Paternal-age-related de novo mutations and risk for five disorders

Abstract

There are established associations between advanced paternal age and offspring risk for psychiatric and developmental disorders. These are commonly attributed to genetic mutations, especially de novo single nucleotide variants (dnSNVs), that accumulate with increasing paternal age. However, the actual magnitude of risk from such mutations in the male germline is unknown. Quantifying this risk would clarify the clinical significance of delayed paternity. Using parent-child trio whole-exome-sequencing data, we estimate the relationship between paternal-age-related dnSNVs and risk for five disorders: autism spectrum disorder (ASD), congenital heart disease, neurodevelopmental disorders with epilepsy, intellectual disability and schizophrenia (SCZ). Using Danish registry data, we investigate whether epidemiologic associations between each disorder and older fatherhood are consistent with the estimated role of dnSNVs. We find that paternal-age-related dnSNVs confer a small amount of risk for these disorders. For ASD and SCZ, epidemiologic associations with delayed paternity reflect factors that may not increase with age.

Fig. 1

Impact of paternal age-related dnSNVs on five disorders. IRR Incidence rate ratio, SCZ schizophrenia, ASD autism spectrum disorder, CHD congenital heart disease, EPI epilepsy, ID intellectual disability. Error bars reflect 95% confidence intervals. Note that confidence intervals are not valid for comparing dnSNV effect within or across disorders (See Methods)

Fig. 2

Disease risk in offspring of older fathers vs. offspring of younger fathers in dnSNV model and Danish population. SCZ schizophrenia, ASD autism spectrum disorder, CHD congenital heart disease, EPI neurodevelopmental disorders with epilepsy, ID intellectual disability. Error bars reflect 95% confidence intervals. *p < 2 × 10⁻⁴ against null hypothesis that epidemiologic association between advanced paternal age and disease risk is equivalent to the dnSNV model’s estimate (empiric p value as described in Methods)