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1.
Int J Pediatr Otorhinolaryngol ; 126: 109630, 2019 Nov.
Article in English | MEDLINE | ID: mdl-31442870

ABSTRACT

OBJECTIVES: More than 50% of congenital hearing loss is attributed to genetic factors. Data of gene mutation associated with hearing loss from large population studies in Chinese population are scarce. In this study, we conducted a comprehensive newborn genetic screening in China to establish the carrier frequency and mutation spectrum of deafness-associated genes. METHODS: A total of 53,033 newborns were screened for hearing defects associated mutations. Twenty hot spot mutations in GJB2, GJB3, SLC26A4 and mitochondria12S rRNA were examined using suspension array analysis. RESULTS: 14,185 newborns (26.75%) were identified with at least one mutated allele. 872 (1.64%) neonates carried homozygous mutations including 112 (0.21%) mitochondrial DNA homoplasmy, 228 (0.43%) were compound heterozygotes, and 11,985 (22.59%) were heterozygotes including 11 (0.02%) mitochondrial DNA heteroplasmy. Top five mutations included 109 G > A, 235 delC, 299-300 delAT in GJB2, IVS7-2 A > G in SLC26A4 and 1555 A > G in mitochondria12S rRNA. Notably, a total of 10,995 neonates (20.73%) carried 109 G > A in GJB2. Moreover, the allele frequencies of 109 G > A were detected 11.61% in Guangdong, 10.44% in Sichuan and 2.88% in Shandong, respectively, a significant difference in prevalence among these geographic regions (p<0.01). In addition, the high frequency of 109 G > A in GJB2 was confirmed by a TaqMan probe-based qPCR assay. Very recently, the ClinGen Hearing Loss Expert Panel reached a consensus and confirmed its pathogenic role in hearing impairment. CONCLUSION: We delineated the mutation profile of common deafness-causing genes in the Chinese population and highlighted the high prevalence of 109 G > A pathogenic mutation. Our study may facilitate early diagnosis/intervention and genetic counseling for hearing impairment in clinical practice.


Subject(s)
Connexins/genetics , Deafness/genetics , Genetic Testing , Mutation , Neonatal Screening , Oligonucleotide Array Sequence Analysis/methods , Asian People/genetics , China/epidemiology , Connexin 26 , Deafness/congenital , Deafness/epidemiology , Female , Gene Frequency , Heterozygote , Homozygote , Humans , Infant, Newborn , Male , Mitochondria/genetics , Prevalence , RNA, Ribosomal/genetics , Sulfate Transporters/genetics
2.
Gynecol Endocrinol ; 34(7): 584-588, 2018 Jul.
Article in English | MEDLINE | ID: mdl-29262729

ABSTRACT

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women, resulting in ovulation failure and other metabolic problems. However, the underlying mechanisms of it remain largely uncertain due to the complexity of clinical manifestations. This systemic disorder is involved in endocrine, metabolism, immune system and many organs, and few studies have explored peripheral blood transcriptome in patients with PCOS. We performed gene expression profiling of peripheral blood from 8 PCOS patients and eight healthy women with microarray. The significance analysis of microarray (SAM) software was employed to screen the differentially expressed genes (DEGs) and gene ontology (GO) was used for functional enrichment analysis. In total, 181 DEGs with fold-changes >2.0 and q-values <0.05 were identified between the two groups. Among them, 149 were up-regulated and 32 down-regulated in PCOS. Unsupervised clustering of expressed genes could readily differentiate PCOS from control. More importantly, inflammatory response pathway including 14 dysregulated genes was highly enriched in PCOS. Furthermore, 10 DEGs were validated using quantitative reverse-transcription PCR (qRT-PCR) assays. Our study provides independent evidence for the involvement of systemic inflammatory response in PCOS and it may facilitate a greater understanding of this complex disease.


Subject(s)
Blood Cells/metabolism , Inflammation/genetics , Polycystic Ovary Syndrome/blood , Polycystic Ovary Syndrome/genetics , Transcriptome , Adult , Case-Control Studies , Cluster Analysis , Female , Gene Expression Profiling , Gene Expression Regulation , Gene Regulatory Networks , Humans , Inflammation/complications , Inflammation/metabolism , Inflammation Mediators/metabolism , Microarray Analysis , Polycystic Ovary Syndrome/complications , Polycystic Ovary Syndrome/pathology
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