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. 2014 May 2;344(6183):519-23.
doi: 10.1126/science.1249547.

Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes

Towfique Raj  1 , Katie Rothamel, Sara Mostafavi, Chun Ye, Mark N Lee, Joseph M Replogle, Ting Feng, Michelle Lee, Natasha Asinovski, Irene Frohlich, Selina Imboywa, Alina Von Korff, Yukinori Okada, Nikolaos A Patsopoulos, Scott Davis, Cristin McCabe, Hyun-il Paik, Gyan P Srivastava, Soumya Raychaudhuri, David A Hafler, Daphne Koller, Aviv Regev, Nir Hacohen, Diane Mathis, Christophe Benoist, Barbara E Stranger, Philip L De Jager
Affiliations

Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes

Towfique Raj et al. Science. .

Abstract

To extend our understanding of the genetic basis of human immune function and dysfunction, we performed an expression quantitative trait locus (eQTL) study of purified CD4(+) T cells and monocytes, representing adaptive and innate immunity, in a multi-ethnic cohort of 461 healthy individuals. Context-specific cis- and trans-eQTLs were identified, and cross-population mapping allowed, in some cases, putative functional assignment of candidate causal regulatory variants for disease-associated loci. We note an over-representation of T cell-specific eQTLs among susceptibility alleles for autoimmune diseases and of monocyte-specific eQTLs among Alzheimer's and Parkinson's disease variants. This polarization implicates specific immune cell types in these diseases and points to the need to identify the cell-autonomous effects of disease susceptibility variants.

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Figures

Fig. 1
Fig. 1. Transcriptome variation among human populations
Heat map of genes that are differentially expressed (VST > 0.2) in monocytes (A) and T cells (B). (C) Example of a cis-eQTL shared across populations. (D) Examples of population-specific cis-eQTLs. (E) Regional association plots of an EU-specific cis-eQTL in the TARSL2 locus.
Fig. 2
Fig. 2. Comparison of meta-analysis results from each cell type
(A) Manhattan plots of the most significant cis-eQTL per gene in monocytes (top) and T cells (bottom). The highlighted genes are representative of genes that (i) are shared, (ii) are cell-specific, or (iii) overlap with a disease association. (B) Inference of the proportion of cis-eQTL sharing between the two cell types using a Bayesian hierarchical model. (C) Expression-level fold-change for the most significant cis-eQTLs in T cells and monocytes. (D) Spearman’s ρ (direction of allelic effect on gene expression) for the most significant cis-eQTLs shared by the two cell types. We highlight genes that have discrepant directions of effect. (E) Example of a context-specific cis-eQTL in a rheumatoid arthritis locus. Mbp, megabase pairs.
Fig. 3
Fig. 3. Polarization of cis-regulatory effects for disease-associated variants
(A) (Left) For each evaluated trait, we report, in parentheses, the number of trait-associated (GWAS) SNPs with cis-eQTL effects over the total number of SNPs, and the number of genes influenced by one or more of these SNPs. For each trait, we present the distribution of the proportion of cell specificity (estimated using a Bayesian hierarchical model) observed for each of 1000 random samplings of matched SNP sets. The proportion of cell-specific cis-eQTL effects observed for a given trait is shown over this distribution using an orange line for monocytes and a green line for T cells. (Right) We report the proportion of cis-eQTLs that are monocyte-specific (orange), shared (blue), and T cell–specific (green). (B) Four diseases with significant polarization (FDR < 0.05) in the distribution of cis-eQTLs: Multiple sclerosis and rheumatoid arthritis are enriched in T cell effects (green), whereas Alzheimer’s and Parkinson’s diseases are enriched in monocyte effects (orange).
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