LAUSR

Abstract This study is presented on behalf of the iPSYCH-Broad ADHD working group, the PGC ADHD working group and the PGC MDD working group. Earlier studies have shed light on the individually unique and shared genetic risk architecture of Attention Deficit Hyperactivity Disorder(ADHD), autism spectrum disorder (ASD), and major depressive disorder (MDD). This involved single trait and cross-disorder genome-wide association studies (GWAS) as well as studies targeted at estimating the degree of genetic variation within and covariation between disorders. Especially for ADHD (but also for ASD) these analyses were potentially biased due to availability of only small samples when compared to other (adult onset) disorders in the analyses. Moreover, the identification of shared risk loci for ADHD with other disorders was likely hindered by the very same limitation. Others and we have recently performed the largest GWASs to date for ADHD (~20k cases), ASD (~18k cases), and MDD (~130k cases). These studies identified numerous genome-wide significant risk loci for the individual disorders and therefore opened the door for reliable estimation of genetic covariation and cross-phenotype association studies that have enough power to detect shared risk loci. This is of interest as comorbidity with these disorders is common in patients with ADHD and identification of shared risk loci might open the door for a better understanding of disease etiology as well as treatment options and prevention. In a first step, we calculated the genetic correlation (rG) between ADHD, ASD, and MDD and found rGs of 0.35 for ADHD/ASD and 0.42 for ADHD/MDD with an rG of 0.44 for ASD and MDD. In a second step, we performed cross-phenotype GWAS analyses for the ADHD/ASD and ADHD/MDD pairs. We identified 8 regions with genome-wide significant SNPs, amongst others harboring the hostgene of miR-9, MANBA, and NUDT12 as shared risk factors for ADHD and ASD. We also identified 67 regions with genome-wide significant signals, amongst many others harboring SORCS3, NEGR1, and the hostgene of miR-9 as shared risk factors for ADHD and MDD. In addition, we are currently using, and will present results from, re-sampling procedures to study genetic correlation and individual SNP associations for individuals with ADHD and without comorbid ASD and/or MDD (and other phenotypes such as bipolar disorder, intellectual disability, and schizophrenia). We hope that these analyses together with other secondary analyses (e.g. using Mendelian Randomization) will help to identify genetically and phenotypically more homogenous subgroups of our sample in order to gain new insights in the etiology of ADHD and most importantly identify new strategies for prevention and treatment.