Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression
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Abstract
Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.
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Crucial regulatory elements governing gene expression, such as enhancers and promoters, were consistently detected by all models across multiple heads and layers.
“Crucial regulatory elements governing gene expression, such as enhancers and promoters41–43, were consistently detected by all models across multiple heads and layers.”
From Nucleotide Transformer: building and evaluating robust foundation models for human genomics (2025) · cites this paper as [43]
The Results section, “Local genetic effects on blood gene expression” (page unavailable), links promoter capture Hi-C contacts to genetic effects on gene expression, supporting the regulatory context. The paper does not itself discuss enhancers as gene-expression regulators; enhancers appear in a cited reference’s title. The statement about detection by models follows the citation and is not attributed to this source. (LLM, conf=0.76)
Experimental — accuracy not yet measuredAnalyses of transcript levels from blood and brain among other tissues have generated eQTLs, identifying potentially causal genes for various diseases.
“Analyses of transcript levels from blood and brain among other tissues have generated expression QTLs (eQTLs) (3–5), identifying potentially causal genes for various diseases.”
From Low overlap of plasma and CSF protein quantitative trait loci affects protein discovery for neurological disease (2026) · cites this paper as [4]
The Introduction and Results report eQTL analyses of blood transcript levels, and the Discussion says the resulting associations can prioritize putative trait-related genes. The paper does not report generating eQTLs from brain transcript levels; its analyses in other tissues concern replication of the blood findings. (LLM, conf=0.85)
Experimental — accuracy not yet measuredIt is probable that the models, without any supervision, have learned to distinguish relevant regulatory genomic features associated with gene expression and methylation variation.
“it is probable that the models, without any supervision, have learned to distinguish relevant regulatory genomic features associated with gene expression and methylation variation.”
From Nucleotide Transformer: building and evaluating robust foundation models for human genomics (2025) · cites this paper as [43]
The Results section on local and distal gene expression describes eQTL meta-analyses, while Online Methods describes expression-data preprocessing and probe matching. Neither reports that unsupervised models learned to distinguish regulatory genomic features associated with both gene-expression and methylation variation (searched: unsupervised models, regulatory genomic features, methylation variation). (LLM, conf=0.76)
Experimental — accuracy not yet measuredThe CSF variant was not significant in any plasma pQTL dataset or in brain/blood eQTL analyses.
“The CSF variant was not significant in any plasma pQTL dataset (9–11) or in brain/blood eQTL analyses (3–5).”
From Low overlap of plasma and CSF protein quantitative trait loci affects protein discovery for neurological disease (2026) · cites this paper as [4]
The Results section, “Meta-analyses on local and distal gene expression” (page unavailable), identifies this paper as a blood eQTL analysis. Neither that passage nor the passages retrieved for “CSF variant” and “cerebrospinal fluid” report whether the particular CSF variant was significant; the plasma pQTL datasets are cited separately. Our copy therefore cannot verify the claimed lack of significance. (LLM, conf=0.72)
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709 · see citing works
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
Yu, G., Wang, L.-G., Han, Y., & He, Q.-Y. (2012) · OMICS: A Journal of Integrative Biology · doi:10.1089/omi.2011.0118 · Cited by 36,259 · see citing works
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089 · 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
Enrichr: a comprehensive gene set enrichment analysis web server 2016 update
Kuleshov, M. V., Jones, M. R., Rouillard, A. D., Fernandez, N. F., Duan, Q., Wang, Z., Koplev, S., Jenkins, S. L., Jagodnik, K. M., Lachmann, A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw377 · Cited by 10,799 · see citing works
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587 · see citing works
Self-citationA 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
Rao, S. S. P., Huntley, M. H., Durand, N. C., Stamenova, E. K., Bochkov, I. D., Robinson, J. T., Sanborn, A. L., Machol, I., Omer, A. D., Lander, E. S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.021 · Cited by 9,212 · 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
Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool
Chen, E. Y., Tan, C. M., Kou, Y., Duan, Q., Wang, Z., Meirelles, G. V., Clark, N. R., & Ma’ayan, A. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-128 · Cited by 7,814 · see citing works
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534 · see citing works
Self-citationGiambartolomei, 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
Genetic effects on gene expression across human tissues
GTEx Consortium (2017) · Nature · doi:10.1038/nature24277 · Cited by 4,036 · see citing works
Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487 · see citing works
Self-citationIntegration of summary data from GWAS and eQTL studies predicts complex trait gene targets
Zhu, Z., Zhang, F., Hu, H., Bakshi, A., Robinson, M. R., Powell, J. E., Montgomery, G. W., Goddard, M. E., Wray, N. R., Visscher, P. M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3538 · Cited by 3,352 · see citing works
Self-citationWiller (2013) · doi:10.1038/ng.2797 · Cited by 2,983 · see citing works
An Expanded View of Complex Traits: From Polygenic to Omnigenic
Boyle, E. A., Li, Y. I., & Pritchard, J. K. (2017) · Cell · doi:10.1016/j.cell.2017.05.038 · Cited by 2,851 · see citing works
Self-citationZerbino, D. R., Achuthan, P., Akanni, W., Amode, M. R., Barrell, D., Bhai, J., Billis, K., Cummins, C., Gall, A., Girón, C. G., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1098 · Cited by 2,605 · see citing works
Liu, J. Z., van Sommeren, S., Huang, H., Ng, S. C., Alberts, R., Takahashi, A., Ripke, S., Lee, J. C., Jostins, L., Shah, T., et al. (2015) · Nature Genetics · doi:10.1038/ng.3359 · Cited by 2,603 · see citing works
Self-citationA comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease
the CARDIoGRAMplusC4D Consortium (2015) · Nature Genetics · doi:10.1038/ng.3396 · Cited by 2,447 · see citing works
Dibner, C., Schibler, U., & Albrecht, U. (2010) · Annual Review of Physiology · doi:10.1146/annurev-physiol-021909-135821 · Cited by 2,421 · see citing works
The ENCODE (ENCyclopedia Of DNA Elements) Project
(2004) · Science · doi:10.1126/science.1105136 · Cited by 2,390 · see citing works
Baechler, E. C., Batliwalla, F., Karypis, G., Gaffney, P. M., Ortmann, W. A., Espe, K. J., Shark, K. B., Grande, W. J., Hughes, K. M. H., Kapur, V., et al. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0337679100 · Cited by 2,246 · see citing works
The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog)
MacArthur, J., Bowler, E., Cerezo, M., Gil, L., Hall, P., Hastings, E., Junkins, H., McMahon, A., Milano, A., Morales, J., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1133 · Cited by 2,161 · see citing works
A Large-Scale, Consortium-Based Genomewide Association Study of Asthma
Moffatt, M. F., Gut, I. G., Démenais, F., Strachan, D. P., Bouzigon, E., Heath, S. C., von Mutius, E., Farrall, M., Lathrop, M. G., & Cookson, W. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa0906312 · Cited by 2,003 · see citing works
Interferon and Granulopoiesis Signatures in Systemic Lupus Erythematosus Blood
Bennett, L. B., Palucka, K., Arce, E., Cantrell, V., Borvák, J., Banchereau, J., & Pascual, V. (2003) · The Journal of Experimental Medicine · doi:10.1084/jem.20021553 · Cited by 1,962 · see citing works
The Electronic Medical Records and Genomics (eMERGE) Consortium, Wood, A. R., The MIGen Consortium, The PAGE Consortium, Study, T. L. C., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., et al. (2014) · Nature Genetics · doi:10.1038/ng.3097 · Cited by 1,853 · see citing works
Self-citationSystematic 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
Self-citationAn atlas of genetic influences on human blood metabolites
The Multiple Tissue Human Expression Resource (MuTHER) Consortium, Shin, S.-Y., Fauman, E. B., Petersen, A.-K., Krumsiek, J., Santos, R., Huang, J., Arnold, M., Erte, I., Forgetta, V., et al. (2014) · Nature Genetics · doi:10.1038/ng.2982 · Cited by 1,515 · see citing works
A User's Guide to the Encyclopedia of DNA Elements (ENCODE)
The ENCODE Project Consortium (2011) · PLoS Biology · doi:10.1371/journal.pbio.1001046 · Cited by 1,495 · see citing works
Binding and Degradation of Low Density Lipoproteins by Cultured Human Fibroblasts
Goldstein, J. L., & Brown, M. S. (1974) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(19)42341-7 · Cited by 1,485 · see citing works
The human transcriptome across tissues and individuals
Melé, M., Ferreira, P. G., Reverter, F., DeLuca, D. S., Monlong, J., Sammeth, M., Young, T. R., Goldmann, J. M., Pervouchine, D. D., Sullivan, T. J., et al. (2015) · Science · doi:10.1126/science.aaa0355 · Cited by 1,304 · see citing works
Self-citationGenome-wide association study identifies 74 loci associated with educational attainment
Okbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A., Turley, P., Chen, G.-B., Emilsson, V., Meddens, S. F. W., et al. (2016) · Nature · doi:10.1038/nature17671 · Cited by 1,297 · see citing works
Self-citationThe Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease
Astle, W. J., Elding, H., Jiang, T., Allen, D., Ruklisa, D., Mann, A. L., Mead, D., Bouman, H., Riveros-Mckay, F., Kostadima, M. A., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.042 · Cited by 1,224 · see citing works
Self-citationGenome-wide meta-analyses identify multiple loci associated with smoking behavior
The Tobacco and Genetics Consortium (2010) · Nature Genetics · doi:10.1038/ng.571 · Cited by 1,098 · see citing works
REST: A mammalian silencer protein that restricts sodium channel gene expression to neurons
Chong, J. A., Tapia-Ramı́rez, J., Kim, S. S. Y., Toledo‐Aral, J. J., Zheng, Y., Boutros, M., Altshuller, Y. M., Frohman, M. A., Kraner, S. D., & Mandel, G. (1995) · Cell · doi:10.1016/0092-8674(95)90298-8 · Cited by 1,089 · see citing works
Schoenherr, C. J., & Anderson, D. J. (1995) · Science · doi:10.1126/science.7871435 · Cited by 1,088 · see citing works
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
Self-citationChEA: transcription factor regulation inferred from integrating genome-wide ChIP-X experiments
Lachmann, A., Xu, H., Krishnan, J., Berger, S., Mazloom, A. R., & Ma’ayan, A. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq466 · Cited by 1,033 · see citing works
Bentham, J., Morris, D. L., Graham, D. S. C., Pinder, C. L., Tombleson, P., Behrens, T. W., Martin, J. J., Fairfax, B. P., Knight, J. C., Chen, L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3434 · Cited by 990 · see citing works
Self-citationrtracklayer: an R package for interfacing with genome browsers
Lawrence, M. F., Gentleman, R. C., & Carey, V. J. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp328 · Cited by 971 · see citing works
Comprehensive functional genomic resource and integrative model for the human brain
Wang, D., Liu, S., Warrell, J., Won, H., Shi, X., Navarro, F. C. P., Clarke, D., Gu, M., Emani, P., Yang, Y. T., et al. (2018) · Science · doi:10.1126/science.aat8464 · Cited by 965 · see citing works
Self-citationGateva, V., Sandling, J. K., Hom, G., Taylor, K. E., Chung, S. A., Sun, X., Ortmann, W. A., Kosoy, R., Ferreira, R. C., Nordmark, G., et al. (2009) · Nature Genetics · doi:10.1038/ng.468 · Cited by 810 · see citing works
Biological interpretation of genome-wide association studies using predicted gene functions
Pers, T. H., Karjalainen, J. M., Chan, Y., Westra, H.-J., Wood, A. R., Yang, J., Lui, J. C., Vedantam, S., Gustafsson, S., Esko, T., et al. (2015) · Nature Communications · doi:10.1038/ncomms6890 · Cited by 787 · see citing works
Self-citationHyde, C. L., Nagle, M. W., Tian, C., Chen, X., Paciga, S. A., Wendland, J. R., Tung, J. Y., Hinds, D. A., Perlis, R. H., & Winslow, A. R. (2016) · Nature Genetics · doi:10.1038/ng.3623 · Cited by 784 · see citing works
Kettunen, J., Demirkan, A., Würtz, P., Draisma, H. H. M., Haller, T., Rawal, R., Vaarhorst, A., Kangas, A. J., Lyytikäinen, L.-P., Pirinen, M., et al. (2016) · Nature Communications · doi:10.1038/ncomms11122 · Cited by 738 · see citing works
Self-citationMassive mining of publicly available RNA-seq data from human and mouse
Lachmann, A., Torre, D., Keenan, A. B., Jagodnik, K. M., Lee, H. J., Wang, L., Silverstein, M. C., & Ma’ayan, A. (2018) · Nature Communications · doi:10.1038/s41467-018-03751-6 · Cited by 701 · see citing works
Colocalization of GWAS and eQTL Signals Detects Target Genes
Hormozdiari, F., van de Bunt, M., Segrè, A. V., Li, X., Joo, J. W. J., Bilow, M., Sul, J. H., Sankararaman, S., Pasaniuc, B., & Eskin, E. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.10.003 · Cited by 697 · see citing works
SHRiMP: Accurate Mapping of Short Color-space Reads
Rumble, S. M., Lacroute, P., Dalca, A. V., Fiume, M., Sidow, A., & Brudno, M. (2009) · PLoS Comput. Biol. · doi:10.1371/journal.pcbi.1000386 · Cited by 639 · see citing works
A scored human protein–protein interaction network to catalyze genomic interpretation
Li, T., Wernersson, R., Hansen, R. B., Horn, H., Mercer, J., Slodkowicz, G., Workman, C. T., Rigina, O., Rapacki, K., Stærfeldt, H., et al. (2016) · Nature Methods · doi:10.1038/nmeth.4083 · Cited by 630 · see citing works
Serine palmitoyltransferase, a key enzyme of sphingolipid metabolism
Hanada, K. (2003) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/s1388-1981(03)00059-3 · Cited by 618 · see citing works
Circadian time signatures of fitness and disease
Bass, J. T., & Lazar, M. A. (2016) · Science · doi:10.1126/science.aah4965 · Cited by 616 · see citing works
Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche
Study, A. O. C., Perry, J. R. B., The GENICA Network, kConFab, Study, T. L. C., The InterAct Consortium, Early Growth Genetics (EGG) Consortium, Day, F., Elks, C. E., Sulem, P., et al. (2014) · Nature · doi:10.1038/nature13545 · Cited by 604 · see citing works
Self-citationMacrophage ABCA1 and ABCG1, but not SR-BI, promote macrophage reverse cholesterol transport in vivo
Wang, X., Collins, H. L., Ranalletta, M., Fuki, I. V., Billheimer, J. T., Rothblat, G. H., Tall, A. R., & Rader, D. J. (2007) · Journal of Clinical Investigation · doi:10.1172/jci32057 · Cited by 593 · see citing works
Natarajan, P., Young, R., Stitziel, N. O., Padmanabhan, S., Baber, U., Mehran, R., Sartori, S., Fuster, V., Reilly, D. F., Butterworth, A., et al. (2017) · Circulation · doi:10.1161/circulationaha.116.024436 · Cited by 570 · see citing works
Trans effects on gene expression can drive omnigenic inheritance
Liu, X., Li, Y. I., & Pritchard, J. K. (2019) · Cell · doi:10.1016/j.cell.2019.04.014 · Cited by 523 · see citing works
Self-citationTrans Effects on Gene Expression Can Drive Omnigenic InheritancePreprint
Liu, X.-Y., Li, Y. I., & Pritchard, J. (2018) · bioRxiv · doi:10.1101/425108 · Cited by 508 · see citing works
Self-citationDisease variants alter transcription factor levels and methylation of their binding sites
Bonder, M. J., Luijk, R., Zhernakova, D. V., Moed, M., Deelen, P., Vermaat, M., van Iterson, M., van Dijk, F., van Galen, M., Bot, J. J., et al. (2016) · Nature Genetics · doi:10.1038/ng.3721 · Cited by 462 · see citing works
Self-citationVariable prediction accuracy of polygenic scores within an ancestry group
Mostafavi, H., Harpak, A., Agarwal, I., Conley, D., Pritchard, J. K., & Przeworski, M. (2020) · eLife · doi:10.7554/elife.48376 · Cited by 457 · see citing works
Self-citationIdentification of context-dependent expression quantitative trait loci in whole blood
Zhernakova, D. V., Deelen, P., Vermaat, M., van Iterson, M., van Galen, M., Arindrarto, W., van 't Hof, P., Mei, H., van Dijk, F., Westra, H.-J., et al. (2017) · Nature Genetics · doi:10.1038/ng.3737 · Cited by 441 · see citing works
Self-citationQi, T., Wu, Y., Zeng, J., Zhang, F., Xue, A., Jiang, L., Zhu, Z., Kemper, K., Yengo, L., Zheng, Z., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04558-1 · Cited by 427 · see citing works
Self-citationthe BIOS Consortium, van Iterson, M., van Zwet, E. W., & Heijmans, B. T. (2017) · Genome biology · doi:10.1186/s13059-016-1131-9 · Cited by 421 · see citing works
Self-citationLemaître, R. N., Tanaka, T., Tang, W., Manichaikul, A. W., Foy, M., Kabagambe, E. K., Nettleton, J. A., King, I. B., Weng, L.-C. C., Bhattacharya, S., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002193 · Cited by 412 · see citing works
Self-citationSingle-cell RNA sequencing identifies celltype-specific cis-eQTLs and co-expression QTLs
Study, L. C., van der Wijst, M. G. P., BIOS Consortium, Brugge, H., de Vries, D. H., Deelen, P., Swertz, M. A., & Franke, L. (2018) · Nature Genetics · doi:10.1038/s41588-018-0089-9 · Cited by 399 · see citing works
Self-citationSignatures of negative selection in the genetic architecture of human complex traits
Zeng, J., de Vlaming, R., Wu, Y., Robinson, M. R., Lloyd-Jones, L. R., Yengo, L., Yap, C. X., Xue, A., Sidorenko, J., McRae, A. F., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0101-4 · Cited by 391 · see citing works
Self-citationTissue-specific regulatory circuits reveal variable modular perturbations across complex diseases
Marbach, D., Lamparter, D., Quon, G., Kellis, M., Kutalik, Z., & Bergmann, S. (2016) · Nature Methods · doi:10.1038/nmeth.3799 · Cited by 326 · see citing works
Self-citationAiolos Regulates B Cell Activation and Maturation to Effector State
Wang, J.-H., Avitahl, N., Cariappa, A., Friedrich, C., Ikeda, T., Renold, A., Andrikopoulos, K., Liang, L., Pillai, S., Morgan, B. A., et al. (1998) · Immunity · doi:10.1016/s1074-7613(00)80637-8 · Cited by 321 · see citing works
Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics
Lamparter, D., Marbach, D., Rueedi, R., Kutalik, Z., & Bergmann, S. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004714 · Cited by 312 · see citing works
Self-citationSeventy-five genetic loci influencing the human red blood cell
van der Harst, P., Zhang, W., Leach, I. M., Rendon, A., Verweij, N., Sehmi, J., Paul, D. S., Elling, U., Allayee, H., Li, X., et al. (2012) · Nature · doi:10.1038/nature11677 · Cited by 306 · see citing works
Self-citationQuantifying genetic effects on disease mediated by assayed gene expression levels
Yao, D. W., O’Connor, L. J., Price, A. L., & Gusev, A. (2020) · Nature Genetics · doi:10.1038/s41588-020-0625-2 · Cited by 274 · see citing works
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O'Connor, L. J., Schoech, A. P., Hormozdiari, F., Gazal, S., Patterson, N., & Price, A. L. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.07.003 · Cited by 268 · see citing works
Optimally weighted Z-test is a powerful method for combining probabilities in meta-analysis
Zaykin, D. V. (2011) · Journal of Evolutionary Biology · doi:10.1111/j.1420-9101.2011.02297.x · Cited by 266 · see citing works
Genome-Wide Association Analysis of Autoantibody Positivity in Type 1 Diabetes Cases
Plagnol, V., Howson, J. M. M., Smyth, D. J., Walker, N. M., Hafler, J. P., Wallace, C., Stevens, H. E., Jackson, L. K., Simmonds, M. J., Bingley, P. J., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002216 · Cited by 262 · see citing works
The Genetic Architecture of Gene Expression in Peripheral Blood
Lloyd‐Jones, L. R., Holloway, A., McRae, A. F., Yang, J., Small, K. S., Zhao, J., Zeng, B., Bakshi, A., Metspalu, A., Dermitzakis, M., et al. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.12.008 · Cited by 243 · see citing works
Self-citationThe single-cell eQTLGen consortium
van der Wijst, M. G. P., de Vries, D., Groot, H. E., Trynka, G., Hon, C.-C., Bonder, M. J., Stegle, O., Nawijn, M. C., Idaghdour, Y., van der Harst, P., et al. (2020) · eLife · doi:10.7554/elife.52155 · Cited by 215 · see citing works
Self-citationPantel, A. R., Teixeira, A., Haddad, E. K., Wood, E. G., Steinman, R. M., & Longhi, M. P. (2014) · PLoS Biology · doi:10.1371/journal.pbio.1001759 · Cited by 210 · see citing works
Yin, X., Low, H. Q., Wang, L., Li, Y., Ellinghaus, E., Han, J., Estivill, X., Sun, L., Zuo, X., Shen, C., et al. (2015) · Nature Communications · doi:10.1038/ncomms7916 · Cited by 200 · see citing works
Price, A. L., Helgason, A., Þorleifsson, G., McCarroll, S. A., Kong, A., & Stefánsson, K. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001317 · Cited by 195 · see citing works
McBride, J., Jiang, J. Z., Abbas, A. R., Morimoto, A. M., Li, J., Maciuca, R. D., Townsend, M. J., Wallace, D. J., Kennedy, W. P., & Drappa, J. (2012) · Arthritis & Rheumatism · doi:10.1002/art.34632 · Cited by 186 · see citing works
Joehanes, R., Zhang, X., Huan, T., Yao, C., Ying, S., Nguyen, Q. T., Demirkale, C. Y., Feolo, M., Sharopova, N., Sturcke, A., et al. (2017) · Genome biology · doi:10.1186/s13059-016-1142-6 · Cited by 181 · see citing works
Prospects for using risk scores in polygenic medicine
Lewis, C., & Vassos, E. (2017) · Genome Medicine · doi:10.1186/s13073-017-0489-y · Cited by 172 · see citing works
Genotype harmonizer: automatic strand alignment and format conversion for genotype data integration
Deelen, P., Bonder, M. J., van der Velde, K., Westra, H.-J., Winder, E., Hendriksen, D., Franke, L., & Swertz, M. A. (2014) · BMC Research Notes · doi:10.1186/1756-0500-7-901 · Cited by 161 · see citing works
Self-citationThe MOLGENIS toolkit: rapid prototyping of biosoftware at the push of a button
Swertz, M. A., Dijkstra, M., Adamusiak, T., van der Velde, J. K., Kanterakis, A., Roos, E. T., Lops, J., Þórisson, G. Á., Arends, D., Byelas, G., et al. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-s12-s12 · Cited by 149 · see citing works
Self-citationCheong, A., Bingham, A. J., Li, J., Kumar, B., Sukumar, P., Munsch, C. M., Buckley, N. J., Neylon, C. B., Porter, K. E., Beech, D. J., et al. (2005) · Molecular Cell · doi:10.1016/j.molcel.2005.08.030 · Cited by 143 · see citing works
Conditional eQTL analysis reveals allelic heterogeneity of gene expression
Jansen, R., Hottenga, J.-J., Nivard, M. G., Abdellaoui, A., Laport, B., de Geus, E. J., Wright, F. A., Penninx, B. W. J. H., & Boomsma, D. I. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx043 · Cited by 141 · see citing works
Deelen, P., van Dam, S., Herkert, J. C., Karjalainen, J. M., Brugge, H., Abbott, K. M., van Diemen, C. C., van der Zwaag, P. A., Gerkes, E. H., Zonneveld-Huijssoon, E., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-10649-4 · Cited by 138 · see citing works
Self-citationYao, Y., Higgs, B. W., Morehouse, C., et al. (2008) · Human Genomics and Proteomics · doi:10.4061/2009/374312 · Cited by 134 · see citing works
Phosphoserine Aminotransferase Deficiency: A Novel Disorder of the Serine Biosynthesis Pathway
Hart, C., Race, V., Achouri, Y., Wiame, E., Sharrard, M. J., Olpin, S. E., Watkinson, J., Bonham, J. R., Jaeken, J., Matthijs, G., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/517888 · Cited by 120 · see citing works
Neu-Laxova Syndrome, an Inborn Error of Serine Metabolism, Is Caused by Mutations in PHGDH
Shaheen, R., Rahbeeni, Z. A., Alhashem, A. M., Faqeih, E., Zhao, Q., Xiong, Y., Almoisheer, A., Al-Qattan, S. M., Almadani, H. A., Alonazi, N. A., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.04.015 · Cited by 118 · see citing works
McLaughlin, H. M., Sakaguchi, R., Giblin, W., et al. (2011) · Human Mutation · doi:10.1002/humu.21635 · Cited by 115 · see citing works
Klomp, L. W. J., de Koning, T. J., Malingré, H. E. M., van Beurden, E. A. C. M., Brink, M., Opdam, F. L., Durán, M., Jaeken, J., Pineda, M., Maldergem, L. V., et al. (2000) · The American Journal of Human Genetics · doi:10.1086/316886 · Cited by 112 · see citing works
Serine biosynthesis and transport defects
El‐Hattab, A. W. (2016) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2016.04.010 · Cited by 110 · see citing works
He, M., Xu, M., Zhang, B., Liang, J., Chen, P., Lee, J.-Y., Johnson, T. A., Li, H., Yang, X., Dai, J., et al. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddu583 · Cited by 106 · see citing works
Dynamic Role of trans Regulation of Gene Expression in Relation to Complex Traits
Yao, C., Joehanes, R., Johnson, A. D., Huan, T., Liu, C., Freedman, J. E., Munson, P. J., Hill, D. E., Vidal, M., & Levy, D. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.02.003 · Cited by 106 · see citing works
Dysregulated Expression of Neuregulin-1 by Cortical Pyramidal Neurons Disrupts Synaptic Plasticity
Agarwal, A., Zhang, M., Trembak-Duff, I., Unterbarnscheidt, T., Radyushkin, K., Dibaj, P., Martins‐de‐Souza, D., Boretius, S., Brzózka, M. M., Steffens, H., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.07.026 · Cited by 105 · see citing works
Wu, Y., Zheng, Z., Visscher, P. M., & Yang, J. (2017) · Genome biology · doi:10.1186/s13059-017-1216-0 · Cited by 100 · see citing works
Self-citationWestra, H.-J., Jansen, R. C., Fehrmann, R. S. N., Meerman, G. J. T., van Heel, D. A., Wijmenga, C., & Franke, L. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr323 · Cited by 95 · see citing works
Self-citationKirsten, H., Al-Hasani, H., Holdt, L. M., Gross, A., Beutner, F., Krohn, K., Horn, K., Ahnert, P., Burkhardt, R., Reiche, K., et al. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv194 · Cited by 92 · see citing works
Self-citationHereditary sensory neuropathy type I
Auer‐Grumbach, M. (2008) · Orphanet Journal of Rare Diseases · doi:10.1186/1750-1172-3-7 · Cited by 80 · see citing works
Brynedal, B., Choi, J., Raj, T., Bjornson, R. D., Stranger, B. E., Neale, B. M., Voight, B. F., & Cotsapas, C. J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.02.004 · Cited by 80 · see citing works
Kõks, G., Uudelepp, M., Limbach, M., Peterson, P., Reimann, E., & Kõks, S. (2015) · American Journal Of Pathology · doi:10.1016/j.ajpath.2015.07.006 · Cited by 79 · see citing works
Sousa, I., Clark, T. G., Holt, R., Pagnamenta, A. T., Mulder, E. J., Minderaa, R. B., Bailey, A. J., Battaglia, A., Klauck, S. M., Poustka, F., et al. (2010) · Molecular Autism · doi:10.1186/2040-2392-1-7 · Cited by 67 · see citing works
Schofield, E. C., Carver, T., Achuthan, P., Freire-Pritchett, P., Spivakov, M., Todd, J. A., & Burren, O. S. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw173 · Cited by 65 · see citing works
Evidence for Weak Selective Constraint on Human Gene Expression
Glassberg, E. C., Gao, Z., Harpak, A., Lan, X., & Pritchard, J. K. (2018) · Genetics · doi:10.1534/genetics.118.301833 · Cited by 63 · see citing works
Self-citationDisturbed phospholipid metabolism in serine biosynthesis defects revealed by metabolomic profiling
Glinton, K. E., Benke, P. J., Lines, M. A., et al. (2017) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2017.12.009 · Cited by 57 · see citing works
Song, C., Tan, P., Zhang, Z., Wu, W., Dong, Y., Zhao, L., Liu, H., Guan, H., & Li, F. (2018) · The FASEB Journal · doi:10.1096/fj.201600825rrr · Cited by 44 · see citing works
Discovering in vivo cytokine-eQTL interactions from a lupus clinical trial
Davenport, E. E., Amariuta, T., Gutiérrez‐Arcelus, M., Slowikowski, K., Westra, H.-J., Luo, Y., Shen, C., Rao, D. A., Zhang, Y., Pearson, S., et al. (2018) · Genome biology · doi:10.1186/s13059-018-1560-8 · Cited by 43 · see citing works
Self-citationActivation of GPR15 and its involvement in the biological effects of smoking
Kõks, S., & Kõks, G. (2017) · Experimental Biology and Medicine · doi:10.1177/1535370217703977 · Cited by 36 · see citing works
Singh, A. B., Kan, C. F. K., Shende, V. R., Dong, B., & Liu, J. (2014) · Journal of Lipid Research · doi:10.1194/jlr.m049429 · Cited by 34 · see citing works
Arginine and glycine stimulate creatine synthesis in creatine transporter 1-deficient lymphoblasts
Leuzzi, V., Alessandri, M., Casarano, M., et al. (2008) · Analytical Biochemistry · doi:10.1016/j.ab.2008.01.018 · Cited by 27 · see citing works
Deelen, P., van Dam, S., Herkert, J. C., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/375766 · Cited by 27 · see citing works
Self-citationOh, Y., & Chung, K. C. (2012) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.336354 · Cited by 24 · see citing works
Ding, Y., Herman, J., Toledo, C. M., et al. (2017) · Oncotarget · doi:10.18632/oncotarget.18153 · Cited by 24 · see citing works
Smirnova, T., Miniou, P., Viégas-Pèquignot, E., et al. (1996) · Genomics · doi:10.1006/geno.1996.0506 · Cited by 15 · see citing works
Tobacco-smoking induced GPR15-expressing T cells in blood do not indicate pulmonary damage
Bauer, M., Fink, B., Seyfarth, H., et al. (2017) · BMC Pulmonary Medicine · doi:10.1186/s12890-017-0509-0 · Cited by 12 · see citing works
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The GTEx Consortium atlas of genetic regulatory effects across human tissues
The GTEx Consortium, Aguet, F., Anand, S., Ardlie, K. G., Gabriel, S., Getz, G. A., Graubert, A., Hadley, K., Handsaker, R. E., Huang, K. H., et al. (2020) · Science · doi:10.1126/science.aaz1776 · Cited by 5,547 · see citing works
Self-citationMapping genomic loci implicates genes and synaptic biology in schizophrenia
Trubetskoy, V., Pardiñas, A. F., Qi, T., Panagiotaropoulou, G., Awasthi, S., Bigdeli, T. B., Bryois, J., Chen, C.-Y., Dennison, C. A., Hall, L. S., et al. (2022) · Nature · doi:10.1038/s41586-022-04434-5 · Cited by 2,964 · see citing works
Self-citationNalls, M. A., Blauwendraat, C., Vallerga, C. L., Heilbron, K., Bandres-Ciga, S., Chang, D., Tan, M., Kia, D. A., Noyce, A. J., Xue, A., et al. (2019) · The Lancet Neurology · doi:10.1016/s1474-4422(19)30320-5 · Cited by 2,454 · see citing works
Self-citationLarge-scale association analyses identify host factors influencing human gut microbiome composition
Kurilshikov, A., Medina-Gomez, C., Bacigalupe, R., Radjabzadeh, D., Wang, J., Demirkan, A., Le Roy, C. I., Raygoza Garay, J. A., Finnicum, C. T., Liu, X., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00763-1 · Cited by 1,786 · see citing works
Self-citationGenome-wide association studies
Uffelmann, E., Huang, Q. Q., Munung, N. S., de Vries, J., Okada, Y., Martin, A. R., Martin, H. C., Lappalainen, T., & Posthuma, D. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00056-9 · Cited by 1,849 · see citing works
Plasma proteomic associations with genetics and health in the UK Biobank
Sun, B. B., Chiou, J., Traylor, M., Benner, C., Hsu, Y.-H., Richardson, T. G., Surendran, P., Mahajan, A., Robins, C., Vasquez-Grinnell, S. G., et al. (2023) · Nature · doi:10.1038/s41586-023-06592-6 · Cited by 1,740 · see citing works
Self-citationSingle-cell eQTL mapping identifies cell type–specific genetic control of autoimmune disease
Yazar, S., Alquicira-Hernandez, J., Wing, K., Senabouth, A., Gordon, M. G., Andersen, S., Lu, Q., Rowson, A., Taylor, T. R. P., Clarke, L., et al. (2022) · Science · doi:10.1126/science.abf3041 · Cited by 682 · see citing works
Self-citationThe Polygenic and Monogenic Basis of Blood Traits and Diseases
Vuckovic, D., Bao, E. L., Akbari, P., Lareau, C. A., Mousas, A., Jiang, T., Chen, M.-H., Raffield, L. M., Tardaguila, M., Huffman, J. E., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.008 · Cited by 671 · see citing works
Self-citationChen, M.-H., Raffield, L. M., Mousas, A., Sakaue, S., Huffman, J. E., Moscati, A., Trivedi, B., Jiang, T., Akbari, P., Vuckovic, D., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.045 · Cited by 661 · see citing works
Nucleotide Transformer: building and evaluating robust foundation models for human genomics
Dalla-Torre, H., Gonzalez, L., Mendoza-Revilla, J., Lopez Carranza, N., Grzywaczewski, A. H., Oteri, F., Dallago, C., Trop, E., de Almeida, B. P., Sirelkhatim, H., et al. (2025) · Nature Methods · doi:10.1038/s41592-024-02523-z · Cited by 656 · see citing works
“Given that most of these genetic variants tend to reside within regulatory regions 41–43 , it is probable that the models, without any supervision, have learned to distinguish relevant regulatory genomic features associated with gene expression and methylation variation.”
Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation
Min, J. L., Hemani, G., Hannon, E., Dekkers, K. F., Castillo-Fernandez, J., Luijk, R., Carnero-Montoro, E., Lawson, D. J., Burrows, K., Suderman, M., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00923-x · Cited by 506 · see citing works
Self-citationSystematic differences in discovery of genetic effects on gene expression and complex traits
Mostafavi, H., Spence, J. P., Naqvi, S., & Pritchard, J. K. (2023) · Nature Genetics · doi:10.1038/s41588-023-01529-1 · Cited by 336 · see citing works
Self-citationPorcu, E., Rüeger, S., Lepik, K., eQTLGen Consortium, Agbessi, M., Ahsan, H., Alves, I., Andiappan, A., Arindrarto, W., Awadalla, P., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-10936-0 · Cited by 322 · see citing works
Self-citationRobertson, 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., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00880-5 · Cited by 302 · see citing works
Where Are the Disease-Associated eQTLs?
Umans, B. D., Battle, A., & Gilad, Y. (2021) · Trends in Genetics · doi:10.1016/j.tig.2020.08.009 · Cited by 296 · see citing works
Self-citationYang, C., Farias, F. H. G., Ibanez, L., Suhy, A., Sadler, B., Fernandez, M. V., Wang, F., Bradley, J. L., Eiffert, B., Bahena, J. A., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00886-6 · Cited by 290 · see citing works
de Klein, N., Tsai, E. A., Vochteloo, M., Baird, D., Huang, Y., Chen, C.-Y., van Dam, S., Oelen, R., Deelen, P., Bakker, O. B., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01300-6 · Cited by 272 · see citing works
Self-citationCombining SNP-to-gene linking strategies to identify disease genes and assess disease omnigenicity
Gazal, S., Weissbrod, O., Hormozdiari, F., Dey, K. K., Nasser, J., Jagadeesh, K. A., Weiner, D. J., Shi, H., Fulco, C. P., O’Connor, L. J., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01087-y · Cited by 181 · see citing works
Single-cell genomics meets human genetics
Cuomo, A. S. E., Nathan, A., Raychaudhuri, S., MacArthur, D. G., & Powell, J. E. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00599-5 · Cited by 124 · see citing works
Self-citationNon-coding variability at the APOE locus contributes to the Alzheimer’s risk
Zhou, X., Chen, Y., Mok, K. Y., Kwok, T. C. Y., Mok, V. C. T., Guo, Q., Ip, F. C., Chen, Y., Mullapudi, N., Initiative, A. D. N., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-10945-z · Cited by 120 · see citing works
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Yuan, Q., & Duren, Z. (2025) · Nature Biotechnology · doi:10.1038/s41587-024-02182-7 · Cited by 118 · see citing works
Western, D., Timsina, J., Wang, L., Wang, C., Yang, C., Phillips, B., Wang, Y., Liu, M., Ali, M., Beric, A., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01972-8 · Cited by 111 · see citing works
Scalable genetic screening for regulatory circuits using compressed Perturb-seq
Yao, D., Binan, L., Bezney, J., Simonton, B., Freedman, J., Frangieh, C. J., Dey, K., Geiger-Schuller, K., Eraslan, B., Gusev, A., et al. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-01964-9 · Cited by 101 · see citing works
Liscovitch-Brauer, N., Montalbano, A., Deng, J., Méndez-Mancilla, A., Wessels, H.-H., Moss, N. G., Kung, C.-Y., Sookdeo, A., Guo, X., Geller, E., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00902-x · Cited by 107 · see citing works
Tang, A. S., Rankin, K. P., Cerono, G., Miramontes, S., Mills, H., Roger, J., Zeng, B., Nelson, C., Soman, K., Woldemariam, S., et al. (2024) · Nature Aging · doi:10.1038/s43587-024-00573-8 · Cited by 86 · see citing works
Self-citationHillary, R. F., McCartney, D. L., Harris, S. E., Stevenson, A. J., Seeboth, A., Zhang, Q., Liewald, D. C., Evans, K. L., Ritchie, C. W., Tucker-Drob, E. M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11177-x · Cited by 78 · see citing works
Small, A. M., Peloso, G. M., Linefsky, J., Aragam, J., Galloway, A., Tanukonda, V., Wang, L.-C., Yu, Z., Sunitha Selvaraj, M., Farber-Eger, E. H., et al. (2023) · Circulation · doi:10.1161/circulationaha.122.061451 · Cited by 76 · see citing works
Junqueira, C., Crespo, Â., Ranjbar, S., Ingber, J., Parry, B., Ravid, S., Lacerda, L. B. D., Lewandrowski, M., Clark, S., Ho, F., et al. (2021) · doi:10.1101/2021.03.06.21252796 · Cited by 70 · see citing works
scQTLbase: an integrated human single-cell eQTL database
Ding, R., Wang, Q., Gong, L., Zhang, T., Zou, X., Xiong, K., Liao, Q., Plass, M., & Li, L. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkad781 · Cited by 62 · see citing works
Chandrashekar, P. B., Alatkar, S., Wang, J., Hoffman, G. E., He, C., Jin, T., Khullar, S., Bendl, J., Fullard, J. F., Roussos, P., et al. (2023) · Genome Medicine · doi:10.1186/s13073-023-01248-6 · Cited by 37 · see citing works
Kleeman, S. O., Thakir, T. M., Demestichas, B., Mourikis, N., Loiero, D., Ferrer, M., Bankier, S., Riazat-Kesh, Y. J. R. A., Lee, H., Chantzichristos, D., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100347 · Cited by 37 · see citing works
Lemmelä, S., Wigmore, E. M., Benner, C., Havulinna, A. S., Ong, R. M., Kempf, T., Wollert, K. C., Blankenberg, S., Zeller, T., Peters, J. E., et al. (2022) · eLife · doi:10.7554/elife.76272 · Cited by 28 · see citing works
Engelmann, J., Zillich, L., Frank, J., Wagner, S., Cetin, M., Herzog, D. P., Müller, M. B., Tadic, A., Foo, J. C., Sirignano, L., et al. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02032-7 · Cited by 29 · see citing works
Archaic Introgression Shaped Human Circadian Traits
Velazquez-Arcelay, K., Colbran, L. L., McArthur, E., Brand, C. M., Rinker, D. C., Siemann, J. K., McMahon, D. G., & Capra, J. A. (2023) · Genome Biology and Evolution · doi:10.1093/gbe/evad203 · Cited by 18 · see citing works
Zheng, X., Wang, Y., & Qiu, X. (2024) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2024.176840 · Cited by 10 · see citing works
Hou, Y., Zhao, J., Xu, W., Chen, L., Yang, J., Wang, Z., & Si, K. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e34089 · Cited by 2 · see citing works
Western, D., Yang, C., Timsina, J., Liu, M., Wang, C., Campbell, M. C., Kotzbauer, P., Perlmutter, J. S., Schindler, S. E., Morris, J. C., et al. (2026) · Science Translational Medicine · doi:10.1126/scitranslmed.adz2016 · Cited by 1 · see citing works
Wang, Z., Wang, Z., Ji, X., Zhao, L., Zheng, K., Yu, W., Zhang, H., Chang, H., & Liu, F. (2026) · Journal of Translational Medicine · doi:10.1186/s12967-026-08301-z
- Authors
- Võsa, U., Claringbould, A., Westra, H.-J., Bonder, M. J., Deelen, P., Zeng, B., Kirsten, H., Saha, A., Kreuzhuber, R., Yazar, S., Brugge, H., Oelen, R., de Vries, D. H., van der Wijst, M. G. P., Kasela, S., Pervjakova, N., Alves, I., Favé, M.-J., Agbessi, M., Christiansen, M. W., Jansen, R., Seppälä, I., Tong, L., Teumer, A., Schramm, K., Hemani, G., Verlouw, J., Yaghootkar, H., Sönmez Flitman, R., Brown, A., Kukushkina, V., Kalnapenkis, A., Rüeger, S., Porcu, E., Kronberg, J., Kettunen, J., Lee, B., Zhang, F., Qi, T., Hernandez, J. A., Arindrarto, W., Beutner, F., BIOS Consortium, ’t Hoen, P. A. C., van Meurs, J., van Dongen, J., van Iterson, M., Swertz, M. A., i2QTL Consortium, Jan Bonder, M., Dmitrieva, J., Elansary, M., Fairfax, B. P., Georges, M., Heijmans, B. T., Hewitt, A. W., Kähönen, M., Kim, Y., Knight, J. C., Kovacs, P., Krohn, K., Li, S., Loeffler, M., Marigorta, U. M., Mei, H., Momozawa, Y., Müller-Nurasyid, M., Nauck, M., Nivard, M. G., Penninx, B. W. J. H., Pritchard, J. K., Raitakari, O. T., Rotzschke, O., Slagboom, E. P., Stehouwer, C. D. A., Stumvoll, M., Sullivan, P., ’t Hoen, P. A. C., Thiery, J., Tönjes, A., van Dongen, J., van Iterson, M., Veldink, J. H., Völker, U., Warmerdam, R., Wijmenga, C., Swertz, M., Andiappan, A., Montgomery, G. W., Ripatti, S., Perola, M., Kutalik, Z., Dermitzakis, E., Bergmann, S., Frayling, T., van Meurs, J., Prokisch, H., Ahsan, H., Pierce, B. L., Lehtimäki, T., Boomsma, D. I., Psaty, B. M., Gharib, S. A., Awadalla, P., Milani, L., Ouwehand, W. H., Downes, K., Stegle, O., Battle, A., Visscher, P. M., Yang, J., Scholz, M., Powell, J., Gibson, G., Esko, T., & Franke, L.
- Affiliations
- University Medical Center Groningen (NL)
- Georgia Institute of Technology (US)
- Leipzig University (DE)
- Johns Hopkins University (US)
- European Bioinformatics Institute (GB)
- Garvan Institute of Medical Research (AU)
- University of Tartu (EE)
- Ontario Institute for Cancer Research (CA)
- University of Washington (US)
- Amsterdam Neuroscience (NL)
- Tampere University (FI)
- Universitätsmedizin Greifswald (DE)
- Helmholtz Munich (DE)
- University of Bristol (GB)
- Erasmus MC (NL)
- Luleå University of Technology (SE)
- University of Geneva (CH)
- Centre Hospitalier Universitaire Vaudois (CH)
- Finnish Institute for Health and Welfare (FI)
- Agency for Science, Technology and Research (SG)
- The University of Queensland (AU)
- Leiden University Medical Center (NL)
- University of Liège (BE)
- Centre for Human Genetics (GB)
- University of Tasmania (AU)
- IFB Adiposity Diseases (DE)
- Ikerbasque (ES)
- Vrije Universiteit Amsterdam (NL)
- Stanford University (US)
- University of Turku (FI)
- Maastricht University Medical Centre (NL)
- Karolinska Institutet (SE)
- Utrecht University (NL)
- Broad Institute (US)
- University of Helsinki (FI)
- SIB Swiss Institute of Bioinformatics (CH)
- University of Exeter (GB)
- University of Chicago (US)
- University of Cambridge (GB)
- Corresponding author
- Võsa, Urmo
- Claringbould, Annique
- Franke, Lude
- ORCID
- Võsa, Urmo
- Claringbould, Annique
- Westra, Harm-Jan
- Deelen, Patrick
- Kirsten, Holger
- Saha, Ashis
- Kreuzhuber, Roman
- Yazar, Seyhan
- Oelen, Roy
- de Vries, Dylan H.
- Kasela, Silva
- Alves, Isabel
- Favé, Marie-Julie
- Agbessi, Mawussé
- Jansen, Rick
- Seppälä, Ilkka
- Teumer, Alexander
- Schramm, Katharina
- Hemani, Gibran
- Verlouw, Joost
- Yaghootkar, Hanieh
- Brown, Andrew
- Kukushkina, Viktorija
- Kalnapenkis, Anette
- Rüeger, Sina
- Porcu, Eleonora
- Kronberg, Jaanika
- Kettunen, Johannes
- Lee, Bernett
- Zhang, Futao
- Qi, Ting
- Hernandez, Jose Alquicira
- Arindrarto, Wibowo
- Dmitrieva, Julia
- Elansary, Mahmoud
- Fairfax, Benjamin P.
- Georges, Michel
- Heijmans, Bastiaan T.
- Hewitt, Alex W.
- Kähönen, Mika
- Knight, Julian C.
- Kovacs, Peter
- Krohn, Knut
- Li, Shuang
- Loeffler, Markus
- Marigorta, Urko M.
- Momozawa, Yukihide
- Müller-Nurasyid, Martina
- Nauck, Matthias
- Nivard, Michel G.
- Penninx, Brenda W. J. H.
- Pritchard, Jonathan K.
- Raitakari, Olli T.
- Slagboom, Eline P.
- Stehouwer, Coen D. A.
- Sullivan, Patrick
- Thiery, Joachim
- Tönjes, Anke
- Veldink, Jan H.
- Völker, Uwe
- Warmerdam, Robert
- Wijmenga, Cisca
- Swertz, Morris
- Andiappan, Anand
- Montgomery, Grant W.
- Ripatti, Samuli
- Perola, Markus
- Dermitzakis, Emmanouil
- Bergmann, Sven
- Frayling, Timothy
- Prokisch, Holger
- Ahsan, Habibul
- Pierce, Brandon L.
- Lehtimäki, Terho
- Boomsma, Dorret I.
- Psaty, Bruce M.
- Gharib, Sina A.
- Awadalla, Philip
- Milani, Lili
- Ouwehand, Willem H.
- Downes, Kate
- Stegle, Oliver
- Battle, Alexis
- Visscher, Peter M.
- Yang, Jian
- Scholz, Markus
- Powell, Joseph
- Gibson, Greg
- Esko, Tõnu
- Franke, Lude
- Venue
- Nature Genetics
- Published
- 2021-09
- Volume
- 53
- Issue
- 9
- Pages
- 1300-1310
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC8432599
- OpenAlex
- W3197364483
- Cited by
- 2,607
- References
- 115
- Citations by year
- 2026: 508 · 2025: 687 · 2024: 543 · 2023: 295 · 2022: 230 · 2021: 181 · 2020: 98 · 2019: 62 · 2018: 1
- FWCI
- 186.31
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature Genetics (publishedVersion, other-oa)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, other-oa)
- Discovery Research Portal (University of Dundee) (publishedVersion, other-oa)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, other-oa)
- VU Research Portal (publishedVersion, other-oa)
- Pure Amsterdam UMC (acceptedVersion, cc-by)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (acceptedVersion, other-oa)
- PubMed Central (acceptedVersion)
- SERVAL (Université de Lausanne) (acceptedVersion, other-oa)
- IRIS (submittedVersion)
- UTAS Research Repository (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion, cc-by)
- Brunel University Research Archive (BURA) (Brunel University London) (submittedVersion)
- Figshare (submittedVersion)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
- ORBi (University of Liège) (submittedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (submittedVersion, other-oa)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Research Publications (Maastricht University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- WOS
- Funders
- National Science Foundation (HHSN261200800001E, 310030)
- University of Miami (DA006227)
- NHS Blood and Transplant
- Wellcome Trust (217065/Z/19/Z, 102215, 092731, 201488/Z/16/Z, WT097835MF)
- Broad Institute (HHSN268201000029C)
- International Society on Thrombosis and Haemostasis
- Leidos (HHSN261200800001E)
- Stichting de Drie Lichten
- National Institute for Health and Care Research (MC_UU_12013/1, WT097835MF)
- British Heart Foundation
- Diabetes UK (WT097835MF, 733100, 17/0005594)
- University of Exeter
- European Commission (184.021.007, PRG1291, 2014‐2020, 2020 ‘, 531003014, 184.033.111, 230374, HORIZON2020, H2020, 733100, 810645, 847776, 772376, 692145)
- Rosetrees Trust
- University of Bristol (MC_UU_12013/1, 092731, MC_UU_12013)
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (102215, 230374, 130342, 152724, 310030)
- Koninklijke Nederlandse Akademie van Wetenschappen (PAH/6635)
- ZonMw (849200011, 56-464-14192, 184.021.007, 184.033.111, 917.14.374, 531003014)
- Eesti Teadusagentuur (IUT20-60, MOBTP108, PRG1291, 2014-2020, IUT24-6, PUT1660, IUT2-4)
- Academy of Finland (307247, 312062, 297338 and 307247, 297338)
- Bundesministerium für Bildung und Forschung (01ZX1906B)
- Fonds De La Recherche Scientifique - FNRS (30770923)
- Fonds Wetenschappelijk Onderzoek (30770923)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (184021007, Veni 192.029, 191G.030, VI.Veni.191G.030, 184.033.111, 192.029, 56‐464‐14192, 230374, VI.Veni.192.029, NWO-Veni 192.029, 917.14.374, 849200011, 30770923, 14192, 184.021.007 and 184.033.111, 637640)
- Jacobs Foundation
- Novo Nordisk
- Universitair Medisch Centrum Groningen
- Universität Leipzig
- Novo Nordisk Fonden (NNF17OC0026062, grant number NNF17OC0026062)
- Freistaat Sachsen
- National Institutes of Health (10XS170, PAH/6635, 184.021.007, UL1TR000124, #HHSN261200800001E, HHSN268201000029C, 10XS171, 092731, 10ST1035, H2020, DK-063491, HL073410)
- Horizon 2020 Framework Programme (810645, 772376, 692145, 733100, # 847776)
- Medical Research Council (102215, MC_UU_12013, MCUU12013/1, 297338, MC_PC_15018, 092731, 307247, MC_PC_19009, WT097835MF)
- European Regional Development Fund (2014-2020’, H2020, MOBTP108, PRG1291)
- Research England
- National Institute on Aging (P30AG073104)
- National Heart, Lung, and Blood Institute (DK-063491, R01HL085251, HL 073410, HHSN268201000029C, HL085251, HHSN261200800001E, R01HL105756)
- National Institute of Mental Health (R01MH101814, PUT1660, HHSN261200800001E, R01MH109905)
- National Human Genome Research Institute (HHSN261200800001E, R01HG008150)
- National Cancer Institute (R01CA107431)
- National Institute of General Medical Sciences (R01GM108711)
- National Institute of Environmental Health Sciences (R21ES024834, R35ES028379, R01ES023834, R01ES020506)
- National Center for Advancing Translational Sciences (DK063491, HHSN261200800001E)
- Common Fund
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- expression quantitative trait loci, cis-eQTL, trans-eQTL, blood gene expression, polygenic risk score, transcription factor regulation, single-cell RNA sequencing, complex phenotypes
- MeSH terms
- Blood Proteins, Gene Expression Regulation, Humans, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study, Transcriptome
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.
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