Browsing by Author "Tromp, Gerard"

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    A genetic association study of maternal and fetal candidate genes that predispose to preterm prelabor rupture of membranes (PROM)
    (MOSBY-ELSEVIER, 2010) Romero, Roberto; Friel, Lara A.; Edwards, Digna R. Velez; Kusanovic, Juan Pedro; Hassan, Sonia S.; Mazaki Tovi, Shali; Vaisbuch, Edi; Kim, Chong Jai; Erez, Offer; Chaiworapongsa, Tinnakorn; Pearce, Brad D.; Bartlett, Jacquelaine; Salisbury, Benjamin A.; Anant, Madan Kumar; Vovis, Gerald F.; Lee, Min Seob; Gomez, Ricardo; Behnke, Ernesto; Oyarzun, Enrique; Tromp, Gerard; Williams, Scott M.; Menon, Ramkumar
    OBJECTIVE: We sought to determine whether maternal/fetal single-nucleotide polymorphisms (SNPs) in candidate genes are associated with preterm prelabor rupture of membranes (pPROM).
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    Analytical approaches to detect maternal/fetal genotype incompatibilities that increase risk of pre-eclampsia
    (2008) Parimi, Neeta; Tromp, Gerard; Kuivaniemi, Helena; Nien, Jyh K.; Gomez, Ricardo; Romero, Roberto; Goddard, Katrina A.
    Abstract Background In utero interactions between incompatible maternal and fetal genotypes are a potential mechanism for the onset or progression of pregnancy related diseases such as pre-eclampsia (PE). However, the optimal analytical approach and study design for evaluating incompatible maternal/offspring genotype combinations is unclear. Methods Using simulation, we estimated the type I error and power of incompatible maternal/offspring genotype models for two analytical approaches: logistic regression used with case-control mother/offspring pairs and the log-linear regression used with case-parent triads. We evaluated a real dataset consisting of maternal/offspring pairs with and without PE for incompatibility effects using the optimal analysis based on the results of the simulation study. Results We identified a single coding scheme for the incompatibility effect that was equally or more powerful than all of the alternative analysis models evaluated, regardless of the true underlying model for the incompatibility effect. In addition, the log-linear regression was more powerful than the logistic regression when the heritability was low, and more robust to adjustment for maternal or fetal effects. For the PE data, this analysis revealed three genes, lymphotoxin alpha (LTA), von Willebrand factor (VWF), and alpha 2 chain of type IV collagen (COL4A2) with possible incompatibility effects. Conclusion The incompatibility model should be evaluated for complications of pregnancy, such as PE, where the genotypes of two individuals may contribute to the presence of disease.Abstract Background In utero interactions between incompatible maternal and fetal genotypes are a potential mechanism for the onset or progression of pregnancy related diseases such as pre-eclampsia (PE). However, the optimal analytical approach and study design for evaluating incompatible maternal/offspring genotype combinations is unclear. Methods Using simulation, we estimated the type I error and power of incompatible maternal/offspring genotype models for two analytical approaches: logistic regression used with case-control mother/offspring pairs and the log-linear regression used with case-parent triads. We evaluated a real dataset consisting of maternal/offspring pairs with and without PE for incompatibility effects using the optimal analysis based on the results of the simulation study. Results We identified a single coding scheme for the incompatibility effect that was equally or more powerful than all of the alternative analysis models evaluated, regardless of the true underlying model for the incompatibility effect. In addition, the log-linear regression was more powerful than the logistic regression when the heritability was low, and more robust to adjustment for maternal or fetal effects. For the PE data, this analysis revealed three genes, lymphotoxin alpha (LTA), von Willebrand factor (VWF), and alpha 2 chain of type IV collagen (COL4A2) with possible incompatibility effects. Conclusion The incompatibility model should be evaluated for complications of pregnancy, such as PE, where the genotypes of two individuals may contribute to the presence of disease.
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    Polymorphisms in maternal and fetal genes encoding for proteins involved in extracellular matrix metabolism alter the risk for small-for-gestational-age
    (TAYLOR & FRANCIS LTD, 2011) Edwards, Digna R. Velez; Romero, Roberto; Kusanovic, Juan Pedro; Hassan, Sonia S.; Mazaki Tovi, Shali; Vaisbuch, Edi; Kim, Chong Jai; Erez, Offer; Chaiworapongsa, Tinnakorn; Pearce, Brad D.; Bartlett, Jacquelaine; Friel, Lara A.; Salisbury, Benjamin A.; Anant, Madan Kumar; Vovis, Gerald F.; Lee, Min Seob; Gomez, Ricardo; Behnke, Ernesto; Oyarzun, Enrique; Tromp, Gerard; Menon, Ramkumar; Williams, Scott M.
    Objective. To examine the association between maternal and fetal genetic variants and small-for-gestational-age (SGA).