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Related Concept Videos

Proteomics01:33

Proteomics

10.2K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos
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Leveraging Multiomic Signatures to Predict Body Composition.

Sri Lakshmi S Devarakonda1, David A Hughes1, Christian Rodriguez1

  • 1Pennington Biomedical Research Center, LSU System, Baton Rouge, LA, United States.

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|April 5, 2026
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Summary
This summary is machine-generated.

New omics-derived blood biomarkers offer a promising alternative to traditional methods for assessing body composition, overcoming hardware limitations and improving accuracy in clinical evaluations for conditions like obesity and sarcopenia.

Keywords:
adipositymetabolomicsmuscularitynutritional assessmentproteomics

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Area of Science:

  • Biochemistry
  • Physiology
  • Biomarker Discovery

Background:

  • Clinical guidelines for obesity, sarcopenia, malnutrition, and cachexia emphasize body composition assessment.
  • Traditional methods often require specialized hardware, limiting accessibility.
  • Body mass index (BMI) is a common but limited proxy for body composition.

Purpose of the Study:

  • To explore the potential of omics-derived circulating blood biomarkers for body composition assessment.
  • To review advances in using metabolites and proteins to estimate body components.
  • To present a perspective on novel body composition phenotyping methods.

Main Methods:

  • Reviewing existing observations linking serum creatinine to skeletal muscle mass and leptin to adipose tissue mass.
  • Examining the development of prediction models incorporating serum measurements with demographic data.
  • Investigating omics technologies for identifying new blood biomarkers.
  • Exploring models based solely on blood biomarker measurements.

Main Results:

  • Serum metabolite and protein levels can be integrated into conventional equations to improve body composition estimation.
  • Omics technologies enable the identification of a broader range of blood biomarkers.
  • New models can be developed using only blood biomarker data for body composition assessment.

Conclusions:

  • Omics-derived blood biomarkers represent a significant advancement in body composition assessment.
  • This approach offers a more accessible and potentially accurate alternative to traditional methods.
  • Further research in this rapidly evolving field holds promise for clinical applications.