ReviewNutrients2025
Integrating Precision Medicine and Digital Health in Personalized Weight Management: The Central Role of Nutrition.
Review in Nutrients, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Precision medicine in low-income settings and small island developing states.Nature reviews. Endocrinology · 2026Review
- ABCG2 transporter: Structural and functional associations with gout (Review).International journal of molecular medicine · 2026Review
- Review
- Intervening at the microbial crossroads: targeting inflammation across the oral-gut-reproductive microbiome crosstalk in atherosclerosis.Antonie van Leeuwenhoek · 2026Review
- Translating dietary standards into healthy meals with few-ingredient substitutions.PLOS digital health · 2026Article
- Intersection of Precision Nutrition and Bladder Cancer: A Narrative State-of-the-Art Review of Potential Applications and Challenges.Journal of clinical medicine · 2026Review
- A multimodal, risk-stratified framework for AI-driven early risk prediction and personalised prevention in obesity.Frontiers in artificial intelligence · 2026Article
- Domain-informed weight forecasting: leveraging behavioral and physiological sequences from wearables.Frontiers in public health · 2026Article
- Towards precision medicine in Tourette syndrome: a perspective on AI-driven predictive modelling and personalised care.Frontiers in computational neuroscience · 2026Review
- Personalized Nutritional Assessment and Intervention for Athletes: A Network Physiology Approach.Nutrients · 2025Review
- Hidden Hunger in Pediatric Obesity: Redefining Malnutrition Through Macronutrient Quality and Micronutrient Deficiency.Nutrients · 2025Review
- Transforming mental health: the future of personalized psychobiotics in anxiety and depression therapy.Frontiers in neuroscience · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Obesity is a global health challenge marked by substantial inter-individual differences in responses to dietary and lifestyle interventions. Traditional weight loss strategies often overlook critical biological variations in genetics, metabolic profiles, and gut microbiota composition, contributing to poor adherence and variable outcomes. Our primary aim is to identify key biological and behavioral effectors relevant to precision medicine for weight control, with a particular focus on nutrition, while also discussing their current and potential integration into digital health platforms. Thus, this review aligns more closely with the identification of influential factors within precision medicine (e.g., genetic, metabolic, and microbiome factors) but also explores how these factors are currently integrated into digital health tools. We synthesize recent advances in nutrigenomics, nutritional metabolomics, and microbiome-informed nutrition, highlighting how tailored dietary strategies-such as high-protein, low-glycemic, polyphenol-enriched, and fiber-based diets-can be aligned with specific genetic variants (e.g., FTO and MC4R), metabolic phenotypes (e.g., insulin resistance), and gut microbiota profiles (e.g.,
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What Socratic holds
Registered trials
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 Socratic graph.