Acute megakaryoblastic leukemia in down syndrome: genes and variants

Genes linked to Acute megakaryoblastic leukemia in down syndrome

• JAK1: Tyrosine-protein kinase JAK1

  It couples many cytokine receptors to STAT transcription factors and is essential for interferon, interleukin, and growth-factor signaling. Loss-of-function can cause immunodeficiency, whereas activating alterations contribute to inflammatory disease and some malignancies.

  1 disease-causing and 0 uncertain variants in JAK1 are linked to Acute megakaryoblastic leukemia in down syndrome.

• NRAS: GTPase NRas

  Its active GTP-bound state drives RAF-MEK-ERK and PI3K signaling downstream of growth-factor receptors. Somatic activating variants are common drivers of melanoma, leukemia, and other cancers, while germline activating variants can cause Noonan syndrome.

  1 disease-causing and 0 uncertain variants in NRAS are linked to Acute megakaryoblastic leukemia in down syndrome.

• SRSF2: Serine/arginine-rich splicing factor 2

  It helps select splice sites during pre-mRNA processing and coordinates multiple stages of RNA maturation. Recurrent P95 hotspot mutations change RNA-binding preferences and are common in myelodysplastic syndromes, chronic myelomonocytic leukemia, and AML.

  1 disease-causing and 0 uncertain variants in SRSF2 are linked to Acute megakaryoblastic leukemia in down syndrome.

• GATA1: Erythroid transcription factor

  It directs erythroid and megakaryocytic differentiation by activating lineage-specific genes and suppressing alternative hematopoietic programs. Germline variants can cause anemia and thrombocytopenia syndromes, while acquired N-terminal mutations are characteristic of transient abnormal myelopoiesis and myeloid leukemia in Down syndrome.

  0 disease-causing and 0 uncertain variants in GATA1 are linked to Acute megakaryoblastic leukemia in down syndrome.

Known disease-causing variants in Acute megakaryoblastic leukemia in down syndrome

Same protein, different disease

• Noonan syndrome is also caused by NRAS variants; they fall mostly in different places as the Acute megakaryoblastic leukemia in down syndrome variants (9 disease-causing).
• RASopathy is also caused by NRAS variants; they fall mostly in different places as the Acute megakaryoblastic leukemia in down syndrome variants (6 disease-causing).

Diseases related to Acute megakaryoblastic leukemia in down syndrome

• Acute myeloid leukemia, also linked to NRAS and SRSF2
• Hypertrophic cardiomyopathy, also linked to NRAS
• RASopathy, also linked to NRAS
• Noonan syndrome, also linked to NRAS
• Noonan syndrome and Noonan-related syndrome, also linked to NRAS
• Cardiofaciocutaneous syndrome, also linked to NRAS
• Autoimmune lymphoproliferative syndrome, also linked to NRAS
• Colorectal cancer, also linked to NRAS
• Costello syndrome, also linked to NRAS
• Vascular malformation, also linked to NRAS
• Juvenile myelomonocytic leukemia, also linked to NRAS
• Hypothyroidism, also linked to JAK1

Frequently asked questions

Which genes are linked to Acute megakaryoblastic leukemia in down syndrome?

In CATVariant, Acute megakaryoblastic leukemia in down syndrome is linked to 4 analyzed proteins: JAK1 (Tyrosine-protein kinase JAK1), NRAS (GTPase NRas), SRSF2 (Serine/arginine-rich splicing factor 2) and GATA1 (Erythroid transcription factor).

How many genetic variants are linked to Acute megakaryoblastic leukemia in down syndrome?

5 variants: 3 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 Acute megakaryoblastic leukemia in down syndrome 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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