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

Lohith Madireddy ,P.a Gourraud ,Matthew R Lincoln ,Christiane Gasperi ,Rogier Q Hintzen ,Bv Taylor ,Jacob L Mccauley ,Michael Khalil ,Ingrid Kockum ,Kicheol Kim ,Tone Berge ,S.d Bos ,Manuel Comabella ,Bernhard Hemmer ,Ashley Beecham ,Christina M Lill ,Pl De Jager ,Janna Saarela ,Clive Hawkins ,Chris Cotsapas ,Gj Stewart ,Booth ,Aarno Palotie ,Farren Briggs ,Xiaoming Jia ,Dana Horáková ,Oksenberg ,Sl Hauser ,M A Pericak‐Vance ,Sandra D’alfonso ,Felix Luessi ,Luisa Bernardinelli ,Bertrand Fontaine ,Ryan A Henry ,E G Celius ,Bruce A.c Cree ,Noriko Isobe ,Giancarlo Comi ,G Hadjigeorgiou ,S J Sawcer ,Filippo Martinelli Boneschi ,Hafler Da ,Rebeca San Martin ,Tomas Olsson ,Alastair Compston ,J Kira ,Federica Esposito ,Haines Jl ,Frauke Zipp ,An Goris ,D Efthimios ,Pierre Duquette ,Bénédicte Dubois ,Katrina Dedham ,Adrian J Ivinson ,Barcellos Lf ,Sj Caillier ,Seema Kalra ,Harbo Hf ,Na Patsopoulos ,Till F M Andlauer ,Annette Bang Oturai ,Adam Santaniello ,Sergio E Baranzini

doi:10.1038/s41467-019-09773-y

Lohith Madireddy , P.a Gourraud + Show 62 more

Open Access

https://doi.org/10.1038/s41467-019-09773-y

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Journal: Nature Communications	Publication Date: May 20, 2019
Citations: 66	License type: open-access

Abstract

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.

Highlights

With the completion of efforts like the Encyclopedia of DNA elements (ENCODE) and the Roadmap Epigenomics Project (REP) a wealth of information on regulatory elements is available from hundreds of cell types and dozens of different tissues[15,16], raising the possibility of applying network-based approaches in a cell-specific manner
We included all genome-wide (GW) significant single nucleotide polymorphisms (SNPs) together with their proxies selected at differing LD thresholds (r2 > 0.5 was used for the main analysis)
Each gene within a given locus received a score (PRE) that does not depend solely on the closest SNP, but that is equal to the weighted sum of all regulatory features potentially affected by variation at nearby associated SNPs (See Methods)

Summary

Results

Predicted regulatory effects (PRE) of MS-associated variants. We integrated genetic association signals from the latest genetic analysis of MS17 with cell specific information on regulatory elements available from the ENCODE and Epigenomics. Two GW significant regions (10 and 21) are shown in larger detail as representative examples (Fig. 1c) Because it integrates actual regulatory information for each associated SNP and those in LD, this approach can prioritize the most likely genes affected by the same association signals in each cell type analyzed (Supplementary Data 29). TNFRSF14 (a member of the TNF receptor superfamily) encodes a protein involved in signal transduction pathways that activate both inflammatory and inhibitory T-cell immune responses due to its particular ability to interact with multiple ligands in distinct configurations[18] Another example is provided by region 21, defined by the lead SNP rs6032662 mapping to chromosome 20.

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Discussion

Methods