DNA methylation of the KLK8 gene in depression symptomatology

Abstract 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.

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EPIGENETIC ALTERATIONS ASSOCIATED WITH PREMATURE OVARIAN FAILURE

Clinical & Investigative Medicine ◽

10.25011/cim.v31i4.4804 ◽

2008 ◽

Vol 31 (4) ◽

pp. 11

Author(s):

Manda Ghahremani ◽

Courtney W Hannah ◽

Maria Peneherrera ◽

Karla L Bretherick ◽

Margo R Fluker ◽

...

Keyword(s):

Dna Methylation ◽

Premature Ovarian Failure ◽

Promoter Region ◽

Gene Promoter ◽

Ovarian Failure ◽

P Value ◽

Epigenetic Alterations ◽

Methylation Array ◽

Cpg Sites ◽

Deficient Mice

Background/Purpose: Premature ovarian failure (POF) affects 1% of women with a largely idiopathic and poorly understood etiology. The objective of this study was to identify specific epigenetic alterations by measuring DNA methylation of gene regulatory regions in women with POF vs. controls. Methods: Blood samples were collected from idiopathic POFpatients (Amenorrhea for at least 3 months and 2 serum FSH levels of > 40mIU/ml obtained > 1 month apart prior to age 40) and control women (CW) (healthy pregnancy after age 37 with out a pregnancy loss). Genomic DNA was extracted from EDTA anticoagulated blood and bisulfite converted for analysis using the Illumina Golden Gate Methylation Panel which measures DNA methylation at 1506 CpG sites in the promoter regions of 807 genes in 10 POF and 12 CW. Candidate genes with altered epigenetic marks between POF and CW at a nominal P-value < 0.05 were identified using a t-testcomparison within the Illumina bead studio software. Genes of interest were further analyzed for quantitative methylation at specific CpG sites using pyrosequencing in 30 POF and 30 CW. Results: Comparison of DNA methylation profiles of our initial POF and CW groups identified several genes with statistically significanthyper- or hypo- methylation in the POF group (P < 0.05), including the Androgen Receptor (AR)promoter region, which was significantly hypermethylated. To further validate these results, DNA methylation of the AR gene promoter was quantified bypryosequencing in a larger group of POF and CW. Pyrosequencing further confirmed a significantly higher DNA methylation of the AR promoter region inPOF vs. CW (P=0.007). Conclusions: This is a novel study identifying epigenetic alterations in POF. The hypermethylation of the AR gene in POF patients may cause decreased level of the AR in these women. This is especially interesting given a recent report of induced POF in AR deficient mice^1. Specific epigenetic markers, as identified by DNA methylation array profiling in blood, may serve as useful biomarkers for POF and other fertility disorders. However, it will need to be determined if these methylation changes are present prior to diagnosis, or are a consequence of menopause itself. Reference: 1.Hiroko S. et al. Premature ovarian failure in androgenreceptor deficient mice. PNAS;103:224-9

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EGFR DNA Methylation Correlates With EGFR Expression, Immune Cell Infiltration, and Overall Survival in Lung Adenocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.691915 ◽

2021 ◽

Vol 11 ◽

Author(s):

Zhanyu Xu ◽

Fanglu Qin ◽

Liqiang Yuan ◽

Jiangbo Wei ◽

Yu Sun ◽

...

Keyword(s):

Dna Methylation ◽

Protein Expression ◽

Lung Adenocarcinoma ◽

Methylation Level ◽

Promoter Region ◽

Body Region ◽

Gene Body ◽

Immune Infiltration ◽

Cpg Sites ◽

Gene Body Region

BackgroundThe epidermal growth factor receptor (EGFR) is a primary target of molecular targeted therapy for lung adenocarcinoma (LUAD). The mechanisms that lead to epigenetic abnormalities of EGFR in LUAD are still unclear. The purpose of our study was to evaluate the abnormal methylation of EGFR CpG sites as potential biomarkers for LUAD.MethodsTo assess the differentially methylation CpG sites of EGFR in LUAD, we used an integrative study of Illumina HumanMethylation450K and RNA-seq data from The Cancer Genome Atlas (TCGA). We evaluated and compared EGFR multiple-omics data to explore the role of CpG sites located in EGFR promoter regions and gene body regions and the association with transcripts, protein expression levels, mutations, and somatic copy number variation. We calculated the correlation coefficients between CpG sites of EGFR and immune infiltration fraction (by MCPcounter and ESTIMATE) and immune-related pathways in LUAD. Finally, we validated the differential methylation of clinically and prognostically relevant CpG sites using quantitative methylation-specific PCR (qMSP).ResultsWe found that the methylation level of many EGFR CpGs in the promoter region was negatively correlated with the transcription level, protein expression, and SCNV, while the methylation at the gene body region was positively correlated with these features. The methylation level of EGFR CpGs in the promoter region was positively correlated with the level of immune infiltration and IFN-γ signature, while the opposite was found for methylation of the gene body region. The qMSP results showed that cg02316066 had a high methylation level, while cg02166842 had a low methylation level in LUAD. There was a high degree of co-methylation between cg02316066 and cg03046247.ConclusionOur data indicate that EGFR is an epigenetic regulator in LUAD acting through DNA methylation. Our research provides a theoretical basis for the further detection of EGFR DNA methylation as a predictive biomarker for LUAD survival and immunotherapy.

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Systematic evaluation of the causal relationship between DNA methylation and C-reactive protein

10.1101/397836 ◽

2018 ◽

Cited By ~ 3

Author(s):

Esther Walton ◽

Gibran Hemani ◽

Abbas Dehghan ◽

Caroline Relton ◽

George Davey Smith

Keyword(s):

Dna Methylation ◽

Multiple Testing ◽

Causal Effect ◽

Systematic Evaluation ◽

Low Grade ◽

Genetic Associations ◽

C Reactive Protein ◽

Individual Level ◽

Reactive Protein ◽

Cpg Sites

AbstractElevated C-reactive protein (CRP) levels are an indicator of chronic low-grade inflammation. Epigenetic modifications, including DNA methylation, have been linked to CRP, but systematic investigations into potential underlying causal relationships have not yet been performed.We systematically performed two-sample Mendelian randomization and colocalization analysis between CRP and DNA methylation levels, using GWAS and EWAS summary statistics as well as individual level data available through the ARIES subset of the Avon Longitudinal Study of Parents and Children (ALSPAC; 1,616 participants).We found no convincing examples for a causal association from CRP to DNA methylation. Testing for the reverse (a putative causal effect of DNA methylation on CRP), we found three CpG sites that had shared genetic effects with CRP levels after correcting for multiple testing (cg26470501 (offspring: beta=0.07 [0.03, 0.11]; mothers: beta=0.08 [0.04, 0.13]), cg27023597 (offspring: beta=0.18 [0.10, 0.25]; mothers: beta=0.20 [0.12, 0.28]) and cg12054453 (offspring: beta=0.09 [0.05, 0.13])) influenced CRP levels. For all three CpG sites, linked to the genes TMEM49, BCL3 and MIR21, increased methylation related to an increase in CRP levels. Two CpGs (cg27023597 and cg12054453) were influenced by SNPs in genomic regions that had not previously been implicated in CRP GWASs, implicating them as novel genetic associations.Overall, our findings suggest that CRP associations with DNA methylation are more likely to be driven by either confounding or causal influences of DNA methylation on CRP levels, rather than the reverse.

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Genome-wide DNA methylation analysis of pulmonary function in middle and old-aged Chinese monozygotic twins

Respiratory Research ◽

10.1186/s12931-021-01896-5 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Tong Wang ◽

Weijing Wang ◽

Weilong Li ◽

Haiping Duan ◽

Chunsheng Xu ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Pulmonary Function ◽

Monozygotic Twins ◽

Linear Mixed Effect Model ◽

Sequencing Analysis ◽

Mixed Effect ◽

Cpg Sites ◽

Genome Wide ◽

Genomic Regions

Abstract Background Previous studies have determined the epigenetic association between DNA methylation and pulmonary function among various ethnics, whereas this association is largely unknown in Chinese adults. Thus, we aimed to explore epigenetic relationships between genome-wide DNA methylation levels and pulmonary function among middle-aged Chinese monozygotic twins. Methods The monozygotic twin sample was drawn from the Qingdao Twin Registry. Pulmonary function was measured by three parameters including forced expiratory volume the first second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio. Linear mixed effect model was used to regress the methylation level of CpG sites on pulmonary function. After that, we applied Genomic Regions Enrichment of Annotations Tool (GREAT) to predict the genomic regions enrichment, and used comb-p python library to detect differentially methylated regions (DMRs). Gene expression analysis was conducted to validate the results of differentially methylated analyses. Results We identified 112 CpG sites with the level of P < 1 × 10–4 which were annotated to 40 genes. We identified 12 common enriched pathways of three pulmonary function parameters. We detected 39 DMRs located at 23 genes, of which PRDM1 was related to decreased pulmonary function, and MPL, LTB4R2, and EPHB3 were related to increased pulmonary function. The gene expression analyses validated DIP2C, ASB2, SLC6A5, and GAS6 related to decreased pulmonary function. Conclusion Our DNA methylation sequencing analysis on identical twins provides new references for the epigenetic regulation on pulmonary function. Several CpG sites, genes, biological pathways and DMRs are considered as possible crucial to pulmonary function.

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DNA methylation partially mediates the relationship between childhood adversity and depressive symptoms in adolescence

10.1101/2021.06.28.21259426 ◽

2021 ◽

Author(s):

Brooke J. Smith ◽

Alexandre A Lussier ◽

Janine Cerutti ◽

Daniel J. Schaid ◽

Andrew J. Simpkin ◽

...

Keyword(s):

Dna Methylation ◽

Depressive Symptoms ◽

Life Course ◽

Adolescent Depression ◽

Childhood Adversity ◽

Depression Symptoms ◽

Cpg Sites ◽

Cpg Site ◽

Sensitive Periods ◽

The Relationship

Background: Exposure to adversity during childhood is estimated to at least double the risk of depression later in life. Some evidence suggests childhood adversity may have a greater impact on depression risk, if experienced during specific windows of development called sensitive periods. During these sensitive periods, there is evidence that adversity may leave behind biological memories, including changes in DNA methylation (DNAm). Here we ask if those changes play a role in the link between adversity and later adolescent depressive symptoms. Methods: We applied a method for high-dimensional mediation analysis using data from a subsample (n=627-675) of the Avon Longitudinal Study of Parents and Children. We first assessed the possibility of time-dependent relationships between seven types of childhood adversity (caregiver abuse, physical/sexual abuse, maternal psychopathology, one-adult household, family instability, financial stress, neighborhood disadvantage), measured on at least four occasions between ages 0-7 years, and adolescent depression at mean age 10.6. Specifically, we considered three types of life course hypotheses (sensitive periods, accumulation, and recency), and then evaluated which of these hypotheses had the strongest association in each adversity-adolescent depression relationship using the structured life course modeling approach (SLCMA; pronounced slick-mah). To conduct the mediation analyses, we used a combination of pruning and sure independence screening (a dimension reduction method) to reduce the number of methylated CpG sites under consideration to a viable subset for our sample size. We then applied a sparse group lasso penalized model to identify the top mediating loci from that subset using the combined strength of the coefficient measuring the relationship between the childhood adversity and a CpG site (α) and of the coefficient measuring the relationship between the CpG site and depressive symptoms (β) as a metric. Using a Monte Carlo method for assessing mediation (MCMAM), we assigned a significance level and confidence interval to each identified mediator. Results: Across all seven adversities, we identified a total of 70 CpG sites that showed evidence of mediating the relationship between adversity and adolescent depression symptoms. Of these 70 mediators, 37 were significant at the p < 0.05 level when applying the MCMAM, a method tailored to estimating the significance of SEM-derived mediation effects. These sites exhibited four different mediating patterns, differentiated by the direction of α and β. These patterns had signals that were: (1) both positive (19 loci), (2) both negative (18 loci), (3) positive α and negative β (23 loci) or (4) negative α and positive β (10 loci). Conclusion: Our results suggest that DNAm partially mediates the relationship between different types of childhood adversity and depressive symptoms in adolescence. These findings provide insight into the biological mechanisms that link childhood adversity to depression, which will ultimately help develop treatments to prevent depression in more vulnerable populations.

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Using Genetic Burden Scores for Gene-by-Methylation Interaction Analysis on Metabolic Syndrome in African Americans

Biological Research For Nursing ◽

10.1177/1099800419828486 ◽

2019 ◽

Vol 21 (3) ◽

pp. 279-285

Author(s):

Jacquelyn Y. Taylor ◽

Erin B. Ware ◽

Michelle L. Wright ◽

Jennifer A. Smith ◽

Sharon L. R. Kardia

Keyword(s):

Metabolic Syndrome ◽

Dna Methylation ◽

Data Analysis ◽

African Americans ◽

Multiple Testing ◽

African American Men ◽

Interaction Analysis ◽

Association Studies ◽

Cpg Sites ◽

Genetic Burden

With the rapid advancement of omics-based research, particularly big data such as genome- and epigenome-wide association studies that include extensive environmental and clinical variables, data analytics have become increasingly complex. Researchers face significant challenges regarding how to analyze multifactorial data and make use of the findings for clinical translation. The purpose of this article is to provide a scientific exemplar for use of genetic burden scores as a data analysis method for studies with both genotype and DNA methylation data in which the goal is to evaluate associations with chronic conditions such as metabolic syndrome (MetS). This study included 739 African American men and women from the Genetic Epidemiology Network of Arteriopathy Study who met diagnostic criteria for MetS and had available genetic and epigenetic data. Genetic burden scores for evaluated genes were not significant after multiple testing corrections, but DNA methylation at 2 CpG sites (dihydroorotate dehydrogenase cg22381196 pFDR = .014; CTNNA3 cg00132141 pFDR = .043) was significantly associated with MetS after controlling for multiple comparisons. Interactions between the marginally significant CpG sites and burden scores, however, were not significant. More work is required in this area to identify intermediate biological pathways influenced by environmental, genetic, and epigenetic variation that may explain the high prevalence of MetS among African Americans. This study does serve, however, as an example of the use of the genetic burden score as an alternative data analysis approach for complex studies involving the analysis of genetic and epigenetic data simultaneously.

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Association of Aberrant DNA Methylation Level in the CD4 and JAK-STAT-Pathway-Related Genes with Mastitis Indicator Traits in Chinese Holstein Dairy Cattle

Animals ◽

10.3390/ani12010065 ◽

2021 ◽

Vol 12 (1) ◽

pp. 65

Author(s):

Tahir Usman ◽

Nawab Ali ◽

Yachun Wang ◽

Ying Yu

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Dairy Cattle ◽

Methylation Level ◽

Promoter Region ◽

Promoter Regions ◽

Cpg Sites ◽

Cell Counts ◽

Aberrant Dna Methylation ◽

Stat Pathway

The present study was designed to evaluate the gene expression and DNA methylation level in the promoter region of the CD4 and the JAK-STAT-pathway-related genes. A total of 24 samples were deployed in the gene expression and 118 samples were used in the DNA methylation study. Student’s t-tests were used to analyze the gene expression and DNA methylation. The evaluation of DNA methylation in promoter regions of JAK2 and STAT5A revealed hypo-methylation levels of CpG sites and higher gene expression in cows diagnosed with mastitis as compared to the healthy control, and vice versa in those with CD4. DNA methylation was negatively correlated with gene expression in JAK2, STAT5A, and CD4 genes. Six, two, and four active transcription factors were identified on the CpG sites in the promoter regions of JAK2, STAT5A, and CD4 genes, respectively. Regarding correlation analysis, the DNA methylation levels of CD4 showed significantly higher positive correlations with somatic cell counts (p < 0.05). Findings of the current study inferred that aberrant DNA methylation in the CpG sites at the 1 kb promoter region in JAK2, STAT5A, and CD4 genes due to mastitis in cows can be used as potential epigenetic markers to estimate bovine mastitis susceptibility in dairy cattle.

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DNA methylation-based immune cell deconvolution in solid tumors

10.1101/619965 ◽

2019 ◽

Cited By ~ 1

Author(s):

Cong Liang ◽

Xiaoqing Yu ◽

Bo Li ◽

Y. Ann Chen ◽

Jose R. Conejo-Garcia ◽

...

Keyword(s):

Dna Methylation ◽

Prediction Models ◽

Immune Cell ◽

Cell Types ◽

Therapeutic Interventions ◽

Clinical Practices ◽

Methylation Array ◽

Cpg Sites ◽

High Concordance ◽

Cancer Types

AbstractUnderstanding of the tumor microenvironment (TME) structure is likely to have a profound and immediate impact on therapeutic interventions as well as the development of signatures for diagnostic and prognostic evaluations. DNA methylation arrays represent one of the most reproducible molecular assays across replicates and studies, but its value of profiling tumor-infiltrating immune lymphocytes (TILs) hasn’t been intensively investigated. Here we report a model-based evaluation of tumor TIL levels using DNA methylation profiles. By employing a hybrid method of stability selection and elastic net, we show that methylation array data in ten TCGA cancer types provide a strikingly accurate prediction of immune cell abundance, in particular the levels of T cells, B cells and cytotoxic cells in skin cutaneous melanoma (SKCM). The immune-informative CpG sites showed significant prognostic values, representing important candidates for further functional validation. Further, we present regression models each using only ten CpG sites to estimate the levels of infiltrated immune cell types in melanoma. To validate these models, we performed matched methylation EPIC array and RNA-seq on 30 new melanoma samples. We observed high concordance on methylation and gene expression predicted tumor immune infiltration levels in our new dataset. Our study demonstrated that DNA methylation data is a valuable resource in reliably evaluating tumor immune responses. The selected methylation panels provide candidate targets for future clinical researches. Our prediction models are easy to implement and will provide reference for future clinical practices.

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Epigenetic changes in islets of Langerhans preceding the onset of diabetes

10.2337/figshare.12794957 ◽

2020 ◽

Author(s):

Ada Admin ◽

Meriem Ouni ◽

Sophie Saussenthaler ◽

Fabian Eichelmann ◽

Markus Jähnert ◽

...

Keyword(s):

Dna Methylation ◽

Islets Of Langerhans ◽

Blood Cells ◽

Multiple Testing ◽

Liver Fat ◽

Receptor Interaction ◽

P Value ◽

Hypergeometric Test ◽

Cpg Sites ◽

Translational Approach

The identiﬁcation of individuals with a high risk of developing type 2 diabetes (T2D) is fundamental for prevention. Here, we used a translational approach and prediction criteria to identify changes in DNA methylation visible before the development of T2D. Islets of Langerhans were isolated from genetically identical 10-week-old female New Zealand Obese mice which differ in their degree of hyperglycemia and in liver fat content. The application of a semi-explorative approach identified 497 differentially expressed and methylated genes (p-value=6.42e-09, hypergeometric test) enriched in pathways linked to insulin secretion and ECM-receptor interaction. The comparison of mouse data with DNA methylation levels of incident T2D cases from the prospective EPIC-Potsdam cohort, revealed 105 genes with altered DNA methylation at 605 CpG sites which were associated with future T2D. AKAP13, TENM2, CTDSPL, PTPRN2 and PTPRS showed the strongest predictive potential (ROC-AUC values 0.62-0.73). Among the new candidates identified in blood cells, 655 CpG sites, located in 99 genes, were differentially methylated in islets of human with T2D. Utilizing correction for multiple testing detected 236 genes with an altered DNA methylation in blood cells and 201 genes in diabetic islets. Thus, the introduced translational approach identified novel putative biomarkers for early pancreatic islet aberrations preceding T2D.

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CoMeBack: DNA methylation array data analysis for co-methylated regions

Bioinformatics ◽

10.1093/bioinformatics/btaa049 ◽

2020 ◽

Vol 36 (9) ◽

pp. 2675-2683

Author(s):

Evan Gatev ◽

Nicole Gladish ◽

Sara Mostafavi ◽

Michael S Kobor

Keyword(s):

Dna Methylation ◽

Statistical Power ◽

Association Studies ◽

Supplementary Information ◽

Statistical Dependence ◽

Methylation Array ◽

Array Data ◽

Multiple Test Correction ◽

Multiple Test ◽

Cpg Sites

Abstract Motivation High-dimensional DNA methylation (DNAm) array coverage, while sparse in the context of the entire DNA methylome, still constitutes a very large number of CpG probes. The ensuing multiple-test corrections affect the statistical power to detect associations, likely contributing to prevalent limited reproducibility. Array probes measuring proximal CpG sites often have correlated levels of DNAm that may not only be biologically meaningful but also imply statistical dependence and redundancy. New methods that account for such correlations between adjacent probes may enable improved specificity, discovery and interpretation of statistical associations in DNAm array data. Results We developed a method named Co-Methylation with genomic CpG Background (CoMeBack) that estimates DNA co-methylation, defined as proximal CpG probes with correlated DNAm across individuals. CoMeBack outputs co-methylated regions (CMRs), spanning sets of array probes constructed based on all genomic CpG sites, including those not measured on the array, and without any phenotypic variable inputs. This approach can reduce the multiple-test correction burden, while enhancing the discovery and specificity of statistical associations. We constructed and validated CMRs in whole blood, using publicly available Illumina Infinium 450 K array data from over 5000 individuals. These CMRs were enriched for enhancer chromatin states, and binding site motifs for several transcription factors involved in blood physiology. We illustrated how CMR-based epigenome-wide association studies can improve discovery and reduce false positives for associations with chronological age. Availability and implementation https://bitbucket.org/flopflip/comeback. Supplementary information Supplementary data are available at Bioinformatics online.

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