SFARI Gene 2.0: a community-driven knowledgebase for the autism spectrum disorders (ASDs)
Open accessAbstract
New technologies enabling genome-wide interrogation have led to a large and rapidly growing number of autism spectrum disorder (ASD) candidate genes. Although encouraging, the volume and complexity of these data make it challenging for scientists, particularly non-geneticists, to comprehensively evaluate available evidence for individual genes. Described here is the Gene Scoring module within SFARI Gene 2.0 ( https://gene.sfari.org/autdb/GS_Home.do ), a platform developed to enable systematic community driven assessment of genetic evidence for individual genes with regard to ASD.
AI snapshot
Written from the paper’s full text.
TL;DR
SFARI Gene 2.0 introduces a community-driven Gene Scoring module that systematically scores human genetic evidence for ASD candidate genes. In an initial 196-gene set, 58% fell into “Minimal Evidence,” and publication attention was only weakly related to evidence category.
Key findings
- Of 196 scored genes, 114 (58.2%) were assigned “Minimal Evidence” (category 4); no genes were placed in “High confidence” (category 1), while 5 (2.6%) were “Strong candidate” and 17 (8.7%) “Suggestive.”
- Publication attention was skewed: among syndromic genes discovered more than four years earlier (n = 17), two genes accounted for almost 50% of ASD-associated publications, while the eight least attended genes in that group collectively accounted for 8.4%.
- Almost half of genes with no or modest support (categories 4/5/6) had more ASD-associated publications than genes with more evidence (categories S/2/3); Table 1 shows syndromic genes had 714 observed versus 160 expected papers (4.4x), while minimal evidence genes had 360 observed versus 834 expected (0.4x).
- The resource includes explicitly defined scoring criteria, downloadable data, community score additions/proposals, and staff/advisory board oversight with versioning.
Methods
- Criteria were developed from a human genetics perspective to quantify evidence for ASD involvement, guided by three principles: use genetic variation in human cohorts, start with no assumptions about individual genes, and make active community involvement central.
- An initial set of 196 genes was scored and annotated in a gene-centric web interface; users with a SFARI login can add scores alongside curated calls, propose new genes, and suggest modifications to scoring criteria, with oversight by staff curators and the SFARI Gene Advisory Board.
- Attention analysis used manually curated publication counts containing “(autism OR autistic)” in the title or abstract; Figure 1 used the PubMed query “(autism OR autistic) AND (‘Gene symbol’)” in the title or abstract, and Table 1 compared observed papers to expected papers based on total observed papers across all categories (n = 1,434).
Limitations
- Stated: the scoring system is “not entirely immune to bias”; scores are not static and will change in the face of new data.
- Evident: the analysis covers only an initial set of 196 genes, and publication counts are used as a proxy for scientific attention; the paper does not report external validation of the scoring categories.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 8 cited sources checked · 0 supported · 0 flagged
- Findingown data
Within syndromic genes discovered more than four years ago (n = 17), two genes accounted for almost 50% of the ASD-associated publications.
“Within syndromic genes discovered more than four years ago (n = 17), for example, two genes accounted for almost 50% of the ASD-associated publications.”
Quote in the paperSubstantial claim - Findingown data
In the initial set of 196 scored genes, 58% were assigned to the "Minimal Evidence" category.
“A total of 58% of the scored genes, many having been highlighted elsewhere as top candidates, were assigned to the “Minimal Evidence” category.”
Quote in the paperSubstantial claim - Findingreasoning
Application of the criteria resulted in identification of genes which despite substantial support had received little or no attention from the field.
“Application of these criteria resulted in the identification of genes which despite substantial support had received little or no attention from the field.”
Quote in the paperSubstantial claim- Rests on an assumption: The scoring categories accurately reflect the strength of genetic evidence for ASD involvement.
- Findingown data
The eight least attended to from this group collectively accounted for only 8.4% of the publications.
“At the other extreme, the eight least attended to from this group collectively accounted for only 8.4% of the publications.”
Quote in the paperSubstantial claim - Findingown data
Almost half of the genes with no or relatively modest support (categories 4/5/6) have a greater number of ASD-associated publications than those with more evidence for involvement in disease (categories S/2/3).
“Finally, almost half of the genes with no or relatively modest support (categories 4/5/6) have a greater number of ASD-associated publications than those with more evidence for involvement in disease (categories S/2/3).”
Quote in the paperSubstantial claim
- Study design and conductreasoning
To minimize bias, the authors did not begin with any discussion or review of the literature, but rather established formalized criteria to quantify available support.
“To minimize bias, we did not begin with any discussion or review of the literature, but rather the establishment of formalized criteria to quantify available support.”
Quote in the paperSubstantial claim - Interpretationown data
The "winner takes most" effect, where two genes attracted almost 50% of the community's attention, is in direct conflict with a comprehensive understanding of autism genetics.
“This “winner takes most” effect, where two genes attracted almost 50% of the community’s attention, is in direct conflict with a comprehensive understanding of autism genetics.”
Quote in the paperSubstantial claim- Rests on an assumption: The number of manually curated publications containing “(autism OR autistic)” in the title or abstract is a valid measure of attention from the scientific community.
- Interpretationown data
There exists only modest support for the majority of autism-candidate genes proposed to date.
“Although scores are not static and will change in the face of new data, these data suggest that there exists only modest support for the majority of autism-candidate genes proposed to date.”
Quote in the paperSubstantial claim- Rests on an assumption: The initial set of 196 scored genes is representative of autism-candidate genes proposed to date.
- Interpretationown data
There is a relatively poor relationship or disconnect between genetic evidence and attention from the scientific community.
“These data highlight a relatively poor relationship between genetic evidence and attention from the scientific community.”
- Also stated in: § Letter to the Editor · plain
“Consistent with a disconnect between attention from the research community and evidence in support of individual genes, the number of publications for individual genes is highly variable and only weakly related to gene category.”
Quote in the paperSubstantial claim- Rests on an assumption: The number of manually curated publications containing “(autism OR autistic)” in the title or abstract is a valid measure of attention from the scientific community.
- Rests on an assumption: The scoring categories accurately reflect the strength of genetic evidence for ASD involvement.
- Also stated in: § Letter to the Editor · plain
- May combine two claims. 8
- Classified as probably not a substantial claim. 4
May combine two claims.
Findingown dataThe number of publications for individual genes is highly variable and only weakly related to gene category.
“Consistent with a disconnect between attention from the research community and evidence in support of individual genes, the number of publications for individual genes is highly variable and only weakly related to gene category.”
Quote in the paperSubstantial claim- Rests on an assumption: The number of manually curated publications containing “(autism OR autistic)” in the title or abstract is a valid measure of attention from the scientific community.
May combine two claims.
Findingown dataEnormous variability was observed both within and between gene categories, along with marked skewing towards specific genes within a given category.
“Enormous variability was observed both within and between categories, along with marked skewing towards specific genes within a given category (Figure 1).”
Quote in the paperSubstantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductnone givenThe scoring system is not entirely immune to bias, but evidence is examined and applied in a systemic fashion and is sensitive to community feedback.
“Although the scoring system we have developed is itself not entirely immune to bias, evidence is examined and applied in a systemic fashion and is sensitive to community feedback.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningSFARI Gene 2.0 allows registered users to add their own scores alongside curated calls, propose scores for new genes, and suggest modifications to scoring criteria.
“For genes already included in the portal, users with a SFARI login are able to add their own scores alongside curated calls (https://gene.sfari.org/autdb/search); these are viewable by the entire community in the form of “counts”.”
- Also stated in: § Letter to the Editor · plain
“Registered individuals are also able to propose scores for genes not yet included in the database (https://gene.sfari.org/autdb/user/AddAGene.do), and also suggest modifications to the scoring criteria.”
Quote in the paperSubstantial claim- Also stated in: § Letter to the Editor · plain
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Study design and conductnone givenExtensive safeguards, including staff and advisory board oversight, are in place to ensure the quality and utility of the resource.
“Extensive safeguards - including staff and advisory board oversight - are in place to ensure the quality and utility of the resource.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
Premisenone givenThe process of evaluating genes for ASD requires integration of diverse lines of support that are unequal.
“Further, this process requires the integration of diverse lines of support that are unequal.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenSFARI Gene 2.0 includes a mechanism enabling researchers to provide reasoned arguments for new genes, offer alternate scores, and suggest modifications to scoring criteria.
“Also new and unique to SFARI Gene 2.0 is a mechanism that enables researchers to provide reasoned arguments for the introduction of new genes, offer alternate scores that sit alongside existing ones, and provide suggestions for the modification of the scoring criteria.”
Quote in the paperSubstantial claimMay combine two claims.
Premisenone givenPrevious curated lists of genes implicated in ASDs and loosely defined evidence scores for entries are incomplete, non-systematic, and static.
“Previous work has crafted curated lists of genes implicated in autism spectrum disorders (ASDs) [1-5], and in some cases developed loosely defined “evidence scores” for entries [6-8]. Such efforts are incomplete, non-systematic and static.”
Quote in the paperSubstantial claim0 of 8 sources checked- cites [1] Basu SN, Kollu R, Banerjee-Basu S: AutDB: a gene reference resource for autism research. Nucleic Acids Res. 2009, 37: 832-836. 10.1093/nar/gkn941. source
Not checked in the free run.
- cites [2] Matuszek G, Talebizadeh Z: Autism Genetic Database (AGD): a comprehensive database including autism susceptibility gene-CNVs integrated with known noncoding RNAs and fragile sites. BMC Med Genet. 2009, 10: 102-10.1186/1471-2350-10-102. Epub 2009/09/26 source
Not checked in the free run.
- cites [3] Pinto D, Pagnamenta AT, Klei L, Anney R, Merico D, Regan R, Conroy J, Magalhaes TR, Correia C, Abrahams BS, Almeida J, Bacchelli E, Bader GD, Bailey AJ, Baird G, Battaglia A, Berney T, Bolshakova N, Bölte S, Bolton PF, Bourgeron T, Brennan S, Brian J, Bryson SE, Carson AR, Casallo G, Casey J, Chung BH, Cochrane L, Corsello C: Functional impact of global rare copy number variation in autism spectrum disorders. Nature. 2010, 466: 368-372. 10.1038/nature09146. source
Not checked in the free run.
- cites [4] Betancur C: Etiological heterogeneity in autism spectrum disorders: more than 100 genetic and genomic disorders and still counting. Brain Res. 2011, 1380: 42-77. source
Not checked in the free run.
- cites [5] Weiss LA, Arking DE, Daly MJ, Chakravarti A, Gene Discovery Project of Johns Hopkins & the Autism Consortium: A genome-wide linkage and association scan reveals novel loci for autism. Chakravarti A. Nature. 2009, 461 (7265): 802-808. source
Not checked in the free run.
- cites [6] Abrahams BS, Geschwind DH: Advances in autism genetics: on the threshold of a new neurobiology. Nat Rev Genet. 2008, 9 (5): 341-355. 10.1038/nrg2346. source
Not checked in the free run.
- cites [7] Abrahams BS, Geschwind DH: Genetics of autism. Vogel and Motulsky's Human Genetics: Problems & Approaches. Edited by: Speicher MR, Antonarakis SE, Motulsky AG. 2009, Berlin: Springer-Verlag, 699-714. 4
Not checked in the free run.
- cites [8] Xu LM, Li JR, Huang Y, Zhao M, Tang X, Wei L: AutismKB: an evidence-based knowledgebase of autism genetics. Nucleic Acids Res. 2012, 40: D1016-D1022. 10.1093/nar/gkr1145. source
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
InterpretationreasoningKey strengths of SFARI Gene 2.0 include explicitly defined scoring criteria, continuous updates, and infrastructure to permit community-based involvement.
“In summary, key strengths of SFARI Gene 2.0 include explicitly defined scoring criteria, continuous updates and infrastructure to permit community based involvement.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningSFARI Gene 2.0 differs from other efforts in philosophy, methodology, and output.
“Although similar in concept to other efforts, SFARI Gene 2.0 differs in terms of philosophy, methodology and output.”
Quote in the paperSubstantial claim
The paper relies on this without support.
Downstream work involves considerable resources.
“Given that downstream work involves considerable resources, a portal and framework enabling systematic assessments of all available evidence holds great value.”
The paper relies on this without support.
The initial set of 196 scored genes is representative of autism-candidate genes proposed to date.
“Using these newly developed criteria, we scored an initial set of 196 genes.”
“these data suggest that there exists only modest support for the majority of autism-candidate genes proposed to date.”
The paper relies on this without support.
The number of manually curated publications containing “(autism OR autistic)” in the title or abstract is a valid measure of attention from the scientific community.
“We then looked at the relationship between category placement and attention from the field, as defined by the number of manually curated publications containing “(autism OR autistic)” in the title or abstract.”
The paper relies on this without support.
The scoring categories accurately reflect the strength of genetic evidence for ASD involvement.
“Using a human genetics perspective, we developed a set of criteria to quantify evidence for involvement in the ASDs.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The ASD SFARI 2014 list comprises 235 genes from the SFARI AutDB database.
“(ii) 235 genes (ASD SFARI 2014) from the SFARI AutDB database22 (accessed on July 2014).”
From Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism (2014) · cites this paper as [22]
Cites
Functional impact of global rare copy number variation in autism spectrum disorders
Pinto, D., Pagnamenta, A. T., Klei, L., Anney, R., Merico, D., Regan, R., Conroy, J., Magalhaes, T. R., Correia, C., Abrahams, B. S., et al. (2010) · Nature · doi:10.1038/nature09146 · Cited by 2,013 · cited 1× · see citing works
“Letter to the Editor Previous work has crafted curated lists of genes implicated in autism spectrum disorders (ASDs) [1-5], and in some cases developed loosely defined “evidence scores” for entries [6-8].”
Self-citationAdvances in autism genetics: on the threshold of a new neurobiology
Abrahams, B. S., & Geschwind, D. H. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2346 · Cited by 1,866 · cited 1× · see citing works
“Letter to the Editor Previous work has crafted curated lists of genes implicated in autism spectrum disorders (ASDs) [1-5], and in some cases developed loosely defined “evidence scores” for entries [6-8].”
Self-citationBetancur, C. (2011) · Brain Research · doi:10.1016/j.brainres.2010.11.078 · Cited by 954 · cited 1× · see citing works
“Letter to the Editor Previous work has crafted curated lists of genes implicated in autism spectrum disorders (ASDs) [1-5], and in some cases developed loosely defined “evidence scores” for entries [6-8].”
A genome-wide linkage and association scan reveals novel loci for autism
The Gene Discovery Project of Johns Hopkins & the Autism Consortium, Weiss, L. A., & Arking, D. E. (2009) · Nature · doi:10.1038/nature08490 · Cited by 619 · cited 1× · see citing works
“Letter to the Editor Previous work has crafted curated lists of genes implicated in autism spectrum disorders (ASDs) [1-5], and in some cases developed loosely defined “evidence scores” for entries [6-8].”
Self-citationAutDB: a gene reference resource for autism research
Basu, S. N., Kollu, R., & Banerjee-Basu, S. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn835 · Cited by 394 · cited 1× · see citing works
“Letter to the Editor Previous work has crafted curated lists of genes implicated in autism spectrum disorders (ASDs) [1-5], and in some cases developed loosely defined “evidence scores” for entries [6-8].”
Self-citationAutismKB: an evidence-based knowledgebase of autism genetics
Xu, L.-M., Li, J.-R., Huang, Y., Zhao, M., Tang, X., & Wei, L. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1145 · Cited by 179 · cited 1× · see citing works
“Letter to the Editor Previous work has crafted curated lists of genes implicated in autism spectrum disorders (ASDs) [1-5], and in some cases developed loosely defined “evidence scores” for entries [6-8].”
Matuszek, G., & Talebizadeh, Z. (2009) · BMC Medical Genetics · doi:10.1186/1471-2350-10-102 · Cited by 48 · cited 1× · see citing works
“Letter to the Editor Previous work has crafted curated lists of genes implicated in autism spectrum disorders (ASDs) [1-5], and in some cases developed loosely defined “evidence scores” for entries [6-8].”
Vogel and Motulsky's Human Genetics: Problems and Approaches
Vogel, F., Motulsky, A. G., Speicher, M. R., et al. (1982) · Medical Entomology and Zoology · Cited by 33 · see citing works
Abrahams, B. S., & Geschwind, D. H. (2009) · Springer eBooks · doi:10.1007/978-3-540-37654-5_29 · Cited by 14 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex
Maynard, K. R., Collado-Torres, L., Weber, L. M., Uytingco, C., Barry, B. K., Williams, S. R., Catallini, J. L., Tran, M. N., Besich, Z., Tippani, M., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-020-00787-0 · Cited by 1,222 · see citing works
“(A) Autism spectrum disorder (ASD) laminar enrichments for SFARI (Abrahams et al., 2013) and Satterstrom et al (Satterstrom et al.”
BackgroundMethodInfluentialFOXG1-Dependent Dysregulation of GABA/Glutamate Neuron Differentiation in Autism Spectrum Disorders
Mariani, J., Coppola, G., Zhang, P., Abyzov, A., Provini, L., Tomasini, L., Amenduni, M., Szekely, A., Palejev, D., Wilson, M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.06.034 · Cited by 1,149 · see citing works
“…respect to the SFARI autism gene dataset, a collection of genetic information that includes data from linkage and association studies, cytogenetic abnormalities, and specific mutations associated with ASD (https://gene.sfari.org) (SFARI category S to 4) (Abrahams et al., 2013) (p value = 6.51E-5).”
Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice
Sharon, G., Cruz, N. J., Kang, D.-W., Gandal, M. J., Wang, B., Kim, Y.-M., Zink, E. M., Casey, C. P., Taylor, B. C., Lane, C. J., et al. (2019) · Cell · doi:10.1016/j.cell.2019.05.004 · Cited by 1,182 · see citing works
“We examined curated lists of high-confidence ASD risk genes, namely SPARK for Autism and the SFARI Gene datasets (Abrahams et al., 2013) (Figure 3C; Table S2).”
MethodSingle-cell genomics identifies cell type–specific molecular changes in autism
Velmeshev, D., Schirmer, L., Jung, D., Haeussler, M., Perez, Y., Mayer, S., Bhaduri, A., Goyal, N., Rowitch, D. H., & Kriegstein, A. R. (2019) · Science · doi:10.1126/science.aav8130 · Cited by 927 · see citing works
Gupta, S., Ellis, S. E., Ashar, F. N., Moes, A., Bader, J. S., Zhan, J., West, A. B., & Arking, D. E. (2014) · Nature Communications · doi:10.1038/ncomms6748 · Cited by 504 · see citing works
Self-citationTrevino, A. E., Müller, F., Andersen, J., Sundaram, L., Kathiria, A., Shcherbina, A., Farh, K., Chang, H. Y., Pașca, A. M., Kundaje, A., et al. (2021) · Cell · doi:10.1016/j.cell.2021.07.039 · Cited by 478 · see citing works
Excitation/Inhibition Imbalance in Animal Models of Autism Spectrum Disorders
Lee, E., Lee, J., & Kim, E. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.05.011 · Cited by 468 · see citing works
Zhou, X., Feliciano, P., Shu, C., Wang, T., Astrovskaya, I., Hall, J. B., Obiajulu, J. U., Wright, J. R., Murali, S. C., Xu, S. X., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01148-2 · Cited by 453 · see citing works
Krishnan, A., Zhang, R., Yao, V., Theesfeld, C. L., Wong, A. K., Tadych, A., Volfovsky, N., Packer, A. I., Lash, A., & Troyanskaya, O. G. (2016) · Nature Neuroscience · doi:10.1038/nn.4353 · Cited by 427 · see citing works
Self-citationFrom cohorts to molecules: adverse impacts of endocrine disrupting mixtures
Caporale, N., Leemans, M., Birgersson, L., Germain, P.-L., Cheroni, C., Borbély, G., Engdahl, E., Lindh, C., Bressan, R. B., Cavallo, F., et al. (2022) · Science · doi:10.1126/science.abe8244 · Cited by 368 · see citing works
Sugathan, A., Biagioli, M., Golzio, C., Erdin, S., Blumenthal, I., Manavalan, P., Ragavendran, A., Brand, H., Lucente, D., Miles, J., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1405266111 · Cited by 342 · see citing works
“0 (19) (574 genes) and AutismKB (20) (171genes; 117 overlap with SFARI) databases, both of which have established varying levels of support for an association with ASD of each gene included (see SI Materials and Methods for details on supporting evidence for these gene lists).”
BackgroundMethodSingle-cell transcriptomic analysis of mouse neocortical development
Loo, L., Simon, J. M., Xing, L., McCoy, E. S., Niehaus, J. K., Guo, J., Anton, E. S., & Zylka, M. J. (2019) · Nature Communications · doi:10.1038/s41467-018-08079-9 · Cited by 289 · see citing works
Methylomic trajectories across human fetal brain development
Spiers, H., Hannon, E., Schalkwyk, L. C., Smith, R., Wong, C. C. Y., O’Donovan, M. C., Bray, N. J., & Mill, J. (2015) · Genome Research · doi:10.1101/gr.180273.114 · Cited by 287 · see citing works
“…high-confidence candidate gene regions were selected from the Simons Foundation Autism Research Initiative (SFARI) gene database (Basu et al. 2009; Abrahams et al. 2013) and complemented by loci identified in recent exome sequencing and genomic studies (Neale et al. 2012; O’Roak et al. 2012a,b;…”
MethodBroad transcriptomic dysregulation occurs across the cerebral cortex in ASD
Gandal, M. J., Haney, J. R., Wamsley, B., Yap, C. X., Parhami, S., Emani, P. S., Chang, N., Chen, G. T., Hoftman, G. D., de Alba, D., et al. (2022) · Nature · doi:10.1038/s41586-022-05377-7 · Cited by 281 · see citing works
Fundamental Elements in Autism: From Neurogenesis and Neurite Growth to Synaptic Plasticity
Gilbert, J. P., & Man, H. (2017) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2017.00359 · Cited by 274 · see citing works
Histone Acetylome-wide Association Study of Autism Spectrum Disorder
Sun, W., Poschmann, J., Cruz-Herrera del Rosario, R., Parikshak, N. N., Hajan, H. S., Kumar, V., Ramasamy, R., Belgard, T. G., Elanggovan, B., Wong, C. C. Y., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.031 · Cited by 306 · see citing works
“DNA sequence variation affecting the function of several hundred genes has been implicated in the etiology of ASD at various levels of significance (Abrahams et al., 2013; de la Torre-Ubieta et al., 2016).”
Molecular and cellular evolution of the primate dorsolateral prefrontal cortex
Ma, S., Škarica, M., Li, Q., Xu, C., Risgaard, R. D., Tebbenkamp, A. T. N., Mato-Blanco, X., Kovner, R., Krsnik, Ž., de Martin, X., et al. (2022) · Science · doi:10.1126/science.abo7257 · Cited by 256 · see citing works
Artificial intelligence for precision medicine in neurodevelopmental disorders
Uddin, M. J., Wang, Y., & Woodbury‐Smith, M. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0191-0 · Cited by 257 · see citing works
Genomics, convergent neuroscience and progress in understanding autism spectrum disorder
Willsey, H. R., Willsey, A. J., Wang, B., & State, M. W. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00576-7 · Cited by 229 · see citing works
Mighell, T. L., Evans-Dutson, S., & O’Roak, B. J. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.03.018 · Cited by 204 · see citing works
Chd8 mediates cortical neurogenesis via transcriptional regulation of cell cycle and Wnt signaling
Durak, O., Gao, F., Kaeser-Woo, Y. J., Rueda, R., Martorell, A. J., Nott, A., Liu, C. Y., Watson, L. A., & Tsai, L.-H. (2016) · Nature Neuroscience · doi:10.1038/nn.4400 · Cited by 243 · see citing works
Widespread RNA editing dysregulation in brains from autistic individuals
Tran, S. S., Jun, H.-I., Bahn, J. H., Azghadi, A., Ramaswami, G., Nostrand, E. L. V., Nguyen, T. B., Hsiao, Y.-H. E., Lee, C., Pratt, G. A., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0287-x · Cited by 213 · see citing works
MVP predicts the pathogenicity of missense variants by deep learning
Qi, H., Zhang, H., Zhao, Y., Chen, C., Long, J. J., Chung, W. K., Guan, Y., & Shen, Y. (2021) · Nature Communications · doi:10.1038/s41467-020-20847-0 · Cited by 198 · see citing works
VarCards: an integrated genetic and clinical database for coding variants in the human genome
Li, J., Shi, L., Zhang, K., Zhang, Y., Hu, S., Zhao, T., Teng, H., Li, X., Jiang, Y. W., Ji, L., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1039 · Cited by 197 · see citing works
Sequence features associated with the cleavage efficiency of CRISPR/Cas9 system
Liu, X., Homma, A., Sayadi, J. J., Yang, S., Ohashi, J., & Takumi, T. (2016) · Scientific Reports · doi:10.1038/srep19675 · Cited by 199 · see citing works
Single-cell analysis of prenatal and postnatal human cortical development
Velmeshev, D., Perez, Y., Yan, Z., Valencia, J. E., Castaneda-Castellanos, D. R., Wang, L., Schirmer, L., Mayer, S., Wick, B., Wang, S., et al. (2023) · Science · doi:10.1126/science.adf0834 · Cited by 204 · see citing works
Ancestry-inclusive dog genomics challenges popular breed stereotypes
Morrill, K. M., Hekman, J. P., Li, X., McClure, J., Logan, B., Goodman, L., Gao, M., Dong, Y., Alonso, M., Carmichael, E., et al. (2022) · Science · doi:10.1126/science.abk0639 · Cited by 196 · see citing works
“4% of 2155 dogs in the genetic dataset) were funded by owner donations to the Darwin’s Ark Foundation, a 501(c)(3) nonprofit organization (82-3942341).”
BackgroundLombardo, M. V., Moon, H. M., Su, J., Palmer, T. D., Courchesne, E., & Pramparo, T. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.15 · Cited by 201 · see citing works
“We then further considered ASD-associated gene classes separated by the expert manually curated categories in the SFARI Gene database (http://gene.sfari.org/) 68,69 (see Supplementary Table S1 for gene lists).”
Autism spectrum disorder: insights into convergent mechanisms from transcriptomics
Quesnel-Vallières, M., Weatheritt, R. J., Cordes, S. P., & Blencowe, B. J. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0066-2 · Cited by 160 · see citing works
Zhang, Y., Li, N., Li, C., Zhang, Z., Teng, H., Wang, Y., Zhao, T., Shi, L., Zhang, K., Xia, K., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-0699-8 · Cited by 177 · see citing works
A functional cellular framework for sex and estrous cycle-dependent gene expression and behavior
Knoedler, J. R., Inoue, S., Bayless, D. W., Yang, T., Tantry, A., Davis, C.-H. O., Leung, N. Y., Parthasarathy, S., Wang, G., Alvarado, M., et al. (2022) · Cell · doi:10.1016/j.cell.2021.12.031 · Cited by 165 · see citing works
Deneault, E., White, S. H., Rodrigues, D. C., Ross, P. J., Faheem, M., Zaslavsky, K., Wang, Z., Alexandrova, R., Pellecchia, G., Wei, W., et al. (2018) · Stem Cell Reports · doi:10.1016/j.stemcr.2018.10.003 · Cited by 145 · see citing works
“For this, we used a proprietary list of 736 genes (highlighted in blue in Table S7) associated with ASD (Abrahams et al., 2013; Pinto et al., 2014; Yuen et al., 2017).”
MethodSingle-cell genomics and regulatory networks for 388 human brains
Emani, P. S., Liu, J. J., Clarke, D., Jensen, M., Warrell, J., Gupta, C., Meng, R., Lee, C.-Y., Xu, S., Dursun, C., et al. (2024) · Science · doi:10.1126/science.adi5199 · Cited by 168 · see citing works
Molecular and network-level mechanisms explaining individual differences in autism spectrum disorder
Buch, A. M., Vértes, P. E., Seidlitz, J., Kim, S. H., Grosenick, L., & Liston, C. M. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01259-x · Cited by 156 · see citing works
Cerebellar associative sensory learning defects in five mouse autism models
Kloth, A. D., Badura, A., Li, A., Cherskov, A., Connolly, S. G., Giovannucci, A., Bangash, M. A., Grasselli, G., Peñagarikano, O., Piochon, C., et al. (2015) · eLife · doi:10.7554/elife.06085 · Cited by 144 · see citing works
“We examined five mouse models that both recapitulate mutations that occur in human idiopathic and syndromic autisms and display phenotypes reminiscent of human autism (Abrahams and Geschwind, 2008; Banerjee-Basu and Packer, 2010; Abrahams et al., 2013; http://gene.sfari.org).”
BackgroundPhan, B. N., Bohlen, J. F., Davis, B. A., Ye, Z., Chen, H.-Y., Mayfield, B., Sripathy, S. R., Page, S. C., Campbell, M. N., Smith, H. L., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-019-0578-x · Cited by 144 · see citing works
Wen, Y., Alshikho, M. J., & Herbert, M. R. (2016) · PLOS ONE · doi:10.1371/journal.pone.0153329 · Cited by 150 · see citing works
“strength of evidence for inclusion, the Gene Scoring module presently under development for this database that would correct for this [54] is not yet completed, with many genes still unscored, so that there is not yet a systematic, consensual way to correct for this problem.”
BackgroundRed fox genome assembly identifies genomic regions associated with tame and aggressive behaviours
Kukekova, A. V., Johnson, J. L., Xiang, X., Feng, S., Liu, S., Rando, H. M., Kharlamova, A. V., Herbeck, Y., Serdyukova, N. A., Xiong, Z., et al. (2018) · Nature Ecology & Evolution · doi:10.1038/s41559-018-0611-6 · Cited by 145 · see citing works
Genetic and Epigenetic Etiology Underlying Autism Spectrum Disorder
Yoon, S. H., Choi, J., Lee, W. Y., & Do, J. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9040966 · Cited by 156 · see citing works
“According to the Simons Foundation Autism Research Initiative (SFARI) database [154], 913 genes and 17 recurrent CNV loci are suggested to be implicated with autism.”
MethodMolecular and cellular dynamics of the developing human neocortex
Wang, L., Wang, C., Moriano, J., Chen, S., Zuo, G., Cebrián‐Silla, A., Zhang, S., Mukhtar, T., Wang, S., Song, M., et al. (2025) · Nature · doi:10.1038/s41586-024-08351-7 · Cited by 173 · see citing works
“Among the core TFs of the top ten eRegulons correlated with ASD, six were recognized as ASD-risk genes in the SFARI gene database 46 .”
A framework for an evidence-based gene list relevant to autism spectrum disorder
Schaaf, C. P., Betancur, C., Yuen, R. K. C., Parr, J. R., Skuse, D., Gallagher, L., Bernier, R., Buchanan, J. A., Buxbaum, J. D., Chen, C., et al. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0231-2 · Cited by 137 · see citing works
Abdelli, L. S., Samsam, A., & Naser, S. A. (2019) · Scientific Reports · doi:10.1038/s41598-019-45348-z · Cited by 145 · see citing works
Leblond, C. S., Le, T.-L., Malesys, S., Cliquet, F., Tabet, A., Delorme, R., Rolland, T., & Bourgeron, T. (2021) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2021.103623 · Cited by 137 · see citing works
Blumenthal, I., Ragavendran, A., Erdin, S., Klei, L., Sugathan, A., Guide, J. R., Manavalan, P., Zhou, J. Q., Wheeler, V. C., Levin, J. Z., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.05.004 · Cited by 145 · see citing works
DNA Methylation and Susceptibility to Autism Spectrum Disorder
Tremblay, M. W., & Jiang, Y. (2019) · Annual Review of Medicine · doi:10.1146/annurev-med-120417-091431 · Cited by 132 · see citing works
Androgens increase excitatory neurogenic potential in human brain organoids
Kelava, I., Chiaradia, I., Pellegrini, L., Kalinka, A. T., & Lancaster, M. A. (2022) · Nature · doi:10.1038/s41586-021-04330-4 · Cited by 123 · see citing works
Gazestani, V., Pramparo, T., Nalabolu, S. R., Kellman, B. P., Murray, S. S., Lopez, L., Pierce, K., Courchesne, E., & Lewis, N. E. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0489-x · Cited by 109 · see citing works
Genome‐wide Association Study of Autism Spectrum Disorder in the East Asian Populations
Liu, X., Shimada, T., Otowa, T., Wu, Y., Kawamura, Y., Tochigi, M., Iwata, Y., Umekage, T., Toyota, T., Maekawa, M., et al. (2015) · Autism Research · doi:10.1002/aur.1536 · Cited by 115 · see citing works
“Out of the 14 genome wide significant genes, 5 genes (GPC6, JARID2, YTHDC2, CNTN4, and CSMD1) are known ASD associated genes based on the SFARI ASD database [Abrahams et al., 2013; Banerjee-Basu & Packer, 2010], suggesting the overall results are unlikely to be caused by false associations.”
BackgroundWells, M. F., Nemesh, J., Ghosh, S., Mitchell, J. M., Salick, M. R., Mello, C. J., Meyer, D., Pietilainen, O., Piccioni, F., Guss, E. J., et al. (2023) · Cell Stem Cell · doi:10.1016/j.stem.2023.01.010 · Cited by 116 · see citing works
Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortexPreprint
Maynard, K. R., Collado‐Torres, L., Weber, L. M., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.28.969931 · Cited by 119 · see citing works
Lombardo, M. V., Pramparo, T., Gazestani, V., Warrier, V., Bethlehem, R. A. I., Barnes, C. C., Lopez, L., Lewis, N. E., Eyler, L. T., Pierce, K., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0281-3 · Cited by 95 · see citing works
Bayesian estimation of cell type–specific gene expression with prior derived from single-cell dataPreprint
Wang, J., Roeder, K., & Devlin, B. (2021) · Genome Research · doi:10.1101/gr.268722.120 · Cited by 86 · see citing works
“…CTS DEGs, six genes (GFAP, NRXN1, LRRC4C, KCNMA1, RORB, SLC6A1) were among the 102 ASD risk genes discovered by Satterstrom et al. (2020) (Fisher’s exact test P-value = 0.04) and 49 genes were among the SFARI autism gene list (Abrahams et al. 2013) (Fisher’s exact test P-value = 2.5 ×10−9).”
BackgroundInfluentialLi, J., Wang, L., Guo, H., Shi, L., Zhang, K., Tang, M., Hu, S., Dong, S., Liu, Y., Wang, T., et al. (2017) · Molecular Psychiatry · doi:10.1038/mp.2017.140 · Cited by 97 · see citing works
Frequency and complexity of de novo structural mutation in autism
Brandler, W. M., Antaki, D., Gujral, M., Noor, A., Rosanio, G., Chapman, T. R., Barrera, D. J., Lin, G. N., Malhotra, D., Watts, A. C., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.02.018 · Cited by 104 · see citing works
“2 (MIM: 615656).(36) Inherited X-linked variants included a Xp21.”
BackgroundLi, J., Wilkinson, B., Clementel, V. A., Hou, J., O’Dell, T. J., & Coba, M. P. (2016) · Science Signaling · doi:10.1126/scisignal.aaf6716 · Cited by 95 · see citing works
Rbfox1 Mediates Cell-type-Specific Splicing in Cortical Interneurons
Wamsley, B., Jaglin, X. H., Favuzzi, E., Quattrocolo, G., Nigro, M. J., Yusuf, N., Khodadadi‐Jamayran, A., Rudy, B., & Fishell, G. (2018) · Neuron · doi:10.1016/j.neuron.2018.09.026 · Cited by 100 · see citing works
Coexpression networks identify brain region–specific enhancer RNAs in the human brain
Yao, P., Lin, P., Gokoolparsadh, A., Assareh, A. A., Thang, M. W. C., & Voineagu, I. (2015) · Nature Neuroscience · doi:10.1038/nn.4063 · Cited by 91 · see citing works
Jourdon, A., Wu, F., Mariani, J., Capauto, D., Norton, S., Tomasini, L., Amiri, A., Šuvakov, M., Schreiner, J. D., Jang, Y., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01399-0 · Cited by 103 · see citing works
Wilkinson, B., Grepo, N., Thompson, B. L., Kim, J. Y., Wang, K., Evgrafov, O. V., Lu, W., Knowles, J. A., & Campbell, D. B. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.62 · Cited by 101 · see citing works
Self-citationPathogenic POGZ mutation causes impaired cortical development and reversible autism-like phenotypes
Matsumura, K., Seiriki, K., Okada, S., Nagase, M., Ayabe, S., Yamada, I., Furuse, T., Shibuya, H., Yasuda, Y., Yamamori, H., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-14697-z · Cited by 106 · see citing works
Xiong, F., Wang, R., Lee, J.-H., Li, S., Chen, S.-F., Liao, Z., Hasani, L. A., Nguyen, P. T.-M., Zhu, X., Krakowiak, J., et al. (2021) · Cell Research · doi:10.1038/s41422-021-00515-8 · Cited by 96 · see citing works
Pharmacological modulation of AMPA receptor rescues social impairments in animal models of autism
Kim, J., Park, K., Kang, R. J., Gonzales, E. L., Kim, D. G., Oh, H. A., Seung, H., Ko, M. J., Kwon, K. J., Kim, K. C., et al. (2018) · Neuropsychopharmacology · doi:10.1038/s41386-018-0098-5 · Cited by 106 · see citing works
Warre-Cornish, K. M., Perfect, L., Nagy, R., Duarte, R. R. R., Reid, M. J., Raval, P., Mueller, A., Evans, A., Couch, A. C. M., Ghevaert, C., et al. (2020) · Science Advances · doi:10.1126/sciadv.aay9506 · Cited by 96 · see citing works
Lalli, M. A., Avey, D. R., Dougherty, J. D., Milbrandt, J., & Mitra, R. D. (2020) · Genome Research · doi:10.1101/gr.262295.120 · Cited by 89 · see citing works
“To establish that LUHMES cells are an appropriate model specifically for the study of ASD genes, we analyzed 25 high-confidence autism-causing genes in the SFARI database, a manually curated database of ASD-associated genes (Abrahams et al. 2013).”
Quartier, A., Chatrousse, L., Redin, C. E., Keime, C., Haumesser, N., Maglott, A., Brino, L., Gras, S. L., Benchoua, A., Mandel, J., et al. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.01.002 · Cited by 86 · see citing works
Taleb, A., Lin, W., Xu, X., Zhang, G., Zhou, Q., Naveed, M., Meng, F. J., Fukunaga, K., & Han, F. (2021) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2021.111322 · Cited by 99 · see citing works
Decomposition of phenotypic heterogeneity in autism reveals underlying genetic programs
Litman, A., Sauerwald, N., Snyder, L. G., Foss‐Feig, J. H., Park, C. Y., Hao, Y., Dinstein, I., Theesfeld, C. L., & Troyanskaya, O. G. (2025) · Nature Genetics · doi:10.1038/s41588-025-02224-z · Cited by 116 · see citing works
“The SFARI gene set was extracted from SFARIGene and included category 1 genes only 19,22 .”
Asif, M., Martiniano, H., Vicente, A. M., & Couto, F. M. (2018) · PLoS ONE · doi:10.1371/journal.pone.0208626 · Cited by 90 · see citing works
“The standard criteria for ranking ASD genes by available reference is not yet completely defined [29], and, therefore, it is possible that incorporating weighting criteria for genes could introduce a bias.”
BackgroundChristian, D. L., Wu, D. Y., Martin, J. R., Moore, J. R., Liu, Y. R., Clemens, A. W., Nettles, S. A., Kirkland, N. M., Papouin, T., Hill, C. A., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108416 · Cited by 78 · see citing works
“Gene sets: ASD module 12 (synaptic) and 16 (immune) identified in weighted-gene coexpression analysis of human ASD brain (Voineagu et al., 2011), and ASD-dysregulated genes previously identified (Abrahams et al., 2013; Gandal et al., 2018).”
BackgroundBoth rare and common genetic variants contribute to autism in the Faroe Islands
Leblond, C. S., Cliquet, F., Carton-Buonafine, C., Huguet, G., Mathieu, A., Kergrohen, T., Buratti, J., Lemière, N., Cuisset, L., Bienvenu, T., et al. (2019) · npj Genomic Medicine · doi:10.1038/s41525-018-0075-2 · Cited by 83 · see citing works
Distinct Roles of Honeybee Gut Bacteria on Host Metabolism and Neurological Processes
Zhang, Z., Mu, X., Shi, Y., & Zheng, H. (2022) · Microbiology Spectrum · doi:10.1128/spectrum.02438-21 · Cited by 91 · see citing works
Zhu, Y., Mordaunt, C. E., Yasui, D. H., Marathe, R., Coulson, R. L., Dunaway, K. W., Jianu, J. M., Walker, C. K., Ozonoff, S. J., Hertz‐Picciotto, I., et al. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddz084 · Cited by 85 · see citing works
Guo, D., Yang, X., & Shi, L. (2020) · Cells · doi:10.3390/cells9040835 · Cited by 73 · see citing works
First glimpses of the neurobiology of autism spectrum disorder
Sanders, S. J. (2015) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2015.10.002 · Cited by 84 · see citing works
Kalish, B. T., Cheadle, L., Hrvatin, S., Nagy, M. A., Rivera, S. A., Crow, M., Gillis, J. A., Kirchner, R. D., & Greenberg, M. E. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1717871115 · Cited by 68 · see citing works
“Our study complements and extends this prior work by focusing on the developing LGN, profiling multiple developmental conditions, and characterizing multiple nonneuronal cell types, including astrocytes, microglia, and endothelial cells (93, 94).”
ResultSaliva MicroRNA Differentiates Children With Autism From Peers With Typical and Atypical Development
Hicks, S. D., Carpenter, R. L., Wagner, K. E., Pauley, R. A., Barros, M., Tierney‐Aves, C., Barns, S., Greene, C. D., & Middleton, F. A. (2019) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2019.03.017 · Cited by 80 · see citing works
Protein phosphatase 2A – structure, function and role in neurodevelopmental disorders
Sandal, P., Jong, C. J., Merrill, R. A., Song, J., & Strack, S. (2021) · Journal of Cell Science · doi:10.1242/jcs.248187 · Cited by 72 · see citing works
Deep evolutionary conservation of autism-related genes
Shpigler, H. Y., Saul, M. C., Corona, F., Block, L. N., Cash-Ahmed, A. C., Zhao, S. D., & Robinson, G. E. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1708127114 · Cited by 70 · see citing works
“Honey bee control gene sets were derived from two RNA-seq expression sets from honey bee MB: (i) DEGs comparing active and inactive male honey bees (44) and (ii) DEGs comparing worker bees trained to forage at specific times of day (45).”
BackgroundMethodResultInfluentialWilliams, S. M., An, J., Edson, J., Watts, M. E., Murigneux, V., Whitehouse, A., Jackson, C. J., Bellgrove, M. A., Cristino, A. S., & Claudianos, C. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0049-x · Cited by 75 · see citing works
Terry, D. M., & Devine, S. E. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2019.01244 · Cited by 71 · see citing works
Landscape of mSWI/SNF chromatin remodeling complex perturbations in neurodevelopmental disorders
Valencia, A. M., Sankar, A., van der Sluijs, P. J., Satterstrom, F. K., Fu, J. M., Talkowski, M. E., Vergano, S. A. S., Santen, G. W. E., & Kadoch, C. (2023) · Nature Genetics · doi:10.1038/s41588-023-01451-6 · Cited by 77 · see citing works
Casingal, C. R., Kikkawa, T., Inada, H., Sasaki, Y., & Osumi, N. (2020) · Molecular Brain · doi:10.1186/s13041-020-00706-1 · Cited by 69 · see citing works
Spatial transcriptomics reveals human cortical layer and area specification
Qian, X., Coleman, K., Jiang, S., Kriz, A. J., Marciano, J. H., Luo, C., Cai, C., Manam, M. D., Caglayan, E., Lai, A., et al. (2025) · Nature · doi:10.1038/s41586-025-09010-1 · Cited by 96 · see citing works
Wang, W., Corominas, R., & Lin, G. N. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00258 · Cited by 70 · see citing works
“Some disease-related gene databases as ASD genes database SFARI (Abrahams et al., 2013) have introduced a scoring parameter that ranks from high confidence to hypothesized but untested, which is extremely useful to evaluate the association of a variant within these genes to the neuropsychiatric phenotype.”
BackgroundGriesi‐Oliveira, K., Fogo, M. S., Pinto, B. G. G., Alves, A. Y., Suzuki, Â. M., Morales, A. G., Ezquina, S., Sosa, J., Sutton, G. J., Sunaga, D. Y., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0669-9 · Cited by 76 · see citing works
Paternò, R., Marafiga, J. R., Ramsay, H. J., Li, T., Salvati, K. A., & Baraban, S. C. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109970 · Cited by 71 · see citing works
“Genome-wide association studies on these patients indicate a genetic basis spanning hundreds of different risk genes (Abrahams et al., 2013; Iakoucheva et al., 2019).”
Identification of 22q13 genes most likely to contribute to Phelan McDermid syndrome
Mitz, A. R., Philyaw, T. J., Boccuto, L., Shcheglovitov, A., Sarasua, S. M., Kaufmann, W. E., & Thurm, A. E. (2018) · European Journal of Human Genetics · doi:10.1038/s41431-017-0042-x · Cited by 70 · see citing works
“We used curated databases and genome-wide association studies (GWAS) for both functional discovery and likelihood of contribution of neuropsychiatricneurodevelopmental genes by locating PMS genes found in the following sources: Class I–III Genes from ASD quartets [38], TADA-65 genes [39], Category S and Category 1–3 S…”
MethodChung, C., Ha, S., Kang, H., Lee, J., Um, S. M., Yan, H., Yoo, Y.-E., Yoo, T., Jung, H., Lee, D., et al. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.09.025 · Cited by 73 · see citing works
“While the number of candidate ASD-risk genes is rapidly increasing (1), our understanding of the underlying mechanisms has lagged, partly because of the intrinsic heterogeneity and complexity of causal mechanisms in different brain regions at different developmental times.”
Zhang, K., Fang, Y., Zhu, J. K., Han, S., Chen, J., Wu, X., Chen, Y., Shen, T., Liao, J., Guo, W., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.03.085 · Cited by 66 · see citing works
Chen, Y., Chen, C.-Y., Mai, T., Chuang, C.-F., Chen, Y., Gupta, S. K., Yen, L., Wang, Y.-D., & Chuang, T. (2020) · Genome Research · doi:10.1101/gr.255463.119 · Cited by 67 · see citing works
“For empirical gene enrichment analysis in the right panel of Figure 3C, we asked whether the targets of the identified circRNA-miRNA-mRNA interaction (2299 genes) had a higher proportion (proportionobs) of the disease-related gene lists (e.g., SFARI genes) compared to a null distribution of the proportion observed in…”
BackgroundMethodInfluentialIdentification of FMR1-regulated molecular networks in human neurodevelopmentPreprint
Li, M., Shin, J., Risgaard, R. D., Parries, M., Wang, J., Chasman, D. A., Liu, S., Roy, S., Bhattacharyya, A., & Zhao, X. (2020) · Genome Research · doi:10.1101/gr.251405.119 · Cited by 71 · see citing works
“The SFARI human autistic gene set (SFARI-Gene_genes_export18-12-2017.csv) was downloaded from https://gene.sfari.org/.”
InfluentialAnder, B. P., Barger, N., Stamova, B. S., Sharp, F. R., & Schumann, C. M. (2015) · Molecular Autism · doi:10.1186/s13229-015-0029-9 · Cited by 68 · see citing works
“(139 genes) [34] and the SFARI database of positively associated ASD genes (573 genes) [35].”
BackgroundEpigenomic signatures reveal mechanistic clues and predictive markers for autism spectrum disorder
LaSalle, J. M. (2023) · Molecular Psychiatry · doi:10.1038/s41380-022-01917-9 · Cited by 79 · see citing works
“This group represents over 800 proteins encoded in the mammalian genome [149] and many known ASD risk genes [45, 150].”
BackgroundCopy number variants in autism spectrum disorders
Vicari, S., Napoli, E., Cordeddu, V., Menghini, D., Alesi, V., Loddo, S., Novelli, A., & Tartaglia, M. (2019) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2019.02.012 · Cited by 76 · see citing works
Dougnon, G., & Matsui, H. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23147550 · Cited by 71 · see citing works
“do, accessed on 10 May 2022), to date, more an 281 genes have been used to explor ASD phenotypes in mouse models [97].”
Parallel social information processing circuits are differentially impacted in autism
Lewis, E. M., Stein-O’Brien, G. L., Patino, A. V., Nardou, R., Grossman, C. D., Brown, M., Bangamwabo, B., Ndiaye, N., Giovinazzo, D., Dardani, I., et al. (2020) · Neuron · doi:10.1016/j.neuron.2020.10.002 · Cited by 72 · see citing works
Qiu, S.-F., Lu, Z.-M., & Levitt, P. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.2580-14.2014 · Cited by 69 · see citing works
“…MET as a risk factor for autism sprectrum disorder (ASD), a highly heritable psychiatric disorder with disrupted ontogeny of neural connectivity (Campbell et al., 2006, 2007; Geschwind and Levitt, 2007; Jackson et al., 2009; Sousa et al., 2009; Thanseem et al., 2010; Abrahams et al., 2013).”
BackgroundBrain-specific functional relationship networks inform autism spectrum disorder gene prediction
Duda, M., Zhang, H., Li, H., Wall, D. P., Burmeister, M., & Guan, Y. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0098-6 · Cited by 63 · see citing works
Wenderski, W., Wang, L., Krokhotin, A., Walsh, J. J., Li, H., Shoji, H., Ghosh, S. G., George, R. D., Miller, E. L., Elias, L., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1908238117 · Cited by 59 · see citing works
“Among the most frequently mutated genes in ASD are subunits of the mammalian SWI/SNF (BAF) ATPdependent chromatin remodeling complex (4).”
BackgroundPost, K. L., Belmadani, M., Ganguly, P., Meili, F., Dingwall, R., McDiarmid, T. A., Meyers, W. M., Herrington, C., Young, B. P., Callaghan, D. B., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15943-0 · Cited by 58 · see citing works
- Authors
- Abrahams, B. S., Arking, D. E., Campbell, D. B., Mefford, H. C., Morrow, E. M., Weiss, L. A., Menashe, I., Wadkins, T., Banerjee-Basu, S., & Packer, A.
- Affiliations
- Albert Einstein College of Medicine (US)
- Johns Hopkins University (US)
- University of Southern California (US)
- University of Washington (US)
- Brown University (US)
- University of California, San Francisco (US)
- Ben-Gurion University of the Negev (IL)
- MindSpec (US)
- Simons Foundation (US)
- Corresponding author
- Packer, Alan
- Venue
- Molecular Autism
- Published
- 2013-10-03
- Volume
- 4
- Issue
- 1
- Pages
- 36-36
- ISSN
- 2040-2392 (ISSN-L)
- PMC
- PMC3851189
- OpenAlex
- W2168950294
- Cited by
- 873
- References
- 9
- Citations by year
- 2026: 103 · 2025: 115 · 2024: 79 · 2023: 94 · 2022: 110 · 2021: 95 · 2020: 89 · 2019: 60 · 2018: 46 · 2017: 31 · 2016: 26 · 2015: 12 · 2014: 10 · 2013: 1
- FWCI
- 8.92
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Molecular Autism (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Simons Foundation
- Simons Foundation Autism Research Initiative
- National Institute of Mental Health (R01MH100027)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- autism spectrum disorder, candidate genes, autism genetics, evidence evaluation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
