BACKGROUND: Steatotic liver disease is a major public health issue, with hepatic iron overload exacerbating fibrotic conditions. This study aimed to identify metabolites associated with hepatic fat and/or iron overload using targeted metabolomics in a population-based cohort. METHODS: We used the cross-sectional KORA-MRI study (N = 376 individuals). Hepatic fat and iron content were derived by magnetic resonance imaging, and serum metabolite concentrations were quantified through targeted metabolomics. Associations between 146 metabolites and 40 indicators with hepatic phenotypes were analyzed, adjusted for confounders, and corrected for multiple testing. Formal pathway analyses and mediation analyses including genetic data were conducted. Performance of metabolomics to diagnose steatosis or hepatic iron overload was evaluated using ROC curves, and compared to the fatty liver index (FLI). RESULTS: Overall, 50.8% of participants (mean age 56.4 years) had hepatic steatosis, and 43.6% iron overload. Twelve unique metabolites/indicators (amino acids, lysophosphatidylcholine, acyl-alkyl-phosphatidylcholine), and sums of branched chain and aromatic amino acids, and five lipids, and ratio of acyl-alkyl-phosphatidylcholines to diacyl-phosphatidylcholines were associated with hepatic fat content. 27 metabolites/indicators, including 25 lipids, were associated with hepatic iron content. Addition of these metabolites to the FLI improved diagnosis of steatosis and iron overload nominally. Glycerophospholipid metabolism, phenylalanine, tyrosine and tryptophan biosynthesis and glycerophospholipid metabolism were shared pathway between steatosis and iron overload. Alanine, isoleucine, glutamine and pimeloylcarnitine (C7-DC) mediated effects between genetic variants and hepatic phenotypes. CONCLUSION: Metabolites were associated with hepatic fat and iron content, shared common pathways, and improved diagnosis of steatosis and iron overload, highlighting the role of iron in hepatic disorders.