Type 1 diabetes mellitus: genes and variants

Type 1 diabetes mellitus is linked to 13 analyzed proteins (INS, IL2RA, BACH2, CD3E, CTLA4, FOXP3, IL10, INSR and 5 more). 8 DNA variants are known to cause it; 12 more are uncertain, and 0 of those already look disease-causing on computable evidence.

Last updated 2026-09-30. Research information, not medical advice.

Also known as: Type 1 diabetes mellitus 10; Type 1 diabetes mellitus 2; Type 1 diabetes mellitus 20; Type 1 diabetes mellitus 22

Genes linked to Type 1 diabetes mellitus

Weakly linked (only a few uncertain records): CCR5, KCNJ11 and LIPC.

Known disease-causing variants in Type 1 diabetes mellitus

VariantPositionProtein partClinical label
INS C96F96Disease-causing (★★)
INS C96R96Disease-causing (★★)
INS C96S96Disease-causing (★★)
INS C96Y96Disease-causing (★★)
INS M1V1Disease-causing (★★)
INS R89H89Disease-causing
INS R89P89Disease-causing
INS R89L89Disease-causing

Same protein, different disease

Diseases related to Type 1 diabetes mellitus

Frequently asked questions

Which genes are linked to Type 1 diabetes mellitus?

In CATVariant, Type 1 diabetes mellitus is linked to 13 analyzed proteins: INS (Insulin), IL2RA (Interleukin-2 receptor subunit alpha), BACH2 (Transcription regulator protein BACH2), CD3E (T-cell surface glycoprotein CD3 epsilon chain), CTLA4 (Cytotoxic T-lymphocyte protein 4), FOXP3 (Forkhead box protein P3) and 7 more.

How many genetic variants are linked to Type 1 diabetes mellitus?

20 variants: 8 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 12 are of uncertain significance or have conflicting reports.

Which uncertain variants in Type 1 diabetes mellitus 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.

Download every variant as CSV · Browse all diseases · Methods · About the Center