An integrative analysis of transcriptome-wide association study and mRNA expression profile identified candidate genes for attention-deficit/hyperactivity disorder

2019 ◽  
Vol 282 ◽  
pp. 112639 ◽  
Author(s):  
Xin Qi ◽  
Sen Wang ◽  
Lu Zhang ◽  
Li Liu ◽  
Yan Wen ◽  
...  
2020 ◽  
pp. 070674372097084
Author(s):  
Om Prakash Kafle ◽  
Xi Wang ◽  
Shiqiang Cheng ◽  
Miao Ding ◽  
Ping Li ◽  
...  

Objectives: Gout is a common inflammatory arthritis, which is caused by hyperuricemia. Limited efforts have been paid to systematically explore the relationships between gout and common psychiatric disorders. Methods: Genome-wide association study summary data of gout were obtained from the GeneATLAS, which contained 452,264 participants including 3,528 gout cases. Linkage disequilibrium score regression (LDSC) was first conducted to evaluate the genetic relationships between gout and 5 common psychiatric disorders. Transcriptome-wide association studies (TWAS) was then conducted to explore the potential biological mechanism underlying the observed genetic correlation between gout and attention-deficit hyperactivity disorder (ADHD). The Database for Annotation, Visualization and Integrated Discovery online functional annotation system was applied for pathway enrichment analysis and gene ontology enrichment analysis. Results: LDSC analysis observed significant genetic correlation between gout and ADHD (genetic correlation coefficients = 0.29, standard error = 0.09 and P value = 0.0015). Further TWAS of gout identified 105 genes with P value < 0.05 in muscle skeleton and 228 genes with P value < 0.05 in blood. TWAS of ADHD also detected 300 genes with P value < 0.05 in blood. Further comparing the TWAS results identified 9 common candidate genes shared by gout and ADHD, such as CD300C ( P gout = 0.0040; P ADHD = 0.0226), KDM6B ( P gout = 0.0074; P ADHD = 0.0460), and BST1 ( P gout = 0.0349; P ADHD = 0.03560). Conclusion: We observed genetic correlation between gout and ADHD and identified multiple candidate genes for gout and ADHD.


2019 ◽  
Vol 29 ◽  
pp. S167-S168
Author(s):  
Paula Rovira ◽  
Cristina Sanchez-Mora ◽  
Iris Garcia-Martínez ◽  
Mireia Pagerols ◽  
Vanesa Richarte ◽  
...  

2019 ◽  
Vol 9 (10) ◽  
pp. 288
Author(s):  
Nicoletta Nuzziello ◽  
Francesco Craig ◽  
Marta Simone ◽  
Arianna Consiglio ◽  
Flavio Licciulli ◽  
...  

Attention Deficit Hyperactivity Disorder (ADHD) is a childhood-onset neurodevelopmental disorder, whose etiology and pathogenesis are still largely unknown. In order to uncover novel regulatory networks and molecular pathways possibly related to ADHD, we performed an integrated miRNA and mRNA expression profiling analysis in peripheral blood samples of children with ADHD and age-matched typically developing (TD) children. The expression levels of 13 miRNAs were evaluated with microfluidic qPCR, and differentially expressed (DE) mRNAs were detected on an Illumina HiSeq 2500 genome analyzer. The miRNA targetome was identified using an integrated approach of validated and predicted interaction data extracted from seven different bioinformatic tools. Gene Ontology (GO) and pathway enrichment analyses were carried out. Results showed that six miRNAs (miR-652-3p, miR-942-5p, let-7b-5p, miR-181a-5p, miR-320a, and miR-148b-3p) and 560 genes were significantly DE in children with ADHD compared to TD subjects. After correction for multiple testing, only three miRNAs (miR-652-3p, miR-148b-3p, and miR-942-5p) remained significant. Genes known to be associated with ADHD (e.g., B4GALT2, SLC6A9 TLE1, ANK3, TRIO, TAF1, and SYNE1) were confirmed to be significantly DE in our study. Integrated miRNA and mRNA expression data identified critical key hubs involved in ADHD. Finally, the GO and pathway enrichment analyses of all DE genes showed their deep involvement in immune functions, reinforcing the hypothesis that an immune imbalance might contribute to the ADHD etiology. Despite the relatively small sample size, in this study we were able to build a complex miRNA-target interaction network in children with ADHD that might help in deciphering the disease pathogenesis. Validation in larger samples should be performed in order to possibly suggest novel therapeutic strategies for treating this complex disease.


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