Author Correction: Bayesian reassessment of the epigenetic architecture of complex traits

Baños, Daniel Trejo; McCartney, Daniel L.; Patxot, Marion; Anchieri, Lucas; Battram, Thomas; Christiansen, Colette; Costeira, Ricardo; Martin, Richard M; Morris, Stewart W.; Campbell, Archie; Zhang, Qian; Porteous, David J.; McRae, Allan F.; Wray, Naomi R.; Visscher, Peter M.; Haley, Chris; Evans, Kathryn; Deary, Ian J.; McIntosh, Andrew M.; Hemani, Gibran; Bell, Jordana T.; Marioni, Riccardo E.; Robinson, Matthew R.

doi:10.1038/s41467-020-19099-9

Cited by 8 publications

(11 citation statements)

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“…We derive a model that we call BayesRR-RC in Supplementary Note 1 and the “Methods” section, which is based on grouped effects with mixture priors, improving on the formulations of refs. 11 – 13 . Like these former methods, we consider a spike probability at zero (Dirac delta function), and a scale mixture of Gaussian distributions as a slab probability density.…”

Section: Resultsmentioning

confidence: 99%

“… 16 , 27 it is showed that the former case requires weaker conditions in order to recover the true vector β consistently than the latter. Although the sampling scheme was different, we have shown that a similar model with only two groups: genetic markers and epigenetic markers, is successful in identifying BMI and smoking epigenetic signatures 13 . The baseline model derivations for this model are outlined in Supplementary Note 1 , a BSP Gibbs sampling scheme and an assessment of its performance is outlined in Supplementary Note 2 , and an assessment of the model performance with correlated covariates is outlined in Supplementary Note 4 .…”

Section: Methodsmentioning

confidence: 99%

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Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits

et al. 2021

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We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only ≤10% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32–44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having ≥95% probability of contributing ≥0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits

et al. 2021

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“…In the study by Langdon et al, 47 methylation scores were evaluated in participants with oropharyngeal cancer and moderately large associations (HR = 1.2‐1.3) with survival were observed for some scores in adjusted models, with modest improvements in terms of prediction. Three other scores were evaluated in that study 10,48,49 as well as just methylation at cg05575921 ( AHRR , smoking), 12 for which the results were similar to those we considered. Other attempts were also made to use individual, or a restricted set of, smoking‐associated methylation marks to predict lung cancer or other smoking‐related outcomes, focusing on the strongest observed associations (eg, AHRR ), for example, in the studies by Baglietto et al including MCCS data, 23 Zhang et al 50,51 and others 52‐55 …”

Section: Discussionmentioning

confidence: 75%

Methylation scores for smoking, alcohol consumption and body mass index and risk of seven types of cancer

Dugué

Hodge

et al. 2023

Intl Journal of Cancer

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Methylation marks of exposure to health risk factors may be useful markers of cancer risk as they might better capture current and past exposures than questionnaires, and reflect different individual responses to exposure. We used data from seven casecontrol studies nested within the Melbourne Collaborative Cohort Study of blood DNA methylation and risk of colorectal, gastric, kidney, lung, prostate and urothelial cancer, and B-cell lymphoma (N cases = 3123). Methylation scores (MS) for smoking, body mass index (BMI), and alcohol consumption were calculated based on published data as weighted averages of methylation values. Rate ratios (RR) and 95% confidence intervals for association with cancer risk were estimated using conditional logistic regression and expressed per SD increase of the MS, with and without adjustment for health-related confounders. The contribution of MS to discriminate cases from controls was evaluated using the area under the curve (AUC). After confounder adjustment, we observed: large associations (RR = 1.5-1.7) with lung cancer risk for smoking MS; moderate associations (RR = 1.2-1.3) with urothelial cancer risk for smoking MS and with mature B-cell neoplasm risk for BMI and alcohol MS; moderate to small associations (RR = 1.1-1.2) for BMI and alcohol MS with several cancer types Abbreviations: AHRR, aryl hydrocarbon receptor repressor; AUC, area under the receiver operating characteristic curve; BMI, body mass index; EWAS, epigenome-wide association study;

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“…This allowed for direct comparisons between protein and EpiScore measures in the context of incident disease analyses, which has only recently been possible owing to the expansion of the cohort’s epigenetic resource. As DNAm may record chronic exposure to a range of environmental risk factors (30) and biological processes such as inflammation (20,31), EpiScores may be reflective of a range of biological pathways that occur upstream of disease diagnoses. Given that GDF15 and Nt-pro-BNP are promising biomarkers for a range of diseases, our EpiScores are well-positioned candidates with many potential use-cases.…”

Section: Discussionmentioning

confidence: 99%

“…The xBayesR+ software implements penalised Bayesian regression on complex traits (30). The BayesR method has been found to outperform linear and mixed model approaches and implicitly adjusts for probe correlations, data structure (such as relatedness) and unobserved confounders (30,32).…”

Section: Methodsmentioning

confidence: 99%

DNAm scores for serum GDF15 and NT-proBNP levels associate with a range of traits affecting the body and brain

Gadd,

Smith,

Mullin

et al. 2023

Preprint

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Background: Plasma growth differentiation factor 15 (GDF15) and Nterminal proBtype natriuretic peptide (NTproBNP) are cardiovascular biomarkers that associate with a range of diseases. Epigenetic scores (EpiScores) for GDF15 and NTproBNP may provide new routes for risk stratification. Results: In the Generation Scotland cohort (N ≥ 16,963), GDF15 levels were associated with incident dementia, ischaemic stroke and type 2 diabetes, whereas NTproBNP levels were associated with incident ischaemic heart disease, ischaemic stroke and type 2 diabetes (all PFDR < 0.05). Bayesian Epigenome wide association studies (EWAS) identified 12 and 4 DNA methylation (DNAm) CpG sites associated (Posterior Inclusion Probability [PIP] > 95%) with levels of GDF15 and NTproBNP, respectively. EpiScores for GDF15 and NTproBNP that were trained in a subset of the population. The GDF15 EpiScore replicated protein associations with incident dementia, type 2 diabetes and ischaemic stroke in the Generation Scotland test set (Hazard Ratios (HR) range 1.36 to 1.41, PFDR <0.03). The EpiScore for NTproBNP replicated the protein association with type 2 diabetes, but failed to replicate an association with ischaemic stroke. EpiScores explained comparable variance in protein levels across both the Generation Scotland test set and the external LBC1936 test cohort (R2 range of 5.7-12.2%). In LBC1936, both EpiScores were associated with indicators of poorer brain health. Neither EpiScore was associated with incident dementia in the LBC1936 population. Conclusions: EpiScores for serum levels of GDF15 and NtproBNP associate with body and brain health traits. These EpiScores are provided as potential tools for disease risk stratification.

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Author Correction: Bayesian reassessment of the epigenetic architecture of complex traits

Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Cited by 8 publications

References 0 publications

Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits

Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits

Methylation scores for smoking, alcohol consumption and body mass index and risk of seven types of cancer

DNAm scores for serum GDF15 and NT-proBNP levels associate with a range of traits affecting the body and brain

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