Chronic progressive multiple sclerosis: genes and variants
Chronic progressive multiple sclerosis is linked to 1 analyzed protein (HNRNPA1). 14 DNA variants are known to cause it; 0 more are uncertain, and 0 of those already look disease-causing on computable evidence.
Last updated 2026-09-30. Research information, not medical advice.
Genes linked to Chronic progressive multiple sclerosis
HNRNPA1: Heterogeneous nuclear ribonucleoprotein A1
It regulates pre-mRNA splicing, RNA transport, translation, and stress-granule dynamics through RNA binding and reversible self-assembly. Rare pathogenic variants can cause multisystem proteinopathy, amyotrophic lateral sclerosis, or related neuromuscular degeneration through altered RNA and protein homeostasis.
14 disease-causing and 0 uncertain variants in HNRNPA1 are linked to Chronic progressive multiple sclerosis.
Where Chronic progressive multiple sclerosis variants cluster
- HNRNPA1 Nuclear targeting sequence (M9) (positions 320–357): 12 of 14 disease-causing changes, 8.4× more than its size predicts.
Known disease-causing variants in Chronic progressive multiple sclerosis
| Variant | Position | Protein part | Clinical label |
|---|---|---|---|
| HNRNPA1 F325L | 325 | Nuclear targeting sequence (M9) | Disease-causing |
| HNRNPA1 F325V | 325 | Nuclear targeting sequence (M9) | Disease-causing |
| HNRNPA1 N353D | 353 | Nuclear targeting sequence (M9) | Disease-causing |
| HNRNPA1 P327S | 327 | Nuclear targeting sequence (M9) | Disease-causing |
| HNRNPA1 R336G | 336 | Nuclear targeting sequence (M9) | Disease-causing |
| HNRNPA1 P351L | 351 | Nuclear targeting sequence (M9) | Disease-causing |
| HNRNPA1 N353S | 353 | Nuclear targeting sequence (M9) | Disease-causing |
| HNRNPA1 K329N | 329 | Nuclear targeting sequence (M9) | Disease-causing |
| HNRNPA1 F333L | 333 | Nuclear targeting sequence (M9) | Disease-causing |
| HNRNPA1 F348L | 348 | Nuclear targeting sequence (M9) | Disease-causing |
| HNRNPA1 F315L | 315 | Disease-causing | |
| HNRNPA1 N317D | 317 | Disease-causing | |
| HNRNPA1 S337G | 337 | Nuclear targeting sequence (M9) | Disease-causing |
| HNRNPA1 Y347C | 347 | Nuclear targeting sequence (M9) | Disease-causing |
Which prediction tools work for Chronic progressive multiple sclerosis
How often each tool ranks a disease-causing variant above a harmless one (AUROC × 100).
- CATVariant: 64 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- SIFT: 60 out of 100
- PolyPhen-2: 44 out of 100 (learned from overlapping clinical labels, so this is optimistic)
Diseases related to Chronic progressive multiple sclerosis
- Amyotrophic lateral sclerosis, also linked to HNRNPA1
- Inclusion body myopathy with Paget disease of bone and frontotemporal dementia, also linked to HNRNPA1
- Relapsing remitting multiple sclerosis, also linked to HNRNPA1
- Inclusion body myopathy with early-onset Paget disease with or without frontotemporal dementia 3, also linked to HNRNPA1
Frequently asked questions
Which genes are linked to Chronic progressive multiple sclerosis?
In CATVariant, Chronic progressive multiple sclerosis is linked to 1 analyzed protein: HNRNPA1 (Heterogeneous nuclear ribonucleoprotein A1).
How many genetic variants are linked to Chronic progressive multiple sclerosis?
19 variants: 14 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 0 are of uncertain significance or have conflicting reports.
Which uncertain variants in Chronic progressive multiple sclerosis look disease-causing?
None of the uncertain variants currently reaches the likely-pathogenic range on computable evidence alone.
Which variant effect predictor works best for Chronic progressive multiple sclerosis?
Among tools not trained on clinical labels, SIFT separates this disease's known disease-causing variants from harmless ones best (AUROC 0.60, based on 14 disease-causing and 8 harmless variants).
About this data
Variant–disease links come from ClinVar, Open Targets and UniProt, pooled from the latest public CATVariant analysis of each human protein. Evidence scores use the ACMG/AMP Bayesian points scale with computable criteria only (position among known disease variants, rarity in gnomAD, calibrated predictors, deep mutational scanning); there is no family or patient data, so they prioritise variants for expert review and never classify them.
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