PEDIATRICS Vol. 122 No. 2 August 2008, pp. e438-e445 (doi:10.1542/peds.2007-3604)
ARTICLE |
Macrophage Migration Inhibitory Factor and Autism Spectrum Disorders
a Child Study Center and Departments of
b Psychology
c Epidemiology and Public Health
e Statistics
f Internal Medicine and Pathology, Yale University, New Haven, Connecticut
d Department of Psychology, Moscow State University, Moscow, Russia
g Sapporo Immuno Diagnostic Laboratory, Sapporo, Japan
h Accare/University Medical Center Groningen, University Center for Child and Adolescent Psychiatry, Groningen, Netherlands
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ABSTRACT |
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OBJECTIVE. Autistic spectrum disorders are childhood neurodevelopmental disorders characterized by social and communicative impairment and repetitive and stereotypical behavior. Macrophage migration inhibitory factor (MIF) is an upstream regulator of innate immunity that promotes monocyte/macrophage-activation responses by increasing the expression of Toll-like receptors and inhibiting activation-induced apoptosis. On the basis of results of previous genetic linkage studies and reported altered innate immune response in autism spectrum disorder, we hypothesized that MIF could represent a candidate gene for autism spectrum disorder or its diagnostic components.
METHODS. Genetic association between autism spectrum disorder and MIF was investigated in 2 independent sets of families of probands with autism spectrum disorder, from the United States (527 participants from 152 families) and Holland (532 participants from 183 families). Probands and their siblings, when available, were evaluated with clinical instruments used for autism spectrum disorder diagnoses. Genotyping was performed for 2 polymorphisms in the promoter region of the MIF gene in both samples sequentially. In addition, MIF plasma analyses were conducted in a subset of Dutch patients from whom plasma was available.
RESULTS. There were genetic associations between known functional polymorphisms in the promoter for MIF and autism spectrum disorder–related behaviors. Also, probands with autism spectrum disorder exhibited higher circulating MIF levels than did their unaffected siblings, and plasma MIF concentrations correlated with the severity of multiple autism spectrum disorder symptoms.
CONCLUSIONS. These results identify MIF as a possible susceptibility gene for autism spectrum disorder. Additional research is warranted on the precise relationship between MIF and the behavioral components of autism spectrum disorder, the mechanism by which MIF contributes to autism spectrum disorder pathogenesis, and the clinical use of MIF genotyping.
Key Words: autism spectrum disorder • ASD • MIF • neurodevelopmental disorders • genetic association • genetic polymorphisms • immunologic insult
Abbreviations: ASD—autism spectrum disorder • CNS—central nervous system • MIF—macrophage migration inhibitory factor • SNP—single-nucleotide polymorphism • ADI—Autism Diagnostic Interview • ADOS—Autism Diagnostic Observational Schedule
The etiopathogenesis of autism spectrum disorders (ASDs) is unknown. ASDs are considered among the most heritable neurodevelopmental disorders 1 and are observed in 34.0 to 62.6 per 10000 children2. There is also evidence for genetic transmission of milder autism-associated phenotypes and autism components.3 Although multiple genomewide scans have been conducted, results generally have been inconsistent. Chromosomal regions 7q and 10p are supported by meta-analytic4 and high-resolution scanning studies, respectively,5 but other regions, including 22q,6,7 may confer susceptibility to ASD. Multiple candidate genes, including those controlling brain growth,8 glutamatergic and y-aminobutyric acid-ergic synaptogenesis,5 and immune function,9 have also been proposed to play a role. In appreciation of this mosaic of findings, the consensus hypothesis is that the etiology of ASD is predominantly oligogenic and likely includes gene-gene and gene-environment interactions.
Individuals with ASD can exhibit additional disorders, including seizures, gastrointestinal and neurologic symptoms, and immunologic deficiencies. The presence of immune abnormalities in patients with ASD has long been noted.10 The relevant literature can be traced back some 3 decades to a report of a high frequency of autoimmune diseases in a family with a proband with ASD.11 This report triggered family studies of the co-occurrence of ASD and autoimmune diseases and confirmation of the observation of elevated counts of autoimmune diseases when compared with control families.12,13 In addition, indicators of chronic neuroinflammation have been reported in the brain,14–17 blood, and urine18–21 of probands with ASD. The literature further describes abnormal cellular immune responses,22–26 a possible cell-mediated immune response to brain tissue in autism,27 and other autoimmune abnormalities in probands with ASD.28,29 Also of interest are a variety of hypotheses linking the well-established hyperserotoninemia and immune abnormalities in ASD.30 Finally, it is important to note that there have been a number of genetic studies investigating allelic association and linkage among genes or in the region of the major histocompatibility complex and ASD; however, results of these studies are mixed, with some pointing to the presence of the association31,32 and others excluding the linkage.33 Some studies suggest that innate rather than adaptive neuroimmune responses are associated with ASD. Thus, the literature on the presence of immune problems in probands with ASD and their families contains a critical mass of information for generating a hypothesis regarding the involvement of autoimmune genes in the etiopathogenesis of ASD. At present, views of possible immune dysfunction in ASD range from conclusions that it may contribute to manifestations of the disorder in some patients18 to hypotheses that neuroimmunopathogenic responses play a fundamental role in ASD.34 Studies suggest that innate rather than adaptive neuroimmune responses are associated with ASD.35
Given a complex model of the inheritance of ASD, 1 possible etiopathic mechanism might involve an immunologic insult to the central nervous system (CNS) in individuals with a susceptible genetic background. We evaluated the genetic association between the innate mediator, macrophage migration inhibitory factor (MIF),36 and different behavioral components of ASD. MIF is encoded in a functionally polymorphic locus on chromosome 22q11.2 (Online Mendelian Inheritance in Man No. 153620, GenBank accession No. NM_002415) that has been associated with the incidence or severity of different autoimmune inflammatory conditions.37 Given its location in a previously identified locus of interest and its upstream action in immunity, MIF may represent a candidate gene for ASD or its components. Thus, the central hypothesis underlying this research was that a genetic predisposition to a particular level of MIF production may lead to a proinflammatory profile of cell activation that, if present during a neurodevelopmentally sensitive period, might contribute to the etiopathogenesis of autism.
The MIF gene (see Fig 1) spans <1 kilobase and is highly conserved. Several functional MIF alleles exist in the general population and differ in the structure of their promoter region. A CATT repeat (–794 CATT5–8) influences basal and stimulus-induced transcriptional activity such that transcription increases in an almost proportional fashion with a repeat number.38 The CATT5 MIF allele is typically referred to as a "low-expression" allele, and the CATT6, CATT7, and (rare) CATT8 MIF alleles are considered "higher-expression" alleles. A single-nucleotide polymorphism (SNP) (–173 G/C) is located within the same haplotype block as the CATT site and may exert a regulatory function by means of linkage disequilibrium or functional interaction with the repeat.39
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METHODS |
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Patients
Two sets of families, 1 recruited through the Yale University Child Study Center in the United States and the other through the University Center for Child and Adolescent Psychiatry, Accare/University Medical Center Groningen in the Netherlands, contributed to this work. Clinical characterization of these families has been described previously.40 All of the research was approved by corresponding institutional review boards, and appropriate consent forms were obtained.
The US samples included 527 individuals from 152 families ascertained through a proband with ASD assessed at the clinics of the Yale University Child Study Center.40 The Dutch sample included 532 participants from 183 families who approached the Accare Center for evaluation purposes.41 For more details on the samples, see Table 1. In the analyses presented here, only families of probands with autism and Asperger syndrome were included.
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Probands and their siblings were evaluated with several clinical instruments used for ASD diagnosis (Autism Diagnostic Interview [ADI], multiple versions,42 and Autism Diagnostic Observational Schedule [ADOS], multiple modules 43). In addition, all of the patients received clinical diagnoses (see Table 1).
Genotyping
Standard methods were used to extract DNA from blood collected in EDTA or from buccal mucosa cells. Analysis of the collected samples for the CATT MIF polymorphism was performed as described previously,38 and the fluor-labeled amplicons were resolved using an ABI 3100 Genetic Analyzer (ABI, Foster City, CA). DNA from previously genotyped homozygous individuals was used to generate control amplicons for size calibration for capillary electrophoresis. The –173 G/C alleles were determined by TaqMan SNP genotyping assays on the ABI Prism 7900HT and analyzed with SDS software (SDS, Foster City, CA). The probe was obtained from Applied Biosystems (Foster City, CA). The 2 samples were genotyped sequentially, with the US sample considered the initial discovery sample and the Dutch sample the replication sample.44 The genotyping was separated by 
8 months and was conducted on the same machinery with the same control DNAs.
Variable Description
As prescribed by corresponding manuals, using all of the designated items, the administration of the ADI resulted in 3 subscores (ADI social, ADI communication, and ADI stereotypical behaviors), and the administration of the ADOS resulted in 4 subscores (ADOS social, ADOS communication, ADOS stereotypical behaviors, and ADOS imaginative skills). For each of the 3 presumed latent traits (social, communication, and stereotypical facets of ASD), we formed combinations of measured scores capturing that latent trait and analyzed the resulting vectors of measured scores with multivariate association models (phenotypes 1–3; Table 4). Before conducting genetic association tests, we regressed each trait on age and gender and transformed the phenotypes using rank transformation; we used these residuals as phenotypes in input data files for the association analyses. In addition, we regressed each of these 3 phenotypes on 2 other domain phenotypes and used the residuals as the phenotype in input data (phenotypes 4–6; Table 4); all 3 were already regressed on age and gender. Such residualization permitted us to focus on specific variance associated with a particular facet of ASD, when variance attributable to other facets was regressed out.
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Association Analyses
We used the Family-Based Association Tests45 software for univariate and haplotype tests. We also used the Tools for Family-Based Association Studies (eg, Pedigree-Based Association Testing)46 software, specifically the R library pbatR, for multivariate tests of the null hypothesis of "no linkage and no association."
Three rounds of analyses were performed. First, we executed an exploratory set of analyses on the US data set with the 6 phenotypes described earlier. Because these analyses involved multiple comparisons, they were followed by a simulation study that generated new threshold empirical P values for interpretation of the nominal P values (see Table 4). We then analyzed the Dutch data as a confirmatory sample; correspondingly, we did not use adjustments for multiple comparisons. Finally, we completed a summative analysis of both samples, using a method initially proposed by Fisher47 and currently being advocated48 for combining results from multiple samples to establish gene-based associations.
Adjustments for Multiple Comparisons
The tests that we performed for several traits for each of several alleles in our discovery (US) sample led to multiple P values. To adjust for multiple comparisons and account for dependence among traits, we conducted a Monte Carlo simulation study designed to assess our results relative to the smallest P values that would arise by chance, assuming the truth of the null hypothesis, with our particular suite of statistical tests and with our particular trait and parental genotype data. We simulated 1000 synthetic data sets according to the null hypothesis of no linkage and no association, conditional on the minimal sufficient statistics identified by Rabinowitz and Laird.49 To create each of the data sets, we simulated new random genotypes for the participants from the appropriate conditional distributions49 while fixing the trait measurements and parental genotypes at the values observed in our data. For each synthetic data set, we then conducted the same statistical tests applied to our original data set, creating a new table of P values. For each of the resulting 1000 tables, we recorded the minimum P value, giving an empirical distribution of the minimum P value. The 5% quantile of that minimum P value distribution was .0071. Thus, the procedure of rejecting each of the null hypotheses for which the P value in Table 4 (US portion) was <.0071 has an overall significance level of .05, taking into account multiple testing.
Plasma MIF Analysis
Circulating MIF was measured by sandwich enzyme-linked immunosorbent assay using specific antibodies and native sequence human MIF that was prepared by Mizue et al50 as a standard.
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RESULTS |
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The allele and genotype frequencies in each sample are shown in Tables 2 and 3. For both the US and Dutch samples, the numbers of informative families for the CATT8 allele were too small (minimum number was set to 20); correspondingly, this allele was not tested for association. We tested alleles CATT5, CATT6, and CATT7. The results of the association analyses are shown in Table 4. Also of note is the degree of linkage disequilibrium between the –794 CATT polymorphism and the –173 SNP, which was repeatedly high in both samples (D' = .57 and .72 in the US and Dutch samples, respectively).
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US Sample
Our findings indicated the presence of a genetic association between the –794 CATT site and ASD. The strongest associations were between the –794 CATT6 MIF alleles and the stereotypical components of ASD, residualized (phenotype 6, P = .00009) and nonresidualized (phenotype 3, P = .00259). We also performed univariate Pedigree-Based Association Testing for each trait, which provided confirmatory information for the multivariate findings. Specifically, the CATT6 allele showed P values of <.05 for both ADOS stereotypical behaviors scores (P = .00059 and.00022, before and after residualization, respectively).
Dutch Sample
The Dutch sample was treated as a confirmatory sample analysis; a number of multivariate phenotypes provided support to the genetic association with MIF. Specifically, consistent with the results of the US sample, the stereotypical components of ASD, residualized (phenotype 6), gave a P value of .02973 with CATT6. In this sample, the –173 SNP also generated statistically significant or borderline P values for nonresidualized multivariate phenotypes of social impairment (phenotype 1, P = .05278), communication impairment (phenotype 2, P = .03700), and stereotypical behaviors (phenotype 3, P = .05638). The genetic associations with MIF were further supported in the Dutch sample by univariate analyses. Specifically, the –173 SNP polymorphism seemed to be associated with all of the ADI and ADOS unresidualized phenotypes (ADI: P values of .01698, .02208, and .017103; ADOS: .025062, .011041, and .024524, for social impairment, communication impairment, and stereotypical behaviors, respectively).
To summarize the patterns of results across the 2 samples, we applied Fisher's product criterion,47,51 which allows for combining different P values obtained for different alleles across the 2 samples in a meta-analytic fashion. Specifically, we combined P values for the 2 multivariate phenotypes (stereotypical behaviors and stereotypical behaviors, residualized) that survived the correction for multiple comparisons in the US sample and for the 2 univariate phenotypes (ADI and ADOS stereotyped behaviors) that contributed to these 2 multivariate phenotypes. The corresponding US-Dutch combined Fisher P values were .01649 and .00047 for multivariate phenotypes. For univariate phenotypes, the ADOS-based indicators gave statistically significant P values (P = .00217 and P = .01749, for stereotypical behaviors and stereotypical behaviors, residualized).
Plasma Analyses
We also measured levels of plasma MIF protein50 in 10 probands52 and their unaffected siblings in an independent Dutch sample from whom DNA was unavailable for study. A significantly higher level of circulating MIF in the ASD-affected group (ASD: 13.12 + 9.18 ng/mL; unaffected siblings: 6.87 + 2.75 ng/mL [mean + SD]; P = .0323; Fig 2), provided independent corroboration of the genetic association findings.
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Moreover, when the plasma MIF protein in 29 probands (10 from the previous sibling comparison and 19 assayed additionally1; the level of circulating MIF = 8.31 + 7.25 ng/mL) was correlated with behavioral indicators, statistically significant positive correlations were obtained between plasma MIF levels and ADOS scores on social impairment, imaginative skills, and total score (r = 0.41, 0.41, and 0.39, respectively; P < .05 for all). The correlation with the ADOS stereotypical behavior score did not reach statistical significance (r = 0.15; P > .10) but trended in the same direction.
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DISCUSSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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Collectively, these data identify MIF as a potential ASD susceptibility gene and support earlier suggestions of a role for innate immunity in the etiopathogenesis of this disease. The strongest results associated the CATT6 with a particular facet of ASD, stereotypical behaviors, as captured by a multivariate trait; this association was registered in both the discovery (US) and the confirmation (Dutch) samples. Additional, although less consistent, associations were registered for CATT5 of the –794 CATT polymorphism in the US sample and for the –173 SNP C/G alleles (different by sign) in the Dutch sample. Similarly, univariate analyses provided reassuring support to the presence of the association between ASD and the 2 MIF polymorphisms, although the associations were not highly concerted. These inconsistencies can be explained by many factors, among which are imprecise phenotyping, still small (although comparable to or larger than other studies in the field) sample size, and possible genetic and disorder-related heterogeneity. However, although the patterns of results might be diverse for different phenotypes and for different alleles within the MIF genes, summative Fisher P values unequivocally indicate the presence of such association between ASD and MIF in the 2 samples investigated in this study when these samples are combined. This finding awaits further confirmation in other, hopefully more powerful and more homogeneous, samples, where probands are well characterized with componential and holistic ASD-related phenotypes. Similarly, only serum, but no DNA, was available for these additional participants.
Overall, the polymorphisms and plasma results provide suggestive evidence for neuroglial and innate immune activation in brain tissue and cerebrospinal fluid17 and increased expression of proinflammatory cytokines in the CNS or blood of patients with ASD.53 Persistent elevation of cytokines in the CNS may reflect an ongoing inflammatory process, microglial activation, or developmental arrest, because some cytokine levels increase during phases of neurodevelopment.35 Because MIF regulates the expression of innate cytokines,36 we hypothesize that a genetic predisposition at the MIF locus may lead to an inappropriate level of MIF production during a neurodevelopmentally sensitive period, contributing to the pathogenesis of ASD. Our data add to the evidence that some innate immunity genes may play an important role in the development of ASD.9
Although numerous studies have linked high-expression MIF alleles with autoimmune diseases,36,38,50,54 a specific role for MIF in CNS disorders has not been described previously, and it may be relevant that MIF is widely expressed in the brain in neurons, astroglia, and ependymal cells.55,56 In vitro studies have shown that the intracellular content of MIF increases during neuronal firing and then acts to reduce the chronotropic effects of further stimulation.57 Thus, the role of the known variant MIF alleles in ASD may involve neuronal functions that extend beyond the well-described immunologic actions of the protein.36 Pharmacologic inhibitors of MIF are presently in preclinical development,58,59 and therapies aimed specifically at MIF pathways in patients with ASD might be feasible, especially if high circulating levels of the protein are indicative of an ongoing disease process.
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CONCLUSIONS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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We present evidence for an association between the MIF locus and ASD, specifically with the stereotypical components of ASD. The association with stereotypical behavior is of interest but should not be overintepreted before replication. Yet, because ASDs are heterogeneous in presentation and etiology, it is possible that different genes underlie the manifestation of different facets of ASD. Given that distinctive diagnostic components of ASD show differential heritability estimates and patterns of familial transmission and, thus, may be fractionable,3,60 these components may be associated with different etiopathogeneses. In the overwhelming majority of (if not all) studies of immunologic abnormalities in ASD, phenotyping was restricted to clinical diagnoses (affected versus unaffected) based on Diagnostic and Statistical Manual of Mental Disorders criteria. Some inconsistencies in the immunologic research results on ASD may be because of cross-study differences in phenotyping and failure to study specific phenotypes of ASD. If our findings, in which immunologic abnormalities are mostly associated with particular facets of ASD, are replicated, this inconsistency may be explained. Similarly, in further investigations of the association between MIF and ASD, the importance of other factors, such as early health and treatment history, might become important. More generally, evidence of higher rates of autoimmunity (rheumatoid arthritis, lupus, asthma, allergies, or thyroid disorders)35 in relatives of individuals with ASD suggests that additional immunologic response genes should also be tested for involvement in ASD.
These initial findings will require additional study in other samples of probands with ASD to determine their replicability. In addition, an examination of samples of probands with other developmental disorders can provide an assessment of the specificity of the association between the MIF genotype and ASD. These results also prompt a reconsideration of previous observations and stimulate the investigation of new hypotheses regarding relationships between early immune function and ASD and possibly other developmental neuropsychiatric disorders. Determination of the MIF genotype or protein levels may assist in better defining ASD phenotypes, thereby improving the prognosis of behavioral abnormalities and potentially enabling new pharmacologic interventions.
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ACKNOWLEDGMENTS |
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These studies were supported by grants from the Cure Autism Now Foundation (to Dr Grigorenko), National Institutes of Health grants NICHD-HD03008 and NICHD-HP35482 (to Drs Volkmar, Grigorenko, and Anderson) and AI042310 and AR049610 (to Dr Bucala), and the Korczak Foundation for Autism Research (to Drs Anderson, Mulder, de Bildt, and Minderaa).
We express our gratitude to Prof David Ward for encouraging our interest in this area, to Luke Turechek for help with genotyping, and to Robyn Rissman for editorial assistance. We are also indebted to the study participants and their families.
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FOOTNOTES |
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Accepted Mar 27, 2008.
Address correspondence to Elena L. Grigorenko, PhD, Yale University, 230 S Frontage Rd, New Haven, CT 06519. E-mail: elena.grigorenko{at}yale.edu
Financial Disclosure: Dr Bucala is a coinventor on a patent describing the therapeutic benefit of MIF inhibition in inflammatory disease.
Ms Han and Ms Yrigollen contributed equally to this work.
| What's Known on This Subject ASDs are clinically complex and characterized by many etiologic pathways involving multiple genetic and environmental risk factors. Although a number of such risk factors have been proposed, no single factor has sustained the scrutiny of replication in multiple diverse samples.
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| What This Study Adds The study contributes data, generated from 2 independent samples of families of probands with ASD, that suggest for the first time a role for the innate cytokine, MIF, in the etiology of ASD.
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