ArticleNature medicine2025
Multimodal AI correlates of glucose spikes in people with normal glucose regulation, pre-diabetes and type 2 diabetes.
Article in Nature medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Trends in AI-based diagnosis and intervention of metabolic diseases: a bibliometric analysis of the literature from 2000 to 2024.Frontiers in medicine · 2025Pooled it
- Artificial intelligence in biomarker discovery for diseases: diagnostic and therapeutic prospects.Signal transduction and targeted therapy · 2026Review
- Advances in erythritol production through synthetic biology and systems metabolic engineering.Archives of microbiology · 2026Review
- Artificial intelligence virtual bone organoids (AIVBOs).Journal of orthopaedic translation · 2026Review
- Human-Centered Innovation: Precision Nutrition and the Future of Food.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Postprandial Glucose Spikes in Free-Living Adults With Normoglycaemia Are Associated With Modifiable Dietary and Temporal Factors: A Real-World CGM Study.Diabetes, obesity & metabolism · 2026Article
- The Programmable Microbiome: Integrative AI and Multi-Omics Frameworks for Precision T2DM Management.Biology · 2026Review
- An atlas of exposome-phenome associations in health and disease risk.Nature medicine · 2026Article
- Metabolic advances in 2025: from clinical breakthroughs to molecular reprogramming.Metabolism open · 2026Article
- Artificial intelligence in prediabetes care: applications in screening, risk prediction, and lifestyle intervention.Frontiers in endocrinology · 2026Review
- Exercise and Diet Reshape Athletes' Gut Microbiota: Countering Health Challenges in Athletes.Life (Basel, Switzerland) · 2025Review
- Bridging ancient wisdom and modern technology: an AI and multi-omics framework for three causes tailored treatment in personalized medicine.Frontiers in molecular biosciences · 2025Review
- Federated multimodal AI for precision-equitable diabetes care.Frontiers in digital health · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
Type 2 diabetes (T2D) is a multifaceted disease associated with several factors, including diet, genetics, exercise, sleep and gut microbiome. Current diagnostic and monitoring methods based on episodic assays like glycated hemoglobin (HbA1c) fail to capture its full complexity. Here, in a prospective cohort of 1,137 participants in the United States, we analyzed multimodal data from 347 deeply phenotyped individuals (174 normoglycemic, 79 prediabetic and 94 T2D). We found significant differences in the distribution of glucose spike metrics among different diabetes states, with longer expected time for spike resolution and higher values of nocturnal hypoglycemia in T2D. We identified significant correlations between mean glucose level and gut microbiome diversity, and between expected time for spike resolution and resting heart rate. Our multimodal glycemic risk profiles, validated in 1,955 normoglycemic and 114 prediabetic individuals from an independent cohort, improved risk stratification by highlighting substantial variability among individuals with the same value of HbA1c. Such a multimodal approach provides a detailed phenotype that can potentially improve T2D prevention, diagnosis and treatment, and is more informative than HbA1c.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.