Co-regulatory networks of human serum proteins link genetics to disease
Open accessAbstract
The blood proteome in disease: Understanding the function of human blood serum proteins in disease has been limited by difficulties in monitoring their production, accumulation, and distribution. Emilsson et al. investigated human serum proteins of more than 5000 Icelanders over the age of 65. The composition of blood serum includes a complex regulatory network of proteins that are globally coordinated across most or all tissues. The authors identified modules and functional groups associated with disease and health outcomes and were able to link genetic variants to complex diseases. Science , this issue p. 769
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The pleiotropic loci included well-established, previously identified pleiotropic loci such as MHC, ABO, ZFPM2, ARHGEF3, GCKR, SERPINA1, SH2B3 and ASGR1.
“These included well-established, previously identified [17][18][19][20] pleiotropic loci such as MHC, ABO, ZFPM2, ARHGEF3, GCKR, SERPINA1, SH2B3 and ASGR1”
From Plasma proteomic associations with genetics and health in the UK Biobank (2023) · cites this paper as [17]
The section “Genetic variants influence serum protein levels” explicitly describes pleiotropy at ABO as well established. Our copy does not identify MHC, ZFPM2, ARHGEF3, GCKR, SERPINA1, SH2B3, or ASGR1 as previously identified pleiotropic loci, so it supports only part of the list. (LLM, conf=0.86)
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Cites
Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135 · see citing works
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950 · see citing works
Error and attack tolerance of complex networks
Albert, R., Jeong, H., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35019019 · Cited by 7,534 · see citing works
Network medicine: a network-based approach to human disease
Barabási, A.-L., Gulbahce, N., & Loscalzo, J. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2918 · Cited by 5,034 · see citing works
Rejuvenation of aged progenitor cells by exposure to a young systemic environment
Conboy, I. M., Conboy, M. J., Wagers, A. J., Girma, E. R., Weissman, I. L., & Rando, T. A. (2005) · Nature · doi:10.1038/nature03260 · Cited by 2,287 · see citing works
Diagnosis and classification of diabetes mellitus
American Diabetes Association (2013) · Diabetes Care · doi:10.2337/dc13-s067 · Cited by 2,245 · see citing works
Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery
Gold, L., Ayers, D., Bertino, J., Bock, C., Bock, A., Brody, E. N., Carter, J., Dalby, A. B., Eaton, B. E., Fitzwater, T., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0015004 · Cited by 1,754 · see citing works
Is My Network Module Preserved and Reproducible?
Langfelder, P., Luo, R., Oldham, M. C., & Horvath, S. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001057 · Cited by 1,012 · see citing works
Conservation and evolution of gene coexpression networks in human and chimpanzee brains
Oldham, M. C., Horvath, S., & Geschwind, D. H. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605938103 · Cited by 566 · see citing works
AGEMAP: A Gene Expression Database for Aging in Mice
Zahn, J. M., Poosala, S., Owen, A. B., Ingram, D. K., Lustig, A., Carter, A., Weeraratna, A. T., Taub, D. D., Gorospe, M., Mazan-Mamczarz, K., et al. (2007) · PLoS Genetics · doi:10.1371/journal.pgen.0030201 · Cited by 431 · see citing works
Gaiteri, C., Ding, Y., French, B., Tseng, G. C., & Sibille, E. (2014) · Genes, Brain and Behavior · doi:10.1111/gbb.12106 · Cited by 289 · see citing works
Identification of genetic variants influencing the human plasma proteome
Johansson, Å., Enroth, S., Palmblad, M., Deelder, A. M., Bergquist, J., & Gyllensten, U. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1217238110 · Cited by 82 · see citing works
Flagged first, then by citations
Research works printed but not linked: 30
- [1]Schwenk JM, J. Proteome Res 16, 4299– 4310 (2017). 28938075 PMC5864247
- [2]Uhlén M, Science 347, 1260419(2015). 25613900
- [3]Stastna M, Van Eyk JE, Proteomics 12, 722– 735 (2012). 22247067 PMC3517109
- [4]Conboy IM, Nature 433, 760– 764 (2005). 15716955
- [5]Villeda SA, Nature 477, 90– 94 (2011). 21886162 PMC3170097
- [6]Schadt EE, Nature 461, 218– 223 (2009). 19741703
- [7]Zhang B, Cell 153, 707– 720 (2013). 23622250 PMC3677161
- [8]Emilsson V, Nature 452, 423– 428 (2008). 18344981
- [9]Chen Y, Nature 452, 429– 435 (2008). v 18344982 PMC2841398
- [10]Davies DR, Proc. Natl. Acad. Sci. U.S.A 109, 19971– 19976 (2012). 23139410 PMC3523867
- [11]Gold L, PLOS ONE 5, e15004(2010). 21165148 PMC3000457
- [12]Harris TB, Am. J. Epidemiol 165, 1076– 1087 (2007). 17351290 PMC2723948
- [13]Barabási AL, Albert R, Science 286, 509– 512 (1999). 10521342
- [14]Zhang B, Horvath S, Stat. Appl. Genet. Mol. Biol 4, e17(2005). 16646834
- [15]Langfelder P, Luo R, Oldham MC, Horvath S, PLOS Comput. Biol 7, e1001057(2011). 21283776 PMC3024255
- [16]Shu L, PLOS Genet. 13, e1007040(2017). 28957322 PMC5634657
- [17]Jeong H, Mason SP, Barabási AL, Oltvai ZN, Nature 411, 41– 42 (2001). 11333967
- [18]Barabási AL, Gulbahce N, Loscalzo J, Nat. Rev. Genet 12, 56– 68 (2011). 21164525 PMC3140052
- [19]Muñoz M, Nat. Genet 48, 980– 983 (2016). 27428752 PMC5989924
- [20]Staley JR, Bioinformatics 32, 3207– 3209 (2016). 27318201 PMC5048068
- [21]Mähler N, PLOS Genet. 13, e1006402(2017). 28406900 PMC5407845
- [22]Pickrell JK, Nat. Genet 48, 709– 717 (2016). 27182965 PMC5207801
- [23]Franchini M, Lippi G, BMC Med 13, 7(2015). 25592962 PMC4295232
- [24]Franchini M, Capra F, Targher G, Montagnana M, Lippi G, Thromb. J 5, 14(2007). 17894864 PMC2042969
- [25]Boyle EA, Li YI, Pritchard JK, Cell 169, 1177– 1186 (2017). 28622505 PMC5536862
- [26]Alfego D, Rodeck U, Kriete A, PLOS ONE 13, e0190457(2018). 29293662 PMC5749797
- [27]Yang J, Sci. Rep 5, 15145(2015). 26477495 PMC4609956
- [28]Zahn JM, PLOS Genet. 3, e201(2007). 18081424 PMC2098796
- [29]Langfelder P, Zhang B, Horvath S, Bioinformatics 24, 719– 720 (2008). 18024473
- [30]Csardi G, Nepusz T, Complex Syst 1695, 1(2006).
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- Authors
- Emilsson, V., Ilkov, M., Lamb, J. R., Finkel, N., Gudmundsson, E. F., Pitts, R., Hoover, H., Gudmundsdottir, V., Horman, S. R., Aspelund, T., Shu, L., Trifonov, V., Sigurdsson, S., Manolescu, A., Zhu, J., Olafsson, Ö., Jakobsdottir, J., Lesley, S. A., To, J., Zhang, J., Harris, T. B., Launer, L. J., Zhang, B., Eiriksdottir, G., Yang, X., Orth, A. P., Jennings, L. L., & Gudnason, V.
- Affiliations
- University of Iceland (IS)
- Icelandic Heart Association (IS)
- Genomics Institute of the Novartis Research Foundation (US)
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA 02139, USA.
- Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Iceland.
- University of California, Los Angeles (US)
- Reykjavík University (IS)
- Icahn School of Medicine at Mount Sinai (US)
- National Institutes of Health (US)
- Corresponding author
- Emilsson, Valur
- Ilkov, Marjan
- Lamb, John R.
- Jennings, Lori L.
- Gudnason, Vilmundur
- ORCID
- Emilsson, Valur
- Ilkov, Marjan
- Lamb, John R.
- Finkel, Nancy
- Gudmundsson, Elias F.
- Pitts, Rebecca
- Hoover, Heather
- Gudmundsdottir, Valborg
- Horman, Shane R.
- Aspelund, Thor
- Shu, Le
- Trifonov, Vladimir
- Sigurdsson, Sigurdur
- Manolescu, Andrei
- Zhu, Jun
- Lesley, Scott A.
- To, Jeremy
- Zhang, Jia
- Harris, Tamara B.
- Launer, Lenore J.
- Zhang, Bin
- Yang, Xia
- Orth, Anthony P.
- Jennings, Lori L.
- Gudnason, Vilmundur
- Venue
- Science
- Published
- 2018-08-24
- Volume
- 361
- Issue
- 6404
- Pages
- 769-773
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC6190714
- OpenAlex
- W2885870007
- Cited by
- 680
- References
- 12
- Citations by year
- 2026: 72 · 2025: 121 · 2024: 114 · 2023: 77 · 2022: 74 · 2021: 98 · 2020: 83 · 2019: 35 · 2018: 6
- FWCI
- 19.82
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (DK104363)
- National Institute of Neurological Disorders and Stroke (NS103088)
- Fondation Leducq
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Keywords
- serum proteome, protein modules, aging, cardiovascular disease, metabolic disorders, overall survival, genetic variants, cis-acting regulation, trans-acting regulation, extracellular proteins, Icelanders, age-related diseases
- MeSH terms
- Blood Proteins, Cardiovascular Diseases, Humans, Iceland, Metabolic Diseases, Genetic Variation, Genetic Predisposition to Disease, Proteome, Proteomics, Aptamers, Nucleotide, Metabolic Networks and Pathways
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