Design and Aims:We conducted whole-exome DNA sequencing on 152 parent-child trios (456 individuals total) that included a child meeting DSM-IV or DSM-5 criteria for ADHD along with both biological parents to identify rare de novo damaging DNA variants associated with ADHD risk. Mutation rates were compared between 147 ADHD trios and 780 unaffected control trios. We aimed to identify specific ADHD risk genes by combining the de novo trio data with rare variant data from an independent case-control cohort.Population Information:ADHD trios were collected from four sites. The 780 control trios were unaffected siblings from the Simons Simplex Collection who scored in the normal range on the Child Behavior Checklist (CBCL) or Adult Behavior Checklist (ABCL) ADHD subscale.Molecular Technologies:Whole-exome DNA sequencing was performed on the ADHD trios using the IDT xGen V1 or Agilent SureSelect All Exon V7 capture and the Illumina NovaSeq6000 sequencer. Control trios were previously sequenced with the NimbleGen SeqCap EzExomeV2 capture and Illumina HiSeq 2000 sequencer. Joint variant calling was performed for all trios. Rare de novo variants with allele frequency &#x3C; 0.001 and ultra-rare variants with frequency &#x3C; 0.00005 were identified.Principal Findings:We found a 1.67-fold enrichment of rare de novo damaging variants and a 1.93-fold enrichment of ultra-rare de novo damaging variants in ADHD cases vs controls. By integrating the de novo data with an independent case-control cohort, <a href="https://www.ncbi.nlm.nih.gov/gene/10765">KDM5B</a> was identified as a high-confidence ADHD risk gene (FDR=0.04). Three potential risk genes were also identified. Twenty-three genes with ultra-rare damaging de novo variants in ADHD overlapped with previously reported risk genes for other neuropsychiatric conditions. Exploratory analyses showed enrichment of these genes in early neurodevelopmental pathways.

Genetic Investigations of Attention-Deficit/Hyperactivity Disorder

Attention Deficit Disorder with Hyperactivity study with SNP/CNV Genotypes (NGS) data on dbGaP (2,781 participants)