Proteomic approaches to predict bioavailability of fatty acids and their influence on cancer and chronic disease prevention

Baukje de Roos, Donato Romagnolo

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

A low intake of fish and PUFA and high dietary trans- and SFA are considered to be among the main preventable causes of death. Unfortunately, epidemiological and preclinical studies have yet to identify biomarkers that accurately predict the influence of fatty acid intake on risk of chronic diseases, including cancer. Changes in protein profile and post-translational modifications in tissue and biofluids may offer important clues about the impact of fatty acids on the etiology of chronic diseases. However, conventional protein methodologies are not adequate for assessing the impact of fatty acids on protein expression patterns and modifications and the discovery of protein biomarkers that predict changes in disease risk and progression in response to fatty acid intake. Although fluctuations in protein structure and abundance and interindividual variability often mask subtle effects caused by dietary intervention, modern proteomic platforms offer tremendous opportunities to increase the sensitivity of protein analysis in tissues and biofluids (plasma, urine) and elucidate the effects of fatty acids on regulation of protein networks. Unfortunately, the number of studies that adopted proteomic tools to investigate the impact of fatty acids on disease risk and progression is quite small. The future success of proteomics in the discovery of biomarkers of fatty acid nutrition requires improved accessibility and standardization of proteomic methodologies, validation of quantitative and qualitative protein changes (e.g., expression levels, posttranslational modifications) induced by fatty acids, and application of bioinformatic tools that can inform about the causeeffect relationships between fatty acid intake and health response.

Original languageEnglish (US)
JournalJournal of Nutrition
Volume142
Issue number7
DOIs
StatePublished - Jul 2012

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Proteomics
Biological Availability
Chronic Disease
Fatty Acids
Neoplasms
Proteins
Biomarkers
Post Translational Protein Processing
Disease Progression
Masks
Computational Biology
Epidemiologic Studies
Cause of Death
Fishes
Urine
Health

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Nutrition and Dietetics

Cite this

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abstract = "A low intake of fish and PUFA and high dietary trans- and SFA are considered to be among the main preventable causes of death. Unfortunately, epidemiological and preclinical studies have yet to identify biomarkers that accurately predict the influence of fatty acid intake on risk of chronic diseases, including cancer. Changes in protein profile and post-translational modifications in tissue and biofluids may offer important clues about the impact of fatty acids on the etiology of chronic diseases. However, conventional protein methodologies are not adequate for assessing the impact of fatty acids on protein expression patterns and modifications and the discovery of protein biomarkers that predict changes in disease risk and progression in response to fatty acid intake. Although fluctuations in protein structure and abundance and interindividual variability often mask subtle effects caused by dietary intervention, modern proteomic platforms offer tremendous opportunities to increase the sensitivity of protein analysis in tissues and biofluids (plasma, urine) and elucidate the effects of fatty acids on regulation of protein networks. Unfortunately, the number of studies that adopted proteomic tools to investigate the impact of fatty acids on disease risk and progression is quite small. The future success of proteomics in the discovery of biomarkers of fatty acid nutrition requires improved accessibility and standardization of proteomic methodologies, validation of quantitative and qualitative protein changes (e.g., expression levels, posttranslational modifications) induced by fatty acids, and application of bioinformatic tools that can inform about the causeeffect relationships between fatty acid intake and health response.",
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