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2021 ◽  
Vol 12 ◽  
Author(s):  
María Marcela Velásquez ◽  
Yvonne Gómez-Maquet ◽  
Eugenio Ferro ◽  
Wilmer Cárdenas ◽  
Silvia González-Nieves ◽  
...  

Major Depression is a complex disorder with a growing incidence worldwide and multiple variables have been associated with its etiology. Nonetheless, its diagnosis is continually changing and the need to understand it from a multidimensional perspective is clear. The purpose of this study was to identify risk factors for depression in a case-control study with 100 depressive inpatients and 87 healthy controls. A multivariate logistic regression analysis was performed including psychosocial factors, cognitive maladaptive schema domains, and specific epigenetic marks (BDNF methylation levels at five CpG sites in promoter IV). A family history of depression, the cognitive schemas of impaired autonomy/performance, impaired limits, other-directedness, and the methylation level of a specific CpG site were identified as predictors. Interestingly, we found a mediating effect of those cognitive schemas in the relationship between childhood maltreatment and depression. Also, we found that depressive patients exhibited hypomethylation in a CpG site of BDNF promoter IV, which adds to the current discussion about the role of methylation in depression. We highlight that determining the methylation of a specific region of a single gene offers the possibility of accessing a highly informative an easily measurable variable, which represents benefits for diagnosis. Following complete replication and validation on larger samples, models like ours could be applicable as additional diagnostic tools in the clinical context.


2021 ◽  
Author(s):  
James R. Occean ◽  
Agaz H. Wani ◽  
Janelle Donglasan ◽  
Allison E. Aiello ◽  
Sandro Galea ◽  
...  

The mechanisms through which exposure to differing trauma types become biologically embedded to shape the risk for subsequent post-traumatic stress disorder (PTSD) is unclear. DNA methylation (5-mC), particularly in stress-relevant genes, may play a role in this relationship. We conducted path analysis using generalized structural equation modeling to investigate whether blood-derived 5-mC in Nuclear Factor of Activated T Cells 1 (NFATC1) mediated the prospective association between each of five different trauma types (assaultive violence, other injury or shocking experience, learning of trauma to loved one, sudden, unexpected death of a close friend or relative, and other) and lifetime PTSD. All five trauma types were significantly associated with reduced methylation at NFATC1 CpG site, cg17057218. Three of the five trauma types were significantly associated with increased methylation at NFATC1 CpG site, cg22324981. Moreover, methylation at cg17057218 significantly mediated 23-34% of the total effect for three of the five trauma types, while methylation at cg22324981 mediated 36-53% of the total effect for two of the five trauma types. These CpG sites were differentially associated with transcription factor binding sites and chromatin state signatures. NFATC1 5-mC may be a potential mechanism in the relationship between some trauma types and prospective risk for PTSD.


2021 ◽  
Author(s):  
Christopher Adanty ◽  
Ahmad Shakeri ◽  
John Strauss ◽  
Ariel Graff ◽  
Vincenzo De Luca

Aim: To explore possible differences in genome-wide methylation between schizophrenia patients who consume various antipsychotics. Methods: We compared DNA methylation in leukocytes between the following cohorts: clozapine (n = 19) versus risperidone (n = 19), clozapine (n = 12) versus olanzapine (n = 12), clozapine (n = 9) versus quetiapine (n = 9) and clozapine (n = 33) versus healthy controls (n = 33). Subjects were matched for age, sex, ethnicity, smoking status and leukocyte proportions. Results: No single CpG site reached genome-wide significance for clozapine versus risperidone/olanzapine/quetiapine. For clozapine versus quetiapine, one significantly differentially methylated region was found – ch5: 176797920–176798049 (fwer = 0.075). Clozapine versus healthy controls yielded thousands of significantly differentially methylated CpG sites. Conclusions: Establishing antipsychotic induced genome-wide methylation patterns will further elucidate the biological and clinical effects of antipsychotic administration.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2376-2376
Author(s):  
Anilkumar Gopalakrishnapillai ◽  
Erin Lynn Crowgey ◽  
Adam Marsh ◽  
E. Anders Kolb ◽  
Sonali P. Barwe

Abstract Pediatric acute myeloid leukemia (AML) patients possessing rearrangement of the KMT2A (previously known as MLL) gene on 11q23 constitute a subclass with a particularly poor prognosis. The five-year survival rate for these patients is only about 44% due to poor response to conventional chemotherapy and frequent early relapse. Aberrant epigenetic modifications play an important role in leukemogenesis in KMT2A-rearranged leukemia. Accordingly, several epigenome modifying drugs have been tested in preclinical studies of KMT2A-rearranged leukemia. Acknowledging the co-regulatory effects of DNA methylation and histone modifications in determining chromatin structure and governing gene expression, we combined DNA hypomethylating agent azacitidine with histone deacetylase inhibitor panobinostat in the hopes of achieving greater efficacy. We showed that this epigenetic drug combination was more efficacious than single agents using cell line derived xenograft models of pediatric AML (Gopalakrishnapillai et al., Leuk Res, 2017). We evaluated the efficacy of this epigenetic drug combination in patient-derived xenograft models of KMT2A rearranged pediatric AML and observed that similar to MV4;11 model, this combination induced complete remission in NTPL-146 model with KMT2A-MLLT1 fusion (Fig. 1A, P<0.001). We analyzed the methylome of AML cells harvested from xenografted mice treated with control, azacitidine, panobinostat, or a combination of the two. Methylation sensitive restriction endonucleases were utilized to fragment genomic DNA prior to library construction for next generation sequencing. GenPro software platform designed for highly quantitative, sensitive, and low error-rate detection of methylation at individual CpG sites was used. Methylation patterns between treatment groups were discriminated using an ordinate analysis technique of non-metric multidimensional scaling (NMDS) (Fig. 1B). CpG methylation profiles were compared among the four groups analyzed to isolate patterns conserved within groups while also differing between groups. The first two component axes were plotted to locate the individual sample points in a 2D plane. Samples from distinct PDX models undergoing similar treatment clustered together. The panobinostat-treated samples showed minimal differences compared to the control, while the azacitidine-treated samples clustered away. Interestingly, the samples treated with the combination, did not overlap with either treatment, indicating that although panobinostat alone showed minimal impact on methylation patterns, panobinostat together with azacitidine produced a distinct methylation pattern. Venn intersection sets of statistically significant differentially methylated CpG sites in the 3-way analyses derived from the control group comparisons showed 2086 CpG sites exclusively altered in the combination treatment (Fig. 1C). In order to determine the effect of the combination treatment on global methylation, the differences in methylation load (dML) per each CpG site between control and the combination treatment were summed across 1MB genome intervals and the distribution of these dML was plotted (Fig. 1D). There was a strong shift in methylation signal, with the majority of the intervals being hypomethylated in the treatment group compared to the control. Although global hypomethylation was observed in combination treatment, the most statistically significant CpG sites were hypermethylated in the combination treatment compared to the control as seen in the volcano plot in which log fold-change was plotted against the p-value (Fig. 1E). Circular ideogram presented with a mean subtraction of CpG methylation scores to calculate a summation methylation load score across chromosomal domains (Fig. 1F). The correlative association between top CpG sites is shown as arcs tracking the highest correlation for each CpG site. Gene labels indicate the positions of the top 60 CpG sites, with green and red indicating higher methylation in control and in combination treatment respectively. In conclusion, we have identified differential methylation patterns following in vivo treatment of KMT2A rearranged pediatric AML xenograft models with azacitidine and panobinostat combination compared to azacitidine alone. These methylation changes are likely to influence the increased survival seen in mice receiving combination treatment. Figure 1 Figure 1. Disclosures Gopalakrishnapillai: Geron: Research Funding. Marsh: Genome Profiling LLC: Current Employment. Barwe: Prelude Therapeutics: Research Funding.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaolei Wang ◽  
Jin Huang ◽  
Yixiang Zheng ◽  
Sisi Long ◽  
Huijun Lin ◽  
...  

AbstractGenome-wide DNA methylation profiling have been used to find maternal CpG sites related to the occurrence of gestational diabetes mellitus (GDM). However, none of these differential sites found has been verified in a larger sample. Here, our aim was to evaluate whether first trimester changes in target CpG sites in the peripheral blood of pregnancy women predict subsequent development of GDM. This nested case–control study was based upon an early pregnancy follow-up cohort (ChiCTR1900020652). Target CpG sites were extracted from related published literature and bioinformatics analysis. The DNA methylation levels at 337 CpG sites of 80 GDM cases and 80 matched healthy controls during the early pregnancy (10–15 weeks) were assessed using MethylTarget sequencing. The best cut-off level for methylation of CpG site was determined using the generated ROC curve. The independent effect of CpG site methylation status on GDM was analyzed using conditional logistic regression. Methylation levels at 6 CpG sites were significantly higher in the GDM group than in controls, whereas those at another 6 CpG sites were significantly lower (FDR < 0.05). The area under the ROC curve at each methylation level of the significant CpG sites ranged between 0.593 and 0.650 for the occurrence of GDM. After adjusting for possible confounders, the hypermethylation status of CpG site 68167324 (OR = 3.168, 1.038–9.666) and 24837915 (OR = 5.232, 1.659–16.506) was identified as more strongly associated with GDM; meanwhile, the hypermethylation of CpG site 157130156 (OR = 0.361, 0.135–0.966) and 89438648 (OR = 0.206, 0.065–0.655) might indicate lower risk of GDM. The methylation status of target CpG sites in the peripheral blood of pregnant women during the first trimester may be associated with GDM pathogenesis, and has potential as a predictor of GDM.


Author(s):  
Jiamin Guo ◽  
Andrew Paterson ◽  
Delnaz Roshandel

Introduction & Objective: Cumulated advanced glycation end products (AGEs) in the bloodstream and tissues contribute to the pathogenesis of diabetes complications. The skin intrinsic fluorescence (SIF) is a non-invasive measurement of dermal AGEs level using spectrometer, and it can be used as a biomarker in AGEs-related diseases. Previously, specific epigenomic factor has been found to be associated with haemoglobin A1c (HbA1c). HbA1c is a type of glycated haemoglobin – the HbA1c test measures the average glycemic control over the period of 3 months. However, the effect of epigenetic factors on the level of AGEs in the skin remains unknown. We hypothesize that some cytosine-guanine dinucleotides (CpGs) are associated with SIF. An epigenome-wide associations study (EWAS) was performed to identify CpG sites associated with SIF in people with type 1 diabetes. Methods: 499 people with type 1 diabetes that have both methylation and SIF from the Diabetes Control Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study were included. We fit linear regression models for SIF with each CpG site one at a time. The epigenome-wide significance level (p=5e-8) was applied. Then the result is compared with the null hypothesis where CpGs are not associated with SIF to check the inflation. In order to check the assumptions of the multiple linear models at a single CpG, we use diagnostic plots. Results: We did not identify a specific CpG that is significantly associated with neither skin intrinsic fluorescence 1 (SIF1) nor skin intrinsic fluorescence 12 (SIF 12).The CpG site with strongest effect is cg06538183 ([SE] -2.73 [0.61], p = 8.72e-6) on SIF1 and cg12871967 ([SE] 2.52, 0.53, p = 2.71e-6) on SIF12. Conclusion: We did not find any specific CpG that was significantly associated with either SIF 1 or SIF12. In general, the result suggests that DNA methylation does not impact the accumulation of AGEs in skin cells. DNA methylation data has a unique pattern of distribution that drives the non-uniform distribution of the p-values. The group of 275,301 CpGs that have means above the median and standard deviations below the median has the expected uniform p-value distribution.


2021 ◽  
Vol 17 (9) ◽  
pp. e1009327
Author(s):  
Gergely Palla ◽  
Péter Pollner ◽  
Judit Börcsök ◽  
András Major ◽  
Béla Molnár ◽  
...  

DNA methylation provides one of the most widely studied biomarkers of ageing. Since the methylation of CpG dinucleotides function as switches in cellular mechanisms, it is plausible to assume that by proper adjustment of these switches age may be tuned. Though, adjusting hundreds of CpG methylation levels coherently may never be feasible and changing just a few positions may lead to biologically unstable state. A prominent example of methylation-based age estimators is provided by Horvath’s clock, based on 353 CpG dinucleotides, showing a high correlation (not necessarily causation) with chronological age across multiple tissue types. On this small subset of CpG dinucleotides we demonstrate how the adjustment of one methylation level leads to a cascade of changes at other sites. Among the studied subset, we locate the most important CpGs (and related genes) that may have a large influence on the rest of the sub-system. According to our analysis, the structure of this network is way more hierarchical compared to what one would expect based on ensembles of uncorrelated connections. Therefore, only a handful of CpGs is enough to modify the system towards a desired state. When propagation of the change over the network is taken into account, the resulting modification in the predicted age can be significantly larger compared to the effect of isolated CpG perturbations. By adjusting the most influential single CpG site and following the propagation of methylation level changes we can reach up to 5.74 years in virtual age reduction, significantly larger than without taking into account of the network control. Extending our approach to the whole methylation network may identify key nodes that have controller role in the ageing process.


2021 ◽  
Vol 331 ◽  
pp. e99-e100
Author(s):  
N.P. Babushkina ◽  
A.V. Markov ◽  
I.A. Goncharova ◽  
R.R. Salahov ◽  
I.A. Koroleva ◽  
...  
Keyword(s):  

Medicine ◽  
2021 ◽  
Vol 100 (29) ◽  
pp. e26648
Author(s):  
Xiang Zhang ◽  
Xuecheng Pang ◽  
Yue Huang ◽  
Sumin Qian

2021 ◽  
Author(s):  
Brooke J. Smith ◽  
Alexandre A Lussier ◽  
Janine Cerutti ◽  
Daniel J. Schaid ◽  
Andrew J. Simpkin ◽  
...  

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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