Comprehensive characterization of pathogenic missense CTRP6 variants and their association with cancer

Abstract

Background

Previous genome-wide association studies have linked three missense single nucleotide polymorphisms (SNPs) in C1q/TNF-related protein 6 (CTRP6) to diseases such as type 1 diabetes and autoimmune diseases. However, the potential association of newly identified missense CTRP6 variants with diseases, especially cancer, remains unclear.

Methods

We used several pathogenicity prediction algorithms to identify deleterious mutations within the highly conserved C1q domain of human CTRP6, following the retrieval of all SNPs from the Ensembl database. We systematically analyzed the effects of these mutations on the protein’s stability, flexibility, structural conformation, compactness, stiffness, and overall functionality using various bioinformatics tools. Additionally, we investigated the association of these mutations with different cancer types using the cBioPortal and canSAR databases.

Results

We identified 11 detrimental missense SNPs within the C1q domain, a region critical for this protein’s functionality. Using various computational methods, we predicted the functional impact of these missense variants and assessed their effects on the stability and flexibility of the CTRP6 structure. Molecular dynamics simulations revealed significant structural differences between the native and mutated structures, including changes in structural conformation, compactness, solvent accessibility, and flexibility. Additionally, our study shows a strong association between two mutations, G181S and R247W, and certain types of cancer: colon adenocarcinoma and uterine corpus endometrial carcinoma, respectively. We also found that the mutational status of CTRP6 and other cancer-related genes, such as MAP2K3, p16, TP53, and JAK1, affected each other’s expression, potentially contributing to cancer development.

Conclusions

Our screening and predictive analysis of pathogenic missense variants in CTRP6 advance the understanding of the functional implications of these mutations, potentially facilitating more focused and efficient research in the future.