Aging and neurodegeneration are associated with increased mutations in single human neurons

Abstract

It has long been hypothesized that aging and neurodegeneration are associated with somatic mutation in neurons; however, methodological hurdles have prevented testing this hypothesis directly. We used single-cell whole-genome sequencing to perform genome-wide somatic single-nucleotide variant (sSNV) identification on DNA from 161 single neurons from the prefrontal cortex and hippocampus of 15 normal individuals (aged 4 months to 82 years), as well as 9 individuals affected by early-onset neurodegeneration due to genetic disorders of DNA repair (Cockayne syndrome and xeroderma pigmentosum). sSNVs increased approximately linearly with age in both areas (with a higher rate in hippocampus) and were more abundant in neurodegenerative disease. The accumulation of somatic mutations with age-which we term genosenium-shows age-related, region-related, and disease-related molecular signatures and may be important in other human age-associated conditions.

Figure 1. Detection of sSNVs across individuals and brain regions using single-neuron WGS and linkage-based analysis

(A) Experimental outline. (B) Schematic of linkage-based mutation calling. A somatic mutation (red) may occur on one allele of a locus (Locus 1), potentially in close proximity to a germline heterozygous site (orange and blue), while other loci, such as Locus 2, remain unmutated. Later amplification errors could create a mismatch (yellow) on one strand of one allele of Locus 2 near a germline variant (purple). For Locus 1, any WGS read that covers both sites and contains the germline (orange) variant should also contain the somatic (red) variant, thus these variants are perfectly linked. In contrast, at Locus 2 some but not all reads that cover the relevant germline variant (purple) will contain the somatic “variant” candidate (yellow), generating two classes of reads, some with the somatic variant on that allele, some without. Only perfectly linked sSNV candidates were considered in this study.

Figure 2. sSNVs increase with age in the PFC and DG, and are elevated in CS and XP

(A) sSNV counts plotted against age for neurons derived from PFC (circles) and DG (triangles), with linear regression lines. There is a strong correlation with age in both cases, with the rate of accumulation being nearly two-fold higher in the DG than in the PFC. (B) Comparison of sSNV counts in matched PFC and DG within brains. (C) CS and XP patient neurons display elevated sSNV counts. * denotes p < 0.05 for B and C. (D, E) Fraction of sSNVs comprised of C>T (D) and T>C (E). *, **, and *** denote p ≤ 0.05, 0.001, and 0.0001, respectively, using 2-way ANOVA with Sidak’s correction.

Figure 3. Signature analysis reveals mutational processes during aging, across brain regions, and in disease

(A) Three mutational signatures identified by non-negative matrix factorization (each substitution is classified by its trinucleotide context). (B) Number of variants from Signatures A, B, and C in each of the 161 neurons in the dataset. (C–E) Signature A strongly correlates with age, regardless of disease status or brain region, while Signatures B and C do not. (F) Signature B is enriched in DG relative to PFC neurons. (G) Signature B increased with age in DG neurons, but not in matched PFC neurons, revealing a DG-specific aging signature. Solid shapes represent regional means, and transparent shapes represent individual neurons. (H–I) Comparison of age-corrected estimate of sSNVs per signature in CS and XP compared to PFC controls revealed enrichment in Signature C in both CS and XP. * and ** denote p ≤ 0.05 and p ≤ 0.001, respectively, mixed linear model.