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A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis


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Madireddy, L, Patsopoulos, NA, Cotsapas, C, Bos, SD, Beecham, A, McCauley, J, Kim, K, Jia, X, Santaniello, A, Caillier, SJ, Andlauer, TFM, Barcellos, LF, Berge, T, Bernardinelli, L, Martinelli-Boneschi, F, Booth, DR, Briggs, F, Celius, EG, Comabella, M, Comi, G, Cree, BAC, D'Alfonso, S, Dedham, K, Duquette, P, Efthimios, D, Esposito, F, Fontaine, B, Gasperi, C, Goris, A, Dubois, B, Gourraud, PA, Hadjigeorgiou, G, Haines, J, Hawkins, C, Hemmer, B, Hintzen, R, Horakova, D, Isobe, N, Kalra, S, Kira, Ji, Khalil, M, Kockum, I, Lill, CM, Lincoln, MR, Luessi, F, Martin, R, Oturai, A, Palotie, A, Pericak-Vance, MA, Henry, R, Saarela, J, Ivinson, A, Olsson, T, Taylor, BV, Stewart, GJ, Harbo, HF, Compston, A, Hauser, SL, Hafler, DA, Zipp, F, De Jager, P, Sawcer, S, Oksenberg, JR and Baranzini, SE 2019 , 'A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis' , Nature Communications, vol. 10, no. 1 , pp. 1-12 , doi: 10.1038/s41467-019-09773-y.

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Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations has proven extremely difficult. Even determining which cell types and which particular gene(s) are relevant continues to be a challenge. Here, we conduct a cell-specific pathway analysis of the latest GWAS in multiple sclerosis (MS), which had analyzed a total of 47,351 cases and 68,284 healthy controls and found more than 200 non-MHC genome-wide associations. Our analysis identifies pan immune cell as well as cell-specific susceptibility genes in T cells, B cells and monocytes. Finally, genotype-level data from 2,370 patients and 412 controls is used to compute intra-individual and cell-specific susceptibility pathways that offer a biological interpretation of the individual genetic risk to MS. This approach could be adopted in any other complex trait for which genome-wide data is available.

Item Type: Article
Authors/Creators:Madireddy, L and Patsopoulos, NA and Cotsapas, C and Bos, SD and Beecham, A and McCauley, J and Kim, K and Jia, X and Santaniello, A and Caillier, SJ and Andlauer, TFM and Barcellos, LF and Berge, T and Bernardinelli, L and Martinelli-Boneschi, F and Booth, DR and Briggs, F and Celius, EG and Comabella, M and Comi, G and Cree, BAC and D'Alfonso, S and Dedham, K and Duquette, P and Efthimios, D and Esposito, F and Fontaine, B and Gasperi, C and Goris, A and Dubois, B and Gourraud, PA and Hadjigeorgiou, G and Haines, J and Hawkins, C and Hemmer, B and Hintzen, R and Horakova, D and Isobe, N and Kalra, S and Kira, Ji and Khalil, M and Kockum, I and Lill, CM and Lincoln, MR and Luessi, F and Martin, R and Oturai, A and Palotie, A and Pericak-Vance, MA and Henry, R and Saarela, J and Ivinson, A and Olsson, T and Taylor, BV and Stewart, GJ and Harbo, HF and Compston, A and Hauser, SL and Hafler, DA and Zipp, F and De Jager, P and Sawcer, S and Oksenberg, JR and Baranzini, SE
Journal or Publication Title: Nature Communications
Publisher: Nature Publishing Group
ISSN: 2041-1723
DOI / ID Number: 10.1038/s41467-019-09773-y
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Copyright 2019 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

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