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Mitochondrial DNA Copy Number in Peripheral Blood in the First Trimester of Pregnancy and Different Preeclampsia Clinical Phenotypes Development: A Pilot Study.
Reproductive Sciences 2018 October 9
Inflammation and oxidative stress are intrinsically linked to early poor placentation, typical of pregnancies complicated by preeclampsia associated with intrauterine growth restriction (PE-IUGR). Low mitochondrial DNA copy number (mtDNAcn) in peripheral blood constitutes a good peripheral surrogate marker of inflammation and oxidative stress. On these basis, we explored a possible correlation between mtDNAcn in peripheral blood in the first trimester of pregnancy and the PE-IUGR onset. To shed light on this issue, we setup a nested case-control study from a prospective cohort of pregnant women undergoing first-trimester aneuploidies screening. Two groups of patients affected by PE classified according to the clinical phenotype were identified: (1) patients who developed PE-IUGR and (2) patients who developed PE associated with appropriate for gestational age intrauterine fetal growth (PE-AGAf). Controls were women with a physiologic pregnancy matched to cases on the basis of age (±6 months, ratio 2:1). Mitochondrial DNA copy number was quantified using real-time polymerase chain reaction and normalized to nuclear DNA. The median (interquartile range) mtDNAcn in peripheral blood in patients with PE-IUGR (n = 12) and in patients with PE-AGAf (n = 16) was 70 (44-97) and 108 (95-145), respectively ( P = .004). Both these values were significantly lower than that detected in the control group (161[133-183], P < .001). The area under the receiver-operator curve for PE-IUGR and PE-AGAf were 0.94 (95% confidence interval [CI]: 0.88-1.00, P < .001) and 0.81 (95%CI: 0.70-0.91, P < .001), respectively. In conclusion, MtDNAcn in peripheral blood resulted significantly lower both in patients affected by PE-IUGR and in those affected by PE-AGAf when compared to controls. The accuracy of this biomarker resulted particularly good in predicting PE-IUGR.
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