ReviewCells2026

Exploring Adipose Tissue Complexity Through Omics Approaches: Implications for Health and Disease.

Rajaa Sebaa

Abstract readReview
In one paragraph

Review in Cells, 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

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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Rajaa SebaaDepartment of Medical Laboratories, College of Applied Medical Sciences, Shaqra University, Shaqra 11961, Saudi Arabia.ORCID 0000-0003-3638-8716

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adipose tissues (ATs) are dynamic and heterogeneous organs divided into three distinct categories, including white, beige, and brown ATs. Collectively, they contribute to systemic energy homeostasis in various ways. White adipocytes primarily store excess energy, whereas brown and beige adipocytes dissipate energy as heat through non-shivering thermogenesis. Recent advances in multi-omics technologies have transformed our understanding of adipocyte biology, enabling comprehensive interrogation of transcriptional, epigenetic, proteomic, and metabolomic networks that define adipocyte identity and function. Transcriptomic studies reveal distinct gene signatures underlying thermogenic activation and lineage commitment, while epigenomic profiling highlights regulatory elements that orchestrate adipocyte plasticity, particularly the inducible browning of white fat. Proteomic and metabolomic analyses further uncover mitochondrial remodeling, lipid turnover pathways, and metabolite, hormone interactions that regulate thermogenic capacity and metabolic health. Integrating these multi-layered datasets provides systems-level insights into the roles of environmental cues, such as diet and temperature, and endogenous factors, including hormonal signaling, circadian rhythms, and genetic background, in reshaping adipocyte phenotypes and influencing whole-body metabolism. Multi-omics approaches are increasingly identifying potential novel biomarkers and therapeutic targets aiming to enhance the activity of brown and beige adipocyte to combat obesity and metabolic disorders. Overall, these technologies provide a powerful framework for elucidating the complexity of ATs and advancing precision strategies for metabolic disease management and prevention.

Indexed as

Adipose TissueHealthProteomicsAdipose Tissue, BrownAnimalsEnergy MetabolismHumansMetabolomicsMultiomicsThermogenesisbeige adipose tissue (BeAT)brown adipose tissue (BAT)omics approacheswhite adipose tissue (WAT)

Identifiers

PMID41827860
PMCPMC12984843

What OpenQuestion holds

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LicenceCC BY
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 OpenQuestion graph.