Biology subjects

Jostins-Dean, L.

Publications and source records attributed to Jostins-Dean, L..

6 recordsLinked to original sources

bioRxiv2026

Reconstructing donor genotypes from scRNA-seq for downstream eQTL and HLA-TCR analysis

Single-cell eQTL studies can reveal heterogeneous genetic effects on gene expression that vary with cell type, but their wider application has been constrained by the frequent absence of matched genotype data. Here, we present single-cell Transcriptome Allelic Prediction and Association Studies (scTAPAS), a bioinformatic framework for reconstructing donor genotypes directly from single-cell RNA-sequencing reads and downstream genetic analysis. Applying scTAPAS to 5' single-cell RNA-sequencing data from the COVID-19 Multi-omic Blood Atlas (COMBAT), we show that reference-based imputation of sparse RNA-derived genetic information generates genotype dosages sufficiently accurate for association testing. Despite testing only 18.0% of the variants available from conventional array-based genotyping and imputation, scTAPAS recovers 68.6% of cell type-eGene pairs identified using conventional array-based genotypes, with strong concordance in effect sizes. We further show that scTAPAS-derived variants can support imputation of classical HLA alleles and enable HLA-aware QTL analyses, including associations between HLA variation and TCR repertoire at single-cell resolution. Using matched single-cell TCR-sequencing data, we identify CD4+ T cell-specific associations between HLA class II alleles and T-cell receptor (TCR) Va; gene segment usage, highlighting the potential of analyses that complement TCR sequencing at single-cell resolution with HLA types. These results show that genetic information recovered from single-cell RNA sequencing data can support both regulatory and immunogenetic association analyses, expanding the discovery potential of single-cell cohorts for which conventional genotyping or HLA typing is unavailable.

bioinformatics↗

bioRxiv2026

Rank-based integration identifies convergent disease mechanisms across omics

The rapid growth of omics studies offers new opportunities to uncover disease mechanisms, yet findings from individual studies or single omics may be influenced by cohort-, platform- and layer-specific variation. Integrating evidence across studies and omics layers can reveal robust biological signals that are reproducible across molecular layers, but differences in assay platforms, sample sizes and feature coverage complicate direct combination of summary statistics. Here we present the Omics Rank-Based Integration Tool (ORBIT), a direction-aware framework for prioritizing concordant signals across omics layers using only within-dataset feature ranks and effect directions. ORBIT tests directional rank consistency across omics layers against a closed-form variance-gamma null distribution while accounting for inter-dataset correlation and incomplete feature overlap. Simulations show that ORBIT maintains well-calibrated false-positive rates under inter-omics correlation, increasing numbers of omics layers and missingness, while detecting concordant signals with increasing power as the number of layers grows. We applied ORBIT to tubulointerstitial transcriptomic data from patients with chronic kidney disease in the C-PROBE cohort and proteomic data from the Kidney Precision Medicine Project, identifying a concordant injury programme marked by inflammatory and fibrotic remodeling together with impaired energy metabolism. We also used ORBIT to integrate ten transcriptomic, four proteomic and one translatomic datasets in dilated cardiomyopathy heart tissue, identifying extracellular matrix remodeling and mitochondrial energy failure as the dominant concordant biological programmes. In both diseases, ORBIT prioritized concordant genes and identified pathways that were not significant in any single omics layer alone. These results show that directional rank integration can be used for integrating heterogeneous omics summary data and prioritizing robust molecular mechanisms.

bioinformatics↗

bioRxiv2023

Novel joint enrichment test demonstrates high performance in simulations and identifies cell-types with enriched expression of inflammatory bowel disease risk loci

A number of methods have been developed to assess the enrichment of polygenic risk variants - from summary statistics of genome-wide association studies (GWAS) - within specific gene-sets, pathways, or cell-type signatures. The assumptions made by these methods vary, which leads to differences in results and performance across different genetic trait architectures and sample sizes. We devise a novel statistical test that combines independent signals from each of three commonly-used enrichment tests (LDSC, MAGMA & SNPsea) into a single P-value, called the block jackknife GWAS joint enrichment test (GWASJET). Through simulations, we show that this method has comparable or greater power than competing methods across a range of sample sizes and trait architectures. We use our new test in an extensive analysis of the cell-type specific enrichment of genetic risk for inflammatory bowel disease (IBD), including Crohns disease (CD) and ulcerative colitis (UC). Counterintuitively, we find stronger enrichments of IBD risk genes in older gene expression data from bulk immune cell-types than in single-cell data from inflamed patient intestinal samples. We demonstrate that GWASJET removes many seemingly-spurious enriched cell-types identified by other methods, and identifies a core set of immune cells that express IBD risk genes, particularly myeloid cells that have been experimentally stimulated. We also demonstrate that many cell-types are differentially enriched for CD compared to UC risk genes, for example gamma-delta T cells show stronger enrichment for CD than UC risk genes. Author summaryGenetic association studies have discovered a number of DNA variations that are associated with heritable human diseases and traits. One method of investigating the functions of these variants is to test whether they are enriched in parts of the genome associated with specific cell-types or cell conditions - defined by gene expression data or other similar data types. However, there are a number of published statistical methods to test such enrichments; these methdos make different assumptions and their results can vary, sometimes dramatically. We present a novel consensus method, called GWASJET, that combines the results of these different methods to produce a single result. We show that GWASJET can outperform individual methods in simulations. We apply this method to gene expression data from a number of tissues and conditions relevant to inflammatory bowel diseases (IBD). Our method removes potentially false results based on a priori biological knowledge, and reveals that IBD genes are generally clustered in a large number of immune cell-types, especially myeloid cells treated with specific stimulatory molecules.

genetics↗

bioRxiv2023

A longitudinal single-cell therapeutic atlas of anti-tumour necrosis factor treatment in inflammatory bowel disease

Precision medicine in immune-mediated inflammatory diseases (IMIDs) requires an understanding of how cellular networks change following therapy. We describe a therapeutic atlas for Crohns disease (CD) and ulcerative colitis (UC) following anti-tumour necrosis factor (TNF) therapy. We generated ~1 million single-cell transcriptomes, organised into 109 cell states, from 216 gut biopsies from 38 patients and three controls, revealing disease- and therapy-specific differences. A systems-biology analysis identified distinct spatially-resolved cellular microenvironments: granuloma signatures in CD and interferon (IFN)-response signatures localising to T-cell aggregates and epithelial damage in CD and UC. Longitudinal comparisons demonstrated that disease progression in non-responders associated with myeloid and stromal cell perturbations in CD and increased multi-cellular IFN signalling in UC. IFN signalling was also observed in rheumatoid arthritis (RA) synovium with a lymphoid pathotype. Our therapeutic atlas informs drug positioning across IMIDs, and suggests a rationale for the use of janus kinase (JAK) inhibition following anti-TNF resistance.

immunology↗

bioRxiv2022

Alternative paths to immune activation: the role of costimulatory risk genes for polygenic inflammatory disease in T helper cells

T cell activation pathways have been repeatedly implicated by genetic studies as being enriched for risk genes for immune and inflammatory diseases. Many of these risk genes code for costimulatory receptors or ligands. Costimulatory receptors are cell surface proteins on T cells, which are engaged by costimulatory ligands on antigen-presenting cells. Both costimulation and antigen binding are required to trigger T cell activation. In order to study the different pathways activated by these costimulatory risk molecules, and the role they may play in inflammatory disease genetics, we carried out gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) profiling of naive and memory CD4+ T cells (N=5 donors) activated via four different costimulatory receptors: CD28 (the standard molecule used for in vitro activation studies), along with alternative costimulatory molecules ICOS, CD6, and CD27. Most, but not all, activation genes and regions are shared by different costimulation conditions. Alternative costimulation induced lower proliferation and cytokine production, but higher lysosome production, altered metabolic processing, and indications of "signal seeking" behaviour (homing and expression of costimulatory and cytokine receptors). We validated a number of these functions at the surface protein level using orthogonal experimental techniques. We found the strongest enrichment of heritability for inflammatory bowel disease in shared regions upregulated by all costimulatory molecules. However, some risk variants and genes were only induced by alternative costimulation, and the impact of these variants on expression were less often successfully mapped in studies of T cells activated by traditional CD28 costimulation. This suggests that future genetics studies of gene expression in activated T cells may benefit from including alternative costimulation conditions.

genomics↗

bioRxiv2020

PYK2 controls intestinal inflammation via activation of IRF5 in macrophages

Inflammatory bowel disease (IBD) is a group of inflammatory disorders of the gastro-intestinal tract caused by a complex combination of genetic and environmental factors. Interferon regulating factor 5 (IRF5) is a multifunctional regulator of immune responses, which plays a key pathogenic role in mouse colitis models and is a genetic risk factor for IBD. A screen of a protein kinase inhibitor library in macrophages revealed a list of putative IRF5 kinases. Among the top hits validated in multiple in vitro assays, protein-tyrosine kinase 2-beta (PTK2B or PYK2) was identified as the only IBD genetic risk factor, known to impact gene expression in myeloid cells1,2. Phospho-proteomics and mutagenesis analyses established that PYK2 directly phosphorylates and activates IRF5 at tyrosine (Y) 171. IRF5 nuclear translocation and recruitment to target genes was impaired in PYK2-deficient cells or in cells treated with PYK2 inhibitors. Importantly, macrophage transcriptomic signature under PYK2 inhibition phenocopied IRF5 deficiency. Treatment with a PYK2 inhibitor reduced pathology and inflammatory cytokine production in Helicobacter hepaticus + anti-IL-10R antibody induced colitis model. It also decreased levels of pro-inflammatory cytokines in human colon biopsies taken from patients with ulcerative colitis. Thus, we have identified a major role for PYK2 in regulating the inflammatory response and mapped its activity to the IRF5 innate sensing pathway, opening opportunities for therapeutic interference with it in IBD and other inflammatory conditions.

immunology↗