Cell-free DNA (cfDNA) is gaining recognition as a promising non-invasive biomarker in precision medicine. It is particularly relevant in systemic lupus erythematosus (SLE), where elevated plasma cfDNA levels have consistently been observed. However, the specific methylation patterns of cfDNA in SLE remain unclear.
A new study sheds light on this gap, revealing that SLE is associated with abnormal immune microenvironments across multiple sample types, including renal tissue, whole blood, peripheral blood mononuclear cells, and plasma cfDNA. These environments also show abnormal activation of interferon-related signaling pathways and antiviral responses.
Using whole-genome bisulfite sequencing, the researchers examined the epigenomic landscape of plasma cfDNA methylation in patients with lupus nephritis (LN). The study found that cfDNA methylation levels were significantly lower in LN patients compared to healthy controls, particularly in gene promoter regions. A total of 13 SLE-related datasets were analyzed, and 163 SLE-associated dysfunctional methylated regions were identified by combining cfDNA methylation data.
A novel cfDNA-based diagnostic model for lupus was developed using a deep-learning neural network, which was validated in two independent cohorts. The model demonstrated excellent diagnostic performance, with an area under the curve (AUC) of 0.987 in the first cohort (GSE82218) and 0.84 in the second cohort (GSE96879). The model also showed a significant ability to differentiate between various disease activity levels, with distinct scores for normal versus SLE (p<0.0001) and low versus high disease activity (p<0.01).
Further multi-omics analyses revealed that the most frequently aberrant methylation sites are linked to immune-related pathways, as well as disease onset and progression. These findings suggest that plasma cfDNA methylation profiling could become a key research focus for lupus nephritis, offering potential for both diagnostic and disease activity assessment applications.
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