IL1R1 Human

What is the genomic structure and expression pattern of IL1R1 in humans?

IL1R1 is a key component of the interleukin-1 signaling pathway that belongs to the immunoglobulin superfamily. The gene encoding IL1R1 in humans is located on chromosome 2 and contains multiple exons that can undergo alternative splicing. Expression patterns vary significantly across tissues, with notable expression in immune cells, fibroblasts, and epithelial cells.

In research contexts, IL1R1 expression is typically assessed using RT-PCR, RNA sequencing, or protein-level detection through Western blotting or flow cytometry. Recent single-cell RNA sequencing approaches have revealed that IL1R1 expression can be heterogeneous even within seemingly uniform cell populations, particularly in CD4+ T cells responding to viral antigens . When studying IL1R1 expression, researchers should consider both tissue-specific and cell-type-specific patterns to accurately interpret experimental results.

How do IL1R1 single nucleotide polymorphisms (SNPs) impact research study design?

Several clinically significant SNPs have been identified in the IL1R1 gene that can affect study outcomes and interpretation. When designing genetic association studies involving IL1R1, researchers should consider:

• Haplotype analysis rather than isolated SNP analysis, as demonstrated in the Leiden Thrombophilia Study where 18 SNPs were used to tag 25 haplotype groups

• Population-specific variation in SNP frequencies

• Functional consequences of specific variants

For example, three SNPs of IL1R1 (rs871659, rs3771202, and rs3917238) have been associated with primary knee osteoarthritis, with sex-specific effects observed for the rs871659 allele A showing higher prevalence in females .

When conducting genetic studies involving IL1R1, sample size calculation should account for expected effect sizes. One study calculated that with a power of 80% (β = 0.2 and α = 0.05), appropriate sample sizes were 100 patients for the control group and 130 for the case group .

What methods are used to measure IL1R1 protein levels in human samples?

Multiple techniques can be employed to quantify IL1R1 protein levels in human samples, each with methodological considerations:

Researchers should be aware that plasma concentrations of IL1R1 protein have been shown to correlate with specific genotypes, as demonstrated in studies examining associations between gene variants such as rs871659 (A/A), rs3771202 (G/G), and rs3917238 (T/T) and plasma IL1R1 levels .

How does IL1R1 signaling influence CD4+ T cell responses to viral antigens?

Recent high-dimensional single-cell analyses have revealed that viral antigen-specific CD4+ T cells, including those specific for SARS-CoV-2 spike protein, express elevated levels of IL1R1 in humans . This expression pattern has significant functional consequences for immune responses.

Methodologically, researchers investigating this phenomenon should consider:

• Using multiplexed approaches (single-cell RNA-seq, mass cytometry, and flow cytometry) to characterize IL1R1+ T cell populations

• Correlating IL1R1 expression with functional markers of T cell activation and cytokine production

• Conducting ex vivo IL1R1 triggering or blocking experiments to assess functional outcomes

In vivo studies using COVID-19 mRNA vaccine mouse models demonstrated that neutralizing IL1R1 decreased IFN-γ expression by spike protein-specific CD4+ T cells and reduced the development of anti-spike protein IgG antibodies . This suggests a critical role for IL1R1 in coordinating T cell-dependent humoral immunity.

When designing experiments to investigate IL1R1 in T cell responses, researchers should include appropriate controls for both IL1R1 stimulation (using recombinant IL-1β) and blocking (using IL-1 receptor antagonists like Anakinra), with careful attention to dosing and timing relative to antigenic stimulation.

What is the role of IL1R1+ fibroblasts in tumor microenvironment modulation?

IL1R1+ cancer-associated fibroblasts (CAFs) have emerged as key modulators of the tumor microenvironment with significant implications for cancer progression. Single-cell sequencing of colorectal cancer patient samples has identified a pro-tumorigenic IL1R1+, IL-1-high-signaling subtype of fibroblasts that is associated with T cell and macrophage suppression .

For researchers studying IL1R1+ CAFs, methodological considerations include:

• Isolation and characterization of CAF subtypes using single-cell approaches

• 3D co-culture systems with cancer cells to assess functional impacts

• In vivo models using fibroblast-specific IL1R1 knockout or pharmacological intervention with IL-1 receptor antagonists

How does telomere length affect IL1R1 expression and function in cancer cells?

An emerging area of IL1R1 research concerns its regulation by telomere length, particularly in cancer contexts. Recent studies have demonstrated that IL-1 signaling is telomere-length dependent in cancer cells, with a mechanism involving non-telomeric TRF2 (telomeric repeat binding factor 2) binding at the IL1R1 promoter .

For researchers investigating telomere-IL1R1 interactions, important methodological approaches include:

• Chromatin immunoprecipitation (ChIP) to assess TRF2 binding and histone modifications at the IL1R1 promoter

• Comparative studies between cells with artificially manipulated telomere lengths

• Assessment of downstream effectors, including NF-κB signaling and cytokine production

Specifically, enhanced TRF2 binding at the IL1R1 promoter in cells with short telomeres directly recruits the histone-acetyl-transferase p300, leading to H3K27 acetylation and IL1R1 activation . This mechanism alters NF-κB signaling and affects downstream cytokines including IL6, IL8, and TNF.

In triple-negative breast cancer (TNBC) clinical samples, IL1R1 expression correlates with telomere length, and infiltration of tumor-associated macrophages shows sensitivity to tumor cell telomere length . This relationship provides a novel framework for understanding immune microenvironment dynamics in cancers with varying telomere biology.

What are the optimal approaches for studying IL1R1 genetic variants in disease association studies?

When investigating IL1R1 genetic variants in disease association studies, researchers should implement several key methodological strategies:

• Haplotype-based analysis rather than isolated SNP studies

• Appropriate control selection and matching for demographic variables

• Adequate statistical power through proper sample size calculation

• Assessment of gene-environment interactions

The Leiden Thrombophilia Study provided a robust methodological framework by genotyping 18 SNPs to tag 25 haplotype groups, enabling the identification of haplotype 5 of IL1RN (tagged by SNP 13888T/G, rs2232354) as a risk factor for venous thrombosis when present in homozygous form (Odds ratio=3.9; 95% confidence interval: 1.6 to 9.7; P=0.002) .

For analyzing genetic association data, specialized statistical tools like Haplo.stats can be employed to assess haplotype effects without requiring definitive haplotype assignment to individuals . This approach is particularly valuable when multiple linked polymorphisms are present within the gene region.

How should researchers design interventional studies targeting IL1R1 signaling?

When designing interventional studies targeting IL1R1 signaling, researchers should consider:

• Selection of appropriate IL1R1 antagonists (small molecules vs. biologics)

• Dosing strategies based on pharmacokinetic/pharmacodynamic models

• Assessment of on-target effects through biomarker evaluation

• Potential compensatory mechanisms through related pathways

In experimental settings, the IL-1 receptor antagonist Anakinra has been successfully employed to block IL1R1 signaling, with studies demonstrating efficacy in reducing tumor growth in vivo and restricting M2 macrophage infiltration in TNBC tumor organoids .

What are the challenges in interpreting IL1R1 expression data across different disease contexts?

Researchers face several challenges when interpreting IL1R1 expression data across disease contexts:

• Cell type-specific expression patterns that may be obscured in bulk tissue analyses

• Context-dependent regulation by factors including telomere length , inflammatory stimuli, and genetic variants

• Post-transcriptional regulation affecting protein levels

• Heterogeneity in expression even within defined cell populations

To address these challenges, researchers should employ multiple complementary techniques, including:

• Single-cell approaches to resolve cell type-specific expression

• Correlation of expression with functional outcomes

• Integration of genetic, epigenetic, and expression data

• Longitudinal sampling where feasible to capture dynamic changes

For example, in TNBC studies, IL1R1 expression varies with telomere length and correlates with tumor-associated macrophage infiltration, highlighting the importance of considering both intrinsic cellular factors and microenvironmental interactions .

How can IL1R1 genotyping inform clinical risk assessment?

IL1R1 genotyping can provide valuable information for clinical risk assessment across several disease contexts:

• Venous thrombosis risk assessment: Homozygous carriers of haplotype 5 of IL1RN (tagged by SNP 13888T/G, rs2232354) have an increased thrombotic risk (OR=3.9)

• Osteoarthritis susceptibility: IL1R1 SNPs rs871659, rs3771202, and rs3917238 associate with primary knee osteoarthritis, with sex-specific effects

• Cancer prognosis: IL1R1 expression patterns in cancer-associated fibroblasts correlate with immune infiltration and patient survival in colorectal cancer

For clinical implementation, researchers should consider:

• Development of clinically validated genotyping panels

• Integration with established risk factors and biomarkers

• Prospective validation in diverse populations

• Cost-effectiveness and accessibility of testing approaches

What are the experimental considerations for targeting IL1R1 in immunotherapy development?

As IL1R1 emerges as a potential therapeutic target, researchers developing immunotherapeutic approaches should consider:

• Cell type-specific targeting strategies to avoid systemic inflammatory effects

• Combination approaches with established immunotherapies

• Biomarker development for patient stratification

• Monitoring of immune cell phenotypes and function during treatment

Experimental evidence supports the potential efficacy of IL1R1 targeting in cancer contexts. In TNBC tumor organoids, both IL-1 Receptor antagonist (IL1RA) and IL1R1 targeting ligands demonstrated ability to abrogate M2 macrophage infiltration . The finding that infiltration of tumor-associated macrophages is sensitive to tumor cell telomere length and highly correlated with IL1R1 expression suggests that patient stratification based on these parameters might improve therapeutic outcomes .

For T cell-directed immunotherapies, the high expression of IL1R1 on viral antigen-specific CD4+ T cells provides a rationale for targeting this pathway to enhance vaccine efficacy or antiviral responses . Experimental approaches should include assessment of IL1R1 manipulation on both T cell effector function and memory formation.

What are emerging technologies for studying IL1R1 signaling dynamics?

Several cutting-edge technologies are advancing our understanding of IL1R1 signaling dynamics:

• Live-cell imaging of IL1R1 trafficking and signaling using fluorescent protein fusions

• CRISPR-based genetic screens to identify novel regulators of IL1R1 expression and function

• Proteomics approaches to comprehensively map IL1R1 signaling complexes

• Spatial transcriptomics to resolve IL1R1 expression patterns within complex tissues

These technologies enable researchers to move beyond static measurements to capture the temporal and spatial dynamics of IL1R1 signaling in physiologically relevant contexts.

How can multi-omics approaches enhance understanding of IL1R1 function in complex diseases?

Integration of multiple -omics approaches provides powerful insights into IL1R1 biology:

The power of multi-omics is exemplified in studies demonstrating that telomere length affects TRF2 binding and histone acetylation at the IL1R1 promoter, altering gene expression and downstream signaling cascades . This mechanistic insight required integration of genomic, epigenomic, and transcriptomic data.

Future research should leverage these integrated approaches to build comprehensive models of IL1R1 function across different physiological and pathological contexts, enabling more precise therapeutic targeting of this key inflammatory pathway.