scholarly journals Cell-Type Specific Changes in DNA Methylation of SNCA Intron 1 in Synucleinopathy Brains

2021 ◽  
Vol 15 ◽  
Author(s):  
Jeffrey Gu ◽  
Julio Barrera ◽  
Young Yun ◽  
Susan K. Murphy ◽  
Thomas G. Beach ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Frontal Cortex ◽  
Cpg Island ◽  
Cell Type ◽  
Neuronal Nuclei ◽  
Intron 1 ◽  
Significant Difference ◽  
Dependent Cell ◽  
A Cell ◽  
Cell Type Specific

Parkinson’s disease (PD) and dementia with Lewy body (DLB) are the most common synucleinopathies. SNCA gene is a major genetic risk factor for these diseases group, and dysregulation of its expression has been implicated in the genetic etiologies of several synucleinopathies. DNA methylation at CpG island (CGI) within SNCA intron 1 has been suggested as a regulatory mechanism of SNCA expression, and changes in methylation levels at this region were associated with PD and DLB. However, the role of DNA methylation in the regulation of SNCA expression in a cell-type specific manner and its contribution to the pathogenesis of PD and DLB remain poorly understood, and the data are conflicting. Here, we employed a bisulfite pyrosequencing technique to profile the DNA methylation across SNCA intron 1 CGI in PD and DLB compared to age- and sex-matched normal control subjects. We analyzed homogenates of bulk post-mortem frozen frontal cortex samples and a subset of neuronal and glia nuclei sorted by the fluorescence-activated nuclei sorting (FANS) method. Bulk brain tissues showed no significant difference in the overall DNA methylation across SNCA intron 1 CGI region between the neuropathological groups. Sorted neuronal nuclei from PD frontal cortex showed significant lower levels of DNA methylation at this region compared to normal controls, but no differences between DLB and control, while sorted glia nuclei exhibited trends of decreased overall DNA methylation in DLB only. In conclusion, our data suggested disease-dependent cell-type specific differential DNA methylation within SNCA intron 1 CGI. These changes may affect SNCA dysregulation that presumably mediates disease-specific risk. Our results can be translated into the development of the SNCA intron 1 CGI region as an attractive therapeutics target for gene therapy in patients who suffer from synucleinopathies due to SNCA dysregulation.

scholarly journals Sex dependent glial-specific changes in the chromatin accessibility landscape in late-onset Alzheimer’s disease brains

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Julio Barrera ◽  
Lingyun Song ◽  
Julia E. Gamache ◽  
Melanie E. Garrett ◽  
Alexias Safi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Late Onset ◽  
Unmet Need ◽  
Chromatin Accessibility ◽  
Cell Type ◽  
Neuronal Nuclei ◽  
Dependent Cell ◽  
A Cell ◽  
Cell Type Specific

Abstract Background In the post-GWAS era, there is an unmet need to decode the underpinning genetic etiologies of late-onset Alzheimer’s disease (LOAD) and translate the associations to causation. Methods We conducted ATAC-seq profiling using NeuN sorted-nuclei from 40 frozen brain tissues to determine LOAD-specific changes in chromatin accessibility landscape in a cell-type specific manner. Results We identified 211 LOAD-specific differential chromatin accessibility sites in neuronal-nuclei, four of which overlapped with LOAD-GWAS regions (±100 kb of SNP). While the non-neuronal nuclei did not show LOAD-specific differences, stratification by sex identified 842 LOAD-specific chromatin accessibility sites in females. Seven of these sex-dependent sites in the non-neuronal samples overlapped LOAD-GWAS regions including APOE. LOAD loci were functionally validated using single-nuclei RNA-seq datasets. Conclusions Using brain sorted-nuclei enabled the identification of sex-dependent cell type-specific LOAD alterations in chromatin structure. These findings enhance the interpretation of LOAD-GWAS discoveries, provide potential pathomechanisms, and suggest novel LOAD-loci. Graphical Abstract

scholarly journals Sex dependent glial-specific changes in the chromatin accessibility landscape in late-onset Alzheimer′s disease brains

2021 ◽  
Author(s):  
Julio A Barrera ◽  
Lingyun Song ◽  
Alexias Safi ◽  
Young Jun Yun ◽  
Melanie E Garrett ◽  
...  
Keyword(s):  
Late Onset ◽  
Unmet Need ◽  
Chromatin Accessibility ◽  
Rna Seq ◽  
Cell Type ◽  
Neuronal Nuclei ◽  
Dependent Cell ◽  
A Cell ◽  
Cell Type Specific ◽  
Load Risk

In the post-GWAS era, there is an unmet need to decode the underpinning genetic etiologies of late-onset Alzheimer′s disease (LOAD) and translate the associations to causation. Toward that goal, we conducted ATAC-seq profiling using neuronal nuclear protein (NeuN) sorted-nuclei from 40 frozen brain tissues to determine LOAD-specific changes in chromatin accessibility landscape in a cell-type specific manner. We identified 211 LOAD-specific differential chromatin accessibility sites in neuronal-nuclei, four of which overlapped with LOAD-GWAS regions (±100kb of SNP). While the non-neuronal nuclei did not show LOAD-specific differences, stratification by sex identified 842 LOAD-specific chromatin accessibility sites in females. Seven of these sex-dependent sites in the non-neuronal samples overlapped LOAD-GWAS regions including APOE. LOAD loci were functionally validated using single-nuclei RNA-seq datasets. In conclusion, using brain sorted-nuclei enabled the identification of sex-dependent cell type-specific LOAD alterations in chromatin structure. These findings enhance the interpretation of LOAD-GWAS discoveries, provide potential pathomechanisms, and suggest novel LOAD-loci. Furthermore, our results convey mechanistic insights into sex differences in LOAD risk and clinicopathology.

scholarly journals Testing cell-type-specific mediation effects in genome-wide epigenetic studies

2020 ◽  
Author(s):  
Xiangyu Luo ◽  
Joel Schwartz ◽  
Andrea Baccarelli ◽  
Zhonghua Liu
Keyword(s):  
Dna Methylation ◽  
Mediation Analysis ◽  
Methylation Data ◽  
Cell Type ◽  
Multiple Testing Procedure ◽  
Mediation Effects ◽  
Cpg Sites ◽  
Genome Wide ◽  
A Cell ◽  
Cell Type Specific

Abstract Epigenome-wide mediation analysis aims to identify DNA methylation CpG sites that mediate the causal effects of genetic/environmental exposures on health outcomes. However, DNA methylations in the peripheral blood tissues are usually measured at the bulk level based on a heterogeneous population of white blood cells. Using the bulk level DNA methylation data in mediation analysis might cause confounding bias and reduce study power. Therefore, it is crucial to get fine-grained results by detecting mediation CpG sites in a cell-type-specific way. However, there is a lack of methods and software to achieve this goal. We propose a novel method (Mediation In a Cell-type-Specific fashion, MICS) to identify cell-type-specific mediation effects in genome-wide epigenetic studies using only the bulk-level DNA methylation data. MICS follows the standard mediation analysis paradigm and consists of three key steps. In step1, we assess the exposure-mediator association for each cell type; in step 2, we assess the mediator-outcome association for each cell type; in step 3, we combine the cell-type-specific exposure-mediator and mediator-outcome associations using a multiple testing procedure named MultiMed [Sampson JN, Boca SM, Moore SC, et al. FWER and FDR control when testing multiple mediators. Bioinformatics 2018;34:2418–24] to identify significant CpGs with cell-type-specific mediation effects. We conduct simulation studies to demonstrate that our method has correct FDR control. We also apply the MICS procedure to the Normative Aging Study and identify nine DNA methylation CpG sites in the lymphocytes that might mediate the effect of cigarette smoking on the lung function.

scholarly journals A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Chenglong You ◽  
Sijie Wu ◽  
Shijie C. Zheng ◽  
Tianyu Zhu ◽  
Han Jing ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Whole Blood ◽  
Immune Cell ◽  
Association Studies ◽  
Meta Analysis ◽  
Epigenetic Alterations ◽  
Cell Type ◽  
Hypersensitive Sites ◽  
A Cell ◽  
Cell Type Specific

Abstract Highly reproducible smoking-associated DNA methylation changes in whole blood have been reported by many Epigenome-Wide-Association Studies (EWAS). These epigenetic alterations could have important implications for understanding and predicting the risk of smoking-related diseases. To this end, it is important to establish if these DNA methylation changes happen in all blood cell subtypes or if they are cell-type specific. Here, we apply a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven large EWAS. We find that most of the highly reproducible smoking-associated hypomethylation signatures are more prominent in the myeloid lineage. A meta-analysis further identifies a myeloid-specific smoking-associated hypermethylation signature enriched for DNase Hypersensitive Sites in acute myeloid leukemia. These results may guide the design of future smoking EWAS and have important implications for our understanding of how smoking affects immune-cell subtypes and how this may influence the risk of smoking related diseases.

IFIH1-deficiency results in a cell-type specific alteration of autophagic activity in response to S. typhimurium

2017 ◽  
Vol 55 (05) ◽  
pp. e28-e56
Author(s):  
S Macheiner ◽  
R Gerner ◽  
A Pfister ◽  
A Moschen ◽  
H Tilg
Keyword(s):  
Cell Type ◽  
A Cell ◽  
Cell Type Specific ◽  
Autophagic Activity ◽  
Specific Alteration

scholarly journals A cell type‐specific expression map of NCoR1 and SMRT transcriptional co‐repressors in the mouse brain

2020 ◽  
Vol 528 (13) ◽  
pp. 2218-2238 ◽  
Author(s):  
Attilio Iemolo ◽  
Patricia Montilla‐Perez ◽  
I‐Chi Lai ◽  
Yinuo Meng ◽  
Syreeta Nolan ◽  
...  
Keyword(s):  
Mouse Brain ◽  
Cell Type ◽  
Specific Expression ◽  
Cell Type Specific Expression ◽  
A Cell ◽  
Cell Type Specific

scholarly journals EMeth: An EM algorithm for cell type decomposition based on DNA methylation data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hanyu Zhang ◽  
Ruoyi Cai ◽  
James Dai ◽  
Wei Sun
Keyword(s):  
Dna Methylation ◽  
Tumor Cells ◽  
T Regulatory Cells ◽  
Simulated Data ◽  
Cell Types ◽  
Computational Method ◽  
Methylation Data ◽  
Cell Type ◽  
A Cell ◽  
Type Decomposition

AbstractWe introduce a new computational method named EMeth to estimate cell type proportions using DNA methylation data. EMeth is a reference-based method that requires cell type-specific DNA methylation data from relevant cell types. EMeth improves on the existing reference-based methods by detecting the CpGs whose DNA methylation are inconsistent with the deconvolution model and reducing their contributions to cell type decomposition. Another novel feature of EMeth is that it allows a cell type with known proportions but unknown reference and estimates its methylation. This is motivated by the case of studying methylation in tumor cells while bulk tumor samples include tumor cells as well as other cell types such as infiltrating immune cells, and tumor cell proportion can be estimated by copy number data. We demonstrate that EMeth delivers more accurate estimates of cell type proportions than several other methods using simulated data and in silico mixtures. Applications in cancer studies show that the proportions of T regulatory cells estimated by DNA methylation have expected associations with mutation load and survival time, while the estimates from gene expression miss such associations.

scholarly journals Cell type‐specific DNA methylation analysis of the prefrontal cortex of patients with schizophrenia

2021 ◽  
Author(s):  
Junko Ueda ◽  
Miki Bundo ◽  
Yutaka Nakachi ◽  
Kiyoto Kasai ◽  
Tadafumi Kato ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Prefrontal Cortex ◽  
Cell Type ◽  
Methylation Analysis ◽  
Cell Type Specific ◽  
Dna Methylation Analysis

Gene therapy can target mutations such as BRAF, which have been shown to make tumors more susceptible to autophagy suppression

2021 ◽  
Author(s):  
Moataz Dowaidar
Keyword(s):  
Signaling Pathways ◽  
Chemotherapy Resistance ◽  
Effective Strategy ◽  
Cell Type ◽  
Normal Cells ◽  
A Cell ◽  
Cell Type Specific ◽  
Catabolic Process ◽  
Specific Impact

Autophagy is a double-edged sword in cancer, and numerous aspects should be taken into account before deciding on the most effective strategy to target the process. The fact that several clinical studies are now ongoing does not mean that the patient group that may benefit from autophagy-targeting medicines has been identified. Autophagy inhibitors that are more potent and specialized, as well as autophagy indicators, are also desperately required. The fact that these inhibitors only work against tumors that rely on autophagy for survival (RAS mutants) makes it difficult to distinguish them from tumors that continue to develop even when autophagy is absent. Furthermore, mutations such as BRAF have been shown to make tumors more susceptible to autophagy suppression, suggesting that targeting such tumours may be a viable strategy for overcoming their chemotherapy resistance. In the meantime, we are unable to identify if autophagy regulation works in vivo or whether it selectively targets a disease while inflicting injury to other healthy organs and tissues. A cell-type-specific impact appears to be observed with such therapy. As a result, it is just as important to consider the differences between tumors that originate in different organs as it is to consider the signaling pathways that are similar across them. For a therapy or cure to be effective, the proposed intervention must be tailored to the specific needs of each patient.Over the last several years, a growing amount of data has implicated autophagy in a variety of disorders, including cancer. In normal cells, this catabolic process is also required for cell survival and homeostasis. Despite the fact that medications targeting intermediates in the autophagy signaling pathway are being created and evaluated at both the preclinical and clinical levels, given the complicated function of autophagy in cancer, we still have a long way to go in terms of establishing an effective therapeutic approach. This article discusses current tactics for exploiting cancer cells' autophagy dependency, as well as obstacles in the area. We believe that the unanswered concerns raised in this work will stimulate researchers to investigate previously unknown connections between autophagy and other signaling pathways, which might lead to the development of novel, highly specialized autophagy therapies.

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