ArticleNature medicine2023
Multiomic signatures of body mass index identify heterogeneous health phenotypes and responses to a lifestyle intervention.
Article in Nature medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers.
What it found
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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.
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Who cites it
87 citing papers in PubMed, 133 citations in OpenAlex.
- Multi-omic modelling of body mass index response to a dietary weight loss intervention.Gut microbes · 2026Article
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- Senescent obesity signature in breast cancer: a paradigm of reverse cardio-oncology.European heart journal · 2026Review
- Gut microbiota-derived imidazole propionate promotes primary sclerosing cholangitis via p38 signalling.Nature metabolism · 2026Article
- Trends in Computational Metabolomics: A Perspective on Five Years of Software Development, Challenges, and Opportunities (2021-2025).Analytical chemistry · 2026Review
- Proteomic clocks combined with deep learning phenotypes track eye aging and diseases.NPJ digital medicine · 2026Article
- Association between body mass index and rheumatoid arthritis: Exploring a possible role for alkaline phosphatase.Medicine · 2026Article
- Blood-based obesity biomarkers and their relevance for disease risk.Nature reviews. Endocrinology · 2026Review
- Global trend and disparity in the burden of ischemic stroke attributable to high body-mass index from 1990 to 2021 and projection to 2050: a systematic analysis based on the Global Burden of Disease Study 2021.Dialogues in health · 2026Article
- Defining Obesity Under the Lancet Commission Criteria: Metabolic Syndrome-Anchored Body Fat Percentage Thresholds in Korean Adults.Diabetes, obesity & metabolism · 2026Article
- Associations of 6600 SomaScan proteins with demographic, lifestyle, environmental and health characteristics in Chinese adults.Scientific reports · 2026Article
- Lipidomic analyses of large cohort studies define the role of lipid metabolism in bridging diet and cardio-metabolic health.Nature communications · 2026Article
- Metabolomic signatures of extreme old age: findings from the New England Centenarian Study.GeroScience · 2026Article
- Integration of multiomic and multi-phenotypic data identifies biological pathways associated with physical fitness.Communications biology · 2026Article
- Multimodal (Bio)Markers and Risk of Obesity - A Comprehensive Scoping Review.Advances in nutrition (Bethesda, Md.) · 2026Article
- Using Machine Learning to Identify Factors Affecting Antibody Production and Adverse Reactions After COVID-19 Vaccination.Vaccines · 2026Article
- Premature aging in serious mental illness.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Review
- GMrepo v3: a curated human gut microbiome database with expanded disease coverage and enhanced cross-dataset biomarker analysis.Nucleic acids research · 2026Article
- Article
27 more citing papers are in PubMed but not listed here.
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
Abstract
Multiomic profiling can reveal population heterogeneity for both health and disease states. Obesity drives a myriad of metabolic perturbations and is a risk factor for multiple chronic diseases. Here we report an atlas of cross-sectional and longitudinal changes in 1,111 blood analytes associated with variation in body mass index (BMI), as well as multiomic associations with host polygenic risk scores and gut microbiome composition, from a cohort of 1,277 individuals enrolled in a wellness program (Arivale). Machine learning model predictions of BMI from blood multiomics captured heterogeneous phenotypic states of host metabolism and gut microbiome composition better than BMI, which was also validated in an external cohort (TwinsUK). Moreover, longitudinal analyses identified variable BMI trajectories for different omics measures in response to a healthy lifestyle intervention; metabolomics-inferred BMI decreased to a greater extent than actual BMI, whereas proteomics-inferred BMI exhibited greater resistance to change. Our analyses further identified blood analyte-analyte associations that were modified by metabolomics-inferred BMI and partially reversed in individuals with metabolic obesity during the intervention. Taken together, our findings provide a blood atlas of the molecular perturbations associated with changes in obesity status, serving as a resource to quantify metabolic health for predictive and preventive medicine.
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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.