2023 American Academy of Neurology Abstract Website

Objective:

To depict systemic cell death from plasma cell-free DNA (cfDNA) from ALS patients with an expanded reference tissue methylome dataset.

Background:

CfDNA is fragments of DNA released by dying cells with a half-life of minutes to 2 hours in plasma that has been utilized for non-invasive prenatal testing and cancer detection. Cell-type-specific methylation of DNA can serve as a marker for the cell-of-origin of cfDNA. Caggiano et al. developed a machine-learning algorithm for tissue-of-origin deconvolution of cfDNA, CelFiE, and reported that muscle-derived cfDNA is significantly elevated in plasma of ALS patients than controls with 19 reference tissues excluding nervous tissues (Caggiano et al, Nat Comm, 2020).

Design/Methods:

Reference tissue methylome was expanded to 39 tissues with multiple immune cells and brain-derived NeuN positive and negative cells. Plasma cfDNA methylome of ALS patients (n=16) and controls (n=16) was re-analyzed with CelFiE and the expanded reference tissue methylome, using the tissue identification markers (TIMs) deduced by the original 19 reference tissues. Estimated cfDNA origins were visualized along with the clinical variables (sex, ethnicity, region of onset, days from the date of onset, and ALSFRS-R) for further limited statistical testing.

Results:

Expanded reference methylome with the original TIMs replicated the elevated muscle-derived cfDNA in ALS patients. Brain-derived cfDNA did not differ between ALS and control. Natural killer cells and eosinophils-derived cfDNA were significantly decreased in ALS than control. Neutrophil-derived cfDNA was significantly decreased in patients with ALSFRS-R ≤31 compared to patients with ALSFRS-R >31.

Conclusions:

CfDNA can depict systemic cell death, even for tissues that have not been studied in the context of ALS and that are otherwise not detectable (e.g., hematopoietic stem cells). To apply cfDNA to biomarker and pathophysiology research for ALS, further study is needed to improve the resolution of deconvolution algorithms with alike tissues, and cost-effective sequencing methods.