Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression

Schmiedel, Benjamin Joachim; Singh, Divya; Madrigal, Ariel; Valdovino-Gonzalez, Alan G; White, Brandie; Zapardiel‐Gonzalo, Jose; Ha, Brendan; Altay, Gökmen; Greenbaum, Jason A.; McVicker, Graham; Seumois, Grégory; Rao, Anjana; Kronenberg, Mitchell; Peters, Bjoern; Vijayanand, Pandurangan

doi:10.1016/j.cell.2018.10.022

Cited by 712 publications

(812 citation statements)

References 66 publications

(79 reference statements)

Supporting

Mentioning

699

Contrasting

Unclassified

Order By: Relevance

“…The ASE signal is localized mostly at the 3'-UTR of the EVC. A peak of expression at this location was also documented by NK cells, T cells-CD4 and classical monocytes as reported by the DICE database (Schmiedel et al 2018). We attribute the extreme signal of the EVC gene to its characteristics as a non-classical imprinted gene.…”

Section: Genomic Loci Rich With Ase Segments Are Associated With Immusupporting

confidence: 76%

“…All cells in the human body share the same genome (exception are cells of the adaptive immune systems and germ cells) which is differentially expressed in tissues and cell types. In this study, we aim to use the collection of ASE-V from AlleleDB to reveal new insights on features that characterize the genomic occurrences of ASE-V. Assessing the extent of ASE across diploid organisms with current sequencing technology reveals that the unbalanced allele expression is a broader phenomenon than anticipated, and accounts for a substantial fraction of the transcriptome (Consortium 2015;Kita et al 2017;Schmiedel et al 2018). The unstable estimates for the extent of ASE from blood samples reflect the variability in cell composition and clonality of the immune cells in the blood (Schmiedel et al 2018).…”

Section: Discussionmentioning

confidence: 99%

“…S3B). The100k bp segment of Chr17 (3.5M-3.6M) is gene rich and the ASE-V overlaps P2RX5 (and P2RX5-TAX1BP3 readthrough) that is expressed on B-cell and activated T-cells (Schmiedel et al 2018). P2RX5 was specified by its random MAE (Gimelbrant et al 2007).…”

Section: Genomic Loci Rich With Ase Segments Are Associated With Immumentioning

confidence: 99%

“…Compilation of data across many individuals in GTEx reveals that ~50% of all genes (with a relaxed definition of ±1M bp) show evidence for cisregulation, with only a small fraction of them being genuine ASE (1.7%-to 3.7%), with the highest fraction in whole blood samples (Consortium 2015). From a catalog of genes from 13 types of immune cells, 41% show cell-type-specific expression that is linked to cis-associated variants (Schmiedel et al 2018), and ~5% show it in human primary T-cells (Heap et al 2010).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Allele Specific Expression in Human – Genomic Makeup and Phenotypic Implications

Wainer-Katsir

Linial

2019

Preprint

View full text Add to dashboard Cite

The allele-specific expression phenomenon refers to unbalanced expression from the two parental alleles in a tissue of a diploid organism. AlleleDB is a high-quality resource that reports on about 30,000 ASE variants (ASE-V) from hundreds of human samples. In this study, we present the genomic characteristics and phenotypic implications of ASE. We identified tens of segments with extreme density of ASE-V, many of them are located at the major histocompatibility complex (MHC) locus. Notably, at a resolution of 100 nucleotides, the likelihood of ASE-V increases with the density of polymorphic sites. Another dominant trend of ASE is a strong bias of the expression to the major allele. This observation relies on the known allele frequencies in the healthy human population. Overlap of ASE-V and GWAS associations was calculated for 48 phenotypes from the UK-Biobank. ASE-V were significantly associated with a risk for inflammation (e.g. asthma), autoimmunity (e.g., rheumatoid arthritis, multiple sclerosis, and type 1 diabetes) and several blood cell traits (e.g., red cell distribution width). At the level of the ASE-genes, we seek association with all traits and conditions reported in the GWAS catalog. The statistical significance of ASE-genes to GWAS catalog reveals association with the susceptibility to virus infection, autoimmunity, inflammation, allergies, blood cancer and more. We postulate that ASE determines phenotype diversity between individuals and the risk for a variety of immune-related conditions.

show abstract

Section: Genomic Loci Rich With Ase Segments Are Associated With Immusupporting

confidence: 76%

Section: Discussionmentioning

confidence: 99%

Section: Genomic Loci Rich With Ase Segments Are Associated With Immumentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Allele Specific Expression in Human – Genomic Makeup and Phenotypic Implications

Wainer-Katsir

Linial

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…While a few trans ‐ associations—involving genes located on different chromosomes—were detected, these associations were either weak or driven by cross mapping errors and changes in cellular composition . The strong potential of eQTL for biomedical applications has rapidly lead to extend this framework to multiple tissues or purified immune cell types, showing a strong tissue specificity of eQTLs. Furthermore, exposing human cells to immune and infectious challenges has allowed the identification of response eQTLs that are associated with changes in gene expression specifically upon immune stimulation (Figure F,G) .…”

Section: Genetic Control Of Transcriptional Activity Is Highly Stimulmentioning

confidence: 99%

Characterising the genetic basis of immune response variation to identify causal mechanisms underlying disease susceptibility

Rotival

2019

HLA

View full text Add to dashboard Cite

Over the last 10 years, genome‐wide association studies (GWAS) have identified hundreds of susceptibility loci for autoimmune diseases. However, despite increasing power for the detection of both common and rare coding variants affecting disease susceptibility, a large fraction of disease heritability has remained unexplained. In addition, a majority of the identified loci are located in noncoding regions, and translation of disease‐associated loci into new biological insights on the etiology of immune disorders has been lagging. This highlights the need for a better understanding of noncoding variation and new strategies to identify causal genes at disease loci. In this review, I will first detail the molecular basis of gene expression and review the various mechanisms that contribute to alter gene activity at the transcriptional and post‐transcriptional level. I will then review the findings from 10 years of functional genomics studies regarding the genetics on gene expression, in particular in the context of infection. Finally, I will discuss the extent to which genetic variants that modulate gene expression at transcriptional and post‐transcriptional level contribute to disease susceptibility and present strategies to leverage this information for the identification of causal mechanisms at disease loci in the era of whole genome sequencing.

show abstract

Gene Expression Profiles of Treatment Response and Non‐Response in Children With Juvenile Dermatomyositis

Stingl

Dvergsten

Eng

et al. 2022

ACR Open Rheumatology

View full text Add to dashboard Cite

Objective The study objective was to identify differences in gene expression between treatment responders (TRs) and treatment non‐responders (TNRs) diagnosed with juvenile dermatomyositis (JDM). Methods Gene expression analyses were performed using whole blood messenger RNA sequencing in patients with JDM (n = 17) and healthy controls (HCs; n = 10). Four analyses were performed (A1‐4) comparing differential gene expression and pathways analysis exploiting the timing of sample acquisition and the treatments received to perform these comparative analyses. Analyses were done at diagnosis and follow‐up, which averaged 7 months later in the cohort. Results At diagnosis, the expression of 10 genes differed between TRs and TNRs. Hallmark and canonical pathway analysis revealed 11 and 60 pathways enriched in TRs and 3 and 21 pathways enriched in TNRs, respectively. Pathway enrichment at diagnosis in TRs was strongest in pathways involved in metabolism, complement activation, and cell signaling as mediated by IL‐8, p38/microtubule associated protein kinases (MAPK)/extracellular signal‐regulated kinases (ERK), Phosphatidylinositol 3 Kinase Gamma (PI3Kγ), and the B cell receptor. Follow‐up hallmark and canonical pathway analysis showed that 2 and 14 pathways were enriched in TRs, whereas 24 and 123 pathways were enriched in treatment TNRs, respectively. Prior treatment with glucocorticoids significantly altered expression of 13 genes in the analysis of subjects at diagnosis with JDM as compared with HCs. Conclusion Numerous genes and pathways differ between TRs and TNRs at diagnosis and follow‐up. Prior treatment with glucocorticoids prior to specimen acquisition had a small effect on the performed analyses.

show abstract

Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression

Cited by 712 publications

References 66 publications

Allele Specific Expression in Human – Genomic Makeup and Phenotypic Implications

Allele Specific Expression in Human – Genomic Makeup and Phenotypic Implications

Characterising the genetic basis of immune response variation to identify causal mechanisms underlying disease susceptibility

Gene Expression Profiles of Treatment Response and Non‐Response in Children With Juvenile Dermatomyositis

Contact Info

Product

Resources

About