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Record W4411704999 · doi:10.1002/ccr3.9660

Expanding the Phenotypic Spectrum of Methylenetetrahydrofolate Reductase ( <scp>MTHFR</scp> ) Deficiency in Childhood: A Case Series

2025· article· en· W4411704999 on OpenAlexfundno aff
Eimear Loftus, Zaineb Elbishari, Patricia Fitzsimons, Caoimhe Howard, Yusra Sheikh, Bryan Lynch, Ellen Crushell, Ina Knerr

Bibliographic record

VenueClinical Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsnot available
FundersChildren's Health Foundation
KeywordsMedicineMethylenetetrahydrofolate reductasePediatricsNewborn screeningHypotoniaGlobal developmental delayMicrocephalyGenotypePhenotypeGenetics

Abstract

fetched live from OpenAlex

Methylenetetrahydrofolate reductase (MTHFR) deficiency is a rare inborn error of folate metabolism. A number of phenotypic findings have been identified to date, and we hereby wish to expand its phenotype based on our Irish experience of the condition. We follow three children with MTHFR deficiency in our National Centre for Inherited Metabolic Disorders, giving an estimated point prevalence of approx. 0.08 cases per 100,000 in the Republic of Ireland. Our first case was referred for a metabolic opinion at 19 months of age. She had a history of global developmental delay with hypotonia, microcephaly, nystagmus, rash, and seizures. The second patient presented at 12 years of age with an osteopenic femoral fracture on the background of low body mass index (BMI). The third case presented at ten and a half years of age with acute mood disturbance with challenging behavior and a history of focal seizures and intellectual disability. It has been reported that early treatment may provide clinical benefit; however, we wish to acknowledge the varying responses to treatment despite pleasing metabolic control in our patients. MTHFR deficiency is a challenging diagnosis in childhood, given its low prevalence, complex phenotypes, and varying responses to treatment. Presymptomatic treatment further to early diagnosis through newborn screening may further improve outcomes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.385
Teacher spread0.346 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations1
Published2025
Admission routes1
Has abstractyes

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