The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
De novo mutations revealed by whole-exome sequencing are strongly associated with autism
Open accessAbstract
Multiple studies have confirmed the contribution of rare de novo copy number variations to the risk for autism spectrum disorders. But whereas de novo single nucleotide variants have been identified in affected individuals, their contribution to risk has yet to be clarified. Specifically, the frequency and distribution of these mutations have not been well characterized in matched unaffected controls, and such data are vital to the interpretation of de novo coding mutations observed in probands. Here we show, using whole-exome sequencing of 928 individuals, including 200 phenotypically discordant sibling pairs, that highly disruptive (nonsense and splice-site) de novo mutations in brain-expressed genes are associated with autism spectrum disorders and carry large effects. On the basis of mutation rates in unaffected individuals, we demonstrate that multiple independent de novo single nucleotide variants in the same gene among unrelated probands reliably identifies risk alleles, providing a clear path forward for gene discovery. Among a total of 279 identified de novo coding mutations, there is a single instance in probands, and none in siblings, in which two independent nonsense variants disrupt the same gene, SCN2A (sodium channel, voltage-gated, type II, α subunit), a result that is highly unlikely by chance.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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 cited source says what the claim attributes to it.
In the citing paper
“TADA requires a mutational model (Sanders et al., 2012; Neale et al., 2012; Samocha et al., 2014) which accounts for gene size and sequence composition to obtain an expectation for mutations per gene, given sample size.”
From Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism (2020) · cites this paper as Sanders et al., 2012
In the citing paper
“CNVs and SNPs have both been reported to play a major role in autism incidence (36–41).”
From Gene × Environment Interactions in Autism Spectrum Disorders: Role of Epigenetic Mechanisms (2014) · cites this paper as [40]
In the citing paper
“The possibility of a “female protective effect” (FPE) against ASD has been described extensively and has received consistent support from the results of genetic studies of de novo variants.4, 5, 6, 7, 8, 9, 10, 11, 12, 13”
From The female protective effect against autism spectrum disorder (2022) · cites this paper as [5]
In the citing paper
“Many types of ASD-associated de novo variants are observed more frequently in female cases.4, 5, 6, 7, 8, 9, 10, 11, 12, 13”
From The female protective effect against autism spectrum disorder (2022) · cites this paper as [5]
In the citing paper
“The previously described differences in rare variant burden, along with preliminary evidence from studies of SNP heritability, already violate that assumption.5, 6, 7, 8,15”
From The female protective effect against autism spectrum disorder (2022) · cites this paper as [5]
In the citing paper
“For each gene, the mutation rate per gene () can be estimated from its exonic length and nucleotide content [1] and hence this quantity can be treated as known.”
From Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes (2013) · cites this paper as [1]
In the citing paper
“As demonstrated previously [1], the power for detecting a gene increases monotonically with increasing sample size and it depends strongly on the gene's mutation rate (Figure 1A).”
From Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes (2013) · cites this paper as [1]
In the citing paper
“Although the error of mutation rate estimation is likely small [1]”
From Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes (2013) · cites this paper as [1]
In the citing paper
“There is an intriguing coincidence in the excess of small p-values - namely that it is very similar to the excess number of genes with single-hit de novo LoF events in ASD subjects compared to their unaffected siblings [1].”
From Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes (2013) · cites this paper as [1]
In the citing paper
“These estimates are similar to published results using somewhat different methods [1], [2].”
From Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes (2013) · cites this paper as [1]
In the citing paper
“analysis of trio-based whole-exome sequencing (WES) has implicated a large number of de novo loss-of-function variants contributing to risk of neurodevelopmental pathologies, including autism spectrum disorders and neurodevelopmental delay (ASD/ND) (4, 5).”
From In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with autism risk genes (2020) · cites this paper as [5]
In the citing paper
“but these studies also demonstrate striking genetic heterogeneity3-5.”
From Altered proliferation and networks in neural cells derived from idiopathic autistic individuals (2017) · cites this paper as [5]
In the citing paper
“Mounting evidence proposes that heritable and de novo genetic variation plays a significant role”
From Altered proliferation and networks in neural cells derived from idiopathic autistic individuals (2017) · cites this paper as [5]
In the citing paper
“Hypomorphic, biallelic mutations, combined with CNVs and heterozygous stop mutations (Neale et al., 2012; O’Roak et al., 2012; Sanders et al., 2012) which completely inactivate one of two alleles, suggest that a common theme for ASD mutations in general might be partial loss of gene function and/or dosage sensitivity.”
From Using Whole-Exome Sequencing to Identify Inherited Causes of Autism (2013) · cites this paper as Sanders et al., 2012
In the citing paper
“An analysis of publicly released whole exome sequence data (Iossifov et al., 2012; O’Roak et al., 2012; Sanders et al., 2012) showed a modest trend towards an excess of biallelic, inherited, rare (MAF<1%), protein-altering variants in cases (8/612 ) compared to control siblings (2/419) (p=0.21, Fisher’s exact test, two-tailed) in at least one of the genes we screened (Table S5).”
From Using Whole-Exome Sequencing to Identify Inherited Causes of Autism (2013) · cites this paper as Sanders et al., 2012
In the citing paper
“ASD is often due to newly arising gene copy number variants (CNVs) — such as a deletion or duplication of a region of a chromosome — or a rare mutation that arises in the germ cell, particularly in sperm of older fathers5–10.”
From Activity-dependent neuronal signalling and autism spectrum disorder (2013) · cites this paper as [7]
In the citing paper
“In addition, very recent exome sequencing of parent-offspring trios has identified de novo exonic mutations in SCN2A, KATNAL2, CHD8, FOXP1, NTNG1, GRIN2B, LAMC3(refs 7–9), extending further the number of genes for which mutation may contribute to ASD.”
From Activity-dependent neuronal signalling and autism spectrum disorder (2013) · cites this paper as [7]
In the citing paper
“These studies demonstrate the ability of new sequencing technologies to significantly advance our understanding of the genetic basis of ASD.”
From Activity-dependent neuronal signalling and autism spectrum disorder (2013) · cites this paper as [7]
In the citing paper
“References 7– 10 use exome and entire genome sequencing to demonstrate the importance of rare mutations in ASD and identify new genetic mutations associated with ASD.”
From Activity-dependent neuronal signalling and autism spectrum disorder (2013) · cites this paper as [7]
In the citing paper
“Together, results from these papers demonstrate a significant role for rare SNVs in genetic liability for ASD”
From Sex differences in autism spectrum disorders (2013) · cites this paper as [50]
In the citing paper
“synonymous SNPs can affect protein folding and messenger RNA splicing, stability and structure57,58.”
From Immune mediators in the brain and peripheral tissues in autism spectrum disorder (2015) · cites this paper as [57]
In the citing paper
“This is particularly salient for ASD where a large effect variant is present in ~15% of cases along with smaller proportions of individuals with TS, ADHD, and SCZ (Iossifov et al., 2012; Sanders et al., 2012; Satterstrom et al., 2018c; Singh et al., 2016; Willsey et al., 2017).”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Sanders et al., 2012
In the citing paper
“Exome and whole-genome sequencing studies have estimated at least another ∼6% contribution to ASD7–10,15”
From Convergence of genes and cellular pathways dysregulated in autism spectrum disorders (2014) · cites this paper as [9]
In the citing paper
“and three other recent studies by Sanders et al.8, O’Roak et al.7 and Neale et al.23 (65 genes combined from all three; referred to as ‘SON-exomes’);”
From Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism (2014) · cites this paper as [8]
In the citing paper
“Various genetic approaches have been successful in identifying the causes of more than 1,000 Mendelian, and fewer non-Mendelian, forms of neurodevelopmental disorders: prototypical examples are intellectual disability62–68, autism spectrum disorder (ASD)69–77, epilepsy78,79 and schizophrenia80–82.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [70]
In the citing paper
“In summary, only three genes [CHD8, SCN2A, and synaptic Ras GTPase activating protein 1 (SYNGAP1)] had two independent truncating de novo mutations in any single study, and no gene had more than three mutations.”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [27]
In the citing paper
“Exome sequencing of ASD/ID families has revealed a significant excess of de novo mutations in probands when compared to unaffected siblings and has identified novel candidate genes contributing to the neurological deficits.”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [27]
In the citing paper
“Overall, these studies suggest that protein-truncating de novo SNVs contribute to the risk of ASD for about 10–15% of probands [26,27]”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [27]
In the citing paper
“probands had two- to threefold more disruptive de novo mutations in comparison to their siblings, or to a random model of mutation [26,27].”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [27]
In the citing paper
“Moreover, a small subset of the de novo mutations (~4% for unaffected and ~9% of affected [26,27]) are disruptive”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [27]
In the citing paper
“Many strong neurobiological candidates have emerged from the genes disrupted by de novo mutations in these studies, including mutations in previously identified ASD/ID genes.”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [27]
In the citing paper
“New exome sequencing technology has identified novel rare variants and has found that sporadic cases of ASD/ID are enriched for disruptive de novo mutations.”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [27]
In the citing paper
“We note that the strongest effects are observed for de novo loss-of-function (or truncating) mutations”
From A de novo convergence of autism genetics and molecular neuroscience (2014) · cites this paper as [27]
In the citing paper
“Simulations based on the observed number of recurrently disrupted genes have estimated that there are some 600-1200 ASD risk genes (21,24,26,51).”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [24]
In the citing paper
“In the case of paternal age, one mediating mechanism lies in the increased rate of de novo SNV and CNV with advancing paternal age (22,24,25,43,44).”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [24]
In the citing paper
“Autosomal de novo loss-of-function SNV has been identified that acts in a dominant manner and carries a large burden for individual risk, with odds ratios of 20 or above for genes identified to date (24,26).”
From Genetics and genomics of autism spectrum disorder: embracing complexity (2015) · cites this paper as [24]
In the citing paper
“Qualitatively, recent studies of rare variants also find it challenging to distinguish risk variation from the background stochastic noise (12–15).”
From Individual common variants exert weak effects on the risk for autism spectrum disorders (2012) · cites this paper as [12]
In the citing paper
“Notably, many of the genes associated with ASD are also linked with elemental homeostasis930, and it is intriguing that genes implicated in ASD converge to specific neuronal co-expression networks especially during the same critical early developmental periods we have observed in this study313233.”
From Fetal and postnatal metal dysregulation in autism (2017) · cites this paper as [30]
In the citing paper
“Albeit rare, de novo mutations have emerged as substantial contributors to ASD risk [83, 165, 166, 254, 261, 309].”
From Autism spectrum disorder: neuropathology and animal models (2017) · cites this paper as [309]
In the citing paper
“This prevalence is similar to the one reported in the four large-scale studies in ASD using exome sequencing [32] (de novo or truncating SHANK2 mutation 1/965, 0.10%).”
From Meta-analysis of SHANK Mutations in Autism Spectrum Disorders: A Gradient of Severity in Cognitive Impairments (2014) · cites this paper as [32]
In the citing paper
“Recent exome sequencing studies only reported one de novo SHANK2 mutation out of 965 patients [32], [36], [37]”
From Meta-analysis of SHANK Mutations in Autism Spectrum Disorders: A Gradient of Severity in Cognitive Impairments (2014) · cites this paper as [32]
In the citing paper
“no truncating coding-sequence variation within SHANK1 and SHANK3”
From Meta-analysis of SHANK Mutations in Autism Spectrum Disorders: A Gradient of Severity in Cognitive Impairments (2014) · cites this paper as [32]
In the citing paper
“the published GWAS for ASD are small by current standards. 86–89”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [86]
In the citing paper
“Many studies of complex neuropsychiatric disorders have also concluded that disease-causing variants are often clustered in protein-interaction networks with a high degree of connectivity among themselves and that these clustered networks are often enriched with functional pathways relevant to brain functions [72–80].”
From An integrated analysis of genes and functional pathways for aggression in human and rodent models (2019) · cites this paper as [73]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
A method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194
Kumar, P., Henikoff, S., & Ng, P. C. (2009) · Nature Protocols · doi:10.1038/nprot.2009.86 · Cited by 6,521
Strong association of de novo copy number mutations with autism
Sebat, J., Lakshmi, B., Malhotra, D., Troge, J., Lese-Martin, C., Walsh, T., Yamrom, B., Yoon, S., Krasnitz, A., Kendall, J., et al. (2007) · Science · doi:10.1126/science.1138659 · Cited by 2,795
Self-citationAmino Acid Difference Formula to Help Explain Protein Evolution
Grantham, R. L. (1974) · Science · doi:10.1126/science.185.4154.862 · Cited by 2,363
Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations
O’Roak, B. J., Vives, L., Girirajan, S., Karakoc, E., Krumm, N., Coe, B. P., Levy, R., Ko, A., Lee, C., Smith, J. D., et al. (2012) · Nature · doi:10.1038/nature10989 · Cited by 2,165
Spatio-temporal transcriptome of the human brain
Kang, H. J., Kawasawa, Y. I., Cheng, F., Zhu, Y., Xu, X., Li, M., Sousa, A. M. M., Pletikos, M., Meyer, K. A., Sedmak, G., et al. (2011) · Nature · doi:10.1038/nature10523 · Cited by 2,084
Self-citationFunctional 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
Self-citationDistribution and intensity of constraint in mammalian genomic sequence
Cooper, G. M., Stone, E. A., Asimenos, G., Green, E. D., Batzoglou, S., & Sidow, A. (2005) · Genome Research · doi:10.1101/gr.3577405 · Cited by 1,359
Flagged first, then by citations
Cited by
Sorted by citations
Items 101–200 of 227
Advanced parental age and autism risk in children: a systematic review and meta‐analysis
Wu, S., Wu, F., Ding, Y., Hou, J., Bi, J., & Zhang, Z. (2017) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.12666 · Cited by 282
The discovery of integrated gene networks for autism and related disorders
Hormozdiari, F., Penn, O., Borenstein, E., & Eichler, E. E. (2015) · Genome Research · doi:10.1101/gr.178855.114 · Cited by 249
Spratt, P. W. E., Ben-Shalom, R., Keeshen, C. M., Burke, K. J., Clarkson, R. L., Sanders, S. J., & Bender, K. J. (2019) · Neuron · doi:10.1016/j.neuron.2019.05.037 · Cited by 244
Self-citationKim, J. Y., Son, M. J., Son, C. Y., Radua, J., Eisenhut, M., Gressier, F., Koyanagi, A., Carvalho, A. F., Stubbs, B., Solmi, M., et al. (2019) · The Lancet Psychiatry · doi:10.1016/s2215-0366(19)30181-6 · Cited by 271
The Emerging Picture of Autism Spectrum Disorder: Genetics and Pathology
Chen, J. A., Peñagarikano, O., Belgard, T. G., Swarup, V., & Geschwind, D. H. (2015) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-012414-040405 · Cited by 254
Self-citationChd8 Mutation Leads to Autistic-like Behaviors and Impaired Striatal Circuits
Platt, R. J., Zhou, Y., Slaymaker, I. M., Shetty, A. S., Weisbach, N. R., Kim, J.-A., Sharma, J., Desai, M., Sood, S., Kempton, H. R., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.03.052 · Cited by 240
SCN2A encephalopathy: A major cause of epilepsy of infancy with migrating focal seizures
Howell, K. B., McMahon, J. M., Carvill, G. L., Tambunan, D., Mackay, M. T., Rodriguez-Casero, V., Webster, R., Clark, D., Freeman, J. L., Calvert, S., et al. (2015) · Neurology · doi:10.1212/wnl.0000000000001926 · Cited by 255
A Comprehensive Assessment of Parental Age and Psychiatric Disorders
McGrath, J. J., Petersen, L., Agerbo, E., Mors, O., Mortensen, P. B., & Pedersen, C. B. (2014) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.4081 · Cited by 253
Modeling non-syndromic autism and the impact of TRPC6 disruption in human neurons
Griesi-Oliveira, K., Acab, A., Gupta, A. R., Sunaga, D. Y., Chailangkarn, T., Nicol, X., Nunez, Y., Walker, M. F., Murdoch, J. D., Sanders, S. J., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.141 · Cited by 236
Self-citationChd8 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
Doherty, J. L., & Owen, M. J. (2014) · Genome Medicine · doi:10.1186/gm546 · Cited by 228
Mutations in the GABA Transporter SLC6A1 Cause Epilepsy with Myoclonic-Atonic Seizures
Carvill, G. L., McMahon, J. M., Schneider, A., Zemel, M., Myers, C. T., Saykally, J., Nguyen, J., Robbiano, A., Zara, F., Specchio, N., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.02.016 · Cited by 227
A Quantitative Framework to Evaluate Modeling of Cortical Development by Neural Stem Cells
Stein, J. L., de la Torre-Ubieta, L., Tian, Y., Parikshak, N. N., Hernández, I. A., Marchetto, M. C., Baker, D. K., Lu, D., Hinman, C. R., Lowe, J. K., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.035 · Cited by 201
Self-citationThe role of sex-differential biology in risk for autism spectrum disorder
Werling, D. M. (2016) · Biology of Sex Differences · doi:10.1186/s13293-016-0112-8 · Cited by 208
Paternally inherited cis-regulatory structural variants are associated with autism
Brandler, W. M., Antaki, D., Gujral, M., Kleiber, M. L., Whitney, J., Maile, M. S., Hong, O., Chapman, T. R., Tan, S., Tandon, P., et al. (2018) · Science · doi:10.1126/science.aan2261 · Cited by 209
Isolated polycystic liver disease genes define effectors of polycystin-1 function
Besse, W., Dong, K., Choi, J., Punia, S., Fedeles, S. V., Choi, M., Gallagher, A.-R., Huang, E. B., Gulati, A., Knight, J., et al. (2017) · Journal of Clinical Investigation · doi:10.1172/jci90129 · Cited by 203
Self-citationGenotype to phenotype relationships in autism spectrum disorders
Chang, J., Gilman, S. R., Chiang, A. H., Sanders, S. J., & Vitkup, D. (2015) · Nature Neuroscience · doi:10.1038/nn.3907 · Cited by 197
Self-citationLoss-of-Function Variants in Schizophrenia Risk and SETD1A as a Candidate Susceptibility Gene
Takata, A., Xu, B., Ionita-Laza, I., Roos, J. L., Gogos, J. A., & Karayiorgou, M. (2014) · Neuron · doi:10.1016/j.neuron.2014.04.043 · Cited by 204
Exonic Mosaic Mutations Contribute Risk for Autism Spectrum Disorder
Krupp, D. R., Barnard, R. A., Duffourd, Y., Evans, S. A., Mulqueen, R. M., Bernier, R., Rivière, J.-B., Fombonne, E., & O’Roak, B. J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.07.016 · Cited by 204
Novel Findings from CNVs Implicate Inhibitory and Excitatory Signaling Complexes in Schizophrenia
Pocklington, A. J., Rees, E., Walters, J. T. R., Han, J., Kavanagh, D. H., Chambert, K. D., Holmans, P., Moran, J. L., McCarroll, S. A., Kirov, G., et al. (2015) · Neuron · doi:10.1016/j.neuron.2015.04.022 · Cited by 193
A Discovery Resource of Rare Copy Number Variations in Individuals with Autism Spectrum Disorder
Prasad, A., Merico, D., Thiruvahindrapuram, B., Wei, J., Lionel, A. C., Sato, D., Rickaby, J., Lu, C., Szatmari, P., Roberts, W., et al. (2012) · G3 Genes|Genomes|Genetics · doi:10.1534/g3.112.004689 · Cited by 206
Kaufman, K. M., Linghu, B., Szustakowski, J. D., Husami, A., Yang, F., Zhang, K., Filipovich, A. H., Fall, N., Harley, J. B., Nirmala, N. R., et al. (2014) · Arthritis & Rheumatology · doi:10.1002/art.38793 · Cited by 207
Disruptive de novo mutations of DYRK1A lead to a syndromic form of autism and ID
van Bon, B. W. M., Coe, B. P., Bernier, R., Green, C., Gerdts, J., Witherspoon, K., Kleefstra, T., Willemsen, M. H., Kumar, R., Bosco, P., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.5 · Cited by 204
Lombardo, 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
Diverse types of genetic variation converge on functional gene networks involved in schizophrenia
Gilman, S. R., Chang, J., Xu, B., Bawa, T. S., Gogos, J. A., Karayiorgou, M., & Vitkup, D. (2012) · Nature Neuroscience · doi:10.1038/nn.3261 · Cited by 200
De Novo Coding Variants Are Strongly Associated with Tourette Disorder
Willsey, A. J., Fernandez, T. V., Yu, D., King, R. A., Dietrich, A., Xing, J., Sanders, S. J., Mandell, J. D., Huang, A. Y., Richer, P., et al. (2017) · Neuron · doi:10.1016/j.neuron.2017.04.024 · Cited by 187
Self-citationMilekic, M. H., Xin, Y., O’Donnell, A., Kumar, K. K., Bradley-Moore, M., Malaspina, D., Moore, H., Brunner, D., Ge, Y., Edwards, J., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.84 · Cited by 190
CACNA1D de novo mutations in autism spectrum disorders activate Cav1.3 L-type calcium channels
Pinggera, A., Lieb, A., Benedetti, B., Lampert, M., Monteleone, S., Liedl, K. R., Tuluc, P., & Striessnig, J. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.11.020 · Cited by 180
Autism genetics: searching for specificity and convergence
Berg, J. M., & Geschwind, D. H. (2012) · Genome Biology · doi:10.1186/gb-2012-13-7-247 · Cited by 192
Self-citationTbr1 haploinsufficiency impairs amygdalar axonal projections and results in cognitive abnormality
Huang, T.-N., Chuang, H.-C., Chou, W.-H., Chen, C.-Y., Wang, H.-F., Chou, S.-J., & Hsueh, Y.-P. (2014) · Nature Neuroscience · doi:10.1038/nn.3626 · Cited by 180
Howrigan, D. P., Rose, S. A., Samocha, K. E., Fromer, M., Cerrato, F., Chen, W. J., Churchhouse, C., Chambert, K., Chandler, S. D., Daly, M. J., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-019-0564-3 · Cited by 168
Urinary p-cresol in autism spectrum disorder
Persico, A. M., & Napolioni, V. (2013) · Neurotoxicology and Teratology · doi:10.1016/j.ntt.2012.09.002 · Cited by 189
Unifying Views of Autism Spectrum Disorders: A Consideration of Autoregulatory Feedback Loops
Mullins, C., Fishell, G., & Tsien, R. W. (2016) · Neuron · doi:10.1016/j.neuron.2016.02.017 · Cited by 167
Autism traits in the RASopathies
Adviento, B., Corbin, I. L., Widjaja, F., Desachy, G., Enrique, N., Rosser, T., Risi, S., Marco, E. J., Hendren, R. L., Bearden, C. E., et al. (2014) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2013-101951 · Cited by 174
Fetal and postnatal metal dysregulation in autism
Arora, M., Reichenberg, A., Willfors, C., Austin, C., Gennings, C., Berggren, S., Lichtenstein, P., Anckarsäter, H., Tammimies, K., & Bölte, S. (2017) · Nature Communications · doi:10.1038/ncomms15493 · Cited by 169
Brain Transcriptional and Epigenetic Associations with Autism
Ginsberg, M. R., Rubin, R. A., Falcone, T., Ting, A. H., & Natowicz, M. R. (2012) · PLoS ONE · doi:10.1371/journal.pone.0044736 · Cited by 164
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
Low load for disruptive mutations in autism genes and their biased transmission
Iossifov, I., Levy, D., Allen, J., Ye, K., Ronemus, M., Lee, Y.-H., Yamrom, B., & Wigler, M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1516376112 · Cited by 156
Tipping the balance of autism risk: potential mechanisms linking pesticides and autism
Shelton, J. F., Hertz-Picciotto, I., & Pessah, I. N. (2012) · Environmental Health Perspectives · doi:10.1289/ehp.1104553 · Cited by 164
Richter, M., Murtaza, N., Scharrenberg, R., White, S. H., Johanns, O., Walker, S., Yuen, R. K. C., Schwanke, B., Bedürftig, B., Henis, M., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-018-0025-5 · Cited by 169
Poultney, C. S., Goldberg, A. P., Drapeau, E., Kou, Y., Harony-Nicolas, H., Kajiwara, Y., De Rubeis, S., Durand, S., Stevens, C., Rehnström, K., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.09.001 · Cited by 169
Menendez, D., Nguyen, T.-A., Freudenberg, J. M., Mathew, V. J., Anderson, C. W., Jothi, R., & Resnick, M. A. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt504 · Cited by 154
Urraca, N., Cleary, J., Brewer, V., Pivnick, E. K., McVicar, K., Thibert, R. L., Schanen, N. C., Esmer, C., Lamport, D., & Reiter, L. T. (2013) · Autism Research · doi:10.1002/aur.1284 · Cited by 164
The Emerging Biology of Autism Spectrum Disorders
State, M. W., & Šestan, N. (2012) · Science · doi:10.1126/science.1224989 · Cited by 164
Self-citationUddin, M., Tammimies, K., Pellecchia, G., Alipanahi, B., Hu, P., Wang, Z., Pinto, D., Lau, L., Nalpathamkalam, T., Marshall, C. R., et al. (2014) · Nature Genetics · doi:10.1038/ng.2980 · Cited by 163
Mitochondrial Dysfunction in Autism Spectrum Disorder: Unique Abnormalities and Targeted Treatments
Frye, R. E. (2020) · Seminars in Pediatric Neurology · doi:10.1016/j.spen.2020.100829 · Cited by 161
Recessive gene disruptions in autism spectrum disorder
Autism Sequencing Consortium, Doan, R. N., Lim, E. T., De Rubeis, S., Betancur, C., Cutler, D. J., Chiocchetti, A. G., Overman, L. M., Soucy, A., Goetze, S., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0433-8 · Cited by 159
A Cross-Disorder Method to Identify Novel Candidate Genes for Developmental Brain Disorders
Gonzalez-Mantilla, A. J., Moreno-De-Luca, A., Ledbetter, D. H., & Martin, C. L. (2016) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.2692 · Cited by 139
Ben-David, E., & Shifman, S. (2013) · Molecular Psychiatry · doi:10.1038/mp.2012.148 · Cited by 148
Robinson, E. B., Samocha, K. E., Kosmicki, J. A., McGrath, L., Neale, B. M., Perlis, R. H., & Daly, M. J. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1409204111 · Cited by 142
Fetit, R., Hillary, R. F., Price, D. J., & Lawrie, S. M. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.07.014 · Cited by 148
Neocortical neurogenesis and the etiology of autism spectrum disorder
Packer, A. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.03.002 · Cited by 138
Prioritization of neurodevelopmental disease genes by discovery of new mutations
Hoischen, A., Krumm, N., & Eichler, E. E. (2014) · Nature Neuroscience · doi:10.1038/nn.3703 · Cited by 149
Autism-Associated Promoter Variant in MET Impacts Functional and Structural Brain Networks
Rudie, J. D., Hernandez, L. M., Brown, J. A., Beck-Pancer, D., Colich, N. L., Gorrindo, P., Thompson, P. M., Geschwind, D. H., Bookheimer, S. Y., Levitt, P., et al. (2012) · Neuron · doi:10.1016/j.neuron.2012.07.010 · Cited by 142
Self-citationBlumenthal, 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
Self-citationRed 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
Recurrent de novo mutations in neurodevelopmental disorders: properties and clinical implications
Wilfert, A. B., Sulovari, A., Turner, T. N., Coe, B. P., & Eichler, E. E. (2017) · Genome Medicine · doi:10.1186/s13073-017-0498-x · Cited by 144
High Loading of Polygenic Risk for ADHD in Children With Comorbid Aggression
Hamshere, M. L., Langley, K., Martin, J., Agha, S. S., Stergiakouli, E., Anney, R. J. L., Buitelaar, J., Faraone, S. V., Lesch, K.-P., Neale, B. M., et al. (2013) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2013.12081129 · Cited by 144
Sestan, N., & State, M. W. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.015 · Cited by 127
Self-citationAceti, M., Creson, T. K., Vaissiere, T., Rojas, C., Huang, W.-C., Wang, Y.-X., Petralia, R. S., Page, D. T., Miller, C. A., & Rumbaugh, G. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.08.001 · Cited by 129
Understanding sex bias in autism spectrum disorder
Werling, D. M., & Geschwind, D. H. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1301602110 · Cited by 135
Self-citationCorominas, R., Yang, X., Lin, G. N., Kang, S., Shen, Y., Ghamsari, L., Broly, M., Rodriguez, M., Tam, S., Wanamaker, S. A., et al. (2014) · Nature Communications · doi:10.1038/ncomms4650 · Cited by 140
“…strong autism candidate in the whole genome sequencing of monozygotic twins 35 ; five preys ( RIMBP3, GOLGA2, MKRN3, C16orf45 and MAGED1 ) were found within newly reported de novo CNVs 6,7,14 ; and two other preys ( CASK and DISC1) were implicated in ASD based on a recent exome sequencing study 4 .”
InfluentialIntegrated systems analysis reveals a molecular network underlying autism spectrum disorders
Li, J., Shi, M., Ma, Z., Zhao, S., Euskirchen, G., Ziskin, J., Urban, A., Hallmayer, J., & Snyder, M. (2014) · Molecular Systems Biology · doi:10.15252/msb.20145487 · Cited by 132
“Overall, these observations revealed the modular architecture of the human protein interactome, with different modules organized for specific functions (Supplementary Fig S5).”
Liu, L., Sabo, A., Neale, B. M., Nagaswamy, U., Stevens, C., Lim, E., Bodea, C. A., Muzny, D., Reid, J. G., Banks, E., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003443 · Cited by 135
Self-citationLazaro, M. T., Taxidis, J., Shuman, T., Bachmutsky, I., Ikrar, T., Santos, R., Marcello, G. M., Mylavarapu, A., Chandra, S., Foreman, A., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.05.006 · Cited by 125
Self-citationOne gene, many neuropsychiatric disorders: lessons from Mendelian diseases
Zhu, X., Need, A. C., Petrovski, S., & Goldstein, D. B. (2014) · Nature Neuroscience · doi:10.1038/nn.3713 · Cited by 131
Whole-genome analyses of whole-brain data: working within an expanded search space
Medland, S. E., Jahanshad, N., Neale, B. M., & Thompson, P. M. (2014) · Nature Neuroscience · doi:10.1038/nn.3718 · Cited by 119
Epigenetics of Autism Spectrum Disorder
Siu, M. T., & Weksberg, R. (2017) · Advances in Experimental Medicine and Biology · doi:10.1007/978-3-319-53889-1_4 · Cited by 121
The female protective effect against autism spectrum disorder
Wigdor, E. M., Weiner, D. J., Grove, J., Fu, J. M., Thompson, W. K., Carey, C. E., Baya, N., van der Merwe, C., Walters, R. K., Satterstrom, F. K., et al. (2021) · doi:10.1101/2021.03.29.21253866 · Cited by 124
Self-citationThe female protective effect against autism spectrum disorder
Wigdor, E. M., Weiner, D. J., Grove, J., Fu, J. M., Thompson, W. K., Carey, C. E., Baya, N., van der Merwe, C., Walters, R. K., Satterstrom, F. K., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100134 · Cited by 124
Self-citationRisk of psychiatric illness from advanced paternal age is not predominantly from de novo mutations
Gratten, J., Wray, N. R., Peyrot, W. J., McGrath, J. J., Visscher, P. M., & Goddard, M. E. (2016) · Nature Genetics · doi:10.1038/ng.3577 · Cited by 118
A twin study of heritable and shared environmental contributions to autism
Frazier, T. W., Thompson, L., Youngstrom, E. A., Law, P., Hardan, A. Y., Eng, C., & Morris, N. (2014) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-014-2081-2 · Cited by 120
Spooren, W., Lindemann, L., Ghosh, A., & Santarelli, L. (2012) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2012.09.004 · Cited by 119
Transmission Disequilibrium of Small CNVs in Simplex Autism
Krumm, N., O’Roak, B. J., Karakoc, E., Mohajeri, K., Nelson, B., Vives, L., Jacquemont, S., Munson, J., Bernier, R., & Eichler, E. E. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.07.024 · Cited by 113
From trans to cis: transcriptional regulatory networks in neocortical development
Shibata, M., Gulden, F. O., & Sestan, N. (2015) · Trends in Genetics · doi:10.1016/j.tig.2014.12.004 · Cited by 109
Wolff, M., Brunklaus, A., & Zuberi, S. M. (2019) · Epilepsia · doi:10.1111/epi.14935 · Cited by 105
Brunner, D., Kabitzke, P., He, D., Cox, K., Thiede, L., Hanania, T., Sabath, E., Alexandrov, V., Saxe, M., Peles, E., et al. (2015) · PLOS ONE · doi:10.1371/journal.pone.0134572 · Cited by 111
Two Rab2 Interactors Regulate Dense-Core Vesicle Maturation
Ailion, M., Hannemann, M., Dalton, S., Pappas, A., Watanabe, S., Hegermann, J., Liu, Q., Han, H.-F., Gu, M., Goulding, M. Q., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.02.017 · Cited by 86
Bishop, S. L., Farmer, C., Bal, V., Robinson, E. B., Willsey, A. J., Werling, D. M., Havdahl, K. A., Sanders, S. J., & Thurm, A. (2017) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2017.16101115 · Cited by 92
Self-citationEpigenomic strategies at the interface of genetic and environmental risk factors for autism
LaSalle, J. M. (2013) · Journal of Human Genetics · doi:10.1038/jhg.2013.49 · Cited by 95
An integrated analysis of genes and functional pathways for aggression in human and rodent models
Zhang-James, Y., Fernàndez-Castillo, N., Hess, J. L., Malki, K., Glatt, S. J., Cormand, B., & Faraone, S. V. (2019) · Molecular Psychiatry · doi:10.1038/s41380-018-0068-7 · Cited by 98
Frye, R. E., & Rossignol, D. A. (2016) · Clinical Medicine Insights Pediatrics · doi:10.4137/cmped.s38337 · Cited by 96
Orosco, L. A., Ross, A. P., Cates, S. L., Scott, S. E., Wu, D., Sohn, J., Pleasure, D., Pleasure, S. J., Adamopoulos, I. E., & Zarbalis, K. S. (2014) · Nature Communications · doi:10.1038/ncomms5692 · Cited by 90
“Neonatal” NaV1.2 reduces neuronal excitability and affects seizure susceptibility and behaviour
Gazina, E. V., Leaw, B. T. W., Richards, K. L., Wimmer, V. C., Kim, T. H., Aumann, T. D., Featherby, T. J., Churilov, L., Hammond, V. E., Reid, C. A., et al. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddu562 · Cited by 89
Intellectual disability is associated with increased runs of homozygosity in simplex autism
Gamsiz, E. D., Viscidi, E. W., Frederick, A. M., Nagpal, S., Sanders, S. J., Murtha, M. T., Schmidt, M., Triche, E. W., Geschwind, D. H., State, M. W., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.06.004 · Cited by 79
Self-citationFirst 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
Self-citationWang, Z.-J., Zhong, P., Ma, K., Seo, J.-S., Yang, F., Hu, Z., Zhang, F., Lin, L., Wang, J., Liu, T., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-019-0351-2 · Cited by 82
Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease
Gratten, J., Visscher, P. M., Mowry, B. J., & Wray, N. R. (2013) · Nature Genetics · doi:10.1038/ng.2555 · Cited by 77
De novo variants in SETD1B are associated with intellectual disability, epilepsy and autism
Hiraide, T., Nakashima, M., Yamoto, K., Fukuda, T., Kato, M., Ikeda, H., Sugie, Y., Aoto, K., Kaname, T., Nakabayashi, K., et al. (2018) · Human Genetics · doi:10.1007/s00439-017-1863-y · Cited by 75
Wang, W., Corominas, R., & Lin, G. N. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00258 · Cited by 70
Increased cortical reactivity to repeated tones at 8 months in infants with later ASD
Kolesnik, A., Begum Ali, J., Gliga, T., Guiraud, J., Charman, T., Johnson, M. H., Jones, E. J. H., & The BASIS Team (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0393-x · Cited by 75
Mutations in HECW2 are associated with intellectual disability and epilepsy
Halvardson, J., Zhao, J. J., Zaghlool, A., Wentzel, C., Georgii-Hemming, P., Månsson, E., Ederth Sävmarker, H., Brandberg, G., Soussi Zander, C., Thuresson, A.-C., et al. (2016) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2016-103814 · Cited by 71
Cappi, C., Brentani, H., Lima, L., Sanders, S. J., Zai, G., Diniz, B. J., Reis, V. N. S., Hounie, A. G., Conceição do Rosário, M., Mariani, D., et al. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.30 · Cited by 71
Self-citationAutism Spectrum Disorder Genetics: Diverse Genes with Diverse Clinical Outcomes
Talkowski, M. E., Minikel, E. V., & Gusella, J. F. (2014) · Harvard Review of Psychiatry · doi:10.1097/hrp.0000000000000002 · Cited by 72
Steinberg, J., & Webber, C. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.09.013 · Cited by 71
Rare inherited variation in autism: Beginning to see the forest and a few trees
Stein, J. L., Parikshak, N. N., & Geschwind, D. H. (2013) · Neuron · doi:10.1016/j.neuron.2013.01.010 · Cited by 68
Self-citationSelected vitamin D metabolic gene variants and risk for Autism Spectrum Disorder in the charge study
Schmidt, R. J., Hansen, R. L., Hartiala, J., Allayee, H., Sconberg, J. L., Schmidt, L. C., Volk, H. E., & Tassone, F. (2015) · Early Human Development · doi:10.1016/j.earlhumdev.2015.05.008 · Cited by 68
Vogel Ciernia, A., Careaga, M., LaSalle, J. M., & Ashwood, P. (2018) · Glia · doi:10.1002/glia.23261 · Cited by 69
Wray, N. R., & Maier, R. (2014) · Current Epidemiology Reports · doi:10.1007/s40471-014-0023-3 · Cited by 67
Oxytocin: Parallel Processing in the Social Brain?
Dölen, G. (2015) · Journal of Neuroendocrinology · doi:10.1111/jne.12284 · Cited by 65
Metadata
- Authors
- Sanders, S. J., Murtha, M. T., Gupta, A. R., Murdoch, J. D., Raubeson, M. J., Willsey, A. J., Ercan-Sencicek, A. G., DiLullo, N. M., Parikshak, N. N., Stein, J. L., Walker, M. F., Ober, G. T., Teran, N. A., Song, Y., El-Fishawy, P., Murtha, R. C., Choi, M., Overton, J. D., Bjornson, R. D., Carriero, N. J., Meyer, K. A., Bilguvar, K., Mane, S. M., Šestan, N., Lifton, R. P., Günel, M., Roeder, K., Geschwind, D. H., Devlin, B., & State, M. W.
- Affiliations
- Yale University (US)
- University of California, Los Angeles (US)
- Howard Hughes Medical Institute (US)
- Carnegie Mellon University (US)
- University of Pittsburgh (US)
- Corresponding author
- Geschwind, Daniel H.
- Devlin, Bernie
- State, Matthew W.
- ORCID
- Venue
- Nature
- Published
- 2012-04-04
- Volume
- 485
- Issue
- 7397
- Pages
- 237-241
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3667984
- OpenAlex
- W2131104106
- Semantic Scholar
- 122b231f10c7693d8adb51eacd8b5106edc50278
- Cited by
- 2,084
- References
- 24
- Citations by year
- 2026: 55 · 2025: 77 · 2024: 84 · 2023: 96 · 2022: 118 · 2021: 160 · 2020: 122 · 2019: 134 · 2018: 159 · 2017: 150 · 2016: 159 · 2015: 174 · 2014: 259 · 2013: 218 · 2012: 112
- FWCI
- 124.84
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institute of Mental Health (K08MH087639, U01MH081896, R25MH077823)
- National Institute of General Medical Sciences (T32GM008042)
- 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, de novo mutations, single nucleotide variants, nonsense mutation, splice site mutation, brain-expressed genes, SCN2A, CHD8, locus heterogeneity, copy number variation, risk alleles, gene discovery
- MeSH terms
- Alleles, Autistic Disorder, Exons, Humans, Mutation, Nerve Tissue Proteins, Sodium Channels, Codon, Nonsense, Genetic Heterogeneity, Genetic Predisposition to Disease, RNA Splice Sites, Siblings, Exome, NAV1.2 Voltage-Gated Sodium Channel
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.
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
