Review Article

Metabolic Syndrome and Risk of Colorectal Adenoma and Colorectal Cancer: A Meta-Analysis

Salah Eddine ELHARAG 1 , Youssouf TRAORÉ 1 Méghit Boumediène KHALED 1,2 *

1 Department of Biology, Faculty of Natural and Life Sciences, Djillali Liabes University,

PO Box 89, Sidi-bel-Abbes (22000), Algeria 

2 Department of Biology, Faculty of Natural and Life Sciences, Laboratory of Health & Environment Djillali Liabes University,

PO Box 89, Sidi-bel-Abbes (22000), Algeria 

* Corresponding author

Tel: +213 551 152 261   

khaled@khaledmb.co.uk

Article edited by : 

Dr. Lamia BENBRAHIM-TALLAA

Dr. Mickaël RIALLAND

 

Received 25 September 2017

Accepted 26 October 2017

Available online 28 October 2017

https://doi.org/10.5281/zenodo.1245604

                

A B S T R A C T

BACKGROUND: Growing evidence suggests that metabolic syndrome (MetS) could be linked with the incidence of colorectal adenoma and cancer (CRA and CRC). AIMS: Conducting a meta analysis to assess the association of MetS with both CRA and CRC. METHODS AND MATERIAL: Relevant studies were identified by systematically searching PubMed database for articles published in the last ten years. A random effect analysis model and Mantel-Haenszel statistical method were used to obtain pooled risk ratios (RRs) and their 95% confidence intervals (CIs) for dichotomous data. The analyses were assessed for heterogeneity and publication bias. RESULTS: 35 studies were included in the meta-analysis involving approximately 13 000 00 participants. A significant high risk for CRA was observed among patients with MetS compared to those without (RR = 1.43; 95% CI = 1.31, 1.57). The pooled RRs of CRC were 1.46 (95% CI = 1.36, 1.56). The risk estimates varied according to the type of the study (cohorts and non-cohorts), gender (men and women), MetS definition (NCEP-ATPIII, IDF, harmonized and others), populations (Asia, Europe, and the USA), and cancer location (colon and rectum). CONCLUSIONS: MetS is associated with an increased risk of CRA and CRC. The risk was higher for advanced adenomas. Taking into consideration MetS patients in the secondary prevention programs and the management of this condition in the aim of the primary prevention is highly recommended.

Keywords: Metabolic syndrome, Colorectal cancer, Colorectal adenoma, Incidence, Meta-analysis

1. INTRODUCTION


 

Colorectal cancer (CRC) is a true public health burden recording more than 1.3 million cases (9.7% of all cancers), and approximately 0.7 million deaths (8.5% of all cancers) worldwide [1]. Age, sex, ethnicity [2], family history of CRC [3], inherited genetic predispositions [4–6], and inflammatory diseases [7, 8] play an essential role in CRC pathophysiology along with other risk factors including diet [9–11], smoking [12], physical inactivity [13], diabetes [14], and MetS [15]. MetS has become a growing public health and a clinical challenge too. 20-25% of world’s adult population has MetS according to the International Diabetes Federation (IDF) [16]. MetS is defined by a cluster of correlated physiological, biochemical, clinical, and metabolic factors reflecting a cohesive pathophysiology. Those factors include visceral obesity, dyslipidemia, hyperglycemia, and hypertension that increase the risk of developing type 2 diabetes mellitus and cardiovascular diseases [17–19]. The association between MetS and CRC has been previously addressed in several studies, although the unavailability of evidence linking MetS with the precancerous lesions (adenomas, adenomatous polyps). Additionally, CRC is supposed to develop following the adenoma-carcinoma sequence [4], and those adenomas precede the cancer stage by several years which could allow for its prevention by targeting those precancerous lesions in the screening programs. Hence, understanding the correlation between CRA and MetS is crucial in clinical practice. Results from studies that addressed the association linking MetS and colorectal neoplasms (CRN) (CRA (colorectal adenoma) and CRC) were inconsistent [20, 21]. In the present meta-analysis, we aimed to tackle this issue, focusing especially on the effect of the full syndrome on CRC and CRA incidence.

 

2. METHODS

Search strategy

The meta-analysis was carried out following the Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA) guidelines [22]. The literature search was independently undertaken by two authors (S.E and Y.T). The author (MB.K) made the final decision in case of any discrepancy. Key terms according to the Medical subject headings (MeSh) were used to identify relevant studies on the relationship between colorectal neoplasm and MetS in PubMed database. Full English studies, published during the past 10 years until 2017/08/01, were systematically searched and the terms used were: "colorectal neoplasms", "colorectal cancer", and "metabolic syndrome".

 

Study selection

Study eligibility was independently assessed by two reviewers (S.E and Y.T), and resolutions, in case of disagreements, were achieved by the author (MB.K).

Cohort, case-control, and cross-sectional studies with MetS as well as CRA and/or CRC incidence were eligible for the analysis. Studies were included if they met the following criteria: (a) CRA and/or CRC as the outcomes considered in the study, (b) MetS as the exposure, (c) the study must provide sufficient data to calculate the RRs and their 95% CIs, (d) the study must state the definition of MetS used. Furthermore, reviews, meta-analyses, articles not published in English, articles not published as full text (case reports, letters to editors, editorials, comments, news etc.), and in vitro or studies where the subjects were organisms other than humans were excluded. The selection of any article was primarily based on title and abstract in order to exclude irrelevant studies. Subsequently, the full texts were strictly analyzed to determine the relevancy of any retrieved study.

 

Data extraction

Data extracted from each included study were: the first author’s name, the year of publication, the country where the study was undertaken, duration of the study, type of lesions, number of subjects, number of events, and the definition of MetS used. Two authors (S.E and Y.T) independently gathered the relevant data.

 

Statistical analysis

Summary measures

A random effect meta-analysis model, which represents the assumption that there is a distribution of true effect sizes and aims to estimate the mean of this distribution [23], was used in our main meta-analysis to assess the relative risks (RRs) and their 95% confidence intervals (CIs) for dichotomous data. Mantel-Haenszel method was used to estimate the amount of the between-study variation. The between-study variance was assessed using the Tausquared (Τ 2 ) statistic. Z-test of the null hypothesis was calculated and P < 0.05 was considered statistically significant.

Synthesis of results

Cochran’s test or Q-test (Χ 2 ) was used to indicate the extent of heterogeneity and P < 0.05 was considered statistically significant. The I2 statistic, which measures the degree of inconsistency across studies in a meta-analysis and which describes the percentage of total variation across studies that is due to heterogeneity rather than chance [24], was as well obtained. A value of 40% suggests low heterogeneity, 40-70% indicates moderate heterogeneity, and a value of > 70% may suggest high heterogeneity. Funnel plots were obtained and visually assessed for risk of publication bias.

Subgroup analysis

Subgroup analysis was undertaken to explore source of heterogeneity according to study design (cohort, casecontrol, and cross-sectional), gender (men and women), MetS definition (NCEP-ATPIII, IDF, the harmonized definition, and other definitions), geography (the USA, Asia, and Europe), cancer site (colon or rectal cancer).

3. RESULTS 

Study selection

The process of selecting studies is displayed in the flowchart on Figure 1. 263 studies were identified through a database search. 179 studies unrelated to the topic and studies unpublished as full text or in the English language were excluded. 84 eligible studies reported MetS and CRA/CRC were retrieved and scanned carefully. 49 studies providing inadequate exposures, outcomes, or data and studies unfitting inclusion criteria were excluded out of the eligible studies. Eventually, 35 studies fulfilled the inclusion criteria comprised the meta-analysis.

 

Study characteristics

Table 1 summarizes properties of the included studies. Our meta-analysis comprised nine cohort studies [20, 21, 25–31], 13 case-control studies [32–44], and 13 cross-sectional studies [45–57]. 26 studies were undertaken in Asia [25, 26, 28–31, 33–35, 37, 38, 42, 44–57] while eight were carried out in European countries [20, 27, 32, 36, 39– 41, 43], and only one study was performed in the USA [21]. Regarding the outcomes considered, 22 studies provided data on CRA risk [21, 25, 26, 28–31, 34–36, 44, 46, 47, 49– 57], 18 concerning CRC [20, 26, 27, 29, 30, 32, 33, 36–43, 45, 46, 48], whereas 5 studies on both outcomes [26, 29, 30, 36, 46]. Furthermore, 20 studies utilized the definition formulated by the NCEP/ATPIII as diagnosis criteria in clinical practice [20, 25–29, 34, 36, 40, 41, 44, 46, 47, 49, 50, 52–55, 57], six studies provided the exposure data in basis of the IDF definition of MetS [20, 32, 38, 41, 43, 56], three used the harmonized definition [39, 41, 51], and nine presented MetS data patients using other definitions [21, 30, 31, 33, 35, 37, 42, 45, 48].

 

Association of MetS with CRA

A random effect meta-analysis model of 22 studies comprising 30 datasets of CRA incidence in individuals with MetS versus without MetS supported the association between MetS and CRA (RR = 1.43; 95% CI = 1.31, 1.57) (Figure 2; Table 2). No evidence of publication bias was observed (Figure 3). The risk estimation showed significant differences between cohort, case-control, and cross-sectional studies, this latter revealed a moderate heterogeneity (I2 = 32%).

The summary of RRs for Asians was significant, but not for the other populations, similarly to studies reporting results for both sexes. The pooled analysis for risk estimates of studies using the NCEP/ATPIII definition of MetS were similar to studies using other definitions (RR = 1.43; 95% CI = 1.28, 1.59) and (RR = 1.45; 95% CI = 1.36, 1.55) respectively.

Association of MetS with advanced adenomas

A fixed-effect meta-analysis model, since there was no evidence of heterogeneity, consisting of six studies and seven datasets reporting the incidence of advanced adenomas among individuals with MetS as compared with individuals without MetS gave evidence of a strong association (Table 2). A RR of 1.85 (95% CI = 1.58, 2.17) was observed, with no heterogeneity (P = 0.61, I2 = 0%).

Association of MetS with CRC

Eighteen studies including 45 datasets were available for the meta-analysis (Figure 4; Table 2). MetS patients showed an RR of 1.46 (95% CI = 1.36, 1.56) to develop CRC compared with individuals without MetS.

Differences between cohort, case-control, and cross-sectional studies were noticed. No significant heterogeneity was observed for cross-sectional studies (P = 0.68) and no evidence of publication bias was noticed (Figure 5). Positive and significant risk estimates were obtained for both Asian and European populations and for studies provided data for both sexes separately. Comparing studies using different definitions of MetS, studies using the harmonized definition and the other definitions had the lowest and the highest risk with no significant heterogeneity (RR = 1.22; 95% CI = 1.07, 1.38; P value for heterogeneity = 0.08) and (RR = 1.74; 95% CI = 1.58, 1.91; P value for heterogeneity = 0.32) respectively. Our results showed that the risk of developing rectal cancer is slightly lower than that of colon cancer with an RR of 1.45 (95% CI = 1.29, 1.63) and 1.53 (95% CI = 1.41, 1.67) correspondingly.

 

Colorectal adenomas versus colorectal cancer

 

We weighted the association of MetS with CRA and CRC using the same datasets. Five studies reported data for both CRA and CRC. The comparison showed that the risk of developing CRC is 10% higher than the risk of developing CRA (RR = 1.48; 95% CI = 1.20, 1.82) and (RR = 1.38; 95% CI = 1.13, 1.68) respectively.

 

4. DISCUSSION

 

Our meta-analysis of 35 studies provided evidence that metabolic syndrome increases the risk of colorectal neoplasm, especially for advanced adenoma and colorectal cancer. To sum up, the results showed 46% and 43% increased CRC and CRA risk among subjects with MetS compared to those without MetS.

Including different types of studies (cohort, case-control, and cross-sectional), MetS definition (NCEP/ATPIII, IDF, the harmonized, and other), gender (men and women), populations (Asia, Europe, and the USA), and the type and location of the lesion slightly influenced the risk estimates. Several factors and signaling pathways are reported to be implicated. The insulin receptor and the IGF-1 receptor are over-stimulated which reduces apoptosis and promotes cancer cells proliferation. Insulin favors type II T helper cell production by modulating the polarization of effector T cells which indirectly favors cancer cells progression and metastasis [58]. In a case-control study including 615 CRC patients and 650 control healthy individuals, high levels of IGF-1 were possibly linked with the initiation of CRC [59]. Moreover, the adipose tissue is the largest endocrine organ of the human body producing free fatty acids, different cytokines (interleukin 6, monocyte chemoattractant protein 1, tumor necrosis factor-α) and hormones (leptin, aromatase, adiponectin, plasminogen activator inhibitor 1), which may be involved in cancer genesis and progression [60, 61].

TNF-α, IL-6, and IL-1β can promote pro-inflammatory gene expression and induce CRC cell lines to express a variety of cytokines and chemokines that recruit and activate APCs and granulocytes through numerous signaling pathways such as MAPK-, JAK/STAT, and NF-κ B-mediated signaling. Similarly, inflammation-induced DNA damage has been linked to altered expression of genes involved in CRC such as p53, APC, KRAS, and BCL- 2 [62]. For instance, the expression of leptin in tissues of 80 CRC patients was assessed in a research study and the results revealed that leptin affects CRC stem cells growth and survival and induces the activation of JAK and ERK signaling pathways that regulate the invasion and adhesion of these cells [63].

MetS is as well strongly associated with other types of cancer [58]. A study was undertaken in the USA has concluded that subjects with prostate cancer have a high prevalence of MetS [64]. In accordance, a Japanese retrospective cohort study endeavored to elucidate the relationship between MetS and the incidence of cancer found that MetS increased the risk of breast cancer and prostate cancer [65].

Although, epidemiological studies provide a strong evidence of an association between MetS and colorectal neoplasm, our understanding of the biological mechanism underlying this association is incomplete. This may be due to the complex pathophysiology and the numerous common factors such as those shared between both diseases [66].

Concerning incidence risk of CRC and MetS, our results agree with several studies. Although the incidence was low compared to our findings, Jinjuvadia et al. reported an increased risk of developing CRA, and CRC among MetS patients (RR = 1.37; 95% CI = 1.26, 1.49) and (RR = 1.30; 95% CI = 1.18, 1.43) respectively [67].

Esposito et al. observed, in a meta-analysis of 17 studies, that MetS was linked with a higher incidence of CRC for women compared to men (RR = 1.41; 95% CI = 1.18, 1.70) for women and (RR = 1.33; 95% CI = 1.18, 1.50) for men [68] which is consistent with our results (RR = 1.47; 95% CI=1.32, 1.63) for women and (RR = 1.41; 95% CI = 1.25, 1.60) for men, though the difference in the magnitude of the risk estimate.

To the best of our knowledge, our meta-analysis could be the first investigating the association between MetS and CRA incidence.

There were some potential limitations in the current study such as the loss of some studies due to inclusion criteria, where non-English articles were excluded. Nevertheless, we found only one Chinese case-control study (included 135 CRC cases and 120 controls) that met the inclusion criteria [69]. There were 46 and 27 MetS patients in the case and control groups respectively. Some analyses showed evidence of heterogeneity. However, subgroup analysis demonstrated sources of heterogeneity. Furthermore, heterogeneity could be attributable to using different definitions of MetS and including cohorts and non-cohorts in the analyses.

5. CONCLUSION

 

In conclusion, our meta-analysis showed that MetS is associated not only with colorectal cancer but with earlier precancerous conditions such as colorectal adenomas and advanced adenomas too. Those conditions are the primary targets for screening programs aiming for an early detection and prevention of this malignancy. Patients with MetS should be included in such programs. Besides, subjects with MetS should consider lifestyle modifications like weight loss, physical activity, and diet [17, 70], along with management of its individual components. The implication of some pharmacological treatments with CRC development should be taking into consideration [71, 72].

6. REFERENCES

1. Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012: Globocan 2012. Int J Cancer. 2015;136(5):E359-E386. doi:10.1002/ijc.29210.

2. Moore JS, Aulet TH. Colorectal Cancer Screening. Adv Colorectal Neoplasia. 2017;97(3):487-502. doi:10.1016/j.suc.2017.01.001.

3. Johnson CM, Wei C, Ensor JE, et al. Meta-analyses of colorectal cancer risk factors. Cancer Causes Control. 2013;24(6):1207-1222. doi:10.1007/s10552- 013-0201-5.

4. Kuipers EJ, Grady WM, Lieberman D, et al. COLORECTAL CANCER. Nat Rev Dis Primer. 2015;1:15065. doi:10.1038/nrdp.2015.65.

5. Aran V, Victorino AP, Thuler LC, Ferreira CG. Colorectal Cancer: Epidemiology, Disease Mechanisms and Interventions to Reduce Onset and Mortality. Clin Colorectal Cancer. 2016;15(3):195-203. doi:10.1016/j.clcc.2016.02.008.

6. Carrer A, Giacca M, Giacca M. Molecular Parameters for Prognostic and Predictive Assessment in Colorectal Cancer. In: de Manzini N, ed. Rectal Cancer. Milano: Springer Milan; 2013:41-62. doi:10.1007/978-88-470-2670-4_4.

7. Jess T, Rungoe C, Peyrin–Biroulet L. Risk of Colorectal Cancer in Patients With Ulcerative Colitis: A Meta-analysis of Population-Based Cohort Studies. Clin Gastroenterol Hepatol. 2012;10(6):639- 645. doi:10.1016/j.cgh.2012.01.010.

8. Colussi D, Brandi G, Bazzoli F, Ricciardiello L. Molecular Pathways Involved in Colorectal Cancer: Implications for Disease Behavior and Prevention. Int J Mol Sci. 2013;14(8):16365-16385. doi:10.3390/ijms140816365.

9. Zhu B, Sun Y, Qi L, Zhong R, Miao X. Dietary legume consumption reduces risk of colorectal cancer: evidence from a meta-analysis of cohort studies. Sci Rep. 2015;5:8797. doi:10.1038/srep08797.

10. Godos J, Bella F, Torrisi A, Sciacca S, Galvano F, Grosso G. Dietary patterns and risk of colorectal adenoma: a systematic review and meta-analysis of observational studies. J Hum Nutr Diet. 2016;29(6):757-767. doi:10.1111/jhn.12395.

11. Vieira AR, Abar L, Chan D, et al. Foods and beverages and colorectal cancer risk: a systematic review and meta-analysis of cohort studies, an update of the evidence of the WCRF-AICR Continuous Update Project. Ann Oncol Off J Eur Soc Med Oncol. April 2017. doi:10.1093/annonc/mdx171.

12. Tsoi KKF, Pau CYY, Wu WKK, Chan FKL, Griffiths S, Sung JJY. Cigarette Smoking and the Risk of Colorectal Cancer: A Meta-analysis of Prospective Cohort Studies. Clin Gastroenterol Hepatol. 2009;7(6):682-688.e5. doi:10.1016/j.cgh.2009.02.016.

13. Zhou X-Y, Yan L, Wang L-L, Wang J. Association between physical activity and colorectal cancer risk and prognosis: A meta-analysis. Cancer Treat Res Commun. 2016;9:62-69. doi:10.1016/j.ctarc.2016.07.002.

14. Kort S de, Masclee AAM, Sanduleanu S, et al. Higher risk of colorectal cancer in patients with newly diagnosed diabetes mellitus before the age of colorectal cancer screening initiation. Sci Rep. 2017;7:46527. doi:10.1038/srep46527.

15. Ishino K, Mutoh M, Totsuka Y, Nakagama H. Metabolic syndrome: a novel high-risk state for colorectal cancer. Cancer Lett. 2013;334(1):56-61. doi:10.1016/j.canlet.2012.10.012.

16. The International Diabetes Federation (IDF). IDF Consensus Worldwide Definition of the Metabolic Syndrome. https://idf.org/e-library/consensusstatements/60-idfconsensus-worldwide-definitionof-the-metabolic-syndrome. Published 2006. Accessed July 17, 2017.

17. Kaur J. A Comprehensive Review on Metabolic Syndrome. Cardiol Res Pract. 2014;2014:e943162. doi:10.1155/2014/943162.

18. Sorrentino MJ. The Metabolic Syndrome. In: Sorrentino MJ, ed. Hyperlipidemia in Primary Care: A Practical Guide to Risk Reduction. Totowa, NJ: Humana Press; 2011:13-39. doi:10.1007/978-1- 60327-502-6_2.

19. LeRoith D, Vinik AI, eds. Controversies in Treating Diabetes. Totowa, NJ: Humana Press; 2008. doi:10.1007/978-1-59745-572-5.

20. Lu Y, Ness-Jensen E, Hveem K, Martling A. Metabolic Predispositions and Increased Risk of Colorectal Adenocarcinoma by Anatomical Location: A Large Population-Based Cohort Study in Norway. Am J Epidemiol. 2015;182(10):883-893. doi:10.1093/aje/kwv141.

21. Tsilidis KK, Brancati FL, Pollak MN, et al. Metabolic syndrome components and colorectal adenoma in the CLUE II cohort. Cancer Causes Control CCC. 2010;21(1):1-10. doi:10.1007/s10552-009-9428-6.

22. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred Reporting Items for Systematic Reviews and MetaAnalyses: The PRISMA Statement. J Clin Epidemiol. 2009;62(10):1006-1012. doi:10.1016/j.jclinepi.2009.06.005.

23. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods. 2010;1(2):97-111. doi:10.1002/jrsm.12.

24. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557. doi:10.1136/bmj.327.7414.557.

25. Chiu H-M, Lee Y-C, Tu C-H, et al. Effects of Metabolic Syndrome and Findings From Baseline Colonoscopies on Occurrence of Colorectal Neoplasms. Clin Gastroenterol Hepatol. 2015;13(6):1134-1142.e8. doi:10.1016/j.cgh.2014.10.022.

26. Lin X-F, Shi K-Q, You J, et al. Increased risk of colorectal malignant neoplasm in patients with nonalcoholic fatty liver disease: a large study. Mol Biol Rep. 2014;41(5):2989-2997. doi:10.1007/s11033- 014-3157-y.

27. Kruijsdijk RCM van, Graaf Y van der, Peeters PHM, Visseren FLJ, Group on behalf of the SM of Art disease (SMART) study. Cancer Risk in Patients with Manifest Vascular Disease: Effects of Smoking, Obesity, and Metabolic Syndrome. Cancer Epidemiol Prev Biomark. 2013;22(7):1267-1277. doi:10.1158/1055-9965.EPI-13-0090.

28. Huang K-W, Leu H-B, Wang Y-J, et al. Patients with nonalcoholic fatty liver disease have higher risk of colorectal adenoma after negative baseline colonoscopy. Colorectal Dis Off J Assoc Coloproctology G B Irel. 2013;15(7):830-835. doi:10.1111/codi.12172.

29. Kim BC, Shin A, Hong CW, et al. Association of colorectal adenoma with components of metabolic syndrome. Cancer Causes Control CCC. 2012;23(5):727-735. doi:10.1007/s10552-012-9942-9.

30. Kaneko R, Sato Y, An Y, et al. Clinico-epidemiologic study of the metabolic syndrome and lifestyle factors associated with the risk of colon adenoma and adenocarcinoma. Asian Pac J Cancer Prev APJCP. 2010;11(4):975-983.

31. Liu C-S, Hsu H-S, Li C-I, et al. Central obesity and atherogenic dyslipidemia in metabolic syndrome are associated with increased risk for colorectal adenoma in a Chinese population. BMC Gastroenterol. 2010;10:51. doi:10.1186/1471-230X-10- 51.

32. Harlid S, Myte R, Van Guelpen B. The Metabolic Syndrome, Inflammation, and Colorectal Cancer Risk: An Evaluation of Large Panels of Plasma Protein Markers Using Repeated, Prediagnostic Samples. Mediators Inflamm. 2017;2017:4803156. doi:10.1155/2017/4803156.

33. Pyo JH, Hong SN, Min B-H, et al. Evaluation of the risk factors associated with rectal neuroendocrine tumors: a big data analytic study from a health screening center. J Gastroenterol. 2016;51(12):1112- 1121. doi:10.1007/s00535-016-1198-9.

34. Pyo JH, Hong SN, Min B-H, et al. Is height a risk factor for colorectal adenoma? Korean J Intern Med. 2016;31(4):653-659. doi:10.3904/kjim.2014.313.

35. Hong SN, Lee TY, Yun S-C. The Risk of Colorectal Neoplasia in Patients with Gallbladder Diseases. J Korean Med Sci. 2015;30(9):1288-1294. doi:10.3346/jkms.2015.30.9.1288.

36. Trabulo D. Metabolic syndrome and colorectal neoplasms: An ominous association. World J Gastroenterol. 2015;21(17):5320. doi:10.3748/wjg.v21.i17.5320.

37. Jeon YJ, Kim JW, Park HM, et al. Interplay between 3′-UTR polymorphisms in the vascular endothelial growth factor (VEGF) gene and metabolic syndrome in determining the risk of colorectal cancer in Koreans. BMC Cancer. 2014;14:881. doi:10.1186/1471- 2407-14-881.

38. Ulaganathan V, Kandiah M, Zalilah MS, et al. Colorectal cancer and its association with the metabolic syndrome: a Malaysian multi-centric case-control study. Asian Pac J Cancer Prev APJCP. 2012;13(8):3873-3877.

39. Danese E, Montagnana M, Minicozzi AM, et al. The role of resistin in colorectal cancer. Clin Chim Acta Int J Clin Chem. 2012;413(7-8):760-764. doi:10.1016/j.cca.2012.01.019.

40. Kontou N, Psaltopoulou T, Soupos N, et al. Metabolic syndrome and colorectal cancer: the protective role of Mediterranean diet--a casecontrol study. Angiology. 2012;63(5):390-396. doi:10.1177/0003319711421164.

41. Aleksandrova K, Boeing H, Jenab M, et al. Metabolic Syndrome and Risks of Colon and Rectal Cancer: The European Prospective Investigation into Cancer and Nutrition Study. Cancer Prev Res (Phila Pa). 2011;4(11):1873. doi:10.1158/1940-6207.CAPR-11- 0218.

42. Shen Z, Wang S, Ye Y, et al. Clinical study on the correlation between metabolic syndrome and colorectal carcinoma. ANZ J Surg. 2010;80(5):331- 336. doi:10.1111/j.1445-2197.2009.05084.x.

43. Pelucchi C, Negri E, Talamini R, et al. Metabolic syndrome is associated with colorectal cancer in men. Eur J Cancer. 2010;46(10):1866-1872. doi:10.1016/j.ejca.2010.03.010.

44. Kang HW, Kim D, Kim HJ, et al. Visceral Obesity and Insulin Resistance as Risk Factors for Colorectal Adenoma: A Cross-Sectional, Case–Control Study. Am J Gastroenterol. 2009;105(1):178-187. doi:10.1038/ajg.2009.541.

45. Pan S, Hong W, Wu W, et al. The relationship of nonalcoholic fatty liver disease and metabolic syndrome for colonoscopy colorectal neoplasm. Žarko. B, ed. Medicine (Baltimore). 2017;96(2):e5809. doi:10.1097/MD.0000000000005809.

46. Koo JE, Kim K-J, Park HW, et al. Prevalence and risk factors of advanced colorectal neoplasms in asymptomatic Korean people between 40 and 49 years of age. J Gastroenterol Hepatol. 2017;32(1):98-105. doi:10.1111/jgh.13454. 47. Kim HJ, Kim JE, Jung JH, et al. Uric Acid Is a Risk Indicator for Metabolic Syndrome-related Colorectal Adenoma: Results in a Korean Population Receiving Screening Colonoscopy. Korean J Gastroenterol Taehan Sohwagi Hakhoe Chi. 2015;66(4):202-208. doi:10.4166/kjg.2015.66.4.202.

48. Jung YS, Yun KE, Chang Y, et al. Risk factors associated with rectal neuroendocrine tumors: a cross-sectional study. Cancer Epidemiol Biomark Prev Publ Am Assoc Cancer Res Cosponsored Am Soc Prev Oncol. 2014;23(7):1406-1413. doi:10.1158/1055-9965.EPI-14-0132.

49. Chang L-C, Wu M-S, Tu C-H, Lee Y-C, Shun C-T, Chiu H-M. Metabolic syndrome and smoking may justify earlier colorectal cancer screening in men. Gastrointest Endosc. 2014;79(6):961-969. doi:10.1016/j.gie.2013.11.035.

50. Lee CG, Hahn SJ, Song MK, et al. Vegetarianism as a Protective Factor for Colorectal Adenoma and Advanced Adenoma in Asians. Dig Dis Sci. 2014;59(5):1025-1035. doi:10.1007/s10620-013- 2974-5.

51. Sato T, Takeda H, Sasaki Y, Kawata S. Increased homeostasis model assessment-insulin resistance is a risk factor for colorectal adenoma in Japanese males. Tohoku J Exp Med. 2011;223(4):297-303.

52. Hu N-C, Chen J-D, Lin Y-M, Chang J-Y, Chen Y-H. Stepwise Relationship Between Components of Metabolic Syndrome and Risk of Colorectal Adenoma in a Taiwanese Population Receiving Screening Colonoscopy. J Formos Med Assoc. 2011;110(2):100-108. doi:10.1016/S0929- 6646(11)60016-8.

53. Yang SY, Kim YS, Chung SJ, et al. Association between colorectal adenoma and coronary atherosclerosis detected by CT coronary angiography in Korean men; a cross-sectional study. J Gastroenterol Hepatol. 2010;25(11):1795- 1799. doi:10.1111/j.1440-1746.2010.06330.x.

54. Hong SN, Kim JH, Choe WH, et al. Prevalence and risk of colorectal neoplasms in asymptomatic, average-risk screenees 40 to 49 years of age. Gastrointest Endosc. 2010;72(3):480-489. doi:10.1016/j.gie.2010.06.022.

55. Hwang ST, Cho YK, Park JH, et al. Relationship of non-alcoholic fatty liver disease to colorectal adenomatous polyps. J Gastroenterol Hepatol. 2010;25(3):562-567. doi:10.1111/j.1440- 1746.2009.06117.x.

56. Oh T-H, Byeon J-S, Myung S-J, et al. Visceral obesity as a risk factor for colorectal neoplasm. J Gastroenterol Hepatol. 2008;23(3):411-417. doi:10.1111/j.1440-1746.2007.05125.x.

57. Kim JH, Lim YJ, Kim Y-H, et al. Is Metabolic Syndrome a Risk Factor for Colorectal Adenoma? Cancer Epidemiol Prev Biomark. 2007;16(8):1543- 1546.

58. Mendonça FM, de Sousa FR, Barbosa AL, et al. Metabolic syndrome and risk of cancer: Which link? Metabolism. 2015;64(2):182-189. doi:10.1016/j.metabol.2014.10.008.

59. Jiang B, Zhang X, Du L-L, et al. Possible roles of insulin, IGF-1 and IGFBPs in initiation and progression of colorectal cancer. World J Gastroenterol. 2014;20(6):1608-1613. doi:10.3748/wjg.v20.i6.1608.

60. Beck-Nielsen H, ed. The Metabolic Syndrome. Vienna: Springer Vienna; 2013. doi:10.1007/978-3- 7091-1331-8.

61. Pietrzyk L, Torres A, Maciejewski R, Torres K. Obesity and Obese-related Chronic Low-grade Inflammation in Promotion of Colorectal Cancer Development. Asian Pac J Cancer Prev APJCP. 2015;16(10):4161-4168.

62. Doerner SK, Heaney JD. Inflammation, Obesity, and Colon Cancer. In: Dannenberg AJ, Berger NA, eds. Obesity, Inflammation and Cancer. New York, NY: Springer New York; 2013:147-180. doi:10.1007/978- 1-4614-6819-6_7.

63. Yoon K-W, Park S-Y, Kim J-Y, et al. Leptin-induced adhesion and invasion in colorectal cancer cell lines. Oncol Rep. 2014;31(6):2493-2498.

64. Yaturu S, Fort C. Prostate cancer is associated with the metabolic syndrome. J Mens Health. 2009;6(2):125-129. doi:10.1016/j.jomh.2009.01.005.

65. Osaki Y, Taniguchi S, Tahara A, Okamoto M, Kishimoto T. Metabolic syndrome and incidence of liver and breast cancers in Japan. Cancer Epidemiol. 2012;36(2):141-147. doi:10.1016/j.canep.2011.03.007.

66. Suchanek S, Grega T, Ngo O, et al. How significant is the association between metabolic syndrome and prevalence of colorectal neoplasia? World J Gastroenterol. 2016;22(36):8103-8111. doi:10.3748/wjg.v22.i36.8103.

67. Jinjuvadia R, Lohia P, Jinjuvadia C, Montoya S, Liangpunsakul S. The Association between Metabolic Syndrome and Colorectal Neoplasm: Systemic review and Meta-analysis. J Clin Gastroenterol. 2013;47(1):33-44. doi:10.1097/MCG.0b013e3182688c15.

68. Esposito K, Chiodini P, Capuano A, et al. Colorectal cancer association with metabolic syndrome and its components: a systematic review with metaanalysis. Endocrine. 2013;44(3):634-647. doi:10.1007/s12020-013-9939-5.

69. Wu Q, Wu Q, Zhang A. [Metabolic disturbance and insulin resistance in patients with colorectal cancer]. Zhonghua Wei Chang Wai Ke Za Zhi Chin J Gastrointest Surg. 2011;14(4):261-263.

70. Inoue K, Maeda N, Funahashi T. Metabolic Syndrome. In: Lammert E, Zeeb M, eds. Metabolism of Human Diseases: Organ Physiology and Pathophysiology. Vienna: Springer Vienna; 2014:199-203. doi:10.1007/978-3-7091-0715-7_30.

71. Kithcart AP, Curigliano G, Beckman JA. Treatment of Hypertension in Patients Receiving Cancer Therapy. In: Kimmick GG, Lenihan DJ, Sawyer DB, Mayer EL, Hershman DL, eds. Cardio-Oncology: The Clinical Overlap of Cancer and Heart Disease. Cham: Springer International Publishing; 2017:105-123. doi:10.1007/978-3-319-43096-6_5.

72. Nie Z, Zhu H, Gu M. Reduced colorectal cancer incidence in type 2 diabetic patients treated with metformin: a meta-analysis. Pharm Biol. 2016;54(11):2636-2642. doi:10.1080/13880209.2016.1176057.

Cite this article as: Elharag SE, Traoré Y, and Khaled MB. Metabolic Syndrome and Risk of Colorectal Adenoma and Cancer: A Meta-Analysis. Nor. Afr. J. Food Nutr. Res. July – December (2017); 01 (02): 30-43. https://doi.org/10.5281/zenodo.1245604