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Biomarkers of Nutrition and Health: New Tools for New Approaches
Open accessAbstract
A main challenge in nutritional studies is the valid and reliable assessment of food intake, as well as its effects on the body. Generally, food intake measurement is based on self-reported dietary intake questionnaires, which have inherent limitations. They can be overcome by the use of biomarkers, capable of objectively assessing food consumption without the bias of self-reported dietary assessment. Another major goal is to determine the biological effects of foods and their impact on health. Systems analysis of dynamic responses may help to identify biomarkers indicative of intake and effects on the body at the same time, possibly in relation to individuals’ health/disease states. Such biomarkers could be used to quantify intake and validate intake questionnaires, analyse physiological or pathological responses to certain food components or diets, identify persons with specific dietary deficiency, provide information on inter-individual variations or help to formulate personalized dietary recommendations to achieve optimal health for particular phenotypes, currently referred as “precision nutrition.” In this regard, holistic approaches using global analysis methods (omics approaches), capable of gathering high amounts of data, appear to be very useful to identify new biomarkers and to enhance our understanding of the role of food in health and disease.
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“Lipid Profile: Total cholesterol (<200 mg/dL). LDL (<100 mg/dL) HDL (>40 mg/dL in men and >50 mg/dL in women) Triglycerides (<150 mg/dL) Assesses cardiovascular risk and fat metabolism.[23]”
From The Seven Methods for the Evaluation of Nutritional Status—ABCDEFG: Narrative Review (2026) · cites this paper as [23]
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“Elevated serum creatinine levels are indicative of decreased glomerular filtration rate (GFR) and may suggest acute or chronic kidney disease.”
From The Seven Methods for the Evaluation of Nutritional Status—ABCDEFG: Narrative Review (2026) · cites this paper as [23]
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Metadata
- Authors
- Picó, C., Serra, F., Rodríguez, A. M., Keijer, J., & Palou, A.
- Affiliations
- Centro de Investigación Biomédica en Red (ES)
- Wageningen University & Research (NL)
- Corresponding author
- Serra, Francisca
- Venue
- Nutrients
- Publisher
- MDPI AG
- Published
- 2019-05-16
- Volume
- 11
- Issue
- 5
- Pages
- 1092
- ISSN
- 2072-6643 (ISSN-L)
- PMC
- PMC6567133
- OpenAlex
- W2945004919
- Cited by
- 287
- References
- 242
- Citations by year
- 2026: 35 · 2025: 42 · 2024: 49 · 2023: 33 · 2022: 50 · 2021: 39 · 2020: 27 · 2019: 11
- FWCI
- 4.21
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Nutrients (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Socio-Environmental Systems Modeling (acceptedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Docusalut (Conselleria de Salut i Consum del Govern de les Illes Balears) (submittedVersion, cc-by)
- Hispana (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- Funders
- Ministerio de Ciencia, Innovación y Universidades (PGC2018-097436-B-I00, PGC 2018)
- European Commission (HORIZON2020, 818318)
- Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición
- Instituto de Salud Carlos III
- Agencia Estatal de Investigación (PGC2018‐097436‐B‐I00)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Keywords
- dietary biomarkers, dietary assessment, biomarker validation, dietary deficiency, personalized nutrition, omics approaches, systems analysis, interindividual variability
- MeSH terms
- Blood Glucose, Humans, Insulin, Nutritional Status, Biomarkers, Nutrition Assessment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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