Genetic variants regulating immune cell levels in health and disease

Abstract

The complex network of specialized cells and molecules in the immune system has evolved to defend against pathogens, but inadvertent immune system attacks on "self" result in autoimmune disease. Both genetic regulation of immune cell levels and their relationships with autoimmunity are largely undetermined. Here, we report genetic contributions to quantitative levels of 95 cell types encompassing 272 immune traits, in a cohort of 1,629 individuals from four clustered Sardinian villages. We first estimated trait heritability, showing that it can be substantial, accounting for up to 87% of the variance (mean 41%). Next, by assessing ∼8.2 million variants that we identified and confirmed in an extended set of 2,870 individuals, 23 independent variants at 13 loci associated with at least one trait. Notably, variants at three loci (HLA, IL2RA, and SH2B3/ATXN2) overlap with known autoimmune disease associations. These results connect specific cellular phenotypes to specific genetic variants, helping to explicate their involvement in disease.

Figure 1. Studied Leukocyte Subpopulations

Color-coded diagram of the cell types analyzed by flow cytometry with arrows depicting the hierarchical levels of separation of circulating cell populations (leukocytes) and constituent subsets of the two main arms, innate and adaptive, of the immune system. Innate cell types, which provide prompt but generic responses to aggressors, include granulocytes (yellow), monocytes (pale blue), and dendritic cells (red). Adaptive cell types, which provide highly specific responses to microbial targets and may maintain a “memory” that enables a faster and greater response to previously encountered pathogens, include B cells (magenta) and T cells (green). The natural killer cells (orange) share features of both arms of the immune system. The name and, when relevant, the identifying marker are indicated beside each population. Cells inside a light-blue rectangle were phenotypically characterized with the antigen pointed to by the adjacent light-blue arrow; for example, the six CD3+ subsets (CD4− CD8−, CD4+, CD4+ CD8 dim, CD4+ CD8br, CD8br, and CD8 dim) are shown within a blue rectangle and were further subdivided into naive, central memory, effector memory, and terminally differentiated cells. The red rectangle indicates that the included cell populations have been jointly analyzed for CD39, the marker indicated by the red arrow. For simplicity, 45 of the 95 analyzed cell types, described in the full text, are shown. See also Figure S1 and Table S1.

Figure 2. Phenotypic and Genetic Clustering

Heatmap of phenotypic (lower-right triangle) and genetic (upper-left triangle) correlations for cell counts and CD4:CD8 and T:B cell ratios. Traits with a phenotypic correlation ≥0.99 were excluded (Extended Experimental Procedures). Genetic and phenotypic triangles follow the same trait order, dictated by the clustering of phenotypic correlations, and the dendrogram at the right reflects the clustering. Traits connected by short branches share stronger phenotypic correlation, whereas traits that join near the root of the tree are weakly correlated. Color gradations indicate correlation strength, with red indicating direct correlation (from 0 to +1) and blue inverse correlation (from 0 to − 1). See also Figure S2 and Table S2 for further details.

Figure 3. Manhattan Plot of Best p Values

For each SNP, the best p value observed among all assessed traits is plotted on a –log10 scale (y axis), according to its genomic coordinates (x axis). SNPs are colored in blue if the corresponding best p value was directly genotyped with ImmunoChip (IC) or Cardio-MetaboChip (MC) and in gray if imputed from genomic sequencing of Sardinians. The dotted horizontal line indicates the threshold for declaring a locus genome wide to be significant (5.26 × 10⁻¹⁰). The best candidate gene is indicated near the peak. Loci below the significance threshold and previously described are marked with an asterisk.

Figure 4. Regional Plot and Box Plot for the Top Signal in ENTPD1

(A and B) Representation of the association in the genomic context (A) and in the biological context (B) for the most strongly associated variant at the ENTPD1 gene. (A) Representation of the association strength (y axis shows the–log10 p value) versus the genomic positions (on hg19/GRCh37 genomic build) around the most significant SNP, which is indicated with a purple circle. Other SNPs in the region are color coded to reflect their LD with the top SNP, as in the left inset (taken from pairwise r² values calculated on Sardinian haplotypes), whereas symbols reflecting genomic functional annotation are indicated in the right inset. Genes and the position of exons, as well as the direction of transcription, are noted in lower boxes. This plot was drawn using the standalone version of the LocusZoom package (Pruim et al., 2010). (B) The distribution of the immunophenotypic levels within each genotype class considering the normalized trait adjusted for age and gender in relation to the 1,629 initial samples, showing the additive effect that was statistically observed.See also Data S1.

Figure 5. Proportion of Heritability Explained

The bar plots show the heritability of each trait (represented by a bar) for which genetic association was detected. The proportion of heritability explained by the detected loci is indicated in dark blue, and the proportion of heritability that remains to be explained is shown in light blue. Bars are grouped in their corresponding biological category, as specified in Table S1B. See also Tables S2A and S5.