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A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Nutrigenetics and Nutrigenomics".

Deadline for manuscript submissions: 20 July 2026 | Viewed by 6447

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Special Issue Editor

Prof. Dr. George Dedoussis

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Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University of Athens, 17671 Athens, Greece
Interests: genetics; nutrigenetics; personalized nutrition; artificial intelligence (AI); machine learning (ML); non-communicable diseases (NCDs); obesity; metabolic dysfunction-associated steatotic liver disease (MASLD)
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Dear Colleagues,

Genome-based personalized nutrition technology represents a transformative approach to optimizing dietary interventions through the integration of genetic information. Advances in genomic sequencing and bioinformatics have enabled the identification of genetic variations that influence metabolism, nutrient absorption, and the risk of disease. These insights facilitate the development of tailored nutritional strategies that enhance health outcomes and manage conditions such as obesity, diabetes, and cardiovascular disease. By addressing individual dietary responses, genome-based nutrition moves beyond traditional one-size-fits-all guidelines toward precision-driven, preventive healthcare. As genomic tools become more accessible and cost-effective, this technology could improve the health of the population while advancing the personalization of dietary recommendations in clinical and public health contexts.

This Special Issue focuses on the latest advancements, applications, and challenges in genome-based personalized nutrition, highlighting its role in precision healthcare and public health. We invite researchers to share their findings, methodologies, and perspectives to enhance our understanding and implementation of interventions in this field.

Prof. Dr. George Dedoussis
Guest Editor

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Keywords

genetics
nutrigenetics
personalized nutrition
artificial intelligence (AI)
machine learning (ML)
non-communicable diseases (NCDs)
obesity
metabolic dysfunction-associated steatotic liver disease (MASLD)

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Published Papers (4 papers)

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Research

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19 pages, 538 KB

Open AccessArticle

Folate Status Shaped by Taste Receptor Genetics and Sociobehavioral Modulation: Evidence from a Hungarian Cohort

by Peter Piko, Judit Dioszegi, Nora Kovacs and Roza Adany

Nutrients 2026, 18(4), 562; https://doi.org/10.3390/nu18040562 - 8 Feb 2026

Viewed by 609

Abstract

Background: Folate is essential for one-carbon metabolism, yet deficiency remains common in non-fortified populations. Bitter-taste-receptor genetics may influence vegetable intake and thus folate status, but the cumulative impact of sensory genetics, diet, and sociodemographic factors is unclear. This study aimed to investigate how taste-related genetic variants, aggregated into a polygenic score (PGS), together with dietary behavior and sociodemographic factors, modulate serum folate levels in a Hungarian adult population, including Roma ethnic minority participants. Methods: In a cross-sectional sample of 626 adults (312 from the Hungarian general population and 314 from the Roma ethnic minority), serum folate was quantified by chemiluminescent immunoassay, and eight taste-related single-nucleotide polymorphisms (SNPs) were genotyped. A four-SNP PGS (TAS2R19 rs10772420, OR10G4 rs1527483, TRPV1 rs8065080, and CD36 rs1761667) was optimized via the stepwise method (ΔR² criterion, FDR q < 0.05). Multivariable linear regression was used to assess associations with continuous folate, and logistic models were used to evaluate deficiency risk (≤13 µmol/L; area under the curve, AUC). Interaction terms were tested for effect modification by education and vegetable intake, and mediation pathways were examined by structural equation modeling with 1000 bootstrap replications. Results: TAS2R19 rs10772420 was found to be the strongest predictor of serum folate level. This effect remained significant even after adjusting for vegetable intake (β = 1.12 nmol/L; p = 0.003), suggesting a persistent genetic association independent of vegetable intake. The taste-related PGS exhibited a significant dose–response relationship with folate levels (p < 0.001) but had only modest discriminatory power for deficiency (AUC = 0.569). Higher educational attainment amplified the associations between the PGS and folate levels (p for interaction < 0.05), whereas vegetable intake did not mediate genetic effects. The associations were consistent across Hungarian general and Roma population subgroups. Conclusions: Bitter-taste-receptor genetics are associated with serum folate levels in a pattern not substantially mediated by self-reported vegetable intake, and this influence is further modified by education. These findings support the development of genome-informed, culturally tailored nutrition strategies for non-fortified populations. Full article

(This article belongs to the Special Issue Current Insights into Genome-Based Personalized Nutrition Technology)

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11 pages, 475 KB

Open AccessArticle

Analysis of the Perception of Nutrigenetics in Conventional Nutritional Practice: A Survey-Based Study Applied to Dietitians from Mexico

by Diana Alejandra Vela-Vásquez, Ivan Delgado-Enciso, Janet Diaz-Martinez and Ana María Sifuentes-Rincón

Nutrients 2025, 17(17), 2776; https://doi.org/10.3390/nu17172776 - 27 Aug 2025

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Abstract

Background/Objectives: Nutrigenetics has emerged as a promising tool to advance personalized nutrition strategies. This study aimed to analyze the scope and perception of Mexican dietitians regarding nutritional genomics with an emphasis on nutrigenetics’ use in clinical practice. Methods: A survey was conducted online among dietitians in Mexico to assess their educational background, awareness of nutrigenetic testing, use in practice, and interest in further training through 33 questions. Results: One hundred and thirty participants from states across six Mexican regions completed the survey, and most of respondents had a bachelor’s degree. The analysis showed that while most respondents were familiar with the concepts of nutrigenomics and nutrigenetics, 92.3% did not incorporate genetic testing into their practice; the main barriers of their use were misinformation, limited access to reliable resources, and ethical concerns surrounding genetic testing. Although 86.2% expressed interest in learning about nutrigenetics, only 31.5% were willing to invest in further training. Social media and non-academic sources were important sources of information, raising concerns about their inaccurate content and highlighting their importance in completing the curricula. Patients’ demand for genetic testing is limited and directed by disease prevention interests. Conclusions: Nutrigenetics is currently an area with limited practical application among Mexican dietitians; however, it is perceived as a valuable tool for future daily practice. The gap between perception and application underscores the need to integrate nutrigenetics into undergraduate curricula and to provide accessible, evidence-based professional development; these are essential to promote the ethical and effective use of nutrigenetics and support the transition toward personalized nutrition. Full article

(This article belongs to the Special Issue Current Insights into Genome-Based Personalized Nutrition Technology)

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14 pages, 972 KB

Open AccessArticle

Assessing the Knowledge and Beliefs of Greek Dietitians and Nutritionists on Nutritional Genomics: A Survey-Based Study

by Ioanna Panagiota Kalafati, Theodora Alexandrou, Evangelia Mentsiou-Nikolaou, Michael Chourdakis and George V. Dedoussis

Nutrients 2025, 17(7), 1107; https://doi.org/10.3390/nu17071107 - 21 Mar 2025

Cited by 1 | Viewed by 1388

Abstract

Background/Objectives: The field of Nutritional Genomics represents a growing area of interest among dietitians and nutritionists. However, knowledge gaps persist globally, limiting the effective application of this science. This study aims to evaluate the demographic characteristics, knowledge levels, and perspectives of Greek dietitians and nutritionists regarding Nutritional Genomics. Methods: A survey was conducted among 155 Greek dietitians and nutritionists from diverse educational and professional backgrounds. A 25-item questionnaire was designed to assess knowledge in Nutritional Genomics, with reliability measured by Cronbach’s Alpha (α = 0.867). Statistical analyses, including chi-square tests and regression modeling, were employed to explore associations between knowledge scores [S (total), E (easy questions), and H (hard questions) scores] and demographic or professional factors. Participants’ views on the clinical utility and future implications of Nutritional Genomics were also assessed. Results: On average, participants replied correctly to 57.7% (±21.7%) of the questions, with significant differences observed based on education level, employment status, and prior interest in genetics. Women demonstrated higher S and E scores compared to men (p = 0.046 and p = 0.006, respectively), while younger participants (26–35 years) outperformed those over 45 years (p = 0.019). Despite moderate knowledge levels, 76.8% believed Nutritional Genomics could benefit their clients, and 77.4% expressed interest in specializing in this field. Conclusions: Greek dietitians and nutritionists exhibited moderate knowledge in Nutritional Genomics, similar to international findings. Education level, age, and prior exposure to genetics significantly influenced knowledge scores. These results underscore the need for the integration of Nutritional Genomics into dietetic curricula and continuing professional education. Full article

(This article belongs to the Special Issue Current Insights into Genome-Based Personalized Nutrition Technology)

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Review

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31 pages, 601 KB

Open AccessReview

Generative AI in Precision Nutrition: A Review of Current Developments and Future Directions

by Lubnaa Abdur Rahman, Vasileios Dedousis, Ioannis Papathanail, Rooholla Poursoleymani, Maria Kafyra, Ioanna Panagiota Kalafati and Stavroula Georgia Mougiakakou

Nutrients 2026, 18(6), 938; https://doi.org/10.3390/nu18060938 - 17 Mar 2026

Cited by 1 | Viewed by 1722

Abstract

Background: Precision nutrition (PN) aims to personalize dietary guidance by accounting for inter-individual variability across biological, metabolic, lifestyle, and environmental factors influencing nutritional needs and health outcomes. While traditional Artificial Intelligence (AI) has advanced nutritional research through systems like automated dietary assessment, these models often operate rigidly. Generative AI (GenAI) introduces the capacity for adaptive interventions for enhanced PN. However, the scope and maturity of its applications remain insufficiently characterized. Objective: This review examined original works applying GenAI in PN, focusing on application, methodology, and limitations. Methods: A systematic search was conducted in PubMed, ACM Digital Library, and Scopus. Inclusion criteria focused on original works deploying GenAI models in PN contexts. Included works were further formally assessed based on data used, validation, transparency, bias, and security and privacy. Results: 21 eligible studies were identified, all published after 2024. The literature indicated a surge in large language model-based systems for personalized dietary recommendations, followed by applications in data foundation building and food effect understanding. A recurrent limitation was questionable evaluation on synthetic data and hallucinations, necessitating a human-expert-in-the-loop, especially in high-stakes clinical settings. Additionally, only 4 of 21 reviewed studies incorporated biological content or biological inputs, and fewer approached biologically grounded PN within implemented personalization workflows using metabolic and/or genomic variables. Conclusions: Although GenAI research in PN is expanding rapidly, most applications remain personalized at a user-preference level rather than including biological determinants. The need for standardized reporting, stronger genome-informed modeling, and consistent human-in-the-loop validation protocols is further highlighted to advance towards holistic PN. Full article

(This article belongs to the Special Issue Current Insights into Genome-Based Personalized Nutrition Technology)

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