Evidence map›Paper›PMID 39609713›Full record

ArticleHuman genomics2024

Long-read sequencing enables comprehensive molecular genetic diagnosis of Fabry disease.

Fengxia Yao, Na Hao, Danhua Li, Weimin Zhang, Jingwen Zhou, Zhengqing Qiu, Aiping Mao, Wanli Meng, Juntao Liu

Abstract read
In one paragraph

Article in Human genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. A New Class of Pathogenic Non-Coding Variants in GLA.International journal of molecular sciences · 2026
    Article
  6. Article
  7. 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

9 authors.

Fengxia Yao *The Laboratory of Clinical Genetics, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Na Hao *Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Danhua Li *Department of Research and Development, Berry Genomics Corporation, Beijing, China.
Weimin ZhangThe Laboratory of Clinical Genetics, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Jingwen ZhouDepartment of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Zhengqing QiuDepartment of Pediatrics, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Aiping MaoDepartment of Research and Development, Berry Genomics Corporation, Beijing, China.
Wanli MengDepartment of Research and Development, Berry Genomics Corporation, Beijing, China.
Juntao LiuDepartment of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China. liujt@pumch.cn.

Funding

National High-Level Hospital Clinical Research Funding 2022-PUMCH-D-002
6 · The paper itself

Abstract

backgroundThe clinical diagnosis of Fabry Disease (FD) can be challenging due to the clinical heterogeneity, especially in females. Patients with FD often experience a prolonged interval between the onset of symptoms and receiving a diagnosis. Genetic testing is the gold standard for precise diagnosis of FD, however conventional genetic testing could miss deep intronic variants and large deletions or duplications. Although next-generation sequencing, which analyzes numerous genes, has been successfully used for FD diagnosis and can detect complex variants, an effective and rapid tool for identifying a wide range of variants is imminent, contributing to decrease the diagnostic delay.

methodsThe comprehensive Analysis of FD (CAFD) assay was developed for FD genetic diagnosis, employing long-range PCR coupled with long-read sequencing to target the full-length GLA gene and its flanking regions. Its clinical performance was assessed through a comparative analysis with Sanger sequencing.

resultsGenetic testing was performed on 82 individuals, including 48 probands and 34 relatives. The CAFD assay additionally identified variants in two probands: one had a novel and de novo pathogenic variant with a 1715 bp insertion in intron 4, and the other carried two deep intronic VUS variants in cis-configuration also in intron 4. In total, CAFD identified 47 different variants among 48 probands. Of these, 42 (89.36%, 42/47) were pathogenic, while 5 (10.64%, 5/47) were VUS. Sixteen (34.04%, 16/47) of the variants were novel, including 15 SNV/Indels and one large intronic insertion. Pedigree analysis of 21 probands identified four de novo disease-causing variants. Hence, FD exhibits not only variable clinical presentations but also a wide spectrum of variants. Utilizing a comprehensive testing algorithm for diagnosing FD, which includes enzyme activity, clinical features, and genetic testing, the diagnostic yield of CAFD is 97.92% (47/48), which is higher than that of conventional Sanger sequencing, at 95.83% (46/48).

conclusionThe duration between initial clinical presentation and diagnosis remains long and winding. CAFD provides precise diagnosis for a wide spectrum of GLA variants, promoting timely diagnosis and appropriate treatment for FD patients.

Indexed as

alpha-GalactosidaseFabry DiseaseGenetic TestingHigh-Throughput Nucleotide SequencingAdultFemaleHumansIntronsMaleMiddle AgedMutationPedigreeYoung Adultalpha-GalactosidaseGLA protein, humanFabry diseaseGenetic diagnosisGLALong-read sequencingNovel variant

Identifiers

PMID39609713
PMCPMC11603755

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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.