Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes

Fast gapped-read alignment with Bowtie 2

Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400 · see citing works

<tt>edgeR</tt> : a Bioconductor package for differential expression analysis of digital gene expression data

Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364 · see citing works

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 · see citing works

Minimap2: Pairwise alignment for nucleotide sequences

Li, H. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty191 · Cited by 14,807 · see citing works

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 14,380 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

A 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 · see citing works

The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible

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 · see citing works

METAL: fast and efficient meta-analysis of genomewide association scans

Willer, C. J., Li, Y., & Abecasis, G. R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq340 · Cited by 5,205 · see citing works

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 · see citing works

Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics

Giambartolomei, C., Vukcevic, D., Schadt, E. E., Franke, L., Hingorani, A. D., Wallace, C., & Plagnol, V. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004383 · Cited by 4,261 · see citing works

Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM).

Spielman, R. S., McGinnis, R. E., & Ewens, W. J. (1993) · PubMed · Cited by 3,679 · see citing works

Robust relationship inference in genome-wide association studies

Manichaikul, A., Mychaleckyj, J. C., Rich, S. S., Daly, K., Sale, M., & Chen, W.-M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq559 · Cited by 3,541 · see citing works

ATAC-seq: a method for assaying chromatin accessibility genome-wide

Buenrostro, J. D., Wu, B., Chang, H. Y., & Greenleaf, W. J. (2015) · Current Protocols in Molecular Biology · doi:10.1002/0471142727.mb2129s109 · Cited by 3,289 · see citing works

Annotation of functional variation in personal genomes using RegulomeDB

Boyle, A. P., Hong, E. L., Hariharan, M., Cheng, Y., Schaub, M. A., Kasowski, M., Karczewski, K. J., Park, J., Hitz, B. C., Weng, S., et al. (2012) · Genome Research · doi:10.1101/gr.137323.112 · Cited by 2,722 · see citing works

Unraveling the polygenic architecture of complex traits using blood eQTL metaanalysis

Võsa, U., Claringbould, A., Westra, H.-J., Bonder, M. J., Deelen, P., Zeng, B., Kirsten, H., Saha, A., Kreuzhuber, R., Kasela, S., et al. (2018) · doi:10.1101/447367 · Cited by 2,607 · see citing works

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

Võsa, U., Claringbould, A., Westra, H.-J., Bonder, M. J., Deelen, P., Zeng, B., Kirsten, H., Saha, A., Kreuzhuber, R., Yazar, S., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00913-z · Cited by 2,607 · see citing works

An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues

Corces, M. R., Trevino, A. E., Hamilton, E. G., Greenside, P. G., Sinnott-Armstrong, N. A., Vesuna, S., Satpathy, A. T., Rubin, A. J., Montine, K. S., Wu, B., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4396 · Cited by 2,496 · see citing works

Genetics of rheumatoid arthritis contributes to biology and drug discovery

the RACI consortium, Okada, Y., the GARNET consortium, Wu, D., Trynka, G., Raj, T., Terao, C., Ikari, K., Kochi, Y., Ohmura, K., et al. (2014) · Nature · doi:10.1038/nature12873 · Cited by 2,310 · see citing works

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Taliun, D., Harris, D. N., Kessler, M. D., Carlson, J., Szpiech, Z. A., Torres, R., Taliun, S. A. G., Corvelo, A., Gogarten, S. M., Kang, H. M., et al. (2021) · Nature · doi:10.1038/s41586-021-03205-y · Cited by 2,213 · see citing works

Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population.

(1995) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040269 · Cited by 1,950 · see citing works

Tofacitinib as Induction and Maintenance Therapy for Ulcerative Colitis

Sandborn, W. J., Su, C. G., Sands, B. E., D’Haens, G., Vermeire, S., Schreiber, S., Danese, S., Feagan, B. G., Reinisch, W., Niezychowski, W., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1606910 · Cited by 1,783 · see citing works

Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes

The Type 1 Diabetes Genetics Consortium, Barrett, J. C., Clayton, D. G., Concannon, P., Akolkar, B., Cooper, J. D., Erlich, H. A., Julier, C., Morahan, G., Nerup, J., et al. (2009) · Nature Genetics · doi:10.1038/ng.381 · Cited by 1,746 · see citing works

Matrix eQTL: ultra fast eQTL analysis via large matrix operations

Shabalin, A. A. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts163 · Cited by 1,694 · see citing works

The support of human genetic evidence for approved drug indications

Nelson, M. R., Tipney, H., Painter, J. L., Shen, J., Nicoletti, P., Shen, Y., Floratos, A., Sham, P. C., Li, M. J., Wang, J., et al. (2015) · Nature Genetics · doi:10.1038/ng.3314 · Cited by 1,666 · see citing works

Systematic identification of trans eQTLs as putative drivers of known disease associations

Westra, H.-J., Peters, M. J., Esko, T., Yaghootkar, H., Schurmann, C., Kettunen, J., Christiansen, M. W., Fairfax, B. P., Schramm, K., Powell, J. E., et al. (2013) · Nature Genetics · doi:10.1038/ng.2756 · Cited by 1,658 · see citing works

Genotype imputation for genome-wide association studies

Marchini, J., & Howie, B. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2796 · Cited by 1,597 · see citing works

Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads

Jiang, H., Lei, R., Ding, S., & Zhu, S. (2014) · BMC Bioinformatics · doi:10.1186/1471-2105-15-182 · Cited by 1,525 · see citing works

Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes

Finland, G. O. T. 1. D. I., Todd, J. A., the Wellcome Trust Case Control Consortium, Walker, N. M., Cooper, J. D., Smyth, D. J., Downes, K., Plagnol, V., Bailey, R., Nejentsev, S., et al. (2007) · Nature Genetics · doi:10.1038/ng2068 · Cited by 1,456 · see citing works

An anti-CD3 antibody, teplizumab, in relatives at risk for type 1 diabetes

Herold, K. C., Bundy, B. N., Long, S. A., Bluestone, J. A., DiMeglio, L. A., Dufort, M. J., Gitelman, S. E., Gottlieb, P. A., Krischer, J. P., Linsley, P. S., et al. (2019) · New England Journal of Medicine · doi:10.1056/nejmoa1902226 · Cited by 1,189 · see citing works

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters

Javierre, B. M., Burren, O. S., Wilder, S. P., Kreuzhuber, R., Hill, S. M., Sewitz, S., Cairns, J., Wingett, S. W., Várnai, C., Thiecke, M. J., et al. (2016) · Cell · doi:10.1016/j.cell.2016.09.037 · Cited by 1,046 · see citing works

Genetic analyses of diverse populations improves discovery for complex traits

Wojcik, G. L., Graff, M., Nishimura, K. K., Tao, R., Haessler, J., Gignoux, C. R., Highland, H. M., Patel, Y. M., Sorokin, E. P., Avery, C. L., et al. (2019) · Nature · doi:10.1038/s41586-019-1310-4 · Cited by 1,033 · see citing works

Measuring reproducibility of high-throughput experiments

Li, Q., Brown, J. B., Huang, H., & Bickel, P. J. (2011) · The Annals of Applied Statistics · doi:10.1214/11-aoas466 · Cited by 1,008 · see citing works

BEDOPS: high-performance genomic feature operations

Neph, S. J., Kuehn, M. S., Reynolds, A. P., Haugen, E., Thurman, R. E., Johnson, A., Rynes, E., Maurano, M. T., Vierstra, J. D., Thomas, S., et al. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts277 · Cited by 971 · see citing works

HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease

Ward, L. D., & Kellis, M. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1340 · Cited by 925 · see citing works

Chromatin-state discovery and genome annotation with ChromHMM

Ernst, J., & Kellis, M. (2017) · Nature Protocols · doi:10.1038/nprot.2017.124 · Cited by 918 · see citing works

Measuring reproducibility of high-throughput experiments

Li, Q., Brown, J. B., Huang, H., & Bickel, P. J. (2010) · UC Berkeley · Cited by 915 · see citing works

Gateways to the FANTOM5 promoter level mammalian expression atlas

Lizio, M., Harshbarger, J., Shimoji, H., Severin, J., Kasukawa, T., Sahin, S., Abugessaisa, I., Fukuda, S., Hori, F., Ishikawa-Kato, S., et al. (2015) · Genome Biology · doi:10.1186/s13059-014-0560-6 · Cited by 871 · see citing works

Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression

Schmiedel, B. J., Singh, D., Madrigal, A., Valdovino-Gonzalez, A. G., White, B. M., Zapardiel-Gonzalo, J., Ha, B., Altay, G., Greenbaum, J. A., McVicker, G., et al. (2018) · Cell · doi:10.1016/j.cell.2018.10.022 · Cited by 867 · see citing works

Innate Immune Activity Conditions the Effect of Regulatory Variants upon Monocyte Gene Expression

Fairfax, B. P., Humburg, P., Makino, S., Naranbhai, V., Wong, D., Lau, E., Jostins, L., Plant, K., Andrews, R., McGee, C., et al. (2014) · Science · doi:10.1126/science.1246949 · Cited by 764 · see citing works

Environmental risk factors for type 1 diabetes

Rewers, M., & Ludvigsson, J. (2016) · The Lancet · doi:10.1016/s0140-6736(16)30507-4 · Cited by 676 · see citing works

Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers

Önengüt-Gümüşcü, S., Chen, W., Burren, O. S., Cooper, N. J., Quinlan, A. R., Mychaleckyj, J. C., Farber, E., Bonnie, J. K., Szpak, M., Schofield, E. C., et al. (2015) · Nature Genetics · doi:10.1038/ng.3245 · Cited by 675 · see citing works

Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval

King, E. A., Davis, J. W., & Degner, J. F. (2019) · PLOS Genetics · doi:10.1371/journal.pgen.1008489 · Cited by 649 · see citing works

Pervasive Sharing of Genetic Effects in Autoimmune Disease

Cotsapas, C., Voight, B. F., Rossin, E., Lage, K., Neale, B. M., Wallace, C., Abecasis, G. R., Barrett, J. C., Behrens, T., Cho, J., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002254 · Cited by 606 · see citing works

Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci

Cooper, J. D., Smyth, D. J., Smiles, A. M., Plagnol, V., Walker, N. M., Allen, J. E., Downes, K., Barrett, J. C., Healy, B. C., Mychaleckyj, J. C., et al. (2008) · Nature Genetics · doi:10.1038/ng.249 · Cited by 529 · see citing works

Genetics of gene expression in primary immune cells identifies cell type-specific master regulators and roles of HLA alleles

Fairfax, B. P., Makino, S., Radhakrishnan, J., Plant, K., Leslie, S., Dilthey, A., Ellis, P., Langford, C., Vannberg, F. O., & Knight, J. C. (2012) · Nature Genetics · doi:10.1038/ng.2205 · Cited by 486 · see citing works

Promise and pitfalls of the Immunochip

Cortes, A., & Brown, M. A. (2010) · Arthritis Research &amp; Therapy · doi:10.1186/ar3204 · Cited by 479 · see citing works

Long-Range LD Can Confound Genome Scans in Admixed Populations

Price, A. L., Weale, M. E., Patterson, N., Myers, S. R., Need, A. C., Shianna, K. V., Ge, D., Rotter, J. I., Torres, E., Taylor, K. D., et al. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.06.005 · Cited by 443 · see citing works

Interpreting type 1 diabetes risk with genetics and single-cell epigenomics

Chiou, J., Geusz, R. J., Okino, M.-L., Han, J. Y., Miller, M., Melton, R. L., Beebe, E., Benaglio, P., Huang, S., Korgaonkar, K., et al. (2021) · Nature · doi:10.1038/s41586-021-03552-w · Cited by 437 · see citing works

Trends in Incidence of Type 1 and Type 2 Diabetes Among Youths — Selected Counties and Indian Reservations, United States, 2002–2015

Divers, J., Mayer‐Davis, E. J., Lawrence, J. M., Isom, S. P., Dabelea, D., Dolan, L. M., Imperatore, G., Marcovina, S. M., Pettitt, D. J., Pihoker, C., et al. (2020) · MMWR Morbidity and Mortality Weekly Report · doi:10.15585/mmwr.mm6906a3 · Cited by 372 · see citing works

Abundant associations with gene expression complicate GWAS follow-up

Liu, B., Gloudemans, M. J., Rao, A. S., Ingelsson, E., & Montgomery, S. B. (2019) · Nature Genetics · doi:10.1038/s41588-019-0404-0 · Cited by 370 · see citing works

Development and standardization of an improved type 1 diabetes genetic risk score for use in newborn screening and incident diagnosis

Sharp, S. A., Rich, S. S., Wood, A. R., Jones, S. E., Beaumont, R. N., Harrison, J. W., Schneider, D. A., Locke, J. M., Tyrrell, J., Weedon, M. N., et al. (2019) · Diabetes Care · doi:10.2337/dc18-1785 · Cited by 366 · see citing works

A Genome-Wide Meta-Analysis of Six Type 1 Diabetes Cohorts Identifies Multiple Associated Loci

Bradfield, J. P., Qu, H., Wang, K., Zhang, H., Abou‐Sleiman, P. M., Kim, C. E., Mentch, F. D., Qiu, H., Glessner, J., Thomas, K., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002293 · Cited by 338 · see citing works

Safety and efficacy of tofacitinib for up to 9.5 years in the treatment of rheumatoid arthritis: final results of a global, open-label, long-term extension study

Wollenhaupt, J., Lee, E.-B., Curtis, J. R., Silverfield, J. C., Terry, K. K., Soma, K., Mojcik, C., DeMasi, R., Strengholt, S., Kwok, K. K., et al. (2019) · Arthritis Research & Therapy · doi:10.1186/s13075-019-1866-2 · Cited by 321 · see citing works

BACH2 regulates CD8+ T cell differentiation by controlling access of AP-1 factors to enhancers

Roychoudhuri, R., Clever, D. C., Li, P., Wakabayashi, Y., Quinn, K. M., Klebanoff, C. A., Ji, Y., Sukumar, M., Eil, R. L., Yu, Z., et al. (2016) · Nature Immunology · doi:10.1038/ni.3441 · Cited by 317 · see citing works

Functional IL6R 358Ala Allele Impairs Classical IL-6 Receptor Signaling and Influences Risk of Diverse Inflammatory Diseases

Ferreira, R. C., Freitag, D. F., Cutler, A. J., Howson, J. M. M., Rainbow, D. B., Smyth, D. J., Kaptoge, S., Clarke, P., Boreham, C., Coulson, R. M., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003444 · Cited by 316 · see citing works

Improved peak-calling with MACS2Preprint

Gaspar, J. M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/496521 · Cited by 305 · see citing works

Landscape of stimulation-responsive chromatin across diverse human immune cells

Calderon, D., Nguyen, M. L. T., Mezger, A., Kathiria, A. S., Müller, F., Nguyen, V. Q., Lescano, N., Wu, B., Trombetta, J. J., Ribado, J. V., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0505-9 · Cited by 282 · see citing works

Limited statistical evidence for shared genetic effects of eQTLs and autoimmune-disease-associated loci in three major immune-cell types

Chun, S., Casparino, A., Patsopoulos, N. A., Croteau-Chonka, D. C., Raby, B. A., De Jager, P. L., Sunyaev, S. R., & Cotsapas, C. (2017) · Nature Genetics · doi:10.1038/ng.3795 · Cited by 259 · see citing works

Prospects of Fine-Mapping Trait-Associated Genomic Regions by Using Summary Statistics from Genome-wide Association Studies

Benner, C., Havulinna, A. S., Järvelin, M., Salomaa, V. V., Ripatti, S., & Pirinen, M. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.08.012 · Cited by 225 · see citing works

Genetic regulatory signatures underlying islet gene expression and type 2 diabetes

Varshney, A., Scott, L. J., Welch, R., Erdos, M. R., Chines, P. S., Narisu, N., Albanus, R. D., Orchard, P., Wolford, B. N., Kursawe, R., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1621192114 · Cited by 212 · see citing works

A genetics-led approach defines the drug target landscape of 30 immune-related traits

Fang, H., Wolf, H. D., Knezevic, B., Burnham, K. L., Osgood, J. A., Sanniti, A., Lara, A. L., Kasela, S., Cesco, S. D., Wegner, J. K., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0456-1 · Cited by 207 · see citing works

Leveraging Functional-Annotation Data in Trans-ethnic Fine-Mapping Studies

Kichaev, G., & Paşaniuc, B. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.06.007 · Cited by 187 · see citing works

Whole-exome sequencing for finding de novo mutations in sporadic mental retardation

Robinson, P. (2010) · Genome Biology · doi:10.1186/gb-2010-11-12-144 · Cited by 180 · see citing works

Evolutionary stochastic search for Bayesian model exploration

Bottolo, L., & Richardson, S. T. (2010) · Bayesian Analysis · doi:10.1214/10-ba523 · Cited by 176 · see citing works

Bach2 maintains T cells in a naive state by suppressing effector memory-related genes

Tsukumo, S.-I., Unno, M., Muto, A., Takeuchi, A., Kometani, K., Kurosaki, T., Igarashi, K., & Saito, T. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1306691110 · Cited by 168 · see citing works

Follow-Up Analysis of Genome-Wide Association Data Identifies Novel Loci for Type 1 Diabetes

Grant, S. F. A., Qu, H., Bradfield, J. P., Marchand, L., Kim, C., Glessner, J., Grabs, R., Taback, S. P., Frackelton, E. C., Eckert, A. W., et al. (2008) · Diabetes · doi:10.2337/db08-1022 · Cited by 161 · see citing works

Integrating Case-control and TDT Studies

Kazeem, G., & Farrall, M. (2005) · Annals of Human Genetics · doi:10.1046/j.1529-8817.2005.00156.x · Cited by 159 · see citing works

Risankizumab in patients with moderate to severe Crohn's disease: an open-label extension study

Feagan, B. G., Panés, J., Ferrante, M., Kaser, A., D’Haens, G., Sandborn, W. J., Louis, E. J., Neurath, M. F., Franchimont, D. P., Dewit, O., et al. (2018) · The Lancet. Gastroenterology & hepatology · doi:10.1016/s2468-1253(18)30233-4 · Cited by 158 · see citing works

The impact of proinflammatory cytokines on the β-cell regulatory landscape provides insights into the genetics of type 1 diabetes

Ramos-Rodríguez, M., Raurell‐Vila, H., Colli, M. L., Alvelos, M. I., Subirana-Granés, M., Juan‐Mateu, J., Norris, R., Turatsinze, J., Nakayasu, E. S., Webb‐Robertson, B., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0524-6 · Cited by 155 · see citing works

BACH2 immunodeficiency illustrates an association between super-enhancers and haploinsufficiency

Afzali, B., Grönholm, J., Vandrovcová, J., O'Brien, C., Sun, H., Vanderleyden, I., Davis, F. P., Khoder, A., Zhang, Y., Hegazy, A. N., et al. (2017) · Nature Immunology · doi:10.1038/ni.3753 · Cited by 151 · see citing works

A Novel Susceptibility Locus for Type 1 Diabetes on Chr12q13 Identified by a Genome-Wide Association Study

Hakonarson, H. H., Qu, H., Bradfield, J. P., Marchand, L., Kim, C., Glessner, J., Grabs, R., Casalunovo, T., Taback, S. P., Frackelton, E. C., et al. (2008) · Diabetes · doi:10.2337/db07-1305 · Cited by 150 · see citing works

Genetic predisposition for beta cell fragility underlies type 1 and type 2 diabetes

Dooley, J., Tian, L., Schönefeldt, S., Delghingaro‐Augusto, V., Garcia‐Perez, J. E., Pasciuto, E., Marino, D. D., Carr, E. J., Oskolkov, N., Lyssenko, V., et al. (2016) · Nature Genetics · doi:10.1038/ng.3531 · Cited by 147 · see citing works

Fine-mapping and functional studies highlight potential causal variants for rheumatoid arthritis and type 1 diabetes

Westra, H.-J., Martínez‐Bonet, M., Önengüt-Gümüşcü, S., Lee, A., Luo, Y., Teslovich, N. C., Worthington, J., Martin, J. J., Huizinga, T. W. J., Klareskog, L., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0216-7 · Cited by 142 · see citing works

Correlation between endothelial function and carotid atherosclerosis in rheumatoid arthritis patients with long-standing disease

González‐Juanatey, C., Llorca, J., & González-Gay, M. Á. (2011) · Arthritis Research & Therapy · doi:10.1186/ar3382 · Cited by 133 · see citing works

1000 Genomes-based imputation identifies novel and refined associations for the Wellcome Trust Case Control Consortium phase 1 Data

Huang, J., Ellinghaus, D., Franke, A., Howie, B., & Li, Y. (2012) · European Journal of Human Genetics · doi:10.1038/ejhg.2012.3 · Cited by 131 · see citing works

Statistical colocalization of genetic risk variants for related autoimmune diseases in the context of common controls

Fortune, M. D., Guo, H., Burren, O. S., Schofield, E. C., Walker, N. M., Ban, M., Sawcer, S. J., Bowes, J., Worthington, J., Barton, A. C., et al. (2015) · Nature Genetics · doi:10.1038/ng.3330 · Cited by 130 · see citing works

Type 1 Diabetes Risk in African-Ancestry Participants and Utility of an Ancestry-Specific Genetic Risk Score

Önengüt-Gümüşcü, S., Chen, W., Robertson, C. C., Bonnie, J. K., Farber, E., Zhu, Z., Oksenberg, J. R., Brant, S. R., Bridges, S. L., Edberg, J. C., et al. (2019) · Diabetes Care · doi:10.2337/dc18-1727 · Cited by 129 · see citing works

Probabilistic colocalization of genetic variants from complex and molecular traits: promise and limitations

Hukku, A., Pividori, M., Luca, F., Piqué-Regi, R., Im, H. K., & Wen, X. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.11.012 · Cited by 128 · see citing works

Predicting Islet Cell Autoimmunity and Type 1 Diabetes: An 8-Year TEDDY Study Progress Report

Krischer, J. P., Liu, X., Vehik, K., Akolkar, B., Hagopian, W., Rewers, M. J., She, J., Toppari, J., Ziegler, A., Lernmark, Å., et al. (2019) · Diabetes Care · doi:10.2337/dc18-2282 · Cited by 122 · see citing works

Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait Loci

Trynka, G., Westra, H.-J., Slowikowski, K., Hu, X., Xu, H., Stranger, B. E., Klein, R. J., Han, B., & Raychaudhuri, S. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.05.016 · Cited by 114 · see citing works

Pathogenic implications for autoimmune mechanisms derived by comparative eQTL analysis of CD4+ versus CD8+ T cells

Kasela, S., Kisand, K., Tserel, L., Kaleviste, E., Remm, A., Fischer, K., Esko, T., Westra, H.-J., Fairfax, B. P., Makino, S., et al. (2017) · PLOS Genetics · doi:10.1371/journal.pgen.1006643 · Cited by 113 · see citing works

Identification of Novel T1D Risk Loci and Their Association With Age and Islet Function at Diagnosis in Autoantibody-Positive T1D Individuals: Based on a Two-Stage Genome-Wide Association Study

Zhu, M., Xu, K., Chen, Y., Gu, Y., Zhang, M., Luo, F., Liu, Y., Gu, W., Hu, J., Xu, H., et al. (2019) · Diabetes Care · doi:10.2337/dc18-2023 · Cited by 100 · see citing works

Targeting IL-23 in psoriasis: current perspectives

Fotiadou, C., Lazaridou, E., Sotiriou, E., & Ioannides, D. (2018) · Psoriasis Targets and Therapy · doi:10.2147/ptt.s98893 · Cited by 89 · see citing works

Chromosome contacts in activated T cells identify autoimmune disease candidate genes

Burren, O. S., Rubio García, A., Javierre, B.-M., Rainbow, D. B., Cairns, J., Cooper, N. J., Lambourne, J. J., Schofield, E., Castro Dopico, X., Ferreira, R. C., et al. (2017) · Genome Biology · doi:10.1186/s13059-017-1285-0 · Cited by 80 · see citing works

PEPATAC: an optimized pipeline for ATAC-seq data analysis with serial alignments

Smith, J. P., Corces, M. R., Xu, J., Reuter, V. P., Chang, H. Y., & Sheffield, N. C. (2021) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqab101 · Cited by 76 · see citing works

Dynamic evolution of regulatory element ensembles in primate CD4+ T cells

Danko, C. G., Choate, L. A., Marks, B. A., Rice, E. J., Wang, Z., Chu, T., Martins, A. L., Dukler, N., Coonrod, S. A., Wojno, E. D. T., et al. (2018) · Nature Ecology & Evolution · doi:10.1038/s41559-017-0447-5 · Cited by 69 · see citing works

Genetic associations at regulatory phenotypes improve fine-mapping of causal variants for 12 immune-mediated diseases

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 · see citing works

A Method for Gene‐Based Pathway Analysis Using Genomewide Association Study Summary Statistics Reveals Nine New Type 1 Diabetes Associations

Evangelou, M., Smyth, D. J., Fortune, M. D., Burren, O. S., Walker, N. M., Guo, H., Önengüt-Gümüşcü, S., Chen, W., CONCANNON, P. J., Rich, S. S., et al. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21853 · Cited by 63 · see citing works

<i>MBV</i> : a method to solve sample mislabeling and detect technical bias in large combined genotype and sequencing assay datasets

Fort, A., Panousis, N. I., Garieri, M., Antonarakis, S. E., Lappalainen, T., Dermitzakis, E. T., & Delaneau, O. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx074 · Cited by 60 · see citing works

Hope vs hype: where are we in type 1 diabetes?

Skyler, J. S. (2018) · Diabetologia · doi:10.1007/s00125-017-4530-x · Cited by 51 · see citing works

Mapping genetic effects on cell type-specific chromatin accessibility and annotating complex immune trait variants using single nucleus ATAC-seq in peripheral blood

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 51 · see citing works

Dissection of a Complex Disease Susceptibility Region Using a Bayesian Stochastic Search Approach to Fine Mapping

Wallace, C., Cutler, A. J., Pontikos, N., Pękalski, M. Ł., Burren, O. S., Cooper, J. D., García, A. R., Ferreira, R. C., Guo, H., Walker, N. M., et al. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005272 · Cited by 50 · see citing works

A Transcriptomic and Epigenomic Comparison of Fetal and Adult Human Cardiac Fibroblasts Reveals Novel Key Transcription Factors in Adult Cardiac Fibroblasts

Jonsson, M. K. B., Hartman, R. J. G., Ackers-Johnson, M. A., Tan, W. L. W., Lim, B., van Veen, T. A. B., & Foo, R. (2016) · JACC Basic to Translational Science · doi:10.1016/j.jacbts.2016.07.007 · Cited by 47 · see citing works

Anti-CD3 Antibody for the Prevention of Type 1 Diabetes: A Story of Perseverance

Gaglia, J. L., & Kissler, S. (2019) · Biochemistry · doi:10.1021/acs.biochem.9b00707 · Cited by 46 · see citing works

Shared genetic risk contributes to type 1 and type 2 diabetes etiology

Aylward, A., Chiou, J., Okino, M.-L., Kadakia, N., & Gaulton, K. J. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy314 · Cited by 44 · see citing works

The chromosome 6q22.33 region is associated with age at diagnosis of type 1 diabetes and disease risk in those diagnosed under 5 years of age

Inshaw, J. R. J., Walker, N. M., Wallace, C., Bottolo, L., & Todd, J. A. (2017) · Diabetologia · doi:10.1007/s00125-017-4440-y · Cited by 40 · see citing works

The Role of ZFYVE27/Protrudin in Hereditary Spastic Paraplegia

Martignoni, M., Riano, E., & Rugarli, E. I. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.05.014 · Cited by 36 · see citing works

Genome-wide analysis of the genetic regulation of gene expression in human neutrophils

Andiappan, A. K., Melchiotti, R., Poh, T. Y., Nah, M., Puan, K. J., Viganò, E., Haase, D., Yusof, N., Luis, B. S., Lum, J., et al. (2015) · Nature Communications · doi:10.1038/ncomms8971 · Cited by 28 · see citing works

Stochastic search and joint fine-mapping increases accuracy and identifies previously unreported associations in immune-mediated diseases

Asimit, J. L., Rainbow, D. B., Fortune, M. D., Grinberg, N. F., Wicker, L. S., & Wallace, C. (2019) · Nature Communications · doi:10.1038/s41467-019-11271-0 · Cited by 25 · see citing works

PEPATAC: An optimized pipeline for ATAC-seq data analysis with serial alignmentsPreprint

Smith, J. P., Corces, M. R., Xu, J., Reuter, V. P., Chang, H. Y., & Sheffield, N. C. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.10.21.347054 · Cited by 18 · see citing works

Genetic associations at regulatory phenotypes improve fine-mapping of causal variants for twelve immune-mediated diseasesPreprint

Kundu, K., Mann, A., Tardáguila, M., Watt, S. B., Ponstingl, H., Vasquez, L. J., Morrell, N. W., Stegle, O., Pastinen, T., Sawcer, S. J., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.01.15.907436 · Cited by 17 · see citing works

Enhanced genetic analysis of type 1 diabetes by selecting variants on both effect size and significance, and by integration with autoimmune thyroid diseasePreprint

Crouch, D. J. M., Inshaw, J. R. J., Robertson, C. C., Zhang, J., Chen, W., Önengüt-Gümüşcü, S., Cutler, A. J., Sidore, C., Cucca, F., Pociot, F., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.05.429962 · Cited by 17 · see citing works

Incorporating Genotype Uncertainties Into the Genotypic TDT for Main Effects and Gene‐Environment Interactions

Taub, M. A., Schwender, H. R., Beaty, T. H., Louis, T. A., & Ruczinski, I. (2012) · Genetic Epidemiology · doi:10.1002/gepi.21615 · Cited by 13 · see citing works

Mapping genetic effects on cell type-specific chromatin accessibility and annotating complex trait variants using single nucleus ATAC-seqPreprint

Benaglio, P., Newsome, J. M., Han, J. Y., Chiou, J., Aylward, A., Corban, S., Okino, M.-L., Kaur, J., Gorkin, D. U., & Gaulton, K. J. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.12.03.387894 · Cited by 7 · see citing works

Large-scale genetic association and single cell accessible chromatin mapping defines cell type-specific mechanisms of type 1 diabetes risk

Chiou, J., Geusz, R. J., Okino, M.-L., et al. (2021) · bioRxiv · doi:10.1101/2021.01.13.426472 · Cited by 6

An anti-CD3 antibody, teplizumab, in relatives at risk for type 1 diabetes

Herold, K., Bundy, B. N., Long, S. A., Bluestone, J. A., DiMeglio, L. A., Dufort, M. J., Gitelman, S., Gottlieb, P. A., Jp, K., Linsley, P. S., et al. (2020) · Yearbook of pediatric endocrinology · doi:10.1530/ey.17.10.8 · Cited by 5 · see citing works

Pathogenesis of autoimmune disease

Pisetsky, D. S. (2023) · Nature Reviews Nephrology · doi:10.1038/s41581-023-00720-1 · Cited by 656 · see citing works

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

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 · see citing works

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 · see citing works

Type 1 diabetes

Quattrin, T., Mastrandrea, L. D., & Walker, L. S. K. (2023) · The Lancet · doi:10.1016/s0140-6736(23)00223-4 · Cited by 261 · see citing works

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 222 · see citing works

Genome-wide association analyses define pathogenic signaling pathways and prioritize drug targets for IgA nephropathy

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 209 · see citing works

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 168 · see citing works

Chromatin 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 174 · see citing works

ISPAD Clinical Practice Consensus Guidelines 2024: Screening, Staging, and Strategies to Preserve Beta-Cell Function in Children and Adolescents with Type 1 Diabetes

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 · see citing works

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

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 157 · see citing works

ISPAD Clinical Practice Consensus Guidelines 2022: Stages of type 1 diabetes in children and adolescents

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 153 · see citing works

The pathogenic “symphony” in type 1 diabetes: A disorder of the immune system, β cells, and exocrine pancreas

Atkinson, M. A., & Mirmira, R. G. (2023) · Cell Metabolism · doi:10.1016/j.cmet.2023.06.018 · Cited by 135 · see citing works

Partners 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 110 · see citing works

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 · see citing works

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 96 · see citing works

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 100 · see citing works

Type 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 97 · see citing works

Fine-mapping across diverse ancestries drives the discovery of putative causal variants underlying human complex traits and diseases

Yuan, 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 95 · see citing works

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 · see citing works

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 · see citing works

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 79 · see citing works

Genetic associations at regulatory phenotypes improve fine-mapping of causal variants for 12 immune-mediated diseases

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 · see citing works

Integrated single-cell transcriptomics and epigenomics reveals strong germinal center–associated etiology of autoimmune risk loci

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 53 · see citing works

A century past the discovery of insulin: global progress and challenges for type 1 diabetes among children and adolescents in low-income and middle-income countries

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 58 · see citing works

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 · see citing works

Mapping genetic effects on cell type-specific chromatin accessibility and annotating complex immune trait variants using single nucleus ATAC-seq in peripheral blood

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 51 · see citing works

Presumption of guilt for T cells in type 1 diabetes: lead culprits or partners in crime depending on age of onset?

Carré, A., Richardson, S. J., Larger, É., & Mallone, R. (2020) · Diabetologia · doi:10.1007/s00125-020-05298-y · Cited by 51 · see citing works

How dysregulation of the immune system promotes diabetes mellitus and cardiovascular risk complications

Girard, D., & Vandiedonck, C. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.991716 · Cited by 51 · see citing works

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 · see citing works

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 41 · see citing works

Ustekinumab for type 1 diabetes in adolescents: a multicenter, double-blind, randomized phase 2 trial

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 43 · see citing works

Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning

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 48 · see citing works

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 37 · see citing works

Type 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 · see citing works

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 37 · see citing works

Localization of enteroviral RNA within the pancreas in donors with T1D and T1D-associated autoantibodies

Geravandi, S., Richardson, S. J., Pugliese, A., & Maedler, K. (2021) · Cell Reports Medicine · doi:10.1016/j.xcrm.2021.100371 · Cited by 36 · see citing works

Low-dose IL-2 reduces IL-21+ T cell frequency and induces anti-inflammatory gene expression in type 1 diabetes

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 38 · see citing works

Human 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 35 · see citing works

Multi-omic human pancreatic islet endoplasmic reticulum and cytokine stress response mapping provides type 2 diabetes genetic insights

Sokolowski, 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 33 · see citing works

Genomic Evidence Supports the Recognition of Endometriosis as an Inflammatory Systemic Disease and Reveals Disease-Specific Therapeutic Potentials of Targeting Neutrophil Degranulation

Bao, C., Wang, H., & Fang, H. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.758440 · Cited by 35 · see citing works

Type 1 diabetes risk genes mediate pancreatic beta cell survival in response to proinflammatory cytokines

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 · see citing works

Inhibition of the type 1 diabetes candidate gene PTPN2 aggravates TNF-α-induced human beta cell dysfunction and death

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 · see citing works

GATD3A-deficiency-induced mitochondrial dysfunction facilitates senescence of fibroblast-like synoviocytes and osteoarthritis progression

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 36 · see citing works

Type 1 diabetes risk factors, risk prediction and presymptomatic detection: Evidence and guidance for screening

Bonifacio, E. E., & Ziegler, A. (2025) · Diabetes Obesity and Metabolism · doi:10.1111/dom.16354 · Cited by 33 · see citing works

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 · see citing works

Identifying shared genetic loci and common risk genes of rheumatoid arthritis associated with three autoimmune diseases based on large-scale cross-trait genome-wide association studies

Wen, Y.-P., & Yu, Z. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1160397 · Cited by 31 · see citing works

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 34 · see citing works

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 28 · see citing works

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 32 · see citing works

Residual insulin secretion in individuals with type 1 diabetes in Finland: longitudinal and cross-sectional analyses

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 29 · see citing works

Single-Cell Multi-Omic Roadmap of Human Fetal Pancreatic DevelopmentPreprint

Sean, D. L. O., Liu, Z., Sun, H., Yu, S., Wong, D. S. M., Chu, E., Rao, S., Eng, N., Peixoto, G. A., Bouza, J. O., et al. (2022) · bioRxiv · doi:10.1101/2022.02.17.480942 · Cited by 24 · see citing works

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 27 · see citing works

The importance of biomarker development for monitoring type 1 diabetes progression rate and therapeutic responsiveness

Fyvie, M. J., & Gillespie, K. M. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1158278 · Cited by 27 · see citing works

Insights From Single Cell RNA Sequencing Into the Immunology of Type 1 Diabetes- Cell Phenotypes and Antigen Specificity

Hanna, S. J., Tatović, D., Thayer, T. C., & Dayan, C. M. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.751701 · Cited by 25 · see citing works

Probabilistic integration of transcriptome-wide association studies and colocalization analysis identifies key molecular pathways of complex traits

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 26 · see citing works

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 26 · see citing works

Metabolic 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 33 · see citing works

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 25 · see citing works

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 27 · see citing works

Genome-wide admixture and association analysis identifies African ancestry–specific risk loci of eosinophilic esophagitis in African Americans

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 · see citing works

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 23 · see citing works

Immunotherapy for type 1 diabetes

Allen, L. A., & Dayan, C. M. (2021) · British Medical Bulletin · doi:10.1093/bmb/ldab027 · Cited by 23 · see citing works

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 23 · see citing works

Non-HLA Gene Polymorphisms in the Pathogenesis of Type 1 Diabetes: Phase and Endotype Specific Effects

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 24 · see citing works

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 22 · see citing works

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 22 · see citing works

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 22 · see citing works

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 23 · see citing works

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 21 · see citing works

Germline genetic variants are associated with development of insulin-dependent diabetes in cancer patients treated with immune checkpoint inhibitors

Caulfield, 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 23 · see citing works

Harnessing Machine Learning, a Subset of Artificial Intelligence, for Early Detection and Diagnosis of Type 1 Diabetes: A Systematic Review

Mittal, 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 · see citing works

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 · see citing works

Prediction 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 · see citing works

Fine-mapping across diverse ancestries drives the discovery of putative causal variants underlying human complex traits and diseases

Yuan, 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

Optimization 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 20 · see citing works

The Immunoregulatory Role of the Signal Regulatory Protein Family and CD47 Signaling Pathway in Type 1 Diabetes

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 · see citing works

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 · see citing works

Population-scale skeletal muscle single-nucleus multi-omic profiling reveals extensive context specific genetic regulationPreprint

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 · see citing works

Characterization of the functional and transcriptomic effects of pro-inflammatory cytokines on human EndoC-βH5 beta cells

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 · see citing works

Genome-wide aggregated trans-effects on risk of type 1 diabetes: A test of the “omnigenic” sparse effector hypothesis of complex trait genetics

Iakovliev, 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 17 · see citing works

Enhanced genetic analysis of type 1 diabetes by selecting variants on both effect size and significance, and by integration with autoimmune thyroid diseasePreprint

Crouch, D. J. M., Inshaw, J. R. J., Robertson, C. C., Zhang, J., Chen, W., Önengüt-Gümüşcü, S., Cutler, A. J., Sidore, C., Cucca, F., Pociot, F., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.05.429962 · Cited by 17 · see citing works

Integration of GWAS, QTLs and keratinocyte functional assays reveals molecular mechanisms of atopic dermatitis

Oliva, 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 · see citing works

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 · see citing works

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 · see citing works

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 15 · see citing works

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 · see citing works

Type 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 18 · see citing works

Polygenic Scores Help Reduce Racial Disparities in Predictive Accuracy of Automated Type 1 Diabetes Classification Algorithms

Deutsch, 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 15 · see citing works

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 14 · see citing works

Multi-omics analysis in primary T cells elucidates mechanisms behind disease-associated genetic loci

Shi, C., Zhao, D.-Y., Butler, J., Frantzeskos, A., Rossi, S., Ding, J., Ferrazzano, C., Wynn, C., Hum, R., Richards, E., et al. (2023) · Genome Biology · doi:10.1186/s13059-025-03492-y · Cited by 14 · see citing works

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 15 · see citing works

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 14 · see citing works

Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases: Workshop Proceedings

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 · see citing works

Combining polygenic risk scores and human leukocyte antigen variants for personalized risk assessment of type 1 diabetes in the Taiwanese population

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 · see citing works

Distinct cellular immune responses in children en route to type 1 diabetes with different first-appearing autoantibodies

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 13 · see citing works

Milder loss of insulin-containing islets in individuals with type 1 diabetes and type 2 diabetes-associated TCF7L2 genetic variants

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 · see citing works

Insulin-like Growth Factor-1 Synergizes with IL-2 to Induce Homeostatic Proliferation of Regulatory T Cells

Shapiro, 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 · see citing works

Cross-population applications of genomics to understand the risk of multifactorial traits involving inflammation and immunity

Alamad, B., Elliott, K., & Knight, J. C. (2024) · Cambridge Prisms Precision Medicine · doi:10.1017/pcm.2023.25 · Cited by 12 · see citing works

Implementation of type 1 diabetes genetic risk screening in children in diverse communities: the Virginia PrIMeD project

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 12 · see citing works

Precision 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 · see citing works

The largest study of genetics of T1DM

Starling, S. (2021) · Nature Reviews Endocrinology · doi:10.1038/s41574-021-00532-y · Cited by 1 · see citing works

Discovery, Fine Mapping, and Functional Characterization of Genetic Susceptibility Loci in Type 1 Diabetes

Robertson, C. (2021) · Libra · doi:10.18130/j3y7-kv91

112-OR: Integrative Analysis of Chromatin Accessibility and Genetic Risk in T1D Patients and Controls

Robertson, C. C., Chen, W., Önengüt-Gümüşcü, S., CONCANNON, P. J., & Rich, S. S. (2020) · Diabetes · doi:10.2337/db20-112-or

A comprehensive integrated post-GWAS analysis of Type 1 diabetes reveals enhancer-based immune dysregulation

Kim, S., Hudgins, A. D., Yang, J., Zhu, Y., Tu, Z., Rosenfeld, M. G., DiLorenzo, T. P., & Suh, Y. (2021) · PLoS ONE · doi:10.1371/journal.pone.0257265 · Cited by 25 · see citing works

Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers

Önengüt-Gümüşcü, S., Chen, W., Burren, O. S., Farber, E., Szpak, M., Schofield, E. C., Achuthan, P., Guo, H., Stevens, H. E., Kundaje, A. B., et al. (2015) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 2 · see citing works