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Background Differential leukocyte counts are usually measured based on cellular morphology or surface marker expression. It has recently been shown that leukocyte counts can also be determined by cell-type–specific DNA methylation (DNAm). Such epigenetic leukocyte counting is applicable to small blood volumes and even frozen material, but for clinical translation, the method needs to be further refined and validated. Methods We further optimized and validated targeted DNAm assays for leukocyte deconvolution using 332 venous and 122 capillary blood samples from healthy donors. In addition, we tested 36 samples from ring trials and venous blood from 266 patients diagnosed with different hematological diseases. Deconvolution of cell types was determined with various models using DNAm values obtained by pyrosequencing or digital droplet PCR (ddPCR). Results Relative leukocyte quantification correlated with conventional blood counts for granulocytes, lymphocytes, B cells, T cells (CD4 or CD8), natural killer cells, and monocytes with pyrosequencing (r = 0.84; r = 0.82; r = 0.58; r = 0.50; r = 0.70; r = 0.61; and r = 0.59, respectively) and ddPCR measurements (r = 0.65; r = 0.79; r = 0.56; r = 0.57; r = 0.75; r = 0.49; and r = 0.46, respectively). In some patients, particularly with hematopoietic malignancies, we observed outliers in epigenetic leukocyte counts, which could be discerned if relative proportions of leukocyte subsets did not sum up to 100%. Furthermore, absolute quantification was obtained by spiking blood samples with a reference plasmid of known copy number. Conclusions Targeted DNAm analysis by pyrosequencing or ddPCR is a valid alternative to quantify leukocyte subsets, but some assays require further optimization.

Identify differentially expressed microRNAs (miRNAs) in aqueous humor (AH) and blood of primary open-angle glaucoma (POAG) patients by using small RNA sequencing. These may provide insight into POAG pathophysiology or serve as diagnostic biomarker.METHODS. AH and plasma of nine POAG patients and 10 cataract control patients were small RNA sequenced on Illumina NovaSeq 6000. Identification of gene transcripts targeted by differentially expressed miRNAs was done with miRWalk and MirPath. These targets were used for pathway analysis and Gene Ontology enrichment. Diagnostic potential was evaluated by receiver operating characteristics analysis. RESULTS.We identified 715 miRNAs in plasma and 62 miRNAs in AH. Plasma miRNA profile did not differ between POAG and control. In contrast, in AH, seven miRNAs were differentially expressed. Hsa-miR-30a-3p, hsa-miR-143-3p, hsa-miR-211-5p, and hsa-miR-221-3p were upregulated, whereas hsa-miR-92a-3p, hsa-miR-451a, and hsa-miR-486-5p were downregulated in POAG. Compared to previous studies, hsa-mir-143-3p, hsa-miR-211-5p, and hsa-miR-221-3p were reported previously, strengthening their involvement in POAG whereas hsa-miR-30a-3p, hsa-miR-92a-3p, and hsa-miR-486-5p are implicated in POAG for the first time. Identified gene transcripts were involved in several pathways, some implicated in glaucoma before (e.g., TGF-β and neurotrophin signaling), whereas others are new (e.g., prolactin and apelin signaling). In respect to diagnostics, AH concentration of hsa-mir-143-3p had an area under the curve (AUC) of 0.889. Combined with hsa-miR-221-3p, AUC improved to 0.96. CONCLUSIONS.Small RNA sequencing identified seven differentially expressed miRNAs in AH of POAG patients. The differentially expressed miRNAs may be useful as POAG biomarkers or could become targets for new therapeutic strategies.