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Background: Beckwith-Wiedemann syndrome and Silver-Russel syndrome are two imprinting disorders caused by opposite molecular alterations in 11p15.5. With the current diagnostic tests, their molecular diagnosis is challenging due to molecular heterogeneity and mosaic occurrence of the most frequent alterations. As the determination of precise (epi)genotype of patients is relevant as the basis for a personalized treatment, different approaches are needed to increase the sensitivity of diagnostic testing of imprinting disorders., Methods: We established methylation-specific droplet digital PCR approaches (MS-ddPCR) for the two imprinting centers in 11p15.5, and analyzed patients with paternal uniparental disomy of chromosome 11p15.5 (upd(11)pat) and other imprinting defects in the region. The results were compared to those from MS-MLPA (multiplex ligation-dependent probe amplification) and MS-pyrosequencing., Results: MS-ddPCR confirmed the molecular alterations in all patients and the results matched well with MS-MLPA. The results of MS-pyrosequencing varied between different runs, whereas MS-ddPCR results were reproducible., Conclusion: We show for the first time that MS-ddPCR is a reliable and easy applicable method for determination of MS-associated changes in imprinting disorders. It is therefore an additional tool for multimethod diagnostics of imprinting disorders suitable to improve the diagnostic yield., (© 2023 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals LLC.)

Background: Cell-type specific DNA methylation (DNAm) can be employed to determine the numbers of leukocyte subsets in blood. In contrast to conventional methods for leukocyte counts, which are based on cellular morphology or surface marker protein expression, the cellular deconvolution based on DNAm levels is applicable for frozen or dried blood. Here, we further enhanced targeted DNAm assays for leukocyte counts in clinical application., Methods: DNAm profiles of 40 different studies were compiled to identify CG dinucleotides (CpGs) with cell-type specific DNAm using a computational framework, CimpleG. DNAm levels at these CpGs were then measured with digital droplet PCR in venous blood from 160 healthy donors and 150 patients with various hematological disorders. Deconvolution was further validated with venous blood (n = 75) and capillary blood (n = 31) that was dried on Whatman paper or on Mitra microsampling devices., Results: In venous blood, automated cell counting or flow cytometry correlated well with epigenetic estimates of relative leukocyte counts for granulocytes (r = 0.95), lymphocytes (r = 0.97), monocytes (r = 0.82), CD4 T cells (r = 0.84), CD8 T cells (r = 0.94), B cells (r = 0.96), and NK cells (r = 0.72). Similar correlations and precisions were achieved for dried blood samples. Spike-in with a reference plasmid enabled accurate epigenetic estimation of absolute leukocyte counts from dried blood samples, correlating with conventional venous (r = 0.86) and capillary (r = 0.80) blood measurements., Conclusions: The advanced selection of cell-type specific CpGs and utilization of digital droplet PCR analysis provided accurate epigenetic blood counts. Analysis of dried blood facilitates self-sampling with a finger prick, thereby enabling easier accessibility to testing., (© Association for Diagnostics & Laboratory Medicine 2023. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

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., (© American Association for Clinical Chemistry 2022.)

Purpose: The trabecular meshwork (TM) is situated in the most frontal part of the eye and is thought to play an important role in the regulation of the eye pressure. However, this tissue is rather difficult to harvest for research. The purpose of this study is therefore to integrate the existing gene expression data of the healthy TM to increase sample size and identify its signature genes and pathways. This provides a robust reference for the study of molecular disease processes and supports the selection of candidate target genes for new treatments., Methods: A systematic search identified microarray data of healthy TM tissue. After quality control, datasets of low quality and deviating samples were excluded. Remaining individuals were jointly normalized and integrated into one database. The average gene expression of each tested gene over all individuals was calculated. The 25% genes with the highest average expression were identified as the most active genes in the healthy TM and used as input for pathway and network analysis. Additionally, ubiquitous pathways and genes were identified and excluded from the results. Lastly, we identified genes which are likely to be TM-specific., Results: The gene expression data of 44 individuals, obtained from 18 datasets, were jointly normalized. Ubiquitous genes (n = 688) and ubiquitous pathways (n = 73) were identified and excluded. Following, 1882 genes and 211 pathways were identified as the signature genes and pathways of the healthy TM. Pathway analysis revealed multiple molecular processes of which some were already known to be active in the TM, for example extracellular matrix and elastic fiber formation. Forty-six candidate TM-specific genes were identified. These consist mainly of pseudogenes or novel transcripts of which the function is unknown., Conclusions: In this comprehensive meta-analysis we identified non-ubiquitous genes and pathways that form the signature of the functioning of the healthy TM. Additionally, 46 candidate TM-specific genes were identified. This method can also be used for other tissues that are difficult to obtain for study., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)