Background: Birth defects and genetic diseases are major threats to infant health. Many genetic diseases present atypically in newborns, who often have critical conditions, rapid progression, and high mortality. Early diagnosis is crucial but challenging. While next-generation sequencing (NGS) technologies like whole genome sequencing (WGS) and whole exome sequencing (WES) have significantly advanced genetic disease diagnosis, conventional WES/WGS has a long detection cycle. Rapid/ultra-rapid sequencing technologies (rWES/urWES, rWGS/urWGS) offer far-reaching clinical value. Study Objective: This study aims to explore the application of transcriptome sequencing in clinically diagnosing neonatal genetic diseases with negative rWGS results, improve diagnostic rates, assist in early determination of disease causes, provide genetic counseling, and achieve targeted, personalized treatment guidance and prognosis evaluation. Study Design: This is a multi-center cohort study led by the First Hospital of Jilin University, involving at least five clinical medical institutions. The planned sample size is 1,000 cases over three years. The study will include critically ill newborns under three months old, suspected of having genetic diseases based on clinical manifestations or family history, with informed consent from parents or legal guardians. Methods: The study will conduct RNA-seq and joint analysis on 1,000 critically ill newborns with negative family-based rWGS results. The goal is to improve the interpretation of variants of uncertain significance (VUS) and the gene-positive diagnostic rate. It will accumulate disease research big data and conduct integrative genomic analyses based on Pathway and protein-protein interaction (PPI) networks to discover potential new molecular genetic mechanisms and guide new treatment developments. Data Management: Data will be promptly, completely, accurately, and clearly recorded in case report forms and entered into a database system. Data verification, cleaning, and archiving will follow strict procedures to ensure data quality and integrity. Data Analysis: Bioinformatics analysis of sequencing data will include quality control, data filtering, sequence alignment, mutation annotation, variant screening, single-gene mode analysis, and joint transcriptome analysis. Statistical analysis will follow traditional clinical trial methods, with a focus on controlling biases and confounding factors.
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Whole genome sequencing analysis
Timeframe: 2025.6.1-2028.12.31