Multivariate genetic architecture of poor sleep quality

Area of Science:

• Genetics and Genomics
• Sleep Medicine
• Computational Biology

Background:

• The genetic architecture of sleep quality remains incompletely understood.
• Previous genome-wide association studies (GWAS) have not directly addressed the multivariate genetic structure of poor sleep quality (PSQ).

Purpose of the Study:

• To investigate the complex genetic underpinnings of poor sleep quality.
• To identify causal single nucleotide polymorphisms (SNPs) associated with PSQ.
• To explore potential disease correlations and predisposing factors for PSQ.

Main Methods:

• Genomic Structural Equation Modeling (Genomic-SEM) and multiple Post-GWAS methods were employed.
• Whole-transcriptome association analyses were conducted to identify susceptible gene loci.
• Polygenic risk scores and disease association analyses were utilized.

Main Results:

• Identified 14 leading SNP loci and 3 fine-mapping significant loci associated with PSQ.
• Discovered gene signal loci strongly correlated with PSQ across various tissues and cell types.
• Assessed correlations between PSQ and approximately 13,000 common diseases, including 20 neurological conditions.

Conclusions:

• This study provides novel insights into the genetic factors contributing to poor sleep quality.
• The findings highlight potential genetic predispositions and disease associations relevant to PSQ.
• The research establishes a foundation for future investigations into the genetic basis of sleep health.