Measles, Mumps, Rubella Vaccination and Autism: A Nationwide Cohort StudyFREE
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Abstract
Background:
The hypothesized link between the measles, mumps, rubella (MMR) vaccine and autism continues to cause concern and challenge vaccine uptake.
Objective:
To evaluate whether the MMR vaccine increases the risk for autism in children, subgroups of children, or time periods after vaccination.
Design:
Nationwide cohort study.
Setting:
Denmark.
Participants:
657 461 children born in Denmark from 1999 through 31 December 2010, with follow-up from 1 year of age and through 31 August 2013.
Measurements:
Danish population registries were used to link information on MMR vaccination, autism diagnoses, other childhood vaccines, sibling history of autism, and autism risk factors to children in the cohort. Survival analysis of the time to autism diagnosis with Cox proportional hazards regression was used to estimate hazard ratios of autism according to MMR vaccination status, with adjustment for age, birth year, sex, other childhood vaccines, sibling history of autism, and autism risk factors (based on a disease risk score).
Results:
During 5 025 754 person-years of follow-up, 6517 children were diagnosed with autism (incidence rate, 129.7 per 100 000 person-years). Comparing MMR-vaccinated with MMR-unvaccinated children yielded a fully adjusted autism hazard ratio of 0.93 (95% CI, 0.85 to 1.02). Similarly, no increased risk for autism after MMR vaccination was consistently observed in subgroups of children defined according to sibling history of autism, autism risk factors (based on a disease risk score) or other childhood vaccinations, or during specified time periods after vaccination.
Limitation:
No individual medical charts were reviewed.
Conclusion:
The study strongly supports that MMR vaccination does not increase the risk for autism, does not trigger autism in susceptible children, and is not associated with clustering of autism cases after vaccination. It adds to previous studies through significant additional statistical power and by addressing hypotheses of susceptible subgroups and clustering of cases.
Primary Funding Source:
Novo Nordisk Foundation and Danish Ministry of Health.
The hypothesized link between the measles, mumps, rubella (MMR) vaccine and autism continues to cause concern and challenge vaccine acceptance almost 2 decades after the controversial and later retracted Lancet paper from 1998 (1), even though observational studies have not been able to identify an increased risk for autism after MMR vaccination. In a 2014 meta-analysis, 10 observational studies on childhood vaccines were identified: 5 cohort studies and 5 case–control studies (2). Of these, 2 cohort studies and 4 case–control studies specifically addressed MMR and autism, all reporting no association. This is consistent with more recent studies of note (3, 4).
We previously addressed this issue in a nationwide cohort study of 537 303 Danish children with 738 cases of autism spectrum disorders (5). In our cohort, MMR vaccination was not associated with autistic disorder (rate ratio, 0.92 [95% CI, 0.68 to 1.24]) or other autism spectrum disorders (rate ratio, 0.83 [CI, 0.65 to 1.07]).
In this study, we aimed to evaluate the association again in a more recent and nonoverlapping cohort of Danish children that has greater statistical power owing to more children, more cases, and longer follow-up. A criticism of our and other previous observational studies has been that these did not address the concern that MMR vaccination could trigger autism in specific groups of presumably susceptible children, in contrast to all children (6); the current study addresses this concern in detail. We evaluate the risk for autism after MMR vaccination in subgroups of children defined according to environmental and familial autism risk factors. Another criticism has been that MMR is associated with a regressive form of autism, leading to a clustering of cases with onset shortly after MMR vaccination (7). We evaluate the risk for autism after MMR vaccination in specific periods in detail.
Methods
Ethical approval is not needed for register-based research in Denmark. The Danish Data Protection Agency approved the study.
Cohort
We conducted a nationwide cohort study of all children born in Denmark of Danish-born mothers from 1 January 1999 through 31 December 2010. We sourced the study cohort from the Danish Civil Registration System, which assigns a unique personal identification number to all people living in Denmark and keeps track of basic demographic information for each individual (8). This unique identifier is used in all other national registries and allows for individual-level linkage of health-related information, including vaccinations and autism diagnoses.
MMR and Other Childhood Vaccinations
The Danish childhood vaccination program is voluntary and free of charge. The mainstays of the early part of the Danish program are MMR and a diphtheria, tetanus, acellular pertussis, inactivated polio, and Haemophilus influenzae type b (DTaP-IPV/Hib) combination. A first dose of MMR vaccine is offered at 15 months (MMR1), with a second dose (MMR2) at 12 years of age or, since 2008, at 4 years of age. The DTaP-IPV/Hib vaccine is offered in 3 doses at 3, 5, and 12 months. Boosters are offered later in childhood. General practitioners administer all childhood vaccinations and are reimbursed when reporting these to the National Board of Health; these reports are included in the Danish National Health Service Register (9).
We obtained individual-level information on MMR1 and MMR2 vaccinations and other childhood vaccinations administered in the first year of life. There were no thimerosal-containing vaccines in the Danish program during the study period. The specific MMR vaccine used in the study period contained the following vaccine strains: Schwarz (measles, 2000 to 2007) or Ender's Edmonton (measles, 2008–2013), Jeryl Lynn (mumps), and Wistar RA 27/3 (rubella).
Autism
Information on autism spectrum disorder diagnoses in the study period was obtained from the Danish Psychiatric Central Register (10). Child psychiatrists diagnose and assign diagnostic codes for this register, which contains information from psychiatric hospitals and psychiatric wards (inpatients and outpatients in the study period). The coding classification used in the study period was the International Classification of Diseases, 10th Revision; we used the codes F84.0 (autistic disorder), F84.1 (atypical autism), F84.5 (Asperger syndrome), F84.8 (other pervasive developmental disorder), and F84.9 (unspecified pervasive developmental disorder). We defined our main study outcome of autism as a diagnosis of any of these autism spectrum disorders.
From the Danish National Patient Register comprising diagnoses from all somatic departments, we obtained information on several syndromes and conditions with an inherent increased risk for autism (fragile X syndrome, tuberous sclerosis, Angelman syndrome, Down syndrome, DiGeorge syndrome, neurofibromatosis, Prader–Willi syndrome, and congenital rubella syndrome) (11). Children with any of these conditions were excluded from the study if the condition was diagnosed before their first birthday or censored at date of the diagnosis if it was made when the child was older than 1 year (14).
Autism Risk Factors
We included many autism risk factors for stratification and confounder adjustment, on the basis of a literature review on environmental autism risk factors and availability of data in our registers (12); these were maternal age, paternal age, smoking during pregnancy, method of delivery, preterm birth, 5-minute Apgar score, low birthweight, and head circumference. For variables with missing values, we included a missing value category in the analyses. Table 1 of the Supplement provides a complete list of variables with categorizations). These variables were obtained from the Danish Medical Birth Registry, which includes information on the parents and the newborn, pregnancy, date of birth, multiple births, gestational age, and vital status and other physical characteristics of the newborn (13).
From the Danish Civil Registration System, we obtained parental links to identify siblings (defined as common father and mother) for each cohort child. Cases of autism among siblings were identified similarly to the main study outcome.
Statistical Analysis
The main goal of our modeling strategy was to evaluate whether the MMR vaccine increases the risk for autism in children, subgroups of children, and time periods after vaccination. We defined subgroups according to 1) sibling history of autism (“genetic susceptibility”), sex, birth cohort, and prior vaccinations in the first year of life and 2) a summary index estimated from a disease risk model combining multiple environmental risk factors. The motivation for a summary index was that the combination of several factors each associated with only a moderate risk increase in autism had the potential of identifying children at higher risk through multiple risk factors, in contrast to many stratified analyses of single moderate risk factors.
We analyzed the study cohort by using survival analysis (14). Children in the cohort contributed person-time to follow-up from 1 year of age and until a first diagnosis of autism, death, emigration, unexplained disappearance from the source registers, diagnoses of autism-associated conditions or syndromes, or end of the study on 31 August 2013.
The MMR vaccination status was considered a time-varying variable; children could contribute time as both unvaccinated and vaccinated in our study. Using the cases of autism among siblings, we constructed a time-varying variable summarizing each child's sibling history of autism with the states “no siblings,” “siblings without autism,” or “siblings with at least one case of autism”; a missing value category covered the children who had unknown fathers. We used sibling history at study entry unless otherwise specified.
In a preliminary analysis based on maternal age, paternal age, smoking during pregnancy, method of delivery, preterm birth, 5-minute Apgar score, low birthweight, and head circumference, we estimated a disease risk score (15) (termed “autism risk score” throughout) for each child in the cohort. The autism risk score was derived in the complete study cohort by fitting a proportional hazards model of autism risk with attained age as underlying time-scale comprising the preselected variables as covariates. For each child, a score (in the form of a hazard ratio [HR] relative to a child with reference values for all variables included) was calculated as the exponential of the sum of the estimated regression coefficients corresponding to the characteristics of the child. The score was categorized according to deciles which were combined into 4 risk groups: very low (first to third decile), low (fourth to sixth decile), moderate (seventh to ninth decile), or high (10th decile).
Survival times were then analyzed by using Cox regression with attained age as underlying time scale, producing HRs according to vaccination status. For fully adjusted models, the baseline hazard function was stratified on birth year, sex, other childhood vaccines received, sibling history of autism and autism risk score (in deciles). We evaluated the proportional hazards assumption of the main analysis by a joint test of homogeneity allowing the effect of vaccination to vary between the age intervals 1 to 3 years, 3 to 5 years, 5 to 7 years, 7 to 10 years, and more than 10 years (16).
We estimated autism HRs (aHRs) according to MMR vaccination status (yes or no), overall in the cohort and in several subanalyses: 4 analyses, each restricting risk time to young children by censoring observed survival times at 3, 5, 7, or 10 years of age; in subgroups characterized by sex, birth cohort, other childhood vaccines received, autism risk score, or autism history in siblings (joint tests for homogeneity of aHRs between levels of each factor were carried out [16]); and in specific periods after vaccination (comparing the hazard rates of autism in the first, second, third, and fourth year after vaccination and more than 4 years after vaccination, respectively, with the rate among unvaccinated children. A test for homogeneity of aHRs between intervals was conducted using a type 3 test (16).
We conducted several sensitivity analyses. To increase the validity of our autism case definition further, we conducted a main analysis with a case definition requiring at least 2 autism diagnosis registrations; an event was defined at date of second autism diagnosis. We evaluated specific autism phenotypes by conducting main analyses of autistic disorder and other autism spectrum disorder separately (with right censoring of other autism spectrum disorder when analyzing autistic disorder and vice versa). We conducted a dose-dependent fully adjusted analysis taking the second MMR dose into account by estimating the increase in HR per vaccination. Instead of adjusting for birth year, sex, other childhood vaccines received, sibling history of autism, and autism risk score by stratification of the baseline hazard, we included these as covariates. Finally, we replaced the autism risk score of the previous model with the 8 variables on which it was based.
Crude associations between variables included in the analyses and autism were estimated in proportional hazards models with attained age as underlying time-scale and autism as outcome, including only the specific variable of interest as a covariate.
Data management and statistical analyses were conducted by using SAS, version 9.4; the figures were created by using R, version 3.5.1. All Cox regressions were fitted by using the SAS PHREG procedure with the Breslow option for handling ties. Cumulative risks were calculated from the Kaplan-Meier estimates using the survfit function in R with the log-log option for confidence limits.
Role of the Funding Source
The study was supported by a grant from the Novo Nordisk Foundation and the Danish Ministry of Health. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Dr. Hviid had full access to all of the data in the study and had overall responsibility for the decision to submit for publication.
Results
We identified 663 236 children born to Danish-born mothers from 1 January 1999 through 31 December 2010 (Figure 1). We excluded 5775 children; 1498 had no registration in the Danish Medical Birth Registry, and 4277 were unavailable for follow-up at study entry (1 year of age) because of death (n = 2673), emigration (n = 770), unexplained disappearance from the source registers (n = 203), an autism diagnosis (n = 11), or an exclusionary diagnosis (n = 620). This resulted in a study cohort of 657 461 children contributing 5 025 754 person-years of follow-up during 1 January 2000 through 31 August 2013.
During follow-up, 6517 children were diagnosed with autism (incidence rate, 129.7 per 100 000 person-years), and 6518 children were censored (335 had an autism-associated syndrome or condition, 628 had died, 5537 had emigrated, and 18 had disappeared from the source registers for unknown reasons). The number of children and autism cases in the study according to age and vaccination status are presented in Figure 1 of the Supplement.
The mean attained age in the study was 8.64 years (SD, 3.48). The first autism-related diagnoses among included autism cases were autistic disorder (n = 1997), atypical autism (n = 537), Asperger syndrome (n = 1098), other pervasive developmental disorder (n = 576), and unspecified pervasive developmental disorder (n = 2309). The mean age at first autism diagnosis was 7.22 years (SD, 2.86), and the mean age among autistic disorder cases was 6.17 years (SD, 2.65). Uptake of the MMR1 vaccine was 95.19%, with a median age at vaccination of 1.34 years (interquartile range, 0.24 years). There were no appreciable differences in vaccine uptake according to sex, birth cohort, autism risk score, or autism history in siblings; MMR vaccinations were more common among children previously vaccinated in early childhood (Table).
The variables used to construct the autism risk score are presented in Table 1 of the Supplement. The largest single risk factors for autism were an older or unknown father, an older mother, poor Apgar score, low birthweight, preterm birth, large head, assisted birth, and smoking in pregnancy (Table 1 of the Supplement). The crude hazard ratios associated with the deciles of the autism risk score ranged from 0.73 (first versus fifth decile) to 1.62 (10th versus fifth decile) (Table 2 of the Supplement). The Harrell C-statistic for the autism risk score was 0.57.
Comparing MMR-vaccinated with MMR-unvaccinated children yielded a fully adjusted aHR of 0.93 (95% CI, 0.85 to 1.02). The test for homogeneity of aHRs in the age intervals 1 to 3, 3 to 5, 5 to 7, 7 to 10, and more than 10 years of age yielded a P value of 0.138. Crude cumulative incidences of autism in MMR-vaccinated and MMR-unvaccinated children are presented in Figure 2. Ending follow-up at 5, 7, and 10 years of age produced similar aHRs (0.97 [CI, 0.81 to 1.15], 0.96 [CI, 0.84 to 1.09], and 0.97 [CI, 0.87 to 1.07], respectively). Ending follow-up at 3 years of age yielded a slightly lower aHR (0.73 [CI, 0.53 to 1.00]).
We compared MMR-vaccinated with MMR-unvaccinated children in subgroups characterized by sex, birth cohort, other childhood vaccines received, autism risk score, or autism history in siblings (Figure 3). Receipt of MMR vaccination reduced the risk for autism in girls (aHR, 0.79 [CI, 0.64 to 0.97]) and in the 1999–2001 birth cohort (aHR, 0.84 [CI, 0.73 to 0.96]). The MMR vaccination did not increase the risk for autism in children characterized by other early childhood vaccinations, high risk for autism, or having autistic siblings (Figure 3). When sibling history of autism was treated as a time-varying covariate, MMR vaccination was also not associated with autism among children with autistic siblings (aHR, 1.15 [CI, 0.71 to 1.87]). Cumulative incidences of autism according to age and MMR vaccination status, stratified by sex and sibling history, are presented in Figure 2 of the Supplement. Cumulative incidences of autism according to age stratified on autism risk score groups are presented in Figure 3 of the Supplement.
Figure 3. Association between measles, mumps, rubella vaccination and autism in subgroups of 657 461 children born in Denmark between 1 January 1999 and 31 December 2010.
Fully adjusted autism hazard ratios comparing children who received measles, mumps, rubella vaccine with those who did not. The hazard ratios are depicted on a logarithmic scale, with bars representing 95% CIs. P values are from a test of homogeneity of effect. DTaP-IPV/Hib = diphtheria, tetanus, acellular pertussis, inactivated poliovirus, and Haemophilus influenzae type b vaccine; NA = not applicable.
The crude effect sizes of sex, birth cohort, other early childhood vaccinations, sibling history of autism, and autism risk score are presented in Tables 2 and 3 of the Supplement. The highest risk for autism was conferred by being a boy (HR, 4.02 [CI, 3.78 to 4.28]), being born in a late birth cohort (2008-2010; HR, 1.34 [CI, 1.18 to 1.52]), having no early childhood vaccinations (HR, 1.17 [CI, 0.98 to 1.38]), and having siblings with autism at study entry (HR, 7.32 [CI, 5.29 to 10.12]). The autism risk score had a modest effect on autism risk compared with sex and sibling history of autism (highest-risk group versus moderate-risk group; HR, 1.38 [CI, 1.28 to 1.48]).
We evaluated HRs in 1-year risk periods after MMR vaccination; we identified no period after MMR vaccination with an increased aHR (Figure 3).
The analysis requiring at least 2 autism diagnosis registrations for case ascertainment resulted in similar results as the main analysis (aHR, 0.99 [CI, 0.88 to 1.11]). Using autistic disorder cases or other autism spectrum cases only resulted in aHRs of 0.96 (CI, 0.81 to 1.13) and 0.91 (CI, 0.82 to 1.02), respectively. In an analysis taking the second MMR dose into account, there was no evidence of a dose-response (increase in aHR per dose, 0.90 [CI, 0.85 to 0.95]). Adjustment for the potential confounders as covariates instead of stratification of the baseline hazard function did not affect the result (aHR, 0.93 [CI, 0.84 to 1.02]). Replacing the autism risk score with the individual covariates used to estimate it in the above model yielded an aHR of 0.94 (CI, 0.85 to 1.03).
Discussion
We found no support for the hypothesis of increased risk for autism after MMR vaccination in a nationwide unselected population of Danish children; no support for the hypothesis of MMR vaccination triggering autism in susceptible subgroups characterized by environmental and familial risk factors; and no support for a clustering of autism cases in specific time periods after MMR vaccination.
We previously addressed this issue in a similar but nonoverlapping nationwide cohort study of 537 303 Danish children (5). Reassuringly, the main results are similar between the 2 studies, which supports the internal and external validity of both. The major difference between our studies is a significant increase in statistical power and additional susceptible subgroup and clustering analyses. In a 2014 meta-analysis of MMR vaccination and autism studies, 2 cohort and 4 case–control studies were identified from Denmark (5), Poland (17), Japan (4, 18), the United Kingdom (19), and the United States (20), with no support for an association—for example, a pooled odds ratio from cohort studies of 0.84 (CI, 0.70 to 1.01) (2).
A concern about observational studies is that they do not often take into account the possibility of MMR vaccination triggering autism in susceptible subgroups of children. The large number of cases in our study allowed us to define subgroups with sufficient statistical power for useful inference. Specific definitions of susceptible subgroups have been lacking. We defined subgroups according to environmental and familial risk factors for autism. We are only aware of 1 previous study taking a similar approach: A U.S. study by Jain and colleagues (3) evaluated the association between MMR and autism according to sibling history of autism. Those researchers found no support for an association in children with a sibling history of autism, but identified lower MMR uptake rates in children with affected siblings, a potentially important public health issue with increasing autism prevalence and supported by other studies (21).
Another frequent criticism of observational studies of MMR vaccination and autism is a perceived failure to take into account the existence of specific autism phenotypes associated with vaccination, such as regressive autism. Our analysis of specific time periods after vaccination does not support a regressive phenotype triggered by vaccination with excessive clustering of cases in the subsequent period, and no other studies have been able to substantiate the existence of this phenotype (22).
A general criticism of observational vaccine effect studies is that they do not include a completely unvaccinated group of children (23). The number of children completely unvaccinated throughout childhood will be low in a country such as Denmark. We evaluated the association between MMR and autism in children with no DTaP-IPV/Hib vaccinations in the first year of life; we found no support for an association in this vaccine-naive subpopulation.
Our study has several strengths. Comprising 6517 cases, it is by far the largest single study to date and adds significantly to our knowledge on the issue, in that it allows us to conclude from one study that even minute increases in autism risk after MMR vaccination are unlikely, assuming unbiased results. We evaluated the hypothesis in an unselected setting with a nationwide cohort from an ethnically and socioeconomically homogenous population. We obtained independent and prospectively collected information on vaccination and autism from nationwide health registries with mandatory reporting reducing concern about ascertainment and recall bias. We included information on a range of environmental and familial risk factors, which allowed us to consider their potential confounding effect.
We obtained autism cases from the Danish Psychiatric Central Register, which has previously been used extensively for autism research in Denmark. This register has a high degree of validity; an earlier medical record review revealed a positive predictive value of 92.5% (5), and our study prevalence of 1.0% is similar to that found in other studies (24) and the estimated general U.S. prevalence of 1.5% (25).
A limitation of our study is that we used date of first diagnosis of autism, which is probably delayed compared with the age at onset of symptoms. This can be a source of information bias—for example, in the case where symptoms precede vaccination and diagnosis occurs after vaccination. This will result in misclassification of autism cases as vaccinated, biasing the hazard ratio toward an effect. If onset of symptoms results in avoidance of vaccination, or conversely if symptoms increase the probability of vaccination through increased health care utilization, bias in either direction is possible. During the study period, the measles strain in the vaccine changed in 2008 from Schwarz to Ender's Edmonton. However, birth cohort–specific HRs were homogeneous, suggesting that the change in composition had no effect on autism risk.
Measles outbreaks are not uncommon in Europe and in the United States, and vaccine hesitancy or avoidance has been identified as a major cause (26). In a mathematical modeling study, U.S. researchers concluded that even a 5% reduction in vaccination coverage would triple measles cases, with significant health economic costs (27). A main reason that parents avoid or are concerned about childhood vaccinations has been the perceived link to autism (28). Our study adds to previous studies through significant additional statistical power and by addressing hypotheses of susceptible subgroups and clustering of cases. We believe that our results offer reassurance and provide reliable data on which clinicians and health authorities can base decisions and public health policies.
In conclusion, our study does not support that MMR vaccination increases the risk for autism, triggers autism in susceptible children, or is associated with clustering of autism cases after vaccination.
Supplemental Material
References
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Published In
Annals of Internal Medicine
Volume 170 • Number 8 • 16 April 2019
Pages: 513 - 520
History
Published online: 5 March 2019
Published in issue: 16 April 2019
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© 2019 American College of Physicians.
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Measles, Mumps, Rubella Vaccination and Autism: A Nationwide Cohort Study. Ann Intern Med.2019;170:513-520. [Epub 5 March 2019]. doi:10.7326/M18-2101
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Study conclusions unsupported.
Susceptible Groups
MMR and autism study is fundamentally flawed
Vaccines are not created equal
The purpose of publishing this study is to use the resultsworldwide. The assumption is that the MMR vaccinecovered in the study is representative of vaccines usedworldwide. But that assumption is false. There are nospecifications that control the thousands of antigens inthe vaccine from the chicken embryo cell culture used togrow the viruses or excipients such as gelatin(non-target antigens (NTA)).
We have seen repeatedlythat adverse events can becaused by NTA.
Gelatinor egg protein containing vaccines caused thedevelopment of allergy to those antigens. (1) Thelatest example is Pandemrix vaccine induced narcolepsy.Pandemrix manufactured in Europe contained largeramounts of H1N1 nucleoproteins (an NTA) and resulted inway more cases of narcolepsy, compared to Arepanrixmanufactured in Canada (2).
Eggprotein amounts in vaccines vary by orders of magnitude,among vendors, batches and over time. (1)
Bovine casein content varied 2-fold in just eight vaccine samples.
Engerix vaccine contains 500% of the yeast proteins as the Recombivax vaccine.
Due to such variation among vaccines, the study results are rendered inapplicable and the purpose of the study is defeated.
Autism mechanisms
There have been many developments in autism research in thelast two decades that the authors have ignored.Antibodies directed against folate receptor alpha,GAD65, glutamate receptors and other antigens, in the child or the mother, can cause autism. Multiple vaccines can induce these antibodies in the child or the mother (3).
Cow’smilk protein containing vaccines (DTaP) cause the vastmajority (75%) of autism cases (4). A subset of autismcan be caused by GAD65 antibodies that are induced byGAD65 proteins in the MMR vaccines. GAD65 can be of chick (cell culture) or animal (gelatin) origin.Maternal antibodies can affect the fetal brain (3). Epidemiological studies cannot account for these variables.
Epidemiological studies
The US IOM committee in their 2011 report (5) wrote:
“The committee concluded the evidence convincingly supports 14 spe-cific vaccine–adverse event relationships. In all but one of these relation-ships,the conclusion was based on strong mechanistic evidence with the epidemiologic evidence rated as either limited confidence or insufficient.”
So in an overwhelming 93% of cases, mechanistic studies provided convincing evidence and epidemiological studies failed.
This study is therefore flawed, misleads and must be retracted.
References
1.Arumugham V. Evidence that Food Proteins inVaccines Cause the Development of Food Allergiesand Its Implications for Vaccine Policy. J DevDrugs. OMICS International; 2015 Oct;04(04):1–3.
2.Godlee F. A tale of two vaccines. BMJ. 2018 Oct4;363:k4152.
3.Arumugham V. Vaccines and Biologics injury tablebased on mechanistic evidence – Mar 2019[Internet]. 2019. Available from: https://doi.org/10.5281/zenodo.2582634
4.Arumugham V, Trushin M V. Autism pathogenesis:Piecing it all together, from end to beginning …. J Pharm Sci Res. 2018;10(11):2787–9.
5. Clayton EW,Rusch E, Ford A, Stratton K. Adverse Effects ofVaccines:: Evidence and Causality. NationalAcademies Press; 2012.
Study supports MMR-autism link in sibling subset
As with their 2002 NEJM study, the coauthors' conclusion is contradicted by their results. The Hazard Ratio that stands out in Figure 3 is MMR risk in children with ASD siblings. The HR from MMR was 2.64 among children with siblings who have autism. Although the magnitude is far greater than any other reported HR in this figure, it is not significant because of the small sample of this group.
It would therefore be preferable for the authors to instead report the risk for autism from having a sibling with autism but no MMR vaccination and then the risk for autism from having both an autistic sibling and MMR vaccination. The increased risk in both groups would both be strong and significant, but the magnitude would be substantially higher in MMR+ASD sibling compared to no MMR+ASD sibling.
The study's results are supportive of an MMR-autism link in the sibling subset with sibling status being an important effect modifier. Yet the conclusion states the opposite. Not surprisingly, the corresponding author of this study did not respond to this reader's concern in email.
After the coauthors' 2002 study was published, a letter to NEJM by an epidemiologist at McGill University suggested they had artificially eliminated the association between MMR and autism by adjusting for age.(1) He suggested that age was an effect modifier and that the authors compare age-stratified rates between subjects 24-29 months post-MMR vaccination to non-MMR vaccinated. His letter was never published or responded to, and his advice was never heeded. We can now add ASD sibling status as yet another effect modifier that the authors dismissed to dismiss the very real MMR vaccine-autism link.
1. Stott C, Blaxill M, Wakefield AJ. MMR and Autism in Perspective: the Denmark Story, J Am Phys Surg. 2004, 9,3, 89-91.
http://www.jpands.org/vol9no3/stott.pdf
Disclosures:
Received funding from Autism Media Channel and Children's Medical Safety Research Institute
Potential Misinterpretation of Epidemiological Studies
The occurrence of an illness following vaccination warrants a detailed analysis of the affected individuals. One topic that the authors have failed to consider is the existence of vaccine-derived, stealth adapted viruses. These viruses are not effectively recognized by the cellular immune system because of deletions or mutations in the genes coding for the relatively few major virus components, which are normally targeted by the cellular immune system. Minor virus components may become immunogenic if the reactivity of the immune system is boosted with adjuvants or live vaccine virus.
DNA sequence data have unequivocally established an African green monkey cytomegalovirus origin of the stealth adapted viruses isolated from a patient with the chronic fatigue syndrome and from another patient who died following a bipolar psychosis (1, 2). This topic should be covered in any discussion of vaccine safety. W. John Martin, MD, PhD.
1. Martin et al. (1995) African green monkey origin of the atypical cytopathic 'stealth virus' isolated from a patient with chronic fatigue syndrome Clinical Diagnostic Virology 4(1):93-103.
2. Martin et al. (1996) Simian cytomegalovirus-related stealth virus isolated from the cerebrospinal fluid of a patient with bipolar psychosis and acute encephalopathy. Pathobiology 64(2): 64-6.
Hypothesis Needs Clarification
I think the vexing part (for both doctors and parents) of the debate is this:
1) Are we asking if MMR can cause Autism at all?
In which case our evidence will almost necessarily be restricted to the occasional case reports and Vaccine Adverse Events registry reports of WELL -INVESTIGATED patients.
OR
2) Are we asking if MMR can cause Autism with a certain large enough probability that it can be picked up on large epidemiological studies (epidemiology being a "blunt tool")?
This paper follows a long line of papers using Epidemiological research methods to prove/disprove the MMR-Autism link (risk/association etc).
My concern with regard to continued "Epidemiological" research is this:
There are a few things we know from previous studies (the stats I am quoting are approximates).
1) Non-MMR-Autism in the population is about eg 2% (varying from 1.5 to 2.5)
2) MRR-Autism (if it exists at all) is probably rarer than 1/1000000 ( this is because MMR induced encephalitis is 1/1000000 so MMR-Autism must be even rarer. In fact, in spite of so many studies it has never been picked up at all!). But lets fix it as 1/1000000=0.0001% for the sake of this argument.
Even if we do an RCT (gold standard) with 2 million children: Given MMR (1M) vs Not given MMR(1M)
No-MMR group= 2% children get autism
MMR group = 2%+0.0001%=2.0001% get autism (that is 1 one child out of the million got MMR-Autism) and (20,000 out of a million got Non-MMR-Autism). BUT we don't know who got which type.
Will (2.0001- 2.0) be "statistically significant"? Likely not.
Will (2.0001-2.0) be "clinically significant"- I think not.
Why?
1) because we know that autism varies from 1.5% to 2.5% within a normal population and 2.0001% is within that normal range.
2) There is bound to be Random Error in the distribution of baseline Non-MMR autism as the cases get distributed to each group, so both groups won't get EXACTLY 2%
3) MMR group with 2.0001 % and Non-MMR group with 2% are almost perfectly balanced.
So, quite naturally we cannot conclude that there is any association between MMR and Autism even though 1 child did have MMR-linked Autism in our example
In short, rare causal events can be masked by natural variation in the incidence of the disease
For us to be able to pick up MMR-Autism on an epidemiological type study it has to be pretty much well and consistently OUTSIDE the 2.5 range.
Or at least we must consistently see a larger difference between the two groups.
Dr Manimalar Selvi Naicker
(MBBS, M.Path (Histopathology), M.MedStats)
Could I try Causal Learning to this Data?
Authors' Response
We appreciate the massive, global attention our paper has received and have carefully evaluated all comments. Below, we address the major claims made by some of our critics.
Mr. Arumugham lists a number of specific biological mechanisms hypothesized to be involved in the etiology of autism, and he rightfully claims that epidemiological studies are not capable of addressing such mechanisms. However, Mr. Arumugham ignores the central message from our present and prior well-conducted epidemiological investigations, namely that regardless of which biological mechanisms lead to autism, there is no difference in autism risk between MMR-vaccinated and MMR-unvaccinated individuals. In this light, it seems illogical and futile to continue the quest to understand the biology of autism by focusing on theoretical adverse effects of a vaccine that seems, rather compellingly, to be safe both overall and, specifically, in relation to autism risk.
Professor Exley wants to know if we took prior exposure to aluminium, for example in vaccinations that include an aluminium adjuvant, into account. Indeed, we did. According to Figure 3 in the paper, MMR vaccination was not associated with autism risk, whether children had been vaccinated with aluminium-adjuvanted vaccines (DTaP-IPV/Hib) in infancy or not.
In response to Mr. Crosby’s comment it should be noted that sibling status at 1 year of age was not an effect modifier (Figure 3, p>0.20), and the confidence interval for the “Siblings with autism” effect estimate overlaps HR=1.00. In Figure 2 of the Supplementary Material, we transparently provide the unadjusted cumulative incidences according to age and vaccination status, and stratified according to child’s sex and sibling history of autism; these supplementary analyses do not support an association in children with autistic siblings. Sibling status at 1 year of age is a conservative measure of “Siblings with autism” with only 5 unvaccinated and 32 vaccinated cases (Figure 3). If we consider sibling history as a time-varying variable, that is, each child’s “sibling status” is updated during the study period, e.g. if a sibling is diagnosed with autism, we gain statistical power. In this analysis, MMR vaccination was also not associated with autism risk in children with autistic siblings (HR, 1.15, 95% CI, 0.71-1.87) (see Results).
The further claim by Mr. Crosby that we “artificially eliminated” an association between MMR vaccination and autism by adjusting for age in our 2002 study is false and reveals an incomplete understanding of survival analysis. Our 2002 study and the current study share many similarities in study design, and thus, the concept of confounding by age is clearly illustrated in Figure 1 of the Supplementary Material, where the distribution of time and autism cases according to vaccination status and age is visualized; here we show that unvaccinated children are younger, and since younger children have lower rates of autism the crude rate ratio is confounded by age. Consequently, adjustment for age is required. In Figure 2, we present cumulative incidences according to age; there is no suggestion of any age interval where vaccinated children have a higher rate of autism than unvaccinated children, and a test of homogeneity yielded a P-value of 0.138 (see Results).
In conclusion, we maintain that we have analyzed the current study as well as our 2002 study using appropriate statistical methods, finding no support for an association between MMR vaccination and autism risk, a lack of an association that also applied in children with autistic siblings.
Sincerely,
Anders Hviid, Jørgen Vinsløv Hansen, Morten Frisch and Mads Melbye
Measles, Mumps, Rubella Vaccination and Autism: insufficient evidence for susceptible children
Since there was a hypothesized link between the MMR vaccine and autism, most of us are much more concerned to know if MMR vaccination could increase the risk for autism in susceptible children. The study showed that MMR vaccination was associated with a hazard ratio of 2.69 (95% confidence interval, 0.58-12.43) in subgroup of siblings with autism. The hazard ratios and 95% confidence intervals were 0.98 (0.84-1.13), 0.89 (0.78-1.01), and 0.89 (0.45-1.77) in subgroups of no siblings with autism, no siblings, and father’s ID missing, respectively. The authors concluded that the study strongly supports that MMR vaccination does not trigger autism in susceptible children because the hazard ratio of 2.69 was accompanied by a wide confidence interval with no statistical significance. One reader recommend the authors to report the risk for autism from having a sibling with autism but no MMR vaccination and the risk for autism from having both an autistic sibling and MMR vaccination. This reader suggested that the study's results are supportive of an MMR-autism link in the subgroup of siblings with autism. I think that it was neither able to conclude there was an MMR-autism link in the sibling subgroup, nor to conclude that there was no MMR-autism link in the sibling subgroup. In the study, there were only 37 children in group of siblings with autism. No matter what result is and if there was a statistically significant result, such low sample size means there was insufficient evidence to make a conclusion between MMR vaccination and autism risk in susceptible children (i.e., children with siblings with autism).
References
1. Hviid A, Hansen JV, Frisch M, Melbye M. Measles, Mumps, Rubella Vaccination and Autism: A Nationwide Cohort Study. Ann Intern Med. 2019 Mar 5. doi: 10.7326/M18-2101. [Epub ahead of print]
Disclosures: None
Authors' response does not answer questions about either study
For example, what is a child’s risk of ASD associated with having an ASD sibling with no MMR vaccination? Now what is the risk associated with the combination of having an ASD sibling and an MMR vaccination? There is clear evidence of an interaction. Yet nothing in the study or supplementary material answers these questions, including the supplementary figure referred to by the authors where the sibling sample is reduced to even smaller groups.
Analyzing sibling status as a “time-varying variable” is also inappropriate when sibling status is supposed to be treated as a marker for innate susceptibility. That susceptibility would be present from birth; it wouldn’t begin with the diagnosis of the sibling.
Also unaddressed are the points made about the 2002 study in the unpublished letter to NEJM by McGill University epidemiologist Dr. Samy Suissa. In his letter, Dr. Suissa demonstrates that the age variable is an effect modifier that was inappropriately treated as confounder in the study. Here is the portion of his letter explaining what the study did wrong:
“Indeed, the rates of autistic disorder by age at vaccination, although not the age at follow-up, are 18.9, 14.8, 24.6, 26.9 and 12.0 per100,000 per year respectively for ages <15, 15-19, 20-24, 25-35 and >35 months. These rates are all above the overall rate of 11.0 for the reference group of no vaccination, over all ages. It is then somewhat implausible for the adjusted rate ratio to fall below 1, unless the risk profile by age in the unvaccinated is vastly different than in the vaccinated (effect-modification). In this case, the adjustment for age could have been artificial. It would be useful then to present rates on subjects 24-29 months since vaccination and on the unvaccinated (crude rate ratio 2.5) stratified by age. Otherwise, one could be tempted to conclude that the figure is in fact suggestive of an association between MMR vaccination and the risk of autism.”(1)
None of the figures from the current study provide the measurements Dr. Suissa suggested. Moreover, those figures are not even for autistic disorder but rather for the total category of ASDs in general.
1. Stott C, Blaxill M, Wakefield AJ. MMR and Autism in Perspective: the Denmark Story, J Am Phys Surg. 2004, 9,3, 89-91.
http://www.jpands.org/vol9no3/stott.pdf
Disclosures: Received funding from Autism Media Channel and Children's Medical Safety Research Institute
Response
Mr. Crosby repeats the claim that the age-adjustment in our original 2002 paper has “artificially eliminated” an association between MMR and autism. He references an unpublished letter by Dr. Suissa, claiming that the rates in Table 2 of our 2002 paper and our adjusted RRs are incompatible and that this might reflect effect modification. This is incorrect. From Table 2 in our 2002 paper, we can calculate the crude relative risk (RR) of autistic disorder as 1.45 (95% CI, 1.08-1.95). Adjusting for age yields a RR of 0.91 (0.68-1.23). As explained previously, the discrepancy between the crude and age-adjusted RRs is due to the follow-up in the unvaccinated group comprising person-time from 1 year of age until age at MMR vaccination from all the MMR vaccinated children. Now, if we start follow-up at 2 years of age instead of 1 year of age we get a crude RR of 0.90 (0.66-1.22) and an age-adjusted RR of 0.88 (0.65-1.19). Clearly, starting follow-up at an age where the unvaccinated and vaccinated groups have similar age distributions yields almost identical results as the main result in the paper; we maintain that adjustment for age is both appropriate and necessary with follow-up from 1 year of age. Similarly, for our current study, we repeat our previous response: In Figure 2, we present cumulative incidences according to age; there is absolutely no suggestion of any age interval where vaccinated children have a higher rate of autism than unvaccinated children, and a test of homogeneity yielded a P-value of 0.138 (see Results).
Mr. Crosby claims that there is clear evidence of an interaction between sibling status and MMR vaccination. We tested this and found no such evidence P>0.20 (see Figure 3). Mr. Crosby also claims that analyzing sibling status, as a time-varying variable is inappropriate. This, too, is not correct. By continually updating sibling status in the event of a sibling receiving an autism diagnosis, all information this variable can supply as a proxy for genetic susceptibility is utilized. Our claim that the two approaches measure the same attribute with differing degrees of statistical precision is supported by a comparison of autism HRs: status at study start HR 7.32 (5.29-10.12) and time-varying status HR 7.64 (6.77-8.62) (Table 3, Supplementary Material).
In conclusion, we maintain that we have analyzed the current study and our 2002 study using appropriate statistical methods, finding no support for an association between MMR vaccination and autism risk, a lack of an association that also applied in children with autistic siblings.
Sincerely,
Anders Hviid, Jørgen Vinsløv Hansen, Morten Frisch, Mads Melbye.
Authors’ inability to address vaccine content variation effect and lack of control for multiple mechanisms is very troubling
In their response the authors were unable to address my point about the effect of wide variation in the unregulated non-target antigen content of vaccines. They should therefore accept that this study has no predictive value and misleads the scientific community. The study conclusions may not even apply to Denmark (much less the rest of the world), as the current vaccines in use there may not have the same characteristics as the ones administered during the study period.
Regarding mechanisms, the authors write: “regardless of which biological mechanisms lead to autism, there is no difference in autism risk between MMR-vaccinated and MMR-unvaccinated individuals.”
Not true. What if more mothers of children in the MMR-unvaccinated group were making maternal autism related antibodies? What if the MMR-unvaccinated group received more cow’s milk protein containing vaccines? That will mask MMR induced autism. (1)
As previously noted, 75% of autism cases are caused by cow’s milk protein containing vaccines such as DTaP, Prevnar 13, Hib. So MMR’s contribution can be easily masked if all other contributors are not carefully controlled.
As I wrote previously, per the US IOM report, epidemiological studies are already weak and rarely provide convincing evidence. On top of that when you fail to control for multiple biological mechanisms, it leads to type II errors, with devastating consequences for millions.
The authors write: “it seems illogical and futile to continue the quest to understand the biology of autism by focusing on theoretical adverse effects of a vaccine”
Filtering the lines of scientific inquiry of autism mechanisms using such flawed and misleading epidemiological studies makes no sense. It is the reason why after billions and decades wasted (2,3), we do not have “official” root cause for autism. This approach is wrong, unscientific and extremely dangerous.
The correct approach to this problem is the far more reliable mechanistic approach involving bioinformatics analysis and autoimmune serology as suggested by Wraith et al. (4)
Further, as others have noted, declaring conflicts of interests and funding does not erase their undesirable impact on the study’s conclusions (5).
References
1. Arumugham V. Epidemiological studies that ignore mechanism of disease causation are flawed and mechanistic evidence demonstrates that vaccines cause autism [Internet]. 2017. Available from: https://doi.org/10.5281/zenodo.1041905
2. Glasziou P, Chalmers I. Research waste is still a scandal-an essay by Paul Glasziou and Iain Chalmers. BMJ. England; 2018 Nov;363:k4645.
3. Gyles C. Skeptical of medical science reports? Can Vet J = La Rev Vet Can. Canadian Veterinary Medical Association; 2015 Oct;56(10):1011–2.
4. Wraith DC, Goldman M, Lambert P-H. Vaccination and autoimmune disease: what is the evidence? Lancet (London, England). England; 2003 Nov;362(9396):1659–66.
5. Opinion | Transparency Hasn’t Stopped Drug Companies From Corrupting Medical Research - The New York Times [Internet]. [cited 2019 Jan 22]. Available from: https://www.nytimes.com/ 2018/09/14/opinion/jose-baselga-research-disclosure-bias.html
The issues remain
Still unaddressed are the disparities in autistic disorder incidence for children by age at MMR vaccination. Also unaddressed is why the incidence for every one of these age groups exceeds the incidence in the MMR-unvaccinated. The supplementary figure from the current study does not explain these disparities in incidence of autistic disorder. The figure does not even display a graph of the incidence of autistic disorder. Age-stratified incidence rates for the MMR-unvaccinated group and the MMR-vaccinated group around the time since vaccination where incidence for autistic disorder peaked would help explain these incidence disparities. That is why Dr. Suissa suggested these stratifications.
All the authors’ supplementary HRs show is that a child’s risk for autism with an ASD sibling is the same regardless of when that sibling is diagnosed. However, children’s siblings may not be diagnosed until after the children’s MMR vaccinations. Those children will be counted and followed up as if they have no ASD siblings until the siblings are diagnosed; this may not even be until after the children themselves are diagnosed. This is not an appropriate method to measure a susceptibility variable. Even though there were nearly 18,000 children in the current study with no MMR vaccination and only non-ASD siblings, the authors chose for their reference group a sample of just 79 participants (Table). The risk of having ASD should have been separately analyzed in the group with an ASD sibling but no MMR vaccination as well as in the group with a combination of both.
The authors’ conclusions are not supported by the results they generated using the methodologies that were employed in either study.
Disclosures: Received funding from Autism Media Channel and Children's Medical Safety Research Institute
The Measles, Mumps and Rubella (MMR) Vaccine and Autism: Commentary
However, comparing autism rates among children receiving and not receiving the MMR would not rule out a possible contributory role for the MMR vaccine in causing autism. Many factors, including the MMR and other vaccines, could be combining with as yet unidentified host and environmental factors to cause autism. The effect of these analyses was therefore to compare autism rates in two highly vaccinated groups, thereby obliterating the potential impact of vaccines in general.
Comparisons should instead be between fully vaccinated and completely unvaccinated groups of children, or between MMR-only vaccinated and completely unvaccinated children in terms of autism. So the question whether MMR-vaccinated children are more likely to be diagnosed with autism than non-MMR-vaccinated may not be the appropriate question to start with.
Evidence now suggests that autism is not an exclusively neuropsychiatric disorder but has many co-morbid features such as allergies, middle ear infections, and numerous systemic complications.1,2 The author and colleagues found that autism and most of these other features were significantly more common in vaccinated than in unvaccinated children, and in a vaccination dose-response relationship;3 moreover, preterm birth coupled with vaccination nearly doubled the odds of a neurodevelopmental disorder.4 These observations suggest that the trigger for autism and related chronic conditions may be related to the cumulative physiological impact of multiple vaccinations administered synchronously or near-synchronously, against a background of prematurity, rather than one or more individual vaccines administered separately. Discovering a biomarker associated with this mechanism would enable potentially susceptible children to be identified in advance and exempted from vaccination.
While measles is generally a mild and short-lived disease, autism is chronic and seriously disabling. Considering that rates of autism among boys are currently 3.63% compared to 0.0005% (1 in 2,000) only 50 years ago5 – the importance of continuing to research the MMR/vaccine-autism question cannot be over-emphasized, not just as a public health problem but as a national emergency.
Conflict of Interest None.
References
1. Xu G, Snetselaar LG, Jing J, Liu B, Strathearn L, Bao W. Association of food allergy and other allergic conditions with autism spectrum disorder in children. JAMA Network Open 2018; 1(2):e180279. doi:10.1001/jamanetworkopen.2018.0279
2. Adams DJ, Susi A, Erdie-Lalena CR, Gorman G, Hisle-Gorman E, Rajnik M, Elrod M, Nylund CM. Otitis media and related complications among children with autism spectrum disorders. J Autism Dev Disord 2016; 46(5):1636-42. doi: 10.1007/s10803-015-2689-x.
3. Mawson AR, Ray BD, Bhuiyan AR, Jacob B. Pilot comparative study on the health of vaccinated and unvaccinated 6- to 12-year-old U.S. children. J Transl Sci 2017; 3: DOI: 10.15761/JTS.1000186
4. Mawson AR, Bhuiyan AR, Jacob B, Ray BD. Preterm birth, vaccination and neurodevelopmental disorders: a cross-sectional study of 6- to 12-year-old vaccinated and unvaccinated children. J Transl Sci 2017; 3: DOI: 10.15761/JTS.1000187
5. Zablotsky B, Black LI, Blumberg SJ. Estimated prevalence of children with diagnosed developmental disabilities in the United States, 2014–2016. NCHS Data Brief, no. 291. Hyattsville, MD: National Center for Health Statistics. 2017.
Additional point: authors’ inappropriate reasoning about 2002 study person-time
The point of using person-time is to account for unequal follow-up by comparing risk of developing a disorder in persons during exposed and unexposed periods. Although the exposed at-risk are not counted as exposed before the exposure, the unexposed at-risk had the opportunity to develop the outcome before ever becoming exposed. While everyone at risk for autistic disorder at MMR vaccination would have first contributed varying quantities of MMR-unvaccinated person-time, everyone at risk had the opportunity to develop autistic disorder before MMR vaccination.
That is why delaying the start of follow-up to two years of age produces a skewed measure of association. The number of cases in both groups remain the same but are now divided against incomplete person-time in each group. Since person-time is disproportionately incomplete in the MMR-unvaccinated group, the result is biased and should not be used to justify any conclusion as the authors have now done.
Disclosures: Received funding from Autism Media Channel and Children's Medical Safety Research Institute
Misleading conclusion
Insufficient sample sizes and possible selection bias should temper conclusions
We should also be alert to the fact that the authors were unable to measure even some of the most conspicuous potential sources of selection bias, such as family history beyond the sibling level. The authors don’t remark on the issue, but if families with increased risk — say, parents who manifest the disorder or have autistic siblings, nieces, or nephews — chose to vaccinate at a markedly lower rate, that could skew results and, incidentally, offer explanatory fodder for the findings of significantly reduced hazard amongst girls and the entire 1999-2001 birth cohort. The latter in particular would cohere with a speculative narrative of greater vaccination fears [2] — especially in those years immediately following publication of Wakefield et al.’s infamous Lancet article — among parents aware of a genetic pre-disposition or early autism symptoms in their infants.
One can hope that a solid mechanistic understanding of the disorder’s development, earlier diagnosis [3], or future availability of a more informative dataset can ultimately ground the underlying conclusions here. Meanwhile, we should be wary of the ill-effects that contentious evidentiary claims on either side of this issue can bring.
1. A. Hviid, J. V. Hansen, M. Frisch, and M. Melbye. Measles, mumps, rubella vaccination and autism: A nationwide cohort study. Annals of internal medicine, 170(8), 513–520 (2019).
2. O. Zerbo et al. Vaccination Patterns in Children After Autism Spectrum Disorder Diagnosis and in Their Younger Siblings. JAMA pediatrics, 172(5), 469-475 (2018).
3. R. W. Emerson et al. Functional neuroimaging of high-risk 6-month-old infants predicts a diagnosis of autism at 24 months of age. Science Translational Medicine, 9(393) (2017).