Analysis of Genetic Variation in Circadian Rhythm Genes and Risk of Ovarian Cancer.

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Sonali Verma, Gresh Chander, Amrita Bhat, Gh.Rasool Bhat, Divya Bakshi, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-257989/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Disruption in biological clock due to genetic variations is associated with increased occurrence of cancers such as breast, ovary, prostate, gastrointestinal and hematological malignancies. Circadian rhythm genes regulate the process of ovulation in the ovaries and are highly expressed in ovarian tumors; whereas disturbance in the circadian rhythm pathway is significantly associated with causative risk factors (i.e. endometriosis, PCOS, etc.) of ovarian cancer. Nevertheless, very few studies have been conducted till date where candidate SNPs of circadian rhythm genes proved as the main prognosticators of ovarian cancer risk and intrusiveness. The main purpose of this study was to investigate some common single nucleotide polymorphisms (SNPs) in circadian rhythm genes (rs475715 of BMAL1 / ARNTL , rs1026071, and rs228644 of PER3, rs3792152 of REV1 , and rs7302060 of TIMELESS ) as causative markers of ovarian cancer risk of in the population of Jammu and Kashmir in India. Results Our study included a total of 600 samples (200 cases and 400 age and sex-matched controls). Analysis of the genotype data from the selected SNPs indicated most significant association of rs3792152 of REV1 (OR=1.6, with 95% CI=0.12-1.2, p=0.0003) and rs4757151 of BMAL1/ARNTL (OR=1.847, with 95% CI=1.406-2.426, p=9.15E-06) with the ovarian cancer . The functional putative analysis revealed a significant regulatory effect of both these variants on other genes. Conclusion These results suggest that some SNPs in circadian rhythm genes, particularly BMAL1/ARNTL and REV1 , might be associated with the risk of ovarian cancer in the J&K population of North India. Epigenetics & Genomics Single Nucleotide Polymorphisms (SNPs) Jammu and Kashmir (J&K) and Ovarian Cancer (OC) Background Ovarian cancer (OC) is one of the most common cancer globally, with more than 239,000 newly diagnosed cases and 152,000 deaths each year [1]. OC ranks 3rd in gynecological malignancies after cervix and uterine cancer [2]. OC has the worst prognosis and the peak death rate. Even though ovarian cancer has a lesser pervasiveness in assessment with breast cancer, it is three times more fatal, and it is foretold that, by the year 2040[3], the death rate of OC will increase significantly. The high death rate in OC patients is mainly due to, asymptomatic and undisclosed progression of the ovarian tumor, deferred beginning of signs and symptoms, and the absence of suitable screening that affects diagnosis of the progressive stages [3]. Despite countless developments in early diagnosis and treatment, OC survival has shown only borderline increase due to the intricacy and heterogeneity of molecular pathways involved, specifically in invasion, relapse of ovaries, and metastasis. Hence, it is crucial to investigate biomarkers to clarify the molecular processes for enlightening the diagnosis of OC. In women, the clock genes under the influence of hormones regulate the ovulation [4]. It was reported that estradiol hormone in ovary is under the influence of gonadotropins which may regulate the expression of clock genes associated with ovarian cancer [5]. From the previous findings, the accruing indication has recommended that circadian clock disturbance is an influential aspect of tumor instigation and proliferation. Epidemiological studies have proved that night workers have raised risk of various cancers (ovary, breast, prostate, and rectal cancer)[5–8] signifying a probable functional association between the biological clock and cancer formation. It has been proved that abnormal expression of circadian rhythm gene is strongly associated with various types of cancers[9]. Various Preceding reports have also confirmed that the anomalous expression of biological clock genes is strongly correlated with the prognosis of cancer patients [10, 11]. It has been reported that circadian genes play an active role in tumor formation and cancer cell proliferation[10]. Single-nucleotide polymorphism (SNP) is considered as an important genetic biomarker for the early prediction of risk, their response to treatment, and the proliferation of cancer cells [12]. Reported studies have proved that there were several SNPs of circadian rhythm genes ( BMAL1, PER3, PER2, CRY, TIMELESS, REVI ) which are significantly associated with the development and progression of various types of cancers (breast ovary, prostate, etc.) [13–17]. Moreover, developing evidence has revealed that SNPs of circadian genes are significantly involved in cancer predisposition [18, 19]. In the present study, we replicated and assessed the effects of candidate variants of circadian rhythm genes ( BMAL1 rs475715, PER3 rs228644, REV1 rs379215,2 and TIMELESS rs7302060) as a case-control study from J&K region of India, which was previously found to be associated with ovarian cancer in North American population by Jim et al [20] Methods Sample collection This case's control study from the J&K population was conducted in the school of Biotechnology, SMVDU, Katra. The cases included females with a histologically confirmed ovarian cancer. The cases have been obtained from various hospitals and clinics of J&K. Controls were age-matched to the cases. The cases with no familial history of cancer were included in the study. All subjects included in this study were unrelated women of J&K whereas their descendants have lived in the J&K for at least 5 generations. Overall, 600 samples including 200 incident cases of ovarian cancer and 400 population-based controls were enrolled in the study. Written informed consent was obtained from all subjects recruited in this study. During sample collection, pre-designed questionnaire was used to get the information which included age, BMI, hormonal status, age at menarche, menopausal status, histology of tumors, oral contraceptive use and breast nodules (Table 1 ) from both cases and controls. Patients who undertook radio/chemotherapy were excluded from the study. Table 1 Clinical details of cases and controls Characteristics Cases (200) Controls (400) P value Age (years) Mean ± S. D 59.2 ± 10.1 56.7 ± 14.4 0.02 BMI Mean ± S. D 22.6 ± 4.52 25.4 ± 4.89 9.74E-12 Menopausal Status Premenopausal 124 276 0.33 Post-menopausal 74 124 Stage (I/II) 78 - - III/IV 110 - Age at menarche (years) > 12 107 215 0.02 < 12 93 185 Histology of tumors Epithelial 138 - - - Germ cell 9 - Sex cord stromal cell 33 - Metastasis 20 - Oral Contraceptive use Yes 80 165 0.1 No 120 165 Breast Nodules Yes 22 - No 162 Selection of SNP Total four crucial selected circadian gene variants ( BMAL1 / ARNTL rs475715 and rs1026071, PER3 rs228644, REV1 rs3792152, and TIMELESS rs7302060) previously reported [20] to be associated with ovarian cancer were investigated in the current study. The details of SNPs were mentioned in Additional File1: Table S1 . The SNPs were selected for genotyping only based on their M.A.F (Minor allele frequency) value (> 0.03 in Gujrati Indians). Linkage disequilibrium (LD) SNPs were excluded from this study. The primers (amplification and extension) were designed by Sequenom Mass ARRAY® Assay Design 3.0 Software (Sequenom, San Diego, USA). The primers were mentioned in additional file 1: Table S3. Genotyping and quality control From the 600 women (200 cases and 400 controls) who provided blood, sufficient DNA was extracted by using manufacturer protocol (Qiagen DNA isolation Kit cat no. 51206). All these subjects were genotyped by the (Sequenom Mass ARRAY platform) using the 384 well chip according to the standardized protocol which were replicated from the study [21]. Software Sequenom Typer was used for the analysis and management of data. Statistical analysis The odds ratios (OR) with their 95% confidence intervals (CI) as well as hardy Weinberg equilibrium were estimated by Plink v1.07. Clinical characteristics of cases and controls were compared using the chi-square t-test for variables (Table 1 ). For the results, SNPs that were not following hardy Weinberg equilibrium (H.W.E) were not included in further analysis. Logistic regression & stratification analysis was used to estimate the risk or to estimate the association with Odds Ratio at 95% confidence interval and respective level of significance as p-value by using SPSS software. The power of the study was calculated statistically by PS software version 3.1.2 [22]. Putative visualization of variants in the human genome was also done by freely available Insilco tools (SNIPA and Haploreg) [23] [24]. Both tools were used to found the functional annotations i.e., to predict the expression quantitative trait locus (eQTL) of risk associated variants and to find the high linkage disequilibrium SNPs ( r 2 > 0.8) with selected candidate variants. Results Four histopathological types of cases were analyzed. The sample characterized are discussed in Table 1 . As estimated, significant differences were observed between cases and controls on ovarian cancer risk factors including age, BMI, age at menarche, breast nodules, oral contraceptive use, and menopausal status (P values < 0.05) (Table 1 ). A total of 5 SNPs in association with circadian rhythm was included in the current 2 SNPs ( REV1 rs3792152 & BMAL1 rs4757151) of circadian rhythm were found to be associated with the risk of ovarian cancer (OR = 1.6, with 95% CI = 0.12–1.2, p = 0.0003) and (OR = 1.847, with 95% CI = 1.406–2.426, p = 9.15E-06) (Table 2 ). After logistic regression with age and BMI, rs3792152 of REVI having genotype AA was found to be associated with increased risk of ovarian cancer (AA + AG vs. GG: adjusted OR = 1.97, 95% CI 1.25–3.1, p = 0.003) and rs4757151 of BMAL1 having genotype AA was also associated with the increased risk of ovarian cancer (AA + AG vs. GG: adjusted OR = 2.4, 95% CI (1.48–3.87), p = 0.0003. Table 2 Allele frequency of SNPs in ovarian cancer S. No GENE SNPS CASES CONTROLS ALLELE OR P VALUE DOMINANT OR P VALUE HWE 1 REVI rs3792152 A = 0.5775 A = 0.4571 1.6(1.2–2.08) 0.0001 1.97(1.25–3.1) 0.003 0.9184 G = 0.4225 G = 0.5429 2 ARNTL /BMALI rs1026071 G = 0.3289 G = 0.3077 1.1(0.83–1.45) 0.48 1.27(0.86–1.86) 0.222 0.2334 A = 0.6711 G = 0.6923 3 ARNTL /BMALI rs4757151 A = 0.5458 A = 0.3941 1.84(1.4–2.42) 9.15E-04 2.4(1.48–3.87) 0.00034 0.7339 G = 0.4542 G = 0.6059 4 PER3 rs228644 A = 0.4218 A = 0.4716 0.81(0.59–1.11) 0.204 0.69(0.41–1.19) 0.186 0.00261 G = 0.5782 G = 0.5284 5 TIMELESS rs7302060 C = 0.4085 C = 0.3469 1.3(0.97–1.73) 0.07 1.48(0.96–2.28) 0.072 0.8051 T = 0.5915 T = 0.6531 The SNPs rs1026071 of BMAL1 ( OR = 1.1,95% CI (0.83–1.45), p = 0.48) & variant rs7302060 (OR = 1.3,95% CI (0.97–1.73), p = 0.07) of TIMELESS gene was found not associated with the ovarian cancer (Table 2 ). The variant rs228644 of PER3 was not following HWE (hardy Weinberg equilibrium) and thus was not analyzed further. The putative visualization of significantly associated variants (rs3792152 of REVI & rs4757151 of BMAL1 ) was done by Haploreg v4.1 ( https://pubs.broadinstitute.org/mammals/haploreg/haploreg.php ) and SNIPA ( https://snipa.helmholtz-muenchen.de/snipa3/ ). These tools predict the possible mechanism underlying the identified associations and determine proxy variants of the identified variants. Haploreg identified that both variants rs3792152 of the REVI gene and rs4757151 of the BMAL1 genes were located in enhancer histone marks. Both risks associated with intronic variants were predicted to change the regulatory binding motifs (Additional File1: Supplementary Figures S1 and Supplementary Figure S2). SNIPA identified that the intronic variant rs3792152 was predicted to have a direct regulatory effect on C2orf15, LIPT1, LYG1, MITD1, REV1, TSGA10, TXNDC9 through eQTL ( Expression quantitative trait loci) with REV1 gene, whereas intronic variant rs4757151 was predicted to have a direct regulatroy effect on transcripts ( RN7SKP151 & BTBD10) through eQTL ARNTL (Additional File1: Supplementary Table S2 and Supplementary Figures S3 and Supplementary Figure S4). Discussion In this case-control study, we reported the significant association of ovarian cancer with the variants of circadian rhythm gene pathway, predominantly with already reported ovarian cancer risk associated circadian gene variants ( BMAL1 / ARNTL rs475715 and rs1026071, PER3 rs228644, REV1 rs3792152, and TIMELESS rs7302060) [20]. We examined variation in the four most common genes of the circadian pathway ( REV1, ARNTL/BMAL1, TIMELESS , and PER3 ) as prognosticators of ovarian cancer risk and invasiveness. We found that two out of five variants were associated with the risk of ovarian cancer. Specifically, the risk of ovarian cancer was associated with variant rs475715 of BMAL1/ARNTL & rs3792152 of REV1 , whereas other variant rs228644 of PER3 , rs7302060 of TIMELESS , and rs1026071 of ARNTL were found to be not associated with ovarian cancer in our studied region. Biological clock in humans called circadian clock / circadian rhythm, autonomously oscillate with a period near 24 hours. The mechanism of the circadian clock is based on the positive/negative response circlets which are produced by core circadian clock genes. The monitoring feedback loop of circadian rhythm consists of PER , CRY , CLOCK , and BMAL1 proteins having a function of regulations in the transcription/translation process. The heterodimer ( BMAL1/CLOCK ) complex inhibiting or repressing the PER/CRY genes activity in the nucleus region where the monitoring feedback loop formation is completed after the complex ( BMAL1/CLOCK ) formation which regulates the transcription of Rev-erbα and Rora (nuclear receptors)[25]. Findings regarding the circadian rhythm seem to be initiated by both transcriptional and post-transcriptional mechanisms which induce gene expression [26, 27]. The transcription of PER and CRY genes is initiated by two transcription factors CLOCK and BMAL1 / ARNTL . After reaching the grave concentration the PER / CRY reduces the effect of CLOCK / BMAL1 facilitated initiation of their particular genes in a negative feedback loop. It was found that both complex PER / CRY and CLOCK / BMAL1 intricate with each other and bound to chromatin. The regular daily oscillations in clock gene is contributed by protein degradation, phosphorylation, and nuclear entry [28]. The regulation of CRY and PER gene expression generates genetic and biochemical evidence [29] but the regulation of the CLOCK / BMAL1 gene is very much less known. Various studies reported that PER and CRY gene establishes a positive feedback loop in the process of BMAL1 transcription [28–30] REV1 (REV1-DNA directed polymerase) is a nuclear receptor that acts as a transcriptional repressor in the circadian pathway, where activates and inhibits the transcription of the BMAL1 gene [31]. The BMAL1 transcription is regulated by REV-ERB alpha, thus it acts as a connector link through which components of negative and positive limb constitute to form a molecular link. It determines the length of the period and phase-shifting properties of the biological clock [30]. It was proved that BMAL1 deficient cells due to DNA damage lead to arrest in cell cycle and reveal a possible modulatory effect on tumor suppressor genes i.e. P53 . It has been reported that the knockdown of the BMAL1 gene induces cell growth, reduced programmed cell death which appears to play a role in carcinogenesis [32]. Our study is the first replicative case-control association study of clock genes. Jin et al [20] reported that the gene expression of the BMAL1 gene has been controlled by cMYC where the overexpression of cMYC leads to the downregulation of BMAL1. So, it has been suggested that BMAL1 gene variants were significantly associated with the risk of ovarian cancer. The circadian gene variants are associated with prostate cancer which was reported in the GWAS study [33]. In some populations of the world, it has been reported that night workers have disturbed biological clocks where the findings of various studies proved the night working women’s and men’s are more prone to cancers (Breast, ovary, and prostate cancer) [19, 33–35]. Our results indicated that BMAL1 and REV1: rs475715 & rs3792152 both intronic variants, were associated with ovarian cancer risk. Functional prediction implicated that rs47515 has direct eQTL effect and regulates the expression of C2orf15, LIPT1, LYG1, MITD1, REV1, TSGA10, and TXNDC9 genes, whereas rs3792152 regulates the RN7SKP151 & BTBD10 with BMAL1 gene. These findings suggest that it is located within a region that directly affects expression potentially through the modulation of the histone markers in the enhancer region. Yeh et al, 2014 [36] proved that in the ovarian cancer cell (in CP70 and MCP2) the H3K27 (histone mark) is supplemented in the promoter region of ARNTL / BMAL1 gene, Whereas the presence of inhibitor (GSK126) of EZH2 region reestablished the expression of ARNTL/ BMAL1 gene in ovarian cancer cells (in CP70 and MCP2). They also confirmed that there is a sensitivity of chemotherapy drug (cisplatin) in ovarian cancer cells after increasing the expression of the ARNTL / BMAL1 gene. With these findings, it was confirmed that BMAL1 /ARNTL may act as a tumor suppressor by regulating the p53 tumor suppressor pathway in ovarian cancer [20, 36]. So, our results climax the implication of circadian rhythm gene variation in ovarian cancer susceptibility and suggest an early role for the BMAL1 and REV1 gene in ovarian cancer pathogenesis. Our results also suggest that the circadian gene variant may play a significant role in the etiology of ovarian cancer. From the literature survey, the identification of a significant association between circadian genes and ovarian cancer is still unpredictable. To the best of our knowledge, the case-control association studies between circadian gene variants and ovarian cancer were investigated in very few studies (20,25–29). Few of them have found an association with ovarian cancer and other cancers at the variant level [20, 37–39]. Even though various previous research studies have implicated circadian genes in the progression of cancers in women. Nevertheless, our study possibly requires more variants of the circadian rhythm pathway to highlight significant associations between certain circadian genes and the risk of aggressive ovarian cancer. Conclusion This study fortifies the current indication supporting the premise of a link between circadian rhythm genes and ovarian cancer risk. Additional studies with larger sample size as well as functional validation of risk associated gene variants is warranted to confirm those findings. Besides these it has been reported that women working during nightshifts are associated with several cancer but its probable role in finding the association between circadian genes and ovarian cancer risk should not be justified till date so this study proposes the need for further studies to investigate the association of carcinogenic effects of circadian disruption in relation with environmental factors, such as night-workers, regular exposure to stressed conditions, irregular diet patterns, and electromagnetic (EM) waves, which disturb circadian rhythm or biological clock by fluctuating the melatonin levels. Abbreviations eQTL: expression quantitative trait locus. M.A.F: Minor allele frequency LD: Linkage disequilibrium Declarations Availability of data and materials Correspondence and requests related to manuscript should be addressed to R.S or R.K. There is no any copyright material in this manuscript. The data has been incorporated is a result of analysis. Acknowledgement The RS, RK and SV thankfully acknowledge the Indian Council of Medical Research (5/10/15/CAR-SMVDU/2018-RBMCH). SV acknowledges Dr. Swarkar Sharma, Dr. Indu Sharma and Dr. Varun Sharma for the suggestions during the scheduling and execution of study. Funding The financial support to conduct this study was provided by Indian Council of Medical Research (5/10/15/CAR-SMVDU/2018-RBMCH) for purchasing consumables and equipment’s. Author contribution R.S, R.K and S.V planned the study. S.V, A.B, G.R.B, B.S and D.B collected the samples. S.V, R.S, A.B and GRB performed experiment in lab. S.V analyzed the results and drafted manuscript. R.S, R.K, A.B, S.S, R.A.Q, H.R and G.C provided critical comments regarding manuscripts. A.W, J.S and H.R provided samples for the study. All authors read and approved the final manuscript. Ethical Approval This study was approved by the Institutional Review Board committee of SMVDU with wide reference no. SMVDU/IERB/14/28. 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Supplementary Files QuestionaireandconsentOvariancancer.pdf SUPPLIMENTARYFILE.docx Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 11 Feb, 2021 Editorial decision: Revise before sending to peer reviewers 11 Feb, 2021 Submission checks completed at journal 11 Feb, 2021 Editor invited by journal 11 Feb, 2021 First submitted to journal 09 Feb, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-257989","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":12753422,"identity":"b9d149a7-7bff-4bdc-9b5b-54dcb893be96","order_by":0,"name":"Sonali Verma","email":"","orcid":"","institution":"Shri Mata Vaishno Devi University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sonali","middleName":"","lastName":"Verma","suffix":""},{"id":12753423,"identity":"b6229e3c-891f-4923-83e1-a004cfee2003","order_by":1,"name":"Gresh Chander","email":"","orcid":"","institution":"Shri Mata Vaishno Devi University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Gresh","middleName":"","lastName":"Chander","suffix":""},{"id":12753424,"identity":"cd0320d8-d00a-4a94-bc5d-55fb278f74be","order_by":2,"name":"Amrita Bhat","email":"","orcid":"","institution":"Shri Mata Vaishno Devi University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Amrita","middleName":"","lastName":"Bhat","suffix":""},{"id":12753425,"identity":"1b8fc3c2-f3d0-4a53-b975-c5824a8fe65a","order_by":3,"name":"Gh.Rasool Bhat","email":"","orcid":"","institution":"Shri Mata Vaishno Devi University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Gh.Rasool","middleName":"","lastName":"Bhat","suffix":""},{"id":12753426,"identity":"7959b63f-ecc5-4b2c-9553-1b54440a45cf","order_by":4,"name":"Divya Bakshi","email":"","orcid":"","institution":"Shri Mata Vaishno Devi University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Divya","middleName":"","lastName":"Bakshi","suffix":""},{"id":12753427,"identity":"1c3b2787-10bc-4cc2-82f8-de38767f2f7e","order_by":5,"name":"Bhanu Sharma","email":"","orcid":"","institution":"Shri Mata Vaishno Devi University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bhanu","middleName":"","lastName":"Sharma","suffix":""},{"id":12753428,"identity":"009459ce-b2f6-47a5-9025-1f9f71294c9b","order_by":6,"name":"Himanshu Rana","email":"","orcid":"","institution":"Government Medical College Doda","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Himanshu","middleName":"","lastName":"Rana","suffix":""},{"id":12753429,"identity":"2534b317-db3e-43c9-9213-e9c9a5d787b0","order_by":7,"name":"Jyotsna Suri","email":"","orcid":"","institution":"Government Medical College Jammu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jyotsna","middleName":"","lastName":"Suri","suffix":""},{"id":12753430,"identity":"07e2defc-32a2-4631-8074-64f3ccb527cc","order_by":8,"name":"Ajay Wakhloo","email":"","orcid":"","institution":"Government Medical College Jammu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ajay","middleName":"","lastName":"Wakhloo","suffix":""},{"id":12753431,"identity":"ca1bdc31-0fb9-475c-bfe8-c5209b3dd382","order_by":9,"name":"Supinder Singh","email":"","orcid":"","institution":"ASCOMs Jammu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Supinder","middleName":"","lastName":"Singh","suffix":""},{"id":12753432,"identity":"75ca58ef-ca61-4649-9ffe-39fb9bb3491d","order_by":10,"name":"Audesh Bhat","email":"","orcid":"","institution":"Central University of Jammu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Audesh","middleName":"","lastName":"Bhat","suffix":""},{"id":12753433,"identity":"321c2f71-18c8-4208-8183-5863b589b657","order_by":11,"name":"Raies Ahmad Qadri","email":"","orcid":"","institution":"University of Kashmir","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Raies","middleName":"Ahmad","lastName":"Qadri","suffix":""},{"id":12753434,"identity":"8640f624-e9ab-44dd-b3c8-cee6513b9ddc","order_by":12,"name":"Ruchi Shah","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYBAC+QbGBiAlAcQJbAwMFUCambkBrxaDAyAtCRIMPCAtB86AtDAS0AImExggWg62gXiEtLAfbnxc+MPC3p49+djjj/Nqo/nbgVp+VGzD7ZeexGbjGQkSiT08z9INDm47njvjMGMDY8+Z27itucHYJs2TIJHAI5FjJnFw27HcBqAWZsY2vFrafwO12EO0zDmWO58ILW3MQC2MPWAtDTW5GwhpMTiT2CzNkwb0yxmgX84cO5C7EajlID6/yLcff/iZx6bOnr09+diDipq63HnnDx988KMCj8PQwGEweYBo9UBQR4riUTAKRsEoGCEAAFhWW/AP5/+YAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-7190-8716","institution":"University of kashmir","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ruchi","middleName":"","lastName":"Shah","suffix":""},{"id":12753435,"identity":"d6058bdd-14b2-4d18-83f7-5eb1599e373c","order_by":13,"name":"Rakesh Kumar","email":"","orcid":"","institution":"Shri Mata Vaishno Devi University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rakesh","middleName":"","lastName":"Kumar","suffix":""}],"badges":[],"createdAt":"2021-02-19 23:56:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-257989/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-257989/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":13673509,"identity":"3c65b53b-88bd-476e-a204-70f406ef6ef5","added_by":"auto","created_at":"2021-09-17 11:17:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1094066,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-257989/v1/6cd05380-bd60-44d8-bf04-0b161606e1dc.pdf"},{"id":6520725,"identity":"19dd70b1-261d-427d-9224-b635012f6749","added_by":"auto","created_at":"2021-03-02 15:10:32","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":259538,"visible":true,"origin":"","legend":"","description":"","filename":"QuestionaireandconsentOvariancancer.pdf","url":"https://assets-eu.researchsquare.com/files/rs-257989/v1/3ddfff433be00bbd676e7b16.pdf"},{"id":6521386,"identity":"6cf6d72d-83f9-4b45-84c1-e30ee8f2c03b","added_by":"auto","created_at":"2021-03-02 15:13:32","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":995339,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLIMENTARYFILE.docx","url":"https://assets-eu.researchsquare.com/files/rs-257989/v1/c997963db6f7af6080809159.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eAnalysis of Genetic Variation in Circadian Rhythm Genes and Risk of Ovarian Cancer.\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eOvarian cancer (OC) is one of the most common cancer globally, with more than 239,000 newly diagnosed cases and 152,000 deaths each year [1]. OC ranks 3rd in gynecological malignancies after cervix and uterine cancer [2]. OC has the worst prognosis and the peak death rate. Even though ovarian cancer has a lesser pervasiveness in assessment with breast cancer, it is three times more fatal, and it is foretold that, by the year 2040[3], the death rate of OC will increase significantly. The high death rate in OC patients is mainly due to, asymptomatic and undisclosed progression of the ovarian tumor, deferred beginning of signs and symptoms, and the absence of suitable screening that affects diagnosis of the progressive stages [3]. Despite countless developments in early diagnosis and treatment, OC survival has shown only borderline increase due to the intricacy and heterogeneity of molecular pathways involved, specifically in invasion, relapse of ovaries, and metastasis. Hence, it is crucial to investigate biomarkers to clarify the molecular processes for enlightening the diagnosis of OC. In women, the clock genes under the influence of hormones regulate the ovulation [4]. It was reported that estradiol hormone in ovary is under the influence of gonadotropins which may regulate the expression of clock genes associated with ovarian cancer [5]. From the previous findings, the accruing indication has recommended that circadian clock disturbance is an influential aspect of tumor instigation and proliferation. Epidemiological studies have proved that night workers have raised risk of various cancers (ovary, breast, prostate, and rectal cancer)[5\u0026ndash;8] signifying a probable functional association between the biological clock and cancer formation.\u003c/p\u003e\n\u003cp\u003eIt has been proved that abnormal expression of circadian rhythm gene is strongly associated with various types of cancers[9]. Various Preceding reports have also confirmed that the anomalous expression of biological clock genes is strongly correlated with the prognosis of cancer patients [10, 11]. It has been reported that circadian genes play an active role in tumor formation and cancer cell proliferation[10].\u003c/p\u003e\n\u003cp\u003eSingle-nucleotide polymorphism (SNP) is considered as an important genetic biomarker for the early prediction of risk, their response to treatment, and the proliferation of cancer cells [12]. Reported studies have proved that there were several SNPs of circadian rhythm genes (\u003cem\u003eBMAL1, PER3, PER2, CRY, TIMELESS, REVI\u003c/em\u003e) which are significantly associated with the development and progression of various types of cancers (breast ovary, prostate, etc.) [13\u0026ndash;17]. Moreover, developing evidence has revealed that SNPs of circadian genes are significantly involved in cancer predisposition [18, 19]. In the present study, we replicated and assessed the effects of candidate variants of circadian rhythm genes (\u003cem\u003eBMAL1\u003c/em\u003e rs475715, \u003cem\u003ePER3\u003c/em\u003e rs228644, \u003cem\u003eREV1\u003c/em\u003e rs379215,2 and \u003cem\u003eTIMELESS\u003c/em\u003e rs7302060) as a case-control study from J\u0026amp;K region of India, which was previously found to be associated with ovarian cancer in North American population by Jim et al [20]\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section3\"\u003e\n\u003ch2\u003eSample collection\u003c/h2\u003e\n\u003cp\u003eThis case's control study from the J\u0026amp;K population was conducted in the school of Biotechnology, SMVDU, Katra. The cases included females with a histologically confirmed ovarian cancer. The cases have been obtained from various hospitals and clinics of J\u0026amp;K. Controls were age-matched to the cases. The cases with no familial history of cancer were included in the study. All subjects included in this study were unrelated women of J\u0026amp;K whereas their descendants have lived in the J\u0026amp;K for at least 5 generations. Overall, 600 samples including 200 incident cases of ovarian cancer and 400 population-based controls were enrolled in the study. Written informed consent was obtained from all subjects recruited in this study. During sample collection, pre-designed questionnaire was used to get the information which included age, BMI, hormonal status, age at menarche, menopausal status, histology of tumors, oral contraceptive use and breast nodules (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) from both cases and controls. Patients who undertook radio/chemotherapy were excluded from the study.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eClinical details of cases and controls\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCharacteristics\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCases (200)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eControls (400)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge (years) Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;S. D\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e59.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e56.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBMI Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;S. D\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.74E-12\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eMenopausal Status\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePremenopausal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e124\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e276\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.33\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePost-menopausal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e124\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eStage\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(I/II)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIII/IV\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e110\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge at menarche (years)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e107\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e215\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e185\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eHistology of tumors\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eEpithelial\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e138\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGerm cell\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSex cord stromal cell\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMetastasis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eOral Contraceptive use\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e165\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e120\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e165\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBreast Nodules\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e162\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003eSelection of SNP\u003c/h2\u003e\n\u003cp\u003eTotal four crucial selected circadian gene variants (\u003cem\u003eBMAL1 / ARNTL\u003c/em\u003e rs475715 and rs1026071, \u003cem\u003ePER3\u003c/em\u003e rs228644, \u003cem\u003eREV1\u003c/em\u003e rs3792152, and \u003cem\u003eTIMELESS\u003c/em\u003e rs7302060) previously reported [20] to be associated with ovarian cancer were investigated in the current study. The details of SNPs were mentioned in \u003cstrong\u003eAdditional File1: Table S1\u003c/strong\u003e. The SNPs were selected for genotyping only based on their M.A.F (Minor allele frequency) value (\u0026gt;\u0026thinsp;0.03 in Gujrati Indians). Linkage disequilibrium (LD) SNPs were excluded from this study. The primers (amplification and extension) were designed by Sequenom Mass ARRAY\u0026reg; Assay Design 3.0 Software (Sequenom, San Diego, USA). The primers were mentioned in additional file 1: Table S3.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003eGenotyping and quality control\u003c/h2\u003e\n\u003cp\u003eFrom the 600 women (200 cases and 400 controls) who provided blood, sufficient DNA was extracted by using manufacturer protocol (Qiagen DNA isolation Kit cat no. 51206). All these subjects were genotyped by the (Sequenom Mass ARRAY platform) using the 384 well chip according to the standardized protocol which were replicated from the study [21]. Software Sequenom Typer was used for the analysis and management of data.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eThe odds ratios (OR) with their 95% confidence intervals (CI) as well as hardy Weinberg equilibrium were estimated by Plink v1.07. Clinical characteristics of cases and controls were compared using the chi-square t-test for variables (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). For the results, SNPs that were not following hardy Weinberg equilibrium (H.W.E) were not included in further analysis.\u003c/p\u003e\n\u003cp\u003eLogistic regression \u0026amp; stratification analysis was used to estimate the risk or to estimate the association with Odds Ratio at 95% confidence interval and respective level of significance as p-value by using SPSS software. The power of the study was calculated statistically by PS software version 3.1.2 [22].\u003c/p\u003e\n\u003cp\u003ePutative visualization of variants in the human genome was also done by freely available Insilco tools (SNIPA and Haploreg) [23] [24]. Both tools were used to found the functional annotations i.e., to predict the expression quantitative trait locus (eQTL) of risk associated variants and to find the high linkage disequilibrium SNPs (\u003cem\u003er\u003c/em\u003e2\u0026thinsp;\u0026gt;\u0026thinsp;0.8) with selected candidate variants.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFour histopathological types of cases were analyzed. The sample characterized are discussed in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. As estimated, significant differences were observed between cases and controls on ovarian cancer risk factors including age, BMI, age at menarche, breast nodules, oral contraceptive use, and menopausal status (P values\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eA total of 5 SNPs in association with circadian rhythm was included in the current 2 SNPs (\u003cem\u003eREV1\u003c/em\u003e rs3792152 \u0026amp; \u003cem\u003eBMAL1\u003c/em\u003e rs4757151) of circadian rhythm were found to be associated with the risk of ovarian cancer (OR\u0026thinsp;=\u0026thinsp;1.6, with 95% CI\u0026thinsp;=\u0026thinsp;0.12\u0026ndash;1.2, p\u0026thinsp;=\u0026thinsp;0.0003) and (OR\u0026thinsp;=\u0026thinsp;1.847, with 95% CI\u0026thinsp;=\u0026thinsp;1.406\u0026ndash;2.426, p\u0026thinsp;=\u0026thinsp;9.15E-06) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). After logistic regression with age and BMI, rs3792152 of \u003cem\u003eREVI\u003c/em\u003e having genotype AA was found to be associated with increased risk of ovarian cancer (AA\u0026thinsp;+\u0026thinsp;AG vs. GG: adjusted OR\u0026thinsp;=\u0026thinsp;1.97, 95% CI 1.25\u0026ndash;3.1, p\u0026thinsp;=\u0026thinsp;0.003) and rs4757151 of \u003cem\u003eBMAL1\u003c/em\u003e having genotype AA was also associated with the increased risk of ovarian cancer (AA\u0026thinsp;+\u0026thinsp;AG vs. GG: adjusted OR\u0026thinsp;=\u0026thinsp;2.4, 95% CI (1.48\u0026ndash;3.87), p\u0026thinsp;=\u0026thinsp;0.0003.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eAllele frequency of SNPs in ovarian cancer\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eS. No\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGENE\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSNPS\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCASES\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCONTROLS\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eALLELE OR\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP\u003c/p\u003e\n\u003cp\u003eVALUE\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eDOMINANT OR\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP\u003c/p\u003e\n\u003cp\u003eVALUE\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eHWE\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eREVI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ers3792152\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u0026thinsp;=\u0026thinsp;0.5775\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u0026thinsp;=\u0026thinsp;0.4571\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.6(1.2\u0026ndash;2.08)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.97(1.25\u0026ndash;3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.9184\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u0026thinsp;=\u0026thinsp;0.4225\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u0026thinsp;=\u0026thinsp;0.5429\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eARNTL\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e/BMALI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ers1026071\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u0026thinsp;=\u0026thinsp;0.3289\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u0026thinsp;=\u0026thinsp;0.3077\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.1(0.83\u0026ndash;1.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.27(0.86\u0026ndash;1.86)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.222\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.2334\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u0026thinsp;=\u0026thinsp;0.6711\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u0026thinsp;=\u0026thinsp;0.6923\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eARNTL\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e/BMALI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ers4757151\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u0026thinsp;=\u0026thinsp;0.5458\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u0026thinsp;=\u0026thinsp;0.3941\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.84(1.4\u0026ndash;2.42)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e9.15E-04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.4(1.48\u0026ndash;3.87)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.00034\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.7339\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u0026thinsp;=\u0026thinsp;0.4542\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u0026thinsp;=\u0026thinsp;0.6059\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePER3\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ers228644\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u0026thinsp;=\u0026thinsp;0.4218\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u0026thinsp;=\u0026thinsp;0.4716\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.81(0.59\u0026ndash;1.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.204\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.69(0.41\u0026ndash;1.19)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.186\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00261\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u0026thinsp;=\u0026thinsp;0.5782\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u0026thinsp;=\u0026thinsp;0.5284\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTIMELESS\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ers7302060\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC\u0026thinsp;=\u0026thinsp;0.4085\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC\u0026thinsp;=\u0026thinsp;0.3469\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.3(0.97\u0026ndash;1.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.48(0.96\u0026ndash;2.28)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.072\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.8051\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eT\u0026thinsp;=\u0026thinsp;0.5915\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eT\u0026thinsp;=\u0026thinsp;0.6531\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe SNPs rs1026071 of \u003cem\u003eBMAL1 (\u003c/em\u003eOR\u0026thinsp;=\u0026thinsp;1.1,95% CI (0.83\u0026ndash;1.45), p\u0026thinsp;=\u0026thinsp;0.48) \u0026amp; variant rs7302060 (OR\u0026thinsp;=\u0026thinsp;1.3,95% CI (0.97\u0026ndash;1.73), p\u0026thinsp;=\u0026thinsp;0.07) of \u003cem\u003eTIMELESS\u003c/em\u003e gene was found not associated with the ovarian cancer (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The variant rs228644 of \u003cem\u003ePER3\u003c/em\u003e was not following HWE (hardy Weinberg equilibrium) and thus was not analyzed further.\u003c/p\u003e\n\u003cp\u003eThe putative visualization of significantly associated variants (rs3792152 of \u003cem\u003eREVI\u003c/em\u003e \u0026amp; rs4757151 of \u003cem\u003eBMAL1\u003c/em\u003e) was done by Haploreg v4.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubs.broadinstitute.org/mammals/haploreg/haploreg.php\u003c/span\u003e\u003c/span\u003e) and SNIPA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://snipa.helmholtz-muenchen.de/snipa3/\u003c/span\u003e\u003c/span\u003e). These tools predict the possible mechanism underlying the identified associations and determine proxy variants of the identified variants. Haploreg identified that both variants rs3792152 of the \u003cem\u003eREVI\u003c/em\u003e gene and rs4757151 of the \u003cem\u003eBMAL1\u003c/em\u003e genes were located in enhancer histone marks. Both risks associated with intronic variants were predicted to change the regulatory binding motifs \u003cstrong\u003e(Additional File1: Supplementary Figures S1 and Supplementary Figure S2).\u003c/strong\u003e SNIPA identified that the intronic variant rs3792152 was predicted to have a direct regulatory effect on \u003cem\u003eC2orf15, LIPT1, LYG1, MITD1, REV1, TSGA10, TXNDC9\u003c/em\u003e through eQTL \u003cem\u003e(\u003c/em\u003eExpression quantitative trait loci) with \u003cem\u003eREV1\u003c/em\u003e gene, whereas intronic variant rs4757151 was predicted to have a direct regulatroy effect on transcripts (\u003cem\u003eRN7SKP151\u003c/em\u003e \u0026amp; \u003cem\u003eBTBD10)\u003c/em\u003e through eQTL \u003cem\u003eARNTL\u003c/em\u003e \u003cstrong\u003e(Additional File1: Supplementary Table S2 and Supplementary Figures S3 and Supplementary Figure S4).\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this case-control study, we reported the significant association of ovarian cancer with the variants of circadian rhythm gene pathway, predominantly with already reported ovarian cancer risk associated circadian gene variants (\u003cem\u003eBMAL1 / ARNTL\u003c/em\u003e rs475715 and rs1026071, \u003cem\u003ePER3\u003c/em\u003e rs228644, \u003cem\u003eREV1\u003c/em\u003e rs3792152, and \u003cem\u003eTIMELESS\u003c/em\u003e rs7302060) [20]. We examined variation in the four most common genes of the circadian pathway (\u003cem\u003eREV1, ARNTL/BMAL1, TIMELESS\u003c/em\u003e, and \u003cem\u003ePER3\u003c/em\u003e) as prognosticators of ovarian cancer risk and invasiveness. We found that two out of five variants were associated with the risk of ovarian cancer. Specifically, the risk of ovarian cancer was associated with variant rs475715 of \u003cem\u003eBMAL1/ARNTL\u003c/em\u003e \u0026amp; rs3792152 of \u003cem\u003eREV1\u003c/em\u003e, whereas other variant rs228644 of \u003cem\u003ePER3\u003c/em\u003e, rs7302060 of \u003cem\u003eTIMELESS\u003c/em\u003e, and rs1026071 of \u003cem\u003eARNTL\u003c/em\u003e were found to be not associated with ovarian cancer in our studied region.\u003c/p\u003e\n\u003cp\u003eBiological clock in humans called circadian clock / circadian rhythm, autonomously oscillate with a period near 24 hours. The mechanism of the circadian clock is based on the positive/negative response circlets which are produced by core circadian clock genes. The monitoring feedback loop of circadian rhythm consists of \u003cem\u003ePER\u003c/em\u003e, \u003cem\u003eCRY\u003c/em\u003e, \u003cem\u003eCLOCK\u003c/em\u003e, and \u003cem\u003eBMAL1\u003c/em\u003e proteins having a function of regulations in the transcription/translation process. The heterodimer (\u003cem\u003eBMAL1/CLOCK\u003c/em\u003e) complex inhibiting or repressing the \u003cem\u003ePER/CRY\u003c/em\u003e genes activity in the nucleus region where the monitoring feedback loop formation is completed after the complex (\u003cem\u003eBMAL1/CLOCK\u003c/em\u003e) formation which regulates the transcription of Rev-erb\u0026alpha; and Rora (nuclear receptors)[25].\u003c/p\u003e\n\u003cp\u003eFindings regarding the circadian rhythm seem to be initiated by both transcriptional and post-transcriptional mechanisms which induce gene expression [26, 27]. The transcription of \u003cem\u003ePER\u003c/em\u003e and \u003cem\u003eCRY\u003c/em\u003e genes is initiated by two transcription factors \u003cem\u003eCLOCK\u003c/em\u003e and \u003cem\u003eBMAL1\u003c/em\u003e / \u003cem\u003eARNTL\u003c/em\u003e. After reaching the grave concentration the \u003cem\u003ePER / CRY\u003c/em\u003e reduces the effect of \u003cem\u003eCLOCK\u003c/em\u003e/ \u003cem\u003eBMAL1\u003c/em\u003e facilitated initiation of their particular genes in a negative feedback loop. It was found that both complex \u003cem\u003ePER / CRY\u003c/em\u003e and \u003cem\u003eCLOCK\u003c/em\u003e/ \u003cem\u003eBMAL1\u003c/em\u003e intricate with each other and bound to chromatin. The regular daily oscillations in clock gene is contributed by protein degradation, phosphorylation, and nuclear entry [28]. The regulation of \u003cem\u003eCRY\u003c/em\u003e and \u003cem\u003ePER\u003c/em\u003e gene expression generates genetic and biochemical evidence [29] but the regulation of the \u003cem\u003eCLOCK\u003c/em\u003e/ \u003cem\u003eBMAL1\u003c/em\u003e gene is very much less known. Various studies reported that \u003cem\u003ePER\u003c/em\u003e and \u003cem\u003eCRY\u003c/em\u003e gene establishes a positive feedback loop in the process of \u003cem\u003eBMAL1\u003c/em\u003e transcription [28\u0026ndash;30]\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eREV1\u003c/em\u003e (REV1-DNA directed polymerase) is a nuclear receptor that acts as a transcriptional repressor in the circadian pathway, where activates and inhibits the transcription of the \u003cem\u003eBMAL1\u003c/em\u003e gene [31]. The \u003cem\u003eBMAL1\u003c/em\u003e transcription is regulated by \u003cem\u003eREV-ERB\u003c/em\u003e alpha, thus it acts as a connector link through which components of negative and positive limb constitute to form a molecular link. It determines the length of the period and phase-shifting properties of the biological clock [30]. It was proved that \u003cem\u003eBMAL1\u003c/em\u003e deficient cells due to DNA damage lead to arrest in cell cycle and reveal a possible modulatory effect on tumor suppressor genes i.e. \u003cem\u003eP53\u003c/em\u003e. It has been reported that the knockdown of the \u003cem\u003eBMAL1\u003c/em\u003e gene induces cell growth, reduced programmed cell death which appears to play a role in carcinogenesis [32].\u003c/p\u003e\n\u003cp\u003eOur study is the first replicative case-control association study of clock genes. Jin et al [20] reported that the gene expression of the \u003cem\u003eBMAL1\u003c/em\u003e gene has been controlled by \u003cem\u003ecMYC\u003c/em\u003e where the overexpression of \u003cem\u003ecMYC\u003c/em\u003e leads to the downregulation of \u003cem\u003eBMAL1.\u003c/em\u003e So, it has been suggested that \u003cem\u003eBMAL1\u003c/em\u003e gene variants were significantly associated with the risk of ovarian cancer. The circadian gene variants are associated with prostate cancer which was reported in the GWAS study [33]. In some populations of the world, it has been reported that night workers have disturbed biological clocks where the findings of various studies proved the night working women\u0026rsquo;s and men\u0026rsquo;s are more prone to cancers (Breast, ovary, and prostate cancer) [19, 33\u0026ndash;35]. Our results indicated that BMAL1 and REV1: rs475715 \u0026amp; rs3792152 both intronic variants, were associated with ovarian cancer risk. Functional prediction implicated that rs47515 has direct eQTL effect and regulates the expression of \u003cem\u003eC2orf15, LIPT1, LYG1, MITD1, REV1, TSGA10, and TXNDC9\u003c/em\u003e genes, whereas rs3792152 regulates the \u003cem\u003eRN7SKP151\u003c/em\u003e \u0026amp; \u003cem\u003eBTBD10\u003c/em\u003e with \u003cem\u003eBMAL1\u003c/em\u003e gene. These findings suggest that it is located within a region that directly affects expression potentially through the modulation of the histone markers in the enhancer region. Yeh et al, 2014 [36] proved that in the ovarian cancer cell (in CP70 and MCP2) the H3K27 (histone mark) is supplemented in the promoter region of \u003cem\u003eARNTL / BMAL1\u003c/em\u003e gene, Whereas the presence of inhibitor (GSK126) of EZH2 region reestablished the expression of \u003cem\u003eARNTL/ BMAL1\u003c/em\u003e gene in ovarian cancer cells (in CP70 and MCP2). They also confirmed that there is a sensitivity of chemotherapy drug (cisplatin) in ovarian cancer cells after increasing the expression of the \u003cem\u003eARNTL / BMAL1\u003c/em\u003e gene. With these findings, it was confirmed that \u003cem\u003eBMAL1 /ARNTL\u003c/em\u003e may act as a tumor suppressor by regulating the p53 tumor suppressor pathway in ovarian cancer [20, 36]. So, our results climax the implication of circadian rhythm gene variation in ovarian cancer susceptibility and suggest an early role for the \u003cem\u003eBMAL1\u003c/em\u003e and \u003cem\u003eREV1\u003c/em\u003e gene in ovarian cancer pathogenesis.\u003c/p\u003e\n\u003cp\u003eOur results also suggest that the circadian gene variant may play a significant role in the etiology of ovarian cancer. From the literature survey, the identification of a significant association between circadian genes and ovarian cancer is still unpredictable. To the best of our knowledge, the case-control association studies between circadian gene variants and ovarian cancer were investigated in very few studies (20,25\u0026ndash;29). Few of them have found an association with ovarian cancer and other cancers at the variant level [20, 37\u0026ndash;39]. Even though various previous research studies have implicated circadian genes in the progression of cancers in women. Nevertheless, our study possibly requires more variants of the circadian rhythm pathway to highlight significant associations between certain circadian genes and the risk of aggressive ovarian cancer.\u003c/p\u003e"},{"header":"Conclusion","content":" \u003cp\u003eThis study fortifies the current indication supporting the premise of a link between circadian rhythm genes and ovarian cancer risk. Additional studies with larger sample size as well as functional validation of risk associated gene variants is warranted to confirm those findings. Besides these it has been reported that women working during nightshifts are associated with several cancer but its probable role in finding the association between circadian genes and ovarian cancer risk should not be justified till date so this study proposes the need for further studies to investigate the association of carcinogenic effects of circadian disruption in relation with environmental factors, such as night-workers, regular exposure to stressed conditions, irregular diet patterns, and electromagnetic (EM) waves, which disturb circadian rhythm or biological clock by fluctuating the melatonin levels.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eeQTL: expression quantitative trait locus.\u003c/p\u003e\n\u003cp\u003eM.A.F: Minor allele frequency\u003c/p\u003e\n\u003cp\u003eLD: Linkage disequilibrium\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence and requests related to manuscript should be addressed to R.S or R.K. There is no any copyright material in this manuscript. The data has been incorporated is a result of analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RS, RK and SV thankfully acknowledge the Indian Council of Medical Research (5/10/15/CAR-SMVDU/2018-RBMCH). SV acknowledges Dr. Swarkar Sharma, Dr. Indu Sharma and Dr. Varun Sharma for the suggestions during the scheduling and execution of study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe financial support to conduct this study was provided by Indian Council of Medical Research (5/10/15/CAR-SMVDU/2018-RBMCH) for purchasing consumables and equipment\u0026rsquo;s.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eR.S, R.K and S.V planned the study. S.V, A.B, G.R.B, B.S and D.B collected the samples. S.V, R.S, A.B and GRB performed experiment in lab. S.V analyzed the results and drafted manuscript. R.S, R.K, A.B, S.S, R.A.Q, H.R and G.C provided critical comments regarding manuscripts. A.W, J.S and H.R provided samples for the study. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board committee of SMVDU with wide reference no. SMVDU/IERB/14/28. Experimental protocols conducted in this study strictly followed the guidelines set by the Institutional Ethical Review Board (IERB) SMVDU.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn behalf of all authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eReid BM, Permuth JB, Sellers TA: \u003cstrong\u003eEpidemiology of ovarian cancer: a review\u003c/strong\u003e. \u003cem\u003eCancer Biol Med \u003c/em\u003e2017, \u003cstrong\u003e14\u003c/strong\u003e(1):9-32.\u003c/li\u003e\n\u003cli\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A: \u003cstrong\u003eGlobal cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries\u003c/strong\u003e. \u003cem\u003eCA: a cancer journal for clinicians \u003c/em\u003e2018, 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\u003cstrong\u003e20\u003c/strong\u003e(22):5704.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mgnm","sideBox":"Learn more about [BMC Medical Genomics](http://bmcmedgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mgnm/default.aspx","title":"BMC Medical Genomics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Single Nucleotide Polymorphisms (SNPs), Jammu and Kashmir (J\u0026K) and Ovarian Cancer (OC)","lastPublishedDoi":"10.21203/rs.3.rs-257989/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-257989/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eDisruption in biological clock due to genetic variations is associated with increased occurrence of cancers such as breast, ovary, prostate, gastrointestinal and hematological malignancies. Circadian rhythm genes regulate the process of ovulation in the ovaries and are highly expressed in ovarian tumors; whereas disturbance in the circadian rhythm pathway is significantly associated with causative risk factors (i.e. endometriosis, PCOS, etc.) of ovarian cancer. Nevertheless, very few studies have been conducted till date where candidate SNPs of circadian rhythm genes proved as the main prognosticators of ovarian cancer risk and intrusiveness. The main purpose of this study was to investigate some common single nucleotide polymorphisms (SNPs) in circadian rhythm genes\u0026nbsp;(rs475715 of\u003cem\u003e BMAL1\u003c/em\u003e/\u003cem\u003eARNTL\u003c/em\u003e, rs1026071, and rs228644 of \u003cem\u003ePER3, \u003c/em\u003ers3792152 of\u003cem\u003e REV1\u003c/em\u003e, and rs7302060 of\u003cem\u003e TIMELESS\u003c/em\u003e) as causative markers of ovarian cancer risk of in the population of Jammu and Kashmir in India. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eOur study included a total of 600 samples (200 cases and 400 age and sex-matched controls). Analysis of the genotype data from the selected SNPs indicated most significant association of rs3792152 of\u0026nbsp;\u003cem\u003eREV1\u003c/em\u003e\u0026nbsp;(OR=1.6, with 95% CI=0.12-1.2, p=0.0003) and rs4757151 of \u003cem\u003eBMAL1/ARNTL \u003c/em\u003e(OR=1.847, with 95% CI=1.406-2.426, p=9.15E-06) with the ovarian cancer\u003cem\u003e.\u003c/em\u003e The functional putative analysis revealed a significant regulatory effect of both these variants on other genes. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThese results suggest that some SNPs in circadian rhythm genes, particularly\u0026nbsp;\u003cem\u003eBMAL1/ARNTL \u003c/em\u003eand \u003cem\u003eREV1\u003c/em\u003e, might be associated with the risk of ovarian cancer in the J\u0026amp;K population of North India.\u003c/p\u003e","manuscriptTitle":"Analysis of Genetic Variation in Circadian Rhythm Genes and Risk of Ovarian Cancer.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-03-02 15:10:30","doi":"10.21203/rs.3.rs-257989/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2021-02-12T00:00:00+00:00","index":"","fulltext":""},{"type":"decision","content":"Revise before sending to peer reviewers","date":"2021-02-12T00:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-02-11T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-02-11T23:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"","date":"2021-02-10T00:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mgnm","sideBox":"Learn more about [BMC Medical Genomics](http://bmcmedgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mgnm/default.aspx","title":"BMC Medical Genomics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9d86c4f4-cf0e-4158-bb70-90748ceb4b07","owner":[],"postedDate":"March 2nd, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":2713648,"name":"Epigenetics \u0026 Genomics"}],"tags":[],"updatedAt":"2021-03-02T15:10:30+00:00","versionOfRecord":[],"versionCreatedAt":"2021-03-02 15:10:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-257989","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-257989","identity":"rs-257989","version":["v1"]},"buildId":"ehx78VzkSd0WSzXnipQa-","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}