Search bioRxiv⌕ Search

bioRxiv · 10.1101/473629

Identification of novel differentially methylated sites with potential as clinical predictors of impaired respiratory function and COPD

Abstract

BackgroundThe causes of poor respiratory function and COPD are incompletely understood, but it is clear that genes and the environment play a role. As DNA methylation is under both genetic and environmental control, we hypothesised that investigation of differential methylation associated with these phenotypes would permit mechanistic insights, and improve prediction of COPD. We investigated genome-wide differential DNA methylation patterns using the recently released 850K Illumina EPIC array in the largest single population sample to date.\n\nMethodsEpigenome-wide association studies (EWASs) of respiratory function and COPD were performed in peripheral blood samples from the Generation Scotland: Scottish Family Health Study (GS:SFHS) cohort (N=3,791; 274 COPD cases and 2,928 controls). In independent COPD incidence data (N=150), significantly differentially methylated sites (DMSs; p<3.6x10-8) were evaluated for their added predictive power when added to a model including clinical variables, age, sex, height and smoking history using receiver operating characteristic analysis. The Lothian Birth Cohort 1936 (LBC1936) was used to replicate association (N=895) and prediction (N=178) results.\n\nFindingsWe identified 29 respiratory function and/or COPD associated DMSs, which mapped to genes involved in alternative splicing, JAK-STAT signalling, and axon guidance. In prediction analyses, we observed significant improvement in discrimination between COPD cases and controls (p<0.05) in independent GS:SFHS (p=0.014) and LBC1936 (p=0.018) datasets by adding DMSs to a clinical model.\n\nInterpretationIdentification of novel DMSs has provided insight into the molecular mechanisms regulating respiratory function and aided prediction of COPD risk.\n\nFundingWellcome Trust Strategic Award 10436/Z/14/Z.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched for articles in PubMed published in English up to July 25, 2018, with the search terms \"DNA methylation\" and \"respiratory function\", or \"COPD\". We found some evidence for association between differential DNA methylation and both respiratory function and COPD. Of the twelve previous studies identified, eight used peripheral blood samples (sample size [N] range = 100-1,085) and four used lung tissue samples (N range = 24-160). The number of CpG loci analysed range from 27,578 to 485,512. These studies have not identified consistent changes in methylation, most likely due to a combination of factors including small sample sizes, technical issues, phenotypic definitions, and study design. In addition, no previous study has: analysed a sample from a large single cohort; used the recently released Illumina EPIC array (which assesses ~850,000 CpG loci); adjusted methylation data and phenotype for smoking history, or used both prevalent and incident COPD electronic health record data.\n\nAdded value of this studyTo our knowledge, this is the largest single cohort epigenome-wide association study (EWAS) of respiratory function and COPD to date (N=3,791). After applying stringent genome-wide significance criteria (P <3.6x10-8), we found that DNA methylation levels at 29 CpG sites in peripheral blood were associated with respiratory function or COPD. Of these 29, seven were testable in an independent population sample: all seven showed consistent direction of effect between the two samples and three showed replication (p<0.007 [0.05/7 CpG sites tested]). Our results suggest that adjustment of both the phenotypic and the DNA methylation probe data for smoking history, which has not been carried out in previous studies, reduces the confounding effects of smoking, identifies larger numbers of associations, and reduces the heterogeneity of effects across smoking strata. We used gene set enrichment and pathway analyses, together with an approach that combines DNA methylation results with gene expression data to provide evidence for enrichment of differentially methylated sites in genes linked to alternative splicing, and JAK-STAT signalling and axon guidance. Finally, we demonstrated that the inclusion of DNA methylation data improves COPD risk prediction over established clinical variables alone in two independent datasets.\n\nImplications of all the available evidenceThere is now accumulating evidence that DNA methylation in peripheral blood is associated with respiratory function and COPD.\n\nOur study has shown that DNA methylation levels at 29 CpG sites are robustly associated with respiratory function and COPD, provide mechanistic insights, and can improve prediction of COPD risk. Further studies are warranted to improve understanding of the aetiology of COPD and to assess the utility of DNA methylation profiling in the clinical management of this condition.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Bermingham, M. L., Walker, R. M., Marioni, R. E., Morris, S. M., Rawlik, K., Zeng, Y., Campbell, A., Redmond, P., Whalley, H. C., Adams, M. J., Hayward, C., Deary, I. J., Porteous, D. J., McIntosh, A. M., Evans, K. L.. 2018-11-19. Identification of novel differentially methylated sites with potential as clinical predictors of impaired respiratory function and COPD. https://doi.org/10.1101/473629

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Longitudinal miRNA-mRNA Profiling Reveals Network Reorganization in Preeclampsia

Background: Preeclampsia (PE) is a leading cause of maternal and perinatal morbidity. Temporal dynamics of molecular dysregulation across pregnancy remain poorly understood. We performed longitudinal RNA sequencing of maternal whole blood to characterize miRNA-mRNA regulatory network evolution in PE. Methods: Whole-blood samples from early (M1: 10-18 weeks) and late pregnancy (M2: 32-38 weeks) were analyzed from 43 PE cases and 106 normotensive controls, including 109 paired samples (36 PE cases, 73 controls). Differential expression, temporal classification, pathway enrichment, and miRNA-mRNA network integration were performed. Placental expression support was assessed using internal RNA-seq and public databases. Key miRNA-mRNA interactions were experimentally validated in HTR-8/SVneo trophoblast cells. Results: PE exhibited marked temporal reorganization of miRNA-mRNA networks, with strongly opposing temporal effect sizes across overlapping miRNA and mRNA features (Spearman {rho} = -0.82, P < 0.0001). PI3K/AKT/mTORC1 signaling showed biphasic reversal (NES = +1.46, FDR = 0.028 at M1; NES = -1.64, FDR = 0.025 at M2), and heme-metabolism programs showed progressive suppression (2.1-fold NES intensification; FDR < 0.05 at both timepoints). Network analysis identified 29 high-confidence biphasic miRNA-mRNA pairs, including convergent targeting of ADGRA2 by three miRNAs and HSD17B1 by three miRNAs. miR-101-3p overexpression reduced DEPP1 mRNA (~40%) and protein (~26%) in trophoblast cells (P < 0.01), supporting a FOXO-DEPP1 axis. Blood-derived pairs showed pathway convergence with placental VGLL3-centered programs (PI3K/AKT, FOXO, TGF-{beta}, trophoblast differentiation). Conclusions: PE is associated with predominantly stage-specific or biphasic miRNA-mRNA network reorganization, with PI3K/AKT/mTORC1 dynamic remodeling and progressive heme-metabolism suppression. These findings support gestational-age-specific biomarker development and identify regulatory axes, including miR-101-3p [->] DEPP1, for mechanistic investigation.

genomics↗

MicroDUET: a dual-headed genomic foundation model for pathogen surveillance

Pathogen genomic surveillance works from raw reads, assembled genomes and alignments, representations that are slow and costly to compare at scale. Compact embeddings from genomic language models offer an alternative, but surveillance requires resolving both evolutionary ancestry (phylogeny) and phenotypic capability (function) - which need not co-vary. Here we present MicroDUET, which adapts a 26.6-million-parameter ProkBERT backbone with two 3.5-million-parameter adapter heads: a phylogeny head trained contrastively on genome windows from the same microbes, and a function head trained to identify genes across taxa. On held-out retrieval benchmarks, the phylogeny head returned the correct species for 80.3% and 66.6% of cellular and viral queries, and the function head the correct gene family for 97.3% and 97.2%, reaching 74.4% accuracy on an independent antimicrobial resistance-class benchmark. Across all three benchmarks MicroDUET outranked 17 other genomic encoders. Without training on lineage, clade or drug-susceptibility tasks, MicroDUET identified Mycobacterium tuberculosis and mpox virus lineages and clades (0.965, 0.975 accuracy), discriminated rifampicin resistance without lineage adjustment (AUROC 0.985), and retrospectively identified an emerging mpox lineage as anomalous (AUROC 0.974). MicroDUET operates 10^3 - 10^4 times faster than single-threaded sequence-based alignments. MicroDUET therefore provides a compact, reusable representation for scalable pathogen surveillance and sequence triage.

genomics↗

A chromosome-level genome assembly of northern dragonhead, Dracocephalum ruyschiana L., 1753

We present a chromosome-level genome assembly for the vascular plant northern dragonhead, Dracocephalum ruyschiana. The assembly comprises two pseudo-haplotypes, hap1 and hap2, of 661 Mb and 681 Mb, with 93.6% and 92.5%, respectively, scaffolded into seven chromosomes each - in line with the known karyotype. Assembly quality was high, with conserved single-copy ortholog completeness scores of 97.9% and 97.8%, combined k-mer completeness of 98.1%, and 38,141 and 38,617 annotated protein-coding genes for hap1 and hap2, respectively. This assembly provides a high-quality genomic resource for future research and conservation of northern dragonhead, as well as the endangered northern dragonhead sap beetle, which depends on the plant for reproduction and whose genome assembly is described in a complementary genome note.

genomics↗