Use of cell-free signals as biomarkers for early and easy prediction of preeclampsia.

Autor:	Gekas J; Department of Medical Genetics, Quebec University Mother and Child Center, Laval Medical University, Quebec City, QC, Canada., Boomer TH; Illumina, Inc., San Diego, CA, United States., Rodrigue MA; Department of Medical Genetics, Quebec University Mother and Child Center, Laval Medical University, Quebec City, QC, Canada., Jinnett KN; Illumina, Inc., San Diego, CA, United States., Bhatt S; Illumina, Inc., San Diego, CA, United States.
Jazyk:	angličtina
Zdroj:	Frontiers in medicine [Front Med (Lausanne)] 2023 May 24; Vol. 10, pp. 1191163. Date of Electronic Publication: 2023 May 24 (Print Publication: 2023).
DOI:	10.3389/fmed.2023.1191163
Abstrakt:	Introduction: Preeclampsia (PE) is a leading cause of maternal and perinatal morbidity worldwide. However, current methods of screening are complicated and require special skill sets. In this observational study of prospectively collected samples, we wanted to evaluate if cell-free ( cf ) DNA could be an efficient biomarker for identification of at-risk patients. Methods: One hundred patients attending a private prenatal clinic in Canada were enrolled in their first trimester of pregnancy and a blood draw was carried out at 11 + 0 to 14 + 2 weeks' (timepoint A) and 17 + 6 to 25 + 5 weeks of gestation (timepoint B). CfDNA signals, namely concentration, fetal fraction, and fragment size distribution, were correlated with clinical outcomes in the test population to develop the logistic regression model. Results: Twelve patients developed PE-four early-stage and eight late-stage PE. Significant differences were observed between PE patients and control cases for all three cfDNA signals at timepoint A, while both fetal fraction and concentration were significantly different between PE patients and control cases at timepoint B. Overall, the model had a sensitivity of up to 100% and specificity of up to 87.5% at Timepoint A. Conclusion: This proof-of-principle study showed that use of this logistic regression model could identify patients at risk of preeclampsia in the first trimester of pregnancy. Competing Interests: TB and SB are employees of and own equity in Illumina, Inc. KJ is a paid consultant for Illumina, Inc. JG and M-AR hold positions at Quebec University Hospital but collaborate respectively as medical and scientific advisors at Prenato clinics, a private medical clinic network in Quebec province, Canada. This study received funding from Illumina, Inc. The funder had the following involvement with the study: study design, analysis and interpretation of data, writing of the article, and the decision to submit the article for publication. All authors declare no other competing interests. (Copyright © 2023 Gekas, Boomer, Rodrigue, Jinnett and Bhatt.)
Databáze:	MEDLINE
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