Development and validation of a proteomic biomarker risk predictor for preterm preeclampsia in asymptomatic women

Background Clinical risk factors for preeclampsia (PE), including previous PE, chronic hypertension, and pregestational diabetes, are poorly predictive of PE. Preterm PE, defined as diagnosis of PE with delivery prior to 37 weeks’ gestational age (GA), is more likely to be associated with serious morbidities and difficult clinical decision making. Therefore, there remains an urgent clinical need to develop a safe, feasible, and accurate predictor of preterm PE that integrates molecular biomarkers and relevant clinical factors into a single risk assessment score that can be used to guide clinical management. Objective(s) To discover, verify, and validate a mid-trimester proteomic biomarker risk predictor for preterm PE, comprised of a composite clinical variable and a small number of maternal serum analytes. Study Design This was a secondary analysis of data from two large clinical trials (PAPR, [NCT02787213][1]; TREETOP, [NCT01371019][2]). PAPR subjects’ eligibility was limited to those who had consented to research into preterm birth and pregnancy complications and who had blood drawn between 180/7 – 226/7 weeks’ gestation. TREETOP subjects were limited to those who had blood drawn between 180/7 – 206/7weeks’ gestation. PAPR subjects were assigned to a discovery cohort, and TREETOP subjects were randomly assigned to a first-phase cohort for verification (comprised of one-third of eligible subjects) and to a separate second-phase cohort for validation (comprised of the remaining two-thirds of eligible subjects). Peptides were analyzed by liquid chromatography-multiple reaction monitoring mass spectrometry measuring 77 pregnancy-related proteins and quality control proteins. Models were limited to a maximum of one additional protein ratio and a composite clinical variable, referred to as Clin3, which was deemed positive if any of three factors was true for the subject: prior PE; pre-existing hypertension; and/or pregestational diabetes. Overall classifier performance was assessed via area under the receiver operating characteristic curve (AUC). Results Verification yielded nine multi-component classifier models for prediction of preterm PE, all of which were subsequently validated. Classifiers exhibited greater predictive performance than clinical factors alone. Example performance metrics across a range of classifier score thresholds and GA at birth cutoffs of 37, 34 and 32 weeks for the Clin3 + inhibin subunit beta c (INHBC)/SHBG classifier, which showed the highest AUC, demonstrating a sensitivity of 89% at a specificity of 75% for prediction of early-onset preeclampsia (<34 weeks’ GA). Conclusion(s) Here, we report on discovery, verification, and validation of models for prediction of preterm PE. The log ratio of INHBC/SHBG along with any one of three clinical risk factors demonstrated high sensitivity and specificity. This combination of protein biomarkers and clinical factors has the potential to be used in the mid-trimester of pregnancy to guide clinical management to avoid both unnecessary medical procedures and the most serious complications of early-onset PE. ### Competing Interest Statement J.B., A.C.F., M.M.B., T.C.F., T.J.G., J.J.B., and P.E.K. are employees of Sera Prognostics, Inc., or were employees at the time of this work, and receive(d) salary and stock options. A.D.P. is a paid consultant to Sera Prognostics, Inc. L.C.L. and G.R.S have no conflict of interest to declare. ### Funding Statement This study was funded by Sera Prognostics, Inc. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The following is a listing of PAPR ([NCT01371019][2]) IRBs: IRB Intermountain Healthcare; IRB for Human Research, Medical University of South Carolina; IRB The University of North Carolina at Chapel Hill; IRB Maricopa Integrated Health System; IRB Baystate Medical Center; IRB Oregon Health & Science University; IRB University of Texas Medical Branch; IRB Christiana Care; WCG IRB (previously Western IRB, used by The Ohio State University, San Diego Perinatal Center, and Regional Obstetrical Consultants). The following is a listing of TREETOP ([NCT02787213][1]) IRBs: IRB for Human Research, Medical University of South Carolina; IRB The University of North Carolina at Chapel Hill; IRB Maricopa Integrated Health System; IRB Oregon Health & Science University; IRB University of Texas Medical Branch; IRB Boston Medical Center; IRB Ochsner Clinic Foundation; IRB University of California San Diego; Human Research Protections Program Northwestern University; IRB Indiana University; IRB Duke Medicine; IRB for Clinical Investigations, Greenville Health System; WCG IRB (previously Western IRB, used by Denver Health & Hospital Authority, University of Colorado-Denver, UC-Irvine, Thomas Jefferson University, Regional Obstetrical Consultants, and Baystate Medical Center). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors. [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT02787213&atom=%2Fmedrxiv%2Fearly%2F2022%2F12%2F22%2F2022.12.21.22282936.atom [2]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT01371019&atom=%2Fmedrxiv%2Fearly%2F2022%2F12%2F22%2F2022.12.21.22282936.atom