Kun Zhang and colleagues present a metric called methylation haplotype load (MHL) that quantifies methylation patterns within blocks of tightly linked CpG dinucleotides. They show that the MHL can distinguish samples from different human somatic tissues and that it can be used to improve detection of cancer-derived circulating DNA and identify its tissue of origin. Kun Zhang and colleagues present a metric called methylation haplotype load (MHL) that quantifies methylation patterns within blocks of tightly linked CpG dinucleotides. They show that the MHL can distinguish samples from different human somatic tissues and that it can be used to improve detection of cancer-derived circulating DNA and identify its tissue of origin. Adjacent CpG sites in mammalian genomes can be co-methylated owing to the processivity of methyltransferases or demethylases, yet discordant methylation patterns have also been observed, which are related to stochastic or uncoordinated molecular processes. We focused on a systematic search and investigation of regions in the full human genome that show highly coordinated methylation. We defined 147,888 blocks of tightly coupled CpG sites, called methylation haplotype blocks, after analysis of 61 whole-genome bisulfite sequencing data sets and validation with 101 reduced-representation bisulfite sequencing data sets and 637 methylation array data sets. Using a metric called methylation haplotype load, we performed tissue-specific methylation analysis at the block level. Subsets of informative blocks were further identified for deconvolution of heterogeneous samples. Finally, using methylation haplotypes we demonstrated quantitative estimation of tumor load and tissue-of-origin mapping in the circulating cell-free DNA of 59 patients with lung or colorectal cancer.

DNA methylation plays an important role in biological processes in human health and disease. Recent technological advances allow unbiased whole-genome DNA methylation (methylome) analysis to be carried out on human cells. Using whole-genome bisulfite sequencing at 24.7-fold coverage (12.3-fold per strand), we report a comprehensive (92.62%) methylome and analysis of the unique sequences in human peripheral blood mononuclear cells (PBMC) from the same Asian individual whose genome was deciphered in the YH project. PBMC constitute an important source for clinical blood tests world-wide. We found that 68.4% of CpG sites and 80% displayed allele-specific expression (ASE). These data demonstrate that ASM is a recurrent phenomenon and is highly correlated with ASE in human PBMCs. Together with recently reported similar studies, our study provides a comprehensive resource for future epigenomic research and confirms new sequencing technology as a paradigm for large-scale epigenomics studies. Epigenetic modifications such as addition of methyl groups to cytosine in DNA play a role in regulating gene expression. To better understand these processes, knowledge of the methylation status of all cytosine bases in the genome (the methylome) is required. DNA methylation can differ between the two gene copies (alleles) in each cell. Such allele-specific methylation (ASM) can be due to parental origin of the alleles (imprinting), X chromosome inactivation in females, and other as yet unknown mechanisms. This may significantly alter the expression profile arising from different allele combinations in different individuals. Using advanced sequencing technology, we have determined the methylome of human peripheral blood mononuclear cells (PBMC). Importantly, the PBMC were obtained from the same male Han Chinese individual whose complete genome had previously been determined. This allowed us, for the first time, to study genome-wide differences in ASM. Our analysis shows that ASM in PBMC is higher than can be accounted for by regions known to undergo parent-of-origin imprinting and frequently (>80%) correlates with allele-specific expression (ASE) of the corresponding gene. In addition, our data reveal a rich landscape of epigenomic variation for 20 genomic features, including regulatory, coding, and non-coding sequences, and provide a valuable resource for future studies. Our work further establishes whole-genome sequencing as an efficient method for methylome analysis.

Rheumatoid arthritis (RA) is a chronic inflammatory joint disease that can lead to clinical manifestations of systemic diseases. Its leading features include chronic synovial inflammation and degeneration of the bones and joints. In the past decades, multiple susceptibilities for rheumatoid arthritis have been identified along with the development of a remarkable variety of drugs for its treatment; which include analgesics, glucocorticoids, nonsteroidal anti-inflammatory medications (NSAIDs), disease-modifying anti-rheumatic drugs (DMARDs), and biologic response modifiers (bDMARDs). Despite the existence of many clinical treatment options, the prognosis of some patients remains poor due to complex mechanism of the disease. Programmed cell death (PCD) has been extensively studied and ascertained to be one of the essential pathological mechanisms of RA. Its dysregulation in various associated cell types contributes to the development of RA. In this review, we summarize the role of apoptosis, cell death-associated neutrophil extracellular trap formation, necroptosis, pyroptosis, and autophagy in the pathophysiology of RA to provide a theoretical reference and insightful direction to the discovery and development of novel therapeutic targets for RA.

Rheumatoid arthritis is an autoimmune disease that exhibits significant clinical heterogeneity. There are various treatments for rheumatoid arthritis, including disease-modifying anti-rheumatic drugs (DMARDs), glucocorticoids, non-steroidal anti-inflammatory drugs (NSAIDs), and inflammatory cytokine inhibitors (ICI), typically associated with differentiated clinical effects and characteristics. Personalized responsiveness is observed to the standard treatment due to the pathophysiological heterogeneity in rheumatoid arthritis, resulting in an overall poor prognosis. Understanding the role of individual variation in cellular and molecular mechanisms related to rheumatoid arthritis will considerably improve clinical care and patient outcomes. In this review, we discuss the source of pathophysiological heterogeneity derived from genetic, molecular, and cellular heterogeneity and their possible impact on precision medicine and personalized treatment of rheumatoid arthritis. We provide emphasized description of the heterogeneity derived from mast cells, monocyte cell, macrophage fibroblast-like synoviocytes and, interactions within immune cells and with inflammatory cytokines, as well as the potential as a new therapeutic target to develop a novel treatment approach. Finally, we summarize the latest clinical trials of treatment options for rheumatoid arthritis and provide a suggestive framework for implementing preclinical and clinical experimental results into clinical practice.