Heterozygous Nonsense Variants in the Ferritin Heavy Chain Gene <i>FTH1</i> Cause a Novel Pediatric Neuroferritinopathy
Bibliographic record
Abstract
Abstract Ferritin, the iron storage protein, is composed of light and heavy chain subunits, encoded by FTL and FTH1 , respectively. Heterozygous variants in FTL cause hereditary neuroferritinopathy, a type of neurodegeneration with brain iron accumulation (NBIA). Variants in FTH1 have not been previously associated with neurologic disease. We describe the clinical, neuroimaging, and neuropathology findings of five unrelated pediatric patients with de novo heterozygous FTH1 variants. Children presented with developmental delay, epilepsy, and progressive neurologic decline. Nonsense FTH1 variants were identified using whole exome sequencing, with a recurrent de novo variant (p.F171*) identified in three unrelated individuals. Neuroimaging revealed diffuse volume loss, features of pontocerebellar hypoplasia and iron accumulation in the basal ganglia. Neuropathology demonstrated widespread ferritin inclusions in the brain. Patient-derived fibroblasts were assayed for ferritin expression, susceptibility to iron accumulation, and oxidative stress. Variant FTH1 mRNA transcripts escape nonsense-mediated decay (NMD), and fibroblasts show elevated ferritin protein levels, markers of oxidative stress, and increased susceptibility to iron accumulation. C-terminus variants in FTH1 truncate ferritin’s E-helix, altering the four-fold symmetric pores of the heteropolymer and likely diminish iron-storage capacity. FTH1 pathogenic variants appear to act by a dominant, toxic gain-of-function mechanism. The data support the conclusion that truncating variants in the last exon of FTH1 cause a novel disorder in the spectrum of NBIA. Targeted knock-down of mutant FTH1 transcript with antisense oligonucleotides rescues cellular phenotypes and suggests a potential therapeutic strategy for this novel pediatric neurodegenerative disorder.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".