ArticleHGG advances2026
Pathway-specific polygenic scores substantially increase the discovery of gene-adiposity interactions impacting liver biomarkers.
Article in HGG advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Polygenic risk scores in human genetics for study design discovery and translation.Human genetics · 2026Review
- Interaction Between Genetic Risk and Parental Feeding Practices in the Prediction of Overweight Across Adolescence.Obesity (Silver Spring, Md.) · 2026Article
- Methods for modeling gene-environment interplay using polygenic risk scores.Statistical applications in genetics and molecular biology · 2026Review
Corrections and comments
- Update of
Authors and funding
4 authors.
Funding
Abstract
Polygenic scores (PGSs) are appealing for detecting gene-environment interactions due to the aggregation of genetic effects and reduced multiple testing burden compared to single-variant genome-wide interaction studies (GWISs). However, standard PGSs reflect many different biological mechanisms, limiting interpretation and potentially diluting pathway-specific interaction signals. Previous work has uncovered a significant genome-wide PGS×Adiposity signal impacting liver function, but there is an opportunity for additional and more interpretable discoveries. Here, we leveraged pathway-specific polygenic scores (pPGSs) to discover mechanism-specific gene-adiposity interactions. We tested for body mass index (BMI) interactions impacting three liver-related biomarkers (ALT, AST, and GGT) using (1) a standard, genome-wide PGS, (2) an array of pPGSs containing variant subsets derived from KEGG pathways, and (3) a GWIS. For ALT, we identified 49 significant pPGS×BMI interactions at a Bonferroni corrected p < 2.7 × 10
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.