Associations between high blood pressure and DNA methylation.

BACKGROUND: High blood pressure is a major risk factor for cardiovascular disease and is influenced by both environmental and genetic factors. Epigenetic processes including DNA methylation potentially mediate the relationship between genetic factors, the environment and cardiovascular disease. Despite an increased risk of hypertension and cardiovascular disease in individuals of South Asians compared to Europeans, it is not clear whether associations between blood pressure and DNA methylation differ between these groups.
METHODS: We performed an epigenome-wide association study and differentially methylated region (DMR) analysis to identify DNA methylation sites and regions that were associated with systolic blood pressure, diastolic blood pressure and hypertension. We analyzed samples from 364 European and 348 South Asian men (first generation migrants to the UK) from the Southall And Brent REvisited cohort, measuring DNA methylation from blood using the Illumina Infinium® HumanMethylation450 BeadChip.
RESULTS: One CpG site was found to be associated with DBP in trans-ancestry analyses (i.e. both ethnic groups combined), while in Europeans alone seven CpG sites were associated with DBP. No associations were identified between DNA methylation and either SBP or hypertension. Comparison of effect sizes between South Asian and European EWAS for DBP, SBP and hypertension revealed little concordance between analyses. DMR analysis identified several regions with known relationships with CVD and its risk factors.
CONCLUSION: This study identified differentially methylated sites and regions associated with blood pressure and revealed ethnic differences in these associations. These findings may point to molecular pathways which may explain the elevated cardiovascular disease risk experienced by those of South Asian ancestry when compared to Europeans.

Introduction

Hypertension results from abnormalities in the control systems that normally regulate blood pressure [1]. It is one of the strongest risk factors for cardiovascular disease (CVD) which is the leading cause of death worldwide [2, 3]. People of South Asian descent have increased risk of CVD compared to Europeans [4, 5]. In South Asians living in the United Kingdom, death rate from stroke is between 20% and 25% greater than the rest of the population [6]. Associations between SBP or DBP and stroke are also stronger in South Asians than Europeans [4].

DNA methylation is an example of an environmentally responsive, mitotically stable, epigenetic mark that is associated with biological processes, including those leading to high blood pressure and stroke [7-9]. Furthermore, candidate gene analyses in cell-line and animal studies have demonstrated a role of DNA methylation in the pathogenesis of hypertension [10-14]. For one of these genes, HSD11B2, DNA methylation has also been associated with hypertension in humans [15]. One recent study found associations between systolic and diastolic BP and DNA methylation among participants of European, Hispanic and African American decent [16]. We aimed to identify DNA methylation associated with SBP, DBP and hypertension in peripheral blood of European and South Asian men in data collected using the Infinium HumanMethylation450 (HM450) BeadChip. We analyzed all samples together in a trans-ancestry analysis, then conducted analyses in each ethnic group separately. We hypothesised that BP associated epigenetic marks would differ between South Asian and European groups, highlighting potential mechanisms explaining the disparity in CVD and stroke risk between the two ethnicities.

Results

Trans-ancestry EWAS analyses

SBP

In the unadjusted EWAS investigating the association between DNA methylation and SBP we identified four CpG sites with Bonferroni-corrected p-value< 1.24×10−07 (Table A in S1 File). After adjustment for potential confounders these associations were markedly attenuated (Table B in S1 File).

DBP

In the unadjusted EWAS investigating the association between DNA methylation and DBP we identified two CpG sites, with Bonferroni-corrected p-value (Table C in S1 File). After adjustment for potential confounders, the associations identified in the unadjusted EWAS were markedly attenuated. However, one additional CpG site (cg07598370 near OR5AP2) was identified in the adjusted EWAS, below the Bonferroni-corrected threshold (Fig 1 and Table D in S1 File). DBP was associated with lower DNA methylation at this CpG site with a 0.1% decrease in DNA methylation per 1 mmHg increase in DBP. The mean and standard deviation (SD) of DNA methylation at this CpG site in the European group was 0.84 (0.07) and in the South Asian group was 0.83 (0.05).

Fig 1

Manhattan plot indicating the associations between DBP and DNA methylation of men of European and South Asian ancestry.

The plot demonstrates the associations between DBP and DNA methylation of European and South Asian men collectively. The model was adjusted for confounders, estimated cell counts and principal components. The uncorrected log10(p-values) are plotted on the y-axis. The blue line is drawn to separate the CpG sites that surpassed p-value<1×10−05, a threshold for a suggestive association and the red line to separate the CpG sites that surpassed the Bonferroni-corrected threshold (p-value<1.24×10−07). The CpG sites that surpassed the Bonferroni-corrected threshold were considered to be associated with the trait.

Hypertension

In the unadjusted EWAS investigating the association between DNA methylation and hypertension, we identified two CpG sites, falling below the Bonferroni-corrected p-value threshold (Table E in S1 File). After adjustment for potential confounders, the associations identified in the unadjusted EWAS were markedly attenuated and no longer associated (Table F in S1 File).

European EWAS

In the EWAS investigating the association between SBP and DNA methylation, no CpG sites were associated with SBP after correction for multiple testing (G and H Tables in S1 File).

In the unadjusted EWAS investigating the association between DNA methylation and DBP, we identified three CpG sites with Bonferroni-corrected p-value<1.24×10−07 (Table I in S1 File). In the fully adjusted EWAS, two of the three CpG sites: cg16241714 (in the gene body of CEBPD), cg00006122 (near the gene C12orf44), were identified as falling below the Bonferroni-corrected threshold (Table J in S1 File). Their direction of association was consistent with the unadjusted EWAS. In addition to these two CpG sites, cg04751533 near AFAP1 was found to be associated with DBP a 0.16% decrease in DNA methylation per 1 mmHg increase in DBP observed at this CpG site (Fig 2 and Table J in S1 File).

Fig 2

A Manhattan plot indicating the associations between DBP and DNA methylation in European men.

The plot demonstrates the associations between DBP and DNA methylation in European men. The model was adjusted for confounders, estimated cell counts and principal components. The uncorrected–log10(p-values) are plotted on the y-axis. The blue line is drawn to separate the CpG sites that surpassed p-value<1×10−05, the threshold suggestive of an association and the red line to separate the CpG sites that surpassed the Bonferroni threshold (p-value<1.24×10−07). The CpG sites that surpassed the Bonferroni threshold were considered to be associated with the trait.

In theEWAS investigating the association between hypertension and DNA methylation, no CpG sites were associated with hypertension after correction for multiple testing (K and L Tables in S1 File).

South Asian EWAS

In the unadjusted EWAS investigating the association between DNA methylation and SBP, we identified one CpG site (cg07963349 in the gene body of GALR2), which fell below the Bonferroni-corrected p-value<1.24×10−07 (Table M in S1 File). In the fully adjusted EWAS, this CpG site was no longer associated after correction for multiple testing but the direction of association was consistent between models (Table N in S1 File).

In the EWAS investigating the association between DBP and DNA methylation, no CpG site was associated following correction for multiple testing (O and P Tables in S1 File).

In both unadjusted and fully adjusted EWAS investigating the association between hypertension and DNA methylation, no CpG site was associated following correction for multiple testing (Q and R Tables in S1 File).

The genomic inflation factor, lambda, for all fully adjusted models is provided in Table 1.

Table 1

Levels of genomic inflation (Lambda) for each EWAS comparison after correcting for confounders including cell counts.

	DBP	SBP	Hypertension
Trans-ancestry	1.07	0.94	1.12
European	1.08	1.00	0.92
South Asian	1.00	0.94	0.99

Comparison of effect sizes between trans-ancestry, European and South Asian EWAS

The magnitude of associations between European and South Asian populations taken from the fully adjusted EWAS of SBP, DBP and hypertension were compared to each other using a linear fit and a random intercept and slope multilevel model in a pair-wise comparison. There was little consistency between the EWAS of Europeans and South Asians (goodness-of-fit R2 = 0 for SBP, DBP and hypertension (Fig 3)).

Fig 3

Consistency between fully adjusted EWAS of SBP, DBP and hypertension between Europeans and South Asian.

DNA methylation associations are shown for 402331 common CpG sites across three EWAS analyses. Each green dot represents a CpG site and the positions of the dots are determined by the effect size in each analysis. The grey lines on each dot denote the confidence intervals (CI) for the estimates. A linear fit of the overall correspondence summarises correlation between compared associations (green dashed line). Grey dashed line shows the line of equality in effect sizes between pairs of analyses. R2 = goodness of linear fit and as such is a measure of the consistency between two EWAS.

Differentially methylated region analysis

DMR analyses were carried out to identify regions of DNA methylation that were associated with SBP, DBP and hypertension. As in the EWAS analyses, DMR analysis was conducted for the full trans-ancestry group, and additionally for European and South Asian sub-groups. Trans-ancestry DMR analysis identified 395 regions of methylation variation (mapped to 326 annotated genes) for SBP, 237 regions (mapped to 157 annotated genes) for DBP and 0 DMRs for hypertension using a FDR-corrected p-value<0.05 (S-XTables in S1 File). Twelve DMRs annotated to genes were common between trans-ancestry SBP and trans-ancestry DBP at FDR p-value<0.05 (Table 2).

Table 2

Overlap of DMRs between fully adjusted DMR analysis of SBP and DBP for trans-ancestry, Europeans and South Asians respectively.

Overlap for trans-ancestry	Overlap for Europeans	Overlap for South Asians
BBS1*	AR	ACCN3
BCORL1*	ARHGEF3	ALDH16A1
CACNA1A**	BBS1	ARID1B
HLX*	BCORL1	ARPP-21
MYT1L	FHL1	ATP5G3
PDZD2	HLX	BBS2
PRCC	PRDM16	C17orf80, FAM104A
PRRT1	SLMO1	C17orf96
SLMO1*		C5orf13
TFAP2D		CACNA1A
ZNF77**		CALHM1
ZNF783		CHD4
		CYFIP1
		DERA
		ELL2
		ERF
		IFFO1
		INPP5A
		LRCH2
		MSRB3
		MYH9
		ORC5L
		P4HA3
		PID1
		PPIL6
		PRKAG2
		PTPRN2
		PURG,WRN
		SNORD113-7
		TRPS1
		WDR27
		WIPF1
		ZIC1
		ZNF57
		ZNF77

* when a gene is common between trans-ancestry and European analyses,

** when a gene is common between trans-ancestry and South Asian analyses.

In Europeans, 348 DMRS for SBP (mapped to 291 annotated genes), 95 for DBP (mapped to 74 annotated genes) and 0 for hypertension were identified using a FDR-corrected p-value<0.05. Nine DMRs annotated to genes were common between European SBP and European DBP at FDR p-value<0.05 (Table 2). In South Asians, 96 DMRs for SBP (mapped to 66 annotated genes), 186 DBP (mapped to 135 annotated genes) and 0 hypertension DMRs were identified using a FDR-corrected p-value<0.05. Thirty-five DMRs annotated to genes were common between South Asian SBP and South Asian DBP at FDR p-value<0.05 (Table 2).

We created Venn diagrams to identify overlap between DMRs (mapped to genes) of SBP and DBP analyses conducted for South Asian and European groups (Fig 4). For SBP, there were three genes in common (WRN, PTPRN2 and CACNA1A). For DBP, there was one DMR in common between South Asian and European groups (PRDM16).

Fig 4

Venn diagrams to identify overlap between DMRs (mapped to genes) of DBP (A) and SBP (B) analyses conducted for South Asian and European groups.

SA denotes South Asian and Eu denotes European ancestry.

We performed pathway analyses for the genes mapped for DMRs of SBP and DBP analyses conducted for South Asian and European groups. For SBP analyses conducted for Europeans and DBP analyses conducted for South Asians, we identified pathways enriched with FDR q-value<0.05. The identified pathways for SBP analyses conducted for Europeans were NOTCH2 intracellular domain regulates transcription and NOTCH4 intracellular domain regulates transcription. The identified pathway for DBP analyses conducted for South Asians was insulin-like growth factor-2 mRNA binding proteins (IGF2BPs/IMPs/VICKZs) bind RNA.

Known genetic variants in DMRs

Two of the twelve DMRs common in trans-ancestry SBP and DBP analysis, TFAP2D and HLX, contain SNPs previously associated with blood pressure [17, 18]. The genetic variant in the PDZD2 DMR was previously associated with myocardial infarction [18]. HLX was also identified in DMR analysis of SBP and DBP in Europeans (Table 2). PRDM16 was found to be common to SBP and DBP in Europeans, its genetic variants were previously associated with dilated cardiomyopathy [19]. PRKAG2 was found to be common to SBP and DBP in South Asians, and has been previously associated with hypertrophic cardiomyopathy [20] and chronic kidney disease [21]. Other identified genes previously reported in GWAS to be associated with CVD-related traits were ELL2 (GWAS of BP [17], insulin [22] and glucose [22]), TRPS1 (GWAS of BP [17]), PID1 (GWAS of stroke [23], lung function [24] and chronic obstructive pulmonary disease [25]) and WIPF1 (GWAS of resting heart rate [26]).

Comparison with previous EWAS

We looked up 126 associations reported earlier [16] that also appeared in the trans-ancestry EWAS of SBP and DBP in our study (Table Y in S1 File). The evidence of associations for these sites was generally weaker in our study. The effect sizes were heterogeneous for the majority of associations but the magnitude of difference between two studies was small. cg19693031 (near TXNIP) and cg18120259 (in gene body LOC100132354), found within the top hundred CpG sites of the trans-ancestry EWAS of SBP in our analyses, were among the 126 previously reported associations [16]. The direction of effect was consistent with the previous analysis and the magnitude of association was slightly larger in our study. The above reported cg18120259 was also the top CpG site in our trans-ancestry EWAS of hypertension, the direction of effect was consistent but the magnitude of association was stronger in our study. These CpG sites were also replicated previously [16].

Discussion

We investigated the association between SBP, DBP and hypertension and DNA methylation measured in peripheral blood of European and South Asian men combined and then across individual ethnicities using the HM450 BeadChip array. In the trans-ancestry fully adjusted EWAS, we found DBP was associated with methylation at one CpG site (cg07598370 near OR5AP2) below the Bonferroni-corrected threshold. A genetic variant near the olfactory receptor, family 5, subfamily AP, member 2 (OR5AP2) has been previously reported to be associated with hematological phenotypes [27], in addition olfactory receptors are known to regulate blood pressure via their renal expression [28]. Evidence has shown that renal sensory receptors play an important role in blood pressure regulation and olfactory receptors belonging to this group of sensory receptors[29]. SBP and hypertension were not associated with DNA methylation after adjustment for confounders, estimated cell counts and PCs. EWAS were also conducted in European and South Asian groups separately. In Europeans fully adjusted EWAS, three CpG sites were associated with DBP with a Bonferroni-corrected p-value below the threshold imposed. In South Asians fully adjusted EWAS, SBP, DBP and hypertension were not associated with DNA methylation after multiple testing corrections. Several of the initial associations observed in the unadjusted model of DBP were noted to be documented loci responsive to tobacco smoking CpG sites, for example, (cg05575921 [30], cg12803068 [31], cg03636183 [32], cg22132788 [33] and cg09935388 [34]), hence their attenuation on adjustment for smoking was predictable. This highlights the capacity of DNA methylation to index exposure to relevant risk factors.

We found three CpG sites associated with DBP in Europeans. One CpG site (cg04751533), in the gene body of AFAP (actin filament-associated protein), acts as an actin-binding and crosslinking protein and is enriched in SRC and phorbol ester induced podosomes [35]. Podosomes are specialized plasma-membrane actin-based microdomains and have been suggested to play a role in arterial vessel remodeling [36]. C12orf44 (cg00006122) encodes autophagy-related protein 101 that is also known as ATG101. ATG101 is an autophagy related protein, with relevance to blood pressure because autophagy plays a key role in pulmonary vascular remodelling via regulation of apoptosis and hyperproliferation of pulmonary arterial endothelial cells [37]. ATG101 is an essential gene for the initiation of autophagy and may be involved in endothelial cell growth through regulation of autophagy in pulmonary hypertension [37]. CEBPD (cg16241714) encodes CCAAT/enhancer binding protein delta. CEBPD is involved in the regulation of apoptosis and cell proliferation and there is evidence that it might acts as tumour suppressor [38].

We compared the results of trans-ancestry analyses to previously reported EWAS of BP. Although the current study is smaller in size, we found evidence of some overlap between our results and the recent EWAS. Our study is the first blood pressure EWAS to our knowledge that has included South Asians, offering the chance to compare results from European and South Asian individuals.

There was no consistency in the magnitude and direction of associations comparing Europeans to South Asians, suggesting that peripheral blood DNA methylation patterns may differ between Europeans and South Asians in relation to blood pressure. This may reflect the fact that DNA methylation could index exposure to a different suite of risk factors in the two ethnic groups, or that different mechanisms contribute to the pathogenesis of hypertension and its related phenotypic traits. Of note, the South Asian participants in the Southall and Brent REvisited (SABRE) study are first generation migrants, arriving in the UK as young adults. The potential early life and developmental antecedents of hypertension and blood pressure will therefore be considerably different between the two ethnic groups. This may explain to some extent the lack of consistency in methylation variable loci observed between the two ethnic groups. However, the study has limited statistical power due to the relatively modest sample size for these analyses and would benefit from replication in another sample of South Asian ancestry.

Where associations were observed, the effect sizes were modest in size between cases and controls at the identified CpG sites. Such differences are unlikely to have profound biological consequences but may in turn exert a polygenic-like effect, altering disease risk or trait characteristics by small amounts. Further work is required to understand the functional consequences of such subtle shifts in DNA methylation.

We carried out DMR analysis and identified a large number of DMRs for SBP and DBP in the trans-ancestry, European and South Asian subgroups. The analyses found support for some of the DMRs for CVD related traits in the literature including BP [17], myocardial infarction [18]¸ dilated cardiomyopathy [19] and stroke [23]. There was some overlap between DMRs (mapped to genes) of SBP and DBP analyses conducted for South Asian and European groups. For SBP, there were three genes in common (WRN, PTPRN2 and CACNA1A). There is evidence that WRN (Werner syndrome RecQ like helicase) protein plays an important role in DNA repair and in DNA replication[39, 40]. A previous study has shown that cells lacking WRN exhibit deletion of telomeres from single sister chromatids[41]. PTPRN2 (protein tyrosine phosphatase, receptor type, N polypeptide 2) encodes a major autoantigen of relevance to type 1 diabetes [42, 43]. The CACNA1A (calcium voltage-gated channel subunit alpha1 A) is located on chromosome 19p13 that encodes the main subunit (1A) of the neuronal P/Q type voltage-gated calcium-ion channel[44]. Mutations in this gene have been associated with various neurological phenotypes [44]. For DBP, there was one DMR in common between South Asian and European groups (PRDM16). PRDM16 (histone-lysine N-methyltransferase PRDM16) functions as a transcriptional regulator[45] and a previous study confirmed a causal role for this locus in human myocardial disease [19].

The strengths of this study include the study design where participants were from two different ethnicities; European and South Asian that were analysed collectively and individually using robust statistical methods. Additionally, the utilisation of HM450 arrays provided good coverage of the genome in terms of known annotated genes (although in total only covers <2% of all CpGs). The relatively modest sample size, the utilisation of only male participants and measurement of BP twice are among the limitations of this work.

Conclusion

In conclusion, we identified associations between methylation and DBP across trans-ancestry and European-specific analyses. Lack of associations identified in South Asian specific analyses indicates that the associations between methylation and blood pressure may be different between European and South Asian populations.

Methods

Participant’s information

SABRE is a population-based cohort including 4,857 people of European, South Asian and African Caribbean origin aged 40 to 69 living in West London, UK [46]. Peripheral blood samples were collected from the Southall participants at baseline (1988–91) for DNA extraction.

In the current analysis, 800 (400 European and 400 South Asian) samples from the SABRE cohort were randomly selected from available baseline samples of good DNA quality. Some samples were removed from the data set during quality control procedures and some samples were excluded due to missing information. After exclusion, 712 (364 European and 348 South Asian) individuals remained. We utilised EPISTRUCTURE[47] to conduct principal component analysis on a subset of 4913 genetically informative methylation probes. We were able to clearly differentiate between self-reported European and South Asian individuals. We did not identify any evidence of population substructure or admixture within either self-reported ancestral group.

These 712 individuals did not have known diabetes or coronary heart disease at baseline and were stratified by four-year age group and ethnicity. The SABRE study predominantly focused on the recruitment of men[46], for that reason epigenetic analyses were restricted to male participants.

Ethnicity in the SABRE cohort was assigned based on grand-parental origins from participant questionnaire. Blood pressure was measured on one occasion (the average of 2 consecutive readings) in the baseline research clinic as described previously [46].

All participants gave written informed consent. Approval for the baseline study was obtained from Ealing, Hounslow and Spelthorne, Parkside and University College London research ethnics committees. Characteristics of participants are shown in Table 3.

Table 3

Distributions of study characteristics included in the EWAS analysis of SBP, DBP and hypertension.

	Trans-ancestry	European	South Asian	P-value
N	712(100%)	364(51.12%)	348(48.88%)
Hypertension cases	126(100%)	54(42.86%)	72(57.14%)	0.02*
SBP	122.7(10.6)	122.0(10.7)	123.5(10.3)	0.24
DBP	78.4(17.4)	76.8(18.1)	80.0(16.6)	8.3×10−5
Age (years)Mean (SD)	51(7.1)	52(7.2)	51(7.0)	0.06
BMI (kg/m2)mean (SD)	25.8(3.5)	26.0(3.3)	25.7(3.6)	0.3
Smokers (ever smokers)	361(100%)	112(31.02%)	266(73.68%)	<0.001*
Social class (Manual)	473(100%)	264(55.81%)	231(48.84%)	0.15*

P-value: t-test for differences between European and South Asian groups and

*P-value = Fisher’s exact test.

Traits of interest

We investigated SBP, DBP and hypertension as our traits of interest. Hypertension was defined as occurrence of SBP≥140 mm Hg and/or DBP≥90 mm Hg, or receiving medication for hypertension as described previously [46]. The BP protocol was based on the INTERSALT study protocol [48].

Covariates

Models were adjusted for age (years), body mass index (BMI) (kg/m2), ethnicity (European or South Asian for trans-ancestry analyses), smoking status (never or ever smoking) and social class (manual or non-manual occupation). Age, ethnicity, smoking status and social class of participants were collected from questionnaires. BMI was calculated from clinic measures of height and weight.

DNA methylation and pre-processing

DNA was bisulfite converted using the Zymo EZ DNA Methylation™ kit (Zymo, Irvine, CA). Following conversion, DNA methylation was measured using the HM450 BeadChip in line with standard protocols at the University of Bristol, UK [49].

Samples failing QC (average probe detection p value≥0.01) were repeated and if unsuccessful excluded from further analysis. BeadChip intensity data were converted to β-values using the minfi package [50] in the R statistical programming language. Methylation beta values range from 0 (no cytosine methylation) to 1 (completely cytosine methylated). Raw beta values were normalised using the Functional Normalisation method of the minfi package [51]. We excluded control probes (n = 65), any probes with a detection p-value > 0.05 in more than 5% samples, non-CpG probes, polymorphic probes (defined as SNP-overlapping probes, probes with a SNP at the target CpG site, or probes with a SNP at the base next to the target CpG) and probes with a minor-allele frequency (MAF) ≥ 5%; based on UCSC common SNPs track for dbSNP build 137. We further excluded probes that are considered as cross-hybridizing [52]. We applied this stringent CpG filtering because polymorphic and cross-hybridizing probes can interfere with accurate detection of methylation levels. After excluding these features, 402,331 probes remained for the analysis.

Estimation of cell counts

Cell count estimates were derived using the reference-based Houseman method [53] in the R minfi package [50] using the Reinius et al. dataset as reference [54]. This method estimates the relative proportions of six white blood cell subtypes (CD4+ T-lymphocytes, CD8+ T-lymphocytes, NK (natural killer) cells, B-lymphocytes, monocytes and granulocytes).

Statistical analyses

Epigenome-wide association study (EWAS) analysis

We considered a trans-ancestry analysis as the primary model because this provided maximal statistical power by enabling us to include all participants. Our primary hypothesis was that the potential epigenetic mechanisms of elevated blood pressure would be different across these two ethnicities. However, we postulated that these differences may be common to key loci, rather than being at completely different loci.

Three sets of EWAS analyses were run to identify CpG sites associated with either SBP, DBP or hypertension. Normalised, untransformed beta-values, which are on a scale of 0 (completely unmethylated) to 1 (completely methylated) were utilised. Multiple linear regression models were run to evaluate the association between traits of interest and DNA methylation. Analyses were run for each ethnic subgroup and with all samples combined in a trans-ancestry analysis. To remove potential batch effects, principal components (PCs) were generated from methylation beta values using Principal Component Analysis (PCA) [55-57]. The PCs were generated for trans-ancestry and for individual ethnicities separately. The first four PCs were included as covariates in each of the EWAS. These PCs were not associated with exposure (i.e. SBP, DBP and hypertension) and captured 27%,27% and 28% of the variance for trans-ancestry, Europeans and South Asians respectively.

Two models were run for each trait of interest: i) an unadjusted model and ii) a model adjusted for confounders (age, BMI, ethnicity (where appropriate), smoking status, social class (occupational status according to the 1980 Registrar Generals classification of occupation; non manual or manual)), estimated cell counts (n = 6) and PCs. We adjusted for the confounders which we a priori selected on the basis that it was plausible they would influence blood pressure and blood DNA methylation[58].

The genomic inflation factor (lambda) was computed and Manhattan plots were generated to compare the genome wide distribution of p-values in EWAS. CpG sites with Bonferroni-corrected p-value<1.24×10−07 were considered to be associated with the trait of interest. We considered the fully adjusted trans-ancestry models as the primary analysis models.

Differentially methylated region analysis

In addition to EWAS analyses, differentially methylated region (DMR) analyses in relation to SBP, DBP and hypertension were conducted separately using the R package DMRcate [59]. In the DMR analysis, normalised, untransformed beta-values were used and the models were adjusted for confounders, estimated cell counts and PCs. DMRcate groups associated probes into separate DMRs if the gap between nucleotides is ≥1000 base pairs. P-values for associations were adjusted for multiple testing using the BH method and by the DMRcate algorithm.

Pathway analyses were carried out using the reactome (https://reactome.org/) to test the genes mapped for DMRs for enrichment of certain biological pathways.

Comparison with previous EWAS

A large EWAS study of SBP and DBP was recently conducted in amongst individuals of European, African American and Hispanic/Latino ancestry (n = 17,101) [16]. The study conducted an overall meta-analysis of the discovery and replication cohorts and identified 126 CpG sites associated with BP after Bonferroni correction (p-value<1.0 × 10−7). We compared our EWAS results of SBP and DBP of trans-ancestry analysis to this previously published EWAS of SBP and DBP.

This file has 25 supplementary tables.

(XLSX)

Click here for additional data file.

File has results of EWAS of diastolic blood pressure for trans-ancestry analyses (i.e. both ethnic groups combined).

(ZIP)

Click here for additional data file.

File has results of EWAS of systolic blood pressure for trans-ancestry analyses (i.e. both ethnic groups combined).

(ZIP)

Click here for additional data file.

File has results of EWAS of hypertension for trans-ancestry analyses (i.e. both ethnic groups combined).

(ZIP)

Click here for additional data file.

File has results of EWAS of diastolic blood pressure for South Asian analyses.

(ZIP)

Click here for additional data file.

File has results of EWAS of systolic blood pressure for South Asian analyses.

(ZIP)

Click here for additional data file.

File has results of EWAS of hypertension for South Asian analyses.

(ZIP)

Click here for additional data file.

File has results of EWAS of diastolic blood pressure for European analyses.

(ZIP)

Click here for additional data file.

File has results of EWAS of hypertension for European analyses.

(ZIP)

Click here for additional data file.

File has results of EWAS of systolic blood pressure for European analyses.

(ZIP)

Click here for additional data file.

4 Sep 2019

PONE-D-19-20995

Associations Between High Blood Pressure and DNA Methylation

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: While this study analyzes an under represented group, the manuscript is a little unclear and could use a few more edits for readability. The authors identify one trans-specific site and a few European specific sites. They in addition found some DMR associated with SBP and DBP.

Comments

Major

----

-Did the authors examine if there was any genetic admixture within the South Asian participants that could impact the results? Perhaps look at some of the methods that have developed over past years for getting at population structure from DNA methylation.

-The authors mention the unadjusted results throughout the document but I do not think that this should be highlighted as for a result to pass EWAS threshold needs to be significant adjusting for all these known confounders.

-What does cg07598370 effect look like in each of the populations?

-Line 192: For the goodness of fit R2. There will likely be good concordance amongst the trans-ancestry and the respective ethnic specific analysis as those European participants or South-Asian participants were included in the trans-ancestry analysis. Would remove and just focus on the South-Asian to European Ancestry. Did the authors examine the spearman correlation? Or examine the correlation of the test statistics.

The document could use some grammatical work, just going through and checking the sentence structure throughout.

Minor

--

-Line 77: “We planned to analyze” Don’t say planned, say we analyzed. Keep tense consistent.

Line 83: Have brief paragraph describing the study participants and place Table 1 here. Otherwise Table 1 is referred to prior to Table 2.

Line 261- Reword sentence. Change “The” to “A”

Line 276-Get rid of second AFB

Line 281- Typo? “related protein likewise many other proteins”

Line 288- Do not say probably. Perhaps say “evidence associated with”.

Line 288- “CD59 (CD59, molecule (CD59, blood group), cg0635652)”. Reword/organize. Part is confusing.

Line 290- Reword “blood coagulation... among its biological pathways”. Reads as though has possession of those pathways. Perhaps say “Gene is known to be related to pathways of…”

Line 298- Reword. Say EWAS twice in one sentence.

Mention that first generation earlier in the document.

Line 348-350: Two repetitive sentences that the study is male.

Line 398: Statistical analysis. Is DNA methylation the dependent variable?

Reviewer #2: In this article, the authors examine the association of DNA methylation with hypertension and continuous blood pressure in both European-descent and South-Asian descent men. The sample size is fairly large, and the analytical plan is carefully described and conducted. The results provide data on a seldom described population in cardiovascular epigenetics that enriches this field of research.

My only major comment is to highlight and emphasis the results of the DMR analysis more. The results of the CpG site-specific analysis take center stage, especially when summarizing main conclusions in the abstract, discussion, and conclusion section and also in the main figures. The DMR analyses reveal quite a few long DMRs in interesting genes. Discovery of DMRs are potentially more informative than single CpG sites which alone may not be very biologically relevant. Can the authors dig into the DMRs more – perhaps providing a Venn Diagram of overlapping genes between the 3 analysis groups for DMRs? Or running a pathway analysis on the genes that show up as q<0.05 in the DMR analysis? Also please explain how q<0.05 is calculated for the DMRs in the methods (is this through the DMRcate algorithm or separately calculated?)

A few minor suggestions are also noted:

-Ln 86 to 91: When discussing these sites, it would be helpful to readers to put together the ones that are in the same genes. Same comment for Ln 137-144.

-Figures 1 and 2 should include indication of which CpG sites passed the significance cut-off used for this study (q<0.05) since the Bonferonni cut-off is mentioned used in the discussion or methods.

-Ln 263: Expand upon this (how do olfactory receptors regulate blood pressure by the kidney)?

-Overall proof-reading/editing of the discussion section is needed.

-Is there any longitudinal data on these participants or only cross-sectional blood pressure?

-Ln 415: What is considered the exposure here? Does that mean the outcome (e.g., blood pressure)?

-Ln 418-420: How were these covariates selected? What is the social class variable? Which cell types were included in the models (all 6 or a subset of them?)

-Table 3: Please denote if there is overlap between trans-ancestry and European and/or South Asian models in these genes lists (example: HLX. The authors could be a symbol by it that denotes overlap).

-Table 1 should include percentages along with numbers for the categorical variables.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Jaclyn Goodrich

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

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18 Oct 2019

Manuscript: Associations Between High Blood Pressure and DNA Methylation

Reviewer #1 comments and response from authors:

While this study analyzes an under represented group, the manuscript is a little unclear and could use a few more edits for readability. The authors identify one trans-specific site and a few European specific sites. They in addition found some DMR associated with SBP and DBP.

Specific comments:

Comment 1: Did the authors examine if there was any genetic admixture within the South Asian participants that could impact the results? Perhaps look at some of the methods that have developed over past years for getting at population structure from DNA methylation.

Response: We thank the reviewer for this comment. We have utilised EPISTRUCTURE (https://epigeneticsandchromatin.biomedcentral.com/articles/10.1186/s13072-016-0108-y) to conduct principal component analysis on a subset of 4913 genetically informative methylation probes. We were able to clearly differentiate between self-reported European and South Asian individuals. We did not identify any evidence of population substructure or admixture within either self-reported ancestral group. We have added few sentences to the main text of the paper to communicate this point.

“We utilised EPISTRUCTURE(54) to conduct principal component analysis on a subset of 4913 genetically informative methylation probes. We were able to clearly differentiate between self-reported European and South Asian individuals. We did not identify any evidence of population substructure or admixture within either self-reported ancestral group.” (page:19; lines: 401-405)

Comment 2: The authors mention the unadjusted results throughout the document but I do not think that this should be highlighted as for a result to pass EWAS threshold needs to be significant adjusting for all these known confounders.

Response: We agree with reviewer and have deleted the unnecessary text emphasising unadjusted EWAS results. Please see the Results section; pages 5-8.

Comment 3: What does cg07598370 effect look like in each of the populations?

Response: The mean (SD) of this CpG in European is 0.84 (0.07) and in South Asian population is 0.83 (0.05). We have added this information to the manuscript:

“However, one additional CpG site (cg07598370 near OR5AP2) was identified in the adjusted EWAS, below the Bonferroni-corrected threshold (Figure 1 and Supplementary File 1, Table S4). DBP was associated with lower DNA methylation at this CpG site with a 0.1% decrease in DNA methylation per 1 mmHg increase in DBP. The mean and standard deviation (SD) of DNA methylation at this CpG site in the European group was 0.84 (0.07) and in the South Asian group was 0.83 (0.05).” (page:6; lines:111-117)

Comment 4: Line 192: For the goodness of fit R2. There will likely be good concordance amongst the trans-ancestry and the respective ethnic specific analysis as those European participants or South-Asian participants were included in the trans-ancestry analysis. Would remove and just focus on the South-Asian to European Ancestry. Did the authors examine the spearman correlation? Or examine the correlation of the test statistics.

Response: We recognise this duplication in data sources when considering this issue and have now removed the comparisons made between trans-ancestry and the European and South Asian ancestry groups but kept the comparisons made between individual ethnicities.

In answer to second point, there was a linear fit between European and South Asian participants data. We have now revised the text in the manuscript accordingly:

“The magnitude of associations between European and South Asian populations taken from the fully adjusted EWAS of SBP, DBP and hypertension were compared to each other using a linear fit and a random intercept and slope multilevel model in a pair-wise comparison.” (page 10; lines: 205-208)

Minor comments

The document could use some grammatical work, just going through and checking the sentence structure throughout.

Response: We have revised the grammar throughout the manuscript.

Comment 1: Line 77: “We planned to analyze” Don’t say planned, say we analyzed. Keep tense consistent.

Response: We have revised the sentence as suggested:

“We analyzed all samples together in a trans-ancestry analysis, then conducted analyses in each ethnic group separately.” (page 4; lines: 81-82)

Comment 2: Line 83: Have brief paragraph describing the study participants and place Table 1 here. Otherwise Table 1 is referred to prior to Table 2.

Response: Thank you for pointing out this mistake. We have now corrected the order of the Tables and their referral.

Comment 3: Line 261- Reword sentence. Change “The” to “A”

Response: We have revised the sentence accordingly:

“A genetic variant near the olfactory receptor, family 5, subfamily AP, member 2 (OR5AP2) has been previously reported to be associated with hematological phenotypes (27), in addition olfactory receptors are known to regulate blood pressure via their renal expression (28).” (page:14; lines: 293-97)

Comment 4: Line 276-Get rid of second AFB

Response: We believe that the reviewer meant AFAP, we have removed the second occurrence of this from the revised draft:

“One CpG site (cg04751533), in the gene body of AFAP (actin filament-associated protein), acts as an actin-binding and crosslinking protein and is enriched in SRC and phorbol ester induced podosomes (35).” (page: 15; lines: 311-314)

Comment 5: Line 281- Typo? “related protein likewise many other proteins”

Response: We have reworded the sentence:

“ATG101 is an autophagy related protein, with relevance to blood pressure because autophagy plays a key role in pulmonary vascular remodelling via regulation of apoptosis and hyperproliferation of pulmonary arterial endothelial cells (37).”(page: 15; lines: 317-321)

Comment 6: Line 288- Do not say probably. Perhaps say “evidence associated with”.

Response: The sentence has been revised:

“CEBPD is involved in the regulation of apoptosis and cell proliferation and there is evidence that it might acts as tumour suppressor (38).” (page: 15; lines: 323-325)

Comment 7: Line 288- “CD59 (CD59, molecule (CD59, blood group), cg0635652)”. Reword/organize. Part is confusing.

Response: This sentence has been removed from the revised draft.

Comment 8: Line 290- Reword “blood coagulation... among its biological pathways”. Reads as though has possession of those pathways. Perhaps say “Gene is known to be related to pathways of…”

Response: This sentence has been removed from the revised draft.

Comment 9: Line 298- Reword. Say EWAS twice in one sentence.

Response: The sentence has been revised:

“We compared the results of trans-ancestry analyses to previously reported EWAS of BP.” (page: 16; line:334-335)

Comment 10: Mention that first generation earlier in the document.

Response: We believe the reviewer is referring to the section: “Of note, the South Asian participants in the Southall and Brent REvisited (SABRE) study are first generation migrants, arriving in the UK as young adults. The potential early life and developmental antecedents of hypertension and blood pressure will therefore be considerably different between the two ethnic groups.”

This is the first time that SABRE was mentioned in the document as, per PLOS guidelines, the Methods section is placed after the Discussion. We have inserted a short sentence in the Abstract to alert readers to this fact much earlier in the manuscript:

“We analyzed samples from 364 European and 348 South Asian men (first generation migrants to the UK) from the Southall And Brent REvisited cohort..” (page:2; lines: 43-44)

Comment 11: Line 348-350: Two repetitive sentences that the study is male.

Response: We have removed the sentence “All individuals were male” to avoid repetition. (page 19)

Comment 12: Line 398: Statistical analysis. Is DNA methylation the dependent variable?

Response: Yes, DNA methylation is a dependent variable.

Reviewer #2 comments and response from authors:

In this article, the authors examine the association of DNA methylation with hypertension and continuous blood pressure in both European-descent and South-Asian descent men. The sample size is fairly large, and the analytical plan is carefully described and conducted. The results provide data on a seldom described population in cardiovascular epigenetics that enriches this field of research.

Specific comments:

My only major comment is to highlight and emphasis the results of the DMR analysis more. The results of the CpG site-specific analysis take center stage, especially when summarizing main conclusions in the abstract, discussion, and conclusion section and also in the main figures. The DMR analyses reveal quite a few long DMRs in interesting genes. Discovery of DMRs are potentially more informative than single CpG sites which alone may not be very biologically relevant. Can the authors dig into the DMRs more – perhaps providing a Venn Diagram of overlapping genes between the 3 analysis groups for DMRs? Or running a pathway analysis on the genes that show up as q<0.05 in the DMR analysis? Also please explain how q<0.05 is calculated for the DMRs in the methods (is this through the DMRcate algorithm or separately calculated?)

Response: We thank the reviewer for this comment. We have now provided more details about the DMR analyses. We have created Venn diagrams to show the overlap between the DMRs identified in the different ethnic groups and have revised the manuscript accordingly.

Results:

“We created Venn diagrams to identify overlap between DMRs (mapped to genes) of SBP and DBP analyses conducted for South Asian and European groups (Figure 4). For SBP, there were three genes in common (WRN, PTPRN2 and CACNA1A). For DBP, there was one DMR in common between South Asian and European groups (PRDM16).

Figure 4. Venn diagrams to identify overlap between DMRs (mapped to genes) of DBP (A) and SBP (B) analyses conducted for South Asian and European groups.

Figure 4. SA denotes South Asian and Eu denotes European ancestry.” (pages: 12-13; lines:251-258)

Discussion:

“There was some overlap between DMRs (mapped to genes) of SBP and DBP analyses conducted for South Asian and European groups. For SBP, there were three genes in common (WRN, PTPRN2 and CACNA1A). There is evidence that WRN (Werner syndrome RecQ like helicase) protein plays an important role in DNA repair and in DNA replication(46, 47). A previous study has shown that cells lacking WRN exhibit deletion of telomeres from single sister chromatids(48). PTPRN2 (protein tyrosine phosphatase, receptor type, N polypeptide 2) encodes a major autoantigen of relevance to type 1 diabetes (49, 50). The CACNA1A (calcium voltage-gated channel subunit alpha1 A) is located on chromosome 19p13 that encodes the main subunit (1A) of the neuronal P/Q type voltage‐gated calcium‐ion channel(51). Mutations in this gene have been associated with various neurological phenotypes (51). For DBP, there was one DMR in common between South Asian and European groups (PRDM16). PRDM16 (histone-lysine N-methyltransferase PRDM16) functions as a transcriptional regulator(52) and a previous study confirmed a causal role for this locus in human myocardial disease (19). ” (pages: 17-18; lines: 361-376)

In answer to “please explain how q<0.05 is calculated for the DMRs in the methods (is this through the DMRcate algorithm or separately calculated?)”

Response: Yes, it was calculated within the DMRcate algorithm. We have added a sentence to the Methods section:

“P-values for associations were adjusted for multiple testing using the BH method and by the DMRcate algorithm.” (page 23; lines:497-498)

Minor comments

Comment 1: Ln 86 to 91: When discussing these sites, it would be helpful to readers to put together the ones that are in the same genes. Same comment for Ln 137-144.

Response: In response to Reviewer 1’s comment (comment #2) we have deleted these lines from the revised draft.

Comment 2: Figures 1 and 2 should include indication of which CpG sites passed the significance cut-off used for this study (q<0.05) since the Bonferonni cut-off is mentioned used in the discussion or methods.

Response: We have revised the legends of the figures indicating that CpGs that were above the red line were considered to be associated with the trait. We have revised the text in Results section accordingly.

“The blue line is drawn to separate the CpG sites that surpassed p-value<1×10-05, a threshold for a suggestive association and the red line to separate the CpG sites that surpassed the Bonferroni-corrected threshold (p-value<1.24×10-07). The CpG sites that surpassed the Bonferroni-corrected threshold were considered to be associated with the trait.”

Comment 3: Ln 263: Expand upon this (how do olfactory receptors regulate blood pressure by the kidney)?

Response: We have provided more detail:

“A genetic variant near the olfactory receptor, family 5, subfamily AP, member 2 (OR5AP2) has been previously reported to be associated with hematological phenotypes (27), in addition olfactory receptors are known to regulate blood pressure via their renal expression (28). Evidence has shown that renal sensory receptors play an important role in blood pressure regulation and olfactory receptors belonging to this group of sensory receptors(29).” (page: 14; lines: 293-99)

Comment 4: Overall proof-reading/editing of the discussion section is needed.

Response: We have proof-read and corrected the grammar throughout the manuscript.

Comment 5: Is there any longitudinal data on these participants or only cross-sectional blood pressure?

Response: The SABRE cohort underwent a follow up clinic approximately 17 years after the baseline study. We collected methylation profiles on <20% of follow up samples corresponding with the baseline samples included in our main analysis. Because the sample size was small (therefore limiting statistical power), we did not conduct longitudinal analyses on these data.

Comment 6: Ln 415: What is considered the exposure here? Does that mean the outcome (e.g., blood pressure)?

Response: We apologise for any confusion; our outcome is DNA methylation and exposures are systolic, diastolic blood pressure and hypertension. We have revised the text in the manuscript to make this clearer:

“The first four PCs were included as covariates in each of the EWAS. These PCs were not associated with exposure (i.e. SBP, DBP and hypertension) and captured 27%,27% and 28% of the variance for trans-ancestry, Europeans and South Asians respectively.” (pages: 22-23; lines: 475-478)

Comment 7: Ln 418-420: How were these covariates selected? What is the social class variable? Which cell types were included in the models (all 6 or a subset of them?)

Response: We adjusted for the confounders which we a priori selected on the basis that it was plausible they would influence blood pressure and blood DNA methylation.

Social class represents occupational status according to the 1980 Registrar General’s classification of occupation (i.e. non manual or manual) and all six cell types were included in the model.

We have revised the text in the manuscript accordingly:

“Two models were run for each trait of interest: i) an unadjusted model and ii) a model adjusted for confounders (age, BMI, ethnicity (where appropriate), smoking status, social class (occupational status according to the 1980 Registrar Generals classification of occupation; non manual or manual)), estimated cell counts (n=6) and PCs. We adjusted for the confounders which we a priori selected on the basis that it was plausible they would influence blood pressure and blood DNA methylation(65).” (page: 23; lines: 460-65)

Comment 8 -Table 3: Please denote if there is overlap between trans-ancestry and European and/or South Asian models in these genes lists (example: HLX. The authors could be a symbol by it that denotes overlap).

Response: We have denoted the overlap between results of trans-ancestry and European analyses by * and between trans-ancestry and South Asian by **. We have provided this information in the legend of Table 2:

“* when a gene is common between trans-ancestry and European analyses, ** when a gene is common between trans-ancestry and South Asian analyses.” (page: 12; lines: 241-242)

Comment 9 -Table 1 should include percentages along with numbers for the categorical variables.

Response: We have provided the percentages. In the revised manuscript Table 1 is now Table 3. (page: 20)

Submitted filename: Rebuttal letter.docx

Click here for additional data file.

12 Nov 2019

PONE-D-19-20995R1

Associations Between High Blood Pressure and DNA Methylation

PLOS ONE

Dear Dr Kazmi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Heming Wang, PhD

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have sufficiently addressed my previous questions and the paper is much improved. I only have a few remaining minor comments/questions.

--Line 187. Differentially methylated region analysis.

I know the authors found four regions of overlap, but I was wondering if the authors looked to see if the other discrepant regions happened to fall in similar pathways?

--Line 216.

This is more of a formatting issue. "Known genetic variants in DMRs" is on the same line as Figure 4 legend.

--Line 370

When were the traits measured? Were they also at baseline?

Reviewer #2: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Jaclyn Goodrich

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

18 Dec 2019

Manuscript: Associations Between High Blood Pressure and DNA Methylation

Reviewer #1:

Comment 1: Line 187. Differentially methylated region analysis. I know the authors found four regions of overlap, but I was wondering if the authors looked to see if the other discrepant regions happened to fall in similar pathways?

Response: Now, we have performed the pathway analyses and revised the manuscript accordingly.

Results:

“We performed pathway analyses for the genes mapped for DMRs of SBP and DBP analyses conducted for South Asian and European groups. For SBP analyses conducted for Europeans and DBP analyses conducted for South Asians, we identified pathways enriched with FDR q-value<0.05. The identified pathways for SBP analyses conducted for Europeans were NOTCH2 intracellular domain regulates transcription and NOTCH4 intracellular domain regulates transcription. The identified pathway for DBP analyses conducted for South Asians was insulin-like growth factor-2 mRNA binding proteins (IGF2BPs/IMPs/VICKZs) bind RNA.”(pages:11-12; lines: 217-224)

Methods:

“Pathway analyses were carried out using the reactome (https://reactome.org/) to test the genes mapped for DMRs for enrichment of certain biological pathways.”(page:22; lines: 452-453)

Comment 2: Line 216. This is more of a formatting issue. "Known genetic variants in DMRs" is on the same line as Figure 4 legend.

Response: We have corrected the formatting issue. Please see line 226 on page 12.

Comment 3: Line 370. When were the traits measured? Were they also at baseline?

Response: Yes, please see:

“Blood pressure was measured on one occasion (the average of 2 consecutive readings) in the baseline research clinic as described previously (46).” (pages 17-18; lines: 366-367)

Submitted filename: Rebuttal letter.docx

Click here for additional data file.

30 Dec 2019

Associations Between High Blood Pressure and DNA Methylation

PONE-D-19-20995R2

Dear Dr. Kazmi,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

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With kind regards,

Heming Wang, PhD

Academic Editor

PLOS ONE

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Reviewers' comments:

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Reviewer #1: (No Response)

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Reviewer #1: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

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Reviewer #1: (No Response)

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Reviewer #1: Yes

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Reviewer #1: The authors have addressed all of my comments. Minor formatting/grammar comment: Line 145: "theEWAS"-> "the EWAS".

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Reviewer #1: No

13 Jan 2020

PONE-D-19-20995R2

Associations Between High Blood Pressure and DNA Methylation

Dear Dr. Kazmi:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Heming Wang

Academic Editor

PLOS ONE