Evidence map›Paper›PMID 41282918›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Mapping Chemical-Gene Interactions for Developmental Lethality and Pregnancy Loss.

Syed Hassan Bukhari, Amrita Nagasuri, Boris Oskotsky, Leen Arnaout, Polina Minkovski, Gonçalo D S Correia, David A MacIntyre, Gary M Shaw, David K Stevenson, Ruth B Lathi and 4 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Syed Hassan BukhariBakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.ORCID 0009-0002-6647-9168
Amrita NagasuriBakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.ORCID 0009-0003-1211-4830
Boris OskotskyBakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.ORCID 0000-0002-9364-7051
Leen ArnaoutBakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.ORCID 0000-0002-5415-2902
Polina MinkovskiBakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.
Gonçalo D S CorreiaParturition Research Group, Institute of Reproductive & Developmental Biology, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.ORCID 0000-0001-8271-9294
David A MacIntyreParturition Research Group, Institute of Reproductive & Developmental Biology, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.ORCID 0000-0002-4186-5567
Gary M ShawDepartment of Pediatrics, Stanford University, Stanford, CA, USA.ORCID 0000-0001-7438-4914
David K StevensonDepartment of Pediatrics, Stanford University, Stanford, CA, USA.ORCID 0000-0002-7127-0281
Ruth B LathiDepartment of Obstetrics and Gynecology, Stanford University, Stanford, CA, USA.ORCID 0000-0003-2159-2714
Svetlana A YatsenkoDepartment of Pathology, Stanford University, Stanford, CA, USA.ORCID 0000-0003-4809-8601
Tomiko T OskotskyBakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.ORCID 0000-0001-7393-5120
Aleksandar RajkovicDivision of Clinical Informatics and Digital Transformation, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0001-8390-0263
Marina SirotaBakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.ORCID 0000-0002-7246-6083

Funding

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
NICHD NIH HHS R01 HD105256
6 · The paper itself

Abstract

Purpose: Pregnancy loss affects 10-15% of clinically recognized pregnancies and is driven by genetic and environmental factors. Interactions between genes and chemicals critically shape developmental outcomes, yet existing resources do not organize chemical-gene evidence by gestational timing, maternal-fetal compartment, or lethality context. Methods: To minimize this gap, we merged Intolerome genes and the Comparative Toxicogenomics Database databases to create a filtered network of 928 lethality-associated genes and ~4,000 chemicals. We developed the Chemical-Gene Atlas (CGA) application, which analyzes chemical-gene interactions using four filters supporting hypothesis generation and clinical translation. Results: Using recurrent pregnancy loss (RPL) as a case study, CGA identified five clinically important genes (F5, F2, AURKB, PADI6, and FOXD1) demonstrating different exposomic patterns with Bisphenol A (BPA) and Benzo[a]pyrene (B[a]P). These exposures affect gene expression, methylation, and coagulation pathways and placental function. Our findings demonstrate that genes with loss-of-function intolerance, especially those expressed in metabolic and cardiovascular systems, are susceptible to environmental disruption during critical windows of development, including implantation, placental development, and early organogenesis. Conclusion: The CGA platform provides a scalable model to investigate chemical-gene interactions leading to developmental lethality. CGA is available at https://cgatlas.org/.

Indexed as

Chemical-Gene InteractionsDevelopmental LethalityExposomicsPregnancy LossRecurrent Pregnancy Loss (RPL)

Identifiers

PMID41282918
PMCPMC12632689

What Socratic 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 Socratic graph.