Evidence map›Paper›PMID 41217551›Full record

SynthesisClinical and experimental medicine2025

The application of next-generation sequencing technology in congenital haemolytic anaemia: a systematic review and meta-analysis.

Shuning Xie, Yanling Zhong

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Clinical and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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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

2 authors.

Shuning XieBlood Transfusion Department, The Seventh Affiliated Hospital, Sun Yat-Sen University, No. 628, Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen City, 518107, Guangdong Province, China.
Yanling ZhongBlood Transfusion Department, The Seventh Affiliated Hospital, Sun Yat-Sen University, No. 628, Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen City, 518107, Guangdong Province, China. zhongyanling2@sysush.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Congenital haemolytic anaemia (CHA) poses diagnostic challenges due to genetic heterogeneity. This systematic review and meta-analysis evaluates the diagnostic efficacy of next-generation sequencing (NGS) in CHA. We systematically searched PubMed and Web of Science until April 2025. Inclusion criteria encompassed studies applying NGS (whole-exome sequencing [WES], whole-genome sequencing [WGS], clinical exome sequencing [CES], or targeted panels) in confirmed/suspected CHA patients. Pooled positive detection rates with 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup analyses stratified by family history and disease subtypes were performed. Study quality was assessed via modified STARD criteria. Ten studies involving 885 patients were included. The pooled positive detection rate of NGS was 44.3% (95% CI: 32.4-56.3%, p < 0.001). Subgroup analysis revealed significantly higher detection rates in patients with family history (51.0%; 95% CI: 32.8-69.2%) versus sporadic cases (16.9%; 95% CI: 8.4-27.2%, p < 0.001). Disease-specific yields varied: red cell membrane disorders showed the highest rate (45.3%; 95% CI: 35.2-55.7%), followed by enzymatic disorders (26.7%; 95% CI: 18.8-35.3%). Among all positive cases, pathogenic variants in five core genes accounted for 76.82% of detected mutations: SPTB (25.06%), PKLR (17.10%), ANK1 (11.94%), SLC4A1 (11.48%), and SPTA1 (11.24%). SPTB and ANK1 mutations were most frequently identified in red cell membrane disorders, while PKLR variants were exclusive to enzymatic disorders. NGS demonstrates substantial diagnostic utility in CHA, resolving nearly half of cases overall and over 50% of familial presentations. Its efficacy is particularly pronounced in red cell membrane disorders linked to cytoskeletal genes (SPTB, ANK1, SPTA1). These findings support integrating NGS into first-line CHA diagnostics, with prioritization of core gene panels for cost-effective implementation.

Indexed as

Anemia, Hemolytic, CongenitalHigh-Throughput Nucleotide SequencingExome SequencingHumansMutationWhole Genome SequencingCongenital haemolytic anaemiaMeta-analysisNext-generation sequencing technologySystematic review

Identifiers

PMID41217551
PMCPMC12605489

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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.