Influence of donor age on induced pluripotent stem cells

Abstract

Induced pluripotent stem cells (iPSCs) are being pursued as a source of cells for autologous therapies, many of which will be aimed at aged patients. To explore the impact of age on iPSC quality, we produced iPSCs from blood cells of 16 donors aged 21-100. We find that iPSCs from older donors retain an epigenetic signature of age, which can be reduced through passaging. Clonal expansion via reprogramming also enables the discovery of somatic mutations present in individual donor cells, which are missed by bulk sequencing methods. We show that exomic mutations in iPSCs increase linearly with age, and all iPSC lines analyzed carry at least one gene-disrupting mutation, several of which have been associated with cancer or dysfunction. Unexpectedly, elderly donors (>90 yrs) harbor fewer mutations than predicted, likely due to a contracted blood progenitor pool. These studies establish that donor age is associated with an increased risk of abnormalities in iPSCs and will inform clinical development of reprogramming technology.

Figure 1. Study overview and epigenetic analyses

A) Left, graph shows the age distribution of donors. Circles represent the number of iPSC lines generated from each individual. Black bars and circles indicate samples used for both epigenetic and exomic analyses. Gray lines indicate additional samples used for somatic mutation detection. Right, schematic of the study design. PBMCs from donors were isolated, expanded and reprogrammed with episomal reprogramming factors. Three iPSC lines per donor were characterized. Unexpanded PBMCs and iPSCs were subjected to exome sequencing and DNA methylation analysis. B) Donor age is strongly correlated with predicted age based on PBMC methylation (left panel) (R² = 0.96, p-value = 6.4·10-8). The predicted age of iPSCs is weakly but significantly correlated with donor age (right panel) (R² = 0.38, p-value = 0.04). Each filled circle represents the average predicted age of three iPSCs per individual; the vertical line is standard error. The dashed line is the linear best fit across all individuals. C) The difference in average methylation levels between elderly and young donors is plotted for CpG sites previously reported to predict age (CpGs that increase in methylation with age on the left; CpGs that decrease in methylation with age on the right). In PBMCs, CpG sites expected to increase in methylation with age (left) show an average increase of methylation in elderly individuals (average of left PBMC plot = 0.09), and CpG sites expected to decrease in methylation with age (right) show an average decrease in of methylation in elderly individuals (average of right PBMC plot = −0.17). On the other hand, in iPSCs, both CpG sites expected to increase (left) and decrease (right) in methylation with age show an average increase of methylation in elderly individuals (average of left iPSC plot = 0.04, average of right iPSC plot = 0.01). Visually, there is a clear dissimilarity in the distribution of the methylation differences at age-related CpG sites in in PBMCs vs iPSCs – with age-related CpG sites displaying two different distributions of methylation differences in PBMCs derived from young vs old donors whereas age-related CpG sites uniformly display increased methylation levels in iPSCs derived from older donors. D) Heat map displaying the methylation status of all CpG sites found to be significantly resistant to demethylation in older individuals compared to younger donors (blue, high, red, low). iPSCs are ordered by the age of donor. CpG sites are clustered based on their methylation pattern across individuals. Genes are labeled on the right side. E) DNA methylation profiles for selected iPSC lines were analyzed at early/intermediate and late passages. The methylation status of six CpG sites is plotted with black circle representing M-value for iPSCs at early passage and red triangle M-value for late passage in selected iPSC lines. The right side shows three CpG sites that correlate with age at early passage, whose methylation is restored after passaging (red linear regression). GJA1 (early passage R² (eR²)= 0.44 p-value < 0.0001; late passage R² (lR²)= 0.043 p-value=0.36), WASL (eR²= 0.45 p-value < 0.0001; lR²= 0.094 p-value = 0.17), ULK4 (eR²= 0.53 p-value < 0.0001; lR²= 0.042 p-value = 0.37). The left part show three CpG that maintained a significant correlation with age, independent of passage TEAD3 (eR²= 0.51 p- value < 0.0001; lR²= 0.54 p-value = 0.0001 ), ZNF217 (eR² = 0.45 p-value<0.0001; (lR²)= 0.45 p-value = 0.0008), ADGRL4 (eR² = 0.47 p-value<0.0001; (lR²)= 0.45 p-value = 0.0009). Pearson correlation with two-tailed p-value.

Figure 2. Somatic Mutations in iPSCs

A) The number of somatic mutations per iPSC line per individual is plotted vs. donor age. Each point represents the average number of somatic ?7 mutations observed in three iPSC lines from one individual. A standard error bar intersects each point. The dashed line represents a linear best fit across all individuals (R² = 0.38, p-value = 0.0011) and the dotted line represents a linear best fit across all individuals younger than 90 yrs (R² = 0.63, p-value < 0.0001). Lines from donors over 90 years old are red. B) The fraction of all identified somatic mutations that were either missense or nonsense is plotted against donor age. Each data point represents the average fraction of somatic coding mutations observed in three iPSC lines per individual. A standard error bar intersects each point. The dashed line represents a linear best fit across all individuals (R² = 0.004, p-value = 0.34). C) The number of somatic mutations is plotted against the coverage per iPSC line. No relationship was observed (R² = 0.002, p-value = 0.38). D) The proportion of somatic mutations that are nucleotide transitions (black circles) vs. transversions (grey squares) is plotted relative to donor age. Each data point represents the average fraction of somatic mutations that are transitions or transversions in the three iPSC lines per individual. A standard error bar intersects each point, representing the variation in somatic mutations per iPSC line in each individual. The dotted lines displays a LOESS curve fit across transition and transversion proportion averages. E) The average level of somatic mosaicism in PBMC samples as determined by deep amplicon sequencing of randomly selected somatic mutations observed in the derived iPSC samples is plotted against donor age. Each data point represents the average level of somatic mosaicism observed per individual based on three somatic mutations per donor. A standard error bar intersects each point, representing the variation in the level of somatic mosaicism per donor. The dashed line represents a linear best fit across all individuals (R² = 0.66, p-value = 0.028). F) Schematic of a model that can explain the apparent reduction in somatic mutations in iPSCs derived from the oldest donors (>90 years old). In this model, few mutations (x’s) are present in all cells of younger donors. Then in middle age the rapidly dividing cells (light grey) accumulate mutations. At very old ages, these cells disappear and smaller number of slowly dividing progenitors (darkest grey) with fewer mutations contribute to the PBMC population.