A study published in Cell (2024) compared somatic mutation patterns in aging human neurons and oligodendrocytes (OLs). Using whole-genome sequencing (WGS) of 86 single OLs, 20 mixed glia, and 56 single neurons from individuals aged 0.4–104 years, the researchers identified over 92,000 somatic single-nucleotide variants (sSNVs) and small insertions/deletions (indels). OLs accumulated sSNVs 81% faster than neurons and indels 28% slower. Mutation analysis revealed that OL mutations were enriched in inactive genomic regions and distributed similarly to mutations in brain cancers, while neuronal mutations were enriched in open, transcriptionally active chromatin. These differences suggest distinct mutagenic processes in OLs and neurons. The study used single-cell WGS, integrated with single-nucleus RNA-seq and ATAC-seq data, to uncover distinct aging-related patterns of somatic mutation in human OLs and neurons. OLs showed higher sSNV accumulation rates and lower indel accumulation rates compared to neurons. Mutational signatures indicated shared and cell-type-specific mechanisms, with OLs showing a stronger association with cell proliferation and aging signatures, while neurons were more associated with transcriptional activity. OL mutations were enriched in inactive chromatin, whereas neuronal mutations were enriched in transcriptionally active regions. The study also found that OL mutations resembled those in glial-derived tumors, suggesting a potential link to cancer initiation. OL mutations were more prevalent in transcriptionally inactive and/or inaccessible chromatin, similar to patterns seen in cancer. Neuronal mutations, in contrast, were enriched in transcriptionally active regions. The study highlights the importance of understanding cell-type-specific mutational processes in aging and disease. OLs accumulate mutations at higher rates than neurons, with distinct mutational signatures and genomic distributions. These findings contribute to a deeper understanding of the mechanisms involved in human brain aging and may have implications for age-related, cell-type-specific pathologies in the human brain.A study published in Cell (2024) compared somatic mutation patterns in aging human neurons and oligodendrocytes (OLs). Using whole-genome sequencing (WGS) of 86 single OLs, 20 mixed glia, and 56 single neurons from individuals aged 0.4–104 years, the researchers identified over 92,000 somatic single-nucleotide variants (sSNVs) and small insertions/deletions (indels). OLs accumulated sSNVs 81% faster than neurons and indels 28% slower. Mutation analysis revealed that OL mutations were enriched in inactive genomic regions and distributed similarly to mutations in brain cancers, while neuronal mutations were enriched in open, transcriptionally active chromatin. These differences suggest distinct mutagenic processes in OLs and neurons. The study used single-cell WGS, integrated with single-nucleus RNA-seq and ATAC-seq data, to uncover distinct aging-related patterns of somatic mutation in human OLs and neurons. OLs showed higher sSNV accumulation rates and lower indel accumulation rates compared to neurons. Mutational signatures indicated shared and cell-type-specific mechanisms, with OLs showing a stronger association with cell proliferation and aging signatures, while neurons were more associated with transcriptional activity. OL mutations were enriched in inactive chromatin, whereas neuronal mutations were enriched in transcriptionally active regions. The study also found that OL mutations resembled those in glial-derived tumors, suggesting a potential link to cancer initiation. OL mutations were more prevalent in transcriptionally inactive and/or inaccessible chromatin, similar to patterns seen in cancer. Neuronal mutations, in contrast, were enriched in transcriptionally active regions. The study highlights the importance of understanding cell-type-specific mutational processes in aging and disease. OLs accumulate mutations at higher rates than neurons, with distinct mutational signatures and genomic distributions. These findings contribute to a deeper understanding of the mechanisms involved in human brain aging and may have implications for age-related, cell-type-specific pathologies in the human brain.