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Nakic, N.

Publications and source records attributed to Nakic, N..

9 recordsLinked to original sources

Integration of genetic and epigenetic data pinpoints autoimmune specific remodelling of enhancer landscape in CD4+ T cells

CD4+ T cells play a crucial role in adaptive immune responses and have been implicated in the pathogenesis of autoimmune diseases (ADs). Despite numerous studies, the molecular mechanisms underlying T cell dysregulation in ADs remain incompletely understood. Here, we used transcriptomic and epigenomic data from CD4+ T cells of healthy donors and patients with systemic lupus erythematosus (SLE), psoriasis, juvenile idiopathic arthritis (JIA), and Graves disease to investigate the role of enhancers in AD pathogenesis. By generating enhancer-based gene regulatory networks (eGRNs), we identified disease-specific dysregulated pathways and potential downstream target genes of enhancers harbouring AD-associated single-nucleotide polymorphisms, which we also validated using CRISPRi in primary CD4+ T cells. Our results suggest that alterations in the regulatory landscapes of CD4+ T cells, including enhancers, contribute to the development of ADs and provide a basis for developing new therapeutic approaches.

genomics↗

Immune disease risk variants regulate gene expression dynamics during CD4+ T cell activation

During activation, T cells undergo extensive changes in gene expression which shape the properties of cells to exert their effector function. Therefore, understanding the genetic regulation of gene expression during T cell activation provides essential insights into how genetic variants influence the response to infections and immune diseases. We generated a single-cell map of expression quantitative trait loci (eQTL) across a T cell activation time-course. We profiled 655,349 CD4+ naive and memory T cells, capturing transcriptional states of unstimulated cells and three time points of cell activation in 119 healthy individuals. We identified 38 cell clusters, including stable clusters such as central and effector memory T cells and transient clusters that were only present at individual time points of activation, such as interferon-responding cells. We mapped eQTLs using a T cell activation trajectory and identified 6,407 eQTL genes, of which a third (2,265 genes) were dynamically regulated during T cell activation. We integrated this information with GWAS variants for immune-mediated diseases and observed 127 colocalizations, with significant enrichment in dynamic eQTLs. Immune disease loci colocalized with genes that are involved in the regulation of T cell activation, and genes with similar functions tended to be perturbed in the same direction by disease risk alleles. Our results emphasize the importance of mapping context-specific gene expression regulation, provide insights into the mechanisms of genetic susceptibility of immune diseases, and help prioritize new therapeutic targets.

genomics↗

Network and pathway expansion of genetic disease associations identifies successful drug targets

It is widely accepted that genetic evidence of disease association acts as a sound basis for the selection of drug targets for complex common diseases and that propagation of genetic evidence through gene or protein interaction networks can accurately infer novel disease associations at genes for which no direct genetic evidence can be observed. However, an empirical test of the utility of combining these beliefs for drug discovery has been lacking. In this study, we examine genetic associations arising from an analysis of 648 UK Biobank GWAS and evaluate whether targets identified as proxies of direct genetic hits are enriched for successful drug targets, as measured by historical clinical trial data. We find that protein networks formed from specific functional linkages such as protein complexes and ligand-receptor pairs are suitable for even naive guilt-by-association network propagation approaches. In addition, more sophisticated approaches applied to global protein-protein interaction networks and pathway databases, also successfully retrieve targets enriched for clinically successful drug targets. We conclude that network propagation of genetic evidence should be used for drug target identification.

genetics↗

Single-cell transcriptomics identifies an effectorness gradient shaping the response of CD4+ T cells to cytokines

Naive CD4+ T cells coordinate the immune response by acquiring an effector phenotype in response to cytokines. However, the cytokine responses in memory T cells remain largely understudied. We used quantitative proteomics, bulk RNA-seq and single-cell RNA-seq of over 40,000 human naive and memory CD4+ T cells to generate a detailed map of cytokine-regulated gene expression programs. We demonstrated that cytokine response differs substantially between naive and memory T cells and showed that memory cells are unable to differentiate into the Th2 phenotype. Moreover, memory T cells acquire a Th17-like phenotype in response to iTreg polarization. At the single-cell level, we demonstrated that T cells form a continuum which progresses from naive to effector memory T cells. This continuum is accompanied by a gradual increase in the expression levels of chemokines and cytokines and thus represents an effectorness gradient. Finally, we found that T cell cytokine responses are determined by where the cells lie in the effectorness gradient and identified genes whose expression is controlled by cytokines in an effectorness-dependent manner. Our results shed light on the heterogeneity of T cells and their responses to cytokines, provide insight into immune disease inflammation and could inform drug development.

immunology↗

Chromatin activity at GWAS loci identifies T cell states driving complex immune diseases

Complex immune disease variants are enriched in active chromatin regions of T cells and macrophages. However, whether these variants function in specific cell states or stages of cell activation is unknown. We stimulated T cells and macrophages in the presence of thirteen different cytokine cocktails linked to immune diseases and profiled active enhancers and promoters together with regions of open chromatin. We observed that T cell activation induced major chromatin remodelling, while additional exposure to cytokines fine-tuned the magnitude of these changes. Therefore, we developed a new statistical method that accounts for subtle changes in chromatin landscape to identify SNP enrichment across cell states. Our results point towards the role of immune disease variants in early rather than late activation of memory CD4+ T cells, and with limited differences across polarizing cytokines. Furthermore, we demonstrate that inflammatory bowel disease variants are enriched in chromatin regions active in Th1 cells, while asthma variants overlap regions active in Th2 cells. We also show that Alzheimers disease variants are enriched in different macrophage cell states. Our results represent the first in-depth analysis of immune disease variants across a comprehensive panel of activation states of T cells and macrophages.

genetics↗

Global variability of the human IgG glycome

Immunoglobulin G (IgG) is the most abundant serum antibody and is a key determinant of the humoral immune response. Its structural characteristics and effector functions are modulated through the attachment of various sugar moieties called glycans. IgG N-glycome patterns change with the age of individual and in different diseases. Variability of IgG glycosylation within a population is well studied and is affected by a combination of genetic and environmental factors. However, global inter-population differences in IgG glycosylation have never been properly addressed. Here we present population-specific N-glycosylation patterns of whole IgG, analysed in 5 different populations totalling 10,482 IgG glycomes, and of IgGs fragment crystallisable region (Fc), analysed in 2,530 samples from 27 populations sampled across the world. We observed that country of residence associates with many N-glycan features and is a strong predictor of monogalactosylation variability. IgG galactosylation also strongly correlated with the development level of a country, defined by United Nations health and socioeconomic development indicators. We found that subjects from developing countries had low IgG galactosylation levels, characteristic for inflammation and ageing. Our results suggest that citizens of developing countries may be exposed to country-specific environmental factors that can cause low-grade chronic inflammation and the apparent increase in biological age.

biochemistry↗

Notch Controls Multiple Pancreatic Cell Fate Regulators Through Direct Hes1-mediated Repression

Notch signaling and its effector Hes1 regulate multiple cell fate choices in the developing pancreas, but few direct target genes are known. Here we use transcriptome analyses combined with chromatin immunoprecipitation with next-generation sequencing (ChIP-seq) to identify direct target genes of Hes1. ChIP-seq analysis of endogenous Hes1 in 266-6 cells, a model of multipotent pancreatic progenitor cells, revealed high-confidence peaks associated with 354 genes. Among these were genes important for tip/trunk segregation such as Ptf1a and Nkx6-1, genes involved in endocrine differentiation such as Insm1 and Dll4, and genes encoding non-pancreatic basic-Helic-Loop-Helix (bHLH) factors such as Neurog2 and Ascl1. Surprisingly, we find that Hes1 binds a large number of loci previously reported to bind Ptf1a, including a site downstream of the Nkx6-1 gene. Notably, we find a number of Hes1 bound genes that are upregulated by {gamma}-secretase inhibition in pancreas explants independently of Neurog3 function, including the tip progenitor/acinar genes; Ptf1a, Gata4, Bhlha15, and Gfi1. Together, our data suggest that Notch signaling suppress the tip cell fate by Hes1-mediated repression of the tip-specific gene regulatory network module that includes transcriptional regulators such as Ptf1a, Gata4, Mist1, and Gfi1. Our data also uncover new molecular targets of Notch signaling that may be important for controlling cell fate choices in pancreas development.

developmental biology↗

Genome-Wide Identification of HES1 Target Genes Uncover Novel Roles for HES1 in Pancreatic Development

Notch signalling and the downstream effector HES1 is required for multiple pancreatic cell fate choices during development, but the direct target genes remain poorly characterised. Here we identify direct HES1 target genes on a genome-wide scale using ChIP-seq and RNA-seq analyses combined with human embryonic stem cell (hESC) directed differentiation of CRISPR/Cas9-generated HES1-/- mutant hESC lines. We found that HES1 binds to a distinct set of endocrine-specific genes, a set of genes encoding basic Helix-Loop-Helix (bHLH) proteins not normally expressed in the pancreas, genes in the Notch pathway, and the known HES1 target NEUROG3. RNA-seq analysis of wild type, HES1-/-, NEUROG3-/-, and HES1-/-NEUROG3-/- mutant hESC lines allowed us to uncover NEUROG3-independent, direct HES1 target genes. Among the HES1 bound genes that were derepressed in HES1-/-NEUROG3-/- cells compared to NEUROG3-/- cells, we found members of the endocrine-specific gene set, the Notch pathway genes DLL1, DLL4, and HEY1, as well as the non-pancreatic bHLH genes ASCL1 and ATOH1. We also found a large number of transcripts specific to the intestinal secretory lineage to be increased in HES1-/-NEUROG3-/- cells. Together, our data reveal that HES1 employs a multi-layered control of endocrine differentiation, controls Notch ligand expression independent of NEUROG3, and prevents initiation of ectopic intestinal transcriptional programmes in pancreas progenitors.

developmental biology↗

Human pancreatic β cell lncRNAs control cell-specific regulatory networks

Recent studies have uncovered thousands of long non-coding RNAs (IncRNAs) in human pancreatic {beta} cells. {beta} cell lncRNAs are often cell type-specific, and exhibit dynamic regulation during differentiation or upon changing glucose concentrations. Although these features hint at a role of lncRNAs in {beta} cell gene regulation and diabetes, the function of {beta} cell lncRNAs remains largely unknown. In this study, we investigated the function of {beta} cell-specific lncRNAs and transcription factors using transcript knockdowns and co-expression network analysis. This revealed lncRNAs that function in concert with transcription factors to regulate {beta} cell-specific transcriptional networks. We further demonstrate that lncRNA PLUTO affects local three-dimensional chromatin structure and transcription of PDX1, encoding a key {beta} cell transcription factor, and that both PLUTO and PDX1 are downregulated in islets from donors with type 2 diabetes or impaired glucose tolerance. These results implicate lncRNAs in the regulation of {beta} cell-specific transcription factor networks.

genomics↗