Early warning biomarkers in major depressive disorder: a strategic approach to a testing question

Purpose: Identification of biomarkers in major depressive disorder (MDD) has proceeded in an extemporised manner. No single biomarker has been identified with utility in screening, diagnosis, prognosis, or monitoring, and screening tests have different characteristics than the other functions. Using chaos, bifurcation, and perturbation (CBP) theories, the aim is to identify biomarkers to aid clinicians in screening for MDD.

Materials and methods: MDD is a complex disorder; consequently, a reductionist approach to characterize the complex system changes found in MDD will be inchoate and unreliable. A holistic approach is used to identify biomarkers reflecting the tipping points seen before the catastrophic bifurcation that results in MDD.

Results: Applying CBP theories revealed skew, resistance to change, flickering, increased variance and autocorrelation as patterns of biomarkers. Integrals and differentials of extracellular and intracellular biomarkers were identified, specifically focussed on hypothalamo-pituitary axis (HPA) dysfunction, metabolic dysfunction, inflammation and mitochondrial oxidative stress, and tryptophan metabolism.

Conclusions: Applying CBP theories to the dysfunctional complex biological systems in MDD led to development of integrals and differentials of biomarkers that can be used in screening for MDD and planning future biomarker research, targeting intracellular and extracellular inflammation, HPA axis dysfunction, and tryptophan metabolism.     

Integrative analysis of DNA methylation and gene expression through machine learning identifies stomach cancer diagnostic and prognostic biomarkers

DNA methylation is an early event in tumorigenesis. Here, by integrative analysis of DNA methylation and gene expression and utilizing machine learning approaches, we introduced potential diagnostic and prognostic methylation signatures for stomach cancer. Differentially-methylated positions (DMPs) and differentially-expressed genes (DEGs) were identified using The Cancer Genome Atlas (TCGA) stomach adenocarcinoma (STAD) data. A total of 256 DMPs consisting of 140 and 116 hyper- and hypomethylated positions were identified between 443 tumour and 27 nontumour STAD samples. Gene expression analysis revealed a total of 2821 DEGs with 1247 upregulated and 1574 downregulated genes. By analysing the impact of cis and trans regulation of methylation on gene expression, a dominant negative correlation between methylation and expression was observed, while for trans regulation, in hypermethylated and hypomethylated genes, there was mainly a negative and positive correlation with gene expression, respectively. To find diagnostic biomarkers, we used 28 hypermethylated probes locating in the promoter of 27 downregulated genes. By implementing a feature selection approach, eight probes were selected and then used to build a support vector machine diagnostic model, which had an area under the curve of 0.99 and 0.97 in the training and validation (GSE30601 with 203 tumour and 94 nontumour samples) cohorts, respectively. Using 412 TCGA-STAD samples with both methylation and clinical data, we also identified four prognostic probes by implementing univariate and multivariate Cox regression analysis. In summary, our study introduced potential diagnostic and prognostic biomarkers for STAD, which demands further validation.     

DNA methylation profiles and biomarkers of oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) constitutes >90% of oral cancers and is the sixth most common malignancy among males worldwide and the fourth leading cause of death due to cancer among males in Taiwan. However, most patients do not receive a diagnosis of OSCC until the late stages, which have a lower survival rate. The use of molecular marker analysis to identify early-stage OSCC would permit optimal timing for treatments and consequently prolong survival. The aim of this study was to identify biomarkers of OSCC using the Illumina GoldenGate Methylation Cancer Panel, which comprised a total of 1,505 CpG sites covering 807 genes. Samples of buccal mucosa resected from 40 OSCC patients and normal tissue samples obtained from 15 patients (normal mucosa from OSCC patients or from patients undergoing surgery unrelated to OSCC) were analyzed. Fms-related tyrosine kinase 4 (FLT4) methylation exhibited a perfect specificity for detecting OSCC, with an area under the receiver operating characteristic curve of 0.91 for both all-stage and early-stage OSCC. Methylation of 7 genes (ASCL1, FGF3, FLT4, GAS7, KDR, TERT, and TFPI2) constitutes the top-20 panels for detecting OSCC. The top-20 panels for detecting early-stage OSCC contain 8 genes: ADCYAP1, EPHA7, FLT4, GSTM2, KDR, MT1A, NPY, and TFPI2. FLT4 RNA expression and methylation level were validated using RT-PCR and a pyrosequencing methylation assay. The median level of FLT4 expression was 2.14-fold for normal relative to OSCC tissue samples (P < 0.0001). Among the 8 pyrosequenced FLT4 CpG sites, methylation level was much higher in the OSCC samples. In conclusion, methylation statuses of selected genes, and especially FLT4, KDR, and TFPI2, might be of great potential as biomarkers for early detection of buccal OSCC.     

Oligonucleotide-based microarray for DNA methylation analysis: principles and applications

Gene silencing via promoter CpG island hypermethylation offers tumor cells growth advantages. This epigenetic event is pharmacologically reversible, and uncovering a unique set of methylation-silenced genes in tumor cells can bring a new avenue to cancer treatment. However, high-throughput tools capable of surveying the methylation status of multiple gene promoters are needed for this discovery process. Herein we describe an oligonucleotide-based microarray technique that is both versatile and sensitive in revealing hypermethylation in defined regions of the genome. DNA samples are bisulfite-treated and PCR-amplified to distinguish CpG dinucleotides that are methylated from those that are not. Fluorescently labeled PCR products are hybridized to arrayed oligonucleotides that can discriminate between methylated and unmethylated alleles in regions of interest. Using this technique, two clinical subtypes of non-Hodgkin's lymphomas, mantle cell lymphoma, and grades I/II follicular lymphoma, were further separated based on the differential methylation profiles of several gene promoters. Work is underway in our laboratory to extend the interrogation power of this microarray system in multiple candidate genes. This novel tool, therefore, holds promise to monitor the outcome of various epigenetic therapies on cancer patients.     

Diabetes mellitus in people with schizophrenia,bipolar disorder and major depressive disorder: a systematic review and large scale meta‐analysis

Type 2 diabetes mellitus (T2DM) is highly predictive of cardiovascular diseases and can have particularly deleterious health impacts in people with severe mental illness (SMI), i.e. schizophrenia, bipolar disorder or major depressive disorder. This meta‐analysis aimed: a) to describe pooled frequencies of T2DM in people with SMI; b) to analyze the influence of demographic, illness and treatment variables as well as T2DM assessment methods; and c) to describe T2DM prevalence in studies directly comparing persons with each specific SMI diagnosis to general population samples. The trim and fill adjusted pooled T2DM prevalence among 438,245 people with SMI was 11.3% (95% CI: 10.0%‐12.6%). In antipsychotic‐naïve participants, the prevalence of T2DM was 2.9% (95% CI: 1.7%‐4.8%). There were no significant diagnostic subgroup differences. A comparative meta‐analysis established that multi‐episode persons with SMI (N=133,470) were significantly more likely to have T2DM than matched controls (N=5,622,664): relative risk, RR=1.85, 95% CI: 1.45‐2.37, p<0.001. The T2DM prevalence was consistently elevated in each of the three major diagnostic subgroups compared to matched controls. Higher T2DM prevalences were observed in women with SMI compared to men (RR=1.43, 95% CI: 1.20‐1.69, p<0.001). Multi‐episode (versus first‐episode) status was the only significant predictor for T2DM in a multivariable meta‐regression analysis (r²=0.52, p<0.001). The T2DM prevalence was higher in patients prescribed antipsychotics, except for aripriprazole and amisulpride. Routine screening and multidisciplinary management of T2DM is needed. T2DM risks of individual antipsychotic medications should be considered when making treatment choices.     

Quantitative DNA methylation analysis of genes coding for kallikrein-related peptidases 6 and 10 as biomarkers for prostate cancer

DNA methylation plays an important role in carcinogenesis and is being recognized as a promising diagnostic and prognostic biomarker for a variety of malignancies including Prostate cancer (PCa). The human kallikrein-related peptidases (KLKs) have emerged as an important family of cancer biomarkers, with KLK3, encoding for Prostate Specific Antigen, being most recognized. However, few studies have examined the epigenetic regulation of KLKs and its implications to PCa. To assess the biological effect of DNA methylation on KLK6 and KLK10 expression, we treated PC3 and 22RV1 PCa cells with a demethylating drug, 5-aza-2′deoxycytidine, and observed increased expression of both KLKs, establishing that DNA methylation plays a role in regulating gene expression. Subsequently, we have quantified KLK6 and KLK10 DNA methylation levels in two independent cohorts of PCa patients operated by radical prostatectomy between 2007–2011 (Cohort I, n = 150) and 1998–2001 (Cohort II, n = 124). In Cohort I, DNA methylation levels of both KLKs were significantly higher in cancerous tissue vs. normal. Further, we evaluated the relationship between DNA methylation and clinicopathological parameters. KLK6 DNA methylation was significantly associated with pathological stage only in Cohort I while KLK10 DNA methylation was significantly associated with pathological stage in both cohorts. In Cohort II, low KLK10 DNA methylation was associated with biochemical recurrence in univariate and multivariate analyses. A similar trend for KLK6 DNA methylation was observed. The results suggest that KLK6 and KLK10 DNA methylation distinguishes organ confined from locally invasive PCa and may have prognostic value.     

Quantitative DNA methylation analysis of genes coding for kallikrein-related peptidases 6 and 10 as biomarkers for prostate cancer

DNA methylation plays an important role in carcinogenesis and is being recognized as a promising diagnostic and prognostic biomarker for a variety of malignancies including Prostate cancer (PCa). The human kallikrein-related peptidases (KLKs) have emerged as an important family of cancer biomarkers, with KLK3, encoding for Prostate Specific Antigen, being most recognized. However, few studies have examined the epigenetic regulation of KLKs and its implications to PCa. To assess the biological effect of DNA methylation on KLK6 and KLK10 expression, we treated PC3 and 22RV1 PCa cells with a demethylating drug, 5-aza-2′deoxycytidine, and observed increased expression of both KLKs, establishing that DNA methylation plays a role in regulating gene expression. Subsequently, we have quantified KLK6 and KLK10 DNA methylation levels in two independent cohorts of PCa patients operated by radical prostatectomy between 2007–2011 (Cohort I, n = 150) and 1998–2001 (Cohort II, n = 124). In Cohort I, DNA methylation levels of both KLKs were significantly higher in cancerous tissue vs. normal. Further, we evaluated the relationship between DNA methylation and clinicopathological parameters. KLK6 DNA methylation was significantly associated with pathological stage only in Cohort I while KLK10 DNA methylation was significantly associated with pathological stage in both cohorts. In Cohort II, low KLK10 DNA methylation was associated with biochemical recurrence in univariate and multivariate analyses. A similar trend for KLK6 DNA methylation was observed. The results suggest that KLK6 and KLK10 DNA methylation distinguishes organ confined from locally invasive PCa and may have prognostic value.     

Chromosome 15q13.3 microduplications are associated with treatment refractory major depressive disorder

Major depressive disorder (MDD) affects approximately 15 million Americans. Approximately 2 million of these are classified as being refractory to treatment (TR‐MDD). Because of the lack of available therapies for TR‐MDD, and the high risk of suicide, there is interest in identifying new treatment modalities and diagnostic methods. Understanding of the impact of genomic copy number variation in the etiology of a variety of neuropsychiatric phenotypes is increasing. Low copy repeat elements at 15q13.3 facilitate non‐allelic homologous recombination, resulting in recurrent copy number variants (CNVs). Numerous reports have described association between microdeletions in this region and a variety of neuropsychiatric phenotypes, with CHRNA7 implicated as a candidate gene. However, the pathogenicity of 15q13.3 duplications is less clear. As part of an ongoing study, in which we have identified a number of metabolomic anomalies in spinal fluid from TR‐MDD patients, we also evaluated genomic copy number variation in patients (n = 125) and controls (n = 26) via array‐based copy number genomic hybridization (CGH); the case frequency was compared with frequencies reported in a prior study as well as a larger population‐sized cohort. We identified five TR‐MDD patients with microduplications involving CHRNA7. CHRNA7 duplications are the most common CNVs identified by clinical CGH in this cohort. Therefore, this study provides insight into the potential involvement of CHRNA7 duplications in the etiology of TR‐MDD and informs those involved with care of affected individuals.     

DNA methylation based biomarkers: Practical considerations and applications

A biomarker is a molecular target analyzed in a qualitative or quantitative manner to detect and diagnose the presence of a disease, to predict the outcome and the response to a specific treatment allowing personalized tailoring of patient management. Biomarkers can belong to different types of biochemical molecules such as proteins, DNA, RNA or lipids, whereby protein biomarkers have been the most extensively studied and used, notably in blood-based protein quantification tests or immunohistochemistry. The rise of interest in epigenetic mechanisms has allowed the identification of a new type of biomarker, DNA methylation, which is of great potential for many applications. This stable and heritable covalent modification mostly affects cytosines in the context of a CpG dinucleotide in humans. It can be detected and quantified by a number of technologies including genome-wide screening methods as well as locus- or gene-specific high-resolution analysis in different types of samples such as frozen tissues and FFPE samples, but also in body fluids such as urine, plasma, and serum obtained through non-invasive procedures. In some cases, DNA methylation based biomarkers have proven to be more specific and sensitive than commonly used protein biomarkers, which could clearly justify their use in clinics. However, very few of them are at the moment used in clinics and even less commercial tests are currently available. The objective of this review is to discuss the advantages of DNA methylation as a biomarker, the practical considerations for their development, and their use in disease detection, prediction of outcome or treatment response, through multiple examples mainly focusing on cancer, but also to evoke their potential for complex diseases and prenatal diagnostics.     

Regulation beyond genome sequences: DNA and histone methylation in embryonic stem cells

Embryonic stem (ES) cells distinct themselves from other cell type populations by their pluripotent ability. The unique features of ES cells are controlled by both genetic and epigenetic factors. Studies have shown that the methylation status of DNA and histones in ES cells is quite different from that of differentiated cells and somatic stem cells. Herein, we summarized recent advances in DNA and histone methylation studies of mammalian ES cells. The methylation status of several key pluripotent regulatory genes is also discussed.     

首发重性抑郁症患者肠道菌群组成及与胃肠道症状的相关性

【背景】重性抑郁症(majordepressivedisorder,MDD)是一种常见的重大精神疾病,MDD患者多伴有胃肠道症状,但很少有研究关注MDD患者胃肠道症状发生的机制。【目的】探索首发未治疗MDD患者肠道菌群的特征及其与炎症标志物和胃肠道症状的相关性,为MDD的治疗提供理论依据。【方法】募集符合入组和排除标准的91例首发未服药MDD患者和105名健康对照者(healthy controls, HCs)。采用16S rRNA基因测序技术和生物信息学分析评估粪便菌群组成。采用酶联免疫吸附试验(enzymelinkedimmunosorbentassay,ELISA)检测外周血高敏C反应蛋白(high-sensitivity C-reactive protein, hs-CRP)、白细胞介素-1β (interleukin-1β, IL-1β)、白细胞介素-6(interleukin-6,IL-6)、白细胞介素-10(interleukin-10,IL-10)和肿瘤坏死因子-α(tumornecrosis factor-α, TNF-α);采用胃肠症状评定量表(gastrointe...     

A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression

Glioblastoma multiforme (GBM) is the most aggressive of all brain tumors, with a median survival of less than 1.5 years. Recently, epigenetic alterations were found to play key roles in both glioma genesis and clinical outcome, demonstrating the need to integrate genetic and epigenetic data in predictive models. To enhance current models through discovery of novel predictive biomarkers, we employed a genome-wide, agnostic strategy to specifically capture both methylation-directed changes in gene expression and alternative associations of DNA methylation with disease survival in glioma. Human GBM-associated DNA methylation, gene expression, IDH1 mutation status, and survival data were obtained from The Cancer Genome Atlas. DNA methylation loci and expression probes were paired by gene, and their subsequent association with survival was determined by applying an accelerated failure time model to previously published alternative and expression-based association equations. Significant associations were seen in 27 unique methylation/expression pairs with expression-based, alternative, and combinatorial associations observed (10, 13, and 4 pairs, respectively). The majority of the predictive DNA methylation loci were located within CpG islands, and all but three of the locus pairs were negatively correlated with survival. This finding suggests that for most loci, methylation/expression pairs are inversely related, consistent with methylation-associated gene regulatory action. Our results indicate that changes in DNA methylation are associated with altered survival outcome through both coordinated changes in gene expression and alternative mechanisms. Furthermore, our approach offers an alternative method of biomarker discovery using a priori gene pairing and precise targeting to identify novel sites for locus-specific therapeutic intervention.     

A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression

Glioblastoma multiforme (GBM) is the most aggressive of all brain tumors, with a median survival of less than 1.5 years. Recently, epigenetic alterations were found to play key roles in both glioma genesis and clinical outcome, demonstrating the need to integrate genetic and epigenetic data in predictive models. To enhance current models through discovery of novel predictive biomarkers, we employed a genome-wide, agnostic strategy to specifically capture both methylation-directed changes in gene expression and alternative associations of DNA methylation with disease survival in glioma. Human GBM-associated DNA methylation, gene expression, IDH1 mutation status, and survival data were obtained from The Cancer Genome Atlas. DNA methylation loci and expression probes were paired by gene, and their subsequent association with survival was determined by applying an accelerated failure time model to previously published alternative and expression-based association equations. Significant associations were seen in 27 unique methylation/expression pairs with expression-based, alternative, and combinatorial associations observed (10, 13, and 4 pairs, respectively). The majority of the predictive DNA methylation loci were located within CpG islands, and all but three of the locus pairs were negatively correlated with survival. This finding suggests that for most loci, methylation/expression pairs are inversely related, consistent with methylation-associated gene regulatory action. Our results indicate that changes in DNA methylation are associated with altered survival outcome through both coordinated changes in gene expression and alternative mechanisms. Furthermore, our approach offers an alternative method of biomarker discovery using a priori gene pairing and precise targeting to identify novel sites for locus-specific therapeutic intervention.     

DNA methylation biomarkers for head and neck squamous cell carcinoma

DNA methylation plays an important role in the etiology and pathogenesis of head and neck squamous cell carcinoma (HNSCC). The current study aimed to identify aberrantly methylated-differentially expressed genes (DEGs) by a comprehensive bioinformatics analysis. In addition, we screened for DEGs affected by DNA methylation modification and further investigated their prognostic values for HNSCC. We included microarray data of DNA methylation (GSE25093 and GSE33202) and gene expression (GSE23036 and GSE58911) from Gene Expression Omnibus. Aberrantly methylated-DEGs were analyzed with R software. The Cancer Genome Atlas (TCGA) RNA sequencing and DNA methylation (Illumina HumanMethylation450) databases were utilized for validation. In total, 27 aberrantly methylated genes accompanied by altered expression were identified. After confirmation by The Cancer Genome Atlas (TCGA) database, 2 hypermethylated-low-expression genes (FAM135B and ZNF610) and 2 hypomethylated-high-expression genes (HOXA9 and DCC) were identified. A receiver operating characteristic (ROC) curve confirmed the diagnostic value of these four methylated genes for HNSCC. Multivariate Cox proportional hazards analysis showed that FAM135B methylation was a favorable independent prognostic biomarker for overall survival of HNSCC patients.     

Risk of metabolic syndrome and its components in people with schizophrenia and related psychotic disorders,bipolar disorder and major depressive disorder: a systematic review and meta‐analysis

Metabolic syndrome (MetS) and its components are highly predictive of cardiovascular diseases. The primary aim of this systematic review and meta‐analysis was to assess the prevalence of MetS and its components in people with schizophrenia and related psychotic disorders, bipolar disorder and major depressive disorder, comparing subjects with different disorders and taking into account demographic variables and psychotropic medication use. The secondary aim was to compare the MetS prevalence in persons with any of the selected disorders versus matched general population controls. The pooled MetS prevalence in people with severe mental illness was 32.6% (95% CI: 30.8%‐34.4%; N = 198; n = 52,678). Relative risk meta‐analyses established that there was no significant difference in MetS prevalence in studies directly comparing schizophrenia versus bipolar disorder, and in those directly comparing bipolar disorder versus major depressive disorder. Only two studies directly compared people with schizophrenia and major depressive disorder, precluding meta‐analytic calculations. Older age and a higher body mass index were significant moderators in the final demographic regression model (z = ?3.6, p = 0.0003, r² = 0.19). People treated with all individual antipsychotic medications had a significantly (p<0.001) higher MetS risk compared to antipsychotic‐naïve participants. MetS risk was significantly higher with clozapine and olanzapine (except vs. clozapine) than other antipsychotics, and significantly lower with aripiprazole than other antipsychotics (except vs. amisulpride). Compared with matched general population controls, people with severe mental illness had a significantly increased risk for MetS (RR = 1.58; 95% CI: 1.35‐1.86; p<0.001) and all its components, except for hypertension (p = 0.07). These data suggest that the risk for MetS is similarly elevated in the diagnostic subgroups of severe mental illness. Routine screening and multidisciplinary management of medical and behavioral conditions is needed in these patients. Risks of individual antipsychotics should be considered when making treatment choices.     

Effect of blue-blocking glasses in major depressive disorder with sleep onset insomnia: A randomized,double-blind,placebo-controlled study

Blue wavelengths form the portion of the visible electromagnetic spectrum that most potently regulates circadian rhythm. We hypothesized that wearing blue-blocking (BB) glasses in the evening may influence circadian rhythm disturbances in patients with major depressive disorder (MDD), resulting in improved sleep and mood. We used a randomized placebo-controlled double-blinded design. Patients with MDD with sleep onset insomnia were randomly assigned to wearing either BB glasses or clear glasses (placebo). Patients were instructed to wear the glasses from 20:00 hours until bedtime for 2 weeks. We assessed sleep state (sleep quality on a visual analog scale, the Morningness–Eveningness Questionnaire [MEQ], and a sleep diary) and depressive symptoms at baseline and after 2 weeks. Data were analyzed with a full analysis set. In total, 20 patients were randomly assigned to the BB and placebo groups (BB group, n = 10; placebo group, n = 10). There were three dropouts (BB group, n = 1; placebo group, n = 2). At baseline, sleep quality, sleep latency (assessed via a sleep diary), and antipsychotics use differed between the groups. To take account of these differences, the baseline sleep state or depressive symptoms and antipsychotics use were used as covariates in the later analysis. The change scores for sleep quality did not show a significant improvement in the BB group compared with the placebo group (mean [standard deviation, SD] scores for BB versus placebo: 36.1 [31.7] versus 16.2 [15.1], p = 0.43), although half of the BB group showed a clear improvement in sleep quality. The change in MEQ scores did not significantly differ between the groups (p = 0.14), although there was a trend of a shift to morning type in the BB group (3.10 [4.95] points) and to evening type in the placebo group (0.50 [3.89] points). There were no statistically significant changes in depressive symptoms in either group. Across both groups, 40% of the participants reported pain or discomfort from wearing the glasses, which were available in only one size. Thus, the failure to find significant differences may have resulted from the glasses used in this study. Glasses fitted to individual patients may improve efficacy and safety. Replication of the study with a larger sample size and size-adjustable glasses is needed.     

DNA methylation aberrancies as a guide for surveillance and treatment of human cancers

DNA methylation aberrancies are hallmarks of human cancers and are characterized by global DNA hypomethylation of repetitive elements and non-CpG rich regions concomitant with locus-specific DNA hypermethylation. DNA methylation changes may result in altered gene expression profiles, most notably the silencing of tumor suppressors, microRNAs, endogenous retorviruses and tumor antigens due to promoter DNA hypermethylation, as well as oncogene upregulation due to gene-body DNA hypermethylation. Here, we review DNA methylation aberrancies in human cancers, their use in cancer surveillance and the interplay between DNA methylation and histone modifications in gene regulation. We also summarize DNA methylation inhibitors and their therapeutic effects in cancer treatment. In this context, we describe the integration of DNA methylation inhibitors with conventional chemotherapies, DNA repair inhibitors and immune-based therapies, to bring the epigenome closer to its normal state and increase sensitivity to other therapeutic agents to improve patient outcome and survival.     

The interplay between DNA and histone methylation: molecular mechanisms and disease implications

Methylation of cytosine in CpG dinucleotides and histone lysine and arginine residues is a chromatin modification that critically contributes to the regulation of genome integrity, replication, and accessibility. A strong correlation exists between the genome‐wide distribution of DNA and histone methylation, suggesting an intimate relationship between these epigenetic marks. Indeed, accumulating literature reveals complex mechanisms underlying the molecular crosstalk between DNA and histone methylation. These in vitro and in vivo discoveries are further supported by the finding that genes encoding DNA‐ and histone‐modifying enzymes are often mutated in overlapping human diseases. Here, we summarize recent advances in understanding how DNA and histone methylation cooperate to maintain the cellular epigenomic landscape. We will also discuss the potential implication of these insights for understanding the etiology of, and developing biomarkers and therapies for, human congenital disorders and cancers that are driven by chromatin abnormalities.