The DOI matches its Crossref record; 90 of the 90 references it cites were found in a registry or an index.
A genomic mutational constraint map using variation in 76,156 human genomes
Open accessPublished version of a preprint
Abstract
The depletion of disruptive variation caused by purifying natural selection (constraint) has been widely used to investigate protein-coding genes underlying human disorders 1-4, but attempts to assess constraint for non-protein-coding regions have proved more difficult. Here we aggregate, process and release a dataset of 76,156 human genomes from the Genome Aggregation Database (gnomAD)-the largest public open-access human genome allele frequency reference dataset-and use it to build a genomic constraint map for the whole genome (genomic non-coding constraint of haploinsufficient variation (Gnocchi)). We present a refined mutational model that incorporates local sequence context and regional genomic features to detect depletions of variation. As expected, the average constraint for protein-coding sequences is stronger than that for non-coding regions. Within the non-coding genome, constrained regions are enriched for known regulatory elements and variants that are implicated in complex human diseases and traits, facilitating the triangulation of biological annotation, disease association and natural selection to non-coding DNA analysis. More constrained regulatory elements tend to regulate more constrained protein-coding genes, which in turn suggests that non-coding constraint can aid the identification of constrained genes that are as yet unrecognized by current gene constraint metrics. We demonstrate that this genome-wide constraint map improves the identification and interpretation of functional human genetic variation.
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 source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Neutral, non-disease causing SALL1 variants (predicted loss-of-function, pLoF) were obtained from the gnomAD 48 database (v4.1.0, https://gnomad.broadinstitute.org/), with the following selection criteria: >2 cases found for each specific variant, no flag associated with dubious sequencing quality or possible pathogenicity.”
From Tetramerisation governs SALL transcription factor function in development and disease (2025) · cites this paper as [48]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“we found that SALL1 is depleted of similar mutations in the healthy population, as a gnomAD 48 database (v4.1.0, https://gnomad.broadinstitute.org/) search identified only three variants, all at the C-terminus of the protein after SALL1 ZFC4”
From Tetramerisation governs SALL transcription factor function in development and disease (2025) · cites this paper as [48]
The cited source says what the claim attributes to it.
In the citing paper
“We note that there are many SNPs common (>5%) in these Polynesian sequences that are entirely absent from gnomAD (Fig. 1B) (6).”
From Message in a bottleneck: Nested founder effects from French Polynesia to Rapa Nui and Hawaiʻi (2026) · cites this paper as [6]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“For inclusion on these population-specific screening panels, the ACMG recommends a carrier frequency of >1/200 (5, 6).”
From Message in a bottleneck: Nested founder effects from French Polynesia to Rapa Nui and Hawaiʻi (2026) · cites this paper as [6]
Experimental — accuracy not yet measured
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
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247
Self-citationpROC: an open-source package for R and S+ to analyze and compare ROC curves
Robin, X., Turck, N., Hainard, A., Tiberti, N., Lisacek, F., Sanchez, J.-C., & Müller, M. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-77 · Cited by 13,697
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-citationThe mutational constraint spectrum quantified from variation in 141,456 humans
Karczewski, K. J., Francioli, L. C., Tiao, G., Cummings, B. B., Alföldi, J., Wang, Q., Collins, R. L., Laricchia, K. M., Ganna, A., Birnbaum, D. P., et al. (2020) · Nature · doi:10.1038/s41586-020-2308-7 · Cited by 9,434
Self-citationIntegrative 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
ClinVar: improving access to variant interpretations and supporting evidence
Landrum, M. J., Lee, J. M., Benson, M., Brown, G. R., Chao, C., Chitipiralla, S., Gu, B., Hart, J., Hoffman, D., Jang, W., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1153 · Cited by 4,196
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
Cited by
Sorted by citations
Items 701–800 of 1,003
Variants in NR6A1 as a cause for congenital renal, vertebral and uterine anomaliesPreprint
Jacquinet, A., Flasse, L. C., Dohet, M., Vanhaeren, R., Pendeville, H., Saunders, C., Lehman, A., Pienkowski, C., Morcel, K., Guerrier, D., et al. (2025) · medRxiv · doi:10.1101/2025.01.08.24319478 · Cited by 3
MutationAssessor in cBioPortalPreprint
Su, Y., Li, X., Reva, B. A., Antipin, Y., Schultz, N. D., de Bruijn, I., & Sander, C. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.10.669566 · Cited by 4
X-linked intellectual disability related to a novel variant of KLHL15
Kido, J., Egami, K., Misumi, Y., Sugawara, K., Tsuchida, N., Matsumoto, N., Ueda, M., & Nakamura, K. (2023) · Human Genome Variation · doi:10.1038/s41439-023-00248-7 · Cited by 2
Živković, M., Stanković, A., KONCAR, I. B., Kolaković, A., Bošković, M., & Djurić, T. (2024) · Molecular Biology Reports · doi:10.1007/s11033-024-09458-w · Cited by 2
Another face of RASA1: Report of familial germline variant in RASA1 with dysmorphic features
Hume, E., Cossio, M.-L., Paula Vargas, I., Celis, M. P. C., Maccioni, A., & Guillermo Lay-Son, R. (2024) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.63711 · Cited by 2
Gaschignard, M., Domenach, L., Lamireau, D., Guibet, C., Roche, S., Richard, E., Redonnet‐Vernhet, I., Mesli, S., & Lebreton, L. (2024) · Frontiers in Genetics · doi:10.3389/fgene.2024.1249480 · Cited by 2
Mammadova, D., Kraus, C. S., Leis, T., Popp, B., Zweier, C., Reis, A., & Trollmann, R. (2024) · Frontiers in Neurology · doi:10.3389/fneur.2024.1458109 · Cited by 2
Lentschat, H., Ließmann, F., Tydings, C. W., Schermeng, T., Stichel, J., Urban, N. D., Schaefer, M., Meiler, J., & Beck‐Sickinger, A. G. (2024) · Angewandte Chemie · doi:10.1002/ange.202417786 · Cited by 2
Her, H.-L., Yee, B. A., Xu, S., Boyle, E. A., Rothamel, K. L., Zhao, Z. Z., Blue, S. M., Mueller, J. R., Park, S. S., Nguyen, G. G., et al. (2026) · Cell Systems · doi:10.1016/j.cels.2026.101588 · Cited by 3
Properties of incompletely penetrant cardiomyopathy-associated genome variants
Zaicenoka, M., Ramensky, V. E., Kiseleva, A. V., Bukaeva, A. A., Ershova, A. I., Meshkov, A. N., & Drapkina, O. M. (2025) · CARDIOVASCULAR THERAPY AND PREVENTION · doi:10.15829/1728-8800-2024-4262 · Cited by 2
Autistic behavior is a common outcome of biallelic disruption of PDZD8 in humans and mice
Pantiru, A., de Sompele, S. V., Ligneul, C., Chatelain, C., Barrea, C., Lerch, J. P., Filippi, B., Alkan, S., Baere, E. B. W. D., Johnston, J., et al. (2025) · Molecular Autism · doi:10.1186/s13229-025-00650-8 · Cited by 4
Development of Publicly Available Forensic DNA Sequence Mixture Data
Romsos, E. L., Kiesler, K. M., Steffen, C. R., Borsuk, L. A., Riman, S., Mullen, L. E., Irwin, J. A., Vallone, P. M., & Gettings, K. B. (2025) · Genes · doi:10.3390/genes16030333 · Cited by 2
Howard, C. J., Abell, N. S., Osuna, B. A., Jones, E. M., Chan, L. Y., Chan, H. W.-S., Artis, D. R., Asfaha, J. B., Bloom, J. S., Cooper, A. R., et al. (2024) · eLife · doi:10.7554/elife.104725.3 · Cited by 26
Detecting known neoepitopes, gene fusions, transposable elements, and circular RNAs in cell-free RNA
Mahajan, M., & Hemberg, M. (2025) · Bioinformatics · doi:10.1093/bioinformatics/btaf138 · Cited by 2
Englisch, C., Jäger, R., Gassner, J., Assinger, A., Preusser, M., Valent, P., Pabinger, I., & Ay, C. (2025) · Research and Practice in Thrombosis and Haemostasis · doi:10.1016/j.rpth.2025.102882 · Cited by 2
“…in Catalogue of somatic mutations in cancer (COSMIC) [24], population allele frequency 0.1% in Genome aggregation database (gnomAD) databases [25], protein-coding, nonsynonymous, variant allele frequency (VAF) between 2% to 40% or 60% to 90% (except for JAK2 V617F mutations, for which all…”
InfluentialThe landscape of non-reference SINE-VNTR-Alus in amyotrophic lateral sclerosis
Pfaff, A. L., Bubb, V. J., Quinn, J. P., & Kõks, S. (2025) · Experimental Biology and Medicine · doi:10.3389/ebm.2025.10600 · Cited by 2
Brunner, M., Meylan-Merlini, J., Muriset, M., Oreshkov, S., Messina, A., Messerer, M., Daniel, R. T., Hewer, E., Brouland, J., & Santoni, F. A. (2025) · BJC Reports · doi:10.1038/s44276-025-00155-0 · Cited by 2
Cuillerier, A., Goodman, A. S., Lawrence, C. J., Villeneuve‐Cloutier, N., Armour, C. M., Bhola, P. T., Bourque, D. K., Carter, M. T., Lazier, J., Sawyer, S. L., et al. (2025) · Clinical Genetics · doi:10.1111/cge.70008 · Cited by 2
Structural diversity and evolutionary constraints of oxidative phosphorylation
Cabrera-Alarcón, J. L., Rosa-Moreno, M., Sánchez-García, L., Hernansanz‐Agustín, P., Jiménez-Gómez, M. C., Martínez, F., Sánchez‐Cabo, F., & Enrı́quez, J. A. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.100945 · Cited by 3
Nynäs, E., Sulkava, S., Nurmi, A. K., Suvanto, M., Aittomäki, K., & Nevanlinna, H. A. (2025) · Genetics in Medicine · doi:10.1016/j.gim.2025.101521 · Cited by 2
Antysheva, Z., Esibov, A. A., Avsievich, E. S., Petriaikina, E. S., Yudin, V. S., Keskinov, A. A., Yudin, S. M., Svetlichnyy, D. V., Krupinova, J. A., Ивашечкин, А. А., et al. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26146648 · Cited by 2
“1.0 and UK Biobank (Allele Frequency Browser) databases [19,21].”
InfluentialComprehensive genotype-phenotype analysis in POLR3-related disorders
Michell‐Robinson, M. A., Perrier, S., Gauthier, S., Derksen, A., Sabbagh, Q., Girbig, M., Misiaszek, A. D., Pizzino, A. M., Renaud, D. L., Pereira, D. D. A., et al. (2025) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2025.100481 · Cited by 2
Khalid, Z., Adams, M., Anees, M., Tehreem, R., Azeem, A., Ahmed, A., Ubeyratna, N., Salter, C. G., Leslie, J. S., Voutsina, N., et al. (2025) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.64191 · Cited by 2
“overrepresented in current reference genomic databases (Sirugo et al. 2019), comprising 77.1% of individuals within the Genome Aggregation Database (gnomAD v4) (Chen et al. 2024), despite Europeans comprising only 9.1% of the global population (US Census Bureau 2024).”
InfluentialMassively parallel characterization of non-coding de novo mutations in autism spectrum disorder
Chen, C., Guo, S., Shi, Y., Gu, X., Xu, Z., Chen, Y., Gu, Y., Qin, N., Jiang, Y., Dai, J., et al. (2025) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2025.07.008 · Cited by 2
Complexities in Variant Analysis, Classification, and Interpretation in Kidney Disease–Related Genes
Westemeyer, M. A., Bloom, M. S., Byrne, A. B., & Charu, V. (2025) · Seminars in Nephrology · doi:10.1016/j.semnephrol.2025.151646 · Cited by 3
Quintana, K., Hutchison, M. R., Wong, C. S., Alkhouri, R. H., Hardy, L., Clericuzio, C. L., & Marble, M. (2025) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.64203 · Cited by 2
Hsu, A. P., Karlins, E., Lack, J., Pepper, T. J., Lau, K., Marshall‐Batty, K. R., Priel, D. L., Davis, J., Fink, D. L., Zerbe, C. S., et al. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1640496 · Cited by 4
Shah, J., Mondal, D., Jain, D. K., Mhatre, P., Patel, K., Iyer, A., Pandya, M., Menghani, B., Dave, G., Sheth, J. J., et al. (2025) · BMC Medical Genomics · doi:10.1186/s12920-025-02204-6 · Cited by 3
“…npInv and SVIM and QUAL score of > 1 for variants called by NanoVar; (b) the presence of the SV in the general population using gnomAD [42, 43] and DGV [44] databases using minor allele frequency (MAF) cutoff of at 1%; (c) number of genes over-lapping the SV requiring at least one gene…”
Ritter, D., Badduke, C., Doonanco, K., Kang, H. C., Pesaran, T. F., Ridd, S., Sheen, C., Farncombe, K. M., Giles, R. H., Luo, M., et al. (2026) · Genetics in Medicine · doi:10.1016/j.gim.2026.102589 · Cited by 2
Cell-free DNA as a potential alternative to genomic DNA in genetic studies
Zeng, J., Zhu, H., Wang, Y., Zeng, G., Liu, P., Ou, R., Lan, X., Zheng, Y., Zhao, C., Li, L., et al. (2025) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaf119 · Cited by 2
“Notable examples include the 1KGP (1000 Genomes Project) [ 2 ], the gnomAD (Genome Aggregation Database) [ 3 ], the TOPMed (Trans-Omics for Precision Medicine) project [ 4 ], the UKB (UK Biobank) [ 5 ], the ChinaMAP (China Metabolic Analytics Project) [ 6 ], and the CKB (China Kadoorie Biobank) [ 7…”
Zamani, S. A., Karyadi, D. M., Hartley, S. W., Gibson, T. M., Sampson, J. N., Kraft, P., Chanock, S. J., & Morton, L. M. (2025) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djaf260 · Cited by 2
APOE p.(Leu167del) variant in hypercholesterolemia: Prevalence & phenotypic expression
Bello-Álvarez, D., Cenarro, A., Bea, A. M., Marco-Benedí, V., Jarauta, E., Ortiz-Palma, P., Ortega, E., González-Lleó, A. M., & Civeira, F. (2025) · Journal of clinical lipidology · doi:10.1016/j.jacl.2025.09.016 · Cited by 2
From paleness to albinism: Contribution of OCA2 exon 10 skipping to hypopigmentation
Mercier, E., Trégouët, D., Campagne, S., Michaud, V., Green, D. J., Mesdaghi, S., Gallais, O. L., Jouannigot-Castano, O., Rigden, D., Estay-Ahumada, C., et al. (2025) · bioRxiv · doi:10.1371/journal.pgen.1011801 · Cited by 2
Evaluation of Long-Read Genome Sequencing for Genomic Profiling of Myeloid Cancers
Abel, H., Mahgoub, M., Davarapalli, N., Kodgule, R., Miller, C. A., Fulton, R. S., Fronick, C. C., Markovic, C., Heath, S. E., Payton, J. E., et al. (2025) · Journal of Molecular Diagnostics · doi:10.1016/j.jmoldx.2025.09.001 · Cited by 3
Valentin, K., Kustermann, M., Schneider, M. R., Aminfar, H., Vollnhofer, K., Wedrich, A., Stapf, C., Bertich, M., Ritter, M., Mendrina, T., et al. (2025) · Genetics in Medicine · doi:10.1016/j.gim.2025.101595 · Cited by 2
Cai, J., Jin, F., Cheng, N., Xia, J., & Ye, C.-L. (2025) · ACS Omega · doi:10.1021/acsomega.5c05407 · Cited by 2
Altay, M. F., Gregor, A., Braun, D., Rieubland, C., Gautschi, M., Hoigné, E. P., Schiller, R., Keren, B., Afenjar, A., Undiagnosed Diseases Network, et al. (2025) · European Journal of Human Genetics · doi:10.1038/s41431-025-01966-y · Cited by 2
Bennett, M. F., Corbett, M. A., Kroes, T., Canafoglia, L., Oliver, K. L., Cameron, J. M., Sikta, N., Munro, J. E., Fearnley, L. G., Ibáñez, K., et al. (2025) · Brain Communications · doi:10.1093/braincomms/fcaf433 · Cited by 2
“27 The gnomAD genotypes were generated using an optimized version of ExpansionHunter (v5.”
Al‐Shafai, K. N., Arar, S., Jamil, A., Azzah, A., Mancha, M. A., Saraiva, L. R., & Abbas, T. O. (2025) · Genes · doi:10.3390/genes16111340 · Cited by 2
“1.0 [36].”
InfluentialPast, present, and future of genomic technologies in cerebellar ataxias
Lucain, M., Duffourd, Y., Malbos, M., Vitobello, A., Thauvin‐Robinet, C., & Thomas, Q. (2025) · Journal of Neurology · doi:10.1007/s00415-025-13478-2 · Cited by 4
“The final steps involve clinical interpretation based on population databases (such as gnomAD [47]), variant effect predictors [48–50], and established classification guidelines (e.g., ACMG criteria [51]).”
Paired tumor-normal sequencing provides insights into the CDKN2A-associated tumor spectrum
Breen, K. E., Mehta, N. N., Ravichandran, V., Mehine, M. M., Gao, C., Fiala, E. M., Mukherjee, S., Gao, M., Arora, K. S., Kemel, Y. M., et al. (2025) · npj Precision Oncology · doi:10.1038/s41698-025-01155-6 · Cited by 2
“1.0 53,54 .”
InfluentialGenome region aware CADD thresholds for noncoding variant prioritization
Tenywa, J.-F., Lamouche, J.-B., Baer, S., Nicaise, S., Béchec, A. L., Piton, A., & Muller, J. (2025) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaf157 · Cited by 2
“0 was downloaded from https:// gnomad.broadinstitute.org/ data (GRCh38/hg38 genome build) [ 13 ].”
InfluentialBülbül, A., Gerdan, G., Portakal, C., Bajrami, S., & Akyerli, C. B. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms262311244 · Cited by 2
“Somatic variation profiling of 23 tumors revealed 1017 alterations dominated by missense mutations (61.2 %), while gnomAD exome [7] data showed these variants are exceedingly rare in the general population (median MAF about 5.5 × 10 − 6 ), indicating a prevalently protein-altering and…”
InfluentialZamora, J., & Faùndes, V. (2025) · Neurogenetics · doi:10.1007/s10048-025-00872-1 · Cited by 2
A rare variant in TRIOBP linked to occupational noise exposure in Meniere disease
Cruz‐Granados, P., Bortoletto, G. B., Zhang, Y., Nadar‐Ponniah, P. T., Bagheri-Loftabad, K., Sartorato, E. L., Sánchez‐Sellero, I., Soto-Varela, A., & Lopez-Escamez, J. A. (2025) · Genes & Diseases · doi:10.1016/j.gendis.2025.101993 · Cited by 2
“1.0 26 to calculate the odds ratio (OR), 95% confidence interval (CI) and p -value adjusted using the Bonferroni correction.”
InfluentialSrinivasan, S., Subramanian, S., Zhou, H., Hoppmann, A., Metzger, P., Boerries, M., & Ramamoorthy, S. (2025) · BMC Genomics · doi:10.1186/s12864-025-12466-0 · Cited by 2
“1) [37, 51].”
Levine, J. M., Calame, D. G., Sangermano, R., Du, H., Saad, A., Lisfeld, J., Bierhals, T., Denecke, J., Üçtepe, E., Çelik, M. Y., et al. (2026) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.12.011 · Cited by 2
Remodeling of XIST regulatory landscape during primate evolution
Cazottes, E., Alfeghaly, C., Rognard, C., Necşulea, A., Loda, A., Castel, G., Villacorta, L., Dong, M. X., Heard, É., Aksoy, I., et al. (2026) · Science Advances · doi:10.1126/sciadv.adw5839 · Cited by 5
Thomas, M. R., Buckle, I., Constantinescu‐Bercu, A., de Groot, R., McCann, S., & Scully, M. (2026) · Journal of Thrombosis and Haemostasis · doi:10.1016/j.jtha.2026.01.023 · Cited by 2
Wagenknecht, J. B., Haque, N., Jorge, S. D., Ratnasinghe, B. D., Urrutia, R. A., Gahl, W. A., Ziegler, S. G., & Zimmermann, M. T. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27041832 · Cited by 2
Tutorial for variant interrogation in tumor samples
Arseneau, R. J., MacLean, L. K., Boudreau, J. E., & Gaston, D. (2026) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1013924 · Cited by 2
A functional ancestry-linked regulatory haplotype influences CYP2D6 expression
McCoy, M. (2026) · The Pharmacogenomics Journal · doi:10.1038/s41397-026-00398-1 · Cited by 2
“These fi ndings reinforce concerns regarding the Eurocentric bias of reference datasets, such as gnomAD, and underscore the importance of ancestry-aware variant interpretation [16, 17, 42].”
Regional nonsense constraint offers biological and clinical insights into genetic disease
Blakes, A. J. M., Whiffin, N., Johnson, C. A., Ellingford, J. M., & Banka, S. (2026) · Nature Communications · doi:10.1038/s41467-026-69983-z · Cited by 3
Self-citationA comprehensive framework for the interpretation of TTN missense variants
Feo, M. F. D., Rees, M., Lillback, V., Kho, A. L., Meybatova, A., Holt, M., Jungbluth, H., Francesco Muntoni, A., Baranello, G., Sárközy, A., et al. (2026) · Genome Medicine · doi:10.1186/s13073-026-01605-1 · Cited by 2
“Together with AlphaMissense predictions, we reported available data on Minor Allele Frequency (MAF) for each TTN missense variants from the gno-mAD database (Additional File 1) [30].”
Brunello, F. G., Castro, S., Zaiat, J., Sansó, G., Izquierdo, A., Urrutia, M., Rey, R. A., Marti, M. A., Grinspon, R. P., & Tellechea, M. L. (2026) · Human Molecular Genetics · doi:10.1093/hmg/ddag007 · Cited by 3
Okuducu, Y. K., Verwillow, A. B., Fracchia, M. S., Abulhamail, A., Yonker, L. M., Nelson, B. A., & Kinane, T. B. (2026) · Pediatric Pulmonology · doi:10.1002/ppul.71539 · Cited by 2
Fortuño, C., Zhang, J., Koufariotis, L. T., Hollway, G. E., Wood, S., Pearson, J. V., Simpson, P. T., Lakhani, S. R., Reed, A. E. M., Thorne, H., et al. (2026) · EBioMedicine · doi:10.1016/j.ebiom.2026.106199 · Cited by 2
“38 A cutoff point of 42 is currently considered an US Food and Drug Administration-approved biomarker to select ovarian cancer patients for PARP inhibition, 39 which we used to differentiate between deficiency and proficiency in this study.”
Massively parallel quantification of mutational impact on IAPP amyloid formation
Badia, M., Batlle, C., & Bolognesi, B. (2026) · Nature Communications · doi:10.1038/s41467-026-70611-z · Cited by 3
“Comparing nucleation scores to allele frequency in the population and in diabetes patients 50 IAPP substitutions have been identi fi ed in the human population, but their clinical signi fi cance remains unknown 69 .”
Probing Electrostatics in a DNA Repair Enzyme with a pH-Sensitive Nitroxyl Spin Label
Ovcherenko, S. S., Bulgakov, N. A., Litvinov, I. A., Shernyukov, А. V., Kuznetsov, D. A., Endutkin, A. V., Zharkov, T. D., Kupryushkin, M. S., Kirilyuk, I. A., Zharkov, D. O., et al. (2026) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.5c07587 · Cited by 2
Kobayashi, T., Yoneda, M., Duseja, A., Fan, J.-G., Nersesov, A., & Nakajima, A. (2026) · Clinics in Liver Disease · doi:10.1016/j.cld.2026.01.010 · Cited by 3
Membrane Protein Insertion in Mammalian Cells
Guna, A., Nguyen, V. N., Stevens, T. A., & Voorhees, R. M. (2026) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-080125-020218 · Cited by 2
Isong, J. A., Ajakwe, S. O., & Kim, D. (2026) · IEEE Internet of Things Journal · doi:10.1109/jiot.2026.3680265 · Cited by 2
“Population-stratified reference allele frequencies for the AFC defense layer are derived from the respective dataset panels or gnomAD v4 [34].”
Biallelic variants in FAT3 cause axonal neuropathy with multisystem neurodevelopmental features
Higuchi, Y., Yoshizaki, K., Nakanishi, K., Yuan, J., Hobara, T., Kojima, F., Hiramatsu, Y., Ando, M., Yoshimura, A., Nozuma, S., et al. (2026) · Genetics in Medicine · doi:10.1016/j.gim.2026.102570 · Cited by 2
Comprehensive overview of the global pharmacogenetic and functional variability in NUDT15
Zhou, Y., Lauschke, L. M., & Lauschke, V. M. (2026) · Human Genomics · doi:10.1186/s40246-026-00959-2 · Cited by 2
“In addition to published studies, we included population frequency data from the Genome Aggregation Database (gnomAD) [6], the Phase 3 1000 Genomes Project [2], the All of Us Research Program (2024) and the Norwegian Variant Frequency Database (https://variant.norgene.no/).”
Clinical features of syndromic microphthalmia in two novel RARB variants
Koyanagi, Y., Anzai, H., Yoshida, T., Tominaga, M., Abe, Y., Kosaki, R., Matsubara, K., Fukami, M., & Nishina, S. (2026) · Human Genome Variation · doi:10.1038/s41439-026-00345-3 · Cited by 2
“Common variants were fi ltered using the Genome Aggregation Database (https:// gnomad.broadinstitute.org/) 13 and Tohoku Medical Megabank Organization (4.7KJPN, https://jmorp.megabank.tohoku.ac.jp/) 14 .”
The Global Parkinson's Disease Genetics ( GP2 ) Genome Browser
Fang, Z., Grant, R. H., Vitale, D., Hernández, C. F., Hong, S., Leonard, H. L., Makarious, M. B., Lange, L. M., Solomonson, M., Heutink, P., et al. (2026) · Movement Disorders · doi:10.1002/mds.70309 · Cited by 4
Self-citationGenomic approaches for understanding the evolution of the human brain
Song, J. H. T., Greenberg, M. E., Reich, D., & Walsh, C. A. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02277-1 · Cited by 2
Citywide premarital genomic screening in a Middle Eastern population
Alblooshi, K., Sharaf, R. R., Shenbagam, S., Sinha, S., Jain, R., Yaslam, S., Alfalasi, R., Abdulbaki, A., Alyassi, A., Alyafei, H., et al. (2026) · Nature Medicine · doi:10.1038/s41591-026-04251-7 · Cited by 2
“Variants with quality ≥ 30, read depth ≥ 10 and genotype quality ≥ 30 were categorized as high-quality variants and were further annotated, using VarSeq (Golden Helix) for allele frequency (Genome Aggregation Database) 35 , reported pathogenic or likely pathogenic status (ClinVar) 36 , reported disease-causing mutatio…”
Ranallo-Benavidez, T. R., Hao, Y., Volpe, E., Jehangir, M., Fukushima, N. H., Stephens, Z. D., Mbegbu, O., Ungaro, M. T., Reiman, R. A., Molnar, J., et al. (2026) · Nucleic Acids Research · doi:10.1093/nar/gkag333 · Cited by 3
“To confirm whether the BJ and IMR-90 SNVs and indels were novel or present in the general population, we compared them to gnomAD [ 47 ] (Fig.”
InfluentialComprehensive mutagenesis defines the functional landscape of human α-tubulin
Xu, K., Guo, Z., Chen, Z., Li, M., Chen, Z., Zhang, D., Wang, Y., Chai, Y., Zhang, J., Wang, H., et al. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2600822123 · Cited by 3
Carrier Frequencies of Medically Actionable Pathogenic Variants in the Russian Population
Suvorova, Y. M., Monakhova, A., Chekanov, N., Musharova, O., Moskovkina, E., Zaigrin, I. V., Antonov, I., Klimchuk, O., Pustoshilov, D., Zorina, D., et al. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27125344 · Cited by 2
“1.2 [42]).”
InfluentialYigit, A., Pekerbaş, M., Salman, B., Bulut, K., Ozzeybek, E., Topaloğlu, M., Akman, B., Yildirim, R. N., Aktug, S., Batur, T., et al. (2026) · European Journal of Human Genetics · doi:10.1038/s41431-026-02177-9 · Cited by 2
“This includes in silico prediction tools, including AlphaMissense [25], PromoterAI [26], SpliceAI [27], and allele frequencies from gnomAD [28] and the Turkish Variome [29].”
AAVC: An automated framework for high-accuracy ACMG-based variant classification
İnan, R. A., Kayaalp, B., Safieh, F., Kars, M. E., Stein, D., Cooper, D. N., Stenson, P. D., Konu, Ö., Casanova, J., Itan, Y., et al. (2026) · Genetics in Medicine · doi:10.1016/j.gim.2026.102624 · Cited by 2
Xenbase: A Guide to the Xenopus Genetics and Genomics Knowledgebase
James‐Zorn, C., Ponferrada, V. G., & Zorn, A. M. (2026) · Methods in molecular biology · doi:10.1007/978-1-0716-5360-9_3 · Cited by 2
Predicting genome-wide functional constraints with GPN-Star
Ye, C., Benegas, G., Albors, C., Li, J. C., Prillo, S., Fields, P. D., Clarke, B., & Song, Y. S. (2026) · Nature · doi:10.1038/s41586-026-11005-5 · Cited by 30
de Aquino, M. M., Xu, C. Y., Engchuan, W., Trost, B., Zhou, X., Miwa, B., Salazar, N. B., Iglar, J., Thiruvahindrapuram, B., Wallich, L., et al. (2026) · Molecular Psychiatry · doi:10.1038/s41380-026-03886-9 · Cited by 2
Chen, T., Zhang, H., Mazumder, R., & Lin, X. (2026) · Nature Methods · doi:10.1038/s41592-026-03235-2 · Cited by 4
“Thus, further work may explore sparser variant sets for consistent PCs across datasets 65,66 .”
Population-scale immune multiome atlas reveals regulatory disease mechanisms
Kanai, M., Delorey, T. M., Jarno, H., Rodosthenous, R. S., Juvila, J., Murphy, S., Teixeira-Soldano, I., Hwang, H. S., Karjalainen, J. M., Halonen, J., et al. (2026) · Nature · doi:10.1038/s41586-026-11078-2 · Cited by 16
Self-citationGlaser, M., Rasokat, A., Prang, D., Nogová, L., Wompner, C., Schmitz, J., Bitter, E., Terjung, I., Eisert, A., Fischer, R. N., et al. (2023) · Lung Cancer · doi:10.1016/j.lungcan.2023.107344 · Cited by 2
Maciel, V. A. Z., Alves, G. M., Frezatti, R. S. S., Alves, A. L. D. M., de Andrade, B. M. A., Leal, R. D. C. C., Tomaselli, P. J., Reilly, M. M., & Marques, W. (2023) · Journal of the Peripheral Nervous System · doi:10.1111/jns.12601 · Cited by 2
Dragomir, M., Călugăru, O.-T., Popescu, B. O., Jardan, C., Jardan, D., Popescu, M., Aposteanu, S., BADELITA, S. N., Nedelcu, G., Șerban, C., et al. (2024) · Cancers · doi:10.3390/cancers16020358 · Cited by 2
Muto, H., Yu, Y., CHAMBERS, J. K., Coghill, L. M., Nakamura, Y., Uchida, K., & Lyons, L. A. (2024) · Journal of Veterinary Internal Medicine · doi:10.1111/jvim.17024 · Cited by 2
Self-citationC and G are frequently mutated into T and A in coding regions of human genes
Wang, Y. L., & Chen, K. (2024) · Molecular Genetics and Genomics · doi:10.1007/s00438-024-02118-5 · Cited by 2
Rare predicted deleterious FEZF2 variants are associated with a neurodevelopmental phenotype
Garber, A., Weingarten, L. S., Abreu, N. J., Elloumi, H. Z., Haack, T. B., Hildebrant, C., Martínez‐Gil, N., Mathews, J., Müller, A. J., Valenzuela, I., et al. (2024) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.63578 · Cited by 2
Self-citationIdentification and functional analysis of rare HECTD1 missense variants in human neural tube defects
Oxman, E., Li, H., Wang, H.-Y., & Zohn, I. E. (2024) · Human Genetics · doi:10.1007/s00439-024-02647-4 · Cited by 2
Ding, M., Chen, K., Yang, Y., & Zhao, H. (2024) · Human Genetics · doi:10.1007/s00439-024-02667-0 · Cited by 2
Destabilization and Degradation of a Disease-Linked PGM1 Protein Variant
Gouliaev, F., Jonsson, N., Gersing, S. K., Lisby, M., Lindorff‐Larsen, K., & Hartmann‐Petersen, R. (2024) · Biochemistry · doi:10.1021/acs.biochem.4c00042 · Cited by 2
GTExome: Modeling commonly expressed missense mutations in the human genome
Hoffman, J., Tan, H., Sandoval-Cooper, C., de Villiers, K., & Reed, S. M. (2024) · PLoS ONE · doi:10.1371/journal.pone.0303604 · Cited by 2
Suzuki, H., Muramatsu, Y., Miya, F., Asada, H., Yamada, M., Nishimura, G., Kosaki, K., & Takenouchi, T. (2024) · European Journal of Medical Genetics · doi:10.1016/j.ejmg.2024.104955 · Cited by 2
Ray, D., Loomis, S. J., Venkataraghavan, S., Zhang, J., Tin, A., Yu, B., Chatterjee, N., Selvin, E., & Duggal, P. (2024) · Diabetes · doi:10.2337/db23-0318 · Cited by 2
Investigating the Protective Role of the Mitochondrial 2158 T > C Variant in Parkinson's Disease
Akçimen, F., van Midden, V. M., Akerman, S. C., Makarious, M. B., Program, G. P. G., Rothstein, J. D., Fang, Z., & Bandrés‐Ciga, S. (2024) · Movement Disorders · doi:10.1002/mds.29892 · Cited by 2
Selamioğlu, A., Balcı, M. C., Karaca, M., Khalil, Y., Hirachan, R., Durmuş, H., Parman, Y., Gedikbaşı, A., Demirkol, M., Clayton, P. T., et al. (2024) · JIMD Reports · doi:10.1002/jmd2.12437 · Cited by 2
Kölz, C., Gaugaz, F. Z., Handin, N., Schaeffeler, E., Tremmel, R., Winter, S., Klein, K., Zanger, U. M., Artursson, P., Schwab, M. G., et al. (2024) · British Journal of Pharmacology · doi:10.1111/bph.16508 · Cited by 2
Bastos, K. L. D. M., Stephan, B. D. O., Linnenkamp, B. D. W., Costa, L. A., Lima, F. R., Carvalho, L. M. L., Honjo, R. S., Tannuri, U., Tannuri, A. C. A., & Kim, C. A. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25168648 · Cited by 2
Lococo, F., Paolis, E. D., Evangelista, J., Dell’Amore, A., Giannarelli, D., Chiappetta, M., Campanella, A., Sassorossi, C., Cancellieri, A., Calabrese, F., et al. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25179560 · Cited by 2
Ogloblinsky, M. C., Bocher, O., Aloui, C., Leutenegger, A., Özışık, O., Baudot, A., Tournier‐Lasserve, E., Castillo-Madeen, H., Lewinsohn, D. P., Conrad, D. F., et al. (2024) · Genetic Epidemiology · doi:10.1002/gepi.22593 · Cited by 2
Sims, M. C., Gierula, M., Stephens, J. C., Tokolyi, A., Stefanucci, L., Persyn, E., Sun, L., Collins, J., Davenport, E. E., Angelantonio, E. D., et al. (2024) · Blood Advances · doi:10.1182/bloodadvances.2024014020 · Cited by 2
StopKB: a comprehensive knowledgebase for nonsense suppression therapies
Haas, N., Thompson, J., Renaud, J., Chennen, K., & Poch, O. (2024) · Database · doi:10.1093/database/baae108 · Cited by 2
Identifying pathogenic variants in rare pediatric neurological diseases using exome sequencing
Komatsu, K., Kato, M., Kubota, K., Fukumura, S., Yamada, K., Hori, I., Shimizu, K., Miyamoto, S., Yamoto, K., Hiraide, T., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-75020-0 · Cited by 2
Homozygous synonymous FAM111A variant underlies an autosomal recessive form of Kenny-Caffey syndrome
Bonde, L. D., Abdelrazek, I. M., Seif, L., Alawi, M., Matrawy, K. A., Nabil, K. M., Abdalla, E. M., Kutsche, K., & Harms, F. L. (2024) · Journal of Human Genetics · doi:10.1038/s10038-024-01301-1 · Cited by 2
Metadata
- Authors
- Chen, S., Francioli, L. C., Goodrich, J. K., Collins, R. L., Kanai, M., Wang, Q., Alföldi, J., Watts, N. A., Vittal, C., Gauthier, L. D., Poterba, T., Wilson, M. W., Tarasova, Y., Phu, W., Grant, R., Yohannes, M. T., Koenig, Z., Farjoun, Y., Banks, E., Donnelly, S., Gabriel, S., Gupta, N., Ferriera, S., Tolonen, C., Novod, S., Bergelson, L., Roazen, D., Ruano-Rubio, V., Covarrubias, M., Llanwarne, C., Petrillo, N., Wade, G., Jeandet, T., Munshi, R., Tibbetts, K., Genome Aggregation Database Consortium, Abreu, M., Aguilar Salinas, C. A., Ahmad, T., Albert, C. M., Ardissino, D., Armean, I. M., Atkinson, E. G., Atzmon, G., Barnard, J., Baxter, S. M., Beaugerie, L., Benjamin, E. J., Benjamin, D., Boehnke, M., Bonnycastle, L. L., Bottinger, E. P., Bowden, D. W., Bown, M. J., Brand, H., Brant, S., Brookings, T., Bryant, S., Calvo, S. E., Campos, H., Chambers, J. C., Chan, J. C., Chao, K. R., Chapman, S., Chasman, D. I., Chisholm, R., Cho, J., Chowdhury, R., Chung, M. K., Chung, W. K., Cibulskis, K., Cohen, B., Connolly, K. M., Correa, A., Cummings, B. B., Dabelea, D., Danesh, J., Darbar, D., Darnowsky, P., Denny, J., Duggirala, R., Dupuis, J., Ellinor, P. T., Elosua, R., Emery, J., England, E., Erdmann, J., Esko, T., Evangelista, E., Fatkin, D., Florez, J., Franke, A., Fu, J., Färkkilä, M., Garimella, K., Gentry, J., Getz, G., Glahn, D. C., Glaser, B., Glatt, S. J., Goldstein, D., Gonzalez, C., Groop, L., Gudmundsson, S., Haessly, A., Haiman, C., Hall, I., Hanis, C. L., Harms, M., Hiltunen, M., Holi, M. M., Hultman, C. M., Jalas, C., Kallela, M., Kaplan, D., Kaprio, J., Kathiresan, S., Kenny, E. E., Kim, B.-J., Kim, Y. J., King, D., Kirov, G., Kooner, J., Koskinen, S., Krumholz, H. M., Kugathasan, S., Kwak, S. H., Laakso, M., Lake, N., Langsford, T., Laricchia, K. M., Lehtimäki, T., Lek, M., Lipscomb, E., Loos, R. J. F., Lu, W., Lubitz, S. A., Luna, T. T., Ma, R. C. W., Marcus, G. M., Marrugat, J., Mattila, K. M., McCarroll, S., McCarthy, M. I., McCauley, J. L., McGovern, D., McPherson, R., Meigs, J. B., Melander, O., Metspalu, A., Meyers, D., Minikel, E. V., Mitchell, B. D., Mootha, V. K., Naheed, A., Nazarian, S., Nilsson, P. M., O’Donovan, M. C., Okada, Y., Ongur, D., Orozco, L., Owen, M. J., Palmer, C., Palmer, N. D., Palotie, A., Park, K. S., Pato, C., Pulver, A. E., Rader, D., Rahman, N., Reiner, A., Remes, A. M., Rhodes, D., Rich, S., Rioux, J. D., Ripatti, S., Roden, D. M., Rotter, J. I., Sahakian, N., Saleheen, D., Salomaa, V., Saltzman, A., Samani, N. J., Samocha, K. E., Sanchis-Juan, A., Scharf, J., Schleicher, M., Schunkert, H., Schönherr, S., Seaby, E. G., Shah, S. H., Shand, M., Sharpe, T., Shoemaker, M. B., Shyong, T., Silverman, E. K., Singer-Berk, M., Sklar, P., Smith, J. T., Smith, J. G., Soininen, H., Sokol, H., Son, R. G., Soto, J., Spector, T., Stevens, C., Stitziel, N. O., Sullivan, P. F., Suvisaari, J., Tai, E. S., Taylor, K. D., Teo, Y. Y., Tsuang, M., Tuomi, T., Turner, D., Tusie-Luna, T., Vartiainen, E., Vawter, M., Wang, L., Wang, A., Ware, J. S., Watkins, H., Weersma, R. K., Weisburd, B., Wessman, M., Whiffin, N., Wilson, J. G., Xavier, R. J., O’Donnell-Luria, A., Solomonson, M., Seed, C., Martin, A. R., Talkowski, M. E., Rehm, H. L., Daly, M. J., Tiao, G., Neale, B. M., MacArthur, D. G., & Karczewski, K. J.
- Affiliations
- Broad Institute (US)
- Lady Davis Institute for Medical Research (CA)
- University of Miami (US)
- Peninsula College of Medicine and Dentistry (GB)
- Brigham and Women's Hospital (US)
- University of Parma (IT)
- Albert Einstein College of Medicine (US)
- Cleveland Clinic (US)
- Sorbonne Université (FR)
- Boston University (US)
- University of Michigan (US)
- National Institutes of Health (US)
- Wake Forest University Health Sciences (US)
- University of Leicester (GB)
- Harvard University (US)
- Rutgers, The State University of New Jersey (US)
- Imperial College Healthcare NHS Trust (GB)
- Chinese University of Hong Kong (HK)
- Northwestern University (US)
- Icahn School of Medicine at Mount Sinai (US)
- University of Cambridge (GB)
- Columbia University Irving Medical Center (US)
- University of Mississippi Medical Center (US)
- Colorado School of Public Health (US)
- University of Illinois Chicago (US)
- Vanderbilt University Medical Center (US)
- Texas A&M University – San Antonio (US)
- University of Lübeck (DE)
- Victor Chang Cardiac Research Institute (AU)
- University of Helsinki (FI)
- Boston Children's Hospital (US)
- SUNY Upstate Medical University (US)
- University of Southern California (US)
- Washington University in St. Louis (US)
- The University of Texas Health Science Center at Houston (US)
- Columbia University (US)
- University of Eastern Finland (FI)
- Helsinki University Hospital (FI)
- Karolinska Institutet (SE)
- Korea National Institute of Health (KR)
- Cardiff University (GB)
- Finnish Institute for Health and Welfare (FI)
- Yale New Haven Hospital (US)
- Emory University (US)
- Seoul National University (KR)
- Yale University (US)
- Tampere University (FI)
- University of Copenhagen (DK)
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (MX)
- University of California, San Francisco (US)
- Centro de Investigación en Red en Enfermedades Cardiovasculares (ES)
- Centre for Human Genetics (GB)
- Cedars-Sinai Medical Center (US)
- Ottawa Heart Institute (CA)
- Lund University (SE)
- University of Tartu (EE)
- University of Arizona (US)
- University of Maryland, Baltimore (US)
- International Centre for Diarrhoeal Disease Research (BD)
- Johns Hopkins University (US)
- Institute for Open and Transdisciplinary Research Initiatives (JP)
- National Institute of Genomic Medicine (MX)
- University of Dundee (GB)
- Children's Hospital of Philadelphia (US)
- Institute of Cancer Research (GB)
- University of Washington (US)
- Oulu University Hospital (FI)
- University of Virginia (US)
- Montreal Heart Institute (CA)
- The Lundquist Institute (US)
- Center for Non-Communicable Diseases (PK)
- Deutsches Herzzentrum München (DE)
- Innsbruck Medical University (AT)
- Duke University (US)
- Vanderbilt University (US)
- National University of Singapore (SG)
- Inserm (FR)
- King's College London (GB)
- University of North Carolina at Chapel Hill (US)
- University of California San Diego (US)
- Hebrew University of Jerusalem (IL)
- University of California, Irvine (US)
- University of Oxford (GB)
- University Medical Center Groningen (NL)
- Beth Israel Deaconess Medical Center (US)
- Corresponding author
- Chen, Siwei
- Karczewski, Konrad J.
- ORCID
- Chen, Siwei
- Francioli, Laurent C.
- Goodrich, Julia K.
- Collins, Ryan L.
- Kanai, Masahiro
- Wang, Qingbo
- Alföldi, Jessica
- Poterba, Timothy
- Wilson, Michael W.
- Phu, William
- Farjoun, Yossi
- Banks, Eric
- Donnelly, Stacey
- Gabriel, Stacey
- Gupta, Namrata
- Abreu, Maria
- Ahmad, Tariq
- Albert, Christine M.
- Ardissino, Diego
- Armean, Irina M.
- Atkinson, Elizabeth G.
- Atzmon, Gil
- Barnard, John
- Baxter, Samantha M.
- Beaugerie, Laurent
- Benjamin, Emelia J.
- Boehnke, Michael
- Bonnycastle, Lori L.
- Bowden, Donald W.
- Bown, Matthew J.
- Brand, Harrison
- Brant, Steven
- Calvo, Sarah E.
- Campos, Hannia
- Chambers, John C.
- Chan, Juliana C.
- Chao, Katherine R.
- Chapman, Sinéad
- Chasman, Daniel I.
- Chisholm, Rex
- Cho, Judy
- Chowdhury, Rajiv
- Chung, Mina K.
- Chung, Wendy K.
- Cibulskis, Kristian
- Cohen, Bruce
- Correa, Adolfo
- Cummings, Beryl B.
- Dabelea, Dana
- Danesh, John
- Darbar, Dawood
- Denny, Joshua
- Duggirala, Ravindranath
- Dupuis, Josée
- Ellinor, Patrick T.
- Erdmann, Jeanette
- Esko, Tõnu
- Evangelista, Emily
- Fatkin, Diane
- Fu, Jack
- Färkkilä, Martti
- Garimella, Kiran
- Getz, Gad
- Glahn, David C.
- Glatt, Stephen J.
- Goldstein, David
- Groop, Leif
- Gudmundsson, Sanna
- Haessly, Andrea
- Haiman, Christopher
- Hall, Ira
- Hanis, Craig L.
- Harms, Matthew
- Hiltunen, Mikko
- Holi, Matti M.
- Hultman, Christina M.
- Jalas, Chaim
- Kallela, Mikko
- Kaprio, Jaakko
- Kathiresan, Sekar
- Kenny, Eimear E.
- Kim, Bong-Jo
- Kim, Young Jin
- Kirov, George
- Kooner, Jaspal
- Koskinen, Seppo
- Krumholz, Harlan M.
- Kugathasan, Subra
- Kwak, Soo Heon
- Laakso, Markku
- Lake, Nicole
- Laricchia, Kristen M.
- Lehtimäki, Terho
- Lek, Monkol
- Loos, Ruth J. F.
- Lu, Wenhan
- Lubitz, Steven A.
- Marcus, Gregory M.
- Marrugat, Jaume
- McCarroll, Steven
- McCarthy, Mark I.
- McCauley, Jacob L.
- McGovern, Dermot
- McPherson, Ruth
- Meigs, James B.
- Melander, Olle
- Metspalu, Andres
- Meyers, Deborah
- Minikel, Eric V.
- Mitchell, Braxton D.
- Mootha, Vamsi K.
- Naheed, Aliya
- Nazarian, Saman
- Nilsson, Peter M.
- O’Donovan, Michael C.
- Okada, Yukinori
- Orozco, Lorena
- Owen, Michael J.
- Palotie, Aarno
- Park, Kyong Soo
- Pato, Carlos
- Pulver, Ann E.
- Rahman, Nazneen
- Reiner, Alex
- Rich, Stephen
- Rioux, John D.
- Ripatti, Samuli
- Roden, Dan M.
- Rotter, Jerome I.
- Saleheen, Danish
- Salomaa, Veikko
- Saltzman, Andrea
- Samani, Nilesh J.
- Samocha, Kaitlin E.
- Scharf, Jeremiah
- Schunkert, Heribert
- Schönherr, Sebastian
- Seaby, Eleanor G.
- Shah, Svati H.
- Shand, Megan
- Shoemaker, Moore B.
- Silverman, Edwin K.
- Sklar, Pamela
- Smith, Jonathan T.
- Soininen, Hilkka
- Sokol, Harry
- Son, Rachel G.
- Spector, Tim
- Stevens, Christine
- Stitziel, Nathan O.
- Sullivan, Patrick F.
- Suvisaari, Jaana
- Tai, E. Shyong
- Taylor, Kent D.
- Tsuang, Ming
- Turner, Dan
- Vartiainen, Erkki
- Vawter, Marquis
- Wang, Lily
- Ware, James S.
- Watkins, Hugh
- Weersma, Rinse K.
- Weisburd, Ben
- Whiffin, Nicola
- Wilson, James G.
- Xavier, Ramnik J.
- O’Donnell-Luria, Anne
- Solomonson, Matthew
- Martin, Alicia R.
- Talkowski, Michael E.
- Rehm, Heidi L.
- Daly, Mark J.
- Tiao, Grace
- Neale, Benjamin M.
- MacArthur, Daniel G.
- Karczewski, Konrad J.
- Venue
- Nature
- Published
- 2023-12-06
- Volume
- 625
- Issue
- 7993
- Pages
- 92-100
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC11629659
- OpenAlex
- W4389367121
- Cited by
- 1,727
- References
- 90
- Citations by year
- 2026: 520 · 2025: 642 · 2024: 442 · 2023: 121
- FWCI
- 286.54
- Type
- journal article
- Language
- en
- Update notices
- correction (2024-01-15)
- Open access
- green
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion)
- PubMed Central (acceptedVersion, other-oa)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Discovery Research Portal (University of Dundee) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- Funders
- Wellcome Trust (107469/Z/15/Z)
- National Institutes of Health
- Medical Research Council (MR/L010305/1)
- National Institute of Mental Health (R01MH115957)
- National Human Genome Research Institute (U24HG011450)
- National Institute of Diabetes and Digestive and Kidney Diseases (U54DK105566)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD081256)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Keywords
- purifying selection, non-coding DNA, regulatory elements, gnocchi, allele frequency, complex diseases, genetic variants, protein-coding genes, sequence context
- MeSH terms
- Chromosome Mapping, Gene Frequency, Humans, Models, Genetic, Mutation, Selection, Genetic, Genetic Variation, Genome, Human, Access to Information, Genomics, Databases, Genetic, Datasets as Topic
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