The Deciphering Developmental Disorders Study has recruited a large cohort of ~13,000 patients with severe developmental disorders (DDs) and is conducting exome sequencing on them and their parents in order to try to uncover the causal genetic mutations (Wright et al., 2015; Deciphering Developmental Disorders Study, 2017). This is a highly heterogeneous cohort, and the most common phenotypes include intellectual disability (79%), seizures (19%) and autism spectrum disorders ASDs) (12%). We have discovered a damaging mutation in approximately 1/3 of the cohort that is thought to account for all or most of their phenotype.

However, it is becoming increasingly clear that common diseases, and in particular, psychiatric phenotypes, can have both common and rare genetic variants contributing to aetiology (Gaugler et al., 2014; Singh et al., 2016; Pardiñas et al., 2016). Thus, we have been investigating the potential role of common variation in DD, using genome-wide genotype data on ~8,000 DDD probands and ~13,000 ancestry-matched controls. We have shown, using these data, that common variants contribute a small proportion of the variation in risk of DD (heritability=9.3%; standard error=4.0%), and also that there is a significant genetic correlation (rg=-0.77; p=5.1E-6) between DD risk and educational attainment (EA) in the general population (i.e. correlation in the phenotypes due to shared polygenic background). In order to increase our power to perform further common variant analyses, we would like to add the ALSPAC data as additional controls, so we are seeking access to the genotype data as well as data on EA and IQ measures.

References:
Deciphering Developmental Disorders Study. Prevalence and architecture of de novo mutations in developmental disorders. Nature, 542, 433–438 (2017).

Gaugler et al. Most genetic risk for autism resides with common variation. Nat. Genet. 46(8) 881-885 (2014).

Pardiñas et al. Common schizophrenia alleles are enriched in mutation-intolerant genes and maintained by background selection. Biorxiv. (2016).

Singh et al. The contribution of rare variants to risk of schizophrenia in individuals with and without intellectual disability. Nat. Genet. 49(8):1167-1173 (2016).

Wright,C.F., Fitzgerald,T.W., Jones,W.D., Clayton,S., McRae,J.F., van Kogelenberg,M., King,D.A., Ambridge,K., Barrett,D.M., Bayzetinova,T., et al. Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data. Lancet, 385, 1305–1314 (2015).