Evidence map›Paper›PMID 38352867›Full record

ArticleFrontiers in immunology2024

Design of a targeted blood transcriptional panel for monitoring immunological changes accompanying pregnancy.

Tobias Brummaier, Darawan Rinchai, Mohammed Toufiq, Mohammed Y Karim, Tanwir Habib, Jürg Utzinger, Daniel H Paris, Rose McGready, Alexandra K Marr, Tomoshige Kino and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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

14 authors at 7 institutions in 5 countries.

Tobias BrummaierShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Sot, Thailand.
Darawan RinchaiResearch Department, Sidra Medicine, Doha, Qatar.
Mohammed ToufiqResearch Department, Sidra Medicine, Doha, Qatar.
Mohammed Y KarimResearch Department, Sidra Medicine, Doha, Qatar.
Tanwir HabibResearch Department, Sidra Medicine, Doha, Qatar.
Jürg UtzingerSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
Daniel H ParisSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
Rose McGreadyShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Sot, Thailand.
Alexandra K MarrResearch Department, Sidra Medicine, Doha, Qatar.
Tomoshige KinoResearch Department, Sidra Medicine, Doha, Qatar.
Annalisa TerranegraResearch Department, Sidra Medicine, Doha, Qatar.
Souhaila Al KhodorResearch Department, Sidra Medicine, Doha, Qatar.
Damien ChaussabelResearch Department, Sidra Medicine, Doha, Qatar.
Basirudeen Syed Ahamed KabeerResearch Department, Sidra Medicine, Doha, Qatar.
Jackson Laboratory · USShoklo Malaria Research Unit · THSt. Jude Children's Research Hospital · USSwiss Tropical and Public Health Institute · CHUniversity of Basel · CHUniversity of Oxford · GBWeill Cornell Medical College in Qatar · QA

Funding

Project 2: The Isoform repertoire and epigenome of Pediatric SLEP50AR070594 · NIAMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI Maria Virginia Pascual · 2016 to 2026
$18.6M
Predictors of Pregnancy Outcome In SLE and APSR01AR049772 · NIAMS · HOSPITAL FOR SPECIAL SURGERY · PI SALMON, JANE E · 2003 to 2012
$12.6M
Lupus CohortR01AR043727 · NIAMS · JOHNS HOPKINS UNIVERSITY · PI PETRI, MICHELLE A · 1997 to 2015
$8.2M
Scientific CoreU19AI082715 · NIAID · WEILL MEDICAL COLL OF CORNELL UNIV · PI PASCUAL, MARIA VIRGINIA · 2009 to 2018
$6.4M
Hopkins Lupus CohortR01AR069572 · NIAMS · JOHNS HOPKINS UNIVERSITY · PI PETRI, MICHELLE A · 2016 to 2020
$3.4M
NIAID NIH HHS U19 AI082715NIAMS NIH HHS P50 AR070594NIAMS NIH HHS R01 AR043727NIAMS NIH HHS R01 AR049772NIAMS NIH HHS R01 AR069572Wellcome Trust
6 · The paper itself

Abstract

Background: Immunomodulatory processes exert steering functions throughout pregnancy. Detecting diversions from this physiologic immune clock may help identify pregnant women at risk for pregnancy-associated complications. We present results from a data-driven selection process to develop a targeted panel of mRNAs that may prove effective in detecting pregnancies diverting from the norm. Methods: Based on a Results: We identified 176 transcripts that were complemented with eight housekeeping genes. Changes in transcript abundance were seen in the early stages of pregnancy and similar patterns were observed in both datasets. Functional gene annotation suggested significant changes in the lymphoid, prostaglandin and inflammation-associated compartments, when compared to the postpartum controls. Conclusion: The gene panel presented here holds promise for the development of predictive, targeted, transcriptional profiling assays. Such assays might become useful for monitoring of pregnant women, specifically to detect potential adverse events early. Prospective validation of this targeted assay, in-depth investigation of functional annotations of differentially expressed genes, and assessment of common pregnancy-associated complications with the aim to identify these early in pregnancy to improve pregnancy outcomes are the next steps.

Indexed as

Pregnancy ComplicationsTranscriptomeFemaleHumansPostpartum PeriodPregnancyPregnancy OutcomeRNA, MessengerRNA, MessengerBloodGen3 moduleimmunomodulatory processespregnancy-associated complicationstranscriptome fingerprinting assaywhole blood gene expression

Identifiers

PMID38352867
PMCPMC10861739
OpenAlexW4391358793

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.