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High-specificity bioinformatics framework for epigenomic profiling of discordant twins reveals specific and shared markers for ACPA and ACPA-positive rheumatoid arthritis

View Article: PubMed Central - PubMed

ABSTRACT

Background: Twin studies are powerful models to elucidate epigenetic modifications resulting from gene–environment interactions. Yet, commonly a limited number of clinical twin samples are available, leading to an underpowered situation afflicted with false positives and hampered by low sensitivity. We investigated genome-wide DNA methylation data from two small sets of monozygotic twins representing different phases during the progression of rheumatoid arthritis (RA) to find novel genes for further research.

Methods: We implemented a robust statistical methodology aimed at investigating a small number of samples to identify differential methylation utilizing the comprehensive CHARM platform with whole blood cell DNA from two sets of twin pairs discordant either for ACPA (antibodies to citrullinated protein antigens)-positive RA versus ACPA-negative healthy or for ACPA-positive healthy (a pre-RA stage) versus ACPA-negative healthy. To deconvolute cell type-dependent differential methylation, we assayed the methylation patterns of sorted cells and used computational algorithms to resolve the relative contributions of different cell types and used them as covariates.

Results: To identify methylation biomarkers, five healthy twin pairs discordant for ACPAs were profiled, revealing a single differentially methylated region (DMR). Seven twin pairs discordant for ACPA-positive RA revealed six significant DMRs. After deconvolution of cell type proportions, profiling of the healthy ACPA discordant twin-set revealed 17 genome-wide significant DMRs. When methylation profiles of ACPA-positive RA twin pairs were adjusted for cell type, the analysis disclosed one significant DMR, associated with the EXOSC1 gene. Additionally, the results from our methodology suggest a temporal connection of the protocadherine beta-14 gene to ACPA-positivity with clinical RA.

Conclusions: Our biostatistical methodology, optimized for a low-sample twin design, revealed non-genetically linked genes associated with two distinct phases of RA. Functional evidence is still lacking but the results reinforce further study of epigenetic modifications influencing the progression of RA. Our study design and methodology may prove generally useful in twin studies.

Electronic supplementary material: The online version of this article (doi:10.1186/s13073-016-0374-0) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus

DMR1, from TS1 after cell proportion correction, at the promoter region of PCDHB14 (chr5 140582954–140584018). DMR denotes the DMR location (grey box); CpGdens denotes CpG density as computed by CHARM [27] (CpG); CGI denotes the location of CpG islands (black box). TS1 Δbeta and TS2 Δbeta shows the smoothed linear slope (differences in methylation or delta) associated with ACPA-positive healthy and ACPA-positive RA twin, respectively, in the linear model which is used CHARM [27] to identify DMR candidates. Every point denotes a probe location. The location of the gene PCDHB14 is shown in a dotted box; the black square on the left denotes the location of the transcription start site
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Fig3: DMR1, from TS1 after cell proportion correction, at the promoter region of PCDHB14 (chr5 140582954–140584018). DMR denotes the DMR location (grey box); CpGdens denotes CpG density as computed by CHARM [27] (CpG); CGI denotes the location of CpG islands (black box). TS1 Δbeta and TS2 Δbeta shows the smoothed linear slope (differences in methylation or delta) associated with ACPA-positive healthy and ACPA-positive RA twin, respectively, in the linear model which is used CHARM [27] to identify DMR candidates. Every point denotes a probe location. The location of the gene PCDHB14 is shown in a dotted box; the black square on the left denotes the location of the transcription start site

Mentions: However, DMR analysis in the TS1 comparison after cell type correction returned 17 DMR candidates (FWER ≤0.10; see “Methods”; detailed list in Table 3). Of those, 14 DMRs were found in either CpG shores or CpG islands (Table 4; Fig. 3; Additional file 1: Figure S7–S23).Table 3


High-specificity bioinformatics framework for epigenomic profiling of discordant twins reveals specific and shared markers for ACPA and ACPA-positive rheumatoid arthritis
DMR1, from TS1 after cell proportion correction, at the promoter region of PCDHB14 (chr5 140582954–140584018). DMR denotes the DMR location (grey box); CpGdens denotes CpG density as computed by CHARM [27] (CpG); CGI denotes the location of CpG islands (black box). TS1 Δbeta and TS2 Δbeta shows the smoothed linear slope (differences in methylation or delta) associated with ACPA-positive healthy and ACPA-positive RA twin, respectively, in the linear model which is used CHARM [27] to identify DMR candidates. Every point denotes a probe location. The location of the gene PCDHB14 is shown in a dotted box; the black square on the left denotes the location of the transcription start site
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5120506&req=5

Fig3: DMR1, from TS1 after cell proportion correction, at the promoter region of PCDHB14 (chr5 140582954–140584018). DMR denotes the DMR location (grey box); CpGdens denotes CpG density as computed by CHARM [27] (CpG); CGI denotes the location of CpG islands (black box). TS1 Δbeta and TS2 Δbeta shows the smoothed linear slope (differences in methylation or delta) associated with ACPA-positive healthy and ACPA-positive RA twin, respectively, in the linear model which is used CHARM [27] to identify DMR candidates. Every point denotes a probe location. The location of the gene PCDHB14 is shown in a dotted box; the black square on the left denotes the location of the transcription start site
Mentions: However, DMR analysis in the TS1 comparison after cell type correction returned 17 DMR candidates (FWER ≤0.10; see “Methods”; detailed list in Table 3). Of those, 14 DMRs were found in either CpG shores or CpG islands (Table 4; Fig. 3; Additional file 1: Figure S7–S23).Table 3

View Article: PubMed Central - PubMed

ABSTRACT

Background: Twin studies are powerful models to elucidate epigenetic modifications resulting from gene–environment interactions. Yet, commonly a limited number of clinical twin samples are available, leading to an underpowered situation afflicted with false positives and hampered by low sensitivity. We investigated genome-wide DNA methylation data from two small sets of monozygotic twins representing different phases during the progression of rheumatoid arthritis (RA) to find novel genes for further research.

Methods: We implemented a robust statistical methodology aimed at investigating a small number of samples to identify differential methylation utilizing the comprehensive CHARM platform with whole blood cell DNA from two sets of twin pairs discordant either for ACPA (antibodies to citrullinated protein antigens)-positive RA versus ACPA-negative healthy or for ACPA-positive healthy (a pre-RA stage) versus ACPA-negative healthy. To deconvolute cell type-dependent differential methylation, we assayed the methylation patterns of sorted cells and used computational algorithms to resolve the relative contributions of different cell types and used them as covariates.

Results: To identify methylation biomarkers, five healthy twin pairs discordant for ACPAs were profiled, revealing a single differentially methylated region (DMR). Seven twin pairs discordant for ACPA-positive RA revealed six significant DMRs. After deconvolution of cell type proportions, profiling of the healthy ACPA discordant twin-set revealed 17 genome-wide significant DMRs. When methylation profiles of ACPA-positive RA twin pairs were adjusted for cell type, the analysis disclosed one significant DMR, associated with the EXOSC1 gene. Additionally, the results from our methodology suggest a temporal connection of the protocadherine beta-14 gene to ACPA-positivity with clinical RA.

Conclusions: Our biostatistical methodology, optimized for a low-sample twin design, revealed non-genetically linked genes associated with two distinct phases of RA. Functional evidence is still lacking but the results reinforce further study of epigenetic modifications influencing the progression of RA. Our study design and methodology may prove generally useful in twin studies.

Electronic supplementary material: The online version of this article (doi:10.1186/s13073-016-0374-0) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus