93 The North African Journal of Food and Nutrition Research: (2018) 02; (04): 93-110 https://doi.org/10.5281/zenodo.1478870 Review Article OPEN ACCESS elSSN: 2588-1582 r\p THE NORTH AFRICAN JOURNAL OF FOOD AND NUTRITION RESEARCH Contents lists available at Journal homepage: https://www.naifnr.org Metabolic Syndrome Components Correlation with Colorectal Neoplasms: A Systematic Review and a Meta-analysis Salah Eddine ELHERRAG \ Youssouf TRAORE \ Mecihit Boumediene 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 Laboratory of Health & Environment, Djillali Liabes University, PO Box 89, Sidi-Bel-Abbes (22000), Algeria ARTICLE INFO ABSTRACT Article history: Received 02 September 2018 Accepted 26 October 2018 Available online 06 November 2018 Keywords: Colorectal Neoplasms Hyperglycemia Hypertension Visceral obesity Dyslipidemia, Meta-analysis. Access this article online Quick Response Code: Website: www.naifnr.orq L@iLi] | https://doi.ora/10.5281/zenodo.1478870 | * Corresponding author Tel: +213 551152261 Background: Patients with metabolic syndrome (MetS) have a higher risk of developing colorectal neoplasms (CRN) including colorectal adenoma (CRA) and colorectal cancer (CRC). Nonetheless, the role and implication of each component of the syndrome, i.e. (hyperglycemia, hypertension, dyslipidemia, and visceral obesity) are not well ascertained. Aims: We conducted a systematic review and a meta-analysis in order to assess the association between MetS components and CRN. Methods and Material: A systematic literature search using the PubMed database was performed with the objective of identifying relevant English studies. Effect estimates were measured. Heterogeneity, subgroup, sensitivity analyses, and publication bias analyses were performed. Results: Thirty-one studies met our inclusion criteria. Generally, subjects with hyperglycemia (RR = 1.33; 95% Cl 1.14-1.54), high waist circumference (RR = 1.30; 95% Cl 1.19-1.42), high triglycerides (RR = 1.30; 95% Cl 1.13-1.49), and hypertension (RR = 1.26; 95% Cl 1.17-1.36) showed a stronger positive significant association with CRA formation risk. A similar pattern was found between high fasting blood glucose (RR = 1.35; 95% Cl 1.23-1.47) and high blood pressure (RR = 1.28; 95% Cl 1.20-1.37) with CRC incidence. A moderate association was found between hypertriglyceridemia and visceral obesity with CRC risk. Conversely, no significant association was found between low high-density lipoprotein-cholesterol (HDL-C) with both outcomes. Conclusions: Our results indicate that hyperglycemia, hypertension, visceral obesity, and hypertriglyceridemia increases CRA and CRC risk. Low HDL-C has no significant effect on those outcomes. Article edited by Dr. Muthalib Murshida Asha and Dr. Hajar K.IAI khaled@khaledmb.co.uk 1 INTRODUCTION Metabolic syndrome (MetS) has become a global health issue [1], According to the International Diabetes Federation (IDF), approximately a quarter of the world's adult population may have the MetS [2], MetS is identified as an aggregation of prevalent metabolic, biochemical, physiological, and clinical disorders related to the risk of progression to cardiovascular diseases and type 2 diabetes mellitus [3—5]. Current MetS definitions include hyperglycemia, dyslipidemia, hypertension, and visceral (abdominal or central) obesity as diagnosis criteria [1-6], Colorectal cancer (CRC) is a multistep process (stepwise model) of carcinogenesis. This process results from the progressive accumulation of genetic mutations and epigenetic alterations that activate oncogenes and inactivate tumor suppressor genes to substitute normal epithelial cells for adenocarcinomas [7-101. Colorectal adenomas are recognized as the precursor lesions for CRC [11]. CRC is a malignancy characterized by high incidence This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2017 The Authors. The North African Journal of Food and Nutrition Research. Nor. Afr. J. Food Nutr. Res. July - December 2018 Volume 02 Issue 04 Elherrag et al.: Metabolic syndrome components and colorectal neoplasms and mortality rates [12], Moreover, CRC is the third prevailing cancer in men and the second in women worldwide. Therefore, 746,000 incident cases among men (10% of all new cancer cases in men) were estimated in 2012 and 614,000 new cases within women (9.2% of all incident cancer cases in women) [IB], In the same year, 373,640 deaths were recorded, making it the fourth cause of mortality by cancer worldwide within men (8% of all cancer deaths in men) and 320,300 deaths among women making it the third cause of death by cancer (9% of all cancer deaths in women) [ 13] , This high incidence and mortality could be attributed to various risk factors [14]. The increasingly aging population, male gender, and ethnicity are linked with a higher risk of developing this malignancy [15], along with a family history of CRC [ 16, 17 1, inherited genetic predispositions (Lynch syndrome, familial adenomatous polyposis, etc.) [18-201 and inflammatory bowel diseases (Crohn's disease, Ulcerative Colitis, etc.) [ 7, 14, 18, 21 1. Other environmental and lifestyle-related risk factors are as well linked with CRC, including dietary habits [ 22-24 1, physical activity [251, smoking [ 9, 26 1, type 2 diabetes mellitus [27], and metabolic syndrome [28]. This latter has been suggested to be associated with risk of developing colorectal neoplasia (CRN) including colorectal adenoma (CRA) and CRC in several epidemiological studies that endeavored to address this issue, though the results were inconsistent [28-301. In addition, the implication of each metabolic condition comprising the MetS in the carcinogenesis process remains ambiguous. We aimed to tackle those issues in our meta-analysis focusing especially on the study of the effect of each component of the MetS on developing both CRA and CRC. 2 MATERIAL AND METHODS 2.1 Search strategy A systematic literature search was carried out on the PubMed database for relevant studies examining the impact of any single component of MetS, i.e. (hypertension, hyperglycemia, dyslipidemia, and visceral obesity) on CRA and/or CRC incidence. Solely full English studies published up to June 2018 were considered and no population limitation was applied. The following Medical subject headings key terms were used: "triglycerides", "HDL cholesterol", "high-density lipoprotein cholesterol", "hyperglycaemia", "hyperglycemia", "waist circumference", and "hypertension", in combination with "colorectal neoplasms", and "metabolic syndrome". 2.2 Study selection The inclusion criteria used to determine the eligibility of any individual retrieved study were as follows: a full English 94 published article, the study design was a cohort, case- control, or cross-sectional; CRA and/or CRC incidence as the outcome; the study must provide adequate data to estimate risk ratios (RR) and their 95% confidence intervals (Cl) of CRA and/or CRC incidence among individuals with MetS and at least one of these parameters (high-density lipoprotein-cholesterol (HDL-C) concentrations, triglycerides (TG) values, fasting blood glucose levels (FBG), blood pressure (BP), and waist circumference measurements (WC)); the study must provide the MetS definition(s) used for diagnosis. Articles not published as full text such as case reports, letters, comments, editorials, news were excluded. In addition, review articles, meta¬ analyses, articles not published in English, and studies dealing with organisms other than humans or in vitro studies were also rejected. We examined titles, abstracts, and full texts to assess the studies relevance and to exclude studies unrelated to the topic. Relevant articles were subsequently examined based on the full text. Articles with inappropriate exposures or outcomes, with missing or inappropriate data, and studies dealing with cancer biology or genetics were left out as well. Two authors (S.E and Y.T) independently performed the literature search and study selection, any disagreement found was resolved by returning to the author (M.B.K) who made the final decision. 2.3 Data extraction and study quality assessment Data extraction was independently undertaken by (S.E and Y.T). Relevant data extracted from each included study involved the first author's name, the year of publication, the study location, the number of subjects, the type of the lesion, the number of events, characteristics of the studied population, and the definition of MetS used. The meta-analysis was performed in conformity with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations [31]. The methodological quality of the included studies was evaluated according to The Newcastle-Ottawa Scale (NOS) [ 321 . The NOS is a tool for assessing the quality of non- randomized studies which allocates a maximum of nine stars for each study on certain criteria including quality assessment of selection, comparability, exposure, and outcome. 2.4 Summary measures Mantel-Haenszel statistical method was used for dichotomous data. Risk ratios (RR) with their 95% confidence intervals were estimated. The fixed-effects meta-analysis model was used when no evidence of statistical heterogeneity was observed and random-effects meta-analysis model was applied when statistical heterogeneity was detected. The fixed-effects model Nor. Afr. J. Food Nutr. Res. 1 July-December 2018 Volume 02 Issue 04 Elherrag et al.: Metabolic syndrome components and colorectal neoplasms assumes that only the chance is responsible for the differences between study results whilst the random- effects meta-analysis model allows for the variations across studies of the effects being estimated and presumes that there is a distribution of these effects 1 331 . 2.5 Synthesis of results Tau-squared (Tau 2 ) was obtained to estimate the between- study variance in the random effect model. Z-test of the null hypothesis, with no effect, was also obtained. Chi- squared test (Chi 2 ), which assesses whether observed differences in results are compatible with chance alone, was measured to assess heterogeneity. A (P < 0.05) was considered to indicate statistical significance. Besides, heterogeneity was assessed with the Z 2 statistic, which unlike the Chi 2 test describes the percentage of the variability in effect estimates that is due to heterogeneity rather than sampling error 1 34, 351 . f values were interpreted as follows: 0-40% inconsistency may not be important, 40-70% may represent moderate heterogeneity, and > 70% may represent considerable heterogeneity. 2.6 Publication bias Publication bias was assessed by a visual investigation of a potential asymmetry of funnel plots. Egger's regression test 1 36 1 and Begg's rank correlation test [37] for funnel plot asymmetry were performed afterward to investigate the small study effect and publication bias. The results were adjusted to publication bias using the trim and fill method [38]. 2.7 Additional analyses 2.7.1 Sensitivity and subgroup analyses With the aim of evaluating the influence of each study on the risk estimates and the heterogeneity, we carried out sensitivity analyses by excluding one dataset at a time. A pre-specified subgroup analyses according to study design (cohort, case-control, and cross-sectional), gender (men and women), MetS definition (NCEP-ATP III, IDF, the harmonized definition, and other definitions), study location (Asia, Europe, North America), and cancer site (colon or rectal cancer) were performed in order to explore heterogeneity and differences between subgroups. The NCEP-ATP III (National Cholesterol Education Program- Adult Treatment Panel III) definition was considered as the conventional definition for MetS diagnosis. Review Manager 5.3 program [39] was used for the meta-analysis, subgroup and sensitivity analyses. Publication bias analyses, test for identifying potential outliers and influential studies [40] and Baujat plots (which illustrates 95 studies that may contribute to overall heterogeneity) [41] were conducted with R program (version 3.5.0) [ 42, 431 . 3 RESULTS 3.1 Study selection The process of study selection is demonstrated in the flow diagram (Figure 1). In order to determine their eligibility for inclusion, 292 articles were initially identified through the database search, and their titles and abstracts were reviewed afterward. Consequently, 198 studies were excluded consisting of non-full text articles (reviews, case reports, editorials, news, letters to editors, comments, etc.) as well as studies irrelevant to the topic in question. Subsequently, 94 publications were considered relevant to the topic and were carefully examined through an intensive reading to determine ultimately the pertinent studies to include in our meta-analysis. Eventually, 31 articles discussing the correlation between the MetS and its components and CRN (CRA and CRC) were included. Figure 1: Flowchart of study selection 3.2 Study characteristics Table 1 summarizes the characteristics of the included studies. The meta-analysis consisted of eight cohort studies [ 44-51 1, 13 case-control studies [ 52-64 1, and ten cross- sectional studies as well [ 65-74 1. With the exception often studies, where five were carried out in European populations [ 47, 52, 55, 56, 581 and five in northern American populations [ 48, 49, 51, 62, 641 , the remaining Nor. Afr. J. Food Nutr. Res. 1 July-December 2018 Volume 02 Issue 04 Elherrag et al.: Metabolic syndrome components and colorectal neoplasms were conducted in Asian populations. CRA was the outcome in 14 studies 1 44, 46-50, 52-58, 661 , whereas 19 studies [ 44-46, 51, 59-65, 67-74 1 reported data on CRC incidence. The NCEP-ATPIII definition was utilized in 14 studies [44- 46, 48, 49, 55, 56, 59, 67, 69-71, 73, 741 , four applied the IDF definition for the diagnosis of individuals with MetS [ 56, 58, 63, 721 , while two studies used the harmonized definition [56, 68 1, and 13 studies employed other definitions [ 47, 50-54, 57, 60-62, 64-66 1. According to the NOS scales, the included cohort studies scored an average of eight stars, the case-control studies were awarded an average of 7.85 stars, while the cross-sectional studies were allocated an average of 7.6 stars. 3.3 Synthesis of results 3.3.1 Hyperglycemia and colorectal neoplasms To examine the association between FBG and CRA, data from nine studies comprising 11 datasets were pooled. Compared to individuals with normal FBG levels, patients with high FBG values (hyperglycemia) were more susceptible to developing CRA (RR = 1.33; 95% Cl 1.14-1.54; P = 92%) (Table 2, Figure 2). There was no evidence of significant publication bias with Begg's test (P = 0.5423), contrarily to Egger's test ( P = 0.0232). None of the subgroups modified the risk estimate. The adjusted summary RR on publication bias was decreased by the trim and fill method to 1.28 (95% Cl 1.11-1.46). The Baujat plot indicated that the dataset (Kim 2012 AA/ NCEP-ATP III) [46] contributed to the overall heterogeneity and the dataset (Hu 2011 CRA / NCEP-ATP III) contributed to the overall result (Figure 3). The risk estimates for the relationship between FBG levels and CRC were consistent with those expressed by the previous analysis concerning CRA. A summary RR of 1.35 (95% Cl 1.23-1.47; P = 59%) was found (Supplementary Figure 1.1), suggesting, therefore, a strong effect of hyperglycemia on both outcomes. There was no evidence of funnel plot asymmetry (P = 0.2792 with the Begg's test and P = 0.2360 with the Egger's test). The pooled analysis result was influenced by study type, study location, and gender. Cohort studies showed a higher association with a summary RR of 1.41 (95% Cl 1.08-1.84; P = 81%) than case- control studies (RR = 1.33; 95% Cl 1.25-1.41; P = 0%). Similarly, the association between hyperglycemia and CRC observed within Asian populations was stronger (RR = 1.42; 95% Cl 1.21-1.67; P = 78%) compared to Europeans (RR = 1.30; 95% Cl 1.20-1.41; P = 0%). When stratified by gender, a stronger association between high FBG and CRC risk was noticed for women (RR = 1.63; 95% Cl 1.18-2.26; P = 86%) than men (RR = 1.34; 95% Cl 1.24-1.45; P = 30%) (Supplementary Table 3). The trim and fill method reduced the summary RR to 1.29 (95% Cl 1.17-1.43). Sensitivity 96 analysis and the Baujat plot showed that the dataset (Lin 2014 CRC / NCEP-ATP III (W)) [44] contributed to the overall heterogeneity (RR = 1.30; 95% Cl 1.22-1.38; P= 18%), and it was considered as an influential study (Supplementary Figure 1.2, Supplementary Table 1.3). 3.3.2 Hypertension and colorectal neoplasms Using a random-effects meta-analysis model, due to evidence of heterogeneity, in 17 studies with 23 datasets involving 38,510 participants, high BP was associated with an increase in CRA incidence (RR = 1.26; 95% Cl 1.17-1.36; P = 82%) (Supplementary Figure 2.1). There was no evidence of significant publication bias with Begg's test {P= 0.1715), contrarily to Egger's test (P = 0.0213). Subgroup analyses revealed that study type and MetS definitions slightly modified the risk estimates (Supplementary Table 2.1). The conventional definition showed a stronger significant positive association (RR = 1.31; 95% Cl 1.18-1.46; P= 88%) compared with studies using unconventional definitions (RR = 1.20; 95% Cl 1.06-1.35; P= 68%). The adjusted effect size to publication bias decreased with the trim and fill method (RR = 1.17; 95% Cl 1.08-1.26). One study [45] contributed to overall heterogeneity and was considered potentially influential (Supplementary Figure 2.2). Comparing individuals with and without hypertension, the summary of RR of 13 studies with 24 datasets including 615,867 participants of which 12,570 cases of a confirmed diagnosis of CRC showed an increased risk of developing this malignancy by 28% (RR = 1.28; 95% Cl 1.20-1.37; P = 66%) (Supplementary Figure 2.3). There was no evidence of funnel plot asymmetry in Begg's test {P = 0.6062) or in Egger's test {P = 0.5381). This analysis was subdivided according to study type, study location, MetS definition, gender, and cancer site. All the strata considerably changed the risk estimate (Supplementary Table 2.1). A stronger relationship between CRC risk and high BP was found in cohort studies (RR = 1.37; 95% Cl 1.31-1.43; P = 41%) than non-cohort studies (RR=1.23; 95% Cl 1.12-1.35; P = 68%). A similar pattern was noticed for studies conducted in Asian populations (RR = 1.43; 95% Cl 1.32-1.56; P= 60%) compared with (RR = 1.18; 95% Cl 1.11-1.24; P = 36%) for studies carried out in European countries. This association was more significant for colon cancer (RR = 1.29; 95% Cl 1.14-1.45; P= 76%) than rectal cancer (RR = 1.23; 95% Cl 1.04-1.45; P= 71%) and among men (RR = 1.22; 95% Cl 1.08- 1.38; P - 59%) while a modest relationship was observed among women (RR = 1.12; 95% Cl 1.02-1.22; P= 12%). No study met the criteria as an influential study, however, the Baujat plot revealed that the dataset (Jeon 2014 RC / Other) [ 54 1 contributed to overall heterogeneity and result (Supplementary Figure 2.4). Nor. Afr. J. Food Nutr. Res. I July-December 2018 Volume 02 Issue 04 Table 1: Characteristics of included studies Elherrag et al.: Metabolic syndrome components and colorectal neoplasms 97 o CM X3 £ % JZ 42 > "O D LO > > & TO > TO C TO c TO XI 1 ° TO E t C g TO 1— C X u E TO < c C >s x S' o u z XI D CD CD C Q_ TO C CD u 1/3 C o c CD > TO cl TO > - c X "to u x TO CD TO L 7) ^ ^ £ =5 3 o ~ 11 S2 £ TO CL E TO LO "to c o TO c TO u "O c TO TO U c TO U o TO >s CD O o TO CL TO X TO E TO > CD o o TO TO e? 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Lnj ase-control studies o OJ o- sj 5^1 Lnl LO[ ohort studies Author, year [re (X) o o OJ ~CQ Qj TO £ o ro O rj Qj 03 c TO O CM o OJ Qj to XD TO m eta! 2012 [46] 3 o OJ Qj 03 C TO n etal. 2014 [44] o OJ ~cS TO O TO CL TO -C hin etal 2017 [50] Author, year [re Qj TO > O "D C TO TO SI CM ~c5 Qj > 2 TO in in no O CM 'cQ Qj TO E TO Jeon etal. 2014 [54 ang etal 2009 [5_ CM o OJ Qj D O c o u CO X ~ 1 LO 1/1 u < H21 X LX Nor. Afr. J. Food Nutr. Res. I July-December 2018 Volume 02 Issue 04 Elherrag et al.: Metabolic syndrome components and colorectal neoplasms 98 Nor. Afr. J. Food Nutr. Res. I July-December 2018 Volume 02 Issue 04 AA advanced adenoma, CC colon cancer, CRA colorectal adenoma, CRC colorectal cancer, IDF International Diabetes Foundation, MetS metabolic syndrome, NCEP-ATP III National Cholesterol Education Program-Adult Treatment Panel III, RC rectal cancer, RNETs rectal neuroendocrine tumors. Elherrag et al.: Metabolic syndrome components and colorectal neoplasms Table 2: Summary of results 99 Z-test Heterogeneity Publication bias (Avalue) (lvalue) Tau 2 Chi 2 (Avalue) /(%) Begg's test Egger's test Hyperglycemia and CRN risk CRA 9 (11) r44. 46. 63-65. 68. 69. 72. 731 RE 1.33 [1.14-1.54] 3.75 (.P = 0.0002) 0.05 123.99, df = 10 (. P< 0.00001) 92 0.5423 0.0232 CRC 7 (14) 144. 46. 48. 52. 54. 56. 571 RE 1.35 [1.23-1.47] 6.61 (P < 0.00001) 0.01 31.66, df = 13 (P = 0.003) 59 0.2792 0.2360 Hypertension and CRN risk CRA 17 (23) 144-46. 51. 59-64. 67-69, 71-74] RE 1.26 [1.17-1.36] 5.79 ( P< 0.00001) 0.02 120.97, df = 22 (P< 0.00001) 82 0.1715 0.0213 CRC 13 (24) 144. 46. 47. 49. 50. 52-58. 661 RE 1.28 [1.20-1.37] 7.51 (P< 0.00001) 0.01 67.35, df = 23 (P< 0.00001) 66 0.6062 0.5381 AA 3 (3) 146. 51. 671 FE 1.43 [1.14-1.79] 3.13 (A= 0.002) NA 0.48, df = 2 (P= 0.79) 0 Hypertriglyceridemia and CRN risk CRA 9 (12) (44. 46. 63-65. 67- 69. 731 RE 1.30 [1.13-1.49] 3.76 (P= 0.0002) 0.05 137.65, df = 11 (P< 0.00001) 92 0.5452 0.0518 CRC 6 (12) 144. 46. 54. 56. 57. 66] RE 1.14 [1.01-1.28] 2.10 (P= 0.04) 0.03 49.46, df = 11 (P< 0.00001) 78 0.3108 0.7347 AA 2 (2) 146. 671 FE 2.12 [1.62-2.77] 5.46 {P < 0.00001) NA 0.56, df = 1 (. P= 0.45) 0 Visceral Obesity and CRN risk CRA 10 (131 146. 60. 63. 65. 67- 70. 72. 7.31 RE 1.30 [1.19-1.42] 5.72 (P < 0.00001) 0.01 37.58, df = 12 (P = 0.0002) 68 0.7650 0.6954 CRC 4 (12) 146. 53. 55. 561 RE 1.18 [1.07-1.31] 3.30 (P= 0.0010) 0.02 39.40, df = 11 (P< 0.0001) 72 0.8406 0.9420 AA 3 (3) 146. 67. 701 RE 1.21 [0.74-1.96] 0.77 [P= 0.44) 0.12 5.83, df = 2 (P= 0.05) 66 Low HDL-Cholesterol and CRN risk CRA 7 (10) 144. 46. 6.3. 67-69. 73] RE 1.02 [0.92-1.12] 0.31 (A= 0.75) 0.01 34.52, df = 9 (P< 0.0001) 74 0.7275 0.0548 CRC 5 (12) r44. 46. 47. 54. 561 RE 1.13 [0.93-1.37] 1.26 (P- 0.21) 0.10 102.94, df = 11 (P< 0.00001) 89 0.7373 0.8443 AA 2 (2) 146. 671 FE 1.18 [0.84-1.66] 0.95 (P= 0.34) NA 0.84, df = 1 (P= 0.36) 0 AA advanced adenoma, CRA colorectal adenoma, CRC colorectal cancer, df degree of freedom, FE fixed-effects, HDL high-density lipoprotein, NA not applicable, RE random-effects, RR risk ratio. 3.3.3 Hypertriglyceridemia and colorectal neoplasms In a pooled analysis of nine studies comprising 12 datasets, a summary RR of 1.30 (95% Cl 1.13-1.49) was found (Supplementary Figure 3.1), with evidence of considerable heterogeneity (P = 92%), suggesting that individuals with elevated levels of triglycerides are more prone to developing CRA than individuals with normal levels. The results of Begg's and Egger's tests revealed no sign of funnel plot asymmetry (P = 0.5452 and P = 0.0518 respectively). A stratified analysis by MetS definitions found a higher significant positive association with CRA risk in studies using the conventional definition (RR = 1.44; 95% Cl 1.18-1.75; P = 95%) compared to a non-significant modest increase of CRA incidence when using unconventional definitions (RR = 1.07; 95% Cl 0.96-1.19; P - 11%) (Supplementary Table 3.1). The Baujat plot illustrated that the dataset (Kim 2012 AA / NCEP-ATP III) [ 461 contributed to overall heterogeneity (Supplementary Figure 3.2). A modest relationship between hypertriglyceridemia and risk of CRC was noticed in a meta-analysis of six studies with 12 datasets involving 73,856 participants (RR = 1.14; 95% Cl 1.01-1.28; P = 78%) (Supplementary Figure 3.3). Begg's test ( P = 0.5452) and Egger's test ( P = 0.0518) suggested no evidence of a small study effect. All the strata considerably influenced the risk estimate. Significant positive associations were noticed in cohort studies (RR = 1.33; 95% Cl 1.15-1.54; P = 60%), studies considering the conventional MetS definition (RR = 1.21; 95% Cl 1.08-1.35; P= 64%), and among men (RR = 1.16; 95% Cl 1.05-1.28; P = 0%), while a non-significant increase of CRC incidence was noticed in non-cohort studies (RR = 1.04; 95% Cl 0.91- 1.20; P = 71%), in studies utilizing unconventional MetS definitions (RR = 1.01; 95% Cl 0.73-1.38; P = 86%), and among women (RR = 1.10; 95% Cl 0.97-1.25; P = 0%). Nor. Afr. J. Food Nutr. Res. I July-December 2018 Volume 02 Issue 04 Elherrag et al.: Metabolic syndrome components and colorectal neoplasms Sensitivity analysis revealed that two datasets (Kim 2012 CC / NCEP-ATP III) [46] and (Jeon 2014 CC / Other) [54] modified the heterogeneity estimation (Supplementary Table 3.3). However, one study contributed to overall heterogeneity and result according to the Baujat plot (Supplementary Figure 3.4). There was a remarkable difference in the magnitude of the risk estimates about the involvement of high values of triglycerides with CRA and CRC. 3.3.4 Visceral obesity and colorectal neoplasms Ten studies with 13 datasets on visceral obesity and CRA incidence were available for the analysis. The combined RRs for patients with versus without central obesity was 1.30 (95% Cl 1.19-1.42, P = 68%) (Supplementary Figure 4.1), suggesting a positive significant association. There was no evidence of small study effect or publication bias (P = 0.7650 with Begg's test and P = 0.6954 with Egger's test). MetS definition influenced the effect estimate. A significant association was found in studies considering 100 the conventional MetS definition (RR = 1.23; 95% Cl 1.07- 1.42; P = 71%), however, the result for the unconventional definitions was stronger (RR = 1.35; 95% Cl 1.20-1.52; P = 63%) (Supplementary Table 4.1). The Baujat plot illustrated that two studies [ 60, 68 1 contributed on the overall result, and one study [67] comprised of two datasets one contributed to the overall heterogeneity and the other on overall result (Supplementary Figure 4.2). This positive statistically significant association was similarly observed in four studies with 12 datasets on the relationship between WC and CRC (RR = 1.18; 95% Cl 1.07-1.31; P = 72%) (Supplementary Figure 4.3). Neither Begg's test (P = 0.8406) nor Egger's test (P= 0.9420) have shown statistical significance for publication bias. MetS definition and cancer site modified the pooled risk ratio. A higher risk estimate, but not statistically significant was observed in studies using unconventional MetS definitions (RR=1.26; 95% Cl 0.99-1.60; P = 85%) than studies applying the conventional definition (RR = 1.14; 95% Cl 1.05-1.25; P = 43%). Study or Subgroup High FBG Events Total Normal FBG Events Total Weight Risk Ratio M-H, Random, 95% Cl Risk Ratio M-H, Random, 95% Cl 3.1.1 Cohort Kim 2012 AA/ NCEP-ATP III 26 323 160 4530 6.3% 2.28 [1.53,3.40] - - - Kim 2012 CRA/NCEP-ATP III 185 482 1586 5956 10.7% 1.44(1.28,1.63] Lin 2014 CRA / NCEP-ATP III (M) 465 564 429 530 11.4% 1.02 [0.96,1.08] Lin 2014 CRA / NCEP-ATP III (W) 323 403 283 372 11.2% 1.05 [0.98,1.14] Tsilidis 2010 CRA/Other 9 14 123 378 6.0% 1.98 [1.30,3.00] Subtotal (95% Cl) 1786 11766 45.7% 1.35 [1.10,1.65] Total events 1008 2581 Heterogeneity; Tau a = 0.04; Chi a = 57.61 ,df= 4(P< 0.00001); l a = 93% Test for overall effect: Z= 2.86 (P 0.004) 3.1.2 Non-Cohort Hong 2015 CRA/Other 326 874 932 3752 11.0% 1.50 [1.36,1.66] Hu 2011 CRA/NCEP-ATP III 109 534 288 2572 9.5% 1.82 [1.49,2.23] — ■ — Kim 2007 CRA/NCEP-ATP III 112 324 619 2207 10.1% 1.23[1.05,1.45] Morita 2005 CRA/IDF 143 459 613 2048 10.3% 1.04 [0.89,1.21] Oh 2008 CRA/IDF 17 48 36 152 5.2% 1.50 [0.93,2.41] Salu 201 1 'w-RAj HartnuhLied Subtotal (95% Cl) 2407 11526 54.3% 1.30(1.07,1.58] Total events 750 2706 Heterogeneity: Tau a = 0.04; Chi a = 32.17, df= 5(P< 0.00001); l a = 84% Test for overall effect: Z= 2.67 (P = 0.008) Total (95% Cl) 4193 23292 100.0% 1.33 [1.14,1.54J ♦ Total events 1758 5287 Heterogeneity: Tau a = 0.05; Chi 3 = 123.99, df = 10 (F < 0.00001); l“ = 32% —i - 1~ Test for overall effect: Z= 3.75 (P = 0.0002) Test for subgroup differences: Ch a = 0.06, df = 1 (P = 0.81), = 0% SE(log[RRD (b) o.i 0.2 0.3-■ 0.2 - Subgroups I— Miuyioups- | Q Cohort Q Non-Cohort Figure 2: Association between FBG and CRA formation: (a) Forest plot; (b) Funnel plot. AA advanced adenomas. Cl confidence interval, CRA colorectal adenoma, FBG fasting blood glucose, IDF International Diabetes Foundation, M men, M-H Mantel-Haenszel, NCEP-ATP III National Cholesterol Education Program-Adult Treatment Panel III, W women. Nor. Afr. J. Food Nutr. Res. I July-December 2018 Volume 02 Issue 04 Elherrag et al.: Metabolic syndrome components and colorectal neoplasms 101 Figure 3: Additional analyses for the association between FBG and CRA development: (a) Funnel plot after adjustment to publication bias with the trim and fill method. One simulated negative study was added (hollow circle) to the pooled estimates from the meta-analysis (solid circles). The adjusted RR slightly decreased from (1.33; 95% Cl 1.14-1.54) in the initial analysis to (1.28; 95% Cl 1.1 1-1.46) after adjustment, (b) Baujat plot: indicates that the 1 st dataset (that falls to the top right quadrant of the Baujat plot which corresponds to (Kim 201 2 AA / NCEP-ATP III)) has contributed to the overall heterogeneity and the 6th dataset (which corresponds to (Hu 201 1 CRA / NCEP-ATP III)) contributed on the overall result, (c) Influence plot: as there is no marked study, no study has met the criteria as an influential study. A stratified analysis by cancer site yielded a stronger association between high waist circumference and colon cancer (RR = 1.31; 95% Cl 1.12-1.52; P = 83%) than rectal cancer (RR = 1.11; 95% Cl 1.00-1.22; P = 0%). The adjusted RR on publication bias was increased to 1.25 (95% Cl 1.13- 1.38). Following the sensitivity analysis, one dataset (Aleksandrova 2011 CC / IDF (M)) [56] significantly modified the heterogeneity evaluation, (RR = 1.15; 95% Cl 1.09-1.22; P = 28%) after its exclusion (Supplementary Table 4.3). The same dataset contributed to overall heterogeneity and was considered potentially influential (Supplementary Figure 4.4). 3.3.5 Low HDL-C and colorectal neoplasms Seven studies, including ten datasets, have reported data about the relationship between CRA risk and low values of FIDL-C. A non-significant positive association was found in a weighted analysis of individuals with normal levels of FIDL-C against individuals with low HDL-C (RR = 1.02; 95% Cl 0.92-1.12; P = 74%) (Supplementary Figure 5.1). Nor. Afr. J. Food Nutr. Res. I July-December 2018 Volume 02 Issue 04 Elherrag et ai: Metabolic syndrome components and colorectal neoplasms Table 3: Subgroup analyses results of the association between hyperglycemia and colorectal neoplasms 102 Heterogeneity Subgroup N° of studies (datasets) ref Model RR [95% Cl] (lvalue) Tau 2 Chi 2 (Avalue) n%) Hyperglycemia and colorectal adenomas All studies 9 mi [44. 46, 63-65. 68. 69. 72. 731 RE 1.33 [1.14-1.54] 3.75 ( P = 0.0002) 0.05 123.99, df = 10 (P< 0.00001) 92 Study type Cohort 2 (4) [44. 461 RE 1.27 [1.03-1.56] 2.25 ( P = 0.02) 0.04 49.54, df = 3 (P< 0.00001) 94 Non-cohort 7 [71 [63—65. 68. 69. 72. 73] RE 1.35 [1.12-1.63] 3.20 (A = 0.001) 0.05 35.49, df = 6 (P< 0.00001) 83 Cross-sectional 5 (5) [65. 68. 69. 72. 731 RE 1.37 [1.13-1.67] 3.21 ( P= 0.001) 0.03 18.57, df = 4 (P= 0.0010) 78 Case-control 2 [21 r63. 641 FE 1.39 [0.74-2.64] 1.02 (P= 0.31) 0.19 8.36, df = 1 {P= 0.004) 88 Study location Asia 8 HOI 144. 46. 63. 65. 68. 69, 72. 731 RE 1.29 [1.11-1.50] 3.35 (A = 0.0008) 0.05 117.99, df = 9 (P< 0.00001) 92 North America 1 (D [64] RE 1.98 [1.30-3.00] 3.20 (A = 0.001) NA NA NA MetS definition Conventional 4 (61 [44. 46. 69. 731 RE 1.35 [1.11-1.64] 3.01 (A = 0.003) 0.05 86.30, df = 5 (P< 0.00001) 94 Unconventional 5 (51 163-65. 68. 721 RE 1.30 [1.01-1.67] 2.04 ( P= 0.04) 0.06 25.61, df = 4 (P< 0.0001) 84 Hyperglycemia and colorectal cancer All studies 7 (141 [44. 46. 48. 52. 54. 56. 571 RE 1.35 [1.23-1.47] 6.61 (. P< 0.00001) 0.01 31.66, df = 13 [P= 0.003) 59 Study type Cohort 3 (61 144. 46. 481 RE 1.41 [1.08-1.84] 2.49 [P= 0.01) 0.08 26.39, df = 5 (P< 0.0001) 81 Case-control 4 (81 [52. 54. 56. 571 FE 1.33 [1.25-1.41] 8.92 (P< 0.00001) NA 5.72, df = 7 (A = 0.57) 0 Study location Asia 4 (71 [44. 46. 54. 571 RE 1.42 [1.21-1.67] 4.18 (P< 0.0001) 0.03 27.26, df = 6 (P= 0.0001) 78 Europe 2 (4) [52, 56] FE 1.30 [1.20-1.41] 6.52 (P< 0.00001) NA 3.45, df = 4 (P= 0.49) 0 North America 1 (2) [48] RE 1.21 [0.83-1.77] 1.00 (A = 0.32) 0.02 1.30, df = 1 (P= 0.25) 23 MetS definition Conventional 4 (101 [44. 46. 48. 561 RE 1.33 [1.18-1.51] 4.50 (P< 0.00001) 0.02 28.42, df = 9 (P= 0.0008) 68 Unconventional 3 (41 [52. 54. 571 FE 1.37 [1.25-1.51] 6.72 (P< 0.00001) NA 2.63, df = 3 (A = 0.45) 0 Gender Men 2 (31 144. 561 FE 1.34 [1.24-1.45] 3.14 (P= 0.002) NA 2.85, df = 2 (A = 0.24) 30 Women 2 (31 144. 561 RE 1.63 [1.18-2.26] 2.95 (P= 0.003) 0.07 14.26, df = 2 (A = 0.0008) 86 Cancer site Colon 4 (51 [46. 48. 54. 561 FE 1.36 [1.25-1.47] 7.17 (P< 0.00001) NA 2.45, df = 4 (A = 0.65) 0 Rectal 3 (41 [46. 54. 561 FE 1.32 [1.18-1.49] 4.64 (P< 0.00001) NA 3.70, df = 3 (P= 0.30) 19 Colorectal adenomas versus colorectal cancer CRA 2 (4) [44. 461 RE 1.27 [1.03-1.56] 2.25 {P= 0.02) 0.04 49.54, df = 3 (P< 0.00001) 94 CRC 2 (4) [44. 461 RE 1.50 [1.06-2.12] 2.30 (P= 0.02) 0.10 25.40, df = 3 (P < 0.0001) 88 CRA colorectal adenoma, CRC colorectal cancer, df degree of freedom, FE fixed-effects, MefS metabolic syndrome, NA not applicable, RE random- effects, RR risk ratio. Nor. Afr. J. Food Nutr. Res. I July - December 2018 Volume 02 I Issue 04 Elherrag et al.: Metabolic syndrome components and colorectal neoplasms There was no evidence of significant publication bias with Begg's test (P = 0.7275) and with Egger's test ( P- 0.0548). The result slightly decreased after adjusting to publication bias via the trim and fill method to 1.00 (95% Cl 0.92-1.09). Two studies [ 44, 691 contributed to overall heterogeneity and result and one study [67] contributed to the overall heterogeneity according to the Baujat plot. One study was considered potentially influential [44] (Supplementary Figure 5.2). Consistently, our results suggest a statistically non¬ significant increase for HDL-C on CRC incidence. The summary of RR was 1.13; 95% Cl 0.93-1.37; / ? = 89%) in five studies with 12 datasets comparing patients with low HDL- C levels and individuals with normal values (Supplementary Figure 5.3). No evidence of the small study effect or publication bias was found (Begg's test P= 0.7373) and (Egger's test P = 0.8443). The study type, study location, and cancer site influenced the risk estimate (Supplementary Table 5.1). The adjusted RR for publication bias increased to 1.18 (95% Cl 0.79-1.43) by the trim and fill method. The Baujat plot illustrated that the dataset (Jeon 2014 RC / Other) [Ml contributed to overall heterogeneity and result (Supplementary Figure 5.4). 3.3.6 Advanced adenomas and components of the MetS Four studies [ 46, 51, 67, 701 provided data on the correlation between advanced colorectal adenoma (AA) and components of the MetS. Our results showed that only hypertriglyceridemia and hypertension seem to significantly increase the AA incidence (Table 2). 3.3.7 Colorectal adenomas versus colorectal cancer We performed an analysis with the purpose of comparing the effect estimates for the different metabolic factors between CRA and CRC using only studies that reported both outcomes. Two studies [ 44, 461 were available for all factors except for waist circumference. Our findings displayed a stronger association between hyperglycemia, hypertriglyceridemia, and hypertension with CRC than CRA (Supplementary Tables 1.1, 2.1, and 3.1). No difference in the magnitude of the effect was observed for the association between FIDF-C and both outcomes (Supplementary Table 5.1). 4 DISCUSSION We focused in this meta-analysis on answering the question of which condition(s) of the MetS are related to the developing of CRA and CRC since we have demonstrated the MetS association with both conditions in a previous study [75]- We also aimed to determine whether these elements influence the carcinogenesis 103 process in its earlier or later stages. Our results suggest that individuals with hyperglycemia, hypertension, and visceral obesity, but not low values of FIDF-C are associated with an increased risk of developing both CRA and CRC. According to a recent worldwide estimate by the World Health Organization, the global prevalence of obesity has become three times as higher since 1975 [76]. Accordingly, in 2016, more than 13% of the world adults (above 18 years) were obese, that is more than 650 million cases. Additionally, 124 million children and adolescents (5-18 years) were considered obese in the same year [ 761 . Subsequently, the key element in the pathogenesis of MetS is the alteration of normal visceral adipose tissue function [6], Visceral obesity regularly measured by WC has long been linked to certain types of cancer in several epidemiological studies, known also as obesity-related cancers F77, 781 . The relationship between WC and CRC was examined in a meta-analysis of 12 studies. The RR of CRC for the highest versus the lowest categories of WC was 1.455 (95% Cl 1.327-1.569; 7 = 10.8%) [79]. Our results suggested an implication of WC in CRC risk with an 18% increase, lower than previous findings (43%) [ 281 . Various factors could relate obesity to CRC. A chronic low- grade inflammation is associated with obesity attributable to the production of pro-inflammatory cytokines such as tumor necrosis factor-alpha and interleukin-6, leading to cell apoptosis inhibition and cell survival promotion [80, 81]- Besides, insulin resistance, which is a characteristic of the MetS, associated with hyperinsulinemia, increased secretion of insulin-like growth factor 1 (IGF1), and hyperglycemia are supposed to promote CRC carcinogenesis. High levels of insulin may lead to an overproduction of IGF1, causing an overstimulation of the receptors, and activation of insulin receptor substrate-1. This can activate various signal pathways, including mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3 kinase that decreases cell apoptosis and enhances cell proliferation [80-841. Hyperglycemia is suggested to promote cancer development by way of a variety of mechanisms. A high glucose level leads to a state of an oxidative stress by increasing the production of reactive oxygen species [85] and enhances inflammatory pathways which lead also to a state of a chronic low-grade inflammation [86], Hyperglycemia provides to cancer cells the necessary energy source which allows for cell survival and resistance to chemotherapy [87] and indirectly increases cancer progression by dysregulating signaling pathways in many types of cancer (breast, lung, and prostate cancer) [88], However, hyperglycemia may be dependent on other factors like hyperinsulinemia and diet [89]. Nor. Afr. J. Food Nutr. Res. I July-December 2018 Volume 02 Issue 04 Elherrag et al.: Metabolic syndrome components and colorectal neoplasms Our results indicated that hyperglycemia increases the risk by 35% for CRC. In a dose-response analysis performed by Shi eta / [90], an RR of 1.015 (95% Cl 1.012-1.019; P= 0.000) was found for each 20 mg/dl increase in blood glucose concentration which agrees with our findings. Furthermore, Esposito eta/. [28] noticed a 9% increase in CRC risk in patients with high blood pressure. However, 25% was the increase that we found in our meta-analysis. The mechanisms by which hypertension affects the development of cancer remain unclear. The renin- angiotensin system which is implicated in the etiology of hypertension is linked to the development of many cancers. The angiotensin II activates downstream MAPK and STAT signal pathways throughout its effect on angiotensin type 1 receptor which induces the expression of proto-oncogenes and subsequently the promotion of cell proliferation [84]. Epidemiological studies have reported the association between hypertension and cancer development. Women with hypertension were at a high risk of endometrial cancer, while a history of hypertension has been related to kidney cancer [91]. The prevalence of hypertension was higher among subjects with prostate cancer [92]. Moreover, a long-term use of anti-hypertensive medication which is an indication of a long duration of hypertension increased the risk of invasive breast cancer [931. The results of the association between dyslipidemia, a condition that includes high serum TG levels and low values of HDL-C, were inconsistent. We noticed that low HDL-C levels do not have a significant effect on the CRC incidence which matched previous findings. In a meta¬ analysis attempting to evaluate the association between serum lipids and CRN, the pooled RR of serum HDL-C for CRC was 0.97 (95% Cl 0.80-1.18; P= 0.77), suggesting no significant relevance [94]. Another meta-analysis presented results for high versus low concentrations of serum HDL-C and CRC risk. A random-effects model yielded a summary RR of 0.84 (95% Cl 0.69, 1.02), with evidence of moderate heterogeneity (P = 0.059, P = 42.5 %) [95]. Tian et at. [94] stated that TG was associated with an increased incidence of CRA, but not CRC. Though, our results disagree with those findings. A stronger association was found among subjects with high TG values for developing CRA than for CRC in our analysis. Additionally, our results are not in line with those found by Tian eta/. [94] (RR = 1.07; 95% Cl 0.99-1.15; P= 0.10) and Esposito et at [28] (RR = 1.12; 95% Cl 0.98-1.27) where a non-significant association of serum TG with CRC risk was observed, our findings suggest a positive significant relationship. By contrast, our findings support those reported by Yao and Tian. [95] when assessing the implication of high levels of TG with CRC risk. Results for 104 high versus low concentrations of serum TG and CRC occurrence yielded a summary RR of 1.18; 95 % Cl 1.04- 1.34), with evidence of moderate heterogeneity (P=0.011, P = 47.8 %). A case-cohort study found that plasma triglycerides and HDL-C were unrelated to CRC risk [ 961 . The biological mechanisms linking dyslipidemia to CRC pathogenesis remain unknown. Nevertheless, some hypotheses were postulated. Fat intake increases bile acids production, which are transformed in the colon to secondary bile acids. The increase in the amounts of secondary bile salts may be carcinogenic for colon cells. Additionally, the constant damage to the colonic mucosa caused by secondary bile acids promotes the proliferation of colonocytes which may leads afterward to CRC development [ 81, 82, 97 1. The results of epidemiological studies on the relationship involving dyslipidemia and cancer development were also conflicting [ 98, 991 . A weak inverse-association, which was dependent on smoking status, was noticed in a prospective cohort study between HDL-C and lung cancer [ 100 1. Moreover, no correlation was observed between low HDL-C and breast cancer incidence for both the total sample and among postmenopausal women, while a modest association was noticed for premenopausal women [ 1011 . Similarly, a retrospective cohort study found no significant association between both HDL-C and TG with liver and breast cancer [ 102 1. Inversely, a strong association was remarked between low HDL-C and high TG values and prostate cancer incidence [92]. In vitro assays showed that HDL-C does not have a role in promoting breast cancer cell proliferation, angiogenesis or metastasis [ 103 1. Research concerning the effect of the MetS and its individual conditions on CRA risk is limited. Tian et at [94] indicated that serum TG was significantly associated with the CRA formation (RR = 1.06; 95% Cl 1.03-1.10; P= 0.0009; / ? = 69%). Yet, this is lower than the 30% increase in the CRA risk observed in our analysis. The meta-analysis undertaken by Tian et at [94] showed that the RR for CRA with serum HDL-C was 1.03 (95 % Cl 0.99-1.06; 2=0.12) with a moderate heterogeneity [P = 43 %). Correspondingly, our analysis revealed a non-significant effect of low levels of HDL-C on CRA risk (RR = 1.02; 95% Cl 0.92-1.12; P = 74%). To the best of our knowledge, our study could be the first comprehensive meta-analysis that shed the light on the effect of each metabolic factor constituting the MetS and CRA formation in addition to their association with the risk of developing CRC. This could be of high importance, particularly to determine the implication of MetS components on CRC carcinogenesis. Future research should focus on determining whether the increased risk of CRN is attributable to the entire cluster or to every particular condition. Moreover, understanding the role of Nor. Afr. J. Food Nutr. Res. I July-December 2018 Volume 02 Issue 04 Elherrag et ai: Metabolic syndrome components and colorectal neoplasms each component and the biological mechanisms relating to those factors and CRN incidence may provide indications for colorectal cancer therapy. In general, no evidence of the small study effect or publication bias was found. Besides, the additional analyses including subgroup, influence, and sensitivity analyses were performed and the Baujat plots were constructed for all the analyses. The results showed that no dataset has contributed in a way that significantly alters the findings, apart from the exceptions mentioned, emphasizing therefore on the strength of our findings. Although, this study has certain limitations. Including case-control and cross-sectional studies may result in selection bias. Several analyses presented results with moderate or considerable heterogeneity, hence these findings should be interpreted with caution. Nevertheless, subgroup and sensitivity analyses were carried out with the aim of exploring the sources of heterogeneity. 5 CONCLUSIONS In summary, our findings demonstrate that hyperglycemia, hypertension, hypertriglyceridemia, and central obesity are associated with a moderately increased risk of both CRA and CRC. In fact, the proportions for the augmentation of the risk oscillated between 26-33% for CRA, and between 14-35% for CRC. In general, regarding the relationship between the increased CRC risk and these conditions, the association was more noticeable in the colon than in rectal cancer and in men than women. Nonetheless, low HDL-C shows a statistically non¬ significant positive effect on both outcomes. Our results display stronger associations between MetS components and CRA risk compared with those of CRC. Thus, screening programs aiming to prevent CRC should take into consideration MetS patients. The management of MetS and its individual components is highly recommended. 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