Cited by 288Genomics and Rare DiseasesGenetics and Neurodevelopmental DisordersGenomic variations and chromosomal abnormalities

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De novo mutations in regulatory elements in neurodevelopmental disorders

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Short, Patrick J., McRae, Jeremy F., Gallone, Giuseppe, Sifrim, Alejandro, Won, Hyejung, Geschwind, Daniel H., Wright, Caroline F., Firth, Helen V., FitzPatrick, David R., Barrett, Jeffrey C., Hurles, Matthew E.·2018·Nature

DOI 10.1038/nature25983PMC PMC5912909

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Abstract

We previously estimated that 42% of patients with severe developmental disorders carry pathogenic de novo mutations in coding sequences. The role of de novo mutations in regulatory elements affecting genes associated with developmental disorders, or other genes, has been essentially unexplored. We identified de novo mutations in three classes of putative regulatory elements in almost 8,000 patients with developmental disorders. Here we show that de novo mutations in highly evolutionarily conserved fetal brain-active elements are significantly and specifically enriched in neurodevelopmental disorders. We identified a significant twofold enrichment of recurrently mutated elements. We estimate that, genome-wide, 1-3% of patients without a diagnostic coding variant carry pathogenic de novo mutations in fetal brain-active regulatory elements and that only 0.15% of all possible mutations within highly conserved fetal brain-active elements cause neurodevelopmental disorders with a dominant mechanism. Our findings represent a robust estimate of the contribution of de novo mutations in regulatory elements to this genetically heterogeneous set of disorders, and emphasize the importance of combining functional and evolutionary evidence to identify regulatory causes of genetic disorders.

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Gentleman, R. C., Carey, V. J., Bates, D. M., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., et al. (2004) · Genome biology · doi:10.1186/gb-2004-5-10-r80 · Cited by 12,082
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587
Self-citation
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368
A general framework for estimating the relative pathogenicity of human genetic variants
Kircher, M., Witten, D. M., Jain, P., O'Roak, B. J., Cooper, G. M., & Shendure, J. (2014) · Nature Genetics · doi:10.1038/ng.2892 · Cited by 6,183
GENCODE: The reference human genome annotation for The ENCODE Project
Harrow, J., Frankish, A., Gonzalez, J. M., Tapanari, E., Diekhans, M., Kokocinski, F., Aken, B. L., Barrell, D., Zadissa, A., Searle, S., et al. (2012) · Genome Research · doi:10.1101/gr.135350.111 · Cited by 4,585
Software for Computing and Annotating Genomic Ranges
Lawrence, M. F., Huber, W. K., Pagès, H., Aboyoun, P., Carlson, M. R. J., Gentleman, R. C., Morgan, M. T., & Carey, V. J. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003118 · Cited by 4,475
Potential etiologic and functional implications of genome-wide association loci for human diseases and traits
Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., & Manolio, T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903103106 · Cited by 4,013
Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes
Siepel, A., Bejerano, G., Pedersen, J. S., Hinrichs, A. S., Hou, M., Rosenbloom, K., Clawson, H., Spieth, J., Hillier, L. W., Richards, S., et al. (2005) · Genome Research · doi:10.1101/gr.3715005 · Cited by 3,971
Systematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716
An atlas of active enhancers across human cell types and tissues
The FANTOM Consortium, Andersson, R., Gebhard, C., Miguel-Escalada, I., Hoof, I., Bornholdt, J., Boyd, M., Chen, Y., Zhao, X., Schmidl, C., et al. (2014) · Nature · doi:10.1038/nature12787 · Cited by 2,550

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EpiDenovo: a platform for linking regulatory de novo mutations to developmental epigenetics and diseases
Mao, F., Liu, Q., Zhao, X., Yang, H., Guo, S., Xiao, L., Li, X., Teng, H., Sun, Z. S., & Dou, Y. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx918 · Cited by 20
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“17,47 Therefore, the next milestones in the interpretation of the human genome sequence will focus on the remaining 98% of genome regions.”
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Cappuccio, G., Attanasio, S., Alagia, M., Mutarelli, M., Borzone, R., Karali, M., Genesio, R., Mormile, A., Nitsch, L., Imperati, F., et al. (2019) · European Journal of Human Genetics · doi:10.1038/s41431-019-0430-5 · Cited by 18
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Background
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Topologically associating domains define the impact of de novo promoter variants on autism spectrum disorder risk
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Background
Recommendations for clinical interpretation of variants found in non-coding regions of the genomePreprint
Ellingford, J. M., Ahn, J. W., Bagnall, R. D., Baralle, D., Barton, S., Campbell, C., Downes, K., Ellard, S., Duff‐Farrier, C. R. A., FitzPatrick, D. R., et al. (2021) · medRxiv · doi:10.1101/2021.12.28.21267792 · Cited by 15
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Background
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Background
Synaptic Formation, Neural Circuits and Neurodevelopmental Disorders Controlled by Signaling, Translation, and Epigenetic Regulation
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MethodSelf-citation
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Result
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Background
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Background
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Background
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“, 2017), neurodevelopmental disorders (Short et al., 2018) and susceptibility to infection (Telenti and di Iulio, 2020), among others.”
Background
Extending the allelic spectrum at noncoding risk loci of orofacial clefting
Thieme, F., Henschel, L., Hammond, N. L., Ishorst, N., Hausen, J., Adamson, A. D., Biedermann, A., Bowes, J., Zieger, H. K., Maj, C., et al. (2021) · Human Mutation · doi:10.1002/humu.24219 · Cited by 9
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Background
Optimising diagnostic yield in highly penetrant genomic diseasePreprint
Wright, C. F., Campbell, P. H., Eberhardt, R. Y., Aitken, S., Perrett, D., Brent, S., Danecek, P., Gardner, E. J., Chundru, V. K., Lindsay, S., et al. (2022) · medRxiv · doi:10.1101/2022.07.25.22278008 · Cited by 9
Self-citation
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Radford, E. J., & Firth, H. V. (2019) · Paediatrics and Child Health · doi:10.1016/j.paed.2019.07.002 · Cited by 8
Self-citation
Rare Does Not Mean Worthless: How Rare Diseases Have Shaped Neurodevelopment Research in the NGS Era
Zaghi, M., Banfi, F., Bellini, E. N., & Sessa, A. (2021) · Biomolecules · doi:10.3390/biom11111713 · Cited by 8
Bridging between Mouse and Human Enhancer-Promoter Long-Range Interactions in Neural Stem Cells, to Understand Enhancer Function in Neurodevelopmental Disease
D’Aurizio, R., Catona, O., Pitasi, M., Li, Y. E., Ren, B., & Nicolis, S. K. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23147964 · Cited by 9
“Further, it was estimated that only 42% of patients with severe developmental disorders carry pathogenic de novo mutations within coding sequences [1], further encouraging consideration of the non-coding genome as an important territory to chart for mutations.”
Background
ORE identifies extreme expression effects enriched for rare variants
Richter, F., Hoffman, G. E., Manheimer, K. B., Patel, N., Sharp, A. J., McKean, D. M., Morton, S. U., DePalma, S. R., Gorham, J., Kitaygorodksy, A., et al. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz202 · Cited by 7
Functional annotation of rare structural variation in the human brainPreprint
Han, L., Zhao, X., Benton, M. L., Perumal, T. M., Collins, R. L., Hoffman, G. E., Johnson, J., Sloofman, L. G., Wang, H. Z., Brennand, K., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/711754 · Cited by 8
Genetic constraint at single amino acid resolution improves missense variant prioritisation and gene discoveryPreprint
Zhang, X., Theotokis, P. I., Li, N., the SHaRe Investigators, Wright, C. F., Samocha, K. E., Whiffin, N., & Ware, J. S. (2022) · medRxiv · doi:10.1101/2022.02.16.22271023 · Cited by 8
Self-citation
Robustness and Evolvability in Transcriptional Regulation
Aguilar-Rodríguez, J., & Payne, J. L. (2021) · Springer eBooks · doi:10.1007/978-3-030-71737-7_9 · Cited by 11
De novo structural variants in autism spectrum disorder disrupt distal regulatory interactions of neuronal genesPreprint
Gjoni, K., Ren, X., Everitt, A., Shen, Y., & Pollard, K. S. (2026) · Genome Research · doi:10.1101/gr.280394.124 · Cited by 7
Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients
McQuerry, J. A., Mclaird, M., Hartin, S. N., Means, J. C., Johnston, J. J., Pastinen, T., & Younger, S. T. (2022) · Scientific Reports · doi:10.1038/s41598-022-11589-8 · Cited by 6
Causes of preterm birth: Genetic factors in preterm birth and preterm infant phenotypes
Dauengauer‐Kirlienė, S., Domarkienė, I., Pilypienė, I., Žukauskaitė, G., Kučinskas, V., & Matulevičienė, A. (2022) · Journal of obstetrics and gynaecology research · doi:10.1111/jog.15516 · Cited by 9
“ders, especially attention-deficit/hyperactivity disorder and autism spectrum disorders (ASD).(21,22) These”
BackgroundResult
Regulatory de novo mutations underlying intellectual disability
Vas, M. G. D., Boulet, F., Joshi, S. S., Garstang, M. G., Khan, T. N., Atla, G., Parry, D., Moore, D., Cebola, I., Zhang, S., et al. (2023) · Life Science Alliance · doi:10.26508/lsa.202201843 · Cited by 6
“Systematic analysis of mutations in evolutionarily ultra-conserved noncoding genomic regions has estimated that around 1 – 3% of patients with developmental disorders but lacking pathogenic coding mutations could carry pathogenic non-coding DNMs in fetal brain cis -regulatory elements (10).”
Prioritization of non-coding elements involved in non-syndromic cleft lip with/without cleft palate through genome-wide analysis of de novo mutations
Zieger, H. K., Weinhold, L., Schmidt, A., Holtgrewe, M., Juranek, S., Siewert, A., Scheer, A. B., Thieme, F., Mangold, E., Ishorst, N., et al. (2022) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2022.100166 · Cited by 6
“…general genomic features with a priori evidence for functional relevance or evolution were included; i.e., (1) 4,307 evolutionarily highly conserved non-coding elements (CNEs) based on a prior publication, 27 and (2) 1,570 enhancer regions from the VISTA enhancer browser 28 (supplemental methods).”
Background
Mapping the regulatory effects of common and rare non-coding variants across cellular and developmental contexts in the brain and heartPreprint
Marderstein, A. R., Kundu, S., Padhi, E. M., Deshpande, S., Wang, A., Robb, E., Sun, Y., Yun, C. M., Pomales-Matos, D. A., Xie, Y., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.18.638922 · Cited by 6
Genetic Variants Associated with Suspected Neonatal Hypoxic Ischaemic Encephalopathy: A Study in a South African Context
Foden, C. J., Durant, K., Mellet, J., Joubert, F., van Rensburg, J., Masemola, K., Velaphi, S., Nakwa, F. L., Horn, A. R., Pillay, S., et al. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26052075 · Cited by 6
“Disease-associated variants in non-coding regions may impact regulatory functions [43].”
Analytic and Translational Genetics
Karczewski, K. J., & Martin, A. R. (2020) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-072018-021148 · Cited by 6
Genome sequencing detects a balanced pericentric inversion with breakpoints that impact the DMD and upstream region of POU3F4 genes
Chandrasekhar, A., Mroczkowski, H. J., Urraca, N., Gross, A. M., Bluske, K. K., Thorpe, E., Hagelstrom, R. T., Schonberg, S., Perry, D., Taft, R. J., et al. (2023) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.63462 · Cited by 5
“Due to both its breadth of analytical capabilities and increasing evidence of clinical utility, cWGS is rapidly emerging as a first-tier diagnostic test that may shorten the diagnostic odyssey for patients (Short et al., 2018) (Lionel et al., 2018).”
Background
Genetics of human brain evolution
Vallender, E. J. (2019) · Progress in brain research · doi:10.1016/bs.pbr.2019.01.003 · Cited by 5
Mutational bias in spermatogonia impacts the anatomy of regulatory sites in the human genomePreprint
Kaiser, V. B., Talmane, L., Kumar, Y., Semple, F., MacLennan, M., Study, D. D. D., FitzPatrick, D. R., Taylor, M. S., & Semple, C. A. M. (2021) · Genome Research · doi:10.1101/gr.275407.121 · Cited by 6
Self-citation
Addiction Susceptibility: Genetic Factors, Personality Traits, and Epigenetic Interactions with the Gut Microbiome
Borrego-Ruiz, A., & Borrego, J. J. (2025) · Genes · doi:10.3390/genes16121447 · Cited by 4
“Variants that influence gene expression have been implicated in diverse behavioral phenotypes and psychiatric conditions, including bipolar disorder (BD), schizophrenia, autism spectrum disorder (ASD), and personality-related traits such as neuroticism [48,67–69].”
Engineering brain organoids and organ-on-chip systems for modeling neurodevelopmental and neurodegenerative pathophysiology
Banerjee, S., Chandu, P. M., Sarkar, M., Soni, T. K., Saha, M., Fathah Muhammad, L., Chatterjee, B., & Das, U. (2025) · Neurological Research · doi:10.1080/01616412.2025.2600434 · Cited by 5
Refining SARS-CoV-2 intra-host variation by leveraging large-scale sequencing data
Mostefai, F., Grenier, J., Poujol, R., & Hussin, J. (2024) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqae145 · Cited by 4
Prediction of Neurodevelopmental Disorders Based on De Novo Coding Variation
Chow, J. C., & Hormozdiari, F. (2022) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-022-05586-z · Cited by 4
“…most NDDs cases cannot be predicted using de novo coding variation alone; the exome constitutes 1–2% of the human genome and the majority of NDD-associated variants are likely to reside in non-coding regions involved in the regulation of gene expression (Short et al., 2018; Turner & Eichler, 2019).”
Background
Genetic variant interpretation for the neurologist – A pragmatic approach in the next-generation sequencing era in childhood epilepsy
Fasaludeen, A., McTague, A., Jose, M., Banerjee, M., Sundaram, S., Madhusoodanan, U. K., Radhakrishnan, A., & Menon, R. N. (2024) · Epilepsy Research · doi:10.1016/j.eplepsyres.2024.107341 · Cited by 4
Predicting regulatory mutations and their target genes by new computational integrative analysis: A study of follicular lymphoma
Wang, J., Yang, M., Ali, O., Dragland, J. S., Bjørås, M., & Farkas, L. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108787 · Cited by 4
Identification and characterization of transcribed enhancers during cerebellar development through enhancer RNA analysis
Ramirez, M., Robert, R., Yeung, J., Wu, J., Abdalla-Wyse, A., & Goldowitz, D. (2023) · BMC Genomics · doi:10.1186/s12864-023-09368-4 · Cited by 4
Epigenomic Profiling and Single-Nucleus-RNA-Seq Reveal Cis -Regulatory Elements in Human Retina, Macula and RPE and Non-Coding Genetic VariationPreprint
Cherry, T. J., Yang, M. G., Harmin, D. A., Tao, P., Timms, A. E., Bauwens, M., Allikmets, R. L., Jones, E., Chen, R., Baere, E. D., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/412361 · Cited by 4
“Such disorders may arise from mutations in genes encoding TFs, chromatin remodeling factors or mutations affecting CREs themselves (Brandler et al., 2018; Iwase et al., 2017; Short et al., 2018) (Jeong et al.”
Background
Identification of essential regulatory elements in the human genomePreprint
Wells, A. C., Heckerman, D. E., Torkamani, A., Li, Y., Ren, B., Telenti, A., & di Iulio, J. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/444562 · Cited by 5
A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes ProjectPreprint
Blakes, A. J. M., Wai, H. A., Davies, I., Moledian, H. E., Ruiz, A., Thomas, T., Bunyan, D. J., Thomas, N. S., Burren, C. P., Greenhalgh, L., et al. (2022) · medRxiv · doi:10.1101/2022.01.28.22270002 · Cited by 4
Proteome-Wide Assessment of Clustering of Missense Variants in Neurodevelopmental Disorders Versus CancerPreprint
Ng, J. K., Chen, Y., Akinwe, T. M., Heins, H. B., Mehinovic, E., Chang, Y., Payne, Z. L., Manuel, J. G., Karchin, R., & Turner, T. N. (2024) · medRxiv · doi:10.1101/2024.02.02.24302238 · Cited by 4
Decoding common and rare noncoding variant effects across cellular and developmental contexts
Marderstein, A. R., Kundu, S., Padhi, E. M., Deshpande, S., Wang, A., Robb, E., Sun, Y., Yun, C. M., Pomales-Matos, D. A., Xie, Y., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02619-6 · Cited by 11
“Although de novo mutations in conserved coding 59 and promoter 60 regions are known to contribute to autism spectrum disorder (ASD), linking distal noncoding de novo mutations to ASD has remained a challenge 60–63 .”
Creation and evaluation of full-text literature-derived, feature-weighted disease models of genetically determined developmental disorders
Yates, T. M., Lain, A., Campbell, J. W., FitzPatrick, D. R., & Simpson, T. I. (2022) · Database · doi:10.1093/database/baac038 · Cited by 3
Self-citation
Benchmarking of variant pathogenicity prediction methods using a population genetics approach
Gudkov, M., Thibaut, L., Monger, S., Das, D., Winlaw, D. S., Dunwoodie, S. L., Giannoulatou, E., Congenital Heart Disease Synergy Study Group, Dunwoodie, S. L., Winlaw, D. S., et al. (2024) · Bioinformatics Advances · doi:10.1093/bioadv/vbaf227 · Cited by 3
“The possibility of using the Adjusted Proportion of Singletons family of metrics, and specifically MAPS, for benchmarking was first expressed in 2018, before the official publication of the currently latest version of MAPS in 2020 (Short et al. 2018).”
Genomically Aided Diagnosis of Severe Developmental Disorders
FitzPatrick, D. R., & Firth, H. V. (2020) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-120919-082329 · Cited by 3
Self-citation
Identification of 3’-UTR single nucleotide variants and prediction of select protein imbalance in mesial temporal lobe epilepsy patients
Chaudhuri, T., Chintalapati, J., & Hosur, M. V. (2021) · PLoS ONE · doi:10.1371/journal.pone.0252475 · Cited by 3
Emerging role of epigenetics in human neurodevelopmental disorders
Mastrototaro, G., Sessa, A., & Zaghi, M. (2023) · Elsevier eBooks · doi:10.1016/b978-0-443-18661-5.00022-1 · Cited by 3
Identification and functional modelling of plausibly causative cis-regulatory variants in a highly-selected cohort with X-linked intellectual disability
Bengani, H., Grozeva, D., Moyon, L., Bhatia, S., Louros, S. R., Hope, J. E., Jackson, A., Prendergast, J. G. D., Owen, L. J., Naville, M., et al. (2021) · PLoS ONE · doi:10.1371/journal.pone.0256181 · Cited by 3
“DNM enrichment is also evident in evolutionarily conserved, brain-active CRE in severe DD at a cohort level [13] but the confident assignment of variants as causative in affected individuals is not yet possible [14].”
BackgroundSelf-citation
The genomic basis of medicine
Stankiewicz, P., & Lupski, J. R. (2020) · doi:10.1093/med/9780198746690.003.0030 · Cited by 3
Structural disruption of genomic regions containing ultraconserved elements is associated with neurodevelopmental phenotypesPreprint
McCole, R. B., Saylor, W., Redin, C. E., Fonseka, C. Y., Brand, H., Erceg, J., Talkowski, M. E., & Wu, C.-T. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/233197 · Cited by 3
Variant-resolved prediction of context-specific isoform variation with a graph-based attention model
Litman, A., Pan, Z., Sokolova, K., Fang, J., Marvin, T. A., Sauerwald, N., Park, C. Y., Theesfeld, C. L., & Troyanskaya, O. G. (2026) · Cell Genomics · doi:10.1016/j.xgen.2025.101126 · Cited by 2
“57,63 68 We classified all brain-expressed exons as either microexons or long exons (>27 nt) and assessed the impact of nearby DNVs ( n = 93,571).”
Non-coding structural variants disrupt FOXG1 transcriptional regulation in early neurodevelopment
Hamerlinck, L., D’haene, E., Vaughan, M., Loon, N. V., Baca, M. D. R. P., Leimbacher, S., Kosicki, M., Colombo, L., Genbrugge, L., Vantomme, L., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-73770-1 · Cited by 4
“1.0, Supplementary Data 6) of the hs1523 element in individuals with neurodevelopmental disordersreinforces a criticalneurodevelopmental role for the hs1523/ hs342 enhancer region 48,54 .”
Influential
Statistical methods for assessing the effects of de novo variants on birth defects
Xie, Y., Wu, R., Li, H., Dong, W., Zhou, G., & Zhao, H. (2024) · Human Genomics · doi:10.1186/s40246-024-00590-z · Cited by 2
“…expected distance from simulated missense DNVs, and the probability of missense variants being as or more clustered than the null model is defined as pClustering [34]. pMisEnrich and pClustering are then combined using Fisher’s method to obtain pMEC . pMEC = combined ( pMisEnrich , pClustering ).”
Method
High-throughput omics in the precision medicine ecosystem
Tebani, A., & Bekri, S. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-819178-1.00003-4 · Cited by 5
NGS: Gestern, heute und morgen
Bolz, H. J., & Hoischen, A. (2019) · Medizinische Genetik · doi:10.1007/s11825-019-0240-8 · Cited by 2
Post-transcriptionally impaired de novo mutations contribute to the genetic etiology of four neuropsychiatric disordersPreprint
Mao, F., Wang, L., Zhao, X., Li, Z., Xiao, L., Rao, R. C., Li, J., Teng, H., He, X., & Sun, Z. S. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/175844 · Cited by 3
Predicting localized affinity of RNA binding proteins to transcripts with convolutional neural networksPreprint
Kitaygorodsky, A., Jin, E., & Shen, Y. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.06.02.446817 · Cited by 2
“Recently several studies have shown that post-transcriptional regulation acts as a major link between rare noncoding variants and human disease [1-3].”
Background
A Genomic Language Model for Zero-Shot Prediction of Promoter Variant EffectsPreprint
Shearer, C. A., Orenbuch, R., Teufel, F., Steinmetz, C. J., Ritter, D., Xie, E., Gazizov, A., Spinner, A., Frazer, J., Dias, M., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.11.623015 · Cited by 2
“…has yielded valuable insights, several studies suggest that individual SNVs are unlikely to have large effects at an organismal scale, especially in non-coding regions [34, 56], due to the redundancy built into biological systems and the generally smaller effect sizes of non-coding variants [68].”

Authors: Short, P. J., McRae, J. F., Gallone, G., Sifrim, A., Won, H., Geschwind, D. H., Wright, C. F., Firth, H. V., FitzPatrick, D. R., Barrett, J. C., & Hurles, M. E.
Affiliations: Wellcome Sanger Institute (GB)
University of California, Los Angeles (US)
University of Exeter (GB)
Cambridge University Hospitals NHS Foundation Trust (GB)
Western General Hospital (GB)
Corresponding author: Hurles, Matthew E.
ORCID: Short, Patrick J.
McRae, Jeremy F.
Sifrim, Alejandro
Won, Hyejung
Geschwind, Daniel H.
Wright, Caroline F.
Firth, Helen V.
FitzPatrick, David R.
Barrett, Jeffrey C.
Hurles, Matthew E.
Venue: Nature
Publisher: Springer Science and Business Media LLC
Published: 2018-03
Volume: 555
Issue: 7698
Pages: 611-616
ISSN: 0028-0836 (ISSN-L)
1476-4687
DOI: 10.1038/nature25983
PMC: PMC5912909
OpenAlex: W2599110791
Cited by: 274
References: 56
Citations by year: 2026: 14 · 2025: 13 · 2024: 34 · 2023: 22 · 2022: 39 · 2021: 43 · 2020: 33 · 2019: 48 · 2018: 22
FWCI: 22.02
Type: journal article
Language: en
Open access: green
doi.org
Licence: cc-by-nd
www.springer.com/tdm (tdm)
Locations: Nature (publishedVersion)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
Open Research Exeter (University of Exeter) (acceptedVersion)
RePEc: Research Papers in Economics (submittedVersion)
eScholarship (California Digital Library) (submittedVersion)
Figshare (submittedVersion)
Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
Funders: Wellcome Trust (WT 098051, 098051)
Medical Research Council (MC_UU_00007/3)
National Institute of Mental Health (U01MH105666, R01MH110927, R00MH113823, K99MH113823)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
Keywords: de novo mutations, regulatory elements, neurodevelopmental disorders, recurrent mutations, rare variants, genetic heterogeneity
MeSH terms: Brain, Developmental Disabilities, Female, Fetus, Humans, Male, Mutation, Regulatory Sequences, Nucleic Acid, Conserved Sequence, Evolution, Molecular, Exome, Neurodevelopmental Disorders

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De novo mutations in regulatory elements in neurodevelopmental disorders

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