ReviewHuman molecular genetics2015
Genetics of human metabolism: an update.
Review in Human molecular genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 3 of them syntheses that pooled it.
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.
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
79 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Multiomic integration analysis identifies atherogenic metabolites mediating between novel immune genes and cardiovascular risk.Genome medicine · 2024Pooled it
- Pooled it
- An atlas of genome-wide gene expression and metabolite associations and possible mediation effects towards body mass index.Journal of molecular medicine (Berlin, Germany) · 2023Pooled it
- Metabolic GWAS of elite athletes reveals novel genetically-influenced metabolites associated with athletic performance.Scientific reports · 2019Trial
- Association of three different dietary patterns with the metabolomic profiles of children: the BiomarKid project.European journal of nutrition · 2026Article
- HistoGWAS: an AI-enabled framework for automated genetic analysis of tissue phenotypes in histology cohorts.Genome biology · 2026Article
- Genetic atlas of plasma metabolome across 40 human common diseases: mapping causal metabolites to disease risk.Genome medicine · 2025Article
- Recent advances in omics and the integration of multi-omics in osteoarthritis research.Arthritis research & therapy · 2025Review
- Merging metabolomics and genomics provides a catalog of genetic factors that influence molecular phenotypes in pigs linking relevant metabolic pathways.Genetics, selection, evolution : GSE · 2025Article
- Genetic mapping of serum metabolome to chronic diseases among Han Chinese.Cell genomics · 2025Article
- Machine learning and multi-omics in precision medicine for ME/CFS.Journal of translational medicine · 2025Review
- EQTL analyses are a formidable tool to define the immunogenetic mechanisms underpinning Spondyloarthropathies.Frontiers in immunology · 2025Article
- Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens.Human genomics · 2024Review
- Two-sample Mendelian randomization analysis reveals causal relationships between blood lipids and venous thromboembolism.Haematologica · 2024Article
- Integrated Assays of Genome-Wide Association Study, Multi-Omics Co-Localization, and Machine Learning Associated Calcium Signaling Genes with Oilseed Rape Resistance toInternational journal of molecular sciences · 2024Article
- Genetic associations with ratios between protein levels detect new pQTLs and reveal protein-protein interactions.Cell genomics · 2024Article
- Article
- Current status of serum metabolites biomarkers for polyps and colorectal cancer: a systematic review.Gastroenterology report · 2024Review
- Systems genetics approaches for understanding complex traits with relevance for human disease.eLife · 2023Review
- Article
19 more citing papers are in PubMed but not listed here.
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
No grant is acknowledged in the PubMed record.
Abstract
Genome-wide association studies with metabolomics (mGWAS) identify genetically influenced metabotypes (GIMs), their ensemble defining the heritable part of every human's metabolic individuality. Knowledge of genetic variation in metabolism has many applications of biomedical and pharmaceutical interests, including the functional understanding of genetic associations with clinical end points, design of strategies to correct dysregulations in metabolic disorders and the identification of genetic effect modifiers of metabolic disease biomarkers. Furthermore, it has been shown that GIMs provide testable hypotheses for functional genomics and metabolomics and for the identification of novel gene functions and metabolite identities. mGWAS with growing sample sizes and increasingly complex metabolic trait panels are being conducted, allowing for more comprehensive and systems-based downstream analyses. The generated large datasets of genetic associations can now be mined by the biomedical research community and provide valuable resources for hypothesis-driven studies. In this review, we provide a brief summary of the key aspects of mGWAS, followed by an update of recently published mGWAS. We then discuss new approaches of integrating and exploring mGWAS results and finish by presenting selected applications of GIMs in recent studies.
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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.