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CLOCK gene 3’UTR and exon 9 polymorphisms show a strong association with essential hypertension in a North Indian population

BMC Medical Genomics volume 17, Article number: 289 (2024) Cite this article

Abstract

Background

Hypertension (HTN) is a medical condition characterized by persistent systolic and diastolic blood pressures of ≥ 140 mmHg and ≥ 90 mmHg, respectively. With more than 1200 million adult patients aged 30–79 years worldwide according to the latest WHO data, HTN is a major health risk factor; more importantly, 46% of patients are unaware of this condition. Essential hypertension (EH), also known as primary hypertension, is the predominant subtype and has a complex etiology that involves both genetic and non-genetic factors. Majority of living organisms are influenced by the light and dark cycle of a day and respond to these changes through an intricate clock referred to as the “biological clock” or “circadian rhythm”. The connection between circadian rhythm and blood pressure is well established, with many studies supporting the role of circadian rhythm gene mutation(s)/polymorphism(s) in EH. To date, no such data are available from any Indian population.

Methods

This case‒control study was conducted on 405 EH patients and 505 healthy controls belonging to the Jammu region of North India after an informed consent was obtained from the participants. A total of three single nucleotide variants, two in the CLOCK gene (rs1801260 and rs34789226) and one in the BMAL1/ARNTL gene (rs6486121), were selected for genotyping. Genotyping was performed via the RFLP technique, and the applicable statistical analyses were performed via the SPSS and SNPStats programs.

Results

Logistic regression analysis revealed a statistically significant association of both CLOCK gene variants rs1801260 (T > C 3’UTR) and rs34789226 (C > T Exon 9) and a nonsignificant association of the BMAL1/ARNTL intronic variant rs6486121 (C > T) with EH. The 3’UTR variant showed a statistically significant association under the codominant (p < 0.0001), dominant (p < 0.0001), and recessive (p = 0.0004) models. In contrast, the exon 9 variant showed a statistically significant negative association under the codominant (p = 0.003) and dominant (p = 0.015) models only. The rs6486121/rs1801260 and rs1801260/rs34789226/rs6486121 haplotypes showed significant differences in their distribution between cases and controls (p < 0.0001). Certain genotypes and haplotypes were found more common in hypertensive males than females.

Conclusion

This is a first report linking circadian rhythm gene polymorphisms with EH in any Indian population. The statistically significant association of the CLOCK gene 3’UTR and exon 9 polymorphisms with EH, highlight the potential role of this gene and probably other genes of the circadian pathway in the etiology of EH in the study population. Additionally, our study also revealed that certain genotypes are making males more susceptible to EH.

Peer Review reports

Background

Essential hypertension (EH) is a major global health concern despite its stable prevalence, as the number of cases has almost doubled in the last three decades, affecting both men and women almost equally [1]. Because it is predominantly asymptomatic, EH is commonly referred to as a ‘silent killer’ and is a major cause of premature death [2], mainly heart disease, stroke, and kidney disease, in addition to being responsible for nonfatal diseases such as vision loss and retinal hemorrhage [3]. According to the WHO guidelines, systolic blood pressure (SBP) and diastolic blood pressure (DBP) of 140 mmHg and 90 mmHg, respectively, or higher is considered hypertension, with approximately 46% of adults being unaware of this condition and with only one out of five patients having their BP under control. Both genetic and non-genetic factors play a role in EH. The known non-genetic factors include increased body mass index, smoking, excessive alcohol intake, lack of physical activity, and several dietary choices, such as NaCl intake and low potassium intake [4,5,6]. There are multiple genetic factors involved, with genes of the renin‒angiotensin‒aldosterone system (RAAS) and the circadian rhythm being the predominant factors. RAAS is the main regulator of BP, with sympathetic‒parasympathetic nervous system and circadian rhythm (CR) also having a role [7]. RAAS exerts its regulatory action through the effector antagonistic peptides angiotensin II (Ang-II) and Ang (1–7), with Ang-II’s biological activity leading to an increase in BP and Ang (1–7) activity leading to a decrease in BP [8,9,10,11]. The sympathetic nervous system senses a decrease in BP through baroreceptors located in the blood vessels and heart, resulting in the activation of the RAAS pathway and the release of adrenergic neurotransmitters, such as epinephrine, norepinephrine, and dopamine, all of which result in increased BP [12, 13].

The daily changes a living organism experiences in its physiology, behavior, and hormone levels in a rhythmic manner, commonly referred to as circadian rhythm, is a universal feature of all living organisms, including humans. These rhythmic changes are under the control of circadian clock, which consists of two major components—the central clock and the peripheral clocks. The central clock is present in the suprachiasmatic nucleus (SCN) of the hypothalamus [14], whereas the peripheral clocks are supposedly present in almost all tissues and organ systems [15].The central clock is responsible for synchronizing the CRs in the peripheral clocks, which include the sleep‒wake cycle and mental and physical activity. There is enough evidence linking a desynchronized CR with several chronic diseases, including hypertension. For example, CR desynchronization alters the daily rhythms of potassium and sodium excretion, thus impacting BP [16,17,18]. At the molecular level, the circadian clock is regulated by four major core genes: CLOCK (Circadian Locomotor Output Cycle Kaput), BMAL1 (Brain and Muscle ARNT-like Protein 1), PER (Period), and CRY (Cryptochrome). Together, these core genes form what is referred to as autoregulatory transcriptional‒translational feedback loops, controlling their daily (∼24-hour) rhythmic expression pattern in the cells. The CLOCK-BMAL1 complex forms a positive feedback loop by binding to the E-box response elements within the PER and CRY gene promoter regions, inducing the expression of the PER1/2/3 and CRY1/2 proteins, respectively, and the PER-CRY complex forms a negative feedback loop by suppressing their own expression by inhibiting the activity of the CLOCK-BMAL1 complex after translocating back into the nucleus [16, 19]. In addition, secondary loops also exist that fine-tune both central and peripheral clocks to ensure the robustness of the clocks [20,21,22].

In the present study, we investigated the associations of the CLOCK gene 3’UTR (rs1801260T > C) and exon 9 (rs34789226T > C) and the BMAL1 gene intronic (rs6486121C > T) single nucleotide polymorphisms (SNPs) with EH in the North Indian population of the Jammu region.

Materials and methods

Ethical statement

The study was approved by the Institutional Human Ethical Committee (IHEC) of Central University of Jammu vide IHEC registration no. IHEC/CUJ/CMB-23/01. An informed consent was taken from the participants, and all relevant details were entered into a predesigned questioner. The experimental research was conducted in compliance with institutional human ethical committee norms.

Subjects

A total of 910 subjects were enrolled from the ethnic population groups of the Jammu region, among which 405 were cases and 505 were ethnicity- and sex-matched healthy controls. Ethnicity was confirmed before enrollment in the study. The demographic characteristics of the cases and controls are shown in Table 1. The average ages of the cases and controls were 55 ± 12 and 52 ± 13 years, respectively.

Table 1 Demographic characteristics and clinical parameter of the controls and cases
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Subjects with any family history of hypertension, renal disorders, thyroid problem or cardiovascular diseases (CVDs) were excluded from the study. A trained medical professional measured the BP with a standard Sphygmomanometer after the patient had rested in a seated position for at least 5 mins. Average BP values were calculated from three separate measurements taken at intervals of 5–10 mins. The average SBP in cases was 157 ± 10 mmHg and 116 ± 8 mmHg in controls. The average DBP was 89 ± 9 mmHg and 73 ± 7 mmHg in cases and controls, respectively. The proportions of females in the cases and controls were 41% and 44%, respectively, which were not statistically significant (p = 0.2732).

Primer design

The following primer pairs were designed via the PRIMER 3 tool (https://www.ncbi.nlm.nih.gov/tools/primer-blast/): 5’-CCCTGGAGGTCATTTCATAGC-3’ forward and 5’-TCCTGGAATTAGTTGGCAGAGA-3’ reverse primers to amplify the CLOCK 3111T > C 3’UTR SNP (rs1801260), 5’-ATTTTCAGGCTTTCAAGGTCA-3’ forward and 5’-ATGGGAGTCCAGGATTTATT-3’ reverse primers to amplify the CLOCK exon 9 862T > C SNP (rs34789226), and 5’-ACATCTTGTCCCGAGCCATG-3’ forward and 5’-TCTAGTGCACCATGGGCTTA-3’ reverse primers to amplify the BMAL1 C > T SNP (rs6486121).

DNA extraction and genotyping

Genomic DNA was extracted from 2 ml of peripheral blood with FlexiGene DNA isolation kit from Qiagen (Qiagen Pvt. Ltd. Hilden, Germany, Cat. No. 51206) following manufacture’s protocol. Polymerase chain reaction was performed with the designed primer pairs following the standard procedure to amplify the target regions of the CLOCK and BMAL1 genes. The final reaction volume was set at 12.5 µl, which included 5 µl of ready-to-use 2X Emerald PCR master mix (DSS Takara Bio, India Pvt. Ltd, Kolkata, India, Cat No. RR310A), 0.5 µl each of 10nm forward and reverse primers, 2 µl of 50 ng of DNA template, and 4.5 µl of nuclease-free water. The cycling steps included initial denaturation at 95 °C for 5 min, followed by 32 cycles of denaturation at 95 °C for 30 s, annealing at 58 °C for 30 s for BMAL1 and CLOCK 3’UTR and 55 °C for 30 s for CLOCK exon 9, and extension at 72 °C for 30 s, followed by a final extension at 72 °C for 10 min. Amplicon products were run on a 2% agarose gel to confirm amplification and specificity (CLOCK 3’UTR 187 bps, CLOCK exon 9 583 bps, and BMAL1 150 bps). RFLP-based genotyping was performed as follows: CLOCK 3’UTR, 1 U of Bsp1286I restriction enzyme (New England Biolabs, Inc., Ipswich, Massachusetts, USA. Cat. No. R0120), overnight incubation at 37 °C; CLOCK exon 9, 2 U of RsaI restriction enzyme (Promega Corporation, Madison, USA. Cat. No. R6371), 6 h incubation at 37 °C; BMAL intronic variant, 1 U of BanII restriction enzyme (New England Biolabs, Inc., Ipswich, Massachusetts, USA. Cat. No. R0119), 4 h incubation at 37 °C. After digestion, samples were subjected to gel electrophoresis on a 2.5% agarose gel to identify the alleles. The genotypes were recorded as follows: CLOCK 3’UTR, no digestion = TT, partial digestion = TC, complete digestion = CC; CLOCK exon 9, no digestion = TT, partial digestion = CT, complete digestion = CC; BMAL1 variant, no digestion = CC, partial digestion = TC, complete digestion = TT. Genotyping was randomly repeated for 5% of the samples to confirm the results. Selected samples representing all the restriction gel profiles were Sanger sequenced from Redcliffe Genomics Lab, New Delhi, India to confirm the RFLP genotyping profile.

Statistical analysis

Unpaired t test was used to statistically assess the differences in age, BMI, sex, and BP measurements between the cases and controls (https://www.graphpad.com/quickcalcs/ttest1/). Pearson’s chi-square (χ2) statistics was used to estimate differences in the genotype frequency distribution between cases and controls and to calculate the Hardy‒Weinberg equilibrium (HWE) for each SNP in controls (https://www.socscistatistics.com/tests/chisquare2/default2.aspx). SPSS statistical software v25.0 (IBM, Armonk, NY, USA) was used to assess the level of association between genotypes and EH, which was calculated as the odds ratio (OR) at 95% confidence interval via binary logistic regression after correction for age, sex, and BMI. Association statistics were further validated through the online statistical tool SNPStats (https://www.snpstats.net/start.htm). The control group was used as the reference category. The dominant genotype was coded as 2 (reference group), the heterozygous genotype was coded as 1, and the recessive genotype was coded as 0. The associations were also evaluated under the dominant and recessive models by calculating ORs via binary logistic regression analysis after correcting for age, sex, and BMI. Haplotype analysis was performed via the online statistical tool SNPStats (https://www.snpstats.net/start.htm). The statistical power of each variant was calculated via the Genetic Power Calculator (http://pngu.mgh.harvard.edu/~purcell/gpc/) [23], and the estimated power of the study for all SNPs was > 80%. For significance levels, a p value of < 0.05 was considered significant. For multiple SNP analysis, a Bonferroni-corrected p value was used to detect the significance level. GTex Portal (https://gtexportal.org/home/) was accessed to assess the impact of different SNPs on gene expression levels in relevant body tissues.

Results

The corresponding CLOCK 3’UTR allelic frequency distribution between cases (A = 0.53 and G = 0.47) and controls (A = 0.64 and G = 0.36) was statistically significant (χ2 [1, N = 1820] = 22.2, p < 0.00001). In contrast, differences in the allelic distributions of CLOCK exon 9 and BMAL1 variants between cases and controls were not found statistically significant (p = 0.22 and p = 0.83, respectively). The genotypic distribution of the SNPs between cases and controls is given in Table 2. None of the SNPs genotyped showed any deviation from HWE in the controls. To determine the maximum impact of risk alleles on EH, binary logistic regression analysis was performed under different genetic models to evaluate the associations between the SNPs and EH. Among the three SNPs genotyped, both CLOCK gene variants were significantly associated with EH under the three genetic models, with rs1801260 showing a positive correlation and rs34789226 showing a negative correlation (Table 2). In the codominant model, the calculated OR (95% CI) for CLOCK 3’UTR TT vs. TC was 1.67 (1.23–2.25, adjusted p = 0.001), and that for TT vs. CC was 2.69 (1.78–4.06, adjusted p < 0.0001). In the dominant (TT vs. TC + CC) and recessive (TT + TC vs. CC) models, the OR statistics revealed a significant association between the CLOCK 3’UTR and EH, with an adjusted p value of < 0.0001 [OR 1.87 (1.4–2.48)] and an adjusted p value of 0.0004 [OR 1.96 (1.36–2.83)], respectively. A significant correlation was also observed for the CLOCK exon 9 variant; however, the correlation was negative for the TT vs. TC genotypes under the codominant model [OR 0.61 (0.45–0.85), adjusted p = 0.003] and TT vs. TC + CC under the dominant model [OR 0.69 (0.51–0.93), adjusted p = 0.015]. No significant associations were observed under the recessive model. We did not observe any significant association between the BMAL1 gene variant and EH under any of the genetic models that were tested (Table 2). All p values were adjusted for age, sex, and BMI.

Table 2 Genotype frequency distribution and risk associated with the different variants under different genetic models
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To elucidate any potential associations between SNP haplotypes and EH, we performed double (rs1801260/rs34789226, rs1801260/rs6486121, rs34789226/rs6486121) and triple (rs1801260/rs34789226/rs6486121) haplotype analyses. The haplotype frequency distributions among the cases and controls are given in Table 3. None of the variants were found in linkage disequilibrium. The global haplotype associations of all haplotype combinations with EH except for rs34789226/rs6486121 were found statistically significant (p < 0.0001). Among the rs1801260/rs34789226 pair, haplotypes C/T and C/C showed a statistically significant association with the EH (p = 0.004 and p = 0.022, respectively). Two haplotypes, C/C and C/T, presented significantly greater odds only in males [OR 1.60 (1.10–2.32) and 1.58 (1.05–2.37), respectively] (Suppl. Table S1). Among the rs1801260/rs6486121 pair, haplotypes C/C and C/T were significantly more common in cases than in controls (p = 0.015 and p = 0.0004, respectively). In a similar association analysis including all three SNPs as a triple haplotype (rs1801260/rs34789226/rs6486121), the global haplotypic differences were highly significant (p < 0.0001), with C/T/C, C/T/T, and C/C/T/T haplotypes being more frequent in cases than in controls, and T/C/C, T/C/T, and T/T/T being more frequent in controls than in cases (Table 3). However, except for the C/C/T haplotype [OR 2.19 (1.14–4.21), p = 0.018)], no haplotype showed a significant association with EH before applying the Bonferroni correction for multiple SNPs, and none showed a significant association with EH after the Bonferroni correction (corrected p = 0.017).

Table 3 Haplotype frequency distribution between cases and controls and their association with hypertension
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Additionally, the gender wise association analysis revealed no overall significant difference in the genotypic distribution of all variants between males and females. However, interestingly CLOCK 3’UTR CC (recessive) genotype was found significantly associated with EH [OR 2.72 (1.42–5.21)] only in females, whereas both recessive and heterozygous genotypes showed a significant correlation with EH in males (Suppl. Table S1). In the CLOCK exon 9 variant, except for the negative correlation between the heterozygous genotype and EH in females [OR 0.60 (0.37–0.97)], no other genotype was found associated with EH in either gender (Suppl. Table S1). At the haplotype level, only rs1801260/rs6486121 C/T haplotype was found positively correlated with EH in males [OR 1.76 (1.19–2.59)] (Suppl. Table S1).

To rule out any major impact of the statistically significant age difference between cases and controls (Table 1), we performed a subgroup analysis by dividing the samples into two age groups; ≤44 year and ≥ 45 year. This grouping was done based on the available literature that the risk of hypertension increase 6.7 folds in the ≥ 45 age group of the Indian population [24]. Both age groups showed a statistically non-significant age difference between cases and controls (p > 0.5). As shown in Suppl. Tables S2 and S3, the significance values of rs1801260 and rs6486121 remained unchanged from the overall data set in both the age groups. On the contrary, the significant association of rs34789226 with EH was lost in the ≥ 45 year age group under all three genetic models and increased further in the ≤ 44 year age group (Suppl. Tables S2–S3).

Discussion

The rhythmic oscillations in human physiology in response to the light‒dark cycle of the day are important adaptations that, if disrupted, have the potential to impact health [18]. This has indeed been demonstrated in several studies, linking disruption in CR to obesity, CVD, hypertension, metabolic and renal disorders [25, 26]. Animal studies have further established the link between CR deregulation and diseases, including abnormal BP [16, 27,28,29,30,31,32]. Blood pressure undergoes a 24-hour rhythmic oscillation of ‘morning surge’, ‘afternoon peak’, and ‘night dip’ in a healthy individual controlled by the CR to maintain normal cardiovascular and renal physiology [33]. Individuals who fail to achieve a night dip of at least 10% or who experience reverse dipping or an excess morning surge in BP are prone to CVDs and chronic kidney disease, although some ethnic differences exist [34,35,36,37,38,39]. Alterations in the expression of any of the CR core genes, viz. CLOCK, BMAL1, PER, and CRY have the potential to disrupt BP oscillation, resulting in BP dysregulation, thus supporting the role of these genes in EH [16, 27,28,29,30,31, 40]. Several SNPs, mainly in the UTR and intronic regions of the core CR genes, have been identified as having the potential to cause diseases, including EH [40,41,42,43,44]. For example, individuals carrying the T allele of the CLOCK T3111C 3’UTR variant (rs1801260) were found to be at a low risk of developing CVD [41]. Furthermore, reports have also associated this polymorphism with hypertension and obesity [45, 46]. Similarly, the role of BMAL1 in BP regulation is also well studied, as mice deficient in this gene lack circadian oscillation in BP [27], and adrenal gland-specific knockout also results in a similar phenotype [47]. In contrast, a nonrhythmic reduction in BP was observed when BMAL1 was deleted in renin-producing kidney cells [48], suggesting a CR-dependent and CR-independent role of BMAL1 in BP regulation. BMAL1, along with PER2, play important roles in heart function and the vasculature, thus having a direct effect on BP [32]. Additionally, several intronic SNPs in the BMAL1 gene with the potential to change gene expression, including rs6486121 [40, 43, 44] have been found to be associated with EH, further confirming its role in BP regulation. In contrast, very little evidence suggests that the exon 9 missense mutation (I169V) is not involved in any type of hypertension or any other disease [49], perhaps because of its predicted benign nature (https://www.uniprot.org/uniprotkb/O15516/variant-viewer).

In this study, we report for the first time a significant association between two CLOCK gene variants, one in the 3’UTR (rs1801260) and another in xon 9 (rs34789226), and a non-significant association between the BMAL1 intronic variant (rs6486121) and EH from a North Indian population. Consistent with the published evidence, the CLOCK gene rs1801260 SNP showed a positive correlation with EH, supporting an increased risk associated with the minor C allele under all three genetic models tested (Table 2), thus implying that individuals carrying the CC genotype are at a greater risk of developing EH than individuals carrying the TT genotype. In contrast, it appears that individuals carrying the TC genotype of the exon 9 variant are at a lower risk of developing EH than are ‘TT’ carrying individuals [OR 0.69 (0.51–0.93)], suggesting that the major allele T is the risk allele in this population group, as the dominant genetic model confirmed this negative correlation with EH [OR 0.69 (0.51–0.93)], adjusted p = 0.015]. Our age subgroup analysis confirmed the significant association of rs1801260 (3’UTR) with EH, however, the non-significant association of rs34789226 (Exon 9 variant) in the ≥ 45 year group and a significant association in the ≤ 44 year group hints towards the role of exon 9 polymorphism only in younger hypertensive population, which requires further validation in a large sample set. Although our sex-based analysis revealed no significant differences in the overall genotype distribution between males and females, with both sexes being at increased risk of EH under homozygous recessive conditions, a non-significant association of the 3’UTR TC genotype with EH in females and a significant association in males suggest a potential underlying factor(s) that makes heterozygous females less prone to EH than males. A highly significant difference in the haplotype distribution (both double and triple) between cases and controls suggests a potential modulatory effect of certain allelic combinations on the EH outcome. For example, both the C/C and C/T haplotypes of the rs1801260/rs34789226 pair appear to increase susceptibility toward EH ~1.60-fold in males but not in females, and when the T allele of BMAL rs6486121 is present on the C/C background of CLOCK SNPs, susceptibility increases further by 2.3-fold in males (Table 3). Similarly, the C/T haplotype of rs1801260/rs6486121 increased the risk 1.76-fold in males but not in females.

Our data provides a strong evidence in support of the role of rs1801260 in EH in the studied North Indian population, which is consistent with the published data. The biological significance of rs1801260 in hypertension could be potentially due to the high expression of the CLOCK and PER2 genes over a 24-hour cycle caused by the T > C transition, as reported in mouse embryonic fibroblasts [32]. However, evidence also suggests that CLOCK levels do not change under any allelic background [50]. These conflicting results could be due to difference in the experimental model (mouse vs. human), suggesting a differential effect of this 3’UTR polymorphism on gene expression in different organisms. To assess the impact of genotyped SNPs on gene expression levels in human cells/tissues, we accessed the GTEx database [gtexportal.org accessed on]. As shown in Fig. 1, a statistically significant reduction in CLOCK gene expression was reported in the thyroid, heart, adrenal gland, and cultured fibroblasts when the CC genotype (GG genotype as per the database) of rs1801260 was present, explaining the potential role this polymorphism may play in blood pressure dysregulation. Although we did not observe any significant association between the BMAL1 rs6486121 and EH and the lack of expression data from relevant tissues/cells in the GTEx database, the potential biological role of this variation is difficult to predict in the absence of any functional data; however, the statistically significant decrease caused by this transition in BMAL1 expression, as detected in human blood samples (Fig. 1), indicates some biological role, probably not independently but rather in conjunction with other BMAL1 and/or CLOCK variants. This assumption may explain the increased fold risk for the C/C/T haplotype that was observed in our haplotype analysis, but future functional studies are needed to test this hypothesis.

Fig. 1
figure 1

CLOCK and BMAL1 expression levels in different human tissues/cells under different genotypic backgrounds

Full size image

Conclusion

In conclusion, our data provide strong evidence in support of a positive correlation between rs1801260 and essential hypertension, with the minor allele C being the risk allele and the major allele T being the protective allele, and a comparatively less significant correlation between rs34789226 and hypertension, with people carrying the major allele T in homozygous conditions being at a higher risk of developing hypertension. In the present study, we focused only on two genes and three SNPs to examine any potential role of circadian rhythm core genes in essential hypertension. However, future studies are necessary to investigate the remaining SNPs and genes to obtain a better understanding of the role of circadian rhythm in essential hypertension in North Indian populations. Even though our conclusion is based on a statistically appropriate sample size, the significant age difference between cases and controls is a major limitation of this study. Additionally, the exclusion of non-genetic risk factors, such as smoking, alcohol consumption, stress etc. is another limitation of this study. We intend to address these limitations in our future studies. In this era of medicine, it is essential to develop an effective treatment through precision diagnostics, especially if the causes are multiple or unknown. Therefore, by identifying the cause precisely and targeting it further, it is possible to achieve milestones in improving both diagnostics and prognostics.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Ang:

Angiotensin

BMAL1:

Brain and Muscle ARNT-like Protein 1

BMI:

Body mass index

BP:

Blood pressure

CI:

Confidence interval

CLOCK:

Circadian Locomotor Output Cycle Kaput

CR:

Circadian rhythm

CRY:

Cryptochrome

CVDs:

Cardiovascular diseases

DBP:

Diastolic blood pressure

EH:

Essential hypertension

HTN:

Hypertension

HWE:

Hardy‒Weinberg equilibrium

IHEC:

Institutional Human Ethical Committee

OR:

Odds ratio

RAAS:

Renin‒angiotensin‒aldosterone system

PER:

Period

RFLP:

Restriction fragment length polymorphism

SBP:

Systolic blood pressure

SCN:

Suprachiasmatic nucleus

SNP:

Single nucleotide polymorphism

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Acknowledgements

AB is the recipient of the ICMR-CAR grant (5/10/15/CAR-SMVDU/2018-RBMCH) and ICMR-EMR grant (6719/2020-DDl/BMS). We acknowlegde Dr. Fayaz Ahmed Wani, Dr. Anupama Shah, Dr. Pankaj Sharma, and Dr. Dharminder Kumar of Govt. Medical College Jammu and Rama Krishna Medical Centre, Jammu, Jammu and Kashmir for their valuable support by facilitating sample collection and BP measurement. We are also thankful to the volunteers who participated in this study.

Funding

This work was partly supported by the ICMR-CAR grant (5/10/15/CAR-SMVDU/2018-RBMCH) santioned to the corresponding author.

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Author notes

  1. Shreya Sopori and Kavinay Kavinay contributed equally to this work.

Authors and Affiliations

  1. Centre for Molecular Biology, Central University of Jammu, Jammu, UT Jammu and Kashmir, 181143, India

    Shreya Sopori, Kavinay Kavinay, Sonali Bhan, Shreya Saxena, Medha Medha & Audesh Bhat

  2. Department of Biotechnology, Shri Mata Vaishnav Devi University, Katra, 182320, India

    Rakesh Kumar

  3. Department of Pharmacy, Birla Institute of Technology and Sciences Pilani, Hyderabad Campus, Telangana, 500078, India

    Arti Dhar

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  1. Shreya Sopori
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Contributions

SS generated the data and wrote the first draft. KK collected the samples and generated the data, SS generated the data, MM designed the primers and generated the data, SB performed the statistical analyses. RK analyzed the data and reviewed the manuscript, AD wrote and revised the manuscript. AB conceived the study, analyzed the data, revised and reviewed the manuscript.

Corresponding author

Correspondence to Audesh Bhat.

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Ethics approval and consent to participate

This study was approved by the Central University Jammu human ethics committee (notification no. IHEC/CUJ/CMB-23/01). A written and informed consent was taken from all the participants.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Sopori, S., Kavinay, K., Bhan, S. et al. CLOCK gene 3’UTR and exon 9 polymorphisms show a strong association with essential hypertension in a North Indian population. BMC Med Genomics 17, 289 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12920-024-02056-6

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BMC Medical Genomics

ISSN: 1755-8794

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