Evidence map›Paper›PMID 40777411›Full record

ArticlebioRxiv : the preprint server for biology2025

Urinary Signatures Predict Calorie Restriction-Mediated Weight Loss in Obese Diversity Outbred Mice.

Evan M Paules, Isis Trujillo-Gonzalez, Melissa VerHague, Jody Albright, Delisha Stewart, Susan J Sumner, Susan L McRitchie, David Kirchner, Michael F Coleman, Brian J Bennett and 4 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

5 · Who and what money

Authors and funding

14 authors.

Evan M PaulesDepartment of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0002-8344-818X
Isis Trujillo-GonzalezDepartment of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Melissa VerHagueNutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA.
Jody AlbrightNutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA.
Delisha StewartCollege of Medicine, Howard University, Washington, DC, USA.ORCID 0000-0001-7516-2790
Susan J SumnerDepartment of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Susan L McRitchieNutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA.
David KirchnerNutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA.
Michael F ColemanDepartment of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0002-6914-848X
Brian J BennettDepartment of Nutrition, University of California, Davis, CA, USA.ORCID 0000-0002-0766-3195
Annie Green HowardDepartment of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Penny Gordon-LarsenDepartment of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
John E FrenchDepartment of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Stephen D HurstingDepartment of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0003-3605-2833

Funding

UNIV OF NORTH CAROLINA CLINICAL NUTRITION RESEARCH UNITP30DK056350 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Venkata Saroja Voruganti · 1999 to 2026
$31.6M
Higher Dietary Carbohydrates Detrimentally Impact Obesity-Associated Breast Cancer ChemoresistanceR35CA197627 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HURSTING, STEPHEN D · 2015 to 2021
$6.0M
Leveraging metabolic pathways and gene expression data to propel understanding of severe obesity in a vulnerable and understudied populationR01DK139598 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Jennifer Below, PENNY GORDON-LARSEN · 2024 to 2026
$2.1M
NCI NIH HHS R35 CA197627NIDDK NIH HHS P30 DK056350NIDDK NIH HHS R01 DK139598
6 · The paper itself

Abstract

Predictive analytics encompassing metabolomic profiles are increasingly being used to forecast responders to dietary interventions. Advances using this approach are particularly needed to personalize and enhance the effectiveness of dietary weight loss interventions. Using obese Diversity Outbred (DO) mice that model genetic and phenotypic heterogeneity of human populations, we aimed to identify urinary metabolite signatures predictive of responsiveness to calorie restriction (CR)-mediated weight loss. DO mice (150 males, 150 females) were fed a high-fat diet for 12 weeks to induce obesity, then urine was collected and an 8-week CR regimen (30% decrease in energy intake) initiated. At study completion, mice were rank-ordered according to their percent body weight change, with mice in the extreme quartiles deemed CR responders (n=67) versus nonresponders (n=67). Targeted semi-quantitative metabolomics identified elevated glutamic acid and hydroxyproline as key urinary metabolites that distinguish CR responders from CR nonresponders, independent of sex. Three urinary metabolites (glutamic acid, hydroxyproline, and putrescine) distinguished male CR responders from nonresponders. Six metabolites (glutamic acid, hydroxyproline, dopamine, histamine, lysine, and spermine) distinguished female CR responders from nonresponders. Multivariate receiver operating characteristic analyses integrated the common metabolites and sex-specific metabolites to reveal moderate (males) to robust (females, males plus females) prediction models of CR-mediated weight loss. Further, pathway analysis identified several metabolic pathways, including arginine and proline metabolism, and alanine, aspartate, and glutamate biosynthesis, that distinguished CR responders from nonresponders and could be indicative of metabolic reprogramming to enhance insulin sensitivity and energy metabolism.

Indexed as

Caloric RestrictionDiet-Induced ObesityDiversity OutbredMetabolomicsUrinary Biomarkers

Identifiers

PMID40777411
PMCPMC12330736

What OpenQuestion holds

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LicenceCC BY
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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.