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Association of Infectious Mononucleosis in Childhood and Adolescence With Risk for a Subsequent Multiple Sclerosis Diagnosis Among Siblings

Association of Infectious Mononucleosis in Childhood and Adolescence With Risk for a Subsequent... Key Points Question Is diagnosis of infectious IMPORTANCE Epstein-Barr virus and its acute manifestation, infectious mononucleosis (IM), are mononucleosis (IM) in childhood or associated with an increased risk of multiple sclerosis (MS). Whether this association is confounded adolescence associated with by susceptibility to infection is still debated. subsequent development of multiple sclerosis (MS)? OBJECTIVE To assess whether hospital-diagnosed IM during childhood, adolescence, or young Findings In this population–based adulthood is associated with subsequent MS diagnosis independent of shared familial factors. cohort study of 2 492 980 individuals in Sweden, IM in childhood and DESIGN, SETTING, AND PARTICIPANTS This population–based cohort study used the Swedish adolescence was associated with an Total Population Register to identify individuals born in Sweden from January 1, 1958, to December increased risk of a subsequent MS 31, 1994. Participants aged 20 years were followed up from January 1, 1978, to December 31, 2018, diagnosis that remained significant after with a median follow-up of 15.38 (IQR, 8.68-23.55; range, 0.01-40.96) years. Data were analyzed controlling for measured and from October 2020 to July 2021. unmeasured shared familial factors. EXPOSURE Hospital-diagnosed IM before 25 years of age. Meaning These findings suggest that IM in childhood and particularly MAIN OUTCOMES AND MEASURES Diagnoses of MS from 20 years of age were identified. Risk of adolescence is a risk factor for a an MS diagnosis associated with IM in childhood (birth to 10 years of age), adolescence (11-19 years subsequent MS diagnosis, independent of age), and early adulthood (20-24 years of age [time-dependent variable]) were estimated using of shared familial factors, making it less conventional and stratified (to address familial environmental or genetic confounding) Cox likely that greater susceptibility to proportional hazards regression. infection is the explanation. RESULTS Of the 2 492 980 individuals (1 312 119 men [52.63%] and 1 180 861 women [47.37%]) Supplemental content included, 5867 (0.24%) had an MS diagnosis from 20 years of age (median age, 31.50 [IQR, 26.78- 37.54] years). Infectious mononucleosis in childhood (hazard ratio [HR], 1.98; 95% CI, 1.21-3.23) and Author affiliations and article information are listed at the end of this article. adolescence (HR, 3.00; 95% CI, 2.48-3.63) was associated with an increased risk of an MS diagnosis that remained significant after controlling for shared familial factors in stratified Cox proportional hazards regression (HRs, 2.87 [95% CI, 1.44-5.74] and 3.19 [95% CI, 2.29-4.46], respectively). Infectious mononucleosis in early adulthood was also associated with risk of a subsequent MS diagnosis (HR, 1.89; 95% CI, 1.18-3.05), but this risk was attenuated and was not significant after controlling for shared familial factors (HR, 1.51; 95% CI, 0.82-2.76). CONCLUSIONS AND RELEVANCE These findings suggest that IM in childhood and particularly adolescence is a risk factor associated with a diagnosis of MS, independent of shared familial factors. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 Open Access. This is an open access article distributed under the terms of the CC-BY License. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 1/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis Introduction Infectious mononucleosis (IM) is a clinical manifestation of viral infection, predominantly caused by Epstein-Barr virus (EBV). Both IM and high levels of anti-EBV nuclear antigen 1 (EBNA-1) antibodies 1,2 are associated with an increased risk for multiple sclerosis (MS). However, the nature of the association between IM and MS is still debated. This association might be explained, at least in part, by common genetic factors relevant to the acute manifestation of IM, subsequent antibody levels, and MS risk. Genome-wide association studies have found that loci in the human leukocyte antigen (HLA) region, such as HLA-DRB1 and HLA-DQA1 genes, are 4-6 associated with both MS risk and elevated anti-EBNA IgG levels. The possibility of confounding is suggested by studies showing that the increased MS risk associated with IM decreased in magnitude or became statistically nonsignificant after controlling for potential confounders, including genetic ancestry and HLA-DRB1*1501 carrier status. However, few studies have extensively addressed measured and unmeasured shared familial genetic and environmental factors as potential confounders that may be associated with both IM and MS. Therefore, methods such as within-sibling studies, which control for unmeasured shared familial factors (because members of the same family share important characteristics) by comparing siblings discordant for IM, are needed to better understand the relationship between IM and MS. Adolescence may be an important period of susceptibility for the putative association of IM with 9,10 MS pathogenesis compared with earlier childhood, consistent with associations for other risk 11,12 13 factors for MS in adolescence: pneumonia and other infections, higher body mass index, 14 15 concussion, and lower serum vitamin D levels. Infectious mononucleosis in early adulthood (20-24 years of age) has also been associated with increased MS risk, although the effect size is smaller than for IM in adolescence. This study used a large population–based birth cohort in Sweden to assess the association of hospital-diagnosed IM in childhood (from birth to 10 years of age) and adolescence (11-19 years of age) with risk of an MS diagnosis from 20 years of age. The association of IM in early adulthood (20-24 years of age) with a subsequent MS diagnosis was also assessed by treating IM as a time- dependent variable to ensure that IM predates the MS diagnosis. Cox proportional hazards regression stratified by family to compare siblings (within-sibling analysis) was used to account for measured and unmeasured shared familial factors. If the association between IM and MS is confounded by shared familial factors, the magnitude of estimates and statistical significance would be attenuated when results from within-sibling analyses are compared with conventional analyses. Methods Study Population This population-based cohort, which was identified by the Total Population Register, comprised all individuals born in Sweden from January 1, 1958, to December 31, 1994, who reached 25 years of age from January 1, 1990, to December 31, 2019, with both parents also alive in 1990 to facilitate identification of all first-degree relatives and identify MS diagnoses in parents. Participants aged 20 years were followed up from January 1, 1978, to December 31, 2018, with a median follow-up of 15.38 (IQR, 8.68-23.55; range, 0.01-40.96) years. The unique individual Swedish personal identification number was used for data linkage across various Swedish registers to identify cohort members’ 17,18 hospital-based diagnoses and their first-degree relatives (eMethods in the Supplement). The analysis was restricted to the youngest generation (including familial information on parents), because most parents, their siblings, and grandparents and their siblings were born at an earlier period when register coverage was too incomplete to adequately capture information on IM in childhood among them. A total of 2 492 980 individuals were included in this study (Figure). Ethical approval for this study was received from the Swedish Ethical Review Authority. Informed consent was not required by the authority because the study was based only on anonymized register data. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 2/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies. Outcome A diagnosis of MS from 20 years of age was identified for members of the index cohort or at any age for parents using International Classification of Diseases, Eighth Revision (ICD-8)or International Classification of Diseases, Ninth Revision (ICD-9) code 340 and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) code G35. To ensure diagnostic accuracy, 2 MS diagnoses recorded at a minimum of 6 months apart were required, which makes exclusion of misdiagnoses and relevant differential diagnoses more likely. Validation studies have shown a high level of accuracy both for MS diagnoses (positive predictive value of 92.50%) and when using at least 2 MS diagnoses to identify MS (positive predictive value and sensitivity >0.90%). The first diagnosis was used to define date of first MS diagnosis. Individuals with only 1 MS diagnosis or with separate MS diagnoses recorded within 6 months were not considered to have confirmed MS (n = 920). Exposure and Potential Confounding Factors Primary or secondary diagnoses of IM before 25 years of age were identified using ICD-8 or ICD-9 code 075 and ICD-10 code B27 (EBV titer data were not available). To examine the age-defined periods of potential susceptibility for the association of IM with risk of an MS diagnosis, IM diagnoses before 25 years of age were categorized as occurring in childhood (from birth to 10 years of age), in 9,10,16 adolescence (11-19 years of age), or in early adulthood (20-24 years of age). Sex, an MS diagnosis in either parent, birth order (first, second, third, or fourth or subsequent), and maternal and paternal age at birth of the cohort member (the difference between cohort member’s date of birth and parents’ date of birth divided by 365.25) were considered potential confounding factors. Statistical Analysis Data were analyzed from October 2020 to July 2021. There was no missing information for outcome and confounding factors. Three individuals who had missing information for date of IM diagnosis were excluded (Figure). STATA, version 16.0 (StataCorp LLC), was used for data analysis. Conventional Cox proportional hazards regression was used to test the association between IM in childhood or adolescence and the risk of an MS diagnosis from 20 years of age. The association of IM in early adulthood with a subsequent MS diagnosis was also examined. Follow-up was from 20 years of age until the first diagnosis of MS, death, first emigration, or study end (December 31, 2018), whichever occurred first. Cohort members who emigrated were censored on the date of first leaving Sweden and could not reenter the cohort to ensure no gaps in follow-up. We split follow-up time before and after the date of an IM diagnosis in early adulthood to model early adulthood IM diagnosis as a time-dependent covariate (ensuring we only considered associations with subsequent MS diagnoses). We adjusted for sex, parental MS diagnosis, birth order, and parental age at birth. Figure. Flowchart of Participant Selection 3 546 995 Patients assessed for eligibility 1 054 015 Excluded Temporary duplicates are due to the assignment of a 4436 Temporary duplicates of personal identification number previously deceased person's personal identification 438 With at least 1 diagnosis of MS before age 20 y number to some immigrants to Sweden. Parents, their 3 Missing date of IM diagnosis siblings, and grandparents and their siblings were not 996 428 Parents and parents’ siblings 52 710 Died or emigrated before age 20 y members of the analysis cohort because register coverage was more incomplete during their childhood. IM indicates infectious mononucleosis; MS, multiple 2 492 980 Included in the primary analysis sclerosis. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 3/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis Second-degree fractional polynomials suggested that parental age at birth was linearly associated with risk of an MS diagnosis. Violations of the proportional hazards assumption were detected for paternal age at birth, a parental MS diagnosis, and birth order using Schoenfeld residuals. However, the effect of violation was minimal based on scaled Schoenfeld residuals plotted against time (eFigure in the Supplement). Thus, results from analyses assuming proportional hazards are reported herein. Further analyses subdivided age categories for IM into 5-year periods and considered first MS diagnosis from 20 to 30 years of age or after 30 years of age (eTable in the Supplement). To adjust for measured and unmeasured familial factors through estimating a cluster (sibling- set)–specific baseline hazard, stratified Cox proportional hazards regression was used for within- sibling analysis where the mother’s identification number was the stratification variable. The follow-up time and variables included in the analysis were the same as those described above. The magnitude of shared familial confounding was measured as the attenuation of estimates from Cox proportional hazards regression models stratified by family, compared with conventional Cox proportional hazards regression. For the stratified Cox proportional hazards regression, fractional polynomials suggested that parental age at birth was linearly associated with risk of an MS diagnosis. Violation of the proportional hazards assumption was detected for birth order using Schoenfeld residuals. Again, the effect of violation was minimal based on scaled Schoenfeld residuals plotted against time. Thus, results from analyses assuming proportional hazards were reported. Huber-White SEs were used to account for clustering within families. A total of 5 sensitivity analyses using stratified Cox proportional hazards regression were performed. Sensitivity analysis 1 used a first MS diagnosis from 25 years of age to reduce possible bias because MS may have a relatively long prodromal period. Sensitivity analysis 2 excluded individuals who were born after 1987 to examine the potential influence of the incomplete national coverage of the Swedish Patient Register until 1987 on the association between IM and risk of an MS diagnosis. Sensitivity analysis 3 only included families with the same mother and father for all the children (within-full-sibling analysis). Sensitivity analysis 4 used the first diagnosis of any demyelinating disease of the central nervous system (CNS) to define the onset date of MS (individuals with a demyelinating disease–defined onset of MS before 20 years of age were excluded) as follows: MS, acute disseminated encephalomyelitis, optic neuritis, other acute disseminated demyelination, and other demyelinating disease of the CNS (ICD-8 or ICD-9 codes 323, 340, and 341 and ICD-10 codes G04, H46, G35, G36, and G37). Acute disseminated encephalitis could not be identified in our data because ICD code precision of 4 digits is required, which was not available; therefore, encephalomyelitis diagnoses (ICD-8 or ICD-9 code 323 and ICD-10 code G04) were exclusion criteria because they include acute disseminated encephalitis. Sensitivity analysis 5 included families with either parent alive in 1990 to address potential selection bias. Results Cohort Characteristics A total of 2 492 980 individuals (1 312 119 men [52.63%] and 1 180 861 women [47.37%]; 1 290 007 first born [51.75%]; 26 954 [1.08%] with IM before 25 years of age; and 17 315 [0.69%] with either parent having an MS diagnosis) were included in this population–based cohort study (Table 1). Of these, 5867 individuals (0.24%) had an MS diagnosis from 20 years of age, at a median age of 31.50 (IQR, 26.78-37.54; range, 20.01-58.93) years. Results from stratified Cox proportional hazards regression indicated that being female (hazard ratio [HR], 2.62; 95% CI, 2.44-2.81) and older maternal age at birth (HR for each additional year, 1.07; 95% CI, 1.04-1.11) were associated with increased risk of an MS diagnosis; later-born children were at lower risk of being diagnosed with MS compared with first-born children (HR for second born, 0.91 [95% CI, 0.83-0.99]; HR for third born, 0.81 [95% CI, 0.68-0.97]; HR for fourth born or subsequent birth, 0.67 [95% CI, 0.49-0.91]) (Table 1); paternal age at birth was not associated with an increased risk of an MS diagnosis (HR, 0.98; 95% CI, 0.96-1.01) (Table 1). As expected, the increased risk associated with either parent having an MS JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 4/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis diagnosis using an adjusted conventional Cox proportional hazards regression model (HR, 8.04; 95% CI, 7.16-9.04) became statistically nonsignificant after controlling for unmeasured shared familial factors using stratified Cox proportional hazards regression (HR, 1.95; 95% CI, 0.37-10.27). IM and Risk of an MS Diagnosis Compared with those without IM, individuals with IM in childhood and adolescence were at a greater risk of being diagnosed with MS using an adjusted conventional Cox proportional hazards regression model (HRs, 1.98 [95% CI, 1.21-3.23] and 3.00 [95% CI, 2.48-3.63], respectively). This risk remained statistically significant and increased in magnitude after further controlling for unmeasured shared familial factors using stratified Cox proportional hazards regression (HRs, 2.87 [95% CI, 1.44-5.74] and 3.19 [95% CI, 2.29-4.46], respectively). Infectious mononucleosis in early adulthood was associated with an increased risk of an MS diagnosis using an adjusted conventional Cox proportional hazards regression model but at a lower magnitude than at younger ages (HR, 1.89; 95% CI, 1.18-3.05). This risk became statistically nonsignificant after controlling for unmeasured shared familial factors using stratified Cox regression (HR, 1.51; 95% CI, 0.82-2.76). The eTable in the Supplement shows a similar pattern of rising and then waning risk with age, with no attenuation of risk magnitude when follow-up begins after 30 years of age. Sensitivity Analyses Results from sensitivity analyses are shown in Table 2. Restricting MS diagnoses to 25 years or older in sensitivity analysis 1 showed that the increased risk of being diagnosed with MS associated with IM in childhood and adolescence remained statistically significant and was not attenuated in magnitude (HRs, 3.72 [95% CI, 1.44-9.56] and 3.96 [95% CI, 2.65-5.90], respectively). Sensitivity Table 1. Characteristics of the Birth Cohort Stratified by MS With HRs for Risk of MS Diagnosis MS diagnosis Cox proportional hazards regression, HR (95% CI) Conventional Absent Present b c d Characteristic (n = 2 487 113) (n = 5867) Unadjusted Adjusted Stratified adjusted Sex Male 1 310 269 (52.68) 1850 (31.53) 1 [Reference] 1 [Reference] 1 [Reference] Female 1 176 844 (47.32) 4017 (68.47) 2.56 (2.42-2.70) 2.55 (2.41-2.69) 2.62 (2.44-2.81) Age at birth, mean (SD), y Maternal 27.62 (5.05) 27.36 (5.10) 1.01 (1.01-1.02) 1.00 (1.00-1.01) 1.07 (1.04-1.11) Paternal 30.48 (5.88) 30.27 (5.84) 1.01 (1.01-1.01) 1.01 (1.00-1.01) 0.98 (0.96-1.01) Abbreviations: HR, hazard ratio; IM, infectious Parental MS mononucleosis; MS, multiple sclerosis. diagnosis Neither parent 2 470 095 (99.32) 5570 (94.94) 1 [Reference] 1 [Reference] 1 [Reference] Unless otherwise indicated, data are expressed as number (%) of participants. Either parent 17 018 (0.68) 297 (5.06) 8.00 (7.12-8.99) 8.04 (7.16-9.04) 1.95 (0.37-10.27) Birth order The association between each variable in the table and risk of an MS diagnosis was examined separately. First 1 286 766 (51.74) 3241 (55.24) 1 [Reference] 1 [Reference] 1 [Reference] All variables in the table were included. Second 861 430 (34.64) 2014 (34.33) 1.10 (1.04-1.17) 1.06 (1.00-1.12) 0.91 (0.83-0.99) Indicates within-sibling analysis in which the Third 269 191 (10.82) 512 (8.73) 1.15 (1.04-1.26) 1.08 (0.98-1.19) 0.81 (0.68-0.97) mother’s identification number was the stratification Fourth or 69 726 (2.80) 100 (1.70) 1.15 (0.94-1.41) 1.05 (0.86-1.29) 0.67 (0.49-0.91) variable; all variables in the table were included. subsequent IM, birth to 10 y Maternal age at birth was highly correlated with paternal age at birth (r = 0.73). To account for No 2 483 029 (99.84) 5851 (99.73) 1 [Reference] 1 [Reference] 1 [Reference] potential collinearity, parental ages at birth were Yes 4084 (0.16) 16 (0.27) 1.85 (1.13-3.02) 1.98 (1.21-3.23) 2.87 (1.44-5.74) included in 2 separate stratified Cox proportional IM, 11-19 y hazards regression models, where model 1 included No 2 469 259 (99.28) 5759 (98.16) 1 [Reference] 1 [Reference] 1 [Reference] maternal age at birth and the rest of the variables Yes 17 854 (0.72) 108 (1.84) 3.27 (2.70-3.95) 3.00 (2.48-3.63) 3.19 (2.29-4.46) listed (excluding paternal age) and model 2 included paternal age at birth and the rest of the variables IM, 20-24 y listed (excluding maternal age). The HRs for maternal No 2 482 238 (99.80) 5850 (99.71) 1 [Reference] 1 [Reference] 1 [Reference] age and paternal age at birth were 1.06 (95% CI, Yes 4875 (0.20) 17 (0.29) 1.69 (1.05-2.72) 1.89 (1.18-3.05) 1.51 (0.82-2.76) 1.04-1.08) and 1.03 (95% CI, 1.01-1.05), respectively. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 5/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis analysis 2 found no substantial differences in HR, excluding or including individuals born after 1987. Sensitivity analysis 3 also found no substantial differences in HR between within-sibling analysis and within-full-sibling analysis. Sensitivity analysis 4 found that IM in childhood (HR, 3.24; 95% CI, 1.87- 5.60) and adolescence (HR, 2.77; 95% CI, 2.08-3.68), but not in early adulthood, was associated with an increased risk of an MS diagnosis when the first demyelinating diseases of the CNS diagnosed from 20 years of age were defined as the possible onset of MS (and after exclusion of anyone with a demyelinating disease diagnosis before 20 years of age). Sensitivity analysis 5 found no substantial differences in HR when excluding or including families with only 1 parent alive in 1990. Discussion Hospital-diagnosed IM in childhood and most notably in adolescence was associated with increased risk of a subsequent MS diagnosis, independent of measured and unmeasured shared familial factors addressed by stratified Cox proportional hazards regression. There was less evidence of an independent association of MS with IM in early adulthood. This age-defined pattern of risk may reflect variation in susceptibility to environmental exposures due to developmental changes of the immune system and CNS. Because MS may have an asymptomatic or prodromal period of approximately 5 to 10 years before clinical onset, a diagnosis of IM in adolescence could potentially signal that IM is a consequence of prodromal MS. Allowing a delay of at least 5 years between IM and MS (with evidence of even longer intervals between IM and MS in further sensitivity analyses) helps to alleviate such concerns, because the magnitude of the estimates for the association of IM in adolescence with subsequent MS were not attenuated. Also, IM in early adulthood was not so notably associated with MS. Table 2. Adjusted HRs for Risk of MS Diagnosis From Sensitivity Analyses Stratified Cox proportional hazards regression, HR (95% CI) Age at IM Sensitivity Sensitivity Sensitivity Sensitivity Sensitivity b c d e f diagnosis analysis 1 analysis 2 analysis 3 analysis 4 analysis 5 Birth to 10 y No 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] Yes 3.72 (1.44-9.56) 2.60 (1.23-5.50) 2.68 (1.32-5.45) 3.24 (1.87-5.60) 2.90 (1.45-5.80) 11-19 y No 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] Yes 3.96 (2.65-5.90) 3.45 (2.34-5.08) 3.45 (2.43-4.89) 2.77 (2.08-3.68) 3.26 (2.32-4.57) 20-24 y No 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] Yes 1.89 (0.99-3.62) 1.51 (0.80-2.83) 1.76 (0.97-3.22) 1.48 (0.91-2.38) 1.53 (0.85-2.72) Abbreviations: HR, hazard ratio; IM, infectious mononucleosis; MS, multiple sclerosis. All variables listed in the table and parental ages at birth, a parental MS diagnosis, birth order, and sex were included in the sensitivity analyses. Uses a first MS diagnosis from 25 years of age to further exclude the possibility of reverse causation. Excludes individuals who were born after 1987 to examine the influence of the incomplete national coverage of the National Patient Register until 1987 on the association between IM and risk of an MS diagnosis. Only includes families with the same mother and father for all of the children (within full sibling analysis). Uses the first demyelinating diseases of the central nervous system diagnosed from 20 years of age as possible onset of MS. Includes families with either parent still alive in 1990. Because maternal age at birth was highly correlated with paternal age at birth (r = 0.73), maternal age at birth data missing for families with only the father still alive in 1990 (1.46% of the population included) was replaced by the paternal age at birth. Similarly, paternal age at birth data missing for families with only the mother still alive in 1990 (5.14% of the population included) was replaced by the maternal age at birth. Parental MS diagnosis was only for either the mother’s or the father’s diagnosis for families with only the mother or the father still alive in 1990 (6.60% of population included). JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 6/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis Infection with EBV in early childhood is common and typically asymptomatic, which reduces the possibility of experiencing subsequent IM owing to EBV, just as the risk of more severe manifestations of other infections increases with age (eg, for poliomyelitis). This is consistent with the association of having older siblings and reduced MS risk, because having older siblings may increase infection risk at an earlier age, thereby reducing risk of other immune-mediated 25,26 diseases. We speculate that the intense immune activation associated with IM (rather than EBV infection per se) results in priming with possible recruitment of mimicry autoimmunity, thus increasing MS risk. We used hospital-diagnosed IM in this study, which is likely to identify more severe manifestations. The waning of IM-associated risk for MS after adolescence is consistent with other research. Our results suggest that childhood and in particular adolescence seem to be periods when acute IM is relevant to MS risk. Such an age-specific pattern is consistent with prior research on other environmental risk factors, in which some exposures seem to have greater consequences in adolescence than in earlier childhood, including hospital-diagnosed infections other than EBV or IM. Mechanisms that potentially explain why acute IM (during age-defined periods of heightened susceptibility) is associated with increased risk of an MS diagnosis include the cross-activation of autoreactive T cells to the CNS due to the homologous sequences or structures shared between the EBV pathogens and myelin antigens. Three EBV proteins—the tegument protein BRRF2, EBNA-1, and the small capsid protein (BFRF3)—share epitopes with myelin basic proteins (eg, DLST and 28,29 septin-9). Antibodies to BRRF2, EBNA-1, and BFRF3 cross-react with myelin antigens, which can 28,29 lead to recurrent autoimmune CNS damage. Antibodies to EBNA-1 can also cross-react with the chloride-channel protein anoctamin 2 and are associated with increased MS risk. Indeed, a significantly increased presence of anti–viral capsid antigen IgG and anti-EBNA-1 IgG antibodies and + + significantly higher CD4 and CD8 T-cell responses to EBNA-1 have been reported in patients with MS compared with control individuals. The EBV-infected autoreactive B cells hypothesis may be another possible mechanism: EBV infects resting B cells and converts them into immortalized lymphoblastoid cell lines, resulting in the production of ENBA-1 through ENBA-6 and latent membrane proteins (LMP-1, LMP-2A, and LMP-2B). B cells can further transform into memory B cells because LMP-1 mimics CD40 signaling. The memory B cells can infiltrate the blood-brain barrier, then become activated and develop into antibody-secreting plasma cells triggered by 33 34 interleukin 21, causing inflammation in the CNS and in turn increasing MS risk. B cells and 34,35 plasmablasts/plasma cells are present in various parts of the CNS in patients with MS. Our findings lend further weight to the notion that EBV plays a role in pathogenesis, where the pattern of exposure and acute manifestation of the infection are relevant, rather than being a bystander phenomenon due to MS disease activity or susceptibility to MS resulting in a greater likelihood of IM. Older maternal, rather than paternal, age at birth was another risk factor for MS diagnosis, which is inconsistent with prior research, possibly because maternal and paternal age are highly correlated (r = 0.73). When only paternal age or maternal age at birth were included in the adjusted stratified Cox proportional hazards regression, both were associated with an increased risk of an MS diagnosis. A diagnosis of MS in a parent conveyed a high magnitude of increased risk for MS, indicating the importance of genetic predisposition. As expected, this association was attenuated by stratified Cox proportional hazards regression that adjusted for shared familial factors. Strengths and Limitations The strengths of this study include the use of a large population-based birth cohort with sufficient statistical power and prospective recording of IM before MS diagnosis. We also examined IM at 3 theoretically relevant developmental stages (childhood, adolescence, and early adulthood) to assess potential periods of susceptibility to EBV exposure. Importantly, stratified Cox proportional hazards regression was used to reduce confounding by shared familial factors invariant among each sibling cluster. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 7/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis This study also has some limitations. Infectious mononucleosis diagnosed and treated in primary care could not be included, and hospital-based outpatient diagnoses were not available until 2001, likely resulting in selection of more severe acute manifestations of the infection. Some IM and MS diagnoses may be missing owing to the incomplete national coverage for inpatient registrations before 1987 and the unavailability of outpatient information before 2001, though our sensitivity analysis found no substantial differences in HRs between analyses including and excluding individuals who were born after 1987. We could not assess MS onset earlier than the first MS diagnosis because the first symptomatic onset of MS could not be identified in the current study. However, excluding those with any demyelinating diseases before 20 years of age and extending the minimal interval between putative exposure and diagnosis did not suggest reverse causation. We could not adjust for vitamin D level, smoking, and body mass index. However, there are strong shared familial influences for body mass 37-40 index, smoking, and vitamin D levels in childhood and adolescence, so the stratified Cox proportional hazards regression should have addressed this issue, at least in part. For complete family linkage and information from both parents, parents had to survive to at least 1990, thus possibly introducing selection bias. A sensitivity analysis based on only 1 surviving parent did not produce notably different results. Conclusions The findings of this population–based cohort study suggest that IM in childhood and particularly adolescence is associated with a subsequent MS diagnosis, independent of shared familial factors. Therefore, greater susceptibility to infection is less likely to be the explanation. ARTICLE INFORMATION Accepted for Publication: July 12, 2021. Published: October 11, 2021. doi:10.1001/jamanetworkopen.2021.24932 Open Access: This is an open access article distributed under the terms of the CC-BY License.©2021XuYetal. JAMA Network Open. Corresponding Author: Scott Montgomery, PhD, Clinical Epidemiology and Biostatistics, School of Medical Sciences, Campus USÖ, Örebro University, SE-703 62 Örebro, Sweden (scott.montgomery@oru.se). Author Affiliations: Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden (Xu, Hiyoshi, Fall, Montgomery); Department of Public Health Sciences, Stockholm University, Stockholm, Sweden (Hiyoshi); Department of Epidemiology and Public Health, University College London, London, United Kingdom (Hiyoshi, Montgomery); Clinical Epidemiology Division, Karolinska Institute, Stockholm, Sweden (Smith, Montgomery); Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden (Piehl, Olsson); Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden (Fall). Author Contributions: Dr Xu had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Olsson, Montgomery. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Xu, Olsson. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Xu, Smith. Obtained funding: Hiyoshi, Piehl, Olsson, Montgomery. Administrative, technical, or material support: Piehl, Olsson, Montgomery. Supervision: Olsson, Montgomery. Conflict of Interest Disclosures: Ms Smith reported receiving grants from AstraZeneca and the Multiple Sclerosis Society of Canada outside the submitted work. Dr Piehl reported receiving grants from the Swedish Medical JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 8/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis Research Council and the County of Stockholm during the conduct of the study and receiving unrestricted academic research grants from Sanofi Genzyme, Merck KGaA, and UCB outside the submitted work. Dr Olsson reported receiving unrestricted MS research grants and/or honoraria for advisory boards/lectures from Biogen Inc, Novartis International AG, Sanofi Genzyme, AstraZeneca PLC, and Merck & Co, Inc. Dr Montgomery reported receiving grants from the UK Social and Economic Research Council and Nyckelfonden (medical charity in Sweden) during the conduct of the study and receiving grants from Roche, Novartis International AG, and AstraZeneca; receiving honorarium for a lecture from Teva Pharmaceutical Industries Ltd; and serving on the advisory board for a study for IQVIA (with payment to Örebro University Hospital) outside the submitted work. No other disclosures were reported. Funding/Support: This study was supported by a grant from Nyckelfonden, grant ES/R008930/1 from the UK Economic and Social Research Council (International Centre for Life Course Studies), and grant 2019-01236 from the Swedish Research Council for Health, Working Life and Welfare (Forte). Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. REFERENCES 1. Hedström AK, Huang J, Michel A, et al. High levels of Epstein–Barr virus nuclear antigen-1–specific antibodies and infectious mononucleosis act both independently and synergistically to increase multiple sclerosis risk. Front Neurol. 2020;10:1368. doi:10.3389/fneur.2019.01368 2. Belbasis L, Bellou V, Evangelou E, Ioannidis JP, Tzoulaki I. Environmental risk factors and multiple sclerosis: an umbrella review of systematic reviews and meta-analyses. Lancet Neurol. 2015;14(3):263-273. doi:10.1016/S1474- 4422(14)70267-4 3. Burnard S, Lechner-Scott J, Scott RJ. EBV and MS: major cause, minor contribution or red-herring? Mult Scler Relat Disord. 2017;16:24-30. doi:10.1016/j.msard.2017.06.002 4. Rubicz R, Yolken R, Drigalenko E, et al. A genome-wide integrative genomic study localizes genetic factors influencing antibodies against Epstein-Barr virus nuclear antigen 1 (EBNA-1). PLoS Genet. 2013;9(1):e1003147. doi: 10.1371/journal.pgen.1003147 5. Zhou Y, Zhu G, Charlesworth JC, et al; ANZgene consortium. Genetic loci for Epstein-Barr virus nuclear antigen-1 are associated with risk of multiple sclerosis. Mult Scler. 2016;22(13):1655-1664. doi:10.1177/1352458515626598 6. Kreft KL, Van Nierop GP, Scherbeijn SMJ, Janssen M, Verjans GMGM, Hintzen RQ. Elevated EBNA-1 IgG in MS is associated with genetic MS risk variants. Neurol Neuroimmunol Neuroinflamm. 2017;4(6):e406. doi:10.1212/NXI. 7. Dobson R, Jitlal M, Marshall CR, et al. Ethnic and socioeconomic associations with multiple sclerosis risk. Ann Neurol. 2020;87(4):599-608. doi:10.1002/ana.25688 8. Langer-Gould A, Wu J, Lucas R, et al. Epstein-Barr virus, cytomegalovirus, and multiple sclerosis susceptibility: a multiethnic study. Neurology. 2017;89(13):1330-1337. doi:10.1212/WNL.0000000000004412 9. Ascherio A, Munger KL. Environmental risk factors for multiple sclerosis, part I: the role of infection. Ann Neurol. 2007;61(4):288-299. doi:10.1002/ana.21117 10. Handel AE, Williamson AJ, Disanto G, Handunnetthi L, Giovannoni G, Ramagopalan SV. An updated meta- analysis of risk of multiple sclerosis following infectious mononucleosis. PLoS One. 2010;5(9):e12496. doi:10.1371/ journal.pone.0012496 11. Smith KA, Hiyoshi A, Burkill S, et al. Hospital diagnosed pneumonia before age 20 years and multiple sclerosis risk. BMJ Neurol Open. 2020;2(1):e000044. doi:10.1136/bmjno-2020-000044 12. Xu Y, Smith KA, Hiyoshi A, Piehl F, Olsson T, Montgomery S. Hospital-diagnosed infections before age 20 and risk of a subsequent multiple sclerosis diagnosis. Brain. Published online March 9, 2021. doi:10.1093/ brain/awab100 13. Xu Y, Hiyoshi A, Brand JS, et al. Higher body mass index at ages 16 to 20 years is associated with increased risk of a multiple sclerosis diagnosis in subsequent adulthood among men. Mult Scler. 2021;27(1):147-150. doi:10.1177/ 14. Montgomery S, Hiyoshi A, Burkill S, Alfredsson L, Bahmanyar S, Olsson T. Concussion in adolescence and risk of multiple sclerosis. Ann Neurol. 2017;82(4):554-561. doi:10.1002/ana.25036 15. Munger KL, Levin LI, Hollis BW, Howard NS, Ascherio A. Serum 25-hydroxyvitamin D levels and risk of multiple sclerosis. JAMA. 2006;296(23):2832-2838. doi:10.1001/jama.296.23.2832 16. Nielsen TR, Rostgaard K, Nielsen NM, et al. Multiple sclerosis after infectious mononucleosis. Arch Neurol. 2007;64(1):72-75. doi:10.1001/archneur.64.1.72 JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 9/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis 17. Ludvigsson JF, Almqvist C, Bonamy AK, et al. Registers of the Swedish total population and their use in medical research. Eur J Epidemiol. 2016;31(2):125-136. doi:10.1007/s10654-016-0117-y 18. Ludvigsson JF, Andersson E, Ekbom A, et al. External review and validation of the Swedish national inpatient register. BMC Public Health. 2011;11(1):450. doi:10.1186/1471-2458-11-450 19. Miller DH, Weinshenker BG, Filippi M, et al. Differential diagnosis of suspected multiple sclerosis: a consensus approach. Mult Scler. 2008;14(9):1157-1174. doi:10.1177/1352458508096878 20. Murley C, Friberg E, Hillert J, Alexanderson K, Yang F. Validation of multiple sclerosis diagnoses in the Swedish National Patient Register. Eur J Epidemiol. 2019;34(12):1161-1169. doi:10.1007/s10654-019-00558-7 21. Marrie RA, Fisk JD, Stadnyk KJ, et al; CIHR Team in the Epidemiology and Impact of Comorbidity on Multiple Sclerosis. The incidence and prevalence of multiple sclerosis in Nova Scotia, Canada. Can J Neurol Sci. 2013;40(6): 824-831. doi:10.1017/S0317167100015961 22. Marrie RA, Yu N, Blanchard J, Leung S, Elliott L. The rising prevalence and changing age distribution of multiple sclerosis in Manitoba. Neurology. 2010;74(6):465-471. doi:10.1212/WNL.0b013e3181cf6ec0 23. Tremlett H, Marrie RA. The multiple sclerosis prodrome: emerging evidence, challenges, and opportunities. Mult Scler. 2021;27(1):6-12. doi:10.1177/1352458520914844 24. Nathanson N, Kew OM. From emergence to eradication: the epidemiology of poliomyelitis deconstructed. Am J Epidemiol. 2010;172(11):1213-1229. doi:10.1093/aje/kwq320 25. Conradi S, Malzahn U, Schröter F, et al. Environmental factors in early childhood are associated with multiple sclerosis: a case-control study. BMC Neurol. 2011;11(1):123. doi:10.1186/1471-2377-11-123 26. Ponsonby AL, van der Mei I, Dwyer T, et al. Exposure to infant siblings during early life and risk of multiple sclerosis. JAMA. 2005;293(4):463-469. doi:10.1001/jama.293.4.463 27. Ramagopalan SV, Dobson R, Meier UC, Giovannoni G. Multiple sclerosis: risk factors, prodromes, and potential causal pathways. Lancet Neurol. 2010;9(7):727-739. doi:10.1016/S1474-4422(10)70094-6 28. Cepok S, Zhou D, Srivastava R, et al. Identification of Epstein-Barr virus proteins as putative targets of the immune response in multiple sclerosis. J Clin Invest. 2005;115(5):1352-1360. doi:10.1172/JCI200523661 29. Lindsey JW. Antibodies to the Epstein-Barr virus proteins BFRF3 and BRRF2 cross-react with human proteins. J Neuroimmunol. 2017;310:131-134. doi:10.1016/j.jneuroim.2017.07.013 30. Tengvall K, Huang J, Hellström C, et al. Molecular mimicry between Anoctamin 2 and Epstein-Barr virus nuclear antigen 1 associates with multiple sclerosis risk. Proc Natl Acad SciUSA. 2019;116(34):16955-16960. doi: 10.1073/pnas.1902623116 31. Santiago O, Gutierrez J, Sorlozano A, de Dios Luna J, Villegas E, Fernandez O. Relation between Epstein-Barr virus and multiple sclerosis: analytic study of scientific production. Eur J Clin Microbiol Infect Dis. 2010;29(7): 857-866. doi:10.1007/s10096-010-0940-0 32. Baker D, Pryce G, Amor S, Giovannoni G, Schmierer K. Learning from other autoimmunities to understand targeting of B cells to control multiple sclerosis. Brain. 2018;141(10):2834-2847. doi:10.1093/brain/awy239 33. Kuchen S, Robbins R, Sims GP, et al. Essential role of IL-21 in B cell activation, expansion, and plasma cell generation during CD4 T cell–B cell collaboration. J Immunol. 2007;179(9):5886-5896. doi:10.4049/jimmunol. 179.9.5886 34. Michel L, Touil H, Pikor NB, Gommerman JL, Prat A, Bar-Or A. B cells in the multiple sclerosis central nervous system: trafficking and contribution to CNS-compartmentalized inflammation. Front Immunol. 2015;6:636. doi:10. 3389/fimmu.2015.00636 35. Serafini B, Rosicarelli B, Franciotta D, et al. Dysregulated Epstein-Barr virus infection in the multiple sclerosis brain. J Exp Med. 2007;204(12):2899-2912. doi:10.1084/jem.20071030 36. Montgomery SM, Lambe M, Olsson T, Ekbom A. Parental age, family size, and risk of multiple sclerosis. Epidemiology. 2004;15(6):717-723. doi:10.1097/01.ede.0000142138.46167.69 37. Elks CE, den Hoed M, Zhao JH, et al. Variability in the heritability of body mass index: a systematic review and meta-regression. Front Endocrinol (Lausanne). 2012;3:29. doi:10.3389/fendo.2012.00029 38. Leonardi-Bee J, Jere ML, Britton J. Exposure to parental and sibling smoking and the risk of smoking uptake in childhood and adolescence: a systematic review and meta-analysis. Thorax. 2011;66(10):847-855. doi:10.1136/ thx.2010.153379 39. Munafò M, Clark T, Johnstone E, Murphy M, Walton R. The genetic basis for smoking behavior: a systematic review and meta-analysis. Nicotine Tob Res. 2004;6(4):583-597. doi:10.1080/14622200410001734030 40. Bahrami A, Sadeghnia HR, Tabatabaeizadeh SA, et al. Genetic and epigenetic factors influencing vitamin D status. J Cell Physiol. 2018;233(5):4033-4043. doi:10.1002/jcp.26216 JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 10/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis SUPPLEMENT. eMethods. Study Population eTable. Adjusted Hazard Ratios for Risk of a Multiple Sclerosis Diagnosis With Infectious Mononucleosis in Smaller Age Categories and Follow-up for First Multiple Sclerosis Diagnosis at Different Ages eFigure. Scaled Schoenfeld Residuals Plotted Against Time for Paternal Age at Birth, a Parental MS Diagnosis, and Birth Order eReferences JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 11/11 Supplementary Online Content Xu Y, Hiyoshi A, Smith KA, et al. Association of infectious mononucleosis in childhood and adolescence with risk for a subsequent multiple sclerosis diagnosis among siblings. JAMA Netw Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 eMethods. Study Population eTable. Adjusted Hazard Ratios for Risk of a Multiple Sclerosis Diagnosis With Infectious Mononucleosis in Smaller Age Categories and Follow-up for First Multiple Sclerosis Diagnosis at Different Ages eFigure. Scaled Schoenfeld Residuals Plotted Against Time for Paternal Age at Birth, a Parental MS Diagnosis, and Birth Order eReferences This supplementary material has been provided by the authors to give readers additional information about their work. © 2021 Xu Y et al. JAMA Network Open. eMethods. Study Population Two Swedish general population-based registers with high validity were used in the current study: the Total Population Register and the National Patient Register. The unique individual Swedish personal identification number was used for data linkage. The Total Population Register has been updated annually since 1968 and collects life events for the entire population of Sweden, including dates of birth, death, and migration. The National Patient Register for inpatient care was established in 1964 and attained complete national coverage in 1987, with hospital-based outpatient diagnoses collected since 2001. The National Patient Register contains data on all inpatient and outpatient diagnoses, admission, discharge, and procedures in hospital. © 2021 Xu Y et al. JAMA Network Open. eTable. Adjusted Hazard Ratios for Risk of a Multiple Sclerosis Diagnosis With Infectious Mononucleosis in Smaller Age Categories and Follow-up for First Multiple Sclerosis Diagnosis at Different Ages Stratified Cox regression Analysis-1 Analysis-2 Analysis-3 MS from age 20 years MS ages 20 to 30 years MS after age 30 years IM, birth to age 5 years No 1 (reference) 1 (reference) 1 (reference) Yes 1.39 (0.49-3.99) 1.24 (0.36-4.29) 2.13 (0.26-17.37) IM, age 6-10 years No 1 (reference) 1 (reference) 1 (reference) Yes 5.72 (1.93-16.96) 5.51 (1.16-26.17) 6.10 (1.38-26.93) IM, age 11-15 years No 1 (reference) 1 (reference) 1 (reference) Yes 3.45 (1.93-6.17) 2.17 (1.04-4.52) 7.50 (3.02-18.63) IM, age 16-19 years No 1 (reference) 1 (reference) 1 (reference) Yes 3.10 (2.09-4.60) 2.98 (1.77-5.00) 3.64 (1.95-6.79) IM, age 20-24 years No 1 (reference) 1 (reference) 1 (reference) Yes 1.50 (0.82-2.76) 0.97 (0.35-2.69) 2.60 (1.07-6.36) © 2021 Xu Y et al. JAMA Network Open. Abbreviations: IM = infectious mononucleosis. MS = multiple sclerosis Hazard ratios and 95% confidence interval from stratified Cox regression (within-sibling analysis with as the stratification variable), adjusted for sex, parental age at birth, parental multiple sclerosis diagnosis, and birth order, were reported here. st For analysis-1, follow-up was from age 20 years until the first diagnosis of MS, death, first emigration, or study end (31 December 2018), whichever occurred first. For analysis-2, follow-up was from age 20 until the first diagnosis of MS, death, first emigration, attaining the age st of 30 years, or study end (31 December 2018), whichever occurred first. For analysis-3, follow-up was from after age 30 years until the first st diagnosis of MS, death, first emigration, or study end (31 December 2018), whichever occurred first. © 2021 Xu Y et al. JAMA Network Open. eFigure. Scaled Schoenfeld Residuals Plotted Against Time for Paternal Age at Birth, a Parental MS Diagnosis, and Birth Order For birth order, the first-born was the reference group. MS = multiple sclerosis; SC = Schoenfeld residuals. © 2021 Xu Y et al. JAMA Network Open. eReferences 1. Ludvigsson JF, Almqvist C, Bonamy AK, et al. Registers of the Swedish total population and their use in medical research. Eur J Epidemiol. 2016;31(2):125-136. doi:10.1007/s10654-016-0117-y 2. Ludvigsson JF, Andersson E, Ekbom A, et al. External review and validation of the Swedish national inpatient register. BMC Public Health. 2011;11(1):450. doi:10.1186/1471-2458-11-450 © 2021 Xu Y et al. JAMA Network Open. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JAMA Network Open American Medical Association

Association of Infectious Mononucleosis in Childhood and Adolescence With Risk for a Subsequent Multiple Sclerosis Diagnosis Among Siblings

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Copyright 2021 Xu Y et al. JAMA Network Open.
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10.1001/jamanetworkopen.2021.24932
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Abstract

Key Points Question Is diagnosis of infectious IMPORTANCE Epstein-Barr virus and its acute manifestation, infectious mononucleosis (IM), are mononucleosis (IM) in childhood or associated with an increased risk of multiple sclerosis (MS). Whether this association is confounded adolescence associated with by susceptibility to infection is still debated. subsequent development of multiple sclerosis (MS)? OBJECTIVE To assess whether hospital-diagnosed IM during childhood, adolescence, or young Findings In this population–based adulthood is associated with subsequent MS diagnosis independent of shared familial factors. cohort study of 2 492 980 individuals in Sweden, IM in childhood and DESIGN, SETTING, AND PARTICIPANTS This population–based cohort study used the Swedish adolescence was associated with an Total Population Register to identify individuals born in Sweden from January 1, 1958, to December increased risk of a subsequent MS 31, 1994. Participants aged 20 years were followed up from January 1, 1978, to December 31, 2018, diagnosis that remained significant after with a median follow-up of 15.38 (IQR, 8.68-23.55; range, 0.01-40.96) years. Data were analyzed controlling for measured and from October 2020 to July 2021. unmeasured shared familial factors. EXPOSURE Hospital-diagnosed IM before 25 years of age. Meaning These findings suggest that IM in childhood and particularly MAIN OUTCOMES AND MEASURES Diagnoses of MS from 20 years of age were identified. Risk of adolescence is a risk factor for a an MS diagnosis associated with IM in childhood (birth to 10 years of age), adolescence (11-19 years subsequent MS diagnosis, independent of age), and early adulthood (20-24 years of age [time-dependent variable]) were estimated using of shared familial factors, making it less conventional and stratified (to address familial environmental or genetic confounding) Cox likely that greater susceptibility to proportional hazards regression. infection is the explanation. RESULTS Of the 2 492 980 individuals (1 312 119 men [52.63%] and 1 180 861 women [47.37%]) Supplemental content included, 5867 (0.24%) had an MS diagnosis from 20 years of age (median age, 31.50 [IQR, 26.78- 37.54] years). Infectious mononucleosis in childhood (hazard ratio [HR], 1.98; 95% CI, 1.21-3.23) and Author affiliations and article information are listed at the end of this article. adolescence (HR, 3.00; 95% CI, 2.48-3.63) was associated with an increased risk of an MS diagnosis that remained significant after controlling for shared familial factors in stratified Cox proportional hazards regression (HRs, 2.87 [95% CI, 1.44-5.74] and 3.19 [95% CI, 2.29-4.46], respectively). Infectious mononucleosis in early adulthood was also associated with risk of a subsequent MS diagnosis (HR, 1.89; 95% CI, 1.18-3.05), but this risk was attenuated and was not significant after controlling for shared familial factors (HR, 1.51; 95% CI, 0.82-2.76). CONCLUSIONS AND RELEVANCE These findings suggest that IM in childhood and particularly adolescence is a risk factor associated with a diagnosis of MS, independent of shared familial factors. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 Open Access. This is an open access article distributed under the terms of the CC-BY License. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 1/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis Introduction Infectious mononucleosis (IM) is a clinical manifestation of viral infection, predominantly caused by Epstein-Barr virus (EBV). Both IM and high levels of anti-EBV nuclear antigen 1 (EBNA-1) antibodies 1,2 are associated with an increased risk for multiple sclerosis (MS). However, the nature of the association between IM and MS is still debated. This association might be explained, at least in part, by common genetic factors relevant to the acute manifestation of IM, subsequent antibody levels, and MS risk. Genome-wide association studies have found that loci in the human leukocyte antigen (HLA) region, such as HLA-DRB1 and HLA-DQA1 genes, are 4-6 associated with both MS risk and elevated anti-EBNA IgG levels. The possibility of confounding is suggested by studies showing that the increased MS risk associated with IM decreased in magnitude or became statistically nonsignificant after controlling for potential confounders, including genetic ancestry and HLA-DRB1*1501 carrier status. However, few studies have extensively addressed measured and unmeasured shared familial genetic and environmental factors as potential confounders that may be associated with both IM and MS. Therefore, methods such as within-sibling studies, which control for unmeasured shared familial factors (because members of the same family share important characteristics) by comparing siblings discordant for IM, are needed to better understand the relationship between IM and MS. Adolescence may be an important period of susceptibility for the putative association of IM with 9,10 MS pathogenesis compared with earlier childhood, consistent with associations for other risk 11,12 13 factors for MS in adolescence: pneumonia and other infections, higher body mass index, 14 15 concussion, and lower serum vitamin D levels. Infectious mononucleosis in early adulthood (20-24 years of age) has also been associated with increased MS risk, although the effect size is smaller than for IM in adolescence. This study used a large population–based birth cohort in Sweden to assess the association of hospital-diagnosed IM in childhood (from birth to 10 years of age) and adolescence (11-19 years of age) with risk of an MS diagnosis from 20 years of age. The association of IM in early adulthood (20-24 years of age) with a subsequent MS diagnosis was also assessed by treating IM as a time- dependent variable to ensure that IM predates the MS diagnosis. Cox proportional hazards regression stratified by family to compare siblings (within-sibling analysis) was used to account for measured and unmeasured shared familial factors. If the association between IM and MS is confounded by shared familial factors, the magnitude of estimates and statistical significance would be attenuated when results from within-sibling analyses are compared with conventional analyses. Methods Study Population This population-based cohort, which was identified by the Total Population Register, comprised all individuals born in Sweden from January 1, 1958, to December 31, 1994, who reached 25 years of age from January 1, 1990, to December 31, 2019, with both parents also alive in 1990 to facilitate identification of all first-degree relatives and identify MS diagnoses in parents. Participants aged 20 years were followed up from January 1, 1978, to December 31, 2018, with a median follow-up of 15.38 (IQR, 8.68-23.55; range, 0.01-40.96) years. The unique individual Swedish personal identification number was used for data linkage across various Swedish registers to identify cohort members’ 17,18 hospital-based diagnoses and their first-degree relatives (eMethods in the Supplement). The analysis was restricted to the youngest generation (including familial information on parents), because most parents, their siblings, and grandparents and their siblings were born at an earlier period when register coverage was too incomplete to adequately capture information on IM in childhood among them. A total of 2 492 980 individuals were included in this study (Figure). Ethical approval for this study was received from the Swedish Ethical Review Authority. Informed consent was not required by the authority because the study was based only on anonymized register data. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 2/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies. Outcome A diagnosis of MS from 20 years of age was identified for members of the index cohort or at any age for parents using International Classification of Diseases, Eighth Revision (ICD-8)or International Classification of Diseases, Ninth Revision (ICD-9) code 340 and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) code G35. To ensure diagnostic accuracy, 2 MS diagnoses recorded at a minimum of 6 months apart were required, which makes exclusion of misdiagnoses and relevant differential diagnoses more likely. Validation studies have shown a high level of accuracy both for MS diagnoses (positive predictive value of 92.50%) and when using at least 2 MS diagnoses to identify MS (positive predictive value and sensitivity >0.90%). The first diagnosis was used to define date of first MS diagnosis. Individuals with only 1 MS diagnosis or with separate MS diagnoses recorded within 6 months were not considered to have confirmed MS (n = 920). Exposure and Potential Confounding Factors Primary or secondary diagnoses of IM before 25 years of age were identified using ICD-8 or ICD-9 code 075 and ICD-10 code B27 (EBV titer data were not available). To examine the age-defined periods of potential susceptibility for the association of IM with risk of an MS diagnosis, IM diagnoses before 25 years of age were categorized as occurring in childhood (from birth to 10 years of age), in 9,10,16 adolescence (11-19 years of age), or in early adulthood (20-24 years of age). Sex, an MS diagnosis in either parent, birth order (first, second, third, or fourth or subsequent), and maternal and paternal age at birth of the cohort member (the difference between cohort member’s date of birth and parents’ date of birth divided by 365.25) were considered potential confounding factors. Statistical Analysis Data were analyzed from October 2020 to July 2021. There was no missing information for outcome and confounding factors. Three individuals who had missing information for date of IM diagnosis were excluded (Figure). STATA, version 16.0 (StataCorp LLC), was used for data analysis. Conventional Cox proportional hazards regression was used to test the association between IM in childhood or adolescence and the risk of an MS diagnosis from 20 years of age. The association of IM in early adulthood with a subsequent MS diagnosis was also examined. Follow-up was from 20 years of age until the first diagnosis of MS, death, first emigration, or study end (December 31, 2018), whichever occurred first. Cohort members who emigrated were censored on the date of first leaving Sweden and could not reenter the cohort to ensure no gaps in follow-up. We split follow-up time before and after the date of an IM diagnosis in early adulthood to model early adulthood IM diagnosis as a time-dependent covariate (ensuring we only considered associations with subsequent MS diagnoses). We adjusted for sex, parental MS diagnosis, birth order, and parental age at birth. Figure. Flowchart of Participant Selection 3 546 995 Patients assessed for eligibility 1 054 015 Excluded Temporary duplicates are due to the assignment of a 4436 Temporary duplicates of personal identification number previously deceased person's personal identification 438 With at least 1 diagnosis of MS before age 20 y number to some immigrants to Sweden. Parents, their 3 Missing date of IM diagnosis siblings, and grandparents and their siblings were not 996 428 Parents and parents’ siblings 52 710 Died or emigrated before age 20 y members of the analysis cohort because register coverage was more incomplete during their childhood. IM indicates infectious mononucleosis; MS, multiple 2 492 980 Included in the primary analysis sclerosis. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 3/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis Second-degree fractional polynomials suggested that parental age at birth was linearly associated with risk of an MS diagnosis. Violations of the proportional hazards assumption were detected for paternal age at birth, a parental MS diagnosis, and birth order using Schoenfeld residuals. However, the effect of violation was minimal based on scaled Schoenfeld residuals plotted against time (eFigure in the Supplement). Thus, results from analyses assuming proportional hazards are reported herein. Further analyses subdivided age categories for IM into 5-year periods and considered first MS diagnosis from 20 to 30 years of age or after 30 years of age (eTable in the Supplement). To adjust for measured and unmeasured familial factors through estimating a cluster (sibling- set)–specific baseline hazard, stratified Cox proportional hazards regression was used for within- sibling analysis where the mother’s identification number was the stratification variable. The follow-up time and variables included in the analysis were the same as those described above. The magnitude of shared familial confounding was measured as the attenuation of estimates from Cox proportional hazards regression models stratified by family, compared with conventional Cox proportional hazards regression. For the stratified Cox proportional hazards regression, fractional polynomials suggested that parental age at birth was linearly associated with risk of an MS diagnosis. Violation of the proportional hazards assumption was detected for birth order using Schoenfeld residuals. Again, the effect of violation was minimal based on scaled Schoenfeld residuals plotted against time. Thus, results from analyses assuming proportional hazards were reported. Huber-White SEs were used to account for clustering within families. A total of 5 sensitivity analyses using stratified Cox proportional hazards regression were performed. Sensitivity analysis 1 used a first MS diagnosis from 25 years of age to reduce possible bias because MS may have a relatively long prodromal period. Sensitivity analysis 2 excluded individuals who were born after 1987 to examine the potential influence of the incomplete national coverage of the Swedish Patient Register until 1987 on the association between IM and risk of an MS diagnosis. Sensitivity analysis 3 only included families with the same mother and father for all the children (within-full-sibling analysis). Sensitivity analysis 4 used the first diagnosis of any demyelinating disease of the central nervous system (CNS) to define the onset date of MS (individuals with a demyelinating disease–defined onset of MS before 20 years of age were excluded) as follows: MS, acute disseminated encephalomyelitis, optic neuritis, other acute disseminated demyelination, and other demyelinating disease of the CNS (ICD-8 or ICD-9 codes 323, 340, and 341 and ICD-10 codes G04, H46, G35, G36, and G37). Acute disseminated encephalitis could not be identified in our data because ICD code precision of 4 digits is required, which was not available; therefore, encephalomyelitis diagnoses (ICD-8 or ICD-9 code 323 and ICD-10 code G04) were exclusion criteria because they include acute disseminated encephalitis. Sensitivity analysis 5 included families with either parent alive in 1990 to address potential selection bias. Results Cohort Characteristics A total of 2 492 980 individuals (1 312 119 men [52.63%] and 1 180 861 women [47.37%]; 1 290 007 first born [51.75%]; 26 954 [1.08%] with IM before 25 years of age; and 17 315 [0.69%] with either parent having an MS diagnosis) were included in this population–based cohort study (Table 1). Of these, 5867 individuals (0.24%) had an MS diagnosis from 20 years of age, at a median age of 31.50 (IQR, 26.78-37.54; range, 20.01-58.93) years. Results from stratified Cox proportional hazards regression indicated that being female (hazard ratio [HR], 2.62; 95% CI, 2.44-2.81) and older maternal age at birth (HR for each additional year, 1.07; 95% CI, 1.04-1.11) were associated with increased risk of an MS diagnosis; later-born children were at lower risk of being diagnosed with MS compared with first-born children (HR for second born, 0.91 [95% CI, 0.83-0.99]; HR for third born, 0.81 [95% CI, 0.68-0.97]; HR for fourth born or subsequent birth, 0.67 [95% CI, 0.49-0.91]) (Table 1); paternal age at birth was not associated with an increased risk of an MS diagnosis (HR, 0.98; 95% CI, 0.96-1.01) (Table 1). As expected, the increased risk associated with either parent having an MS JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 4/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis diagnosis using an adjusted conventional Cox proportional hazards regression model (HR, 8.04; 95% CI, 7.16-9.04) became statistically nonsignificant after controlling for unmeasured shared familial factors using stratified Cox proportional hazards regression (HR, 1.95; 95% CI, 0.37-10.27). IM and Risk of an MS Diagnosis Compared with those without IM, individuals with IM in childhood and adolescence were at a greater risk of being diagnosed with MS using an adjusted conventional Cox proportional hazards regression model (HRs, 1.98 [95% CI, 1.21-3.23] and 3.00 [95% CI, 2.48-3.63], respectively). This risk remained statistically significant and increased in magnitude after further controlling for unmeasured shared familial factors using stratified Cox proportional hazards regression (HRs, 2.87 [95% CI, 1.44-5.74] and 3.19 [95% CI, 2.29-4.46], respectively). Infectious mononucleosis in early adulthood was associated with an increased risk of an MS diagnosis using an adjusted conventional Cox proportional hazards regression model but at a lower magnitude than at younger ages (HR, 1.89; 95% CI, 1.18-3.05). This risk became statistically nonsignificant after controlling for unmeasured shared familial factors using stratified Cox regression (HR, 1.51; 95% CI, 0.82-2.76). The eTable in the Supplement shows a similar pattern of rising and then waning risk with age, with no attenuation of risk magnitude when follow-up begins after 30 years of age. Sensitivity Analyses Results from sensitivity analyses are shown in Table 2. Restricting MS diagnoses to 25 years or older in sensitivity analysis 1 showed that the increased risk of being diagnosed with MS associated with IM in childhood and adolescence remained statistically significant and was not attenuated in magnitude (HRs, 3.72 [95% CI, 1.44-9.56] and 3.96 [95% CI, 2.65-5.90], respectively). Sensitivity Table 1. Characteristics of the Birth Cohort Stratified by MS With HRs for Risk of MS Diagnosis MS diagnosis Cox proportional hazards regression, HR (95% CI) Conventional Absent Present b c d Characteristic (n = 2 487 113) (n = 5867) Unadjusted Adjusted Stratified adjusted Sex Male 1 310 269 (52.68) 1850 (31.53) 1 [Reference] 1 [Reference] 1 [Reference] Female 1 176 844 (47.32) 4017 (68.47) 2.56 (2.42-2.70) 2.55 (2.41-2.69) 2.62 (2.44-2.81) Age at birth, mean (SD), y Maternal 27.62 (5.05) 27.36 (5.10) 1.01 (1.01-1.02) 1.00 (1.00-1.01) 1.07 (1.04-1.11) Paternal 30.48 (5.88) 30.27 (5.84) 1.01 (1.01-1.01) 1.01 (1.00-1.01) 0.98 (0.96-1.01) Abbreviations: HR, hazard ratio; IM, infectious Parental MS mononucleosis; MS, multiple sclerosis. diagnosis Neither parent 2 470 095 (99.32) 5570 (94.94) 1 [Reference] 1 [Reference] 1 [Reference] Unless otherwise indicated, data are expressed as number (%) of participants. Either parent 17 018 (0.68) 297 (5.06) 8.00 (7.12-8.99) 8.04 (7.16-9.04) 1.95 (0.37-10.27) Birth order The association between each variable in the table and risk of an MS diagnosis was examined separately. First 1 286 766 (51.74) 3241 (55.24) 1 [Reference] 1 [Reference] 1 [Reference] All variables in the table were included. Second 861 430 (34.64) 2014 (34.33) 1.10 (1.04-1.17) 1.06 (1.00-1.12) 0.91 (0.83-0.99) Indicates within-sibling analysis in which the Third 269 191 (10.82) 512 (8.73) 1.15 (1.04-1.26) 1.08 (0.98-1.19) 0.81 (0.68-0.97) mother’s identification number was the stratification Fourth or 69 726 (2.80) 100 (1.70) 1.15 (0.94-1.41) 1.05 (0.86-1.29) 0.67 (0.49-0.91) variable; all variables in the table were included. subsequent IM, birth to 10 y Maternal age at birth was highly correlated with paternal age at birth (r = 0.73). To account for No 2 483 029 (99.84) 5851 (99.73) 1 [Reference] 1 [Reference] 1 [Reference] potential collinearity, parental ages at birth were Yes 4084 (0.16) 16 (0.27) 1.85 (1.13-3.02) 1.98 (1.21-3.23) 2.87 (1.44-5.74) included in 2 separate stratified Cox proportional IM, 11-19 y hazards regression models, where model 1 included No 2 469 259 (99.28) 5759 (98.16) 1 [Reference] 1 [Reference] 1 [Reference] maternal age at birth and the rest of the variables Yes 17 854 (0.72) 108 (1.84) 3.27 (2.70-3.95) 3.00 (2.48-3.63) 3.19 (2.29-4.46) listed (excluding paternal age) and model 2 included paternal age at birth and the rest of the variables IM, 20-24 y listed (excluding maternal age). The HRs for maternal No 2 482 238 (99.80) 5850 (99.71) 1 [Reference] 1 [Reference] 1 [Reference] age and paternal age at birth were 1.06 (95% CI, Yes 4875 (0.20) 17 (0.29) 1.69 (1.05-2.72) 1.89 (1.18-3.05) 1.51 (0.82-2.76) 1.04-1.08) and 1.03 (95% CI, 1.01-1.05), respectively. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 5/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis analysis 2 found no substantial differences in HR, excluding or including individuals born after 1987. Sensitivity analysis 3 also found no substantial differences in HR between within-sibling analysis and within-full-sibling analysis. Sensitivity analysis 4 found that IM in childhood (HR, 3.24; 95% CI, 1.87- 5.60) and adolescence (HR, 2.77; 95% CI, 2.08-3.68), but not in early adulthood, was associated with an increased risk of an MS diagnosis when the first demyelinating diseases of the CNS diagnosed from 20 years of age were defined as the possible onset of MS (and after exclusion of anyone with a demyelinating disease diagnosis before 20 years of age). Sensitivity analysis 5 found no substantial differences in HR when excluding or including families with only 1 parent alive in 1990. Discussion Hospital-diagnosed IM in childhood and most notably in adolescence was associated with increased risk of a subsequent MS diagnosis, independent of measured and unmeasured shared familial factors addressed by stratified Cox proportional hazards regression. There was less evidence of an independent association of MS with IM in early adulthood. This age-defined pattern of risk may reflect variation in susceptibility to environmental exposures due to developmental changes of the immune system and CNS. Because MS may have an asymptomatic or prodromal period of approximately 5 to 10 years before clinical onset, a diagnosis of IM in adolescence could potentially signal that IM is a consequence of prodromal MS. Allowing a delay of at least 5 years between IM and MS (with evidence of even longer intervals between IM and MS in further sensitivity analyses) helps to alleviate such concerns, because the magnitude of the estimates for the association of IM in adolescence with subsequent MS were not attenuated. Also, IM in early adulthood was not so notably associated with MS. Table 2. Adjusted HRs for Risk of MS Diagnosis From Sensitivity Analyses Stratified Cox proportional hazards regression, HR (95% CI) Age at IM Sensitivity Sensitivity Sensitivity Sensitivity Sensitivity b c d e f diagnosis analysis 1 analysis 2 analysis 3 analysis 4 analysis 5 Birth to 10 y No 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] Yes 3.72 (1.44-9.56) 2.60 (1.23-5.50) 2.68 (1.32-5.45) 3.24 (1.87-5.60) 2.90 (1.45-5.80) 11-19 y No 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] Yes 3.96 (2.65-5.90) 3.45 (2.34-5.08) 3.45 (2.43-4.89) 2.77 (2.08-3.68) 3.26 (2.32-4.57) 20-24 y No 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] Yes 1.89 (0.99-3.62) 1.51 (0.80-2.83) 1.76 (0.97-3.22) 1.48 (0.91-2.38) 1.53 (0.85-2.72) Abbreviations: HR, hazard ratio; IM, infectious mononucleosis; MS, multiple sclerosis. All variables listed in the table and parental ages at birth, a parental MS diagnosis, birth order, and sex were included in the sensitivity analyses. Uses a first MS diagnosis from 25 years of age to further exclude the possibility of reverse causation. Excludes individuals who were born after 1987 to examine the influence of the incomplete national coverage of the National Patient Register until 1987 on the association between IM and risk of an MS diagnosis. Only includes families with the same mother and father for all of the children (within full sibling analysis). Uses the first demyelinating diseases of the central nervous system diagnosed from 20 years of age as possible onset of MS. Includes families with either parent still alive in 1990. Because maternal age at birth was highly correlated with paternal age at birth (r = 0.73), maternal age at birth data missing for families with only the father still alive in 1990 (1.46% of the population included) was replaced by the paternal age at birth. Similarly, paternal age at birth data missing for families with only the mother still alive in 1990 (5.14% of the population included) was replaced by the maternal age at birth. Parental MS diagnosis was only for either the mother’s or the father’s diagnosis for families with only the mother or the father still alive in 1990 (6.60% of population included). JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 6/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis Infection with EBV in early childhood is common and typically asymptomatic, which reduces the possibility of experiencing subsequent IM owing to EBV, just as the risk of more severe manifestations of other infections increases with age (eg, for poliomyelitis). This is consistent with the association of having older siblings and reduced MS risk, because having older siblings may increase infection risk at an earlier age, thereby reducing risk of other immune-mediated 25,26 diseases. We speculate that the intense immune activation associated with IM (rather than EBV infection per se) results in priming with possible recruitment of mimicry autoimmunity, thus increasing MS risk. We used hospital-diagnosed IM in this study, which is likely to identify more severe manifestations. The waning of IM-associated risk for MS after adolescence is consistent with other research. Our results suggest that childhood and in particular adolescence seem to be periods when acute IM is relevant to MS risk. Such an age-specific pattern is consistent with prior research on other environmental risk factors, in which some exposures seem to have greater consequences in adolescence than in earlier childhood, including hospital-diagnosed infections other than EBV or IM. Mechanisms that potentially explain why acute IM (during age-defined periods of heightened susceptibility) is associated with increased risk of an MS diagnosis include the cross-activation of autoreactive T cells to the CNS due to the homologous sequences or structures shared between the EBV pathogens and myelin antigens. Three EBV proteins—the tegument protein BRRF2, EBNA-1, and the small capsid protein (BFRF3)—share epitopes with myelin basic proteins (eg, DLST and 28,29 septin-9). Antibodies to BRRF2, EBNA-1, and BFRF3 cross-react with myelin antigens, which can 28,29 lead to recurrent autoimmune CNS damage. Antibodies to EBNA-1 can also cross-react with the chloride-channel protein anoctamin 2 and are associated with increased MS risk. Indeed, a significantly increased presence of anti–viral capsid antigen IgG and anti-EBNA-1 IgG antibodies and + + significantly higher CD4 and CD8 T-cell responses to EBNA-1 have been reported in patients with MS compared with control individuals. The EBV-infected autoreactive B cells hypothesis may be another possible mechanism: EBV infects resting B cells and converts them into immortalized lymphoblastoid cell lines, resulting in the production of ENBA-1 through ENBA-6 and latent membrane proteins (LMP-1, LMP-2A, and LMP-2B). B cells can further transform into memory B cells because LMP-1 mimics CD40 signaling. The memory B cells can infiltrate the blood-brain barrier, then become activated and develop into antibody-secreting plasma cells triggered by 33 34 interleukin 21, causing inflammation in the CNS and in turn increasing MS risk. B cells and 34,35 plasmablasts/plasma cells are present in various parts of the CNS in patients with MS. Our findings lend further weight to the notion that EBV plays a role in pathogenesis, where the pattern of exposure and acute manifestation of the infection are relevant, rather than being a bystander phenomenon due to MS disease activity or susceptibility to MS resulting in a greater likelihood of IM. Older maternal, rather than paternal, age at birth was another risk factor for MS diagnosis, which is inconsistent with prior research, possibly because maternal and paternal age are highly correlated (r = 0.73). When only paternal age or maternal age at birth were included in the adjusted stratified Cox proportional hazards regression, both were associated with an increased risk of an MS diagnosis. A diagnosis of MS in a parent conveyed a high magnitude of increased risk for MS, indicating the importance of genetic predisposition. As expected, this association was attenuated by stratified Cox proportional hazards regression that adjusted for shared familial factors. Strengths and Limitations The strengths of this study include the use of a large population-based birth cohort with sufficient statistical power and prospective recording of IM before MS diagnosis. We also examined IM at 3 theoretically relevant developmental stages (childhood, adolescence, and early adulthood) to assess potential periods of susceptibility to EBV exposure. Importantly, stratified Cox proportional hazards regression was used to reduce confounding by shared familial factors invariant among each sibling cluster. JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 7/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis This study also has some limitations. Infectious mononucleosis diagnosed and treated in primary care could not be included, and hospital-based outpatient diagnoses were not available until 2001, likely resulting in selection of more severe acute manifestations of the infection. Some IM and MS diagnoses may be missing owing to the incomplete national coverage for inpatient registrations before 1987 and the unavailability of outpatient information before 2001, though our sensitivity analysis found no substantial differences in HRs between analyses including and excluding individuals who were born after 1987. We could not assess MS onset earlier than the first MS diagnosis because the first symptomatic onset of MS could not be identified in the current study. However, excluding those with any demyelinating diseases before 20 years of age and extending the minimal interval between putative exposure and diagnosis did not suggest reverse causation. We could not adjust for vitamin D level, smoking, and body mass index. However, there are strong shared familial influences for body mass 37-40 index, smoking, and vitamin D levels in childhood and adolescence, so the stratified Cox proportional hazards regression should have addressed this issue, at least in part. For complete family linkage and information from both parents, parents had to survive to at least 1990, thus possibly introducing selection bias. A sensitivity analysis based on only 1 surviving parent did not produce notably different results. Conclusions The findings of this population–based cohort study suggest that IM in childhood and particularly adolescence is associated with a subsequent MS diagnosis, independent of shared familial factors. Therefore, greater susceptibility to infection is less likely to be the explanation. ARTICLE INFORMATION Accepted for Publication: July 12, 2021. Published: October 11, 2021. doi:10.1001/jamanetworkopen.2021.24932 Open Access: This is an open access article distributed under the terms of the CC-BY License.©2021XuYetal. JAMA Network Open. Corresponding Author: Scott Montgomery, PhD, Clinical Epidemiology and Biostatistics, School of Medical Sciences, Campus USÖ, Örebro University, SE-703 62 Örebro, Sweden (scott.montgomery@oru.se). Author Affiliations: Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden (Xu, Hiyoshi, Fall, Montgomery); Department of Public Health Sciences, Stockholm University, Stockholm, Sweden (Hiyoshi); Department of Epidemiology and Public Health, University College London, London, United Kingdom (Hiyoshi, Montgomery); Clinical Epidemiology Division, Karolinska Institute, Stockholm, Sweden (Smith, Montgomery); Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden (Piehl, Olsson); Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden (Fall). Author Contributions: Dr Xu had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Olsson, Montgomery. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Xu, Olsson. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Xu, Smith. Obtained funding: Hiyoshi, Piehl, Olsson, Montgomery. Administrative, technical, or material support: Piehl, Olsson, Montgomery. Supervision: Olsson, Montgomery. Conflict of Interest Disclosures: Ms Smith reported receiving grants from AstraZeneca and the Multiple Sclerosis Society of Canada outside the submitted work. Dr Piehl reported receiving grants from the Swedish Medical JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 8/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis Research Council and the County of Stockholm during the conduct of the study and receiving unrestricted academic research grants from Sanofi Genzyme, Merck KGaA, and UCB outside the submitted work. Dr Olsson reported receiving unrestricted MS research grants and/or honoraria for advisory boards/lectures from Biogen Inc, Novartis International AG, Sanofi Genzyme, AstraZeneca PLC, and Merck & Co, Inc. Dr Montgomery reported receiving grants from the UK Social and Economic Research Council and Nyckelfonden (medical charity in Sweden) during the conduct of the study and receiving grants from Roche, Novartis International AG, and AstraZeneca; receiving honorarium for a lecture from Teva Pharmaceutical Industries Ltd; and serving on the advisory board for a study for IQVIA (with payment to Örebro University Hospital) outside the submitted work. No other disclosures were reported. Funding/Support: This study was supported by a grant from Nyckelfonden, grant ES/R008930/1 from the UK Economic and Social Research Council (International Centre for Life Course Studies), and grant 2019-01236 from the Swedish Research Council for Health, Working Life and Welfare (Forte). Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. REFERENCES 1. Hedström AK, Huang J, Michel A, et al. High levels of Epstein–Barr virus nuclear antigen-1–specific antibodies and infectious mononucleosis act both independently and synergistically to increase multiple sclerosis risk. Front Neurol. 2020;10:1368. doi:10.3389/fneur.2019.01368 2. Belbasis L, Bellou V, Evangelou E, Ioannidis JP, Tzoulaki I. Environmental risk factors and multiple sclerosis: an umbrella review of systematic reviews and meta-analyses. Lancet Neurol. 2015;14(3):263-273. doi:10.1016/S1474- 4422(14)70267-4 3. Burnard S, Lechner-Scott J, Scott RJ. EBV and MS: major cause, minor contribution or red-herring? Mult Scler Relat Disord. 2017;16:24-30. doi:10.1016/j.msard.2017.06.002 4. Rubicz R, Yolken R, Drigalenko E, et al. A genome-wide integrative genomic study localizes genetic factors influencing antibodies against Epstein-Barr virus nuclear antigen 1 (EBNA-1). PLoS Genet. 2013;9(1):e1003147. doi: 10.1371/journal.pgen.1003147 5. Zhou Y, Zhu G, Charlesworth JC, et al; ANZgene consortium. Genetic loci for Epstein-Barr virus nuclear antigen-1 are associated with risk of multiple sclerosis. Mult Scler. 2016;22(13):1655-1664. doi:10.1177/1352458515626598 6. Kreft KL, Van Nierop GP, Scherbeijn SMJ, Janssen M, Verjans GMGM, Hintzen RQ. Elevated EBNA-1 IgG in MS is associated with genetic MS risk variants. Neurol Neuroimmunol Neuroinflamm. 2017;4(6):e406. doi:10.1212/NXI. 7. Dobson R, Jitlal M, Marshall CR, et al. Ethnic and socioeconomic associations with multiple sclerosis risk. Ann Neurol. 2020;87(4):599-608. doi:10.1002/ana.25688 8. Langer-Gould A, Wu J, Lucas R, et al. Epstein-Barr virus, cytomegalovirus, and multiple sclerosis susceptibility: a multiethnic study. Neurology. 2017;89(13):1330-1337. doi:10.1212/WNL.0000000000004412 9. Ascherio A, Munger KL. Environmental risk factors for multiple sclerosis, part I: the role of infection. Ann Neurol. 2007;61(4):288-299. doi:10.1002/ana.21117 10. Handel AE, Williamson AJ, Disanto G, Handunnetthi L, Giovannoni G, Ramagopalan SV. An updated meta- analysis of risk of multiple sclerosis following infectious mononucleosis. PLoS One. 2010;5(9):e12496. doi:10.1371/ journal.pone.0012496 11. Smith KA, Hiyoshi A, Burkill S, et al. Hospital diagnosed pneumonia before age 20 years and multiple sclerosis risk. BMJ Neurol Open. 2020;2(1):e000044. doi:10.1136/bmjno-2020-000044 12. Xu Y, Smith KA, Hiyoshi A, Piehl F, Olsson T, Montgomery S. Hospital-diagnosed infections before age 20 and risk of a subsequent multiple sclerosis diagnosis. Brain. Published online March 9, 2021. doi:10.1093/ brain/awab100 13. Xu Y, Hiyoshi A, Brand JS, et al. Higher body mass index at ages 16 to 20 years is associated with increased risk of a multiple sclerosis diagnosis in subsequent adulthood among men. Mult Scler. 2021;27(1):147-150. doi:10.1177/ 14. Montgomery S, Hiyoshi A, Burkill S, Alfredsson L, Bahmanyar S, Olsson T. Concussion in adolescence and risk of multiple sclerosis. Ann Neurol. 2017;82(4):554-561. doi:10.1002/ana.25036 15. Munger KL, Levin LI, Hollis BW, Howard NS, Ascherio A. Serum 25-hydroxyvitamin D levels and risk of multiple sclerosis. JAMA. 2006;296(23):2832-2838. doi:10.1001/jama.296.23.2832 16. Nielsen TR, Rostgaard K, Nielsen NM, et al. Multiple sclerosis after infectious mononucleosis. Arch Neurol. 2007;64(1):72-75. doi:10.1001/archneur.64.1.72 JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 9/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis 17. Ludvigsson JF, Almqvist C, Bonamy AK, et al. Registers of the Swedish total population and their use in medical research. Eur J Epidemiol. 2016;31(2):125-136. doi:10.1007/s10654-016-0117-y 18. Ludvigsson JF, Andersson E, Ekbom A, et al. External review and validation of the Swedish national inpatient register. BMC Public Health. 2011;11(1):450. doi:10.1186/1471-2458-11-450 19. Miller DH, Weinshenker BG, Filippi M, et al. Differential diagnosis of suspected multiple sclerosis: a consensus approach. Mult Scler. 2008;14(9):1157-1174. doi:10.1177/1352458508096878 20. Murley C, Friberg E, Hillert J, Alexanderson K, Yang F. Validation of multiple sclerosis diagnoses in the Swedish National Patient Register. Eur J Epidemiol. 2019;34(12):1161-1169. doi:10.1007/s10654-019-00558-7 21. Marrie RA, Fisk JD, Stadnyk KJ, et al; CIHR Team in the Epidemiology and Impact of Comorbidity on Multiple Sclerosis. The incidence and prevalence of multiple sclerosis in Nova Scotia, Canada. Can J Neurol Sci. 2013;40(6): 824-831. doi:10.1017/S0317167100015961 22. Marrie RA, Yu N, Blanchard J, Leung S, Elliott L. The rising prevalence and changing age distribution of multiple sclerosis in Manitoba. Neurology. 2010;74(6):465-471. doi:10.1212/WNL.0b013e3181cf6ec0 23. Tremlett H, Marrie RA. The multiple sclerosis prodrome: emerging evidence, challenges, and opportunities. Mult Scler. 2021;27(1):6-12. doi:10.1177/1352458520914844 24. Nathanson N, Kew OM. From emergence to eradication: the epidemiology of poliomyelitis deconstructed. Am J Epidemiol. 2010;172(11):1213-1229. doi:10.1093/aje/kwq320 25. Conradi S, Malzahn U, Schröter F, et al. Environmental factors in early childhood are associated with multiple sclerosis: a case-control study. BMC Neurol. 2011;11(1):123. doi:10.1186/1471-2377-11-123 26. Ponsonby AL, van der Mei I, Dwyer T, et al. Exposure to infant siblings during early life and risk of multiple sclerosis. JAMA. 2005;293(4):463-469. doi:10.1001/jama.293.4.463 27. Ramagopalan SV, Dobson R, Meier UC, Giovannoni G. Multiple sclerosis: risk factors, prodromes, and potential causal pathways. Lancet Neurol. 2010;9(7):727-739. doi:10.1016/S1474-4422(10)70094-6 28. Cepok S, Zhou D, Srivastava R, et al. Identification of Epstein-Barr virus proteins as putative targets of the immune response in multiple sclerosis. J Clin Invest. 2005;115(5):1352-1360. doi:10.1172/JCI200523661 29. Lindsey JW. Antibodies to the Epstein-Barr virus proteins BFRF3 and BRRF2 cross-react with human proteins. J Neuroimmunol. 2017;310:131-134. doi:10.1016/j.jneuroim.2017.07.013 30. Tengvall K, Huang J, Hellström C, et al. Molecular mimicry between Anoctamin 2 and Epstein-Barr virus nuclear antigen 1 associates with multiple sclerosis risk. Proc Natl Acad SciUSA. 2019;116(34):16955-16960. doi: 10.1073/pnas.1902623116 31. Santiago O, Gutierrez J, Sorlozano A, de Dios Luna J, Villegas E, Fernandez O. Relation between Epstein-Barr virus and multiple sclerosis: analytic study of scientific production. Eur J Clin Microbiol Infect Dis. 2010;29(7): 857-866. doi:10.1007/s10096-010-0940-0 32. Baker D, Pryce G, Amor S, Giovannoni G, Schmierer K. Learning from other autoimmunities to understand targeting of B cells to control multiple sclerosis. Brain. 2018;141(10):2834-2847. doi:10.1093/brain/awy239 33. Kuchen S, Robbins R, Sims GP, et al. Essential role of IL-21 in B cell activation, expansion, and plasma cell generation during CD4 T cell–B cell collaboration. J Immunol. 2007;179(9):5886-5896. doi:10.4049/jimmunol. 179.9.5886 34. Michel L, Touil H, Pikor NB, Gommerman JL, Prat A, Bar-Or A. B cells in the multiple sclerosis central nervous system: trafficking and contribution to CNS-compartmentalized inflammation. Front Immunol. 2015;6:636. doi:10. 3389/fimmu.2015.00636 35. Serafini B, Rosicarelli B, Franciotta D, et al. Dysregulated Epstein-Barr virus infection in the multiple sclerosis brain. J Exp Med. 2007;204(12):2899-2912. doi:10.1084/jem.20071030 36. Montgomery SM, Lambe M, Olsson T, Ekbom A. Parental age, family size, and risk of multiple sclerosis. Epidemiology. 2004;15(6):717-723. doi:10.1097/01.ede.0000142138.46167.69 37. Elks CE, den Hoed M, Zhao JH, et al. Variability in the heritability of body mass index: a systematic review and meta-regression. Front Endocrinol (Lausanne). 2012;3:29. doi:10.3389/fendo.2012.00029 38. Leonardi-Bee J, Jere ML, Britton J. Exposure to parental and sibling smoking and the risk of smoking uptake in childhood and adolescence: a systematic review and meta-analysis. Thorax. 2011;66(10):847-855. doi:10.1136/ thx.2010.153379 39. Munafò M, Clark T, Johnstone E, Murphy M, Walton R. The genetic basis for smoking behavior: a systematic review and meta-analysis. Nicotine Tob Res. 2004;6(4):583-597. doi:10.1080/14622200410001734030 40. Bahrami A, Sadeghnia HR, Tabatabaeizadeh SA, et al. Genetic and epigenetic factors influencing vitamin D status. J Cell Physiol. 2018;233(5):4033-4043. doi:10.1002/jcp.26216 JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 10/11 JAMA Network Open | Neurology Association of Childhood Mononucleosis With Risk for Subsequent MS Diagnosis SUPPLEMENT. eMethods. Study Population eTable. Adjusted Hazard Ratios for Risk of a Multiple Sclerosis Diagnosis With Infectious Mononucleosis in Smaller Age Categories and Follow-up for First Multiple Sclerosis Diagnosis at Different Ages eFigure. Scaled Schoenfeld Residuals Plotted Against Time for Paternal Age at Birth, a Parental MS Diagnosis, and Birth Order eReferences JAMA Network Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 (Reprinted) October 11, 2021 11/11 Supplementary Online Content Xu Y, Hiyoshi A, Smith KA, et al. Association of infectious mononucleosis in childhood and adolescence with risk for a subsequent multiple sclerosis diagnosis among siblings. JAMA Netw Open. 2021;4(10):e2124932. doi:10.1001/jamanetworkopen.2021.24932 eMethods. Study Population eTable. Adjusted Hazard Ratios for Risk of a Multiple Sclerosis Diagnosis With Infectious Mononucleosis in Smaller Age Categories and Follow-up for First Multiple Sclerosis Diagnosis at Different Ages eFigure. Scaled Schoenfeld Residuals Plotted Against Time for Paternal Age at Birth, a Parental MS Diagnosis, and Birth Order eReferences This supplementary material has been provided by the authors to give readers additional information about their work. © 2021 Xu Y et al. JAMA Network Open. eMethods. Study Population Two Swedish general population-based registers with high validity were used in the current study: the Total Population Register and the National Patient Register. The unique individual Swedish personal identification number was used for data linkage. The Total Population Register has been updated annually since 1968 and collects life events for the entire population of Sweden, including dates of birth, death, and migration. The National Patient Register for inpatient care was established in 1964 and attained complete national coverage in 1987, with hospital-based outpatient diagnoses collected since 2001. The National Patient Register contains data on all inpatient and outpatient diagnoses, admission, discharge, and procedures in hospital. © 2021 Xu Y et al. JAMA Network Open. eTable. Adjusted Hazard Ratios for Risk of a Multiple Sclerosis Diagnosis With Infectious Mononucleosis in Smaller Age Categories and Follow-up for First Multiple Sclerosis Diagnosis at Different Ages Stratified Cox regression Analysis-1 Analysis-2 Analysis-3 MS from age 20 years MS ages 20 to 30 years MS after age 30 years IM, birth to age 5 years No 1 (reference) 1 (reference) 1 (reference) Yes 1.39 (0.49-3.99) 1.24 (0.36-4.29) 2.13 (0.26-17.37) IM, age 6-10 years No 1 (reference) 1 (reference) 1 (reference) Yes 5.72 (1.93-16.96) 5.51 (1.16-26.17) 6.10 (1.38-26.93) IM, age 11-15 years No 1 (reference) 1 (reference) 1 (reference) Yes 3.45 (1.93-6.17) 2.17 (1.04-4.52) 7.50 (3.02-18.63) IM, age 16-19 years No 1 (reference) 1 (reference) 1 (reference) Yes 3.10 (2.09-4.60) 2.98 (1.77-5.00) 3.64 (1.95-6.79) IM, age 20-24 years No 1 (reference) 1 (reference) 1 (reference) Yes 1.50 (0.82-2.76) 0.97 (0.35-2.69) 2.60 (1.07-6.36) © 2021 Xu Y et al. JAMA Network Open. Abbreviations: IM = infectious mononucleosis. MS = multiple sclerosis Hazard ratios and 95% confidence interval from stratified Cox regression (within-sibling analysis with as the stratification variable), adjusted for sex, parental age at birth, parental multiple sclerosis diagnosis, and birth order, were reported here. st For analysis-1, follow-up was from age 20 years until the first diagnosis of MS, death, first emigration, or study end (31 December 2018), whichever occurred first. For analysis-2, follow-up was from age 20 until the first diagnosis of MS, death, first emigration, attaining the age st of 30 years, or study end (31 December 2018), whichever occurred first. For analysis-3, follow-up was from after age 30 years until the first st diagnosis of MS, death, first emigration, or study end (31 December 2018), whichever occurred first. © 2021 Xu Y et al. JAMA Network Open. eFigure. Scaled Schoenfeld Residuals Plotted Against Time for Paternal Age at Birth, a Parental MS Diagnosis, and Birth Order For birth order, the first-born was the reference group. MS = multiple sclerosis; SC = Schoenfeld residuals. © 2021 Xu Y et al. JAMA Network Open. eReferences 1. Ludvigsson JF, Almqvist C, Bonamy AK, et al. Registers of the Swedish total population and their use in medical research. Eur J Epidemiol. 2016;31(2):125-136. doi:10.1007/s10654-016-0117-y 2. Ludvigsson JF, Andersson E, Ekbom A, et al. External review and validation of the Swedish national inpatient register. BMC Public Health. 2011;11(1):450. doi:10.1186/1471-2458-11-450 © 2021 Xu Y et al. JAMA Network Open.

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Published: Oct 11, 2021

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