Genetic susceptibility for retinopathy of prematurity and its associated comorbidities.

BACKGROUND: Retinopathy of prematurity (ROP) is one of the leading cause of child blindness. Preterm newborns of very low gestational age (GA) and very low birth weight are at the greatest risk. Our objective was to evaluate the role of genetic variants associated with ROP risk and its comorbidities in an Argentinian sample of premature infants. METHODS: A sample of 437 preterm infants <33 weeks GA, born at a maternity hospital in Tucumán, Argentina, 2005-2010, was analyzed. Environmental factors, perinatal outcomes, and fourteen single nucleotide polymorphisms associated with ROP were evaluated, comparing ROP with non-ROP newborns. A lasso logistic regression was performed to select variables; then, a conditional logistic regression was used to identify ROP maternal and perinatal risk factors adjusting by maternal and gestational ages, respectively. RESULTS: ROP maternal risk factors were alcohol intake, periodontal infections, and severe stress. Respiratory distress, sepsis, and intracranial hemorrhage were the ROP perinatal risk factors. Markers rs186085 of EPAS1 and rs427832 of AGTR1 were significantly associated with ROP newborns. CONCLUSION: We identified three maternal and three perinatal risk factors associated with ROP. Genes EPAS1 and AGTR1, involved in angiogenesis and vascularization, were identified to be of risk for ROP. IMPACT: Genetic and environmental risk factors associated with ROP and its comorbidities are evaluated in a Latin American population. Genes EPAS1 and AGTR1, involved in angiogenesis and vascularization, were identified to be of risk for ROP. Three maternal and three perinatal risk factors associated with ROP were also identified. A matrix of significant relationships among genetic markers and comorbidities is presented. Reported data may help develop more effective preventive measures for ROP in the Latin American region.

Indirect Effects of Neighbourhood Socioeconomic Status on Preterm Birth Risk in an Argentine Population.

BACKGROUND: Preterm birth (PTB) is the main condition related to perinatal morbimortality worldwide. The aim of this study was to determine the indirect effects of neighbourhood socioeconomic status (NSES) on the risk of spontaneous PTB. METHODS: We carried out a retrospective case-control study including sociodemographic and obstetric data of multigravid women who gave birth at a maternity hospital in Tucumán, Argentina, between 2005 and 2010: 949 women without previous PTB nor pregnancy loss who delivered at term and 552 who had spontaneous PTB. NSES was estimated from the Unsatisfied Basic Needs index of census data. Variables selected through penalised regressions were used to create a data-driven Bayesian network; then, pathways were identified and mediation analyses performed. RESULTS: Maternal age less than 20 years mediated part of the protective effect of high NSES on spontaneous PTB [natural indirect effect (NIE) -0.0125, 95% confidence interval (CI) (-0.0208, -0.0041)] and on few prenatal visits (< 5) [NIE - 0.0095, 95% CI (-0.0166, -0.0025)]. These pathways showed greater sensitivity to unobserved confounders that affect the variables mediator-outcome in the same direction, and exposure-mediator in the opposite direction. They did not show sensitivity to observed potential confounders, nor to the parameterization used to define NSES. Meanwhile, urinary tract infections showed a trend in mediating the effect of low NSES on spontaneous PTB [NIE 0.0044, 95% CI (-0.0006, 0.0093), P 0.0834]. CONCLUSIONS: High NSES has protective indirect effects on spontaneous PTB risk, mainly associated with a lower frequency of teenage pregnancy.

Gene-environment interactions and preterm birth predictors: A Bayesian network approach.

Preterm birth (PTB) is the main condition related to perinatal morbimortality worldwide. The aim of this study was to identify gene-environment interactions associated with spontaneous PTB or its predictors. We carried out a retrospective case-control study including parental sociodemographic and obstetric data as well as newborn genetic variants of 69 preterm and 61 at term newborns born at a maternity hospital from Tucumán, Argentina, between 2005 and 2010. A data-driven Bayesian network including the main PTB predictors was created where we identified gene-environment interactions. We used logistic regressions to calculate the odds ratios and confidence intervals of the interactions. From the main PTB predictors (nine exposures and six genetic variants) we identified an interaction between low neighbourhood socioeconomic status and rs2074351 (PON1, genotype GG) variant that was associated with an increased risk of toxoplasmosis (odds ratio 12.51, confidence interval 95%: 1.71 - 91.36). The results of this exploratory study suggest that structural social disparities could influence the PTB risk by increasing the frequency of exposures that potentiate the risk associated with individual characteristics such as genetic traits. Future studies with larger sample sizes are necessary to confirm these findings.