DNA methylation in human diseases

Polymerases and DNA Repair in Neurons: Implications in Neuronal Survival and Neurodegenerative Diseases

Most of the neurodegenerative diseases and aging are associated with reactive oxygen species (ROS) or other intracellular damaging agents that challenge the genome integrity of the neurons. As most of the mature neurons stay in G0/G1 phase, replication-uncoupled DNA repair pathways including BER, NER, SSBR, and NHEJ, are pivotal, efficient, and economic mechanisms to maintain genomic stability without reactivating cell cycle. In these progresses, polymerases are prominent, not only because they are responsible for both sensing and repairing damages, but also for their more diversified roles depending on the cell cycle phase and damage types. In this review, we summarized recent knowledge on the structural and biochemical properties of distinct polymerases, including DNA and RNA polymerases, which are known to be expressed and active in nervous system; the biological relevance of these polymerases and their interactors with neuronal degeneration would be most graphically illustrated by the neurological abnormalities observed in patients with hereditary diseases associated with defects in DNA repair; furthermore, the vicious cycle of the trinucleotide repeat (TNR) and impaired DNA repair pathway is also discussed. Unraveling the mechanisms and contextual basis of the role of the polymerases in DNA damage response and repair will promote our understanding about how long-lived postmitotic cells cope with DNA lesions, and why disrupted DNA repair contributes to disease origin, despite the diversity of mutations in genes. This knowledge may lead to new insight into the development of targeted intervention for neurodegenerative diseases.

Is Aberrant DNA Methylation a Key Factor in Molar Incisor Hypomineralization?

Molar incisor hypomineralization (MIH) is a qualitative disturbance of the enamel of the permanent molars and/or incisors. Its etiology is not clearly defined but is connected with different factors occurring before and after birth. It remains difficult to identify a single factor or group of factors, and the problem is further complicated by various overlapping mechanisms. In this study, we attempted to determine whether DNA methylation-an epigenetic mechanism-plays a key role in the etiology of MIH. We collected the epithelium of the oral mucosa from children with MIH and healthy individuals and analyzed its global DNA methylation level in each child using a 5-mC DNA ELISA kit after DNA isolation. There was no statistically significant difference between the global DNA methylation levels in the study and control groups. Then, we also analyzed the associations of the DNA methylation levels with different prenatal, perinatal, and postnatal factors, using appropriate statistical methods. Factors such as number of pregnancies, number of births, type of delivery, varicella infection (under 3 years old), and high fever (under 3 years old) were significantly important. This work can be seen as the first step towards further studies of the epigenetic background of the MIH etiology.

Harnessing the Full Potential of Multi-Omic Analyses to Advance the Study and Treatment of Chronic Kidney Disease

Chronic kidney disease (CKD) was the 12th leading cause of death globally in 2017 with the prevalence of CKD estimated at ~9%. Early detection and intervention for CKD may improve patient outcomes, but standard testing approaches even in developed countries do not facilitate identification of patients at high risk of developing CKD, nor those progressing to end-stage kidney disease (ESKD). Recent advances in CKD research are moving towards a more personalised approach for CKD. Heritability for CKD ranges from 30% to 75%, yet identified genetic risk factors account for only a small proportion of the inherited contribution to CKD. More in depth analysis of genomic sequencing data in large cohorts is revealing new genetic risk factors for common diagnoses of CKD and providing novel diagnoses for rare forms of CKD. Multi-omic approaches are now being harnessed to improve our understanding of CKD and explain some of the so-called 'missing heritability'. The most common omic analyses employed for CKD are genomics, epigenomics, transcriptomics, metabolomics, proteomics and phenomics. While each of these omics have been reviewed individually, considering integrated multi-omic analysis offers considerable scope to improve our understanding and treatment of CKD. This narrative review summarises current understanding of multi-omic research alongside recent experimental and analytical approaches, discusses current challenges and future perspectives, and offers new insights for CKD.

Dynamic changes in hepatic DNA methylation during the development of nonalcoholic fatty liver disease induced by a high-sugar diet

DNA methylation is an important epigenetic mechanism of gene expression control. The present study aimed to evaluate the temporal effect of isocaloric high-sugar diet (HSD) intake on the development of nonalcoholic fatty liver disease (NAFLD) and the role of DNA methylation in this event. Newly weaned Wistar rats were divided into eight groups and fed a standard chow diet or an HSD ad libitum for 4 weeks, 8 weeks, 15 weeks, and 18 weeks. After the experimental periods, the animals were euthanized and their livers were removed for histological analysis, gene expression of maintenance methylase (Dnmt1), de novo methylases (Dnmt3a and Dnmt3b), demethylases (Tet2 and Tet3) of DNA, and global DNA methylation. HSD intake led to the gradual development of NAFLD. HSD intake for 18 weeks was associated with downregulation of Dnmt1 expression and global DNA hypomethylation; these results were negatively correlated with more severe steatosis scores observed in these animals. The HSD consumption for 18 weeks was also associated with a decrease in Dnmt3a and Tet2 expression. Interestingly, the expression of de novo methyltransferase Dnmt3b was reduced by HSD during all experimental periods. Together, these results indicate that the downregulation of de novo DNA methylation, Dnmt3b, induced by HSD is the primary factor in the development of NAFLD. On the other hand, disease progression is associated with downregulation of maintenance DNA methylation and global DNA hypomethylation. These results suggest a link between the dynamic changes in hepatic DNA methylation and the development of NAFLD induced by an HSD intake.

State of the Art of Chemosensors in a Biomedical Context

Healthcare is undergoing large transformations, and it is imperative to leverage new technologies to support the advent of personalized medicine and disease prevention. It is now well accepted that the levels of certain biological molecules found in blood and other bodily fluids, as well as in exhaled breath, are an indication of the onset of many human diseases and reflect the health status of the person. Blood, urine, sweat, or saliva biomarkers can therefore serve in early diagnosis of diseases such as cancer, but also in monitoring disease progression, detecting metabolic disfunctions, and predicting response to a given therapy. For most point-of-care sensors, the requirement that patients themselves can use and apply them is crucial not only regarding the diagnostic part, but also at the sample collection level. This has stimulated the development of such diagnostic approaches for the non-invasive analysis of disease-relevant analytes. Considering these timely efforts, this review article focuses on novel, sensitive, and selective sensing systems for the detection of different endogenous target biomarkers in bodily fluids as well as in exhaled breath, which are associated with human diseases.

Challenges in Analyzing Functional Epigenetic Data in Perspective of Adolescent Psychiatric Health

The formative period of adolescence plays a crucial role in the development of skills and abilities for adulthood. Adolescents who are affected by mental health conditions are at risk of suicide and social and academic impairments. Gene-environment complementary contributions to the molecular mechanisms involved in psychiatric disorders have emphasized the need to analyze epigenetic marks such as DNA methylation (DNAm) and non-coding RNAs. However, the large and diverse bioinformatic and statistical methods, referring to the confounders of the statistical models, application of multiple-testing adjustment methods, questions regarding the correlation of DNAm across tissues, and sex-dependent differences in results, have raised challenges regarding the interpretation of the results. Based on the example of generalized anxiety disorder (GAD) and depressive disorder (MDD), we shed light on the current knowledge and usage of methodological tools in analyzing epigenetics. Statistical robustness is an essential prerequisite for a better understanding and interpretation of epigenetic modifications and helps to find novel targets for personalized therapeutics in psychiatric diseases.

Regulation of glutamate transport and neuroinflammation in a term newborn rat model of hypoxic–ischaemic brain injury

In the newborn brain, moderate-severe hypoxia–ischaemia induces glutamate excitotoxicity and inflammation, possibly via dysregulation of candidate astrocytic glutamate transporter ( Glt1) and pro-inflammatory cytokines (e.g. Tnfα, Il1β, Il6). Epigenetic mechanisms may mediate dysregulation. Hypotheses: (1) hypoxia–ischaemia dysregulates mRNA expression of these candidate genes; (2) expression changes in Glt1 are mediated by DNA methylation changes; and (3) methylation values in brain and blood are correlated. Seven-day-old rat pups ( n = 42) were assigned to nine groups based on treatment (for each timepoint: naïve ( n = 3), sham ( n = 3), hypoxia–ischaemia ( n = 8) and timepoint for tissue collection (6, 12 and 24 h post-hypoxia). Moderate hypoxic–ischemic brain injury was induced via ligation of the left common carotid artery followed by 100 min hypoxia (8% O2, 36°C). mRNA was quantified in cortex and hippocampus for the candidate genes, myelin ( Mbp), astrocytic ( Gfap) and neuronal ( Map2) markers (qPCR). DNA methylation was measured for Glt1 in cortex and blood (bisulphite pyrosequencing). Hypoxia–ischaemia induced pro-inflammatory cytokine upregulation in both brain regions at 6 h. This was accompanied by gene expression changes potentially indicating onset of astrogliosis and myelin injury. There were no significant changes in expression or promoter DNA methylation of Glt1. This pilot study supports accumulating evidence that hypoxia–ischaemia causes neuroinflammation in the newborn brain and prioritises further expression and DNA methylation analyses focusing on this pathway. Epigenetic blood biomarkers may facilitate identification of high-risk newborns at birth, maximising chances of neuroprotective interventions.

Alpha-synuclein overexpression induces epigenomic dysregulation of glutamate signaling and locomotor pathways

Parkinson’s disease (PD) is a neurological disorder with complex interindividual etiology that is becoming increasingly prevalent worldwide. Elevated alpha-synuclein levels can increase risk of PD and may influence epigenetic regulation of PD pathways. Here, we report genome-wide DNA methylation and hydroxymethylation alterations associated with overexpression of two PD-linked alpha-synuclein variants (wild-type and A30P) in LUHMES cells differentiated to dopaminergic neurons. Alpha-synuclein altered DNA methylation at thousands of CpGs and DNA hydroxymethylation at hundreds of CpGs in both genotypes, primarily in locomotor behavior and glutamate signaling pathway genes. In some cases, epigenetic changes were associated with transcription. SMITE network analysis incorporating H3K4me1 ChIP-seq to score DNA methylation and hydroxymethylation changes across promoters, enhancers, and gene bodies confirmed epigenetic and transcriptional deregulation of glutamate signaling modules in both genotypes. Our results identify distinct and shared impacts of alpha-synuclein variants on the epigenome, and associate alpha-synuclein with the epigenetic etiology of PD.

7-Aminoalkoxy-Quinazolines from Epigenetic Focused Libraries Are Potent and Selective Inhibitors of DNA Methyltransferase 1

Inhibitors of epigenetic writers such as DNA methyltransferases (DNMTs) are attractive compounds for epigenetic drug and probe discovery. To advance epigenetic probes and drug discovery, chemical companies are developing focused libraries for epigenetic targets. Based on a knowledge-based approach, herein we report the identification of two quinazoline-based derivatives identified in focused libraries with sub-micromolar inhibition of DNMT1 (30 and 81 nM), more potent than S-adenosylhomocysteine. Also, both compounds had a low micromolar affinity of DNMT3A and did not inhibit DNMT3B. The enzymatic inhibitory activity of DNMT1 and DNMT3A was rationalized with molecular modeling. The quinazolines reported in this work are known to have low cell toxicity and be potent inhibitors of the epigenetic target G9a. Therefore, the quinazoline-based compounds presented are attractive not only as novel potent inhibitors of DNMTs but also as dual and selective epigenetic agents targeting two families of epigenetic writers.

Oncogenomic Changes in Pancreatic Cancer and Their Detection in Stool

Pancreatic cancer (PC) is an aggressive malignancy with a dismal prognosis. To improve patient survival, the development of screening methods for early diagnosis is pivotal. Oncogenomic alterations present in tumor tissue are a suitable target for non-invasive screening efforts, as they can be detected in tumor-derived cells, cell-free nucleic acids, and extracellular vesicles, which are present in several body fluids. Since stool is an easily accessible source, which enables convenient and cost-effective sampling, it could be utilized for the screening of these traces. Herein, we explore the various oncogenomic changes that have been detected in PC tissue, such as chromosomal aberrations, mutations in driver genes, epigenetic alterations, and differentially expressed non-coding RNA. In addition, we briefly look into the role of altered gut microbiota in PC and their possible associations with oncogenomic changes. We also review the findings of genomic alterations in stool of PC patients, and the potentials and challenges of their future use for the development of stool screening tools, including the possible combination of genomic and microbiota markers.

Can Epigenetics Help Solve the Puzzle Between Concomitant Cardiovascular Injury and Severity of Coronavirus Disease 2019?

ABSTRACT

The ongoing coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 has significant implications in patients with concomitant cardiovascular disease (CVD) because they are the population at the greatest risk of death. The treatment of such patients and complications may represent a new challenge for the fields of cardiology and pharmacology. Thus, understanding the involvement of this viral infection in CVD might help to reduce the aggressiveness of SARS-CoV-2 in causing multiorgan infection and damage. SARS-CoV-2 disturbs the host epigenome and several epigenetic processes involved in the pathophysiology of COVID-19 that can directly affect the function and structure of the cardiovascular system (CVS). Hence, it would be relevant to identify epigenetic alterations that directly impact CVS physiology after SARS-CoV-2 infection. This could contribute to the view of this virus-induced CVS injury and direct forthcoming tackles for COVID-19 treatment to reduce mortality in patients with CVD. Targeting epigenetic marks could offer strong evidence for the development of novel antiviral therapies, especially in the context of COVID-19-related CVS damage. In this review, we address some of the main signaling pathways that are currently known as being involved in COVID-19 pathophysiology and the importance of this glint on epigenetics and some of its modifiers (epidrugs) to control the unregulated epitope activity in the context of SARS-CoV-2 infection, COVID-19, and underlying CVD.

Development of a Droplet Digital™ PCR DNA methylation detection and quantification assay of prenatal tobacco exposure

DNA methylation is a labile modification associated with gene expression control and environmental adaptations. High throughput, scalable and quantitative assessments of specific DNA methylation modifications in complex genomic regions for use in large population studies are needed. The performance of Droplet Digital™ PCR (ddPCR™) was investigated for DNA methylation detection against next-generation bisulfite sequencing (NGS) to demonstrate the ability of ddPCR to detect and validate DNA methylation levels and complex patterns among neighboring CpGs in regions associated with prenatal tobacco exposure. While both techniques are reproducible, ddPCR demonstrates a unique advantage for high-throughput DNA methylation analysis in large-scale population studies and provides the specificity to accurately measure DNA methylation of target CpGs in complex regions.

Future Perspectives in Oxidative Stress in Trisomy 13 and 18 Evaluation

Autosomal aneuploidies are the most frequently occurring congenital abnormalities and are related to many metabolic disorders, hormonal dysfunctions, neurotransmitter abnormalities, and intellectual disabilities. Trisomies are generated by an error of chromosomal segregation during cell division. Accumulating evidence has shown that deregulated gene expression resulting from the triplication of chromosomes 13 and 18 is associated with many disturbed cellular processes. Moreover, a disturbed oxidative stress status may be implicated in the occurrence of fetal malformations. Therefore, a literature review was undertaken to provide novel insights into the evaluation of trisomy 13 (T13) and 18 (T18) pathogeneses, with a particular concern on the oxidative stress. Corresponding to the limited literature data focused on factors leading to T13 and T18 phenotype occurrence, the importance of oxidative stress evaluation in T13 and T18 could enable the determination of subsequent disturbed metabolic pathways, highlighting the related role of mitochondrial dysfunction or epigenetics. This review illustrates up-to-date T13 and T18 research and discusses the strengths, limitations, and possible directions for future studies. The progressive unification of trisomy-related research protocols might provide potential medical targets in the future along with the implementation of the foundation of modern prenatal medicine.

Molecular manipulations and intestinal stem cell-derived organoids in inflammatory bowel disease

The pathogenesis of inflammatory bowel diseases (IBD) involves genetic predisposition, environmental factors, and a broadly dysregulated intestinal immune response to the commensal intestinal microflora. The interface between genetic predisposition and environmental factors is reflected in the epigenetic regulation at the transcriptional level. Treatment targets now involve mucosal and histological healing, but the future might additionally include normalization of intestinal cellular functions also at the molecular level, for example comprising complete restoration of phenotypic, genotypic, and epigenetic states. Recent developments in patient-derived epithelial intestinal stem cell (ISC) organoid technologies have opened exciting new therapeutic opportunities to potentially attain molecular healing by combining stem cell therapy with molecular manipulations using (epi)drugs and/or CRISPR/Cas9 genome editing. Here, we are the first to discuss the possibility for phenotypic, genotypic, and epigenetic restoration via molecular manipulations and stem cell therapy in IBD from a clinical perspective.

DNA Methylation Patterns According to Fatty Liver Index and Longitudinal Changes from the Korean Genome and Epidemiology Study (KoGES)

The role of differentially methylated regions (DMRs) in nonalcoholic fatty liver disease (NAFLD) is unclear. This study aimed to identify the role of DMR in NAFLD development and progression using the Korean Genome and Epidemiology Study (KoGES) cohort. We used laboratory evaluations and Illumina Methylation 450 k DNA methylation microarray data from KoGES. The correlation between fatty liver index (FLI) and genomic CpG sites was analyzed in 322 subjects. Longitudinal changes over 8 years were confirmed in 33 subjects. To identify CpG sites and genes related to FLI, we obtained enrichment terms for 6765 genes. DMRs were identified for both high (n = 128) and low (n = 194) groups on the basis of FLI 30 in 142 men and 180 women. To confirm longitudinal changes in 33 subjects, the ratio of follow-up and baseline investigation values was obtained. Correlations and group comparisons were performed for the 8 year change values. PITPNM3, RXFP3, and THRB were hypermethylated in the increased FLI groups, whereas SLC9A2 and FOXI3 were hypermethylated in the decreased FLI groups. DMRs describing NAFLD were determined, and functions related to inflammation were identified. Factors related to longitudinal changes are suggested, and blood circulation-related functions appear to be important in the management of NAFLD.

Interaction between a diabetes-related methylation site (TXNIP cg19693031) and variant (GLUT1 rs841853) on fasting blood glucose levels among non-diabetics

Background

Type 2 diabetes mellitus (T2DM) is caused by a combination of environmental, genetic, and epigenetic factors including, fasting blood glucose (FBG), genetic variant rs841853, and cg19693031 methylation. We evaluated the interaction between rs841853 and cg19693031 on the FBG levels of non-diabetic Taiwanese adults.

Methods

We used Taiwan Biobank (TWB) data collected between 2008 and 2016. The TWB data source contains information on basic demographics, personal lifestyles, medical history, methylation, and genotype. The study participants included 1300 people with DNA methylation data. The association of cg19693031 methylation (stratified into quartiles) with rs841853 and FBG was determined using multiple linear regression analysis. The beta-coefficients (β) and p-values were estimated.

Results

The mean ± standard deviation (SD) of FBG in rs841853-CC individuals (92.07 ± 7.78) did not differ significantly from that in the CA + AA individuals (91.62 ± 7.14). However, the cg19693031 methylation levels were significantly different in the two groups (0.7716 ± 0.05 in CC individuals and 0.7631 ± 0.05 in CA + AA individuals (p = 0.002). The cg19693031 methylation levels according to quartiles were β < 0.738592 (< Q1), 0.738592 ≤ 0.769992 (Q1–Q2), 0.769992 ≤ 0.800918 (Q2–Q3), and β ≥ 0.800918 (≥ Q3). FBG increased with decreasing cg19693031 methylation levels in a dose–response manner (p_trend = 0.005). The β-coefficient was − 0.0236 (p = 0.965) for Q2–Q3, 1.0317 (p = 0.058) for Q1–Q2, and 1.3336 (p = 0.019 for < Q1 compared to the reference quartile (≥ Q3). The genetic variant rs841853 was not significantly associated with FBG. However, its interaction with cg19693031 methylation was significant (p-value = 0.036). Based on stratification by rs841853 genotypes, only the CC group retained the inverse and dose–response association between FBG and cg19693031 methylation. The β (p-value) was 0.8082 (0.255) for Q2–Q3, 1.6930 (0.022) for Q1–Q2, and 2.2190 (0.004) for < Q1 compared to the reference quartile (≥ Q3). The p_trend was 0.002.

Conclusion

Summarily, methylation at cg19693031 was inversely associated with fasting blood glucose in a dose-dependent manner. The inverse association was more prominent in rs841853-CC individuals, suggesting that rs841853 could modulate the association between cg19693031 methylation and FBG. Our results suggest that genetic variants may be involved in epigenetic mechanisms associated with FBG, a hallmark of diabetes. Therefore, integrating genetic and epigenetic data may provide more insight into the early-onset of diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03269-y.

Steroidogenic enzymes in the hippocampus: Transcriptional regulation aspects

Neurosteroids are steroids synthesized de novo from cholesterol in brain regions, and regulate processes associated with the development and functioning of the nervous system. Enzymes and proteins involved in the synthesis of these steroids have been detected in several brain regions, including hippocampus, hypothalamus, and cerebral cortex. Hippocampus has long been associated with learning and memory functions, while the loss of its functionality has been linked to neurodegenerative pathologies. In this sense, neurosteroids are critical for the maintenance of hippocampal functions and neuroprotective effects. Moreover, several factors have been shown to deregulate expression of steroidogenic enzymes in the rodent brain, including aging, enrichment experiences, diet habits, drug/alcohol consumption, hormone fluctuations, neurodegenerative processes and other diseases. These transcriptional deregulations are mediated mainly by transcription factors and epigenetic mechanisms. An epigenetic modification of chromatin involves changes in bases and associated proteins in the absence of changes in the DNA sequence. One of the most well-studied mechanisms related to gene silencing is DNA methylation, which involves a reversible addition of methyl groups in a cytosine base. Importantly, these epigenetic marks could be maintained over time and could be transmitted transgenerationally. The aim of this chapter is to present the most relevant steroidogenic enzymes described in rodent hippocampus; to discuss about their transcriptional regulation under different conditions; to show the main gene control regions and to propose DNA methylation as an epigenetic mechanism through which the expression of these enzymes could be controlled.

DNA methylation of circadian genes and markers of cardiometabolic risk in female hospital workers: An exploratory study

Night shift work has been linked to increased risk of cardiovascular disease (CVD); however, the underlying mechanisms remain unclear. A compelling yet understudied mechanism involves differential DNA methylation of circadian genes. To investigate the relevance of this mechanism, we conducted an exploratory cross-sectional study of 74 female hospital personnel (38 day workers, 36 night shift workers). Sociodemographic, lifestyle, and health characteristics as well as shift work status and history were determined through self-report. Fasting blood samples were collected to measure markers of cardiometabolic risk and DNA was extracted to measure DNA methylation of 1150 cytosine-guanine (CpG) sites across 22 circadian genes. Associations between methylation levels at individual CpG sites (β-values) and markers of cardiometabolic risk were analyzed while considering effect modification by shift work status. The false discovery rate was applied to account for multiple comparisons (q ≤ 0.20). Two CpG sites [cg06758649 (CRY1) and cg06899802 (CSNK1A1)] were differentially associated with waist circumference and body mass index by shift work status, and eight CpG sites [cg26103512 (CSNK1D), cg03941313 (CSNK1E), cg18217763 (CSNK1E), cg16682686 (DEC1), cg12061096 (RORA), cg10133825 (RORA), cg19652148 (RORA), and cg22904654 (RORA)] were differentially associated with LDL cholesterol concentration by shift work status (all q ≤ 0.20). Our findings suggest that the relationship between DNA methylation of circadian genes and cardiometabolic risk differs by day and night shift worker status, which may contribute to mechanisms of increased risk of CVD observed among night shift workers.

16S rRNA Methyltransferases as Novel Drug Targets Against Tuberculosis

Tuberculosis (TB) is an airborne infectious disease caused by Mycobacterium tuberculosis (M.tb) whose natural history traces back to 70,000 years. TB remains a major global health burden. Methylation is a type of post-replication, post-transcriptional and post-translational epi-genetic modification involved in transcription, translation, replication, tissue specific expression, embryonic development, genomic imprinting, genome stability and chromatin structure, protein protein interactions and signal transduction indicating its indispensable role in survival of a pathogen like M.tb. The pathogens use this epigenetic mechanism to develop resistance against certain drug molecules and survive the lethality. Drug resistance has become a major challenge to tackle and also a major concern raised by WHO. Methyltransferases are enzymes that catalyze the methylation of various substrates. None of the current TB targets belong to methyltransferases which provides therapeutic opportunities to develop novel drugs through studying methyltransferases as potential novel targets against TB. Targeting 16S rRNA methyltransferases serves two purposes simultaneously: a) translation inhibition and b) simultaneous elimination of the ability to methylate its substrates hence stopping the emergence of drug resistance strains. There are ~ 40 different rRNA methyltransferases and 13 different 16S rRNA specific methyltransferases which are unexplored and provide a huge opportunity for treatment of TB.

Methylation patterns of the CDKN2B and CDKN2A genes in an indigenous population exposed to pesticides

The INK4 -ARF locus includes the CDKN2B and CDKN2A genes and is functionally relevant in the regulation of both cell proliferation and senescence. Studies have reported modifications of DNA methylation in this locus by exposure to environmental contaminants including pesticides; however, until now, specific methylation profiles have not been reported in genetically conserved populations exposed to occupational pesticides. The aim of this study was to determine the methylation profiles of the CDKN2B and CDKN2A genes in a genetically conserved population exposed to pesticides. A cross-sectional and analytical study was carried out in 190 Huichol indigenous persons. Information related to pesticide exposure, diet and other variables were obtained through the use of a structured questionnaire. Blood and urine samples were collected for methylation test and dialkylphosphates (DAP) determination, respectively. DNA methylation was measured by the pyrosequencing of bisulfite-treated DNA and DAP concentrations by gas chromatography-tandem mass spectrometry (GC/MS). The most frequent metabolite in the population was dimethylthiophosphate. The farmer group presented a higher methylation percentage of CDKN2B than the non-farmer group, but no differences in CDKN2A were observed between groups. A positive correlation between methylation of CpG site 3 of CDKN2B and time working in the field was observed in the farmer group. An association between methylation percentage of CDKN2B and age was also observed in the non-farmer group. These results suggest that pesticide exposure and exposure time in Huichol indigenous individuals could modify the methylation pattern of the CDKN2B gene.

Novel diagnostic DNA methylation episignatures expand and refine the epigenetic landscapes of Mendelian disorders

Overlapping clinical phenotypes and an expanding breadth and complexity of genomic associations are a growing challenge in the diagnosis and clinical management of Mendelian disorders. The functional consequences and clinical impacts of genomic variation may involve unique, disorder-specific, genomic DNA methylation episignatures. In this study, we describe 19 novel episignature disorders and compare the findings alongside 38 previously established episignatures for a total of 57 episignatures associated with 65 genetic syndromes. We demonstrate increasing resolution and specificity ranging from protein complex, gene, sub-gene, protein domain, and even single nucleotide-level Mendelian episignatures. We show the power of multiclass modeling to develop highly accurate and disease-specific diagnostic classifiers. This study significantly expands the number and spectrum of disorders with detectable DNA methylation episignatures, improves the clinical diagnostic capabilities through the resolution of unsolved cases and the reclassification of variants of unknown clinical significance, and provides further insight into the molecular etiology of Mendelian conditions.

The Role of Oxidative Stress in Intervertebral Disc Degeneration

Intervertebral disc degeneration is a very common type of degenerative disease causing severe socioeconomic impact, as well as a major cause of discogenic low back pain and herniated discs, placing a heavy burden on patients and the clinicians who treat them. IDD is known to be associating with a complex process involving in extracellular matrix and cellular damage, and in recent years, there is increasing evidence that oxidative stress is an important activation mechanism of IDD and that reactive oxygen and reactive nitrogen species regulate matrix metabolism, proinflammatory phenotype, autophagy and senescence in intervertebral disc cells, apoptosis, autophagy, and senescence. Despite the tremendous efforts of researchers within the field of IDD pathogenesis, the proven strategies to prevent and treat this disease are still very limited. Up to now, several antioxidants have been proved to be effective for alleviating IDD. In this article, we discussed that oxidative stress accelerates disc degeneration by influencing aging, inflammation, autophagy, and DNA methylation, and summarize some antioxidant therapeutic measures for IDD, indicating that antioxidant therapy for disc degeneration holds excellent promise.

Research Progress on Epigenetics of Diabetic Cardiomyopathy in Type 2 Diabetes

Diabetic cardiomyopathy (DCM) is characterized by diastolic relaxation abnormalities in its initial stages and by clinical heart failure (HF) without dyslipidemia, hypertension, and coronary artery disease in its last stages. DCM contributes to the high mortality and morbidity rates observed in diabetic populations. Diabetes is a polygenic, heritable, and complex condition that is exacerbated by environmental factors. Recent studies have demonstrated that epigenetics directly or indirectly contribute to pathogenesis. While epigenetic mechanisms such as DNA methylation, histone modifications, and non-coding RNAs, have been recognized as key players in the pathogenesis of DCM, some of their impacts remain not well understood. Furthering our understanding of the roles played by epigenetics in DCM will provide novel avenues for DCM therapeutics and prevention strategies.

Plasma microRNA-320a as a Potential Biomarker of Physiological Changes during Training in Professional Volleyball Players

A deeper insight into the mechanisms responsible for athlete performance that may serve as specific and detailed training indicators is still desired, because conventionally used biomarkers provide limited information about the adaptive processes that occur during exercise. The objective of our study was to assess insulin-like growth factor 1 receptors (IGF1R) gene expression and evaluate plasma concentration of selected microRNAs (miRNAs) during a 10-week training period (sampling times: week 1, 4, 7, and 10) in a group of 12 professional female volleyball players. Circulating miRNAs (miR-223, miR-320a, and miR-486) with established concentration in plasma and documented association with the IGF1 signaling pathway, which is involved in muscle development and recovery, were tested. The levels of analyzed miRNAs, tested by one-way ANOVA, were significantly different between four training periods during a 10-week training cycle (miR-223 p < 0.0001, miR-320a p = 0.00021, miR-486 p = 0.0037, respectively). The levels of IGF1R also appeared to be different (p = 0.00092), and their expression showed a trend to increase between the first and third periods. In the fourth period, the expression decreased, although it was higher compared with the baseline. Correlations between concentration levels of miR-223 and miR-320a (rs = 0.54, p < 0.001), as well as between miR-320a and miR-486 (rs = 0.73, p < 0.001) were also found. In the fourth period, a negative correlation between miR-223 plasma level and leucocyte IGF1R expression was found (rs = -0.63, p = 0.028). Multiple linear regression analysis showed that miR-320a (p = 0.024) and creatine kinase (p = 0.028) had the greatest impact on the expression levels of the IGF1R gene. Future studies are required to define whether these miRNAs, especially miR-320a, as well as IGF1R expression could be useful biomarkers of physiological changes during exercise and to discover their detailed biological roles in mode-specific exercise training adaptations of professional athletes.

Analysis of the DNA methylation pattern of the promoter region of calcitonin gene-related peptide 1 gene in patients with episodic migraine: An exploratory case-control study

Recent studies suggested that epigenetic mechanisms, including DNA methylation, may be involved in migraine pathogenesis. The calcitonin gene-related peptide (CGRP), encoded by calcitonin gene-related peptide 1 (CALCA) gene, plays a key role in the disease. The aim of the study was to evaluate DNA methylation of CALCA gene in patients with episodic migraine. 22 patients with episodic migraine (F/M 15/7, mean age 39.7 ± 13.4 years) and 20 controls (F/M 12/8, mean age 40.5 ± 14.8 years) were recruited. Genomic DNA was extracted from peripheral blood. Cytosine-to-thymine conversion was obtained with sodium bisulfite. The methylation pattern of two CpG islands in the promoter region of CALCA gene was analyzed. No difference of methylation of the 30 CpG sites at the distal region of CALCA promoter was observed between migraineurs and controls. Interestingly, in patients with episodic migraine the methylation level was lower in 2 CpG sites at the proximal promoter region (CpG -1461, p = 0.037, and -1415, p = 0.035, respectively). Furthermore, DNA methylation level at different CpG sites correlates with several clinical characteristics of the disease, as age at onset, presence of nausea/vomiting, depression and anxiety (p < 0.05). In conclusion, we found that DNA methylation profile in two CpG sites at the proximal promoter region of CALCA is lower in migraineurs when compared to controls. Intriguingly, the -1415 hypomethylated unit is located at the CREB binding site, a nuclear transcription factor. In addition, we found a correlation between the level of CALCA methylation and several clinical features of migraine. Further studies with larger sample size are needed to confirm these results.

Accurate Measurement of DNA Methylation: Challenges and Bias Correction

DNA methylation is a key epigenetic modification involved in gene regulation whose contribution to disease susceptibility is still not fully understood. As the cost of genome sequencing technologies continues to drop, it will soon become commonplace to perform genome-wide quantification of DNA methylation at a single base-pair resolution. However, the demand for its accurate quantification might vary across studies. When the scope of the analysis is to detect regions of the genome with different methylation patterns between two or more conditions, e.g., case vs control; treatments vs placebo, accuracy is not crucial. This is the case in epigenome-wide association studies used as genome-wide screening of methylation changes to detect new candidate genes and regions associated with a specific disease or condition. If the aim of the analysis is to use DNA methylation measurements as a biomarker for diseases diagnosis and treatment (Laird, Nat Rev Cancer 3:253-266, 2003; Bock, Epigenomics 1:99-110, 2009), it is instead recommended to produce accurate methylation measurements. Furthermore, if the objective is the detection of DNA methylation in subclonal tumor cell populations or in circulating tumor DNA or in any case of mosaicism, the importance of accuracy becomes critical. The aim of this chapter is to describe the factors that could affect the precise measurement of methylation levels and a recent Bayesian statistical method called MethylCal and its extension that have been proposed to minimize this problem.

A novel workflow for the qualitative analysis of DNA methylation data

•

A novel R package (EpiStatProfiler) for the qualitative analysis of DNA methylation data.

•

A novel workflow for the analysis of CG and non-CG epialleles starting from any type of bisulfite sequencing data.

•

EpiStatProfiler can perform strand-specific characterization of epialleles composition.

•

Important loci can be annotated along with their biological role and potential functions.

•

EpiStatProfiler has the ability to identify loci whose epiallelic profile is associated with disease pathogenesis.

DNA methylation is an epigenetic modification that plays a pivotal role in major biological mechanisms, such as gene regulation, genomic imprinting, and genome stability. Different combinations of methylated cytosines for a given DNA locus generate different epialleles and alterations of these latter have been associated with several pathological conditions. Existing computational methods and statistical tests relevant to DNA methylation analysis are mostly based on the comparison of average CpG sites methylation levels and they often neglect non-CG methylation. Here, we present EpiStatProfiler, an R package that allows the analysis of CpG and non-CpG based epialleles starting from bisulfite sequencing data through a collection of dedicated extraction functions and statistical tests. EpiStatProfiler is provided with a set of useful auxiliary features, such as customizable genomic ranges, strand-specific epialleles analysis, locus annotation and gene set enrichment analysis. We showcase the package functionalities on two public datasets by identifying putative relevant loci in mice harboring the Huntington’s disease-causing Htt gene mutation and in Ctcf +/− mice compared to their wild-type counterparts. To our knowledge, EpiStatProfiler is the first package providing functionalities dedicated to the analysis of epialleles composition derived from any kind of bisulfite sequencing experiment.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

Epigenetics in the Uterine Environment: How Maternal Diet and ART May Influence the Epigenome in the Offspring with Long-Term Health Consequences

The societal burden of non-communicable disease is closely linked with environmental exposures and lifestyle behaviours, including the adherence to a poor maternal diet from the earliest preimplantation period of the life course onwards. Epigenetic variations caused by a compromised maternal nutritional status can affect embryonic development. This review summarises the main epigenetic modifications in mammals, especially DNA methylation, histone modifications, and ncRNA. These epigenetic changes can compromise the health of the offspring later in life. We discuss different types of nutritional stressors in human and animal models, such as maternal undernutrition, seasonal diets, low-protein diet, high-fat diet, and synthetic folic acid supplement use, and how these nutritional exposures epigenetically affect target genes and their outcomes. In addition, we review the concept of thrifty genes during the preimplantation period, and some examples that relate to epigenetic change and diet. Finally, we discuss different examples of maternal diets, their effect on outcomes, and their relationship with assisted reproductive technology (ART), including their implications on epigenetic modifications.

Intellectual disability genomics: current state, pitfalls and future challenges

Intellectual disability (ID) can be caused by non-genetic and genetic factors, the latter being responsible for more than 1700 ID-related disorders. The broad ID phenotypic and genetic heterogeneity, as well as the difficulty in the establishment of the inheritance pattern, often result in a delay in the diagnosis. It has become apparent that massive parallel sequencing can overcome these difficulties. In this review we address: (i) ID genetic aetiology, (ii) clinical/medical settings testing, (iii) massive parallel sequencing, (iv) variant filtering and prioritization, (v) variant classification guidelines and functional studies, and (vi) ID diagnostic yield. Furthermore, the need for a constant update of the methodologies and functional tests, is essential. Thus, international collaborations, to gather expertise, data and resources through multidisciplinary contributions, are fundamental to keep track of the fast progress in ID gene discovery.

Biophysics is reshaping our perception of the epigenome: from DNA-level to high-throughput studies

Epigenetic research holds great promise to advance our understanding of biomarkers and regulatory processes in health and disease. An increasing number of new approaches, ranging from molecular to biophysical analyses, enable identifying epigenetic changes on the level of a single gene or the whole epigenome. The aim of this review is to highlight how the field is shifting from completely molecular-biology-driven solutions to multidisciplinary strategies including more reliance on biophysical analysis tools. Biophysics not only offers technical advancements in imaging or structure analysis but also helps to explore regulatory interactions. New computational methods are also being developed to meet the demand of growing data volumes and their processing. Therefore, it is important to capture these new directions in epigenetics from a biophysical perspective and discuss current challenges as well as multiple applications of biophysical methods and tools. Specifically, we gradually introduce different biophysical research methods by first considering the DNA-level information and eventually higher-order chromatin structures. Moreover, we aim to highlight that the incorporation of bioinformatics, machine learning, and artificial intelligence into biophysical analysis allows gaining new insights into complex epigenetic processes. The gained understanding has already proven useful in translational and clinical research providing better patient stratification options or new therapeutic insights. Together, this offers a better readiness to transform bench-top experiments into industrial high-throughput applications with a possibility to employ developed methods in clinical practice and diagnostics.

ANGPT1 methylation and delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage patients

Background:

Delayed cerebral ischemia (DCI) is a common secondary complication and an important cause of disability and mortality among patients who survive aneurysmal subarachnoid hemorrhage (aSAH). Knowledge on DCI pathogenesis, risk factors, and biomarkers are essential for early detection and improved prognosis. To investigate the role of DNA methylation in DCI risk, we conducted an epigenome-wide association study (EWAS) in 68 patients followed up to 1 year after the initial aneurysm rupture. Blood samples were collected within 48 h post hemorrhage and used for DNA methylation profiling at ~ 450k CpG sites. A separate cohort of 175 patients was sequenced for the top CpG sites from the discovery analysis for a replication of the EWAS findings.

Results:

EWAS did not identify any epigenome-wide significant CpGs. The top signal, cg18031596, was annotated to ANGPT1, a gene with critical functions in angiogenesis after vascular injury. Post hoc power calculations indicated a well-powered discovery analysis for cg18031596. Analysis of the replication cohort showed that four out of the five CpG sites sequenced at the ANGPT1 locus passed a Bonferroni-adjusted significance threshold. In a pooled analysis of the entire sample, three out of five yielded a significant p-value, and the top association signal (p-value = 0.004) was seen for a CpG that was not originally measured in the discovery EWAS. However, four ANGPT1 CpG sites had an opposite effect direction in the replication analysis compared to the discovery EWAS, marking a failure of replication. We carefully examined this observed flip in directions and propose several possible explanations in addition to that it was a random chance that ANGPT1 ranked at the top in the discovery EWAS.

Conclusions:

We failed to demonstrate a significant and consistent effect of ANGPT1 methylation in DCI risk in two cohorts. Though the replication attempt to weaken the overall support of this gene, given its relevant function and top rank of significance in the EWAS, our results call for future studies of larger aSAH cohorts to determine its relevance for the occurrence of DCI.

Epigenetic Measurement of Key Vertebrate Population Biology Parameters

The age, sex, and sexual maturity of individual animals are key parameters in assessing wild populations and informing conservation management strategies. These parameters represent the reproductive potential of a population and can indicate recovery rates or vulnerabilities. Natural populations of wild animals are difficult to study; logistically, economically, and due to the impacts of invasive biomonitoring. Genetic and epigenetic analyses offer a low impact, low cost, and information-rich alternative. As epigenetic mechanisms are intrinsically linked with both biological aging and reproductive processes, DNA methylation can be used as a suitable biomarker for population biology study. This review assesses published research utilizing DNA methylation analysis in relation to three key population parameters: age, sex, and sexual maturity. We review studies on wild vertebrates that investigate epigenetic age relationships, with successful age estimation assays designed for mammals, birds, and fish. For both determination of sex and identification of sexual maturity, very little has been explored regarding DNA methylation-based assays. Related research, however, confirms the links between DNA methylation and these processes. Future development of age estimation assays for underrepresented and key conservation taxa is suggested, as is the experimental development and design of DNA methylation-based assays for both sex and sexual maturity identification, further expanding the genomics toolkit for population biology studies.

Laboratory methods to decipher epigenetic signatures: a comparative review

Epigenetics refers to nucleotide sequence-independent events, and heritable changes, including DNA methylation and histone modification (as the two main processes), contributing to the phenotypic features of the cell. Both genetics and epigenetics contribute to determining the outcome of regulatory gene expression systems. Indeed, the flexibility of epigenetic effects and stability of genetic coding lead to gene regulation complexity in response signals. Since some epigenetic changes are significant in abnormalities such as cancers and neurodegenerative diseases, the initial changes, dynamic and reversible properties, and diagnostic potential of epigenomic phenomena are subject to epigenome-wide association studies (EWAS) for therapeutic aims. Based on recent studies, methodological developments are necessary to improve epigenetic research. As a result, several methods have been developed to explore epigenetic alterations at low, medium, and high scales, focusing on DNA methylation and histone modification detection. In this research field, bisulfite-, enzyme sensitivity- and antibody specificity-based techniques are used for DNA methylation, whereas histone modifications are gained based on antibody recognition. This review provides a mechanism-based understanding and comparative overview of the most common techniques for detecting the status of epigenetic effects, including DNA methylation and histone modifications, for applicable approaches from low- to high-throughput scales.

DNA Methylation and Type 2 Diabetes: Novel Biomarkers for Risk Assessment?

Diabetes is a severe threat to global health. Almost 500 million people live with diabetes worldwide. Most of them have type 2 diabetes (T2D). T2D patients are at risk of developing severe and life-threatening complications, leading to an increased need for medical care and reduced quality of life. Improved care for people with T2D is essential. Actions aiming at identifying undiagnosed diabetes and at preventing diabetes in those at high risk are needed as well. To this end, biomarker discovery and validation of risk assessment for T2D are critical. Alterations of DNA methylation have recently helped to better understand T2D pathophysiology by explaining differences among endophenotypes of diabetic patients in tissues. Recent evidence further suggests that variations of DNA methylation might contribute to the risk of T2D even more significantly than genetic variability and might represent a valuable tool to predict T2D risk. In this review, we focus on recent information on the contribution of DNA methylation to the risk and the pathogenesis of T2D. We discuss the limitations of these studies and provide evidence supporting the potential for clinical application of DNA methylation marks to predict the risk and progression of T2D.

Beyond sequencing: machine learning algorithms extract biology hidden in Nanopore signal data

Nanopore sequencing provides signal data corresponding to the nucleotide motifs sequenced. Through machine learning-based methods, these signals are translated into long-read sequences that overcome the read size limit of short-read sequencing. However, analyzing the raw nanopore signal data provides many more opportunities beyond just sequencing genomes and transcriptomes: algorithms that use machine learning approaches to extract biological information from these signals allow the detection of DNA and RNA modifications, the estimation of poly(A) tail length, and the prediction of RNA secondary structures. In this review, we discuss how developments in machine learning methodologies contributed to more accurate basecalling and lower error rates, and how these methods enable new biological discoveries. We argue that direct nanopore sequencing of DNA and RNA provides a new dimensionality for genomics experiments and highlight challenges and future directions for computational approaches to extract the additional information provided by nanopore signal data.

Adverse Childhood Experiences and Subsequent Chronic Diseases Among Middle-aged or Older Adults in China and Associations With Demographic and Socioeconomic Characteristics

IMPORTANCE

Associations between adverse childhood experiences (ACEs) and chronic diseases among middle-aged or older Chinese individuals have not been well documented. In addition, whether demographic and socioeconomic characteristics modify any such associations has been underexplored.

OBJECTIVES

To examine associations between ACEs and subsequent chronic diseases and to assess whether age, sex, educational level, annual per capita household expenditure level, and childhood economic hardship modify these associations.

DESIGN, SETTING, AND PARTICIPANTS

This population-based cross-sectional study used data from the China Health and Retirement Longitudinal Study (CHARLS), a survey of residents aged 45 years or older in 28 provinces across China; specifically, the study used data from the CHARLS life history survey conducted from June 1 to December 31, 2014, and a CHARLS follow-up health survey conducted from July 1 to September 30, 2015. The study population included 11 972 respondents aged 45 years or older who had data on at least 1 of 14 specified chronic diseases and information on all 12 of the ACE indicators included in this study. Data analysis was performed from December 1 to 30, 2020.

EXPOSURES

Any of 12 ACEs (physical abuse, emotional neglect, household substance abuse, household mental illness, domestic violence, incarcerated household member, parental separation or divorce, unsafe neighborhood, bullying, parental death, sibling death, and parental disability), measured by indicators on a questionnaire. The number of ACEs per participant was summed and categorized into 1 of 5 cumulative-score groups: 0, 1, 2, 3, and 4 or more.

MAIN OUTCOMES AND MEASURES

Hypertension, dyslipidemia, diabetes, heart disease, stroke, chronic lung disease, asthma, liver disease, cancer, digestive disease, kidney disease, arthritis, psychiatric disease, and memory-related disease were defined by self-reported physician diagnoses or in combination with health assessment and medication data. Multimorbidity was defined as the presence of 2 or more of these 14 chronic diseases. Logistic regression models were used to assess associations of the 12 ACEs with the 14 chronic diseases and with multimorbidity. Modification of the associations by demographic and socioeconomic characteristics was assessed by stratified analyses and tests for interaction.

RESULTS

Of the 11 972 individuals included (mean [SD] age, 59.85 [9.56] years; 6181 [51.6%] were females), 80.9% had been exposed to at least 1 ACE and 18.0% reported exposure to 4 or more ACEs. Compared with those without ACE exposure, participants who experienced 4 or more ACEs had increased risks of dyslipidemia, chronic lung disease, asthma, liver disease, digestive disease, kidney disease, arthritis, psychiatric disease, memory-related disease, and multimorbidity. The estimated odds ratios (ORs) ranged from 1.27 (95% CI, 1.02-1.59) for dyslipidemia to 2.59 (95% CI, 2.16-3.11) for digestive disease. A dose-response association was also observed between the number of ACEs and the risk of most of the chronic diseases (excluding hypertension, diabetes, and cancer) (eg, chronic lung disease for ≥4 ACEs vs none: OR, 2.01; 95% CI, 1.59-2.55; P < .001 for trend) and of multimorbidity (for individuals among the overall study population with ≥4 ACEs vs none: OR, 2.03; 95% CI, 1.70-2.41; P < .001 for trend). The demographic or socioeconomic characteristics of age, sex, educational level, annual per capita household expenditure level, or childhood economic hardship were not shown to significantly modify the associations between ACEs and multimorbidity.

CONCLUSIONS AND RELEVANCE

In this population-based, cross-sectional study of adults in China, exposure to ACEs was associated with higher risks of chronic diseases regardless of demographic and socioeconomic characteristics during childhood or adulthood. These findings suggest a need to prevent ACEs and a need for a universal life-course public health strategy to reduce potential adverse health outcomes later in life among individuals who experience them.

Ambient temperature and genome-wide DNA methylation: A twin and family study in Australia

Little is known about the association between ambient temperature and DNA methylation, which is a potential biological process through which ambient temperature affects health. This study aimed to evaluate the association between ambient temperature and DNA methylation across human genome. We included 479 Australian women, including 132 twin pairs and 215 sisters of these twins. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on average ambient temperature during eight different exposure windows [lag0d (the blood draw day), lag0-7d (the current day and previous seven days prior to blood draw), lag0-14d, lag0-21d, lag0-28d, lag0-90d, lag0-180d, and lag0-365d)] was linked to each participant's home address. For each cytosine-guanine dinucleotide (CpG), we evaluated the association between its methylation level and temperature using generalized estimating equations (GEE), adjusting for important covariates. We used comb-p and DMRcate to identify differentially methylated regions (DMRs). We identified 31 CpGs at which blood DNA methylation were significantly associated with ambient temperature with false discovery rate [FDR] < 0.05. There were 82 significant DMRs identified by both comb-p (Sidak p-value < 0.01) and DMRcate (FDR < 0.01). Most of these CpGs and DMRs only showed association with temperature during one specific exposure window. These CpGs and DMRs were mapped to 85 genes. These related genes have been related to many human chronic diseases or phenotypes (e.g., diabetes, arthritis, breast cancer, depression, asthma, body height) in previous studies. The signals of short-term windows (lag0d and lag0-21d) showed enrichment in biological processes related to cell adhesion. In conclusion, short-, medium-, and long-term exposures to ambient temperature were all associated with blood DNA methylation, but the target genomic loci varied by exposure window. These differential methylation signals may serve as potential biomarkers to understand the health impacts of temperature.

Deep structure of DNA for genomic analysis

Recent advances in next generation sequencing, deep networks and other bioinformatic tools have enabled us to mine huge amount of genomic information about living organisms in the post-microarray era. However, these tools do not explicitly factor in the role of the underlying DNA biochemistry (particularly, DNA hybridization) essential to life processes. Here, we focus more precisely on the role that DNA hybridization plays in determining properties of biological organisms at the macro-level. We illustrate its role with solutions to challenging problems in human disease. These solutions are made possible by novel structural properties of DNA hybridization landscapes revealed by a metric model of oligonucleotides of a common length that makes them reminiscent of some planets in our solar system, particularly earth and saturn. They allow a judicious selection of so-called noncrosshybridizing (nxh) bases that offer substantial reduction of DNA sequences of arbitrary length into a few informative features. The quality assessment of the information extracted by them is high because of their very low Shannon Entropy, i.e. they minimize the degree of uncertainty in hybridization that makes results on standard microarrays irreproducible. For example, SNP classification (pathogenic/nonpathogenic) and pathogen identification can be solved with high sensitivity (~77%/100%) and specificity (~92%/100%, respectively) for combined taxa on a sample of over 264 fully coding sequences in whole bacterial genomes and fungal mitochondrial genomes using machine learning (ML) models. These methods can be applied to several other interesting research questions that could be addressed with similar genomic analyses.

An effective processing pipeline for harmonizing DNA methylation data from Illumina's 450K and EPIC platforms for epidemiological studies

OBJECTIVE

Illumina BeadChip arrays are commonly used to generate DNA methylation data for large epidemiological studies. Updates in technology over time create challenges for data harmonization within and between studies, many of which obtained data from the older 450K and newer EPIC platforms. The pre-processing pipeline for DNA methylation is not trivial, and influences the downstream analyses. Incorporating different platforms adds a new level of technical variability that has not yet been taken into account by recommended pipelines. Our study evaluated the performance of various tools on different versions of platform data harmonization at each step of pre-processing pipeline, including quality control (QC), normalization, batch effect adjustment, and genomic inflation. We illustrate our novel approach using 450K and EPIC data from the Diabetes Autoimmunity Study in the Young (DAISY) prospective cohort.

RESULTS

We found normalization and probe filtering had the biggest effect on data harmonization. Employing a meta-analysis was an effective and easily executable method for accounting for platform variability. Correcting for genomic inflation also helped with harmonization. We present guidelines for studies seeking to harmonize data from the 450K and EPIC platforms, which includes the use of technical replicates for evaluating numerous pre-processing steps, and employing a meta-analysis.

Genome-wide methylation data improves dissection of the effect of smoking on body mass index

Variation in obesity-related traits has a genetic basis with heritabilities between 40 and 70%. While the global obesity pandemic is usually associated with environmental changes related to lifestyle and socioeconomic changes, most genetic studies do not include all relevant environmental covariates, so the genetic contribution to variation in obesity-related traits cannot be accurately assessed. Some studies have described interactions between a few individual genes linked to obesity and environmental variables but there is no agreement on their total contribution to differences between individuals. Here we compared self-reported smoking data and a methylation-based proxy to explore the effect of smoking and genome-by-smoking interactions on obesity related traits from a genome-wide perspective to estimate the amount of variance they explain. Our results indicate that exploiting omic measures can improve models for complex traits such as obesity and can be used as a substitute for, or jointly with, environmental records to better understand causes of disease.

Accelerated Epigenetic Aging in Peripheral Blood does not Predict Dementia Risk

BACKGROUND

There is strong evidence that epigenetic age acceleration is associated with increased risk of later-life diseases and all-cause mortality. However, there is currently limited evidence that suggests accelerated epigenetic age is associated with dementia risk.

OBJECTIVE

This study aims to clarify whether epigenetic biomarkers of accelerated aging can predict dementia risk, which is an important consideration as aging is the greatest risk factor for the disease.

METHODS

DNA methylation was measured in peripheral blood samples provided by 160 participants from the ASPirin in Reducing Events in the Elderly study, including 73 pre-symptomatic dementia cases and 87 controls matched for age, sex, and smoking and education status. Epigenetic age was calculated using Horvath, Hannum, GrimAge and PhenoAge DNA methylation clocks, and age acceleration (the disparity between chronological age and epigenetic age) was determined.

RESULTS

There was no difference in age acceleration between dementia cases and controls. In males, only Hannum's intrinsic epigenetic age acceleration was increased in pre-symptomatic dementia cases compared to controls (Δ +1.8 years, p = 0.03).

CONCLUSION

These findings provide no strong evidence that accelerated epigenetic aging measured in peripheral blood can predict dementia risk.

Epigenetic age prediction in semen - marker selection and model development

DNA methylation analysis is becoming increasingly useful in biomedical research and forensic practice. The discovery of differentially methylated sites (DMSs) that continuously change over an individual's lifetime has led to breakthroughs in molecular age estimation. Although semen samples are often used in forensic DNA analysis, previous epigenetic age prediction studies mainly focused on somatic cell types. Here, Infinium MethylationEPIC BeadChip arrays were applied to semen-derived DNA samples, which identified numerous novel DMSs moderately correlated with age. Validation of the ten most age-correlated novel DMSs and three previously known sites in an independent set of semen-derived DNA samples using targeted bisulfite massively parallel sequencing, confirmed age-correlation for nine new and three previously known markers. Prediction modelling revealed the best model for semen, based on 6 CpGs from newly identified genes SH2B2, EXOC3, IFITM2, and GALR2 as well as the previously known FOLH1B gene, which predict age with a mean absolute error of 5.1 years in an independent test set. Further increases in the accuracy of age prediction from semen DNA will require technological progress to allow sensitive, simultaneous analysis of a much larger number of age correlated DMSs from the compromised DNA typical of forensic semen stains.

CRISPR as a Diagnostic Tool

Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system has recently gained growing attention as a diagnostic tool due to its capability of specific gene targeting. It consists of Cas enzymes and a guide RNA (gRNA) that can cleave the target DNA or RNA based on the sequence of the gRNA, making it an attractive genetic engineering technique. In addition to the target-specific binding and cleavage, the trans-cleavage activity was reported for some Cas proteins, including Cas12a and Cas13a, which is to cleave the surrounding single-stranded DNA or RNA upon the target binding of Cas-gRNA complex. All these activities of the CRISPR-Cas system are based on its target-specific binding, making it applied to develop diagnostic methods by detecting the disease-related gene as well as microRNAs and the genetic variations such as single nucleotide polymorphism and DNA methylation. Moreover, it can be applied to detect the non-nucleic acids target such as proteins. In this review, we cover the various CRISPR-based diagnostic methods by focusing on the activity of the CRISPR-Cas system and the form of the target. The CRISPR-based diagnostic methods without target amplification are also introduced briefly.

Characteristics and Clinical Application of Extracellular Vesicle-Derived DNA

Extracellular vesicles (EVs) carry RNA, proteins, lipids, and diverse biomolecules for intercellular communication. Recent studies have reported that EVs contain double-stranded DNA (dsDNA) and oncogenic mutant DNA. The advantage of EV-derived DNA (EV DNA) over cell-free DNA (cfDNA) is the stability achieved through the encapsulation in the lipid bilayer of EVs, which protects EV DNA from degradation by external factors. The existence of DNA and its stability make EVs a useful source of biomarkers. However, fundamental research on EV DNA remains limited, and many aspects of EV DNA are poorly understood. This review examines the known characteristics of EV DNA, biogenesis of DNA-containing EVs, methylation, and next-generation sequencing (NGS) analysis using EV DNA for biomarker detection. On the basis of this knowledge, this review explores how EV DNA can be incorporated into diagnosis and prognosis in clinical settings, as well as gene transfer of EV DNA and its therapeutic potential.

Promoter Methylation Status in Pro-opiomelanocortin Does Not Contribute to Dyspigmentation in Hypertrophic Scar

Burn injuries frequently result in hypertrophic scars (HTSs), specifically when excision and grafting are delayed due to limited resources or patient complications. In patient populations with dark baseline pigmentation, one symptom of HTS that often occurs is dyspigmentation. The mechanism behind dyspigmentation has not been explored, and, as such, prevention and treatment strategies for this morbidity are lacking. The mechanism by which cells make pigment is controlled at the apex of the pathway by pro-opiomelanocortin (POMC), which is cleaved to its products alpha-melanocyte-stimulating hormone (α-MSH) and adrenocorticotropin hormone (ACTH). α-MSH and ACTH secreted by keratinocytes bind to melanocortin 1 receptor (MC1R), expressed on melanocytes, to initiate melanogenesis. POMC protein expression is upregulated in hyperpigmented scar compared to hypopigmented scar by an unknown mechanism in a Duroc pig model of HTS. POMC RNA levels, as well as the POMC gene promoter methylation status were investigated as a possible mechanism. DNA was isolated from biopsies obtained from distinct areas of hyper- or hypopigmented scar and normal skin. DNA was bisulfite-converted, and amplified using two sets of primers to observe methylation patterns in two different CpG islands near the POMC promoter. Amplicons were then sequenced and methylation patterns were evaluated. POMC gene expression was significantly downregulated in hypopigmented scar compared to normal skin, consistent with previously reported protein expression levels. There were significant changes in methylation of the POMC promoter; however, none that would account for the development of hyper- or hypopigmentation. Future work will focus on other areas of POMC transcriptional regulation.

Functional Interplay between Methyltransferases and Inflammasomes in Inflammatory Responses and Diseases

An inflammasome is an intracellular protein complex that is activated in response to a pathogenic infection and cellular damage. It triggers inflammatory responses by promoting inflammatory cell death (called pyroptosis) and the secretion of pro-inflammatory cytokines, interleukin (IL)-1β and IL-18. Many types of inflammasomes have been identified and demonstrated to play a central role in inducing inflammatory responses, leading to the onset and progression of numerous inflammatory diseases. Methylation is a biological process by which methyl groups are transferred from methyl donors to proteins, nucleic acids, and other cellular molecules. Methylation plays critical roles in various biological functions by modulating gene expression, protein activity, protein localization, and molecular stability, and aberrant regulation of methylation causes deleterious outcomes in various human diseases. Methylation is a key determinant of inflammatory responses and diseases. This review highlights the current understanding of the functional relationship between inflammasome regulation and methylation of cellular molecules in inflammatory responses and diseases.

Exploiting Single-Cell Tools in Gene and Cell Therapy

Single-cell molecular tools have been developed at an incredible pace over the last five years as sequencing costs continue to drop and numerous molecular assays have been coupled to sequencing readouts. This rapid period of technological development has facilitated the delineation of individual molecular characteristics including the genome, transcriptome, epigenome, and proteome of individual cells, leading to an unprecedented resolution of the molecular networks governing complex biological systems. The immense power of single-cell molecular screens has been particularly highlighted through work in systems where cellular heterogeneity is a key feature, such as stem cell biology, immunology, and tumor cell biology. Single-cell-omics technologies have already contributed to the identification of novel disease biomarkers, cellular subsets, therapeutic targets and diagnostics, many of which would have been undetectable by bulk sequencing approaches. More recently, efforts to integrate single-cell multi-omics with single cell functional output and/or physical location have been challenging but have led to substantial advances. Perhaps most excitingly, there are emerging opportunities to reach beyond the description of static cellular states with recent advances in modulation of cells through CRISPR technology, in particular with the development of base editors which greatly raises the prospect of cell and gene therapies. In this review, we provide a brief overview of emerging single-cell technologies and discuss current developments in integrating single-cell molecular screens and performing single-cell multi-omics for clinical applications. We also discuss how single-cell molecular assays can be usefully combined with functional data to unpick the mechanism of cellular decision-making. Finally, we reflect upon the introduction of spatial transcriptomics and proteomics, its complementary role with single-cell RNA sequencing (scRNA-seq) and potential application in cellular and gene therapy.

Oncolytic Viruses in Combination Therapeutic Approaches with Epigenetic Modulators: Past, Present, and Future Perspectives

Simple Summary

Cancer rates have been accelerating significantly in recent years. Despite notable advances having been made in cancer therapy, and numerous studies being currently conducted in clinical trials, research is always looking for new treatment. Novel and promising anticancer therapies comprise combinations of oncolytic viruses and epigenetic modulators, including chromatin modifiers, such as DNA methyltransferase and histone deacetylases, and microRNA. Combinatorial treatments have several advantages: they enhance viral entry, replication, and spread between proximal cells and, moreover, they strengthen the immune response. In this review we summarize the main combination of therapeutic approaches, giving an insight into past, present, and future perspectives.

Abstract

According to the World Cancer Report, cancer rates have been increased by 50% with 15 million new cases in the year 2020. Hepatocellular carcinoma (HCC) is the only one of the most common tumors to cause a huge increase in mortality with a survival rate between 40% and 70% at 5 years, due to the high relapse and limitations associated with current therapies. Despite great progress in medicine, oncological research is always looking for new therapies: different technologies have been evaluated in clinical trials and others have been already used in clinics. Among them, oncolytic virotherapy represents a therapeutic option with a widespread possibility of approaches and applications. Oncolytic viruses are naturally occurring, or are engineered, viruses characterized by the unique features of preferentially infecting, replicating, and lysing malignant tumor cells, as well as activating the immune response. The combination of oncolytic virotherapy and chemical drugs are arousing great interest in the tumor treatment. In this scenario, novel and promising anticancer therapies comprise combinations of oncolytic viruses and epigenetic modulators or inhibitors of the signalling pathways. Combination treatments are required to improve the immune response and allow viral entry, replication, and diffusion between proximal cells. In this review, we summarize all combination therapies associated with virotherapy, including co-administered inhibitors of chromatin modifiers (combination strategies) and inserted target sites for miRNAs (recombination or arming strategies).