Nature CommunicationsGeneticsPeer-reviewed journal article
Transcriptome-wide association study of attention deficit hyperactivity disorder identifies associated genes and phenotypes
Calwing LiaoiD, Alexandre Dionne Laporte, Dan SpiegelmaniD, Fulya AkçimeniD, Ridha JooberiD, Patrick A. DioniD, Guy Armand RouleauiD
Abstract
Attention deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental psychiatric disorders. Previous studies have shown that the disorder is highly heritable and associated with several different risk-taking behaviors. Additionally, brain-imaging studies have identified various brain regions such as the cerebellum and frontal cortex to be altered in ADHD. Large genome-wide association studies (GWAS) have identified several loci associated with ADHD. However, understanding the biological relevance of these genetic loci has proven to be difficult. Here, we conducted the largest ADHD transcriptome-wide association study (TWAS) to date consisting of 19,099 cases and 34,194 controls and identified 9 transcriptome-wide significant hits. We successfully demonstrate that several previous GWAS hits can be largely explained by expression. Probabilistic causal fine-mapping of TWAS signals prioritized KAT2B with a posterior probability of 0.467 in the dorsolateral prefrontal cortex and TMEM161B with a posterior probability of 0.838 in the amygdala. Furthermore, pathway enrichments identified dopaminergic and norepinephrine pathways, which are highly relevant for ADHD. Finally, we used the top eQTLs associated with the TWAS genes to identify phenotypes relevant to ADHD and found an inverse genetic correlation with educational attainment and a positive correlation with \"ever smoker\", maternal smoking at birth, BMI, and schizophrenia. Overall, our findings highlight the power of TWAS to identify novel risk loci and prioritize putatively causal genes.
- organism: human
- assay: GWAS summary statistics
- research focus: fine-mapping
- research focus: gene regulatory network inference
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 128
- FWCI
- 13.71
- Field percentile
- top 1%
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