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Application of Transcriptome Sequencing Combined With Family-Based Whole Genome Sequencing in Improving Precise Diagnosis of Critically Ill Newborns in Northeast China

J

Jilin University

Status

Not yet enrolling

Conditions

Necrotizing Enterocolitis

Treatments

Genetic: Whole genome sequencing analysis

Study type

Observational

Funder types

Other

Identifiers

NCT06990334
25K160-001

Details and patient eligibility

About

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.

Enrollment

1,000 estimated patients

Sex

All

Ages

1 to 28 days old

Volunteers

No Healthy Volunteers

Inclusion criteria

Critically ill newborns under the age of 3 months. Suspected of having a genetic disease based on clinical manifestations (such as abnormal phenotypes) or family history.

Parents or legal guardians provide informed consent to participate in the study and agree to undergo rapid/ultra-rapid WGS sequencing. In cases of negative results, further transcriptome sequencing will be conducted.

Exclusion criteria

The principal investigator deems the participant unsuitable for the study. Diseases caused by pregnancy, perinatal infection, ischemia, hypoxia, and other non-genetic factors.

Inability to fully cooperate with the study, affecting data integrity. The child already has a genetic diagnosis that fully explains the disease onset.

Trial design

1,000 participants in 1 patient group

Newborns suspected of having a genetic disease based on clinical manifestations
Treatment:
Genetic: Whole genome sequencing analysis

Trial contacts and locations

0

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Central trial contact

Hui Wu The first hospital of Jilin university

Data sourced from clinicaltrials.gov

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