FEZF2FEZ family zinc finger 2
Autism Reports / Total Reports
5 / 10Rare Variants / Common Variants
8 / 2Aliases
FEZF2, FEZ, FEZL, FKSG36, FLJ10142, TOF, ZFP312, ZNF312Associated Syndromes
-Chromosome Band
3p14.2Associated Disorders
-Relevance to Autism
Genetic association has been found between the FEZF2 gene and autism in two large cohorts (AGRE and ACC) of European ancestry and replicated in two other cohorts (CAP and CART) (Wang et al., 2009). In addition, a rare mutation in the FEZF2 gene has been identified in an individual with ASD (Sanders et al., 2012). A de novo loss-of-function variant in FEZF2 was identified in an ASD proband from the SPARK cohort in Feliciano et al., 2019; in the same report, a meta-analysis of de novo variants in 4773 published ASD trios and 465 SPARK trios using TADA identified FEZF2 as an ASD candidate gene with a q-value 0.1.
Molecular Function
Regulation of transcription
External Links
SFARI Genomic Platforms
Reports related to FEZF2 (10 Reports)
| # | Type | Title | Author, Year | Autism Report | Associated Disorders |
|---|---|---|---|---|---|
| 1 | Highly Cited | Zinc finger protein too few controls the development of monoaminergic neurons | Levkowitz G , et al. (2002) | No | - |
| 2 | Highly Cited | Fezl is required for the birth and specification of corticospinal motor neurons | Molyneaux BJ , et al. (2005) | No | - |
| 3 | Recent Recommendation | The Fezf2-Ctip2 genetic pathway regulates the fate choice of subcortical projection neurons in the developing cerebral cortex | Chen B , et al. (2008) | No | - |
| 4 | Recent Recommendation | SOX5 postmitotically regulates migration, postmigratory differentiation, and projections of subplate and deep-layer neocortical neurons | Kwan KY , et al. (2008) | No | - |
| 5 | Primary | Common genetic variants on 5p14.1 associate with autism spectrum disorders | Wang K , et al. (2009) | Yes | - |
| 6 | Support | De novo mutations revealed by whole-exome sequencing are strongly associated with autism | Sanders SJ , et al. (2012) | Yes | - |
| 7 | Positive Association | A genome-wide association study of autism incorporating autism diagnostic interview-revised, autism diagnostic observation schedule, and social responsiveness scale | Connolly JJ , et al. (2012) | Yes | - |
| 8 | Support | Clinical genomics expands the morbid genome of intellectual disability and offers a high diagnostic yield | Anazi S , et al. (2016) | No | - |
| 9 | Recent Recommendation | Exome sequencing of 457 autism families recruited online provides evidence for autism risk genes | Feliciano P et al. (2019) | Yes | - |
| 10 | Recent Recommendation | - | Alison Garber et al. (2024) | Yes | ADHD |
Rare Variants (8)
| Status | Allele Change | Residue Change | Variant Type | Inheritance Pattern | Parental Transmission | Family Type | PubMed ID | Author, Year |
|---|---|---|---|---|---|---|---|---|
| - | - | copy_number_loss | De novo | - | - | 38425142 | Alison Garber et al. (2024) | |
| c.1257C>A | p.Cys419Ter | stop_gained | De novo | - | - | 38425142 | Alison Garber et al. (2024) | |
| c.1030C>T | p.Arg344Cys | missense_variant | De novo | - | Simplex | 22495306 | Sanders SJ , et al. (2012) | |
| c.1193del | p.Phe398SerfsTer7 | frameshift_variant | De novo | - | - | 31452935 | Feliciano P et al. (2019) | |
| c.352dup | p.Ala118GlyfsTer67 | frameshift_variant | Unknown | - | - | 38425142 | Alison Garber et al. (2024) | |
| c.907dup | p.Arg303LysfsTer32 | frameshift_variant | De novo | - | - | 38425142 | Alison Garber et al. (2024) | |
| c.1030C>T | p.Arg344Cys | missense_variant | Familial | Paternal | Multiplex | 38425142 | Alison Garber et al. (2024) | |
| c.710_721del | p.Arg237_Ala240del | inframe_deletion | Familial | Both parents | Multiplex | 27431290 | Anazi S , et al. (2016) |
Common Variants (2)
| Status | Allele Change | Residue Change | Variant Type | Inheritance Pattern | Paternal Transmission | Family Type | PubMed ID | Author, Year |
|---|---|---|---|---|---|---|---|---|
| c.-1476A>G | - | 2KB_upstream_variant | - | - | - | 22935194 | Connolly JJ , et al. (2012) | |
| c.-1476A>G | C to T | 2KB_upstream_variant | - | - | - | 19404256 | Wang K , et al. (2009) |
SFARI Gene score
2
Strong Candidate
A single unreplicated association has been reported by Wang et al., 2009 (PMID: 19404256).
Score Delta: Score remained at 2
criteria met
See SFARI Gene'scoring criteriaWe 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
3
2
Decreased from 3 to 2
Description
A single unreplicated association has been reported by Wang et al., 2009 (PMID: 19404256).
10/1/2019
4
3
Decreased from 4 to 3
New Scoring Scheme
Description
A single unreplicated association has been reported by Wang et al., 2009 (PMID: 19404256).
7/1/2016
4
4
Decreased from 4 to 4
Description
A single unreplicated association has been reported by Wang et al., 2009 (PMID: 19404256).
7/1/2014
No data
4
Increased from No data to 4
Description
A single unreplicated association has been reported by Wang et al., 2009 (PMID: 19404256).
4/1/2014
No data
4
Increased from No data to 4
Description
A single unreplicated association has been reported by Wang et al., 2009 (PMID: 19404256).
Krishnan Probability Score
Score 0.57238848515629
Ranking 712/25841 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.
ExAC Score
Score 0.90203350358252
Ranking 3215/18225 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
Sanders TADA Score
Score 0.74810144667959
Ranking 1536/18665 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).
Larsen Cumulative Evidence Score
Score 15.5
Ranking 125/461 scored genes
[Show Scoring Methodology]
Larsen and colleagues generated gene scores based on the sum of evidence for all available
ASD-associated variants in a gene, with assessments based on mode of inheritance, effect size,
and variant frequency in the general population. The approach was first presented in Mol Autism
7:44 (2016), and scores for 461 genes can be found in column I in supplementary table 4 from
that paper.
Zhang D Score
Score 0.23517135705202
Ranking 3685/20870 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.