Cargando…

Late first trimester circulating microparticle proteins predict the risk of preeclampsia < 35 weeks and suggest phenotypic differences among affected cases

We hypothesize that first trimester circulating micro particle (CMP) proteins will define preeclampsia risk while identifying clusters of disease subtypes among cases. We performed a nested case–control analysis among women with and without preeclampsia. Cases diagnosed < 34 weeks’ gestation were...

Descripción completa

Detalles Bibliográficos
Autores principales: McElrath, Thomas F., Cantonwine, David E., Gray, Kathryn J., Mirzakhani, Hooman, Doss, Robert C., Khaja, Najmuddin, Khalid, Malik, Page, Gail, Brohman, Brian, Zhang, Zhen, Sarracino, David, Rosenblatt, Kevin P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578826/
https://www.ncbi.nlm.nih.gov/pubmed/33087742
http://dx.doi.org/10.1038/s41598-020-74078-w
_version_ 1783598450382733312
author McElrath, Thomas F.
Cantonwine, David E.
Gray, Kathryn J.
Mirzakhani, Hooman
Doss, Robert C.
Khaja, Najmuddin
Khalid, Malik
Page, Gail
Brohman, Brian
Zhang, Zhen
Sarracino, David
Rosenblatt, Kevin P.
author_facet McElrath, Thomas F.
Cantonwine, David E.
Gray, Kathryn J.
Mirzakhani, Hooman
Doss, Robert C.
Khaja, Najmuddin
Khalid, Malik
Page, Gail
Brohman, Brian
Zhang, Zhen
Sarracino, David
Rosenblatt, Kevin P.
author_sort McElrath, Thomas F.
collection PubMed
description We hypothesize that first trimester circulating micro particle (CMP) proteins will define preeclampsia risk while identifying clusters of disease subtypes among cases. We performed a nested case–control analysis among women with and without preeclampsia. Cases diagnosed < 34 weeks’ gestation were matched to controls. Plasma CMPs were isolated via size exclusion chromatography and analyzed using global proteome profiling based on HRAM mass spectrometry. Logistic models then determined feature selection with best performing models determined by cross-validation. K-means clustering examined cases for phenotypic subtypes and biological pathway enrichment was examined. Our results indicated that the proteins distinguishing cases from controls were enriched in biological pathways involved in blood coagulation, hemostasis and tissue repair. A panel consisting of C1RL, GP1BA, VTNC, and ZA2G demonstrated the best distinguishing performance (AUC of 0.79). Among the cases of preeclampsia, two phenotypic sub clusters distinguished cases; one enriched for platelet degranulation and blood coagulation pathways and the other for complement and immune response-associated pathways (corrected p < 0.001). Significantly, the second of the two clusters demonstrated lower gestational age at delivery (p = 0.049), increased protein excretion (p = 0.01), more extreme laboratory derangement (p < 0.0001) and marginally increased diastolic pressure (p = 0.09). We conclude that CMP-associated proteins at 12 weeks’ gestation predict the overall risk of developing early preeclampsia and indicate distinct subtypes of pathophysiology and clinical morbidity.
format Online
Article
Text
id pubmed-7578826
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-75788262020-10-23 Late first trimester circulating microparticle proteins predict the risk of preeclampsia < 35 weeks and suggest phenotypic differences among affected cases McElrath, Thomas F. Cantonwine, David E. Gray, Kathryn J. Mirzakhani, Hooman Doss, Robert C. Khaja, Najmuddin Khalid, Malik Page, Gail Brohman, Brian Zhang, Zhen Sarracino, David Rosenblatt, Kevin P. Sci Rep Article We hypothesize that first trimester circulating micro particle (CMP) proteins will define preeclampsia risk while identifying clusters of disease subtypes among cases. We performed a nested case–control analysis among women with and without preeclampsia. Cases diagnosed < 34 weeks’ gestation were matched to controls. Plasma CMPs were isolated via size exclusion chromatography and analyzed using global proteome profiling based on HRAM mass spectrometry. Logistic models then determined feature selection with best performing models determined by cross-validation. K-means clustering examined cases for phenotypic subtypes and biological pathway enrichment was examined. Our results indicated that the proteins distinguishing cases from controls were enriched in biological pathways involved in blood coagulation, hemostasis and tissue repair. A panel consisting of C1RL, GP1BA, VTNC, and ZA2G demonstrated the best distinguishing performance (AUC of 0.79). Among the cases of preeclampsia, two phenotypic sub clusters distinguished cases; one enriched for platelet degranulation and blood coagulation pathways and the other for complement and immune response-associated pathways (corrected p < 0.001). Significantly, the second of the two clusters demonstrated lower gestational age at delivery (p = 0.049), increased protein excretion (p = 0.01), more extreme laboratory derangement (p < 0.0001) and marginally increased diastolic pressure (p = 0.09). We conclude that CMP-associated proteins at 12 weeks’ gestation predict the overall risk of developing early preeclampsia and indicate distinct subtypes of pathophysiology and clinical morbidity. Nature Publishing Group UK 2020-10-21 /pmc/articles/PMC7578826/ /pubmed/33087742 http://dx.doi.org/10.1038/s41598-020-74078-w Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
McElrath, Thomas F.
Cantonwine, David E.
Gray, Kathryn J.
Mirzakhani, Hooman
Doss, Robert C.
Khaja, Najmuddin
Khalid, Malik
Page, Gail
Brohman, Brian
Zhang, Zhen
Sarracino, David
Rosenblatt, Kevin P.
Late first trimester circulating microparticle proteins predict the risk of preeclampsia < 35 weeks and suggest phenotypic differences among affected cases
title Late first trimester circulating microparticle proteins predict the risk of preeclampsia < 35 weeks and suggest phenotypic differences among affected cases
title_full Late first trimester circulating microparticle proteins predict the risk of preeclampsia < 35 weeks and suggest phenotypic differences among affected cases
title_fullStr Late first trimester circulating microparticle proteins predict the risk of preeclampsia < 35 weeks and suggest phenotypic differences among affected cases
title_full_unstemmed Late first trimester circulating microparticle proteins predict the risk of preeclampsia < 35 weeks and suggest phenotypic differences among affected cases
title_short Late first trimester circulating microparticle proteins predict the risk of preeclampsia < 35 weeks and suggest phenotypic differences among affected cases
title_sort late first trimester circulating microparticle proteins predict the risk of preeclampsia < 35 weeks and suggest phenotypic differences among affected cases
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578826/
https://www.ncbi.nlm.nih.gov/pubmed/33087742
http://dx.doi.org/10.1038/s41598-020-74078-w
work_keys_str_mv AT mcelraththomasf latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases
AT cantonwinedavide latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases
AT graykathrynj latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases
AT mirzakhanihooman latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases
AT dossrobertc latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases
AT khajanajmuddin latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases
AT khalidmalik latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases
AT pagegail latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases
AT brohmanbrian latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases
AT zhangzhen latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases
AT sarracinodavid latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases
AT rosenblattkevinp latefirsttrimestercirculatingmicroparticleproteinspredicttheriskofpreeclampsia35weeksandsuggestphenotypicdifferencesamongaffectedcases