Introduction: As High-density lipoprotein (HDL) is directly associated with cardiovascular disease, the factors affecting the levels of this fat can be effective in reducing heart diseases. In addition to biochemical and environmental factors, genetic interactions also affect HDL level. Since polymorphism effects can be time-dependent, study of genetic interactions on HDL over time is important. In this study, we proposed Transition Logic Regression to analyze interactions in binary longitudinal data and used it to investigate polymorphism interactions related to low HDL over time. Materials and Methods: Data of 329 subjects who participated in three phases of TLGS was analyzed using the proposed model. Results: Results showed that subjects with high triglyceride levels and increased waist circumference have an odds ratio of 2.29 (CI95%: 1.51, 3.48) of having low HDL. Also, being in phase 2 and being a carrier of the minor allele of ApoA1M1 or being homozygous for the common allele of ApoCIII, were associated with an increased odds of having low HDL (OR= 2.30, CI95%: 1.77, 2.99). The odds ratio for having low HDL in male subjects with high blood pressure or being homozygous for the minor allele of SRB1 is 0.38 (CI95%: 0.25,0.59). Conclusions: Considering the identification of gene interactions in genetic studies and their importance over time, Transition Logic Regression was introduced and used to find gene interactions influencing low HDL over time and the most important models for gene interactions were identified.