Advanced paternal age is a well-established risk factor for the development of schizophrenia (SZ),1, 2, 3 and an increased rate of de novo mutations with increasing paternal age has been proposed as the chief explanation for this association.4 However, the paternal age effect could also be as a result of other potential explanations. For example, analyses of Danish registry data revealed that the paternal age effect was attributable to paternal age at birth of the first child in the sibship, rather than to age at birth of the child with SZ,5 which suggests that some explanation other than de novo mutations may explain the reported paternal age association with SZ. Furthermore, advanced maternal age, that has also been implicated in the risk of neurodevelopmental disorders (NDDs) via unknown mechanisms (that is, not de novo mutation), should also be incorporated in this conceptualization.6, 7 Therefore, findings regarding de novo mutations as the explanation for the association between advanced paternal age and SZ are inconclusive because covariates, such as maternal age8 and family size,9 which may index other potential mechanisms than paternally derived de novo mutations, have not been simultaneously considered in most prior analyses.
Studies of birth order effects in SZ in both population-based samples10, 11 and clinical samples12, 13 have yielded conflicting findings. Nevertheless, Jaffe et al.14 consider affected proband birth order as a proxy for de novo mutations. Their analyses did not support an association between paternal age and birth order as an index of de novo mutations in a SZ data set after controlling for maternal age and family size. In order to determine if this was a robust finding, we attempted to replicate this work in our local SZ data using similar methods to those described by Jaffe et al.14 Furthermore, because both advanced paternal age and increased de novo mutations have also been reported among cases of autism spectrum disorder (ASD)15 and other NDDs,2 we examined whether the paternal age/proband birth order association is specific to SZ or is more broadly related to NDDs by extending the analyses to an ASD sample.
The study samples included in these analyses were cases with SZ from an Irish collection (N=264, 69% male)16 and cases with ASD from the Simons Simplex Collection (SSC, version 14, N=2539, 87% male).17 Cases were limited to those with available data on birth order of the proband, and either maternal or paternal age at the proband‘s birth (see Supplementary Information for further details on the Irish SZ collection, and see Figure 1 for proband birth order and parental age distributions). We hypothesised that the results of our Irish SZ collection would mirror those of Jaffe et al.,14 and given the conclusions of Kong et al.,4 we expected the ASD results to follow the same pattern.
In order to establish whether there was an association between affected proband birth order and parental age in these collections, following Jaffe et al.,14 we examined birth order patterns (first born versus last born) between paternal age categories (younger fathers ⩽30 years and older fathers >40 years) and maternal age categories (younger mothers ⩽25 years and older mothers >35 years). In both collections, higher proband birth order was associated with both maternal and paternal older age categories (SZ: paternal age P<0.0001, maternal age P<0.0001; ASD: paternal age P<0.0001, maternal age P<0.0001). As would be expected, maternal age and paternal age were highly correlated in both collections (SZ: Pearson’s r 0.81, P<0.0001; ASD: Pearson’s r 0.71, P<0.0001), so we examined the impact of both of these variables on proband birth order simultaneously. In addition, we controlled for family size in the ordinal regression models that were used to identify associations between proband birth order and the explanatory variables (maternal age and paternal age at birth of the affected proband). From this model we see that for the SZ collection, an increase in 1 year of maternal age resulted in a greater odds (odds ratio (OR)=1.171, P<0.0001) of having a higher proband birth order, assuming that paternal age and family size remain constant. Similarly, for paternal age in the SZ data, for a 1-year increase in paternal age, there was a greater odds (OR=1.066, P=0.0114) of having a higher proband birth order, assuming the other two variables are fixed. Family size was also significantly associated with birth order of the affected proband (OR=2.000, P<0.0001). These results do not replicate those of Jaffe et al., who found that when both maternal and paternal age are entered into a model, only maternal age had a significant effect on proband birth order.
Parallel analyses of the ASD collection yielded a similar pattern of results to those seen in the SZ data. For a 1-year increase in maternal age the odds of an ASD proband having a higher birth order increased (OR=1.140, P<0.0001), again assuming the remaining variables are kept constant. For a 1-year increase in paternal age in the ASD data, the odds of a proband having a higher birth order also increased (OR=1.049, P<0.0001), assuming the remaining variables are kept constant. The family size was also significantly associated with affected proband birth order in the ASD data (OR=6.771, P<0.0001). Therefore, for both SZ and ASD, our findings do not support the conclusions of Jaffe et al.,14 because in the analyses for both disorders presented here, paternal age remained significantly associated with proband birth order when maternal age was included in the model. Therefore we cannot use these data to rule out the role of paternally derived de novo mutations in the aetiology of SZ or ASD. Moreover, the significant maternal age association leads us to believe that maternal age must also be part of the explanation of the aetiology of NDDs, as shown in recent research.8
Differences between our findings and those of Jaffe et al.14 could be attributable to either our analytic methods or to the heterogeneity of the samples. Although our ordinal regression analyses, which considered birth order as an ordinal-level variable, differed from the multiple linear regression analyses of Jaffe et al.,14 we did repeat the analyses with multiple linear regressions obtaining similar results to the ordinal regressions (see Supplementary Information for details). Moreover, our SZ sample was a clinical collection, rather than a family-based sample, and our sample was exclusively of homogenous Irish ethnicity.
To our knowledge, this is the first analysis of de novo mutations in ASD, as indexed by birth order, as an explanation for the paternal age effect that simultaneously considered maternal age and family size. The SSC sample, which was limited to sporadic cases of ASD, presumed to be enriched for de novo mutations, is a particularly powerful sample to examine this question.
In conclusion, this work adds to the growing body of research that probes potential determinants of the association between de novo mutations and NDDs; however, the conflicting results between our work and that of Jaffe et al.14 highlight the complexity of factors that may influence the relationship between advanced paternal age, de novo mutations, and NDDs. We highlight the importance of considering both maternal and paternal age,18 and birth order,13, 19 as well as the specificity of the findings for SZ and other NDDs.20 Moreover, other factors such as birth interval,10 and sex11 should also be considered in future studies, along with comparison to the mutation rate in control subjects. In fact, the lack of availability of the full range of potential explanatory variables within the same sample may be one source of the inconsistency of results in previous parental age research. For example, recent evidence suggests that epigenetic mechanisms rather than structural changes may be more strongly associated with paternal age.19 Direct examination of de novo mutations and other genetic variants, together with phenotype information, parental age information, and other relevant perinatal factors using translational epidemiological approaches may be a more fruitful line of investigation.21
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The authors are grateful to all of the families at the participating SSC sites, as well as the principal investigators (A. Beaudet, R. Bernier, J. Constantino, E. Cook, E. Fombonne, D. Geschwind, R. Goin-Kochel, E. Hanson, D. Grice, A. Klin, D. Ledbetter, C. Lord, C. Martin, D. Martin, R. Maxim, J. Miles, O. Ousley, K. Pelphrey, B. Peterson, J. Piggot, C. Saulnier, M. State, W. Stone, J. Sutcliffe, C. Walsh, Z. Warren, E. Wijsman), and appreciate obtaining access to phenotypic data on SFARI Base. Approved researchers can obtain the SSC population data set described in this study by applying at https://base.sfari.org. The authors acknowledge funding from the Wellcome Trust (UK), Science Foundation Ireland, the National Institute of Mental Health (USA) and the Meath Foundation (Ireland).
The authors declare no conflict of interest.
Supplementary Information accompanies the paper on the Molecular Psychiatry website
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Merikangas, A., Segurado, R., Kelleher, E. et al. Parental age, birth order and neurodevelopmental disorders. Mol Psychiatry 21, 728–730 (2016). https://doi.org/10.1038/mp.2015.127
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