[Disease spectrum and pathogenic genes of inherited metabolic disorder in Gansu Province of China]. / ç”˜è‚ƒåœ°åŒºé—ä¼ ä»£è°¢ç— ç–¾ç— è°±åŠè‡´ç— åŸºå› åˆ†æž.

OBJECTIVES: To investigate the disease spectrum and pathogenic genes of inherited metabolic disorder (IMD) among neonates in Gansu Province of China. METHODS: A retrospective analysis was conducted on the tandem mass spectrometry data of 286 682 neonates who received IMD screening in Gansu Provincial Maternal and Child Health Hospital from January 2018 to December 2021. A genetic analysis was conducted on the neonates with positive results in tandem mass spectrometry during primary screening and reexamination. RESULTS: A total of 23 types of IMD caused by 28 pathogenic genes were found in the 286 682 neonates, and the overall prevalence rate of IMD was 0.63 (1/1 593), among which phenylketonuria showed the highest prevalence rate of 0.32 (1/3 083), followed by methylmalonic acidemia (0.11, 1/8 959) and tetrahydrobiopterin deficiency (0.06, 1/15 927). In this study, 166 variants were identified in the 28 pathogenic genes, with 13 novel variants found in 9 genes. According to American College of Medical Genetics and Genomics guidelines, 5 novel variants were classified as pathogenic variants, 7 were classified as likely pathogenic variants, and 1 was classified as the variant of uncertain significance. CONCLUSIONS: This study enriches the database of pathogenic gene variants for IMD and provides basic data for establishing an accurate screening and diagnosis system for IMD in this region.

Prevention and Control of Pathogens Based on Big-Data Mining and Visualization Analysis.

Morbidity and mortality caused by infectious diseases rank first among all human illnesses. Many pathogenic mechanisms remain unclear, while misuse of antibiotics has led to the emergence of drug-resistant strains. Infectious diseases spread rapidly and pathogens mutate quickly, posing new threats to human health. However, with the increasing use of high-throughput screening of pathogen genomes, research based on big data mining and visualization analysis has gradually become a hot topic for studies of infectious disease prevention and control. In this paper, the framework was performed on four infectious pathogens (Fusobacterium, Streptococcus, Neisseria, and Streptococcus salivarius) through five functions: 1) genome annotation, 2) phylogeny analysis based on core genome, 3) analysis of structure differences between genomes, 4) prediction of virulence genes/factors with their pathogenic mechanisms, and 5) prediction of resistance genes/factors with their signaling pathways. The experiments were carried out from three angles: phylogeny (macro perspective), structure differences of genomes (micro perspective), and virulence and drug-resistance characteristics (prediction perspective). Therefore, the framework can not only provide evidence to support the rapid identification of new or unknown pathogens and thus plays a role in the prevention and control of infectious diseases, but also help to recommend the most appropriate strains for clinical and scientific research. This paper presented a new genome information visualization analysis process framework based on big data mining technology with the accommodation of the depth and breadth of pathogens in molecular level research.

Spatial pattern and variations in the prevalence of congenital heart disease in children aged 4-18 years in the Qinghai-Tibetan Plateau.

PURPOSE: This study aimed to investigate the spatial distribution pattern of the prevalence of congenital heart disease (CHD) in children in Qinghai-Tibetan Plateau (QTP), a high-altitude region in China. METHODS: Epidemiological data from a survey on the prevalence of CHD in Qinghai Province including 288,066 children (4-18 years) were used in this study. The prevalence and distribution pattern of CHD was determined by sex, CHD subtype, and nationality and altitude. Spatial pattern analysis using Getis-Ord Gi⁎ was used to identify the spatial distribution of CHD. Bayesian spatial binomial regression was performed to examine the relationship between the prevalence of CHD and environmental risk factors in the QTP. RESULTS: The prevalence of CHD showed a significant spatial clustering pattern. The Tibetan autonomous prefecture of Yushu (average altitude > 4000 m) and the Mongolian autonomous county of Henan (average altitude > 3600 m) in Huangnan had the highest prevalence of CHD. Univariate analysis showed that with ascending altitude, the total prevalence of CHD, that in girls and boys with CHD, and that of the subtypes PDA and ASD increasing accordingly. Thus, environmental factors greatly contributed to the prevalence of CHD. CONCLUSIONS: The prevalence of CHD shows significant spatial clustering pattern in the QTP. The CHD subtype prevalence clustering pattern has statistical regularity which would provide convenient clues of environmental risk factors. Our results may provide support to make strategies of CHD prevention, to reduce the incidence of CHD in high altitude regions of China.

MicroRNA expression and regulation in the uterus during embryo implantation in rat.

Embryo implantation is a complex initial step in establishment of a successful pregnancy. Many mRNAs have been shown to be differentially expressed in the rat uterus during embryo implantation. However, the expression profiles of microRNAs (miRNAs), a key post-transcriptional regulator of gene expression, in the rat uterus between the pre-receptive and receptive phases are still unknown. Here, an miRNA microarray was used to examine differential expression of miRNAs in the rat uterus between the pre-receptive and receptive phases. Twenty-eight miRNAs were up-regulated and 29 miRNAs were down-regulated at least twofold during the receptive phase in rat uterus; these results were confirmed by Northern blotting. miR-29a was only highly expressed in rat uterus during the implantation period, and activation of delayed implantation and artificial decidualization enhanced the miR-29a level. Further investigation revealed that both the pro-apoptotic factor genes Bak1 and Bmf and the anti-apoptotic factor gene Bcl-w are targets of miR-29a. There was weak binding between miR-29a and the 3' UTR of the anti-apoptotic factor gene Mcl1. Over-expression of miR-29a inhibited the late apoptosis of endometrial stromal cells, which may be due to the stronger binding capacity between miR-29a and the 3' UTR of pro-apoptotic factors than that between miR-29a and the 3' UTR of anti-apoptotic factors. Collectively, miR-29a plays an important role during embryo implantation by regulating both pro-apoptotic and anti-apoptotic factors. miR-29a may predominantly bind pro-apoptotic factors, leading to inhibition of cell apoptosis.

MiR-98 is involved in rat embryo implantation by targeting Bcl-xl.

In a previous study, via microRNA microarray analysis we found that miR-98 is differentially expressed in rat uteri during the peri-implantation period (unpublished data). However, the role of miR-98 in rat embryo implantation remains elusive. Here, we found that the level of miR-98 is lower on day 5 and 6 of gestation (g.d. 5-6) than that on g.d. 3-4 and g.d. 7-8 in rat. MiR-98 expression is significantly decreased by delayed implantation. Down-regulation of miR-98 promotes ESC proliferation and inhibits apoptosis. Up-regulation of miR-98 displays opposite effects. Further investigation revealed that miR-98 can bind to the 3'-untranslated region (3'-UTR) of B-cell lymphoma-extra large (Bcl-xl) to inhibit Bcl-xl translation. Collectively, down-regulation of miR-98 in rat uterus during the receptive phase is linked to the increase of cell proliferation via targeting Bcl-xl.

[Analysis of population stratification using random SNPs in genome-wide association studies].

Since population genetic STRUCTURE can increase false-positive rate in genome-wide association studies (GWAS) for complex diseases, the effect of population stratification should be taken into account in GWAS. However, the effect of randomly selected SNPs in population stratification analysis is underdetermined. In this study, based on the genotype data generated on Genome-Wide Human SNP Array 6.0 from unrelated individuals of HapMap Phase2, we randomly selected SNPs that were evenly distributed across the whole-genome, and acquired Ancestry Informative Markers (AIMs) by the method of f value and allelic Fisher exact test. F-statistics and STRUCTURE analysis based on the select different sets of SNPs were used to evaluate the effect of distinguishing the populations from HapMap Phase3. We found that randomly selected SNPs that were evenly distributed across the whole-genome were able to be used to identify the population structure. This study further indicated that more than 3 000 randomly selected SNPs that were evenly distributed across the whole-genome were substituted for AIMs in population stratification analysis, when there were no available AIMs for spe-cific populations.

[Standardization for sharing and utilization of Chinese genetic resources].

National Infrastructure of Chinese Genetic Resources is a part of National Infrastructure of Natural Resources for Science and Technology. To strengthen and standardize the collection, integration, conservation, sharing and utilization of Chinese Genetic Resources, we have been carrying out the research on standardization of trimming, integration and sharing of Chinese Genetic Resources, according the advanced experiences abroad on that and abiding by the related laws and regulations. In the paper, National Infrastructure of Chinese Genetic Resources will be introduced on the standardization of integration, database construction and sharing of Chinese Genetic Resources.