Literature DB >> 31846480

Primary Epstein-Barr virus infection with and without infectious mononucleosis.

Klaus Rostgaard1, Henry H Balfour2,3, Ruth Jarrett4, Christian Erikstrup5, Ole Pedersen6, Henrik Ullum7, Lars Peter Nielsen8, Marianne Voldstedlund9, Henrik Hjalgrim1,10.   

Abstract

BACKGROUND: Infectious mononucleosis (IM) is a common adverse presentation of primary infection with Epstein-Barr virus (EBV) in adolescence and later, but is rarely recognized in early childhood where primary EBV infection commonly occurs. It is not known what triggers IM, and also not why IM risk upon primary EBV infection (IM attack rate) seemingly varies between children and adolescents. IM symptoms may be severe and persist for a long time. IM also markedly elevates the risk of Hodgkin lymphoma and multiple sclerosis for unknown reasons. The way IM occurrence depends on age and sex is incompletely described and hard to interpret etiologically, because it depends on three quantities that are not readily observable: the prevalence of EBV-naϊve persons, the hazard rate of seroconverting and the attack rate, i.e. the fraction of primary EBV infections that is accompanied by IM. We therefore aimed to provide these quantities indirectly, to obtain epidemiologically interpretable measures of the dynamics of IM occurrence to provide etiological clues. METHODS AND
FINDINGS: We used joint modeling of EBV prevalence and IM occurrence data to provide detailed sex- and age-specific EBV infection rates and IM attack rates and derivatives thereof for a target population of all Danes age 0-29 years in 2006-2011. We demonstrate for the first time that IM attack rates increase dramatically rather precisely in conjunction to typical ages of puberty onset. The shape of the seroconversion hazard rate for children and teenagers confirmed a priori expectations and underlined the importance of what happens at age 0-2 years. The cumulative risk of IM before age 30 years was 13.3% for males and 22.4% for females. IM is likely to become more common through delaying EBV infection in years to come.
CONCLUSIONS: The change in attack rate at typical ages of puberty onset suggests that the immunologic response to EBV drastically changes over a relatively short age-span. We speculate that these changes are an integrated part of normal sexual maturation. Our findings may inform further etiologic research into EBV-related diseases and vaccine design. Our methodology is applicable to the epidemiological study of any infectious agent that establishes a persistent infection in the host and the sequelae thereof.

Entities:  

Mesh:

Year:  2019        PMID: 31846480      PMCID: PMC6917282          DOI: 10.1371/journal.pone.0226436

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Most people are infected with Epstein-Barr virus (EBV) during childhood or adolescence, resulting in a persistent, mostly latent EBV infection. The primary EBV infection often manifests as infectious mononucleosis (IM), especially in adolescence [1,2]. Globally EBV is causally linked to nearly 200000 incident cancers and 18000 deaths from multiple sclerosis annually [3,4], with IM elevating the risk of Hodgkin lymphoma and multiple sclerosis for unknown reasons [5-7]. Functions of EBV antibody levels as predictors of disease risk is an active field of research, see [8] and references therein. At the same time it is unclear why upon primary EBV infection some individuals present with IM, while others do not [9]. Disease severity and duration correlate much better with e.g. CD8+ cell counts than with the viral kinetics itself and the expansion of the CD8+ cell count is controlled in asymptomatic EBV infection despite virus loads similar to those experienced in symptomatic EBV infection [1,2,10-14]. Hence current understanding suggests that IM is caused by overreaction by the immune system, rather than EBV infection per se (viremia or B-cell expansion). There now seems to be broad agreement that a massive expansion of the number of EBV-specific CD8+ cells is a characteristic of IM, while changes in the proportions of other cell populations seem less well-established [1,2,10-13,15,16]. Clinically, IM is typically characterized by fever, pharyngitis, lymphadenopathy and fatigue. The IM symptoms are believed to be caused mostly, if not entirely by the exaggerated CD8+ response [2,15,16]. Presumably IM is the same disease in teenagers as in children, because the immunological response to EBV infection is recognizably the same [10,17]. The way IM occurrence depends on age and sex is incompletely described and hard to interpret etiologically. The age distribution of incident IM is dominated by a distinct peak in the middle of the teenage years [18,19]. However, as an etiological clue this is not particularly useful because the depicted rate is not really a rate, i.e. a number of IM cases divided by the time at risk of those who have not seroconverted. Rather it is a product of the prevalence of EBV-naϊve persons, the hazard rate of seroconverting and the attack rate, i.e. the fraction of primary EBV infections that is accompanied by IM. Attack rates have only been estimated in young adults [20-23], and estimated sero-conversion rates are practically non-existent too. It would therefore be valuable to devise and fit a mathematically coherent model, projecting what would be the age- and sex-specific seroconversion rate and attack rate in a hypothetical population where the observed age- and sex-specific EBV-prevalence and IM occurrence in the target population apply. Such a model could quantify e.g. how much of the IM teenage peak is due to changed behavior (changing hazard of seroconversion), and how much to changed susceptibility to IM (changing attack rate) in teenagers compared with pre-adolescents. As proof of concept we therefore fitted such a model based on a few large data sets, with Danes age 0–29 years in 2006–2011 as our target population.

Methods

Materials

We used the Danish Civil Registration System [24] to follow-up persons while resident in Denmark in 2006–2011 and of age 0–29 years for incident IM in NPR. Incident IM in the Danish National Patient Register (NPR) [25] for a person was defined as the first hospital contact with IM as main, secondary, or underlying diagnosis, classified as code 075* in ICD-8 and code B27* in ICD-10 [19,26]. In 2010 and 2011 the Danish Blood Donor Study (DBDS) [27] asked participants:”Were you ever told by a doctor that you had infectious mononucleosis” and if so–”At what age?”. The study base of IM cases from DBDS was defined as DBDS participants who either 1) had reported IM in 2006–2011 at age 0–29 years or 2) had reported IM at age 0–14 years or 3) were IM cases in NPR at age 0–29 years at time of DBDS interview and born in 1976+. We then searched for these persons as IM cases in the NPR. Criterion 2) ensures that we can estimate IM hospitalization rates at age 0–17 years (donors must be 18+ years at interview) and criterion 3) makes a hospital diagnosis of IM equally valid as one proclaimed by a general practitioner. EBV test results recorded in the Laboratory Information Management System of Statens Serum Institut, Copenhagen, Denmark were mapped into positive and negative results as in Rostgaard et al [19]. The first result was retrieved for all persons serologically tested for primary EBV infection from January 2005 to May 2011. The serological test was based on measurements of IgG antibody titers to EBV nuclear antigen (EBNA) and IgG and IgM antibody titers to EBV capsid antigen (VCA). All measurements were performed using enzyme-linked immunosorbent assay (Biotest, BioNordika, Herlev, Denmark). Each test result was coded as 1)”prior infection” if EBNA was positive, 2)”positive” if VCA IgG or VCA IgM were”positive” or”weak” while at the same time EBNA was”negative” or”weak” and 3)”negative” if VCA IgG, VCA IgM and EBNA were all”negative”. Any test result that did not match any of these three disjoint criteria was discarded [19]. The test results were obtained from analyzing test samples sent from hospitals and general practitioners from all parts of Denmark, but predominantly from Sealand [19]. For convenience we used a discrete survival model and hence lumped age into 61-day intervals denoted by a = 0,1,2,…,179, a = 180 ≈ 30 years. The data were aggregated accordingly. In order to obey a data discretionary rule of at least 5 observations in a cell, the data were sorted by type, sex and age and cells then aggregated on a running basis to fulfil this criterion, the age interval denoted by the rounded mean of a. The data were used in that form and are available in . We did not use data from the first year of life due to the maternally-derived EBV sero-positivity shortly after birth [17,28].

Statistical methods

The statistical framework for this paper is a Markov model with the following states (see pages 1–25 and 457–475 in [29]): 0: EBV negative 1: EBV positive, no history of IM 2: EBV positive, a history of IM We describe the dynamics of the system only in terms of age a and sex s. Let S(a,s) be the sex- and age-specific probability of being in state 0. Let the probability of moving from state 0 to state 1 or state 2 be f(a,s) and f(a,s), respectively. These are expressed in terms of the probability of being at risk in state 0, S(a-1,s), the probability of moving out of state 0 if in that state, (1+exp(-ε(a))) and the probability of presenting with IM upon seroconversion, P(a,s) = (1+exp(-ϊ(a))), i.e. f(a,s) = (1-P(a,s))(1+exp(-ε(a)))S(a-1,s) and f(a,s) = P(a,s)(1+exp(-ε(a)))S(a-1,s). Let the probability of hospitalized IM among IM cases in DBDS be P(a,s) = (1+exp(-ν(a))). Let p0, p1 and p2 be shorthand for the probability of being in state 0, 1, and 2. Similarly let imfrac and hospfrac be shorthand for the probability of IM upon seroconversion and hospitalization upon having IM. The model was fitted using SAS proc HPNLMOD. The functions ε(a), and ν(a) were modeled as fractional polynomials of degree 4 and 2, with power sets (-1,0,0.5,1) and (2,1), respectively (see pages 77–98 in [30]). Thus ν(a) was a second degree polynomial in a. These fractional polynomials sufficed to provide an adequate fit, according to goodness-of-fit tests and inspection of residuals. Preliminary analyses revealed that ϊ(a) were complicated functions, requiring 8–12 degrees of freedom for an adequate fit. The functions ϊ(a) were modeled as restricted cubic splines (see pages 20–24 in [31]). The knots for the splines were common for the sexes and at the outset placed at deciles of the number of IM events in NPR. We then added knots at the 2.5, 5 and 7.5 percentile to obtain a satisfactory fit also in a region with few IM cases but much change in seroconversion rates. imfrac did not look as expected in the tail and very different between the sexes. We considered this to be a consequence of model uncertainty regarding the post-teenage years in combination with the notorious wigglyness of high-dimensional splines. To remedy this we therefore removed the two top knots, retaining an adequate model fit according to goodness-of-fit tests. Finally we fixed ϊ(a) to be constant above the new top knot, at the cost of an increase in deviance of 2.5–3 in each sex in order to remove unrealistic decreasing trends above the top knot. The link between model and data was provided by the following contributions to the model log-likelihood (ll): for EBV prevalence data with POS positives among N tested: ll = POS*log(p1+p2)+(N-POS)*log(p0) for DBDS data with POS hospitalized among N IM cases: ll = POS*log(hospfrac)+(N-POS)*log(1-hospfrac) for NPR data with EVENTS IM cases in PYRS person-years at risk: ll = EVENTS*log(him)-him*PYRS where him = 6*imfrac/((1+exp(-ϊ))*(1+exp(-ν)))*p0/(p0+p1)/0.9 The construction of most of the graphs in Fig 1 from quantities described here is immediate. The seroconversion hazard rate in Fig 1C is 6/(1+exp(-ε(a))) events per person-year.
Fig 1

Model predictions with 95% confidence limits by age for females (red) and males (blue). The model was created from jointly fitting C, D, E; the results in B, F, G and H were derived from this. The flat attack rate above age 18 years in subgraph D is a self-imposed model constraint, see Methods. Subgraph A is the EBV-seroprevalence by age in Denmark in 2006–2011. The dotted line was predicted from the model.

Model predictions with 95% confidence limits by age for females (red) and males (blue). The model was created from jointly fitting C, D, E; the results in B, F, G and H were derived from this. The flat attack rate above age 18 years in subgraph D is a self-imposed model constraint, see Methods. Subgraph A is the EBV-seroprevalence by age in Denmark in 2006–2011. The dotted line was predicted from the model.

Assumptions

We assume that all persons start in state 0 at birth, i.e. we ignore that EBV can pass across the placenta during pregnancy [32]. Death, emigration etc is considered non-informative censoring. The incubation time of around 42 days [12] from EBV infection to possibly overt IM is ignored. Since they are few, and not directly identifiable, we have not created a special state for persons who will remain EBV-negative [33,34], e.g. due to lack of the EBV receptor CD21 on B-cells [33]. Similarly, states 1 and 2 are absorbing, so we do not allow alternation between susceptible and non-susceptible states, suggested as possible by Helminen et al. [34], nor do we allow multiple EBV infections where the first did not cause IM, but one of the later did, i.e. we assume that once a latent EBV infection is established you cannot get IM caused by EBV. We assume that a person can have IM only once, e.g. that a person cannot have a second IM caused by e.g. cytomegalovirus. The data on IM incidence will usually be exaggerated due to lack of proper laboratory confirmation of EBV involvement in IM-like disease symptoms. Part of the problem is that only 90% of true IM is caused by EBV [35], that is the 0.9 in the expression for 'him' above.

Miscellanea

The risk of getting IM before age 30 years was calculated as 1-exp(-H(a)), where H(a) is the cumulative population IM incidence rate at age a, i.e. the integral of the curves shown in Fig 1F. Estimates and confidence limits as presented in the figures were calculated from the predict logic of SAS proc HPNLMOD. In these calculations the leading coefficient of ν(a) was fixed to avoid inexplicable variance inflation in Fig 1H. The variance estimates in the other graphs were essentially unaltered by this fix. All statistical calculations were performed using SAS statistical software (SAS Institute, Cary, NC. version 9.4). The study was approved by the institutional review board of Statens Serum Institut and the Scientific Ethics Committee Central Denmark (M2009237). As such it adheres to Danish law, including the European Union General Data Protection Regulation and is conducted according to the principles expressed in the Declaration of Helsinki. Written informed consent was obtained at enrollment into the DBDS[27], while specific informed consent for use of the other (register) data sources in this study was not needed according to Danish law.

Results

All Danes age 0–29 years resident in Denmark somewhen during calendar years 2006–2011, in all 2,485,292 persons, were followed up in the same age and period range for a hospital contact with an IM diagnosis during 11,376,713 person-years of follow-up, yielding 4703 incidents of hospitalized IM. 2487 blood donors from The Danish Blood Donor Study, who had self-reported IM or had been hospitalized with IM under the right conditions (age and period, see Methods) were assessed for hospitalized IM to yield the fraction of hospitalized IM among IM cases (185/2487 = 7% of IM cases). 6145 persons tested for EBV antibodies at Statens Serum Institut at age 0–29 years during calendar years 2006–2011 yielded 3513 (57%) infected with EBV. The three statistically sufficient data sets for these three outcomes and the only data sets used for our analyses are available in , labelled in the type variable as NPR, DBDS and EBVPREV, respectively. The results of our modeling are a set of age- and sex-specific predictions, presented in Fig 1A–1H, and the same predictions in a slightly aggregated life-table format in Table 1, with columns labelled B to H. Throughout we shall only refer to the figures, the reader may consult the relevant columns of the table instead.
Table 1

Model predictions by age and sex.

Prevalent cases per 100,000 cases (B), events per 100,000 person-years (C,F,G,H) and probability x 100,000 (D,E). B: EBV naive, C: seroconversion hazard rate, D: attack rate, E: fraction of hospitalized IM cases, F: IM population hazard rate, G: seroconversion population hazard rate and H: hospitalized IM population hazard rate. C-H are averages within the age group, B is the maximum within the age group, i.e. who were EBV-naïve at exact age 1,2,…Refer to Fig 1 and methods for further details.

BCDEFGH
agemfmfmfmfmfmfmf
1915208276524843201572614204910627478526020646156982517
27326070853717445021301157841541233646349513831452611
369067682042792220849624849347751987110078191214953515
4673406679818321802783074942895316939107100122811973117
566158656091643190377137890240881449793109108312432216
6650776434017572287910191382011112473115149114014642318
7639176282720662917941990071690710802138182131618202320
862565609382544379580497406143519423141188158522932018
960932585613185492163315798123268287135183192928481715
1058945556193975627251725008107297351133191232534331414
115655852092488777864995557994776581152247273539741416
125376248038586993686501927485025947226455311543951927
1350599435946850108931211922756775154264621177341946423663
14471543896177471222023511470587186500094624633614471268123
154355834368847013220339006339267764655138632403680460294151
1639957300298944137904055270366650143781625337736084318106148
1736495261059118138764464462818634741601692271434113883107113
18332912269489731347438086583136306399413172176310633578387
19304311982685251263336242579746377387511001810273228107070
2027955174817821114463624257974656238009391475233122906256
2125875156086932100263624257974687137657791175193418245344
22241721414359398498362425797473203770630917156414234635
23228101301749216973362425797479323816497702123510893927
242174712166394655453624257974873839023835279518193321
252093511532306542763624257974978140332883897166042816
2620330110702306320136242579741111842122122825264372312
271988810737168323273624257974128204444152200377310199
281957310503119316453624257974149764738106139264215167
291935410341821113136242579741769251047294180146135

Model predictions by age and sex.

Prevalent cases per 100,000 cases (B), events per 100,000 person-years (C,F,G,H) and probability x 100,000 (D,E). B: EBV naive, C: seroconversion hazard rate, D: attack rate, E: fraction of hospitalized IM cases, F: IM population hazard rate, G: seroconversion population hazard rate and H: hospitalized IM population hazard rate. C-H are averages within the age group, B is the maximum within the age group, i.e. who were EBV-naïve at exact age 1,2,…Refer to Fig 1 and methods for further details. The EBV prevalence in our data set was generally lower than in older unselected Danish data [36,37], but otherwise similarly distributed (Fig 1A). Sex-specific corresponding proportions of EBV naϊve individuals are shown in Fig 1B. Both sexes experienced peaks in seroconversion rate as infants and as young adults (Fig 1C). The seroconversion rates for boys and girls were similar on the left side of the nadir in seroconversion rate, but girls had the highest rate to the right of the nadir (Fig 1C). The seroconversion rate peaked at age 17.2 years in females and at age 17.5 years in males. The IM attack rate rose from practically nothing in children aged 0–2 years to represent a very common phenomenon in teenagers (Fig 1D). A peak in attack rate appeared in teenage years, and was especially pronounced among girls. The attack rate was higher in females than males throughout the teenage years. The attack rate peaked at age 16.3 years in girls and at age 17.3 years in boys and likewise the local minimum in attack rate to the left of the peak occurred at age 11.0 years in boys and at age 10.5 years in girls (Fig 1D). For all ages the fraction of hospitalized IM cases was larger for males than for females. The fraction of IM cases becoming hospitalized was unimodal and typically low with a minimum of 6% at age 18.3 years and 4% at age 21.8 years for males and females, respectively (Fig 1E). Fig 1F, 1G and 1H contain what we call population rates. The denominator in these rates is time at risk for the entire population, not just the subpopulation of EBV naϊve. The IM population hazard rate is the product of the seroconversion population hazard rate and the attack rate. The location and shape of the IM population hazard rate peak in teenage years (Fig 1F) was essentially determined by the attack rate (Fig 1D), which varied considerably more in this age span than the seroconversion population hazard rate (Fig 1G). The combination of information in Fig 1C and 1D revealed several things. For children age 0–2 years the attack rate was low and the seroconversion rate high, as a priori expected from prevalence and rate data. For 3–12 years old children the IM population hazard rate was kept low mainly by a small seroconversion rate, since the attack rate, relatively speaking increased substantially compared to the attack rate in 0–2 years old children. Comparing children age 4 to 5 years (the nadir of seroconversion) with teenagers age 16 to 17 years (the peak in IM attack rate) the seroconversion rate was lower by a factor of 6 to 8, while the corresponding attack rate was lower by a factor of 6 to 10. Accordingly, the low incidence of IM in 3–12 years old children was roughly equally due to low attack rate and low seroconversion rate.

Discussion

Our analyses for the first time provide detailed and compelling evidence that the accumulation of IM among adolescents, a characteristic of western industrialized countries, reflects age-dependent variations both in IM attack rates and EBV seroconversion hazard rates. Both early childhood and adolescence are age-periods characterized by social behaviors involving the exchange of saliva, the primary route for EBV transmission, e.g. through sharing of toys and utensils in early childhood and through kissing in adolescence and early adulthood [38]. Deep kissing as the main route of EBV transmission in adolescence and beyond is well established [9], while the evidence for sharing of toys and utensils in early childhood as an important route of EBV transmission is weaker and indirect, e.g. a marked reduction in IM risk for each additional sibling, especially when the age-differential is small[19,39], presumably due to pre-teenage EBV infection. To become infected, EBV naϊve individuals must interact with EBV-positive infectious individuals. Consequently, spreading of EBV depends on patterns of interaction between EBV-susceptible and EBV-infectious individuals and the likelihood of EBV transmission and infection at such encounters. In early childhood when the vast majority of individuals are still EBV-naϊve, EBV will spread rapidly because many encounters between these EBV-naϊve children and EBV-positive parents/adults/same age children has the potential to create an EBV infection in the EBV-naϊve child. The steep decline in seroconversion hazard rates between ages 2 and 5 years is disproportionate to the decrease in EBV-susceptible individuals. Therefore, rather than the gradual reduction in proportions of susceptible and possibly also acutely infected (infectious) individuals, the decreasing risk of EBV-infection and the plateauing sero-prevalence likely reflect age-related changes in behavior associated with lower risk of EBV transmission from both other children and parents/adults. The second wave of EBV infection occurred in adolescence through early adulthood, with the highest EBV hazard rates occurring at slightly younger ages in females than in males. This may reflect earlier puberty in girls than in boys, and the typical age-disparity in female-male relationships with girls tending to partner with older boys [40]. Because of the age-dependent increase in EBV-sero-positivity, girls at any age would tend to engage with boys more likely to be EBV infected than boys their own age, whereas the opposite would be true for boys who would engage with younger girls, less likely to be EBV infected than girls their own age. Although of waning relevance in Western societies we also speculate that girls more often than boys expose themselves as caretakers to siblings and other children of age 0–3 years, whom we have identified as risk factors for IM and thus primary EBV infection [19]. All these interaction patterns would accelerate seroconversion in the female population and decelerate it in the male population. The shape of the attack rate essentially complies with the dogma of IM being more frequent and severe the older the age at seroconversion [41-43] yielding something close to a monotone increase by age (Fig 1D). The mechanisms underlying the age-dependent variation in IM attack rate have remained elusive, but proposed explanations include corresponding variations in mode and dose of infection and in host immune response [2,11,15,44]. The host immune response may vary by age for at least two reasons: 1) NK cell responses may assume greater importance, and perhaps be more effective, in combating virus infections early in life [15], and/or 2) adolescents infected with EBV may recruit large numbers of cross-reactive memory T cells previously created in response to other viral infections, which may more easily be activated but be less efficient in controlling the infection than primary responses from recruited naϊve T cells [44]. However, in light of the very rapid change in IM attack rate, we do not consider cross-reactivity of memory T cells to be a likely major contributor to this change. Similarly Balfour et al. found no evidence of influenza-EBV dual specific CD8+ T cells in their study cohort to support this explanation [9,11]. Likewise both simulations [44] and observational studies [2,12,45] suggest that the initial viral load, and hence dose or mode of delivery is of little importance for IM risk. Our results, including the fact that the adolescent attack rate peak among females occurs at a slightly younger age than the corresponding peak in males, instead point to IM susceptibility as somehow being subject to mechanisms that involve growth and/or sex hormones whose levels change as part of sexual maturation. In this regard, it is noteworthy that both estrogen and androgens are known to influence immune responses via epigenetic mechanisms, see [46] and references therein.

Strengths and weaknesses

We believe the serological data on prevalent EBV status to be accurate. They are based on enzyme-linked immunosorbent assays, which can perform very similarly to the gold standard of immunofluorescence arrays [1,47-49]. However, the tested patients were not randomly sampled, and as such may yield a biased representation of the age- and sex-specific EBV-prevalence in our population. Specifically, most persons in our sample were presumably tested in order to determine whether symptoms similar to IM could be due to an acute EBV infection. Furthermore, we suspect that many of the samples were sent for serological testing due to atypical IM symptoms or results of a quick but unreliable IM test, that the general practitioner did not trust. As such one would expect to sample too many recently EBV-infected persons. On the other hand, comparison with older unselected Danish data sets suggest, if anything, that we have too few EBV-infected persons in our sample at a given age. Secular changes, specifically the Danish society becoming more affluent would tend to lower the age-specific sero-prevalence in our material compared to older Danish materials [1,50]. This could explain the discrepancy, and recent examples of such trends in other Western countries exist [11,41]. In Denmark the gradual increase in childcare attendance from around 1965 to 2000 [51] would tend to work in the opposite direction, but the effect is probably modest since the most common type of childcare for children age 0–2 years is by daycare mothers, i.e. caretakers taking care of only a few children. Currently only a third of a generation of children age 0–2 years attends an institution (creche, kindergarten or integrated institution), see {}. Altogether, we believe that our estimated seroconversion rates are sufficiently accurate to model the essential seroconversion dynamics in our target population. For the purpose of attributing causes for IM in different age groups, it seems more important to get the ratios of age-specific attack rates within sexes, rather than the exact level, correct. We see no reason why our data or modeling should be noticeably biased with respect to assessing ratios of age-specific attack rates within sexes. Furthermore, our estimated attack rates around age 20 years are compatible with earlier detailed longitudinal studies on university students and army recruits [20-22], and do not de facto become 100% at any age as would be the sign of a severe upwardly biased ascertainment of incident IM. We believe the variation in the fraction of IM cases hospitalized to be a natural screening phenomenon. Specifically, we believe that general practitioners expect IM symptoms in teenagers to be caused by IM and therefore do not admit such cases to hospital, while the more unexpected and for children more non-specific IM symptoms [52-55] would cause general practitioners to admit a patient to hospital for further investigation more often. We do not know why the fraction of hospitalized IM cases is higher in boys than in girls; if anything, girls seem on average to have the most vigorous immune response as measured by EBV antibody titers [56-58]. Furthermore, there seemingly is no age gradient (age 6–17 years) in EBV antibody titers [58], supporting the view that the bathtub shaped curves are a screening phenomenon, rather than due to physiology. The cumulative risk of IM before age 30 years was 13.3% for males and 22.4% for females. This estimate is quite high compared to other estimates (≈ 5% with much variation) (Rostgaard et al. [26] and Table 5 in Hjalgrim [59]). We have no immediate explanation for this. However, we do not consider it surprising to have a substantially larger ''lifetime'' risk of IM in our target population than in other older and less affluent settings referred to above. E.g. the percentage of 15–17 year old EBV naϊve Americans increased from 22 to 31 over just 6 years (Table 2 in Balfour et al. [1]), which all else equal should increase the occurrence of IM in that age span a factor 31/22 = 1.41. If the percentage of EBV naϊve at the IM teenage peak was much lower in the past a change in the occurrence of IM of a factor 3 or 4 is certainly possible. Furthermore the blood donors in our study being on average better educated and wealthier than non-donors [60] would suggest them to be recruited from affluent population strata and as such more prone to late EBV infection and thus presenting with IM than the general population.

Conclusion

Studies to predict the possible benefit of a specific EBV vaccine was one of five priorities outlined at an EBV-vaccine meeting organized by the US National Institutes of Health in 2011[61]. The present study provides for the first time some of the knowledge needed for that purpose by precisely displaying at what age persons seroconvert and when it has consequences in terms of IM, with all the sequelae that goes with that [3-7]. Mathematically the pair of descriptors (EBV hazard rate, IM attack rate) has the advantage compared with (EBV prevalence, IM incidence) of being more”local” in time, and therefore better suited to generation of causal interpretations and hypotheses, as causal mechanisms work locally in time, i.e. causes continually transmit their effects [62]. We think our study vindicates this point of view. Methodologically we found it relatively easy to transform prevalence data into mathematically coherent and equivalent forms, primarily smooth hazard functions. We found these more informative than the raw prevalence data for, in this case, the dynamics of EBV infection. Our prevalence data were very detailed regarding age, but usually much cruder data would suffice for obtaining a model-based smooth hazard function. We believe that this type of analysis would be helpful in many future studies of the epidemiology of specific persistent infections.

The raw data for model fitting.

(TXT) Click here for additional data file.

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This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present. 4 Oct 2019 PONE-D-19-25327 Primary Epstein-Barr virus infection with and without infectious mononucleosis PLOS ONE Dear Mr. Rostgaard, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. We would appreciate receiving your revised manuscript by Nov 18 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out. We look forward to receiving your revised manuscript. Kind regards, Gulfaraz Khan, PhD, FRCPath Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Our internal editors have looked over your manuscript and determined that it may be within the scope of our Mathematical Modelling of Infectious Disease Dynamics Call for Papers. The Collection will encompass a diverse range of research articles on using mathematical models to better understand infectious diseases. Additional information can be found on our announcement page: https://collections.plos.org/s/mathematical-disease-dynamics. If you would like your manuscript to be considered for this collection, please let us know in your cover letter and we will ensure that your paper is treated as if you were responding to this call. If you would prefer to remove your manuscript from collection consideration, please specify this in the cover letter. 3. Please note that PLOS ONE has specific guidelines on software sharing (http://journals.plos.org/plosone/s/materials-and-software-sharing#loc-sharing-software) for manuscripts whose main purpose is the description of a new software or software package. In this case, new software must conform to the Open Source Definition (https://opensource.org/docs/osd) and be deposited in an open software archive. Please see http://journals.plos.org/plosone/s/materials-and-software-sharing#loc-depositing-software for more information on depositing your software. Additional Editor Comments (if provided): [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Partly Reviewer #2: Yes ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: I Don't Know Reviewer #2: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: No Reviewer #2: Yes ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: It would be useful to report the number of individuals included in the study, and a descriptive table showing the number of individuals who are EBV positive or negative at each age. A multiple-decrement life table could provide at a glance a good sense of the infection and disease process, and thus a more convincing presentation of the results presented. Reviewer #2: Manuscript Nr.: PONE-D-19-25327 Rostgaard et al., "Primary Epstein-Barr virus infection with and without infectious mononucleosis" The authors evaluate the age and sex dependency of infectious mononucleosis (IM) in the Danish population between 2006 and 2011 for the ages between 0 and 29 years. IM is identified by hospitalization or self-reporting. The Epstein Barr virus (EBV) serostatus is assessed by IgG and IgM responses to virus capsid antigen (VCA) and IgG to the nuclear antigen 1 of EBV (EBNA1). They report that the cumulative IM risk for males before 30 years of age is 13% and for females 22%. IM peaks during puberty at 16.3 years earlier in girls than with 17.3 years in boys. The authors suggest that alterations in the immune system during puberty might account for the increased risk to develop the immunopathology of IM in response to primary EBV infection. The reported data and the differences between girls and boys are interesting. One wonders if however quantitative data could be obtained from the assessed serotests and if other virus specific serologies were reported in at least a subgroup of individuals. Major comments: 1. As pointed out by the authors overall viral loads do not differ between individuals with asymptomatic or symptomatic EBV infection. However, the composition of the primary infection might be altered during IM. Do the authors find any evidence that seroconversion during adolescence irrespective of IM results in an altered ratio of VCA (lytic infection) versus EBNA1 (latent and lytic infection) specific antibody titers? 2. Additional infections have been proposed to mature or alter the human immune system. Was the serostatus to other pathogens assessed and shows a similar bimodal distribution with two peaks of acquisition (0-2 years and during puberty)? 3. The increased rate of IM related hospitalization in males compared to females despite higher IM incidence in females is puzzling and could point towards more severe immunopathology in males during IM. Do the authors observe higher immunoglobulin titers against EBV antigens in males compared to females? Minor comments: 1. In their results the authors often stay vague by just stating that one incidence rate is higher than another etc. I think it would be helpful if the manuscript would indicate the actual numbers that the deployed modelling generated. In summary, this is an interesting manuscript on IM in the Danish population, reporting a surprisingly high cumulative risk in females with a fairly narrow IM peak around puberty. The study could be further improved by reporting some of the available immune parameters quantitatively. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step. 11 Nov 2019 We thank the editor and the reviewers for this opportunity to make the presentation in our manuscript more informative. We hope our solutions will satisfy all parties and lead to the acceptance of the revised manuscript for publication. 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: It would be useful to report the number of individuals included in the study, and a descriptive table showing the number of individuals who are EBV positive or negative at each age. A multiple-decrement life table could provide at a glance a good sense of the infection and disease process, and thus a more convincing presentation of the results presented. A: We have created a life-table with cells by sex and 1-year age group, containing estimates on the form N per 100000 as per life table tradition of all the model predictions in the figure. The new table and the original figures thus form a complementary presentation of our findings. We have added a new first paragraph to the results section, introducing the figures and the new life-table and providing totals of persons contributing to various parts of the model. The new paragraph reads: “All Danes age 0-29 years resident in Denmark somewhen during calendar years 2006-2011, in all 2,485,292 persons, were followed up in the same age and period range for a hospital contact with an IM diagnosis during 11,376,713 person-years of follow-up, yielding 4703 incidents of hospitalized IM. 2487 blood donors from The Danish Blood Donor Study, who had self-reported IM or had been hospitalized with IM under the right conditions (age and period, see Methods) were assessed for hospitalized IM to yield the fraction of hospitalized IM among IM cases (185/2487=7% of IM cases). 6145 persons tested for EBV antibodies at Statens Serum Institut at age 0-29 years during calendar years 2006-2011 yielded 3513 (57%) infected with EBV. The three statistically sufficient data sets for these three outcomes and the only data sets used for our analyses are available in S1 Data, labelled in the type variable as NPR, DBDS and EBVPREV, respectively. The results of our modeling are a set of age- and sex-specific predictions, presented in Fig 1A-1H, and the same predictions in a slightly aggregated life-table format in Table 1, with columns labelled B to H. Throughout we shall only refer to the figures, the reader may consult the relevant columns of the table instead.” Reviewer #2: Manuscript Nr.: PONE-D-19-25327 Rostgaard et al., "Primary Epstein-Barr virus infection with and without infectious mononucleosis" The authors evaluate the age and sex dependency of infectious mononucleosis (IM) in the Danish population between 2006 and 2011 for the ages between 0 and 29 years. IM is identified by hospitalization or self-reporting. The Epstein Barr virus (EBV) serostatus is assessed by IgG and IgM responses to virus capsid antigen (VCA) and IgG to the nuclear antigen 1 of EBV (EBNA1). They report that the cumulative IM risk for males before 30 years of age is 13% and for females 22%. IM peaks during puberty at 16.3 years earlier in girls than with 17.3 years in boys. The authors suggest that alterations in the immune system during puberty might account for the increased risk to develop the immunopathology of IM in response to primary EBV infection. The reported data and the differences between girls and boys are interesting. One wonders if however quantitative data could be obtained from the assessed serotests and if other virus specific serologies were reported in at least a subgroup of individuals. A: Our data material was collected with the sole purpose of illuminating IM epidemiology. We therefore do not have access to other microbiological test result regarding (a subset of) our EBV tested cohort. Furthermore, all our test results regarding the specific biomarkers are of a semi-qualitative nature: “positive”, “weakly positive”, “negative” etc. We therefore are unable to address the following reviewer questions based on our own biomarker materials. We have instead tried to address the questions based on the available literature, and added content to the discussion when possible and informative. 1. As pointed out by the authors overall viral loads do not differ between individuals with asymptomatic or symptomatic EBV infection. However, the composition of the primary infection might be altered during IM. Do the authors find any evidence that seroconversion during adolescence irrespective of IM results in an altered ratio of VCA (lytic infection) versus EBNA1 (latent and lytic infection) specific antibody titers? A: We have not been able to find relevant references on the specific question. And unfortunately, as far as we can see, we do not have data available that would at least put us in a position to suggest an answer to it. We have therefore decided only to flag this interesting avenue of research. We have added to the end of the first paragraph of the introduction: “Functions of EBV antibody levels as predictors of disease risk is an active field of research, see REF and references therein.” 2. Additional infections have been proposed to mature or alter the human immune system. Was the serostatus to other pathogens assessed and shows a similar bimodal distribution with two peaks of acquisition (0-2 years and during puberty)? A: As we do not have such samples, and since we consider the evidence to be had from other infections for an age-dependently altered immune system as part explanation for the bimodal EBV seroconversion rate as weak we have not changed the text. 3. The increased rate of IM related hospitalization in males compared to females despite higher IM incidence in females is puzzling and could point towards more severe immunopathology in males during IM. Do the authors observe higher immunoglobulin titers against EBV antigens in males compared to females? A: To the end of the fifth paragraph in “Strengths and weaknesses” we have added: “We do not know why the fraction of hospitalized IM cases is higher in boys than in girls; if anything, girls seem on average to have the most vigorous immune response as measured by EBV antibody titers (REFS). Furthermore, there seemingly is no age gradient (age 6-17 years) in EBV antibody titers (REF), supporting the view that the bathtub shaped curves are a screening phenomenon, rather than due to physiology.” Minor comments: 1. In their results the authors often stay vague by just stating that one incidence rate is higher than another etc. I think it would be helpful if the manuscript would indicate the actual numbers that the deployed modelling generated. A: Done. See answer to reviewer 1. In summary, this is an interesting manuscript on IM in the Danish population, reporting a surprisingly high cumulative risk in females with a fairly narrow IM peak around puberty. The study could be further improved by reporting some of the available immune parameters quantitatively. Submitted filename: Rostgaard_imp3_Replyletter.docx Click here for additional data file. 27 Nov 2019 Primary Epstein-Barr virus infection with and without infectious mononucleosis PONE-D-19-25327R1 Dear Dr. Rostgaard, We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements. Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication. Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. With kind regards, Gulfaraz Khan, PhD, FRCPath Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: (No Response) Reviewer #2: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: (No Response) Reviewer #2: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: (No Response) Reviewer #2: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: (No Response) Reviewer #2: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: (No Response) Reviewer #2: Manuscript Nr.: PONE-D-19-25327R1 Rostgaard et al., "Primary Epstein-Barr virus infection with and without infectious mononucleosis" The authors evaluate the age and sex dependency of infectious mononucleosis (IM) in the Danish population between 2006 and 2011 for the ages between 0 and 29 years. IM is identified by hospitalization or self-reporting. The Epstein Barr virus (EBV) serostatus is assessed by IgG and IgM responses to virus capsid antigen (VCA) and IgG to the nuclear antigen 1 of EBV (EBNA1). They report that the cumulative IM risk for males before 30 years of age is 13% and for females 22%. IM peaks during puberty at 16.3 years earlier in girls than with 17.3 years in boys. The authors suggest that alterations in the immune system during puberty might account for the increased risk to develop the immunopathology of IM in response to primary EBV infection. The revised manuscript version continues to report an interesting dichotomy between girls and boys for IM with a higher frequency and earlier onset in girls, but more frequent hospitalization of boys. Even so the authors could not provide quantitative data on the measured serologies, they have discussed these outstanding issues and now report their data more quantitatively. Therefore, the revised manuscript is improved. Minor comment: 1. The title could be more informative and reflect some findings of the manuscript. Something along the lines of “Earlier onset and higher frequency of infectious mononucleosis in Danish females than males” would seem appropriate. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: Yes: Christian Münz 9 Dec 2019 PONE-D-19-25327R1 Primary Epstein-Barr virus infection with and without infectious mononucleosis Dear Dr. Rostgaard: I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. For any other questions or concerns, please email plosone@plos.org. Thank you for submitting your work to PLOS ONE. With kind regards, PLOS ONE Editorial Office Staff on behalf of Prof Gulfaraz Khan Academic Editor PLOS ONE
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Authors:  Henry H Balfour; Oludare A Odumade; David O Schmeling; Beth D Mullan; Julie A Ed; Jennifer A Knight; Heather E Vezina; William Thomas; Kristin A Hogquist
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