Atrial septal defect: genes and variants

Atrial septal defect is linked to 9 analyzed proteins (NKX2-5, ACTC1, GATA4, TBX20, MYH6, ABCC8, GATA6, TGFB2 and 1 more). 35 DNA variants are known to cause it; 523 more are uncertain, and 2 of those already look disease-causing on computable evidence.

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

Also known as: atrial septal defect 1; atrial septal defect 2; atrial septal defect 3; Atrial septal defect 4; atrial septal defect 5; atrial septal defect 7; atrial septal defect 9

Genes linked to Atrial septal defect

Weakly linked (only a few uncertain records): CREBBP and TBX5.

Where Atrial septal defect variants cluster

Known disease-causing variants in Atrial septal defect

VariantPositionProtein partClinical label
GATA4 R284H284GATA-type 2Disease-causing (★★)
NKX2-5 T178M178HomeoboxDisease-causing (★★)
ACTC1 G247D247Disease-causing (★★)
ACTC1 I289T289Disease-causing (★★)
NKX2-5 L171P171HomeoboxDisease-causing (★★)
ACTC1 T128I128Disease-causing (★★)
GATA4 R283H283GATA-type 2Disease-causing (★★)
ACTC1 R256C256Disease-causing (★)
NKX2-5 F145L145HomeoboxDisease-causing (★)
ACTC1 A333P333Disease-causing (★)
ABCC8 R598Q598ABC transmembrane type-1 1Disease-causing (★)
NKX2-5 Q187H187HomeoboxDisease-causing (★)
NKX2-5 N188K188HomeoboxDisease-causing (★)
NKX2-5 R189G189HomeoboxDisease-causing (★)
NKX2-5 R190H190HomeoboxDisease-causing (★)
NKX2-5 Y191C191HomeoboxDisease-causing (★)
ACTC1 K52T52Disease-causing (★)
NKX2-5 Q22K22Disease-causing (★)
NKX2-5 L153P153HomeoboxDisease-causing (★)
NKX2-5 Q181H181HomeoboxDisease-causing (★)
ACTC1 I194N194Disease-causing (★)
ACTC1 K317N317Disease-causing (★)
GATA4 Y298C298Disease-causing (★)
TBX20 D176N176T-boxDisease-causing (★)
ACTC1 A297S297Disease-causing (★)
TPM1 S229F229Coiled coilDisease-causing
MYH6 I820N820Disease-causing
NKX2-5 K15I15Disease-causing
NKX2-5 E154G154HomeoboxDisease-causing
TBX20 I121M121T-boxDisease-causing
TGFB2 P338T338Disease-causing
ACTC1 M125V125Disease-causing
GATA4 S52F52Disease-causing
GATA4 G296C296Disease-causing
NKX2-5 D299G299Disease-causing

Uncertain variants in Atrial septal defect that look disease-causing

VariantPositionProtein partClinical labelEvidence
ACTC1 A333V333Conflicting reports (★)+6: in a 3D region that tolerates change poorly (3R); A333P at the same position is pathogenic; REVEL 0.919
NKX2-5 R189Q189HomeoboxUncertain (★)+6: 5 other pathogenic changes within 3 positions; R189G at the same position is pathogenic; REVEL 0.912

Which prediction tools work for Atrial septal defect

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

Same protein, different disease

Diseases related to Atrial septal defect

Frequently asked questions

Which genes are linked to Atrial septal defect?

In CATVariant, Atrial septal defect is linked to 9 analyzed proteins: NKX2-5 (Homeobox protein Nkx-2.5), ACTC1 (Actin, alpha cardiac muscle 1), GATA4 (Transcription factor GATA-4), TBX20 (T-box transcription factor TBX20), MYH6 (Myosin-6), ABCC8 (ATP-binding cassette sub-family C member 8) and 3 more.

How many genetic variants are linked to Atrial septal defect?

613 variants: 35 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 523 are of uncertain significance or have conflicting reports.

Which uncertain variants in Atrial septal defect look disease-causing?

2 uncertain variants reach the likely-pathogenic range of the ACMG/AMP points scale on computable evidence, for example ACTC1 A333V and NKX2-5 R189Q. These are leads for expert review, not diagnoses.

Which variant effect predictor works best for Atrial septal defect?

Among tools not trained on clinical labels, SIFT separates this disease's known disease-causing variants from harmless ones best (AUROC 0.85, based on 18 disease-causing and 286 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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