Genomic imprinting: A missing piece of the Multiple Sclerosis puzzle?

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Contents lists available at ScienceDirect

The International Journal of Biochemistry & Cell Biology journal homepage: www.elsevier.com/locate/biocel

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Genomic imprinting: A missing piece of the Multiple Sclerosis puzzle?夽

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Sabrina Ruhrmann, Pernilla Stridh, Lara Kular, Maja Jagodic ∗ Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden

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Article history: Received 24 February 2015 Received in revised form 10 May 2015 Accepted 11 May 2015 Available online xxx

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Keywords: Parent-of-origin Genomic imprinting Multiple Sclerosis (MS) Experimental autoimmune encephalomyelitis (EAE) Epigenetic Inflammation Complex disease

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Contents

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Evidence for parent-of-origin effects in complex diseases such as Multiple Sclerosis (MS) strongly suggests a role for epigenetic mechanisms in their pathogenesis. In this review, we describe the importance of accounting for parent-of-origin when identifying new risk variants for complex diseases and discuss how genomic imprinting, one of the best-characterized epigenetic mechanisms causing parent-of-origin effects, may impact etiology of complex diseases. While the role of imprinted genes in growth and development is well established, the contribution and molecular mechanisms underlying the impact of genomic imprinting in immune functions and inflammatory diseases are still largely unknown. Here we discuss emerging roles of imprinted genes in the regulation of inflammatory responses with a particular focus on the Dlk1 cluster that has been implicated in etiology of experimental MS-like disease and Type 1 Diabetes. Moreover, we speculate on the potential wider impact of imprinting via the action of imprinted microRNAs, which are abundantly present in the Dlk1 locus and predicted to fine-tune important immune functions. Finally, we reflect on how unrelated imprinted genes or imprinted genes together with non-imprinted genes can interact in so-called imprinted gene networks (IGN) and suggest that IGNs could partly explain observed parent-of-origin effects in complex diseases. Unveiling the mechanisms of parent-of-origin effects is therefore likely to teach us not only about the etiology of complex diseases but also about the unknown roles of this fascinating phenomenon underlying uneven genetic contribution from our parents. This article is part of a Directed Issue entitled: Epigenetics dynamics in development and disease. © 2015 Published by Elsevier Ltd.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 Parent-of-origin effects and genomic imprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 2.1. Parent-of-origin effects in complex diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 2.2. Genomic imprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 2.3. Identification of imprinted genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 Mechanisms by which imprinted genes can control inflammation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 3.1. Imprinted genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 3.2. Imprinted microRNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 3.3. Interaction between imprinted and non-imprinted genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 Conclusions and future perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 Funding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00

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Abbreviations: MS, Multiple Sclerosis; QTLs, quantitative trait loci; EAE, experimental autoimmune encephalomyelitis; IGN, imprinted gene networks; T1D, Type 1 Diabetes; RA, Rheumatoid Arthritis; SLE, Systemic Lupus Erythematosus; HLA, Human Leukocyte Antigen; GWAS, genome-wide association studies; DMR, differentially methylated region; ICR, imprinting control region; SNP, single nucleotide polymorphism; nt, nucleotide; lncRNA, long non-coding RNA; miRNA, microRNA. 夽 This article is part of a Directed Issue entitled: Epigenetics dynamics in development and disease. ∗ Corresponding author. Tel.: +46 739801889. E-mail address: [email protected] (M. Jagodic). http://dx.doi.org/10.1016/j.biocel.2015.05.010 1357-2725/© 2015 Published by Elsevier Ltd.

Please cite this article in press as: Ruhrmann, S., et al., Genomic imprinting: A missing piece of the Multiple Sclerosis puzzle? Int J Biochem Cell Biol (2015), http://dx.doi.org/10.1016/j.biocel.2015.05.010

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1. Introduction

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Complex diseases, also known as multifactorial diseases, are conditions that arise from an intricate interplay between multiple genes in combination with environmental and lifestyle factors. The majority of diseases falls in this category and includes a large group of inflammatory disorders that underlie a variety of human diseases such as allergy and autoimmune diseases but also atherosclerosis and cancer. With the initial optimism of solving disease etiology by identifying the catalog of genes predisposing for each disease, a lot of effort has been placed in genetic studies. However, decades of genetic epidemiology research suggest that the complexity is even greater than originally anticipated, and many of the contributing factors have yet to be identified. Moreover, complex diseases cannot be described merely by the sum of genetic and environmental effects. One phenomenon observed in several complex diseases is an uneven genetic contribution from the parents, also known as parent-of-origin effects. Genomic imprinting, whereby a gene is expressed only from the maternally or paternally inherited chromosome, is one of the causes underlying such parent-of-origin effects. The expression of one allele is achieved by epigenetic mechanisms that refer to modifications of the DNA (e.g. methylation) resulting in altered gene expression without a change in the actual DNA sequence. Inflammation is a response of body tissues to potentially harmful stimuli and while inflammation has a protective role failure to tightly regulate inflammatory response can lead to inflammatory diseases. This failure is often associated with abnormalities in the immune system, which is the body’s defense against infectious agents and other invaders. Chronic inflammatory diseases such as Multiple Sclerosis (MS), Type 1 Diabetes (T1D), Rheumatoid Arthritis (RA) and Systemic Lupus Erythematosus (SLE) among others show typical features of complex genetic diseases. They present with clinical, etiological and genetic heterogeneity and involve many factors, none of which are essential or sufficient to cause disease on their own. MS, which is one of the leading causes of neurological disability in young adults, is characterized by autoimmune destruction of myelin and neurons in the central nervous system. Although T cells are considered as key mediators nearly every cell type of the innate and adaptive immune system has been implicated in immunopathology of MS as recently reviewed (Hartung et al., 2014; Kutzelnigg and Lassmann, 2014; Naegele and Martin, 2014). While the cause of MS remains unknown, epidemiological studies clearly establish MS as a heritable disease (Ebers et al., 1986; O’Gorman et al., 2013; Sadovnick et al., 1988; Westerlind et al., 2014). The first genetic risk factor was established in the 1970s and it mapped to the Human Leukocyte Antigen (HLA) complex region (Jersild et al., 1975; Jersild et al., 1972). The HLA region contains over 200 genes, many of which are involved in immune system development and functions, and alleles at different loci are often inherited together in established haplotypes. The original association was later refined to the extended haplotype HLA-DRB5*0101–HLADRB1*1501–HLA-DQA1*0102–HLA-DQB1*0602 (Fogdell et al., 1995) encoding key molecules that present antigens to T lymphocytes and conferring a threefold increase in risk to develop MS. Since then, more than 100 genetic variants have been identified to predispose for MS (Australia and New Zealand Multiple Sclerosis Genetics Consortium, 2009; Beecham et al., 2013; Sawcer et al., 2011), including multiple variants and alleles within the HLA locus (Patsopoulos et al., 2013). Jointly, the 110 non-HLA and the HLA effects explain 20% of the sibling recurrence risk (Beecham et al., 2013). A recent meta-analysis estimated genetic heritability of MS to be 54% and a model of inheritance that is consistent with one locus of moderate effect and many loci of modest effects (O’Gorman et al., 2013). The difference between estimated and explained heritability begs the question of where the ‘hidden heritability’ resides.

Increasing incidence of MS during the last several decades (Melcon et al., 2014) is speculated to result from changes in the environment and gene–environment interactions. Among the best established environmental factors are infection with Epstein–Barr virus, low vitamin D and sun exposure, high BMI and smoking (Ascherio, 2013). Recently, an interaction between smoking and the HLA-DRB1*15 and HLA-A*02 genes was reported to modulate risk to develop MS (Hedstrom et al., 2011). It is tempting to speculate that epigenetic mechanisms can mediate some of the impact of the environmental factors. For example, both current smoking and prenatal exposure to smoking induce DNA methylation changes (Lee and Pausova, 2013). Those changes, which can be passed on through cell divisions, might provide an explanation for the fact that the increased risk of MS in smokers persists at least five years after cessation (Hedstrom et al., 2013). Taken together, there is emerging evidence for complex interactions of genetic, environmental and epigenetic mechanisms underlying the pathogenesis of MS. To understand complex diseases and MS in particular we need to extend our quest beyond risk variants and environmental triggers to encompass parent-of-origin effects such as genomic imprinting and epigenetic mechanisms in general.

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2. Parent-of-origin effects and genomic imprinting

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2.1. Parent-of-origin effects in complex diseases

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The Mendel’s laws of inheritance describe the way genetic traits are transmitted from one generation to another. One of the assumptions of Mendelian inheritance is that genes originating from maternal and paternal genomes are equally expressed in the offspring. The term parent-of-origin effect refers to the phenomenon in which the phenotype depends on the parental origin of the associated allele, i.e. on whether the allele was inherited from the mother or father, causing non-Mendelian inheritance. In other words, the allele influences the trait only if it is inherited from a particular parent. Parent-of-origin effects comprise a range of genetic and epigenetic mechanisms, and combinations thereof. Genomic imprinting, where one parental allele is expressed while the other remains silent, is one of the best-characterized epigenetic mechanisms that cause parent-of-origin effects. Additional mechanisms involve the sex chromosomes, mitochondria, gender transmission bias, and trans-generational effects (including maternal intrauterine effects and maternal-offspring interactions) (Guilmatre and Sharp, 2012). The extent to which parent-of-origin effects contribute to the heritability of complex diseases is not yet known. Moreover, parent-of-origin effects, in particular epigenetic silencing of one allele, could mask the effect of genetic variation since only the expressed allele would be informative in the studied population. This could be one of many explanations for ‘hidden heritability’, i.e. why all the identified risk variants together explain only a fraction of heritability to complex diseases (Lander, 2011). Despite a number of studies that implicate parent-of-origin effects in the etiology of MS, the exact mechanisms are difficult to establish and study, often due to the lack of detailed information regarding the degree of relatedness between studied individuals. Moreover, parent-of-origin effects can easily be confounded by environmental and in utero effects. In a large Canadian cohort, half-siblings and avuncular pairs have been studied to assess parent-of-origin effects in MS. The maternal route was favored in disease transmission, with maternal half-siblings of MS-affected persons having a significantly higher risk for developing MS compared to paternal half siblings (Ebers et al., 2004; Herrera et al., 2008). Similarly, significantly more MS-affected

Please cite this article in press as: Ruhrmann, S., et al., Genomic imprinting: A missing piece of the Multiple Sclerosis puzzle? Int J Biochem Cell Biol (2015), http://dx.doi.org/10.1016/j.biocel.2015.05.010

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aunt/uncle–niece/nephew pairs were connected through an unaffected mother than father (Ebers et al., 2004; Herrera et al., 2008). Maternal parent-of-origin effects have also been suggested to influence the time of MS onset, although this finding has not been replicated (Sadovnick et al., 2009). Similar parent-of-origin effects have been demonstrated for the HLA haplotype, with greater transmission of the risk haplotype HLA-DRB1*15 from mothers than from fathers (Chao et al., 2009; Ramagopalan et al., 2008). While maternal transmission of risk has been confirmed in an isolated Dutch population (Hoppenbrouwers et al., 2008), studies in other populations have not yielded similar evidence (Hupperts et al., 2001; Westerlind et al., 2014). Even though the HLA locus encompasses the strongest genetic risk variants for many inflammatory diseases, studies of parent-of-origin effects on susceptibility to other diseases at this locus are less conclusive. Indeed, while parentof-origin effects have been suggested for the non-transmitted maternal DR3-DQ2 or DR4-DQ8 in T1D (Pani et al., 2002), other studies have reported the absence of this effect (Bronson et al., 2009; Hermann et al., 2003; Lambert et al., 2003; Sugihara et al., 2012). Similarly, no parent-of-origin effect in the HLA class II genes was observed in SLE (Bronson et al., 2010). Studies in experimental models of MS have, on the other hand, clearly demonstrated parent-of-origin effects. Experimental autoimmune encephalomyelitis (EAE) has been widely used to investigate pathogenic mechanisms shared with MS and to develop therapies and biomarkers. Several studies that aimed at identifying quantitative trait loci (QTLs), i.e. genomic regions harboring genetic variation(s) that predisposes for EAE, demonstrated that some QTLs depend on the parental origin of inherited alleles (Becanovic et al., 2003; Encinas et al., 2001; Stridh et al., 2014). In a recent study, we used two reciprocal backcross populations to detect and validate QTLs that predispose for EAE and investigate the impact of parentof-origin effects while controlling for maternal genetic effects. Our data demonstrate that between 30% and 50% of the QTLs, to various degrees, depend on the parent-of-origin in rat EAE (Stridh et al., 2014), which is similar to observations in mouse EAE (Encinas et al., 2001). A majority of the loci display an imprinting-like pattern, whereby a gene expressed only from the maternal or paternal copy exerted an effect. Similar significant effects were reported for >100 QTLs for multiple metabolic traits in an advanced intercross line of mice, where about 60% of the QTLs displayed imprinted effects (Cheverud et al., 2011; Lawson et al., 2011, 2010). Recently, Mott and colleagues reported that 36% (FDR 25%) of the 837 known QTLs for 97 complex traits studied in a heterogeneous stock of mice depend on the parental origin, and that 93% of the investigated traits exert parent-of-origin effects (Mott et al., 2014). Similar to observations in these studies we found that some of the parentof-origin dependent EAE QTLs overlap well-known imprinted loci whereas others do not (Stridh et al., 2014). Importantly, accounting for parental origin enabled us to unveil more of the genetic component of EAE and to identify, with higher certainty, a larger number of QTLs carrying risk alleles. Taken together, these studies show that parent-of-origin effects contribute substantially to complex diseases in experimental models. These findings have important implications for genetic studies of complex diseases in humans, currently dominated by genomewide association studies (GWAS) in case–control cohorts, which do not take parent-of-origin into account and consider the maternal and paternal route of allele transmission as functionally equivalent. Indeed, a handful of studies in which the parental origin of alleles was taken into consideration demonstrated additional risk variants that predispose for disease development (Hanson et al., 2013; Hoggart et al., 2014; Kong et al., 2009; Perry et al., 2014; Prokopenko et al., 2014; Wallace et al., 2010). However, owing to the availability of case–control cohorts, the most widely used GWAS design does not allow simple inference of the parental

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origin of the inherited alleles. Kong and colleagues used an elegant approach that exploited the detailed family history information, using the extensive pedigree records available in Icelanders, and long-range haplotypes phasing to determine the parent-of-origin of alleles (Kong et al., 2009). Family history, however, may not be available for most other populations and other approaches are needed. The trio GWAS design (mother, father and offspring) can provide the necessary parental genotype for the inference of the parental origin of inherited alleles. Different statistical methods and their advantages and limitation in detecting and deciphering different parent-of-origin effects in trio GWAS have been reviewed elsewhere (Connolly and Heron, 2014). 2.2. Genomic imprinting We will here focus on the potential role of genomic imprinting in the etiology of MS and other complex diseases, while other mechanisms causing parent-of-origin effects have been reviewed elsewhere (Guilmatre and Sharp, 2012). The term genomic imprinting describes an epigenetic mechanism that restricts the expression of a gene to one of the parental chromosomes. The first three imprinted genes were discovered in mice in 1991, namely Igf2r, Igf2 and H19 (Barlow et al., 1991; Bartolomei et al., 1991; DeChiara et al., 1991; Ferguson-Smith et al., 1991). The imprinted Igf2 and H19 genes are encoded in close proximity of each other, which gave the first evidence that imprinted genes may occur in clusters (Bartolomei et al., 1991). Consistent with this observation, imprinted genes tend to function in clusters of 3–12 genes spread over 80–3700 kb of DNA. At present there are seven well-examined clusters of imprinted genes in mice (Igf2r, Kcnq1, PWS, Gnas, Grb10, Igf2 and Dlk1). DNA methylation is the best-known and most studied mechanism responsible for establishing the imprint on one of the parental chromosomes. DNA methylation is a modification that covalently adds a methyl group to the cytosine residue in CpG dinucleotides and it is acquired and maintained through the action of methyltransferases such as DNMT3A/DNMT3B and DNMT1, respectively (Li and Zhang, 2014). Indeed, a feature shared by all seven imprinted clusters is the presence of a differentially methylated region (DMR), which is established in one gamete and maintained only on one parental chromosome in diploid cells of the embryo. Mutations in DNA methyltransferases generate DNA methylation deficient embryos that display an altered imprinted gene expression, indicating the importance of DNA methylation in the establishment of genomic imprinting (Barlow and Bartolomei, 2014). Five (Igf2r, Kcnq1, Gnas, Grb10 and PWS) of the seven imprinted clusters have a maternal methylation imprint on the DMR acquired during oogenesis, whereas two clusters (Igf2 and Dlk1) have paternal methylation imprints acquired during spermatogenesis. The DMR controls the imprinted expression of either the whole or a part of the cluster and is therefore also considered to be the imprinting control region (ICR) (Barlow, 2011). DNA methylation changes at ICRs are believed to be responsible for time- and cell type-dependent genomic imprinting. Indeed, for example, the Dlk1 gene, which is known to be exclusively paternally expressed during embryogenesis, loses its imprinting in the neurogenic niche shortly after birth, concomitant with a gain of methylation of the DMR on the maternal chromosome (Fig. 1A) (Ferron et al., 2011). Another common characteristic of these seven imprinted gene clusters is that they consist of multiple mRNAs and at least one long non-coding RNA (lncRNA). LncRNAs, which generally show reciprocal parental-specific expression compared to the imprinted mRNA genes, have been proposed to contribute to the regulation of genomic imprinting (e.g. through silencing of the imprinted mRNA genes) (Barlow and Bartolomei, 2014). As an example, illustrated in Fig. 1A for the Dlk1 locus, methylation of the DMR occurs

Please cite this article in press as: Ruhrmann, S., et al., Genomic imprinting: A missing piece of the Multiple Sclerosis puzzle? Int J Biochem Cell Biol (2015), http://dx.doi.org/10.1016/j.biocel.2015.05.010

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Fig. 1. Potential impact of Dlk1 cluster miRNAs on immune functions. (A) Schematic representation of the imprinted Dlk1 cluster. Exclusively maternally expressed genes such as the lncRNA Gtl2 and exclusively paternally expressed genes like the Dlk1 gene are represented in pink and blue, respectively. Silenced genes are displayed in gray on both parental chromosomes. DNA methylation imprint (black filled circle) on the paternal chromosome silences the lncRNA Gtl2 and permits mRNA expression of Dlk1, Rtl1 and Dio3 genes. Pink and blue arrows indicate direction of transcription on the maternal and the paternal chromosome, respectively. (B) MiRNAs differentially expressed between EAE-susceptible and EAE-resistant rat strains after EAE induction (Bergman et al., 2013). (C) Significant functions predicted to be targeted by anti-RTL1 miRNAs (miR-433, -431, -127, -432 and -136) in the DLK1 cluster. (D) Graphic representation of most common signaling pathways from C. Target genes (purple circles) were predicted using Targetscan and data were analyzed using QIAGEN’s Ingenuity® Pathway Analysis. Only multiple miRNAs that target single genes are shown. 296 297 298 299 300 301 302 303

on the chromosome that carries the silent copy of the imprinted lncRNA named Gtl2, thus preventing its expression and allowing for mRNA expression of additional genes on the same chromosome such as Dlk1 (Kota et al., 2014). More generally, in addition to the prominent role of DNA methylation, the monoallelic expression of imprinted genes can be achieved by the interaction of other epigenetic mechanisms, including histone modifications, the action of long non-coding RNAs and long-range chromatin interactions

facilitated by the methylation-sensitive binding of the architectural protein CTCF (Ferguson-Smith, 2011). 2.3. Identification of imprinted genes Several genome-wide approaches have led to successful identification of novel imprinted genes. Attempts to detect imprinted genes have included techniques such as (i) microarray

Please cite this article in press as: Ruhrmann, S., et al., Genomic imprinting: A missing piece of the Multiple Sclerosis puzzle? Int J Biochem Cell Biol (2015), http://dx.doi.org/10.1016/j.biocel.2015.05.010

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expression profiling of embryos that obtain their chromosomes either exclusively from the female (parthenogenetic) or male (androgenetic) parent (Kuzmin et al., 2008; Mizuno et al., 2002; Nikaido et al., 2003) and mice that receive two copies of a chromosome or part of a chromosome from only one parent (uniparental disomy) (Choi et al., 2001, 2005; Schulz et al., 2006), (ii) allele specific single nucleotide polymorphism (SNP) arrays (Brideau et al., 2010; Morcos et al., 2011; Pollard et al., 2008; Serre et al., 2008), (iii) computational prediction methods and (Brideau et al., 2010; Ke et al., 2002; Luedi et al., 2007; Luedi et al., 2005; Yang et al., 2003), (iv) DNA methylation based methods (Peters et al., 1999; Smith et al., 2003). Since all of these methods face different limitations, including only detecting a certain subset of genes (microarray expression profiling), encountering a high false positive rate (computational prediction methods) or missing imprinted genes that are not associated to differentially methylated regions (DNA methylation based methods) (Wang et al., 2011), RNA sequencing (RNA-seq) has recently become the method of choice. Several groups have applied RNA-seq to quantitatively measure allele specific expression in samples from reciprocal crosses of inbred mouse strains. Allele specific expression was quantified by counting reads with the reference allele as well as reads with the alternative allele on known SNP positions (Babak et al., 2008; DeVeale et al., 2012; Gregg et al., 2010a, 2010b; Okae et al., 2012; Wang et al., 2011, 2008). This approach has successfully identified imprinted genes, but as demonstrated in the validation study by DeVaele et al., RNA-seq can also lead to erroneous calling of imprinted genes if the impact of biological variation and technical variation is not accounted for (DeVeale et al., 2012). This emphasizes that, regardless of the method, independent validation with a complementary technology is always necessary.

imprinted genes located on chromosomes 14, 12 and 6 in human, mouse and rat, respectively (Fig. 1A) (Takada et al., 2000; Wylie et al., 2000). The DLK1 gene encodes for an EGF repeat containing protein similar to molecules involved in the Notch signaling pathway. Several studies provide evidence of the involvement of DLK1 in immune system development and function. Namely, DLK1 has been shown to affect development and function of B cells (Bauer et al., 1998; Raghunandan et al., 2008; Sakajiri et al., 2005) and it has been suggested that DLK1 can affect expression of many immune-related genes, including proinflammatory cytokines, as well as transactivation of the NF-kappaB factor (Abdallah et al., 2007). It is plausible that DLK1 exerts these roles, at least in part, by acting as an atypical Notch ligand that has the potential to inhibit Notch signaling (Baladron et al., 2005; Nueda et al., 2007). Wallace et al. reported a SNP (rs941576) (Wallace et al., 2010), located in the DLK1 cluster that associates with paternally inherited risk of developing T1D. We have observed similar tendency in a small Swedish T1D family cohort (unpublished observations). We recently identified a locus encompassing the Dlk1 cluster that predisposes for development of EAE in rats only when the risk allele is paternally inherited (Stridh et al., 2014). Moreover, we showed that the paternally inherited risk allele associates with a lower Dlk1 expression in immune tissues in rats and that the transgenic overexpression of Dlk1 reduces disease severity in mice. This modulation of EAE severity associated with alterations in the adaptive immune response, i.e. T and B cells, which is in line with the role of DLK1 in the Notch pathway in MS and EAE pathogenesis (Jurynczyk and Selmaj, 2010). However, whether epigenetic regulation in the DLK1 cluster plays a role in inflammatory diseases or epigenetic mechanisms modulate penetrance of genetic variant(s) in the DLK1 cluster remains to be studied.

3. Mechanisms by which imprinted genes can control inflammation

3.2. Imprinted microRNAs

Most of the imprinted genes play important roles in growth and development. While these roles have been well established, it is less clear to what extent and how imprinted genes affect the immune system and inflammatory diseases. It is even less certain if the imprinting, which affects only a small portion of the genes in the genome, can exert sizable impact on inflammation. In the coming paragraphs we discuss emerging roles of imprinted genes in regulation of inflammatory responses. Moreover, we discuss potential effects of imprinted genes that extend from the influence of a single imprinted gene to a wider range of genes modulated by imprinted microRNAs (miRNAs), and a potentially even wider impact of non-imprinted genes that are engaged in complex networks with imprinted genes. 3.1. Imprinted genes Besides their role in development, several imprinted genes have been implicated in regulation of immune responses, including differentiation and activation of T and B lymphocytes that constitute the major cellular components of the adaptive immune response. For example, it has been shown that the loss of imprinting of IGF2 occurs in T cells from healthy subjects upon T cell stimulation and is accompanied with IGF2 expression and cell proliferation (Hofmann et al., 2002). An increased expression of IGF2 resulting from a loss of IGF2 imprinting has also been reported in RA patients (MartinTrujillo et al., 2010), however it is unknown whether this is a cause or a consequence of inflammation. We will therefore focus on potential roles of DLK1 since genetic studies provide evidence of a causal role of DLK1 in inflammatory diseases. The paternally expressed DLK1 gene belongs to the well-known DLK1 cluster of

Remarkably, most of the imprinted domains contain clusters of non-coding RNAs including miRNAs (Table 1), which makes the imprinted regions the densest regions of small non-coding RNAs in the genome. Many of these miRNAs have also been confirmed to be imprinted (Zhang et al., 2010). Mature miRNAs are small, about 22 nucleotides (nt), evolutionary conserved non-coding RNAs that act by binding through partial complementary of the “seed” (nt 2–8) to sequences in the 3 UTRs of mRNAs. This binding results in a negative regulation of gene transcription in a post-transcriptional manner, either by RNA degradation or by translational inhibition. It has been estimated that a single miRNA has the potential to regulate hundreds of target genes and that >60% of human protein-coding genes are likely under miRNA control (Friedman et al., 2009). While some imprinted miRNAs exert important functions related to regulation of genomic imprinting (Davis et al., 2005; Seitz et al., 2003), current hypotheses favor a trans-acting role of miRNAs on mRNAs unrelated to imprinting. Previous studies of predicted miRNA targets identified several imprinted miRNAs potentially involved in regulation of genes common to many inflammatory diseases (Camprubi and Monk, 2011; Royo and Cavaille, 2008). We extended this analysis to all potentially imprinted miRNAs and found that several miRNAs have potential to regulate the major risk factor for MS and many other inflammatory diseases, namely HLA-DRB1 (Table 1). Despite the growing body of evidence suggesting a complex genetic interplay between HLA genes (e.g. HLA-C, HLA-G, HLA-DPB1) and miRNAs in immune homeostasis (Greliche et al., 2012) and pathologies such as HIV, Crohn’s disease, asthma and SLE (Consiglio et al., 2011; Greliche et al., 2012; Kulkarni et al., 2013; Tan et al., 2007), no study has demonstrated regulation of the HLA-DRB1 gene by imprinted or non-imprinted miRNAs yet. However, the potential for imprinted miRNAs to regulate HLA-DRB1 may

Please cite this article in press as: Ruhrmann, S., et al., Genomic imprinting: A missing piece of the Multiple Sclerosis puzzle? Int J Biochem Cell Biol (2015), http://dx.doi.org/10.1016/j.biocel.2015.05.010

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Table 1 MicroRNAs encoded in the imprinted gene clusters. Cluster

Gene

MMU (Mb)

HSA (Mb)

Gnas Sgce-Peg10 Copg2-Mest Snrpn-Snurf H19-Igf2 Rasgrf1 Dlk1-Dio3

Mir296, Mir298† Mir653, Mir489 Mir335†, Mir29a, Mir29b-1 Mir344(m) family Mir675, Mir483 Mir184 Mir770, Mir673(m/r), Mir493†, Mir337, Mir3544(m/r), Mir540(m/r), Mir665†, Mir3070-1(m), Mir3070-2(m), Mir431, Mir433, Mir127, Mir434(m/r), Mir432(h/m), Mir3071(m), Mir136*, Mir341(m/r), Mir1188(m/r), Mir370, Mir882(m), Mir379, Mir411, Mir299a, Mir299b, Mir380*, Mir1197(h/m), Mir323, Mir758, Mir329, Mir494*, Mir679(m/r), Mir1193, Mir666(m/r), Mir543*, Mir495, Mir667(m/r), Mir376c, Mir654(h/m), Mir376b, Mir376a, Mir300, Mir381, Mir487b, Mir539*, Mir544*, Mir382, Mir134, Mir668, Mir485*, Mir453(m), Mir154, Mir496a, Mir377, Mir541, Mir409, Mir412, Mir369, Mir410, Mir3072(m/r), Mir1247 Mir371a

2 (174.3) 6 (3.7) 6 (30.7–31.1) 7 (61.7–62.1) 7 (142.6) 9 (89.8) 12 (109.6–10.3)

20 (58.8) 7 (93.5) 7 (130.5–130.9) – 11 (2.0–2.1) 15 (79.2) 14 (100.8–101.1)

(NLRP2)

–

19 (53.8)

MicroRNAs indicated in bold are reported to be imprinted by minimum two out of the three databases of imprinted genes (http://www.mousebook.org/, http://www. Q4 geneimprint.com/, http://igc.otago.ac.nz/) and the imprinting status has been reviewed in detail elsewhere (Benetatos et al., 2013; Robson et al., 2012; Royo et al., 2006; Royo and Cavaille, 2008). Gene names and genomic information are given for mice (MMU) and humans (HSA) (miRBase, release 21, http://www.mirbase.org/) unless otherwise indicated. MiRNAs that do not exist in all three species are denoted with h, m and r in parenthesis that indicate humans, mice and rats, respectively. MiRNAs predicted to target the major MS genetic risk factor, HLA-DRB1, by >3 prediction tools, DIANA, miRanda, miRWalk and Targetscan, and additional miRNA predicted by TargetMiner are indicated with * and †, respectively.

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provide insight into the aforementioned parent-of-origin effects in MS. The largest cluster of imprinted miRNAs is encoded in the Dlk1 cluster highlighting the potential role of the Dlk1 cluster miRNAs in pathogenesis of inflammatory diseases. As previously mentioned, we found that the locus encompassing the Dlk1 cluster predisposes for EAE in rats in a parent-of-origin dependent manner (Stridh et al., 2014). Although our data point to Dlk1, we cannot rule out additional influence from the miRNA(s) in the cluster, especially since we found differences in the expression of several of them between EAE-resistant and EAE-susceptible strains after disease induction (Fig. 1B) (Bergman et al., 2013). Pathway analysis performed on the targets of miRNAs encoded in the anti-Rtl1 transcript in the Dlk1 cluster implicates regulation of multiple signaling cascades that are crucial in autoimmunity (Fig. 1C). In particular, there is enrichment of functions involved in proliferation and activation of T cells (Fig. 1C and D), which are known initiators of pathogenesis in EAE and MS (Comabella and Khoury, 2012). This is further consistent with previous studies showing enrichment of the predicted target of the miRNAs in the Dlk1 cluster in immune functions (Benetatos et al., 2013; Vinuesa et al., 2009). Undoubtedly, prediction of miRNA targets might result in overestimation given that some of the imprinted miRNAs or target mRNA might not be expressed in the relevant cell types or at the crucial time window during immune responses. Nevertheless, loss of imprinting at ICRs that control miRNAs expression has been suggested to affect other complex diseases (Girardot et al., 2012). For instance, a recent study has shown that the DLK1 miRNA cluster is highly expressed in human ␤-cells and involved in the control of ␤-cell apoptosis, but strongly repressed in islets from Type 2 Diabetes patients (Kameswaran et al., 2014). Repression of this miRNA cluster is strongly correlated with hypermethylation of one of the DMRs present in the locus. Thus, is likely that imprinted miRNAs can also contribute to pathogenesis of inflammatory diseases thereby extending the impact of parent-of-origin to non-imprinted transcripts.

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3.3. Interaction between imprinted and non-imprinted genes

434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468

471 472 473 474

The identification of mechanisms governing genomic imprinting has been instrumental in understanding basic concepts of parent-of-origin effects. Studies have recently highlighted coexpression of imprinted genes and suggested that seemingly

unrelated imprinted genes might belong to the same network called imprinted gene network (IGN). These IGNs have been further shown to comprise co-regulated imprinted genes together with biallelic non-imprinted genes in a temporal and spatial manner (Al Adhami et al., 2015; Andrade et al., 2010; Lui et al., 2008; Varrault et al., 2006). Interestingly, the investigation of the mechanisms underlying the IGNs has revealed that (i) different IGNs can be coordinated by the same master regulator in a context dependent manner, as it has been shown for Zac1/Plagl1 (Arima et al., 2005; Iglesias-Platas et al., 2014; Ribarska et al., 2014; Varrault et al., 2006) and (ii) IGNs can be governed by non-canonical pathways (distinct from classical imprinting control), e.g. by non-imprinting genes (Massah et al., 2014; Zacharek et al., 2011) or by loss of growth receptors (Boucher et al., 2014). Further work is needed to uncover which imprinted gene networks are invariant across all cell types and which subset of imprinted genes and biallelic gene networks are co-expressed only in specific cell types. This would reinforce the hypothesis of an alternative mechanism in which genes within an IGN cooperatively control a single biological process at the cellular level that could differ from the properties of imprinted genes at organismal level or across tissues (Prickett and Oakey, 2012). The description of IGNs emphasizes the importance of a network of interacting imprinted and non-imprinted genes over the influence of a single imprinted gene. This is further compatible with the recent evidence that non-imprinting genes can generate parent-of-origin effects by interacting with imprinted loci (Mott et al., 2014). It also raises the hypothesis that genes involved in inflammatory diseases, such as HLA-DRB1, might be part of an extend network of imprinted and biallelic genes which expressions are coordinated simultaneously upon specific immune dysregulation. The molecular mechanisms of parent-oforigin effects at the HLA-DRB1 gene in MS remain to be elucidated, and they could involve the action of imprinted ncRNA such as miRNAs (as discussed above), establishment of DMRs, binding of transcription factors or CTCF at specific regulatory sites, ultimately resulting in asymmetry between the two parental alleles. More generally, given that the monoallelic nature of imprinted genes renders them highly susceptible to genetic and epigenetic perturbations, disturbance of an IGN encompassing specific immune genes would potentially result in development of inflammatory disease in a parent-of-origin- and context-dependent manner.

Please cite this article in press as: Ruhrmann, S., et al., Genomic imprinting: A missing piece of the Multiple Sclerosis puzzle? Int J Biochem Cell Biol (2015), http://dx.doi.org/10.1016/j.biocel.2015.05.010

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References

Fig. 2. A hypothetical model explaining the role of parent-of-origin effects in Multiple Sclerosis and other complex diseases with similar etiologies. A well-recognized contribution of environmental factors and multiple (non-imprinted) genes to the etiology of Multiple Sclerosis might further be modulated by a contribution from genes that depend on parental origin and involve classically imprinted genes as well as non-imprinted genes that form networks with other imprinted genes. Abbreviations: IGN, imprinted gene network.

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4. Conclusions and future perspectives Parent-of-origin effects were until recently almost exclusively discussed in the context of classical diseases of genomic imprinting such as the Prader-Willi and Angelman syndromes but they are now receiving recognition in a wider range of diseases including complex inflammatory diseases such as MS. The potential of parent-of-origin effects to explain part of the ‘hidden’ heritability strengthens the need to take into account such effects in conventional studies. Although there is emerging evidence of the role of known imprinted genes like IGF2 and DLK1 in the development and function of the immune system, the molecular bases of parent-oforigin effects in inflammatory diseases remain to be elucidated. Recent data that suggest context-specific networks of co-regulated imprinted and non-imprinted genes that coordinate a given cellular function offer promising perspectives for understanding the parental contribution to complex diseases like MS, which would extend beyond the effect of a few imprinted genes (Fig. 2). Therefore, unveiling the mechanisms of parent-of-origin effects is likely to teach us not only about the etiology of complex diseases but also about the unknown roles of this fascinating phenomenon underlying uneven genetic contribution from our parents.

Funding This work was supported by grants from The Swedish Research Council, Harald and Greta Jeanssons Foundation; The Swedish Association for Persons with Neurological Disabilities; Åke Wibergs Foundation; Åke Löwnertz Foundation; Swedish Brain Foundation; Socialstyrelsen; Karolinska Institutets funds; Bibbi and Nils Jensens Foundation; and Söderbergs Foundation. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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