Noonan syndrome with multiple lentigines: genes and variants

Noonan syndrome with multiple lentigines is linked to 3 analyzed proteins (PTPN11, BRAF and MAP2K1). 4 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 Noonan syndrome with multiple lentigines

Weakly linked (only a few uncertain records): RAF1.

Known disease-causing variants in Noonan syndrome with multiple lentigines

VariantPositionProtein partClinical label
PTPN11 T468M468Tyrosine-protein phosphataseDisease-causing (★★★)
PTPN11 Q510P510Tyrosine-protein phosphataseDisease-causing (★★★)
PTPN11 Q256R256Tyrosine-protein phosphataseDisease-causing (★★)
PTPN11 R498L498Tyrosine-protein phosphataseDisease-causing (★★)

Same protein, different disease

Diseases related to Noonan syndrome with multiple lentigines

Frequently asked questions

Which genes are linked to Noonan syndrome with multiple lentigines?

In CATVariant, Noonan syndrome with multiple lentigines is linked to 3 analyzed proteins: PTPN11 (Tyrosine-protein phosphatase non-receptor type 11), BRAF (Serine/threonine-protein kinase B-raf) and MAP2K1 (Dual specificity mitogen-activated protein kinase kinase 1).

How many genetic variants are linked to Noonan syndrome with multiple lentigines?

14 variants: 4 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 Noonan syndrome with multiple lentigines look disease-causing?

None of the uncertain variants currently reaches the likely-pathogenic range on computable evidence alone.

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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