Multicenter Analysis of Genomic and Metabolic Data of Neonatal Genetic Diseases
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 40,000
- 试验地点
- 1
- 主要终点
- Number of gene sequencing data in neonatal gene bank
研究概览
简要总结
object name: Multicenter analysis of genomic and metabolic data of neonatal genetic diseases.
goal of study:(1) Gene sequencing data (138 genes related to 133 common genetic diseases) and tandem mass spectrometry metabolomics data (11 amino acids and 28 acylcarnitines) of about 40,000 newborns from the South China Neonatal Genetic Screening Alliance participating units were collected and collated to complete the database construction of genes and mass spectrometry.
(2) Explore the use of genome and metabolome big data and machine learning algorithms such as Random forest, Support Vector Machine, Elastic net, Multilayer Perceptron to construct prediction models for common genetic diseases, and strive to achieve accurate diagnosis and prediction of common genetic diseases using simple tandem mass spectrometry metabolome data, and expand the application range of tandem mass spectrometry technology for disease detection.
research design:retrospective observational study Research period:September 2022 to December 2025 Participating units:South China Neonatal genetic screening Alliance (including cooperation units of 123 hospitals) research object:Gene screening data of 40,000 newborns ( 138 genes related to 133 common genetic diseases ) and tandem mass spectrometry data ( 11 amino acids and 28 acylcarnitines ).
Inclusion criteria:( 1 ) Newborns who underwent genetic screening and tandem mass spectrometry at the same time. ( 2 ) Age : 0-28 days, gestational age 37-42 weeks.
Excluded criteria:Data that meets any of the following conditions need to be eliminated : ( 1 ) Neonatal data with unclear clinical basic information ; ( 2 ) Lack of traceability core information data ; ( 3 ) The data that the test results cannot be analyzed and interpreted.
data collection:( 1 ) Basic information : gender, age, sample type, subject traceability number / ID number, etc. ( 2 ) Clinical symptoms, biochemical and imaging data of positive samples. ( 3 ) Gene detection results and tandem mass spectrometry results. ( 4 ) Date of test data, instrument model, reagent type, etc.
详细描述
Research Design: This study is a multi-center cooperative study of the South China Neonatal Genetic Screening Alliance. The principal investigator ( PI ) and project leader of this study are Hao Hu, chief physician of pediatrics of the Sixth Affiliated Hospital of Sun Yat-sen University, who plans to include 123 cooperative units of the South China Neonatal Genetic Screening Alliance. In this study, 40,000 neonatal genetic screening data and MS / MS data were retrospectively analyzed through multi-center cooperation. The collection date was from January 2019 to August 2022.
Through the statistical analysis of neonatal genetic screening data ( 138 genes related to 133 common genetic diseases ), the incidence of common genetic diseases in newborns in China, the carrying rate of pathogenic variation and the high-frequency variation sites of the population were clarified, and the epidemiological characteristics of newborns in China were studied.
Through the statistical analysis of neonatal genetic screening data and MS / MS metabolomics data ( 11 amino acids and 28 acylcarnitines ), the correlation between gene and metabolism will be explored, and the pathogenicity of high-frequency VUS mutation sites will be identified by using protein function artificial intelligence analysis platform and tandem mass spectrometry metabolite data.
The prediction model of common genetic diseases is constructed by using machine learning algorithms such as random forest, support vector machine, elastic network and multi-layer perceptron, so as to realize the accurate diagnosis of common genetic diseases through tandem mass spectrometry metabolomics data, and expand 2-3 kinds of diseases that can be detected by MS / MS technology.
Sample size: This study plans to collect genetic screening data ( 138 genes related to 133 common genetic diseases ) and tandem mass spectrometry metabolomics data ( 11 amino acids and 28 acylcarnitines ) of about 40,000 newborns from January 2019 to August 2022 in 123 cooperative units of the South China Neonatal Genetic Screening Alliance.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 1 Day 至 28 Days（Child）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Age 1-28 days
- •gestational age 37-42 weeks
排除标准
- •Neonatal data with unclear clinical basic information
- •Lack of traceability core information data
- •The data that the test results cannot be analyzed and interpreted
结局指标
主要结局
Number of gene sequencing data in neonatal gene bank
时间窗: From birth to completion of genetic screening, the process last up to 3 months.
Each newborn that was sequenced was counted as 1. Keep all the data in the gene bank, and finally calculate the number of completed gene sequencing data.
Gene mutation rate
时间窗: From birth to completion of genetic screening, the process last up to 3 months.
Taking the number of newborn babies as denominator and the number of neonates with gene mutation detected in gene sequencing as molecules, the whole neonatal gene mutation rate in China was obtained.
次要结局
未报告次要终点
研究者
HaoHu
Project leader
Sixth Affiliated Hospital, Sun Yat-sen University