A new perspective on population genetics: Deciphering the relationship between genetic variants and disease prevalence in Psoriasis

Abstract

In the quest to identify the genetic underpinnings of complex diseases, we developed a novel approach called Causal Genotype Combination Patterns (CGCP) to uncover characteristic genetic signatures of common diseases. In this study, we applied the CGCP method to a whole-exome sequencing dataset of 781 psoriasis cases and 676 healthy controls from the Chinese Han population. Our analysis revealed 620 genotype combinations specific to psoriasis, covering 4.7% to 10% of all cases, with each genotype having a frequency of at least 1%. These genotypes converged into 134 genes, including 41 previously reported to be associated with psoriasis. By leveraging public data from the 1000 Genomes Project Phase III and literature reviews on psoriasis prevalence in various ethnic populations, we established a strong positive correlation and linear regression model (y = 61.72x + 0.48, 95% CI [21.60, 101.84]) between the average frequency of these psoriasis-specific genotype combinations and disease prevalence across populations. This finding may explain the varying prevalence of psoriasis in different populations. Our strategy offers a new perspective on understanding the characteristics of population genetics in common diseases.