Abstract
OBJECTIVE: To screen for possible pathogenic mutations in polycystic ovary syndrome (PCOS) patients with diabetes and preliminarily explore the relationship between genotype and phenotype to offer a research basis for PCOS pathogenesis with diabetes. METHODS: Four patients with PCOS and diabetes were recruited and their demographic and clinical data were collected. Genomic DNA was extracted from peripheral blood leukocytes of the study subjects. High-throughput whole-exome sequencing was conducted to identify candidate genes that could play a pathogenic role in PCOS with diabetes in Aiji Taikang. The sequencing data obtained were evaluated using a variety of bioinformatics tools. Verification of candidate sites was done by Sanger sequencing. RESULTS: Based on whole-exome sequencing, six mutations residing in three genes were detected in these four patients: (1) MUC4 located at Chr 3q29, (2) FSHD region gene 1 (FRG1)gene located at Chr 4q35.2, and (3) androgen receptor (AR) located at Chr Xq11-q12 were detected in these four patients (every patients had the 6 mutations). Of the six genetic mutations, an insertion/deletion (indel) mutation was found in the mucin 4 (MUC4) gene [MUC4:NM_018406.6:2/25:c.7701_7702insTCAGTATCCACAGGTCATGCCACCCCTCTTCATGTCACCGACACTTCC:p.(Ser2567_Ala2568insSerValSerThrGlyHisAlaThrProLeuHisValThrAspThrSer)], and an indel mutation in the AR gene (AR:NM_000044:exon1:c.173_174insGCAGCA:p. Q58delinsQQQ), while the other four were missense single-nucleotide polymorphisms (SNPs) located in FRG1 of uncertain significance (FRG1:NM_004477:exon8:c.T692C:p. L231P, FRG1:NM_004477:exon8:c.C728T:p.T243M, FRG1:NM_004477:exon8:c.C733A:p.L245M, FRG1:NM_004477:exon8:c.T734G:p.L245R). A Mucin 4 (MUC4) gene indel mutation was detected at the same site in four patients, which could be associated with endometriosis-related infertility. The AR gene indel mutation, AR:NM_000044:exon1:c.173_174insGCAGCA: p. Q58delinsQQQ was detected simultaneously in four patients. CONCLUSION: Whole exome sequencing can quickly identify candidate genes for genes. Gaining an in-depth understanding of the AR mutations underlying PCOS with diabetes will deepen our understanding of the endocrine factors involved in the disease etiology, and provide potential targets for treatment.