When cells die (apoptosis or necrosis), their DNA fragments enter the bloodstream. By analyzing methylation patterns on these fragments, you can determine which tissue they came from (each tissue has a unique methylation fingerprint). Also includes cf-mtDNA (mitochondrial cell-free DNA).
Reading this chart
Y-axis shows fold-change in cfDNA levels vs pre-flight. The steady rise peaking at 3.8x at R+1 means increasing cell death/turnover, especially in immune cells post-landing. Mitochondrial cfDNA was elevated throughout — a sign of sustained mitochondrial stress even before reaching orbit.
Elevated cfDNA from a specific tissue = that tissue is experiencing damage or increased turnover. Elevated immune-cell-origin cfDNA post-landing = immune system activation. Elevated mitochondrial cfDNA = mitochondrial stress/damage across the body.
Fragment counts per tissue-of-origin (deconvolution percentages). Fold-change from baseline. cf-mtDNA is measured as copies/mL. Simple ratios and time-series comparison.
All AP-level math. No differential equations, no ML required. With n=4, descriptive statistics are more honest than hypothesis testing.
cf-mtDNA significantly elevated across all mission phases
Immune cell cfDNA signature spiked post-landing
Tissue deconvolution revealed organ-specific stress patterns
Non-invasive proxy for tissue damage assessment
Feeds into both Mitochondrial Function (cf-mtDNA) and DNA Damage Response domains. Tissue-of-origin data adds a 'which organs are affected' dimension that other omics can't provide.