Common genetic overlap in childhood psychiatric disorders

Many psychiatric disorders are already present, or nascent, in childhood and adolescence and pose a great burden on these children and their families (Costello et al., 2005). This thesis focuses on the common genetic variation that is associated with heritable neurodevelopmental and psychiatric disorders (Demontis & Walters, 2017; Grove & et.al., 2017; Polderman et al., 2015) occurring during childhood and adolescence such as ASD and ADHD. The underlying assumption is that complex disorders are influenced by genetic and environmental variation and by their interplay, called gene environment interaction and gene environment correlation. The genetic component comprises rare and common variations (Visscher et al., 2017). The focus of this thesis is on the common genetic variation (occurring >1% in the general population). Recent GWAS discoveries show that each associated common genetic variant has a very small effect size (Wray et al., 2020). We assume the effects to be cumulative, located in genetic and molecular networks which become impaired if enough local SNP mutations occur (Schadt, 2009). Due to the small effect size and assumed accumulation in specific networks it makes sense to not only analyze SNPs by themselves but additionally test the larger unit to which SNPs and genes (might) belong by means of gene-set analysis (de Leeuw et al., 2015; Duncan et al., 2014; Goudriaan et al., 2013). This approach is capable of identifying if common genetic variants grouped in a priori selected gene-sets are significantly associated with disorders, compared to genes not in the gene-set. A predictive tool based on GWAS discoveries is the PRS analysis. PRS involves calculating a weighted sum of SNPs consolidating the effect in a single measure (Wray et al., 2014, 2020) to be used in further analyses. Both gene-set analysis and PRS analysis are important tools used in this thesis. Using the clinical child and adolescent sample (‘Inside-Out’ described in Ch. 2) and control samples (NESCOG and BePS, described in Ch. 3, 4 and 5 when included), this thesis aimed to provide insights on the overlap of associated SNPs between psychiatric disorders. The first main aim of this thesis is to quantify the predictive capacity of common genetic variation of a variety of traits, as captured by their PRS. I aim to predict case-control status in a child and adolescent psychiatric sample with a variety of psychiatric disorders to reveal which traits are associated with the genetic risk contributing to general psychiatric symptoms present in several psychiatric disorders (Chapter 3). The second aim was to investigate if the common genetic variation related to ASD and ADHD, as captured by their PRS, is capable of predicting case-control status in an ASD and/or ADHD sample (Chapter 4). The third aim was to test if SNPs significantly associated with ASD occur more often in gene-sets linked to SCZ, which might be genetically linked to ASD. This might be a result of a large accumulation of SNPs with a small effect size assigned to included genes, or be due to a select group of SNPs with a large effect size (Chapter 5).