Genome- and Exome-Wide Identification of Common-to-Rare Variants Associated with Middle Ear Cholesteatoma

To investigate the genetic susceptibility of middle ear cholesteatoma (MEC) and construct an MEC risk prediction model by integrating genetic risk with clinical factors.

MEC represents a relatively rare disorder that is associated with high morbidity, whereas its genetic etiology remains poorly understood.

Using genetic data from the UK Biobank (UKB), we performed both genome-wide association study (GWAS) and exome-wide association study (ExWAS) involving 702 MEC patients and 491,503 controls. Gene-based and gene set-based association studies were then performed to identify risk genes and gene sets of MEC, respectively. In addition, logistic regression models were applied to identify clinically significant MEC-associated diseases, of which the genetic and causal relationships with MEC were further characterized using linkage disequilibrium score regression, genetic analysis incorporating pleiotropy and annotation, and Mendelian randomization. Moreover, logistic regression models were employed to construct MEC risk prediction models by integrating genetic risk with clinical factors.

Our study identified 159 common variants across 8 genomic loci and 39 rare variants spanning 17 genomic regions that were significantly associated with MEC, with PLD1 being prioritized as the top-ranked MEC candidate target gene. Additionally, 10 different types of diseases showed significant associations with MEC, but no inconclusive genetic or causal relationship was established between them. Moreover, we successfully constructed a high-performance MEC risk prediction model with an area under the curve of 0.704, showing the potential for clinical application.

These findings advance our understanding of the genetic susceptibility of MEC and provide insights into its risk prediction, thus contributing to improved MEC prevention and management.