Zika Virus and Birth Defects--Reviewing the Evidence for Causality.
By S. Rasmussen, D. Jamieson, M. Honein, L. Petersen. New England Journal of Medicine, 2016
1,749 citations recorded by the source corpus.
Summary The Zika virus has spread rapidly in the Americas since its first identification in Brazil in early 2015. Prenatal Zika virus infection has been linked to adverse pregnancy and birth outcomes, most notably microcephaly and other serious brain anomalies. To determine whether Zika virus infection during pregnancy causes these adverse outcomes, we evaluated available data using criteria that have been proposed for the assessment of potential teratogens. On the basis of this review, we conclude that a causal relationship exists between prenatal Zika virus infection and microcephaly and other serious brain anomalies. Evidence that was used to support this causal relationship included Zika virus infection at times during prenatal development that were consistent with the defects observed; a specific, rare phenotype involving microcephaly and associated brain anomalies in fetuses or infants with presumed or confirmed congenital Zika virus infection; and data that strongly support biologic plausibility, including the identification of Zika virus in the brain tissue of affected fetuses and infants. Given the recognition of this causal relationship, we need to intensify our efforts toward the prevention of adverse outcomes caused by congenital Zika virus infection. However, many questions that are critical to our prevention efforts remain, including the spectrum of defects caused by prenatal Zika virus infection, the degree of relative and absolute risks of adverse outcomes among fetuses whose mothers were infected at different times during pregnancy, and factors that might affect a woman’s risk of adverse pregnancy or birth outcomes. Addressing these questions will improve our ability to reduce the burden of the effects of Zika virus infection during pregnancy.
Subfields: Obstetrics and Gynecology, Pediatrics, Perinatology and Child Health, Public Health, Environmental and Occupational Health
View Paper: https://www.semanticscholar.org/paper/e4cd8232e83cd42360c97d8189e92ea92002d1d6
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Citations in the corpus
- Brain organoids: advances, applications and challenges (2019, background): “Moreover, such infected cortical organoids display a series of characteristics identified in congenital Zika syndrome, including thinning of the neuronal layer, disruption of apical surface adherens junctions and dilation of the ventricular lumen, offering direct evidence for the causal relationship”
- Coronavirus Disease 2019 (COVID-19) and pregnancy: what obstetricians need to know (2020, background): “merging infections have been E shown to have an important impact on pregnant women and their fetuses,(1) with the increased risk of complications in pregnant women with the 2009 pandemicH1N1 influenza virus(2) and the severe fetal effects of Zika virus as recent examples.(3,4) The emergence of a cor”
- Zika virus targets human STAT2 to inhibit type I interferon signaling (2016, background): “The ZIKV epidemic is associated with severe fetal abnormalities including stillbirth and microcephaly (Rasmussen et al., 2016), or with the Guillain-Barré syndrome in infected adults (Cao-Lormeau et al.”
- Congenital Zika Syndrome: Characterizing the Pattern of Anomalies for Pediatric Healthcare Providers (2017, background): “Although many of the components of this syndrome, such as cognitive, sensory, and motor disabilities, are shared by other congenital infections, there are 5 features that are rarely seen with other congenital infections or are unique to congenital Zika virus infection: (1) severe microcephaly with p”
- Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models (2017, background): “The growing burden of these diseases (including links between Zika infection and both microcephaly and Guillain-Barré syndrome [3]) and potential for spread into new areas creates an urgent need for predictive models that can inform risk assessment and guide interventions such as mosquito control, c”