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Cited by 894Genetic Associations and EpidemiologyGenomics and Chromatin DynamicsGenetic Mapping and Diversity in Plants and Animals

Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression

Open access
Schmiedel, Benjamin J., Singh, Divya, Madrigal, Ariel, Valdovino-Gonzalez, Alan G., White, Brandie M., Zapardiel-Gonzalo, Jose, Ha, Brendan, Altay, Gokmen +7 more·2018·Cell
DOI 10.1016/j.cell.2018.10.022PMC PMC6289654
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Abstract

SUMMARY While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE (Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics) project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis (http://dice-database.org).

AI snapshot

Written from the paper’s full text.

TL;DR

The DICE project mapped transcriptomes and cis-eQTLs across 13 human immune cell types and activation conditions from 91 healthy subjects, identifying 12,254 eGenes with highly cell-specific genetic effects. It also found extensive sex-biased immune gene expression and linked GWAS disease variants to specific immune cell types.

Key findings

  • cis-eQTLs were identified for 12,254 unique genes, representing 61% of expressed protein-coding genes and 49% of lncRNAs; 41% showed a strong cis-association with genotype in only a single cell type. More than 2,000 eGenes were found per common cell type, and CD4+ memory/TREG subsets yielded over 7,800 eGenes, of which >2,500 were unique to those subsets.
  • About 19% of eGenes per immune cell type overlapped GWAS SNPs (2,297 unique GWAS eGenes; 599–987 eGenes/cell type), and for about 36% of these eGenes associations were observed in only one or two cell types. Examples included IRAK3 in naïve B cells (rs1732886, adj. P = 6.82 × 10−17) and NAB1 in NK cells (rs13028201, adj. P = 1.41 × 10−14).
  • Sex-biased expression was found for 1,875 unique transcripts, including 1,553 protein-coding transcripts and 196 lncRNAs; 93% were autosomal and >72% showed sex-biased expression in only a single immune cell type. FAM13A was female-biased in naïve CD4+ T cells, with homozygous CC versus TT females showing 3.5-fold greater FAM13A transcripts compared to <1.5-fold in males.
  • Cell-specific transcriptional signatures included 4,602 highly cell-specific transcripts, and differential expression among CD4+ T cell subsets revealed over 700 genes enriched in one specific subset.

Methods

  • The study analyzed 13 immune cell types plus activated naïve CD4+ and CD8+ T cells from 106 leukapheresis samples provided by 91 healthy subjects (54 males, 37 females; median age 27 years, range 18–61).
  • RNA-seq was performed on FACS-sorted cells, with genotyping and imputation using the 1,000 Genomes Project phase 3 reference; cis-eQTLs were tested within ±1 Mb of the transcription start site using Matrix eQTL with thresholds FDR < 0.05, raw P < 0.0001, and TPM > 1.0.
  • Differential expression used DESeq2; GWAS overlap used PheGenI data with 14,321 lead GWAS SNPs and 846 traits; functional validation used siRNA knockdowns in primary immune cells.

Limitations

  • The paper states that next phases of DICE will add additional rare immune cell types and cell-specific epigenomic profiles, and that several lncRNA and disease-gene links require further study and functional confirmation.
  • The cohort was limited to 91 healthy volunteers from the San Diego area with a median age of 27 years, so generalizability to older, diseased, or more ancestrally diverse populations is not established by this dataset.
  • The eQTL analysis did not cover the pseudoautosomal regions of chr X or chr Y (stated in the paper), and it focused on cis windows of ±1 Mb around the TSS rather than trans effects.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.cell.2018.10.022

Cites

68 of 68 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 4 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    lncRNAs as a class were expressed at lower levels than protein-coding transcripts.

    “which as a class were expressed at lower levels compared to protein-coding transcripts”
    Quote in the paperNot a substantial claim
  • Findingown data

    Across all immune cell types and conditions studied, the DICE project identified cis-eQTLs for 12,254 unique genes.

    “Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes”
    Quote in the paperSubstantial claim
  • Findingown data

    RNA-Seq detected similar numbers of transcripts, ranging from 14,500 to 17,000, about 39% of annotated transcripts, across all cell types and activation conditions.

    “RNA-Seq analysis showed that similar numbers of transcripts (ranging from 14,500 to 17,000, ~39% of all annotated transcripts) were detected (>1.0 transcripts per million, TPM) across all cell types and activation conditions”
    Quote in the paperNot a substantial claim
  • Findingown data

    Biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner.

    “We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner.”
    Quote in the paperSubstantial claim
  • Findingown data

    The eGenes include 49% of all lncRNAs expressed in the studied immune cell types.

    “representing 61% of all expressed protein-coding genes and 49% of all lncRNAs, respectively”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim. 17
  • May combine two claims. 18

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    About 18% of the detected transcripts were long noncoding RNAs.

    “About 18% of these transcripts were long-noncoding RNAs (lncRNAs)”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Most transcripts were detected in multiple cell types, but their relative abundance varied substantially, producing distinct clustering patterns of different cell types.

    “Though a majority of transcripts were detected in multiple cell types (Fig. S1H,I), their relative abundance varied substantially, resulting in distinct clustering patterns of different cell types”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The PBC-risk variant rs74804869 influenced SYNGR1 expression in NK cells and also CD8+ T cells.

    “The PBC-risk variant rs74804869 influenced SYNGR1 expression in NK and also CD8+ T cells”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    eQTL analysis of CD4+ memory and TREG subsets yielded over 7,800 eGenes, of which more than 2,500 were unique to these subsets.

    “Our eQTL analysis of CD4+ memory and TREG subsets yielded over 7,800 eGenes, of which >2,500 were unique to these subsets”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The Crohn's disease-risk variant rs9567293C/C was associated with reduced LACC1 expression in CD4+ memory T cell subsets and in resting and activated naïve T cells, but not in monocytes.

    “the CD-risk variant (rs9567293C/C) was associated with reduced expression of LACC1 in CD4+ memory T cell subsets, as well as in resting and activated naïve T cells but not in monocytes”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    NAB1 displayed a prominent genotype-dependent association, rs13028201, only in NK cells, although it was widely expressed across all other immune cell types studied.

    “we found that the expression of NAB1 displayed prominent genotype-dependent association (rs13028201, adj. P = 1.41 × 10−14) only in NK cells”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    CCNG2 had a peak eQTL, rs4859751, specifically in TH1/17 and TH17 cells although it was also highly expressed in other TH subsets and immune cell types.

    “CCNG2, encoding for a cell cycle protein, cyclin G2, showed a peak eQTL (rs4859751) specifically in TH1/17 and TH17 cells although it was also highly expressed in other TH subsets and immune cell types”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    An RA-risk variant rs3093026 and a celiac disease-risk variant rs7374671 were associated with expression of CCR6 and CCR2, respectively, in TH1/17 and TH17 subsets.

    “an RA-risk variant (rs3093026) and celiac disease-risk variant (rs7374671) that were associated with expression of chemokine receptor genes CCR6 and CCR2, respectively, in TH1/17 and TH17 subsets”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Of the sex-biased transcripts, 1,553 were protein-coding and 196 were lncRNAs.

    “1,875 unique transcripts, including 1,553 protein-coding transcripts and 196 lncRNAs, were differentially expressed between sexes”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The cis-eQTL rs1246642 had a stronger impact on FAM13A expression in female subjects; homozygous CC versus TT females had 3.5-fold greater FAM13A transcript levels compared to a less than 1.5-fold increase in males.

    “We also found a cis-eQTL (rs1246642) whose impact on expression was stronger in female subjects (Fig. 6F,G and Fig. S6B,C); homozygous females carrying the CC versus TT genotype had 3.5-fold greater levels of FAM13A transcripts compared to a <1.5-fold increase in males.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    TREG cells were most susceptible to the effects of several autoimmune disease-risk variants, with notable eGenes including IKZF4, PDE4A, and PTGIR.

    “TREG cells were most susceptible to the effects of several autoimmune disease-risk variants. Notable eGenes associated with these variants include IKZF4, PDE4A and PTGIR”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    PBC-risk variants that modulate NAB1 and SYNGR1 expression are likely to impact NK cell function and influence PBC disease susceptibility.

    “Together, these results suggested that PBC-risk variants that modulate NAB1 and SYNGR1 expression are likely to impact NK cell function and influence PBC disease susceptibility.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Overlap between GWAS SNPs and eQTLs indicates that the disease risk variant modulates expression of the linked gene in the susceptible cell type.
    • Rests on an assumption: Knockdown of a gene in immune cells reflects the functional consequence of genetically reduced expression of that gene.

  • Classified as probably not a substantial claim.

    Study design and conductown data

    The identity of each RNA-Seq sample was confirmed by matching genotype data from the same subject via genome-wide SNP analysis of exonic regions.

    “The identity of all individual RNA-Seq samples was confirmed by cross-comparison with genotyping data for a given subject by genome-wide analysis of SNPs overlapping exons.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    Samples for each cell type were processed in a single RNA-Seq batch to prevent experimental batch effects.

    “Further, samples from each specific cell types were processed for RNASeq in one batch to avoid any experimental batch effects.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    In the analysis of sex-biased transcripts, ancestry and age were included as covariates.

    “Sex-biased transcripts were identified by performing pairwise comparison (female (n = 37) versus male (n = 54) subjects) using DESeq2 and considering ancestry and age as covariates; we considered a transcript expressed differentially when the DESeq2 analysis resulted in a Benjamini-Hochberg adj. P value of < 0.05.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The first two principal components of genotype data were included as covariates to reduce possible ancestry differences among samples.

    “The first two principal components of the genotyping data were used as covariates to minimize possible differences introduced by the different ancestry in the samples.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The study received approval from the institutional review board at the La Jolla Institute for Allergy and Immunology under protocol SGE-121-0714.

    “The Institutional Review Board (IRB) of the La Jolla Institute for Allergy and Immunology (LJI; IRB protocol no. SGE-121–0714) approved the study.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    RNA-Seq expression data were regularized-log transformed and quantile-normalized to reduce the influence of possible outliers.

    “To diminish the effects of possible outliers, the regularized log transformation of the DESeq2 package (Love et al., 2014) was applied and the homoscedastic data were then quantile-normalized.”
    • Also stated in: § Genotyping, imputation and determination of Eqtl · plain
      “The regularized log transformation of the DESeq2 package (Love et al., 2014) was applied and the homoscedastic data were then quantile-normalized to diminish the effects of possible outliers.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Love et al., 2014 source

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductcitation

    Low-quality SNPs were removed: those failing in more than 5% of samples and those with Illumina GC scores below 0.2 in more than 10% of samples were filtered out.

    “The data quality was assessed using the snpQC package (Gondro et al., 2014) for R v3.2.3 (http://www.R-project.org) and low-quality SNPs were removed for downstream analysis: SNPs failing in more than 5% of the samples and SNPs with Illumina’s GC scores less than 0.2 in more than 10% of the samples were filtered out.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Gondro et al., 2014 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    The PheGenI dataset used for GWAS SNP analysis contained 14,321 significant SNP-trait associations (P < 5 × 10−8) and 846 distinct phenotypes.

    “To define the collection of SNPs from GWAS studies, we downloaded the dataset of the Phenotype-Genotype Integrator (PheGenI) (Ramos et al., 2014), which merges NHGRI GWAS Catalog data with several databases of the National Center for Biotechnology Information (NCBI), including Gene, dbGaP, OMIM, eQTL and dbSNP (September 2017; https://www.ncbi.nlm.nih.gov/gap/phegeni).”
    • Also stated in: § GWAS SNP database construction and analysis · plain
      “the resulting catalog of SNP-trait associations included 14,321 significant associations (lead GWAS SNPs; defined as P < 5 × 10−8) and 846 distinct phenotypes/traits.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Ramos et al., 2014 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Transcripts whose mean TPM was under 1.0 in every sample of a cell type were removed.

    “Transcripts with mean TPM < 1.0 across all samples of a given cell type were excluded from the analysis.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    The products of autoimmune risk-eGenes PDE4A and PTGIR are likely to modulate cAMP-mediated immunoregulation and influence disease pathogenesis.

    “Thus, the products of autoimmune risk-eGenes PDE4A and PTGIR are likely to modulate cAMP-mediated immunoregulation and influence disease pathogenesis.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The eQTL analysis excluded the pseudoautosomal regions of chromosomes X and Y, reducing the number of annotated transcripts analyzed from 57,820 to 57,215 (605 genes missing).

    “Notably, the eQTL analysis did not cover the pseudoautosomal regions of chr X or chr Y, thereby slightly lowering the annotated transcript count from 57,820 to 57,215 (605 missing genes).”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    For eQTL analysis, SNPs missing in more than 5% of samples or with minor allele frequency below 5% were excluded.

    “SNPs missing for more than 5% of the samples or with a minimum allele frequency (MAF) lower than 5% were removed from the analysis.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    Transcripts with low expression-the bottom one-third for at least 80% of samples-were filtered out before eQTL analysis.

    “Briefly, transcripts with low expression values – the bottom one-third of all transcripts for at least 80% of the samples – were filtered out.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    The cohort comprised 54 male and 37 female subjects with a median age of 27 years (range 18-61).

    “The cohort consisted of 54 males and 37 female subjects with a median age of 27 years (range 18 to 61 years).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Samples that failed quality control were excluded from downstream analysis; 1,544 RNA-Seq samples were included.

    “Samples failing any quality control step (RNA quality and quantity, PCR amplification, library fragment size) were eliminated from further downstream steps.”
    • Also stated in: § QUANTIFICATION AND STATISTICAL ANALYSIS · plain
      “Any samples failing established quality controls (QC) were eliminated from downstream analysis; assay details and QCs on RNA-Seq samples included are provided in Table S1B (1,544 samples in total).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Library preparation was automated on the Biomek FXP platform to reduce assay-to-assay variability.

    “Sequencing library preparation steps were performed in a 96-well format, utilizing the automated platform Biomek FXP (Beckman Coulter), to reduce assay-to-assay variability.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    Ninety-one healthy volunteers from the San Diego area provided leukapheresis samples at the San Diego Blood Bank after giving written informed consent.

    “A total of 91 healthy volunteers were recruited in the San Diego area, who provided leukapheresis samples at the San Diego Blood Bank (SDBB) after written informed consent.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    All subjects self-reported ethnicity and race and tested negative for hepatitis B, hepatitis C, and HIV.

    “All study subjects self-reported ethnicity and race details, and were tested negative for hepatitis B, hepatitis C and human immunodeficiency virus (HIV).”
    Quote in the paperNot a substantial claim
30 of 30

  • The paper relies on this without support.

    Overlap between GWAS SNPs and eQTLs indicates that the disease risk variant modulates expression of the linked gene in the susceptible cell type.

    “To shed light on the disease relevance of the eQTLs identified in human immune cells, we next focused on the subset of eGenes linked to eQTLs that directly overlapped haploblocks of significant GWAS SNPs”

  • The paper relies on this without support.

    Knockdown of a gene in immune cells reflects the functional consequence of genetically reduced expression of that gene.

    “As a first step in that process, we knocked down these genes in human NK cells and tested their impact on NK cell activity”

  • The paper relies on this without support.

    The 13 immune cell types and activation conditions studied are representative enough of human immune cells to generalize eQTL and sex-biased expression findings.

    “The cell types presented here comprise over 60% of all circulating mononuclear cells”
3 of 3

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Within the correlated gene sets were genes known to be enriched or functionally important in the memory T cell subset driven by the transcription factor in question, such as IL4R for GATA3 and CTLA4 for both Helios and FOXP3.

    “Within these correlated gene sets were genes known to be enriched or functionally important in the memory T cell subset driven by the TF in question, such as IL4R for GATA3 and CTLA4 for both Helios and FOXP324.”

    From NEAT-seq: simultaneous profiling of intra-nuclear proteins, chromatin accessibility and gene expression in single cells (2022) · cites this paper as [24]

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Authors
Schmiedel, B. J., Singh, D., Madrigal, A., Valdovino-Gonzalez, A. G., White, B. M., Zapardiel-Gonzalo, J., Ha, B., Altay, G., Greenbaum, J. A., McVicker, G., Seumois, G., Rao, A., Kronenberg, M., Peters, B., & Vijayanand, P.
Affiliations
  • La Jolla Institute for Immunology (US)
  • Salk Institute for Biological Studies (US)
Corresponding author
Vijayanand, Pandurangan
ORCID
Venue
Cell
Publisher
Elsevier BV
Published
2018-11
Volume
175
Issue
6
Pages
1701-1715.e16
ISSN
0092-8674 (ISSN-L)
DOI
10.1016/j.cell.2018.10.022
PMC
PMC6289654
OpenAlex
W2901765988
Semantic Scholar
0b385de9f5adec440b108379bcbf8f8f00d13552
Cited by
867
References
68
Citations by year
2026: 87 · 2025: 124 · 2024: 148 · 2023: 114 · 2022: 137 · 2021: 133 · 2020: 77 · 2019: 43 · 2018: 2
FWCI
39.71
Type
journal article
Language
en
Open access
Licence
Locations
  • Cell (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • ePrints Soton (University of Southampton) (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
  • B.P. Koirala Institute of Health Sciences (S10RR027366, S10OD016262)
  • National Institutes of Health (R24 AI108564)
  • William K. Bowes, Jr. Foundation
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords
genetic polymorphism, immune cell gene expression, cis-eQTL, expression quantitative trait loci, single-cell transcriptomics, sex differences in gene expression, cell type-specific gene regulation, immune cell types
MeSH terms
Adolescent, Adult, Female, Gene Expression Regulation, Genotype, Humans, Male, Middle Aged, Sex Characteristics, Polymorphism, Single Nucleotide, Gene Expression Profiling, Quantitative Trait Loci, Genome-Wide Association Study

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