Preeclampsia is a serious pregnancy complication with limited treatment. Etiology is hypothesized to originate during placentation, and may have both maternal and fetal contributions. There is a well-established enigmatic inverse relationship between maternal smoking and preeclampsia. A plausible biological explanation for this relationship is through response to cigarette smoke components, via vasodilation or activation of smoking detoxification pathways. Examining genes in these pathways and their modification by smoking, while incorporating maternal and child genetic contributions, could provide support for a genetic or related biological mechanism. We conducted a nested case-control study within the Norwegian Mother and Child Birth Cohort of 1,545 case-pairs and 995 control-pairs from 2,540 validated dyads (2,011 complete pairs, 529 missing mother or child genotype). For aim 1, we selected 1,518 single nucleotide polymorphisms (SNPs) in nitric oxide and carbon monoxide signaling pathways. For aim 2, we analyzed these and 397 additional SNPs in smoking detoxification pathways for their modification by maternal smoking during placentation. We used log-linear Poisson regression models and likelihood ratio tests to assess maternal and child effects and included a SNP by smoking interaction term to assess maternal and child genotype-smoking interactions. The child variant, rs12547243 in adenylate cyclase 8 (ADCY8), was associated with an increased risk (RR=1.42 [95% CI: 1.20, 1.69] for AG vs GG, RR=2.14 [1.47, 3.11] for AA vs GG, Q=0.03). We also found suggestive associations of SNPs in PDE1C for preeclampsia sub-phenotypes. We found limited evidence for multiplicative SNP by smoking interaction after correction for multiple comparisons. This study uses a novel approach to disentangle maternal and child genotypic effects of smoking-related genes on preeclampsia. Our findings do not provide strong support that the inverse smoking-preeclampsia relationship is due to a genetic effect in these pathways, although our power was limited due to the low prevalence of smoking in this population. Dyad methods and gene-environment interaction analysis may be useful for the study of pregnancy outcomes, particularly preeclampsia. Larger populations, such as multi-cohort consortia combined with these evolving methods may be necessary to dissect this enigmatic association.