Human Gene Module / Chromosome 5 / GABRB2

GABRB2gamma-aminobutyric acid type A receptor subunit beta2

SFARI Gene Score
1
High Confidence Criteria 1.1
Autism Reports / Total Reports
4 / 6
Rare Variants / Common Variants
7 / 0
EAGLE Score
0.3
Limited Learn More
Aliases
GABRB2, ICEE2
Associated Syndromes
-
Chromosome Band
5q34
Associated Disorders
-
Genetic Category
Rare Single Gene Mutation
Relevance to Autism

Three de novo missense variants in the GABRB2 gene, including one that was predicted to be damaging (defined as MPC 2), were identified in ASD probands from the Simons Simplex Collection and the Autism Sequencing Consortium (Iossifov et al., 2014; Satterstrom et al., 2020), while two protein-truncating variants in this gene were observed in case samples from the Danish iPSYCH study (Satterstrom et al., 2020). TADA analysis of de novo variants from the Simons Simplex Collection and the Autism Sequencing Consortium and protein-truncating variants from iPSYCH in Satterstrom et al., 2020 identified GABRB2 as a candidate gene with a false discovery rate (FDR) between 0.05 and 0.1 (0.05 < FDR 0.1).

Molecular Function

The gamma-aminobutyric acid (GABA) A receptor is a multisubunit chloride channel that mediates the fastest inhibitory synaptic transmission in the central nervous system. This gene encodes GABA A receptor, beta 2 subunit. Heterozygous mutations in this gene are responsible for infantile or early childhood epileptic encephalopathy-2 (IECEE2; OMIM 617829), a neurodevelopmental disorder characterized in most patients by onset of seizures in infancy or childhood and associated with global developmental delay and variable intellectual disability.

External Links
Gene CardOpen Targets PlatformgnomAD browserSynGO portalPubMed
Human
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Mouse
Entrez GeneMouse Genome InformaticsAllen Brain Atlas
SFARI Genomic Platforms
GPF browser SFARI genome browser
Reports related to GABRB2 (6 Reports)
# Type Title Author, Year Autism Report Associated Disorders
1 Primary The contribution of de novo coding mutations to autism spectrum disorder Iossifov I et al. (2014) Yes -
2 Recent recommendation Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism Satterstrom FK et al. (2020) Yes -
3 Support - Mahjani B et al. (2021) Yes -
4 Support - Zhou X et al. (2022) Yes -
5 Support - Lucie Sedlackova et al. (2024) No -
6 Support - Marketa Wayhelova et al. (2024) No -
Rare Variants   (7)
Status Allele Change Residue Change Variant Type Inheritance Pattern Parental Transmission Family Type PubMed ID Author, Year
c.541+7C>T - splice_region_variant De novo - - 35982159 Zhou X et al. (2022)
c.573C>G p.Tyr191Ter stop_gained Unknown - - 34615535 Mahjani B et al. (2021)
c.50T>C p.Leu17Ser missense_variant De novo - Simplex 25363768 Iossifov I et al. (2014)
c.895A>C p.Ile299Leu missense_variant De novo - - 38008000 Lucie Sedlackova et al. (2024)
c.946G>A p.Val316Ile missense_variant De novo - Simplex 31981491 Satterstrom FK et al. (2020)
c.1088A>C p.His363Pro missense_variant De novo - Simplex 31981491 Satterstrom FK et al. (2020)
c.869C>T p.Thr290Ile missense_variant Familial Maternal - 38321498 Marketa Wayhelova et al. (2024)
Common Variants  

No common variants reported.

SFARI Gene score
1

High Confidence

Score Delta: Score remained at 1

criteria met
See SFARI Gene'scoring criteria
1

High Confidence

See all Category 1 Genes

We considered a rigorous statistical comparison between cases and controls, yielding genome-wide statistical significance, with independent replication, to be the strongest possible evidence for a gene. These criteria were relaxed slightly for category 2.

4/1/2022
icon
1

Increased from to 1

Krishnan Probability Score

Score 0.5690218874309

Ranking 1069/25841 scored genes


[Show Scoring Methodology]
Krishnan and colleagues generated probability scores genome-wide by using a machine learning approach on a human brain-specific gene network. The method was first presented in Nat Neurosci 19, 1454-1462 (2016), and scores for more than 25,000 RefSeq genes can be accessed in column G of supplementary table 3 (see: http://www.nature.com/neuro/journal/v19/n11/extref/nn.4353-S5.xlsx). A searchable browser, with the ability to view networks of associated ASD risk genes, can be found at asd.princeton.edu.
Original Source
ExAC Score

Score 0.94029923046859

Ranking 2825/18225 scored genes


[Show Scoring Methodology]
The Exome Aggregation Consortium (ExAC) is a summary database of 60,706 exomes that has been widely used to estimate 'constraint' on mutation for individual genes. It was introduced by Lek et al. Nature 536, 285-291 (2016), and the ExAC browser can be found at exac.broadinstitute.org. The pLI score was developed as measure of intolerance to loss-of- function mutation. A pLI > 0.9 is generally viewed as highly constrained, and thus any loss-of- function mutations in autism in such a gene would be more likely to confer risk. For a full list of pLI scores see: ftp://ftp.broadinstitute.org/pub/ExAC_release/release0.3.1/functional_gene_constraint/fordist_cle aned_exac_nonTCGA_z_pli_rec_null_data.txt
Original Source
Sanders TADA Score

Score 0.85719962106846

Ranking 3734/18665 scored genes


[Show Scoring Methodology]
The TADA score ('Transmission and De novo Association') was introduced by He et al. PLoS Genet 9(8):e1003671 (2013), and is a statistic that integrates evidence from both de novo and transmitted mutations. It forms the basis for the claim of 65 individual genes being strongly associated with autism risk at a false discovery rate of 0.1 (Sanders et al. Neuron 87, 1215-1233 (2015)). The calculated TADA score for 18,665 RefSeq genes can be found in column P of Supplementary Table 6 in the Sanders et al. paper (the column headed 'tadaFdrAscSscExomeSscAgpSmallDel'), which represents a combined analysis of exome data and small de novo deletions (see www.cell.com/cms/attachment/2038545319/2052606711/mmc7.xlsx).
Original Source
Zhang D Score

Score 0.60980413763394

Ranking 65/20870 scored genes


[Show Scoring Methodology]
The DAMAGES score (disease-associated mutation analysis using gene expression signatures), or D score, was developed to combine evidence from de novo loss-of- function mutation with evidence from cell-type- specific gene expression in the mouse brain (specifically translational profiles of 24 specific mouse CNS cell types isolated from 6 different brain regions). Genes with positive D scores are more likely to be associated with autism risk, with higher-confidence genes having higher D scores. This statistic was first presented by Zhang & Shen (Hum Mutat 38, 204- 215 (2017), and D scores for more than 20,000 RefSeq genes can be found in column M in supplementary table 2 from that paper.
Original Source
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