The genetic variability and commonality of neurodevelopmental disease

Abstract

Despite detailed clinical definition and refinement of neurodevelopmental disorders and neuropsychiatric conditions, the underlying genetic etiology has proved elusive. Recent genetic studies have revealed some common themes: considerable locus heterogeneity, variable expressivity for the same mutation, and a role for multiple disruptive events in the same individual affecting genes in common pathways. Recurrent copy number variation (CNV), in particular, has emphasized the importance of either de novo or essentially private mutations creating imbalances for multiple genes. CNVs have foreshadowed a model where the distinction between milder neuropsychiatric conditions from those of severe developmental impairment may be a consequence of increased mutational burden affecting more genes.

Figure 1

Autosomal CNV burden across various neurodevelopmental phenotypes. Displayed are the odds ratios as a function of CNV size across various phenotypes from two recent studies. A: A comparison of multiple sample cohorts, ascertained using standard diagnostic criteria for each phenotype, profiled on the same targeted micro array CGH platform [Girirajan et al., 2011]. Odds ratios were calculated compared to 306 National Institute of Mental Health controls. B: Information obtained from 15,767 cases with a general diagnosis of ID/DD [Cooper et al., 2011]. The autism, epilepsy, and craniofacial abnormality phenotypes represent subsets of this overall ID/DD population. Odds ratios were calculated against 8,329 control samples [Cooper et al., 2011].

Figure 2

Variable expressivity of hotspot CNVs. The frequency of CNV deletions and reciprocal duplications for six genomic hotspots associated with neurological disease are shown (ID/DD, autism, epilepsy, schizophrenia, and bipolar disorders). Data sources are as follows. ID/DD: all sites n = 31,516 [Cooper et al., 2011; Kaminsky et al., 2011]. Autism: all sites n = 1,551 [Marshall et al., 2008; Sanders et al., 2011]. Epilepsy: all sites n = 399 [Mefford et al., 2010]; 15q13.3 n = 647 [Helbig et al., 2009; Mefford et al., 2010]; 16p11.2 n = 1,234 [de Kovel et al., 2010; Mefford et al., 2010]. Schizophrenia: all sites n = 4,168 [The International Schizophrenia Consortium, 2008; Malhotra et al., 2011], 15q13.3 n = 6,948 [The International Schizophrenia Consortium, 2008; Stefansson et al., 2008; Malhotra et al., 2011], 1q21.1 n = 12,117 [The International Schizophrenia Consortium, 2008; Stefansson et al., 2008; Malhotra et al., 2011], 3q29 n = 4,413 [The International Schizophrenia Consortium, 2008; Mulle et al., 2010; Malhotra et al., 2011]. Bipolar disorders: all sites n = 2,053 [Grozeva et al., 2010; Malhotra et al., 2011]. Controls: n = 8,329 [Cooper et al., 2011].

Figure 3

Phenotypic severity as an outcome of CNV burden. Rare CNVs (defined as present in <0.1% of controls and unaffected siblings) were analyzed in the context of full-scale IQ for 841 Simons Simplex autism probands. A: Full-scale IQ weakly correlates with the largest rare CNV carried by an individual (Pearson’s r = −0.11, >500 kbp, r = −0.36); however, when we split the population at increasing CNV size cutoffs (B), we observe a striking drop in median IQ, most noticeable past 500 kbp. When we filter CNVs <500 kbp, we observe a striking correlation between median IQ and CNV size (Spearman’s r = −0.97, P = 0.0009). The calculation of P-values was performed by computing 10,000 random permutations of IQ across samples and repeating the median IQ calculations. The P-value represents the fraction of permutations with a more extreme correlation than that observed for the raw data.

Figure 4

An oligogenic model for neurodevelopmental phenotypes. Presented is a model where an increasing number of genes disrupted by rare CNVs correlates with an increase in phenotypic severity (defined as increasing comorbidity of ID and congenital abnormalities).