SynthesisNature communications2025
Discovery of obesity genes through cross-ancestry analysis.
Synthesis in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Discovery of obesity genes through cross-ancestry analysis.Nature communications · 2025Pooled it
- From GWAS Signals to Molecular Mechanisms: Explainable AI for Causal Gene Prioritization and Biomolecular Target Interpretation.Biomolecules · 2026Review
- Mini-Galaxy: Rethinking Complex Human Diseases Through the Lens of Systems Biology and Multilayered AI Network Perspectives.International journal of molecular sciences · 2026Review
- GPR75 in glutamatergic neurons regulates body weight.Cell reports · 2026Article
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2 authors.
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Abstract
Gene discoveries in obesity have largely relied on homogeneous populations, limiting their generalizability across ancestries. Here, we conduct a gene-based rare variant association study of BMI on 839,110 individuals from six ancestries across two population-scale biobanks. A cross-ancestry meta-analysis identifies 13 genes, including YLPM1, RIF1, GIGYF1, SLC5A3, and GRM7, that confer about three-fold risk for severe obesity, are expressed in the brain and adipose tissue, and are linked to obesity traits such as body-fat percentage. While YLPM1, MC4R, and SLTM show consistent effects, GRM7 and APBA1 show significant ancestral heterogeneity. Polygenic risk additively increases obesity penetrance, and phenome-wide studies reveal additional associations, including YLPM1 with altered mental status. These genes also influence cardiometabolic comorbidities, including GIGYF1 and SLTM towards type 2 diabetes with or without BMI as a mediator, and altered levels of plasma proteins, such as LECT2 and NCAN, which in turn affect BMI. Our findings provide insights into the genetic basis of obesity and its related comorbidities across ancestries and ascertainments.
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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.