Guidance for the design and analysis of cell-type specific epigenetic epidemiology studies. DOI Creative Commons
Emma Walker, Emma Dempster, Alice Franklin

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 8, 2024

Abstract Recent studies on the role of epigenetics in disease have focused DNA methylation profiled bulk tissues limiting detection cell-type affected by related changes. Advances isolating homogeneous populations cells now make it possible to identify differences associated with specific cell-types. Critically, these datasets will require a bespoke analytical framework that can characterise whether difference affects multiple or is particular cell-type. We take advantage large set profiles (n = 751) obtained from five different purified cell isolated human prefrontal cortex samples and evaluate effects study design, data preprocessing statistical analysis for cell-specific studies, particularly scenarios where types are included. describe novel quality control metrics confirm successful isolation populations, which when included standard pipelines provide confidence dataset. Our power calculations show substantial gains detecting differentially methylated positions some compared tissue analyses, countering concerns regarding feasibility generating enough sample sizes informative epidemiological studies. In simulation study, we evaluated regression models finding this choice impacts robustness results. These findings informed our proposed two-stage association analyses. Overall, results guidance EWAS, establishing standards design analysis, while showcasing potential analyses reveal links between epigenetic dysregulation disease.

Language: Английский

Brain cell-type shifts in Alzheimer’s disease, autism, and schizophrenia interrogated using methylomics and genetics DOI Creative Commons
Chloe X. Yap, Daniel Vo,

Matthew G. Heffel

et al.

Science Advances, Journal Year: 2024, Volume and Issue: 10(21)

Published: May 23, 2024

Few neuropsychiatric disorders have replicable biomarkers, prompting high-resolution and large-scale molecular studies. However, we still lack consensus on a more foundational question: whether quantitative shifts in cell types-the functional unit of life-contribute to disorders. Leveraging advances human brain single-cell methylomics, deconvolve seven major types using bulk DNA methylation profiling across 1270 postmortem brains, including from individuals diagnosed with Alzheimer's disease, schizophrenia, autism. We observe replicate cell-type compositional for disease (endothelial loss), autism (increased microglia), schizophrenia (decreased oligodendrocytes), find age- sex-related changes. Multiple layers evidence indicate that endothelial loss contributes comparable effect size

Language: Английский

Citations

8
Captopril attenuates oxidative stress and neuroinflammation implicated in cisplatin-induced cognitive deficits in rats DOI Creative Commons

Fatma Mostafa,

Eman M. Mantawy,

Riham S. Said

et al.

Psychopharmacology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 14, 2025

Language: Английский

Citations

0
HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data DOI Creative Commons
Youshu Cheng, Biao Cai, Hongyu Li

et al.

Genome biology, Journal Year: 2024, Volume and Issue: 25(1)

Published: Oct. 15, 2024

Methylation quantitative trait loci (meQTLs) quantify the effects of genetic variants on DNA methylation levels. However, most published studies utilize bulk datasets composed different cell types and limit our understanding cell-type-specific regulation. We propose a hierarchical Bayesian interaction (HBI) model to infer meQTLs, which integrates large-scale data small-scale data. Through simulations, we show that HBI enhances estimation meQTLs. In real analyses, demonstrate can further improve functional annotation identify biologically relevant for complex traits.

Language: Английский

Citations

1
DNA methylation studies in Parkinson’s disease DOI
Lasse Pihlstrøm

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 135 - 151

Published: Oct. 1, 2024

Citations

0
Examining epigenetic aging in the post-mortem brain in attention deficit hyperactivity disorder DOI Creative Commons

Gauri G. Shastri,

Gustavo Sudre,

Kwangmi Ahn

et al.

Frontiers in Genetics, Journal Year: 2024, Volume and Issue: 15

Published: Oct. 8, 2024

Mathematical algorithms known as “epigenetic clocks” use methylation values at a set of CpG sites to estimate the biological age an individual in tissue-specific manner. These clocks have demonstrated both acceleration and delays epigenetic aging multiple neuropsychiatric conditions, including schizophrenia neurodevelopmental disorders such autism spectrum disorder. However, no study date has examined ADHD despite its status one most prevalent with 1 9 children having ever received diagnosis US. Only handful studies brain tissue from none focused on ADHD, obvious relevance pathogenesis. Thus, here we asked if post-mortem those lifetime histories would show accelerated or delayed age, been found for other conditions. We applied four different individuals unaffected controls cortical (anterior cingulate cortex, N = 55) striatal (caudate, 56) tissue, well peripheral blood (N 84) saliva 112). After determining which clock performed best each was associated altered corticostriatal tissues. that range accurately predicted chronological all also not significantly differential aging, neither postmortem ACC caudate, nor findings held when accounting comorbid psychiatric diagnoses, substance use, stimulant medication. this find evidence regions tissue. consider reasons unexpected finding, limited sampling regions, studied, possibility processes accelerate may be counteracted by developmental delay posited some models ADHD.

Language: Английский

Citations

0
Guidance for the design and analysis of cell-type specific epigenetic epidemiology studies. DOI Creative Commons
Emma Walker, Emma Dempster, Alice Franklin

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 8, 2024

Abstract Recent studies on the role of epigenetics in disease have focused DNA methylation profiled bulk tissues limiting detection cell-type affected by related changes. Advances isolating homogeneous populations cells now make it possible to identify differences associated with specific cell-types. Critically, these datasets will require a bespoke analytical framework that can characterise whether difference affects multiple or is particular cell-type. We take advantage large set profiles (n = 751) obtained from five different purified cell isolated human prefrontal cortex samples and evaluate effects study design, data preprocessing statistical analysis for cell-specific studies, particularly scenarios where types are included. describe novel quality control metrics confirm successful isolation populations, which when included standard pipelines provide confidence dataset. Our power calculations show substantial gains detecting differentially methylated positions some compared tissue analyses, countering concerns regarding feasibility generating enough sample sizes informative epidemiological studies. In simulation study, we evaluated regression models finding this choice impacts robustness results. These findings informed our proposed two-stage association analyses. Overall, results guidance EWAS, establishing standards design analysis, while showcasing potential analyses reveal links between epigenetic dysregulation disease.

Language: Английский

Citations

0