Longitudinal personal DNA methylome dynamics in a human with a chronic condition

Neoantigen landscape supports feasibility of personalized cancer vaccine for follicular lymphoma

ABSTRACT

Personalized cancer vaccines designed to target neoantigens represent a promising new treatment paradigm in oncology. In contrast to classical idiotype vaccines, we hypothesized that "polyvalent" vaccines could be engineered for the personalized treatment of follicular lymphoma (FL) using neoantigen discovery by combined whole-exome sequencing (WES) and RNA sequencing (RNA-seq). Fifty-eight tumor samples from 57 patients with FL underwent WES and RNA-seq. Somatic and B-cell clonotype neoantigens were predicted and filtered to identify high-quality neoantigens. B-cell clonality was determined by the alignment of B-cell receptor (BCR) CDR3 regions from RNA-seq data, grouping at the protein level, and comparison with the BCR repertoire from healthy individuals using RNA-seq data. An average of 52 somatic mutations per patient (range, 2-172) were identified, and ≥2 (median, 15) high-quality neoantigens were predicted for 56 of 58 FL samples. The predicted neoantigen peptides were composed of missense mutations (77%), indels (9%), gene fusions (3%), and BCR sequences (11%). Building off of these preclinical analyses, we initiated a pilot clinical trial using personalized neoantigen vaccination combined with PD-1 blockade in patients with relapsed or refractory FL (#NCT03121677). Synthetic long peptide vaccines targeting predicted high-quality neoantigens were successfully synthesized for and administered to all 4 patients enrolled. Initial results demonstrate feasibility, safety, and potential immunologic and clinical responses. Our study suggests that a genomics-driven personalized cancer vaccine strategy is feasible for patients with FL, and this may overcome prior challenges in the field. This trial was registered at www.ClinicalTrials.gov as #NCT03121677.

Comparative transcriptome and methylome of polar bears, giant and red pandas reveal diet-driven adaptive evolution

Epigenetic regulation plays an important role in the evolution of species adaptations, yet little information is available on the epigenetic mechanisms underlying the adaptive evolution of bamboo-eating in both giant pandas (Ailuropoda melanoleuca) and red pandas (Ailurus fulgens). To investigate the potential contribution of epigenetic to the adaptive evolution of bamboo-eating in giant and red pandas, we performed hepatic comparative transcriptome and methylome analyses between bamboo-eating pandas and carnivorous polar bears (Ursus maritimus). We found that genes involved in carbohydrate, lipid, amino acid, and protein metabolism showed significant differences in methylation and expression levels between the two panda species and polar bears. Clustering analysis of gene expression revealed that giant pandas did not form a sister group with the more closely related polar bears, suggesting that the expression pattern of genes in livers of giant pandas and red pandas have evolved convergently driven by their similar diets. Compared to polar bears, some key genes involved in carbohydrate metabolism and biological oxidation and cholesterol synthesis showed hypomethylation and higher expression in giant and red pandas, while genes involved in fat digestion and absorption, fatty acid metabolism, lysine degradation, resistance to lipid peroxidation and detoxification showed hypermethylation and low expression. Our study elucidates the special nutrient utilization mechanism of giant pandas and red pandas and provides some insights into the molecular mechanism of their adaptive evolution of bamboo feeding. This has important implications for the breeding and conservation of giant pandas and red pandas.

Differential methylation patterns from clusters associated with glucose metabolism: evidence from a Shanghai twin study

Aim: To assess the associations between genome-wide DNA methylation (DNAm) and glucose metabolism among a Chinese population, in particular the multisite correlation. Materials & methods: Epigenome-wide associations with fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) were analyzed among 100 Shanghai monozygotic (MZ) twin pairs using the Infinium HumanMethylationEPIC v2.0 BeadChip. We conducted a Pearson's correlation test, hierarchical cluster and pairwise analysis to examine the differential methylation patterns from clusters. Results: Cg01358804 (TXNIP) was identified as the most significant site associated with FPG and HbA1c. Two clusters with hypermethylated and hypomethylated patterns were observed for both FPG and HbA1c. Conclusion: Differential methylation patterns from clusters may provide new clues for epigenetic changes and biological mechanisms in glucose metabolism.

DNA methylation-mediated Rbpjk suppression protects against fracture nonunion caused by systemic inflammation

Challenging skeletal repairs are frequently seen in patients experiencing systemic inflammation. To tackle the complexity and heterogeneity of the skeletal repair process, we performed single-cell RNA sequencing and revealed that progenitor cells were one of the major lineages responsive to elevated inflammation and this response adversely affected progenitor differentiation by upregulation of Rbpjk in fracture nonunion. We then validated the interplay between inflammation (via constitutive activation of Ikk2, Ikk2ca) and Rbpjk specifically in progenitors by using genetic animal models. Focusing on epigenetic regulation, we identified Rbpjk as a direct target of Dnmt3b. Mechanistically, inflammation decreased Dnmt3b expression in progenitor cells, consequently leading to Rbpjk upregulation via hypomethylation within its promoter region. We also showed that Dnmt3b loss-of-function mice phenotypically recapitulated the fracture repair defects observed in Ikk2ca-transgenic mice, whereas Dnmt3b-transgenic mice alleviated fracture repair defects induced by Ikk2ca. Moreover, Rbpjk ablation restored fracture repair in both Ikk2ca mice and Dnmt3b loss-of-function mice. Altogether, this work elucidates a common mechanism involving a NF-κB/Dnmt3b/Rbpjk axis within the context of inflamed bone regeneration. Building on this mechanistic insight, we applied local treatment with epigenetically modified progenitor cells in a previously established mouse model of inflammation-mediated fracture nonunion and showed a functional restoration of bone regeneration under inflammatory conditions through an increase in progenitor differentiation potential.

Serial Sampling of the Small Airway Epithelium to Identify Persistent Smoking-dysregulated Genes

Rationale: The small airway epithelium (beyond the sixth generation), the initiation site of smoking-induced airway disorders, is highly sensitive to the stress of smoking. Because of variations over time in smoking habits, the small airway epithelium transcriptome is dynamic, fluctuating not only among smokers but also within each smoker. Objectives: To perform accurate assessment of the smoking-related dysregulation of the human small airway epithelium despite the variation of smoking within the same individual and of the effects of smoking cessation on the dysregulated transcriptome. Methods: We conducted serial sampling of the same smokers and nonsmoker control subjects over time to identify persistent smoking dysregulation of the biology of the small airway epithelium over 1 year. We conducted serial sampling of smokers who quit smoking, before and after smoking cessation, to assess the effect of smoking cessation on the smoking-dysregulated genes. Measurements and Main Results: Repeated measures ANOVA of the small airway epithelium transcriptome sampled four times in the same individuals over 1 year enabled the identification of 475 persistent smoking-dysregulated genes. Most genes were normalized after 12 months of smoking cessation; however, 53 (11%) genes, including CYP1B1, PIR, ME1, and TRIM16, remained persistently abnormally expressed. Dysregulated pathways enriched with the nonreversible genes included xenobiotic metabolism signaling, bupropion degradation, and nicotine degradation. Conclusions: Analysis of repetitive sampling of the same individuals identified persistent smoking-induced dysregulation of the small airway epithelium transcriptome and the effect of smoking cessation. These results help identify targets for the development of therapies that can be applicable to smoking-related airway diseases.

An epigenetic signature of advanced colorectal cancer metastasis

Colorectal cancer (CRC) is a leading cause of morbidity and mortality worldwide. The majority of CRC deaths are caused by tumor metastasis, even following treatment. There is strong evidence for epigenetic changes, such as DNA methylation, accompanying CRC metastasis and poorer patient survival. Earlier detection and a better understanding of molecular drivers for CRC metastasis are of critical clinical importance. Here, we identify a signature of advanced CRC metastasis by performing whole genome-scale DNA methylation and full transcriptome analyses of paired primary cancers and liver metastases from CRC patients. We observed striking methylation differences between primary and metastatic pairs. A subset of loci showed coordinated methylation-expression changes, suggesting these are potentially epigenetic drivers that control the expression of critical genes in the metastatic cascade. The identification of CRC epigenomic markers of metastasis has the potential to enable better outcome prediction and lead to the discovery of new therapeutic targets.

Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes

DNA methylation variations are prevalent in human obesity but evidence of a causative role in disease pathogenesis is limited. Here, we combine epigenome-wide association and integrative genomics to investigate the impact of adipocyte DNA methylation variations in human obesity. We discover extensive DNA methylation changes that are robustly associated with obesity (N = 190 samples, 691 loci in subcutaneous and 173 loci in visceral adipocytes, P < 1 × 10-7). We connect obesity-associated methylation variations to transcriptomic changes at >500 target genes, and identify putative methylation-transcription factor interactions. Through Mendelian Randomisation, we infer causal effects of methylation on obesity and obesity-induced metabolic disturbances at 59 independent loci. Targeted methylation sequencing, CRISPR-activation and gene silencing in adipocytes, further identifies regional methylation variations, underlying regulatory elements and novel cellular metabolic effects. Our results indicate DNA methylation is an important determinant of human obesity and its metabolic complications, and reveal mechanisms through which altered methylation may impact adipocyte functions.

A methylation clock model of mild SARS-CoV-2 infection provides insight into immune dysregulation

DNA methylation comprises a cumulative record of lifetime exposures superimposed on genetically determined markers. Little is known about methylation dynamics in humans following an acute perturbation, such as infection. We characterized the temporal trajectory of blood epigenetic remodeling in 133 participants in a prospective study of young adults before, during, and after asymptomatic and mildly symptomatic SARS-CoV-2 infection. The differential methylation caused by asymptomatic or mildly symptomatic infections was indistinguishable. While differential gene expression largely returned to baseline levels after the virus became undetectable, some differentially methylated sites persisted for months of follow-up, with a pattern resembling autoimmune or inflammatory disease. We leveraged these responses to construct methylation-based machine learning models that distinguished samples from pre-, during-, and postinfection time periods, and quantitatively predicted the time since infection. The clinical trajectory in the young adults and in a diverse cohort with more severe outcomes was predicted by the similarity of methylation before or early after SARS-CoV-2 infection to the model-defined postinfection state. Unlike the phenomenon of trained immunity, the postacute SARS-CoV-2 epigenetic landscape we identify is antiprotective.

Biological age is increased by stress and restored upon recovery

Aging is classically conceptualized as an ever-increasing trajectory of damage accumulation and loss of function, leading to increases in morbidity and mortality. However, recent in vitro studies have raised the possibility of age reversal. Here, we report that biological age is fluid and exhibits rapid changes in both directions. At epigenetic, transcriptomic, and metabolomic levels, we find that the biological age of young mice is increased by heterochronic parabiosis and restored following surgical detachment. We also identify transient changes in biological age during major surgery, pregnancy, and severe COVID-19 in humans and/or mice. Together, these data show that biological age undergoes a rapid increase in response to diverse forms of stress, which is reversed following recovery from stress. Our study uncovers a new layer of aging dynamics that should be considered in future studies. The elevation of biological age by stress may be a quantifiable and actionable target for future interventions.

Integrative Approaches of DNA Methylation Patterns According to Age, Sex and Longitudinal Changes

Background

In humans, age-related DNA methylation has been studied in blood, tissues, buccal swabs, and fibroblasts, and changes in DNA methylation patterns according to age and sex have been detected. To date, approximately 137,000 samples have been analyzed from 14,000 studies, and the information has been uploaded to the NCBI GEO database.

Methods

A correlation between age and methylation level and longitudinal changes in methylation levels was revealed in both sexes. Here, 20 public datasets derived from whole blood were analyzed using the Illumina BeadChip. Batch effects with respect to the time differences were correlated. The overall change in the pattern was provided as the inverse of the coefficient of variation (COV).

Results

Of the 20 datasets, nine were from a longitudinal study. All data had age and sex as common variables. Comprehensive details of age-, sex-, and longitudinal change-based DNA methylation levels in the whole blood sample were elucidated in this study. ELOVL2 and FHL2 showed the maximum correlation between age and DNA methylation. The methylation patterns of genes related to mental health differed according to age. Age-correlated genes have been associated with malformations (anteverted nostril, craniofacial abnormalities, and depressed nasal bridge) and drug addiction (drug habituation and smoking).

Conclusion

Based on 20 public DNA methylation datasets, methylation levels according to age and longitudinal changes by sex were identified and visualized using an integrated approach. The results highlight the molecular mechanisms underlying the association of sex and biological age with changes in DNA methylation, and the importance of optimal genomic information management.

Gene expressions between obligate bamboo-eating pandas and non-herbivorous mammals reveal converged specialized bamboo diet adaptation

BACKGROUND

It is inevitable to change the function or expression of genes during the environmental adaption of species. Both the giant panda (Ailuropoda melanoleuca) and red panda (Ailurus fulgens) belong to Carnivora and have developed similar adaptations to the same dietary switch to bamboos at the morphological and genomic levels. However, the genetic adaptation at the gene expression level is unclear. Therefore, we aimed to examine the gene expression patterns of giant and red panda convergent specialized bamboo-diets. We examined differences in liver and pancreas transcriptomes between the two panda species and other non-herbivorous species.

RESULTS

The clustering and PCA plots suggested that the specialized bamboo diet may drive similar expression shifts in these two species of pandas. Therefore, we focused on shared liver and pancreas DEGs (differentially expressed genes) in the giant and red panda relative to other non-herbivorous species. Genetic convergence occurred at multiple levels spanning carbohydrate metabolism, lipid metabolism, and lysine degradation. The shared adaptive convergence DEGs in both organs probably be an evolutionary response to the high carbohydrate, low lipid and lysine bamboo diet. Convergent expression of those nutrient metabolism-related genes in both pandas was an intricate process and subjected to multi-level regulation, including DNA methylation and transcription factor. A large number of lysine degradation and lipid metabolism related genes were hypermethylated in promoter regions in the red panda. Most genes related to carbohydrate metabolism had reduced DNA methylation with increased mRNA expression in giant pandas. Unlike the red panda, the core gene of the lysine degradation pathway (AASS) doesn't exhibit hypermethylation modification in the giant panda, and dual-luciferase reporter assay showed that transcription factor, NR3C1, functions as a transcriptional activator in AASS transcription through the binding to AASS promoter region.

CONCLUSIONS

Our results revealed the adaptive expressions and regulations of the metabolism-related genes responding to the unique nutrients in bamboo food and provided data accumulation and research hints for the future revelation of complex mechanism of two pandas underlying convergent adaptation to a specialized bamboo diet.

Genome-Wide DNA Methylation Profile Indicates Potential Epigenetic Regulation of Aging in the Rhesus Macaque Thymus

We analyzed whole-genome bisulfite sequencing (WGBS) and RNA sequencing data of two young (1 year old) and two adult (9 years old) rhesus macaques (Macaca mulatta) to characterize the genomic DNA methylation profile of the thymus and explore the molecular mechanism of age-related changes in the thymus. Combining the two-omics data, we identified correlations between DNA methylation and gene expression and found that DNA methylation played an essential role in the functional changes of the aging thymus, especially in immunity and coagulation. The hypomethylation levels of C3 and C5AR2 and the hypermethylation level of C7 may lead to the high expressions of these genes in adult rhesus macaque thymuses, thus activating the classical complement pathway and the alternative pathway and enhancing their innate immune function. Adult thymuses had an enhanced coagulation pathway, which may have resulted from the hypomethylation and upregulated expressions of seven coagulation-promoting factor genes (F13A1, CLEC4D, CLEC4E, FCN3, PDGFRA, FGF2 and FGF7) and the hypomethylation and low expression of CPB2 to inhibit the degradation of blood clots. Furthermore, the functional decline in differentiation, activation and maturation of T cells in adult thymuses was also closely related to the changes in methylation levels and gene expression levels of T cell development genes (CD3G, GAD2, ADAMDEC1 and LCK) and the thymogenic hormone gene TMPO. A comparison of the age-related methylated genes among four mammal species revealed that most of the epigenetic clocks were species-specific. Furthermore, based on the genomic landscape of allele-specific DNA methylation, we identified several age-related clustered sequence-dependent allele-specific DNA methylated (cS-ASM) genes. Overall, these DNA methylation patterns may also help to assist with understanding the mechanisms of the aging thymus with the epigenome.

Epigenetic aging, knee pain and physical performance in community-dwelling middle-to-older age adults

Knee pain is a leading cause of disability in the aging population and may indirectly accelerate biological aging processes. Chronological aging increases the risk of developing of knee pain and knee pain reduces physical function; however, limited data exist on how epigenetic aging, a known hallmark of biological aging shown to predict health span and mortality, may influence this relationship. The purpose of this study was to examine whether decreased physical performance associated with knee pain is mediated by markers of epigenetic aging. Participants (57.91 ± 8.04 years) with low impact knee pain (n = 95), high impact knee pain (n = 53) and pain-free controls (n = 26) completed self-reported pain, a blood draw and a short physical performance battery (SPPB) that included balance, walking, and sit to stand tasks. We employed an epigenetic clock previously associated with knee pain and shown to predict overall mortality risk (DNAmGrimAge). Bootstrapped-mediation analyses were used to determine associations of DNAmGrimAge and SPPB between pain groups. Those with high impact and low impact pain had a biologically older epigenetic age (5.14y ± 5.66 and 1.32y ± 5.41, respectively). However, while there were direct effects of pain on overall physical performance, these were not explained by epigenetic aging. Epigenetic aging only mediated the effect of pain on balance performance. Future work is needed to examine pain's impact on biological aging processes including epigenetic aging and its ultimate effect on physical function measures known to predict health span and mortality.

Longitudinal Study of DNA Methylation and Epigenetic Clocks Prior to and Following Test-Confirmed COVID-19 and mRNA Vaccination

The host epigenetic landscape rapidly changes during SARS-CoV-2 infection, and evidence suggest that severe COVID-19 is associated with durable scars to the epigenome. Specifically, aberrant DNA methylation changes in immune cells and alterations to epigenetic clocks in blood relate to severe COVID-19. However, a longitudinal assessment of DNA methylation states and epigenetic clocks in blood from healthy individuals prior to and following test-confirmed non-hospitalized COVID-19 has not been performed. Moreover, the impact of mRNA COVID-19 vaccines upon the host epigenome remains understudied. Here, we first examined DNA methylation states in the blood of 21 participants prior to and following test-confirmed COVID-19 diagnosis at a median time frame of 8.35 weeks; 756 CpGs were identified as differentially methylated following COVID-19 diagnosis in blood at an FDR adjusted p-value < 0.05. These CpGs were enriched in the gene body, and the northern and southern shelf regions of genes involved in metabolic pathways. Integrative analysis revealed overlap among genes identified in transcriptional SARS-CoV-2 infection datasets. Principal component-based epigenetic clock estimates of PhenoAge and GrimAge significantly increased in people over 50 following infection by an average of 2.1 and 0.84 years. In contrast, PCPhenoAge significantly decreased in people fewer than 50 following infection by an average of 2.06 years. This observed divergence in epigenetic clocks following COVID-19 was related to age and immune cell-type compositional changes in CD4+ T cells, B cells, granulocytes, plasmablasts, exhausted T cells, and naïve T cells. Complementary longitudinal epigenetic clock analyses of 36 participants prior to and following Pfizer and Moderna mRNA-based COVID-19 vaccination revealed that vaccination significantly reduced principal component-based Horvath epigenetic clock estimates in people over 50 by an average of 3.91 years for those who received Moderna. This reduction in epigenetic clock estimates was significantly related to chronological age and immune cell-type compositional changes in B cells and plasmablasts pre- and post-vaccination. These findings suggest the potential utility of epigenetic clocks as a biomarker of COVID-19 vaccine responses. Future research will need to unravel the significance and durability of short-term changes in epigenetic age related to COVID-19 exposure and mRNA vaccination.

Epigenomic profiling indicates a role for DNA methylation in the postnatal liver and pancreas development of giant pandas

Giant pandas are unique within Carnivora with a strict bamboo diet. Here, the epigenomic profiles of giant panda liver and pancreas tissues collected from three important feeding stages were investigated using BS-seq. Few differences in DNA methylation profiles were exhibited between no feeding and suckling groups in both tissues. However, we observed a tendency toward a global loss of DNA methylation in the gene-body and promoter region of metabolism-related genes from newborn to adult. Correlation analysis revealed a significant negative correlation between the changes in methylation levels within gene promoters and gene expression. The majority of genes related to nutrition metabolism had lost DNA methylation with increased mRNA expression in adult giant pandas. The few galactose metabolism and unsaturated fatty acid metabolism related genes that were hypomethylated and highly-expressed at early stages of giant panda development may meet the nutritional requirement of this species' highly altricial neonates.

How to Slow down the Ticking Clock: Age-Associated Epigenetic Alterations and Related Interventions to Extend Life Span

Epigenetic alterations pose one major hallmark of organismal aging. Here, we provide an overview on recent findings describing the epigenetic changes that arise during aging and in related maladies such as neurodegeneration and cancer. Specifically, we focus on alterations of histone modifications and DNA methylation and illustrate the link with metabolic pathways. Age-related epigenetic, transcriptional and metabolic deregulations are highly interconnected, which renders dissociating cause and effect complicated. However, growing amounts of evidence support the notion that aging is not only accompanied by epigenetic alterations, but also at least in part induced by those. DNA methylation clocks emerged as a tool to objectively determine biological aging and turned out as a valuable source in search of factors positively and negatively impacting human life span. Moreover, specific epigenetic signatures can be used as biomarkers for age-associated disorders or even as targets for therapeutic approaches, as will be covered in this review. Finally, we summarize recent potential intervention strategies that target epigenetic mechanisms to extend healthy life span and provide an outlook on future developments in the field of longevity research.

Unique Associations of DNA Methylation Regions With 24-Hour Blood Pressure Phenotypes in Blacks

BACKGROUND

Epigenetic marks (eg, DNA methylation) may capture the effect of gene-environment interactions. DNA methylation is involved in blood pressure (BP) regulation and hypertension development; however, no studies have evaluated its relationship with 24-hour BP phenotypes (daytime, nighttime, and 24-hour average BPs).

METHODS

We examined the association of whole blood DNA methylation with 24-hour BP phenotypes and clinic BPs in a discovery cohort of 281 Blacks using reduced representation bisulfite sequencing. We developed a deep and region-specific methylation sequencing method, Bisulfite ULtrapLEx Targeted Sequencing and utilized it to validate our findings in a separate validation cohort (n=117).

RESULTS

Analysis of 38 215 DNA methylation regions (MRs), derived from 1 549 368 CpG sites across the genome, identified up to 72 regions that were significantly associated with 24-hour BP phenotypes. No MR was significantly associated with clinic BP. Two to 3 MRs were significantly associated with various 24-hour BP phenotypes after adjustment for age, sex, and body mass index. Together, these MRs explained up to 16.5% of the variance of 24-hour average BP, while age, sex, and BMI explained up to 11.0% of the variance. Analysis of one of the MRs in an independent cohort using Bisulfite ULtrapLEx Targeted Sequencing confirmed its association with 24-hour average BP phenotype.

CONCLUSIONS

We identified several MRs that explain a substantial portion of variances in 24-hour BP phenotypes, which might be excellent markers of cumulative effect of factors influencing 24-hour BP levels. The Bisulfite ULtrapLEx Targeted Sequencing workflow has potential to be suitable for clinical testing and population screenings on a large scale.

Integrating Choline and Specific Intestinal Microbiota to Classify Type 2 Diabetes in Adults: A Machine Learning Based Metagenomics Study

Emerging evidence is examining the precise role of intestinal microbiota in the pathogenesis of type 2 diabetes. The aim of this study was to investigate the association of intestinal microbiota and microbiota-generated metabolites with glucose metabolism systematically in a large cross-sectional study in China. 1160 subjects were divided into three groups based on their glucose level: normal glucose group (n=504), prediabetes group (n=394), and diabetes group (n=262). Plasma concentrations of TMAO, choline, betaine, and carnitine were measured. Intestinal microbiota was measured in a subgroup of 161 controls, 144 prediabetes and 56 diabetes by using metagenomics sequencing. We identified that plasma choline [Per SD of log-transformed change: odds ratio 1.36 (95 confidence interval 1.16, 1.58)] was positively, while betaine [0.77 (0.66, 0.89)] was negatively associated with diabetes, independently of TMAO. Individuals with diabetes could be accurately distinguished from controls by integrating data on choline, and certain microbiota species, as well as traditional risk factors (AUC=0.971). KOs associated with the carbohydrate metabolism pathway were enhanced in individuals with high choline level. The functional shift in the carbohydrate metabolism pathway in high choline group was driven by species Ruminococcus lactaris, Coprococcus catus and Prevotella copri. We demonstrated the potential ability for classifying diabetic population by choline and specific species, and provided a novel insight of choline metabolism linking the microbiota to impaired glucose metabolism and diabetes.

The potential of using blood circular RNA as liquid biopsy biomarker for human diseases

Circular RNA (circRNA) is a novel class of single-stranded RNAs with a closed loop structure. The majority of circRNAs are formed by a back-splicing process in pre-mRNA splicing. Their expression is dynamically regulated and shows spatiotemporal patterns among cell types, tissues and developmental stages. CircRNAs have important biological functions in many physiological processes, and their aberrant expression is implicated in many human diseases. Due to their high stability, circRNAs are becoming promising biomarkers in many human diseases, such as cardiovascular diseases, autoimmune diseases and human cancers. In this review, we focus on the translational potential of using human blood circRNAs as liquid biopsy biomarkers for human diseases. We highlight their abundant expression, essential biological functions and significant correlations to human diseases in various components of peripheral blood, including whole blood, blood cells and extracellular vesicles. In addition, we summarize the current knowledge of blood circRNA biomarkers for disease diagnosis or prognosis.

COVID-19-Induced New-Onset Diabetes: Trends and Technologies

The coronavirus disease 2019 (COVID-19) global pandemic continues to spread worldwide with approximately 216 million confirmed cases and 4.49 million deaths to date. Intensive efforts are ongoing to combat this disease by suppressing viral transmission, understanding its pathogenesis, developing vaccination strategies, and identifying effective therapeutic targets. Individuals with preexisting diabetes also show higher incidence of COVID-19 illness and poorer prognosis upon infection. Likewise, an increased frequency of diabetes onset and diabetes complications has been reported in patients following COVID-19 diagnosis. COVID-19 may elevate the risk of hyperglycemia and other complications in patients with and without prior diabetes history. It is unclear whether the virus induces type 1 or type 2 diabetes or instead causes a novel atypical form of diabetes. Moreover, it remains unknown if recovering COVID-19 patients exhibit a higher risk of developing new-onset diabetes or its complications going forward. The aim of this review is to summarize what is currently known about the epidemiology and mechanisms of this bidirectional relationship between COVID-19 and diabetes. We highlight major challenges that hinder the study of COVID-19-induced new-onset of diabetes and propose a potential framework for overcoming these obstacles. We also review state-of-the-art wearables and microsampling technologies that can further study diabetes management and progression in new-onset diabetes cases. We conclude by outlining current research initiatives investigating the bidirectional relationship between COVID-19 and diabetes, some with emphasis on wearable technology.

Multiomics and digital monitoring during lifestyle changes reveal independent dimensions of human biology and health

We explored opportunities for personalized and predictive health care by collecting serial clinical measurements, health surveys, genomics, proteomics, autoantibodies, metabolomics, and gut microbiome data from 96 individuals who participated in a data-driven health coaching program over a 16-month period with continuous digital monitoring of activity and sleep. We generated a resource of >20,000 biological samples from this study and a compendium of >53 million primary data points for 558,032 distinct features. Multiomics factor analysis revealed distinct and independent molecular factors linked to obesity, diabetes, liver function, cardiovascular disease, inflammation, immunity, exercise, diet, and hormonal effects. For example, ethinyl estradiol, a common oral contraceptive, produced characteristic molecular and physiological effects, including increased levels of inflammation and impact on thyroid, cortisol levels, and pulse, that were distinct from other sources of variability observed in our study. In total, this work illustrates the value of combining deep molecular and digital monitoring of human health. A record of this paper's transparent peer review process is included in the supplemental information.

Longitudinal analysis of individual cfDNA methylome patterns in metastatic prostate cancer

Background

Disease progression and therapeutic resistance are hallmarks of advanced stage prostate cancer (PCa), which remains a major cause of cancer-related mortality around the world. Longitudinal studies, coupled with the use of liquid biopsies, offer a potentially new and minimally invasive platform to study the dynamics of tumour progression. Our aim was to investigate the dynamics of personal DNA methylomic profiles of metastatic PCa (mPCa) patients, during disease progression and therapy administration.

Results

Forty-eight plasma samples from 9 mPCa patients were collected, longitudinally, over 13–21 months. After circulating cell-free DNA (cfDNA) isolation, DNA methylation was profiled using the Infinium MethylationEPIC BeadChip. The top 5% most variable probes across time, within each individual, were utilised to study dynamic methylation patterns during disease progression and therapeutic response. Statistical testing was carried out to identify differentially methylated genes (DMGs) in cfDNA, which were subsequently validated in two independent mPCa (cfDNA and FFPE tissue) cohorts. Individual cfDNA global methylation patterns were temporally stable throughout the disease course. However, a proportion of CpG sites presented a dynamic temporal pattern that was consistent with clinical events, including different therapies, and were prominently associated with genes linked to immune response pathways. Additionally, study of the tumour fraction of cfDNA identified > 2000 DMGs with dynamic methylation patterns.

Conclusions

Longitudinal assessment of cfDNA methylation in mPCa patients unveiled dynamic patterns associated with disease progression and therapy administration, thus highlighting the potential of using liquid biopsies to study PCa evolution at a methylomic level.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01155-w.

DNA methylation signature on phosphatidylethanol, not on self-reported alcohol consumption, predicts hazardous alcohol consumption in two distinct populations

The process of diagnosing hazardous alcohol drinking (HAD) is based on self-reported data and is thereby vulnerable to bias. There has been an interest in developing epigenetic biomarkers for HAD that might complement clinical assessment. Because alcohol consumption has been previously linked to DNA methylation (DNAm), we aimed to select DNAm signatures in blood to predict HAD from two demographically and clinically distinct populations (Ntotal = 1,549). We first separately conducted an epigenome-wide association study (EWAS) for phosphatidylethanol (PEth), an objective measure of alcohol consumption, and for self-reported alcohol consumption in Cohort 1. We identified 83 PEth-associated CpGs, including 23 CpGs previously associated with alcohol consumption or alcohol use disorder. In contrast, no CpG reached epigenome-wide significance on self-reported alcohol consumption. Using a machine learning approach, two CpG subsets from EWAS on PEth and on self-reported alcohol consumption from Cohort 1 were separately tested for the prediction of HAD in Cohort 2. We found that a subset of 143 CpGs selected from the EWAS on PEth showed an excellent prediction of HAD with the area under the receiver operating characteristic curve (AUC) of 89.4% in training set and 73.9% in validation set of Cohort 2. However, CpGs preselected from the EWAS on self-reported alcohol consumption showed a poor prediction of HAD with AUC 75.2% in training set and 57.6% in validation set. Our results demonstrate that an objective measure for alcohol consumption is a more informative phenotype than self-reported data for revealing epigenetic mechanisms. The PEth-associated DNAm signature in blood could serve as a robust biomarker for alcohol consumption.

DNA methylomic homogeneity and heterogeneity in muscles and testes throughout pig adulthood

DNA methylome pattern is significantly different among tissues, ages, breeds, and genders. We assessed 20 methylome and transcriptome data in longissimus dorsi (LD) or testicles from Bamaxiang (BMX) and Large White pigs (LW) by deep sequencing technology. We identified ~55.7M CpGs and 5.30M, 0.20M, 1.20M, and 0.16M differential CpGs (P<0.01) between tissues, ages, breeds, and genders, respectively. Interestingly, 7.54% of differentially methylated regions (DMRs) are co-localized with promoters, which potentially regulate gene expression. RNA-seq analysis revealed that 23.42% CpGs are significantly correlated with gene expression (mean |r|=0.58, P<0.01), most of which are enriched in tissue-specific functions. Specially, we also found that the methylation levels in promoters of 655 genes were strongly associated with their expression levels (mean |r|=0.66, P<0.01). In addition, differentially methylated CpGs (DMCpGs) between breeds in HOXC gene cluster imply important regulatory roles in myocytes hypertrophy and intermuscular fat (IMF) deposition. Dramatically, higher similarity of methylation pattern was observed within pedigree than across pedigrees, which indicates the existence of heritable methylation regions. In summary, a part of CpGs in promoter can change its methylation pattern and play a marked regulatory function in different physiological or natural environments.

DNA methylation biomarker selected by an ensemble machine learning approach predicts mortality risk in an HIV-positive veteran population

Background: With the improved life expectancy of people living with HIV (PLWH), identifying vulnerable subpopulations at high mortality risk is important. Evidences showed that DNA methylation (DNAm) is associated with mortality in non-HIV populations. Here, we established a panel of DNAm biomarkers that can predict mortality risk among PLWH.

Methods: 1,081 HIV-positive participants from the Veterans Ageing Cohort Study (VACS) were divided into training (N = 460), validation (N = 114), and testing (N = 507) sets. VACS index was used as a measure of mortality risk among PLWH. Model training and fine-tuning were conducted using the ensemble method in the training and validation sets and prediction performance was assessed in the testing set. The survival analysis comparing the predicted high and low mortality risk groups and the Gene Ontology enrichment analysis of the predictive CpG sites were performed.

Results: We selected a panel of 393 CpGs for the ensemble prediction model that showed excellent performance in predicting high mortality risk with an auROC of 0.809 (95%CI: 0.767,0.851) and a balanced accuracy of 0.653 (95%CI: 0.611, 0.693) in the testing set. The high mortality risk group was significantly associated with 10-year mortality (hazard ratio = 1.79, p = 4E-05) compared with low risk group. These 393 CpGs were located in 280 genes enriched in immune and inflammation response pathways.

Conclusions: We identified a panel of DNAm features associated with mortality risk in PLWH. These DNAm features may serve as predictive biomarkers for mortality risk among PLWH.

Abbreviations: AUC: Area Under Curve; CI: Confidence interval; DMR: differentially methylated region; DNA: Deoxyribonucleic acid; DNAm: DNA methylation; DAVID: Database for Annotation, Visualization, and Integrated Discovery; EWA: epigenome-wide association; FDR: False discovery rate; FWER: Family-wise error rate; GLMNET: elastic-net-regularized generalized linear models; GO: Gene ontology; HIV: Human immunodeficiency virus; HM450K: Human Methylation 450 K BeadChip; k-NN: k-nearest neighbours; NK: Natural killer; PC: Principal component; PLWH: people living with HIV; QC: Quality control; SVM: Support Vector Machines; VACS: Veterans Ageing Cohort Study; XGBoost: Extreme Gradient Boosting Tree

Longitudinal assessment of clonal mosaicism in human hematopoiesis via mitochondrial mutation tracking

Our ability to track cellular dynamics in humans over time in vivo has been limited. Here, we demonstrate how somatic mutations in mitochondrial DNA (mtDNA) can be used to longitudinally track the dynamic output of hematopoietic stem and progenitor cells in humans. Over the course of 3 years of blood sampling in a single individual, our analyses reveal somatic mtDNA sequence variation and evolution reminiscent of models of hematopoiesis established by genetic labeling approaches. Furthermore, we observe fluctuations in mutation heteroplasmy, coinciding with specific clinical events, such as infections, and further identify lineage-specific somatic mtDNA mutations in longitudinally sampled circulating blood cell subsets in individuals with leukemia. Collectively, these observations indicate the significant potential of using tracking of somatic mtDNA sequence variation as a broadly applicable approach to systematically assess hematopoietic clonal dynamics in human health and disease.

The Association Between Breast Cancer and Blood-Based Methylation of S100P and HYAL2 in the Chinese Population

Previous work has shown that DNA methylation in peripheral blood may be associated with malignancy; however, these studies have mainly been conducted within Caucasian populations. Here, we investigated the association between blood-based methylation of S100 calcium-binding protein P gene (S100P) and hyaluronoglucosaminidase 2 gene (HYAL2) and breast cancer (BC) via mass spectrometry in two independent case-control studies of the Chinese population with a total of 351 BC cases and 427 cancer-free female controls. In Study I, in which subjects had an average of 45 years, hypomethylation of S100P showed a protective effect for women ≤45 years (six out of nine CpG sites, p < 0.05) but not for women >45 years. In contrast, hypomethylation of HAYL2 was not correlated with BC in women ≤45 years but was a risk factor for women >45 years (three out of four CpG sites, p < 0.05). We proposed an age-dependent correlation between BC and methylation of S100P and HYAL2 and performed further validation in Study II with older subjects (average age = 52.5 years), where hypomethylation of both S100P and HYAL2 was a risk factor for BC (p < 0.05 for 10 CpG sites) as reported in Caucasians who develop BC around 55 years old. Together with the observation that Chinese cancer-free females having variant basal methylation levels comparing to Caucasians, we assumed that blood-based methylation might be modified by ethnic background, hormone status, and lifestyle. Here, we highlighted that the epigenetic biomarkers warrant validations when its application in variant ethnic groups is considered.

The Guangzhou Twin Eye Study: 2019 Update

The primary aim of the Guangzhou Twin Eye Study (GTES) is to explore the impact that genes and environmental influences have on common eye diseases. Since 2006, approximately 1300 pairs of twins, aged 7-15 years, were enrolled at baseline. Progressive phenotypes, such as cycloplegic refraction, axial length, height and weight, have been collected annually. Nonprogressive phenotypes such as parental refraction, corneal thickness, fundus photo, intraocular pressure and DNA were collected once at baseline. We are collaborating with fellow international twin researchers and psychologists to further explore links with general medical conditions. In this article, we review the history, major findings and future research directions for the GTES.

Interaction of Sleep and Cortical Structural Maintenance From an Individual Person Microlongitudinal Perspective and Implications for Precision Medicine Research

Sleep and maintenance of brain structure are essential for the continuity of a person's cognitive/mental health. Interestingly, whether normal structural maintenance of the brain and sleep continuously interact in some way over day-week-month times has never been assessed at an individual-person level. This study used unconventional microlongitudinal sampling, structural magnetic resonance imaging, and n-of-1 analyses to assess normal interactions between fluctuations in the structural maintenance of cerebral cortical thickness and sleep duration for day, week, and multi-week intervals over a 6-month period in a healthy adult man. Correlation and time series analyses provided indications of "if-then," i.e., "if" this preceded "then" this followed, sleep-to-thickness maintenance and thickness maintenance-to-sleep bidirectional inverse interactions. Inverse interaction patterns were characterized by concepts of graded influences across nights, bilaterally positive relationships, continuity across successive weeks, and longer delayed/prolonged effects in the thickness maintenance-to-sleep than sleep-to-thickness maintenance direction. These interactions are proposed to involve normal circadian/allostatic/homeostatic mechanisms that continuously influence, and are influenced by, cortical substrate remodeling/turnover and sleep/wake cycle. Understanding interactions of individual person "-omics" is becoming a central interest in precision medicine research. The present n-of-1 findings contribute to this interest and have implications for precision medicine research use of a person's cortical structural and sleep "-omics" to optimize the continuous maintenance of that individual's cortical structure, sleep, and cognitive/mental health.

Gene-methylation interactions: discovering region-wise DNA methylation levels that modify SNP-associated disease risk

BACKGROUND

Current technology allows rapid assessment of DNA sequences and methylation levels at a single-site resolution for hundreds of thousands of sites in the human genome, in thousands of individuals simultaneously. This has led to an increase in epigenome-wide association studies (EWAS) of complex traits, particularly those that are poorly explained by previous genome-wide association studies (GWAS). However, the genome and epigenome are intertwined, e.g., DNA methylation is known to affect gene expression through, for example, genomic imprinting. There is thus a need to go beyond single-omics data analyses and develop interaction models that allow a meaningful combination of information from EWAS and GWAS.

RESULTS

We present two new methods for genetic association analyses that treat offspring DNA methylation levels as environmental exposure. Our approach searches for statistical interactions between SNP alleles and DNA methylation (G ×Me) and between parent-of-origin effects and DNA methylation (PoO ×Me), using case-parent triads or dyads. We use summarized methylation levels over nearby genomic region to ease biological interpretation. The methods were tested on a dataset of parent-offspring dyads, with EWAS data on the offspring. Our results showed that methylation levels around a SNP can significantly alter the estimated relative risk. Moreover, we show how a control dataset can identify false positives.

CONCLUSIONS

The new methods, G ×Me and PoO ×Me, integrate DNA methylation in the assessment of genetic relative risks and thus enable a more comprehensive biological interpretation of genome-wide scans. Moreover, our strategy of condensing DNA methylation levels within regions helps overcome specific disadvantages of using sparse chip-based measurements. The methods are implemented in the freely available R package Haplin ( https://cran.r-project.org/package=Haplin ), enabling fast scans of multi-omics datasets.

Glucose-induced, duration-dependent genome-wide DNA methylation changes in human endothelial cells

DNA methylation, a critical epigenetic mechanism, plays an important role in governing gene expressions during biological processes such as aging, which is well known to be accelerated in hyperglycemia (diabetes). In the present study, we investigated the effects of glucose on whole genome DNA methylation in small [human retinal microvascular endothelial cells (HRECs)] and large [human umbilical vein endothelial cells (HUVECs)] vessel endothelial cell (EC) lines exposed to basal or high glucose-containing media for variable lengths of time. Using the Infinium EPIC array, we obtained 773,133 CpG sites (probes) for analysis. Unsupervised clustering of the top 5% probes identified four distinct clusters within EC groups, with significant methylation differences attributed to EC types and the duration of cell culture rather than glucose stimuli alone. When comparing the ECs incubated for 2 days versus 7 days, hierarchical clustering analyses [methylation change >10% and false discovery rate (FDR) <0.05] identified 17,354 and 128 differentially methylated CpGs for HUVECs and HRECs, respectively. Predominant DNA hypermethylation was associated with the length of culture and was enriched for gene enhancer elements and regions surrounding CpG shores and shelves. We identified 88 differentially methylated regions (DMRs) for HUVECs and 8 DMRs for HRECs (all FDR <0.05). Pathway enrichment analyses of DMRs highlighted involvement of regulators of embryonic development (i.e., HOX genes) and cellular differentiation [transforming growth factor-β (TGF-β) family members]. Collectively, our findings suggest that DNA methylation is a complex process that involves tightly coordinated, cell-specific mechanisms. Such changes in methylation overlap genes critical for cellular differentiation and embryonic development.

DNA Methylation Biomarkers in Aging and Age-Related Diseases

Recent research efforts provided compelling evidence of genome-wide DNA methylation alterations in aging and age-related disease. It is currently well established that DNA methylation biomarkers can determine biological age of any tissue across the entire human lifespan, even during development. There is growing evidence suggesting epigenetic age acceleration to be strongly linked to common diseases or occurring in response to various environmental factors. DNA methylation based clocks are proposed as biomarkers of early disease risk as well as predictors of life expectancy and mortality. In this review, we will summarize key advances in epigenetic clocks and their potential application in precision health. We will also provide an overview of progresses in epigenetic biomarker discovery in Alzheimer's, type 2 diabetes, and cardiovascular disease. Furthermore, we will highlight the importance of prospective study designs to identify and confirm epigenetic biomarkers of disease.

Psychotropic drug-induced genetic-epigenetic modulation of CRTC1 gene is associated with early weight gain in a prospective study of psychiatric patients

BACKGROUND

Metabolic side effects induced by psychotropic drugs represent a major health issue in psychiatry. CREB-regulated transcription coactivator 1 (CRTC1) gene plays a major role in the regulation of energy homeostasis and epigenetic mechanisms may explain its association with obesity features previously described in psychiatric patients. This prospective study included 78 patients receiving psychotropic drugs that induce metabolic disturbances, with weight and other metabolic parameters monitored regularly. Methylation levels in 76 CRTC1 probes were assessed before and after 1 month of psychotropic treatment in blood samples.

RESULTS

Significant methylation changes were observed in three CRTC1 CpG sites (i.e., cg07015183, cg12034943, and cg 17006757) in patients with early and important weight gain (i.e., equal or higher than 5% after 1 month; FDR p value = 0.02). Multivariable models showed that methylation decrease in cg12034943 was more important in patients with early weight gain (≥ 5%) than in those who did not gain weight (p = 0.01). Further analyses combining genetic and methylation data showed that cg12034943 was significantly associated with early weight gain in patients carrying the G allele of rs4808844A>G (p = 0.03), a SNP associated with this methylation site (p = 0.03).

CONCLUSIONS

These findings give new insights on psychotropic-induced weight gain and underline the need of future larger prospective epigenetic studies to better understand the complex pathways involved in psychotropic-induced metabolic side effects.

DNA methylation aging clocks: challenges and recommendations

Epigenetic clocks comprise a set of CpG sites whose DNA methylation levels measure subject age. These clocks are acknowledged as a highly accurate molecular correlate of chronological age in humans and other vertebrates. Also, extensive research is aimed at their potential to quantify biological aging rates and test longevity or rejuvenating interventions. Here, we discuss key challenges to understand clock mechanisms and biomarker utility. This requires dissecting the drivers and regulators of age-related changes in single-cell, tissue- and disease-specific models, as well as exploring other epigenomic marks, longitudinal and diverse population studies, and non-human models. We also highlight important ethical issues in forensic age determination and predicting the trajectory of biological aging in an individual.

An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasis

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D.

Epigenome Remodeling in Cholangiocarcinoma

Cholangiocarcinoma (CCA) comprises a heterogeneous collection of malignancies arising within the biliary tract, characterized by late diagnosis, innate chemoresistance, and abysmal prognosis. Sequencing data have uncovered recurrent mutations in diverse epigenetic regulators, implicating epigenetic destabilization at the root of these tumors. However, few studies have characterized biliary tumor epigenomes. In this Opinion article, we argue that an epigenome-oriented approach to CCA could establish diverse interconnections between many key aspects of research on this disease, including molecular heterogeneity, diverse cells of origin, and prominent tumor microenvironments. Moreover, we discuss plausible causes of epigenome dysregulation in biliary tumors, including genetic, epigenetic, metabolic, microenvironmental, and physiological factors. Lastly, we assess the translational potential of epigenomics in CCA to uncover robust biomarkers and therapeutic opportunities for this growing group of patients with limited treatment options.

100 Years of evolving gene-disease complexities and scientific debutants

It's been over 100 years since the word `gene' is around and progressively evolving in several scientific directions. Time-to-time technological advancements have heavily revolutionized the field of genomics, especially when it's about, e.g. triple code development, gene number proposition, genetic mapping, data banks, gene-disease maps, catalogs of human genes and genetic disorders, CRISPR/Cas9, big data and next generation sequencing, etc. In this manuscript, we present the progress of genomics from pea plant genetics to the human genome project and highlight the molecular, technical and computational developments. Studying genome and epigenome led to the fundamentals of development and progression of human diseases, which includes chromosomal, monogenic, multifactorial and mitochondrial diseases. World Health Organization has classified, standardized and maintained all human diseases, when many academic and commercial online systems are sharing information about genes and linking to associated diseases. To efficiently fathom the wealth of this biological data, there is a crucial need to generate appropriate gene annotation repositories and resources. Our focus has been how many gene-disease databases are available worldwide and which sources are authentic, timely updated and recommended for research and clinical purposes. In this manuscript, we have discussed and compared 43 such databases and bioinformatics applications, which enable users to connect, explore and, if possible, download gene-disease data.

Applying circulating tumor DNA methylation in the diagnosis of lung cancer

Lung cancer is the leading cause of cancer-related deaths worldwide. Low dose computed tomography (LDCT) is commonly used for disease screening, with identified candidate cancerous regions further diagnosed using tissue biopsy. However, existing techniques are all invasive and unavoidably cause multiple complications. In contrast, liquid biopsy is a noninvasive, ideal surrogate for tissue biopsy that can identify circulating tumor DNA (ctDNA) containing tumorigenic signatures. It has been successfully implemented to assist treatment decisions and disease outcome prediction. ctDNA methylation, a type of lipid biopsy that profiles critical epigenetic alterations occurring during carcinogenesis, has gained increasing attention. Indeed, aberrant ctDNA methylation occurs at early stages in lung malignancy and therefore can be used as an alternative for the early diagnosis of lung cancer. In this review, we give a brief synopsis of the biological basis and detecting techniques of ctDNA methylation. We then summarize the latest progress in use of ctDNA methylation as a diagnosis biomarker. Lastly, we discuss the major issues that limit application of ctDNA methylation in the clinic, and propose possible solutions to enhance its usage.