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Highlights • This study provided a novel insight to the pathophysiology of Attention-Deficit Hyperactivity Disorder (ADHD). • Genome-wide integrated analysis of ADHD prioritized overall 47 genes. • LSG1 , HYAL3 , NUP43 , PIDD , and PNPL2 prioritized as the most causal genes for ADHD. These causal genes were highly expressed in the nerve tibial, cerebellum, hippocampus, and whole blood. • Disease associated pathways were associated with transporters, cellular delocalization, cytoplasmic regions, adhesion, and lysosome. • 49.69% of the causal genes were the co-expression genes, 39.25% of genes were found to be involved in Physical interactions while only 3.11% share protein domains. Abstract Recent genome-wide association study (GWAS) identified 12 independent loci for Attention-deficit hyperactivity disorder (ADHD). However, the causal genes expression and pathways of ADHD is still vague. We integrated GWAS, eQTL and genes expression data to find the causal genes, genes expression, and genes prioritization in the different brain tissues and whole blood cells. Overall 47 genes were prioritized, the most promising genes were LSG1, HYAL3, PIDD, PNPLA2 , BLOC1S2 , PLK1S1, CALN1, KAT2B, CTNNB1 and WDR11. Whereas, the CALN1, KAT2B , and WDR11 were previously associated with schizophrenia (SZ), bipolar (BP) and drug abuse. Gene ontology analysis shows that the glutamate receptor signaling pathway (P = 8.009E-07, with false discovery rate (FDR) < 5%), GRIK5 sub network (P = 2.887E-06, FDR < 5%), abnormal gait (P = 3.657E-06, FDR < 5%), REACTOME_SIGNALING_BY_ERBB2 (P = 5.161E-06, FDR < 5%), and abnormal nervous system physiology (P = 5.239E-06, FDR < 5%) were associated with ADHD. These causal genes were highly expressed in Fetal Astrocytes, Neurons, and Microglia/Macrophage. This study illustrates the comprehensive GWAS integrative approach of ADHD. However, further genetic and functional studies are required to validate the role of these genes in the etiology of ADHD, which should provide novel insights into the understanding of this disease. [ABSTRACT FROM AUTHOR]

Multiple genetic risk factors have been associated with psychiatric disorders which provides the genetic insight to these disorders; however, the etiology of these disorders is still elusive. 15q13.3 was previously associated with schizophrenia, bipolar and other neurodevelopmental disorders. Whereas, the FAN1 which encodes the Fanconi anemia associated nuclease 1 was suggested to be causal gene for 15q13.3 related psychiatric disorders. This study aimed to investigate the association of FAN1 with three major psychiatric disorders. Herein, we conducted a case-control study with the Chinese Han population. Three single nucleotide polymorphisms (SNPs) of FAN1 were genotyped in 1248 schizophrenia cases, 1344 bipolar disorder cases, 1056 major depressive disorder cases and 1248 normal controls. We found that SNPs rs7171212 was associated with bipolar (p allele = 0.023, p genotype = 0.022, OR = 0.658) and schizophrenia (p allele = 0.021, p genotype = 0.019, OR = 0.645). Whereas, rs4779796 was associated with schizophrenia (p genotype = 0.001, adjusted p genotype = 0.003, OR = 1.089). In addition, rs7171212 (adjusted p allele = 0.018, adjusted p genotype = 0.018, OR = 0.652) and rs4779796 (adjusted p genotype = 0.024, OR = 1.12) showed significantly associated with combined cases of schizophrenia and bipolar disorder. Further, meta-analysis was performed with the case-control data and dataset extracted from previously reported genome-wide association study to validate the promising SNPs. Our results provide the new evidence that FAN1 may be a common susceptibility gene for schizophrenia and bipolar disorder in Han Chinese. These novel findings need further validation with larger sample size and functional characterization to understand the underlying pathogenic mechanism behind FAN1 in the prevalence of schizophrenia and bipolar disorders. • Association study of FAN1 for SCZ, BPD and MDD in Han Chinese was conducted. • Rs7171212 is a risk locus for schizophrenia and bipolar disorder. • Rs4779796 significantly associated with schizophrenia in genotype distribution. • Meta-analysis was performed with the previously reported GWAS datasets. [ABSTRACT FROM AUTHOR]