Large-scale sequencing has characterized an enormous number of genetic variations (GVs), and the functional analysis of GVs is fundamental to understanding differences in disease susceptibility and therapeutic response among and within populations. Using a combination of a sequence-based predictor with known phosphorylation and protein–protein interaction information, we computationally detected 9606 potential phosSNPs (phosphorylation-related single nucleotide polymorphisms), including 720 known, disease-associated SNPs that dramatically modify the human phosSNP-associated kinase–substrate network. Further analyses demonstrated that the proteins in the network are heavily associated in various signaling and cancer pathways, while cancer genes and drug targets are significantly enriched. We re-constructed four population-specific kinase–substrate networks and found that several inherited disease or cancer genes, such as IRS1, RAF1, and EGFR, were differentially regulated by phosSNPs. Thus, phosSNPs may influence disease susceptibility and be involved in cancer development by reconfiguring phosphorylation networks in different populations. Moreover, by systematically characterizing potential phosphorylation-related cancer mutations (phosCMs) in 12 types of cancers, we observed that both types of GVs preferentially occur in the known cancer genes, while a considerable number of phosphorylated proteins, especially those over-representing cancer genes, contain both phosSNPs and phosCMs. Furthermore, it was observed that phosSNPs were significantly enriched in amplification genes identified from breast cancers and tyrosine kinase circuits of lung cancers. Taken together, these results should prove helpful for further elucidation of the functional impacts of disease-associated SNPs.