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Published on: November 20, 2015
Maternal effects for preterm birth: a genetic epidemiologic study of 630,000 families
Anna C Svensson1, Sven Sandin, Sven Cnattingius
1Division of Public Health Epidemiology, Department of Public Health Sciences, Karolinska Institutet, Norrbacka, Fifth Floor, SE-171 76 Stockholm, Sweden. anna.svensson@ki.se
This study was undertaken to disentangle the maternal genetic from the fetal genetic effects for preterm birth and to study the possibility of these effects being explained by known risk factors. By cross-linking of the population-based Swedish Multigeneration and Medical Birth registers, 989,027 births between 1992 and 2004 were identified. Alternating logistic regression was applied to model the familial clustering with pairwise odds ratios (PORs), and covariates were included to evaluate if the familial aggregation was explained by exposure to shared risk factors. Generalized linear mixed models were used to estimate the contribution of genetic and environmental effects. Sisters of women who had a preterm delivery had themselves an increased odds of having a preterm delivery (POR = 1.8, 95% confidence interval: 1.5, 2.1), while there was no corresponding increase in odds in families joined by brothers (POR = 1.1, 95% confidence interval: 0.9, 1.4). Twenty-five percent of the variation in preterm birth was explained by maternal genetic factors, whereas fetal genetic factors only marginally influenced the variation in liability. The increased odds ratio between offspring of sisters was independent of maternal risk factors for preterm birth, suggesting that the relative importance of maternal effects is not explained by these well-known risk factors.
This study was undertaken to disentangle the maternal genetic from the fetal genetic effects for preterm birth and to study the possibility of these effects being explained by known risk factors. By cross-linking of the population-based Swedish Multigeneration and Medical Birth registers, 989,027 births between 1992 and 2004 were identified. Alternating logistic regression was applied to model the familial clustering with pairwise odds ratios (PORs), and covariates were included to evaluate if the familial aggregation was explained by exposure to shared risk factors. Generalized linear mixed models were used to estimate the contribution of genetic and environmental effects. Sisters of women who had a preterm delivery had themselves an increased odds of having a preterm delivery (POR = 1.8, 95% confidence interval: 1.5, 2.1), while there was no corresponding increase in odds in families joined by brothers (POR = 1.1, 95% confidence interval: 0.9, 1.4). Twenty-five percent of the variation in preterm birth was explained by maternal genetic factors, whereas fetal genetic factors only marginally influenced the variation in liability. The increased odds ratio between offspring of sisters was independent of maternal risk factors for preterm birth, suggesting that the relative importance of maternal effects is not explained by these well-known risk factors.
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