Evidence map›Paper›PMID 40253074›Full record

ReviewAmerican journal of obstetrics and gynecology2025

Single-cell omics technologies - Fundamentals on how to create single-cell looking glasses for reproductive health.

Maïgane Diop, Brittany R Davidson, Gabriela K Fragiadakis, Marina Sirota, Brice Gaudillière, Alexis J Combes

Abstract readReview
In one paragraph

Review in American journal of obstetrics and gynecology, 2025. 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
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.

  1. Review
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

6 authors.

Maïgane DiopProgram in Immunology, Stanford University School of Medicine, Stanford, CA; Medical Scientist Training Program, Stanford University School of Medicine, Stanford, CA.
Brittany R DavidsonUCSF CoLabs, University of California, San Francisco, CA.
Gabriela K FragiadakisUCSF CoLabs, University of California, San Francisco, CA; Bakar ImmunoX Initiative, University of California, San Francisco, CA; Division of Rheumatology, Department of Medicine, University of California, San Francisco, CA. Electronic address: Gabriela.Fragiadakis@ucsf.edu.
Marina SirotaBakar Computational Health Sciences Institute, University of California, San Francisco, CA; Department of Pediatrics, University of California, San Francisco, CA. Electronic address: marina.sirota@ucsf.edu.
Brice GaudillièreDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA. Electronic address: gbrice@stanford.edu.
Alexis J CombesUCSF CoLabs, University of California, San Francisco, CA; Department of Pathology, University of California, San Francisco, CA; Bakar ImmunoX Initiative, University of California, San Francisco, CA; Division of Gastroenterology, Department of Medicine, University of California, San Francisco, CA. Electronic address: Alexis.Combes@ucsf.edu.

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007365 · NIGMS · STANFORD UNIVERSITY · PI CHUA, KATRIN F · 1985 to 2021
$33.8M
Project 4: Human Endometrial Programming for Successful ImplantationP50HD055764 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FUNG, JENNIFER C · 2014 to 2022
$16.4M
Medical Scientist Training ProgramT32GM145402 · NIGMS · STANFORD UNIVERSITY · PI Katrin F. Chua · 2022 to 2026
$10.0M
RESOURCE-BASED CENTER FOR THE ADVANCEMENT OF PRECISION MEDICINE IN RHEUMATOLOGYP30AR070155 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Mary C Nakamura · 2016 to 2026
$8.2M
UCSF Stanford Endometriosis Center for Discovery, Innovation, Training and Community EngagementP01HD106414 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GAUDILLIERE, BRICE, GIUDICE, LINDA C · 2021 to 2025
$7.1M
Trio Analysis of Recurrent Pregnancy Loss Integrated Bioinformatics Genomics Study (TRIOS)R01HD105256 · NICHD · STANFORD UNIVERSITY · PI LATHI, RUTH B, RAJKOVIC, ALEKSANDAR · 2021 to 2025
$7.0M
Tissue mechanics reprograms the tissue to malignancy and metastasisR35CA242447 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI VALERIE MARIE WEAVER · 2020 to 2026
$6.6M
NCI NIH HHS R35 CA242447NIAMS NIH HHS P30 AR070155NICHD NIH HHS P01 HD106414NICHD NIH HHS P50 HD055764NICHD NIH HHS R01 HD105256NIGMS NIH HHS T32 GM007365NIGMS NIH HHS T32 GM145402
6 · The paper itself

Abstract

Over the last decade, in line with the goals of precision medicine to offer individualized patient care, various single-cell technologies measuring gene and proteomic expression in various tissues have rapidly advanced to study health and disease at the single cell level. Precisely understanding cell composition, position within tissues, signaling pathways, and communication can reveal insights into disease mechanisms and systemic changes during development, pregnancy, and gynecologic disorders across the lifespan. Single-cell technologies dissect the complex cellular compositions of reproductive tract tissues, providing insights into mechanisms behind reproductive tract dysfunction which impact wellness and quality of life. These technologies aim to understand basic tissue and organ functions and, clinically, to develop novel diagnostics, early disease biomarkers, and cell-targeted therapies for currently suboptimally-treated disorders. Increasingly, they are applied to pregnancy and pregnancy disorders, gynecologic malignancies, and uterine and ovarian physiology and aging, which are discussed in more detail in manuscripts in this special issue of AJOG. Here, we review recent applications of single-cell technologies to the study of gynecologic disorders and systemic biological adaptations during fetal development, pregnancy, and across a woman's lifespan. We discuss sequencing- and proteomic-based single-cell methods, as well as spatial transcriptomics and high-dimensional proteomic imaging, describing each technology's mechanism, workflow, quality control, and highlighting specific benefits, drawbacks, and utility in the context of reproductive medicine. We consider analytical methods for the high-dimensional single-cell data generated, highlighting statistical constraints and recent computational techniques for downstream clinical translation. Overall, current and evolving single-cell "looking glasses", or perspectives, have the potential to transform fundamental understanding of women's health and reproductive disorders and alter the trajectory of clinical practice and patient outcomes in the future.

Indexed as

Genital Diseases, FemaleProteomicsReproductive HealthSingle-Cell AnalysisFemaleHumansPregnancymulti-omicsproteomicsreproductive biologysingle-celltranscriptomics

Identifiers

PMID40253074
PMCPMC12090843

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.