Evidence map›Paper›PMID 41268615›Full record

ReviewInternational journal of molecular medicine2026

Decoding structural birth defects through genomic landscapes: Innovative frameworks for diagnosis (Review).

Ruihao Xu, Haoming Ren, Zhengwei Yuan, Wanqi Huang, Hui Gu

Abstract readReview
In one paragraph

Review in International journal of molecular medicine, 2026. 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

5 authors.

Ruihao XuSecond Clinical College, Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, P.R. China.
Haoming RenClinical College, Alberta Institute, Wenzhou Medical University, Wenzhou, Zhejiang 325035, P.R. China.
Zhengwei YuanNHC Key Laboratory of Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, P.R. China.
Wanqi HuangNHC Key Laboratory of Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, P.R. China.
Hui GuNHC Key Laboratory of Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Structural birth defects (SBDs) represent a major subset of congenital malformations arising from abnormalities during organogenesis and subsequent tissue morphogenesis. The triad of congenital heart defects (CHDs), orofacial clefts (OFCs) and neural tube defects (NTDs) dominates the global epidemiology of SBDs, collectively contributing to considerable neonatal mortality while imposing profound clinical and socioeconomic burdens. Conventional genetic screening approaches, such as karyotype and non‑invasive prenatal testing, remain limited in their capacity to decipher the complex genomic factors underlying these SBDs. The advent of advanced genomic technologies (including chromosomal microarray analysis and next‑generation sequencing) and integrated genomic analysis methods [such as copy number variation analysis, single nucleotide variation/insertion and deletion analysis and genome‑wide association studies (GWAS)] has enhanced the capacity to identify pathogenic genetic factors, thereby transforming the mode of prenatal diagnosis and genetic counseling. The application of these technologies, by virtue of more accurate diagnosis and finer disease classification, not only provides a more comprehensive basis for assessing disease severity and prognosis in clinical decision‑making but also offers support for implementing targeted intervention and treatment. The present review systematically evaluates state‑of‑the‑art genomic methodologies and computational approaches for detecting genomic aberrations in CHDs, OFCs and NTDs, and integrates insights from GWAS to elucidate the underlying genetic architecture, contributing to achieving precise predictive modeling and targeted therapeutic innovation for SBDs.

Indexed as

Congenital AbnormalitiesGenomicsDNA Copy Number VariationsGenetic TestingGenome-Wide Association StudyHumansPrenatal Diagnosiscopy number variationgenome‑wide association studygenomicssingle nucleotide variants/insertion and deletionsstructural birth defects

Identifiers

PMID41268615
PMCPMC12668783

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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.