Mercury (Hg) exposure in various forms remains a persistent public health concern in many parts of the world. In previous studies, we have described a biomarker of mercury exposure characterized by increased urinary concentrations of specific porphyrins, pentacarboxyporphyrin (5-CP) and coproporphyrin (4-CP), and the atypical keto-isocoproporphyrin (KICP), based on selective interference with the fifth (uroporphyrinogen decarboxylase, UROD) and sixth (coproporphyrinogen oxidase, CPOX) enzymes of the heme biosynthetic pathway. Whereas this response occurs in a predictable manner among approximately 85% of subjects with Hg exposure, an atypical porphyrinogenic response (APR) has been observed in approximately 15% of Hg-exposed persons, in which the three porphyrins that are affected by Hg, i.e., 5-CP, 4-CP and, KICP, are excreted in substantial excess of that predicted on the basis of Hg exposure alone. This APR has been attributed to a specific polymorphism in exon 4 of the CPOX gene (CPOX4). In the present study, we sought to further confirm the hypothesis that the observed changes in porphyrin excretion patterns might serve as a biomarker of Hg exposure and potential toxicity by statistically modeling the cascading effects on porphyrin concentrations within the heme biosynthetic pathway of Hg exposure and CPOX4 polymorphism in a human population with long-term occupational exposure to elemental mercury. Our results are highly consistent with this hypothesis. After controlling for precursor porphyrin concentrations, we demonstrated that 5-CP and 4-CP are independently associated with Hg concentration, while KICP is associated only with the CPOX4. An unpredicted association of Hg with heptacarboxyporphyrin (7-CP) may indicate a previously unidentified point of mercury inhibition of UROD. These findings lend further support to the proposed utility of urinary porphyrin changes as a biomarker of exposure and potential toxicity in subjects with mercury exposure. Additionally, these findings demonstrate the successful application of a computational model for characterizing complex metabolic responses and interactions associated with both toxicant exposure and genetic variation in human subjects.