Genome-Wide Association Study on Blood Pressure Traits in the Iranian Population Suggests ZBED9 as A New Locus for Hypertension.

doi:10.21203/rs.3.rs-120994/v1

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Genome-Wide Association Study on Blood Pressure Traits in the Iranian Population Suggests ZBED9 as A New Locus for Hypertension.

https://doi.org/10.21203/rs.3.rs-120994/v1

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High blood pressure is the heritable risk factor for cardiovascular and kidney diseases. Genome-wide association studies(GWAS) on blood pressure traits increase our understanding of its underlying genetic basis. However, a large proportion of GWAS was conducted in Europeans, and some roadblocks deprive other populations to benefit from their results. Iranians population with a high degree of genomic specificity has not been represented in international databases to date, so to fill the gap, we explored the effects of 652,919 genomic variants on Systolic Blood Pressure(SBP), Diastolic Blood Pressure(DBP), and Hypertension(HTN) in 7,694 Iranian adults aged 18 and over from Tehran Cardiometabolic Genetic Study(TCGS). We identified consistent signals on ZBED9 associated with HTN in the genome-wide borderline threshold after adjusting for two different sets of environmental predictors(P value=2.21×10^-7). Moreover, strong signals on ABHD17C and suggestive signals on FBN1 were detected for DBP and SBP, respectively, while these signals were not consistent in different GWA analysis. Our finding on ZBED9 was confirmed for all BP traits by linkage analysis in an independent sample. Although there is no strong evidence to support the function of ZBED9 in blood pressure regulation, it provides new insight into the pleiotropic effects of hypertension and other cardiovascular diseases.

Cardiac & Cardiovascular Systems

Epidemiology

GWAS

Blood pressure

Hypertension

cardiovascular diseases

Iran

High blood pressure as a heritable risk factor with direct and indirect effects on the incidence of cardiovascular diseases (CVD), stroke, and chronic renal failure is the leading cause of morbidity and mortality worldwide. [1, 2]. In the analysis of world data, one in three adults is expected to be affected by high blood pressure up to 2025, while macro or microvascular complications are not limited to extreme ranges of systolic and diastolic blood pressures (SBP and DBP)[3]. Elevated BP is categorized into primary and secondary hypertension based on disease etiology. While the latter is secondary due to other diseases, some medications, and related side effects, the former is known as essential hypertension and is prevalent in all populations [4, 5].

Genetic and environmental risk factors such as age, obesity, and lifestyle are attributed to the heterogeneity of essential hypertension risk in the general population [6, 7]. Emerging new genotyping technologies has facilitated studies with Genome-Wide Association (GWA) design in non-communicable and infectious diseases to detect risky or preventive genetic variants after adjusting for environmental risk factors. Promising results from these hypothesis-free studies addressing different pathophysiologic pathways and gene targets for future pharmacologic interventions in complex diseases [8].

Unlike brilliant genomic findings with replicated results for several complex traits, efforts to detect causative variants have not been translated into similar achievements in BP traits. In other words, the non-generality of GWAS findings on BP traits restrained the developing precision medicine in diverse populations with different genetic backgrounds [9, 10].

From the viewpoint of genomic architectures, different distribution of risk allele frequencies are contributed to the non-generality of findings between ethnicities [11]. A recent review addressed evidence concerning the origin of non-generality of GWAS findings on BP traits in different ethnic groups. Accordingly, a large proportion of GWAS was conducted in individuals with European ancestry, and it was introduced as a major cause of low reproducibility of findings in other populations [12].

In comparing super populations in 1 KG project including, Europeans, East Asians, South Asians, Africans and Hispanics, a large number of novel variants with a higher degree of genomic specificity were identified in the Iranian population [13]. However, the Iranian population has not been represented in international genomic databases to date, so there is no evidence concerning the effect(s) of genetic variants in regulating BP in this population. To fill the gap, we conducted the first study using GWA design to investigate the replication or discovery of genetic variants on the Iranian population's BP traits.

Study subjects: The Tehran Cardiometabolic Genetic Study (TCGS) is a family-based genetic analysis of the Tehran Lipid and Glucose Study (TLGS) as the oldest Iranian cohort. In total, more than 20,000 participants are followed in 7 phases since 1999 and underwent a clinical examination on more than 230 metabolic-related traits in each phase of the study. The Medical Ethics Committee of Shahid Beheshti University of Medical Sciences approved this study. All participants gave written informed consent to participate in the original cohort and TCGS. In the case of younger participants, written formal consent was obtained from the parents or guardians. Principles for clinical investigations could be found in the original TCGS and TLGS papers [14,15].

In the present study, 17,462 participants from the five phases of TCGS (1999-2014) were recruited to investigate hypertension. More details on DNA sample collection, genotype quality control process, phenotype measurements, covariate imputation, case definition, and selection criteria are explained in the supplementary.

Study Design: Based on critical points of BP changes in the age trajectory, all study subjects aged 18 or above were included in the present study, and average values of SBP and DBP during follow up visits were considered in GWA analysis. For binary trait analysis, HTN incident cases and a random sample of healthy individuals with two or more follow-up records were included in the analysis (Supplementary file, Figure S1, S2). Age, Body Mass Index (BMI), Waist Circumference (WC), and insulin resistance were included in both GWA analysis on quantitative and binary traits after imputing their missing values, using the Expectation-Maximization method with Bootstrapping (EMB) approach by Amelia package in R [16](Supplementary file, Figure S3).

Quality control of genotypes: To maximize power against the removal of individuals and markers, quality control (QC) of genotyping data was implemented on a per-individual basis before per-marker using PLINK version 1.9 and R [17]. Accordingly, a standard QC pipeline on 652,919 SNP, with an average mean distance of 4 kilobases, were performed in 7,694 adults after excluding Individuals with discordance of genetically inferred sex versus self-report, genotype rate ≤10%, missing phenotype, genotype failure rate≥3%, and high heterozygosity (F_statistics ± 3 standard deviation). Moreover, related subjects with Identity By Decent (IBD) ≥ 18.5% were excluded from the study. In genotype level variants with minor allele frequency (MAF) < 1%, missing genotype calls >5%, and Hardy Weinberg Equilibrium (HWE) with a P-value < 9×10^-6 in the presence of BP traits were filtered out (Supplementary file, Figure S4).

Statistical analysis: After checking collinearity for all covariates (r²>0.8), linear and logistic regression association tests were performed. Additive and overdominant inheritance models on autosomal chromosomes were checked for GWAS on the quantitative and binary traits in PLINK v1.9, respectively. A conventional genome-wide threshold of 5×10^-8 considered for a significant P-value. The genomic inflation factor was computed for each analysis, and observed versus expected P values were highlighted in the Q-Q plots to check for population stratification. Finally, four regression-based multivariate analyses evaluated the predictive accuracy of initial GWAS outputs for quantitative traits [18]. Accordingly, Polygenic Risk Score (PRS) was calculated after adjusting for the covariates, and the proportion of variance, which is explained by genomic variants (R²) was computed. Moreover, discrimination of PRS was assessed for each analysis according to sex.

Confirmation study: The confirmation study was conducted on 1618 participants in 210 selected TCGS families with an age range of 1 to 93 and familial aggregation of ≥ two affected (HTN) cases. Similar to initial GWAS, the QC processes were applied in the confirmation study. After removing Mendelian errors and pruning out SNPs in linkage disequilibrium (LD) with a correlation coefficient of >0.2, the effects of significant independent SNPs in the initial GWAS were tested in the presence of the same covariate sets using two-level Haseman-Elston regression model by SAGE version 6.4 [19].

Post GWAS: Three consecutive steps were followed to explain probable functions and pathophysiologic pathway(s) of discovered variants' effects on BP with P values less than 1×10^-4. In the first step, chromosomal coordinates, genes, transcripts, and variants on protein sequence were annotated in Ensemble Variant Effect Predicator [20]. In the second step, GWAS catalog information was retrieved to identify the association of specified loci on BP traits [21]. Moreover, we sought to map known BP loci by assessing these loci's functional consequences in Ensemble [22]. In the case of a similar locus, ldlink browser by National Cancer Institute was checked for LD of detected and previously reported variant(s) in three populations of South Asians, East Asians, and Europeans using the website (http://analysistools.nci.nih.gov/LDlink/). In the second step, a list of detailed information on all loci was retrieved separately in Open Targets POST GWAS, including disease associations, protein interactions, pathways, similar targets based on diseases in common, RNA, and protein baseline expression by the anatomical system and organ [23].In the final step, the overall association score was retrieved for each locus and other genes whose protein products interact with new loci through protein interaction networks [24,25]. Open Target Platform provided the score from 20 data sources, is ranged from 0 to 1, that the former implies no evidence and later corresponds to the most reliable evidence supporting evidence based on frequency, severity, and significance of association [26].

GWAS Datasets:

Table 1 describes the phenotypes and covariates characteristics in three datasets of discovery and confirmation studies. After applying DNA samples and genomic markers metrics, 4,657 individuals with 616,263 SNPs on the quantitative traits and 4,214 individuals with 616,308 SNPs on the HTN trait passed genotype QC. The discovery sample had a larger proportion of normotensive individuals, whereas the proportion of affected and unaffected cases was balanced in the confirmation study. Further, there was no significant difference between covariates in discovery and confirmation datasets, while high collinearity between BMI and WC was highlighted; hence, these effects were adjusted in two different sets of covariates (Supplementary file, Figure S5, Figure S6).

GWAS result

Table 2 describes GWAS findings in the discovery and confirmation studies. In a genome-wide analysis of quantitative traits, three signal on ABHD17C was detected for DBP corresponding to the genome-wide significance threshold. Moreover, suggestive signals within 6p22.1 (ZBED9) and FBN1 with borderline P values were detected with the HTN and SBP traits, respectively (Figure 1). Except for rs450630 on ZBED9 was associated with HTN by two different sets of covariates, the remained SNPs were merely associated after adjustment for WC. The test statistic of genomic inflation was low for both analyses on quantitative and binary traits (λ: 1.001-1.01), and there was no population stratification (Figure 2).

In the replication analysis for detected SNPs in initial GWAS, the association with SBP was replicated for rs2303505 on FBN1, while the association of rs450630 on ZBED9 was replicated for SBP, DBP, and HTN traits after LD pruning on other variants (P-value < 0.05). The associations of other genetic variants on ZBED9 with QRS amplitude and interval in Europeans and also ABHD17C and FBN1 with BP traits or cardiovascular diseases in Europeans and East Asians were previously reported in GWAS literature. However, there is no correlation (LD) between detected and previously reported genetic variants in the same locus. (Supplementary file, Figure S7).

Polygenic risk score estimation

Multivariate analysis of PRS on initial GWAS outputs showed evidence of association with SBP and DBP levels in three out of four models. The genomic variants account for 4.5%-12.7% of the total variance of quantitative traits (Figure 3-A). Moreover, a similar distribution of PRS-trait correlation was seen by sex for each statistical model in discrimination analysis (Figure 3-B).

Variant effects on protein-coding sequence

In the locus-based regulatory annotation, detected signals on ABHD17C and ZBED9 were annotated as an intronic variant. All detected SNPs on the FBN1 gene were in relatively high LD, while rs363830 and rs363838 were missense and splice variants. Also, two variants on ABHD17C were in moderate LD (r²:0.4-0.6). In further investigation via sentinel variants, we found rs853684 on ZSCAN31 as a missense consequence in moderate LD (r²>0.60) and five missense variants in perfect LD (r²=1.0) with detected variants on ZBED9 (Figure 4).

Prioritization of targets by scoring target-disease association

The cumulative evidence for association with BP traits for three detected loci was retrieved in the Open Targets POST GWAS. The overall association scores were summarized in figure 5, with varying blue shades: the darker the blue, the stronger the association. Two previously reported loci of FBN1 and ABHD17C to show evidence for a strong association with BP and cardiovascular disease traits, so they were prioritized as biological targets (Overall association score=1). Further, the protein interaction network suggests gene subnetworks for ZBED9 with relatively low association with BP and cardiovascular diseases (overall association score ≤0.40), respectively.

To our knowledge, this is the first GWAS to examine genetic associations with BP traits in the Iranian population. This study identified suggestive and strong signals on ZBED9, FBN1, and ABHD17C, associated with HTN, SBP, and DBP, respectively. There is no LD between detected and previously reported genetic variants on three loci in Europeans and other populations including, South Asian, Hispanic or Latin American, East Asian, African American, and Afro-Caribbean populations. The detected signals were not consistent after adjusting for two different sets of covariates on FBN1 and ABHD17C. On the other hand, the association of genetic variants on ZBED9 and BP traits has not been previously reported in other populations, while their effects were consistent after controlling for environmental factors by two different GWA analysis. Further, the confirmed association of genetic variants on ZBED9 in discovery study with SBP, DBP, and HTN in an independent sample of TCGS families substantially increase our knowledge of its effects on HTN in the Iranian population.

In an effort to explain the function of new loci by RNA and protein baseline expression, the rate of expression for all detected loci was in the range of low to moderate in the circulatory system, including blood, endothelial cells of the umbilical vein, aorta, coronary artery, left heart ventricle, tibial artery, atrium auricular region, and heart muscle, provided by Human Protein Atlas and Expression Atlas [26]. There is no evidence to support the direct effects of ZBED9 on BP regulation. However, GeneHancer-gene association results indicate some known BP loci, including EBF1, NR2F2, SOX5, and PRDM6, are likely acting as transcription factor binding sites or gene targets ZBED9 [28-31,35-39]. In this way, significant association with QRS interval and amplitude as a surrogate of myocardial mass in European population and replication with SBP, DBP and also HTN using different criteria based on reference adjusted curves in the Iranian children and adolescents [40], who was included in TCGS confirmation study is a signal for further investigations on the functional role of ZBED9 in BP regulation pathway in other populations.

High blood pressure is directly associated with vascular mortality due to stroke, cardiomyopathy, aneurysm, cardiac hypertrophy, aorta stenosis, sudden cardiac arrest, and myocardial infarction [41]. Accordingly, gene-set-based analysis by Open Target Post GWAS highlighted the probable pleiotropic effects of detected loci, which are likely acting as a common genetic etiology for BP and cardiovascular diseases. Accordingly, the lethal cardiovascular diseases may affect allele frequency of effective variants with advancing age in our study due to survival reduction, so overlook the effect of functional variants in older groups as a competing risk [42,43].

We acknowledge that some limitations are evident in our study. First, there is evidence for significant differences in the magnitude of genetic variants effects on high blood pressure between men and women [44]. However, there was inadequate statistical power to conduct GWAS by sex after removing related individuals in our study. Moreover, the calculated PRS for the quantitative traits showed similar patterns by sex. Second, despite the high predictive accuracy of PRS by genomic variants and confirm ten significant SNPs with family-based regression analysis, it was a case for overfitting due to selecting individuals with similar genetic background from the TCGS cohort. Accordingly, our findings should be cross-validated in an independent sample of the Iranian population, but such a sample was not available. Third, using a family-based design for GWAS has the advantages of complete robustness against genetic heterogeneity. However, family-based designs are likely biased due to population substructures, and association tests yield at the price of inflated type I error and reduce statistical power [45,46]. In this way, we included independent samples from a family bases cohort.

Additionally, there was no association between autozygosity and BP quantitative traits in an international meta-analysis, including TCGS families with a relatively high inbreeding rate [47]. Finally, we found signals which were not in LD with previously reported genetic variants on BP traits. Further investigation is necessary to fine mapping of these regions when imputed variants on the Iranian genome become available.

We identified three loci, of which two loci were previously reported in individuals with European and Non-European ancestries. The association of genetic variants on ZBED9 and BP traits has not been previously reported in other populations. Their effects were consistent after controlling environmental factors by two different GWA analyses and confirmed in a family-based linkage study. Although there is no strong evidence to support the function of ZBED9 in blood pressure regulation by Open Target Post GWAS, its association with QRS interval and QRS amplitude as surrogates of myocardial mass may provide new insight into pleiotropic effects of hypertension and other cardiovascular diseases.

Acknowledgment:

This study has been funded by grants from the Deputy for Research Affairs of Shahid Beheshti University of Medical Sciences. We are grateful to all TLGS and Gemiran colleagues that assisted with this study through the data collection process. Moreover, we would like to thank Dr. Hossein Mozafar Sadati for his comments on missing data imputation.

Author Contributions:

MSD and GK had full access to all the data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis; GK, MSD, SS, MA, and FH contributed to study concept, design, and supervision; MSD, BSK, KG, MA, and GK contributed in acquisition of data; GK, MSD, SS, MA, FH, and BSK contributed in analysis and interpretation of data; GK, MSD, MA, SS, and SR contributed in statistical analysis; FA, MSD, and FH contributed in administrative, technical, or material support; GK, MSD, BSK, MA, SS, FH, KG, MAR and FA: drafting of the manuscript and critical revision of the manuscript for important intellectual content. All authors read and approved the final manuscript.

Conflict of interest:

The authors have no conflicts of interest to declare.

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Table 1

Descriptive characteristics of phenotypes and covariates in GWAS and confirmation datasets.
	Discovery		Confirmation
	SBP/DBP	HTN	SBP/DBP/HTN
	Adults (N = 4657)	Adults (N = 4214)	TCGS Families (N = 210) Fam. members(N = 1618)
Age (yrs.)	40.8 ± 15.9	40.0 ± 13.5	35.6 ± 19.4
Female (%)	2523 (54%)	2143 (51%)	834 (52%)
SBP (mmHg)	116.29 ± 17.61	112.61 ± 12.29	117.61 ± 18.94
DBP (mmHg)	76.21 ± 9.72	74.70 ± 7.62	77.36 ± 10.49
BMI (Kg/m²)	27.07 ± 4.51	27.01 ± 4.28	24.45 ± 6.90
WC (cm)	90.82 ± 11.51	90.60 ± 10.72	86.06 ± 15.77
TG/HDL	3.81 ± 3.11	3.87 ± 2.08	-
HTN Case (%)	NA	970 (23%)	855 (53%)
Mean ± Standard Deviation, NA: Not applicable, Fam. Members: Family members

Table 2. GWA findings on BP traits in discovery and confirmation studies.

Locus Nearby	Position	rs ID	Effect/Other Allele	EAF	*Discovery*		*Confirmation*		Reported locus (Ref)
					*Adults*		*TCGS Families*
					St. β	P-value	P-value	Trait
*ZBED9*	6:28574647	rs450630	A/G	0.43	1.89^#	2.21E-07^‡	0.032	SBP,DBP,HTN	Reported [27]
	6:28611694	rs450630	T/C	0.43	1.89^#	2.77E-07^‡	NA
	6:28602172	rs9501180	T/C	0.43	1.89^#	6.56E-07^‡	NA
	6:28554918	rs380914	G/A	0.43	1.91^#	1.93E-07^‡	NA
	6:28682576	rs6456825	A/G	0.43	1.89^#	2.52E-07^‡	NA
	6:28677393	rs9885928	T/G	0.44	1.89^#	5.52E-07^‡	NA
*FBN1*	15:48420560	rs2303505	T/G	0.02	0.42	9.61E-08ⵜ	0.045	SBP	Reported [28-31]
	15:48428455	rs363830	T/C	0.02	0.43	9.98E-08ⵜ	NA
	15:48420679	rs363838	G/T	0.02	0.42	9.89E-08ⵜ	NA
*ABHD17C*	15:80717774	rs1078107	C/T	0.01	0.10	4.51E-11*	0.17	-	Reported [28-30,32-34]
*ABHD17C*	15:80689205	rs16972291	C/T	0.01	0.10	4.46E-11*	NA	-	Reported [28-30,32-34]

EAF, effect allele frequency in TCGS; St.β, Standardized effect estimate.

NA: Not applicable due to removing variant in LD pruning process (r²>0.8).

#: Odds ratio.

‡: reach the genome-wide borderline P-value threshold after adjustment for either BMI or WC on HTN.

ⵜ: reach the genome-wide borderline P-value threshold after adjustment for WC on SBP.

*: reach genome-wide threshold after adjustment for WC on DBP.

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Editorial decision: Major revision
08 Feb, 2021
Reviews received at journal
06 Feb, 2021
Reviews received at journal
27 Jan, 2021
Reviewers agreed at journal
20 Jan, 2021
Reviewers invited by journal
20 Jan, 2021
Editor assigned by journal
20 Jan, 2021
Editor invited by journal
09 Dec, 2020
Submission checks completed at journal
09 Dec, 2020
First submitted to journal
03 Dec, 2020

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Genome-Wide Association Study on Blood Pressure Traits in the Iranian Population Suggests ZBED9 as A New Locus for Hypertension.

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