I was able to get the full text of the 2013 paper and take a closer look.
One thing to note is that these studies all involve mitochondrial DNA, not nuclear DNA. There is far less mitochondrial DNA than nuclear DNA in any cell and it is much more difficult to isolate, extract and work with.
Sample Amount The first sensitive 2013 latest and gretaest paper you cite uses 500-800 mg brain tissue from each subject. Well over half a gram of tissue. An average pea weighs 0.1-0.3 grams, so they used 2-8 peas worth of solid tissue to perform the test. Blood is 55% plasma by volume and 45% cells. So, you'd need 4-16 "peas" worth of blood to get the equivalent number of cells. However, the vast majority of these cells are red blood cells which do not have any nuclei or mitochondria. White blood cells (leukocytes) and platelettes are the only things in the cellular blood fraction that have mitochondria. There are only 1 white blood cell and forty platelets for every 600 red blood cells. (Source). So, only 41 out of 641 blood cells will have nuclei or mitochondria to test or 0.06% (of the 45% of blood that has any cells at all). So, now we're looking at 67-267 peas worth of blood to get the equivalent amount of cells containing mitochondria. (This back of the envelope calculation neglects things like cell size, and the relative densities of peas and brain, but should be sufficient to illustrate that much more blood is needed to get a similar amount of mitochondrial DNA. "pea" was chosen as a convenient unit of measurement for size visualization, since most of us would have difficulty visualizing the size of 500 mg of brain).
Mutation Rate - Per the paper, the mitochondrial genome is 16,569 base pairs. The "~5-fold increase in mutational frequency, relative to those obtained from young individuals (Young: 3.7±0.9×10-6 vs. Aged: 1.9±0.2×10-5) from the paper is the difference in 0.06 mutations per mitochondria and 0.3 mutations per mitochondria. For 1000 mitochondria you've got 60 mutations vs 300 mutations, but out of the 16,569 bases per mitochondria, in the young sample 99.64% of the DNA is going to be identical / unmutated. In the old sample, 98.19 is going to be identical. So, for 1000 mitochondria, you're looking at 240 mutations difference over 80 years. Even assuming that this is linear, which the paper never states. You're looking at 3 mutations per year per thousand mitochondria. On average. And this isn't like a germ line mutation in a sperm or egg where every cell accumulates that mutation. That is 3 bases different per 16,569,000 bases of 1000 mitochondria.
Brain tissue was specifically tested in this study, because it is the most metabolically active tissue with the hardest working mitochondria in the body. It was selected for this reason because they were trying to detect changes. The mitochondrial mutation rates in other tissues are likely to be smaller. How much smaller? Don't really know, but these rates are alreay quite small.
Nowhere in the paper does it state that the rate is mutation is linear over time. In fact, they hypothesized and the prevailing models in the field suggest that the rate increases with age. You assumed a linear chage, which is the only relationship you can establish between two groups young vs. old.
And they do mean young and old. As in less than one year old for young and 79-90 for old.
Again, interesting idea, but the bottom line is that the magnitude of the changes are far too small to be of any practical value in reliably and difinitively concluding blood samples came from ten years apart.