Dynamic epigenetic age mosaicism in the human atherosclerotic artery.

Accelerated epigenetic ageing, a promising marker of disease risk, has been detected in peripheral blood cells of atherosclerotic patients, but evidence in the vascular wall is lacking. Understanding the trends of epigenetic ageing in the atheroma may provide insights into mechanisms of atherogenesis or identify targets for molecular therapy. We surveyed DNA methylation age in two human artery samples: a set of donor-matched, paired atherosclerotic and healthy aortic portions, and a set of carotid artery atheromas. The well-characterized pan-tissue Horvath epigenetic clock was used, together with the Weidner whole-blood-specific clock as validation. For the first time, we document dynamic DNA methylation age mosaicism of the vascular wall that is atherosclerosis-related, switches from acceleration to deceleration with chronological ageing, and is consistent in human aorta and carotid atheroma. At CpG level, the Horvath epigenetic clock showed modest differential methylation between atherosclerotic and healthy aortic portions, weak association with atheroma histological grade and no clear evidence for participation in atherosclerosis-related cellular pathways. Our data suggest caution when assigning a unidirectional DNA methylation age change to the atherosclerotic arterial wall. Also, the results support previous conclusions that epigenetic ageing reflects non-disease-specific cellular alterations.

Introduction

The concept that ageing is associated with causal changes in DNA, whether genetic or epigenetic, is at least half-a-century old [1]. A consequential hypothesis is that epigenetic and chronological age diverge in disease, thus providing a possible marker of disease risk. Microarray platforms that determine DNA methylation at CpG level with high reproducibility have provided opportunities to test that hypothesis in a variety of human conditions. In general, epigenetic clocks calculate a predicted age as weighted average of a core set of CpG that are selected based on their robust correlation with chronological age of healthy blood or tissue sample. Epigenetic age acceleration or deceleration in a diseased tissue is determined by calculating the differential between predicted and chronological age [2]. Notably, epigenetic clock predicted age with higher precision than telomere length in one study [3]. Accelerated epigenetic ageing has been detected in peripheral blood cells of atherosclerotic patients, but evidence in the vascular wall is limited even outside the atherosclerosis field [4-7]. To our knowledge, epigenetic ageing of the vascular wall was addressed by two studies, one that tested for associations with haemostatic factors, and another that documented differential DNA methylation age (DNAmAge) between arteries and veins [8, 9]. In the present study, we use a within-donor comparison design to contrast DNAmAge of atherosclerotic and adjacent normal vascular tissue. Strengths of that design include: inter-individual confounders (genetic, environmental, stochastic variation) are reduced; it detects any intra-vascular bed mosaicism, a strong indication that epigenetic ageing is functionally associated with atherosclerosis and not just an epiphenomenon; it allows to dissect the role of systemic or local epigenetic ageing in atherogenesis. For those reasons, the description of epigenetic ageing in the atheroma may be relevant, as it potentially provides insights into mechanisms of aberrant gene expression that predispose to or accompany the natural history of atherosclerosis, and may identify potential epigenomic targets for molecular therapy. We surveyed DNAmAge of two sets of human atherosclerotic and healthy arteries for which we previously obtained extensive DNA methylome data, by using the well-characterized, pan-tissue Horvath clock and Weidner whole-blood-specific clock [3, 10, 11]. The Horvath clock uses 353 CpG as core age predictor and has been shown to accurately calculate the age of a variety of healthy human tissues, and to detect DNAmAge deviations from chronological age (i.e. acceleration or deceleration) in a range of diseases. Genes that harbour the 353 Horvath CpG are enriched in cell growth, cell survival and regulation of development functions. The Weidner clock has been designed to compute epigenetic age of blood cells. The clock uses three CpG as core predictor, located in genes that encode proteins involved in cell-cell communication (integrin, alpha 2b), aminoacid metabolism (aspartoacylase) and cAMP hydrolysis (phosphodiesterase 4C). The Weidner clock is expected to loosely match the Horvath clock, but we included both in our analysis reasoning that an identical direction of change of DNAmAge in the two clocks would be interpreted as validation of Horvath clock predictions.

Materials and methods

Donor-matched pairs of atherosclerotic and histologically normal portions of the aorta (A-aorta and N-aorta, respectively; n = 15 pairs) obtained post mortem, carotid atheromas obtained by endarterectomy from symptomatic and asymptomatic patients (A-car; n = 19 each) and corresponding Infinium HumanMethylation450 BeadChip (Illumina) data were previously described [10, 12]. The characteristics of participating patients are reported in . Aortic and carotid artery samples were obtained in two distinct environments (Spain and Sweden, respectively). The observation that 98% of differentially methylated CpG coincided between aortic and carotid artery samples suggests that batch or geographic origin effects were minimal [10]. Similarly, any significant effect of post mortem time to collection was ruled out in the original study, strongly supporting previous conclusions that DNA methylation profiles are stable after death and can be extrapolated to ex vivo samples [10, 13]. DNA methylation array data were extensively validated in the original study [10]. The study conformed to the principles of the Declaration of Helsinki and patients or relatives in the case of post mortem samples gave written consent prior to their participation. The protocol was approved by the Bellvitge Hospital ethical committee (authorization no. PR311/11). DNA methylation microarray data are freely available at the Gene Expression Omnibus database (www.ncbi.nlm.nih.gov/geo/) with accession number GSE46401 [10]. To determine DNAmAge, Infinium HumanMethylation450 BeadChip data were formatted according to the calculator requirements and uploaded to the freely available epigenetic age calculator maintained by Horvath’s laboratory at https://dnamage.genetics.ucla.edu/. The calculator yields predicted ages calculated with Horvath or Weidner clock algorithms and adjusts for sex and cell type. Output files generated by the calculator have been deposited on the University of Guanajuato cloud and are available at the native (non-shortened) URL: https://ugtomx-my.sharepoint.com/:f:/g/personal/szaina_ugto_mx/Eg-ccQD7c9dHjNekBqjRU1kBkg3zA895OzgJJWF24VZ1NA?e=W1l17j. T-test and one-way ANOVA were used for two group and multiple group comparisons. Pearson’s r was used for correlation tests. Paired t-test of M-values was used to compare CpG methylation data [14]. Genome-wide significance was set at Bonferroni-corrected p<10−7 [10]. Statistical tests were performed with StatPlus Pro (AnalystSoft Inc.). Functional enrichment analysis of CpG-harbouring genes was performed with the DAVID tool (david.ncifcrf.gov) [15, 16].

Results and discussion

Comparison of donor-matched aortas revealed a significant DNAmAge acceleration in A-aorta relative to N-aorta (average +4.3 years, p = 8.0x10-4) (). That differential DNAmAge was above the performance-assessed Horvath clock accuracy (3.6 years) and ~2 years higher than reported in peripheral blood of recurrent stroke patients [11, 17]. Weidner clock also yielded A-aorta DNAmAge acceleration although ~4.5-fold higher (+16.6 years, p = 9.5x10-5). These discrepancies are in line with previous comparisons of performance among clocks [18]. A-aorta and A-aorta-to-N-aorta differential DNAmAge did not differ between histological grades, except borderline significance in Weidner clock (Horvath: p = 0.147 and p = 0.783, respectively; Weidner: p = 0.056 and p = 0.253, respectively). Unexpectedly, N-aortas were on average younger relative to chronological age (Horvath: -4.9 years, p = 0.018; Weidner: -39.7 years, p = 1.69x10-9). Conversely, A-aortas DNAmAge matched chronological age (Horvath: -0.4 years, p = 0.804; Weidner: -1.1 years, p = 0.421). Also, the differential between either A-aorta or N-aorta DNAmAge and chronological age was strongly and inversely correlated with chronological age according to Horvath clock (r = -0.72 and r = -0.89, respectively, p<0.001), while marginally significant in A-aortas by Weidner clock (r = -0.48, p = 0.070, and r = -0.93, p = 10−6). That trend reflected the tendency for accelerated DNAmAge in chronologically younger aortas, followed by a deceleration at older chronological age (). This coincided with slow DNA methylation ageing across chronological age, as indicated by DNAmAge (y axis)/chronological age (x axis) slope <1 in N-aortas and A-aortas (0.46 and 0.57, respectively, in either Horvath or Weidner). Partially echoing our findings, peripheral blood DNAmAge is accelerated in young stroke patients but realigns with chronological age in older patients [4].

Chronological and Horvath DNA methylation age in aortas and carotid atheromas.

Samples are ordered by increasing chronological age (reported on the y-axis) and positioned at regular intervals on the x-dimension. A, donor-matched atherosclerotic and histologically normal portions of the aorta; B, carotid atheromas. Interpolating lines are not regression slopes, rather are intended to convey differences in ageing pace. Notice the tendency for accelerated and decelerated DNA methylation age at early and later ages, respectively.

We replicated the above analysis in the A-car set. A-car and A-aorta were comparable: considering age-matched data points only (n = 14), A-car DNAmAge did not differ from A-aorta DNAmAge or from chronological age (Horvath: +2.4 years, p = 0.167 and +1.0 years, p = 0.661; Weidner: +2.5 years, p = 0.124 and +1.8 years, p = 0.110). The data confirms the high correlation previously observed between the two DNA methylation array data sets [10]. Conversely, A-car DNAmAge was accelerated relative to N-aorta (Horvath: +7.4 years, p = 2.8x10-4; Weidner: +24.7 years, p = 3.1x10-16). Mirroring the aorta data set, the differential between A-car DNAmAge and chronological age was inversely correlated with chronological age (Horvath: r = -0.75, p<10−6; Weidner: r = -0.56, p = 2.6x10-4). Also, a tendency to DNAmAge acceleration followed by deceleration with chronological age was observed in A-car, concomitant with a slower DNA methylation ageing than chronological ageing (DNAmAge (y axis)/chronological age (x axis) slope <1: Horvath: 0.44; Weidner: 0.22) (). Furthermore, the A-car data set allowed to explore associations of DNAmAge with asymptomatic/symptomatic status and with symptom-to-endarterectomy time. DNAmAge was not different between symptomatic and asymptomatic patient atheromas (Horvath: p = 0.116; Weidner: p = 0.151). Likewise, no significant association was detected of DNAmAge with symptom-to-endarterectomy time (Horvath: r = -0.104; Weidner: r = 0.173; p>0.307 in either clock).

In order to gain insights into possible mechanisms underlying the above observations, we assessed the methylation status of the 353 Horvath clock CpG in A-aorta and N-aorta samples [11]. Four CpG (or 1.13%) were differentially methylated between A-aorta and N-aorta at genome-wide significance (p<10−7, Bonferroni correction) (, ). Since differences of methylation β were below 16% in all cases, those CpG did not pass differential methylation criteria in the original analysis of A-aorta and N-aorta [10]. Those four CpG map to proximal (cg01656216) or distal (cg01353448, cg14329157, cg22809047) promoters. Comparatively little or no published evidence links the four corresponding genes to atherosclerosis. HtrA serine peptidase 2 (HTRA2) and chromosome 9 open reading frame 64 (C9orf64) have not been implicated in atherogenesis. Limited evidence indicates that polo like kinase 1 (PLK1), encoding a stimulator of cell proliferation, and acyl-CoA oxidase 1 (ACOX1), encoding a player in fatty acid metabolism, are upregulated in peripheral blood cells of atherosclerotic patients and linked to resolution of inflammation, respectively [19, 20]. Furthermore, less than 10% of Horvath clock CpG were correlated with chronological age or histological grade (30 and 14, respectively) at nominal significance level (overall lowest significance p = 4.7x10-4), but none reached genome-wide significance (p<10−7;) (). None of those 44 CpG was differentially methylated between A-aorta and N-aorta. No significant functional enrichment (Gene_Ontology, Pathways, Protein_Interactions, Tissue_Expression) was observed for the corresponding genes in either case. The majority (~78.6%) of histological grade-associated Horvath clock CpG were also correlated with chronological age, reflecting the fact that chronological age tended to be lower in grade III atheromas than in grade VII counterparts (p = 0.055; ANOVA, Fisher LSD post hoc). Taken together, the analysis of Horvath clock CpG confirmed previous conclusions that epigenetic ageing reflects alterations in fundamental, rather than disease-specific, cellular epigenetic maintenance systems (the concept of EMS discussed in [11]). A few studies support that notion. Peripheral blood cell profiling of six cohorts spanning a wide range of chronological age and pathological conditions, revealed that a minority of Horvath clock CpG correlate with expression of genes in cis that are not significantly enriched in any Gene Ontology term [21]. Epigenetic ageing was weakly associated with classical cardiovascular risk factors in the large MESA and HRS cohorts [22]. Furthermore, no association of epigenetic age with development of cardiovascular risk factors was observed in a cohort of 6–10 years old children [23]. The results of the latter two studies agree with our observation that epigenetic ageing was not associated with asymptomatic/symptomatic status in the carotid atheroma. As caveat, Horvath clock CpG are associated with gene expression in trans in loci that regulate T cell function and may therefore be relevant for atherosclerosis [21, 24, 25]. As the atheroma discontinuously expands by bursts in macrophage infiltration and cellular proliferation, it is possible that the epigenetic clock is a readout of mitotic age in atherosclerosis [26]. Yet, that hypothesis runs counter to the fact that the Horvath epigenetic clock was previously found to be independent of mitotic age and was not associated with histological grade—a proxy of the proliferative history of the atheroma—in this study. In the light of the mentioned evidence, epigenetic ageing may be the consequence of poorly understood cellular mechanisms [27], or may simply be a useful epiphenomenon for marker identification purposes.

In conclusion, we document for the first time dynamic epigenetic age mosaicism of the vascular wall that is atherosclerosis-related, switches from acceleration to deceleration with chronological ageing, and is consistent in human aorta and carotid atheromas. Our data suggest caution when assigning unidirectional DNAmAge change to the atherosclerotic artery. Additionally, Horvath clock CpG methylation profiles reinforce the notion that epigenetic ageing reflects poorly understood, non-disease-specific cellular events.

Horvath clock CpG that were differentially methylated between atherosclerotic and healthy aortic portions, or associated with chronological age or atheroma histological grade.

Differential methylation was significant at genome-wide level (p<10−7, Bonferroni correction; see Table 1 for details). Other associations were significant at nominal significance level (p<0.05; see S1 Table for details).

Table 1

Horvath epigenetic clock CpG (n = 353) that are significantly different between atherosclerotic and healthy portions of the aorta.

CpG ID	A-N¶ Δβ	p§	Chromosome: position‡	Gene symbol	Relevance for atherosclerosis
cg01353448	0.13	6.23x10-8	2:74,609,742	HTRA2	Unknown
cg01656216	0.16	4.11x10-8	9:85,761,834	C9orf64	Unknown
cg14329157	0.05	1.80x10-9	16:23,597,303	PLK1	Overexpressed in atherosclerosis [19]
cg22809047	0.08	8.97x10-8	17:71,487,684	ACOX1	Involved in inflammation resolution [20]

¶A and N, atherosclerotic and healthy portion of the aorta, respectively.

§Comparison of M-values, paired t-test, Bonferroni-corrected (threshold: p = 10−7).

‡Genome build 36.

(PPTX)

Click here for additional data file.

Patient information.

(DOCX)

Click here for additional data file.

CpG associated with chronological age or histological grade.

(XLSX)

Click here for additional data file.

27 Apr 2022

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Supported by the following grants to ME: European Research Council (ERC) grant EPINORC under agreement no. 268626, the MICINN Project: SAF2011-22803, the Cellex Foundation, the Botin Foundation, the European Community’s Seventh Framework Programme (FP7/2007– 2013) from grant HEALTH-F5-2011–282510–BLUEPRINT and the Health and Science Departments of the Generalitat de Catalunya. SZ was supported by a CONACyT (Mexico) Sabbatical Fellowship no. 166058. ME is an Institució Catalana de Recerca i Estudis Avançats (ICREA) Research Professor.)

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Reviewer #1: Review for “Dynamic epigenetic age mosaicism in the human atherosclerotic artery”

Zaina and colleagues utilized 2 datasets to evaluate associations of epigenetic aging in atherosclerotic aortas, normal aortas, and carotid atheromas using the Illumina Infinium HumanMethylation450 BeadChip. Through their analyses, they found that atherosclerotic aortas had greater age acceleration when compared to normal aortas. However, in comparison to chronological age, atherosclerotic aortas showed no acceleration, and normal aortas showed a deceleration in aging. An analysis of carotid atheromas showed accelerated epigenetic aging when compared to normal aortas, but when compared to atherosclerotic aortas, there was no difference.

Methods and Materials:

Line 55: Were there any location/batch effects observed?

Line 58: Do you expect there to be differences between post mortem and live tissue samples? Would this impact the results?

Results:

1) Your graph shows a non-linear relationship for atherosclerotic heart. I’m not sure if you can make a comparison with chronological age. Fitting a spline might help.

Figures:

1) Is the x-axis meaningful? A legend mapping out the meaning of circles etc. would be helpful. Reading it in the figure legend at the bottom makes it difficult to read.

1A) Could this be split into 2 graphs? It’s difficult to read.

S1) Including the p-value thresholds in the figure legend will be helpful.

Reviewer #2: The manuscript under the title: “Dynamic epigenetic age mosaicism in the human atherosclerotic artery” represents an interesting original scientific paper describing the role of epigenetic aging (DNA methylation) in the settings of donor-matched, paired atherosclerotic, and healthy aortic portions and in the settings of carotid artery atheroma.

However, some obstacles prevent the manuscript from publication in its current form.

These, among others, include:

The Materials and method section should be more extensive. Although the characteristics of samples used in the current study were, according to the authors, described in the original research (Zaina et al., 2014), some basic patient information should be described in the current study as well.

The description of the pan-tissue Horvath epigenetic clock and the Weidner whole-blood-specific clock and the calculation of DNAmAge should be more detailed to be more understandable to the scientists outside the field.

The authors have written. “Those four CpG map to proximal (cg01656216) or distal promoters”. - The distal promoters should be, if possible, mentioned as well.

The authors have written: “Comparatively little, or no published evidence links the four corresponding genes to atherosclerosis.” - The corresponding four genes should be mentioned in the text.

It seems, at least to me, that most of the data described in the Result section are not illustrated in the form of a table or figure presentation.

A major revision of the manuscript is recommended.

Reviewer #3: The authors aimed to test epigenetic aging in human artery samples, a set of donor-matched,

paired atherosclerotic and healthy aortic portions, and a set of carotid artery atheromas. I do not get the point of the analysis since we all know that epigenetic modifications are tissue specific. Since a lot of epigenetic sites were available, it would be good to analyze these as the main part, which, however, has been published by this group. Thus, I may recommend rejection at this point as this work does not add new to the field. Also the results were not well organized and it seem hard to get what the authors wanted to show.

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2 May 2022

Dear Dr. El-Maarri,

We are grateful for the opportunity to submit a revised version of our manuscript PONE-D-22-05348 "Dynamic epigenetic age mosaicism in the human atherosclerotic artery" and appreciate your time and effort to find three independent Reviewers.

Please find in the next pages a detailed rebuttal to the points raised by the Reviewers. We responded to the third Reviewer's strong criticism by pitching the merit of the study the best way we could.

We also addressed the additional requirements that you indicated in the decision email as follows:

1. We checked the manuscript to adhere to PLOS ONE's style requirements.

2. We submit an amended funding statement that reads as follows:

Supported by the following grants to ME: European Research Council (ERC) grant EPINORC under agreement no. 268626, the MICINN Project: SAF2011-22803, the Cellex Foundation, the Botin Foundation, the European Community’s Seventh Framework Programme (FP7/2007–2013) from grant HEALTH-F5-2011–282510–BLUEPRINT and the Health and Science Departments of the Generalitat de Catalunya. SZ was supported by a CONACyT (Mexico) Sabbatical Fellowship no. 166058. ME is an Institució Catalana de Recerca i Estudis Avançats (ICREA) Research Professor. There was no additional external funding received for this study.

We hope that the amended funding statement is acceptable. As you indicated in the decision email, the statement is part of this cover letter but has not been changed in the manuscript.

3. We make a minimal data set - i.e. output files generated by the DNA methylation age calculator - available from the cloud of the University of Guanajuato, to which I am affiliated. We specify the corresponding link in the Methods section (lines 88-89).

Please let us know whether any required information is missing.

We look forward to the Editorial decision.

Sincerely,

Silvio Zaina

Reviewer #1: Review for “Dynamic epigenetic age mosaicism in the human atherosclerotic artery” Zaina and colleagues utilized 2 datasets to evaluate associations of epigenetic aging in atherosclerotic aortas, normal aortas, and carotid atheromas using the Illumina Infinium HumanMethylation450 BeadChip. Through their analyses, they found that atherosclerotic aortas had greater age acceleration when compared to normal aortas. However, in comparison to chronological age, atherosclerotic aortas showed no acceleration, and normal aortas showed a deceleration in aging. An analysis of carotid atheromas showed accelerated epigenetic aging when compared to normal aortas, but when compared to atherosclerotic aortas, there was no difference.

Methods and Materials:

Line 55: Were there any location/batch effects observed?

Authors' response: We addressed this important point in the original study (Methods, lines 72-74) and in the Results and Discussion section (lines 125-126).

Line 58: Do you expect there to be differences between post mortem and live tissue samples? Would this impact the results?

Authors' response: No correlation between post mortem time at specimen collection and methylation of relevant loci was observed in the original study (Zaina et al., page 696). This is strong evidence for DNA methylation stability across our specimen, irrespective of origin. We added this valid point to the Methods section (line 74-77).

Results:

1) Your graph shows a non-linear relationship for atherosclerotic heart. I’m not sure if you can make a comparison with chronological age. Fitting a spline might help.

Authors' response: Sorry for not conveying the substance of the data shown in Figure 1. The non-linearity is visually true but misleading, as it reflects a slightly wider distribution of chronological age at the two extremes of the age range. Please note that samples are equally spaced along the x-dimension. The x-axis does not represent any biological variable that describes the samples in any way. We do not want to dodge this valid comment, but fitting the curve would have a weak biological justification. We maintain that interpolating lines are in this case more illustrative than non-linear fitting.

Figures:

1) Is the x-axis meaningful? A legend mapping out the meaning of circles etc. would be helpful. Reading it in the figure legend at the bottom makes it difficult to read.

Authors' response: We modified Figure 1 accordingly, hoping that quality improved. The figure has no x-axis. Samples were ordered by chronological age (reported on the y-axis) and positioned at regular intervals on the x-dimension. This rationale in constructing the figure has been added to the legend. We hope that this adequately addresses the reviewer's concern.

1A) Could this be split into 2 graphs? It’s difficult to read.

Authors' response: We gave a lot of thought to this comment. The three data sets in Figure 1A are linked and splitting them into two panels would mean either plotting DNA methylation age alone without chronological age or plotting chronological age twice with DNA methylation age of control aorta in one panel, and of atherosclerotic aorta in the other. Again, we do not want to dodge the Reviewer's point; but we feel that by adopting either solution readability would not improve.

S1) Including the p-value thresholds in the figure legend will be helpful.

Authors' response: We changed the figure legend accordingly and have actually indicated the threshold p values in Table I (line 181) and in the text (line 92, line 152). Thanks for the suggestion.

Reviewer #2: The manuscript under the title: “Dynamic epigenetic age mosaicism in the human atherosclerotic artery” represents an interesting original scientific paper describing the role of epigenetic aging (DNA methylation) in the settings of donor-matched, paired atherosclerotic, and healthy aortic portions and in the settings of carotid artery atheroma. However, some obstacles prevent the manuscript from publication in its current form. These, among others, include:

The Materials and method section should be more extensive. Although the characteristics of samples used in the current study were, according to the authors, described in the original research (Zaina et al., 2014), some basic patient information should be described in the current study as well.

Authors' response: We thank this reviewer for the overall encouraging comments. We have added a supplemental table (S1 Table) with patient information (lines 70-71).

The description of the pan-tissue Horvath epigenetic clock and the Weidner whole-bloodspecific clock and the calculation of DNAmAge should be more detailed to be more understandable to the scientists outside the field.

Authors' response: The Reviewer is right. We rewrote and expanded the Introduction section (lines 31-65). It now contains an essential description of the broad rationale behind epigenetic clocks and of the loci used to predict age by Horvath or Weidner clocks. Also, we now outline the methodology used to calculate the predicted age (Methods section, lines 82-86) and made the output files generated by the calculator available (lines 86-89). In Results, we added a sentence on variation among epigenetic clocks (lines 100-101).

The authors have written. “Those four CpG map to proximal (cg01656216) or distal promoters”.

- The distal promoters should be, if possible, mentioned as well.

Authors' response: We changed that sentence accordingly (line 144).

The authors have written: “Comparatively little, or no published evidence links the four corresponding genes to atherosclerosis.” - The corresponding four genes should be mentioned in the text.

Authors' response: We mention the gene names and biological function and cite relevant literature in the text (lines 145-150).

It seems, at least to me, that most of the data described in the Result section are not illustrated in the form of a table or figure presentation.

Authors' response: We carefully revised the text for data to be included in new figures or tables. The first segment of the Results section (lines 96-115) describes data that are included in Figure 1A or statistical analysis of those data that if spelled out in the figure would compromise readability. The same can be said of the part of Results describing carotid artery samples and referring to Figure 1B (lines 122-137). As for the segment describing individual CpG (lines 138-177), we added a supplemental table (S2 Table; line 152-153) that describes CpG correlation statistics and genomic position, and the identity of genes that harbour the chronological age-associated or histological grade-associated Horvath CpG. In our view, the new S2 Table should provide a complete information about the results of the analysis at CpG level, together with and complementing S1 Figure. We hope that this Reviewer will now find that tables and figures sufficiently cover our results, taking into account that the new S1 Table was also added (see above).

A major revision of the manuscript is recommended.

Authors' response: We have striven to revise the manuscript the best way we could and hope that we appropriately addressed the Reviewer's concerns.

Reviewer #3: The authors aimed to test epigenetic aging in human artery samples, a set of donor-matched, paired atherosclerotic and healthy aortic portions, and a set of carotid artery atheromas. I do not get the point of the analysis since we all know that epigenetic modifications are tissue specific. Since a lot of epigenetic sites were available, it would be good to analyze these as the main part, which, however, has been published by this group. Thus, I may recommend rejection at this point as this work does not add new to the field. Also the results were not well organized and it seem hard to get what the authors wanted to show.

Authors' response: We are sorry for the bad impression our manuscript left this Reviewer with. We have revised the manuscript based on the other two Reviewers' criticism. This Reviewer may thererfore find the new manuscript version more intelligible. It is true that DNA methylation profiles are in part tissue-specific. However, in this study we addressed a distinct question: whether epigenetic ageing is mosaic within the same vascular bed and particularly between atherosclerotic and healthy portions. We believe that this approach has been overlooked, as most epigenetic age studies address ageing in whole blood and use that information as proxy of the organism's age to compare epigenetic ageing pace among individuals. We tried to explain that epigenetic age mosaicism within an artery would have significant implications: divergence of ageing would provide strong indication that the epigenetic clock is functionally associated with atherogenesis, and that epigenetic ageing is local rather than systemic. Although that would not be enough per se to deduce causality, it may help to understand the molecular basis of atherosclerosis and identify therapeutic targets (Introduction section, lines 46-53). We respectfully ask this Reviewer to consider our rebuttal and to take a fresh look at our results.

23 May 2022

Dynamic epigenetic age mosaicism in the human atherosclerotic artery

PONE-D-22-05348R1

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27 May 2022

PONE-D-22-05348R1

Dynamic epigenetic age mosaicism in the human atherosclerotic artery

Dear Dr. Zaina:

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