Primary ciliary dyskinesia: genes and variants

Genes linked to Primary ciliary dyskinesia

• DNAH5: Dynein axonemal heavy chain 5

  17 disease-causing and 1,173 uncertain variants in DNAH5 are linked to Primary ciliary dyskinesia.

• RPGR: X-linked retinitis pigmentosa GTPase regulator

  It coordinates protein trafficking through the photoreceptor connecting cilium, which is essential for continual renewal of outer segments. Pathogenic variants are a major cause of X-linked retinitis pigmentosa and can also produce cone-rod dystrophy.

  6 disease-causing and 24 uncertain variants in RPGR are linked to Primary ciliary dyskinesia.

• NFKB1: Nuclear factor NF-kappa-B p105 subunit

  It produces p105 and the p50 NF-kappaB subunit, which regulate transcriptional responses to immune receptors, cytokines, and cellular stress. Haploinsufficiency can cause common-variable-immunodeficiency-like disease with recurrent infection, autoimmunity, and variable lymphoproliferation.

  1 disease-causing and 0 uncertain variants in NFKB1 are linked to Primary ciliary dyskinesia.

Weakly linked (only a few uncertain records): CREBBP, CYBB and RAG1.

Where Primary ciliary dyskinesia variants cluster

• DNAH5 AAA 3 (positions 2550–2803): 6 of 17 disease-causing changes, 6.4× more than its size predicts.
• RPGR RCC1 2 (positions 106–158): 3 of 6 disease-causing changes, 9.6× more than its size predicts.

Known disease-causing variants in Primary ciliary dyskinesia

Uncertain variants in Primary ciliary dyskinesia that look disease-causing

Which prediction tools work for Primary ciliary dyskinesia

How often each tool ranks a disease-causing variant above a harmless one (AUROC × 100).

• REVEL: 96 out of 100 (learned from overlapping clinical labels, so this is optimistic)
• CATVariant: 93 out of 100 (learned from overlapping clinical labels, so this is optimistic)
• CADD: 92 out of 100
• PolyPhen-2: 86 out of 100 (learned from overlapping clinical labels, so this is optimistic)
• AlphaMissense: 85 out of 100
• MetaLR: 84 out of 100 (learned from overlapping clinical labels, so this is optimistic)
• MutPred2: 83 out of 100 (learned from overlapping clinical labels, so this is optimistic)
• EVE: 79 out of 100
• phyloP: 78 out of 100
• SIFT: 74 out of 100

Same protein, different disease

• RPGR-related retinopathy is also caused by RPGR variants; they fall mostly in different places as the Primary ciliary dyskinesia variants (6 disease-causing).
• Retinitis pigmentosa is also caused by RPGR variants; they fall mostly in different places as the Primary ciliary dyskinesia variants (4 disease-causing).

Diseases related to Primary ciliary dyskinesia

• Retinitis pigmentosa, also linked to RPGR
• Cone-rod dystrophy, also linked to RPGR
• RPGR-related retinopathy, also linked to RPGR
• Immunodeficiency, common variable, 10, also linked to NFKB1
• Common variable immunodeficiency, also linked to NFKB1

Frequently asked questions

Which genes are linked to Primary ciliary dyskinesia?

In CATVariant, Primary ciliary dyskinesia is linked to 3 analyzed proteins: DNAH5 (Dynein axonemal heavy chain 5), RPGR (X-linked retinitis pigmentosa GTPase regulator) and NFKB1 (Nuclear factor NF-kappa-B p105 subunit).

How many genetic variants are linked to Primary ciliary dyskinesia?

1,707 variants: 24 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 1,200 are of uncertain significance or have conflicting reports.

Which uncertain variants in Primary ciliary dyskinesia look disease-causing?

1 uncertain variants reach the likely-pathogenic range of the ACMG/AMP points scale on computable evidence, for example DNAH5 R1716Q. These are leads for expert review, not diagnoses.

Which variant effect predictor works best for Primary ciliary dyskinesia?

Among tools not trained on clinical labels, CADD separates this disease's known disease-causing variants from harmless ones best (AUROC 0.92, based on 11 disease-causing and 566 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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