Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

The oxytocin receptor gene (OXTR) is associated with autism spectrum disorder: a meta-analysis

Abstract

The oxytocin receptor gene (OXTR) has been studied as a risk factor for autism spectrum disorder (ASD) owing to converging evidence from multiple levels of analysis that oxytocin (OXT) has an important role in the regulation of affiliative behavior and social bonding in both nonhuman mammals and humans. Inconsistency in the effect sizes of the OXTR variants included in association studies render it unclear whether OXTR is truly associated with ASD, and, if so, which OXTR single-nucleotide polymorphisms (SNPs) are associated. Thus, a meta-analytic review of extant studies is needed to determine whether OXTR shows association with ASD, and to elucidate which specific SNPs have a significant effect on ASD. The current meta-analysis of 16 OXTR SNPs included 3941 individuals with ASD from 11 independent samples, although analyses of each individual SNP included a subset of this total. We found significant associations between ASD and the SNPs rs7632287, rs237887, rs2268491 and rs2254298. OXTR was also significantly associated with ASD in a gene-based test. The current meta-analysis is the largest and most comprehensive investigation of the association of OXTR with ASD and the findings suggest directions for future studies of the etiology of ASD.

Introduction

Autism spectrum disorder (ASD) refers to a group of neurodevelopmental disorders characterized by developmental delays, impaired functioning in social and communicative skills and the presence of restricted, repetitive behavior.1 Researchers have estimated the heritability of ASD at 55–80%,2,3 indicating that genetic influences are responsible for most of its etiology. Neuropeptide genes have been investigated in relation to ASD owing to evidence that oxytocin (OXT) and arginine vasopressin have an important role in the regulation of affiliative behavior and social bonding in both nonhuman mammals and humans4,5 and are differentially expressed in the blood of autistic individuals in comparison with non-autistic individuals.6,7 The oxytocin receptor gene (OXTR) is the neuropeptide gene most frequently studied for association with ASD. This gene contains many single-nucleotide polymorphisms (SNPs), and each association study of OXTR and ASD has analyzed a different set of these variants, leading to considerable heterogeneity in the literature. Further, inconsistency in the effect sizes of the OXTR variants renders it unclear whether OXTR is truly associated with ASD, and, if so, which OXTR SNPs are associated. Thus, we conducted a meta-analytic review of the current literature to determine whether OXTR and its constituent SNPs are associated with ASD.

Genetics of ASD

Although there has been considerable research devoted to finding specific genes that underlie ASD, most of its heritability remains unexplained.8 ASD is likely a highly polygenic condition, with no one gene expected to explain a substantial proportion of its variance.8 Further, variants associated with ASD are often rare or even de novo mutations (spontaneous mutations that neither parent possessed or transmitted), making the reliable identification of associated genes difficult, especially without large sample sizes.8 Nevertheless, several genes and genomic regions have shown relatively consistent association with ASD.

Geneticists have used several methodologies in an attempt to uncover the sources of heritability in ASD. Genome-wide linkage studies have identified dozens of genomic regions likely to harbor autism risk genes.9 Several genome-wide association studies (GWAS) of ASD also have been conducted,10, 11, 12 although replicated results have yet to emerge.8,13 An area of recent growth is the exploration of copy-number variants in individuals with ASD. Recent studies have shown that large, rare copy-number variants occur more frequently in ASD individuals than in controls14 and that 5–11% of ASD individuals have at least one rare or de novo copy-number variant,14 most of which were unique to each individual.14,15 Beyond copy-number variants, recent exome sequencing studies16, 17, 18 found that de novo point mutations (single-base substitutions) were more frequent in individuals with ASD, particularly in genes involved in cell structure and protein binding in the brain.8 Although these genome-wide, ‘hypothesis-free’ approaches have begun to yield results, many researchers also study specific genes based on their hypothesized role in the etiology of ASD.

Genes in several biological pathways have been examined for association with ASD, with a particular focus on pathways involved in neuronal and cortical functioning. For example, studies have found that ASD is significantly associated with the genes for hepatocyte growth factor and its receptor, MET,9,19 the gene that codes for the protein Reelin,20 and genes in serotonergic, GABAergic and glutamatergic pathways.21 Researchers have also investigated biological factors thought to be particularly involved in social and communicative functioning, such as OXT.

Oxytocin and social behavior

OXT is a peptide constituted by oligopepetide chains of nine amino acids.22 The gene that codes for the OXT receptor, OXTR, spans 19.2 kilobases on chromosome 3 and is expressed in humans throughout the body in reproductive structures22 as well as in neural regions, such as the frontal cortex, amygdala, hypothalamus and olfactory nucleus.5,23

Nonhuman mammal research has established a role for OXT in social behavior. OXT receptors are expressed in neural regions related to social behavior, pair-bonding, social memory and social aggression in nonhuman mammals.24 In particular, OXT neurons in the hypothalamus project to the nucleus accumbens and posterior pituitary in prairie voles.25 Researchers have found that OXT seems to promote approach behavior by inhibiting instinctual avoidance of closeness and defensive behavior.5,26 Disrupting oxytocin receptor functioning also seems to disrupt social behavior. For example, OXTR knockout mice have impaired social memory and recognition,27 impaired mother-offspring interaction28 and increased aggression.28 This evidence suggests that OXT has a causal role in the development and maintenance of social functioning in rodent species. These findings have prompted researchers to investigate the role that OXT and OXTR have in human social behavior.

OXT in humans has been shown to impact the processing of social stimuli. For example, intranasal OXT administration has been shown to increase calmness and decrease anxiety in response to a social stressor,29 increase ability to infer affective states from viewing the eye regions of emotional faces30 and increase social referencing to eye regions.31 Further, OXT in humans increases affiliative behavior and trust in social situations.32 It is worth noting that commonly used methods for measuring peripheral oxytocin can be unreliable, and it is not known how much OXT reaches the brain after intranasal administration,33 thus these results should be interpreted with caution. Nonetheless, findings in the human literature suggest that OXT has a complex but facilitative effect on social behavior, paralleling findings in the animal literature. These results have led researchers to investigate whether genetic variation in the human OXTR gene is associated with social functioning.

OXTR contains several dozen SNPs22 that have been genotyped in association studies of various traits and behaviors in humans. Researchers have found that various OXTR SNPs are associated with generous behavior,34 prosociality ratings,35 empathy and social communication,36 amygdala and hypothalamus functioning,36 reduced physiological reactivity to stress,37 increased benefits from social support38 and greater parenting sensitivity,39 among other social and biological traits. Taken together, these results suggest associations between OXTR and various aspects of human social behavior, although the mechanisms underlying OXTR’s influence and the contributions of particular OXTR SNPs is unclear.

Oxytocin in ASD

Recent research on the relation between OXT and ASD has produced promising, if preliminary, results. Young children with ASD have reduced OXT plasma levels6,40 and increased unprocessed OXT peptides,40 suggesting that low levels of OXT are associated with ASD. Intranasal or intravenous administrations of OXT in individuals with ASD have been shown to increase performance on an emotion recognition task,41 recognition of social cooperation, trust, and preference42 and the time gazing at eyes while viewing pictures of faces.42 Further, one study found that an OXTR SNP (rs237887) explains 10% of the variance in face-recognition memory in families with an autistic child.43 These results suggest that OXT may both have a role in the etiology of ASD and also be a treatment target.

Given the aforementioned results, as well as findings of a genetic linkage peak directly over the OXTR gene,44 researchers have investigated whether variation in OXTR is associated with ASD. At the time of this study, there have been 10 genetic association studies of OXTR SNPs with ASD,23,45, 46, 47, 48, 49, 50, 51, 52, 53 comprising 13 independent samples, 11 of which used family-based designs. Family-based designs examine the over-transmission of a putative high-risk allele at an SNP from heterozygous parents to their affected offspring, under the assumption that if an allele is transmitted more often than expected by chance (i.e., 50%) then it is associated with the disorder. Each of these studies tested a different set of OXTR SNPs, and no SNP has been found to be significantly associated with ASD in every study in which it has been examined, rendering a qualitative synthesis of this literature difficult. Also, no studies to date have performed a gene-based test to evaluate the association between OXTR and ASD. Gene-based tests combine significance levels across multiple SNPs and the linkage disequilibrium among them, thus reducing type I error and increasing statistical power.54 Owing to the considerable heterogeneity across studies in the SNPs tested and their evidence for association, a meta-analysis is needed to determine whether OXTR as a whole and specific OXTR SNPs are associated with ASD.

The present meta-analysis

The primary aims of the current meta-analysis are to evaluate the main effects of OXTR and variants therein on ASD, and to test for heterogeneity in the effects of these variants across studies. Unfortunately, too few studies currently exist to reliably explore variables that may explain between-study heterogeneity. Nonetheless, characterizing the magnitude of heterogeneity will facilitate the future examination of study-level moderators as samples increase. We also use the extant data to perform a gene-based test of association between OXTR and ASD.

Methods

Literature search and selection strategy

A systematic literature search was conducted to collect studies relevant for the current meta-analysis. First, we searched three online databases (PubMed, PsycInfo and Google Scholar) for articles published in English on associations between variants in OXTR and ASD. Search terms used to identify studies were a combination of terms identifying the gene (‘OXTR’, ‘OXTR gene’ and ‘oxytocin receptor gene’) and terms identifying the phenotype of interest (‘autism’, ‘ASD’ and ‘Asperger’ ‘pervasive developmental disorder’).

After identifying a set of publications returned from each search, we collated the results and eliminated duplicates. We then reviewed the titles, abstracts, keywords and texts of all studies to exclude studies that were clearly irrelevant. We searched the literature review and reference sections of the publications to find additional publications that were missed in the original search. Finally, we applied criteria to the set of studies to determine their inclusion or exclusion in the present meta-analysis.

Inclusion and exclusion criteria

The following criteria were applied to select studies for inclusion in the meta-analyses: (1) the study must have examined the association between at least one variant in OXTR and autism disorder, Asperger’s syndrome, pervasive developmental disorder not otherwise specified or ASD broadly using either a case-control or family-based association design; (2) the study must have reported data from at least one independent sample; (3) the study must have included ASD diagnoses made by either psychiatric assessment or using standard diagnostic instruments. Diagnostic instruments used in studies included in the meta-analysis included the Autism Diagnostic Interview-Revised,55 the Autism Diagnosis Observation Schedule-Generic,56 the Child Autism Rating Scale57 and the Developmental, Dimensional, and Diagnostic Interview.58 The Autism Diagnostic Interview-Revised is a semi-structured interview for caregivers of children and adults focused on the three ASD symptom clusters. The Autism Diagnosis Observation Schedule-Generic is a semi-structured observational measure that assesses communication, social interaction and play in children. The Child Autism Rating Scale is a behavior rating scale that can be completed by clinicians, teachers or parents. The Developmental, Dimensional, and Diagnostic Interview is a computerized procedure administered by trained interviewers to parents that measures autistic features dimensionally.

The following criteria were applied to exclude studies from the meta-analyses: (1) the study did not use either case-control or family-based association designs; and (2) the sample did not contain individuals with ASD diagnoses (e.g., the study measured autism-related traits in exclusively non-disordered populations). We identified a total of 10 eligible studies with 13 independent samples.23,44, 45, 46, 47, 48, 49, 50, 51, 52 One study was excluded because its sample contained solely non-disordered individuals,52 leaving a total of 9 studies with 12 independent samples that were eligible for data extraction.

Data extraction

The following data were extracted from each article when possible: first author, year of publication, study design, country, predominant ethnicity of participants, mean age, proportion of males, risk and non-risk allele count or allele frequencies in cases and controls (for case-control studies) or transmitted and non-transmitted risk allele counts from heterozygous parents to probands (for family-based studies), effect sizes and diagnostic criteria used. The data were double-extracted independently and the results were cross-checked for discrepancies. Several discrepancies in the study-level data were found and corrected. No discrepancies were found in the SNP-level data. Given the large number of markers tested in many of the studies, several publications omitted the requisite information for inclusion of a particular SNP in a meta-analysis. In these cases, authors were contacted via email and asked to provide the missing data. After this process, we were able to include 8 studies with 11 independent samples23,44, 45,47, 48, 49, 50, 51 in the meta-analysis. One study contained two independent samples48 and another contained three independent samples,23 all of which were included and treated as independent.

Meta-analytic methods

OXTR SNPs were selected for the meta-analysis if they were tested for association with ASD in at least four independent samples. Separate meta-analyses for each SNP then were performed using the meta-analysis software program, Metasoft (http://genetics.cs.ucla.edu/meta).59 Metasoft allows users to input effect sizes and standard errors, conducts fixed- and random-effects meta-analyses and outputs pooled fixed-effects and random-effects effect sizes and corresponding tests of significance and heterogeneity (i.e., the Q-statistic and I2 index). Metasoft also outputs P-values from Han & Eskin’s58 alternative random-effects model that is optimized to detect associations under heterogeneity by assuming no heterogeneity under the null hypothesis. This model has greater power than traditional random-effects models and even fixed-effects models when heterogeneity is substantial.59 We chose to report both traditional and alternative random-effect P-values for all analyses. Fixed-effects and random-effect P-values were identical when no heterogeneity was present.

Gene-based tests of association

Gene-based tests of association between ASD and OXTR as a whole were conducted separately by ethnicity (i.e., Asian- and European-background samples) to account for differing linkage disequilibrium (LD) patterns by ethnicity using both traditional and alternative random-effect model P-values. Gene-based tests were conducted using KGG (http://statgenpro.psychiatry.hku.hk/limx/kgg/),60 a software package that combines SNP-based P-values with estimates of linkage disequilibrium among SNPs within the gene to provide a gene-based P-value. Gene-based tests were conducted using the hybrid set-based test method,61 a combination of a scaled χ2-test and an extended Simes test that integrates SNP association P-values and LD among the SNPs within a gene to obtain an overall P-value for the entire gene. The Asian- and European-background samples were tested separately using the HapMap22 linkage disequilibrium information appropriate for each ethnicity. The results were then combined across ethnicity using MetaP,62 a program that performs meta-analysis by combining P-values from independent samples. We reported Stouffer’s z P-values, which take sample size into account.

Tests of publication bias and excess significance

We performed Egger’s test for publication bias63 and Ioannidis’s test for excess significance64 for the SNPs with significant pooled odds ratios. Specifically, Egger’s test for publication bias tests the significance of the intercept in a linear regression of each study’s standardized odd ratio on the inverse of the s.e. of each study’s odds ratio with an alpha level of α=0.10.63 Ioannidis’s test for excess significance is to calculate the expected number of significant findings in each set of studies by summing the power of each study and then to compare that value to the observed number of significant findings with a χ2-test.64

Results

Meta-analyses of OXTR and ASD

After applying inclusion and exclusion criteria (see Materials and Methods), data from 8 studies with 11 independent samples23,43, 44,46, 47, 48, 49, 50 were included in the meta-analysis for OXTR. Across these samples, 57 different SNPs were analyzed for association with OXTR, 16 of which were tested in 4 or more samples and thus included in our meta-analysis (see Table 1). Table 2 shows the pooled odds ratios, their 95% confidence intervals and P-values and heterogeneity tests and indices (Q-statistics, P-values and I2) for the pooled estimates for each OXTR SNP. Of the 16 SNPs meta-analyzed, significant pooled odds ratios were found for 4 SNPs: rs7632287 (‘A’ allele is risk-inducing), rs237887 (‘A’ allele is risk-inducing), rs2268491 (‘T’ allele is risk-inducing) and rs2254298 (‘A’ allele is risk-inducing).

Table 1 Characteristics of studies investigating associations between OXTR and autism spectrum disorder
Table 2 Meta-analytic results of SNPs in OXTR and autism spectrum disorder

For rs7632287, the OR was significant and large: OR=1.44 (95% CI: 1.23–1.68, P=0.000005) (see Figure 1a) and there was no significant between-study heterogeneity (Q-statistic: χ2=0.92, P=0.819, I2=0%). For rs237887, the OR was significant but small: OR=0.88 (95% CI: 0.79–0.98, P=0.024) (see Figure 1b) and there was no significant between-study heterogeneity (Q-statistic: χ2=2.07, P=0.839, I2=0%). For rs2268491, the OR was significant and moderate: OR=1.19 (95% CI: 1.05–1.36, P=0.0075) (see Figure 1c) and there was no significant between-study heterogeneity (Q-statistic: χ2=4.13, P=0.531, I2=0%). For rs2254298, the OR was significant under the alternative random-effect model: OR=1.15 (95% CI: 0.93–1.43, P=0.0038) (see Figure 1d), but nonsignificant under the traditional random-effects model (P=0.16). There also was substantial heterogeneity in the estimated effect sizes (Q-statistic: χ2=11.2, P=0.048, I2=55%).

Figure 1
figure1

Depicts forest plots of odds ratios from the analyses of SNPs found to have significant effects on ASD. (a) Forest plot of odds ratios from the fixed-effects model for rs7632287. (b) Forest plot of odds ratios from fixed-effects model for rs237887. (c) Forest plot of odds ratios from the fixed-effects model for rs2268491. (d) Forest plot of odds ratios from the random-effects model for rs2254298.

PowerPoint slide

We next conducted gene-based tests of association between OXTR and ASD separately in Asian- and European-background samples to account for different LD patterns by ethnicity. The gene-based test for the Asian samples was significant (traditional random effects P=0.019, alternative random effects P=0.016), whereas the gene-based test in the European-background samples was highly significant (traditional random effects P=0.000067, alternative random effects P=0.000045). Meta-analytic combination of the gene-based test results from the two ethnicities was also highly significant (traditional random effects P=0.0000077, alternative random effects P=0.0000053), suggesting that OXTR is associated with ASD.

Tests of publication bias and excess significance

We tested the sets of studies of the four SNPs with significant pooled ORs for excess significance64 and publication bias.63 There was no evidence of excess significance for rs7632287 (P=0.620), rs237887 (P=0.444), rs2268491 (P=0.927) or rs2254298 (P=0.386). There was no evidence of publication bias for rs7632287 (P=0.419), rs237887 (P=0.649) or rs2268491 (P=0.995), although rs2254298 showed evidence of significant but slight publication bias (P=0.077). The significance of this test is driven by the study by Jacob et al.46 which had an OR of 0.43, quite distant from the other estimates (see Figure 1). Removing this study rendered the test of publication bias nonsignificant (P=0.437), increased the estimated effect size (OR=1.26) (95% CI: 1.10–1.43, P=0.0006), and rendered the heterogeneity between studies nonsignificant (Q-statistic: χ2=4.17, P=0.3837, I2=4%). Removing this study also slightly increased the significance of the gene-based test in the European-background sample (P=0.000047) and the meta-analytically combined sample (P=0.0000047).

Discussion

We performed a meta-analysis of the association of ASD with 16 SNPs in OXTR using data from 3941 individuals with ASD from 11 independent samples (although analyses of each individual SNP only included a subset of this total). We found associations between ASD and rs7632287 (‘A’ allele is risk-inducing), rs237887 (‘A’ allele is risk-inducing), rs2268491 (‘T’ allele is risk-inducing) and rs2254298 (‘A’ allele is risk-inducing), as well as OXTR as a whole.

Interpretation of OXTR findings

The association of the ‘A’ allele of rs7632287 with ASD was found to be particularly strong, consistent with converging research that this marker may be involved in human social behavior.50,52 Given its location in the promoter region of OXTR, rs7632287 may be involved in transcription factor binding, although it has not been experimentally demonstrated that it alters gene expression.50 The ‘A’ allele was associated with lower pair-bonding and social skills scores across three normative samples,52 suggesting that rs7632287 has a role in normal and autism-related social behavior. Although the pooled OR for rs7632287 was relatively large (1.44), recent GWAS of ASD did not have sufficient power to detect effects of that size,16, 17, 18,65 which may explain why SNPs in OXTR have yet to emerge as significantly associated with ASD in GWAS. Given the present results, as GWAS increase in sample size SNPs in OXTR should begin to emerge as significantly associated with ASD.

The association of the ‘A’ allele of rs237887 with ASD also has some corroborating evidence in the literature. One study found that although this allele was not associated with ASD diagnosis, it was associated with communication and daily living skills in ASD individuals.46 Another study found that the ‘A’ allele of rs237887 was associated with lower altruism in two separate behavior tasks,34 suggesting that rs237887 may underlie various aspects of human social behavior. This allele was also associated with reduced face-recognition memory in families with an autistic child.43

Two SNPs, rs2268491 is and rs2254298,49 are in very high LD (r2>0.95) and were both significantly associated with ASD in the meta-analysis, suggesting that signals from these two SNPs may reflect a common association with ASD. Some corroborating evidence exist that the ‘T’ allele of rs2268491 and the ‘A’ allele of rs2254298 are involved in social behavior. Specifically, rs2268491 has been found to be associated with aspects of empathy (although the ‘T’ allele was associated with higher empathy),66 and the ‘A’ allele of rs2254298 has been found to be associated with attachment security (with effect direction dependent on sample ethnicity),67 less sensitive parenting and lower plasma OXT levels,68 suggesting that these SNPs may have a role in both normal and autism-related social behavior. There also was evidence of slight publication bias for rs2254298, as demonstrated by significant positive skew around the estimated effect size. The significance of this test was driven by the study by Jacob et al.,46 which had an effect size that was quite discrepant from the other estimates (see Figure 1). Removing this study rendered the test of publication bias nonsignificant, increased the estimated effect size (OR increased from 1.15 to 1.26) and rendered the heterogeneity between studies minimal and nonsignificant (I2 dropped from 55 to 4%). Notably, the removed study included exclusively Caucasian individuals, whereas the other studies of rs2254298 with positive effect sizes included exclusively Asian individuals, highlighting the importance of examining ethnic heterogeneity in effects in future association studies.

The gene-based test for OXTR suggested that the gene is highly associated with ASD overall (P=0.0000053) as well as in both Asian- (P=0.016) and European-background individuals (P=0.000045). Gene-based tests maximize the amount of genetic variation analyzed simultaneously and can provide substantially increased power to detect association, particularly in moderate sample sizes.53,54 The strength of this association suggests that although the effects of individual SNPs within OXTR may differ depending on sample size, ethnicity or other study-level factors, OXTR as a whole influences ASD.

Limitations

Several limitations should be taken into account when interpreting the results of this meta-analysis. Given that the SNP-based meta-analyses comprised only 4–8 studies, a conservative interpretation of these results is that they reflect the current state of the literature and can guide future research, rather than representing definitive estimates of the effect sizes attributable to each SNP. Further, for SNPs for which heterogeneity was detected, we had too few studies to reliably test moderators of that heterogeneity, such as ethnicity, sex or intelligence quotient.

A second set of limitations arises from differences in the SNPs included in each individual study. Although many of the studies that examined associations between ASD and OXTR included multiallelic or haplotype-based analyses, inconsistencies in the SNPs tested and results reported across studies rendered it impossible to meta-analytically evaluate any of these associations. Gene-based analyses encompassing multiple SNPs more comprehensively characterize variation across the genes and may thus better capture risk for ASD.

Future directions

Several important issues remain for future research on the OXTR’s role in ASD. First, little is known regarding the functionality of specific OXTR variants. Understanding which OXTR variants are functional and how they affect OXTR’s expression in the brain is crucial for understanding OXTR’s effects on social behavior and autism-related traits.

Second, there is evidence that OXTR influences social behavior in both normative and clinical samples. Future studies should examine whether OXTR’s effects differ for normal-range social behavior versus clinical extremes such as ASD. Such research should include continuous measures of social behavior and compare effect sizes of OXTR between non-disordered and ASD samples.

Third, studies included in the current meta-analyses did not consistently include analyses of associations of OXTR with components of ASD, or even differential associations with specific ASD diagnoses (i.e., autistic disorder, Asperger syndrome, or pervasive developmental disorder not otherwise specified). The studies that did include analyses of components of ASD found that associations with OXTR tended to replicate across these components.46,49 Namely, although OXTR was investigated owing to its hypothesized relation to social and communicative deficits, studies have found OXTR to be associated with stereotyped behaviors as well.46,49 Multivariate behavior genetic studies have compared the degree of genetic overlap between the three symptom clusters of ASD and have found that each has a unique genetic component in addition to the genetic influences that they share in common.69,70 Thus it is unclear whether OXTR is primarily related to the social and communicative aspects of ASD, or to ASD more generally. Researchers should rigorously test associations of OXTR with specific components of ASD as this might provide stronger and more replicable results if OXTR’s effects are more specific. Relatedly, we were unable to evaluate potential sources of heterogeneity such as ethnicity, sex, age or intelligence quotient, given that these moderators were not examined in any of the included studies. Researchers should more consistently test whether these moderators have a significant effect on the relation between OXTR and ASD.

Fourth, our results demonstrate that gene-based tests can evaluate association across a gene while taking into account population LD structure and thus facilitate interpretation of separate SNP-based tests. As genome-wide data become more widely available, researchers should consider using gene-based and pathway-based approaches to develop a more comprehensive framework of genetic risk for ASD.

Finally, much of the data from the current set of studies was unusable in the meta-analysis owing to heterogeneity in sets of SNPs analyzed. Determining a standard set of SNPs for future research is essential for maximizing comparability across studies. Such a set should include previously studied SNPs as well as a set of tagging SNPs that capture well the genetic variation across OXTR via high LD. In addition to researchers making available data necessary for inclusion in meta-analyses, comprehensive SNP selection will facilitate more systematic evaluations of the association of OXTR and ASD.

Conclusions

The current meta-analysis found significant main effects of rs7632287, rs237887, rs2268491 and rs2254298 in OXTR on ASD. In a gene-based test, OXTR was highly associated with ASD. Significant heterogeneity was found in the estimated effect sizes across studies for several SNPs in OXTR, suggesting that potential moderator variables, such as ethnicity, may cause the observed differences in effect sizes across studies. Thus, although the current results suggest that OXTR has a role in ASD, further investigation of this putative association is warranted. Future researchers should attempt to include as many previously studied variants as possible and comprehensively ‘tag’ OXTR to maximize the comparability across studies and make available data necessary for inclusion in meta-analyses. The current meta-analysis is the largest and most comprehensive investigation of the association of OXTR with ASD, and the findings should help guide further investigations of the etiology of ASD.

References

  1. 1

    Volkmar FR, Lord C, Bailey A, Schultz RT, Klin A . Autism and pervasive developmental disorders. J Child Psychol Psychiatry 2004; 45: 135–170.

    Article  Google Scholar 

  2. 2

    Freitag CM, Staal W, Klauck SM, Duketis E, Waltes R . Genetics of autistic disorders: review and clinical implications. Eur Child Adolesc Psychiatry 2010; 19: 169–178.

    Article  Google Scholar 

  3. 3

    Lichtenstein P, Carlström E, Råstam M, Gillberg C, Anckarsäter H . The genetics of autism spectrum disorders and related neuropsychiatric disorders in childhood. Am J Psychiatry 2010; 167: 1357–1363.

    Article  Google Scholar 

  4. 4

    Lim MM, Young LJ . Neuropeptidergic regulation of affiliative behavior and social bonding in animals. Horm Behav 2006; 50: 506–517.

    CAS  Article  Google Scholar 

  5. 5

    Heinrichs M, Domes G . Neuropeptides and social behaviour: effects of oxytocin and vasopressin in humans. Prog Brain Res 2008; 170: 337–350.

    CAS  Article  Google Scholar 

  6. 6

    Modahl C, Green L, Fein D, Morris M, Waterhouse L, Feinstein C et al. Plasma oxytocin levels in autistic children. Bio Psychiatry 1998; 43: 270–277.

    CAS  Article  Google Scholar 

  7. 7

    Boso M, Emanuele E, Politi P, Pace A, Arra M, Ucelli di Nemi S et al. Reduced plasma apelin levels in patients with autistic spectrum disorder. Arch Med Res 2007; 38: 70–74.

    CAS  Article  Google Scholar 

  8. 8

    Yates D . Neurogenetics: unravelling the genetics of autism. Nat Rev Neurosci 2012; 13: 359.

    CAS  Article  Google Scholar 

  9. 9

    Yang M, Gill M . A review of gene linkage, association and expression studies in autism and an assessment of convergent evidence. Int J Dev Neurosci 2007; 25: 69–85.

    CAS  Article  Google Scholar 

  10. 10

    Lauritsen MB, Als TD, Dahl HA, Flint TJ, Wang AG, Vang M et al. A genome-wide search for alleles and haplotypes associated with autism and related pervasive developmental disorders on the Faroe Islands. Mol Psychiatry 2006; 11: 37–46.

    CAS  Article  Google Scholar 

  11. 11

    Ma D, Salyakina D, Jaworski JM, Konidari I, Whitehead PL, Andersen AN et al. A genome-wide association study of autism reveals a common novel risk locus at 5p14.1. Ann Hum Genet 2009; 73: 263–273.

    CAS  Article  Google Scholar 

  12. 12

    Hussman JP, Chung RH, Griswold AJ, Jaworski JM, Salyakina D, Ma D et al. A noise-reduction GWAS analysis implicates altered regulation of neurite outgrowth and guidance in autism. Mol Autism 2011; 2: 1.

    Article  Google Scholar 

  13. 13

    Schaaf CP, Zoghbi HY . Solving the autism puzzle a few pieces at a time. Neuron 2011; 70: 806–808.

    CAS  Article  Google Scholar 

  14. 14

    Sebat J, Lakshmi B, Malhotra D, Troge J . Strong association of de novo copy number mutations with autism. Science 2007; 316: 445–449.

    CAS  Article  Google Scholar 

  15. 15

    Levy D, Ronemus M, Yamrom B, Lee YH, Leotta A, Kendall J et al. Rare de novo and transmitted copy-number variation in autistic spectrum disorders. Neuron 2011; 70: 886–897.

    CAS  Article  Google Scholar 

  16. 16

    O’Roak BJ, Vives L, Girirajan S, Karakoc E, Krumm N, Coe BP et al. Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations. Nature 2012; 485: 246–250.

    Article  Google Scholar 

  17. 17

    Sanders SJ, Murtha MT, Gupta AR, Murdoch JD, Raubeson MJ, Willsey AJ et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature 2012; 485: 237–241.

    CAS  Article  Google Scholar 

  18. 18

    Neale BM, Kou Y, Liu L, Ma'ayan A, Samocha KE, Sabo A et al. Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature 2012; 485: 242–245.

    CAS  Article  Google Scholar 

  19. 19

    Campbell DB, D'Oronzio R, Garbett K, Ebert PJ, Mirnics K, Levitt P et al. Disruption of cerebral cortex MET signaling in autism spectrum disorder. Ann Neurol 2007; 62: 243–250.

    Article  Google Scholar 

  20. 20

    Skaar DA, Shao Y, Haines JL, Stenger JE, Jaworski J, Martin ER et al. Analysis of the RELN gene as a genetic risk factor for autism. Mol Psychiatry 2005; 10: 563–571.

    CAS  Article  Google Scholar 

  21. 21

    Zimmerman AW, Connors SL, Pardo-Villamizar CA . Neuroimmunology and neurotransmitters in autism. In: Tuchman R, Rabin I (eds), Autism: A Neurological Disorder of Early Brain Development. Mac Keith Press: London, UK, 2006, pp 141–159.

    Google Scholar 

  22. 22

    The International HapMap Consortium. A second generation human haplotype map of over 3.1 million SNPs. Nature 2007; 449: 851–861.

    Article  Google Scholar 

  23. 23

    Tansey KE, Brookes KJ, Hill MJ, Cochrane LE, Gill M, Skuse D et al. Oxytocin receptor (OXTR) does not play a major role in the aetiology of autism: genetic and molecular studies. Neurosci Lett 2010; 474: 163–167.

    CAS  Article  Google Scholar 

  24. 24

    Landgraf R, Neumann I . Vasopressin and oxytocin release within the brain: a dynamic concept of multiple and variable modes of neuropeptide communication. Front Neuroendocrinol 2004; 25: 150–176.

    CAS  Article  Google Scholar 

  25. 25

    Ross H, Young L . Oxytocin and the neural mechanisms regulating social cognition and affiliative behavior. Front Neuroendocrinol 2009; 30: 534–547.

    CAS  Article  Google Scholar 

  26. 26

    McGraw L, Young L . The prairie vole: an emerging model organism for understanding the social brain. Trends Neurosci 2010; 33: 1–14.

    Article  Google Scholar 

  27. 27

    Lee HJ, Caldwell HK, Macbeth AH, Tolu SG, Young WSY . A conditional knockout mouse line of the oxytocin receptor. Endocrinol 2008; 149: 3256–3263.

    CAS  Article  Google Scholar 

  28. 28

    Nishimori K, Takayanagi Y, Yoshida M, Kasahara Y, Young LJ, Kawamata M . New aspects of oxytocin receptor function revealed by knockout mice: sociosexual behavior and control of energy balance. Prog Brain Res 2008; 180: 79–90.

    Article  Google Scholar 

  29. 29

    Heinrichs M, Baumgartner T, Kirschbaum C, Ehlert U . Social support and oxytocin interact to suppress cortisol and subjective responses to psychosocial stress. Biol Psychiatry 2003; 54: 1389–1398.

    CAS  Article  Google Scholar 

  30. 30

    Domes G, Heinrichs M, Michel A, Berger C, Herpertz SC . Oxytocin improves ‘mind-reading’ in humans. Biol Psychiatry 2007; 61: 731–733.

    CAS  Article  Google Scholar 

  31. 31

    Guastella AJ, Mitchell PB, Dadds MR . Oxytocin increases gaze to the eye region of human faces. Biol Psychiatry 2008; 63: 3–5.

    CAS  Article  Google Scholar 

  32. 32

    Kosfeld M, Heinrichs M, Zak PJ, Fischbacher U, Fehr E . Oxytocin increases trust in humans. Nature 2005; 435: 673–676.

    CAS  Article  Google Scholar 

  33. 33

    McCullugh ME, Churchland PS, Mendez AJ . Problems with measuring peripheral oxytocin: can the data on oxytocin ad human behavior be trusted?. Neurosci Biobehav Rev 2013; 37: 1485–1492.

    Article  Google Scholar 

  34. 34

    Israel S et al. The oxytocin receptor contributes to prosocial fund allocations in the dictator game and the social value orientations task. PLoS One 2009; 4: e5535.

    Article  Google Scholar 

  35. 35

    Kogan A, Saslow LR, Impett EA, Oveis C, Keltner D, Rodrigues-Saturn S . Thin-slicing study of the oxytocin receptor (OXTR) gene and the evaluation and expression of the prosocial disposition. Proc Natl Acad Sci USA 2011; 108: 19189–19192.

    CAS  Article  Google Scholar 

  36. 36

    Tost H, Kolachana B, Hakimi S, Lemaitre H, Verchinski BA, Mattay VS et al. A common allele in the oxytocin receptor gene (OXTR) impacts prosocial temperament and human hypothalamic-limbic structure and function. Proc Natl Acad Sci USA 2010; 107: 13936–13941.

    CAS  Article  Google Scholar 

  37. 37

    Rodrigues SM, Saslow LR, Garcia N, John OP, Keltner D . Oxytocin receptor genetic variation relates to empathy and stress reactivity in humans. Proc Natl Acad Sci USA 2009; 106: 21437–21441.

    CAS  Article  Google Scholar 

  38. 38

    Chen FS, Johnson SC . An oxytocin receptor gene variant predicts attachment anxiety in females and autism-spectrum traits in males. Soc Psychol Personal Sci 2011; 3: 93–99.

    Article  Google Scholar 

  39. 39

    Bakermans-Kranenburg MJ, van Ijzendoorn MH . Oxytocin receptor (OXTR) and serotonin transporter (5-HTT) genes associated with observed parenting. Soc Cogn Affect Neurosci 2008; 3: 128–134.

    Article  Google Scholar 

  40. 40

    Green L, Fein D, Modahl C, Feinstein C, Waterhouse L, Morris M . Oxytocin and autistic disorder: alterations in peptide forms. Biol Psychiatry 2001; 50: 609–613.

    CAS  Article  Google Scholar 

  41. 41

    Guastella A, Einfeld SL, Gray KM, Rinehart NJ, Tonge BJ, Lambert TJ et al. Intranasal oxytocin improves emotion recognition for youth with autism spectrum disorders. Biol Psychiatry 2010; 6: 692–694.

    Article  Google Scholar 

  42. 42

    Andari E, Duhamel JR, Zalla T, Herbrecht E, Leboyer M, Sirigu A . Promoting social behavior with oxytocin in high-functioning autism spectrum disorders. Proc Natl Acad Sci USA 2010; 107: 4389–4394.

    CAS  Article  Google Scholar 

  43. 43

    Skuse DH, Lori A, Cubells JF, Lee I, Conneely KN, Puura K et al. Common polymorphism in the oxytocin receptor gene (OXTR) is associated with human social recognition skills. Proc Natl Acad Sci USA 2013; 111: 1987–1992.

    Article  Google Scholar 

  44. 44

    Ylisaukko-oja T, Alarcón M, Cantor RM, Auranen M, Vanhala R, Kempas E et al. Search for autism loci by combined analysis of autism genetic resource exchange and finnish families. Ann Neurol 2006; 59: 145–155.

    Article  Google Scholar 

  45. 45

    Wu S, Jia M, Ruan Y, Liu J, Guo Y, Shuang M, Gong X et al. Positive association of the oxytocin receptor gene (OXTR) with autism in the Chinese Han population. Biol Psychiatry 2005; 58: 74–77.

    CAS  Article  Google Scholar 

  46. 46

    Jacob S, Brune C, Carter C, Leventhal B . Association of the oxytocin receptor gene OXTR in Caucasian children and adolescents with autism. Neurosci 2007; 417: 6–9.

    CAS  Google Scholar 

  47. 47

    Lerer E, Levi S, Salomon S, Darvasi A, Yirmiya N, Ebstein RP . Association between the oxytocin receptor (OXTR) gene and autism: relationship to Vineland Adaptive Behavior Scales and cognition. Mol Psychiatry 2007; 13: 980–988.

    Article  Google Scholar 

  48. 48

    Yrigollen C, Han S, Kochetkova A, Babitz T . Genes controlling affiliative behavior as candidate genes for autism. Biol Psychiatry 2008; 63: 911–916.

    CAS  Article  Google Scholar 

  49. 49

    Wermter AK, Kamp-Becker I, Hesse P, Schulte-Körne G, Strauch K, Remschmidt H . Evidence for the involvement of genetic variation in the oxytocin receptor gene (OXTR) in the etiology of autistic disorders on high-functioning level. Am J Med Genet B Neuropsychiatr Genet 2010; 153B: 629–639.

    CAS  Article  Google Scholar 

  50. 50

    Liu X, Kawamura Y, Shimada T, Otowa T, Koishi S, Sugiyama T et al. Association of the oxytocin receptor (OXTR) gene polymorphisms with autism spectrum disorder (ASD) in the Japanese population. J Hum Genet 2010; 55: 137–141.

    CAS  Article  Google Scholar 

  51. 51

    Campbell DB, Datta D, Jones ST, Batey Lee E, Sutcliffe JS, Hammock EA et al. Association of oxytocin receptor (OXTR) gene variants with multiple phenotype domains of autism spectrum disorder. J Neurodev Disord 2011; 3: 101–112.

    Article  Google Scholar 

  52. 52

    Chakrabarti B, Dudbridge F, Kent L, Wheelwright S, Hill-Cawthorne G, Allison C et al. Genes related to sex steroids, neural growth, and social-emotional behavior are associated with autistic traits, empathy, and Asperger Syndrome. Autism Res 2009; 2: 157–177.

    CAS  Article  Google Scholar 

  53. 53

    Walum H, Lichtenstein P, Neiderhiser JM, Reiss D, Ganiban JM, Spotts EL et al. Variation in the oxytocin receptor gene is associated with pair-bonding and social behavior. Biol Psychiatry 2012; 71: 419–426.

    CAS  Article  Google Scholar 

  54. 54

    Luo L, Peng G, Zhu Y, Dong H, Amos CI, Xiong M . Genome-wide gene and pathway analysis. Eur J Hum Genet 2010; 18: 1045–1053.

    CAS  Article  Google Scholar 

  55. 55

    Lord C, Rutter M, Couteur A . Autism Diagnostic Interview-Revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Neurodev Disord 1994; 24: 659–685.

    CAS  Article  Google Scholar 

  56. 56

    Lord C, Risi S, Lambrecht L, Cook EH Jr, Leventhal BL, DiLavore PC et al. The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Neurodev Disord 2000; 30: 205–223.

    CAS  Article  Google Scholar 

  57. 57

    Schopler E, Reichler RJ, DeVillis RF, Daly K . Toward objective classification of childhood autism: Childhood Autism Rating Scale (CARS). J Autism Neurodev Disord 1980; 10: 91–103.

    CAS  Article  Google Scholar 

  58. 58

    Skuse D, Warrington R, Bishop D, Chowdhury U, Lau J, Mandy W et al. The Developmental, Dimensional and Diagnostic Interview (3di): A novel computerized assessment for autism spectrum disorders. J Am Acad Child Adolesc Psychiatry 2004; 45: 548–558.

    Article  Google Scholar 

  59. 59

    Han B, Eskin E . Random-effects model aimed at discovering associations in meta-analysis of genome-wide association studies. Am J Hum Genet 2011; 88: 586–598.

    CAS  Article  Google Scholar 

  60. 60

    Li MX, Sham PC, Cherny SS, Son YQ . A knowledge-based weighting framework to boost the power of genome-wide association studies. PLoS One 2010; 5: e14480.

    CAS  Article  Google Scholar 

  61. 61

    Li MX, Gui HS, Kwan JS, Sham PC . GATES: a rapid and powerful gene-based association test using extended Simes procedure. Am J Hum Genet 2011; 88: 283–293.

    CAS  Article  Google Scholar 

  62. 62

    Ge D . 2009 MetaP [Software]. Available from http://compute1.lsrc.duke.edu/softwares/MetaP/metap.php.

  63. 63

    Egger M, Smith GD, Schneider M, Minder C . Bias in meta-analysis detected by a simple, graphical test. Brit Med J 1997; 315: 629–634.

    CAS  Article  Google Scholar 

  64. 64

    Ioannidis JPA, Trikalinos TA . An exploratory test for an excess of significant findings. Clin Trials 2007; 4: 245–253.

    Article  Google Scholar 

  65. 65

    Anney R, Klei L, Pinto D, Regan R, Conroy J, Magalhaes TR et al. A genome-wide scan for common alleles affecting risk for autism. Hum Mol Genet 2010; 19: 4072–4082.

    CAS  Article  Google Scholar 

  66. 66

    Wu N, Li Z, Su Y . The association between oxytocin receptor gene polymorphism (OXTR) and trait empathy. J Affect Disord 2012; 138: 468–472.

    CAS  Article  Google Scholar 

  67. 67

    Chen FS, Barth ME, Johnson SL, Gotlib IH, Johnson SC . Oxytocin receptor (OXTR) polymorphisms and attachment in human infants. Front Psychol 2011; 2: 200.

    PubMed  PubMed Central  Google Scholar 

  68. 68

    Feldman R, Zagoory-Sharon O, Weisman O, Schneiderman I, Gordon I, Maoz R et al. Sensitive parenting is associated with plasma oxytocin and polymorphisms in the OXTR and CD38 genes. Biol Psychiatry 2012; 72: 175–18.

    CAS  Article  Google Scholar 

  69. 69

    Ronald A, Happé F, Bolton P, Butcher LM, Price TS, Wheelwright S et al. Genetic heterogeneity between the three components of the autism spectrum: a twin study. J Am Acad Child Psy 2006; 45: 691–699.

    Article  Google Scholar 

  70. 70

    Mazefsky CA, Williams DL, Minshew NJ . Variability in adaptive behavior in autism: Evidence for the importance of family history. J Abnorm Child Psych 2008; 36: 591–599.

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to D LoParo.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

LoParo, D., Waldman, I. The oxytocin receptor gene (OXTR) is associated with autism spectrum disorder: a meta-analysis. Mol Psychiatry 20, 640–646 (2015). https://doi.org/10.1038/mp.2014.77

Download citation

Further reading

Search

Quick links