Evidence map›Paper›PMID 31937438›Full record

SynthesisMolecular genetics and metabolism2020

The natural history of Type 1 infantile GM1 gangliosidosis: A literature-based meta-analysis.

Frederick M Lang, Paul Korner, Mark Harnett, Ajith Karunakara, Cynthia J Tifft

Open access · greenAbstract readMeta-AnalysisReview
In one paragraph

Synthesis in Molecular genetics and metabolism, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 16% of its field
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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. GM1 gangliosidosis type II: Results of a 10-year prospective study.Genetics in medicine : official journal of the American College of Medical Genetics · 2024
    Observational
  15. Review
  16. Article
  17. GM1 Gangliosidosis Type II: Results of a 10-Year Prospective Study.medRxiv : the preprint server for health sciences · 2024
    Article
  18. Article
  19. Article
  20. 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

5 authors at 1 institution in 1 country.

Frederick M LangAxovant Sciences, a subsidiary of Axovant Gene Therapies (Axovant), United States of America.
Paul KornerAxovant Sciences, a subsidiary of Axovant Gene Therapies (Axovant), United States of America.
Mark HarnettAxovant Sciences, a subsidiary of Axovant Gene Therapies (Axovant), United States of America.
Ajith KarunakaraAxovant Sciences, a subsidiary of Axovant Gene Therapies (Axovant), United States of America.
Cynthia J TifftOffice of the Clinical Director & Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health (NHGRI), United States of America. Electronic address: cynthiat@mail.nih.gov.
National Human Genome Research Institute · US

Funding

Intramural NIH HHS Z99 HG999999
6 · The paper itself

Abstract

introductionType 1 GM1 gangliosidosis is an ultra-rare, rapidly fatal lysosomal storage disorder, with life expectancy of <3 years of age. To date, only one prospective natural history study of limited size has been reported. Thus, there is a need for additional research to provide a better understanding of the progression of this disease. We have leveraged the past two decades of medical literature to conduct the first comprehensive retrospective study characterizing the natural history of Type 1 GM1 gangliosidosis.

objectivesThe objectives of this study were to establish a large sample of patients from the literature in order to identify: 1) clinically distinguishing factors between Type 1 and Type 2 GM1 gangliosidosis, 2) age at first symptom onset, first hospital admission, diagnosis, and death, 3) time to onset of common clinical findings, and 4) timing of developmental milestone loss.

methodsPubMed was searched with the keyword "GM1 Gangliosidosis" and for articles from the year 2000 onwards. A preliminary review of these results was conducted to establish subtype classification criteria for inclusion of only Type 1 patients, resulting in 44 articles being selected to generate the literature dataset of 154 Type 1 GM1 gangliosidosis patients. Key clinical events of these patient cases were recorded from the articles.

resultsComprehensive subtyping criteria for Type 1 GM1 gangliosidosis were created, and clinical events, including onset, diagnosis, death, and symptomology, were mapped over time. In this dataset, average age of diagnosis was 8.7 months, and average age of death was 18.9 months. DISCUSSION: This analysis demonstrates the predictable clinical course of this disease, as almost all patients experienced significant multi-organ system dysfunction and neurodevelopmental regression, particularly in the 6- to 18-month age range. Patients were diagnosed at a late age relative to disease progression, indicating the need for improved public awareness and screening.

conclusionThis study highlights the significant burden of illness in this disease and provides critical natural history data to drive earlier diagnosis, inform clinical trial design, and facilitate family counseling.

Indexed as

beta-GalactosidaseGangliosidosis, GM1HumansInfantLysosomal Storage DiseasesNeurodevelopmental DisordersPubMedRare DiseasesRetrospective Studiesbeta-GalactosidaseGM1 gangliosidosisLiterature reviewLysosomal storage disorderMeta-analysisNatural history studyType 1

Identifiers

PMID31937438
PMCPMC7093236
OpenAlexW2997436122

What OpenQuestion holds

Textmetadata
LicenceTDM
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.