Human Gene Module / Chromosome 10 / KAT6B

KAT6Blysine acetyltransferase 6B

SFARI Gene Score
3
Suggestive Evidence Criteria 3.1
Autism Reports / Total Reports
6 / 14
Rare Variants / Common Variants
65 / 0
Aliases
KAT6B, GTPTS,  MORF,  MOZ2,  MYST4,  ZC2HC6B,  qkf,  querkopf
Associated Syndromes
SBBYSS syndrome
Chromosome Band
10q22.2
Associated Disorders
DD/NDD
Relevance to Autism

A de novo missense variant in the KAT6B gene was identified in an ASD proband from the Simons Simplex Collection (Iossifov et al., 2014), while a paternally-inherited nonsense variant in this gene was identified in an ASD proband from the SPARK cohort (Feliciano et al., 2019). Additional de novo variants in KAT6B have been identified in probands with intellectual disability (Lelieveld et al., 2016) and from the Deciphering Developmental Disorders 2017 study. Single-molecular molecular inversion probe (smMIP) sequencing of 7,954 probands from cohorts with a primary diagnosis of ASD in Wang et al., 2020 identified one individual with a likely-gene disruptive variant and 17 individuals with missense variants with CADD scores 30 in the KAT6B gene.

Molecular Function

The protein encoded by this gene is a histone acetyltransferase and component of the MOZ/MORF protein complex. In addition to its acetyltransferase activity, the encoded protein has transcriptional activation activity in its N-terminal end and transcriptional repression activity in its C-terminal end. This protein is necessary for RUNX2-dependent transcriptional activation and could be involved in brain development. Heterozygous mutations in KAT6B have been found in patients with genitopatellar syndrome (OMIM 606170) and SBBYSS syndrome (OMIM 603736).

External Links
Gene CardOpen Targets PlatformgnomAD browserPubMed
Human
Entrez GeneOMIMUniProtHumanBaseVariCarta
Mouse
Entrez GeneMouse Genome InformaticsAllen Brain Atlas
SFARI Genomic Platforms
GPF browser SFARI genome browser
Reports related to KAT6B (14 Reports)
# Type Title Author, Year Autism Report Associated Disorders
1 Support The contribution of de novo coding mutations to autism spectrum disorder Iossifov I et al. (2014) Yes -
2 Support Meta-analysis of 2,104 trios provides support for 10 new genes for intellectual disability Lelieveld SH et al. (2016) No -
3 Support Prevalence and architecture of de novo mutations in developmental disorders et al. (2017) No -
4 Support Exome sequencing of 457 autism families recruited online provides evidence for autism risk genes Feliciano P et al. (2019) Yes -
5 Primary Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders Wang T et al. (2020) Yes DD
6 Support - Yabumoto M et al. (2021) No ASD, ADHD, epilepsy/seizures
7 Support - Brea-Fernández AJ et al. (2022) No -
8 Support - Sheth F et al. (2023) Yes DD, ID, epilepsy/seizures
9 Recent Recommendation - Maria I Bergamasco et al. (2024) No -
10 Support - Ruohao Wu et al. (2024) Yes -
11 Support - Axel Schmidt et al. (2024) No Cognitive impairment
12 Support - Soo-Whee Kim et al. (2024) Yes -
13 Support - Hosneara Akter et al. () No -
14 Support - Maria I Bergamasco et al. (2024) No -
Rare Variants   (65)
Status Allele Change Residue Change Variant Type Inheritance Pattern Parental Transmission Family Type PubMed ID Author, Year
c.2347C>T p.Arg783Ter stop_gained Unknown - - 33004838 Wang T et al. (2020)
c.3373-2A>G - splice_site_variant De novo - Simplex 28135719 et al. (2017)
c.2347C>T p.Arg783Ter stop_gained De novo - Simplex 28135719 et al. (2017)
c.3887C>A p.Ser1296Ter stop_gained De novo - Simplex 28135719 et al. (2017)
c.5389C>T p.Arg1797Ter stop_gained De novo - Simplex 28135719 et al. (2017)
c.236G>A p.Arg79His missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.307C>T p.Arg103Cys missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.2348G>A p.Arg783Gln missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.2479C>T p.Arg827Trp missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.2696G>A p.Arg899His missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.3349C>T p.Gln1117Ter stop_gained De novo - - 34519438 Yabumoto M et al. (2021)
c.3580C>T p.Gln1194Ter stop_gained De novo - - 34519438 Yabumoto M et al. (2021)
c.5254C>T p.Gln1752Ter stop_gained De novo - - 34519438 Yabumoto M et al. (2021)
c.5389C>T p.Arg1797Ter stop_gained De novo - - 34519438 Yabumoto M et al. (2021)
c.3028C>T p.Arg1010Trp missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.3154C>T p.Arg1052Trp missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.3455C>T p.Thr1152Met missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.3760C>T p.Arg1254Cys missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.5390G>A p.Arg1797Gln missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.5837G>A p.Arg1946His missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.5870G>A p.Arg1957Gln missense_variant Unknown - - 33004838 Wang T et al. (2020)
c.3172C>T p.Arg1058Ter stop_gained De novo - - 39039281 Axel Schmidt et al. (2024)
c.5015G>C p.Ser1672Thr missense_variant De novo - Simplex 28135719 et al. (2017)
c.5041G>A p.Glu1681Lys missense_variant De novo - Simplex 28135719 et al. (2017)
c.2374-1G>A p.? splice_site_variant De novo - - 39334436 Soo-Whee Kim et al. (2024)
c.5327del p.Leu1776Ter frameshift_variant De novo - Simplex 28135719 et al. (2017)
c.3029G>A p.Arg1010Gln missense_variant Unknown - - 39342494 Hosneara Akter et al. ()
c.176C>G p.Ser59Ter stop_gained De novo - Simplex 27479843 Lelieveld SH et al. (2016)
c.104C>T p.Ala35Val missense_variant Familial Maternal - 33004838 Wang T et al. (2020)
c.2165_2166dup p.Ile723Ter frameshift_variant Unknown - - 33004838 Wang T et al. (2020)
c.1566+2T>A - splice_site_variant De novo - Simplex 27479843 Lelieveld SH et al. (2016)
c.626del p.Arg209LeufsTer41 frameshift_variant Unknown - - 33004838 Wang T et al. (2020)
c.1030C>T p.Arg344Ter stop_gained De novo - Simplex 27479843 Lelieveld SH et al. (2016)
c.5386G>C p.Glu1796Gln missense_variant Unknown - Simplex 37543562 Sheth F et al. (2023)
c.3409C>T p.Arg1137Cys missense_variant Familial Maternal - 33004838 Wang T et al. (2020)
c.3802G>A p.Gly1268Arg missense_variant Familial Maternal - 33004838 Wang T et al. (2020)
c.4834C>T p.Arg1612Cys missense_variant Familial Paternal - 33004838 Wang T et al. (2020)
c.3401del p.Gly1134ValfsTer11 frameshift_variant Unknown - - 33004838 Wang T et al. (2020)
c.2623C>T p.Asp875Tyr missense_variant De novo - Simplex 38764027 Ruohao Wu et al. (2024)
c.2190del p.Leu731SerfsTer34 frameshift_variant De novo - Simplex 28135719 et al. (2017)
c.2588del p.Leu863CysfsTer68 frameshift_variant De novo - Simplex 28135719 et al. (2017)
c.2852del p.Gly951ValfsTer11 frameshift_variant De novo - Simplex 28135719 et al. (2017)
c.3231C>A p.Asp1077Glu missense_variant De novo - Simplex 25363768 Iossifov I et al. (2014)
c.3201del p.Gly1068GlufsTer21 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.3553dup p.Glu1185GlyfsTer19 frameshift_variant Unknown - - 34519438 Yabumoto M et al. (2021)
c.4538dup p.Lys1514GlufsTer27 frameshift_variant Unknown - - 34519438 Yabumoto M et al. (2021)
c.3349_3350del p.Gln1117ValfsTer19 frameshift_variant Unknown - - 33004838 Wang T et al. (2020)
c.1507C>T p.Gln503Ter stop_gained Familial Paternal Simplex 31452935 Feliciano P et al. (2019)
c.2800_2801del p.Gln934ValfsTer19 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.3590_3591del p.Lys1197ArgfsTer6 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.4205_4206del p.Ser1402CysfsTer5 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.4368_4369dup p.Glu1457GlyfsTer5 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.3220_3223del p.Lys1075GlyfsTer13 frameshift_variant Unknown - - 34519438 Yabumoto M et al. (2021)
c.3413_3414del p.Gln1138ArgfsTer20 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.3532_3580dup p.Asn1194ArgfsTer26 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.3769_3772del p.Lys1258GlyfsTer13 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.4048_4054del p.Ala1350TrpfsTer14 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.4652_4661del p.Met1551LysfsTer87 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.3477_3480dup p.Asp1161LeufsTer2 frameshift_variant De novo - - 39039281 Axel Schmidt et al. (2024)
c.3769_3772delTCTA p.Lys1258GfsTer13 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.1946del p.Asn649MetfsTer27 frameshift_variant De novo - Simplex 27479843 Lelieveld SH et al. (2016)
c.2709del p.Glu904ArgfsTer27 frameshift_variant De novo - Simplex 27479843 Lelieveld SH et al. (2016)
c.3769_3772delTCTA p.Lys1258GlyfsTer13 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
c.3152del p.Ser1051ThrfsTer63 frameshift_variant De novo - - 35322241 Brea-Fernández AJ et al. (2022)
c.3918_3919insCAACAGG p.Ile1307GlnfsTer4 frameshift_variant De novo - - 34519438 Yabumoto M et al. (2021)
Common Variants  

No common variants reported.

SFARI Gene score
3

Suggestive Evidence

Score Delta: Score remained at 3

criteria met
See SFARI Gene'scoring criteria
3

Suggestive Evidence

See all Category 3 Genes

The literature is replete with relatively small studies of candidate genes, using either common or rare variant approaches, which do not reach the criteria set out for categories 1 and 2. Genes that had two such lines of supporting evidence were placed in category 3, and those with one line of evidence were placed in category 4. Some additional lines of "accessory evidence" (indicated as "acc" in the score cards) could also boost a gene from category 4 to 3.

4/1/2022
icon
3

Increased from to 3

Krishnan Probability Score

Score 0.56885486707029

Ranking 1088/25841 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 0.99999992257334

Ranking 189/18225 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
Iossifov Probability Score

Score 0.859

Ranking 183/239 scored genes


[Show Scoring Methodology]
Supplementary dataset S2 in the paper by Iossifov et al. (PNAS 112, E5600-E5607 (2015)) lists 239 genes with a probability of at least 0.8 of being associated with autism risk (column I). This probability metric combines the evidence from de novo likely-gene- disrupting and missense mutations and assesses it against the background mutation rate in unaffected individuals from the University of Washington’s Exome Variant Sequence database (evs.gs.washington.edu/EVS/). The list of probability scores can be found here: www.pnas.org/lookup/suppl/doi:10.1073/pnas.1516376112/- /DCSupplemental/pnas.1516376112.sd02.xlsx
Original Source
Sanders TADA Score

Score 0.94860557539956

Ranking 17752/18665 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 0.60615758996033

Ranking 70/20870 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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