Brandie D Taylor1, Gong Tang2, Roberta B Ness3, Jørn Olsen4, David M Hougaard5, Kristin Skogstrand5, James M Roberts6, Catherine L Haggerty7. 1. Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Epidemiology and Biostatistics, Texas A&M Health Science Center, College Station, TX, USA. Electronic address: Taylor@sph.tamhsc.edu. 2. Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA. 3. University of Texas School of Public Health, Houston, TX, USA. 4. Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark. 5. Danish Centre for Neonatal Screening, Department of Clinical Biochemistry, Immunology and Genetics, Statens Serum Institut, Copenhagen, Denmark. 6. Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Magee-Womens Research Institute, University of Pittsburgh Medical Center, Pittsburgh, PA, USA; Department of Obstetrics, Gynecology, and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, USA; University of Pittsburgh Clinical and Translational Research, Pittsburgh, PA, USA. 7. Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Magee-Womens Research Institute, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Abstract
OBJECTIVES: To determine if mid-pregnancy circulating immune biomarkers are associated with preeclampsia. STUDY DESIGN: Nested case-control study of 410 preeclamptic women and 297 normotensive controls with primiparous singleton pregnancies enrolled in the Danish National Birth Cohort. The mean gestational age in our cohort is 16 weeks (range 9-26). MAIN OUTCOME MEASURES: Preeclampsia was defined by blood pressure ⩾140/90 mmHg and proteinuria ⩾3 g/24 h. Serum immune biomarkers included interleukin (IL)-6, IL-6 receptor, IL-4, IL-4 receptor, IL-5, IL-12, IL-2, TNF-α, TNF-β, TNF-receptor, IL-1β, IL-1α, IL-8, IL-10, IFN-γ, IL-18, macrophage migration inhibitory factor, macrophage inflammatory protein, transforming growth factor-beta (TGF-β), and RANTES. Associations with preeclampsia, term preeclampsia and preterm preeclampsia were determined using two logistic regression models; (1) biomarkers were dichotomized by the limit of detection (LOD); (2) on the continuous scale, non-detectable values were imputed by LOD/2 and transformed (base 2). All models were adjusted for body mass index and smoking. RESULTS: IL1β was significantly associated with a decrease in the log odds of preeclampsia (p=0.0065), term preeclampsia (p=0.0230) and preterm preeclampsia (p=0.0068). Results were similar for IL4r and preeclampsia (p=0.0383). In the dichotomized models, detectable TNF-β was significantly associated with preeclampsia (ORadj 1.6, 95% CI 1.1-2.3) and term preeclampsia (OR 1.7, 95% CI 1.1-2.5) but not preterm preeclampsia. Detectable IL6 was significantly with term preeclampsia only (OR 1.5, 95% CI 1.1-2.2). CONCLUSION: Mid-pregnancy circulating IL1β, IL4r, IL6, and TNFβ were associated with preeclampsia. However, results were not consistent across statistical models. As the relationship is complex, future studies should explore cytokine clusters in preeclampsia risk.
OBJECTIVES: To determine if mid-pregnancy circulating immune biomarkers are associated with preeclampsia. STUDY DESIGN: Nested case-control study of 410 preeclamptic women and 297 normotensive controls with primiparous singleton pregnancies enrolled in the Danish National Birth Cohort. The mean gestational age in our cohort is 16 weeks (range 9-26). MAIN OUTCOME MEASURES: Preeclampsia was defined by blood pressure ⩾140/90 mmHg and proteinuria ⩾3 g/24 h. Serum immune biomarkers included interleukin (IL)-6, IL-6 receptor, IL-4, IL-4 receptor, IL-5, IL-12, IL-2, TNF-α, TNF-β, TNF-receptor, IL-1β, IL-1α, IL-8, IL-10, IFN-γ, IL-18, macrophage migration inhibitory factor, macrophage inflammatory protein, transforming growth factor-beta (TGF-β), and RANTES. Associations with preeclampsia, term preeclampsia and preterm preeclampsia were determined using two logistic regression models; (1) biomarkers were dichotomized by the limit of detection (LOD); (2) on the continuous scale, non-detectable values were imputed by LOD/2 and transformed (base 2). All models were adjusted for body mass index and smoking. RESULTS:IL1β was significantly associated with a decrease in the log odds of preeclampsia (p=0.0065), term preeclampsia (p=0.0230) and preterm preeclampsia (p=0.0068). Results were similar for IL4r and preeclampsia (p=0.0383). In the dichotomized models, detectable TNF-β was significantly associated with preeclampsia (ORadj 1.6, 95% CI 1.1-2.3) and term preeclampsia (OR 1.7, 95% CI 1.1-2.5) but not preterm preeclampsia. Detectable IL6 was significantly with term preeclampsia only (OR 1.5, 95% CI 1.1-2.2). CONCLUSION: Mid-pregnancy circulating IL1β, IL4r, IL6, and TNFβ were associated with preeclampsia. However, results were not consistent across statistical models. As the relationship is complex, future studies should explore cytokine clusters in preeclampsia risk.
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