Multicenter Analysis of Genomic and Metabolic Data of Neonatal Genetic Diseases

Study Overview
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Brief Summary
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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.

Detailed Description
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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 ) A retrospective analysis of the incidence, pathogenic mutations, suspected pathogenic mutations, and the carrying rate of unexplained mutations of 133 common neonatal genetic diseases in 40,000 cases was conducted, and the distribution of high-frequency variation sites in the population was counted, providing a scientific basis for the selection of mutation sites for large-scale genetic screening of neonatal genetic diseases. ( 3 ) Protein function prediction and enzyme catalytic activity analysis were performed on high-frequency mutation sites of genetic metabolic diseases ( IEM ). Characteristic metabolites were analyzed and verified for mutation sites with low enzyme catalytic activity. The feasibility of using protein function artificial intelligence analysis platform and tandem mass spectrometry metabolite data to accurately predict the pathogenicity of genetic metabolic lesions was explored. ( 4 ) 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. sample size:Gene screening and tandem mass spectrometry data of 40,000 newborns. 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. Statistical processing:IBM-SPSS 26.0 statistical software was used to analyze the test results. Logistic regression analysis was used to evaluate the correlation between genotype and clinical phenotype. Generalized multifactor dimensionality reduction method was used to analyze gene-gene interaction and genotype-phenotype correlation. Based on tandem mass spectrometry data, machine learning algorithms such as random forest, support vector machine, elastic network, and multi-layer perceptron were used to construct a genotype prediction model. The prediction effect of the model was evaluated by accuracy, balance accuracy, sensitivity, and specificity.

Official Title
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Multicenter Analysis of Genomic and Metabolic Data of Neonatal Genetic Diseases

Conditions
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Hereditary Diseases

Intervention / Treatment
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* Genetic: Genomic sequencing


Participation Criteria
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Eligibility Criteria
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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. Exclusion 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.

Ages Eligible for Study
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Maximum Age: 28 Days

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Sick Neonatal Cohort<br>Infants and their parents enrolled through Neonatal Intensive Care Unit of member hospitals who are un-randomized to receive genomic sequencing. Results disclosure sessions will include a discussion of: family history report, results from standard newborn screening, any potentially medically relevant findings from the baby&#39;s medical history/physical exam, and the results of the genomic sequencing report. | Genetic: Genomic sequencing<br>* Both sick and high-risk newborn un-randomized to receive genomic sequencing will receive a Genomic Newborn Sequencing Report which will include pathogenic or likely pathogenic variants identified in genes associated with childhood-onset disease.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Number of gene sequencing data in neonatal gene bank | 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. | From birth to completion of genetic screening, the process last up to 3 months. | 
| Gene mutation rate | 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. | From birth to completion of genetic screening, the process last up to 3 months. | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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neonatal genetic diseases, Defect, Newborn