Evidence map›Paper›PMID 42990957›Full record

ReviewFrontiers in medicine2026

Kidney adiposity in obesity and chronic kidney disease: mechanisms, measurement, and clinical implications.

Yunxi Zhang

Abstract readReview
In one paragraph

Review in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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.

Yunxi ZhangSchool of Medicine, Tulane University, New Orleans, LA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kidney outcomes vary substantially among people with similar body mass index (BMI), and conventional measures of obesity do not specify the adipose compartments that lie closest to the kidney or the biological state of those tissues. Human imaging, physiological studies, and paired-tissue analyses now permit a more anatomically explicit account of kidney adiposity. Perirenal adipose tissue (PRAT), renal sinus adipose tissue (RSAT), and intrarenal lipid are distinct constructs and should not be collapsed into a single 'fatty kidney' construct. This critical narrative review examines kidney adiposity at the obesity-CKD interface using a claim-conditioned translational evidence continuum spanning association, partial independence from systemic adiposity, prospective association, human mechanistic support, treatment-associated depot remodeling, depot-renal response linkage, causal mediation, and treatment-effect modification. Selected kidney-associated fat measures are associated with albuminuria, filtration, intrarenal haemodynamics, and CKD status, and some signals persist after adjustment for BMI or visceral adipose tissue. In paired tissue from healthy kidney donors, PRAT and RSAT show distinct metabolic and immune profiles. However, much of the human evidence derives from cohorts enriched for type 2 diabetes, which limits extrapolation to non-diabetic obesity-associated CKD. Acquisition, segmentation, normalisation, external validation, and clinically useful thresholds also remain unsettled. Intervention studies show that selected kidney-associated fat measures can change with lifestyle or sodium-glucose cotransporter-2 inhibition, whereas major kidney-outcome trials often did not measure kidney-adiposity compartments. These parallel observations do not establish that depot remodeling mediates renal protection. Compartment-resolved assessment of kidney adiposity should therefore be regarded as a research strategy rather than a clinical classification. Its future value depends on incremental prognostic or decision information beyond eGFR, albuminuria, and validated CKD risk models, and on direct testing of whether depot modification contributes causally to kidney response.

Indexed as

adipose-kidney crosstalkchronic kidney diseaseectopic renal lipidimagingobesityperirenal adipose tissuerenal sinus fattreatment associated remodeling

Identifiers

PMID42990957
PMCPMC13735895

What OpenQuestion holds

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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.