Evidence map›Paper›PMID 38053926›Full record

ArticleMolecular genetics and metabolism reports2023

Predicting the pathogenicity of missense variants based on protein instability to support diagnosis of patients with novel variants of ARSL.

Eriko Aoki, Noriyoshi Manabe, Shiho Ohno, Taiga Aoki, Jun-Ichi Furukawa, Akira Togayachi, Kiyoko Aoki-Kinoshita, Jin-Ichi Inokuchi, Kenji Kurosawa, Tadashi Kaname and 2 more

Open access · goldAbstract read
In one paragraph

Article in Molecular genetics and metabolism reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 24% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Neuromuscular Defects in aBiomolecules · 2025
    Article
  2. Review
  3. Article
  4. Article
  5. Article
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

12 authors at 5 institutions in 1 country.

Eriko AokiGlycan & Life Systems Integration Center (GaLSIC), Soka University, Hachioji 192-8577, Japan.
Noriyoshi ManabeDivision of Structural Glycobiology, Institute of Molecular Biomembrane and Glycobiology, Tohoku Medical and Pharmaceutical University, Sendai 981-8558, Japan.
Shiho OhnoDivision of Structural Glycobiology, Institute of Molecular Biomembrane and Glycobiology, Tohoku Medical and Pharmaceutical University, Sendai 981-8558, Japan.
Taiga AokiDepartment of Genome Medicine, National Center for Child Health and Development, Tokyo 157-8535, Japan.
Jun-Ichi FurukawaInstitute for Glyco-Core Research (iGCORE), Nagoya University, Nagoya 466-8550, Japan.
Akira TogayachiGlycan & Life Systems Integration Center (GaLSIC), Soka University, Hachioji 192-8577, Japan.
Kiyoko Aoki-KinoshitaGlycan & Life Systems Integration Center (GaLSIC), Soka University, Hachioji 192-8577, Japan.
Jin-Ichi InokuchiDivision of Structural Glycobiology, Institute of Molecular Biomembrane and Glycobiology, Tohoku Medical and Pharmaceutical University, Sendai 981-8558, Japan.
Kenji KurosawaDivision of Medical Genetics, Kanagawa Children's Medical Center, Yokohama 232-8555, Japan.
Tadashi KanameDepartment of Genome Medicine, National Center for Child Health and Development, Tokyo 157-8535, Japan.
Yoshiki YamaguchiDivision of Structural Glycobiology, Institute of Molecular Biomembrane and Glycobiology, Tohoku Medical and Pharmaceutical University, Sendai 981-8558, Japan.
Shoko NishiharaGlycan & Life Systems Integration Center (GaLSIC), Soka University, Hachioji 192-8577, Japan.
Soka University · JPTohoku Medical and Pharmaceutical University · JPNational Center For Child Health and Development · JPKanagawa Children's Medical Center · JPNagoya University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rare diseases are estimated to affect 3.5%-5.9% of the population worldwide and are difficult to diagnose. Genome analysis is useful for diagnosis. However, since some variants, especially missense variants, are also difficult to interpret, tools to accurately predict the effect of missense variants are very important and needed. Here we developed a method, "VarMeter", to predict whether a missense variant is damaging based on Gibbs free energy and solvent-accessible surface area calculated from the AlphaFold 3D protein model. We applied this method to the whole-exome sequencing data of 900 individuals with rare or undiagnosed disease in our in-house database, and identified four who were hemizygous for missense variants of arylsulfatase L (ARSL; known as the genetic cause of chondrodysplasia punctata 1, CPDX1). Two individuals had a novel Ser89 to Asn (Ser89Asn) or Arg469 to Trp (Arg469Trp) substitution, respectively predicted as "damaging" or "benign"; the other two had an Arg111 to His (Arg111His) or Gly117 to Arg (Gly117Arg) substitution, respectively predicted as "damaging" or "possibly damaging" and previously reported in patients showing clinical manifestations of CDPX1. Expression and analysis of the missense variant proteins showed that the predicted pathogenic variants (Ser89Asn, Arg111His, and Gly117Arg) had complete loss of sulfatase activity and reduced protease resistance due to destabilization of protein structure, while the predicted benign variant (Arg469Trp) had activity and protease resistance comparable to those of wild-type ARSL. The individual with the novel pathogenic Ser89Asn variant exhibited characteristics of CDPX1, while the individual with the benign Arg469Trp variant exhibited no such characteristics. These findings demonstrate that VarMeter may be used to predict the deleteriousness of variants found in genome sequencing data and thereby support disease diagnosis.

Indexed as

Arylsulfatase LMissense variantProtein instabilityRare diseaseStabilization energySulfatase activity

Identifiers

PMID38053926
PMCPMC10694752
OpenAlexW4388007888

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.