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Record W3170980390 · doi:10.3389/fneur.2021.668640

NANS-CDG: Delineation of the Genetic, Biochemical, and Clinical Spectrum

2021· article· en· W3170980390 on OpenAlexaff
Bibiche den Hollander, Anne Rasing, Merel A. Post, Willemijn M. Klein, Machteld M. Oud, Marion M. Brands, Lonneke de Boer, Udo F. H. Engelke, Peter van Essen, Sabine A. Fuchs, Charlotte A. Haaxma, Brynjar Ö. Jensson, Leo A. J. Kluijtmans, Anna Lengyel, Klaske D. Lichtenbelt, Elsebet Østergaard, Gera Peters, Ramona Salvarinova, Marleen Simon, Kāri Stefánsson, Ólafur Thorarensen, Ulrike Ulmen, Karlien L. M. Coene, Michèl A.A.P. Willemsen, Dirk J. Lefeber, Clara van Karnebeek

Bibliographic record

VenueFrontiers in Neurology · 2021
Typearticle
Languageen
FieldMedicine
TopicCongenital Diaphragmatic Hernia Studies
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersRadboud Universitair Medisch CentrumRigshospitaletGentofte HospitalRadboud Universiteit
KeywordsBiologyPsychologyEvolutionary biologyComputational biologyGenetics

Abstract

fetched live from OpenAlex

Background: NANS-CDG is a recently described congenital disorder of glycosylation caused by biallelic genetic variants in NANS , encoding an essential enzyme in de novo sialic acid synthesis. Sialic acid at the end of glycoconjugates plays a key role in biological processes such as brain and skeletal development. Here, we present an observational cohort study to delineate the genetic, biochemical, and clinical phenotype and assess possible correlations. Methods: Medical and laboratory records were reviewed with retrospective extraction and analysis of genetic, biochemical, and clinical data (2016–2020). Results: Nine NANS-CDG patients (nine families, six countries) referred to the Radboudumc CDG Center of Expertise were included. Phenotyping confirmed the hallmark features including intellectual developmental disorder (IDD) ( n = 9/9; 100%), facial dysmorphisms ( n = 9/9; 100%), neurologic impairment ( n = 9/9; 100%), short stature ( n = 8/9; 89%), skeletal dysplasia ( n = 8/9; 89%), and short limbs ( n = 8/9; 89%). Newly identified features include ophthalmological abnormalities ( n = 6/9; 67%), an abnormal septum pellucidum ( n = 6/9; 67%), (progressive) cerebral atrophy and ventricular dilatation ( n = 5/9; 56%), gastrointestinal dysfunction ( n = 5/9; 56%), thrombocytopenia ( n = 5/9; 56%), and hypo–low-density lipoprotein cholesterol ( n = 4/9; 44%). Biochemically, elevated urinary excretion of N -acetylmannosamine (ManNAc) is pathognomonic, the concentrations of which show a significant correlation with clinical severity. Genotypically, eight novel NANS variants were identified. Three severely affected patients harbored identical compound heterozygous pathogenic variants, one of whom was initiated on experimental prenatal and postnatal treatment with oral sialic acid. This patient showed markedly better psychomotor development than the other two genotypically identical males. Conclusions: ManNAc screening should be considered in all patients with IDD, short stature with short limbs, facial dysmorphisms, neurologic impairment, and an abnormal septum pellucidum +/– congenital and neurodegenerative lesions on brain imaging, to establish a precise diagnosis and contribute to prognostication. Personalized management includes accurate genetic counseling and access to proper supports and tailored care for gastrointestinal symptoms, thrombocytopenia, and epilepsy, as well as rehabilitation services for cognitive and physical impairments. Motivated by the short-term positive effects of experimental treatment with oral sialic, we have initiated this intervention with protocolized follow-up of neurologic, systemic, and growth outcomes in four patients. Research is ongoing to unravel pathophysiology and identify novel therapeutic targets.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.275
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2021
Admission routes1
Has abstractyes

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