The DOI matches its Crossref record; 109 of the 109 references it cites were found in a registry or an index.
Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes
Open accessPublished version of a preprint
Abstract
We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P < 5 × 10−8) regions, including 36 that are new. We define credible sets of T1D-associated variants and show that they are enriched in immune-cell accessible chromatin, particularly CD4+ effector T cells. Using chromatin-accessibility profiling of CD4+ T cells from 115 individuals, we map chromatin-accessibility quantitative trait loci and identify five regions where T1D risk variants co-localize with chromatin-accessibility quantitative trait loci. We highlight rs72928038 in BACH2 as a candidate causal T1D variant leading to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritize potential drug targets by integrating genetic evidence, functional genomic maps and immune protein–protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D. A large-scale genetic analysis of type 1 diabetes identifies new susceptibility variants, highlights potential regulatory mechanisms and provides genetic support for therapeutic targets for immune intervention.
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.
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
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364
featureCounts: an efficient general purpose program for assigning sequence reads to genomic features
Liao, Y., Smyth, G. K., & Shi, W. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt656 · Cited by 27,219
Minimap2: Pairwise alignment for nucleotide sequences
Li, H. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty191 · Cited by 14,807
ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data
Wang, K., Li, M., & Hakonarson, H. H. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq603 · Cited by 14,724
Second-generation PLINK: rising to the challenge of larger and richer datasets
Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015) · Gigascience · doi:10.1186/s13742-015-0047-8 · Cited by 12,709
The control of the false discovery rate in multiple testing under dependency
Benjamini, Y., & Yekutieli, D. (2001) · The Annals of Statistics · doi:10.1214/aos/1013699998 · Cited by 10,490
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
Self-citationA scaling normalization method for differential expression analysis of RNA-seq data
Robinson, M. D., & Oshlack, A. (2010) · Genome Biology · doi:10.1186/gb-2010-11-3-r25 · Cited by 7,876
Szklarczyk, D., Morris, J. H., Cook, H., Kuhn, M., Wyder, S., Simonovic, M., Santos, A., Doncheva, N. T., Roth, A., Bork, P., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw937 · Cited by 6,980
Cited by
Sorted by citations
Pathogenesis of autoimmune disease
Pisetsky, D. S. (2023) · Nature Reviews Nephrology · doi:10.1038/s41581-023-00720-1 · Cited by 715
Sacks, D. B., Arnold, M., Bakris, G. L., Bruns, D. E., Horvath, A. R., Lernmark, Å., Metzger, B. E., Nathan, D. M., & Kirkman, M. S. (2023) · Diabetes Care · doi:10.2337/dci23-0036 · Cited by 351
Synergistic insights into human health from aptamer- and antibody-based proteomic profiling
Pietzner, M., Wheeler, E., Carrasco-Zanini, J., Kerrison, N. D., Oerton, E., Koprulu, M., Luan, J., Hingorani, A. D., Williams, S. A., Wareham, N. J., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-27164-0 · Cited by 234
Quattrin, T., Mastrandrea, L. D., & Walker, L. S. K. (2023) · The Lancet · doi:10.1016/s0140-6736(23)00223-4 · Cited by 292
The immunology of type 1 diabetes
Herold, K. C., Delong, T., Perdigoto, A. L., Biru, N., Brusko, T. M., & Walker, L. S. K. (2024) · Nature reviews. Immunology · doi:10.1038/s41577-023-00985-4 · Cited by 241
Kiryluk, K., Sánchez, E., Zhou, S., Zanoni, F., Liu, L., Mladkova, N., Khan, A., Marasà, M., Zhang, J. Y., Balderes, O., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01422-x · Cited by 212
Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus
Downes, D. J., Cross, A. R., Peng, H., Roberts, N. A., Schweßinger, R., Cutler, A. J., Munis, A. M., Brown, J. M., Mielczarek, O., de Andrea, C. E., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00955-3 · Cited by 174
Self-citationChromatin accessibility: biological functions, molecular mechanisms and therapeutic application
Chen, Y., Liang, R., Li, Y., Jiang, L., Ma, D., Luo, Q., & Song, G. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-02030-9 · Cited by 195
Haller, M. J., Bell, K. J., Besser, R. E. J., Casteels, K., Couper, J. J., Craig, M. E., Elding Larsson, H., Jacobsen, L., Lange, K., Oron, T., et al. (2024) · Hormone Research in Paediatrics · doi:10.1159/000543035 · Cited by 151
Sacks, D. B., Arnold, M. A., Bakris, G. L., Bruns, D. E., Horvath, A. R., Lernmark, Å., Metzger, B. E., Nathan, D. M., & Kirkman, M. S. (2023) · Clinical Chemistry · doi:10.1093/clinchem/hvad080 · Cited by 164
Besser, R. E. J., Bell, K. J., Couper, J., Ziegler, A., Wherrett, D. K., Knip, M., Speake, C., Casteels, K., Driscoll, K. A., Jacobsen, L. M., et al. (2022) · Pediatric Diabetes · doi:10.1111/pedi.13410 · Cited by 161
Atkinson, M. A., & Mirmira, R. G. (2023) · Cell Metabolism · doi:10.1016/j.cmet.2023.06.018 · Cited by 139
Self-citationPartners in Crime: Beta-Cells and Autoimmune Responses Complicit in Type 1 Diabetes Pathogenesis
Toren, E., Burnette, K., Banerjee, R. R., Hunter, C. S., & Tse, H. M. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.756548 · Cited by 115
Pathogenesis of Type 1 Diabetes: Established Facts and New Insights
Zajec, A., Podkrajšek, K. T., Tesovnik, T., Šket, R., Kern, B. Č., Bizjan, B. J., Schweiger, D. Š., Battelino, T., & Kovač, J. (2022) · Genes · doi:10.3390/genes13040706 · Cited by 117
Insights from complex trait fine-mapping across diverse populationsPreprint
Kanai, M., Ulirsch, J. C., Karjalainen, J. M., Kurki, M., Karczewski, K. J., Fauman, E. B., Wang, Q. S., Jacobs, H., Aguet, F., Ardlie, K., et al. (2021) · medRxiv · doi:10.1101/2021.09.03.21262975 · Cited by 105
A gut microbial peptide and molecular mimicry in the pathogenesis of type 1 diabetes
Girdhar, K., Huang, Q., Chow, I., Vatanen, T., Brady, C., Raisingani, A., Autissier, P., Atkinson, M. A., Kwok, W. W., Kahn, C. R., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2120028119 · Cited by 103
Self-citationType 1 diabetes in diverse ancestries and the use of genetic risk scores
REDONDO, M. J., Gignoux, C. R., Dabelea, D., Hagopian, W., Önengüt-Gümüşcü, S., Oram, R. A., & Rich, S. S. (2022) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(22)00159-0 · Cited by 106
Self-citationYuan, K., Longchamps, R. J., Pardiñas, A. F., Yu, M., Chen, T., Lin, S., Chen, Y., Lam, M., Liu, R., Xia, Y., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01870-z · Cited by 97
Excitatory amino acid transporter supports inflammatory macrophage responses
Gan, Z., Guo, Y., Zhao, M., Ye, Y., Liao, Y., Liu, B., Yin, J., Zhou, X., Yan, Y., Yin, Y., et al. (2024) · 中国科学通报：英文版 · doi:10.1016/j.scib.2024.03.055 · Cited by 88
Utility of genetic risk scores in type 1 diabetes
Luckett, A. M., Weedon, M. N., Hawkes, G., Leslie, R. D., Oram, R. A., & Grant, S. F. A. (2023) · Diabetologia · doi:10.1007/s00125-023-05955-y · Cited by 80
Interpreting non-coding disease-associated human variants using single-cell epigenomics
Gaulton, K. J., Preißl, S., & Ren, B. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00598-6 · Cited by 81
Kundu, K., Tardáguila, M., Mann, A., Watt, S., Ponstingl, H., Vasquez, L. J., Schiller, D. V., Morrell, N. W., Stegle, O., Pastinen, T., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01025-y · Cited by 66
King, H. W., Wells, K. L., Shipony, Z., Kathiria, A. S., Wagar, L. E., Lareau, C. A., Orban, N. T., Capasso, R., Davis, M. M., Steinmetz, L. M., et al. (2021) · Science Immunology · doi:10.1126/sciimmunol.abh3768 · Cited by 55
Bhutta, Z. A., Salam, R. A., Gomber, A., Lewis-Watts, L., Narang, T., Mbanya, J. C., & Alleyne, G. A. O. (2021) · The Lancet · doi:10.1016/s0140-6736(21)02247-9 · Cited by 61
Cathepsin H: Molecular characteristics and clues to function and mechanism
Wang, Y., Zhao, J., Gu, Y., Wang, H., Jiang, M., Zhao, S., Qing, H., & Ni, J. (2023) · Biochemical Pharmacology · doi:10.1016/j.bcp.2023.115585 · Cited by 52
Benaglio, P., Newsome, J. M., Han, J. Y., Chiou, J., Aylward, A., Corban, S., Miller, M., Okino, M.-L., Kaur, J., Preißl, S., et al. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010759 · Cited by 50
Carré, A., Richardson, S. J., Larger, É., & Mallone, R. (2020) · Diabetologia · doi:10.1007/s00125-020-05298-y · Cited by 53
Girard, D., & Vandiedonck, C. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.991716 · Cited by 55
De‐ coding genetic risk variants in type 1 diabetes
Shapiro, M. R., Thirawatananond, P., Peters, L. D., Sharp, R. C., Ogundare, S. O., Posgai, A. L., Perry, D. J., & Brusko, T. M. (2021) · Immunology and Cell Biology · doi:10.1111/imcb.12438 · Cited by 47
Functional Impact of Risk Gene Variants on the Autoimmune Responses in Type 1 Diabetes
Gootjes, C., Zwaginga, J. J., Roep, B. O., & Nikolić, T. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.886736 · Cited by 44
Tatović, D., Marwaha, A., Taylor, P. N., Hanna, S. J., Carter, K., Cheung, W., Luzio, S. D., Dunseath, G. J., Hutchings, H. A., Holland, G., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-03115-2 · Cited by 53
Monti, R., Eick, L., Hudjashov, G., Läll, K., Kanoni, S., Wolford, B. N., Wingfield, B., Pain, O., Wharrie, S., Jermy, B. S., et al. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.06.003 · Cited by 52
A multi-ancestry genome-wide association study in type 1 diabetes
Michalek, D. A., Tern, C., Zhou, W., Robertson, C. C., Farber, E., Campolieto, P., Chen, W., Önengüt-Gümüşcü, S., & Rich, S. S. (2024) · Human Molecular Genetics · doi:10.1093/hmg/ddae024 · Cited by 43
Self-citationType I interferons as key players in pancreatic β-cell dysfunction in type 1 diabetes
Marroquí, L., Perez-Serna, A. A., Babiloni-Chust, I., & dos Santos, R. S. (2021) · International review of cytology · doi:10.1016/bs.ircmb.2021.02.011 · Cited by 37
Priority index: database of genetic targets in immune-mediated disease
Fang, H., & Knight, J. C. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab994 · Cited by 38
Geravandi, S., Richardson, S. J., Pugliese, A., & Maedler, K. (2021) · Cell Reports Medicine · doi:10.1016/j.xcrm.2021.100371 · Cited by 38
Zhang, J., Hamey, F., Trzupek, D., Mickunas, M., Lee, M., Godfrey, L., Yang, J. H. M., Pękalski, M. Ł., Kennet, J., Waldron-Lynch, F., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-34162-3 · Cited by 40
Self-citationHuman immune phenotyping reveals accelerated aging in type 1 diabetes
Shapiro, M. R., Dong, X., Perry, D. J., McNichols, J., Thirawatananond, P., Posgai, A. L., Peters, L. D., Motwani, K., Musca, R. S., MUIR, A. B., et al. (2023) · JCI Insight · doi:10.1172/jci.insight.170767 · Cited by 36
Self-citationSokolowski, E. K., Kursawe, R., Selvam, V., Bhuiyan, R. M., Thibodeau, A., Zhao, C. G., Spracklen, C. N., Ucar, D., & Stitzel, M. L. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2024.09.006 · Cited by 37
Bao, C., Wang, H., & Fang, H. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.758440 · Cited by 36
Benaglio, P., Zhu, H., Okino, M.-L., Yan, J., Elgamal, R. M., Nariai, N., Beebe, E., Korgaonkar, K., Qiu, Y., Donovan, M. K. R., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100214 · Cited by 35
Roca-Rivada, A., Marín‐Cañas, S., Colli, M. L., Vinci, C., Sawatani, T., Marselli, L., Cnop, M., Marchetti, P., & Eizirik, D. L. (2023) · Diabetologia · doi:10.1007/s00125-023-05908-5 · Cited by 33
Shen, K., Zhou, H., Zuo, Q., Gu, Y., Cheng, J., Yan, K., Zhang, H., Song, H., Liang, W.-W., Zhou, J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-55335-2 · Cited by 42
Bonifacio, E. E., & Ziegler, A. (2025) · Diabetes Obesity and Metabolism · doi:10.1111/dom.16354 · Cited by 35
Genetic regulation of RNA splicing in human pancreatic islets
Atla, G., Bonàs‐Guarch, S., Cuenca-Ardura, M., Beucher, A., Crouch, D. J. M., García-Hurtado, J., Morán, I., Cnop, M., Eliasson, L., Esguerra, J. L. S., et al. (2022) · Genome biology · doi:10.1186/s13059-022-02757-0 · Cited by 31
Self-citationWen, Y.-P., & Yu, Z. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1160397 · Cited by 33
Diabetes mellitus and the key role of endoplasmic reticulum stress in pancreatic β cells
Lytrivi, M., Tong, Y. A., Virgilio, E., Yi, X., & Cnop, M. (2025) · Nature Reviews Endocrinology · doi:10.1038/s41574-025-01129-5 · Cited by 36
Towards a global view of multiple sclerosis genetics
Jacobs, B. M., Peter, M., Giovannoni, G., Noyce, A. J., Morris, H. R., & Dobson, R. (2022) · Nature Reviews Neurology · doi:10.1038/s41582-022-00704-y · Cited by 31
Type 1 diabetes presenting in adults: Trends, diagnostic challenges and unique features
Evans‐Molina, C., & Oram, R. A. (2025) · Diabetes Obesity and Metabolism · doi:10.1111/dom.16402 · Cited by 34
Harsunen, M. H., Haukka, J. K., Harjutsalo, V., Mars, N., Syreeni, A., Härkönen, T., Käräjämäki, A., Ilonen, J., Knip, M., Sandholm, N., et al. (2023) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(23)00123-7 · Cited by 33
Single-Cell Multi-Omic Roadmap of Human Fetal Pancreatic DevelopmentPreprint
Sean de la, O., Liu, Z., Sun, H., Yu, S. K., Wong, D. M., Chu, E., Rao, S. A., Eng, N., Peixoto, G. A., BOUZA, J. O., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.02.17.480942 · Cited by 29
Update on the genetics of allergic diseases
Lawson, L. P., Parameswaran, S., Panganiban, R. A. M., Constantine, G. M., Weirauch, M. T., & Kottyan, L. C. (2025) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2025.03.012 · Cited by 33
Fyvie, M. J., & Gillespie, K. M. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1158278 · Cited by 29
Hanna, S. J., Tatović, D., Thayer, T. C., & Dayan, C. M. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.751701 · Cited by 25
Okamoto, J., Wang, L., Yin, X., Luca, F., Piqué-Regi, R., Helms, A. S., Im, H. K., Morrison, J., & Wen, X. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.12.002 · Cited by 25
β Cell and Autophagy: What Do We Know?
Mohammadi‐Motlagh, H., Sadeghalvad, M., Yavari, N., Primavera, R., Soltani, S., Chetty, S. S., Ganguly, A., Regmi, S., Fløyel, T., Kaur, S., et al. (2023) · Biomolecules · doi:10.3390/biom13040649 · Cited by 27
Self-citationMetabolic disorders in young people around the world
Boddu, S. K., Giannini, C., & Marcovecchio, M. L. (2025) · Diabetologia · doi:10.1007/s00125-025-06450-2 · Cited by 35
The β-Cell Genomic Landscape in T1D: Implications for Disease Pathogenesis
Ramos-Rodríguez, M., Pérez-González, B., & Pasquali, L. (2021) · Current Diabetes Reports · doi:10.1007/s11892-020-01370-4 · Cited by 26
Genetic overlap between type 1 diabetes and other autoimmune diseases
Márquez, A., & Martin, J. J. (2021) · Seminars in Immunopathology · doi:10.1007/s00281-021-00885-6 · Cited by 29
Gautam, Y., Caldwell, J. M., Kottyan, L. C., Chehade, M., Dellon, E. S., Rothenberg, M. E., Baye, T. M., Wechsler, J. B., Davis, C., Furuta, G. T., et al. (2022) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2022.09.040 · Cited by 26
Advances in integrative African genomics
Zhang, C., Hansen, M. E. B., & Tishkoff, S. A. (2021) · Trends in Genetics · doi:10.1016/j.tig.2021.09.013 · Cited by 24
Immunotherapy for type 1 diabetes
Allen, L. A., & Dayan, C. M. (2021) · British Medical Bulletin · doi:10.1093/bmb/ldab027 · Cited by 24
Early DNA methylation changes in children developing beta cell autoimmunity at a young age
Starskaia, I., Laajala, E., Grönroos, T., Härkönen, T., Junttila, S., Kattelus, R., Kallionpää, H., Laiho, A., Suni, V., Tillmann, V., et al. (2022) · Diabetologia · doi:10.1007/s00125-022-05657-x · Cited by 27
Laine, A., Valta, M., Toppari, J., Knip, M., Veijola, R., Ilonen, J., & Lempainen, J. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.909020 · Cited by 26
A phase 1b open-label dose-finding study of ustekinumab in young adults with type 1 diabetes
Marwaha, A., Chow, S., Pesenacker, A. M., Cook, L. E., Sun, A. C., Long, S. A., Yang, J. H. M., Ward‐Hartstonge, K. A., Williams, E., Domingo‐Vila, C., et al. (2021) · Immunotherapy Advances · doi:10.1093/immadv/ltab022 · Cited by 25
Maternal type 1 diabetes and relative protection against offspring transmission
Allen, L. A., Taylor, P. N., Gillespie, K. M., Oram, R. A., & Dayan, C. M. (2023) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(23)00190-0 · Cited by 26
Lessons and Applications of Omics Research in Diabetes Epidemiology
Yu, G., Tam, H. C. H., Huang, C., Shi, M., Lim, C. K. P., Chan, J. C. N., & Ronald, C. W. (2024) · Current Diabetes Reports · doi:10.1007/s11892-024-01533-7 · Cited by 23
Diabetes mellitus polygenic risk scores: heterogeneity and clinical translation
Ortega, H. I., Udler, M. S., Gloyn, A. L., & Sharp, S. A. (2025) · Nature Reviews Endocrinology · doi:10.1038/s41574-025-01132-w · Cited by 26
Toward Disease-Modifying Therapies in Type 1 Diabetes: Focus on Teplizumab
Mathieu, C., Sims, E. K., Chatenoud, L., James, E. A., Atkinson, M. A., & Herold, K. C. (2025) · Diabetes Care · doi:10.2337/dci25-0066 · Cited by 23
Self-citationCaulfield, J. I., Aizenbud, L., Perdigoto, A. L., Meffre, E., Jilaveanu, L. B., Michalek, D. A., Rich, S. S., Aizenbud, Y., Adeniran, A., Herold, K. C., et al. (2023) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2022-006570 · Cited by 25
Self-citationMittal, R., Weiss, M. B., Rendon, A., Shafazand, S., Lemos, J. R. N., & Hirani, K. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26093935 · Cited by 21
Gene expression signature predicts rate of type 1 diabetes progression
Suomi, T., Starskaia, I., Ullah, U., Rasool, O., Jaakkola, M. K., Grönroos, T., Välikangas, T., Brorsson, C., Mazzoni, G., Bruggraber, S. F. A., et al. (2023) · EBioMedicine · doi:10.1016/j.ebiom.2023.104625 · Cited by 20
Self-citationPrediction of progression to type 1 diabetes with dynamic biomarkers and risk scores
Joglekar, M. V., Kaur, S., Pociot, F., & Hardikar, A. A. (2024) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(24)00103-7 · Cited by 21
Self-citationYuan, K., Longchamps, R. J., Pardiñas, A. F., Yu, M., Chen, T.-T., Lin, S.-C., Chen, Y., Lam, M., Liu, R., Xia, Y., et al. (2023) · doi:10.1101/2023.01.07.23284293 · Cited by 94
Self-citationOptimization of multi-ancestry polygenic risk score disease prediction models
Lerga-Jaso, J., Terpolovsky, A., Novković, B., Osama, A., Manson, C., Bohn, S., Marino, A. D., Kunitomi, M., & Yazdi, P. G. (2025) · Scientific Reports · doi:10.1038/s41598-025-02903-1 · Cited by 21
Sharp, R. C., Brown, M. E., Shapiro, M. R., Posgai, A. L., & Brusko, T. M. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.739048 · Cited by 17
Use of Induced Pluripotent Stem Cells to Build Isogenic Systems and Investigate Type 1 Diabetes
Armitage, L. H., Stimpson, S. E., Santostefano, K. E., Sui, L., Ogundare, S. O., Newby, B. N., Castro-Gutiérrez, R., Huber, M. K., Taylor, J. P., Sharma, P., et al. (2021) · Frontiers in Endocrinology · doi:10.3389/fendo.2021.737276 · Cited by 19
Varshney, A., Manickam, N., Orchard, P., Tovar, A., Ventresca, C., Zhang, Z., Feng, F., Mears, J., Erdos, M. R., Narisu, N., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.15.571696 · Cited by 18
Frørup, C., Gerwig, R. H., Svane, C. A. B., de Melo, J. M. L., Henriksen, K., Fløyel, T., Pociot, F., Kaur, S., & Størling, J. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1128523 · Cited by 17
Self-citationIakovliev, A., McGurnaghan, S. J., Hayward, C., Colombo, M., Lipschutz, D., Spiliopoulou, A., Colhoun, H. M., & McKeigue, P. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.04.003 · Cited by 18
Crouch, D. J. M., Inshaw, J., Robertson, C. C., Zhang, J.-Y., Chen, W.-M., Onengut-Gumuscu, S., Cutler, A. J., Sidore, C., Cucca, F., Pociot, F., et al. (2021) · bioRxiv · doi:10.1101/2021.02.05.429962 · Cited by 13
Self-citationOliva, M., Sarkar, M. K., March, M., Saeidian, A. H., Mentch, F. D., Hsieh, C.-L., Tang, F., Uppala, R., Patrick, M. T., Li, Q., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-58310-7 · Cited by 23
Potential Protective Link Between Type I Diabetes and Parkinson's Disease Risk and Progression
Senkevich, K. A., Alipour, P., Chernyavskaya, E. А., Yu, E., Noyce, A. J., & Gan‐Or, Z. (2023) · Movement Disorders · doi:10.1002/mds.29424 · Cited by 16
Genetic architecture of type 1 diabetes with low genetic risk score informed by 41 unreported loci
Qu, H., Qu, J., Bradfield, J. P., Marchand, L., Glessner, J., Chang, X., March, M., Li, J., Connolly, J. J., Roizen, J. D., et al. (2021) · Communications Biology · doi:10.1038/s42003-021-02368-8 · Cited by 16
Linking big biomedical datasets to modular analysis with Portable Encapsulated Projects
Sheffield, N. C., Stolarczyk, M., Reuter, V. P., & Rendeiro, A. F. (2021) · GigaScience · doi:10.1093/gigascience/giab077 · Cited by 16
A genomic data archive from the Network for Pancreatic Organ donors with Diabetes
Perry, D. J., Shapiro, M. R., Chamberlain, S. W., Kusmartseva, I., Chamala, S., Balzano‐Nogueira, L., Yang, M., Brant, J. O., Brusko, M., Williams, M. D., et al. (2023) · Scientific Data · doi:10.1038/s41597-023-02244-6 · Cited by 14
Self-citationType 1 Diabetes Genetics Consortium
Önengüt-Gümüşcü, S., CONCANNON, P. J., Akolkar, B., Erlich, H. A., Julier, C., Morahan, G., Nierras, C. R., Pociot, F., Todd, J. A., & Rich, S. S. (2025) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgaf181 · Cited by 20
Self-citationDeutsch, A. J., Stalbow, L. A., Majarian, T. D., Mercader, J. M., Manning, A. K., Florez, J. C., Loos, R. J. F., & Udler, M. S. (2023) · Diabetes Care · doi:10.2337/dc22-1833 · Cited by 16
Epigenetic and proteomic signatures associate with clonal hematopoiesis expansion rate
Mack, T., Raddatz, M. A., Pershad, Y., Nachun, D. C., Taylor, K. D., Guo, X., Shuldiner, A. R., O’Connell, J. R., Kenny, E. E., Loos, R. J. F., et al. (2024) · Nature Aging · doi:10.1038/s43587-024-00647-7 · Cited by 16
Self-citationMulti-omics analysis in primary T cells elucidates mechanisms behind disease-associated genetic loci
Shi, C., Zhao, D., Butler, J. S., Frantzeskos, A., Rossi, S., Ding, J., Ferrazzano, C., Wynn, C., Hum, R. M., Richards, E., et al. (2025) · Genome biology · doi:10.1186/s13059-025-03492-y · Cited by 14
Four decades of the Bart’s Oxford study: Improved tests to predict type 1 diabetes
Gillespie, K. M., Fareed, R., & Mortimer, G. (2021) · Diabetic Medicine · doi:10.1111/dme.14717 · Cited by 16
Self-Antigens Targeted by Regulatory T Cells in Type 1 Diabetes
Mitchell, A. M., & Michels, A. W. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23063155 · Cited by 15
Mastracci, T. L., Apte, M. V., Amundadottir, L. T., Alvarsson, A., Artandi, S. E., Bellin, M. D., Bernal‐Mizrachi, E., Caicedo, A., Campbell‐Thompson, M., Cruz‐Monserrate, Z., et al. (2023) · Diabetes · doi:10.2337/db22-0942 · Cited by 15
Liao, W., Huang, Y., Chang, Y., Liu, T., Lu, H., Tiao, Z., Su, P., Wang, C., & Tsai, F. (2023) · Diabetes Obesity and Metabolism · doi:10.1111/dom.15187 · Cited by 13
Starskaia, I., Valta, M., Pietilä, S., Suomi, T., Pahkuri, S., Ullah, U., Rasool, O., Rydgren, E., Hyöty, H., Knip, M., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-47918-w · Cited by 16
REDONDO, M. J., Richardson, S. J., Perry, D. J., Minard, C. G., Carr, A. L. J., Brusko, T. M., Kusmartseva, I., Pugliese, A., & Atkinson, M. A. (2022) · Diabetologia · doi:10.1007/s00125-022-05818-y · Cited by 13
Self-citationShapiro, M. R., Peters, L. D., Brown, M. E., Cabello-Kindelan, C., Posgai, A. L., Bayer, A. L., & Brusko, T. M. (2023) · The Journal of Immunology · doi:10.4049/jimmunol.2200651 · Cited by 14
Alamad, B., Elliott, K., & Knight, J. C. (2024) · Cambridge Prisms Precision Medicine · doi:10.1017/pcm.2023.25 · Cited by 12
Guertin, K. A., Repaske, D. R., Taylor, J. F., Williams, E. S., Önengüt-Gümüşcü, S., Chen, W., Boggs, S. R., Yu, L., Allen, L., Botteon, L., et al. (2024) · Genome Medicine · doi:10.1186/s13073-024-01305-8 · Cited by 13
Self-citationPrecision Medicine in Type 1 Diabetes
Michalek, D. A., Önengüt-Gümüşcü, S., Repaske, D. R., & Rich, S. S. (2023) · Journal of the Indian Institute of Science · doi:10.1007/s41745-023-00356-x · Cited by 14
Self-citation
Metadata
- Authors
- Robertson, C. C., Inshaw, J. R. J., Onengut-Gumuscu, S., Chen, W.-M., Santa Cruz, D. F., Yang, H., Cutler, A. J., Crouch, D. J. M., Farber, E., Bridges, S. L., Edberg, J. C., Kimberly, R. P., Buckner, J. H., Deloukas, P., Divers, J., Dabelea, D., Lawrence, J. M., Marcovina, S., Shah, A. S., Greenbaum, C. J., Atkinson, M. A., Gregersen, P. K., Oksenberg, J. R., Pociot, F., Rewers, M. J., Steck, A. K., Dunger, D. B., Type 1 Diabetes Genetics Consortium, Wicker, L. S., Concannon, P., Todd, J. A., & Rich, S. S.
- Affiliations
- University of Virginia (US)
- Centre for Human Genetics (GB)
- Hospital for Special Surgery (US)
- University of Alabama at Birmingham (US)
- Benaroya Research Institute (US)
- Queen Mary University of London (GB)
- NYU Grossman Long Island School of Medicine (US)
- Colorado School of Public Health (US)
- Kaiser Permanente (US)
- Medpace (United States) (US)
- Cincinnati Children's Hospital Medical Center (US)
- University of Florida (US)
- Northwell Health (US)
- University of California, San Francisco (US)
- University of Copenhagen (DK)
- University of Colorado Anschutz (US)
- University of Cambridge (GB)
- Corresponding author
- Todd, John A.
- ORCID
- Robertson, Catherine C.
- Inshaw, Jamie R. J.
- Onengut-Gumuscu, Suna
- Chen, Wei-Min
- Yang, Hanzhi
- Cutler, Antony J.
- Crouch, Daniel J. M.
- Farber, Emily
- Bridges, S. Louis
- Kimberly, Robert P.
- Buckner, Jane H.
- Deloukas, Panos
- Divers, Jasmin
- Dabelea, Dana
- Lawrence, Jean M.
- Marcovina, Santica
- Shah, Amy S.
- Greenbaum, Carla J.
- Atkinson, Mark A.
- Gregersen, Peter K.
- Oksenberg, Jorge R.
- Pociot, Flemming
- Rewers, Marian J.
- Steck, Andrea K.
- Dunger, David B.
- Wicker, Linda S.
- Concannon, Patrick
- Todd, John A.
- Rich, Stephen S.
- Venue
- Nature Genetics
- Published
- 2021-06-14
- Volume
- 53
- Issue
- 7
- Pages
- 962-971
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC8273124
- OpenAlex
- W3171115266
- Semantic Scholar
- e41e3ba0695f1da1b7c897ccfd64b223b9963243
- Cited by
- 302
- References
- 107
- Citations by year
- 2026: 42 · 2025: 63 · 2024: 66 · 2023: 65 · 2022: 39 · 2021: 26
- FWCI
- 27.56
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Nature Genetics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Funders
- Juvenile Diabetes Research Foundation (4-SRA-2017-473-A-A)
- Wellcome Trust (107212/A/15/Z)
- U.S. Department of Health & Human Services | NIH | U.S. National Library of Medicine (5T32LM012416)
- University of Virginia
- U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (N01-AR-0-2247, N01 AR-6-2278)
- U.S. Department of Health & Human Services | National Institutes of Health (UL1-TR001417)
- U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (U48/CCU919219, U01 DP000250, 107212/A/15/Z, U01 DP000247, U18DP000247-06A1, U01 DP000246, U58/CCU019235-4, U01 DP000244, U18DP002710-01, U48/CCU519239, U01 DP000248, 1U18DP002709, U01 DK103282, U01 DK127404, R01 DK032493, P30 DK116073, DK-115694, DP3-111906, U01 DK-062418)
- U.S. Department of Health & Human Services | Centers for Disease Control and Prevention (200-2010-35171)
- U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (P01AI042288)
- National Multiple Sclerosis Society (SI-2001-35701)
- U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (UL1 TR000154)
- JDRF
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- type 1 diabetes, genetic risk variants, fine mapping, chromatin accessibility, CD4+ T cells, BACH2, enhancer accessibility, causal variants, therapeutic target, immune cells
- MeSH terms
- Alleles, Chromosome Mapping, Diabetes Mellitus, Type 1, Humans, Genetic Variation, CD4-Positive T-Lymphocytes, Autoimmunity, Gene Expression, Genetic Predisposition to Disease, Genomics, Protein Interaction Mapping, Drug Discovery, Molecular Targeted Therapy
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
