scholarly journals An effective processing pipeline for harmonizing DNA methylation data from Illumina’s 450K and EPIC platforms for epidemiological studies

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Lauren A. Vanderlinden ◽  
Randi K. Johnson ◽  
Patrick M. Carry ◽  
Fran Dong ◽  
Dawn L. DeMeo ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Meta Analysis ◽  
Epidemiological Studies ◽  
Methylation Data ◽  
Data Harmonization ◽  
Technical Variability ◽  
Processing Pipeline ◽  
Novel Approach ◽  
Processing Steps ◽  
Over Time

Abstract Objective Illumina BeadChip arrays are commonly used to generate DNA methylation data for large epidemiological studies. Updates in technology over time create challenges for data harmonization within and between studies, many of which obtained data from the older 450K and newer EPIC platforms. The pre-processing pipeline for DNA methylation is not trivial, and influences the downstream analyses. Incorporating different platforms adds a new level of technical variability that has not yet been taken into account by recommended pipelines. Our study evaluated the performance of various tools on different versions of platform data harmonization at each step of pre-processing pipeline, including quality control (QC), normalization, batch effect adjustment, and genomic inflation. We illustrate our novel approach using 450K and EPIC data from the Diabetes Autoimmunity Study in the Young (DAISY) prospective cohort. Results We found normalization and probe filtering had the biggest effect on data harmonization. Employing a meta-analysis was an effective and easily executable method for accounting for platform variability. Correcting for genomic inflation also helped with harmonization. We present guidelines for studies seeking to harmonize data from the 450K and EPIC platforms, which includes the use of technical replicates for evaluating numerous pre-processing steps, and employing a meta-analysis.

scholarly journals An Effective Processing Pipeline for Harmonizing DNA Methylation Data from Illumina’s 450K and EPIC Platforms for Epidemiological Studies

2020 ◽  
Author(s):  
Lauren A Vanderlinden ◽  
Randi K Johnson ◽  
Patrick M Carry ◽  
Fran Dong ◽  
Dawn L. DeMeo ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Meta Analysis ◽  
Epidemiological Studies ◽  
Methylation Data ◽  
Data Harmonization ◽  
Technical Variability ◽  
Processing Pipeline ◽  
Novel Approach ◽  
Processing Steps ◽  
Over Time

Abstract Objective: Illumina BeadChip arrays are commonly used to generate DNA methylation data for large epidemiological studies. Updates in technology over time create challenges for data harmonization within and between studies, many of which obtained data from the older 450K and newer EPIC platforms. The pre-processing pipeline for DNA methylation is not trivial, and influences the downstream analyses. Incorporating different platforms adds a new level of technical variability that has not yet been taken into account by recommended pipelines. Our study evaluated the performance of various tools on different versions of platform data harmonization at each step of pre-processing pipeline, including quality control (QC), normalization, batch effect adjustment, and genomic inflation. We illustrate our novel approach using 450K and EPIC data from the Diabetes Autoimmunity Study in the Young (DAISY) prospective cohort. Results: We found normalization and probe filtering had the biggest effect on data harmonization. Employing a meta-analysis was an effective and easily executable method for accounting for platform variability. Correcting for genomic inflation also helped with harmonization. We present guidelines for studies seeking to harmonize data from the 450K and EPIC platforms, which includes the use of technical replicates for evaluating numerous pre-processing steps, and employing a meta-analysis.

scholarly journals Evaluation of pre-processing on the meta-analysis of DNA methylation data from the Illumina HumanMethylation450 BeadChip platform

PLoS ONE ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. e0229763 ◽  
Author(s):  
Claudia Sala ◽  
Pietro Di Lena ◽  
Danielle Fernandes Durso ◽  
Andrea Prodi ◽  
Gastone Castellani ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Meta Analysis ◽  
Methylation Data ◽  
Illumina Humanmethylation450 ◽  
Illumina Humanmethylation450 Beadchip

scholarly journals PEIS: a novel approach of tumor purity estimation by identifying information sites through integrating signal based on DNA methylation data

2019 ◽  
Vol 20 (S22) ◽  
Author(s):  
Shudong Wang ◽  
Lihua Wang ◽  
Yuanyuan Zhang ◽  
Shanchen Pang ◽  
Xinzeng Wang
Keyword(s):  
Dna Methylation ◽  
Strong Correlation ◽  
Estimation Methods ◽  
Methylation Data ◽  
Tumor Purity ◽  
Novel Approach ◽  
Highly Sensitive ◽  
Number Variation ◽  
High Consistency ◽  
Selection Of

Abstract Background Tumor purity plays an important role in understanding the pathogenic mechanism of tumors. The purity of tumor samples is highly sensitive to tumor heterogeneity. Due to Intratumoral heterogeneity of genetic and epigenetic data, it is suitable to study the purity of tumors. Among them, there are many purity estimation methods based on copy number variation, gene expression and other data, while few use DNA methylation data and often based on selected information sites. Consequently, how to choose methylation sites as information sites has an important influence on the purity estimation results. At present, the selection of information sites was often based on the differentially methylated sites that only consider the mean signal, without considering other possible signals and the strong correlation among adjacent sites. Results Considering integrating multi-signals and strong correlation among adjacent sites, we propose an approach, PEIS, to estimate the purity of tumor samples by selecting informative differential methylation sites. Application to 12 publicly available tumor datasets, it is shown that PEIS provides accurate results in the estimation of tumor purity which has a high consistency with other existing methods. Also, through comparing the results of different information sites selection methods in the evaluation of tumor purity, it shows the PEIS is superior to other methods. Conclusions A new method to estimate the purity of tumor samples is proposed. This approach integrates multi-signals of the CpG sites and the correlation between the sites. Experimental analysis shows that this method is in good agreement with other existing methods for estimating tumor purity.

scholarly journals DNA methylation meta-analysis reveals cellular alterations in psychosis and markers of treatment-resistant schizophrenia

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Eilis Hannon ◽  
Emma L Dempster ◽  
Georgina Mansell ◽  
Joe Burrage ◽  
Nick Bass ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Association Studies ◽  
Meta Analysis ◽  
Genetic Association Studies ◽  
Methylation Data ◽  
Treatment Resistant ◽  
Systematic Analysis ◽  
Factors Associated ◽  
Cell Counts ◽  
Smoking Exposure

We performed a systematic analysis of blood DNA methylation profiles from 4,483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1,048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia.

scholarly journals Epigenome-wide meta-analysis of PTSD across 10 military and civilian cohorts identifies methylation changes in AHRR

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Alicia K. Smith ◽  
◽  
Andrew Ratanatharathorn ◽  
Adam X. Maihofer ◽  
Robert K. Naviaux ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Aryl Hydrocarbon Receptor ◽  
Smoking Status ◽  
Meta Analysis ◽  
Multiple Comparisons ◽  
Immune Dysregulation ◽  
Methylation Data ◽  
Metabolomics Data ◽  
Cpg Sites ◽  
Aryl Hydrocarbon

AbstractEpigenetic differences may help to distinguish between PTSD cases and trauma-exposed controls. Here, we describe the results of the largest DNA methylation meta-analysis of PTSD to date. Ten cohorts, military and civilian, contribute blood-derived DNA methylation data from 1,896 PTSD cases and trauma-exposed controls. Four CpG sites within the aryl-hydrocarbon receptor repressor (AHRR) associate with PTSD after adjustment for multiple comparisons, with lower DNA methylation in PTSD cases relative to controls. Although AHRR methylation is known to associate with smoking, the AHRR association with PTSD is most pronounced in non-smokers, suggesting the result was independent of smoking status. Evaluation of metabolomics data reveals that AHRR methylation associated with kynurenine levels, which are lower among subjects with PTSD. This study supports epigenetic differences in those with PTSD and suggests a role for decreased kynurenine as a contributor to immune dysregulation in PTSD.

scholarly journals A meta-analysis of the associations between common variation in the PDE8B gene and thyroid hormone parameters, including assessment of longitudinal stability of associations over time and effect of thyroid hormone replacement

2011 ◽  
Vol 164 (5) ◽  
pp. 773-780 ◽  
Author(s):  
Peter N Taylor ◽  
Vijay Panicker ◽  
Adrian Sayers ◽  
Beverley Shields ◽  
Ahmed Iqbal ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Thyroid Hormone ◽  
Meta Analysis ◽  
Hormone Replacement ◽  
Epidemiological Studies ◽  
Health Study ◽  
Single Nucleotide ◽  
New Association ◽  
The Stability ◽  
Over Time

ObjectiveCommon variants in PDE8B are associated with TSH but apparently without any effect on thyroid hormone levels that is difficult to explain. Furthermore, the stability of the association has not been examined in longitudinal studies or in patients on levothyroxine (l-T4).DesignTotally, four cohorts were used (n=2557): the Busselton Health Study (thyroid function measured on two occasions), DEPTH, EFSOCH (selective cohorts), and WATTS (individuals on l-T4).MethodsMeta-analysis to clarify associations between the rs4704397 single nucleotide polymorphism in PDE8B on TSH, tri-iodothyronine (T3), and T4 levels.ResultsMeta-analysis confirmed that genetic variation in PDE8B was associated with TSH (P=1.64×10−10 0.20 s.d./allele, 95% confidence interval (CI) 0.142, 0.267) and identified a possible new association with free T4 (P=0.023, −0.07 s.d./allele, 95% CI −0.137, −0.01), no association was seen with free T3 (P=0.218). The association between PDE8B and TSH was similar in 1981 (0.14 s.d./allele, 95% CI 0.04, 0.238) and 1994 (0.20 s.d./allele, 95% CI 0.102, 0.300) and even more consistent between PDE8B and free T4 in 1981 (−0.068 s.d./allele, 95% CI −0.167, 0.031) and 1994 (−0.07 s.d./allele, 95% CI −0.170, 0.030). No associations were seen between PDE8B and thyroid hormone parameters in individuals on l-T4.ConclusionCommon genetic variation in PDE8B is associated with reciprocal changes in TSH and free T4 levels that are consistent over time and lost in individuals on l-T4. These findings identify a possible genetic marker reflecting variation in thyroid hormone output that will be of value in epidemiological studies and provides additional evidence that PDE8B is involved in TSH signaling in the thyroid.

Forecasting Interconnections in International Housing Markets: Evidence from the Dynamic Model Averaging Approach

2020 ◽  
Vol 42 (1) ◽  
pp. 37-103
Author(s):  
Hardik A. Marfatia
Keyword(s):  
Dynamic Model ◽  
Model Averaging ◽  
Housing Markets ◽  
The United States ◽  
Forecasting Model ◽  
Change Over Time ◽  
The United Kingdom ◽  
Novel Approach ◽  
Dynamic Model Averaging ◽  
Over Time

In this paper, I undertake a novel approach to uncover the forecasting interconnections in the international housing markets. Using a dynamic model averaging framework that allows both the coefficients and the entire forecasting model to dynamically change over time, I uncover the intertwined forecasting relationships in 23 leading international housing markets. The evidence suggests significant forecasting interconnections in these markets. However, no country holds a constant forecasting advantage, including the United States and the United Kingdom, although the U.S. housing market's predictive power has increased over time. Evidence also suggests that allowing the forecasting model to change is more important than allowing the coefficients to change over time.

scholarly journals P34 Characteristics, diagnosis and management of Cushing’s disease - A systematic review and meta-analysis

BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
Chan Hee Koh ◽  
Danyal Z Khan ◽  
Ronneil Digpal ◽  
Hugo Layard Horsfall ◽  
Hani J Marcus ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Cushing’S Disease ◽  
Meta Analysis ◽  
A Priori ◽  
Pituitary Surgery ◽  
Serum Cortisol ◽  
Cushing's Disease ◽  
Diagnosis And Management ◽  
Over Time

Abstract Introduction The clinical practice and research in the diagnosis and management of Cushing’s disease remains heterogeneous and challenging to this day. We sought to establish the characteristics of Cushing’s disease, and the trends in diagnosis, management and reporting in this field. Methods Searches of PubMed and Embase were conducted. Study protocol was registered a-priori. Random-effects analyses were conducted to establish numerical estimates. Results Our screening returned 159 papers. The average age of adult patients with Cushing’s disease was 39.3, and 13.6 for children. The male:female ratio was 1:3. 8% of patients had undergone previous transsphenoidal resection. The ratio of macroadenomas: microadenomas:imaging-undetectable adenomas was 18:53:29. The most commonly reported preoperative biochemical investigations were serum cortisol (average 26.4µg/dL) and ACTH (77.5pg/dL). Postoperative cortisol was most frequently used to define remission (74.8%), most commonly with threshold of 5µg/dL (44.8%). Average remission rates were 77.8% with recurrence rate of 13.9%. Median follow-up was 38 months. Majority of papers reported age (81.9%) and sex (79.4%). Only 56.6% reported whether their patients had previous pituitary surgery. 45.3% reported whether their adenomas were macroadenoma, microadenoma or undetectable. Only 24.1% reported preoperative cortisol, and this did not improve over time. 60.4% reported numerical thresholds for cortisol in defining remission, and this improved significantly over time (p = 0.004). Visual inspection of bubbleplots showed increasing preference for threshold of 5µg/dL. 70.4% reported the length of follow up. Conclusion We quantified the characteristics of Cushing’s disease, and analysed the trends in investigation and reporting. This review may help to inform future efforts in forming guidelines for research and clinical practice.

scholarly journals Profile of copper-associated DNA methylation and its association with incident acute coronary syndrome

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Pinpin Long ◽  
Qiuhong Wang ◽  
Yizhi Zhang ◽  
Xiaoyan Zhu ◽  
Kuai Yu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Acute Coronary Syndrome ◽  
Methylation Level ◽  
Meta Analysis ◽  
Regulation Of Gene Expression ◽  
Density Lipoprotein ◽  
Blood Leukocytes ◽  
Coronary Syndrome ◽  
A Genome ◽  
Increased Risk

Abstract Background Acute coronary syndrome (ACS) is a cardiac emergency with high mortality. Exposure to high copper (Cu) concentration has been linked to ACS. However, whether DNA methylation contributes to the association between Cu and ACS is unclear. Methods We measured methylation level at > 485,000 cytosine-phosphoguanine sites (CpGs) of blood leukocytes using Human Methylation 450 Bead Chip and conducted a genome-wide meta-analysis of plasma Cu in a total of 1243 Chinese individuals. For plasma Cu-related CpGs, we evaluated their associations with the expression of nearby genes as well as major cardiovascular risk factors. Furthermore, we examined their longitudinal associations with incident ACS in the nested case-control study. Results We identified four novel Cu-associated CpGs (cg20995564, cg18608055, cg26470501 and cg05825244) within a 5% false discovery rate (FDR). DNA methylation level of cg18608055, cg26470501, and cg05825244 also showed significant correlations with expressions of SBNO2, BCL3, and EBF4 gene, respectively. Higher DNA methylation level at cg05825244 locus was associated with lower high-density lipoprotein cholesterol level and higher C-reactive protein level. Furthermore, we demonstrated that higher cg05825244 methylation level was associated with increased risk of ACS (odds ratio [OR], 1.23; 95% CI 1.02–1.48; P = 0.03). Conclusions We identified novel DNA methylation alterations associated with plasma Cu in Chinese populations and linked these loci to risk of ACS, providing new insights into the regulation of gene expression by Cu-related DNA methylation and suggesting a role for DNA methylation in the association between copper and ACS.

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