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. 2012 Aug 23;488(7412):508-511.
doi: 10.1038/nature11307.

TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis

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TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis

Adam P Gregory et al. Nature. .

Abstract

Although there has been much success in identifying genetic variants associated with common diseases using genome-wide association studies (GWAS), it has been difficult to demonstrate which variants are causal and what role they have in disease. Moreover, the modest contribution that these variants make to disease risk has raised questions regarding their medical relevance. Here we have investigated a single nucleotide polymorphism (SNP) in the TNFRSF1A gene, that encodes tumour necrosis factor receptor 1 (TNFR1), which was discovered through GWAS to be associated with multiple sclerosis (MS), but not with other autoimmune conditions such as rheumatoid arthritis, psoriasis and Crohn’s disease. By analysing MS GWAS data in conjunction with the 1000 Genomes Project data we provide genetic evidence that strongly implicates this SNP, rs1800693, as the causal variant in the TNFRSF1A region. We further substantiate this through functional studies showing that the MS risk allele directs expression of a novel, soluble form of TNFR1 that can block TNF. Importantly, TNF-blocking drugs can promote onset or exacerbation of MS, but they have proven highly efficacious in the treatment of autoimmune diseases for which there is no association with rs1800693. This indicates that the clinical experience with these drugs parallels the disease association of rs1800693, and that the MS-associated TNFR1 variant mimics the effect of TNF-blocking drugs. Hence, our study demonstrates that clinical practice can be informed by comparing GWAS across common autoimmune diseases and by investigating the functional consequences of the disease-associated genetic variation.

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Figures

Figure 1
Figure 1
MS-associated TNFRSF1A region and rs1800693-dependent splicing. (a) MS association signal plot for the UK cohort. Top: primary association with strongest signal at rs1800693 (blue: typed variants; light blue: variants imputed from 1000 Genomes Project). Bottom: signal conditional on rs1800693 (red: typed; orange: imputed). Inset: linkage disequilibrium to rs1800693 in 1000 Genomes Project (black: typed; untyped - red: r2≥0.05; blue: r2<0.05). (b) Rs1800693-dependent TNFR1 splicing using a minigene system. SD/SA: vector splice donor/acceptor site. (c) Relative expression of transcripts lacking exon 6 in primary human cells. Data = mean ±SEM; for A/A, A/G, G/G, n = 15, 28 and 13 donors.
Figure 2
Figure 2
Δ6-TNFR1 localization and analysis of isoform association. (a) TNFR1 subcellular localization. (b) FL/Δ6-TNFR1 localization analysis. Data = mean ±SEM; FL-TNFR1, n = 20, Δ6-TNFR1, n = 27 cells; scale bar: 1 μm. (c) FL/Δ6-TNFR1 association analysis. HEK 293T double-positive cells expressing ECFP/EYFP-tagged TNFR1 isoforms were analyzed for FRET to assess isoform association. FL-TNFR1-ECFP + FAS180-EYFP co-transfection was used for background signal definition with non-interacting proteins. Percentage of FRET-positive events (indicating protein association) is shown. (d) HEK 293T cells expressing HA-tagged FL- or Δ6-TNFR1-EYFP were analyzed for cell surface and total protein expression. ECFP/EYFP: enhanced cyan/yellow fluorescent protein.
Figure 3
Figure 3
Δ6-TNFR1 solubility and TNF binding and neutralization. (a) Soluble TNFR1 detected by anti-HA ELISA using TNFR1-transfected HEK 293T supernatants. AFU: absolute fluorescence units; NT: non-transfected. (b) TNF-FLAG pulldown using TNFR1-Fc proteins. Inset: negative control for TNF binding (DR5.CRD1-Fc). (c) Surface plasmon resonance analysis of TNFR1-Fc protein TNF binding. Sensorgrams show resonance units (RU) over time and model fit for dissociation constant (Kd) derivation. (d) TNF neutralization by TNFR1-Fc proteins using HEK-Blue™ TNFα SEAP reporter cells. Dotted lines = IC50 for TNFR1-Fc and Δ6-TNFR1-Fc (158 and 3,035 ng/ml, respectively). Data = mean ±SEM; n = 3.

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