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Comparative Study
. 2021 Jan 1;206(1):101-108.
doi: 10.4049/jimmunol.2000576. Epub 2020 Dec 7.

Sex-Biased Aging Effects on Ig Somatic Hypermutation Targeting

Affiliations
Comparative Study

Sex-Biased Aging Effects on Ig Somatic Hypermutation Targeting

Ang Cui et al. J Immunol. .

Abstract

Aged individuals, particularly males, display an impaired level of Ab response compared with their younger counterparts, yet the molecular mechanisms responsible for the discrepancy are not well understood. We hypothesize that some of this difference may be linked to B cell somatic hypermutation (SHM) targeting, including error-prone DNA repair activities that are crucial to Ab diversification. To examine the effects of aging on SHM targeting, we analyzed B cell Ig repertoire sequences from 27 healthy male and female human subjects aged 20-89. By studying mutation patterns based on 985,069 mutations obtained from 123,415 sequences, we found that the SHM mutability hierarchies on microsequence motifs (i.e., SHM hot/cold spots) are mostly consistent between different age and sex groups. However, we observed a lower frequency in mutations involving Phase II SHM DNA repair activities in older males, but not in females. We also observed, from a separate study, a decreased expression level of DNA mismatch repair genes involved in SHM in older individuals compared with younger individuals, with larger fold changes in males than in females. Finally, we showed that the balance between Phase I versus Phase II SHM activities impacts the resulting Ig phenotypes. Our results showed that the SHM process is altered in some older individuals, providing insights into observed clinical differences in immunologic responses between different age and sex groups.

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Figures

Figure 1:
Figure 1:. SHM mutability hierarchy on micro-sequence motifs is consistent across age and sex groups.
A) SHM targeting model for each age and sex group. Hedgehog plots depict the relative targeting of 5-mer motifs centered on the bases A, T, C, and G, with each center base in an individual circle. Classic hot spots are colored in red (WRC/GYW) and green (WA/TW), whereas cold spots are colored in blue (SYC/GRS). B) Scatterplot of 5-mer mutabilities between each age and sex group built on silent mutations in functional sequences. C) Scatterplot of 5-mer mutabilities between each age and sex group built on all mutations in non-functional sequences. Each dot represents the mutability value of a 5-mer motif. R denotes Spearman correlation coefficient.
Figure 2:
Figure 2:. Older males display a lower level of A/T mutability in SHM.
A/T mutability was calculated by normalizing frequency of unselected mutations occurring on A or T nucleotides by frequency of A or T bases in germline immunoglobulin sequences for each individual in the AIRR-seq dataset. Unselected mutations were obtained from silent mutations in functional sequences (Functional) or all mutations in non-functional sequences (Non-functional). Boxes represent the median and interquartile range of A/T mutabilities in each age and sex group. The analysis was performed in all three technical replicates: RNA (left panels), DNA-GC (middle panels), DNA-Roche (right panels). p-values were obtained from Welch’s t-test.
Figure 3:
Figure 3:. Older males display a decrease in the expression of DNA repair genes involved in SHM.
Log transformed expressions of SHM-repair genes with high detection levels in the gene expression dataset (described in Materials and Methods). Housekeeping genes were included as a control. Boxes represent the median and interquartile range of gene expressions in each age and sex group. p-values were obtained from Welch’s t-test.
Figure 4:
Figure 4:. Changes in somatic hypermutation targeting affects immunoglobulin phenotype.
Comparison between A/T mutability found in non-functional sequences (reflecting intrinsic SHM targeting biases) and the proportion of amino acid substitutions that are exclusively caused by A/T nucleotide changes in functional sequences (reflecting properties of amino acid sequences encoding functional BCRs) in the AIRR-seq dataset. Each point represents an individual; their corresponding age group is indicated by shade and sex group is indicated by shape. The analysis was performed in all three technical replicates: RNA (shown here), DNA-GC and DNA-Roche (Figure S4).

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