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Nikolaos Panousis

Bio: Nikolaos Panousis is an academic researcher from Wellcome Trust Sanger Institute. The author has contributed to research in topics: Expression quantitative trait loci & Microglia. The author has an hindex of 2, co-authored 4 publications receiving 38 citations.

Papers
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Journal ArticleDOI
TL;DR: In this paper, gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery was profiled using expression quantitative trait loci (eQTL) mapping.
Abstract: Microglia, the tissue-resident macrophages of the central nervous system (CNS), play critical roles in immune defense, development and homeostasis. However, isolating microglia from humans in large numbers is challenging. Here, we profiled gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery. Using single-cell and bulk RNA sequencing, we identify how age, sex and clinical pathology influence microglia gene expression and which genetic variants have microglia-specific functions using expression quantitative trait loci (eQTL) mapping. We follow up one of our findings using a human induced pluripotent stem cell-based macrophage model to fine-map a candidate causal variant for Alzheimer's disease at the BIN1 locus. Our study provides a population-scale transcriptional map of a critically important cell for human CNS development and disease.

79 citations

Posted ContentDOI
20 Dec 2019-bioRxiv
TL;DR: This study provides the first population-scale transcriptional map of a critically important cell for neurodegenerative disorders and fine-map candidate causal variants at risk loci for Alzheimer’s disease.
Abstract: Microglia, the tissue resident macrophages of the CNS, are implicated in a broad range of neurological pathologies, from acute brain injury to dementia. Here, we profiled gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery. Using single cell and bulk RNA sequencing, we defined distinct cellular populations of acutely in vivo-activated microglia, and characterised a dramatic switch in microglial population composition in patients suffering from acute brain injury. We mapped expression quantitative trait loci (eQTLs) in human microglia and show that many disease-associated eQTLs in microglia replicate well in a human induced pluripotent stem cell (hIPSC) derived macrophage model system. Using ATAC-seq from 95 individuals in this hIPSC model we fine-map candidate causal variants at risk loci for Alzheimer9s disease, the most prevalent neurodegenerative condition in acute brain injury patients. Our study provides the first population-scale transcriptional map of a critically important cell for neurodegenerative disorders.

68 citations

Posted ContentDOI
01 Sep 2021-bioRxiv
TL;DR: GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity) as mentioned in this paper is a statistical approach designed to identify dynamic eQTLs across a transcriptional trajectory of cell populations, without aggregating single-cell data into pseudo-bulk.
Abstract: Common genetic variants modulate the cellular response to viruses and are implicated in a range of immune pathologies, including infectious and autoimmune diseases. The transcriptional antiviral response is known to vary between infected cells from a single individual, yet how genetic variants across individuals modulate the antiviral response (and its cell-to-cell variability) is not well understood. Here, we triggered the antiviral response in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-seq. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), the first statistical approach designed to identify dynamic eQTLs across a transcriptional trajectory of cell populations, without aggregating single-cell data into pseudo-bulk. This allows us to uncover the underlying architecture and variability of antiviral response across responding cells, and to identify more than two thousands eQTLs modulating the dynamic changes during this response. Many of these eQTLs colocalise with risk loci identified in GWAS of infectious and autoimmune diseases. As a case study, we focus on a COVID-19 susceptibility locus, colocalised with the antiviral OAS1 splicing QTL. We validated it in blood cells from a patient cohort and in the infected nasal cells of a patient with the risk allele, demonstrating the utility of GASPACHO to fine-map and functionally characterise a genetic locus. In summary, our novel analytical approach provides a new framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution.

9 citations

Posted ContentDOI
29 Jan 2020-bioRxiv
TL;DR: Through a computational framework for the segmentation of gene expression data, extensive fragmentation and reorganization of gene co-regulation domains in SLE are revealed, that correlates with disease activity states, and could provide valuable insights into disease pathogenesis and the mechanisms underlying disease flares.
Abstract: Systemic Lupus Erythematosus (SLE) is the prototype of autoimmune diseases, characterized by extensive gene expression perturbations in peripheral blood immune cells. Circumstantial evidence suggests that these perturbations may be due to altered epigenetic profiles and chromatin accessibility but the relationship between transcriptional deregulation and genome organization remains largely unstudied. We developed a genomic approach that leverages patterns of gene coexpression from genome-wide transcriptome profiles in order to identify statistically robust Domains of Co-ordinated gene Expression (DCEs). By implementing this method on gene expression data from a large SLE patient cohort, we identify significant disease-associated alterations in gene co-regulation patterns, which also correlate with the SLE activity status. Low disease activity patient genomes are characterized by extensive fragmentation leading to DCEs of smaller size. High disease activity genomes display excessive spatial redistribution of co-expression domains with expanded and newly-appearing (emerged) DCEs. Fragmentation and redistribution of gene coexpression patterns correlate with SLE-implicated biological pathways and clinically relevant endophenotypes such as kidney involvement. Notably, genes lying at the boundaries of split DCEs of low activity genomes are enriched in the interferon and other SLE susceptibility signatures, suggesting the implication of DCE fragmentation at early disease stages. Interrogation of promoter-enhancer interactions from various immune cell subtypes shows that a significant percentage of nested connections are disrupted by a DCE split or depletion in SLE genomes. Collectively, our results underlining an important role for genome organization in shaping gene expression in SLE, could provide valuable insights into disease pathogenesis and the mechanisms underlying disease flares.

1 citations


Cited by
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Journal Article
TL;DR: In this article, a multivariate Hidden Markov Model was used to reveal chromatin states in human T cells, based on recurrent and spatially coherent combinations of chromatin marks.
Abstract: A plethora of epigenetic modifications have been described in the human genome and shown to play diverse roles in gene regulation, cellular differentiation and the onset of disease. Although individual modifications have been linked to the activity levels of various genetic functional elements, their combinatorial patterns are still unresolved and their potential for systematic de novo genome annotation remains untapped. Here, we use a multivariate Hidden Markov Model to reveal chromatin states in human T cells, based on recurrent and spatially coherent combinations of chromatin marks.We define 51 distinct chromatin states, including promoter-associated, transcription-associated, active intergenic, largescale repressed and repeat-associated states. Each chromatin state shows specific enrichments in functional annotations, sequence motifs and specific experimentally observed characteristics, suggesting distinct biological roles. This approach provides a complementary functional annotation of the human genome that reveals the genome-wide locations of diverse classes of epigenetic function.

720 citations

Journal ArticleDOI
Douglas P Wightman1, Iris E. Jansen1, Jeanne E. Savage1, Alexey A. Shadrin2, Shahram Bahrami3, Shahram Bahrami2, Dominic Holland4, Arvid Rongve5, Sigrid Børte2, Sigrid Børte6, Sigrid Børte3, Bendik S. Winsvold6, Bendik S. Winsvold3, Ole Kristian Drange6, Amy E Martinsen6, Amy E Martinsen2, Amy E Martinsen3, Anne Heidi Skogholt6, Cristen J. Willer7, Geir Bråthen6, Ingunn Bosnes8, Ingunn Bosnes6, Jonas B. Nielsen9, Jonas B. Nielsen6, Jonas B. Nielsen7, Lars G. Fritsche7, Laurent F. Thomas6, Linda M. Pedersen3, Maiken Elvestad Gabrielsen6, Marianne Bakke Johnsen2, Marianne Bakke Johnsen3, Marianne Bakke Johnsen6, Tore Wergeland Meisingset6, Wei Zhou7, Wei Zhou10, Petroula Proitsi11, Angela Hodges11, Richard Dobson, Latha Velayudhan11, Karl Heilbron, Adam Auton, Julia M. Sealock12, Lea K. Davis12, Nancy L. Pedersen13, Chandra A. Reynolds14, Ida K. Karlsson13, Ida K. Karlsson15, Sigurdur H. Magnusson16, Hreinn Stefansson16, Steinunn Thordardottir, Palmi V. Jonsson17, Jon Snaedal, Anna Zettergren18, Ingmar Skoog18, Ingmar Skoog19, Silke Kern18, Silke Kern19, Margda Waern18, Margda Waern19, Henrik Zetterberg, Kaj Blennow18, Kaj Blennow19, Eystein Stordal6, Eystein Stordal8, Kristian Hveem6, John-Anker Zwart3, John-Anker Zwart6, John-Anker Zwart2, Lavinia Athanasiu2, Lavinia Athanasiu3, Per Selnes20, Ingvild Saltvedt6, Sigrid Botne Sando6, Ingun Ulstein3, Srdjan Djurovic5, Srdjan Djurovic3, Tormod Fladby20, Tormod Fladby2, Dag Aarsland21, Dag Aarsland11, Geir Selbæk3, Geir Selbæk2, Stephan Ripke10, Stephan Ripke22, Stephan Ripke23, Kari Stefansson16, Ole A. Andreassen2, Ole A. Andreassen3, Danielle Posthuma24, Danielle Posthuma1 
TL;DR: This paper identified microglia, immune cells and protein catabolism as relevant genes for late-onset Alzheimer's disease, while identifying and prioritizing previously unidentified genes of potential interest.
Abstract: Late-onset Alzheimer's disease is a prevalent age-related polygenic disease that accounts for 50-70% of dementia cases. Currently, only a fraction of the genetic variants underlying Alzheimer's disease have been identified. Here we show that increased sample sizes allowed identification of seven previously unidentified genetic loci contributing to Alzheimer's disease. This study highlights microglia, immune cells and protein catabolism as relevant to late-onset Alzheimer's disease, while identifying and prioritizing previously unidentified genes of potential interest. We anticipate that these results can be included in larger meta-analyses of Alzheimer's disease to identify further genetic variants that contribute to Alzheimer's pathology.

269 citations

Journal ArticleDOI
TL;DR: In this paper, the authors performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including new associations near CCDC6, TSPAN14, NCK2 and SPRED2.
Abstract: Genome-wide association studies have discovered numerous genomic loci associated with Alzheimer's disease (AD); yet the causal genes and variants are incompletely identified. We performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including new associations near CCDC6, TSPAN14, NCK2 and SPRED2. Using three SNP-level fine-mapping methods, we identified 21 SNPs with >50% probability each of being causally involved in AD risk and others strongly suggested by functional annotation. We followed this with colocalization analyses across 109 gene expression quantitative trait loci datasets and prioritization of genes by using protein interaction networks and tissue-specific expression. Combining this information into a quantitative score, we found that evidence converged on likely causal genes, including the above four genes, and those at previously discovered AD loci, including BIN1, APH1B, PTK2B, PILRA and CASS4.

189 citations

Journal ArticleDOI
TL;DR: The eQTL Catalogue as discussed by the authors is a set of gene expression quantitative trait locus (eQTL) studies published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization.
Abstract: Many gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue ( https://www.ebi.ac.uk/eqtl ), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.

122 citations

Journal ArticleDOI
TL;DR: In this article, the authors integrated Alzheimer's disease (AD) GWAS data with myeloid cell genomics, and reported that myELoid active enhancers are most burdened by AD risk alleles.
Abstract: Genome-wide association studies (GWAS) have identified more than 40 loci associated with Alzheimer’s disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown, impeding a mechanistic understanding of AD pathogenesis. Previously, we showed that AD risk alleles are enriched in myeloid-specific epigenomic annotations. Here, we show that they are specifically enriched in active enhancers of monocytes, macrophages and microglia. We integrated AD GWAS with myeloid epigenomic and transcriptomic datasets using analytical approaches to link myeloid enhancer activity to target gene expression regulation and AD risk modification. We identify AD risk enhancers and nominate candidate causal genes among their likely targets (including AP4E1, AP4M1, APBB3, BIN1, MS4A4A, MS4A6A, PILRA, RABEP1, SPI1, TP53INP1, and ZYX) in twenty loci. Fine-mapping of these enhancers nominates candidate functional variants that likely modify AD risk by regulating gene expression in myeloid cells. In the MS4A locus we identified a single candidate functional variant and validated it in human induced pluripotent stem cell (hiPSC)-derived microglia and brain. Taken together, this study integrates AD GWAS with multiple myeloid genomic datasets to investigate the mechanisms of AD risk alleles and nominates candidate functional variants, regulatory elements and genes that likely modulate disease susceptibility. This study integrates Alzheimer’s disease (AD) GWAS data with myeloid cell genomics, and reports that myeloid active enhancers are most burdened by AD risk alleles. The authors also nominate candidate causal regulatory elements, variants and genes that likely modulate the risk for AD.

95 citations