Toward Clinical Application of Leukocyte Counts Based on Targeted DNA Methylation Analysis.

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.

Epigenetic Clocks Are Not Accelerated in COVID-19 Patients.

Age is a major risk factor for severe outcome of the 2019 coronavirus disease (COVID-19). In this study, we followed the hypothesis that particularly patients with accelerated epigenetic age are affected by severe outcomes of COVID-19. We investigated various DNA methylation datasets of blood samples with epigenetic aging signatures and performed targeted bisulfite amplicon sequencing. Overall, epigenetic clocks closely correlated with the chronological age of patients, either with or without acute respiratory distress syndrome. Furthermore, lymphocytes did not reveal significantly accelerated telomere attrition. Thus, these biomarkers cannot reliably predict higher risk for severe COVID-19 infection in elderly patients.

Proinflammatory phenotype of iPS cell-derived JAK2 V617F megakaryocytes induces fibrosis in 3D in vitro bone marrow niche.

The myeloproliferative disease polycythemia vera (PV) driven by the JAK2 V617F mutation can transform into myelofibrosis (post-PV-MF). It remains an open question how JAK2 V617F in hematopoietic stem cells induces MF. Megakaryocytes are major players in murine PV models but are difficult to study in the human setting. We generated induced pluripotent stem cells (iPSCs) from JAK2 V617F PV patients and differentiated them into megakaryocytes. In differentiation assays, JAK2 V617F iPSCs recapitulated the pathognomonic skewed megakaryocytic and erythroid differentiation. JAK2 V617F iPSCs had a TPO-independent and increased propensity to differentiate into megakaryocytes. RNA sequencing of JAK2 V617F iPSC-derived megakaryocytes reflected a proinflammatory, profibrotic phenotype and decreased ribosome biogenesis. In three-dimensional (3D) coculture, JAK2 V617F megakaryocytes induced a profibrotic phenotype through direct cell contact, which was reversed by the JAK2 inhibitor ruxolitinib. The 3D coculture system opens the perspective for further disease modeling and drug discovery.

Epigenetic Clocks for Mice Based on Age-Associated Regions That are Conserved Between Mouse Strains and Human.

Aging of mice can be tracked by DNA methylation changes at specific sites in the genome. In this study, we used the recently released Infinium Mouse Methylation BeadChip to compare such epigenetic modifications in C57BL/6 (B6) and DBA/2J (DBA) mice. We observed marked differences in age-associated DNA methylation in these commonly used inbred mouse strains, indicating that epigenetic clocks for one strain cannot be simply applied to other strains without further verification. In B6 mice age-associated hypomethylation prevailed with focused hypermethylation at CpG islands, whereas in DBA mice CpG islands revealed rather hypomethylation upon aging. Interestingly, the CpGs with highest age-correlation were still overlapping in B6 and DBA mice and included the genes Hsf4, Prima1, Aspa, and Wnt3a. Notably, Hsf4 and Prima1 were also top candidates in previous studies based on whole genome deep sequencing approaches. Furthermore, Hsf4, Aspa, and Wnt3a revealed highly significant age-associated DNA methylation in the homologous regions in human. Subsequently, we used pyrosequencing of the four relevant regions to establish a targeted epigenetic clock that provided very high correlation with chronological age in independent cohorts of B6 (R 2 = 0.98) and DBA (R 2 = 0.91). Taken together, the methylome differs extensively between B6 and DBA mice, while prominent age-associated changes are conserved among these strains and even in humans. Our new targeted epigenetic clock with 4 CpGs provides a versatile tool for other researchers analyzing aging in mice.

PRDM8 reveals aberrant DNA methylation in aging syndromes and is relevant for hematopoietic and neuronal differentiation.

BACKGROUND: Dyskeratosis congenita (DKC) and idiopathic aplastic anemia (AA) are bone marrow failure syndromes that share characteristics of premature aging with severe telomere attrition. Aging is also reflected by DNA methylation changes, which can be utilized to predict donor age. There is evidence that such epigenetic age predictions are accelerated in premature aging syndromes, but it is yet unclear how this is related to telomere length. DNA methylation analysis may support diagnosis of DKC and AA, which still remains a challenge for these rare diseases. RESULTS: In this study, we analyzed blood samples of 70 AA and 18 DKC patients to demonstrate that their epigenetic age predictions are overall increased, albeit not directly correlated with telomere length. Aberrant DNA methylation was observed in the gene PRDM8 in DKC and AA as well as in other diseases with premature aging phenotype, such as Down syndrome and Hutchinson-Gilford-Progeria syndrome. Aberrant DNA methylation patterns were particularly found within subsets of cell populations in DKC and AA samples as measured with barcoded bisulfite amplicon sequencing (BBA-seq). To gain insight into the functional relevance of PRDM8, we used CRISPR/Cas9 technology to generate induced pluripotent stem cells (iPSCs) with heterozygous and homozygous knockout. Loss of PRDM8 impaired hematopoietic and neuronal differentiation of iPSCs, even in the heterozygous knockout clone, but it did not impact on epigenetic age. CONCLUSION: Taken together, our results demonstrate that epigenetic aging is accelerated in DKC and AA, independent from telomere attrition. Furthermore, aberrant DNA methylation in PRDM8 provides another biomarker for bone marrow failure syndromes and modulation of this gene in cellular subsets may be related to the hematopoietic and neuronal phenotypes observed in premature aging syndromes.