Erratum: Characterization of functional methylomes by next-generation capture sequencing identifies novel disease-associated variants

Thousands of CpGs Show DNA Methylation Differences in ACPA-Positive Individuals

High levels of anti-citrullinated protein antibodies (ACPA) are often observed prior to a diagnosis of rheumatoid arthritis (RA). We undertook a replication study to confirm CpG sites showing evidence of differential methylation in subjects positive vs. negative for ACPA, in a new subset of 112 individuals sampled from the population cohort and biobank CARTaGENE in Quebec, Canada. Targeted custom capture bisulfite sequencing was conducted at approximately 5.3 million CpGs located in regulatory or hypomethylated regions from whole blood; library and protocol improvements had been instituted between the original and this replication study, enabling better coverage and additional identification of differentially methylated regions (DMRs). Using binomial regression models, we identified 19,472 ACPA-associated differentially methylated cytosines (DMCs), of which 430 overlapped with the 1909 DMCs reported by the original study; 814 DMRs of relevance were clustered by grouping adjacent DMCs into regions. Furthermore, we performed an additional integrative analysis by looking at the DMRs that overlap with RA related loci published in the GWAS Catalog, and protein-coding genes associated with these DMRs were enriched in the biological process of cell adhesion and involved in immune-related pathways.

High-resolution epigenome analysis in nasal samples derived from children with respiratory viral infections reveals striking changes upon SARS-CoV-2 infection

Background

DNA methylation patterns of the human genome can be modified by environmental stimuli and provide dense information on gene regulatory circuitries. We studied genome-wide DNA methylation in nasal samples from infants (<6 months) applying whole-genome bisulfite sequencing (WGBS) to characterize epigenome response to 10 different respiratory viral infections including SARS-CoV-2.

Results

We identified virus-specific differentially methylated regions (vDMR) with human metapneumovirus (hMPV) and SARS-CoV-2 followed by Influenza B (Flu B) causing the weakest vs. strongest epigenome response with 496 vs. 78541 and 14361 vDMR, respectively. We found a strong replication rate of FluB (52%) and SARS-CoV-2 (42%) vDMR in independent samples indicating robust epigenome perturbation upon infection. Among the FluB and SARS-CoV-2 vDMRs, around 70% were hypomethylated and significantly enriched among epithelial cell-specific regulatory elements whereas the hypermethylated vDMRs for these viruses mapped more frequently to immune cell regulatory elements, especially those of the myeloid lineage. The hypermethylated vDMRs were also enriched among genes and genetic loci in monocyte activation pathways and monocyte count. Finally, we perform single-cell RNA-sequencing characterization of nasal mucosa in response to these two viruses to functionally analyze the epigenome perturbations. Which supports the trends we identified in methylation data and highlights and important role for monocytes.

Conclusions

All together, we find evidence indicating genetic predisposition to innate immune response upon a respiratory viral infection. Our genome-wide monitoring of infant viral response provides first catalogue of associated host regulatory elements. Assessing epigenetic variation in individual patients may reveal evidence for viral triggers of childhood disease.

Capturing functional epigenomes for insight into metabolic diseases

Background

Metabolic diseases such as obesity are known to be driven by both environmental and genetic factors. Although genome-wide association studies of common variants and their impact on complex traits have provided some biological insight into disease etiology, identified genetic variants have been found to contribute only a small proportion to disease heritability, and to map mainly to non-coding regions of the genome. To link variants to function, association studies of cellular traits, such as epigenetic marks, in disease-relevant tissues are commonly applied.

Scope of the review

We review large-scale efforts to generate genome-wide maps of coordinated epigenetic marks and their utility in complex disease dissection with a focus on DNA methylation. We contrast DNA methylation profiling methods and discuss the advantages of using targeted methods for single-base resolution assessments of methylation levels across tissue-specific regulatory regions to deepen our understanding of contributing factors leading to complex diseases.

Major conclusions

Large-scale assessments of DNA methylation patterns in metabolic disease-linked study cohorts have provided insight into the impact of variable epigenetic variants in disease etiology. In-depth profiling of epigenetic marks at regulatory regions, particularly at tissue-specific elements, will be key to dissect the genetic and environmental components contributing to metabolic disease onset and progression.

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Changes in epigenetic marks have been linked to metabolic disease phenotypes.

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Disease-linked sites of variable DNA methylation status are enriched in distal regulatory regions of disease-linked tissues.

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Distal regulatory elements remain underrepresented in popular array-based methylation profiling technologies.

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Novel next-generation capture methods provide cost-effective solutions to assess the impact of DNA methylation in metabolic diseases specifically at regulatory elements.

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Improvements in methodologies to account for tissue heterogeneity and causality will be crucial in future epigenome-wide association studies.

Reflections on the Field of Human Genetics: A Call for Increased Disease Genetics Theory

Development of human genetics theoretical models and the integration of those models with experiment and statistical evaluation are critical for scientific progress. This perspective argues that increased effort in disease genetics theory, complementing experimental, and statistical efforts, will escalate the unraveling of molecular etiologies of complex diseases. In particular, the development of new, realistic disease genetics models will help elucidate complex disease pathogenesis, and the predicted patterns in genetic data made by these models will enable the concurrent, more comprehensive statistical testing of multiple aspects of disease genetics predictions, thereby better identifying disease loci. By theoretical human genetics, I intend to encompass all investigations devoted to modeling the heritable architecture underlying disease traits and studies of the resulting principles and dynamics of such models. Hence, the scope of theoretical disease genetics work includes construction and analysis of models describing how disease-predisposing alleles (1) arise, (2) are transmitted across families and populations, and (3) interact with other risk and protective alleles across both the genome and environmental factors to produce disease states. Theoretical work improves insight into viable genetic models of diseases consistent with empirical results from linkage, transmission, and association studies as well as population genetics. Furthermore, understanding the patterns of genetic data expected under realistic disease models will enable more powerful approaches to discover disease-predisposing alleles and additional heritable factors important in common diseases. In spite of the pivotal role of disease genetics theory, such investigation is not particularly vibrant.