Elevated triglycerides (TG) or low high density lipoprotein cholesterol (HDL-C) levels are common cardiometabolic risk factors in children. From a systems genetics standpoint, Visualization of Statistical Epistasis Networks (ViSEN) is a nonparametric entropy-based method that can characterize the global structure of interacting genetic factors. We identified a novel set of connected genetic and cardiometabolic risk factors with strong and significant interaction effects on two important dyslipidemia phenotypes (low HDL-C and high TG) in children and adolescents. Study participants were recruited from five schools in Istanbul, Turkey (n=360; 170 boys, 190 girls). Participants with TG levels >= 75th and HDL-C levels <= 25th percentile were defined as 'high TG' and 'low HDL-C', respectively. We genotyped participants for six single nucleotide polymorphisms (SNPs) in five genes with known associations to lipid levels (rs328 in LPL, rs708272 in CETP, rs1800588 in LIPC, rs1800977 in ABCA1, rs1799941 and rs6257 in SHBG gene). ViSEN was used to identify associations with dyslipidemia phenotypes. There were 71 (50 males, 21 females) and 93 (60 males and 33 females) subjects with low HDL-C and high TG, respectively. Biological variables including age, gender, and BMI were significantly associated with both phenotypes (p<0.001). Importantly, a single SNP, rs708272, was associated with low HDL-C (IG=2.24%, p=0.026). Pairwise and higher order interaction analyses in the full dataset for low HDL-C and high TG revealed the largest effects in the models containing rs1800977, rs708272, age (IG=6.20%, p=0.046) and rs1800588, age, BMI (IG, 3.06%, p=0.022), respectively. In conclusion, the present study brings us a step closer to a systems genetic approach in understanding lipid phenotypes in children. Further efforts can integrate population and laboratory-based studies, hence accelerate the preventive medicine efforts.