Cardiac Disease Associated Genetic Variants in Yi Nationality in Regions with High Incidence of Yunnan Sudden Unexplained Death / 法医学杂志

Objective To explore the association of cardiac disease associated genetic variants and the high incidence of Yunnan sudden unexplained death （YNSUD） in Yi nationality. Methods The genomic DNA was extracted from peripheral blood samples collected from 205 Yi villagers from YNSUD aggregative villages （inpatient group） and 197 healthy Yi villagers from neighboring villages （control group）. Fifty-two single nucleotide variants （SNVs） of 25 cardiac disease associated genes were genotyped using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry （MALDI-TOF-MS）. The SPSS 17.0 was used to analyze data. The pathogenicities of variants with differences between the two groups that have statistical significance were predicted by protein function prediction software PolyPhen-2 and SIFT. All villagers from inpatient group were given electrocardiogram （ECG） examination using a 12-lead electrocardiograph. Results The allele frequency and the genotype frequency of missense mutation DSG2 （rs2278792, c.2318G>A, p.R773K） of pathogenic genes of arrhythmogenic right ventricular cardiomyopathy （ARVC） in inpatient group was higher than that in control group （P<0.05）. Abnormal ECG changes were detected in 71 individuals （34.6%） in the inpatient group, among which 54 individuals carried R773K mutation, including clockwise （counterclockwise） rotation, left （right） axis deviation, ST segment and T wave alteration and heart-blocking. Conclusion Definite pathogenic mutations have not been found in the 52 cardiac disease genes associated SNVs detected in Yi nationality in regions with high incidence of YNSUD. The cause of high incidence of YNSUD in Yi nationality needs further study.

Minor alleles of genetic variants in second heart field increase the risk of hypoplastic right heart syndrome

Hypoplastic right heart syndrome(HRHS) is characterized by hypoplastic right ventricle (RV); Numerous transcriptional cascades in the second heart field (SHF) regulateRVdevelopment. The relationship of SHF gene variants with humanHRHS remains unknown. The whole lengths of 17 SHF genes were sequenced in 16 HRHS, and the selected single-nucleotide variants (SNVs) were then genotyped in HRHS, other congenital heart disease (CHD) and healthy control. Luciferase assay was performed to verify the effect of FOXC2: rs34221221A>GandTBX20: rs59854940C>Gat the transcription level. There were 151 (12.86%) novel SNVs after sequence analysis, of which three were in exons (one was synonymous SNV and two were nonsynonymous SNVs), two in promoter, and most SNVs (89.95%) were in intronic regions. Genotype analyses revealed that the minor alleles of FOXC2: rs34221221 A>G and TBX20: rs59854940 C>G could increase HRHS risk (P<0.05), but not in other CHD or healthy control. Luciferase assay showed that the minor G allele in rs34221221 significantly increased FOXC2 transcription while in rs59854940 it decreased TBX20 transcription significantly. Novel variants of SHF gene associated with HRHS were identified. Minor alleles in two variants from FOXC2 and TBX20 could increase the risk of HRHS.

MAP: Mutation Arranger for Defining Phenotype-Related Single-Nucleotide Variant

Next-generation sequencing (NGS) is widely used to identify the causative mutations underlying diverse human diseases, including cancers, which can be useful for discovering the diagnostic and therapeutic targets. Currently, a number of single-nucleotide variant (SNV)-calling algorithms are available; however, there is no tool for visualizing the recurrent and phenotype-specific mutations for general researchers. In this study, in order to support defining the recurrent mutations or phenotype-specific mutations from NGS data of a group of cancers with diverse phenotypes, we aimed to develop a user-friendly tool, named mutation arranger for defining phenotype-related SNV (MAP). MAP is a user-friendly program with multiple functions that supports the determination of recurrent or phenotype-specific mutations and provides graphic illustration images to the users. Its operation environment, the Microsoft Windows environment, enables more researchers who cannot operate Linux to define clinically meaningful mutations with NGS data from cancer cohorts.