A team of researchers from China have performed an integrative genomic analysis and identified five genes associated with insomnia.
Insomnia is one of the most prevalent mental disorders worldwide and is characterised by persistent dissatisfaction with sleep. As a result, this impacts physical and mental health (including suicide, depression and post-traumatic stress disorder). Amongst the general population, the prevalence is around 10-20%. Previous research has identified a genetic component to insomnia, with heritability rates estimated to be 59% in females and 38% in males.
In recent years, genome-wide association studies (GWAS) have identified various genetic variants associated with insomnia complaints and symptoms. Researchers have identified over 200 genomic loci from these studies, yet their biological significance remains unclear. Importantly, there is strong evidence to suggest that abnormal expression in risk genes plays a key role in the disease pathogenesis.
Integrative genomic analysis
In the study, published in Bioscience Reports, the researchers used eQTL and GWAS data to determine whether expression-associated SNPs could confer risk to insomnia. They also aimed to detect insomnia-associated risk genes by using the Sherlock Bayesian-based integrative analysis approach.
Using this approach, the team identified 449 genes, whose alterations in gene expression may be implicated in insomnia. Researchers found these genes significantly overrepresented in six key biological pathways. These included Huntington’s disease, Alzheimer’s disease, Parkinson’s disease, spliceosome, oxidative phosphorylation and WNT signalling pathways.
5 candidate genes
To validate and prioritise these genes, the team performed another analysis on an independent brain eQTL dataset. Out of the 449 genes, 5 replicated in an independent brain eQTL dataset. These included: DALRD3, LDHA, HEBP2, TEX264 and FGFR3. Through a psychophysiological interaction (PPI) network analysis, the team found that these genes interacted with each other.
Interestingly, they observed that brain tissue expression of DALRD3, LDHA and HEBP2 was significantly lower in patients with insomnia compared to controls. In addition, the five identified genes showed differential expression patterns in mice between sleeping duration and sleep deprivation at different time points.
Together, these findings provide evidence to support that these newly identified genes may represent key candidates which contribute to the aetiology of insomnia risk. These findings also suggest that individuals suffering from insomnia may be at a greater risk of neurodegenerative disorders. Further research is needed to determine the function of these identified genes and risk variants