Enrichment methods provide a feasible approach to comprehensive and adequately powered investigations of the brain methylome

Insights from a methylome-wide association study of antidepressant exposure

This study tests the association of whole-blood DNA methylation and antidepressant exposure in 16,531 individuals from Generation Scotland (GS), using self-report and prescription-derived measures. We identify 8 associations and a high concordance of results between self-report and prescription-derived measures. Sex-stratified analyses observe nominally significant increased effect estimates in females for four CpGs. There is observed enrichment for genes expressed in the Amygdala and annotated to synaptic vesicle membrane ontology. Two CpGs (cg15071067; DGUOK-AS1 and cg26277237; KANK1) show correlation between DNA methylation with the time in treatment. There is a significant overlap in the top 1% of CpGs with another independent methylome-wide association study of antidepressant exposure. Finally, a methylation profile score trained on this sample shows a significant association with antidepressant exposure in a meta-analysis of eight independent external datasets. In this large investigation of antidepressant exposure and DNA methylation, we demonstrate robust associations which warrant further investigation to inform on the design of more effective and tolerated treatments for depression.

Circulating tumor DNA methylation: a promising clinical tool for cancer diagnosis and management

Cancer continues to pose significant challenges to the medical community. Early detection, accurate molecular profiling, and adequate assessment of treatment response are critical factors in improving the quality of life and survival of cancer patients. Accumulating evidence shows that circulating tumor DNA (ctDNA) shed by tumors into the peripheral blood preserves the genetic and epigenetic information of primary tumors. Notably, DNA methylation, an essential and stable epigenetic modification, exhibits both cancer- and tissue-specific patterns. As a result, ctDNA methylation has emerged as a promising molecular marker for noninvasive testing in cancer clinics. In this review, we summarize the existing techniques for ctDNA methylation detection, describe the current research status of ctDNA methylation, and present the potential applications of ctDNA-based assays in the clinic. The insights presented in this article could serve as a roadmap for future research and clinical applications of ctDNA methylation.

Cell-type specific methylation changes in the newborn child associated to obstetric pain relief

Although it is widely known that various pharmaceuticals affect the methylome, the knowledge of the effects from anesthesia is limited, and nearly nonexistent regarding the effects of obstetric anesthesia on the newborn child. Using sequencing based-methylation data and a reference-based statistical deconvolution approach we performed methylome-wide association studies (MWAS) of neonatal whole blood, and for each cell-type specifically, to detect methylation variations that are associated with the pain relief administered to the mother during delivery. Significant findings were replicated in a different dataset and followed-up with gene ontology analysis to pinpoint biological functions of potential relevance to these neonatal methylation alterations. The MWAS analyses detected methylome-wide significant (q<0.1) alterations in the newborn for laughing gas in granulocytes (two CpGs, p<5.50x10-9, q = 0.067), and for pudendal block in monocytes (five CpGs across three loci, p<1.51 x10-8, q = 0.073). Suggestively significant findings (p<1.00x10-6) were detected for both treatments for bulk and all cell-types, and replication analyses showed consistent significant enrichment (odds ratios ranging 3.47-39.02; p<4.00×10-4) for each treatment, suggesting our results are robust. In contrast, we did not observe any overlap across treatments, suggesting that the treatments are associated with different alterations of the neonatal blood methylome. Gene ontology analyses of the replicating suggestively significant results indicated functions related to, for example, cell differentiation, intracellular membrane-bound organelles and calcium transport. In conclusion, for the first time, we investigated and detected effect of obstetric pain-relief on the blood methylome in the newborn child. The observed differences suggest that anesthetic treatment, such as laughing gas or pudendal block, may alter the neonatal methylome in a cell-type specific manner. Some of the observed alterations are part of gene ontology terms that previously have been suggested in relation to anesthetic treatment, supporting its potential role also in obstetric anesthesia.

The Impact of Childhood Mental Health and Substance Use on Methylation Aging Into Adulthood

OBJECTIVE

To test whether childhood mental health symptoms, substance use, and early adversity accelerate the rate of DNA methylation (DNAm) aging from adolescence to adulthood.

METHOD

DNAm was assayed from blood samples in 381 participants in both adolescence (mean [SD] age = 13.9 [1.6] years) and adulthood (mean [SD] age = 25.9 [2.7] years). Structured diagnostic interviews were completed with participants and their parents at multiple childhood observations (1,950 total) to assess symptoms of common mental health disorders (attention-deficit/hyperactivity disorder, oppositional defiant disorder, conduct disorder, anxiety, and depression) and common types of substance use (alcohol, cannabis, nicotine) and early adversities.

RESULTS

Neither childhood mental health symptoms nor substance use variables were associated with DNAm aging cross-sectionally. In contrast, the following mental health symptoms and substance variables were associated with accelerated DNAm aging from adolescence to adulthood: depressive symptoms (b = 0.314, SE = 0.127, p = .014), internalizing symptoms (b = 0.108, SE = 0.049, p = .029), weekly cannabis use (b =1.665, SE = 0.591, p = .005), and years of weekly cannabis use (b = 0.718, SE = 0.283, p = .012). In models testing all individual variables simultaneously, the combined effect of the variables was equivalent to a potential difference of 3.17 to 3.76 years in DNAm aging. A final model tested a variable assessing cumulative exposure to mental health symptoms, substance use, and early adversities. This cumulative variable was strongly associated with accelerated aging (b = 0.126, SE = 0.044, p = .005).

CONCLUSION

Mental health symptoms and substance use accelerated DNAm aging into adulthood in a manner consistent with a shared risk mechanism.

PLAIN LANGUAGE SUMMARY

Using data from 381 participants in the Great Smoky Mountains Study, the authors examined whether childhood mental health symptoms, substance use, and early adversity accelerate biological aging, as measured by DNA methylation age, from adolescence to adulthood. Depressive symptoms and cannabis use were found to significantly accelerate biological aging. Models that tested the combined effect of mental health symptoms, substance use, and early adversity demonstrated that there was a shared effect across these types of childhood problems on accelerated aging.

Is ctDNA ready to outpace imaging in monitoring early and advanced breast cancer?

INTRODUCTION

Circulating tumor DNA (ctDNA) and radiological imaging are increasingly recognized as crucial elements in breast cancer management. While radiology remains the cornerstone for screening and monitoring, ctDNA holds distinctive advantages in anticipating diagnosis, recurrence, or progression, providing concurrent biological insights complementary to imaging results.

AREAS COVERED

This review delves into the current evidence on the synergistic relationship between ctDNA and imaging in breast cancer. It presents data on the clinical validity and utility of ctDNA in both early and advanced settings, providing insights into emerging liquid biopsy techniques like epigenetics and fragmentomics. Simultaneously, it explores the present and future landscape of imaging methodologies, particularly focusing on radiomics.

EXPERT OPINION

Numerous are the current technical, strategic, and economic challenges preventing the clinical integration of ctDNA analysis in the breast cancer monitoring. Understanding these complexities and devising targeted strategies is pivotal to effectively embedding this methodology into personalized patient care.

Investigating neonatal health risk variables through cell-type specific methylome-wide association studies

Adverse neonatal outcomes are a prevailing risk factor for both short- and long-term mortality and morbidity in infants. Given the importance of these outcomes, refining their assessment is paramount for improving prevention and care. Here we aim to enhance the assessment of these often correlated and multifaceted neonatal outcomes. To achieve this, we employ factor analysis to identify common and unique effects and further confirm these effects using criterion-related validity testing. This validation leverages methylome-wide profiles from neonatal blood. Specifically, we investigate nine neonatal health risk variables, including gestational age, Apgar score, three indicators of body size, jaundice, birth diagnosis, maternal preeclampsia, and maternal age. The methylomic profiles used for this research capture data from nearly all 28 million methylation sites in human blood, derived from the blood spot collected from 333 neonates, within 72 h post-birth. Our factor analysis revealed two common factors, size factor, that captured the shared effects of weight, head size, height, and gestational age and disease factor capturing the orthogonal shared effects of gestational age, combined with jaundice and birth diagnosis. To minimize false positives in the validation studies, validation was limited to variables with significant cumulative association as estimated through an in-sample replication procedure. This screening resulted in that the two common factors and the unique effects for gestational age, jaundice and Apgar were further investigated with full-scale cell-type specific methylome-wide association analyses. Highly significant, cell-type specific, associations were detected for both common effect factors and for Apgar. Gene Ontology analyses revealed multiple significant biologically relevant terms for the five fully investigated neonatal health risk variables. Given the established links between adverse neonatal outcomes and both immediate and long-term health, the distinct factor effects (representing the common and unique effects of the risk variables) and their biological profiles confirmed in our work, suggest their potential role as clinical biomarkers for assessing health risks and enhancing personalized care.

Antidepressant Exposure and DNA Methylation: Insights from a Methylome-Wide Association Study

Importance

Understanding antidepressant mechanisms could help design more effective and tolerated treatments.

Objective

Identify DNA methylation (DNAm) changes associated with antidepressant exposure.

Design

Case-control methylome-wide association studies (MWAS) of antidepressant exposure were performed from blood samples collected between 2006-2011 in Generation Scotland (GS). The summary statistics were tested for enrichment in specific tissues, gene ontologies and an independent MWAS in the Netherlands Study of Depression and Anxiety (NESDA). A methylation profile score (MPS) was derived and tested for its association with antidepressant exposure in eight independent cohorts, alongside prospective data from GS.

Setting

Cohorts; GS, NESDA, FTC, SHIP-Trend, FOR2107, LBC1936, MARS-UniDep, ALSPAC, E-Risk, and NTR.

Participants

Participants with DNAm data and self-report/prescription derived antidepressant exposure.

Main Outcomes and Measures

Whole-blood DNAm levels were assayed by the EPIC/450K Illumina array (9 studies, N exposed = 661, N unexposed = 9,575) alongside MBD-Seq in NESDA (N exposed = 398, N unexposed = 414). Antidepressant exposure was measured by self- report and/or antidepressant prescriptions.

Results

The self-report MWAS (N = 16,536, N exposed = 1,508, mean age = 48, 59% female) and the prescription-derived MWAS (N = 7,951, N exposed = 861, mean age = 47, 59% female), found hypermethylation at seven and four DNAm sites (p < 9.42x10 -8 ), respectively. The top locus was cg26277237 ( KANK1, p self-report = 9.3x10 -13 , p prescription = 6.1x10 -3 ). The self-report MWAS found a differentially methylated region, mapping to DGUOK-AS1 ( p adj = 5.0x10 -3 ) alongside significant enrichment for genes expressed in the amygdala, the "synaptic vesicle membrane" gene ontology and the top 1% of CpGs from the NESDA MWAS (OR = 1.39, p < 0.042). The MPS was associated with antidepressant exposure in meta-analysed data from external cohorts (N studies = 9, N = 10,236, N exposed = 661, f3 = 0.196, p < 1x10 -4 ).

Conclusions and Relevance

Antidepressant exposure is associated with changes in DNAm across different cohorts. Further investigation into these changes could inform on new targets for antidepressant treatments.

3 Key Points

Question: Is antidepressant exposure associated with differential whole blood DNA methylation?Findings: In this methylome-wide association study of 16,536 adults across Scotland, antidepressant exposure was significantly associated with hypermethylation at CpGs mapping to KANK1 and DGUOK-AS1. A methylation profile score trained on this sample was significantly associated with antidepressant exposure (pooled f3 [95%CI]=0.196 [0.105, 0.288], p < 1x10 -4 ) in a meta-analysis of external datasets. Meaning: Antidepressant exposure is associated with hypermethylation at KANK1 and DGUOK-AS1 , which have roles in mitochondrial metabolism and neurite outgrowth. If replicated in future studies, targeting these genes could inform the design of more effective and better tolerated treatments for depression.

Broodstock nutritional programming differentially affects the hepatic transcriptome and genome-wide DNA methylome of farmed gilthead sea bream (Sparus aurata) depending on genetic background

BACKGROUND

Broodstock nutritional programming improves the offspring utilization of plant-based diets in gilthead sea bream through changes in hepatic metabolism. Attention was initially focused on fatty acid desaturases, but it can involve a wide range of processes that remain largely unexplored. How all this can be driven by a different genetic background is hardly underlined, and the present study aimed to assess how broodstock nutrition affects differentially the transcriptome and genome-wide DNA methylome of reference and genetically selected fish within the PROGENSA® selection program.

RESULTS

After the stimulus phase with a low fish oil diet, two offspring subsets of each genetic background received a control or a FUTURE-based diet. This highlighted a different hepatic transcriptome (RNA-seq) and genome-wide DNA methylation (MBD-seq) pattern depending on the genetic background. The number of differentially expressed transcripts following the challenge phase varied from 323 in reference fish to 2,009 in genetically selected fish. The number of discriminant transcripts, and associated enriched functions, were also markedly higher in selected fish. Moreover, correlation analysis depicted a hyper-methylated and down-regulated gene expression state in selected fish with the FUTURE diet, whereas the opposite pattern appeared in reference fish. After filtering for highly represented functions in selected fish, 115 epigenetic markers were retrieved in this group. Among them, lipid metabolism genes (23) were the most reactive following ordering by fold-change in expression, rendering a final list of 10 top markers with a key role on hepatic lipogenesis and fatty acid metabolism (cd36, pitpna, cidea, fasn, g6pd, lipt1, scd1a, acsbg2, acsl14, acsbg2).

CONCLUSIONS

Gene expression profiles and methylation signatures were dependent on genetic background in our experimental model. Such assumption affected the magnitude, but also the type and direction of change. Thus, the resulting epigenetic clock of reference fish might depict an older phenotype with a lower methylation for the epigenetically responsive genes with a negative methylation-expression pattern. Therefore, epigenetic markers will be specific of each genetic lineage, serving the broodstock programming in our selected fish to prevent and mitigate later in life the risk of hepatic steatosis through changes in hepatic lipogenesis and fatty acid metabolism.

Methylome-wide association study of anxiety disorders

Anxiety Disorders (ANX) such as panic disorder, generalized anxiety disorder, and phobias, are highly prevalent conditions that are moderately heritable. Evidence suggests that DNA methylation may play a role, as it is involved in critical adaptations to changing environments. Applying an enrichment-based sequencing approach covering nearly 28 million autosomal CpG sites, we conducted a methylome-wide association study (MWAS) of lifetime ANX in 1132 participants (618 cases/514 controls) from the Netherlands Study of Depression and Anxiety. Using epigenomic deconvolution, we performed MWAS for the main cell types in blood: granulocytes, T-cells, B-cells and monocytes. Cell-type specific analyses identified 280 and 82 methylome-wide significant associations (q-value < 0.1) in monocytes and granulocytes, respectively. Our top finding in monocytes was located in ZNF823 on chromosome 19 (p = 1.38 × 10-10) previously associated with schizophrenia. We observed significant overlap (p < 1 × 10-06) with the same direction of effect in monocytes (210 sites), T-cells (135 sites), and B-cells (727 sites) between this Discovery MWAS signal and a comparable replication dataset from the Great Smoky Mountains Study (N = 433). Overlapping Discovery-Replication MWAS signal was enriched for findings from published GWAS of ANX, major depression, and post-traumatic stress disorder. In monocytes, two specific sites in the FZR1 gene showed significant replication after Bonferroni correction with an additional 15 nominally replicated sites in monocytes and 4 in T-cells. FZR1 regulates neurogenesis in the hippocampus, and its knockout leads to impairments in associative fear memory and long-term potentiation in mice. In the largest and most extensive methylome-wide study of ANX, we identified replicable methylation sites located in genes of potential relevance for brain mechanisms of psychiatric conditions.

Genes implicated by a methylome-wide schizophrenia study in neonatal blood show differential expression in adult brain samples

Schizophrenia is a disabling disorder involving genetic predisposition in combination with environmental influences that likely act via dynamic alterations of the epigenome and the transcriptome but its detailed pathophysiology is largely unknown. We performed cell-type specific methylome-wide association study of neonatal blood (N = 333) from individuals who later in life developed schizophrenia and controls. Suggestively significant associations (P < 1.0 × 10-6) were detected in all cell-types and in whole blood with methylome-wide significant associations in monocytes (P = 2.85 × 10-9-4.87 × 10-9), natural killer cells (P = 1.72 × 10-9-7.82 × 10-9) and B cells (P = 3.8 × 10-9). Validation of methylation findings in post-mortem brains (N = 596) from independent schizophrenia cases and controls showed significant enrichment of transcriptional differences (enrichment ratio = 1.98-3.23, P = 2.3 × 10-3-1.0 × 10-5), with specific highly significant differential expression for, for example, BDNF (t = -6.11, P = 1.90 × 10-9). In addition, expression difference in brain significantly predicted schizophrenia (multiple correlation = 0.15-0.22, P = 3.6 × 10-4-4.5 × 10-8). In summary, using a unique design combining pre-disease onset (neonatal) blood methylomic data and post-disease onset (post-mortem) brain transcriptional data, we have identified genes of likely functional relevance that are associated with schizophrenia susceptibility, rather than confounding disease associated artifacts. The identified loci may be of clinical value as a methylation-based biomarker for early detection of increased schizophrenia susceptibility.

Early adversities accelerate epigenetic aging into adulthood: a 10-year, within-subject analysis

BACKGROUND

Longitudinal studies are needed to clarify whether early adversities are associated with advanced methylation age or if they actually accelerate methylation aging. This study test whether different dimensions of childhood adversity accelerate biological aging from childhood to adulthood, and, if so, via which mechanisms.

METHODS

381 participants provided one blood sample in childhood (average age 15.0; SD = 2.3) and another in young adulthood (average age 23.1; SD = 2.8). Participants and their parents provided a median of 6 childhood assessments (total = 1,950 childhood observations), reporting exposures to different types of adversity dimensions (i.e. threat, material deprivation, loss, unpredictability). The blood samples were assayed to estimate DNA methylation age in both childhood and adulthood and also change in methylation age across this period.

RESULTS

Cross-sectional associations between the childhood adversity dimensions and childhood measures of methylation age were non-significant. In contrast, multiple adversity dimensions were associated with accelerated within-person change in methylation age from adolescence to young adulthood. These associations attenuated in model testing all dimensions at the same time. Accelerated aging increased with increasing number of childhood adversities: Individuals with highest number of adversities experienced 2+ additional years of methylation aging compared to those with no exposure to childhood adversities. The association between total childhood adversity exposure and accelerated aging was partially explained by childhood depressive symptoms, but not anxiety or behavioral symptoms.

CONCLUSIONS

Early adversities accelerate epigenetic aging long after they occur, in proportion to the total number of such experiences, and in a manner consistent with a shared effect that crosses multiple early dimensions of risk.

CDH1 (E-cadherin) Gene Methylation in Human Breast Cancer: Critical Appraisal of a Long and Twisted Story

Simple Summary

Genes can be inactivated by specific modifications of DNA bases, most often by adding a methyl group to the DNA base cytosine if it is followed by guanosine (CG methylation). This modification prevents gene expression and has been reported for many different genes in nearly all types of cancer. A prominent example is the gene CDH1, which encodes the cell-adhesion molecule E-cadherin. This is an important player in the spreading of tumor cells within the body (metastasis). Particularly in human breast cancer, many different research groups have studied the inactivation of the CDH1 gene via DNA methylation using various methods. Over the last 20 years, different, in part, even contradicting results have been published for the CDH1 gene in breast cancer. This review summarizes the most important publications and explains the bewildering heterogeneity of results through careful analysis of the methods which have been used.

Abstract

Epigenetic inactivation of a tumor suppressor gene by aberrant DNA methylation is a well-established defect in human tumor cells, complementing genetic inactivation by mutation (germline or somatic). In human breast cancer, aberrant gene methylation has diagnostic, prognostic, and predictive potential. A prominent example is the hypermethylation of the CDH1 gene, encoding the adhesion protein E-Cadherin (“epithelial cadherin”). In numerous publications, it is reported as frequently affected by gene methylation in human breast cancer. However, over more than two decades of research, contradictory results concerning CDH1 gene methylation in human breast cancer accumulated. Therefore, we review the available evidence for and against the role of DNA methylation of the CDH1 gene in human breast cancer and discuss in detail the methodological reasons for conflicting results, which are of general importance for the analysis of aberrant DNA methylation in human cancer specimens. Since the loss of E-cadherin protein expression is a hallmark of invasive lobular breast cancer (ILBC), special attention is paid to CDH1 gene methylation as a potential mechanism for loss of expression in this special subtype of human breast cancer. Proper understanding of the methodological basis is of utmost importance for the correct interpretation of results supposed to demonstrate the presence and clinical relevance of aberrant DNA methylation in cancer specimens.

DNA methylation signatures of childhood trauma predict psychiatric disorders and other adverse outcomes 17 years after exposure

Childhood trauma is robustly linked to a broad range of adverse outcomes with consequences persisting far into adulthood. We conducted a prospective longitudinal study to predict psychiatric disorders and other adverse outcomes from trauma-related methylation changes 16.9 years after trauma exposure in childhood. Methylation was assayed using a sequencing-based approach that provides near-complete coverage of all 28 million sites in the blood methylome. Methylation data involved 673 assays from 489 participants aged 13.6 years (SD = 1.9) with outcomes measures collected at age 30.4 (SD = 2.26). For a subset of 303 participants we also generated methylation data in adulthood. Trauma-related methylation risk scores (MRSs) significantly predicted adult depression, externalizing problems, nicotine dependence, alcohol use disorder, serious medical problems, social problems and poverty. The predictive power of the MRSs was higher than that of reported trauma and could not be explained by the reported trauma, correlations with demographic variables, or a continuity of the predicted health problems from childhood to adulthood. Rather than measuring the occurrence of traumatic events, the MRSs seemed to capture the subject-specific impact of trauma. The majority of predictive sites did not remain associated with the outcomes suggesting the signatures of trauma do not become biologically embedded in the blood methylome. Instead, the long-term effects of trauma therefore seemed more consistent with a developmental mechanism where the initial subject-specific impacts of trauma are magnified over time. The MRSs have the potential to be a novel clinical biomarker for the assessment of trauma-related health risks.

Tracking the Evolution of Metastasis with Self-Functionalized 3D Nanoprobes

Despite recent advances in cancer treatment, metastasis is the cause of mortality in 90% of cancer cases. It has now been well-established that dissemination of cancer cells to distant sites occurs very early during tumorigenesis, resulting in the minimal effect of surgical or chemotherapeutic treatments after the detection of metastasis. The underlying reason for this challenge is mostly due to the limited understanding of molecular mechanisms of the metastasis cascade, particularly related to metastatic traits. Therefore, there is an urgent need to investigate this currently invisible evolution of metastasis. The tracking of metastasis evolution has not been addressed yet. Here, we introduce, for the first time, a synchronous approach to unveil the molecular mechanisms of the metastasis cascade. As cancer stem cells (CSCs) demonstrate cancer initiation, drug resistance, metastasis, and tumor relapse and can exist in a quasi-intermediate epithelial-mesenchymal transition state, the tumor-initiating events during a CSCs metamorphosis were monitored with single-cell sensitivity. Because of the invasive and resistive properties of the metastable intermediate CSCs, investigation of the molecular profiles of the quasi-intermediate CSCs was necessary for the detection of metastasis dissemination. For this purpose, the ultrasensitive technique of surface-enhanced Raman scattering (SERS) was adopted. Titanium-based, biocompatible three-dimensional (3D) nanoprobes that were synthesized for multiphoton ionization achieved a substantial SERS enhancement of ∼80-fold due to the oxygen vacancy-enriched composition of the nanoprobes. The 3D interconnected complex nanoarchitecture of the nanoprobes enabled us to entrap the nonadherent CSCs of three metastatic cancer cell lines (triple negative breast adenocarcinoma (MDAMB231), human Caucasian colon adenocarcinoma (COLO 205), and cervical adenocarcinoma (HeLa)─all very aggressive forms of cancer). The nanoprobes not only promoted the CSC proliferation to successfully attain the quasi-intermediate states but also monitored its reprogramming into a cancer cell state. The nanoprobes substantially amplified weak intracellular Raman signals to capture the molecular events during a CSC transformation. The detection of cancer was achieved with 100% accuracy. We experimentally demonstrated that the molecular signatures of CSC reprogramming are cancer-type specific. This observation enabled us to identify the origin of metastasis with 100% accuracy, providing more clarity on the relatively unknown quasi-intermediate states. This first demonstration of CSC-based tracking of metastasis evolution has the potential to provide an insightful perspective of tumorigenesis that could be useful in cancer diagnosis and prognosis as well as in the monitoring of therapeutic interventions.

Dual methylation and hydroxymethylation study of alcohol use disorder

Using an integrative, multi-tissue design, we sought to characterize methylation and hydroxymethylation changes in blood and brain associated with alcohol use disorder (AUD). First, we used epigenomic deconvolution to perform cell-type-specific methylome-wide association studies within subpopulations of granulocytes/T-cells/B-cells/monocytes in 1132 blood samples. Blood findings were then examined for overlap with AUD-related associations with methylation and hydroxymethylation in 50 human post-mortem brain samples. Follow-up analyses investigated if overlapping findings mediated AUD-associated transcription changes in the same brain samples. Lastly, we replicated our blood findings in an independent sample of 412 individuals and aimed to replicate published alcohol methylation findings using our results. Cell-type-specific analyses in blood identified methylome-wide significant associations in monocytes and T-cells. The monocyte findings were significantly enriched for AUD-related methylation and hydroxymethylation in brain. Hydroxymethylation in specific sites mediated AUD-associated transcription in the same brain samples. As part of the most comprehensive methylation study of AUD to date, this work involved the first cell-type-specific methylation study of AUD conducted in blood, identifying and replicating a finding in DLGAP1 that may be a blood-based biomarker of AUD. In this first study to consider the role of hydroxymethylation in AUD, we found evidence for a novel mechanism for cognitive deficits associated with AUD. Our results suggest promising new avenues for AUD research.

Computational challenges in detection of cancer using cell-free DNA methylation

Cell-free DNA(cfDNA) methylation profiling is considered promising and potentially reliable for liquid biopsy to study progress of diseases and develop reliable and consistent diagnostic and prognostic biomarkers. There are several different mechanisms responsible for the release of cfDNA in blood plasma, and henceforth it can provide information regarding dynamic changes in the human body. Due to the fragmented nature, low concentration of cfDNA, and high background noise, there are several challenges in its analysis for regular use in diagnosis of cancer. Such challenges in the analysis of the methylation profile of cfDNA are further aggravated due to heterogeneity, biomarker sensitivity, platform biases, and batch effects. This review delineates the origin of cfDNA methylation, its profiling, and associated computational problems in analysis for diagnosis. Here we also contemplate upon the multi-marker approach to handle the scenario of cancer heterogeneity and explore the utility of markers for 5hmC based cfDNA methylation pattern. Further, we provide a critical overview of deconvolution and machine learning methods for cfDNA methylation analysis. Our review of current methods reveals the potential for further improvement in analysis strategies for detecting early cancer using cfDNA methylation.

Methylomic Investigation of Problematic Adolescent Cannabis Use and Its Negative Mental Health Consequences

OBJECTIVE

The impact of adolescent cannabis use is a pressing public health question owing to the high rates of use and links to negative outcomes. This study considered the association between problematic adolescent cannabis use and methylation.

METHOD

Using an enrichment-based sequencing approach, a methylome-wide association study (MWAS) was performed of problematic adolescent cannabis use in 703 adolescent samples from the Great Smoky Mountain Study. Using epigenomic deconvolution, MWASs were performed for the main cell types in blood: granulocytes, T cells, B cells, and monocytes. Enrichment testing was conducted to establish overlap between cannabis-associated methylation differences and variants associated with negative mental health effects of adolescent cannabis use.

RESULTS

Whole-blood analyses identified 45 significant CpGs, and cell type-specific analyses yielded 32 additional CpGs not identified in the whole-blood MWAS. Significant overlap was observed between the B-cell MWAS and genetic studies of education attainment and intelligence. Furthermore, the results from both T cells and monocytes overlapped with findings from an MWAS of psychosis conducted in brain tissue.

CONCLUSION

In one of the first methylome-wide association studies of adolescent cannabis use, several methylation sites located in genes of importance for potentially relevant brain functions were identified. These findings resulted in several testable hypotheses by which cannabis-associated methylation can impact neurological development and inflammation response as well as potential mechanisms linking cannabis-associated methylation to potential downstream mental health effects.

Cancer Detection and Classification by CpG Island Hypermethylation Signatures in Plasma Cell-Free DNA

Simple Summary

The detection of DNA methylation changes in blood has emerged as a promising approach for cancer diagnosis and management. Our group has previously optimized a blood DNA methylation profiling technology that is based on affinity capture of methylated DNA, termed cfMBD-seq. The aim of this study was to assess the potential clinical feasibility of cfMBD-seq. We applied cfMBD-seq to the blood samples of cancer patients and identified methylation signatures that can not only discriminate cancer patients from cancer-free individuals but can also enable accurate multi-cancer classification. Our findings will help to expand on existing blood-based molecular diagnostic tests and identify novel methylation biomarkers for early cancer detection and classification.

Abstract

Cell-free DNA (cfDNA) methylation has emerged as a promising biomarker for early cancer detection, tumor type classification, and treatment response monitoring. Enrichment-based cfDNA methylation profiling methods such as cfMeDIP-seq have shown high accuracy in the classification of multiple cancer types. We have previously optimized another enrichment-based approach for ultra-low input cfDNA methylome profiling, termed cfMBD-seq. We reported that cfMBD-seq outperforms cfMeDIP-seq in the enrichment of high-CpG-density regions, such as CpG islands. However, the clinical feasibility of cfMBD-seq is unknown. In this study, we applied cfMBD-seq to profiling the cfDNA methylome using plasma samples from cancer patients and non-cancer controls. We identified 1759, 1783, and 1548 differentially hypermethylated CpG islands (DMCGIs) in lung, colorectal, and pancreatic cancer patients, respectively. Interestingly, the vast majority of DMCGIs were overlapped with aberrant methylation changes in corresponding tumor tissues, indicating that DMCGIs detected by cfMBD-seq were mainly driven by tumor-specific DNA methylation patterns. From the overlapping DMCGIs, we carried out machine learning analyses and identified a set of discriminating methylation signatures that had robust performance in cancer detection and classification. Overall, our study demonstrates that cfMBD-seq is a powerful tool for sensitive detection of tumor-derived epigenomic signals in cfDNA.

DNA methylation of the KLK8 gene in depression symptomatology

Background

Depression is a common, complex, and debilitating mental disorder estimated to be under-diagnosed and insufficiently treated in society. Liability to depression is influenced by both genetic and environmental risk factors, which are both capable of impacting DNA methylation (DNAm). Accordingly, numerous studies have researched for DNAm signatures of this disorder. Recently, an epigenome-wide association study of monozygotic twins identified an association between DNAm status in the KLK8 (neuropsin) promoter region and severity of depression symptomatology.

Methods

In this study, we aimed to investigate: (i) if blood DNAm levels, quantified by pyrosequencing, at two CpG sites in the KLK8 promoter are associated with depression symptomatology and depression diagnosis in an independent clinical cohort and (ii) if KLK8 DNAm levels are associated with depression, postpartum depression, and depression symptomatology in four independent methylomic cohorts, with blood and brain DNAm quantified by either MBD-seq or 450 k methylation array.

Results

DNAm levels in KLK8 were not significantly different between depression cases and controls, and were not significantly associated with any of the depression symptomatology scores after correction for multiple testing (minimum p value for KLK8 CpG1 = 0.12 for ‘Depressed mood,’ and for CpG2 = 0.03 for ‘Loss of self-confidence with other people’). However, investigation of the link between KLK8 promoter DNAm levels and depression-related phenotypes collected from four methylomic cohorts identified significant association (p value < 0.05) between severity of depression symptomatology and blood DNAm levels at seven CpG sites.

Conclusions

Our findings suggest that variance in blood DNAm levels in KLK8 promoter region is associated with severity of depression symptoms, but not depression diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01184-5.

Guidelines for pre-analytical conditions for assessing the methylation of circulating cell-free DNA

Methylation analysis of circulating cell-free DNA (cirDNA), as a liquid biopsy, has a significant potential to advance the detection, prognosis, and treatment of cancer, as well as many genetic disorders. The role of epigenetics in disease development has been reported in several hereditary disorders, and epigenetic modifications are regarded as one of the earliest and most significant genomic aberrations that arise during carcinogenesis. Liquid biopsy can be employed for the detection of these epigenetic biomarkers. It consists of isolation (pre-analytical) and detection (analytical) phases. The choice of pre-analytical variables comprising cirDNA extraction and bisulfite conversion methods can affect the identification of cirDNA methylation. Indeed, different techniques give a different return of cirDNA, which confirms the importance of pre-analytical procedures in clinical diagnostics. Although novel techniques have been developed for the simplification of methylation analysis, the process remains complex, as the steps of DNA extraction, bisulfite treatment, and methylation detection are each carried out separately. Recent studies have noted the absence of any standard method for the pre-analytical processing of methylated cirDNA. We have therefore conducted a comprehensive and systematic review of the important pre-analytical and analytical variables and the patient-related factors which form the basis of our guidelines for analyzing methylated cirDNA in liquid biopsy.

Decreased DNA methylation at promoters and gene-specific neuronal hypermethylation in the prefrontal cortex of patients with bipolar disorder

Bipolar disorder (BD) is a severe mental disorder characterized by repeated mood swings. Although genetic factors are collectively associated with the etiology of BD, the underlying molecular mechanisms, particularly how environmental factors affect the brain, remain largely unknown. We performed promoter-wide DNA methylation analysis of neuronal and nonneuronal nuclei in the prefrontal cortex of patients with BD (N = 34) and controls (N = 35). We found decreased DNA methylation at promoters in both cell types in the BD patients. Gene Ontology (GO) analysis of differentially methylated region (DMR)-associated genes revealed enrichment of molecular motor-related genes in neurons, chemokines in both cell types, and ion channel- and transporter-related genes in nonneurons. Detailed GO analysis further revealed that growth cone- and dendrite-related genes, including NTRK2 and GRIN1, were hypermethylated in neurons of BD patients. To assess the effect of medication, neuroblastoma cells were cultured under therapeutic concentrations of three mood stabilizers. We observed that up to 37.9% of DMRs detected in BD overlapped with mood stabilizer-induced DMRs. Interestingly, mood stabilizer-induced DMRs showed the opposite direction of changes in DMRs, suggesting the therapeutic effects of mood stabilizers. Among the DMRs, 12 overlapped with loci identified in a genome-wide association study (GWAS) of BD. We also found significant enrichment of neuronal DMRs in the loci reported in another GWAS of BD. Finally, we performed qPCR of DNA methylation-related genes and found that DNMT3B was overexpressed in BD. The cell-type-specific DMRs identified in this study will be useful for understanding the pathophysiology of BD.

Cell-free DNA methylome profiling by MBD-seq with ultra-low input

Methylation signatures in cell-free DNA (cfDNA) have shown great sensitivity and specificity in the characterization of tumour status and classification of tumour types, as well as the response to therapy and recurrence. Currently, most cfDNA methylation studies are based on bisulphite conversion, especially targeted bisulphite sequencing, while enrichment-based methods such as cfMeDIP-seq are beginning to show potential. Here, we report an enrichment-based ultra-low input cfDNA methylation profiling method using methyl-CpG binding proteins capture, termed cfMBD-seq. We optimized the conditions for cfMBD capture by adjusting the amount of MethylCap protein along with using methylated filler DNA. Our data show high correlation between low input cfMBD-seq and standard MBD-seq (>1000 ng input). When compared to cfMEDIP-seq, cfMBD-seq demonstrates higher sequencing data quality with more sequenced reads passed filter and less duplicate rate. cfMBD-seq also outperforms cfMeDIP-seq in the enrichment of CpG islands. This new bisulphite-free ultra-low input methylation profiling technology has great potential in non-invasive and cost-effective cancer detection and classification.

Integrated Transcriptomic and Epigenetic Study of PCOS: Impact of Map3k1 and Map1lc3a Promoter Methylation on Autophagy

Polycystic ovary syndrome (PCOS) is a prevalent heterogeneous endocrine and metabolic disorder in women of reproductive age. Epigenetic mechanisms contribute to the development of PCOS. Nevertheless, the role of DNA methylation in the development of PCOS remains unclear. To investigate the molecular mechanisms underlying the hyperandrogenic phenotype of PCOS, dihydrotestosterone (DHT)-induced prenatally androgenized (PNA) mice were used to mimic this phenotype. Ovarian samples from PNA and control mice were subjected to methyl-CpG-binding domain (MBD)-seq and RNA-seq, and validation was conducted using methylation-specific polymerase chain reaction (MSP) and quantitative real-time PCR (RT-qPCR). Immunohistochemical analysis (using anti-LC3II antibody) and transmission electron microscopy were conducted using ovarian tissue sections (which included granulosa cells) from PNA and control mice. There were 857 genes with differentially methylated promoter regions and 3,317 differentially expressed genes (DEGs) in the PNA mice compared to the control mice. Downregulation of Dnmt1 (which encodes DNA methyltransferase 1), accompanied by global hypomethylation, was observed in the PNA mice compared to the control mice. The promoter regions of Map3k1 (which encodes MEKK1) and Map1lc3a (which encodes LC3II) were hypomethylated, accompanied by upregulation of Map3k1 and Map1lc3a mRNA expression. The autophagy profiling results showed that LC3II protein expression and autophagosomes were significantly increased in the granulosa cells of PNA mice. Additionally, the mRNA expression of genes related to the mitogen-activated protein kinase (MAPK)/p53 pathway (Mapk14, Mapkapk3, and Trp53) and the autophagy-related gene Becn1 were significantly increased. DHT could change the DNA methylation and transcription level of Map3k1 and lead to an activation of autophagy in granulosa cells. These observations indicated that the change in autophagy may be driven by MAPK/p53 pathway activation, which may have been caused by DHT-induced transcriptional, and the methylation level changed of the key upstream gene Map3k1. Our study provides a novel genetic basis and new insights regarding the pathogenesis of PCOS.

Liquid Biopsy of Methylation Biomarkers in Cell-Free DNA

Liquid biopsies, in particular, analysis of cell-free DNA (cfDNA), have emerged as a promising noninvasive diagnostic approach in oncology. Abnormal distribution of DNA methylation is one of the hallmarks of many cancers and methylation changes occur early during carcinogenesis. Systemic analysis of cfDNA methylation profiles is being developed for cancer early detection, monitoring for minimal residual disease (MRD), predicting treatment response and prognosis, and tracing the tissue origin. This review highlights the advantages and disadvantages of ctDNA profiling for noninvasive diagnosis of early-stage cancers and explores recent advances in the clinical application of ctDNA methylation assays. We also summarize the technologies for ctDNA methylation analysis and provide a brief overview of the bioinformatic approaches for analyzing DNA methylation sequencing data.

A methylation study of long-term depression risk

Recurrent and chronic major depressive disorder (MDD) accounts for a substantial part of the disease burden because this course is most prevalent and typically requires long-term treatment. We associated blood DNA methylation profiles from 581 MDD patients at baseline with MDD status 6 years later. A resampling approach showed a highly significant association between methylation profiles in blood at baseline and future disease status (P = 2.0 × 10^-16). Top MWAS results were enriched specific pathways, overlapped with genes found in GWAS of MDD disease status, autoimmune disease and inflammation, and co-localized with eQTLS and (genic enhancers of) of transcription sites in brain and blood. Many of these findings remained significant after correction for multiple testing. The major themes emerging were cellular responses to stress and signaling mechanisms linked to immune cell migration and inflammation. This suggests that an immune signature of treatment-resistant depression is already present at baseline. We also created a methylation risk score (MRS) to predict MDD status 6 years later. The AUC of our MRS was 0.724 and higher than risk scores created using a set of five putative MDD biomarkers, genome-wide SNP data, and 27 clinical, demographic and lifestyle variables. Although further studies are needed to examine the generalizability to different patient populations, these results suggest that methylation profiles in blood may present a promising avenue to support clinical decision making by providing empirical information about the likelihood MDD is chronic or will recur in the future.

Methylome-wide association findings for major depressive disorder overlap in blood and brain and replicate in independent brain samples

We present the first large-scale methylome-wide association studies (MWAS) for major depressive disorder (MDD) to identify sites of potential importance for MDD etiology. Using a sequencing-based approach that provides near-complete coverage of all 28 million common CpGs in the human genome, we assay methylation in MDD cases and controls from both blood (N = 1132) and postmortem brain tissues (N = 61 samples from Brodmann Area 10, BA10). The MWAS for blood identified several loci with P ranging from 1.91 × 10^-8 to 4.39 × 10^-8 and a resampling approach showed that the cumulative association was significant (P = 4.03 × 10^-10) with the signal coming from the top 25,000 MWAS markers. Furthermore, a permutation-based analysis showed significant overlap (P = 5.4 × 10^-3) between the MWAS findings in blood and brain (BA10). This overlap was significantly enriched for a number of features including being in eQTLs in blood and the frontal cortex, CpG islands and shores, and exons. The overlapping sites were also enriched for active chromatin states in brain including genic enhancers and active transcription start sites. Furthermore, three loci located in GABBR2, RUFY3, and in an intergenic region on chromosome 2 replicated with the same direction of effect in the second brain tissue (BA25, N = 60) from the same individuals and in two independent brain collections (BA10, N = 81 and 64). GABBR2 inhibits neuronal activity through G protein-coupled second-messenger systems and RUFY3 is implicated in the establishment of neuronal polarity and axon elongation. In conclusion, we identified and replicated methylated loci associated with MDD that are involved in biological functions of likely importance to MDD etiology.

Cell Type-Specific Methylome-wide Association Studies Implicate Neurotrophin and Innate Immune Signaling in Major Depressive Disorder

BACKGROUND

We sought to characterize methylation changes in brain and blood associated with major depressive disorder (MDD). As analyses of bulk tissue may obscure association signals and hamper the biological interpretation of findings, these changes were studied on a cell type-specific level.

METHODS

In 3 collections of human postmortem brain (n = 206) and 1 collection of blood samples (N = 1132) of MDD cases and controls, we used epigenomic deconvolution to perform cell type-specific methylome-wide association studies within subpopulations of neurons/glia for the brain data and granulocytes/T cells/B cells/monocytes for the blood data. Sorted neurons/glia from a fourth postmortem brain collection (n = 58) were used for validation purposes.

RESULTS

Cell type-specific methylome-wide association studies identified multiple findings in neurons/glia that were detected across brain collections and were reproducible in physically sorted nuclei. Cell type-specific analyses in blood samples identified methylome-wide significant associations in T cells, monocytes, and whole blood that replicated findings from a past methylation study of MDD. Pathway analyses implicated p75 neurotrophin receptor/nerve growth factor signaling and innate immune toll-like receptor signaling in MDD. Top results in neurons, glia, bulk brain, T cells, monocytes, and whole blood were enriched for genes supported by genome-wide association studies for MDD and other psychiatric disorders.

CONCLUSIONS

We both replicated and identified novel MDD-methylation associations in human brain and blood samples at a cell type-specific level. Our results provide mechanistic insights into how the immune system may interact with the brain to affect MDD susceptibility. Importantly, our findings involved associations with MDD in human samples that implicated many closely related biological pathways. These disease-linked sites and pathways represent promising new therapeutic targets for MDD.

Independent Methylome-Wide Association Studies of Schizophrenia Detect Consistent Case-Control Differences

Methylome-wide association studies (MWASs) are promising complements to sequence variation studies. We used existing sequencing-based methylation data, which assayed the majority of all 28 million CpGs in the human genome, to perform an MWAS for schizophrenia in blood, while controlling for cell-type heterogeneity with a recently generated platform-specific reference panel. Next, we compared the MWAS results with findings from 3 existing large-scale array-based schizophrenia methylation studies in blood that assayed up to ~450 000 CpGs. Our MWAS identified 22 highly significant loci (P < 5 × 10-8) and 852 suggestively significant loci (P < 1 × 10-5). The top finding (P = 5.62 × 10-11, q = 0.001) was located in MFN2, which encodes mitofusin-2 that regulates Ca2+ transfer from the endoplasmic reticulum to mitochondria in cooperation with DISC1. The second-most significant site (P = 1.38 × 10-9, q = 0.013) was located in ALDH1A2, which encodes an enzyme for astrocyte-derived retinoic acid-a key neuronal morphogen with relevance for schizophrenia. Although the most significant MWAS findings were not assayed on the arrays, we observed significant enrichment of overlapping findings with 2 of the 3 array datasets (P = 0.0315, 0.0045, 0.1946). Overrepresentation analysis of Gene Ontology terms for the genes in the significant overlaps suggested high similarity in the biological functions detected by the different datasets. Top terms were related to immune and/or stress responses, cell adhesion and motility, and a broad range of processes essential for neurodevelopment.

MBD-seq - realities of a misunderstood method for high-quality methylome-wide association studies

The majority of methylome-wide association studies (MWAS) have been performed using commercially available array-based technologies such as the Infinium Human Methylation 450K and the Infinium MethylationEPIC arrays (Illumina). While these arrays offer a convenient and relatively robust assessment of the probed sites they only allow interrogation of 2-4% of all CpG sites in the human genome. Methyl-binding domain sequencing (MBD-seq) is an alternative approach for MWAS that provides near-complete coverage of the methylome at similar costs as the array-based technologies. However, despite publication of multiple positive evaluations, the use of MBD-seq for MWAS is often fiercely criticized. Here we discuss key features of the method and debunk misconceptions using empirical data. We conclude that MBD-seq represents an excellent approach for large-scale MWAS and that increased utilization is likely to result in more discoveries, advance biological knowledge, and expedite the clinical translation of methylome-wide research findings.

Cell-Free DNA Methylation Profiling Analysis-Technologies and Bioinformatics

Analysis of circulating nucleic acids in bodily fluids, referred to as “liquid biopsies”, is rapidly gaining prominence. Studies have shown that cell-free DNA (cfDNA) has great potential in characterizing tumor status and heterogeneity, as well as the response to therapy and tumor recurrence. DNA methylation is an epigenetic modification that plays an important role in a broad range of biological processes and diseases. It is well known that aberrant DNA methylation is generalizable across various samples and occurs early during the pathogenesis of cancer. Methylation patterns of cfDNA are also consistent with their originated cells or tissues. Systemic analysis of cfDNA methylation profiles has emerged as a promising approach for cancer detection and origin determination. In this review, we will summarize the technologies for DNA methylation analysis and discuss their feasibility for liquid biopsy applications. We will also provide a brief overview of the bioinformatic approaches for analysis of DNA methylation sequencing data. Overall, this review provides informative guidance for the selection of experimental and computational methods in cfDNA methylation-based studies.

RaMWAS: fast methylome-wide association study pipeline for enrichment platforms

Motivation

Enrichment-based technologies can provide measurements of DNA methylation at tens of millions of CpGs for thousands of samples. Existing tools for methylome-wide association studies cannot analyze datasets of this size and lack important features like principal component analysis, combined analysis with SNP data and outcome predictions that are based on all informative methylation sites.

Results

We present a Bioconductor R package called RaMWAS with a full set of tools for large-scale methylome-wide association studies. It is free, cross-platform, open source, memory efficient and fast.

Availability and implementation

Release version and vignettes with small case study at bioconductor.org/packages/ramwas Development version at github.com/andreyshabalin/ramwas.

Supplementary information

Supplementary data are available at Bioinformatics online.

A Whole Methylome Study of Ethanol Exposure in Brain and Blood: An Exploration of the Utility of Peripheral Blood as Proxy Tissue for Brain in Alcohol Methylation Studies

BACKGROUND

Recent reviews have highlighted the potential use of blood-based methylation biomarkers as diagnostic and prognostic tools of current and future alcohol use and addiction. Due to the substantial overlap that often exists between methylation patterns across different tissues, including blood and brain, blood-based methylation may track methylation changes in brain; however, little work has explored the overlap in alcohol-related methylation in these tissues.

METHODS

To study the effects of alcohol on the brain methylome and identify possible biomarkers of these changes in blood, we performed a methylome-wide association study in brain and blood from 40 male DBA/2J mice that received either an acute ethanol (EtOH) or saline intraperitoneal injection. To investigate all 22 million CpGs in the mouse genome, we enriched for the methylated genomic fraction using methyl-CpG binding domain (MBD) protein capture followed by next-generation sequencing (MBD-seq). We performed association tests in blood and brain separately followed by enrichment testing to determine whether there was overlapping alcohol-related methylation in the 2 tissues.

RESULTS

The top result for brain was a CpG located in an intron of Ttc39b (p = 5.65 × 10^-08 ), and for blood, the top result was located in Espnl (p = 5.11 × 10^-08 ). Analyses implicated pathways involved in inflammation and neuronal differentiation, such as CXCR4, IL-7, and Wnt signaling. Enrichment tests indicated significant overlap among the top results in brain and blood. Pathway analyses of the overlapping genes converge on MAPKinase signaling (p = 5.6 × 10^-05 ) which plays a central role in acute and chronic responses to alcohol and glutamate receptor pathways, which can regulate neuroplastic changes underlying addictive behavior.

CONCLUSIONS

Overall, we have shown some methylation changes in brain and blood after acute EtOH administration and that the changes in blood partly mirror the changes in brain suggesting the potential for DNA methylation in blood to be biomarkers of alcohol use.

Convergence of evidence from a methylome-wide CpG-SNP association study and GWAS of major depressive disorder

DNA methylation is an epigenetic modification that provides stability and diversity to the cellular phenotype. It is influenced by both genetic sequence variation and environmental factors, and can therefore potentially account for variation of heritable phenotypes and disorders. Therefore, methylome-wide association studies (MWAS) are promising complements to genome-wide association studies (GWAS) of genetic variants. Of particular interest are methylation sites (CpGs) that are created or destroyed by the alleles of single-nucleotide polymorphisms (SNPs), as these so-called CpG-SNPs may show variation in methylation levels on top of what can be explained by the sequence variation. Using sequencing-based data from 1132 major depressive disorder (MDD) cases and controls, we performed a MWAS of 970,414 common CpG-SNPs. The analysis identified 27 suggestively significant (P < 1.00 × 10^-5) CpG-SNPs associations. Furthermore, the MWAS results were over-represented (odds ratios ranging 1.36-5.00; P ranging 4.9 × 10^-3-8.1 × 10^-2) among findings from three recent GWAS for MDD-related phenotypes. Overlapping loci included, e.g., ROBO2, ASIC2, and DCC. As the CpG-SNP analysis accounts for the number of alleles that creates CpGs, the methylation differences could not be explained by differences in allele frequencies. Thus, the results show that the MWAS and GWASs provide independent lines of evidence for the involvement of these loci in MDD. In conclusion, our methylation study of MDD contributes novel information about loci of relevance that complements previous findings and generates new hypothesis about MDD etiology, such as that the functional effects of genetic association may be partly mediated and/or enhanced by the methylation status in these loci.

Epigenetic Aging in Major Depressive Disorder

OBJECTIVE

Major depressive disorder is associated with an increased risk of mortality and aging-related diseases. The authors examined whether major depression is associated with higher epigenetic aging in blood as measured by DNA methylation (DNAm) patterns, whether clinical characteristics of major depression have a further impact on these patterns, and whether the findings replicate in brain tissue.

METHOD

DNAm age was estimated using all methylation sites in blood of 811 depressed patients and 319 control subjects with no lifetime psychiatric disorders and low depressive symptoms from the Netherlands Study of Depression and Anxiety. The residuals of the DNAm age estimates regressed on chronological age were calculated to indicate epigenetic aging. Major depression diagnosis and clinical characteristics were assessed with questionnaires and psychiatric interviews. Analyses were adjusted for sociodemographic characteristics, lifestyle, and health status. Postmortem brain samples of 74 depressed patients and 64 control subjects were used for replication. Pathway enrichment analysis was conducted using ConsensusPathDB to gain insight into the biological processes underlying epigenetic aging in blood and brain.

RESULTS

Significantly higher epigenetic aging was observed in patients with major depression compared with control subjects (Cohen's d=0.18), with a significant dose effect with increasing symptom severity in the overall sample. In the depression group, epigenetic aging was positively and significantly associated with childhood trauma score. The case-control difference was replicated in an independent data set of postmortem brain samples. The top significantly enriched Gene Ontology terms included neuronal processes.

CONCLUSIONS

As compared with control subjects, patients with major depression exhibited higher epigenetic aging in blood and brain tissue, suggesting that they are biologically older than their corresponding chronological age. This effect was even more profound in the presence of childhood trauma.

A MBD-seq protocol for large-scale methylome-wide studies with (very) low amounts of DNA

We recently showed that, after optimization, our methyl-CpG binding domain sequencing (MBD-seq) application approximates the methylome-wide coverage obtained with whole-genome bisulfite sequencing (WGB-seq), but at a cost that enables adequately powered large-scale association studies. A prior drawback of MBD-seq is the relatively large amount of genomic DNA (ideally >1 µg) required to obtain high-quality data. Biomaterials are typically expensive to collect, provide a finite amount of DNA, and may simply not yield sufficient starting material. The ability to use low amounts of DNA will increase the breadth and number of studies that can be conducted. Therefore, we further optimized the enrichment step. With this low starting material protocol, MBD-seq performed equally well, or better, than the protocol requiring ample starting material (>1 µg). Using only 15 ng of DNA as input, there is minimal loss in data quality, achieving 93% of the coverage of WGB-seq (with standard amounts of input DNA) at similar false/positive rates. Furthermore, across a large number of genomic features, the MBD-seq methylation profiles closely tracked those observed for WGB-seq with even slightly larger effect sizes. This suggests that MBD-seq provides similar information about the methylome and classifies methylation status somewhat more accurately. Performance decreases with <15 ng DNA as starting material but, even with as little as 5 ng, MBD-seq still achieves 90% of the coverage of WGB-seq with comparable genome-wide methylation profiles. Thus, the proposed protocol is an attractive option for adequately powered and cost-effective methylome-wide investigations using (very) low amounts of DNA.