Neonatal Encephalopathy Multi-Omic Data from South African Cohort

Carina C. Babbo's figshare dataset contains clinical and molecular data from a multi-center observational study on neonatal encephalopathy. The 5.5 KB XLS file integrates whole genome sequencing, DNA methylation, RNA-seq, proteomics, metabolomics, and placental microbiome data from neonates with hypoxic-ischaemic encephalopathy and healthy controls. The dataset was last updated in April 2026.

Use Cases

• Identify clinical risk factors associated with NESHIE by analyzing integrated clinical data columns.
• Detect genetic variants linked to disease susceptibility using whole genome sequencing data.
• Analyze DNA methylation patterns from bisulfite sequencing to study epigenetic regulation.
• Assess differential gene expression between patient and control groups using bulk and single-cell RNA-seq data.
• Characterize proteomic and metabolomic profiles from dried blood spot samples via liquid chromatography–mass spectrometry data.

Strengths

• Dataset integrates seven distinct molecular data types: genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome, and histopathology.
• Multi-center design with ethics approvals from three South African universities and their hospitals.
• Data is shared under a permissive CC-BY-4.0 license.

Limitations

• The dataset is extremely small at 5.5 KB, suggesting it may contain only summary metadata or a very limited sample subset.
• Specific sample sizes, row counts, and column names for clinical and molecular features are not provided.
• Geographic scope is limited to a South African cohort, which may limit generalizability.

Provenance

Source

Carina C. Babbo via figshare.

Collection Method

Multi-center observational study recruiting neonates with moderate to severe NESHIE and healthy term controls.

Time Range

null

Freshness

Last updated in April 2026, indicating planned future data releases.

Geography

South Africa (Gauteng and Western Cape provinces).