Comparative predictive power of serum vs plasma proteomic signatures in feto-maternal medicine.
biobanking
biomarker
biorepository
cohort study
gestational age
maternal health
multivariate model
plasma
prediction
pregnancy
proteins
proteomics
serum
Journal
AJOG global reports
ISSN: 2666-5778
Titre abrégé: AJOG Glob Rep
Pays: United States
ID NLM: 101777907
Informations de publication
Date de publication:
Aug 2023
Aug 2023
Historique:
medline:
17
7
2023
pubmed:
17
7
2023
entrez:
17
7
2023
Statut:
epublish
Résumé
Blood proteins are frequently measured in serum or plasma, because they provide a wealth of information. Differences in the ex vivo processing of serum and plasma raise concerns that proteomic health and disease signatures derived from serum or plasma differ in content and quality. However, little is known about their respective power to predict feto-maternal health outcomes. Predictive power is a sentinel characteristic to determine the clinical use of biosignatures. This study aimed to compare the power of serum and plasma proteomic signatures to predict a physiological pregnancy outcome. Paired serum and plasma samples from 73 women were obtained from biorepositories of a multinational prospective cohort study on pregnancy outcomes. Gestational age at the time of sampling was the predicted outcome, because the proteomic signatures have been validated for such a prediction. Multivariate and cross-validated models were independently derived for serum and plasma proteins. A total of 1116 proteins were measured in 88 paired samples from 73 women with a highly multiplexed platform using proximity extension technology (Olink Proteomics Inc, Watertown, MA). The plasma proteomic signature showed a higher predictive power (R=0.64; confidence interval, 0.42-0.79; Findings suggest that serum proteomics are less informative than plasma proteomics. They are compatible with the view that the partial ex-vivo degradation and modification of serum proteins during sample processing are an underlying reason. The rationale for collecting and analyzing serum and plasma samples should be carefully considered when deriving proteomic biosignatures to ascertain that specimens of the highest scientific and clinical yield are processed. Findings suggest that plasma is the preferred matrix.
Sections du résumé
BACKGROUND
BACKGROUND
Blood proteins are frequently measured in serum or plasma, because they provide a wealth of information. Differences in the ex vivo processing of serum and plasma raise concerns that proteomic health and disease signatures derived from serum or plasma differ in content and quality. However, little is known about their respective power to predict feto-maternal health outcomes. Predictive power is a sentinel characteristic to determine the clinical use of biosignatures.
OBJECTIVE
OBJECTIVE
This study aimed to compare the power of serum and plasma proteomic signatures to predict a physiological pregnancy outcome.
STUDY DESIGN
METHODS
Paired serum and plasma samples from 73 women were obtained from biorepositories of a multinational prospective cohort study on pregnancy outcomes. Gestational age at the time of sampling was the predicted outcome, because the proteomic signatures have been validated for such a prediction. Multivariate and cross-validated models were independently derived for serum and plasma proteins.
RESULTS
RESULTS
A total of 1116 proteins were measured in 88 paired samples from 73 women with a highly multiplexed platform using proximity extension technology (Olink Proteomics Inc, Watertown, MA). The plasma proteomic signature showed a higher predictive power (R=0.64; confidence interval, 0.42-0.79;
CONCLUSION
CONCLUSIONS
Findings suggest that serum proteomics are less informative than plasma proteomics. They are compatible with the view that the partial ex-vivo degradation and modification of serum proteins during sample processing are an underlying reason. The rationale for collecting and analyzing serum and plasma samples should be carefully considered when deriving proteomic biosignatures to ascertain that specimens of the highest scientific and clinical yield are processed. Findings suggest that plasma is the preferred matrix.
Identifiants
pubmed: 37456144
doi: 10.1016/j.xagr.2023.100244
pii: S2666-5778(23)00085-0
pmc: PMC10339042
doi:
Types de publication
Journal Article
Langues
eng
Pagination
100244Informations de copyright
© 2023 The Authors.
Références
Proteomics Clin Appl. 2019 Sep;13(5):e1800060
pubmed: 31162828
Kidney Med. 2022 Jun 02;4(8):100496
pubmed: 36061370
J Matern Fetal Neonatal Med. 2022 Dec;35(25):5621-5628
pubmed: 33653202
Nat Med. 2019 Dec;25(12):1851-1857
pubmed: 31792462
Clin Vaccine Immunol. 2011 Jan;18(1):173-5
pubmed: 21047999
Ultrasound Obstet Gynecol. 2014 Dec;44(6):641-8
pubmed: 25044000
Ultrasound Obstet Gynecol. 2016 Dec;48(6):719-726
pubmed: 26924421
Gates Open Res. 2018 Dec 4;2:25
pubmed: 30706053
N Engl J Med. 2019 Aug 15;381(7):668-676
pubmed: 31412182
Electrophoresis. 2017 Dec;38(24):3111-3123
pubmed: 28869764
Proteomics. 2005 Aug;5(13):3414-22
pubmed: 16038021
PLoS One. 2014 Apr 22;9(4):e95192
pubmed: 24755770
Am J Obstet Gynecol. 2018 Mar;218(3):347.e1-347.e14
pubmed: 29277631
Sci Rep. 2019 Oct 28;9(1):15385
pubmed: 31659186
Reprod Biol Endocrinol. 2021 Apr 19;19(1):56
pubmed: 33874952
Nat Med. 2019 Dec;25(12):1843-1850
pubmed: 31806903
Nucleic Acids Res. 2011 Aug;39(15):e102
pubmed: 21646338
J Glob Health. 2017 Dec;7(2):021202
pubmed: 29163938
JAMA Netw Open. 2020 Dec 1;3(12):e2029655
pubmed: 33337494
Ann Intern Med. 2007 Oct 16;147(8):573-7
pubmed: 17938396
Bioinformatics. 2019 Jan 1;35(1):95-103
pubmed: 30561547
PLoS One. 2019 Jun 4;14(6):e0217273
pubmed: 31163045
J Proteome Res. 2022 Nov 4;21(11):2687-2702
pubmed: 36154181
PLoS One. 2010 Dec 07;5(12):e15004
pubmed: 21165148