In Utero Exposure to Selective Serotonin Reuptake Inhibitors and Risk for Autism Spectrum Disorder

Abstract

We investigated whether there is an association between increased risk for autism spectrum disorders (ASD) and selective serotonin reuptake inhibitors (SSRIs) used during pregnancy. This study used Denmark’s health and population registers to obtain information regarding prescription drugs, ASD diagnosis, and health and socioeconomic status. There were 1.5 % of cases and 0.7 % of controls exposed to SSRIs during the pregnancy period, and higher effect estimates observed with longer use. We found evidence that in utero exposure to SSRIs increases a child’s risk associated with ASD. These results, while adding to the limited knowledge on prenatal pharmacological exposures as potential ASD risk factors, need to be balanced against the benefits of indicated medication use by pregnant mothers.

Appendix

We used simulation analyses to explore the effects of under-reporting of SSRI use and depression in the register. For each simulation, a Monte Carlo approach was used simulating 1,000 datasets to randomly assign an unexposed mother to being exposed from a normal distribution. From each of the 1,000 simulated datasets we obtained the odds ratio and then took 1,000 samples from each odds ratio normal distribution. We then took the median effect estimate from these 1,000,000 samples as the odds ratio and the 2.5 and 97.5 % percentile to estimate the 95 % confidence interval. Models used in the simulations were unconditional logistic regressions adjusting for the matching variables as covariates.

Because the observed SSRI exposure prevalence (0.7 %) was below published estimates for other Nordic countries (Kieler et al. 2012) we completed simulations increasing the observed prevalence of SSRI exposure from 0.7 to 3 %. We assumed under-reporting was non-differential with respect to outcome by keeping sensitivity and specificity equal in case and control groups. Specificity was assumed to be 100 %, because it is unlikely a prescription for an SSRI would be documented in the register when none was given, and sensitivity was assumed to be 26 % because that corresponds to a true SSRI use prevalence of 3 %.

Simulations also examined the impact of under-ascertainment of maternal depression (which would lead to incomplete control for confounding by indication) because published estimates of the prevalence of maternal depression during pregnancy in Europe range from 3 to 17 % (Evans et al. 2001; Josefsson et al. 2001; Lund et al. 2009; Olsen et al. 2004)—higher than our observed prevalence of 0.6 %. Simulations were done increasing maternal depression prevalence to 5 % and then 15 %. Maternal depression under-reporting was assumed to be non-differential with respect to ASD case status because depression is assessed prior to the birth of the child and, thus, could not be influenced by subsequent diagnosis of the offspring. Specificity was assumed to be 100 %; in other words, all mothers truly without a history of depression where assumed to be correctly classified as without depression in the register, and sensitivity was set to 4.7 % to reflect the under-reporting needed where the true depression prevalence of 15 %.

Table 4 shows the results from simulation analyses exploring the influence of misclassification. The first row presents effect estimates and confidence bounds for any prenatal SSRI exposure from simulations assuming increased SSRI prevalence and non-differential misclassification as described above. Estimates for the full sample were very close to the comparable Model 1 adjusted (parental age and sex of the child) estimate in Tables 2, suggesting that exposure misclassification is unlikely to have strongly influenced results. The following rows show results from simulations investigating the potential effects of non-differential under-reporting of maternal depression. By increasing the assumed depression prevalence to 5 %, the pooled effect estimate, 2.2 (95 % CI 1.9–2.4), is extremely close to the comparable Model 1 adjusted (parental age and sex of the child) estimates shown in Table 2. At 15 % assumed depression prevalence, the SSRI effect is only moderately attenuated. Under the assumed 15 % depression prevalence scenario we also estimated depression-stratified effects. A positive association was observed in both strata, though the effect was smaller among mothers with depression, with median adjusted odds ratios and confidence intervals of 1.4 (95 % CI 0.9–2.4) and 2.1 (1.5–3.0), respectively. These results suggest that the original restriction approach to controlling for confounding by indication may have been influenced by depression misclassification.

Lastly, we performed a sensitivity analysis to determine how robust our quantitative estimates were to unmeasured confounding. Following the method of Lin et al. (1998) we assumed a binary confounder U existed such that U increased the risk of ASD, and that U was more prevalent in SSRI-exposed mothers than in unexposed mothers. Given the strength of relationship of U with ASD, and the prevalences of U in the exposed and unexposed, it is therefore possible to estimate odds ratios that are corrected for this unmeasured confounder U. We estimated corrected odds ratios over a range of plausible parameters.

In our analysis to measure the impact of unmeasured confounding, our results appear to be moderately robust. For example, if there were an unmeasured confounder U that doubled the risk of ASD, and had 50 % prevalence in SSRI-exposed mothers and only 5 % prevalence in SSRI-unexposed mothers, the corrected OR would still be 1.3 (1.0, 1.6). Similarly, if U doubled the risk of ASD, and was 40 % prevalent in SSRI-exposed mothers and only 10 % prevalent in SSRI-unexposed mothers, the corrected OR would be 1.4 (1.1, 1.8). We find it unlikely that such an unmeasured confounder or residual confounding, after adjustment for parental age, sex of child, history of maternal depression, and other SSRI indications, would be powerful enough to wholly explain our findings.

Table 5 Impact of unmeasured confounding of the effect estimates for prenatal SSRI exposure and risk for ASD