Evidence map›Paper›PMID 31412146›Full record

ArticleRapid communications in mass spectrometry : RCM2020

Differential processing of high-molecular-weight kininogen during normal pregnancy.

Stephenie H Droll, Yen-Michael Sheng Hsu, Steven K Drake, Ashley Kim, Weixin Wang, Katherine R Calvo, Zheng Cao, Tony Y Hu, Zhen Zhao

Open access · bronzeAbstract read
In one paragraph

Article in Rapid communications in mass spectrometry : RCM, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 89% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 2 countries.

Stephenie H DrollChemistry Section, Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.ORCID https://orcid.org/0000-0002-0655-3576
Yen-Michael Sheng HsuDepartment of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, NY, 10065, USA.
Steven K DrakeCritical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland, USA.
Ashley KimDepartment of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, 14853, USA.
Weixin WangHematology Section, Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.
Katherine R CalvoHematology Section, Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.
Zheng CaoDepartment of Laboratory Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China.
Tony Y HuVirginia G. Piper Biodesign Center for Personalized Diagnostics, The Biodesign Institute, Arizona State University, Tempe, AZ, 85281, USA.
Zhen ZhaoChemistry Section, Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.
Cornell University · USNational Institutes of Health Clinical Center · USCapital Medical University · CNNorthwestern University · USTulane University · US

Funding

The Role of microRNA in Hematologic MalignanciesZIACL090025 · CLC · CLINICAL CENTER · PI CALVO, KATHERINE · 2010 to 2025
$0k
Intramural NIH HHS Z99 CL999999Weill Cornell Medicine
6 · The paper itself

Abstract

rationaleStudies identified kininogen as a potential biomarker of preeclampsia, a major cause of adverse maternal outcomes. High-molecular-weight kininogen (HK) and its activated form participate in numerous pathways associated with establishing and maintaining pregnancy. However, dynamic changes in HK and naturally occurring HK-derived peptides during the natural course of pregnancy are largely unknown.

methodsLongitudinal serum samples during the course of normal pregnancy (trimesters T1, T2, T3) from 60 pregnant women were analyzed by western blot with an anti-HK antibody. Circulating peptides in longitudinal serum specimens derived from 50 participants were enriched using nanoporous silica thin films. Peptides were identified by liquid chromatography/tandem mass spectrometry (LC/MS/MS) and database searching. Relative quantification was performed using MaxQuant and in-house scripts. Normality was evaluated by either ANOVA or Friedman tests with p < 0.05 for statistical significance.

resultsWestern blotting revealed that HK significantly decreased during normal pregnancy (T1 vs T2, p < 0.05; T1 vs T3, p < 0.0001). A 100 kDa intermediate increased during pregnancy (T1 vs T2, p < 0.005; T1 vs T3, p < 0.01). Moreover, the heavy chain (T1 vs T2, p < 0.0001; T1 vs T3, p < 0.0001; T2 vs T3, p < 0.01) and light chain (T1 vs T2, p < 0.0001; T1 vs T3, p < 0.0001; T2 vs T3, p < 0.05) significantly increased during pregnancy. LC/MS/MS analysis identified 180 kininogen-1 peptides, of which 167 mapped to domain 5 (D5). Seventy-three peptides with ten or more complete data sets were included for further analysis. Seventy peptides mapped to D5, and 3, 24, and 43 peptides showed significant decrease, no trend, and significant increase, respectively, during pregnancy.

conclusionsThis study demonstrates dynamic changes in HK and naturally occurring HK-derived peptides during pregnancy. Our study sheds light on the gestational changes of HK and its peptides for further validation of them as potential biomarkers for pregnancy-related complications.

Indexed as

AdultChromatography, LiquidFemaleHumansKininogen, High-Molecular-WeightPeptidesPregnancyProteolysisRetrospective StudiesTandem Mass SpectrometryYoung AdultKininogen, High-Molecular-WeightPeptides

Identifiers

PMID31412146
PMCPMC7018535
OpenAlexW2967203276

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.