ABSTRACT
Nonobstructive azoospermia (NOA) is a severe condition in infertile men, and increasing numbers of causative genes have been identified during the last few decades. Although certain causative genes can explain the presence of NOA in some patients, a proportion of NOA patients remain to be addressed. This study aimed to investigate potential high-risk genes associated with spermatogenesis in idiopathic NOA patients by whole-exome sequencing. Whole-exome sequencing was performed in 46 male patients diagnosed with NOA. First, screening was performed for 119 genes known to be related to male infertility. Next, further screening was performed to determine potential high-risk causative genes for NOA by comparisons with 68 healthy male controls. Finally, risk genes with high/specific expression in the testes were selected and their expression fluctuations during spermatogenesis were graphed. The frequency of cystic fibrosis transmembrane conductance regulator (CFTR) gene pathogenic variant carriers was higher in the NOA patients compared with the healthy controls. Potential risk genes that may be causes of NOA were identified, including seven genes that were highly/specifically expressed in the testes. Four risk genes previously reported to be involved in spermatogenesis (MutS homolog 5 [MSH5], cilia- and flagella-associated protein 54 [CFAP54], MAP7 domain containing 3 [MAP7D3], and coiled-coil domain containing 33 [CCDC33]) and three novel risk genes (coiled-coil domain containing 168 [CCDC168], chromosome 16 open reading frame 96 [C16orf96], and serine protease 48 [PRSS48]) were identified to be highly or specifically expressed in the testes and significantly different in the 46 NOA patients compared with 68 healthy controls. This study on clinical NOA patients provides further evidence for the four previously reported risk genes. The present findings pave the way for further functional investigations and provide candidate risk genes for genetic diagnosis of NOA.
Subject(s)
Humans , Male , Azoospermia/pathology , East Asian People , Exome Sequencing , Mutation , Proteins/geneticsABSTRACT
Objective:To investigate the correlation between single nucleic acid polymorphisms (SNPs) of MEIS1, BTBD9, MAP2K5, PTPRD and restless leg syndrome (RLS).Methods:By searching the literatures published before March 1, 2021 at home and abroad, case-control studies on risk genes associated with RLS were collected, and the Review Manager 5.3 and Stata 15.1 softwares were used for statistical analysis.Results:A total of 8 studies were included, with a total of 7 824 cases and 14 645 controls.Meta analysis results showed that the SNPs locus of the risk gene associated with RLS was MEIS1 rs2300478( OR=1.68, 95% CI: 1.59-1.78), BTBD9 rs9296249( OR=1.62, 95% CI: 1.47-1.77), BTBD9 rs9357271( OR=1.49, 95% CI: 1.44-1.55), MAP2K5 rs12593813( OR=1.44, 95% CI: 1.36-1.53), MAP2K5 rs11635424( OR=1.47, 95% CI: 1.34-1.60)and PTPRD rs1975197( OR=1.34, 95% CI: 1.21-1.49). Conclusion:MEIS1 rs2300478, BTBD9 rs9296249, BTBD9 rs9357271, MAP2K5 rs12593813, MAP2K5 rs11635424 and PTPRD rs1975197 are the risk loci of RLS.
ABSTRACT
The autism spectrum disorders(ASDs)are a complex group of neuropsychiatric conditions defined by impairment in three core behavioral domains:social interaction,verbal and non-verbal communication,and restricted interests/repetitive behaviors. Extensive genetic studies have led to the identification of many autism susceptibility genes,and increased understanding on the contribution of de novo and inherited copy number variation. Here,we seek to place recent genetic findings within a developmental and brain circuit context,and approach the basic understanding of autism neuropathology from multiple genetic,molecular,cellular and neural circuit domains. The authors reviewed literatures that interrogates brain mechanisms of ASDs utilizing animal models,primarily in mice. Understanding genetic data within a brain development context will shed light on how individual risk genes operate to determine patient symptomatology,which will inform circuit specific behavioral interventions leading to better intervention and disease outcomes.