ArticleObesity (Silver Spring, Md.)2025
Uncovering covariance patterns across energy balance traits enables the discovery of new obesity-related genes.
Article in Obesity (Silver Spring, Md.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Hiding in plain sight: uncovering the genetic basis of complex phenotypes through low-risk groups.Genetics · 2026Article
- Article
- Regulatory Potential of piRNAs TargetingGenes · 2026Article
- Multifaceted roles of fibronectin type III domain containing 3B (FNDC3B) in cell biology and signaling.Frontiers in molecular biosciences · 2026Review
- Uncovering covariance patterns across energy balance traits enables the discovery of new obesity-related genes.Obesity (Silver Spring, Md.) · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
objectiveEffective solutions to obesity remain elusive, partly owing to its root in a positive energy balance (EB), which stems from the interplay of numerous traits spanning body size and composition, diet, physical activity, and metabolic profile. Nevertheless, EB-contributing traits are typically studied in isolation. We integrate numerous EB-related traits measured in the UK Biobank to uncover the underlying patterns of EB and associated genes in study participants.
methodsWe used sparse factor analysis to integrate traits and performed genome-wide association analyses on the integrated phenotypes to elucidate EB-related genes and metabolic pathways. We performed pleiotropy analyses on candidate single-nucleotide polymorphisms to uncover the genetic basis of EB.
resultsWe identified multiple genes and genomic regions associated with EB, including many that have previously not been directly associated with obesity measures (e.g., MIR5591, FNDC3B, ANAPC10, SULT1A1, AXIN1, SKIDA1, ERLIN1, DOCK7), which we validated using an independent subset of the UK Biobank dataset along with data from the Atherosclerosis Risk in Communities cohort. We found that the covariances in EB traits are primarily driven by genome-wide pleiotropic associations.
conclusionsWe offer new insight into EB patterns and the genetic basis of EB.
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