Brain RNA profiling highlights multiple disease pathways in persons with HIV-associated neurocognitive disorder

Area of Science:

• Neuroscience
• Virology
• Genomics
• Machine Learning

Background:

• HIV-associated neurocognitive disorder (HAND) presents significant neurological challenges.
• Understanding the molecular mechanisms underlying HAND is crucial for effective treatment.
• Dysregulation of RNA expression and microRNA (miRNA) interactions may play a role in HAND pathogenesis.

Purpose of the Study:

• To identify microRNA (miRNA)-RNA transcript interactions dysregulated in the brains of individuals with HAND.
• To investigate host RNA expression patterns in different HIV clinical groups using advanced computational tools.
• To uncover potential molecular targets and pathways implicated in HAND pathogenesis.

Main Methods:

• Analysis of brain-derived host RNA transcript and miRNA expression from individuals with and without HAND using bioinformatics.
• Integration of next-generation sequencing, droplet digital PCR for HIV-1 quantitation, and statistical analyses.
• Application of machine learning algorithms to identify key miRNA-RNA transcript interactions associated with differential gene expression.

Main Results:

• Significant differential expression of 147 transcripts and 43 miRNAs was observed across clinical groups.
• Antiviral signaling (type I interferon), neural cell maintenance, and neurodevelopmental pathways were predominantly affected.
• Machine learning identified miR-4683 and miR-154-5p as dominant miRNAs associated with host RNA expression changes in HAND.

Conclusions:

• Brain-specific antiviral and neurodevelopmental pathways are associated with HAND.
• Correlated RNA transcripts and miRNAs provide insights into the molecular underpinnings of HAND.
• Integrated molecular and machine learning approaches offer a promising direction for understanding and potentially treating HAND.