Fig. 6: Multi-omics integration of (perfluoroheptanoic acid) PFHpA, proteomics, and metabolomics to identify high-risk clusters for metabolic dysfunction-associated steatotic liver disease (MASLD) (n = 131).

Using LUCID (Latent Unknown Clustering Integrating multi-omics Data) framework, we identified a distinct multi-omics risk profile associated with increased odds of MASLD. The profile links elevated PFHpA plasma concentration with increased plasma protein expression and decreased plasma metabolite expression. a Associations between predicted individual profile scores (PIPS) from unsupervised LUCID models and MASLD status (yes/no). The model incorporates both omics layers (proteins and metabolites) as well as PFHpA concentration and is adjusted for the following variables: age (continuous; years), sex (binary; male or female), race (binary; white or other), parental income (categorical; <25,000 United States Dollars (USD) per year, 25,000–74,999 USD per year, ≥75,000 USD per year), and study site (categorical; Baylor College of Medicine [BCM], Cincinnati Children’s Hospital [CIN], Nationwide Children’s Hospital [NCH], University of Alabama at Birmingham [UAB]). PFHpA is log2 transformed and interpretated as per doubling of exposure. b Classification of individuals into high- and low-risk MASLD profiles based on protein, metabolite, and PFHpA exposure. Abbreviations: PFHpA perfluoroheptanoic acid, MASLD metabolic dysfunction-associated steatotic liver disease, LUCID Latent Unknown Clustering Integrating multi-omics Data, PIPS predicted individual profile scores, n number of participants, HYAL1 hyaluronidase-1, F7 coagulation factor VII, CA5A carbonic anhydrase 5A, C2 complement component 2, ADH4 alcohol dehydrogenase 4, ACY1 aminoacylase-1.