Transcriptomic aging clock analysis identifies key genes in opioid dependence
Hai Duc Nguyen1, Mary Peace McRae2, Sangkyu Kim3
1Division of Microbiology, Tulane National Biomedical Research Center, Tulane University, Covington, LA 70433, USA.
Aging
|July 29, 2026
Summary
This study reveals key molecular mechanisms in opioid dependence, highlighting immune pathways, neuronal signaling, and aging-related gene expression changes. Findings point to specific genes and genetic variants involved in this complex disorder.
Area of Science:
- Genomics and Molecular Biology
- Neuroscience
- Aging Research
Background:
- Opioid dependence is a complex condition with poorly understood molecular underpinnings.
- Aging and genetic factors significantly influence opioid dependence.
- Investigating molecular mechanisms is crucial for understanding and treating opioid dependence.
Purpose of the Study:
- To elucidate the molecular mechanisms of opioid dependence by integrating transcriptomic, aging clock, and GWAS data.
- To identify key genes, pathways, and genetic variants associated with opioid dependence.
- To explore the interplay between aging and molecular alterations in opioid dependence.
Main Methods:
- In silico analysis combining transcriptomic profiling, transcriptomic aging clock modeling, and Genome-Wide Association Studies (GWAS) on brain samples.
- Differential gene expression analysis to identify genes altered in opioid dependence.
- Network centrality analysis to pinpoint hub genes and GWAS analysis to identify significant single nucleotide polymorphism (SNP) associations.
Main Results:
- 161 differentially expressed genes (DEGs) were identified, predominantly involved in immune and inflammatory pathways (TNF signaling).
- Key hub genes including CCL2, CD44, THBS1, TIMP1, CD163, IL6, IL1B, and MYC were highlighted.
- Transcriptomic aging clock analysis revealed altered age-related transcriptional states in opioid dependence, with genes like PHYH and LUCAT1 associated with age-prediction residuals. GWAS identified significant variants in genes such as ADGRV1 and OPRM1.
Conclusions:
- Immune pathways, neuronal signaling, and aging-related molecular processes are critical components of opioid dependence.
- Specific genes and genetic variants identified may serve as potential targets for understanding and treating opioid dependence.
- The study underscores the complex interplay between aging, genetics, and molecular alterations in the pathophysiology of opioid dependence.
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