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We thank Prof. Plewis and Prof. Paumgartten for their interestin our article and their comments related to the applicationof statistical analyses accounting for litter effects in bothfirst- and second-generation rats (Plewis 2019; Paumgartten2019). To address this issue, we have re-analyzed our datausing linear mixed models (LMMs), which allow accountingfor the lack of independence of observations from the samelitter (Lazic and Essioux 2013).Two sets of LMMs were constructed using the statisticalsoftware R version 3.6.1 (The R foundation for statisticalcomputing, https ://www.r-proje ct.org/), package lme4, functionslmer and glmer (Bates et al. 2015). In the first set, theresponse variable was the ?pre-implantation loss rate of F1dams?, the fixed effect was ?treatment? (three-level categoricalvariable), and the random intercept included to adjust forthe litter effect was the ?ID of the F0 dams?. In the secondset of LMMs, the response variables were the feto-placentalparameters of F2 offspring (fetal length, fetal weight,placental weight, and placental index), the fixed effect was?treatment?, and the random intercept included to adjust forthe litter effect was the nested random effect ?F1 dam ID/F2 dam ID?. In addition, variables deemed a priori to bepotential confounders were individually included in bothsets of models to adjust for their influence on the relationshipof interest (McNamee 2005), and were removed fromthe model if they did not contribute to the model?s goodnessof fit (GOF). The potential confounders assessed were:food consumption of F0 dams during treatment, weight ofF0 dams at the beginning of pregnancy, number of F1 pupsper litter, F1 litter weight at birth, F1 female pup weight atbirth, age of F1 females at the time of becoming pregnant,number of F2 pups per litter.The results of our statistical re-analysis are shown inTables 1 and 2. In agreement with our previous reports(Milesi et al. 2018), we found a significant increase in therate of pre-implantation loss in the GBH-HD group comparedto controls. None of the potential confounders assessedimproved the GOF of the LMMs (Table 1).After re-analyzing our data and considering all the commentsraised by Profs. Plewis and Paumgartten, we reaffirmthe conclusions of our work (Milesi et al. 2018), in which wefound that perinatal exposure to a GBH formulation impairsreproductive performance in F1 females rats and inducesfetal growth retardation and structural congenital anomaliesin their progeny (F2 generation). Fil: Milesi, Maria Mercedes. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Salud y Ambiente del Litoral. Universidad Nacional del Litoral. Instituto de Salud y Ambiente del Litoral; Argentina Fil: Lorenz, Virginia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Salud y Ambiente del Litoral. Universidad Nacional del Litoral. Instituto de Salud y Ambiente del Litoral; Argentina Fil: Beldomenico, Pablo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; Argentina Fil: Vaira, Stella Maris. Liseb, Fbcb, Unl; Argentina Fil: Varayoud, Jorgelina Guadalupe. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Salud y Ambiente del Litoral. Universidad Nacional del Litoral. Instituto de Salud y Ambiente del Litoral; Argentina Fil: Luque, Enrique Hugo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Salud y Ambiente del Litoral. Universidad Nacional del Litoral. Instituto de Salud y Ambiente del Litoral; Argentina |
