register interest

Dr Calliope Dendrou

Research Area: Immunology
Technology Exchange: Cell sorting, Cellular immunology, Flow cytometry, Protein interaction, Transcript profiling and Transgenesis
Scientific Themes: Immunology & Infectious Disease and Genetics & Genomics
Keywords: Autoimmune diseases, Genotype-to-phenotype analyses, Single cell signalling and gene expression dynamics and Cytokine signalling

Autoimmune diseases affect ~10% of the population worldwide and they have no cure. Currently available immunomodulatory drugs can help to alleviate symptoms, but have variable efficacy and can lead to severe side effects. Progress in identifying the genetic determinants of autoimmune and immune-mediated diseases is helping to improve our knowledge of the pathophysiological mechanisms that underlie these conditions. The key research interests of my group are to better understand the architecture of genetic predisposition across different autoimmune and immune-mediated diseases, and to explore the functional relevance and potential clinical utility of such cross-comparisons.   

Assessing patterns of genetic association between autoimmune diseases to date reveals heterogeneity, but also a few key variants that are emerging as immunopathological foci. We aim to investigate shared molecular circuits and cellular mechanisms across conditions for the purpose of identifying immunological ‘hubs’ that may be targeted therapeutically via drug repositioning approaches.

A further aim is to interrogate the relationship between genetic variation and the spatiotemporal dynamics of immune cell responsiveness, and how this may parallel the spectrum of immune-mediated diseases spanning malignancies, autoimmunity and infections. Elucidating these relationships can have implications for precision medicine in the context of patient stratification, prognostication, and optimal drug dosaging to balance efficacy and side effects.

Name Department Institution Country
Prof Lars Fugger (RDM) Weatherall Institute of Molecular Medicine Oxford University, Weatherall Institute of Molecular Medicine United Kingdom
Prof Jim R Hughes (RDM) Nuffield Division of Clinical Laboratory Sciences Oxford University, Weatherall Institute of Molecular Medicine United Kingdom
Prof Fredrik Karpe (RDM) OCDEM Oxford University, Oxford Centre for Diabetes, Endocrinology & Metabolism United Kingdom
Professor Gil McVean FRS FMedSci Big Data Institute Oxford University, Henry Wellcome Building of Genomic Medicine United Kingdom
Cortes A, Dendrou CA, Motyer A, Jostins L, Vukcevic D, Dilthey A, Donnelly P, Leslie S, Fugger L, McVean G. 2017. Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank. Nat Genet, 49 (9), pp. 1311-1318. | Show Abstract | Read more

Genetic discovery from the multitude of phenotypes extractable from routine healthcare data can transform understanding of the human phenome and accelerate progress toward precision medicine. However, a critical question when analyzing high-dimensional and heterogeneous data is how best to interrogate increasingly specific subphenotypes while retaining statistical power to detect genetic associations. Here we develop and employ a new Bayesian analysis framework that exploits the hierarchical structure of diagnosis classifications to analyze genetic variants against UK Biobank disease phenotypes derived from self-reporting and hospital episode statistics. Our method displays a more than 20% increase in power to detect genetic effects over other approaches and identifies new associations between classical human leukocyte antigen (HLA) alleles and common immune-mediated diseases (IMDs). By applying the approach to genetic risk scores (GRSs), we show the extent of genetic sharing among IMDs and expose differences in disease perception or diagnosis with potential clinical implications.

Kaur G, Gras S, Mobbs JI, Vivian JP, Cortes A, Barber T, Kuttikkatte SB, Jensen LT, Attfield KE, Dendrou CA et al. 2017. Structural and regulatory diversity shape HLA-C protein expression levels. Nat Commun, 8 pp. 15924. | Show Abstract | Read more

Expression of HLA-C varies widely across individuals in an allele-specific manner. This variation in expression can influence efficacy of the immune response, as shown for infectious and autoimmune diseases. MicroRNA binding partially influences differential HLA-C expression, but the additional contributing factors have remained undetermined. Here we use functional and structural analyses to demonstrate that HLA-C expression is modulated not just at the RNA level, but also at the protein level. Specifically, we show that variation in exons 2 and 3, which encode the α1/α2 domains, drives differential expression of HLA-C allomorphs at the cell surface by influencing the structure of the peptide-binding cleft and the diversity of peptides bound by the HLA-C molecules. Together with a phylogenetic analysis, these results highlight the diversity and long-term balancing selection of regulatory factors that modulate HLA-C expression.

Haghikia A, Dendrou CA, Schneider R, Grüter T, Postert T, Matzke M, Stephanik H, Fugger L, Gold R. 2017. Severe B-cell-mediated CNS disease secondary to alemtuzumab therapy. Lancet Neurol, 16 (2), pp. 104-106. | Read more

Dendrou CA, McVean G, Fugger L. 2016. Neuroinflammation - using big data to inform clinical practice. Nat Rev Neurol, 12 (12), pp. 685-698. | Show Abstract | Read more

Neuroinflammation is emerging as a central process in many neurological conditions, either as a causative factor or as a secondary response to nervous system insult. Understanding the causes and consequences of neuroinflammation could, therefore, provide insight that is needed to improve therapeutic interventions across many diseases. However, the complexity of the pathways involved necessitates the use of high-throughput approaches to extensively interrogate the process, and appropriate strategies to translate the data generated into clinical benefit. Use of 'big data' aims to generate, integrate and analyse large, heterogeneous datasets to provide in-depth insights into complex processes, and has the potential to unravel the complexities of neuroinflammation. Limitations in data analysis approaches currently prevent the full potential of big data being reached, but some aspects of big data are already yielding results. The implementation of 'omics' analyses in particular is becoming routine practice in biomedical research, and neuroimaging is producing large sets of complex data. In this Review, we evaluate the impact of the drive to collect and analyse big data on our understanding of neuroinflammation in disease. We describe the breadth of big data that are leading to an evolution in our understanding of this field, exemplify how these data are beginning to be of use in a clinical setting, and consider possible future directions.

Dendrou CA, Cortes A, Shipman L, Evans HG, Attfield KE, Jostins L, Barber T, Kaur G, Kuttikkatte SB, Leach OA et al. 2016. Resolving TYK2 locus genotype-to-phenotype differences in autoimmunity. Sci Transl Med, 8 (363), pp. 363ra149. | Show Abstract | Read more

Thousands of genetic variants have been identified, which contribute to the development of complex diseases, but determining how to elucidate their biological consequences for translation into clinical benefit is challenging. Conflicting evidence regarding the functional impact of genetic variants in the tyrosine kinase 2 (TYK2) gene, which is differentially associated with common autoimmune diseases, currently obscures the potential of TYK2 as a therapeutic target. We aimed to resolve this conflict by performing genetic meta-analysis across disorders; subsequent molecular, cellular, in vivo, and structural functional follow-up; and epidemiological studies. Our data revealed a protective homozygous effect that defined a signaling optimum between autoimmunity and immunodeficiency and identified TYK2 as a potential drug target for certain common autoimmune disorders.

Dendrou CA, Fugger L, Friese MA. 2015. Immunopathology of multiple sclerosis. Nat Rev Immunol, 15 (9), pp. 545-558. | Show Abstract | Read more

Two decades of clinical experience with immunomodulatory treatments for multiple sclerosis point to distinct immunological pathways that drive disease relapses and progression. In light of this, we discuss our current understanding of multiple sclerosis immunopathology, evaluate long-standing hypotheses regarding the role of the immune system in the disease and delineate key questions that are still unanswered. Recent and anticipated advances in the field of immunology, and the increasing recognition of inflammation as an important component of neurodegeneration, are shaping our conceptualization of disease pathophysiology, and we explore the potential implications for improved healthcare provision to patients in the future.

Taylor JC, Martin HC, Lise S, Broxholme J, Cazier JB, Rimmer A, Kanapin A, Lunter G, Fiddy S, Allan C et al. 2015. Factors influencing success of clinical genome sequencing across a broad spectrum of disorders. Nat Genet, 47 (7), pp. 717-726. | Show Abstract | Read more

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.

Moutsianas L, Jostins L, Beecham AH, Dilthey AT, Xifara DK, Ban M, Shah TS, Patsopoulos NA, Alfredsson L, Anderson CA et al. 2015. Class II HLA interactions modulate genetic risk for multiple sclerosis. Nat Genet, 47 (10), pp. 1107-1113. | Show Abstract | Read more

Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on 17,465 cases and 30,385 controls from 11 cohorts of European ancestry, in combination with imputation of classical HLA alleles, to build a high-resolution map of HLA genetic risk and assess the evidence for interactions involving classical HLA alleles. Among new and previously identified class II risk alleles (HLA-DRB1*15:01, HLA-DRB1*13:03, HLA-DRB1*03:01, HLA-DRB1*08:01 and HLA-DQB1*03:02) and class I protective alleles (HLA-A*02:01, HLA-B*44:02, HLA-B*38:01 and HLA-B*55:01), we find evidence for two interactions involving pairs of class II alleles: HLA-DQA1*01:01-HLA-DRB1*15:01 and HLA-DQB1*03:01-HLA-DQB1*03:02. We find no evidence for interactions between classical HLA alleles and non-HLA risk-associated variants and estimate a minimal effect of polygenic epistasis in modulating major risk alleles.

Cited:

135

Scopus

Dendrou CA, Fugger L, Friese MA. 2015. Immunopathology of multiple sclerosis NATURE REVIEWS IMMUNOLOGY, 15 (9), pp. 545-558. | Show Abstract | Read more

© 2015 Macmillan Publishers Limited. Two decades of clinical experience with immunomodulatory treatments for multiple sclerosis point to distinct immunological pathways that drive disease relapses and progression. In light of this, we discuss our current understanding of multiple sclerosis immunopathology, evaluate long-standing hypotheses regarding the role of the immune system in the disease and delineate key questions that are still unanswered. Recent and anticipated advances in the field of immunology, and the increasing recognition of inflammation as an important component of neurodegeneration, are shaping our conceptualization of disease pathophysiology, and we explore the potential implications for improved healthcare provision to patients in the future.

Dendrou CA, Fugger L. 2014. Please mind the gap: axonal transport deficits in multiple sclerosis neurodegeneration. Neuron, 84 (6), pp. 1105-1107. | Show Abstract | Read more

In this issue, Sorbara et al. (2014) demonstrate that axonal transport impairment is an early feature of neurodegeneration in multiple sclerosis models. This transport deficit is reversible by anti-inflammatory intervention but, if untreated, can contribute to late-stage axonal dystrophy.

Dendrou CA, Fugger L. 2014. Please mind the gap: Axonal transport deficits in multiple sclerosis neurodegeneration Neuron, 84 (6), pp. 1105-1107. | Show Abstract | Read more

© 2014 Elsevier Inc. In this issue, Sorbara etal. (2014) demonstrate that axonal transport impairment is an early feature of neurodegeneration in multiple sclerosis models. This transport deficit is reversible by anti-inflammatory intervention but, if untreated, can contribute to late-stage axonal dystrophy. In this issue Sorbara etal. (2014) demonstrate that axonal transport impairment is an early feature of neurodegeneration in multiple sclerosis models. This transport deficit is reversible by anti-inflammatory intervention but, if untreated, can contribute to late-stage axonal dystrophy.

Dendrou CA, Bell JI, Fugger L. 2013. A clinical conundrum: the detrimental effect of TNF antagonists in multiple sclerosis. Pharmacogenomics, 14 (12), pp. 1397-1404. | Show Abstract | Read more

Although TNF antagonists are efficacious in treating a range of autoimmune conditions, they exacerbate or even promote multiple sclerosis (MS)--a clinical finding that has been a conundrum for over a decade and has been a source of debate regarding the role of these drugs and of TNF signaling in the development of demyelinating disease. Recent work investigating the functional consequences of MS-associated genetic variation in the gene encoding TNFR1 has demonstrated that genetic risk drives the production of a novel, endogenous TNF antagonist. This mirrors the clinical experience with the drugs and indicates that the net effect of TNF function in MS development is a protective one, warranting a re-evaluation of the studies that have contributed to our understanding of TNF signaling in inflammation, immunoregulation and neuroprotection, to determine how future research can be directed towards targeting this pathway for therapeutic benefit.

Dendrou CA, Bell JI, Fugger L. 2013. Weighing in on autoimmune disease: Big data tip the scale. Nat Med, 19 (2), pp. 138-139. | Read more

Pekalski ML, Ferreira RC, Coulson RM, Cutler AJ, Guo H, Smyth DJ, Downes K, Dendrou CA, Castro Dopico X, Esposito L et al. 2013. Postthymic expansion in human CD4 naive T cells defined by expression of functional high-affinity IL-2 receptors. J Immunol, 190 (6), pp. 2554-2566. | Show Abstract | Read more

As the thymus involutes with age, the maintenance of peripheral naive T cells in humans becomes strongly dependent on peripheral cell division. However, mechanisms that orchestrate homeostatic division remain unclear. In this study we present evidence that the frequency of naive CD4 T cells that express CD25 (IL-2 receptor α-chain) increases with age on subsets of both CD31(+) and CD31(-) naive CD4 T cells. Analyses of TCR excision circles from sorted subsets indicate that CD25(+) naive CD4 T cells have undergone more rounds of homeostatic proliferation than their CD25(-) counterparts in both the CD31(+) and CD31(-) subsets, indicating that CD25 is a marker of naive CD4 T cells that have preferentially responded to survival signals from self-Ags or cytokines. CD25 expression on CD25(-) naive CD4 T cells can be induced by IL-7 in vitro in the absence of TCR activation. Although CD25(+) naive T cells respond to lower concentrations of IL-2 as compared with their CD25(-) counterparts, IL-2 responsiveness is further increased in CD31(-) naive T cells by their expression of the signaling IL-2 receptor β-chain CD122, forming with common γ-chain functional high-affinity IL-2 receptors. CD25 plays a role during activation: CD25(+) naive T cells stimulated in an APC-dependent manner were shown to produce increased levels of IL-2 as compared with their CD25(-) counterparts. This study establishes CD25(+) naive CD4 T cells, which are further delineated by CD31 expression, as a major functionally distinct immune cell subset in humans that warrants further characterization in health and disease.

Dendrou CA, Bell JI, Fugger L. 2013. Big data tip the scale Nature Medicine, 19 (2), pp. 138-139. | Read more

Gregory AP, Dendrou CA, Attfield KE, Haghikia A, Xifara DK, Butter F, Poschmann G, Kaur G, Lambert L, Leach OA et al. 2012. TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis. Nature, 488 (7412), pp. 508-511. | Show Abstract | Read more

Although there has been much success in identifying genetic variants associated with common diseases using genome-wide association studies (GWAS), it has been difficult to demonstrate which variants are causal and what role they have in disease. Moreover, the modest contribution that these variants make to disease risk has raised questions regarding their medical relevance. Here we have investigated a single nucleotide polymorphism (SNP) in the TNFRSF1A gene, that encodes tumour necrosis factor receptor 1 (TNFR1), which was discovered through GWAS to be associated with multiple sclerosis (MS), but not with other autoimmune conditions such as rheumatoid arthritis, psoriasis and Crohn’s disease. By analysing MS GWAS data in conjunction with the 1000 Genomes Project data we provide genetic evidence that strongly implicates this SNP, rs1800693, as the causal variant in the TNFRSF1A region. We further substantiate this through functional studies showing that the MS risk allele directs expression of a novel, soluble form of TNFR1 that can block TNF. Importantly, TNF-blocking drugs can promote onset or exacerbation of MS, but they have proven highly efficacious in the treatment of autoimmune diseases for which there is no association with rs1800693. This indicates that the clinical experience with these drugs parallels the disease association of rs1800693, and that the MS-associated TNFR1 variant mimics the effect of TNF-blocking drugs. Hence, our study demonstrates that clinical practice can be informed by comparing GWAS across common autoimmune diseases and by investigating the functional consequences of the disease-associated genetic variation.

Attfield KE, Dendrou CA, Fugger L. 2012. Bridging the gap from genetic association to functional understanding: the next generation of mouse models of multiple sclerosis. Immunol Rev, 248 (1), pp. 10-22. | Show Abstract | Read more

Multiple sclerosis (MS) is a disabling autoimmune disease of the central nervous system, which affects approximately 0.1% of the population with variable degrees of severity. Disease susceptibility is jointly determined by genetic predisposition and environmental contribution. However, as only a handful of genetic risk factors have been investigated beyond initial genome-wide association studies and environmental factors are largely unidentified, the exact mechanism of how these associations interact remains speculative. Our current understanding of this complex and heterogeneous disease has been advanced by experimental data obtained from animal modeling, with particular focus on the mouse MS model, experimental autoimmune encephalomyelitis. Manipulation of the mouse genome to study genetic risk factors has largely proved informative, but it also has limitations. Integration effects of transgene insertion, gene copy number, and expression variation, as well as differences in regulatory elements between mouse and human, are some of the hurdles faced when using such models to understand human gene variants in mice. Furthermore, as the list of MS disease-associated genetic variants continues to increase, so does the demand to find new approaches to study them. A new generation of humanized mice aims to tighten the gap between mouse and human, such that MS-associated genetic variants can be modeled more physiologically and systematically.

Fraser HI, Dendrou CA, Healy B, Rainbow DB, Howlett S, Smink LJ, Gregory S, Steward CA, Todd JA, Peterson LB, Wicker LS. 2010. Nonobese diabetic congenic strain analysis of autoimmune diabetes reveals genetic complexity of the Idd18 locus and identifies Vav3 as a candidate gene. J Immunol, 184 (9), pp. 5075-5084. | Show Abstract | Read more

We have used the public sequencing and annotation of the mouse genome to delimit the previously resolved type 1 diabetes (T1D) insulin-dependent diabetes (Idd)18 interval to a region on chromosome 3 that includes the immunologically relevant candidate gene, Vav3. To test the candidacy of Vav3, we developed a novel congenic strain that enabled the resolution of Idd18 to a 604-kb interval, designated Idd18.1, which contains only two annotated genes: the complete sequence of Vav3 and the last exon of the gene encoding NETRIN G1, Ntng1. Targeted sequencing of Idd18.1 in the NOD mouse strain revealed that allelic variation between NOD and C57BL/6J (B6) occurs in noncoding regions with 138 single nucleotide polymorphisms concentrated in the introns between exons 20 and 27 and immediately after the 3' untranslated region. We observed differential expression of VAV3 RNA transcripts in thymocytes when comparing congenic mouse strains with B6 or NOD alleles at Idd18.1. The T1D protection associated with B6 alleles of Idd18.1/Vav3 requires the presence of B6 protective alleles at Idd3, which are correlated with increased IL-2 production and regulatory T cell function. In the absence of B6 protective alleles at Idd3, we detected a second T1D protective B6 locus, Idd18.3, which is closely linked to, but distinct from, Idd18.1. Therefore, genetic mapping, sequencing, and gene expression evidence indicate that alteration of VAV3 expression is an etiological factor in the development of autoimmune beta-cell destruction in NOD mice. This study also demonstrates that a congenic strain mapping approach can isolate closely linked susceptibility genes.

Dendrou CA, Fung E, Esposito L, Todd JA, Wicker LS, Plagnol V. 2009. Fluorescence intensity normalisation: correcting for time effects in large-scale flow cytometric analysis. Adv Bioinformatics, 2009 pp. 476106. | Show Abstract | Read more

A next step to interpret the findings generated by genome-wide association studies is to associate molecular quantitative traits with disease-associated alleles. To this end, researchers are linking disease risk alleles with gene expression quantitative trait loci (eQTL). However, gene expression at the mRNA level is only an intermediate trait and flow cytometry analysis can provide more downstream and biologically valuable protein level information in multiple cell subsets simultaneously using freshly obtained samples. Because the throughput of flow cytometry is currently limited, experiments may need to span over several weeks or months to obtain a sufficient sample size to demonstrate genetic association. Therefore, normalisation methods are needed to control for technical variability and compare flow cytometry data over an extended period of time. We show how the use of normalising fluorospheres improves the repeatability of a cell surface CD25-APC mean fluorescence intensity phenotype on CD4(+) memory T cells. We investigate two types of normalising beads: broad spectrum and spectrum matched. Lastly, we propose two alternative normalisation procedures that are usable in the absence of normalising beads.

Dendrou CA, Plagnol V, Fung E, Yang JH, Downes K, Cooper JD, Nutland S, Coleman G, Himsworth M, Hardy M et al. 2009. Cell-specific protein phenotypes for the autoimmune locus IL2RA using a genotype-selectable human bioresource. Nat Genet, 41 (9), pp. 1011-1015. | Show Abstract | Read more

Genome-wide association studies (GWAS) have identified over 300 regions associated with more than 70 common diseases. However, identifying causal genes within an associated region remains a major challenge. One approach to resolving causal genes is through the dissection of gene-phenotype correlations. Here we use polychromatic flow cytometry to show that differences in surface expression of the human interleukin-2 (IL-2) receptor alpha (IL2RA, or CD25) protein are restricted to particular immune cell types and correlate with several haplotypes in the IL2RA region that have previously been associated with two autoimmune diseases, type 1 diabetes (T1D) and multiple sclerosis. We confirm our strongest gene-phenotype correlation at the RNA level by allele-specific expression (ASE). We also define key parameters for the design and implementation of post-GWAS gene-phenotype investigations and demonstrate the usefulness of a large bioresource of genotype-selectable normal donors from whom fresh, primary cells can be analyzed.

Dendrou CA, Wicker LS. 2008. The IL-2/CD25 pathway determines susceptibility to T1D in humans and NOD mice. J Clin Immunol, 28 (6), pp. 685-696. | Show Abstract | Read more

Although the interleukin-2 (IL-2)/IL-2R signaling pathway has been the focus of numerous studies, certain aspects of its molecular regulation are not well characterized, especially in non-T cells, and a more complete understanding of the pathway is necessary to discern the functional basis of the genetic association between the IL-2-IL-21 and IL-2RA/CD25 gene regions and T1D in humans. Genetic variation in these regions may promote T1D susceptibility by influencing transcription and/or splicing and, hence, IL-2 and IL-2RA/CD25 expression at the protein level in different immune cell subsets; thus, there is a need to establish links between the genetic variation and immune cell phenotypes and functions in humans, which can be further investigated and validated in mouse models. The detection and characterization of genetically determined immunophenotypes should aid in elucidating disease mechanisms and may enable future monitoring of disease initiation and progression in prediabetic subjects and of responses to therapeutic intervention.

Morriswood B, Ryzhakov G, Puri C, Arden SD, Roberts R, Dendrou C, Kendrick-Jones J, Buss F. 2007. T6BP and NDP52 are myosin VI binding partners with potential roles in cytokine signalling and cell adhesion. J Cell Sci, 120 (Pt 15), pp. 2574-2585. | Show Abstract | Read more

Myosin VI has been implicated in many cellular processes including endocytosis, secretion, membrane ruffling and cell motility. We carried out a yeast two-hybrid screen and identified TRAF6-binding protein (T6BP) and nuclear dot protein 52 (NDP52) as myosin VI binding partners. Myosin VI interaction with T6BP and NDP52 was confirmed in vitro and in vivo and the binding sites on each protein were accurately mapped. Immunofluorescence and electron microscopy showed that T6BP, NDP52 and myosin VI are present at the trans side of the Golgi complex, and on vesicles in the perinuclear region. Although the SKICH domain in T6BP and NDP52 does not mediate recruitment into membrane ruffles, loss of T6BP and NDP52 in RNAi knockdown cells results in reduced membrane ruffling activity and increased stress fibre and focal adhesion formation. Furthermore, we observed in these knockdown cells an upregulation of constitutive secretion of alkaline phosphatase, implying that both proteins act as negative regulators of secretory traffic at the Golgi complex. T6BP was also found to inhibit NF-kappaB activation, implicating it in the regulation of TRAF6-mediated cytokine signalling. Thus myosin VI-T6BP interactions may link membrane trafficking pathways with cell adhesion and cytokine-dependent cell signalling.

Cited:

43

Scopus

Morriswood B, Ryzhakov G, Puri C, Arden SD, Roberts R, Dendrou C, Kendrick-Jones J, Buss F. 2007. T6BP and NDP52 are myosin VI binding partners with potential roles in cytokine signalling and cell adhesion Journal of Cell Science, 120 (15), pp. 2574-2585. | Show Abstract | Read more

Myosin VI has been implicated in many cellular processes including endocytosis, secretion, membrane ruffling and cell motility. We carried out a yeast two-hybrid screen and identified TRAF6-binding protein (T6BP) and nuclear dot protein 52 (NDP52) as myosin VI binding partners. Myosin VI interaction with T6BP and NDP52 was confirmed in vitro and in vivo and the binding sites on each protein were accurately mapped. Immunofluorescence and electron microscopy showed that T6BP, NDP52 and myosin VI are present at the trans side of the Golgi complex, and on vesicles in the perinuclear region. Although the SKICH domain in T6BP and NDP52 does not mediate recruitment into membrane ruffles, loss of T6BP and NDP52 in RNAi knockdown cells results in reduced membrane ruffling activity and increased stress fibre and focal adhesion formation. Furthermore, we observed in these knockdown cells an upregulation of constitutive secretion of alkaline phosphatase, implying that both proteins act as negative regulators of secretory traffic at the Golgi complex. T6BP was also found to inhibit NF-ΚB activation, implicating it in the regulation of TRAF6-mediated cytokine signalling. Thus myosin VI-T6BP interactions may link membrane trafficking pathways with cell adhesion and cytokine-dependent cell signalling.

Cortes A, Dendrou CA, Motyer A, Jostins L, Vukcevic D, Dilthey A, Donnelly P, Leslie S, Fugger L, McVean G. 2017. Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank. Nat Genet, 49 (9), pp. 1311-1318. | Show Abstract | Read more

Genetic discovery from the multitude of phenotypes extractable from routine healthcare data can transform understanding of the human phenome and accelerate progress toward precision medicine. However, a critical question when analyzing high-dimensional and heterogeneous data is how best to interrogate increasingly specific subphenotypes while retaining statistical power to detect genetic associations. Here we develop and employ a new Bayesian analysis framework that exploits the hierarchical structure of diagnosis classifications to analyze genetic variants against UK Biobank disease phenotypes derived from self-reporting and hospital episode statistics. Our method displays a more than 20% increase in power to detect genetic effects over other approaches and identifies new associations between classical human leukocyte antigen (HLA) alleles and common immune-mediated diseases (IMDs). By applying the approach to genetic risk scores (GRSs), we show the extent of genetic sharing among IMDs and expose differences in disease perception or diagnosis with potential clinical implications.

Haghikia A, Dendrou CA, Schneider R, Grüter T, Postert T, Matzke M, Stephanik H, Fugger L, Gold R. 2017. Severe B-cell-mediated CNS disease secondary to alemtuzumab therapy. Lancet Neurol, 16 (2), pp. 104-106. | Read more

Dendrou CA, McVean G, Fugger L. 2016. Neuroinflammation - using big data to inform clinical practice. Nat Rev Neurol, 12 (12), pp. 685-698. | Show Abstract | Read more

Neuroinflammation is emerging as a central process in many neurological conditions, either as a causative factor or as a secondary response to nervous system insult. Understanding the causes and consequences of neuroinflammation could, therefore, provide insight that is needed to improve therapeutic interventions across many diseases. However, the complexity of the pathways involved necessitates the use of high-throughput approaches to extensively interrogate the process, and appropriate strategies to translate the data generated into clinical benefit. Use of 'big data' aims to generate, integrate and analyse large, heterogeneous datasets to provide in-depth insights into complex processes, and has the potential to unravel the complexities of neuroinflammation. Limitations in data analysis approaches currently prevent the full potential of big data being reached, but some aspects of big data are already yielding results. The implementation of 'omics' analyses in particular is becoming routine practice in biomedical research, and neuroimaging is producing large sets of complex data. In this Review, we evaluate the impact of the drive to collect and analyse big data on our understanding of neuroinflammation in disease. We describe the breadth of big data that are leading to an evolution in our understanding of this field, exemplify how these data are beginning to be of use in a clinical setting, and consider possible future directions.

Dendrou CA, Cortes A, Shipman L, Evans HG, Attfield KE, Jostins L, Barber T, Kaur G, Kuttikkatte SB, Leach OA et al. 2016. Resolving TYK2 locus genotype-to-phenotype differences in autoimmunity. Sci Transl Med, 8 (363), pp. 363ra149. | Show Abstract | Read more

Thousands of genetic variants have been identified, which contribute to the development of complex diseases, but determining how to elucidate their biological consequences for translation into clinical benefit is challenging. Conflicting evidence regarding the functional impact of genetic variants in the tyrosine kinase 2 (TYK2) gene, which is differentially associated with common autoimmune diseases, currently obscures the potential of TYK2 as a therapeutic target. We aimed to resolve this conflict by performing genetic meta-analysis across disorders; subsequent molecular, cellular, in vivo, and structural functional follow-up; and epidemiological studies. Our data revealed a protective homozygous effect that defined a signaling optimum between autoimmunity and immunodeficiency and identified TYK2 as a potential drug target for certain common autoimmune disorders.

Taylor JC, Martin HC, Lise S, Broxholme J, Cazier JB, Rimmer A, Kanapin A, Lunter G, Fiddy S, Allan C et al. 2015. Factors influencing success of clinical genome sequencing across a broad spectrum of disorders. Nat Genet, 47 (7), pp. 717-726. | Show Abstract | Read more

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.

Moutsianas L, Jostins L, Beecham AH, Dilthey AT, Xifara DK, Ban M, Shah TS, Patsopoulos NA, Alfredsson L, Anderson CA et al. 2015. Class II HLA interactions modulate genetic risk for multiple sclerosis. Nat Genet, 47 (10), pp. 1107-1113. | Show Abstract | Read more

Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on 17,465 cases and 30,385 controls from 11 cohorts of European ancestry, in combination with imputation of classical HLA alleles, to build a high-resolution map of HLA genetic risk and assess the evidence for interactions involving classical HLA alleles. Among new and previously identified class II risk alleles (HLA-DRB1*15:01, HLA-DRB1*13:03, HLA-DRB1*03:01, HLA-DRB1*08:01 and HLA-DQB1*03:02) and class I protective alleles (HLA-A*02:01, HLA-B*44:02, HLA-B*38:01 and HLA-B*55:01), we find evidence for two interactions involving pairs of class II alleles: HLA-DQA1*01:01-HLA-DRB1*15:01 and HLA-DQB1*03:01-HLA-DQB1*03:02. We find no evidence for interactions between classical HLA alleles and non-HLA risk-associated variants and estimate a minimal effect of polygenic epistasis in modulating major risk alleles.

Cited:

135

Scopus

Dendrou CA, Fugger L, Friese MA. 2015. Immunopathology of multiple sclerosis NATURE REVIEWS IMMUNOLOGY, 15 (9), pp. 545-558. | Show Abstract | Read more

© 2015 Macmillan Publishers Limited. Two decades of clinical experience with immunomodulatory treatments for multiple sclerosis point to distinct immunological pathways that drive disease relapses and progression. In light of this, we discuss our current understanding of multiple sclerosis immunopathology, evaluate long-standing hypotheses regarding the role of the immune system in the disease and delineate key questions that are still unanswered. Recent and anticipated advances in the field of immunology, and the increasing recognition of inflammation as an important component of neurodegeneration, are shaping our conceptualization of disease pathophysiology, and we explore the potential implications for improved healthcare provision to patients in the future.

Dendrou CA, Bell JI, Fugger L. 2013. Weighing in on autoimmune disease: Big data tip the scale. Nat Med, 19 (2), pp. 138-139. | Read more

Gregory AP, Dendrou CA, Attfield KE, Haghikia A, Xifara DK, Butter F, Poschmann G, Kaur G, Lambert L, Leach OA et al. 2012. TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis. Nature, 488 (7412), pp. 508-511. | Show Abstract | Read more

Although there has been much success in identifying genetic variants associated with common diseases using genome-wide association studies (GWAS), it has been difficult to demonstrate which variants are causal and what role they have in disease. Moreover, the modest contribution that these variants make to disease risk has raised questions regarding their medical relevance. Here we have investigated a single nucleotide polymorphism (SNP) in the TNFRSF1A gene, that encodes tumour necrosis factor receptor 1 (TNFR1), which was discovered through GWAS to be associated with multiple sclerosis (MS), but not with other autoimmune conditions such as rheumatoid arthritis, psoriasis and Crohn’s disease. By analysing MS GWAS data in conjunction with the 1000 Genomes Project data we provide genetic evidence that strongly implicates this SNP, rs1800693, as the causal variant in the TNFRSF1A region. We further substantiate this through functional studies showing that the MS risk allele directs expression of a novel, soluble form of TNFR1 that can block TNF. Importantly, TNF-blocking drugs can promote onset or exacerbation of MS, but they have proven highly efficacious in the treatment of autoimmune diseases for which there is no association with rs1800693. This indicates that the clinical experience with these drugs parallels the disease association of rs1800693, and that the MS-associated TNFR1 variant mimics the effect of TNF-blocking drugs. Hence, our study demonstrates that clinical practice can be informed by comparing GWAS across common autoimmune diseases and by investigating the functional consequences of the disease-associated genetic variation.

Dendrou CA, Plagnol V, Fung E, Yang JH, Downes K, Cooper JD, Nutland S, Coleman G, Himsworth M, Hardy M et al. 2009. Cell-specific protein phenotypes for the autoimmune locus IL2RA using a genotype-selectable human bioresource. Nat Genet, 41 (9), pp. 1011-1015. | Show Abstract | Read more

Genome-wide association studies (GWAS) have identified over 300 regions associated with more than 70 common diseases. However, identifying causal genes within an associated region remains a major challenge. One approach to resolving causal genes is through the dissection of gene-phenotype correlations. Here we use polychromatic flow cytometry to show that differences in surface expression of the human interleukin-2 (IL-2) receptor alpha (IL2RA, or CD25) protein are restricted to particular immune cell types and correlate with several haplotypes in the IL2RA region that have previously been associated with two autoimmune diseases, type 1 diabetes (T1D) and multiple sclerosis. We confirm our strongest gene-phenotype correlation at the RNA level by allele-specific expression (ASE). We also define key parameters for the design and implementation of post-GWAS gene-phenotype investigations and demonstrate the usefulness of a large bioresource of genotype-selectable normal donors from whom fresh, primary cells can be analyzed.

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