Differential miRNA expression in B cells is associated with inter-individual differences in humoral immune response to measles vaccination

Abstract

Background

MicroRNAs are important mediators of post-transcriptional regulation of gene expression through RNA degradation and translational repression, and are emerging biomarkers of immune system activation/response after vaccination.

Methods

We performed Next Generation Sequencing (mRNA-Seq) of intracellular miRNAs in measles virus-stimulated B and CD4+ T cells from high and low antibody responders to measles vaccine. Negative binomial generalized estimating equation (GEE) models were used for miRNA assessment and the DIANA tool was used for gene/target prediction and pathway enrichment analysis.

Results

We identified a set of B cell-specific miRNAs (e.g., miR-151a-5p, miR-223, miR-29, miR-15a-5p, miR-199a-3p, miR-103a, and miR-15a/16 cluster) and biological processes/pathways, including regulation of adherens junction proteins, Fc-receptor signaling pathway, phosphatidylinositol-mediated signaling pathway, growth factor signaling pathway/pathways, transcriptional regulation, apoptosis and virus-related processes, significantly associated with neutralizing antibody titers after measles vaccination. No CD4+ T cell-specific miRNA expression differences between high and low antibody responders were found.

Conclusion

Our study demonstrates that miRNA expression directly or indirectly influences humoral immunity to measles vaccination and suggests that B cell-specific miRNAs may serve as useful predictive biomarkers of vaccine humoral immune response.

About the Authors:

Iana H. Haralambieva

Roles Conceptualization, Data curation, Writing – original draft, Writing – review & editing

Affiliation: Mayo Clinic Vaccine Research Group, Mayo Clinic, Rochester, Minnesota, United States of America

Richard B. Kennedy

Roles Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing

Affiliation: Mayo Clinic Vaccine Research Group, Mayo Clinic, Rochester, Minnesota, United States of America

Whitney L. Simon

Roles Data curation, Writing – original draft

Affiliation: Mayo Clinic Vaccine Research Group, Mayo Clinic, Rochester, Minnesota, United States of America

Krista M. Goergen

Roles Formal analysis, Writing – original draft, Writing – review & editing

Affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

Diane E. Grill

Roles Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing

Affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

Inna G. Ovsyannikova

Roles Conceptualization, Data curation, Formal analysis, Writing – original draft, Writing – review & editing

Affiliation: Mayo Clinic Vaccine Research Group, Mayo Clinic, Rochester, Minnesota, United States of America

Gregory A. Poland

Roles Conceptualization, Funding acquisition, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation: Mayo Clinic Vaccine Research Group, Mayo Clinic, Rochester, Minnesota, United States of America

ORCID logo http://orcid.org/0000-0001-5057-4457

Introduction

Immune responses to vaccines (e.g., live measles vaccine) have a high degree of inter-individual variation, including poor/non-response, which eventually leads to an accumulation of susceptible individuals and subsequent disease outbreaks. Studies focusing on host genetic factors, transcriptional responses (differential gene expression upon measles virus exposure or in vitro viral stimulation), environmental, demographic and clinical variables, have tried to elucidate the mechanisms behind these variations in measles antibody titers. [1,2,3,4,5,6] Multiple studies in our laboratory have led to estimates that genetic factors (HLA alleles and common single nucleotide polymorphisms) only explain ~30% of the inter-individual variation in antibody titers after measles vaccination.[1] Novel high-dimensional technologies, omics assays, and vaccinomics/systems biology approaches [1] are increasingly being applied to vaccine studies in order to identify other biomarkers of protective and non-protective (low) vaccine-induced immune responses.

MicroRNAs (miRNA) have emerged as master regulators of RNA silencing and post-transcriptional modulation of gene expression. Over 1,000 miRNA species have been identified in the human genome, targeting more than 60% of the human genes. [7] miRNAs are small non-coding (21 to 23 nucleotides) sequences encoded in the intergenic regions or within introns/exons of genes. Functional miRNAs are produced from larger pre-miRNA transcripts (hairpins) cleaved in the cytoplasm by the endonuclease enzyme Dicer. One-strand miRNAs are assembled into the RNA-induced silencing complex (RISC), which binds to 3’ UTR sequences of target mRNA molecules with a sequence specificity provided by the miRNA component of the complex. This process results in RNA silencing through target mRNA cleavage, destabilization, or lower translation efficiency [8]. Each miRNA is able to control multiple (sometimes inter-related) genes and thus represents an important regulatory feature of the transcriptome. Dysregulated miRNA expression has been associated with various diseases and biological processes, including autoimmunity, and infectious diseases, immune function and viral replication. [8,9,10,11,12]

Expert opinion and the literature supports the importance of humoral immunity and neutralizing antibodies in protection against measles, and antibody titers above 120–200 mIU/ml have been accepted as a correlate of protection.[1, 2, 3, 4, 5, 6, 13, 14] Antigen-induced B cell differentiation with the help of CD4+ T cells is recognized as a key biological phenomenon underlying the formation of ASCs (and memory B cells) to mount a protective anti-viral humoral immune response. [13,14].

The goal of the current study was to characterize B and T-cell-specific miRNA profiles after in vitro measles virus stimulation in order to identify distinctive miRNAs—along with their targeted genes and pathways—that are associated with high (protective) and low (below the level of protection) neutralizing antibody titers following measles vaccination.

Methods

The methods described here are similar or identical to our previously published papers involving the described methodology and this cohort. [3,6,15,16,17,18,19,20]

Study subjects

Twenty-three subjects were selected for miRNA profiling from previously recruited subjects (3,191 healthy children/adolescents and young adults; 11–40 years old) who received two doses of MMRII vaccine. The demographic, clinical, and immune variables of this large cohort have been previously published. [6,15] The subjects for the current study were selected based on sample availability and extremes of neutralizing antibody titer (11 high antibody responders with a median titer of 2,055 mIU/mL, and 12 low antibody responders with a median titer of 246 mIU/mL). The currently accepted threshold for protection against symptomatic measles infection is a plaque reduction neutralization titer ≥120, corresponding to 210 mIU/mL in this study.[18]

The Institutional Review Boards of the Mayo Clinic (Rochester, MN) and the Naval Health Research Center (NHRC) (San Diego, CA) approved the study, and written informed consent was obtained from each subject (i.e., from age-appropriate participants, and the parents of all children who participated in the study).

Plaque reduction microneutralization assay (PRMN).

As previously published, measles virus (MV)-specific neutralizing antibody titers were measured using a high-throughput plaque-reduction microneutralization fluorescence-based assay with a coefficient of variation in our laboratory of 5.7%. [3,18] This assay quantifies all anti-measles virus neutralizing antibodies (i.e., both anti-H and anti-F antibodies). Karber’s formula was used to calculate the 50% neutralizing dose (ND50) and transformed into mIU/mL using the third international WHO anti-measles antibody standard. [18]

Cell purification and miRNA isolation

Cryopreserved PBMCs were thawed using standard procedures.[21] B cells and monocytes were purified using a human CD19 MicroBeads positive selection kit (Miltenyi Biotec; San Diego, CA) and a human CD14 MicroBeads positive selection kit (Miltenyi Biotec), respectively. B cells and monocytes cells were left uninfected, or were infected overnight with the Edmonston strain of MV at a multiplicity of infection 0.2. CD4+ T cells were isolated using the CD4+T Cell Isolation Kit (Miltenyi Biotec) and co-cultured overnight with or without MV-infected monocytes, after which the CD4+ T cell isolation was repeated (on the mixed cultures) to ensure that the T cell samples were not contaminated with monocytes. The purity of the cells was ascertained using flow cytometry. Total RNA (including miRNA) from B and T cells was extracted using miRNeasy Mini Kits (Qiagen; Valencia, CA) according to manufacturer’s instructions.

Next Generation Sequencing and Bioinformatics

Subjects were randomized prior to library preparation. Three subjects, each with four cell types/samples (unstimulated B cells, stimulated B cells, unstimulated CD4+ T cells and stimulated CD4+ T cells), were allocated to a single lane; therefore, lanes were balanced by cell type in addition to immune response status and sex. The quantity and quality of extracted RNA were assessed using an Agilent 2010 Bioanalyzer (Agilent; Palo Alto, CA). Illumina TruSeq miRNA library construction was performed at the Mayo Clinic Advanced Genomics Technology Center to generate small RNA libraries. Adapter sequences were ligated onto the 3' and 5' ends of each miRNA, and then the miRNA products were PCR-enriched and purified. Library validation and quantification was carried out using DNA 1000 Nano Chip kits on an Agilent 2100 Bioanalyzer (Agilent; Palo Alto, CA). Twelve samples were multiplexed in each lane. Libraries were loaded onto flow cell lanes and single-end read sequencing was performed using the Illumin HiSeq 2000 (Illumina; San Diego, CA), as described previously [3,6,22].

The Mayo Clinic Bioinformatics Systems Unit processed the FASTQ files using a comprehensive pre-processing and analytical pipeline (CAP-miRNA)[23] that assesses read quality (FastQC), trims adapter sequences (Cutadapt), and aligns reads for IGV viewing and detection of mature, precursor, and novel miRNAs (miRDeep2).[24]

Statistical analysis

B-cell samples and CD4+ T-cell samples were evaluated separately. Prior to normalization, mature miRNA was filtered using a median cutoff of 4, leaving 351 miRNAs available for the analysis of B-cell samples and 339 miRNAs for the analysis of CD4+ T-cell samples. Normalization was performed using the trimmed mean of M-values (TMM) normalization method [25] and was evaluated visually using boxplots and minus-versus-average plots. One CD4+ T-cell sample failed quality control and was removed from further analysis. Negative Binomial Generalized Estimating Equation (GEE) models [26], comparing stimulated versus unstimulated samples and stimulated high responders versus stimulated low responders, were run for each miRNA. Models were run in SAS using the proc genmod procedure, incorporating the TMM offset and Tagwise dispersion parameters estimates that were computed in R using the edgeR package.[27] Q-values were computed using the Storey and Tibshirani method (2003).[28]

The top miRNA results from the GEE models (q-value < 0.10) for B-cell interaction analysis (n = 14), B-cell overall analysis (n = 8), and CD4+ T-cell overall analysis (n = 15, cutoff at top 15 miRNA) were assessed using the DIANA pathway tool.[29] We analyzed Genes Union and Categories/Pathways Union methods for both KEGG and GO pathways using the default settings.

Results

Study subjects’ characterization

For this study, we used samples from 23 subjects representing the extremes of the neutralizing antibody response after measles vaccination (following two doses of MMR II vaccine) from a large study cohort. The median neutralizing antibody titer of the high antibody responders (n = 11) was 2,055 mIU/mL, while the median neutralizing antibody titer of the low antibody responders (n = 12) was 246 mIU/mL. All demographic and clinical/immune variables are presented in Table 1. Despite differences in vaccine-induced antibody titer, no statistically significant differences in other variables (including secretion of MV-specific Th1/Th2 and innate/inflammatory cytokines; and MV-specific IFNγ ELISPOT response) were noted between the two responder groups (Table 1).

[Figure omitted. See PDF.]

Table 1. Demographic and immune response variables of the study subject.

https://doi.org/10.1371/journal.pone.0191812.t001

miRNA expression in B and CD4+ T cells after in vitro MV stimulation

We first assessed miRNA expression in purified MV-stimulated B and CD4+ T cells irrespective of immune response status to measles vaccination (i.e., overall analysis in all samples to assess the effect of viral stimulation). The results (see S1 and S2 Tables) identify 10 and 329 miRNAs (q-value <0.2) for B and CD4+ T cells, respectively, that were significantly up/down-regulated upon MV stimulation. We observed five overlapping miRNAs that were significantly regulated in both B and CD4+ T cells (i.e., hsa-miR-409-3p, hsa-miR-543, hsa-miR-10b-5p, hsa-miR-7704, and hsa-miR-99b-5p). These differentially expressed miRNAs were found to regulate many common (for B and CD4+ T cells) biological pathways and processes, such as several signaling pathways, viral infection-associated processes, and processes related to regulation of transcriptional activity (S3 Table). In addition, some miRNAs were also found to regulate unique (for the examined cell subset) pathways/processes; for example, Toll-like receptors (TLRs) and TLR signaling pathway genes that were targeted by miRNAs in B cells after MV stimulation (S3 Table).

Specific B cell miRNAs are associated with neutralizing antibody titers after measles vaccination

We also evaluated lymphocyte-specific miRNAs demonstrating differences in expression between high and low antibody responders to measles vaccination (q-value < 0.2). Per-miRNA negative binomial GEE modeling was utilized to identify B cell-specific (and T cell-specific) miRNAs discriminating high from low antibody response. This yielded a group of 21 statistically significant miRNAs from B cells that were correlated with measles-specific neutralizing antibody titer after vaccination (p<0.017, q-value <0.2, Table 2). Although we found differential miRNA expression in CD4+ T cells upon MV stimulation (i.e., overall analysis in all samples), no CD4+ T cell-specific miRNA expression differences between high and low antibody responders were noted when we compared the two groups (q-value <0.2, S4 Table).

[Figure omitted. See PDF.]

Table 2. B cell-specific miRNAs demonstrating differences in expression between high and low antibody responders to measles vaccination (interaction analysis, q-value < 0.2).

https://doi.org/10.1371/journal.pone.0191812.t002

miRNA-modulated biological processes and pathways associated with neutralizing antibody response in high vs. low antibody responders to measles vaccination

Predicted targets of the B cell-specific miRNAs (demonstrating differences between high and low antibody responders) were identified (for miRNAs with q-value < 0.10, Table 2). Pathway-enrichment analysis identified GO/KEGG pathways, including Fc-receptor and several other signaling pathways, as well as pathways related to transcriptional regulation, viral infection, lipid biosynthesis/metabolism, cytoskeletal protein binding, extracellular matrix (ECM)-receptor interactions and apoptosis. The activity of those pathways is likely differentially regulated by miRNAs in B cells of high and low antibody vaccine responders (Table 3).

[Figure omitted. See PDF.]

Table 3. Immune function-related pathways/biological processes differentially regulated by MV response-specific miRNAs in B cells of high and low antibody vaccine responders.

https://doi.org/10.1371/journal.pone.0191812.t003

Discussion

MicroRNAs are important mediators of post-transcriptional regulation of gene expression through RNA degradation, translational repression, and other mechanisms. They have been demonstrated to regulate various immune functions and are plausible biomarkers of lymphocyte activation and infectious diseases pathogenesis, course and clinical outcome. [30,31,32,33] Several studies have provided evidence for altered miRNA expression in humans infected with influenza A/H1N1 and A/H3N2 viruses, HIV-1, VZV, HBV, and HCV. [33,34,35,36,37] Given the critical role of host miRNAs in the regulation of gene expression, antiviral response and immunity, miRNAs are emerging as important markers of responsiveness to vaccination (e.g., influenza and hepatitis B vaccination).[38, 39, 40] While we and others have identified specific gene-expression patterns during measles infection and/or vaccination and identified (gene) transcriptional signatures associated with antibody response after measles vaccination [3,4,5], intracellular and/or serum miRNAs have never been explored as factors influencing measles immunity. The results of the current study demonstrate that intracellular B cell-specific miRNA expression is associated with direct or indirect regulation of humoral immunity to measles vaccination.

The assessment of MV-stimulated miRNA expression in purified B and CD4+ T cells from vaccinees revealed several pathways/biological processes targeted by miRNAs in both cell types (e.g., transcriptional regulation, TGF-beta signaling pathway, epidermal and fibroblast growth factor receptor-signaling pathways, neurotrophin TRK receptor-signaling pathway, extracellular matrix (ECM)-receptor interactions, and viral infection processes). TGF-beta signaling pathway, for example, is an essential pathway in the maintenance of T and B cell homeostasis. It regulates T helper cell differentiation, the development of central memory, the response to antigenic stimulation, and is vital for regulatory T cell function. This pathway may also directly impact B cell expansion/homeostasis, immunoglobulin concentrations and antigen presentation.[41, 42] Thus, the observed MV-stimulated expression of miRNAs targeting this pathway in both B and CD4+ T cells of vaccinees is likely to impact adaptive immune function, although no miRNA expression differences (of these specific miRNAs) were found between the high and low antibody responder groups in our study. Of note, we observed virus-induced differential expression of miRNAs affecting multiple TLR signaling pathways in B cells, including the TLR2 signaling pathway, which is known to be activated by the MV hemagglutinin. [43]

Evaluation of intracellular miRNA expression differences between the high and the low antibody responder groups enabled us to identify of a set of B cell-specific miRNAs that were associated with neutralizing antibody response after measles vaccination (i.e., they were differentially expressed after MV stimulation in the B cells of high vs. low antibody responders). The top miRNA, miR-151a-5p, among other targets, regulates the expression of MT-CYB (mitochondrially encoded cytochrome b) and thus may regulate critical cellular function, such as the mitochondrial respiratory activity and ATP production. [44] Predicted gene targets of miR-151a-5p include NXF1 (involved in the regulation of gene expression of MHC class II molecules), TAPBP (TAP-binding protein involved in the assembly of MHC class I complex), RHOH (expressed in hematopoietic cells, regulator of cell growth and survival), EEF2 (the eukaryotic translation elongation factor 2), and five genes of the adherens junctions pathway (ACTB, IQGAP1, CTNNB1, INSR, and MAPK1). Although the adherens junction protein nectin-4 (NECTIN4/PVRL4), which is a recently identified epithelial receptor for MV [45,46], was not found to be regulated by the identified set of miRNAs, it is likely that adherens junction proteins, extracellular matrix-receptor interactions (highlighted pathway in Table 3), and the adhesion and regulation of the cytoskeleton are important biological processes involved in MV infection and measles immunity. In support of this, three other B-cell miRNAs associated with vaccine-induced antibody titers (Table 2) were found to target the gene expression of nectins (miR-15a-5p of PVRL1, PVRL2 and PVRL3, miR-199a-3p of PVRL3, and miR-103a-3p of PVRL1 and PVRL2). The differential regulation of miR199a, for example, has been reported during hepatitis C infection and is associated with pathogenicity, and in addition, miR199a has been found to inhibit viral replication of some herpesviruses and alphaviruses. [33,34,35,36,37,47] Other interesting miRNAs include the following: miR-223, which is implicated primarily in the regulation of granulocyte, erythrocyte, and NK-cell development/function (e.g., GZMB is a direct target of miR-223) and in HIV-1 infection [48,49,50]; the miR-15a/16 cluster, which targets pro-apoptotic genes and apoptosis regulators (BCL2) that are key for cell-cycle regulation and apoptosis in B cells [51,52]; and miR-29/29c, a critical factor in the regulation of virus-induced apoptosis and innate immunity to influenza A/H1N1 and A/H3N2 through targeting BCL2L2, DNMT, COX2 activity, IFN-alpha receptor (IFNAR1) and the Jak/STAT signaling pathway. [35,47,53] Mir-29 has also been reported to target and downregulate the viral Nef protein expression during HIV-1 infection. [33,34,35,36,37] In addition, enriched pathways and processes with relevance to adaptive immunity (that are regulated by the identified set of B-cell miRNAs) include the Fc-receptor signaling pathway, the phosphatidylinositol-mediated signaling pathway, growth factor signaling pathways, transcriptional regulation activity, apoptosis, metabolism, and virus-related processes. The differential activation of signaling pathways by different Fc receptors, for example, is known to promote a wide variety of immune cellular functions and is closely involved in immune regulation. [54]

The strengths of our study include the use of purified cell populations from subjects with the extremes of antibody response (high and low antibody response to measles vaccine) and the use of a new technology/analysis not previously applied to measles (first miRNA study on measles vaccine) to assess immunity after vaccination. Limitations include the relatively small sample size (n = 23) and the lack of replication and/or functional validation of identified gene targets and pathways that warrant further exploration. Further functional studies (e.g., RISC-Seq) are needed to identify/validate suggested miRNA targets and the cellular processes and functions regulated by vaccine/virus-induced miRNAs. [55] The overall assessment of miRNA expression in MV-stimulated T and B cells irrespective of immune response status (overall analysis, S1 and S2 Tables) yielded the identification of more T cell-specific miRNAs than B cell-specific miRNAs. However, as noted, no CD4+ T cell-specific miRNA expression differences between high and low antibody responders were found (i.e., only B cell-specific miRNA expression differences were identified) when we compared the two groups. This could be related to the relatively small sample size and/or to the fact that the groups were selected based on antibody response (and not MV-specific cellular immune response), which is directly related to biological processes and pathways regulated in B cells. To differentiate the measles virus-specific miRNA expression from the miRNA expression specific to other components of the MMR vaccine (i.e., mumps and rubella), we used measles virus in vitro stimulation of purified B and T cells from vaccinees. While this study design may not fully recapitulate miRNA regulation in vivo after MMR vaccination, no practical method exists to administer measles vaccine alone in the US. Regardless the listed limitations, the biologic plausibility of the identified targets and pathways in regards to humoral immunity, and the lack of any other pre-existing studies in this area, all increase the importance of disseminating these findings.

In conclusion, our study provides new knowledge on vaccine-induced immune function and modulation of immune response via miRNA regulation of gene expression. We identified B cell-specific miRNAs that are likely regulating humoral immunity after measles vaccination, which may explain (in part) inter-individual variations in antibody response. These miRNAs, in concert with their gene targets and/or other measles-specific transcriptomic [3,18] and immunogenetic [1,2,3,4,5,6] signatures, could potentially serve as predictive biomarkers of measles vaccine antibody response.

Supporting information

[Figure omitted. See PDF.]

S1 Table. miRNA expression in MV-stimulated B cells irrespective of immune response status (i.e., overall analysis in all samples, q<0.2).

https://doi.org/10.1371/journal.pone.0191812.s001

(DOCX)

S2 Table. miRNA expression in MV-stimulated CD4+ T cells irrespective of immune response status (i.e., overall analysis in all samples, q<0.2).

https://doi.org/10.1371/journal.pone.0191812.s002

(DOCX)

S3 Table. Pathways and biological processes differentially regulated upon stimulation with MV in B cells or CD4+ T cells (overall analysis in all samples).

https://doi.org/10.1371/journal.pone.0191812.s003

(DOCX)

S4 Table. CD4+ T cell-specific miRNA expression differences between high and low antibody responders to measles vaccination (no significant differences were noted, top 10 miRNAs are listed).

https://doi.org/10.1371/journal.pone.0191812.s004

(DOCX)

Acknowledgments

We thank the Mayo Clinic Vaccine Research Group staff and the study participants. We thank Caroline L. Vitse for her editorial assistance with this manuscript.

Citation: Haralambieva IH, Kennedy RB, Simon WL, Goergen KM, Grill DE, Ovsyannikova IG, et al. (2018) Differential miRNA expression in B cells is associated with inter-individual differences in humoral immune response to measles vaccination. PLoS ONE 13(1): e0191812. https://doi.org/10.1371/journal.pone.0191812

References

1. Haralambieva IH, Kennedy RB, Ovsyannikova IG, Whitaker JA, Poland GA (2015) Variability in Humoral Immunity to Measles Vaccine: New Developments. Trends Molec Med 21: 789–801.

2. Haralambieva IH, Ovsyannikova IG, Pankratz VS, Kennedy RB, Jacobson RM, Poland GA (2013) The genetic basis for interindividual immune response variation to measles vaccine: new understanding and new vaccine approaches. Exp Rev Vaccines 12: 57–70.

3. Haralambieva IH, Zimmermann MT, Ovsyannikova IG, Grill DE, Oberg AL, Kennedy RB, et al. (2016) Whole Transcriptome Profiling Identifies CD93 and Other Plasma Cell Survival Factor Genes Associated with Measles-Specific Antibody Response after Vaccination. PLos ONE 11: e0160970. pmid:27529750

4. Zilliox MJ, Moss WJ, Griffin DE (2007) Gene expression changes in peripheral blood mononuclear cells during measles virus infection. Clin Vaccine Immunol 14: 918–923. pmid:17538120

5. Zilliox MJ, Parmigiani G, Griffin DE (2006) Gene expression patterns in dendritic cells infected with measles virus compared with other pathogens. Proc Natl Acad Sci USA 103: 3363–3368. pmid:16492729

6. Haralambieva IH, Ovsyannikova IG, Kennedy RB, Larrabee BR, Zimmermann MT, Grill DE, et al. (2017) Genome-Wide Associations of CD46 and IFI44L Genetic Variants with Neutralizing Antibody Response to Measles Vaccine. Human Genet 136: 421–435.

7. Hogg DR, Harries LW (2014) Human genetic variation and its effect on miRNA biogenesis, activity and function. Biochem Soc Trans 42: 1184–1189. pmid:25110023

8. Gracias DT, Katsikis PD (2011) MicroRNAs: key components of immune regulation. Adv Exp Med Biol 780: 15–26. pmid:21842361

9. Turner ML, Schnorfeil FM, Brocker T (2011) MicroRNAs regulate dendritic cell differentiation and function. J Immunol 187: 3911–3917. pmid:21969315

10. Zhan Y, Wu L (2012) Functional regulation of monocyte-derived dendritic cells by microRNAs. Protein Cell 3: 497–507. pmid:22773340

11. Gottwein E, Cullen BR (2008) Viral and cellular microRNAs as determinants of viral pathogenesis and immunity. Cell Host Microbe 3: 375–387. pmid:18541214

12. Ding SW, Lu R (2011) Virus-derived siRNAs and piRNAs in immunity and pathogenesis. Curr Opin Virol 1: 533–544. pmid:22180767

13. Bouche FB, Ertl OT, Muller CP (2002) Neutralizing B cell response in measles. Viral Immunol 15: 451–471. pmid:12479395

14. de Vries RD, de Swart RL (2012) Evaluating measles vaccines: can we assess cellular immunity? Exp Rev Vaccines 11: 779–782.

15. Voigt EA, Ovsyannikova IG, Haralambieva IH, Kennedy RB, Larrabee BR, Schaid DJ, et al. (2016) Genetically defined race, but not sex, is associated with higher humoral and cellular immune responses to measles vaccination. Vaccine 34: 4913–4919. pmid:27591105

16. Lambert ND, Haralambieva IH, Kennedy RB, Ovsyannikova IG, Pankrantz VS, Poland GA (2015) Polymorphisms in HLA-DPB1 are associated with differences in rubella-specific humoral immunity after vaccination. J Infect Dis 211: 898–905.

17. Kennedy RB, Ovsyannikova IG, Haralambieva IH, Lambert ND, Pankratz VS, Poland GA (2014) Genetic polymorphisms associated with rubella virus-specific cellular immunity following MMR vaccination. Human Genet 133: 1407–1417.

18. Haralambieva IH, Ovsyannikova IG, O'Byrne M, Pankratz VS, Jacobson RM, Poland GA (2011) A large observational study to concurrently assess persistence of measles specific B-cell and T-cell immunity in individuals following two doses of MMR vaccine. Vaccine 29: 4485–4491. pmid:21539880

19. Haralambieva IH, Ovsyannikova IG, Kennedy RB, Vierkant RA, Pankratz SV, Jacobson RM, et al. (2011) Associations between single nucleotide polymorphisms and haplotypes in cytokine and cytokine receptor genes and immunity to measles vaccination. Vaccine 29: 7883–7895. pmid:21875636

20. Haralambieva IH, Ovsyannikova IG, Umlauf BJ, Vierkant RA, Pankratz SV, Jacobson RM, et al. (2011) Genetic polymorphisms in host antiviral genes: associations with humoral and cellular immunity to measles vaccine. Vaccine 29: 8988–8997. pmid:21939710

21. Umlauf BJ, Haralambieva IH, Ovsyannikova IG, Kennedy RB, Pankratz VS, Jacobson RM, et al. (2012) Associations between demographic variables and multiple measles-specific innate and cell-mediated immune responses after measles vaccination. Viral Immunol 25: 29–36. pmid:22239234

22. Ovsyannikova IG, Salk HM, Kennedy RB, Haralambieva IH, Zimmermann MT, Grill DE, et al. (2016) Gene signatures associated with adaptive humoral immunity following seasonal influenza A/H1N1 vaccination. Genes Immun 17: 371–379. pmid:27534615

23. Sun Z, Evans J, Bhagwate A, Middha S, Bockol M, Yan H, et al. (2014) CAP-miRSeq: a comprehensive analysis pipeline for microRNA sequencing data. BMC Genomics 15: 423. pmid:24894665

24. Friedlander MR, Mackowiak SD, Li N, Chen W, Rajewsky N (2012) miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res 40: 37–52. pmid:21911355

25. Robinson MD, Oshlack A (2010) A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol 11: R25. pmid:20196867

26. Zeger SL, Liang KY (1986) Longitudinal data analysis for discrete and continuous outcomes. Biometrics 42: 121–130. pmid:3719049

27. Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26: 139–140. pmid:19910308

28. Storey JD, Tibshirani R (2003) Statistical significance for genomewide studies. Proc Natl Acad Sci U S A 100: 9440–9445. pmid:12883005

29. Vlachos IS, Zagganas K, Paraskevopoulou MD, Georgakilas G, Karagkouni D, Vergoulis T, et al. (2015) DIANA-miRPath v3.0: deciphering microRNA function with experimental support. Nucleic Acids Res 43: W460–466. pmid:25977294

30. de Candia P, Torri A, Pagani M, Abrignani S (2014) Serum microRNAs as Biomarkers of Human Lymphocyte Activation in Health and Disease. Frontiers Immunol 5: 43.

31. Zan H, Casali P (2015) Epigenetics of Peripheral B-Cell Differentiation and the Antibody Response. Frontiers Immunol 6: 631.

32. Correia CN, Nalpas NC, McLoughlin KE, Browne JA, Gordon SV, MacHugh DE, et al. (2017) Circulating microRNAs as Potential Biomarkers of Infectious Disease. Frontiers Immunol 8: 118.

33. Verma P, Pandey RK, Prajapati P, Prajapati VK (2016) Circulating MicroRNAs: Potential and Emerging Biomarkers for Diagnosis of Human Infectious Diseases. Frontiers Microbiol 7: 1274.

34. Tambyah PA, Sepramaniam S, Mohamed Ali J, Chai SC, Swaminathan P, Armugam A, et al. (2013) microRNAs in circulation are altered in response to influenza A virus infection in humans. PLos ONE 8: e76811. pmid:24116168

35. Ma Y, Ouyang J, Wei J, Maarouf M, Chen JL (2016) Involvement of Host Non-Coding RNAs in the Pathogenesis of the Influenza Virus. Intl J Molec Sci 18.

36. Qi Y, Zhu Z, Shi Z, Ge Y, Zhao K, Zhou M, et al. (2014) Dysregulated microRNA expression in serum of non-vaccinated children with varicella. Viruses 6: 1823–1836. pmid:24759212

37. Egana-Gorrono L, Escriba T, Boulanger N, Guardo AC, Leon A, Bargallo ME, et al. (2014) Differential microRNA expression profile between stimulated PBMCs from HIV-1 infected elite controllers and viremic progressors. PLos ONE 9: e106360. pmid:25225963

38. Nakaya HI, Hagan T, Duraisingham SS, Lee EK, Kwissa M, Rouphael N, et al. (2015) Systems Analysis of Immunity to Influenza Vaccination across Multiple Years and in Diverse Populations Reveals Shared Molecular Signatures. Immunity 43: 1186–1198. pmid:26682988

39. de Candia P, Torri A, Gorletta T, Fedeli M, Bulgheroni E, Cheroni C, et al. (2013) Intracellular modulation, extracellular disposal and serum increase of MiR-150 mark lymphocyte activation. PLos ONE 8: e75348. pmid:24205408

40. Xiong Y, Chen S, Liu L, Zhao Y, Lin W, Ni J (2013) Increased serum microRNA-155 level associated with nonresponsiveness to hepatitis B vaccine. Clin Vaccine Immunol 20: 1089–1091. pmid:23637039

41. Kelly A, Houston SA, Sherwood E, Casulli J, Travis MA (2017) Regulation of Innate and Adaptive Immunity by TGFbeta. Advances Immunol 134: 137–233.

42. Gorelik L, Flavell RA (2002) Transforming growth factor-beta in T-cell biology. Nature Rev Immunol 2: 46–53.

43. Bieback K, Lien E, Klagge IM, Avota E, Schneider-Schaulies J, Duprex WP, et al. (2002) Hemagglutinin protein of wild-type measles virus activates toll-like receptor 2 signaling. J Virol 76: 8729–8736. pmid:12163593

44. Zhou R, Wang R, Qin Y, Ji J, Xu M, Wu W, et al. (2015) Mitochondria-related miR-151a-5p reduces cellular ATP production by targeting CYTB in asthenozoospermia. Sci Rep 5: 17743. pmid:26626315

45. Muhlebach MD, Mateo M, Sinn PL, Prufer S, Uhlig KM, Leonard VH, et al. (2011) Adherens junction protein nectin-4 is the epithelial receptor for measles virus. Nature 480: 530–533. pmid:22048310

46. Noyce RS, Bondre DG, Ha MN, Lin LT, Sisson G, Tsao MS, et al. (2011) Tumor Cell Marker PVRL4 (Nectin 4) Is an Epithelial Cell Receptor for Measles Virus. PLoS Pathog 7: e1002240. pmid:21901103

47. Bruscella P, Bottini S, Baudesson C, Pawlotsky JM, Feray C, Trabucchi M (2017) Viruses and miRNAs: More Friends than Foes. Frontiers Microbiol 8: 824.

48. Fehniger TA, Wylie T, Germino E, Leong JW, Magrini VJ, Koul S, et al. (2010) Next-generation sequencing identifies the natural killer cell microRNA transcriptome. Genome Res 20: 1590–1604. pmid:20935160

49. Merkerova M, Belickova M, Bruchova H (2008) Differential expression of microRNAs in hematopoietic cell lineages. Eur J Haematol 81: 304–310. pmid:18573170

50. Johnnidis JB, Harris MH, Wheeler RT, Stehling-Sun S, Lam MH, Kirak O, et al. (2008) Regulation of progenitor cell proliferation and granulocyte function by microRNA-223. Nature 451: 1125–1129. pmid:18278031

51. Cimmino A, Calin GA, Fabbri M, Iorio MV, Ferracin M, Shimizu M, et al. (2005) miR-15 and miR-16 induce apoptosis by targeting BCL2. Proc Natl Acad Sci USA 102: 13944–13949. pmid:16166262

52. Aqeilan RI, Calin GA, Croce CM (2010) miR-15a and miR-16-1 in cancer: discovery, function and future perspectives. Cell Death Differ 17: 215–220. pmid:19498445

53. Fang J, Hao Q, Liu L, Li Y, Wu J, Huo X, et al. (2012) Epigenetic changes mediated by microRNA miR29 activate cyclooxygenase 2 and lambda-1 interferon production during viral infection. J Virol 86: 1010–1020. pmid:22072783

54. Rosales C (2017) Fcgamma Receptor Heterogeneity in Leukocyte Functional Responses. Frontiers Immunol 8: 280.

55. Matkovich SJ, Van Booven DJ, Eschenbacher WH, Dorn GW 2nd (2011) RISC RNA sequencing for context-specific identification of in vivo microRNA targets. Circ Res 108: 18–26. pmid:21030712