Transcriptomic aging clock and GWAS analysis of brain samples in opioid dependence
An in silico analysis of brain samples reported altered age-related transcriptional states in opioid dependence, with immune and inflammatory pathways, neuronal signaling genes and two genes linked to age-prediction residuals. [1]
Automatic summary · not editorially reviewed
The key findings
The in silico study combined transcriptomic profiling, transcriptomic aging clock modeling and GWAS analysis of brain samples to investigate mechanisms associated with opioid dependence. [1]
The aging clock showed moderate predictive performance (r=0.686, MAE=5.16) and significant differences in age-prediction residuals between younger and older groups. [1]
An analysis of six GWAS studies identified 223 SNP associations, including genome-wide significant variants in genes implicated in neuronal signaling and opioid pharmacology. [1]
The source at a glance
- Study type / format
- In silico transcriptomic, aging clock and GWAS analysis (abstract)
- Population / context
- Brain samples from individuals with opioid dependence, analyzed in silico
- Summary based on
- Study abstract
- Original publication
- July 27, 2026
Brain samples, aging clock and GWAS in opioid dependence
This in silico study combined transcriptomic profiling, transcriptomic aging clock modeling and GWAS analysis of brain samples to examine molecular mechanisms associated with opioid dependence. The authors describe opioid dependence as a complex disorder influenced by multiple factors, including aging and genetic factors, whose molecular mechanisms remain incompletely understood.
Supporting source [1]
DEGs, hub genes and age-prediction residuals
The analysis identified 161 differentially expressed genes, 147 upregulated and 14 downregulated, involved in immune and inflammatory pathways such as TNF signaling. Network centrality analysis highlighted CCL2, CD44, THBS1, TIMP1, CD163, IL6, IL1B and MYC as potential hub genes. FAM174B was downregulated in older individuals with opioid dependence, whereas ZNF256 was upregulated in younger individuals. The aging clock showed moderate predictive performance (r=0.686, MAE=5.16) and significant differences in age-prediction residuals between younger and older groups, suggesting altered age-related transcriptional states. PHYH and LUCAT1 were strongly associated with these residuals.
Supporting source [1]
GWAS variants and scope of the abstract
An analysis of six GWAS studies identified 223 SNP associations, including genome-wide significant variants in ADGRV1, OPRM1, CNIH3, RGMA, GPRIN3, GAPDHP15, SRP72P1 and CTCF-DT genes implicated in neuronal signaling and opioid pharmacology. Together, the findings highlight immune pathways, neuronal signaling and aging-related molecular processes as key components of opioid dependence. These are associations from an in silico analysis, not evidence of cause or of clinical benefit.
Supporting source [1]
How to interpret this
Abstract only; the full text was not reviewed. This is an in silico analysis of brain samples, and the reported gene, pathway and variant findings are associations, not evidence of causation or clinical benefit.
Based on the study abstract; the full paper, tables and supplementary data were not reviewed.
Source & supporting passages
Nguyen HD, McRae MP, Kim S, Kim WK. · europepmc.org · July 27, 2026