FAN1, a DNA Repair Nuclease, as a Modifier of Repeat Expansion Disorders
Bibliographic record
Abstract
FAN1 encodes a DNA repair nuclease. Genetic deficiencies, copy number variants, and single nucleotide variants of FAN1 have been linked to karyomegalic interstitial nephritis, 15q13.3 microdeletion/microduplication syndrome (autism, schizophrenia, and epilepsy), cancer, and most recently repeat expansion diseases. For seven CAG repeat expansion diseases (Huntington's disease (HD) and certain spinocerebellar ataxias), modification of age of onset is linked to variants of specific DNA repair proteins. FAN1 variants are the strongest modifiers. Non-coding disease-delaying FAN1 variants and coding disease-hastening variants (p.R507H and p.R377W) are known, where the former may lead to increased FAN1 levels and the latter have unknown effects upon FAN1 functions. Current thoughts are that ongoing repeat expansions in disease-vulnerable tissues, as individuals age, promote disease onset. Fan1 is required to suppress against high levels of ongoing somatic CAG and CGG repeat expansions in tissues of HD and FMR1 transgenic mice respectively, in addition to participating in DNA interstrand crosslink repair. FAN1 is also a modifier of autism, schizophrenia, and epilepsy. Coupled with the association of these diseases with repeat expansions, this suggests a common mechanism, by which FAN1 modifies repeat diseases. Yet how any of the FAN1 variants modify disease is unknown. Here, we review FAN1 variants, associated clinical effects, protein structure, and the enzyme's attributed functional roles. We highlight how variants may alter its activities in DNA damage response and/or repeat instability. A thorough awareness of the FAN1 gene and FAN1 protein functions will reveal if and how it may be targeted for clinical benefit.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".