Evidence map›Paper›PMID 41326768›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2025

Unveiling long-term prenatal nutrition biomarkers in beef cattle via multi-tissue and multi-OMICs analysis.

Guilherme Henrique Gebim Polizel, Ángela Cánovas, Wellison J S Diniz, German D Ramírez-Zamudio, Aline Silva Mello Cesar, Heidge Fukumasu, Arícia Christofaro Fernandes, Édison Furlan, Miguel Henrique de Almeida Santana

Abstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2025. 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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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

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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

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5 · Who and what money

Authors and funding

9 authors.

Guilherme Henrique Gebim PolizelDepartment of Animal Science, GOPec, Faculty of Animal Science and Food Engineering, University of São Paulo, Av. Duque de Caxias Norte, 225, Pirassununga, SP, 13635-900, Brazil. guilherme.polizel@usp.br.
Ángela CánovasDepartment of Animal Biosciences, Centre for Genetic Improvement of Livestock, University of Guelph, 50 Stone Road East, Guelph, ON, Canada.
Wellison J S DinizDepartment of Animal Sciences, College of Agriculture, Auburn University, Auburn, AL, 36849, USA.
German D Ramírez-ZamudioDepartment of Animal Science, GOPec, Faculty of Animal Science and Food Engineering, University of São Paulo, Av. Duque de Caxias Norte, 225, Pirassununga, SP, 13635-900, Brazil.
Aline Silva Mello CesarDepartment of Food Science and Technology, Luiz de Queiroz College of Agriculture, University of São Paulo, Av. Pádua Dias 11, Piracicaba, SP, 13418-900, Brazil.
Heidge FukumasuDepartment of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of São Paulo, Av. Duque de Caxias Norte, 225, Pirassununga, SP, 13635-900, Brazil.
Arícia Christofaro FernandesDepartment of Animal Science, GOPec, Faculty of Animal Science and Food Engineering, University of São Paulo, Av. Duque de Caxias Norte, 225, Pirassununga, SP, 13635-900, Brazil.
Édison FurlanDepartment of Animal Science, GOPec, Faculty of Animal Science and Food Engineering, University of São Paulo, Av. Duque de Caxias Norte, 225, Pirassununga, SP, 13635-900, Brazil.
Miguel Henrique de Almeida SantanaDepartment of Animal Science, GOPec, Faculty of Animal Science and Food Engineering, University of São Paulo, Av. Duque de Caxias Norte, 225, Pirassununga, SP, 13635-900, Brazil.

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 307593/2021-5Fundação de Amparo à Pesquisa do Estado de São Paulo 17/12105-2Fundação de Amparo à Pesquisa do Estado de São Paulo 23/09113-4
6 · The paper itself

Abstract

introductionMaternal nutrition during gestation plays a crucial role in shaping offspring development, metabolism, and long-term health, yet the underlying molecular mechanisms remain poorly understood.

objectivesThis study investigated potential biomarkers through multi-OMICs and multi-tissue analyses in offspring of beef cows subjected to different gestational nutrition regimes.

methodsA total of 126 cows were allocated to three groups: NP (control, mineral supplementation only), PP (protein-energy supplementation in the last trimester), and FP (protein-energy supplementation throughout gestation). Post-finishing phase, samples (blood, feces, ruminal fluid, fat, liver, and longissimus muscle/meat) were collected from 63 male offspring. RNA sequencing was performed on muscle and liver, metabolomics on plasma, fat, liver, and meat, and 16S rRNA sequencing on feces and ruminal fluid. Data were analyzed via DIABLO (mixOmics, R).

resultsThe muscle transcriptome showed strong cross-block correlations (|r| > 0.7), highlighting its sensitivity to maternal nutrition. Plasma glycerophospholipids (PC ae C30:0, PC ae C38:1, lysoPC a C28:0) were key biomarkers, particularly for FP. The PP group exhibited liver-associated markers (IL4I1 gene, butyrylcarnitine), reflecting late-gestation effects, while NP had reduced ruminal Clostridia (ASV151, ASV241), suggesting impaired microbial energy metabolism.

conclusionsThis integrative multi-OMICs approach provided deeper insights than single-layer analyses, distinguishing nutritional groups and revealing tissue- and OMIC-specific patterns. These findings demonstrate the value of combining transcriptomic, metabolomic, and microbiome data to identify biomarkers linked to maternal nutrition in beef cattle.

Indexed as

BiomarkersMaternal Nutritional Physiological PhenomenaMetabolomicsPrenatal Nutritional Physiological PhenomenaAnimalsCattleFemaleLiverMaleMultiomicsPregnancyTranscriptomeBiomarkersBeef prenatal nutritionMetabolomicsMetagenomicsSystems biologyTranscriptomics

Identifiers

PMID41326768
PMCPMC12669329

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LicenceCC BY
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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.